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Sample records for Fuel consumption Road transport Dynamic Panel Data model GMM estimates

  1. Estimating road transport fuel consumption in Ecuador

    International Nuclear Information System (INIS)

    Sierra, Jaime Cevallos

    2016-01-01

    Road transport is one of the sectors with highest energy consumptions in the planet, with large dependence of fossil fuels, and contribution for global greenhouse gas emissions. Although, Latin America is not a high-energy consumer, its share in global consumption is expected to grow, especially in the transportation sector. This make essential for developing countries the adoption of better policies to identify the vehicle groups with largest fuel demands. The present study describes the VKT technique to disaggregate road transport energy consumption by vehicle type, applied to the road transportation system of Ecuador. It also describes the procedures performed to estimate the variables required to run the model, and some of the practical applications that be used to create public policies. Results show as the biggest fuel consumers the heavy-duty freight cargo, followed by light duty vehicles. The estimation of greenhouse gas emissions evidence that road transport released 14.3 million tons of CO_2 in 2012. When fuel consumption is compared by it costs, it can be confirmed that Ecuadorean Government covered, through subsidies, for 68% of the annual fuel costs of national road transport, demonstrating the importance of restructuring these expenditures in order to achieve an efficient road transport system. - Highlights: •The vehicle-kilometers traveled has been estimated from local info. •The fuel economy has been calculated from national and international data. •The groups with higher fuel consumption has been located. •The fuel-type dependency has been estimated for each vehicle group. •Greenhouse gas emission, and fuel costs, has been estimated for local road transport.

  2. A Dynamic Model for Road Gasoline and Diesel Consumption: An Application for Spanish Regions

    Directory of Open Access Journals (Sweden)

    Rosa Marina González Marrero

    2012-01-01

    Full Text Available This paper analyzes the factors explaining the aggregate fuel consumption for road transport in Spain in a dynamic panel data framework. Three features on this study are the use of a balanced panel using regional data, the distinction between gasoline and diesel and the specification of a dynamic panel data (DPD model and estimate it by system Generalized Methods of Moments (GMM. Our results show that most explanatory variables are significant in explaining the evolution of gasoline consumption, while diesel consumption is found to be independent of most of these factors. The differences between the markets of the gasoline (most for passenger transport use and the diesel (passenger and freight transport are important could explain the results for the diesel model. Moreover, the intensive dieselization process that has taken place in Spain over the last decade, which has resulted in diesel consumption being exposed to factors - i.e., regulatory - which are not of a strictly economic nature. This finding highlights the need to consider different explanatory variables and models for gasoline and diesel consumption, and to go further in the research. Finally, we find that traditional estimation procedures, such as fixed and random effect estimators, produce important differences with respect to system-GMM, which may even change policy recommendations.

  3. Estimation of Nonlinear Dynamic Panel Data Models with Individual Effects

    Directory of Open Access Journals (Sweden)

    Yi Hu

    2014-01-01

    Full Text Available This paper suggests a generalized method of moments (GMM based estimation for dynamic panel data models with individual specific fixed effects and threshold effects simultaneously. We extend Hansen’s (Hansen, 1999 original setup to models including endogenous regressors, specifically, lagged dependent variables. To address the problem of endogeneity of these nonlinear dynamic panel data models, we prove that the orthogonality conditions proposed by Arellano and Bond (1991 are valid. The threshold and slope parameters are estimated by GMM, and asymptotic distribution of the slope parameters is derived. Finite sample performance of the estimation is investigated through Monte Carlo simulations. It shows that the threshold and slope parameter can be estimated accurately and also the finite sample distribution of slope parameters is well approximated by the asymptotic distribution.

  4. Dynamic panel data models

    NARCIS (Netherlands)

    Bun, M.J.G.; Sarafidis, V.

    2013-01-01

    This Chapter reviews the recent literature on dynamic panel data models with a short time span and a large cross-section. Throughout the discussion we considerlinear models with additional endogenous covariates. First we give a broad overview of available inference methods placing emphasis on GMM.

  5. Efficient Estimation of Non-Linear Dynamic Panel Data Models with Application to Smooth Transition Models

    DEFF Research Database (Denmark)

    Gørgens, Tue; Skeels, Christopher L.; Wurtz, Allan

    This paper explores estimation of a class of non-linear dynamic panel data models with additive unobserved individual-specific effects. The models are specified by moment restrictions. The class includes the panel data AR(p) model and panel smooth transition models. We derive an efficient set...... of moment restrictions for estimation and apply the results to estimation of panel smooth transition models with fixed effects, where the transition may be determined endogenously. The performance of the GMM estimator, both in terms of estimation precision and forecasting performance, is examined in a Monte...

  6. Estimation of Dynamic Panel Data Models with Stochastic Volatility Using Particle Filters

    Directory of Open Access Journals (Sweden)

    Wen Xu

    2016-10-01

    Full Text Available Time-varying volatility is common in macroeconomic data and has been incorporated into macroeconomic models in recent work. Dynamic panel data models have become increasingly popular in macroeconomics to study common relationships across countries or regions. This paper estimates dynamic panel data models with stochastic volatility by maximizing an approximate likelihood obtained via Rao-Blackwellized particle filters. Monte Carlo studies reveal the good and stable performance of our particle filter-based estimator. When the volatility of volatility is high, or when regressors are absent but stochastic volatility exists, our approach can be better than the maximum likelihood estimator which neglects stochastic volatility and generalized method of moments (GMM estimators.

  7. Fiscal Deficit, National Saving and Sustainability of Economic Growth in Emerging Economies: A Dynamic GMM Panel Data Approach

    Directory of Open Access Journals (Sweden)

    Buscemi Antonino

    2012-01-01

    Full Text Available The neoclassical growth models argued that the movement to steady states; technology, exogenous rate of savings, population growth and technical progress stimulate higher growth levels (Solow 1956. Contrary to the neoclassical argument, endogenous growth model argues that, in the theory of endogenous growth, government play a significant role in promoting accumulation of knowledge, research and development, public investment, human capital development, law and order can generate growth both in the short and long run. Moreover, they assumed technical progress as endogenous variable for growth (Barro 1995. This study analyze the effects of fiscal deficit on sustainability of economic growth and provided new empirical evidence on the effects of fiscal deficit on saving and sustainability of economic growth based on the assumption of endogenous growth model. We estimated using the reduced form of GMM method for dynamic panels covers 1990-2009 for three emerging countries that includes China, India and South Africa.

  8. Direct energy rebound effect for road passenger transport in China: A dynamic panel quantile regression approach

    International Nuclear Information System (INIS)

    Zhang, Yue-Jun; Peng, Hua-Rong; Liu, Zhao; Tan, Weiping

    2015-01-01

    The transport sector appears a main energy consumer in China and plays a significant role in energy conservation. Improving energy efficiency proves an effective way to reduce energy consumption in transport sector, whereas its effectiveness may be affected by the rebound effect. This paper proposes a dynamic panel quantile regression model to estimate the direct energy rebound effect for road passenger transport in the whole country, eastern, central and western China, respectively, based on the data of 30 provinces from 2003 to 2012. The empirical results reveal that, first of all, the direct rebound effect does exist for road passenger transport and on the whole country, the short-term and long-term direct rebound effects are 25.53% and 26.56% on average, respectively. Second, the direct rebound effect for road passenger transport in central and eastern China tends to decrease, increase and then decrease again, whereas that in western China decreases and then increases, with the increasing passenger kilometers. Finally, when implementing energy efficiency policy in road passenger transport sector, the effectiveness of energy conservation in western China proves much better than that in central China overall, while the effectiveness in central China is relatively better than that in eastern China. - Highlights: • The direct rebound effect (RE) for road passenger transport in China is estimated. • The direct RE in the whole country, eastern, central, and western China is analyzed. • The short and long-term direct REs are 25.53% and 26.56% within the sample period. • Western China has better energy-saving performance than central and eastern China.

  9. A fuel consumption model for off-road use of mobile machinery in agriculture

    International Nuclear Information System (INIS)

    Van linden, Veerle; Herman, Lieve

    2014-01-01

    Until 2009, the annual reporting of emissions by off-road transport in agriculture in Belgium was based on a 1994 calculation model that needed to be updated. An energy consumption model was established for plant production in Belgium as a backbone for a new emission model. The model starts from agricultural activities involving off-road fuel consumption. Effects of soil type, tractor size, field size and machine load are modelled. Twenty-seven FCIs (fuel consumption indicators) were computed for plant production. FCIs are expressed per year and are used for emission estimates on a regional level. FCIs ranged from 37 to 311 L/ha. Sensitivity analysis showed the highest impact of tractor size with a surplus fuel consumption between 10 and 41% depending on the crop type. Fuel consumption (L) can be further processed into greenhouse gas emissions. FCIs can be adopted in LCA (life cycle assessment) studies. With ∼310 L/ha, orchards are most fuel intensive, followed by field vegetables and sugar beets (∼150 L/ha). The total off-road energy consumption of field vegetables is high because second cropping is a common practice. - Highlights: • An energy consumption model is proposed that is based on farming activities. • No statistical data on fuel consumption are required for the calculation. • The published FCIs can be adopted in LCA studies directly or as an allocation key

  10. Robust estimation and moment selection in dynamic fixed-effects panel data models

    NARCIS (Netherlands)

    Cizek, Pavel; Aquaro, Michele

    Considering linear dynamic panel data models with fixed effects, existing outlier–robust estimators based on the median ratio of two consecutive pairs of first-differenced data are extended to higher-order differencing. The estimation procedure is thus based on many pairwise differences and their

  11. Fuel demand in Brazil in a dynamic panel data approach

    International Nuclear Information System (INIS)

    Santos, Gervásio F.

    2013-01-01

    The purpose of this paper is to evaluate the sensitivity of fuel consumers regarding price and income, taking recent changes in the Brazilian fuel market into account. In this market, new market rules, energy policy towards fuel diversification and introduction of flex-fuel engines have determined fuel competition among gasoline, ethanol and compressed natural gas. Using a dynamic panel data model, demand equations for these three fuels are econometrically estimated to obtain consumer adjustment coefficients, price, cross-price and income elasticities in the short and long-run. In addition, the effect of the introduction of flex-fuel engines in the market and the rationality of consumers towards efficiency constraints of the engines were tested. Apart from considerable competition, results show that the dynamics of the Brazilian fuel market revolves around ethanol instead of gasoline. While demands for gasoline and natural gas are inelastic to price, demand for ethanol is elastic in Brazil. Furthermore, after the introduction of the flex-fuel technology the sensitivity of consumers to fuel prices changed, and ethanol consumers take efficiency constrains into account when ethanol prices reach the threshold of 70% of gasoline prices. - Highlights: ► Fuel demand in Brazil is evaluated, considering the changes in the fuel market. ► A dynamic panel data model is used to fit demand equations for fuels. ► Adjustment coefficients, price, cross-price and income elasticities are estimated. ► The impact of flex-fuel technology on the consumer behavior is tested. ► The results showed that the dynamic of the fuel market revolves around ethanol. ► The flex-fuel technology increased the competition among fuels

  12. Robust Estimation and Moment Selection in Dynamic Fixed-effects Panel Data Models

    NARCIS (Netherlands)

    Cizek, P.; Aquaro, M.

    2015-01-01

    This paper extends an existing outlier-robust estimator of linear dynamic panel data models with fixed effects, which is based on the median ratio of two consecutive pairs of first-differenced data. To improve its precision and robust properties, a general procedure based on many pairwise

  13. Estimating Vehicle Fuel Consumption and Emissions Using GPS Big Data

    Directory of Open Access Journals (Sweden)

    Zihan Kan

    2018-03-01

    Full Text Available The energy consumption and emissions from vehicles adversely affect human health and urban sustainability. Analysis of GPS big data collected from vehicles can provide useful insights about the quantity and distribution of such energy consumption and emissions. Previous studies, which estimated fuel consumption/emissions from traffic based on GPS sampled data, have not sufficiently considered vehicle activities and may have led to erroneous estimations. By adopting the analytical construct of the space-time path in time geography, this study proposes methods that more accurately estimate and visualize vehicle energy consumption/emissions based on analysis of vehicles’ mobile activities (MA and stationary activities (SA. First, we build space-time paths of individual vehicles, extract moving parameters, and identify MA and SA from each space-time path segment (STPS. Then we present an N-Dimensional framework for estimating and visualizing fuel consumption/emissions. For each STPS, fuel consumption, hot emissions, and cold start emissions are estimated based on activity type, i.e., MA, SA with engine-on and SA with engine-off. In the case study, fuel consumption and emissions of a single vehicle and a road network are estimated and visualized with GPS data. The estimation accuracy of the proposed approach is 88.6%. We also analyze the types of activities that produced fuel consumption on each road segment to explore the patterns and mechanisms of fuel consumption in the study area. The results not only show the effectiveness of the proposed approaches in estimating fuel consumption/emissions but also indicate their advantages for uncovering the relationships between fuel consumption and vehicles’ activities in road networks.

  14. Estimating Vehicle Fuel Consumption and Emissions Using GPS Big Data.

    Science.gov (United States)

    Kan, Zihan; Tang, Luliang; Kwan, Mei-Po; Zhang, Xia

    2018-03-21

    The energy consumption and emissions from vehicles adversely affect human health and urban sustainability. Analysis of GPS big data collected from vehicles can provide useful insights about the quantity and distribution of such energy consumption and emissions. Previous studies, which estimated fuel consumption/emissions from traffic based on GPS sampled data, have not sufficiently considered vehicle activities and may have led to erroneous estimations. By adopting the analytical construct of the space-time path in time geography, this study proposes methods that more accurately estimate and visualize vehicle energy consumption/emissions based on analysis of vehicles' mobile activities ( MA ) and stationary activities ( SA ). First, we build space-time paths of individual vehicles, extract moving parameters, and identify MA and SA from each space-time path segment (STPS). Then we present an N-Dimensional framework for estimating and visualizing fuel consumption/emissions. For each STPS, fuel consumption, hot emissions, and cold start emissions are estimated based on activity type, i.e., MA , SA with engine-on and SA with engine-off. In the case study, fuel consumption and emissions of a single vehicle and a road network are estimated and visualized with GPS data. The estimation accuracy of the proposed approach is 88.6%. We also analyze the types of activities that produced fuel consumption on each road segment to explore the patterns and mechanisms of fuel consumption in the study area. The results not only show the effectiveness of the proposed approaches in estimating fuel consumption/emissions but also indicate their advantages for uncovering the relationships between fuel consumption and vehicles' activities in road networks.

  15. Consistency in Estimation and Model Selection of Dynamic Panel Data Models with Fixed Effects

    Directory of Open Access Journals (Sweden)

    Guangjie Li

    2015-07-01

    Full Text Available We examine the relationship between consistent parameter estimation and model selection for autoregressive panel data models with fixed effects. We find that the transformation of fixed effects proposed by Lancaster (2002 does not necessarily lead to consistent estimation of common parameters when some true exogenous regressors are excluded. We propose a data dependent way to specify the prior of the autoregressive coefficient and argue for comparing different model specifications before parameter estimation. Model selection properties of Bayes factors and Bayesian information criterion (BIC are investigated. When model uncertainty is substantial, we recommend the use of Bayesian Model Averaging to obtain point estimators with lower root mean squared errors (RMSE. We also study the implications of different levels of inclusion probabilities by simulations.

  16. The Accuracy of Inference in Small Samples of Dynamic Panel Data Models

    NARCIS (Netherlands)

    Bun, M.J.G.; Kiviet, J.F.

    2001-01-01

    Through Monte Carlo experiments the small sample behavior is examined of various inference techniques for dynamic panel data models when both the time-series and cross-section dimensions of the data set are small. The LSDV technique and corrected versions of it are compared with IV and GMM

  17. Economic growth-electricity consumption causality in 12 European countries: A dynamic panel data approach

    International Nuclear Information System (INIS)

    Ciarreta, A.; Zarraga, A.

    2010-01-01

    This paper applies recent panel methodology to investigate the long-run and causal relationship between electricity consumption and real GDP for a set of 12 European countries using annual data for the period 1970-2007. The sample countries have moved faster than other neighboring countries towards the creation of a single electricity market over the past 30 years. Energy prices are also included in the study due to their important role in affecting the above variables, thus avoiding the problem of omitted variable bias. Tests for panel unit roots, cointegration in heterogeneous panels and panel causality are employed in a trivariate VECM estimated by system GMM. The results show evidence of a long-run equilibrium relationship between the three series and a negative short-run and strong causality from electricity consumption to GDP. As expected, there is bidirectional causality between energy prices and GDP and weaker evidence between electricity consumption and energy prices. These results support the policies implemented towards the creation of a common European electricity market.

  18. Bus fuel consumption model

    Energy Technology Data Exchange (ETDEWEB)

    Zargari, S.A. [Iran Univ. of Science and Technology, Teheran (Iran, Islamic Republic of); Khan, A.M. [Carleton Univ., Ottawa, ON (Canada). Dept. of Civil and Environmental Engineering

    2000-07-01

    The interest in rapid bus transit has increased sharply with the realization that modern metropolitan areas rely on public transit to provide for strong economies and communities. As a prevention tool against traffic congestion, deteriorating air quality and rising greenhouse gas emissions, this study of bus fuel consumption was designed to assist in the planning and management of rapid bus transit. The Australian Road Research Board's (ARRB) Road Fuel Consumption Model was used as a starting point. The estimations required were realized with the help of Newtonian Mechanics. The four states of vehicular traffic were examined: acceleration, cruise, deceleration, and idle. The estimated total power required from the engine to overcome resistance forces, to run vehicle accessories and overcome internal engine friction was calculated. The data for the standard and articulated bus was obtained from OC Transpo in Ottawa. The study permitted the authors to conclude that the estimations for the parameters for power requirements and fuel consumption for heavy duty vehicles are appropriate. The methodology for the estimation of fuel consumption on the Transitway, which is part of the rapid bus transit system, proved adequate. In addition, the methodology was useful to estimate fuel savings resulting from demand management strategies with potential for modal shift. 9 refs., 6 tabs.

  19. An energy-economic scenario analysis of alternative fuels for personal transport using the Global Multi-regional MARKAL model (GMM)

    International Nuclear Information System (INIS)

    Guel, Timur; Kypreos, Socrates; Turton, Hal; Barreto, Leonardo

    2009-01-01

    This paper deals with the long-term prospects of alternative fuels in global personal transport. It aims at assessing key drivers and key bottlenecks for their deployment, focusing particularly on the role of biofuels and hydrogen in meeting climate policy objectives. The analysis is pursued using the Global Multi-regional MARKAL model (GMM), a perfect foresight ''bottom-up'' model of the global energy system with a detailed representation of alternative fuel chains, linked to the Model for the Assessment of Greenhouse Gas Induced Climate Change (MAGICC). The analysis shows that biofuels are limited by the regional availability of low-cost biomass, but can be important for meeting mild climate policy targets. If policy-makers intend to pursue more stringent climate policy, then hydrogen becomes a competitive option. However, the analysis finds that the use of hydrogen in personal transport is restricted to very stringent climate policy, as only such policy provides enough incentive to build up the required delivery infrastructure. An analysis of costs additionally shows that ''keeping the hydrogen option open'' does not take considerable investments compared to the investment needs in the power sector within the next decades, but allows the use of hydrogen for the pursuit of stringent climate policy in the second half of the century. (author)

  20. Dynamic linkages between road transport energy consumption, economic growth, and environmental quality: evidence from Pakistan.

    Science.gov (United States)

    Danish; Baloch, Muhammad Awais

    2018-03-01

    The focus of the present research work is to investigate the dynamic relationship between economic growth, road transport energy consumption, and environmental quality. To this end, we rely on time series data for the period 1971 to 2014 in the context of Pakistan. To use sulfur dioxide (SO 2 ) emission from transport sector as a new proxy for measuring environmental quality, the present work employs time series technique ARDL which allows energy consumption from the transport sector, urbanization, and road infrastructure to be knotted by symmetric relationships with SO 2 emissions and economic growth. From the statistical results, we confirm that road infrastructure boosts economic growth. Simultaneously, road infrastructure and urbanization hampers environmental quality and causes to accelerate emission of SO 2 in the atmosphere. Furthermore, economic growth has a diminishing negative impact on total SO 2 emission. Moreover, we did not find any proof of the expected role of transport energy consumption in SO 2 emission. The acquired results directed that care should be taken in the expansion of road infrastructure and green city policies and planning are required in the country.

  1. Modelling the effects of transport policy levers on fuel efficiency and national fuel consumption

    International Nuclear Information System (INIS)

    Kirby, H.R.; Hutton, B.; McQuaid, R.W.; Napier Univ., Edinburgh; Raeside, R.; Napier Univ., Edinburgh; Zhang, Xiayoan; Napier Univ., Edinburgh

    2000-01-01

    The paper provides an overview of the main features of a Vehicle Market Model (VMM) which estimates changes to vehicle stock/kilometrage, fuel consumed and CO 2 emitted. It is disaggregated into four basic vehicle types. The model includes: the trends in fuel consumption of new cars, including the role of fuel price: a sub-model to estimate the fuel consumption of vehicles on roads characterised by user-defined driving cycle regimes; procedures that reflect distribution of traffic across different area/road types; and the ability to vary the speed (or driving cycle) from one year to another, or as a result of traffic growth. The most significant variable influencing fuel consumption of vehicles was consumption in the previous year, followed by dummy variables related to engine size. the time trend (a proxy for technological improvements), and then fuel price. Indeed the effect of fuel price on car fuel efficiency was observed to be insignificant (at the 95% level) in two of the three versions of the model, and the size of fuel price term was also the smallest. This suggests that the effectiveness of using fuel prices as a direct policy tool to reduce fuel consumption may he limited. Fuel prices may have significant indirect impacts (such as influencing people to purchase more fuel efficient cars and vehicle manufacturers to invest in developing fuel efficient technology) as may other factors such as the threat of legislation. (Author)

  2. Assessing links between energy consumption, freight transport, and economic growth: evidence from dynamic simultaneous equation models.

    Science.gov (United States)

    Nasreen, Samia; Saidi, Samir; Ozturk, Ilhan

    2018-06-01

    We investigate this study to examine the relationship between economic growth, freight transport, and energy consumption for 63 developing countries over the period of 1990-2016. In order to make the panel data analysis more homogeneous, we apply the income level of countries to divide the global panel into three sub-panels, namely, lower-middle income countries (LMIC), upper-middle income countries (UMIC), and high-income countries (HIC). Using the generalized method of moments (GMM), the results prove evidence of bidirectional causal relationship between economic growth and freight transport for all selected panels and between economic growth and energy consumption for the high- and upper-middle income panels. For the lower-middle income panel, the causality is unidirectional running from energy consumption to economic growth. Also, the results indicate that the relationship between freight transport and energy use is bidirectional for the high-income countries and unidirectional from freight transport to energy consumption for the upper-middle and lower-middle income countries. Empirical evidence demonstrates the importance of energy for economic activity and rejects the neo-classical assumption that energy is neutral for growth. An important policy recommendation is that there is need of advancements in vehicle technology which can reduce energy intensity from transport sector and improve the energy efficiency in transport activity which in turn allows a greater positive role of transport in global economic activity.

  3. Estimating diesel fuel consumption and carbon dioxide emissions from forest road construction

    Science.gov (United States)

    Dan Loeffler; Greg Jones; Nikolaus Vonessen; Sean Healey; Woodam Chung

    2009-01-01

    Forest access road construction is a necessary component of many on-the-ground forest vegetation treatment projects. However, the fuel energy requirements and associated carbon dioxide emissions from forest road construction are unknown. We present a method for estimating diesel fuel consumed and related carbon dioxide emissions from constructing forest roads using...

  4. Model for Estimation of Fuel Consumption of Cruise Ships

    Directory of Open Access Journals (Sweden)

    Morten Simonsen

    2018-04-01

    Full Text Available This article presents a model to estimate the energy use and fuel consumption of cruise ships that sail Norwegian waters. Automatic identification system (AIS data and technical information about cruise ships provided input to the model, including service speed, total power, and number of engines. The model was tested against real-world data obtained from a small cruise vessel and both a medium and large cruise ship. It is sensitive to speed and the corresponding engine load profile of the ship. A crucial determinate for total fuel consumption is also associated with hotel functions, which can make a large contribution to the overall energy use of cruise ships. Real-world data fits the model best when ship speed is 70–75% of service speed. With decreased or increased speed, the model tends to diverge from real-world observations. The model gives a proxy for calculation of fuel consumption associated with cruise ships that sail to Norwegian waters and can be used to estimate greenhouse gas emissions and to evaluate energy reduction strategies for cruise ships.

  5. A guide for estimating dynamic panel models: the macroeconomics models specifiness

    International Nuclear Information System (INIS)

    Coletta, Gaetano

    2005-10-01

    The aim of this paper is to review estimators for dynamic panel data models, a topic in which the interest has grown recently. As a consequence 01 this late interest, different estimation techniques have been proposed in the last few years and, given the last development of the subject, there is still a lack 01 a comprehensive guide for panel data applications, and for macroeconomics panel data models in particular. Finally, we also provide some indications about the Stata software commands to estimate dynamic panel data models with the techniques illustrated in the paper [it

  6. On-Road Validation of a Simplified Model for Estimating Real-World Fuel Economy: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Wood, Eric; Gonder, Jeff; Jehlik, Forrest

    2017-01-01

    On-road fuel economy is known to vary significantly between individual trips in real-world driving conditions. This work introduces a methodology for rapidly simulating a specific vehicle's fuel economy over the wide range of real-world conditions experienced across the country. On-road test data collected using a highly instrumented vehicle is used to refine and validate this modeling approach. Model accuracy relative to on-road data collection is relevant to the estimation of 'off-cycle credits' that compensate for real-world fuel economy benefits that are not observed during certification testing on a chassis dynamometer.

  7. Wood fuel consumption and mortality rates in Sub-Saharan Africa: Evidence from a dynamic panel study.

    Science.gov (United States)

    Sulaiman, Chindo; Abdul-Rahim, A S; Chin, Lee; Mohd-Shahwahid, H O

    2017-06-01

    This study examined the impact of wood fuel consumption on health outcomes, specifically under-five and adult mortality in Sub-Saharan Africa, where wood usage for cooking and heating is on the increase. Generalized method of moment (GMM) estimators were used to estimate the impact of wood fuel consumption on under-five and adult mortality (and also male and female mortality) in the region. The findings revealed that wood fuel consumption had significant positive impact on under-five and adult mortality. It suggests that over the studied period, an increase in wood fuel consumption has increased the mortality of under-five and adult. Importantly, it indicated that the magnitude of the effect of wood fuel consumption was more on the under-five than the adults. Similarly, assessing the effect on a gender basis, it was revealed that the effect was more on female than male adults. This finding suggests that the resultant mortality from wood smoke related infections is more on under-five children than adults, and also are more on female adults than male adults. We, therefore, recommended that an alternative affordable, clean energy source for cooking and heating should be provided to reduce the wood fuel consumption. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Impacts of GDP, Fossil Fuel Energy Consumption, Energy Consumption Intensity, and Economic Structure on SO2 Emissions: A Multi-Variate Panel Data Model Analysis on Selected Chinese Provinces

    Directory of Open Access Journals (Sweden)

    Haoran Zhao

    2018-03-01

    Full Text Available Atmospheric pollution gradually become a focus of concern all over the world owing to its detrimental influence on human health as well as long range impact on global ecosystem. This paper investigated the relationship among SO2 emissions, GDP, fossil fuel energy consumption, energy consumption intensity, and economic structure of five provinces in China with the highest SO2 emissions spanning from 2002–2015 based on panel data model. Through comparatively analyzing the coefficients in the established panel data model for Hebei, Henan, Inner Mongolia, Shandong, and Shanxi, we can obtain that: (1 fossil fuel energy consumption made the most devotion to SO2 discharge compared with GDP, energy consumption intensity, and economic structure. And the more the fossil fuel energy consumption, the more the devotion made by it to SO2 discharge. (2 GDP devoted less to SO2 emissions than fossil fuel energy consumption, and the larger the scale of the economy, the greater the contribution made by it to SO2 emissions. (3 The higher the proportion of the secondary industry added value accounted in GDP, the more the devotion made by the economic structure and energy consumption intensity to SO2 emissions. Through analyzing the Granger causality examination results, it can be concluded that: (1 there existed a bi-directional causal relationship between fossil fuel energy consumption and SO2 emissions among five selected provinces. (2 There existed uni-directional causal nexus running from GDP to SO2 emissions, from energy consumption intensity to SO2 emissions, and from economic structure to SO2 emissions among five chosen provinces. Based on the empirical analysis, several policy implications were proposed to provide references for policy makers, which were (1 Giving full play to the guiding role of price signals, and improving the price policy for desulfurization. (2 Formulating a new comprehensive evaluation system to measure the regional development level

  9. Emissions and Fuel Consumption Modeling for Evaluating Environmental Effectiveness of ITS Strategies

    Directory of Open Access Journals (Sweden)

    Yuan-yuan Song

    2013-01-01

    Full Text Available Road transportation is a major fuel consumer and greenhouse gas emitter. Recently, the intelligent transportation systems (ITSs technologies, which can improve traffic flow and safety, have been developed to reduce the fuel consumption and vehicle emissions. Emission and fuel consumption estimation models play a key role in the evaluation of ITS technologies. Based on the influence analysis of driving parameters on vehicle emissions, this paper establishes a set of mesoscopic vehicle emission and fuel consumption models using the real-world vehicle operation and emission data. The results demonstrate that these models are more appropriate to evaluate the environmental effectiveness of ITS strategies with enough estimation accuracy.

  10. A Fuzzy Modeling Approach to Road Transport with Application to a Case of Spent Nuclear Fuel Transport

    International Nuclear Information System (INIS)

    Marseguerra, Marzio; Zio, Enrico; Bianchi, Mauro

    2004-01-01

    In this paper, we propose a general fuzzy inference approach to building a model of hazardous road transport that relates given traffic, weather, and vehicle-speed conditions to the accident rate. The development of the model is discussed in detail, and its validation is provided with reference to literature data regarding the transport of spent nuclear fuel to its final confinement repository

  11. Accurate Fuel Estimates using CAN Bus Data and 3D Maps

    DEFF Research Database (Denmark)

    Andersen, Ove; Torp, Kristian

    2018-01-01

    The focus on reducing CO 2 emissions from the transport sector is larger than ever. Increasingly stricter reductions on fuel consumption and emissions are being introduced by the EU, e.g., to reduce the air pollution in many larger cities. Large sets of high-frequent GPS data from vehicles already...... the accuracy of fuel consumption estimates with up to 40% on hilly roads. There is only very little improvement of the high-precision (H3D) map over the simple 3D map. The fuel consumption estimates are most accurate on flat terrain with average fuel estimates of up to 99% accuracy. The fuel estimates are most...... exist. However, fuel consumption data is still rarely collected even though it is possible to measure the fuel consumption with high accuracy, e.g., using an OBD-II device and a smartphone. This paper, presents a method for comparing fuel-consumption estimates using the SIDRA TRIP model with real fuel...

  12. Monte Carlo Simulation Of The Portfolio-Balance Model Of Exchange Rates: Finite Sample Properties Of The GMM Estimator

    OpenAIRE

    Hong-Ghi Min

    2011-01-01

    Using Monte Carlo simulation of the Portfolio-balance model of the exchange rates, we report finite sample properties of the GMM estimator for testing over-identifying restrictions in the simultaneous equations model. F-form of Sargans statistic performs better than its chi-squared form while Hansens GMM statistic has the smallest bias.

  13. An iterated GMM procedure for estimating the Campbell-Cochrane habit formation model, with an application to Danish stock and bond returns

    DEFF Research Database (Denmark)

    Engsted, Tom; Møller, Stig V.

    We suggest an iterated GMM approach to estimate and test the consumption based habit persistence model of Campbell and Cochrane (1999), and we apply the approach on annual and quarterly Danish stock and bond returns. For comparative purposes we also estimate and test the standard CRRA model...... than 80 years there is absolutely no evidence of superior performance of the Campbell-Cochrane model. For the shorter and more recent quarterly data over a 20-30 year period, there is some evidence of counter-cyclical time-variation in the degree of risk-aversion, in accordance with the Campbell...

  14. Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix

    NARCIS (Netherlands)

    Bun, M.J.G.

    2003-01-01

    Approximation formulae are developed for the bias of ordinary and generalized Least Squares Dummy Variable (LSDV) estimators in dynamic panel data models. Results from Kiviet [Kiviet, J. F. (1995), on bias, inconsistency, and efficiency of various estimators in dynamic panel data models, J.

  15. An Iterated GMM Procedure for Estimating the Campbell-Cochrane Habit Formation Model, with an Application to Danish Stock and Bond Returns

    DEFF Research Database (Denmark)

    Engsted, Tom; Møller, Stig Vinther

    2010-01-01

    We suggest an iterated GMM approach to estimate and test the consumption based habit persistence model of Campbell and Cochrane, and we apply the approach on annual and quarterly Danish stock and bond returns. For comparative purposes we also estimate and test the standard constant relative risk...... covering more than 80 years there is absolutely no evidence of superior performance of the Campbell-Cochrane model. For the shorter and more recent quarterly data over a 20-30 year period, there is some evidence of counter-cyclical time-variation in the degree of risk-aversion, in accordance...

  16. GMM Estimator: An Application to Intraindustry Trade

    Directory of Open Access Journals (Sweden)

    Nuno Carlos Leitão

    2012-01-01

    Full Text Available This paper investigates the determinants of intraindustry trade (IIT, horizontal IIT (HIIT, and Vertical IIT (VIIT in the automobile industry in Portugal. The trade in this sector between Portugal and the European Union (EU-27 was examined, between 1995 and 2008, using a dynamic panel data. We apply the GMM system to solve the problems of serial correlation and the endogeneity of some explanatory variables. The findings are consistent with the literature. The difference between per capita incomes and factor endowments present a positive sign. These results are according to Heckscher-Ohlin predictions. The economic dimension has a positive impact on trade. A negative effect of the distance on bilateral trade was expected and the results confirm this, underlining the importance of neighbour partnerships for all trade.

  17. Inference in High-dimensional Dynamic Panel Data Models

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl; Tang, Haihan

    We establish oracle inequalities for a version of the Lasso in high-dimensional fixed effects dynamic panel data models. The inequalities are valid for the coefficients of the dynamic and exogenous regressors. Separate oracle inequalities are derived for the fixed effects. Next, we show how one can...

  18. Societal Economics of the European Union Liquid Fuel Consumption for Road Transportation

    Directory of Open Access Journals (Sweden)

    Alfred Wong

    2016-08-01

    Full Text Available In order for the EU to achieve its goal of 10% biofuel for all EU motor vehicles by 2020, a substantial amount of biofuel as well as a biofuel feedstock would need to be imported largely from developing countries where the climate is warm and labor is inexpensive. But there may never be sufficient supply to fulfill the evergrowing demand for biofuel for road transportation in the EU, even as motor vehicles are increasingly becoming more fuel-efficient. The constraint to realizing an effective and equitable reduction in greenhousegas emission is the overbearing political economics of neoliberalism. A different remedial strategy is needed to address the dual problems of the excessive uses of motor fuels and greenhouse-gas emission.

  19. A GMM-IG framework for selecting genes as expression panel biomarkers.

    Science.gov (United States)

    Wang, Mingyi; Chen, Jake Y

    2010-01-01

    The limitation of small sample size of functional genomics experiments has made it necessary to integrate DNA microarray experimental data from different sources. However, experimentation noises and biases of different microarray platforms have made integrated data analysis challenging. In this work, we propose an integrative computational framework to identify candidate biomarker genes from publicly available functional genomics studies. We developed a new framework, Gaussian Mixture Modeling-Coupled Information Gain (GMM-IG). In this framework, we first apply a two-component Gaussian mixture model (GMM) to estimate the conditional probability distributions of gene expression data between two different types of samples, for example, normal versus cancer. An expectation-maximization algorithm is then used to estimate the maximum likelihood parameters of a mixture of two Gaussian models in the feature space and determine the underlying expression levels of genes. Gene expression results from different studies are discretized, based on GMM estimations and then unified. Significantly differentially-expressed genes are filtered and assessed with information gain (IG) measures. DNA microarray experimental data for lung cancers from three different prior studies was processed using the new GMM-IG method. Target gene markers from a gene expression panel were selected and compared with several conventional computational biomarker data analysis methods. GMM-IG showed consistently high accuracy for several classification assessments. A high reproducibility of gene selection results was also determined from statistical validations. Our study shows that the GMM-IG framework can overcome poor reliability issues from single-study DNA microarray experiment while maintaining high accuracies by combining true signals from multiple studies. We present a conceptually simple framework that enables reliable integration of true differential gene expression signals from multiple

  20. Modeling vehicle fuel consumption and emissions at signalized intersection approaches : integrating field-collected data into microscopic simulation.

    Science.gov (United States)

    2012-07-01

    Microscopic models produce emissions and fuel consumption estimates with higher temporal resolution than other scales of : models. Most emissions and fuel consumption models were developed with data from dynamometer testing which are : sufficiently a...

  1. Does ICT Participate in Economic Convergence among Asian Countries: Evidence from Dynamic Panel Data Model

    Directory of Open Access Journals (Sweden)

    Bilal MEHMOOD

    2013-01-01

    Full Text Available Conventional Convergence models usually oversee the role of information and communications technology (ICT as a determinant of convergence. This paper introduces ICT as a factor contributing towards economic convergence in Asian countries. In addition to ICT, other factors like demographic traits, level of human development and electricity consumption are used as regressors. System GMM technique is used to estimate convergence regression for se-lected Asian countries for data of time span 2001-2010. Support for ICT-augmented conver-gence is found, implying that ICT has the tendency to participate in convergence process. Suitable demographic features, human development and electricity consumption are also found to contribute to economic convergence in the sample countries of Asia. Findings of this paper indicate the need to complement the favorable demographic endowments in Asian economies with economically productive usage of ICT to proceed towards economic convergence in Asian Region.

  2. Estimation of Turkish road transport emissions

    International Nuclear Information System (INIS)

    Soylu, Seref

    2007-01-01

    Using the COPERT III program, an inventory of Turkish road transport emissions was calculated and the contributions of road transport to global and local air pollutant emissions were examined for the year 2004. It was observed that passenger cars are the main source of CO, HC, and Pb emissions while heavy duty vehicles are mainly responsible for NO x , particulate matter (PM), and SO 2 emissions. Taking the emissions for the year 2004 as the baseline, a parametric study was conducted to determine the emission reduction potentials of different road transport strategies. The results indicated that the following road transport strategies; fleet renewal, promotion of public transportation, and faster urban traffic speed are very effective strategies for reducing regulated emissions and fuel consumption (FC) from a technical point of view. It was also noted that replacement of two-stroke motorcycles with four-stroke motorcycles is as effective as fleet renewal in reducing HC emissions

  3. Developing Singapore Driving Cycle for passenger cars to estimate fuel consumption and vehicular emissions

    Science.gov (United States)

    Ho, Sze-Hwee; Wong, Yiik-Diew; Chang, Victor Wei-Chung

    2014-11-01

    Singapore has pledged to attain 7-11% Business-As-Usual carbon emissions reduction by 2020. Road transport sector is a significant source of carbon emissions, estimated to be the third largest sector in Singapore. A current gap in environmental evaluation for road transport activities in Singapore is the lack of a representative driving cycle for passenger cars (64% of the total population of 974,170 vehicles). This Singapore Driving Cycle (SDC) is hence developed for Singapore roads and traffic conditions. A chase-car (instrumented vehicle) was used to collect on-road data along 12 designed routes, and circulation driving on highly utilized arterial roads (including those in Central Business District (CBD) and both inner and outer ring roads fringing the CBD area). The SDC was thus hence constructed, with consideration of road type proportions, time periods and desired distance, duration and peak-lull proportion. In essence, the SDC is a 2400-s speed-time profile to represent the driving pattern for passenger car in Singapore. Microscopic estimation model (CMEM) shows that, as compared to SDC, the New European Driving Cycle (NEDC) underestimates most of the vehicular emissions (fuel, CO2, HC and NOx by 5%, 5%, 22% and 47%, respectively) and overestimates CO by 8%. The SDC is thus more suitable than the NEDC that is currently in use in Singapore; the SDC can be used to generate more accurate fuel consumption and emissions ratings for various uses (for example, inventory of vehicular emissions and fuel economy labelling).

  4. Heavy truck modeling for fuel consumption. Simulations and measurements

    Energy Technology Data Exchange (ETDEWEB)

    Sandberg, T.

    2001-12-01

    Fuel consumption for heavy trucks depends on many factors like roads, weather, and driver behavior that are hard for a manufacturer to influence. However, one design possibility is the power train configuration. Here a new simulation program for heavy trucks is created to find the configuration of the power train that gives the lowest fuel consumption for each transport task. For efficient simulations the model uses production code for speed and gear control, and it uses exchangeable data sets to allow simulation of the whole production range of engine types, on recorded road profiles from all over the world. Combined with a graphical user interface this application is called STARS (Scania Truck And Road Simulation). The forces of rolling resistance and air resistance in the model are validated through an experiment where the propeller shaft torque of a heavy truck is measured. It is found that the coefficient of rolling resistance is strongly dependent on tire temperature, not only on vehicle speed as expected. This led to the development of a new model for rolling resistance. The model includes the dynamic behavior of the tires and relates rolling resistance to tire temperature and vehicle speed. In another experiment the fuel consumption of a test truck in highway driving is measured. The altitude of the road is recorded with a barometer and used in the corresponding simulations. Despite of the limited accuracy of this equipment the simulation program manage to predict a level of fuel consumption only 2% lower than the real measurements. It is concluded that STARS is a good tool for predicting fuel consumption for trucks in highway driving and for comparing different power train configurations.

  5. Denton, Texas: Using Transportation Data to Reduce Fuel Consumption (City Energy: From Data to Decisions)

    Energy Technology Data Exchange (ETDEWEB)

    Office of Strategic Programs, Strategic Priorities and Impact Analysis Team

    2017-09-29

    This fact sheet "Denton, Texas: Using Transportation Data to Reduce Fuel Consumption" explains how the City of Denton used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

  6. Systems GMM estimates of the health care spending and GDP relationship: a note.

    Science.gov (United States)

    Kumar, Saten

    2013-06-01

    This paper utilizes the systems generalized method of moments (GMM) [Arellano and Bover (1995) J Econometrics 68:29-51; Blundell and Bond (1998) J Econometrics 87:115-143], and panel Granger causality [Hurlin and Venet (2001) Granger Causality tests in panel data models with fixed coefficients. Mime'o, University Paris IX], to investigate the health care spending and gross domestic product (GDP) relationship for organisation for economic co-operation and development countries over the period 1960-2007. The system GMM estimates confirm that the contribution of real GDP to health spending is significant and positive. The panel Granger causality tests imply that a bi-directional causality exists between health spending and GDP. To this end, policies aimed at raising health spending will eventually improve the well-being of the population in the long run.

  7. Reducing stress and fuel consumption providing road information

    Directory of Open Access Journals (Sweden)

    Víctor CORCOBA MAGAÑA

    2014-12-01

    Full Text Available In this paper, we propose a solution to reduce the stress level of the driver, minimize fuel consumption and improve safety. The system analyzes the driving style and the driver’s workload during the trip while driving. If it discovers an area where the stress increases and the driving style is not appropriate from the point of view of energy efficiency and safety for a particular driver, the location of this area is saved in a shared database. On the other hand, the implemented solution warns a particular user when approaching a region where the driving is difficult (high fuel consumption and stress using the shared database based on previous recorded knowledge of similar drivers in that area. In this case, the proposal provides an optimal deceleration profile if the vehicle speed is not adequate. Therefore, he or she may adjust the vehicle speed with both a positive impact on the driver workload and fuel consumption. The Data Envelopment Analysis algorithm is used to estimate the efficiency of driving and the driver’s workload in in each area. We employ this method because there is no preconceived form on the data in order to calculate the efficiency and stress level. A validation experiment has been conducted using both a driving simulator and a real environment with 12 participants who made 168 driving tests. The system reduced the slowdowns (38%, heart rate (4.70%, and fuel consumption (12.41% in the real environment. The proposed solution is implemented on Android mobile devices and does not require the installation of infrastructure on the road. It can be installed on any model of vehicle.

  8. The Relationship between Residential Electricity Consumption and Income: A Piecewise Linear Model with Panel Data

    Directory of Open Access Journals (Sweden)

    Yanan Liu

    2016-10-01

    Full Text Available There are many uncertainties and risks in residential electricity consumption associated with economic development. Knowledge of the relationship between residential electricity consumption and its key determinant—income—is important to the sustainable development of the electric power industry. Using panel data from 30 provinces for the 1995–2012 period, this study investigates how residential electricity consumption changes as incomes increase in China. Previous studies typically used linear or quadratic double-logarithmic models imposing ex ante restrictions on the indistinct relationship between residential electricity consumption and income. Contrary to those models, we employed a reduced piecewise linear model that is self-adaptive and highly flexible and circumvents the problem of “prior restrictions”. Robust tests of different segment specifications and regression methods are performed to ensure the validity of the research. The results provide strong evidence that the income elasticity was approximately one, and it remained stable throughout the estimation period. The income threshold at which residential electricity consumption automatically remains stable or slows has not been reached. To ensure the sustainable development of the electric power industry, introducing higher energy efficiency standards for electrical appliances and improving income levels are vital. Government should also emphasize electricity conservation in the industrial sector rather than in residential sector.

  9. Bias corrrection in the dynamic panel data model with a nonscalar disturbance covariance matrix

    NARCIS (Netherlands)

    Bun, M.J.G.

    2001-01-01

    Approximation formulae are developed for the bias of ordinary andgeneralized Least Squares Dummy Variable (LSDV) estimators in dynamicpanel data models. Results from Kiviet (1995, 1999) are extended tohigher-order dynamic panel data models with general covariancestructure. The focus is on estimation

  10. State energy data report 1996: Consumption estimates

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-02-01

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the Combined State Energy Data System (CSEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining CSEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. CSEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public and (2) to provide the historical series necessary for EIA`s energy models. To the degree possible, energy consumption has been assigned to five sectors: residential, commercial, industrial, transportation, and electric utility sectors. Fuels covered are coal, natural gas, petroleum, nuclear electric power, hydroelectric power, biomass, and other, defined as electric power generated from geothermal, wind, photovoltaic, and solar thermal energy. 322 tabs.

  11. State energy data report 1996: Consumption estimates

    International Nuclear Information System (INIS)

    1999-02-01

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the Combined State Energy Data System (CSEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining CSEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. CSEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public and (2) to provide the historical series necessary for EIA's energy models. To the degree possible, energy consumption has been assigned to five sectors: residential, commercial, industrial, transportation, and electric utility sectors. Fuels covered are coal, natural gas, petroleum, nuclear electric power, hydroelectric power, biomass, and other, defined as electric power generated from geothermal, wind, photovoltaic, and solar thermal energy. 322 tabs

  12. System Estimation of Panel Data Models under Long-Range Dependence

    DEFF Research Database (Denmark)

    Ergemen, Yunus Emre

    A general dynamic panel data model is considered that incorporates individual and interactive fixed effects allowing for contemporaneous correlation in model innovations. The model accommodates general stationary or nonstationary long-range dependence through interactive fixed effects...... and innovations, removing the necessity to perform a priori unit-root or stationarity testing. Moreover, persistence in innovations and interactive fixed effects allows for cointegration; innovations can also have vector-autoregressive dynamics; deterministic trends can be featured. Estimations are performed...

  13. CAUSAL RELATIONSHIP BETWEEN ENERGY CONSUMPTION, ECONOMIC GROWTH AND CO2 EMISSIONS: A DYNAMIC PANEL DATA APPROACH

    Directory of Open Access Journals (Sweden)

    Chaido Dritsaki

    2014-04-01

    Full Text Available Energy plays an important role in economic development worldwide. The increase of energy consumption showed that CO2 emissions in the atmosphere have increased dramatically, and these lead many scientists to push governments of the developing countries to take action for the formulation of environmental policies. Many studies have attempted to look for the direction of causality between energy consumption (EC, economic growth (GDP and CO2 emissions mainly on developing countries. This paper, therefore, applies the panel unit root tests, panel cointegration methods and panel causality test to investigate the relationship between energy consumption (EC, economic growth (GDP and CO2 emissions for three countries of Southern Europe (Greece, Spain, and Portugal covering the annual period 1960-2009. The FMOLS and DOLS are then used to estimate the long run relationship between the variables. The findings of this study reveal that there is a short-run bilateral causal link between the examined variables. However, in the long run, there is a unidirectional causality running from CO2 emissions to energy consumption (EC, and economic growth (GDP and a bilateral causality between energy consumption and economic growth. This indicates that energy is a force for economic growth both in short and long run as it is driven from economic growth. Moreover, to face the heterogeneity on the three countries of Southern Europe we use the FMOLS and DOLS estimation methods.

  14. Estimating Energy Consumption of Transport Modes in China Using DEA

    Directory of Open Access Journals (Sweden)

    Weibin Lin

    2015-04-01

    Full Text Available The rapid growth of transport requirements in China will incur increasing transport energy demands and associated environmental pressures. In this paper, we employ a generalized data envelopment analysis (DEA to evaluate the relative energy efficiency of rail, road, aviation and water transport from 1971 to 2011 by considering the energy input and passenger-kilometers (PKM and freight ton-kilometers (TKM outputs. The results show that the optimal energy efficiencies observed in 2011 are for rail and water transport, with the opposite observed for the energy efficiencies of aviation and road transport. In addition, we extend the DEA model to estimate future transport energy consumption in China. If each transport mode in 2020 is optimized throughout the observed period, the national transport energy consumption in 2020 will reach 497,701 kilotons coal equivalent (ktce, whereas the annual growth rate from 2011 to 2020 will be 5.7%. Assuming that efficiency improvements occur in this period, the estimated national transport energy consumption in 2020 will be 443,126 ktce, whereas the annual growth rate from 2011 to 2020 will be 4.4%, which is still higher than that of the national total energy consumption (3.8%.

  15. Fuel Burn Estimation Model

    Science.gov (United States)

    Chatterji, Gano

    2011-01-01

    Conclusions: Validated the fuel estimation procedure using flight test data. A good fuel model can be created if weight and fuel data are available. Error in assumed takeoff weight results in similar amount of error in the fuel estimate. Fuel estimation error bounds can be determined.

  16. Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time

    NARCIS (Netherlands)

    Mesters, G.; Koopman, S.J.

    2014-01-01

    An exact maximum likelihood method is developed for the estimation of parameters in a nonlinear non-Gaussian dynamic panel data model with unobserved random individual-specific and time-varying effects. We propose an estimation procedure based on the importance sampling technique. In particular, a

  17. A guide for estimating dynamic panel models: the macroeconomics models specifiness; Una guida per la stima dei modelli panel dinamici: le specificita dei modelli macroeconomici

    Energy Technology Data Exchange (ETDEWEB)

    Coletta, Gaetano [ENEA, Centro Ricerche Casaccia, Rome (Italy). Unita di Agenzia per lo Sviluppo Sostenibile Advisor

    2005-10-15

    The aim of this paper is to review estimators for dynamic panel data models, a topic in which the interest has grown recently. As a consequence 01 this late interest, different estimation techniques have been proposed in the last few years and, given the last development of the subject, there is still a lack 01 a comprehensive guide for panel data applications, and for macroeconomics panel data models in particular. Finally, we also provide some indications about the Stata software commands to estimate dynamic panel data models with the techniques illustrated in the paper. [Italian] L'obiettivo del presente lavoro e quello di effettuare una rassegna degli stimatori per modelli panel dinamici, una materia per cui l'interesse e cresciuto di recente. In conseguenza di questo crescente interesse, negli ultimi anni sono stati proposti una serie di differenti tecniche di stima ma, dato il rapido sviluppo della materia, non esiste, infatti, una guida esaustiva per le applicazioni su dati panel, in particolare nel caso di modelli macroeconomici. A conclusione del lavoro sono fornite, infine, alcune indicazioni relative ai comandi del software Stata per stimare i modelli panel dinamici con le tecniche illustrate nel testo.

  18. Estimating a theoretical model of state banking competition using a dynamic panel: the Brazilian case

    Directory of Open Access Journals (Sweden)

    Fábio A. Miessi Sanches

    2009-03-01

    Full Text Available In this paper we set up a model of regional banking competition based on Bresnahan (1982, Lau (1982 and Nakane (2002. The structural model is estimated using data from eight Brazilian states and a dynamic panel. The results show that on average the level of competition in the Brazilian banking system is high, even tough the null of perfect competition can be rejected at the usual significance levels. This result also prevails at the state level: Rio Grande do Sul, São Paulo, Rio de Janeiro, Pernambuco and Minas Gerais have high degree of competition.

  19. Dynamic spatial panels : models, methods, and inferences

    NARCIS (Netherlands)

    Elhorst, J. Paul

    This paper provides a survey of the existing literature on the specification and estimation of dynamic spatial panel data models, a collection of models for spatial panels extended to include one or more of the following variables and/or error terms: a dependent variable lagged in time, a dependent

  20. Accessing and constructing driving data to develop fuel consumption forecast model

    Science.gov (United States)

    Yamashita, Rei-Jo; Yao, Hsiu-Hsen; Hung, Shih-Wei; Hackman, Acquah

    2018-02-01

    In this study, we develop a forecasting models, to estimate fuel consumption based on the driving behavior, in which vehicles and routes are known. First, the driving data are collected via telematics and OBDII. Then, the driving fuel consumption formula is used to calculate the estimate fuel consumption, and driving behavior indicators are generated for analysis. Based on statistical analysis method, the driving fuel consumption forecasting model is constructed. Some field experiment results were done in this study to generate hundreds of driving behavior indicators. Based on data mining approach, the Pearson coefficient correlation analysis is used to filter highly fuel consumption related DBIs. Only highly correlated DBI will be used in the model. These DBIs are divided into four classes: speed class, acceleration class, Left/Right/U-turn class and the other category. We then use K-means cluster analysis to group to the driver class and the route class. Finally, more than 12 aggregate models are generated by those highly correlated DBIs, using the neural network model and regression analysis. Based on Mean Absolute Percentage Error (MAPE) to evaluate from the developed AMs. The best MAPE values among these AM is below 5%.

  1. Environmental Kuznets Curve in China: New evidence from dynamic panel analysis

    International Nuclear Information System (INIS)

    Li, Tingting; Wang, Yong; Zhao, Dingtao

    2016-01-01

    This paper applies a panel of 28 provinces of China from 1996 to 2012 to study the impacts of economic development, energy consumption, trade openness, and urbanization on the carbon dioxide, waste water, and waste solid emissions. By estimating a dynamic panel model with the system Generalized Method of Moments (GMM) estimator and an autoregressive distributed lag (ARDL) model with alternative panel estimators, respectively, we find that the Environmental Kuznets Curve (EKC) hypothesis is well supported for all three major pollutant emissions in China across different models and estimation methods. Our study also confirms positive effects of energy consumption on various pollutant emissions. In addition, we find some evidence that trade and urbanization may deteriorate environmental quality in the long run, albeit not in the short run. From policy perspective, our estimation results bode well for Chinese government's goal of capping greenhouse emissions by 2030 as outlined in the recent China-US climate accord, while containing energy consumption and harm effects from expanding trade and urbanization remains some environmental challenges that China faces. - Highlights: •We apply dynamic panel estimations to study the EKC hypothesis with Chinese panel data. •Our study covers three indicators: carbon dioxide, waste water, and waste solid emissions. •We find robust support for the EKC hypothesis for all three indicators of pollution. •Energy consumption has significantly positive effects on all three pollutant emissions. •Trade and urbanization may have harmful environmental impacts in the long run.

  2. Road transport fuels in europe: the explosion of demand for diesel fuel

    International Nuclear Information System (INIS)

    Bensaid, B.

    2004-01-01

    In the last 20 years, road transport fuel consumption has more than doubled in European countries, due to strong growth on the diesel passenger car segment and in the transport of road freight. In an economy heavily dependent on oil, European authorities are seeking to promote alternative energy solutions, such as motor fuels produced from biomass

  3. Impact of Energy Consumption on Economic Growth in Major OECD Economies (1977-2014): A Panel Data Approach

    OpenAIRE

    Aali-Bujari, Alí; Venegas-Martínez, Francisco; Palafox-Roca, Alfredo Omar

    2017-01-01

    This paper is aimed at assessing the impact of energy use growth on economic growth in the major economies of the Organization for Economic Cooperation and Development (OECD) during the period 1977-2014. To do this, a Granger causality analysis among relevant variables is carried out and, subsequently, a panel data model is estimated with the Generalized Method of Moments (GMM). The main empirical finding is that real GDP per capita growth is positively affected by the growth rate of energy u...

  4. Modeling of pollutant emissions from road transport; Modelisation des emissions de polluants par le transport routier

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2003-07-01

    COPERT III (computer programme to calculate emissions from road transport) is the third version of an MS Windows software programme aiming at the calculation of air pollutant emissions from road transport. COPERT estimates emissions of all regulated air pollutants (CO, NO{sub x}, VOC, PM) produced by different vehicle categories as well as CO{sub 2} emissions on the basis of fuel consumption. This research seminar was organized by the French agency of environment and energy mastery (Ademe) around the following topics: the uncertainties and sensitiveness analysis of the COPERT III model, the presentation of case studies that use COPERT III for the estimation of road transport emissions, and the future of the modeling of road transport emissions: from COPERT III to ARTEMIS (assessment and reliability of transport emission models and inventory systems). This document is a compilation of 8 contributions to this seminar and dealing with: the uncertainty and sensitiveness analysis of the COPERT III model; the road mode emissions of the ESCOMPTE program: sensitivity study; the sensitivity analysis of the spatialized traffic at the time-aggregation level: application in the framework of the INTERREG project (Alsace); the road transport aspect of the regional air quality plan of Bourgogne region: exhaustive consideration of the road network; intercomparison of tools and methods for the inventory of emissions of road transport origin; evolution of the French park of vehicles by 2025: new projections; application of COPERT III to the French context: a new version of IMPACT-ADEME; the European ARTEMIS project: new structural considerations for the modeling of road transport emissions. (J.S.)

  5. A model for the estimation of energy consumption and air pollutant emissions from rail transport

    DEFF Research Database (Denmark)

    Lindgreen, Erik Bjørn Grønning; Sorenson, Spencer C

    2003-01-01

    A model is presented for the calculation of energy consumption and air pollutant emissions from rail transport. It is based on the estimation of energy consumption from a matirx describing the distribution of speeds and accelerations for operation. It is shown that calculations can be performed...

  6. Fuel Burn Estimation Using Real Track Data

    Science.gov (United States)

    Chatterji, Gano B.

    2011-01-01

    A procedure for estimating fuel burned based on actual flight track data, and drag and fuel-flow models is described. The procedure consists of estimating aircraft and wind states, lift, drag and thrust. Fuel-flow for jet aircraft is determined in terms of thrust, true airspeed and altitude as prescribed by the Base of Aircraft Data fuel-flow model. This paper provides a theoretical foundation for computing fuel-flow with most of the information derived from actual flight data. The procedure does not require an explicit model of thrust and calibrated airspeed/Mach profile which are typically needed for trajectory synthesis. To validate the fuel computation method, flight test data provided by the Federal Aviation Administration were processed. Results from this method show that fuel consumed can be estimated within 1% of the actual fuel consumed in the flight test. Next, fuel consumption was estimated with simplified lift and thrust models. Results show negligible difference with respect to the full model without simplifications. An iterative takeoff weight estimation procedure is described for estimating fuel consumption, when takeoff weight is unavailable, and for establishing fuel consumption uncertainty bounds. Finally, the suitability of using radar-based position information for fuel estimation is examined. It is shown that fuel usage could be estimated within 5.4% of the actual value using positions reported in the Airline Situation Display to Industry data with simplified models and iterative takeoff weight computation.

  7. Using field data to assess model predictions of surface and ground fuel consumption by wildfire in coniferous forests of California

    Science.gov (United States)

    Lydersen, Jamie M.; Collins, Brandon M.; Ewell, Carol M.; Reiner, Alicia L.; Fites, Jo Ann; Dow, Christopher B.; Gonzalez, Patrick; Saah, David S.; Battles, John J.

    2014-03-01

    Inventories of greenhouse gas (GHG) emissions from wildfire provide essential information to the state of California, USA, and other governments that have enacted emission reductions. Wildfires can release a substantial amount of GHGs and other compounds to the atmosphere, so recent increases in fire activity may be increasing GHG emissions. Quantifying wildfire emissions however can be difficult due to inherent variability in fuel loads and consumption and a lack of field data of fuel consumption by wildfire. We compare a unique set of fuel data collected immediately before and after six wildfires in coniferous forests of California to fuel consumption predictions of the first-order fire effects model (FOFEM), based on two different available fuel characterizations. We found strong regional differences in the performance of different fuel characterizations, with FOFEM overestimating the fuel consumption to a greater extent in the Klamath Mountains than in the Sierra Nevada. Inaccurate fuel load inputs caused the largest differences between predicted and observed fuel consumption. Fuel classifications tended to overestimate duff load and underestimate litter load, leading to differences in predicted emissions for some pollutants. When considering total ground and surface fuels, modeled consumption was fairly accurate on average, although the range of error in estimates of plot level consumption was very large. These results highlight the importance of fuel load input to the accuracy of modeled fuel consumption and GHG emissions from wildfires in coniferous forests.

  8. Alternative transport fuels: supply, consumption and conservation

    International Nuclear Information System (INIS)

    Trindade, S.C.

    1990-01-01

    Road-based passenger and freight transport almost exclusively uses petroleum/hydrocarbon fuels in the fluid form. These fuels will probably continue to be major transport fuels well into the 21st century. As such there is need to prolong their use which can be done through: (1) conservation of fuel by increasing efficiency of internal combustion engines, and (2) conversion of natural gas, coal and peat, and biomass into alternate fuels such as ethanol, methanol, CNG, LNG, LPG, low heat-content (producer) gas and vegetable oils. Research, development and demonstration (RD and D) priorities in supply, consumption and conservation of these alternate fuels are identified and ranked in the context of situation prevailing in Brazil. Author has assigned the highest priority for research in the impact of pricing, economic, fiscal and trade policies, capital allocation criteria and institutional and legislative framework. It has also been emphasised that an integrated or systems approach is mandatory to achieve net energy gains in transport sector. (M.G.B.). 33 refs., 11 tabs., 4 figs

  9. Does Climate Change Mitigation Activity Affect Crude Oil Prices? Evidence from Dynamic Panel Model

    OpenAIRE

    Dike, Jude C.

    2014-01-01

    This paper empirically investigates how climate change mitigation affects crude oil prices while using carbon intensity as the indicator for climate change mitigation. The relationship between crude oil prices and carbon intensity is estimated using an Arellano and Bond GMM dynamic panel model. This study undertakes a regional-level analysis because of the geographical similarities among the countries in a region. Regions considered for the study are Africa, Asia and Oceania, Central and Sout...

  10. Markov models for digraph panel data : Monte Carlo-based derivative estimation

    NARCIS (Netherlands)

    Schweinberger, Michael; Snijders, Tom A. B.

    2007-01-01

    A parametric, continuous-time Markov model for digraph panel data is considered. The parameter is estimated by the method of moments. A convenient method for estimating the variance-covariance matrix of the moment estimator relies on the delta method, requiring the Jacobian matrix-that is, the

  11. Estimating emissions on vehicular traffic based on projected energy and transport demand on rural roads: Policies for reducing air pollutant emissions and energy consumption

    International Nuclear Information System (INIS)

    Ozan, Cenk; Haldenbilen, Soner; Ceylan, Halim

    2011-01-01

    This study deals with the estimation of emissions caused by vehicular traffic based on transport demand and energy consumption. Projected transport demand is calculated with Genetic Algorithm (GA) using population, gross domestic product per capita (GDPPC) and the number of vehicles. The energy consumption is modelled with the GA using the veh-km. The model age of the vehicles and their corresponding share for each year using the reference years is obtained. The pollutant emissions are calculated with estimated transport and energy demand. All the calculations are made in line to meet the European standards. For this purpose, two cases are composed. Case 1: Emissions based on energy consumption, and Case 2: Emissions based on transport demand. The both cases are compared. Three policies are proposed to control demand and the emissions. The policies provided the best results in terms of minimum emissions and the reasonable share of highway and railway mode as 70% and 30% usage for policy I, respectively. The emission calculation procedure presented in this study would provide an alternative way to make policies when there is no adequate data on emission measurement in developing countries. - Research highlights: → Emissions caused by vehicular traffic are modelled. → The pollutant emissions are calculated with estimated transport and energy demand. → All the calculations are made in line with to meet the European standards. → The calculation procedure will provide an alternative way to make policies. → The procedure will help planners to convince politicians to impose policies.

  12. Estimation of Panel Data Regression Models with Two-Sided Censoring or Truncation

    DEFF Research Database (Denmark)

    Alan, Sule; Honore, Bo E.; Hu, Luojia

    2014-01-01

    This paper constructs estimators for panel data regression models with individual speci…fic heterogeneity and two–sided censoring and truncation. Following Powell (1986) the estimation strategy is based on moment conditions constructed from re–censored or re–truncated residuals. While these moment...

  13. Modeling vehicle operating speed on urban roads in Montreal: a panel mixed ordered probit fractional split model.

    Science.gov (United States)

    Eluru, Naveen; Chakour, Vincent; Chamberlain, Morgan; Miranda-Moreno, Luis F

    2013-10-01

    Vehicle operating speed measured on roadways is a critical component for a host of analysis in the transportation field including transportation safety, traffic flow modeling, roadway geometric design, vehicle emissions modeling, and road user route decisions. The current research effort contributes to the literature on examining vehicle speed on urban roads methodologically and substantively. In terms of methodology, we formulate a new econometric model framework for examining speed profiles. The proposed model is an ordered response formulation of a fractional split model. The ordered nature of the speed variable allows us to propose an ordered variant of the fractional split model in the literature. The proposed formulation allows us to model the proportion of vehicles traveling in each speed interval for the entire segment of roadway. We extend the model to allow the influence of exogenous variables to vary across the population. Further, we develop a panel mixed version of the fractional split model to account for the influence of site-specific unobserved effects. The paper contributes substantively by estimating the proposed model using a unique dataset from Montreal consisting of weekly speed data (collected in hourly intervals) for about 50 local roads and 70 arterial roads. We estimate separate models for local roads and arterial roads. The model estimation exercise considers a whole host of variables including geometric design attributes, roadway attributes, traffic characteristics and environmental factors. The model results highlight the role of various street characteristics including number of lanes, presence of parking, presence of sidewalks, vertical grade, and bicycle route on vehicle speed proportions. The results also highlight the presence of site-specific unobserved effects influencing the speed distribution. The parameters from the modeling exercise are validated using a hold-out sample not considered for model estimation. The results indicate

  14. A Linear Model for the Estimation of Fuel Consumption and the Impact Evaluation of Advanced Driving Assistance Systems

    Directory of Open Access Journals (Sweden)

    Gennaro Nicola Bifulco

    2015-10-01

    Full Text Available Reduction of the environmental impact of cars represents one of the biggest transport industry challenges. Beyond more efficient engines, a promising approach is to use eco-driving technologies that help drivers achieve lower fuel consumption and emission levels. In this study, a real-time microscopic fuel consumption model was developed. It was designed to be integrated into simulation platforms for the design and testing of Advanced Driving Assistance Systems (ADAS, aimed at keeping the vehicle within the environmentally friendly driving zone and hence reducing harmful exhaust gases. To allow integration in platforms employed at early stages of ADAS development and testing, the model was kept very simple and dependent on a few easily computable variables. To show the feasibility of the identification of the model (and to validate it, a large experiment involving more than 100 drivers and about 8000 km of driving was carried out using an instrumented vehicle. An instantaneous model was identified based on vehicle speed, acceleration level and gas pedal excursion, applicable in an extra-urban traffic context. Both instantaneous and aggregate validation was performed and the model was shown to estimate vehicle fuel consumption consistently with in-field instantaneous measurements. Very accurate estimations were also shown for the aggregate consumption of each driving session.

  15. Municipal solid waste conversion to transportation fuels: a life-cycle estimation of global warming potential and energy consumption

    DEFF Research Database (Denmark)

    Pressley, Phillip N.; Aziz, Tarek N.; DeCarolis, Joseph F.

    2014-01-01

    This paper utilizes life cycle assessment (LCA) methodology to evaluate the conversion of U.S. municipal solid waste (MSW) to liquid transportation fuels via gasification and Fischer-Tropsch (FT). The model estimates the cumulative energy demand and global warming potential (GWP) associated...

  16. Ethanol as a Fuel for Road Transportation

    Energy Technology Data Exchange (ETDEWEB)

    Larsen, U.; Johansen, T.; Schramm, J.

    2009-05-15

    Bioethanol as a motor fuel in the transportation sector, mainly for road transportation, has been subject to many studies and much discussion. Furthermore, the topic involves not only the application and engine technical aspects, but also the understanding of the entire life cycle of the fuel, well-to-wheels, including economical, environmental, and social aspects. It is not, however, the aim of this report to assess every single one of these aspects. The present report aims to address the technical potential and problems as well as the central issues related to the general application of bioethanol as an energy carrier in the near future. A suitable place to start studying a fuel is at the production stage, and bioethanol has been found to have a potential to mitigate greenhouse gases, depending on the production method. This and a potential for replacing fossil fuel-based oil (and being renewable) are the main reasons why ethanol is considered and implemented. Therefore, we must focus on two central questions related to ethanol implementation: how much carbon dioxide (CO2) can be mitigated and how much fossil fuel can be replaced? A number of life cycle assessments have been performed in order to provide estimates. These assessments have generally shown that bioethanol has very good potential and can mitigate CO2 emissions very effectively, but It has also been shown that the potential for both fossil fuel replacement and CO2 mitigation is totally dependent on the method used to produce the fuel. Bioethanol can be made from a wide range of biomass resources, not all equally effective at mitigating CO2 emissions and replacing fossil fuel. The Brazilian ethanol experience has in many ways shown the way for the rest of the world, not least in the production stage. Brazil was the first and biggest producer of bioethanol, but the United States, China, India, and European Union have since then increased their production dramatically. Overall, bioethanol represents the

  17. Road transport-related energy consumption: Analysis of driving factors in Tunisia

    International Nuclear Information System (INIS)

    Mraihi, Rafaa; Abdallah, Khaled ben; Abid, Mehdi

    2013-01-01

    The rapid growth of urban population and the development of road infrastructures in Tunisian cities have brought about many environmental and economic problems, including the rise scored in energy consumption and the increase in the quantity of gas emissions arising from road transport. Despite the critical nature of such problems, no policies have yet been adopted to improve energy efficiency in the transport sector. This paper aims to determine driving factors of energy consumption change for the road mode. It uses decomposition analysis to discuss the effects of economic, demographic and urban factors on the evolution of transport energy consumption. The main result highlighted in the present work is that vehicle fuel intensity, vehicle intensity, GDP per capita, urbanized kilometers and national road network are found to be the main drivers of energy consumption change in the road transport sector during 1990–2006 period. Consequently, several strategies can be elaborated to reduce road transport energy. Economic, fiscal and regulatory instruments can be applied in order to make road transport more sustainable. -- Highlights: •We are interested in determining driving factors of transport energy consumption growth in Tunisia. •We use decomposition analysis approach. •Vehicle fuel and road vehicle intensities are found to be principal factors. •Motorization and urbanization are also found to be responsible

  18. Alternative approaches for econometric analysis of panel count data using dynamic latent class models (with application to doctor visits data).

    Science.gov (United States)

    Hyppolite, Judex; Trivedi, Pravin

    2012-06-01

    Cross-sectional latent class regression models, also known as switching regressions or hidden Markov models, cannot identify transitions between classes that may occur over time. This limitation can potentially be overcome when panel data are available. For such data, we develop a sequence of models that combine features of the static cross-sectional latent class (finite mixture) models with those of hidden Markov models. We model the probability of movement between categories in terms of a Markovian structure, which links the current state with a previous state, where state may refer to the category of an individual. This article presents a suite of mixture models of varying degree of complexity and flexibility for use in a panel count data setting, beginning with a baseline model which is a two-component mixture of Poisson distribution in which latent classes are fixed and permanent. Sequentially, we extend this framework (i) to allow the mixing proportions to be smoothly varying continuous functions of time-varying covariates, (ii) to add time dependence to the benchmark model by modeling the class-indicator variable as a first-order Markov chain and (iii) to extend item (i) by making it dynamic and introducing covariate dependence in the transition probabilities. We develop and implement estimation algorithms for these models and provide an empirical illustration using 1995-1999 panel data on the number of doctor visits derived from the German Socio-Economic Panel. Copyright © 2012 John Wiley & Sons, Ltd.

  19. A multiclass vehicular dynamic traffic flow model for main roads and dedicated lanes/roads of multimodal transport network

    Energy Technology Data Exchange (ETDEWEB)

    Sossoe, K.S., E-mail: kwami.sossoe@irt-systemx.fr [TECHNOLOGICAL RESEARCH INSTITUTE SYSTEMX (France); Lebacque, J-P., E-mail: jean-patrick.lebacque@ifsttar.fr [UPE/IFSTTAR-COSYS-GRETTIA (France)

    2015-03-10

    We present in this paper a model of vehicular traffic flow for a multimodal transportation road network. We introduce the notion of class of vehicles to refer to vehicles of different transport modes. Our model describes the traffic on highways (which may contain several lanes) and network transit for pubic transportation. The model is drafted with Eulerian and Lagrangian coordinates and uses a Logit model to describe the traffic assignment of our multiclass vehicular flow description on shared roads. The paper also discusses traffic streams on dedicated lanes for specific class of vehicles with event-based traffic laws. An Euler-Lagrangian-remap scheme is introduced to numerically approximate the model’s flow equations.

  20. Urban transportation energy conservation: analytic procedures for estimating changes in travel demand and fuel consumption. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Atherton, T.J.; Suhrbier, J.H.

    1979-10-01

    This series of reports provides metropolitan planning organizations with analytical tools that can be used to evaluate the effectiveness of alternative transportation policies in achieving reductions in overall fuel consumption. To ensure a high measure of accuracy, the analysis goes beyond the first order effects, i.e., the shift from single occupant autos as the mode chosen for the work trip to more fuel efficient means of travel. Questions treated include what will happen with the autos left at home as a result of increased carpooling for work trips. Will certain policies, such as gasoline price increases, directly impact non-work tripmaking. Will a particular transportation policy affect all segments of the population, or will certain groups be impacted significantly more than others. The methodology developed links together several disaggregate travel demand models to predict auto ownership, work trip mode choice, and non-work travel demands. This report introduces the theoretical basis for the travel demand models used, describes these models and their linkages both with each other and with the various submodels, and documents the assumptions made in developing the model system and using it to forecast responses to alternative transportation policies. Emphasis is placed on the conceptual framework of the model system and specification of the individual models and submodels.

  1. End use energy consumption data base: transportation sector

    Energy Technology Data Exchange (ETDEWEB)

    Hooker, J.N.; Rose, A.B.; Greene, D.L.

    1980-02-01

    The transportation fuel and energy use estimates developed a Oak Ridge National Laboratory (ORNL) for the End Use Energy Consumption Data Base are documented. The total data base contains estimates of energy use in the United States broken down into many categories within all sectors of the economy: agriculture, mining, construction, manufacturing, commerce, the household, electric utilities, and transportation. The transportation data provided by ORNL generally cover each of the 10 years from 1967 through 1976 (occasionally 1977 and 1978), with omissions in some models. The estimtes are broken down by mode of transport, fuel, region and State, sector of the economy providing transportation, and by the use to which it is put, and, in the case of automobile and bus travel, by the income of the traveler. Fuel types include natural gas, motor and aviation gasoline, residual and diesel oil, liuqefied propane, liquefied butane, and naphtha- and kerosene-type jet engine fuels. Electricity use is also estimated. The mode, fuel, sector, and use categories themselves subsume one, two, or three levels of subcategories, resulting in a very detailed categorization and definitive accounting.

  2. Electricity consumption and economic growth in the GCC countries: Panel data analysis

    International Nuclear Information System (INIS)

    Osman, Mohamed; Gachino, Geoffrey; Hoque, Ariful

    2016-01-01

    Applying recent advances in panel data analysis, we investigate the relationship between electricity consumption and economic growth in the GCC countries using annual data from 1975 to 2012. Within a framework which takes into consideration dynamics, heterogeneity and cross-sectional dependence in the panel, we show that the results obtained from using the PMGE, demeaned PMG, AMG, MGE and DFE models indicate a long-run equilibrium relationship between electricity consumption and economic growth. In order to determine the appropriate model and decide the preferred estimator, the Hausman test was performed. The PMGE model emerged as the most efficient of the three estimators. Also, the results obtained revealed a bi-directional causality between economic growth and electricity consumption in these countries, which supports the feedback hypothesis. As a result, this implies that if these countries adopt or implement any energy or electricity conservation policies, this may have a negative impact on its economic growth. - Highlights: • The relationship between electricity consumption and GDP is explored. • Panel data econometric analysis is used to obtain the results. • Bidirectional causality between these variables is observed. • The results support the feedback hypothesis in the GCC countries.

  3. Juxtaposition of micro and macro dynamics of dividend policy on stock price volatility in financial sector of Pakistan : (comparative analysis through common, fixed, random and GMM effect)

    OpenAIRE

    Hamid, Kashif; Khurram, Muhammad Usman; Ghaffar, Wasim

    2017-01-01

    The purpose of this study is to analyze the dividend policy dynamics in context to firm specific and macroeconomic variables with stock price volatility in the financial sector of Pakistan. Panel data is used for the period 2006-2014 to identify the common, fixed, random and GMM effect. It is concluded that dividend payout ratio, market value, interest volatility and inflation volatility have positive significant correlation with price volatility. Common effect model shows that dividend payou...

  4. Sustainable passenger road transport scenarios to reduce fuel consumption, air pollutants and GHG (greenhouse gas) emissions in the Mexico City Metropolitan Area

    International Nuclear Information System (INIS)

    Chavez-Baeza, Carlos; Sheinbaum-Pardo, Claudia

    2014-01-01

    This paper presents passenger road transport scenarios that may assist the MCMA (Mexico City Metropolitan Area) in achieving lower emissions in both criteria air pollutants (CO, NO x , NMVOC (non-methane volatile organic compounds), and PM 10 ) and GHG (greenhouse gas) (CH 4 , N 2 O and CO 2 ), while also promoting better mobility and quality of life in this region. We developed a bottom-up model to estimate the historical trends of energy demand, criteria air pollutants and GHG emissions caused by passenger vehicles circulating in the Mexico City Metropolitan Area (MCMA) in order to construct a baseline scenario and two mitigation scenarios that project their impact to 2028. Mitigation scenario “eff” considers increasing fuel efficiencies and introducing new technologies for vehicle emission controls. Mitigation scenario “BRT” considers a modal shift from private car trips to a Bus Rapid Transport system. Our results show significant reductions in air pollutants and GHG emissions. Incentives and environmental regulations are needed to enable these scenarios. - Highlights: • More than 4.2 million passenger vehicles in the MCMA (Mexico City Metropolitan Area) that represent 61% of criteria pollutants and 44% of GHG (greenhouse gas) emissions. • Emissions of CO, NO x and NMVOC (non-methane volatile organic compounds) in baseline scenario decrease with respect to its 2008 value because emission standards. • Emissions of PM 10 and GHG increase in baseline scenario. • Emissions of PM 10 and GHG decrease in eff + BRT scenario from year 2020. • Additional reductions are possible with better standards for diesel vehicles and other technologies

  5. Estimating Dynamic Equilibrium Models using Macro and Financial Data

    DEFF Research Database (Denmark)

    Christensen, Bent Jesper; Posch, Olaf; van der Wel, Michel

    We show that including financial market data at daily frequency, along with macro series at standard lower frequency, facilitates statistical inference on structural parameters in dynamic equilibrium models. Our continuous-time formulation conveniently accounts for the difference in observation...... of the estimators and estimate the model using 20 years of U.S. macro and financial data....

  6. Companies’ investment determinants: comparison of different panel data estimators

    Directory of Open Access Journals (Sweden)

    Zelia Serrasqueiro

    2011-08-01

    Full Text Available In this study, Aivazian, Ge and Qiu’s (2005 analysis using static panel models is extended to using dynamic panel estimators, considering data for listed Portuguese companies. The results confirm Aivazian et al.’s (2005 conclusion that an ordinary Least Squares (OLS regression is not the best way to estimate the investment/determinant relationship. Investment decisions are probably dynamic, so the most suitable way to estimate the investment/determinant(s relationship is using dynamic panel estimators. Alternatively a fixed effect panel model can be used, consistent with a first order autocorrelation. In this way, firstly, it is possible to determine more accurately the positive impact of sales (Neo-classic theory and cash flow (Free Cash Flow theory on the investments of listed Portuguese companies. Secondly, the positive effect of growth opportunities (Agency theory is not overestimated when it seems to be the consequence of a first order autocorrelation. Using dynamic panel estimators permits correct measurement of dynamism in company investment decisions by examining the relationship between investment in the previous and the current periods.

  7. Extensions to the energy system GMM model: An overview

    International Nuclear Information System (INIS)

    Barreto, L.; Kypreos, S.

    2006-09-01

    This report describes recent extensions to the energy-systems GMM (Global Multiregional MARKAL) model undertaken by the Energy Economics Group (EEG) of the Paul Scherrer Institute (PSI) in Switzerland (hereon referred to as PSI-EEG) in the context of the SAPIENTIA project sponsored by the European Commission (DG Research) and the Swiss National Centre for Competence in Research on Climate (NCCR-Climate). GMM is a multi-regional 'bottom-up' energy-systems optimization model that endogenizes technology learning. The model has been developed and is used at PSI-EEG. The main extensions undertaken here concern the incorporation of a clusters approach to technology learning, the introduction of an improved representation of the transportation sector with emphasis on the passenger sub-sector and the implementation of marginal abatement curves for CH 4 and N 2 O, two main non-CO 2 greenhouse gases. Also, a linear representation of the atmospheric concentration of CO 2 , CH 4 and N 2 O has been included. Other changes are related to the inclusion of additional technologies for production of synthetic fuels (hydrogen and Fischer- Tropsch liquids) and the inclusion of CO 2 capture in fossil-based and biomass-based hydrogen production. Several of the developments described here follow the work of Turton and Barreto (2004, 2006) for the ERIS model at the Environmentally Compatible Energy Strategies (ECS) Program of IIASA. The remainder of this report is organized as follows. Section 2 describes the basic structure of the GMM model, the main assumptions for the scenario developed and the basic approach to endogenize technology learning in the model and examine the effects of R+D and D+D programs. Section 3 discusses the implementation of technology clusters and describes the key components chosen here. Section 4 presents the improvements to the transportation sector with emphasis on the passenger car subsector. Section 5 briefly describes the new technologies for synthetic fuel

  8. Mitigation potential of greenhouse gas emission and implications on fuel consumption due to clean energy vehicles as public passenger transport in Kathmandu Valley of Nepal: A case study of trolley buses in Ring Road

    International Nuclear Information System (INIS)

    Pradhan, Shreekar; Ale, Bhakta Bahadur; Amatya, Vishwa Bhusan

    2006-01-01

    This paper estimates the consequences in fuel consumption and greenhouse gas emission due to the possible intervention of the electric run trolley buses in the existing public transport system in a particular road up to the year 2025 in Kathmandu Valley. It projects the scenarios on the basis that the passenger travel demand is the function of population and income. Basically, it uses the Long Range Energy Alternatives Planning System software to develop Business as Usual scenario and the five alternative scenarios. The alternative scenarios are 100% replacement of vehicles catering to mass-transit in the concerned routes, 50% replacement, 25% replacement, stopping future growth of other vehicles catering to mass-transit in the concerned routes and 25% replacement in the first year, and combination scenarios. The results estimate that the passenger travel demand will increase by three folds from the year 2003 to the year 2025. It projects the three-fold increase of the existing vehicle activity by the year 2025 in Business as Usual scenario. The fuel consumption will increase by 2.4 times compared to the year 2003. It estimates the total greenhouse gas (GHG) emission as 8.5 thousands tons in year 2003 which will increase by more than 3 times in year 2025. It estimates that 174.3 thousands t CO 2 e can be avoided in combination scenario. The paper concludes that the intervention of clean energy transport in the existing public transport can have a significant positive impact on the GHG emission and current fuel consumption

  9. Fuel Consumption Management in the Transportation Sector in Iran

    DEFF Research Database (Denmark)

    Dastjerdi, Aliasghar M.; Araghi, Bahar Namaki

    2011-01-01

    Energy consumption in the transportation sector in Iran is significantly higher than global norms and standards which caused some issues including wasting national resources, deteriorating air quality, GHG emissions etc. The major purpose of this paper is to introduce practical policies, strategies...... and technologies to reduce liquid fuel consumption known as a dominant source of energy in transport sector in Iran. Since, the road subsector has the major share in consuming liquid fuel amongst others, more attention is given to the methods for reducing consumption in this subsector. The relating policies...... and actions were classified by optimization measures according to four separate categories as follows; “Optimization of Supply of Transportation Services”, “Optimization of Transport Demand”, “Optimization of Energy Consumption” and “Optimization of Car Manufacturing”....

  10. Use of GMM and SCMS for Accurate Road Centerline Extraction from the Classified Image

    Directory of Open Access Journals (Sweden)

    Zelang Miao

    2015-01-01

    Full Text Available The extraction of road centerline from the classified image is a fundamental image analysis technology. Common problems encountered in road centerline extraction include low ability for coping with the general case, production of undesired objects, and inefficiency. To tackle these limitations, this paper presents a novel accurate centerline extraction method using Gaussian mixture model (GMM and subspace constraint mean shift (SCMS. The proposed method consists of three main steps. GMM is first used to partition the classified image into several clusters. The major axis of the ellipsoid of each cluster is extracted and deemed to be taken as the initial centerline. Finally, the initial result is adjusted using SCMS to produce precise road centerline. Both simulated and real datasets are used to validate the proposed method. Preliminary results demonstrate that the proposed method provides a comparatively robust solution for accurate centerline extraction from a classified image.

  11. Estimation on oil demand and oil saving potential of China's road transport sector

    International Nuclear Information System (INIS)

    Lin, Boqiang; Xie, Chunping

    2013-01-01

    China is currently in the stage of industrialization and urbanization, which is characterized by rigid energy demand and rapid growth of energy consumption. Therefore, energy conservation will become a major strategy for China in a transition to low-carbon economy. China's transport industry is of high energy consumption. In 2010, oil consumption in transport industry takes up 38.2% of the country's total oil demand, of which 23.6% is taken up by road transport sector. As a result, oil saving in China's road transport sector is vital to the whole nation. The co-integration method is developed to find a long-run relationship between oil consumption and affecting factors such as GDP, road condition, labor productivity and oil price, to estimate oil demand and to predict future oil saving potential in China's transport sector under different oil-saving scenarios. Monte Carlo simulation is further used for risk analysis. Results show that under BAU condition, oil demand of China's road transport sector will reach 278.5 million ton of oil equivalents (MTOE) in 2020. Oil saving potential will be 86 MTOE and 131 MTOE under moderate oil-saving scenario and advanced oil-saving scenario, respectively. This paper provides a reference to establishing oil saving policy for China's road transport sector. - Highlights: • We adopt the co-integration model to estimate oil demand and oil saving potential of China's road transport sector. • Monte Carlo simulation is further used for risk analysis. • GDP, ratio of classified highway, labor productivity and oil price are main factors affecting oil consumption. • Scenario analysis approach is applied to calculate oil saving potential under different energy saving scenarios. • Future policy for oil conservation in China's road transport sector is suggested

  12. Analysis of consumer response to fuel price fluctuations applying sample selection model to GPS panel data : Dynamics in individuals' car use

    NARCIS (Netherlands)

    Yang, Dujuan; Timmermans, Harry

    2015-01-01

    The effects of fuel price increases on people's car use have been widely discussed during the last few decades in travel behavior research. It is well recognized that fuel price has significant effects on driving distance and driving efficiency. However, most of this research assumed that these

  13. Retesting the causality between energy consumption and GDP in China: Evidence from sectoral and regional analyses using dynamic panel data

    International Nuclear Information System (INIS)

    Zhang, Chuanguo; Xu, Jiao

    2012-01-01

    The increasing attention on energy policy needs has provided a renewed stimulus to research the linkages between energy consumption and economic performance in China. This paper examined the causal relationship between energy consumption and economic growth in the regional and sectoral aspects by adopting provincial panel data in China from 1995 to 2008. The results indicate that economic growth causes more energy consumption in China not only at the national level but also at the regional and sectoral levels. Then the Eastern Region and the industrial sector show results quite similar to that of the whole country, in which a bidirectional causality relationship exists between energy consumption and economic growth. The implication for energy policies in China is that the Eastern Region and the industrial sector should play a leading role in the adjustment of energy consumption patterns and the transformation of the economy structure. Energy prices have limited effects on energy consumption but do have effects on economic growth because the energy price mechanism is more government-oriented than market-oriented in China.

  14. From laboratory to road: Modeling the divergence between official and real-world fuel consumption and CO_2 emission values in the German passenger car market for the years 2001–2014

    International Nuclear Information System (INIS)

    Tietge, Uwe; Mock, Peter; Franco, Vicente; Zacharof, Nikiforos

    2017-01-01

    Official fuel consumption and carbon dioxide (CO_2) emission values of European passenger cars are widely recognized to be unrepresentative of real-world driving. The divergence between official and real-world values undermines national vehicle taxation schemes and EU-wide CO_2 standards for passenger cars, particularly since the divergence increases with new model generations. This study examines real-world fuel consumption data from more than 130,000 vehicles to investigate the development of the divergence. The analysis validates and refines a regression model developed by , which estimates real-world fuel consumption of cars based on readily available vehicle characteristics, namely official fuel consumption values, vehicle mass, and engine capacity. The regression model yielded coefficients of determination of 0.87 or higher, but was found to underestimate fuel consumption of newer vehicles and company cars. This study proposes to add vehicle build year as a regressor to account for the increasing divergence between official and real-world fuel consumption figures. - Highlights: • Real-world fuel consumption of new cars in Germany is 36% higher than official values. • The divergence between official and real-world fuel consumption has grown over time. • A simple regression accounts for ≥87% of the variance in real-world fuel consumption values. • Vehicle age must be included in the model to account for the growing divergence.

  15. Motorcycle On-Road Driving Parameters Influencing Fuel Consumption and Emissions on Congested Signalized Urban Corridor

    Directory of Open Access Journals (Sweden)

    Atthapol Seedam

    2017-01-01

    Full Text Available This study aims to find the on-road driving parameters influencing fuel consumption and emissions of motorcycle driving on a congested signalized urban corridor. A motorcycle onboard measurement system was developed to measure instantaneously and continuously record on-road driving data, including speed-time profile, emissions, and fuel consumption, by the second. The test motorcycles were driven by 30 sample motorcyclists on a signalized urban corridor in Khon Kaen City, Thailand, to collect their on-road driving behavior during the morning peak period. Cluster analysis was applied to analyze collected driving data and to categorize the drivers by level of fuel consumption and on-road driver behavior. The on-road driving parameter influencing fuel consumption and emissions was then determined. Results revealed that proportion of idle time significantly influenced fuel consumption and emissions of motorcycle driving on a congested signalized urban corridor, though aggressive driving behavior, hard acceleration and deceleration, did not have the same kind of influence.

  16. Are standards effective in improving automobile fuel economy? An international panel analysis

    International Nuclear Information System (INIS)

    Clerides, Sofronis; Zachariadis, Theodoros

    2007-01-01

    Although the adoption of fuel economy standards has induced fuel savings in new motor vehicles, there are arguments against standards and in favour of fuel tax increases because the latter may have lower welfare costs. We therefore attempted to analyze the impact of standards and fuel prices in the fuel consumption of new cars with the aid of cross-section time series analysis of data from 18 countries. To our knowledge, this study is the first one that attempts to explore econometrically this issue at an international level. We built an unbalanced panel comprising 384 observations from the US, Canada, Australia, Japan, Switzerland and 13 EU countries spanning a period between 1975 and 2003. We specified a dynamic panel model of fuel economy and estimated the model for the whole sample and also for North America and Europe separately. Based on these estimates, we derived three important policy conclusions. Firstly, it seems that if there were no FE standards or voluntary targets in force, transportation energy use would increase more rapidly. Secondly, if CO 2 targets are not to be tightened in Europe, retail fuel prices might have to double in order to attain the currently discussed target of 120 g CO 2 /km in the future. Thirdly, without higher fuel prices and/or tighter FE standards, one should not expect any marked improvements in fuel economy under 'business as usual' conditions. European policy makers might need to consider this issue carefully because some recent European studies tend to be optimistic in this respect

  17. Heterogeneity of growth in the west Balkans and emerging Europe: A dynamic panel data model approach

    Directory of Open Access Journals (Sweden)

    Josifidis Kosta

    2012-01-01

    Full Text Available This paper explores the heterogeneity of growth in the Western Balkan and Emerging European economies. For that purpose, growth determinants are estimated in the period 1997-2009 by dynamic panel data models. The chosen period provides a comparison for the model results with those estimated for the period up to 2007 in order to analyze changes caused by the global instability. According to the main findings of the paper, macroeconomic stabilization and structural reforms still matter in determining economic growth, but foreign direct investments and economic integrations seem to have the most important role in stimulating growth in the observed countries. Moreover, significant positive effects of foreign direct investments and economic integrations produce differences in growth paths between Emerging European and Western Balkan economies. Sharp decrease of foreign inflows in 2008 determined contractions of growth rates firstly in Emerging European economies with subsequent spill-over on the Western Balkan economies during 2009. Consequently, in the period of global instability, differences between two groups of economies become even more obvious.

  18. State energy data report 1994: Consumption estimates

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-10-01

    This document provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), operated by EIA. SEDS provides State energy consumption estimates to members of Congress, Federal and State agencies, and the general public, and provides the historical series needed for EIA`s energy models. Division is made for each energy type and end use sector. Nuclear electric power is included.

  19. State energy data report 1994: Consumption estimates

    International Nuclear Information System (INIS)

    1996-10-01

    This document provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), operated by EIA. SEDS provides State energy consumption estimates to members of Congress, Federal and State agencies, and the general public, and provides the historical series needed for EIA's energy models. Division is made for each energy type and end use sector. Nuclear electric power is included

  20. Modeling studies of water consumption for transportation fuel options: Hawaii, US-48

    Science.gov (United States)

    King, C. W.; Webber, M. E.

    2011-12-01

    There are now major drivers to move from petroleum transportation: moving to low-carbon transport life cycles for climate change mitigation, fuel diversity to reduce reliance on imported oil, and economic concerns regarding the relatively high price of oil ( $100/barrel) and the resulting impact on discretionary income. Unfortunately many transportation fuel alternatives also have some environmental impacts, particularly with regard to water consumption and biodiversity. In this presentation we will discuss the water and energy sustainability struggle ongoing in Hawai'i on the island of Maui with a brief history and discussion of energy and water modeling scenarios. The vast majority of surface water on Maui is diverted via man-made ditches for irrigation on sugar cane plantations. Maui currently allocates between 250 and 300 million gallons per day (Mgal/d) of irrigation water for sugarcane cultivation each day, and it is likely that the island could support a biofuel-focused sugarcane plantation by shifting production focus from raw sugar to ethanol. However, future water availability is likely to be less than existing water availability because Maui is growing, more water is being reserved for environmental purposes, and precipitation levels are on decline for the past two decades and some expect this trend to continue. While Maui residents cannot control precipitation patterns, they can control the levels of increased requirements for instream flow in Maui's streams. The Hawaii State Commission on Water Resource Management (CWRM) sets instream flow standards, and choosing not to restore instream flow could have what many locals consider negative environmental and cultural impacts that must be weighed against the effects of reducing surface water availability for agriculture. Instream flow standards that reduce legal withdrawals for streams that supply irrigation water would reduce the amount of surface water available for biofuel crop irrigation. Environmental

  1. Development of a Life Cycle Inventory of Water Consumption Associated with the Production of Transportation Fuels

    Energy Technology Data Exchange (ETDEWEB)

    Lampert, David J. [Argonne National Lab. (ANL), Argonne, IL (United States); Cai, Hao [Argonne National Lab. (ANL), Argonne, IL (United States); Wang, Zhichao [Argonne National Lab. (ANL), Argonne, IL (United States); Keisman, Jennifer [Argonne National Lab. (ANL), Argonne, IL (United States); Wu, May [Argonne National Lab. (ANL), Argonne, IL (United States); Han, Jeongwoo [Argonne National Lab. (ANL), Argonne, IL (United States); Dunn, Jennifer [Argonne National Lab. (ANL), Argonne, IL (United States); Sullivan, John L. [Argonne National Lab. (ANL), Argonne, IL (United States); Elgowainy, Amgad [Argonne National Lab. (ANL), Argonne, IL (United States); Wang, Michael [Argonne National Lab. (ANL), Argonne, IL (United States); Keisman, Jennifer [American Association for the Advancemetn of Science (AAAS), Washington, DC (United States)

    2015-10-01

    The production of all forms of energy consumes water. To meet increased energy demands, it is essential to quantify the amount of water consumed in the production of different forms of energy. By analyzing the water consumed in different technologies, it is possible to identify areas for improvement in water conservation and reduce water stress in energy-producing regions. The transportation sector is a major consumer of energy in the United States. Because of the relationships between water and energy, the sustainability of transportation is tied to management of water resources. Assessment of water consumption throughout the life cycle of a fuel is necessary to understand its water resource implications. To perform a comparative life cycle assessment of transportation fuels, it is necessary first to develop an inventory of the water consumed in each process in each production supply chain. The Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model is an analytical tool that can used to estimate the full life-cycle environmental impacts of various transportation fuel pathways from wells to wheels. GREET is currently being expanded to include water consumption as a sustainability metric. The purpose of this report was to document data sources and methodologies to estimate water consumption factors (WCF) for the various transportation fuel pathways in GREET. WCFs reflect the quantity of freshwater directly consumed per unit production for various production processes in GREET. These factors do not include consumption of precipitation or low-quality water (e.g., seawater) and reflect only water that is consumed (i.e., not returned to the source from which it was withdrawn). The data in the report can be combined with GREET to compare the life cycle water consumption for different transportation fuels.

  2. State Energy Data Report, 1991: Consumption estimates

    International Nuclear Information System (INIS)

    1993-05-01

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to the Government, policy makers, and the public; and (2) to provide the historical series necessary for EIA's energy models

  3. State energy data report 1993: Consumption estimates

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-07-01

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public; and (2) to provide the historical series necessary for EIA`s energy models.

  4. A pseudo-panel data model of household electricity demand

    Energy Technology Data Exchange (ETDEWEB)

    Bernard, Jean-Thomas; Bolduc, Denis [GREEN, Department of Economics, Universite Laval, Quebec (Canada); Yameogo, Nadege-Desiree [Analysis Group Inc., 1080 Beaver Hill, Suite 1810, Montreal, Quebec (Canada)

    2011-01-15

    We study the dynamic behaviour of household electricity consumption on the basis of four large independent surveys conducted in the province of Quebec from 1989 to 2002. The latter region displays some rather unique features such as the very extensive use of electricity for space heating in a cold climate and the wide range of energy sources used to meet space heating requirements. We adopt approach to create 25 cohorts of households that form a pseudo-panel. The cohorts have on average 131 households. The model error terms allow for group heteroskedasticity and serial correlation. Short-run and long-run own and cross-price elasticities are statistically significant. Electricity and natural gas are estimated to be substitutes while electricity and fuel oil are complements, as it may occur in the Quebec context. The estimate of the income elasticity is not significant. Comparisons with related studies are provided. (author)

  5. The Euler equation with habits and measurement errors: Estimates on Russian micro data

    Directory of Open Access Journals (Sweden)

    Khvostova Irina

    2016-01-01

    Full Text Available This paper presents estimates of the consumption Euler equation for Russia. The estimation is based on micro-level panel data and accounts for the heterogeneity of agents’ preferences and measurement errors. The presence of multiplicative habits is checked using the Lagrange multiplier (LM test in a generalized method of moments (GMM framework. We obtain estimates of the elasticity of intertemporal substitution and of the subjective discount factor, which are consistent with the theoretical model and can be used for the calibration and the Bayesian estimation of dynamic stochastic general equilibrium (DSGE models for the Russian economy. We also show that the effects of habit formation are not significant. The hypotheses of multiplicative habits (external, internal, and both external and internal are not supported by the data.

  6. Estimation of Road Friction Coefficient in Different Road Conditions Based on Vehicle Braking Dynamics

    Science.gov (United States)

    Zhao, You-Qun; Li, Hai-Qing; Lin, Fen; Wang, Jian; Ji, Xue-Wu

    2017-07-01

    The accurate estimation of road friction coefficient in the active safety control system has become increasingly prominent. Most previous studies on road friction estimation have only used vehicle longitudinal or lateral dynamics and often ignored the load transfer, which tends to cause inaccurate of the actual road friction coefficient. A novel method considering load transfer of front and rear axles is proposed to estimate road friction coefficient based on braking dynamic model of two-wheeled vehicle. Sliding mode control technique is used to build the ideal braking torque controller, which control target is to control the actual wheel slip ratio of front and rear wheels tracking the ideal wheel slip ratio. In order to eliminate the chattering problem of the sliding mode controller, integral switching surface is used to design the sliding mode surface. A second order linear extended state observer is designed to observe road friction coefficient based on wheel speed and braking torque of front and rear wheels. The proposed road friction coefficient estimation schemes are evaluated by simulation in ADAMS/Car. The results show that the estimated values can well agree with the actual values in different road conditions. The observer can estimate road friction coefficient exactly in real-time and resist external disturbance. The proposed research provides a novel method to estimate road friction coefficient with strong robustness and more accurate.

  7. Establishing bonds between vehicle certification data and real-world vehicle fuel consumption – A Vehicle Specific Power approach

    International Nuclear Information System (INIS)

    Duarte, G.O.; Gonçalves, G.A.; Baptista, P.C.; Farias, T.L.

    2015-01-01

    Highlights: • Innovative methodology to estimate VSP fuel consumption based on public available data. • Model validation with accurate fuel consumption results (absolute deviation from 4.7% to 9.2%). • Best-selling vehicles in Portugal case study was developed for different driving cycles. - Abstract: A method to perform the energy characterization of a vehicle according to the specific power required while driving was developed using public vehicle certification data. Using a portable emission measurement system, fuel consumption was quantified in a second-by-second basis under on-road conditions for 19 vehicles (spark-ignition, compression-ignition and hybrids). This data allowed building generic curves of fuel consumption as a function of the specific power, according to Vehicle Specific Power methodology. Comparing on-road measurements and the model estimates, a R 2 higher than 0.9 for conventional and hybrid vehicles was obtained regarding modal fuel consumption. Comparing the fuel consumption measured on the drive cycles performed by each vehicle and the correspondent estimates, an absolute deviation of 9.2% ± 9.2% was found for conventional vehicles and 4.7% ± 1.8% for hybrids vehicles. This methodology was validated and applied to estimate the energy impacts of the best-selling vehicles in Portugal for different driving cycles. This prompt method, that does not require vehicle monitoring, can estimate curves of fuel consumption in g/s, as a function of specific power, which allows quantifying the absolute fuel use for any driving cycle

  8. Progress in the development of the GMM-2 gravity field model for Mars

    Science.gov (United States)

    Lemoine, F. G.; Smith, D. E.; Lerch, F. J.; Zuber, M. T.; Patel, G. B.

    1994-01-01

    Last year we published the GMM-1 (Goddard Mars Model-1) gravity model for Mars. We have completely re-analyzed the Viking and Mariner 9 tracking data in the development of the new field, designated GMM-2. The model is complete to degree and order 70. Various aspects of the model are discussed.

  9. Motion estimation by data assimilation in reduced dynamic models

    International Nuclear Information System (INIS)

    Drifi, Karim

    2013-01-01

    Motion estimation is a major challenge in the field of image sequence analysis. This thesis is a study of the dynamics of geophysical flows visualized by satellite imagery. Satellite image sequences are currently underused for the task of motion estimation. A good understanding of geophysical flows allows a better analysis and forecast of phenomena in domains such as oceanography and meteorology. Data assimilation provides an excellent framework for achieving a compromise between heterogeneous data, especially numerical models and observations. Hence, in this thesis we set out to apply variational data assimilation methods to estimate motion on image sequences. As one of the major drawbacks of applying these assimilation techniques is the considerable computation time and memory required, we therefore define and use a model reduction method in order to significantly decrease the necessary computation time and the memory. We then explore the possibilities that reduced models provide for motion estimation, particularly the possibility of strictly imposing some known constraints on the computed solutions. In particular, we show how to estimate a divergence free motion with boundary conditions on a complex spatial domain [fr

  10. State energy data report 1995 - consumption estimates

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-12-01

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public, and (2) to provide the historical series necessary for EIA`s energy models.

  11. Residential water demand and water consumption: an econometric analysis on municipal panel data

    International Nuclear Information System (INIS)

    Musolesi, Antonio; Nosvelli, Mario

    2005-01-01

    This paper focuses on residential water demand estimation, a rather neglected issue in the Italian environmental economics literature as compared to other European countries and the USA. This may depend on the difficulties in gathering proper data and, most of all, panel data. In some cases statistical information are not suitably collected, while in other cases legal privacy ties put some obstacles to data set transfer. Our panel data set refers to 102 municipalities in Lombardy (Italy) for the period 1998-2002. When estimating the effect of water price, we control for other relevant variables such as: income, households demographical variables - (age structure, number of component for each family) number of firms in tertiary sector, water system length. In the considered period, the data show both an increase in population (1,5 %) and in the number of water consumers (7%) associated, on aggregate, with a slight reduction in water consumption (-1,1 %). Water demand models are estimated both in a static and in a dynamic framework. In the former, the emphasis is set on the sources of endogeneity in the average price by estimating a system of simultaneous equations and relevant variables for assessing consumer behaviour - such as socio demographic ones - are incorporated in the model. In the latter, econometric methods especially designed for endogeneity in panel data models (Arellano e Bond, 1991), are employed in order to estimate the long run elasticity of water demand with respect to average price. We find evidence both that consumers significantly respond to average price only in the long run with an elasticity of about - 0,3-0,4 and that income and demographic variables are crucial in explaining consumers' behaviour. Furthermore, water consumption presents a strong auto-regressive component, showing the emergence of inertia and path dependency in consumption habits. Such results suggest important implications for water policy planning. On one side demographic

  12. Renewable Energy Innovations in Europe: A Dynamic Panel Data Approach

    OpenAIRE

    Nadia Ayari; Szabolcs Blazsek; Pedro Mendi

    2009-01-01

    Abstract We investigate the determinants of renewable energy R&D intensity and the impact of renewable energy innovations on firm performance, using several dynamic panel data models. We estimate these models using a large data set of European firms from 19 different countries, with some patenting activity in areas related with renewable energies during the 1987-2007 period. Our results confirm our priors on the determinants of the rapid development of renewable energy R&D intensit...

  13. A dynamic analysis of motorcycle ownership and usage: a panel data modeling approach.

    Science.gov (United States)

    Wen, Chieh-Hua; Chiou, Yu-Chiun; Huang, Wan-Ling

    2012-11-01

    This study aims to develop motorcycle ownership and usage models with consideration of the state dependence and heterogeneity effects based on a large-scale questionnaire panel survey on vehicle owners. To account for the independence among alternatives and heterogeneity among individuals, the modeling structure of motorcycle ownership adopts disaggregate choice models considering the multinomial, nested, and mixed logit formulations. Three types of panel data regression models--ordinary, fixed, and random effects--are developed and compared for motorcycle usage. The estimation results show that motorcycle ownership in the previous year does exercise a significantly positive effect on the number of motorcycles owned by households in the current year, suggesting that the state dependence effect does exist in motorcycle ownership decisions. In addition, the fixed effects model is the preferred specification for modeling motorcycle usage, indicating strong evidence for existence of heterogeneity. Among various management strategies evaluated under different scenarios, increasing gas prices and parking fees will lead to larger reductions in total kilometers traveled. Copyright © 2011 Elsevier Ltd. All rights reserved.

  14. Capital mobility in the panel GMM framework: Evidence from EU members

    Directory of Open Access Journals (Sweden)

    Natalya Ketenci

    2015-06-01

    Full Text Available This paper examines the level of international capital mobility in European Union members under the Feldstein and Horioka (1980 hypothesis. The validity of the Feldstein-Horioka puzzle is investigated taking into account the impact of the global financial crisis employing the generalized method of moments (GMM estimation technique developed by Hansen (1982. In general, the world countries with time have a tendency to a higher level of capital market openness. According to Feldstein and Horioka (1980, a higher saving-investment correlation is related to lower capital mobility. In this paper, panel data for 27 European countries were used for the period of 1995-2013 on the quarterly basis. The empirical results provide evidence of high capital mobility in EU members, obtaining a low value of a saving retention coefficient. The results of estimations indicate significant dependence of investments on its past values. It is found that the global financial crisis had a deeply negative impact on investment rates in 2007 and for the general period of 2007-2013. The empirical results indicate that the level of capital mobility increased during the global financial crisis, 2007-2013. Thus decrease in investments and increase in the international capital mobility level of European countries during the period of the global financial crisis of 2007-2013, taking into account high risk in the international market, indicates a reallocation of capital from international to regional markets.

  15. Trends of energy efficiency in Finnish road freight transport 1995-2009 and forecast to 2016

    Energy Technology Data Exchange (ETDEWEB)

    Liimatainen, Heikki; Poellaenen, Markus [Department of Business Information Management and Logistics, Tampere University of Technology, P.O. Box 541, 33101 Tampere (Finland)

    2010-12-15

    A framework for modeling and analyzing the energy efficiency of road freight transport is presented in this paper. This framework is tested by using the data from the Finnish Goods Transport by Road statistics. The data was enhanced by calculating the fuel consumption for each trip in the data. To calculate this, weight-fuel consumption functions were estimated for each Euro-class vehicles and road type. This is a new method for analyzing the energy efficiency of road freight transport and it could be applied also in other countries gathering freight transport data with continuous company surveys. The analysis show that the energy efficiency of road freight transport in Finland improved during 1995-2002, but has declined since. The major drivers in the development have been the changes in the level of empty running and vehicle fuel efficiency. Extrapolating current statistical trends of factors that influence the energy efficiency show that the target set by the Finnish government for improving energy efficiency by 9% until 2016 will not be achieved. However, the target is possible to be achieved by a combination of small changes to some determinants. (author)

  16. Dynamic linkages among transport energy consumption, income and CO2 emission in Malaysia

    International Nuclear Information System (INIS)

    Azlina, A.A.; Law, Siong Hook; Nik Mustapha, Nik Hashim

    2014-01-01

    This paper examines the dynamic relationship between income, energy use and carbon dioxide (CO 2 ) emissions in Malaysia using time-series data during 1975 to 2011. This study also attempts to validate the environmental Kuznet curve (EKC) hypothesis. Applying a multivariate model of income, energy consumption in the transportation sector, carbon emissions, structural change in the economy and renewable energy use, the empirical evidence confirmed that there is a long-run relationship between the variables as shown by the result of co-integration analysis. The results indicate that the inverted U-shape EKC hypothesis does not fully agree with the theory. The coefficient of squared GDP is not statistically different from zero. The time duration and the annual data used for the present study do not seem to strongly validate the existence of EKC hypothesis in the case of Malaysia. Causality test shows that the relationship between GDP and CO 2 is unidirectional. The Granger causality test results reveal that emissions Granger-cause income, energy consumption and renewable energy use. Moreover, we find that income Granger-causes energy consumption and renewable energy use, and both structural change and renewable energy use Granger-cause energy consumption in road transportation. - Highlights: • We examine the dynamic relationship among energy consumption in transportation sector, income and CO 2 and also attempts to validate the environmental Kuznet curve (EKC) hypothesis. • We used a multivariate approach based on VECM. • The inverted U-shape EKC hypothesis is not valid in the case of Malaysia. • Uni-directional causality exists from emission to income, energy consumption and renewable energy use. • Income Granger-causes energy consumption and renewable energy use, and both structural change and renewable energy use Granger-cause energy consumption in road transportation

  17. Advanced fuel cycle cost estimation model and its cost estimation results for three nuclear fuel cycles using a dynamic model in Korea

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sungki, E-mail: sgkim1@kaeri.re.kr [Korea Atomic Energy Research Institute, 1045 Daedeokdaero, Yuseong-gu, Daejeon 305-353 (Korea, Republic of); Ko, Wonil [Korea Atomic Energy Research Institute, 1045 Daedeokdaero, Yuseong-gu, Daejeon 305-353 (Korea, Republic of); Youn, Saerom; Gao, Ruxing [University of Science and Technology, 217 Gajungro, Yuseong-gu, Daejeon 305-350 (Korea, Republic of); Bang, Sungsig, E-mail: ssbang@kaist.ac.kr [Korea Advanced Institute of Science and Technology, Department of Business and Technology Management, 291 Deahak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of)

    2015-11-15

    Highlights: • The nuclear fuel cycle cost using a new cost estimation model was analyzed. • The material flows of three nuclear fuel cycle options were calculated. • The generation cost of once-through was estimated to be 66.88 mills/kW h. • The generation cost of pyro-SFR recycling was estimated to be 78.06 mills/kW h. • The reactor cost was identified as the main cost driver of pyro-SFR recycling. - Abstract: The present study analyzes advanced nuclear fuel cycle cost estimation models such as the different discount rate model and its cost estimation results. To do so, an analysis of the nuclear fuel cycle cost of three options (direct disposal (once through), PWR–MOX (Mixed OXide fuel), and Pyro-SFR (Sodium-cooled Fast Reactor)) from the viewpoint of economic sense, focusing on the cost estimation model, was conducted using a dynamic model. From an analysis of the fuel cycle cost estimation results, it was found that some cost gap exists between the traditional same discount rate model and the advanced different discount rate model. However, this gap does not change the priority of the nuclear fuel cycle option from the viewpoint of economics. In addition, the fuel cycle costs of OT (Once-Through) and Pyro-SFR recycling based on the most likely value using a probabilistic cost estimation except for reactor costs were calculated to be 8.75 mills/kW h and 8.30 mills/kW h, respectively. Namely, the Pyro-SFR recycling option was more economical than the direct disposal option. However, if the reactor cost is considered, the economic sense in the generation cost between the two options (direct disposal vs. Pyro-SFR recycling) can be changed because of the high reactor cost of an SFR.

  18. Spent fuel transport in Romania by road: An approach considering safety, risk and radiological consequences

    International Nuclear Information System (INIS)

    Vieru, G.

    2001-01-01

    The transport of high-level radioactive wastes, involving Type B packages, is a part of the safety of the Romanian waste management programme and the overall aim of this activity is to promote the safe transport of radioactive materials in Romania. The paper presents a safety case analysis of the transport of a single spent fuel CANDU bundle, using a Romanian built Type B package, from the CANDU type nuclear power plant Cernavoda to the INR Pitesti, in order to be examined within INR's hot-cells facilities. The safety assessment includes the following main aspects: (1) evaluation and analysis of available data on road traffic accidents; (2) estimation of the expected frequency for severe road accident scenarios resulting in potential radionuclide release; and (3) evaluation of the expected radiological consequences and accident risks of transport operations. (author)

  19. THE DYNAMIC STOCHASTIC LINEAR PROGRAMMING MODEL FOR MANAGEMENT IN THE CONSUMPTION OF FUEL IN FLEX

    Directory of Open Access Journals (Sweden)

    Paulo Cesar Chagas Rodrigues

    2012-07-01

    Full Text Available From the amount invested in fuel prices, the rate of road that owners of vehicles powered by combustion need to run within the city and on the roads in the region, began a study in order to allow a better definition as to the cost of supply of vehicle with Ethanol or gasoline. And to analyze the equation that the government, through Petrobras announces in the media, because it is mentioned that to obtain the lowest cost when the supply should divide the value of a liter of Ethanol Gasoline for that case stay above 0.70 is the ideal fuel to petrol and vice versa.

  20. Models for predicting fuel consumption in sagebrush-dominated ecosystems

    Science.gov (United States)

    Clinton S. Wright

    2013-01-01

    Fuel consumption predictions are necessary to accurately estimate or model fire effects, including pollutant emissions during wildland fires. Fuel and environmental measurements on a series of operational prescribed fires were used to develop empirical models for predicting fuel consumption in big sagebrush (Artemisia tridentate Nutt.) ecosystems....

  1. PLATINUM, FUEL CELLS, AND FUTURE ROAD TRANSPORT

    Science.gov (United States)

    A vehicle powered by a fuel cell will emit virtually no air polution and, depending on fuel choice, can substantially improve fuel economy above that of current technology. Those attributes are complementary to issues of increasing national importance including the effects of tra...

  2. Estimating Reduced Consumption for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Chelmis, Charalampos [Univ. of Southern California, Los Angeles, CA (United States); Aman, Saima [Univ. of Southern California, Los Angeles, CA (United States); Saeed, Muhammad Rizwan [Univ. of Southern California, Los Angeles, CA (United States); Frincu, Marc [Univ. of Southern California, Los Angeles, CA (United States); Prasanna, Viktor K. [Univ. of Southern California, Los Angeles, CA (United States)

    2015-01-30

    Growing demand is straining our existing electricity generation facilities and requires active participation of the utility and the consumers to achieve energy sustainability. One of the most effective and widely used ways to achieve this goal in the smart grid is demand response (DR), whereby consumers reduce their electricity consumption in response to a request sent from the utility whenever it anticipates a peak in demand. To successfully plan and implement demand response, the utility requires reliable estimate of reduced consumption during DR. This also helps in optimal selection of consumers and curtailment strategies during DR. While much work has been done on predicting normal consumption, reduced consumption prediction is an open problem that is under-studied. In this paper, we introduce and formalize the problem of reduced consumption prediction, and discuss the challenges associated with it. We also describe computational methods that use historical DR data as well as pre-DR conditions to make such predictions. Our experiments are conducted in the real-world setting of a university campus microgrid, and our preliminary results set the foundation for more detailed modeling.

  3. Alternative Fuels Data Center: South Dakota Transportation Data for

    Science.gov (United States)

    Grants Ethanol and Methanol Tax Liquefied Natural Gas (LNG) Tax Biofuel Franchising Contract Regulations Natural Gas Transportation Fuel Consumption Source: State Energy Data System based on beta data converted

  4. Transportation and socioeconomic impacts of bypasses on communities : an integrated synthesis of panel data, multilevel, and spatial econometric models with case studies.

    Science.gov (United States)

    2011-09-21

    Title: Transportation and Socioeconomic Impacts of Bypasses on Communities: An Integrated Synthesis of Panel Data, Multilevel, and Spatial Econometric Models with Case Studies. The title used at the start of this project was Transportation and Soc...

  5. Estimation of Energy Consumption and Greenhouse Gas Emissions of Transportation in Beef Cattle Production

    Directory of Open Access Journals (Sweden)

    Narayanan Kannan

    2016-11-01

    Full Text Available Accounting for transportation is an important part of the life cycle analysis (LCA of beef cattle production because it is associated with energy consumption and greenhouse gas emissions. This paper describes the development and application of a model that estimates energy consumption and greenhouse gas emissions of transport in beef cattle production. The animal transport model is based on the weight and number of animals in each weight category, type of trailer, vehicle, and fuel used. The energy consumption and greenhouse gas emission estimates of animal feed transportation are based on the weight of a truckload and the number of truckloads of feed transported. Our results indicate that a truckload is travelling approximately 326 km in connection with beef cattle production in the study region. The fuel consumption amounts to 24 L of fossil fuel per 1000 kg of boneless beef. The corresponding greenhouse gas emission is 83 kg. It appears from our results that the majority of energy consumption and greenhouse gas emissions are associated with sending the finished cattle to slaughterhouses and bringing feeder cattle to feedlots. Our results point out appreciable reductions in energy consumption and greenhouse gas emissions by changing from conventional fuel to bio-fuel.

  6. Induced motor vehicle travel from improved fuel efficiency and road expansion

    Energy Technology Data Exchange (ETDEWEB)

    Su Qing, E-mail: suq1@nku.edu [Department of Marketing, Economics and Sports Business, Northern Kentucky University, AST Center, Office 338, Nunn Drive, Highland Heights, KY 41099 (United States)

    2011-11-15

    This paper investigates the impact of improved fuel efficiency and road network expansion on motor vehicle travel using a system dynamic panel data estimator and panel data at the state level for the 2001-2008 period. Our model accounts for endogenous changes in fuel efficiency, congestion, fuel cost per mile, and vehicle stock. Our regression results suggest that the short run rebound effect is 0.0276 while the long run rebound effect is 0.11. The short run effect of road capacity per capita is 0.066 while the long run effect is 0.26. - Highlights: > We estimate two effects: the rebound effect and induced travel effect at the state level. > System dynamic panel data approach is used to address endogeneity issue. > In the period of 2001-2008, the rebound effect is 0.0276 in the short run and 0.11 in the long run. > Increase in road capacity induces motor vehicle travel. > Induced travel effect is 0. 0.066 in the short run and 0.26 in the long run.

  7. Induced motor vehicle travel from improved fuel efficiency and road expansion

    International Nuclear Information System (INIS)

    Su Qing

    2011-01-01

    This paper investigates the impact of improved fuel efficiency and road network expansion on motor vehicle travel using a system dynamic panel data estimator and panel data at the state level for the 2001-2008 period. Our model accounts for endogenous changes in fuel efficiency, congestion, fuel cost per mile, and vehicle stock. Our regression results suggest that the short run rebound effect is 0.0276 while the long run rebound effect is 0.11. The short run effect of road capacity per capita is 0.066 while the long run effect is 0.26. - Highlights: → We estimate two effects: the rebound effect and induced travel effect at the state level. → System dynamic panel data approach is used to address endogeneity issue. → In the period of 2001-2008, the rebound effect is 0.0276 in the short run and 0.11 in the long run. → Increase in road capacity induces motor vehicle travel. → Induced travel effect is 0. 0.066 in the short run and 0.26 in the long run.

  8. Identification issues in forward-looking models estimated by GMM, with an application to the Phillips curve

    NARCIS (Netherlands)

    Mavroeidis, S.

    2005-01-01

    Limited-information methods are commonly used to estimate forwardlooking models with rational expectations, such as the "New Keynesian Phillips Curve" of Galí and Gertler (1999). In this paper, we address issues of identification that have been overlooked due to the incompleteness of the

  9. Predicting vehicle fuel consumption patterns using floating vehicle data.

    Science.gov (United States)

    Du, Yiman; Wu, Jianping; Yang, Senyan; Zhou, Liutong

    2017-09-01

    The status of energy consumption and air pollution in China is serious. It is important to analyze and predict the different fuel consumption of various types of vehicles under different influence factors. In order to fully describe the relationship between fuel consumption and the impact factors, massive amounts of floating vehicle data were used. The fuel consumption pattern and congestion pattern based on large samples of historical floating vehicle data were explored, drivers' information and vehicles' parameters from different group classification were probed, and the average velocity and average fuel consumption in the temporal dimension and spatial dimension were analyzed respectively. The fuel consumption forecasting model was established by using a Back Propagation Neural Network. Part of the sample set was used to train the forecasting model and the remaining part of the sample set was used as input to the forecasting model. Copyright © 2017. Published by Elsevier B.V.

  10. Comparing fixed effects and covariance structure estimators for panel data

    DEFF Research Database (Denmark)

    Ejrnæs, Mette; Holm, Anders

    2006-01-01

    In this article, the authors compare the traditional econometric fixed effect estimator with the maximum likelihood estimator implied by covariance structure models for panel data. Their findings are that the maximum like lipoid estimator is remarkably robust to certain types of misspecifications...

  11. Food transport refrigeration - Approaches to reduce energy consumption and environmental impacts of road transport

    International Nuclear Information System (INIS)

    Tassou, S.A.; De-Lille, G.; Ge, Y.T.

    2009-01-01

    Food transport refrigeration is a critical link in the food chain not only in terms of maintaining the temperature integrity of the transported products but also its impact on energy consumption and CO 2 emissions. This paper provides a review of (a) current approaches in road food transport refrigeration, (b) estimates of their environmental impacts, and (c) research on the development and application of alternative technologies to vapour compression refrigeration systems that have the potential to reduce the overall energy consumption and environmental impacts. The review and analysis indicate that greenhouse gas emissions from conventional diesel engine driven vapour compression refrigeration systems commonly employed in food transport refrigeration can be as high as 40% of the greenhouse gas emissions from the vehicle's engine. For articulated vehicles over 33 ton, which are responsible for over 80% of refrigerated food transportation in the UK, the reject heat available form the engine is sufficient to drive sorption refrigeration systems and satisfy most of the refrigeration requirements of the vehicle. Other promising technologies that can lead to a reduction in CO 2 emissions are air cycle refrigeration and hybrid systems in which conventional refrigeration technologies are integrated with thermal energy storage. For these systems, however, to effectively compete with diesel driven vapour compression systems, further research and development work is needed to improve their efficiency and reduce their weight

  12. Modeling of terminal-area airplane fuel consumption

    Science.gov (United States)

    2009-08-01

    Accurate modeling of airplane fuel consumption is necessary for air transportation policy-makers to properly : adjudicate trades between competing environmental and economic demands. Existing public models used for : computing terminal-area airplane ...

  13. Does Climate Change Mitigation Activity Affect Crude Oil Prices? Evidence from Dynamic Panel Model

    Directory of Open Access Journals (Sweden)

    Jude C. Dike

    2014-01-01

    Full Text Available This paper empirically investigates how climate change mitigation affects crude oil prices while using carbon intensity as the indicator for climate change mitigation. The relationship between crude oil prices and carbon intensity is estimated using an Arellano and Bond GMM dynamic panel model. This study undertakes a regional-level analysis because of the geographical similarities among the countries in a region. Regions considered for the study are Africa, Asia and Oceania, Central and South America, the EU, the Middle East, and North America. Results show that there is a positive relationship between crude oil prices and carbon intensity, and a 1% change in carbon intensity is expected to cause about 1.6% change in crude oil prices in the short run and 8.4% change in crude oil prices in the long run while the speed of adjustment is 19%.

  14. State energy data report 1992: Consumption estimates

    Energy Technology Data Exchange (ETDEWEB)

    1994-05-01

    This is a report of energy consumption by state for the years 1960 to 1992. The report contains summaries of energy consumption for the US and by state, consumption by source, comparisons to other energy use reports, consumption by energy use sector, and describes the estimation methodologies used in the preparation of the report. Some years are not listed specifically although they are included in the summary of data.

  15. Panel discussion: In vivo pet modeling and data analysis

    International Nuclear Information System (INIS)

    Koeppe, R.A.

    1991-01-01

    Following the first afternoon session on in vivo PET modeling and data analysis, a panel assembled to discuss in greater detail some of the issues pertinent to the kinetic analysis of PET data. The discussion was opened with a comment on some of the diofficulties of PET imaging in the study of neurotransmitter and receptor systems, including resolution limitations, image distortions, and levels of nonspecific binding. Dr. Hutchins reiterated that the imaging distortions predicted by his simulation studies include both open-quotes scaleclose quotes and open-quotes shape open-quotes distortions. Then the panel discussed the issue of registration of functional (PET) and anatomic (MRI or CT) images. The use of an anatomic image as a road map or guide to where one is in the physiologic PET image is a very important part of performing PET studies. It is at least as important to align a dynamic PET sequence internally, from frame to frame, as it is to align the PET study to an anatomic study. If a dynamic imaging procedure will take 30-90 min or more, a method is needed to assure that the patient has not moved substantially during the procedure or that the movement can be accounted for. Several possibilities were discussed. The next topic considered the issue of model complexity versus model reduction. If a model is too complex, it cannot provide accurate estimates of the model parameters due to the lack of identifiability of individual parameters. Modeling approaches such as simplifying the model to two parameters and changing the experimental protocol to provide more information so model simplification is not necessary were discussed on the basis of the tradeoff between procedural complexity and quality of information

  16. Risk management model in road transport systems

    Science.gov (United States)

    Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.

    2016-08-01

    The article presents the results of a study of road safety indicators that influence the development and operation of the transport system. Road safety is considered as a continuous process of risk management. Authors constructed a model that relates the social risks of a major road safety indicator - the level of motorization. The model gives a fairly accurate assessment of the level of social risk for any given level of motorization. Authors calculated the dependence of the level of socio-economic costs of accidents and injured people in them. The applicability of the concept of socio-economic damage is caused by the presence of a linear relationship between the natural and economic indicators damage from accidents. The optimization of social risk is reduced to finding the extremum of the objective function that characterizes the economic effect of the implementation of measures to improve safety. The calculations make it possible to maximize the net present value, depending on the costs of improving road safety, taking into account socio-economic damage caused by accidents. The proposed econometric models make it possible to quantify the efficiency of the transportation system, allow to simulate the change in road safety indicators.

  17. Trip Energy Estimation Methodology and Model Based on Real-World Driving Data for Green Routing Applications: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Holden, Jacob [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Van Til, Harrison J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wood, Eric W [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Gonder, Jeffrey D [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhu, Lei [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-02-09

    A data-informed model to predict energy use for a proposed vehicle trip has been developed in this paper. The methodology leverages nearly 1 million miles of real-world driving data to generate the estimation model. Driving is categorized at the sub-trip level by average speed, road gradient, and road network geometry, then aggregated by category. An average energy consumption rate is determined for each category, creating an energy rates look-up table. Proposed vehicle trips are then categorized in the same manner, and estimated energy rates are appended from the look-up table. The methodology is robust and applicable to almost any type of driving data. The model has been trained on vehicle global positioning system data from the Transportation Secure Data Center at the National Renewable Energy Laboratory and validated against on-road fuel consumption data from testing in Phoenix, Arizona. The estimation model has demonstrated an error range of 8.6% to 13.8%. The model results can be used to inform control strategies in routing tools, such as change in departure time, alternate routing, and alternate destinations to reduce energy consumption. This work provides a highly extensible framework that allows the model to be tuned to a specific driver or vehicle type.

  18. Fuel consumption in the transport of technical broadleaf roundwood in lowland areas

    Directory of Open Access Journals (Sweden)

    Danilović Milorad

    2015-01-01

    Full Text Available This paper presents the results of an analysis of fuel consumption in the transport of technical roundwood of soft broadleaves from the felling site to a roadside landing using forwarders and tractor assemblies. The research was performed in various operating conditions in the area of FE "Banat" Pančevo. On the basis of the results of the analysis of variance, the data recorded in a variety of conditions were grouped. In addition, the dependence of fuel consumption on the average volume of tour was estimated. The results of the conducted analysis indicate that operating conditions significantly affect fuel consumption of the investigated vehicles. The elements of statistical analysis of the dependence of fuel consumption on the volume of load indicate that an increase in load causes increased fuel consumption per unit of production. Having in mind the results of the analysis of variance, unique norms of fuel consumption were adopted for practical purposes. The highest average consumption (1.21 L/m3 was achieved by a tractor assembly (Same Laser 130 tractor and Imako TP12 trailer with a Loglift 61F hydraulic crane, while significantly lower consumption was achieved by a John Deere 1210E forwarder (1.06 L/m3. In favourable operating conditions, consumption of the forwarder was about 0.9 L/m3.

  19. Future of energy efficiency and carbon dioxide emissions of Finnish road freight transport

    Energy Technology Data Exchange (ETDEWEB)

    Liimatainen, H.

    2013-05-15

    The targets to reduce the carbon dioxide emissions to mitigate climate change are as much applicable to the road freight transport sector as they are to all other sectors of society. The aim of this research is to support the initiatives of the Finnish government for improving the energy efficiency and reducing the CO{sub 2} emissions of road freight transport. This is done by forecasting the future development and giving the policy makers guidance on effective measures for promoting road freight energy efficiency and CO{sub 2} reduction. In the study a new method was introduced for connecting the fuel consumption data and goods transport data gathered from the official Finnish road statistics. This method enabled a detailed analysis of the interrelations between the economy, road freight transport, energy consumption and emissions. This analysis was conducted for the years 1995-2010 and the results were used as background information in the Delphi panel of experts. The experts estimated the development of the Finnish road freight sector to the year 2030. Furthermore, a web-based survey was conducted among Finnish road freight hauliers and shippers in order to explore the attitudes and measures related to the energy efficiency. Expert panel workshops were also organised to identify obstacles for the development of the energy efficiency of road freight transport as well as a wide selection of measures to overcome them. The results indicate that the economic development of different branches has a great effect on the energy efficiency and carbon dioxide emissions of road freight transport. Reaching the carbon emission target for the year 2030 is possible in the light of the scenarios which were formed based on expert forecasts. However, the target can be achieved with very different development paths, e.g. the structure of the national economy and the volume of transport seem to vary widely in the different scenarios. In the proposed recommendations on the measures

  20. Data structure for estimating emissions from non-road sources

    Energy Technology Data Exchange (ETDEWEB)

    Sorenson, S C; Kalivoda, M; Vacarro, R; Trozzi, C; Samaras, Z; Lewis, C A

    1997-03-01

    The work described in the following is a portion of the MEET project (Methodologies for Estimation Air Pollutant Emissions from Transport). The overall goal of the MEET project is to consolidate and present methodologies which can be used to estimate air pollutant emissions from various types of traffic sources. One of the goals of MEET is to provide methodologies to be used in the COMMUTE project also funded by DG VII. COMMUTE is developing computer software which can be used to provide emissions inventories on the European scale. Although COMMUTE is viewed as a prime user of the information generated in MEET, the MEET results are intended to be used in a broader area, and on both smaller and larger spatial scales. The methodologies and data presented will be useful for planners on a more local scale than a national or continental basis. While most attention in previous years has been concentrated on emissions from road transport, it has become increasingly apparent in later years that the so-called off road transportation contributes significantly to the emission of air pollutants. The three most common off-road traffic modes are Air Traffic, Rail Traffic, and Ship or Marine traffic. In the following, the basic structure of the methods for estimating the emissions from these sectors will be given and of the input and output data associated with these calculations. The structures will of necessity be different for the different types of traffic. The data structures in the following reflect these variations and uncertainties. In some instances alternative approaches to emissions estimation will be suggested. The user must evaluate the amount and reliability of available data for the application at hand, and select the method which would be expected to give the highest accuracy. In any event, a large amount of uncertainty is inherent in the estimation of emissions from the non-road traffic sources, particularly those involving rail and maritime transport. (EG)

  1. Applicability of models to estimate traffic noise for urban roads.

    Science.gov (United States)

    Melo, Ricardo A; Pimentel, Roberto L; Lacerda, Diego M; Silva, Wekisley M

    2015-01-01

    Traffic noise is a highly relevant environmental impact in cities. Models to estimate traffic noise, in turn, can be useful tools to guide mitigation measures. In this paper, the applicability of models to estimate noise levels produced by a continuous flow of vehicles on urban roads is investigated. The aim is to identify which models are more appropriate to estimate traffic noise in urban areas since several models available were conceived to estimate noise from highway traffic. First, measurements of traffic noise, vehicle count and speed were carried out in five arterial urban roads of a brazilian city. Together with geometric measurements of width of lanes and distance from noise meter to lanes, these data were input in several models to estimate traffic noise. The predicted noise levels were then compared to the respective measured counterparts for each road investigated. In addition, a chart showing mean differences in noise between estimations and measurements is presented, to evaluate the overall performance of the models. Measured Leq values varied from 69 to 79 dB(A) for traffic flows varying from 1618 to 5220 vehicles/h. Mean noise level differences between estimations and measurements for all urban roads investigated ranged from -3.5 to 5.5 dB(A). According to the results, deficiencies of some models are discussed while other models are identified as applicable to noise estimations on urban roads in a condition of continuous flow. Key issues to apply such models to urban roads are highlighted.

  2. An improved gravity model for Mars: Goddard Mars Model-1 (GMM-1)

    Science.gov (United States)

    Smith, D. E.; Lerch, F. J.; Nerem, R. S.; Zuber, M. T.; Patel, G. B.; Fricke, S. K.; Lemoine, F. G.

    1993-01-01

    Doppler tracking data of three orbiting spacecraft have been reanalyzed to develop a new gravitational field model for the planet Mars, GMM-1 (Goddard Mars Model-1). This model employs nearly all available data, consisting of approximately 1100 days of S-bank tracking data collected by NASA's Deep Space Network from the Mariner 9, and Viking 1 and Viking 2 spacecraft, in seven different orbits, between 1971 and 1979. GMM-1 is complete to spherical harmonic degree and order 50, which corresponds to a half-wavelength spatial resolution of 200-300 km where the data permit. GMM-1 represents satellite orbits with considerably better accuracy than previous Mars gravity models and shows greater resolution of identifiable geological structures. The notable improvement in GMM-1 over previous models is a consequence of several factors: improved computational capabilities, the use of optimum weighting and least-squares collocation solution techniques which stabilized the behavior of the solution at high degree and order, and the use of longer satellite arcs than employed in previous solutions that were made possible by improved force and measurement models. The inclusion of X-band tracking data from the 379-km altitude, near-polar orbiting Mars Observer spacecraft should provide a significant improvement over GMM-1, particularly at high latitudes where current data poorly resolves the gravitational signature of the planet.

  3. Regional analysis of renewable transportation fuels - production and consumption

    Science.gov (United States)

    Liu, Xiaoshuai

    The transportation sector contributes more than a quarter of total U.S. greenhouse gas emissions. Replacing fossil fuels with renewable fuels can be a key solution to mitigate GHG emissions from the transportation sector. Particularly, we have focused on land-based production of renewable fuels from landfills and brownfield in the southeastern region of the United States. These so call marginal lands require no direct land-use change to avoid environmental impact and, furthermore, have rendered opportunities for carbon trading and low-carbon intensity business. The resources potential and production capacity were derived using federal and state energy databases with the aid of GIS techniques. To maximize fuels production and land-use efficiency, a scheme of co-location renewable transportation fuels for production on landfills was conducted as a case study. Results of economic modeling analysis indicate that solar panel installed on landfill sites could generate a positive return within the project duration, but the biofuel production within the landfill facility is relatively uncertain, requiring proper sizing of the onsite processing facility, economic scale of production and available tax credits. From the consumers' perspective, a life-cycle cost analysis has been conducted to determine the economic and environmental implications of different transportation choices by consumers. Without tax credits, only the hybrid electric vehicles have lifetime total costs equivalent to a conventional vehicles differing by about 1 to 7%. With tax credits, electric and hybrid electric vehicles could be affordable and attain similar lifetime total costs as compared to conventional vehicles. The dissertation research has provided policy-makers and consumers a pathway of prioritizing investment on sustainable transportation systems with a balance of environmental benefits and economic feasibility.

  4. The rebound effect on road freight transport: Empirical evidence from Portugal

    International Nuclear Information System (INIS)

    Matos, Fernando J.F.; Silva, Francisco J.F.

    2011-01-01

    Because a large proportion of total operating costs for transportation companies goes towards energy, a reduction in energy operating costs, brought about by an increase in fleet fuel efficiency, or an increase in operational efficiency, results in a change in the relative cost of road freight transportation. This fact could result in an increase in the demand for such services. If this is true, the result would be an increase in total fuel consumption. Consequently, that part of the energy savings obtained through the increased energy efficiency would be lost. The existence of a 'Rebound Effect' is especially important in the road freight transportation sector and is crucial for the definition of a national energy policy. In this study, data from the road freight transportation sector in Portugal for the years of 1987 through 2006 was analyzed. It was determined that an increase in energy efficiency did not cause a backfire, but did cause a total direct rebound effect of 24.1%. In addition, fleet operators were more inclined to adopt operational efficiencies than technological fuel efficiencies as a means of increasing the total operational efficiency. - Research highlights: → We estimate a direct rebound effect for road freight transportation in Portugal. → The functional form chosen was a log-log model and the estimation method used was the two stage least squares model. → Increasing energy efficiency by 1% results in a reduction of 0.759% in energy consumption (a direct rebound effect of about 24.1%). → Estimates of reduced fuel consumption without considering the direct rebound effect may be overestimated by about 0.87 million liters of diesel per year for each percentage point increase in energy efficiency.

  5. Assessment of Clmate Change Mitigation Strategies for the Road Transport Sector of India

    Science.gov (United States)

    Singh, N.; Mishra, T.; Banerjee, R.

    2017-12-01

    India is one of the fastest growing major economies of the world. It imports three quarters of its oil demand, making transport sector major contributor of greenhouse gas (GHG) emissions. 40% of oil consumption in India comes from transport sector and over 90% of energy demand is from road transport sector. This has led to serious increase in CO2 emission and concentration of air pollutants in India. According to Intergovernmental Panel on Climate Change (IPCC), transport can play a crucial role for mitigation of global greenhouse gas emissions. Therefore, assessment of appropriate mitigation policies is required for emission reduction and cost benefit potential. The present study aims to estimate CO2, SO2, PM and NOx emissions from the road transport sector for the base year (2014) and target year (2030) by applying bottom up emission inventory model. Effectiveness of different mitigation strategies like inclusion of natural gas as alternate fuel, penetration of electric vehicle as alternate vehicle, improvement of fuel efficiency and increase share of public transport is evaluated for the target year. Emission reduction achieved from each mitigation strategies in the target year (2030) is compared with the business as usual scenario for the same year. To obtain cost benefit analysis, marginal abatement cost for each mitigation strategy is estimated. The study evaluates mitigation strategies not only on the basis of emission reduction potential but also on their cost saving potential.

  6. GHG emission estimates for road transport in national GHG inventories

    NARCIS (Netherlands)

    Pulles, M.P.J.; Yang, H.

    2011-01-01

    The annual reporting procedures of the United Nations Framework Convention on Climate Change (UNFCCC) have now produced greenhouse gas (GHG) emission inventories from 40 so-called Annex I countries for 18 years. This article analyses a subset of these data: emissions from road transport. The article

  7. Energy consumption and income. A semiparametric panel data analysis

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen-Van, Phu [BETA, CNRS and Universite de Strasbourg, 61 avenue de la Foret Noire, F-67085 Strasbourg (France)

    2010-05-15

    This paper proposes a semiparametric analysis for the study of the relationship between energy consumption per capita and income per capita for an international panel dataset. It shows little evidence for the existence of an environmental Kuznets curve for energy consumption. Energy consumption increases with income for a majority of countries and then stabilizes for very high income countries. Neither changes in energy structure nor macroeconomic cycle/technological change have significant effect on energy consumption. (author)

  8. Fuel consumption modeling in support of ATM environmental decision-making

    Science.gov (United States)

    2009-07-01

    The FAA has recently updated the airport terminal : area fuel consumption methods used in its environmental models. : These methods are based on fitting manufacturers fuel : consumption data to empirical equations. The new fuel : consumption metho...

  9. Trends of energy efficiency in Finnish road freight transport 1995-2009 and forecast to 2016

    International Nuclear Information System (INIS)

    Liimatainen, Heikki; Poellaenen, Markus

    2010-01-01

    A framework for modeling and analyzing the energy efficiency of road freight transport is presented in this paper. This framework is tested by using the data from the Finnish Goods Transport by Road statistics. The data was enhanced by calculating the fuel consumption for each trip in the data. To calculate this, weight-fuel consumption functions were estimated for each Euro-class vehicles and road type. This is a new method for analyzing the energy efficiency of road freight transport and it could be applied also in other countries gathering freight transport data with continuous company surveys. The analysis show that the energy efficiency of road freight transport in Finland improved during 1995-2002, but has declined since. The major drivers in the development have been the changes in the level of empty running and vehicle fuel efficiency. Extrapolating current statistical trends of factors that influence the energy efficiency show that the target set by the Finnish government for improving energy efficiency by 9% until 2016 will not be achieved. However, the target is possible to be achieved by a combination of small changes to some determinants. - Research highlights: →A new method for analyzing energy efficiency by adding fuel data to national freight statistics. →Energy efficiency improved in Finland from 1995 to 2002 but has declined since. →Energy efficiency in Finland is still on a good level internationally. →Target of the Finnish energy efficiency agreement was quantified for the first time in this study. →The target will not be achieved if the past trends continue.

  10. Reduction of CO2 emissions from road transport in cities impact of dynamic route guidance system on greenhouse gas emission

    CERN Document Server

    Markiewicz, Michal

    2017-01-01

    Michal Markiewicz presents the outcomes of his research regarding the influence of dynamic route guidance system on overall emission of carbon dioxide from road transport in rural areas. Sustainable transportation in smart cities is a big challenge of our time, but before electric vehicles replace vehicles that burn fossil fuels we have to think about traffic optimization methods that reduce the amount of greenhouse gas emissions. Contents Comparison of Travel Time Measurements Using Floating Car Data and Intelligent Infrastructure Integration of Cellular Automata Traffic Simulator with CO2 Emission Model Impact of Dynamic Route Guidance System on CO2 Emission Naxos Vehicular Traffic Simulator Target Groups Lecturers and students of computer science, transportation and logistics Traffic engineers The Author Dr. Michal Markiewicz defended his PhD thesis in computer science at the University of Bremen,TZI Technologie-Zentrum Informatik und Informationstechnik, Germany. Currently, he is working on commercializat...

  11. Panel data models with spatial correlation: Estimation theory and an empirical investigation of the United States wholesale gasoline industry

    Science.gov (United States)

    Kapoor, Mudit

    The first part of my dissertation considers the estimation of a panel data model with error components that are both spatially and time-wise correlated. The dissertation combines widely used model for spatial correlation (Cliff and Ord (1973, 1981)) with the classical error component panel data model. I introduce generalizations of the generalized moments (GM) procedure suggested in Kelejian and Prucha (1999) for estimating the spatial autoregressive parameter in case of a single cross section. I then use those estimators to define feasible generalized least squares (GLS) procedures for the regression parameters. I give formal large sample results concerning the consistency of the proposed GM procedures, as well as the consistency and asymptotic normality of the proposed feasible GLS procedures. The new estimators remain computationally feasible even in large samples. The second part of my dissertation employs a Cliff-Ord-type model to empirically estimate the nature and extent of price competition in the US wholesale gasoline industry. I use data on average weekly wholesale gasoline price for 289 terminals (distribution facilities) in the US. Data on demand factors, cost factors and market structure that affect price are also used. I consider two time periods, a high demand period (August 1999) and a low demand period (January 2000). I find a high level of competition in prices between neighboring terminals. In particular, price in one terminal is significantly and positively correlated to the price of its neighboring terminal. Moreover, I find this to be much higher during the low demand period, as compared to the high demand period. In contrast to previous work, I include for each terminal the characteristics of the marginal customer by controlling for demand factors in the neighboring location. I find these demand factors to be important during period of high demand and insignificant during the low demand period. Furthermore, I have also considered spatial

  12. Modeling the Dynamics and Spillovers of the Health Labor Market: Evidence from China’s Provincial Panel Data

    Directory of Open Access Journals (Sweden)

    Bin Zhu

    2018-01-01

    Full Text Available Health workforce misdistribution is a major challenge faced by almost all countries. A more profound understanding of the dynamics of the health labor market provides evidence for policy makers to balance health workforce distribution with solid evidence. However, one major deficit of existing theoretical and empirical studies is that they often ignore the intra-regional spillovers of the health labor market. This study builds a theoretical “supply–demand–spillover” model that considers both intra-regional supply and demand-side factors, and inter-regional spillovers, hence providing a theoretical reference point for further in-depth studies. Using spatial econometric panel models, the effect of all determinants and spillovers were empirically measured based on a Chinese panel data set, shedding light on health workforce policies in China.

  13. Fuel Estimation Using Dynamic Response

    National Research Council Canada - National Science Library

    Hines, Michael S

    2007-01-01

    ...?s simulated satellite (SimSAT) to known control inputs. With an iterative process, the moment of inertia of SimSAT about the yaw axis was estimated by matching a model of SimSAT to the measured angular rates...

  14. Data mining, mining data : energy consumption modelling

    Energy Technology Data Exchange (ETDEWEB)

    Dessureault, S. [Arizona Univ., Tucson, AZ (United States)

    2007-09-15

    Most modern mining operations are accumulating large amounts of data on production and business processes. Data, however, provides value only if it can be translated into information that appropriate users can utilize. This paper emphasized that a new technological focus should emerge, notably how to concentrate data into information; analyze information sufficiently to become knowledge; and, act on that knowledge. Researchers at the Mining Information Systems and Operations Management (MISOM) laboratory at the University of Arizona have created a method to transform data into action. The data-to-action approach was exercised in the development of an energy consumption model (ECM), in partnership with a major US-based copper mining company, 2 software companies, and the MISOM laboratory. The approach begins by integrating several key data sources using data warehousing techniques, and increasing the existing level of integration and data cleaning. An online analytical processing (OLAP) cube was also created to investigate the data and identify a subset of several million records. Data mining algorithms were applied using the information that was isolated by the OLAP cube. The data mining results showed that traditional cost drivers of energy consumption are poor predictors. A comparison was made between traditional methods of predicting energy consumption and the prediction formed using data mining. Traditionally, in the mines for which data were available, monthly averages of tons and distance are used to predict diesel fuel consumption. However, this article showed that new information technology can be used to incorporate many more variables into the budgeting process, resulting in more accurate predictions. The ECM helped mine planners improve the prediction of energy use through more data integration, measure development, and workflow analysis. 5 refs., 11 figs.

  15. CO2 emissions, energy consumption and economic growth in China: A panel data analysis

    International Nuclear Information System (INIS)

    Wang, S.S.; Zhou, D.Q.; Zhou, P.; Wang, Q.W.

    2011-01-01

    This paper examines the causal relationships between carbon dioxide emissions, energy consumption and real economic output using panel cointegration and panel vector error correction modeling techniques based on the panel data for 28 provinces in China over the period 1995-2007. Our empirical results show that CO 2 emissions, energy consumption and economic growth have appeared to be cointegrated. Moreover, there exists bidirectional causality between CO 2 emissions and energy consumption, and also between energy consumption and economic growth. It has also been found that energy consumption and economic growth are the long-run causes for CO 2 emissions and CO 2 emissions and economic growth are the long-run causes for energy consumption. The results indicate that China's CO 2 emissions will not decrease in a long period of time and reducing CO 2 emissions may handicap China's economic growth to some degree. Some policy implications of the empirical results have finally been proposed. - Highlights: → We conduct a panel data analysis of the energy-CO 2 -economy nexus in China. → CO 2 emissions, energy use and economic growth appear to be cointegrated. → There exists bidirectional causality between energy consumption and economic growth. → Energy consumption and economic growth are the long-run causes for CO 2 emissions.

  16. Estimating fuel consumption during prescribed fires in Arkansas

    Science.gov (United States)

    Virginia L. McDaniel; James M. Guldin; Roger W. Perry

    2012-01-01

    While prescribed fire is essential to maintaining numerous plant communities, fine particles produced in smoke can impair human health and reduce visibility in scenic areas. The Arkansas Smoke Management Program was established to mitigate the impacts of smoke from prescribed fires. This program uses fuel loading and consumption estimates from standard fire-behavior...

  17. Vehicle technologies, fuel-economy policies, and fuel-consumption rates of Chinese vehicles

    International Nuclear Information System (INIS)

    Huo Hong; He Kebin; Wang, Michael; Yao Zhiliang

    2012-01-01

    One of the principal ways to reduce transport-related energy use is to reduce fuel-consumption rates of motor vehicles (usually measured in liters of fuel per 100 km). Since 2004, China has implemented policies to improve vehicle technologies and lower the fuel-consumption rates of individual vehicles. Policy evaluation requires accurate and adequate information on vehicle fuel-consumption rates. However, such information, especially for Chinese vehicles under real-world operating conditions, is rarely available from official sources in China. For each vehicle type we first review the vehicle technologies and fuel-economy policies currently in place in China and their impacts. We then derive real-world (or on-road) fuel-consumption rates on the basis of information collected from various sources. We estimate that the real-world fuel-consumption rates of vehicles in China sold in 2009 are 9 L/100 km for light-duty passenger vehicles, 11.4 L/100 km for light-duty trucks, 22 L/100 km for inter-city transport buses, 40 L/100 km for urban transit buses, and 24.9 L/100 km for heavy-duty trucks. These results aid in understanding the levels of fuel consumption of existing Chinese vehicle fleets and the effectiveness of policies in reducing on-road fuel consumption, which can help in designing and evaluating future vehicle energy-efficiency policies. - Highlights: ► Vehicle fuel-consumption rate (VFCR) data are rarely available in China. ► We review the fuel-economy policies currently in place in China and their impacts. ► We derive real-world VFCRs on the basis of information collected from various sources. ► Results aid in understanding the fuel consumption levels of Chinese vehicle fleets. ► Results help in designing and evaluating future vehicle energy-efficiency policies.

  18. Change Point Estimation in Panel Data without Boundary Issue

    Czech Academy of Sciences Publication Activity Database

    Peštová, Barbora; Pešta, M.

    2017-01-01

    Roč. 5, č. 1 (2017), č. článku 7. E-ISSN 2227-9091 Institutional support: RVO:67985807 Keywords : change point * estimation * consistency * panel data * short panels * boundary issue * structural change * bootstrap * non-life insurance * change in claim amounts Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics

  19. A smoothed maximum score estimator for the binary choice panel data model with individual fixed effects and applications to labour force participation

    NARCIS (Netherlands)

    Charlier, G.W.P.

    1994-01-01

    In a binary choice panel data model with individual effects and two time periods, Manski proposed the maximum score estimator, based on a discontinuous objective function, and proved its consistency under weak distributional assumptions. However, the rate of convergence of this estimator is low (N)

  20. RISK AND FIRM VALUE IN EUROPEAN COMPANIES: A DYNAMIC PANEL DATA APPROACH

    Directory of Open Access Journals (Sweden)

    Claudiu Botoc

    2015-07-01

    Full Text Available Recent uncertainties in financial markets and several company bankruptcies reinforce the relationship between risk and return as a cornerstone in corporate finance. Enterprise risk management theories offer unambiguous predictions about the relation between firm value and risk. The main aim of the paper is to provide new empirical evidence on the risk as a driver for company value creation process for European developed countries over the period 2001-2011. Using dynamic panel data model with two-step GMM-SYS method and enterprise multiple as a new approach to measure for firm value the results suggest that firm value is negatively related with risk, which is consistent with Bowman’s risk and return paradox. The negative relation between firm value and risk is robust through alternative measures, but it does not hold for companies from civil law countries. Additional control variables included in the model are significant and suggest that both growth and capital structure are negatively related with firm value.

  1. Limit Theory for Panel Data Models with Cross Sectional Dependence and Sequential Exogeneity.

    Science.gov (United States)

    Kuersteiner, Guido M; Prucha, Ingmar R

    2013-06-01

    The paper derives a general Central Limit Theorem (CLT) and asymptotic distributions for sample moments related to panel data models with large n . The results allow for the data to be cross sectionally dependent, while at the same time allowing the regressors to be only sequentially rather than strictly exogenous. The setup is sufficiently general to accommodate situations where cross sectional dependence stems from spatial interactions and/or from the presence of common factors. The latter leads to the need for random norming. The limit theorem for sample moments is derived by showing that the moment conditions can be recast such that a martingale difference array central limit theorem can be applied. We prove such a central limit theorem by first extending results for stable convergence in Hall and Hedye (1980) to non-nested martingale arrays relevant for our applications. We illustrate our result by establishing a generalized estimation theory for GMM estimators of a fixed effect panel model without imposing i.i.d. or strict exogeneity conditions. We also discuss a class of Maximum Likelihood (ML) estimators that can be analyzed using our CLT.

  2. Panel estimation for urbanization, energy consumption and CO2 emissions: A regional analysis in China

    International Nuclear Information System (INIS)

    Zhang Chuanguo; Lin Yan

    2012-01-01

    As urbanization accelerates, urban areas play a leading role in energy consumption and CO 2 emissions in China. The existing research is extensively concerned with the relationships between urbanization, energy consumption and CO 2 emissions in recent years, but little attention has been paid to the regional differences. This paper is an analysis of the impact of urbanization on energy consumption and CO 2 emissions at the national and regional levels using the STIRPAT model and provincial panel data from 1995 to 2010 in China. The results showed that urbanization increases energy consumption and CO 2 emissions in China. The effects of urbanization on energy consumption vary across regions and decline continuously from the western region to the central and eastern regions. The impact of urbanization on CO 2 emissions in the central region is greater than that in the eastern region. The impact of urbanization on energy consumption is greater than the impact on CO 2 emissions in the eastern region. And some evidences support the argument of compact city theory. These results not only contribute to advancing the existing literature, but also merit particular attention from policy makers and urban planners in China. - Highlights: ► We analyze the impact of urbanization on energy use and CO 2 emissions in China. ► Urbanization increases energy consumption and CO 2 emissions in China. ► The effects of urbanization on energy use and CO 2 emissions vary across regions.

  3. The Transportation Leapfrog: Using Smart Phones to Collect Driving Data and Model Fuel Economy in India

    Energy Technology Data Exchange (ETDEWEB)

    Gopal, Anand [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Schewel, Laura [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Saxena, Samveg [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Phadke, Amol [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division

    2013-05-01

    Car ownership in India is expected to skyrocket in the coming decades, strongly driven by rising incomes. This phenomenon provides unprecedented opportunities for automakers and equally unprecedented social and environmental challenges. Policymakers, urban planners and civil society see this car boom leading to an explosion in problems related to congestion, infrastructure, air pollution, safety, higher oil imports and climate change. For all these stakeholders to take effective action, good data on how people use their cars, their demand for mobility and their behavior in mobility is essential. Unfortunately, there is very little data on the Indian transport sector as a whole and virtually none on real-world vehicle performance and use. The rapid development of high quality mobile telecommunications infrastructure provides India with the opportunity to leapfrog the West in cheaply collecting vast amounts of useful data from transportation. In this paper, we describe a pilot project in which we use commercial smart phone apps to collect per second car driving data from the city of Pune, instantly upload it through 3G and prepare it for analysis using advanced noise filtering algorithms for less than $1 per day per car. We then use our data in an Autonomie simulation to show that India’s currently planned fuel economy test procedures will result in over-estimates of fuel economy of approximately 35% for a typical Indian car when it is operated in real world conditions. Supporting better driving cycle development is just one of many applications for smart phone derived data in Indian transportation.

  4. Psychological determinants of fuel consumption of purchased new cars

    OpenAIRE

    Peters, A; Gutscher, H; Scholz, R W

    2011-01-01

    With regard to reducing fuel consumption and CO2 emissions of road transport consumers' adoption of fuel-efficient vehicles is crucial. However, facing the ongoing trend of increasing car size and power, fuel consumption is apparently of lesser importance to most buyers. For the design of effective measures to change behavior and promote fuel-efficient cars, psychological factors should be considered. Drawing from psychological research on environmental behavior, we propose a model which inte...

  5. Modeling an impact of road geometric design on vehicle energy consumption

    Science.gov (United States)

    Luin, Blaž; Petelin, Stojan; Al-Mansour, Fouad

    2017-11-01

    Some roads connect traffic origins and destinations directly, some use winding, indirect routes. Indirect connections result in longer distances driven and increased fuel consumption. A similar effect is observed on congested roads and mountain roads with many changes in altitude. Therefore a framework to assess road networks based on energy consumption is proposed. It has been shown that road geometry has significant impact on overall traffic energy consumption and emissions. The methodology presented in the paper analyzes impact of traffic volume, shares of vehicle classes, road network configuration on the energy used by the vehicles. It can be used to optimize energy consumption with efficient traffic management and to choose optimum new road in the design phase. This is especially important as the energy consumed by the vehicles shortly after construction supersedes the energy spent for the road construction.

  6. Energy consumption and economic growth relationship: Evidence from panel data for low and middle income countries

    International Nuclear Information System (INIS)

    Ozturk, Ilhan; Aslan, Alper; Kalyoncu, Huseyin

    2010-01-01

    This paper uses the panel data of energy consumption (EC) and economic growth (GDP) for 51 countries from 1971 to 2005. These countries are divided into three groups: low income group, lower middle income group and upper middle income group countries. Firstly, a relationship between energy consumption and economic growth is investigated by employing panel cointegration method. Secondly, panel causality test is applied to investigate the way of causality between the energy consumption and economic growth. Finally, we test whether there is a strong or weak relationship between these variables by using method. The empirical results of this study are as follows: i) Energy consumption and GDP are cointegrated for all three income group countries. ii) The panel causality test results reveal that there is long-run Granger causality running from GDP to EC for low income countries and there is bidirectional causality between EC and GDP for middle income countries. iii) The estimated cointegration factor, β, is not close to 1. In other words, no strong relation is found between energy consumption and economic growth for all income groups considered in this study. The findings of this study have important policy implications and it shows that this issue still deserves further attention in future research.

  7. Global emission projections for the transportation sector using dynamic technology modeling

    Science.gov (United States)

    Yan, F.; Winijkul, E.; Streets, D. G.; Lu, Z.; Bond, T. C.; Zhang, Y.

    2014-06-01

    In this study, global emissions of gases and particles from the transportation sector are projected from the year 2010 to 2050. The Speciated Pollutant Emission Wizard (SPEW)-Trend model, a dynamic model that links the emitter population to its emission characteristics, is used to project emissions from on-road vehicles and non-road engines. Unlike previous models of global emission estimates, SPEW-Trend incorporates considerable detail on the technology stock and builds explicit relationships between socioeconomic drivers and technological changes, such that the vehicle fleet and the vehicle technology shares change dynamically in response to economic development. Emissions from shipping, aviation, and rail are estimated based on other studies so that the final results encompass the entire transportation sector. The emission projections are driven by four commonly-used IPCC (Intergovernmental Panel on Climate Change) scenarios (A1B, A2, B1, and B2). With global fossil-fuel use (oil and coal) in the transportation sector in the range of 128-171 EJ across the four scenarios, global emissions are projected to be 101-138 Tg of carbon monoxide (CO), 44-54 Tg of nitrogen oxides (NOx), 14-18 Tg of non-methane total hydrocarbons (THC), and 3.6-4.4 Tg of particulate matter (PM) in the year 2030. At the global level, a common feature of the emission scenarios is a projected decline in emissions during the first one or two decades (2010-2030), because the effects of stringent emission standards offset the growth in fuel use. Emissions increase slightly in some scenarios after 2030, because of the fast growth of on-road vehicles with lax or no emission standards in Africa and increasing emissions from non-road gasoline engines and shipping. On-road vehicles and non-road engines contribute the most to global CO and THC emissions, while on-road vehicles and shipping contribute the most to NOx and PM emissions. At the regional level, Latin America and East Asia are the two

  8. Road transport of LWR spent fuel in the Federal Republic of Germany

    International Nuclear Information System (INIS)

    Bach, R.

    1987-01-01

    Since 1967, when fuel from LWRs was first transported by road from the Kahl reactor in the Federal Republic of Germany to the Eurochemic reprocessing plant in Belgium, a total of more than 400 road transports have been performed without any adverse effect on the environment. In the beginning, road transport was the dominant mode. However, in recent years large capacity rail flasks with a weight ranging from 80 to 110 tonnes have been put into service in order to cope with the increasing demand of transport services and to replace existing smaller flasks designed primarily for road transport. Therefore, the number of spent fuel transports by road has declined. However, road transport of heavy flasks from reactor sites without a direct rail link to a nearby rail terminal has become an important task and a number of special problems have had to be solved. The following items are discussed, with special emphasis placed on heavy load transports by road from the reactor to a nearby rail terminal: design of road transport equipment to meet the requirements of the national traffic law; application of technical and administrative procedures to meet the IAEA Regulations; transport restrictions due to overload/oversize; transfer of the flask from the reactor to the transport vehicle; handling of the flask at the rail terminal; turn-around inspection and periodic maintenance of equipment to ensure safe performance of transport; and physical protection during transport and handling at rail terminals. (author). 4 figs

  9. An integrated data model to estimate spatiotemporal occupancy, abundance, and colonization dynamics

    Science.gov (United States)

    Williams, Perry J.; Hooten, Mevin B.; Womble, Jamie N.; Esslinger, George G.; Bower, Michael R.; Hefley, Trevor J.

    2017-01-01

    Ecological invasions and colonizations occur dynamically through space and time. Estimating the distribution and abundance of colonizing species is critical for efficient management or conservation. We describe a statistical framework for simultaneously estimating spatiotemporal occupancy and abundance dynamics of a colonizing species. Our method accounts for several issues that are common when modeling spatiotemporal ecological data including multiple levels of detection probability, multiple data sources, and computational limitations that occur when making fine-scale inference over a large spatiotemporal domain. We apply the model to estimate the colonization dynamics of sea otters (Enhydra lutris) in Glacier Bay, in southeastern Alaska.

  10. Determinants of fuel consumption in mining trucks

    International Nuclear Information System (INIS)

    Dindarloo, Saeid R.; Siami-Irdemoosa, Elnaz

    2016-01-01

    Analysis of fuel consumption in a large surface mine, during more than 5000 cycles of material transportation, revealed considerable variability in the data. Truck fuel estimation based on the mining truck manufacturers' manuals/estimates is not capable of capturing this variability in the fuel consumption data. Partial least squares regression and autoregressive integrated moving average methods were employed to examine the effect of cyclic activities on fuel consumption, and to recommend relevant remedies for consumption reduction. Proper modifications of the operation can result in improved cycle times. Consequently, minimizing some cyclic activities would enhance energy efficiency. The truck “empty idle time” was a major contributor to unnecessary fuel consumption. Since the truck queues at shovels are a major component of the “empty idle time”, decisions should be reviewed to reduce the truck queues at loading points. Improved dispatching strategies, optimal muck pile shape and size distribution, and improved shovel/loader operator skills are effective preventive measures to minimize truck flow bottlenecks at loading points, and thus to improve energy efficiency at mines. - Highlights: • A large fleet of mining trucks consumes considerable amounts of energy. • Current energy models do not consider the effect of site-specific mining conditions. • A new methodology based on material handling cyclic activities is proposed. • Fuel consumption rates in different truck operating modes are determined. • The new model is compared with the truck manufacturer's energy consumption guideline.

  11. Health and safety of competing fuel options for fuel cells in the road transport sector

    Energy Technology Data Exchange (ETDEWEB)

    Green, E.; Short, S.; Stutt, E.; Wickramatillake, H.; Harrison, P.

    2000-07-01

    This report presents a critical analysis of the health and safety issues surrounding competing transport fuel options, including those for possible future fuel-cell powered vehicles. The fuels considered in this report are gasoline (unleaded and reformulated), diesel, hydrogen (H{sub 2}), methanol, natural gas and liquefied petroleum gas (LPG). The analysis presented here is based on available information in peer-reviewed, published papers and other sources such as government department or research laboratory reports and websites. An overall evaluation of the fuels in terms of their toxicity and health effects, environmental fate, and fire and explosion safety aspects is presented. The report is based on current knowledge and makes no assumptions as to how fuels may change in the future if they are to be used in fuel-cell vehicles. The report identifies the hazards of the fuels but does not estimate the risks likely to be associated with their eventual use in fuel-cell vehicles. The focus is on the fuels themselves and not their exhaust or reaction products. sNo assessment has been made of the environmental effects data for the fuels. Broad environmental considerations such as ozone forming potential and also global warming are not considered. Basic information on environmental fate is included to provide an understanding of migratory pathways, environmental compartmentalisation and potential routes of human exposure. Other factors such as economics, government incentives or disincentives and public attitudes may have a bearing on which of the fuels are considered most appropriate for future fuel-cell vehicles; these factors are not considered in any detail in this report. (Author)

  12. ROAD AND ROADSIDE FEATURE EXTRACTION USING IMAGERY AND LIDAR DATA FOR TRANSPORTATION OPERATION

    Directory of Open Access Journals (Sweden)

    S. Ural

    2015-03-01

    Full Text Available Transportation agencies require up-to-date, reliable, and feasibly acquired information on road geometry and features within proximity to the roads as input for evaluating and prioritizing new or improvement road projects. The information needed for a robust evaluation of road projects includes road centerline, width, and extent together with the average grade, cross-sections, and obstructions near the travelled way. Remote sensing is equipped with a large collection of data and well-established tools for acquiring the information and extracting aforementioned various road features at various levels and scopes. Even with many remote sensing data and methods available for road extraction, transportation operation requires more than the centerlines. Acquiring information that is spatially coherent at the operational level for the entire road system is challenging and needs multiple data sources to be integrated. In the presented study, we established a framework that used data from multiple sources, including one-foot resolution color infrared orthophotos, airborne LiDAR point clouds, and existing spatially non-accurate ancillary road networks. We were able to extract 90.25% of a total of 23.6 miles of road networks together with estimated road width, average grade along the road, and cross sections at specified intervals. Also, we have extracted buildings and vegetation within a predetermined proximity to the extracted road extent. 90.6% of 107 existing buildings were correctly identified with 31% false detection rate.

  13. A new look at the FDI–income–energy–environment nexus: Dynamic panel data analysis of ASEAN

    International Nuclear Information System (INIS)

    Baek, Jungho

    2016-01-01

    The main focus of this paper is to estimate the effects of foreign direct investment (FDI) inflows, income and energy consumption on CO_2 emissions using panel data of five ASEAN countries over 1981–2010. The results based on the pooled mean group (PMG) estimator of dynamic panels show that FDI tends to increase CO_2 emissions, supporting evidence of the pollution haven hypothesis. We also find that income and energy consumption have a detrimental impact on reducing CO_2 emissions. - Highlights: • This study examines the FDI–income–energy–environment nexus. • The pooled mean group (PMG) estimator is applied to panel data of 5 ASEAN countries. • FDI deteriorates the environment, supporting the pollution haven hypothesis. • Growth and energy consumption have a detrimental effect on the environment.

  14. Traffic flow dynamics. Data, models and simulation

    Energy Technology Data Exchange (ETDEWEB)

    Treiber, Martin [Technische Univ. Dresden (Germany). Inst. fuer Wirtschaft und Verkehr; Kesting, Arne [TomTom Development Germany GmbH, Berlin (Germany)

    2013-07-01

    First comprehensive textbook of this fascinating interdisciplinary topic which explains advances in a way that it is easily accessible to engineering, physics and math students. Presents practical applications of traffic theory such as driving behavior, stability analysis, stop-and-go waves, and travel time estimation. Presents the topic in a novel and systematic way by addressing both microscopic and macroscopic models with a focus on traffic instabilities. Revised and extended edition of the German textbook ''Verkehrsdynamik und -simulation''. This textbook provides a comprehensive and instructive coverage of vehicular traffic flow dynamics and modeling. It makes this fascinating interdisciplinary topic, which to date was only documented in parts by specialized monographs, accessible to a broad readership. Numerous figures and problems with solutions help the reader to quickly understand and practice the presented concepts. This book is targeted at students of physics and traffic engineering and, more generally, also at students and professionals in computer science, mathematics, and interdisciplinary topics. It also offers material for project work in programming and simulation at college and university level. The main part, after presenting different categories of traffic data, is devoted to a mathematical description of the dynamics of traffic flow, covering macroscopic models which describe traffic in terms of density, as well as microscopic many-particle models in which each particle corresponds to a vehicle and its driver. Focus chapters on traffic instabilities and model calibration/validation present these topics in a novel and systematic way. Finally, the theoretical framework is shown at work in selected applications such as traffic-state and travel-time estimation, intelligent transportation systems, traffic operations management, and a detailed physics-based model for fuel consumption and emissions.

  15. Mechanistic Fluid Transport Model to Estimate Gastrointestinal Fluid Volume and Its Dynamic Change Over Time.

    Science.gov (United States)

    Yu, Alex; Jackson, Trachette; Tsume, Yasuhiro; Koenigsknecht, Mark; Wysocki, Jeffrey; Marciani, Luca; Amidon, Gordon L; Frances, Ann; Baker, Jason R; Hasler, William; Wen, Bo; Pai, Amit; Sun, Duxin

    2017-11-01

    Gastrointestinal (GI) fluid volume and its dynamic change are integral to study drug disintegration, dissolution, transit, and absorption. However, key questions regarding the local volume and its absorption, secretion, and transit remain unanswered. The dynamic fluid compartment absorption and transit (DFCAT) model is proposed to estimate in vivo GI volume and GI fluid transport based on magnetic resonance imaging (MRI) quantified fluid volume. The model was validated using GI local concentration of phenol red in human GI tract, which was directly measured by human GI intubation study after oral dosing of non-absorbable phenol red. The measured local GI concentration of phenol red ranged from 0.05 to 168 μg/mL (stomach), to 563 μg/mL (duodenum), to 202 μg/mL (proximal jejunum), and to 478 μg/mL (distal jejunum). The DFCAT model characterized observed MRI fluid volume and its dynamic changes from 275 to 46.5 mL in stomach (from 0 to 30 min) with mucus layer volume of 40 mL. The volumes of the 30 small intestine compartments were characterized by a max of 14.98 mL to a min of 0.26 mL (0-120 min) and a mucus layer volume of 5 mL per compartment. Regional fluid volumes over 0 to 120 min ranged from 5.6 to 20.38 mL in the proximal small intestine, 36.4 to 44.08 mL in distal small intestine, and from 42 to 64.46 mL in total small intestine. The DFCAT model can be applied to predict drug dissolution and absorption in the human GI tract with future improvements.

  16. Estimation of economic costs of particulate air pollution from road transport in China

    Science.gov (United States)

    Guo, X. R.; Cheng, S. Y.; Chen, D. S.; Zhou, Y.; Wang, H. Y.

    2010-09-01

    Valuation of health effects of air pollution is becoming a critical component of the performance of cost-benefit analysis of pollution control measures, which provides a basis for setting priorities for action. Beijing has focused on control of transport emission as vehicular emissions have recently become an important source of air pollution, particularly during Olympic games and Post-games. In this paper, we conducted an estimation of health effects and economic cost caused by road transport-related air pollution using an integrated assessment approach which utilizes air quality model, engineering, epidemiology, and economics. The results show that the total economic cost of health impacts due to air pollution contributed from transport in Beijing during 2004-2008 was 272, 297, 310, 323, 298 million US (mean value), respectively. The economic costs of road transport accounted for 0.52, 0.57, 0.60, 0.62, and 0.58% of annual Beijing GDP from 2004 to 2008. Average cost per vehicle and per ton of PM 10 emission from road transport can also be estimated as 106 US /number and 3584 US $ t -1, respectively. These findings illustrate that the impact of road transport contributed particulate air pollution on human health could be substantial in Beijing, whether in physical and economic terms. Therefore, some control measures to reduce transport emissions could lead to considerable economic benefit.

  17. A Dynamic Travel Time Estimation Model Based on Connected Vehicles

    Directory of Open Access Journals (Sweden)

    Daxin Tian

    2015-01-01

    Full Text Available With advances in connected vehicle technology, dynamic vehicle route guidance models gradually become indispensable equipment for drivers. Traditional route guidance models are designed to direct a vehicle along the shortest path from the origin to the destination without considering the dynamic traffic information. In this paper a dynamic travel time estimation model is presented which can collect and distribute traffic data based on the connected vehicles. To estimate the real-time travel time more accurately, a road link dynamic dividing algorithm is proposed. The efficiency of the model is confirmed by simulations, and the experiment results prove the effectiveness of the travel time estimation method.

  18. Panel estimation for renewable and non-renewable energy consumption, economic growth, CO2 emissions, the composite trade intensity, and financial openness of the commonwealth of independent states.

    Science.gov (United States)

    Rasoulinezhad, Ehsan; Saboori, Behnaz

    2018-04-13

    This article investigates the long-run and causal linkages between economic growth, CO 2 emissions, renewable and non-renewable (fossil fuels) energy consumption, the Composite Trade Intensity (CTI) as a proxy for trade openness, and the Chinn-Ito index as a proxy for financial openness for a panel of the Commonwealth of Independent States (CIS) region including Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan over the period of 1992-2015. It is the first time that CTI and the Chinn-Ito indexes are used in an economic-pollution model. Employing three panel unit root tests, panel cointegration estimation methods (DOLS and FMOLS), and two panel causality tests, the main empirical results provided evidence for the bidirectional long-run relationship between all the variables in all 12 sampled countries except for economic growth-renewable energy use linkage. The findings of causality tests indicated that there is a unidirectional short-run panel causality running from economic growth, financial openness, and trade openness to CO 2 emissions and from fossil fuel energy consumption to renewable energy use.

  19. ROAD TRANSPORT OF DANGEROUS SUBSTANCE WITH SPECIAL EMPHASIS ON LIQUID FUELS

    Directory of Open Access Journals (Sweden)

    Adam Salomon

    2015-09-01

    Full Text Available The article presents the characteristics of the transport of dangerous goods by road transport. It contains issues relating to the legal aspects, the risk to traffic and transport requirements for participants in force in the European Union and Poland. Particular emphasis has been placed on issues related to the carriage of liquid fuels.

  20. The impact of anti-congestion policies on fuel consumption, carbon dioxide emissions and urban sprawl: Application of RELU-TRAN2, a CGE model

    Science.gov (United States)

    Hiramatsu, Tomoru

    RELU-TRAN (Regional Economy and Land Use and Transportation) is a numerically solvable general equilibrium model (Anas and Liu, 2007), which treats in a unified manner the regional economy, urban land use and urban personal transportation sectors. In this dissertation, the model is extended by adding the consumer-workers' choice of private vehicle type according to the vehicle's fuel economy, by treating congestion on local roads as well as on major roads and by introducing car fuel consumption as a function of congested vehicle speed. By making the extensions, the model becomes more suitable to analyze the fuel consumption and CO2 emission consequences of urban development. The model is calibrated and simulated for the Chicago metropolitan area. By adjusting the model to the longer time span gradually, the shortand long-run price elasticities of fuel consumption are examined. As the time span becomes longer, fuel consumption becomes more elastic with respect to gasoline price, but when technological improvements in car fuel economy over comparable time spans are introduced exogenously, then the elasticity of fuel with respect to gasoline price becomes similar to that estimated in the econometric literature. Comparative statics exercises show that, if travel by auto becomes relatively more attractive in terms of travel time or travel cost than travel by public transit, then the Chicago MSA becomes more sprawled in total developed land area, whereas if public transit travel becomes relatively more attractive, then the Chicago MSA becomes more centralized. To mitigate fuel consumption and CO2 emissions, relative effectiveness of quasi-Pigouvian congestion tolls, a fuel tax on gasoline, a cordon toll around the downtown and a downtown parking fee are tested. All of these policies successfully reduce the aggregate fuel consumption and CO2. The urban growth boundary (UGB) is an alternative policy tested by the model. The UGB directly makes the Chicago MSA more

  1. A panel data analysis of the determinants of oil consumption: The case of Australia

    International Nuclear Information System (INIS)

    Narayan, Paresh Kumar; Wong, Philip

    2009-01-01

    The goal of this paper is to examine the determinants of oil consumption for a panel consisting of six Australian States and one territory, namely Queensland, New South Wales, Victoria, Tasmania, South Australia, Western Australia, and the Northern territory, for the period 1985-2006. We find that oil consumption, oil prices and income are panel cointegrated. We estimate long-run elasticities and find that oil prices have had a statistically insignificant impact on oil consumption, while income has had a statistically significant positive effect on oil consumption. (author)

  2. Inequality and development: Evidence from semiparametric estimation with panel data

    OpenAIRE

    Zhou, X.; Li, Kui-Wai

    2011-01-01

    Evidences from nonparametric and semiparametric unbalanced panel data models with fixed effects show that Kuznet’s inverted-U relationship is confirmed when economic development reaches a threshold. The model tests justify semiparametric specification. The integrated net contribution of control variables to inequality reduction is significant.

  3. On the determinants of renewable energy consumption: International Evidence

    OpenAIRE

    Anis Omri; Duc Khuong Nguyen

    2014-01-01

    Over recent years, renewable energy sources have emerged as an important component of world energy consumption. Little is however known about the determinants of renewable energy consumption. This article tackles this issue for a global panel consisting of 64 countries over the period 1990-2011 by using a dynamic system- GMM panel model. We also consider three homogeneous subpanels which are constructed based on the income level of sample countries (high-, middle-, and low-income subpanels). ...

  4. Real driving emissions and fuel consumption characteristics of Istanbul public transportation

    Directory of Open Access Journals (Sweden)

    Ozener Orkun

    2017-01-01

    Full Text Available Public transportation, which uses intra city lines frequently, has vital importance on the cities air pollution. The fossil fuel based drive units, which emits pollutants, are the primary source of this interest. Also, the fuel consumption is another major concern because of economic aspects. For an efficient and clear transportation, the pollutants and fuel consumption has to be analyzed, considering the operating conditions. In this context, the Metrobus line of Istanbul city which crosses from European side to Asian side of the city was analyzed with portable emission measurement system and portable fuel consumption meter devices. The relevant bus operating data were also collected during the operation. The data were analyzed while considering the operating modes like acceleration, deceleration, and constant speed cruises. The emission factors were developed. The pollutant emissions generally decreased as the vehicle speed increased while the fuel consumption increased for the same acceleration level. These results show the importance of operating conditions and their non-linear effect on emissions and fuel consumption Istanbul public transportation.

  5. Panel data nonparametric estimation of production risk and risk preferences

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    approaches for obtaining firm-specific measures of risk attitudes. We found that Polish dairy farmers are risk averse regarding production risk and price uncertainty. According to our results, Polish dairy farmers perceive the production risk as being more significant than the risk related to output price......We apply nonparametric panel data kernel regression to investigate production risk, out-put price uncertainty, and risk attitudes of Polish dairy farms based on a firm-level unbalanced panel data set that covers the period 2004–2010. We compare different model specifications and different...

  6. Panel estimation for CO2 emissions, energy consumption, economic growth, trade openness and urbanization of newly industrialized countries

    International Nuclear Information System (INIS)

    Sharif Hossain, Md.

    2011-01-01

    This paper empirically examines the dynamic causal relationships between carbon dioxide emissions, energy consumption, economic growth, trade openness and urbanization for the panel of newly industrialized countries (NIC) using the time series data for the period 1971-2007. Using four different panel unit root tests it is found that all panel variables are integrated of order 1. From the Johansen Fisher panel cointegration test it is found that there is a cointegration vector among the variables. The Granger causality test results support that there is no evidence of long-run causal relationship, but there is unidirectional short-run causal relationship from economic growth and trade openness to carbon dioxide emissions, from economic growth to energy consumption, from trade openness to economic growth, from urbanization to economic growth and from trade openness to urbanization. It is found that the long-run elasticity of carbon dioxide emissions with respect to energy consumption (1.2189) is higher than short run elasticity of 0.5984. This indicates that over time higher energy consumption in the newly industrialized countries gives rise to more carbon dioxide emissions as a result our environment will be polluted more. But in respect of economic growth, trade openness and urbanization the environmental quality is found to be normal good in the long-run. - Highlights: → Dynamic causal relationships are conducted for different panel variables of NIC. → Test results support only existence of unidirectional short-run causal relationships. → Environment will be polluted more due to energy consumption in the long-run. → But environmental quality is found to be normally good in respect of other variables. → NIC should use solar energy as the substitute of oil to control CO 2 emissions.

  7. Fuel Prices as a Factor of Shaping Profitability of Road Transport in Poland

    Directory of Open Access Journals (Sweden)

    Marzantowicz Łukasz

    2016-12-01

    Full Text Available The goal of this article is to determine the relation between the price of fuel and the profitability of the company. For this purpose, the article defines the profitability of transport enterprises and points the source of the impact of changes in fuel prices on the profitability of companies in the road transport sector. The case of the ABC transport company shows the relationship between the costs incurred for the purchase of fuel and the cost of transport activities. To test the theoretical assumptions, case study method was used.

  8. HIV Model Parameter Estimates from Interruption Trial Data including Drug Efficacy and Reservoir Dynamics

    Science.gov (United States)

    Luo, Rutao; Piovoso, Michael J.; Martinez-Picado, Javier; Zurakowski, Ryan

    2012-01-01

    Mathematical models based on ordinary differential equations (ODE) have had significant impact on understanding HIV disease dynamics and optimizing patient treatment. A model that characterizes the essential disease dynamics can be used for prediction only if the model parameters are identifiable from clinical data. Most previous parameter identification studies for HIV have used sparsely sampled data from the decay phase following the introduction of therapy. In this paper, model parameters are identified from frequently sampled viral-load data taken from ten patients enrolled in the previously published AutoVac HAART interruption study, providing between 69 and 114 viral load measurements from 3–5 phases of viral decay and rebound for each patient. This dataset is considerably larger than those used in previously published parameter estimation studies. Furthermore, the measurements come from two separate experimental conditions, which allows for the direct estimation of drug efficacy and reservoir contribution rates, two parameters that cannot be identified from decay-phase data alone. A Markov-Chain Monte-Carlo method is used to estimate the model parameter values, with initial estimates obtained using nonlinear least-squares methods. The posterior distributions of the parameter estimates are reported and compared for all patients. PMID:22815727

  9. Emissions of road transport

    International Nuclear Information System (INIS)

    Maekelae, K.; Tuominen, A.

    2001-01-01

    Information on the emissions and energy consumption of different vehicles per transported amount of goods has up to last years been minimal. The unit emissions mean the amount of harmful compounds in the flue gases of a vehicle per service, time or energy unit. National three-year MOBILE 2-research program, started in 1999, determines the unit emissions of all the traffic sectors in Finland. VTT Building and Transport mainly carry out the research, but the Institute of Transportation Engineering of the Tampere University of Technology (TTKK) is responsible for a part of the research. The objective of the project is to create common rules for the determination of unit emissions values, and to determine the best possible values for Finnish conditions. Unit emission data is mainly needed for evaluation of the environmental impacts of production plants and other activities containing transportation of commodities. At the web sites of VTT Building and Transport there are about 60 pages of text and tables (about 4000 values) on unit emissions. The URL of the pages is http://www.vtt.fi/rte/projects/lipastoe/index.htm. These web pages present data on all the transportation sectors (road, railroad, water and air transportation), most of the materials concerning road transportation. Following compounds and values are included: CO, HC, NO x , particulates, SO 2 , CO 2 and energy consumption. Methane and nitrous oxide emissions values have also been presented

  10. Estimating the direct rebound effect for on-road freight transportation

    International Nuclear Information System (INIS)

    Winebrake, James J.; Green, Erin H.; Comer, Bryan; Corbett, James J.; Froman, Sarah

    2012-01-01

    Energy and environmental concerns have spawned new policies aimed at reducing emissions and fuel consumption of heavy-duty vehicles (HDVs) worldwide. While such policies intend to reduce HDV energy consumption and emissions, energy savings that reduce transportation costs may lead to increased demand for HDV transportation services. Increased HDV transportation, in turn, can result in increased energy use and emissions—i.e., a direct “rebound effect.” This paper provides a critical review of the literature related to the HDV rebound effect. Results of this review demonstrate that the lack of focused studies in this area combined with the variability and heterogeneity of the trucking sector limit general understanding of the HDV rebound effect. Currently, the studies that do exist often create biased or erroneous rebound effect estimates by inappropriately relying on freight elasticities or applying metrics that omit important elements of fuel consumption. Research following a more transparent and coherent approach can improve estimates of the rebound effect from policy measures to improve HDV energy efficiency. - Highlights: ► Provides a critical review of HDV rebound effect literature. ► Demonstrates limitations of HDV rebound effect estimates. ► Provides framework for considering more complete HDV rebound effect.

  11. Mind the Gap: The Vicious Circle of Measuring Automobile Fuel Use

    DEFF Research Database (Denmark)

    Figueroa, Maria; author), L. Schipper (main; Price, L.

    1993-01-01

    We review the circularity between estimates of automobile use, fuel consumption and fuel intensity. We find that major gaps exist between estimates of road gasoline, the quantity most often used to represent automobile fuel use in economic studies of transport fuel use, and the actual sales data...

  12. Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data.

    Science.gov (United States)

    Chen, Feng; Chen, Suren; Ma, Xiaoxiang

    2018-06-01

    Driving environment, including road surface conditions and traffic states, often changes over time and influences crash probability considerably. It becomes stretched for traditional crash frequency models developed in large temporal scales to capture the time-varying characteristics of these factors, which may cause substantial loss of critical driving environmental information on crash prediction. Crash prediction models with refined temporal data (hourly records) are developed to characterize the time-varying nature of these contributing factors. Unbalanced panel data mixed logit models are developed to analyze hourly crash likelihood of highway segments. The refined temporal driving environmental data, including road surface and traffic condition, obtained from the Road Weather Information System (RWIS), are incorporated into the models. Model estimation results indicate that the traffic speed, traffic volume, curvature and chemically wet road surface indicator are better modeled as random parameters. The estimation results of the mixed logit models based on unbalanced panel data show that there are a number of factors related to crash likelihood on I-25. Specifically, weekend indicator, November indicator, low speed limit and long remaining service life of rutting indicator are found to increase crash likelihood, while 5-am indicator and number of merging ramps per lane per mile are found to decrease crash likelihood. The study underscores and confirms the unique and significant impacts on crash imposed by the real-time weather, road surface, and traffic conditions. With the unbalanced panel data structure, the rich information from real-time driving environmental big data can be well incorporated. Copyright © 2018 National Safety Council and Elsevier Ltd. All rights reserved.

  13. Determination of prerequisites for the estimation of transportation cost of spent fuels

    International Nuclear Information System (INIS)

    Choi, Heui Joo; Lee, Jong Youl; Kim, Seong Ki; Cha, Jeong Hoon; Choi, Jong Won

    2007-10-01

    The cost for the spent fuel management includes the costs for the interim storage, the transportation, and the permanent disposal of the spent fuels. The scope of this report is limited to the cost for the spent fuel transportation. KAERI is developing a cost estimation method for the spent fuel transportation through a joint study with the French AREVA TN. Several prerequisites should be fixed in order to estimate the cost for the spent fuel transportation properly. In this report we produced them considering the Korean current status on the management of spent fuels. The representative characteristics of a spent fuel generated from the six nuclear reactors at the YG site were determined. Total 7,200 tons of spent fuels are projected with the lifespan of 60 years. As the transportation mode, sea transportation and road transportation is recommended considering the location of the YG site and the hypothetical Centralized Interim Storage Facility (CISF) and Final Repository (FR). The sea route and transportation time were analyzed by using a sea distance analysis program which the NORI (National Oceanographic Research Institute) supplies on a web. Based on the results of the analysis, the shipping rates were determined. The regulations related to the spent fuel transportation were reviewed. The characteristics of the transportation vessel and a trailer were suggested. The handling and transportation systems at the YG site, Centralized Interim Storage Facility, and the Final Repository were described in detail for the purpose of the cost estimation of the spent fuel transportation. From the detail description the major components of the transportation system were determined for the conceptual design. It is believed that the conceptual design of the transportation system developed in this report will be used for the analysis of transportation logistics and the cost estimation of spent fuels

  14. A three-dimensional cohesive sediment transport model with data assimilation: Model development, sensitivity analysis and parameter estimation

    Science.gov (United States)

    Wang, Daosheng; Cao, Anzhou; Zhang, Jicai; Fan, Daidu; Liu, Yongzhi; Zhang, Yue

    2018-06-01

    Based on the theory of inverse problems, a three-dimensional sigma-coordinate cohesive sediment transport model with the adjoint data assimilation is developed. In this model, the physical processes of cohesive sediment transport, including deposition, erosion and advection-diffusion, are parameterized by corresponding model parameters. These parameters are usually poorly known and have traditionally been assigned empirically. By assimilating observations into the model, the model parameters can be estimated using the adjoint method; meanwhile, the data misfit between model results and observations can be decreased. The model developed in this work contains numerous parameters; therefore, it is necessary to investigate the parameter sensitivity of the model, which is assessed by calculating a relative sensitivity function and the gradient of the cost function with respect to each parameter. The results of parameter sensitivity analysis indicate that the model is sensitive to the initial conditions, inflow open boundary conditions, suspended sediment settling velocity and resuspension rate, while the model is insensitive to horizontal and vertical diffusivity coefficients. A detailed explanation of the pattern of sensitivity analysis is also given. In ideal twin experiments, constant parameters are estimated by assimilating 'pseudo' observations. The results show that the sensitive parameters are estimated more easily than the insensitive parameters. The conclusions of this work can provide guidance for the practical applications of this model to simulate sediment transport in the study area.

  15. Detecting the relationship between economic growth, CO2 and energy consumption by using panel data approach

    Science.gov (United States)

    Sayed, Ahmed R. M. Al; Isa, Zaidi

    2015-09-01

    Many scholars have shown their interest into the relationship between energy consumption (EC), gross domestic product (GDP) and emissions. The main objective of this study is to investigate the relationship between GDP, EC and CO2 within multivariate model by using panel data method in Asian countries; Korea, Malaysia, Japan and China for annually data during the period 1960 to 2010. The main finding shows that CO2 can be explained more than 86% & 78% by EC and GDP in each of cross section model and period model respectively. As a result of that, CO2 emissions should be considered as an important factor in energy consumption and gross domestic product by policy maker.

  16. Detecting the relationship between economic growth, CO2 and energy consumption by using panel data approach

    International Nuclear Information System (INIS)

    Sayed, Ahmed R. M. Al; Isa, Zaidi

    2015-01-01

    Many scholars have shown their interest into the relationship between energy consumption (EC), gross domestic product (GDP) and emissions. The main objective of this study is to investigate the relationship between GDP, EC and CO 2 within multivariate model by using panel data method in Asian countries; Korea, Malaysia, Japan and China for annually data during the period 1960 to 2010. The main finding shows that CO 2 can be explained more than 86% & 78% by EC and GDP in each of cross section model and period model respectively. As a result of that, CO 2 emissions should be considered as an important factor in energy consumption and gross domestic product by policy maker

  17. Evaluation of alternative fuels for the Greek road transport sector using the analytic hierarchy process

    International Nuclear Information System (INIS)

    Tsita, Katerina G.; Pilavachi, Petros A.

    2012-01-01

    This paper evaluates alternative fuels for the Greek road transport sector, using the Analytic Hierarchy Process. Seven different alternatives of fuel mode are considered in this paper: internal combustion engine (ICE) and its combination with petroleum and 1st and 2nd generation biofuels blends, fuel cells, hybrid vehicles, plug-in hybrids and electric vehicles. The evaluation of alternative fuel modes is performed according to cost and policy aspects. In order to evaluate each alternative fuel, one base scenario and ten alternative scenarios with different weight factors selection per criterion are presented. After deciding the alternative fuels’ scoring against each criterion and the criteria weights, their synthesis gives the overall score and ranking for all ten alternative scenarios. It is concluded that ICE blended with 1st and 2nd generation biofuels are the most suitable alternative fuels for the Greek road transport sector. - Highlights: ► Alternative fuels for the Greek road transport sector have been evaluated. ► The method of the AHP was used. ► Seven different alternatives of fuel mode are considered. ► The evaluation is performed according to cost and policy aspects. ► The ICE with 1st and 2nd generation biofuels are the most suitable fuels.

  18. Dynamic heat transfer modeling and parametric study of thermoelectric radiant cooling and heating panel system

    International Nuclear Information System (INIS)

    Luo, Yongqiang; Zhang, Ling; Liu, Zhongbing; Wang, Yingzi; Wu, Jing; Wang, Xiliang

    2016-01-01

    Highlights: • Dynamic model of thermoelectric radiant panel system is established. • The internal parameters of thermoelectric module are dynamically calculated in simulation. • Both artificial neural networks model and system model are verified through experiment data. • Optimized system structure is obtained through parametric study. - Abstract: Radiant panel system can optimize indoor thermal comfort with lower energy consumption. The thermoelectric radiant panel (TERP) system is a new and effective prototype of radiant system using thermoelectric module (TEM) instead of conventional water pipes, as heat source. The TERP can realize more stable and easier system control as well as lower initial and operative cost. In this study, an improved system dynamic model was established by combining analytical system model and artificial neural networks (ANN) as well as the dynamic calculation functions of internal parameters of TEM. The double integral was used for the calculation of surface average temperature of TERP. The ANN model and system model were in good agreement with experiment data in both cooling and heating mode. In order to optimize the system design structure, parametric study was conducted in terms of the thickness of aluminum panel and insulation, as well as the arrangement of TEMs on the surface of radiant panel. It was found through simulation results that the optimum thickness of aluminum panel and insulation are respectively around 1–2 mm and 40–50 mm. In addition, TEMs should be uniformly installed on the surface of radiant panel and each TEM should stand at the central position of a square-shaped typical region with length around 0.387–0.548 m.

  19. Green Routing Fuel Saving Opportunity Assessment: A Case Study on California Large-Scale Real-World Travel Data

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Lei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Holden, Jacob [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Gonder, Jeffrey D [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wood, Eric W [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-07-31

    New technologies, such as connected and automated vehicles, have attracted more and more researchers for improving the energy efficiency and environmental impact of current transportation systems. The green routing strategy instructs a vehicle to select the most fuel-efficient route before the vehicle departs. It benefits the current transportation system with fuel saving opportunity through identifying the greenest route. This paper introduces an evaluation framework for estimating benefits of green routing based on large-scale, real-world travel data. The framework has the capability to quantify fuel savings by estimating the fuel consumption of actual routes and comparing to routes procured by navigation systems. A route-based fuel consumption estimation model, considering road traffic conditions, functional class, and road grade is proposed and used in the framework. An experiment using a large-scale data set from the California Household Travel Survey global positioning system trajectory data base indicates that 31% of actual routes have fuel savings potential with a cumulative estimated fuel savings of 12%.

  20. Green Routing Fuel Saving Opportunity Assessment: A Case Study on California Large-Scale Real-World Travel Data: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Lei; Holden, Jacob; Gonder, Jeff; Wood, Eric

    2017-07-13

    New technologies, such as connected and automated vehicles, have attracted more and more researchers for improving the energy efficiency and environmental impact of current transportation systems. The green routing strategy instructs a vehicle to select the most fuel-efficient route before the vehicle departs. It benefits the current transportation system with fuel saving opportunity through identifying the greenest route. This paper introduces an evaluation framework for estimating benefits of green routing based on large-scale, real-world travel data. The framework has the capability to quantify fuel savings by estimating the fuel consumption of actual routes and comparing to routes procured by navigation systems. A route-based fuel consumption estimation model, considering road traffic conditions, functional class, and road grade is proposed and used in the framework. An experiment using a large-scale data set from the California Household Travel Survey global positioning system trajectory data base indicates that 31% of actual routes have fuel savings potential with a cumulative estimated fuel savings of 12%.

  1. Modeling transit bus fuel consumption on the basis of cycle properties.

    Science.gov (United States)

    Delgado, Oscar F; Clark, Nigel N; Thompson, Gregory J

    2011-04-01

    A method exists to predict heavy-duty vehicle fuel economy and emissions over an "unseen" cycle or during unseen on-road activity on the basis of fuel consumption and emissions data from measured chassis dynamometer test cycles and properties (statistical parameters) of those cycles. No regression is required for the method, which relies solely on the linear association of vehicle performance with cycle properties. This method has been advanced and examined using previously published heavy-duty truck data gathered using the West Virginia University heavy-duty chassis dynamometer with the trucks exercised over limited test cycles. In this study, data were available from a Washington Metropolitan Area Transit Authority emission testing program conducted in 2006. Chassis dynamometer data from two conventional diesel buses, two compressed natural gas buses, and one hybrid diesel bus were evaluated using an expanded driving cycle set of 16 or 17 different driving cycles. Cycle properties and vehicle fuel consumption measurements from three baseline cycles were selected to generate a linear model and then to predict unseen fuel consumption over the remaining 13 or 14 cycles. Average velocity, average positive acceleration, and number of stops per distance were found to be the desired cycle properties for use in the model. The methodology allowed for the prediction of fuel consumption with an average error of 8.5% from vehicles operating on a diverse set of chassis dynamometer cycles on the basis of relatively few experimental measurements. It was found that the data used for prediction should be acquired from a set that must include an idle cycle along with a relatively slow transient cycle and a relatively high speed cycle. The method was also applied to oxides of nitrogen prediction and was found to have less predictive capability than for fuel consumption with an average error of 20.4%.

  2. Productivity and Regional Employment in Spain: A Dynamic Approach

    Directory of Open Access Journals (Sweden)

    F. Javier Escribá Pérez

    2013-01-01

    Full Text Available This paper analyses the impact of sectorial and territorial factors on the dynamics of employment in regional industries in Spain over the period 1980-2006. A dynamic panel data model is estimated using panel data techniques (System-GMM, which provide an alternative methodology for addressing the problem of variable endogeneity. The results confirm the robustness of the contemporary effects: diversification, market size and dynamics in the sector affect employment in the short term. However, effects in the long term are more uncertain.

  3. Dynamic modeling and predictive control in solid oxide fuel cells first principle and data-based approaches

    CERN Document Server

    Huang, Biao; Murshed, A K M Monjur

    2012-01-01

    The high temperature solid oxide fuel cell (SOFC) is identified as one of the leading fuel cell technology contenders to capture the energy market in years to come. However, in order to operate as an efficient energy generating system, the SOFC requires an appropriate control system which in turn requires a detailed modelling of process dynamics. Introducting state-of-the-art dynamic modelling, estimation, and control of SOFC systems, this book presents original modelling methods and brand new results as developed by the authors. With comprehensive coverage and bringing together many

  4. Estimating the effect of urban density on fuel demand

    Energy Technology Data Exchange (ETDEWEB)

    Karathodorou, Niovi; Graham, Daniel J. [Imperial College London, London, SW7 2AZ (United Kingdom); Noland, Robert B. [Rutgers University, New Brunswick, NJ 08901 (United States)

    2010-01-15

    Much of the empirical literature on fuel demand presents estimates derived from national data which do not permit any explicit consideration of the spatial structure of the economy. Intuitively we would expect the degree of spatial concentration of activities to have a strong link with transport fuel consumption. The present paper addresses this theme by estimating a fuel demand model for urban areas to provide a direct estimate of the elasticity of demand with respect to urban density. Fuel demand per capita is decomposed into car stock per capita, fuel consumption per kilometre and annual distance driven per car per year. Urban density is found to affect fuel consumption, mostly through variations in the car stock and in the distances travelled, rather than through fuel consumption per kilometre. (author)

  5. Thermal model of spent fuel transport cask

    International Nuclear Information System (INIS)

    Ahmed, E.E.M.; Rahman, F.A.; Sultan, G.F.; Khalil, E.E.

    1996-01-01

    The investigation provides a theoretical model to represent the thermal behaviour of the spent fuel elements when transported in a dry shipping cask under normal transport conditions. The heat transfer process in the spent fuel elements and within the cask are modeled which include the radiant heat transfer within the cask and the heat transfer by thermal conduction within the spent fuel element. The model considers the net radiant method for radiant heat transfer process from the inner most heated element to the surrounding spent elements. The heat conduction through fuel interior, fuel-clad interface and on clad surface are also presented. (author) 6 figs., 9 refs

  6. A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data model

    Science.gov (United States)

    Jeong, Jina; Park, Eungyu; Han, Weon Shik; Kim, Kue-Young; Jun, Seong-Chun; Choung, Sungwook; Yun, Seong-Taek; Oh, Junho; Kim, Hyun-Jun

    2017-11-01

    In this study, a data-driven method for predicting CO2 leaks and associated concentrations from geological CO2 sequestration is developed. Several candidate models are compared based on their reproducibility and predictive capability for CO2 concentration measurements from the Environment Impact Evaluation Test (EIT) site in Korea. Based on the data mining results, a one-dimensional solution of the advective-dispersive equation for steady flow (i.e., Ogata-Banks solution) is found to be most representative for the test data, and this model is adopted as the data model for the developed method. In the validation step, the method is applied to estimate future CO2 concentrations with the reference estimation by the Ogata-Banks solution, where a part of earlier data is used as the training dataset. From the analysis, it is found that the ensemble mean of multiple estimations based on the developed method shows high prediction accuracy relative to the reference estimation. In addition, the majority of the data to be predicted are included in the proposed quantile interval, which suggests adequate representation of the uncertainty by the developed method. Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model. The proposed method is not confined to estimations of CO2 concentration and may be applied to various real-time monitoring data from subsurface sites to develop automated control, management or decision-making systems.

  7. High degree gravitational sensitivity from Mars orbiters for the GMM-1 gravity model

    Science.gov (United States)

    Lerch, F. J.; Smith, D. E.; Chan, J. C.; Patel, G. B.; Chinn, D. S.

    1994-01-01

    Orbital sensitivity of the gravity field for high degree terms (greater than 30) is analyzed on satellites employed in a Goddard Mars Model GMM-1, complete in spherical harmonics through degree and order 50. The model is obtained from S-band Doppler data on Mariner 9 (M9), Viking Orbiter 1 (VO1), and Viking Orbiter 2 (VO2) spacecraft, which were tracked by the NASA Deep Space Network on seven different highly eccentric orbits. The main sensitivity of the high degree terms is obtained from the VO1 and VO2 low orbits (300 km periapsis altitude), where significant spectral sensitivity is seen for all degrees out through degree 50. The velocity perturbations show a dominant effect at periapsis and significant effects out beyond the semi-latus rectum covering over 180 degrees of the orbital groundtrack for the low altitude orbits. Because of the wideband of periapsis motion covering nearly 180 degrees in w and +39 degrees in latitude coverage, the VO1 300 km periapsis altitude orbit with inclination of 39 degrees gave the dominant sensitivity in the GMM-1 solution for the high degree terms. Although the VO2 low periapsis orbit has a smaller band of periapsis mapping coverage, it strongly complements the VO1 orbit sensitivity for the GMM-1 solution with Doppler tracking coverage over a different inclination of 80 degrees.

  8. Atmospheric emissions from road transportation in India

    International Nuclear Information System (INIS)

    Baidya, S.; Borken-Kleefeld, J.

    2009-01-01

    India has become one of the biggest emitters of atmospheric pollutants from the road transportation sector globally. Here we present an up-to-date inventory of the exhaust emissions of ten species. This inventory has been calculated bottom-up from the vehicle mileage, differentiating by seven vehicle categories, four age/technology layers and three fuel types each, for the seven biggest cities as well as for the whole nation. The age composition of the rolling fleet has been carefully modelled, deducting about one quarter of vehicles still registered but actually out-of-service. The vehicle mileage is calibrated to the national fuel consumption which is essential to limit uncertainties. Sensitivity analyses reveal the primary impact of the emission factors and the secondary influence of vehicle mileage and stock composition on total emissions. Emission estimates since 1980 are reviewed and qualified. A more comprehensive inspection and maintenance is essential to limit pollutant emissions; this must properly include commercial vehicles. They are also the most important vehicle category to address when fuel consumption and CO 2 emissions shall be contained. (author)

  9. Alcohol affordability and alcohol demand: cross-country trends and panel data estimates, 1975 to 2008.

    Science.gov (United States)

    Nelson, Jon P

    2014-04-01

    Relatively little is known about cross-country differences in alcohol affordability or factors that determine differences in affordability over time. This information is potentially important for alcohol policy, especially policies that focus on higher taxes or prices to reduce total alcohol consumption. This study estimates cross-country alcohol consumption relationships using economic models incorporating income and prices and alternative models based on alcohol affordability. The data and analysis are restricted to higher income countries. Data for alcohol consumption per capita (ages 15+) are analyzed for 2 samples: first, 17 countries in the Organisation for Economic Co-operation and Development for the period 1975 to 2000; second, 22 countries in the European Union for the period from 2000 to 2008. Panel data models are utilized, with country and time fixed-effects to control for confounding influences. In economic demand models, covariates are real per capita income and real alcohol price indices. In affordability models, income is divided by prices to yield an index of alcohol affordability. Analysis of data trends reveals that much of the increase in affordability is due to rising real incomes, and not falling real prices. Economic models of demand perform slightly better statistically, but differences are not substantial as income and affordability are highly correlated. For both samples, exogenous rates of growth of alcohol consumption are negative. Price and income elasticities, on average, are within the range of prior estimates. Affordability elasticities are between 0.21 and 0.25. Although alcohol affordability is a valid concept statistically, its use in policy discussions tends to hide underlying causes of changes in affordability. A better approach is a comparison and analysis of trends and cross-country differences in real incomes and real alcohol prices together with the affordability index. Country-level analysis of income and price

  10. Navigation API Route Fuel Saving Opportunity Assessment on Large-Scale Real-World Travel Data for Conventional Vehicles and Hybrid Electric Vehicles: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Lei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Holden, Jacob [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Gonder, Jeffrey D [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-12-06

    The green routing strategy instructing a vehicle to select a fuel-efficient route benefits the current transportation system with fuel-saving opportunities. This paper introduces a navigation API route fuel-saving evaluation framework for estimating fuel advantages of alternative API routes based on large-scale, real-world travel data for conventional vehicles (CVs) and hybrid electric vehicles (HEVs). The navigation APIs, such Google Directions API, integrate traffic conditions and provide feasible alternative routes for origin-destination pairs. This paper develops two link-based fuel-consumption models stratified by link-level speed, road grade, and functional class (local/non-local), one for CVs and the other for HEVs. The link-based fuel-consumption models are built by assigning travel from a large number of GPS driving traces to the links in TomTom MultiNet as the underlying road network layer and road grade data from a U.S. Geological Survey elevation data set. Fuel consumption on a link is calculated by the proposed fuel consumption model. This paper envisions two kinds of applications: 1) identifying alternate routes that save fuel, and 2) quantifying the potential fuel savings for large amounts of travel. An experiment based on a large-scale California Household Travel Survey GPS trajectory data set is conducted. The fuel consumption and savings of CVs and HEVs are investigated. At the same time, the trade-off between fuel saving and time saving for choosing different routes is also examined for both powertrains.

  11. Improving A Priori Demand Estimates Transport Models using Mobile Phone Data : A Rotterdam-Region Case

    NARCIS (Netherlands)

    Wismans, Luc Johannes Josephus; Friso, K.; Rijsdijk, J.; de Graaf, S.W.; Keij, J.

    2016-01-01

    Mobile phone data are a rich source to infer all kinds of mobility related information. In this research we present an approach where mobile phone data is used and analysed for enriching the transport model of the region of Rotterdam. In our research we used Call Detail Records (CDR) from one of the

  12. Improving A Priori Demand Estimates Transport Models using Mobile Phone Data : A Rotterdam-Region Case

    NARCIS (Netherlands)

    Wismans, Luc Johannes Josephus; Friso, K.; Rijsdijk, J.; de Graaf, S.W.; Keij, J.

    2018-01-01

    Mobile phone data are a rich source to infer all kinds of mobility- related information. In this research, we present an approach where mobile phone data are used and analyzed for enriching the transport model of the region of Rotterdam. In this research Call Detail Records (CDR) are used from a

  13. Distributed Road Grade Estimation for Heavy Duty Vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Sahlholm, Per

    2011-07-01

    An increasing need for goods and passenger transportation drives continued worldwide growth in traffic. As traffic increases environmental concerns, traffic safety, and cost efficiency become ever more important. Advancements in microelectronics open the possibility to address these issues through new advanced driver assistance systems. Applications such as predictive cruise control, automated gearbox control, predictive front lighting control, and hybrid vehicle state-of-charge control decrease the energy consumption of vehicles and increase the safety. These control systems can benefit significantly from preview road grade information. This information is currently obtained using specialized survey vehicles, and is not widely available. This thesis proposes new methods to obtain road grade information using on-board sensors. The task of creating road grade maps is addressed by the proposal of a framework where vehicles using a road network collect the necessary data for estimating the road grade. The estimation can then be carried out locally in the vehicle, or in the presence of a communication link to the infrastructure, centrally. In either case the accuracy of the map increases over time, and costly road surveys can be avoided. This thesis presents a new distributed method for creating accurate road grade maps for vehicle control applications. Standard heavy duty vehicles in normal operation are used to collect measurements. Estimates from multiple passes along a road segment are merged to form a road grade map, which improves each time a vehicle retraces a route. The design and implementation of the road grade estimator are described, and the performance is experimentally evaluated using real vehicles. Three different grade estimation methods, based on different assumption on the road grade signal, are proposed and compared. They all use data from sensors that are standard equipment in heavy duty vehicles. Measurements of the vehicle speed and the engine

  14. A linear model for estimation of neurotransmitter response profiles from dynamic PET data

    OpenAIRE

    Normandin, M.D.; Schiffer, W.K.; Morris, E.D.

    2011-01-01

    The parametric ntPET model (p-ntPET) estimates the kinetics of neurotransmitter release from dynamic PET data with receptor-ligand radiotracers. Here we introduce a linearization (lp-ntPET) that is computationally efficient and can be applied to single-scan data. lp-ntPET employs a non-invasive reference region input function and extends the LSRRM of Alpert et al. (2003) using basis functions to characterize the time course of neurotransmitter activation. In simulation studies, the temporal p...

  15. Dynamic N -occupancy models: estimating demographic rates and local abundance from detection-nondetection data

    Science.gov (United States)

    Sam Rossman; Charles B. Yackulic; Sarah P. Saunders; Janice Reid; Ray Davis; Elise F. Zipkin

    2016-01-01

    Occupancy modeling is a widely used analytical technique for assessing species distributions and range dynamics. However, occupancy analyses frequently ignore variation in abundance of occupied sites, even though site abundances affect many of the parameters being estimated (e.g., extinction, colonization, detection probability). We introduce a new model (“dynamic

  16. A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data model.

    Science.gov (United States)

    Jeong, Jina; Park, Eungyu; Han, Weon Shik; Kim, Kue-Young; Jun, Seong-Chun; Choung, Sungwook; Yun, Seong-Taek; Oh, Junho; Kim, Hyun-Jun

    2017-11-01

    In this study, a data-driven method for predicting CO 2 leaks and associated concentrations from geological CO 2 sequestration is developed. Several candidate models are compared based on their reproducibility and predictive capability for CO 2 concentration measurements from the Environment Impact Evaluation Test (EIT) site in Korea. Based on the data mining results, a one-dimensional solution of the advective-dispersive equation for steady flow (i.e., Ogata-Banks solution) is found to be most representative for the test data, and this model is adopted as the data model for the developed method. In the validation step, the method is applied to estimate future CO 2 concentrations with the reference estimation by the Ogata-Banks solution, where a part of earlier data is used as the training dataset. From the analysis, it is found that the ensemble mean of multiple estimations based on the developed method shows high prediction accuracy relative to the reference estimation. In addition, the majority of the data to be predicted are included in the proposed quantile interval, which suggests adequate representation of the uncertainty by the developed method. Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model. The proposed method is not confined to estimations of CO 2 concentration and may be applied to various real-time monitoring data from subsurface sites to develop automated control, management or decision-making systems. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Reconfiguration of photovoltaic panels for reducing the hydrogen consumption in fuel cells of hybrid systems

    Directory of Open Access Journals (Sweden)

    Daniel González-Montoya

    2017-05-01

    Full Text Available Hybrid generation combines advantages from fuel cell systems with non-predictable generation approaches, such as photovoltaic and wind generators. In such hybrid systems, it is desirable to minimize as much as possible the fuel consumption, for the sake of reducing costs and increasing the system autonomy. This paper proposes an optimization algorithm, referred to as population-based incremental learning, in order to maximize the produced power of a photovoltaic generator. This maximization reduces the fuel consumption in the hybrid aggregation. Moreover, the algorithm's speed enables the real-time computation of the best configuration for the photovoltaic system, which also optimizes the fuel consumption in the complementary fuel cell system. Finally, a system experimental validation is presented considering 6 photovoltaic modules and a NEXA 1.2KW fuel cell. Such a validation demonstrates the effectiveness of the proposed algorithm to reduce the hydrogen consumption in these hybrid systems.

  18. Climate Projection Data base for Roads - CliPDaR: Design a guideline for a transnational database of downscaled climate projection data for road impact models - within the Conference's of European Directors of Roads (CEDR) TRANSNATIONAL ROAD RESEARCH PROG

    Science.gov (United States)

    Matulla, Christoph; Namyslo, Joachim; Fuchs, Tobias; Türk, Konrad

    2013-04-01

    The European road sector is vulnerable to extreme weather phenomena, which can cause large socio-economic losses. Almost every year there occur several weather triggered events (like heavy precipitation, floods, landslides, high winds, snow and ice, heat or cold waves, etc.), that disrupt transportation, knock out power lines, cut off populated regions from the outside and so on. So, in order to avoid imbalances in the supply of vital goods to people as well as to prevent negative impacts on health and life of people travelling by car it is essential to know present and future threats to roads. Climate change might increase future threats to roads. CliPDaR focuses on parts of the European road network and contributes, based on the current body of knowledge, to the establishment of guidelines helping to decide which methods and scenarios to apply for the estimation of future climate change based challenges in the field of road maintenance. Based on regional scale climate change projections specific road-impact models are applied in order to support protection measures. In recent years, it has been recognised that it is essential to assess the uncertainty and reliability of given climate projections by using ensemble approaches and downscaling methods. A huge amount of scientific work has been done to evaluate these approaches with regard to reliability and usefulness for investigations on possible impacts of climate changes. CliPDaR is going to collect the existing approaches and methodologies in European countries, discuss their differences and - in close cooperation with the road owners - develops a common line on future applications of climate projection data to road impact models. As such, the project will focus on reviewing and assessing existing regional climate change projections regarding transnational highway transport needs. The final project report will include recommendations how the findings of CliPDaR may support the decision processes of European

  19. The relationship between air pollution, fossil fuel energy consumption, and water resources in the panel of selected Asia-Pacific countries.

    Science.gov (United States)

    Rafindadi, Abdulkadir Abdulrashid; Yusof, Zarinah; Zaman, Khalid; Kyophilavong, Phouphet; Akhmat, Ghulam

    2014-10-01

    The objective of the study is to examine the relationship between air pollution, fossil fuel energy consumption, water resources, and natural resource rents in the panel of selected Asia-Pacific countries, over a period of 1975-2012. The study includes number of variables in the model for robust analysis. The results of cross-sectional analysis show that there is a significant relationship between air pollution, energy consumption, and water productivity in the individual countries of Asia-Pacific. However, the results of each country vary according to the time invariant shocks. For this purpose, the study employed the panel least square technique which includes the panel least square regression, panel fixed effect regression, and panel two-stage least square regression. In general, all the panel tests indicate that there is a significant and positive relationship between air pollution, energy consumption, and water resources in the region. The fossil fuel energy consumption has a major dominating impact on the changes in the air pollution in the region.

  20. Estimated consequences from severe spent nuclear fuel transportation accidents

    International Nuclear Information System (INIS)

    Arnish, J.J.; Monette, F.; LePoire, D.; Biwer, B.M.

    1996-01-01

    The RISKIND software package is used to estimate radiological consequences of severe accident scenarios involving the transportation of spent nuclear fuel. Radiological risks are estimated for both a collective population and a maximally exposed individual based on representative truck and rail cask designs described in the U.S. Nuclear Regulatory Commission (NRC) modal study. The estimate of collective population risk considers all possible environmental pathways, including acute and long-term exposures, and is presented in terms of the 50-y committed effective dose equivalent. Radiological risks to a maximally exposed individual from acute exposure are estimated and presented in terms of the first year and 50-y committed effective dose equivalent. Consequences are estimated for accidents occurring in rural and urban population areas. The modeled pathways include inhalation during initial passing of the radioactive cloud, external exposure from a reduction of the cask shielding, long-term external exposure. from ground deposition, and ingestion from contaminated food (rural only). The major pathways and contributing radionuclides are identified, and the effects of possible mitigative actions are discussed. The cask accident responses and the radionuclide release fractions are modeled as described in the NRC modal study. Estimates of severe accident probabilities are presented for both truck and rail modes of transport. The assumptions made in this study tend to be conservative; however, a set of multiplicative factors are identified that can be applied to estimate more realistic conditions

  1. Estimating Price Elasticity of Demand for Motor Fuel in the Transport Sectors

    Directory of Open Access Journals (Sweden)

    Olga Vasilyevna Mazurova

    2015-03-01

    Full Text Available Modeling of long-term forecasts of prices and demand on regional energy markets requires accounting for the future changes in the interactions between the greater economy and its energy sector, along with the possible emergence of new factors and specific regional features determining those interactions. The proposed approach allows the study of a correlation between demand and prices for motor fuel, taking into account the competition of energy carriers, the dynamics of energy prices, resource constraints, the use of new technologies and the uncertainty of input data. The main feature of the proposed approach is the combined estimation of the price elasticity of demand for motor fuel with optimization of fuel supply in the region. Thus the author determined elasticity of demand based on the comparison of economic efficiency of the use of different fuels. The study includes results of experimental calculations and forecasted price according to demand for motor fuel in freight transportation for the expected development conditions of the Far Eastern federal district

  2. Trends of greenhouse gas emissions from the road transport sector in India

    International Nuclear Information System (INIS)

    Singh, Anil; Gangopadhyay, S.; Nanda, P.K.; Bhattacharya, S.; Sharma, C.; Bhan, C.

    2008-01-01

    The road transport sector is the largest consumer of commercial fuel energy within the transportation system in India and accounts for nearly 35% of the total liquid commercial fuel consumption by all sectors. Gasoline and diesel consumption for road transportation have quadrupled between 1980 and 2000 due to about nine times increase in the number of vehicles and four-fold increase in freight and passenger travel demands. The paper elaborates the trends of energy consumption and consequent emissions of greenhouse gases such as CO 2 , CH 4 and N 2 O and ozone precursor gases like CO, NO x and NMVOC in the road transport sector in India for the period from 1980 to 2000. For the first time, efforts have been made to apportion the fuels, both diesel and gasoline, across different categories of vehicles operating on the Indian roads. In order to generate more comprehensive and complete emission estimates, additionally, other minor fuel types like light diesel oil and fuel oil along with lubricants have also been taken into account. Emission estimates have revealed that nearly 27 Mt of CO 2 were emitted in 1980, increasing to about 105 Mt in 2000. Similar trends have also been observed for other gases. Further scope for improvements in emission estimation is possible by generating country specific emission factors for different vehicle categories and improvement in documentation of fuel consumption at segregated levels by fuel types and vehicle types

  3. A panel data investigation of real exchange rate misalignment and growth

    Directory of Open Access Journals (Sweden)

    Flávio Vilela Vieira

    2012-09-01

    Full Text Available The paper investigates the role of real exchange rate misalignment on long-run growth for a set of ninety countries using time series data from 1980 to 2004. We first estimate a panel data model (fixed and random effects for the real exchange rate in order to produce estimates of the equilibrium real exchange rate and this is then used to construct measures of real exchange rate misalignment. We provide an alternative set of estimates of RER misalignment using panel cointegration methods. The results for the two-step System GMM panel growth models indicate that the coefficients for real exchange rate misalignment are positive for different model specification and samples, which means that a more depreciated (appreciated real exchange rate helps (harms long-run growth. The estimated coefficients are higher for developing and emerging countries.

  4. Panel estimation for transport sector CO2 emissions and its affecting factors: A regional analysis in China

    International Nuclear Information System (INIS)

    Zhang, Chuanguo; Nian, Jiang

    2013-01-01

    With rapid economic growth, the transport sector plays an important role in China′s CO 2 emissions. The existing research is extensively concerned with transport sector CO 2 emissions in recent years, but little attention has been paid to regional differences. This paper investigates CO 2 emissions in the transport sector at the national and regional levels using the STIRPAT model and provincial panel data from 1995 to 2010 in China. The results showed that passenger transport dominates CO 2 emissions in the transport sector, but its influence varies across regions. Electrification has significant potential to lower CO 2 emissions because of resulting higher fuel efficiency and reduced pollution. Energy efficiency improvement is effective but limited in reducing emissions due to increasing demand from economic development and population growth. These results not only contribute to advancing the existing literature, but also merit particular attention from policy makers in China. - Highlights: • We investigate China′s CO 2 emissions in the transport sector. • Passenger transport dominates CO 2 emissions in the transport sector. • The effects of passenger transport on CO 2 emissions vary across regions. • Energy efficiency improvement is effective but limited in reducing emissions

  5. Environmental data book 2011. Estimated emission factors for fuels, electricity, heat and transport in Sweden; Miljoefaktaboken 2011. Uppskattade emissionsfaktorer foer braenslen, el, vaerme och transporter

    Energy Technology Data Exchange (ETDEWEB)

    Gode, Jenny; Martinsson, Fredrik; Hagberg, Linus; Oeman, Andreas; Hoeglund, Jonas; Palm, David

    2011-04-15

    The environmental data book summarizes current and general emission factors for most fuels and sources of Swedish electricity and heat and to power vehicles. Emission data are compiled for wood fuels, energy crops, bio-oils, waste fuels, fossil fuels and peat, biofuels, wind power, hydro power, nuclear power and solar power

  6. Trends in road freight transportation carbon dioxide emissions and policies in China

    International Nuclear Information System (INIS)

    Li, Hongqi; Lu, Yue; Zhang, Jun; Wang, Tianyi

    2013-01-01

    We adopted the simple average Divisia index approach to explore the impacts of factors on the carbon dioxide (CO 2 ) emissions from road freight transportation in China from 1985 to 2007. CO 2 emissions were investigated using the following as influencing factors: the emission coefficient, vehicle fuel intensity, working vehicle stock per freight transport operator, market concentration level, freight transportation distance, market share of road freight transportation, ton-kilometer per value added of industry, industrialization level and economic growth. Building on the results, we suggest that economic growth is the most important factor in increasing CO 2 emissions, whereas the ton-kilometer per value added of industry and the market concentration level contribute significantly to decreasing CO 2 emissions. We also discussed some recent important policies concerning factors contained in the decomposition model. - Highlights: ► We estimated road freight fuel consumption and CO 2 emissions in China. ► Factors implying features of road freight were considered in decomposition model. ► Some policies were discussed to affect CO 2 emissions from road freight

  7. Integrated modeling for optimized regional transportation with compressed natural gas fuel

    Directory of Open Access Journals (Sweden)

    Hossam A. Gabbar

    2016-03-01

    Full Text Available Transportation represents major energy consumption where fuel is considered as a primary energy source. Recent development in the vehicle technology revealed possible economical improvements when using natural gas as a fuel source instead of traditional gasoline. There are several fuel alternatives such as electricity, which showed potential for future long-term transportation. However, the move from current situation where gasoline vehicle is dominating shows high cost compared to compressed natural gas vehicle. This paper presents modeling and simulation methodology to optimize performance of transportation based on quantitative study of the risk-based performance of regional transportation. Emission estimation method is demonstrated and used to optimize transportation strategies based on life cycle costing. Different fuel supply scenarios are synthesized and evaluated, which showed strategic use of natural gas as a fuel supply.

  8. Fuel consumption models for pine flatwoods fuel types in the southeastern United States

    Science.gov (United States)

    Clinton S. Wright

    2013-01-01

    Modeling fire effects, including terrestrial and atmospheric carbon fluxes and pollutant emissions during wildland fires, requires accurate predictions of fuel consumption. Empirical models were developed for predicting fuel consumption from fuel and environmental measurements on a series of operational prescribed fires in pine flatwoods ecosystems in the southeastern...

  9. A Bayesian Panel Data Approach to Explaining Market Beta Dynamics

    NARCIS (Netherlands)

    R. Bauer (Rob); M.M.J.E. Cosemans (Mathijs); R. Frehen (Rik); P.C. Schotman (Peter)

    2008-01-01

    markdownabstractWe characterize the process that drives the market betas of individual stocks by setting up a hierarchical Bayesian panel data model that allows a flexible specification for beta. We show that combining the parametric relationship between betas and conditioning variables specified by

  10. Mathematical model of statistical identification of information support of road transport

    Directory of Open Access Journals (Sweden)

    V. G. Kozlov

    2016-01-01

    Full Text Available In this paper based on the statistical identification method using the theory of self-organizing systems, built multifactor model the relationship of road transport and training system. Background information for the model represented by a number of parameters of average annual road transport operations and information provision, including training complex system parameters (inputs, road management and output parameters. Ask two criteria: stability criterion model and test correlation. The program determines their minimum, and is the only model of optimal complexity. The predetermined number of parameters established mathematical relationship of each output parameter with the others. To improve the accuracy and regularity of the forecast of the interpolation nodes allocated in the test data sequence. Other data form the training sequence. Decision model based on the principle of selection. Running it with the gradual complication of the mathematical description and exhaustive search of all possible variants of the models on the specified criteria. Advantages of the proposed model: adequately reflects the actual process, allows you to enter any additional input parameters and determine their impact on the individual output parameters of the road transport, allows in turn change the values of key parameters in a certain ratio and to determine the appropriate changes the output parameters of the road transport, allows to predict the output parameters road transport operations.

  11. GREET 1.5 - transportation fuel-cycle model - Vol. 1 : methodology, development, use, and results

    International Nuclear Information System (INIS)

    Wang, M. Q.

    1999-01-01

    This report documents the development and use of the most recent version (Version 1.5) of the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model. The model, developed in a spreadsheet format, estimates the full fuel-cycle emissions and energy associated with various transportation fuels and advanced vehicle technologies for light-duty vehicles. The model calculates fuel-cycle emissions of five criteria pollutants (volatile organic compounds, carbon monoxide, nitrogen oxides, particulate matter with diameters of 10 micrometers or less, and sulfur oxides) and three greenhouse gases (carbon dioxide, methane, and nitrous oxide). The model also calculates total energy consumption, fossil fuel consumption, and petroleum consumption when various transportation fuels are used. The GREET model includes the following cycles: petroleum to conventional gasoline, reformulated gasoline, conventional diesel, reformulated diesel, liquefied petroleum gas, and electricity via residual oil; natural gas to compressed natural gas, liquefied natural gas, liquefied petroleum gas, methanol, Fischer-Tropsch diesel, dimethyl ether, hydrogen, and electricity; coal to electricity; uranium to electricity; renewable energy (hydropower, solar energy, and wind) to electricity; corn, woody biomass, and herbaceous biomass to ethanol; soybeans to biodiesel; flared gas to methanol, dimethyl ether, and Fischer-Tropsch diesel; and landfill gases to methanol. This report also presents the results of the analysis of fuel-cycle energy use and emissions associated with alternative transportation fuels and advanced vehicle technologies to be applied to passenger cars and light-duty trucks

  12. Report of the seminar modeling of pollutants emissions by road transport; Compte-rendu du seminaire modelisation des emissions de polluants par le transport routier

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2003-07-01

    This seminar was organised by A.D.E.M.E. around the following themes: uncertainties and sensitivity analysis of the C.O.P.E.R.T. 3 model (computer programme to calculate emissions from road transport), presentation of studies using the C.O.P.E.R.T. 3 model for the estimation of road transport emissions, the future of the modeling of transport emissions from C.O.P.E.R.T.3 to A.R.T.E.M.I.S. (assessment and reliability of transport emission models and inventory systems). The interventions were as follow: uncertainties and sensitivity analysis of the C.O.P.E.R.T. 3 model, emissions from road transport in the E.S.C.O.M.P.T.E. programme (study of sensitivity), analysis of sensitivity at the level of temporal aggregation of the spatialized traffic (to evaluate the sensitivity of an inventory at the level of temporal aggregation of traffic data on an important geographic area) application in the case of the I.N.T.E.R.R.E.G. project (Alsace), the road transport part of the regional plan for air quality in Bourgogne taking into account the road network, intercomparison of tools and inventory methods of road transport emissions, evolution of the French automobile park until 2005 and new projections, application of C.O.P.E.R.T. 3 to the French context a new version of I.M.P.A.C.T.- A.D.E.M.E., the European project A.R.T.E.M.I.S. structures novelties considered for the road transport emissions modeling. (N.C.)

  13. Distributed Traffic Control for Reduced Fuel Consumption and Travel Time in Transportation Networks

    Science.gov (United States)

    2018-04-01

    Current technology in traffic control is limited to a centralized approach that has not paid appropriate attention to efficiency of fuel consumption and is subject to the scale of transportation networks. This project proposes a transformative approa...

  14. Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

    Science.gov (United States)

    Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

    2015-01-01

    Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes. PMID:26294903

  15. Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes.

    Science.gov (United States)

    Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

    2015-01-01

    Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

  16. Application of Is-Mp-Ia Model and Taylor Rule to Cesee Economies

    Directory of Open Access Journals (Sweden)

    Josheski Dushko

    2016-06-01

    Full Text Available In this paper, the extended framework of the IS-MP-IA model has been tested. Since the appearance of the Romer’s (2000 model, a bulk of studies with its extensions have been published. Perhaps, the most notable amongst them were those proposed by Hsing (2004, 2013 and Giese and Wagner (2006 - which are integral part of this paper. The application of the extended Romer (2000 model to selected Central Eastern and South Eastern Europe (CESEE countries (Albania, Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Macedonia, Moldova, Romania, Russian Federation, Slovak Republic, Slovenia and Ukraine shows that on an average, higher world output and lower world interest rate and inflation have positive effect on real output. A lower government consumption to gross domestic product (GDP ratio also increases the real output. However, the insignificant government consumption implies that the Ricardian equivalence might hold in these economies. Hence, fiscal prudence is needed, and the conventional approach of real currency depreciation, in order to stimulate exports and raise real output, is not recommendable for the selected CESEE countries. The results from this paper can be useful for the policymakers and the academia. They prove the theoretical and empirical value of the Romer’s IS-MP-IA model. From a methodological point of view, we use generalised method of moments (GMM estimator for dynamic panel data models, that is, first-differenced GMM.

  17. Study on a method for estimating fuel consumption in a seaway

    DEFF Research Database (Denmark)

    Iseki, Toshio; Nielsen, Ulrik Dam

    2013-01-01

    direction has a great influence on the main engine horse power and fuel consumption, and also shows a possibility of fuel efficiency prediction. In order to develop an eco-friendly navigation support system, results of Bayesian wave estimation are applied to fuel efficiency prediction. The Bayesian method...

  18. Energy Consumption, Economic Growth and CO2 Emissions: Evidence from Panel Data for MENA Region

    Directory of Open Access Journals (Sweden)

    Sahbi Farhani

    2012-01-01

    Full Text Available Energy plays a vital role in economic development. It performs a key for sustainable development. Hence, many studies have attempted to look for the direction of causality between energy consumption (EC, economic growth (GDP and CO2 emissions. This paper, therefore, applies the panel unit root tests, panel cointegration methods and panel causality test to investigate the relationship between EC, GDP and CO2 emissions for 15 MENA countries covering the annual period 1973-2008. The finding of this study reveals that there is no causal link between GDP and EC; and between CO2 emissions and EC in the short run. However, in the long run, there is a unidirectional causality running from GDP and CO2 emissions to EC. In addition, to deal with the heterogeneity in countries and the endogeneity bias in regressors, this paper applies respectively the FMOLS and the DOLS approach to estimate the long-run relationship between these three factors.

  19. Causal relationships between energy consumption, foreign direct investment and economic growth: Fresh evidence from dynamic simultaneous-equations models

    International Nuclear Information System (INIS)

    Omri, Anis; Kahouli, Bassem

    2014-01-01

    This paper examines the interrelationships between energy consumption, foreign direct investment and economic growth using dynamic panel data models in simultaneous-equations for a global panel consisting of 65 countries. The time component of our dataset is 1990–2011 inclusive. To make the panel data analysis more homogenous, we also investigate this interrelationship for a number of sub-panels which are constructed based on the income level of countries. In this way, we end up with three income panels; namely, high income, middle income, and low income panels. In the empirical part, we draw on the growth theory and augment the classical growth model, which consists of capital stock, labor force and inflation, with foreign direct investment and energy. Generally, we show mixed results about the interrelationship between energy consumption, FDI and economic growth. - Highlights: • We examine the energy–FDI–growth nexus for a global panel of 65 countries. • Dynamic simultaneous-equation panel data models are used to address this issue. • We also investigate this nexus for three sub-panels which are constructed based on the income level of countries. • We show mixed results about the interrelationship between the three variables

  20. A Fuel-Based Assessment of On-Road and Off-Road Mobile Source Emission Trends

    Science.gov (United States)

    Dallmann, T. R.; Harley, R. A.

    2009-12-01

    Mobile sources contribute significantly to emissions of nitrogen oxides (NOx) and fine particulate matter (PM2.5) in the United States. These emissions lead to a variety of environmental concerns including adverse human health effects and climate change. In the electric power sector, sulfur dioxide (SO2) and NOx emissions from power plants are measured directly using continuous emission monitoring systems. In contrast for mobile sources, statistical models are used to estimate average emissions from a very large and diverse population of engines. Despite much effort aimed at improving them, mobile source emission inventories continue to have large associated uncertainties. Alternate methods are needed to help evaluate estimates of mobile source emissions and quantify and reduce the associated uncertainties. In this study, a fuel-based approach is used to estimate emissions from mobile sources, including on-road and off-road gasoline and diesel engines. In this approach, engine activity is measured by fuel consumed (in contrast EPA mobile source emission models are based on vehicle km of travel and total amount of engine work output for on-road and off-road engines, respectively). Fuel consumption is defined in this study based on highway fuel tax reports for on-road engines, and from surveys of fuel wholesalers who sell tax-exempt diesel fuel for use in various off-road sectors such as agriculture, construction, and mining. Over the decade-long time period (1996-2006) that is the focus of the present study, national sales of taxable gasoline and diesel fuel intended for on-road use increased by 15 and 43%, respectively. Diesel fuel use by off-road equipment increased by about 20% over the same time period. Growth in fuel consumption offset some of the reductions in pollutant emission factors that occurred during this period. This study relies on in-use measurements of mobile source emission factors, for example from roadside and tunnel studies, remote sensing, and

  1. Modeling the highway transportation of spent fuel

    International Nuclear Information System (INIS)

    Harrison, I.G.

    1986-01-01

    There will be a substantial increase in the number of spent fuel shipments on the nation's highway system in the next thirty years. Most of the spent fuel will be moving from reactors to a spent fuel repository. This study develops two models that evaluate the risk and cost of moving the spent fuel. The Minimum Total Transport Risk Model (MTTRM) seeks an efficient solution for this problem by finding the minimum risk path through the network and sending all the spent fuel shipments over this one path. The Equilibrium Transport Risk Model (ETRM) finds an equitable solution by distributing the shipments over a number of paths in the network. This model decreases the risk along individual paths, but increases society's risk because the spent fuel shipments are traveling over more links in the network. The study finds that there is a trade off between path risk and societal risk. As path risk declines, societal risk rises. The cost of shipping also increases as the number of paths expand. The cost and risk of shipping spent fuel from ten reactors to four potential repository sites are evaluated using the MTTRM. The temporary monitored retrievable storage (MRS) facility in Tennessee is found to be the minimum cost and minimum risk solution. When direct shipment to the permanent sites is considered, Deaf Smith, Texas is the least cost and least incident free transport risk location. Yucca Mountain, Nevada is the least risk location when the focus is placed on the potential consequences of an accident

  2. GHG emissions inventory for on-road transportation in the town of Sassari (Sardinia, Italy)

    Science.gov (United States)

    Sanna, Laura; Ferrara, Roberto; Zara, Pierpaolo; Duce, Pierpaolo

    2016-04-01

    The IPCC Fifth Assessment Report (AR5) accounts an increase of the total annual anthropogenic GHG emissions between 2000 and 2010 that directly came from the transport sector. In 2010, 14% of GHG emissions were released by transport and fossil-fuel-related CO2 emissions reached about 32 GtCO2 per year. The report also considers adaptation and mitigation as complementary strategies for reducing the risks of climate change for sustainable development of urban areas. This paper describes the on-road traffic emission estimated in the framework of a Sardinian regional project [1] for the town of Sassari (Sardinia, Italy), one of the Sardinian areas where the fuel consumption for on-road transportation purposes is higher [2]. The GHG emissions have been accounted (a) by a calculation-based methodology founded on a linear relationship between source activity and emission, and (b) by the COPERT IV methodology through the EMITRA (EMIssions from road TRAnsport) software tool [3]. Inventory data for annual fossil fuel consumption associated with on-road transportation (diesel, gasoline, gas) have been collected through the Dogane service, the ATP and ARST public transport services and vehicle fleet data are available from the Public Vehicle Database (PRA), using 2010 as baseline year. During this period, the estimated CO2 emissions accounts for more than 180,000 tCO2. The calculation of emissions due to on-road transport quantitatively estimates CO2 and other GHG emissions and represents a useful baseline to identify possible adaptation and mitigation strategies to face the climate change risks at municipal level. Acknowledgements This research was funded by the Sardinian Regional Project "Development, functional checking and setup of an integrated system for the quantification of CO2 net exchange and for the evaluation of mitigation strategies at urban and territorial scale", (Legge Regionale 7 agosto 2007, No. 7). References [1] Sanna L., Ferrara R., Zara P. & Duce P. (2014

  3. Quasi-three dimensional dynamic modeling of a proton exchange membrane fuel cell with consideration of two-phase water transport through a gas diffusion layer

    International Nuclear Information System (INIS)

    Kang, Sanggyu

    2015-01-01

    Water management is one of the challenging issues for low-temperature PEMFCs (proton exchange membrane fuel cells). When liquid water is formed at the GDL (gas diffusion layer), the pathway of reactant gas can be blocked, which inhibits the electrochemical reaction of PEMFC. Thus, liquid water transport through GDL is a critical factor determining the performance of a PEMFC. In present study, quasi-three dimensional dynamic modeling of PEMFC with consideration of two-phase water transport through GDL is developed. To investigate the distributions of PEMFC characteristics, including current density, species mole fraction, and membrane hydration, the PEMFC was discretized into twenty control volumes along the anode channel. To resolve the mass and energy conservation, the PEMFC is discretized into eleven and fifteen control volumes in the perpendicular direction, respectively. The dynamic variation of PEMFC characteristics of cell voltage, overvoltage of activation and ohmic, liquid water saturation through a GDL, and oxygen concentration were captured during transient behavior. - Highlights: • A quasi-three dimensional two-phase dynamic model of PEMFC is developed. • Presented model is validated by comparison with experimental data. • Two-phase model is compared with one-phase model at steady-states and transients.

  4. Parameter Estimation of Spacecraft Fuel Slosh Model

    Science.gov (United States)

    Gangadharan, Sathya; Sudermann, James; Marlowe, Andrea; Njengam Charles

    2004-01-01

    Fuel slosh in the upper stages of a spinning spacecraft during launch has been a long standing concern for the success of a space mission. Energy loss through the movement of the liquid fuel in the fuel tank affects the gyroscopic stability of the spacecraft and leads to nutation (wobble) which can cause devastating control issues. The rate at which nutation develops (defined by Nutation Time Constant (NTC can be tedious to calculate and largely inaccurate if done during the early stages of spacecraft design. Pure analytical means of predicting the influence of onboard liquids have generally failed. A strong need exists to identify and model the conditions of resonance between nutation motion and liquid modes and to understand the general characteristics of the liquid motion that causes the problem in spinning spacecraft. A 3-D computerized model of the fuel slosh that accounts for any resonant modes found in the experimental testing will allow for increased accuracy in the overall modeling process. Development of a more accurate model of the fuel slosh currently lies in a more generalized 3-D computerized model incorporating masses, springs and dampers. Parameters describing the model include the inertia tensor of the fuel, spring constants, and damper coefficients. Refinement and understanding the effects of these parameters allow for a more accurate simulation of fuel slosh. The current research will focus on developing models of different complexity and estimating the model parameters that will ultimately provide a more realistic prediction of Nutation Time Constant obtained through simulation.

  5. Use of fatal real-life crashes to analyze a safe road transport system model, including the road user, the vehicle, and the road.

    Science.gov (United States)

    Stigson, Helena; Krafft, Maria; Tingvall, Claes

    2008-10-01

    To evaluate if the Swedish Road Administration (SRA) model for a safe road transport system, which includes the interaction between the road user, the vehicle, and the road, could be used to classify fatal car crashes according to some safety indicators. Also, to present a development of the model to better identify system weakness. Real-life crashes with a fatal outcome were classified according to the vehicle's safety rating by Euro NCAP (European Road Assessment Programme) and fitment of ESC (Electronic Stability Control). For each crash, the road was also classified according to EuroRAP (European Road Assessment Programme) criteria, and human behavior in terms of speeding, seat belt use, and driving under the influence of alcohol. Each crash was compared with the model criteria, to identify components that might have contributed to fatal outcome. All fatal crashes where a car occupant was killed that occurred in Sweden during 2004 were included: in all, 215 crashes with 248 fatalities. The data were collected from the in-depth fatal crash data of the Swedish Road Administration (SRA). It was possible to classify 93% of the fatal car crashes according to the SRA model. A number of shortcomings in the criteria were identified since the model did not address rear-end or animal collisions or collisions with stationary/parked vehicles or trailers (18 out of 248 cases). Using the further developed model, it was possible to identify that most of the crashes occurred when two or all three components interacted (in 85 of the total 230 cases). Noncompliance with safety criteria for the road user, the vehicle, and the road led to fatal outcome in 43, 27, and 75 cases, respectively. The SRA model was found to be useful for classifying fatal crashes but needs to be further developed to identify how the components interact and thereby identify weaknesses in the road traffic system. This developed model might be a tool to systematically identify which of the components are

  6. Competitiveness in Road Transport

    DEFF Research Database (Denmark)

    Borgström, Benedikte; Gammelgaard, Britta; Bruun, Poul

    Road transport is an important sector, connecting time and space of production and consumption. Its market conditions has changed. The EU single market implementation has increased price pressure due to supply of low cost road freight transport from counties with lower cost structures. Changes...... in the market also encourage strategic development of some road hauliers into providers of unique services. Such road haulier strategic development contributes to efficiency and effectiveness in basically all business sectors of EU. Little research is available of such strategic and operational management....... In this paper we will explore that knowledge gap and analyze what value proposition(s) and capabilities can transform potential cost disadvantages of acting in a market that includes both high- and low-cost-country actors? And in conceptual terminology, how are capabilities deployed and developed to construct...

  7. Model Year 2017 Fuel Economy Guide: EPA Fuel Economy Estimates

    Energy Technology Data Exchange (ETDEWEB)

    None

    2016-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles.

  8. Model Year 2012 Fuel Economy Guide: EPA Fuel Economy Estimates

    Energy Technology Data Exchange (ETDEWEB)

    None

    2011-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles.

  9. Model Year 2013 Fuel Economy Guide: EPA Fuel Economy Estimates

    Energy Technology Data Exchange (ETDEWEB)

    None

    2012-12-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles.

  10. Model Year 2011 Fuel Economy Guide: EPA Fuel Economy Estimates

    Energy Technology Data Exchange (ETDEWEB)

    None

    2010-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles.

  11. Model Year 2018 Fuel Economy Guide: EPA Fuel Economy Estimates

    Energy Technology Data Exchange (ETDEWEB)

    None

    2017-12-07

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles.

  12. Fuel Cell System for Transportation -- 2005 Cost Estimate

    Energy Technology Data Exchange (ETDEWEB)

    Wheeler, D.

    2006-10-01

    Independent review report of the methodology used by TIAX to estimate the cost of producing PEM fuel cells using 2005 cell stack technology. The U.S. Department of Energy (DOE) Hydrogen, Fuel Cells and Infrastructure Technologies Program Manager asked the National Renewable Energy Laboratory (NREL) to commission an independent review of the 2005 TIAX cost analysis for fuel cell production. The NREL Systems Integrator is responsible for conducting independent reviews of progress toward meeting the DOE Hydrogen Program (the Program) technical targets. An important technical target of the Program is the proton exchange membrane (PEM) fuel cell cost in terms of dollars per kilowatt ($/kW). The Program's Multi-Year Program Research, Development, and Demonstration Plan established $125/kW as the 2005 technical target. Over the last several years, the Program has contracted with TIAX, LLC (TIAX) to produce estimates of the high volume cost of PEM fuel cell production for transportation use. Since no manufacturer is yet producing PEM fuel cells in the quantities needed for an initial hydrogen-based transportation economy, these estimates are necessary for DOE to gauge progress toward meeting its targets. For a PEM fuel cell system configuration developed by Argonne National Laboratory, TIAX estimated the total cost to be $108/kW, based on assumptions of 500,000 units per year produced with 2005 cell stack technology, vertical integration of cell stack manufacturing, and balance-of-plant (BOP) components purchased from a supplier network. Furthermore, TIAX conducted a Monte Carlo analysis by varying ten key parameters over a wide range of values and estimated with 98% certainty that the mean PEM fuel cell system cost would be below DOE's 2005 target of $125/kW. NREL commissioned DJW TECHNOLOGY, LLC to form an Independent Review Team (the Team) of industry fuel cell experts and to evaluate the cost estimation process and the results reported by TIAX. The results of

  13. Dynamics of intermodal logistical systems on containerisation and road transportation in Durban, South Africa

    Directory of Open Access Journals (Sweden)

    Nerissa Govender

    2014-12-01

    Full Text Available The underlying port operations in Durban, South Africa, epitomise intense global competitiveness in the intermodal logistics chain. The link between containerisation and theroad transport network can falter as a result of the dynamics of the logistics system. The main objective of the study was to establish the extent of the intermodal challenges of logistical systems on containerisation to which the role of intermodal sea–road freight transportation enhances the logistical competitiveness. It further examined the intermodal relationship on containerised freight between the challenges of containerisation processes and the effects on road freight transport mode. The impact of containerisation on intermodalism, the sea–road freight transport network and the technological attributes of security-based systems and logistical tracking protocols influence the systematic movement of containers on Durban’s public roads.

  14. Panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable

    NARCIS (Netherlands)

    Elhorst, J. Paul

    2001-01-01

    This paper surveys panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable. In particular, it focuses on the specification and estimation of four panel data models commonly used in applied research: the fixed effects model, the random effects model, the

  15. An innovative multivariate tool for fuel consumption and costs estimation of agricultural operations

    Directory of Open Access Journals (Sweden)

    Mirko Guerrieri

    2016-12-01

    Full Text Available The estimation of operating costs of agricultural and forestry machineries is a key factor in both planning agricultural policies and farm management. Few works have tried to estimate operating costs and the produced models are normally based on deterministic approaches. Conversely, in the statistical model randomness is present and variable states are not described by unique values, but rather by probability distributions. In this study, for the first time, a multivariate statistical model based on Partial Least Squares (PLS was adopted to predict the fuel consumption and costs of six agricultural operations such as: ploughing, harrowing, fertilization, sowing, weed control and shredding. The prediction was conducted on two steps: first of all few initial selected parameters (time per surface-area unit, maximum engine power, purchase price of the tractor and purchase price of the operating machinery were used to estimate the fuel consumption; then the predicted fuel consumption together with the initial parameters were used to estimate the operational costs. Since the obtained models were based on an input dataset very heterogeneous, these resulted to be extremely efficient and so generalizable and robust. In details the results show prediction values in the test with r always ≥ 0.91. Thus, the approach may results extremely useful for both farmers (in terms of economic advantages and at institutional level (representing an innovative and efficient tool for planning future Rural Development Programmes and the Common Agricultural Policy. In light of these advantages the proposed approach may as well be implemented on a web platform and made available to all the stakeholders.

  16. An innovative multivariate tool for fuel consumption and costs estimation of agricultural operations

    International Nuclear Information System (INIS)

    Guerrieri, M.; Fedrizzi, M.; Antonucci, F.; Pallottino, F.; Sperandio, G.; Pagano, M.; Figorilli, S.; Menesatti, P.; Costa, C.

    2016-01-01

    The estimation of operating costs of agricultural and forestry machineries is a key factor in both planning agricultural policies and farm management. Few works have tried to estimate operating costs and the produced models are normally based on deterministic approaches. Conversely, in the statistical model randomness is present and variable states are not described by unique values, but rather by probability distributions. In this study, for the first time, a multivariate statistical model based on Partial Least Squares (PLS) was adopted to predict the fuel consumption and costs of six agricultural operations such as: ploughing, harrowing, fertilization, sowing, weed control and shredding. The prediction was conducted on two steps: first of all few initial selected parameters (time per surface-area unit, maximum engine power, purchase price of the tractor and purchase price of the operating machinery) were used to estimate the fuel consumption; then the predicted fuel consumption together with the initial parameters were used to estimate the operational costs. Since the obtained models were based on an input dataset very heterogeneous, these resulted to be extremely efficient and so generalizable and robust. In details the results show prediction values in the test with r always ≥ 0.91. Thus, the approach may results extremely useful for both farmers (in terms of economic advantages) and at institutional level (representing an innovative and efficient tool for planning future Rural Development Programmes and the Common Agricultural Policy). In light of these advantages the proposed approach may as well be implemented on a web platform and made available to all the stakeholders.

  17. An innovative multivariate tool for fuel consumption and costs estimation of agricultural operations

    Energy Technology Data Exchange (ETDEWEB)

    Guerrieri, M.; Fedrizzi, M.; Antonucci, F.; Pallottino, F.; Sperandio, G.; Pagano, M.; Figorilli, S.; Menesatti, P.; Costa, C.

    2016-07-01

    The estimation of operating costs of agricultural and forestry machineries is a key factor in both planning agricultural policies and farm management. Few works have tried to estimate operating costs and the produced models are normally based on deterministic approaches. Conversely, in the statistical model randomness is present and variable states are not described by unique values, but rather by probability distributions. In this study, for the first time, a multivariate statistical model based on Partial Least Squares (PLS) was adopted to predict the fuel consumption and costs of six agricultural operations such as: ploughing, harrowing, fertilization, sowing, weed control and shredding. The prediction was conducted on two steps: first of all few initial selected parameters (time per surface-area unit, maximum engine power, purchase price of the tractor and purchase price of the operating machinery) were used to estimate the fuel consumption; then the predicted fuel consumption together with the initial parameters were used to estimate the operational costs. Since the obtained models were based on an input dataset very heterogeneous, these resulted to be extremely efficient and so generalizable and robust. In details the results show prediction values in the test with r always ≥ 0.91. Thus, the approach may results extremely useful for both farmers (in terms of economic advantages) and at institutional level (representing an innovative and efficient tool for planning future Rural Development Programmes and the Common Agricultural Policy). In light of these advantages the proposed approach may as well be implemented on a web platform and made available to all the stakeholders.

  18. Lead emissions from road transport in Europe. A revision of current estimates using various estimation methodologies

    NARCIS (Netherlands)

    Denier van der Gon, H.A.C.; Appelman, W.

    2009-01-01

    Large-scale use of leaded gasoline was an important source of the neurotoxin lead in the European environment. After a sequence of regulations on the allowed gasoline lead content and, eventually, a ban on the use of lead additives in gasoline, road transport was no longer considered a source of

  19. Reduction of Fuel Consumption and Exhaust Pollutant Using Intelligent Transport Systems

    Directory of Open Access Journals (Sweden)

    Mostofa Kamal Nasir

    2014-01-01

    Full Text Available Greenhouse gas emitted by the transport sector around the world is a serious issue of concern. To minimize such emission the automobile engineers have been working relentlessly. Researchers have been trying hard to switch fossil fuel to alternative fuels and attempting to various driving strategies to make traffic flow smooth and to reduce traffic congestion and emission of greenhouse gas. Automobile emits a massive amount of pollutants such as Carbon Monoxide (CO, hydrocarbons (HC, carbon dioxide (CO2, particulate matter (PM, and oxides of nitrogen (NOx. Intelligent transport system (ITS technologies can be implemented to lower pollutant emissions and reduction of fuel consumption. This paper investigates the ITS techniques and technologies for the reduction of fuel consumption and minimization of the exhaust pollutant. It highlights the environmental impact of the ITS application to provide the state-of-art green solution. A case study also advocates that ITS technology reduces fuel consumption and exhaust pollutant in the urban environment.

  20. Reduction of fuel consumption and exhaust pollutant using intelligent transport systems.

    Science.gov (United States)

    Nasir, Mostofa Kamal; Md Noor, Rafidah; Kalam, M A; Masum, B M

    2014-01-01

    Greenhouse gas emitted by the transport sector around the world is a serious issue of concern. To minimize such emission the automobile engineers have been working relentlessly. Researchers have been trying hard to switch fossil fuel to alternative fuels and attempting to various driving strategies to make traffic flow smooth and to reduce traffic congestion and emission of greenhouse gas. Automobile emits a massive amount of pollutants such as Carbon Monoxide (CO), hydrocarbons (HC), carbon dioxide (CO2), particulate matter (PM), and oxides of nitrogen (NO x ). Intelligent transport system (ITS) technologies can be implemented to lower pollutant emissions and reduction of fuel consumption. This paper investigates the ITS techniques and technologies for the reduction of fuel consumption and minimization of the exhaust pollutant. It highlights the environmental impact of the ITS application to provide the state-of-art green solution. A case study also advocates that ITS technology reduces fuel consumption and exhaust pollutant in the urban environment.

  1. Reduction of Fuel Consumption and Exhaust Pollutant Using Intelligent Transport Systems

    Science.gov (United States)

    Nasir, Mostofa Kamal; Md Noor, Rafidah; Kalam, M. A.; Masum, B. M.

    2014-01-01

    Greenhouse gas emitted by the transport sector around the world is a serious issue of concern. To minimize such emission the automobile engineers have been working relentlessly. Researchers have been trying hard to switch fossil fuel to alternative fuels and attempting to various driving strategies to make traffic flow smooth and to reduce traffic congestion and emission of greenhouse gas. Automobile emits a massive amount of pollutants such as Carbon Monoxide (CO), hydrocarbons (HC), carbon dioxide (CO2), particulate matter (PM), and oxides of nitrogen (NOx). Intelligent transport system (ITS) technologies can be implemented to lower pollutant emissions and reduction of fuel consumption. This paper investigates the ITS techniques and technologies for the reduction of fuel consumption and minimization of the exhaust pollutant. It highlights the environmental impact of the ITS application to provide the state-of-art green solution. A case study also advocates that ITS technology reduces fuel consumption and exhaust pollutant in the urban environment. PMID:25032239

  2. A Price Index Model for Road Freight Transportation and Its Empirical analysis in China

    Directory of Open Access Journals (Sweden)

    Liu Zhishuo

    2017-01-01

    Full Text Available The aim of price index for road freight transportation (RFT is to reflect the changes of price in the road transport market. Firstly, a price index model for RFT based on the sample data from Alibaba logistics platform is built. This model is a three levels index system including total index, classification index and individual index and the Laspeyres method is applied to calculate these indices. Finally, an empirical analysis of the price index for RFT market in Zhejiang Province is performed. In order to demonstrate the correctness and validity of the exponential model, a comparative analysis with port throughput and PMI index is carried out.

  3. Application of an Intelligent Fuzzy Regression Algorithm in Road Freight Transportation Modeling

    Directory of Open Access Journals (Sweden)

    Pooya Najaf

    2013-07-01

    Full Text Available Road freight transportation between provinces of a country has an important effect on the traffic flow of intercity transportation networks. Therefore, an accurate estimation of the road freight transportation for provinces of a country is so crucial to improve the rural traffic operation in a large scale management. Accordingly, the focused case study database in this research is the information related to Iran’s provinces in the year 2008. Correlation between road freight transportation with variables such as transport cost and distance, population, average household income and Gross Domestic Product (GDP of each province is calculated. Results clarify that the population is the most effective factor in the prediction of provinces’ transported freight. Linear Regression Model (LRM is calibrated based on the population variable, and afterwards Fuzzy Regression Algorithm (FRA is generated on the basis of the LRM. The proposed FRA is an intelligent modified algorithm with an accurate prediction and fitting ability. This methodology can be significantly useful in macro-level planning problems where decreasing prediction error values is one of the most important concerns for decision makers. In addition, Back-Propagation Neural Network (BPNN is developed to evaluate the prediction capability of the models and to be compared with FRA. According to the final results, the modified FRA estimates road freight transportation values more accurately than the BPNN and LRM. Finally, in order to predict the road freight transportation values, the reliability of the calibrated models is analyzed using the information of the year 2009. Results show higher reliability for the proposed modified FRA.

  4. Transport fuel demand responses to fuel price and income projections : Comparison of integrated assessment models

    NARCIS (Netherlands)

    Edelenbosch, O. Y.; van Vuuren, Detlef; Bertram, C.; Carrara, S.; Emmerling, J.; Daly, H.; Kitous, A.; McCollum, D. L.; Saadi Failali, N.

    Income and fuel price pathways are key determinants in projections of the energy system in integrated assessment models. In recent years, more details have been added to the transport sector representation in these models. To better understand the model dynamics, this manuscript analyses transport

  5. A model of integration among prediction tools: applied study to road freight transportation

    Directory of Open Access Journals (Sweden)

    Henrique Dias Blois

    Full Text Available Abstract This study has developed a scenery analysis model which has integrated decision-making tools on investments: prospective scenarios (Grumbach Method and systems dynamics (hard modeling, with the innovated multivariate analysis of experts. It was designed through analysis and simulation scenarios and showed which are the most striking events in the study object as well as highlighted the actions could redirect the future of the analyzed system. Moreover, predictions are likely to be developed through the generated scenarios. The model has been validated empirically with road freight transport data from state of Rio Grande do Sul, Brazil. The results showed that the model contributes to the analysis of investment because it identifies probabilities of events that impact on decision making, and identifies priorities for action, reducing uncertainties in the future. Moreover, it allows an interdisciplinary discussion that correlates different areas of knowledge, fundamental when you wish more consistency in creating scenarios.

  6. The Road Transport world exhibition in Paris

    International Nuclear Information System (INIS)

    Anon.

    1995-01-01

    Following the agreement between French and German professionals of automobile and industrial vehicle, the Road Transport world exhibition will take place alternatively in Paris and Hanover. The 1995 meeting has taken place in Paris (September 15-21) and about 20 countries were represented. Road transport is the principal way of goods transportation in France and represent 88% of the traffic explained in tons gross and 70% in tons km. The petroleum dependence of the transportation sector is becoming a worrying problem as the gasoline and diesel fuels taxes will be discussed in the 1996 financial laws project. According to the last ''Worldwide energetic perspectives'' report published by the IEA, in 2010 the transportation sector could absorb more than 60% of the worldwide petroleum consumption. This increase represents a challenge to the petroleum industry to increase the energetic efficiency of the vehicle fuels and the production of diesel fuels, and conversely to reduce the pollution effluents. (J.S.). 4 tabs

  7. Alternative Fuels Data Center: Biodiesel Truck Transports Capitol Christmas

    Science.gov (United States)

    Tree Biodiesel Truck Transports Capitol Christmas Tree to someone by E-mail Share Alternative Fuels Data Center: Biodiesel Truck Transports Capitol Christmas Tree on Facebook Tweet about Alternative Fuels Data Center: Biodiesel Truck Transports Capitol Christmas Tree on Twitter Bookmark Alternative

  8. A Panel Data Model for Subjective Information on Household Income Growth

    NARCIS (Netherlands)

    Das, J.W.M.; van Soest, A.H.O.

    1996-01-01

    Subjective expectations about future income changes are analyzed, using household panel data.The models used are extensions of existing binary choice panel data models to the case of ordered response.We consider both random and fixed individual effects.The random effects model is estimated by

  9. The nexus between carbon emissions, energy consumption and economic growth in Middle East countries: A panel data analysis

    International Nuclear Information System (INIS)

    Ozcan, Burcu

    2013-01-01

    The environmental Kuznets curve (EKC) hypothesis assumes that there is an inverted U-shaped relationship between environmental degradation and income per capita. In other words, as a country grows, it is assumed that its environmental quality improves. In this study, we aim to test the EKC hypothesis for 12 Middle East countries during the period 1990–2008 by employing recently developed panel data methods. Our results provide evidence contrary to the EKC hypothesis. We found evidence favorable to the U-shaped EKC for 5 Middle East countries, whereas an inverted U-shaped curve was identified for only 3 Middle East countries. Furthermore, there appear to be no causal links between income and CO 2 emissions for the other 4 countries. Regarding the direction of causality, there appears to be a unidirectional causality from economic growth to energy consumption in the short-run; in the long-run, however, the unidirectional causality chain runs from energy consumption and economic growth to CO 2 emissions. We also suggest some crucial policy implications depending on these results. - Highlights: • The relationship between CO 2 emissions, energy consumption, and growth is examined. • Panel data estimation methods are used for 12 Middle East countries. • We obtain a U-shaped curve contrary to the EKC hypothesis. • The causality runs from economic growth to energy consumption in the short-run. • In the long-run, causality runs from energy consumption and growth to CO 2 emissions

  10. Modeling near-road air quality using a computational fluid dynamics model, CFD-VIT-RIT.

    Science.gov (United States)

    Wang, Y Jason; Zhang, K Max

    2009-10-15

    It is well recognized that dilution is an important mechanism governing the near-road air pollutant concentrations. In this paper, we aim to advance our understanding of turbulent mixing mechanisms on and near roadways using computation fluid dynamics. Turbulent mixing mechanisms can be classified into three categories according to their origins: vehicle-induced turbulence (VIT), road-induced turbulence (RIT), and atmospheric boundary layer turbulence. RIT includes the turbulence generated by road embankment, road surface thermal effects, and roadside structures. Both VIT and RIT are affected by the roadway designs. We incorporate the detailed treatment of VIT and RIT into the CFD (namely CFD-VIT-RIT) and apply the model in simulating the spatial gradients of carbon monoxide near two major highways with different traffic mix and roadway configurations. The modeling results are compared to the field measurements and those from CALINE4 and CFD without considering VIT and RIT. We demonstrate that the incorporation of VIT and RIT considerably improves the modeling predictions, especially on vertical gradients and seasonal variations of carbon monoxide. Our study implies that roadway design can significantly influence the near-road air pollution. Thus we recommend that mitigating near-road air pollution through roadway designs be considered in the air quality and transportation management In addition, thanks to the rigorous representation of turbulent mixing mechanisms, CFD-VIT-RIT can become valuable tools in the roadway designs process.

  11. Development of a Trip Energy Estimation Model Using Real-World Global Positioning System Driving Data: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Holden, Jacob [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wood, Eric W [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhu, Lei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Gonder, Jeffrey D [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Tian, Ye [Metropia, Inc.

    2017-09-15

    A data-driven technique for estimation of energy requirements for a proposed vehicle trip has been developed. Based on over 700,000 miles of driving data, the technique has been applied to generate a model that estimates trip energy requirements. The model uses a novel binning approach to categorize driving by road type, traffic conditions, and driving profile. The trip-level energy estimations can easily be aggregated to any higher-level transportation system network desired. The model has been tested and validated on the Austin, Texas, data set used to build this model. Ground-truth energy consumption for the data set was obtained from Future Automotive Systems Technology Simulator (FASTSim) vehicle simulation results. The energy estimation model has demonstrated 12.1 percent normalized total absolute error. The energy estimation from the model can be used to inform control strategies in routing tools, such as change in departure time, alternate routing, and alternate destinations, to reduce energy consumption. The model can also be used to determine more accurate energy consumption of regional or national transportation networks if trip origin and destinations are known. Additionally, this method allows the estimation tool to be tuned to a specific driver or vehicle type.

  12. Bayesian Data Assimilation for Improved Modeling of Road Traffic

    NARCIS (Netherlands)

    Van Hinsbergen, C.P.Y.

    2010-01-01

    This thesis deals with the optimal use of existing models that predict certain phenomena of the road traffic system. Such models are extensively used in Advanced Traffic Information Systems (ATIS), Dynamic Traffic Management (DTM) or Model Predictive Control (MPC) approaches in order to improve the

  13. The Dynamics of Franchise Contracting: Evidence from Panel Data

    OpenAIRE

    Francine Lafontaine; Kathryn L. Shaw

    1996-01-01

    In this paper, we model the determinants of franchise contract terms, namely royalty rates and franchise fees, using a unique panel data set of about 1000 franchisors for the period 1980-1992. We focus on the extent to which firms adjust the terms of their contracts as they become better established, and find that adjustment is relatively infrequent and that firms do not systematically raise or lower their royalty rates or franchise fees when they do adjust them. These results tend to refute ...

  14. Field Measurement and Calibration of HDM-4 Fuel Consumption Model on Interstate Highway in Florida

    Directory of Open Access Journals (Sweden)

    Xin Jiao

    2015-03-01

    Full Text Available Fuel consumptions are measured by operating passenger car and tractor-trailer on two interstate roadway sites in Florida. Each site contains flexible pavement and rigid pavement with similar pavement, traffic and environmental condition. Field test reveals that the average fuel consumption differences between vehicle operating on flexible pavement and rigid pavement at given test condition are 4.04% for tractor-trailer and 2.50% for passenger car, with a fuel saving on rigid pavement. The fuel consumption differences are found statistically significant at 95% confidence level for both vehicle types. Test data are then used to calibrate the Highway Development and Management IV (HDM-4 fuel consumption model and model coefficients are obtained for three sets of observations. Field measurement and prediction by calibrated model shows generally good agreement. Nevertheless, verification and adjustment with more experiment or data sources would be expected in future studies.

  15. OPTIMIZATION METHOD AND SOFTWARE FOR FUEL COST REDUCTION IN CASE OF ROAD TRANSPORT ACTIVITY

    Directory of Open Access Journals (Sweden)

    György Kovács

    2017-06-01

    Full Text Available The transport activity is one of the most expensive processes in the supply chain and the fuel cost is the highest cost among the cost components of transportation. The goal of the research is to optimize the transport costs in case of a given transport task both by the selecting the optimal petrol station and by determining the optimal amount of the refilled fuel. Recently, in practice, these two decisions have not been made centrally at the forwarding company, but they depend on the individual decision of the driver. The aim of this study is to elaborate a precise and reliable mathematical method for selecting the optimal refuelling stations and determining the optimal amount of the refilled fuel to fulfil the transport demands. Based on the elaborated model, new decision-supporting software is developed for the economical fulfilment of transport trips.

  16. Transport Studies and Modeling in PEM Fuel Cells

    Energy Technology Data Exchange (ETDEWEB)

    Mittelsteadt, Cortney K. [Giner, Inc., Auburndale, MA (United States); Xu, Hui [Giner, Inc., Auburndale, MA (United States); Brawn, Shelly [Giner, Inc., Auburndale, MA (United States)

    2014-07-30

    This project’s aim was to develop fuel cell components (i.e. membranes, gas-diffusion media (GDM), bipolar plates and flow fields) that possess specific properties (i.e. water transport and conductivity). A computational fluid dynamics model was developed to elucidate the effect of certain parameters on these specific properties. Ultimately, the model will be used to determine sensitivity of fuel cell performance to component properties to determine limiting components and to guide research. We have successfully reached our objectives and achieved most of the milestones of this project. We have designed and synthesized a variety of hydrocarbon block polymer membranes with lower equivalent weight, structure, chemistry, phase separation and process conditions. These membranes provide a broad selection with optimized water transport properties. We have also designed and constructed a variety of devices that are capable of accurately measuring the water transport properties (water uptake, water diffusivity and electro-osmatic drag) of these membranes. These transport properties are correlated to the membranes’ structures derived from X-ray and microscopy techniques to determine the structure-property relationship. We successfully integrated hydrocarbon membrane MEAs with a current distribution board (CBD) to study the impact of hydrocarbon membrane on water transport in fuel cells. We have designed and fabricated various GDM with varying substrate, diffusivity and micro-porous layers (MPL) and characterized their pore structure, tortuosity and hydrophobicity. We have derived a universal chart (MacMullin number as function of wet proofing and porosity) that can be used to characterize various GDM. The abovementioned GDMs have been evaluated in operating fuel cells; their performance is correlated to various pore structure, tortuosity and hydrophobicity of the GDM. Unfortunately, determining a universal relationship between the MacMullin number and these properties

  17. Off-road vehicle dynamics analysis, modelling and optimization

    CERN Document Server

    Taghavifar, Hamid

    2017-01-01

    This book deals with the analysis of off-road vehicle dynamics from kinetics and kinematics perspectives and the performance of vehicle traversing over rough and irregular terrain. The authors consider the wheel performance, soil-tire interactions and their interface, tractive performance of the vehicle, ride comfort, stability over maneuvering, transient and steady state conditions of the vehicle traversing, modeling the aforementioned aspects and optimization from energetic and vehicle mobility perspectives. This book brings novel figures for the transient dynamics and original wheel terrain dynamics at on-the-go condition.

  18. CO2 emissions, energy consumption and economic growth nexus in MENA countries: Evidence from simultaneous equations models

    International Nuclear Information System (INIS)

    Omri, Anis

    2013-01-01

    This paper examines the nexus between CO 2 emissions, energy consumption and economic growth using simultaneous-equations models with panel data of 14 MENA countries over the period 1990–2011. Our empirical results show that there exists a bidirectional causal relationship between energy consumption and economic growth. However, the results support the occurrence of unidirectional causality from energy consumption to CO 2 emissions without any feedback effects, and there exists a bidirectional causal relationship between economic growth and CO 2 emissions for the region as a whole. The study suggests that environmental and energy policies should recognize the differences in the nexus between energy consumption and economic growth in order to maintain sustainable economic growth in the MENA region. - Graphical abstract: Interaction between CO 2 , energy and GDP for MENA countries. - Highlights: • We investigate the energy–environment–GDP nexus for 14 MENA countries. • We have used simultaneous equations models estimated by the GMM-estimator. • Results show bi-directional causal relationship between energy consumption and economic growth. • There is uni-directional causality from energy consumption to CO 2 . • There exists bi-directional causal relationship between economic growth and pollutant emissions

  19. Dynamic Modeling of a Reformed Methanol Fuel Cell System using Empirical Data and Adaptive Neuro-Fuzzy Inference System Models

    DEFF Research Database (Denmark)

    Justesen, Kristian Kjær; Andreasen, Søren Juhl; Shaker, Hamid Reza

    2013-01-01

    In this work, a dynamic MATLAB Simulink model of a H3-350 Reformed Methanol Fuel Cell (RMFC) stand-alone battery charger produced by Serenergy is developed on the basis of theoretical and empirical methods. The advantage of RMFC systems is that they use liquid methanol as a fuel instead of gaseous...... of the reforming process are implemented. Models of the cooling flow of the blowers for the fuel cell and the burner which supplies process heat for the reformer are made. The two blowers have a common exhaust, which means that the two blowers influence each other’s output. The models take this into account using...... an empirical approach. Fin efficiency models for the cooling effect of the air are also developed using empirical methods. A fuel cell model is also implemented based on a standard model which is adapted to fit the measured performance of the H3-350 module. All the individual parts of the model are verified...

  20. Dynamic Modeling of a Reformed Methanol Fuel Cell System using Empirical Data and Adaptive Neuro-Fuzzy Inference System Models

    DEFF Research Database (Denmark)

    Justesen, Kristian Kjær; Andreasen, Søren Juhl; Shaker, Hamid Reza

    2014-01-01

    In this work, a dynamic MATLAB Simulink model of a H3-350 Reformed Methanol Fuel Cell (RMFC) stand-alone battery charger produced by Serenergy is developed on the basis of theoretical and empirical methods. The advantage of RMFC systems is that they use liquid methanol as a fuel instead of gaseous...... of the reforming process are implemented. Models of the cooling flow of the blowers for the fuel cell and the burner which supplies process heat for the reformer are made. The two blowers have a common exhaust, which means that the two blowers influence each other’s output. The models take this into account using...... an empirical approach. Fin efficiency models for the cooling effect of the air are also developed using empirical methods. A fuel cell model is also implemented based on a standard model which is adapted to fit the measured performance of the H3-350 module. All the individual parts of the model are verified...

  1. Macroscopic Modeling of Transport Phenomena in Direct Methanol Fuel Cells

    DEFF Research Database (Denmark)

    Olesen, Anders Christian

    An increasing need for energy efficiency and high energy density has sparked a growing interest in direct methanol fuel cells for portable power applications. This type of fuel cell directly generates electricity from a fuel mixture consisting of methanol and water. Although this technology...... surpasses batteries in important areas, fundamental research is still required to improve durability and performance. Particularly the transport of methanol and water within the cell structure is difficult to study in-situ. A demand therefore exist for the fundamental development of mathematical models...... for studying their transport. In this PhD dissertation the macroscopic transport phenomena governing direct methanol fuel cell operation are analyzed, discussed and modeled using the two-fluid approach in the computational fluid dynamics framework of CFX 14. The overall objective of this work is to extend...

  2. MAARGHA: A Prototype System for Road Condition and Surface Type Estimation by Fusing Multi-Sensor Data

    Directory of Open Access Journals (Sweden)

    Deepak Rajamohan

    2015-07-01

    Full Text Available Road infrastructure in countries like India is expanding at a rapid pace and is becoming increasingly difficult for authorities to identify and fix the bad roads in time. Current Geographical Information Systems (GIS lack information about on-road features like road surface type, speed breakers and dynamic attribute data like the road quality. Hence there is a need to build road monitoring systems capable of collecting such information periodically. Limitations of satellite imagery with respect to the resolution and availability, makes road monitoring primarily an on-field activity. Monitoring is currently performed using special vehicles that are fitted with expensive laser scanners and need skilled resource besides providing only very low coverage. Hence such systems are not suitable for continuous road monitoring. Cheaper alternative systems using sensors like accelerometer and GPS (Global Positioning System exists but they are not equipped to achieve higher information levels. This paper presents a prototype system MAARGHA (MAARGHA in Sanskrit language means an eternal path to solution, which demonstrates that it can overcome the disadvantages of the existing systems by fusing multi-sensory data like camera image, accelerometer data and GPS trajectory at an information level, apart from providing additional road information like road surface type. MAARGHA has been tested across different road conditions and sensor data characteristics to assess its potential applications in real world scenarios. The developed system achieves higher information levels when compared to state of the art road condition estimation systems like Roadroid. The system performance in road surface type classification is dependent on the local environmental conditions at the time of imaging. In our study, the road surface type classification accuracy reached 100% for datasets with near ideal environmental conditions and dropped down to 60% for datasets with shadows and

  3. An Evaluation of Financial Institutions: Impact on Consumption and Investment Using Panel Data and the Theory of Risk-Bearing.

    Science.gov (United States)

    Alem, Mauro; Townsend, Robert M

    2014-11-01

    The theory of the optimal allocation of risk and the Townsend Thai panel data on financial transactions are used to assess the impact of the major formal and informal financial institutions of an emerging market economy. We link financial institution assessment to the actual impact on clients, rather than ratios and non-performing loans. We derive both consumption and investment equations from a common core theory with both risk and productive activities. The empirical specification follows closely from this theory and allows both OLS and IV estimation. We thus quantify the consumption and investment smoothing impact of financial institutions on households including those running farms and small businesses. A government development bank (BAAC) is shown to be particularly helpful in smoothing consumption and investment, in no small part through credit, consistent with its own operating system, which embeds an implicit insurance operation. Commercial banks are smoothing investment, largely through formal savings accounts. Other institutions seem ineffective by these metrics.

  4. An Evaluation of Financial Institutions: Impact on Consumption and Investment Using Panel Data and the Theory of Risk-Bearing*

    Science.gov (United States)

    Alem, Mauro; Townsend, Robert M.

    2013-01-01

    The theory of the optimal allocation of risk and the Townsend Thai panel data on financial transactions are used to assess the impact of the major formal and informal financial institutions of an emerging market economy. We link financial institution assessment to the actual impact on clients, rather than ratios and non-performing loans. We derive both consumption and investment equations from a common core theory with both risk and productive activities. The empirical specification follows closely from this theory and allows both OLS and IV estimation. We thus quantify the consumption and investment smoothing impact of financial institutions on households including those running farms and small businesses. A government development bank (BAAC) is shown to be particularly helpful in smoothing consumption and investment, in no small part through credit, consistent with its own operating system, which embeds an implicit insurance operation. Commercial banks are smoothing investment, largely through formal savings accounts. Other institutions seem ineffective by these metrics. PMID:25400319

  5. Automotive fuel consumption in Brazil. Applying static and dynamic systems of demand equations

    Energy Technology Data Exchange (ETDEWEB)

    Iootty, Mariana [IE-UFRJ (Institute of Economics - Federal University of Rio de Janeiro), Energy Economics Group (Brazil); UFRRJ (Federal Rural University of Rio de Janeiro) (Brazil); Pinto, Helder Jr. [IE-UFRJ (Institute of Economics - Federal University of Rio de Janeiro), Energy Economics Group (Brazil); Ebeling, Francisco [Brazilian Petroleum Institute (Brazil)

    2009-12-15

    This paper aims to investigate and explain the performance of the Brazilian demand for automotive fuels in the period 1970-2005. It estimates the price and income elasticities for all the available fuels in the automotive sector in the country: gasoline, compressed natural gas (CNG), ethanol and diesel. The analysis of the expenditure allocation process among these fuels is carried out through the estimation of a linear approximation of an Almost Ideal Demand System (AIDS) model. Two estimation methods were implemented: the static (through a seemingly unrelated regression) and a dynamic (through a vector error correction model). Specification tests support the use of the latter. The empirical analysis suggests a high substitutability between gasoline and ethanol; being this relation higher than the one observed between gasoline and CNG. The study shows that gasoline, ethanol and diesel are normal goods, and with the exception of ethanol, they are expenditure elastic. CNG was estimated as an inferior good. (author)

  6. Automotive fuel consumption in Brazil. Applying static and dynamic systems of demand equations

    International Nuclear Information System (INIS)

    Iootty, Mariana; Pinto, Helder Jr.; Ebeling, Francisco

    2009-01-01

    This paper aims to investigate and explain the performance of the Brazilian demand for automotive fuels in the period 1970-2005. It estimates the price and income elasticities for all the available fuels in the automotive sector in the country: gasoline, compressed natural gas (CNG), ethanol and diesel. The analysis of the expenditure allocation process among these fuels is carried out through the estimation of a linear approximation of an Almost Ideal Demand System (AIDS) model. Two estimation methods were implemented: the static (through a seemingly unrelated regression) and a dynamic (through a vector error correction model). Specification tests support the use of the latter. The empirical analysis suggests a high substitutability between gasoline and ethanol; being this relation higher than the one observed between gasoline and CNG. The study shows that gasoline, ethanol and diesel are normal goods, and with the exception of ethanol, they are expenditure elastic. CNG was estimated as an inferior good. (author)

  7. Wildland fire emissions, carbon, and climate: Modeling fuel consumption

    Science.gov (United States)

    Roger D. Ottmar

    2014-01-01

    Fuel consumption specifies the amount of vegetative biomass consumed during wildland fire. It is a two-stage process of pyrolysis and combustion that occurs simultaneously and at different rates depending on the characteristics and condition of the fuel, weather, topography, and in the case of prescribed fire, ignition rate and pattern. Fuel consumption is the basic...

  8. Model Year 2015 Fuel Economy Guide: EPA Fuel Economy Estimates

    Energy Technology Data Exchange (ETDEWEB)

    None

    2014-12-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  9. Model Year 2009 Fuel Economy Guide: EPA Fuel Economy Estimates

    Energy Technology Data Exchange (ETDEWEB)

    None

    2008-10-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  10. Model Year 2005 Fuel Economy Guide: EPA Fuel Economy Estimates

    Energy Technology Data Exchange (ETDEWEB)

    None

    2004-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  11. Model Year 2016 Fuel Economy Guide: EPA Fuel Economy Estimates

    Energy Technology Data Exchange (ETDEWEB)

    None

    2015-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  12. Model Year 2010 Fuel Economy Guide: EPA Fuel Economy Estimates

    Energy Technology Data Exchange (ETDEWEB)

    None

    2009-10-14

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  13. Model Year 2014 Fuel Economy Guide: EPA Fuel Economy Estimates

    Energy Technology Data Exchange (ETDEWEB)

    None

    2013-12-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  14. The Stickiness of Aggregate Consumption Growth in OECD Countries: A Panel Data Analysis

    NARCIS (Netherlands)

    G. Everaert (Gerdie); L.C.G. Pozzi (Lorenzo)

    2010-01-01

    textabstractThis paper examines the sources of stickiness in aggregate consumption growth. We first derive a dynamic consumption equation which nests recent developments in consumption theory: rule-of-thumb consumption, habit formation, non-separabilities between both private consumption and hours

  15. Estimating under-reporting of road crash injuries to police using multiple linked data collections.

    Science.gov (United States)

    Watson, Angela; Watson, Barry; Vallmuur, Kirsten

    2015-10-01

    The reliance on police data for the counting of road crash injuries can be problematic, as it is well known that not all road crash injuries are reported to police which under-estimates the overall burden of road crash injuries. The aim of this study was to use multiple linked data sources to estimate the extent of under-reporting of road crash injuries to police in the Australian state of Queensland. Data from the Queensland Road Crash Database (QRCD), the Queensland Hospital Admitted Patients Data Collection (QHAPDC), Emergency Department Information System (EDIS), and the Queensland Injury Surveillance Unit (QISU) for the year 2009 were linked. The completeness of road crash cases reported to police was examined via discordance rates between the police data (QRCD) and the hospital data collections. In addition, the potential bias of this discordance (under-reporting) was assessed based on gender, age, road user group, and regional location. Results showed that the level of under-reporting varied depending on the data set with which the police data was compared. When all hospital data collections are examined together the estimated population of road crash injuries was approximately 28,000, with around two-thirds not linking to any record in the police data. The results also showed that the under-reporting was more likely for motorcyclists, cyclists, males, young people, and injuries occurring in Remote and Inner Regional areas. These results have important implications for road safety research and policy in terms of: prioritising funding and resources; targeting road safety interventions into areas of higher risk; and estimating the burden of road crash injuries. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Economic Growth, Electricity Consumption, Labor Force and Capital Input: A More Comprehensive Analysis on North China Using Panel Data

    Directory of Open Access Journals (Sweden)

    Huiru Zhao

    2016-10-01

    Full Text Available Over the past three decades, China’s economy has witnessed remarkable growth, with an average annual growth rate over 9%. However, China also faces great challenges to balance this spectacular economic growth and continuously increasing energy use like many other economies in the world. With the aim of designing effective energy and environmental policies, policymakers are required to master the relationship between energy consumption and economic growth. Therefore, in the case of North China, a multivariate model employing panel data analysis method based on the Cobb-Douglas production function which introduces electricity consumption as a main factor was established in this paper. The equilibrium relationship and causal relationship between real GDP, electricity consumption, total investment in fixed assets, and the employment were explored using data during the period of 1995–2014 for six provinces in North China, including Beijing City, Tianjin City, Hebei Province, Shanxi Province, Shandong Province and Inner Mongolia. The results of panel co-integration tests clearly state that all variables are co-integrated in the long term. Finally, Granger causality tests were used to examine the causal relationship between economic growth, electricity consumption, labor force and capital. From the Granger causality test results, we can draw the conclusions that: (1 There exist bi-directional causal relationships between electricity consumption and real GDP in six provinces except Hebei; and (2 there is a bi-directional relationship between capital input and economic growth and between labor force input and economic growth except Beijing and Hebei. Therefore, the ways to solve the contradiction of economic growth and energy consumption in North China are to reduce fossil energy consumption, develop renewable and sustainable energy sources, improve energy efficiency, and increase the proportion of the third industry, especially the sectors which

  17. Evaluation of the CONSUME and FOFEM fuel consumption models in pine and mixed hardwood forests of the eastern United States

    Science.gov (United States)

    Susan J. Prichard; Eva C. Karau; Roger D. Ottmar; Maureen C. Kennedy; James B. Cronan; Clinton S. Wright; Robert E. Keane

    2014-01-01

    Reliable predictions of fuel consumption are critical in the eastern United States (US), where prescribed burning is frequently applied to forests and air quality is of increasing concern. CONSUME and the First Order Fire Effects Model (FOFEM), predictive models developed to estimate fuel consumption and emissions from wildland fires, have not been systematically...

  18. The irradiance and temperature dependent mathematical model for estimation of photovoltaic panel performances

    International Nuclear Information System (INIS)

    Barukčić, M.; Ćorluka, V.; Miklošević, K.

    2015-01-01

    Highlights: • The temperature and irradiance dependent model for the I–V curve estimation is presented. • The purely mathematical model based on the analysis of the I–V curve shape is presented. • The model includes the Gompertz function with temperature and irradiance dependent parameters. • The input data are extracted from the data sheet I–V curves. - Abstract: The temperature and irradiance dependent mathematical model for photovoltaic panel performances estimation is proposed in the paper. The base of the model is the mathematical function of the photovoltaic panel current–voltage curve. The model of the current–voltage curve is based on the sigmoid function with temperature and irradiance dependent parameters. The temperature and irradiance dependencies of the parameters are proposed in the form of analytic functions. The constant parameters are involved in the analytical functions. The constant parameters need to be estimated to get the temperature and irradiance dependent current–voltage curve. The mathematical model contains 12 constant parameters and they are estimated by using the evolutionary algorithm. The optimization problem is defined for this purpose. The optimization problem objective function is based on estimated and extracted (measured) current and voltage values. The current and voltage values are extracted from current–voltage curves given in datasheet of the photovoltaic panels. The new procedure for estimation of open circuit voltage value at any temperature and irradiance is proposed in the model. The performance of the proposed mathematical model is presented for three different photovoltaic panel technologies. The simulation results indicate that the proposed mathematical model is acceptable for estimation of temperature and irradiance dependent current–voltage curve and photovoltaic panel performances within temperature and irradiance ranges

  19. Fuel consumption rates of passenger cars in China: Labels versus real-world

    International Nuclear Information System (INIS)

    Huo Hong; Yao Zhiliang; He Kebin; Yu Xin

    2011-01-01

    Recently, China has implemented many policy measures to control the oil demand of on-road vehicles. In 2010, China started to report the fuel consumption rates of light-duty vehicles tested in laboratory and to require new vehicles to show the rates on window labels. In this study, we examined the differences between the test and real-world fuel consumption of Chinese passenger cars by using the data reported by real-world drivers on the internet voluntarily. The sales-weighted average fuel consumption of new cars in China in 2009 was 7.80 L/100 km in laboratory and 9.02 L/100 km in real-world, representing a difference of 15.5%. For the 153 individual car models examined, the real-world fuel consumption rates were -8 to 60% different from the test values. The simulation results of the International Vehicle Emission model show that the real-world driving cycles in 22 selected Chinese cities could result in -8 to 34% of changes in fuel consumption compared to the laboratory driving cycle. Further government effort on fuel consumption estimates adjustment, local driving cycle development, and real-world data accumulation through communication with the public is needed to improve the accuracy of the labeling policy. - Research highlights: → China requires new cars sold to show the test fuel use levels on window labels. → Real-world fuel consumption rates of cars are 15.5% higher than the label values. → Discrepancy between the test cycle and real conditions is a major cause for the gap. → China should adjust the estimates, collect fuel use data, and develop driving cycles. → More official and academic efforts are needed to improve the labeling policy.

  20. CFTSIM-ITER dynamic fuel cycle model

    International Nuclear Information System (INIS)

    Busigin, A.; Gierszewski, P.

    1998-01-01

    Dynamic system models have been developed for specific tritium systems with considerable detail and for integrated fuel cycles with lesser detail (e.g. D. Holland, B. Merrill, Analysis of tritium migration and deposition in fusion reactor systems, Proceedings of the Ninth Symposium Eng. Problems of Fusion Research (1981); M.A. Abdou, E. Vold, C. Gung, M. Youssef, K. Shin, DT fuel self-sufficiency in fusion reactors, Fusion Technol. (1986); G. Spannagel, P. Gierszewski, Dynamic tritium inventory of a NET/ITER fuel cycle with lithium salt solution blanket, Fusion Eng. Des. (1991); W. Kuan, M.A. Abdou, R.S. Willms, Dynamic simulation of a proposed ITER tritium processing system, Fusion Technol. (1995)). In order to provide a tool to understand and optimize the behavior of the ITER fuel cycle, a dynamic fuel cycle model called CFTSIM is under development. The CFTSIM code incorporates more detailed ITER models, specifically for the important isotope separation system, and also has an easier-to-use graphical interface. This paper provides an overview of CFTSIM Version 1.0. The models included are those with significant and varying tritium inventories over a test campaign: fueling, plasma and first wall, pumping, fuel cleanup, isotope separation and storage. An illustration of the results is shown. (orig.)

  1. Maximum Simulated Likelihood and Expectation-Maximization Methods to Estimate Random Coefficients Logit with Panel Data

    DEFF Research Database (Denmark)

    Cherchi, Elisabetta; Guevara, Cristian

    2012-01-01

    with cross-sectional or with panel data, and (d) EM systematically attained more efficient estimators than the MSL method. The results imply that if the purpose of the estimation is only to determine the ratios of the model parameters (e.g., the value of time), the EM method should be preferred. For all......The random coefficients logit model allows a more realistic representation of agents' behavior. However, the estimation of that model may involve simulation, which may become impractical with many random coefficients because of the curse of dimensionality. In this paper, the traditional maximum...... simulated likelihood (MSL) method is compared with the alternative expectation- maximization (EM) method, which does not require simulation. Previous literature had shown that for cross-sectional data, MSL outperforms the EM method in the ability to recover the true parameters and estimation time...

  2. Detecting the relationship between economic growth, CO{sub 2} and energy consumption by using panel data approach

    Energy Technology Data Exchange (ETDEWEB)

    Sayed, Ahmed R. M. Al; Isa, Zaidi [School of Mathematical Sciences Universiti Kebangsaan Malaysia 43600 Bangi, Selangor (Malaysia)

    2015-09-25

    Many scholars have shown their interest into the relationship between energy consumption (EC), gross domestic product (GDP) and emissions. The main objective of this study is to investigate the relationship between GDP, EC and CO{sub 2} within multivariate model by using panel data method in Asian countries; Korea, Malaysia, Japan and China for annually data during the period 1960 to 2010. The main finding shows that CO{sub 2} can be explained more than 86% & 78% by EC and GDP in each of cross section model and period model respectively. As a result of that, CO{sub 2} emissions should be considered as an important factor in energy consumption and gross domestic product by policy maker.

  3. Superioridad relativa de los estimadores Kiviet y Blundell-Bond (GMM1 en paneles dinámicos. Un experimento Monte Carlo con muestras finitas

    Directory of Open Access Journals (Sweden)

    Andrés Eduardo Rangel Jiménez

    2012-10-01

    Full Text Available Dado el amplio uso de los datos de panel en modelos dinamicos, es relevante evaluar el desempeno de sus diferentes estimadores en muestras finitas en presencia de baja y alta persistencia. El presente articulo tiene como objetivo analizar, mediante simulaciones tipo Monte Carlo, las propiedades de los estimadores de efectos fijos (LSDV, Arellano y Bond (AB-GMM1, Blundell y Bond (BB-GMM1, Anderson y Hsiao (AH y Kiviet. Se concluye que en series no persistentes el estimador de Kiviet es el de mejor desempeno, basandose en los criterios de error cuadratico medio, sesgo y desviacion estandar; con alta persistencia, el estimador BB-GMM1 es el de mejor desempeno seguido por el estimador de Kiviet, que se comporta bien excepto en micropaneles con series persistentes.

  4. Passenger car fuel consumption survey

    Energy Technology Data Exchange (ETDEWEB)

    1984-03-01

    This survey originated from a proposal to monitor the fuel consumption and fuel economy of personal use passenger cars operated in Canada. Its purpose is to establish a data base which would contain information on total distance travelled, total amount of fuel consumed, average distance obtained per unit of fuel, total expenditures on fuel, and seasonal fluctuations in fuel consumption and in distance travelled. Among the needs served by this data base are the monitoring of passenger car fuel economy standards and the estimation of pasenger car fuel requirements in conditions involving fuel shortages. Survey methodology is by telephone interview to trace selected vehicles to the registered owners, at which time a fuel purchase diary is then mailed to the principal driver of the car. The results are tabulated on a quarterly basis and to be released as they become available in bulletins similar to this. Data are presented for each province and the total for Canada is given. During the fourth quarter of 1982, it is estimated that there were 7.3 million personal use passenger cars operated in Canada. These cars were driven 28 billion kilometers and consumed 4.3 billion litres of fuel. Their average litres/100 kilometres and the average fuel consumption was 590 litres. 8 tabs.

  5. Estimate of Fuel Consumption and GHG Emission Impact on an Automated Mobility District: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Yuche; Young, Stanley; Gonder, Jeff; Qi, Xuewei

    2015-12-11

    This study estimates the range of fuel and emissions impact of an automated-vehicle (AV) based transit system that services campus-based developments, termed an automated mobility district (AMD). The study develops a framework to quantify the fuel consumption and greenhouse gas (GHG) emission impacts of a transit system comprised of AVs, taking into consideration average vehicle fleet composition, fuel consumption/GHG emission of vehicles within specific speed bins, and the average occupancy of passenger vehicles and transit vehicles. The framework is exercised using a previous mobility analysis of a personal rapid transit (PRT) system, a system which shares many attributes with envisioned AV-based transit systems. Total fuel consumption and GHG emissions with and without an AMD are estimated, providing a range of potential system impacts on sustainability. The results of a previous case study based of a proposed implementation of PRT on the Kansas State University (KSU) campus in Manhattan, Kansas, serves as the basis to estimate personal miles traveled supplanted by an AMD at varying levels of service. The results show that an AMD has the potential to reduce total system fuel consumption and GHG emissions, but the amount is largely dependent on operating and ridership assumptions. The study points to the need to better understand ride-sharing scenarios and calls for future research on sustainability benefits of an AMD system at both vehicle and system levels.

  6. Development and use of GREET 1.6 fuel-cycle model for transportation fuels and vehicle technologies

    International Nuclear Information System (INIS)

    Wang, M. Q.

    2001-01-01

    Since 1995, with funds from the U.S. Department of Energy's (DOE's) Office of Transportation Technologies (OTT), Argonne National Laboratory has been developing the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model. The model is intended to serve as an analytical tool for use by researchers and practitioners in estimating fuel-cycle energy use and emissions associated with alternative transportation fuels and advanced vehicle technologies. Argonne released the first version of the GREET model--GREET 1.0--in June 1996. Since then, it has released a series of GREET versions with revisions, updates, and upgrades. In February 2000, the latest public version of the model--GREET 1.5a--was posted on Argonne's Transportation Technology Research and Development Center (TTRDC) Web site (www.transportation.anl.gov/ttrdc/greet). Major publications that address GREET development are listed. These reports document methodologies, development, key default assumptions, applications, and results of the GREET model. They are also posted, along with additional materials for the GREET model, on the TTRDC Web site. For a given transportation fuel/technology combination, the GREET model separately calculates: (A)--Fuel-cycle energy consumption for the following three source categories: (1) Total energy (all energy sources), (2) Fossil fuels (petroleum, natural gas [NG], and coal), and (3) Petroleum. (B)--Fuel-cycle emissions of the following three greenhouse gases (GHGs): (1) Carbon dioxide (CO 2 ) (with a global warming potential [GWP] of 1), (2) Methane (CH 4 ) (with a GWP of 21), and (3) Nitrous oxide (N 2 O) (with a GWP of 310). (C)--Fuel-cycle emissions of the following five criteria pollutants (separated into total [T] and urban [U] emissions): (1) Volatile organic compounds (VOCs), (2) Carbon monoxide (CO), (3) Nitrogen oxides (NO x ), (4) Particulate matter with a mean aerodynamic diameter of 10 (micro)m or less (PM 10 ), and (5) Sulfur oxides

  7. Fuel Consumption and Vehicle Emission Models for Evaluating Environmental Impacts of the ETC System

    Directory of Open Access Journals (Sweden)

    Jiancheng Weng

    2015-07-01

    Full Text Available The environmental outcome of the Electronic Toll Collection (ETC system is an important aspect in evaluating the impacts of the ETC system, which is influenced by various factors including the vehicle type, travel speed, traffic volume, and average queue length of Manual Toll Collection (MTC lanes. The primary objective of this paper is to develop a field data-based practical model for evaluating the effects of ETC system on the fuel efficiency and vehicle emission. First, laboratory experiments of seven types of vehicles under various scenarios for toll collection were conducted based on the Vehicle Emissions Testing System (VETS. The indicator calculation models were then established to estimate the comprehensive benefit of ETC system by comparing the test results of MTC lane and ETC lane. Finally, taking Beijing as a case study, the paper calibrated the model parameters, and estimated the monetization value of environmental benefit of the ETC system in terms of vehicle emissions reduction and fuel consumption decrease. The results shows that the applications of ETC system are expected to save fuel consumption of 4.1 million liters and reduce pollution emissions by 730.89 tons in 2013 in Beijing.

  8. Effects of fuel price fluctuation on individual CO2 traffic emissions : empirical findings from pseudo panel data

    NARCIS (Netherlands)

    Yang, D.; Timmermans, H.J.P.

    2012-01-01

    Globalized concerns about greenhouse gasses and increased energy consumptions have stimulated research in transportation about the relationships between fuel prices and emissions. Many researchers have found that higher fuel price can reduce fuel consumption and CO2 emissions through a number of

  9. Do Consumers Substitute Opium for Hashish? An Economic Analysis of Simultaneous Cannabinoid and Opiate Consumption in a Legal Regime

    Science.gov (United States)

    Chandra, Madhur

    2015-01-01

    Aim To analyze interrelationships in the consumption of opiates and cannabinoids in a legal regime and, specifically, whether consumers of opiates and cannabinoids treat them as substitutes for each other. Method Econometric dynamic panel data models for opium consumption are estimated using the generalized method of moments (GMM). A unique dataset containing information about opiate (opium) consumption from the Punjab province of British India for the years 1907–1918 is analyzed (n=272) as a function of its own price, the prices of two forms of cannabis (the leaf (bhang), and the resin (charas, or hashish)), and wage income. Cross-price elasticities are examined to reveal substitution or complementarity between opium and cannabis. Results Opium is a substitute for charas (or hashish), with a cross price elasticity (β3) of 0.14 (p 0.10). Opium consumption (β1 = 0.47 to 0.49, p opium is slightly responsive (inelastic) to changes in its own price (β2 = −0.34 to −0.35, p Opium and hashish, a form of cannabis, are substitutes. In addition, opium consumption displays properties of habit persistence and slight price and wage income responsiveness (inelasticity) consistent with an addictive substance. PMID:26455552

  10. Point process modeling and estimation: Advances in the analysis of dynamic neural spiking data

    Science.gov (United States)

    Deng, Xinyi

    2016-08-01

    A common interest of scientists in many fields is to understand the relationship between the dynamics of a physical system and the occurrences of discrete events within such physical system. Seismologists study the connection between mechanical vibrations of the Earth and the occurrences of earthquakes so that future earthquakes can be better predicted. Astrophysicists study the association between the oscillating energy of celestial regions and the emission of photons to learn the Universe's various objects and their interactions. Neuroscientists study the link between behavior and the millisecond-timescale spike patterns of neurons to understand higher brain functions. Such relationships can often be formulated within the framework of state-space models with point process observations. The basic idea is that the dynamics of the physical systems are driven by the dynamics of some stochastic state variables and the discrete events we observe in an interval are noisy observations with distributions determined by the state variables. This thesis proposes several new methodological developments that advance the framework of state-space models with point process observations at the intersection of statistics and neuroscience. In particular, we develop new methods 1) to characterize the rhythmic spiking activity using history-dependent structure, 2) to model population spike activity using marked point process models, 3) to allow for real-time decision making, and 4) to take into account the need for dimensionality reduction for high-dimensional state and observation processes. We applied these methods to a novel problem of tracking rhythmic dynamics in the spiking of neurons in the subthalamic nucleus of Parkinson's patients with the goal of optimizing placement of deep brain stimulation electrodes. We developed a decoding algorithm that can make decision in real-time (for example, to stimulate the neurons or not) based on various sources of information present in

  11. A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver Authentication.

    Science.gov (United States)

    Yang, Ching-Han; Chang, Chin-Chun; Liang, Deron

    2018-03-28

    All drivers have their own distinct driving habits, and usually hold and operate the steering wheel differently in different driving scenarios. In this study, we proposed a novel Gaussian mixture model (GMM)-based method that can improve the traditional GMM in modeling driving behavior. This new method can be applied to build a better driver authentication system based on the accelerometer and orientation sensor of a smartwatch. To demonstrate the feasibility of the proposed method, we created an experimental system that analyzes driving behavior using the built-in sensors of a smartwatch. The experimental results for driver authentication-an equal error rate (EER) of 4.62% in the simulated environment and an EER of 7.86% in the real-traffic environment-confirm the feasibility of this approach.

  12. Spent nuclear fuel system dynamic stability under normal conditions of transportation

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Hao; Wang, Jy-An John, E-mail: wangja@ornl.gov

    2016-12-15

    Highlights: • A conformational potential effect of fuel assembly contact interaction induced transient shock. • Complex vibration modes and vibration load intensity were observed from fuel assembly system. • The project was able to link the periodic transient shock to spent fuel fatigue strength reduction. - Abstract: In a horizontal layout of a spent nuclear fuel (SNF) assembly under normal conditions of transportation (NCT), the fuel assembly’s skeleton formed by guide tubes and spacer grids is the primary load bearing structure for carrying and transferring the vibration loads within an SNF assembly. Therefore, the integrity of guide tubes and spacer grids will dictate the vibration amplitude/intensity of the fuel assembly during transport, and must be considered when designing multipurpose purpose canister (MPC) for safe SNF transport. This paper investigates the SNF assembly deformation dynamics during normal vibration mode, as well as the transient shock mode inside the cask during NCT. Dynamic analyses were performed in the frequency domain to study frequency characteristic of the fuel assembly system and in the time domain to simulate the transient dynamic response of the fuel assembly. To further evaluate the intensity of contact interaction induced by the local contacts’ impact loading at the spacer grid, detailed models of the actual spring and dimples of the spacer grids were created. The impacts between the fuel rod and springs and dimples were simulated with a 20 g transient shock load. The associated contact interaction intensities, in terms of reaction forces, were estimated from the finite element analyses (FEA) results. The bending moment estimated from the resultant stress on the clad under 20 g transient shock can be used to define the loading in cyclic integrated reversible-bending fatigue tester (CIRFT) vibration testing for the equivalent condition. To estimate the damage potential of the transient shock to the SNF vibration

  13. Transport dynamics of a high-power-density matrix-type hydrogen-oxygen fuel cell

    Science.gov (United States)

    Prokopius, P. R.; Hagedorn, N. H.

    1974-01-01

    Experimental transport dynamics tests were made on a space power fuel cell of current design. Various operating transients were introduced and transport-related response data were recorded with fluidic humidity sensing instruments. Also, sampled data techniques were developed for measuring the cathode-side electrolyte concentration during transient operation.

  14. Road Transport Entrepreneurs and Road Transportation Revolution ...

    African Journals Online (AJOL)

    Toshiba

    upon a massive road-building programme throughout the colony. The rapid expansion ..... transportation problems of his textile customers and palm produce producers and ... unflinching loyalty and solidarity with their illustrious son, General.

  15. Fuel consumption impacts of auto roof racks

    International Nuclear Information System (INIS)

    Chen, Yuche; Meier, Alan

    2016-01-01

    The after-market roof rack is one of the most common components attached to a vehicle for carrying over-sized items, such as bicycles and skis. It is important to understand these racks’ fuel consumption impacts on both individual vehicles and the national fleet because they are widely used. We estimate the national fuel consumption impacts of roof racks using a bottom-up approach. Our model incorporates real-world data and vehicle stock information to enable assessing fuel consumption impacts for several categories of vehicles, rack configurations, and usage conditions. In addition, the model draws on two new data-gathering techniques, on-line forums and crowd-sourcing. The results show that nationwide, roof racks are responsible for 0.8‰ of light duty vehicle fuel consumption in 2015, corresponding to 100 million gallons of gasoline per year. Sensitivity analyses show that results are most sensitive to the fraction of vehicles with installed roof racks but carrying no equipment. The aerodynamic efficiency of typical roof racks can be greatly improved and reduce individual vehicle fuel consumption; however, government policies to minimize extensive driving with empty racks—if successful—could save more fuel nationally. - Highlights: •First estimate of national energy impacts of auto roof racks—about 1‰. •A bottom-up approach reveals details of the fuel consumption penalty caused by racks. •Two novel data collection techniques, on-line forums and crowd-sourcing, improve estimate. •Technical and behavioral policies could significantly cut fuel penalties from roof racks.

  16. Battery electric vehicle energy consumption modelling for range estimation

    NARCIS (Netherlands)

    Wang, J.; Besselink, I.J.M.; Nijmeijer, H.

    2017-01-01

    Range anxiety is considered as one of the major barriers to the mass adoption of battery electric vehicles (BEVs). One method to solve this problem is to provide accurate range estimation to the driver. This paper describes a vehicle energy consumption model considering the influence of weather

  17. GMM - a general microstructural model for qualitative and quantitative studies of smectite clays

    International Nuclear Information System (INIS)

    Pusch, R.; Karnland, O.; Hoekmark, H.

    1990-12-01

    A few years ago an attempt was made to accommodate a number of basic ideas on the fabric and interparticle forces that are assumed to be valid in montmorillonite clay in an integrated microstructural model and this resulted in an SKB report on 'Outlines of models of water and gas flow through smectite clay buffers'. This model gave reasonable agreement between predicted hydraulic conductivity values and actually recorded ones for room temperature and porewater that is poor in electrolytes. The present report describes an improved model that also accounts for effects generated by salt porewater and heating, and that provides a basis for both quantitative determination of transport capacities in a more general way, and also for analysis and prediction of rheological behaviour in bulk. It has been understood very early by investigators in this scientific field that full understanding of the physical state of porewater is asked for in order to make it possible to develop models for clay particle interaction. In particular, a deep insight in the nature of the interlamellar water and of the hydration mechanisms leading to an equilibrium state between the two types of water, and of forcefields in matured smectite clay, requires very qualified multi-discipline research and attempts have been made by the senior author to initiate and coordinate such work in the last 30 years. Despite this effort it has not been possible to get an unanimous understanding of these things but a number of major features have become more clear through the work that we have been able to carry out in the current SKB research work. Thus, NMR studies and precision measurements of the density of porewater as well as comprehensive electron microscopy and rheological testing in combination with application of stochastical mechanics, have led to the hypothetical microstructural model - the GMM - presented in this report. (au)

  18. Ethanol as a fuel for road transportation. Main report; Contribution to IEA Implementing Agreement on Advanced Motor Fuels

    Energy Technology Data Exchange (ETDEWEB)

    Larsen, Ulrik; Johansen, T.; Schramm, J.

    2009-05-15

    Bioethanol as a motor fuel in the transportation sector, mainly for road transportation, has been subject to many studies and much discussion. Furthermore, the topic involves not only the application and engine technical aspects, but also the understanding of the entire life cycle of the fuel, well-to-wheels, including economical, environmental, and social aspects. It is not, however, the aim of this report to assess every single one of these aspects. The present report aims to address the technical potential and problems as well as the central issues related to the general application of bioethanol as an energy carrier in the near future. In discussions of the advantages and drawbacks of ethanol, the type of application is important. Generalization is not possible, because ethanol can be used in many forms. Furthermore, a wide range of ethanol/gasoline blends has not yet been investigated sufficiently. The most favorable type of application is determined by infrastructural factors, especially vehicle fleet configuration. From a technical point of view, optimal usage involves a high degree of water content in the ethanol, and this excludes low-percentage-ethanol fuels. The benefits seem strongly related to the amount of ethanol in a given blend, that is, the more the better. Both engine efficiencies and emissions improve with more ethanol in the fuel. Wet ethanol constitutes an even cleaner fuel in both the production and application phases. In summary, ethanol application has many possibilities, but with each type of application comes a set of challenges. Nevertheless, technical solutions for each challenge are available. (ln)

  19. Road profile estimation of city roads using DTPS

    Science.gov (United States)

    Wang, Qi; McDaniel, J. Gregory; Sun, Nian X.; Wang, Ming L.

    2013-04-01

    This work presents a non-destructive and non-contact acoustic sensing approach for measuring road profile of road and bridge deck with vehicles running at normal speed without stopping traffic. This approach uses an instantaneous and real-time dynamic tire pressure sensor (DTPS) that can measure dynamic response of the tire-road interaction and increases the efficiency of currently used road profile measuring systems with vehicle body-mounted profilers and axle-mounted accelerometers. In this work, a prototype of real-time DTPS system has been developed and demonstrated on a testing van at speeds from 5 to 80 miles per hour (mph). A data analysis algorithm has been developed to remove axle dynamic motions from the measured DTPS data and to find the transfer function between dynamic tire pressure change and the road profile. Field test has been performed to estimate road profiles. The road profile resolution is approximately 5 to 10 cm in width and sensitivity is 0. 3 cm for the height road surface features at driving speeds of 5 to 80 mph.

  20. Dynamic modeling and experimental investigation of a high temperature PEM fuel cell stack

    DEFF Research Database (Denmark)

    Nguyen, Gia; Sahlin, Simon Lennart; Andreasen, Søren Juhl

    2016-01-01

    High temperature polymer fuel cells operating at 100 to 200◦C require simple fuel processing and produce high quality heat that can integrate well with domestic heating systems. Because the transportation of hydrogen is challenging, an alternative option is to reform natural gas on site....... This article presents the development of a dynamic model and the comparison with experimental data from a high temperature proton exchange membrane fuel cell stack operating on hydrogen with carbon monoxide concentrations up to 0.8%, and temperatures from 155 to 175◦C. The dynamic response of the fuel cell...... is investigated with simulated reformate gas. The dynamic response of the fuel cell stack was compared with a step change in current from 0.09 to 0.18 and back to 0.09 A/cm2 . This article shows that the dynamic model calculates the voltage at steady state well. The dynamic response for a change in current shows...

  1. Robust Determinants of Growth in Asian Developing Economies: A Bayesian Panel Data Model Averaging Approach

    OpenAIRE

    LEON-GONZALEZ, Roberto; VINAYAGATHASAN, Thanabalasingam

    2013-01-01

    This paper investigates the determinants of growth in the Asian developing economies. We use Bayesian model averaging (BMA) in the context of a dynamic panel data growth regression to overcome the uncertainty over the choice of control variables. In addition, we use a Bayesian algorithm to analyze a large number of competing models. Among the explanatory variables, we include a non-linear function of inflation that allows for threshold effects. We use an unbalanced panel data set of 27 Asian ...

  2. Emission Inventory of On-Road Transport in Bangkok Metropolitan Region (BMR Development during 2007 to 2015 Using the GAINS Model

    Directory of Open Access Journals (Sweden)

    Penwadee Cheewaphongphan

    2017-09-01

    Full Text Available Bangkok Metropolitan Region (BMR, including the capital city and five adjacent provinces, constitutes one of the top 10 megacities experiencing serious traffic congestion in the world, leading to air quality problems with significant adverse human health risks. Previously, there have been many operations planned to influence the fuel consumption and emissions from the on-road transport sector in the BMR area. It is necessary to estimate emissions using detailed information in order to thoroughly understand the reason for changes in emission levels and their impact on air quality. This paper aims to determine the successful implementation of energy and air pollution control policies in Thailand through an investigation of the emissions inventory of on-road transport in BMR, including ozone precursors (CO, NOX, Non-methane volatile organic compounds (NMVOCs , greenhouse gases (CO2, CH4, N2O, acidic substances (SO2 and NH3, and particulate matters (PM2.5, PM10, Black Carbon (BC, Organic Carbon (OC during the period from 2007 to 2015, using the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS model based on the country-specific activity data together with the emission factor from the GAINS-Asia database. This study found that the amount of exhaust emissions over the BMR area in the year 2015 (and the trend during the period from 2007 to 2015 is approximately 139 kt of CO (−7.9%, 103 kt of NOX (−4.1%, 19.9 kt of NMVOC (−6.7%, 15 kt of CO2 (+1.6%, 8.6 kt of CH4 (+6.8%, 0.59 kt of N2O (+1.3%, 0.87 kt of SO2 (−25.8%, 1.1 kt of NH3 (+7.8%, 4.9 kt of PM2.5 (−5.5%, 5.1 kt of PM10 (−7.9%, 3.1 kt of BC (−2.5%, and 1.4 kt of OC (−7.7%. The change in emissions in each pollutant is a result of the more stringent control of fuel and engine standards, the shift in the fuel type used, and the effects of controlling some emissions. Light duty car gasoline fuel is identified as a major contributor of CO, NH3, N2O, and NMVOC, whereas

  3. Energy information. Status, cost, and need for energy, consumption and fuel switching data

    International Nuclear Information System (INIS)

    Fultz, Keith O.; Milans, Flora H.; Hale, Richard A.; Weaver, Joanne E.; D'Amico, Nicholas C.

    1989-04-01

    In 1986, EIA's Manufacturing Energy Consumption Survey collected calendar year 1985 fuel switching and energy consumption information from a sample of manufacturers. Although the construction, agriculture, mining, fishing, and forestry segments of the industrial sector were not surveyed, in 1985 the manufacturing segment accounted for about 75 to 80 percent of the total energy consumed in the industrial sector. The results of the energy consumption segment of the survey were published in November 1988, and the results of the fuel switching segment were published in December 1988. In 1989, EIA will conduct the second triennial survey, collecting energy consumption and fuel switching data for 1988. EIA estimated that the cost of the survey to the U.S. government, consisting of EIA and Census Bureau costs to design and conduct the survey, was about $1.8 million (in 1988 dollars) and that the cost to the manufacturers participating in the survey was more than $4 million (in 1988 dollars). According to EIA's justification to the Office of Management and Budget (OMB) for the survey, most of the potential users of the survey data were federal offices. Officials of seven of the eight federal offices we contacted indicated various uses for the energy consumption data, such as updating the national input-output tables and energy accounts, analyzing the competitiveness of U.S. industries, and doing energy emergency contingency planning. Officials of five of the eight federal offices indicated uses for the fuel switching data and most frequently cited its use for contingency planning for emergencies or supply disruptions. EIA's justification to OMB also identified 17 states as potential users, but officials of the 3 state offices that we contacted told us that the EIA data would not be useful because it cannot be summarized for individual states

  4. Potential of greenhouse gas emission reduction in Thai road transport by ethanol bus technology

    International Nuclear Information System (INIS)

    Chollacoop, Nuwong; Saisirirat, Peerawat; Sukkasi, Sittha; Tongroon, Manida; Fukuda, Tuenjai; Fukuda, Atsushi; Nivitchanyong, Siriluck

    2013-01-01

    Highlights: ► Energy demand modeling in Thai road transportation sector was developed. ► Such model was used to assess environment impact by ethanol bus technology (ED95). ► Ethanol bus technology (ED95) shows beneficial impacts to Thailand. ► Increase in ethanol demand and decrease in GHG emission in Thailand by ethanol bus. ► Ethanol bus (ED95) has been successfully demonstrated in Thailand. -- Abstract: Over decades, Thailand energy consumption has been concentrated in three main sectors, namely manufacturing, power and transportation. Energy consumption in transportation sector has also been dominated by road transport due to limited coverage by rail and water transportation. Hence, road transport has been a major contributor for greenhouse gas emission in Thailand over recent years. Along with global warming concern throughout the world, Thailand has taken various adaptation and mitigation measures, especially the strong policy push to use carbon–neutral biofuel in transportation sector due to Thailand competitive advantage in agriculture sector. National Renewable Energy Plan (2008–2022) has set challenging targets of 9 and 4.5 million liters/day of ethanol and biodiesel consumption by 2022, respectively. Various blends of ethanol in gasoline (10%, 20% and 85%) and biodiesel in diesel (up to 5%) have been commercially available. However, since current consumption of diesel is twice as much of gasoline, ethanol blend in gasoline would widen the imbalance consumption of gasoline and diesel. The present study however offers an insight into a possibility to use ethanol as diesel substitute. A case study of ethanol bus technology was investigated by recourse to energy demand modeling. Necessary data, such as a number of vehicles (NVs) for various vehicle types, vehicle kilometer of travel (VKT) and fuel economy (FE) were collected, with reasonable assumptions made for those unavailable data, to construct predicative energy demand model. Scenario

  5. The impact of environmental pollution on public health expenditure: dynamic panel analysis based on Chinese provincial data.

    Science.gov (United States)

    Hao, Yu; Liu, Shuang; Lu, Zhi-Nan; Huang, Junbing; Zhao, Mingyuan

    2018-05-01

    In recent years, along with rapid economic growth, China's environmental problems have become increasingly prominent. At the same time, the level of China's pollution has been growing rapidly, which has caused huge damages to the residents' health. In this regard, the public health expenditure ballooned as the environmental quality deteriorated in China. In this study, the effect of environmental pollution on residents' health expenditure is empirically investigated by employing the first-order difference generalized method of moments (GMM) method to control for potential endogeneity. Using a panel data of Chinese provinces for the period of 1998-2015, this study found that the environmental pollution (represented by SO 2 and soot emissions) would indeed lead to the increase in the medical expenses of Chinese residents. At the current stage of economic development, an increase in SO 2 and soot emissions per capita would push up the public health expenditure per capita significantly. The estimation results are quite robust for different types of regression specifications and different combinations of control variables. Some social and economic variables such as public services and education may also have remarkable influences on residential medical expenses through different channels.

  6. Systematic screening for Chlamydia trachomatis : Estimating cost-effectiveness using dynamic modeling and Dutch data

    NARCIS (Netherlands)

    de Vries, R.; Van Bergen, J.E.A.M.; de Jong-van den Berg, Lolkje; Postma, Maarten

    2006-01-01

    To estimate the cost-effectiveness of a systematic one-off Chlamydia trachomatis (CT) screening program including partner treatment for Dutch young adults. Data on infection prevalence, participation rates, and sexual behavior were obtained from a large pilot study conducted in The Netherlands.

  7. Systematic screening for Chlamydia trachomatis: estimating cost-effectiveness using dynamic modeling and Dutch data

    NARCIS (Netherlands)

    de Vries, Robin; van Bergen, Jan E. A. M.; de Jong-van den Berg, Lolkje T. W.; Postma, Maarten J.

    2006-01-01

    To estimate the cost-effectiveness of a systematic one-off Chlamydia trachomatis (CT) screening program including partner treatment for Dutch young adults. Data on infection prevalence, participation rates, and sexual behavior were obtained from a large pilot study conducted in The Netherlands.

  8. The Model of Temperature Dynamics of Pulsed Fuel Assembly

    CERN Document Server

    Bondarchenko, E A; Popov, A K

    2002-01-01

    Heat exchange process differential equations are considered for a subcritical fuel assembly with an injector. The equations are obtained by means of the use of the Hermit polynomial. The model is created for modelling of temperature transitional processes. The parameters and dynamics are estimated for hypothetical fuel assembly consisting of real mountings: the powerful proton accelerator and the reactor IBR-2 core at its subcritica l state.

  9. Do consumers substitute opium for hashish? An economic analysis of simultaneous cannabinoid and opiate consumption in a legal regime.

    Science.gov (United States)

    Chandra, Siddharth; Chandra, Madhur

    2015-11-01

    To analyze interrelationships in the consumption of opiates and cannabinoids in a legal regime and, specifically, whether consumers of opiates and cannabinoids treat them as substitutes for each other. Econometric dynamic panel data models for opium consumption are estimated using the generalized method of moments (GMM). A unique dataset containing information about opiate (opium) consumption from the Punjab province of British India for the years 1907-1918 is analyzed (n=252) as a function of its own price, the prices of two forms of cannabis (the leaf (bhang), and the resin (charas, or hashish)), and wage income. Cross-price elasticities are examined to reveal substitution or complementarity between opium and cannabis. Opium is a substitute for charas (or hashish), with a cross price elasticity (βˆ3) of 0.14 (pprice elasticity=0.00, p>0.10). Opium consumption (βˆ1=0.47 to 0.49, pprice (βˆ2=-0.34 to -0.35, pprice and wage income responsiveness (inelasticity) consistent with an addictive substance. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  10. Real-world emissions and fuel consumption of diesel buses and trucks in Macao: From on-road measurement to policy implications

    Science.gov (United States)

    Wu, Xiaomeng; Zhang, Shaojun; Wu, Ye; Li, Zhenhua; Zhou, Yu; Fu, Lixin; Hao, Jiming

    2015-11-01

    A total of 13 diesel buses and 12 diesel trucks in Macao were tested using portable emission measurement systems (PEMS) including a SEMTECH-DS for gaseous emissions and a SEMTECH-PPMD for PM2.5. The average emission rates of gaseous pollutants and CO2 are developed with the operating mode defined by the instantaneous vehicle specific power (VSP) and vehicle speed. Both distance-based and fuel mass-based emission factors for gaseous pollutants (e.g., CO, THC and NOX) are further estimated under typical driving conditions. The average distance-based NOX emission of heavy-duty buses (HDBs) is higher than 13 g km-1. Considering the unfavorable conditions for selective reductions catalyst (SCR) systems, such as low-speed driving conditions, more effective technology options (e.g., dedicated natural gas buses and electric buses) should be considered by policy makers in Macao. We identified strong effects of the vehicle size, engine displacement and driving conditions on real-world CO2 emission factors and fuel consumption for diesel vehicles. Therefore, detailed profiles regarding vehicle specifications can reduce the uncertainty in their fleet-average on-road fuel consumption. In addition, strong correlations between relative emission factors and driving conditions indicated by the average speed of generated micro-trips are identified based on a micro-trip method. For example, distance-based emission factors of HDBs will increase by 39% for CO, 29% for THC, 43% for NOX and 26% for CO2 when the average speed decreases from 30 km h-1 to 20 km h-1. The mitigation of on-road emissions from diesel buses and trucks by improving traffic conditions through effective traffic and economic management measures is therefore required. This study demonstrates the important role of PEMS in understanding vehicle emissions and mitigation strategies from science to policy perspectives.

  11. A GMM-Based Test for Normal Disturbances of the Heckman Sample Selection Model

    Directory of Open Access Journals (Sweden)

    Michael Pfaffermayr

    2014-10-01

    Full Text Available The Heckman sample selection model relies on the assumption of normal and homoskedastic disturbances. However, before considering more general, alternative semiparametric models that do not need the normality assumption, it seems useful to test this assumption. Following Meijer and Wansbeek (2007, the present contribution derives a GMM-based pseudo-score LM test on whether the third and fourth moments of the disturbances of the outcome equation of the Heckman model conform to those implied by the truncated normal distribution. The test is easy to calculate and in Monte Carlo simulations it shows good performance for sample sizes of 1000 or larger.

  12. Fuel taxes and road expenditures: making the link

    International Nuclear Information System (INIS)

    Derkson, W.W.; Shurvell, S.J.

    1999-11-01

    This document reports on a study undertaken at the request of the United Grain Growers regarding government fuel tax revenue and the relationship to expenditures on roads. The account of fuel tax revenues was compiled from data collected from several different sources, as was the case for the road expenditures at the federal, provincial, local and modal levels. The emphasis was placed on the effects of fuel taxes on grain handling and transportation in the Prairie provinces. The authors presented fuel tax revenues broken down by mode of transportation and by province. The document was divided as follows: the first part was the introduction with the second part dealing with fuel tax rates and policies. In the third part, the topic of fuel tax and road related revenues was examined. Part four discussed road expenditures. The authors concluded that Transport Canada has traditionally represented the most important federal link to provincial highway infrastructure. It was noted that 4.2 billion dollars in road fuel taxes were collected by the federal government in 1998/1999, and of that amount, 198 million dollars, or 4.7 per cent, was reinvested in the National Highway System in programs managed by Transport Canada. Nearly one dollar on roads is spent by provincial governments on a Prairie-wide basis for every dollar collected in road fuel taxes, with Alberta spending the most and Saskatchewan spending the least. 15 tabs

  13. Usage of Production Functions in the Comparative Analysis of Transport Related Fuel Consumption

    Directory of Open Access Journals (Sweden)

    Torok Adam

    2014-12-01

    Full Text Available This contribution aims to examine the relationship between the transport sector and the macroeconomy, particularly in fossil energy use, capital and labour relations. The authors have investigated the transport related fossil fuel consumption 2003 -2010 in a macroeconomic context in Hungary and Germany. The Cobb-Douglas type of production function could be justified empirically, while originating from the general CES (Constant Elasticity of Substitution production function. Furthermore, as a policy implication, the results suggest that a solution for the for the reduction of anthropogenic CO2 driven by the combustion of fossil fuels presupposes technological innovation to reach emission reduction targets. Other measures, such as increasing the fossil fuel price by levying taxes, would consequently lead to an undesirable GDP decline.

  14. Capital adjustment cost and bias in income based dynamic panel models with fixed effects

    OpenAIRE

    Yoseph Yilma Getachew; Keshab Bhattarai; Parantap Basu

    2012-01-01

    The fixed effects (FE) estimator of "conditional convergence" in income based dynamic panel models could be biased downward when capital adjustment cost is present. Such a capital adjustment cost means a rising marginal cost of investment which could slow down the convergence. The standard FE regression fails to take into account of this capital adjustment cost and thus it could overestimate the rate of convergence. Using a Ramsey model with long-run adjustment cost of capital, we characteriz...

  15. Correction of Dynamic Characteristics of SAR Cryogenic GTE on Consumption of Gasified Fuel

    Science.gov (United States)

    Bukin, V. A.; Gimadiev, A. G.; Gangisetty, G.

    2018-01-01

    When the gas turbine engines (GTE) NK-88 were developed for liquid hydrogen and NK-89 for liquefied natural gas, performance of the systems with a turbo-pump unitary was improved and its proved without direct regulation of the flow of a cryogenic fuel, which was supplied by a centrifugal pump of the turbo-pump unit (TPU) Command from the “kerosene” system. Such type of the automatic control system (SAR) has the property of partial “neutralization” of the delay caused by gasification of the fuel. This does not require any measurements in the cryogenic medium, and the failure of the centrifugal cryogenic pump does not lead to engine failure. On the other hand, the system without direct regulation of the flow of cryogenic fuel has complex internal dynamic connections, their properties are determined by the characteristics of the incoming units and assemblies, and it is difficult to maintain accurate the maximum boundary level and minimum fuel consumption due to the influence of a booster pressure change. Direct regulation of the consumption of cryogenic fuel (prior to its gasification) is the preferred solution, since for using traditional liquid and gaseous fuels this is the main and proven method. The scheme of correction of dynamic characteristics of a single-loop SAR GTE for the consumption of a liquefied cryogenic fuel with a flow rate correction in its gasified state, which ensures the dynamic properties of the system is not worse than for NK-88 and NK-89 engines.

  16. Alternative Fuels Data Center: Virginia Transportation Data for Alternative

    Science.gov (United States)

    /2018 Biodiesel and Green Diesel Definitions updated 4/9/2018 Data Download Fueling Stations 706 stations in Virginia with alternative fuels Fuel Public Private Biodiesel (B20 and above) 1 9 Compressed unit sold per GGE per unit sold per GGE Biodiesel (B20) $2.47/gallon $2.25/GGE $2.84/gallon $2.58/GGE

  17. Alternative Fuels Data Center: Maine Transportation Data for Alternative

    Science.gov (United States)

    Biodiesel-Blended Diesel Documentation Requirement Data Download Fueling Stations 149 stations in Maine with alternative fuels Fuel Public Private Biodiesel (B20 and above) 2 1 Compressed Natural Gas (CNG) 0 2 Electric ://www.youtube.com/embed/jHftlruFR40 Video thumbnail for Maine's Only Biodiesel Manufacturer Powers Fleets in the

  18. Three-dimensional multi-phase flow computational fluid dynamics model for analysis of transport phenomena and thermal stresses in PEM fuel cells

    Energy Technology Data Exchange (ETDEWEB)

    Maher, A.R.; Al-Baghdadi, S. [International Technological Univ., London (United Kingdom). Dept. of Mechanical Engineering; Haroun, A.K.; Al-Janabi, S. [Babylon Univ., Babylon (Iraq). Dept. of Mechanical Engineering

    2007-07-01

    Fuel cell technology is expected to play an important role in meeting the growing demand for distributed generation because it can convert the chemical energy of a clean fuel directly into electrical energy. An operating fuel cell has varying local conditions of temperature, humidity, and power generation across the active area of the fuel cell in 3D. This paper presented a model that was developed to improve the basic understanding of the transport phenomena and thermal stresses in PEM fuel cells, and to investigate the behaviour of polymer membrane under hygro and thermal stresses during the cell operation. This comprehensive 3D, multiphase, non-isothermal model accounts for the major transport phenomena in a PEM fuel cell, notably convective and diffusive heat and mass transfer; electrode kinetics; transport and phase change mechanism of water; and potential fields. The model accounts for the liquid water flux inside the gas diffusion layers by viscous and capillary forces and can therefore predict the amount of liquid water inside the gas diffusion layers. This study also investigated the key parameters affecting fuel cell performance including geometry, materials and operating conditions. The model considers the many interacting, complex electrochemical, transport phenomena, thermal stresses and deformation that cannot be studied experimentally. It was concluded that the model can provide a computer-aided tool for the design and optimization of future fuel cells with much higher power density and lower cost. 21 refs., 2 tabs., 14 figs.

  19. Risk assessment in spent fuel storage and transportation

    International Nuclear Information System (INIS)

    Pandimani, S.

    1989-01-01

    Risk assessment in various stages of nuclear fuel cycle is still an active area of Nuclear safety studies. From the results of risk assessment available in literature, it can be determined that the risk resulting from shipments of plutonium and spent-fuel are much greater than that resulting from the transport of other materials within the nuclear fuel cycle. In India spent fuels are kept in Spent Fuel Storage Pool (SFSP) for about 240-400 days, which is relatively a longer period compared to the usual 120 days as recommended by regulatory authorities. After cooling spent fuels are transported to the reprocessing sites which are mostly situated close to the plants. India has two high level waste treatment facilities, one PREFRE (Plutonium Reprocessing and Fuel Recycling) at Tarapur and the other one, a unit of Nuclear Fuel Complex at Hyderabad. This paper presents the risk associated with spent fuel storage and transportation for the Indian conditions. All calculations are based on a typical CANDU reactor system. Simple fault tree models are evolved for SFSP and for Transportation Accident Mode (TAM) for both road and rail. Fault tree quantification and risk assessment are done to each of these models. All necessary data for SFSP are taken mostly from Reactor Safety Study, (1975). Similarly, the data for rail TAM are taken from Annual Statistical Statements, (1987-8) and that for road TAM from Special Issue on Motor Vehicle Accident Statistics in India, (1986). Simulation method is used wherever necessary. Risk is also estimated for normal/accident free transport

  20. Two-Dimensional Modeling of Heat and Moisture Dynamics in Swedish Roads: Model Set up and Parameter Sensitivity

    Science.gov (United States)

    Rasul, H.; Wu, M.; Olofsson, B.

    2017-12-01

    Modelling moisture and heat changes in road layers is very important to understand road hydrology and for better construction and maintenance of roads in a sustainable manner. In cold regions due to the freezing/thawing process in the partially saturated material of roads, the modeling task will become more complicated than simple model of flow through porous media without freezing/thawing pores considerations. This study is presenting a 2-D model simulation for a section of highway with considering freezing/thawing and vapor changes. Partial deferential equations (PDEs) are used in formulation of the model. Parameters are optimized from modelling results based on the measured data from test station on E18 highway near Stockholm. Impacts of phase change considerations in the modelling are assessed by comparing the modeled soil moisture with TDR-measured data. The results show that the model can be used for prediction of water and ice content in different layers of the road and at different seasons. Parameter sensitivities are analyzed by implementing a calibration strategy. In addition, the phase change consideration is evaluated in the modeling process, by comparing the PDE model with another model without considerations of freezing/thawing in roads. The PDE model shows high potential in understanding the moisture dynamics in the road system.

  1. An Agent-Based Model for Optimization of Road Width and Public Transport Frequency

    Directory of Open Access Journals (Sweden)

    Mark E. Koryagin

    2015-04-01

    Full Text Available An urban passenger transportation problem is studied. Municipal authorities and passengers are regarded as participants in the passenger transportation system. The municipal authorities have to optimise road width and public transport frequency. The road consists of a dedicated bus lane and lanes for passenger cars. The car travel time depends on the number of road lanes and passengers’ choice of travel mode. The passengers’ goal is to minimize total travel costs, including time value. The passengers try to find the optimal ratio between public transport and cars. The conflict between municipal authorities and the passengers is described as a game theoretic model. The existence of Nash equilibrium in the model is proved. The numerical example shows the influence of the value of time and intensity of passenger flow on the equilibrium road width and public transport frequency.

  2. Zero-truncated panel Poisson mixture models: Estimating the impact on tourism benefits in Fukushima Prefecture.

    Science.gov (United States)

    Narukawa, Masaki; Nohara, Katsuhito

    2018-04-01

    This study proposes an estimation approach to panel count data, truncated at zero, in order to apply a contingent behavior travel cost method to revealed and stated preference data collected via a web-based survey. We develop zero-truncated panel Poisson mixture models by focusing on respondents who visited a site. In addition, we introduce an inverse Gaussian distribution to unobserved individual heterogeneity as an alternative to a popular gamma distribution, making it possible to capture effectively the long tail typically observed in trip data. We apply the proposed method to estimate the impact on tourism benefits in Fukushima Prefecture as a result of the Fukushima Nuclear Power Plant No. 1 accident. Copyright © 2018 Elsevier Ltd. All rights reserved.

  3. Forecasting of Energy and Petroleum Consumption by Motor Transport in the Regions of the Russian Federation

    Directory of Open Access Journals (Sweden)

    Leontiy Viktorovich Eder

    2017-09-01

    Full Text Available The paper offers the directions for the improvement of methodological approach to forecasting the energy consumption in transport, taking into account special features of Russian regions. The authors developed a multivariate model allowing to predict the motor vehicle rate specified for the regions of the Russian Federation depending on the economic, social and institutional features. We formalized the dynamic (trend model for predicting the effectiveness of energy consumption per unit of the vehicle in Russia with details on Federal districts. In the study, in predicting the number of motor transport, the authors applied the methods of economic and mathematical simulation modelling based on the results of the econometric analysis for the calculation of the population having motor transport. In determining the potential specific energy consumption, we have aggregated trending patterns and convergence. The study has shown that by 2040, the number of passenger cars in Russia will grow to 57.1 million, and the total number of all types of road transport will grow by 14.9 million units to 66.2 million. The highest growth rates are predicted in the Central regions of Russia and in some areas of Siberia. The smallest growth rates are expected in the Chukotka Autonomous District, Kamchatka and Primorsky regions. Energy efficiency in transport and active introduction of alternative motor fuels, primarily methane, will reduce the consumption of gasoline and diesel fuel by motor transport. Thus, in the forecast period of 2018–2040, the consumption of petroleum products by motor transport will be reduced by 8.9 million tons: from 61,9 million tons of oil to 51.7 million tons of oil. The results of the study can be applied for the formulation of proposals on the creation of scientific and methodological apparatus to predict the development of transport sector and oil products supply in of the regions of Russia.

  4. A new gridded on-road CO2 emissions inventory for the United States, 1980-2011

    Science.gov (United States)

    Gately, C.; Hutyra, L.; Sue Wing, I.

    2013-12-01

    On-road transportation is responsible for 28% of all U.S. fossil fuel CO2 emissions. However, mapping vehicle emissions at regional scales is challenging due to data limitations. Existing emission inventories have used spatial proxies such as population and road density to downscale national or state level data, which may introduce errors where the proxy variables and actual emissions are weakly correlated. We have developed a national on-road emissions inventory product based on roadway-level traffic data obtained from the Highway Performance Monitoring System. We produce annual estimates of on-road CO2 emissions at a 1km spatial resolution for the contiguous United States for the years 1980 through 2011. For the year 2011 we also produce an hourly emissions product at the 1km scale using hourly traffic volumes from hundreds of automated traffic counters across the country. National on-road emissions rose at roughly 2% per year from 1980 to 2006, with emissions peaking at 1.71 Tg CO2 in 2007. However, while national emissions have declined 6% since the peak, we observe considerable regional variation in emissions trends post-2007. While many states show stable or declining on-road emissions, several states and metropolitan areas in the Midwest, mountain west and south had emissions increases of 3-10% from 2008 to 2011. Our emissions estimates are consistent with state-reported totals of gasoline and diesel fuel consumption. This is in contrast to on-road CO2 emissions estimated by the Emissions Database of Global Atmospheric Research (EDGAR), which we show to be inconsistent in matching on-road emissions to published fuel consumption at the scale of U.S. states, due to the non-linear relationships between emissions and EDGAR's chosen spatial proxies at these scales. Since our emissions estimates were generated independent of population density and other demographic data, we were able to conduct a panel regression analysis to estimate the relationship between these

  5. Globalization of the automobile industry in China: dynamics and barriers in greening of the road transportation

    International Nuclear Information System (INIS)

    Gan Lin

    2003-01-01

    This article describes the state of the automobile industry and urban road transportation management in China. It reviews how the automobile industry is evolving to respond to challenges in economic development, environmental regulations, and technological change. The dynamics and barriers resulting from technological change of automobiles in response to reduction of exhaust emissions and energy-efficiency improvement are analyzed. It is argued that consideration of externality costs should be integrated in automobile industrial policymaking and transportation management. Efforts need to be made to use more economic incentives for emissions reduction, and to promote technological change for cleaner vehicle development. This paper questions the current government policy of encouraging private car ownership, and suggests that improvement in public transportation systems, stronger emissions control, and technology innovation on environmental friendly automobile technologies would be relevant to China's drive toward sustainable transportation development. Social inequities resulted from automobile use is also stressed in the analysis

  6. Globalization of the automobile industry in China. Dynamics and barriers in the greening of road transportation

    Energy Technology Data Exchange (ETDEWEB)

    Gan, Lin

    2001-08-01

    This article describes the state of the automobile industry and urban road transportation management in China. It reviews how the automobile industry is evolving to respond to challenges in economic development, environmental regulations, and technological change. The dynamics and barriers resulting from technological change of the automobile in response to reduction of exhaust emissions and energy-efficiency improvement are analyzed. It is argued that consideration of externality costs should be integrated in automobile industrial policy making and transport management. This paper questions the current government policy of encouraging private car ownership, and suggests that improvement in public transportation systems and stronger emissions control would be relevant to China's drive toward sustainable transportation development. (author)

  7. Globalization of the automobile industry in China: dynamics and barriers in greening of the road transportation

    Energy Technology Data Exchange (ETDEWEB)

    Lin Gan [Center for International Climate and Environmental Research, Oslo (Norway)

    2003-05-01

    This article describes the state of the automobile industry and urban road transportation management in China. It reviews how the automobile industry is evolving to respond to challenges in economic development, environmental regulations, and technological change. The dynamics and barriers resulting from technological change of automobiles in response to reduction of exhaust emissions and energy-efficiency improvement are analysed. It is argued that consideration of externality costs should be integrated in automobile industrial policymaking and transportation management. Efforts need to be made to use more economic incentives for emissions reduction, and to promote technological change for cleaner vehicle development. This paper questions the current government policy of encouraging private car ownership, and suggests that improvement in public transportation systems, stronger emissions control, and technology innovation on environmental friendly automobile technologies would be relevant to China's drive toward sustainable transportation development. Social inequities resulted from automobile use is also stressed in the analysis. (author)

  8. Globalization of the automobile industry in China: dynamics and barriers in greening of the road transportation

    Energy Technology Data Exchange (ETDEWEB)

    Gan Lin E-mail: lin.gan@cicero.uio.no

    2003-05-01

    This article describes the state of the automobile industry and urban road transportation management in China. It reviews how the automobile industry is evolving to respond to challenges in economic development, environmental regulations, and technological change. The dynamics and barriers resulting from technological change of automobiles in response to reduction of exhaust emissions and energy-efficiency improvement are analyzed. It is argued that consideration of externality costs should be integrated in automobile industrial policymaking and transportation management. Efforts need to be made to use more economic incentives for emissions reduction, and to promote technological change for cleaner vehicle development. This paper questions the current government policy of encouraging private car ownership, and suggests that improvement in public transportation systems, stronger emissions control, and technology innovation on environmental friendly automobile technologies would be relevant to China's drive toward sustainable transportation development. Social inequities resulted from automobile use is also stressed in the analysis.

  9. Causal relationship between trade openness, economic growth and energy consumption: A panel data analysis of Asian countries

    International Nuclear Information System (INIS)

    Nasreen, Samia; Anwar, Sofia

    2014-01-01

    This paper explores the causal relationship between economic growth, trade openness and energy consumption using data of 15 Asian countries. The study covers the period of 1980–2011. We have applied panel cointegration and causality approaches to examine the long-run and causal relationship between variables. Empirical results confirm the presence of cointegration between variables. The impact of economic growth and trade openness on energy consumption is found to be positive. The panel Granger causality analysis reveals the bidirectional causality between economic growth and energy consumption, trade openness and energy consumption. - Highlights: • This study analyzes causality between energy, growth and trade in the Asian region. • Empirical results supported cointegrating relationship between variables. • Positive impact of growth and trade openness on energy usage is found in the long run. • Bidirectional Granger causality is observed between selected variables in the long run

  10. Harnessing Big-Data for Estimating the Energy Consumption and Driving Range of Electric Vehicles

    DEFF Research Database (Denmark)

    Fetene, Gebeyehu Manie; Prato, Carlo Giacomo; Kaplan, Sigal

    -effects econometrics model used in this paper predicts that the energy saving speed of driving is between 45 and 56 km/h. In addition to the contribution to the literature about energy efficiency of electric vehicles, the findings from this study enlightens consumers to choose appropriate cars that suit their travel......This study analyses the driving range and investigates the factors affecting the energy consumption rate of fully-battery electric vehicles under real-world driving patterns accounting for weather condition, drivers’ characteristics, and road characteristics. Four data sources are used: (i) up...

  11. On-farm estimation of pig growth parameters from longitudinal data of live weight and feed consumption and the use of a mathematical model

    Directory of Open Access Journals (Sweden)

    Stefano Schiavon

    2010-01-01

    Full Text Available Experimental data of feed consumption and composition, recorded over 5 consecutive short periods of growth from 30 crossbred male pigs divided 2 two groups and fed two restricted feeding regimes from 25 to 160 kg LW, were used to run a model in which a set of theoretical values, to describe the potential chemical growth of the pig, was preliminarily assumed. Simulated values of average daily gain (ADG and feed conversion ratio (FCR were the outputs. Estimates of protein mass at maturity (Pm, kg and relative growth rate (B, d-1 for each feeding regimes where successively obtained through an optimization procedure which has minimized the coefficients of variation of the differences between the estimates and the measurements of ADG and FCR. The very similar values of Pm (33.7 and 33.2 kg, and B (0.0104 and 0.0105 d-1, obtained for the two feed treatments suggested that these values can be used as operational data to describe the growth parameters of the experimental pigs used.

  12. The prospects of use of alternative types of fuel in road transport ...

    African Journals Online (AJOL)

    The article is devoted to the analysis of possibilities of using alternative types of fuel in transport. Gas engine fuels are considered as potential energy carriers for diesel engines. Since the constructions of vehicles, using gas and traditional types of fuel, have some differences, the most important are the issues of ensuring ...

  13. Modeling Heavy/Medium-Duty Fuel Consumption Based on Drive Cycle Properties

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Lijuan; Duran, Adam; Gonder, Jeffrey; Kelly, Kenneth

    2015-10-13

    This paper presents multiple methods for predicting heavy/medium-duty vehicle fuel consumption based on driving cycle information. A polynomial model, a black box artificial neural net model, a polynomial neural network model, and a multivariate adaptive regression splines (MARS) model were developed and verified using data collected from chassis testing performed on a parcel delivery diesel truck operating over the Heavy Heavy-Duty Diesel Truck (HHDDT), City Suburban Heavy Vehicle Cycle (CSHVC), New York Composite Cycle (NYCC), and hydraulic hybrid vehicle (HHV) drive cycles. Each model was trained using one of four drive cycles as a training cycle and the other three as testing cycles. By comparing the training and testing results, a representative training cycle was chosen and used to further tune each method. HHDDT as the training cycle gave the best predictive results, because HHDDT contains a variety of drive characteristics, such as high speed, acceleration, idling, and deceleration. Among the four model approaches, MARS gave the best predictive performance, with an average absolute percent error of -1.84% over the four chassis dynamometer drive cycles. To further evaluate the accuracy of the predictive models, the approaches were first applied to real-world data. MARS outperformed the other three approaches, providing an average absolute percent error of -2.2% of four real-world road segments. The MARS model performance was then compared to HHDDT, CSHVC, NYCC, and HHV drive cycles with the performance from Future Automotive System Technology Simulator (FASTSim). The results indicated that the MARS method achieved a comparative predictive performance with FASTSim.

  14. The road maintenance funding models in Indonesia use earmarked tax

    Science.gov (United States)

    Gultom, Tiopan Henry M.; Tamin, Ofyar Z.; Sjafruddin, Ade; Pradono

    2017-11-01

    One of the solutions to get a sustainable road maintenance fund is to separate road sector revenue from other accounts, afterward, form a specific account for road maintenance. In 2001, Antameng and the Ministry of Public Works proposed a road fund model in Indonesia. Sources of the road funds proposal was a tariff formed on the nominal total tax. The policy of road funds was proposed to finance the road network maintenance of districts and provincials. This research aims to create a policy model of road maintenance funds in Indonesia using an earmarked tax mechanism. The research method is qualitative research, with data collection techniques are triangulation. Interview methods conducted were semi-structured. Strength, Weakness, Opportunities, and Threat from every part of the models were showen on the survey format. Respondents were representative of executives who involved directly against the financing of road maintenance. Validation model conducted by a discussion panel, it was called the Focus Group Discussion (FGD). The FGD involved all selected respondents. Road maintenance financing model that most appropriately applied in Indonesia was a model of revenue source use an earmarked PBBKB, PKB and PPnBM. Revenue collection mechanism was added tariff of registered vehicle tax (PKB), Vehicle Fuel Tax (PBBKB) and the luxury vehicle sales tax (PPnBM). The funds are managed at the provincial level by a public service agency.

  15. A Dynamic Panel Model of the Associations of Sweetened Beverage Purchases With Dietary Quality and Food-Purchasing Patterns

    Science.gov (United States)

    Piernas, Carmen; Ng, Shu Wen; Mendez, Michelle A.; Gordon-Larsen, Penny; Popkin, Barry M.

    2015-01-01

    Investigating the association between consumption of sweetened beverages and dietary quality is challenging because issues such as reverse causality and unmeasured confounding might result in biased and inconsistent estimates. Using a dynamic panel model with instrumental variables to address those issues, we examined the independent associations of beverages sweetened with caloric and low-calorie sweeteners with dietary quality and food-purchasing patterns. We analyzed purchase data from the Homescan survey, an ongoing, longitudinal, nationally representative US survey, from 2000 to 2010 (n = 34,294). Our model included lagged measures of dietary quality and beverage purchases (servings/day in the previous year) as exposures to predict the outcomes (macronutrient (kilocalories per capita per day; %), total energy, and food purchases) in the next year after adjustment for other sociodemographic covariates. Despite secular declines in purchases (kilocalories per capita per day) from all sources, each 1-serving/day increase in consumption of either beverage type resulted in higher purchases of total daily kilocalories and kilocalories from food, carbohydrates, total sugar, and total fat. Each 1-serving/day increase in consumption of either beverage was associated with more purchases of caloric-sweetened desserts or sweeteners, which accounted for a substantial proportion of the increase in total kilocalories. We concluded that consumers of both beverages sweetened with low-calorie sweeteners and beverages sweetened with caloric sweeteners had poorer dietary quality, exhibited higher energy from all purchases, sugar, and fat, and purchased more caloric-sweetened desserts/caloric sweeteners compared with nonconsumers. PMID:25834139

  16. A dynamic panel model of the associations of sweetened beverage purchases with dietary quality and food-purchasing patterns.

    Science.gov (United States)

    Piernas, Carmen; Ng, Shu Wen; Mendez, Michelle A; Gordon-Larsen, Penny; Popkin, Barry M

    2015-05-01

    Investigating the association between consumption of sweetened beverages and dietary quality is challenging because issues such as reverse causality and unmeasured confounding might result in biased and inconsistent estimates. Using a dynamic panel model with instrumental variables to address those issues, we examined the independent associations of beverages sweetened with caloric and low-calorie sweeteners with dietary quality and food-purchasing patterns. We analyzed purchase data from the Homescan survey, an ongoing, longitudinal, nationally representative US survey, from 2000 to 2010 (n = 34,294). Our model included lagged measures of dietary quality and beverage purchases (servings/day in the previous year) as exposures to predict the outcomes (macronutrient (kilocalories per capita per day; %), total energy, and food purchases) in the next year after adjustment for other sociodemographic covariates. Despite secular declines in purchases (kilocalories per capita per day) from all sources, each 1-serving/day increase in consumption of either beverage type resulted in higher purchases of total daily kilocalories and kilocalories from food, carbohydrates, total sugar, and total fat. Each 1-serving/day increase in consumption of either beverage was associated with more purchases of caloric-sweetened desserts or sweeteners, which accounted for a substantial proportion of the increase in total kilocalories. We concluded that consumers of both beverages sweetened with low-calorie sweeteners and beverages sweetened with caloric sweeteners had poorer dietary quality, exhibited higher energy from all purchases, sugar, and fat, and purchased more caloric-sweetened desserts/caloric sweeteners compared with nonconsumers. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  17. Learning dynamics in research alliances: A panel data analysis

    NARCIS (Netherlands)

    Duso, T.; Pennings, E.; Seldeslachts, J.

    2010-01-01

    The aim of this paper is to empirically test the determinants of Research Joint Ventures’ (RJVs) group dynamics. We develop a model based on learning and transaction cost theories, which represent the benefits and costs of RJV participation, respectively. According to our framework, firms at each

  18. Scenario analysis on alternative fuel/vehicle for China's future road transport: Life-cycle energy demand and GHG emissions

    International Nuclear Information System (INIS)

    Ou Xunmin; Zhang Xiliang; Chang Shiyan

    2010-01-01

    The rapid growth of vehicles has resulted in continuing growth in China's oil demand. This paper analyzes future trends of both direct and life cycle energy demand (ED) and greenhouse gas (GHG) emissions in China's road transport sector, and assesses the effectiveness of possible reduction measures by using alternative vehicles/fuels. A model is developed to derive a historical trend and to project future trends. The government is assumed to do nothing additional in the future to influence the long-term trends in the business as usual (BAU) scenario. Four specific scenarios are used to describe the future cases where different alternative fuel/vehicles are applied. The best case scenario is set to represent the most optimized case. Direct ED and GHG emissions would reach 734 million tonnes of oil equivalent and 2384 million tonnes carbon dioxide equivalent by 2050 in the BAU case, respectively, more than 5.6 times of 2007 levels. Compared with the BAU case, the relative reductions achieved in the best case would be 15.8% and 27.6% for life cycle ED and GHG emissions, respectively. It is suggested for future policy implementation to support sustainable biofuel and high efficient electric-vehicles, and the deployment of coal-based fuels accompanied with low-carbon technology.

  19. A Modelling Framework for estimating Road Segment Based On-Board Vehicle Emissions

    International Nuclear Information System (INIS)

    Lin-Jun, Yu; Ya-Lan, Liu; Yu-Huan, Ren; Zhong-Ren, Peng; Meng, Liu Meng

    2014-01-01

    Traditional traffic emission inventory models aim to provide overall emissions at regional level which cannot meet planners' demand for detailed and accurate traffic emissions information at the road segment level. Therefore, a road segment-based emission model for estimating light duty vehicle emissions is proposed, where floating car technology is used to collect information of traffic condition of roads. The employed analysis framework consists of three major modules: the Average Speed and the Average Acceleration Module (ASAAM), the Traffic Flow Estimation Module (TFEM) and the Traffic Emission Module (TEM). The ASAAM is used to obtain the average speed and the average acceleration of the fleet on each road segment using FCD. The TFEM is designed to estimate the traffic flow of each road segment in a given period, based on the speed-flow relationship and traffic flow spatial distribution. Finally, the TEM estimates emissions from each road segment, based on the results of previous two modules. Hourly on-road light-duty vehicle emissions for each road segment in Shenzhen's traffic network are obtained using this analysis framework. The temporal-spatial distribution patterns of the pollutant emissions of road segments are also summarized. The results show high emission road segments cluster in several important regions in Shenzhen. Also, road segments emit more emissions during rush hours than other periods. The presented case study demonstrates that the proposed approach is feasible and easy-to-use to help planners make informed decisions by providing detailed road segment-based emission information

  20. Highly-resolved modeling of personal transportation energy consumption in the United States

    International Nuclear Information System (INIS)

    Muratori, Matteo; Moran, Michael J.; Serra, Emmanuele; Rizzoni, Giorgio

    2013-01-01

    This paper centers on the estimation of the total primary energy consumption for personal transportation in the United States, to include gasoline and/or electricity consumption, depending on vehicle type. The bottom-up sector-based estimation method introduced here contributes to a computational tool under development at The Ohio State University for assisting decision making in energy policy, pricing, and investment. In order to simulate highly-resolved consumption profiles three main modeling steps are needed: modeling the behavior of drivers, generating realistic driving profiles, and simulating energy consumption of different kinds of vehicles. The modeling proposed allows for evaluating the impact of plug-in electric vehicles on the electric grid – especially at the distribution level. It can serve as a tool to compare different vehicle types and assist policy-makers in estimating their impact on primary energy consumption and the role transportation can play to reduce oil dependency. - Highlights: • Modeling primary energy consumption for personal transportation in the United States. • Behavior of drivers has been simulated in order to establish when driving events occur and the length of each event. • Realistic driving profiles for each driving event are generated using a stochastic model. • The model allows for comparing the initial cost of different vehicles and their expected energy-use operating cost. • Evaluation of the impact of PEVs on the electric grid – especially at the distribution level – can be performed

  1. Continuous time modeling of panel data by means of SEM

    NARCIS (Netherlands)

    Oud, J.H.L.; Delsing, M.J.M.H.; Montfort, C.A.G.M.; Oud, J.H.L.; Satorra, A.

    2010-01-01

    After a brief history of continuous time modeling and its implementation in panel analysis by means of structural equation modeling (SEM), the problems of discrete time modeling are discussed in detail. This is done by means of the popular cross-lagged panel design. Next, the exact discrete model

  2. Can UK passenger vehicles be designed to meet 2020 emissions targets? A novel methodology to forecast fuel consumption with uncertainty analysis

    International Nuclear Information System (INIS)

    Martin, Niall P.D.; Bishop, Justin D.K.; Choudhary, Ruchi; Boies, Adam M.

    2015-01-01

    Highlights: • This paper introduces a Bayesian methodology to quantify new car fuel consumption. • Model presents user with more realistic, on-road, fuel consumption estimates. • Sources of NEDC uncertainty attributed to imprecise assumptions for resistances. • Fuel consumption of average UK car projected to exceed 2020 emissions standards. - Abstract: Vehicle manufacturers are required to reduce their European sales-weighted emissions to 95 g CO_2/km by 2020, with the aim of reducing on-road fleet fuel consumption. Nevertheless, current fuel consumption models are not suited for the European market and are unable to account for uncertainties when used to forecast passenger vehicle energy-use. Therefore, a new methodology is detailed herein to quantify new car fleet fuel consumption based on vehicle design metrics. The New European Driving Cycle (NEDC) is shown to underestimate on-road fuel consumption in Spark (SI) and Compression Ignition (CI) vehicles by an average of 16% and 13%, respectively. A Bayesian fuel consumption model attributes these discrepancies to differences in rolling, frictional and aerodynamic resistances. Using projected inputs for engine size, vehicle mass, and compression ratio, the likely average 2020 on-road fuel consumption was estimated to be 7.6 L/100 km for SI and 6.4 L/100 km for CI vehicles. These compared to NEDC based estimates of 5.34 L/100 km (SI) and 4.28 L/100 km (CI), both of which exceeded mandatory 2020 fuel equivalent emissions standards by 30.2% and 18.9%, respectively. The results highlight the need for more stringent technological developments for manufacturers to ensure adherence to targets, and the requirements for more accurate measurement techniques that account for discrepancies between standardised and on-road fuel consumption.

  3. Estimated routine radiation doses to transportation workers in alternative spent-fuel transportation systems

    International Nuclear Information System (INIS)

    Schneider, K.J.; Smith, R.I.; Daling, P.M.; Ross, W.A.; McNair, G.W.

    1988-01-01

    The federal system for the management of spent fuel and high-level radioactive waste includes the acceptance by the US Department of Energy (DOE) of the spent fuel or waste loaded in casks at the reactor or other waste generators, its transportation to a repository, and its handling and final emplacement in the repository. The DOE plans to implement a transportation system that is safe, secure, efficient, and cost-effective and will meet applicable regulatory safety and security requirements. The DOE commissioned the Pacific Northwest Laboratory (PNL) to develop estimates of the routine radiation doses that would result from the operation of a system postulated using current designs and practices. From that evaluation, PNL identified activities/operations that result in the higher fraction of doses, proposed conceptual alternatives that would effectively reduce such exposures, and evaluated the cost-effectiveness of such alternatives. The study is one of a series used in making overall system design and operational decisions in the development of the DOE's spent-fuel/high-level waste transportation system. This paper contains the highlights from the PNL study of the estimated radiation doses to the transportation workers in a postulated reference transportation system and potential alternatives to that system

  4. Analysis of energy consumption and CO{sub 2} emissions of the life cycle of bio-hydrogen applied to the Portuguese road transportation sector

    Energy Technology Data Exchange (ETDEWEB)

    Ferreira, Ana Filipa; Baptista, Patricia; Silva, Carla [IDMEC (Portugal). Dept. of Mechanical Engineering

    2010-07-01

    In this work the main objective is to analyze energy consumption and CO{sub 2} emissions of biohydrogen for use in the transportation sector in Portugal. A life cycle assessment will be performed in order to evaluate bio-hydrogen pathways, having biodiesel and conventional fossil diesel as reference. The pathways were production of feedstock, pre-treatment, treatment, compression, distribution and applications. For the well-to-tank analysis the SimaPro 7.1 software and excel tools are used. This study includes not only a well-to-tank analysis but also a tank-to-wheel analysis (using ADVISOR software) estimating hydrogen consumption and electricity consumption of a fuel cell hybrid and a plug-in hybrid. Several bio-hydrogen feedstocks to produce hydrogen through fermentation processes will be considered: potato peels. (orig.)

  5. Dynamic analysis and application of fuel elements pneumatic transportation in a pebble bed reactor

    International Nuclear Information System (INIS)

    Liu, Hongbing; Du, Dong; Han, Zandong; Zou, Yirong; Pan, Jiluan

    2015-01-01

    Almost 10,000 spherical fuel elements are transported pneumatically one by one in the pipeline outside the core of a pebble bed reactor every day. Any failure in the transportation will lead to the shutdown of the reactor, even safety accidents. In order to ensure a stable and reliable transportation, it's of great importance to analyze the motion and force condition of the fuel element. In this paper, we focus on the dynamic analysis of the pneumatic transportation of the fuel element and derive kinetic equations. Then we introduce the design of the transportation pipeline. On this basis we calculate some important data such as the velocity of the fuel element, the force between the fuel element and the pipeline and the efficiency of the pneumatic transportation. Then we analyze these results and provide some suggestions for the design of the pipeline. The experiment was carried out on an experimental platform. The velocities of the fuel elements were measured. The experimental results were consistent with and validated the theoretical analysis. The research may offer the basis for the design of the transportation pipeline and the optimization of the fuel elements transportation in a pebble bed reactor. - Highlights: • The kinetic equations of the fuel element in pneumatic transportation are derived. • The dynamic characteristics of the fuel element are analyzed. • Some important parameters are calculated based on the kinetic equations. • The experimental results were consistent with the analysis and verified the analysis. • This paper may offer an important guide to the research of a pebble bed reactor

  6. Assessment of alternative fuel and powertrain transit bus options using real-world operations data: Life-cycle fuel and emissions modeling

    International Nuclear Information System (INIS)

    Xu, Yanzhi; Gbologah, Franklin E.; Lee, Dong-Yeon; Liu, Haobing; Rodgers, Michael O.; Guensler, Randall L.

    2015-01-01

    Highlights: • We present a practical fuel and emissions modeling tool for alternative fuel buses. • The model assesses well-to-wheels emissions impacts of bus fleet decisions. • Mode-based approach is used to account for duty cycles and local conditions. • A case study using real-world operations data from Atlanta, GA is presented. • Impacts of alternative bus options depend on operating and geographic features. - Abstract: Hybrid and electric powertrains and alternative fuels (e.g., compressed natural gas (CNG), biodiesel, or hydrogen) can often reduce energy consumption and emissions from transit bus operations relative to conventional diesel. However, the magnitude of these energy and emissions savings can vary significantly, due to local conditions and transit operating characteristics. This paper introduces the transit Fuel and Emissions Calculator (FEC), a mode-based life-cycle emissions modeling tool for transit bus and rail technologies that compares the performance of multiple alternative fuels and powertrains across a range of operational characteristics and conditions. The purpose of the FEC is to provide a practical, yet technically sophisticated tool for regulatory agencies and policy analysts in assessing transit fleet options. The FEC’s modal modeling approach estimates emissions as a function of engine load, which in turn is a function of transit service parameters, including duty cycle (idling and speed-acceleration profile), road grade, and passenger loading. This approach allows for customized assessments that account for local conditions. Direct emissions estimates are derived from the scaled tractive power (STP) operating mode bins and emissions factors employed in the U.S. EPA’s MOVES (MOtor Vehicle Emissions Simulator) model. Life-cycle emissions estimates are calculated using emissions factors from the GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) model. The case study presented in this paper

  7. Flow and nutrient dynamics in a subterranean estuary (Waquoit Bay, MA, USA) : Field data and reactive transport modeling

    NARCIS (Netherlands)

    Spiteri, C.; Slomp, C.P.; Charette, M.A.; Tuncay, K.; Meile, C.

    2008-01-01

    A two-dimensional (2D) reactive transport model is used to investigate the controls on nutrient (NO3-, NH4+, PO4) dynamics in a coastal aquifer. The model couples density-dependent flow to a reaction network which includes oxic degradation of organic matter, denitrification, iron oxide reduction,

  8. Estimating increment-decrement life tables with multiple covariates from panel data: the case of active life expectancy.

    Science.gov (United States)

    Land, K C; Guralnik, J M; Blazer, D G

    1994-05-01

    A fundamental limitation of current multistate life table methodology-evident in recent estimates of active life expectancy for the elderly-is the inability to estimate tables from data on small longitudinal panels in the presence of multiple covariates (such as sex, race, and socioeconomic status). This paper presents an approach to such an estimation based on an isomorphism between the structure of the stochastic model underlying a conventional specification of the increment-decrement life table and that of Markov panel regression models for simple state spaces. We argue that Markov panel regression procedures can be used to provide smoothed or graduated group-specific estimates of transition probabilities that are more stable across short age intervals than those computed directly from sample data. We then join these estimates with increment-decrement life table methods to compute group-specific total, active, and dependent life expectancy estimates. To illustrate the methods, we describe an empirical application to the estimation of such life expectancies specific to sex, race, and education (years of school completed) for a longitudinal panel of elderly persons. We find that education extends both total life expectancy and active life expectancy. Education thus may serve as a powerful social protective mechanism delaying the onset of health problems at older ages.

  9. Model architecture of intelligent data mining oriented urban transportation information

    Science.gov (United States)

    Yang, Bogang; Tao, Yingchun; Sui, Jianbo; Zhang, Feizhou

    2007-06-01

    Aiming at solving practical problems in urban traffic, the paper presents model architecture of intelligent data mining from hierarchical view. With artificial intelligent technologies used in the framework, the intelligent data mining technology improves, which is more suitable for the change of real-time road condition. It also provides efficient technology support for the urban transport information distribution, transmission and display.

  10. Elucidating the consumption and CO_2 emissions of fossil fuels and low-carbon energy in the United States using Lotka–Volterra models

    International Nuclear Information System (INIS)

    Tsai, Bi-Huei; Chang, Chih-Jen; Chang, Chun-Hsien

    2016-01-01

    By using the Lotka–Volterra model, this work examines for the first time the feasibility of using low-carbon energy to reduce fossil fuel consumption in the United States and, ultimately, to decrease CO_2 emissions. The research sample in this work consists of data on energy consumption and CO_2 emissions in the United States. Parameter estimation results reveal that although the consumption of low-carbon energy increases the consumption of fossil fuels, the latter does not affect the former. Low-carbon energy usage, including nuclear energy and solar photovoltaic power, increases fossil fuel consumption because the entire lifetime of a nuclear or solar energy facility, from the construction of electricity plants to decommissioning, consumes tremendous amounts of fossil fuels. This result verifies the infeasibility of low-carbon energy to replace fossil fuels under the current mining technology, electricity generation skills and governmental policy in the United States and explains why the United States refused to become a signatory of the Kyoto Protocol. Equilibrium analysis results indicate that the annual consumption of fossil fuels will ultimately exceed that of low-carbon energy by 461%. Since our proposed Lotka–Volterra model accurately predicts the consumption and CO_2 emission of different energy sources, this work contributes to the energy policies. - Highlights: • Our Lotka–Volterra model accurately predicts consumption of different energy sources. • We find the current infeasibility of using low-carbon energy to reduce fossil fuels. • The set-up of nuclear and solar plants increases fossil fuel usage in the U.S. • The consumption of fossil fuels will exceed that of low-carbon energy by 435%. • United States government prefers economic development over environmental protection.

  11. A New Model for the Estimation of Cell Proliferation Dynamics Using CFSE Data

    Science.gov (United States)

    2011-08-20

    CFSE FI has a linear relationship with the concentration of CFSE used in the staining process [49, Fig. 3] and is expected to correlate with the mass...approximately 1. Thus it appears that cellular autofluorescence is sufficient to account for the observed relationships between subsequent division...and V. Subramanian, On the impact of correlation between collaterally consanguineous cells on lymphocyte population dynamics, J. Math. Biol. 59 (2009

  12. Coordination of ministerial actions regarding the use of liquefied natural gas (LNG) as fuel. LNG, a European component of the energy transition in road freight transport

    International Nuclear Information System (INIS)

    Maler, Philippe; Erhardt, Jean-Bernard; Ourliac, Jean-Paul

    2015-09-01

    This report is the third of a series dealing with the coordination of ministerial actions in favor of the use of liquefied natural gas (LNG) as fuel in transports. LNG is an important potential substitute to diesel fuel in road transport and would allow significant abatement of nitrogen oxides emissions. Bio-LNG is ten times less polluting than fossil fuel LNG and thus important efforts are to be made in bio-LNG R and D. An important work has been carried out for adapting EU regulations and standards to LNG vehicles and LNG supply developments. This report presents, first, a summary of the report's recommendations and the aim of this coordination study, and, then, treats more thoroughly of the different coordination aspects: 1 - European framework of energy transition in the road freight transport (differences with maritime transport, CO 2 emissions abatement, trucks pollution and fuel quality standards, trucks technical specifications and equipment, fuel taxes in EU countries); 2 - European policy and national actions in favour of LNG development for road transport (LNG as alternate fuel, the Paris agreement, the French national energy plan); 3 - Environmental benefits of LNG in road transport (public health impacts, nitrogen oxides abatement, divergent views and expertise, LNG and CO 2 abatement measures, bio-LNG environmental evaluation; 4 - LNG development actors in road transport and the administrative coordination (professional organizations, public stakeholders, LNG topics information dissemination at the Ministry); 5 - LNG development in road transport at the worldwide, European and national scales; 6 - European regulations and standards allowing trucks LNG fueling and circulation (standard needs, users information, regulation works); 7 - Common rules to define and implement for personnel training; 8 - reflexion on LNG taxation; 9 - support policy for a road transport LNG supply chain (infrastructures, European financing, lessons learnt from maritime

  13. Modeling real-world fuel consumption and carbon dioxide emissions with high resolution for light-duty passenger vehicles in a traffic populated city

    International Nuclear Information System (INIS)

    Zhang, Shaojun; Wu, Ye; Un, Puikei; Fu, Lixin; Hao, Jiming

    2016-01-01

    Modeling fuel consumption of light-duty passenger vehicles has created substantial concerns due to the uncertainty from real-world operating conditions. Macao is world-renowned for its tourism industry and high population density. An empirical model is developed to estimate real-world fuel consumption and carbon dioxide emissions for gasoline-powered light-duty passenger vehicles in Macao by considering local fleet configuration and operating conditions. Thanks to increasingly stringent fuel consumption limits in vehicle manufacturing countries, estimated type-approval fuel consumption for light-duty passenger vehicles in Macao by model year was reduced from 7.4 L/100 km in 1995 to 5.9 L/100 km in 2012, although a significant upsizing trend has considerably offset potential energy-saving benefit. However, lower driving speed and the air-conditioning usage tend to raise fleet-average fuel consumption and carbon dioxide emission factors, which are estimated to be 10.1 L/100 km and 240 g/km in 2010. Fleet-total fuel consumption and carbon dioxide emissions are modeled through registered vehicle population-based and link-level traffic demand approaches and the results satisfactorily coincide with the historical record of fuel sales in Macao. Temporal and spatial variations in fuel consumption and carbon dioxide emissions from light-duty passenger vehicles further highlight the importance of effective traffic management in congested areas of Macao. - Highlights: • A fuel consumption model is developed for Macao's light-duty passenger cars. • Increased vehicle size partially offset energy benefit from tightened fuel consumption standard. • Lower speed and use of air-conditioning greatly increase fuel use of Macao light-duty passenger cars. • A high resolution inventory of fuel use and carbon dioxide emissions is built with link-level traffic data. • Policy suggestions are provided to mitigate fuel use in a traffic populated city.

  14. A Bayesian framework based on a Gaussian mixture model and radial-basis-function Fisher discriminant analysis (BayGmmKda V1.1) for spatial prediction of floods

    Science.gov (United States)

    Tien Bui, Dieu; Hoang, Nhat-Duc

    2017-09-01

    In this study, a probabilistic model, named as BayGmmKda, is proposed for flood susceptibility assessment in a study area in central Vietnam. The new model is a Bayesian framework constructed by a combination of a Gaussian mixture model (GMM), radial-basis-function Fisher discriminant analysis (RBFDA), and a geographic information system (GIS) database. In the Bayesian framework, GMM is used for modeling the data distribution of flood-influencing factors in the GIS database, whereas RBFDA is utilized to construct a latent variable that aims at enhancing the model performance. As a result, the posterior probabilistic output of the BayGmmKda model is used as flood susceptibility index. Experiment results showed that the proposed hybrid framework is superior to other benchmark models, including the adaptive neuro-fuzzy inference system and the support vector machine. To facilitate the model implementation, a software program of BayGmmKda has been developed in MATLAB. The BayGmmKda program can accurately establish a flood susceptibility map for the study region. Accordingly, local authorities can overlay this susceptibility map onto various land-use maps for the purpose of land-use planning or management.

  15. A Bayesian framework based on a Gaussian mixture model and radial-basis-function Fisher discriminant analysis (BayGmmKda V1.1 for spatial prediction of floods

    Directory of Open Access Journals (Sweden)

    D. Tien Bui

    2017-09-01

    Full Text Available In this study, a probabilistic model, named as BayGmmKda, is proposed for flood susceptibility assessment in a study area in central Vietnam. The new model is a Bayesian framework constructed by a combination of a Gaussian mixture model (GMM, radial-basis-function Fisher discriminant analysis (RBFDA, and a geographic information system (GIS database. In the Bayesian framework, GMM is used for modeling the data distribution of flood-influencing factors in the GIS database, whereas RBFDA is utilized to construct a latent variable that aims at enhancing the model performance. As a result, the posterior probabilistic output of the BayGmmKda model is used as flood susceptibility index. Experiment results showed that the proposed hybrid framework is superior to other benchmark models, including the adaptive neuro-fuzzy inference system and the support vector machine. To facilitate the model implementation, a software program of BayGmmKda has been developed in MATLAB. The BayGmmKda program can accurately establish a flood susceptibility map for the study region. Accordingly, local authorities can overlay this susceptibility map onto various land-use maps for the purpose of land-use planning or management.

  16. Dinamika PMA dan PMDN di Indonesia Sebagai Dampak Dari Upah Minimum, Inflasi dan PDRB Tahun 2004-2012: Pendekatan Dynamic Panel Data Model

    Directory of Open Access Journals (Sweden)

    Lea Widowati Sugiharto

    2016-06-01

    Full Text Available This paper aims at investigating the behavior of foreign direct investment (FDI and domestic direct investment (DDI in Indonesia, which is expected to be explained by several explanatory variables including the setting of regional minimum wage, inflation, as well as regional domestic product. More specifically, the investigation is focused on the effect of annual increase in the minimum regional wage, provided that it is a sensitive issue for investors. Using 33 provincial level data in a period from 2004 to 2012, this paper uses a dynamic panel data which allows us to see the behavior of direct investment in the short run as well as in the long run. The result shows that an increase in the regional minimum wage setting reduces both DDI and FDI in the short run. However, in the long run, an increase in the regional minimum wage is likely to increase both DDI and FDI. This is likely indicating that in the long run an increase in wage is expected to be accompanied by higher productivity, eventhough in the short run higher wage increases cost of production which will undermine investment.

  17. Cost and energy consumption estimates for the aluminum-air battery anode fuel cycle

    Science.gov (United States)

    1990-01-01

    At the request of DOE's Office of Energy Storage and Distribution (OESD), Pacific Northwest Laboratory (PNL) conducted a study to generate estimates of the energy use and costs associated with the aluminum anode fuel cycle of the aluminum-air (Al-air) battery. The results of this analysis indicate that the cost and energy consumption characteristics of the mechanically rechargeable Al-air battery system are not as attractive as some other electrically rechargeable electric vehicle battery systems being developed by OESD. However, there are distinct advantages to mechanically rechargeable batteries, which may make the Al-air battery (or other mechanically rechargeable batteries) attractive for other uses, such as stand-alone applications. Fuel cells, such as the proton exchange membrane (PEM), and advanced secondary batteries may be better suited to electric vehicle applications.

  18. Testing woody fuel consumption models for application in Australian southern eucalypt forest fires

    Science.gov (United States)

    J.J. Hollis; S. Matthews; Roger Ottmar; S.J. Prichard; S. Slijepcevic; N.D. Burrows; B. Ward; K.G. Tolhurst; W.R. Anderson; J S. Gould

    2010-01-01

    Five models for the consumption of coarse woody debris or woody fuels with a diameter larger than 0.6 cm were assessed for application in Australian southern eucalypt forest fires including: CONSUME models for (1) activity fuels, (2) natural western woody and (3) natural southern woody fuels, (4) the BURNUP model and (5) the recommendation by the Australian National...

  19. Impact of mixed modes on measurement errors and estimates of change in panel data

    Directory of Open Access Journals (Sweden)

    Alexandru Cernat

    2015-07-01

    Full Text Available Mixed mode designs are receiving increased interest as a possible solution for saving costs in panel surveys, although the lasting effects on data quality are unknown. To better understand the effects of mixed mode designs on panel data we will examine its impact on random and systematic error and on estimates of change. The SF12, a health scale, in the Understanding Society Innovation Panel is used for the analysis. Results indicate that only one variable out of 12 has systematic differences due to the mixed mode design. Also, four of the 12 items overestimate variance of change in time in the mixed mode design. We conclude that using a mixed mode approach leads to minor measurement differences but it can result in the overestimation of individual change compared to a single mode design.

  20. Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks

    OpenAIRE

    Chaoyang Shi; Bi Yu Chen; William H. K. Lam; Qingquan Li

    2017-01-01

    Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are f...

  1. Fast Food Consumption and Food Prices: Evidence from Panel Data on 5th and 8th Grade Children

    OpenAIRE

    Khan, Tamkeen; Powell, Lisa M.; Wada, Roy

    2012-01-01

    Fast food consumption is a dietary factor associated with higher prevalence of childhood obesity in the United States. The association between food prices and consumption of fast food among 5th and 8th graders was examined using individual-level random effects models utilizing consumption data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K), price data from American Chamber of Commerce Researchers Association (ACCRA), and contextual outlet density data from...

  2. Estimation of unemployment rates using small area estimation model by combining time series and cross-sectional data

    Science.gov (United States)

    Muchlisoh, Siti; Kurnia, Anang; Notodiputro, Khairil Anwar; Mangku, I. Wayan

    2016-02-01

    Labor force surveys conducted over time by the rotating panel design have been carried out in many countries, including Indonesia. Labor force survey in Indonesia is regularly conducted by Statistics Indonesia (Badan Pusat Statistik-BPS) and has been known as the National Labor Force Survey (Sakernas). The main purpose of Sakernas is to obtain information about unemployment rates and its changes over time. Sakernas is a quarterly survey. The quarterly survey is designed only for estimating the parameters at the provincial level. The quarterly unemployment rate published by BPS (official statistics) is calculated based on only cross-sectional methods, despite the fact that the data is collected under rotating panel design. The study purpose to estimate a quarterly unemployment rate at the district level used small area estimation (SAE) model by combining time series and cross-sectional data. The study focused on the application and comparison between the Rao-Yu model and dynamic model in context estimating the unemployment rate based on a rotating panel survey. The goodness of fit of both models was almost similar. Both models produced an almost similar estimation and better than direct estimation, but the dynamic model was more capable than the Rao-Yu model to capture a heterogeneity across area, although it was reduced over time.

  3. Demand for road-fuel in a small developing economy: The case of Sri Lanka

    International Nuclear Information System (INIS)

    Chandrasiri, Sunil

    2006-01-01

    This paper estimates the demand for road fuel (petrol and auto-diesel) in the context of a small developing economy-Sri Lanka. The data set covers a period of 39 years from 1964 to 2002 representing both close economy and open economy policy regimes. The estimation procedure is based on seemingly unrelated regression equation (SURE) methodology mainly to capture substitutability of petrol and diesel in road transportation. The effect of auto-fuel prices on vehicle demand is also analyzed as a part of the analysis. In addition to confirming existing evidence on road-fuel demand, the findings reveal some interesting evidence with respect to own-price elasticity, cross-price elasticity, lag effects, income and vehicle mix variables

  4. Reduction potentials of energy demand and GHG emissions in China's road transport sector

    International Nuclear Information System (INIS)

    Yan Xiaoyu; Crookes, Roy J.

    2009-01-01

    Rapid growth of road vehicles, private vehicles in particular, has resulted in continuing growth in China's oil demand and imports, which has been widely accepted as a major factor effecting future oil availability and prices, and a major contributor to China's GHG emission increase. This paper is intended to analyze the future trends of energy demand and GHG emissions in China's road transport sector and to assess the effectiveness of possible reduction measures. A detailed model has been developed to derive a reliable historical trend of energy demand and GHG emissions in China's road transport sector between 2000 and 2005 and to project future trends. Two scenarios have been designed to describe the future strategies relating to the development of China's road transport sector. The 'Business as Usual' scenario is used as a baseline reference scenario, in which the government is assumed to do nothing to influence the long-term trends of road transport energy demand. The 'Best Case' scenario is considered to be the most optimized case where a series of available reduction measures such as private vehicle control, fuel economy regulation, promoting diesel and gas vehicles, fuel tax and biofuel promotion, are assumed to be implemented. Energy demand and GHG emissions in China's road transport sector up to 2030 are estimated in these two scenarios. The total reduction potentials in the 'Best Case' scenario and the relative reduction potentials of each measure have been estimated

  5. Modeling and simulation of the dynamic behavior of portable proton exchange membrane fuel cells

    Energy Technology Data Exchange (ETDEWEB)

    Ziegler, C.

    2005-07-01

    In order to analyze the operational behavior, a mathematical model of planar self-breathing fuel cells is developed and validated in Chapter 3 of this thesis. The multicomponent transport of the species is considered as well as the couplings between the transport processes of heat, charge, and mass and the electrochemical reactions. Furthermore, to explain the oxygen mass transport limitation in the porous electrode of the cathode side an agglomerate model for the oxygen reduction reaction is developed. In Chapter 4 the important issue of liquid water generation and transport in PEMFCs is addressed. One of the major tasks when operating this type of fuel cell is avoiding the complete flooding of the PEMFC during operation. A one-dimensional and isothermal model is developed that is based on a coupled system of partial differential equations. The model contains a dynamic and two-phase description of the proton exchange membrane fuel cell. The mass transport in the gas phase and in the liquid phase is considered as well as the phase transition between liquid water and water vapor. The transport of charges and the electrochemical reactions are part of the model. Flooding effects that are caused by liquid water accumulation are described by this model. Moreover, the model contains a time-dependent description of the membrane that accounts for Schroeder's paradox. The model is applied to simulate cyclic voltammograms. Chapter 5 is focused on the dynamic investigation of PEMFC stacks. Understanding the dynamic behavior of fuel cell stacks is important for the operation and control of fuel cell stacks. Using the single cell model of Chapter 3 and the dynamic model of Chapter 4 as basis, a mathematical model of a PEMFC stack is developed. However, due to the complexity of a fuel cell stack, the spatial resolution and dynamic description of the liquid water transport are not accounted for. These restrictions allow for direct comparison between the solution variables of

  6. Estimating the Returns to Firm-Sponsored on-the-Job and Classroom Training

    OpenAIRE

    Benoit Dostie

    2010-01-01

    In this paper, we estimate returns to classroom and on-the-job firm-sponsored training in terms of value-added per worker using longitudinal linked employee-employer Canadian data from 1999 to 2006. We estimate a standard production function controlling for endogenous training decisions because of perceived net benefits and time-varying market conditions using dynamic panel GMM methods. We find that employees who undertook classroom training are 11 percent more productive than otherwise simil...

  7. Comparison of the transportation risks for the spent fuel in Korea for different transportation scenarios

    International Nuclear Information System (INIS)

    Jeong, Jongtae; Cho, D.K.; Choi, H.J.; Choi, J.W.

    2011-01-01

    According to the long term management strategy for spent fuels in Korea, they will be transported from the spent fuel pools in each nuclear power plant to the central interim storage facility (CISF) which is to start operation in 2016. At the start of the operation of the final repository (FR), by the year 2065, transport will then take place between the CISF and the FR. Therefore, we have to determine the safe and economical logistics for the transportation of these spent fuels by considering their transportation risks and costs. In this study, we developed four transportation scenarios for a maritime transportation by considering the type of transportation casks and transport means in order to suggest safe and economical transportation logistics for the spent fuels in Korea. And, we estimated and compared the transportation risks for these four transportation scenarios. Also, we estimated and compared the transportation risks resulting from accidents during the transportation of PWR and PHWR spent fuels by road trailers from the CISF and the FR. From the results of this study, we found that risks resulting from accidents during the transportation of the spent fuels have a very low radiological risk activity with a manageable safety and health consequences. The results of this study can be used as basic data for the development of safe and economical logistics for a transportation of the spent fuels in Korea by considering the transportation costs for the four scenarios which will be needed in the near future.

  8. Dynamics of Metabolism and Decision Making During Alcohol Consumption: Modeling and Analysis.

    Science.gov (United States)

    Giraldo, Luis Felipe; Passino, Kevin M; Clapp, John D; Ruderman, Danielle

    2017-11-01

    Heavy alcohol consumption is considered an important public health issue in the United States as over 88 000 people die every year from alcohol-related causes. Research is being conducted to understand the etiology of alcohol consumption and to develop strategies to decrease high-risk consumption and its consequences, but there are still important gaps in determining the main factors that influence the consumption behaviors throughout the drinking event. There is a need for methodologies that allow us not only to identify such factors but also to have a comprehensive understanding of how they are connected and how they affect the dynamical evolution of a drinking event. In this paper, we use previous empirical findings from laboratory and field studies to build a mathematical model of the blood alcohol concentration dynamics in individuals that are in drinking events. We characterize these dynamics as the result of the interaction between a decision-making system and the metabolic process for alcohol. We provide a model of the metabolic process for arbitrary alcohol intake patterns and a characterization of the mechanisms that drive the decision-making process of a drinker during the drinking event. We use computational simulations and Lyapunov stability theory to analyze the effects of the parameters of the model on the blood alcohol concentration dynamics that are characterized. Also, we propose a methodology to inform the model using data collected in situ and to make estimations that provide additional information to the analysis. We show how this model allows us to analyze and predict previously observed behaviors, to design new approaches for the collection of data that improves the construction of the model, and help with the design of interventions.

  9. Evaluating the Impact of Road Grade on Simulated Commercial Vehicle Fuel Economy Using Real-World Drive Cycles

    Energy Technology Data Exchange (ETDEWEB)

    Lopp, Sean; Wood, Eric; Duran, Adam

    2015-10-13

    Commercial vehicle fuel economy is known to vary significantly with both positive and negative road grade. Medium- and heavy-duty vehicles operating at highway speeds require incrementally larger amounts of energy to pull heavy payloads up inclines as road grade increases. Non-hybrid vehicles are then unable to recapture energy on descent and lose energy through friction braking. While the on-road effects of road grade are well understood, the majority of standard commercial vehicle drive cycles feature no climb or descent requirements. Additionally, existing literature offers a limited number of sources that attempt to estimate the on-road energy implications of road grade in the medium- and heavy-duty space. This study uses real-world commercial vehicle drive cycles from the National Renewable Energy Laboratory's Fleet DNA database to simulate the effects of road grade on fuel economy across a range of vocations, operating conditions, and locations. Drive-cycles are matched with vocation-specific vehicle models and simulated with and without grade. Fuel use due to grade is presented, and variation in fuel consumption due to drive cycle and vehicle characteristics is explored through graphical and statistical comparison. The results of this study suggest that road grade accounts for 1%-9% of fuel use in commercial vehicles on average and up to 40% on select routes.

  10. Improved estimation of geocenter motion and changes in the Earth's dynamic oblateness from GRACE data and an ocean bottom pressure model

    Science.gov (United States)

    Sun, Y.; Ditmar, P.; Riva, R.

    2015-12-01

    The Gravity Recovery and Climate Experiment (GRACE) satellite mission, since the launch in 2002, has enabled the monitoring of mass transport in the Earth's system on a monthly basis. In spite of continuous improvements in data processing techniques, an estimation of very low-degree spherical harmonic coefficients remains problematic. GRACE is insensitive to variations in the degree-1 coefficients (ΔC11, ΔS11 and ΔC10), which reflect the motion of the geocenter. The variations of C20 coefficients, which characterize changes in the Earth's dynamic oblateness (Δ J2) are corrupted by ocean tide aliases and usually replaced with estimates from other techniques.In this study, the methodology proposed by Swenson et al. (2008) to estimate geocenter motion is updated and extended to co-estimate changes in the Earth's dynamic oblateness. The algorithm uses monthly GRACE gravity solutions (in the form of spherical harmonic coefficients), an ocean bottom pressure model (over the oceans), and a glacial isostatic adjustment (GIA) model (globally). GRACE solutions over coastal areas may suffer from signal leakage due to their limited spectral content and to filtering. We effectively avoid the influence of this effect by introducing a carefully chosen buffer zone. We also take into account self-attraction and loading effects when dealing with water redistribution in the oceans. The estimated annual amplitude of ΔC10 , i.e. the Z component of the geocenter motion, is significantly amplified compared to the original estimations of Swenson et al. (2008) and it is in line with estimates from other techniques, such as the global GPS inversion. The resulting ΔC20 time-series agree remarkably well with a solution based on satellite laser ranging data, which is currently believed to be one of the most accurate sources of information on changes in the Earth's dynamic oblateness. Trends in both geocenter position and the Earth's oblateness are estimated as well. The results show a

  11. Supply and demand in physician markets: a panel data analysis of GP services in Australia.

    Science.gov (United States)

    McRae, Ian; Butler, James R G

    2014-09-01

    To understand the trends in any physician services market it is necessary to understand the nature of both supply and demand, but few studies have jointly examined supply and demand in these markets. This study uses aggregate panel data on general practitioner (GP) services at the Statistical Local Area level in Australia spanning eight years to estimate supply and demand equations for GP services. The structural equations of the model are estimated separately using population-weighted fixed effects panel modelling with the two stage least squares formulation of the generalised method of moments approach (GMM (2SLS)). The estimated price elasticity of demand of [Formula: see text] is comparable with other studies. The direct impact of GP density on demand, while significant, proves almost immaterial in the context of near vertical supply curves. Supply changes are therefore due to shifts in the position of the curves, partly determined by a time trend. The model is validated by comparing post-panel model predictions with actual market outcomes over a period of three years and is found to provide surprisingly accurate projections over a period of significant policy change. The study confirms the need to jointly consider supply and demand in exploring the behaviour of physician services markets.

  12. Does electricity consumption panel Granger cause GDP? A new global evidence

    Energy Technology Data Exchange (ETDEWEB)

    Narayan, Paresh Kumar [School of Accounting, Economics and Finance, Faculty of Business and Economics, Deakin University, Melbourne (Australia); Narayan, Seema [School of Economics, Finance, and Marketing, RMIT University, Melbourne (Australia); Popp, Stephan [Department of Economics, University of Duisburg-Essen (Germany)

    2010-10-15

    The goal of this paper is to undertake a panel data investigation of long-run Granger causality between electricity consumption and real GDP for seven panels, which together consist of 93 countries. We use a new panel causality test and find that in the long-run both electricity consumption and real GDP have a bidirectional Granger causality relationship except for the Middle East where causality runs only from GDP to electricity consumption. Finally, for the G6 panel the estimates reveal a negative sign effect, implying that increasing electricity consumption in the six most industrialised nations will reduce GDP. (author)

  13. An Adjusted Discount Rate Model for Fuel Cycle Cost Estimation

    Energy Technology Data Exchange (ETDEWEB)

    Kim, S. K.; Kang, G. B.; Ko, W. I. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2013-10-15

    Owing to the diverse nuclear fuel cycle options available, including direct disposal, it is necessary to select the optimum nuclear fuel cycles in consideration of the political and social environments as well as the technical stability and economic efficiency of each country. Economic efficiency is therefore one of the significant evaluation standards. In particular, because nuclear fuel cycle cost may vary in each country, and the estimated cost usually prevails over the real cost, when evaluating the economic efficiency, any existing uncertainty needs to be removed when possible to produce reliable cost information. Many countries still do not have reprocessing facilities, and no globally commercialized HLW (High-level waste) repository is available. A nuclear fuel cycle cost estimation model is therefore inevitably subject to uncertainty. This paper analyzes the uncertainty arising out of a nuclear fuel cycle cost evaluation from the viewpoint of a cost estimation model. Compared to the same discount rate model, the nuclear fuel cycle cost of a different discount rate model is reduced because the generation quantity as denominator in Equation has been discounted. Namely, if the discount rate reduces in the back-end process of the nuclear fuel cycle, the nuclear fuel cycle cost is also reduced. Further, it was found that the cost of the same discount rate model is overestimated compared with the different discount rate model as a whole.

  14. An Adjusted Discount Rate Model for Fuel Cycle Cost Estimation

    International Nuclear Information System (INIS)

    Kim, S. K.; Kang, G. B.; Ko, W. I.

    2013-01-01

    Owing to the diverse nuclear fuel cycle options available, including direct disposal, it is necessary to select the optimum nuclear fuel cycles in consideration of the political and social environments as well as the technical stability and economic efficiency of each country. Economic efficiency is therefore one of the significant evaluation standards. In particular, because nuclear fuel cycle cost may vary in each country, and the estimated cost usually prevails over the real cost, when evaluating the economic efficiency, any existing uncertainty needs to be removed when possible to produce reliable cost information. Many countries still do not have reprocessing facilities, and no globally commercialized HLW (High-level waste) repository is available. A nuclear fuel cycle cost estimation model is therefore inevitably subject to uncertainty. This paper analyzes the uncertainty arising out of a nuclear fuel cycle cost evaluation from the viewpoint of a cost estimation model. Compared to the same discount rate model, the nuclear fuel cycle cost of a different discount rate model is reduced because the generation quantity as denominator in Equation has been discounted. Namely, if the discount rate reduces in the back-end process of the nuclear fuel cycle, the nuclear fuel cycle cost is also reduced. Further, it was found that the cost of the same discount rate model is overestimated compared with the different discount rate model as a whole

  15. REDUCING GREENHOUSE EMISSIONS AND FUEL CONSUMPTION

    Directory of Open Access Journals (Sweden)

    Susan A. SHAHEEN, Ph.D.

    2007-01-01

    Fortunately, transportation technologies and strategies are emerging that can help to meet the climate challenge. These include automotive and fuel technologies, intelligent transportation systems (ITS, and mobility management strategies that can reduce the demand for private vehicles. While the climate change benefits of innovative engine and vehicle technologies are relatively well understood, there are fewer studies available on the energy and emission impacts of ITS and mobility management strategies. In the future, ITS and mobility management will likely play a greater role in reducing fuel consumption. Studies are often based on simulation models, scenario analysis, and limited deployment experience. Thus, more research is needed to quantify potential impacts. Of the nine ITS technologies examined, traffic signal control, electronic toll collection, bus rapid transit, and traveler information have been deployed more widely and demonstrated positive impacts (but often on a limited basis. Mobility management approaches that have established the greatest CO2 reduction potential, to date, include road pricing policies (congestion and cordon and carsharing (short-term auto access. Other approaches have also indicated CO2 reduction potential including: low-speed modes, integrated regional smart cards, park-and-ride facilities, parking cash out, smart growth, telecommuting, and carpooling.

  16. Varying Coefficient Panel Data Model in the Presence of Endogenous Selectivity and Fixed Effects

    OpenAIRE

    Malikov, Emir; Kumbhakar, Subal C.; Sun, Yiguo

    2013-01-01

    This paper considers a flexible panel data sample selection model in which (i) the outcome equation is permitted to take a semiparametric, varying coefficient form to capture potential parameter heterogeneity in the relationship of interest, (ii) both the outcome and (parametric) selection equations contain unobserved fixed effects and (iii) selection is generalized to a polychotomous case. We propose a two-stage estimator. Given consistent parameter estimates from the selection equation obta...

  17. Hybrid-Electric Passenger Car Carbon Dioxide and Fuel Consumption Benefits Based on Real-World Driving.

    Science.gov (United States)

    Holmén, Britt A; Sentoff, Karen M

    2015-08-18

    Hybrid-electric vehicles (HEVs) have lower fuel consumption and carbon dioxide (CO2) emissions than conventional vehicles (CVs), on average, based on laboratory tests, but there is a paucity of real-world, on-road HEV emissions and performance data needed to assess energy use and emissions associated with real-world driving, including the effects of road grade. This need is especially great as the electrification of the passenger vehicle fleet (from HEVs to PHEVs to BEVs) increases in response to climate and energy concerns. We compared tailpipe CO2 emissions and fuel consumption of an HEV passenger car to a CV of the same make and model during real-world, on-the-road network driving to quantify the in-use benefit of one popular full HEV technology. Using vehicle specific power (VSP) assignments that account for measured road grade, the mean CV/HEV ratios of CO2 tailpipe emissions or fuel consumption defined the corresponding HEV "benefit" factor for each VSP class (1 kW/ton resolution). Averaging over all VSP classes for driving in all seasons, including temperatures from -13 to +35 °C in relatively steep (-13.2 to +11.5% grade), hilly terrain, mean (±SD) CO2 emission benefit factors were 4.5 ± 3.6, 2.5 ± 1.7, and 1.4 ± 0.5 for city, exurban/suburban arterial and highway driving, respectively. Benefit factor magnitude corresponded to the frequency of electric-drive-only (EDO) operation, which was modeled as a logarithmic function of VSP. A combined model explained 95% of the variance in HEV benefit for city, 75% for arterial and 57% for highway driving. Benefit factors consistently exceeded 2 for VSP classes with greater than 50% EDO (i.e., only city and arterial driving). The reported HEV benefits account for real-world road grade that is often neglected in regulatory emissions and fuel economy tests. Fuel use HEV benefit factors were 1.3 and 2 for the regulatory highway (HWFET) and city (FTP) cycles, respectively, 18% and 31% higher than the EPA adjusted

  18. Is an increased elderly population related to decreased CO2 emissions from road transportation?

    International Nuclear Information System (INIS)

    Okada, Akira

    2012-01-01

    Few studies have focused on the potential effects of an increase in the share of aged population on the environmental impacts of road transportation. In order to fill this gap in the literature, this paper empirically analyzes whether there is a relationship between the share of aged population and carbon dioxide (CO 2 ) emissions from road transportation by applying a quadratic function. Using international panel data, it also addresses the level of the turning point in the relationships between the share of aged population and CO 2 emissions. The analysis in this paper uses a first-order differential equation to estimate an inverted U-shaped relationship between them in order to alleviate the unit roots issue. The results from 25 OECD countries, consisting mainly of European countries and Japan, indicate that there is a quadratic relationship between CO 2 emissions per capita and the share of aged population, and that the turning point is around 16 percent. The results also imply that a relative increase in the number of elderly people is associated with a decrease in CO 2 emissions per capita from the road sector when the share of aged population reaches more than 16 percent. - Highlights: ► I estimate the relationship between a country's share of elderly population and CO 2 emissions from road transport. ► In order to alleviate the unit roots issue, the analysis uses a first-order differential equation to estimate models. ► There is a quadratic relationship between CO 2 emissions per capita and the share of elderly. ► The level of the turning point in terms of the share of elderly in OECD European countries and Japan is around 16 percent.

  19. Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks

    Directory of Open Access Journals (Sweden)

    Chaoyang Shi

    2017-12-01

    Full Text Available Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks.

  20. Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks.

    Science.gov (United States)

    Shi, Chaoyang; Chen, Bi Yu; Lam, William H K; Li, Qingquan

    2017-12-06

    Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks.

  1. Road transportation impact on Ghana's future energy and environment

    Energy Technology Data Exchange (ETDEWEB)

    Faah, George

    2008-11-07

    This research work explored the environmental and socio-economic benefits derived, if some proportion of daily passenger trips made using private cars in Ghana could be shifted to the use of public transport. The research applied the computer software COPERT III in estimating road transport Greenhouse gas (GHG) emissions and fuel consumption in Ghana for the base year 2005 and forecast years 2010 and 2020. The research reveals that if no major change occur in policies or economic determinants in meeting road transport and energy in Ghana, then the 2005 total emissions value is expected to rise by 36% in 2010 and over double in 2020 i.e. from 4.6 to 6.25 in 2010 and to 9.77 Mt CO{sub 2}e in 2020. However, if just 10% of daily passenger trips using private cars can be shifted towards the use of public transport, then the end results in reduction in emissions could earn Ghana about USD 6.6million/year under the Kyoto Protocol CDM initiative. The research also demonstrated that with a further 10% daily passenger trip shift, the outcome could be more promising, increasing to USD 13million/year. (orig.)

  2. The Consumption-Investment-Unemployment Relationship in Spain: an Analysis with Regional Data

    OpenAIRE

    Bande, Roberto; Riveiro, Dolores

    2012-01-01

    In this paper we analyse the consequences of changes in the consumption patterns on unemployment through an intermediate channel via investment. Specifically, after presenting our theoretical framework, we build a dynamic econometric multiequational model, in which we estimate a consumption function, an investment function and an unemployment rate equation, using a panel of 17 Spanish regions. This model is characterised by its dynamics and the cross equation relationships. After estimating t...

  3. SAS-macros for estimation and prediction in an model of the electricity consumption

    DEFF Research Database (Denmark)

    1998-01-01

    SAS-macros for estimation and prediction in an model of the electricity consumption'' is a large collection of SAS-macros for handling a model of the electricity consumption in the Eastern Denmark. The macros are installed at Elkraft, Ballerup.......SAS-macros for estimation and prediction in an model of the electricity consumption'' is a large collection of SAS-macros for handling a model of the electricity consumption in the Eastern Denmark. The macros are installed at Elkraft, Ballerup....

  4. Do foreign direct investment and renewable energy consumption affect the CO2 emissions? New evidence from a panel ARDL approach to Kyoto Annex countries.

    Science.gov (United States)

    Mert, Mehmet; Bölük, Gülden

    2016-11-01

    This study examines the impact of foreign direct investment (FDI) and the potential of renewable energy consumption on carbon dioxide (CO 2 ) emissions in 21 Kyoto countries using an unbalanced panel data. For this purpose, Environmental Kuznets Curve (EKC) hypothesis was tested using panel cointegration analysis. Panel causality tests show that there are significant long-run causalities from the variables to carbon emissions, renewable energy consumption, fossil fuel energy consumption and inflow foreign direct investments. The results of our model support the pollution haloes hypothesis which states that FDI brings in clean technology and improves the environmental standards. However, an inverted U-shaped relationship (EKC) was not supported by the estimated model for the 21 Kyoto countries. This means that economic growth cannot ensure environmental protection itself or environmental goals cannot await economic growth. Another important finding is that renewable energy consumption decreases carbon emissions. Based on the empirical results, some important policy implications emerge. Kyoto countries should stimulate the FDI inflows and usage of renewable energy consumption to mitigate the air pollution and meet the emission targets. This paper provides new insights into environment and energy policies through FDI inclusion.

  5. The impacts of tourism, energy consumption and political instability on economic growth in the MENA countries

    International Nuclear Information System (INIS)

    Tang, Chor Foon; Abosedra, Salah

    2014-01-01

    Using panel data of 24 countries in the Middle East and North African (MENA) region from 2001 to 2009, the purpose of this study is to examine the impacts of tourism, energy consumption and political instability on economic growth within the neoclassical growth framework. To address the objective of this study, we utilise both the static panel data approach as well as the dynamic generalised method of moments (GMM) estimator to examine the impact of candidate variables. Our results show that energy consumption and tourism significantly contribute to the economic growth of countries in the MENA region. Hence, our study lends some support to the existence of the tourism-led growth and energy-led growth hypotheses in the region. In line with our expectation, our estimation results also reveal that political instability impedes the process of economic growth and development in the MENA region. Therefore, macroeconomic policies to promote expansion in tourism and energy consumption will directly stimulate economic growth. Additionally, efforts to help the region overcome its history of political instability would attract more international tourist arrivals and further invigorate economic growth. - Highlights: • Tourism and energy consumption have positive impacts on GDP growth. • GDP reacts negatively to political instability. • Energy-led growth and tourism-led growth hypotheses are validated in MENA countries. • Supporting tourism, energy use and political stability will enhance economic growth

  6. Alternative Fuels Data Center: Indiana Transportation Data for Alternative

    Science.gov (United States)

    (nameplate, MW) 1,430 Source: BioFuels Atlas from the National Renewable Energy Laboratory Case Studies Video Alternative Fuels Save Money in Indy April 1, 2012 More Case Studies Videos Text Version More Indiana Videos on YouTube Video thumbnail for Indiana Beverage Company Invests in Alternative Fuels Indiana Beverage

  7. Alternative Fuels Data Center: Alabama Transportation Data for Alternative

    Science.gov (United States)

    Public Private Biodiesel (B20 and above) 2 8 Compressed Natural Gas (CNG) 10 23 Electric 84 67 Ethanol Boasts 200-Plus Flex Fuel Vehicles May 24, 2013 Video thumbnail for Biodiesel Fuels Education in Alabama Biodiesel Fuels Education in Alabama May 1, 2012 More Case Studies Videos Text Version More Alabama Videos

  8. Transportation of nuclear fuel

    International Nuclear Information System (INIS)

    Prowse, D.R.

    1979-01-01

    Shipment of used fuel from nuclear reactors to a central fuel management facility is discussed with particular emphasis on the assessment of the risk to the public due to these shipments. The methods of transporting used fuel in large shipping containers is reviewed. In terms of an accident scenario, it is demonstrated that the primary risk of transport of used fuel is due to injury and death in common road accidents. The radiological nature of the used fuel cargo is, for all practical purposes, an insignificant factor in the total risk to the public. (author)

  9. Alternatives to traditional transportation fuels: An overview

    Energy Technology Data Exchange (ETDEWEB)

    1994-06-01

    This report presents the first compilation by the Energy Information Administration (EIA) of information on alternatives to gasoline and diesel fuel. The purpose of the report is: (1) to provide background information on alternative transportation fuels and replacement fuels compared with gasoline and diesel fuel, and (2) to furnish preliminary estimates of alternative transportation fuels and alternative fueled vehicles as required by the Energy Policy Act of 1992 (EPACT), Title V, Section 503, ``Replacement Fuel Demand Estimates and Supply Information.`` Specifically, Section 503 requires the EIA to report annually on: (1) the number and type of alternative fueled vehicles in existence the previous year and expected to be in use the following year, (2) the geographic distribution of these vehicles, (3) the amounts and types of replacement fuels consumed, and (4) the greenhouse gas emissions likely to result from replacement fuel use. Alternative fueled vehicles are defined in this report as motorized vehicles licensed for on-road use, which may consume alternative transportation fuels. (Alternative fueled vehicles may use either an alternative transportation fuel or a replacement fuel.) The intended audience for the first section of this report includes the Secretary of Energy, the Congress, Federal and State agencies, the automobile manufacturing industry, the transportation fuel manufacturing and distribution industries, and the general public. The second section is designed primarily for persons desiring a more technical explanation of and background for the issues surrounding alternative transportation fuels.

  10. A Harmonized Perspective on Transportation Management in Smart Cities: The Novel IoT-Driven Environment for Road Traffic Modeling.

    Science.gov (United States)

    Masek, Pavel; Masek, Jan; Frantik, Petr; Fujdiak, Radek; Ometov, Aleksandr; Hosek, Jiri; Andreev, Sergey; Mlynek, Petr; Misurec, Jiri

    2016-11-08

    The unprecedented growth of today's cities together with increased population mobility are fueling the avalanche in the numbers of vehicles on the roads. This development led to the new challenges for the traffic management, including the mitigation of road congestion, accidents, and air pollution. Over the last decade, researchers have been focusing their efforts on leveraging the recent advances in sensing, communications, and dynamic adaptive technologies to prepare the deployed road traffic management systems (TMS) for resolving these important challenges in future smart cities. However, the existing solutions may still be insufficient to construct a reliable and secure TMS that is capable of handling the anticipated influx of the population and vehicles in urban areas. Along these lines, this work systematically outlines a perspective on a novel modular environment for traffic modeling, which allows to recreate the examined road networks in their full resemblance. Our developed solution is targeted to incorporate the progress in the Internet of Things (IoT) technologies, where low-power, embedded devices integrate as part of a next-generation TMS. To mimic the real traffic conditions, we recreated and evaluated a practical traffic scenario built after a complex road intersection within a large European city.

  11. A Harmonized Perspective on Transportation Management in Smart Cities: The Novel IoT-Driven Environment for Road Traffic Modeling

    Directory of Open Access Journals (Sweden)

    Pavel Masek

    2016-11-01

    Full Text Available The unprecedented growth of today’s cities together with increased population mobility are fueling the avalanche in the numbers of vehicles on the roads. This development led to the new challenges for the traffic management, including the mitigation of road congestion, accidents, and air pollution. Over the last decade, researchers have been focusing their efforts on leveraging the recent advances in sensing, communications, and dynamic adaptive technologies to prepare the deployed road traffic management systems (TMS for resolving these important challenges in future smart cities. However, the existing solutions may still be insufficient to construct a reliable and secure TMS that is capable of handling the anticipated influx of the population and vehicles in urban areas. Along these lines, this work systematically outlines a perspective on a novel modular environment for traffic modeling, which allows to recreate the examined road networks in their full resemblance. Our developed solution is targeted to incorporate the progress in the Internet of Things (IoT technologies, where low-power, embedded devices integrate as part of a next-generation TMS. To mimic the real traffic conditions, we recreated and evaluated a practical traffic scenario built after a complex road intersection within a large European city.

  12. Spatiotemporal variation of domestic biomass burning emissions in rural China based on a new estimation of fuel consumption.

    Science.gov (United States)

    Xing, Xiaofan; Zhou, Ying; Lang, Jianlei; Chen, Dongsheng; Cheng, Shuiyuan; Han, Lihui; Huang, Dawei; Zhang, Yanyun

    2018-06-01

    Domestic biomass burning (DBB) influences both indoor and outdoor air quality due to the multiple pollutants released during incomplete and inefficient combustion. The emissions are not well quantified because of insufficient information, which were the key parameters related to fuel consumption estimation, such as province- and year-specific percentage of domestic straw burning (P straw ) and firewood consumption (Fc). In this study, we established the quantitative relationship between rural-related socioeconomic parameters (e.g., rural per-capita income and rural Engel's coefficient) and P straw /Fc. DBB emissions, including 12 crop straw types and firewood for 12 kinds of pollutants in China during the period 1995-2014, were estimated based on fuel-specific emission factors and detailed fuel consumption data. The results revealed that the national emissions generally increased initially and then decreased with the turning point around 2007-2008. Firewood burning was the major source of the NH 3 and BC emissions; straw burning contributed more to SO 2 , NMVOC, CO, OC, and CH 4 emissions; while the major contributor changed from firewood to domestic straw burning for NOx, PM 10 , PM 2.5 , CO 2 , and Hg emissions. The emission trends varied among the 31 provinces. The major agricultural regions of north-eastern, central, and south-western China were always characterized by high emissions. The spatial variation mainly occurred in the northeast and north China (increase), and central-south and coastal regions of China (decrease). Copyright © 2018 Elsevier B.V. All rights reserved.

  13. Cost estimate modeling of transportation management plans for highway projects.

    Science.gov (United States)

    2012-05-01

    Highway rehabilitation and reconstruction projects frequently cause road congestion and increase safety concerns while limiting access for road users. State Transportation Agencies (STAs) are challenged to find safer and more efficient ways to renew ...

  14. A Two-Stage Estimation Method for Random Coefficient Differential Equation Models with Application to Longitudinal HIV Dynamic Data.

    Science.gov (United States)

    Fang, Yun; Wu, Hulin; Zhu, Li-Xing

    2011-07-01

    We propose a two-stage estimation method for random coefficient ordinary differential equation (ODE) models. A maximum pseudo-likelihood estimator (MPLE) is derived based on a mixed-effects modeling approach and its asymptotic properties for population parameters are established. The proposed method does not require repeatedly solving ODEs, and is computationally efficient although it does pay a price with the loss of some estimation efficiency. However, the method does offer an alternative approach when the exact likelihood approach fails due to model complexity and high-dimensional parameter space, and it can also serve as a method to obtain the starting estimates for more accurate estimation methods. In addition, the proposed method does not need to specify the initial values of state variables and preserves all the advantages of the mixed-effects modeling approach. The finite sample properties of the proposed estimator are studied via Monte Carlo simulations and the methodology is also illustrated with application to an AIDS clinical data set.

  15. Estimation of 1945 to 1957 food consumption

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, D.M.; Bates, D.J.; Marsh, T.L.

    1993-03-01

    This report details the methods used and the results of the study on the estimated historic levels of food consumption by individuals in the Hanford Environmental Dose Reconstruction (HEDR) study area from 1945--1957. This period includes the time of highest releases from Hanford and is the period for which data are being collected in the Hanford Thyroid Disease Study. These estimates provide the food-consumption inputs for the HEDR database of individual diets. This database will be an input file in the Hanford Environmental Dose Reconstruction Integrated Code (HEDRIC) computer model that will be used to calculate the radiation dose. The report focuses on fresh milk, eggs, lettuce, and spinach. These foods were chosen because they have been found to be significant contributors to radiation dose based on the Technical Steering Panel dose decision level.

  16. A flexible model for correlated medical costs, with application to medical expenditure panel survey data.

    Science.gov (United States)

    Chen, Jinsong; Liu, Lei; Shih, Ya-Chen T; Zhang, Daowen; Severini, Thomas A

    2016-03-15

    We propose a flexible model for correlated medical cost data with several appealing features. First, the mean function is partially linear. Second, the distributional form for the response is not specified. Third, the covariance structure of correlated medical costs has a semiparametric form. We use extended generalized estimating equations to simultaneously estimate all parameters of interest. B-splines are used to estimate unknown functions, and a modification to Akaike information criterion is proposed for selecting knots in spline bases. We apply the model to correlated medical costs in the Medical Expenditure Panel Survey dataset. Simulation studies are conducted to assess the performance of our method. Copyright © 2015 John Wiley & Sons, Ltd.

  17. Regression analysis of mixed recurrent-event and panel-count data with additive rate models.

    Science.gov (United States)

    Zhu, Liang; Zhao, Hui; Sun, Jianguo; Leisenring, Wendy; Robison, Leslie L

    2015-03-01

    Event-history studies of recurrent events are often conducted in fields such as demography, epidemiology, medicine, and social sciences (Cook and Lawless, 2007, The Statistical Analysis of Recurrent Events. New York: Springer-Verlag; Zhao et al., 2011, Test 20, 1-42). For such analysis, two types of data have been extensively investigated: recurrent-event data and panel-count data. However, in practice, one may face a third type of data, mixed recurrent-event and panel-count data or mixed event-history data. Such data occur if some study subjects are monitored or observed continuously and thus provide recurrent-event data, while the others are observed only at discrete times and hence give only panel-count data. A more general situation is that each subject is observed continuously over certain time periods but only at discrete times over other time periods. There exists little literature on the analysis of such mixed data except that published by Zhu et al. (2013, Statistics in Medicine 32, 1954-1963). In this article, we consider the regression analysis of mixed data using the additive rate model and develop some estimating equation-based approaches to estimate the regression parameters of interest. Both finite sample and asymptotic properties of the resulting estimators are established, and the numerical studies suggest that the proposed methodology works well for practical situations. The approach is applied to a Childhood Cancer Survivor Study that motivated this study. © 2014, The International Biometric Society.

  18. Dynamic Modeling of the Microalgae Cultivation Phase for Energy Production in Open Raceway Ponds and Flat Panel Photobioreactors

    Energy Technology Data Exchange (ETDEWEB)

    Marsullo, Matteo [Department of Industrial Engineering, University of Padova, Padova (Italy); Mian, Alberto [Industrial Process and Energy System Engineering Group (IPESE), École Polytechnique Fédérale de Lausanne, Lausanne (Switzerland); Ensinas, Adriano Viana [Industrial Process and Energy System Engineering Group (IPESE), École Polytechnique Fédérale de Lausanne, Lausanne (Switzerland); Universidade Federal do ABC, Santo Andre (Brazil); Manente, Giovanni; Lazzaretto, Andrea, E-mail: andrea.lazzaretto@unipd.it [Department of Industrial Engineering, University of Padova, Padova (Italy); Marechal, François [Industrial Process and Energy System Engineering Group (IPESE), École Polytechnique Fédérale de Lausanne, Lausanne (Switzerland)

    2015-09-15

    A dynamic model of microalgae cultivation phase is presented in this work. Two cultivation technologies are taken into account: the open raceway pond and the flat panel photobioreactor. For each technology, the model is able to evaluate the microalgae areal and volumetric productivity and the energy production and consumption. Differently from the most common existing models in literature, which deal with a specific part of the overall cultivation process, the model presented here includes all physical and chemical quantities that mostly affect microalgae growth: the equation of the specific growth rate for the microalgae is influenced by CO{sub 2} and nutrients concentration in the water, light intensity, temperature of the water in the reactor, and by the microalgae species being considered. All these input parameters can be tuned to obtain reliable predictions. A comparison with experimental data taken from the literature shows that the predictions are consistent and slightly overestimating the productivity in the case of closed photobioreactor. The results obtained by the simulation runs are consistent with those found in literature, being the areal productivity for the open raceway pond between 50 and 70 t/(ha × year) in Southern Spain (Sevilla) and Brazil (Petrolina) and between 250 and 350 t/(ha × year) for the flat panel photobioreactor in the same locations.

  19. Dynamic modeling of the microalgae cultivation phase for energy production in open raceway ponds and flat panel photobioreactors

    Directory of Open Access Journals (Sweden)

    Matteo eMarsullo

    2015-09-01

    Full Text Available A dynamic model of microalgae cultivation phase is presented in this work. Two cultivation technologies are taken into account: the open raceway pond and the flat panel photobioreactor. For each technology, the model is able to evaluate the microalgae areal and volumetric productivity and the energy production and consumption. Differently from the most common existing models in literature, which deal with a specific part of the overall cultivation process, the model presented here includes all physical and chemical quantities that mostly affect microalgae growth: the equation of the specific growth rate for the microalgae is influenced by CO2 and nutrients concentration in the water, light intensity, temperature of the water in the reactor and by the microalgae species being considered. All these input parameters can be tuned to obtain reliable predictions. A comparison with experimental data taken from the literature shows that the predictions are consistent, slightly overestimating the productivity in case of closed photobioreactor. The results obtained by the simulation runs are consistent with those found in literature, being the areal productivity for the open raceway pond between 50 and 70 t/(ha*year in Southern Spain (Sevilla and Brazil (Petrolina and between 250 and 350 t/(ha*year for the flat panel photobioreactor in the same locations.

  20. A Statistical Model for the Estimation of Natural Gas Consumption

    Czech Academy of Sciences Publication Activity Database

    Vondráček, Jiří; Pelikán, Emil; Konár, Ondřej; Čermáková, Jana; Eben, Kryštof; Malý, Marek; Brabec, Marek

    2008-01-01

    Roč. 85, c. 5 (2008), s. 362-370 ISSN 0306-2619 R&D Projects: GA AV ČR 1ET400300513 Institutional research plan: CEZ:AV0Z10300504 Keywords : nonlinear regression * gas consumption modeling Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.371, year: 2008

  1. Removing Traffic Emissions from CO2 Time Series Measured at a Tall Tower Using on-Road Measurements and WRF-Stilt Transport Modeling

    Science.gov (United States)

    Schmidt, A.; Rella, C.; Goeckede, M.; Hanson, C. V.; Yang, Z.; Law, B. E.

    2014-12-01

    In recent years, measurements of atmospheric carbon dioxide with high precision and accuracy have become increasingly important for climate change research, in particular to inform terrestrial biosphere models. Anthropogenic carbon dioxide emissions from fossil fuel burning have long been recognized to contribute a significant portion of the carbon dioxide in the atmosphere. Here, we present an approach to remove the traffic related carbon dioxide emissions from mole fractions measured at a tall tower by using the corresponding carbon monoxide measurements in combination with footprint analyses and transport modeling. This technique improves the suitability of the CO2 data to be used in inverse modeling approaches of atmosphere-biosphere exchange that do not account for non-biotic portions of CO2. In our study region in Oregon, road traffic emissions are the biggest source of anthropogenic carbon dioxide and carbon monoxide. A three-day mobile campaign covering 1700 km of roads in northwestern Oregon was performed during summer of 2012 using a laser-based Cavity Ring Down Spectrometer. The mobile measurements incorporated different roads including main highways, urban streets, and back-roads, largely within the typical footprint of a tall CO2 observation tower in Oregon's Willamette Valley. For the first time, traffic related CO:CO2 emission ratios were measured directly at the sources during an on-road campaign under a variety of different driving conditions. An average emission ratio of 7.43 (±1.80) ppb CO per ppm CO2 was obtained for the study region and applied to separate the traffic related portion of CO2 from the mole fraction time series. The road traffic related portion of the CO2 mole fractions measured at the tower site reached maximum values from 9.8 to 12 ppm, depending on the height above the surface, during summer 2012.

  2. Engineering solutions of traffic safety problems of road transport

    Directory of Open Access Journals (Sweden)

    M. Bogdevičius

    2004-02-01

    Full Text Available The authors of this paper focus on the simulation of the motor vehicle movement (taking into consideration motor vehicle dynamics, motor vehicle hydraulic brake system influence on motor vehicle movement, interaction between its wheels with road pavements, road guardrail characteristics, interaction between motor vehicle and road guardrail on a certain road section and propose their specific solution of this problem. The presented results, illustrating the motor vehicle movement trajectories (motor vehicle braking and interaction between motor vehicle and road guardrail at various initial conditions and at various certain pavement surface of the road section under investigation and work of a motor vehicle hydraulic brake system. Taking into consideration the presented general mathematical model and computer aided test results it is possible to investigate various road transport traffic situations as well as to investigate various transport traffic safety problems.

  3. Does urbanization affect energy intensities across provinces in China?Long-run elasticities estimation using dynamic panels with heterogeneous slopes

    International Nuclear Information System (INIS)

    Ma, Ben

    2015-01-01

    Although there has been extensive debate in the literature that addresses the impact of urbanization on total energy use, the relative magnitude of each impact channel has not been empirically examined and urbanization's effects on energy transition dynamics in China remains unknown. Using panel datasets at the provincial level from 1986 to 2011, this paper employs dynamic models to investigate both the long-run and short-run elasticities of urbanization on energy intensities and the most significant impact channel is identified. Coal intensity and electricity intensity are also modeled to reveal energy transition dynamics driven by urbanization. A set of newly developed regression techniques, namely well-performed common correlated effects mean group (CCEMG) and augmented mean group (AMG) estimators, are used to treat residual cross-sectional dependence, nonstationary residuals, and unlikely-to-hold homogeneous slope assumptions. The results obtained verify that the net effects of urbanization on overall energy intensity and electricity intensity are statistically positive, with long-run elasticities of 0.14% to 0.37% and 0.23% to 0.29%, respectively, whereas China's urbanization does not significantly increase coal intensity. The fact that short-run elasticities account for a majority of corresponding long-run values indicates that the short-run effect, that is, indirect energy use induced by urban infrastructures is the most significant impact channel of urbanization on energy use in China. An energy transition from high-pollution coal to clean electricity is also present in China, although the fundamental transition to renewable energy is still in its infancy. From a regional perspective, urbanization exerts asymmetric impacts on provincial energy use so that energy policies associated with urbanization should be province-specific. The findings also illustrate that for a panel dataset on regional dimension within large and fast-growing economies such

  4. Alternative Fuels Data Center: Rhode Island Transportation Data for

    Science.gov (United States)

    stations in Rhode Island with alternative fuels Fuel Public Private Biodiesel (B20 and above) 3 3 More Rhode Island Videos on YouTube Video thumbnail for Cooking Oil Powers Biodiesel Vehicles in Rhode Island Cooking Oil Powers Biodiesel Vehicles in Rhode Island July 14, 2017 https://www.youtube.com/embed

  5. Alternative Fuels Data Center: Vermont Transportation Data for Alternative

    Science.gov (United States)

    alternative fuels Fuel Public Private Biodiesel (B20 and above) 3 0 Compressed Natural Gas (CNG) 1 2 Electric Recycled Cooking Oil Powers Biodiesel Vehicles in Vermont Recycled Cooking Oil Powers Biodiesel Vehicles in sold per GGE Biodiesel (B20) $2.79/gallon $2.54/GGE $2.84/gallon $2.58/GGE Biodiesel (B99-B100) $2.47

  6. Alternative Fuels Data Center: Missouri Transportation Data for Alternative

    Science.gov (United States)

    stations in Missouri with alternative fuels Fuel Public Private Biodiesel (B20 and above) 1 2 Compressed Students Get Hands-On Training With Biodiesel Missouri High School Students Get Hands-On Training With Biodiesel Feb. 5, 2016 https://youtube.com/embed/p4pVRgoWyZw Video thumbnail for AT&T Fleet Reaches

  7. Alternative Fuels Data Center: Washington Transportation Data for

    Science.gov (United States)

    stations in Washington with alternative fuels Fuel Public Private Biodiesel (B20 and above) 8 33 Compressed Partnerships Spark Biodiesel Success for Essential Baking Company Partnerships Spark Biodiesel Success for Videos on YouTube Video thumbnail for Seattle Bakery Delivers With Biodiesel Trucks Seattle Bakery

  8. A New Dynamic Model for Nuclear Fuel Cycle System Analysis

    International Nuclear Information System (INIS)

    Choi, Sungyeol; Ko, Won Il

    2014-01-01

    The evaluation of mass flow is a complex process where numerous parameters and their complex interaction are involved. Given that many nuclear power countries have light and heavy water reactors and associated fuel cycle technologies, the mass flow analysis has to consider a dynamic transition from the open fuel cycle to other cycles over decades or a century. Although an equilibrium analysis provides insight concerning the end-states of fuel cycle transitions, it cannot answer when we need specific management options, whether the current plan can deliver these options when needed, and how fast the equilibrium can be achieved. As a pilot application, the government brought several experts together to conduct preliminary evaluations for nuclear fuel cycle options in 2010. According to Table 1, they concluded that the closed nuclear fuel cycle has long-term advantages over the open fuel cycle. However, it is still necessary to assess these options in depth and to optimize transition paths of these long-term options with advanced dynamic fuel cycle models. A dynamic simulation model for nuclear fuel cycle systems was developed and its dynamic mass flow analysis capability was validated against the results of existing models. This model can reflects a complex combination of various fuel cycle processes and reactor types, from once-through to multiple recycling, within a single nuclear fuel cycle system. For the open fuel cycle, the results of the developed model are well matched with the results of other models

  9. Dynamic modeling, experimental evaluation, optimal design and control of integrated fuel cell system and hybrid energy systems for building demands

    Science.gov (United States)

    Nguyen, Gia Luong Huu

    obtained experimental data, the research studied the control of airflow to regulate the temperature of reactors within the fuel processor. The dynamic model provided a platform to test the dynamic response for different control gains. With sufficient sensing and appropriate control, a rapid response to maintain the temperature of the reactor despite an increase in power was possible. The third part of the research studied the use of a fuel cell in conjunction with photovoltaic panels, and energy storage to provide electricity for buildings. This research developed an optimization framework to determine the size of each device in the hybrid energy system to satisfy the electrical demands of buildings and yield the lowest cost. The advantage of having the fuel cell with photovoltaic and energy storage was the ability to operate the fuel cell at baseload at night, thus reducing the need for large battery systems to shift the solar power produced in the day to the night. In addition, the dispatchability of the fuel cell provided an extra degree of freedom necessary for unforeseen disturbances. An operation framework based on model predictive control showed that the method is suitable for optimizing the dispatch of the hybrid energy system.

  10. Detection of Outliers in Panel Data of Intervention Effects Model Based on Variance of Remainder Disturbance

    Directory of Open Access Journals (Sweden)

    Yanfang Lyu

    2015-01-01

    Full Text Available The presence of outliers can result in seriously biased parameter estimates. In order to detect outliers in panel data models, this paper presents a modeling method to assess the intervention effects based on the variance of remainder disturbance using an arbitrary strictly positive twice continuously differentiable function. This paper also provides a Lagrange Multiplier (LM approach to detect and identify a general type of outlier. Furthermore, fixed effects models and random effects models are discussed to identify outliers and the corresponding LM test statistics are given. The LM test statistics for an individual-based model to detect outliers are given as a particular case. Finally, this paper performs an application using panel data and explains the advantages of the proposed method.

  11. Estimation of fuel loss due to idling of vehicles at a signalized intersection in Chennai, India

    Science.gov (United States)

    Vasantha Kumar, S.; Gulati, Himanshu; Arora, Shivam

    2017-11-01

    The vehicles while waiting at signalized intersections are generally found to be in idling condition, i.e., not switching off their vehicles during red times. This phenomenon of idling of vehicles during red times at signalized intersections may lead to huge economic loss as lot of fuel is consumed by vehicles when they are in idling condition. The situation may even be worse in countries like India as different vehicle types consume varying amount of fuel. Only limited studies have been reported on estimation of fuel loss due to idling of vehicles in India. In the present study, one of the busy intersections in Chennai, namely, Tidel Park Junction in Rajiv Gandhi salai was considered. Data collection was carried out in one approach road of the intersection during morning and evening peak hours on a typical working day by manually noting down the red timings of each cycle and the corresponding number of two-wheelers, three-wheelers, passenger cars, light commercial vehicles (LCV) and heavy motorized vehicles (HMV) that were in idling mode. Using the fuel consumption values of various vehicles types suggested by Central Road Research Institute (CRRI), the total fuel loss during the study period was found to be Rs. 4,93,849/-. The installation of red timers, synchronization of signals, use of non-motorized transport for short trips and public awareness are some of the measures which government need to focus to save the fuel wasted at signalized intersections in major cities of India.

  12. A Hybrid Tabu Search Algorithm for a Real-World Open Vehicle Routing Problem Involving Fuel Consumption Constraints

    Directory of Open Access Journals (Sweden)

    Yunyun Niu

    2018-01-01

    Full Text Available Outsourcing logistics operation to third-party logistics has attracted more attention in the past several years. However, very few papers analyzed fuel consumption model in the context of outsourcing logistics. This problem involves more complexity than traditional open vehicle routing problem (OVRP, because the calculation of fuel emissions depends on many factors, such as the speed of vehicles, the road angle, the total load, the engine friction, and the engine displacement. Our paper proposed a green open vehicle routing problem (GOVRP model with fuel consumption constraints for outsourcing logistics operations. Moreover, a hybrid tabu search algorithm was presented to deal with this problem. Experiments were conducted on instances based on realistic road data of Beijing, China, considering that outsourcing logistics plays an increasingly important role in China’s freight transportation. Open routes were compared with closed routes through statistical analysis of the cost components. Compared with closed routes, open routes reduce the total cost by 18.5% with the fuel emissions cost down by nearly 29.1% and the diver cost down by 13.8%. The effect of different vehicle types was also studied. Over all the 60- and 120-node instances, the mean total cost by using the light-duty vehicles is the lowest.

  13. Carbon emissions, logistics volume and GDP in China: empirical analysis based on panel data model.

    Science.gov (United States)

    Guo, Xiaopeng; Ren, Dongfang; Shi, Jiaxing

    2016-12-01

    This paper studies the relationship among carbon emissions, GDP, and logistics by using a panel data model and a combination of statistics and econometrics theory. The model is based on the historical data of 10 typical provinces and cities in China during 2005-2014. The model in this paper adds the variability of logistics on the basis of previous studies, and this variable is replaced by the freight turnover of the provinces. Carbon emissions are calculated by using the annual consumption of coal, oil, and natural gas. GDP is the gross domestic product. The results showed that the amount of logistics and GDP have a contribution to carbon emissions and the long-term relationships are different between different cities in China, mainly influenced by the difference among development mode, economic structure, and level of logistic development. After the testing of panel model setting, this paper established a variable coefficient model of the panel. The influence of GDP and logistics on carbon emissions is obtained according to the influence factors among the variables. The paper concludes with main findings and provides recommendations toward rational planning of urban sustainable development and environmental protection for China.

  14. Estimating traffic volume on Wyoming low volume roads using linear and logistic regression methods

    Directory of Open Access Journals (Sweden)

    Dick Apronti

    2016-12-01

    Full Text Available Traffic volume is an important parameter in most transportation planning applications. Low volume roads make up about 69% of road miles in the United States. Estimating traffic on the low volume roads is a cost-effective alternative to taking traffic counts. This is because traditional traffic counts are expensive and impractical for low priority roads. The purpose of this paper is to present the development of two alternative means of cost-effectively estimating traffic volumes for low volume roads in Wyoming and to make recommendations for their implementation. The study methodology involves reviewing existing studies, identifying data sources, and carrying out the model development. The utility of the models developed were then verified by comparing actual traffic volumes to those predicted by the model. The study resulted in two regression models that are inexpensive and easy to implement. The first regression model was a linear regression model that utilized pavement type, access to highways, predominant land use types, and population to estimate traffic volume. In verifying the model, an R2 value of 0.64 and a root mean square error of 73.4% were obtained. The second model was a logistic regression model that identified the level of traffic on roads using five thresholds or levels. The logistic regression model was verified by estimating traffic volume thresholds and determining the percentage of roads that were accurately classified as belonging to the given thresholds. For the five thresholds, the percentage of roads classified correctly ranged from 79% to 88%. In conclusion, the verification of the models indicated both model types to be useful for accurate and cost-effective estimation of traffic volumes for low volume Wyoming roads. The models developed were recommended for use in traffic volume estimations for low volume roads in pavement management and environmental impact assessment studies.

  15. Climate policies for road transport revisited (II): Closing the policy gap with cap-and-trade

    International Nuclear Information System (INIS)

    Flachsland, Christian; Brunner, Steffen; Edenhofer, Ottmar; Creutzig, Felix

    2011-01-01

    Current policies in the road transport sector fail to deliver consistent and efficient incentives for greenhouse gas abatement (see companion article by ). Market-based instruments such as cap-and-trade systems close this policy gap and complement traditional policies that are required where specific market failures arise. Even in presence of strong existing non-market policies, cap-and-trade delivers additional abatement and efficiency by incentivizing demand side abatement options. This paper analyzes generic design options and economic impacts of including the European road transport sector into the EU ETS. Suitable points of regulation are up- and midstream in the fuel chain to ensure effectiveness (cover all emissions and avoid double-counting), efficiency (incentivize all abatement options) and low transaction costs. Based on year 2020 marginal abatement cost curves from different models and current EU climate policy objectives we show that in contrast to conventional wisdom, road transport inclusion would not change the EU ETS allowance price. Hence, industrial carbon leakage induced by adding road transport to the EU ETS may be less important than previously estimated. - Research highlights: → We analyze the rationale, design and economic impacts of including road transportation into GHG cap-and-trade systems. → Suitable points of regulation are up- and mid-stream. → Including European road transport into the EU ETS by 2020 would not change the EU allowance price.

  16. Alternative Fuels Data Center: Alaska Transportation Data for Alternative

    Science.gov (United States)

    fuels Fuel Public Private Biodiesel (B20 and above) 0 0 Compressed Natural Gas (CNG) 1 0 Electric 8 0 Coast Region National Average per unit sold per GGE per unit sold per GGE Biodiesel (B20) $3.01/gallon $2.74/GGE $2.84/gallon $2.58/GGE Biodiesel (B99-B100) $3.61/gallon $3.57/GGE $3.48/gallon $3.45/GGE

  17. Revised estimates of the radiological impact of the transport of irradiated nuclear fuels within the UK

    International Nuclear Information System (INIS)

    Macdonald, H.F.

    1987-10-01

    This report presents revised estimates of individual and collective doses associated with irradiated fuel movements from CEGB and SSEB nuclear power stations within the UK. In particular, earlier estimates of transport doses have been updated to take account of recent changes in the patterns of rail traffic. This results in a reduction in the estimated maximum individual doses to members of the public living near marshalling yards where flasks stop en route and also to rail workers incidentally exposed at these locations. The maximum levels of individual dose associated with irradiated fuel transport within the UK are in general low compared with those due to natural background radiation. Further, the associated collective doses are small compared with other sources of dose arising in the nuclear fuel cycle and represent -4 % of the natural background radiation dose to the UK population. In absolute terms the maximum contributions to the annual transport collective doses from Magnox, AGR and projected PWR fuel movements are estimated to be 18, 9 and 0.7 man mSv · a -1 respectively. These results neglect any reduction in doses due to the effects of shielding by buildings or natural obstacles such as railway cuttings or tunnels. Inclusion of these effects has been estimated to reduce the annual transport collective doses to 13, 6 and 0.45 man mSv · a -1 for Magnox, AGR and PWR fuels respectively. (U.K.)

  18. Panel data analysis using EViews

    CERN Document Server

    Agung, I Gusti Ngurah

    2013-01-01

    A comprehensive and accessible guide to panel data analysis using EViews software This book explores the use of EViews software in creating panel data analysis using appropriate empirical models and real datasets. Guidance is given on developing alternative descriptive statistical summaries for evaluation and providing policy analysis based on pool panel data. Various alternative models based on panel data are explored, including univariate general linear models, fixed effect models and causal models, and guidance on the advantages and disadvantages of each one is given. Panel Data Analysis

  19. Alternative Fuels Data Center: Fleet Application for School Transportation

    Science.gov (United States)

    Propane Buses Jan. 26, 2016 Video thumbnail for Biodiesel Offers an Easy Alternative for Fleets Biodiesel thumbnail for Biodiesel Fuels Education in Alabama Biodiesel Fuels Education in Alabama May 1, 2012 Video School Transportation Videos on YouTube Video thumbnail for New Hampshire Cleans up with Biodiesel Buses

  20. Scenarios for the transportation sector's energy consumption in Denmark. Focus on road transport. Documentation report; Scenarier for transportsektorens energiforbrug i Danmark. Med fokus paa vejtransporten. Dokumentationsrapport

    Energy Technology Data Exchange (ETDEWEB)

    Hethey, J.; Kofoed-Wiuff, A.; Lindboe, H.H.

    2011-05-15

    The purpose of this project was to make a number of predictions of how the Danish energy consumption for transport purposes may evolve until 2035. The analyses include the total energy consumption for passenger and freight transport and transportation-related energy consumption in the production industry. Air and maritime transport and freight trains are not considered in the analyses. Five scenarios have been calculated, including a reference scenario, three technology scenarios (efficiency, electric vehicle, a biofuel scenario), and a combined scenario. For all scenarios, the development of fuel consumption is calculated and CO{sub 2} emissions both locally and totally are presented. The analyses show that the total energy consumption and total CO{sub 2} emission had a peak in 2007, after which the already registered decrease is likely to continue. This continued decline happens in spite of continued growth in transport services, primarily due to the assumed and expected development of more fuel-efficient cars. (ln)

  1. A case study predicting environmental impacts of urban transport planning in China.

    Science.gov (United States)

    Chen, Chong; Shao, Li-guo; Xu, Ling; Shang, Jin-cheng

    2009-10-01

    Predicting environmental impacts is essential when performing an environmental assessment on urban transport planning. System dynamics (SD) is usually used to solve complex nonlinear problems. In this study, we utilized system dynamics (SD) to evaluate the environmental impacts associated with urban transport planning in Jilin City, China with respect to the local economy, society, transport, the environment and resources. To accomplish this, we generated simulation models comprising interrelated subsystems designed to utilize changes in the economy, society, road construction, changes in the number of vehicles, the capacity of the road network capacity, nitrogen oxides emission, traffic noise, land used for road construction and fuel consumption associated with traffic to estimate dynamic trends in the environmental impacts associated with Jilin's transport planning. Two simulation scenarios were then analyzed comparatively. The results of this study indicated that implementation of Jilin transport planning would improve the current urban traffic conditions and boost the local economy and development while benefiting the environment in Jilin City. In addition, comparative analysis of the two scenarios provided additional information that can be used to aid in scientific decision-making regarding which aspects of the transport planning to implement in Jilin City. This study demonstrates that our application of the SD method, which is referred to as the Strategic Environmental Assessment (SEA), is feasible for use in urban transport planning.

  2. Improvement of road noise by reduction of acoustic radiation from body panels; Panel no hoshaon teigen ni yoru road noise no kaizen

    Energy Technology Data Exchange (ETDEWEB)

    Kamura, T; Utsunomiya, A; Sugihara, T; Tobita, K [Mazda Motor Corp., Hiroshima (Japan)

    1997-10-01

    This paper describes road noise reduction methods accomplished by reducing acoustic power radiated from body panels. Fundamental study of acoustic and dynamic characteristics with rectangular panels revealed following results: (1) The lower stiffness panel had lower radiation efficiency and made damping materials work more effective to reduce the acoustic power. (2) The acoustic power was also reduced by designing the panel so that it can generate the vibration of (2, 2) mode, which has the lowest radiation efficiency, in road noise frequency region. By applying these methods to a vehicle floor, we confirmed the improvement of road noise performance. 3 refs., 12 figs.

  3. Improvement in soil-plant-atmosphere modelling of {sup 14}C dynamics and the application of two models to data from a nuclear fuel reprocessing plant

    Energy Technology Data Exchange (ETDEWEB)

    Limer, Laura M.C. [Quintessa Limited, 633/635 Birchwood Boulevard, WA3 7QU, Warrington (United Kingdom); Le Dizes-Maurel, Severine; Maro, Denis [Institut de Radioprotection et de Surete Nucleaire (IRSN), PRP-ENV, SERIS, LM2E, Cadarache, Saint-Paul Lez Durance (France); Klos, Ryk [Aleksandria Sciences Limited, S7 2DD, Sheffield (United Kingdom); Norden, Maria [Swedish Radiation Safety Authority, SE-171 16, Stockholm (Sweden)

    2014-07-01

    The need to address radiological impacts from {sup 14}C released to the biosphere has been recognised for some time. However, because of its role in biological processes and its ecological cycling, the standard methods employed to model long-term radionuclide transport and accumulation in the biosphere cannot be used satisfactorily for {sup 14}C. The degree of complexity in any {sup 14}C model used must be balanced against the availability of supporting data and the assessment context. In 2011, the model SSPAM14C was developed on behalf of the Swedish Radiation Safety Authority (SSM), with the intention to usage in both long-term and short-term release assessments (Limer et al., 2013). As part of the model testing it was applied to data collected during laboratory experiments performed by Imperial College London in the 1990's (Tucker and Shaw, 1997). Independently, IRSN has also been developing its own {sup 14}C model, TOCATTA (Le Dizes et al., 2012), and has previously tested it against field data collected by IRSN, between 2006 and 2008, in the vicinity of the La Hague nuclear fuel reprocessing plant in France (Aulagnier et al., 2012). The main conclusion drawn from these comparisons highlighted the need to develop an hourly time step model of {sup 14}C transfer based more thoroughly on knowledge arising from plant physiology, soil science and meteorology (Farquhar and von Caemmerer, 1982). These models have undergone further development, and have been applied here to the La Hague field data as it represents a medium term data set with both short term variation and a sizeable time series of measurements against which to compare the models. By increasing the temporal resolution of the IRSN model, a new version called TOCATTA-ccan simulate the impact of intermittent {sup 14}C releases occurring either the day or night (Aulagnier et al., 2013). Simplification of the soil sub-model in SSPAM14C is also shown to be justified for application to operational release

  4. Unobserved Heterogeneity in the Binary Logit Model with Cross-Sectional Data and Short Panels

    DEFF Research Database (Denmark)

    Holm, Anders; Jæger, Mads Meier; Pedersen, Morten

    This paper proposes a new approach to dealing with unobserved heterogeneity in applied research using the binary logit model with cross-sectional data and short panels. Unobserved heterogeneity is particularly important in non-linear regression models such as the binary logit model because, unlike...... in linear regression models, estimates of the effects of observed independent variables are biased even when omitted independent variables are uncorrelated with the observed independent variables. We propose an extension of the binary logit model based on a finite mixture approach in which we conceptualize...

  5. Spatial Spillover Effects of Transport Infrastructure in Chinese New Silk Road Economic Belt

    Directory of Open Access Journals (Sweden)

    Jian Li

    2017-04-01

    Full Text Available Based on the inner-effect mechanism of transport infrastructure and regional economic growth, this paper builds a specialized spatial weight matrix by utilizing the panel data from 31 provinces in New Silk Road Economic Belt (NSREB and other areas from 2005 to 2014, and combines with the spatial panel model to analyze the spatial spillover effects of transport infrastructure. According to the analysis, the transport infrastructure plays an obvious lead role in regional economy growth alongside the NSREB, and the economic growth invigorates common development in surrounding regions. In addition, differences were observed among the different transport infrastructure with regard to their influences on regional economic development, as the highway transport affects regional economic growth to a larger degree than railway transport.

  6. EU policies on car emissions and fuel quality. Reducing the climate impact from road transport

    Energy Technology Data Exchange (ETDEWEB)

    Christensen, Anne Raaum; Gulbrandsen, Lars H.

    2012-07-01

    Transport is the second biggest source of greenhouse gas (GHG) emissions in the EU, and contributes about one-quarter of the EU's total emissions of CO{sub 2}. Significant reductions in GHG emissions from transport are required if the EU is to achieve its long-term climate goals. This report examines the making and implementation of two of the regulations the EU has put in place to lower emissions from the transport sector: the EU's revised Fuel Quality Directive (Directive 2009/30/EC) and the cars/CO{sub 2} regulation (Regulation (EC) 443/2009). It was found that the relevance of various theories of policymaking in the EU varies with different policy phases. A policy-network understanding of EU policymaking is strengthened when assessing the policy-initiation phase. The Commission played a key role in this phase and drafted legislation in close collaboration with the car and oil refining industries. An intergovernmentalist understanding of EU policy-making is strengthened when assessing the decision-making phase. In this phase, member states defending the interests of their domestic industries had strong influence, but the European Parliament played an important role in this phase too, employing its power in the co-decision procedure. Finally, the implementation process is best understood as a multi-level governance process in which several actors and institutions - notably the Commission, member states, industries, and NGOs - influenced the process. (Author)

  7. Aids to determining fuel models for estimating fire behavior

    Science.gov (United States)

    Hal E. Anderson

    1982-01-01

    Presents photographs of wildland vegetation appropriate for the 13 fuel models used in mathematical models of fire behavior. Fuel model descriptions include fire behavior associated with each fuel and its physical characteristics. A similarity chart cross-references the 13 fire behavior fuel models to the 20 fuel models used in the National Fire Danger Rating System....

  8. Analysis of Panel Data

    Science.gov (United States)

    Hsiao, Cheng

    2003-02-01

    Panel data models have become increasingly popular among applied researchers due to their heightened capacity for capturing the complexity of human behavior, as compared to cross-sectional or time series data models. This second edition represents a substantial revision of the highly successful first edition (1986). Recent advances in panel data research are presented in an accessible manner and are carefully integrated with the older material. The thorough discussion of theory and the judicious use of empirical examples make this book useful to graduate students and advanced researchers in economics, business, sociology and political science.

  9. Gasoline prices, gasoline consumption, and new-vehicle fuel economy: Evidence for a large sample of countries

    International Nuclear Information System (INIS)

    Burke, Paul J.; Nishitateno, Shuhei

    2013-01-01

    Countries differ considerably in terms of the price drivers pay for gasoline. This paper uses data for 132 countries for the period 1995–2008 to investigate the implications of these differences for the consumption of gasoline for road transport. To address the potential for simultaneity bias, we use both a country's oil reserves and the international crude oil price as instruments for a country's average gasoline pump price. We obtain estimates of the long-run price elasticity of gasoline demand of between − 0.2 and − 0.5. Using newly available data for a sub-sample of 43 countries, we also find that higher gasoline prices induce consumers to substitute to vehicles that are more fuel-efficient, with an estimated elasticity of + 0.2. Despite the small size of our elasticity estimates, there is considerable scope for low-price countries to achieve gasoline savings and vehicle fuel economy improvements via reducing gasoline subsidies and/or increasing gasoline taxes. - Highlights: ► We estimate the determinants of gasoline demand and new-vehicle fuel economy. ► Estimates are for a large sample of countries for the period 1995–2008. ► We instrument for gasoline prices using oil reserves and the world crude oil price. ► Gasoline demand and fuel economy are inelastic with respect to the gasoline price. ► Large energy efficiency gains are possible via higher gasoline prices

  10. Oracle Efficient Variable Selection in Random and Fixed Effects Panel Data Models

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl

    This paper generalizes the results for the Bridge estimator of Huang et al. (2008) to linear random and fixed effects panel data models which are allowed to grow in both dimensions. In particular we show that the Bridge estimator is oracle efficient. It can correctly distinguish between relevant...... and irrelevant variables and the asymptotic distribution of the estimators of the coefficients of the relevant variables is the same as if only these had been included in the model, i.e. as if an oracle had revealed the true model prior to estimation. In the case of more explanatory variables than observations......, we prove that the Marginal Bridge estimator can asymptotically correctly distinguish between relevant and irrelevant explanatory variables. We do this without restricting the dependence between covariates and without assuming sub Gaussianity of the error terms thereby generalizing the results...

  11. Alternative Fuels Data Center: New Mexico Transportation Data for

    Science.gov (United States)

    to alternative fuels and advanced vehicles Recent Additions and Updates Biodiesel Blend Mandate Public Private Biodiesel (B20 and above) 1 4 Compressed Natural Gas (CNG) 8 3 Electric 59 4 Ethanol (E85 GGE Biodiesel (B20) $2.60/gallon $2.37/GGE $2.84/gallon $2.58/GGE Biodiesel (B99-B100) $2.49/gallon

  12. Alternatives to traditional transportation fuels 1993

    Energy Technology Data Exchange (ETDEWEB)

    1995-01-01

    In recent years, gasoline and diesel fuel have accounted for about 80 percent of total transportation fuel and nearly all of the fuel used in on-road vehicles. Growing concerns about the environmental effects of fossil fuel use and the Nation`s high level of dependence on foreign oil are providing impetus for the development of replacements or alternatives for these traditional transportation fuels. (The Energy Policy Act of 1992 definitions of {open_quotes}replacement{close_quotes} and {open_quotes}alternative{close_quotes} fuels are presented in the following box.) The Alternative Motor Fuels Act of 1988, the Clean Air Act Amendments of 1990 (CAAA90) and the Energy Policy Act of 1992 (EPACT) are significant legislative forces behind the growth of replacement fuel use. Alternatives to Traditional Transportation Fuels 1993 provides the number of on-road alternative fueled vehicles in use in the United States, alternative and replacement fuel consumption, and information on greenhouse gas emissions resulting from the production, delivery, and use of replacement fuels for 1992, 1993, and 1995.

  13. An integrated modeling approach to estimating Gunnison Sage-Grouse population dynamics: combining index and demographic data.

    Science.gov (United States)

    Davis, Amy J.; Hooten, Mevin B.; Phillips, Michael L.; Doherty, Paul F.

    2014-01-01

    Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large-scale, population count data. These data are commonly based on sampling methods that lack consistent sampling effort, do not account for detectability, and are complicated by observer bias. For some species, short-term studies of demographic rates have been conducted as well, but the data from such studies are typically analyzed separately. To utilize the strengths and minimize the weaknesses of these two data types, we developed a novel Bayesian integrated model that links population count data and population demographic data through population growth rate (λ) for Gunnison sage-grouse (Centrocercus minimus). The long-term population index data available for Gunnison sage-grouse are annual (years 1953–2012) male lek counts. An intensive demographic study was also conducted from years 2005 to 2010. We were able to reduce the variability in expected population growth rates across time, while correcting for potential small sample size bias in the demographic data. We found the population of Gunnison sage-grouse to be variable and slightly declining over the past 16 years.

  14. Re-estimating temperature-dependent consumption parameters in bioenergetics models for juvenile Chinook salmon

    Science.gov (United States)

    Plumb, John M.; Moffitt, Christine M.

    2015-01-01

    Researchers have cautioned against the borrowing of consumption and growth parameters from other species and life stages in bioenergetics growth models. In particular, the function that dictates temperature dependence in maximum consumption (Cmax) within the Wisconsin bioenergetics model for Chinook Salmon Oncorhynchus tshawytscha produces estimates that are lower than those measured in published laboratory feeding trials. We used published and unpublished data from laboratory feeding trials with subyearling Chinook Salmon from three stocks (Snake, Nechako, and Big Qualicum rivers) to estimate and adjust the model parameters for temperature dependence in Cmax. The data included growth measures in fish ranging from 1.5 to 7.2 g that were held at temperatures from 14°C to 26°C. Parameters for temperature dependence in Cmax were estimated based on relative differences in food consumption, and bootstrapping techniques were then used to estimate the error about the parameters. We found that at temperatures between 17°C and 25°C, the current parameter values did not match the observed data, indicating that Cmax should be shifted by about 4°C relative to the current implementation under the bioenergetics model. We conclude that the adjusted parameters for Cmax should produce more accurate predictions from the bioenergetics model for subyearling Chinook Salmon.

  15. Improving accuracy in road safety data exchange for navigation systems: European Union Location Framework Transportation Pilot

    OpenAIRE

    BORZACCHIELLO MARIA TERESA; BOGUSLAWSKI RAYMOND; PIGNATELLI Francesco

    2016-01-01

    In the near future, the travel experience for drivers will radically change from what they were used to a decade ago: advanced safety systems will guide drivers and help reduce road accidents; built-in vehicle sensors will detect road and traffic conditions and adapt the behaviour of the vehicle; automatic control of the engine will enable the reduction of emissions and contribute to the objective of decarbonisation of transport. All this will be possible thanks to the application of Informat...

  16. An estimation of the energy and exergy efficiencies for the energy resources consumption in the transportation sector in Malaysia

    International Nuclear Information System (INIS)

    Saidur, R.; Sattar, M.A.; Masjuki, H.H.; Ahmed, S.; Hashim, U.

    2007-01-01

    The purpose of this work is to apply the useful energy and exergy analysis models for different modes of transport in Malaysia and to compare the result with a few countries. In this paper, energy and exergy efficiencies of the various sub-sectors are presented by considering the energy and exergy flows from 1995 to 2003. Respective flow diagrams to find the overall energy and exergy efficiencies of Malaysian transportation sector are also presented. The estimated overall energy efficiency ranges from 22.74% (1999) to 22.98% (1998) with a mean of 22.82+/-0.06% and that of overall exergy efficiency ranges from 22.44% (2000) to 22.82% (1998) with a mean of 22.55+/-0.12%. The results are compared with respect to present energy and exergy efficiencies in each sub-sector. The transportation sector used about 40% of the total energy consumed in 2002. Therefore, it is important to identify the energy and exergy flows and the pertinent losses. The road sub-sector has appeared to be the most efficient one compared to the air and marine sub-sectors. Also found that the energy and exergy efficiencies of Malaysian transportation sector are lower than that of Turkey but higher than Norway

  17. Effects of EU dairy policy reform for Dutch dairy farming : a primal approach using GMM estimation

    NARCIS (Netherlands)

    Ooms, D.L.; Peerlings, J.H.M.

    2005-01-01

    This paper estimates a production function for milk using a generalised method of moments estimator to avoid the endogeneity problem. Using the first-order conditions for profit maximisation, the economic effects for individual Dutch dairy farms of the 2003 EU dairy policy reform are analysed. With

  18. GIS Data Based Automatic High-Fidelity 3D Road Network Modeling

    Science.gov (United States)

    Wang, Jie; Shen, Yuzhong

    2011-01-01

    3D road models are widely used in many computer applications such as racing games and driving simulations_ However, almost all high-fidelity 3D road models were generated manually by professional artists at the expense of intensive labor. There are very few existing methods for automatically generating 3D high-fidelity road networks, especially those existing in the real world. This paper presents a novel approach thai can automatically produce 3D high-fidelity road network models from real 2D road GIS data that mainly contain road. centerline in formation. The proposed method first builds parametric representations of the road centerlines through segmentation and fitting . A basic set of civil engineering rules (e.g., cross slope, superelevation, grade) for road design are then selected in order to generate realistic road surfaces in compliance with these rules. While the proposed method applies to any types of roads, this paper mainly addresses automatic generation of complex traffic interchanges and intersections which are the most sophisticated elements in the road networks

  19. Electric and hydrogen consumption analysis in plug-in road vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Ribau, Joao P.; Silva, Carla M.; Faria, Tiago L. [IDMEC, Instituto Superior Tecnico, Technical University of Lisbon, Department of Mechanical Engineering, Av. Rovisco Pais, 1 Pav. Mecanica I, 2 andar, 1049-001 Lisboa (Portugal)

    2010-07-01

    The main goal of the present study is to analyze some of the capabilities and behavior of two types of plug-in cars: battery electric and hydrogen fuel cell hybrid electric, facing different driving styles, different road gradients, different occupation rates, different electrical loads, and different battery's initial state of charge. In order to do that, four vehicles with different power/weight (kW/kg) ratio (0.044 to 0.150) were simulated in the software ADVISOR, which gives predictions of energy consumption, and behavior of vehicle's power train components (including energy regeneration) along specified driving cycles. The required energy, electricity and/or hydrogen, to overcome the specified driving schedules, allowed to estimate fuel life cycle's CO2 emissions and primary energy. A vehicle with higher power/weight ratio (kW/kg) demonstrated to be less affected in operation and in variation of the energy consumption, facing the different case studies, however may have higher consumptions in some cases. The autonomy, besides depending on the fuel consumption, is directly associated with the type and capacity (kWh) of the chosen battery, plus the stored hydrogen (if fuel cell vehicles are considered, PHEV-FC). The PHEV-FC showed to have higher autonomy than the battery vehicles, but higher energy consumption which is extremely dependent on the type and ratio of energy used, hydrogen or electricity. An aggressive driving style, higher road gradient and increase of weight, required more energy and power to the vehicle and presented consumption increases near to 77%, 621%, 19% respectively. Higher electrical load and battery's initial state of charge, didn't affect directly vehicle's dynamic. The first one drained energy directly from the battery plus demanded a fraction of its power, with energy consumption maximum increasing near 71%. The second one restricted the autonomy without influence directly the energy consumption per

  20. Complex Road Intersection Modelling Based on Low-Frequency GPS Track Data

    Science.gov (United States)

    Huang, J.; Deng, M.; Zhang, Y.; Liu, H.

    2017-09-01

    It is widely accepted that digital map becomes an indispensable guide for human daily traveling. Traditional road network maps are produced in the time-consuming and labour-intensive ways, such as digitizing printed maps and extraction from remote sensing images. At present, a large number of GPS trajectory data collected by floating vehicles makes it a reality to extract high-detailed and up-to-date road network information. Road intersections are often accident-prone areas and very critical to route planning and the connectivity of road networks is mainly determined by the topological geometry of road intersections. A few studies paid attention on detecting complex road intersections and mining the attached traffic information (e.g., connectivity, topology and turning restriction) from massive GPS traces. To the authors' knowledge, recent studies mainly used high frequency (1 s sampling rate) trajectory data to detect the crossroads regions or extract rough intersection models. It is still difficult to make use of low frequency (20-100 s) and easily available trajectory data to modelling complex road intersections geometrically and semantically. The paper thus attempts to construct precise models for complex road intersection by using low frequency GPS traces. We propose to firstly extract the complex road intersections by a LCSS-based (Longest Common Subsequence) trajectory clustering method, then delineate the geometry shapes of complex road intersections by a K-segment principle curve algorithm, and finally infer the traffic constraint rules inside the complex intersections.

  1. Fast Food Consumption and Food Prices: Evidence from Panel Data on 5th and 8th Grade Children

    Directory of Open Access Journals (Sweden)

    Tamkeen Khan

    2012-01-01

    Full Text Available Fast food consumption is a dietary factor associated with higher prevalence of childhood obesity in the United States. The association between food prices and consumption of fast food among 5th and 8th graders was examined using individual-level random effects models utilizing consumption data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K, price data from American Chamber of Commerce Researchers Association (ACCRA, and contextual outlet density data from Dun and Bradstreet (D&B. The results found that contextual factors including the price of fast food, median household income, and fast food restaurant outlet densities were significantly associated with fast food consumption patterns among this age group. Overall, a 10% increase in the price of fast food was associated with 5.7% lower frequency of weekly fast food consumption. These results suggest that public health policy pricing instruments such as taxes may be effective in reducing consumption of energy-dense foods and possibly reducing the prevalence of overweight and obesity among US children and young adolescents.

  2. Use of car crashes resulting in fatal and serious injuries to analyze a safe road transport system model and to identify system weaknesses.

    Science.gov (United States)

    Stigson, Helena; Hill, Julian

    2009-10-01

    The objective of this study was to evaluate a model for a safe road transport system, based on some safety performance indicators regarding the road user, the vehicle, and the road, by using crashes with fatally and seriously injured car occupants. The study also aimed to evaluate whether the model could be used to identify system weaknesses and components (road user, vehicles, and road) where improvements would yield the highest potential for further reductions in serious injuries. Real-life car crashes with serious injury outcomes (Maximum Abbreviated Injury Scale 2+) were classified according to the vehicle's safety rating by Euro NCAP (European New Car Assessment Programme) and whether the vehicle was fitted with ESC (Electronic Stability Control). For each crash, the road was also classified according to EuroRAP (European Road Assessment Programme) criteria, and human behavior in terms of speeding, seat belt use, and driving under the influence of alcohol/drugs. Each crash was compared and classified according to the model criteria. Crashes where the safety criteria were not met in more than one of the 3 components were reclassified to identify whether all the components were correlated to the injury outcome. In-depth crash injury data collected by the UK On The Spot (OTS) accident investigation project was used in this study. All crashes in the OTS database occurring between 2000 and 2005 with a car occupant with injury rated MAIS2+ were included, for a total of 101 crashes with 120 occupants. It was possible to classify 90 percent of the crashes according to the model. Eighty-six percent of the occupants were injured when more than one of the 3 components were noncompliant with the safety criteria. These cases were reclassified to identify whether all of the components were correlated to the injury outcome. In 39 of the total 108 cases, at least two components were still seen to interact. The remaining cases were only related to one of the safety criteria

  3. Flow and nutrient dynamics in a subterranean estuary (Waquoit Bay, MA, USA): Field data and reactive transport modeling

    Science.gov (United States)

    Spiteri, Claudette; Slomp, Caroline P.; Charette, Matthew A.; Tuncay, Kagan; Meile, Christof

    2008-07-01

    A two-dimensional (2D) reactive transport model is used to investigate the controls on nutrient ( NO3-, NH4+, PO 4) dynamics in a coastal aquifer. The model couples density-dependent flow to a reaction network which includes oxic degradation of organic matter, denitrification, iron oxide reduction, nitrification, Fe 2+ oxidation and sorption of PO 4 onto iron oxides. Porewater measurements from a well transect at Waquoit Bay, MA, USA indicate the presence of a reducing plume with high Fe 2+, NH4+, DOC (dissolved organic carbon) and PO 4 concentrations overlying a more oxidizing NO3--rich plume. These two plumes travel nearly conservatively until they start to overlap in the intertidal coastal sediments prior to discharge into the bay. In this zone, the aeration of the surface beach sediments drives nitrification and allows the precipitation of iron oxide, which leads to the removal of PO 4 through sorption. Model simulations suggest that removal of NO3- through denitrification is inhibited by the limited overlap between the two freshwater plumes, as well as by the refractory nature of terrestrial DOC. Submarine groundwater discharge is a significant source of NO3- to the bay.

  4. An algorithm for the estimation of road traffic space mean speeds from double loop detector data

    Energy Technology Data Exchange (ETDEWEB)

    Martinez-Diaz, M.; Perez Perez, I.

    2016-07-01

    Most algorithms trying to analyze or forecast road traffic rely on many inputs, but in practice, calculations are usually limited by the available data and measurement equipment. Generally, some of these inputs are substituted by raw or even inappropriate estimations, which in some cases come into conflict with the fundamentals of traffic flow theory. This paper refers to one common example of these bad practices. Many traffic management centres depend on the data provided by double loop detectors, which supply, among others, vehicle speeds. The common data treatment is to compute the arithmetic mean of these speeds over different aggregation periods (i.e. the time mean speeds). Time mean speed is not consistent with Edie’s generalized definitions of traffic variables, and therefore it is not the average speed which relates flow to density. This means that current practice begins with an error that can have negative effects in later studies and applications. The algorithm introduced in this paper enables easily the estimation of space mean speeds from the data provided by the loops. It is based on two key hypotheses: stationarity of traffic and log-normal distribution of the individual speeds in each time interval of aggregation. It could also be used in case of transient traffic as a part of any data fusion methodology. (Author)

  5. Development and use of GREET 1.6 fuel-cycle model for transportation fuels and vehicle technologies

    International Nuclear Information System (INIS)

    Wang, M. Q.

    2001-01-01

    Since 1995, with funds from the U.S. Department of Energy's (DOE's) Office of Transportation Technologies (OTT), Argonne National Laboratory has been developing the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model. The model is intended to serve as an analytical tool for use by researchers and practitioners in estimating fuel-cycle energy use and emissions associated with alternative transportation fuels and advanced vehicle technologies. Argonne released the first version of the GREET mode--GREET 1.0--in June 1996. Since then, it has released a series of GREET versions with revisions, updates, and upgrades. In February 2000, the latest public version of the model--GREET 1.5a--was posted on Argonne's Transportation Technology Research and Development Center (TTRDC) Web site (www.transportation.anl.gov/ttrdc/greet)

  6. Micro-level Estimation of Optimal Consumption Choice With Intertemporal Nonseparability in Preferences and Measurement Errors

    DEFF Research Database (Denmark)

    Gayle, Wayne-Roy; Khorunzhina, Natalia

    2018-01-01

    This article investigates the presence of habit formation in household consumption, using data from the Panel Study of Income Dynamics. We develop an econometric model of internal habit formation of the multiplicative specification. The restrictions of the model allow for classical measurement er...

  7. Advances in dynamic network modeling in complex transportation systems

    CERN Document Server

    Ukkusuri, Satish V

    2013-01-01

    This book focuses on the latest in dynamic network modeling, including route guidance and traffic control in transportation systems and other complex infrastructure networks. Covers dynamic traffic assignment, flow modeling, mobile sensor deployment and more.

  8. Determinan Permintaan Pariwisata di ASEAN (Analisis Data Panel Dinamis 2000-2015 [Tourism Demand Determinants in ASEAN (Dynamic Panel Data Analysis 2000-2015

    Directory of Open Access Journals (Sweden)

    Christina Ruth Elisabeth

    2018-05-01

    Full Text Available The purpose of this study is to examine the determinants of tourism demands in ASEAN during the period of 2000-2015. This study uses Generalized Method of Moments (GMM to measure the impact of tourism price, infrastructure, health, openness, government