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.

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.

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.

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.

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.

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

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.

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

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

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

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.

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

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%.

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.

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).

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)

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.

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.)

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

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.

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.

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

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...

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

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.

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.

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

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%.

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

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

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.

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%.

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.

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

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%.

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.

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.

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”....

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)

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.

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

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...

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.

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...

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.

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.

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

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.

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...

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.

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

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

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

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.

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.

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

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...

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.

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.

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

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...

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...

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

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.

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

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.

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...

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

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.

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

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

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.

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.

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

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

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.

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.

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). ...

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.

Methods of rational fuel consumption by the dump trucks in deep pits

Directory of Open Access Journals (Sweden)

Yu. I. Lel’

2017-12-01

Full Text Available The detailed analysis of “consumption Norms of fuel and lubricants...” has been performed. It was approved by the Ministry of transport of the Russian Federation and it is an official document for the valuation and planning of fuel consumption in road transport, including open pits. It was found that the “rate...” was deficient in the specific operating conditions of mining dump trucks and a significant discrepancy with the actual fuel consumption. To the greatest extent, these shortcomings are noticeable in deep pits. In the result of experimental and analytical studies a new method of rationing the diesel fuel consumption of mining dump trucks was developed. It is based on the calculation of fuel consumption for vehicle cycle and bringing the actual path length to the conventional horizontal transportation distances using the criterion of energy. This method requires comprehensive consideration of the design parameters of mining dump trucks – mining and road traffic conditions. As a criterion for evaluating the difficulty of transporting it justifies the use of the coefficient of difficulty of the course, showing how many times the energy consumption in the movement of trucks on the highway exceed the real energy consumption while driving on a horizontal road with the crushed-stone surface of the same length. The formulae are derived to determine the given distance of transportation on the basis of the horizontal equivalent of the vertical movement of the rock mass. It was found that the linear rate of flow of diesel fuel to mileage and transportation work under other equal conditions is determined by two main factors: the distance of transportation of L and the coefficient μ of difficulty of the course. As an example, the calculation of the linear differentiated norms of fuel consumption of dump trucks CAT 785B in an “Udachny” pit AK “ALROSA” (JSC. The developed method provides high accuracy of regulation of diesel fuel

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.

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.

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)

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

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)

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...

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.

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.

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

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.

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.

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)

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.

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.

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.

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.

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.

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.

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)

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

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.

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.

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

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...

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.

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...

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

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

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....

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.

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 ...

Gasoline demand in Europe. New insights

International Nuclear Information System (INIS)

Pock, Markus

2010-01-01

This study utilizes a panel data set from 14 European countries over the period 1990-2004 to estimate a dynamic model specification for gasoline demand. Previous studies estimating gasoline consumption per total passenger cars ignore the recent increase in the number of diesel cars in most European countries leading to biased elasticity estimates. We apply several common dynamic panel estimators to our small sample. Results show that specifications neglecting the share of diesel cars overestimate short-run income, price and car ownership elasticities. It appears that the results of standard pooled estimators are more reliable than common IV/GMM estimators applied to our small data set. (author)

Gasoline demand in Europe. New insights

Energy Technology Data Exchange (ETDEWEB)

Pock, Markus [Department of Economics and Finance, HealthEcon IHS - Institute for Advanced Studies, Vienna Stumpergasse 56, 1060 Vienna (Austria)

2010-01-15

This study utilizes a panel data set from 14 European countries over the period 1990-2004 to estimate a dynamic model specification for gasoline demand. Previous studies estimating gasoline consumption per total passenger cars ignore the recent increase in the number of diesel cars in most European countries leading to biased elasticity estimates. We apply several common dynamic panel estimators to our small sample. Results show that specifications neglecting the share of diesel cars overestimate short-run income, price and car ownership elasticities. It appears that the results of standard pooled estimators are more reliable than common IV/GMM estimators applied to our small data set. (author)

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.

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.

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%.

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

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%.

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.

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

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.

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

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)

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.

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

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.

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.

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

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

Spatial and temporal disaggregation of transport-related carbon dioxide emissions in Bogota - Colombia

Science.gov (United States)

Hernandez-Gonzalez, L. A.; Jimenez Pizarro, R.; Néstor Y. Rojas, N. Y.

2011-12-01

As a result of rapid urbanization during the last 60 years, 75% of the Colombian population now lives in cities. Urban areas are net sources of greenhouse gases (GHG) and contribute significantly to national GHG emission inventories. The development of scientifically-sound GHG mitigation strategies require accurate GHG source and sink estimations. Disaggregated inventories are effective mitigation decision-making tools. The disaggregation process renders detailed information on the distribution of emissions by transport mode, and the resulting a priori emissions map allows for optimal definition of sites for GHG flux monitoring, either by eddy covariance or inverse modeling techniques. Fossil fuel use in transportation is a major source of carbon dioxide (CO2) in Bogota. We present estimates of CO2 emissions from road traffic in Bogota using the Intergovernmental Panel on Climate Change (IPCC) reference method, and a spatial and temporal disaggregation method. Aggregated CO2 emissions from mobile sources were estimated from monthly and annual fossil fuel (gasoline, diesel and compressed natural gas - CNG) consumption statistics, and estimations of bio-ethanol and bio-diesel use. Although bio-fuel CO2 emissions are considered balanced over annual (or multi-annual) agricultural cycles, we included them since CO2 generated by their combustion would be measurable by a net flux monitoring system. For the disaggregation methodology, we used information on Bogota's road network classification, mean travel speed and trip length for each vehicle category and road type. The CO2 emission factors were taken from recent in-road measurements for gasoline- and CNG-powered vehicles and also estimated from COPERT IV. We estimated emission factors for diesel from surveys on average trip length and fuel consumption. Using IPCC's reference method, we estimate Bogota's total transport-related CO2 emissions for 2008 (reference year) at 4.8 Tg CO2. The disaggregation method estimation is

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.

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

Market penetration analysis of the use of hydrogen in the road transport sector of the Madrid region, using MARKAL

International Nuclear Information System (INIS)

Contreras, A.; Guervos, E.; Posso, F.

2009-01-01

Nobody can doubt today that hydrogen will, in the not-too-distant future, represent a very significant percentage of the total energy used by the transport sector. This study therefore consists of the modelling and simulation of energy consumption, by type of vehicle and fuel or energetic vector, in the road transport sector of the Madrid Region, during the period 2010-2050, using the MARKAL model. It has been necessary to complete this model by adding numerous specifications in order to determine the features of the Madrid Region, the richest Region in Spain. For the purpose of the study, three growth scenarios, based on short-term energy forecasts made by different official organizations, have been proposed for the energy consumption of the road transport sector in the Region. The results show a profound change in the current situation as there is a significant decrease in the consumption of fossil fuels and an increase in that of alternative non-fossil fuels and hydrogen. The latter, in particular, will rise from 0.1% in the year 2010, to around 50% in the year 2050, which will mean a drastic drop in the sector's CO 2 and atmospheric pollutant emissions. (author)

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.

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

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.

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

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

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

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.

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

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.

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.

Policy Pathways: Improving the Fuel Economy of Road Vehicles - A policy package

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-07-01

The transportation sector accounts for approximately one-fifth of global final energy consumption and will account for nearly all future growth in oil use, particularly for road vehicles. The right policy mix can allow countries to improve the fuel economy of road vehicles, which in turn can enhance energy security and reduce CO2 emissions. Improving the Fuel Economy of Road Vehicles highlights lessons learned and examples of good practices from countries with experience in implementing fuel economy policies for vehicles. The report, part of the IEA’s Policy Pathway series, outlines key steps in planning, implementation, monitoring and evaluation. It complements the IEA Technology Roadmap: Fuel Economy for Road Vehicles, which outlines technical options, potentials, and costs towards improvement in the near, medium and long term.

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...

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...

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.

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

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...

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.

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.

Market penetration analysis of the use of hydrogen in the road transport sector of the Madrid region, using MARKAL

Energy Technology Data Exchange (ETDEWEB)

Contreras, A.; Guervos, E. [Chemical Engineering Department, Universidad Nacional de Educacion a Distancia (UNED), Juan del Rosal 12, Madrid 28040 (Spain); Posso, F. [Science Department, ULA - Tachira, San Cristobal 5001 (Venezuela)

2009-01-15

Nobody can doubt today that hydrogen will, in the not-too-distant future, represent a very significant percentage of the total energy used by the transport sector. This study therefore consists of the modelling and simulation of energy consumption, by type of vehicle and fuel or energetic vector, in the road transport sector of the Madrid Region, during the period 2010-2050, using the MARKAL model. It has been necessary to complete this model by adding numerous specifications in order to determine the features of the Madrid Region, the richest Region in Spain. For the purpose of the study, three growth scenarios, based on short-term energy forecasts made by different official organizations, have been proposed for the energy consumption of the road transport sector in the Region. The results show a profound change in the current situation as there is a significant decrease in the consumption of fossil fuels and an increase in that of alternative non-fossil fuels and hydrogen. The latter, in particular, will rise from 0.1% in the year 2010, to around 50% in the year 2050, which will mean a drastic drop in the sector's CO{sub 2} and atmospheric pollutant emissions. (author)

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.

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.

Transport Emissions and Energy Consumption Impacts of Private Capital Investment in Public Transport

Directory of Open Access Journals (Sweden)

Yunqiang Xue

2017-10-01

Full Text Available Introducing private capital into the public transport system for its sustainable development has been increasing around the world. However, previous research ignores emissions and energy consumption impacts, which are important for private capital investment policy-making. To address this problem, the system dynamic (SD approach was used to quantitatively analyze the cumulative effects of different private capital investment models in public transport from the environmental perspective. The SD model validity was verified in the case study of Jinan public traffic. Simulation results show that the fuel consumption and emission reductions are obvious when the private capital considering passenger value invests in public transport compared with the no private capital investment and traditional investment models. There are obvious cumulative reductions for fuel consumption, CO2, CO, SO2, and PM10 emissions for 100 months compared with no private capital investment. This research verifies the superiority of the passenger value investment model in public transport from the environmental point of view, and supplies a theoretical tool for administrators to evaluate the private capital investment effects systematically.

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.

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

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.

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...

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.

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

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...

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.

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.

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...

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.

Transport systems - solid indigenous fuels. [Identification of fuel transport problems in Sweden]. Transportsystem foer fasta inhemska braenslen

Energy Technology Data Exchange (ETDEWEB)

Colliander, J

1985-12-01

The following problems have been indentified: - A rational structure of transporting requires an established and relatively open market. - The necessary rolling stock for fuel conveyance by rail is not available. - Roads have to be improved and new roads have to be built. Railways with low load now might get a motivation for reinforcement. - Because of the irregular spread of consumption storing and terminals problems will arise and increase the cost of transport. - Terminals and stores are situated at a convenient place for one single enterprice. On a far-away aim this will not be rational.

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.)

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

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.

The Influence of the Urban Transport System in Java on City Fuel ...

African Journals Online (AJOL)

The system of city transportation and city typology in Central Java affects the fluctuation of fuel consumption. The population size, number of private motor vehicles, RGDP (Regional Gross Domesic Product), number of motorcycles and road length have high correlation with fuel consumption. The higher the population size, ...

Brazilian Amazon Roads and Parks: Temporal & Spatial Deforestation Dynamics

Science.gov (United States)

Pfaff, A.; Robalino, J.

2011-12-01

Heterogeneous Forest Impacts of Transport Infrastructure: spatial frontier dynamics & impacts of Brazilian Amazon road changes Prior research on road impacts has almost completely ignored heterogeneity of impacts and as a result both empirically understated potential impact and missed policy potential. We note von Thunen's model suggests not only heterogeneity with distance from market but also specifically road impacts rising then falling with distance ('non-monoThunicity') Endogenous development and partial adjustment dynamics support this for the short run. Causal effects result from studying Brazilian Amazon deforestation (1976-87, 2000-04) using matching for short-run responses to lagged new roads changes (1968-75, 1985-00). We show the critical role of prior development, proxied by 1968 and 1985 road distances, for which exact matching addresses development trends and transforms impact estimates. Splitting the sample on this measure finds confirmation of the nonmonotonic predictions: new road impacts are relatively low if a prior road was close, such that prior transport access and endogenous development dynamics compete with the new road for influence, but also if a prior road was far, since first-decade adjustment in pristine areas is limited; yet in between these bounds, investments immediately raise deforestation significantly. This pattern helps to explain lower estimates within research on a single average impact. It suggests potential for REDD if a country chooses to shift its spatial transport networks. Protected Areas & Brazilian Amazon Deforestation: modeling and testing the impacts of varied PA strategies We model and then estimate the impacts of multiple types of protected areas upon 2000 - 2004 deforestation in the Brazilian Amazon. Our modeling starts with federal versus state objectives and predicts differences in both choice and implementation of each PA strategy that we examine. Our empirical examination brings not only breakdowns sufficient

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.

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.

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.

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.

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.

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.

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.

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.

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

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...

International comparisons of energy and environmental efficiency in the road transport sector

International Nuclear Information System (INIS)

Ben Abdallah, Khaled; Belloumi, Mounir; De Wolf, Daniel

2015-01-01

The present work provides an international comparison of the energy intensity and the carbon dioxide intensity in road transport for a group of 90 countries over the period 1980–2012. This paper attempts to perform a comparative analysis to find the most appropriate mapping of the energy performance in road transport taking into account the three dimensions of sustainable energy development, namely road transport-related energy consumption, economic growth and carbon dioxide emissions. An important result of the study is the inverse relationship between energy efficiency and environmental efficiency. Through the calculated Theil coefficient, our empirical findings highlight the existence of spatial and temporal disparities between countries. In 2012, Tunisia occupies the 48th and the 38th rank respectively in terms of energy and environmental efficiency. Based on a general index of energy performance in the road transport sector, it is deemed to have a medium–high energy performance by occupying the 34th rank. The study shows the importance of enhancing a number of policies for the road transport system through the joint improvement of the fuel price policy, of the road infrastructure policy and of the fuel-efficient road vehicles policy, in order to maintain sustainable energy road transport. - Highlights: • The paper presents an international comparative analysis of the energy performance. • The road transport is analyzed for a group of 90 countries over the period 1980–2012. • There is no convergence between energy and environmental efficiencies. • Tunisia has a medium-high energy performance by occupying the 34th rank in 2012. • The findings show the importance of enhancing some policies for the road transport.

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

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.

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

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.

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.

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.

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

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

Energy for sustainable road transportation in China: Challenges, initiatives and policy implications

Energy Technology Data Exchange (ETDEWEB)

Hu, Xiaojun; Chang, Shiyan; Li, Jingjie; Qin, Yining [Institute of Energy and Environmental Economics, Energy Science Building, Tsinghua University, Beijing 100084 (China)

2010-11-15

This paper presents an overview of the initiatives launched in energy supply and consumption and the challenges encountered in sustainable road transportation development in China. It analyzes the main energy challenges related to road transportation development arising in the context of economic development, rapid urbanization, and improvement in living standards. It also discusses technological- and policy initiatives needed to deal with these challenges, drawing comparisons with foreign experience: promoting the development and dissemination of alternative fuels and clean vehicles such as: LPG, CNG, EV, HEV, FCV, ethanol, methanol, DME, bio-diesel, and CTL, strengthening regulations relating to vehicle fuel economy and emission, improving traffic efficiency and facilitating public transport development, and strengthening management of the soaring motor vehicle population. If the current pattern continues, by the year 2030, the vehicle population in China will be 400 million and fuel demand will be 350 million tons. The potential energy saving capacity being 60%, the actual oil demand by 2030 from on-road vehicles might technically be kept at the current level by improving fuel economy, propagating use of HEV and diesel vehicles, improving supply of alternative fuels, and developing public transport. Several uncertainties are identified that could greatly influence the effect of the technical proposals: traffic efficiency, central government's resolve, and consumers' choice. (author)

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.

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.)

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)

CO2 mitigation scenarios in China's road transport sector

International Nuclear Information System (INIS)

Wang, Can; Cai, Wenjia; Lu, Xuedu; Chen, Jining

2007-01-01

China is the world's second largest greenhouse gas emitter, and emissions from the road transport sector represent one of the fastest growing GHG sources in China. Taking previous research on China's projected future vehicle ownership and future CO 2 emissions in the transport sector as a starting point, this paper reviews all recent environmental policies relating to the automobile industry and employs a scenario analysis to estimate different emissions inventories for different development strategies. The new policy scenario considers all possible mitigation options available to the road transport sector from a bottom up perspective and examines the effects for fuel efficiency improvement and the cost of these mitigation options - vehicle technology improvement, bus rapid transit system and fuel switching, through which the carbon dioxide emissions reduction potential is estimated. Not only does this paper indicate that a large emissions reduction potential exists in China's road transport sector, but it implies that vehicle technology improvement, especially engine technology is likely to be the most effective means to meet emissions reduction targets. This paper concludes by identifying key barriers to implementing those options in China and deduces the technical, financial and institutional aspects of the demand in China for national capacity building and international aid in order to achieve the emissions reduction goals

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

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

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.

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.

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.

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.

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.

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.

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)

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.

Integrating pro-environmental behavior with transportation network modeling: User and system level strategies, implementation, and evaluation

Science.gov (United States)

Aziz, H. M. Abdul

Personal transport is a leading contributor to fossil fuel consumption and greenhouse (GHG) emissions in the U.S. The U.S. Energy Information Administration (EIA) reports that light-duty vehicles (LDV) are responsible for 61% of all transportation related energy consumption in 2012, which is equivalent to 8.4 million barrels of oil (fossil fuel) per day. The carbon content in fossil fuels is the primary source of GHG emissions that links to the challenge associated with climate change. Evidently, it is high time to develop actionable and innovative strategies to reduce fuel consumption and GHG emissions from the road transportation networks. This dissertation integrates the broader goal of minimizing energy and emissions into the transportation planning process using novel systems modeling approaches. This research aims to find, investigate, and evaluate strategies that minimize carbon-based fuel consumption and emissions for a transportation network. We propose user and system level strategies that can influence travel decisions and can reinforce pro-environmental attitudes of road users. Further, we develop strategies that system operators can implement to optimize traffic operations with emissions minimization goal. To complete the framework we develop an integrated traffic-emissions (EPA-MOVES) simulation framework that can assess the effectiveness of the strategies with computational efficiency and reasonable accuracy. The dissertation begins with exploring the trade-off between emissions and travel time in context of daily travel decisions and its heterogeneous nature. Data are collected from a web-based survey and the trade-off values indicating the average additional travel minutes a person is willing to consider for reducing a lb. of GHG emissions are estimated from random parameter models. Results indicate that different trade-off values for male and female groups. Further, participants from high-income households are found to have higher trade-off values

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.)

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.

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.

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.

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.

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.

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.

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.

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.

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.

Modifying the rebound: It depends! Explaining mobility behavior on the basis of the German socio-economic panel

International Nuclear Information System (INIS)

Matiaske, Wenzel; Menges, Roland; Spiess, Martin

2012-01-01

We address the empirical question of the extent to which higher fuel efficiency of cars affects additional travel and the way this behavioral aspect is modified by additional variables. The data set used to estimate a theoretical model of the rebound effect covers two panel waves, 1998 and 2003, taken from the German Socio-Economic Panel (SOEP). To take full advantage of the information in the data available, and to avoid problems due to possible selection effects, we estimated an unbalanced two-wave random effects panel model. Our results suggest that in line with the rebound hypothesis, car efficiency has a negative effect on the kilometers driven. That is, the lower the fuel consumption, the greater the distance driven. However, contrasting recent empirical literature about the rebound effect in the transportation sector, this seems to be true only for cars with a consumption of more than roughly 8 l per 100 km. In addition, we find a positive diesel effect, which implies that owning a diesel engine car is positively correlated with the distance driven. Both effects can be interpreted as support for the rebound hypothesis, although not in a simple linear way. Moreover, it can be shown that some “soft” variables such as certain attitudes towards the environment tend to amplify this non-linear rebound effect. - Research Highlights: ► We address the empirical question of the extent to which higher fuel efficiency of cars affects additional travel. ► The data set covers two panel waves, 1998 and 2003, taken from the German Socio-Economic Panel (SOEP). We estimate an unbalanced two-wave random effects panel model. ► Contrasting recent empirical literature, this seems to be true only for cars with a consumption of more than roughly 8 l per 100 km.► In addition, we find a positive diesel effect: Owning a diesel engine car has a positive effect on the distance driven. Both effects support the rebound hypothesis, although not in a simple linear way.► It can

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.

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

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.

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.

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.

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...

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

Investment patterns in Dutch glasshouse horticulture

NARCIS (Netherlands)

Goncharova, N.

2007-01-01

Keywords: investment, uncertainty, investment spikes, entry, exit, duration model, GMM dynamic panel data estimator, Negative Binomial model, Heckman selection model, moving window ARIMA, Principal Component analysis, horticulture

This thesis focuses on the analysis of investment

Experimental and numerical assessment of on-road diesel and biodiesel emissions

Energy Technology Data Exchange (ETDEWEB)

West, B.H.; Storey, J.M.; Lewis, S.A.; Devault, G.L.; Green, J.B. [Oak Ridge National Lab., TN (United States); Sluder, C.S.; Hodgson, J.W.; Moore, B.L. [Univ. of Tennessee, Knoxville, TN (United States)

1997-12-31

The Federal Highway Administration`s TRAF-series of models use modal data to estimate fuel consumption and emissions for different traffic scenarios. A process for producing data-based modal models from road and dynamometer measurements has been developed and applied to a number of light-duty gasoline vehicles for the FHWA. The resulting models, or lookup tables, provide emissions and fuel consumption as functions of vehicle speed and acceleration. Surface plots of the data provide a valuable visual benchmark of the emissions characteristics of the vehicles. Due to the potential fuel savings in the light-duty sector via introduction of diesels, and the concomitant growing interest in diesel engine emissions, the measurement methodology has been extended under DOE sponsorship to include a diesel pickup truck running a variety of fuels, including number 2 diesel fuel, biodiesel, Fischer-Tropsch, and blends.

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.

Proceedings of the 2008 transportation technologies and fuels forum

International Nuclear Information System (INIS)

2008-01-01

As a large emitter of pollutants, the transportation industry is now seeking to develop a sustainable transportation plan for the future by developing methods of reducing emissions and improving the fuel efficiency of vehicles. This forum discussed recent innovations in vehicle transportation technologies. Industry leaders, government representatives, and researchers discussed methods of reducing greenhouse gases (GHGs) and air pollution in the transportation sector. Advanced combustion technologies were outlined, and recent developments in hybrid electric-powered vehicles were discussed. Research related to fuel cells, hydrogen fuels and biofuels was presented. The impacts of polluting vehicles on public health were also discussed. The forum was divided into the following 5 sessions: (1) setting the scene, (2) future fuels, (3) emissions, (4) EVs now, and (5) the road to the future. The sessions were followed by a panel on technology roadmaps. The forum featured 14 presentations, of which 4 have been catalogued separately for inclusion in this database. tabs., figs.

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

Real-world comparison of probe vehicle emissions and fuel consumption using diesel and 5% biodiesel (B5) blend

Energy Technology Data Exchange (ETDEWEB)

Ropkins, Karl; Quinn, Robert; Tate, James; Bell, Margaret [Institute for Transport Studies, University of Leeds, Leeds, LS2 9JT (United Kingdom); Beebe, Joe [National Center for Vehicle Emissions Control and Safety, Colorado State University, Colorado 80523-1584 (United States); Li, Hu; Daham, Basil; Andrews, Gordon [Energy and Resources Research Institute, University of Leeds, Leeds, LS2 9JT (United Kingdom)

2007-04-15

An instrumented EURO I Ford Mondeo was used to perform a real-world comparison of vehicle exhaust (carbon dioxide, carbon monoxide, hydrocarbons and oxides of nitrogen) emissions and fuel consumption for diesel and 5% biodiesel in diesel blend (B5) fuels. Data were collected on multiple replicates of three standardised on-road journeys: (1) a simple urban route; (2) a combined urban/inter-urban route; and, (3) an urban route subject to significant traffic management. At the total journey measurement level, data collected here indicate that replacing diesel with a B5 substitute could result in significant increases in both NO{sub x} emissions (8-13%) and fuel consumption (7-8%). However, statistical analysis of probe vehicle data demonstrated the limitations of comparisons based on such total journey measurements, i.e., methods analogous to those used in conventional dynamometer/drive cycle fuel comparison studies. Here, methods based on the comparison of speed/acceleration emissions and fuel consumption maps are presented. Significant variations across the speed/acceleration surface indicated that direct emission and fuel consumption impacts were highly dependent on the journey/drive cycle employed. The emission and fuel consumption maps were used both as descriptive tools to characterise impacts and predictive tools to estimate journey-specific emission and fuel consumption effects. (author)

Real-world comparison of probe vehicle emissions and fuel consumption using diesel and 5% biodiesel (B5) blend

International Nuclear Information System (INIS)

Ropkins, Karl; Quinn, Robert; Tate, James; Bell, Margaret; Beebe, Joe; Li, Hu; Daham, Basil; Andrews, Gordon

2007-01-01

An instrumented EURO I Ford Mondeo was used to perform a real-world comparison of vehicle exhaust (carbon dioxide, carbon monoxide, hydrocarbons and oxides of nitrogen) emissions and fuel consumption for diesel and 5% biodiesel in diesel blend (B5) fuels. Data were collected on multiple replicates of three standardised on-road journeys: (1) a simple urban route; (2) a combined urban/inter-urban route; and, (3) an urban route subject to significant traffic management. At the total journey measurement level, data collected here indicate that replacing diesel with a B5 substitute could result in significant increases in both NO x emissions (8-13%) and fuel consumption (7-8%). However, statistical analysis of probe vehicle data demonstrated the limitations of comparisons based on such total journey measurements, i.e., methods analogous to those used in conventional dynamometer/drive cycle fuel comparison studies. Here, methods based on the comparison of speed/acceleration emissions and fuel consumption maps are presented. Significant variations across the speed/acceleration surface indicated that direct emission and fuel consumption impacts were highly dependent on the journey/drive cycle employed. The emission and fuel consumption maps were used both as descriptive tools to characterise impacts and predictive tools to estimate journey-specific emission and fuel consumption effects. (author)

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.

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...

Energy consumption, political regime and economic growth in sub-Saharan Africa

International Nuclear Information System (INIS)

Adams, Samuel; Klobodu, Edem Kwame Mensah; Opoku, Eric Evans Osei

2016-01-01

In this paper, we examine the relationship between energy consumption and economic growth, and how democracy moderates this relationship using panel data of 16 sub-Saharan African (SSA) countries for the period 1971–2013. Employing a panel vector autoregressive model (PVAR) in a generalized method of moments (GMM) framework, the findings support the feedback hypothesis for energy consumption and growth. Second, the interaction variable (energy consumption and democracy) is positively and significantly related to economic growth, supporting the view that democracy moderates the energy consumption and growth nexus. Further, the results provide strong evidence of a uni-directional relationship from trade openness to energy consumption. Additionally, impulse responses and variance decompositions also confirm positive feedback relationships between energy consumption and economic growth, energy prices and economic growth. - Highlights: •Feedback exists between energy consumption and economic growth. •Democracy moderates the energy consumption and growth nexus. •positive feedback between energy prices and economic growth. •Uni-directional relationship from openness to energy consumption.

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...

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.

A fuel-based approach to estimating motor vehicle exhaust emissions

Science.gov (United States)

Singer, Brett Craig

Motor vehicles contribute significantly to air pollution problems; accurate motor vehicle emission inventories are therefore essential to air quality planning. Current travel-based inventory models use emission factors measured from potentially biased vehicle samples and predict fleet-average emissions which are often inconsistent with on-road measurements. This thesis presents a fuel-based inventory approach which uses emission factors derived from remote sensing or tunnel-based measurements of on-road vehicles. Vehicle activity is quantified by statewide monthly fuel sales data resolved to the air basin level. Development of the fuel-based approach includes (1) a method for estimating cold start emission factors, (2) an analysis showing that fuel-normalized emission factors are consistent over a range of positive vehicle loads and that most fuel use occurs during loaded-mode driving, (3) scaling factors relating infrared hydrocarbon measurements to total exhaust volatile organic compound (VOC) concentrations, and (4) an analysis showing that economic factors should be considered when selecting on-road sampling sites. The fuel-based approach was applied to estimate carbon monoxide (CO) emissions from warmed-up vehicles in the Los Angeles area in 1991, and CO and VOC exhaust emissions for Los Angeles in 1997. The fuel-based CO estimate for 1991 was higher by a factor of 2.3 +/- 0.5 than emissions predicted by California's MVEI 7F model. Fuel-based inventory estimates for 1997 were higher than those of California's updated MVEI 7G model by factors of 2.4 +/- 0.2 for CO and 3.5 +/- 0.6 for VOC. Fuel-based estimates indicate a 20% decrease in the mass of CO emitted, despite an 8% increase in fuel use between 1991 and 1997; official inventory models predict a 50% decrease in CO mass emissions during the same period. Cold start CO and VOC emission factors derived from parking garage measurements were lower than those predicted by the MVEI 7G model. Current inventories

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...

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.

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

Fuel-Efficient Road Vehicle Non-Engine Components

Energy Technology Data Exchange (ETDEWEB)

NONE

2007-07-01

The need to address global energy issues, i.e. energy security and climate change, is more urgent than ever. Road vehicles dominate global oil consumption and are one of the fastest growing energy end-uses. This paper studies policies and measures to improve on-road fuel efficiency of vehicles by focusing on energy efficiency of automobile components not generally considered in official fuel efficiency test, namely tyres, cooling technologies and lightings. In this paper, current policies and industry activities on these components are reviewed, fuel saving potential by the components analysed and possible policies to realise the potential recommended.

Transportation Secure Data Center: Real-World Data for Planning, Modeling, and Analysis

Energy Technology Data Exchange (ETDEWEB)

2018-01-19

The Transportation Secure Data Center (TSDC) at www.nrel.gov/tsdc provides free, web-based access to detailed transportation data from a variety of travel surveys conducted across the nation. While preserving the privacy of survey participants, this online repository makes vital transportation data broadly available to users from the comfort of their own desks via a secure online connection. Data Available through the TSDC: Maintained by the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) in partnership with the U.S. Department of Transportation (DOT), the TSDC houses data from travel surveys and studies conducted using global positioning system (GPS) devices. It features millions of data points - second-by-second GPS readings, vehicle characteristics (if applicable), and demographics - for all modes of travel. NREL screens the initial data for quality control, translates each data set into a consistent format, and interprets the data for spatial analysis. NREL's processing routines add information on vehicle fuel economy and road grades and join data points to the road network.

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

Estimating Energy Consumption of Mobile Fluid Power in the United States

Energy Technology Data Exchange (ETDEWEB)

Lynch, Lauren [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zigler, Bradley T. [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-11-02

This report estimates the market size and energy consumption of mobile off-road applications utilizing hydraulic fluid power, and summarizes technology gaps and implementation barriers. Mobile fluid power is the use of hydraulic fluids under pressure to transmit power in mobile equipment applications. The mobile off-road fluid power sector includes various uses of hydraulic fluid power equipment with fundamentally diverse end-use application and operational requirements, such as a skid steer loader, a wheel loader or an agriculture tractor. The agriculture and construction segments dominate the mobile off-road fluid power market in component unit sales volume. An estimated range of energy consumed by the mobile off-road fluid power sector is 0.36 - 1.8 quads per year, which was 1.3 percent - 6.5 percent of the total energy consumed in 2016 by the transportation sector. Opportunities for efficiency improvements within the fluid power system result from needs to level and reduce the peak system load requirements and develop new technologies to reduce fluid power system level losses, both of which may be facilitated by characterizing duty cycles to define standardized performance test methods. There are currently no commonly accepted standardized test methods for evaluating equipment level efficiency over a duty cycle. The off-road transportation sector currently meets criteria emissions requirements, and there are no efficiency regulations requiring original equipment manufacturers (OEM) to invest in new architecture development to improve the fuel economy of mobile off-road fluid power systems. In addition, the end-user efficiency interests are outweighed by low equipment purchase or lease price concerns, required payback periods, and reliability and durability requirements of new architecture. Current economics, low market volumes with high product diversity, and regulation compliance challenge OEM investment in commercialization of new architecture development.

Emission projections of the transport Sector in China: 2015-2040

Science.gov (United States)

Yan, L.

2016-12-01

Driven by the significant growth freight and passenger transport demand, transport sector has become a sector that is largely responsible for increases in emissions of atmospheric pollutants (NOx, CO, HC, PM2.5) in China. Figuring out the emission trend in China's transport sector has great influence on formulating emission reduction measures in the future. In this work, both on-road and off-road transport emissions in China were estimated from 2015 to 2040 for CO, NOx, HC and PM2.5. The projection was conducted based on on the energy consumption structure forecast from IEA (International Energy Agency), the future national average annual distance traveled per vehicle and fuel consumption per distance derived from simulation results of the Fuel Economy and Environmental Impact (FEEI) model. The results show that the ownership of on-road vehicles in China increases rapidly during 2015 to 2030 and then the growth slows down. Finally, the total amount reaches up to 522 million in 2040 in which 84.5% turns out to be light-duty vehicles. Because current control legislations for the transport sector in China will continue to be strengthened in the future, the total emissions of China's transport sector were projected to peak around 2030, due to the improvement of vehicle emission standard and the retirement of old vehicles are the most effective measures. The off-road transport will become the main contributor to emissions from transport sector in China since 2030. This work provides a new perspective to understand emissions from both on-road and off-road transport in China, which can support the achievement of improving air quality promised by the Chinese government. This work provides a new perspective to understand the emission trends of on-road and off-road transport sector in China from 2015 to 2040, which can support the achievement of the air quality goal promised by the Chinese government. Driven by the significant growth freight and passenger transport demand

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...

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.

Energy and environmental impacts of alternative pathways for the Portuguese road transportation sector

International Nuclear Information System (INIS)

Baptista, Patrícia C.; Silva, Carla M.; Farias, Tiago L.; Heywood, John B.

2012-01-01

This study presents a methodology to develop scenarios of evolution from 2010 to 2050, for energy consumption and emissions (CO 2 , HC, CO, NO x , PM) of the road transportation sector (light-duty and heavy-duty vehicles). The methodology is applied to Portugal and results are analyzed in a life-cycle perspective. A BAU trend and 5 additional scenarios are explored: Policy-based (Portuguese political targets considered); Liquid fuels-based (dependency on liquid fuels and no deployment of alternative refueling infrastructure); Diversified (introduction of a wide diversity of alternative vehicle technology/energy sources); Electricity vision (deployment of a wide spread electricity recharging infrastructure); Hydrogen pathway (a broad hydrogen refueling infrastructure is deployed). Total life-cycle energy consumption could decrease between 2 and 66% in 2050 relatively to 2010, while CO 2 emissions will decrease between 7 and 73% in 2050 relatively to 2010. In 2050 the BAU scenario remains 30% above the 1990 level for energy consumption and CO 2 emissions; the other considered scenarios lead to 4 to 29% reductions for energy consumption and 10 to 33% for CO 2 emissions in 2050 compared to the BAU. Therefore, alternative vehicle technologies are required in the long-term, but changes in taxation and alternative transportation modes policies are crucial for achieving short-term impacts. - Highlight: ► Assess future energy consumption and emissions scenarios for road transportation. ► LCA energy consumption could decrease 2 to 66% in 2050 relatively to 2010. ► Alternative vehicle technologies can help to lower the BAU scenario impacts. ► Different deployments of alternative technologies can lead to similar impacts.

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....

STUDY ABOUT THE ROAD TRANSPORTATION COSTS AND FISCALITY IN THE ROMANIAN COMPANIES

Directory of Open Access Journals (Sweden)

Violeta Isai

2013-12-01

Full Text Available The economic development of the European countries in the second half of the XXth century, and also the increase of commercial international exchanges, generated the transportation development in general, and especially the road transportation. The road transports knew an ascendant evolution due to their advantages: superior mobility; fast adaptability to every land conditions, without special investments; the capacity to complete the other modalities of transportation, in order to achieve the transportation chain; the only one type or transportation which can be done by self; the insurance of wares perishability, without require supplementary manipulations during the transportation. It’s obvious that, there are also negative aspects like: pollution and supplementary fuel consumption. On the level of Romanian companies, transports rise problems related on their costs, the costs structure and the directions to make this activity profitable.The Romanian government established fiscal measures, in order to make the companies more responsible in the vehicles use and their efficient exploitation.

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

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

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.

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.

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

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

Robust generative asymmetric GMM for brain MR image segmentation.

Science.gov (United States)

Ji, Zexuan; Xia, Yong; Zheng, Yuhui

2017-11-01

Accurate segmentation of brain tissues from magnetic resonance (MR) images based on the unsupervised statistical models such as Gaussian mixture model (GMM) has been widely studied during last decades. However, most GMM based segmentation methods suffer from limited accuracy due to the influences of noise and intensity inhomogeneity in brain MR images. To further improve the accuracy for brain MR image segmentation, this paper presents a Robust Generative Asymmetric GMM (RGAGMM) for simultaneous brain MR image segmentation and intensity inhomogeneity correction. First, we develop an asymmetric distribution to fit the data shapes, and thus construct a spatial constrained asymmetric model. Then, we incorporate two pseudo-likelihood quantities and bias field estimation into the model's log-likelihood, aiming to exploit the neighboring priors of within-cluster and between-cluster and to alleviate the impact of intensity inhomogeneity, respectively. Finally, an expectation maximization algorithm is derived to iteratively maximize the approximation of the data log-likelihood function to overcome the intensity inhomogeneity in the image and segment the brain MR images simultaneously. To demonstrate the performances of the proposed algorithm, we first applied the proposed algorithm to a synthetic brain MR image to show the intermediate illustrations and the estimated distribution of the proposed algorithm. The next group of experiments is carried out in clinical 3T-weighted brain MR images which contain quite serious intensity inhomogeneity and noise. Then we quantitatively compare our algorithm to state-of-the-art segmentation approaches by using Dice coefficient (DC) on benchmark images obtained from IBSR and BrainWeb with different level of noise and intensity inhomogeneity. The comparison results on various brain MR images demonstrate the superior performances of the proposed algorithm in dealing with the noise and intensity inhomogeneity. In this paper, the RGAGMM

Transportation Sector Model of the National Energy Modeling System. Volume 1

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-01-01

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. The NEMS Transportation Model comprises a series of semi-independent models which address different aspects of the transportation sector. The primary purpose of this model is to provide mid-term forecasts of transportation energy demand by fuel type including, but not limited to, motor gasoline, distillate, jet fuel, and alternative fuels (such as CNG) not commonly associated with transportation. The current NEMS forecast horizon extends to the year 2010 and uses 1990 as the base year. Forecasts are generated through the separate consideration of energy consumption within the various modes of transport, including: private and fleet light-duty vehicles; aircraft; marine, rail, and truck freight; and various modes with minor overall impacts, such as mass transit and recreational boating. This approach is useful in assessing the impacts of policy initiatives, legislative mandates which affect individual modes of travel, and technological developments. The model also provides forecasts of selected intermediate values which are generated in order to determine energy consumption. These elements include estimates of passenger travel demand by automobile, air, or mass transit; estimates of the efficiency with which that demand is met; projections of vehicle stocks and the penetration of new technologies; and estimates of the demand for freight transport which are linked to forecasts of industrial output. Following the estimation of energy demand, TRAN produces forecasts of vehicular emissions of the following pollutants by source: oxides of sulfur, oxides of nitrogen, total carbon, carbon dioxide, carbon monoxide, and volatile organic compounds.

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...