An inexact fuzzy-chance-constrained air quality management model.

Science.gov (United States)

Xu, Ye; Huang, Guohe; Qin, Xiaosheng

2010-07-01

Regional air pollution is a major concern for almost every country because it not only directly relates to economic development, but also poses significant threats to environment and public health. In this study, an inexact fuzzy-chance-constrained air quality management model (IFAMM) was developed for regional air quality management under uncertainty. IFAMM was formulated through integrating interval linear programming (ILP) within a fuzzy-chance-constrained programming (FCCP) framework and could deal with uncertainties expressed as not only possibilistic distributions but also discrete intervals in air quality management systems. Moreover, the constraints with fuzzy variables could be satisfied at different confidence levels such that various solutions with different risk and cost considerations could be obtained. The developed model was applied to a hypothetical case of regional air quality management. Six abatement technologies and sulfur dioxide (SO2) emission trading under uncertainty were taken into consideration. The results demonstrated that IFAMM could help decision-makers generate cost-effective air quality management patterns, gain in-depth insights into effects of the uncertainties, and analyze tradeoffs between system economy and reliability. The results also implied that the trading scheme could achieve lower total abatement cost than a nontrading one.

Risk-constrained self-scheduling of a fuel and emission constrained power producer using rolling window procedure

International Nuclear Information System (INIS)

Kazempour, S. Jalal; Moghaddam, Mohsen Parsa

2011-01-01

This work addresses a relevant methodology for self-scheduling of a price-taker fuel and emission constrained power producer in day-ahead correlated energy, spinning reserve and fuel markets to achieve a trade-off between the expected profit and the risk versus different risk levels based on Markowitz's seminal work in the area of portfolio selection. Here, a set of uncertainties including price forecasting errors and available fuel uncertainty are considered. The latter uncertainty arises because of uncertainties in being called for reserve deployment in the spinning reserve market and availability of power plant. To tackle the price forecasting errors, variances of energy, spinning reserve and fuel prices along with their covariances which are due to markets correlation are taken into account using relevant historical data. In order to tackle available fuel uncertainty, a framework for self-scheduling referred to as rolling window is proposed. This risk-constrained self-scheduling framework is therefore formulated and solved as a mixed-integer non-linear programming problem. Furthermore, numerical results for a case study are discussed. (author)

Modeling the microstructural evolution during constrained sintering

DEFF Research Database (Denmark)

Bjørk, Rasmus; Frandsen, Henrik Lund; Tikare, V.

A numerical model able to simulate solid state constrained sintering of a powder compact is presented. The model couples an existing kinetic Monte Carlo (kMC) model for free sintering with a finite element (FE) method for calculating stresses on a microstructural level. The microstructural response...... to the stress field as well as the FE calculation of the stress field from the microstructural evolution is discussed. The sintering behavior of two powder compacts constrained by a rigid substrate is simulated and compared to free sintering of the same samples. Constrained sintering result in a larger number...

A 3D model of polarized dust emission in the Milky Way

Science.gov (United States)

Martínez-Solaeche, Ginés; Karakci, Ata; Delabrouille, Jacques

2018-05-01

We present a three-dimensional model of polarized galactic dust emission that takes into account the variation of the dust density, spectral index and temperature along the line of sight, and contains randomly generated small-scale polarization fluctuations. The model is constrained to match observed dust emission on large scales, and match on smaller scales extrapolations of observed intensity and polarization power spectra. This model can be used to investigate the impact of plausible complexity of the polarized dust foreground emission on the analysis and interpretation of future cosmic microwave background polarization observations.

Epoch of reionization 21 cm forecasting from MCMC-constrained semi-numerical models

Science.gov (United States)

Hassan, Sultan; Davé, Romeel; Finlator, Kristian; Santos, Mario G.

2017-06-01

The recent low value of Planck Collaboration XLVII integrated optical depth to Thomson scattering suggests that the reionization occurred fairly suddenly, disfavouring extended reionization scenarios. This will have a significant impact on the 21 cm power spectrum. Using a semi-numerical framework, we improve our model from instantaneous to include time-integrated ionization and recombination effects, and find that this leads to more sudden reionization. It also yields larger H II bubbles that lead to an order of magnitude more 21 cm power on large scales, while suppressing the small-scale ionization power. Local fluctuations in the neutral hydrogen density play the dominant role in boosting the 21 cm power spectrum on large scales, while recombinations are subdominant. We use a Monte Carlo Markov chain approach to constrain our model to observations of the star formation rate functions at z = 6, 7, 8 from Bouwens et al., the Planck Collaboration XLVII optical depth measurements and the Becker & Bolton ionizing emissivity data at z ˜ 5. We then use this constrained model to perform 21 cm forecasting for Low Frequency Array, Hydrogen Epoch of Reionization Array and Square Kilometre Array in order to determine how well such data can characterize the sources driving reionization. We find that the Mock 21 cm power spectrum alone can somewhat constrain the halo mass dependence of ionizing sources, the photon escape fraction and ionizing amplitude, but combining the Mock 21 cm data with other current observations enables us to separately constrain all these parameters. Our framework illustrates how the future 21 cm data can play a key role in understanding the sources and topology of reionization as observations improve.

Lightning NOx emissions over the USA constrained by TES ozone observations and the GEOS-Chem model

Science.gov (United States)

Jourdain, L.; Kulawik, S. S.; Worden, H. M.; Pickering, K. E.; Worden, J.; Thompson, A. M.

2010-01-01

Improved estimates of NOx from lightning sources are required to understand tropospheric NOx and ozone distributions, the oxidising capacity of the troposphere and corresponding feedbacks between chemistry and climate change. In this paper, we report new satellite ozone observations from the Tropospheric Emission Spectrometer (TES) instrument that can be used to test and constrain the parameterization of the lightning source of NOx in global models. Using the National Lightning Detection (NLDN) and the Long Range Lightning Detection Network (LRLDN) data as well as the HYPSLIT transport and dispersion model, we show that TES provides direct observations of ozone enhanced layers downwind of convective events over the USA in July 2006. We find that the GEOS-Chem global chemistry-transport model with a parameterization based on cloud top height, scaled regionally and monthly to OTD/LIS (Optical Transient Detector/Lightning Imaging Sensor) climatology, captures the ozone enhancements seen by TES. We show that the model's ability to reproduce the location of the enhancements is due to the fact that this model reproduces the pattern of the convective events occurrence on a daily basis during the summer of 2006 over the USA, even though it does not well represent the relative distribution of lightning intensities. However, this model with a value of 6 Tg N/yr for the lightning source (i.e.: with a mean production of 260 moles NO/Flash over the USA in summer) underestimates the intensities of the ozone enhancements seen by TES. By imposing a production of 520 moles NO/Flash for lightning occurring in midlatitudes, which better agrees with the values proposed by the most recent studies, we decrease the bias between TES and GEOS-Chem ozone over the USA in July 2006 by 40%. However, our conclusion on the strength of the lightning source of NOx is limited by the fact that the contribution from the stratosphere is underestimated in the GEOS-Chem simulations.

Multi-Sensor Constrained Time Varying Emissions Estimation of Black Carbon: Attributing Urban and Fire Sources Globally

Science.gov (United States)

Cohen, J. B.

2015-12-01

The short lifetime and heterogeneous distribution of Black Carbon (BC) in the atmosphere leads to complex impacts on radiative forcing, climate, and health, and complicates analysis of its atmospheric processing and emissions. Two recent papers have estimated the global and regional emissions of BC using advanced statistical and computational methods. One used a Kalman Filter, including data from AERONET, NOAA, and other ground-based sources, to estimate global emissions of 17.8+/-5.6 Tg BC/year (with the increase attributable to East Asia, South Asia, Southeast Asia, and Eastern Europe - all regions which have had rapid urban, industrial, and economic expansion). The second additionally used remotely sensed measurements from MISR and a variance maximizing technique, uniquely quantifying fire and urban sources in Southeast Asia, as well as their large year-to-year variability over the past 12 years, leading to increases from 10% to 150%. These new emissions products, when run through our state-of-the art modelling system of chemistry, physics, transport, removal, radiation, and climate, match 140 ground stations and satellites better in both an absolute and a temporal sense. New work now further includes trace species measurements from OMI, which are used with the variance maximizing technique to constrain the types of emissions sources. Furthermore, land-use change and fire estimation products from MODIS are also included, which provide other constraints on the temporal and spatial nature of the variations of intermittent sources like fires or new permanent sources like expanded urbanization. This talk will introduce a new, top-down constrained, weekly varying BC emissions dataset, show that it produces a better fit with observations, and draw conclusions about the sources and impacts from urbanization one hand, and fires on another hand. Results specific to the Southeast and East Asia will demonstrate inter- and intra-annual variations, such as the function of

Reflected stochastic differential equation models for constrained animal movement

Science.gov (United States)

Hanks, Ephraim M.; Johnson, Devin S.; Hooten, Mevin B.

2017-01-01

Movement for many animal species is constrained in space by barriers such as rivers, shorelines, or impassable cliffs. We develop an approach for modeling animal movement constrained in space by considering a class of constrained stochastic processes, reflected stochastic differential equations. Our approach generalizes existing methods for modeling unconstrained animal movement. We present methods for simulation and inference based on augmenting the constrained movement path with a latent unconstrained path and illustrate this augmentation with a simulation example and an analysis of telemetry data from a Steller sea lion (Eumatopias jubatus) in southeast Alaska.

Constrained optimization via simulation models for new product innovation

Science.gov (United States)

Pujowidianto, Nugroho A.

2017-11-01

We consider the problem of constrained optimization where the decision makers aim to optimize the primary performance measure while constraining the secondary performance measures. This paper provides a brief overview of stochastically constrained optimization via discrete event simulation. Most review papers tend to be methodology-based. This review attempts to be problem-based as decision makers may have already decided on the problem formulation. We consider constrained optimization models as there are usually constraints on secondary performance measures as trade-off in new product development. It starts by laying out different possible methods and the reasons using constrained optimization via simulation models. It is then followed by the review of different simulation optimization approach to address constrained optimization depending on the number of decision variables, the type of constraints, and the risk preferences of the decision makers in handling uncertainties.

Mathematical Modeling of Constrained Hamiltonian Systems

NARCIS (Netherlands)

Schaft, A.J. van der; Maschke, B.M.

1995-01-01

Network modelling of unconstrained energy conserving physical systems leads to an intrinsic generalized Hamiltonian formulation of the dynamics. Constrained energy conserving physical systems are directly modelled as implicit Hamiltonian systems with regard to a generalized Dirac structure on the

Physics constrained nonlinear regression models for time series

International Nuclear Information System (INIS)

Majda, Andrew J; Harlim, John

2013-01-01

A central issue in contemporary science is the development of data driven statistical nonlinear dynamical models for time series of partial observations of nature or a complex physical model. It has been established recently that ad hoc quadratic multi-level regression (MLR) models can have finite-time blow up of statistical solutions and/or pathological behaviour of their invariant measure. Here a new class of physics constrained multi-level quadratic regression models are introduced, analysed and applied to build reduced stochastic models from data of nonlinear systems. These models have the advantages of incorporating memory effects in time as well as the nonlinear noise from energy conserving nonlinear interactions. The mathematical guidelines for the performance and behaviour of these physics constrained MLR models as well as filtering algorithms for their implementation are developed here. Data driven applications of these new multi-level nonlinear regression models are developed for test models involving a nonlinear oscillator with memory effects and the difficult test case of the truncated Burgers–Hopf model. These new physics constrained quadratic MLR models are proposed here as process models for Bayesian estimation through Markov chain Monte Carlo algorithms of low frequency behaviour in complex physical data. (paper)

Constraining Methane Emissions from Natural Gas Production in Northeastern Pennsylvania Using Aircraft Observations and Mesoscale Modeling

Science.gov (United States)

Barkley, Z.; Davis, K.; Lauvaux, T.; Miles, N.; Richardson, S.; Martins, D. K.; Deng, A.; Cao, Y.; Sweeney, C.; Karion, A.; Smith, M. L.; Kort, E. A.; Schwietzke, S.

2015-12-01

Leaks in natural gas infrastructure release methane (CH4), a potent greenhouse gas, into the atmosphere. The estimated fugitive emission rate associated with the production phase varies greatly between studies, hindering our understanding of the natural gas energy efficiency. This study presents a new application of inverse methodology for estimating regional fugitive emission rates from natural gas production. Methane observations across the Marcellus region in northeastern Pennsylvania were obtained during a three week flight campaign in May 2015 performed by a team from the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Division and the University of Michigan. In addition to these data, CH4 observations were obtained from automobile campaigns during various periods from 2013-2015. An inventory of CH4 emissions was then created for various sources in Pennsylvania, including coalmines, enteric fermentation, industry, waste management, and unconventional and conventional wells. As a first-guess emission rate for natural gas activity, a leakage rate equal to 2% of the natural gas production was emitted at the locations of unconventional wells across PA. These emission rates were coupled to the Weather Research and Forecasting model with the chemistry module (WRF-Chem) and atmospheric CH4 concentration fields at 1km resolution were generated. Projected atmospheric enhancements from WRF-Chem were compared to observations, and the emission rate from unconventional wells was adjusted to minimize errors between observations and simulation. We show that the modeled CH4 plume structures match observed plumes downwind of unconventional wells, providing confidence in the methodology. In all cases, the fugitive emission rate was found to be lower than our first guess. In this initial emission configuration, each well has been assigned the same fugitive emission rate, which can potentially impair our ability to match the observed spatial variability

Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging Data to Constrain a Positron Emission Tomography Kinetic Model: Theory and Simulations

Directory of Open Access Journals (Sweden)

Jacob U. Fluckiger

2013-01-01

Full Text Available We show how dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI data can constrain a compartmental model for analyzing dynamic positron emission tomography (PET data. We first develop the theory that enables the use of DCE-MRI data to separate whole tissue time activity curves (TACs available from dynamic PET data into individual TACs associated with the blood space, the extravascular-extracellular space (EES, and the extravascular-intracellular space (EIS. Then we simulate whole tissue TACs over a range of physiologically relevant kinetic parameter values and show that using appropriate DCE-MRI data can separate the PET TAC into the three components with accuracy that is noise dependent. The simulations show that accurate blood, EES, and EIS TACs can be obtained as evidenced by concordance correlation coefficients >0.9 between the true and estimated TACs. Additionally, provided that the estimated DCE-MRI parameters are within 10% of their true values, the errors in the PET kinetic parameters are within approximately 20% of their true values. The parameters returned by this approach may provide new information on the transport of a tracer in a variety of dynamic PET studies.

A constrained supersymmetric left-right model

Energy Technology Data Exchange (ETDEWEB)

Hirsch, Martin [AHEP Group, Instituto de Física Corpuscular - C.S.I.C./Universitat de València, Edificio de Institutos de Paterna, Apartado 22085, E-46071 València (Spain); Krauss, Manuel E. [Bethe Center for Theoretical Physics & Physikalisches Institut der Universität Bonn, Nussallee 12, 53115 Bonn (Germany); Institut für Theoretische Physik und Astronomie, Universität Würzburg,Emil-Hilb-Weg 22, 97074 Wuerzburg (Germany); Opferkuch, Toby [Bethe Center for Theoretical Physics & Physikalisches Institut der Universität Bonn, Nussallee 12, 53115 Bonn (Germany); Porod, Werner [Institut für Theoretische Physik und Astronomie, Universität Würzburg,Emil-Hilb-Weg 22, 97074 Wuerzburg (Germany); Staub, Florian [Theory Division, CERN,1211 Geneva 23 (Switzerland)

2016-03-02

We present a supersymmetric left-right model which predicts gauge coupling unification close to the string scale and extra vector bosons at the TeV scale. The subtleties in constructing a model which is in agreement with the measured quark masses and mixing for such a low left-right breaking scale are discussed. It is shown that in the constrained version of this model radiative breaking of the gauge symmetries is possible and a SM-like Higgs is obtained. Additional CP-even scalars of a similar mass or even much lighter are possible. The expected mass hierarchies for the supersymmetric states differ clearly from those of the constrained MSSM. In particular, the lightest down-type squark, which is a mixture of the sbottom and extra vector-like states, is always lighter than the stop. We also comment on the model’s capability to explain current anomalies observed at the LHC.

Simplifiying global biogeochemistry models to evaluate methane emissions

Science.gov (United States)

Gerber, S.; Alonso-Contes, C.

2017-12-01

Process-based models are important tools to quantify wetland methane emissions, particularly also under climate change scenarios, evaluating these models is often cumbersome as they are embedded in larger land-surface models where fluctuating water table and the carbon cycle (including new readily decomposable plant material) are predicted variables. Here, we build on these large scale models but instead of modeling water table and plant productivity we provide values as boundary conditions. In contrast, aerobic and anaerobic decomposition, as well as soil column transport of oxygen and methane are predicted by the model. Because of these simplifications, the model has the potential to be more readily adaptable to the analysis of field-scale data. Here we determine the sensitivity of the model to specific setups, parameter choices, and to boundary conditions in order to determine set-up needs and inform what critical auxiliary variables need to be measured in order to better predict field-scale methane emissions from wetland soils. To that end we performed a global sensitivity analysis that also considers non-linear interactions between processes. The global sensitivity analysis revealed, not surprisingly, that water table dynamics (both mean level and amplitude of fluctuations), and the rate of the carbon cycle (i.e. net primary productivity) are critical determinants of methane emissions. The depth-scale where most of the potential decomposition occurs also affects methane emissions. Different transport mechanisms are compensating each other to some degree: If plant conduits are constrained, methane emissions by diffusive flux and ebullition compensate to some degree, however annual emissions are higher when plants help to bypass methanotrophs in temporally unsaturated upper layers. Finally, while oxygen consumption by plant roots help creating anoxic conditions it has little effect on overall methane emission. Our initial sensitivity analysis helps guiding

Modelling carbon dioxide emissions from agricultural soils in Canada.

Science.gov (United States)

Yadav, Dhananjay; Wang, Junye

2017-11-01

Agricultural soils are a leading source of atmospheric greenhouse gas (GHG) emissions and are major contributors to global climate change. Carbon dioxide (CO 2 ) makes up 20% of the total GHG emitted from agricultural soil. Therefore, an evaluation of CO 2 emissions from agricultural soil is necessary in order to make mitigation strategies for environmental efficiency and economic planning possible. However, quantification of CO 2 emissions through experimental methods is constrained due to the large time and labour requirements for analysis. Therefore, a modelling approach is needed to achieve this objective. In this paper, the DeNitrification-DeComposition (DNDC), a process-based model, was modified to predict CO 2 emissions for Canada from regional conditions. The modified DNDC model was applied at three experimental sites in the province of Saskatchewan. The results indicate that the simulations of the modified DNDC model are in good agreement with observations. The agricultural management of fertilization and irrigation were evaluated using scenario analysis. The simulated total annual CO 2 flux changed on average by ±13% and ±1% following a ±50% variance of the total amount of N applied by fertilising and the total amount of water through irrigation applications, respectively. Therefore, careful management of irrigation and applications of fertiliser can help to reduce CO 2 emissions from the agricultural sector. Copyright © 2017 Elsevier Ltd. All rights reserved.

Nongrowing season methane emissions-a significant component of annual emissions across northern ecosystems.

Science.gov (United States)

Treat, Claire C; Bloom, A Anthony; Marushchak, Maija E

2018-03-22

Wetlands are the single largest natural source of atmospheric methane (CH 4 ), a greenhouse gas, and occur extensively in the northern hemisphere. Large discrepancies remain between "bottom-up" and "top-down" estimates of northern CH 4 emissions. To explore whether these discrepancies are due to poor representation of nongrowing season CH 4 emissions, we synthesized nongrowing season and annual CH 4 flux measurements from temperate, boreal, and tundra wetlands and uplands. Median nongrowing season wetland emissions ranged from 0.9 g/m 2 in bogs to 5.2 g/m 2 in marshes and were dependent on moisture, vegetation, and permafrost. Annual wetland emissions ranged from 0.9 g m -2  year -1 in tundra bogs to 78 g m -2  year -1 in temperate marshes. Uplands varied from CH 4 sinks to CH 4 sources with a median annual flux of 0.0 ± 0.2 g m -2  year -1 . The measured fraction of annual CH 4 emissions during the nongrowing season (observed: 13% to 47%) was significantly larger than that was predicted by two process-based model ensembles, especially between 40° and 60°N (modeled: 4% to 17%). Constraining the model ensembles with the measured nongrowing fraction increased total nongrowing season and annual CH 4 emissions. Using this constraint, the modeled nongrowing season wetland CH 4 flux from >40° north was 6.1 ± 1.5 Tg/year, three times greater than the nongrowing season emissions of the unconstrained model ensemble. The annual wetland CH 4 flux was 37 ± 7 Tg/year from the data-constrained model ensemble, 25% larger than the unconstrained ensemble. Considering nongrowing season processes is critical for accurately estimating CH 4 emissions from high-latitude ecosystems, and necessary for constraining the role of wetland emissions in a warming climate. © 2018 John Wiley & Sons Ltd.

Cosmogenic photons strongly constrain UHECR source models

Directory of Open Access Journals (Sweden)

van Vliet Arjen

2017-01-01

Full Text Available With the newest version of our Monte Carlo code for ultra-high-energy cosmic ray (UHECR propagation, CRPropa 3, the flux of neutrinos and photons due to interactions of UHECRs with extragalactic background light can be predicted. Together with the recently updated data for the isotropic diffuse gamma-ray background (IGRB by Fermi LAT, it is now possible to severely constrain UHECR source models. The evolution of the UHECR sources especially plays an important role in the determination of the expected secondary photon spectrum. Pure proton UHECR models are already strongly constrained, primarily by the highest energy bins of Fermi LAT’s IGRB, as long as their number density is not strongly peaked at recent times.

CP properties of symmetry-constrained two-Higgs-doublet models

CERN Document Server

Ferreira, P M; Nachtmann, O; Silva, Joao P

2010-01-01

The two-Higgs-doublet model can be constrained by imposing Higgs-family symmetries and/or generalized CP symmetries. It is known that there are only six independent classes of such symmetry-constrained models. We study the CP properties of all cases in the bilinear formalism. An exact symmetry implies CP conservation. We show that soft breaking of the symmetry can lead to spontaneous CP violation (CPV) in three of the classes.

Terrestrial Sagnac delay constraining modified gravity models

Science.gov (United States)

Karimov, R. Kh.; Izmailov, R. N.; Potapov, A. A.; Nandi, K. K.

2018-04-01

Modified gravity theories include f(R)-gravity models that are usually constrained by the cosmological evolutionary scenario. However, it has been recently shown that they can also be constrained by the signatures of accretion disk around constant Ricci curvature Kerr-f(R0) stellar sized black holes. Our aim here is to use another experimental fact, viz., the terrestrial Sagnac delay to constrain the parameters of specific f(R)-gravity prescriptions. We shall assume that a Kerr-f(R0) solution asymptotically describes Earth's weak gravity near its surface. In this spacetime, we shall study oppositely directed light beams from source/observer moving on non-geodesic and geodesic circular trajectories and calculate the time gap, when the beams re-unite. We obtain the exact time gap called Sagnac delay in both cases and expand it to show how the flat space value is corrected by the Ricci curvature, the mass and the spin of the gravitating source. Under the assumption that the magnitude of corrections are of the order of residual uncertainties in the delay measurement, we derive the allowed intervals for Ricci curvature. We conclude that the terrestrial Sagnac delay can be used to constrain the parameters of specific f(R) prescriptions. Despite using the weak field gravity near Earth's surface, it turns out that the model parameter ranges still remain the same as those obtained from the strong field accretion disk phenomenon.

Constraining new physics models with isotope shift spectroscopy

Science.gov (United States)

Frugiuele, Claudia; Fuchs, Elina; Perez, Gilad; Schlaffer, Matthias

2017-07-01

Isotope shifts of transition frequencies in atoms constrain generic long- and intermediate-range interactions. We focus on new physics scenarios that can be most strongly constrained by King linearity violation such as models with B -L vector bosons, the Higgs portal, and chameleon models. With the anticipated precision, King linearity violation has the potential to set the strongest laboratory bounds on these models in some regions of parameter space. Furthermore, we show that this method can probe the couplings relevant for the protophobic interpretation of the recently reported Be anomaly. We extend the formalism to include an arbitrary number of transitions and isotope pairs and fit the new physics coupling to the currently available isotope shift measurements.

Marine N2O Emissions From Nitrification and Denitrification Constrained by Modern Observations and Projected in Multimillennial Global Warming Simulations

Science.gov (United States)

Battaglia, G.; Joos, F.

2018-01-01

Nitrous oxide (N2O) is a potent greenhouse gas (GHG) and ozone destructing agent; yet global estimates of N2O emissions are uncertain. Marine N2O stems from nitrification and denitrification processes which depend on organic matter cycling and dissolved oxygen (O2). We introduce N2O as an obligate intermediate product of denitrification and as an O2-dependent by-product from nitrification in the Bern3D ocean model. A large model ensemble is used to probabilistically constrain modern and to project marine N2O production for a low (Representative Concentration Pathway (RCP)2.6) and high GHG (RCP8.5) scenario extended to A.D. 10,000. Water column N2O and surface ocean partial pressure N2O data serve as constraints in this Bayesian framework. The constrained median for modern N2O production is 4.5 (±1σ range: 3.0 to 6.1) Tg N yr-1, where 4.5% stems from denitrification. Modeled denitrification is 65.1 (40.9 to 91.6) Tg N yr-1, well within current estimates. For high GHG forcing, N2O production decreases by 7.7% over this century due to decreasing organic matter export and remineralization. Thereafter, production increases slowly by 21% due to widespread deoxygenation and high remineralization. Deoxygenation peaks in two millennia, and the global O2 inventory is reduced by a factor of 2 compared to today. Net denitrification is responsible for 7.8% of the long-term increase in N2O production. On millennial timescales, marine N2O emissions constitute a small, positive feedback to climate change. Our simulations reveal tight coupling between the marine carbon cycle, O2, N2O, and climate.

CONSTRAINING RADIO EMISSION FROM MAGNETARS

Energy Technology Data Exchange (ETDEWEB)

Lazarus, P.; Kaspi, V. M.; Dib, R. [Department of Physics, Rutherford Physics Building, McGill University, 3600 University Street, Montreal, Quebec H3A 2T8 (Canada); Champion, D. J. [Max-Planck-Institut fuer Radioastronomie, Auf dem Huegel 69, 53121 Bonn (Germany); Hessels, J. W. T., E-mail: plazar@physics.mcgill.ca [Netherlands Institute for Radio Astronomy (ASTRON), Postbus 2, 7990 AA Dwingeloo (Netherlands)

2012-01-10

We report on radio observations of five magnetars and two magnetar candidates carried out at 1950 MHz with the Green Bank Telescope in 2006-2007. The data from these observations were searched for periodic emission and bright single pulses. Also, monitoring observations of magnetar 4U 0142+61 following its 2006 X-ray bursts were obtained. No radio emission was detected for any of our targets. The non-detections allow us to place luminosity upper limits of L{sub 1950} {approx}< 1.60 mJy kpc{sup 2} for periodic emission and L{sub 1950,single} {approx}< 7.6 Jy kpc{sup 2} for single pulse emission. These are the most stringent limits yet for the magnetars observed. The resulting luminosity upper limits together with previous results are discussed, as is the importance of further radio observations of radio-loud and radio-quiet magnetars.

Inverse modeling and mapping US air quality influences of inorganic PM2.5 precursor emissions using the adjoint of GEOS-Chem

Science.gov (United States)

Henze, D. K.; Seinfeld, J. H.; Shindell, D. T.

2009-08-01

Influences of specific sources of inorganic PM2.5 on peak and ambient aerosol concentrations in the US are evaluated using a combination of inverse modeling and sensitivity analysis. First, sulfate and nitrate aerosol measurements from the IMPROVE network are assimilated using the four-dimensional variational (4D-Var) method into the GEOS-Chem chemical transport model in order to constrain emissions estimates in four separate month-long inversions (one per season). Of the precursor emissions, these observations primarily constrain ammonia (NH3). While the net result is a decrease in estimated US~NH3 emissions relative to the original inventory, there is considerable variability in adjustments made to NH3 emissions in different locations, seasons and source sectors, such as focused decreases in the midwest during July, broad decreases throughout the US~in January, increases in eastern coastal areas in April, and an effective redistribution of emissions from natural to anthropogenic sources. Implementing these constrained emissions, the adjoint model is applied to quantify the influences of emissions on representative PM2.5 air quality metrics within the US. The resulting sensitivity maps display a wide range of spatial, sectoral and seasonal variability in the susceptibility of the air quality metrics to absolute emissions changes and the effectiveness of incremental emissions controls of specific source sectors. NH3 emissions near sources of sulfur oxides (SOx) are estimated to most influence peak inorganic PM2.5 levels in the East; thus, the most effective controls of NH3 emissions are often disjoint from locations of peak NH3 emissions. Controls of emissions from industrial sectors of SOx and NOx are estimated to be more effective than surface emissions, and changes to NH3 emissions in regions dominated by natural sources are disproportionately more effective than regions dominated by anthropogenic sources. NOx controls are most effective in northern states in

Global terrestrial isoprene emission models: sensitivity to variability in climate and vegetation

Directory of Open Access Journals (Sweden)

A. Arneth

2011-08-01

Full Text Available Due to its effects on the atmospheric lifetime of methane, the burdens of tropospheric ozone and growth of secondary organic aerosol, isoprene is central among the biogenic compounds that need to be taken into account for assessment of anthropogenic air pollution-climate change interactions. Lack of process-understanding regarding leaf isoprene production as well as of suitable observations to constrain and evaluate regional or global simulation results add large uncertainties to past, present and future emissions estimates. Focusing on contemporary climate conditions, we compare three global isoprene models that differ in their representation of vegetation and isoprene emission algorithm. We specifically aim to investigate the between- and within model variation that is introduced by varying some of the models' main features, and to determine which spatial and/or temporal features are robust between models and different experimental set-ups. In their individual standard configurations, the models broadly agree with respect to the chief isoprene sources and emission seasonality, with maximum monthly emission rates around 20–25 Tg C, when averaged by 30-degree latitudinal bands. They also indicate relatively small (approximately 5 to 10 % around the mean interannual variability of total global emissions. The models are sensitive to changes in one or more of their main model components and drivers (e.g., underlying vegetation fields, climate input which can yield increases or decreases in total annual emissions of cumulatively by more than 30 %. Varying drivers also strongly alters the seasonal emission pattern. The variable response needs to be interpreted in view of the vegetation emission capacities, as well as diverging absolute and regional distribution of light, radiation and temperature, but the direction of the simulated emission changes was not as uniform as anticipated. Our results highlight the need for modellers to evaluate their

Constraining star formation through redshifted CO and CII emission in archival CMB data

Science.gov (United States)

Switzer, Eric

cross-power with galaxy surveys directly constrains the redshifted line emission. Residual foregrounds and interlopers increase errors but do not add bias. There are 300 resolution elements of the 7 degree FIRAS top-hat inside the BOSS quasar survey, spanning 66 spectral pixels to z 2. While FIRAS noise per voxel is 200 times brighter than the expected peak cosmological CII emission, strt-N averaging of spatial and spectral modes above results in a gain of 140. Intensity mapping is in its infancy, with predictions for surface brightness of line emission ranging over an order of magnitude, and limited knowledge of the intensity-weighted bias. Even if only upper bounds are possible, they complement existing measurements of individual galaxies, which can constitute a lower bound because they measure only a portion of the luminosity function. FIRAS and Planck provide unique opportunities to pursue CII and CO intensity mapping with well-characterized instruments that overlap with galaxy surveys in angular coverage and redshift. We will re-analyze the FIRAS data to optimize sensitivity and robustness, developing a spectral line response model, splitting the data into sub-missions to isolate noise properties, and re- evaluating data cuts. The tools and results here will support future survey concepts with significantly lower noise, such as PIXIE, PRISM, SPHEREX and proposed suborbital experiments designed specifically for intensity mapping. There is a growing appreciation that many phenomena could lie just below the published FIRAS bounds. The proposed work is an early step toward this new science.

Toward Cognitively Constrained Models of Language Processing: A Review

Directory of Open Access Journals (Sweden)

Margreet Vogelzang

2017-09-01

Full Text Available Language processing is not an isolated capacity, but is embedded in other aspects of our cognition. However, it is still largely unexplored to what extent and how language processing interacts with general cognitive resources. This question can be investigated with cognitively constrained computational models, which simulate the cognitive processes involved in language processing. The theoretical claims implemented in cognitive models interact with general architectural constraints such as memory limitations. This way, it generates new predictions that can be tested in experiments, thus generating new data that can give rise to new theoretical insights. This theory-model-experiment cycle is a promising method for investigating aspects of language processing that are difficult to investigate with more traditional experimental techniques. This review specifically examines the language processing models of Lewis and Vasishth (2005, Reitter et al. (2011, and Van Rij et al. (2010, all implemented in the cognitive architecture Adaptive Control of Thought—Rational (Anderson et al., 2004. These models are all limited by the assumptions about cognitive capacities provided by the cognitive architecture, but use different linguistic approaches. Because of this, their comparison provides insight into the extent to which assumptions about general cognitive resources influence concretely implemented models of linguistic competence. For example, the sheer speed and accuracy of human language processing is a current challenge in the field of cognitive modeling, as it does not seem to adhere to the same memory and processing capacities that have been found in other cognitive processes. Architecture-based cognitive models of language processing may be able to make explicit which language-specific resources are needed to acquire and process natural language. The review sheds light on cognitively constrained models of language processing from two angles: we

Multiplatform inversion of the 2013 Rim Fire smoke emissions using regional-scale modeling: important nocturnal fire activity, air quality, and climate impacts

Science.gov (United States)

Saide, P. E.; Peterson, D. A.; da Silva, A. M., Jr.; Ziemba, L. D.; Anderson, B.; Diskin, G. S.; Sachse, G. W.; Hair, J. W.; Butler, C. F.; Fenn, M. A.; Jimenez, J. L.; Campuzano Jost, P.; Dibb, J. E.; Yokelson, R. J.; Toon, B.; Carmichael, G. R.

2014-12-01

Large wildfire events are increasingly recognized for their adverse effects on air quality and visibility, thus providing motivation for improving smoke emission estimates. The Rim Fire, one of the largest events in California's history, produced a large smoke plume that was sampled by the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) DC-8 aircraft with a full suite of in-situ and remote sensing measurements on 26-27 August 2013. We developed an inversion methodology which uses the WRF-Chem modeling system to constrain hourly fire emissions, using as initial estimates the NASA Quick Fire Emissions Dataset (QFED). This method differs from the commonly performed top-down estimates that constrain daily (or longer time scale) emissions. The inversion method is able to simultaneously improve the model fit to various SEAC4RS airborne measurements (e.g., organic aerosol, carbon monoxide (CO), aerosol extinction), ground based measurements (e.g., AERONET aerosol optical depth (AOD), CO), and satellite data (MODIS AOD) by modifying fire emissions and utilizing the information content of all these measurements. Preliminary results show that constrained emissions for a 6 day period following the largest fire growth are a factor 2-4 higher than the initial top-down estimates. Moreover, there is a tendency to increase nocturnal emissions by factors sometimes larger than 20, indicating that vigorous fire activity continued during the night. This deviation from a typical diurnal cycle is confirmed using geostationary satellite data. The constrained emissions also have a larger day-to-day variability than the initial emissions and correlate better to daily area burned estimates as observed by airborne infrared measurements (NIROPS). Experiments with the assimilation system show that performing the inversion using only satellite AOD data produces much smaller correction factors than when using all available data

High estimates of supply constrained emissions scenarios for long-term climate risk assessment

International Nuclear Information System (INIS)

Ward, James D.; Mohr, Steve H.; Myers, Baden R.; Nel, Willem P.

2012-01-01

The simulated effects of anthropogenic global warming have become important in many fields and most models agree that significant impacts are becoming unavoidable in the face of slow action. Improvements to model accuracy rely primarily on the refinement of parameter sensitivities and on plausible future carbon emissions trajectories. Carbon emissions are the leading cause of global warming, yet current considerations of future emissions do not consider structural limits to fossil fuel supply, invoking a wide range of uncertainty. Moreover, outdated assumptions regarding the future abundance of fossil energy could contribute to misleading projections of both economic growth and climate change vulnerability. Here we present an easily replicable mathematical model that considers fundamental supply-side constraints and demonstrate its use in a stochastic analysis to produce a theoretical upper limit to future emissions. The results show a significant reduction in prior uncertainty around projected long term emissions, and even assuming high estimates of all fossil fuel resources and high growth of unconventional production, cumulative emissions tend to align to the current medium emissions scenarios in the second half of this century. This significant finding provides much-needed guidance on developing relevant emissions scenarios for long term climate change impact studies. - Highlights: ► GHG emissions from conventional and unconventional fossil fuels modelled nationally. ► Assuming worst-case: large resource, high growth, rapid uptake of unconventional. ► Long-term cumulative emissions align well with the SRES medium emissions scenario. ► High emissions are unlikely to be sustained through the second half of this century. ► Model designed to be easily extended to test other scenarios e.g. energy shortages.

Constraining supergravity models from gluino production

International Nuclear Information System (INIS)

Barbieri, R.; Gamberini, G.; Giudice, G.F.; Ridolfi, G.

1988-01-01

The branching ratios for gluino decays g tilde → qanti qΧ, g tilde → gΧ into a stable undetected neutralino are computed as functions of the relevant parameters of the underlying supergravity theory. A simple way of constraining supergravity models from gluino production emerges. The effectiveness of hadronic versus e + e - colliders in the search for supersymmetry can be directly compared. (orig.)

A model for optimal constrained adaptive testing

NARCIS (Netherlands)

van der Linden, Willem J.; Reese, Lynda M.

2001-01-01

A model for constrained computerized adaptive testing is proposed in which the information on the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum

A model for optimal constrained adaptive testing

NARCIS (Netherlands)

van der Linden, Willem J.; Reese, Lynda M.

1997-01-01

A model for constrained computerized adaptive testing is proposed in which the information in the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum

Models of Flux Tubes from Constrained Relaxation

Indian Academy of Sciences (India)

tribpo

J. Astrophys. Astr. (2000) 21, 299 302. Models of Flux Tubes from Constrained Relaxation. Α. Mangalam* & V. Krishan†, Indian Institute of Astrophysics, Koramangala,. Bangalore 560 034, India. *e mail: mangalam @ iiap. ernet. in. † e mail: vinod@iiap.ernet.in. Abstract. We study the relaxation of a compressible plasma to ...

ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.

Directory of Open Access Journals (Sweden)

Jan Hasenauer

2014-07-01

Full Text Available Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.

ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.

Science.gov (United States)

Hasenauer, Jan; Hasenauer, Christine; Hucho, Tim; Theis, Fabian J

2014-07-01

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.

A Local Search Modeling for Constrained Optimum Paths Problems (Extended Abstract

Directory of Open Access Journals (Sweden)

Quang Dung Pham

2009-10-01

Full Text Available Constrained Optimum Path (COP problems appear in many real-life applications, especially on communication networks. Some of these problems have been considered and solved by specific techniques which are usually difficult to extend. In this paper, we introduce a novel local search modeling for solving some COPs by local search. The modeling features the compositionality, modularity, reuse and strengthens the benefits of Constrained-Based Local Search. We also apply the modeling to the edge-disjoint paths problem (EDP. We show that side constraints can easily be added in the model. Computational results show the significance of the approach.

On meeting capital requirements with a chance-constrained optimization model.

Science.gov (United States)

Atta Mills, Ebenezer Fiifi Emire; Yu, Bo; Gu, Lanlan

2016-01-01

This paper deals with a capital to risk asset ratio chance-constrained optimization model in the presence of loans, treasury bill, fixed assets and non-interest earning assets. To model the dynamics of loans, we introduce a modified CreditMetrics approach. This leads to development of a deterministic convex counterpart of capital to risk asset ratio chance constraint. We pursue the scope of analyzing our model under the worst-case scenario i.e. loan default. The theoretical model is analyzed by applying numerical procedures, in order to administer valuable insights from a financial outlook. Our results suggest that, our capital to risk asset ratio chance-constrained optimization model guarantees banks of meeting capital requirements of Basel III with a likelihood of 95 % irrespective of changes in future market value of assets.

CONSTRAINING A MODEL OF TURBULENT CORONAL HEATING FOR AU MICROSCOPII WITH X-RAY, RADIO, AND MILLIMETER OBSERVATIONS

International Nuclear Information System (INIS)

Cranmer, Steven R.; Wilner, David J.; MacGregor, Meredith A.

2013-01-01

Many low-mass pre-main-sequence stars exhibit strong magnetic activity and coronal X-ray emission. Even after the primordial accretion disk has been cleared out, the star's high-energy radiation continues to affect the formation and evolution of dust, planetesimals, and large planets. Young stars with debris disks are thus ideal environments for studying the earliest stages of non-accretion-driven coronae. In this paper we simulate the corona of AU Mic, a nearby active M dwarf with an edge-on debris disk. We apply a self-consistent model of coronal loop heating that was derived from numerical simulations of solar field-line tangling and magnetohydrodynamic turbulence. We also synthesize the modeled star's X-ray luminosity and thermal radio/millimeter continuum emission. A realistic set of parameter choices for AU Mic produces simulated observations that agree with all existing measurements and upper limits. This coronal model thus represents an alternative explanation for a recently discovered ALMA central emission peak that was suggested to be the result of an inner 'asteroid belt' within 3 AU of the star. However, it is also possible that the central 1.3 mm peak is caused by a combination of active coronal emission and a bright inner source of dusty debris. Additional observations of this source's spatial extent and spectral energy distribution at millimeter and radio wavelengths will better constrain the relative contributions of the proposed mechanisms

Mapping pan-Arctic CH4 emissions using an adjoint method by integrating process-based wetland and lake biogeochemical models and atmospheric CH4 concentrations

Science.gov (United States)

Tan, Z.; Zhuang, Q.; Henze, D. K.; Frankenberg, C.; Dlugokencky, E. J.; Sweeney, C.; Turner, A. J.

2015-12-01

Understanding CH4 emissions from wetlands and lakes are critical for the estimation of Arctic carbon balance under fast warming climatic conditions. To date, our knowledge about these two CH4 sources is almost solely built on the upscaling of discontinuous measurements in limited areas to the whole region. Many studies indicated that, the controls of CH4 emissions from wetlands and lakes including soil moisture, lake morphology and substrate content and quality are notoriously heterogeneous, thus the accuracy of those simple estimates could be questionable. Here we apply a high spatial resolution atmospheric inverse model (nested-grid GEOS-Chem Adjoint) over the Arctic by integrating SCIAMACHY and NOAA/ESRL CH4 measurements to constrain the CH4 emissions estimated with process-based wetland and lake biogeochemical models. Our modeling experiments using different wetland CH4 emission schemes and satellite and surface measurements show that the total amount of CH4 emitted from the Arctic wetlands is well constrained, but the spatial distribution of CH4 emissions is sensitive to priors. For CH4 emissions from lakes, our high-resolution inversion shows that the models overestimate CH4 emissions in Alaskan costal lowlands and East Siberian lowlands. Our study also indicates that the precision and coverage of measurements need to be improved to achieve more accurate high-resolution estimates.

Modeling and analysis of rotating plates by using self sensing active constrained layer damping

Energy Technology Data Exchange (ETDEWEB)

Xie, Zheng Chao; Wong, Pak Kin; Chong, Ian Ian [Univ. of Macau, Macau (China)

2012-10-15

This paper proposes a new finite element model for active constrained layer damped (CLD) rotating plate with self sensing technique. Constrained layer damping can effectively reduce the vibration in rotating structures. Unfortunately, most existing research models the rotating structures as beams that are not the case many times. It is meaningful to model the rotating part as plates because of improvements on both the accuracy and the versatility. At the same time, existing research shows that the active constrained layer damping provides a more effective vibration control approach than the passive constrained layer damping. Thus, in this work, a single layer finite element is adopted to model a three layer active constrained layer damped rotating plate. Unlike previous ones, this finite element model treats all three layers as having the both shear and extension strains, so all types of damping are taken into account. Also, the constraining layer is made of piezoelectric material to work as both the self sensing sensor and actuator. Then, a proportional control strategy is implemented to effectively control the displacement of the tip end of the rotating plate. Additionally, a parametric study is conducted to explore the impact of some design parameters on structure's modal characteristics.

Modeling and analysis of rotating plates by using self sensing active constrained layer damping

International Nuclear Information System (INIS)

Xie, Zheng Chao; Wong, Pak Kin; Chong, Ian Ian

2012-01-01

This paper proposes a new finite element model for active constrained layer damped (CLD) rotating plate with self sensing technique. Constrained layer damping can effectively reduce the vibration in rotating structures. Unfortunately, most existing research models the rotating structures as beams that are not the case many times. It is meaningful to model the rotating part as plates because of improvements on both the accuracy and the versatility. At the same time, existing research shows that the active constrained layer damping provides a more effective vibration control approach than the passive constrained layer damping. Thus, in this work, a single layer finite element is adopted to model a three layer active constrained layer damped rotating plate. Unlike previous ones, this finite element model treats all three layers as having the both shear and extension strains, so all types of damping are taken into account. Also, the constraining layer is made of piezoelectric material to work as both the self sensing sensor and actuator. Then, a proportional control strategy is implemented to effectively control the displacement of the tip end of the rotating plate. Additionally, a parametric study is conducted to explore the impact of some design parameters on structure's modal characteristics

Fuzzy chance constrained linear programming model for scrap charge optimization in steel production

DEFF Research Database (Denmark)

Rong, Aiying; Lahdelma, Risto

2008-01-01

the uncertainty based on fuzzy set theory and constrain the failure risk based on a possibility measure. Consequently, the scrap charge optimization problem is modeled as a fuzzy chance constrained linear programming problem. Since the constraints of the model mainly address the specification of the product...

Simulations of atmospheric methane for Cape Grim, Tasmania, to constrain southeastern Australian methane emissions

Directory of Open Access Journals (Sweden)

Z. M. Loh

2015-01-01

Full Text Available This study uses two climate models and six scenarios of prescribed methane emissions to compare modelled and observed atmospheric methane between 1994 and 2007, for Cape Grim, Australia (40.7° S, 144.7° E. The model simulations follow the TransCom-CH4 protocol and use the Australian Community Climate and Earth System Simulator (ACCESS and the CSIRO Conformal-Cubic Atmospheric Model (CCAM. Radon is also simulated and used to reduce the impact of transport differences between the models and observations. Comparisons are made for air samples that have traversed the Australian continent. All six emission scenarios give modelled concentrations that are broadly consistent with those observed. There are three notable mismatches, however. Firstly, scenarios that incorporate interannually varying biomass burning emissions produce anomalously high methane concentrations at Cape Grim at times of large fire events in southeastern Australia, most likely due to the fire methane emissions being unrealistically input into the lowest model level. Secondly, scenarios with wetland methane emissions in the austral winter overestimate methane concentrations at Cape Grim during wintertime while scenarios without winter wetland emissions perform better. Finally, all scenarios fail to represent a~methane source in austral spring implied by the observations. It is possible that the timing of wetland emissions in the scenarios is incorrect with recent satellite measurements suggesting an austral spring (September–October–November, rather than winter, maximum for wetland emissions.

A multiwavelength study of Swift GRB 060111B constraining the origin of its prompt optical emission

Science.gov (United States)

Stratta, G.; Pozanenko, A.; Atteia, J.-L.; Klotz, A.; Basa, S.; Gendre, B.; Verrecchia, F.; Boër, M.; Cutini, S.; Henze, M.; Holland, S.; Ibrahimov, M.; Ienna, F.; Khamitov, I.; Klose, S.; Rumyantsev, V.; Biryukov, V.; Sharapov, D.; Vachier, F.; Arnouts, S.; Perley, D. A.

2009-09-01

Context: The detection of bright optical emission measured with good temporal resolution during the prompt phase of GRB 060111Bmakes this GRB a rare event that is especially useful for constraining theories of the prompt emission. Aims: For this reason an extended multi-wavelength campaign was performed to further constrain the physical interpretation of the observations. Methods: In this work, we present the results obtained from our multi-wavelength campaign, as well as from the public Swift/BAT, XRT, and UVOT data. Results: We identified the host galaxy at R˜25 mag from deep R-band exposures taken 5 months after the trigger. Its featureless spectrum and brightness, as well as the non-detection of any associated supernova 16 days after the trigger, enabled us to constrain the distance scale of GRB 060111B11 within 0.4≤ z ≤3 in the most conservative case. The host galaxy spectral continuum is best fit with a redshift of z˜2, and other independent estimates converge to z˜1-2. From the analysis of the early afterglow SED, we find that non-negligible host galaxy dust extinction, in addition to the Galactic one, affects the observed flux in the optical regime. The extinction-corrected optical-to-gamma-ray SED during the prompt emission shows a flux density ratio Fγ/F_opt=10-2-10-4 with spectral index βγ,opt > βγ, strongly suggesting a separate origin of the optical and gamma-ray components. This result is supported by the lack of correlated behavior in the prompt emission light curves observed in the two energy domains. The temporal properties of the prompt optical emission observed during GRB 060111B11 and their similarities to other rapidly-observed events favor interpretation of this optical light as radiation from the reverse shock. Observations are in good agreement with theoretical expectations for a thick shell limit in slow cooling regime. The expected peak flux is consistent with the observed one corrected for the host extinction, likely

Modeling Spatial and Temporal Variability in Ammonia Emissions from Agricultural Fertilization

Science.gov (United States)

Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

2013-12-01

Ammonia (NH3), is an important component of the reactive nitrogen cycle and a precursor to formation of atmospheric particulate matter (PM). Predicting regional PM concentrations and deposition of nitrogen species to ecosystems requires representative emission inventories. Emission inventories have traditionally been developed using top down approaches and more recently from data assimilation based on satellite and ground based ambient concentrations and wet deposition data. The National Emission Inventory (NEI) indicates agricultural fertilization as the predominant contributor (56%) to NH3 emissions in Midwest USA, in 2002. However, due to limited understanding of the complex interactions between fertilizer usage, farm practices, soil and meteorological conditions and absence of detailed statistical data, such emission estimates are currently based on generic emission factors, time-averaged temporal factors and coarse spatial resolution. Given the significance of this source, our study focuses on developing an improved NH3 emission inventory for agricultural fertilization at finer spatial and temporal scales for air quality modeling studies. Firstly, a high-spatial resolution 4 km x 4 km NH3 emission inventory for agricultural fertilization has been developed for Illinois by modifying spatial allocation of emissions based on combining crop-specific fertilization rates with cropland distribution in the Sparse Matrix Operator Kernel Emissions model. Net emission estimates of our method are within 2% of NEI, since both methods are constrained by fertilizer sales data. However, we identified localized crop-specific NH3 emission hotspots at sub-county resolutions absent in NEI. Secondly, we have adopted the use of the DeNitrification-DeComposition (DNDC) Biogeochemistry model to simulate the physical and chemical processes that control volatilization of nitrogen as NH3 to the atmosphere after fertilizer application and resolve the variability at the hourly scale

Constraining Swiss Methane Emissions from Atmospheric Observations: Sensitivities and Temporal Development

Science.gov (United States)

Henne, Stephan; Leuenberger, Markus; Steinbacher, Martin; Eugster, Werner; Meinhardt, Frank; Bergamaschi, Peter; Emmenegger, Lukas; Brunner, Dominik

2017-04-01

Similar to other Western European countries, agricultural sources dominate the methane (CH4) emission budget in Switzerland. 'Bottom-up' estimates of these emissions are still connected with relatively large uncertainties due to considerable variability and uncertainties in observed emission factors for the underlying processes (e.g., enteric fermentation, manure management). Here, we present a regional-scale (˜300 x 200 km2) atmospheric inversion study of CH4 emissions in Switzerland making use of the recently established CarboCount-CH network of four stations on the Swiss Plateau as well as the neighbouring mountain-top sites Jungfraujoch and Schauinsland (Germany). Continuous observations from all CarboCount-CH sites are available since 2013. We use a high-resolution (7 x 7 km2) Lagrangian particle dispersion model (FLEXPART-COSMO) in connection with two different inversion systems (Bayesian and extended Kalman filter) to estimate spatially and temporally resolved CH4 emissions for the Swiss domain in the period 2013 to 2016. An extensive set of sensitivity inversions is used to assess the overall uncertainty of our inverse approach. In general we find good agreement of the total Swiss CH4 emissions between our 'top-down' estimate and the national 'bottom-up' reporting. In addition, a robust emission seasonality, with reduced winter time values, can be seen in all years. No significant trend or year-to-year variability was observed for the analysed four-year period, again in agreement with a very small downward trend in the national 'bottom-up' reporting. Special attention is given to the influence of boundary conditions as taken from different global scale model simulations (TM5, FLEXPART) and remote observations. We find that uncertainties in the boundary conditions can induce large offsets in the national total emissions. However, spatial emission patterns are less sensitive to the choice of boundary condition. Furthermore and in order to demonstrate the

Online constrained model-based reinforcement learning

CSIR Research Space (South Africa)

Van Niekerk, B

2017-08-01

Full Text Available Constrained Model-based Reinforcement Learning Benjamin van Niekerk School of Computer Science University of the Witwatersrand South Africa Andreas Damianou∗ Amazon.com Cambridge, UK Benjamin Rosman Council for Scientific and Industrial Research, and School... MULTIPLE SHOOTING Using direct multiple shooting (Bock and Plitt, 1984), problem (1) can be transformed into a structured non- linear program (NLP). First, the time horizon [t0, t0 + T ] is partitioned into N equal subintervals [tk, tk+1] for k = 0...

Modeling constrained sintering of bi-layered tubular structures

DEFF Research Database (Denmark)

Tadesse Molla, Tesfaye; Kothanda Ramachandran, Dhavanesan; Ni, De Wei

2015-01-01

Constrained sintering of tubular bi-layered structures is being used in the development of various technologies. Densification mismatch between the layers making the tubular bi-layer can generate stresses, which may create processing defects. An analytical model is presented to describe the densi...... and thermo-mechanical analysis. Results from the analytical model are found to agree well with finite element simulations as well as measurements from sintering experiment....

Application of High Resolution Air-Borne Remote Sensing Observations for Monitoring NOx Emissions

Science.gov (United States)

Souri, A.; Choi, Y.; Pan, S.; Curci, G.; Janz, S. J.; Kowalewski, M. G.; Liu, J.; Herman, J. R.; Weinheimer, A. J.

2017-12-01

Nitrogen oxides (NOx=NO+NO2) are one of the air pollutants, responsible for the formation of tropospheric ozone, acid rain and particulate nitrate. The anthropogenic NOx emissions are commonly estimated based on bottom-up inventories which are complicated by many potential sources of error. One way to improve the emission inventories is to use relevant observations to constrain them. Fortunately, Nitrogen dioxide (NO2) is one of the most successful detected species from remote sensing. Although many studies have shown the capability of using space-borne remote sensing observations for monitoring emissions, the insufficient sample number and footprint of current measurements have introduced a burden to constrain emissions at fine scales. Promisingly, there are several air-borne sensors collected for NASA's campaigns providing high spatial resolution of NO2 columns. Here, we use the well-characterized NO2 columns from the Airborne Compact Atmospheric Mapper (ACAM) onboard NASA's B200 aircraft into a 1×1 km regional model to constrain anthropogenic NOx emissions in the Houston-Galveston-Brazoria area. Firstly, in order to incorporate the data, we convert the NO2 slant column densities to vertical ones using a joint of a radiative transfer model and the 1x1 km regional model constrained by P3-B aircraft measurements. After conducting an inverse modeling method using the Kalman filter, we find the ACAM observations are resourceful at mitigating the overprediction of model in reproducing NO2 on regular days. Moreover, the ACAM provides a unique opportunity to detect an anomaly in emissions leading to strong air quality degradation that is lacking in previous works. Our study provides convincing evidence that future geostationary satellites with high spatial and temporal resolutions will give us insights into uncertainties associated with the emissions at regional scales.

Frequency Constrained ShiftCP Modeling of Neuroimaging Data

DEFF Research Database (Denmark)

Mørup, Morten; Hansen, Lars Kai; Madsen, Kristoffer H.

2011-01-01

The shift invariant multi-linear model based on the CandeComp/PARAFAC (CP) model denoted ShiftCP has proven useful for the modeling of latency changes in trial based neuroimaging data[17]. In order to facilitate component interpretation we presently extend the shiftCP model such that the extracted...... components can be constrained to pertain to predefined frequency ranges such as alpha, beta and gamma activity. To infer the number of components in the model we propose to apply automatic relevance determination by imposing priors that define the range of variation of each component of the shiftCP model...

Modeling Polarized Emission from Black Hole Jets: Application to M87 Core Jet

Directory of Open Access Journals (Sweden)

Monika Mościbrodzka

2017-09-01

Full Text Available We combine three-dimensional general-relativistic numerical models of hot, magnetized Advection Dominated Accretion Flows around a supermassive black hole and the corresponding outflows from them with a general relativistic polarized radiative transfer model to produce synthetic radio images and spectra of jet outflows. We apply the model to the underluminous core of M87 galaxy. The assumptions and results of the calculations are discussed in context of millimeter observations of the M87 jet launching zone. Our ab initio polarized emission and rotation measure models allow us to address the constrains on the mass accretion rate onto the M87 supermassive black hole.

Allowable carbon emissions for medium-to-high mitigation scenarios

Energy Technology Data Exchange (ETDEWEB)

Tachiiri, Kaoru; Hargreaves, Julia C.; Annan, James D.; Kawamiya, Michio [Research Inst. for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokohama, (Japan)], e-mail: tachiiri@jamstec.go.jp; Huntingford, Chris [Centre for Ecology and Hydrology, Wallingford (United Kingdom)

2013-11-15

Using an ensemble of simulations with an intermediate complexity climate model and in a probabilistic framework, we estimate future ranges of carbon dioxide (CO{sub 2}) emissions in order to follow three medium-high mitigation concentration pathways: RCP2.6, RCP4.5 and SCP4.5 to 2.6. Uncertainty is first estimated by allowing modelled equilibrium climate sensitivity, aerosol forcing and intrinsic physical and biogeochemical processes to vary within widely accepted ranges. Results are then constrained by comparison against contemporary measurements. For both constrained and unconstrained projections, our calculated allowable emissions are close to the standard (harmonised) emission scenarios associated with these pathways. For RCP4.5, which is the most moderate scenario considered in terms of required emission abatement, then after year 2100 very low net emissions are needed to maintain prescribed year 2100 CO{sub 2} concentrations. As expected, RCP2.6 and SCP4.5 to 2.6 require more strict emission reductions. The implication of this is that direct sequestration of carbon dioxide is likely to be required for RCP4.5 or higher mitigation scenarios, to offset any minimum emissions for society to function (the 'emissions floor'). Despite large uncertainties in the physical and biogeochemical processes, constraints from model-observational comparisons support a high degree of confidence in predicting the allowable emissions consistent with a particular concentration pathway. In contrast the uncertainty in the resulting temperature range remains large. For many parameter sets, and especially for RCP2.6, the land will turn into a carbon source within the twenty first century, but the ocean will remain as a carbon sink. For land carbon storage and our modelling framework, major reductions are seen in northern high latitudes and the Amazon basin even after atmospheric CO{sub 2} is stabilised, while for ocean carbon uptake, the tropical ocean regions will be a

Application of Recent Advances in Forward Modeling of Emissions from Boreal and Temperate Wildfires to Real-time Forecasting of Aerosol and Trace Gas Concentrations

Science.gov (United States)

Hyer, E. J.; Reid, J. S.; Kasischke, E. S.; Allen, D. J.

2005-12-01

The magnitude of trace gas and aerosol emissions from wildfires is a scientific problem with important implications for atmospheric composition, and is also integral to understanding carbon cycling in terrestrial ecosystems. Recent ecological research on modeling wildfire emissions has integrated theoretical advances derived from ecological fieldwork with improved spatial and temporal databases to produce "post facto" estimates of emissions with high spatial and temporal resolution. These advances have been shown to improve agreement with atmospheric observations at coarse scales, but can in principle be applied to applications, such as forecasting, at finer scales. However, several of the approaches employed in these forward models are incompatible with the requirements of real-time forecasting, requiring modification of data inputs and calculation methods. Because of the differences in data inputs used for real-time and "post-facto" emissions modeling, the key uncertainties in the forward problem are not necessarily the same for these two applications. However, adaptation of these advances in forward modeling to forecasting applications has the potential to improve air quality forecasts, and also to provide a large body of experimental data which can be used to constrain crucial uncertainties in current conceptual models of wildfire emissions. This talk describes a forward modeling method developed at the University of Maryland and its application to the Fire Locating and Modeling of Burning Emissions (FLAMBE) system at the Naval Research Laboratory. Methods for applying the outputs of the NRL aerosol forecasting system to the inverse problem of constraining emissions will also be discussed. The system described can use the feedback supplied by atmospheric observations to improve the emissions source description in the forecasting model, and can also be used for hypothesis testing regarding fire behavior and data inputs.

Slow logarithmic relaxation in models with hierarchically constrained dynamics

OpenAIRE

Brey, J. J.; Prados, A.

2000-01-01

A general kind of models with hierarchically constrained dynamics is shown to exhibit logarithmic anomalous relaxation, similarly to a variety of complex strongly interacting materials. The logarithmic behavior describes most of the decay of the response function.

3Es System Optimization under Uncertainty Using Hybrid Intelligent Algorithm: A Fuzzy Chance-Constrained Programming Model

Directory of Open Access Journals (Sweden)

Jiekun Song

2016-01-01

Full Text Available Harmonious development of 3Es (economy-energy-environment system is the key to realize regional sustainable development. The structure and components of 3Es system are analyzed. Based on the analysis of causality diagram, GDP and industrial structure are selected as the target parameters of economy subsystem, energy consumption intensity is selected as the target parameter of energy subsystem, and the emissions of COD, ammonia nitrogen, SO2, and NOX and CO2 emission intensity are selected as the target parameters of environment system. Fixed assets investment of three industries, total energy consumption, and investment in environmental pollution control are selected as the decision variables. By regarding the parameters of 3Es system optimization as fuzzy numbers, a fuzzy chance-constrained goal programming (FCCGP model is constructed, and a hybrid intelligent algorithm including fuzzy simulation and genetic algorithm is proposed for solving it. The results of empirical analysis on Shandong province of China show that the FCCGP model can reflect the inherent relationship and evolution law of 3Es system and provide the effective decision-making support for 3Es system optimization.

Constraining atmospheric ammonia emissions through new observations with an open-path, laser-based sensor

Science.gov (United States)

Sun, Kang

emission estimates. Finally, NH3 observations from the TES instrument on NASA Aura satellite were validated with mobile measurements and aircraft observations. Improved validations will help to constrain NH3 emissions at continental to global scales. Ultimately, these efforts will improve the understanding of NH3 emissions from all scales, with implications on the global nitrogen cycle and atmospheric chemistry-climate interactions.

Inverse modelling of national and European CH4 emissions using the atmospheric zoom model TM5

Directory of Open Access Journals (Sweden)

P. Bergamaschi

2005-01-01

Full Text Available A synthesis inversion based on the atmospheric zoom model TM5 is used to derive top-down estimates of CH4 emissions from individual European countries for the year 2001. We employ a model zoom over Europe with 1° × 1° resolution that is two-way nested into the global model domain (with resolution of 6° × 4°. This approach ensures consistent boundary conditions for the zoom domain and thus European top-down estimates consistent with global CH4 observations. The TM5 model, driven by ECMWF analyses, simulates synoptic scale events at most European and global sites fairly well, and the use of high-frequency observations allows exploiting the information content of individual synoptic events. A detailed source attribution is presented for a comprehensive set of 56 monitoring sites, assigning the atmospheric signal to the emissions of individual European countries and larger global regions. The available observational data put significant constraints on emissions from different regions. Within Europe, in particular several Western European countries are well constrained. The inversion results suggest up to 50-90% higher anthropogenic CH4 emissions in 2001 for Germany, France and UK compared to reported UNFCCC values (EEA, 2003. A recent revision of the German inventory, however, resulted in an increase of reported CH4 emissions by 68.5% (EEA, 2004, being now in very good agreement with our top-down estimate. The top-down estimate for Finland is distinctly smaller than the a priori estimate, suggesting much smaller CH4 emissions from Finnish wetlands than derived from the bottom-up inventory. The EU-15 totals are relatively close to UNFCCC values (within 4-30% and appear very robust for different inversion scenarios.

Emissions Modeling Clearinghouse

Data.gov (United States)

U.S. Environmental Protection Agency — The Emissions Modeling Clearinghouse (EMCH) supports and promotes emissions modeling activities both internal and external to the EPA. Through this site, the EPA...

Complementarity of flux- and biometric-based data to constrain parameters in a terrestrial carbon model

Directory of Open Access Journals (Sweden)

Zhenggang Du

2015-03-01

Full Text Available To improve models for accurate projections, data assimilation, an emerging statistical approach to combine models with data, have recently been developed to probe initial conditions, parameters, data content, response functions and model uncertainties. Quantifying how many information contents are contained in different data streams is essential to predict future states of ecosystems and the climate. This study uses a data assimilation approach to examine the information contents contained in flux- and biometric-based data to constrain parameters in a terrestrial carbon (C model, which includes canopy photosynthesis and vegetation–soil C transfer submodels. Three assimilation experiments were constructed with either net ecosystem exchange (NEE data only or biometric data only [including foliage and woody biomass, litterfall, soil organic C (SOC and soil respiration], or both NEE and biometric data to constrain model parameters by a probabilistic inversion application. The results showed that NEE data mainly constrained parameters associated with gross primary production (GPP and ecosystem respiration (RE but were almost invalid for C transfer coefficients, while biometric data were more effective in constraining C transfer coefficients than other parameters. NEE and biometric data constrained about 26% (6 and 30% (7 of a total of 23 parameters, respectively, but their combined application constrained about 61% (14 of all parameters. The complementarity of NEE and biometric data was obvious in constraining most of parameters. The poor constraint by only NEE or biometric data was probably attributable to either the lack of long-term C dynamic data or errors from measurements. Overall, our results suggest that flux- and biometric-based data, containing different processes in ecosystem C dynamics, have different capacities to constrain parameters related to photosynthesis and C transfer coefficients, respectively. Multiple data sources could also

First Top-Down Estimates of Anthropogenic NOx Emissions Using High-Resolution Airborne Remote Sensing Observations

Science.gov (United States)

Souri, Amir H.; Choi, Yunsoo; Pan, Shuai; Curci, Gabriele; Nowlan, Caroline R.; Janz, Scott J.; Kowalewski, Matthew G.; Liu, Junjie; Herman, Jay R.; Weinheimer, Andrew J.

2018-03-01

A number of satellite-based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high-quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NOx emissions in the Houston-Galveston-Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO2 profiles from a high-resolution regional model (1 × 1 km2) constrained by P-3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO2 absorption line, and (iii) high-resolution surface albedo constrained by ground-based spectrometers. We characterize errors in the GCAS NO2 columns by comparing them to Pandora measurements and find a striking correlation (r > 0.74) with an uncertainty of 3.5 × 1015 molecules cm-2. On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2-50% reduction in polluted areas, partly counterbalancing the well-documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top-down emissions.

Government control or low carbon lifestyle? – Analysis and application of a novel selective-constrained energy-saving and emission-reduction dynamic evolution system

International Nuclear Information System (INIS)

Fang, Guochang; Tian, Lixin; Fu, Min; Sun, Mei

2014-01-01

This paper explores a novel selective-constrained energy-saving and emission-reduction (ESER) dynamic evolution system, analyzing the impact of cost of conserved energy (CCE), government control, low carbon lifestyle and investment in new technology of ESER on energy intensity and economic growth. Based on artificial neural network, the quantitative coefficients of the actual system are identified. Taking the real situation in China for instance, an empirical study is undertaken by adjusting the parameters of the actual system. The dynamic evolution behavior of energy intensity and economic growth in reality are observed, with the results in perfect agreement with actual situation. The research shows that the introduction of CCE into ESER system will have certain restrictive effect on energy intensity in the earlier period. However, with the further development of the actual system, carbon emissions could be better controlled and energy intensity would decline. In the long run, the impacts of CCE on economic growth are positive. Government control and low carbon lifestyle play a decisive role in controlling ESER system and declining energy intensity. But the influence of government control on economic growth should be considered at the same time and the controlling effect of low carbon lifestyle on energy intensity should be strengthened gradually, while the investment in new technology of ESER can be neglected. Two different cases of ESER are proposed after a comprehensive analysis. The relations between variables and constraint conditions in the ESER system are harmonized remarkably. A better solution to carry out ESER is put forward at last, with numerical simulations being carried out to demonstrate the results. - Highlights: • Use of nonlinear dynamical method to model the selective-constrained ESER system. • Monotonic evolution curves of energy intensity and economic growth are obtained. • Detailed analysis of the game between government control and low

Evaluation of methane emissions from West Siberian wetlands based on inverse modeling

Energy Technology Data Exchange (ETDEWEB)

Kim, H-S; Inoue, G [Research Institute for Humanity and Nature, 457-4 Motoyama, Kamigamo, Kita-ku, Kyoto 603-8047 (Japan); Maksyutov, S; Machida, T [National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506 (Japan); Glagolev, M V [Lomonosov Moscow State University, GSP-1, Leninskie Gory, Moscow 119991 (Russian Federation); Patra, P K [Research Institute for Global Change/JAMSTEC, 3173-25 Showa-cho, Kanazawa-ku, Yokohama, Kanagawa 236-0001 (Japan); Sudo, K, E-mail: heonsook.kim@gmail.com [Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601 (Japan)

2011-07-15

West Siberia contains the largest extent of wetlands in the world, including large peat deposits; the wetland area is equivalent to 27% of the total area of West Siberia. This study used inverse modeling to refine emissions estimates for West Siberia using atmospheric CH{sub 4} observations and two wetland CH{sub 4} emissions inventories: (1) the global wetland emissions dataset of the NASA Goddard Institute for Space Studies (the GISS inventory), which includes emission seasons and emission rates based on climatology of monthly surface air temperature and precipitation, and (2) the West Siberian wetland emissions data (the Bc7 inventory), based on in situ flux measurements and a detailed wetland classification. The two inversions using the GISS and Bc7 inventories estimated annual mean flux from West Siberian wetlands to be 2.9 {+-} 1.7 and 3.0 {+-} 1.4 Tg yr{sup -1}, respectively, which are lower than the 6.3 Tg yr{sup -1} predicted in the GISS inventory, but similar to those of the Bc7 inventory (3.2 Tg yr{sup -1}). The well-constrained monthly fluxes and a comparison between the predicted CH{sub 4} concentrations in the two inversions suggest that the Bc7 inventory predicts the seasonal cycle of West Siberian wetland CH{sub 4} emissions more reasonably, indicating that the GISS inventory predicts more emissions from wetlands in northern and middle taiga.

Constraining the 2012-2014 growing season Alaskan methane budget using CARVE aircraft measurements

Science.gov (United States)

Hartery, S.; Chang, R. Y. W.; Commane, R.; Lindaas, J.; Miller, S. M.; Wofsy, S. C.; Karion, A.; Sweeney, C.; Miller, C. E.; Dinardo, S. J.; Steiner, N.; McDonald, K. C.; Watts, J. D.; Zona, D.; Oechel, W. C.; Kimball, J. S.; Henderson, J.; Mountain, M. E.

2015-12-01

Soil in northen latitudes contains rich carbon stores which have been historically preserved via permafrost within the soil bed; however, recent surface warming in these regions is allowing deeper soil layers to thaw, influencing the net carbon exchange from these areas. Due to the extreme nature of its climate, these eco-regions remain poorly understood by most global models. In this study we analyze methane fluxes from Alaska using in situ aircraft observations from the 2012-2014 Carbon in Arctic Reservoir Vulnerability Experiment (CARVE). These observations are coupled with an atmospheric particle transport model which quantitatively links surface emissions to atmospheric observations to make regional methane emission estimates. The results of this study are two-fold. First, the inter-annual variability of the methane emissions was found to be <1 Tg over the area of interest and is largely influenced by the length of time the deep soil remains unfrozen. Second, the resulting methane flux estimates and mean soil parameters were used to develop an empirical emissions model to help spatially and temporally constrain the methane exchange at the Alaskan soil surface. The empirical emissions model will provide a basis for exploring the sensitivity of methane emissions to subsurface soil temperature, soil moisture, organic carbon content, and other parameters commonly used in process-based models.

Dark matter scenarios in a constrained model with Dirac gauginos

CERN Document Server

Goodsell, Mark D.; Müller, Tobias; Porod, Werner; Staub, Florian

2015-01-01

We perform the first analysis of Dark Matter scenarios in a constrained model with Dirac Gauginos. The model under investigation is the Constrained Minimal Dirac Gaugino Supersymmetric Standard model (CMDGSSM) where the Majorana mass terms of gauginos vanish. However, $R$-symmetry is broken in the Higgs sector by an explicit and/or effective $B_\\mu$-term. This causes a mass splitting between Dirac states in the fermion sector and the neutralinos, which provide the dark matter candidate, become pseudo-Dirac states. We discuss two scenarios: the universal case with all scalar masses unified at the GUT scale, and the case with non-universal Higgs soft-terms. We identify different regions in the parameter space which fullfil all constraints from the dark matter abundance, the limits from SUSY and direct dark matter searches and the Higgs mass. Most of these points can be tested with the next generation of direct dark matter detection experiments.

Sensitivity of wetland methane emissions to model assumptions: application and model testing against site observations

Directory of Open Access Journals (Sweden)

L. Meng

2012-07-01

Full Text Available Methane emissions from natural wetlands and rice paddies constitute a large proportion of atmospheric methane, but the magnitude and year-to-year variation of these methane sources are still unpredictable. Here we describe and evaluate the integration of a methane biogeochemical model (CLM4Me; Riley et al., 2011 into the Community Land Model 4.0 (CLM4CN in order to better explain spatial and temporal variations in methane emissions. We test new functions for soil pH and redox potential that impact microbial methane production in soils. We also constrain aerenchyma in plants in always-inundated areas in order to better represent wetland vegetation. Satellite inundated fraction is explicitly prescribed in the model, because there are large differences between simulated fractional inundation and satellite observations, and thus we do not use CLM4-simulated hydrology to predict inundated areas. A rice paddy module is also incorporated into the model, where the fraction of land used for rice production is explicitly prescribed. The model is evaluated at the site level with vegetation cover and water table prescribed from measurements. Explicit site level evaluations of simulated methane emissions are quite different than evaluating the grid-cell averaged emissions against available measurements. Using a baseline set of parameter values, our model-estimated average global wetland emissions for the period 1993–2004 were 256 Tg CH₄ yr⁻¹ (including the soil sink and rice paddy emissions in the year 2000 were 42 Tg CH₄ yr⁻¹. Tropical wetlands contributed 201 Tg CH₄ yr⁻¹, or 78% of the global wetland flux. Northern latitude (>50 N systems contributed 12 Tg CH₄ yr⁻¹. However, sensitivity studies show a large range (150–346 Tg CH₄ yr⁻¹ in predicted global methane emissions (excluding emissions from rice paddies. The large range is

Constraining the interacting dark energy models from weak gravity conjecture and recent observations

International Nuclear Information System (INIS)

Chen Ximing; Wang Bin; Pan Nana; Gong Yungui

2011-01-01

We examine the effectiveness of the weak gravity conjecture in constraining the dark energy by comparing with observations. For general dark energy models with plausible phenomenological interactions between dark sectors, we find that although the weak gravity conjecture can constrain the dark energy, the constraint is looser than that from the observations.

Satellite-based emission constraint for nitrogen oxides: Capability and uncertainty

Science.gov (United States)

Lin, J.; McElroy, M. B.; Boersma, F.; Nielsen, C.; Zhao, Y.; Lei, Y.; Liu, Y.; Zhang, Q.; Liu, Z.; Liu, H.; Mao, J.; Zhuang, G.; Roozendael, M.; Martin, R.; Wang, P.; Spurr, R. J.; Sneep, M.; Stammes, P.; Clemer, K.; Irie, H.

2013-12-01

Vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) retrieved from satellite remote sensing have been employed widely to constrain emissions of nitrogen oxides (NOx). A major strength of satellite-based emission constraint is analysis of emission trends and variability, while a crucial limitation is errors both in satellite NO2 data and in model simulations relating NOx emissions to NO2 columns. Through a series of studies, we have explored these aspects over China. We separate anthropogenic from natural sources of NOx by exploiting their different seasonality. We infer trends of NOx emissions in recent years and effects of a variety of socioeconomic events at different spatiotemporal scales including the general economic growth, global financial crisis, Chinese New Year, and Beijing Olympics. We further investigate the impact of growing NOx emissions on particulate matter (PM) pollution in China. As part of recent developments, we identify and correct errors in both satellite NO2 retrieval and model simulation that ultimately affect NOx emission constraint. We improve the treatments of aerosol optical effects, clouds and surface reflectance in the NO2 retrieval process, using as reference ground-based MAX-DOAS measurements to evaluate the improved retrieval results. We analyze the sensitivity of simulated NO2 to errors in the model representation of major meteorological and chemical processes with a subsequent correction of model bias. Future studies will implement these improvements to re-constrain NOx emissions.

Constrained convex minimization via model-based excessive gap

OpenAIRE

Tran Dinh, Quoc; Cevher, Volkan

2014-01-01

We introduce a model-based excessive gap technique to analyze first-order primal- dual methods for constrained convex minimization. As a result, we construct new primal-dual methods with optimal convergence rates on the objective residual and the primal feasibility gap of their iterates separately. Through a dual smoothing and prox-function selection strategy, our framework subsumes the augmented Lagrangian, and alternating methods as special cases, where our rates apply.

Minimal models from W-constrained hierarchies via the Kontsevich-Miwa transform

CERN Document Server

Gato-Rivera, Beatriz

1992-01-01

A direct relation between the conformal formalism for 2d-quantum gravity and the W-constrained KP hierarchy is found, without the need to invoke intermediate matrix model technology. The Kontsevich-Miwa transform of the KP hierarchy is used to establish an identification between W constraints on the KP tau function and decoupling equations corresponding to Virasoro null vectors. The Kontsevich-Miwa transform maps the $W^{(l)}$-constrained KP hierarchy to the $(p^\\prime,p)$ minimal model, with the tau function being given by the correlator of a product of (dressed) $(l,1)$ (or $(1,l)$) operators, provided the Miwa parameter $n_i$ and the free parameter (an abstract $bc$ spin) present in the constraints are expressed through the ratio $p^\\prime/p$ and the level $l$.

Dark matter, constrained minimal supersymmetric standard model, and lattice QCD.

Science.gov (United States)

Giedt, Joel; Thomas, Anthony W; Young, Ross D

2009-11-13

Recent lattice measurements have given accurate estimates of the quark condensates in the proton. We use these results to significantly improve the dark matter predictions in benchmark models within the constrained minimal supersymmetric standard model. The predicted spin-independent cross sections are at least an order of magnitude smaller than previously suggested and our results have significant consequences for dark matter searches.

SkyFACT: high-dimensional modeling of gamma-ray emission with adaptive templates and penalized likelihoods

Energy Technology Data Exchange (ETDEWEB)

Storm, Emma; Weniger, Christoph [GRAPPA, Institute of Physics, University of Amsterdam, Science Park 904, 1090 GL Amsterdam (Netherlands); Calore, Francesca, E-mail: e.m.storm@uva.nl, E-mail: c.weniger@uva.nl, E-mail: francesca.calore@lapth.cnrs.fr [LAPTh, CNRS, 9 Chemin de Bellevue, BP-110, Annecy-le-Vieux, 74941, Annecy Cedex (France)

2017-08-01

We present SkyFACT (Sky Factorization with Adaptive Constrained Templates), a new approach for studying, modeling and decomposing diffuse gamma-ray emission. Like most previous analyses, the approach relies on predictions from cosmic-ray propagation codes like GALPROP and DRAGON. However, in contrast to previous approaches, we account for the fact that models are not perfect and allow for a very large number (∼> 10{sup 5}) of nuisance parameters to parameterize these imperfections. We combine methods of image reconstruction and adaptive spatio-spectral template regression in one coherent hybrid approach. To this end, we use penalized Poisson likelihood regression, with regularization functions that are motivated by the maximum entropy method. We introduce methods to efficiently handle the high dimensionality of the convex optimization problem as well as the associated semi-sparse covariance matrix, using the L-BFGS-B algorithm and Cholesky factorization. We test the method both on synthetic data as well as on gamma-ray emission from the inner Galaxy, |ℓ|<90{sup o} and | b |<20{sup o}, as observed by the Fermi Large Area Telescope. We finally define a simple reference model that removes most of the residual emission from the inner Galaxy, based on conventional diffuse emission components as well as components for the Fermi bubbles, the Fermi Galactic center excess, and extended sources along the Galactic disk. Variants of this reference model can serve as basis for future studies of diffuse emission in and outside the Galactic disk.

Calibrating the sqHIMMELI v1.0 wetland methane emission model with hierarchical modeling and adaptive MCMC

Science.gov (United States)

Susiluoto, Jouni; Raivonen, Maarit; Backman, Leif; Laine, Marko; Makela, Jarmo; Peltola, Olli; Vesala, Timo; Aalto, Tuula

2018-03-01

Estimating methane (CH4) emissions from natural wetlands is complex, and the estimates contain large uncertainties. The models used for the task are typically heavily parameterized and the parameter values are not well known. In this study, we perform a Bayesian model calibration for a new wetland CH4 emission model to improve the quality of the predictions and to understand the limitations of such models.The detailed process model that we analyze contains descriptions for CH4 production from anaerobic respiration, CH4 oxidation, and gas transportation by diffusion, ebullition, and the aerenchyma cells of vascular plants. The processes are controlled by several tunable parameters. We use a hierarchical statistical model to describe the parameters and obtain the posterior distributions of the parameters and uncertainties in the processes with adaptive Markov chain Monte Carlo (MCMC), importance resampling, and time series analysis techniques. For the estimation, the analysis utilizes measurement data from the Siikaneva flux measurement site in southern Finland. The uncertainties related to the parameters and the modeled processes are described quantitatively. At the process level, the flux measurement data are able to constrain the CH4 production processes, methane oxidation, and the different gas transport processes. The posterior covariance structures explain how the parameters and the processes are related. Additionally, the flux and flux component uncertainties are analyzed both at the annual and daily levels. The parameter posterior densities obtained provide information regarding importance of the different processes, which is also useful for development of wetland methane emission models other than the square root HelsinkI Model of MEthane buiLd-up and emIssion for peatlands (sqHIMMELI). The hierarchical modeling allows us to assess the effects of some of the parameters on an annual basis. The results of the calibration and the cross validation suggest that

Modeling 13.3nm Fe XXIII Flare Emissions Using the GOES-R EXIS Instrument

Science.gov (United States)

Rook, H.; Thiemann, E.

2017-12-01

The solar EUV spectrum is dominated by atomic transitions in ionized atoms in the solar atmosphere. As solar flares evolve, plasma temperatures and densities change, influencing abundances of various ions, changing intensities of different EUV wavelengths observed from the sun. Quantifying solar flare spectral irradiance is important for constraining models of Earth's atmosphere, improving communications quality, and controlling satellite navigation. However, high time cadence measurements of flare irradiance across the entire EUV spectrum were not available prior to the launch of SDO. The EVE MEGS-A instrument aboard SDO collected 0.1nm EUV spectrum data from 2010 until 2014, when the instrument failed. No current or future instrument is capable of similar high resolution and time cadence EUV observation. This necessitates a full EUV spectrum model to study EUV phenomena at Earth. It has been recently demonstrated that one hot flare EUV line, such as the 13.3nm Fe XXIII line, can be used to model cooler flare EUV line emissions, filling the role of MEGS-A. Since unblended measurements of Fe XXIII are typically unavailable, a proxy for the Fe XXIII line must be found. In this study, we construct two models of this line, first using the GOES 0.1-0.8nm soft x-ray (SXR) channel as the Fe XXIII proxy, and second using a physics-based model dependent on GOES emission measure and temperature data. We determine that the more sophisticated physics-based model shows better agreement with Fe XXIII measurements, although the simple proxy model also performs well. We also conclude that the high correlation between Fe XXIII emissions and the GOES 0.1-0.8nm band is because both emissions tend to peak near the GOES emission measure peak despite large differences in their contribution functions.

Modeling Oil Exploration and Production: Resource-Constrained and Agent-Based Approaches

International Nuclear Information System (INIS)

Jakobsson, Kristofer

2010-05-01

Energy is essential to the functioning of society, and oil is the single largest commercial energy source. Some analysts have concluded that the peak in oil production is soon about to happen on the global scale, while others disagree. Such incompatible views can persist because the issue of 'peak oil' cuts through the established scientific disciplines. The question is: what characterizes the modeling approaches that are available today, and how can they be further developed to improve a trans-disciplinary understanding of oil depletion? The objective of this thesis is to present long-term scenarios of oil production (Paper I) using a resource-constrained model; and an agent-based model of the oil exploration process (Paper II). It is also an objective to assess the strengths, limitations, and future development potentials of resource-constrained modeling, analytical economic modeling, and agent-based modeling. Resource-constrained models are only suitable when the time frame is measured in decades, but they can give a rough indication of which production scenarios are reasonable given the size of the resource. However, the models are comprehensible, transparent and the only feasible long-term forecasting tools at present. It is certainly possible to distinguish between reasonable scenarios, based on historically observed parameter values, and unreasonable scenarios with parameter values obtained through flawed analogy. The economic subfield of optimal depletion theory is founded on the notion of rational economic agents, and there is a causal relation between decisions made at the micro-level and the macro-result. In terms of future improvements, however, the analytical form considerably restricts the versatility of the approach. Agent-based modeling makes it feasible to combine economically motivated agents with a physical environment. An example relating to oil exploration is given in Paper II, where it is shown that the exploratory activities of individual

Constraining Parameters in Pulsar Models of Repeating FRB 121102 with High-energy Follow-up Observations

Energy Technology Data Exchange (ETDEWEB)

Xiao, Di; Dai, Zi-Gao, E-mail: dzg@nju.edu.cn [School of Astronomy and Space Science, Nanjing University, Nanjing 210093 (China)

2017-09-10

Recently, a precise (sub-arcsecond) localization of the repeating fast radio burst (FRB) 121102 led to the discovery of persistent radio and optical counterparts, the identification of a host dwarf galaxy at a redshift of z = 0.193, and several campaigns of searches for higher-frequency counterparts, which gave only upper limits on the emission flux. Although the origin of FRBs remains unknown, most of the existing theoretical models are associated with pulsars, or more specifically, magnetars. In this paper, we explore persistent high-energy emission from a rapidly rotating highly magnetized pulsar associated with FRB 121102 if internal gradual magnetic dissipation occurs in the pulsar wind. We find that the efficiency of converting the spin-down luminosity to the high-energy (e.g., X-ray) luminosity is generally much smaller than unity, even for a millisecond magnetar. This provides an explanation for the non-detection of high-energy counterparts to FRB 121102. We further constrain the spin period and surface magnetic field strength of the pulsar with the current high-energy observations. In addition, we compare our results with the constraints given by the other methods in previous works and expect to apply our new method to some other open issues in the future.

Constraining Parameters in Pulsar Models of Repeating FRB 121102 with High-energy Follow-up Observations

International Nuclear Information System (INIS)

Xiao, Di; Dai, Zi-Gao

2017-01-01

Recently, a precise (sub-arcsecond) localization of the repeating fast radio burst (FRB) 121102 led to the discovery of persistent radio and optical counterparts, the identification of a host dwarf galaxy at a redshift of z = 0.193, and several campaigns of searches for higher-frequency counterparts, which gave only upper limits on the emission flux. Although the origin of FRBs remains unknown, most of the existing theoretical models are associated with pulsars, or more specifically, magnetars. In this paper, we explore persistent high-energy emission from a rapidly rotating highly magnetized pulsar associated with FRB 121102 if internal gradual magnetic dissipation occurs in the pulsar wind. We find that the efficiency of converting the spin-down luminosity to the high-energy (e.g., X-ray) luminosity is generally much smaller than unity, even for a millisecond magnetar. This provides an explanation for the non-detection of high-energy counterparts to FRB 121102. We further constrain the spin period and surface magnetic field strength of the pulsar with the current high-energy observations. In addition, we compare our results with the constraints given by the other methods in previous works and expect to apply our new method to some other open issues in the future.

An analysis of energy strategies for CO2 emission reduction in China. Case studies by MARKAL model

International Nuclear Information System (INIS)

Li Guangya

1994-12-01

The China's energy system has been analyzed by using the MARKAL model in this study and the time period is from the year 1990 to 2050. The MARKAL model is applied here to evaluate the cost effective energy strategies for CO 2 emission reduction in China. Firstly the Reference Energy System (RES) of China and its database were established, and the useful energy demand was projected on the basis of China's economic target and demographic forecasting. Four scenarios, BASE1-BASE4 were defined with different assumptions of crude oil and natural uranium availability. Analytical results show that without CO 2 emission constrains coal consumption will continue to hold a dominant position in primary energy supply, and CO 2 emissions in 2050 will be 9.55 BtCO 2 and 10.28 BtCO 2 with different natural uranium availability. Under the CO 2 emission constraints, nuclear and renewable energy will play important roles in CO 2 emission reduction, and feasible maximum CO 2 emission reduction estimated by this study is 3.16 BtCO 2 in 2050. The cumulative CO 2 emission from 1990 to 2050 will be 418.25 BtCO 2 and 429.16 BtCO 2 with different natural uranium availability. Total feasible maximum CO 2 emission reduction from 1990 to 2050 is 95.97 BtCO 2 . (author)

Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?

Science.gov (United States)

Quesada-Montano, Beatriz; Westerberg, Ida K.; Fuentes-Andino, Diana; Hidalgo-Leon, Hugo; Halldin, Sven

2017-04-01

Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information - to locally observed discharge - can be used to constrain model parameter uncertainty for ungauged catchments. Climate variability exerts a strong influence on streamflow variability on long and short time scales, in particular in the Central-American region. We therefore explored the use of climate variability knowledge to constrain the simulated discharge uncertainty of a conceptual hydrological model applied to a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty we first rejected parameter relationships that disagreed with our understanding of the system. We then assessed how well climate-based constraints applied at long-term, inter-annual and intra-annual time scales could constrain model uncertainty. Finally, we compared the climate-based constraints to a constraint on low-flow statistics based on information obtained from global maps. We evaluated our method in terms of the ability of the model to reproduce the observed hydrograph and the active catchment processes in terms of two efficiency measures, a statistical consistency measure, a spread measure and 17 hydrological signatures. We found that climate variability knowledge was useful for reducing model uncertainty, in particular, unrealistic representation of deep groundwater processes. The constraints based on global maps of low-flow statistics provided more constraining information than those based on climate variability, but the latter rejected slow rainfall-runoff representations that the low flow statistics did not reject. The use of such knowledge, together with information on low-flow statistics and constraints on parameter relationships showed to be useful to

An Equilibrium Chance-Constrained Multiobjective Programming Model with Birandom Parameters and Its Application to Inventory Problem

Directory of Open Access Journals (Sweden)

Zhimiao Tao

2013-01-01

Full Text Available An equilibrium chance-constrained multiobjective programming model with birandom parameters is proposed. A type of linear model is converted into its crisp equivalent model. Then a birandom simulation technique is developed to tackle the general birandom objective functions and birandom constraints. By embedding the birandom simulation technique, a modified genetic algorithm is designed to solve the equilibrium chance-constrained multiobjective programming model. We apply the proposed model and algorithm to a real-world inventory problem and show the effectiveness of the model and the solution method.

Emission constrained secure economic dispatch

International Nuclear Information System (INIS)

Arya, L.D.; Choube, S.C.; Kothari, D.P.

1997-01-01

This paper describes a methodology for secure economic operation of power system accounting emission constraint areawise as well as in totality. Davidon-Fletcher-Powell's method of optimization has been used. Inequality constraints are accounted for by a penalty function. Sensitivity coefficients have been used to evaluate the gradient vector as well as for the calculation of incremental transmission loss (ITL). AC load flow results are required in the beginning only. The algorithm has been tested on IEEE 14- and 25-bus test systems. (Author)

Multiple Observation Types Jointly Constrain Terrestrial Carbon and Water Cycles

Science.gov (United States)

Raupach, M. R.; Haverd, V.; Briggs, P. R.; Canadell, J.; Davis, S. J.; Isaac, P. R.; Law, R.; Meyer, M.; Peters, G. P.; Pickett Heaps, C.; Roxburgh, S. H.; Sherman, B.; van Gorsel, E.; Viscarra Rossel, R.; Wang, Z.

2012-12-01

Information about the carbon cycle potentially constrains the water cycle, and vice versa. This paper explores the utility of multiple observation sets to constrain carbon and water fluxes and stores in a land surface model, and a resulting determination of the Australian terrestrial carbon budget. Observations include streamflow from 416 gauged catchments, measurements of evapotranspiration (ET) and net ecosystem production (NEP) from 12 eddy-flux sites, litterfall data, and data on carbon pools. The model is a version of CABLE (the Community Atmosphere-Biosphere-Land Exchange model), coupled with CASAcnp (a biogeochemical model) and SLI (Soil-Litter-Iso, a soil hydrology model including liquid and vapour water fluxes and the effects of litter). By projecting observation-prediction residuals onto model uncertainty, we find that eddy flux measurements provide a significantly tighter constraint on Australian continental net primary production (NPP) than the other data types. However, simultaneous constraint by multiple data types is important for mitigating bias from any single type. Results emerging from the multiply-constrained model are as follows (with all values applying over 1990-2011 and all ranges denoting ±1 standard error): (1) on the Australian continent, a predominantly semi-arid region, over half (0.64±0.05) of the water loss through ET occurs through soil evaporation and bypasses plants entirely; (2) mean Australian NPP is 2200±400 TgC/y, making the NPP/precipitation ratio about the same for Australia as the global land average; (3) annually cyclic ("grassy") vegetation and persistent ("woody") vegetation respectively account for 0.56±0.14 and 0.43±0.14 of NPP across Australia; (4) the average interannual variability of Australia's NEP (±180 TgC/y) is larger than Australia's total anthropogenic greenhouse gas emissions in 2011 (149 TgCeq/y), and is dominated by variability in desert and savannah regions. The mean carbon budget over 1990

MOVES (MOTOR VEHICLE EMISSION SIMULATOR) MODEL ...

Science.gov (United States)

A computer model, intended to eventually replace the MOBILE model and to incorporate the NONROAD model, that will provide the ability to estimate criteria and toxic air pollutant emission factors and emission inventories that are specific to the areas and time periods of interest, at scales ranging from local to national. Development of a new emission factor and inventory model for mobile source emissions. The model will be used by air pollution modelers within EPA, and at the State and local levels.

Modeling emissions for three-dimensional atmospheric chemistry transport models.

Science.gov (United States)

Matthias, Volker; Arndt, Jan A; Aulinger, Armin; Bieser, Johannes; Denier Van Der Gon, Hugo; Kranenburg, Richard; Kuenen, Jeroen; Neumann, Daniel; Pouliot, George; Quante, Markus

2018-01-24

Poor air quality is still a threat for human health in many parts of the world. In order to assess measures for emission reductions and improved air quality, three-dimensional atmospheric chemistry transport modeling systems are used in numerous research institutions and public authorities. These models need accurate emission data in appropriate spatial and temporal resolution as input. This paper reviews the most widely used emission inventories on global and regional scale and looks into the methods used to make the inventory data model ready. Shortcomings of using standard temporal profiles for each emission sector are discussed and new methods to improve the spatio-temporal distribution of the emissions are presented. These methods are often neither top-down nor bottom-up approaches but can be seen as hybrid methods that use detailed information about the emission process to derive spatially varying temporal emission profiles. These profiles are subsequently used to distribute bulk emissions like national totals on appropriate grids. The wide area of natural emissions is also summarized and the calculation methods are described. Almost all types of natural emissions depend on meteorological information, which is why they are highly variable in time and space and frequently calculated within the chemistry transport models themselves. The paper closes with an outlook for new ways to improve model ready emission data, for example by using external databases about road traffic flow or satellite data to determine actual land use or leaf area. In a world where emission patterns change rapidly, it seems appropriate to use new types of statistical and observational data to create detailed emission data sets and keep emission inventories up-to-date. Emission data is probably the most important input for chemistry transport model (CTM) systems. It needs to be provided in high temporal and spatial resolution and on a grid that is in agreement with the CTM grid. Simple

Modeling natural emissions in the Community Multiscale Air Quality (CMAQ) Model-I: building an emissions data base

Science.gov (United States)

Smith, S. N.; Mueller, S. F.

2010-05-01

A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE) emissions processing system) currently estimates non-methane volatile organic compound (NMVOC) emissions from biogenic sources, nitrogen oxide (NOx) emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, windblown dust particulate, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide), 44% of total NOx, 80% of reactive carbonaceous gases (NMVOCs and carbon monoxide), 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride), and 84% of fine particles (i.e., those smaller than 2.5 μm in size) released into the atmosphere

Isoprene emissions over Asia 1979-2012 : impact of climate and land use changes

Science.gov (United States)

Stavrakou, Trissevgeni; Müller, Jean-Francois; Bauwens, Maite; Guenther, Alex; De Smedt, Isabelle; Van Roozendael, Michel

2014-05-01

Due to the scarcity of observational contraints and the rapidly changing environment in East and Southeast Asia, isoprene emissions predicted by models are expected to bear substantial uncertainties. This study aims at improving upon current bottom-up estimates, and investigate the temporal evolution of isoprene fluxes in Asia over 1979-2012. For that, we use the MEGAN model and incorporate (i) changes in land use, including the rapid expansion of oil palms, (ii) meteorological variability, (iii) long-term changes in solar radiation constrained by surface network measurements, and (iv) recent experimental evidence that South Asian forests are much weaker isoprene emitters than previously assumed. These effects lead to a significant reduction of the total isoprene fluxes over the studied domain compared to the standard simulation. The bottom-up emissions are evaluated using satellite-based emission estimates derived from inverse modelling constrained by GOME-2/MetOp-A formaldehyde columns through 2007-2012. The top-down estimates support our assumptions and confirm the lower isoprene emission rate in tropical forests of Indonesia and Malaysia.

Venus Surface Composition Constrained by Observation and Experiment

Science.gov (United States)

Gilmore, Martha; Treiman, Allan; Helbert, Jörn; Smrekar, Suzanne

2017-11-01

New observations from the Venus Express spacecraft as well as theoretical and experimental investigation of Venus analogue materials have advanced our understanding of the petrology of Venus melts and the mineralogy of rocks on the surface. The VIRTIS instrument aboard Venus Express provided a map of the southern hemisphere of Venus at ˜1 μm allowing, for the first time, the definition of surface units in terms of their 1 μm emissivity and derived mineralogy. Tessera terrain has lower emissivity than the presumably basaltic plains, consistent with a more silica-rich or felsic mineralogy. Thermodynamic modeling and experimental production of melts with Venera and Vega starting compositions predict derivative melts that range from mafic to felsic. Large volumes of felsic melts require water and may link the formation of tesserae to the presence of a Venus ocean. Low emissivity rocks may also be produced by atmosphere-surface weathering reactions unlike those seen presently. High 1 μm emissivity values correlate to stratigraphically recent flows and have been used with theoretical and experimental predictions of basalt weathering to identify regions of recent volcanism. The timescale of this volcanism is currently constrained by the weathering of magnetite (higher emissivity) in fresh basalts to hematite (lower emissivity) in Venus' oxidizing environment. Recent volcanism is corroborated by transient thermal anomalies identified by the VMC instrument aboard Venus Express. The interpretation of all emissivity data depends critically on understanding the composition of surface materials, kinetics of rock weathering and their measurement under Venus conditions. Extended theoretical studies, continued analysis of earlier spacecraft results, new atmospheric data, and measurements of mineral stability under Venus conditions have improved our understanding atmosphere-surface interactions. The calcite-wollastonite CO2 buffer has been discounted due, among other things, to

Optimization of Fuel Consumption and Emissions for Auxiliary Power Unit Based on Multi-Objective Optimization Model

Directory of Open Access Journals (Sweden)

Yongpeng Shen

2016-02-01

Full Text Available Auxiliary power units (APUs are widely used for electric power generation in various types of electric vehicles, improvements in fuel economy and emissions of these vehicles directly depend on the operating point of the APUs. In order to balance the conflicting goals of fuel consumption and emissions reduction in the process of operating point choice, the APU operating point optimization problem is formulated as a constrained multi-objective optimization problem (CMOP firstly. The four competing objectives of this CMOP are fuel-electricity conversion cost, hydrocarbon (HC emissions, carbon monoxide (CO emissions and nitric oxide (NO x emissions. Then, the multi-objective particle swarm optimization (MOPSO algorithm and weighted metric decision making method are employed to solve the APU operating point multi-objective optimization model. Finally, bench experiments under New European driving cycle (NEDC, Federal test procedure (FTP and high way fuel economy test (HWFET driving cycles show that, compared with the results of the traditional fuel consumption single-objective optimization approach, the proposed multi-objective optimization approach shows significant improvements in emissions performance, at the expense of a slight drop in fuel efficiency.

Modeling the Anomalous Microwave Emission with Spinning Nanoparticles: No PAHs Required

Energy Technology Data Exchange (ETDEWEB)

Hensley, Brandon S. [Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109 (United States); Draine, B. T., E-mail: brandon.s.hensley@jpl.nasa.gov [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States)

2017-02-20

In light of recent observational results indicating an apparent lack of correlation between the anomalous microwave emission (AME) and mid-infrared emission from polycyclic aromatic hydrocarbons, we assess whether rotational emission from spinning silicate and/or iron nanoparticles could account for the observed AME without violating observational constraints on interstellar abundances, ultraviolet extinction, and infrared emission. By modifying the SpDust code to compute the rotational emission from these grains, we find that nanosilicate grains could account for the entirety of the observed AME, whereas iron grains could be responsible for only a fraction, even for extreme assumptions on the amount of interstellar iron concentrated in ultrasmall iron nanoparticles. Given the added complexity of contributions from multiple grain populations to the total spinning dust emission, as well as existing uncertainties due to the poorly constrained grain size, charge, and dipole moment distributions, we discuss generic, carrier-independent predictions of spinning dust theory and observational tests that could help identify the AME carrier(s).

Constraining a hybrid volatility basis-set model for aging of wood-burning emissions using smog chamber experiments: a box-model study based on the VBS scheme of the CAMx model (v5.40)

Science.gov (United States)

Ciarelli, Giancarlo; El Haddad, Imad; Bruns, Emily; Aksoyoglu, Sebnem; Möhler, Ottmar; Baltensperger, Urs; Prévôt, André S. H.

2017-06-01

In this study, novel wood combustion aging experiments performed at different temperatures (263 and 288 K) in a ˜ 7 m3 smog chamber were modelled using a hybrid volatility basis set (VBS) box model, representing the emission partitioning and their oxidation against OH. We combine aerosol-chemistry box-model simulations with unprecedented measurements of non-traditional volatile organic compounds (NTVOCs) from a high-resolution proton transfer reaction mass spectrometer (PTR-MS) and with organic aerosol measurements from an aerosol mass spectrometer (AMS). Due to this, we are able to observationally constrain the amounts of different NTVOC aerosol precursors (in the model) relative to low volatility and semi-volatile primary organic material (OMsv), which is partitioned based on current published volatility distribution data. By comparing the NTVOC / OMsv ratios at different temperatures, we determine the enthalpies of vaporization of primary biomass-burning organic aerosols. Further, the developed model allows for evaluating the evolution of oxidation products of the semi-volatile and volatile precursors with aging. More than 30 000 box-model simulations were performed to retrieve the combination of parameters that best fit the observed organic aerosol mass and O : C ratios. The parameters investigated include the NTVOC reaction rates and yields as well as enthalpies of vaporization and the O : C of secondary organic aerosol surrogates. Our results suggest an average ratio of NTVOCs to the sum of non-volatile and semi-volatile organic compounds of ˜ 4.75. The mass yields of these compounds determined for a wide range of atmospherically relevant temperatures and organic aerosol (OA) concentrations were predicted to vary between 8 and 30 % after 5 h of continuous aging. Based on the reaction scheme used, reaction rates of the NTVOC mixture range from 3.0 × 10-11 to 4. 0 × 10-11 cm3 molec-1 s-1. The average enthalpy of vaporization of secondary organic aerosol

Improved Modeling Approaches for Constrained Sintering of Bi-Layered Porous Structures

DEFF Research Database (Denmark)

Tadesse Molla, Tesfaye; Frandsen, Henrik Lund; Esposito, Vincenzo

2012-01-01

Shape instabilities during constrained sintering experiment of bi-layer porous and dense cerium gadolinium oxide (CGO) structures have been analyzed. An analytical and a numerical model based on the continuum theory of sintering has been implemented to describe the evolution of bow and densificat...

Nitrous Oxide Emissions from a Large, Impounded River: The Ohio River

Science.gov (United States)

Models suggest that microbial activity in streams and rivers is a globally significant source of anthropogenic nitrous oxide (N2O), a potent greenhouse gas and the leading cause of stratospheric ozone destruction. However, model estimates of N2O emissions are poorly constrained ...

Infrared Emission from Kilonovae: The Case of the Nearby Short Hard Burst GRB 160821B

Energy Technology Data Exchange (ETDEWEB)

Kasliwal, Mansi M.; Lau, Ryan M. [Division of Physics, Mathematics and Astronomy, California Institute of Technology, Pasadena, CA 91125 (United States); Korobkin, Oleg; Wollaeger, Ryan; Fryer, Christopher L. [Computational Methods Group (CCS-2), Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM, 87545 (United States)

2017-07-10

We present constraints on Ks-band emission from one of the nearest short hard gamma-ray bursts, GRB 160821B, at z = 0.16, at three epochs. We detect a red relativistic afterglow from the jetted emission in the first epoch but do not detect any excess kilonova emission in the second two epochs. We compare upper limits obtained with Keck I/MOSFIRE to multi-dimensional radiative transfer models of kilonovae, that employ composition-dependent nuclear heating and LTE opacities of heavy elements. We discuss eight models that combine toroidal dynamical ejecta and two types of wind and one model with dynamical ejecta only. We also discuss simple, empirical scaling laws of predicted emission as a function of ejecta mass and ejecta velocity. Our limits for GRB 160821B constrain the ejecta mass to be lower than 0.03 M {sub ⊙} for velocities greater than 0.1 c. At the distance sensitivity range of advanced LIGO, similar ground-based observations would be sufficiently sensitive to the full range of predicted model emission including models with only dynamical ejecta. The color evolution of these models shows that I – K color spans 7–16 mag, which suggests that even relatively shallow infrared searches for kilonovae could be as constraining as optical searches.

Ozone response to emission changes: a modeling study during the MCMA-2006/MILAGRO Campaign

Directory of Open Access Journals (Sweden)

J. Song

2010-04-01

Full Text Available The sensitivity of ozone production to precursor emissions was investigated under five different meteorological conditions in the Mexico City Metropolitan Area (MCMA during the MCMA-2006/MILAGRO field campaign using the gridded photochemical model CAMx driven by observation-nudged WRF meteorology. Precursor emissions were constrained by the comprehensive data from the field campaign and the routine ambient air quality monitoring network. Simulated plume mixing and transport were examined by comparing with measurements from the G-1 aircraft during the campaign. The observed concentrations of ozone precursors and ozone were reasonably well reproduced by the model. The effects of reducing precursor emissions on urban ozone production were performed for three representative emission control scenarios. A 50% reduction in VOC emissions led to 7 to 22 ppb decrease in daily maximum ozone concentrations, while a 50% reduction in NO_x emissions leads to 4 to 21 ppb increase, and 50% reductions in both NO_x and VOC emission decrease the daily maximum ozone concentrations up to 10 ppb. These results along with a chemical indicator analysis using the chemical production ratios of H₂O₂ to HNO₃ demonstrate that the MCMA urban core region is VOC-limited for all meteorological episodes, which is consistent with the results from MCMA-2003 field campaign; however the degree of the VOC-sensitivity is higher during MCMA-2006 due to lower VOCs, lower VOC reactivity and moderately higher NO_x emissions. Ozone formation in the surrounding mountain/rural area is mostly NO_x-limited, but can be VOC-limited, and the range of the NO_x-limited or VOC-limited areas depends on meteorology.

Modeling air pollutant emissions from Indian auto-rickshaws: Model development and implications for fleet emission rate estimates

Science.gov (United States)

Grieshop, Andrew P.; Boland, Daniel; Reynolds, Conor C. O.; Gouge, Brian; Apte, Joshua S.; Rogak, Steven N.; Kandlikar, Milind

2012-04-01

Chassis dynamometer tests were conducted on 40 Indian auto-rickshaws with 3 different fuel-engine combinations operating on the Indian Drive Cycle (IDC). Second-by-second (1 Hz) data were collected and used to develop velocity-acceleration look-up table models for fuel consumption and emissions of CO2, CO, total hydrocarbons (THC), oxides of nitrogen (NOx) and fine particulate matter (PM2.5) for each fuel-engine combination. Models were constructed based on group-average vehicle activity and emissions data in order to represent the performance of a 'typical' vehicle. The models accurately estimated full-cycle emissions for most species, though pollutants with more variable emission rates (e.g., PM2.5) were associated with larger errors. Vehicle emissions data showed large variability for single vehicles ('intra-vehicle variability') and within the test group ('inter-vehicle variability'), complicating the development of a single model to represent a vehicle population. To evaluate the impact of this variability, sensitivity analyses were conducted using vehicle activity data other than the IDC as model input. Inter-vehicle variability dominated the uncertainty in vehicle emission modeling. 'Leave-one-out' analyses indicated that the model outputs were relatively insensitive to the specific sample of vehicles and that the vehicle samples were likely a reasonable representation of the Delhi fleet. Intra-vehicle variability in emissions was also substantial, though had a relatively minor impact on model performance. The models were used to assess whether the IDC, used for emission factor development in India, accurately represents emissions from on-road driving. Modeling based on Global Positioning System (GPS) activity data from real-world auto-rickshaws suggests that, relative to on-road vehicles in Delhi, the IDC systematically under-estimates fuel use and emissions; real-word auto-rickshaws consume 15% more fuel and emit 49% more THC and 16% more PM2.5. The models

Emissions Models and Other Methods to Produce Emission Inventories

Science.gov (United States)

An emissions inventory is a summary or forecast of the emissions produced by a group of sources in a given time period. Inventories of air pollution from mobile sources are often produced by models such as the MOtor Vehicle Emission Simulator (MOVES).

Modeling natural emissions in the Community Multiscale Air Quality (CMAQ) model - Part 1: Building an emissions data base

Science.gov (United States)

Smith, S. N.; Mueller, S. F.

2010-01-01

A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE) emissions processing system) currently estimates volatile organic compound (VOC) emissions from biogenic sources, nitrogen oxide (NOx) emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as windblown dust and sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide), 44% of total NOx, 80% of reactive carbonaceous gases (VOCs and carbon monoxide), 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride), and 84% of fine particles (i.e., those smaller than 2.5 μm in size) released into the atmosphere. The seasonality and

Multiple Observation Types Jointly Constrain Australian Terrestrial Carbon and Water Cycles

Science.gov (United States)

Haverd, Vanessa; Raupach, Michael; Briggs, Peter; Canadell, Pep; Davis, Steven; Isaac, Peter; Law, Rachel; Meyer, Mick; Peters, Glenn; Pickett-Heaps, Christopher; Roxburgh, Stephen; Sherman, Bradford; van Gorsel, Eva; Viscarra Rossel, Raphael; Wang, Ziyuan

2013-04-01

Information about the carbon cycle potentially constrains the water cycle, and vice versa. This paper explores the utility of multiple observation sets to constrain carbon and water fluxes and stores in a land surface model, and a resulting determination of the Australian terrestrial carbon budget. Observations include streamflow from 416 gauged catchments, measurements of evapotranspiration (ET) and net ecosystem production (NEP) from 12 eddy-flux sites, litterfall data, and data on carbon pools. The model is a version of CABLE (the Community Atmosphere-Biosphere-Land Exchange model), coupled with CASAcnp (a biogeochemical model) and SLI (Soil-Litter-Iso, a soil hydrology model including liquid and vapour water fluxes and the effects of litter). By projecting observation-prediction residuals onto model uncertainty, we find that eddy flux measurements provide a significantly tighter constraint on Australian continental net primary production (NPP) than the other data types. However, simultaneous constraint by multiple data types is important for mitigating bias from any single type. Results emerging from the multiply-constrained model are as follows (with all values applying over 1990-2011 and all ranges denoting ±1 standard error): (1) on the Australian continent, a predominantly semi-arid region, over half (0.64±0.05) of the water loss through ET occurs through soil evaporation and bypasses plants entirely; (2) mean Australian NPP is 2200±400 TgC/y, making the NPP/precipitation ratio about the same for Australia as the global land average; (3) annually cyclic ("grassy") vegetation and persistent ("woody") vegetation respectively account for 0.56±0.14 and 0.43±0.14 of NPP across Australia; (4) the average interannual variability of Australia's NEP (±180 TgC/y) is larger than Australia's total anthropogenic greenhouse gas emissions in 2011 (149 TgCeq/y), and is dominated by variability in desert and savannah regions. The mean carbon budget over 1990

NORTRIP emission model user guide

Energy Technology Data Exchange (ETDEWEB)

Denby, Rolstad Bruce

2012-07-01

The NORTRIP emission model has been developed at NILU, in conjunction with other Nordic institutes, to model non-exhaust traffic induced emissions. This short summary document explains how to run the NORTRIP model from the MATLAB environment or by using the executable user interface version. It also provides brief information on input files and the model architecture.(Author)

Modelling and Vibration Control of Beams with Partially Debonded Active Constrained Layer Damping Patch

Science.gov (United States)

SUN, D.; TONG, L.

2002-05-01

A detailed model for the beams with partially debonded active constraining damping (ACLD) treatment is presented. In this model, the transverse displacement of the constraining layer is considered to be non-identical to that of the host structure. In the perfect bonding region, the viscoelastic core is modelled to carry both peel and shear stresses, while in the debonding area, it is assumed that no peel and shear stresses be transferred between the host beam and the constraining layer. The adhesive layer between the piezoelectric sensor and the host beam is also considered in this model. In active control, the positive position feedback control is employed to control the first mode of the beam. Based on this model, the incompatibility of the transverse displacements of the active constraining layer and the host beam is investigated. The passive and active damping behaviors of the ACLD patch with different thicknesses, locations and lengths are examined. Moreover, the effects of debonding of the damping layer on both passive and active control are examined via a simulation example. The results show that the incompatibility of the transverse displacements is remarkable in the regions near the ends of the ACLD patch especially for the high order vibration modes. It is found that a thinner damping layer may lead to larger shear strain and consequently results in a larger passive and active damping. In addition to the thickness of the damping layer, its length and location are also key factors to the hybrid control. The numerical results unveil that edge debonding can lead to a reduction of both passive and active damping, and the hybrid damping may be more sensitive to the debonding of the damping layer than the passive damping.

Modeling Global Biogenic Emission of Isoprene: Exploration of Model Drivers

Science.gov (United States)

Alexander, Susan E.; Potter, Christopher S.; Coughlan, Joseph C.; Klooster, Steven A.; Lerdau, Manuel T.; Chatfield, Robert B.; Peterson, David L. (Technical Monitor)

1996-01-01

Vegetation provides the major source of isoprene emission to the atmosphere. We present a modeling approach to estimate global biogenic isoprene emission. The isoprene flux model is linked to a process-based computer simulation model of biogenic trace-gas fluxes that operates on scales that link regional and global data sets and ecosystem nutrient transformations Isoprene emission estimates are determined from estimates of ecosystem specific biomass, emission factors, and algorithms based on light and temperature. Our approach differs from an existing modeling framework by including the process-based global model for terrestrial ecosystem production, satellite derived ecosystem classification, and isoprene emission measurements from a tropical deciduous forest. We explore the sensitivity of model estimates to input parameters. The resulting emission products from the global 1 degree x 1 degree coverage provided by the satellite datasets and the process model allow flux estimations across large spatial scales and enable direct linkage to atmospheric models of trace-gas transport and transformation.

HEAVY-DUTY GREENHOUSE GAS EMISSIONS MODEL ...

Science.gov (United States)

Class 2b-8 vocational truck manufacturers and Class 7/8 tractor manufacturers would be subject to vehicle-based fuel economy and emission standards that would use a truck simulation model to evaluate the impact of the truck tires and/or tractor cab design on vehicle compliance with any new standards. The EPA has created a model called “GHG Emissions Model (GEM)”, which is specifically tailored to predict truck GHG emissions. As the model is designed for the express purpose of vehicle compliance demonstration, it is less configurable than similar commercial products and its only outputs are GHG emissions and fuel consumption. This approach gives a simple and compact tool for vehicle compliance without the overhead and costs of a more sophisticated model. Evaluation of both fuel consumption and CO2 emissions from heavy-duty highway vehicles through a whole-vehicle operation simulation model.

A Few Expanding Integrable Models, Hamiltonian Structures and Constrained Flows

International Nuclear Information System (INIS)

Zhang Yufeng

2011-01-01

Two kinds of higher-dimensional Lie algebras and their loop algebras are introduced, for which a few expanding integrable models including the coupling integrable couplings of the Broer-Kaup (BK) hierarchy and the dispersive long wave (DLW) hierarchy as well as the TB hierarchy are obtained. From the reductions of the coupling integrable couplings, the corresponding coupled integrable couplings of the BK equation, the DLW equation, and the TB equation are obtained, respectively. Especially, the coupling integrable coupling of the TB equation reduces to a few integrable couplings of the well-known mKdV equation. The Hamiltonian structures of the coupling integrable couplings of the three kinds of soliton hierarchies are worked out, respectively, by employing the variational identity. Finally, we decompose the BK hierarchy of evolution equations into x-constrained flows and t n -constrained flows whose adjoint representations and the Lax pairs are given. (general)

Comparative Evaluation of Five Fire Emissions Datasets Using the GEOS-5 Model

Science.gov (United States)

Ichoku, C. M.; Pan, X.; Chin, M.; Bian, H.; Darmenov, A.; Ellison, L.; Kucsera, T. L.; da Silva, A. M., Jr.; Petrenko, M. M.; Wang, J.; Ge, C.; Wiedinmyer, C.

2017-12-01

Wildfires and other types of biomass burning affect most vegetated parts of the globe, contributing 40% of the annual global atmospheric loading of carbonaceous aerosols, as well as significant amounts of numerous trace gases, such as carbon dioxide, carbon monoxide, and methane. Many of these smoke constituents affect the air quality and/or the climate system directly or through their interactions with solar radiation and cloud properties. However, fire emissions are poorly constrained in global and regional models, resulting in high levels of uncertainty in understanding their real impacts. With the advent of satellite remote sensing of fires and burned areas in the last couple of decades, a number of fire emissions products have become available for use in relevant research and applications. In this study, we evaluated five global biomass burning emissions datasets, namely: (1) GFEDv3.1 (Global Fire Emissions Database version 3.1); (2) GFEDv4s (Global Fire Emissions Database version 4 with small fires); (3) FEERv1 (Fire Energetics and Emissions Research version 1.0); (4) QFEDv2.4 (Quick Fire Emissions Dataset version 2.4); and (5) Fire INventory from NCAR (FINN) version 1.5. Overall, the spatial patterns of biomass burning emissions from these inventories are similar, although the magnitudes of the emissions can be noticeably different. The inventories derived using top-down approaches (QFEDv2.4 and FEERv1) are larger than those based on bottom-up approaches. For example, global organic carbon (OC) emissions in 2008 are: QFEDv2.4 (51.93 Tg), FEERv1 (28.48 Tg), FINN v1.5 (19.48 Tg), GFEDv3.1 (15.65 Tg) and GFEDv4s (13.76 Tg); representing a factor of 3.7 difference between the largest and the least. We also used all five biomass-burning emissions datasets to conduct aerosol simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5), and compared the resulting aerosol optical depth (AOD) output to the corresponding retrievals from MODIS

Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations

Science.gov (United States)

Wei Li; Philippe Ciais; Shushi Peng; Chao Yue; Yilong Wang; Martin Thurner; Sassan S. Saatchi; Almut Arneth; Valerio Avitabile; Nuno Carvalhais; Anna B. Harper; Etsushi Kato; Charles Koven; Yi Y. Liu; Julia E. M. S. Nabel; Yude Pan; Julia Pongratz; Benjamin Poulter; Thomas A. M. Pugh; Maurizio Santoro; Stephen Sitch; Benjamin D. Stocker; Nicolas Viovy; Andy Wiltshire; Rasoul Yousefpour; Sönke Zaehle

2017-01-01

The use of dynamic global vegetation models (DGVMs) to estimate CO2 emissions from land-use and land-cover change (LULCC) offers a new window to account for spatial and temporal details of emissions and for ecosystem processes affected by LULCC. One drawback of LULCC emissions from DGVMs, however, is lack of observation constraint. Here, we...

X-ray Emission Line Spectroscopy of Nearby Galaxies

Science.gov (United States)

Wang, Daniel

What are the origins of the diffuse soft X-ray emission from non-AGN galaxies? Preliminary analysis of XMM-Newton RGS spectra shows that a substantial fraction of the emission cannot arise from optically-thin thermal plasma, as commonly assumed, and may originate in charge exchange at the interface with neutral gas. We request the support for a comprehensive observing, data analysis, and modeling program to spectroscopically determine the origins of the emission. First, we will use our scheduled XMM-Newton AO-10 368 ks observations of the nearest compact elliptical galaxy M32 to obtain the first spectroscopic calibration of the cumulative soft X-ray emission from the old stellar population and will develop a spectral model for the charge exchange, as well as analysis tools to measure the spatial and kinematic properties of the X-ray line- emitting plasma. Second, we will characterize the truly diffuse emission from the hot plasma and/or its interplay with the neutral gas in a sample of galactic spheroids and active star forming/starburst regions in nearby galaxies observed by XMM-Newton. In particular, we will map out the spatial distributions of key emission lines and measure (or tightly constrain) the kinematics of hot plasma outflows for a few X-ray-emitting regions with high-quality RGS data. For galaxies with insufficient counting statistics in individual emission lines, we will conduct a spectral stacking analysis to constrain the average properties of the X-ray-emitting plasma. We will use the results of these X-ray spectroscopic analyses, together with complementary X-ray CCD imaging/spectral data and observations in other wavelength bands, to test the models of the emission. In addition to the charge exchange, alternative scenarios such as resonance scattering and relic AGN photo-ionization will also be examined for suitable regions. These studies are important to the understanding of the relationship between the diffuse soft X-ray emission and various

Criticisms and defences of the balance-of-payments constrained growth model: some old, some new

Directory of Open Access Journals (Sweden)

John S.L. McCombie

2011-12-01

Full Text Available This paper assesses various critiques that have been levelled over the years against Thirlwall’s Law and the balance-of-payments constrained growth model. It starts by assessing the criticisms that the law is largely capturing an identity; that the law of one price renders the model incoherent; and that statistical testing using cross-country data rejects the hypothesis that the actual and the balance-of-payments equilibrium growth rates are the same. It goes on to consider the argument that calculations of the “constant-market-shares” income elasticities of demand for exports demonstrate that the UK (and by implication other advanced countries could not have been balance-of-payments constrained in the early postwar period. Next Krugman’s interpretation of the law (or what he terms the “45-degree rule”, which is at variance with the usual demand-oriented explanation, is examined. The paper next assesses attempts to reconcile the demand and supply side of the model and examines whether or not the balance-of-payments constrained growth model is subject to the fallacy of composition. It concludes that none of these criticisms invalidate the model, which remains a powerful explanation of why growth rates differ.

CONSTRAINING VERY HIGH MASS POPULATION III STARS THROUGH He II EMISSION IN GALAXY BDF-521 AT z = 7.01

Energy Technology Data Exchange (ETDEWEB)

Cai, Zheng; Fan, Xiaohui; Davé, Romeel; Zabludoff, Ann [Steward Observatory, University of Arizona, Tucson, AZ 85721 (United States); Jiang, Linhua [Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871 (China); Oh, S. Peng [Department of Physics, University of California, Broida Hall, Santa Barbara, CA 93106-9530 (United States); Yang, Yujin, E-mail: caiz@email.arizona.edu [Argelander-Institut fuer Astronomie, Auf dem Huegel 71, D-53121 Bonn (Germany)

2015-01-30

Numerous theoretical models have long proposed that a strong He II λ1640 emission line is the most prominent and unique feature of massive Population III (Pop III) stars in high-redshift galaxies. The He II λ1640 line strength can constrain the mass and initial mass function (IMF) of Pop III stars. We use F132N narrowband filter on the Hubble Space Telescope's (HST) Wide Field Camera 3 to look for strong He II λ1640 emission in the galaxy BDF-521 at z = 7.01, one of the most distant spectroscopically confirmed galaxies to date. Using deep F132N narrowband imaging, together with our broadband imaging with F125W and F160W filters, we do not detect He II emission from this galaxy, but place a 2σ upper limit on the flux of 5.3×10{sup −19} erg s{sup −1} cm{sup −2}. This measurement corresponds to a 2σ upper limit on the Pop III star formation rate (SFR{sub PopIII}) of ∼0.2 M {sub ☉} yr{sup –1}, assuming a Salpeter IMF with 50 ≲ M/M {sub ☉} ≲ 1000. From the high signal-to-noise broadband measurements in F125W and F160W, we fit the UV continuum for BDF-521. The spectral flux density is ∼3.6×10{sup −11}×λ{sup −2.32} erg s{sup −1} cm{sup −2} Å{sup –1}, which corresponds to an overall unobscured SFR of ∼5 M {sub ☉} yr{sup –1}. Our upper limit on SFR{sub PopIII} suggests that massive Pop III stars represent ≲ 4% of the total star formation. Further, the HST high-resolution imaging suggests that BDF-521 is an extremely compact galaxy, with a half-light radius of 0.6 kpc.

Constraining a hybrid volatility basis-set model for aging of wood-burning emissions using smog chamber experiments: a box-model study based on the VBS scheme of the CAMx model (v5.40

Directory of Open Access Journals (Sweden)

G. Ciarelli

2017-06-01

Full Text Available In this study, novel wood combustion aging experiments performed at different temperatures (263 and 288 K in a ∼ 7 m3 smog chamber were modelled using a hybrid volatility basis set (VBS box model, representing the emission partitioning and their oxidation against OH. We combine aerosol–chemistry box-model simulations with unprecedented measurements of non-traditional volatile organic compounds (NTVOCs from a high-resolution proton transfer reaction mass spectrometer (PTR-MS and with organic aerosol measurements from an aerosol mass spectrometer (AMS. Due to this, we are able to observationally constrain the amounts of different NTVOC aerosol precursors (in the model relative to low volatility and semi-volatile primary organic material (OMsv, which is partitioned based on current published volatility distribution data. By comparing the NTVOC ∕ OMsv ratios at different temperatures, we determine the enthalpies of vaporization of primary biomass-burning organic aerosols. Further, the developed model allows for evaluating the evolution of oxidation products of the semi-volatile and volatile precursors with aging. More than 30 000 box-model simulations were performed to retrieve the combination of parameters that best fit the observed organic aerosol mass and O : C ratios. The parameters investigated include the NTVOC reaction rates and yields as well as enthalpies of vaporization and the O : C of secondary organic aerosol surrogates. Our results suggest an average ratio of NTVOCs to the sum of non-volatile and semi-volatile organic compounds of ∼ 4.75. The mass yields of these compounds determined for a wide range of atmospherically relevant temperatures and organic aerosol (OA concentrations were predicted to vary between 8 and 30 % after 5 h of continuous aging. Based on the reaction scheme used, reaction rates of the NTVOC mixture range from 3.0 × 10−11 to 4. 0 × 10−11 cm3 molec−1 s−1

An Experimental Comparison of Similarity Assessment Measures for 3D Models on Constrained Surface Deformation

Science.gov (United States)

Quan, Lulin; Yang, Zhixin

2010-05-01

To address the issues in the area of design customization, this paper expressed the specification and application of the constrained surface deformation, and reported the experimental performance comparison of three prevail effective similarity assessment algorithms on constrained surface deformation domain. Constrained surface deformation becomes a promising method that supports for various downstream applications of customized design. Similarity assessment is regarded as the key technology for inspecting the success of new design via measuring the difference level between the deformed new design and the initial sample model, and indicating whether the difference level is within the limitation. According to our theoretical analysis and pre-experiments, three similarity assessment algorithms are suitable for this domain, including shape histogram based method, skeleton based method, and U system moment based method. We analyze their basic functions and implementation methodologies in detail, and do a series of experiments on various situations to test their accuracy and efficiency using precision-recall diagram. Shoe model is chosen as an industrial example for the experiments. It shows that shape histogram based method gained an optimal performance in comparison. Based on the result, we proposed a novel approach that integrating surface constrains and shape histogram description with adaptive weighting method, which emphasize the role of constrains during the assessment. The limited initial experimental result demonstrated that our algorithm outperforms other three algorithms. A clear direction for future development is also drawn at the end of the paper.

Characterizing and modeling the free recovery and constrained recovery behavior of a polyurethane shape memory polymer

International Nuclear Information System (INIS)

Volk, Brent L; Lagoudas, Dimitris C; Maitland, Duncan J

2011-01-01

In this work, tensile tests and one-dimensional constitutive modeling were performed on a high recovery force polyurethane shape memory polymer that is being considered for biomedical applications. The tensile tests investigated the free recovery (zero load) response as well as the constrained displacement recovery (stress recovery) response at extension values up to 25%, and two consecutive cycles were performed during each test. The material was observed to recover 100% of the applied deformation when heated at zero load in the second thermomechanical cycle, and a stress recovery of 1.5–4.2 MPa was observed for the constrained displacement recovery experiments. After the experiments were performed, the Chen and Lagoudas model was used to simulate and predict the experimental results. The material properties used in the constitutive model—namely the coefficients of thermal expansion, shear moduli, and frozen volume fraction—were calibrated from a single 10% extension free recovery experiment. The model was then used to predict the material response for the remaining free recovery and constrained displacement recovery experiments. The model predictions match well with the experimental data

Inexact nonlinear improved fuzzy chance-constrained programming model for irrigation water management under uncertainty

Science.gov (United States)

Zhang, Chenglong; Zhang, Fan; Guo, Shanshan; Liu, Xiao; Guo, Ping

2018-01-01

An inexact nonlinear mλ-measure fuzzy chance-constrained programming (INMFCCP) model is developed for irrigation water allocation under uncertainty. Techniques of inexact quadratic programming (IQP), mλ-measure, and fuzzy chance-constrained programming (FCCP) are integrated into a general optimization framework. The INMFCCP model can deal with not only nonlinearities in the objective function, but also uncertainties presented as discrete intervals in the objective function, variables and left-hand side constraints and fuzziness in the right-hand side constraints. Moreover, this model improves upon the conventional fuzzy chance-constrained programming by introducing a linear combination of possibility measure and necessity measure with varying preference parameters. To demonstrate its applicability, the model is then applied to a case study in the middle reaches of Heihe River Basin, northwest China. An interval regression analysis method is used to obtain interval crop water production functions in the whole growth period under uncertainty. Therefore, more flexible solutions can be generated for optimal irrigation water allocation. The variation of results can be examined by giving different confidence levels and preference parameters. Besides, it can reflect interrelationships among system benefits, preference parameters, confidence levels and the corresponding risk levels. Comparison between interval crop water production functions and deterministic ones based on the developed INMFCCP model indicates that the former is capable of reflecting more complexities and uncertainties in practical application. These results can provide more reliable scientific basis for supporting irrigation water management in arid areas.

Constraining The Abundance Of Massive Black Hole Binaries By Spectroscopic Monitoring Of Quasars With Offset Broad Emission Lines

Science.gov (United States)

Liu, Xin; Shen, Y.

2012-05-01

A fraction of quasars have long been known to show significant bulk velocity offsets (of a few hundred to thousands of km/s) in the broad permitted emission lines with respect to host galaxy systemic redshift. Various scenarios may explain these features such as massive black hole binaries or broad line region gas kinematics. As previously demonstrated by the dedicated work of Eracleous and colleagues, long-term spectroscopic monitoring provides a promising test to discriminate between alternative scenarios. Here, we present a sample of 300 shifted-line quasars homogeneously selected from the SDSS DR7. For 60 of them, we have conducted second-epoch optical spectra using MMT/BCS, ARC 3.5m/DIS, and/or FLWO 1.5m/FAST. These new observations, combined with the existing SDSS spectra, enable us to constrain the velocity drifts of these shifted broad lines with time baselines of a few years up to a decade. Previous work has been focusing on objects with extreme velocity offsets: > 1000 km/s. Our work extends to the parameter space of smaller velocity offsets, where larger velocity drifts would be expected in the binary scenario. Our results may be used to identify strong candidates for and to constrain the abundance of massive black hole binaries, which are expected in the hierarchical universe, but have so far been illusive.

Efficient non-negative constrained model-based inversion in optoacoustic tomography

International Nuclear Information System (INIS)

Ding, Lu; Luís Deán-Ben, X; Lutzweiler, Christian; Razansky, Daniel; Ntziachristos, Vasilis

2015-01-01

The inversion accuracy in optoacoustic tomography depends on a number of parameters, including the number of detectors employed, discrete sampling issues or imperfectness of the forward model. These parameters result in ambiguities on the reconstructed image. A common ambiguity is the appearance of negative values, which have no physical meaning since optical absorption can only be higher or equal than zero. We investigate herein algorithms that impose non-negative constraints in model-based optoacoustic inversion. Several state-of-the-art non-negative constrained algorithms are analyzed. Furthermore, an algorithm based on the conjugate gradient method is introduced in this work. We are particularly interested in investigating whether positive restrictions lead to accurate solutions or drive the appearance of errors and artifacts. It is shown that the computational performance of non-negative constrained inversion is higher for the introduced algorithm than for the other algorithms, while yielding equivalent results. The experimental performance of this inversion procedure is then tested in phantoms and small animals, showing an improvement in image quality and quantitativeness with respect to the unconstrained approach. The study performed validates the use of non-negative constraints for improving image accuracy compared to unconstrained methods, while maintaining computational efficiency. (paper)

A distance constrained synaptic plasticity model of C. elegans neuronal network

Science.gov (United States)

Badhwar, Rahul; Bagler, Ganesh

2017-03-01

Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

Genetic Algorithm Based Microscale Vehicle Emissions Modelling

Directory of Open Access Journals (Sweden)

Sicong Zhu

2015-01-01

Full Text Available There is a need to match emission estimations accuracy with the outputs of transport models. The overall error rate in long-term traffic forecasts resulting from strategic transport models is likely to be significant. Microsimulation models, whilst high-resolution in nature, may have similar measurement errors if they use the outputs of strategic models to obtain traffic demand predictions. At the microlevel, this paper discusses the limitations of existing emissions estimation approaches. Emission models for predicting emission pollutants other than CO2 are proposed. A genetic algorithm approach is adopted to select the predicting variables for the black box model. The approach is capable of solving combinatorial optimization problems. Overall, the emission prediction results reveal that the proposed new models outperform conventional equations in terms of accuracy and robustness.

Robust model predictive control for constrained continuous-time nonlinear systems

Science.gov (United States)

Sun, Tairen; Pan, Yongping; Zhang, Jun; Yu, Haoyong

2018-02-01

In this paper, a robust model predictive control (MPC) is designed for a class of constrained continuous-time nonlinear systems with bounded additive disturbances. The robust MPC consists of a nonlinear feedback control and a continuous-time model-based dual-mode MPC. The nonlinear feedback control guarantees the actual trajectory being contained in a tube centred at the nominal trajectory. The dual-mode MPC is designed to ensure asymptotic convergence of the nominal trajectory to zero. This paper extends current results on discrete-time model-based tube MPC and linear system model-based tube MPC to continuous-time nonlinear model-based tube MPC. The feasibility and robustness of the proposed robust MPC have been demonstrated by theoretical analysis and applications to a cart-damper springer system and a one-link robot manipulator.

Natural gas fugitive emissions rates constrained by global atmospheric methane and ethane.

Science.gov (United States)

Schwietzke, Stefan; Griffin, W Michael; Matthews, H Scott; Bruhwiler, Lori M P

2014-07-15

The amount of methane emissions released by the natural gas (NG) industry is a critical and uncertain value for various industry and policy decisions, such as for determining the climate implications of using NG over coal. Previous studies have estimated fugitive emissions rates (FER)--the fraction of produced NG (mainly methane and ethane) escaped to the atmosphere--between 1 and 9%. Most of these studies rely on few and outdated measurements, and some may represent only temporal/regional NG industry snapshots. This study estimates NG industry representative FER using global atmospheric methane and ethane measurements over three decades, and literature ranges of (i) tracer gas atmospheric lifetimes, (ii) non-NG source estimates, and (iii) fossil fuel fugitive gas hydrocarbon compositions. The modeling suggests an upper bound global average FER of 5% during 2006-2011, and a most likely FER of 2-4% since 2000, trending downward. These results do not account for highly uncertain natural hydrocarbon seepage, which could lower the FER. Further emissions reductions by the NG industry may be needed to ensure climate benefits over coal during the next few decades.

PANCHROMATIC OBSERVATIONS OF THE TEXTBOOK GRB 110205A: CONSTRAINING PHYSICAL MECHANISMS OF PROMPT EMISSION AND AFTERGLOW

Energy Technology Data Exchange (ETDEWEB)

Zheng, W. [Department of Physics, University of Michigan, 450 Church Street, Ann Arbor, MI 48109 (United States); Shen, R. F. [Department of Astronomy and Astrophysics, University of Toronto, Toronto, Ontario M5S 3H4 (Canada); Sakamoto, T. [Center for Research and Exploration in Space Science and Technology (CRESST), NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Beardmore, A. P. [Department of Physics and Astronomy, University of Leicester, Leicester LE1 7RH (United Kingdom); De Pasquale, M. [Mullard Space Science Laboratory, University College London, Holmbury Road, Holmbury St. Mary, Dorking RH5 6NT (United Kingdom); Wu, X. F.; Zhang, B. [Department of Physics and Astronomy, University of Nevada Las Vegas, Las Vegas, NV 89154 (United States); Gorosabel, J. [Instituto de Astrofisica de Andalucia (IAA-CSIC), 18008 Granada (Spain); Urata, Y. [Institute of Astronomy, National Central University, Chung-Li 32054, Taiwan (China); Sugita, S. [EcoTopia Science Institute, Nagoya University, Furo-cho, chikusa, Nagoya 464-8603 (Japan); Pozanenko, A. [Space Research Institute (IKI), 84/32 Profsoyuznaya St., Moscow 117997 (Russian Federation); Nissinen, M. [Taurus Hill Observatory, Haerkaemaeentie 88, 79480 Kangaslampi (Finland); Sahu, D. K. [CREST, Indian Institute of Astrophysics, Koramangala, Bangalore 560034 (India); Im, M. [Center for the Exploration of the Origin of the Universe, Department of Physics and Astronomy, FPRD, Seoul National University, Shillim-dong, San 56-1, Kwanak-gu, Seoul (Korea, Republic of); Ukwatta, T. N. [Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824 (United States); Andreev, M. [Terskol Branch of Institute of Astronomy of RAS, Kabardino-Balkaria Republic 361605 (Russian Federation); Klunko, E., E-mail: zwk@umich.edu, E-mail: rfshen@astro.utoronto.ca, E-mail: zhang@physics.unlv.edu [Institute of Solar-Terrestrial Physics, Lermontov St., 126a, Irkutsk 664033 (Russian Federation); and others

2012-06-01

We present a comprehensive analysis of a bright, long-duration (T{sub 90} {approx} 257 s) GRB 110205A at redshift z = 2.22. The optical prompt emission was detected by Swift/UVOT, ROTSE-IIIb, and BOOTES telescopes when the gamma-ray burst (GRB) was still radiating in the {gamma}-ray band, with optical light curve showing correlation with {gamma}-ray data. Nearly 200 s of observations were obtained simultaneously from optical, X-ray, to {gamma}-ray (1 eV to 5 MeV), which makes it one of the exceptional cases to study the broadband spectral energy distribution during the prompt emission phase. In particular, we clearly identify, for the first time, an interesting two-break energy spectrum, roughly consistent with the standard synchrotron emission model in the fast cooling regime. Shortly after prompt emission ({approx}1100 s), a bright (R = 14.0) optical emission hump with very steep rise ({alpha} {approx} 5.5) was observed, which we interpret as the reverse shock (RS) emission. It is the first time that the rising phase of an RS component has been closely observed. The full optical and X-ray afterglow light curves can be interpreted within the standard reverse shock (RS) + forward shock (FS) model. In general, the high-quality prompt and afterglow data allow us to apply the standard fireball model to extract valuable information, including the radiation mechanism (synchrotron), radius of prompt emission (R{sub GRB} {approx} 3 Multiplication-Sign 10{sup 13} cm), initial Lorentz factor of the outflow ({Gamma}{sub 0} {approx} 250), the composition of the ejecta (mildly magnetized), the collimation angle, and the total energy budget.

The costs of mitigating carbon emissions in China: findings from China MARKAL-MACRO modeling

International Nuclear Information System (INIS)

Chen Wenying

2005-01-01

In this paper MARKAL-MACRO, an integrated energy-environment-economy model, is used to generate China's reference scenario for future energy development and carbon emission through the year 2050. The results show that with great efforts on structure adjustment, energy efficiency improvement and energy substitution, China's primary energy consumption is expected to be 4818 Mtce and carbon emission 2394 MtC by 2050 with annual decrease rate of 3% for the carbon intensity per GDP during the period 2000-2050. On the basis of this reference scenario, China's marginal abatement cost curves of carbon for the year 2010, 2020 and 2030 are derived from the model, and the impacts of carbon emission abatement on GDP are also simulated. The results are compared with those from other sources. The research shows that the marginal abatement costs vary from 12US$/tC to 216US$/tC and the rates of GDP losses relative to reference range from 0.1% to 2.54% for the reduction rates between 5% and 45%. Both the marginal abatement costs and the rates of GDP losses further enlarge on condition that the maximum capacity of nuclear power is constrained to 240 GW or 160 GW by 2050. The paper concludes that China's costs of carbon abatement is rather high in case of carbon emissions are further cut beyond the reference scenario, and China's carbon abatement room is limited due to her coal-dominant energy resource characteristic. As economic development still remains the priority and per capita income as well as per capita carbon emission are far below the world average, it will be more realistic for China to make continuous contributions to combating global climate change by implementing sustainable development strategy domestically and playing an active role in the international carbon mitigation cooperation mechanisms rather than accepting a carbon emission ceiling

Dynamical insurance models with investment: Constrained singular problems for integrodifferential equations

Science.gov (United States)

Belkina, T. A.; Konyukhova, N. B.; Kurochkin, S. V.

2016-01-01

Previous and new results are used to compare two mathematical insurance models with identical insurance company strategies in a financial market, namely, when the entire current surplus or its constant fraction is invested in risky assets (stocks), while the rest of the surplus is invested in a risk-free asset (bank account). Model I is the classical Cramér-Lundberg risk model with an exponential claim size distribution. Model II is a modification of the classical risk model (risk process with stochastic premiums) with exponential distributions of claim and premium sizes. For the survival probability of an insurance company over infinite time (as a function of its initial surplus), there arise singular problems for second-order linear integrodifferential equations (IDEs) defined on a semiinfinite interval and having nonintegrable singularities at zero: model I leads to a singular constrained initial value problem for an IDE with a Volterra integral operator, while II model leads to a more complicated nonlocal constrained problem for an IDE with a non-Volterra integral operator. A brief overview of previous results for these two problems depending on several positive parameters is given, and new results are presented. Additional results are concerned with the formulation, analysis, and numerical study of "degenerate" problems for both models, i.e., problems in which some of the IDE parameters vanish; moreover, passages to the limit with respect to the parameters through which we proceed from the original problems to the degenerate ones are singular for small and/or large argument values. Such problems are of mathematical and practical interest in themselves. Along with insurance models without investment, they describe the case of surplus completely invested in risk-free assets, as well as some noninsurance models of surplus dynamics, for example, charity-type models.

Modelling carbon emissions in electric systems

International Nuclear Information System (INIS)

Lau, E.T.; Yang, Q.; Forbes, A.B.; Wright, P.; Livina, V.N.

2014-01-01

Highlights: • We model carbon emissions in electric systems. • We estimate emissions in generated and consumed energy with UK carbon factors. • We model demand profiles with novel function based on hyperbolic tangents. • We study datasets of UK Elexon database, Brunel PV system and Irish SmartGrid. • We apply Ensemble Kalman Filter to forecast energy data in these case studies. - Abstract: We model energy consumption of network electricity and compute Carbon emissions (CE) based on obtained energy data. We review various models of electricity consumption and propose an adaptive seasonal model based on the Hyperbolic tangent function (HTF). We incorporate HTF to define seasonal and daily trends of electricity demand. We then build a stochastic model that combines the trends and white noise component and the resulting simulations are estimated using Ensemble Kalman Filter (EnKF), which provides ensemble simulations of groups of electricity consumers; similarly, we estimate carbon emissions from electricity generators. Three case studies of electricity generation and consumption are modelled: Brunel University photovoltaic generation data, Elexon national electricity generation data (various fuel types) and Irish smart grid data, with ensemble estimations by EnKF and computation of carbon emissions. We show the flexibility of HTF-based functions for modelling realistic cycles of energy consumption, the efficiency of EnKF in ensemble estimation of energy consumption and generation, and report the obtained estimates of the carbon emissions in the considered case studies

Constraining neutrinoless double beta decay

International Nuclear Information System (INIS)

Dorame, L.; Meloni, D.; Morisi, S.; Peinado, E.; Valle, J.W.F.

2012-01-01

A class of discrete flavor-symmetry-based models predicts constrained neutrino mass matrix schemes that lead to specific neutrino mass sum-rules (MSR). We show how these theories may constrain the absolute scale of neutrino mass, leading in most of the cases to a lower bound on the neutrinoless double beta decay effective amplitude.

TeV Diffuse Emission From the Inner Galaxy

Directory of Open Access Journals (Sweden)

Amid Nayerhoda

2018-04-01

Full Text Available The TeV diffuse emission from the Galactic plane is produced by multi TeV electrons and nuclei interacting with radiation fields and ambient gas, respectively. Measurements of the TeV diffuse emission help constrain CR origin and transport properties. We present a preliminary analysis of HAWC diffuse emission data from the inner Galaxy. The HAWC measurements will be used to constrain particle transport properties close to the Galaxy center correlating the HAWC maps with predictions of the DRAGON code.

Modeling greenhouse gas emissions from dairy farms.

Science.gov (United States)

Rotz, C Alan

2017-11-15

Dairy farms have been identified as an important source of greenhouse gas emissions. Within the farm, important emissions include enteric CH 4 from the animals, CH 4 and N 2 O from manure in housing facilities during long-term storage and during field application, and N 2 O from nitrification and denitrification processes in the soil used to produce feed crops and pasture. Models using a wide range in level of detail have been developed to represent or predict these emissions. They include constant emission factors, variable process-related emission factors, empirical or statistical models, mechanistic process simulations, and life cycle assessment. To fully represent farm emissions, models representing the various emission sources must be integrated to capture the combined effects and interactions of all important components. Farm models have been developed using relationships across the full scale of detail, from constant emission factors to detailed mechanistic simulations. Simpler models, based upon emission factors and empirical relationships, tend to provide better tools for decision support, whereas more complex farm simulations provide better tools for research and education. To look beyond the farm boundaries, life cycle assessment provides an environmental accounting tool for quantifying and evaluating emissions over the full cycle, from producing the resources used on the farm through processing, distribution, consumption, and waste handling of the milk and dairy products produced. Models are useful for improving our understanding of farm processes and their interacting effects on greenhouse gas emissions. Through better understanding, they assist in the development and evaluation of mitigation strategies for reducing emissions and improving overall sustainability of dairy farms. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article

Challenges in constraining anthropogenic aerosol effects on cloud radiative forcing using present-day spatiotemporal variability.

Science.gov (United States)

Ghan, Steven; Wang, Minghuai; Zhang, Shipeng; Ferrachat, Sylvaine; Gettelman, Andrew; Griesfeller, Jan; Kipling, Zak; Lohmann, Ulrike; Morrison, Hugh; Neubauer, David; Partridge, Daniel G; Stier, Philip; Takemura, Toshihiko; Wang, Hailong; Zhang, Kai

2016-05-24

A large number of processes are involved in the chain from emissions of aerosol precursor gases and primary particles to impacts on cloud radiative forcing. Those processes are manifest in a number of relationships that can be expressed as factors dlnX/dlnY driving aerosol effects on cloud radiative forcing. These factors include the relationships between cloud condensation nuclei (CCN) concentration and emissions, droplet number and CCN concentration, cloud fraction and droplet number, cloud optical depth and droplet number, and cloud radiative forcing and cloud optical depth. The relationship between cloud optical depth and droplet number can be further decomposed into the sum of two terms involving the relationship of droplet effective radius and cloud liquid water path with droplet number. These relationships can be constrained using observations of recent spatial and temporal variability of these quantities. However, we are most interested in the radiative forcing since the preindustrial era. Because few relevant measurements are available from that era, relationships from recent variability have been assumed to be applicable to the preindustrial to present-day change. Our analysis of Aerosol Comparisons between Observations and Models (AeroCom) model simulations suggests that estimates of relationships from recent variability are poor constraints on relationships from anthropogenic change for some terms, with even the sign of some relationships differing in many regions. Proxies connecting recent spatial/temporal variability to anthropogenic change, or sustained measurements in regions where emissions have changed, are needed to constrain estimates of anthropogenic aerosol impacts on cloud radiative forcing.

Elastic Model Transitions Using Quadratic Inequality Constrained Least Squares

Science.gov (United States)

Orr, Jeb S.

2012-01-01

A technique is presented for initializing multiple discrete finite element model (FEM) mode sets for certain types of flight dynamics formulations that rely on superposition of orthogonal modes for modeling the elastic response. Such approaches are commonly used for modeling launch vehicle dynamics, and challenges arise due to the rapidly time-varying nature of the rigid-body and elastic characteristics. By way of an energy argument, a quadratic inequality constrained least squares (LSQI) algorithm is employed to e ect a smooth transition from one set of FEM eigenvectors to another with no requirement that the models be of similar dimension or that the eigenvectors be correlated in any particular way. The physically unrealistic and controversial method of eigenvector interpolation is completely avoided, and the discrete solution approximates that of the continuously varying system. The real-time computational burden is shown to be negligible due to convenient features of the solution method. Simulation results are presented, and applications to staging and other discontinuous mass changes are discussed

Model for traffic emissions estimation

Science.gov (United States)

Alexopoulos, A.; Assimacopoulos, D.; Mitsoulis, E.

A model is developed for the spatial and temporal evaluation of traffic emissions in metropolitan areas based on sparse measurements. All traffic data available are fully employed and the pollutant emissions are determined with the highest precision possible. The main roads are regarded as line sources of constant traffic parameters in the time interval considered. The method is flexible and allows for the estimation of distributed small traffic sources (non-line/area sources). The emissions from the latter are assumed to be proportional to the local population density as well as to the traffic density leading to local main arteries. The contribution of moving vehicles to air pollution in the Greater Athens Area for the period 1986-1988 is analyzed using the proposed model. Emissions and other related parameters are evaluated. Emissions from area sources were found to have a noticeable share of the overall air pollution.

Modeling Dynamic Contrast-Enhanced MRI Data with a Constrained Local AIF

DEFF Research Database (Denmark)

Duan, Chong; Kallehauge, Jesper F.; Pérez-Torres, Carlos J

2018-01-01

PURPOSE: This study aims to develop a constrained local arterial input function (cL-AIF) to improve quantitative analysis of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) data by accounting for the contrast-agent bolus amplitude error in the voxel-specific AIF. PROCEDURES....... RESULTS: When the data model included the cL-AIF, tracer kinetic parameters were correctly estimated from in silico data under contrast-to-noise conditions typical of clinical DCE-MRI experiments. Considering the clinical cervical cancer data, Bayesian model selection was performed for all tumor voxels...

A Chance-Constrained Economic Dispatch Model in Wind-Thermal-Energy Storage System

Directory of Open Access Journals (Sweden)

Yanzhe Hu

2017-03-01

Full Text Available As a type of renewable energy, wind energy is integrated into the power system with more and more penetration levels. It is challenging for the power system operators (PSOs to cope with the uncertainty and variation of the wind power and its forecasts. A chance-constrained economic dispatch (ED model for the wind-thermal-energy storage system (WTESS is developed in this paper. An optimization model with the wind power and the energy storage system (ESS is first established with the consideration of both the economic benefits of the system and less wind curtailments. The original wind power generation is processed by the ESS to obtain the final wind power output generation (FWPG. A Gaussian mixture model (GMM distribution is adopted to characterize the probabilistic and cumulative distribution functions with an analytical expression. Then, a chance-constrained ED model integrated by the wind-energy storage system (W-ESS is developed by considering both the overestimation costs and the underestimation costs of the system and solved by the sequential linear programming method. Numerical simulation results using the wind power data in four wind farms are performed on the developed ED model with the IEEE 30-bus system. It is verified that the developed ED model is effective to integrate the uncertain and variable wind power. The GMM distribution could accurately fit the actual distribution of the final wind power output, and the ESS could help effectively decrease the operation costs.

Constraining spatial variations of the fine-structure constant in symmetron models

Directory of Open Access Journals (Sweden)

A.M.M. Pinho

2017-06-01

Full Text Available We introduce a methodology to test models with spatial variations of the fine-structure constant α, based on the calculation of the angular power spectrum of these measurements. This methodology enables comparisons of observations and theoretical models through their predictions on the statistics of the α variation. Here we apply it to the case of symmetron models. We find no indications of deviations from the standard behavior, with current data providing an upper limit to the strength of the symmetron coupling to gravity (log⁡β2<−0.9 when this is the only free parameter, and not able to constrain the model when also the symmetry breaking scale factor aSSB is free to vary.

Modelling of mid-infrared interferometric signature of hot exozodiacal dust emission

Science.gov (United States)

Kirchschlager, Florian; Wolf, Sebastian; Brunngräber, Robert; Matter, Alexis; Krivov, Alexander V.; Labdon, Aaron

2018-01-01

Hot exozodiacal dust emission was detected in recent surveys around two dozen main-sequence stars at distances of less than 1 au using the H- and K-band interferometry. Due to the high contrast as well as the small angular distance between the circumstellar dust and the star, direct observation of this dust component is challenging. An alternative way to explore the hot exozodiacal dust is provided by mid-infrared interferometry. We analyse the L, M and N bands interferometric signature of this emission in order to find stronger constraints for the properties and the origin of the hot exozodiacal dust. Considering the parameters of nine debris disc systems derived previously, we model the discs in each of these bands. We find that the M band possesses the best conditions to detect hot dust emission, closely followed by L and N bands. The hot dust in three systems - HD 22484 (10 Tau), HD 102647 (β Leo) and HD 177724 (ζ Aql) - shows a strong signal in the visibility functions, which may even allow one to constrain the dust location. In particular, observations in the mid-infrared could help to determine whether the dust piles up at the sublimation radius or is located at radii up to 1 au. In addition, we explore observations of the hot exozodiacal dust with the upcoming mid-infrared interferometer Multi AperTure mid-Infrared SpectroScopic Experiment (MATISSE) at the Very Large Telescope Interferometer.

Inexact Multistage Stochastic Chance Constrained Programming Model for Water Resources Management under Uncertainties

Directory of Open Access Journals (Sweden)

Hong Zhang

2017-01-01

Full Text Available In order to formulate water allocation schemes under uncertainties in the water resources management systems, an inexact multistage stochastic chance constrained programming (IMSCCP model is proposed. The model integrates stochastic chance constrained programming, multistage stochastic programming, and inexact stochastic programming within a general optimization framework to handle the uncertainties occurring in both constraints and objective. These uncertainties are expressed as probability distributions, interval with multiply distributed stochastic boundaries, dynamic features of the long-term water allocation plans, and so on. Compared with the existing inexact multistage stochastic programming, the IMSCCP can be used to assess more system risks and handle more complicated uncertainties in water resources management systems. The IMSCCP model is applied to a hypothetical case study of water resources management. In order to construct an approximate solution for the model, a hybrid algorithm, which incorporates stochastic simulation, back propagation neural network, and genetic algorithm, is proposed. The results show that the optimal value represents the maximal net system benefit achieved with a given confidence level under chance constraints, and the solutions provide optimal water allocation schemes to multiple users over a multiperiod planning horizon.

Model Predictive Control Based on Kalman Filter for Constrained Hammerstein-Wiener Systems

Directory of Open Access Journals (Sweden)

Man Hong

2013-01-01

Full Text Available To precisely track the reactor temperature in the entire working condition, the constrained Hammerstein-Wiener model describing nonlinear chemical processes such as in the continuous stirred tank reactor (CSTR is proposed. A predictive control algorithm based on the Kalman filter for constrained Hammerstein-Wiener systems is designed. An output feedback control law regarding the linear subsystem is derived by state observation. The size of reaction heat produced and its influence on the output are evaluated by the Kalman filter. The observation and evaluation results are calculated by the multistep predictive approach. Actual control variables are computed while considering the constraints of the optimal control problem in a finite horizon through the receding horizon. The simulation example of the CSTR tester shows the effectiveness and feasibility of the proposed algorithm.

Recent Changes in Global Photosynthesis and Terrestrial Ecosystem Respiration Constrained From Multiple Observations

Science.gov (United States)

Li, Wei; Ciais, Philippe; Wang, Yilong; Yin, Yi; Peng, Shushi; Zhu, Zaichun; Bastos, Ana; Yue, Chao; Ballantyne, Ashley P.; Broquet, Grégoire; Canadell, Josep G.; Cescatti, Alessandro; Chen, Chi; Cooper, Leila; Friedlingstein, Pierre; Le Quéré, Corinne; Myneni, Ranga B.; Piao, Shilong

2018-01-01

To assess global carbon cycle variability, we decompose the net land carbon sink into the sum of gross primary productivity (GPP), terrestrial ecosystem respiration (TER), and fire emissions and apply a Bayesian framework to constrain these fluxes between 1980 and 2014. The constrained GPP and TER fluxes show an increasing trend of only half of the prior trend simulated by models. From the optimization, we infer that TER increased in parallel with GPP from 1980 to 1990, but then stalled during the cooler periods, in 1990-1994 coincident with the Pinatubo eruption, and during the recent warming hiatus period. After each of these TER stalling periods, TER is found to increase faster than GPP, explaining a relative reduction of the net land sink. These results shed light on decadal variations of GPP and TER and suggest that they exhibit different responses to temperature anomalies over the last 35 years.

Constraining viscous dark energy models with the latest cosmological data

Science.gov (United States)

Wang, Deng; Yan, Yang-Jie; Meng, Xin-He

2017-10-01

Based on the assumption that the dark energy possessing bulk viscosity is homogeneously and isotropically permeated in the universe, we propose three new viscous dark energy (VDE) models to characterize the accelerating universe. By constraining these three models with the latest cosmological observations, we find that they just deviate very slightly from the standard cosmological model and can alleviate effectively the current H_0 tension between the local observation by the Hubble Space Telescope and the global measurement by the Planck Satellite. Interestingly, we conclude that a spatially flat universe in our VDE model with cosmic curvature is still supported by current data, and the scale invariant primordial power spectrum is strongly excluded at least at the 5.5σ confidence level in the three VDE models as the Planck result. We also give the 95% upper limits of the typical bulk viscosity parameter η in the three VDE scenarios.

Source model for the Copahue volcano magmaplumbing system constrained by InSARsurface deformation observations

Science.gov (United States)

Lundgren, P.; Nikkhoo, M.; Samsonov, S. V.; Milillo, P.; Gil-Cruz, F., Sr.; Lazo, J.

2017-12-01

Copahue volcano straddling the edge of the Agrio-Caviahue caldera along the Chile-Argentinaborder in the southern Andes has been in unrest since inflation began in late 2011. We constrain Copahue'ssource models with satellite and airborne interferometric synthetic aperture radar (InSAR) deformationobservations. InSAR time series from descending track RADARSAT-2 and COSMO-SkyMed data span theentire inflation period from 2011 to 2016, with their initially high rates of 12 and 15 cm/yr, respectively,slowing only slightly despite ongoing small eruptions through 2016. InSAR ascending and descending tracktime series for the 2013-2016 time period constrain a two-source compound dislocation model, with a rate ofvolume increase of 13 × 106 m3/yr. They consist of a shallow, near-vertical, elongated source centered at2.5 km beneath the summit and a deeper, shallowly plunging source centered at 7 km depth connecting theshallow source to the deeper caldera. The deeper source is located directly beneath the volcano tectonicseismicity with the lower bounds of the seismicity parallel to the plunge of the deep source. InSAR time seriesalso show normal fault offsets on the NE flank Copahue faults. Coulomb stress change calculations forright-lateral strike slip (RLSS), thrust, and normal receiver faults show positive values in the north caldera forboth RLSS and normal faults, suggesting that northward trending seismicity and Copahue fault motion withinthe caldera are caused by the modeled sources. Together, the InSAR-constrained source model and theseismicity suggest a deep conduit or transfer zone where magma moves from the central caldera toCopahue's upper edifice.

Maximum entropy production: Can it be used to constrain conceptual hydrological models?

Science.gov (United States)

M.C. Westhoff; E. Zehe

2013-01-01

In recent years, optimality principles have been proposed to constrain hydrological models. The principle of maximum entropy production (MEP) is one of the proposed principles and is subject of this study. It states that a steady state system is organized in such a way that entropy production is maximized. Although successful applications have been reported in...

Chance-constrained/stochastic linear programming model for acid rain abatement. I. Complete colinearity and noncolinearity

Energy Technology Data Exchange (ETDEWEB)

Ellis, J H; McBean, E A; Farquhar, G J

1985-01-01

A Linear Programming model is presented for development of acid rain abatement strategies in eastern North America. For a system comprised of 235 large controllable point sources and 83 uncontrolled area sources, it determines the least-cost method of reducing SO/sub 2/ emissions to satisfy maximum wet sulfur deposition limits at 20 sensitive receptor locations. In this paper, the purely deterministic model is extended to a probabilistic form by incorporating the effects of meteorologic variability on the long-range pollutant transport processes. These processes are represented by source-receptor-specific transfer coefficients. Experiments for quantifying the spatial variability of transfer coefficients showed their distributions to be approximately lognormal with logarithmic standard deviations consistently about unity. Three methods of incorporating second-moment random variable uncertainty into the deterministic LP framework are described: Two-Stage Programming Under Uncertainty, Chance-Constrained Programming and Stochastic Linear Programming. A composite CCP-SLP model is developed which embodies the two-dimensional characteristics of transfer coefficient uncertainty. Two probabilistic formulations are described involving complete colinearity and complete noncolinearity for the transfer coefficient covariance-correlation structure. The completely colinear and noncolinear formulations are considered extreme bounds in a meteorologic sense and yield abatement strategies of largely didactic value. Such strategies can be characterized as having excessive costs and undesirable deposition results in the completely colinear case and absence of a clearly defined system risk level (other than expected-value) in the noncolinear formulation.

A new approach for monthly updates of anthropogenic sulfur dioxide emissions from space: Application to China and implications for air quality forecasts

Science.gov (United States)

Wang, Yi; Wang, Jun; Xu, Xiaoguang; Henze, Daven K.; Wang, Yuxuan; Qu, Zhen

2016-09-01

SO2 emissions, the largest source of anthropogenic aerosols, can respond rapidly to economic and policy driven changes. However, bottom-up SO2 inventories have inherent limitations owing to 24-48 months latency and lack of month-to-month variation in emissions (especially in developing countries). This study develops a new approach that integrates Ozone Monitoring Instrument (OMI) SO2 satellite measurements and GEOS-Chem adjoint model simulations to constrain monthly anthropogenic SO2 emissions. The approach's effectiveness is demonstrated for 14 months in East Asia; resultant posterior emissions not only capture a 20% SO2 emission reduction in Beijing during the 2008 Olympic Games but also improve agreement between modeled and in situ surface measurements. Further analysis reveals that posterior emissions estimates, compared to the prior, lead to significant improvements in forecasting monthly surface and columnar SO2. With the pending availability of geostationary measurements of tropospheric composition, we show that it may soon be possible to rapidly constrain SO2 emissions and associated air quality predictions at fine spatiotemporal scales.

Fermi-LAT upper limits on gamma-ray emission from colliding wind binaries

International Nuclear Information System (INIS)

Werner, Michael; Reimer, O.; Reimer, A.

2013-01-01

Here, colliding wind binaries (CWBs) are thought to give rise to a plethora of physical processes including acceleration and interaction of relativistic particles. Observation of synchrotron radiation in the radio band confirms there is a relativistic electron population in CWBs. Accordingly, CWBs have been suspected sources of high-energy γ-ray emission since the COS-B era. Theoretical models exist that characterize the underlying physical processes leading to particle acceleration and quantitatively predict the non-thermal energy emission observable at Earth. Furthermore, we strive to find evidence of γ-ray emission from a sample of seven CWB systems: WR 11, WR 70, WR 125, WR 137, WR 140, WR 146, and WR 147. Theoretical modelling identified these systems as the most favourable candidates for emitting γ-rays. We make a comparison with existing γ-ray flux predictions and investigate possible constraints. We used 24 months of data from the Large Area Telescope (LAT) on-board the Fermi Gamma Ray Space Telescope to perform a dedicated likelihood analysis of CWBs in the LAT energy range. As a result, we find no evidence of γ-ray emission from any of the studied CWB systems and determine corresponding flux upper limits. For some CWBs the interplay of orbital and stellar parameters renders the Fermi-LAT data not sensitive enough to constrain the parameter space of the emission models. In the cases of WR140 and WR147, the Fermi-LAT upper limits appear to rule out some model predictions entirely and constrain theoretical models over a significant parameter space. A comparison of our findings to the CWB η Car is made.

A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback.

Science.gov (United States)

Koven, C D; Schuur, E A G; Schädel, C; Bohn, T J; Burke, E J; Chen, G; Chen, X; Ciais, P; Grosse, G; Harden, J W; Hayes, D J; Hugelius, G; Jafarov, E E; Krinner, G; Kuhry, P; Lawrence, D M; MacDougall, A H; Marchenko, S S; McGuire, A D; Natali, S M; Nicolsky, D J; Olefeldt, D; Peng, S; Romanovsky, V E; Schaefer, K M; Strauss, J; Treat, C C; Turetsky, M

2015-11-13

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation-Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2-33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9-112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of -14 to -19 Pg C °C(-1) on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10-18%. The simplified approach

Inversion of CO and NOx emissions using the adjoint of the IMAGES model

Directory of Open Access Journals (Sweden)

J.-F. Müller

2005-01-01

over Europe and Asia. Our inversion results have been evaluated against independent observations from aircraft campaigns. This comparison shows that the optimization of CO emissions constrained by both CO and NO2 observations leads to a better agreement between modelled and observed values, especially in the Tropics and the Southern Hemisphere, compared to the case where only CO observations are used. A posteriori estimation of errors on the control parameters shows that a significant error reduction is achieved for the majority of the anthropogenic source parameters, whereas biomass burning emissions are still subject to large errors after optimization. Nonetheless, the constraints provided by the GOME measurements allow to reduce the uncertainties on savanna burning emissions of both CO and NOx, suggesting thus that the incorporation of these data in the inversion yields more robust results for carbon monoxide.

Modeling biomass burning over the South, South East and East Asian Monsoon regions using a new, satellite constrained approach

Science.gov (United States)

Lan, R.; Cohen, J. B.

2017-12-01

Biomass burning over the South, South East and East Asian Monsoon regions, is a crucial contributor to the total local aerosol loading. Furthermore, the impact of the ITCZ, and Monsoonal circulation patterns coupled with complex topography also have a prominent impact on the aerosol loading throughout much of the Northern Hemisphere. However, at the present time, biomass burning emissions are highly underestimated over this region, in part due to under-reported emissions in space and time, and in part due to an incomplete understanding of the physics and chemistry of the aerosols emitted in fires and formed downwind from them. Hence, a better understanding of the four-dimensional source distribution, plume rise, and in-situ processing, in particular in regions with significant quantities of urban air pollutants, is essential to advance our knowledge of this problem. This work uses a new modeling methodology based on the simultaneous constraints of measured AOD and some trace gasses over the region. The results of the 4-D constrained emissions are further expanded upon using different fire plume height rise and in-situ processing assumptions. Comparisons between the results and additional ground-based and remotely sensed measurements, including AERONET, CALIOP, and NOAA and other ground networks are included. The end results reveal a trio of insights into the nonlinear processes most-important to understand the impacts of biomass burning in this part of the world. Model-measurement comparisons are found to be consistent during the typical burning years of 2016. First, the model performs better under the new emissions representations, than it does using any of the standard hotspot based approaches currently employed by the community. Second, long range transport and mixing between the boundary layer and free troposphere contribute to the spatial-temporal variations. Third, we indicate some source regions that are new, either because of increased urbanization, or of

Minimal constrained supergravity

Energy Technology Data Exchange (ETDEWEB)

Cribiori, N. [Dipartimento di Fisica e Astronomia “Galileo Galilei”, Università di Padova, Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova, Via Marzolo 8, 35131 Padova (Italy); Dall' Agata, G., E-mail: dallagat@pd.infn.it [Dipartimento di Fisica e Astronomia “Galileo Galilei”, Università di Padova, Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova, Via Marzolo 8, 35131 Padova (Italy); Farakos, F. [Dipartimento di Fisica e Astronomia “Galileo Galilei”, Università di Padova, Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova, Via Marzolo 8, 35131 Padova (Italy); Porrati, M. [Center for Cosmology and Particle Physics, Department of Physics, New York University, 4 Washington Place, New York, NY 10003 (United States)

2017-01-10

We describe minimal supergravity models where supersymmetry is non-linearly realized via constrained superfields. We show that the resulting actions differ from the so called “de Sitter” supergravities because we consider constraints eliminating directly the auxiliary fields of the gravity multiplet.

Minimal constrained supergravity

International Nuclear Information System (INIS)

Cribiori, N.; Dall'Agata, G.; Farakos, F.; Porrati, M.

2017-01-01

We describe minimal supergravity models where supersymmetry is non-linearly realized via constrained superfields. We show that the resulting actions differ from the so called “de Sitter” supergravities because we consider constraints eliminating directly the auxiliary fields of the gravity multiplet.

Constraining viscous dark energy models with the latest cosmological data

Energy Technology Data Exchange (ETDEWEB)

Wang, Deng [Nankai University, Theoretical Physics Division, Chern Institute of Mathematics, Tianjin (China); Yan, Yang-Jie; Meng, Xin-He [Nankai University, Department of Physics, Tianjin (China)

2017-10-15

Based on the assumption that the dark energy possessing bulk viscosity is homogeneously and isotropically permeated in the universe, we propose three new viscous dark energy (VDE) models to characterize the accelerating universe. By constraining these three models with the latest cosmological observations, we find that they just deviate very slightly from the standard cosmological model and can alleviate effectively the current H{sub 0} tension between the local observation by the Hubble Space Telescope and the global measurement by the Planck Satellite. Interestingly, we conclude that a spatially flat universe in our VDE model with cosmic curvature is still supported by current data, and the scale invariant primordial power spectrum is strongly excluded at least at the 5.5σ confidence level in the three VDE models as the Planck result. We also give the 95% upper limits of the typical bulk viscosity parameter η in the three VDE scenarios. (orig.)

A prognostic pollen emissions model for climate models (PECM1.0

Directory of Open Access Journals (Sweden)

M. C. Wozniak

2017-11-01

Full Text Available We develop a prognostic model called Pollen Emissions for Climate Models (PECM for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus, evergreen needleleaf trees (Cupressaceae, Pinaceae, grasses (Poaceae; C3, C4, and ragweed (Ambrosia. This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in the Regional Climate Model version 4 (RegCM4 over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model using (1 a taxa-specific land cover database, phenology, and emission potential, and (2 a plant functional type (PFT land cover, phenology, and emission potential. The simulated surface pollen concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model; however, we note that the PFT-based version provides a useful and climate-flexible emissions

Constraint on Parameters of Inverse Compton Scattering Model for ...

Indian Academy of Sciences (India)

B2319+60, two parameters of inverse Compton scattering model, the initial Lorentz factor and the factor of energy loss of relativistic particles are constrained. Key words. Pulsar—inverse Compton scattering—emission mechanism. 1. Introduction. Among various kinds of models for pulsar radio emission, the inverse ...

Interannual variability of carbon monoxide emission estimates over South America from 2006 to 2010

NARCIS (Netherlands)

Hooghiemstra, P.B.; Krol, M.C.; Leeuwen, van T.T.; Werf, van der G.R.; Novelli, P.C.; Deeter, M.N.; Aben, I.; Rockmann, T.

2012-01-01

We present the first inverse modeling study to estimate CO emissions constrained by both surface and satellite observations. Our 4D-Var system assimilates National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA/ESRL) Global Monitoring Division (GMD) surface and

Modeling of greenhouse gas emission from livestock

Directory of Open Access Journals (Sweden)

Sanjo eJose

2016-04-01

Full Text Available The effects of climate change on humans and other living ecosystems is an area of on-going research. The ruminant livestock sector is considered to be one of the most significant contributors to the existing greenhouse gas (GHG pool. However the there are opportunities to combat climate change by reducing the emission of GHGs from ruminants. Methane (CH4 and nitrous oxide (N2O are emitted by ruminants via anaerobic digestion of organic matter in the rumen and manure, and by denitrification and nitrification processes which occur in manure. The quantification of these emissions by experimental methods is difficult and takes considerable time for analysis of the implications of the outputs from empirical studies, and for adaptation and mitigation strategies to be developed. To overcome these problems computer simulation models offer substantial scope for predicting GHG emissions. These models often include all farm activities while accurately predicting the GHG emissions including both direct as well as indirect sources. The models are fast and efficient in predicting emissions and provide valuable information on implementing the appropriate GHG mitigation strategies on farms. Further, these models help in testing the efficacy of various mitigation strategies that are employed to reduce GHG emissions. These models can be used to determine future adaptation and mitigation strategies, to reduce GHG emissions thereby combating livestock induced climate change.

Minimal constrained supergravity

Directory of Open Access Journals (Sweden)

N. Cribiori

2017-01-01

Full Text Available We describe minimal supergravity models where supersymmetry is non-linearly realized via constrained superfields. We show that the resulting actions differ from the so called “de Sitter” supergravities because we consider constraints eliminating directly the auxiliary fields of the gravity multiplet.

Future sea level rise constrained by observations and long-term commitment

Science.gov (United States)

Mengel, Matthias; Levermann, Anders; Frieler, Katja; Robinson, Alexander; Marzeion, Ben; Winkelmann, Ricarda

2016-01-01

Sea level has been steadily rising over the past century, predominantly due to anthropogenic climate change. The rate of sea level rise will keep increasing with continued global warming, and, even if temperatures are stabilized through the phasing out of greenhouse gas emissions, sea level is still expected to rise for centuries. This will affect coastal areas worldwide, and robust projections are needed to assess mitigation options and guide adaptation measures. Here we combine the equilibrium response of the main sea level rise contributions with their last century's observed contribution to constrain projections of future sea level rise. Our model is calibrated to a set of observations for each contribution, and the observational and climate uncertainties are combined to produce uncertainty ranges for 21st century sea level rise. We project anthropogenic sea level rise of 28–56 cm, 37–77 cm, and 57–131 cm in 2100 for the greenhouse gas concentration scenarios RCP26, RCP45, and RCP85, respectively. Our uncertainty ranges for total sea level rise overlap with the process-based estimates of the Intergovernmental Panel on Climate Change. The “constrained extrapolation” approach generalizes earlier global semiempirical models and may therefore lead to a better understanding of the discrepancies with process-based projections. PMID:26903648

Future sea level rise constrained by observations and long-term commitment.

Science.gov (United States)

Mengel, Matthias; Levermann, Anders; Frieler, Katja; Robinson, Alexander; Marzeion, Ben; Winkelmann, Ricarda

2016-03-08

Sea level has been steadily rising over the past century, predominantly due to anthropogenic climate change. The rate of sea level rise will keep increasing with continued global warming, and, even if temperatures are stabilized through the phasing out of greenhouse gas emissions, sea level is still expected to rise for centuries. This will affect coastal areas worldwide, and robust projections are needed to assess mitigation options and guide adaptation measures. Here we combine the equilibrium response of the main sea level rise contributions with their last century's observed contribution to constrain projections of future sea level rise. Our model is calibrated to a set of observations for each contribution, and the observational and climate uncertainties are combined to produce uncertainty ranges for 21st century sea level rise. We project anthropogenic sea level rise of 28-56 cm, 37-77 cm, and 57-131 cm in 2100 for the greenhouse gas concentration scenarios RCP26, RCP45, and RCP85, respectively. Our uncertainty ranges for total sea level rise overlap with the process-based estimates of the Intergovernmental Panel on Climate Change. The "constrained extrapolation" approach generalizes earlier global semiempirical models and may therefore lead to a better understanding of the discrepancies with process-based projections.

Direct stratospheric injection of biomass burning emissions: a case study of the 2009 Australian bushfires using the NASA GISS ModelE2 composition-climate model

Science.gov (United States)

Field, Robert; From, Mike; Voulgarakis, Apostolos; Shindell, Drew; Flannigan, Mike; Bernath, Peter

2014-05-01

Direct stratospheric injection (DSI) of forest fire smoke represents a direct biogeochemical link between the land surface and stratosphere. DSI events occur regularly in the northern and southern extratropics, and have been observed across a wide range of measurements, but their fate and effects are not well understood. DSIs result from explosive, short-lived fires, and their plumes stand out from background concentrations immediately. This makes it easier to associate detected DSIs to individual fires and their estimated emissions. Because the emissions pulses are brief, chemical decay can be more clearly assessed, and because the emissions pulses are so large, a wide range of rare chemical species can be detected. Observational evidence suggests that they can persist in the stratosphere for several months, enhance ozone production, and be self-lofted to the middle stratosphere through shortwave absorption and diabatic heating. None of these phenomena have been evaluated, however, with a physical model. To that end, we are simulating the smoke plumes from the February 2009 Australia 'Black Saturday' bushfires using the NASA GISS ModelE2 composition-climate model, nudged toward horizontal winds from reanalysis. To-date, this is the best-observed DSI in the southern hemisphere. Chemical and aerosol signatures of the plume were observed in a wide array of limb and nadir satellite retrievals. Detailed estimates of fuel consumption and injection height have been made because of the severity of the fires. Uncommon among DSIs events was a large segment of the plume that entrained into the upper equatorial easterlies. Preliminary modeling results show that the relative strengths of the equatorial and extratropical plume segments are sensitive to the plume's initial injection height. This highlights the difficulty in reconciling uncertainty in the reanalysis over the Southern Hemisphere with fairly-well constrained estimates of fire location and injection height at the

Measurement model and calibration experiment of over-constrained parallel six-dimensional force sensor based on stiffness characteristics analysis

International Nuclear Information System (INIS)

Niu, Zhi; Zhao, Yanzhi; Zhao, Tieshi; Cao, Yachao; Liu, Menghua

2017-01-01

An over-constrained, parallel six-dimensional force sensor has various advantages, including its ability to bear heavy loads and provide redundant force measurement information. These advantages render the sensor valuable in important applications in the field of aerospace (space docking tests, etc). The stiffness of each component in the over-constrained structure has a considerable influence on the internal force distribution of the structure. Thus, the measurement model changes when the measurement branches of the sensor are under tensile or compressive force. This study establishes a general measurement model for an over-constrained parallel six-dimensional force sensor considering the different branch tensions and compression stiffness values. Numerical calculations and analyses are performed using practical examples. Based on the parallel mechanism, an over-constrained, orthogonal structure is proposed for a six-dimensional force sensor. Hence, a prototype is designed and developed, and a calibration experiment is conducted. The measurement accuracy of the sensor is improved based on the measurement model under different branch tensions and compression stiffness values. Moreover, the largest class I error is reduced from 5.81 to 2.23% full scale (FS), and the largest class II error is reduced from 3.425 to 1.871% FS. (paper)

Instantaneous wave emission model

International Nuclear Information System (INIS)

Kruer, W.L.

1970-12-01

A useful treatment of electrostatic wave emission by fast particles in a plasma is given. First, the potential due to a fast particle is expressed as a simple integration over the particle orbit; several interesting results readily follow. The potential in the wake of an accelerating particle is shown to be essentially that produced through local excitation of the plasma by the particle free-streaming about its instantaneous orbit. Application is made to one dimension, and it is shown that the wave emission and adsorption synchronize to the instantaneous velocity distribution function. Guided by these calculations, we then formulate a test particle model for computing the instantaneous wave emission by fast particles in a Vlasov plasma. This model lends itself to physical interpretation and provides a direct approach to many problems. By adopting a Fokker-Planck description for the particle dynamics, we calculate the broadening of the wave-particle resonance due to velocity diffusion and drag

Sampling from stochastic reservoir models constrained by production data

Energy Technology Data Exchange (ETDEWEB)

Hegstad, Bjoern Kaare

1997-12-31

When a petroleum reservoir is evaluated, it is important to forecast future production of oil and gas and to assess forecast uncertainty. This is done by defining a stochastic model for the reservoir characteristics, generating realizations from this model and applying a fluid flow simulator to the realizations. The reservoir characteristics define the geometry of the reservoir, initial saturation, petrophysical properties etc. This thesis discusses how to generate realizations constrained by production data, that is to say, the realizations should reproduce the observed production history of the petroleum reservoir within the uncertainty of these data. The topics discussed are: (1) Theoretical framework, (2) History matching, forecasting and forecasting uncertainty, (3) A three-dimensional test case, (4) Modelling transmissibility multipliers by Markov random fields, (5) Up scaling, (6) The link between model parameters, well observations and production history in a simple test case, (7) Sampling the posterior using optimization in a hierarchical model, (8) A comparison of Rejection Sampling and Metropolis-Hastings algorithm, (9) Stochastic simulation and conditioning by annealing in reservoir description, and (10) Uncertainty assessment in history matching and forecasting. 139 refs., 85 figs., 1 tab.

An inexact log-normal distribution-based stochastic chance-constrained model for agricultural water quality management

Science.gov (United States)

Wang, Yu; Fan, Jie; Xu, Ye; Sun, Wei; Chen, Dong

2018-05-01

In this study, an inexact log-normal-based stochastic chance-constrained programming model was developed for solving the non-point source pollution issues caused by agricultural activities. Compared to the general stochastic chance-constrained programming model, the main advantage of the proposed model is that it allows random variables to be expressed as a log-normal distribution, rather than a general normal distribution. Possible deviations in solutions caused by irrational parameter assumptions were avoided. The agricultural system management in the Erhai Lake watershed was used as a case study, where critical system factors, including rainfall and runoff amounts, show characteristics of a log-normal distribution. Several interval solutions were obtained under different constraint-satisfaction levels, which were useful in evaluating the trade-off between system economy and reliability. The applied results show that the proposed model could help decision makers to design optimal production patterns under complex uncertainties. The successful application of this model is expected to provide a good example for agricultural management in many other watersheds.

Constraining the Dynamics of Periodic Behavior at Mt. Semeru, Indonesia, Combining Numerical Modeling and Field Measurements of Gas emission

Science.gov (United States)

Smekens, J.; Clarke, A. B.; De'Michieli Vitturi, M.; Moore, G. M.

2012-12-01

Mt. Semeru is one of the most active explosive volcanoes on the island of Java in Indonesia. The current eruption style consists of small but frequent explosions and/or gas releases (several times a day) accompanied by continuous lava effusion that sporadically produces block-and-ash flows down the SE flank of the volcano. Semeru presents a unique opportunity to investigate the magma ascent conditions that produce this kind of persistent periodic behavior and the coexistence of explosive and effusive eruptions. In this work we use DOMEFLOW, a 1.5D transient isothermal numerical model, to investigate the dynamics of lava extrusion at Semeru. Petrologic observations from tephra and ballistic samples collected at the summit help us constrain the initial conditions of the system. Preliminary model runs produced periodic lava extrusion and pulses of gas release at the vent, with a cycle period on the order of hours, even though a steady magma supply rate was prescribed at the bottom of the conduit. Enhanced shallow permeability implemented in the model appears to create a dense plug in the shallow subsurface, which in turn plays a critical role in creating and controlling the observed periodic behavior. We measured SO2 fluxes just above the vent, using a custom UV imaging system. The device consists of two high-sensitivity CCD cameras with narrow UV filters centered at 310 and 330 nm, and a USB2000+ spectrometer for calibration and distance correction. The method produces high-frequency flux series with an accurate determination of the wind speed and plume geometry. The model results, when combined with gas measurements, and measurements of sulfur in both the groundmass and melt inclusions in eruptive products, could be used to create a volatile budget of the system. Furthermore, a well-calibrated model of the system will ultimately allow the characteristic periodicity and corresponding gas flux to be used as a proxy for magma supply rate.

Constraining walking and custodial technicolor

DEFF Research Database (Denmark)

Foadi, Roshan; Frandsen, Mads Toudal; Sannino, Francesco

2008-01-01

We show how to constrain the physical spectrum of walking technicolor models via precision measurements and modified Weinberg sum rules. We also study models possessing a custodial symmetry for the S parameter at the effective Lagrangian level-custodial technicolor-and argue that these models...

Constraining the location of rapid gamma-ray flares in the flat spectrum radio quasar 3C 273 [Constraining the location of rapid gamma-ray flares in the FSRQ 3C 273

International Nuclear Information System (INIS)

Rani, B.; Lott, B.; Krichbaum, T. P.; Fuhrmann, L.; Zensus, J. A.

2013-01-01

Here, we present a γ-ray photon flux and spectral variability study of the flat-spectrum radio quasar 3C 273 over a rapid flaring activity period between September 2009 to April 2010. Five major flares were observed in the source during this period. The most rapid flare observed in the source has a flux doubling time of 1.1 hr. The rapid γ-ray flares allow us to constrain the location and size of the γ-ray emission region in the source. The γγ-opacity constrains the Doppler factor δ_γ ≥ 10 for the highest energy (15 GeV) photon observed by the Fermi-Large Area Telescope (LAT). Causality arguments constrain the size of the emission region to 1.6 × 10"1"5 cm. The γ-ray spectra measured over this period show clear deviations from a simple power law with a break in the 1–2 GeV energy range. We discuss possible explanations for the origin of the γ-ray spectral breaks. Our study suggests that the γ-ray emission region in 3C 273 is located within the broad line region (< 1.6 pc). As a result, the spectral behavior and temporal characteristics of the individual flares indicate the presence of multiple shock scenarios at the base of the jet.

Uncovering the Best Skill Multimap by Constraining the Error Probabilities of the Gain-Loss Model

Science.gov (United States)

Anselmi, Pasquale; Robusto, Egidio; Stefanutti, Luca

2012-01-01

The Gain-Loss model is a probabilistic skill multimap model for assessing learning processes. In practical applications, more than one skill multimap could be plausible, while none corresponds to the true one. The article investigates whether constraining the error probabilities is a way of uncovering the best skill assignment among a number of…

Constrained noninformative priors

International Nuclear Information System (INIS)

Atwood, C.L.

1994-10-01

The Jeffreys noninformative prior distribution for a single unknown parameter is the distribution corresponding to a uniform distribution in the transformed model where the unknown parameter is approximately a location parameter. To obtain a prior distribution with a specified mean but with diffusion reflecting great uncertainty, a natural generalization of the noninformative prior is the distribution corresponding to the constrained maximum entropy distribution in the transformed model. Examples are given

Constrained consequence

CSIR Research Space (South Africa)

Britz, K

2011-09-01

Full Text Available their basic properties and relationship. In Section 3 we present a modal instance of these constructions which also illustrates with an example how to reason abductively with constrained entailment in a causal or action oriented context. In Section 4 we... of models with the former approach, whereas in Section 3.3 we give an example illustrating ways in which C can be de ned with both. Here we employ the following versions of local consequence: De nition 3.4. Given a model M = hW;R;Vi and formulas...

Explosive Volcanism in Io's Lava Lakes - The Key To Constraining Eruption Temperature?

Science.gov (United States)

Davies, A. G.; Keszthelyi, L. P.; McEwen, A. S.

2010-12-01

Active lava lakes are open volcanic systems, where lava circulates between a magma chamber and the surface. Rare on Earth, lava lakes may be common on Io, the highly volcanic jovian moon (e.g., [1]). Io’s low atmospheric pressure means that activity within Io’s lava lakes may be explosive, exposing lava at near-liquid temperatures (currently poorly constrained for Io). Lava lakes are therefore important targets for future missions to Io [2, 3]. With this in mind, hand-held infrared imagers were used to collect thermal emission data from the phonolite Erebus (Antarctica) lava lake [4] and the basalt lava lake at Erta’Ale (Ethiopia). Temperature-area distributions and the integrated thermal emission spectra for each lava lake were determined from the data. These calculated spectra have been used to test models developed for analysis of remote sensing data of lava lakes and lava flows on both Earth and Io, where no ground-truth exists. The silicate cooling model [5] assumes, for the lava lake model variant, that the existing surface crust has been created at a fixed rate. Model output consists of a synthesized thermal emission spectrum, estimate of surface age range, and a rate of surface crust area formation. The cooling model provides accurate reproductions of actual thermal spectra and the total emitting area to within a few percent of actual emitting area. Model resurfacing rates broadly agree with observed behaviour at both lakes. Despite different composition lavas, the short-wavelength infrared thermal emission spectra from the two terrestrial lava lakes studied are very similar in shape, and, importantly, bear a striking similarity to spectra of Pele, an Io volcano that has been proposed to be a persistent, active lava lake [6] and which is the source of a 300-km high dust and gas plume. Our study of the cooling of the hottest lava exposed at Erta’Ale yields constraints on the ability of multispectral imagers to determine eruption temperature. We find

Three-dimensional Forward-fit Modeling of the Hard X-Ray and Microwave Emissions of the 2015 June 22 M6.5 Flare

Science.gov (United States)

Kuroda, Natsuha; Gary, Dale E.; Wang, Haimin; Fleishman, Gregory D.; Nita, Gelu M.; Jing, Ju

2018-01-01

The well-established notion of a “common population” of the accelerated electrons simultaneously producing the hard X-ray (HXR) and microwave (MW) emission during the flare impulsive phase has been challenged by some studies reporting the discrepancies between the HXR-inferred and MW-inferred electron energy spectra. The traditional methods of spectral inversion have some problems that can be mainly attributed to the unrealistic and oversimplified treatment of the flare emission. To properly address this problem, we use a nonlinear force-free field (NLFFF) model extrapolated from an observed photospheric magnetogram as input to the three-dimensional, multiwavelength modeling platform GX Simulator and create a unified electron population model that can simultaneously reproduce the observed HXR and MW observations. We model the end of the impulsive phase of the 2015 June 22 M6.5 flare and constrain the modeled electron spatial and energy parameters using observations made by the highest-resolving instruments currently available in two wavelengths, the Reuven Ramaty High Energy Solar Spectroscopic Imager for HXR and the Expanded Owens Valley Solar Array for MW. Our results suggest that the HXR-emitting electron population model fits the standard flare model with a broken power-law spectrum ({E}{break}∼ 200 keV) that simultaneously produces the HXR footpoint emission and the MW high-frequency emission. The model also includes an “HXR-invisible” population of nonthermal electrons that are trapped in a large volume of magnetic field above the HXR-emitting loops, which is observable by its gyrosynchrotron radiation emitting mainly in the MW low-frequency range.

Space-Charge-Limited Emission Models for Particle Simulation

Science.gov (United States)

Verboncoeur, J. P.; Cartwright, K. L.; Murphy, T.

2004-11-01

Space-charge-limited (SCL) emission of electrons from various materials is a common method of generating the high current beams required to drive high power microwave (HPM) sources. In the SCL emission process, sufficient space charge is extracted from a surface, often of complicated geometry, to drive the electric field normal to the surface close to zero. The emitted current is highly dominated by space charge effects as well as ambient fields near the surface. In this work, we consider computational models for the macroscopic SCL emission process including application of Gauss's law and the Child-Langmuir law for space-charge-limited emission. Models are described for ideal conductors, lossy conductors, and dielectrics. Also considered is the discretization of these models, and the implications for the emission physics. Previous work on primary and dual-cell emission models [Watrous et al., Phys. Plasmas 8, 289-296 (2001)] is reexamined, and aspects of the performance, including fidelity and noise properties, are improved. Models for one-dimensional diodes are considered, as well as multidimensional emitting surfaces, which include corners and transverse fields.

Coding for Two Dimensional Constrained Fields

DEFF Research Database (Denmark)

Laursen, Torben Vaarbye

2006-01-01

a first order model to model higher order constraints by the use of an alphabet extension. We present an iterative method that based on a set of conditional probabilities can help in choosing the large numbers of parameters of the model in order to obtain a stationary model. Explicit results are given...... for the No Isolated Bits constraint. Finally we present a variation of the encoding scheme of bit-stuffing that is applicable to the class of checkerboard constrained fields. It is possible to calculate the entropy of the coding scheme thus obtaining lower bounds on the entropy of the fields considered. These lower...... bounds are very tight for the Run-Length limited fields. Explicit bounds are given for the diamond constrained field as well....

Adaptively Constrained Stochastic Model Predictive Control for the Optimal Dispatch of Microgrid

Directory of Open Access Journals (Sweden)

Xiaogang Guo

2018-01-01

Full Text Available In this paper, an adaptively constrained stochastic model predictive control (MPC is proposed to achieve less-conservative coordination between energy storage units and uncertain renewable energy sources (RESs in a microgrid (MG. Besides the economic objective of MG operation, the limits of state-of-charge (SOC and discharging/charging power of the energy storage unit are formulated as chance constraints when accommodating uncertainties of RESs, considering mild violations of these constraints are allowed during long-term operation, and a closed-loop online update strategy is performed to adaptively tighten or relax constraints according to the actual deviation probability of violation level from the desired one as well as the current change rate of deviation probability. Numerical studies show that the proposed adaptively constrained stochastic MPC for MG optimal operation is much less conservative compared with the scenario optimization based robust MPC, and also presents a better convergence performance to the desired constraint violation level than other online update strategies.

Constrained superfields in supergravity

Energy Technology Data Exchange (ETDEWEB)

Dall’Agata, Gianguido; Farakos, Fotis [Dipartimento di Fisica ed Astronomia “Galileo Galilei”, Università di Padova,Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova,Via Marzolo 8, 35131 Padova (Italy)

2016-02-16

We analyze constrained superfields in supergravity. We investigate the consistency and solve all known constraints, presenting a new class that may have interesting applications in the construction of inflationary models. We provide the superspace Lagrangians for minimal supergravity models based on them and write the corresponding theories in component form using a simplifying gauge for the goldstino couplings.

Bilevel Fuzzy Chance Constrained Hospital Outpatient Appointment Scheduling Model

Directory of Open Access Journals (Sweden)

Xiaoyang Zhou

2016-01-01

Full Text Available Hospital outpatient departments operate by selling fixed period appointments for different treatments. The challenge being faced is to improve profit by determining the mix of full time and part time doctors and allocating appointments (which involves scheduling a combination of doctors, patients, and treatments to a time period in a department optimally. In this paper, a bilevel fuzzy chance constrained model is developed to solve the hospital outpatient appointment scheduling problem based on revenue management. In the model, the hospital, the leader in the hierarchy, decides the mix of the hired full time and part time doctors to maximize the total profit; each department, the follower in the hierarchy, makes the decision of the appointment scheduling to maximize its own profit while simultaneously minimizing surplus capacity. Doctor wage and demand are considered as fuzzy variables to better describe the real-life situation. Then we use chance operator to handle the model with fuzzy parameters and equivalently transform the appointment scheduling model into a crisp model. Moreover, interactive algorithm based on satisfaction is employed to convert the bilevel programming into a single level programming, in order to make it solvable. Finally, the numerical experiments were executed to demonstrate the efficiency and effectiveness of the proposed approaches.

Modeling natural emissions in the Community Multiscale Air Quality (CMAQ Model–I: building an emissions data base

Directory of Open Access Journals (Sweden)

S. F. Mueller

2010-05-01

Full Text Available A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE emissions processing system currently estimates non-methane volatile organic compound (NMVOC emissions from biogenic sources, nitrogen oxide (NOx emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, windblown dust particulate, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide, 44% of total NOx, 80% of reactive carbonaceous gases (NMVOCs and carbon monoxide, 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride, and 84% of fine particles (i.e., those smaller than 2.5 μm in size released into the

Kovacs effect and fluctuation-dissipation relations in 1D kinetically constrained models

International Nuclear Information System (INIS)

Buhot, Arnaud

2003-01-01

Strong and fragile glass relaxation behaviours are obtained simply changing the constraints of the kinetically constrained Ising chain from symmetric to purely asymmetric. We study the out-of-equilibrium dynamics of these two models focusing on the Kovacs effect and the fluctuation-dissipation (FD) relations. The Kovacs or memory effect, commonly observed in structural glasses, is present for both constraints but enhanced with the asymmetric ones. Most surprisingly, the related FD relations satisfy the FD theorem in both cases. This result strongly differs from the simple quenching procedure where the asymmetric model presents strong deviations from the FD theorem

Modeling and query the uncertainty of network constrained moving objects based on RFID data

Science.gov (United States)

Han, Liang; Xie, Kunqing; Ma, Xiujun; Song, Guojie

2007-06-01

The management of network constrained moving objects is more and more practical, especially in intelligent transportation system. In the past, the location information of moving objects on network is collected by GPS, which cost high and has the problem of frequent update and privacy. The RFID (Radio Frequency IDentification) devices are used more and more widely to collect the location information. They are cheaper and have less update. And they interfere in the privacy less. They detect the id of the object and the time when moving object passed by the node of the network. They don't detect the objects' exact movement in side the edge, which lead to a problem of uncertainty. How to modeling and query the uncertainty of the network constrained moving objects based on RFID data becomes a research issue. In this paper, a model is proposed to describe the uncertainty of network constrained moving objects. A two level index is presented to provide efficient access to the network and the data of movement. The processing of imprecise time-slice query and spatio-temporal range query are studied in this paper. The processing includes four steps: spatial filter, spatial refinement, temporal filter and probability calculation. Finally, some experiments are done based on the simulated data. In the experiments the performance of the index is studied. The precision and recall of the result set are defined. And how the query arguments affect the precision and recall of the result set is also discussed.

Constraining Microwave Emission from Extensive Air Showers via the MIDAS Experiment

Science.gov (United States)

Richardson, Matthew; Privitera, Paolo

2017-01-01

Ultra high energy cosmic rays (UHECRs) are accelerated by the most energetic processes in the universe. Upon entering Earth’s atmosphere they produce particle showers known as extensive air showers (EASs). Observatories like the Pierre Auger Observatory sample the particles and light produced by the EASs through large particle detector arrays or nitrogen fluorescence detectors to ascertain the fundamental properties of UHECRs. The large sample of high quality data provided by the Pierre Auger Observatory can be attributed to the hybrid technique which utilizes the two aforementioned techniques simultaneously; however, the limitation of only being able to observe nitrogen fluorescence from EASs on clear moonless nights yields a limited 10% duty cycle for the hybrid technique. One proposal for providing high quality data at increased statistics is the observation of isotropic microwave emission from EASs, as such emission would be observed with a 100% duty cycle. Measurements of microwave emission from laboratory air plasmas conducted by Gorham et al. (2008) produced promising results indicating that the microwave emission should be observable using inexpensive detectors. The Microwave Detection of Air Showers (MIDAS) experiment was built at the University of Chicago to characterize the isotropic microwave emission from EASs and has collected 359 days of observational data at the location of the Pierre Auger experiment. We have performed a time coincidence analysis between this data and data from Pierre Auger and we report a null result. This result places stringent limits on microwave emission from EASs and demonstrates that the laboratory measurements of Gorham et al. (2008) are not applicable to EASs, thus diminishing the feasibility of using isotropic microwave emission to detect EASs.

A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback

Science.gov (United States)

Koven, C.D.; Schuur, E.A.G.; Schädel, C.; Bohn, T. J.; Burke, E. J.; Chen, G.; Chen, X.; Ciais, P.; Grosse, G.; Harden, J.W.; Hayes, D.J.; Hugelius, G.; Jafarov, Elchin E.; Krinner, G.; Kuhry, P.; Lawrence, D.M.; MacDougall, A. H.; Marchenko, Sergey S.; McGuire, A. David; Natali, Susan M.; Nicolsky, D.J.; Olefeldt, David; Peng, S.; Romanovsky, V.E.; Schaefer, Kevin M.; Strauss, J.; Treat, C.C.; Turetsky, M.

2015-01-01

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of −14 to −19 Pg C °C−1 on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. The

POLLUTANT EMISSION NUMERICAL ANALYSIS OF A MARINE ENGINE

Directory of Open Access Journals (Sweden)

DOREL DUMITRU VELCEA

2016-06-01

Full Text Available The energies produced by the diesel engines of strong power are largely used in marine propulsion because of their favorable reliability and their significant output. However, the increasingly constraining legislations, aimed at limiting the pollutant emissions from the exhaust gas produced by these engines, tend to call into question their supremacy. The analysis of the pollutant emissions and their reduction in the exhaust gas of the slow turbocharged marine diesel engine using ANSYS 15 constitutes the principal objective of this study. To address problems of global air pollution due to the pollutant emission from fuel oil engin e combustion, it is necessary to understand the mechanisms by which pollutants are produced in combustion processes. In the present work, an experimental and numerical study is carried out on a unit of real use aboard a car ferry ship. A numerical model based on a detailed chemical kinetics scheme is used to calculate the emissions of NOx, SOx and Sooth in an internal combustion engine model for the same characteristics of the real unit.

Nebular Continuum and Line Emission in Stellar Population Synthesis Models

Energy Technology Data Exchange (ETDEWEB)

Byler, Nell; Dalcanton, Julianne J. [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 (United States); Conroy, Charlie; Johnson, Benjamin D., E-mail: ebyler@astro.washington.edu [Department of Astronomy, Harvard University, Cambridge, MA 02138 (United States)

2017-05-01

Accounting for nebular emission when modeling galaxy spectral energy distributions (SEDs) is important, as both line and continuum emissions can contribute significantly to the total observed flux. In this work, we present a new nebular emission model integrated within the Flexible Stellar Population Synthesis code that computes the line and continuum emission for complex stellar populations using the photoionization code Cloudy. The self-consistent coupling of the nebular emission to the matched ionizing spectrum produces emission line intensities that correctly scale with the stellar population as a function of age and metallicity. This more complete model of galaxy SEDs will improve estimates of global gas properties derived with diagnostic diagrams, star formation rates based on H α , and physical properties derived from broadband photometry. Our models agree well with results from other photoionization models and are able to reproduce observed emission from H ii regions and star-forming galaxies. Our models show improved agreement with the observed H ii regions in the Ne iii/O ii plane and show satisfactory agreement with He ii emission from z = 2 galaxies, when including rotating stellar models. Models including post-asymptotic giant branch stars are able to reproduce line ratios consistent with low-ionization emission regions. The models are integrated into current versions of FSPS and include self-consistent nebular emission predictions for MIST and Padova+Geneva evolutionary tracks.

JuPOETs: a constrained multiobjective optimization approach to estimate biochemical model ensembles in the Julia programming language.

Science.gov (United States)

Bassen, David M; Vilkhovoy, Michael; Minot, Mason; Butcher, Jonathan T; Varner, Jeffrey D

2017-01-25

Ensemble modeling is a promising approach for obtaining robust predictions and coarse grained population behavior in deterministic mathematical models. Ensemble approaches address model uncertainty by using parameter or model families instead of single best-fit parameters or fixed model structures. Parameter ensembles can be selected based upon simulation error, along with other criteria such as diversity or steady-state performance. Simulations using parameter ensembles can estimate confidence intervals on model variables, and robustly constrain model predictions, despite having many poorly constrained parameters. In this software note, we present a multiobjective based technique to estimate parameter or models ensembles, the Pareto Optimal Ensemble Technique in the Julia programming language (JuPOETs). JuPOETs integrates simulated annealing with Pareto optimality to estimate ensembles on or near the optimal tradeoff surface between competing training objectives. We demonstrate JuPOETs on a suite of multiobjective problems, including test functions with parameter bounds and system constraints as well as for the identification of a proof-of-concept biochemical model with four conflicting training objectives. JuPOETs identified optimal or near optimal solutions approximately six-fold faster than a corresponding implementation in Octave for the suite of test functions. For the proof-of-concept biochemical model, JuPOETs produced an ensemble of parameters that gave both the mean of the training data for conflicting data sets, while simultaneously estimating parameter sets that performed well on each of the individual objective functions. JuPOETs is a promising approach for the estimation of parameter and model ensembles using multiobjective optimization. JuPOETs can be adapted to solve many problem types, including mixed binary and continuous variable types, bilevel optimization problems and constrained problems without altering the base algorithm. JuPOETs is open

The pulsar contribution to the diffuse galactic gamma-ray emission

DEFF Research Database (Denmark)

Pohl, M.; Kanbach, G.; Hunter, S.D.

1997-01-01

There is active interest in the extent to which unresolved gamma-ray pulsars contribute to the Galactic diffuse emission, and in whether unresolved gamma-ray pulsars could be responsible for the excess of diffuse Galactic emission above 1 GeV that has been observed by EGRET. The diffuse gamma......-ray intensity due to unresolved pulsars is directly linked to the number of objects that should be observed in the EGRET data. We can therefore use our knowledge of the unidentified EGRET sources to constrain model parameters like the pulsar birthrate and their beaming angle. This analysis is based only...... on the properties of the six pulsars that have been identified in the EGRET data and is independent of choice of a pulsar emission model. We find that pulsars contribute very little to the diffuse emission at lower energies, whereas above 1 GeV they can account for 18% of the observed intensity in selected regions...

Air Quality Modelling and the National Emission Database

DEFF Research Database (Denmark)

Jensen, S. S.

The project focuses on development of institutional strengthening to be able to carry out national air emission inventories based on the CORINAIR methodology. The present report describes the link between emission inventories and air quality modelling to ensure that the new national air emission...... inventory is able to take into account the data requirements of air quality models...

Global emissions and models of photochemically active compounds

International Nuclear Information System (INIS)

Penner, J.E.; Atherton, C.S.; Graedel, T.E.

1993-01-01

Anthropogenic emissions from industrial activity, fossil fuel combustion, and biomass burning are now known to be large enough (relative to natural sources) to perturb the chemistry of vast regions of the troposphere. A goal of the IGAC Global Emissions Inventory Activity (GEIA) is to provide authoritative and reliable emissions inventories on a 1 degree x 1 degree grid. When combined with atmospheric photochemical models, these high quality emissions inventories may be used to predict the concentrations of major photochemical products. Comparison of model results with measurements of pertinent species allows us to understand whether there are major shortcomings in our understanding of tropospheric photochemistry, the budgets and transport of trace species, and their effects in the atmosphere. Through this activity, we are building the capability to make confident predictions of the future consequences of anthropogenic emissions. This paper compares IGAC recommended emissions inventories for reactive nitrogen and sulfur dioxide to those that have been in use previously. We also present results from the three-dimensional LLNL atmospheric chemistry model that show how emissions of anthropogenic nitrogen oxides might potentially affect tropospheric ozone and OH concentrations and how emissions of anthropogenic sulfur increase sulfate aerosol loadings

Constrained parameterisation of photosynthetic capacity causes significant increase of modelled tropical vegetation surface temperature

Science.gov (United States)

Kattge, J.; Knorr, W.; Raddatz, T.; Wirth, C.

2009-04-01

Photosynthetic capacity is one of the most sensitive parameters of terrestrial biosphere models whose representation in global scale simulations has been severely hampered by a lack of systematic analyses using a sufficiently broad database. Due to its coupling to stomatal conductance changes in the parameterisation of photosynthetic capacity may potentially influence transpiration rates and vegetation surface temperature. Here, we provide a constrained parameterisation of photosynthetic capacity for different plant functional types in the context of the photosynthesis model proposed by Farquhar et al. (1980), based on a comprehensive compilation of leaf photosynthesis rates and leaf nitrogen content. Mean values of photosynthetic capacity were implemented into the coupled climate-vegetation model ECHAM5/JSBACH and modelled gross primary production (GPP) is compared to a compilation of independent observations on stand scale. Compared to the current standard parameterisation the root-mean-squared difference between modelled and observed GPP is substantially reduced for almost all PFTs by the new parameterisation of photosynthetic capacity. We find a systematic depression of NUE (photosynthetic capacity divided by leaf nitrogen content) on certain tropical soils that are known to be deficient in phosphorus. Photosynthetic capacity of tropical trees derived by this study is substantially lower than standard estimates currently used in terrestrial biosphere models. This causes a decrease of modelled GPP while it significantly increases modelled tropical vegetation surface temperatures, up to 0.8°C. These results emphasise the importance of a constrained parameterisation of photosynthetic capacity not only for the carbon cycle, but also for the climate system.

DATA-CONSTRAINED CORONAL MASS EJECTIONS IN A GLOBAL MAGNETOHYDRODYNAMICS MODEL

Energy Technology Data Exchange (ETDEWEB)

Jin, M. [Lockheed Martin Solar and Astrophysics Lab, Palo Alto, CA 94304 (United States); Manchester, W. B.; Van der Holst, B.; Sokolov, I.; Tóth, G.; Gombosi, T. I. [Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI 48109 (United States); Mullinix, R. E.; Taktakishvili, A.; Chulaki, A., E-mail: jinmeng@lmsal.com, E-mail: chipm@umich.edu, E-mail: richard.e.mullinix@nasa.gov, E-mail: Aleksandre.Taktakishvili-1@nasa.gov [Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States)

2017-01-10

We present a first-principles-based coronal mass ejection (CME) model suitable for both scientific and operational purposes by combining a global magnetohydrodynamics (MHD) solar wind model with a flux-rope-driven CME model. Realistic CME events are simulated self-consistently with high fidelity and forecasting capability by constraining initial flux rope parameters with observational data from GONG, SOHO /LASCO, and STEREO /COR. We automate this process so that minimum manual intervention is required in specifying the CME initial state. With the newly developed data-driven Eruptive Event Generator using Gibson–Low configuration, we present a method to derive Gibson–Low flux rope parameters through a handful of observational quantities so that the modeled CMEs can propagate with the desired CME speeds near the Sun. A test result with CMEs launched with different Carrington rotation magnetograms is shown. Our study shows a promising result for using the first-principles-based MHD global model as a forecasting tool, which is capable of predicting the CME direction of propagation, arrival time, and ICME magnetic field at 1 au (see the companion paper by Jin et al. 2016a).

Affine Lie algebraic origin of constrained KP hierarchies

International Nuclear Information System (INIS)

Aratyn, H.; Gomes, J.F.; Zimerman, A.H.

1994-07-01

It is presented an affine sl(n+1) algebraic construction of the basic constrained KP hierarchy. This hierarchy is analyzed using two approaches, namely linear matrix eigenvalue problem on hermitian symmetric space and constrained KP Lax formulation and we show that these approaches are equivalent. The model is recognized to be generalized non-linear Schroedinger (GNLS) hierarchy and it is used as a building block for a new class of constrained KP hierarchies. These constrained KP hierarchies are connected via similarity-Backlund transformations and interpolate between GNLS and multi-boson KP-Toda hierarchies. The construction uncovers origin of the Toda lattice structure behind the latter hierarchy. (author). 23 refs

New Approach in Modelling Indonesian Peat Fire Emission

Science.gov (United States)

Putra, E. I.; Cochrane, M. A.; Saharjo, B.; Yokelson, R. J.; Stockwell, C.; Vetrita, Y.; Zhang, X.; Hagen, S. C.; Nurhayati, A. D.; Graham, L.

2017-12-01

Peat fires are a serious problem for Indonesia, producing devastating environmental effects and making the country the 3rd largest emitter of CO2. Extensive fires ravaged vast areas of peatlands in Sumatra, Kalimantan and Papua during the pronounced El-Nino of 2015, causing international concern when the resultant haze blanketed Indonesia and neighboring countries, severely impacting the health of millions of people. Our recent unprecedented in-situ studies of aerosol and gas emissions from 35 peat fires of varying depths near Palangka Raya, Central Kalimantan have documented the range and variability of emissions from these major fires. We strongly suggest revisions to previously recommended IPPC's emission factors (EFs) from peat fires, notably: CO2 (-8%), CH4 (-55%), NH3 (-86%), and CO (+39%). Our findings clearly showed that Indonesian carbon equivalent measurements (100 years) might have been 19% less than what current IPCC emission factors indicate. The results also demonstrate the toxic air quality in the area with HCN, which is almost only emitted by biomass burning, accounting for 0.28% and the carcinogenic compound formaldehyde 0.04% of emissions. However, considerable variation in emissions may exist between peat fires of different Indonesian peat formations, illustrating the need for additional regional field emissions measurements for parameterizing peatland emissions models for all of Indonesia's major peatland areas. Through the continuous mutual research collaboration between the Indonesian and USA scientists, we will implement our standardized field-based analyses of fuels, hydrology, peat burning characteristics and fire emissions to characterize the three major Indonesian peatland formations across four study provinces (Central Kalimantan, Riau, Jambi and West Papua). We will provide spatial and temporal drivers of the modeled emissions and validate them at a national level using biomass burning emissions estimations derived from Visible

Constraining the Q10 of respiration in water-limited environments

Science.gov (United States)

Collins, A.; Ryan, M. G.; Xu, C.; Grossiord, C.; Michaletz, S. T.; McDowell, N. G.

2016-12-01

If the current rate of greenhouse emissions remains constant over the next few decades, projections of climate change forecast increased atmospheric temperatures by a least 1.1°C by the end of the century. Warmer temperatures are expected to largely influence the exchange of energy, carbon and water between plants and the atmosphere. Several studies support that terrestrial ecosystems currently act as a major carbon sink, however warmer temperatures may amplify respiration processes and shift terrestrial ecosystems from a sink to a source of carbon in the future. Most Earth System Models incorporate the temperature dependence of plant respiration (Q10) to estimate and predict respiration processes and associated carbon fluxes. Using a temperature and precipitation manipulation experiment in natural conditions, we present evidence that this parameter is poorly constrained especially in water-limited environments. We discuss the utility of the Q10 framework and suggest improvements for this parameter along with trait-based approaches to better resolve models.

A cost-constrained model of strategic service quality emphasis in nursing homes.

Science.gov (United States)

Davis, M A; Provan, K G

1996-02-01

This study employed structural equation modeling to test the relationship between three aspects of the environmental context of nursing homes; Medicaid dependence, ownership status, and market demand, and two basic strategic orientations: low cost and differentiation based on service quality emphasis. Hypotheses were proposed and tested against data collected from a sample of nursing homes operating in a single state. Because of the overwhelming importance of cost control in the nursing home industry, a cost constrained strategy perspective was supported. Specifically, while the three contextual variables had no direct effect on service quality emphasis, the entire model was supported when cost control orientation was introduced as a mediating variable.

Constrained-path quantum Monte Carlo approach for non-yrast states within the shell model

Energy Technology Data Exchange (ETDEWEB)

Bonnard, J. [INFN, Sezione di Padova, Padova (Italy); LPC Caen, ENSICAEN, Universite de Caen, CNRS/IN2P3, Caen (France); Juillet, O. [LPC Caen, ENSICAEN, Universite de Caen, CNRS/IN2P3, Caen (France)

2016-04-15

The present paper intends to present an extension of the constrained-path quantum Monte Carlo approach allowing to reconstruct non-yrast states in order to reach the complete spectroscopy of nuclei within the interacting shell model. As in the yrast case studied in a previous work, the formalism involves a variational symmetry-restored wave function assuming two central roles. First, it guides the underlying Brownian motion to improve the efficiency of the sampling. Second, it constrains the stochastic paths according to the phaseless approximation to control sign or phase problems that usually plague fermionic QMC simulations. Proof-of-principle results in the sd valence space are reported. They prove the ability of the scheme to offer remarkably accurate binding energies for both even- and odd-mass nuclei irrespective of the considered interaction. (orig.)

The Far-Infrared Emission Line and Continuum Spectrum of the Seyfert Galaxy NGC 1068

Science.gov (United States)

Spinoglio, Luigi; Smith, Howard A.; Gonzalez-Alfonso, Eduardo; Fisher, Jacqueline

2005-01-01

We report on the analysis of the first complete far-infrared spectrum (43-197 microns) of the Seyfert 2 galaxy NGC 1068 as observed with the Long Wavelength Spectrometer (LWS) onboard the Infrared Space Observatory (ISO). In addition to the 7 expected ionic fine structure emission lines, the OH rotational lines at 79, 119 and 163 microns were all detected in emission, which is unique among galaxies with full LWS spectra, where the 119 micron line, where detected, is always in absorption. The observed line intensities were modelled together with IS0 Short Wavelength Spectrometer (SWS) and optical and ultraviolet line intensities from the literature, considering two independent emission components: the AGN component and the starburst component in the circumnuclear ring of approximately 3kpc in size. Using the UV to mid-IR emission line spectrum to constrain the nuclear ionizing continuum, we have confirmed previous results: a canonical power-law ionizing spectrum is a poorer fit than one with a deep absorption trough, while the presence of a big blue bump is ruled out. Based on the instantaneous starburst age of 5 Myr constrained by the Br gamma equivalent width in the starburst ring, and starburst synthesis models of the mid- and far-infrared fine-structure line emission, a low ionization parameter (U=10(exp -3.5)) and low densities (n=100 cm (exp -3)) are derived. Combining the AGN and starburst components, we succeed in modeling the overall UV to far-IR atomic spectrum of SGC 1068, reproducing the line fluxes to within a factor 2.0 on average with a standard deviation of 1.4. The OH 119 micron emission indicates that the line is collisionally excited, and arises in a warm and dense region. The OH emission has been modeled using spherically symmetric, non-local, non-LTE radiative transfer models. The models indicate that the bulk of the emission arises from the nuclear region, although some extended contribution from the starburst is not ruled out. The OH abundance

Electricity in a Climate-Constrained World

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-07-01

After experiencing a historic drop in 2009, electricity generation reached a record high in 2010, confirming the close linkage between economic growth and electricity usage. Unfortunately, CO2 emissions from electricity have also resumed their growth: Electricity remains the single-largest source of CO2 emissions from energy, with 11.7 billion tonnes of CO2 released in 2010. The imperative to 'decarbonise' electricity and improve end-use efficiency remains essential to the global fight against climate change. The IEA’s Electricity in a Climate-Constrained World provides an authoritative resource on progress to date in this area, including statistics related to CO2 and the electricity sector across ten regions of the world (supply, end-use and capacity additions). It also presents topical analyses on the challenge of rapidly curbing CO2 emissions from electricity. Looking at policy instruments, it focuses on emissions trading in China, using energy efficiency to manage electricity supply crises and combining policy instruments for effective CO2 reductions. On regulatory issues, it asks whether deregulation can deliver decarbonisation and assesses the role of state-owned enterprises in emerging economies. And from technology perspectives, it explores the rise of new end-uses, the role of electricity storage, biomass use in Brazil, and the potential of carbon capture and storage for ‘negative emissions’ electricity supply.

Chance-constrained programming models for capital budgeting with NPV as fuzzy parameters

Science.gov (United States)

Huang, Xiaoxia

2007-01-01

In an uncertain economic environment, experts' knowledge about outlays and cash inflows of available projects consists of much vagueness instead of randomness. Investment outlays and annual net cash flows of a project are usually predicted by using experts' knowledge. Fuzzy variables can overcome the difficulties in predicting these parameters. In this paper, capital budgeting problem with fuzzy investment outlays and fuzzy annual net cash flows is studied based on credibility measure. Net present value (NPV) method is employed, and two fuzzy chance-constrained programming models for capital budgeting problem are provided. A fuzzy simulation-based genetic algorithm is provided for solving the proposed model problems. Two numerical examples are also presented to illustrate the modelling idea and the effectiveness of the proposed algorithm.

COMPILATION OF REGIONAL TO GLOBAL INVENTORIES OF ANTHROPOGENIC EMISSIONS

International Nuclear Information System (INIS)

BENKOVITZ, C.M.

2002-01-01

The mathematical modeling of the transport and transformation of trace species in the atmosphere is one of the scientific tools currently used to assess atmospheric chemistry, air quality, and climatic conditions. From the scientific but also from the management perspectives accurate inventories of emissions of the trace species at the appropriate spatial, temporal, and species resolution are required. There are two general methodologies used to estimate regional to global emissions: bottom-up and top-down (also known as inverse modeling). Bottom-up methodologies to estimate industrial emissions are based on activity data, emission factors (amount of emissions per unit activity), and for some inventories additional parameters (such as sulfur content of fuels). Generally these emissions estimates must be given finer sectoral, spatial (usually gridded), temporal, and for some inventories species resolution. Temporal and spatial resolution are obtained via the use of surrogate information, such as population, land use, traffic counts, etc. which already exists in or can directly be converted to gridded form. Speciation factors have been and are being developed to speciate inventories of NO(sub x), particulate matter, and hydrocarbons. Top-down (inverse modeling) methodologies directly invert air quality measurements in terms of poorly known but critical parameters to constrain the emissions needed to explain these measurements; values of these parameters are usually computed using atmospheric transport models. Currently there are several strong limitations of inverse modeling, but the continued evolution of top-down estimates will be facilitated by the development of denser monitoring networks and by the massive amounts of data from satellite observations

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.)

Unilateral regulation of bilateral trade in greenhouse gas emission permits

International Nuclear Information System (INIS)

Rehdanz, Katrin; Tol, Richard S.J.

2005-01-01

This paper considers the coordination of domestic markets for tradable emission permits where countries determine their own emission reduction targets, using a two-country model. Linking such schemes is beneficial to both countries but may cause the exporting country to decrease its emission reduction target and export more permits. This in turn would not only reduce the costs for both countries as less emissions have to be reduced, but it also lowers the environmental benefits of the importing country. One price instrument (tariff) and two quantity instruments (discount, quota) to prevent the exporting country from issuing more permits are examined. Each instrument restricts trade and alters the terms of trade for the two countries. The importing country (and regulator) prefers an import tariff and an import quota to a carbon discount. If the exporting country releases additional permits, the importing country should not try to keep total emissions constant, as that would be ineffective and maybe even counterproductive. Instead, the importing country should aim to keep the total import constant; this would impose costs on the exporting country that are independent of the policy instrument; an import quota would be the cheapest option for the importing country. An import quota would also stress the idea of supplementary of the flexible mechanism as it increases the share of emissions reduced domestically. Compliance and liability issues constrain the market further. However, both the importing and the exporting country would prefer that the permit seller is liable in case of non-compliance, as sellers' liability would less constrain the market

Constrained Vapor Bubble Experiment

Science.gov (United States)

Gokhale, Shripad; Plawsky, Joel; Wayner, Peter C., Jr.; Zheng, Ling; Wang, Ying-Xi

2002-11-01

Microgravity experiments on the Constrained Vapor Bubble Heat Exchanger, CVB, are being developed for the International Space Station. In particular, we present results of a precursory experimental and theoretical study of the vertical Constrained Vapor Bubble in the Earth's environment. A novel non-isothermal experimental setup was designed and built to study the transport processes in an ethanol/quartz vertical CVB system. Temperature profiles were measured using an in situ PC (personal computer)-based LabView data acquisition system via thermocouples. Film thickness profiles were measured using interferometry. A theoretical model was developed to predict the curvature profile of the stable film in the evaporator. The concept of the total amount of evaporation, which can be obtained directly by integrating the experimental temperature profile, was introduced. Experimentally measured curvature profiles are in good agreement with modeling results. For microgravity conditions, an analytical expression, which reveals an inherent relation between temperature and curvature profiles, was derived.

MR constrained simultaneous reconstruction of activity and attenuation maps in brain TOF-PET/MR imaging

Energy Technology Data Exchange (ETDEWEB)

Mehranian, Abolfazl; Zaidi, Habib [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva (Switzerland)

2014-07-29

The maximum likelihood estimation of attenuation and activity (MLAA) algorithm has been proposed to jointly estimate activity and attenuation from emission data only. Salomon et al employed the MLAA to estimate activity and attenuation from time-of-flight PET data with spatial MR prior information on attenuation. Recently, we proposed a novel algorithm to impose both spatial and statistical constraints on attenuation estimation within the MLAA algorithm using Dixon MR images and a constrained Gaussian mixture model (GMM). In this study, we compare the proposed algorithm with MLAA and MLAA-Salomon in brain TOF-PET/MR imaging.

MR constrained simultaneous reconstruction of activity and attenuation maps in brain TOF-PET/MR imaging

International Nuclear Information System (INIS)

Mehranian, Abolfazl; Zaidi, Habib

2014-01-01

The maximum likelihood estimation of attenuation and activity (MLAA) algorithm has been proposed to jointly estimate activity and attenuation from emission data only. Salomon et al employed the MLAA to estimate activity and attenuation from time-of-flight PET data with spatial MR prior information on attenuation. Recently, we proposed a novel algorithm to impose both spatial and statistical constraints on attenuation estimation within the MLAA algorithm using Dixon MR images and a constrained Gaussian mixture model (GMM). In this study, we compare the proposed algorithm with MLAA and MLAA_Salomon in brain TOF-PET/MR imaging.

Modeling regional-scale wildland fire emissions with the wildland fire emissions information system

Science.gov (United States)

Nancy H.F. French; Donald McKenzie; Tyler Erickson; Benjamin Koziol; Michael Billmire; K. Endsley; Naomi K.Y. Scheinerman; Liza Jenkins; Mary E. Miller; Roger Ottmar; Susan Prichard

2014-01-01

As carbon modeling tools become more comprehensive, spatial data are needed to improve quantitative maps of carbon emissions from fire. The Wildland Fire Emissions Information System (WFEIS) provides mapped estimates of carbon emissions from historical forest fires in the United States through a web browser. WFEIS improves access to data and provides a consistent...

Gluon field strength correlation functions within a constrained instanton model

International Nuclear Information System (INIS)

Dorokhov, A.E.; Esaibegyan, S.V.; Maximov, A.E.; Mikhailov, S.V.

2000-01-01

We suggest a constrained instanton (CI) solution in the physical QCD vacuum which is described by large-scale vacuum field fluctuations. This solution decays exponentially at large distances. It is stable only if the interaction of the instanton with the background vacuum field is small and additional constraints are introduced. The CI solution is explicitly constructed in the ansatz form, and the two-point vacuum correlator of the gluon field strengths is calculated in the framework of the effective instanton vacuum model. At small distances the results are qualitatively similar to the single instanton case; in particular, the D 1 invariant structure is small, which is in agreement with the lattice calculations. (orig.)

Technical discussions on Emissions and Atmospheric Modeling (TEAM)

Science.gov (United States)

Frost, G. J.; Henderson, B.; Lefer, B. L.

2017-12-01

A new informal activity, Technical discussions on Emissions and Atmospheric Modeling (TEAM), aims to improve the scientific understanding of emissions and atmospheric processes by leveraging resources through coordination, communication and collaboration between scientists in the Nation's environmental agencies. TEAM seeks to close information gaps that may be limiting emission inventory development and atmospheric modeling and to help identify related research areas that could benefit from additional coordinated efforts. TEAM is designed around webinars and in-person meetings on particular topics that are intended to facilitate active and sustained informal communications between technical staff at different agencies. The first series of TEAM webinars focuses on emissions of nitrogen oxides, a criteria pollutant impacting human and ecosystem health and a key precursor of ozone and particulate matter. Technical staff at Federal agencies with specific interests in emissions and atmospheric modeling are welcome to participate in TEAM.

Uncertainties in emission estimates of greenhouse gases and air pollutants in China and India and their impacts on regional air quality

Science.gov (United States)

Saikawa, E.; Trail, M.; Young, C. L.; Zhong, M.; Avramov, A.; Kim, H.; Wu, Q.; Janssens-Maenhout, G. G. A.; Kurokawa, J. I.; Klimont, Z.; Wagner, F.; Naik, V.; Horowitz, L. W.; Zhao, Y.; Nagpure, A.; Gurjar, B.; Zhang, Q.

2017-12-01

Greenhouse gas and air pollutant precursor emissions have been increasing rapidly in both China and India, resulting in local to regional scale effects on air quality. Modelers use emission inventories to represent the temporal and spatial distribution of impacts of air pollutant emissions on regional and global air quality. However, large uncertainties exist in emission inventories. Quantification of uncertainties in emission estimates is essential to better understand the linkages among emissions, air quality, climate, and health. We use Monte Carlo methods to assess the uncertainties of the existing carbon dioxide (CO2), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOx), and particulate matter (PM) emission estimates for both China and India. We focus on the period between 2000 and 2008. In addition to national totals, we also analyze emissions from four source sectors, including industry, transport, power, and residential. We also assess differences in the existing emission estimates within each of the subnational regions. We find large disagreements among the existing inventories at disaggregated levels. We further assess the impact of these differences in emissions on air quality using a chemical transport model. More efforts are needed to constrain emissions, especially in the Indo-Gangetic Plains and in the East and Central regions of China, where large differences across emission inventories result in concomitant large differences in the simulated concentrations of PM and ozone. Our study also highlights the importance of constraining SO2, NOx, and NH3 emissions for secondary PM concentrations over China and India.

The DINA model as a constrained general diagnostic model: Two variants of a model equivalency.

Science.gov (United States)

von Davier, Matthias

2014-02-01

The 'deterministic-input noisy-AND' (DINA) model is one of the more frequently applied diagnostic classification models for binary observed responses and binary latent variables. The purpose of this paper is to show that the model is equivalent to a special case of a more general compensatory family of diagnostic models. Two equivalencies are presented. Both project the original DINA skill space and design Q-matrix using mappings into a transformed skill space as well as a transformed Q-matrix space. Both variants of the equivalency produce a compensatory model that is mathematically equivalent to the (conjunctive) DINA model. This equivalency holds for all DINA models with any type of Q-matrix, not only for trivial (simple-structure) cases. The two versions of the equivalency presented in this paper are not implied by the recently suggested log-linear cognitive diagnosis model or the generalized DINA approach. The equivalencies presented here exist independent of these recently derived models since they solely require a linear - compensatory - general diagnostic model without any skill interaction terms. Whenever it can be shown that one model can be viewed as a special case of another more general one, conclusions derived from any particular model-based estimates are drawn into question. It is widely known that multidimensional models can often be specified in multiple ways while the model-based probabilities of observed variables stay the same. This paper goes beyond this type of equivalency by showing that a conjunctive diagnostic classification model can be expressed as a constrained special case of a general compensatory diagnostic modelling framework. © 2013 The British Psychological Society.

OBSERVATION OF CORRELATED OPTICAL AND GAMMA EMISSIONS FROM GRB 081126

International Nuclear Information System (INIS)

Klotz, A.; Boer, M.; Gendre, B.; Atteia, J. L.; Coward, D. M.; Imerito, A. C.

2009-01-01

We present an analysis of time-resolved optical emissions observed from the gamma-ray burst GRB 081126 during the prompt phase. The analysis employed time-resolved photometry using optical data obtained by the TAROT telescope, using BAT data from the Swift spacecraft, and time-resolved spectroscopy at high energies from the GBM instrument onboard the Fermi spacecraft. The optical emission of GRB 081126 is found to be compatible with the second gamma emission pulse shifted by a positive time lag of 8.4 ± 3.9 s. This is the first well-resolved observation of a time lag between optical and gamma emissions during a gamma-ray burst. Our observations could potentially provide new constraints on the fireball model for gamma-ray burst early emissions. Furthermore, observations of time lags between optical and gamma ray photons provides an exciting opportunity to constrain quantum gravity theories.

A Correlated Optical and Gamma Emission from GRB 081126A

International Nuclear Information System (INIS)

Gendre, B.; Klotz, A.; Atteia, J. L.; Boeer, M.; Coward, D. M.; Imerito, A. C.

2010-01-01

We present an analysis of time-resolved optical emissions observed from the gamma-ray burst GRB 081126 during the prompt phase. The analysis employed time-resolved photometry using optical data obtained by the TAROT telescope, BAT data from the Swift spacecraft and time-resolved spectroscopy at high energies from the GBM instrument onboard the Fermi spacecraft. The optical emission of GRB 081126 is found to be compatible with the second gamma emission pulse shifted by a positive time-lag of 8.4±3.9 sec. This is the first well resolved observation of a time lag between optical and gamma emissions during a gamma-ray burst. Our observations could potentially provide new constraints on the fireball model for gamma ray burst early emissions. Furthermore, observations of time-lags between optical and gamma ray photons provides an exciting opportunity to constrain quantum gravity theories.

Application of the emission inventory model TEAM: Uncertainties in dioxin emission estimates for central Europe

NARCIS (Netherlands)

Pulles, M.P.J.; Kok, H.; Quass, U.

2006-01-01

This study uses an improved emission inventory model to assess the uncertainties in emissions of dioxins and furans associated with both knowledge on the exact technologies and processes used, and with the uncertainties of both activity data and emission factors. The annual total emissions for the

Stock management in hospital pharmacy using chance-constrained model predictive control.

Science.gov (United States)

Jurado, I; Maestre, J M; Velarde, P; Ocampo-Martinez, C; Fernández, I; Tejera, B Isla; Prado, J R Del

2016-05-01

One of the most important problems in the pharmacy department of a hospital is stock management. The clinical need for drugs must be satisfied with limited work labor while minimizing the use of economic resources. The complexity of the problem resides in the random nature of the drug demand and the multiple constraints that must be taken into account in every decision. In this article, chance-constrained model predictive control is proposed to deal with this problem. The flexibility of model predictive control allows taking into account explicitly the different objectives and constraints involved in the problem while the use of chance constraints provides a trade-off between conservativeness and efficiency. The solution proposed is assessed to study its implementation in two Spanish hospitals. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Constrained 3D Density Model of the Upper Crust from Gravity Data Interpretation for Central Costa Rica

Directory of Open Access Journals (Sweden)

Oscar H. Lücke

2010-01-01

Full Text Available The map of complete Bouguer anomaly of Costa Rica shows an elongated NW-SE trending gravity low in the central region. This gravity low coincides with the geographical region known as the Cordillera Volcánica Central. It is built by geologic and morpho-tectonic units which consist of Quaternary volcanic edifices. For quantitative interpretation of the sources of the anomaly and the characterization of fluid pathways and reservoirs of arc magmatism, a constrained 3D density model of the upper crust was designed by means of forward modeling. The density model is constrained by simplified surface geology, previously published seismic tomography and P-wave velocity models, which stem from wide-angle refraction seismic, as well as results from methods of direct interpretation of the gravity field obtained for this work. The model takes into account the effects and influence of subduction-related Neogene through Quaternary arc magmatism on the upper crust.

Bounds on the Capacity of Weakly constrained two-dimensional Codes

DEFF Research Database (Denmark)

Forchhammer, Søren

2002-01-01

Upper and lower bounds are presented for the capacity of weakly constrained two-dimensional codes. The maximum entropy is calculated for two simple models of 2-D codes constraining the probability of neighboring 1s as an example. For given models of the coded data, upper and lower bounds...... on the capacity for 2-D channel models based on occurrences of neighboring 1s are considered....

Modeling Dzyaloshinskii-Moriya Interaction at Transition Metal Interfaces: Constrained Moment versus Generalized Bloch Theorem

KAUST Repository

Dong, Yao-Jun

2017-10-29

Dzyaloshinskii-Moriya interaction (DMI) at Pt/Co interfaces is investigated theoretically using two different first principles methods. The first one uses the constrained moment method to build a spin spiral in real space, while the second method uses the generalized Bloch theorem approach to construct a spin spiral in reciprocal space. We show that although the two methods produce an overall similar total DMI energy, the dependence of DMI as a function of the spin spiral wavelength is dramatically different. We suggest that long-range magnetic interactions, that determine itinerant magnetism in transition metals, are responsible for this discrepancy. We conclude that the generalized Bloch theorem approach is more adapted to model DMI in transition metal systems, where magnetism is delocalized, while the constrained moment approach is mostly applicable to weak or insulating magnets, where magnetism is localized.

Modeling Dzyaloshinskii-Moriya Interaction at Transition Metal Interfaces: Constrained Moment versus Generalized Bloch Theorem

KAUST Repository

Dong, Yao-Jun; Belabbes, Abderrezak; Manchon, Aurelien

2017-01-01

Dzyaloshinskii-Moriya interaction (DMI) at Pt/Co interfaces is investigated theoretically using two different first principles methods. The first one uses the constrained moment method to build a spin spiral in real space, while the second method uses the generalized Bloch theorem approach to construct a spin spiral in reciprocal space. We show that although the two methods produce an overall similar total DMI energy, the dependence of DMI as a function of the spin spiral wavelength is dramatically different. We suggest that long-range magnetic interactions, that determine itinerant magnetism in transition metals, are responsible for this discrepancy. We conclude that the generalized Bloch theorem approach is more adapted to model DMI in transition metal systems, where magnetism is delocalized, while the constrained moment approach is mostly applicable to weak or insulating magnets, where magnetism is localized.

Constraining groundwater flow model with geochemistry in the FUA and Cabril sites. Use in the ENRESA 2000 PA exercise

International Nuclear Information System (INIS)

Samper, J.; Carrera, J.; Bajos, C.; Astudillo, J.; Santiago, J.L.

1999-01-01

Hydrogeochemical activities have been a key factor for the verification and constraining of the groundwater flow model developed for the safety assessment of the FUA Uranium mill tailings restoration and the Cabril L/ILW disposal facility. The lesson learned in both sites will be applied to the ground water transport modelling in the current PA exercises (ENRESA 2000). The groundwater flow model in the Cabril site, represents a low permeability fractured media, and was performed using the TRANSIN code series developed by UPC-ENRESA. The hydrogeochemical data obtained from systematic yearly sampling and analysis campaigns were successfully applied to distinguish between local and regional flow and young and old groundwater. The salinity content, mainly the chlorine anion content, was the most critical hydrogeochemical data for constraining the groundwater flow model. (author)

Spatial distribution of emissions to air - the SPREAD model

Energy Technology Data Exchange (ETDEWEB)

Plejdrup, M S; Gyldenkaerne, S

2011-04-15

The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark's obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously, a distribution on the 17x17 km EMEP grid has been set up and used in research projects combined with detailed distributions for a few sectors or sub-sectors e.g. a distribution for emissions from road traffic on 1x1 km resolution. SPREAD is developed to generate improved spatial emission data for e.g. air quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation of distributions for single sectors and for a number of sub-sectors and single sources as well. This report documents the methodologies in this first version of SPREAD and presents selected results. Further, a number of potential improvements for later versions of SPREAD are addressed and discussed. (Author)

Network-constrained Cournot models of liberalized electricity markets. The devil is in the details

Energy Technology Data Exchange (ETDEWEB)

Neuhoff, Karsten [Department of Applied Economics, Sidgwick Ave., University of Cambridge, CB3 9DE (United Kingdom); Barquin, Julian; Vazquez, Miguel [Instituto de Investigacion Tecnologica, Universidad Pontificia Comillas, c/Santa Cruz de Marcenado 26-28015 Madrid (Spain); Boots, Maroeska G. [Energy Research Centre of the Netherlands ECN, Badhuisweg 3, 1031 CM Amsterdam (Netherlands); Ehrenmann, Andreas [Judge Institute of Management, University of Cambridge, Trumpington Street, CB2 1AG (United Kingdom); Hobbs, Benjamin F. [Department of Geography and Environmental Engineering, Johns Hopkins University, Baltimore, MD 21218 (United States); Rijkers, Fieke A.M. [Contributed while at ECN, now at Nederlandse Mededingingsautoriteit (NMa), Dte, Postbus 16326, 2500 BH Den Haag (Netherlands)

2005-05-15

Numerical models of transmission-constrained electricity markets are used to inform regulatory decisions. How robust are their results? Three research groups used the same data set for the northwest Europe power market as input for their models. Under competitive conditions, the results coincide, but in the Cournot case, the predicted prices differed significantly. The Cournot equilibria are highly sensitive to assumptions about market design (whether timing of generation and transmission decisions is sequential or integrated) and expectations of generators regarding how their decisions affect transmission prices and fringe generation. These sensitivities are qualitatively similar to those predicted by a simple two-node model.

Methanol emissions from maize: Ontogenetic dependence to varying light conditions and guttation as an additional factor constraining the flux

Science.gov (United States)

Mozaffar, A.; Schoon, N.; Digrado, A.; Bachy, A.; Delaplace, P.; du Jardin, P.; Fauconnier, M.-L.; Aubinet, M.; Heinesch, B.; Amelynck, C.

2017-03-01

Because of its high abundance and long lifetime compared to other volatile organic compounds in the atmosphere, methanol (CH3OH) plays an important role in atmospheric chemistry. Even though agricultural crops are believed to be a large source of methanol, emission inventories from those crop ecosystems are still scarce and little information is available concerning the driving mechanisms for methanol production and emission at different developmental stages of the plants/leaves. This study focuses on methanol emissions from Zea mays L. (maize), which is vastly cultivated throughout the world. Flux measurements have been performed on young plants, almost fully grown leaves and fully grown leaves, enclosed in dynamic flow-through enclosures in a temperature and light-controlled environmental chamber. Strong differences in the response of methanol emissions to variations in PPFD (Photosynthetic Photon Flux Density) were noticed between the young plants, almost fully grown and fully grown leaves. Moreover, young maize plants showed strong emission peaks following light/dark transitions, for which guttation can be put forward as a hypothetical pathway. Young plants' average daily methanol fluxes exceeded by a factor of 17 those of almost fully grown and fully grown leaves when expressed per leaf area. Absolute flux values were found to be smaller than those reported in the literature, but in fair agreement with recent ecosystem scale flux measurements above a maize field of the same variety as used in this study. The flux measurements in the current study were used to evaluate the dynamic biogenic volatile organic compound (BVOC) emission model of Niinemets and Reichstein. The modelled and measured fluxes from almost fully grown leaves were found to agree best when a temperature and light dependent methanol production function was applied. However, this production function turned out not to be suitable for modelling the observed emissions from the young plants

Modeling emission rates and exposures from outdoor cooking

Science.gov (United States)

Edwards, Rufus; Princevac, Marko; Weltman, Robert; Ghasemian, Masoud; Arora, Narendra K.; Bond, Tami

2017-09-01

Approximately 3 billion individuals rely on solid fuels for cooking globally. For a large portion of these - an estimated 533 million - cooking is outdoors, where emissions from cookstoves pose a health risk to both cooks and other household and village members. Models that estimate emissions rates from stoves in indoor environments that would meet WHO air quality guidelines (AQG), explicitly don't account for outdoor cooking. The objectives of this paper are to link health based exposure guidelines with emissions from outdoor cookstoves, using a Monte Carlo simulation of cooking times from Haryana India coupled with inverse Gaussian dispersion models. Mean emission rates for outdoor cooking that would result in incremental increases in personal exposure equivalent to the WHO AQG during a 24-h period were 126 ± 13 mg/min for cooking while squatting and 99 ± 10 mg/min while standing. Emission rates modeled for outdoor cooking are substantially higher than emission rates for indoor cooking to meet AQG, because the models estimate impact of emissions on personal exposure concentrations rather than microenvironment concentrations, and because the smoke disperses more readily outdoors compared to indoor environments. As a result, many more stoves including the best performing solid-fuel biomass stoves would meet AQG when cooking outdoors, but may also result in substantial localized neighborhood pollution depending on housing density. Inclusion of the neighborhood impact of pollution should be addressed more formally both in guidelines on emissions rates from stoves that would be protective of health, and also in wider health impact evaluation efforts and burden of disease estimates. Emissions guidelines should better represent the different contexts in which stoves are being used, especially because in these contexts the best performing solid fuel stoves have the potential to provide significant benefits.

Evaluation of green house gas emissions models.

Science.gov (United States)

2014-11-01

The objective of the project is to evaluate the GHG emissions models used by transportation agencies and industry leaders. Factors in the vehicle : operating environment that may affect modal emissions, such as, external conditions, : vehicle fleet c...

The soft-X-ray emission of Ark 120. XMM-Newton, NuSTAR, and the importance of taking the broad view

DEFF Research Database (Denmark)

Matt, G.; Marinucci, A.; Guainazzi, M.

2014-01-01

We present simultaneous XMM-Newton and NuSTAR observations of the 'bare' Seyfert 1 galaxy, Ark 120, a system in which ionized absorption is absent. The NuSTAR hard-X-ray spectral coverage allows us to constrain different models for the excess soft-X-ray emission. Among phenomenological models, a ...

Historical gaseous and primary aerosol emissions in the United States from 1990 to 2010

Directory of Open Access Journals (Sweden)

J. Xing

2013-08-01

Full Text Available An accurate description of emissions is crucial for model simulations to reproduce and interpret observed phenomena over extended time periods. In this study, we used an approach based on activity data to develop a consistent series of spatially resolved emissions in the United States from 1990 to 2010. The state-level anthropogenic emissions of SO2, NOx, CO, NMVOC (non-methane volatile organic compounds, NH3, PM10 and PM2.5 for a total of 49 sectors were estimated based on several long-term databases containing information about activities and emission controls. Activity data for energy-related stationary sources were derived from the State Energy Data System. Corresponding emission factors reflecting implemented emission controls were calculated back from the National Emissions Inventory (NEI for seven years (i.e., 1990, 1995, 1996, 1999, 2001, 2002 and 2005, and constrained by the AP-42 (US EPA's Compilation of Air Pollutant Emissions Factors dataset. Activity data for mobile sources including different types of highway vehicles and non-highway equipment were obtained from highway statistics reported by the Federal Highway Administration. The trends in emission factors for highway mobile source were informed by the 2011 National Transportation Statistics. Emissions for all non-energy-related sources were either scaled by the growth ratio of activity indicators or adjusted based on the NEI trends report. Because of the strengthened control efforts, particularly for the power sector and mobile sources, emissions of all pollutants except NH3 were reduced by half over the last two decades. The emission trends developed in this study are comparable with the NEI trend report and EDGAR (Emissions Database for Global Atmospheric Research data, but better constrained by trends in activity data. Reductions in SO2, NOx, CO and EC (speciation of PM2.5 by SMOKE, Sparse Matrix Operator Kernel Emissions emissions agree well with the observed changes in

Spatial distribution of emissions to air - the SPREAD model

Energy Technology Data Exchange (ETDEWEB)

Plejdrup, M.S.; Gyldenkaerne, S.

2011-04-15

The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark's obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously, a distribution on the 17x17 km EMEP grid has been set up and used in research projects combined with detailed distributions for a few sectors or sub-sectors e.g. a distribution for emissions from road traffic on 1x1 km resolution. SPREAD is developed to generate improved spatial emission data for e.g. air quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation of distributions for single sectors and for a number of sub-sectors and single sources as well. This report documents the methodologies in this first version of SPREAD and presents selected results. Further, a number of potential improvements for later versions of SPREAD are addressed and discussed. (Author)

Mathematical Model of the Emissions of a selected vehicle

Directory of Open Access Journals (Sweden)

Matušů Radim

2014-10-01

Full Text Available The article addresses the quantification of exhaust emissions from gasoline engines during transient operation. The main targeted emissions are carbon monoxide and carbon dioxide. The result is a mathematical model describing the production of individual emissions components in all modes (static and dynamic. It also describes the procedure for the determination of emissions from the engine’s operating parameters. The result is compared with other possible methods of measuring emissions. The methodology is validated using the data from an on-road measurement. The mathematical model was created on the first route and validated on the second route.

Constraining model parameters on remotely sensed evaporation: justification for distribution in ungauged basins?

Directory of Open Access Journals (Sweden)

H. C. Winsemius

2008-12-01

Full Text Available In this study, land surface related parameter distributions of a conceptual semi-distributed hydrological model are constrained by employing time series of satellite-based evaporation estimates during the dry season as explanatory information. The approach has been applied to the ungauged Luangwa river basin (150 000 (km² in Zambia. The information contained in these evaporation estimates imposes compliance of the model with the largest outgoing water balance term, evaporation, and a spatially and temporally realistic depletion of soil moisture within the dry season. The model results in turn provide a better understanding of the information density of remotely sensed evaporation. Model parameters to which evaporation is sensitive, have been spatially distributed on the basis of dominant land cover characteristics. Consequently, their values were conditioned by means of Monte-Carlo sampling and evaluation on satellite evaporation estimates. The results show that behavioural parameter sets for model units with similar land cover are indeed clustered. The clustering reveals hydrologically meaningful signatures in the parameter response surface: wetland-dominated areas (also called dambos show optimal parameter ranges that reflect vegetation with a relatively small unsaturated zone (due to the shallow rooting depth of the vegetation which is easily moisture stressed. The forested areas and highlands show parameter ranges that indicate a much deeper root zone which is more drought resistent. Clustering was consequently used to formulate fuzzy membership functions that can be used to constrain parameter realizations in further calibration. Unrealistic parameter ranges, found for instance in the high unsaturated soil zone values in the highlands may indicate either overestimation of satellite-based evaporation or model structural deficiencies. We believe that in these areas, groundwater uptake into the root zone and lateral movement of

THE ROLE OF THE DIFFUSIVE PROTONS IN THE GAMMA-RAY EMISSION OF SUPERNOVA REMNANT RX J1713.7–3946—A TWO-ZONE MODEL

Energy Technology Data Exchange (ETDEWEB)

Zhang, Xiao; Chen, Yang [Department of Astronomy, Nanjing University, 163 Xianlin Avenue, Nanjing 210023 (China)

2016-04-10

RX J1713.7−3946 is a prototype in the γ-ray-bright supernova remnants (SNRs) and is in continuing debates on its hadronic versus leptonic origin of the γ-ray emission. We explore the role played by the diffusive relativistic protons that escape from the SNR shock wave in the γ-ray emission, apart from the high-energy particles’ emission from the inside of the SNR. In the scenario that the SNR shock propagates in a clumpy molecular cavity, we consider that the γ-ray emission from the inside of the SNR may arise either from the inverse Compton scattering or from the interaction between the trapped energetic protons and the shocked clumps. The dominant origin between them depends on the electron-to-proton number ratio. The diffusive protons that escaped from the shock wave during the expansion history can provide an outer hadronic γ-ray component by bombarding the surrounding dense matter. The broadband spectrum can be well explained by this two-zone model, in which the γ-ray emission from the inside governs the TeV band, while the outer emission component substantially contributes to the GeV γ-rays. The two-zone model can also explain the TeV γ-ray radial brightness profile that significantly stretches beyond the nonthermal X-ray-emitting region. In the calculation, we present a simplified algorithm for Li and Chen's “accumulative diffusion” model for escaping protons and apply the Markov Chain Monte Carlo method to constrain the physical parameters.

Optimizing Fukushima Emissions Through Pattern Matching and Genetic Algorithms

Science.gov (United States)

Lucas, D. D.; Simpson, M. D.; Philip, C. S.; Baskett, R.

2017-12-01

Hazardous conditions during the Fukushima Daiichi nuclear power plant (NPP) accident hindered direct observations of the emissions of radioactive materials into the atmosphere. A wide range of emissions are estimated from bottom-up studies using reactor inventories and top-down approaches based on inverse modeling. We present a new inverse modeling estimate of cesium-137 emitted from the Fukushima NPP. Our estimate considers weather uncertainty through a large ensemble of Weather Research and Forecasting model simulations and uses the FLEXPART atmospheric dispersion model to transport and deposit cesium. The simulations are constrained by observations of the spatial distribution of cumulative cesium deposited on the surface of Japan through April 2, 2012. Multiple spatial metrics are used to quantify differences between observed and simulated deposition patterns. In order to match the observed pattern, we use a multi-objective genetic algorithm to optimize the time-varying emissions. We find that large differences with published bottom-up estimates are required to explain the observations. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Assessing Uncertainties in Gridded Emissions: A Case Study for Fossil Fuel Carbon Dioxide (FFCO2) Emission Data

Science.gov (United States)

Oda, T.; Ott, L.; Lauvaux, T.; Feng, S.; Bun, R.; Roman, M.; Baker, D. F.; Pawson, S.

2017-01-01

Fossil fuel carbon dioxide (CO2) emissions (FFCO2) are the largest input to the global carbon cycle on a decadal time scale. Because total emissions are assumed to be reasonably well constrained by fuel statistics, FFCO2 often serves as a reference in order to deduce carbon uptake by poorly understood terrestrial and ocean sinks. Conventional atmospheric CO2 flux inversions solve for spatially explicit regional sources and sinks and estimate land and ocean fluxes by subtracting FFCO2. Thus, errors in FFCO2 can propagate into the final inferred flux estimates. Gridded emissions are often based on disaggregation of emissions estimated at national or regional level. Although national and regional total FFCO2 are well known, gridded emission fields are subject to additional uncertainties due to the emission disaggregation. Assessing such uncertainties is often challenging because of the lack of physical measurements for evaluation. We first review difficulties in assessing uncertainties associated with gridded FFCO2 emission data and present several approaches for evaluation of such uncertainties at multiple scales. Given known limitations, inter-emission data differences are often used as a proxy for the uncertainty. The popular approach allows us to characterize differences in emissions, but does not allow us to fully quantify emission disaggregation biases. Our work aims to vicariously evaluate FFCO2 emission data using atmospheric models and measurements. We show a global simulation experiment where uncertainty estimates are propagated as an atmospheric tracer (uncertainty tracer) alongside CO2 in NASA's GEOS model and discuss implications of FFCO2 uncertainties in the context of flux inversions. We also demonstrate the use of high resolution urban CO2 simulations as a tool for objectively evaluating FFCO2 data over intense emission regions. Though this study focuses on FFCO2 emission data, the outcome of this study could also help improve the knowledge of similar

Development of combined low-emissions burner devices for low-power boilers

Science.gov (United States)

Roslyakov, P. V.; Proskurin, Yu. V.; Khokhlov, D. A.

2017-08-01

Low-power water boilers are widely used for autonomous heat supply in various industries. Firetube and water-tube boilers of domestic and foreign manufacturers are widely represented on the Russian market. However, even Russian boilers are supplied with licensed foreign burner devices, which reduce their competitiveness and complicate operating conditions. A task of developing efficient domestic low-emissions burner devices for low-power boilers is quite acute. A characteristic property of ignition and fuel combustion in such boilers is their flowing in constrained conditions due to small dimensions of combustion chambers and flame tubes. These processes differ significantly from those in open combustion chambers of high-duty power boilers, and they have not been sufficiently studied yet. The goals of this paper are studying the processes of ignition and combustion of gaseous and liquid fuels, heat and mass transfer and NO x emissions in constrained conditions, and the development of a modern combined low-emissions 2.2 MW burner device that provides efficient fuel combustion. A burner device computer model is developed and numerical studies of its operation on different types of fuel in a working load range from 40 to 100% of the nominal are carried out. The main features of ignition and combustion of gaseous and liquid fuels in constrained conditions of the flame tube at nominal and decreased loads are determined, which differ fundamentally from the similar processes in steam boiler furnaces. The influence of the burner devices design and operating conditions on the fuel underburning and NO x formation is determined. Based on the results of the design studies, a design of the new combined low-emissions burner device is proposed, which has several advantages over the prototype.

VIRTIS on Venus Express thermal emission spectra near 1μm

Science.gov (United States)

Mueller, Nils; Tsang, Constantine; Helbert, Joern; Smrekar, Suzanne; Piccioni, Giuseppe; Drossart, Pierre

2016-10-01

Thermal emission from the surface of Venus is observable through narrow spectral windows close to 1μm. Surface temperature is strongly constrained by surface elevation, due to the thick and dense atmosphere. The data from Visible and InfraRed Thermal Imaging Spectrometer VIRTIS on Venus Express together with altimetry constrain surface emissivity. In VIRTIS observations at 1.02μm, strongly deformed highland plateaus (tesserae) appear to have a lower emissivity consistent with continental crust, an interpretation that implies existence of an early ocean. Comparison between the Magellan stereo digital elevation model (DEM) and altimetry shows that the altimetry height error in rough tesserae greatly exceeds the formal error. In the one tesserae outlier covered by altimetry, DEM, and VIRTIS, the height error could account for the observed emissivity variation. The radiances observed at 1.10 and 1.18μm have a different response to topography, mostly due to spectrally varying absorption in the overlying atmospheric column. Thus if the tesserae have the same emissivity as volcanic plains, its spectrum should be the same as that of plains of the correct surface elevation. In order to investigate this statistically, we create a database of all long exposure duration VIRTIS spectra in the range of 1 - 1.4μm. The spectra are corrected for the ubiquitous straylight from the dayside, based on analysis of spectra showing deep space. Because the 1.10 and 1.18μm peaks are narrow compared to the variation of instrument spectral registration, we fit each spectrum with a synthetic spectrum from an atmospheric radiative transfer model, using wavelength offset and bandwidths as parameters in addition to atmospheric variables. This dataset of ~28 million thermal emission spectra spans a wide range of southern latitudes and night local times, and thus may be useful for studies beyond the question of surface emissivity. A portion of this research was conducted at the Jet Propulsion

Game theoretic analysis for carbon emission permits trading among multiple world regions with an optimizing global energy model; Saitekikagata sekai energy model ni motozuku tachiikikan CO2 haishutsu kyokasho torihiki no game ronteki bunseki

Energy Technology Data Exchange (ETDEWEB)

Akimoto, K.; Matsunaga, A.; Fujii, Y. [Yokohama National University, Yokohama (Japan); Yamaji, K. [The University of Tokyo, Tokyo (Japan)

1998-10-01

Carbon emissions which would cause global warming were agreed to be constrained at COP3 in Kyoto. In addition, carton emission permits trading was also approved to be introduced. The emission permits trading is expected to achieve efficient carbon emission reduction, equalizing the marginal costs of the emission reduction for the participating countries. In other words, the permits trading allows participants to reduce emissions where it is least expensive to do so. However, the inadequate introduction of the trading systems may impose unfairly greater burden on some countries, and therefore careful evaluation of the system would be indispensable for its implementation. In this paper, we attempt to analyze the emission permits trading. using the theory of cooperative games with a global energy model of optimization type. We assumed that seven world regions as players participate the permits trading system under the condition of the emission reduction target presented at COP3 and so on, and show the nucleolus of the grand coalition games, and the computational results of primary energy supplies and CO2 shadow prices. The insights of this research indicate that in order to stabilize the grand coalition, a noticeable amount of additional transfer of money would be needed besides the payments associated with the emission permits trading. 10 refs., 7 figs., 5 tabs.

Short-Term Power Plant GHG Emissions Forecasting Model

International Nuclear Information System (INIS)

Vidovic, D.

2016-01-01

In 2010, the share of greenhouse gas (GHG) emissions from power generation in the total emissions at the global level was about 25 percent. From January 1st, 2013 Croatian facilities have been involved in the European Union Emissions Trading System (EU ETS). The share of the ETS sector in total GHG emissions in Croatia in 2012 was about 30 percent, where power plants and heat generation facilities contributed to almost 50 percent. Since 2013 power plants are obliged to purchase all emission allowances. The paper describes the short-term climate forecasting model of greenhouse gas emissions from power plants while covering the daily load diagram of the system. Forecasting is done on an hourly domain typically for one day, it is possible and more days ahead. Forecasting GHG emissions in this way would enable power plant operators to purchase additional or sell surplus allowances on the market at the time. Example that describes the operation of the above mentioned forecasting model is given at the end of the paper.(author).

Constrained variability of modeled T:ET ratio across biomes

Science.gov (United States)

Fatichi, Simone; Pappas, Christoforos

2017-07-01

A large variability (35-90%) in the ratio of transpiration to total evapotranspiration (referred here as T:ET) across biomes or even at the global scale has been documented by a number of studies carried out with different methodologies. Previous empirical results also suggest that T:ET does not covary with mean precipitation and has a positive dependence on leaf area index (LAI). Here we use a mechanistic ecohydrological model, with a refined process-based description of evaporation from the soil surface, to investigate the variability of T:ET across biomes. Numerical results reveal a more constrained range and higher mean of T:ET (70 ± 9%, mean ± standard deviation) when compared to observation-based estimates. T:ET is confirmed to be independent from mean precipitation, while it is found to be correlated with LAI seasonally but uncorrelated across multiple sites. Larger LAI increases evaporation from interception but diminishes ground evaporation with the two effects largely compensating each other. These results offer mechanistic model-based evidence to the ongoing research about the patterns of T:ET and the factors influencing its magnitude across biomes.

Modelling of pesticide emissions for Life Cycle Inventory analysis: Model development, applications and implications

DEFF Research Database (Denmark)

Dijkman, Teunis Johannes

with variations in the climates and soils present in Europe. Emissions of pesticides to surface water and groundwater calculated by PestLCI 2.0 were compared with models used for risk assessment. Compared to the MACRO module in SWASH 3.1 model, which calculates surface water emissions by runoff and drainage...... chromatographic flow of water through the soil), which was attributed to the omission of emissions via macropore flow in the latter model. The comparison was complicated by the fact that the scenarios used were not fully identical. In order to quantify the implications of using PestLCI 2.0, human toxicity......The work presented in this thesis deals with quantification of pesticide emissions in the Life Cycle Inventory (LCI) analysis phase of Life Cycle Assessment (LCA). The motivation to model pesticide emissions is that reliable LCA results not only depend on accurate impact assessment models, but also...

Particle Reduction Strategies - PAREST. Traffic emission modelling. Model comparision and alternative scenarios. Sub-report

International Nuclear Information System (INIS)

Kugler, Ulrike; Theloke, Jochen; Joerss, Wolfram

2013-01-01

The modeling of the reference scenario and the various reduction scenarios in PAREST was based on the Central System of Emissions (CSE) (CSE, 2007). Emissions from road traffic were calculated by using the traffic emission model TREMOD (Knoerr et al., 2005) and fed into the CSE. The version TREMOD 4.17 has been used. The resulting emission levels in PAREST reference scenario were supplemented by the emission-reducing effect of the implementation of the future Euro 5 and 6 emission standards for cars and light commercial vehicles and Euro VI for heavy commercial vehicles in combination with the truck toll extension. [de

Sensitivity of modeled ozone concentrations to uncertainties in biogenic emissions

International Nuclear Information System (INIS)

Roselle, S.J.

1992-06-01

The study examines the sensitivity of regional ozone (O3) modeling to uncertainties in biogenic emissions estimates. The United States Environmental Protection Agency's (EPA) Regional Oxidant Model (ROM) was used to simulate the photochemistry of the northeastern United States for the period July 2-17, 1988. An operational model evaluation showed that ROM had a tendency to underpredict O3 when observed concentrations were above 70-80 ppb and to overpredict O3 when observed values were below this level. On average, the model underpredicted daily maximum O3 by 14 ppb. Spatial patterns of O3, however, were reproduced favorably by the model. Several simulations were performed to analyze the effects of uncertainties in biogenic emissions on predicted O3 and to study the effectiveness of two strategies of controlling anthropogenic emissions for reducing high O3 concentrations. Biogenic hydrocarbon emissions were adjusted by a factor of 3 to account for the existing range of uncertainty in these emissions. The impact of biogenic emission uncertainties on O3 predictions depended upon the availability of NOx. In some extremely NOx-limited areas, increasing the amount of biogenic emissions decreased O3 concentrations. Two control strategies were compared in the simulations: (1) reduced anthropogenic hydrocarbon emissions, and (2) reduced anthropogenic hydrocarbon and NOx emissions. The simulations showed that hydrocarbon emission controls were more beneficial to the New York City area, but that combined NOx and hydrocarbon controls were more beneficial to other areas of the Northeast. Hydrocarbon controls were more effective as biogenic hydrocarbon emissions were reduced, whereas combined NOx and hydrocarbon controls were more effective as biogenic hydrocarbon emissions were increased

Network-constrained Cournot models of liberalized electricity markets: the devil is in the details

Energy Technology Data Exchange (ETDEWEB)

Neuhoff, Karsten [Cambridge Univ., Dept. of Applied Economics, Cambridge (United Kingdom); Barquin, Julian; Vazquez, Miguel [Universidad Pontificia Comillas, Inst. de Investigacion Tecnologica, Madrid (Spain); Boots, Maroeska; Rijkers, Fieke A.M. [Energy Research Centre of the Netherlands ECN, Amsterdam (Netherlands); Ehrenmann, Andreas [Cambridge Univ., Judge Inst. of Management, Cambridge (United Kingdom); Hobbs, Benjamin F. [Johns Hopkins Univ., Dept. of Geography and Environmental Engineering, Baltimore, MD (United States)

2005-05-01

Numerical models of transmission-constrained electricity markets are used to inform regulatory decisions. How robust are their results? Three research groups used the same data set for the northwest Europe power market as input for their models. Under competitive conditions, the results coincide, but in the Cournot case, the predicted prices differed significantly. The Cournot equilibria are highly sensitive to assumptions about market design (whether timing of generation and transmission decisions is sequential or integrated) and expectations of generators regarding how their decisions affect transmission prices and fringe generation. These sensitivities are qualitatively similar to those predicted by a simple two-node model. (Author)

Network-constrained Cournot models of liberalized electricity markets: the devil is in the details

International Nuclear Information System (INIS)

Neuhoff, Karsten; Barquin, Julian; Vazquez, Miguel; Boots, Maroeska; Rijkers, Fieke A.M.; Ehrenmann, Andreas; Hobbs, Benjamin F.

2005-01-01

Numerical models of transmission-constrained electricity markets are used to inform regulatory decisions. How robust are their results? Three research groups used the same data set for the northwest Europe power market as input for their models. Under competitive conditions, the results coincide, but in the Cournot case, the predicted prices differed significantly. The Cournot equilibria are highly sensitive to assumptions about market design (whether timing of generation and transmission decisions is sequential or integrated) and expectations of generators regarding how their decisions affect transmission prices and fringe generation. These sensitivities are qualitatively similar to those predicted by a simple two-node model. (Author)

Global CO emission estimates inferred from assimilation of MOPITT and IASI CO data, together with observations of O3, NO2, HNO3, and HCHO.

Science.gov (United States)

Zhang, X.; Jones, D. B. A.; Keller, M.; Jiang, Z.; Bourassa, A. E.; Degenstein, D. A.; Clerbaux, C.; Pierre-Francois, C.

2017-12-01

Atmospheric carbon monoxide (CO) emissions estimated from inverse modeling analyses exhibit large uncertainties, due, in part, to discrepancies in the tropospheric chemistry in atmospheric models. We attempt to reduce the uncertainties in CO emission estimates by constraining the modeled abundance of ozone (O3), nitrogen dioxide (NO2), nitric acid (HNO3), and formaldehyde (HCHO), which are constituents that play a key role in tropospheric chemistry. Using the GEOS-Chem four-dimensional variational (4D-Var) data assimilation system, we estimate CO emissions by assimilating observations of CO from the Measurement of Pollution In the Troposphere (MOPITT) and the Infrared Atmospheric Sounding Interferometer (IASI), together with observations of O3 from the Optical Spectrograph and InfraRed Imager System (OSIRIS) and IASI, NO2 and HCHO from the Ozone Monitoring Instrument (OMI), and HNO3 from the Microwave Limb Sounder (MLS). Our experiments evaluate the inferred CO emission estimates from major anthropogenic, biomass burning and biogenic sources. Moreover, we also infer surface emissions of nitrogen oxides (NOx = NO + NO2) and isoprene. Our results reveal that this multiple species chemical data assimilation produces a chemical consistent state that effectively adjusts the CO-O3-OH coupling in the model. The O3-induced changes in OH are particularly large in the tropics. Overall, our analysis results in a better constrained tropospheric chemical state.

Constraining the models' response of tropical low clouds to SST forcings using CALIPSO observations

Science.gov (United States)

Cesana, G.; Del Genio, A. D.; Ackerman, A. S.; Brient, F.; Fridlind, A. M.; Kelley, M.; Elsaesser, G.

2017-12-01

Low-cloud response to a warmer climate is still pointed out as being the largest source of uncertainty in the last generation of climate models. To date there is no consensus among the models on whether the tropical low cloudiness would increase or decrease in a warmer climate. In addition, it has been shown that - depending on their climate sensitivity - the models either predict deeper or shallower low clouds. Recently, several relationships between inter-model characteristics of the present-day climate and future climate changes have been highlighted. These so-called emergent constraints aim to target relevant model improvements and to constrain models' projections based on current climate observations. Here we propose to use - for the first time - 10 years of CALIPSO cloud statistics to assess the ability of the models to represent the vertical structure of tropical low clouds for abnormally warm SST. We use a simulator approach to compare observations and simulations and focus on the low-layered clouds (i.e. z fraction. Vertically, the clouds deepen namely by decreasing the cloud fraction in the lowest levels and increasing it around the top of the boundary-layer. This feature is coincident with an increase of the high-level cloud fraction (z > 6.5km). Although the models' spread is large, the multi-model mean captures the observed variations but with a smaller amplitude. We then employ the GISS model to investigate how changes in cloud parameterizations affect the response of low clouds to warmer SSTs on the one hand; and how they affect the variations of the model's cloud profiles with respect to environmental parameters on the other hand. Finally, we use CALIPSO observations to constrain the model by determining i) what set of parameters allows reproducing the observed relationships and ii) what are the consequences on the cloud feedbacks. These results point toward process-oriented constraints of low-cloud responses to surface warming and environmental

Modelling nitrous oxide emissions from grazed grassland systems

International Nuclear Information System (INIS)

Wang Junye; Cardenas, Laura M.; Misselbrook, Tom H.; Cuttle, Steve; Thorman, Rachel E.; Li Changsheng

2012-01-01

Grazed grassland systems are an important component of the global carbon cycle and also influence global climate change through their emissions of nitrous oxide and methane. However, there are huge uncertainties and challenges in the development and parameterisation of process-based models for grazed grassland systems because of the wide diversity of vegetation and impacts of grazing animals. A process-based biogeochemistry model, DeNitrification-DeComposition (DNDC), has been modified to describe N 2 O emissions for the UK from regional conditions. This paper reports a new development of UK-DNDC in which the animal grazing practices were modified to track their contributions to the soil nitrogen (N) biogeochemistry. The new version of UK-DNDC was tested against datasets of N 2 O fluxes measured at three contrasting field sites. The results showed that the responses of the model to changes in grazing parameters were generally in agreement with observations, showing that N 2 O emissions increased as the grazing intensity increased. - Highlights: ► Parameterisation of grazing system using grazing intensity. ► Modification of UK D NDC for the UK soil and weather conditions. ► Validation of the UK D NDC against measured data of N 2 O emissions in three UK sites. ► Estimating influence of animal grazing practises on N 2 O emissions. - Grazing system was parameterised using grazing intensity and UK-DNDC model was modified and validated against measured data of N 2 O emissions in three UK sites.

Modeling Greenhouse Gas Emissions from Enteric Fermentation

NARCIS (Netherlands)

Kebreab, E.; Tedeschi, L.; Dijkstra, J.; Ellis, J.L.; Bannink, A.; France, J.

2016-01-01

Livestock directly contribute to greenhouse gas (GHG) emissions mainly through methane (CH4) and nitrous oxide (N2O) emissions. For cost and practicality reasons, quantification of GHG has been through development of various types of mathematical models. This chapter addresses the utility and

Isoprene emissions modelling for West Africa: MEGAN model evaluation and sensitivity analysis

Directory of Open Access Journals (Sweden)

J. Ferreira

2010-09-01

Full Text Available Isoprene emissions are the largest source of reactive carbon to the atmosphere, with the tropics being a major source region. These natural emissions are expected to change with changing climate and human impact on land use. As part of the African Monsoon Multidisciplinary Analyses (AMMA project the Model of Emissions of Gases and Aerosols from Nature (MEGAN has been used to estimate the spatial and temporal distribution of isoprene emissions over the West African region. During the AMMA field campaign, carried out in July and August 2006, isoprene mixing ratios were measured on board the FAAM BAe-146 aircraft. These data have been used to make a qualitative evaluation of the model performance.

MEGAN was firstly applied to a large area covering much of West Africa from the Gulf of Guinea in the south to the desert in the north and was able to capture the large scale spatial distribution of isoprene emissions as inferred from the observed isoprene mixing ratios. In particular the model captures the transition from the forested area in the south to the bare soils in the north, but some discrepancies have been identified over the bare soil, mainly due to the emission factors used. Sensitivity analyses were performed to assess the model response to changes in driving parameters, namely Leaf Area Index (LAI, Emission Factors (EF, temperature and solar radiation.

A high resolution simulation was made of a limited area south of Niamey, Niger, where the higher concentrations of isoprene were observed. This is used to evaluate the model's ability to simulate smaller scale spatial features and to examine the influence of the driving parameters on an hourly basis through a case study of a flight on 17 August 2006.

This study highlights the complex interactions between land surface processes and the meteorological dynamics and chemical composition of the PBL. This has implications for quantifying the impact of biogenic emissions

Small-kernel constrained-least-squares restoration of sampled image data

Science.gov (United States)

Hazra, Rajeeb; Park, Stephen K.

1992-10-01

Constrained least-squares image restoration, first proposed by Hunt twenty years ago, is a linear image restoration technique in which the restoration filter is derived by maximizing the smoothness of the restored image while satisfying a fidelity constraint related to how well the restored image matches the actual data. The traditional derivation and implementation of the constrained least-squares restoration filter is based on an incomplete discrete/discrete system model which does not account for the effects of spatial sampling and image reconstruction. For many imaging systems, these effects are significant and should not be ignored. In a recent paper Park demonstrated that a derivation of the Wiener filter based on the incomplete discrete/discrete model can be extended to a more comprehensive end-to-end, continuous/discrete/continuous model. In a similar way, in this paper, we show that a derivation of the constrained least-squares filter based on the discrete/discrete model can also be extended to this more comprehensive continuous/discrete/continuous model and, by so doing, an improved restoration filter is derived. Building on previous work by Reichenbach and Park for the Wiener filter, we also show that this improved constrained least-squares restoration filter can be efficiently implemented as a small-kernel convolution in the spatial domain.

Challenges and Conundrums in Modeling Global Methane Emissions from Wetlands: An Empiricist's Viewpoint

Science.gov (United States)

Bridgham, S. D.

2015-12-01

Wetlands emit a third to half of the global CH4 flux and have the largest uncertainty of any emission source. Moreover, wetlands have provided an important radiative feedback to climate in the geologic and recent past. A number of largescale wetland CH4 models have been developed recently, but intermodel comparisons show wide discrepancies in their predictions. I present an empiricist's overview of the current limitations and challenges of more accurately modeling wetland CH4 emissions. One of the largest limitations is simply the poor knowledge of wetland area, with estimated global values varying by a more than a factor of three. The areas of seasonal and tropical wetlands are particularly poorly constrained. There are also few wetlands with complete, multi-year datasets for all of the input variables for many models, and this lack of data is particularly alarming in tropical wetlands given that they are arguably the single largest natural or anthropogenic global CH4 source. Almost all largescale CH4 models have little biogeochemical mechanistic detail and treat anaerobic carbon cycling in a highly simplified manner. The CH4:CO2 ratio in anaerobic carbon mineralization is a central parameter in many models, but is at most set at a few values with no mechanistic underpinning. However, empirical data show that this ratio varies by five orders of magnitude in different wetlands, and tropical wetlands appear to be particularly methanogenic, all for reasons that are very poorly understood. The predominance of the acetoclastic pathway of methanogenesis appears to be related to total CH4 production, but different methanogenesis pathways are generally not incorporated into models. Other important anaerobic processes such as humic substances acting as terminal electron acceptors, fermentation, homoacetogenesis, and anaerobic CH4 oxidation are also not included in most models despite evidence of their importance in empirical studies. Moreover, there has been an explosion

Development of a forecast model for global air traffic emissions

Energy Technology Data Exchange (ETDEWEB)

Schaefer, Martin

2012-07-01

The thesis describes the methodology and results of a simulation model that quantifies fuel consumption and emissions of civil air traffic. Besides covering historical emissions, the model aims at forecasting emissions in the medium-term future. For this purpose, simulation models of aircraft and engine types are used in combination with a database of global flight movements and assumptions about traffic growth, fleet rollover and operational aspects. Results from an application of the model include emissions of scheduled air traffic for the years 2000 to 2010 as well as forecasted emissions until the year 2030. In a baseline scenario of the forecast, input assumptions (e.g. traffic growth rates) are in line with predictions by the aircraft industry. Considering the effects of advanced technologies of the short-term and medium-term future, the forecast focusses on fuel consumption and emissions of nitric oxides. Calculations for historical air traffic additionally cover emissions of carbon monoxide, unburned hydrocarbons and soot. Results are validated against reference data including studies by the International Civil Aviation Organization (ICAO) and simulation results from international research projects. (orig.)

Use of stratigraphic models as soft information to constrain stochastic modeling of rock properties: Development of the GSLIB-Lynx integration module

International Nuclear Information System (INIS)

Cromer, M.V.; Rautman, C.A.

1995-10-01

Rock properties in volcanic units at Yucca Mountain are controlled largely by relatively deterministic geologic processes related to the emplacement, cooling, and alteration history of the tuffaceous lithologic sequence. Differences in the lithologic character of the rocks have been used to subdivide the rock sequence into stratigraphic units, and the deterministic nature of the processes responsible for the character of the different units can be used to infer the rock material properties likely to exist in unsampled regions. This report proposes a quantitative, theoretically justified method of integrating interpretive geometric models, showing the three-dimensional distribution of different stratigraphic units, with numerical stochastic simulation techniques drawn from geostatistics. This integration of soft, constraining geologic information with hard, quantitative measurements of various material properties can produce geologically reasonable, spatially correlated models of rock properties that are free from stochastic artifacts for use in subsequent physical-process modeling, such as the numerical representation of ground-water flow and radionuclide transport. Prototype modeling conducted using the GSLIB-Lynx Integration Module computer program, known as GLINTMOD, has successfully demonstrated the proposed integration technique. The method involves the selection of stratigraphic-unit-specific material-property expected values that are then used to constrain the probability function from which a material property of interest at an unsampled location is simulated

Modeling Aircraft Emissions for Regional-scale Air Quality: Adapting a New Global Aircraft Emissions Database for the U.S

Science.gov (United States)

Arunachalam, S.; Baek, B. H.; Vennam, P. L.; Woody, M. C.; Omary, M.; Binkowski, F.; Fleming, G.

2012-12-01

Commercial aircraft emit substantial amounts of pollutants during their complete activity cycle that ranges from landing-and-takeoff (LTO) at airports to cruising in upper elevations of the atmosphere, and affect both air quality and climate. Since these emissions are not uniformly emitted over the earth, and have substantial temporal and spatial variability, it is vital to accurately evaluate and quantify the relative impacts of aviation emissions on ambient air quality. Regional-scale air quality modeling applications do not routinely include these aircraft emissions from all cycles. Federal Aviation Administration (FAA) has developed the Aviation Environmental Design Tool (AEDT), a software system that dynamically models aircraft performance in space and time to calculate fuel burn and emissions from gate-to-gate for all commercial aviation activity from all airports globally. To process in-flight aircraft emissions and to provide a realistic representation of these for treatment in grid-based air quality models, we have developed an interface processor called AEDTproc that accurately distributes full-flight chorded emissions in time and space to create gridded, hourly model-ready emissions input data. Unlike the traditional emissions modeling approach of treating aviation emissions as ground-level sources or processing emissions only from the LTO cycles in regional-scale air quality studies, AEDTproc distributes chorded inventories of aircraft emissions during LTO cycles and cruise activities into a time-variant 3-D gridded structure. We will present results of processed 2006 global emissions from AEDT over a continental U.S. modeling domain to support a national-scale air quality assessment of the incremental impacts of aircraft emissions on surface air quality. This includes about 13.6 million flights within the U.S. out of 31.2 million flights globally. We will focus on assessing spatio-temporal variability of these commercial aircraft emissions, and

Freight from Space: Evaluating Freight Activity and Emissions Trends from Satellite Data

Science.gov (United States)

Bickford, E.; Holloway, T.; Oberman, J.; Janssen, M.

2012-12-01

Heavy duty diesel freight trucks are the fastest growing source of highway emissions in the U.S., with domestic freight tonnage projected to double by 2050. Highway diesel vehicles currently account for 42% of on-road emissions of nitrogen oxides (NOx), 58% of on-road fine particulate (PM2.5) emissions, and 21% of on-road carbon dioxide emissions. Because most surface air quality monitors are located in densely populated areas and not rural highways, it is difficult to use ground-based observations to validate spatial trends in transportation emissions. Therefore, we have employed satellite retrievals from the OMI instrument to inform surface freight transportation inventory estimates by validating modeled tropospheric vertical column total nitrogen dioxide (NO2) against satellite observations. For this research we built a roadway-by-roadway bottom-up diesel truck emissions inventory using GIS, the U.S. Federal Highway Administration's Freight Analysis Framework (FAF) activity dataset, and the U.S. Environmental Protection Agency's MOVES emissions model. We use freight rail emissions from the Eastern Regional Technical Advisory Committee (ERTAC), inventory emissions from the Lake Michigan's Air Directors Consortium (LADCO) and the EPA's Community Multiscale Air Qualiy (CMAQ) model to simulate ground-level and tropospheric column concentrations of NO2. We also use the combination of models and satellite data to evaluate weekday-weekend patterns of NO2 concentrations and the relative contributions of highway diesel vehicles, highway gasoline vehicles, and freight rail to transportation-related pollution. This research presents the first evaluation of surface freight transport from space-based observations. We find satellite retrievals of surface pollutants provide a useful data tool for evaluating air quality models and constraining emissions sources.

Taylor O(h³) Discretization of ZNN Models for Dynamic Equality-Constrained Quadratic Programming With Application to Manipulators.

Science.gov (United States)

Liao, Bolin; Zhang, Yunong; Jin, Long

2016-02-01

In this paper, a new Taylor-type numerical differentiation formula is first presented to discretize the continuous-time Zhang neural network (ZNN), and obtain higher computational accuracy. Based on the Taylor-type formula, two Taylor-type discrete-time ZNN models (termed Taylor-type discrete-time ZNNK and Taylor-type discrete-time ZNNU models) are then proposed and discussed to perform online dynamic equality-constrained quadratic programming. For comparison, Euler-type discrete-time ZNN models (called Euler-type discrete-time ZNNK and Euler-type discrete-time ZNNU models) and Newton iteration, with interesting links being found, are also presented. It is proved herein that the steady-state residual errors of the proposed Taylor-type discrete-time ZNN models, Euler-type discrete-time ZNN models, and Newton iteration have the patterns of O(h(3)), O(h(2)), and O(h), respectively, with h denoting the sampling gap. Numerical experiments, including the application examples, are carried out, of which the results further substantiate the theoretical findings and the efficacy of Taylor-type discrete-time ZNN models. Finally, the comparisons with Taylor-type discrete-time derivative model and other Lagrange-type discrete-time ZNN models for dynamic equality-constrained quadratic programming substantiate the superiority of the proposed Taylor-type discrete-time ZNN models once again.

Fuel conservation and GHG (Greenhouse gas) emissions mitigation scenarios for China’s passenger vehicle fleet

International Nuclear Information System (INIS)

Hao, Han; Wang, Hewu; Ouyang, Minggao

2011-01-01

Passenger vehicles are the main consumers of gasoline in China. We established a bottom-up model which focuses on the simulation of energy consumptions and greenhouse gas (GHG) emissions growth by China’s passenger vehicle fleet. The fuel conservation and GHG emissions mitigation effects of five measures including constraining vehicle registration, reducing vehicle travel, strengthening fuel consumption rate (FCR) limits, vehicle downsizing and promoting electric vehicle (EV) penetration were evaluated. Based on the combination of these measures, the fuel conservation and GHG emissions mitigation scenarios for China’s passenger vehicle fleet were analyzed. Under reference scenario with no measures implemented, the fuel consumptions and life cycle GHG emissions will reach 520 million tons of oil equivalent (Mtoe) and 2.15 billion tons in 2050, about 8.1 times the level in 2010. However, substantial fuel conservation can be achieved by implementing the measures. By implementing all five measures together, the fuel consumption will reach 138 Mtoe in 2030 and decrease to 126 Mtoe in 2050, which is only 37.1% and 24.3% of the consumption under reference scenario. Similar potential lies in GHG mitigation. The results and scenarios provided references for the Chinese government’s policy-making. -- Highlights: ► We established a bottom-up model to simulate the fuel consumptions and GHG (Greenhouse gas) emissions growth by China’s passenger vehicle fleet. ► Five measures including constraining vehicle registration, reducing vehicle travel, improving fuel efficiency, vehicle downsizing and promoting EV penetration were evaluated. ► The fuel conservation and GHG emissions mitigation scenarios for China’s passenger vehicle fleet were provided as references for policy-making.

Performance evaluation of four directional emissivity analytical models with thermal SAIL model and airborne images.

Science.gov (United States)

Ren, Huazhong; Liu, Rongyuan; Yan, Guangjian; Li, Zhao-Liang; Qin, Qiming; Liu, Qiang; Nerry, Françoise

2015-04-06

Land surface emissivity is a crucial parameter in the surface status monitoring. This study aims at the evaluation of four directional emissivity models, including two bi-directional reflectance distribution function (BRDF) models and two gap-frequency-based models. Results showed that the kernel-driven BRDF model could well represent directional emissivity with an error less than 0.002, and was consequently used to retrieve emissivity with an accuracy of about 0.012 from an airborne multi-angular thermal infrared data set. Furthermore, we updated the cavity effect factor relating to multiple scattering inside canopy, which improved the performance of the gap-frequency-based models.

Prescribed Grassland Burning Smoke Emission Measurements in the Northern Flint Hills Region

Science.gov (United States)

Wilkins, J. L.; Baker, K. R.; Landis, M.; Aurell, J.; Gullett, B.

2017-12-01

Historically, frequent wildfires were essential for the maintenance of native prairie fire adapted ecosystems. Today prescribed fires are used to control invasive woody species and potentially improve forage production in these same prairie ecosystems for the beef-cattle industry. The emission of primary particulate matter, secondary aerosol, ozone precursors, and air toxics from prescribed grassland burning operations has been implicated as drivers of downwind air quality problems across a multi-state area. A field study has been planned to quantify prescribed burn smoke emissions using both surface and aerial sampling platforms to better constrain emissions rates for organic and inorganic pollutants. Multiple prescribed burns on tallgrass prairie fields in the northern Flint Hills ecoregion are planned for March 2017 at the Konza Prairie Biological Station in Kansas. An array of measurement systems will be deployed to quantify a suite of continuous and integrated air pollution parameters, combustion conditions, meteorological parameters, and plume dynamics to calculate more accurate and condition-specific emission factors that will be used to better predict primary and secondary pollutants both locally and regionally. These emissions measurements will allow for evaluation and improvement of the U.S. Forest Service's Bluesky modeling framework which includes the Fire Emission Production Simulator (FEPS) and Fuel characterization classification system (FCCS). Elucidating grassland prescribed burning emission factors based on fuel type, loading, and environmental conditions is expected to provide an improved understanding of the impact of this land management practice on air quality in the greater Flint Hills region. It is also expected that measurements will be made to help constrain and develop better routines for fire plume rise, vertical allocation, and smoke optical properties.

Toward cognitively constrained models of language processing : A review

NARCIS (Netherlands)

Vogelzang, Margreet; Mills, Anne C.; Reitter, David; van Rij, Jacolien; Hendriks, Petra; van Rijn, Hedderik

2017-01-01

Language processing is not an isolated capacity, but is embedded in other aspects of our cognition. However, it is still largely unexplored to what extent and how language processing interacts with general cognitive resources. This question can be investigated with cognitively constrained

Methane emissions from rice paddies. Experiments and modelling

International Nuclear Information System (INIS)

Van Bodegom, P.M.

2000-01-01

This thesis describes model development and experimentation on the comprehension and prediction of methane (CH4) emissions from rice paddies. The large spatial and temporal variability in CH4 emissions and the dynamic non-linear relationships between processes underlying CH4 emissions impairs the applicability of empirical relations. Mechanistic concepts are therefore starting point of analysis throughout the thesis. The process of CH4 production was investigated by soil slurry incubation experiments at different temperatures and with additions of different electron donors and acceptors. Temperature influenced conversion rates and the competitiveness of microorganisms. The experiments were used to calibrate and validate a mechanistic model on CH4 production that describes competition for acetate and H2/CO2, inhibition effects and chemolithotrophic reactions. The redox sequence leading eventually to CH4 production was well predicted by the model, calibrating only the maximum conversion rates. Gas transport through paddy soil and rice plants was quantified by experiments in which the transport of SF6 was monitored continuously by photoacoustics. A mechanistic model on gas transport in a flooded rice system based on diffusion equations was validated by these experiments and could explain why most gases are released via plant mediated transport. Variability in root distribution led to highly variable gas transport. Experiments showed that CH4 oxidation in the rice rhizosphere was oxygen (O2) limited. Rice rhizospheric O2 consumption was dominated by chemical iron oxidation, and heterotrophic and methanotrophic respiration. The most abundant methanotrophs and heterotrophs were isolated and kinetically characterised. Based upon these experiments it was hypothesised that CH4 oxidation mainly occurred at microaerophilic, low acetate conditions not very close to the root surface. A mechanistic rhizosphere model that combined production and consumption of O2, carbon and iron

Global Emissions of Nitrous Oxide: Key Source Sectors, their Future Activities and Technical Opportunities for Emission Reduction

Science.gov (United States)

Winiwarter, W.; Höglund-Isaksson, L.; Klimont, Z.; Schöpp, W.; Amann, M.

2017-12-01

Nitrous oxide originates primarily from natural biogeochemical processes, but its atmospheric concentrations have been strongly affected by human activities. According to IPCC, it is the third largest contributor to the anthropogenic greenhouse gas emissions (after carbon dioxide and methane). Deep decarbonization scenarios, which are able to constrain global temperature increase within 1.5°C, require strategies to cut methane and nitrous oxide emissions on top of phasing out carbon dioxide emissions. Employing the Greenhouse gas and Air pollution INteractions and Synergies (GAINS) model, we have estimated global emissions of nitrous oxide until 2050. Using explicitly defined emission reduction technologies we demonstrate that, by 2030, about 26% ± 9% of the emissions can be avoided assuming full implementation of currently existing reduction technologies. Nearly a quarter of this mitigation can be achieved at marginal costs lower than 10 Euro/t CO2-eq with the chemical industry sector offering important reductions. Overall, the largest emitter of nitrous oxide, agriculture, also provides the largest emission abatement potentials. Emission reduction may be achieved by precision farming methods (variable rate technology) as well as by agrochemistry (nitrification inhibitors). Regionally, the largest emission reductions are achievable where intensive agriculture and industry are prevalent (production and application of mineral fertilizers): Centrally Planned Asia including China, North and Latin America, and South Asia including India. Further deep cuts in nitrous oxide emissions will require extending reduction efforts beyond strictly technological solutions, i.e., considering behavioral changes, including widespread adoption of "healthy diets" minimizing excess protein consumption.

Emissions and Air Quality Impacts of Freight Transportation

Science.gov (United States)

Bickford, Erica

the photochemically modeled WIFE inventory against satellite retrievals of NO2 from OMI showed better spatial agreement between WIFE and OMI compared to another diesel inventory (LADCO), however with larger bias and error, especially in urban areas. This preliminary analysis illustrates the utility of satellite data in evaluating air quality model performance, and constraining surface emissions estimates.

The Balance-of-Payments-Constrained Growth Model and the Limits to Export-Led Growth

Directory of Open Access Journals (Sweden)

Robert A. Blecker

2000-12-01

Full Text Available This paper discusses how A. P. Thirlwall's model of balance-of-payments-constrained growth can be adapted to analyze the idea of a "fallacy of composition" in the export-led growth strategy of many developing countries. The Deaton-Muellbauer model of the Almost Ideal Demand System (AIDS is used to represent the adding-up constraints on individual countries' exports, when they are all trying to export competing products to the same foreign markets (i.e. newly industrializing countries are exporting similar types of manufactured goods to the OECD countries. The relevance of the model to the recent financial crises in developing countries and policy alternatives for redirecting development strategies are also discussed.

Modelling emissions from natural gas flaring

Directory of Open Access Journals (Sweden)

G. Ezaina Umukoro

2017-04-01

Full Text Available The world today recognizes the significance of environmental sustainability to the development of nations. Hence, the role oil and gas industry plays in environmental degrading activities such as gas flaring is of global concern. This study presents material balance equations and predicts results for non-hydrocarbon emissions such as CO2, CO, NO, NO2, and SO2 etc. from flaring (combustion of 12 natural gas samples representing composition of natural gas of global origin. Gaseous emission estimates and pattern were modelled by coding material balance equations for six reaction types and combustion conditions with a computer program. On the average, anticipated gaseous emissions from flaring natural gas with an average annual global flaring rate 126 bcm per year (between 2000 and 2011 in million metric tonnes (mmt are 560 mmt, 48 mmt, 91 mmt, 93 mmt and 50 mmt for CO2, CO, NO, NO2 and SO2 respectively. This model predicted gaseous emissions based on the possible individual combustion types and conditions anticipated in gas flaring operation. It will assist in the effort by environmental agencies and all concerned to track and measure the extent of environmental pollution caused by gas flaring operations in the oil and gas industry.

An algorithm for mass matrix calculation of internally constrained molecular geometries

International Nuclear Information System (INIS)

Aryanpour, Masoud; Dhanda, Abhishek; Pitsch, Heinz

2008-01-01

Dynamic models for molecular systems require the determination of corresponding mass matrix. For constrained geometries, these computations are often not trivial but need special considerations. Here, assembling the mass matrix of internally constrained molecular structures is formulated as an optimization problem. Analytical expressions are derived for the solution of the different possible cases depending on the rank of the constraint matrix. Geometrical interpretations are further used to enhance the solution concept. As an application, we evaluate the mass matrix for a constrained molecule undergoing an electron-transfer reaction. The preexponential factor for this reaction is computed based on the harmonic model

An algorithm for mass matrix calculation of internally constrained molecular geometries.

Science.gov (United States)

Aryanpour, Masoud; Dhanda, Abhishek; Pitsch, Heinz

2008-01-28

Dynamic models for molecular systems require the determination of corresponding mass matrix. For constrained geometries, these computations are often not trivial but need special considerations. Here, assembling the mass matrix of internally constrained molecular structures is formulated as an optimization problem. Analytical expressions are derived for the solution of the different possible cases depending on the rank of the constraint matrix. Geometrical interpretations are further used to enhance the solution concept. As an application, we evaluate the mass matrix for a constrained molecule undergoing an electron-transfer reaction. The preexponential factor for this reaction is computed based on the harmonic model.

Modeling and predicting low-speed vehicle emissions as a function of driving kinematics.

Science.gov (United States)

Hao, Lijun; Chen, Wei; Li, Lei; Tan, Jianwei; Wang, Xin; Yin, Hang; Ding, Yan; Ge, Yunshan

2017-05-01

An instantaneous emission model was developed to model and predict the real driving emissions of the low-speed vehicles. The emission database used in the model was measured by using portable emission measurement system (PEMS) under actual traffic conditions in the rural area, and the characteristics of the emission data were determined in relation to the driving kinematics (speed and acceleration) of the low-speed vehicle. The input of the emission model is driving cycle, and the model requires instantaneous vehicle speed and acceleration levels as input variables and uses them to interpolate the pollutant emission rate maps to calculate the transient pollutant emission rates, which will be accumulated to calculate the total emissions released during the whole driving cycle. And the vehicle fuel consumption was determined through the carbon balance method. The model predicted the emissions and fuel consumption of an in-use low-speed vehicle type model, which agreed well with the measured data. Copyright © 2016. Published by Elsevier B.V.

Top-down Estimates of Isoprene Emissions in Australia Inferred from OMI Satellite Data.

Science.gov (United States)

Greenslade, J.; Fisher, J. A.; Surl, L.; Palmer, P. I.

2017-12-01

Australia is a global hotspot for biogenic isoprene emission factors predicted by process-based models such as the Model of Emissions of Gases and Aerosols from Nature (MEGAN). It is also prone to increasingly frequent temperature extremes that can drive episodically high emissions. Estimates of biogenic isoprene emissions from Australia are poorly constrained, with the frequently used MEGAN model overestimating emissions by a factor of 4-6 in some areas. Evaluating MEGAN and other models in Australia is difficult due to sparse measurements of emissions and their ensuing chemical products. In this talk, we will describe efforts to better quantify Australian isoprene emissions using top-down estimates based on formaldehyde (HCHO) observations from the OMI satellite instrument, combined with modelled isoprene to HCHO yields obtained from the GEOS-Chem chemical transport model. The OMI-based estimates are evaluated using in situ observations from field campaigns conducted in southeast Australia. We also investigate the impact on the inferred emission of horizontal resolution used for the yield calculations, particularly in regions on the boundary between low- and high-NOx chemistry. The prevalence of fire smoke plumes roughly halves the available satellite dataset over Australia for much of the year; however, seasonal averages remain robust. Preliminary results show that the top-down isoprene emissions are lower than MEGAN estimates by up to 90% in summer. The overestimates are greatest along the eastern coast, including areas surrounding Australia's major population centres in Sydney, Melbourne, and Brisbane. The coarse horizontal resolution of the model significantly affects the emissions estimates, as many biogenic emitting regions lie along narrow coastal stretches. Our results confirm previous findings that the MEGAN biogenic emission model is poorly calibrated for the Australian environment and suggests that chemical transport models driven by MEGAN are likely

Towards an Integrated Assessment Model for Tropospheric Ozone-Emission Inventories, Scenarios and Emission-control Options

OpenAIRE

Olsthoorn, X.

1994-01-01

IIASA intends to extend its RAINS model for addressing the issue of transboundary ozone air pollution. This requires the development of a VOC-emissions module, VOCs being precursors in ozone formation. The module should contain a Europe-wide emission inventory, a submodule for developing emission scenarios and a database of measures for VOC-emission control, including data about control effectiveness and control costs. It is recommended to use the forthcoming CORINAIR90 inventory for construc...

Vehicle-specific emissions modeling based upon on-road measurements.

Science.gov (United States)

Frey, H Christopher; Zhang, Kaishan; Rouphail, Nagui M

2010-05-01

Vehicle-specific microscale fuel use and emissions rate models are developed based upon real-world hot-stabilized tailpipe measurements made using a portable emissions measurement system. Consecutive averaging periods of one to three multiples of the response time are used to compare two semiempirical physically based modeling schemes. One scheme is based on internally observable variables (IOVs), such as engine speed and manifold absolute pressure, while the other is based on externally observable variables (EOVs), such as speed, acceleration, and road grade. For NO, HC, and CO emission rates, the average R(2) ranged from 0.41 to 0.66 for the former and from 0.17 to 0.30 for the latter. The EOV models have R(2) for CO(2) of 0.43 to 0.79 versus 0.99 for the IOV models. The models are sensitive to episodic events in driving cycles such as high acceleration. Intervehicle and fleet average modeling approaches are compared; the former account for microscale variations that might be useful for some types of assessments. EOV-based models have practical value for traffic management or simulation applications since IOVs usually are not available or not used for emission estimation.

Modeling of Particle Emission During Dry Orthogonal Cutting

Science.gov (United States)

Khettabi, Riad; Songmene, Victor; Zaghbani, Imed; Masounave, Jacques

2010-08-01

Because of the risks associated with exposure to metallic particles, efforts are being put into controlling and reducing them during the metal working process. Recent studies by the authors involved in this project have presented the effects of cutting speeds, workpiece material, and tool geometry on particle emission during dry machining; the authors have also proposed a new parameter, named the dust unit ( D u), for use in evaluating the quantity of particle emissions relative to the quantity of chips produced during a machining operation. In this study, a model for predicting the particle emission (dust unit) during orthogonal turning is proposed. This model, which is based on the energy approach combined with the microfriction and the plastic deformation of the material, takes into account the tool geometry, the properties of the worked material, the cutting conditions, and the chip segmentation. The model is validated using experimental results obtained during the orthogonal turning of 6061-T6 aluminum alloy, AISI 1018, AISI 4140 steels, and grey cast iron. A good agreement was found with experimental results. This model can help in designing strategies for reducing particle emission during machining processes, at the source.

The analysis and the three-dimensional, forward-fit modeling of the X-ray and the microwave emissions of major solar flares

Science.gov (United States)

Kuroda, Natsuha; Wang, Haimin; Gary, Dale E.

2017-08-01

It is well known that the time profiles of the hard X-ray (HXR) emission and the microwave (MW) emission during the impulsive phase of the solar flare are well correlated, and that their analysis can lead to the understandings of the flare-accelerated electrons. In this work, we first studied the source locations of seven distinct temporal peaks observed in HXR and MW lightcurves of the 2011-02-15 X2.2 flare using the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) and Nobeyama Radioheliograph. We found that the seven emission peaks did not come from seven spatially distinct sites in HXR and MW, but rather in HXR we observed a sudden change in location only between the second and the third peak, with the same pattern occurring, but evolving more slowly in MW, which is consistent with the tether-cutting model of solar flares. Next, we closely examine the widely-used notion of a "common population" of the accelerated electrons producing the HXR and the MW, which has been challenged by some studies suggesting the differences in the inferred energy spectral index and emitting energies of the HXR- and MW- producing electrons. We use the Non-linear Force Free Field model extrapolated from the observed photospheric magnetogram in the three-dimensional, multi-wavelength modeling platform GX Simulator, and attempt to create a unified electron population model that can simultaneously reproduce the observed X-ray and MW observations of the 2015-06-22 M6.5 flare. We constrain the model parameters by the observations made by the highest-resolving instruments currently available in two wavelengths, the RHESSI for X-ray and the Expanded Owens Valley Solar Array for MW. The results suggest that the X-ray emitting electron population model fits to the standard flare model with the broken, hardening power-law spectrum at ~300 keV that simultaneously produces the HXR footpoint emission and the MW high frequency emission, and also reveals that there could be a �

Ammonia emission model for whole farm evaluation of dairy production systems.

Science.gov (United States)

Rotz, C Alan; Montes, Felipe; Hafner, Sasha D; Heber, Albert J; Grant, Richard H

2014-07-01

Ammonia (NH) emissions vary considerably among farms as influenced by climate and management. Because emission measurement is difficult and expensive, process-based models provide an alternative for estimating whole farm emissions. A model that simulates the processes of NH formation, speciation, aqueous-gas partitioning, and mass transfer was developed and incorporated in a whole farm simulation model (the Integrated Farm System Model). Farm sources included manure on the floor of the housing facility, manure in storage (if used), field-applied manure, and deposits on pasture (if grazing is used). In a comprehensive evaluation of the model, simulated daily, seasonal, and annual emissions compared well with data measured over 2 yr for five free stall barns and two manure storages on dairy farms in the eastern United States. In a further comparison with published data, simulated and measured barn emissions were similar over differing barn designs, protein feeding levels, and seasons of the year. Simulated emissions from manure storage were also highly correlated with published emission data across locations, seasons, and different storage covers. For field applied manure, the range in simulated annual emissions normally bounded reported mean values for different manure dry matter contents and application methods. Emissions from pastures measured in northern Europe across seasons and fertilization levels were also represented well by the model. After this evaluation, simulations of a representative dairy farm in Pennsylvania illustrated the effects of animal housing and manure management on whole farm emissions and their interactions with greenhouse gas emissions, nitrate leaching, production costs, and farm profitability. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Constrained structural dynamic model verification using free vehicle suspension testing methods

Science.gov (United States)

Blair, Mark A.; Vadlamudi, Nagarjuna

1988-01-01

Verification of the validity of a spacecraft's structural dynamic math model used in computing ascent (or in the case of the STS, ascent and landing) loads is mandatory. This verification process requires that tests be carried out on both the payload and the math model such that the ensuing correlation may validate the flight loads calculations. To properly achieve this goal, the tests should be performed with the payload in the launch constraint (i.e., held fixed at only the payload-booster interface DOFs). The practical achievement of this set of boundary conditions is quite difficult, especially with larger payloads, such as the 12-ton Hubble Space Telescope. The development of equations in the paper will show that by exciting the payload at its booster interface while it is suspended in the 'free-free' state, a set of transfer functions can be produced that will have minima that are directly related to the fundamental modes of the payload when it is constrained in its launch configuration.

Constraint on the polarization of electric dipole emission from spinning dust

Energy Technology Data Exchange (ETDEWEB)

Hoang, Thiem; Martin, P. G. [Canadian Institute for Theoretical Astrophysics, University of Toronto, 60 St. George Street, Toronto, ON M5S 3H8 (Canada); Lazarian, A. [Department of Astronomy, University of Wisconsin-Madison, Madison, WI 53705 (United States)

2013-12-20

Planck results have revealed that the electric dipole emission from polycyclic aromatic hydrocarbons (PAHs) is the most reliable explanation for the anomalous microwave emission that interferes with cosmic microwave background (CMB) radiation experiments. The emerging question is to what extent this emission component contaminates the polarized CMB radiation. We present constraints on polarized dust emission for the model of grain-size distribution and grain alignment that best fits the observed extinction and polarization curves. Two stars with a prominent polarization feature at λ = 2175 Å—HD 197770 and HD 147933-4—are chosen for our study. For HD 197770, we find that the model with aligned silicate grains plus weakly aligned PAHs can successfully reproduce the 2175 Å polarization feature; in contrast, for HD 147933-4, we find that the alignment of only silicate grains can account for that feature. The alignment function of PAHs for the best-fit model to the HD 197770 data is used to constrain polarized spinning dust emission. We find that the degree of polarization of spinning dust emission is about 1.6% at frequency ν ≈ 3 GHz and declines to below 0.9% for ν > 20 GHz. We also predict the degree of polarization of thermal dust emission at 353 GHz to be P {sub em} ≈ 11% and 14% for the lines of sight to the HD 197770 and HD 147933-4 stars, respectively.

Data-Constrained Projections of Methane Fluxes in a Northern Minnesota Peatland in Response to Elevated CO2 and Warming

Science.gov (United States)

Ma, Shuang; Jiang, Jiang; Huang, Yuanyuan; Shi, Zheng; Wilson, Rachel M.; Ricciuto, Daniel; Sebestyen, Stephen D.; Hanson, Paul J.; Luo, Yiqi

2017-11-01

Large uncertainties exist in predicting responses of wetland methane (CH4) fluxes to future climate change. However, sources of the uncertainty have not been clearly identified despite the fact that methane production and emission processes have been extensively explored. In this study, we took advantage of manual CH4 flux measurements under ambient environment from 2011 to 2014 at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site and developed a data-informed process-based methane module. The module was incorporated into the Terrestrial ECOsystem (TECO) model before its parameters were constrained with multiple years of methane flux data for forecasting CH4 emission under five warming and two elevated CO2 treatments at SPRUCE. We found that 9°C warming treatments significantly increased methane emission by approximately 400%, and elevated CO2 treatments stimulated methane emission by 10.4%-23.6% in comparison with ambient conditions. The relative contribution of plant-mediated transport to methane emission decreased from 96% at the control to 92% at the 9°C warming, largely to compensate for an increase in ebullition. The uncertainty in plant-mediated transportation and ebullition increased with warming and contributed to the overall changes of emissions uncertainties. At the same time, our modeling results indicated a significant increase in the emitted CH4:CO2 ratio. This result, together with the larger warming potential of CH4, will lead to a strong positive feedback from terrestrial ecosystems to climate warming. The model-data fusion approach used in this study enabled parameter estimation and uncertainty quantification for forecasting methane fluxes.

Feasibility Assessment of a Fine-Grained Access Control Model on Resource Constrained Sensors.

Science.gov (United States)

Uriarte Itzazelaia, Mikel; Astorga, Jasone; Jacob, Eduardo; Huarte, Maider; Romaña, Pedro

2018-02-13

Upcoming smart scenarios enabled by the Internet of Things (IoT) envision smart objects that provide services that can adapt to user behavior or be managed to achieve greater productivity. In such environments, smart things are inexpensive and, therefore, constrained devices. However, they are also critical components because of the importance of the information that they provide. Given this, strong security is a requirement, but not all security mechanisms in general and access control models in particular are feasible. In this paper, we present the feasibility assessment of an access control model that utilizes a hybrid architecture and a policy language that provides dynamic fine-grained policy enforcement in the sensors, which requires an efficient message exchange protocol called Hidra. This experimental performance assessment includes a prototype implementation, a performance evaluation model, the measurements and related discussions, which demonstrate the feasibility and adequacy of the analyzed access control model.

Consistency checks in beam emission modeling for neutral beam injectors

International Nuclear Information System (INIS)

Punyapu, Bharathi; Vattipalle, Prahlad; Sharma, Sanjeev Kumar; Baruah, Ujjwal Kumar; Crowley, Brendan

2015-01-01

In positive neutral beam systems, the beam parameters such as ion species fractions, power fractions and beam divergence are routinely measured using Doppler shifted beam emission spectrum. The accuracy with which these parameters are estimated depend on the accuracy of the atomic modeling involved in these estimations. In this work, an effective procedure to check the consistency of the beam emission modeling in neutral beam injectors is proposed. As a first consistency check, at a constant beam voltage and current, the intensity of the beam emission spectrum is measured by varying the pressure in the neutralizer. Then, the scaling of measured intensity of un-shifted (target) and Doppler shifted intensities (projectile) of the beam emission spectrum at these pressure values are studied. If the un-shifted component scales with pressure, then the intensity of this component will be used as a second consistency check on the beam emission modeling. As a further check, the modeled beam fractions and emission cross sections of projectile and target are used to predict the intensity of the un-shifted component and then compared with the value of measured target intensity. An agreement between the predicted and measured target intensities provide the degree of discrepancy in the beam emission modeling. In order to test this methodology, a systematic analysis of Doppler shift spectroscopy data obtained on the JET neutral beam test stand data was carried out

A Hybrid Method for the Modelling and Optimisation of Constrained Search Problems

Directory of Open Access Journals (Sweden)

Sitek Pawel

2014-08-01

Full Text Available The paper presents a concept and the outline of the implementation of a hybrid approach to modelling and solving constrained problems. Two environments of mathematical programming (in particular, integer programming and declarative programming (in particular, constraint logic programming were integrated. The strengths of integer programming and constraint logic programming, in which constraints are treated in a different way and different methods are implemented, were combined to use the strengths of both. The hybrid method is not worse than either of its components used independently. The proposed approach is particularly important for the decision models with an objective function and many discrete decision variables added up in multiple constraints. To validate the proposed approach, two illustrative examples are presented and solved. The first example is the authors’ original model of cost optimisation in the supply chain with multimodal transportation. The second one is the two-echelon variant of the well-known capacitated vehicle routing problem.

CONSTRAINING GAMMA-RAY BURST EMISSION PHYSICS WITH EXTENSIVE EARLY-TIME, MULTIBAND FOLLOW-UP

International Nuclear Information System (INIS)

Cucchiara, A.; Cenko, S. B.; Bloom, J. S.; Morgan, A.; Perley, D. A.; Li, W.; Butler, N. R.; Filippenko, A. V.; Melandri, A.; Kobayashi, S.; Smith, R. J.; Mundell, C. G.; Steele, I. A.; Hora, J. L.; Da Silva, R. L.; Prochaska, J. X.; Worseck, G.; Fumagalli, M.; Milne, P. A.; Cobb, B.

2011-01-01

Understanding the origin and diversity of emission processes responsible for gamma-ray bursts (GRBs) remains a pressing challenge. While prompt and contemporaneous panchromatic observations have the potential to test predictions of the internal-external shock model, extensive multiband imaging has been conducted for only a few GRBs. We present rich, early-time, multiband data sets for two Swift events, GRB 110205A and GRB 110213A. The former shows optical emission since the early stages of the prompt phase, followed by the steep rising in flux up to ∼1000 s after the burst (t –α with α = –6.13 ± 0.75). We discuss this feature in the context of the reverse-shock scenario and interpret the following single power-law decay as being forward-shock dominated. Polarization measurements, obtained with the RINGO2 instrument mounted on the Liverpool Telescope, also provide hints on the nature of the emitting ejecta. The latter event, instead, displays a very peculiar optical to near-infrared light curve, with two achromatic peaks. In this case, while the first peak is probably due to the onset of the afterglow, we interpret the second peak to be produced by newly injected material, signifying a late-time activity of the central engine.

CONSTRAINING GAMMA-RAY BURST EMISSION PHYSICS WITH EXTENSIVE EARLY-TIME, MULTIBAND FOLLOW-UP

Energy Technology Data Exchange (ETDEWEB)

Cucchiara, A.; Cenko, S. B.; Bloom, J. S.; Morgan, A.; Perley, D. A.; Li, W.; Butler, N. R.; Filippenko, A. V. [Department of Astronomy, University of California, Berkeley, CA 94720-3411 (United States); Melandri, A. [INAF, Osservatorio Astronomicodi Brera, via E. Bianchi 46, I-23807 Merate (Saint Lucia) (Italy); Kobayashi, S.; Smith, R. J.; Mundell, C. G.; Steele, I. A. [Astrophysics Research Institute, Liverpool John Moores University, Twelve Quays House, Egerton Wharf, Birkenhead, CH41 1LD (United Kingdom); Hora, J. L. [Harvard-Smithsonian Center for Astrophysics, 60 Garden St., Cambridge, MA 02138 (United States); Da Silva, R. L.; Prochaska, J. X.; Worseck, G.; Fumagalli, M. [Department of Astronomy and Astrophysics, UCO/Lick Observatory, University of California, 1156 High Street, Santa Cruz, CA 95064 (United States); Milne, P. A. [Steward Observatory, University of Arizona, 933 N. Cherry Ave., Tucson, AZ 85719 (United States); Cobb, B., E-mail: acucchia@ucolick.org [Department of Physics, George Washington University, Corcoran 105, 725 21st St, NW, Washington, DC 20052 (United States); and others

2011-12-20

Understanding the origin and diversity of emission processes responsible for gamma-ray bursts (GRBs) remains a pressing challenge. While prompt and contemporaneous panchromatic observations have the potential to test predictions of the internal-external shock model, extensive multiband imaging has been conducted for only a few GRBs. We present rich, early-time, multiband data sets for two Swift events, GRB 110205A and GRB 110213A. The former shows optical emission since the early stages of the prompt phase, followed by the steep rising in flux up to {approx}1000 s after the burst (t{sup -{alpha}} with {alpha} = -6.13 {+-} 0.75). We discuss this feature in the context of the reverse-shock scenario and interpret the following single power-law decay as being forward-shock dominated. Polarization measurements, obtained with the RINGO2 instrument mounted on the Liverpool Telescope, also provide hints on the nature of the emitting ejecta. The latter event, instead, displays a very peculiar optical to near-infrared light curve, with two achromatic peaks. In this case, while the first peak is probably due to the onset of the afterglow, we interpret the second peak to be produced by newly injected material, signifying a late-time activity of the central engine.

Hard x-ray Morphological and Spectral Studies of the Galactic Center Molecular Cloud SGR B2: Constraining Past SGR A* Flaring Activity

DEFF Research Database (Denmark)

Zhang, Shuo; Hailey, Charles J.; Mori, Kaya

2015-01-01

In 2013, NuSTAR observed the Sgr B2 region and for the first time resolved its hard X-ray emission on subarcminute scales. Two prominent features are detected above 10 keV:. a newly emerging cloud, G0.66-0.13, and the central 90 '' radius region containing two compact cores, Sgr B2(M) and Sgr B2(N......), surrounded by diffuse emission. It is inconclusive whether the remaining level of Sgr. B2 emission is still decreasing or has reached a constant background level. A decreasing X-ray emission can be best explained by the X-ray reflection nebula scenario, where the cloud reprocesses a past giant outburst from...... Sgr A*. In the X-ray reflection nebula (XRN) scenario, the 3-79 keV Sgr. B2 spectrum allows us to self-consistently test the XRN model using both the Fe K alpha line and the continuum emission. The peak luminosity of the past Sgr A* outburst is constrained to L3-79keV∼5 x 1038 ergs s-1. A newly...

Evolutionary constrained optimization

CERN Document Server

Deb, Kalyanmoy

2015-01-01

This book makes available a self-contained collection of modern research addressing the general constrained optimization problems using evolutionary algorithms. Broadly the topics covered include constraint handling for single and multi-objective optimizations; penalty function based methodology; multi-objective based methodology; new constraint handling mechanism; hybrid methodology; scaling issues in constrained optimization; design of scalable test problems; parameter adaptation in constrained optimization; handling of integer, discrete and mix variables in addition to continuous variables; application of constraint handling techniques to real-world problems; and constrained optimization in dynamic environment. There is also a separate chapter on hybrid optimization, which is gaining lots of popularity nowadays due to its capability of bridging the gap between evolutionary and classical optimization. The material in the book is useful to researchers, novice, and experts alike. The book will also be useful...

Isoprene emissions over Asia 1979-2012: impact of climate and land use changes

Science.gov (United States)

Stavrakou, T.; Müller, J.-F.; Bauwens, M.; De Smedt, I.; Van Roozendael, M.; Guenther, A.; Wild, M.; Xia, X.

2013-11-01

Due to the scarcity of observational constraints and the rapidly changing environment in East and Southeast Asia, isoprene emissions predicted by models are expected to bear substantial uncertainties. The aim of this study is to improve upon the existing bottom-up estimates, and investigate the temporal evolution of the fluxes in Asia over 1979-2012. To this purpose, we calculate the hourly emissions at 0.5° × 0.5° resolution using the MEGAN-MOHYCAN model driven by ECMWF ERA-Interim climatology. This study incorporates (i) changes in land use, including the rapid expansion of oil palms, (ii) meteorological variability according to ERA-Interim, (iii) long-term changes in solar radiation (dimming/brightening) constrained by surface network radiation measurements, and (iv) recent experimental evidence that South Asian tropical forests are much weaker isoprene emitters than previously assumed, and on the other hand, that oil palms hold a strong isoprene emission capacity. These effects lead to a significant lowering (factor of two) in the total isoprene fluxes over the studied domain, and to emission reductions reaching a~factor of 3.5 in Southeast Asia. The bottom-up annual isoprene emissions for 2005 are estimated at 7.0, 4.8, 8.3, 2.9 Tg in China, India, Indonesia and Malaysia, respectively. Changes in temperature and solar radiation are the major drivers of the interannual variability and trend in the emissions. An annual positive flux trend of 0.2% and 0.52% is found in Asia and China, respectively, through the entire period, related to positive trend in temperature and solar radiation. The impact of oil palm expansion in Indonesia and Malaysia is to enhance the trends over that region, e.g. from 1.17% to 1.5% in 1979-2005 in Malaysia. A negative emission trend is derived in India (-0.4%), owing to the negative trend in solar radiation data associated to the strong dimming effect likely due to increasing aerosol loadings. The bottom-up emissions are evaluated

Lidar Penetration Depth Observations for Constraining Cloud Longwave Feedbacks

Science.gov (United States)

Vaillant de Guelis, T.; Chepfer, H.; Noel, V.; Guzman, R.; Winker, D. M.; Kay, J. E.; Bonazzola, M.

2017-12-01

Satellite-borne active remote sensing Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations [CALIPSO; Winker et al., 2010] and CloudSat [Stephens et al., 2002] provide direct measurements of the cloud vertical distribution, with a very high vertical resolution. The penetration depth of the laser of the lidar Z_Opaque is directly linked to the LongWave (LW) Cloud Radiative Effect (CRE) at Top Of Atmosphere (TOA) [Vaillant de Guélis et al., in review]. In addition, this measurement is extremely stable in time making it an excellent observational candidate to verify and constrain the cloud LW feedback mechanism [Chepfer et al., 2014]. In this work, we present a method to decompose the variations of the LW CRE at TOA using cloud properties observed by lidar [GOCCP v3.0; Guzman et al., 2017]. We decompose these variations into contributions due to changes in five cloud properties: opaque cloud cover, opaque cloud altitude, thin cloud cover, thin cloud altitude, and thin cloud emissivity [Vaillant de Guélis et al., in review]. We apply this method, in the real world, to the CRE variations of CALIPSO 2008-2015 record, and, in climate model, to LMDZ6 and CESM simulations of the CRE variations of 2008-2015 period and of the CRE difference between a warm climate and the current climate. In climate model simulations, the same cloud properties as those observed by CALIOP are extracted from the CFMIP Observation Simulator Package (COSP) [Bodas-Salcedo et al., 2011] lidar simulator [Chepfer et al., 2008], which mimics the observations that would be performed by the lidar on board CALIPSO satellite. This method, when applied on multi-model simulations of current and future climate, could reveal the altitude of cloud opacity level observed by lidar as a strong constrain for cloud LW feedback, since the altitude feedback mechanism is physically explainable and the altitude of cloud opacity accurately observed by lidar.

Regional emission metrics for short-lived climate forcers from multiple models

Directory of Open Access Journals (Sweden)

B. Aamaas

2016-06-01

Full Text Available For short-lived climate forcers (SLCFs, the impact of emissions depends on where and when the emissions take place. Comprehensive new calculations of various emission metrics for SLCFs are presented based on radiative forcing (RF values calculated in four different (chemical-transport or coupled chemistry–climate models. We distinguish between emissions during summer (May–October and winter (November–April for emissions in Europe and East Asia, as well as from the global shipping sector and global emissions. The species included in this study are aerosols and aerosol precursors (BC, OC, SO2, NH3, as well as ozone precursors (NOx, CO, VOCs, which also influence aerosols to a lesser degree. Emission metrics for global climate responses of these emissions, as well as for CH4, have been calculated using global warming potential (GWP and global temperature change potential (GTP, based on dedicated RF simulations by four global models. The emission metrics include indirect cloud effects of aerosols and the semi-direct forcing for BC. In addition to the standard emission metrics for pulse and sustained emissions, we have also calculated a new emission metric designed for an emission profile consisting of a ramping period of 15 years followed by sustained emissions, which is more appropriate for a gradual implementation of mitigation policies.For the aerosols, the emission metric values are larger in magnitude for emissions in Europe than East Asia and for summer than winter. A variation is also observed for the ozone precursors, with largest values for emissions in East Asia and winter for CO and in Europe and summer for VOCs. In general, the variations between the emission metrics derived from different models are larger than the variations between regions and seasons, but the regional and seasonal variations for the best estimate also hold for most of the models individually. Further, the estimated climate impact of an illustrative mitigation

Node Discovery and Interpretation in Unstructured Resource-Constrained Environments

DEFF Research Database (Denmark)

Gechev, Miroslav; Kasabova, Slavyana; Mihovska, Albena D.

2014-01-01

for the discovery, linking and interpretation of nodes in unstructured and resource-constrained network environments and their interrelated and collective use for the delivery of smart services. The model is based on a basic mathematical approach, which describes and predicts the success of human interactions...... in the context of long-term relationships and identifies several key variables in the context of communications in resource-constrained environments. The general theoretical model is described and several algorithms are proposed as part of the node discovery, identification, and linking processes in relation...

The EUMETSAT OSI SAF near 50 GHz sea ice emissivity model

Directory of Open Access Journals (Sweden)

Rasums T. Tonboe

2013-02-01

Full Text Available A sea ice thermal microwave emission model for 50 GHz was developed under EUMETSAT's Ocean and Sea Ice Satellite Application Facility (OSI SAF programme. The model is based on correlations between the surface brightness temperature at 18, 36 and 50 GHz. The model coefficients are estimated using simulated data from a combined thermodynamic and emission model. The intention with the model is to provide a first guess sea ice surface emissivity estimate for atmospheric temperature sounding applications in the troposphere in numerical weather prediction (NWP models assimilating Advanced Microwave Sounding Unit (AMSU and Special Sensor Microwave Imager/Sounder (SSMIS data. The spectral gradient ratio is defined as the difference over the sum of the SSMIS brightness temperatures at 18 and 36 GHz vertical linear polarisation (GR1836. The GR1836 is related to the emissivity at the atmospheric temperature sounding channels at around 50 GHz. Furthermore, the brightness temperatures and the polarisation ratio (PR at the neighbouring 18, 36 and 50 GHz channels are highly correlated. Both the gradient ratio at 18 and 36 GHz and the PR at 36 GHz measured by SSMIS are input into the model predicting the 50 GHz emissivity for horizontal and vertical linear polarisations and incidence angles between 0° and 60° The simulated emissivity is compared to the emissivity derived with alternative methods. The fit to real AMSU observations is investigated using the different emissivity estimates for simulating the observations with atmospheric data from a regional weather prediction model.

Image denoising: Learning the noise model via nonsmooth PDE-constrained optimization

KAUST Repository

Reyes, Juan Carlos De los

2013-11-01

We propose a nonsmooth PDE-constrained optimization approach for the determination of the correct noise model in total variation (TV) image denoising. An optimization problem for the determination of the weights corresponding to different types of noise distributions is stated and existence of an optimal solution is proved. A tailored regularization approach for the approximation of the optimal parameter values is proposed thereafter and its consistency studied. Additionally, the differentiability of the solution operator is proved and an optimality system characterizing the optimal solutions of each regularized problem is derived. The optimal parameter values are numerically computed by using a quasi-Newton method, together with semismooth Newton type algorithms for the solution of the TV-subproblems. © 2013 American Institute of Mathematical Sciences.

Image denoising: Learning the noise model via nonsmooth PDE-constrained optimization

KAUST Repository

Reyes, Juan Carlos De los; Schö nlieb, Carola-Bibiane

2013-01-01

We propose a nonsmooth PDE-constrained optimization approach for the determination of the correct noise model in total variation (TV) image denoising. An optimization problem for the determination of the weights corresponding to different types of noise distributions is stated and existence of an optimal solution is proved. A tailored regularization approach for the approximation of the optimal parameter values is proposed thereafter and its consistency studied. Additionally, the differentiability of the solution operator is proved and an optimality system characterizing the optimal solutions of each regularized problem is derived. The optimal parameter values are numerically computed by using a quasi-Newton method, together with semismooth Newton type algorithms for the solution of the TV-subproblems. © 2013 American Institute of Mathematical Sciences.

Implications of CO2 Emissions Trading for Short-run Electricity Outcomes in Northwest Europe

International Nuclear Information System (INIS)

Chen, Y.; Sijm, J.P.M.; Hobbs, B.F.; Lise, W.

2008-02-01

We examine the short-run implications of CO2 trading for power production, prices, emissions, and generator profits in northwest Europe in 2005. Simulation results from a transmission-constrained oligopoly model are compared with theoretical analyses to quantify price increases and windfall profits earned by generators. The analyses indicate that the rates at which CO2 costs are passed through to wholesale prices are affected by market competitiveness, merit order changes, and elasticities of demand and supply. Emissions trading results in large windfall profits, much but not all of which is due to free allocation of allowances. Profits also increase for some generators because their generation mix has low emissions, and so they benefit from electricity price increases. Most emission reductions appear to be due to demand response, not generation redispatch

Implications of CO2 Emissions Trading for Short-run Electricity Outcomes in Northwest Europe

Energy Technology Data Exchange (ETDEWEB)

Chen, Y. [School of Social Sciences, Humanities, and Arts and School of Engineering, Sierra Nevada Research Institute, University of California, Merced, 5200 N. Lake Rd., Merced, CA 95343 (United States); Sijm, J.P.M. [Policy Studies Unit, Energy Research Centre of the Netherlands ECN, P.O. Box 37154, 1020 Amsterdam (Netherlands); Hobbs, B.F. [Department of Geography and Environmental Engineering, The Johns Hopkins University, 3400 N. Charles St, Ames Hall, Baltimore, MD 21218 (United States); Lise, W. [IBS Research and Consultancy, Aga Hamami Caddesi, Aga Han 17/6, Cihangir, 34433 Beyoglu, Istanbul (Turkey)

2008-02-15

We examine the short-run implications of CO2 trading for power production, prices, emissions, and generator profits in northwest Europe in 2005. Simulation results from a transmission-constrained oligopoly model are compared with theoretical analyses to quantify price increases and windfall profits earned by generators. The analyses indicate that the rates at which CO2 costs are passed through to wholesale prices are affected by market competitiveness, merit order changes, and elasticities of demand and supply. Emissions trading results in large windfall profits, much but not all of which is due to free allocation of allowances. Profits also increase for some generators because their generation mix has low emissions, and so they benefit from electricity price increases. Most emission reductions appear to be due to demand response, not generation redispatch.

European initiatives for modeling emissions from transport

DEFF Research Database (Denmark)

Joumard, Robert; Hickman, A. John; Samaras, Zissis

1998-01-01

In Europe there have been many cooperative studies into transport emission inventories since the late 80s. These cover the scope of CORINAIR program involving experts from seven European Community laboratories addressing only road transport emissions at national level. These also include the latest...... covered are the composition of the vehicle fleets, emission factors, driving statistics and the modeling approach. Many of the European initiatives aim also at promoting further cooperation between national laboratories and at defining future research needs. An assessment of these future needs...... is presented from a European point of view....

Modeling the effects of atmospheric emissions on groundwater composition

International Nuclear Information System (INIS)

Brown, T.J.

1994-01-01

A composite model of atmospheric, unsaturated and groundwater transport is developed to evaluate the processes determining the distribution of atmospherically derived contaminants in groundwater systems and to test the sensitivity of simulated contaminant concentrations to input parameters and model linkages. One application is to screen specific atmospheric emissions for their potential in determining groundwater age. Temporal changes in atmospheric emissions could provide a recognizable pattern in the groundwater system. The model also provides a way for quantifying the significance of uncertainties in the tracer source term and transport parameters on the contaminant distribution in the groundwater system, an essential step in using the distribution of contaminants from local, point source atmospheric emissions to examine conceptual models of groundwater flow and transport

Particulate matter emission modelling based on soot and SOF from direct injection diesel engines

International Nuclear Information System (INIS)

Tan, P.Q.; Hu, Z.Y.; Deng, K.Y.; Lu, J.X.; Lou, D.M.; Wan, G.

2007-01-01

Particulate matter (PM) emission is one of the major pollutants from diesel engines, and it is harmful for human health and influences the atmospheric visibility. In investigations for reducing PM emission, a simulation model for PM emission is a useful tool. In this paper, a phenomenological, composition based PM model of direct injection (DI) diesel engines has been proposed and formulated to simulate PM emission. The PM emission model is based on a quasi-dimensional multi-zone combustion model using the formation mechanisms of the two main compositions of PM: soot and soluble organic fraction (SOF). First, the quasi-dimensional multi-zone combustion model is given. Then, two models for soot and SOF emissions are established, respectively, and after that, the two models are integrated into a single PM emission model. The soot emission model is given by the difference between a primary formation model and an oxidation model of soot. The soot primary formation model is the Hiroyasu soot formation model, and the Nagle and Strickland-Constable model is adopted for soot oxidation. The SOF emission model is based on an unburned hydrocarbons (HC) emission model, and the HC emission model is given by the difference between a HC primary formation model and a HC oxidation model. The HC primary formation model considers fuel injected and mixed beyond the lean combustion limit during ignition delay and fuel effusing from the nozzle sac volume at low pressure and low velocity. In order to validate the PM emission model, experiments were performed on a six cylinder, turbocharged and intercooled DI diesel engine. The simulation results show good agreement with the experimental data, which indicates the validity of the PM emission model. The calculation results show that the distinctions between PM and soot formation rates are mainly in the early combustion stage. The SOF formation has an important influence on the PM formation at lower loads, and soot formation dominates the

Methane emissions from rice paddies : experiments and modelling

NARCIS (Netherlands)

Bodegom, van P.M.

2000-01-01

This thesis describes model development and experimentation on the comprehension and prediction of methane (CH ₄ ) emissions from rice paddies. The large spatial and temporal variability in CH ₄ emissions and the dynamic non-linear relationships

Self-scheduling and bidding strategies of thermal units with stochastic emission constraints

International Nuclear Information System (INIS)

Laia, R.; Pousinho, H.M.I.; Melíco, R.; Mendes, V.M.F.

2015-01-01

Highlights: • The management of thermal power plants is considered for different emission allowance levels. • The uncertainty on electricity price is considered by a set of scenarios. • A stochastic MILP approach allows devising the bidding strategies and hedging against price uncertainty and emission allowances. - Abstract: This paper is on the self-scheduling problem for a thermal power producer taking part in a pool-based electricity market as a price-taker, having bilateral contracts and emission-constrained. An approach based on stochastic mixed-integer linear programming approach is proposed for solving the self-scheduling problem. Uncertainty regarding electricity price is considered through a set of scenarios computed by simulation and scenario-reduction. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. A requirement on emission allowances to mitigate carbon footprint is modelled by a stochastic constraint. Supply functions for different emission allowance levels are accessed in order to establish the optimal bidding strategy. A case study is presented to illustrate the usefulness and the proficiency of the proposed approach in supporting biding strategies

Offset, tilted dipole models of Uranian smooth high-frequency radio emission

International Nuclear Information System (INIS)

Schweitzer, A.E.; Romig, J.H.; Evans, D.R.; Sawyer, C.B.; Warwick, J.W.

1990-01-01

During the Voyager 2 encounter with Uranus in January 1986, the Planetary Radio Astronomy (PRA) experiment detected a complex pattern of radio emissions. Two types of emissions were seen: smooth and bursty. The smooth emission has been divided into smooth high-frequency (SHF) and smooth low-frequency (SLF) components which are presumed to come from different sources because of their distinctly different characteristics. The SHF component is considered in this paper. The SHF emission has been modeled by many authors on OTD (offset, tilted dipole (Ness et al., 1986)) L shells ranging from 5 to 40. However, the bursts have been modeled at much higher L shells. The authors complete an OTD investigation of the SHF emission at high L shells within the range of the bursty source locations, and present a viable high L shell model. This model has fundamentally the same longitudinally symmetric net emission pattern in space as the L shell 5 model presented in Romig et al. (1987) and Barbosa (1988). However, they were unable to produce an acceptable model on intermediate L shells without restricting source longitude. They discuss the similarities and distinctions between their two models and the models of other authors. They believe that the high L shell model (and others similar to it) cannot account for the observed smoothness and periodicity of the SHF emissions because it has open field lines containing untrapped particles, which should produce more variable emission than that seen in the SHF data. Therefore, the authors prefer models at L shells less than 18, the boundary for closed field lines (Ness et al., 1986). They then discuss and contrast two models within this boundary: the L = 5 model and an L ∼ 12 model by Kaiser et al. (1987) and Farrell and Calvert (1989b). The main distinction between these two models is the longitudinal extent of the source location

Carbon Monoxide Emission and Concentration Models for Chiang Mai Urban Area

Institute of Scientific and Technical Information of China (English)

无

2006-01-01

An emission inventory containing emissions from traffic and other sources was complied. Based on the analysis, Carbon Monoxide (CO) emissions from traffic play a very important role in CO levels in Chiang Mai area. Analysis showed that CO emissions from traffic during rush hours contributed approximately 90% of total CO emissions. Regional Atmospheric Modeling System (RAMS) was applied to simulate wind fields and temperatures in the Chiang Mai area, and eight cases were selected to study annual variations in wind fields and temperatures. Model results can reflect major features of wind fields and diurnal variations in temperatures. For evaluating the model performance, model results were compared with observed wind speed, wind direction and temperature, which were monitored at a meteorological tower. Comparison showed that model results are in good agreement with observations, and the model captured many of the observed features. HYbrid Particle And Concentration Transport model (HYPACT) was used to simulate CO concentration in the Chiang Mai area. Model results generally agree well with observed CO concentrations at the air quality monitoring stations, and can explain observed CO diurnal variations.

Tropospheric ozone changes, radiative forcing and attribution to emissions in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP

Directory of Open Access Journals (Sweden)

D. S. Stevenson

2013-03-01

Full Text Available Ozone (O3 from 17 atmospheric chemistry models taking part in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP has been used to calculate tropospheric ozone radiative forcings (RFs. All models applied a common set of anthropogenic emissions, which are better constrained for the present-day than the past. Future anthropogenic emissions follow the four Representative Concentration Pathway (RCP scenarios, which define a relatively narrow range of possible air pollution emissions. We calculate a value for the pre-industrial (1750 to present-day (2010 tropospheric ozone RF of 410 mW m−2. The model range of pre-industrial to present-day changes in O3 produces a spread (±1 standard deviation in RFs of ±17%. Three different radiation schemes were used – we find differences in RFs between schemes (for the same ozone fields of ±10%. Applying two different tropopause definitions gives differences in RFs of ±3%. Given additional (unquantified uncertainties associated with emissions, climate-chemistry interactions and land-use change, we estimate an overall uncertainty of ±30% for the tropospheric ozone RF. Experiments carried out by a subset of six models attribute tropospheric ozone RF to increased emissions of methane (44±12%, nitrogen oxides (31 ± 9%, carbon monoxide (15 ± 3% and non-methane volatile organic compounds (9 ± 2%; earlier studies attributed more of the tropospheric ozone RF to methane and less to nitrogen oxides. Normalising RFs to changes in tropospheric column ozone, we find a global mean normalised RF of 42 mW m−2 DU−1, a value similar to previous work. Using normalised RFs and future tropospheric column ozone projections we calculate future tropospheric ozone RFs (mW m−2; relative to 1750 for the four future scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5 of 350, 420, 370 and 460 (in 2030, and 200, 300, 280 and 600 (in 2100. Models show some coherent responses of ozone to climate change

Constraining the Dust Opacity Law in Three Small and Isolated Molecular Clouds

Energy Technology Data Exchange (ETDEWEB)

Webb, K. A.; Thanjavur, K. [Department of Physics and Astronomy, 3800 Finnerty Road, University of Victoria, Victoria, BC, V8P 5C2 (Canada); Di Francesco, J. [National Research Council of Canada, Herzberg Institute of Astrophysics, 5071 West Saanich Road, Victoria, BC, V9E 2E7 (Canada); Sadavoy, S. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Launhardt, R.; Vicente, J. Abreu; Kainulainen, J. [Max-Planck-Institut für Astronomy, Königstuhl 17, D-69117, Heidelberg (Germany); Shirley, Y. [Steward Observatory, 933 North Cherry Avenue, Tucson, AZ 85721 (United States); Stutz, A., E-mail: kawebb@uvic.ca [Departmento de Astronomìa, Facultad Ciencias Físicas y Matemáticas, Universidad de Concepción, Av. Esteban Iturra s/n Barro Universitario, Casilla 160-C, Concepción (Chile)

2017-11-01

Density profiles of isolated cores derived from thermal dust continuum emission rely on models of dust properties, such as mass opacity, that are poorly constrained. With complementary measures from near-infrared extinction maps, we can assess the reliability of commonly used dust models. In this work, we compare Herschel -derived maps of the optical depth with equivalent maps derived from CFHT WIRCAM near-infrared observations for three isolated cores: CB 68, L 429, and L 1552. We assess the dust opacities provided from four models: OH1a, OH5a, Orm1, and Orm4. Although the consistency of the models differs between the three sources, the results suggest that the optical properties of dust in the envelopes of the cores are best described by either silicate and bare graphite grains (e.g., Orm1) or carbonaceous grains with some coagulation and either thin or no ice mantles (e.g., OH5a). None of the models, however, individually produced the most consistent optical depth maps for every source. The results suggest that either the dust in the cores is not well-described by any one dust property model, the application of the dust models cannot be extended beyond the very center of the cores, or more complex SED fitting functions are necessary.

Characterizing and Quantifying Emissions and Transport of Fugitive Dust Emissions Due to Department of Defense Activities

Science.gov (United States)

2015-09-19

response to shear stress (τ, N m-2) induced by the PI-SWERL®, the viscosity of the fluid exerts a torque (N m-1) that eventually balances with τ. The...Engelbrecht et al. (2012) from CCSEM measurements, report that these silicate mineral particles are largely coated by a veneer of clay minerals and fine...content does not, by itself, contribute to the high emissions observed at YTC. The presence of high clay content can constrain the emissions by

Spatiotemporal variability of biogenic terpenoid emissions in Pearl River Delta, China, with high-resolution land-cover and meteorological data

Science.gov (United States)

Wang, Xuemei; Situ, Shuping; Guenther, Alex; Chen, Fei; Wu, Zhiyong; Xia, Beicheng; Wang, Tijian

2011-04-01

This study intended to provide 4-km gridded, hourly, year-long, regional estimates of terpenoid emissions in the Pearl River Delta (PRD), China. It combined Thematic Mapper images and local-survey data to characterize plant functional types, and used observed emission potential of biogenic volatile organic compounds (BVOC) from local plant species and high-resolution meteorological outputs from the MM5 model to constrain the MEGAN BVOC-emission model. The estimated annual emissions for isoprene, monoterpene and sesquiterpene are 95.55 × 106 kg C, 117.35 × 106 kg C and 9.77 × 106 kg C, respectively. The results show strong variabilities of terpenoid emissions spanning diurnal and seasonal time scales, which are mainly distributed in the remote areas (with more vegetation and less economic development) in PRD. Using MODIS PFTs data reduced terpenoid emissions by 27% in remote areas. Using MEGAN-model default emission factors led to a 24% increase in BVOC emission. The model errors of temperature and radiation in MM5 output were used to assess impacts of uncertainties in meteorological forcing on emissions: increasing (decreasing) temperature and downward shortwave radiation produces more (less) terpenoid emissions for July and January. Strong temporal variability of terpenoid emissions leads to enhanced ozone formation during midday in rural areas where the anthropogenic VOC emissions are limited.

Probabilistic model for the simulation of secondary electron emission

Directory of Open Access Journals (Sweden)

M. A. Furman

2002-12-01

Full Text Available We provide a detailed description of a model and its computational algorithm for the secondary electron emission process. The model is based on a broad phenomenological fit to data for the secondary-emission yield and the emitted-energy spectrum. We provide two sets of values for the parameters by fitting our model to two particular data sets, one for copper and the other one for stainless steel.

Methane emissions from a landfill in north-east India: Performance of various landfill gas emission models.

Science.gov (United States)

Gollapalli, Muralidhar; Kota, Sri Harsha

2018-03-01

Rapid urbanization and economic growth has led to significant increase in municipal solid waste generation in India during the last few decades and its management has become a major issue because of poor waste management practices. Solid waste generated is deposited into open dumping sites with hardly any segregation and processing. Carbon dioxide (CO 2 ), methane (CH 4 ) and nitrous oxide (N 2 O) are the major greenhouse gases that are released from the landfill sites due to the biodegradation of organic matter. In this present study, CH 4 and CO 2 emissions from a landfill in north-east India are estimated using a flux chamber during September, 2015 to August, 2016. The average emission rates of CH 4 and CO 2 are 68 and 92 mg/min/m 2 , respectively. The emissions are highest in the summer whilst being lowest in winter. The diurnal variation of emissions indicated that the emissions follow a trend similar to temperature in all the seasons. Correlation coefficients of CH 4 and temperature in summer, monsoon and winter are 0.99, 0.87 and 0.97, respectively. The measured CH 4 in this study is in the range of other studies around the world. Modified Triangular Method (MTM), IPCC model and the USEPA Landfill gas emissions model (LandGEM) were used to predict the CH 4 emissions during the study year. The consequent simulation results indicate that the MTM, LandGEM-Clean Air Act, LandGEM-Inventory and IPCC models predict 1.9, 3.3, 1.6 and 1.4 times of the measured CH 4 emission flux in this study. Assuming that this higher prediction of CH 4 levels observed in this study holds well for other landfills in this region, a new CH 4 emission inventory (Units: Tonnes/year), with a resolution of 0.1 0  × 0.1 0 has been developed. This study stresses the importance of biodegradable composition of waste and meteorology, and also points out the drawbacks of the widely used landfill emission models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Maximizing entropy of image models for 2-D constrained coding

DEFF Research Database (Denmark)

Forchhammer, Søren; Danieli, Matteo; Burini, Nino

2010-01-01

This paper considers estimating and maximizing the entropy of two-dimensional (2-D) fields with application to 2-D constrained coding. We consider Markov random fields (MRF), which have a non-causal description, and the special case of Pickard random fields (PRF). The PRF are 2-D causal finite...... context models, which define stationary probability distributions on finite rectangles and thus allow for calculation of the entropy. We consider two binary constraints and revisit the hard square constraint given by forbidding neighboring 1s and provide novel results for the constraint that no uniform 2...... £ 2 squares contains all 0s or all 1s. The maximum values of the entropy for the constraints are estimated and binary PRF satisfying the constraint are characterized and optimized w.r.t. the entropy. The maximum binary PRF entropy is 0.839 bits/symbol for the no uniform squares constraint. The entropy...

Constraining the dark energy models with H (z ) data: An approach independent of H0

Science.gov (United States)

Anagnostopoulos, Fotios K.; Basilakos, Spyros

2018-03-01

We study the performance of the latest H (z ) data in constraining the cosmological parameters of different cosmological models, including that of Chevalier-Polarski-Linder w0w1 parametrization. First, we introduce a statistical procedure in which the chi-square estimator is not affected by the value of the Hubble constant. As a result, we find that the H (z ) data do not rule out the possibility of either nonflat models or dynamical dark energy cosmological models. However, we verify that the time varying equation-of-state parameter w (z ) is not constrained by the current expansion data. Combining the H (z ) and the Type Ia supernova data, we find that the H (z )/SNIa overall statistical analysis provides a substantial improvement of the cosmological constraints with respect to those of the H (z ) analysis. Moreover, the w0-w1 parameter space provided by the H (z )/SNIa joint analysis is in very good agreement with that of Planck 2015, which confirms that the present analysis with the H (z ) and supernova type Ia (SNIa) probes correctly reveals the expansion of the Universe as found by the team of Planck. Finally, we generate sets of Monte Carlo realizations in order to quantify the ability of the H (z ) data to provide strong constraints on the dark energy model parameters. The Monte Carlo approach shows significant improvement of the constraints, when increasing the sample to 100 H (z ) measurements. Such a goal can be achieved in the future, especially in the light of the next generation of surveys.

Distributional aspects of emissions in climate change integrated assessment models

International Nuclear Information System (INIS)

Cantore, Nicola

2011-01-01

The recent failure of Copenhagen negotiations shows that concrete actions are needed to create the conditions for a consensus over global emission reduction policies. A wide coalition of countries in international climate change agreements could be facilitated by the perceived fairness of rich and poor countries of the abatement sharing at international level. In this paper I use two popular climate change integrated assessment models to investigate the path and decompose components and sources of future inequality in the emissions distribution. Results prove to be consistent with previous empirical studies and robust to model comparison and show that gaps in GDP across world regions will still play a crucial role in explaining different countries contributions to global warming. - Research highlights: → I implement a scenario analysis with two global climate change models. → I analyse inequality in the distribution of emissions. → I decompose emissions inequality components. → I find that GDP per capita is the main Kaya identity source of emissions inequality. → Current rich countries will mostly remain responsible for emissions inequality.

Comparison of models used for national agricultural ammonia emission inventories in Europe

DEFF Research Database (Denmark)

Reidy, B; Dämmgen, U; Döhler, H

2008-01-01

and harmonized the available knowledge on emission factors (EFs) for nitrogen (N)-flow emission calculation models and initiated a new generation of emission inventories. As a first step in summarizing the available knowledge, six N-flow models, used to calculate national NH3 emissions from agriculture...... the variation in the results generated awareness and consensus concerning available scientific data and the importance of specific processes not yet included in some models...

Empirical Succession Mapping and Data Assimilation to Constrain Demographic Processes in an Ecosystem Model

Science.gov (United States)

Kelly, R.; Andrews, T.; Dietze, M.

2015-12-01

Shifts in ecological communities in response to environmental change have implications for biodiversity, ecosystem function, and feedbacks to global climate change. Community composition is fundamentally the product of demography, but demographic processes are simplified or missing altogether in many ecosystem, Earth system, and species distribution models. This limitation arises in part because demographic data are noisy and difficult to synthesize. As a consequence, demographic processes are challenging to formulate in models in the first place, and to verify and constrain with data thereafter. Here, we used a novel analysis of the USFS Forest Inventory Analysis to improve the representation of demography in an ecosystem model. First, we created an Empirical Succession Mapping (ESM) based on ~1 million individual tree observations from the eastern U.S. to identify broad demographic patterns related to forest succession and disturbance. We used results from this analysis to guide reformulation of the Ecosystem Demography model (ED), an existing forest simulator with explicit tree demography. Results from the ESM reveal a coherent, cyclic pattern of change in temperate forest tree size and density over the eastern U.S. The ESM captures key ecological processes including succession, self-thinning, and gap-filling, and quantifies the typical trajectory of these processes as a function of tree size and stand density. Recruitment is most rapid in early-successional stands with low density and mean diameter, but slows as stand density increases; mean diameter increases until thinning promotes recruitment of small-diameter trees. Strikingly, the upper bound of size-density space that emerges in the ESM conforms closely to the self-thinning power law often observed in ecology. The ED model obeys this same overall size-density boundary, but overestimates plot-level growth, mortality, and fecundity rates, leading to unrealistic emergent demographic patterns. In particular

Event-triggered decentralized robust model predictive control for constrained large-scale interconnected systems

Directory of Open Access Journals (Sweden)

Ling Lu

2016-12-01

Full Text Available This paper considers the problem of event-triggered decentralized model predictive control (MPC for constrained large-scale linear systems subject to additive bounded disturbances. The constraint tightening method is utilized to formulate the MPC optimization problem. The local predictive control law for each subsystem is determined aperiodically by relevant triggering rule which allows a considerable reduction of the computational load. And then, the robust feasibility and closed-loop stability are proved and it is shown that every subsystem state will be driven into a robust invariant set. Finally, the effectiveness of the proposed approach is illustrated via numerical simulations.

Characterizing the X-ray Emission in Small Magellanic Cloud Supernova Remnants

Science.gov (United States)

Man, Nicole; Auchettl, Katie; Lopez, Laura

2018-01-01

The Small Magellanic Cloud is a close, metal-poor galaxy with active star formation, and it has a diverse population of 24 supernova remnants (SNRs) that have been identified at several wavelengths. Past work has characterized the X-ray emission in these sources separately and aimed to constrain their explosive origins from observations with Chandra and XMM-Newton. Three SNRs have possible evidence for Type Ia explosions based on strong Fe-L emission in their X-ray spectra, although the environments and intermediate-mass element abundances are more consistent with those of core-collapse SNe. In this poster, we analyze the archival Chandra and XMM-Newton observations of the SMC SNR sample, and we model the sources' X-ray spectra in a systematic way to derive the plasma properties and to constrain the nature of the explosions. In one SNR, we note the presence of an X-ray binary near the source's geometric center, suggesting the compact object was produced in the SN explosion. As one of only three SNRs known in the Local Group to host a binary system, this source is worthy of follow-up investigations to probe explosions of massive stars in binary systems.

Estimates of reservoir methane emissions based on a spatially balanced probabilistic-survey

Science.gov (United States)

Global estimates of methane (CH4) emissions from reservoirs are poorly constrained, partly due to the challenges of accounting for intra-reservoir spatial variability. Reservoir-scale emission rates are often estimated by extrapolating from measurement made at a few locations; h...

FORECASTING MODEL OF GHG EMISSION IN MANUFACTURING SECTORS OF THAILAND

Directory of Open Access Journals (Sweden)

Pruethsan Sutthichaimethee

2017-01-01

Full Text Available This study aims to analyze the modeling and forecasting the GHG emission of energy consumption in manufacturing sectors. The scope of the study is to analysis energy consumption and forecasting GHG emission of energy consumption for the next 10 years (2016-2025 and 25 years (2016-2040 by using ARIMAX model from the Input-output table of Thailand. The result shows that iron and steel has the highest value of energy consumption and followed by cement, fluorite, air transport, road freight transport, hotels and places of loading, coal and lignite, petrochemical products, other manufacturing, road passenger transport, respectively. The prediction results show that these models are effective in forecasting by measured by using RMSE, MAE, and MAPE. The results forecast of each model is as follows: 1 Model 1(2,1,1 shows that GHG emission will be increasing steadily and increasing at 25.17% by the year 2025 in comparison to 2016. 2 Model 2 (2,1,2 shows that GHG emission will be rising steadily and increasing at 41.51% by the year 2040 in comparison to 2016.

Bayesian inverse modeling of the atmospheric transport and emissions of a controlled tracer release from a nuclear power plant

International Nuclear Information System (INIS)

Lucas, Donald D.; Simpson, Matthew; Cameron-Smith, Philip; Baskett, Ronald L.

2017-01-01

Probability distribution functions (PDFs) of model inputs that affect the transport and dispersion of a trace gas released from a coastal California nuclear power plant are quantified using ensemble simulations, machine-learning algorithms, and Bayesian inversion. The PDFs are constrained by observations of tracer concentrations and account for uncertainty in meteorology, transport, diffusion, and emissions. Meteorological uncertainty is calculated using an ensemble of simulations of the Weather Research and Forecasting (WRF) model that samples five categories of model inputs (initialization time, boundary layer physics, land surface model, nudging options, and reanalysis data). The WRF output is used to drive tens of thousands of FLEXPART dispersion simulations that sample a uniform distribution of six emissions inputs. Machine-learning algorithms are trained on the ensemble data and used to quantify the sources of ensemble variability and to infer, via inverse modeling, the values of the 11 model inputs most consistent with tracer measurements. We find a substantial ensemble spread in tracer concentrations (factors of 10 to 10 3 ), most of which is due to changing emissions inputs (about 80 %), though the cumulative effects of meteorological variations are not negligible. The performance of the inverse method is verified using synthetic observations generated from arbitrarily selected simulations. When applied to measurements from a controlled tracer release experiment, the inverse method satisfactorily determines the location, start time, duration and amount. In a 2 km x 2 km area of possible locations, the actual location is determined to within 200 m. The start time is determined to within 5 min out of 2 h, and the duration to within 50 min out of 4 h. Over a range of release amounts of 10 to 1000 kg, the estimated amount exceeds the actual amount of 146 kg by only 32 kg. The inversion also estimates probabilities of different WRF configurations. To best match

Bayesian inverse modeling of the atmospheric transport and emissions of a controlled tracer release from a nuclear power plant

Energy Technology Data Exchange (ETDEWEB)

Lucas, Donald D.; Simpson, Matthew; Cameron-Smith, Philip; Baskett, Ronald L. [Lawrence Livermore National Laboratory, Livermore, CA (United States)

2017-07-01

Probability distribution functions (PDFs) of model inputs that affect the transport and dispersion of a trace gas released from a coastal California nuclear power plant are quantified using ensemble simulations, machine-learning algorithms, and Bayesian inversion. The PDFs are constrained by observations of tracer concentrations and account for uncertainty in meteorology, transport, diffusion, and emissions. Meteorological uncertainty is calculated using an ensemble of simulations of the Weather Research and Forecasting (WRF) model that samples five categories of model inputs (initialization time, boundary layer physics, land surface model, nudging options, and reanalysis data). The WRF output is used to drive tens of thousands of FLEXPART dispersion simulations that sample a uniform distribution of six emissions inputs. Machine-learning algorithms are trained on the ensemble data and used to quantify the sources of ensemble variability and to infer, via inverse modeling, the values of the 11 model inputs most consistent with tracer measurements. We find a substantial ensemble spread in tracer concentrations (factors of 10 to 10{sup 3}), most of which is due to changing emissions inputs (about 80 %), though the cumulative effects of meteorological variations are not negligible. The performance of the inverse method is verified using synthetic observations generated from arbitrarily selected simulations. When applied to measurements from a controlled tracer release experiment, the inverse method satisfactorily determines the location, start time, duration and amount. In a 2 km x 2 km area of possible locations, the actual location is determined to within 200 m. The start time is determined to within 5 min out of 2 h, and the duration to within 50 min out of 4 h. Over a range of release amounts of 10 to 1000 kg, the estimated amount exceeds the actual amount of 146 kg by only 32 kg. The inversion also estimates probabilities of different WRF configurations. To best

Constraining Light-Quark Yukawa Couplings from Higgs Distributions

CERN Document Server

Bishara, Fady

2017-03-20

We propose a novel strategy to constrain the bottom and charm Yukawa couplings by exploiting LHC measurements of transverse momentum distributions in Higgs production. Our method does not rely on the reconstruction of exclusive final states or heavy-flavour tagging. Compared to other proposals it leads to an enhanced sensitivity to the Yukawa couplings due to distortions of the differential Higgs spectra from emissions which either probe quark loops or are associated to quark-initiated production. We derive constraints using data from LHC Run I, and we explore the prospects of our method at future LHC runs. Finally, we comment on the possibility of bounding the strange Yukawa coupling.

INTEGRAL Upper Limits on Gamma-Ray Emission Associated with the Gravitational Wave Event GW150914

DEFF Research Database (Denmark)

Savchenko, V.; Ferrigno, C.; Mereghetti, S.

2016-01-01

Using observations of the INTErnational Gamma-Ray Astrophysics Laboratory (INTEGRAL), we place upper limits on the gamma-ray and hard X-ray prompt emission associated with the gravitational wave event GW150914, which was discovered by the LIGO/Virgo Collaboration. The omnidirectional view...... in the 75 keV-2 MeV energy range for typical spectral models. Our results constrain the ratio of the energy promptly released in gamma-rays in the direction of the observer to the gravitational wave energy Eγ/EGW ... of the gravitational wave source, based on the available predictions for prompt electromagnetic emission....

Integrating satellite retrieved leaf chlorophyll into land surface models for constraining simulations of water and carbon fluxes

KAUST Repository

Houborg, Rasmus

2013-07-01

In terrestrial biosphere models, key biochemical controls on carbon uptake by vegetation canopies are typically assigned fixed literature-based values for broad categories of vegetation types although in reality significant spatial and temporal variability exists. Satellite remote sensing can support modeling efforts by offering distributed information on important land surface characteristics, which would be very difficult to obtain otherwise. This study investigates the utility of satellite based retrievals of leaf chlorophyll for estimating leaf photosynthetic capacity and for constraining model simulations of water and carbon fluxes. © 2013 IEEE.

[Measurement model of carbon emission from forest fire: a review].

Science.gov (United States)

Hu, Hai-Qing; Wei, Shu-Jing; Jin, Sen; Sun, Long

2012-05-01

Forest fire is the main disturbance factor for forest ecosystem, and an important pathway of the decrease of vegetation- and soil carbon storage. Large amount of carbonaceous gases in forest fire can release into atmosphere, giving remarkable impacts on the atmospheric carbon balance and global climate change. To scientifically and effectively measure the carbonaceous gases emission from forest fire is of importance in understanding the significance of forest fire in the carbon balance and climate change. This paper reviewed the research progress in the measurement model of carbon emission from forest fire, which covered three critical issues, i. e., measurement methods of forest fire-induced total carbon emission and carbonaceous gases emission, affecting factors and measurement parameters of measurement model, and cause analysis of the uncertainty in the measurement of the carbon emissions. Three path selections to improve the quantitative measurement of the carbon emissions were proposed, i. e., using high resolution remote sensing data and improving algorithm and estimation accuracy of burned area in combining with effective fuel measurement model to improve the accuracy of the estimated fuel load, using high resolution remote sensing images combined with indoor controlled environment experiments, field measurements, and field ground surveys to determine the combustion efficiency, and combining indoor controlled environment experiments with field air sampling to determine the emission factors and emission ratio.

Hydrologic and hydraulic flood forecasting constrained by remote sensing data

Science.gov (United States)

Li, Y.; Grimaldi, S.; Pauwels, V. R. N.; Walker, J. P.; Wright, A. J.

2017-12-01

Flooding is one of the most destructive natural disasters, resulting in many deaths and billions of dollars of damages each year. An indispensable tool to mitigate the effect of floods is to provide accurate and timely forecasts. An operational flood forecasting system typically consists of a hydrologic model, converting rainfall data into flood volumes entering the river system, and a hydraulic model, converting these flood volumes into water levels and flood extents. Such a system is prone to various sources of uncertainties from the initial conditions, meteorological forcing, topographic data, model parameters and model structure. To reduce those uncertainties, current forecasting systems are typically calibrated and/or updated using ground-based streamflow measurements, and such applications are limited to well-gauged areas. The recent increasing availability of spatially distributed remote sensing (RS) data offers new opportunities to improve flood forecasting skill. Based on an Australian case study, this presentation will discuss the use of 1) RS soil moisture to constrain a hydrologic model, and 2) RS flood extent and level to constrain a hydraulic model.The GRKAL hydrological model is calibrated through a joint calibration scheme using both ground-based streamflow and RS soil moisture observations. A lag-aware data assimilation approach is tested through a set of synthetic experiments to integrate RS soil moisture to constrain the streamflow forecasting in real-time.The hydraulic model is LISFLOOD-FP which solves the 2-dimensional inertial approximation of the Shallow Water Equations. Gauged water level time series and RS-derived flood extent and levels are used to apply a multi-objective calibration protocol. The effectiveness with which each data source or combination of data sources constrained the parameter space will be discussed.

Road salt emissions: A comparison of measurements and modelling using the NORTRIP road dust emission model

Science.gov (United States)

Denby, B. R.; Ketzel, M.; Ellermann, T.; Stojiljkovic, A.; Kupiainen, K.; Niemi, J. V.; Norman, M.; Johansson, C.; Gustafsson, M.; Blomqvist, G.; Janhäll, S.; Sundvor, I.

2016-09-01

De-icing of road surfaces is necessary in many countries during winter to improve vehicle traction. Large amounts of salt, most often sodium chloride, are applied every year. Most of this salt is removed through drainage or traffic spray processes but a certain amount may be suspended, after drying of the road surface, into the air and will contribute to the concentration of particulate matter. Though some measurements of salt concentrations are available near roads, the link between road maintenance salting activities and observed concentrations of salt in ambient air is yet to be quantified. In this study the NORTRIP road dust emission model, which estimates the emissions of both dust and salt from the road surface, is applied at five sites in four Nordic countries for ten separate winter periods where daily mean ambient air measurements of salt concentrations are available. The model is capable of reproducing many of the salt emission episodes, both in time and intensity, but also fails on other occasions. The observed mean concentration of salt in PM10, over all ten datasets, is 4.2 μg/m3 and the modelled mean is 2.8 μg/m3, giving a fractional bias of -0.38. The RMSE of the mean concentrations, over all 10 datasets, is 2.9 μg/m3 with an average R2 of 0.28. The mean concentration of salt is similar to the mean exhaust contribution during the winter periods of 2.6 μg/m3. The contribution of salt to the kerbside winter mean PM10 concentration is estimated to increase by 4.1 ± 3.4 μg/m3 for every kg/m2 of salt applied on the road surface during the winter season. Additional sensitivity studies showed that the accurate logging of salt applications is a prerequisite for predicting salt emissions, as well as good quality data on precipitation. It also highlights the need for more simultaneous measurements of salt loading together with ambient air concentrations to help improve model parameterisations of salt and moisture removal processes.

Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling

Directory of Open Access Journals (Sweden)

R. Locatelli

2013-10-01

Full Text Available A modelling experiment has been conceived to assess the impact of transport model errors on methane emissions estimated in an atmospheric inversion system. Synthetic methane observations, obtained from 10 different model outputs from the international TransCom-CH4 model inter-comparison exercise, are combined with a prior scenario of methane emissions and sinks, and integrated into the three-component PYVAR-LMDZ-SACS (PYthon VARiational-Laboratoire de Météorologie Dynamique model with Zooming capability-Simplified Atmospheric Chemistry System inversion system to produce 10 different methane emission estimates at the global scale for the year 2005. The same methane sinks, emissions and initial conditions have been applied to produce the 10 synthetic observation datasets. The same inversion set-up (statistical errors, prior emissions, inverse procedure is then applied to derive flux estimates by inverse modelling. Consequently, only differences in the modelling of atmospheric transport may cause differences in the estimated fluxes. In our framework, we show that transport model errors lead to a discrepancy of 27 Tg yr−1 at the global scale, representing 5% of total methane emissions. At continental and annual scales, transport model errors are proportionally larger than at the global scale, with errors ranging from 36 Tg yr−1 in North America to 7 Tg yr−1 in Boreal Eurasia (from 23 to 48%, respectively. At the model grid-scale, the spread of inverse estimates can reach 150% of the prior flux. Therefore, transport model errors contribute significantly to overall uncertainties in emission estimates by inverse modelling, especially when small spatial scales are examined. Sensitivity tests have been carried out to estimate the impact of the measurement network and the advantage of higher horizontal resolution in transport models. The large differences found between methane flux estimates inferred in these different configurations highly

Accurate Models for Evaluating the Direct Conducted and Radiated Emissions from Integrated Circuits

Directory of Open Access Journals (Sweden)

Domenico Capriglione

2018-03-01

Full Text Available This paper deals with the electromagnetic compatibility (EMC issues related to the direct and radiated emissions from a high-speed integrated circuits (ICs. These emissions are evaluated here by means of circuital and electromagnetic models. As for the conducted emission, an equivalent circuit model is derived to describe the IC and the effect of its loads (package, printed circuit board, decaps, etc., based on the Integrated Circuit Emission Model template (ICEM. As for the radiated emission, an electromagnetic model is proposed, based on the superposition of the fields generated in the far field region by the loop currents flowing into the IC and the package pins. A custom experimental setup is designed for validating the models. Specifically, for the radiated emission measurement, a custom test board is designed and realized, able to highlight the contribution of the direct emission from the IC, usually hidden by the indirect emission coming from the printed circuit board. Measurements of the package currents and of the far-field emitted fields are carried out, providing a satisfactory agreement with the model predictions.

GRB 080916C AND GRB 090510: THE HIGH-ENERGY EMISSION AND THE AFTERGLOW

International Nuclear Information System (INIS)

Gao Weihong; Mao Jirong; Xu Dong; Fan Yizhong

2009-01-01

We constrain the physical composition of the outflows of GRBs 080916C and 090510 with the prompt emission data and find that the former is likely magnetic, while the latter may be baryonic. The X-ray and optical afterglow emission of both GRBs can be reasonably fitted using the standard external shock model but the density profiles of the circum-burst medium are different. We also propose a simple method to estimate the number of seed photons supposing the GeV afterglow photons are due to the inverse Compton radiation of external forward shock electrons. The seed photons needed in the modeling are too many to be realistic for both events. The synchrotron radiation of the forward shock seems able to account for the GeV afterglow data.

Validated analytical modeling of diesel engine regulated exhaust CO emission rate

Directory of Open Access Journals (Sweden)

Waleed F Faris

2016-06-01

Full Text Available Albeit vehicle analytical models are often favorable for explainable mathematical trends, no analytical model has been developed of the regulated diesel exhaust CO emission rate for trucks yet. This research unprecedentedly develops and validates for trucks a model of the steady speed regulated diesel exhaust CO emission rate analytically. It has been found that the steady speed–based CO exhaust emission rate is based on (1 CO2 dissociation, (2 the water–gas shift reaction, and (3 the incomplete combustion of hydrocarbon. It has been found as well that the steady speed–based CO exhaust emission rate based on CO2 dissociation is considerably less than the rate that is based on the water–gas shift reaction. It has also been found that the steady speed–based CO exhaust emission rate based on the water–gas shift reaction is the dominant source of CO exhaust emission. The study shows that the average percentage of deviation of the steady speed–based simulated results from the corresponding field data is 1.7% for all freeway cycles with 99% coefficient of determination at the confidence level of 95%. This deviation of the simulated results from field data outperforms its counterpart of widely recognized models such as the comprehensive modal emissions model and VT-Micro for all freeway cycles.

Spatial distribution of emissions to air – the SPREAD model

DEFF Research Database (Denmark)

Plejdrup, Marlene Schmidt; Gyldenkærne, Steen

The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark’s obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long...... quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation...

The Role of Temporal Evolution in Modeling Atmospheric Emissions from Tropical Fires

Science.gov (United States)

Marlier, Miriam E.; Voulgarakis, Apostolos; Shindell, Drew T.; Faluvegi, Gregory S.; Henry, Candise L.; Randerson, James T.

2014-01-01

Fire emissions associated with tropical land use change and maintenance influence atmospheric composition, air quality, and climate. In this study, we explore the effects of representing fire emissions at daily versus monthly resolution in a global composition-climate model. We find that simulations of aerosols are impacted more by the temporal resolution of fire emissions than trace gases such as carbon monoxide or ozone. Daily-resolved datasets concentrate emissions from fire events over shorter time periods and allow them to more realistically interact with model meteorology, reducing how often emissions are concurrently released with precipitation events and in turn increasing peak aerosol concentrations. The magnitude of this effect varies across tropical ecosystem types, ranging from smaller changes in modeling the low intensity, frequent burning typical of savanna ecosystems to larger differences when modeling the short-term, intense fires that characterize deforestation events. The utility of modeling fire emissions at a daily resolution also depends on the application, such as modeling exceedances of particulate matter concentrations over air quality guidelines or simulating regional atmospheric heating patterns.

A comparative analysis of several vehicle emission models for road freight transportation

NARCIS (Netherlands)

Demir, E.; Bektas, T.; Laporte, G.

2011-01-01

Reducing greenhouse gas emissions in freight transportation requires using appropriate emission models in the planning process. This paper reviews and numerically compares several available freight transportation vehicle emission models and also considers their outputs in relations to field studies.

Modeling and Simulation of the Gonghe geothermal field (Qinghai, China) Constrained by Geophysical

Science.gov (United States)

Zeng, Z.; Wang, K.; Zhao, X.; Huai, N.; He, R.

2017-12-01

The Gonghe geothermal field in Qinghai is important because of its variety of geothermal resource types. Now, the Gonghe geothermal field has been a demonstration area of geothermal development and utilization in China. It has been the topic of numerous geophysical investigations conducted to determine the depth to and the nature of the heat source, and to image the channel of heat flow. This work focuses on the causes of geothermal fields used numerical simulation method constrained by geophysical data. At first, by analyzing and inverting an magnetotelluric (MT) measurements profile across this area we obtain the deep resistivity distribution. Using the gravity anomaly inversion constrained by the resistivity profile, the density of the basins and the underlying rocks can be calculated. Combined with the measured parameters of rock thermal conductivity, the 2D geothermal conceptual model of Gonghe area is constructed. Then, the unstructured finite element method is used to simulate the heat conduction equation and the geothermal field. Results of this model were calibrated with temperature data for the observation well. A good match was achieved between the measured values and the model's predicted values. At last, geothermal gradient and heat flow distribution of this model are calculated(fig.1.). According to the results of geophysical exploration, there is a low resistance and low density region (d5) below the geothermal field. We recognize that this anomaly is generated by tectonic motion, and this tectonic movement creates a mantle-derived heat upstream channel. So that the anomalous basement heat flow values are higher than in other regions. The model's predicted values simulated using that boundary condition has a good match with the measured values. The simulated heat flow values show that the mantle-derived heat flow migrates through the boundary of the low-resistance low-density anomaly area to the Gonghe geothermal field, with only a small fraction

Historical Carbon Dioxide Emissions Caused by Land-Use Changes are Possibly Larger than Assumed

Science.gov (United States)

Arneth, A.; Sitch, S.; Pongratz, J.; Stocker, B. D.; Ciais, P.; Poulter, B.; Bayer, A. D.; Bondeau, A.; Calle, L.; Chini, L. P.;

Communication Schemes with Constrained Reordering of Resources

DEFF Research Database (Denmark)

Popovski, Petar; Utkovski, Zoran; Trillingsgaard, Kasper Fløe

2013-01-01

This paper introduces a communication model inspired by two practical scenarios. The first scenario is related to the concept of protocol coding, where information is encoded in the actions taken by an existing communication protocol. We investigate strategies for protocol coding via combinatorial...... reordering of the labelled user resources (packets, channels) in an existing, primary system. However, the degrees of freedom of the reordering are constrained by the operation of the primary system. The second scenario is related to communication systems with energy harvesting, where the transmitted signals...... are constrained by the energy that is available through the harvesting process. We have introduced a communication model that covers both scenarios and elicits their key feature, namely the constraints of the primary system or the harvesting process. We have shown how to compute the capacity of the channels...

Capacity Constrained Routing Algorithms for Evacuation Route Planning

National Research Council Canada - National Science Library

Lu, Qingsong; George, Betsy; Shekhar, Shashi

2006-01-01

.... In this paper, we propose a new approach, namely a capacity constrained routing planner which models capacity as a time series and generalizes shortest path algorithms to incorporate capacity constraints...

Modelling Emission of Pollutants from transportation using mobile sensing data

DEFF Research Database (Denmark)

Lehmann, Anders

The advent and the proliferation of the smartphone has promised new possibilities for researchers to gain knowledge about the habits and behaviour of people, as the ubiqui- tous smartphone with an array of sensors is capable of deliver a wealth of information. This dissertation addresses methods...... to use data acquired from smartphones to im- prove transportation related air quality models and models for climate gas emission from transportation. These models can be used for planning of transportation net- works, monitoring of air quality, and automate transport related green accounting. More...... database imple- mentations are a subfield of computer science. I have worked to bring these diverse research fields together to solve the challenge of improving modelling of transporta- tion related air quality emissions as well as modelling of transportation related climate gas emissions. The main...

Mechanistic modeling of reactive soil nitrogen emissions across agricultural management practices

Science.gov (United States)

Rasool, Q. Z.; Miller, D. J.; Bash, J. O.; Venterea, R. T.; Cooter, E. J.; Hastings, M. G.; Cohan, D. S.

2017-12-01

The global reactive nitrogen (N) budget has increased by a factor of 2-3 from pre-industrial levels. This increase is especially pronounced in highly N fertilized agricultural regions in summer. The reactive N emissions from soil to atmosphere can be in reduced (NH3) or oxidized (NO, HONO, N2O) forms, depending on complex biogeochemical transformations of soil N reservoirs. Air quality models like CMAQ typically neglect soil emissions of HONO and N2O. Previously, soil NO emissions estimated by models like CMAQ remained parametric and inconsistent with soil NH3 emissions. Thus, there is a need to more mechanistically and consistently represent the soil N processes that lead to reactive N emissions to the atmosphere. Our updated approach estimates soil NO, HONO and N2O emissions by incorporating detailed agricultural fertilizer inputs from EPIC, and CMAQ-modeled N deposition, into the soil N pool. EPIC addresses the nitrification, denitrification and volatilization rates along with soil N pools for agricultural soils. Suitable updates to account for factors like nitrite (NO2-) accumulation not addressed in EPIC, will also be made. The NO and N2O emissions from nitrification and denitrification are computed mechanistically using the N sub-model of DAYCENT. These mechanistic definitions use soil water content, temperature, NH4+ and NO3- concentrations, gas diffusivity and labile C availability as dependent parameters at various soil layers. Soil HONO emissions found to be most probable under high NO2- availability will be based on observed ratios of HONO to NO emissions under different soil moistures, pH and soil types. The updated scheme will utilize field-specific soil properties and N inputs across differing manure management practices such as tillage. Comparison of the modeled soil NO emission rates from the new mechanistic and existing schemes against field measurements will be discussed. Our updated framework will help to predict the diurnal and daily variability

Hyperbolicity and constrained evolution in linearized gravity

International Nuclear Information System (INIS)

Matzner, Richard A.

2005-01-01

Solving the 4-d Einstein equations as evolution in time requires solving equations of two types: the four elliptic initial data (constraint) equations, followed by the six second order evolution equations. Analytically the constraint equations remain solved under the action of the evolution, and one approach is to simply monitor them (unconstrained evolution). Since computational solution of differential equations introduces almost inevitable errors, it is clearly 'more correct' to introduce a scheme which actively maintains the constraints by solution (constrained evolution). This has shown promise in computational settings, but the analysis of the resulting mixed elliptic hyperbolic method has not been completely carried out. We present such an analysis for one method of constrained evolution, applied to a simple vacuum system, linearized gravitational waves. We begin with a study of the hyperbolicity of the unconstrained Einstein equations. (Because the study of hyperbolicity deals only with the highest derivative order in the equations, linearization loses no essential details.) We then give explicit analytical construction of the effect of initial data setting and constrained evolution for linearized gravitational waves. While this is clearly a toy model with regard to constrained evolution, certain interesting features are found which have relevance to the full nonlinear Einstein equations

Dynamics of the oil transition: Modeling capacity, depletion, and emissions

International Nuclear Information System (INIS)

Brandt, Adam R.; Plevin, Richard J.; Farrell, Alexander E.

2010-01-01

The global petroleum system is undergoing a shift to substitutes for conventional petroleum (SCPs). The Regional Optimization Model for Emissions from Oil Substitutes, or ROMEO, models this oil transition and its greenhouse gas impacts. ROMEO models the global liquid fuel market in an economic optimization framework, but in contrast to other models it solves each model year sequentially, with investment and production optimized under uncertainty about future prevailing prices or resource quantities. ROMEO includes more hydrocarbon resource types than integrated assessment models of climate change. ROMEO also includes the carbon intensities and costs of production of these resources. We use ROMEO to explore the uncertainty of future costs, emissions, and total fuel production under a number of scenarios. We perform sensitivity analysis on the endowment of conventional petroleum and future carbon taxes. Results show incremental emissions from production of oil substitutes of ∼ 0-30 gigatonnes (Gt) of carbon over the next 50 years (depending on the carbon tax). Also, demand reductions due to the higher cost of SCPs could reduce or eliminate these increases. Calculated emissions are highly sensitive to the endowment of conventional oil and less sensitive to a carbon tax.

Where do fossil fuel carbon dioxide emissions from California go? An analysis based on radiocarbon observations and an atmospheric transport model

Energy Technology Data Exchange (ETDEWEB)

Riley, W.J.; Hsueh, D.Y.; Randerson, J.T.; Fischer, M.L.; Hatch, J.G.; Pataki, D.E.; Wang, W.; Goulden, M.L.

2008-05-01

Characterizing flow patterns and mixing of fossil fuel-derived CO{sub 2} is important for effectively using atmospheric measurements to constrain emissions inventories. Here we used measurements and a model of atmospheric radiocarbon ({sup 14}C) to investigate the distribution and fluxes of atmospheric fossil fuel CO{sub 2} across the state of California. We sampled {sup 14}C in annual C{sub 3} grasses at 128 sites and used these measurements to test a regional model that simulated anthropogenic and ecosystem CO{sub 2} fluxes, transport in the atmosphere, and the resulting {sup 14}C of annual grasses ({Delta}{sub g}). Average measured {Delta}{sub g} in Los Angeles, San Francisco, the Central Valley, and the North Coast were 27.7 {+-} 20.0, 44.0 {+-} 10.9, 48.7 {+-} 1.9, and 59.9 {+-} 2.5{per_thousand}, respectively, during the 2004-2005 growing season. Model predictions reproduced regional patterns reasonably well, with estimates of 27.6 {+-} 2.4, 39.4 {+-} 3.9, 46.8 {+-} 3.0, and 59.3 {+-} 0.2{per_thousand} for these same regions and corresponding to fossil fuel CO{sub 2} mixing ratios (Cf) of 13.7, 6.1, 4.8, and 0.3 ppm. {Delta}{sub g} spatial heterogeneity in Los Angeles and San Francisco was higher in the measurements than in the predictions, probably from insufficient spatial resolution in the fossil fuel inventories (e.g., freeways are not explicitly included) and transport (e.g., within valleys). We used the model to predict monthly and annual transport patterns of fossil fuel-derived CO{sub 2} within and out of California. Fossil fuel CO{sub 2} emitted in Los Angeles and San Francisco was predicted to move into the Central Valley, raising Cf above that expected from local emissions alone. Annually, about 21, 39, 35, and 5% of fossil fuel emissions leave the California airspace to the north, east, south, and west, respectively, with large seasonal variations in the proportions. Positive correlations between westward fluxes and Santa Ana wind conditions were

Probabilistic and technology-specific modeling of emissions from municipal solid-waste incineration.

Science.gov (United States)

Koehler, Annette; Peyer, Fabio; Salzmann, Christoph; Saner, Dominik

2011-04-15

The European legislation increasingly directs waste streams which cannot be recycled toward thermal treatment. Models are therefore needed that help to quantify emissions of waste incineration and thus reveal potential risks and mitigation needs. This study presents a probabilistic model which computes emissions as a function of waste composition and technological layout of grate incineration plants and their pollution-control equipment. In contrast to previous waste-incineration models, this tool is based on a broader empirical database and allows uncertainties in emission loads to be quantified. Comparison to monitoring data of 83 actual European plants showed no significant difference between modeled emissions and measured data. An inventory of all European grate incineration plants including technical characteristics and plant capacities was established, and waste material mixtures were determined for different European countries, including generic elemental waste-material compositions. The model thus allows for calculation of country-specific and material-dependent emission factors and enables identification and tracking of emission sources. It thereby helps to develop strategies to decrease plant emissions by reducing or redirecting problematic waste fractions to other treatment options or adapting the technological equipment of waste incinerators.

Identification of different geologic units using fuzzy constrained resistivity tomography

Science.gov (United States)

Singh, Anand; Sharma, S. P.

2018-01-01

Different geophysical inversion strategies are utilized as a component of an interpretation process that tries to separate geologic units based on the resistivity distribution. In the present study, we present the results of separating different geologic units using fuzzy constrained resistivity tomography. This was accomplished using fuzzy c means, a clustering procedure to improve the 2D resistivity image and geologic separation within the iterative minimization through inversion. First, we developed a Matlab-based inversion technique to obtain a reliable resistivity image using different geophysical data sets (electrical resistivity and electromagnetic data). Following this, the recovered resistivity model was converted into a fuzzy constrained resistivity model by assigning the highest probability value of each model cell to the cluster utilizing fuzzy c means clustering procedure during the iterative process. The efficacy of the algorithm is demonstrated using three synthetic plane wave electromagnetic data sets and one electrical resistivity field dataset. The presented approach shows improvement on the conventional inversion approach to differentiate between different geologic units if the correct number of geologic units will be identified. Further, fuzzy constrained resistivity tomography was performed to examine the augmentation of uranium mineralization in the Beldih open cast mine as a case study. We also compared geologic units identified by fuzzy constrained resistivity tomography with geologic units interpreted from the borehole information.

The zonal structure of tropical O3 and CO as observed by the Tropospheric Emission Spectrometer in November 2004 – Part 2: Impact of surface emissions on O3 and its precursors

Directory of Open Access Journals (Sweden)

G. Osterman

2009-06-01

Full Text Available The impact of surface emissions on the zonal structure of tropical tropospheric ozone and carbon monoxide is investigated for November 2004 using satellite observations, in-situ measurements, and chemical transport models in conjunction with inverse-estimated surface emissions.Vertical ozone profiles from the Tropospheric Emission Spectrometer (TES and ozone sonde measurements from the Southern Hemisphere Additional Ozonesondes (SHADOZ network show elevated concentrations of ozone over Indonesia and Australia (60–70 ppb in the lower troposphere against the backdrop of the well-known zonal "wave-one" pattern with ozone concentrations of (70–80 ppb centered over the Atlantic . Observational evidence from TES CO vertical profiles and Ozone Monitoring Instrument (OMI NO2 columns point to regional surface emissions as an important contributor to the elevated ozone over Indonesia. This contribution is investigated with the GEOS-Chem chemistry and transport model using surface emission estimates derived from an optimal inverse model, which was constrained by TES and Measurements Of Pollution In The Troposphere (MOPITT CO profiles (Jones et al., 2009. These a posteriori estimates, which were over a factor of 2 greater than climatological emissions, reduced differences between GEOS-Chem and TES ozone observations by 30–40% over Indonesia. The response of the free tropospheric chemical state to the changes in these emissions is investigated for ozone, CO, NOx, and PAN. Model simulations indicate that ozone over Indonesian/Australian is sensitive to regional changes in surface emissions of NOx but relatively insensitive to lightning NOx. Over sub-equatorial Africa and South America, free tropospheric NOx was reduced in response to increased surface emissions potentially muting ozone production.

Sharp spatially constrained inversion

DEFF Research Database (Denmark)

Vignoli, Giulio G.; Fiandaca, Gianluca G.; Christiansen, Anders Vest C A.V.C.

2013-01-01

We present sharp reconstruction of multi-layer models using a spatially constrained inversion with minimum gradient support regularization. In particular, its application to airborne electromagnetic data is discussed. Airborne surveys produce extremely large datasets, traditionally inverted...... by using smoothly varying 1D models. Smoothness is a result of the regularization constraints applied to address the inversion ill-posedness. The standard Occam-type regularized multi-layer inversion produces results where boundaries between layers are smeared. The sharp regularization overcomes...... inversions are compared against classical smooth results and available boreholes. With the focusing approach, the obtained blocky results agree with the underlying geology and allow for easier interpretation by the end-user....

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

Directory of Open Access Journals (Sweden)

Yuan-yuan Song

2013-01-01

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

On the convergence of the dynamic series solution of a constrained ...

African Journals Online (AJOL)

The one dimensional problem of analysing the dynamic behaviour of an elevated water tower with elastic deflection–control device and subjected to a dynamic load was examined in [2]. The constrained elastic system was modeled as a column carrying a concentrated mass at its top and elastically constrained at a point ...

Constraining the neutrino magnetic dipole moment from white dwarf pulsations

International Nuclear Information System (INIS)

Córsico, A.H.; Althaus, L.G.; Bertolami, M.M. Miller; Kepler, S.O.; García-Berro, E.

2014-01-01

Pulsating white dwarf stars can be used as astrophysical laboratories to constrain the properties of weakly interacting particles. Comparing the cooling rates of these stars with the expected values from theoretical models allows us to search for additional sources of cooling due to the emission of axions, neutralinos, or neutrinos with magnetic dipole moment. In this work, we derive an upper bound to the neutrino magnetic dipole moment (μ ν ) using an estimate of the rate of period change of the pulsating DB white dwarf star PG 1351+489. We employ state-of-the-art evolutionary and pulsational codes which allow us to perform a detailed asteroseismological period fit based on fully DB white dwarf evolutionary sequences. Plasmon neutrino emission is the dominant cooling mechanism for this class of hot pulsating white dwarfs, and so it is the main contributor to the rate of change of period with time (Pidot) for the DBV class. Thus, the inclusion of an anomalous neutrino emission through a non-vanishing magnetic dipole moment in these sequences notably influences the evolutionary timescales, and also the expected pulsational properties of the DBV stars. By comparing the theoretical Pidot value with the rate of change of period with time of PG 1351+489, we assess the possible existence of additional cooling by neutrinos with magnetic dipole moment. Our models suggest the existence of some additional cooling in this pulsating DB white dwarf, consistent with a non-zero magnetic dipole moment with an upper limit of μ ν  ∼< 10 -11  μ B . This bound is somewhat less restrictive than, but still compatible with, other limits inferred from the white dwarf luminosity function or from the color-magnitude diagram of the Globular cluster M5. Further improvements of the measurement of the rate of period change of the dominant pulsation mode of PG 1351+489 will be necessary to confirm our bound

Bridging greenhouse gas emissions and renewable energy deployment target: Comparative assessment of China and India

International Nuclear Information System (INIS)

Mittal, Shivika; Dai, Hancheng; Fujimori, Shinichiro; Masui, Toshihiko

2016-01-01

Highlights: • India and China’s latest renewable energy targets toward 2030 are assessed. • Carbon emission cap is in line with 2-degree target and governmental commitment. • The impacts of renewable energy on emissions and mitigation costs are quantified. - Abstract: Renewable energy has a critical role in limiting the greenhouse gas (GHG) emissions. This paper assesses the implication of aligning renewable energy deployment target with national emission reduction target for mitigation cost. The assessment methodology uses Asia-Pacific Integrated Assessment/computable general equilibrium (AIM/CGE) model to determine the mitigation cost in terms of GDP and welfare loss under alternative renewable targets in different climate-constrained scenarios. A range of country-specific emission constraints is taken to address the uncertainties related to global emission pathway and emission entitlement scheme. Comparative results show that China needs to increase its share of non-fossil fuel significantly in the primary energy mix to achieve the stringent emission reduction target compared to India. The mitigation cost in terms of economic and welfare loss can be reduced by increasing the penetration of the renewable energy to achieve the same emission reduction target. The modeling results show that coordinated national climate and renewable energy policies help to achieve the GHG emission reduction target in an efficient and cost-effective manner.

The first 1-year-long estimate of the Paris region fossil fuel CO2 emissions based on atmospheric inversion

Directory of Open Access Journals (Sweden)

J. Staufer

2016-11-01

Full Text Available The ability of a Bayesian atmospheric inversion to quantify the Paris region's fossil fuel CO2 emissions on a monthly basis, based on a network of three surface stations operated for 1 year as part of the CO2-MEGAPARIS experiment (August 2010–July 2011, is analysed. Differences in hourly CO2 atmospheric mole fractions between the near-ground monitoring sites (CO2 gradients, located at the north-eastern and south-western edges of the urban area, are used to estimate the 6 h mean fossil fuel CO2 emission. The inversion relies on the CHIMERE transport model run at 2 km  ×  2 km horizontal resolution, on the spatial distribution of fossil fuel CO2 emissions in 2008 from a local inventory established at 1 km  ×  1 km horizontal resolution by the AIRPARIF air quality agency, and on the spatial distribution of the biogenic CO2 fluxes from the C-TESSEL land surface model. It corrects a prior estimate of the 6 h mean budgets of the fossil fuel CO2 emissions given by the AIRPARIF 2008 inventory. We found that a stringent selection of CO2 gradients is necessary for reliable inversion results, due to large modelling uncertainties. In particular, the most robust data selection analysed in this study uses only mid-afternoon gradients if wind speeds are larger than 3 m s−1 and if the modelled wind at the upwind site is within ±15° of the transect between downwind and upwind sites. This stringent data selection removes 92 % of the hourly observations. Even though this leaves few remaining data to constrain the emissions, the inversion system diagnoses that their assimilation significantly reduces the uncertainty in monthly emissions: by 9 % in November 2010 to 50 % in October 2010. The inverted monthly mean emissions correlate well with independent monthly mean air temperature. Furthermore, the inverted annual mean emission is consistent with the independent revision of the AIRPARIF inventory for the year

Top-down NOx and SO2 emissions simultaneously estimated from different OMI retrievals and inversion frameworks

Science.gov (United States)

Qu, Z.; Henze, D. K.; Wang, J.; Xu, X.; Wang, Y.

2017-12-01

Quantifying emissions trends of nitrogen oxides (NOx) and sulfur dioxide (SO2) is important for improving understanding of air pollution and the effectiveness of emission control strategies. We estimate long-term (2005-2016) global (2° x 2.5° resolution) and regional (North America and East Asia at 0.5° x 0.667° resolution) NOx emissions using a recently developed hybrid (mass-balance / 4D-Var) method with GEOS-Chem. NASA standard product and DOMINO retrievals of NO2 column are both used to constrain emissions; comparison of these results provides insight into regions where trends are most robust with respect to retrieval uncertainties, and highlights regions where seemingly significant trends are retrieval-specific. To incorporate chemical interactions among species, we extend our hybrid method to assimilate NO2 and SO2 observations and optimize NOx and SO2 emissions simultaneously. Due to chemical interactions, inclusion of SO2 observations leads to 30% grid-scale differences in posterior NOx emissions compared to those constrained only by NO2 observations. When assimilating and optimizing both species in pseudo observation tests, the sum of the normalized mean squared error (compared to the true emissions) of NOx and SO2 posterior emissions are 54-63% smaller than when observing/constraining a single species. NOx and SO2 emissions are also correlated through the amount of fuel combustion. To incorporate this correlation into the inversion, we optimize seven sector-specific emission scaling factors, including industry, energy, residential, aviation, transportation, shipping and agriculture. We compare posterior emissions from inversions optimizing only species' emissions, only sector-based emissions, and both species' and sector-based emissions. In situ measurements of NOx and SO2 are applied to evaluate the performance of these inversions. The impacts of the inversion on PM2.5 and O3 concentrations and premature deaths are also evaluated.

Model for bremsstrahlung emission accompanying interactions between protons and nuclei from low energies up to intermediate energies: Role of magnetic emission

Science.gov (United States)

Maydanyuk, Sergei P.

2012-07-01

A model of the bremsstrahlung emission which accompanies proton decay and collisions of protons off nuclei in the low- to intermediate-energy region has been developed. This model includes spin formalism, a potential approach for describing the interaction between protons and nuclei, and an emission that includes a component of the magnetic emission (defined on the basis of the Pauli equation). For the problem of bremsstrahlung during proton decay the role of magnetic emission is studied by using such a model. For the 146Tm nucleus the following has been studied: (1) How much does the magnetic emission change the full bremsstrahlung spectrum? (2) At which angle is the magnetic emission the most intensive relative to the electric emission? (3) Is there some spatial region where the magnetic emission increases strongly relative to the electric emission? (4) How intensive is the magnetic emission in the tunneling region? (5) Which is the maximal probability? Which value does it equal to at the zero-energy limit of the emitted photons? It is demonstrated that the model is able to describe well enough experimental data of bremsstrahlung emission which accompanies collisions of protons off 9C, 64Cu, and 107Ag nuclei at an incident energy of Tlab=72 MeV (at a photon energy up to 60 MeV) and off 9Be, 12C, and 208Pb nuclei at an incident energy of Tlab=140 MeV (at a photon energy up to 120 MeV).

Development of an emissions inventory model for mobile sources

Energy Technology Data Exchange (ETDEWEB)

Reynolds, A W; Broderick, B M [Trinity College, Dublin (Ireland). Dept. of Civil, Structural and Environmental Engineering

2000-07-01

Traffic represents one of the largest sources of primary air pollutants in urban areas. As a consequence, numerous abatement strategies are being pursued to decrease the ambient concentrations of a wide range of pollutants. A mutual characteristic of most of these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emissions inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for a wide range of vehicle types. The majority of inventories are compiled using 'passive' data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. Current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this paper. a methodology for estimating emissions from mobile sources using real-time data is described. This methodology is used to calculate emissions of sulphur dioxide (SO{sub 2}), oxides of nitrogen (NO{sub x}), carbon monoxide (CO). volatile organic compounds (VOC), particulate matter less than 10 {mu}m aerodynamic diameter (PM{sub 10}), 1,3-butadiene (C{sub 4}H{sub 6}) and benzene (C{sub 6}H{sub 6}) at a test junction in Dublin. Traffic data, which are required on a street-by-street basis, is obtained from induction loops and closed circuit televisions (CCTV) as well as statistical data. The observed traffic data are compared to simulated data from a travel demand model. As a test case, an emissions inventory is compiled for a heavily trafficked signalized junction in an urban environment using the measured data. In order that the model may be validated, the predicted emissions are employed in a dispersion model along with local meteorological conditions and site geometry. The resultant pollutant concentrations are compared to average ambient kerbside conditions

NUMERICAL PREDICTION MODELS FOR AIR POLLUTION BY MOTOR VEHICLE EMISSIONS

Directory of Open Access Journals (Sweden)

M. M. Biliaiev

2016-12-01

Full Text Available Purpose. Scientific work involves: 1 development of 3D numerical models that allow calculating the process of air pollution by motor vehicles emissions; 2 creation of models which would allow predicting the air pollution level in urban areas. Methodology. To solve the problem upon assessing the level of air pollution by motor vehicles emissions fundamental equations of aerodynamics and mass transfer are used. For the solution of differential equations of aerodynamics and mass transfer finite-difference methods are used. For the numerical integration of the equation for the velocity potential the method of conditional approximations is applied. The equation for the velocity potential written in differential form, splits into two equations, where at each step of splitting an unknown value of the velocity potential is determined by an explicit scheme of running computation, while the difference scheme is implicit one. For the numerical integration of the emissions dispersion equation in the atmosphere applies the implicit alternating-triangular difference scheme of splitting. Emissions from the road are modeled by a series of point sources of given intensity. Developed numerical models form is the basis of the created software package. Findings. 3D numerical models were developed; they belong to the class of «diagnostic models». These models take into account main physical factors that influence the process of dispersion of harmful substances in the atmosphere when emissions from vehicles in the city occur. Based on the constructed numerical models the computational experiment was conducted to assess the level of air pollution in the street. Originality. Authors have developed numerical models that allow to calculate the 3D aerodynamics of the wind flow in urban areas and the process of mass transfer emissions from the highway. Calculations to determine the area of contamination, which is formed near the buildings, located along the highway were

Constraining Light-Quark Yukawa Couplings from Higgs Distributions

Science.gov (United States)

Bishara, Fady; Haisch, Ulrich; Monni, Pier Francesco; Re, Emanuele

2017-03-01

We propose a novel strategy to constrain the bottom and charm Yukawa couplings by exploiting Large Hadron Collider (LHC) measurements of transverse momentum distributions in Higgs production. Our method does not rely on the reconstruction of exclusive final states or heavy-flavor tagging. Compared to other proposals, it leads to an enhanced sensitivity to the Yukawa couplings due to distortions of the differential Higgs spectra from emissions which either probe quark loops or are associated with quark-initiated production. We derive constraints using data from LHC run I, and we explore the prospects of our method at future LHC runs. Finally, we comment on the possibility of bounding the strange Yukawa coupling.

Constraining Light-Quark Yukawa Couplings from Higgs Distributions.

Science.gov (United States)

Bishara, Fady; Haisch, Ulrich; Monni, Pier Francesco; Re, Emanuele

2017-03-24

We propose a novel strategy to constrain the bottom and charm Yukawa couplings by exploiting Large Hadron Collider (LHC) measurements of transverse momentum distributions in Higgs production. Our method does not rely on the reconstruction of exclusive final states or heavy-flavor tagging. Compared to other proposals, it leads to an enhanced sensitivity to the Yukawa couplings due to distortions of the differential Higgs spectra from emissions which either probe quark loops or are associated with quark-initiated production. We derive constraints using data from LHC run I, and we explore the prospects of our method at future LHC runs. Finally, we comment on the possibility of bounding the strange Yukawa coupling.

A chance-constrained stochastic approach to intermodal container routing problems.

Science.gov (United States)

Zhao, Yi; Liu, Ronghui; Zhang, Xi; Whiteing, Anthony

2018-01-01

We consider a container routing problem with stochastic time variables in a sea-rail intermodal transportation system. The problem is formulated as a binary integer chance-constrained programming model including stochastic travel times and stochastic transfer time, with the objective of minimising the expected total cost. Two chance constraints are proposed to ensure that the container service satisfies ship fulfilment and cargo on-time delivery with pre-specified probabilities. A hybrid heuristic algorithm is employed to solve the binary integer chance-constrained programming model. Two case studies are conducted to demonstrate the feasibility of the proposed model and to analyse the impact of stochastic variables and chance-constraints on the optimal solution and total cost.

Constraining the mass of the Local Group

Science.gov (United States)

Carlesi, Edoardo; Hoffman, Yehuda; Sorce, Jenny G.; Gottlöber, Stefan

2017-03-01

The mass of the Local Group (LG) is a crucial parameter for galaxy formation theories. However, its observational determination is challenging - its mass budget is dominated by dark matter that cannot be directly observed. To meet this end, the posterior distributions of the LG and its massive constituents have been constructed by means of constrained and random cosmological simulations. Two priors are assumed - the Λ cold dark matter model that is used to set up the simulations, and an LG model that encodes the observational knowledge of the LG and is used to select LG-like objects from the simulations. The constrained simulations are designed to reproduce the local cosmography as it is imprinted on to the Cosmicflows-2 data base of velocities. Several prescriptions are used to define the LG model, focusing in particular on different recent estimates of the tangential velocity of M31. It is found that (a) different vtan choices affect the peak mass values up to a factor of 2, and change mass ratios of MM31 to MMW by up to 20 per cent; (b) constrained simulations yield more sharply peaked posterior distributions compared with the random ones; (c) LG mass estimates are found to be smaller than those found using the timing argument; (d) preferred Milky Way masses lie in the range of (0.6-0.8) × 1012 M⊙; whereas (e) MM31 is found to vary between (1.0-2.0) × 1012 M⊙, with a strong dependence on the vtan values used.

A supply function model for representing the strategic bidding of the producers in constrained electricity markets

International Nuclear Information System (INIS)

Bompard, Ettore; Napoli, Roberto; Lu, Wene; Jiang, Xiuchen

2010-01-01

The modeling of the bidding behaviour of the producer is a key-point in the modeling and simulation of the competitive electricity markets. In our paper, the linear supply function model is applied so as to find the Supply Function Equilibrium analytically. It also proposed a new and efficient approach to find SFEs for the network constrained electricity markets by finding the best slope of the supply function with the help of changing the intercept, and the method can be applied on the large systems. The approach proposed is applied to study IEEE-118 bus test systems and the comparison between bidding slope and bidding intercept is presented, as well, with reference to the test system. (author)

Constrained optimization of test intervals using a steady-state genetic algorithm

International Nuclear Information System (INIS)

Martorell, S.; Carlos, S.; Sanchez, A.; Serradell, V.

2000-01-01

There is a growing interest from both the regulatory authorities and the nuclear industry to stimulate the use of Probabilistic Risk Analysis (PRA) for risk-informed applications at Nuclear Power Plants (NPPs). Nowadays, special attention is being paid on analyzing plant-specific changes to Test Intervals (TIs) within the Technical Specifications (TSs) of NPPs and it seems to be a consensus on the need of making these requirements more risk-effective and less costly. Resource versus risk-control effectiveness principles formally enters in optimization problems. This paper presents an approach for using the PRA models in conducting the constrained optimization of TIs based on a steady-state genetic algorithm (SSGA) where the cost or the burden is to be minimized while the risk or performance is constrained to be at a given level, or vice versa. The paper encompasses first with the problem formulation, where the objective function and constraints that apply in the constrained optimization of TIs based on risk and cost models at system level are derived. Next, the foundation of the optimizer is given, which is derived by customizing a SSGA in order to allow optimizing TIs under constraints. Also, a case study is performed using this approach, which shows the benefits of adopting both PRA models and genetic algorithms, in particular for the constrained optimization of TIs, although it is also expected a great benefit of using this approach to solve other engineering optimization problems. However, care must be taken in using genetic algorithms in constrained optimization problems as it is concluded in this paper

A Lifecycle Emissions Model (LEM): Lifecycle Emissions from Transportation Fuels, Motor Vehicles, Transportation Modes, Electricity Use, Heating and Cooking Fuels, and Materials

OpenAIRE

Delucchi, Mark

2003-01-01

This report documents changes to the methods and data in a recently revised version of the greenhouse-gas emissions model originally documented in Emissions of Greenhouse Gases from the Use of Transportation Fuels and Electricity, ANL/ESD/TM-22, Volumes 1 and 2, Center for Transportation Research, Argonne National Laboratory, Argonne (ANL), Illinois (DeLuchi, 1991, 1993). The revised Lifecycle Emissions Model (LEM) calculates energy use, air-pollutant emissions, and CO2-equivalent emissions o...

Effects of improved spatial and temporal modeling of on-road vehicle emissions.

Science.gov (United States)

Lindhjem, Christian E; Pollack, Alison K; DenBleyker, Allison; Shaw, Stephanie L

2012-04-01

Numerous emission and air quality modeling studies have suggested the need to accurately characterize the spatial and temporal variations in on-road vehicle emissions. The purpose of this study was to quantify the impact that using detailed traffic activity data has on emission estimates used to model air quality impacts. The on-road vehicle emissions are estimated by multiplying the vehicle miles traveled (VMT) by the fleet-average emission factors determined by road link and hour of day. Changes in the fraction of VMT from heavy-duty diesel vehicles (HDDVs) can have a significant impact on estimated fleet-average emissions because the emission factors for HDDV nitrogen oxides (NOx) and particulate matter (PM) are much higher than those for light-duty gas vehicles (LDGVs). Through detailed road link-level on-road vehicle emission modeling, this work investigated two scenarios for better characterizing mobile source emissions: (1) improved spatial and temporal variation of vehicle type fractions, and (2) use of Motor Vehicle Emission Simulator (MOVES2010) instead of MOBILE6 exhaust emission factors. Emissions were estimated for the Detroit and Atlanta metropolitan areas for summer and winter episodes. The VMT mix scenario demonstrated the importance of better characterizing HDDV activity by time of day, day of week, and road type. More HDDV activity occurs on restricted access road types on weekdays and at nonpeak times, compared to light-duty vehicles, resulting in 5-15% higher NOx and PM emission rates during the weekdays and 15-40% lower rates on weekend days. Use of MOVES2010 exhaust emission factors resulted in increases of more than 50% in NOx and PM for both HDDVs and LDGVs, relative to MOBILE6. Because LDGV PM emissions have been shown to increase with lower temperatures, the most dramatic increase from MOBILE6 to MOVES2010 emission rates occurred for PM2.5 from LDGVs that increased 500% during colder wintertime conditions found in Detroit, the northernmost

Hydrochlorofluorocarbon and hydrofluorocarbon emissions in East Asia determined by inverse modeling

Directory of Open Access Journals (Sweden)

A. Stohl

2010-04-01