Guevara, M; Tena, C; Soret, A; Serradell, K; Guzmán, D; Retama, A; Camacho, P; Jaimes-Palomera, M; Mediavilla, A
2017-04-15
This article describes the High-Elective Resolution Modelling Emission System for Mexico (HERMES-Mex) model, an emission processing tool developed to transform the official Mexico City Metropolitan Area (MCMA) emission inventory into hourly, gridded (up to 1km 2 ) and speciated emissions used to drive mesoscale air quality simulations with the Community Multi-scale Air Quality (CMAQ) model. The methods and ancillary information used for the spatial and temporal disaggregation and speciation of the emissions are presented and discussed. The resulting emission system is evaluated, and a case study on CO, NO 2 , O 3 , VOC and PM 2.5 concentrations is conducted to demonstrate its applicability. Moreover, resulting traffic emissions from the Mobile Source Emission Factor Model for Mexico (MOBILE6.2-Mexico) and the MOtor Vehicle Emission Simulator for Mexico (MOVES-Mexico) models are integrated in the tool to assess and compare their performance. NO x and VOC total emissions modelled are reduced by 37% and 26% in the MCMA when replacing MOBILE6.2-Mexico for MOVES-Mexico traffic emissions. In terms of air quality, the system composed by the Weather Research and Forecasting model (WRF) coupled with the HERMES-Mex and CMAQ models properly reproduces the pollutant levels and patterns measured in the MCMA. The system's performance clearly improves in urban stations with a strong influence of traffic sources when applying MOVES-Mexico emissions. Despite reducing estimations of modelled precursor emissions, O 3 peak averages are increased in the MCMA core urban area (up to 30ppb) when using MOVES-Mexico mobile emissions due to its VOC-limited regime, while concentrations in the surrounding suburban/rural areas decrease or increase depending on the meteorological conditions of the day. The results obtained suggest that the HERMES-Mex model can be used to provide model-ready emissions for air quality modelling in the MCMA. Copyright © 2017 Elsevier B.V. All rights reserved.
Single stage queueing/manufacturing system model that involves emission variable
NASA Astrophysics Data System (ADS)
Murdapa, P. S.; Pujawan, I. N.; Karningsih, P. D.; Nasution, A. H.
2018-04-01
Queueing is commonly occured at every industry. The basic model of queueing theory gives a foundation for modeling a manufacturing system. Nowadays, carbon emission is an important and inevitable issue due to its huge impact to our environment. However, existing model of queuing applied for analysis of single stage manufacturing system has not taken Carbon emissions into consideration. If it is applied to manufacturing context, it may lead to improper decisisions. By taking into account of emission variables into queuing models, not only the model become more comprehensive but also it creates awareness on the issue to many parties that involves in the system. This paper discusses the single stage M/M/1 queueing model that involves emission variable. Hopefully it could be a starting point for the next more complex models. It has a main objective for determining how carbon emissions could fit into the basic queueing theory. It turned out that the involvement of emission variables into the model has modified the traditional model of a single stage queue to a calculation model of production lot quantity allowed per period.
The importance of biogenic emissions for regional air quality modeling is generally recognized [Guenther et al., 2000]. Since the 1980s, biogenic emission estimates have been derived from algorithms such as the Biogenic Emissions Inventory System (BEIS) [Pierce et. al., 1998]....
(EDMUNDS, WA) WILDLAND FIRE EMISSIONS MODELING: INTEGRATING BLUESKY AND SMOKE
This presentation is a status update of the BlueSky emissions modeling system. BlueSky-EM has been coupled with the Sparse Matrix Operational Kernel Emissions (SMOKE) system, and is now available as a tool for estimating emissions from wildland fires
NASA Astrophysics Data System (ADS)
Ma, Junhai; Yang, Wenhui; Lou, Wandong
This paper establishes an oligopolistic game model under the carbon emission reduction constraint and investigates its complex characteristics like bifurcation and chaos. Two oligopolistic manufacturers comprise three mixed game models, aiming to explore the variation in the status of operating system as per the upgrading of benchmark reward-penalty mechanism. Firstly, we set up these basic models that are respectively distinguished with carbon emission quantity and study these models using different game methods. Then, we concentrate on one typical game model to further study the dynamic complexity of variations in the system status, through 2D bifurcation diagrams and 4D parameter adjustment features based on the bounded rationality scheme for price, and the adaptive scheme for carbon emission. The results show that the carbon emission constraint has significant influence on the status variation of two-oligopolistic game operating systems no matter whether it is stable or chaotic. Besides, the new carbon emission regulation meets government supervision target and achieves the goal of being environment friendly by motivating the system to operate with lower carbon emission.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 6 2010-07-01 2010-07-01 false Model Rule-Requirements for Continuous Emission Monitoring Systems (CEMS) 4 Table 4 to Subpart FFFF of Part 60 Protection of Environment...—Model Rule—Requirements for Continuous Emission Monitoring Systems (CEMS) As stated in § 60.3039, you...
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 6 2011-07-01 2011-07-01 false Model Rule-Requirements for Continuous Emission Monitoring Systems (CEMS) 4 Table 4 to Subpart FFFF of Part 60 Protection of Environment...—Model Rule—Requirements for Continuous Emission Monitoring Systems (CEMS) As stated in § 60.3039, you...
USDA-ARS?s Scientific Manuscript database
Modeling routines of the Integrated Farm System Model (IFSM version 4.2) and Dairy Gas Emission Model (DairyGEM version 3.2), two whole-farm simulation models developed and maintained by USDA-ARS, were revised with new components for: (1) simulation of ammonia (NH3) and greenhouse gas emissions gene...
Modeling regional-scale wildland fire emissions with the wildland fire emissions information system
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...
O'Brien, D; Shalloo, L; Patton, J; Buckley, F; Grainger, C; Wallace, M
2012-09-01
Life cycle assessment (LCA) and the Intergovernmental Panel on Climate Change (IPCC) guideline methodology, which are the principal greenhouse gas (GHG) quantification methods, were evaluated in this study using a dairy farm GHG model. The model was applied to estimate GHG emissions from two contrasting dairy systems: a seasonal calving pasture-based dairy farm and a total confinement dairy system. Data used to quantify emissions from these systems originated from a research study carried out over a 1-year period in Ireland. The genetic merit of cows modelled was similar for both systems. Total mixed ration was fed in the Confinement system, whereas grazed grass was mainly fed in the grass-based system. GHG emissions from these systems were quantified per unit of product and area. The results of both methods showed that the dairy system that emitted the lowest GHG emissions per unit area did not necessarily emit the lowest GHG emissions possible for a given level of product. Consequently, a recommendation from this study is that GHG emissions be evaluated per unit of product given the growing affluent human population and increasing demand for dairy products. The IPCC and LCA methods ranked dairy systems' GHG emissions differently. For instance, the IPCC method quantified that the Confinement system reduced GHG emissions per unit of product by 8% compared with the grass-based system, but the LCA approach calculated that the Confinement system increased emissions by 16% when off-farm emissions associated with primary dairy production were included. Thus, GHG emissions should be quantified using approaches that quantify the total GHG emissions associated with the production system, so as to determine whether the dairy system was causing emissions displacement. The IPCC and LCA methods were also used in this study to simulate, through a dairy farm GHG model, what effect management changes within both production systems have on GHG emissions. The findings suggest that single changes have a small mitigating effect on GHG emissions (<5%), except for strategies used to control emissions from manure storage in the Confinement system (14% to 24%). However, when several management strategies were combined, GHG emissions per unit of product could be reduced significantly (15% to 30%). The LCA method was identified as the preferred approach to assess the effect of management changes on GHG emissions, but the analysis indicated that further standardisation of the approach is needed given the sensitivity of the approach to allocation decisions regarding milk and meat.
Dace, Elina; Muizniece, Indra; Blumberga, Andra; Kaczala, Fabio
2015-09-15
European Union (EU) Member States have agreed to limit their greenhouse gas (GHG) emissions from sectors not covered by the EU Emissions Trading Scheme (non-ETS). That includes also emissions from agricultural sector. Although the Intergovernmental Panel on Climate Change (IPCC) has established a methodology for assessment of GHG emissions from agriculture, the forecasting options are limited, especially when policies and their interaction with the agricultural system are tested. Therefore, an advanced tool, a system dynamics model, was developed that enables assessment of effects various decisions and measures have on agricultural GHG emissions. The model is based on the IPCC guidelines and includes the main elements of an agricultural system, i.e. land management, livestock farming, soil fertilization and crop production, as well as feedback mechanisms between the elements. The case of Latvia is selected for simulations, as agriculture generates 22% of the total anthropogenic GHG emissions in the country. The results demonstrate that there are very limited options for GHG mitigation in the agricultural sector. Thereby, reaching the non-ETS GHG emission targets will be very challenging for Latvia, as the level of agricultural GHG emissions will be exceeded considerably above the target levels. Thus, other non-ETS sectors will have to reduce their emissions drastically to "neutralize" the agricultural sector's emissions for reaching the EU's common ambition to move towards low-carbon economy. The developed model may serve as a decision support tool for impact assessment of various measures and decisions on the agricultural system's GHG emissions. Although the model is applied to the case of Latvia, the elements and structure of the model developed are similar to agricultural systems in many countries. By changing numeric values of certain parameters, the model can be applied to analyze decisions and measures in other countries. Copyright © 2015 Elsevier B.V. All rights reserved.
USDA-ARS?s Scientific Manuscript database
Animal facilities are significant contributors of gaseous emissions including ammonia (NH3) and nitrous oxide (N2O). Previous versions of the Integrated Farm System Model (IFSM version 4.0) and Dairy Gas Emissions Model (DairyGEM version 3.0), two whole-farm simulation models developed by USDA-ARS, ...
System-wide emissions implications of increased wind power penetration.
Valentino, Lauren; Valenzuela, Viviana; Botterud, Audun; Zhou, Zhi; Conzelmann, Guenter
2012-04-03
This paper discusses the environmental effects of incorporating wind energy into the electric power system. We present a detailed emissions analysis based on comprehensive modeling of power system operations with unit commitment and economic dispatch for different wind penetration levels. First, by minimizing cost, the unit commitment model decides which thermal power plants will be utilized based on a wind power forecast, and then, the economic dispatch model dictates the level of production for each unit as a function of the realized wind power generation. Finally, knowing the power production from each power plant, the emissions are calculated. The emissions model incorporates the effects of both cycling and start-ups of thermal power plants in analyzing emissions from an electric power system with increasing levels of wind power. Our results for the power system in the state of Illinois show significant emissions effects from increased cycling and particularly start-ups of thermal power plants. However, we conclude that as the wind power penetration increases, pollutant emissions decrease overall due to the replacement of fossil fuels.
Modeling methane and nitrous oxide emissions from direct-seeded rice systems
NASA Astrophysics Data System (ADS)
Simmonds, Maegen B.; Li, Changsheng; Lee, Juhwan; Six, Johan; van Kessel, Chris; Linquist, Bruce A.
2015-10-01
Process-based modeling of CH4 and N2O emissions from rice fields is a practical tool for conducting greenhouse gas inventories and estimating mitigation potentials of alternative practices at the scale of management and policy making. However, the accuracy of these models in simulating CH4 and N2O emissions in direct-seeded rice systems under various management practices remains a question. We empirically evaluated the denitrification-decomposition model for estimating CH4 and N2O fluxes in California rice systems. Five and nine site-year combinations were used for calibration and validation, respectively. The model was parameterized for two cultivars, M206 and Koshihikari, and able to simulate 30% and 78% of the variation in measured yields, respectively. Overall, modeled and observed seasonal CH4 emissions were similar (R2 = 0.85), but there was poor correspondence in fallow period CH4 emissions and in seasonal and fallow period N2O emissions. Furthermore, management effects on seasonal CH4 emissions were highly variable and not well represented by the model (0.2-465% absolute relative deviation). Specifically, simulated CH4 emissions were oversensitive to fertilizer N rate but lacked sensitivity to the type of seeding system (dry seeding versus water seeding) and prior fallow period straw management. Additionally, N2O emissions were oversensitive to fertilizer N rate and field drainage. Sensitivity analysis showed that CH4 emissions were highly sensitive to changes in the root to total plant biomass ratio, suggesting that it is a significant source of model uncertainty. These findings have implications for model-directed field research that could improve model representation of paddy soils for application at larger spatial scales.
NASA Astrophysics Data System (ADS)
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. The seasonality and relative importance of the various natural emissions categories are described.
NASA Astrophysics Data System (ADS)
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 relative importance of the various natural emissions categories are described.
NASA Astrophysics Data System (ADS)
Reid, J. S.; Westphal, D. L.; Christopher, S. A.; Prins, E. M.; Gasso, S.; Reid, E.; Theisen, M.; Schmidt, C. C.; Hunter, J.; Eck, T.
2002-05-01
The Fire Locating and Modeling of Burning Emissions (FLAMBE') project is a joint Navy, NOAA, NASA and university project to integrate satellite products with numerical aerosol models to produce a real time fire and emissions inventory. At the center of the program is the Wildfire Automated Biomass Burning Algorithm (WF ABBA) which provides real-time fire products and the NRL Aerosol Analysis and Prediction System to model smoke transport. In this presentation we give a brief overview of the system and methods, but emphasize new estimations of smoke coverage and emission fluxes from the South American continent. Temporal and smoke patterns compare reasonably well with AERONET and MODIS aerosol optical depth products for the 2000 and 2001 fire seasons. Fluxes are computed by relating NAAPS output fields and MODIS optical depth maps with modeled wind fields. Smoke emissions and transport fluxes out of the continent can then be estimated by perturbing the modeled emissions to gain agreement with the satellite and wind products. Regional smoke emissions are also presented for grass and forest burning.
40 CFR 60.1725 - How are the data from the continuous emission monitoring systems used?
Code of Federal Regulations, 2011 CFR
2011-07-01
... emission monitoring systems used? 60.1725 Section 60.1725 Protection of Environment ENVIRONMENTAL... Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1725 How are the data from the continuous emission monitoring systems used? You must use data from the continuous emission monitoring...
40 CFR 60.1725 - How are the data from the continuous emission monitoring systems used?
Code of Federal Regulations, 2010 CFR
2010-07-01
... emission monitoring systems used? 60.1725 Section 60.1725 Protection of Environment ENVIRONMENTAL... Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1725 How are the data from the continuous emission monitoring systems used? You must use data from the continuous emission monitoring...
Validation of the measure automobile emissions model : a statistical analysis
DOT National Transportation Integrated Search
2000-09-01
The Mobile Emissions Assessment System for Urban and Regional Evaluation (MEASURE) model provides an external validation capability for hot stabilized option; the model is one of several new modal emissions models designed to predict hot stabilized e...
The Dairy Greenhouse Gas Emission Model: Reference Manual
USDA-ARS?s Scientific Manuscript database
The Dairy Greenhouse Gas Model (DairyGHG) is a software tool for estimating the greenhouse gas emissions and carbon footprint of dairy production systems. A relatively simple process-based model is used to predict the primary greenhouse gas emissions, which include the net emission of carbon dioxide...
Waldrip, Heidi M; Rotz, C Alan; Hafner, Sasha D; Todd, Richard W; Cole, N Andy
2014-07-01
Ammonia (NH) volatilization from manure in beef cattle feedyards results in loss of agronomically important nitrogen (N) and potentially leads to overfertilization and acidification of aquatic and terrestrial ecosystems. In addition, NH is involved in the formation of atmospheric fine particulate matter (PM), which can affect human health. Process-based models have been developed to estimate NH emissions from various livestock production systems; however, little work has been conducted to assess their accuracy for large, open-lot beef cattle feedyards. This work describes the extension of an existing process-based model, the Integrated Farm Systems Model (IFSM), to include simulation of N dynamics in this type of system. To evaluate the model, IFSM-simulated daily per capita NH emission rates were compared with emissions data collected from two commercial feedyards in the Texas High Plains from 2007 to 2009. Model predictions were in good agreement with observations and were sensitive to variations in air temperature and dietary crude protein concentration. Predicted mean daily NH emission rates for the two feedyards had 71 to 81% agreement with observations. In addition, IFSM estimates of annual feedyard emissions were within 11 to 24% of observations, whereas a constant emission factor currently in use by the USEPA underestimated feedyard emissions by as much as 79%. The results from this study indicate that IFSM can quantify average feedyard NH emissions, assist with emissions reporting, provide accurate information for legislators and policymakers, investigate methods to mitigate NH losses, and evaluate the effects of specific management practices on farm nutrient balances. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
An intercomparison of biogenic emissions estimates from BEIS2 and BIOME: Reconciling the differences
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wilkinson, J.G.; Emigh, R.A.; Pierce, T.E.
1996-12-31
Biogenic emissions play a critical role in urban and regional air quality. For instance, biogenic emissions contribute upwards of 76% of the daily hydrocarbon emissions in the Atlanta, Georgia airshed. The Biogenic Emissions Inventory System-Version 2.0 (BEIS2) and the Biogenic Model for Emissions (BIOME) are two models that compute biogenic emissions estimates. BEIS2 is a FORTRAN-based system, and BIOME is an ARC/INFO{reg_sign} - and SAS{reg_sign}-based system. Although the technical formulations of the models are similar, the models produce different biogenic emissions estimates for what appear to be essentially the same inputs. The goals of our study are the following: (1)more » Determine why BIOME and BEIS2 produce different emissions estimates; (2) Attempt to understand the impacts that the differences have on the emissions estimates; (3) Reconcile the differences where possible; and (4) Present a framework for the use of BEIS2 and BIOME. In this study, we used the Coastal Oxidant Assessment for Southeast Texas (COAST) biogenics data which were supplied to us courtesy of the Texas Natural Resource Conservation Commission (TNRCC), and we extracted the BEIS2 data for the same domain. We compared the emissions estimates of the two models using their respective data sets BIOME Using TNRCC data and BEIS2 using BEIS2 data.« less
Code of Federal Regulations, 2012 CFR
2012-07-01
... Emission Monitoring Systems (CEMS) 4 Table 4 to Subpart FFFF of Part 60 Protection of Environment... Construction On or Before December 9, 2004 Pt. 60, Subpt. FFFF, Table 4 Table 4 to Subpart FFFF of Part 60—Model Rule—Requirements for Continuous Emission Monitoring Systems (CEMS) As stated in § 60.3039, you...
Code of Federal Regulations, 2013 CFR
2013-07-01
... Emission Monitoring Systems (CEMS) 4 Table 4 to Subpart FFFF of Part 60 Protection of Environment... Construction On or Before December 9, 2004 Pt. 60, Subpt. FFFF, Table 4 Table 4 to Subpart FFFF of Part 60—Model Rule—Requirements for Continuous Emission Monitoring Systems (CEMS) As stated in § 60.3039, you...
Code of Federal Regulations, 2014 CFR
2014-07-01
... Emission Monitoring Systems (CEMS) 4 Table 4 to Subpart FFFF of Part 60 Protection of Environment... Construction On or Before December 9, 2004 Pt. 60, Subpt. FFFF, Table 4 Table 4 to Subpart FFFF of Part 60—Model Rule—Requirements for Continuous Emission Monitoring Systems (CEMS) As stated in § 60.3039, you...
NASA Technical Reports Server (NTRS)
Tan, Qian; Santanello, Joseph A., Jr.; Zhou, Shujia; Tao, Zhining; Peters-Lidard, Christa d.; Chn, Mian
2011-01-01
Land-Atmosphere coupling is typically designed and implemented independently for physical (e.g. water and energy) and chemical (e.g. biogenic emissions and surface depositions)-based models and applications. Differences in scale, data requirements, and physics thus limit the ability of Earth System models to be fully coupled in a consistent manner. In order for the physical-chemical-biological coupling to be complete, treatment of the land in terms of surface classification, condition, fluxes, and emissions must be considered simultaneously and coherently across all components. In this study, we investigate a coupling strategy for the NASA-Unified Weather Research and Forecasting (NU-WRF) model that incorporates the traditionally disparate fluxes of water and energy through NASA's LIS (Land Information System) and biogenic emissions through BEIS (Biogenic Emissions Inventory System) and MEGAN (Model of Emissions of Gases and Aerosols from Nature) into the atmosphere. In doing so, inconsistencies across model inputs and parameter data are resolved such that the emissions from a particular plant species are consistent with the heat and moisture fluxes calculated for that land cover type. In turn, the response of the atmospheric turbulence and mixing in the planetary boundary layer (PBL) acts on the identical surface type, fluxes, and emissions for each. In addition, the coupling of dust emission within the NU-WRF system is performed in order to ensure consistency and to maximize the benefit of high-resolution land representation in LIS. The impacts of those self-consistent components on' the simulation of atmospheric aerosols are then evaluated through the WRF-Chem-GOCART (Goddard Chemistry Aerosol Radiation and Transport) model. Overall, this ambitious project highlights the current difficulties and future potential of fully coupled. components. in Earth System models, and underscores the importance of the iLEAPS community in supporting improved knowledge of processes and innovative approaches for models and observations.
Radiated Emissions from a Remote-Controlled Airplane-Measured in a Reverberation Chamber
NASA Technical Reports Server (NTRS)
Ely, Jay J.; Koppen, Sandra V.; Nguyen, Truong X.; Dudley, Kenneth L.; Szatkowski, George N.; Quach, Cuong C.; Vazquez, Sixto L.; Mielnik, John J.; Hogge, Edward F.; Hill, Boyd L.;
2011-01-01
A full-vehicle, subscale all-electric model airplane was tested for radiated emissions, using a reverberation chamber. The mission of the NASA model airplane is to test in-flight airframe damage diagnosis and battery prognosis algorithms, and provide experimental data for other aviation safety research. Subscale model airplanes are economical experimental tools, but assembling their systems from hobbyist and low-cost components may lead to unforseen electromagnetic compatibility problems. This report provides a guide for accommodating the on-board radio systems, so that all model airplane systems may be operated during radiated emission testing. Radiated emission data are provided for on-board systems being operated separately and together, so that potential interferors can be isolated and mitigated. The report concludes with recommendations for EMI/EMC best practices for subscale model airplanes and airships used for research.
HEMCO v1.0: A Versatile, ESMF-Compliant Component for Calculating Emissions in Atmospheric Models
NASA Technical Reports Server (NTRS)
Keller, C. A.; Long, M. S.; Yantosca, R. M.; Da Silva, A. M.; Pawson, S.; Jacob, D. J.
2014-01-01
We describe the Harvard-NASA Emission Component version 1.0 (HEMCO), a stand-alone software component for computing emissions in global atmospheric models. HEMCO determines emissions from different sources, regions, and species on a user-defined grid and can combine, overlay, and update a set of data inventories and scale factors, as specified by the user through the HEMCO configuration file. New emission inventories at any spatial and temporal resolution are readily added to HEMCO and can be accessed by the user without any preprocessing of the data files or modification of the source code. Emissions that depend on dynamic source types and local environmental variables such as wind speed or surface temperature are calculated in separate HEMCO extensions. HEMCO is fully compliant with the Earth System Modeling Framework (ESMF) environment. It is highly portable and can be deployed in a new model environment with only few adjustments at the top-level interface. So far, we have implemented HEMCO in the NASA Goddard Earth Observing System (GEOS-5) Earth system model (ESM) and in the GEOS-Chem chemical transport model (CTM). By providing a widely applicable framework for specifying constituent emissions, HEMCO is designed to ease sensitivity studies and model comparisons, as well as inverse modeling in which emissions are adjusted iteratively. The HEMCO code, extensions, and the full set of emissions data files used in GEOS-Chem are available at http: //wiki.geos-chem.org/HEMCO.
Jensen, Trine S; Jensen, Jørgen D; Hasler, Berit; Illerup, Jytte B; Andersen, Frits M
2007-01-01
Integrated modelling of the interaction between environmental pressure and economic development is a useful tool to evaluate environmental consequences of policy initiatives. However, the usefulness of such models is often restricted by the fact that these models only include a limited set of environmental impacts, which are often energy-related emissions. In order to evaluate the development in the overall environmental pressure correctly, these model systems must be extended. In this article an integrated macroeconomic model system of the Danish economy with environmental modules of energy related emissions is extended to include the agricultural contribution to climate change and acidification. Next to the energy sector, the agricultural sector is the most important contributor to these environmental themes and subsequently the extended model complex calculates more than 99% of the contribution to both climate change and acidification. Environmental sub-models are developed for agriculture-related emissions of CH(4), N(2)O and NH(3). Agricultural emission sources related to the production specific activity variables are mapped and emission dependent parameters are identified in order to calculate emission coefficients. The emission coefficients are linked to the economic activity variables of the Danish agricultural production. The model system is demonstrated by projections of agriculture-related emissions in Denmark under two alternative sets of assumptions: a baseline projection of the general economic development and a policy scenario for changes in the husbandry sector within the agricultural sector.
EMISSION AND SURFACE EXCHANGE PROCESS
This task supports the development, evaluation, and application of emission and dry deposition algorithms in air quality simulation models, such as the Models-3/Community Multiscale Air Quality (CMAQ) modeling system. Emission estimates influence greatly the accuracy of air qual...
Locatelli, R.; Bousquet, P.; Chevallier, F.; ...
2013-10-08
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 10more » 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. Here 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 question the consistency of transport model errors in current inverse systems.« less
NASA Astrophysics Data System (ADS)
Mayfield, E. N.; Robinson, A. L.; Cohon, J. L.
2017-12-01
This work assesses trade-offs between system-wide and superemitter policy options for reducing methane emissions from compressor stations in the U.S. transmission and storage system. Leveraging recently collected national emissions and activity data sets, we developed a new process-based emissions model implemented in a Monte Carlo simulation framework to estimate emissions for each component and facility in the system. We find that approximately 83% of emissions, given the existing suite of technologies, have the potential to be abated, with only a few emission categories comprising a majority of emissions. We then formulate optimization models to determine optimal abatement strategies. Most emissions across the system (approximately 80%) are efficient to abate, resulting in net benefits ranging from 160M to 1.2B annually across the system. The private cost burden is minimal under standard and tax instruments, and if firms market the abated natural gas, private net benefits may be generated. Superemitter policies, namely, those that target the highest emitting facilities, may reduce the private cost burden and achieve high emission reductions, especially if emissions across facilities are highly skewed. However, detection across all facilities is necessary regardless of the policy option and there are nontrivial net benefits resulting from abatement of relatively low-emitting sources.
Mayfield, Erin N; Robinson, Allen L; Cohon, Jared L
2017-05-02
This work assesses trade-offs between system-wide and superemitter policy options for reducing methane emissions from compressor stations in the U.S. transmission and storage system. Leveraging recently collected national emissions and activity data sets, we developed a new process-based emissions model implemented in a Monte Carlo simulation framework to estimate emissions for each component and facility in the system. We find that approximately 83% of emissions, given the existing suite of technologies, have the potential to be abated, with only a few emission categories comprising a majority of emissions. We then formulate optimization models to determine optimal abatement strategies. Most emissions across the system (approximately 80%) are efficient to abate, resulting in net benefits ranging from $160M to $1.2B annually across the system. The private cost burden is minimal under standard and tax instruments, and if firms market the abated natural gas, private net benefits may be generated. Superemitter policies, namely, those that target the highest emitting facilities, may reduce the private cost burden and achieve high emission reductions, especially if emissions across facilities are highly skewed. However, detection across all facilities is necessary regardless of the policy option and there are nontrivial net benefits resulting from abatement of relatively low-emitting sources.
Land Surface Microwave Emissivity Dynamics: Observations, Analysis and Modeling
NASA Technical Reports Server (NTRS)
Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Kumar, Sujay; Ringerud, Sarah
2014-01-01
Land surface microwave emissivity affects remote sensing of both the atmosphere and the land surface. The dynamical behavior of microwave emissivity over a very diverse sample of land surface types is studied. With seven years of satellite measurements from AMSR-E, we identified various dynamical regimes of the land surface emission. In addition, we used two radiative transfer models (RTMs), the Community Radiative Transfer Model (CRTM) and the Community Microwave Emission Modeling Platform (CMEM), to simulate land surface emissivity dynamics. With both CRTM and CMEM coupled to NASA's Land Information System, global-scale land surface microwave emissivities were simulated for five years, and evaluated against AMSR-E observations. It is found that both models have successes and failures over various types of land surfaces. Among them, the desert shows the most consistent underestimates (by approx. 70-80%), due to limitations of the physical models used, and requires a revision in both systems. Other snow-free surface types exhibit various degrees of success and it is expected that parameter tuning can improve their performances.
Code of Federal Regulations, 2010 CFR
2010-07-01
... Continuous Emission Monitoring Systems (CEMS) 6 Table 6 to Subpart BBBB of Part 60 Protection of Environment...—Requirements for Validating Continuous Emission Monitoring Systems (CEMS) For the following continuous emission monitoring systems Use the following methods in appendix A of this part to validate poollutant concentratin...
Code of Federal Regulations, 2011 CFR
2011-07-01
... Continuous Emission Monitoring Systems (CEMS) 6 Table 6 to Subpart BBBB of Part 60 Protection of Environment...—Requirements for Validating Continuous Emission Monitoring Systems (CEMS) For the following continuous emission monitoring systems Use the following methods in appendix A of this part to validate poollutant concentratin...
Carbon accounting and economic model uncertainty of emissions from biofuels-induced land use change.
Plevin, Richard J; Beckman, Jayson; Golub, Alla A; Witcover, Julie; O'Hare, Michael
2015-03-03
Few of the numerous published studies of the emissions from biofuels-induced "indirect" land use change (ILUC) attempt to propagate and quantify uncertainty, and those that have done so have restricted their analysis to a portion of the modeling systems used. In this study, we pair a global, computable general equilibrium model with a model of greenhouse gas emissions from land-use change to quantify the parametric uncertainty in the paired modeling system's estimates of greenhouse gas emissions from ILUC induced by expanded production of three biofuels. We find that for the three fuel systems examined--US corn ethanol, Brazilian sugar cane ethanol, and US soybean biodiesel--95% of the results occurred within ±20 g CO2e MJ(-1) of the mean (coefficient of variation of 20-45%), with economic model parameters related to crop yield and the productivity of newly converted cropland (from forestry and pasture) contributing most of the variance in estimated ILUC emissions intensity. Although the experiments performed here allow us to characterize parametric uncertainty, changes to the model structure have the potential to shift the mean by tens of grams of CO2e per megajoule and further broaden distributions for ILUC emission intensities.
Carbon Dioxide Emissions Effects of Grid-Scale Electricity Storage in a Decarbonizing Power System
Craig, Michael T.; Jaramillo, Paulina; Hodge, Bri-Mathias
2018-01-03
While grid-scale electricity storage (hereafter 'storage') could be crucial for deeply decarbonizing the electric power system, it would increase carbon dioxide (CO 2) emissions in current systems across the United States. To better understand how storage transitions from increasing to decreasing system CO 2 emissions, we quantify the effect of storage on operational CO 2 emissions as a power system decarbonizes under a moderate and strong CO 2 emission reduction target through 2045. Under each target, we compare the effect of storage on CO 2 emissions when storage participates in only energy, only reserve, and energy and reserve markets. Wemore » conduct our study in the Electricity Reliability Council of Texas (ERCOT) system and use a capacity expansion model to forecast generator fleet changes and a unit commitment and economic dispatch model to quantify system CO 2 emissions with and without storage. We find that storage would increase CO 2 emissions in the current ERCOT system, but would decrease CO 2 emissions in 2025 through 2045 under both decarbonization targets. Storage reduces CO 2 emissions primarily by enabling gas-fired generation to displace coal-fired generation, but also by reducing wind and solar curtailment. We further find that the market in which storage participates drives large differences in the magnitude, but not the direction, of the effect of storage on CO 2 emissions.« less
Carbon Dioxide Emissions Effects of Grid-Scale Electricity Storage in a Decarbonizing Power System
DOE Office of Scientific and Technical Information (OSTI.GOV)
Craig, Michael T.; Jaramillo, Paulina; Hodge, Bri-Mathias
While grid-scale electricity storage (hereafter 'storage') could be crucial for deeply decarbonizing the electric power system, it would increase carbon dioxide (CO 2) emissions in current systems across the United States. To better understand how storage transitions from increasing to decreasing system CO 2 emissions, we quantify the effect of storage on operational CO 2 emissions as a power system decarbonizes under a moderate and strong CO 2 emission reduction target through 2045. Under each target, we compare the effect of storage on CO 2 emissions when storage participates in only energy, only reserve, and energy and reserve markets. Wemore » conduct our study in the Electricity Reliability Council of Texas (ERCOT) system and use a capacity expansion model to forecast generator fleet changes and a unit commitment and economic dispatch model to quantify system CO 2 emissions with and without storage. We find that storage would increase CO 2 emissions in the current ERCOT system, but would decrease CO 2 emissions in 2025 through 2045 under both decarbonization targets. Storage reduces CO 2 emissions primarily by enabling gas-fired generation to displace coal-fired generation, but also by reducing wind and solar curtailment. We further find that the market in which storage participates drives large differences in the magnitude, but not the direction, of the effect of storage on CO 2 emissions.« less
Carbon dioxide emissions effects of grid-scale electricity storage in a decarbonizing power system
NASA Astrophysics Data System (ADS)
Craig, Michael T.; Jaramillo, Paulina; Hodge, Bri-Mathias
2018-01-01
While grid-scale electricity storage (hereafter ‘storage’) could be crucial for deeply decarbonizing the electric power system, it would increase carbon dioxide (CO2) emissions in current systems across the United States. To better understand how storage transitions from increasing to decreasing system CO2 emissions, we quantify the effect of storage on operational CO2 emissions as a power system decarbonizes under a moderate and strong CO2 emission reduction target through 2045. Under each target, we compare the effect of storage on CO2 emissions when storage participates in only energy, only reserve, and energy and reserve markets. We conduct our study in the Electricity Reliability Council of Texas (ERCOT) system and use a capacity expansion model to forecast generator fleet changes and a unit commitment and economic dispatch model to quantify system CO2 emissions with and without storage. We find that storage would increase CO2 emissions in the current ERCOT system, but would decrease CO2 emissions in 2025 through 2045 under both decarbonization targets. Storage reduces CO2 emissions primarily by enabling gas-fired generation to displace coal-fired generation, but also by reducing wind and solar curtailment. We further find that the market in which storage participates drives large differences in the magnitude, but not the direction, of the effect of storage on CO2 emissions.
40 CFR 60.3038 - What continuous emission monitoring systems must I install?
Code of Federal Regulations, 2011 CFR
2011-07-01
... December 9, 2004 Model Rule-Monitoring § 60.3038 What continuous emission monitoring systems must I install? (a) You must install, calibrate, maintain, and operate continuous emission monitoring systems for... system according to the “Monitoring Requirements” in § 60.13. ...
40 CFR 60.3038 - What continuous emission monitoring systems must I install?
Code of Federal Regulations, 2010 CFR
2010-07-01
... December 9, 2004 Model Rule-Monitoring § 60.3038 What continuous emission monitoring systems must I install? (a) You must install, calibrate, maintain, and operate continuous emission monitoring systems for... system according to the “Monitoring Requirements” in § 60.13. ...
Impact of High Resolution Land-Use Data in Meteorology and Air Quality Modeling Systems
Accurate land use information is important in meteorology for land surface exchanges, in emission modeling for emission spatial allocation, and in air quality modeling for chemical surface fluxes. Currently, meteorology, emission, and air quality models often use outdated USGS Gl...
Long, Shicheng; Zhu, Yun; Jang, Carey; Lin, Che-Jen; Wang, Shuxiao; Zhao, Bin; Gao, Jian; Deng, Shuang; Xie, Junping; Qiu, Xuezhen
2016-03-01
This article describes the development and application of a streamlined air control and response modeling system with a novel response surface modeling-linear coupled fitting method and a new module to provide streamlined model data for PM2.5 attainment assessment in China. This method is capable of significantly reducing the dimensions required to establish a response surface model, as well as capturing more realistic response of PM2.5 to emission changes with a limited number of model simulations. The newly developed module establishes a data link between the system and the Software for Model Attainment Test-Community Edition (SMAT-CE), and has the ability to rapidly provide model responses to emission control scenarios for SMAT-CE using a simple interface. The performance of this streamlined system is demonstrated through a case study of the Yangtze River Delta (YRD) in China. Our results show that this system is capable of reproducing the Community Multi-Scale Air Quality (CMAQ) model simulation results with maximum mean normalized error<3.5%. It is also demonstrated that primary emissions make a major contribution to ambient levels of PM2.5 in January and August (e.g., more than 50% contributed by primary emissions in Shanghai), and Shanghai needs to have regional emission control both locally and in its neighboring provinces to meet China's annual PM2.5 National Ambient Air Quality Standard. The streamlined system provides a real-time control/response assessment to identify the contributions of major emission sources to ambient PM2.5 (and potentially O3 as well) and streamline air quality data for SMAT-CE to perform attainment assessments. Copyright © 2015. Published by Elsevier B.V.
Delay-feedback control strategy for reducing CO2 emission of traffic flow system
NASA Astrophysics Data System (ADS)
Zhang, Li-Dong; Zhu, Wen-Xing
2015-06-01
To study the signal control strategy for reducing traffic emission theoretically, we first presented a kind of discrete traffic flow model with relative speed term based on traditional coupled map car-following model. In the model, the relative speed difference between two successive running cars is incorporated into following vehicle's acceleration running equation. Then we analyzed its stability condition with discrete control system stability theory. Third, we designed a delay-feedback controller to suppress traffic jam and decrease traffic emission based on modern controller theory. Last, numerical simulations are made to support our theoretical results, including the comparison of models' stability analysis, the influence of model type and signal control on CO2 emissions. The results show that the temporal behavior of our model is superior to other models, and the traffic signal controller has good effect on traffic jam suppression and traffic CO2 emission, which fully supports the theoretical conclusions.
PARTICULATE EMISSIONS AND CONTROL IN FLUIDIZED-BED COMBUSTION: MODELING AND PARAMETRIC PERFORMANCE
The report discusses a model, developed to describe the physical characteristics of the particulates emitted from fluidized-bed combustion (FBC) systems and to evaluate data on FBC particulate control systems. The model, which describes the particulate emissions profile from FBC,...
NASA Astrophysics Data System (ADS)
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.
Greenhouse gas emissions from integrated urban drainage systems: Where do we stand?
NASA Astrophysics Data System (ADS)
Mannina, Giorgio; Butler, David; Benedetti, Lorenzo; Deletic, Ana; Fowdar, Harsha; Fu, Guangtao; Kleidorfer, Manfred; McCarthy, David; Steen Mikkelsen, Peter; Rauch, Wolfgang; Sweetapple, Chris; Vezzaro, Luca; Yuan, Zhiguo; Willems, Patrick
2018-04-01
As sources of greenhouse gas (GHG) emissions, integrated urban drainage systems (IUDSs) (i.e., sewer systems, wastewater treatment plants and receiving water bodies) contribute to climate change. This paper, produced by the International Working Group on Data and Models, which works under the IWA/IAHR Joint Committee on Urban Drainage, reviews the state-of-the-art and modelling tools developed recently to understand and manage GHG emissions from IUDS. Further, open problems and research gaps are discussed and a framework for handling GHG emissions from IUDSs is presented. The literature review reveals that there is a need to strengthen already available mathematical models for IUDS to take GHG into account.
Pulsed Rabi oscillations in quantum two-level systems: beyond the area theorem
NASA Astrophysics Data System (ADS)
Fischer, Kevin A.; Hanschke, Lukas; Kremser, Malte; Finley, Jonathan J.; Müller, Kai; Vučković, Jelena
2018-01-01
The area theorem states that when a short optical pulse drives a quantum two-level system, it undergoes Rabi oscillations in the probability of scattering a single photon. In this work, we investigate the breakdown of the area theorem as both the pulse length becomes non-negligible and for certain pulse areas. Using simple quantum trajectories, we provide an analytic approximation to the photon emission dynamics of a two-level system. Our model provides an intuitive way to understand re-excitation, which elucidates the mechanism behind the two-photon emission events that can spoil single-photon emission. We experimentally measure the emission statistics from a semiconductor quantum dot, acting as a two-level system, and show good agreement with our simple model for short pulses. Additionally, the model clearly explains our recent results (Fischer and Hanschke 2017 et al Nat. Phys.) showing dominant two-photon emission from a two-level system for pulses with interaction areas equal to an even multiple of π.
Modeling and predicting low-speed vehicle emissions as a function of driving kinematics.
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.
NASA Astrophysics Data System (ADS)
Jalkanen, J.-P.; Johansson, L.; Kukkonen, J.; Brink, A.; Kalli, J.; Stipa, T.
2011-08-01
A method is presented for the evaluation of the exhaust emissions of marine traffic, based on the messages provided by the Automatic Identification System (AIS), which enable the positioning of ship emissions with a high spatial resolution (typically a few metres). The model also takes into account the detailed technical data of each individual vessel. The previously developed model was applicable for evaluating the emissions of NOx, SOx and CO2. This paper addresses a substantial extension of the modelling system, to allow also for the mass-based emissions of particulate matter (PM) and carbon monoxide (CO). The presented Ship Traffic Emissions Assessment Model (STEAM2) allows for the influences of accurate travel routes and ship speed, engine load, fuel sulphur content, multiengine setups, abatement methods and waves. We address in particular the modeling of the influence on the emissions of both engine load and the sulphur content of the fuel. The presented methodology can be used to evaluate the total PM emissions, and those of organic carbon, elemental carbon, ash and hydrated sulphate. We have evaluated the performance of the extended model against available experimental data on engine power, fuel consumption and the composition-resolved emissions of PM. As example results, the geographical distributions of the emissions of PM and CO are presented for the marine regions surrounding the Danish Straits.
Coupling population dynamics with earth system models: the POPEM model.
Navarro, Andrés; Moreno, Raúl; Jiménez-Alcázar, Alfonso; Tapiador, Francisco J
2017-09-16
Precise modeling of CO 2 emissions is important for environmental research. This paper presents a new model of human population dynamics that can be embedded into ESMs (Earth System Models) to improve climate modeling. Through a system dynamics approach, we develop a cohort-component model that successfully simulates historical population dynamics with fine spatial resolution (about 1°×1°). The population projections are used to improve the estimates of CO 2 emissions, thus transcending the bulk approach of existing models and allowing more realistic non-linear effects to feature in the simulations. The module, dubbed POPEM (from Population Parameterization for Earth Models), is compared with current emission inventories and validated against UN aggregated data. Finally, it is shown that the module can be used to advance toward fully coupling the social and natural components of the Earth system, an emerging research path for environmental science and pollution research.
Code of Federal Regulations, 2013 CFR
2013-07-01
... Emission Monitoring Systems (CEMS) 7 Table 7 to Subpart BBBB of Part 60 Protection of Environment... or Before August 30, 1999 Pt. 60, Subpt. BBBB, Table 7 Table 7 to Subpart BBBB of Part 60—Model Rule... sulfur dioxide emissions of the municipal waste combustion unit 4. Carbon Monoxide 125 percent of the...
Code of Federal Regulations, 2012 CFR
2012-07-01
... Emission Monitoring Systems (CEMS) 7 Table 7 to Subpart BBBB of Part 60 Protection of Environment... or Before August 30, 1999 Pt. 60, Subpt. BBBB, Table 7 Table 7 to Subpart BBBB of Part 60—Model Rule... sulfur dioxide emissions of the municipal waste combustion unit 4. Carbon Monoxide 125 percent of the...
Code of Federal Regulations, 2014 CFR
2014-07-01
... Emission Monitoring Systems (CEMS) 7 Table 7 to Subpart BBBB of Part 60 Protection of Environment... or Before August 30, 1999 Pt. 60, Subpt. BBBB, Table 7 Table 7 to Subpart BBBB of Part 60—Model Rule... sulfur dioxide emissions of the municipal waste combustion unit 4. Carbon Monoxide 125 percent of the...
Zhang, Xiaodong; Huang, Gordon
2014-03-15
Waste management activities can release greenhouse gases (GHGs) to the atmosphere, intensifying global climate change. Mitigation of the associated GHG emissions is vital and should be considered within integrated municipal solid waste (MSW) management planning. In this study, a fuzzy possibilistic integer programming (FPIM) model has been developed for waste management facility expansion and waste flow allocation planning with consideration of GHG emission trading in an MSW management system. It can address the interrelationships between MSW management planning and GHG emission control. The scenario of total system GHG emission control is analyzed for reflecting the feature that GHG emission credits may be tradable. An interactive solution algorithm is used to solve the FPIM model based on the uncertainty-averse preferences of decision makers in terms of p-necessity level, which represents the certainty degree of the imprecise objective. The FPIM model has been applied to a hypothetical MSW planning problem, where optimal decision schemes for facility expansion and waste flow allocation have been achieved with consideration of GHG emission control. The results indicate that GHG emission credit trading can decrease total system cost through re-allocation of GHG emission credits within the entire MSW management system. This will be helpful for decision makers to effectively determine the allowable GHG emission permits in practices. Copyright © 2014 Elsevier Ltd. All rights reserved.
LSPM J1314+1320: An Oversized Magnetic Star with Constraints on the Radio Emission Mechanism
DOE Office of Scientific and Technical Information (OSTI.GOV)
MacDonald, James; Mullan, D. J.
LSPM J1314+1320 (=NLTT 33370) is a binary star system consisting of two nearly identical pre-main-sequence stars of spectral type M7. The system is remarkable among ultracool dwarfs for being the most luminous radio emitter over the widest frequency range. Masses and luminosities are at first sight consistent with the system being coeval at age ∼80 Myr according to standard (nonmagnetic) evolutionary models. However, these models predict an average effective temperature of ∼2950 K, which is 180 K hotter than the empirical value. Thus, the empirical radii are oversized relative to the standard models by ≈13%. We demonstrate that magnetic stellarmore » models can quantitatively account for the oversizing. As a check on our models, we note that the radio emission limits the surface magnetic field strengths: the limits depend on identifying the radio emission mechanism. We find that the field strengths required by our magnetic models are too strong to be consistent with gyrosynchrotron emission but are consistent with electron cyclotron maser emission.« less
A new windblown dust emission treatment was incorporated in the Community Multiscale Air Quality (CMAQ) modeling system. This new model treatment has been built upon previously developed physics-based parameterization schemes from the literature. A distinct and novel feature of t...
DOT National Transportation Integrated Search
2007-07-01
In early 2001, the US Federal Aviation Administration embarked on a multi-year effort to develop a new computer model, the System for assessing Aviation's Global Emissions (SAGE). Currently at Version 1.5, the basic use of the model has centered on t...
NASA Astrophysics Data System (ADS)
Jalkanen, J.-P.; Johansson, L.; Kukkonen, J.; Brink, A.; Kalli, J.; Stipa, T.
2012-03-01
A method is presented for the evaluation of the exhaust emissions of marine traffic, based on the messages provided by the Automatic Identification System (AIS), which enable the positioning of ship emissions with a high spatial resolution (typically a few tens of metres). The model also takes into account the detailed technical data of each individual vessel. The previously developed model was applicable for evaluating the emissions of NOx, SOx and CO2. This paper addresses a substantial extension of the modelling system, to allow also for the mass-based emissions of particulate matter (PM) and carbon monoxide (CO). The presented Ship Traffic Emissions Assessment Model (STEAM2) allows for the influences of accurate travel routes and ship speed, engine load, fuel sulphur content, multiengine setups, abatement methods and waves. We address in particular the modeling of the influence on the emissions of both engine load and the sulphur content of the fuel. The presented methodology can be used to evaluate the total PM emissions, and those of organic carbon, elemental carbon, ash and hydrated sulphate. We have evaluated the performance of the extended model against available experimental data on engine power, fuel consumption and the composition-resolved emissions of PM. We have also compared the annually averaged emission values with those of the corresponding EMEP inventory, As example results, the geographical distributions of the emissions of PM and CO are presented for the marine regions of the Baltic Sea surrounding the Danish Straits.
Updating the conceptual model for fine particle mass emissions from combustion systems.
Robinson, Allen L; Grieshop, Andrew P; Donahue, Neil M; Hunt, Sherri W
2010-10-01
Atmospheric transformations determine the contribution of emissions from combustion systems to fine particulate matter (PM) mass. For example, combustion systems emit vapors that condense onto existing particles or form new particles as the emissions are cooled and diluted. Upon entering the atmosphere, emissions are exposed to atmospheric oxidants and sunlight, which causes them to evolve chemically and physically, generating secondary PM. This review discusses these transformations, focusing on organic PM. Organic PM emissions are semi-volatile at atmospheric conditions and thus their partitioning varies continuously with changing temperature and concentration. Because organics contribute a large portion of the PM mass emitted by most combustion sources, these emissions cannot be represented using a traditional, static emission factor. Instead, knowledge of the volatility distribution of emissions is required to explicitly account for changes in gas-particle partitioning. This requires updating how PM emissions from combustion systems are measured and simulated from combustion systems. Secondary PM production often greatly exceeds the direct or primary PM emissions; therefore, secondary PM must be included in any assessment of the contribution of combustion systems to ambient PM concentrations. Low-volatility organic vapors emitted by combustion systems appear to be very important secondary PM precursors that are poorly accounted for in inventories and models. The review concludes by discussing the implications that the dynamic nature of these PM emissions have on source testing for emission inventory development and regulatory purposes. This discussion highlights important linkages between primary and secondary PM, which could lead to simplified certification test procedures while capturing the emission components that contribute most to atmospheric PM mass.
Robinson, Allen L; Grieshop, Andrew P; Donahue, Neil M; Hunt, Sherri W
2010-10-01
Atmospheric transformations determine the contribution of emissions from combustion systems to fine particulate matter (PM) mass. For example, combustion systems emit vapors that condense onto existing particles or form new particles as the emissions are cooled and diluted. Upon entering the atmosphere, emissions are exposed to atmospheric oxidants and sunlight, which causes them to evolve chemically and physically, generating secondary PM. This review discusses these transformations, focusing on organic PM. Organic PM emissions are semi -volatile at atmospheric conditions and thus their partitioning varies continuously with changing temperature and concentration. Because organics contribute a large portion of the PM mass emitted by most combustion sources, these emissions cannot be represented using a traditional, static emission factor. Instead, knowledge of the volatility distribution of emissions is required to explicitly account for changes in gas-particle partitioning. This requires updating how PM emissions from combustion systems are measured and simulated from combustion systems. Secondary PM production often greatly exceeds the direct or primary PM emissions; therefore, secondary PM must be included in any assessment of the contribution of combustion systems to ambient PM concentrations. Low-volatility organic vapors emitted by combustion systems appear to be very important secondary PM precursors that are poorly accounted for in inventories and models. The review concludes by discussing the implications that the dynamic nature of these PM emissions have on source testing for emission inventory development and regulatory purposes. This discussion highlights important linkages between primary and secondary PM, which could lead to simplified certification test procedures while capturing the emission components that contribute most to atmospheric PM mass.
Wu, Jian-Bin; Wang, Zifa; Wang, Qian; Li, Jie; Xu, Jianming; Chen, HuanSheng; Ge, Baozhu; Zhou, Guangqiang; Chang, Luyu
2017-02-01
An on-line source-tagged model coupled with an air quality model (Nested Air Quality Prediction Model System, NAQPMS) was applied to estimate source contributions of primary and secondary sulfate, nitrate and ammonium (SNA) during a representative winter period in Shanghai. This source-tagged model system could simultaneously track spatial and temporal sources of SNA, which were apportioned to their respective primary precursors in a simulation run. The results indicate that in the study period, local emissions in Shanghai accounted for over 20% of SNA contributions and that Jiangsu and Shandong were the two major non-local sources. In particular, non-local emissions had higher contributions during recorded pollution periods. This suggests that the transportation of pollutants plays a key role in air pollution in Shanghai. The temporal contributions show that the emissions from the "current day" (emission contribution from the current day during which the model was simulating) contributed 60%-70% of the sulfate and ammonium concentrations but only 10%-20% of the nitrate concentration, while the previous days' contributions increased during the recorded pollution periods. Emissions that were released within three days contributed over 85% averagely for SNA in January 2013. To evaluate the source-tagged model system, the results were compared by sensitivity analysis (emission perturbation of -30%) and backward trajectory analysis. The consistency of the comparison results indicated that the source-tagged model system can track sources of SNA with reasonable accuracy. Copyright © 2016 Elsevier Ltd. All rights reserved.
Analysis and Design of International Emission Trading Markets Applying System Dynamics Techniques
NASA Astrophysics Data System (ADS)
Hu, Bo; Pickl, Stefan
2010-11-01
The design and analysis of international emission trading markets is an important actual challenge. Time-discrete models are needed to understand and optimize these procedures. We give an introduction into this scientific area and present actual modeling approaches. Furthermore, we develop a model which is embedded in a holistic problem solution. Measures for energy efficiency are characterized. The economic time-discrete "cap-and-trade" mechanism is influenced by various underlying anticipatory effects. With a systematic dynamic approach the effects can be examined. First numerical results show that fair international emissions trading can only be conducted with the use of protective export duties. Furthermore a comparatively high price which evokes emission reduction inevitably has an inhibiting effect on economic growth according to our model. As it always has been expected it is not without difficulty to find a balance between economic growth and emission reduction. It can be anticipated using our System Dynamics model simulation that substantial changes must be taken place before international emissions trading markets can contribute to global GHG emissions mitigation.
NASA Astrophysics Data System (ADS)
Farhadi, L.; Bateni, S. M.; Auligne, T.; Navari, M.
2017-12-01
Snow emissivity is a key parameter for the estimation of snow surface temperature, which is needed as an initial value in climate models and determination of the outgoing long-wave radiation. Moreover, snow emissivity is required for retrieval of atmospheric parameters (e.g., temperature and humidity profiles) from satellite measurements and satellite data assimilations in numerical weather prediction systems. Microwave emission models and remote sensing data cannot accurately estimate snow emissivity due to limitations attributed to each of them. Existing microwave emission models introduce significant uncertainties in their snow emissivity estimates. This is mainly due to shortcomings of the dense media theory for snow medium at high frequencies, and erroneous forcing variables. The well-known limitations of passive microwave data such as coarse spatial resolution, saturation in deep snowpack, and signal loss in wet snow are the major drawbacks of passive microwave retrieval algorithms for estimation of snow emissivity. A full exploitation of the information contained in the remote sensing data can be achieved by merging them with snow emission models within a data assimilation framework. Such an optimal merging can overcome the specific limitations of models and remote sensing data. An Ensemble Batch Smoother (EnBS) data assimilation framework was developed in this study to combine the synthetically generated passive microwave brightness temperatures at 1.4-, 18.7-, 36.5-, and 89-GHz frequencies with the MEMLS microwave emission model to reduce the uncertainty of the snow emissivity estimates. We have used the EnBS algorithm in the context of observing system simulation experiment (or synthetic experiment) at the local scale observation site (LSOS) of the NASA CLPX field campaign. Our findings showed that the developed methodology significantly improves the estimates of the snow emissivity. The simultaneous assimilation of passive microwave brightness temperatures at all frequencies (i.e., 1.4-, 18.7-, 36.5-, and 89-GHz) reduce the root-mean-square-error (RMSE) of snow emissivity at 1.4-, 18.7-, 36.5-, and 89-GHz (H-pol.) by 80%, 42%, 52%, 40%, respectively compared to the corresponding snow emissivity estimates from the open-loop model.
Carbon footprint and ammonia emissions of California beef production systems
USDA-ARS?s Scientific Manuscript database
Beef production is a recognized source of greenhouse gas (GHG) and ammonia (NH3) emissions; however, little information exists on the net emissions from beef production systems. A partial life cycle assessment (LCA) was conducted using the Integrated Farm System Model (IFSM) to estimate GHG and NH3 ...
40 CFR 60.1720 - What continuous emission monitoring systems must I install for gaseous pollutants?
Code of Federal Regulations, 2014 CFR
2014-07-01
... systems must I install for gaseous pollutants? 60.1720 Section 60.1720 Protection of Environment... or Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1720 What continuous..., maintain, and operate continuous emission monitoring systems for oxygen (or carbon dioxide), sulfur dioxide...
40 CFR 60.1720 - What continuous emission monitoring systems must I install for gaseous pollutants?
Code of Federal Regulations, 2012 CFR
2012-07-01
... systems must I install for gaseous pollutants? 60.1720 Section 60.1720 Protection of Environment... or Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1720 What continuous..., maintain, and operate continuous emission monitoring systems for oxygen (or carbon dioxide), sulfur dioxide...
40 CFR 60.1720 - What continuous emission monitoring systems must I install for gaseous pollutants?
Code of Federal Regulations, 2013 CFR
2013-07-01
... systems must I install for gaseous pollutants? 60.1720 Section 60.1720 Protection of Environment... or Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1720 What continuous..., maintain, and operate continuous emission monitoring systems for oxygen (or carbon dioxide), sulfur dioxide...
NASA Astrophysics Data System (ADS)
Pavlovic, Radenko; Chen, Jack; Beaulieu, Paul-Andre; Anselmp, David; Gravel, Sylvie; Moran, Mike; Menard, Sylvain; Davignon, Didier
2014-05-01
A wildfire emissions processing system has been developed to incorporate near-real-time emissions from wildfires and large prescribed burns into Environment Canada's real-time GEM-MACH air quality (AQ) forecast system. Since the GEM-MACH forecast domain covers Canada and most of the U.S.A., including Alaska, fire location information is needed for both of these large countries. During AQ model runs, emissions from individual fire sources are injected into elevated model layers based on plume-rise calculations and then transport and chemistry calculations are performed. This "on the fly" approach to the insertion of the fire emissions provides flexibility and efficiency since on-line meteorology is used and computational overhead in emissions pre-processing is reduced. GEM-MACH-FireWork, an experimental wildfire version of GEM-MACH, was run in real-time mode for the summers of 2012 and 2013 in parallel with the normal operational version. 48-hour forecasts were generated every 12 hours (at 00 and 12 UTC). Noticeable improvements in the AQ forecasts for PM2.5 were seen in numerous regions where fire activity was high. Case studies evaluating model performance for specific regions and computed objective scores will be included in this presentation. Using the lessons learned from the last two summers, Environment Canada will continue to work towards the goal of incorporating near-real-time intermittent wildfire emissions into the operational air quality forecast system.
An original traffic additional emission model and numerical simulation on a signalized road
NASA Astrophysics Data System (ADS)
Zhu, Wen-Xing; Zhang, Jing-Yu
2017-02-01
Based on VSP (Vehicle Specific Power) model traffic real emissions were theoretically classified into two parts: basic emission and additional emission. An original additional emission model was presented to calculate the vehicle's emission due to the signal control effects. Car-following model was developed and used to describe the traffic behavior including cruising, accelerating, decelerating and idling at a signalized intersection. Simulations were conducted under two situations: single intersection and two adjacent intersections with their respective control policy. Results are in good agreement with the theoretical analysis. It is also proved that additional emission model may be used to design the signal control policy in our modern traffic system to solve the serious environmental problems.
Tabatabaie, Seyed Mohammad Hossein; Bolte, John P; Murthy, Ganti S
2018-06-01
The goal of this study was to integrate a crop model, DNDC (DeNitrification-DeComposition), with life cycle assessment (LCA) and economic analysis models using a GIS-based integrated platform, ENVISION. The integrated model enables LCA practitioners to conduct integrated economic analysis and LCA on a regional scale while capturing the variability of soil emissions due to variation in regional factors during production of crops and biofuel feedstocks. In order to evaluate the integrated model, the corn-soybean cropping system in Eagle Creek Watershed, Indiana was studied and the integrated model was used to first model the soil emissions and then conduct the LCA as well as economic analysis. The results showed that the variation in soil emissions due to variation in weather is high causing some locations to be carbon sink in some years and source of CO 2 in other years. In order to test the model under different scenarios, two tillage scenarios were defined: 1) conventional tillage (CT) and 2) no tillage (NT) and analyzed with the model. The overall GHG emissions for the corn-soybean cropping system was simulated and results showed that the NT scenario resulted in lower soil GHG emissions compared to CT scenario. Moreover, global warming potential (GWP) of corn ethanol from well to pump varied between 57 and 92gCO 2 -eq./MJ while GWP under the NT system was lower than that of the CT system. The cost break-even point was calculated as $3612.5/ha in a two year corn-soybean cropping system and the results showed that under low and medium prices for corn and soybean most of the farms did not meet the break-even point. Copyright © 2017 Elsevier B.V. All rights reserved.
Code of Federal Regulations, 2012 CFR
2012-07-01
... appendix F requirements to evaluate continuous emission monitoring systems? 60.1735 Section 60.1735... Combustion Units Constructed on or Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1735... to also evaluate your oxygen (or carbon dioxide) continuous emission monitoring system. Therefore...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hampden Kuhns; Eladio M. Knipping; Jeffrey M. Vukovich,
2005-05-01
The Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study investigated the sources of haze at Big Bend National Park in southwest Texas. The modeling domain includes most of the continental United States and Mexico. The BRAVO emissions inventory was constructed from the 1999 National Emission Inventory for the United States, modified to include finer-resolution data for Texas and 13 U.S. states in close proximity. The inventory includes emissions for CO, nitrogen oxides, sulfur dioxide, volatile organic compounds (VOCs), ammonia, particulate matter (PM) {lt}10 {mu}m in aerodynamic diameter, and PM {lt}2.5 {mu}m in aerodynamic diameter. The SMOKE modeling system wasmore » used to generate gridded emissions fields for use with the Regional Modeling System for Aerosols and Deposition (REMSAD) and the Community Multiscale Air Quality model modified with the Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (CMAQ-MADRID). The compilation of the inventory, supporting model input data, and issues encountered during the development of the inventory are documented. A comparison of the BRAVO emissions inventory for Mexico with other emerging Mexican emission inventories illustrates their uncertainty. 65 refs., 4 figs., 9 tabs.« less
"Updates to Model Algorithms & Inputs for the Biogenic Emissions Inventory System (BEIS) Model"
We have developed new canopy emission algorithms and land use data for BEIS. Simulations with BEIS v3.4 and these updates in CMAQ v5.0.2 are compared these changes to the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and evaluated the simulations against observatio...
Cecchel, S; Chindamo, D; Turrini, E; Carnevale, C; Cornacchia, G; Gadola, M; Panvini, A; Volta, M; Ferrario, D; Golimbioschi, R
2018-02-01
This study presents a modelling system to evaluate the impact of weight reduction in light commercial vehicles with diesel engines on air quality and greenhouse gas emissions. The PROPS model assesses the emissions of one vehicle in the aforementioned category and its corresponding reduced-weight version. The results serve as an input to the RIAT+ tool, an air quality integrated assessment modelling system. This paper applies the tools in a case study in the Lombardy region (Italy) and discusses the input data pre-processing, the PROPS-RIAT+ modelling system runs, and the results. Copyright © 2017 Elsevier B.V. All rights reserved.
Meier, Matthias S; Stoessel, Franziska; Jungbluth, Niels; Juraske, Ronnie; Schader, Christian; Stolze, Matthias
2015-02-01
Comprehensive assessment tools are needed that reliably describe environmental impacts of different agricultural systems in order to develop sustainable high yielding agricultural production systems with minimal impacts on the environment. Today, Life Cycle Assessment (LCA) is increasingly used to assess and compare the environmental sustainability of agricultural products from conventional and organic agriculture. However, LCA studies comparing agricultural products from conventional and organic farming systems report a wide variation in the resource efficiency of products from these systems. The studies show that impacts per area farmed land are usually less in organic systems, but related to the quantity produced impacts are often higher. We reviewed 34 comparative LCA studies of organic and conventional agricultural products to analyze whether this result is solely due to the usually lower yields in organic systems or also due to inaccurate modeling within LCA. Comparative LCAs on agricultural products from organic and conventional farming systems often do not adequately differentiate the specific characteristics of the respective farming system in the goal and scope definition and in the inventory analysis. Further, often only a limited number of impact categories are assessed within the impact assessment not allowing for a comprehensive environmental assessment. The most critical points we identified relate to the nitrogen (N) fluxes influencing acidification, eutrophication, and global warming potential, and biodiversity. Usually, N-emissions in LCA inventories of agricultural products are based on model calculations. Modeled N-emissions often do not correspond with the actual amount of N left in the system that may result in potential emissions. Reasons for this may be that N-models are not well adapted to the mode of action of organic fertilizers and that N-emission models often are built on assumptions from conventional agriculture leading to even greater deviances for organic systems between the amount of N calculated by emission models and the actual amount of N available for emissions. Improvements are needed regarding a more precise differentiation between farming systems and regarding the development of N emission models that better represent actual N-fluxes within different systems. We recommend adjusting N- and C-emissions during farmyard manure management and farmyard manure fertilization in plant production to the feed ration provided in the animal production of the respective farming system leading to different N- and C-compositions within the excrement. In the future, more representative background data on organic farming systems (e.g. N content of farmyard manure) should be generated and compiled so as to be available for use within LCA inventories. Finally, we recommend conducting consequential LCA - if possible - when using LCA for policy-making or strategic environmental planning to account for different functions of the analyzed farming systems. Copyright © 2014 Elsevier Ltd. All rights reserved.
Directional Canopy Emissivity Estimation Based on Spectral Invariants
NASA Astrophysics Data System (ADS)
Guo, M.; Cao, B.; Ren, H.; Yongming, D.; Peng, J.; Fan, W.
2017-12-01
Land surface emissivity is a crucial parameter for estimating land surface temperature from remote sensing data and also plays an important role in the physical process of surface energy and water balance from local to global scales. To our knowledge, the emissivity varies with surface type and cover. As for the vegetation, its canopy emissivity is dependent on vegetation types, viewing zenith angle and structure that changes in different growing stages. Lots of previous studies have focused on the emissivity model, but few of them are analytic and suited to different canopy structures. In this paper, a new physical analytic model is proposed to estimate the directional emissivity of homogenous vegetation canopy based on spectral invariants. The initial model counts the directional absorption in six parts: the direct absorption of the canopy and the soil, the absorption of the canopy and soil after a single scattering and after multiple scattering within the canopy-soil system. In order to analytically estimate the emissivity, the pathways of photons absorbed in the canopy-soil system are traced using the re-collision probability in Fig.1. After sensitive analysis on the above six absorptions, the initial complicated model was further simplified as a fixed mathematic expression to estimate the directional emissivity for vegetation canopy. The model was compared with the 4SAIL model, FRA97 model, FRA02 model and DART model in Fig.2, and the results showed that the FRA02 model is significantly underestimated while the FRA97 model is a little underestimated, on basis of the new model. On the contrary, the emissivity difference between the new model with the 4SAIL model and DART model was found to be less than 0.002. In general, since the new model has the advantages of mathematic expression with accurate results and clear physical meaning, the model is promising to be extended to simulate the directional emissivity for the discrete canopy in further study.
Path Dependence of Regional Climate Change
NASA Astrophysics Data System (ADS)
Herrington, Tyler; Zickfeld, Kirsten
2013-04-01
Path dependence of the climate response to CO2 forcing has been investigated from a global mean perspective, with evidence suggesting that long-term global mean temperature and precipitation changes are proportional to cumulative CO2 emissions, and independent of emissions pathway. Little research, however, has been done on path dependence of regional climate changes, particularly in areas that could be affected by tipping points. Here, we utilize the UVic Earth System Climate Model version 2.9, an Earth System Model of Intermediate Complexity. It consists of a 3-dimensional ocean general circulation model, coupled with a dynamic-thermodynamic sea ice model, and a thermodynamic energy-moisture balance model of the atmosphere. This is then coupled with a terrestrial carbon cycle model and an ocean carbon-cycle model containing an inorganic carbon and marine ecosystem component. Model coverage is global with a zonal resolution of 3.6 degrees and meridional resolution of 1.8 degrees. The model is forced with idealized emissions scenarios across five cumulative emission groups (1300 GtC, 2300 GtC, 3300 GtC, 4300 GtC, and 5300 GtC) to explore the path dependence of (and the possibility of hysteresis in) regional climate changes. Emission curves include both fossil carbon emissions and emissions from land use changes, and span a variety of peak and decline scenarios with varying emission rates, as well as overshoot and instantaneous pulse scenarios. Tipping points being explored include those responsible for the disappearance of summer Arctic sea-ice, the irreversible melt of the Greenland Ice Sheet, the collapse of the Atlantic Thermohaline Circulation, and the dieback of the Amazonian Rainforest. Preliminary results suggest that global mean climate change after cessation of CO2 emissions is independent of the emissions pathway, only varying with total cumulative emissions, in accordance with results from earlier studies. Forthcoming analysis will investigate path dependence of regional climate change. Some evidence exists to support the idea of hysteresis in the Greenland Ice Sheet, and since tipping points represent non-linear elements of the climate system, we suspect that the other tipping points might also show path dependence.
40 CFR 60.1725 - How are the data from the continuous emission monitoring systems used?
Code of Federal Regulations, 2013 CFR
2013-07-01
... emission monitoring systems used? 60.1725 Section 60.1725 Protection of Environment ENVIRONMENTAL... Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1725 How are the data from the... systems for sulfur dioxide, nitrogen oxides, and carbon monoxide to demonstrate continuous compliance with...
40 CFR 60.1725 - How are the data from the continuous emission monitoring systems used?
Code of Federal Regulations, 2014 CFR
2014-07-01
... emission monitoring systems used? 60.1725 Section 60.1725 Protection of Environment ENVIRONMENTAL... Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1725 How are the data from the... systems for sulfur dioxide, nitrogen oxides, and carbon monoxide to demonstrate continuous compliance with...
40 CFR 60.1725 - How are the data from the continuous emission monitoring systems used?
Code of Federal Regulations, 2012 CFR
2012-07-01
... emission monitoring systems used? 60.1725 Section 60.1725 Protection of Environment ENVIRONMENTAL... Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1725 How are the data from the... systems for sulfur dioxide, nitrogen oxides, and carbon monoxide to demonstrate continuous compliance with...
NASA Astrophysics Data System (ADS)
Kato, E.; Kawamiya, M.
2010-12-01
For CMIP5 experiments, emissions scenarios data sets for climate models are prepared as Representative Concentration Pathways (RCPs) by the Integrated Assessment Models (IAMs). IAMs also have depicted regional land-use scenarios based on the socioeconomic assumption of the future scenarios of RCPs. In the land-use harmonization project, gridded land-use transition data has been constructed from the regional IAMs future land-use scenarios which smoothly connects historical reconstructions of land-use based on HYDE 3 data and FAO wood harvest data. In this study, using the gridded transition land-use scenario data, global net CO2 emission from land-use change for each RCPs scenarios is evaluated with a offline version of terrestrial biogeochemical model, VISIT (Vegetation Integrative SImulation Tool), utilizing a protocol to estimate carbon emission from deforested biomass considering delayed decomposition of product pools, and regrowth absorption from the secondary lands with abandoned agricultural lands. From the model output, effect of CO2 fertilization and land-use scenario itself on the emission is assessed to see the consistency of the scenarios. In addition, to see the effect of climate change and the climate-carbon feedback on terrestrial ecosystems, net land-use change CO2 emission is also evaluated with an earth system model, MIROC-ESM incorporating a DGVM with land-use change component. In the simulations with earth system model, RCP 6.0 scenario has been evaluated by model runs with and without land-use change forcing.
McFarland, James; Zhou, Yuyu; Clarke, Leon; ...
2015-06-10
The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Fewer studies have explored the physical impacts of climate change on the power sector. Our present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effectsmore » of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. Moreover, the increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.« less
Isoprene emission response to drought and the impact on global atmospheric chemistry
NASA Astrophysics Data System (ADS)
Jiang, Xiaoyan; Guenther, Alex; Potosnak, Mark; Geron, Chris; Seco, Roger; Karl, Thomas; Kim, Saewung; Gu, Lianhong; Pallardy, Stephen
2018-06-01
Biogenic isoprene emissions play a very important role in atmospheric chemistry. These emissions are strongly dependent on various environmental conditions, such as temperature, solar radiation, plant water stress, ambient ozone and CO2 concentrations, and soil moisture. Current biogenic emission models (i.e., Model of Emissions of Gases and Aerosols from Nature, MEGAN) can simulate emission responses to some of the major driving variables, such as short-term variations in temperature and solar radiation, but the other factors are either missing or poorly represented. In this paper, we propose a new modelling approach that considers the physiological effects of drought stress on plant photosynthesis and isoprene emissions for use in the MEGAN3 biogenic emission model. We test the MEGAN3 approach by integrating the algorithm into the existing MEGAN2.1 biogenic emission model framework embedded into the global Community Land Model of the Community Earth System Model (CLM4.5/CESM1.2). Single-point simulations are compared against available field measurements at the Missouri Ozarks AmeriFlux (MOFLUX) field site. The modelling results show that the MEGAN3 approach of using of a photosynthesis parameter (Vcmax) and soil wetness factor (βt) to determine the drought activity factor leads to better simulated isoprene emissions in non-drought and drought periods. The global simulation with the MEGAN3 approach predicts a 17% reduction in global annual isoprene emissions, in comparison to the value predicted using the default CLM4.5/MEGAN2.1 without any drought effect. This reduction leads to changes in surface ozone and oxidants in the areas where the reduction of isoprene emissions is observed. Based on the results presented in this study, we conclude that it is important to simulate the drought-induced response of biogenic isoprene emission accurately in the coupled Earth System model.
Ammonia emission model for whole farm evaluation of dairy production systems.
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.
Emissions from ships in the northwestern United States.
Corbett, James J
2002-03-15
Recent inventory efforts have focused on developing nonroad inventories for emissions modeling and policy insights. Characterizing these inventories geographically and explicitly treating the uncertaintiesthat result from limited emissions testing, incomplete activity and usage data, and other important input parameters currently pose the largest methodological challenges. This paper presents a commercial marine vessel (CMV) emissions inventory for Washington and Oregon using detailed statistics regarding fuel consumption, vessel movements, and cargo volumes for the Columbia and Snake River systems. The inventory estimates emissions for oxides of nitrogen (NOx), particulate matter (PM), and oxides of sulfur (SOx). This analysis estimates that annual NOx emissions from marine transportation in the Columbia and Snake River systems in Washington and Oregon equal 6900 t of NOx (as NO2) per year, 2.6 times greater than previous NO, inventories for this region. Statewide CMV NO, emissions are estimated to be 9,800 t of NOx per year. By relying on a "bottom-up" fuel consumption model that includes vessel characteristics and transit information, the river system inventory may be more accurate than previous estimates. This inventory provides modelers with bounded parametric inputs for sensitivity analysis in pollution modeling. The ability to parametrically model the uncertainty in commercial marine vessel inventories also will help policy-makers determine whether better policy decisions can be enabled through further vessel testing and improved inventory resolution.
Hydroxylamine diffusion can enhance N₂O emissions in nitrifying biofilms: a modeling study.
Sabba, Fabrizio; Picioreanu, Cristian; Pérez, Julio; Nerenberg, Robert
2015-02-03
Wastewater treatment plants can be significant sources of nitrous oxide (N2O), a potent greenhouse gas. However, little is known about N2O emissions from biofilm processes. We adapted an existing suspended-growth mathematical model to explore N2O emissions from nitrifying biofilms. The model included N2O formation by ammonia-oxidizing bacteria (AOB) via the hydroxylamine and the nitrifier denitrification pathways. Our model suggested that N2O emissions from nitrifying biofilms could be significantly greater than from suspended growth systems under similar conditions. The main cause was the formation and diffusion of hydroxylamine, an AOB nitrification intermediate, from the aerobic to the anoxic regions of the biofilm. In the anoxic regions, hydroxylamine oxidation by AOB provided reducing equivalents used solely for nitrite reduction to N2O, since there was no competition with oxygen. For a continuous system, very high and very low dissolved oxygen (DO) concentrations resulted in lower emissions, while intermediate values led to higher emissions. Higher bulk ammonia concentrations and greater biofilm thicknesses increased emissions. The model effectively predicted N2O emissions from an actual pilot-scale granular sludge reactor for sidestream nitritation, but significantly underestimated the emissions when the NH2OH diffusion coefficient was assumed to be minimal. This numerical study suggests an unexpected and important role of hydroxylamine in N2O emission in biofilms.
NASA Astrophysics Data System (ADS)
Aksenova, Olesya; Nikolaeva, Evgenia; Cehlár, Michal
2017-11-01
This work aims to investigate the effectiveness of mathematical and three-dimensional computer modeling tools in the planning of processes of fuel and energy complexes at the planning and design phase of a thermal power plant (TPP). A solution for purification of gas emissions at the design development phase of waste treatment systems is proposed employing mathematical and three-dimensional computer modeling - using the E-nets apparatus and the development of a 3D model of the future gas emission purification system. Which allows to visualize the designed result, to select and scientifically prove economically feasible technology, as well as to ensure the high environmental and social effect of the developed waste treatment system. The authors present results of a treatment of planned technological processes and the system for purifying gas emissions in terms of E-nets. using mathematical modeling in the Simulink application. What allowed to create a model of a device from the library of standard blocks and to perform calculations. A three-dimensional model of a system for purifying gas emissions has been constructed. It allows to visualize technological processes and compare them with the theoretical calculations at the design phase of a TPP and. if necessary, make adjustments.
Holistic energy system modeling combining multi-objective optimization and life cycle assessment
NASA Astrophysics Data System (ADS)
Rauner, Sebastian; Budzinski, Maik
2017-12-01
Making the global energy system more sustainable has emerged as a major societal concern and policy objective. This transition comes with various challenges and opportunities for a sustainable evolution affecting most of the UN’s Sustainable Development Goals. We therefore propose broadening the current metrics for sustainability in the energy system modeling field by using industrial ecology techniques to account for a conclusive set of indicators. This is pursued by including a life cycle based sustainability assessment into an energy system model considering all relevant products and processes of the global supply chain. We identify three pronounced features: (i) the low-hanging fruit of impact mitigation requiring manageable economic effort; (ii) embodied emissions of renewables cause increasing spatial redistribution of impact from direct emissions, the place of burning fuel, to indirect emissions, the location of the energy infrastructure production; (iii) certain impact categories, in which more overall sustainable systems perform worse than the cost minimal system, require a closer look. In essence, this study makes the case for future energy system modeling to include the increasingly important global supply chain and broaden the metrics of sustainability further than cost and climate change relevant emissions.
Modeling emissions for three-dimensional atmospheric chemistry transport models.
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 methods to distribute the emissions in time and space need to be replaced by sophisticated emission models in order to improve the CTM results. New methods, e.g. for ammonia emissions, provide grid cell dependent temporal profiles. In the future, large data fields from traffic observations or satellite observations could be used for more detailed emission data.
On the potential of GHG emissions estimation by multi-species inverse modeling
NASA Astrophysics Data System (ADS)
Gerbig, Christoph; Boschetti, Fabio; Filges, Annette; Marshall, Julia; Koch, Frank-Thomas; Janssens-Maenhout, Greet; Nedelec, Philippe; Thouret, Valerie; Karstens, Ute
2016-04-01
Reducing anthropogenic emissions of greenhouse gases is one of the most important elements in mitigating climate change. However, as emission reporting is often incomplete or incorrect, there is a need to independently monitor the emissions. Despite this, in the case of CO2 one typically assumes that emissions from fossil fuel burning are well known, and only natural fluxes are constrained by atmospheric measurements via inverse modelling. On the other hand, species such as CO2, CH4, and CO often have common emission patterns, and thus share part of the uncertainties, both related to the prior knowledge of emissions, and to model-data mismatch error. We implemented the Lagrangian transport model STILT driven by ECMWF analysis and short-term forecast meteorological fields together with emission sector and fuel-type specific emissions of CO2, CH4 and CO from EDGARv4.3 at a spatial resolution of 0.1 x 0.1 deg., providing an atmospheric fingerprint of anthropogenic emissions for multiple trace gases. We combine the regional STILT simulations with lateral boundary conditions for CO2 and CO from MACC forecasts and CH4 from TM3 simulations. Here we apply this framework to airborne in-situ measurements made in the context of IAGOS (In-service Aircraft for a Global Observing System) and in the context of a HALO mission conducted for testing the active remote sensing system CHARM-F during April/May 2015 over central Europe. Simulated tracer distributions are compared to observed profiles of CO2, CH4, and CO, and the potential for a multi-species inversion using synergies between different tracers is assessed with respect to the uncertainty reduction in retrieved emission fluxes. Implications for inversions solving for anthropogenic emissions using atmospheric observations from ICOS (Integrated Carbon Observing System) are discussed.
Lu, Hongwei; Sun, Shichao; Ren, Lixia; He, Li
2015-03-02
This study advances an integrated MSW management model under inexact input information for the city of Beijing, China. The model is capable of simultaneously generating MSW management policies, performing GHG emission control, and addressing system uncertainty. Results suggest that: (1) a management strategy with minimal system cost can be obtained even when suspension of certain facilities becomes unavoidable through specific increments of the remaining ones; (2) expansion of facilities depends only on actual needs, rather than enabling the full usage of existing facilities, although it may prove to be a costly proposition; (3) adjustment of waste-stream diversion ratio directly leads to a change in GHG emissions from different disposal facilities. Results are also obtained from the comparison of the model with a conventional one without GHG emissions consideration. It is indicated that (1) the model would reduce the net system cost by [45, 61]% (i.e., [3173, 3520] million dollars) and mitigate GHG emissions by [141, 179]% (i.e., [76, 81] million tons); (2) increased waste would be diverted to integrated waste management facilities to prevent overmuch CH4 emission from the landfills. Copyright © 2014 Elsevier B.V. All rights reserved.
Integration of biogenic emissions in environmental fate, transport, and exposure systems
NASA Astrophysics Data System (ADS)
Efstathiou, Christos I.
Biogenic emissions make a significant contribution to the levels of aeroallergens and secondary air pollutants such as ozone. Understanding major factors contributing to allergic airway diseases requires accurate characterization of emissions and transport/transformation of biogenic emissions. However, biogenic emission estimates are laden with large uncertainties. Furthermore, the current biogenic emission estimation models use low-resolution data for estimating land use, vegetation biomass and VOC emissions. Furthermore, there are currently no established methods for estimating bioaerosol emissions over continental or regional scale, which can impact the ambient levels of pollent that have synergestic effects with other gaseous pollutants. In the first part of the thesis, an detailed review of different approaches and available databases for estimating biogenic emissions was conducted, and multiple geodatabases and satellite imagery were used in a consistent manner to improve the estimates of biogenic emissions over the continental United States. These emissions represent more realistic, higher resolution estimates of biogenic emissions (including those of highly reactive species such as isoprene). The impact of these emissions on tropospheric ozone levels was studied at a regional scale through the application of the USEPA's Community Multiscale Air Quality (CMAQ) model. Minor, but significant differences in the levels of ambient ozone were observed. In the second part of the thesis, an algorithm for estimating emissions of pollen particles from major allergenic tree and plant families in the United States was developed, extending the approach for modeling biogenic gas emissions in the Biogenic Emission Inventory System (BEIS). A spatio-temporal vegetation map was constructed from different remote sensing sources and local surveys, and was coupled with a meteorological model to develop pollen emissions rates. This model overcomes limitations posed by the lack of temporally resolved dynamic vegetation mapping in traditional pollen emission estimation methods. The pollen emissions model was applied to study the pollen emissions for North East US at 12 km resolution for comparison with ground level tree pollen data. A pollen transport model that simulates complex dispersion and deposition was developed through modifications to the USEPA's Community Multiscale Air Quality (CMAQ) model. The peak pollen emission predictions were within a day of peak pollen counts measured, thus corroborating independent model verification. Furthermore, the peak predicted pollen concentration estimates were within two days of the peak measured pollen counts, thus providing independent corroboration. The models for emissions and dispersion allow data-independent estimation of pollen levels, and provide an important component in assessing exposures of populations to pollen, especially under different climate change scenarios.
Ashrafi, Omid; Yerushalmi, Laleh; Haghighat, Fariborz
2013-03-01
Greenhouse gas (GHG) emission in wastewater treatment plants of the pulp-and-paper industry was estimated by using a dynamic mathematical model. Significant variations were shown in the magnitude of GHG generation in response to variations in operating parameters, demonstrating the limited capacity of steady-state models in predicting the time-dependent emissions of these harmful gases. The examined treatment systems used aerobic, anaerobic, and hybrid-anaerobic/aerobic-biological processes along with chemical coagulation/flocculation, anaerobic digester, nitrification and denitrification processes, and biogas recovery. The pertinent operating parameters included the influent substrate concentration, influent flow rate, and temperature. Although the average predictions by the dynamic model were only 10 % different from those of steady-state model during 140 days of operation of the examined systems, the daily variations of GHG emissions were different up to ± 30, ± 19, and ± 17 % in the aerobic, anaerobic, and hybrid systems, respectively. The variations of process variables caused fluctuations in energy generation from biogas recovery by ± 6, ± 7, and ± 4 % in the three examined systems, respectively. The lowest variations were observed in the hybrid system, showing the stability of this particular process design.
Wild Fire Emissions for the NOAA Operational HYSPLIT Smoke Model
NASA Astrophysics Data System (ADS)
Huang, H. C.; ONeill, S. M.; Ruminski, M.; Shafran, P.; McQueen, J.; DiMego, G.; Kondragunta, S.; Gorline, J.; Huang, J. P.; Stunder, B.; Stein, A. F.; Stajner, I.; Upadhayay, S.; Larkin, N. K.
2015-12-01
Particulate Matter (PM) generated from forest fires often lead to degraded visibility and unhealthy air quality in nearby and downstream areas. To provide near-real time PM information to the state and local agencies, the NOAA/National Weather Service (NWS) operational HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory Model) smoke modeling system (NWS/HYSPLIT smoke) provides the forecast of smoke concentration resulting from fire emissions driven by the NWS North American Model 12 km weather predictions. The NWS/HYSPLIT smoke incorporates the U.S. Forest Service BlueSky Smoke Modeling Framework (BlueSky) to provide smoke fire emissions along with the input fire locations from the NOAA National Environmental Satellite, Data, and Information Service (NESDIS)'s Hazard Mapping System fire and smoke detection system. Experienced analysts inspect satellite imagery from multiple sensors onboard geostationary and orbital satellites to identify the location, size and duration of smoke emissions for the model. NWS/HYSPLIT smoke is being updated to use a newer version of USFS BlueSky. The updated BlueSky incorporates the Fuel Characteristic Classification System version 2 (FCCS2) over the continental U.S. and Alaska. FCCS2 includes a more detailed description of fuel loadings with additional plant type categories. The updated BlueSky also utilizes an improved fuel consumption model and fire emission production system. For the period of August 2014 and June 2015, NWS/HYSPLIT smoke simulations show that fire smoke emissions with updated BlueSky are stronger than the current operational BlueSky in the Northwest U.S. For the same comparisons, weaker fire smoke emissions from the updated BlueSky were observed over the middle and eastern part of the U.S. A statistical evaluation of NWS/HYSPLIT smoke predicted total column concentration compared to NOAA NESDIS GOES EAST Aerosol Smoke Product retrievals is underway. Preliminary results show that using the newer version of BlueSky leads to improved performance of NWS/HYSPLIT-smoke for June 2015. These results are partially due to the default fuel loading selected for Canadian fires that lead to stronger fire emissions there. The use of more realistic Canadian fuel loading may improve NWS/HYSPLIT smoke forecast.
BIOGENIC HYDROCARBON EMISSION INVENTORY FOR THE U.S. USING A SIMPLE FOREST CANOPY MODEL
A biogenic hydrocarbon emission inventory system, developed for acid deposition and regional oxidant modeling, is described, and results for a U.S. emission inventory are presented. or deciduous and coniferous forests, scaling relationships are used to account for canopy effects ...
Code of Federal Regulations, 2014 CFR
2014-07-01
... the effects of emissions on air quality, for example, an assessment using EPA's community multi-scale... Source Complex Model or Emission and Dispersion Model System) to determine the effects of emissions on... that it is not a significant precursor, and (iii) Volatile organic compounds (VOC) and ammonia (NH3...
Code of Federal Regulations, 2012 CFR
2012-07-01
... the effects of emissions on air quality, for example, an assessment using EPA's community multi-scale... Source Complex Model or Emission and Dispersion Model System) to determine the effects of emissions on... that it is not a significant precursor, and (iii) Volatile organic compounds (VOC) and ammonia (NH3...
Code of Federal Regulations, 2013 CFR
2013-07-01
... the effects of emissions on air quality, for example, an assessment using EPA's community multi-scale... Source Complex Model or Emission and Dispersion Model System) to determine the effects of emissions on... that it is not a significant precursor, and (iii) Volatile organic compounds (VOC) and ammonia (NH3...
Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations
NASA Technical Reports Server (NTRS)
Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.
2012-01-01
Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.
MOVES is a state-of-the-science emission modeling system that estimates emissions for mobile sources at the national, county, and project level for criteria air pollutants, greenhouse gases, and air toxics.
The GOSSIP on the MCV V347 Pavonis
NASA Astrophysics Data System (ADS)
Potter, S. B.; Cropper, Mark; Hakala, P. J.
Modelling of the polarized cyclotron emission from magnetic cataclysmic variables (MCVs) has been a powerful technique for determining the structure of the accretion zones on the white dwarf. Until now, this has been achieved by constructing emission regions (for example arcs and spots) put in by hand, in order to recover the polarized emission. These models were all inferred indirectly from arguments based on polarization and X-ray light curves. Potter, Hakala & Cropper (1998) presented a technique (Stokes imaging) which objectively and analytically models the polarized emission to recover the structure of the cyclotron emission region(s) in MCVs. We demonstrate this technique with the aid of a test case, then we apply the technique to polarimetric observations of the AM Her system V347 Pav. As the system parameters of V347 Pav (for example its inclination) have not been well determined, we describe an extension to the Stokes imaging technique which also searches the system parameter space (GOSSIP).
Martins, V; Miranda, A I; Carvalho, A; Schaap, M; Borrego, C; Sá, E
2012-01-01
The main purpose of this work is to estimate the impact of forest fires on air pollution applying the LOTOS-EUROS air quality modeling system in Portugal for three consecutive years, 2003-2005. Forest fire emissions have been included in the modeling system through the development of a numerical module, which takes into account the most suitable parameters for Portuguese forest fire characteristics and the burnt area by large forest fires. To better evaluate the influence of forest fires on air quality the LOTOS-EUROS system has been applied with and without forest fire emissions. Hourly concentration results have been compared to measure data at several monitoring locations with better modeling quality parameters when forest fire emissions were considered. Moreover, hourly estimates, with and without fire emissions, can reach differences in the order of 20%, showing the importance and the influence of this type of emissions on air quality. Copyright © 2011 Elsevier B.V. All rights reserved.
Tuning the photon statistics of a strongly coupled nanophotonic system
NASA Astrophysics Data System (ADS)
Dory, Constantin; Fischer, Kevin A.; Müller, Kai; Lagoudakis, Konstantinos G.; Sarmiento, Tomas; Rundquist, Armand; Zhang, Jingyuan L.; Kelaita, Yousif; Sapra, Neil V.; Vučković, Jelena
2017-02-01
We investigate the dynamics of single- and multiphoton emission from detuned strongly coupled systems based on the quantum-dot-photonic-crystal resonator platform. Transmitting light through such systems can generate a range of nonclassical states of light with tunable photon counting statistics due to the nonlinear ladder of hybridized light-matter states. By controlling the detuning between emitter and resonator, the transmission can be tuned to strongly enhance either single- or two-photon emission processes. Despite the strongly dissipative nature of these systems, we find that by utilizing a self-homodyne interference technique combined with frequency filtering we are able to find a strong two-photon component of the emission in the multiphoton regime. In order to explain our correlation measurements, we propose rate equation models that capture the dominant processes of emission in both the single- and multiphoton regimes. These models are then supported by quantum-optical simulations that fully capture the frequency filtering of emission from our solid-state system.
Modeling carbon emissions from urban traffic system using mobile monitoring.
Sun, Daniel Jian; Zhang, Ying; Xue, Rui; Zhang, Yi
2017-12-01
Comprehensive analyses of urban traffic carbon emissions are critical in achieving low-carbon transportation. This paper started from the architecture design of a carbon emission mobile monitoring system using multiple sets of equipment and collected the corresponding data about traffic flow, meteorological conditions, vehicular carbon emissions and driving characteristics on typical roads in Shanghai and Wuxi, Jiangsu province. Based on these data, the emission model MOVES was calibrated and used with various sensitivity and correlation evaluation indices to analyze the traffic carbon emissions at microscopic, mesoscopic and macroscopic levels, respectively. The major factors that influence urban traffic carbon emissions were investigated, so that emission factors of CO, CO 2 and HC were calculated by taking representative passenger cars as a case study. As a result, the urban traffic carbon emissions were assessed quantitatively, and the total amounts of CO, CO 2 and HC emission from passenger cars in Shanghai were estimated as 76.95kt, 8271.91kt, and 2.13kt, respectively. Arterial roads were found as the primary line source, accounting for 50.49% carbon emissions. In additional to the overall major factors identified, the mobile monitoring system and carbon emission quantification method proposed in this study are of rather guiding significance for the further urban low-carbon transportation development. Copyright © 2017 Elsevier B.V. All rights reserved.
MODELS TO ESTIMATE VOLATILE ORGANIC HAZARDOUS AIR POLLUTANT EMISSIONS FROM MUNICIPAL SEWER SYSTEMS
Emissions from municipal sewers are usually omitted from hazardous air pollutant (HAP) emission inventories. This omission may result from a lack of appreciation for the potential emission impact and/or from inadequate emission estimation procedures. This paper presents an analys...
Methane, carbon dioxide, and nitrous oxide emissions from septic tank systems.
Diaz-Valbuena, Libia R; Leverenz, Harold L; Cappa, Christopher D; Tchobanoglous, George; Horwath, William R; Darby, Jeannie L
2011-04-01
Emissions of CH4, CO2, and N2O from conventional septic tank systems are known to occur, but there is a dearth of information as to the extent. Mass emission rates of CH4, CO2, and N2O, as measured with a modified flux chamber approach in eight septic tank systems, were determined to be 11, 33.3, and 0.005 g capita(-1) day(-1), respectively, in this research. Existing greenhouse gas (GHG) emission models based on BOD (biochemical oxygen demand) loading have estimated methane emissions to be as high as 27.1 g CH4 capita(-1) day(-1), more than twice the value measured in our study, and concluded that septic tanks are potentially significant sources of GHGs due to the large number of systems currently in use. Based on the measured CH4 emission value, a revised CH4 conversion factor of 0.22 (compared to 0.5) for use in the emissions models is suggested. Emission rates of CH4, CO2, and N2O were also determined from measurements of gas concentrations and flow rates in the septic vent system and were found to be 10.7, 335, and 0.2 g capita(-1)day(-1), respectively. The excellent agreement in the CH4 emission rates between the flux chamber and the vent values indicates the dominant CH4 source is the septic tank.
Modeling long-term carbon residue in the ocean-atmosphere system following large CO2 emissions
NASA Astrophysics Data System (ADS)
Towles, N. J.; Olson, P.; Gnanadesikan, A.
2013-12-01
We use the LOSCAR carbon cycle model (Zeebe et al., 2009; Zeebe, 2012) to calculate the residual carbon in the ocean and atmosphere following large CO2 emissions. We consider the system response to CO2 emissions ranging from 100 to 20000 PgC, and emission durations from 100 yr to 100 kyr, subject to a wide range of system parameters such as the strengths of silicate weathering and the oceanic biological carbon pump. We define the carbon gain factor as the ratio of residual carbon in the ocean-atmosphere to the total emitted carbon. For moderate sized emissions shorter than about 50 kyr, we find that the carbon gain factor grows during the emission and peaks at about 1.7, primarily due to the erosion of carbonate marine sediments. In contrast, for longer emissions, the carbon gain factor peaks at a smaller value, and for very large emissions (more than 5000 PgC), the gain factor decreases with emission size due to carbonate sediment exhaustion. This gain factor is sensitive to model parameters such as low latitude efficiency of the biological pump. The timescale for removal of the residual carbon (reducing the carbon gain factor to zero) depends strongly on the assumed sensitivity of silicate weathering to atmospheric pCO2, and ranges from less than one million years to several million years.
NASA Astrophysics Data System (ADS)
Simmonds, M.; Li, C.; Lee, J.; Six, J.; Van Kessel, C.; Linquist, B.
2015-12-01
Process-based modeling of CH4 and N2O emissions from rice fields is a practical tool for conducting greenhouse gas inventories and estimating mitigation potentials of alternative practices at the scales of management and policy-making. However, few studies have evaluated site-level model performance in side-by-side field trials of various management practices during both the growing season and fallow periods. We empirically evaluated the DeNitrification-DeComposition (DNDC) model for estimating CH4 and N2O fluxes in California rice systems under varying management (N fertilizer application rate, type of seeding system, fallow period straw and water management), soil environments, and weather conditions. Five and nine site-year combinations were used for calibration and validation, respectively. The model was parameterized for two cultivars, M206 and Koshihikari, and able to simulate 30% and 78% of the measured variation in yields, respectively. A major strength of DNDC was in estimating general site-level seasonal CH4 emissions (R2 = 0.85). However, a major limitation was in simulating finer resolution of differences in CH4 emissions (or lack thereof) among side-by-side management treatments (range of 0.2-465% relative absolute deviation). Additionally, DNDC did not satisfactorily simulate fallow period CH4 emissions, or seasonal and fallow period N2O emissions across all sites with the exception of a few cases. Specifically, simulated CH4 emissions were oversensitive to fertilizer N rates, but lacked sensitivity to the type of seeding system and prior fallow period straw management. Additionally, N2O emissions were oversensitive to fertilizer N rates and field drainage. Sensitivity analysis showed that CH4 emissions were highly sensitive to changes in the root to total plant biomass ratio. Overall, uncertainty in model predictions was attributed to uncertainty in both the input parameters due to in-field spatiotemporal variability of soil properties, and in the model structure (e.g., genotype by environment interactions, clay effects, and simulation routines for field drainage, and diffusion and ebullition of gasses). These findings have implications for model-directed field research that could improve model uncertainty for application at larger spatial scales.
Song, Guohua; Zhou, Xixi; Yu, Lei
2015-05-01
The intersection is one of the biggest emission points for buses and also the high exposure site for people. Several traffic performance indexes have been developed and widely used for intersection evaluations. However, few studies have focused on the relationship between these indexes and emissions at intersections. This paper intends to propose a model that relates emissions to the two commonly used measures of effectiveness (i.e. delay time and number of stops) by using bus activity data and emission data at intersections. First, with a large number of field instantaneous emission data and corresponding activity data collected by the Portable Emission Measurement System (PEMS), emission rates are derived for different vehicle specific power (VSP) bins. Then, 2002 sets of trajectory data, an equivalent of about 140,000 sets of second-by-second activity data, are obtained from Global Position Systems (GPSs)-equipped diesel buses in Beijing. The delay and the emission factors of each trajectory are estimated. Then, by using baseline emission factors for two types of intersections, e.g. the Arterial @ Arterial Intersection and the Arterial @ Collector, delay correction factors are calculated for the two types of intersections at different congestion levels. Finally, delay correction models are established for adjusting emission factors for each type of intersections and different numbers of stops. A comparative analysis between estimated and field emission factors demonstrates that the delay correction model is reliable. Copyright © 2015 Elsevier B.V. All rights reserved.
Development of On-line Wildfire Emissions for the Operational Canadian Air Quality Forecast System
NASA Astrophysics Data System (ADS)
Pavlovic, R.; Menard, S.; Chen, J.; Anselmo, D.; Paul-Andre, B.; Gravel, S.; Moran, M. D.; Davignon, D.
2013-12-01
An emissions processing system has been developed to incorporate near-real-time emissions from wildfires and large prescribed burns into Environment Canada's real-time GEM-MACH air quality (AQ) forecast system. Since the GEM-MACH forecast domain covers Canada and most of the USA, including Alaska, fire location information is needed for both of these large countries. Near-real-time satellite data are obtained and processed separately for the two countries for organizational reasons. Fire location and fuel consumption data for Canada are provided by the Canadian Forest Service's Canadian Wild Fire Information System (CWFIS) while fire location and emissions data for the U.S. are provided by the SMARTFIRE (Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation) system via the on-line BlueSky Gateway. During AQ model runs, emissions from individual fire sources are injected into elevated model layers based on plume-rise calculations and then transport and chemistry calculations are performed. This 'on the fly' approach to the insertion of emissions provides greater flexibility since on-line meteorology is used and reduces computational overhead in emission pre-processing. An experimental wildfire version of GEM-MACH was run in real-time mode for the summers of 2012 and 2013. 48-hour forecasts were generated every 12 hours (at 00 and 12 UTC). Noticeable improvements in the AQ forecasts for PM2.5 were seen in numerous regions where fire activity was high. Case studies evaluating model performance for specific regions, computed objective scores, and subjective evaluations by AQ forecasters will be included in this presentation. Using the lessons learned from the last two summers, Environment Canada will continue to work towards the goal of incorporating near-real-time intermittent wildfire emissions within the operational air quality forecast system.
Process level improvements in the CMAQ system have been made to WRF meteorology, national ammonia emission profiles, and CMAQ ammonia air-surface exchange. An incremental study was conducted to quantify the impact of individual and combined changes on modeled inorganic depositio...
Mathematical modeling of nitrous oxide (N2O) emissions from full-scale wastewater treatment plants.
Ni, Bing-Jie; Ye, Liu; Law, Yingyu; Byers, Craig; Yuan, Zhiguo
2013-07-16
Mathematical modeling of N2O emissions is of great importance toward understanding the whole environmental impact of wastewater treatment systems. However, information on modeling of N2O emissions from full-scale wastewater treatment plants (WWTP) is still sparse. In this work, a mathematical model based on currently known or hypothesized metabolic pathways for N2O productions by heterotrophic denitrifiers and ammonia-oxidizing bacteria (AOB) is developed and calibrated to describe the N2O emissions from full-scale WWTPs. The model described well the dynamic ammonium, nitrite, nitrate, dissolved oxygen (DO) and N2O data collected from both an open oxidation ditch (OD) system with surface aerators and a sequencing batch reactor (SBR) system with bubbling aeration. The obtained kinetic parameters for N2O production are found to be reasonable as the 95% confidence regions of the estimates are all small with mean values approximately at the center. The model is further validated with independent data sets collected from the same two WWTPs. This is the first time that mathematical modeling of N2O emissions is conducted successfully for full-scale WWTPs. While clearly showing that the NH2OH related pathways could well explain N2O production and emission in the two full-scale plants studied, the modeling results do not prove the dominance of the NH2OH pathways in these plants, nor rule out the possibility of AOB denitrification being a potentially dominating pathway in other WWTPs that are designed or operated differently.
Del Prado, A; Crosson, P; Olesen, J E; Rotz, C A
2013-06-01
The farm level is the most appropriate scale for evaluating options for mitigating greenhouse gas (GHG) emissions, because the farm represents the unit at which management decisions in livestock production are made. To date, a number of whole farm modelling approaches have been developed to quantify GHG emissions and explore climate change mitigation strategies for livestock systems. This paper analyses the limitations and strengths of the different existing approaches for modelling GHG mitigation by considering basic model structures, approaches for simulating GHG emissions from various farm components and the sensitivity of GHG outputs and mitigation measures to different approaches. Potential challenges for linking existing models with the simulation of impacts and adaptation measures under climate change are explored along with a brief discussion of the effects on other ecosystem services.
Tradeoffs between costs and greenhouse gas emissions in the design of urban transit systems
NASA Astrophysics Data System (ADS)
Griswold, Julia B.; Madanat, Samer; Horvath, Arpad
2013-12-01
Recent investments in the transit sector to address greenhouse gas emissions have concentrated on purchasing efficient replacement vehicles and inducing mode shift from the private automobile. There has been little focus on the potential of network and operational improvements, such as changes in headways, route spacing, and stop spacing, to reduce transit emissions. Most models of transit system design consider user and agency cost while ignoring emissions and the potential environmental benefit of operational improvements. We use a model to evaluate the user and agency costs as well as greenhouse gas benefit of design and operational improvements to transit systems. We examine how the operational characteristics of urban transit systems affect both costs and greenhouse gas emissions. The research identifies the Pareto frontier for designing an idealized transit network. Modes considered include bus, bus rapid transit (BRT), light rail transit (LRT), and metro (heavy) rail, with cost and emissions parameters appropriate for the United States. Passenger demand follows a many-to-many travel pattern with uniformly distributed origins and destinations. The approaches described could be used to optimize the network design of existing bus service or help to select a mode and design attributes for a new transit system. The results show that BRT provides the lowest cost but not the lowest emissions for our large city scenarios. Bus and LRT systems have low costs and the lowest emissions for our small city scenarios. Relatively large reductions in emissions from the cost-optimal system can be achieved with only minor increases in user travel time.
Modeling emissions of volatile organic compounds from silage storages and feed lanes
USDA-ARS?s Scientific Manuscript database
An initial volatile organic compound (VOC) emission model for silage sources, developed using experimental data from previous studies, was incorporated into the Integrated Farm System Model (IFSM), a whole-farm simulation model used to assess the performance, environmental impacts, and economics of ...
Evaluation of CMAQ and CAMx Ensemble Air Quality Forecasts during the 2015 MAPS-Seoul Field Campaign
NASA Astrophysics Data System (ADS)
Kim, E.; Kim, S.; Bae, C.; Kim, H. C.; Kim, B. U.
2015-12-01
The performance of Air quality forecasts during the 2015 MAPS-Seoul Field Campaign was evaluated. An forecast system has been operated to support the campaign's daily aircraft route decisions for airborne measurements to observe long-range transporting plume. We utilized two real-time ensemble systems based on the Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emissions (SMOKE)-Comprehensive Air quality Model with extensions (CAMx) modeling framework and WRF-SMOKE- Community Multi_scale Air Quality (CMAQ) framework over northeastern Asia to simulate PM10 concentrations. Global Forecast System (GFS) from National Centers for Environmental Prediction (NCEP) was used to provide meteorological inputs for the forecasts. For an additional set of retrospective simulations, ERA Interim Reanalysis from European Centre for Medium-Range Weather Forecasts (ECMWF) was also utilized to access forecast uncertainties from the meteorological data used. Model Inter-Comparison Study for Asia (MICS-Asia) and National Institute of Environment Research (NIER) Clean Air Policy Support System (CAPSS) emission inventories are used for foreign and domestic emissions, respectively. In the study, we evaluate the CMAQ and CAMx model performance during the campaign by comparing the results to the airborne and surface measurements. Contributions of foreign and domestic emissions are estimated using a brute force method. Analyses on model performance and emissions will be utilized to improve air quality forecasts for the upcoming KORUS-AQ field campaign planned in 2016.
NASA Astrophysics Data System (ADS)
Wang, S.
2014-12-01
Atmospheric ammonia (NH3) plays an important role in fine particle formation. Accurate estimates of ammonia can reduce uncertainties in air quality modeling. China is one of the largest countries emitting ammonia with the majority of NH3 emissions coming from the agricultural practices, such as fertilizer applications and animal operations. The current ammonia emission estimates in China are mainly based on pre-defined emission factors. Thus, there are considerable uncertainties in estimating NH3 emissions, especially in time and space distribution. For example, fertilizer applications vary in the date of application and amount by geographical regions and crop types. In this study, the NH3 emission from the agricultural fertilizer use in China of 2011 was estimated online by an agricultural fertilizer modeling system coupling a regional air-quality model and an agro-ecosystem model, which contains three main components 1) the Environmental Policy Integrated Climate (EPIC) model, 2) the meso-scale meteorology Weather Research and Forecasting (WRF) model and 3) the CMAQ air quality model with bi-directional ammonia fluxes. The EPIC output information about daily fertilizer application and soil characteristics would be the input of the CMAQ model. In order to run EPIC model, much Chinese local information is collected and processed. For example, Crop land data are computed from the MODIS land use data at 500-m resolution and crop categories at Chinese county level; the fertilizer use rate for different fertilizer types, crops and provinces are obtained from Chinese statistic materials. The system takes into consideration many influencing factors on agriculture ammonia emission, including weather, the fertilizer application method, timing, amount, and rate for specific pastures and crops. The simulated fertilizer data is compared with the NH3 emissions and fertilizer application data from other sources. The results of CMAQ modeling are also discussed and analyzed with field measurements. The estimated agricultural fertilizer NH3 emission in this study is about 3Tg in 2011. The regions with the highest emission rates are located in the North China Plain. Monthly, the peak ammonia emissions occur in April to July.
Federal Register 2010, 2011, 2012, 2013, 2014
2013-03-06
... to address basic SIP requirements, including emissions inventories, monitoring, and modeling to... basic structural SIP elements such as modeling, monitoring, and emissions inventories that are designed...): Emission limits and other control measures. 110(a)(2)(B): Ambient air quality monitoring/data system. 110(a...
Assessment of the Electrification of the Road Transport Sector on Net System Emissions
NASA Astrophysics Data System (ADS)
Miller, James
As worldwide environmental consciousness grows, electric vehicles (EVs) are becoming more common and despite the incredible potential for emissions reduction, the net emissions of the power system supply side plus the transportation system are dependent on the generation matrix. Current EV charging patterns tend to correspond directly with the peak consumption hours and have the potential to increase demand sharply allowing for only a small penetration of Electric Vehicles. Using the National Household Travel Survey (NHTS) data a model is created for vehicle travel patterns using trip chaining. Charging schemes are modeled to include uncontrolled residential, uncontrolled residential/industrial charging, optimized charging and optimized charging with vehicle to grid discharging. A charging profile is then determined based upon the assumption that electric vehicles would directly replace a percentage of standard petroleum-fueled vehicles in a known system. Using the generation profile for the specified region, a unit commitment model is created to establish not only the generation dispatch, but also the net CO2 profile for variable EV penetrations and charging profiles. This model is then used to assess the impact of the electrification of the road transport sector on the system net emissions.
Development of a database for chemical mechanism assignments for volatile organic emissions.
Carter, William P L
2015-10-01
The development of a database for making model species assignments when preparing total organic gas (TOG) emissions input for atmospheric models is described. This database currently has assignments of model species for 12 different gas-phase chemical mechanisms for over 1700 chemical compounds and covers over 3000 chemical categories used in five different anthropogenic TOG profile databases or output by two different biogenic emissions models. This involved developing a unified chemical classification system, assigning compounds to mixtures, assigning model species for the mechanisms to the compounds, and making assignments for unknown, unassigned, and nonvolatile mass. The comprehensiveness of the assignments, the contributions of various types of speciation categories to current profile and total emissions data, inconsistencies with existing undocumented model species assignments, and remaining speciation issues and areas of needed work are also discussed. The use of the system to prepare input for SMOKE, the Speciation Tool, and for biogenic models is described in the supplementary materials. The database, associated programs and files, and a users manual are available online at http://www.cert.ucr.edu/~carter/emitdb . Assigning air quality model species to the hundreds of emitted chemicals is a necessary link between emissions data and modeling effects of emissions on air quality. This is not easy and makes it difficult to implement new and more chemically detailed mechanisms in models. If done incorrectly, it is similar to errors in emissions speciation or the chemical mechanism used. Nevertheless, making such assignments is often an afterthought in chemical mechanism development and emissions processing, and existing assignments are usually undocumented and have errors and inconsistencies. This work is designed to address some of these problems.
NASA Astrophysics Data System (ADS)
Domínguez Chovert, Angel; Félix Alonso, Marcelo; Frassoni, Ariane; José Ferreira, Valter; Eiras, Denis; Longo, Karla; Freitas, Saulo
2017-04-01
Numerical modeling is a fundamental tool for studying the earth system components along with weather and climate forecast. In fact, the development of on-line models allows to simulate conditions of the atmosphere, for example, to evaluate certain chemicals in weather events with the purpose of improving a region's quality of air. For this determined purpose, the on-line models employ information from a broad range of sources in order to generate its variables forecasts. But beyond vast information sources, for a region's quality of air study, the data concerning the amount and distribution of emissions of polluting gases must be representative, as well as, it's required complete georeferenced emissions for simulations made with high resolution. Consequently, the modifications made in this work to the PREP-CHEM-SRC (Preprocessor of trace gas and aerosol emission fields for regional and a global atmospheric chemistry models) tool are presented to meliorate the initialization files for BRAMS models, 5.2 version (Brazilian Developments on the Regional Atmospheric Modeling System) and WRF (Weather Research and Forecasting Model) with vehicle emissions in the state of Rio de Janeiro, Brazil. It was determined the annual vehicle emission, until the year 2030, of the nitrogen oxides species (NOx) and carbon monoxide (CO) for each city and using different scenarios. For Rio de Janeiro city, a process of distribution by emissions of the main pollutant gases was implemented. In total, five different types of routes were used and the emission percentage for each one was calculated using the most current traffic information in them. For to check the industrial contributions to the emissions were used the global datasets RETRO (REanalysis of TROpospheric chemical composition) and EDGAR-HTAP (Emission Database for Global Atmospheric Research). On the other hand, for the biogenic contributions was used information from the MEGAN model (Model of Emissions of Gases and Aerosols from Nature). For all the analyzed species it was possible to observe the strong influence of the vehicular activity on the emission distribution.
Seasonal methane and nitrous oxide emissions of several rice cultivars in direct-seeded systems
USDA-ARS?s Scientific Manuscript database
Understanding cultivar effects on field greenhouse gas (GHG) emissions in rice (Oryza sativa L.) systems is needed to improve the accuracy of predictive models used for estimating GHG emissions and determine to what extent choice of cultivar may have on GHG mitigation. We compared methane (CH4) and...
Numerical Modeling of Transport of Biomass Burning Emissions on South America
NASA Technical Reports Server (NTRS)
RibeirodeFreitas, Saulo
2001-01-01
Our research efforts have addressed theoretical and numerical modeling of sources emissions and transport processes of trace gases and aerosols emitted by biomass burning on the central of Brazil and Amazon basin. For this effort we coupled all Eulerian transport model with the mesoscale atmospheric model RAMS (Regional Atmospheric Modeling System).
Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions
Feng, Sha; Lauvaux, Thomas; Newman, Sally; ...
2016-07-22
Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less
Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Feng, Sha; Lauvaux, Thomas; Newman, Sally
Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less
[Emission Factors of Vehicle Exhaust in Beijing].
Fan, Shou-bin; Tian, Ling-di; Zhang, Dong-xu; Qu, Song
2015-07-01
Based on the investigation of basic data such as vehicle type composition, driving conditions, ambient temperature and oil quality, etc., emission factors of vehicle exhaust pollutants including carbon monoxide (CO), nitrogen oxides (NOx), hydrocarbons (HC) and particulate matter(PM) were calculated using COPERT IV model. Emission factors of typical gasoline passenger cars and diesel trucks were measured using on-board measurement system on actual road. The measured and modeled emission factors were compared and the results showed that: the measured emission factors of CO, NOx and HC were 0. 96, 0. 64 and 4. 89 times of the modeled data for passenger cars conforming to the national IV emission standard. For the light, medium and heavy diesel trucks conforming to the national III emission standard, the measured data of CO emission factors were 1.61, 1. 07 and 1.76 times of the modeled data, respectively, the measured data of NOx emission factors were 1. 04, 1. 21 and 1. 18 times of the modeled data, and the measured data of HC emission factors were 3. 75, 1. 84 and 1. 47 times of the modeled data, while the model data of PM emission factors were 1. 31, 3. 42 and 6. 42 times of the measured data, respectively.
DOT National Transportation Integrated Search
2005-09-01
The United States (US) Federal Aviation Administration (FAA) Office of Environment and Energy (AEE) has : developed the System for assessing Aviations Global Emissions (SAGE) with support from the Volpe National : Transportation Systems Center (Vo...
Improved Fossil/Industrial CO2 Emissions Modeling for the North American Carbon Program
NASA Astrophysics Data System (ADS)
Gurney, K. R.; Seib, B.; Mendoza, D.; Knox, S.; Fischer, M.; Murtishaw, S.
2005-05-01
The quantification of fossil fuel CO2 emissions has implications for a wide variety of scientific and policy- related questions. Improvement in inverse-estimated carbon fluxes, country-level carbon budgeting, analysis of regional emissions trading systems, and targeting of observational systems are all important applications better served by improvements in understanding where and when fossil fuel/industrial CO2 is emitted. Traditional approaches to quantifying fossil/industrial CO2 emissions have relied on national sales/consumption of fossil fuels with secondary spatial footprints performed via proxies such as population. This approach has provided global spatiotemporal resolution of one degree/monthly. In recent years the need has arisen for emission estimates that not only achieve higher spatiotemporal scales but include a process- level component. This latter attribute provides dynamic linkages between energy policy/decisionmaking and emissions for use in projecting changes to energy systems and the implications these changes may have on climate change. We have embarked on a NASA-funded research strategy to construct a process-level fossil/industrial CO2 emissions model/database for North America that will resolve fossil/industrial CO2 emissions hourly and at 36 km. This project is a critical component of the North American Carbon Program. Our approach builds off of many decades of air quality monitoring for regulated pollutants such as NOx, VOCs and CO that has been performed by regional air quality managers, states, and the Environmental Protection Agency in the United States. By using the highly resolved monitoring data supplied to the EPA, we have computed CO2 emissions for residential, commercial/industrial, transportation, and biogenic sources. This effort employs a new emissions modeling system (CONCEPT) that spatially and temporally distributes the monitored emissions across the US. We will provide a description of the methodology we have employed, the difficulties encountered and some preliminary results. We will then compare our results to the traditional fossil/industrial CO2 emissions based on national sale/consumption statistics.
Improved Fossil/Industrial CO2 Emissions Modeling for the North American Carbon Program
NASA Astrophysics Data System (ADS)
Gurney, K. R.; Seib, B.; Mendoza, D.; Knox, S.; Fischer, M.; Murtishaw, S.
2006-12-01
The quantification of fossil fuel CO2 emissions has implications for a wide variety of scientific and policy- related questions. Improvement in inverse-estimated carbon fluxes, country-level carbon budgeting, analysis of regional emissions trading systems, and targeting of observational systems are all important applications better served by improvements in understanding where and when fossil fuel/industrial CO2 is emitted. Traditional approaches to quantifying fossil/industrial CO2 emissions have relied on national sales/consumption of fossil fuels with secondary spatial footprints performed via proxies such as population. This approach has provided global spatiotemporal resolution of one degree/monthly. In recent years the need has arisen for emission estimates that not only achieve higher spatiotemporal scales but include a process- level component. This latter attribute provides dynamic linkages between energy policy/decisionmaking and emissions for use in projecting changes to energy systems and the implications these changes may have on climate change. We have embarked on a NASA-funded research strategy to construct a process-level fossil/industrial CO2 emissions model/database for North America that will resolve fossil/industrial CO2 emissions hourly and at 36 km. This project is a critical component of the North American Carbon Program. Our approach builds off of many decades of air quality monitoring for regulated pollutants such as NOx, VOCs and CO that has been performed by regional air quality managers, states, and the Environmental Protection Agency in the United States. By using the highly resolved monitoring data supplied to the EPA, we have computed CO2 emissions for residential, commercial/industrial, transportation, and biogenic sources. This effort employs a new emissions modeling system (CONCEPT) that spatially and temporally distributes the monitored emissions across the US. We will provide a description of the methodology we have employed, the difficulties encountered and some preliminary results. We will then compare our results to the traditional fossil/industrial CO2 emissions based on national sale/consumption statistics.
Assessing fossil fuel CO2 emissions in California using atmospheric observations and models
NASA Astrophysics Data System (ADS)
Graven, H.; Fischer, M. L.; Lueker, T.; Jeong, S.; Guilderson, T. P.; Keeling, R. F.; Bambha, R.; Brophy, K.; Callahan, W.; Cui, X.; Frankenberg, C.; Gurney, K. R.; LaFranchi, B. W.; Lehman, S. J.; Michelsen, H.; Miller, J. B.; Newman, S.; Paplawsky, W.; Parazoo, N. C.; Sloop, C.; Walker, S. J.
2018-06-01
Analysis systems incorporating atmospheric observations could provide a powerful tool for validating fossil fuel CO2 (ffCO2) emissions reported for individual regions, provided that fossil fuel sources can be separated from other CO2 sources or sinks and atmospheric transport can be accurately accounted for. We quantified ffCO2 by measuring radiocarbon (14C) in CO2, an accurate fossil-carbon tracer, at nine observation sites in California for three months in 2014–15. There is strong agreement between the measurements and ffCO2 simulated using a high-resolution atmospheric model and a spatiotemporally-resolved fossil fuel flux estimate. Inverse estimates of total in-state ffCO2 emissions are consistent with the California Air Resources Board’s reported ffCO2 emissions, providing tentative validation of California’s reported ffCO2 emissions in 2014–15. Continuing this prototype analysis system could provide critical independent evaluation of reported ffCO2 emissions and emissions reductions in California, and the system could be expanded to other, more data-poor regions.
NASA Astrophysics Data System (ADS)
Bensaida, K.; Alie, Colin; Elkamel, A.; Almansoori, A.
2017-08-01
This paper presents a novel techno-economic optimization model for assessing the effectiveness of CO2 mitigation options for the electricity generation sub-sector that includes renewable energy generation. The optimization problem was formulated as a MINLP model using the GAMS modeling system. The model seeks the minimization of the power generation costs under CO2 emission constraints by dispatching power from low CO2 emission-intensity units. The model considers the detailed operation of the electricity system to effectively assess the performance of GHG mitigation strategies and integrates load balancing, carbon capture and carbon taxes as methods for reducing CO2 emissions. Two case studies are discussed to analyze the benefits and challenges of the CO2 reduction methods in the electricity system. The proposed mitigations options would not only benefit the environment, but they will as well improve the marginal cost of producing energy which represents an advantage for stakeholders.
Development , Implementation and Evaluation of a Physics-Base Windblown Dust Emission Model
A physics-based windblown dust emission parametrization scheme is developed and implemented in the CMAQ modeling system. A distinct feature of the present model includes the incorporation of a newly developed, dynamic relation for the surface roughness length, which is important ...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mahowald, Natalie
Soils in natural and managed ecosystems and wetlands are well known sources of methane, nitrous oxides, and reactive nitrogen gases, but the magnitudes of gas flux to the atmosphere are still poorly constrained. Thus, the reasons for the large increases in atmospheric concentrations of methane and nitrous oxide since the preindustrial time period are not well understood. The low atmospheric concentrations of methane and nitrous oxide, despite being more potent greenhouse gases than carbon dioxide, complicate empirical studies to provide explanations. In addition to climate concerns, the emissions of reactive nitrogen gases from soils are important to the changing nitrogenmore » balance in the earth system, subject to human management, and may change substantially in the future. Thus improved modeling of the emission fluxes of these species from the land surface is important. Currently, there are emission modules for methane and some nitrogen species in the Community Earth System Model’s Community Land Model (CLM-ME/N); however, there are large uncertainties and problems in the simulations, resulting in coarse estimates. In this proposal, we seek to improve these emission modules by combining state-of-the-art process modules for emissions, available data, and new optimization methods. In earth science problems, we often have substantial data and knowledge of processes in disparate systems, and thus we need to combine data and a general process level understanding into a model for projections of future climate that are as accurate as possible. The best methodologies for optimization of parameters in earth system models are still being developed. In this proposal we will develop and apply surrogate algorithms that a) were especially developed for computationally expensive simulations like CLM-ME/N models; b) were (in the earlier surrogate optimization Stochastic RBF) demonstrated to perform very well on computationally expensive complex partial differential equations in earth science with limited numbers of simulations; and, c) will be (as part of the proposed research) significantly improved both by adding asynchronous parallelism, early truncation of unsuccessful simulations, and the improvement of both serial and parallel performance by the use of derivative and sensitivity information from global and local surrogate approximations S(x). The algorithm development and testing will be focused on the CLM-ME/N model application, but the methods are general and are expected to also perform well on optimization for parameter estimation of other climate models and other classes of continuous multimodal optimization problems arising from complex simulation models. In addition, this proposal will compile available datasets of emissions of methane, nitrous oxides and reactive nitrogen species and develop protocols for site level comparisons with the CLM-ME/N. Once the model parameters are optimized against site level data, the model will be simulated at the global level and compared to atmospheric concentration measurements for the current climate, and future emissions will be estimated using climate change as simulated by the CESM. This proposal combines experts in earth system modeling, optimization, computer science, and process level understanding of soil gas emissions in an interdisciplinary team in order to improve the modeling of methane and nitrogen gas emissions. This proposal thus meets the requirements of the SciDAC RFP, by integrating state-of-the-art computer science and earth system to build an improved earth system model.« less
Simulating N2O emissions under different tillage systems of irrigated corn using RZ-Shaw model
USDA-ARS?s Scientific Manuscript database
Nitrous oxide (N2O) is potent greenhouse gas (GHG) and agriculture is a global source of N2O emissions from soil fertility management. Yet emissions vary by agronomic practices and environmental factors that govern soil moisture and temperature. Ecosystem models are important tools to estimate N2O e...
NASA Astrophysics Data System (ADS)
Ahmadov, R.; Grell, G. A.; James, E.; Freitas, S.; Pereira, G.; Csiszar, I. A.; Tsidulko, M.; Pierce, R. B.; McKeen, S. A.; Saide, P.; Alexander, C.; Benjamin, S.; Peckham, S.
2016-12-01
Wildfires can have huge impact on air quality and visibility over large parts of the US. It is quite challenging to accurately predict wildfire air quality given significant uncertainties in modeling of biomass burning (BB) emissions, fire size, plume rise and smoke transport. We developed a new smoke modeling system (HRRR-Smoke) based on the coupled meteorology-chemistry model WRF-Chem. The HRRR-Smoke modeling system uses fire radiative power (FRP) data measured by the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership satellite. Using the FRP data enables predicting fire emissions, fire size and plume rise more accurately. Another advantage of the VIIRS data is the fire detection and characterization at high spatial resolution during both day and nighttime. The HRRR-Smoke model is run in real-time for summer 2016 on 3km horizontal grid resolution over CONUS domain by NOAA/ESRL Global Systems Division (GSD). The model simulates advection and mixing of fine particulate matter (PM2.5 or smoke) emitted by calculated BB emissions. The BB emissions include both smoldering and flaming fractions. Fire plume rise is parameterized in an online mode during the model integration. In addition to smoke, anthropogenic emissions of PM2.5 are transported in an inline mode as a passive tracer by HRRR-Smoke. The HRRR-Smoke real-time runs use meteorological fields for initial and lateral boundary conditions from the experimental real-time HRRR(X) numerical weather prediction model also run at NOAA/ESRL/GSD. The model is initialized every 6 hours (00, 06, 12 and 18UTC) daily using newly generated meteorological fields and FRP data obtained during previous 24 hours. Then the model produces meteorological and smoke forecasts for next 36 hours. The smoke fields are cycled from one forecast to the next one. Predicted near-surface and vertically integrated smoke concentrations are visualized online on a web-site: http://rapidrefresh.noaa.gov/HRRRsmoke/In this talk, we discuss the major components of the HRRR-Smoke modeling system. We present modeled smoke fields for some major wildfire cases over the western US in 2016 and discuss the model performance for those cases.
NASA Astrophysics Data System (ADS)
Mertens, Mariano; Kerkweg, Astrid; Grewe, Volker; Jöckel, Patrick
2016-04-01
Road traffic is an important anthropogenic source of NOx, CO and non-methane hydrocarbons (NMHCs) which act as precursors for the formation of tropospheric ozone. The formation of ozone is highly non-linear. This means that the contribution of the road traffic sector cannot directly be derived from the amount of emitted species, because they are also determined by local emissions of other anthropogenic and natural sources. In addition, long range transport of precursors and ozone can play an important role in determining the local ozone budget. For a complete assessment of the impact of road traffic emissions it is therefore important to resolve both, local emissions and long range transport. This can be achieved by the use of the newly developed MECO(n) model system, which on-line couples the global chemistry-climate-model EMAC with the regional chemistry-climate-model COSMO-CLM/MESSy. Both models use the same chemical speciation. This allows a highly consistent model chain from the global to the local scale. To quantify the contribution of the road traffic emissions to tropospheric ozone we use an accounting system of the relevant reaction pathways of the different species from different sources (called tagging method). This tagging scheme is implemented consistently on all scales, allowing a direct comparison of the contributions. With this model configuration we investigate the impact of road traffic emissions to the tropospheric ozone budget in Europe. For the year 2008 we compare different emission scenarios and investigate the influence of both model and emission resolution. In addition, results of a mitigation scenario for the year 2030 are presented. They indicate that the contribution of the road traffic sector can be reduced by local reductions of emissions during summer. During winter the importance of long range transport increases. This can lead to increased contributions of the road traffic sector (e.g. by increased emissions in the US) even if local emissions are reduced.
The role of carbon dioxide in ammonia emission from manure
USDA-ARS?s Scientific Manuscript database
Ammonia emission from manure is a significant loss of fixed N from agricultural systems, and contributes to air pollution and ecosystem degradation. Despite the development of numerous mathematical models for predicting ammonia emission, the interactions between carbon dioxide emission, manure pH, a...
Development of database of real-world diesel vehicle emission factors for China.
Shen, Xianbao; Yao, Zhiliang; Zhang, Qiang; Wagner, David Vance; Huo, Hong; Zhang, Yingzhi; Zheng, Bo; He, Kebin
2015-05-01
A database of real-world diesel vehicle emission factors, based on type and technology, has been developed following tests on more than 300 diesel vehicles in China using a portable emission measurement system. The database provides better understanding of diesel vehicle emissions under actual driving conditions. We found that although new regulations have reduced real-world emission levels of diesel trucks and buses significantly for most pollutants in China, NOx emissions have been inadequately controlled by the current standards, especially for diesel buses, because of bad driving conditions in the real world. We also compared the emission factors in the database with those calculated by emission factor models and used in inventory studies. The emission factors derived from COPERT (Computer Programmer to calculate Emissions from Road Transport) and MOBILE may both underestimate real emission factors, whereas the updated COPERT and PART5 (Highway Vehicle Particulate Emission Modeling Software) models may overestimate emission factors in China. Real-world measurement results and emission factors used in recent emission inventory studies are inconsistent, which has led to inaccurate estimates of emissions from diesel trucks and buses over recent years. This suggests that emission factors derived from European or US-based models will not truly represent real-world emissions in China. Therefore, it is useful and necessary to conduct systematic real-world measurements of vehicle emissions in China in order to obtain the optimum inputs for emission inventory models. Copyright © 2015. Published by Elsevier B.V.
USDA-ARS?s Scientific Manuscript database
Agricultural production systems and land use change for agriculture and forestry are important sources of anthropogenic greenhouse gas (GHG) emissions. Recent commitments by the European Union, the United States, and China to reduce GHG emissions highlight the need to improve estimates of current em...
NASA Astrophysics Data System (ADS)
Dorich, C.; Contosta, A.; Li, C.; Brito, A.; Varner, R. K.
2013-12-01
Agriculture contributes 20 to 25 % of the total anthropogenic greenhouse gas (GHG) emissions globally. These agricultural emissions are primarily in the form of methane (CH4) and nitrous oxide (N2O) with these GHG accounting for roughly 40 and 80 % of the total anthropogenic emissions of CH4 and N2O, respectively. Due to varied management and the complexities of agricultural ecosystems, it is difficult to estimate these CH4 and N2O emissions. The IPCC emission factors can be used to yield rough estimates of CH4 and N2O emissions but they are often based on limited data. Accurate modeling validated by measurements is needed in order to identify potential mitigation areas, reduce GHG emissions from agriculture, and improve sustainability of farming practices. The biogeochemical model Manure DNDC was validated using measurements from two dairy farms in New Hampshire, USA in order to quantify GHG emissions under different management systems. One organic and one conventional dairy farm operated by the University of New Hampshire's Agriculture Experiment Station were utilized as the study sites for validation of Manure DNDC. Compilation of management records started in 2011 to provide model inputs. Model results were then compared to field collected samples of soil carbon and nitrogen, above-ground biomass, and GHG fluxes. Fluxes were measured in crop, animal, housing, and waste management sites on the farms in order to examine the entire farm ecosystem and test the validity of the model. Fluxes were measured by static flux chambers, with enteric fermentation measurements being conducted by the SF6 tracer test as well as a new method called Greenfeeder. Our preliminary GHG flux analysis suggests higher emissions than predicted by IPCC emission factors and equations. Results suggest that emissions from manure management is a key concern at the conventional dairy farm while bedded housing at the organic dairy produced large quantities of GHG.
NASA Astrophysics Data System (ADS)
Valenzuela, Victor Hugo
Air pollution emissions control strategies to reduce ozone precursor pollutants are analyzed by applying a photochemical modeling system. Simulations of air quality conditions during an ozone episode which occurred in June, 2006 are undertaken by increasing or reducing area source emissions in Ciudad Juarez, Chihuahua, Mexico. Two air pollutants are primary drivers in the formation of tropospheric ozone. Oxides of nitrogen (NOx) and volatile organic compounds (VOC) undergo multiple chemical reactions under favorable meteorological conditions to form ozone, which is a secondary pollutant that irritates respiratory systems in sensitive individuals especially the elderly and young children. The U.S. Environmental Protection Agency established National Ambient Air Quality Standards (NAAQS) to limit ambient air pollutants such as ozone by establishing an 8-hour average concentration of 0.075 ppm as the threshold at which a violation of the standard occurs. Ozone forms primarily due reactions in the troposphere of NOx and VOC emissions generated primarily by anthropogenic sources in urban regions. Data from emissions inventories indicate area sources account for ˜15 of NOx and ˜45% of regional VOC emissions. Area sources include gasoline stations, automotive paint bodyshops and nonroad mobile sources. Multiplicity of air pollution emissions sources provides an opportunity to investigate and potentially implement air quality improvement strategies to reduce emissions which contribute to elevated ozone concentrations. A baseline modeling scenario was established using the CAMx photochemical air quality model from which a series of sensitivity analyses for evaluating air quality control strategies were conducted. Modifications to area source emissions were made by varying NOx and / or VOC emissions in the areas of particular interest. Model performance was assessed for each sensitivity analysis. Normalized bias (NB) and normalized error (NE) were used to identify variability of the PREDICTED to OBSERVED ozone concentrations of both BASELINE model and simulations with modified emissions assessed by the sensitivity analysis. All simulations were found to vary within acceptable ranges of these two criteria variables. Simulation results indicate ozone formation in the PdN region is VOC-limited. Under VOC-limited conditions, modifications to NOx emissions do not produce a marked increase or decrease in ozone concentrations. Modifications to VOC emissions generated the highest variability in ozone concentrations. Increasing VOC emissions by 75% produced results which minimized model bias and error when comparing PREDICTED and OBSERVED ozone concentrations. Increasing VOC emissions by 75% either alone or in combination with a 75% increase in NOx emissions generated PREDICTED ozone concentrations very near to OBSERVED ozone. By evaluating the changes in ambient ozone concentrations through photochemical modeling, air quality planners may identify the most efficient or effective VOC emissions control strategies for area sources. Among the strategies to achieve emissions reductions are installation of gasoline vapor recovery systems, replacing high-pressure low-volume surface coating paint spray guns with high-volume low-pressure spray paint guns, requiring emissions control booths for surface coating operations as well as undertaking solvent management practices, requiring the sale of low VOC paint solvents in the surface-coating industry, and requiring low-VOC solvents in the dry cleaning industry. Other strategies to reduce VOC emissions include initiating Eco-Driving strategies to reduce fuel consumption from mobile sources and minimize vehicle idling at the international ports of entry by reducing bridge wait times. This dissertation depicts a tool for evaluating impacts of emissions on regional air quality by addressing the highly unresolved fugitive emissions in the Paso del Norte region. It provides a protocol for decision makers to assess the effects of various emission control strategies in the region. Impacts of specific source categories such as the international ports of entry, gasoline stations, paint body shops, truck stops, and military installations on the regional air quality can be easily and systematically addressed in a timely manner in the future.
Wit, Hero P; van Dijk, Pim; Manley, Geoffrey A
2012-11-01
Spontaneous otoacoustic emissions (SOAEs) and stimulus frequency otoacoustic emissions (SFOAEs) have been described from lizard ears. Although there are several models for these systems, none has modeled the characteristics of both of these types of otoacoustic emissions based upon their being derived from hair cells as active oscillators. Data from the ears of two lizard species, one lacking a tectorial membrane and one with a chain of tectorial sallets, as described by Bergevin et al. ["Coupled, active oscillators and lizard otoacoustic emissions," AIP Conf. Proc. 1403, 453 (2008)], are modeled as an array of coupled self-sustained oscillators. The model, originally developed by Vilfan and Duke ["Frequency clustering in spontaneous otoacoustic emissions from a lizard's ear," Biophys. J. 95, 4622-4630 (2008)], well describes both the amplitude and phase characteristics of SFOAEs and the relation between SFOAEs and SOAEs.
Time-Dependent Cryospheric Longwave Surface Emissivity Feedback in the Community Earth System Model
NASA Astrophysics Data System (ADS)
Kuo, Chaincy; Feldman, Daniel R.; Huang, Xianglei; Flanner, Mark; Yang, Ping; Chen, Xiuhong
2018-01-01
Frozen and unfrozen surfaces exhibit different longwave surface emissivities with different spectral characteristics, and outgoing longwave radiation and cooling rates are reduced for unfrozen scenes relative to frozen ones. Here physically realistic modeling of spectrally resolved surface emissivity throughout the coupled model components of the Community Earth System Model (CESM) is advanced, and implications for model high-latitude biases and feedbacks are evaluated. It is shown that despite a surface emissivity feedback amplitude that is, at most, a few percent of the surface albedo feedback amplitude, the inclusion of realistic, harmonized longwave, spectrally resolved emissivity information in CESM1.2.2 reduces wintertime Arctic surface temperature biases from -7.2 ± 0.9 K to -1.1 ± 1.2 K, relative to observations. The bias reduction is most pronounced in the Arctic Ocean, a region for which Coupled Model Intercomparison Project version 5 (CMIP5) models exhibit the largest mean wintertime cold bias, suggesting that persistent polar temperature biases can be lessened by including this physically based process across model components. The ice emissivity feedback of CESM1.2.2 is evaluated under a warming scenario with a kernel-based approach, and it is found that emissivity radiative kernels exhibit water vapor and cloud cover dependence, thereby varying spatially and decreasing in magnitude over the course of the scenario from secular changes in atmospheric thermodynamics and cloud patterns. Accounting for the temporally varying radiative responses can yield diagnosed feedbacks that differ in sign from those obtained from conventional climatological feedback analysis methods.
Optimal optical filters of fluorescence excitation and emission for poultry fecal detection
USDA-ARS?s Scientific Manuscript database
Purpose: An analytic method to design excitation and emission filters of a multispectral fluorescence imaging system is proposed and was demonstrated in an application to poultry fecal inspection. Methods: A mathematical model of a multispectral imaging system is proposed and its system parameters, ...
Comparative Assessment of Models and Methods To Calculate Grid Electricity Emissions.
Ryan, Nicole A; Johnson, Jeremiah X; Keoleian, Gregory A
2016-09-06
Due to the complexity of power systems, tracking emissions attributable to a specific electrical load is a daunting challenge but essential for many environmental impact studies. Currently, no consensus exists on appropriate methods for quantifying emissions from particular electricity loads. This paper reviews a wide range of the existing methods, detailing their functionality, tractability, and appropriate use. We identified and reviewed 32 methods and models and classified them into two distinct categories: empirical data and relationship models and power system optimization models. To illustrate the impact of method selection, we calculate the CO2 combustion emissions factors associated with electric-vehicle charging using 10 methods at nine charging station locations around the United States. Across the methods, we found an up to 68% difference from the mean CO2 emissions factor for a given charging site among both marginal and average emissions factors and up to a 63% difference from the average across average emissions factors. Our results underscore the importance of method selection and the need for a consensus on approaches appropriate for particular loads and research questions being addressed in order to achieve results that are more consistent across studies and allow for soundly supported policy decisions. The paper addresses this issue by offering a set of recommendations for determining an appropriate model type on the basis of the load characteristics and study objectives.
Carbon footprint and ammonia emissions of California beef production systems.
Stackhouse-Lawson, K R; Rotz, C A; Oltjen, J W; Mitloehner, F M
2012-12-01
Beef production is a recognized source of greenhouse gas (GHG) and ammonia (NH(3)) emissions; however, little information exists on the net emissions from beef production systems. A partial life cycle assessment (LCA) was conducted using the Integrated Farm System Model (IFSM) to estimate GHG and NH(3) emissions from representative beef production systems in California. The IFSM is a process-level farm model that simulates crop growth, feed production and use, animal growth, and the return of manure nutrients back to the land to predict the environmental impacts and economics of production systems. Ammonia emissions are determined by summing the emissions from animal housing facilities, manure storage, field applied manure, and direct deposits of manure on pasture and rangeland. All important sources and sinks of methane, nitrous oxide, and carbon dioxide are predicted from primary and secondary emission sources. Primary sources include enteric fermentation, manure, cropland used in feed production, and fuel combustion. Secondary emissions occur during the production of resources used on the farm, which include fuel, electricity, machinery, fertilizer, and purchased animals. The carbon footprint is the net exchange of all GHG in carbon dioxide equivalent (CO(2)e) units per kg of HCW produced. Simulated beef production systems included cow-calf, stocker, and feedlot phases for the traditional British beef breeds and calf ranch and feedlot phases for Holstein steers. An evaluation of differing production management strategies resulted in ammonia emissions ranging from 98 ± 13 to 141 ± 27 g/kg HCW and carbon footprints of 10.7 ± 1.4 to 22.6 ± 2.0 kg CO(2)e/kg HCW. Within the British beef production cycle, the cow-calf phase was responsible for 69 to 72% of total GHG emissions with 17 to 27% from feedlot sources. Holstein steers that entered the beef production system as a by-product of dairy production had the lowest carbon footprint because the emissions associated with their mothers were primarily attributed to milk rather than meat production. For the Holstein system, the feedlot phase was responsible for 91% of the total GHG emission, while the calf-ranch phase was responsible for 7% with the remaining 2% from transportation. This simulation study provides baseline emissions data for California beef production systems and indicates where mitigation strategies can be most effective in reducing emissions.
NASA Astrophysics Data System (ADS)
VanderZaag, A. C.; MacDonald, J. D.; Evans, L.; Vergé, X. P. C.; Desjardins, R. L.
2013-09-01
Methane emissions from manure management represent an important mitigation opportunity, yet emission quantification methods remain crude and do not contain adequate detail to capture changes in agricultural practices that may influence emissions. Using the Canadian emission inventory methodology as an example, this letter explores three key aspects for improving emission quantification: (i) obtaining emission measurements to improve and validate emission model estimates, (ii) obtaining more useful activity data, and (iii) developing a methane emission model that uses the available farm management activity data. In Canada, national surveys to collect manure management data have been inconsistent and not designed to provide quantitative data. Thus, the inventory has not been able to accurately capture changes in management systems even between manure stored as solid versus liquid. To address this, we re-analyzed four farm management surveys from the past decade and quantified the significant change in manure management which can be linked to the annual agricultural survey to create a continuous time series. In the dairy industry of one province, for example, the percentage of manure stored as liquid increased by 300% between 1991 and 2006, which greatly affects the methane emission estimates. Methane emissions are greatest from liquid manure, but vary by an order of magnitude depending on how the liquid manure is managed. Even if more complete activity data are collected on manure storage systems, default Intergovernmental Panel on Climate Change (IPCC) guidance does not adequately capture the impacts of management decisions to reflect variation among farms and regions in inventory calculations. We propose a model that stays within the IPCC framework but would be more responsive to farm management by generating a matrix of methane conversion factors (MCFs) that account for key factors known to affect methane emissions: temperature, retention time and inoculum. This MCF matrix would be populated using a mechanistic emission model verified with on-farm emission measurements. Implementation of these MCF values will require re-analysis of farm surveys to quantify liquid manure emptying frequency and timing, and will rely on the continued collection of this activity data in the future. For model development and validation, emission measurement campaigns will be needed on representative farms over at least one full year, or manure management cycle (whichever is longer). The proposed approach described in this letter is long-term, but is required to establish baseline data for emissions from manure management systems. With these improvements, the manure management emission inventory will become more responsive to the changing practices on Canadian livestock farms.
NASA Astrophysics Data System (ADS)
Lyon, David Richard
Methane emissions from the oil and gas (O&G) supply chain reduce potential climate benefits of natural gas as a replacement for other fossil fuels that emit more carbon dioxide per energy produced. O&G facilities have skewed emission rate distributions with a small fraction of sites contributing the majority of emissions. Knowledge of the identity and cause of these high emission facilities, referred to as super-emitters or fat-tail sources, is critical for reducing supply chain emissions. This dissertation addresses the quantification of super-emitter emissions, assessment of their prevalence and relationship to site characteristics, and mitigation with continuous leak detection systems. Chapter 1 summarizes the state of the knowledge of O&G methane emissions. Chapter 2 constructs a spatially-resolved emission inventory to estimate total and O&G methane emissions in the Barnett Shale as part of a coordinated research campaign using multiple top-down and bottom-up methods to quantify emissions. The emission inventory accounts for super-emitters with two-phase Monte Carlo simulations that combine site measurements collected with two approaches: unbiased sampling and targeted sampling of super-emitters. More comprehensive activity data and the inclusion of super-emitters, which account for 19% of O&G emissions, produces a emission inventory that is not statistically different than top-down regional emission estimates. Chapter 3 describes a helicopter-based survey of over 8,000 well pads in seven basins with infrared optical gas imaging to assess high emission sources. Four percent of sites are observed to have high emissions with over 90% of observed sources from tanks. The occurrence of high emissions is weakly correlated to site parameters and the best statistical model explains only 14% of variance, which demonstrates that the occurrence of super-emitters is primarily stochastic. Chapter 4 presents a Gaussian dispersion model for optimizing the placement of continuous leak detection systems at three example well pads. The model demonstrates that large leaks can be detected quickly with first generation systems. Continuous leak detection can be used in the near future to cost-effectively mitigate methane emissions from O&G super-emitters.
The generation of amplified spontaneous emission in high-power CPA laser systems.
Keppler, Sebastian; Sävert, Alexander; Körner, Jörg; Hornung, Marco; Liebetrau, Hartmut; Hein, Joachim; Kaluza, Malte Christoph
2016-03-01
An analytical model is presented describing the temporal intensity contrast determined by amplified spontaneous emission in high-intensity laser systems which are based on the principle of chirped pulse amplification. The model describes both the generation and the amplification of the amplified spontaneous emission for each type of laser amplifier. This model is applied to different solid state laser materials which can support the amplification of pulse durations ≤350 fs . The results are compared to intensity and fluence thresholds, e.g. determined by damage thresholds of a certain target material to be used in high-intensity applications. This allows determining if additional means for contrast improvement, e.g. plasma mirrors, are required for a certain type of laser system and application. Using this model, the requirements for an optimized high-contrast front-end design are derived regarding the necessary contrast improvement and the amplified "clean" output energy for a desired focussed peak intensity. Finally, the model is compared to measurements at three different high-intensity laser systems based on Ti:Sapphire and Yb:glass. These measurements show an excellent agreement with the model.
Impacts of Aging Emission Control Systems on In-Use Heavy-Duty Diesel Truck Emission Rates
NASA Astrophysics Data System (ADS)
Preble, C.; Cados, T.; Harley, R.; Kirchstetter, T.
2017-12-01
Heavy-duty diesel trucks are a major source of nitrogen oxides (NOx) and black carbon (BC) in urban environments, contributing to persistent ozone and particulate matter air quality problems. Recently, diesel particle filter (DPF) and selective catalytic reduction (SCR) emission control systems have become standard equipment on new trucks. Particle filters can also be installed as a retrofit on older engines. Prior work has shown that exhaust filters and SCR systems effectively reduce BC and NOx emission rates by up to 90 and 80%, respectively (Preble et al., ES&T 2015). There is concern, however, that DPFs may promote the formation of ultrafine particles (UFP) and increase tailpipe emissions of nitrogen dioxide (NO2). Additionally, urea-based SCR systems for NOx control may form nitrous oxide (N2O), an important contributor to stratospheric ozone depletion. The effectiveness of these emission controls has been thoroughly evaluated in the laboratory, but the long-term durability of in-use systems and their impacts on co-emitted species have not been well characterized. To evaluate the in-use performance of DPF and SCR systems, pollutant emissions from thousands of diesel trucks were measured over several years at the Port of Oakland and the Caldecott Tunnel in the San Francisco Bay Area. Pollutants present in the exhaust plumes of individual trucks were measured at high time resolution (≥1 Hz) as trucks passed under a mobile lab stationed on an overpass. Fuel-based emission factors (g pollutant emitted per kg fuel burned) were calculated for individual trucks and linked via recorded license plates to vehicle attributes, including engine model year and installed emission control systems. Use of DPFs reduced the BC emission rate by up to 95% at both locations. SCR systems were more effective at reducing NOx emissions under the uphill, highway driving conditions at the Caldecott Tunnel. The emission rates of co-emitted species NO2, UFP, and N2O depended on driving mode. Some DPFs on trucks with 2007-2009 model year engines showed deterioration or failure in filter performance, leading to higher BC emission rates compared to the average for trucks without filters. Emission inventories may underestimate total on-road emissions from diesel trucks, especially if particle filter failure rates continue to increase over time.
Development and Evaluation of the Biogenic Emissions Inventory System (BEIS) Model v3.6
We have developed new canopy emission algorithms and land use data for BEIS v3.6. Simulations with BEIS v3.4 and BEIS v3.6 in CMAQ v5.0.2 are compared these changes to the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and evaluated the simulations against observati...
U.S. emissions of HFC-134a derived for 2008-2012 from an extensive flask-air sampling network
NASA Astrophysics Data System (ADS)
Hu, Lei; Montzka, Stephen A.; Miller, John B.; Andrews, Aryln E.; Lehman, Scott J.; Miller, Benjamin R.; Thoning, Kirk; Sweeney, Colm; Chen, Huilin; Godwin, David S.; Masarie, Kenneth; Bruhwiler, Lori; Fischer, Marc L.; Biraud, Sebastien C.; Torn, Margaret S.; Mountain, Marikate; Nehrkorn, Thomas; Eluszkiewicz, Janusz; Miller, Scot; Draxler, Roland R.; Stein, Ariel F.; Hall, Bradley D.; Elkins, James W.; Tans, Pieter P.
2015-01-01
national and regional emissions of HFC-134a are derived for 2008-2012 based on atmospheric observations from ground and aircraft sites across the U.S. and a newly developed regional inverse model. Synthetic data experiments were first conducted to optimize the model assimilation design and to assess model-data mismatch errors and prior flux error covariances computed using a maximum likelihood estimation technique. The synthetic data experiments also tested the sensitivity of derived national and regional emissions to a range of assumed prior emissions, with the goal of designing a system that was minimally reliant on the prior. We then explored the influence of additional sources of error in inversions with actual observations, such as those associated with background mole fractions and transport uncertainties. Estimated emissions of HFC-134a range from 52 to 61 Gg yr-1 for the contiguous U.S. during 2008-2012 for inversions using air transport from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model driven by the 12 km resolution meteorogical data from North American Mesoscale Forecast System (NAM12) and all tested combinations of prior emissions and background mole fractions. Estimated emissions for 2008-2010 were 20% lower when specifying alternative transport from Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by the Weather Research and Forecasting (WRF) meteorology. Our estimates (for HYSPLIT-NAM12) are consistent with annual emissions reported by U.S. Environmental Protection Agency for the full study interval. The results suggest a 10-20% drop in U.S. national HFC-134a emission in 2009 coincident with a reduction in transportation-related fossil fuel CO2 emissions, perhaps related to the economic recession. All inversions show seasonal variation in national HFC-134a emissions in all years, with summer emissions greater than winter emissions by 20-50%.
NASA Astrophysics Data System (ADS)
Aziz, H. M. Abdul
Personal transport is a leading contributor to fossil fuel consumption and greenhouse (GHG) emissions in the U.S. The U.S. Energy Information Administration (EIA) reports that light-duty vehicles (LDV) are responsible for 61% of all transportation related energy consumption in 2012, which is equivalent to 8.4 million barrels of oil (fossil fuel) per day. The carbon content in fossil fuels is the primary source of GHG emissions that links to the challenge associated with climate change. Evidently, it is high time to develop actionable and innovative strategies to reduce fuel consumption and GHG emissions from the road transportation networks. This dissertation integrates the broader goal of minimizing energy and emissions into the transportation planning process using novel systems modeling approaches. This research aims to find, investigate, and evaluate strategies that minimize carbon-based fuel consumption and emissions for a transportation network. We propose user and system level strategies that can influence travel decisions and can reinforce pro-environmental attitudes of road users. Further, we develop strategies that system operators can implement to optimize traffic operations with emissions minimization goal. To complete the framework we develop an integrated traffic-emissions (EPA-MOVES) simulation framework that can assess the effectiveness of the strategies with computational efficiency and reasonable accuracy. The dissertation begins with exploring the trade-off between emissions and travel time in context of daily travel decisions and its heterogeneous nature. Data are collected from a web-based survey and the trade-off values indicating the average additional travel minutes a person is willing to consider for reducing a lb. of GHG emissions are estimated from random parameter models. Results indicate that different trade-off values for male and female groups. Further, participants from high-income households are found to have higher trade-off values compared with other groups. Next, we propose personal mobility carbon allowance (PMCA) scheme to reduce emissions from personal travel. PMCA is a market-based scheme that allocates carbon credits to users at no cost based on the emissions reduction goal of the system. Users can spend carbon credits for travel and a market place exists where users can buy or sell credits. This dissertation addresses two primary dimensions: the change in travel behavior of the users and the impact at network level in terms of travel time and emissions when PMCA is implemented. To understand this process, a real-time experimental game tool is developed where players are asked to make travel decisions within the carbon budget set by PMCA and they are allowed to trade carbon credits in a market modeled as a double auction game. Random parameter models are estimated to examine the impact of PMCA on short-term travel decisions. Further, to assess the impact at system level, a multi-class dynamic user equilibrium model is formulated that captures the travel behavior under PMCA scheme. The equivalent variational inequality problem is solved using projection method. Results indicate that PMCA scheme is able to reduce GHG emissions from transportation networks. Individuals with high value of travel time (VOTT) are less sensitive to PMCA scheme in context of work trips. High and medium income users are more likely to have non-work trips with lower carbon cost (higher travel time) to save carbon credits for work trips. Next, we focus on the strategies from the perspectives of system operators in transportation networks. Learning based signal control schemes are developed that can reduce emissions from signalized urban networks. The algorithms are implemented and tested in VISSIM micro simulator. Finally, an integrated emissions-traffic simulator framework is outlined that can be used to evaluate the effectiveness of the strategies. The integrated framework uses MOVES2010b as the emissions simulator. To estimate the emissions efficiently we propose a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the link driving schedules for MOVES2010b. Test results using the data from a five-intersection corridor show that HC-DTW technique can significantly reduce emissions estimation time without compromising the accuracy. The benefits are found to be most significant when the level of congestion variation is high. In addition to finding novel strategies for reducing emissions from transportation networks, this dissertation has broader impacts on behavior based energy policy design and transportation network modeling research. The trade-off values can be a useful indicator to identify which policies are most effective to reinforce pro-environmental travel choices. For instance, the model can estimate the distribution of trade-off between emissions and travel time, and provide insights on the effectiveness of policies for New York City if we are able to collect data to construct a representative sample. The probability of route choice decisions vary across population groups and trip contexts. The probability as a function of travel and demographic attributes can be used as behavior rules for agents in an agent-based traffic simulation. Finally, the dynamic user equilibrium based network model provides a general framework for energy policies such carbon tax, tradable permit, and emissions credits system.
Modeling the trade-off between diet costs and methane emissions: A goal programming approach.
Moraes, L E; Fadel, J G; Castillo, A R; Casper, D P; Tricarico, J M; Kebreab, E
2015-08-01
Enteric methane emission is a major greenhouse gas from livestock production systems worldwide. Dietary manipulation may be an effective emission-reduction tool; however, the associated costs may preclude its use as a mitigation strategy. Several studies have identified dietary manipulation strategies for the mitigation of emissions, but studies examining the costs of reducing methane by manipulating diets are scarce. Furthermore, the trade-off between increase in dietary costs and reduction in methane emissions has only been determined for a limited number of production scenarios. The objective of this study was to develop an optimization framework for the joint minimization of dietary costs and methane emissions based on the identification of a set of feasible solutions for various levels of trade-off between emissions and costs. Such a set of solutions was created by the specification of a systematic grid of goal programming weights, enabling the decision maker to choose the solution that achieves the desired trade-off level. Moreover, the model enables the calculation of emission-mitigation costs imputing a trading value for methane emissions. Emission imputed costs can be used in emission-unit trading schemes, such as cap-and-trade policy designs. An application of the model using data from lactating cows from dairies in the California Central Valley is presented to illustrate the use of model-generated results in the identification of optimal diets when reducing emissions. The optimization framework is flexible and can be adapted to jointly minimize diet costs and other potential environmental impacts (e.g., nitrogen excretion). It is also flexible so that dietary costs, feed nutrient composition, and animal nutrient requirements can be altered to accommodate various production systems. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Harrison, Kenneth W.; Tian, Yudong; Peters-Lidard, Christa D.; Ringerud, Sarah; Kumar, Sujay V.
2018-01-01
Better estimation of land surface microwave emissivity promises to improve over-land precipitation retrievals in the GPM era. Forward models of land microwave emissivity are available but have suffered from poor parameter specification and limited testing. Here, forward models are calibrated and the accompanying change in predictive power is evaluated. With inputs (e.g., soil moisture) from the Noah land surface model and applying MODIS LAI data, two microwave emissivity models are tested, the Community Radiative Transfer Model (CRTM) and Community Microwave Emission Model (CMEM). The calibration is conducted with the NASA Land Information System (LIS) parameter estimation subsystem using AMSR-E based emissivity retrievals for the calibration dataset. The extent of agreement between the modeled and retrieved estimates is evaluated using the AMSR-E retrievals for a separate 7-year validation period. Results indicate that calibration can significantly improve the agreement, simulating emissivity with an across-channel average root-mean-square-difference (RMSD) of about 0.013, or about 20% lower than if relying on daily estimates based on climatology. The results also indicate that calibration of the microwave emissivity model alone, as was done in prior studies, results in as much as 12% higher across-channel average RMSD, as compared to joint calibration of the land surface and microwave emissivity models. It remains as future work to assess the extent to which the improvements in emissivity estimation translate into improvements in precipitation retrieval accuracy. PMID:29795962
Regional air quality models are frequently used for regulatory applications to predict changes in air quality due to changes in emissions or changes in meteorology. Dynamic model evaluation is thus an important step in establishing credibility in the model predicted pollutant re...
NASA Astrophysics Data System (ADS)
Cohen, J. B.; Xi, X.; Wang, C.
2012-12-01
Black Carbon (BC) and other absorbing aerosols uniquely impact the climate system by both scattering and absorbing solar radiation, leading to simultaneous heating and cooling of the climate system. A critical understanding of the emissions, processing, transport, and removal of these aerosols are necessary to increase our understanding of their impacts on climate system. However, BC is tricky to model: it has a mostly anthropogenic origin that is highly variable in both space and time. Furthermore, its atmospheric chemical and physical processing involves interaction with third-party chemical species. Finally, there is a strong correlation between uncertainty in prediction of the primary removal mechanism, precipitation, and those regions having the highest emissions, such as Monsoon regions of Asia. Recent work using a coupled climate/radiation/aerosol/urbanization model, data of BC concentrations and remotely sensed AAODs from more than 100 different sites, and a Kalman Filter, has lead to an average estimate of the BC average and uncertainty range of emissions. These average results ranged from about 200% to 300% the emissions currently used by the IPCC, AEROCOM, and GFED. The differences in the modeled concentrations, AAODs, radiative forcings, and climate response between these annual average different emissions levels, as well as the error bounds associated with the Kalman Filter emissions has been explored and will be summarized. Additionally, since absorbing aerosols are regionally and temporally non-uniform, an improved comparison between these differences will be highlighted using an additional data source: MISR AOD and a new analysis technique to mathematically constrain and identify unique temporally and spatially varying properties. These new constraints will be further combined with model runs under the different emissions scenarios to test the impacts of both annual average as well as more realistic cases of large-scale, season-to-season, and year-to-year variations. These results will be displayed, compared against measurements, and the influence of the time-varying component quantified both globally as well as over two regions exhibiting such an influence. It is hoped that such quantification can lead to further improvement of the emissions estimates and their impact on the climate system.
Methodologies for Evaluating Environmental Benefits of Intelligent Transportation Systems
DOT National Transportation Integrated Search
2001-05-01
This report provides an overview of the current state of practice in evaluation of air quality impacts and also in emissions modeling. This report also describes the recent developments in emissions modeling. The air quality impacts of various ITS st...
Chien, T W; Chu, H; Hsu, W C; Tseng, T K; Hsu, C H; Chen, K Y
2003-08-01
The continuous emission monitoring system (CEMS) can monitor flue gas emissions continuously and instantaneously. However, it has the disadvantages of enormous cost, easily producing errors in sampling periods of bad weather, lagging response in variable ambient environments, and missing data in daily zero and span tests and maintenance. The concept of a predictive emission monitoring system (PEMS) is to use the operating parameters of combustion equipment through thermodynamic or statistical methods to construct a mathematic model that can predict emissions by a computer program. The goal of this study is to set up a PEMS in a gas-fired combined cycle power generation unit at the Hsinta station of Taiwan Power Co. The emissions to be monitored include nitrogen oxides (NOx) and oxygen (O2) in flue gas. The major variables of the predictive model were determined based on the combustion theory. The data of these variables then were analyzed to establish a regression model. From the regression results, the influences of these variables are discussed and the predicted values are compared with the CEMS data for accuracy. In addition, according to the cost information, the capital and operation and maintenance costs for a PEMS can be much lower than those for a CEMS.
Cost of lower NO x emissions: Increased CO 2 emissions from heavy-duty diesel engines
NASA Astrophysics Data System (ADS)
Krishnamurthy, Mohan; Carder, Daniel K.; Thompson, Gregory; Gautam, Mridul
This paper highlights the effect of emissions regulations on in-use emissions from heavy-duty vehicles powered by different model year engines. More importantly, fuel economy data for pre- and post-consent decree engines are compared. The objective of this study was to determine the changes in brake-specific emissions of NO x as a result of emission regulations, and to highlight the effect these have had on brake-specific CO 2 emission; hence, fuel consumption. For this study, in-use, on-road emission measurements were collected. Test vehicles were instrumented with a portable on-board tailpipe emissions measurement system, WVU's Mobile Emissions Measurement System, and were tested on specific routes, which included a mix of highway and city driving patterns, in order to collect engine operating conditions, vehicle speed, and in-use emission rates of CO 2 and NO x. Comparison of on-road in-use emissions data suggests NO x reductions as high as 80% and 45% compared to the US Federal Test Procedure and Not-to-Exceed standards for model year 1995-2002. However, the results indicate that the fuel consumption; hence, CO 2 emissions increased by approximately 10% over the same period, when the engines were operating in the Not-to-Exceed region.
Understanding Methane Emission from Natural Gas Activities Using Inverse Modeling Techniques
NASA Astrophysics Data System (ADS)
Abdioskouei, M.; Carmichael, G. R.
2015-12-01
Natural gas (NG) has been promoted as a bridge fuel that can smooth the transition from fossil fuels to zero carbon energy sources by having lower carbon dioxide emission and lower global warming impacts in comparison to other fossil fuels. However, the uncertainty around the estimations of methane emissions from NG systems can lead to underestimation of climate and environmental impacts of using NG as a replacement for coal. Accurate estimates of methane emissions from NG operations is crucial for evaluation of environmental impacts of NG extraction and at larger scale, adoption of NG as transitional fuel. However there is a great inconsistency within the current estimates. Forward simulation of methane from oil and gas operation sites for the US is carried out based on NEI-2011 using the WRF-Chem model. Simulated values are compared against measurements of observations from different platforms such as airborne (FRAPPÉ field campaign) and ground-based measurements (NOAA Earth System Research Laboratory). A novel inverse modeling technique is used in this work to improve the model fit to the observation values and to constrain methane emission from oil and gas extraction sites.
Simulating Electron Cyclotron Maser Emission for Low Mass Stars
NASA Astrophysics Data System (ADS)
Llama, Joe; Jardine, Moira
2018-01-01
Zeeman-Doppler Imaging (ZDI) is a powerful technique that enables us to map the large-scale magnetic fields of stars spanning the pre- and main-sequence. Coupling these magnetic maps with field extrapolation methods allow us to investigate the topology of the closed, X-ray bright corona, and the cooler, open stellar wind.Using ZDI maps of young M dwarfs with simultaneous radio light curves obtained from the VLA, we present the results of modeling the Electron-Cyclotron Maser (ECM) emission from these systems. We determine the X-ray luminosity and ECM emission that is produced using the ZDI maps and our field extrapolation model. We compare these findings with the observed radio light curves of these stars. This allows us to predict the relative phasing and amplitude of the stellar X-ray and radio light curves.This benchmarking of our model using these systems allows us to predict the ECM emission for all stars that have a ZDI map and an observed X-ray luminosity. Our model allows us to understand the origin of transient radio emission observations and is crucial for disentangling stellar and exoplanetary radio signals.
The effect of CO2 regulations on the cost of corn ethanol production
NASA Astrophysics Data System (ADS)
Plevin, R. J.; Mueller, S.
2008-04-01
To explore the effect of CO2 price on the effective cost of ethanol production we have developed a model that integrates financial and emissions accounting for dry-mill corn ethanol plants. Three policy options are modeled: (1) a charge per unit of life cycle CO2 emissions, (2) a charge per unit of direct biorefinery emissions only, and (3) a low carbon fuel standard (LCFS). A CO2 charge on life cycle emissions increases production costs by between 0.005 and 0.008 l-1 per 10 Mg-1 CO2 price increment, across all modeled plant energy systems, with increases under direct emissions somewhat lower in all cases. In contrast, a LCFS increases the cost of production for selected plant energy systems only: a LCFS requiring reductions in average fuel global warming intensity (GWI) with a target of 10% below the 2005 baseline increases the production costs for coal-fired plants only. For all other plant types, the LCFS operates as a subsidy. The findings depend strongly on the magnitude of a land use change adder. Some land use change adders currently discussed in the literature will push the GWI of all modeled production systems above the LCFS target, flipping the CO2 price from a subsidy to a tax.
Meteorological air quality forecasting using the WRF-Chem model during the LMOS2017 field campaign
NASA Astrophysics Data System (ADS)
Stanier, C. O.; Abdioskouei, M.; Carmichael, G. R.; Christiansen, M.; Sobhani, N.
2017-12-01
The Lake Michigan Ozone Study (LMOS 2017) occurred during May and June 2017 to address the high ozone episodes in coastal communities surrounding Lake Michigan. Aircraft, ship, mobile lab, and ground-based stations were used in this campaign to build an extensive dataset regarding ozone, its precursors, and particulate matter. The University of Iowa produced high-resolution (4x4 km2 horizontal resolution and 53 vertical levels) forecast products using the WRF-Chem modeling system in support of experimental planning during LMOS 2017. The base forecast system used WRF-Chem 3.6.1 and updated National Emission Inventory (NEI-2011v2). In the updated NEI-2011v2, we reduced the NOx emissions by 28% based on EPA's estimated NOx trends from 2011 to 2017. We ran another daily forecast (perturbed forecast) with 50% reduced NOx emission to capture the sensitivity of ozone to NOx emission and account for the impact of weekend emissions on ozone values. Preliminary in-field evaluation of model performance for clouds, on-shore flows, and surface and aircraft sampled ozone and NOx concentrations found that the model successfully captured much of the observed synoptic variability of onshore flows. The model captured the variability of O3 well, but underpredicted peak ozone during high O3 episodes. In post-campaign WRF-Chem simulations, we investigated the sensitivity of the model to the hydrocarbon emission.
Liao, Ruohua; Chen, Xumei; Yu, Lei; Sun, Xiaofei
2018-01-12
Unknown remaining time of signal phase at a signalized intersection generally results in extra accelerations and decelerations that increase variations of operating conditions and thus emissions. A cooperative vehicle-infrastructure system can reduce unnecessary speed changes by establishing communications between vehicles and the signal infrastructure. However, the environmental benefits largely depend on drivers' compliance behaviors. To quantify the effects of drivers' compliance rates on emissions, this study applied VISSIM 5.20 (Planung Transport Verkehr AG, Karlsruhe, Germany) to develop a simulation model for a signalized intersection, in which light duty vehicles were equipped with a cooperative vehicle-infrastructure system. A vehicle-specific power (VSP)-based model was used to estimate emissions. Based on simulation data, the effects of different compliance rates on VSP distributions, emission factors, and total emissions were analyzed. The results show the higher compliance rate decreases the proportion of VSP bin = 0, which means that the frequencies of braking and idling were lower and light duty vehicles ran more smoothly at the intersection if more light duty vehicles complied with the cooperative vehicle-infrastructure system, and emission factors for light duty vehicles decreased significantly as the compliance rate increased. The case study shows higher total emission reductions were observed with higher compliance rate for all of CO₂, NO x , HC, and CO emissions. CO₂ was reduced most significantly, decreased by 16% and 22% with compliance rates of 0.3 and 0.7, respectively.
Liao, Ruohua; Yu, Lei; Sun, Xiaofei
2018-01-01
Unknown remaining time of signal phase at a signalized intersection generally results in extra accelerations and decelerations that increase variations of operating conditions and thus emissions. A cooperative vehicle-infrastructure system can reduce unnecessary speed changes by establishing communications between vehicles and the signal infrastructure. However, the environmental benefits largely depend on drivers’ compliance behaviors. To quantify the effects of drivers’ compliance rates on emissions, this study applied VISSIM 5.20 (Planung Transport Verkehr AG, Karlsruhe, Germany) to develop a simulation model for a signalized intersection, in which light duty vehicles were equipped with a cooperative vehicle-infrastructure system. A vehicle-specific power (VSP)-based model was used to estimate emissions. Based on simulation data, the effects of different compliance rates on VSP distributions, emission factors, and total emissions were analyzed. The results show the higher compliance rate decreases the proportion of VSP bin = 0, which means that the frequencies of braking and idling were lower and light duty vehicles ran more smoothly at the intersection if more light duty vehicles complied with the cooperative vehicle-infrastructure system, and emission factors for light duty vehicles decreased significantly as the compliance rate increased. The case study shows higher total emission reductions were observed with higher compliance rate for all of CO2, NOx, HC, and CO emissions. CO2 was reduced most significantly, decreased by 16% and 22% with compliance rates of 0.3 and 0.7, respectively. PMID:29329214
Ziu, Xiao Xia; Zhang, Xiao Jun; Wang, Yue Fu; Wang, Ming Lun
2018-03-01
Clarifying the carbon emissions in wheat-summer direct-seeding peanut planting (W-P) system could help realize the synergistic effects of high yield and low carbon emissions. Based on whole life cycle method, we constructed a carbon footprint model to calculate the carbon emissions of W-P system. We found that the net income of W-P system was 71.2%-88.3% higher than that of wheat-maize rotation (W-M) system. The carbon emissions per unit area under W-P system was 6977.9-8018.5 kg·hm -2 , being 6.2% higher than that of W-M system. The carbon emission of per net income under W-P system was 0.23-0.28 kg CO 2 -eq·yuan -1 , which was 37.4%-44.1% lower than that of W-M system. Combining the net income and carbon emissions of per net income, W-P system could achieve synergistic effects of high yield and low carbon emissions, which would fulfill the targets of agricultural supply-side structural reform with optimizing supply, enhancing quality and efficiency, and increasing income of peasants.
NASA Astrophysics Data System (ADS)
Brandt, Jørgen; Silver, Jeremy David; Heile Christensen, Jesper; Skou Andersen, Mikael; Geels, Camilla; Gross, Allan; Buus Hansen, Ayoe; Mantzius Hansen, Kaj; Brandt Hedegaard, Gitte; Ambelas Skjøth, Carsten
2010-05-01
Air pollution has significant negative impacts on human health and well-being, which entail substantial economic consequences. We have developed an integrated model system, EVA (External Valuation of Air pollution), to assess health-related economic externalities of air pollution resulting from specific emission sources/sectors. The EVA system was initially developed to assess externalities from power production, but in this study it is extended to evaluate costs at the national level. The EVA system integrates a regional-scale atmospheric chemistry transport model (DEHM), address-level population data, exposure-response functions and monetary values applicable for Danish/European conditions. Traditionally, systems that assess economic costs of health impacts from air pollution assume linear approximations in the source-receptor relationships. However, atmospheric chemistry is non-linear and therefore the uncertainty involved in the linear assumption can be large. The EVA system has been developed to take into account the non-linear processes by using a comprehensive, state-of-the-art chemical transport model when calculating how specific changes to emissions affect air pollution levels and the subsequent impacts on human health and cost. Furthermore, we present a new "tagging" method, developed to examine how specific emission sources influence air pollution levels without assuming linearity of the non-linear behaviour of atmospheric chemistry. This method is more precise than the traditional approach based on taking the difference between two concentration fields. Using the EVA system, we have estimated the total external costs from the main emission sectors in Denmark, representing the ten major SNAP codes. Finally, we assess the impacts and external costs of emissions from international ship traffic around Denmark, since there is a high volume of ship traffic in the region.
Modelling the multiwavelength emission of Ultraluminous X-ray sources accreting above Eddington
NASA Astrophysics Data System (ADS)
Ambrosi, E.; Zampieri, L.
2017-10-01
Understanding ULXs requires a comprehensive modelling of their multiwavelength emission properties. We compute the optical-through-X-ray emission of ULXs assuming that they are binary systems with stellar-mass or massive-stellar Black Holes and considering the possibility that a non-standard disc sets in when the mass transfer rate (\\dot{M}) becomes highly super-Eddington. The emission model is applied to self-consistent simulations of ULX binaries. We compare our color-magnitude diagrams (CMDs) with those in the literature and find significant differences in the post main sequence evolution. When the donor is on the main-sequence and \\dot{M} is mildly super-Eddington, the behaviour of the system is similar to that found in previous investigations. However, when the donor star leaves the main-sequence and \\dot{M} becomes highly super-Eddington, the optical luminosity of the system is systematically larger and the colours show a markedly different evolution. The emission properties depend on the variable shielding of the outer disc and donor induced by the changing inner disc structure. We determine also the effects caused by the onset of a strong optically thick outflow. CMDs in various photometric systems are compared to the observed properties of the optical counterparts of several ULXs, obtaining updated constraints on their donor mass and accretion rate.
NASA Astrophysics Data System (ADS)
Arellano, A. F., Jr.; Tang, W.
2017-12-01
Assimilating observational data of chemical constituents into a modeling system is a powerful approach in assessing changes in atmospheric composition and estimating associated emissions. However, the results of such chemical data assimilation (DA) experiments are largely subject to various key factors such as: a) a priori information, b) error specification and representation, and c) structural biases in the modeling system. Here we investigate the sensitivity of an ensemble-based data assimilation state and emission estimates to these key factors. We focus on investigating the assimilation performance of the Community Earth System Model (CESM)/CAM-Chem with the Data Assimilation Research Testbed (DART) in representing biomass burning plumes in the Amazonia during the 2008 fire season. We conduct the following ensemble DA MOPITT CO experiments: 1) use of monthly-average NCAR's FINN surface fire emissionss, 2) use of daily FINN surface fire emissions, 3) use of daily FINN emissions with climatological injection heights, and 4) use of perturbed FINN emission parameters to represent not only the uncertainties in combustion activity but also in combustion efficiency. We show key diagnostics of assimilation performance for these experiments and verify with available ground-based and aircraft-based measurements.
Code of Federal Regulations, 2014 CFR
2014-07-01
... Continuous Emission Monitoring Systems (CEMS) 6 Table 6 to Subpart BBBB of Part 60 Protection of Environment... or Before August 30, 1999 Pt. 60, Subpt. BBBB, Table 6 Table 6 to Subpart BBBB of Part 60—Model Rule... levels Use the following methods in appendix A of this part to measure oxygen (or carbon dioxide) 1...
Code of Federal Regulations, 2012 CFR
2012-07-01
... Continuous Emission Monitoring Systems (CEMS) 6 Table 6 to Subpart BBBB of Part 60 Protection of Environment... or Before August 30, 1999 Pt. 60, Subpt. BBBB, Table 6 Table 6 to Subpart BBBB of Part 60—Model Rule... levels Use the following methods in appendix A of this part to measure oxygen (or carbon dioxide) 1...
NASA Astrophysics Data System (ADS)
Wang, Lina; Jayaratne, Rohan; Heuff, Darlene; Morawska, Lidia
A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.
Constraining CO emission estimates using atmospheric observations
NASA Astrophysics Data System (ADS)
Hooghiemstra, P. B.
2012-06-01
We apply a four-dimensional variational (4D-Var) data assimilation system to optimize carbon monoxide (CO) emissions and to reduce the uncertainty of emission estimates from individual sources using the chemistry transport model TM5. In the first study only a limited amount of surface network observations from the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA/ESRL) Global Monitoring Division (GMD) is used to test the 4D-Var system. Uncertainty reduction up to 60% in yearly emissions is observed over well-constrained regions and the inferred emissions compare well with recent studies for 2004. However, since the observations only constrain total CO emissions, the 4D-Var system has difficulties separating anthropogenic and biogenic sources in particular. The inferred emissions are validated with NOAA aircraft data over North America and the agreement is significantly improved from the prior to posterior simulation. Validation with the Measurements Of Pollution In The Troposphere (MOPITT) instrument shows a slight improved agreement over the well-constrained Northern Hemisphere and in the tropics (except for the African continent). However, the model simulation with posterior emissions underestimates MOPITT CO total columns on the remote Southern Hemisphere (SH) by about 10%. This is caused by a reduction in SH CO sources mainly due to surface stations on the high southern latitudes. In the second study, we compare two global inversions to estimate carbon monoxide (CO) emissions for 2004. Either surface flask observations from NOAA or CO total columns from the MOPITT instrument are assimilated in a 4D-Var framework. In the Southern Hemisphere (SH) three important findings are reported. First, due to their different vertical sensitivity, the stations-only inversion increases SH biomass burning emissions by 108 Tg CO/yr more than the MOPITT-only inversion. Conversely, the MOPITT-only inversion results in SH natural emissions (mainly CO from oxidation of NMVOCs) that are 185 Tg CO/yr higher compared to the stations-only inversion. Second, MOPITT-only derived biomass burning emissions are reduced with respect to the prior which is in contrast to previous (inverse) modeling studies. Finally, MOPITT derived total emissions are significantly higher for South America and Africa compared to the stations-only inversion. This is likely due to a positive bias in the MOPITT V4 product. This bias is also apparent from validation with surface stations and ground-truth FTIR columns. In the final study we present the first inverse modeling study to estimate CO emissions constrained by both surface (NOAA) and satellite (MOPITT) observations using a bias correction scheme. This approach leads to the identification of a positive bias of maximum 5 ppb in MOPITT column-averaged CO mixing ratios in the remote Southern Hemisphere (SH). The 4D-Var system is used to estimate CO emissions over South America in the period 2006-2010 and to analyze the interannual variability (IAV) of these emissions. We infer robust, high spatial resolution CO emission estimates that show slightly smaller IAV due to fires compared to the Global Fire Emissions Database (GFED3) prior emissions. Moreover, CO emissions probably associated with pre-harvest burning of sugar cane plantations are underestimated in current inventories by 50-100%.
Real-time emissions from construction equipment compared with model predictions.
Heidari, Bardia; Marr, Linsey C
2015-02-01
The construction industry is a large source of greenhouse gases and other air pollutants. Measuring and monitoring real-time emissions will provide practitioners with information to assess environmental impacts and improve the sustainability of construction. We employed a portable emission measurement system (PEMS) for real-time measurement of carbon dioxide (CO), nitrogen oxides (NOx), hydrocarbon, and carbon monoxide (CO) emissions from construction equipment to derive emission rates (mass of pollutant emitted per unit time) and emission factors (mass of pollutant emitted per unit volume of fuel consumed) under real-world operating conditions. Measurements were compared with emissions predicted by methodologies used in three models: NONROAD2008, OFFROAD2011, and a modal statistical model. Measured emission rates agreed with model predictions for some pieces of equipment but were up to 100 times lower for others. Much of the difference was driven by lower fuel consumption rates than predicted. Emission factors during idling and hauling were significantly different from each other and from those of other moving activities, such as digging and dumping. It appears that operating conditions introduce considerable variability in emission factors. Results of this research will aid researchers and practitioners in improving current emission estimation techniques, frameworks, and databases.
NASA Astrophysics Data System (ADS)
Pehl, Michaja; Arvesen, Anders; Humpenöder, Florian; Popp, Alexander; Hertwich, Edgar G.; Luderer, Gunnar
2017-12-01
Both fossil-fuel and non-fossil-fuel power technologies induce life-cycle greenhouse gas emissions, mainly due to their embodied energy requirements for construction and operation, and upstream CH4 emissions. Here, we integrate prospective life-cycle assessment with global integrated energy-economy-land-use-climate modelling to explore life-cycle emissions of future low-carbon power supply systems and implications for technology choice. Future per-unit life-cycle emissions differ substantially across technologies. For a climate protection scenario, we project life-cycle emissions from fossil fuel carbon capture and sequestration plants of 78-110 gCO2eq kWh-1, compared with 3.5-12 gCO2eq kWh-1 for nuclear, wind and solar power for 2050. Life-cycle emissions from hydropower and bioenergy are substantial (˜100 gCO2eq kWh-1), but highly uncertain. We find that cumulative emissions attributable to upscaling low-carbon power other than hydropower are small compared with direct sectoral fossil fuel emissions and the total carbon budget. Fully considering life-cycle greenhouse gas emissions has only modest effects on the scale and structure of power production in cost-optimal mitigation scenarios.
Air Quality Modeling Using the NASA GEOS-5 Multispecies Data Assimilation System
NASA Technical Reports Server (NTRS)
Keller, Christoph A.; Pawson, Steven; Wargan, Krzysztof; Weir, Brad
2018-01-01
The NASA Goddard Earth Observing System (GEOS) data assimilation system (DAS) has been expanded to include chemically reactive tropospheric trace gases including ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). This system combines model analyses from the GEOS-5 model with detailed atmospheric chemistry and observations from MLS (O3), OMI (O3 and NO2), and MOPITT (CO). We show results from a variety of assimilation test experiments, highlighting the improvements in the representation of model species concentrations by up to 50% compared to an assimilation-free control experiment. Taking into account the rapid chemical cycling of NO2 when applying the assimilation increments greatly improves assimilation skills for NO2 and provides large benefits for model concentrations near the surface. Analysis of the geospatial distribution of the assimilation increments suggest that the free-running model overestimates biomass burning emissions but underestimates lightning NOx emissions by 5-20%. We discuss the capability of the chemical data assimilation system to improve atmospheric composition forecasts through improved initial value and boundary condition inputs, particularly during air pollution events. We find that the current assimilation system meaningfully improves short-term forecasts (1-3 day). For longer-term forecasts more emphasis on updating the emissions instead of initial concentration fields is needed.
Oates, Lawrence G.; Duncan, David S.; Gelfand, Ilya; ...
2015-05-14
Greenhouse gas (GHG) emissions from soils are a key sustainability metric of cropping systems. During crop establishment, disruptive land-use change is known to be a critical, but under reported period, for determining GHG emissions. We measured soil N 2O emissions and potential environmental drivers of these fluxes from a three-year establishment-phase bioenergy cropping systems experiment replicated in southcentral Wisconsin (ARL) and southwestern Michigan (KBS). Cropping systems treatments were annual monocultures (continuous corn, corn–soybean–canola rotation), perennial monocultures (switchgrass, miscanthus, and poplar), and perennial polycultures (native grass mixture, early successional community, and restored prairie) all grown using best management practices specific tomore » the system. Cumulative three-year N 2O emissions from annuals were 142% higher than from perennials, with fertilized perennials 190% higher than unfertilized perennials. Emissions ranged from 3.1 to 19.1 kg N 2O-N ha -1 yr -1 for the annuals with continuous corn > corn–soybean–canola rotation and 1.1 to 6.3 kg N 2O-N ha -1 yr -1 for perennials. Nitrous oxide peak fluxes typically were associated with precipitation events that closely followed fertilization. Bayesian modeling of N 2O fluxes based on measured environmental factors explained 33% of variability across all systems. Models trained on single systems performed well in most monocultures (e.g., R 2 = 0.52 for poplar) but notably worse in polycultures (e.g., R 2 = 0.17 for early successional, R 2 = 0.06 for restored prairie), indicating that simulation models that include N 2O emissions should be parameterized specific to particular plant communities. These results indicate that perennial bioenergy crops in their establishment phase emit less N 2O than annual crops, especially when not fertilized. These findings should be considered further alongside yield and other metrics contributing to important ecosystem services.« less
Atmospheric ammonia (NH3) plays an important role in fine-mode aerosol formation. Accurate estimates of ammonia from both human and natural emissions can reduce uncertainties in air quality modeling. The majority of ammonia anthropogenic emissions come from the agricul...
Methods for Analysis of Urban Energy Systems: A New York City Case Study
NASA Astrophysics Data System (ADS)
Howard, Bianca
This dissertation describes methods developed for analysis of the New York City energy system. The analysis specifically aims to consider the built environment and its' impacts on greenhouse gas (GHG) emissions. Several contributions to the urban energy systems literature were made. First, estimates of annual energy intensities of the New York building stock were derived using a statistical analysis that leveraged energy consumption and tax assessor data collected by the Office of the Mayor. These estimates provided the basis for an assessment of the spatial distribution of building energy consumption. The energy consumption estimates were then leveraged to estimate the potential for combined heat and power (CHP) systems in New York City at both the building and microgrid scales. In aggregate, given the 2009 non-baseload GHG emissions factors for electricity production, these systems could reduce citywide GHG emissions by 10%. The operational characteristics of CHP systems were explored further considering different prime movers, climates, and GHG emissions factors. A combination of mixed integer linear programing and controlled random search algorithms were the methods used to determine the optimal capacity and operating strategies for the CHP systems under the various scenarios. Lastly a multi-regional unit commitment model of electricity and GHG emissions production for New York State was developed using data collected from several publicly available sources. The model was used to estimate average and marginal GHG emissions factors for New York State and New York City. The analysis found that marginal GHG emissions factors could reduce by 30% to 370 g CO2e/kWh in the next 10 years.
Brandt, Adam R
2012-01-17
Because of interest in greenhouse gas (GHG) emissions from transportation fuels production, a number of recent life cycle assessment (LCA) studies have calculated GHG emissions from oil sands extraction, upgrading, and refining pathways. The results from these studies vary considerably. This paper reviews factors affecting energy consumption and GHG emissions from oil sands extraction. It then uses publicly available data to analyze the assumptions made in the LCA models to better understand the causes of variability in emissions estimates. It is found that the variation in oil sands GHG estimates is due to a variety of causes. In approximate order of importance, these are scope of modeling and choice of projects analyzed (e.g., specific projects vs industry averages); differences in assumed energy intensities of extraction and upgrading; differences in the fuel mix assumptions; treatment of secondary noncombustion emissions sources, such as venting, flaring, and fugitive emissions; and treatment of ecological emissions sources, such as land-use change-associated emissions. The GHGenius model is recommended as the LCA model that is most congruent with reported industry average data. GHGenius also has the most comprehensive system boundaries. Last, remaining uncertainties and future research needs are discussed.
Impacts of Climate Change on Forest Isoprene Emission: Diversity Matters
NASA Astrophysics Data System (ADS)
Wang, B.; Shugart, H. H., Jr.; Lerdau, M.
2016-12-01
Many abiotic and biotic factors influence volatile organic compound (VOC) production and emission by plants; for example, climate warming is widely projected to enhance VOC emissions by stimulating their biosynthesis. The species-dependent nature of VOC production by plants indicates that changes in species abundances may play an important role in determining VOC production and emission at the ecosystem scale. To date, however, the role of species abundances in affecting VOC emissions has not been well studied. We examine the role of forest systems as sources of VOC's in terms of how species diversity and abundance influence isoprene emission under climate warming by using an individual-based forest VOC emission model—UVAFME-VOC 1.0—that can explicitly simulate forest compositional and structural change and VOC production/emission at the individual and canopy scales. We simulate isoprene emissions under two warming scenarios (warming by 2 and 4 °C) for temperate deciduous forests of the southeastern United States, where the dominant isoprene-emitting species are oaks (Quercus). The simulations show that, contrary to previous expectations, a warming by 2 °C does not affect isoprene emissions, while a further warming by 4 °C causes a large reduction of isoprene emissions. Interestingly, climate warming can directly enhance isoprene emission and simultaneously indirectly reduce it by lowering the abundance of isoprene-emitting species. Under gradual continuous warming, the indirect effect outweighs the direct effect, thus reducing overall forest isoprene emission. This modelling study shows that climate warming does not necessarily stimulate ecosystem VOC emissions and, more generally, that ecosystem diversity and composition can play a significant role in determining vegetation VOC emission capacity. Future earth system models and climate-chemistry models should better represent species diversity in projecting climate-air quality feedbacks and making management policy recommendations.
Mapping Isoprene Emissions over North America using Formaldehyde Column Observations from Space
NASA Technical Reports Server (NTRS)
Palmer, Paul I.; Jacob, Daniel J.; Fiore, Arlene M.; Martin, Randall V.; Chance, Kelly; Kurosu, Thomas P.
2004-01-01
I] We present a methodology for deriving emissions of volatile organic compounds (VOC) using space-based column observations of formaldehyde (HCHO) and apply it to data from the Global Ozone Monitoring Experiment (GOME) satellite instrument over North America during July 1996. The HCHO column is related to local VOC emissions, with a spatial smearing that increases with the VOC lifetime. lsoprene is the dominant HCHO precursor over North America in summer, and its lifetime (approx. = 1 hour) is sufficiently short that the smearing can be neglected. We use the Goddard Earth Observing System global 3-D model of tropospheric chemistry (GEOS-CHEM) to derive the relationship between isoprene emissions and HCHO columns over North America and use these relationships to convert the GOME HCHO columns to isoprene emissions. We also use the GEOS-CHEM model as an intermediary to validate the GOME HCHO column measurements by comparison with in situ observations. The GEOS-CHEM model including the Global Emissions Inventory Activity (GEIA) isoprene emission inventory provides a good simulation of both the GOME data (r(sup 2) = 0.69, n = 756, bias = +l1 %) and the in situ summertime HCHO measurements over North America (r(sup 2) = 0.47, n = 10, bias = -3%). The GOME observations show high values over regions of known high isoprene emissions and a day-to-day variability that is consistent with the temperature dependence of isoprene emission. Isoprene emissions inferred from the GOME data are 20% less than GEIA on average over North America and twice those from the U S . EPA Biogenic Emissions Inventory System (BEIS2) inventory. The GOME isoprene inventory when implemented in the GEOS-CHEM model provides a better simulation of the HCHO in situ measurements thaneitherGEIAorBEIS2 (r(sup 2) = 0.71,n= 10, bias = -10 %).
NASA Astrophysics Data System (ADS)
Kyle, P.; Müller, C.; Calvin, K. V.; Thomson, A. M.
2013-12-01
The Representative Concentration Pathways (RCPs) have formed the basis for much of the current scientific understanding of future climate change impacts and mitigation. However, the emissions scenarios underlying the RCPs were produced by integrated assessment models that did not include impacts of future climate change on the modeled evolution of the agricultural and energy systems. Given the prominent role of bioenergy in greenhouse gas emissions mitigation, and given the importance of land-use-related emissions in determining future atmospheric CO2 concentrations, it is possible that agricultural climate impacts may cause significant changes to the means and costs of mitigating greenhouse gas emissions. This study builds on several international modeling exercises aimed at improving understanding of climate change impacts--CMIP-5 and ISI-MIP--that have generated global gridded climate impacts on yields of major agricultural crops in each of the four RCPs. We use the climate outcomes from the HadGEM2-ES climate model, and the agricultural yield outcomes from the LPJmL crop growth model to inform inputs to the GCAM integrated assessment model, allowing analysis of how agricultural climate impacts may affect the long-term global and regional strategies for achieving the greenhouse gas concentration pathways of the RCPs. Our results indicate that for this combination of models and emissions scenarios, strongly negative climate impacts on several major commodity classes--prominently cereals and oil seeds, and particularly in the high-radiative-forcing RCPs--lead to a long-term increase in cropland and therefore land-use-related CO2 emissions. All else equal, this increases the emissions mitigation burden on the rest of the system, and therefore increases total net costs of emissions mitigation. However, the future climate change impacts on C4 bioenergy crops tend to be positive, limiting the shock of agricultural climate impacts on the modeled energy supply and demand systems. As well, endogenous adaptation in the agricultural sector--mostly through inter-regional shifting in production and changes in trade patterns--limits the shock of climate impacts to consumers. Global average climate impacts on wheat yields for the four emissions scenarios, using base-year weights (asterisks) and using the endogenous land allocations in GCAM (filled diamonds)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nguyen, Khai; Bogdanović, Tamara
Motivated by advances in observational searches for sub-parsec supermassive black hole binaries (SBHBs) made in the past few years, we develop a semi-analytic model to describe spectral emission-line signatures of these systems. The goal of this study is to aid the interpretation of spectroscopic searches for binaries and to help test one of the leading models of binary accretion flows in the literature: SBHB in a circumbinary disk. In this work, we present the methodology and a comparison of the preliminary model with the data. We model SBHB accretion flows as a set of three accretion disks: two mini-disks thatmore » are gravitationally bound to the individual black holes and a circumbinary disk. Given a physically motivated parameter space occupied by sub-parsec SBHBs, we calculate a synthetic database of nearly 15 million broad optical emission-line profiles and explore the dependence of the profile shapes on characteristic properties of SBHBs. We find that the modeled profiles show distinct statistical properties as a function of the semimajor axis, mass ratio, eccentricity of the binary, and the degree of alignment of the triple disk system. This suggests that the broad emission-line profiles from SBHB systems can in principle be used to infer the distribution of these parameters and as such merit further investigation. Calculated profiles are more morphologically heterogeneous than the broad emission lines in observed SBHB candidates and we discuss improved treatment of radiative transfer effects, which will allow a direct statistical comparison of the two groups.« less
Hristov, A N; Kebreab, E; Niu, M; Oh, J; Bannink, A; Bayat, A R; Boland, T B; Brito, A F; Casper, D P; Crompton, L A; Dijkstra, J; Eugène, M; Garnsworthy, P C; Haque, N; Hellwing, A L F; Huhtanen, P; Kreuzer, M; Kuhla, B; Lund, P; Madsen, J; Martin, C; Moate, P J; Muetzel, S; Muñoz, C; Peiren, N; Powell, J M; Reynolds, C K; Schwarm, A; Shingfield, K J; Storlien, T M; Weisbjerg, M R; Yáñez-Ruiz, D R; Yu, Z
2018-04-18
Ruminant production systems are important contributors to anthropogenic methane (CH 4 ) emissions, but there are large uncertainties in national and global livestock CH 4 inventories. Sources of uncertainty in enteric CH 4 emissions include animal inventories, feed dry matter intake (DMI), ingredient and chemical composition of the diets, and CH 4 emission factors. There is also significant uncertainty associated with enteric CH 4 measurements. The most widely used techniques are respiration chambers, the sulfur hexafluoride (SF 6 ) tracer technique, and the automated head-chamber system (GreenFeed; C-Lock Inc., Rapid City, SD). All 3 methods have been successfully used in a large number of experiments with dairy or beef cattle in various environmental conditions, although studies that compare techniques have reported inconsistent results. Although different types of models have been developed to predict enteric CH 4 emissions, relatively simple empirical (statistical) models have been commonly used for inventory purposes because of their broad applicability and ease of use compared with more detailed empirical and process-based mechanistic models. However, extant empirical models used to predict enteric CH 4 emissions suffer from narrow spatial focus, limited observations, and limitations of the statistical technique used. Therefore, prediction models must be developed from robust data sets that can only be generated through collaboration of scientists across the world. To achieve high prediction accuracy, these data sets should encompass a wide range of diets and production systems within regions and globally. Overall, enteric CH 4 prediction models are based on various animal or feed characteristic inputs but are dominated by DMI in one form or another. As a result, accurate prediction of DMI is essential for accurate prediction of livestock CH 4 emissions. Analysis of a large data set of individual dairy cattle data showed that simplified enteric CH 4 prediction models based on DMI alone or DMI and limited feed- or animal-related inputs can predict average CH 4 emission with a similar accuracy to more complex empirical models. These simplified models can be reliably used for emission inventory purposes. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
NASA Astrophysics Data System (ADS)
Werner, C.; Kraus, D.; Mai, T. V.; Butterbach-Bahl, K.
2016-12-01
Agriculture is the economic backbone for over two thirds of Vietnam's population, providing food security, employment and income. However, agriculture in Vietnam is challenged by climate change and climate extremes and at the same time, agriculture remains a key source of greenhouse gas (GHG) emissions. The first bi-annual update report (BUR1), published in 2014 indicated that while the proportion of GHG emissions from agriculture had fallen from 43.1% to 33.2% from 2000 to 2010, the emission total increased from 65.1 mio to 88.4 mio t CO2e. Reducing GHG emissions from agriculture has thus become a key issue within the national strategy of GHG emission management. Here we present first data using IPCC Tier 3 modeling for quantifying the source strength of rice based crop systems for CH4 and N2O. We used LandscapeDNDC and linked it to a newly developed spatial landuse and land management database (climate, soil properties, and detailed field management data). Site application showed good agreement of simulated biomass, yield and GHG emissions with field observations, providing confidence for model use at national scale. Our results also show good agreement with national yield data and total annual emissions of the simulated period (2006-2015) ranged from 1060 - 1502 kt CH4 and 6.2 - 7.7 kt N2O, respectively. The dominating emission hotspot for CH4 is the Mekong Delta region with its double and triple rice cropping systems (819 kt CH4/yr, Fig. 1). With regard to N2O, emission hotspots have been identified to be closely related to regions with high fertilizer use and single to double rice cropping systems (Fig. 1). Though, our emission estimates are likely representing the best of current knowledge on national GHG emissions from rice based systems in Vietnam, the uncertainty is significant as information on rice system management remains vague. Sensitivity studies show that changes in field management affecting the soil organic carbon dynamics (duration of flooding, stubble amounts and fraction tilled or manure application) can lead to substantial differences in emission rates. In a next step we plan to explore mitigation options such as Alternative Wetting and Drying for reducing national GHG emissions from the agricultural sector and to identify regions which are most suitable and most promising in terms of GHG reduction.
NASA Astrophysics Data System (ADS)
Cao, Y.; Barkley, Z.; Cervone, G.; Lauvaux, T.; Deng, A.; Sarmiento, D. P.
2015-12-01
Natural gas production from multiple shale formations has increased significantly in the last decade. More particularly, a growing number of unconventional wells is the result of intense drilling in the Marcellus shale area. The Marcellus shale production represents a third of the production of natural gas in the entire US. This unprecedented increase could lead to additional fugitive methane (CH4) emissions at a level that remains highly uncertain. If natural gas is to replace less energy-efficient fossil fuels, the emissions during the production phase ought to be relatively small. However, the magnitude and the spatial distribution of CH4 emissions from unconventional wells in the Marcellus shale remains poorly documented. The novelty of this research consists in coupling various sources of information to map accurately the methane emissions, combining Geographical Information System (GIS) data, atmospheric measurements of greenhouse gases, and atmospheric modeling tools. We first collected various GIS data to estimate CH4 emissions caused by the shale gas industry, such as wells, facilities, and pipelines, with the other major contributors such as wetlands, farming activities, and soils. We present our projection methods to generate model input in gridded format while preserving the distribution and magnitude of the emissions and assembling a diverse database. The projection tools for GIS data are generalized to the use of GIS data in atmospheric modeling systems. We then present the atmospheric concentrations simulated by the Weather Research and Forecast (WRF) model, used to represent the transport and the dispersion of CH4 emissions. We compare the WRF model results to aircraft measurements collected during a 3-week campaign to identify missing sources in our initial inventory. We finally propose a new approach to identify the area at the surface that could potentially influence the aircraft measurements using spatial analysis of particle footprints. This technique aims at identifying undocumented sources and unreported large emitters to quantify more rigorously the emissions of CH4 over the Marcellus shale.
Energy consumption and CO{sub 2} emissions in Iran, 2025
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mirzaei, Maryam
Climate change and global warming as the key human societies' threats are essentially associated with energy consumption and CO{sub 2} emissions. A system dynamic model was developed in this study to model the energy consumption and CO{sub 2} emission trends for Iran over 2000–2025. Energy policy factors are considered in analyzing the impact of different energy consumption factors on environmental quality. The simulation results show that the total energy consumption is predicted to reach 2150 by 2025, while that value in 2010 is 1910, which increased by 4.3% yearly. Accordingly, the total CO{sub 2} emissions in 2025 will reach 985more » million tonnes, which shows about 5% increase yearly. Furthermore, we constructed policy scenarios based on energy intensity reduction. The analysis show that CO{sub 2} emissions will decrease by 12.14% in 2025 compared to 2010 in the scenario of 5% energy intensity reduction, and 17.8% in the 10% energy intensity reduction scenario. The results obtained in this study provide substantial awareness regarding Irans future energy and CO{sub 2} emission outlines. - Highlights: • Creation of an energy consumption model using system dynamics. • The effect of different policies on energy consumption and emission reductions. • An ascending trend for the environmental costs caused by CO{sub 2} emissions is observed. • An urgent need for energy saving and emission reductions in Iran.« less
Emissions model of waste treatment operations at the Idaho Chemical Processing Plant
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schindler, R.E.
1995-03-01
An integrated model of the waste treatment systems at the Idaho Chemical Processing Plant (ICPP) was developed using a commercially-available process simulation software (ASPEN Plus) to calculate atmospheric emissions of hazardous chemicals for use in an application for an environmental permit to operate (PTO). The processes covered by the model are the Process Equipment Waste evaporator, High Level Liquid Waste evaporator, New Waste Calcining Facility and Liquid Effluent Treatment and Disposal facility. The processes are described along with the model and its assumptions. The model calculates emissions of NO{sub x}, CO, volatile acids, hazardous metals, and organic chemicals. Some calculatedmore » relative emissions are summarized and insights on building simulations are discussed.« less
40 CFR 60.3038 - What continuous emission monitoring systems must I install?
Code of Federal Regulations, 2012 CFR
2012-07-01
... systems must I install? 60.3038 Section 60.3038 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... December 9, 2004 Model Rule-Monitoring § 60.3038 What continuous emission monitoring systems must I install... carbon monoxide and for oxygen. You must monitor the oxygen concentration at each location where you...
40 CFR 60.3038 - What continuous emission monitoring systems must I install?
Code of Federal Regulations, 2014 CFR
2014-07-01
... systems must I install? 60.3038 Section 60.3038 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... December 9, 2004 Model Rule-Monitoring § 60.3038 What continuous emission monitoring systems must I install... carbon monoxide and for oxygen. You must monitor the oxygen concentration at each location where you...
40 CFR 60.3038 - What continuous emission monitoring systems must I install?
Code of Federal Regulations, 2013 CFR
2013-07-01
... systems must I install? 60.3038 Section 60.3038 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... December 9, 2004 Model Rule-Monitoring § 60.3038 What continuous emission monitoring systems must I install... carbon monoxide and for oxygen. You must monitor the oxygen concentration at each location where you...
40 CFR 1037.550 - Special procedures for testing hybrid systems.
Code of Federal Regulations, 2014 CFR
2014-07-01
... simulating a chassis test with a pre-transmission or post-transmission hybrid system for A to B testing...) AIR POLLUTION CONTROLS CONTROL OF EMISSIONS FROM NEW HEAVY-DUTY MOTOR VEHICLES Test and Modeling...) Collect CO2 emissions while operating the system over the test cycles specified in § 1037.510. (c) Collect...
NASA Astrophysics Data System (ADS)
Laurent, B.; Heinold, B.; Tegen, I.; Bouet, C.; Cautenet, G.
2008-05-01
After a decade of research on improving the description of surface and soil features in desert regions to accurately model mineral dust emissions, we now emphasize the need for deeper evaluating the accuracy of modeled 10-m surface wind speeds U 10 . Two mesoscale models, the Lokal-Modell (LM) and the Regional Atmospheric Modeling System (RAMS), coupled with an explicit dust emission model have previously been used to simulate mineral dust events in the Bodélé region. We compare LM and RAMS U 10 , together with measurements at the Chicha site (BoDEx campaign) and Faya-Largeau meteorological station. Surface features and soil schemes are investigated to correctly simulate U 10 intensity and diurnal variability. The uncertainties in dust emissions computed with LM and RAMS U 10 and different soil databases are estimated. This sensitivity study shows the importance of accurate computation of surface winds to improve the quantification of regional dust emissions from the Bodélé
Kou, Weibin; Chen, Xumei; Yu, Lei; Gong, Huibo
2018-04-18
Most existing signal timing models are aimed to minimize the total delay and stops at intersections, without considering environmental factors. This paper analyzes the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. First, considering the different operating modes of cruising, acceleration, deceleration, and idling, field data of emissions and Global Positioning System (GPS) are collected to estimate emission rates for heavy-duty and light-duty vehicles. Second, multiobjective signal timing optimization model is established based on a genetic algorithm to minimize delay, stops, and emissions. Finally, a case study is conducted in Beijing. Nine scenarios are designed considering different weights of emission and traffic efficiency. The results compared with those using Highway Capacity Manual (HCM) 2010 show that signal timing optimized by the model proposed in this paper can decrease vehicles delay and emissions more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development. Vehicle emissions are heavily at signal intersections in urban area. The multiobjective signal timing optimization model is proposed considering the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. The results indicate that signal timing optimized by the model proposed in this paper can decrease vehicle emissions and delays more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development.
Efstathiou, Christos; Isukapalli, Sastry
2011-01-01
Allergic airway diseases represent a complex health problem which can be exacerbated by the synergistic action of pollen particles and air pollutants such as ozone. Understanding human exposures to aeroallergens requires accurate estimates of the spatial distribution of airborne pollen levels as well as of various air pollutants at different times. However, currently there are no established methods for estimating allergenic pollen emissions and concentrations over large geographic areas such as the United States. A mechanistic modeling system for describing pollen emissions and transport over extensive domains has been developed by adapting components of existing regional scale air quality models and vegetation databases. First, components of the Biogenic Emissions Inventory System (BEIS) were adapted to predict pollen emission patterns. Subsequently, the transport module of the Community Multiscale Air Quality (CMAQ) modeling system was modified to incorporate description of pollen transport. The combined model, CMAQ-pollen, allows for simultaneous prediction of multiple air pollutants and pollen levels in a single model simulation, and uses consistent assumptions related to the transport of multiple chemicals and pollen species. Application case studies for evaluating the combined modeling system included the simulation of birch and ragweed pollen levels for the year 2002, during their corresponding peak pollination periods (April for birch and September for ragweed). The model simulations were driven by previously evaluated meteorological model outputs and emissions inventories for the eastern United States for the simulation period. A semi-quantitative evaluation of CMAQ-pollen was performed using tree and ragweed pollen counts in Newark, NJ for the same time periods. The peak birch pollen concentrations were predicted to occur within two days of the peak measurements, while the temporal patterns closely followed the measured profiles of overall tree pollen. For the case of ragweed pollen, the model was able to capture the patterns observed during September 2002, but did not predict an early peak; this can be associated with a wider species pollination window and inadequate spatial information in current land cover databases. An additional sensitivity simulation was performed to comparatively evaluate the dispersion patterns predicted by CMAQ-pollen with those predicted by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, which is used extensively in aerobiological studies. The CMAQ estimated concentration plumes matched the equivalent pollen scenario modeled with HYSPLIT. The novel pollen modeling approach presented here allows simultaneous estimation of multiple airborne allergens and other air pollutants, and is being developed as a central component of an integrated population exposure modeling system, the Modeling Environment for Total Risk studies (MENTOR) for multiple, co-occurring contaminants that include aeroallergens and irritants. PMID:21516207
NASA Astrophysics Data System (ADS)
Efstathiou, Christos; Isukapalli, Sastry; Georgopoulos, Panos
2011-04-01
Allergic airway diseases represent a complex health problem which can be exacerbated by the synergistic action of pollen particles and air pollutants such as ozone. Understanding human exposures to aeroallergens requires accurate estimates of the spatial distribution of airborne pollen levels as well as of various air pollutants at different times. However, currently there are no established methods for estimating allergenic pollen emissions and concentrations over large geographic areas such as the United States. A mechanistic modeling system for describing pollen emissions and transport over extensive domains has been developed by adapting components of existing regional scale air quality models and vegetation databases. First, components of the Biogenic Emissions Inventory System (BEIS) were adapted to predict pollen emission patterns. Subsequently, the transport module of the Community Multiscale Air Quality (CMAQ) modeling system was modified to incorporate description of pollen transport. The combined model, CMAQ-pollen, allows for simultaneous prediction of multiple air pollutants and pollen levels in a single model simulation, and uses consistent assumptions related to the transport of multiple chemicals and pollen species. Application case studies for evaluating the combined modeling system included the simulation of birch and ragweed pollen levels for the year 2002, during their corresponding peak pollination periods (April for birch and September for ragweed). The model simulations were driven by previously evaluated meteorological model outputs and emissions inventories for the eastern United States for the simulation period. A semi-quantitative evaluation of CMAQ-pollen was performed using tree and ragweed pollen counts in Newark, NJ for the same time periods. The peak birch pollen concentrations were predicted to occur within two days of the peak measurements, while the temporal patterns closely followed the measured profiles of overall tree pollen. For the case of ragweed pollen, the model was able to capture the patterns observed during September 2002, but did not predict an early peak; this can be associated with a wider species pollination window and inadequate spatial information in current land cover databases. An additional sensitivity simulation was performed to comparatively evaluate the dispersion patterns predicted by CMAQ-pollen with those predicted by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, which is used extensively in aerobiological studies. The CMAQ estimated concentration plumes matched the equivalent pollen scenario modeled with HYSPLIT. The novel pollen modeling approach presented here allows simultaneous estimation of multiple airborne allergens and other air pollutants, and is being developed as a central component of an integrated population exposure modeling system, the Modeling Environment for Total Risk studies (MENTOR) for multiple, co-occurring contaminants that include aeroallergens and irritants.
Fundamental mass transfer modeling of emission of volatile organic compounds from building materials
NASA Astrophysics Data System (ADS)
Bodalal, Awad Saad
In this study, a mass transfer theory based model is presented for characterizing the VOC emissions from building materials. A 3-D diffusion model is developed to describe the emissions of volatile organic compounds (VOCs) from individual sources. Then the formulation is extended to include the emissions from composite sources (system comprising an assemblage of individual sources). The key parameters for the model (The diffusion coefficient of the VOC in the source material D, and the equilibrium partition coefficient k e) were determined independently (model parameters are determined without the use of chamber emission data). This procedure eliminated to a large extent the need for emission testing using environmental chambers, which is costly, time consuming, and may be subject to confounding sink effects. An experimental method is developed and implemented to measure directly the internal diffusion (D) and partition coefficients ( ke). The use of the method is illustrated for three types of VOC's: (i) Aliphatic Hydrocarbons, (ii) Aromatic Hydrocarbons and ( iii) Aldehydes, through typical dry building materials (carpet, plywood, particleboard, vinyl floor tile, gypsum board, sub-floor tile and OSB). Then correlations for predicting D and ke based solely on commonly available properties such as molecular weight and vapour pressure were proposed for each product and type of VOC. These correlations can be used to estimate the D and ke when direct measurement data are not available, and thus facilitate the prediction of VOC emissions from the building materials using mass transfer theory. The VOC emissions from a sub-floor material (made of the recycled automobile tires), and a particleboard are measured and predicted. Finally, a mathematical model to predict the diffusion coefficient through complex sources (floor adhesive) as a function of time was developed. Then this model (for diffusion coefficient in complex sources) was used to predict the emission rate from material system (namely, substrate//glue//vinyl tile).
Kuhns, Hampden; Knipping, Eladio M; Vukovich, Jeffrey M
2005-05-01
The Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study was commissioned to investigate the sources of haze at Big Bend National Park in southwest Texas. The modeling domain of the BRAVO Study includes most of the continental United States and Mexico. The BRAVO emissions inventory was constructed from the 1999 National Emission Inventory for the United States, modified to include finer-resolution data for Texas and 13 U.S. states in close proximity. The first regional-scale Mexican emissions inventory designed for air-quality modeling applications was developed for 10 northern Mexican states, the Tula Industrial Park in the state of Hidalgo, and the Popocatépetl volcano in the state of Puebla. Emissions data were compiled from numerous sources, including the U.S. Environmental Protection Agency (EPA), the Texas Natural Resources Conservation Commission (now Texas Commission on Environmental Quality), the Eastern Research Group, the Minerals Management Service, the Instituto Nacional de Ecología, and the Instituto Nacional de Estadistica Geografía y Informática. The inventory includes emissions for CO, nitrogen oxides, sulfur dioxide, volatile organic compounds (VOCs), ammonia, particulate matter (PM) < 10 microm in aerodynamic diameter, and PM < 2.5 microm in aerodynamic diameter. Wind-blown dust and biomass burning were not included in the inventory, although high concentrations of dust and organic PM attributed to biomass burning have been observed at Big Bend National Park. The SMOKE modeling system was used to generate gridded emissions fields for use with the Regional Modeling System for Aerosols and Deposition (REMSAD) and the Community Multiscale Air Quality model modified with the Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (CMAQ-MADRID). The compilation of the inventory, supporting model input data, and issues encountered during the development of the inventory are documented. A comparison of the BRAVO emissions inventory for Mexico with other emerging Mexican emission inventories illustrates their uncertainty.
Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA.
Integrated Assessment Models (IAMs) characterize the interactions among human and earth systems. IAMs typically have been applied to investigate future energy, land use, and emission pathways at global to continental scales. Recent directions in IAM development include enhanced t...
NASA Astrophysics Data System (ADS)
Civerolo, Kevin; Hogrefe, Christian; Zalewsky, Eric; Hao, Winston; Sistla, Gopal; Lynn, Barry; Rosenzweig, Cynthia; Kinney, Patrick L.
2010-10-01
This paper compares spatial and seasonal variations and temporal trends in modeled and measured concentrations of sulfur and nitrogen compounds in wet and dry deposition over an 18-year period (1988-2005) over a portion of the northeastern United States. Substantial emissions reduction programs occurred over this time period, including Title IV of the Clean Air Act Amendments of 1990 which primarily resulted in large decreases in sulfur dioxide (SO 2) emissions by 1995, and nitrogen oxide (NO x) trading programs which resulted in large decreases in warm season NO x emissions by 2004. Additionally, NO x emissions from mobile sources declined more gradually over this period. The results presented here illustrate the use of both operational and dynamic model evaluation and suggest that the modeling system largely captures the seasonal and long-term changes in sulfur compounds. The modeling system generally captures the long-term trends in nitrogen compounds, but does not reproduce the average seasonal variation or spatial patterns in nitrate.
This site provides access to emissions data, regulations and guidance, electronic system access, resources and tools to support trends analysis, regional, and local scale air quality modeling, regulatory impact assessments.
Road vehicle emission factors development: A review
NASA Astrophysics Data System (ADS)
Franco, Vicente; Kousoulidou, Marina; Muntean, Marilena; Ntziachristos, Leonidas; Hausberger, Stefan; Dilara, Panagiota
2013-05-01
Pollutant emissions need to be accurately estimated to ensure that air quality plans are designed and implemented appropriately. Emission factors (EFs) are empirical functional relations between pollutant emissions and the activity that causes them. In this review article, the techniques used to measure road vehicle emissions are examined in relation to the development of EFs found in emission models used to produce emission inventories. The emission measurement techniques covered include those most widely used for road vehicle emissions data collection, namely chassis and engine dynamometer measurements, remote sensing, road tunnel studies and portable emission measurements systems (PEMS). The main advantages and disadvantages of each method with regards to emissions modelling are presented. A review of the ways in which EFs may be derived from test data is also performed, with a clear distinction between data obtained under controlled conditions (engine and chassis dynamometer measurements using standard driving cycles) and measurements under real-world operation.
Deducing dust emission mechanisms from field measurements
USDA-ARS?s Scientific Manuscript database
Field observations are needed to both develop and test theories on dust emission for use in global modeling systems. The mechanism of dust emission (aerodynamic entrainment, saltation bombardment, aggregate disintegration) and the amount and particle-size distribution of emitted dust may vary under ...
Application for certification for 1979 model year for light-duty vehicles - Audi
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles or heavy-duty engines submits to EPA an application for certification. The application consists of two parts. In the part I, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems and exhaust and evaporative emission control systems. The part I also provides information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements tomore » be followed during testing. The part II application submitted after emission testing is completed, contains the results of emission testing, a statement of compliance to the regulations, and maintenance instructions to be followed by the ultimate owners of the vehicles.« less
Application for certification for 1979 model year for light-duty vehicles - Peugeot
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles or heavy-duty engines submits to EPA an application for certification. The application consists of two parts. In the part I, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems and exhaust and evaporative emission control systems. The part I also provides information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements tomore » be followed during testing. The part II application, submitted after emission testing is completed, contains the results of emission testing, a statement of compliance to the regulations, and maintenance instructions to be followed by the ultimate owners of the vehicles.« less
Modelled and field measurements of biogenic hydrocarbon emissions from a Canadian deciduous forest
NASA Astrophysics Data System (ADS)
Fuentes, J. D.; Wang, D.; Den Hartog, G.; Neumann, H. H.; Dann, T. F.; Puckett, K. J.
The Biogenic Emission Inventory System (BEIS) used by the United States Environmental Protection Agency (Lamb et al., 1993, Atmospheric Environment21, 1695-1705; Pierce and Waldruff, 1991, J. Air Waste Man. Ass.41, 937-941) was tested for its ability to provide realistic microclimate descriptions within a deciduous forest in Canada. The microclimate description within plant canopies is required because isoprene emission rates from plants are strongly influenced by foliage temperature and photosynthetically active radiation impinging on leaves while monoterpene emissions depend primarily on leaf temperature. Model microclimate results combined with plant emission rates and local biomass distribution were used to derive isoprene and α-pinene emissions from the deciduous forest canopy. In addition, modelled isoprene emission estimates were compared to measured emission rates at the leaf level. The current model formulation provides realistic microclimatic conditions for the forest crown where modelled and measured air and foliage temperature are within 3°C. However, the model provides inadequate microclimate characterizations in the lower canopy where estimated and measured foliage temperatures differ by as much as 10°C. This poor agreement may be partly due to improper model characterization of relative humidity and ambient temperature within the canopy. These uncertainties in estimated foliage temperature can lead to underestimates of hydrocarbon emission estimates of two-fold. Moreover, the model overestimates hydrocarbon emissions during the early part of the growing season and underestimates emissions during the middle and latter part of the growing season. These emission uncertainties arise because of the assumed constant biomass distribution of the forest and constant hydrocarbon emission rates throughout the season. The BEIS model, which is presently used in Canada to estimate inventories of hydrocarbon emissions from vegetation, underestimates emission rates by at least two-fold compared to emissions derived from field measurements. The isoprene emission algorithm proposed by Guenther et al. (1993), applied at the leaf level, provides relatively good agreement compared to measurements. Field measurements indicate that isoprene emissions change with leaf ontogeny and differ amongst tree species. Emission rates defined as function of foliage development stage and plant species need to be introduced in the hydrocarbon emission algorithms. Extensive model evaluation and more hydrocarbon emission measurement;: from different plant species are required to fully assess the appropriateness of this emission calculation approach for Canadian forests.
Visual Environment for Rich Data Interpretation (VERDI) program for environmental modeling systems
VERDI is a flexible, modular, Java-based program used for visualizing multivariate gridded meteorology, emissions and air quality modeling data created by environmental modeling systems such as the CMAQ model and WRF.
Downscaling Global Emissions and Its Implications Derived from Climate Model Experiments
Abe, Manabu; Kinoshita, Tsuguki; Hasegawa, Tomoko; Kawase, Hiroaki; Kushida, Kazuhide; Masui, Toshihiko; Oka, Kazutaka; Shiogama, Hideo; Takahashi, Kiyoshi; Tatebe, Hiroaki; Yoshikawa, Minoru
2017-01-01
In climate change research, future scenarios of greenhouse gas and air pollutant emissions generated by integrated assessment models (IAMs) are used in climate models (CMs) and earth system models to analyze future interactions and feedback between human activities and climate. However, the spatial resolutions of IAMs and CMs differ. IAMs usually disaggregate the world into 10–30 aggregated regions, whereas CMs require a grid-based spatial resolution. Therefore, downscaling emissions data from IAMs into a finer scale is necessary to input the emissions into CMs. In this study, we examined whether differences in downscaling methods significantly affect climate variables such as temperature and precipitation. We tested two downscaling methods using the same regionally aggregated sulfur emissions scenario obtained from the Asian-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model. The downscaled emissions were fed into the Model for Interdisciplinary Research on Climate (MIROC). One of the methods assumed a strong convergence of national emissions intensity (e.g., emissions per gross domestic product), while the other was based on inertia (i.e., the base-year remained unchanged). The emissions intensities in the downscaled spatial emissions generated from the two methods markedly differed, whereas the emissions densities (emissions per area) were similar. We investigated whether the climate change projections of temperature and precipitation would significantly differ between the two methods by applying a field significance test, and found little evidence of a significant difference between the two methods. Moreover, there was no clear evidence of a difference between the climate simulations based on these two downscaling methods. PMID:28076446
MOBILE EMISSIONS ASSESSMENT SYSTEM FOR URBAN AND REGIONAL EVALUATION
A working research model for Atlanta, GA has been developed by Georgia Tech, and is called the Mobile Emissions Assessment System for Urban and Regional Evaluation (MEASURE). The EPA Office of Research and Development has developed an additional implementation of the MEASURE res...
NASA Astrophysics Data System (ADS)
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 comparing upper tropospheric budgets of NOx from aircraft and lightning sources in the modeling domain.
Assessment of State-of-the-Art Dust Emission Scheme in GEOS
NASA Technical Reports Server (NTRS)
Darmenov, Anton; Liu, Xiaohong; Prigent, Catherine
2017-01-01
The GEOS modeling system has been extended with state of the art parameterization of dust emissions based on the vertical flux formulation described in Kok et al 2014. The new dust scheme was coupled with the GOCART and MAM aerosol models. In the present study we compare dust emissions, aerosol optical depth (AOD) and radiative fluxes from GEOS experiments with the standard and new dust emissions. AOD from the model experiments are also compared with AERONET and satellite based data. Based on this comparative analysis we concluded that the new parameterization improves the GEOS capability to model dust aerosols originating from African sources, however it lead to overestimation of dust emissions from Asian and Arabian sources. Further regional tuning of key parameters controlling the threshold friction velocity may be required in order to achieve more definitive and uniform improvement in the dust modeling skill.
NASA Astrophysics Data System (ADS)
Phillips, N.; Crosson, E.; Down, A.; Hutyra, L.; Jackson, R. B.; McKain, K.; Rella, C.; Raciti, S. M.; Wofsy, S. C.
2012-12-01
Lost and unaccounted natural gas can amount to over 6% of Massachusetts' total annual greenhouse gas inventory (expressed as equivalent CO2 tonnage). An unknown portion of this loss is due to natural gas leaks in pipeline distribution systems. The objective of the Boston Methane Project is to estimate the overall leak rate from natural gas systems in metropolitan Boston, and to compare this flux with fluxes from the other primary methane emissions sources. Companion talks at this meeting describe the atmospheric measurement and modeling framework, and chemical and isotopic tracers that can partition total atmospheric methane flux into natural gas and non-natural gas components. This talk focuses on estimation of surface emissions that inform the atmospheric modeling and partitioning. These surface emissions include over 3,300 pipeline natural gas leaks in Boston. For the state of Massachusetts as a whole, the amount of natural gas reported as lost and unaccounted for by utility companies was greater than estimated landfill emissions by an order of magnitude. Moreover, these landfill emissions were overwhelmingly located outside of metro Boston, while gas leaks are concentrated in exactly the opposite pattern, increasing from suburban Boston toward the urban core. Work is in progress to estimate spatial distribution of methane emissions from wetlands and sewer systems. We conclude with a description of how these spatial data sets will be combined and represented for application in atmospheric modeling.
NASA Astrophysics Data System (ADS)
Schaap, Martijn; Segers, Arjo; Curier, Lyana; Timmermans, Renske
2016-04-01
Consistent and long time series of remotely sensed trace gas levels may provide a useful tool to estimate surface emissions and emission trends. We use the OMI-NO2 product in conjunction with the LOTOS-EUROS CTM to estimate European emission trends through correction of the OMI-time series for meteorological variability as well as through assimilation using an ensemble kalman filter system (EnKF). The chemistry transport model captures a large fraction of the variability in NO2 columns at a synoptic timescale, although a seasonal signal in the bias between the modeled and retrieved column data remains. Prior to the assimilation, the OMI-NO2 data have been analyzed to establish the spatially variable temporal and spatial correlation lengths, required for the settings in the EnKF system. The assimilation run for 2005-2013 was performed using constant 2005 emissions to be able to quantify the emission change. The assimilation reduces the model-observation differences considerably. Significant negative trends of 2-3 % per year (as compared to 2005) were found in highly industrialized areas across Western Europe. The assimilation system also identifies the areas with major emission reductions in e.g. northern Spain as identified in earlier studies. Comparison of the trends derived from the assimilation and the data itself shows a high level of agreement, both the trends found in this way are smaller than those reported.
A process-based emission model of volatile organic compounds from silage sources on farms
NASA Astrophysics Data System (ADS)
Bonifacio, H. F.; Rotz, C. A.; Hafner, S. D.; Montes, F.; Cohen, M.; Mitloehner, F. M.
2017-03-01
Silage on dairy farms can emit large amounts of volatile organic compounds (VOCs), a precursor in the formation of tropospheric ozone. Because of the challenges associated with direct measurements, process-based modeling is another approach for estimating emissions of air pollutants from sources such as those from dairy farms. A process-based model for predicting VOC emissions from silage was developed and incorporated into the Integrated Farm System Model (IFSM, v. 4.3), a whole-farm simulation of crop, dairy, and beef production systems. The performance of the IFSM silage VOC emission model was evaluated using ethanol and methanol emissions measured from conventional silage piles (CSP), silage bags (SB), total mixed rations (TMR), and loose corn silage (LCS) at a commercial dairy farm in central California. With transport coefficients for ethanol refined using experimental data from our previous studies, the model performed well in simulating ethanol emission from CSP, TMR, and LCS; its lower performance for SB could be attributed to possible changes in face conditions of SB after silage removal that are not represented in the current model. For methanol emission, lack of experimental data for refinement likely caused the underprediction for CSP and SB whereas the overprediction observed for TMR can be explained as uncertainty in measurements. Despite these limitations, the model is a valuable tool for comparing silage management options and evaluating their relative effects on the overall performance, economics, and environmental impacts of farm production. As a component of IFSM, the silage VOC emission model was used to simulate a representative dairy farm in central California. The simulation showed most silage VOC emissions were from feed lying in feed lanes and not from the exposed face of silage storages. This suggests that mitigation efforts, particularly in areas prone to ozone non-attainment status, should focus on reducing emissions during feeding. For the simulated dairy farm, a reduction of around 30% was found if cows were housed and fed in a barn rather than in an open lot, and 23% if feeds were delivered as four feedings per day rather than as one. Reducing the exposed face of storage can also be useful. Simulated use of silage bags resulted in 90% and 18% reductions in emissions from the storage face and whole farm, respectively.
NASA Astrophysics Data System (ADS)
Kangasaho, V. E.; Tsuruta, A.; Aalto, T.; Backman, L. B.; Houweling, S.; Krol, M. C.; Peters, W.; van der Laan-Luijkx, I. T.; Lienert, S.; Joos, F.; Dlugokencky, E. J.; Michael, S.; White, J. W. C.
2017-12-01
The atmospheric burden of CH4 has more than doubled since preindustrial time. Evaluating the contribution from anthropogenic and natural emissions to the global methane budget is of great importance to better understand the significance of different sources at the global scale, and their contribution to changes in growth rate of atmospheric CH4 before and after 2006. In addition, observations of δ13C-CH4 suggest an increase in natural sources after 2006, which matches the observed increase and variation of CH4 abudance. Methane emission sources can be identified using δ13C-CH4, because different sources produce methane with process-specific isotopic signatures. This study focuses on inversion model based estimates of global anthropogenic and natural methane emission rates to evaluate the existing methane emission estimates with a new δ13C-CH4 inversion system. In situ measurements of atmospheric methane and δ13C-CH4 isotopic signature, provided by the NOAA Global Monitoring Division and the Institute of Arctic and Alpine Research, will be assimilated into the CTDAS-13C-CH4. The system uses the TM5 atmospheric transport model as an observation operator, constrained by ECMWF ERA Interim meteorological fields, and off-line TM5 chemistry fields to account for the atmospheric methane sink. LPX-Bern DYPTOP ecosystem model is used for prior natural methane emissions from wetlands, peatlands and mineral soils, GFED v4 for prior fire emissions and EDGAR v4.2 FT2010 inventory for prior anthropogenic emissions. The EDGAR antropogenic emissions are re-divided into enteric fermentation and manure management, landfills and waste water, rice, coal, oil and gas, and residential emissions, and the trend of total emissions is scaled to match optimized anthropogenic emissions from CTE-CH4. In addition to these categories, emissions from termites and oceans are included. Process specific δ13C-CH4 isotopic signatures are assigned to each emission source to estimate 13CH4 fraction in CH4 emissions. Among the priors, anthropogenic and natural emissions are optimized and others are directly imposed from the prior. A detailed emission estimates of antropogenic and natural CH4 emissions will be constructed in order to provide a more comprehensive understanding of methane emission source divisions.
New Developments in Wildfire Pollution Forecasting at the Canadian Meteorological Centre
NASA Astrophysics Data System (ADS)
Pavlovic, Radenko; Chen, Jack; Munoz-Alpizar, Rodrigo; Davignon, Didier; Beaulieu, Paul-Andre; Landry, Hugo; Menard, Sylvain; Gravel, Sylvie; Moran, Michael
2017-04-01
Environment and Climate Change Canada's air quality forecast system with near-real-time wildfire emissions, named FireWork, was developed in 2012 and has been run by the Canadian Meteorological Centre Operations division (CMCO) since 2013. In June 2016 this system was upgraded to operational status and wildfire smoke forecasts for North America are now available to the general public. FireWork's ability to model the transport and diffusion of wildfire smoke plumes has proved to be valuable to regional air quality forecasters and emergency first responders. Some of the most challenging issues with wildfire pollution modelling concern the production of wildfire emission estimates and near-source dispersion within the air quality model. As a consequence, FireWork is undergoing constant development. During the massive Fort McMurray wildfire event in western Canada in May 2016, for example, different wildfire emissions processing approaches and wildfire emissions injection and dispersion schemes were tested within the air quality model. Work on various FireWork components will continue in order to deliver a new operational version of the forecasting system for the 2017 wildfire season. Some of the proposed improvements will be shown in this presentation along with current and planned FireWork post-processing products.
USDA-ARS?s Scientific Manuscript database
Greenhouse gas (GHG) emissions and their potential impact on the environment has become an important national and international concern. Animal agriculture is a recognized source of GHG emissions, but good information does not exist on the net emissions from our farms. A software tool called the Dai...
Modeling crop residue burning experiments to evaluate smoke emissions and plume transport
Crop residue burning is a common land management practice that results in emissions of a variety of pollutants with negative health impacts. Modeling systems are used to estimate air quality impacts of crop residue burning to support retrospective regulatory assessments and also ...
NASA Astrophysics Data System (ADS)
Shonkwiler, K. B.; Ham, J. M.; Williams, C. M.
2013-12-01
Ammonia (NH3) that volatilizes from confined animal feeding operations (CAFOs) can form aerosols that travel long distances where such aerosols can deposit in sensitive regions, potentially causing harm to local ecosystems. However, quantifying the emissions of ammonia from CAFOs through direct measurement is very difficult and costly to perform. A system was therefore developed at Colorado State University for conditionally sampling NH3 concentrations based on weather parameters measured using inexpensive equipment. These systems use passive diffusive cartridges (Radiello, Sigma-Aldrich, St. Louis, MO, USA) that provide time-averaged concentrations representative of a two-week deployment period. The samplers are exposed by a robotic mechanism so they are only deployed when wind is from the direction of the CAFO at 1.4 m/s or greater. These concentration data, along with other weather variables measured during each sampler deployment period, can then be used in a simple inverse model (FIDES, UMR Environnement et Grandes Cultures, Thiverval-Grignon, France) to estimate emissions. There are not yet any direct comparisons of the modeled emissions derived from time-averaged concentration data to modeled emissions from more sophisticated backward Lagrangian stochastic (bLs) techniques that utilize instantaneous measurements of NH3 concentration. In the summer and autumn of 2013, a suite of robotic passive sampler systems were deployed at a 25,000-head cattle feedlot at the same time as an open-path infrared (IR) diode laser (GasFinder2, Boreal Laser Inc., Edmonton, Alberta, Canada) which continuously measured ammonia concentrations instantaneously over a 225-m path. This particular laser is utilized in agricultural settings, and in combination with a bLs model (WindTrax, Thunder Beach Scientific, Inc., Halifax, Nova Scotia, Canada), has become a common method for estimating NH3 emissions from a variety of agricultural and industrial operations. This study will first compare the ammonia concentrations measured with the Radiello system to that measured with the long-path IR laser. Second, NH3 emissions estimated using the simple inverse model (FIDES) and the time-averaged data will be compared to emissions derived from the bLS model (WindTrax) using the laser-based NH3 data. Results could lead to a more cost-efficient and simpler technique for monitoring ammonia fluxes from of CAFOs and other strong areal sources.
Improved system integration for integrated gasification combined cycle (IGCC) systems.
Frey, H Christopher; Zhu, Yunhua
2006-03-01
Integrated gasification combined cycle (IGCC) systems are a promising technology for power generation. They include an air separation unit (ASU), a gasification system, and a gas turbine combined cycle power block, and feature competitive efficiency and lower emissions compared to conventional power generation technology. IGCC systems are not yet in widespread commercial use and opportunities remain to improve system feasibility via improved process integration. A process simulation model was developed for IGCC systems with alternative types of ASU and gas turbine integration. The model is applied to evaluate integration schemes involving nitrogen injection, air extraction, and combinations of both, as well as different ASU pressure levels. The optimal nitrogen injection only case in combination with an elevated pressure ASU had the highest efficiency and power output and approximately the lowest emissions per unit output of all cases considered, and thus is a recommended design option. The optimal combination of air extraction coupled with nitrogen injection had slightly worse efficiency, power output, and emissions than the optimal nitrogen injection only case. Air extraction alone typically produced lower efficiency, lower power output, and higher emissions than all other cases. The recommended nitrogen injection only case is estimated to provide annualized cost savings compared to a nonintegrated design. Process simulation modeling is shown to be a useful tool for evaluation and screening of technology options.
Kwak, Sehyun; Svensson, J; Brix, M; Ghim, Y-C
2016-02-01
A Bayesian model of the emission spectrum of the JET lithium beam has been developed to infer the intensity of the Li I (2p-2s) line radiation and associated uncertainties. The detected spectrum for each channel of the lithium beam emission spectroscopy system is here modelled by a single Li line modified by an instrumental function, Bremsstrahlung background, instrumental offset, and interference filter curve. Both the instrumental function and the interference filter curve are modelled with non-parametric Gaussian processes. All free parameters of the model, the intensities of the Li line, Bremsstrahlung background, and instrumental offset, are inferred using Bayesian probability theory with a Gaussian likelihood for photon statistics and electronic background noise. The prior distributions of the free parameters are chosen as Gaussians. Given these assumptions, the intensity of the Li line and corresponding uncertainties are analytically available using a Bayesian linear inversion technique. The proposed approach makes it possible to extract the intensity of Li line without doing a separate background subtraction through modulation of the Li beam.
Integrating Biodiversity into Biosphere-Atmosphere Interactions Using Individual-Based Models (IBM)
NASA Astrophysics Data System (ADS)
Wang, B.; Shugart, H. H., Jr.; Lerdau, M.
2017-12-01
A key component regulating complex, nonlinear, and dynamic biosphere-atmosphere interactions is the inherent diversity of biological systems. The model frameworks currently widely used, i.e., Plant Functional Type models) do not even begin to capture the metabolic and taxonomic diversity found in many terrestrial systems. We propose that a transition from PFT-based to individual-based modeling approaches (hereafter referred to as IBM) is essential for integrating biodiversity into research on biosphere-atmosphere interactions. The proposal emerges from our studying the interactions of forests with atmospheric processes in the context of climate change using an individual-based forest volatile organic compounds model, UVAFME-VOC. This individual-based model can explicitly simulate VOC emissions based on an explicit modelling of forest dynamics by computing the growth, death, and regeneration of each individual tree of different species and their competition for light, moisture, and nutrient, from which system-level VOC emissions are simulated by explicitly computing and summing up each individual's emissions. We found that elevated O3 significantly altered the forest dynamics by favoring species that are O3-resistant, which, meanwhile, are producers of isoprene. Such compositional changes, on the one hand, resulted in unsuppressed forest productivity and carbon stock because of the compensation by O3-resistant species. On the other hand, with more isoprene produced arising from increased producers, a possible positive feedback loop between tropospheric O3 and forest thereby emerged. We also found that climate warming will not always stimulate isoprene emissions because warming simultaneously reduces isoprene emissions by causing a decline in the abundance of isoprene-emitting species. These results suggest that species diversity is of great significance and that individual-based modelling strategies should be applied in studying biosphere-atmosphere interactions.
Can dust emission mechanisms be determined from field measurements?
USDA-ARS?s Scientific Manuscript database
Field observations are needed to develop and test theories on dust emission for use in dust modeling systems. The dust emission mechanism (aerodynamic entrainment, saltation bombardment, aggregate disintegration) as well as the amount and particle-size distribution of emitted dust may vary under sed...
Disentangling dust emission mechanisms – a field study
USDA-ARS?s Scientific Manuscript database
Field observations are needed to both develop and test theories on dust emission for use in global modeling systems. The dust emission mechanism (aerodynamic entrainment, saltation bombardment, aggregate disintegration) as well as the amount and particle-size distribution of emitted dust may vary un...
A GIS-BASED MODAL MODEL OF AUTOMOBILE EXHAUST EMISSIONS
The report presents progress toward the development of a computer tool called MEASURE, the Mobile Emission Assessment System for Urban and Regional Evaluation. The tool works toward a goal of providing researchers and planners with a way to assess new mobile emission mitigation s...
Yin, Shasha; Zheng, Junyu; Lu, Qing; Yuan, Zibing; Huang, Zhijiong; Zhong, Liuju; Lin, Hui
2015-05-01
Accurate and gridded VOC emission inventories are important for improving regional air quality model performance. In this study, a four-level VOC emission source categorization system was proposed. A 2010-based gridded Pearl River Delta (PRD) regional VOC emission inventory was developed with more comprehensive source coverage, latest emission factors, and updated activity data. The total anthropogenic VOC emission was estimated to be about 117.4 × 10(4)t, in which on-road mobile source shared the largest contribution, followed by industrial solvent use and industrial processes sources. Among the industrial solvent use source, furniture manufacturing and shoemaking were major VOC emission contributors. The spatial surrogates of VOC emission were updated for major VOC sources such as industrial sectors and gas stations. Subsector-based temporal characteristics were investigated and their temporal variations were characterized. The impacts of updated VOC emission estimates and spatial surrogates were evaluated by modeling O₃ concentration in the PRD region in the July and October of 2010, respectively. The results indicated that both updated emission estimates and spatial allocations can effectively reduce model bias on O₃ simulation. Further efforts should be made on the refinement of source classification, comprehensive collection of activity data, and spatial-temporal surrogates in order to reduce uncertainty in emission inventory and improve model performance. Copyright © 2015 Elsevier B.V. All rights reserved.
Bichenkova, Elena V; Sardarian, Ali R; Wilton, Amanda N; Bonnet, Pascal; Bryce, Richard A; Douglas, Kenneth T
2006-01-21
Organic intramolecular exciplexes, N-(4-dimethylaminobenzyl)-N-(1-pyrenemethyl)amine (1) and N'-4-dimethylaminonaphthyl-N-(1-pyrenemethyl)amine (2), were used as model systems to reveal major factors affecting their exciplex fluorescence, and thus lay the basis for developing emissive target-assembled exciplexes for DNA-mounted systems in solution. These models with an aromatic pyrenyl hydrocarbon moiety as an electron acceptor appropriately connected to an aromatic dimethylamino electron donor component (N,N-dimethylaminophenyl or N,N-dimethylaminonaphthyl) showed strong intramolecular exciplex emission in both non-polar and highly polar solvents. The effect of dielectric constant on the maximum wavelength for exciplex emission was studied, and emission was observed for 1 and 2 over the full range of solvent from non-polar hydrocarbons up to N-methylformamide with a dielectric constant of 182. Quantum yields were determined for these intramolecular exciplexes in a range of solvents relative to that for Hoechst 33,258. Conformational analysis of 1 was performed both computationally and via qualitative 2D NMR using (1)H-NOESY experiments. The results obtained indicated the contribution of pre-folded conformation(s) to the ground state of 1 conducive to exciplex emission. This research provides the initial background for design of self-assembled, DNA-mounted exciplexes and underpins further development of exciplex-based hybridisation bioassays.
NASA Astrophysics Data System (ADS)
ONeill, S. M.; Chung, S. H.; Wiedinmyer, C.; Larkin, N. K.; Martinez, M. E.; Solomon, R. C.; Rorig, M.
2014-12-01
Emissions from fires in the Western US are substantial and can impact air quality and regional climate. Many methods exist that estimate the particulate and gaseous emissions from fires, including those run operationally for use with chemical forecast models. The US Forest Service Smartfire2/BlueSky modeling framework uses satellite data and reported information about fire perimeters to estimate emissions of pollutants to the atmosphere. The emission estimates are used as inputs to dispersion models, such as HYSPLIT, and chemical transport models, such as CMAQ and WRF-Chem, to assess the chemical and physical impacts of fires on the atmosphere. Here we investigate the use of Smartfire2/BlueSky and WRF-Chem to simulate emissions from the 2013 fire summer fire season, with special focus on the Rim Fire in northern California. The 2013 Rim Fire ignited on August 17 and eventually burned more than 250,000 total acres before being contained on October 24. Large smoke plumes and pyro-convection events were observed. In this study, the Smartfire2/BlueSky operational emission estimates are compared to other estimation methods, such as the Fire INventory from NCAR (FINN) and other global databases to quantify variations in emission estimation methods for this wildfire event. The impact of the emissions on downwind chemical composition is investigated with the coupled meteorology-chemistry WRF-Chem model. The inclusion of aerosol-cloud and aerosol-radiation interactions in the model framework enables the evaluation of the downwind impacts of the fire plume. The emissions and modeled chemistry can also be evaluated with data collected from the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) aircraft field campaign, which intersected the fire plume.
Barnett, J Matthew; Yu, Xiao-Ying; Recknagle, Kurtis P; Glissmeyer, John A
2016-11-01
A planned laboratory space and exhaust system modification to the Pacific Northwest National Laboratory Material Science and Technology Building indicated that a new evaluation of the mixing at the air sampling system location would be required for compliance to ANSI/HPS N13.1-2011. The modified exhaust system would add a third fan, thereby increasing the overall exhaust rate out the stack, thus voiding the previous mixing study. Prior to modifying the radioactive air emissions exhaust system, a three-dimensional computational fluid dynamics computer model was used to evaluate the mixing at the sampling system location. Modeling of the original three-fan system indicated that not all mixing criteria could be met. A second modeling effort was conducted with the addition of an air blender downstream of the confluence of the three fans, which then showed satisfactory mixing results. The final installation included an air blender, and the exhaust system underwent full-scale tests to verify velocity, cyclonic flow, gas, and particulate uniformity. The modeling results and those of the full-scale tests show agreement between each of the evaluated criteria. The use of a computational fluid dynamics code was an effective aid in the design process and allowed the sampling system to remain in its original location while still meeting the requirements for sampling at a well mixed location.
Cryptic Methane Emissions from Upland Forest Ecosystems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Megonigal, Patrick; Pitz, Scott
This exploratory research on Cryptic Methane Emissions from Upland Forest Ecosystems was motivated by evidence that upland ecosystems emit 36% as much methane to the atmosphere as global wetlands, yet we knew almost nothing about this source. The long-term objective was to refine Earth system models by quantifying methane emissions from upland forests, and elucidate the biogeochemical processes that govern upland methane emissions. The immediate objectives of the grant were to: (i) test the emerging paradigm that upland trees unexpectedly transpire methane, (ii) test the basic biogeochemical assumptions of an existing global model of upland methane emissions, and (iii) developmore » the suite of biogeochemical approaches that will be needed to advance research on upland methane emissions. We instrumented a temperate forest system in order to explore the processes that govern upland methane emissions. We demonstrated that methane is emitted from the stems of dominant tree species in temperate upland forests. Tree emissions occurred throughout the growing season, while soils adjacent to the trees consumed methane simultaneously, challenging the concept that forests are uniform sinks of methane. High frequency measurements revealed diurnal cycling in the rate of methane emissions, pointing to soils as the methane source and transpiration as the most likely pathway for methane transport. We propose the forests are smaller methane sinks than previously estimated due to stem emissions. Stem emissions may be particularly important in upland tropical forests characterized by high rainfall and transpiration, resolving differences between models and measurements. The methods we used can be effectively implemented in order to determine if the phenomenon is widespread.« less
Fu, Mingliang; Ge, Yunshan; Wang, Xin; Tan, Jianwei; Yu, Linxiao; Liang, Bin
2013-05-01
NOx and particulate matter (PM) emissions from heavy-duty diesel vehicles (HDVs) have become the most important sources of pollutants affecting urban air quality in China. In recent years, a series of emission control strategies and diesel engine polices have been introduced that require advanced emission control technology. China and Europe mostly have used Selective Catalytic Reduction (SCR) with urea to meet the Euro IV diesel engine emission standard. In this study, two Euro IV busses with SCR were tested by using potable emission measurement system (PEMS) to assess NOx emissions associated with urban, suburban and freeway driving patterns. The results indicated that with the SCR system, the urea injection time for the entire driving period increased with higher vehicle speed. For freeway driving, the urea injection time covered 71%-83% of the driving period; the NOx emission factors from freeway driving were lower than those associated with urban and suburban driving. Unfortunately, the NOx emission factors were 2.6-2.8-, 2.3-2.7- and 2.2-2.3-fold higher than the Euro IV standard limits for urban, suburban and freeway driving, respectively; NOx emission factors (in g/km and g/(kW·h)) from the original vehicles (without SCR) were higher than their corresponding vehicles with SCR for suburban and freeway driving. Compared with the IVE model results, the measured NOx emission factors were 1.60-1.16-, 1.77-1.27-, 2.49-2.44-fold higher than the NOx predicted by the IVE model for urban and suburban driving, respectively. Thus, an adjustment of emission factors is needed to improve the estimation of Euro IV vehicle emissions in China. Copyright © 2013 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Ahmadov, R.; Grell, G. A.; James, E.; Alexander, C.; Stewart, J.; Benjamin, S.; McKeen, S. A.; Csiszar, I. A.; Tsidulko, M.; Pierce, R. B.; Pereira, G.; Freitas, S. R.; Goldberg, M.
2017-12-01
We present a new real-time smoke modeling system, the High Resolution Rapid Refresh coupled with smoke (HRRR-Smoke), to simulate biomass burning (BB) emissions, plume rise and smoke transport in real time. The HRRR is the NOAA Earth System Research Laboratory's 3km grid spacing version of the Weather Research and Forecasting (WRF) model used for weather forecasting. Here we make use of WRF-Chem (the WRF model coupled with chemistry) and simulate fine particulate matter (smoke) emissions emitted by BB. The HRRR-Smoke modeling system ingests fire radiative power (FRP) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (S-NPP) satellite to calculate BB emissions. The FRP product is based on processing 750m resolution "M" bands. The algorithms for fire detection and FRP retrieval are consistent with those used to generate the MODIS fire detection data. For the purpose of ingesting VIIRS fire data into the HRRR-Smoke model, text files are generated to provide the location and detection confidence of fire pixels, as well as FRP. The VIIRS FRP data from the text files are processed and remapped over the HRRR-Smoke model domains. We process the FRP data to calculate BB emissions (smoldering part) and fire size for the model input. In addition, HRRR-Smoke uses the FRP data to simulate the injection height for the flaming emissions using concurrently simulated meteorological fields by the model. Currently, there are two 3km resolution domains covering the contiguous US and Alaska which are used to simulate smoke in real time. In our presentation, we focus on the CONUS domain. HRRR-Smoke is initialized 4 times per day to forecast smoke concentrations for the next 36 hours. The VIIRS FRP data, as well as near-surface and vertically integrated smoke mass concentrations are visualized for every forecast hour. These plots are provided to the public via the HRRR-Smoke web-page: https://rapidrefresh.noaa.gov/HRRRsmoke/. Model evaluations for a case study are presented, where simulated smoke concentrations are compared with hourly PM2.5 measurements from EPA's Air Quality System network. These comparisons demonstrate the model's ability in simulating high aerosol loadings during major wildfire events in the western US.
Evaluation of modelled methane emissions over northern peatland sites
NASA Astrophysics Data System (ADS)
Gao, Yao; Burke, Eleanor; Chadburn, Sarah; Raivonen, Maarit; Susiluoto, Jouni; Vesala, Timo; Aurela, Mika; Lohila, Annalea; Aalto, Tuula
2017-04-01
Methane (CH4) is a powerful greenhouse gas, with approximately 34 times the global warming potential of carbon dioxide (CO2) over a century time horizon (IPCC, 2013). The strong sensitivity of methane emissions to environmental factors has led to concerns about potential positive feedbacks to climate change. Evaluation of the ability of the process-based land surface models of earth system models (ESMs) in simulating CH4 emission over peatland is needed for more precise future predictions. In this study, two peatland sites of poor and rich soil nutrient conditions, in southern and northern Finland respectively, are adopted. The measured CH4 fluxes at the two sites are used to evaluate the CH4 emissions simulated by the land surface model (JULES) of the UK Earth System model and by the Helsinki peatland methane emission model (HIMMELI), which is developed at Finnish Meteorological Institute and Helsinki University. In JULES, CH4 flux is simply related to soil temperature, wetland fraction and effective substrate availability. However, HIMMELI has detailed descriptions of microbial and transport processes for simulating CH4 flux. The seasonal dynamics of CH4 fluxes at the two sites are relatively well captured by both models, but model biases exist. Simulated CH4 flux is sensitive to water table depth (WTD) at both models. However, the simulated WTD is limited to be below ground in JULES. It is also important to have the annual cycle of LAI correct when coupling JULES with HIMMELI.
NASA Astrophysics Data System (ADS)
J. Lima, I.; Vilega Rodrigues, C.; Medeiros Gomes Silva, K.; Luna, G.; D Amico, F.; Goulart Coelho, J.
2017-10-01
Intermediate polars are compact binaries in which mass transfer occurs from a low-mass star onto a magnetic white dwarf. A shock structure is formed in the magnetic accretion column nearby the white-dwarf surface. High-energy emission is produced in the post-shock region and the main physical process envolved is bremsstrahlung and line emission. Some systems show optical polarization, which may be also originated in the post-shock region. Our main goal is to study the magnetic structure of intermediate polars by simultaneously modelling optical polarimetry and X-ray data using the CYCLOPS code. This code was developed by our group to peform multi-wavelength fitting of the accretion column flux. It considers cyclotron and free-free emission from a 3D post-shock region, which is non-homogeneous in terms of density, temperature, and magnetic field. In this study, we present our modelling of the optical polarization and X-ray emission of V405 Aurigae, the intermediate polar that has the highest magnetic field. Previous studies of this system were not successful in proposing a geometry that explains both the optical and X-ray emissions.
Ng, Carla A; von Goetz, Natalie
2017-01-01
Food is a major pathway for human exposure to hazardous chemicals. The modern food system is becoming increasingly complex and globalized, but models for food-borne exposure typically assume locally derived diets or use concentrations directly measured in foods without accounting for food origin. Such approaches may not reflect actual chemical intakes because concentrations depend on food origin, and representative analysis is seldom available. Processing, packaging, storage, and transportation also impart different chemicals to food and are not yet adequately addressed. Thus, the link between environmental emissions and realistic human exposure is effectively broken. We discuss the need for a fully integrated treatment of the modern industrialized food system, and we propose strategies for using existing models and relevant supporting data sources to track chemicals during production, processing, packaging, storage, and transport. Fate and bioaccumulation models describe how chemicals distribute in the environment and accumulate through local food webs. Human exposure models can use concentrations in food to determine body burdens based on individual or population characteristics. New models now include the impacts of processing and packaging but are far from comprehensive. We propose to close the gap between emissions and exposure by utilizing a wider variety of models and data sources, including global food trade data, processing, and packaging models. A comprehensive approach that takes into account the complexity of the modern global food system is essential to enable better prediction of human exposure to chemicals in food, sound risk assessments, and more focused risk abatement strategies. Citation: Ng CA, von Goetz N. 2017. The global food system as a transport pathway for hazardous chemicals: the missing link between emissions and exposure. Environ Health Perspect 125:1-7; http://dx.doi.org/10.1289/EHP168.
Smoke and Emissions Model Intercomparison Project (SEMIP)
NASA Astrophysics Data System (ADS)
Larkin, N. K.; Raffuse, S.; Strand, T.; Solomon, R.; Sullivan, D.; Wheeler, N.
2008-12-01
Fire emissions and smoke impacts from wildland fire are a growing concern due to increasing fire season severity, dwindling tolerance of smoke by the public, tightening air quality regulations, and their role in climate change issues. Unfortunately, while a number of models and modeling system solutions are available to address these issues, the lack of quantitative information on the limitations and difference between smoke and emissions models impedes the use of these tools for real-world applications (JFSP, 2007). We describe a new, open-access project to directly address this issue, the open-access Smoke Emissions Model Intercomparison Project (SEMIP) and invite the community to participate. Preliminary work utilizing the modular BlueSky framework to directly compare fire location and size information, fuel loading amounts, fuel consumption rates, and fire emissions from a number of current models that has found model-to-model variability as high as two orders of magnitude for an individual fire. Fire emissions inventories also show significant variability on both regional and national scales that are dependant on the fire location information used (ground report vs. satellite), the fuel loading maps assumed, and the fire consumption models employed. SEMIP expands on this work and creates an open-access database of model results and observations with the goal of furthering model development and model prediction usability for real-world decision support.
NASA Astrophysics Data System (ADS)
Tavani, Marco; Arons, Jonathan
1997-03-01
We study the physical processes in the system containing the 47 ms radio pulsar PSR B1259-63 orbiting around a Be star in a highly eccentric orbit. This system is the only known binary where a radio pulsar is observed to interact with gaseous material from a Be star. A rapidly rotating radio pulsar such as PSR B1259-63 is expected to produce a wind of electromagnetic emission and relativistic particles, and this binary is an ideal astrophysical laboratory to study the mass outflow/pulsar interaction in a highly time-variable environment. Motivated by the results of a recent multiwavelength campaign during the 1994 January periastron passage of PSR B1259-63, we discuss several issues regarding the mechanism of high-energy emission. Unpulsed power-law emission from the PSR B1259-63 system was detected near periastron in the energy range 1-200 keV. The observed X-ray/soft γ-ray emission is characterized by moderate luminosity, small and constant column density, lack of detectable pulsations, and peculiar spectral and intensity variability. In principle, high-energy (X-ray and gamma-ray) emission from the system can be produced by different mechanisms including (1) mass accretion onto the surface of the neutron star, (2) ``propeller''-like magnetospheric interaction at a small pulsar distance, and (3) shock-powered emission in a pulsar wind termination shock at a large distance from the pulsar. We carry out a series of calculations aimed at modeling the high-energy data of the PSR B1259-63 system throughout its orbit and especially near periastron. We find that the observed high-energy emission from the PSR B1259-63 system is not compatible with accretion or propeller-powered emission. This conclusion is supported by a model based on standard properties of Be stars and for plausible assumptions about the pulsar/outflow interaction geometry. We find that shock-powered high-energy emission produced by the pulsar/outflow interaction is consistent with all the characteristics of the high-energy emission of the PSR B1259-63 system. This opens the possibility of obtaining for the first time constraints on the physical properties of the PSR B1259-63 pulsar wind and its interaction properties in a strongly time-variable nebular environment. By studying the time evolution of the pulsar cavity, we can constrain the magnitude and geometry of the mass outflow as the PSR B1259-63 orbits around its Be star companion. The pulsar/outflow interaction is most likely mediated by a collisionless shock at the internal boundary of the pulsar cavity. The system shows all the characteristics of a binary plerion being diffuse and compact near apastron and periastron, respectively. The PSR B1259-63 system is subject to different radiative regimes depending on whether synchrotron or inverse-Compton (IC) cooling dominates the radiation of electron/positron pairs (e+/- pairs) advected away from the inner boundary of the pulsar cavity. The highly nonthermal nature of the observed X-ray/soft γ-ray emission from the PSR B1259-63 system near periastron establishes the existence of an efficient particle acceleration mechanism within a timescale shown to be less than ~102-103 s. A synchrotron/IC model of emission of e+/- pairs accelerated at the inner shock front of the pulsar cavity and adiabatically expanding in the MHD flow provides an excellent explanation of the observed time-variable X-ray flux and spectrum from the PSR B1259-63 system. We find that the best model for the PSR B1259-63 system is consistent with the pulsar orbital plane being misaligned with the plane of a thick equatorial Be star outflow. The angular width of the equatorially enhanced Be star outflow is constrained to be ~50° at the pulsar distance, and the misalignment angle is >~25°. We calculate the intensity and spectrum of the high-energy emission for the whole PSR B1259-63 orbit and predict the characteristics of the emission near the apastron region based on the periastron results. The mass-loss rate is deduced to be approximately constant in time during a ~2 yr period. Our results for the Be star outflow of the PSR B1259-63 system are consistent with models of the radio eclipses near periastron. The consequences of our analysis have general validity. Our study of the PSR B1259-63 system shows that X-ray emission can be caused by a mechanism alternative to accretion in a system containing an energetic pulsar interacting with nebular material. This fact can have far-reaching consequences for the interpretation of galactic astrophysical systems showing nonthermal X-ray and γ-ray emission. We show that a binary system such as PSR B1259-63 offers a novel way to study the acceleration process of relativistic plasmas subject to strongly time variable radiative environments.
Simulating the Earth System Response to Negative Emissions
NASA Astrophysics Data System (ADS)
Jackson, R. B.; Milne, J.; Littleton, E. W.; Jones, C.; Canadell, J.; Peters, G. P.; van Vuuren, D.; Davis, S. J.; Jonas, M.; Smith, P.; Ciais, P.; Rogelj, J.; Torvanger, A.; Shrestha, G.
2016-12-01
The natural carbon sinks of the land and oceans absorb approximately half the anthropogenic CO2 emitted every year. The CO2 that is not absorbed accumulates in the Earth's atmosphere and traps the suns rays causing an increase in the global mean temperature. Removing this left over CO2 using negative emissions technologies (NETs) has been proposed as a strategy to lessen the accumulating CO2 and avoid dangerous climate change. Using CMIP5 Earth system model simulations this study assessed the impact on the global carbon cycle, and how the Earth system might respond, to negative emissions strategies applied to low emissions scenarios, over different times horizons from the year 2000 to 2300. The modeling results suggest that using NETs to remove atmospheric CO2 over five 50-year time horizons has varying effects at different points in time. The effects of anthropogenic and natural sources and sinks, can result in positive or negative changes in atmospheric CO2 concentration. Results show that historic emissions and the current state of the Earth System have impacts on the behavior of atmospheric CO2, as do instantaneous anthropogenic emissions. Indeed, varying background scenarios seemed to have a greater effect on atmospheric CO2 than the actual amount and timing of NETs. These results show how NETs interact with the physical climate-carbon cycle system and highlight the need for more research on earth-system dynamics as they relate to carbon sinks and sources and anthropogenic perturbations.
Role of natural gas in meeting an electric sector emissions ...
With advances in natural gas extraction technologies, there is an increase in availability of domestic natural gas, and natural gas is gaining a larger share of use as a fuel in electricity production. At the power plant, natural gas is a cleaner burning fuel than coal, but uncertainties exist in the amount of methane leakage occurring upstream in the extraction and production of natural gas. At high leakage levels, these methane emissions could outweigh the benefits of switching from coal to natural gas. This analysis uses the MARKAL linear optimization model to compare the carbon emissions profiles and system-wide global warming potential of the U.S. energy system over a series of model runs in which the power sector is asked to meet a specific CO2 reduction target and the availability of natural gas changes. Scenarios are run with a range of upstream methane emission leakage rates from natural gas production. While the total CO2 emissions are reduced in most scenarios, total greenhouse gas emissions show an increase or no change when both natural gas availability and methane emissions from natural gas production are high. Article presents summary of results from an analyses of natural gas resource availability and power sector emissions reduction strategies under different estimates of methane leakage rates during natural gas extraction and production. This was study was undertaken as part of the Energy Modeling Forum Study #31:
Mercury emission and dispersion models from soils contaminated by cinnabar mining and metallurgy.
Llanos, Willians; Kocman, David; Higueras, Pablo; Horvat, Milena
2011-12-01
The laboratory flux measurement system (LFMS) and dispersion models were used to investigate the kinetics of mercury emission flux (MEF) from contaminated soils. Representative soil samples with respect to total Hg concentration (26-9770 μg g(-1)) surrounding a decommissioned mercury-mining area (Las Cuevas Mine), and a former mercury smelter (Cerco Metalúrgico de Almadenejos), in the Almadén mercury mining district (South Central Spain), were collected. Altogether, 14 samples were analyzed to determine the variation in mercury emission flux (MEF) versus distance from the sources, regulating two major environmental parameters comprising soil temperature and solar radiation. In addition, the fraction of the water-soluble mercury in these samples was determined in order to assess how MEF from soil is related to the mercury in the aqueous soil phase. Measured MEFs ranged from less than 140 to over 10,000 ng m(-2) h(-1), with the highest emissions from contaminated soils adjacent to point sources. A significant decrease of MEF was then observed with increasing distance from these sites. Strong positive effects of both temperature and solar radiation on MEF was observed. Moreover, MEF was found to occur more easily in soils with higher proportions of soluble mercury compared to soils where cinnabar prevails. Based on the calculated Hg emission rates and with the support of geographical information system (GIS) tools and ISC AERMOD software, dispersion models for atmospheric mercury were implemented. In this way, the gaseous mercury plume generated by the soil-originated emissions at different seasons was modeled. Modeling efforts revealed that much higher emissions and larger mercury plumes are generated in dry and warm periods (summer), while the plume is smaller and associated with lower concentrations of atmospheric mercury during colder periods with higher wind activity (fall). Based on the calculated emissions and the model implementation, yearly emissions from the "Cerco Metalúrgico de Almadenejos" decommissioned metallurgical precinct were estimated at 16.4 kg Hg y(-1), with significant differences between seasons.
The potential impact of hydrogen energy use on the atmosphere
NASA Astrophysics Data System (ADS)
van Ruijven, B. J.; Lamarque, J. F.; van Vuuren, D. P.; Kram, T.; Eerens, H.
2009-04-01
Energy models show very different trajectories for future energy systems (partly as function of future climate policy). One possible option is a transition towards a hydrogen-based energy system. The potential impact of such hydrogen economy on atmospheric emissions is highly uncertain. On the one hand, application of hydrogen in clean fuel cells reduces emissions of local air pollutants, like SOx and NOx. On the other hand, emissions of hydrogen from system leakages are expected to change the atmospheric concentrations and behaviour (see also Price et al., 2007; Sanderson et al., 2003; Schultz et al., 2003; Tromp et al., 2003). The uncertainty arises from several sources: the expected use of hydrogen, the intensity of leakages and emissions, and the atmospheric chemical behaviour of hydrogen. Existing studies to the potential impacts of a hydrogen economy on the atmosphere mostly use hydrogen emission scenarios that are based on simple assumptions. This research combines two different modelling efforts to explore the range of impacts of hydrogen on atmospheric chemistry. First, the potential role of hydrogen in the global energy system and the related emissions of hydrogen and other air pollutants are derived from the global energy system simulation model TIMER (van Vuuren, 2007). A set of dedicated scenarios on hydrogen technology development explores the most pessimistic and optimistic cases for hydrogen deployment (van Ruijven et al., 2008; van Ruijven et al., 2007). These scenarios are combined with different assumptions on hydrogen emission factors. Second, the emissions from the TIMER model are linked to the NCAR atmospheric model (Lamarque et al., 2005; Lamarque et al., 2008), in order to determine the impacts on atmospheric chemistry. By combining an energy system model and an atmospheric model, we are able to consistently explore the boundaries of both hydrogen use, emissions and impacts on atmospheric chemistry. References: Lamarque, J.-F., Kiehl, J. T., Hess, P. G., Collins, W. D., Emmons, L. K., Ginoux, P., Luo, C. and Tie, X. X. (2005). "Response of a coupled chemistry-climate model to changes in aerosol emissions: Global impact on the hydrological cycle and the tropospheric burdens of OH, ozone and NOx." Geophysical Research Letters 32(16). Lamarque, J.-F., Kinnison, D. E., Hess, P. G. and Vitt, F. (2008). "Simulated lower stratospheric trends between 1970 and 2005: identifying the role of climate and composition changes." Journal of Geophysical Research 113(D12301). Price, H., Jaegle, L., Rice, A., Quay, P., Novelli, P. C. and Gammon, R. (2007). "Global budget of molecular hydrogen and its deuterium content: constraints from ground station, cruise, and aircraft observations." Journal of Geophysical Research 112(D22108). Sanderson, M. G., Collins, W. J., Derwent, R. G. and Johnson, C. E. (2003). "Simulation of Global Hydrogen Levels Using a Lagrangian Three-Dimensional Model." Journal of Atmospheric Chemistry 46(1): 15-28. Schultz, M. G., Diehl, T., Brasseur, G. P. and Zittel, W. (2003). "Air Pollution and Climate-Forcing Impacts of a Global Hydrogen Economy." Science 302(5645): 624-627. Tromp, T. K., Shia, R. L., Allen, M., Eiler, J. M. and Yung, Y. L. (2003). "Potential environmental impact of a hydrogen economy on the stratosphere." Science 300(5626): 1740-1742. van Ruijven, B., Hari, L., van Vuuren, D. P. and de Vries, B. (2008). "The potential role of hydrogen in India and Western Europe." Energy Policy 36(5): 1649-1665. van Ruijven, B., van Vuuren, D. P. and de Vries, B. (2007). "The potential role of hydrogen in energy systems with and without climate policy." International Journal of Hydrogen Energy 32(12): 1655-1672. van Vuuren, D. P. (2007). Energy systems and climate policy. Dept. of Science, Technology and Society, Faculty of Science. Utrecht, Utrecht University: 326.
Trends and Patterns in a New Time Series of Natural and Anthropogenic Methane Emissions, 1980-2000
NASA Astrophysics Data System (ADS)
Matthews, E.; Bruhwiler, L.; Themelis, N. J.
2007-12-01
We report on a new time series of methane (CH4) emissions from anthropogenic and natural sources developed for a multi-decadal methane modeling study (see following presentation by Bruhwiler et al.). The emission series extends from 1980 through the early 2000s with annual emissions for all countries has several features distinct from the source histories based on IPCC methods typically employed in modeling the global methane cycle. Fossil fuel emissions rely on 7 fuel-process emission combinations and minimize reliance on highly-uncertain emission factors. Emissions from ruminant animals employ regional profiles of bovine populations that account for the influence of variable age- and size-demographics on emissions and are ~15% lower than other estimates. Waste-related emissions are developed using an approach that avoids using of data-poor emission factors and accounts for impacts of recycling and thermal treatment of waste on diverting material from landfills and CH4 capture at landfill facilities. Emissions from irrigated rice use rice-harvest areas under 3 water-management systems and a new historical data set that analyzes multiple sources for trends in water management since 1980. A time series of emissions from natural wetlands was developed by applying a multiple-regression model derived from full process-based model of Walter with analyzed meteorology from the ERA-40 reanalysis.
Comparisons of MOVES Light-duty Gasoline NOx Emission Rates with Real-world Measurements
NASA Astrophysics Data System (ADS)
Choi, D.; Sonntag, D.; Warila, J.
2017-12-01
Recent studies have shown differences between air quality model estimates and monitored values for nitrogen oxides. Several studies have suggested that the discrepancy between monitored and modeled values is due to an overestimation of NOx from mobile sources in EPA's emission inventory, particularly for light-duty gasoline vehicles. EPA's MOtor Vehicle Emission Simulator (MOVES) is an emission modeling system that estimates emissions for cars, trucks and other mobile sources at the national, county, and project level for criteria pollutants, greenhouse gases, and air toxics. Studies that directly measure vehicle emissions provide useful data for evaluating MOVES when the measurement conditions are properly accounted for in modeling. In this presentation, we show comparisons of MOVES2014 to thousands of real-world NOx emissions measurements from individual light-duty gasoline vehicles. The comparison studies include in-use vehicle emissions tests conducted on chassis dynamometer tests in support of Denver, Colorado's Vehicle Inspection & Maintenance Program and remote sensing data collected using road-side instruments in multiple locations and calendar years in the United States. In addition, we conduct comparisons of MOVES predictions to fleet-wide emissions measured from tunnels. We also present details on the methodology used to conduct the MOVES model runs in comparing to the independent data.
Fermi-LAT upper limits on gamma-ray emission from colliding wind binaries
Werner, Michael; Reimer, O.; Reimer, A.; ...
2013-07-09
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, WRmore » 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.« less
Federal Register 2010, 2011, 2012, 2013, 2014
2011-07-22
... emissions inventories, monitoring, and modeling, to assure attainment and maintenance of the standards... NAAQS required the deployment of a system of new monitors to measure ambient levels of that new... requirements, including emissions inventories, monitoring, and modeling to assure attainment and maintenance of...
Evaluating the mitigation of greenhouse gas emissions and adaptation in dairy production.
USDA-ARS?s Scientific Manuscript database
Process-level modeling at the farm scale provides a tool for evaluating strategies for both mitigating greenhouse gas emissions and adapting to climate change. The Integrated Farm System Model (IFSM) simulates representative crop, beef or dairy farms over many years of weather to predict performance...
DEVELOPMENT OF AN EMPIRICAL MODEL OF METHANE EMISSIONS FROM LANDFILLS
The report gives results of a field study of 21 U.S. landfills with gas recovery systems, to gather information that can be used to develop an empirical model of methane (CH4) emissions. Site-specific information includes average CH4 recovery rate, landfill size, tons of refuse (...
Modelling the spatial distribution of SO2 and NOx emissions in Ireland.
de Kluizenaar, Y; Aherne, J; Farrell, E P
2001-01-01
The spatial distributions of sulphur dioxide (SO2) and nitrogen oxides (NOx) emissions are essential inputs to models of atmospheric transport and deposition. Information of this type is required for international negotiations on emission reduction through the critical load approach. High-resolution emission maps for the Republic of Ireland have been created using emission totals and a geographical information system, supported by surrogate statistics and landcover information. Data have been subsequently allocated to the EMEP 50 x 50-km grid, used in long-range transport models for the investigation of transboundary air pollution. Approximately two-thirds of SO2 emissions in Ireland emanate from two grid-squares. Over 50% of total SO2 emissions originate from one grid-square in the west of Ireland, where the largest point sources of SO2 are located. Approximately 15% of the total SO2 emissions originate from the grid-square containing Dublin. SO2 emission densities for the remaining areas are very low, < 1 t km-2 year-1 for most grid-squares. NOx emissions show a very similar distribution pattern. However, NOx emissions are more evenly spread over the country, as about 40% of total NOx emissions originate from road transport.
NASA Astrophysics Data System (ADS)
Hyer, E. J.; Reid, J. S.; Schmidt, C. C.; Giglio, L.; Prins, E.
2009-12-01
The diurnal cycle of fire activity is crucial for accurate simulation of atmospheric effects of fire emissions, especially at finer spatial and temporal scales. Estimating diurnal variability in emissions is also a critical problem for construction of emissions estimates from multiple sensors with variable coverage patterns. An optimal diurnal emissions estimate will use as much information as possible from satellite fire observations, compensate known biases in those observations, and use detailed theoretical models of the diurnal cycle to fill in missing information. As part of ongoing improvements to the Fire Location and Monitoring of Burning Emissions (FLAMBE) fire monitoring system, we evaluated several different methods of integrating observations with different temporal sampling. We used geostationary fire detections from WF_ABBA, fire detection data from MODIS, empirical diurnal cycles from TRMM, and simple theoretical diurnal curves based on surface heating. Our experiments integrated these data in different combinations to estimate the diurnal cycles of emissions for each location and time. Hourly emissions estimates derived using these methods were tested using an aerosol transport model. We present results of this comparison, and discuss the implications of our results for the broader problem of multi-sensor data fusion in fire emissions modeling.
Evaluations of in-use emission factors from off-road construction equipment
NASA Astrophysics Data System (ADS)
Cao, Tanfeng; Durbin, Thomas D.; Russell, Robert L.; Cocker, David R.; Scora, George; Maldonado, Hector; Johnson, Kent C.
2016-12-01
Gaseous and particle emissions from construction engines contribute an important fraction of the total air pollutants released into the atmosphere and are gaining increasing regulatory attention. Robust quantification of nitrogen oxides (NOx) and particulate matter (PM) emissions are necessary to inventory the contribution of construction equipment to atmospheric loadings. Theses emission inventories require emissions factors from construction equipment as a function of equipment type and modes of operation. While the development of portable emissions measurement systems (PEMS) has led to increased studies of construction equipment emissions, emissions data are still much more limited than for on-road vehicles. The goal of this research program was to obtain accurate in-use emissions data from a test fleet of newer construction equipment (model year 2002 or later) using a Code of Federal Requirements (CFR) compliant PEMS system. In-use emission measurements were made from twenty-seven pieces of construction equipment, which included four backhoes, six wheel loaders, four excavators, two scrapers (one with two engines), six bulldozers, and four graders. The engines ranged in model year from 2003 to 2012, in rated horsepower (hp) from 92 to 540 hp, and in hours of operation from 24 to 17,149 h. This is the largest study of off-road equipment emissions using 40 CFR part 1065 compliant PEMS equipment for all regulated gaseous and particulate emissions.
How much do electric drive vehicles matter to future U.S. emissions?
Babaee, Samaneh; Nagpure, Ajay S; DeCarolis, Joseph F
2014-01-01
Hybrid, plug-in hybrid, and battery electric vehicles--known collectively as electric drive vehicles (EDVs)--may represent a clean and affordable option to meet growing U.S. light duty vehicle (LDV) demand. The goal of this study is 2-fold: identify the conditions under which EDVs achieve high LDV market penetration in the U.S. and quantify the associated change in CO2, SO2, and NOX emissions through midcentury. We employ the Integrated MARKAL-EFOM System (TIMES), a bottom-up energy system model, along with a U.S. data set developed for this analysis. To characterize EDV deployment through 2050, varying assumptions related to crude oil and natural gas prices, a CO2 policy, a federal renewable portfolio standard, and vehicle battery cost were combined to form 108 different scenarios. Across these scenarios, oil prices and battery cost have the biggest effect on EDV deployment. The model results do not demonstrate a clear and consistent trend toward lower system-wide emissions as EDV deployment increases. In addition to the trade-off between lower tailpipe and higher electric sector emissions associated with plug-in vehicles, the scenarios produce system-wide emissions effects that often mask the effect of EDV deployment.
Greenhouse gas emissions of waste management processes and options: A case study.
de la Barrera, Belen; Hooda, Peter S
2016-07-01
Increasing concern about climate change is prompting organisations to mitigate their greenhouse gas emissions. Waste management activities also contribute to greenhouse gas emissions. In the waste management sector, there has been an increasing diversion of waste sent to landfill, with much emphasis on recycling and reuse to prevent emissions. This study evaluates the carbon footprint of the different processes involved in waste management systems, considering the entire waste management stream. Waste management data from the Royal Borough of Kingston upon Thames, London (UK), was used to estimate the carbon footprint for its (Royal Borough of Kingston upon Thames) current source segregation system. Second, modelled full and partial co-mingling scenarios were used to estimate carbon emissions from these proposed waste management approaches. The greenhouse gas emissions from the entire waste management system at Royal Borough of Kingston upon Thames were 12,347 t CO2e for the source-segregated scenario, and 11,907 t CO2e for the partial co-mingled model. These emissions amount to 203.26 kg CO2e t(-1) and 196.02 kg CO2e t(-1) municipal solid waste for source-segregated and partial co-mingled, respectively. The change from a source segregation fleet to a partial co-mingling fleet reduced the emissions, at least partly owing to a change in the number and type of vehicles. © The Author(s) 2016.
Quaassdorff, Christina; Borge, Rafael; Pérez, Javier; Lumbreras, Julio; de la Paz, David; de Andrés, Juan Manuel
2016-10-01
This paper presents the evaluation of emissions from vehicle operations in a domain of 300m×300m covering a complex urban roundabout with high traffic density in Madrid. Micro-level simulation was successfully applied to estimate the emissions on a scale of meters. Two programs were used: i) VISSIM to simulate the traffic on the square and to compute velocity-time profiles; and ii) VERSIT+micro through ENVIVER that uses VISSIM outputs to compute the related emissions at vehicle level. Data collection was achieved by a measurement campaign obtaining empirical data of vehicle flows and traffic intensities. Twelve simulations of different traffic situations (scenarios) were conducted, representing different hours from several days in a week and the corresponding NOX and PM10 emissions were estimated. The results show a general reduction on average speeds for higher intensities due to braking-acceleration patterns that contribute to increase the average emission factor and, therefore, the total emissions in the domain, especially on weekdays. The emissions are clearly related to traffic volume, although maximum emission scenario does not correspond to the highest traffic intensity due to congestion and variations in fleet composition throughout the day. These results evidence the potential that local measures aimed at alleviating congestion may have in urban areas to reduce emissions. In general, scenario-averaged emission factors estimated with the VISSIM-VERSIT+micro modelling system fitted well those from the average-speed model COPERT, used as a preliminary validation of the results. The largest deviations between these two models occur in those scenarios with more congestion. The design and resolution of the microscale modelling system allow to reflect the impact of actual traffic conditions on driving patterns and related emissions, making it useful for the design of mitigation measures for specific traffic hot-spots. Copyright © 2016 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Duran, P.; Holloway, T.; Brinkman, G.; Denholm, P.; Littlefield, C. M.
2011-12-01
Solar photovoltaics (PV) are an attractive technology because they can be locally deployed and tend to yield high production during periods of peak electric demand. These characteristics can reduce the need for conventional large-scale electricity generation, thereby reducing emissions of criteria air pollutants (CAPs) and improving ambient air quality with regard to such pollutants as nitrogen oxides, sulfur oxides and fine particulates. Such effects depend on the local climate, time-of-day emissions, available solar resources, the structure of the electric grid, and existing electricity production among other factors. This study examines the air quality impacts of distributed PV across the United States Eastern Interconnection. In order to accurately model the air quality impact of distributed PV in space and time, we used the National Renewable Energy Lab's (NREL) Regional Energy Deployment System (ReEDS) model to form three unique PV penetration scenarios in which new PV construction is distributed spatially based upon economic drivers and natural solar resources. Those scenarios are 2006 Eastern Interconnection business as usual, 10% PV penetration, and 20% PV penetration. With the GridView (ABB, Inc) dispatch model, we used historical load data from 2006 to model electricity production and distribution for each of the three scenarios. Solar PV electric output was estimated using historical weather data from 2006. To bridge the gap between dispatch and air quality modeling, we will create emission profiles for electricity generating units (EGUs) in the Eastern Interconnection from historical Continuous Emissions Monitoring System (CEMS) data. Via those emissions profiles, we will create hourly emission data for EGUs in the Eastern Interconnect for each scenario during 2006. Those data will be incorporated in the Community Multi-scale Air Quality (CMAQ) model using the Sparse Matrix Operator Kernel Emissions (SMOKE) model. Initial results indicate that PV penetration significantly reduces conventional peak electricity production and that, due to reduced emissions during periods of extremely active photochemistry, air quality could see benefits.
NASA Astrophysics Data System (ADS)
Liu, Yongqiang; Mamtimin, Ali; He, Qing
2014-05-01
Because land surface emissivity (ɛ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply assumption, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, 0.96 for soil and wetland in the Global and Regional Assimilation and Prediction System (GRAPES) Common Land Model (CoLM). This is the so-called emissivity assumption. Accurate broadband emissivity data are needed as model inputs to better simulate the land surface climate. It is demonstrated in this paper that the assumption of the emissivity induces errors in modeling the surface energy budget over Taklimakan Desert where ɛ is far smaller than original value. One feasible solution to this problem is to apply the accurate broadband emissivity into land surface models. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has routinely measured spectral emissivities in six thermal infrared bands. The empirical regression equations have been developed in this study to convert these spectral emissivities to broadband emissivity required by land surface models. In order to calibrate the regression equations, using a portable Fourier Transform infrared (FTIR) spectrometer instrument, crossing Taklimakan Desert along with highway from north to south, to measure the accurate broadband emissivity. The observed emissivity data show broadband ɛ around 0.89-0.92. To examine the impact of improved ɛ to radiative energy redistribution, simulation studies were conducted using offline CoLM. The results illustrate that large impacts of surface ɛ occur over desert, with changes up in surface skin temperature, as well as evident changes in sensible heat fluxes. Keywords: Taklimakan Desert, surface broadband emissivity, Fourier Transform infrared spectrometer, MODIS, CoLM
A model for inventory of ammonia emissions from agriculture in the Netherlands
NASA Astrophysics Data System (ADS)
Velthof, G. L.; van Bruggen, C.; Groenestein, C. M.; de Haan, B. J.; Hoogeveen, M. W.; Huijsmans, J. F. M.
2012-01-01
Agriculture is the major source of ammonia (NH 3). Methodologies are needed to quantify national NH 3 emissions and to identify the most effective options to mitigate NH 3 emissions. Generally, NH 3 emissions from agriculture are quantified using a nitrogen (N) flow approach, in which the NH 3 emission is calculated from the N flows and NH 3 emission factors. Because of the direct dependency between NH 3 volatilization and Total Ammoniacal N (TAN; ammonium-N + N compounds readily broken down to ammonium) an approach based on TAN is preferred to calculate NH 3 emission instead of an approach based on total N. A TAN-based NH 3-inventory model was developed, called NEMA (National Emission Model for Ammonia). The total N excretion and the fraction of TAN in the excreted N are calculated from the feed composition and N digestibility of the components. TAN-based emission factors were derived or updated for housing systems, manure storage outside housing, manure application techniques, N fertilizer types, and grazing. The NEMA results show that the total NH 3 emission from agriculture in the Netherlands in 2009 was 88.8 Gg NH 3-N, of which 50% from housing, 37% from manure application, 9% from mineral N fertilizer, 3% from outside manure storage, and 1% from grazing. Cattle farming was the dominant source of NH 3 in the Netherlands (about 50% of the total NH 3 emission). The NH 3 emission expressed as percentage of the excreted N was 22% of the excreted N for poultry, 20% for pigs, 15% for cattle, and 12% for other livestock, which is mainly related to differences in emissions from housing systems. The calculated ammonia emission was most sensitive to changes in the fraction of TAN in the excreted manure and to the emission factor of manure application. From 2011, NEMA will be used as official methodology to calculate the national NH 3 emission from agriculture in the Netherlands.
S. P. Urbanski; W. M. Hao; B. Nordgren
2011-01-01
Biomass burning emission inventories serve as critical input for atmospheric chemical transport models that are used to understand the role of biomass fires in the chemical composition of the atmosphere, air quality, and the climate system. Significant progress has been achieved in the development of regional and global biomass burning emission inventories over the...
NASA Astrophysics Data System (ADS)
Nergui, T.; Lee, Y.; Chung, S. H.; Lamb, B. K.; Yokelson, R. J.; Barsanti, K.
2017-12-01
A number of chamber and field measurements have shown that atmospheric organic aerosols and their precursors produced from wildfires are significantly underestimated in the emission inventories used for air quality models for various applications such as regulatory strategy development, impact assessments of air pollutants, and air quality forecasting for public health. The AIRPACT real-time air quality forecasting system consistently underestimates surface level fine particulate matter (PM2.5) concentrations in the summer at both urban and rural locations in the Pacific Northwest, primarily result of errors in organic particulate matter. In this work, we implement updated chemical speciation and emission factors based on FLAME-IV (Fourth Fire Lab at Missoula Experiment) and other measurements in the Blue-Sky fire emission model and the SMOKE emission preprocessor; and modified parameters for the secondary organic aerosol (SOA) module in CMAQ chemical transport model of the AIRPACT modeling system. Simulation results from CMAQ version 5.2 which has a better treatment for anthropogenic SOA formation (as a base case) and modified parameterization used for fire emissions and chemistry in the model (fire-soa case) are evaluated against airborne measurements downwind of the Big Windy Complex Fire and the Colockum Tarps Fire, both of which occurred in the Pacific Northwest in summer 2013. Using the observed aerosol chemical composition and mass loadings for organics, nitrate, sulfate, ammonium, and chloride from aircraft measurements during the Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS) and the Biomass Burning Observation Project (BBOP), we assess how new knowledge gained from wildfire measurements improve model predictions for SOA and its contribution to the total mass of PM2.5 concentrations.
Reducing CO2 emissions and energy consumption of heat-integrated distillation systems.
Gadalla, Mamdouh A; Olujic, Zarko; Jansens, Peter J; Jobson, Megan; Smith, Robin
2005-09-01
Distillation systems are energy and power intensive processes and contribute significantly to the greenhouse gases emissions (e.g. carbon dioxide). Reducing CO2 emissions is an absolute necessity and expensive challenge to the chemical process industries in orderto meetthe environmental targets as agreed in the Kyoto Protocol. A simple model for the calculation of CO2 emissions from heat-integrated distillation systems is introduced, considering typical process industry utility devices such as boilers, furnaces, and turbines. Furnaces and turbines consume large quantities of fuels to provide electricity and process heats. As a result, they produce considerable amounts of CO2 gas to the atmosphere. Boilers are necessary to supply steam for heating purposes; besides, they are also significant emissions contributors. The model is used in an optimization-based approach to optimize the process conditions of an existing crude oil atmospheric tower in order to reduce its CO2 emissions and energy demands. It is also applied to generate design options to reduce the emissions from a novel internally heat-integrated distillation column (HIDiC). A gas turbine can be integrated with these distillation systems for larger emissions reduction and further energy savings. Results show that existing crude oil installations can save up to 21% in energy and 22% in emissions, when the process conditions are optimized. Additionally, by integrating a gas turbine, the total emissions can be reduced further by 48%. Internal heat-integrated columns can be a good alternative to conventional heat pump and other energy intensive close boiling mixtures separations. Energy savings can reach up to 100% with respect to reboiler heat requirements. Emissions of these configurations are cut down by up to 83%, compared to conventional units, and by 36%, with respect to heat pump alternatives. Importantly, cost savings and more profit are gained in parallel to emissions minimization.
Chen, Dan; Wang, Cong; Shen, Jianlin; Li, Yong; Wu, Jinshui
2018-04-01
Paddy soil plays an essential role in contributing to the emission of methane (CH 4 ), a potent greenhouse gas, to the atmosphere. This study aimed to demonstrate the effects of straw incorporation and straw-derived biochar amendment on CH 4 emissions from double-rice cropping fields and to explore their potential mechanisms based on in-situ field measurements conducted for a period of three years (2012-2014) and model analysis. The results showed that the improved soil aeration due to biochar amendment resulted in low CH 4 emissions and that sufficient substrate carbon availability in straw amendment treatments caused high CH 4 emissions. The newly developed CH 4 emission module for the water and nitrogen management model (WNMM), a process-based biophysical model, performed well when simulating both daily CH 4 fluxes and the annual cumulative CH 4 emissions under straw incorporation and biochar amendment. Results of our study indicate that the model has a great potential for upscaling and could benefit mechanism analyses about the factors regulating CH 4 emissions. Application of biochar into paddy fields provides a great opportunity to reduce CH 4 emissions, and the decrease in CH 4 emissions following biochar amendment with repeated crop cycles would sustain for a prolonged period. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Reidy, B.; Webb, J.; Misselbrook, T. H.; Menzi, H.; Luesink, H. H.; Hutchings, N. J.; Eurich-Menden, B.; Döhler, H.; Dämmgen, U.
Six N-flow models, used to calculate national ammonia (NH 3) emissions from agriculture in different European countries, were compared using standard data sets. Scenarios for litter-based systems were run separately for beef cattle and for broilers, with three different levels of model standardisation: (a) standardized inputs to all models (FF scenario); (b) standard N excretion, but national values for emission factors (EFs) (FN scenario); (c) national values for N excretion and EFs (NN scenario). Results of the FF scenario for beef cattle produced very similar estimates of total losses of total ammoniacal-N (TAN) (±6% of the mean total), but large differences in NH 3 emissions (±24% of the mean). These differences arose from the different approaches to TAN immobilization in litter, other N losses and mineralization in the models. As a result of those differences estimates of TAN available at spreading differed by a factor of almost 3. Results of the FF scenario for broilers produced a range of estimates of total changes in TAN (±9% of the mean total), and larger differences in the estimate of NH 3 emissions (±17% of the mean). The different approaches among the models to TAN immobilization, other N losses and mineralization, produced estimates of TAN available at spreading which differed by a factor of almost 1.7. The differences in estimates of NH 3 emissions decreased as estimates of immobilization and other N losses increased. Since immobilization and denitrification depend also on the C:N ratio in manure, there would be advantages to include C flows in mass-flow models. This would also provide an integrated model for the estimation of emissions of methane, non-methane VOCs and carbon dioxide. Estimation of these would also enable an estimate of mass loss, calculation of the N and TAN concentrations in litter-based manures and further validation of model outputs.
John B Kim; Erwan Monier; Brent Sohngen; G Stephen Pitts; Ray Drapek; James McFarland; Sara Ohrel; Jefferson Cole
2016-01-01
We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a...
Implications of near-term coal power plant retirement for SO2 and NOX and life cycle GHG emissions.
Venkatesh, Aranya; Jaramillo, Paulina; Griffin, W Michael; Matthews, H Scott
2012-09-18
Regulations monitoring SO(2), NO(X), mercury, and other metal emissions in the U.S. will likely result in coal plant retirement in the near-term. Life cycle assessment studies have previously estimated the environmental benefits of displacing coal with natural gas for electricity generation, by comparing systems that consist of individual natural gas and coal power plants. However, such system comparisons may not be appropriate to analyze impacts of coal plant retirement in existing power fleets. To meet this limitation, simplified economic dispatch models for PJM, MISO, and ERCOT regions are developed in this study to examine changes in regional power plant dispatch that occur when coal power plants are retired. These models estimate the order in which existing power plants are dispatched to meet electricity demand based on short-run marginal costs, with cheaper plants being dispatched first. Five scenarios of coal plant retirement are considered: retiring top CO(2) emitters, top NO(X) emitters, top SO(2) emitters, small and inefficient plants, and old and inefficient plants. Changes in fuel use, life cycle greenhouse gas emissions (including uncertainty), and SO(2) and NO(X) emissions are estimated. Life cycle GHG emissions were found to decrease by less than 4% in almost all scenarios modeled. In addition, changes in marginal damage costs due to SO(2), and NO(X) emissions are estimated using the county level marginal damage costs reported in the Air Pollution Emissions Experiments and Policy (APEEP) model, which are a proxy for measuring regional impacts of SO(2) and NO(X) emissions. Results suggest that location specific parameters should be considered within environmental policy frameworks targeting coal plant retirement, to account for regional variability in the benefits of reducing the impact of SO(2) and NO(X) emissions.
Albanito, Fabrizio; Lebender, Ulrike; Cornulier, Thomas; Sapkota, Tek B; Brentrup, Frank; Stirling, Clare; Hillier, Jon
2017-03-10
There has been much debate about the uncertainties associated with the estimation of direct and indirect agricultural nitrous oxide (N 2 O) emissions in developing countries and in particular from tropical regions. In this study, we report an up-to-date review of the information published in peer-review journals on direct N 2 O emissions from agricultural systems in tropical and sub-tropical regions. We statistically analyze net-N 2 O-N emissions to estimate tropic-specific annual N 2 O emission factors (N 2 O-EFs) using a Generalized Additive Mixed Model (GAMM) which allowed the effects of multiple covariates to be modelled as linear or smooth non-linear continuous functions. Overall the mean N 2 O-EF was 1.2% for the tropics and sub-tropics, thus within the uncertainty range of IPCC-EF. On a regional basis, mean N 2 O-EFs were 1.4% for Africa, 1.1%, for Asia, 0.9% for Australia and 1.3% for Central &South America. Our annual N 2 O-EFs, estimated for a range of fertiliser rates using the available data, do not support recent studies hypothesising non-linear increase N 2 O-EFs as a function of applied N. Our findings highlight that in reporting annual N 2 O emissions and estimating N 2 O-EFs, particular attention should be paid in modelling the effect of study length on response of N 2 O.
Albanito, Fabrizio; Lebender, Ulrike; Cornulier, Thomas; Sapkota, Tek B.; Brentrup, Frank; Stirling, Clare; Hillier, Jon
2017-01-01
There has been much debate about the uncertainties associated with the estimation of direct and indirect agricultural nitrous oxide (N2O) emissions in developing countries and in particular from tropical regions. In this study, we report an up-to-date review of the information published in peer-review journals on direct N2O emissions from agricultural systems in tropical and sub-tropical regions. We statistically analyze net-N2O-N emissions to estimate tropic-specific annual N2O emission factors (N2O-EFs) using a Generalized Additive Mixed Model (GAMM) which allowed the effects of multiple covariates to be modelled as linear or smooth non-linear continuous functions. Overall the mean N2O-EF was 1.2% for the tropics and sub-tropics, thus within the uncertainty range of IPCC-EF. On a regional basis, mean N2O-EFs were 1.4% for Africa, 1.1%, for Asia, 0.9% for Australia and 1.3% for Central & South America. Our annual N2O-EFs, estimated for a range of fertiliser rates using the available data, do not support recent studies hypothesising non-linear increase N2O-EFs as a function of applied N. Our findings highlight that in reporting annual N2O emissions and estimating N2O-EFs, particular attention should be paid in modelling the effect of study length on response of N2O. PMID:28281637
NASA Astrophysics Data System (ADS)
Albanito, Fabrizio; Lebender, Ulrike; Cornulier, Thomas; Sapkota, Tek B.; Brentrup, Frank; Stirling, Clare; Hillier, Jon
2017-03-01
There has been much debate about the uncertainties associated with the estimation of direct and indirect agricultural nitrous oxide (N2O) emissions in developing countries and in particular from tropical regions. In this study, we report an up-to-date review of the information published in peer-review journals on direct N2O emissions from agricultural systems in tropical and sub-tropical regions. We statistically analyze net-N2O-N emissions to estimate tropic-specific annual N2O emission factors (N2O-EFs) using a Generalized Additive Mixed Model (GAMM) which allowed the effects of multiple covariates to be modelled as linear or smooth non-linear continuous functions. Overall the mean N2O-EF was 1.2% for the tropics and sub-tropics, thus within the uncertainty range of IPCC-EF. On a regional basis, mean N2O-EFs were 1.4% for Africa, 1.1%, for Asia, 0.9% for Australia and 1.3% for Central & South America. Our annual N2O-EFs, estimated for a range of fertiliser rates using the available data, do not support recent studies hypothesising non-linear increase N2O-EFs as a function of applied N. Our findings highlight that in reporting annual N2O emissions and estimating N2O-EFs, particular attention should be paid in modelling the effect of study length on response of N2O.
NASA Astrophysics Data System (ADS)
de Oliveira Silva, R.; Barioni, L. G.; Hall, J. A. J.; Folegatti Matsuura, M.; Zanett Albertini, T.; Fernandes, F. A.; Moran, D.
2016-05-01
Recent debate about agricultural greenhouse gas emissions mitigation highlights trade-offs inherent in the way we produce and consume food, with increasing scrutiny on emissions-intensive livestock products. Although most research has focused on mitigation through improved productivity, systemic interactions resulting from reduced beef production at the regional level are still unexplored. A detailed optimization model of beef production encompassing pasture degradation and recovery processes, animal and deforestation emissions, soil organic carbon (SOC) dynamics and upstream life-cycle inventory was developed and parameterized for the Brazilian Cerrado. Economic return was maximized considering two alternative scenarios: decoupled livestock-deforestation (DLD), assuming baseline deforestation rates controlled by effective policy; and coupled livestock-deforestation (CLD), where shifting beef demand alters deforestation rates. In DLD, reduced consumption actually leads to less productive beef systems, associated with higher emissions intensities and total emissions, whereas increased production leads to more efficient systems with boosted SOC stocks, reducing both per kilogram and total emissions. Under CLD, increased production leads to 60% higher emissions than in DLD. The results indicate the extent to which deforestation control contributes to sustainable intensification in Cerrado beef systems, and how alternative life-cycle analytical approaches result in significantly different emission estimates.
Bell, Matthew J.; Cullen, Brendan R.; Eckard, Richard J.
2012-01-01
Simple Summary Livestock production systems and the agricultural industries in general face challenges to meet the global demand for food, whilst also minimizing their environmental impact through the production of greenhouse gas (GHG) emissions. Livestock grazing systems in southern Australia are low input and reliant on pasture as a low-cost source of feed. The balance between productivity and GHG emission intensity of beef cow-calf grazing systems was studied at sites chosen to represent a range of climatic zones, soil and pasture types. While the climatic and edaphic characteristics of a location may impact on the emissions from a grazing system, management to efficiently use pasture can reduce emissions per unit product. Abstract A biophysical whole farm system model was used to simulate the interaction between the historical climate, soil and pasture type at sites in southern Australia and assess the balance between productivity and greenhouse gas emissions (expressed in carbon dioxide equivalents, CO2-eq.) intensity of beef cow-calf grazing systems. Four sites were chosen to represent a range of climatic zones, soil and pasture types. Poorer feed quality and supply limited the annual carrying capacity of the kikuyu pasture compared to phalaris pastures, with an average long-term carrying capacity across sites estimated to be 0.6 to 0.9 cows/ha. A relative reduction in level of feed intake to productivity of calf live weight/ha at weaning by feeding supplementary feed reduced the average CO2-eq. emissions/kg calf live weight at weaning of cows on the kikuyu pasture (18.4 and 18.9 kg/kg with and without supplementation, respectively), whereas at the other sites studied an increase in intake level to productivity and emission intensity was seen (between 10.4 to 12.5 kg/kg without and with supplementary feed, respectively). Enteric fermentationand nitrous oxide emissions from denitrification were the main sources of annual variability in emissions intensity, particularly at the lower rainfall sites. Emissions per unit product of low input systems can be minimized by efficient utilization of pasture to maximize the annual turnoff of weaned calves and diluting resource input per unit product. PMID:26487163
NASA Astrophysics Data System (ADS)
Williams, M.; Beevers, S.; Lott, M. C.; Kitwiroon, N.
2016-12-01
This paper presents a preliminary analysis of different pathways to meet the UK Climate Change Act target for 2050, of an 80% reduction in carbon dioxide equivalent emissions on a base year of 1990. The pathways can result in low levels of air pollution emissions through the use of renewables and nuclear power. But large increases in biomass burning and the continued use of diesel cars they can result in larger air quality impacts. The work evaluated the air quality impacts in several pathways using an energy system optimisation model (UK TIMES) and a chemical transport model (CMAQ). The work described in this paper goes beyond the `damage cost' approach where only emissions in each are assessed. In this work we used scenarios produced by the UK TIMES model which we converted into air pollution emissions. Emissions of ammonia from agriculture are not attributed to the energy system and are thus not captured by energy system models, yet are crucial in forming PM2.5, acknowledged to be currently the most important pollutant associated with premature deaths. Our model includes these emissions and other non-energy sources of hydrocarbons which lead to the formation of ozone, another significant cause of air pollution health impacts. A key policy issue is how much biogenic hydrocarbons contribute to ozone formation compared with man-made emissions. We modelled pollution concentrations at a resolution of 7 km across the UK and at 2km in urban areas. These results allow us to estimate changes in premature mortality and morbidity associated with the changes in air pollution and subsequently the economic cost of the impacts on public health. The work shows that in the `clean' scenario, urban exposures to particles (PM2.5) and NO2 could decrease by very large amounts, but ozone exposures are likely to increase without further significant reductions world-wide. Large increases in biomass use however could lead to increases in urban levels of carcinogens and primary PM.
[Real world instantaneous emission simulation for light-duty diesel vehicle].
Huang, Cheng; Chen, Chang-Hong; Dai, Pu; Li, Li; Huang, Hai-Ying; Cheng, Zhen; Jia, Ji-Hong
2008-10-01
Core architecture and input parameters of CMEM model were introduced to simulation the second by second vehicle emission rate on real world by taking a light-duty diesel car as a case. On-board test data by a portable emission measurement system were then used to validate the simulation results. Test emission factors of CO, THC, NO(x) and CO2 were respectively 0.81, 0.61, 2.09, and 193 g x km(-1), while calculated emission factors were 0.75, 0.47, 2.47, and 212 g x km(-1). The correlation coefficients reached 0.69, 0.69, 0.75, and 0.72. Simulated instantaneous emissions of the light duty diesel vehicle by CMEM model were strongly coherent with the transient driving cycle. By analysis, CO, THC, NO(x), and CO2 emissions would be reduced by 50%, 47%, 45%, and 44% after improving the traffic situation at the intersection. The result indicated that it is necessary and feasible to simulate the instantaneous emissions of mixed vehicle fleet in some typical traffic areas by the micro-scale vehicle emission model.
Emission Data For Climate-Chemistry Interactions
NASA Astrophysics Data System (ADS)
Smith, S. J.
2012-12-01
Data on anthropogenic and natural emissions of reactive species are a critical input for studies of atmospheric chemistry and climate. The availability and characteristics of anthropogenic emissions data that can be used for such studies are reviewed and pathways for future work discuss Global and regional datasets for historical and future emissions are available, but their characteristics and applicability for specific studies differ. For the first time, a coordinated set of historical emissions (Lamarque et al 2010) and the future projections (van Vuurren et al. 2011) have been developed for use in the CMIP5 and ACCMIP long-term simulation comparison projects. These data have decadal resolution and were designed for long-term, global simulations. These data, however, lack finer-scale spatial and temporal detail that might be needed for some studies. Robust and timely updates of emissions data is generally lacking, although recent updates will be presented. While historical emission data is often treated as known, emissions are uncertain, even though this uncertainty is rarely quantified. Uncertainty varies by species and location. Inverse modeling is starting to indicate where emission data may be uncertain, which opens the way to improving these data overall. Further interaction between the chemistry modeling and inventory development communities are needed. Future projections are intrinsically uncertain, and while institutions and processes are in place to develop and review long-term century-scale scenarios, a need has remained for a wider range in shorter-term (e.g., several decade) projections. Emissions and scenario development communities have been working to fill this need. Communication across disciplines of the assumptions embedded in emissions projections remains a challenge. Atmospheric chemistry models are a central tool needed for studying chemistry-climate interactions. Simpler models, however, are also needed in order to examine interactions between different physical systems and also between the physical and human systems. Statistical models of system responses are particularly needed both to parameterize interactions in models that cannot simulate particular processes directly, and also to represent uncertainty. Coordinated model experiments are necessary to provide the information needed to develop these representations (i.e. Wild et al 2011). Lamarque, J. F, et al. (2010) Historical (1850-2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application. Atmospheric Chemistry and Physics 10 pp. 7017-7039. doi:10.5194/acp-10-7017-2010 Van Vuuren, D, JA Edmonds, M Kainuma, K Riahi, AM Thomson, KA Hibbard, G Hurtt, T Kram, V Krey, JF Lamarque, matsui, M Meinhausen, N Nakicenovic, SJ Smith, and SK Rose. 2011. "The Representative Concentration Pathways: An Overview." Climatic Change 109 (1-2) 5-31. doi: 10.1007/s10584-011-0148-z. Wild, O., et al. (2012) Modelling future changes in surface ozone: A parameterized approach. Atmos. Chem. Phys., 12, 2037-2054, doi:10.5194/acp-12-2037-2012.
Energy Efficiency and Environmental Impact Analyses of Supermarket Refrigeration Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fricke, Brian A; Bansal, Pradeep; Zha, Shitong
This paper presents energy and life cycle climate performance (LCCP) analyses of a variety of supermarket refrigeration systems to identify designs that exhibit low environmental impact and high energy efficiency. EnergyPlus was used to model refrigeration systems in a variety of climate zones across the United States. The refrigeration systems that were modeled include the traditional multiplex DX system, cascade systems with secondary loops and the transcritical CO2 system. Furthermore, a variety of refrigerants were investigated, including R-32, R-134a, R-404A, R-1234yf, R-717, and R-744. LCCP analysis was used to determine the direct and indirect carbon dioxide emissions resulting from themore » operation of the various refrigeration systems over their lifetimes. Our analysis revealed that high-efficiency supermarket refrigeration systems may result in up to 44% less energy consumption and 78% reduced carbon dioxide emissions compared to the baseline multiplex DX system. This is an encouraging result for legislators, policy makers and supermarket owners to select low emission, high-efficiency commercial refrigeration system designs for future retrofit and new projects.« less
NASA Astrophysics Data System (ADS)
Ye, X.; Lauvaux, T.; Kort, E. A.; Lin, J. C.; Oda, T.; Yang, E.; Wu, D.
2016-12-01
Rapid economic development has given rise to a steady increase of global carbon emissions, which have accumulated in the atmosphere for the past 200 years. Urbanization has concentrated about 70% of the global fossil-fuel CO2 emissions in large metropolitan areas distributed around the world, which represents the most significant anthropogenic contribution to climate change. However, highly uncertain quantifications of urban CO2 emissions are commonplace for numerous cities because of poorly-documented inventories of energy consumption. Therefore, accurate estimates of carbon emissions from global observing systems are a necessity if mitigation strategies are meant to be implemented at global scales. Space-based observations of total column averaged CO2 concentration (XCO2) provide a very promising and powerful tool to quantify urban CO2 fluxes. For the first time, measurements from the Orbiting Carbon Observatory 2 (OCO-2) mission are assimilated in a high resolution inverse modeling system to quantify fossil-fuel CO2 emissions of multiple cities around the globe. The Open-source Data Inventory for Anthropogenic CO2 (ODIAC) emission inventory is employed as a first guess, while the atmospheric transport is simulated using the WRF-Chem model at 1-km resolution. Emission detection and quantification is performed with an Ensemble Kalman Filter method. We demonstrate here the potential of the inverse approach for assimilating thousands of OCO-2 retrievals along tracks near metropolitan areas. We present the detection potential of the system with real-case applications near power plants and present inverse emissions using actual OCO-2 measurements on various urban landscapes. Finally, we will discuss the potential of OCO-2-like satellite instruments for monitoring temporal variations of fossil-fuel CO2 emissions over multiple years, which can provide valuable insights for future satellite observation strategies.
NASA Astrophysics Data System (ADS)
Williams, Richard; Roussenov, Vassil; Goodwin, Philip; Resplandy, Laure; Bopp, Laurent
2017-04-01
Insight into how to avoid dangerous climate may be obtained from Earth system model projections, which reveal a near-linear dependence of global-mean surface warming on cumulative carbon emissions. This dependence of surface warming on carbon emissions is interpreted in terms of a product of three terms: the dependence of surface warming on radiative forcing, the fractional radiative forcing contribution from atmospheric CO2 and the dependence of radiative forcing from atmospheric CO2 on cumulative carbon emissions. Mechanistically each of these dependences varies, respectively, with ocean heat uptake, the CO2 and non-CO2 radiative forcing, and the ocean and terrestrial uptake of carbon. An ensemble of 9 Earth System models forced by up to 4 Representative Concentration Pathways are diagnosed. In all cases, the dependence of surface warming on carbon emissions evolves primarily due to competing effects of heat and carbon uptake over the upper ocean: there is a reduced effect of radiative forcing from CO2 due to ocean carbon uptake, which is partly compensated by enhanced surface warming due to a reduced effect of ocean heat uptake. There is a wide spread in the dependence of surface warming on carbon emissions, undermining the ability to identify the maximum permitted carbon emission to avoid dangerous climate. Our framework reveals how uncertainty in the future warming trend is high over the next few decades due to relatively high uncertainties in ocean heat uptake, non-CO2 radiative forcing and the undersaturation of carbon in the ocean.
NASA Astrophysics Data System (ADS)
Sofiev, Mikhail; Soares, Joana; Kouznetsov, Rostislav; Vira, Julius; Prank, Marje
2016-04-01
Top-down emission estimation via inverse dispersion modelling is used for various problems, where bottom-up approaches are difficult or highly uncertain. One of such areas is the estimation of emission from wild-land fires. In combination with dispersion modelling, satellite and/or in-situ observations can, in principle, be used to efficiently constrain the emission values. This is the main strength of the approach: the a-priori values of the emission factors (based on laboratory studies) are refined for real-life situations using the inverse-modelling technique. However, the approach also has major uncertainties, which are illustrated here with a few examples of the Integrated System for wild-land Fires (IS4FIRES). IS4FIRES generates the smoke emission and injection profile from MODIS and SEVIRI active-fire radiative energy observations. The emission calculation includes two steps: (i) initial top-down calibration of emission factors via inverse dispersion problem solution that is made once using training dataset from the past, (ii) application of the obtained emission coefficients to individual-fire radiative energy observations, thus leading to bottom-up emission compilation. For such a procedure, the major classes of uncertainties include: (i) imperfect information on fires, (ii) simplifications in the fire description, (iii) inaccuracies in the smoke observations and modelling, (iv) inaccuracies of the inverse problem solution. Using examples of the fire seasons 2010 in Russia, 2012 in Eurasia, 2007 in Australia, etc, it is pointed out that the top-down system calibration performed for a limited number of comparatively moderate cases (often the best-observed ones) may lead to errors in application to extreme events. For instance, the total emission of 2010 Russian fires is likely to be over-estimated by up to 50% if the calibration is based on the season 2006 and fire description is simplified. Longer calibration period and more sophisticated parameterization (including the smoke injection model and distinguishing all relevant vegetation types) can improve the predictions. The other significant parameter, so far weakly addressed in fire emission inventories, is the size spectrum of the emitted aerosols. Direct size-resolving measurements showed, for instance, that smoke from smouldering fires has smaller particles as compares with smoke from flaming fires. Due to dependence of the smoke optical thickness on the size distribution, such variability can lead to significant changes in the top-down calibration step. Experiments with IS4FIRES-SILAM system manifested up to a factor of two difference in AOD, depending on the assumption on particle spectrum.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Simons, Carl A.
1988-06-01
One major objective of this study was to compare several woodstove particulate emission sampling methods under laboratory and in-situ conditions. The laboratory work compared the EPA Method 5H, EPA Method 5G, and OMNI Automated Woodstove Emission Sampler (AWES)/Data LOG'r particulate emission sampling systems. A second major objective of the study was to evaluate the performance of two integral catalytic, two low emission non-catalytic, and two conventional technology woodstoves under in-situ conditions with AWES/Data LOG'r system. The AWES/Data LOG'r and EPA Method 5G sampling systems were also compared in an in-situ test on one of the integral catalytic woodstove models. 7more » figs., 12 tabs.« less
Estimating Lightning NOx Emissions for Regional Air Quality Modeling
NASA Astrophysics Data System (ADS)
Holloway, T.; Scotty, E.; Harkey, M.
2014-12-01
Lightning emissions have long been recognized as an important source of nitrogen oxides (NOx) on a global scale, and an essential emission component for global atmospheric chemistry models. However, only in recent years have regional air quality models incorporated lightning NOx emissions into simulations. The growth in regional modeling of lightning emissions has been driven in part by comparisons with satellite-derived estimates of column NO2, especially from the Ozone Monitoring Instrument (OMI) aboard the Aura satellite. We present and evaluate a lightning inventory for the EPA Community Multiscale Air Quality (CMAQ) model. Our approach follows Koo et al. [2010] in the approach to spatially and temporally allocating a given total value based on cloud-top height and convective precipitation. However, we consider alternate total NOx emission values (which translate into alternate lightning emission factors) based on a review of the literature and performance evaluation against OMI NO2 for July 2007 conditions over the U.S. and parts of Canada and Mexico. The vertical distribution of lightning emissions follow a bimodal distribution from Allen et al. [2012] calculated over 27 vertical model layers. Total lightning NO emissions for July 2007 show the highest above-land emissions in Florida, southeastern Texas and southern Louisiana. Although agreement with OMI NO2 across the domain varied significantly depending on lightning NOx assumptions, agreement among the simulations at ground-based NO2 monitors from the EPA Air Quality System database showed no meaningful sensitivity to lightning NOx. Emissions are compared with prior studies, which find similar distribution patterns, but a wide range of calculated magnitudes.
A sustainable manufacturing system design: A fuzzy multi-objective optimization model.
Nujoom, Reda; Mohammed, Ahmed; Wang, Qian
2017-08-10
In the past decade, there has been a growing concern about the environmental protection in public society as governments almost all over the world have initiated certain rules and regulations to promote energy saving and minimize the production of carbon dioxide (CO 2 ) emissions in many manufacturing industries. The development of sustainable manufacturing systems is considered as one of the effective solutions to minimize the environmental impact. Lean approach is also considered as a proper method for achieving sustainability as it can reduce manufacturing wastes and increase the system efficiency and productivity. However, the lean approach does not include environmental waste of such as energy consumption and CO 2 emissions when designing a lean manufacturing system. This paper addresses these issues by evaluating a sustainable manufacturing system design considering a measurement of energy consumption and CO 2 emissions using different sources of energy (oil as direct energy source to generate thermal energy and oil or solar as indirect energy source to generate electricity). To this aim, a multi-objective mathematical model is developed incorporating the economic and ecological constraints aimed for minimization of the total cost, energy consumption, and CO 2 emissions for a manufacturing system design. For the real world scenario, the uncertainty in a number of input parameters was handled through the development of a fuzzy multi-objective model. The study also addresses decision-making in the number of machines, the number of air-conditioning units, and the number of bulbs involved in each process of a manufacturing system in conjunction with a quantity of material flow for processed products. A real case study was used for examining the validation and applicability of the developed sustainable manufacturing system model using the fuzzy multi-objective approach.
Pulsar Emission Geometry and Accelerating Field Strength
NASA Technical Reports Server (NTRS)
DeCesar, Megan E.; Harding, Alice K.; Miller, M. Coleman; Kalapotharakos, Constantinos; Parent, Damien
2012-01-01
The high-quality Fermi LAT observations of gamma-ray pulsars have opened a new window to understanding the generation mechanisms of high-energy emission from these systems, The high statistics allow for careful modeling of the light curve features as well as for phase resolved spectral modeling. We modeled the LAT light curves of the Vela and CTA I pulsars with simulated high-energy light curves generated from geometrical representations of the outer gap and slot gap emission models. within the vacuum retarded dipole and force-free fields. A Markov Chain Monte Carlo maximum likelihood method was used to explore the phase space of the magnetic inclination angle, viewing angle. maximum emission radius, and gap width. We also used the measured spectral cutoff energies to estimate the accelerating parallel electric field dependence on radius. under the assumptions that the high-energy emission is dominated by curvature radiation and the geometry (radius of emission and minimum radius of curvature of the magnetic field lines) is determined by the best fitting light curves for each model. We find that light curves from the vacuum field more closely match the observed light curves and multiwavelength constraints, and that the calculated parallel electric field can place additional constraints on the emission geometry
Federal Register 2010, 2011, 2012, 2013, 2014
2012-03-27
... Integrated Routing System-- NIRS].'' The FAA developed the AEDT 2a to model aircraft noise, fuel burn, and... operations schedule. These data are used to compute aircraft noise, fuel burn and emissions simultaneously... DEPARTMENT OF TRANSPORTATION Federal Aviation Administration Air Traffic Noise, Fuel Burn, and...
Uncertainties in key elements of emissions and meteorology inputs to air quality models (AQMs) can range from 50 to 100% with some areas of emissions uncertainty even higher (Russell and Dennis, 2000). Uncertainties in the chemical mechanisms are thought to be smaller (Russell an...
NASA Astrophysics Data System (ADS)
Colarco, P. R.; Rocha Lima, A.; Darmenov, A.; Bloecker, C.
2017-12-01
Mineral dust aerosols scatter and absorb solar and infrared radiation, impacting the energy budget of the Earth system which in turns feeds back on the dynamical processes responsible for mobilization of dust in the first place. In previous work with radiatively interactive aerosols in the NASA Goddard Earth Observing System global model (GEOS-5) we found a positive feedback between dust absorption and emissions. Emissions were the largest for the highest shortwave absorption considered, which additionally produced simulated dust transport in the best agreement with observations. The positive feedback found was in contrast to other modeling studies which instead found a negative feedback, where the impact of dust absorption was to stabilize the surface levels of the atmosphere and so reduce wind speeds. A key difference between our model and other models was that in GEOS-5 we simulated generally larger dust particles, with correspondingly larger infrared absorption that led to a pronounced difference in the diurnal cycle of dust emissions versus simulations where these long wave effects were not considered. In this paper we seek to resolve discrepancies between our previous simulations and those of other modeling groups. We revisit the question of dust radiative feedback on emissions with a recent version of the GEOS-5 system running at a higher spatial resolution and including updates to the parameterizations for dust mobilization, initial dust particle size distribution, loss processes, and radiative transfer, and identify key uncertainties that remain based on dust optical property assumptions.
Bulk energy storage increases United States electricity system emissions.
Hittinger, Eric S; Azevedo, Inês M L
2015-03-03
Bulk energy storage is generally considered an important contributor for the transition toward a more flexible and sustainable electricity system. Although economically valuable, storage is not fundamentally a "green" technology, leading to reductions in emissions. We model the economic and emissions effects of bulk energy storage providing an energy arbitrage service. We calculate the profits under two scenarios (perfect and imperfect information about future electricity prices), and estimate the effect of bulk storage on net emissions of CO2, SO2, and NOx for 20 eGRID subregions in the United States. We find that net system CO2 emissions resulting from storage operation are nontrivial when compared to the emissions from electricity generation, ranging from 104 to 407 kg/MWh of delivered energy depending on location, storage operation mode, and assumptions regarding carbon intensity. Net NOx emissions range from -0.16 (i.e., producing net savings) to 0.49 kg/MWh, and are generally small when compared to average generation-related emissions. Net SO2 emissions from storage operation range from -0.01 to 1.7 kg/MWh, depending on location and storage operation mode.
Global assessment of shipping emissions in 2015 on a high spatial and temporal resolution
NASA Astrophysics Data System (ADS)
Johansson, Lasse; Jalkanen, Jukka-Pekka; Kukkonen, Jaakko
2017-10-01
We present a comprehensive global shipping emission inventory and the global activities of ships for the year 2015. The emissions were evaluated using the Ship Traffic Emission Assessment Model (STEAM3), which uses Automatic Identification System data to describe the traffic activities of ships. We have improved the model regarding (i) the evaluation of the missing technical specifications of ships, and (ii) the treatment of shipping activities in case of sparse satellite AIS-data. We have developed a model for the collection and processing of available information on the technical specifications, using data assimilation techniques. We have also developed a path regeneration model that constructs, whenever necessary, the detailed geometry of the ship routes. The presented results for fuel consumption were qualitatively in agreement both with those in the 3rd Greenhouse Gas Study of the International Maritime Organisation and those reported by the International Energy Agency. We have also presented high-resolution global spatial distributions of the shipping emissions of NOx, CO2, SO2 and PM2.5. The emissions were also analysed in terms of selected sea areas, ship categories, the sizes of ships and flag states. The emission datasets provided by this study are available upon request; the datasets produced by the model can be utilized as input data for air quality modelling on a global scale, including the full temporal and spatial variation of shipping emissions for the first time. Dispersion modelling using this inventory as input can be used to assess the impacts of various emission abatement scenarios. The emission computation methods presented in this paper could also be used, e.g., to provide annual updates of the global ship emissions.
Uncertainties in Episodic Ozone Modeling Stemming from Uncertainties in the Meteorological Fields.
NASA Astrophysics Data System (ADS)
Biswas, Jhumoor; Trivikrama Rao, S.
2001-02-01
This paper examines the uncertainty associated with photochemical modeling using the Variable-Grid Urban Airshed Model (UAM-V) with two different prognostic meteorological models. The meteorological fields for ozone episodes that occurred during 17-20 June, 12-15 July, and 30 July-2 August in the summer of 1995 were derived from two meteorological models, the Regional Atmospheric Modeling System (RAMS) and the Fifth-Generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5). The simulated ozone concentrations from the two photochemical modeling systems, namely, RAMS/UAM-V and MM5/UAM-V, are compared with each other and with ozone observations from several monitoring sites in the eastern United States. The overall results indicate that neither modeling system performs significantly better than the other in reproducing the observed ozone concentrations. The results reveal that there is a significant variability, about 20% at the 95% level of confidence, in the modeled 1-h ozone concentration maxima from one modeling system to the other for a given episode. The model-to-model variability in the simulated ozone levels is for most part attributable to the unsystematic type of errors. The directionality for emission controls (i.e., NOx versus VOC sensitivity) is also evaluated with UAM-V using hypothetical emission reductions. The results reveal that not only the improvement in ozone but also the VOC-sensitive and NOx-sensitive regimes are influenced by the differences in the meteorological fields. Both modeling systems indicate that a large portion of the eastern United States is NOx limited, but there are model-to-model and episode-to-episode differences at individual grid cells regarding the efficacy of emission reductions.
ECONOMIC GROWTH ANALYSIS SYSTEM: USER'S GUIDE
The two-volume report describes the development of, and provides information needed to operate, a prototype Economic Growth Analysis System (E-GAS) modeling system. The model will be used to project emissions inventories of volatile organic compounds (VOCs), oxides of nitrogen (...
ECONOMIC GROWTH ANALYSIS SYSTEM: REFERENCE MANUAL
The two-volume report describes the development of, and provides information needed to operate, a prototype Economic Growth Analysis System (E-GAS) modeling system. The model will be used to project emissions inventories of volatile organic compounds (VOCs), oxides of nitrogen (...
NASA Astrophysics Data System (ADS)
Liu, Q.
2011-09-01
At first, research advances on radiation transfer modeling on multi-scale remote sensing data are presented: after a general overview of remote sensing radiation transfer modeling, several recent research advances are presented, including leaf spectrum model (dPROS-PECT), vegetation canopy BRDF models, directional thermal infrared emission models(TRGM, SLEC), rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed. The land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation etc. are taken as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is designed and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China will be introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.
NASA Astrophysics Data System (ADS)
Cui, Z. L.; Ye, Y. L.; Ma, W. Q.; Chen, X. P.; Zhang, F. S.
2013-10-01
Although the concept of producing higher yields with reduced greenhouse gas (GHG) emissions is a goal that attracts increasing public and scientific attention, the tradeoff between crop productivity and GHG emissions in intensive agricultural production is not well understood. In this study, we investigated 33 sites of on-farm experiments to evaluate the tradeoff between grain yield and GHG emissions using two systems (conventional practice, CP; high-yielding systems, HY) of intensive irrigation wheat (Triticum aestivum L.) in China. Furthermore, we discussed the potential to produce higher yields with lower GHG emissions based on a survey of 2938 farmers. However, in both the HY and CP systems, wheat grain yield response to GHG emissions fit a linear-plateau model, whereas the curve for grain yield from the HY system was always higher than that from the CP system. Compared to the CP system, grain yield was 44% (2.6 Mg ha-1) higher in the HY system, while GHG emissions increased by only 2.5%, and GHG emission intensity was reduced by 29%. The current intensive irrigation wheat system with farmers' practice had a median yield and maximum GHG emission rate of 6.05 Mg ha-1 and 4783 kg CO2 eq ha-1, respectively; however, this system can be transformed to maintain yields while reducing GHG emissions by 40% (5.96 Mg ha-1, and 2890 kg CO2 eq ha-1). Further, the HY system was found to increase grain yield by 41% with a simultaneous reduction in GHG emissions by 38% (8.55 Mg ha-1, and 2961 kg CO2 eq ha-1, respectively). In the future, we suggest moving the tradeoff relationships and calculations from grain yield and GHG emissions, to new measures of productivity and environmental protection using innovative management technologies. This shift in focus is critical to achieve food and environmental security.
Climate Variability and Wildfires: Insights from Global Earth System Models
NASA Astrophysics Data System (ADS)
Ward, D. S.; Shevliakova, E.; Malyshev, S.; Lamarque, J. F.; Wittenberg, A. T.
2016-12-01
Better understanding of the relationship between variability in global climate and emissions from wildfires is needed for predictions of fire activity on interannual to multi-decadal timescales. Here we investigate this relationship using the long, preindustrial control simulations and historical ensembles of two Earth System models; CESM1 and the NOAA/GFDL ESM2Mb. There is smaller interannual variability of global fires in both models than in present day inventories, especially in boreal regions where observed fires vary substantially from year to year. Patterns of fire response to climate oscillation indices, including the El Niño / Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Atlantic Meridional Oscillation (AMO) are explored with the model results and compared to the response derived from satellite measurements and proxy observations. Increases in fire emissions in southeast Asia and boreal North America are associated with positive ENSO and PDO, while United States fires and Sahel fires decrease for the same climate conditions. Boreal fire emissions decrease in CESM1 for the warm phase of the AMO, while ESM2Mb did not produce a reliable AMO. CESM1 produces a weak negative trend in global fire emissions for the period 1920 to 2005, while ESM2Mb produces a positive trend over the same period. Both trends are statistically significant at a confidence level of 95% or greater given the variability derived from the respective preindustrial controls. In addition to climate variability impacts on fires, we also explore the impacts of fire emissions on climate variability and atmospheric chemistry. We analyze three long, free-evolving ESM2Mb simulations; one without fire emissions, one with constant year-over-year fire emissions based on a present day inventory, and one with interannually varying fire emissions coupled between the terrestrial and atmospheric components of the model, to gain a better understanding of the role of fire emissions in climate over long timescales.
NASA Astrophysics Data System (ADS)
Capps, S. L.; Pinder, R. W.; Loughlin, D. H.; Bash, J. O.; Turner, M. D.; Henze, D. K.; Percell, P.; Zhao, S.; Russell, M. G.; Hakami, A.
2014-12-01
Tropospheric ozone (O3) affects the productivity of ecosystems in addition to degrading human health. Concentrations of this pollutant are significantly influenced by precursor gas emissions, many of which emanate from energy production and use processes. Energy system optimization models could inform policy decisions that are intended to reduce these harmful effects if the contribution of precursor gas emissions to human health and ecosystem degradation could be elucidated. Nevertheless, determining the degree to which precursor gas emissions harm ecosystems and human health is challenging because of the photochemical production of ozone and the distinct mechanisms by which ozone causes harm to different crops, tree species, and humans. Here, the adjoint of a regional chemical transport model is employed to efficiently calculate the relative influences of ozone precursor gas emissions on ecosystem and human health degradation, which informs an energy system optimization. Specifically, for the summer of 2007 the Community Multiscale Air Quality (CMAQ) model adjoint is used to calculate the location- and sector-specific influences of precursor gas emissions on potential productivity losses for the major crops and sensitive tree species as well as human mortality attributable to chronic ozone exposure in the continental U.S. The atmospheric concentrations are evaluated with 12-km horizontal resolution with crop production and timber biomass data gridded similarly. These location-specific factors inform the energy production and use technologies selected in the MARKet ALlocation (MARKAL) model.
Guo, Lisha; Vanrolleghem, Peter A
2014-02-01
An activated sludge model for greenhouse gases no. 1 was calibrated with data from a wastewater treatment plant (WWTP) without control systems and validated with data from three similar plants equipped with control systems. Special about the calibration/validation approach adopted in this paper is that the data are obtained from simulations with a mathematical model that is widely accepted to describe effluent quality and operating costs of actual WWTPs, the Benchmark Simulation Model No. 2 (BSM2). The calibration also aimed at fitting the model to typical observed nitrous oxide (N₂O) emission data, i.e., a yearly average of 0.5% of the influent total nitrogen load emitted as N₂O-N. Model validation was performed by challenging the model in configurations with different control strategies. The kinetic term describing the dissolved oxygen effect on the denitrification by ammonia-oxidizing bacteria (AOB) was modified into a Haldane term. Both original and Haldane-modified models passed calibration and validation. Even though their yearly averaged values were similar, the two models presented different dynamic N₂O emissions under cold temperature conditions and control. Therefore, data collected in such situations can potentially permit model discrimination. Observed seasonal trends in N₂O emissions are simulated well with both original and Haldane-modified models. A mechanistic explanation based on the temperature-dependent interaction between heterotrophic and autotrophic N₂O pathways was provided. Finally, while adding the AOB denitrification pathway to a model with only heterotrophic N₂O production showed little impact on effluent quality and operating cost criteria, it clearly affected N2O emission productions.
The Study of Biogenetic Organic Compound Emissions and Ozone in a Subtropical Bamboo Forest
NASA Astrophysics Data System (ADS)
Bai, Jianhui; Guenther, Alex; Turnipseed, Andrew; Duhl, Tiffany; Duhl, Nanhao; van der A, Ronald; Yu, Shuquan; Wang, Bin
2016-08-01
Emissions of Biogenic Volatile Organic compounds (BVOCs), Photosynthetically Active Radiation (PAR), and meteorological parameters were measured in some ecosystems in China. A Relaxed Eddy Accumulation system and an enclosure technique were used to measure BVOC emissions. Obvious diurnal and seasonal variations of BVOC emissions were found. Empirical models of BVOC emissions were developed, the estimated BVOC emissions were in agreement with observations. BVOC emissions in growing seasons in the Inner Mongolia grassland, Chnagbai Mountain temperate forest, LinAn subtropical bamboo forest were estimated. The emission factors of these ecosystems were calculated.
Update of NOx emission temporal profiles using CMAQ-HDDM
NASA Astrophysics Data System (ADS)
Bae, C.; Lee, J. B.; Kim, H. C.; Kim, B. U.; Kim, S.
2017-12-01
This study demonstrates the impact of revised temporal profiles of NOx emissions on air quality simulations in the Seoul Metropolitan Area (SMA), South Korea. Air pollutants such as ozone and nitrogen oxides can be harmful to the human body even with short-term exposure. Since most of air quality models use predefined temporal profiles which are often outdated or taken from different chemical environment, providing accurate temporal variation of emissions are challenging in prediction of correct local air quality. Considering secondary formation of pollutants are important in mega cities and temporal variations of emissions are not coincident with those of resultant concentrations, we utilized CMAQ-HDDM to link emissions and consequential concentrations from different time steps. Base simulations were conducted using WRF, SMOKE, and CMAQ modeling frame using CREATE 2015 and CAPSS 2013 emissions inventories for East Asia and South Korea, respectively. With current modeling system, modeled NOx concentrations underestimate 4% in the daytime (10-16 LST), but overestimate 30% in the nighttime during May to August 2015. Applying revised temporal profiles based on HDDM sensitivities, model performance was improved significantly. We conclude that the proposed temporal allocation method can be useful to reduce the model-observation discrepancies when the activity data for emission sources are difficult to obtain with a bottom-up approach.
RCP4.5: A Pathway for Stabilization of Radiative Forcing by 2100
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thomson, Allison M.; Calvin, Katherine V.; Smith, Steven J.
2011-07-29
Representative Concentration Pathway (RCP) 4.5 is a scenario that stabilizes radiative forcing at 4.5 W m{sup -2} in the year 2100 without ever exceeding that value. Simulated with the Global Change Assessment Model (GCAM), RCP4.5 includes long-term, global emissions of greenhouse gases, short-lived species, and land-use-land-cover in a global economic framework. RCP4.5 was updated from earlier GCAM scenarios to incorporate historical emissions and land cover information common to the RCP process and follows a cost-minimizing pathway to reach the target radiative forcing. The imperative to limit emissions in order to reach this target drives changes in the energy system, includingmore » shifts to electricity, to lower emissions energy technologies and to the deployment of carbon capture and geologic storage technology. In addition, the RCP4.5 emissions price also applies to land use emissions; as a result, forest lands expand from their present day extent. The simulated future emissions and land use were downscaled from the regional simulation to a grid to facilitate transfer to climate models. While there are many alternative pathways to achieve a radiative forcing level of 4.5 W m{sup -2}, the application of the RCP4.5 provides a common platform for climate models to explore the climate system response to stabilizing the anthropogenic components of radiative forcing.« less
Evaluation of a Mobile Phone for Aircraft GPS Interference
NASA Technical Reports Server (NTRS)
Nguyen, Truong X.
2004-01-01
Measurements of spurious emissions from a mobile phone are conducted in a reverberation chamber for the Global Positioning System (GPS) radio frequency band. This phone model was previously determined to have caused interference to several aircraft GPS receivers. Interference path loss (IPL) factors are applied to the emission data, and the outcome compared against GPS receiver susceptibility. The resulting negative safety margins indicate there are risks to aircraft GPS systems. The maximum emission level from the phone is also shown to be comparable with some laptop computer's emissions, implying that laptop computers can provide similar risks to aircraft GPS receivers.
Carbon loss and greenhouse gas emission from extreme fire events occurred in Sardinia, Italy
NASA Astrophysics Data System (ADS)
Bacciu, V. M.; Salis, M.; Pellizzaro, G.; Arca, B.; Duce, P.; Spano, D.
2011-12-01
It is widely recognized that biomass burning is a significant driver of CO2 cycling and a source of greenhouse gases, aerosol particles, and other chemically reactive atmospheric gases. The large amounts of carbon that fires release into the atmosphere could approach levels of anthropogenic carbon emissions, especially in years of extreme fire activity. CO2 emissions from 2007 forest fires in Greece were in the range of 4.5 Mt, representing about the 4% of the total annual CO2 emissions of that country (http://effis.jrc.it/). Barbosa et al. (2006) reported a similar percentage of fire emissions to total emissions of CO2 in Portugal during the extreme fire seasons of 2003 and 2005. Currently, inventory methods for biomass burning emission use the equation first proposed by Seiler and Crutzen (1980), taking into account the area burned, the amount of biomass burned, and the emission factors associated with each specific chemical species. However, several errors and uncertainties can affect the emission assessment, due to the estimate consistency of the various parameters involved in the equation, including flaming and smoldering combustion periods, appropriate fuel load evaluations and gaseous emission factors for different fuel fractions and fire types. In this context, model approaching can contribute to better appraise fuel consumption and the resultant emissions. In addition, more comprehensive and accurate data inputs would be of valuable help for predicting and quantifying the source and the composition of fire emissions. The purpose of this work is to explore the impacts of extreme fire events occurred in Sardinia Island (Italy) using an integrated approach combining modelling fire emissions, field observations and remotely-sensed data. In order to achieve realistic fire emission estimates, we used the FOFEM model, due to the necessity to use a consistent modeling methodology across source categories, the input required, and its ability to estimate flaming and smoldering emissions. FOFEM input fuel load data were surveyed to represent those combusted, and fuel availability was obtained from supervised classification of remotely-sensed images. Data relative to fire perimeters, fire weather data, and fire behaviour were gathered by the Sardinian Forestry Corps (CFVA). Consumptions and emissions for each fuel types were estimated through FOFEM. Finally, all the data were assembled into a Geographical Information System (GIS) to facilitate manipulation and display of the data. The results showed the crucial role of appropriate fuel, fire, and weather data and maps to attain reasonable simulations of fuel consumption and smoke emissions. Carbon emission estimates are sensitive to pre-fire fuel loads, so the method used to establish initial fuel conditions is crucial. The FOFEM outputs and the derived smoke emission maps are useful for several applications including emissions inventories, air quality management plans, and emission source models coupled with dispersion models and decision support systems.
Advances in understanding, models and parameterisations of biosphere-atmosphere ammonia exchange
NASA Astrophysics Data System (ADS)
Flechard, C. R.; Massad, R.-S.; Loubet, B.; Personne, E.; Simpson, D.; Bash, J. O.; Cooter, E. J.; Nemitz, E.; Sutton, M. A.
2013-03-01
Atmospheric ammonia (NH3) dominates global emissions of total reactive nitrogen (Nr), while emissions from agricultural production systems contribute about two thirds of global NH3 emissions; the remaining third emanates from oceans, natural vegetation, humans, wild animals and biomass burning. On land, NH3 emitted from the various sources eventually returns to the biosphere by dry deposition to sink areas, predominantly semi-natural vegetation, and by wet and dry deposition as ammonium (NH4+) to all surfaces. However, the land/atmosphere exchange of gaseous NH3 is in fact bi-directional over unfertilized as well as fertilized ecosystems, with periods and areas of emission and deposition alternating in time (diurnal, seasonal) and space (patchwork landscapes). The exchange is controlled by a range of environmental factors, including meteorology, surface layer turbulence, thermodynamics, air and surface heterogeneous-phase chemistry, canopy geometry, plant development stage, leaf age, organic matter decomposition, soil microbial turnover, and, in agricultural systems, by fertilizer application rate, fertilizer type, soil type, crop type, and agricultural management practices. We review the range of processes controlling NH3 emission and uptake in the different parts of the soil-canopy-atmosphere continuum, with NH3 emission potentials defined at the substrate and leaf levels by different [NH4+] / [H+] ratios (Γ). Surface/atmosphere exchange models for NH3 are necessary to compute the temporal and spatial patterns of emissions and deposition at the soil, plant, field, landscape, regional and global scales, in order to assess the multiple environmental impacts of air-borne and deposited NH3 and NH4+. Models of soil/vegetation/atmosphereem NH3 exchange are reviewed from the substrate and leaf scales to the global scale. They range from simple steady-state, "big leaf" canopy resistance models, to dynamic, multi-layer, multi-process, multi-chemical species schemes. Their level of complexity depends on their purpose, the spatial scale at which they are applied, the current level of parameterisation, and the availability of the input data they require. State-of-the-art solutions for determining the emission/sink Γ potentials through the soil/canopy system include coupled, interactive chemical transport models (CTM) and soil/ecosystem modelling at the regional scale. However, it remains a matter for debate to what extent realistic options for future regional and global models should be based on process-based mechanistic versus empirical and regression-type models. Further discussion is needed on the extent and timescale by which new approaches can be used, such as integration with ecosystem models and satellite observations.
Advances in understanding, models and parameterizations of biosphere-atmosphere ammonia exchange
NASA Astrophysics Data System (ADS)
Flechard, C. R.; Massad, R.-S.; Loubet, B.; Personne, E.; Simpson, D.; Bash, J. O.; Cooter, E. J.; Nemitz, E.; Sutton, M. A.
2013-07-01
Atmospheric ammonia (NH3) dominates global emissions of total reactive nitrogen (Nr), while emissions from agricultural production systems contribute about two-thirds of global NH3 emissions; the remaining third emanates from oceans, natural vegetation, humans, wild animals and biomass burning. On land, NH3 emitted from the various sources eventually returns to the biosphere by dry deposition to sink areas, predominantly semi-natural vegetation, and by wet and dry deposition as ammonium (NH4+) to all surfaces. However, the land/atmosphere exchange of gaseous NH3 is in fact bi-directional over unfertilized as well as fertilized ecosystems, with periods and areas of emission and deposition alternating in time (diurnal, seasonal) and space (patchwork landscapes). The exchange is controlled by a range of environmental factors, including meteorology, surface layer turbulence, thermodynamics, air and surface heterogeneous-phase chemistry, canopy geometry, plant development stage, leaf age, organic matter decomposition, soil microbial turnover, and, in agricultural systems, by fertilizer application rate, fertilizer type, soil type, crop type, and agricultural management practices. We review the range of processes controlling NH3 emission and uptake in the different parts of the soil-canopy-atmosphere continuum, with NH3 emission potentials defined at the substrate and leaf levels by different [NH4+] / [H+] ratios (Γ). Surface/atmosphere exchange models for NH3 are necessary to compute the temporal and spatial patterns of emissions and deposition at the soil, plant, field, landscape, regional and global scales, in order to assess the multiple environmental impacts of airborne and deposited NH3 and NH4+. Models of soil/vegetation/atmosphere NH3 exchange are reviewed from the substrate and leaf scales to the global scale. They range from simple steady-state, "big leaf" canopy resistance models, to dynamic, multi-layer, multi-process, multi-chemical species schemes. Their level of complexity depends on their purpose, the spatial scale at which they are applied, the current level of parameterization, and the availability of the input data they require. State-of-the-art solutions for determining the emission/sink Γ potentials through the soil/canopy system include coupled, interactive chemical transport models (CTM) and soil/ecosystem modelling at the regional scale. However, it remains a matter for debate to what extent realistic options for future regional and global models should be based on process-based mechanistic versus empirical and regression-type models. Further discussion is needed on the extent and timescale by which new approaches can be used, such as integration with ecosystem models and satellite observations.
Detecting and Understanding Changing Arctic Carbon Emissions
NASA Astrophysics Data System (ADS)
Bruhwiler, L.
2017-12-01
Warming in the Arctic has proceeded faster than anyplace on Earth. Our current understanding of biogeochemistry suggests that we can expect feedbacks between climate and carbon in the Arctic. Changes in terrestrial fluxes of carbon can be expected as the Arctic warms, and the vast stores of organic carbon frozen in Arctic soils could be mobilized to the atmosphere, with possible significant impacts on global climate. Quantifying trends in Arctic carbon exchanges is important for policymaking because greater reductions in anthropogenic emissions may be required to meet climate goals. Observations of greenhouse gases in the Arctic and globally have been collected for several decades. Analysis of this data does not currently support significantly changed Arctic emissions of CH4, however it is difficult to detect changes in Arctic emissions because of transport from lower latitudes and large inter-annual variability. Unfortunately, current space-based remote sensing systems have limitations at Arctic latitudes. Modeling systems can help untangle the Arctic budget of greenhouse gases, but they are dependent on underlying prior fluxes, wetland distributions and global anthropogenic emissions. Also, atmospheric transport models may have significant biases and errors. For example, unrealistic near-surface stability can lead to underestimation of emissions in atmospheric inversions. We discuss our current understanding of the Arctic carbon budget from both top-down and bottom-up approaches. We show that current atmospheric inversions agree well on the CH4 budget. On the other hand, bottom-up models vary widely in their predictions of natural emissions, with some models predicting emissions too large to be accommodated by the budget implied by global observations. Large emissions from the shallow Arctic ocean are also inconsistent with atmospheric observations. We also discuss the sensitivity of the current atmospheric network to what is likely small, gradual increases in emissions over time by examining modeled and observed spatial and seasonal variability. An issue we will consider is whether well-mixed background atmospheric records are more likely to detect changing Arctic emissions compared to stronger, but more variable signal from local sources.
Application of GIS to modified models of vehicle emission dispersion
NASA Astrophysics Data System (ADS)
Jin, Taosheng; Fu, Lixin
This paper reports on a preliminary study of the forecast and evaluation of transport-related air pollution dispersion in urban areas. Some modifications of the traditional Gauss dispersion models are provided, and especially a crossroad model is built, which considers the great variation of vehicle emission attributed to different driving patterns at the crossroad. The above models are combined with a self-developed geographic information system (GIS) platform, and a simulative system with graphical interfaces is built. The system aims at visually describing the influences on the urban environment by urban traffic characteristics and therefore gives a reference to the improvement of urban air quality. Due to the introduction of a self-developed GIS platform and a creative crossroad model, the system is more effective, flexible and accurate. Finally, a comparison of the simulated (predicted) and observed hourly concentration is given, which indicates a good simulation.
Estimation of vegetative mercury emissions in China.
Quan, Jiannong; Zhang, Xiaoshan; Shim, Shang Gyoo
2008-01-01
Vegetative mercury emissions were estimated within the framework of Biogenic Emission Inventory System (BEIS3 V3.11). In this estimation, the 19 categories of U.S. Geological Survey landcover data were incorporated to generate the vegetation-specific mercury emissions in a 81-km Lambert Conformal model grid covering the total Chinese continent. The surface temperature and cloud-corrected solar radiation from a Mesoscale Meteorological model (MM5) were retrieved and used for calculating the diurnal variation. The implemented emission factors were either evaluated from the measured mercury flux data for forest, agriculture and water, or assumed for other land fields without available flux data. Annual simulations using the MM5 data were performed to investigate the seasonal emission variation. From the sensitivity analysis using two sets of emission factors, the vegetative mercury emissions in China domain were estimated to range from a lower limit of 79 x 10(3) kg/year to an upper limit of 177 x 10(3) kg/year. The modeled vegetative emissions were mainly generated from the eastern and southern China. Using the estimated data, it is shown that mercury emissions from vegetation are comparable to that from anthropogenic sources during summer. However, the vegetative emissions decrease greatly during winter, leaving anthropogenic sources as the major sources of emission.
Haugen, Molly J; Bishop, Gary A
2018-05-15
Two California heavy-duty fleets have been measured in 2013, 2015, and 2017 using the On-Road Heavy-Duty Measurement System. The Port of Los Angeles drayage fleet has increased in age by 3.3 model years (4.2-7.5 years old) since 2013, with little fleet turnover. Large increases in fuel-specific particle emissions (PM) observed in 2015 were reversed in 2017, returning to near 2013 levels, suggesting repairs and or removal of high emitting vehicles. Fuel-specific oxides of nitrogen (NO x ) emissions of this fleet have increased, and NO x after-treatment systems do not appear to perform ideally in this setting. At the Cottonwood weigh station in northern California, the fleet age has declined (7.8 to 6 years old) since 2013 due to fleet turnover, significantly lowering the average fuel-specific emissions for PM (-87%), black carbon (-76%), and particle number (-64%). Installations of retrofit-diesel particulate filters in model year 2007 and older vehicles have further decreased particle emissions. Cottonwood fleet fuel-specific NO x emissions have decreased slightly (-8%) during this period; however, newer technology vehicles with selective catalytic reduction systems (SCR) promise an additional factor of 4-5 further reductions in the long-haul fleet emissions as California transitions to an all SCR-equipped fleet.
Greenhouse gases emissions from waste management practices using Life Cycle Inventory model.
Chen, Tsao-Chou; Lin, Cheng-Fang
2008-06-30
When exploring the correlation between municipal solid waste management and green house gas emission, the volume and physical composition of the waste matter must be taken into account. Due to differences in local environments and lifestyles the quantity and composition of waste often vary. This leads to differences in waste treatment methods and causes different volumes of greenhouse gases (GHGs), highlighting the need for local research. In this study the Life Cycle Inventory method was used with global warming indicator GHGs as the variables. By quantifying the data and adopting a region-based approach, this created a model of household MSWM in Taipei City, a metropolitan region in Taiwan. To allow analysis and comparison a compensatory system was then added to expand the system boundary. The results of the analysis indicated that out of all the solid waste management sub-models for a function unit, recycling was the most effective method for reducing GHG emissions while using kitchen food waste as swine feeding resulted in the most GHG emissions. As for the impact of waste collection vehicles on emissions, if the efficiency of transportation could be improved and energy consumption reduced, this will help solid waste management to achieve its goal of reducing GHG emissions.
How Sensitive Is the Carbon Budget Approach to Potential Carbon Cycle Changes?
NASA Astrophysics Data System (ADS)
Matthews, D.
2014-12-01
The recent development of global Earth-system models, which include dynamic representations of both physical climate and carbon cycle processes, has led to new insights about how the climate responds to human carbon dioxide emissions. Notably, several model analyses have now shown that global temperature responds linearly to cumulative CO2 emissions across a wide range of emissions scenarios. This implies that the timing of CO2 emissions does not affect the overall climate response, and allows a finite global carbon carbon budget to be defined for a given global temperature target. This linear climate response, however, emerges from the interaction of several non-linear processes and feedbacks involving how carbon sinks respond to changes in atmospheric CO2 and climate. In this presentation, I will give an overview of how carbon sinks and carbon cycle feedbacks contribute to the overall linearity of the climate response to cumulative emissions, and will assess how robust this relationship is to a range of possible changes in the carbon cycle, including (a) potential positive carbon cycle feedbacks that are not well represented in the current generation of Earth-system models and (b) negative emission scenarios resulting from possible technological strategies to remove CO2 from the atmosphere.
Neutron-$$\\gamma$$ competition for β-delayed neutron emission
Mumpower, Matthew Ryan; Kawano, Toshihiko; Moller, Peter
2016-12-19
Here we present a coupled quasiparticle random phase approximation and Hauser-Feshbach (QRPA+HF) model for calculating delayed particle emission. This approach uses microscopic nuclear structure information, which starts with Gamow-Teller strength distributions in the daughter nucleus and then follows the statistical decay until the initial available excitation energy is exhausted. Explicitly included at each particle emission stage is γ-ray competition. We explore this model in the context of neutron emission of neutron-rich nuclei and find that neutron-γ competition can lead to both increases and decreases in neutron emission probabilities, depending on the system considered. Finally, a second consequence of this formalismmore » is a prediction of more neutrons on average being emitted after β decay for nuclei near the neutron drip line compared to models that do not consider the statistical decay.« less
Edelenbosch, O. Y.; Kermeli, K.; Crijns-Graus, W.; ...
2017-01-09
The industry sector consumes more energy and emits more greenhouse gas (GHG) emissions than any other end-use sector. Integrated assessment models (IAMs) and energy system models have been widely used to evaluate climate policy at a global level, and include a representation of industrial energy use. In this study, the projected industrial energy use and accompanying GHG emissions, as well as the model structure of multiple long-term energy models are compared. The models show varying degrees to which energy consumption is decoupled from GDP growth in the future. In all models, the sector remains mostly (>50%) reliant on fossil energymore » through 2100 in a reference scenario (i.e., absent emissions mitigation policies), though there is significant divergence in the projected ability to switch to alternative fuels to mitigate GHG emissions. Among the set analyzed here, the more technologically detailed models tend to have less capacity for switching from fossil fuels to electricity. This highlights the importance of understanding of economy-wide mitigation responses and costs as an area for future improvement. Analyzing industry subsector material and energy use details can improve the ability to interpret results, and provide insight in feasibility of how emissions reduction can be achieved.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Edelenbosch, O. Y.; Kermeli, K.; Crijns-Graus, W.
The industry sector consumes more energy and emits more greenhouse gas (GHG) emissions than any other end-use sector. Integrated assessment models (IAMs) and energy system models have been widely used to evaluate climate policy at a global level, and include a representation of industrial energy use. In this study, the projected industrial energy use and accompanying GHG emissions, as well as the model structure of multiple long-term energy models are compared. The models show varying degrees to which energy consumption is decoupled from GDP growth in the future. In all models, the sector remains mostly (>50%) reliant on fossil energymore » through 2100 in a reference scenario (i.e., absent emissions mitigation policies), though there is significant divergence in the projected ability to switch to alternative fuels to mitigate GHG emissions. Among the set analyzed here, the more technologically detailed models tend to have less capacity for switching from fossil fuels to electricity. This highlights the importance of understanding of economy-wide mitigation responses and costs as an area for future improvement. Analyzing industry subsector material and energy use details can improve the ability to interpret results, and provide insight in feasibility of how emissions reduction can be achieved.« less
Irreducible Uncertainty in Terrestrial Carbon Projections
NASA Astrophysics Data System (ADS)
Lovenduski, N. S.; Bonan, G. B.
2016-12-01
We quantify and isolate the sources of uncertainty in projections of carbon accumulation by the ocean and terrestrial biosphere over 2006-2100 using output from Earth System Models participating in the 5th Coupled Model Intercomparison Project. We consider three independent sources of uncertainty in our analysis of variance: (1) internal variability, driven by random, internal variations in the climate system, (2) emission scenario, driven by uncertainty in future radiative forcing, and (3) model structure, wherein different models produce different projections given the same emission scenario. Whereas uncertainty in projections of ocean carbon accumulation by 2100 is 100 Pg C and driven primarily by emission scenario, uncertainty in projections of terrestrial carbon accumulation by 2100 is 50% larger than that of the ocean, and driven primarily by model structure. This structural uncertainty is correlated with emission scenario: the variance associated with model structure is an order of magnitude larger under a business-as-usual scenario (RCP8.5) than a mitigation scenario (RCP2.6). In an effort to reduce this structural uncertainty, we apply various model weighting schemes to our analysis of variance in terrestrial carbon accumulation projections. The largest reductions in uncertainty are achieved when giving all the weight to a single model; here the uncertainty is of a similar magnitude to the ocean projections. Such an analysis suggests that this structural uncertainty is irreducible given current terrestrial model development efforts.
Modeling of pesticide emissions from agricultural ecosystems
NASA Astrophysics Data System (ADS)
Li, Rong
2012-04-01
Pesticides are applied to crops and soils to improve agricultural yields, but the use of pesticides has become highly regulated because of concerns about their adverse effects on human health and environment. Estimating pesticide emission rates from soils and crops is a key component for risk assessment for pesticide registration, identification of pesticide sources to the contamination of sensitive ecosystems, and appreciation of transport and fate of pesticides in the environment. Pesticide emission rates involve processes occurring in the soil, in the atmosphere, and on vegetation surfaces and are highly dependent on soil texture, agricultural practices, and meteorology, which vary significantly with location and/or time. To take all these factors into account for simulating pesticide emissions from large agricultural ecosystems, this study coupled a comprehensive meteorological model with a dynamic pesticide emission model. The combined model calculates hourly emission rates from both emission sources: current applications and soil residues resulting from historical use. The coupled modeling system is used to compute a gridded (36 × 36 km) hourly toxaphene emission inventory for North America for the year 2000 using a published U.S. toxaphene residue inventory and a Mexican toxaphene residue inventory developed using its historical application rates and a cropland inventory. To my knowledge, this is the first such hourly toxaphene emission inventory for North America. Results show that modeled emission rates have strong diurnal and seasonal variations at a given location and over the entire domain. The simulated total toxaphene emission from contaminated agricultural soils in North America in 2000 was about 255 t, which compares reasonably well to a published annual estimate. Most emissions occur in spring and summer, with domain-wide emission rates in April, May and, June of 36, 51, and 35 t/month, respectively. The spatial distribution of emissions depends on the distribution of toxaphene soil residues, and high emission rates coincide with heavily contaminated areas.
Pump-to-Wheels Methane Emissions from the Heavy-Duty Transportation Sector.
Clark, Nigel N; McKain, David L; Johnson, Derek R; Wayne, W Scott; Li, Hailin; Akkerman, Vyacheslav; Sandoval, Cesar; Covington, April N; Mongold, Ronald A; Hailer, John T; Ugarte, Orlando J
2017-01-17
Pump-to-wheels (PTW) methane emissions from the heavy-duty (HD) transportation sector, which have climate change implications, are poorly documented. In this study, methane emissions from HD natural gas fueled vehicles and the compressed natural gas (CNG) and liquefied natural gas (LNG) fueling stations that serve them were characterized. A novel measurement system was developed to quantify methane leaks and losses. Engine related emissions were characterized from twenty-two natural gas fueled transit buses, refuse trucks, and over-the-road (OTR) tractors. Losses from six LNG and eight CNG stations were characterized during compression, fuel delivery, storage, and from leaks. Cryogenic boil-off pressure rise and pressure control venting from LNG storage tanks were characterized using theoretical and empirical modeling. Field and laboratory observations of LNG storage tanks were used for model development and evaluation. PTW emissions were combined with a specific scenario to view emissions as a percent of throughput. Vehicle tailpipe and crankcase emissions were the highest sources of methane. Data from this research are being applied by the authors to develop models to forecast methane emissions from the future HD transportation sector.
How do farm models compare when estimating greenhouse gas emissions from dairy cattle production?
Hutchings, N J; Özkan Gülzari, Ş; de Haan, M; Sandars, D
2018-01-09
The European Union Effort Sharing Regulation (ESR) will require a 30% reduction in greenhouse gas (GHG) emissions by 2030 compared with 2005 from the sectors not included in the European Emissions Trading Scheme, including agriculture. This will require the estimation of current and future emissions from agriculture, including dairy cattle production systems. Using a farm-scale model as part of a Tier 3 method for farm to national scales provides a more holistic and informative approach than IPCC (2006) Tier 2 but requires independent quality control. Comparing the results of using models to simulate a range of scenarios that explore an appropriate range of biophysical and management situations can support this process by providing a framework for placing model results in context. To assess the variation between models and the process of understanding differences, estimates of GHG emissions from four farm-scale models (DairyWise, FarmAC, HolosNor and SFARMMOD) were calculated for eight dairy farming scenarios within a factorial design consisting of two climates (cool/dry and warm/wet)×two soil types (sandy and clayey)×two feeding systems (grass only and grass/maize). The milk yield per cow, follower:cow ratio, manure management system, nitrogen (N) fertilisation and land area were standardised for all scenarios in order to associate the differences in the results with the model structure and function. Potential yield and application of available N in fertiliser and manure were specified separately for grass and maize. Significant differences between models were found in GHG emissions at the farm-scale and for most contributory sources, although there was no difference in the ranking of source magnitudes. The farm-scale GHG emissions, averaged over the four models, was 10.6 t carbon dioxide equivalents (CO2e)/ha per year, with a range of 1.9 t CO2e/ha per year. Even though key production characteristics were specified in the scenarios, there were still significant differences between models in the annual milk production per ha and the amounts of N fertiliser and concentrate feed imported. This was because the models differed in their description of biophysical responses and feedback mechanisms, and in the extent to which management functions were internalised. We conclude that comparing the results of different farm-scale models when applied to a range of scenarios would build confidence in their use in achieving ESR targets, justifying further investment in the development of a wider range of scenarios and software tools.
Biogenic Emission Inventories: Scaling Local Biogenic Measurements to Regions
NASA Astrophysics Data System (ADS)
Lamb, B.; Pressley, S.; Westberg, H.; Guenther, A.
2002-12-01
Biogenic Hydrocarbons, such as isoprene, are important trace gas species that are naturally emitted by vegetation and that affect the oxidative capacity of the atmosphere. Biogenic emissions are regulated by many environmental variables; the most important variables are thought to be temperature and light. Long-term isoprene flux measurements are useful for verifying existing canopy models and exploring other correlations between isoprene fluxes and environmental parameters. Biogenic Emission Models, such as BEIS (Biogenic Emission Inventory System) rely on above canopy environmental parameters and below canopy scaling factors to estimate canopy scale biogenic hydrocarbon fluxes. Other models, which are more complex, are coupled micrometeorological and physiological modules that provide feedback mechanisms present in a canopy environment. These types of models can predict biogenic emissions well, however, the required input is extensive, and for regional applications, they can be cumbersome. This paper presents analyses based on long-term isoprene flux measurements that have been collected since 1999 at the AmeriFlux site located at the University of Michigan Biological Station (UMBS) as part of the Program for Research on Oxidants: PHotochemistry, Emissions, and Transport (PROPHET). The goals of this research were to explore a potential relationship between the surface energy budget (primarily sensible heat flux) and isoprene emissions. Our hypothesis is that the surface energy flux is a better model parameter for isoprene emissions at the canopy scale than temperature and light levels, and the link to the surface energy budget will provide a significant improvement in isoprene emission models. Preliminary results indicate a significant correlation between daily isoprene emissions and sensible heat fluxes for a predominantly aspen/oak stand located in northern Michigan. Since surface energy budgets are an integral part of mesoscale meteorological models, this could potentially be a useful tool for including biogenic emissions into regional atmospheric models. Comparison of measured isoprene fluxes with current BEIS estimates will also be shown as an example of where emission inventories currently stand.
Assessing air quality and climate impacts of future ground freight choice in United States
NASA Astrophysics Data System (ADS)
Liu, L.; Bond, T. C.; Smith, S.; Lee, B.; Ouyang, Y.; Hwang, T.; Barkan, C.; Lee, S.; Daenzer, K.
2013-12-01
The demand for freight transportation has continued to increase due to the growth of domestic and international trade. Emissions from ground freight (truck and railways) account for around 7% of the greenhouse gas emissions, 4% of the primary particulate matter emission and 25% of the NOx emissions in the U.S. Freight railways are generally more fuel efficient than trucks and cause less congestion. Freight demand and emissions are affected by many factors, including economic activity, the spatial distribution of demand, freight modal choice and routing decision, and the technology used in each modal type. This work links these four critical aspects of freight emission system to project the spatial distribution of emissions and pollutant concentration from ground freight transport in the U.S. between 2010 and 2050. Macroeconomic scenarios are used to forecast economic activities. Future spatial structure of employment and commodity demand in major metropolitan areas are estimated using spatial models and a shift-share model, respectively. Freight flow concentration and congestion patterns in inter-regional transportation networks are predicted from a four-step freight demand forecasting model. An asymptotic vehicle routing model is also developed to estimate delivery ton-miles for intra-regional freight shipment in metropolitan areas. Projected freight activities are then converted into impacts on air quality and climate. CO2 emissions are determined using a simple model of freight activity and fuel efficiency, and compared with the projected CO2 emissions from the Second Generation Model. Emissions of air pollutants including PM, NOx and CO are calculated with a vehicle fleet model SPEW-Trend, which incorporates the dynamic change of technologies. Emissions are projected under three economic scenarios to represent different plausible futures. Pollutant concentrations are then estimated using tagged chemical tracers in an atmospheric model with the emissions serving as input.
Lakhan, Calvin
2016-11-01
This study highlights the economic and environmental challenges of recycling in Ontario, specifically examining the effect of attempting to increase the emissions target for the province's household recycling programme. The findings from the cost model analysis found that Ontario's Blue Box programme reduces overall carbon emissions by approximately 1.8 million tonnes every year. This study also found that targeting specific materials for recovery could result in a scenario where the province could improve both overall diversion and emissions offsets while reducing material management costs. Under our modelled scenario, as the tonnes of greenhouse gases (GHGs) avoided increases, the system cost per tonne of GHG avoided initial declines. However, after avoiding 2.05 million tonnes of GHGs, the system cost/tonne GHG avoided increases. To achieve an emissions target in excess of 2.05 million tonnes, the province will have to start recycling higher cost non-core materials (composite materials, other plastics, etc.). © The Author(s) 2016.
N2 triplet band systems and atomic oxygen in the dayglow
NASA Astrophysics Data System (ADS)
Broadfoot, A. L.; Hatfield, D. B.; Anderson, E. R.; Stone, T. C.; Sandel, B. R.; Gardner, J. A.; Murad, E.; Knecht, D. J.; Pike, C. P.; Viereck, R. A.
1997-06-01
New spectrographic observations of the Earth's dayglow have been acquired by the Arizona Airglow Experiment (GLO) flown on the space shuttle. GLO is an imaging spectrograph that records simultaneous vertical profiles of prominent Earth limb emissions occurring at wavelengths between 115 and 900 nm. This study addresses the measured emissions from the N2 triplet states (first positive, second positive, and Vegard-Kaplan band systems) and their excitation by the local photoelectron flux. The triplet state population distributions modeled for aurora by Cartwright [1978] are modified for dayglow conditions by changing to a photoelectron-flux energy distribution and including resonance scattering by the first positive system. Modeled and observed intensities are in excellent agreement, in contrast to the well-studied auroral case. This work concentrates on dayglow conditions at 200 km altitude near the subsolar point. Parameters to infer the local photoelectron flux from the emission band intensities are provided. Several atomic oxygen dayglow emission features were analyzed to complement the N2 analysis. The photoelectron-excited O I(135.6, 777.4 nm) lines were found to be 3 to 4 times weaker than predicted while the O I(630.0, 844.6 nm) lines were in close agreement with the model prediction.
Theory of lasing in a multiple-scattering medium
NASA Astrophysics Data System (ADS)
John, Sajeev; Pang, Gendi
1996-10-01
In several recent experiments, isotropic lasing action was observed in paints that contain rhodamine 640 dye molecules in methanol solution as gain media and titania particles as optical scatterers. These so-called paint-on laser systems are extraordinary because they are highly disordered systems. The microscopic mechanism for laser activity and the coherence properties of light emission in this multiple-light-scattering medium have not yet been elucidated. In this paper we derive the emission intensity properties of a model dye system with excited singlet and triplet electronic energy levels, which is immersed in a multiple-scattering medium with transport mean free path l*. Using physically reasonable estimates for the absorption and emission cross section for the singlet and triplet manifolds, and the singlet-triplet intersystem crossing rate, we solve the nonlinear laser rate equations for the dye molecules. This leads to a diffusion equation for the light intensity in the medium with a nonlinear intensity-dependent gain coefficient. Using this model we are able to account for nearly all of the experimentally observed properties of laser paint reported so far when l*>>λ0, the emission wavelength. This includes the dependence of the peak intensity of amplified emission on the mean free path l*, the dye concentration ρ, and the pump intensity characteristics. Our model recaptures the collapse of the emission linewidth at a specific threshold pump intensity and describes how this threshold intensity varies with l*. In addition, our model predicts a dramatic increase in the peak intensity and a further lowering of the lasing threshold for the strong scattering limit l*-->λ0. This suggests a striking enhancement of the characteristics of laser paint near the photon localization threshold in a disordered medium.
NASA Astrophysics Data System (ADS)
Jing, B. Y.; Wu, L.; Mao, H. J.; Gong, S. L.; He, J. J.; Zou, C.; Song, G. H.; Li, X. Y.; Wu, Z.
2015-10-01
As the ownership of vehicles and frequency of utilization increase, vehicle emissions have become an important source of air pollution in Chinese cities. An accurate emission inventory for on-road vehicles is necessary for numerical air quality simulation and the assessment of implementation strategies. This paper presents a bottom-up methodology based on the local emission factors, complemented with the widely used emission factors of Computer Programme to Calculate Emissions from Road Transport (COPERT) model and near real time (NRT) traffic data on road segments to develop a high temporal-spatial resolution vehicle emission inventory (HTSVE) for the urban Beijing area. To simulate real-world vehicle emissions accurately, the road has been divided into segments according to the driving cycle (traffic speed) on this road segment. The results show that the vehicle emissions of NOx, CO, HC and PM were 10.54 × 104, 42.51 × 104 and 2.13 × 104 and 0.41 × 104 Mg, respectively. The vehicle emissions and fuel consumption estimated by the model were compared with the China Vehicle Emission Control Annual Report and fuel sales thereafter. The grid-based emissions were also compared with the vehicular emission inventory developed by the macro-scale approach. This method indicates that the bottom-up approach better estimates the levels and spatial distribution of vehicle emissions than the macro-scale method, which relies on more information. Additionally, the on-road vehicle emission inventory model and control effect assessment system in Beijing, a vehicle emission inventory model, was established based on this study in a companion paper (He et al., 2015).
NASA Astrophysics Data System (ADS)
Campbell, E. E.; Dorich, C.; Contosta, A.; Varner, R. K.
2017-12-01
In livestock agroecosystems, the combined contributions of enteric fermentation, manure management, and livestock grazing and/or feed production play an important role in agroecosystem carbon (C) storage and GHG losses, with complete livestock system models acting as important tools to evaluate the full impacts of these complex systems. The Manure-DeNitrification-DeComposition (DNDC) model is one such example, simulating impacts on C and nitrogen cycling, estimating methane, carbon dioxide, nitrous oxide, and ammonium dynamics in fields, manure storage, and enteric emissions. This allows the evaluation of differences in GHG and soil C impacts between conventional and organic dairy production systems, which differ in their use of grazed pasture versus confined feeding operations. However, Manure-DNDC has received limited testing in representing variations in grazed pasture management (i.e. intensive rotational grazing versus standard grazing practices). Using a set of forage biomass, soil C, and GHG emissions data collected at four sites across New England, we parameterized and validated Manure-DNDC estimations of GHG emissions and soil C in grazed versus un-grazed systems. Soil observations from these sites showed little effect from grazing practices, but larger soil carbon differences between farms. This may be due to spatial variation in SOC, making it difficult to measure and model, or due to controls of edaphic properties that make management moot. However, to further address these questions, model development will be needed to improve Manure-DNDC simulation of rotational grazing, as high stocking density grazing over short periods resulted in forage not re-growing sufficiently within the model. Furthermore, model simulations did not account for variation in interactions between livestock and soil given variability in field microclimates, perhaps requiring simulations that divide a single field into multiple paddocks to move towards more accurate evaluation of grazing management used in dairy operations in cool season pastures.
Fertilizer Emission Scenario Tool for crop management system scenarios
The Fertilizer Emission Scenario Tool for CMAQ is a high-end computer interface that simulates daily fertilizer application information for any gridded domain. It integrates the Weather Research and Forecasting model and CMAQ.
Model study of the ship emissions impact on the air quality in the Adriatic/Ionian area
NASA Astrophysics Data System (ADS)
Karagiannidis, Athanasios; Poupkou, Anastasia; Liora, Natalia; Dimopoulos, Spiros; Giannaros, Christos; Melas, Dimitrios; Argiriou, Athanassios
2015-04-01
The increase of the ship traffic for touristic and commercial purposes is one of the EU Blue Growth targets. The Adriatic/Ionian is one of the sea-basin strategic areas for this target. The purpose of the study is the examination of the impact of the ship emissions on the gaseous and particulate pollutants concentrations in the Adriatic/Ionian area for which the current scientific knowledge is limited. The impact is simulated over a domain covering the Central and Eastern Mediterranean in 10 km resolution during a summer period (July) and a winter period (January) of the year 2012. The modeling system used consists of the photochemical model CAMx off line coupled with the meteorological model WRF. The zero-out modeling method is implemented involving CAMx simulations performed while including and omitting the ship emission data. The simulations are based on the European scale anthropogenic emission inventory of The Netherlands Organisation (TNO) for the reference year 2009. Natural emissions (NMVOCs from the vegetation, sea salt, wind-blown dust), estimated with the use of the Natural Emission MOdel (NEMO) developed by the Aristotle University of Thessaloniki, are accounted for in the photochemical model runs. The spatial distribution of the resulting differences in the gaseous and particulate pollutant concentration fields for both emission scenarios are presented and discussed, providing an estimation of the contribution of ship emissions on the determination of the air quality in the Adriatic/Ionian countries
Variability of fire emissions on interannual to multi-decadal timescales in two Earth System models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ward, D. S.; Shevliakova, E.; Malyshev, S.
Connections between wildfires and modes of variability in climate are sought as a means for predicting fire activity on interannual to multi-decadal timescales. Several fire drivers, such as temperature and local drought index, have been shown to vary on these timescales, and analysis of tree-ring data suggests covariance between fires and climate oscillation indices in some regions. HBut, the shortness of the satellite record of global fire events limits investigations on larger spatial scales. Here we explore the interplay between climate variability and wildfire emissions with the preindustrial long control numerical experiments and historical ensembles of CESM1 and the NOAA/GFDLmore » ESM2Mb. We find that interannual variability in fires is underpredicted in both Earth System models (ESMs) compared to present day fire emission inventories. Modeled fire emissions respond to the El Niño/southern oscillation (ENSO) and Pacific decadal oscillation (PDO) with increases in southeast Asia and boreal North America emissions, and decreases in southern North America and Sahel emissions, during the ENSO warm phase in both ESMs, and the PDO warm phase in CESM1. In addition, CESM1 produces decreases in boreal northern hemisphere fire emissions for the warm phase of the Atlantic Meridional Oscillation. Through analysis of the long control simulations, we show that the 20th century trends in both ESMs are statistically significant, meaning that the signal of anthropogenic activity on fire emissions over this time period is detectable above the annual to decadal timescale noise. However, the trends simulated by the two ESMs are of opposite sign (CESM1 decreasing, ESM2Mb increasing), highlighting the need for improved understanding, proxy observations, and modeling to resolve this discrepancy.« less
Variability of fire emissions on interannual to multi-decadal timescales in two Earth System models
NASA Astrophysics Data System (ADS)
Ward, D. S.; Shevliakova, E.; Malyshev, S.; Lamarque, J.-F.; Wittenberg, A. T.
2016-12-01
Connections between wildfires and modes of variability in climate are sought as a means for predicting fire activity on interannual to multi-decadal timescales. Several fire drivers, such as temperature and local drought index, have been shown to vary on these timescales, and analysis of tree-ring data suggests covariance between fires and climate oscillation indices in some regions. However, the shortness of the satellite record of global fire events limits investigations on larger spatial scales. Here we explore the interplay between climate variability and wildfire emissions with the preindustrial long control numerical experiments and historical ensembles of CESM1 and the NOAA/GFDL ESM2Mb. We find that interannual variability in fires is underpredicted in both Earth System models (ESMs) compared to present day fire emission inventories. Modeled fire emissions respond to the El Niño/southern oscillation (ENSO) and Pacific decadal oscillation (PDO) with increases in southeast Asia and boreal North America emissions, and decreases in southern North America and Sahel emissions, during the ENSO warm phase in both ESMs, and the PDO warm phase in CESM1. Additionally, CESM1 produces decreases in boreal northern hemisphere fire emissions for the warm phase of the Atlantic Meridional Oscillation. Through analysis of the long control simulations, we show that the 20th century trends in both ESMs are statistically significant, meaning that the signal of anthropogenic activity on fire emissions over this time period is detectable above the annual to decadal timescale noise. However, the trends simulated by the two ESMs are of opposite sign (CESM1 decreasing, ESM2Mb increasing), highlighting the need for improved understanding, proxy observations, and modeling to resolve this discrepancy.
Variability of fire emissions on interannual to multi-decadal timescales in two Earth System models
Ward, D. S.; Shevliakova, E.; Malyshev, S.; ...
2016-12-02
Connections between wildfires and modes of variability in climate are sought as a means for predicting fire activity on interannual to multi-decadal timescales. Several fire drivers, such as temperature and local drought index, have been shown to vary on these timescales, and analysis of tree-ring data suggests covariance between fires and climate oscillation indices in some regions. HBut, the shortness of the satellite record of global fire events limits investigations on larger spatial scales. Here we explore the interplay between climate variability and wildfire emissions with the preindustrial long control numerical experiments and historical ensembles of CESM1 and the NOAA/GFDLmore » ESM2Mb. We find that interannual variability in fires is underpredicted in both Earth System models (ESMs) compared to present day fire emission inventories. Modeled fire emissions respond to the El Niño/southern oscillation (ENSO) and Pacific decadal oscillation (PDO) with increases in southeast Asia and boreal North America emissions, and decreases in southern North America and Sahel emissions, during the ENSO warm phase in both ESMs, and the PDO warm phase in CESM1. In addition, CESM1 produces decreases in boreal northern hemisphere fire emissions for the warm phase of the Atlantic Meridional Oscillation. Through analysis of the long control simulations, we show that the 20th century trends in both ESMs are statistically significant, meaning that the signal of anthropogenic activity on fire emissions over this time period is detectable above the annual to decadal timescale noise. However, the trends simulated by the two ESMs are of opposite sign (CESM1 decreasing, ESM2Mb increasing), highlighting the need for improved understanding, proxy observations, and modeling to resolve this discrepancy.« less
Comparison of Field Measurements to Methane Emissions ...
Due to both technical and economic limitations, estimates of methane emissions from landfills rely primarily on models. While models are easy to implement, there is uncertainty due to the use of parameters that are difficult to validate. The objective of this research was to compare modeled emissions using several greenhouse gas (GHG) emissions reporting protocols including: (1) Intergovernmental Panel on Climate Change (IPCC); (2) U.S. Environmental Protection Agency Greenhouse Gas Reporting Program (EPA GHGRP); (3) California Air Resources Board (CARB); (4) Solid Waste Industry for Climate Solutions (SWICS); and (5) an industry model from the Dutch waste company Afvalzorg, with measured data collected over 3 calendar years from a young landfill with no gas collection system. By working with whole landfill measurements of fugitive methane emissions and methane oxidation, the collection efficiency could be set to zero, thus eliminating one source of parameter uncertainty. The models consistently overestimated annual methane emissions by a factor ranging from 4 – 32.Varying input parameters over reasonable ranges reduced this range to 1.3 - 8. Waste age at the studied landfill was less than four years and the results suggest the need for measurements at additional landfills to evaluate the accuracy of the tested models to young landfills. This is a submission to a peer reviewed journal. The paper discusses landfill emission measurements and models for a new la
A flare event of the long-period RS Canum Venaticorum system IM Pegasi
NASA Technical Reports Server (NTRS)
Buzasi, Derek L.; Ramsey, Lawrence W.; Huenemoerder, David P.
1987-01-01
The characteristics of a flare event detected on the long-period RS CVn system IM Pegasi are reported. The low-resolution spectrum show enhancements of up to a factor of five in some emission lines. All of the ultraviolet emission lines normally visible are enhanced significantly more than the normal 30 rotational modulation. Emission fluxes of both the quiescent and flare event are used to construct models of the density and temperature variation with height. These models reveal a downward shift of the transition region during the flare. Scaled models of the quiet and flaring solar outer atmosphere are used to estimate the filling factor of the flare event at about 30 percent of the stellar surface. The pattern of line enhancements in the flare is the same as a previous event in Lambda Andromeda observed previously.
NASA Astrophysics Data System (ADS)
Kim, Y.; Woo, J. H.; Choi, K. C.; Lee, J. B.; Song, C. K.; Kim, S. K.; Hong, J.; Hong, S. C.; Zhang, Q.; Hong, C.; Tong, D.
2015-12-01
Future emission scenarios based on up-to-date regional socio-economic and control policy information were developed in support of climate-air quality integrated modeling research over East Asia. Two IPCC-participated Integrated Assessment Models(IAMs) were used to developed those scenario pathways. The two emission processing systems, KU-EPS and SMOKE-Asia, were used to convert these future scenario emissions to comprehensive chemical transport model-ready form. The NIER/KU-CREATE (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment) served as the regional base-year emission inventory. For anthropogenic emissions, it has 54 fuel classes, 201 sub-sectors and 13 pollutants, including CO2, CH4, N2O, SO2, NOx, CO, NMVOC, NH3, OC, BC, PM10, PM2.5, and mercury. Fast energy growth and aggressive penetration of the control measures make emissions projection very active for East Asia. Despite of more stringent air pollution control policies by the governments, however, air quality over the region seems not been improved as much - even worse in many cases. The needs of more scientific understanding of inter-relationship among emissions, transport, chemistry over the region are very high to effectively protect public health and ecosystems against ozone, fine particles, and other toxic pollutants in the air. After developing these long-term future emissions, therefore, we also tried to apply our future scenarios to develop the present emissions inventory for chemical weather forecasting and aircraft field campaign. On site, we will present; 1) the future scenario development framework and process methodologies, 2) initial development results of the future emission pathways, 3) present emission inventories from short-term projection, and 4) air quality modeling performance improvements over the region.
USDA-ARS?s Scientific Manuscript database
The DAYCENT biogeochemical model was used to investigate how the use of fertilisers coated with nitrification inhibitors and the introduction of legumes in the crop rotation can affect subtropical cereal production and N2O emissions. The model was validated using comprehensive multi-seasonal, high-f...
USDA-ARS?s Scientific Manuscript database
Process-level modeling at the farm scale provides a tool for evaluating both strategies for mitigating greenhouse gas emissions and strategies for adapting to climate change. The Integrated Farm System Model (IFSM) simulates representative crop, beef or dairy farms over many years of weather to pred...
Two specific fires from 2011 are tracked for local to regional scale contribution to ozone (O3) and fine particulate matter (PM2.5) using a freely available regulatory modeling system that includes the BlueSky wildland fire emissions tool, Spare Matrix Operator Kernel Emissions (...
Modeling crop residue burning experiments to evaluate smoke emissions and plume transport
Luxi Zhou; Kirk R. Baker; Sergey L. Napelenok; George Pouliot; Robert Elleman; Susan M. O' Neill; Shawn P. Urbanski; David C. Wong
2018-01-01
Crop residue burning is a common land management practice that results in emissions of a variety of pollutants with negative health impacts. Modeling systems are used to estimate air quality impacts of crop residue burning to support retrospective regulatory assessments and also for forecasting purposes. Ground and airborne measurements from a recent field experiment...
Wu, Weiwei; Yang, Huanjia; Chew, David; Hou, Yanhong; Li, Qiming
2014-01-01
Buildings' sustainability is one of the crucial parts for achieving urban sustainability. Applied to buildings, life-cycle assessment encompasses the analysis and assessment of the environmental effects of building materials, components and assemblies throughout the entire life of the building construction, use and demolition. Estimate of carbon emissions is essential and crucial for an accurate and reasonable life-cycle assessment. Addressing the need for more research into integrating analysis of real-time and automatic recording of key indicators for a more accurate calculation and comparison, this paper aims to design a real-time recording model of these crucial indicators concerning the calculation and estimation of energy use and carbon emissions of buildings based on a Radio Frequency Identification (RFID)-based system. The architecture of the RFID-based carbon emission recording/tracking system, which contains four functional layers including data record layer, data collection/update layer, data aggregation layer and data sharing/backup layer, is presented. Each of these layers is formed by RFID or network devices and sub-systems that operate at a specific level. In the end, a proof-of-concept system is developed to illustrate the implementation of the proposed architecture and demonstrate the feasibility of the design. This study would provide the technical solution for real-time recording system of building carbon emissions and thus is of great significance and importance to improve urban sustainability. PMID:24831109
Wu, Weiwei; Yang, Huanjia; Chew, David; Hou, Yanhong; Li, Qiming
2014-05-14
Buildings' sustainability is one of the crucial parts for achieving urban sustainability. Applied to buildings, life-cycle assessment encompasses the analysis and assessment of the environmental effects of building materials, components and assemblies throughout the entire life of the building construction, use and demolition. Estimate of carbon emissions is essential and crucial for an accurate and reasonable life-cycle assessment. Addressing the need for more research into integrating analysis of real-time and automatic recording of key indicators for a more accurate calculation and comparison, this paper aims to design a real-time recording model of these crucial indicators concerning the calculation and estimation of energy use and carbon emissions of buildings based on a Radio Frequency Identification (RFID)-based system. The architecture of the RFID-based carbon emission recording/tracking system, which contains four functional layers including data record layer, data collection/update layer, data aggregation layer and data sharing/backup layer, is presented. Each of these layers is formed by RFID or network devices and sub-systems that operate at a specific level. In the end, a proof-of-concept system is developed to illustrate the implementation of the proposed architecture and demonstrate the feasibility of the design. This study would provide the technical solution for real-time recording system of building carbon emissions and thus is of great significance and importance to improve urban sustainability.
The Benefits of Internalizing Air Quality and Greenhouse Gas Externalities in the US Energy System
NASA Astrophysics Data System (ADS)
Brown, Kristen E.
The emission of pollutants from energy use has effects on both local air quality and the global climate, but the price of energy does not reflect these externalities. This study aims to analyze the effect that internalizing these externalities in the cost of energy would have on the US energy system, emissions, and human health. In this study, we model different policy scenarios in which fees are added to emissions related to generation and use of energy. The fees are based on values of damages estimated in the literature and are applied to upstream and combustion emissions related to electricity generation, industrial energy use, transportation energy use, residential energy use, and commercial energy use. The energy sources and emissions are modeled through 2055 in five-year time steps. The emissions in 2045 are incorporated into a continental-scale atmospheric chemistry and transport model, CMAQ, to determine the change in air quality due to different emissions reduction scenarios. A benefit analysis tool, BenMAP, is used with the air quality results to determine the monetary benefit of emissions reductions related to the improved air quality. We apply fees to emissions associated with health impacts, climate change, and a combination of both. We find that the fees we consider lead to reductions in targeted emissions as well as co-reducing non-targeted emissions. For fees on the electric sector alone, health impacting pollutant (HIP) emissions reductions are achieved mainly through control devices while Greenhouse Gas (GHG) fees are addressed through changes in generation technologies. When sector specific fees are added, reductions come mainly from the industrial and electricity generation sectors, and are achieved through a mix of energy efficiency, increased use of renewables, and control devices. Air quality is improved in almost all areas of the country with fees, including when only GHG fees are applied. Air quality tends to improve more in regions with larger emissions reductions, especially for PM2.5.
Application for certification 1980 model year light-duty vehicles - Audi
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles, or heavy-duty engines submits to EPA an application for certification. In the application, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems, and exhaust and evaporative emission control systems. It also provides information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements to be followed during testing. Section 16 of the applicationmore » contains the results of emission testing, a statement of compliance to the regulations, production engine parameters, and a Summary Sheet Input Form on which issuance of a Certificate of Conformity is based.« less
Application for certification, 1990 model-year light-duty vehicles - Audi
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles, or heavy-duty engines submits to EPA an application for certification. In the application, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems and exhaust and evaporative emission control systems. It also provides information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements to be followed during testing. Section 16 of the applicationmore » contains the results of emission testing, a statement of compliance to the regulations, production engine parameters, and a Summary Sheet Input Form on which issuance of a Certificate of Conformity is based.« less
Application for certification 1993 model year light-duty vehicles - Audi
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles, or heavy-duty engines submits to EPA an application for certification. In the application, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems and exhaust and evaporative emission control systems. It also provides information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements to be followed during testing. Section 16 of the applicationmore » contains the results of emission testing, a statement of compliance to the regulations, production engine parameters, and a Summary Sheet Input Form on which issuance of a Certificate of Conformity is based.« less
Application for certification, 1991 model-year light-duty vehicles - Audi
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles, or heavy-duty engines submits to EPA an application for certification. In the application, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model-year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems and exhaust and evaporative emission control systems. It also provides information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements to be followed during testing. Section 16 of the application containsmore » the results of emission testing, a statement of compliance to the regulations, production engine parameters and a Summary Sheet Input Form on which issuance of a Certificate of Conformity is based.« less
Application for certification 1981 model year light-duty vehicles - Audi
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles, or heavy-duty engines submits to EPA an application for certification. In the application, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems and exhaust and evaporative emission control systems. It also provides information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements to be followed during testing. Section 16 of the applicationmore » contains the results of emission testing, a statement of compliance to the regulations, production engine parameters, and a Summary Sheet Input Form on which issuance of a Certificate of Conformity is based.« less
Application for certification 1987 model year light-duty vehicles - Peugeot
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles, or heavy-duty engines submits to EPA an application for certification. In the application, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model year. The engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems and exhaust and evaporative emission control systems. They also provide information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements to be followed during testing. Section 16 of the applicationmore » contains the results of emission testing, a statement of compliance to the regulations, production engine parameters, and a Summary Sheet Input Form on which issuance of a Certificate of Conformity is based.« less
Application for certification 1981 model year light-duty vehicles - Peugeot
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles, or heavy-duty engines submits to EPA an application for certification. In the application, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems and exhaust and evaporative emission control systems. It also provides information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements to be followed during testing. Section 16 of the applicationmore » contains the results of emission testing, a statement of compliance to the regulations, production engine parameters, and a Summary Sheet Input Form on which issuance of a Certificate of Conformity is based.« less
Ma, Yuchun; Schwenke, Graeme; Sun, Liying; Liu, De Li; Wang, Bin; Yang, Bo
2018-07-15
Limited information exists on potential impacts of climate change on nitrous oxide (N 2 O) emissions by including N 2 -fixing legumes in crop rotations from rain-fed cropping systems. Data from two 3-yr crop rotations in northern NSW, Australia, viz. chickpea-wheat-barley (CpWB) and canola-wheat-barley (CaWB), were used to gain an insight on the role of legumes in mitigation of N 2 O emissions. High-frequency N 2 O fluxes measured with an automated system of static chambers were utilized to test the applicability of Denitrification and Decomposition model. The DNDC model was run using the on-site observed weather, soil and farming management conditions as well as the representative concentration pathways adopted by the Intergovernmental Panel on Climate Change in its Fifth Assessment Report. The DNDC model captured the cumulative N 2 O emissions with variations falling within the deviation ranges of observations (0.88±0.31kgNha -1 rotation -1 for CpWB, 1.44±0.02kgNha -1 rotation -1 for CaWB). The DNDC model can be used to predict between modeled and measured N 2 O flux values for CpWB (n=390, RSR=0.45) and CaWB (n=390, RSR=0.51). Long-term (80-yr) simulations were conducted with RCP 4.5 representing a global greenhouse gas stabilization scenario, as well RCP 8.5 representing a very high greenhouse gas emission scenario based on RCP scenarios. Compared with the baseline scenarios for CpWB and CaWB, the long-term simulation results under RCP scenarios showed that, (1) N 2 O emissions would increase by 35-44% for CpWB and 72-76% for CaWB under two climate scenarios; (2) grain yields would increase by 9% and 18% under RCP 4.5, and 2% and 14% under RCP 8.5 for CpWB and CaWB, respectively; and (3) yield-scaled N 2 O-N emission would increase by 24-42% for CpWB and 46-54% for CaWB under climate scenarios, respectively. Our results suggest that 25% of the yield-scaled N 2 O-N emission would be saved by switching to a legume rotation under climate change conditions. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.
Can dust emission mechanisms be determined from field measurements?
NASA Astrophysics Data System (ADS)
Klose, Martina; Webb, Nicholas; Gill, Thomas E.; Van Pelt, Scott; Okin, Gregory
2017-04-01
Field observations are needed to develop and test theories on dust emission for use in dust modeling systems. The dust emission mechanism (aerodynamic entrainment, saltation bombardment, aggregate disintegration) as well as the amount and particle-size distribution of emitted dust may vary under sediment supply- and transport-limited conditions. This variability, which is caused by heterogeneity of the surface and the atmosphere, cannot be fully captured in either field measurements or models. However, uncertainty in dust emission modeling can be reduced through more detailed observational data on the dust emission mechanism itself. To date, most measurements do not provide enough information to allow for a determination of the mechanisms leading to dust emission and often focus on a small variety of soil and atmospheric settings. Additionally, data sets are often not directly comparable due to different measurement setups. As a consequence, the calibration of dust emission schemes has so far relied on a selective set of observations, which leads to an idealization of the emission process in models and thus affects dust budget estimates. Here, we will present results of a study which aims to decipher the dust emission mechanism from field measurements as an input for future model development. Detailed field measurements are conducted, which allow for a comparison of dust emission for different surface and atmospheric conditions. Measurements include monitoring of the surface, loose erodible material, transported sediment, and meteorological data, and are conducted in different environmental settings in the southwestern United States. Based on the field measurements, a method is developed to differentiate between the different dust emission mechanisms.
Multiple Sensitivity Testing for Regional Air Quality Model in summer 2014
NASA Astrophysics Data System (ADS)
Tang, Y.; Lee, P.; Pan, L.; Tong, D.; Kim, H. C.; Huang, M.; Wang, J.; McQueen, J.; Lu, C. H.; Artz, R. S.
2015-12-01
The NOAA Air Resources laboratory leads to improve the performance of the U.S. Air Quality Forecasting Capability (NAQFC). It is operational in NOAA National Centers for Environmental Prediction (NCEP) which focuses on predicting surface ozone and PM2.5. In order to improve its performance, we tested several approaches, including NOAA Environmental Modeling System Global Aerosol Component (NGAC) simulation derived ozone and aerosol lateral boundary conditions (LBC), bi-direction NH3 emission and HMS(Hazard Mapping System)-BlueSky emission with the latest U.S. EPA Community Multi-scale Air Quality model (CMAQ) version and the U.S EPA National Emission Inventory (NEI)-2011 anthropogenic emissions. The operational NAQFC uses static profiles for its lateral boundary condition (LBC), which does not impose severe issue for near-surface air quality prediction. However, its degraded performance for the upper layer (e.g. above 3km) is evident when comparing with aircraft measured ozone. NCEP's Global Forecast System (GFS) has tracer O3 prediction treated as 3-D prognostic variable (Moorthi and Iredell, 1998) after being initialized with Solar Backscatter Ultra Violet-2 (SBUV-2) satellite data. We applied that ozone LBC to the CMAQ's upper layers and yield more reasonable O3 prediction than that with static LBC comparing with the aircraft data in Discover-AQ Colorado campaign. NGAC's aerosol LBC also improved the PM2.5 prediction with more realistic background aerosols. The bi-direction NH3 emission used in CMAQ also help reduce the NH3 and nitrate under-prediction issue. During summer 2014, strong wildfires occurred in northwestern USA, and we used the US Forest Service's BlueSky fire emission with HMS fire counts to drive CMAQ and tested the difference of day-1 and day-2 fire emission estimation. Other related issues were also discussed.
Code of Federal Regulations, 2010 CFR
2010-07-01
...—Requirements for Continuous Emission Monitoring Systems (CEMS) For the following pollutants Use the following span values for CEMS Use the following performance specifications in appendix B of this part for your CEMS If needed to meet minimum data requirements, use the folloiwng alternate methods in appendix A of...
Code of Federal Regulations, 2011 CFR
2011-07-01
...—Requirements for Continuous Emission Monitoring Systems (CEMS) For the following pollutants Use the following span values for CEMS Use the following performance specifications in appendix B of this part for your CEMS If needed to meet minimum data requirements, use the folloiwng alternate methods in appendix A of...
Lengers, Bernd; Schiefler, Inga; Büscher, Wolfgang
2013-12-01
The overall measurement of farm level greenhouse gas (GHG) emissions in dairy production is not feasible, from either an engineering or administrative point of view. Instead, computational model systems are used to generate emission inventories, demanding a validation by measurement data. This paper tests the GHG calculation of the dairy farm-level optimization model DAIRYDYN, including methane (CH₄) from enteric fermentation and managed manure. The model involves four emission calculation procedures (indicators), differing in the aggregation level of relevant input variables. The corresponding emission factors used by the indicators range from default per cow (activity level) emissions up to emission factors based on feed intake, manure amount, and milk production intensity. For validation of the CH₄ accounting of the model, 1-year CH₄ measurements of an experimental free-stall dairy farm in Germany are compared to model simulation results. An advantage of this interdisciplinary study is given by the correspondence of the model parameterization and simulation horizon with the experimental farm's characteristics and measurement period. The results clarify that modeled emission inventories (2,898, 4,637, 4,247, and 3,600 kg CO₂-eq. cow(-1) year(-1)) lead to more or less good approximations of online measurements (average 3,845 kg CO₂-eq. cow(-1) year(-1) (±275 owing to manure management)) depending on the indicator utilized. The more farm-specific characteristics are used by the GHG indicator; the lower is the bias of the modeled emissions. Results underline that an accurate emission calculation procedure should capture differences in energy intake, owing to milk production intensity as well as manure storage time. Despite the differences between indicator estimates, the deviation of modeled GHGs using detailed indicators in DAIRYDYN from on-farm measurements is relatively low (between -6.4% and 10.5%), compared with findings from the literature.
NASA Astrophysics Data System (ADS)
Christen, Andreas; Johnson, Mark; Molodovskaya, Marina; Ketler, Rick; Nesic, Zoran; Crawford, Ben; Giometto, Marco; van der Laan, Mike
2013-04-01
The most important long-lived greenhouse gas (LLGHG) emitted during combustion of fuels is carbon dioxide (CO2), however also traces of the LLGHGs methane (CH4) and nitrous oxide (N2O) are released, the quantities of which depend largely on the conditions of the combustion process. Emission factors determine the mass of LLGHGs emitted per energy used (or kilometre driven for cars) and are key inputs for bottom-up emission modelling. Emission factors for CH4 are typically determined in the laboratory or on a test stand for a given combustion system using a small number of samples (vehicles, furnaces), yet associated with larger uncertainties when scaled to entire fleets. We propose an alternative, different approach - Can integrated emission factors be independently determined using direct micrometeorological flux measurements over an urban surface? If so, do emission factors determined from flux measurements (top-down) agree with up-scaled emission factors of relevant combustion systems (heating, vehicles) in the source area of the flux measurement? Direct flux measurements of CH4 were carried out between February and May, 2012 over a relatively densely populated, urban surface in Vancouver, Canada by means of eddy covariance (EC). The EC-system consisted of an ultrasonic anemometer (CSAT-3, Campbell Scientific Inc.) and two open-path infrared gas analyzers (Li7500 and Li7700, Licor Inc.) on a tower at 30m above the surface. The source area of the EC system is characterised by a relative homogeneous morphometry (5.3m average building height), but spatially and temporally varying emission sources, including two major intersecting arterial roads (70.000 cars drive through the 50% source area per day) and seasonal heating in predominantly single-family houses (natural gas). An inverse dispersion model (turbulent source area model), validated against large eddy simulations (LES) of the urban roughness sublayer, allows the determination of the spatial area that contributes to each measurement interval (30 min), which varies with wind direction and stability. A detailed geographic information system of the urban surface combined with traffic counts and building energy models makes it possible to statistically relate fluxes to vehicle density (km driven) and buildings (gas heated volume) - and ultimately quantify the contribution of space heating, transport sector and fugitive emissions to the total emitted CH4 from an urban environment. The measured fluxes of CH4 over the selected urban environment averaged to 22.8 mg CH4 m-2 day-1 during the study period. Compared with the simultaneously measured CO2 emissions, the contribution of CH4, however, accounts for only about 3% of the total LLGHG emissions from this particular urban surface. Traffic contributed 8.8 mg CH4 m-2 day-1, equivalent to 39% of the total CH4 flux. The determined emission factor for the typical fleet composition is 0.062 g CH4 per km driven which is higher than upscaled fleet emission factors (EPA) by a factor of two. This discrepancy can be partially explained through the slower city traffic with frequent idling (traffic congestion), fleet composition and cold starts. Emissions of CH4 by domestic space heating (55% of the total CH4 flux or 12.7 mg CH4 m-2 day-1) are also higher than estimated from upscaled emission factors. There is no evidence of substantial unknown sources such as soil processes, combustion of wood, and leakages from gas distribution pipes (residual: 6% or 1.3 mg CH4 m-2 day-1). The presented study is among the first direct measurements of CH4 emissions over an urban surface and demonstrates that flux measurements of greenhouse gases can be used to determine sources and emission factors in complex urban situations.
Operational air quality forecasting system for Spain: CALIOPE
NASA Astrophysics Data System (ADS)
Baldasano, J. M.; Piot, M.; Jorba, O.; Goncalves, M.; Pay, M.; Pirez, C.; Lopez, E.; Gasso, S.; Martin, F.; García-Vivanco, M.; Palomino, I.; Querol, X.; Pandolfi, M.; Dieguez, J. J.; Padilla, L.
2009-12-01
The European Commission (EC) and the United States Environmental Protection Agency (US-EPA) have shown great concerns to understand the transport and dynamics of pollutants in the atmosphere. According to the European directives (1996/62/EC, 2002/3/EC, 2008/50/EC), air quality modeling, if accurately applied, is a useful tool to understand the dynamics of air pollutants, to analyze and forecast the air quality, and to develop programs reducing emissions and alert the population when health-related issues occur. The CALIOPE project, funded by the Spanish Ministry of the Environment, has the main objective to establish an air quality forecasting system for Spain. A partnership of four research institutions composes the CALIOPE project: the Barcelona Supercomputing Center (BSC), the center of investigation CIEMAT, the Earth Sciences Institute ‘Jaume Almera’ (IJA-CSIC) and the CEAM Foundation. CALIOPE will become the official Spanish air quality operational system. This contribution focuses on the recent developments and implementation of the integrated modelling system for the Iberian Peninsula (IP) and Canary Islands (CI) with a high spatial and temporal resolution (4x4 sq. km for IP and 2x2 sq. km for CI, 1 hour), namely WRF-ARW/HERMES04/CMAQ/BSC-DREAM. The HERMES04 emission model has been specifically developed as a high-resolution (1x1 sq. km, 1 hour) emission model for Spain. It includes biogenic and anthropogenic emissions such as on-road and paved-road resuspension production, power plant generation, ship and plane traffic, airports and ports activities, industrial and agricultural sectors as well as domestic and commercial emissions. The qualitative and quantitative evaluation of the model was performed for a reference year (2004) using data from ground-based measurement networks. The products of the CALIOPE system will provide 24h and 48h forecasts for O3, NO2, SO2, CO, PM10 and PM2.5 at surface level. An operational evaluation system has been developed to provide near real-time evaluation products for the Spanish territory. For this purpose, more than 130 surface stations, 2 ozonesondes and the OMI satellite retrieval information are introduced to the system on a daily basis. A web-based visualization system allows a straightforward access to all the evaluation products. The present contribution will describe the main characteristics of the operational system and results of the operational evaluation.
Chamber study of PCB emissions from caulking materials and light ballasts.
Liu, Xiaoyu; Guo, Zhishi; Krebs, Kenneth A; Stinson, Rayford A; Nardin, Joshua A; Pope, Robert H; Roache, Nancy F
2015-10-01
The emissions of polychlorinated biphenyl (PCB) congeners from thirteen caulk samples were tested in a micro-chamber system. Twelve samples were from PCB-contaminated buildings and one was prepared in the laboratory. Nineteen light ballasts collected from buildings that represent 13 different models from five manufacturers were tested in 53-L environmental chambers. The rates of PCB congener emissions from caulking materials and light ballasts were determined. Several factors that may have affected the emission rates were evaluated. The experimentally determined emission factors showed that, for a given PCB congener, there is a linear correlation between the emission factor and the concentration of the PCB congener in the source. Furthermore, the test results showed that an excellent log-linear correlation exists between the normalized emission factor and the vapor pressure (coefficient of determination, r(2)⩾0.8846). The PCB congener emissions from ballasts at or near room temperature were relatively low with or without electrical load. However, the PCB congener emission rates increased significantly as the temperature increased. The results of this research provide new data and models for ranking the primary sources of PCBs and supports the development and refinement of exposure assessment models for PCBs. Published by Elsevier Ltd.
Global modelling of Cryptosporidium in surface water
NASA Astrophysics Data System (ADS)
Vermeulen, Lucie; Hofstra, Nynke
2016-04-01
Introduction Waterborne pathogens that cause diarrhoea, such as Cryptosporidium, pose a health risk all over the world. In many regions quantitative information on pathogens in surface water is unavailable. Our main objective is to model Cryptosporidium concentrations in surface waters worldwide. We present the GloWPa-Crypto model and use the model in a scenario analysis. A first exploration of global Cryptosporidium emissions to surface waters has been published by Hofstra et al. (2013). Further work has focused on modelling emissions of Cryptosporidium and Rotavirus to surface waters from human sources (Vermeulen et al 2015, Kiulia et al 2015). A global waterborne pathogen model can provide valuable insights by (1) providing quantitative information on pathogen levels in data-sparse regions, (2) identifying pathogen hotspots, (3) enabling future projections under global change scenarios and (4) supporting decision making. Material and Methods GloWPa-Crypto runs on a monthly time step and represents conditions for approximately the year 2010. The spatial resolution is a 0.5 x 0.5 degree latitude x longitude grid for the world. We use livestock maps (http://livestock.geo-wiki.org/) combined with literature estimates to calculate spatially explicit livestock Cryptosporidium emissions. For human Cryptosporidium emissions, we use UN population estimates, the WHO/UNICEF JMP sanitation country data and literature estimates of wastewater treatment. We combine our emissions model with a river routing model and data from the VIC hydrological model (http://vic.readthedocs.org/en/master/) to calculate concentrations in surface water. Cryptosporidium survival during transport depends on UV radiation and water temperature. We explore pathogen emissions and concentrations in 2050 with the new Shared Socio-economic Pathways (SSPs) 1 and 3. These scenarios describe plausible future trends in demographics, economic development and the degree of global integration. Results and Conclusions GloWPa-Crypto is the first global model that can be used to analyse dynamics in surface water pathogen concentrations worldwide. Global human Cryptosporidium emissions are estimated at 1 x 10^17 oocysts/ year for the year 2010.We estimated future emissions for SSP1 and SSP3. Preliminary results show that for SSP1human emissions are approximately halved by 2050. The SSP3 human emissions are 1.5 times higher than the 2010 emissions due to increased population growth and urbanisation. Livestock Cryptosporidium emissions are expected to increase under both SSP1 and SSP3, as meat consumption continues to rise. We conclude that population growth, urbanization, changes in sanitation systems and treatment, and changes in livestock consumption and production systems are important processes that determine future Cryptosporidium emissions to surface water. References Hofstra N, Bouwman A F, Beusen A H W and Medema G J 2013 Exploring global Cryptosporidium emissions to surface water Sci. Total Environ. 442 10-9 Kiulia N M, Hofstra N, Vermeulen L C, Obara M A, Medema G J and Rose J B 2015 Global occurrence and emission of rotaviruses to surface waters Pathogens 4 229-55 Vermeulen L C, De Kraker J, Hofstra N, Kroeze C and Medema G J 2015 Modelling the impact of sanitation, population and urbanization estimates on human emissions of Cryptosporidium to surface waters - a case study for Bangladesh and India Environ. Res. Lett. 10
Vehicle-specific emissions modeling based upon on-road measurements.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jackson, Brian K.; Lewis, Nikole K.; Showman, Adam P.
2012-06-01
We present a new model for Ellipsoidal Variations Induced by a Low-Mass Companion, the EVIL-MC model. We employ several approximations appropriate for planetary systems to substantially increase the computational efficiency of our model relative to more general ellipsoidal variation models and improve upon the accuracy of simpler models. This new approach gives us a unique ability to rapidly and accurately determine planetary system parameters. We use the EVIL-MC model to analyze Kepler Quarter 0-2 (Q0-2) observations of the HAT-P-7 system, an F-type star orbited by a {approx} Jupiter-mass companion. Our analysis corroborates previous estimates of the planet-star mass ratio qmore » = (1.10 {+-} 0.06) Multiplication-Sign 10{sup -3}, and we have revised the planet's dayside brightness temperature to 2680{sup +10}{sub -20} K. We also find a large difference between the day- and nightside planetary flux, with little nightside emission. Preliminary dynamical+radiative modeling of the atmosphere indicates that this result is qualitatively consistent with high altitude absorption of stellar heating. Similar analyses of Kepler and CoRoT photometry of other planets using EVIL-MC will play a key role in providing constraints on the properties of many extrasolar systems, especially given the limited resources for follow-up and characterization of these systems. However, as we highlight, there are important degeneracies between the contributions from ellipsoidal variations and planetary emission and reflection. Consequently, for many of the hottest and brightest Kepler and CoRoT planets, accurate estimates of the planetary emission and reflection, diagnostic of atmospheric heat budgets, will require accurate modeling of the photometric contribution from the stellar ellipsoidal variation.« less
Vaquero, Juan José; Kinahan, Paul
2015-01-01
Positron emission tomography (PET) imaging is based on detecting two time-coincident high-energy photons from the emission of a positron-emitting radioisotope. The physics of the emission, and the detection of the coincident photons, give PET imaging unique capabilities for both very high sensitivity and accurate estimation of the in vivo concentration of the radiotracer. PET imaging has been widely adopted as an important clinical modality for oncological, cardiovascular, and neurological applications. PET imaging has also become an important tool in preclinical studies, particularly for investigating murine models of disease and other small-animal models. However, there are several challenges to using PET imaging systems. These include the fundamental trade-offs between resolution and noise, the quantitative accuracy of the measurements, and integration with X-ray computed tomography and magnetic resonance imaging. In this article, we review how researchers and industry are addressing these challenges.
Vaquero, Juan José; Kinahan, Paul
2017-01-01
Positron emission tomography (PET) imaging is based on detecting two time-coincident high-energy photons from the emission of a positron-emitting radioisotope. The physics of the emission, and the detection of the coincident photons, give PET imaging unique capabilities for both very high sensitivity and accurate estimation of the in vivo concentration of the radiotracer. PET imaging has been widely adopted as an important clinical modality for oncological, cardiovascular, and neurological applications. PET imaging has also become an important tool in preclinical studies, particularly for investigating murine models of disease and other small-animal models. However, there are several challenges to using PET imaging systems. These include the fundamental trade-offs between resolution and noise, the quantitative accuracy of the measurements, and integration with X-ray computed tomography and magnetic resonance imaging. In this article, we review how researchers and industry are addressing these challenges. PMID:26643024
Multiscale optical imaging of rare-earth-doped nanocomposites in a small animal model
NASA Astrophysics Data System (ADS)
Higgins, Laura M.; Ganapathy, Vidya; Kantamneni, Harini; Zhao, Xinyu; Sheng, Yang; Tan, Mei-Chee; Roth, Charles M.; Riman, Richard E.; Moghe, Prabhas V.; Pierce, Mark C.
2018-03-01
Rare-earth-doped nanocomposites have appealing optical properties for use as biomedical contrast agents, but few systems exist for imaging these materials. We describe the design and characterization of (i) a preclinical system for whole animal in vivo imaging and (ii) an integrated optical coherence tomography/confocal microscopy system for high-resolution imaging of ex vivo tissues. We demonstrate these systems by administering erbium-doped nanocomposites to a murine model of metastatic breast cancer. Short-wave infrared emissions were detected in vivo and in whole organ imaging ex vivo. Visible upconversion emissions and tissue autofluorescence were imaged in biopsy specimens, alongside optical coherence tomography imaging of tissue microstructure. We anticipate that this work will provide guidance for researchers seeking to image these nanomaterials across a wide range of biological models.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jardine, Kolby
In conjunction with the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility GoAmazon campaign, the Terrestrial Ecosystem Science (TES)-funded Green Ocean Amazon (GoAmazon 2014/15) terrestrial ecosystem project (Geco) was designed to: • evaluate the strengths and weaknesses of leaf-level algorithms for biogenic volatile organic compounds (BVOCs) emissions in Amazon forests near Manaus, Brazil, and • conduct mechanistic field studies to characterize biochemical and physiological processes governing leaf- and landscape-scale tropical forest BVOC emissions, and the influence of environmental drivers that are expected to change with a warming climate. Through a close interaction between modeling and observationalmore » activities, including the training of MS and PhD graduate students, post-doctoral students, and technicians at the National Institute for Amazon Research (INPA), the study aimed at improving the representation of BVOC-mediated biosphere-atmosphere interactions and feedbacks under a warming climate. BVOCs can form cloud condensation nuclei (CCN) that influence precipitation dynamics and modify the quality of down welling radiation for photosynthesis. However, our ability to represent these coupled biosphere-atmosphere processes in Earth system models suffers from poor understanding of the functions, identities, quantities, and seasonal patterns of BVOC emissions from tropical forests as well as their biological and environmental controls. The Model of Emissions of Gases and Aerosols from Nature (MEGAN), the current BVOC sub-model of the Community Earth System Model (CESM), was evaluated to explore mechanistic controls over BVOC emissions. Based on that analysis, a combination of observations and experiments were studied in forests near Manaus, Brazil, to test existing parameterizations and algorithm structures in MEGAN. The model was actively modified as needed to improve tropical BVOC emission simulations on a regional scale.« less
NASA Astrophysics Data System (ADS)
Ding, Aiju
2000-10-01
A large seasonal variation in methane emission from Texas rice fields was observed in most of the growing seasons from 1989 through 1997. In general, the pattern showed small fluxes in the early season of cultivation and reached maximum at post-heading time, then declined and stopped after fields were drained. The amount of methane emission positively relates to the aboveground biomass, the number of effective stems and tillers, and nitrogen addition. The day-to-day pattern of methane emissions was similar among all cultivars. The seasonal total methane emission shows a significant positive correlation with post-heading plant height. The total methane emission from Texas rice fields was estimated as 33.25 × 109 g in 1993, ranging from 25.85 × 109 g/yr to 40.65 × 109 g/yr. A mitigation technique was developed to obtain both high yield and less methane emission from Texas rice fields. A new approach was also developed to evaluate regional to large-scale methane emission from irrigated rice paddies. By combining modeling, ground truth information and remote sensing into a Geographic Information System (GIS)-a computer based system, the seasonal methane emission from a large area can be calculated efficiently and more accurately. The methodology was tested at the Richmond Irrigation District (RID) site in Texas. The average daily methane emission varied from field to field and even within a single field. The calculated seasonal total methane emission from RID rice fields was as low as 3.34 × 108 g CH4 in 1996 and as high as 7.80 × 108 g CH4 in 1998. To support the application of the estimation method in a worldwide study, an algorithm describing the mapping of irrigated rice paddies from Landsat TM data was demonstrated. The accuracy in 1998- supervised classification approached 95% when cloud cover was taken into account. Model uncertainty and data availability are the two major potential problems in worldwide application of the new approach. A potential alternative model is proposed which allows estimation of regional methane emission from rice plant height.
NASA Astrophysics Data System (ADS)
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.
THE EMISSION PROCESSING SYSTEM FOR THE ETA/CMAQ AIR QUALITY FORECAST SYSTEM
NOAA and EPA have created an Air Quality Forecast (AQF) system. This AQF system links an adaptation of the EPA's Community Multiscale Air Quality Model with the 12 kilometer ETA model running operationally at NOAA's National Center for Environmental Predication (NCEP). One of th...
NASA Astrophysics Data System (ADS)
Song, S.; Kim, Y.; Shon, Z.; Kang, Y.; Jeong, J.
2012-12-01
The impact of pollutant emissions by the huge amount of road traffic around beaches on the ozone (O3) concentrations in the surrounding regions were evaluated using a numerical modeling approach during the beach opening period (BOP) (July to August). This analysis was performed based on two simulation conditions: 1) with mobile emissions during the BOP (i.e. BOP case); and 2) during the normal period (i.e. NOR case). On-road mobile emissions were estimated from the emission factors, vehicle kilometers traveled, and deterioration factors at several roads close to beaches in Busan, Korea during a 4-day observation period (29 and 31 July and 1 and 3 August) of the BOP in 2010. The emission data was then applied to the 3-D chemical transport model (i.e. the WRF-CMAQ modeling system). A process analysis (PA) was also used to assess the contributions of the individual physical and chemical processes to the production or loss of O3 in the study area. The model study suggested the possibility that road traffic emissions near the beach area can have a direct impact on the O3 concentrations in the source regions as well as their surrounding/downwind regions. The maximum negative impact of mobile emissions on the O3 concentrations between the BOP and NOR cases was predicted near the beach areas: by -4 ppb during the day due to the high NOx emissions with the high NOx/VOC ratio and -8 ppb during the late evening due to the fast titration of O3 by NO. The PA showed that the rate of O3 destruction due to the road traffic emissions around the beach areas decreased by -2.3 (weekend, 31 July) and -5.5 ppb h-1 (weekday, 3 August) during the day. Acknowledgments: This work was funded by the Korea Meteorological Administration Research and Development Program under Grant CATER_2012-6140. This work was also funded by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0021141).
NASA Astrophysics Data System (ADS)
Wu, D.; Lin, J. C.; Oda, T.; Ye, X.; Lauvaux, T.; Yang, E. G.; Kort, E. A.
2017-12-01
Urban regions are large emitters of CO2 whose emission inventories are still associated with large uncertainties. Therefore, a strong need exists to better quantify emissions from megacities using a top-down approach. Satellites — e.g., the Orbiting Carbon Observatory 2 (OCO-2), provide a platform for monitoring spatiotemporal column CO2 concentrations (XCO2). In this study, we present a Lagrangian receptor-oriented model framework and evaluate "model-retrieved" XCO2 by comparing against OCO-2-retrieved XCO2, for three megacities/regions (Riyadh, Cairo and Pearl River Delta). OCO-2 soundings indicate pronounced XCO2 enhancements (dXCO2) when crossing Riyadh, which are successfully captured by our model with a slight latitude shift. From this model framework, we can identify and compare the relative contributions of dXCO2 resulted from anthropogenic emission versus biospheric fluxes. In addition, to impose constraints on emissions for Riyadh through inversion methods, three uncertainties sources are addressed in this study, including 1) transport errors, 2) receptor and model setups in atmospheric models, and 3) urban emission uncertainties. For 1), we calculate transport errors by adding a wind error component to randomize particle distributions. For 2), a set of sensitivity tests using bootstrap method is performed to describe proper ways to setup receptors in Lagrangian models. For 3), both emission uncertainties from the Fossil Fuel Data Assimilation System (FFDAS) and the spread among three emission inventories are used to approximate an overall fractional uncertainty in modeled anthropogenic signal (dXCO2.anthro). Lastly, we investigate the definition of background (clean) XCO2 for megacities from retrieved XCO2 by means of statistical tools and our model framework.
A multi-scale comparison of modeled and observed seasonal methane emissions in northern wetlands
Xu, Xiyan; Riley, William J.; Koven, Charles D.; ...
2016-09-13
Wetlands are the largest global natural methane (CH 4) source, and emissions between 50 and 70° N latitude contribute 10-30 % to this source. Predictive capability of land models for northern wetland CH 4 emissions is still low due to limited site measurements, strong spatial and temporal variability in emissions, and complex hydrological and biogeochemical dynamics. To explore this issue, we compare wetland CH 4 emission predictions from the Community Land Model 4.5 (CLM4.5-BGC) with site- to regional-scale observations. A comparison of the CH 4 fluxes with eddy flux data highlighted needed changes to the model's estimate of aerenchyma area,more » which we implemented and tested. The model modification substantially reduced biases in CH 4 emissions when compared with CarbonTracker CH 4 predictions. CLM4.5 CH 4 emission predictions agree well with growing season (May–September) CarbonTracker Alaskan regional-level CH 4 predictions and site-level observations. However, CLM4.5 underestimated CH 4 emissions in the cold season (October–April). The monthly atmospheric CH 4 mole fraction enhancements due to wetland emissions are also assessed using the Weather Research and Forecasting-Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) model coupled with daily emissions from CLM4.5 and compared with aircraft CH 4 mole fraction measurements from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) campaign. Both the tower and aircraft analyses confirm the underestimate of cold-season CH 4 emissions by CLM4.5. The greatest uncertainties in predicting the seasonal CH 4 cycle are from the wetland extent, cold-season CH 4 production and CH 4 transport processes. We recommend more cold-season experimental studies in high-latitude systems, which could improve the understanding and parameterization of ecosystem structure and function during this period. Predicted CH 4 emissions remain uncertain, but we show here that benchmarking against observations across spatial scales can inform model structural and parameter improvements.« less
A multi-scale comparison of modeled and observed seasonal methane emissions in northern wetlands
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, Xiyan; Riley, William J.; Koven, Charles D.
Wetlands are the largest global natural methane (CH 4) source, and emissions between 50 and 70° N latitude contribute 10-30 % to this source. Predictive capability of land models for northern wetland CH 4 emissions is still low due to limited site measurements, strong spatial and temporal variability in emissions, and complex hydrological and biogeochemical dynamics. To explore this issue, we compare wetland CH 4 emission predictions from the Community Land Model 4.5 (CLM4.5-BGC) with site- to regional-scale observations. A comparison of the CH 4 fluxes with eddy flux data highlighted needed changes to the model's estimate of aerenchyma area,more » which we implemented and tested. The model modification substantially reduced biases in CH 4 emissions when compared with CarbonTracker CH 4 predictions. CLM4.5 CH 4 emission predictions agree well with growing season (May–September) CarbonTracker Alaskan regional-level CH 4 predictions and site-level observations. However, CLM4.5 underestimated CH 4 emissions in the cold season (October–April). The monthly atmospheric CH 4 mole fraction enhancements due to wetland emissions are also assessed using the Weather Research and Forecasting-Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) model coupled with daily emissions from CLM4.5 and compared with aircraft CH 4 mole fraction measurements from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) campaign. Both the tower and aircraft analyses confirm the underestimate of cold-season CH 4 emissions by CLM4.5. The greatest uncertainties in predicting the seasonal CH 4 cycle are from the wetland extent, cold-season CH 4 production and CH 4 transport processes. We recommend more cold-season experimental studies in high-latitude systems, which could improve the understanding and parameterization of ecosystem structure and function during this period. Predicted CH 4 emissions remain uncertain, but we show here that benchmarking against observations across spatial scales can inform model structural and parameter improvements.« less
Cities worldwide face the challenges of accommodating a growing population, while reducing emissions to meet climate mitigation targets. Public transit investments are often proposed as a way to curb emissions while maintaining healthy urban economies. However, cities face a syst...
USDA-ARS?s Scientific Manuscript database
Abstract: Dairy production, along with all other types of animal agriculture, is a recognized source of greenhouse gas (GHG) emissions, but little information exists on the net emissions from our farms. Component models for representing all important sources and sinks of CH4, N2O, and CO2 in dairy p...
NASA Astrophysics Data System (ADS)
Vara Vela, A. L.; Muñoz, A.; Lomas, A., Sr.; González, C. M.; Calderon, M. G.; Andrade, M. D. F.
2017-12-01
The Weather Research and Forecasting with Chemistry (WRF-Chem) community model have been widely used for the study of pollutants transport, formation of secondary pollutants, as well as for the assessment of air quality policies implementation. A key factor to improve the WRF-Chem air quality simulations over urban areas is the representation of anthropogenic emission sources. There are several tools that are available to assist users in creating their own emissions based on global emissions information (e.g. anthro_emiss, prep_chem_src); however, there is no single tool that will construct local emissions input datasets for any particular domain at this time. Because the official emissions pre-processor (emiss_v03) is designed to work with domains located over North America, this work presents the Another Assimilation System for WRF-Chem (AAS4WRF), a ncl based mass-conserving emissions pre-processor designed to create WRF-Chem ready emissions files from local inventories on a lat/lon projection. AAS4WRF is appropriate to scale emission rates from both surface and elevated sources, providing the users an alternative way to assimilate their emissions to WRF-Chem. Since it was successfully tested for the first time for the city of Lima, Peru in 2014 (managed by SENAMHI, the National Weather Service of the country), several studies on air quality modelling have applied this utility to convert their emissions to those required for WRF-Chem. Two case studies performed in the metropolitan areas of Sao Paulo and Manizales in Brazil and Colombia, respectively, are here presented in order to analyse the influence of using local or global emission inventories in the representation of regulated air pollutants such as O3 and PM2.5. Although AAS4WRF works with local emissions information at the moment, further work is being conducted to make it compatible with global/regional emissions data file format. The tool is freely available upon request to the corresponding author.
Bian, Rongxing; Xin, Danhui; Chai, Xiaoli
2018-01-01
Global climate change and ecological problems brought about by greenhouse gas effect have become a severe threat to humanity in the 21st century. Vegetation plays an important role in methane (CH 4 ) transport, oxidation and emissions from municipal solid waste (MSW) landfills as it modifies the physical and chemical properties of the cover soil, and transports CH 4 to the atmosphere directly via their conduits, which are mainly aerenchymatous structures. In this study, a novel 2-D simulation CH 4 emission model was established, based on an interactive mechanism of cover soil and vegetation, to model CH 4 transport, oxidation and emissions in landfill cover soil. Results of the simulation model showed that the distribution of CH 4 concentration and emission fluxes displayed a significant difference between vegetated and non-vegetated areas. CH 4 emission flux was 1-2 orders of magnitude higher than bare areas in simulation conditions. Vegetation play a negative role in CH 4 emissions from landfill cover soil due to the strong CH 4 transport capacity even though vegetation also promotes CH 4 oxidation via changing properties of cover soil and emitting O 2 via root system. The model will be proposed to allow decision makers to reconsider the actual CH 4 emission from vegetated and non-vegetated covered landfills. Copyright © 2017 Elsevier Ltd. All rights reserved.
Ng, Carla A.; von Goetz, Natalie
2016-01-01
Background: Food is a major pathway for human exposure to hazardous chemicals. The modern food system is becoming increasingly complex and globalized, but models for food-borne exposure typically assume locally derived diets or use concentrations directly measured in foods without accounting for food origin. Such approaches may not reflect actual chemical intakes because concentrations depend on food origin, and representative analysis is seldom available. Processing, packaging, storage, and transportation also impart different chemicals to food and are not yet adequately addressed. Thus, the link between environmental emissions and realistic human exposure is effectively broken. Objectives: We discuss the need for a fully integrated treatment of the modern industrialized food system, and we propose strategies for using existing models and relevant supporting data sources to track chemicals during production, processing, packaging, storage, and transport. Discussion: Fate and bioaccumulation models describe how chemicals distribute in the environment and accumulate through local food webs. Human exposure models can use concentrations in food to determine body burdens based on individual or population characteristics. New models now include the impacts of processing and packaging but are far from comprehensive. We propose to close the gap between emissions and exposure by utilizing a wider variety of models and data sources, including global food trade data, processing, and packaging models. Conclusions: A comprehensive approach that takes into account the complexity of the modern global food system is essential to enable better prediction of human exposure to chemicals in food, sound risk assessments, and more focused risk abatement strategies. Citation: Ng CA, von Goetz N. 2017. The global food system as a transport pathway for hazardous chemicals: the missing link between emissions and exposure. Environ Health Perspect 125:1–7; http://dx.doi.org/10.1289/EHP168 PMID:27384039
NASA Astrophysics Data System (ADS)
Tonitto, C.; Gurwick, N. P.
2012-12-01
Policy initiatives to reduce greenhouse gas emissions (GHG) have promoted the development of agricultural management protocols to increase SOC storage and reduce GHG emissions. We review approaches for quantifying N2O flux from agricultural landscapes. We summarize the temporal and spatial extent of observations across representative soil classes, climate zones, cropping systems, and management scenarios. We review applications of simulation and empirical modeling approaches and compare validation outcomes across modeling tools. Subsequently, we review current model application in agricultural management protocols. In particular, we compare approaches adapted for compliance with the California Global Warming Solutions Act, the Alberta Climate Change and Emissions Management Act, and by the American Carbon Registry. In the absence of regional data to drive model development, policies that require GHG quantification often use simple empirical models based on highly aggregated data of N2O flux as a function of applied N - Tier 1 models according to IPCC categorization. As participants in development of protocols that could be used in carbon offset markets, we observed that stakeholders outside of the biogeochemistry community favored outcomes from simulation modeling (Tier 3) rather than empirical modeling (Tier 2). In contrast, scientific advisors were more accepting of outcomes based on statistical approaches that rely on local observations, and their views sometimes swayed policy practitioners over the course of policy development. Both Tier 2 and Tier 3 approaches have been implemented in current policy development, and it is important that the strengths and limitations of both approaches, in the face of available data, be well-understood by those drafting and adopting policies and protocols. The reliability of all models is contingent on sufficient observations for model development and validation. Simulation models applied without site-calibration generally result in poor validation results, and this point particularly needs to be emphasized during policy development. For cases where sufficient calibration data are available, simulation models have demonstrated the ability to capture seasonal patterns of N2O flux. The reliability of statistical models likewise depends on data availability. Because soil moisture is a significant driver of N2O flux, the best outcomes occur when empirical models are applied to systems with relevant soil classification and climate. The structure of current carbon offset protocols is not well-aligned with a budgetary approach to GHG accounting. Current protocols credit field-scale reduction in N2O flux as a result of reduced fertilizer use. Protocols do not award farmers credit for reductions in CO2 emissions resulting from reduced production of synthetic N fertilizer. To achieve the greatest GHG emission reductions through reduced synthetic N production and reduced landscape N saturation requires a re-envisioning of the agricultural landscape to include cropping systems with legume and manure N sources. The current focus on on-farm GHG sources focuses credits on simple reductions of N applied in conventional systems rather than on developing cropping systems which promote higher recycling and retention of N.
NASA Astrophysics Data System (ADS)
Bouet, Christel; Cautenet, Guy; Marticorena, Béatrice; Bergametti, Gilles; Minvielle, Fanny; Schmechtig, Catherine; Laurent, Benoit
2010-05-01
Atmospheric aerosols are known to play an important role in the Earth's climate system. However, the quantification of aerosol radiative impact on the Earth's radiative budget is very complex because of the high variability in space and time of aerosol mass and particle number concentrations, and optical properties as well. In many regions, like in desert regions, dust is the largest contribution to aerosol optical thickness [Tegen et al., 1997]. Consequently, it appears fundamental to well represent mineral dust emissions to reduce uncertainties concerning aerosol radiative impact on the Earth's radiative budget. Recently, several studies (e.g. Prospero et al. [2002]) underlined that the Bodélé depression, in northern Chad, is probably the most important source of mineral dust in the world. However many models fail in simulating these large dust emissions. Indeed, dust emission is a threshold phenomenon mainly driven by the intensity of surface wind velocity. Realistic estimates of dust emissions then rely on the quality and accuracy of the surface wind fields. Koren and Kaufman [2004] showed that the reanalysis data (NCEP), which can be used as input data in numerical models, underestimates surface wind velocity in the Bodélé Depression by up to 50%. Such an uncertainty on surface wind velocity cannot allow an accurate simulation of the dust emission. In mesoscale meteorological models, global reanalysis datasets are used to initialize and laterally nudge the models that compute meteorological parameters (like wind velocity) with a finer spatial and temporal resolutions. The question arises concerning the precision of the wind speeds calculated by these models. Using the Regional Atmospheric Modeling System (RAMS, Cotton et al. [2003]) coupled online with the dust production model developed by Marticorena and Bergametti [1995] and recently improved by Laurent et al. [2008] for Africa, the influence of the horizontal resolution of the mesoscale meteorological model on the simulation of dust emission in the Bodélé Depression is investigated. A one year simulation is run in order to test the capability of the model to represent the pronounced seasonal cycle of dust emission in this region. Routine measurements from meteorological stations as well as satellite imagery are used to evaluate the accuracy of the simulations.
NASA Astrophysics Data System (ADS)
Ogle, S. M.; DelGrosso, S.; Parton, W. J.
2017-12-01
Soil nitrous oxide emissions from agricultural management are a key source of greenhouse gas emissions in many countries due to the widespread use of nitrogen fertilizers, manure amendments from livestock production, planting legumes and other practices that affect N dynamics in soils. In the United States, soil nitrous oxide emissions have ranged from 250 to 280 Tg CO2 equivalent from 1990 to 2015, with uncertainties around 20-30 percent. A Tier 3 method has been used to estimate the emissions with the DayCent ecosystem model. While the Tier 3 approach is considerably more accurate than IPCC Tier 1 methods, there is still the possibility of biases in emission estimates if there are processes and drivers that are not represented in the modeling framework. Furthermore, a key principle of IPCC guidance is that inventory compilers estimate emissions as accurately as possible. Freeze-thaw cycles and associated hot moments of nitrous oxide emissions are one of key drivers influencing emissions in colder climates, such as the cold temperate climates of the upper Midwest and New England regions of the United States. Freeze-thaw activity interacts with management practices that are increasing N availability in the plant-soil system, leading to greater nitrous oxide emissions during transition periods from winter to spring. Given the importance of this driver, the DayCent model has been revised to incorproate freeze-thaw cycles, and the results suggests that including this driver can significantly modify the emissions estimates in cold temperate climate regions. Consequently, future methodological development to improve estimation of nitrous oxide emissions from soils would benefit from incorporating freeze-thaw cycles into the modeling framework for national territories with a cold climate.
NASA Astrophysics Data System (ADS)
Sarofim, M. C.
2007-12-01
Emissions of greenhouses gases and conventional pollutants are closely linked through shared generation processes and thus policies directed toward long-lived greenhouse gases affect emissions of conventional pollutants and, similarly, policies directed toward conventional pollutants affect emissions of greenhouse gases. Some conventional pollutants such as aerosols also have direct radiative effects. NOx and VOCs are ozone precursors, another substance with both radiative and health impacts, and these ozone precursors also interact with the chemistry of the hydroxyl radical which is the major methane sink. Realistic scenarios of future emissions and concentrations must therefore account for both air pollution and greenhouse gas policies and how they interact economically as well as atmospherically, including the regional pattern of emissions and regulation. We have modified a 16 region computable general equilibrium economic model (the MIT Emissions Prediction and Policy Analysis model) by including elasticities of substitution for ozone precursors and aerosols in order to examine these interactions between climate policy and air pollution policy on a global scale. Urban emissions are distributed based on population density, and aged using a reduced form urban model before release into an atmospheric chemistry/climate model (the earth systems component of the MIT Integrated Global Systems Model). This integrated approach enables examination of the direct impacts of air pollution on climate, the ancillary and complementary interactions between air pollution and climate policies, and the impact of different population distribution algorithms or urban emission aging schemes on global scale properties. This modeling exercise shows that while ozone levels are reduced due to NOx and VOC reductions, these reductions lead to an increase in methane concentrations that eliminates the temperature effects of the ozone reductions. However, black carbon reductions do have significant direct effects on global mean temperatures, as do ancillary reductions of greenhouse gases due to the pollution constraints imposed in the economic model. Finally, we show that the economic benefits of coordinating air pollution and climate policies rather than separate implementation are on the order of 20% of the total policy cost.
Land cover maps, BVOC emissions, and SOA burden in a global aerosol-climate model
NASA Astrophysics Data System (ADS)
Stanelle, Tanja; Henrot, Alexandra; Bey, Isaelle
2015-04-01
It has been reported that different land cover representations influence the emission of biogenic volatile organic compounds (BVOC) (e.g. Guenther et al., 2006). But the land cover forcing used in model simulations is quite uncertain (e.g. Jung et al., 2006). As a consequence the simulated emission of BVOCs depends on the applied land cover map. To test the sensitivity of global and regional estimates of BVOC emissions on the applied land cover map we applied 3 different land cover maps into our global aerosol-climate model ECHAM6-HAM2.2. We found a high sensitivity for tropical regions. BVOCs are a very prominent precursor for the production of Secondary Organic Aerosols (SOA). Therefore the sensitivity of BVOC emissions on land cover maps impacts the SOA burden in the atmosphere. With our model system we are able to quantify that impact. References: Guenther et al. (2006), Estimates of global terrestrial isoprene emissions using MEGAN, Atmos. Chem. Phys., 6, 3181-3210, doi:10.5194/acp-6-3181-2006. Jung et al. (2006), Exploiting synergies of global land cover products for carbon cycle modeling, Rem. Sens. Environm., 101, 534-553, doi:10.1016/j.rse.2006.01.020.
Impacts of Residential Biofuel Emissions on Air Quality and Climate
NASA Astrophysics Data System (ADS)
Huang, Y.; Unger, N.; Harper, K.; Storelvmo, T.
2016-12-01
The residential biofuel sector is defined as fuelwood, agricultural residues and dung used for household cooking and heating. Aerosol emissions from this human activity play an important role affecting local, regional and global air quality, climate and public health. However, there are only few studies available that evaluate the net impacts and large uncertainties persist. Here we use the Community Atmosphere Model version 5.3 (CAM v5.3) within the Community Earth System Model version 1.2.2, to quantify the impacts of cook-stove biofuel emissions on air quality and climate. The model incorporates a novel advanced treatment of black carbon (BC) effects on mixed-phase/ice clouds. We update the global anthropogenic emission inventory in CAM v5.3 to a state-of-the-art emission inventory from the Greenhouse Gas-Air Pollution Interactions and Synergies integrated assessment model. Global in-situ and aircraft campaign observations for BC and organic carbon are used to evaluate and validate the model performance. Sensitivity simulations are employed to assess the impacts of residential biofuel emissions on regional and global direct and indirect radiative forcings in the contemporary world. We focus the analyses on several key regions including India, China and Sub-Saharan Africa.
Sensitivity analyses of factors influencing CMAQ performance for fine particulate nitrate.
Shimadera, Hikari; Hayami, Hiroshi; Chatani, Satoru; Morino, Yu; Mori, Yasuaki; Morikawa, Tazuko; Yamaji, Kazuyo; Ohara, Toshimasa
2014-04-01
Improvement of air quality models is required so that they can be utilized to design effective control strategies for fine particulate matter (PM2.5). The Community Multiscale Air Quality modeling system was applied to the Greater Tokyo Area of Japan in winter 2010 and summer 2011. The model results were compared with observed concentrations of PM2.5 sulfate (SO4(2-)), nitrate (NO3(-)) and ammonium, and gaseous nitric acid (HNO3) and ammonia (NH3). The model approximately reproduced PM2.5 SO4(2-) concentration, but clearly overestimated PM2.5 NO3(-) concentration, which was attributed to overestimation of production of ammonium nitrate (NH4NO3). This study conducted sensitivity analyses of factors associated with the model performance for PM2.5 NO3(-) concentration, including temperature and relative humidity, emission of nitrogen oxides, seasonal variation of NH3 emission, HNO3 and NH3 dry deposition velocities, and heterogeneous reaction probability of dinitrogen pentoxide. Change in NH3 emission directly affected NH3 concentration, and substantially affected NH4NO3 concentration. Higher dry deposition velocities of HNO3 and NH3 led to substantial reductions of concentrations of the gaseous species and NH4NO3. Because uncertainties in NH3 emission and dry deposition processes are probably large, these processes may be key factors for improvement of the model performance for PM2.5 NO3(-). The Community Multiscale Air Quality modeling system clearly overestimated the concentration of fine particulate nitrate in the Greater Tokyo Area of Japan, which was attributed to overestimation of production of ammonium nitrate. Sensitivity analyses were conducted for factors associated with the model performance for nitrate. Ammonia emission and dry deposition of nitric acid and ammonia may be key factors for improvement of the model performance.
NASA Astrophysics Data System (ADS)
Almatroushi, H. R.; Lootah, F. H.; Deighan, J.; Fillingim, M. O.; Jain, S.; Bougher, S. W.; England, S.; Schneider, N. M.
2017-12-01
This research focuses on developing empirical and theoretical models for OI 135.6 nm and CO 4PG band system FUV dayglow emissions in the Martian thermosphere as predicted to be seen from the Emirates Mars Ultraviolet Spectrometer (EMUS), one of the three scientific instruments aboard the Emirates Mars Mission (EMM) to be launched in 2020. These models will aid in simulating accurate disk radiances which will be utilized as an input to an EMUS instrument simulator. The developed zonally averaged empirical models are based on FUV data from the IUVS instrument onboard the MAVEN mission, while the theoretical models are based on a basic Chapman profile. The models calculate the brightness (B) of those emissions taking into consideration observation geometry parameters such as emission angle (EA), solar zenith angle (SZA) and planet distance from the sun (Ds). Specifically, the empirical models takes a general form of Bn=A*cos(SZA)n/cos(EA)m , where Bn is the normalized brightness value of an emission feature, and A, n, and m are positive constant values. The model form shows that the brightness has a positive correlation with EA and a negative correlation with SZA. A comparison of both models are explained in this research while examining full Mars and half Mars disk images generated using geometry code specially developed for the EMUS instrument. Sensitivity analyses have also been conducted for the theoretical modeling to observe the contributions of electron impact on atomic oxygen and CO2 to the brightness of OI 135.6nm, in addition to the effect of electron temperature on the CO2± dissociative recombination contribution to the CO 4PG band system.
2015-01-01
A traditional traffic signal control system is established based on vehicular delay, queue length, saturation and other indicators. However, due to the increasing severity of urban environmental pollution issues and the development of a resource-saving and environmentally friendly social philosophy, the development of low-carbon and energy-efficient urban transport is required. This paper first defines vehicular trajectories and the calculation of vehicular emissions based on VSP. Next, a regression analysis method is used to quantify the relationship between vehicular emissions and delay, and a traffic signal control model is established to reduce emissions and delay using the enumeration method combined with saturation constraints. Finally, one typical intersection of Changchun is selected to verify the model proposed in this paper; its performance efficiency is also compared using simulations in VISSIM. The results of this study show that the proposed model can significantly reduce vehicle delay and traffic emissions simultaneously. PMID:26720095
Lin, Ciyun; Gong, Bowen; Qu, Xin
2015-01-01
A traditional traffic signal control system is established based on vehicular delay, queue length, saturation and other indicators. However, due to the increasing severity of urban environmental pollution issues and the development of a resource-saving and environmentally friendly social philosophy, the development of low-carbon and energy-efficient urban transport is required. This paper first defines vehicular trajectories and the calculation of vehicular emissions based on VSP. Next, a regression analysis method is used to quantify the relationship between vehicular emissions and delay, and a traffic signal control model is established to reduce emissions and delay using the enumeration method combined with saturation constraints. Finally, one typical intersection of Changchun is selected to verify the model proposed in this paper; its performance efficiency is also compared using simulations in VISSIM. The results of this study show that the proposed model can significantly reduce vehicle delay and traffic emissions simultaneously.
Impacts of Canadian and global black carbon shipping emissions on Arctic climate
NASA Astrophysics Data System (ADS)
Shrestha, R.; von Salzen, K.
2017-12-01
Shipping activities have increased across the Arctic and are projected to continue to increase in the future. In this study we compare the climate impacts of Canadian and global shipping black carbon (BC) emissions on the Arctic using the Canadian Center for Climate Modelling and Analysis Earth System Model (CanESM4.1). The model simulations are performed with and without shipping emissions at T63 (128 x 64) spectral resolution. Results indicate that shipping activities enhance BC concentrations across the area close to the shipping emissions, which causes increased absorption of solar radiation (direct effect). An impact of shipping on temperatures is simulated across the entire Arctic, with maximum warming in fall and winter seasons. Although global mean temperature changes are very similar between the two simulations, increase in Canadian BC shipping emissions cause warmer Arctic land surface temperature in summer due to the direct radiative effects of aerosol.
NASA Astrophysics Data System (ADS)
Malanushenko, A. V.
2015-12-01
We present a systemic exploration of the properties of coronal heating, by forward-modeling the emission of the ensemble of 1D quasi-steady loops. This approximations were used in many theoretical models of the coronal heating. The latter is described in many such models in the form of power laws, relating heat flux through the photosphere or volumetric heating to the strength of the magnetic field and length of a given field line. We perform a large search in the parameter space of these power laws, amongst other variables, and compare the resulting emission of the active region to that observed by AIA. We use a recently developed magnetic field model which uses shapes of coronal loops to guide the magnetic model; the result closely resembles observed structures by design. We take advantage of this, by comparing, in individual sub-regions of the active region, the emission of the active region and its synthetic model. This study allows us to rule out many theoretical models and formulate predictions for the heating models to come.
NASA Astrophysics Data System (ADS)
Kim, E.; Kim, S.; Kim, H. C.; Kim, B. U.; Cho, J. H.; Woo, J. H.
2017-12-01
In this study, we investigated the contributions of major emission source categories located upwind of South Korea to Particulate Matter (PM) in South Korea. In general, air quality in South Korea is affected by anthropogenic air pollutants emitted from foreign countries including China. Some studies reported that foreign emissions contributed 50 % of annual surface PM total mass concentrations in the Seoul Metropolitan Area, South Korea in 2014. Previous studies examined PM contributions of foreign emissions from all sectors considering meteorological variations. However, little studies conducted to assess contributions of specific foreign source categories. Therefore, we attempted to estimate sectoral contributions of foreign emissions from China to South Korea PM using our air quality forecasting system. We used Model Inter-Comparison Study in Asia 2010 for foreign emissions and Clean Air Policy Support System 2010 emission inventories for domestic emissions. To quantify contributions of major emission sectors to South Korea PM, we applied the Community Multi-scale Air Quality system with brute force method by perturbing emissions from industrial, residential, fossil-fuel power plants, transportation, and agriculture sectors in China. We noted that industrial sector was pre-dominant over the region except during cold season for primary PMs when residential emissions drastically increase due to heating demand. This study will benefit ensemble air quality forecasting and refined control strategy design by providing quantitative assessment on seasonal contributions of foreign emissions from major source categories.
NASA Astrophysics Data System (ADS)
Lamb, B. K.; Gonzalez Abraham, R.; Avise, J. C.; Chung, S. H.; Salathe, E. P.; Zhang, Y.; Guenther, A. B.; Wiedinmyer, C.; Duhl, T.; Streets, D. G.
2013-05-01
Global change will clearly have a significant impact on the environment. Among the concerns for future air quality in North America, intercontinental transport of pollution has become increasingly important. In this study, we examined the effect of projected changes in Asian emissions and emissions from lightning and wildfires to produce ozone background concentrations within Mexico and the continental US. This provides a basis for developing an understanding of North American background levels and how they may change in the future. Meteorological fields were downscaled from the results of the ECHAM5 global climate model using the Weather Research Forecast (WRF) model. Two nested domains were employed, one covering most of the Northern Hemisphere from eastern Asia to North America using 220 km grid cells (semi-hemispheric domain) and one covering the continental US and northern Mexico using 36 km grid cells. Meteorological results from WRF were used to drive the MEGAN biogenic emissions model, the SMOKE emissions processing tool, and the CMAQ chemical transport model to predict ozone concentrations for current (1995-2004) and future (2045-2054) summertime conditions. The MEGAN model was used to calculate biogenic emissions for all simulations. For the semi-hemispheric domain, year 2000 global emissions of gases (ozone precursors) from anthropogenic (outside of North America), natural, and biomass burning sources from the POET and EDGAR emission inventories were used. The global tabulation for black and organic carbon (BC and OC respectively) was obtained from Bond et al. (2004) For the future decade, the current emissions were projected to the year 2050 following the Intergovernmental Panel for Climate Change (IPCC) A1B emission scenario. Anthropogenic emissions from the US, Canada, and Mexico were omitted so that only global background concentrations, and local biogenic, wildfire, and lightning emissions were treated. In this paper, we focus on background ozone levels in Mexico due to changes in future climate, local biogenic emissions and global emissions.
NASA Astrophysics Data System (ADS)
Shonkwiler, K. B.; Ham, J. M.; Nash, C.
2014-12-01
Accurately quantifying emissions of ammonia (NH3) from confined animal feeding operations (CAFOs) is vital not only to the livestock industry, but essential to understanding nitrogen cycling along the Front Range of Colorado, USA, where intensive agriculture, urban sprawl, and pristine ecosystems (e.g., Rocky Mtn Nat'l Park) lie within 100-km of each other. Most observation-based techniques for estimating NH3 emissions can be expensive and highly technical. Many methods rely on concentration observations on location, which implicitly depends on weather conditions. A system for sampling NH3 using on-site weather data was developed to allow remote measurement of NH3 in a simple, cost-effective way. These systems use passive diffusive cartridges (Radiello, Sigma-Aldrich) that provide time-averaged concentrations representative of a typical two-week deployment. Cartridge exposure is robotically managed so they are only visible when winds are 1.4 m/s or greater from the direction of the CAFO. These concentration data can be coupled with stability parameters (measured on-site) in a simple inverse model to estimate emissions (FIDES, UMR Environnement et Grandes Cultures). Few studies have directly compared emissions estimates of NH3 using concentration data obtained from multiple measurement systems at different temporal and spatial scales. Therefore, in the summer and autumn of 2014, several conditional sampler systems were deployed at a 25,000-head cattle feedlot concomitant with an open-path infrared laser (GasFinder2, Boreal Laser Inc.) and a Cavity Ring Down Spectrometer (CRDS) (G1103, Picarro Inc.) which each measured instantaneous NH3 concentrations. This study will test the sampler technology by first comparing concentration data from the three different methods. In livestock research, it is common to estimate NH3 emissions by using such instantaneous data in a backward Lagrangian stochastic (bLs) model (WindTrax, Thunder Beach Sci.) Considering this, NH3 fluxes from the inverse model (FIDES) using all three datasets will be compared to emissions from the bLS model (WindTrax) using only high speed data (laser; CRDS). Results may lend further validity to the conditional sampler approach for more easily and accurately monitoring NH3 fluxes from CAFOs and other strong areal sources.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ehleringer, James; Randerson, James; Lai, Chun-Ta
The objective of the proposed research was to collect data and develop models to improve our understanding of the role of drought and fire impacts on the terrestrial carbon cycle in the western US, including impacts associated with urban systems as they impacted regional carbon cycles. Using data we collected and a synthesis of other measurements, we developed new ways (a) to evaluate the representation of drought stress and fire emissions in the Community Land Model, (b) to model net ecosystem exchange combining ground level atmospheric observations with boundary layer theory, (c) to model upstream impacts of fire and fossilmore » fuel emissions on atmospheric carbon dioxide observations, and (d) to model carbon dioxide observations within urban systems and at the urban-wildland interfaces of forest ecosystems.« less
NASA Astrophysics Data System (ADS)
Wang, Yilong; Broquet, Grégoire; Ciais, Philippe; Chevallier, Frédéric; Vogel, Felix; Wu, Lin; Yin, Yi; Wang, Rong; Tao, Shu
2018-03-01
Combining measurements of atmospheric CO2 and its radiocarbon (14CO2) fraction and transport modeling in atmospheric inversions offers a way to derive improved estimates of CO2 emitted from fossil fuel (FFCO2). In this study, we solve for the monthly FFCO2 emission budgets at regional scale (i.e., the size of a medium-sized country in Europe) and investigate the performance of different observation networks and sampling strategies across Europe. The inversion system is built on the LMDZv4 global transport model at 3.75° × 2.5° resolution. We conduct Observing System Simulation Experiments (OSSEs) and use two types of diagnostics to assess the potential of the observation and inverse modeling frameworks. The first one relies on the theoretical computation of the uncertainty in the estimate of emissions from the inversion, known as posterior uncertainty
, and on the uncertainty reduction compared to the uncertainty in the inventories of these emissions, which are used as a prior knowledge by the inversion (called prior uncertainty
). The second one is based on comparisons of prior and posterior estimates of the emission to synthetic true
emissions when these true emissions are used beforehand to generate the synthetic fossil fuel CO2 mixing ratio measurements that are assimilated in the inversion. With 17 stations currently measuring 14CO2 across Europe using 2-week integrated sampling, the uncertainty reduction for monthly FFCO2 emissions in a country where the network is rather dense like Germany, is larger than 30 %. With the 43 14CO2 measurement stations planned in Europe, the uncertainty reduction for monthly FFCO2 emissions is increased for the UK, France, Italy, eastern Europe and the Balkans, depending on the configuration of prior uncertainty. Further increasing the number of stations or the sampling frequency improves the uncertainty reduction (up to 40 to 70 %) in high emitting regions, but the performance of the inversion remains limited over low-emitting regions, even assuming a dense observation network covering the whole of Europe. This study also shows that both the theoretical uncertainty reduction (and resulting posterior uncertainty) from the inversion and the posterior estimate of emissions itself, for a given prior and true
estimate of the emissions, are highly sensitive to the choice between two configurations of the prior uncertainty derived from the general estimate by inventory compilers or computations on existing inventories. In particular, when the configuration of the prior uncertainty statistics in the inversion system does not match the difference between these prior and true estimates, the posterior estimate of emissions deviates significantly from the truth. This highlights the difficulty of filtering the targeted signal in the model-data misfit for this specific inversion framework, the need to strongly rely on the prior uncertainty characterization for this and, consequently, the need for improved estimates of the uncertainties in current emission inventories for real applications with actual data. We apply the posterior uncertainty in annual emissions to the problem of detecting a trend of FFCO2, showing that increasing the monitoring period (e.g., more than 20 years) is more efficient than reducing uncertainty in annual emissions by adding stations. The coarse spatial resolution of the atmospheric transport model used in this OSSE (typical of models used for global inversions of natural CO2 fluxes) leads to large representation errors (related to the inability of the transport model to capture the spatial variability of the actual fluxes and mixing ratios at subgrid scales), which is a key limitation of our OSSE setup to improve the accuracy of the monitoring of FFCO2 emissions in European regions. Using a high-resolution transport model should improve the potential to retrieve FFCO2 emissions, and this needs to be investigated.
A dynamic evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.1 was conducted to evaluate the model's ability to predict changes in ozone levels between 2002 and 2005, a time period characterized by emission reductions associated with the EPA's N...
USDA-ARS?s Scientific Manuscript database
Emissions of ammonia (NH3) and nitrous oxide (N2O) vary among animal facilities due to differences in housing structure and associated manure management. Bedded pack barns are structures with a roof and sidewalls resulting in a lower air velocity and evaporation potential inside the structure. But s...
Mechanisms of nitrous oxide (N2 O) formation and reduction in denitrifying biofilms.
Sabba, Fabrizio; Picioreanu, Cristian; Nerenberg, Robert
2017-12-01
Nitrous oxide (N 2 O) is a potent greenhouse gas that can be formed in wastewater treatment processes by ammonium oxidizing and denitrifying microorganisms. While N 2 O emissions from suspended growth systems have been extensively studied, and some recent studies have addressed emissions from nitrifying biofilms, much less is known about N 2 O emissions from denitrifying biofilm processes. This research used modeling to evaluate the mechanisms of N 2 O formation and reduction in denitrifying biofilms. The kinetic model included formation and consumption of key denitrification species, including nitrate (NO3-), nitrite (NO2-), nitric oxide (NO), and N 2 O. The model showed that, in presence of excess of electron donor, denitrifying biofilms have two distinct layers of activity: an outer layer where there is net production of N 2 O and an inner layer where there is net consumption. The presence of oxygen (O 2 ) had an important effect on N 2 O emission from suspended growth systems, but a smaller effect on biofilm systems. The effects of NO3- and O 2 differed significantly based on the biofilm thickness. Overall, the effects of biofilm thickness and bulk substrate concentrations on N 2 O emissions are complex and not always intuitive. A key mechanism for denitrifying biofilms is the diffusion of N 2 O and other intermediates from one zone of the biofilm to another. This leads to zones of N 2 O formation or consumption transformations that would not exist in suspended growth systems. © 2017 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Liora, Natalia; Poupkou, Anastasia; Markakis, Konstantinos; Giannaros, Theodoros; Karagiannidis, Athanasios; Melas, Dimitrios
2013-04-01
The aim of this study is the estimation of the future emissions in the area of the large urban center of Thessaloniki (Greece) with emphasis on the emissions originated from the maritime sector within the port area of the city which are presented in detail. In addition, the contribution of the future anthropogenic emissions to atmospheric pollution levels in Thessaloniki focusing on PM levels is studied. A 2km spatial resolution anthropogenic gaseous and particulate matter emission inventory has been compiled for the port city of Thessaloniki for the year 2010 with the anthropogenic emission model MOSESS, developed by Laboratory of Atmospheric Physics of the Aristotle University of Thessaloniki. MOSESS was used for the estimation of emissions from several emission sources (road transport, central heating, industries, maritime sector etc) while the natural emission model NEMO was implemented for the calculation of dust, sea salt and biogenic emissions. Maritime emissions originated from the various processes inside the area of the port (harbor operations such as stockpiles, loading/unloading operations, machineries etc) as well as from the maritime transport sector including passenger ships, cargo shipping, inland waterways vessels (e.g. pleasure crafts) and fish catching ships. Ship emissions were estimated for the three operation modes; cruising, maneuvering and hotelling. For the calculation of maritime emissions, the activity data used were provided by local and national authorities (e.g.Thessaloniki Port Authority S.A.). Pollutant anthropogenic emissions were projected to the year 2020. The emissions from all the anthropogenic sources except for the maritime sector were projected using factors provided by the GAINS model. Future emissions from the maritime activities were estimated on the basis of the future activity data provided by the Port Authority and of the legislation for shipping in the future. Future maritime emissions are determined by the vessels traffic changes as foreseen for the year 2020 by the Port Authority Investment Plan and by the reduction of the sulfur content in fuels used by ships in cruising mode to 0.5% m/m according to a revision of the MARPOL Annex VI. Based on the above, an approximately 60% increase in the future maritime sector PM10 emissions is expected due to the high increase of the traffic of vessels. The impact of future emissions on the air quality of Thessaloniki is examined with the use of the modelling system WRF-CAMx applied with 2km spatial resolution over the study area. Simulations of the modelling system are performed for a summertime (July 2011) and a wintertime (15 November to 15 December 2011) period accounting for present time (scenario A) and future time (scenario B) pollutant emissions. The differences in pollutant levels (mainly PM) between the scenarios examined are presented and discussed.
Hogrefe, Christian; Isukapalli, Sastry S.; Tang, Xiaogang; Georgopoulos, Panos G.; He, Shan; Zalewsky, Eric E.; Hao, Winston; Ku, Jia-Yeong; Key, Tonalee; Sistla, Gopal
2011-01-01
The role of emissions of volatile organic compounds and nitric oxide from biogenic sources is becoming increasingly important in regulatory air quality modeling as levels of anthropogenic emissions continue to decrease and stricter health-based air quality standards are being adopted. However, considerable uncertainties still exist in the current estimation methodologies for biogenic emissions. The impact of these uncertainties on ozone and fine particulate matter (PM2.5) levels for the eastern United States was studied, focusing on biogenic emissions estimates from two commonly used biogenic emission models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emissions Inventory System (BEIS). Photochemical grid modeling simulations were performed for two scenarios: one reflecting present day conditions and the other reflecting a hypothetical future year with reductions in emissions of anthropogenic oxides of nitrogen (NOx). For ozone, the use of MEGAN emissions resulted in a higher ozone response to hypothetical anthropogenic NOx emission reductions compared with BEIS. Applying the current U.S. Environmental Protection Agency guidance on regulatory air quality modeling in conjunction with typical maximum ozone concentrations, the differences in estimated future year ozone design values (DVF) stemming from differences in biogenic emissions estimates were on the order of 4 parts per billion (ppb), corresponding to approximately 5% of the daily maximum 8-hr ozone National Ambient Air Quality Standard (NAAQS) of 75 ppb. For PM2.5, the differences were 0.1–0.25 μg/m3 in the summer total organic mass component of DVFs, corresponding to approximately 1–2% of the value of the annual PM2.5 NAAQS of 15 μg/m3. Spatial variations in the ozone and PM2.5 differences also reveal that the impacts of different biogenic emission estimates on ozone and PM2.5 levels are dependent on ambient levels of anthropogenic emissions. PMID:21305893
NASA Astrophysics Data System (ADS)
Escriva-Bou, A.; Lund, J. R.; Pulido-Velazquez, M.; Medellin-Azuara, J.
2015-12-01
Most individual processes relating water and energy interdependence have been assessed in many different ways over the last decade. It is time to step up and include the results of these studies in management by proportionating a tool for integrating these processes in decision-making to effectively understand the tradeoffs between water and energy from management options and scenarios. A simple but powerful decision support system (DSS) for water management is described that includes water-related energy use and GHG emissions not solely from the water operations, but also from final water end uses, including demands from cities, agriculture, environment and the energy sector. Because one of the main drivers of energy use and GHG emissions is water pumping from aquifers, the DSS combines a surface water management model with a simple groundwater model, accounting for their interrelationships. The model also explicitly includes economic data to optimize water use across sectors during shortages and calculate return flows from different uses. Capabilities of the DSS are demonstrated on a case study over California's intertied water system. Results show that urban end uses account for most GHG emissions of the entire water cycle, but large water conveyance produces significant peaks over the summer season. Also the development of more efficient water application on the agricultural sector has increased the total energy consumption and the net water use in the basins.
NASA Astrophysics Data System (ADS)
Kogure, K.
2013-12-01
Human activities in river basin affect river water quality as water discharges into river with pollutant after we use it. By detecting pollutants source, pathway, and influential factor of human activities, it will be possible to consider proper river basin management. In this study, material flow analysis was done first and then nutrient emission modeling by MONERIS was conducted. So as to clarify land use contribution and climate condition, comparison of Japanese and European river basin area has been made. The model MONERIS (MOdelling Nutrient Emissions in RIver Systems; Behrendt et al., 2000) was applied to estimate the nutrient emissions in the Danube river basin by point sources and various diffuse pathways. Work for the Mur River Basin in Austria was already carried out by the Institute of Water Quality, Resources and Waste Management at the Vienna University of Technology. This study treats data collection, modelling for the Tone River in Japan, and comparative analysis for these two river basins. The estimation of the nutrient emissions was carried out for 11 different sub catchment areas covering the Tone River Basin for the time period 2000 to 2006. TN emissions into the Tone river basin were 51 kt/y. 67% was via ground water and dominant for all sub catchments. Urban area was also important emission pathway. Human effect is observed in urban structure and agricultural activity. Water supply and sewer system make urban water cycle with pipeline structure. Excess evapotranspiration in arable land is also influential in water cycle. As share of arable land is 37% and there provides agricultural products, it is thought that N emission from agricultural activity is main pollution source. Assumption case of 10% N surplus was simulated and the result was 99% identical to the actual. Even though N surplus reduction does not show drastic impact on N emission, it is of importance to reduce excess of fertilization and to encourage effective agricultural activity. Population rate of waste water treatment is 67 % in the total catchment area. Assumption case of 100% WWT was simulated and the result suggests that connection to public sewer system with WWTP is effective potential measure. TN emission in the Tone is higher than it in the Mur. Emission per capita is almost same level for both basin areas. Though the personal pollution stresses same as European basin area, the basin has huge population and activities to support their daily life. Agricultural activity and urban structure have great impacts on N emission and on the river water quality. Possible remedy for river pollution is construction of sewer system with waste water treatment. Agricultural activity is potential betterment factor. Comparison of Mur, Tone and assumption cases
Dynamic evaluation of CMAQ part I: Separating the effects of ...
A dynamic evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.1 was conducted to evaluate the model's ability to predict changes in ozone levels between 2002 and 2005, a time period characterized by emission reductions associated with the EPA's Nitrogen Oxides State Implementation Plan as well as significant reductions in mobile source emissions. Model results for the summers of 2002 and 2005 were compared to simulations from a previous version of CMAQ to assess the impact of model updates on predicted pollutant response. Changes to the model treatment of emissions, meteorology and chemistry had substantial impacts on the simulated ozone concentrations. While the median bias for high summertime ozone decreased in both years compared to previous simulations, the observed decrease in ozone from 2002 to 2005 in the eastern US continued to be underestimated by the model. Additional “cross” simulations were used to decompose the model predicted change in ozone into the change due to emissions, the change due to meteorology and any remaining change not explained individually by these two components. The decomposition showed that the emission controls led to a decrease in modeled high summertime ozone close to twice as large as the decrease attributable to changes in meteorology alone. Quantifying the impact of retrospective emission controls by removing the impacts of meteorology during the control period can be a valuable approac
Cai, Hao; Wang, Michael Q
2014-10-21
The climate impact assessment of vehicle/fuel systems may be incomplete without considering short-lived climate forcers of black carbon (BC) and primary organic carbon (POC). We quantified life-cycle BC and POC emissions of a large variety of vehicle/fuel systems with an expanded Greenhouse gases, Regulated Emissions, and Energy use in Transportation model developed at Argonne National Laboratory. Life-cycle BC and POC emissions have small impacts on life-cycle greenhouse gas (GHG) emissions of gasoline, diesel, and other fuel vehicles, but would add 34, 16, and 16 g CO2 equivalent (CO2e)/mile, or 125, 56, and 56 g CO2e/mile with the 100 or 20 year Global Warming Potentials of BC and POC emissions, respectively, for vehicles fueled with corn stover-, willow tree-, and Brazilian sugarcane-derived ethanol, mostly due to BC- and POC-intensive biomass-fired boilers in cellulosic and sugarcane ethanol plants for steam and electricity production, biomass open burning in sugarcane fields, and diesel-powered agricultural equipment for biomass feedstock production/harvest. As a result, life-cycle GHG emission reduction potentials of these ethanol types, though still significant, are reduced from those without considering BC and POC emissions. These findings, together with a newly expanded GREET version, help quantify the previously unknown impacts of BC and POC emissions on life-cycle GHG emissions of U.S. vehicle/fuel systems.
Predicting gaseous emissions from small-scale combustion of agricultural biomass fuels.
Fournel, S; Marcos, B; Godbout, S; Heitz, M
2015-03-01
A prediction model of gaseous emissions (CO, CO2, NOx, SO2 and HCl) from small-scale combustion of agricultural biomass fuels was developed in order to rapidly assess their potential to be burned in accordance to current environmental threshold values. The model was established based on calculation of thermodynamic equilibrium of reactive multicomponent systems using Gibbs free energy minimization. Since this method has been widely used to estimate the composition of the syngas from wood gasification, the model was first validated by comparing its prediction results with those of similar models from the literature. The model was then used to evaluate the main gas emissions from the combustion of four dedicated energy crops (short-rotation willow, reed canary grass, switchgrass and miscanthus) previously burned in a 29-kW boiler. The prediction values revealed good agreement with the experimental results. The model was particularly effective in estimating the influence of harvest season on SO2 emissions. Copyright © 2014 Elsevier Ltd. All rights reserved.
Chen, Li; Han, Ting-Ting; Li, Tao; Ji, Ya-Qin; Bai, Zhi-Peng; Wang, Bin
2012-07-01
Due to the lack of a prediction model for current wind erosion in China and the slow development for such models, this study aims to predict the wind erosion of soil and the dust emission and develop a prediction model for wind erosion in Tianjin by investigating the structure, parameter systems and the relationships among the parameter systems of the prediction models for wind erosion in typical areas, using the U.S. wind erosion prediction system (WEPS) as reference. Based on the remote sensing technique and the test data, a parameter system was established for the prediction model of wind erosion and dust emission, and a model was developed that was suitable for the prediction of wind erosion and dust emission in Tianjin. Tianjin was divided into 11 080 blocks with a resolution of 1 x 1 km2, among which 7 778 dust emitting blocks were selected. The parameters of the blocks were localized, including longitude, latitude, elevation and direction, etc.. The database files of blocks were localized, including wind file, climate file, soil file and management file. The weps. run file was edited. Based on Microsoft Visualstudio 2008, secondary development was done using C + + language, and the dust fluxes of 7 778 blocks were estimated, including creep and saltation fluxes, suspension fluxes and PM10 fluxes. Based on the parameters of wind tunnel experiments in Inner Mongolia, the soil measurement data and climate data in suburbs of Tianjin, the wind erosion module, wind erosion fluxes, dust emission release modulus and dust release fluxes were calculated for the four seasons and the whole year in suburbs of Tianjin. In 2009, the total creep and saltation fluxes, suspension fluxes and PM10 fluxes in the suburbs of Tianjin were 2.54 x 10(6) t, 1.25 x 10(7) t and 9.04 x 10(5) t, respectively, among which, the parts pointing to the central district were 5.61 x 10(5) t, 2.89 x 10(6) t and 2.03 x 10(5) t, respectively.
Multi-Year On-Road Emission Factor Trends of Two Heavy-Duty California Fleets
NASA Astrophysics Data System (ADS)
Haugen, M.; Bishop, G.
2017-12-01
New heavy-duty vehicle emission regulations have resulted in the development of advanced exhaust after-treatment systems that specifically target particulate matter (PM) and nitrogen oxides (NOx = NO + NO2). This has resulted in significant decreases in the emissions of these species. The University of Denver has collected three data sets of on-road gaseous (CO, HC, NO and NOx) and PM (particle mass, black carbon and particle number) emission measurements from heavy-duty vehicles (HDVs) in the spring of 2013, 2015 and 2017 at two different locations in California. One site is located at the Port of Los Angeles, CA (1,150 HDVs measured in 2017) and the other site is located at a weigh station in Northern California near Cottonwood, CA (780 HDVs measured in 2017). The On-Road Heavy-Duty Measurement Setup measures individual HDV's fuel specific emissions (DOI: 10.1021/acs.est.6b06172). Vehicles drive under a tent-like structure that encapsulates vehicle exhaust and 15 seconds of data collection is integrated to give fuel specific information. The measurements obtained from these campaigns contain real-world emissions affected by different driving modes, after-treatment systems and location. The Port of Los Angeles contributes a fleet that is fully equipped with diesel particulate filters (DPFs) as a result of the San Pedro Ports Clean Air Action Plan enforced since 2010 that allows only vehicles model year 2007 or newer on the premises. This fleet, although comprised with relatively new HDVs with lower PM emissions, has increased PM emissions as it has aged. Cottonwood's fleet contains vehicles with and without after-treatment systems, a result of a gradual turnover rate, and fleet PM has decreased at a slower rate than at the Port of Los Angeles. The decrease in PM emissions is a result of more HDVs being newer model years as well as older model years being retrofit with DPFs. The complimentary fleets, studied over multiple years, have given the University of Denver an extensive data repository to quantify on-road vehicle emission trends on individual vehicles as well as categories of vehicles. Here, the 2017 campaign results will be discussed and compared to previous campaigns.
Climate Science: How Earth System Models are Reshaping the Science Policy Interface.
NASA Technical Reports Server (NTRS)
Ruane, Alex
2015-01-01
This talk is oriented at a general audience including the largest French utility company, and will describe the basics of climate change before moving into emissions scenarios and agricultural impacts that we can test with our earth system models and impacts models.
NASA Astrophysics Data System (ADS)
Zemenkova, M. Yu; Zemenkov, Yu D.; Shantarin, V. D.
2016-10-01
The paper reviews the development of methodology for calculation of hydrocarbon emissions during seepage and evaporation to monitor the reliability and safety of hydrocarbon storage and transportation. The authors have analyzed existing methods, models and techniques for assessing the amount of evaporated oil. Models used for predicting the material balance of multicomponent two-phase systems have been discussed. The results of modeling the open-air hydrocarbon evaporation from an oil spill are provided and exemplified by an emergency pit. Dependences and systems of differential equations have been obtained to assess parameters of mass transfer from the open surface of a liquid multicomponent mixture.
NASA Astrophysics Data System (ADS)
Millar, Richard J.; Nicholls, Zebedee R.; Friedlingstein, Pierre; Allen, Myles R.
2017-06-01
Projections of the response to anthropogenic emission scenarios, evaluation of some greenhouse gas metrics, and estimates of the social cost of carbon often require a simple model that links emissions of carbon dioxide (CO2) to atmospheric concentrations and global temperature changes. An essential requirement of such a model is to reproduce typical global surface temperature and atmospheric CO2 responses displayed by more complex Earth system models (ESMs) under a range of emission scenarios, as well as an ability to sample the range of ESM response in a transparent, accessible and reproducible form. Here we adapt the simple model of the Intergovernmental Panel on Climate Change 5th Assessment Report (IPCC AR5) to explicitly represent the state dependence of the CO2 airborne fraction. Our adapted model (FAIR) reproduces the range of behaviour shown in full and intermediate complexity ESMs under several idealised carbon pulse and exponential concentration increase experiments. We find that the inclusion of a linear increase in 100-year integrated airborne fraction with cumulative carbon uptake and global temperature change substantially improves the representation of the response of the climate system to CO2 on a range of timescales and under a range of experimental designs.
EMISSIONS PROCESSING FOR THE ETA/ CMAQ AIR QUALITY FORECAST SYSTEM
NOAA and EPA have created an Air Quality Forecast (AQF) system. This AQF system links an adaptation of the EPA's Community Multiscale Air Quality Model with the 12 kilometer ETA model running operationally at NOAA's National Center for Environmental Predication (NCEP). One of the...
Application for certification, 1988 model year light-duty vehicles - Volkswagen, Audi
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles, or heavy-duty engines submits to EPA an application for certification. In the application, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems, and exhaust and evaporative emission-control systems. Information is also provided on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements to be followed during testing. Section 16 of the application containsmore » the results of emission testing, a statement of compliance to the regulations, production engine parameters, and a Summary Sheet Input Form on which issuance of a Certificate of Conformity is based.« less
Application for certification, 1986 model year light-duty vehicles - Volkswagen/Audi
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles, or heavy-duty engines submits to EPA an application for certification. In the application, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems and exhaust and evaporative emission control systems. It also provides information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements to be followed during testing. Section 16 of the applicationmore » contains the results of emission testing, a statement of compliance to the regulations, production engine parameters, and a Summary Sheet Input Form on which issuance of a Certificate of Conformity is based.« less
Application for certification, 1993 model-year light-duty trucks - Grumman Olson
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1992-01-01
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles, or heavy-duty engines submits to EPA an application for certification. The report deals with light-duty trucks from Grumman Olson Company. In the application, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems and exhaust and evaporative emission control systems. It also provides information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirementsmore » to be followed during testing. Section 16 of the application contains the results of emission testing, a statement of compliance to the regulations, production engine parameters, and a Summary Sheet Input Form on which issuance of a Certificate of Conformity is based.« less
Application for certification, 1992 model-year light-duty vehicles - Grumman Olson
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1991-01-01
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles, or heavy-duty engines submits to EPA an application for certification. In the application, the manufacturer gives a detailed technical description of the vehicles or engines that he intends to market during the upcoming model year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems and exhaust and evaporative emission control systems. It also provides information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements to be followed during testing. Section 16 of themore » application contains the results of emission testing, a statement of compliance to the regulations, production engine parameters, and a Summary Sheet Input Form on which issuance of a Certificate of Conformity is based.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles, or heavy-duty engines submits to EPA an application for certification. In the application, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems and exhaust and evaporative emission control systems. It also provides information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements to be followed during testing. Section 16 of the applicationmore » contains the results of emission testing, a statement of compliance to the regulations, production engine parameters, and a Summary Sheet Input Form on which issuance of a Certificate of Conformity is based.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
Every year, each manufacturer of passenger cars, light-duty trucks, motorcycles, or heavy-duty engines submits to EPA an application for certification. In the application, the manufacturer gives a detailed technical description of the vehicles or engines he intends to market during the upcoming model year. These engineering data include explanations and/or drawings which describe engine/vehicle parameters such as basic engine design, fuel systems, ignition systems and exhaust and evaporative emission control systems. It also provides information on emission test procedures, service accumulation procedures, fuels to be used, and proposed maintenance requirements to be followed during testing. Section 16 of the applicationmore » contains the results of emission testing, a statement of compliance to the regulations, production engine parameters, and a Summary Sheet Input Form on which issuance of a Certificate of Conformity is based.« less
Analysis of the Flicker Level Produced by a Fixed-Speed Wind Turbine
NASA Astrophysics Data System (ADS)
Suppioni, Vinicius; P. Grilo, Ahda
2013-10-01
In this article, the analysis of the flicker emission during continuous operation of a mid-scale fixed-speed wind turbine connected to a distribution system is presented. Flicker emission is investigated based on simulation results, and the dependence of flicker emission on short-circuit capacity, grid impedance angle, mean wind speed, and wind turbulence is analyzed. The simulations were conducted in different programs in order to provide a more realistic wind emulation and detailed model of mechanical and electrical components of the wind turbine. Such aim is accomplished by using FAST (Fatigue, Aerodynamics, Structures, and Turbulence) to simulate the mechanical parts of the wind turbine, Simulink/MatLab to simulate the electrical system, and TurbSim to obtain the wind model. The results show that, even for a small wind generator, the flicker level can limit the wind power capacity installed in a distribution system.
NASA Astrophysics Data System (ADS)
Gourdji, S. M.; Yadav, V.; Karion, A.; Mueller, K. L.; Conley, S.; Ryerson, T.; Nehrkorn, T.; Kort, E. A.
2018-04-01
Urban greenhouse gas (GHG) flux estimation with atmospheric measurements and modeling, i.e. the ‘top-down’ approach, can potentially support GHG emission reduction policies by assessing trends in surface fluxes and detecting anomalies from bottom-up inventories. Aircraft-collected GHG observations also have the potential to help quantify point-source emissions that may not be adequately sampled by fixed surface tower-based atmospheric observing systems. Here, we estimate CH4 emissions from a known point source, the Aliso Canyon natural gas leak in Los Angeles, CA from October 2015–February 2016, using atmospheric inverse models with airborne CH4 observations from twelve flights ≈4 km downwind of the leak and surface sensitivities from a mesoscale atmospheric transport model. This leak event has been well-quantified previously using various methods by the California Air Resources Board, thereby providing high confidence in the mass-balance leak rate estimates of (Conley et al 2016), used here for comparison to inversion results. Inversions with an optimal setup are shown to provide estimates of the leak magnitude, on average, within a third of the mass balance values, with remaining errors in estimated leak rates predominantly explained by modeled wind speed errors of up to 10 m s‑1, quantified by comparing airborne meteorological observations with modeled values along the flight track. An inversion setup using scaled observational wind speed errors in the model-data mismatch covariance matrix is shown to significantly reduce the influence of transport model errors on spatial patterns and estimated leak rates from the inversions. In sum, this study takes advantage of a natural tracer release experiment (i.e. the Aliso Canyon natural gas leak) to identify effective approaches for reducing the influence of transport model error on atmospheric inversions of point-source emissions, while suggesting future potential for integrating surface tower and aircraft atmospheric GHG observations in top-down urban emission monitoring systems.
A study of Tycho's SNR at TeV energies with the HEGRA CT-System
NASA Astrophysics Data System (ADS)
Aharonian, F. A.; Akhperjanian, A. G.; Barrio, J. A.; Bernlöhr, K.; Börst, H.; Bojahr, H.; Bolz, O.; Contreras, J. L.; Cortina, J.; Denninghoff, S.; Fonseca, V.; Gonzalez, J. C.; Götting, N.; Heinzelmann, G.; Hermann, G.; Heusler, A.; Hofmann, W.; Horns, D.; Ibarra, A.; Jung, I.; Kankanyan, R.; Kestel, M.; Kettler, J.; Kohnle, A.; Konopelko, A.; Kornmeyer, H.; Kranich, D.; Krawczynski, H.; Lampeitl, H.; Lorenz, E.; Lucarelli, F.; Magnussen, N.; Mang, O.; Meyer, H.; Mirzoyan, R.; Moralejo, A.; Padilla, L.; Panter, M.; Plaga, R.; Plyasheshnikov, A.; Prahl, J.; Pühlhofer, G.; Rauterberg, G.; Röhring, A.; Rhode, W.; Rowell, G. P.; Sahakian, V.; Samorski, M.; Schilling, M.; Schröder, F.; Stamm, W.; Tluczykont, M.; Völk, H. J.; Wiedner, C.; Wittek, W.
2001-07-01
Tycho's supernova remnant (SNR) was observed during 1997 and 1998 with the HEGRA Čerenkov Telescope System in a search for gamma-ray emission at energies above ~ 1 TeV. An analysis of these data, ~ 65 hours in total, resulted in no evidence for TeV gamma-ray emission. The 3sigma upper limit to the gamma-ray flux (>1 TeV) from Tycho is estimated at 5.78x 10-13 photons cm-2 s-1, or 33 milli-Crab. We interpret our upper limit within the framework of the following scenarios: (1) that the observed hard X-ray tail is due to synchrotron emission. A lower limit on the magnetic field within Tycho may be estimated B>=22 mu G, assuming that the RXTE-detected X-rays were due to synchrotron emission. However, using results from a detailed model of the ASCA emission, a more conservative lower limit B>=6 mu G is derived. (2) The hadronic model of Drury and (3) the more recent time-dependent kinetic theory of Berezhko & Völk. Our upper limit lies within the range of predicted values of both hadronic models, according to uncertainties in physical parameters of Tycho, and shock acceleration details. In the latter case, the model was scaled to suit the parameters of Tycho and re-normalised to account for a simplification of the original model. We find that we cannot rule out Tycho as a potential contributor at an average level to the Galactic cosmic-ray flux.
The combined meteorology and air quality modeling system composed of the Weather Research and Forecast (WRF) model and Community Multiscale Air Quality (CMAQ) model is an important decision support tool that is used in research and regulatory decisions related to emissions, meteo...
The Models-3 Community Multi-scale Air Quality (CMAQ) model, first released by the USEPA in 1999 (Byun and Ching. 1999), continues to be developed and evaluated. The principal components of the CMAQ system include a comprehensive emission processor known as the Sparse Matrix O...
NASA Astrophysics Data System (ADS)
Zhao, Y.; Mao, P.; Zhou, Y.
2017-12-01
Improved emission inventories are crucial for better understanding atmospheric chemistry with air quality simulation at regional or local scales. Using the bottom-up approach, a high-resolution emission inventory was developed for Jiangsu China. Key parameters for over 6000 industrial sources were investigated, compiled and revised at plant level based on various data sources and on-site survey. Totally 56 NMVOCs samples were collected in 9 chemical plants and analyzed with a gas chromatography-mass spectrometry system. Source profiles of stack emissions from synthetic rubber, acetate fiber, polyether, vinyl acetate, and ethylene production, and those of fugitive emissions from ethylene, butanol and octanol, propylene epoxide, polyethylene and glycol production were obtained. Improvement of this provincial inventory was evaluated through comparisons with other inventories at larger spatial scales, using satellite observation and air quality modeling. Three inventories (national, regional, and provincial by this work) were applied in the Models-3/Community Multi-scale Air Quality (CMAQ) system to evaluate the model performances with different emission inputs. The best agreement between available ground observation and simulation was found when the provincial inventory was applied, indicated by the smallest normalized mean bias (NMB) and normalized mean errors (NME) for all the concerned species SO2, NO2, O3 and PM2.5. The result thus implied the advantage of improved emission inventory at local scale for high resolution air quality modeling. Under the unfavorable meteorology in which horizontal and vertical movement of atmosphere was limited, the simulated SO2 concentrations at downtown Nanjing (the capital city of Jiangsu) using the regional or national inventories were much higher than observation, implying overestimated urban emissions when economy or population densities were applied to downscale or allocate the emissions. With more accurate spatial distribution of emissions at city level, the simulated concentrations using the provincial inventory were much closer to observation. For daily 1h-max O3, better performance was found for January, April and October 2012 when the provincial inventory was used, indicating the benefits of improved chemical speciation of VOC emissions.
Whole-system carbon balance for a regional temperate forest in Northern Wisconsin, USA
NASA Astrophysics Data System (ADS)
Peckham, S. D.; Gower, S. T.
2010-12-01
The whole-system (biological + industrial) carbon (C) balance was estimated for the Chequamegon-Nicolet National Forest (CNNF), a temperate forest covering 600,000 ha in Northern Wisconsin, USA. The biological system was modeled using a spatially-explicit version of the ecosystem process model Biome-BGC. The industrial system was modeled using life cycle inventory (LCI) models for wood and paper products. Biome-BGC was used to estimate net primary production, net ecosystem production (NEP), and timber harvest (H) over the entire CNNF. The industrial carbon budget (Ci) was estimated by applying LCI models of CO2 emissions resulting from timber harvest and production of specific wood and paper products in the CNNF region. In 2009, simulated NEP of the CNNF averaged 3.0 tC/ha and H averaged 0.1 tC/ha. Despite model uncertainty, the CNNF region is likely a carbon sink (NEP - Ci > 0), even when CO2 emissions from timber harvest and production of wood and paper products are included in the calculation of the entire forest system C budget.
Impact of freeway weaving segment design on light-duty vehicle exhaust emissions.
Li, Qing; Qiao, Fengxiang; Yu, Lei; Chen, Shuyan; Li, Tiezhu
2018-06-01
In the United States, 26% of greenhouse gas emissions is emitted from the transportation sector; these emisssions meanwhile are accompanied by enormous toxic emissions to humans, such as carbon monoxide (CO), nitrogen oxides (NO x ), and hydrocarbon (HC), approximately 2.5% and 2.44% of a total exhaust emissions for a petrol and a diesel engine, respectively. These exhaust emissions are typically subject to vehicles' intermittent operations, such as hard acceleration and hard braking. In practice, drivers are inclined to operate intermittently while driving through a weaving segment, due to complex vehicle maneuvering for weaving. As a result, the exhaust emissions within a weaving segment ought to vary from those on a basic segment. However, existing emission models usually rely on vehicle operation information, and compute a generalized emission result, regardless of road configuration. This research proposes to explore the impacts of weaving segment configuration on vehicle emissions, identify important predictors for emission estimations, and develop a nonlinear normalized emission factor (NEF) model for weaving segments. An on-board emission test was conducted on 12 subjects on State Highway 288 in Houston, Texas. Vehicles' activity information, road conditions, and real-time exhaust emissions were collected by on-board diagnosis (OBD), a smartphone-based roughness app, and a portable emission measurement system (PEMS), respectively. Five feature selection algorithms were used to identify the important predictors for the response of NEF and the modeling algorithm. The predictive power of four algorithm-based emission models was tested by 10-fold cross-validation. Results showed that emissions are also susceptible to the type and length of a weaving segment. Bagged decision tree algorithm was chosen to develop a 50-grown-tree NEF model, which provided a validation error of 0.0051. The estimated NEFs are highly correlated with the observed NEFs in the training data set as well as in the validation data set, with the R values of 0.91 and 0.90, respectively. Existing emission models usually rely on vehicle operation information to compute a generalized emission result, regardless of road configuration. In practice, while driving through a weaving segment, drivers are inclined to perform erratic maneuvers, such as hard braking and hard acceleration due to the complex weaving maneuver required. As a result, the exhaust emissions within a weaving segment vary from those on a basic segment. This research proposes to involve road configuration, in terms of the type and length of a weaving segment, in constructing an emission nonlinear model, which significantly improves emission estimations at a microscopic level.
Human-model hybrid Korean air quality forecasting system.
Chang, Lim-Seok; Cho, Ara; Park, Hyunju; Nam, Kipyo; Kim, Deokrae; Hong, Ji-Hyoung; Song, Chang-Keun
2016-09-01
The Korean national air quality forecasting system, consisting of the Weather Research and Forecasting, the Sparse Matrix Operator Kernel Emissions, and the Community Modeling and Analysis (CMAQ), commenced from August 31, 2013 with target pollutants of particulate matters (PM) and ozone. Factors contributing to PM forecasting accuracy include CMAQ inputs of meteorological field and emissions, forecasters' capacity, and inherent CMAQ limit. Four numerical experiments were conducted including two global meteorological inputs from the Global Forecast System (GFS) and the Unified Model (UM), two emissions from the Model Intercomparison Study Asia (MICS-Asia) and the Intercontinental Chemical Transport Experiment (INTEX-B) for the Northeast Asia with Clear Air Policy Support System (CAPSS) for South Korea, and data assimilation of the Monitoring Atmospheric Composition and Climate (MACC). Significant PM underpredictions by using both emissions were found for PM mass and major components (sulfate and organic carbon). CMAQ predicts PM2.5 much better than PM10 (NMB of PM2.5: -20~-25%, PM10: -43~-47%). Forecasters' error usually occurred at the next day of high PM event. Once CMAQ fails to predict high PM event the day before, forecasters are likely to dismiss the model predictions on the next day which turns out to be true. The best combination of CMAQ inputs is the set of UM global meteorological field, MICS-Asia and CAPSS 2010 emissions with the NMB of -12.3%, the RMSE of 16.6μ/m(3) and the R(2) of 0.68. By using MACC data as an initial and boundary condition, the performance skill of CMAQ would be improved, especially in the case of undefined coarse emission. A variety of methods such as ensemble and data assimilation are considered to improve further the accuracy of air quality forecasting, especially for high PM events to be comparable to for all cases. The growing utilization of the air quality forecast induced the public strongly to demand that the accuracy of the national forecasting be improved. In this study, we investigated the problems in the current forecasting as well as various alternatives to solve the problems. Such efforts to improve the accuracy of the forecast are expected to contribute to the protection of public health by increasing the availability of the forecast system.
Stackhouse, K R; Rotz, C A; Oltjen, J W; Mitloehner, F M
2012-12-01
Increased animal performance is suggested as one of the most effective mitigation strategies to decrease greenhouse gas (GHG) and ammonia (NH(3)) emissions from livestock production per unit of product produced. Little information exists, however, on the effects of increased animal productivity on the net decrease in emission from beef production systems. A partial life cycle assessment (LCA) was conducted using the Integrated Farm System Model (IFSM) to estimate GHG and NH(3) emissions from representative beef production systems in California that use various management technologies to enhance animal performance. The IFSM is a farm process model that simulates crop growth, feed production, animal performance, and manure production and handling through time to predict the performance, economics, and environmental impacts of production systems. The simulated beef production systems compared were 1) Angus-natural, with no use of growth-enhancing technologies, 2) Angus-implant, with ionophore and growth-promoting implant (e.g., estrogen/trenbolone acetate-based) application, 3) Angus-ß2-adrenergic agonists (BAA; e.g., zilpaterol), with ionophore, growth-promoting implant, and BAA application, 4) Holstein-implant, with growth implant and ionophore application, and 5) Holstein-BAA, with ionophore, growth implant, and BAA use. During the feedlot phase, use of BAA decreased NH(3) emission by 4 to 9 g/kg HCW, resulting in a 7% decrease in NH(3) loss from the full production system. Combined use of ionophore, growth implant, and BAA treatments decreased NH(3) emission from the full production system by 14 g/kg HCW, or 13%. The C footprint of beef was decreased by 2.2 kg carbon dioxide equivalent (CO(2)e)/kg HCW using all the growth-promoting technologies, and the Holstein beef footprint was decreased by 0.5 kg CO(2)e/kg HCW using BAA. Over the full production systems, these decreases were relatively small at 9% and 5% for Angus and Holstein beef, respectively. The growth-promoting technologies we evaluated are a cost-effective way to mitigate GHG and NH(3) emissions, but naturally managed cattle can bring a similar net return to Angus cattle treated with growth-promoting technologies when sold at an 8% greater premium price.
Unintended greenhouse gas consequences of lowering level of service in urban transit systems
NASA Astrophysics Data System (ADS)
Griswold, Julia B.; Cheng, Han; Madanat, Samer; Horvath, Arpad
2014-12-01
Public transit is often touted as a ‘green’ transportation option and a way for users to reduce their environmental footprint by avoiding automobile emissions, but that may not be the case when systems run well below passenger capacity. In previous work, we explored an approach to optimizing the design and operations of transit systems for both costs and emissions, using continuum approximation models and assuming fixed demand. In this letter, we expand upon our previous work to explore how the level of service for users impacts emissions. We incorporate travel time elasticities into the optimization to account for demand shifts from transit to cars, resulting from increases in transit travel time. We find that emissions reductions are moderated, but not eliminated, for relatively inelastic users. We consider two scenarios: the first is where only the agency faces an emissions budget; the second is where the entire city faces an emissions budget. In the latter scenario, the emissions reductions resulting from reductions in transit level of service are mitigated as users switch to automobile.
Application of the Software as a Service Model to the Control of Complex Building Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stadler, Michael; Donadee, Jonathan; Marnay, Chris
2011-03-17
In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building.more » The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analysed.« less
Application of the Software as a Service Model to the Control of Complex Building Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stadler, Michael; Donadee, Jon; Marnay, Chris
2011-03-18
In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building.more » The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analyzed.« less
Specific model for the estimation of methane emission from municipal solid waste landfills in India.
Kumar, Sunil; Nimchuk, Nick; Kumar, Rakesh; Zietsman, Josias; Ramani, Tara; Spiegelman, Clifford; Kenney, Megan
2016-09-01
The landfill gas (LFG) model is a tool for measuring methane (CH4) generation rates and total CH4 emissions from a particular landfill. These models also have various applications including the sizing of the LFG collection system, evaluating the benefits of gas recovery projects, and measuring and controlling gaseous emissions. This research paper describes the development of a landfill model designed specifically for Indian climatic conditions and the landfill's waste characteristics. CH4, carbon dioxide (CO2), oxygen (O2) and temperature were considered as the prime factor for the development of this model. The developed model was validated for three landfill sites in India: Shillong, Kolkata, and Jaipur. The autocorrelation coefficient for the model was 0.915, while the R(2) value was 0.429. Copyright © 2016 Elsevier Ltd. All rights reserved.
Modeling and measurement of microwave emission and backscattering from bare soil surfaces
NASA Technical Reports Server (NTRS)
Saatchi, S.; Wegmuller, U.
1992-01-01
A multifrequency ground-based radiometer-scatterometer system working at frequencies between 3.0 GHz and 11.0 GHz has been used to study the effect of soil moisture and roughness on microwave emission and backscattering. The freezing and thawing effect of the soil surface and the changes of the surface roughness due to rain and erosion are reported. To analyze the combined active and passive data, a scattering model based on physical optics approximation for the low frequency and geometrical optics approximation for high frequency has been developed. The model is used to calculate the bistatic scattering coefficients from the surface. By considering the conservation of energy, the result has been integrated over a hemisphere above the surface to calculate the emissivity. The backscattering and emission model has been coupled with the observed data in order to extract soil moisture and surface roughness.
Research on the energy and ecological efficiency of mechanical equipment remanufacturing systems
NASA Astrophysics Data System (ADS)
Shi, Junli; Cheng, Jinshi; Ma, Qinyi; Wang, Yajun
2017-08-01
According to the characteristics of mechanical equipment remanufacturing system, the dynamic performance of energy consumption and emission is explored, the equipment energy efficiency and emission analysis model is established firstly, and then energy and ecological efficiency analysis method of the remanufacturing system is put forward, at last, the energy and ecological efficiency of WD615.87 automotive diesel engine remanufacturing system as an example is analyzed, the way of energy efficiency improvementnt and environmental friendly mechanism of remanufacturing process is put forward.
Development of WRF-CO2 4DVAR Data Assimilation System
NASA Astrophysics Data System (ADS)
Zheng, T.; French, N. H. F.
2016-12-01
Four dimensional variational (4DVar) assimilation systems have been widely used for CO2 inverse modeling at global scale. At regional scale, however, 4DVar assimilation systems have been lacking. At present, most regional CO2 inverse models use Lagrangian particle backward trajectory tools to compute influence function in an analytical/synthesis framework. To provide a 4DVar based alternative, we developed WRF-CO2 4DVAR based on Weather Research and Forecasting (WRF), its chemistry extension (WRF-Chem), and its data assimilation system (WRFDA/WRFPLUS). Different from WRFDA, WRF-CO2 4DVAR does not optimize meteorology initial condition, instead it solves for the optimized CO2 surface fluxes (sources/sink) constrained by atmospheric CO2 observations. Based on WRFPLUS, we developed tangent linear and adjoint code for CO2 emission, advection, vertical mixing in boundary layer, and convective transport. Furthermore, we implemented an incremental algorithm to solve for optimized CO2 emission scaling factors by iteratively minimizing the cost function in a Bayes framework. The model sensitivity (of atmospheric CO2 with respect to emission scaling factor) calculated by tangent linear and adjoint model agrees well with that calculated by finite difference, indicating the validity of the newly developed code. The effectiveness of WRF-CO2 4DVar for inverse modeling is tested using forward-model generated pseudo-observation data in two experiments: first-guess CO2 fluxes has a 50% overestimation in the first case and 50% underestimation in the second. In both cases, WRF-CO2 4DVar reduces cost function to less than 10-4 of its initial values in less than 20 iterations and successfully recovers the true values of emission scaling factors. We expect future applications of WRF-CO2 4DVar with satellite observations will provide insights for CO2 regional inverse modeling, including the impacts of model transport error in vertical mixing.
Microcomputer pollution model for civilian airports and Air Force bases. Model description
DOE Office of Scientific and Technical Information (OSTI.GOV)
Segal, H.M.; Hamilton, P.L.
1988-08-01
This is one of three reports describing the Emissions and Dispersion Modeling System (EDMS). EDMS is a complex source emissions/dispersion model for use at civilian airports and Air Force bases. It operates in both a refined and a screening mode and is programmed for an IBM-XT (or compatible) computer. This report--MODEL DESCRIPTION--provides the technical description of the model. It first identifies the key design features of both the emissions (EMISSMOD) and dispersion (GIMM) portions of EDMS. It then describes the type of meteorological information the dispersion model can accept and identifies the manner in which it preprocesses National Climatic Centermore » (NCC) data prior to a refined-model run. The report presents the results of running EDMS on a number of different microcomputers and compares EDMS results with those of comparable models. The appendices elaborate on the information noted above and list the source code.« less
Senapati, Nimai; Chabbi, Abad; Giostri, André Faé; Yeluripati, Jagadeesh B; Smith, Pete
2016-12-01
The DailyDayCent biogeochemical model was used to simulate nitrous oxide (N 2 O) emissions from two contrasting agro-ecosystems viz. a mown-grassland and a grain-cropping system in France. Model performance was tested using high frequency measurements over three years; additionally a local sensitivity analysis was performed. Annual N 2 O emissions of 1.97 and 1.24kgNha -1 year -1 were simulated from mown-grassland and grain-cropland, respectively. Measured and simulated water filled pore space (r=0.86, ME=-2.5%) and soil temperature (r=0.96, ME=-0.63°C) at 10cm soil depth matched well in mown-grassland. The model predicted cumulative hay and crop production effectively. The model simulated soil mineral nitrogen (N) concentrations, particularly ammonium (NH 4 + ), reasonably, but the model significantly underestimated soil nitrate (NO 3 - ) concentration under both systems. In general, the model effectively simulated the dynamics and the magnitude of daily N 2 O flux over the whole experimental period in grain-cropland (r=0.16, ME=-0.81gNha -1 day -1 ), with reasonable agreement between measured and modelled N 2 O fluxes for the mown-grassland (r=0.63, ME=-0.65gNha -1 day -1 ). Our results indicate that DailyDayCent has potential for use as a tool for predicting overall N 2 O emissions in the study region. However, in-depth analysis shows some systematic discrepancies between measured and simulated N 2 O fluxes on a daily basis. The current exercise suggests that the DailyDayCent may need improvement, particularly the sub-module responsible for N transformations, for better simulating soil mineral N, especially soil NO 3 - concentration, and N 2 O flux on a daily basis. The sensitivity analysis shows that many factors such as climate change, N-fertilizer use, input uncertainty and parameter value could influence the simulation of N 2 O emissions. Sensitivity estimation also helped to identify critical parameters, which need careful estimation or site-specific calibration for successful modelling of N 2 O emissions in the study region. Copyright © 2016 Elsevier B.V. All rights reserved.
Understanding Emissions in East Asia - The KORUS 2015 Emissions Inventory
NASA Astrophysics Data System (ADS)
Woo, J. H.; Kim, Y.; Park, R.; Choi, Y.; Simpson, I. J.; Emmons, L. K.; Streets, D. G.
2017-12-01
The air quality over Northeast Asia have been deteriorated for decades due to high population and energy use in the region. Despite of more stringent air pollution control policies by the governments, air quality over the region seems not been improved as much - even worse sometimes. The needs of more scientific understanding of inter-relationship among emissions, transport, chemistry over the region are much higher to effectively protect public health and ecosystems. Two aircraft filed campaigns targeting year 2016, MAPS-Seoul and KORUS-AQ, have been organized to study the air quality of over Korea and East Asia relating to chemical evolution, emission inventories, trans-boundary contribution, and satellite application. We developed a new East-Asia emissions inventory, named KORUS2015, based on NIER/KU-CREATE (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment), in support of the filed campaigns. For anthropogenic emissions, it has 54 fuel classes, 201 sub-sectors and 13 pollutants, including CO2, SO2, NOx, CO, NMVOC, NH3, PM10, and PM2.5. Since the KORUS2015 emissions framework was developed using the integrated climate and air quality assessment modeling framework (i.e. GAINS) and is fully connected with the comprehensive emission processing/modeling systems (i.e. SMOKE, KU-EPS, and MEGAN), it can be effectively used to support atmospheric field campaigns for science and policy. During the field campaigns, we are providing modeling emissions inventory to participating air quality models, such as CMAQ, WRF-Chem, CAMx, GEOS-Chem, MOZART, for forecasting and post-analysis modes. Based on initial assessment of those results, we are improving our emissions, such as VOC speciation, biogenic VOCs modeling. From the 2nditeration between emissions and modeling/measurement, further analysis results will be presented at the conference. Acknowledgements : This subject is supported by Korea Ministry of Environment as "Climate Change Correspondence Program." This work was supported under the framework of national strategy project on fine particulate matters by Ministry of Science, ICT and Future Planning.
Temporal Arctic longwave surface emissivity feedbacks in the Community Earth System Model
NASA Astrophysics Data System (ADS)
Kuo, C.; Feldman, D.; Huang, X.; Flanner, M.; Yang, P.; Chen, X.
2017-12-01
We have investigated how the inclusion of realistic and consistent surface emissivity in both land-surface and atmospheric components of the CESM coupled-climate model affects a wide range of climate variables. We did this by replacing the unit emissivity values in RRTMG_LW for water, fine-grained snow, and desert scenes with spectral emissivity values, and by replacing broadband emissivity values in surface components with the Planck-curve weighted counterparts. We find that this harmonized treatment of surface emissivity within CESM can be important for reducing high-latitude temperature biases. We also find that short-term effects of atmospheric dynamics and spectral information need to be considered to understand radiative effects in higher detail, and are possible with radiative kernels computed for every grid and time point for the entire model integration period. We find that conventional climatological feedback calculations indicate that sea-ice emissivity feedback is positive in sign, but that the radiative effects of the difference in emissivity between frozen and unfrozen surfaces exhibit seasonal dependence. Furthermore, this seasonality itself exhibits meridional asymmetry due to differences in sea-ice response to climate forcing between the Arctic and the Antarctic. In the Arctic, this seasonal, temporally higher order analysis exhibits increasing outgoing surface emissivity radiative response in a warming climate. While the sea-ice emissivity feedback and seasonal sea-ice emissivity radiative response amplitudes are a few percent of surface albedo feedbacks, the feedback analysis methods outlined in this work demonstrate that spatially and temporally localized feedback analysis can give insight into the mechanisms at work on those scales which differ in amplitude and sign from conventional climatological analyses. We note that the inclusion of this realistic physics leads to improved agreement between CESM model results and Arctic surface temperatures and sea-ice trends. This reduction of persistent high-latitude model biases suggests that the current unrealistic representation of surface emissivity in model component radiation routines may be an important contributing factor to cold-pole biases.
Emergent dynamics of the climate-economy system in the Anthropocene.
Kellie-Smith, Owen; Cox, Peter M
2011-03-13
Global CO(2) emissions are understood to be the largest contributor to anthropogenic climate change, and have, to date, been highly correlated with economic output. However, there is likely to be a negative feedback between climate change and human wealth: economic growth is typically associated with an increase in CO(2) emissions and global warming, but the resulting climate change may lead to damages that suppress economic growth. This climate-economy feedback is assumed to be weak in standard climate change assessments. When the feedback is incorporated in a transparently simple model it reveals possible emergent behaviour in the coupled climate-economy system. Formulae are derived for the critical rates of growth of global CO(2) emissions that cause damped or long-term boom-bust oscillations in human wealth, thereby preventing a soft landing of the climate-economy system. On the basis of this model, historical rates of economic growth and decarbonization appear to put the climate-economy system in a potentially damaging oscillatory regime.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Scheutz, Charlotte; Pedersen, Rasmus Broe; Petersen, Per Haugsted
Highlights: • An innovative biocover system was constructed on a landfill cell to mitigate the methane emission. • The biocover system had a mitigation efficiently of typically 80%. • The system also worked efficiently at ambient temperatures below freezing. • A whole landfill emission measurement tool was required to document the biocover system efficiency. - Abstract: Methane generated at landfills contributes to global warming and can be mitigated by biocover systems relying on microbial methane oxidation. As part of a closure plan for an old unlined landfill without any gas management measures, an innovative biocover system was established. The systemmore » was designed based on a conceptual model of the gas emission patterns established through an initial baseline study. The study included construction of gas collection trenches along the slopes of the landfill where the majority of the methane emissions occurred. Local compost materials were tested as to their usefulness as bioactive methane oxidizing material and a suitable compost mixture was selected. Whole site methane emission quantifications based on combined tracer release and downwind measurements in combination with several local experimental activities (gas composition within biocover layers, flux chamber based emission measurements and logging of compost temperatures) proved that the biocover system had an average mitigation efficiency of approximately 80%. The study showed that the system also had a high efficiency during winter periods with temperatures below freezing. An economic analysis indicated that the mitigation costs of the biocover system were competitive to other existing greenhouse gas mitigation options.« less
Environmental impact analysis with the airspace concept evaluation system
NASA Technical Reports Server (NTRS)
Augustine, Stephen; Capozzi, Brian; DiFelici, John; Graham, Michael; Thompson, Terry; Miraflor, Raymond M. C.
2005-01-01
The National Aeronautics and Space Administration (NASA) Ames Research Center has developed the Airspace Concept Evaluation System (ACES), which is a fast-time simulation tool for evaluating Air Traffic Management (ATM) systems. This paper describes linking a capability to ACES which can analyze the environmental impact of proposed future ATM systems. This provides the ability to quickly evaluate metrics associated with environmental impacts of aviation for inclusion in multi-dimensional cost-benefit analysis of concepts for evolution of the National Airspace System (NAS) over the next several decades. The methodology used here may be summarized as follows: 1) Standard Federal Aviation Administration (FAA) noise and emissions-inventory models, the Noise Impact Routing System (NIRS) and the Emissions and Dispersion Modeling System (EDMS), respectively, are linked to ACES simulation outputs; 2) appropriate modifications are made to ACES outputs to incorporate all information needed by the environmental models (e.g., specific airframe and engine data); 3) noise and emissions calculations are performed for all traffic and airports in the study area for each of several scenarios, as simulated by ACES; and 4) impacts of future scenarios are compared to the current NAS baseline scenario. This paper also provides the results of initial end-to-end, proof-of-concept runs of the integrated ACES and environmental-modeling capability. These preliminary results demonstrate that if no growth is likely to be impeded by significant environmental impacts that could negatively affect communities throughout the nation.
How much would five trillion tonnes of carbon warm the climate?
NASA Astrophysics Data System (ADS)
Tokarska, Katarzyna Kasia; Gillett, Nathan P.; Weaver, Andrew J.; Arora, Vivek K.
2016-04-01
While estimates of fossil fuel reserves and resources are very uncertain, and the amount which could ultimately be burnt under a business as usual scenario would depend on prevailing economic and technological conditions, an amount of five trillion tonnes of carbon (5 EgC), corresponding to the lower end of the range of estimates of the total fossil fuel resource, is often cited as an estimate of total cumulative emissions in the absence of mitigation actions. The IPCC Fifth Assessment Report indicates that an approximately linear relationship between warming and cumulative carbon emissions holds only up to around 2 EgC emissions. It is typically assumed that at higher cumulative emissions the warming would tend to be less than that predicted by such a linear relationship, with the radiative saturation effect dominating the effects of positive carbon-climate feedbacks at high emissions, as predicted by simple carbon-climate models. We analyze simulations from four state-of-the-art Earth System Models (ESMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and seven Earth System Models of Intermediate Complexity (EMICs), driven by the Representative Concentration Pathway 8.5 Extension scenario (RCP 8.5 Ext), which represents a very high emission scenario of increasing greenhouse gas concentrations in absence of climate mitigation policies. Our results demonstrate that while terrestrial and ocean carbon storage varies between the models, the CO2-induced warming continues to increase approximately linearly with cumulative carbon emissions even for higher levels of cumulative emissions, in all four ESMs. Five of the seven EMICs considered simulate a similarly linear response, while two exhibit less warming at higher cumulative emissions for reasons we discuss. The ESMs simulate global mean warming of 6.6-11.0°C, mean Arctic warming of 15.3-19.7°C, and mean regional precipitation increases and decreases by more than a factor of four, in response to 5EgC, with smaller forcing contributions from other greenhouse gases. These results indicate that the unregulated exploitation of the fossil fuel resource would ultimately result in considerably more profound climate changes than previously suggested.
NASA Astrophysics Data System (ADS)
Rolland, Joran; Achatz, Ulrich
2017-04-01
The differentially heated, rotating annulus configuration has been used for a long time as a model system of the earth troposphere. It can easily reproduce thermal wind and baroclinic waves in the laboratory. It has recently been shown numerically that provided the Rossby number, the rotation rate and the Brunt-Väisälä frequency were well chosen, this configuration also reproduces the spontaneous emission of gravity waves by jet front systems [1]. This offers a very practical configuration in which to study an important process of emission of atmospheric gravity waves. It has also been shown experimentally that this configuration can be modified in order to add the possibility for the emitted wave to reach a strongly stratified region [2]. It thus creates a system containing a model troposphere where gravity waves are spontaneously emitted and can propagate to a model stratosphere. For this matter a stratification was created using a salinity gradient in the experimental apparatus. Through double diffusion, this generates a strongly stratified layer in the middle of the flow (the model stratosphere) and two weakly stratified region in the top and bottom layers (the model troposphere). In this poster, we present simulations of this configuration displaying baroclinic waves in the top and bottom layers. We aim at creating jet front systems strong enough that gravity waves can be spontaneously emitted. This will thus offer the possibility of studying the wave characteristic and mechanisms in emission and propagation in details. References [1] S. Borchert, U. Achatz, M.D. Fruman, Spontaneous Gravity wave emission in the differentially heated annulus, J. Fluid Mech. 758, 287-311 (2014). [2] M. Vincze, I. Borcia, U. Harlander, P. Le Gal, Double-diffusive convection convection and baroclinic instability in a differentially heated and initially stratified rotating system: the barostrat instability, Fluid Dyn. Res. 48, 061414 (2016).
NASA Astrophysics Data System (ADS)
Li, Xuping; Ogden, Joan; Yang, Christopher
2013-11-01
This study models the operation of molten carbonate fuel cell (MCFC) tri-generation systems for “big box” store businesses that combine grocery and retail business, and sometimes gasoline retail. Efficiency accounting methods and parameters for MCFC tri-generation systems have been developed. Interdisciplinary analysis and an engineering/economic model were applied for evaluating the technical, economic, and environmental performance of distributed MCFC tri-generation systems, and for exploring the optimal system design. Model results show that tri-generation is economically competitive with the conventional system, in which the stores purchase grid electricity and NG for heat, and sell gasoline fuel. The results are robust based on sensitivity analysis considering the uncertainty in energy prices and capital cost. Varying system sizes with base case engineering inputs, energy prices, and cost assumptions, it is found that there is a clear tradeoff between the portion of electricity demand covered and the capital cost increase of bigger system size. MCFC Tri-generation technology provides lower emission electricity, heat, and H2 fuel. With NG as feedstock the CO2 emission can be reduced by 10%-43.6%, depending on how the grid electricity is generated. With renewable methane as feedstock CO2 emission can be further reduced to near zero.
NASA Astrophysics Data System (ADS)
Di Giuseppe, Francesca; Rémy, Samuel; Pappenberger, Florian; Wetterhall, Fredrik
2018-04-01
The atmospheric composition analysis and forecast for the European Copernicus Atmosphere Monitoring Services (CAMS) relies on biomass-burning fire emission estimates from the Global Fire Assimilation System (GFAS). The GFAS is a global system and converts fire radiative power (FRP) observations from MODIS satellites into smoke constituents. Missing observations are filled in using persistence, whereby observed FRP values from the previous day are progressed in time until a new observation is recorded. One of the consequences of this assumption is an increase of fire duration, which in turn translates into an increase of emissions estimated from fires compared to what is available from observations. In this study persistence is replaced by modelled predictions using the Canadian Fire Weather Index (FWI), which describes how atmospheric conditions affect the vegetation moisture content and ultimately fire duration. The skill in predicting emissions from biomass burning is improved with the new technique, which indicates that using an FWI-based model to infer emissions from FRP is better than persistence when observations are not available.
Cao, Tanfeng; Russell, Robert L; Durbin, Thomas D; Cocker, David R; Burnette, Andrew; Calavita, Joseph; Maldonado, Hector; Johnson, Kent C
2018-04-13
Hybrid engine technology is a potentially important strategy for reduction of tailpipe greenhouse gas (GHG) emissions and other pollutants that is now being implemented for off-road construction equipment. The goal of this study was to evaluate the emissions and fuel consumption impacts of electric-hybrid excavators using a Portable Emissions Measurement System (PEMS)-based methodology. In this study, three hybrid and four conventional excavators were studied for both real world activity patterns and tailpipe emissions. Activity data was obtained using engine control module (ECM) and global positioning system (GPS) logged data, coupled with interviews, historical records, and video. This activity data was used to develop a test cycle with seven modes representing different types of excavator work. Emissions data were collected over this test cycle using a PEMS. The results indicated the HB215 hybrid excavator provided a significant reduction in tailpipe carbon dioxide (CO 2 ) emissions (from -13 to -26%), but increased diesel particulate matter (PM) (+26 to +27%) when compared to a similar model conventional excavator over the same duty cycle. Copyright © 2018 Elsevier B.V. All rights reserved.
A framework to analyze emissions implications of ...
Future year emissions depend highly on the evolution of the economy, technology and current and future regulatory drivers. A scenario framework was adopted to analyze various technology development pathways and societal change while considering existing regulations and future uncertainty in regulations and evaluate resulting emissions growth patterns. The framework integrates EPA’s energy systems model with an economic Input-Output (I/O) Life Cycle Assessment model. The EPAUS9r MARKAL database is assembled from a set of technologies to represent the U.S. energy system within MARKAL bottom-up technology rich energy modeling framework. The general state of the economy and consequent demands for goods and services from these sectors are taken exogenously in MARKAL. It is important to characterize exogenous inputs about the economy to appropriately represent the industrial sector outlook for each of the scenarios and case studies evaluated. An economic input-output (I/O) model of the US economy is constructed to link up with MARKAL. The I/O model enables user to change input requirements (e.g. energy intensity) for different sectors or the share of consumer income expended on a given good. This gives end-users a mechanism for modeling change in the two dimensions of technological progress and consumer preferences that define the future scenarios. The framework will then be extended to include environmental I/O framework to track life cycle emissions associated
Study of angular momentum variation due to entrance channel effect in heavy ion fusion reactions
NASA Astrophysics Data System (ADS)
Kumar, Ajay
2014-05-01
A systematic investigation of the properties of hot nuclei may be studied by detecting the evaporated particles. These emissions reflect the behavior of the nucleus at various stages of the deexcitation cascade. When the nucleus is formed by the collision of a heavy nucleus with a light particle, the statistical model has done a good job of predicting the distribution of evaporated particles when reasonable choices were made for the level densities and yrast lines. Comparison to more specific measurements could, of course, provide a more severe test of the model and enable one to identify the deviations from the statistical model as the signature of other effects not included in the model. Some papers have claimed that experimental evaporation spectra from heavy-ion fusion reactions at higher excitation energies and angular momenta are no longer consistent with the predictions of the standard statistical model. In order to confirm this prediction we have employed two systems, a mass-symmetric (31P+45Sc) and a mass-asymmetric channel (12C+64Zn), leading to the same compound nucleus 76Kr* at the excitation energy of 75 MeV. Neutron energy spectra of the asymmetric system (12C+64Zn) at different angles are well described by the statistical model predictions using the normal value of the level density parameter a = A/8 MeV-1. However, in the case of the symmetric system (31P+45Sc), the statistical model interpretation of the data requires the change in the value of a = A/10 MeV-1. The delayed evolution of the compound system in case of the symmetric 31P+45Sc system may lead to the formation of a temperature equilibrated dinuclear complex, which may be responsible for the neutron emission at higher temperature, while the protons and alpha particles are evaporated after neutron emission when the system is sufficiently cooled down and the higher g-values do not contribute in the formation of the compound nucleus for the symmetric entrance channel in case of charged particle emission.
The potential of satellite spectro-imagery for monitoring CO2 emissions from large cities
NASA Astrophysics Data System (ADS)
Broquet, Grégoire; Bréon, François-Marie; Renault, Emmanuel; Buchwitz, Michael; Reuter, Maximilian; Bovensmann, Heinrich; Chevallier, Frédéric; Wu, Lin; Ciais, Philippe
2018-02-01
This study assesses the potential of 2 to 10 km resolution imagery of CO2 concentrations retrieved from the shortwave infrared measurements of a space-borne passive spectrometer for monitoring the spatially integrated emissions from the Paris area. Such imagery could be provided by missions similar to CarbonSat, which was studied as a candidate Earth Explorer 8 mission by the European Space Agency (ESA). This assessment is based on observing system simulation experiments (OSSEs) with an atmospheric inversion approach at city scale. The inversion system solves for hourly city CO2 emissions and natural fluxes, or for these fluxes per main anthropogenic sector or ecosystem, during the 6 h before a given satellite overpass. These 6 h correspond to the period during which emissions produce CO2 plumes that can be identified on the image from this overpass. The statistical framework of the inversion accounts for the existence of some prior knowledge with 50 % uncertainty on the hourly or sectorial emissions, and with ˜ 25 % uncertainty on the 6 h mean emissions, from an inventory based on energy use and carbon fuel consumption statistics. The link between the hourly or sectorial emissions and the vertically integrated column of CO2 observed by the satellite is simulated using a coupled flux and atmospheric transport model. This coupled model is built with the information on the spatial and temporal distribution of emissions from the emission inventory produced by the local air-quality agency (Airparif) and a 2 km horizontal resolution atmospheric transport model. Tests are conducted for different realistic simulations of the spatial coverage, resolution, precision and accuracy of the imagery from sun-synchronous polar-orbiting missions, corresponding to the specifications of CarbonSat and Sentinel-5 or extrapolated from these specifications. First, OSSEs are conducted with a rather optimistic configuration in which the inversion system is perfectly informed about the statistics of the limited number of error sources. These OSSEs indicate that the image resolution has to be finer than 4 km to decrease the uncertainty in the 6 h mean emissions by more than 50 %. More complex experiments assess the impact of more realistic error estimates that current inversion methods do not properly account for, in particular, the systematic measurement errors with spatially correlated patterns. These experiments highlight the difficulty to improve current knowledge on CO2 emissions for urban areas like Paris with CO2 observations from satellites, and call for more technological innovations in the remote sensing of vertically integrated columns of CO2 and in the inversion systems that exploit it.
Emission Projections for Long-Haul Freight Trucks and Rail in the United States through 2050.
Liu, Liang; Hwang, Taesung; Lee, Sungwon; Ouyang, Yanfeng; Lee, Bumsoo; Smith, Steven J; Yan, Fang; Daenzer, Kathryn; Bond, Tami C
2015-10-06
This work develops an integrated model approach for estimating emissions from long-haul freight truck and rail transport in the United States between 2010 and 2050. We connect models of macroeconomic activity, freight demand by commodity, transportation networks, and emission technology to represent different pathways of future freight emissions. Emissions of particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), and total hydrocarbon (THC) decrease by 60%-70% from 2010 to 2030, as older vehicles built to less-stringent emission standards retire. Climate policy, in the form of carbon tax that increases apparent fuel prices, causes a shift from truck to rail, resulting in a 30% reduction in fuel consumption and a 10%-28% reduction in pollutant emissions by 2050, if rail capacity is sufficient. Eliminating high-emitting conditions in the truck fleet affects air pollutants by 20% to 65%; although these estimates are highly uncertain, they indicate the importance of durability in vehicle engines and emission control systems. Future infrastructure investment will be required both to meet transport demand and to enable actions that reduce emissions of air and climate pollutants. By driving the integrated model framework with two macroeconomic scenarios, we show that the effect of carbon tax on air pollution is robust regardless of growth levels.
A multi-objective programming model for assessment the GHG emissions in MSW management
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mavrotas, George, E-mail: mavrotas@chemeng.ntua.gr; Skoulaxinou, Sotiria; Gakis, Nikos
2013-09-15
Highlights: • The multi-objective multi-period optimization model. • The solution approach for the generation of the Pareto front with mathematical programming. • The very detailed description of the model (decision variables, parameters, equations). • The use of IPCC 2006 guidelines for landfill emissions (first order decay model) in the mathematical programming formulation. - Abstract: In this study a multi-objective mathematical programming model is developed for taking into account GHG emissions for Municipal Solid Waste (MSW) management. Mathematical programming models are often used for structure, design and operational optimization of various systems (energy, supply chain, processes, etc.). The last twenty yearsmore » they are used all the more often in Municipal Solid Waste (MSW) management in order to provide optimal solutions with the cost objective being the usual driver of the optimization. In our work we consider the GHG emissions as an additional criterion, aiming at a multi-objective approach. The Pareto front (Cost vs. GHG emissions) of the system is generated using an appropriate multi-objective method. This information is essential to the decision maker because he can explore the trade-offs in the Pareto curve and select his most preferred among the Pareto optimal solutions. In the present work a detailed multi-objective, multi-period mathematical programming model is developed in order to describe the waste management problem. Apart from the bi-objective approach, the major innovations of the model are (1) the detailed modeling considering 34 materials and 42 technologies, (2) the detailed calculation of the energy content of the various streams based on the detailed material balances, and (3) the incorporation of the IPCC guidelines for the CH{sub 4} generated in the landfills (first order decay model). The equations of the model are described in full detail. Finally, the whole approach is illustrated with a case study referring to the application of the model in a Greek region.« less
NASA Astrophysics Data System (ADS)
Pereira, Gabriel; Siqueira, Ricardo; Rosário, Nilton E.; Longo, Karla L.; Freitas, Saulo R.; Cardozo, Francielle S.; Kaiser, Johannes W.; Wooster, Martin J.
2016-06-01
Fires associated with land use and land cover changes release large amounts of aerosols and trace gases into the atmosphere. Although several inventories of biomass burning emissions cover Brazil, there are still considerable uncertainties and differences among them. While most fire emission inventories utilize the parameters of burned area, vegetation fuel load, emission factors, and other parameters to estimate the biomass burned and its associated emissions, several more recent inventories apply an alternative method based on fire radiative power (FRP) observations to estimate the amount of biomass burned and the corresponding emissions of trace gases and aerosols. The Brazilian Biomass Burning Emission Model (3BEM) and the Fire Inventory from NCAR (FINN) are examples of the first, while the Brazilian Biomass Burning Emission Model with FRP assimilation (3BEM_FRP) and the Global Fire Assimilation System (GFAS) are examples of the latter. These four biomass burning emission inventories were used during the South American Biomass Burning Analysis (SAMBBA) field campaign. This paper analyzes and inter-compared them, focusing on eight regions in Brazil and the time period of 1 September-31 October 2012. Aerosol optical thickness (AOT550 nm) derived from measurements made by the Moderate Resolution Imaging Spectroradiometer (MODIS) operating on board the Terra and Aqua satellites is also applied to assess the inventories' consistency. The daily area-averaged pyrogenic carbon monoxide (CO) emission estimates exhibit significant linear correlations (r, p > 0.05 level, Student t test) between 3BEM and FINN and between 3BEM_ FRP and GFAS, with values of 0.86 and 0.85, respectively. These results indicate that emission estimates in this region derived via similar methods tend to agree with one other. However, they differ more from the estimates derived via the alternative approach. The evaluation of MODIS AOT550 nm indicates that model simulation driven by 3BEM and FINN typically underestimate the smoke particle loading in the eastern region of Amazon forest, while 3BEM_FRP estimations to the area tend to overestimate fire emissions. The daily regional CO emission fluxes from 3BEM and FINN have linear correlation coefficients of 0.75-0.92, with typically 20-30 % higher emission fluxes in FINN. The daily regional CO emission fluxes from 3BEM_FRP and GFAS show linear correlation coefficients between 0.82 and 0.90, with a particularly strong correlation near the arc of deforestation in the Amazon rainforest. In this region, GFAS has a tendency to present higher CO emissions than 3BEM_FRP, while 3BEM_FRP yields more emissions in the area of soybean expansion east of the Amazon forest. Atmospheric aerosol optical thickness is simulated by using the emission inventories with two operational atmospheric chemistry transport models: the IFS from Monitoring Atmospheric Composition and Climate (MACC) and the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modelling System (CCATT-BRAMS). Evaluation against MODIS observations shows a good representation of the general patterns of the AOT550 nm time series. However, the aerosol emissions from fires with particularly high biomass consumption still lead to an underestimation of the atmospheric aerosol load in both models.
Using the HOMER Model in Air Quality Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
2004-08-01
HOMER, the micropower optimization model created by the National Renewable Energy Laboratory (NREL), helps design and analyze off-grid and grid-connected power systems. One of HOMER's newest features is its enhanced ability to estimate air emissions for different micropower systems.
Rao, Anand B; Rubin, Edward S
2002-10-15
Capture and sequestration of CO2 from fossil fuel power plants is gaining widespread interest as a potential method of controlling greenhouse gas emissions. Performance and cost models of an amine (MEA)-based CO2 absorption system for postcombustion flue gas applications have been developed and integrated with an existing power plant modeling framework that includes multipollutant control technologies for other regulated emissions. The integrated model has been applied to study the feasibility and cost of carbon capture and sequestration at both new and existing coal-burning power plants. The cost of carbon avoidance was shown to depend strongly on assumptions about the reference plant design, details of the CO2 capture system design, interactions with other pollution control systems, and method of CO2 storage. The CO2 avoidance cost for retrofit systems was found to be generally higher than for new plants, mainly because of the higher energy penalty resulting from less efficient heat integration as well as site-specific difficulties typically encountered in retrofit applications. For all cases, a small reduction in CO2 capture cost was afforded by the SO2 emission trading credits generated by amine-based capture systems. Efforts are underway to model a broader suite of carbon capture and sequestration technologies for more comprehensive assessments in the context of multipollutant environmental management.
Errors associated with fitting Gaussian profiles to noisy emission-line spectra
NASA Technical Reports Server (NTRS)
Lenz, Dawn D.; Ayres, Thomas R.
1992-01-01
Landman et al. (1982) developed prescriptions to predict profile fitting errors for Gaussian emission lines perturbed by white noise. We show that their scaling laws can be generalized to more complicated signal-dependent 'noise models' of common astronomical detector systems.
Brown, Kristen E; Hottle, Troy Alan; Bandyopadhyay, Rubenka; Babaee, Samaneh; Dodder, Rebecca Susanne; Kaplan, Pervin Ozge; Lenox, Carol; Loughlin, Dan
2018-06-21
The energy system is the primary source of air pollution. Thus, evolution of the energy system into the future will affect society's ability to maintain air quality. Anticipating this evolution is difficult because of inherent uncertainty in predicting future energy demand, fuel use, and technology adoption. We apply Scenario Planning to address this uncertainty, developing four very different visions of the future. Stakeholder engagement suggested technological progress and social attitudes toward the environment are critical and uncertain factors for determining future emissions. Combining transformative and static assumptions about these factors yields a matrix of four scenarios that encompass a wide range of outcomes. We implement these scenarios in the U.S. EPA MARKAL model. Results suggest that both shifting attitudes and technology transformation may lead to emission reductions relative to present, even without additional policies. Emission caps, such as the Cross State Air Pollution Rule, are most effective at protecting against future emission increases. An important outcome of this work is the scenario implementation approach, which uses technology-specific discount rates to encourage scenario-specific technology and fuel choices. End-use energy demands are modified to approximate societal changes. This implementation allows the model to respond to perturbations in manners consistent with each scenario.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Abdelaziz, Omar; Fricke, Brian A; Vineyard, Edward Allan
Commercial refrigeration systems are known to be prone to high leak rates and to consume large amounts of electricity. As such, direct emissions related to refrigerant leakage and indirect emissions resulting from primary energy consumption contribute greatly to their Life Cycle Climate Performance (LCCP). In this paper, an LCCP design tool is used to evaluate the performance of a typical commercial refrigeration system with alternative refrigerants and minor system modifications to provide lower Global Warming Potential (GWP) refrigerant solutions with improved LCCP compared to baseline systems. The LCCP design tool accounts for system performance, ambient temperature, and system load; systemmore » performance is evaluated using a validated vapor compression system simulation tool while ambient temperature and system load are devised from a widely used building energy modeling tool (EnergyPlus). The LCCP design tool also accounts for the change in hourly electricity emission rate to yield an accurate prediction of indirect emissions. The analysis shows that conventional commercial refrigeration system life cycle emissions are largely due to direct emissions associated with refrigerant leaks and that system efficiency plays a smaller role in the LCCP. However, as a transition occurs to low GWP refrigerants, the indirect emissions become more relevant. Low GWP refrigerants may not be suitable for drop-in replacements in conventional commercial refrigeration systems; however some mixtures may be introduced as transitional drop-in replacements. These transitional refrigerants have a significantly lower GWP than baseline refrigerants and as such, improved LCCP. The paper concludes with a brief discussion on the tradeoffs between refrigerant GWP, efficiency and capacity.« less
Searches for Periodic Neutrino Emission from Binary Systems with 22 and 40 Strings of IceCube
NASA Technical Reports Server (NTRS)
Abassi, R.; Abdou, Y.; Abu-Zayyad, T.; Ackermann, M.; Adams, J.; Aguilar, J. A.; Ahlers, M.; Allen, M. M.; Altmann, D.; Andeen, K.;
2011-01-01
Recent observations of GeV /TeV photon emission from several X-ray binaries have sparked a renewed interest in these objects as galactic particle accelerators. In spite of the available multi-wavelength data, their acceleration mechanisms are not determined, and the nature of the accelerated particles (hadrons or leptons) is unknown. While much evidence favors leptonic emission, it is very likely that a hadronic component is also accelerated in the jets of these binary systems. The observation of neutrino emission would be clear evidence for the presence of a hadronic component in the outflow of these sources. In this paper we look for periodic neutrino emission from binary systems. Such modulation, observed in the photon flux, would be caused by the geometry of these systems. The results of two searches are presented that differ in the treatment of the spectral shape and phase of the emission. The 'generic' search allows parameters to vary freely and best fit values, in a 'model-dependent' search, predictions are used to constrain these parameters. We use the IceCube data taken from May 31, 2007 to April 5, 2008 with its 22-string configuration, and from April 5, 2008 and May 20, 2009 with its 40-string configuration. For the generic search and the 40 string sample, we find that the most significant source in the catalog of 7 binary stars is Cygnus X-3 with a 1.8% probability after trials (2.10" sigma one-sided) of being produced by statistical fluctuations of the background. The model-dependent method tested a range of system geometries - the inclination and the massive star's disk size - for LS I+61 deg 303, no significant excess was found.
Study of Regional Downscaled Climate and Air Quality in the United States
NASA Astrophysics Data System (ADS)
Gao, Y.; Fu, J. S.; Drake, J.; Lamarque, J.; Lam, Y.; Huang, K.
2011-12-01
Due to the increasing anthropogenic greenhouse gas emissions, the global and regional climate patterns have significantly changed. Climate change has exerted strong impact on ecosystem, air quality and human life. The global model Community Earth System Model (CESM v1.0) was used to predict future climate and chemistry under projected emission scenarios. Two new emission scenarios, Representative Community Pathways (RCP) 4.5 and RCP 8.5, were used in this study for climate and chemistry simulations. The projected global mean temperature will increase 1.2 and 1.7 degree Celcius for the RCP 4.5 and RCP 8.5 scenarios in 2050s, respectively. In order to take advantage of local detailed topography, land use data and conduct local climate impact on air quality, we downscaled CESM outputs to 4 km by 4 km Eastern US domain using Weather Research and Forecasting (WRF) Model and Community Multi-scale Air Quality modeling system (CMAQ). The evaluations between regional model outputs and global model outputs, regional model outputs and observational data were conducted to verify the downscaled methodology. Future climate change and air quality impact were also examined on a 4 km by 4 km high resolution scale.
Modeling crop residue burning experiments to evaluate smoke emissions and plume transport.
Zhou, Luxi; Baker, Kirk R; Napelenok, Sergey L; Pouliot, George; Elleman, Robert; O'Neill, Susan M; Urbanski, Shawn P; Wong, David C
2018-06-15
Crop residue burning is a common land management practice that results in emissions of a variety of pollutants with negative health impacts. Modeling systems are used to estimate air quality impacts of crop residue burning to support retrospective regulatory assessments and also for forecasting purposes. Ground and airborne measurements from a recent field experiment in the Pacific Northwest focused on cropland residue burning was used to evaluate model performance in capturing surface and aloft impacts from the burning events. The Community Multiscale Air Quality (CMAQ) model was used to simulate multiple crop residue burns with 2 km grid spacing using field-specific information and also more general assumptions traditionally used to support National Emission Inventory based assessments. Field study specific information, which includes area burned, fuel consumption, and combustion completeness, resulted in increased biomass consumption by 123 tons (60% increase) on average compared to consumption estimated with default methods in the National Emission Inventory (NEI) process. Buoyancy heat flux, a key parameter for model predicted fire plume rise, estimated from fuel loading obtained from field measurements can be 30% to 200% more than when estimated using default field information. The increased buoyancy heat flux resulted in higher plume rise by 30% to 80%. This evaluation indicates that the regulatory air quality modeling system can replicate intensity and transport (horizontal and vertical) features for crop residue burning in this region when region-specific information is used to inform emissions and plume rise calculations. Further, previous vertical emissions allocation treatment of putting all cropland residue burning in the surface layer does not compare well with measured plume structure and these types of burns should be modeled more similarly to prescribed fires such that plume rise is based on an estimate of buoyancy. Copyright © 2018 Elsevier B.V. All rights reserved.
A hybrid model describing ion induced kinetic electron emission
NASA Astrophysics Data System (ADS)
Hanke, S.; Duvenbeck, A.; Heuser, C.; Weidtmann, B.; Wucher, A.
2015-06-01
We present a model to describe the kinetic internal and external electron emission from an ion bombarded metal target. The model is based upon a molecular dynamics treatment of the nuclear degree of freedom, the electronic system is assumed as a quasi-free electron gas characterized by its Fermi energy, electron temperature and a characteristic attenuation length. In a series of previous works we have employed this model, which includes the local kinetic excitation as well as the rapid spread of the generated excitation energy, in order to calculate internal and external electron emission yields within the framework of a Richardson-Dushman-like thermionic emission model. However, this kind of treatment turned out to fail in the realistic prediction of experimentally measured internal electron yields mainly due to the restriction of the treatment of electronic transport to a diffusive manner. Here, we propose a slightly modified approach additionally incorporating the contribution of hot electrons which are generated in the bulk material and undergo ballistic transport towards the emitting interface.
A study of regional-scale aerosol assimilation using a Stretch-NICAM
NASA Astrophysics Data System (ADS)
Misawa, S.; Dai, T.; Schutgens, N.; Nakajima, T.
2013-12-01
Although aerosol is considered to be harmful to human health and it became a social issue, aerosol models and emission inventories include large uncertainties. In recent studies, data assimilation is applied to aerosol simulation to get more accurate aerosol field and emission inventory. Most of these studies, however, are carried out only on global scale, and there are only a few researches about regional scale aerosol assimilation. In this study, we have created and verified an aerosol assimilation system on regional scale, in hopes to reduce an error associated with the aerosol emission inventory. Our aerosol assimilation system has been developed using an atmospheric climate model, NICAM (Non-hydrostaric ICosahedral Atmospheric Model; Satoh et al., 2008) with a stretch grid system and coupled with an aerosol transport model, SPRINTARS (Takemura et al., 2000). Also, this assimilation system is based on local ensemble transform Kalman filter (LETKF). To validate this system, we used a simulated observational data by adding some artificial errors to the surface aerosol fields constructed by Stretch-NICAM-SPRINTARS. We also included a small perturbation in original emission inventory. This assimilation with modified observational data and emission inventory was performed in Kanto-plane region around Tokyo, Japan, and the result indicates the system reducing a relative error of aerosol concentration by 20%. Furthermore, we examined a sensitivity of the aerosol assimilation system by varying the number of total ensemble (5, 10 and 15 ensembles) and local patch (domain) size (radius of 50km, 100km and 200km), both of which are the tuning parameters in LETKF. The result of the assimilation with different ensemble number 5, 10 and 15 shows that the larger the number of ensemble is, the smaller the relative error become. This is consistent with ensemble Kalman filter theory and imply that this assimilation system works properly. Also we found that assimilation system does not work well in a case of 200km radius, while a domain of 50km radius is less efficient than when domain of 100km radius is used.Therefore, we expect that the optimized size lies somewhere between 50km to 200km. We will show a real analysis of real data from suspended particle matter (SPM) network in the Kanto-plane region.
Directional infrared temperature and emissivity of vegetation: Measurements and models
NASA Technical Reports Server (NTRS)
Norman, J. M.; Castello, S.; Balick, L. K.
1994-01-01
Directional thermal radiance from vegetation depends on many factors, including the architecture of the plant canopy, thermal irradiance, emissivity of the foliage and soil, view angle, slope, and the kinetic temperature distribution within the vegetation-soil system. A one dimensional model, which includes the influence of topography, indicates that thermal emissivity of vegetation canopies may remain constant with view angle, or emissivity may increase or decrease as view angle from nadir increases. Typically, variations of emissivity with view angle are less than 0.01. As view angle increases away from nadir, directional infrared canopy temperature usually decreases but may remain nearly constant or even increase. Variations in directional temperature with view angle may be 5C or more. Model predictions of directional emissivity are compared with field measurements in corn canopies and over a bare soil using a method that requires two infrared thermometers, one sensitive to the 8 to 14 micrometer wavelength band and a second to the 14 to 22 micrometer band. After correction for CO2 absorption by the atmosphere, a directional canopy emissivity can be obtained as a function of view angle in the 8 to 14 micrometer band to an accuracy of about 0.005. Modeled and measured canopy emissivities for corn varied slightly with view angle (0.990 at nadir and 0.982 at 75 deg view zenith angle) and did not appear to vary significantly with view angle for the bare soil. Canopy emissivity is generally nearer to unity than leaf emissivity may vary by 0.02 with wavelength even though leaf emissivity. High spectral resolution, canopy thermal emissivity may vary by 0.02 with wavelength even though leaf emissivity may vary by 0.07. The one dimensional model provides reasonably accurate predictions of infrared temperature and can be used to study the dependence of infrared temperature on various plant, soil, and environmental factors.
Direct and Indirect Measurements and Modeling of Methane Emissions in Indianapolis, Indiana.
Lamb, Brian K; Cambaliza, Maria O L; Davis, Kenneth J; Edburg, Steven L; Ferrara, Thomas W; Floerchinger, Cody; Heimburger, Alexie M F; Herndon, Scott; Lauvaux, Thomas; Lavoie, Tegan; Lyon, David R; Miles, Natasha; Prasad, Kuldeep R; Richardson, Scott; Roscioli, Joseph Robert; Salmon, Olivia E; Shepson, Paul B; Stirm, Brian H; Whetstone, James
2016-08-16
This paper describes process-based estimation of CH4 emissions from sources in Indianapolis, IN and compares these with atmospheric inferences of whole city emissions. Emissions from the natural gas distribution system were estimated from measurements at metering and regulating stations and from pipeline leaks. Tracer methods and inverse plume modeling were used to estimate emissions from the major landfill and wastewater treatment plant. These direct source measurements informed the compilation of a methane emission inventory for the city equal to 29 Gg/yr (5% to 95% confidence limits, 15 to 54 Gg/yr). Emission estimates for the whole city based on an aircraft mass balance method and from inverse modeling of CH4 tower observations were 41 ± 12 Gg/yr and 81 ± 11 Gg/yr, respectively. Footprint modeling using 11 days of ethane/methane tower data indicated that landfills, wastewater treatment, wetlands, and other biological sources contribute 48% while natural gas usage and other fossil fuel sources contribute 52% of the city total. With the biogenic CH4 emissions omitted, the top-down estimates are 3.5-6.9 times the nonbiogenic city inventory. Mobile mapping of CH4 concentrations showed low level enhancement of CH4 throughout the city reflecting diffuse natural gas leakage and downstream usage as possible sources for the missing residual in the inventory.
Hendriks, Carlijn; Kuenen, Jeroen; Kranenburg, Richard; Scholz, Yvonne; Schaap, Martijn
2015-03-01
Effective air pollution and short-lived climate forcer mitigation strategies can only be designed when the effect of emission reductions on pollutant concentrations and health and ecosystem impacts are quantified. Within integrated assessment modeling source-receptor relationships (SRRs) based on chemistry transport modeling are used to this end. Currently, these SRRs are made using invariant emission time profiles. The LOTOS-EUROS model equipped with a source attribution module was used to test this assumption for renewable energy scenarios. Renewable energy availability and thereby fossil fuel back up are strongly dependent on meteorological conditions. We have used the spatially and temporally explicit energy model REMix to derive time profiles for backup power generation. These time profiles were used in LOTOS-EUROS to investigate the effect of emission timing on air pollutant concentrations and SRRs. It is found that the effectiveness of emission reduction in the power sector is significantly lower when accounting for the shift in the way emissions are divided over the year and the correlation of emissions with synoptic situations. The source receptor relationships also changed significantly. This effect was found for both primary and secondary pollutants. Our results indicate that emission timing deserves explicit attention when assessing the impacts of system changes on air quality and climate forcing from short lived substances.
Propulsion Investigation for Zero and Near-Zero Emissions Aircraft
NASA Technical Reports Server (NTRS)
Snyder, Christopher A.; Berton, Jeffrey J.; Brown, Gerald v.; Dolce, James L.; Dravid, Marayan V.; Eichenberg, Dennis J.; Freeh, Joshua E.; Gallo, Christopher A.; Jones, Scott M.; Kundu, Krishna P.;
2009-01-01
As world emissions are further scrutinized to identify areas for improvement, aviation s contribution to the problem can no longer be ignored. Previous studies for zero or near-zero emissions aircraft suggest aircraft and propulsion system sizes that would perform propulsion system and subsystems layout and propellant tankage analyses to verify the weight-scaling relationships. These efforts could be used to identify and guide subsequent work on systems and subsystems to achieve viable aircraft system emissions goals. Previous work quickly focused these efforts on propulsion systems for 70- and 100-passenger aircraft. Propulsion systems modeled included hydrogen-fueled gas turbines and fuel cells; some preliminary estimates combined these two systems. Hydrogen gas-turbine engines, with advanced combustor technology, could realize significant reductions in nitrogen emissions. Hydrogen fuel cell propulsion systems were further laid out, and more detailed analysis identified systems needed and weight goals for a viable overall system weight. Results show significant, necessary reductions in overall weight, predominantly on the fuel cell stack, and power management and distribution subsystems to achieve reasonable overall aircraft sizes and weights. Preliminary conceptual analyses for a combination of gas-turbine and fuel cell systems were also performed, and further studies were recommended. Using gas-turbine engines combined with fuel cell systems can reduce the fuel cell propulsion system weight, but at higher fuel usage than using the fuel cell only.
Progress toward an Integrated Global GHG Information System (IG3IS)
NASA Astrophysics Data System (ADS)
DeCola, Philip
2016-04-01
Accurate and precise atmospheric measurements of greenhouse gas (GHG) concentrations have shown the inexorable rise of global GHG concentrations due to human socioeconomic activity. Scientific observations also show a resulting rise in global temperatures and evidence of negative impacts on society. In response to this amassing evidence, nations, states, cities and private enterprises are accelerating efforts to reduce emissions of GHGs, and the UNFCCC process recently forged the Paris Agreement. Emission reduction strategies will vary by nation, region, and economic sector (e.g., INDCs), but regardless of the strategies and mechanisms applied, the ability to implement policies and manage them effectively over time will require consistent, reliable and timely information. A number of studies [e.g., Verifying Greenhouse Gas Emissions: Methods to Support International Climate Agreements (2010); GEO Carbon Strategy (2010); IPCC Task Force on National GHG Inventories: Expert Meeting Report on Uncertainty and Validation of Emission Inventories (2010)] have reported on the state of carbon cycle research, observations and models and the ability of these atmospheric observations and models to independently validate and improve the accuracy of self-reported emission inventories based on fossil fuel usage and land use activities. These studies concluded that by enhancing our in situ and remote-sensing observations and atmospheric data assimilation modeling capabilities, a GHG information system could be achieved in the coming decade to serve the needs of policies and actions to reduce GHG emissions. Atmospheric measurements and models are already being used to provide emissions information on a global and continental scale through existing networks, but these efforts currently provide insufficient information at the human-dimensions where nations, states, cities, and private enterprises can take valuable, and additional action that can reduce emissions for a specific GHG from a specific human activity. Based upon the recent advances in GHG observation technologies, new data-mining tools for acquiring socioeconomic activity data, and enhancements to the computational models used to merge this data, WMO and its partners are developing a plan for an Integrated Global GHG Information System (IG3IS) able to evaluate the efficacy of policy, reduce emission inventory uncertainty, and inform additional mitigation actions. The presentation will cover the principles and objectives of IG3IS, as well as progress toward answering the questions: What research capabilities are ready and able to deliver useful information for whom? What decisions will be informed? What valuable and additional outcomes will result?
Observation of the black widow B1957+20 millisecond pulsar binary system with the MAGIC telescopes
NASA Astrophysics Data System (ADS)
Ahnen, M. L.; Ansoldi, S.; Antonelli, L. A.; Arcaro, C.; Babić, A.; Banerjee, B.; Bangale, P.; Barres de Almeida, U.; Barrio, J. A.; Becerra González, J.; Bednarek, W.; Bernardini, E.; Berti, A.; Biasuzzi, B.; Biland, A.; Blanch, O.; Bonnefoy, S.; Bonnoli, G.; Borracci, F.; Bretz, T.; Carosi, R.; Carosi, A.; Chatterjee, A.; Colin, P.; Colombo, E.; Contreras, J. L.; Cortina, J.; Covino, S.; Cumani, P.; da Vela, P.; Dazzi, F.; de Angelis, A.; de Lotto, B.; De Oña Wilhelmi, E.; Di Pierro, F.; Doert, M.; Domínguez, A.; Dominis Prester, D.; Dorner, D.; Doro, M.; Einecke, S.; Eisenacher Glawion, D.; Elsaesser, D.; Engelkemeier, M.; Fallah Ramazani, V.; Fernández-Barral, A.; Fidalgo, D.; Fonseca, M. V.; Font, L.; Fruck, C.; Galindo, D.; García López, R. J.; Garczarczyk, M.; Gaug, M.; Giammaria, P.; Godinović, N.; Gora, D.; Gozzini, S. R.; Griffiths, S.; Guberman, D.; Hadasch, D.; Hahn, A.; Hassan, T.; Hayashida, M.; Herrera, J.; Hose, J.; Hrupec, D.; Hughes, G.; Ishio, K.; Konno, Y.; Kubo, H.; Kushida, J.; Kuveždić, D.; Lelas, D.; Lindfors, E.; Lombardi, S.; Longo, F.; López, M.; Majumdar, P.; Makariev, M.; Maneva, G.; Manganaro, M.; Mannheim, K.; Maraschi, L.; Mariotti, M.; Martínez, M.; Mazin, D.; Menzel, U.; Mirzoyan, R.; Moralejo, A.; Moreno, V.; Moretti, E.; Neustroev, V.; Niedzwiecki, A.; Nievas Rosillo, M.; Nilsson, K.; Nishijima, K.; Noda, K.; Nogués, L.; Paiano, S.; Palacio, J.; Paneque, D.; Paoletti, R.; Paredes, J. M.; Paredes-Fortuny, X.; Pedaletti, G.; Peresano, M.; Perri, L.; Persic, M.; Poutanen, J.; Prada Moroni, P. G.; Prandini, E.; Puljak, I.; Garcia, J. R.; Reichardt, I.; Rhode, W.; Ribó, M.; Rico, J.; Saito, T.; Satalecka, K.; Schroeder, S.; Schweizer, T.; Sillanpää, A.; Sitarek, J.; Šnidarić, I.; Sobczynska, D.; Stamerra, A.; Strzys, M.; Surić, T.; Takalo, L.; Tavecchio, F.; Temnikov, P.; Terzić, T.; Tescaro, D.; Teshima, M.; Torres, D. F.; Torres-Albà, N.; Treves, A.; Vanzo, G.; Vazquez Acosta, M.; Vovk, I.; Ward, J. E.; Will, M.; Wu, M. H.; Zarić, D.; MAGIC Collaboration; Cognard, I.; Guillemot, L.
2017-10-01
B1957+20 is a millisecond pulsar located in a black-widow-type compact binary system with a low-mass stellar companion. The interaction of the pulsar wind with the companion star wind and/or the interstellar plasma is expected to create plausible conditions for acceleration of electrons to TeV energies and subsequent production of very high-energy γ-rays in the inverse Compton process. We performed extensive observations with the Major Atmospheric Gamma Imaging Cherenkov Telescopes (MAGIC) telescopes of B1957+20. We interpret results in the framework of a few different models, namely emission from the vicinity of the millisecond pulsar, the interaction of the pulsar and stellar companion wind region or bow shock nebula. No significant steady very high-energy γ-ray emission was found. We derived a 95 per cent confidence level upper limit of 3.0 × 10-12 cm-2 s-1 on the average γ-ray emission from the binary system above 200 GeV. The upper limits obtained with the MAGIC constrain, for the first time, different models of the high-energy emission in B1957+20. In particular, in the inner mixed wind nebula model with mono-energetic injection of electrons, the acceleration efficiency of electrons is constrained to be below ˜2-10 per cent of the pulsar spin-down power. For the pulsar emission, the obtained upper limits for each emission peak are well above the exponential cut-off fits to the Fermi-LAT data, extrapolated to energies above 50 GeV. The MAGIC upper limits can rule out a simple power-law tail extension through the sub-TeV energy range for the main peak seen at radio frequencies.
CO2 acclimation impacts leaf isoprene emissions: evidence from past to future CO2 levels
NASA Astrophysics Data System (ADS)
de Boer, Hugo; van der Laan, Annick; Dekker, Stefan; Holzinger, Rupert
2017-04-01
Isoprene is emitted by many plant species as a side-product of photosynthesis. Once in the atmosphere, isoprene exhibits climate forcing through various feedback mechanisms. In order to quantify the climate feedbacks of biogenic isoprene emission it is crucial to establish how isoprene emissions are effected by plant acclimation to rising atmospheric CO2 levels. A promising development for modelling CO2-induced changes in isoprene emissions is the Leaf-Energetic-Status model (referred to as LES-model hereafter, see Harrison et al., 2013 and Morfopoulos et al., 2014). This model simulates isoprene emissions based on the hypothesis that isoprene biosynthesis depends on the imbalance between the photosynthetic electron supply of reducing power and the electron demands of carbon fixation. The energetic imbalance is critically related to the photosynthetic electron transport capacity (Jmax) and the maximum carboxylation capacity of Rubisco (Vcmax). Here we compare predictions of the LES-model with observed isoprene emission responses of Quercus robur (pedunculate oak) specimen that acclimated to CO2 growth conditions representative of the last glacial, the present and the end of this century (200, 400 and 800 ppm, respectively) for two growing seasons. These plants were grown in walk-in growth chambers with tight control of light, temperature, humidity and CO2 concentrations. Photosynthetic biochemical parameters Vcmax and Jmax were determined with a Licor LI-6400XT photosynthesis system. The relationship between photosynthesis and isoprene emissions was measured by coupling the photosynthesis system with a Proton-Transfer Reaction Time-of-Flight Mass Spectrometer. Our empirical results support the LES-model and show that the fractional allocation of carbon to isoprene biosynthesis is reduced in response to both short-term and long-term CO2 increases. In the short term, an increase in CO2 stimulates photosynthesis through an increase in the leaf interior CO2 concentration and marginally decreases isoprene production owing to an increase in the electron demand for carbon fixation. In the long-term, acclimation to rising CO2 growth conditions leads to down regulation of both Jmax and Vcmax, which modulates the stimulating effect of rising CO2 on photosynthesis. This CO2 effect is most pronounced between sub-ambient to present CO2. Our results highlight that the LES-model provides a suitable theoretical framework to model changes in leaf isoprene emissions related to biochemical acclimation to rising CO2. References Harrison, S. P. et al: Volatile isoprenoid emissions from plastid to planet, New Phytol., 197(1), 49-57, 2013. Morfopoulos, C. et al: A model of plant isoprene emission based on available reducing power captures responses to atmospheric CO2, New Phytol., 203(1), 125-139, 2014.
A modeling comparison of deep greenhouse gas emissions reduction scenarios by 2030 in California
Yeh, Sonia; Yang, Christopher; Gibbs, Michael; ...
2016-10-21
California aims to reduce greenhouse gas (GHG) emissions to 40% below 1990 levels by 2030. We compare six energy models that have played various roles in informing the state policymakers in setting climate policy goals and targets. These models adopt a range of modeling structures, including stock-turnover back-casting models, a least-cost optimization model, macroeconomic/macro-econometric models, and an electricity dispatch model. Results from these models provide useful insights in terms of the transformations in the energy system required, including efficiency improvements in cars, trucks, and buildings, electrification of end-uses, low- or zero-carbon electricity and fuels, aggressive adoptions of zero-emission vehicles (ZEVs),more » demand reduction, and large reductions of non-energy GHG emissions. Some of these studies also suggest that the direct economic costs can be fairly modest or even generate net savings, while the indirect macroeconomic benefits are large, as shifts in employment and capital investments could have higher economic returns than conventional energy expenditures. These models, however, often assume perfect markets, perfect competition, and zero transaction costs. They also do not provide specific policy guidance on how these transformative changes can be achieved. Greater emphasis on modeling uncertainty, consumer behaviors, heterogeneity of impacts, and spatial modeling would further enhance policymakers' ability to design more effective and targeted policies. Here, this paper presents an example of how policymakers, energy system modelers and stakeholders interact and work together to develop and evaluate long-term state climate policy targets. Lastly, even though this paper focuses on California, the process of dialogue and interactions, modeling results, and lessons learned can be generally adopted across different regions and scales.« less
Odour and ammonia emissions from intensive poultry units in Ireland.
Hayes, E T; Curran, T P; Dodd, V A
2006-05-01
Odour and ammonia emissions were measured from three broiler, two layer and two turkey houses in Ireland. The broiler units gave a large range of odour and ammonia emission rates depending on the age of the birds and the season. A considerable variation between the odour and ammonia emission rates was evident for the two layer units which may have been due to the different manure handling systems utilised in the houses. There was relatively little difference in the odour and ammonia emissions from the two turkey houses. As a precautionary principle, odour emission rates utilised in atmospheric dispersion models should use the maximum values for broilers and turkeys (1.22 and 10.5 ou(E) s(-1) bird(-1) respectively) and the mean value for the layers depending on the manure handling system used (0.47 or 1.35 ou(E) s(-1) bird(-1)).
Campbell, Patrick; Zhang, Yang; Yan, Fang; Lu, Zifeng; Streets, David
2018-07-01
Emissions from the transportation sector are rapidly changing worldwide; however, the interplay of such emission changes in the face of climate change are not as well understood. This two-part study examines the impact of projected emissions from the U.S. transportation sector (Part I) on ambient air quality in the face of climate change (Part II). In Part I of this study, we describe the methodology and results of a novel Technology Driver Model (see graphical abstract) that includes 1) transportation emission projections (including on-road vehicles, non-road engines, aircraft, rail, and ship) derived from a dynamic technology model that accounts for various technology and policy options under an IPCC emission scenario, and 2) the configuration/evaluation of a dynamically downscaled Weather Research and Forecasting/Community Multiscale Air Quality modeling system. By 2046-2050, the annual domain-average transportation emissions of carbon monoxide (CO), nitrogen oxides (NO x ), volatile organic compounds (VOCs), ammonia (NH 3 ), and sulfur dioxide (SO 2 ) are projected to decrease over the continental U.S. The decreases in gaseous emissions are mainly due to reduced emissions from on-road vehicles and non-road engines, which exhibit spatial and seasonal variations across the U.S. Although particulate matter (PM) emissions widely decrease, some areas in the U.S. experience relatively large increases due to increases in ship emissions. The on-road vehicle emissions dominate the emission changes for CO, NO x , VOC, and NH 3 , while emissions from both the on-road and non-road modes have strong contributions to PM and SO 2 emission changes. The evaluation of the baseline 2005 WRF simulation indicates that annual biases are close to or within the acceptable criteria for meteorological performance in the literature, and there is an overall good agreement in the 2005 CMAQ simulations of chemical variables against both surface and satellite observations. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Christen, A.; Crawford, B.; Ketler, R.; Lee, J. K.; McKendry, I. G.; Nesic, Z.; Caitlin, S.
2015-12-01
Measurements of long-lived greenhouse gases in the urban atmosphere are potentially useful to constrain and validate urban emission inventories, or space-borne remote-sensing products. We summarize and compare three different approaches, operating at different scales, that directly or indirectly identify, attribute and quantify emissions (and uptake) of carbon dioxide (CO2) in urban environments. All three approaches are illustrated using in-situ measurements in the atmosphere in and over Vancouver, Canada. Mobile sensing may be a promising way to quantify and map CO2 mixing ratios at fine scales across heterogenous and complex urban environments. We developed a system for monitoring CO2 mixing ratios at street level using a network of mobile CO2 sensors deployable on vehicles and bikes. A total of 5 prototype sensors were built and simultaneously used in a measurement campaign across a range of urban land use types and densities within a short time frame (3 hours). The dataset is used to aid in fine scale emission mapping in combination with simultaneous tower-based flux measurements. Overall, calculated CO2 emissions are realistic when compared against a spatially disaggregated scale emission inventory. The second approach is based on mass flux measurements of CO2 using a tower-based eddy covariance (EC) system. We present a continuous 7-year long dataset of CO2 fluxes measured by EC at the 28m tall flux tower 'Vancouver-Sunset'. We show how this dataset can be combined with turbulent source area models to quantify and partition different emission processes at the neighborhood-scale. The long-term EC measurements are within 10% of a spatially disaggregated scale emission inventory. Thirdly, at the urban scale, we present a dataset of CO2 mixing ratios measured using a tethered balloon system in the urban boundary layer above Vancouver. Using a simple box model, net city-scale CO2 emissions can be determined using measured rate of change of CO2 mixing ratios, estimated CO2 advection and entrainment fluxes. Daily city-scale emissions totals predicted by the model are within 32% of a spatially scaled municipal greenhouse gas inventory. In summary, combining information from different approaches and scales is a promising approach to establish long-term emission monitoring networks in cities.
Francisca, Franco Matías; Montoro, Marcos Alexis; Glatstein, Daniel Alejandro
2017-05-01
Landfill gas (LFG) management is one of the most important tasks for landfill operation and closure because of its impact in potential global warming. The aim of this work is to present a case history evaluating an LFG capture and treatment system for the present landfill facility in Córdoba, Argentina. The results may be relevant for many developing countries around the world where landfill gas is not being properly managed. The LFG generation is evaluated by modeling gas production applying the zero-order model, Landfill Gas Emissions Model (LandGEM; U.S. Environmental Protection Agency [EPA]), Scholl Canyon model, and triangular model. Variability in waste properties, weather, and landfill management conditions are analyzed in order to evaluate the feasibility of implementing different treatment systems. The results show the advantages of capturing and treating LFG in order to reduce the emissions of gases responsible for global warming and to determine the revenue rate needed for the project's financial requirements. This particular project reduces by half the emission of equivalent tons of carbon dioxide (CO 2 ) compared with the situation where there is no gas treatment. In addition, the study highlights the need for a change in the electricity prices if it is to be economically feasible to implement the project in the current Argentinean electrical market. Methane has 21 times more greenhouse gas potential than carbon dioxide. Because of that, it is of great importance to adequately manage biogas emissions from landfills. In addition, it is environmentally convenient to use this product as an alternative energy source, since it prevents methane emissions while preventing fossil fuel consumption, minimizing carbon dioxide emissions. Performed analysis indicated that biogas capturing and energy generation implies 3 times less equivalent carbon dioxide emissions; however, a change in the Argentinean electrical market fees are required to guarantee the financial feasibility of the project.
Parajulee, Abha; Wania, Frank
2014-03-04
Emissions of organic substances with potential toxicity to humans and the environment are a major concern surrounding the rapid industrial development in the Athabasca oil sands region (AOSR). Although concentrations of polycyclic aromatic hydrocarbons (PAHs) in some environmental samples have been reported, a comprehensive picture of organic contaminant sources, pathways, and sinks within the AOSR has yet to be elucidated. We sought to use a dynamic multimedia environmental fate model to reconcile the emissions and residue levels reported for three representative PAHs in the AOSR. Data describing emissions to air compiled from two official sources result in simulated concentrations in air, soil, water, and foliage that tend to fall close to or below the minimum measured concentrations of phenanthrene, pyrene, and benzo(a)pyrene in the environment. Accounting for evaporative emissions (e.g., from tailings pond disposal) provides a more realistic representation of PAH distribution in the AOSR. Such indirect emissions to air were found to be a greater contributor of PAHs to the AOSR atmosphere relative to reported direct emissions to air. The indirect pathway transporting uncontrolled releases of PAHs to aquatic systems via the atmosphere may be as significant a contributor of PAHs to aquatic systems as other supply pathways. Emission density estimates for the three PAHs that account for tailings pond disposal are much closer to estimated global averages than estimates based on the available emissions datasets, which fall close to the global minima. Our results highlight the need for improved accounting of PAH emissions from oil sands operations, especially in light of continued expansion of these operations.
Infrared polar brightenings on Jupiter. V - A thermal equilibrium model for the north polar hot spot
NASA Technical Reports Server (NTRS)
Halthore, Rangasayi; Burrows, Adam; Caldwell, John
1988-01-01
Voyager IRIS instrument records of the IR hydrocarbon emissions from Jupiter's north polar region are presently studied to determine the spatial and other characteristics of the north polar hot spot. Attention is given to a thermal equilibrium model that exploits the asymmetry found in 7.8-micron emission of stratospheric methane with respect to system III longitude in order to estimate stratospheric zonal wind velocity. This model accurately predicts the observed asymmetry in acetylene's 13.6-micron emission; this requires, however, enhanced acetylene abundance in the hot spot, as well as ethane depletion. Energetic charged particles are suggested to be the most probable cause of these effects.
Cui, Yu Yan; Brioude, Jerome; McKeen, Stuart A.; ...
2015-07-28
Methane (CH 4) is the primary component of natural gas and has a larger global warming potential than CO 2. Some recent top-down studies based on observations showed CH 4 emissions in California's South Coast Air Basin (SoCAB) were greater than those expected from population-apportioned bottom-up state inventories. In this study, we quantify CH 4 emissions with an advanced mesoscale inverse modeling system at a resolution of 8 km × 8 km, using aircraft measurements in the SoCAB during the 2010 Nexus of Air Quality and Climate Change campaign to constrain the inversion. To simulate atmospheric transport, we use themore » FLEXible PARTicle-Weather Research and Forecasting (FLEXPART-WRF) Lagrangian particle dispersion model driven by three configurations of the Weather Research and Forecasting (WRF) mesoscale model. We determine surface fluxes of CH 4 using a Bayesian least squares method in a four-dimensional inversion. Simulated CH4 concentrations with the posterior emission inventory achieve much better correlations with the measurements (R2 = 0.7) than using the prior inventory (U.S. Environmental Protection Agency's National Emission Inventory 2005, R 2 = 0.5). The emission estimates for CH 4 in the posterior, 46.3 ± 9.2 Mg CH 4/h, are consistent with published observation-based estimates. Changes in the spatial distribution of CH 4 emissions in the SoCAB between the prior and posterior inventories are discussed. Missing or underestimated emissions from dairies, the oil/gas system, and landfills in the SoCAB seem to explain the differences between the prior and posterior inventories. Furthermore, we estimate that dairies contributed 5.9 ± 1.7 Mg CH 4/h and the two sectors of oil and gas industries (production and downstream) and landfills together contributed 39.6 ± 8.1 Mg CH 4/h in the SoCAB.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nils Johnson; Joan Ogden
2010-12-31
In this final report, we describe research results from Phase 2 of a technical/economic study of fossil hydrogen energy systems with carbon dioxide (CO{sub 2}) capture and storage (CCS). CO{sub 2} capture and storage, or alternatively, CO{sub 2} capture and sequestration, involves capturing CO{sub 2} from large point sources and then injecting it into deep underground reservoirs for long-term storage. By preventing CO{sub 2} emissions into the atmosphere, this technology has significant potential to reduce greenhouse gas (GHG) emissions from fossil-based facilities in the power and industrial sectors. Furthermore, the application of CCS to power plants and hydrogen production facilitiesmore » can reduce CO{sub 2} emissions associated with electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs) and, thus, can also improve GHG emissions in the transportation sector. This research specifically examines strategies for transitioning to large-scale coal-derived energy systems with CCS for both hydrogen fuel production and electricity generation. A particular emphasis is on the development of spatially-explicit modeling tools for examining how these energy systems might develop in real geographic regions. We employ an integrated modeling approach that addresses all infrastructure components involved in the transition to these energy systems. The overall objective is to better understand the system design issues and economics associated with the widespread deployment of hydrogen and CCS infrastructure in real regions. Specific objectives of this research are to: Develop improved techno-economic models for all components required for the deployment of both hydrogen and CCS infrastructure, Develop novel modeling methods that combine detailed spatial data with optimization tools to explore spatially-explicit transition strategies, Conduct regional case studies to explore how these energy systems might develop in different regions of the United States, and Examine how the design and cost of coal-based H{sub 2} and CCS infrastructure depend on geography and location.« less
NASA Astrophysics Data System (ADS)
Liu, Q.; Li, J.; Du, Y.; Wen, J.; Zhong, B.; Wang, K.
2011-12-01
As the remote sensing data accumulating, it is a challenge and significant issue how to generate high accurate and consistent land surface parameter product from the multi source remote observation and the radiation transfer modeling and inversion methodology are the theoretical bases. In this paper, recent research advances and unresolved issues are presented. At first, after a general overview, recent research advances on multi-scale remote sensing radiation transfer modeling are presented, including leaf spectrum model, vegetation canopy BRDF models, directional thermal infrared emission models, rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed, taking the land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is suggested and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China are introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.
NASA Astrophysics Data System (ADS)
Olguin, Marcela; Wayson, Craig; Fellows, Max; Birdsey, Richard; Smyth, Carolyn E.; Magnan, Michael; Dugan, Alexa J.; Mascorro, Vanessa S.; Alanís, Armando; Serrano, Enrique; Kurz, Werner A.
2018-03-01
The Paris Agreement of the United Nation Framework Convention on Climate Change calls for a balance of anthropogenic greenhouse emissions and removals in the latter part of this century. Mexico indicated in its Intended Nationally Determined Contribution and its Climate Change Mid-Century Strategy that the land sector will contribute to meeting GHG emission reduction goals. Since 2012, the Mexican government through its National Forestry Commission, with international financial and technical support, has been developing carbon dynamics models to explore climate change mitigation options in the forest sector. Following a systems approach, here we assess the biophysical mitigation potential of forest ecosystems, harvested wood products and their substitution benefits (i.e. the change in emissions resulting from substitution of wood for more emissions-intensive products and fossil fuels), for policy alternatives considered by the Mexican government, such as a net zero deforestation rate and sustainable forest management. We used available analytical frameworks (Carbon Budget Model of the Canadian Forest Sector and a harvested wood products model), parameterized with local input data in two contrasting Mexican states. Using information from the National Forest Monitoring System (e.g. forest inventories, remote sensing, disturbance data), we demonstrate that activities aimed at reaching a net-zero deforestation rate can yield significant CO2e mitigation benefits by 2030 and 2050 relative to a baseline scenario (‘business as usual’), but if combined with increasing forest harvest to produce long-lived products and substitute more energy-intensive materials, emissions reductions could also provide other co-benefits (e.g. jobs, illegal logging reduction). We concluded that the relative impact of mitigation activities is locally dependent, suggesting that mitigation strategies should be designed and implemented at sub-national scales. We were also encouraged about the ability of the modeling framework to effectively use Mexico’s data, and showed the need to include multiple sectors and types of collaborators (scientific and policy-maker communities) to design more comprehensive portfolios for climate change mitigation.
Measuring and modeling of soil N2O emissions - How well are we doing?
NASA Astrophysics Data System (ADS)
Butterbach-Bahl, K.; Ralf, K.; Werner, C.; Wolf, B.
2017-12-01
Microbial processes in soils are the primarily source of atmospheric N2O. Fertilizer use to boost food and feed production of agricultural systems as well as nitrogen deposition to natural and semi-natural ecosystems due to emissions of NOx and NH3 from agriculture and energy production and re-deposition to terrestrial ecosystems has likely nearly doubled the pre-industrial source strength of soils for atmospheric N2O. Quantifying soil emissions and identifying mitigation options is becoming a major focus in the climate debate as N2O emissions from agricultural soils are a major contributor to the greenhouse gas footprint of agricultural systems, with agriculture incl. land use change contributing up to 30% to total anthropogenic GHG emissions. The increasing number of annual datasets show that soil emissions a) are largely depended on soil N availability and thus e.g. fertilizer application, b) vary with management (e.g. timing of fertilization, residue management, tillage), c) depend on soil properties such as organic matter content and pH, e) are affected by plant N uptake, and e) are controlled by environmental factors such as moisture and temperature regimes. It is remarkable that the magnitude of annual emissions is largely controlled by short-term N2O pulses occurring due to fertilization, wetting and drying or freezing and thawing of soils. All of this contributes to a notorious variability of soil N2O emissions in space and time. Overcoming this variability for quantification of source strengths and identifying tangible mitigation options requires targeted measuring approaches as well as the translation of our knowledge on mechanisms underlying emissions into process oriented models, which finally might be used for upscaling and scenario studies. This paper aims at reviewing current knowledge on measurements, modelling and upscaling of soil N2O emissions, thereby identifying short comes and uncertainties of the various approaches and fields for future research.
NASA Astrophysics Data System (ADS)
Woolf, Dominic; Lehmann, Johannes
2014-05-01
With CO2 emissions still tracking the upper bounds of projected emissions scenarios, it is becoming increasingly urgent to reduce net greenhouse gas (GHG) emissions, and increasingly likely that restricting future atmospheric GHG concentrations to within safe limits will require an eventual transition towards net negative GHG emissions. Few measures capable of providing negative emissions at a globally-significant scale are currently known. Two that are most often considered include carbon sequestration in biomass and soil, and biomass energy with carbon capture and storage (BECCS). In common with these two approaches, biochar also relies on the use of photosynthetically-bound carbon in biomass. But, because biomass and land are limited, it is critical that these resources are efficiently allocated between biomass/soil sequestration, bioenergy, BECCS, biochar, and other competing uses such as food, fiber and biodiversity. In many situations, biochar can offer advantages that may make it the preferred use of a limited biomass supply. These advantages include that: 1) Biochar can provide valuable benefits to agriculture by improving soil fertility and crop production, and reducing fertlizer and irrigation requirements. 2) Biochar is significantly more stable than biomass or other forms of soil carbon, thus lowering the risk of future losses compared to sequestration in biomass or soil organic carbon. 3) Gases and volatiles produced by pyrolysis can be combusted for energy (which may offset fossil fuel emissions). 4) Biochar can further lower GHG emissions by reducing nitrous oxide emissions from soil and by enhancing net primary production. Determining the optimal use of biomass requires that we are able to model not only the climate-change mitigation impact of each option, but also their economic and wider environmental impacts. Thus, what is required is a systems modelling approach that integrates components representing soil biogeochemistry, hydrology, crop production, land use, thermochemical conversion (to both biochar and energy products), climate, economics, and also the interactions between these components. Early efforts to model the life-cycle impacts of biochar systems have typically used simple empirical estimates of the strength of various feedback mechanisms, such as the impact of biochar on crop-growth, soil GHG fluxes, and native soil organic carbon. However, an environmental management perspective demands consideration of impacts over a longer time-scale and in broader agroecological situations than can be reliably extrapolated from simple empirical relationships derived from trials and experiments of inevitably limited scope and duration. Therefore, reliable quantification of long-term and large-scale impacts demands an understanding of the fundamental underlying mechanisms. Here, a systems-modelling approach that incorporates mechanistic assumptions will be described, and used to examine how uncertainties in the biogeochemical processes which drive the biochar-plant-soil interactions (particularly those responsible for priming, crop-growth and soil GHG emissions) translate into sensitivities of large scale and long-term impacts. This approach elucidates the aspects of process-level biochar biogeochemistry most critical to determining the large-scale GHG and economic impacts, and thus provides a useful guide to future model-led research.
MESAS: Measuring the Emission of Stellar Atmospheres at Submillimeter/millimeter Wavelengths
NASA Astrophysics Data System (ADS)
White, Jacob Aaron; Aufdenberg, Jason; Boley, A. C.; Hauschildt, Peter; Hughes, Meredith; Matthews, Brenda; Wilner, David
2018-06-01
In the early stages of planet formation, small dust grains grow to become millimeter-sized particles in debris disks around stars. These disks can in principle be characterized by their emission at submillimeter and millimeter wavelengths. Determining both the occurrence and abundance of debris in unresolved circumstellar disks of A-type main-sequence stars requires that the stellar photospheric emission be accurately modeled. To better constrain the photospheric emission for such systems, we present observations of Sirius A, an A-type star with no known debris, from the James Clerk Maxwell Telescope, Submillimeter Array, and Jansky Very Large Array at 0.45, 0.85, 0.88, 1.3, 6.7, and 9.0 mm. We use these observations to inform a PHOENIX model of Sirius A’s atmosphere. We find the model provides a good match to these data and can be used as a template for the submillimeter/millimeter emission of other early A-type stars where unresolved debris may be present. The observations are part of an ongoing observational campaign entitled Measuring the Emission of Stellar Atmospheres at Submillimeter/millimeter wavelengths.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Greenberg, Jim; Penuelas, J.; Guenther, Alex B.
To survey landscape-scale fluxes of biogenic gases, a100-meterTeflon tube was attached to a tethered balloon as a sampling inlet for a fast response Proton Transfer Reaction Mass Spectrometer (PTRMS). Along with meteorological instruments deployed on the tethered balloon and at 3-mand outputs from a regional weather model, these observations were used to estimate landscape scale biogenic volatile organic compound fluxes with two micrometeorological techniques: mixed layer variance and surface layer gradients. This highly mobile sampling system was deployed at four field sites near Barcelona to estimate landscape-scale BVOC emission factors in a relatively short period (3 weeks). The two micrometeorologicalmore » techniques agreed within the uncertainty of the flux measurements at all four sites even though the locations had considerable heterogeneity in species distribution and complex terrain. The observed fluxes were significantly different than emissions predicted with an emission model using site-specific emission factors and land-cover characteristics. Considering the wide range in reported BVOC emission factors of VOCs for individual vegetation species (more than an order of magnitude), this flux estimation technique is useful for constraining BVOC emission factors used as model inputs.« less
Advances in Estimating Methane Emissions from Enteric Fermentation
NASA Astrophysics Data System (ADS)
Kebreab, E.; Appuhamy, R.
2016-12-01
Methane from enteric fermentation of livestock is the largest contributor to the agricultural GHG emissions. The quantification of methane emissions from livestock on a global scale relies on prediction models because measurements require specialized equipment and may be expensive. Most countries use a fixed number (kg methane/year) or calculate as a proportion of energy intake to estimate enteric methane emissions in national inventories. However, diet composition significantly regulates enteric methane production in addition to total feed intake and thus the main target in formulating mitigation options. The two current methodologies are not able to assess mitigation options, therefore, new estimation methods are required that can take feed composition into account. The availability of information on livestock production systems has increased substantially enabling the development of more detailed methane prediction models. Limited number of process-based models have been developed that represent biological relationships in methane production, however, these require extensive inputs and specialized software that may not be easily available. Empirical models may provide a better alternative in practical situations due to less input requirements. Several models have been developed in the last 10 years but none of them work equally well across all regions of the world. The more successful models particularly in North America require three major inputs: feed (or energy) intake, fiber and fat concentration of the diet. Given the significant variability of emissions within regions, models that are able to capture regional variability of feed intake and diet composition perform the best in model evaluation with independent data. The utilization of such models may reduce uncertainties associated with prediction of methane emissions and allow a better examination and representation of policies regulating emissions from cattle.
European drought under climate change and an assessment of the uncertainties in projections
NASA Astrophysics Data System (ADS)
Yu, R. M. S.; Osborn, T.; Conway, D.; Warren, R.; Hankin, R.
2012-04-01
Extreme weather/climate events have significant environmental and societal impacts, and anthropogenic climate change has and will continue to alter their characteristics (IPCC, 2011). Drought is one of the most damaging natural hazards through its effects on agricultural, hydrological, ecological and socio-economic systems. Climate change is stimulating demand, from public and private sector decision-makers and also other stakeholders, for better understanding of potential future drought patterns which could facilitate disaster risk management. There remain considerable levels of uncertainty in climate change projections, particularly in relation to extreme events. Our incomplete understanding of the behaviour of the climate system has led to the development of various emission scenarios, carbon cycle models and global climate models (GCMs). Uncertainties arise also from the different types and definitions of drought. This study examines climate change-induced changes in European drought characteristics, and illustrates the robustness of these projections by quantifying the effects of using different emission scenarios, carbon cycle models and GCMs. This is achieved by using the multi-institutional modular "Community Integrated Assessment System (CIAS)" (Warren et al., 2008), a flexible integrated assessment system for modelling climate change. Simulations generated by the simple climate model MAGICC6.0 are assessed. These include ten C4MIP carbon cycle models and eighteen CMIP3 GCMs under five IPCC SRES emission scenarios, four Representative Concentration Pathway (RCP) scenarios, and three mitigation scenarios with CO2-equivalent levels stabilising at 550 ppm, 500 ppm and 450 ppm. Using an ensemble of 2160 future precipitation scenarios, we present an analysis on both short (3-month) and long (12-month) meteorological droughts based on the Standardised Precipitation Index (SPI) for the baseline period (1951-2000) and two future periods of 2001-2050 and 2051-2100. Results indicate, with the exception of high latitude regions, a marked increase in drought condition across Europe especially in the second half of 21st century. Patterns, however, vary substantially depending on the model, emission scenario, region and season. While the variance introduced by choice of carbon cycle model is of minor importance, contribution of emission scenario becomes more important in the second half of the century; nevertheless, GCM uncertainty remains the dominant source throughout the 21st century and across all regions.
Ye, Liu; Ni, Bing-Jie; Law, Yingyu; Byers, Craig; Yuan, Zhiguo
2014-01-01
The quantification of nitrous oxide (N2O) emissions from open-surface wastewater treatment systems with surface aerators is difficult as emissions from the surface aerator zone cannot be easily captured by floating hoods. In this study, we propose and demonstrate a novel methodology to estimate N2O emissions from such systems through determination of the N2O transfer coefficient (kLa) induced by surface aerators based on oxygen balance for the entire system. The methodology is demonstrated through its application to a full-scale open oxidation ditch wastewater treatment plant with surface aerators. The estimated kLa profile based on a month-long measurement campaign for oxygen balance, intensive monitoring of dissolved N2O profiles along the oxidation ditch over a period of four days, together with mathematical modelling, enabled to determine the N2O emission factor from this treatment plant (0.52 ± 0.16%). Majority of the N2O emission was found to occur in the surface aerator zone, which would be missed if the gas hood method was applied alone. Copyright © 2013 Elsevier Ltd. All rights reserved.
Qi, Yi; Padiath, Ameena; Zhao, Qun; Yu, Lei
2016-10-01
The Motor Vehicle Emission Simulator (MOVES) quantifies emissions as a function of vehicle modal activities. Hence, the vehicle operating mode distribution is the most vital input for running MOVES at the project level. The preparation of operating mode distributions requires significant efforts with respect to data collection and processing. This study is to develop operating mode distributions for both freeway and arterial facilities under different traffic conditions. For this purpose, in this study, we (1) collected/processed geographic information system (GIS) data, (2) developed a model of CO2 emissions and congestion from observations, (3) implemented the model to evaluate potential emission changes from a hypothetical roadway accident scenario. This study presents a framework by which practitioners can assess emission levels in the development of different strategies for traffic management and congestion mitigation. This paper prepared the primary input, that is, the operating mode ID distribution, required for running MOVES and developed models for estimating emissions for different types of roadways under different congestion levels. The results of this study will provide transportation planners or environmental analysts with the methods for qualitatively assessing the air quality impacts of different transportation operation and demand management strategies.
Study of emissions from light-duty vehicles in Denver. Final report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1981-08-31
A sample of 300 light-duty vehicles normally operated in the Denver metropolitan area was tested for emissions and fuel economy. The vehicles were from the 1978 through 1982 model years and included both passenger cars and light-duty trucks. One purpose of the program was to gather information for calculations and projections of ambient air quality. Another purpose was to assemble data on current model year vehicles for use in the support of Inspection/Maintenance and other regulatory programs. The vehicles were tested for exhaust emissions utilizing the Federal Test Procedure, the Highway Fuel Economy Test (HFET), and four short mode tests.more » 125 vehicles from the 1980-82 model years received an evaporative emission test using the sealed housing evaporative determination (SHED) technique. Other actions were taken in relation to each vehicle tested. These included an engine and emission control system maladjustment/disablement and status inspection, driveability evaluations, and owner interviews to obtain vehicle maintenance and usage data.« less
Josh Hyde; Eva K. Strand; Andrew T. Hudak; Dale Hamilton
2015-01-01
The use of fire as a land management tool is well recognized for its ecological benefits in many natural systems. To continue to use fire while complying with air quality regulations, land managers are often tasked with modeling emissions from fire during the planning process. To populate such models, the Landscape Fire and Resource Management Planning Tools (...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Iyer, Gokul C.; Clarke, Leon E.; Edmonds, James A.
The United States has articulated a deep decarbonization strategy for achieving a reduction in economy-wide greenhouse gas (GHG) emissions of 80% below 2005 levels by 2050. Achieving such deep emissions reductions will entail a major transformation of the energy system and of the electric power sector in particular. , This study uses a detailed state-level model of the U.S. energy system embedded within a global integrated assessment model (GCAM-USA) to demonstrate pathways for the evolution of the U.S. electric power sector that achieve 80% economy-wide reductions in GHG emissions by 2050. The pathways presented in this report are based onmore » feedback received during a workshop of experts organized by the U.S. Department of Energy’s Office of Energy Policy and Systems Analysis. Our analysis demonstrates that achieving deep decarbonization by 2050 will require substantial decarbonization of the electric power sector resulting in an increase in the deployment of zero-carbon and low-carbon technologies such as renewables and carbon capture utilization and storage. The present results also show that the degree to which the electric power sector will need to decarbonize and low-carbon technologies will need to deploy depends on the nature of technological advances in the energy sector, the ability of end-use sectors to electrify and level of electricity demand.« less
NASA Astrophysics Data System (ADS)
Meng, L.; Mahowald, N. M.; Hess, P. G.; Yavitt, J. B.; Riley, W. J.; Subin, Z. M.; Lawrence, D. M.; Swenson, S. C.; Jauhiainen, J.; Fuka, D. R.
2012-12-01
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 is 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 inundated area. 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 y-1 (including the soil sink). Tropical wetlands contributed 201 Tg CH4 y-1, or 78% of the global wetland flux. Northern latitude (>50N) systems contributed 12 Tg CH4 y-1. Our sensitivity studies show a large range (150-346 Tg CH4 y-1) in predicted global methane emissions. In order to evaluate our methane emissions on the regional and global scales against atmospheric measurements, we conducted simulations with the Community Atmospheric Model with chemistry (CAM-chem) forced with our baseline simulation of wetland and rice paddy emissions along with other methane sources (e.g. anthropogenic, fire, and termite emissions) and compared model simulations against measured atmospheric concentrations obtained from the World Data Centre for Greenhouse Gases (WDCGG) at http://ds.data.jma.go.jp/gmd/wdcgg/. Overall, using our estimated wetland and rice paddy emissions, CAM-chem model can produce seasonal and interannual variations of observed atmospheric concentration performs well. Thus, within the current level of uncertainty, our emissions appear to be reasonable.
NASA Astrophysics Data System (ADS)
Wu, Q.
2013-12-01
The MM5-SMOKE-CMAQ model system, which is developed by the United States Environmental Protection Agency(U.S. EPA) as the Models-3 system, has been used for the daily air quality forecast in the Beijing Municipal Environmental Monitoring Center(Beijing MEMC), as a part of the Ensemble Air Quality Forecast System for Beijing(EMS-Beijing) since the Olympic Games year 2008. In this study, we collect the daily forecast results of the CMAQ model in the whole year 2010 for the model evaluation. The results show that the model play a good model performance in most days but underestimate obviously in some air pollution episode. A typical air pollution episode from 11st - 20th January 2010 was chosen, which the air pollution index(API) of particulate matter (PM10) observed by Beijing MEMC reaches to 180 while the prediction of PM10-API is about 100. Taking in account all stations in Beijing, including urban and suburban stations, three numerical methods are used for model improvement: firstly, enhance the inner domain with 4km grids, the coverage from only Beijing to the area including its surrounding cities; secondly, update the Beijing stationary area emission inventory, from statistical county-level to village-town level, that would provide more detail spatial informance for area emissions; thirdly, add some industrial points emission in Beijing's surrounding cities, the latter two are both the improvement of emission. As the result, the peak of the nine national standard stations averaged PM10-API, which is simulated by CMAQ as daily hindcast PM10-API, reach to 160 and much near to the observation. The new results show better model performance, which the correlation coefficent is 0.93 in national standard stations average and 0.84 in all stations, the relative error is 15.7% in national standard stations averaged and 27% in all stations. The time series of 9 national standard in Beijing urban The scatter diagram of all stations in Beijing, the red is the forecast and the blue is new result.
Multiscale optical imaging of rare-earth-doped nanocomposites in a small animal model.
Higgins, Laura M; Ganapathy, Vidya; Kantamneni, Harini; Zhao, Xinyu; Sheng, Yang; Tan, Mei-Chee; Roth, Charles M; Riman, Richard E; Moghe, Prabhas V; Pierce, Mark C
2018-03-01
Rare-earth-doped nanocomposites have appealing optical properties for use as biomedical contrast agents, but few systems exist for imaging these materials. We describe the design and characterization of (i) a preclinical system for whole animal in vivo imaging and (ii) an integrated optical coherence tomography/confocal microscopy system for high-resolution imaging of ex vivo tissues. We demonstrate these systems by administering erbium-doped nanocomposites to a murine model of metastatic breast cancer. Short-wave infrared emissions were detected in vivo and in whole organ imaging ex vivo. Visible upconversion emissions and tissue autofluorescence were imaged in biopsy specimens, alongside optical coherence tomography imaging of tissue microstructure. We anticipate that this work will provide guidance for researchers seeking to image these nanomaterials across a wide range of biological models. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
Geometry dependent suppression of collective quantum jumps in Rydberg atoms
NASA Astrophysics Data System (ADS)
Lees, Eitan; Clemens, James
2015-05-01
We consider N driven, damped Rydberg atoms in different spatial arrangements. Treating the atoms as two-level systems we model the coupling to the environment via the Lehmberg-Agarwal master equation which interpolates between fully independent and fully collective spontaneous emission depending on the specific locations of the atoms. We also include a collective dipole-dipole energy shift in the excited Rydberg state which leads to collective quantum jumps in the atomic excitation when the system is driven off resonance. We show that the quantum jumps are suppressed as the system makes a transition from independent to collective emission as the spacing of a linear array of atoms is decreased below the emission wavelength.
A model to calculate consistent atmospheric emission projections and its application to Spain
NASA Astrophysics Data System (ADS)
Lumbreras, Julio; Borge, Rafael; de Andrés, Juan Manuel; Rodríguez, Encarnación
Global warming and air quality are headline environmental issues of our time and policy must preempt negative international effects with forward-looking strategies. As part of the revision of the European National Emission Ceilings Directive, atmospheric emission projections for European Union countries are being calculated. These projections are useful to drive European air quality analyses and to support wide-scale decision-making. However, when evaluating specific policies and measures at sectoral level, a more detailed approach is needed. This paper presents an original methodology to evaluate emission projections. Emission projections are calculated for each emitting activity that has emissions under three scenarios: without measures (business as usual), with measures (baseline) and with additional measures (target). The methodology developed allows the estimation of highly disaggregated multi-pollutant, consistent emissions for a whole country or region. In order to assure consistency with past emissions included in atmospheric emission inventories and coherence among the individual activities, the consistent emission projection (CEP) model incorporates harmonization and integration criteria as well as quality assurance/quality check (QA/QC) procedures. This study includes a sensitivity analysis as a first approach to uncertainty evaluation. The aim of the model presented in this contribution is to support decision-making process through the assessment of future emission scenarios taking into account the effect of different detailed technical and non-technical measures and it may also constitute the basis for air quality modelling. The system is designed to produce the information and formats related to international reporting requirements and it allows performing a comparison of national results with lower resolution models such as RAINS/GAINS. The methodology has been successfully applied and tested to evaluate Spanish emission projections up to 2020 for 26 pollutants but the methodology could be adopted for any particular region for different purposes, especially for European countries.
NASA Astrophysics Data System (ADS)
Sokolov, A. P.; Paltsev, S.; Chen, Y. H. H.; Monier, E.; Libardoni, A. G.; Forest, C. E.
2017-12-01
In December of 2015 during COP21 meeting in Paris almost 200 countries signed an agreement pledging to reduce their anthropogenic greenhouse gas (GHG) emissions. Recently USA announced plans to withdraw from the agreement. In this study, we estimate an impact of this decision on future climate using the MIT Integrated Global System Model, which consists of the human activity model, Economic Projection and Policy Analysis (EPPA) model, and a climate model of intermediate complexity, the MIT Earth System Model (MESM). For comparison, we also estimated impacts of possible withdrawals of China, Europe or India. In addition to the "no climate policy" scenario, we consider five emissions scenarios: Paris, Paris_no_USA, Paris_no_EUR and so on. Climate simulations were carried out from 1861 to 2005 driven by prescribed changes in GHGs and natural forcings and them continued to 2100 driven by GHG emissions produced by EPPA model. Because Paris agreement only cover the period up to 2030, last five scenarios were created assuming that emissions or carbon intensity will continue to decrease after 2030 at the same rate as in the 2020-2030 period. To account for uncertainty in climate system response to external forcing, we carry out 400 member ensembles on climate simulations for each scenario. Probability distributions for climate parameters are obtained by comparing simulated climate for 1861 to 2010 with observations. Our analysis shows that, full implementation of Paris agreement (under above-descried assumptions) will increase probability of surface air temperature in the last decade of this century increasing by less than 3oC relative to pre-industrial form about 20% for "no climate policy" to about 86%. Withdrawal of USA, China, Europe or India will decrease this probability to about 63, 67, 75 and 82%, respectively.
An agent-based model for an air emissions cap and trade program: A case study in Taiwan.
Huang, Hsing-Fu; Ma, Hwong-Wen
2016-12-01
To determine the actual status of individuals in a system and the trading interaction between polluters, this study uses an agent-based model to set up a virtual world that represents the Kaohsiung and Pingtung regions in Taiwan, which are under the country's air emissions cap and trade program. The model can simulate each controlled industry's dynamic behavioral condition with the bottom-up method and can investigate the impact of the program and determine the industry's emissions reduction and trading condition. This model can be used elastically to predict the impact of the trading market through adjusting different settings of the program rules or combining the settings with other measures. The simulation results show that the emissions trading market has an oversupply, but we find that the market trading amounts are low. Additionally, we find that increasing the air pollution fee and offset rate restrains the agents' trading decision, according to the simulation results of each scenario. In particular, NO x and SO x trading amounts are easily impacted by the pollution fee, reduction rate, and offset rate. Also, the more transparent the market, the more it can help polluters trade. Therefore, if authorities want to intervene in the emissions trading market, they must be careful in adjusting the air pollution fee and program rules; otherwise, the trading market system cannot work effectively. We also suggest setting up a trading platform to help the dealers negotiate successfully. Copyright © 2016 Elsevier Ltd. All rights reserved.
Chamber study of PCBemissions from caulking materials and ...
The emissions of polychlorinated biphenyl (PCB) congeners from 13 caulk samples were tested in a micro-chamber system. Twelve samples were from PCB-contaminated buildings and one was prepared in the laboratory. Nineteen light ballasts collected from buildings that represent 13 different models from five manufacturers were tested in 53-liter environmental chambers. The rates of PCB congener emissions from caulking materials and light ballasts were determined. Several factors that may have affected the emission rates were evaluated. The experimentally determined emission factors showed that, for a given PCB congener, there is a linear correlation between the emission factor and the concentration of the PCB congener in the source. Furthermore, the test results showed that an excellent log-linear correlation exists between the normalized emission factor and the vapor pressure (coefficient of determination, r2 ≥0.8846). The PCB congener emissions from ballasts at or near room temperature were relatively low with or without electrical load. However, the PCB congener emission rates increased significantly as the temperature increased. The results of this research provide new data and models for ranking the primary sources of PCBs and supports the development and refinement of exposure assessment models for PCBs. This study supplemented and complemented the field measurements in buildings conducted by U.S. EPA National Exposure Research Laboratory by providing a bette
van Puijenbroek, P J T M; Bouwman, A F; Beusen, A H W; Lucas, P L
2015-01-01
Households are an important source of nutrient loading to surface water. Sewage systems without or with only primary wastewater treatment are major polluters of surface water. Future emission levels will depend on population growth, urbanisation, increases in income and investments in sanitation, sewage systems and wastewater treatment plants. This study presents the results for two possible shared socioeconomic pathways (SSPs). SSP1 is a scenario that includes improvement of wastewater treatment and SSP3 does not include such improvement, with fewer investments and a higher population growth. The main drivers for the nutrient emission model are population growth, income growth and urbanisation. Under the SSP1 scenario, 5.7 billion people will be connected to a sewage system and for SSP3 this is 5 billion. Nitrogen and phosphorus emissions increase by about 70% under both SSP scenarios, with the largest increase in SSP1. South Asia and Africa have the largest emission increases, in the developed countries decrease the nutrient emissions. The higher emission level poses a risk to ecosystem services.
Comparison of GFED3, QFED2 and FEER1 Biomass Burning Emissions Datasets in a Global Model
NASA Technical Reports Server (NTRS)
Pan, Xiaohua; Ichoku, Charles; Bian, Huisheng; Chin, Mian; Ellison, Luke; da Silva, Arlindo; Darmenov, Anton
2015-01-01
Biomass burning contributes about 40% of the global loading of carbonaceous aerosols, significantly affecting air quality and the climate system by modulating solar radiation and cloud properties. However, fire emissions are poorly constrained in models on global and regional levels. In this study, we investigate 3 global biomass burning emission datasets in NASA GEOS5, namely: (1) GFEDv3.1 (Global Fire Emissions Database version 3.1); (2) QFEDv2.4 (Quick Fire Emissions Dataset version 2.4); (3) FEERv1 (Fire Energetics and Emissions Research version 1.0). The simulated aerosol optical depth (AOD), absorption AOD (AAOD), angstrom exponent and surface concentrations of aerosol plumes dominated by fire emissions are evaluated and compared to MODIS, OMI, AERONET, and IMPROVE data over different regions. In general, the spatial patterns of biomass burning emissions from these inventories are similar, although the strength of the emissions can be noticeably different. The emissions estimates from QFED are generally larger than those of FEER, which are in turn larger than those of GFED. AOD simulated with all these 3 databases are lower than the corresponding observations in Southern Africa and South America, two of the major biomass burning regions in the world.
Weilenmann, Martin F; Alvarez, Robert; Keller, Mario
2010-07-01
Mobile air conditioning (MAC) systems are the second-largest energy consumers in cars after driving itself. While different measurement series are available to illustrate their behavior in hot ambient conditions, little data are available for lower temperatures. There are also no data available on diesel vehicles, despite these being quite common in Europe (up to 70% of the fleet in some countries). In the present study, six representative modern diesel passenger cars were tested. In combination with data from previous measurements on gasoline cars, a new model was developed - EEMAC = Empa Emission model for Mobile Air Conditioning systems - to predict emissions from air conditioning. The measurements obtained show that A/C activity still occurs at temperatures below the desired interior temperature. The EEMAC model was applied to the average meteorological year of a central European region and compared with the US EPA MOBILE6 model. As temperatures in central Europe are often below 20 degrees C (the point below which the two models differ), the overall results differ clearly. The estimated average annual CO(2) output according to EEMAC is six times higher than that of MOBILE6. EEMAC also indicates that around two-thirds of the fuel used for air conditioning could be saved by switching the MAC system off below 18 degrees C.
NASA Astrophysics Data System (ADS)
Feng, Jun-shu; Jin, Yan-ming; Hao, Wei-hua
2017-01-01
Based on modelling the environmental influence index of power transmission and transformation project and energy-saving and emission-reducing index of source-grid-load of power system, this paper establishes an objective decision model of power grid environmental protection, with constraints of power grid environmental protection objectives being legal and economical, and considering both positive and negative influences of grid on the environmental in all-life grid cycle. This model can be used to guide the programming work of power grid environmental protection. A numerical simulation of Jiangsu province’s power grid environmental protection objective decision model has been operated, and the results shows that the maximum goal of energy-saving and emission-reducing benefits would be reached firstly as investment increasing, and then the minimum goal of environmental influence.
Evaluation of model-predicted hazardous air pollutants (HAPs) near a mid-sized U.S. airport
NASA Astrophysics Data System (ADS)
Vennam, Lakshmi Pradeepa; Vizuete, William; Arunachalam, Saravanan
2015-10-01
Accurate modeling of aircraft-emitted pollutants in the vicinity of airports is essential to study the impact on local air quality and to answer policy and health-impact related issues. To quantify air quality impacts of airport-related hazardous air pollutants (HAPs), we carried out a fine-scale (4 × 4 km horizontal resolution) Community Multiscale Air Quality model (CMAQ) model simulation at the T.F. Green airport in Providence (PVD), Rhode Island. We considered temporally and spatially resolved aircraft emissions from the new Aviation Environmental Design Tool (AEDT). These model predictions were then evaluated with observations from a field campaign focused on assessing HAPs near the PVD airport. The annual normalized mean error (NME) was in the range of 36-70% normalized mean error for all HAPs except for acrolein (>70%). The addition of highly resolved aircraft emissions showed only marginally incremental improvements in performance (1-2% decrease in NME) of some HAPs (formaldehyde, xylene). When compared to a coarser 36 × 36 km grid resolution, the 4 × 4 km grid resolution did improve performance by up to 5-20% NME for formaldehyde and acetaldehyde. The change in power setting (from traditional International Civil Aviation Organization (ICAO) 7% to observation studies based 4%) doubled the aircraft idling emissions of HAPs, but led to only a 2% decrease in NME. Overall modeled aircraft-attributable contributions are in the range of 0.5-28% near a mid-sized airport grid-cell with maximum impacts seen only within 4-16 km from the airport grid-cell. Comparison of CMAQ predictions with HAP estimates from EPA's National Air Toxics Assessment (NATA) did show similar annual mean concentrations and equally poor performance. Current estimates of HAPs for PVD are a challenge for modeling systems and refinements in our ability to simulate aircraft emissions have made only incremental improvements. Even with unrealistic increases in HAPs aviation emissions the model could not match observed concentrations near the runway airport site. Our results suggest other uncertainties in the modeling system such as meteorology, HAPs chemistry, or other emission sources require increased scrutiny.