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Sample records for air-quality modeling system

  1. Urban air quality simulation with community multi-scale air quality (CMAQ) modeling system

    SciTech Connect

    Byun, D.; Young, J.; Gipson, G.; Schere, K.; Godowitch, J.

    1998-11-01

    In an effort to provide a state-of-the-science air quality modeling capability, US EPA has developed a new comprehensive and flexible Models-3 Community Multi-scale Air Quality (CMAQ) modeling system. The authors demonstrate CMAQ simulations for a high ozone episode in the northeastern US during 12-15 July 1995 and discuss meteorological issues important for modeling of urban air quality.

  2. COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM (ONE ATMOSPHERE)

    EPA Science Inventory

    This task supports ORD's strategy by providing responsive technical support of EPA's mission and provides credible state of the art air quality models and guidance. This research effort is to develop and improve the Community Multiscale Air Quality (CMAQ) modeling system, a mu...

  3. REFINED PHOTOLYSIS RATES FOR ADVANCED AIR QUALITY MODELING SYSTEM

    EPA Science Inventory

    Accurate modeling of photochemistry is critical and fundamental to reducing the uncertainty in air quality model predictions. lmost all chemical reactions in the atmosphere are initiated by the photodissociation of a number of trace gases. irect measure of this photodissociation ...

  4. Downscaling modelling system for multi-scale air quality forecasting

    NASA Astrophysics Data System (ADS)

    Nuterman, R.; Baklanov, A.; Mahura, A.; Amstrup, B.; Weismann, J.

    2010-09-01

    Urban modelling for real meteorological situations, in general, considers only a small part of the urban area in a micro-meteorological model, and urban heterogeneities outside a modelling domain affect micro-scale processes. Therefore, it is important to build a chain of models of different scales with nesting of higher resolution models into larger scale lower resolution models. Usually, the up-scaled city- or meso-scale models consider parameterisations of urban effects or statistical descriptions of the urban morphology, whereas the micro-scale (street canyon) models are obstacle-resolved and they consider a detailed geometry of the buildings and the urban canopy. The developed system consists of the meso-, urban- and street-scale models. First, it is the Numerical Weather Prediction (HIgh Resolution Limited Area Model) model combined with Atmospheric Chemistry Transport (the Comprehensive Air quality Model with extensions) model. Several levels of urban parameterisation are considered. They are chosen depending on selected scales and resolutions. For regional scale, the urban parameterisation is based on the roughness and flux corrections approach; for urban scale - building effects parameterisation. Modern methods of computational fluid dynamics allow solving environmental problems connected with atmospheric transport of pollutants within urban canopy in a presence of penetrable (vegetation) and impenetrable (buildings) obstacles. For local- and micro-scales nesting the Micro-scale Model for Urban Environment is applied. This is a comprehensive obstacle-resolved urban wind-flow and dispersion model based on the Reynolds averaged Navier-Stokes approach and several turbulent closures, i.e. k -ɛ linear eddy-viscosity model, k - ɛ non-linear eddy-viscosity model and Reynolds stress model. Boundary and initial conditions for the micro-scale model are used from the up-scaled models with corresponding interpolation conserving the mass. For the boundaries a

  5. REGULATORY AIR QUALITY MODELS

    EPA Science Inventory

    Appendix W to 40CFR Part 51 (Guideline on Air Quality Models) specifies the models to be used for purposes of permitting, PSD, and SIPs. Through a formal regulatory process this modeling guidance is periodically updated to reflect current science. In the most recent action, thr...

  6. The air quality forecast in Beijing with Community Multi-scale Air Quality Modeling (CMAQ) System: model evaluation and improvement

    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

  7. Atmospheric Boundary Layer Modeling for Combined Meteorology and Air Quality Systems

    EPA Science Inventory

    Atmospheric Eulerian grid models for mesoscale and larger applications require sub-grid models for turbulent vertical exchange processes, particularly within the Planetary Boundary Layer (PSL). In combined meteorology and air quality modeling systems consistent PSL modeling of wi...

  8. LINKING ETA MODEL WITH THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODELING SYSTEM: OZONE BOUNDARY CONDITIONS

    EPA Science Inventory

    A prototype surface ozone concentration forecasting model system for the Eastern U.S. has been developed. The model system is consisting of a regional meteorological and a regional air quality model. It demonstrated a strong prediction dependence on its ozone boundary conditions....

  9. EPA third-generation air quality modeling system: Models-3 user manual. Standard tutorial

    SciTech Connect

    1998-09-01

    Models-3 is a flexible software system designed to simplify the development and use of environmental assessment and other decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of atmospheric chemistry and physics. The initial version of Models-3 contains a Community Multi-scale Air Quality (CMAQ) modeling system for urban to regional scale air quality simulation of tropospheric ozone, acid deposition, visibility, and fine particles. Models-3 and CMAQ in combination form a powerful third generation air quality modeling and assessment system that enables a user to execute air quality simulation models and visualize their results. Models-3/CMAQ also assists the model developer to assemble, test, and evaluate science process components and their impact on chemistry-transport model predictions by facilitating the interchange of science codes, transparent use of multiple computing platforms, and access of data across the network. The Models-3/CMAQ provides flexibility to change key model specifications such as grid resolution and chemistry mechanism without rewriting the code. Models-3/CMAQ is intended to serve as a community framework for continual advancement and use of environmental assessment tools. This User Manual Tutorial serves as a guide to show the steps necessary to implement an application in Models-3/CMAQ.

  10. Community Multiscale Air Quality Model

    EPA Science Inventory

    The U.S. EPA developed the Community Multiscale Air Quality (CMAQ) system to apply a “one atmosphere” multiscale and multi-pollutant modeling approach based mainly on the “first principles” description of the atmosphere. The multiscale capability is supported by the governing di...

  11. Impact of High Resolution Land-Use Data in Meteorology and Air Quality Modeling Systems

    EPA Science Inventory

    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...

  12. EVALUATING ADVECTION SCHEMES FOR USE IN THE NEXT GENERATION OF AIR QUALITY MODELING SYSTEMS

    EPA Science Inventory

    A simple air quality model prototype for EPA's third-generation modeling system, the Models-3 system, was recently implemented to test several design concepts. he prototype uses a time-splitting approach and process modules can be exchanged easily, without any restructuring of th...

  13. User manual for the EPA third-generation air quality modeling system (Models-3 version 3.0). Appendices

    SciTech Connect

    1999-06-01

    Models-3 is a flexible third generation software modeling system designed to simplify the development and use of the environmental assessment and other decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of atmospheric chemistry and physics. This version of Models-3 contains a Community Multiscale Air Quality (CMAQ) system for urban to regional scale air quality simulation of tropospheric ozone, acid deposition, visibility and fine particulate. Models-3 and CMAQ in combination form a powerful third generation air quality modeling and assessment system. Third generation models treat multiple pollutants simultaneously up to continental scales and incorporate feedback between chemical and meteorological components.

  14. User manual for the EPA third-generation air quality modeling system (Models-3 version 3.0)

    SciTech Connect

    1999-06-01

    Models-3 is a flexible third generation software modeling system designed to simplify the development and use of the environmental assessment and other decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of atmospheric chemistry and physics. This version of Models-3 contains a Community Multiscale Air Quality (CMAQ) system for urban to regional scale air quality simulation of tropospheric ozone, acid deposition, visibility and fine particulate. Models-3 and CMAQ in combination form a powerful third generation air quality modeling and assessment system. Third generation models treat multiple pollutants simultaneously up to continental scales and incorporate feedback between chemical and meteorological components.

  15. Development of a PC-based system for regional air quality modeling

    SciTech Connect

    Tran, K.T.; Cuq, F.

    1996-12-31

    Several large urban areas throughout the world are plagued by severe air quality problems. One of the most common problems in photochemical smog of ozone which is formed under sunlight by chemical reactions between nitrogen oxides and volatile organic compounds. These primary pollutants are emitted by a wide range of emission sources, most notably mobile sources such as automobiles, stationary point sources such as power plants and oil refineries, and stationary area sources such as residential heating. A sophisticated three-dimensional Eulerian grid model is frequently used to predict the air quality impacts of existing or proposed emission sources, or to assess the effectiveness of emission control measures. Until recently, regional air quality modelling is computer-intensive and requires the use of a mainframe or a supercomputer. Large advances in computer technology in recent years have resulted in inexpensive personal computers and workstations approaching the speed of the supercomputers of a few years ago. This paper describes the development of a state-of-the-art modeling system named SMART (System for Modeling Atmospheric Release and Transport) which is suitable for a wide range of regional air quality impact analyses yet capable of running on these inexpensive computers.

  16. FUNCTIONALITY OF AN INTEGRATED EMISSION PREPROCESSING SYSTEM FOR AIR QUALITY MODELING: THE MODELS-3 EMISSION PREPROCESSOR

    EPA Science Inventory

    Conventional preparation of emission inventories for air quality modeling is typically an extended process using computer routines to reformat, quality check, chemically speciate, and temporally and spatially allocate data. rocessing of emission inventories for regional modeling ...

  17. Implementation of a WRF-CMAQ Air Quality Modeling System in Bogotá, Colombia

    NASA Astrophysics Data System (ADS)

    Nedbor-Gross, R.; Henderson, B. H.; Pachon, J. E.; Davis, J. R.; Baublitz, C. B.; Rincón, A.

    2014-12-01

    Due to a continuous economic growth Bogotá, Colombia has experienced air pollution issues in recent years. The local environmental authority has implemented several strategies to curb air pollution that have resulted in the decrease of PM10 concentrations since 2010. However, more activities are necessary in order to meet international air quality standards in the city. The University of Florida Air Quality and Climate group is collaborating with the Universidad de La Salle to prioritize regulatory strategies for Bogotá using air pollution simulations. To simulate pollution, we developed a modeling platform that combines the Weather Research and Forecasting Model (WRF), local emissions, and the Community Multi-scale Air Quality model (CMAQ). This platform is the first of its kind to be implemented in the megacity of Bogota, Colombia. The presentation will discuss development and evaluation of the air quality modeling system, highlight initial results characterizing photochemical conditions in Bogotá, and characterize air pollution under proposed regulatory strategies. The WRF model has been configured and applied to Bogotá, which resides in a tropical climate with complex mountainous topography. Developing the configuration included incorporation of local topography and land-use data, a physics sensitivity analysis, review, and systematic evaluation. The threshold, however, was set based on synthesis of model performance under less mountainous conditions. We will evaluate the impact that differences in autocorrelation contribute to the non-ideal performance. Air pollution predictions are currently under way. CMAQ has been configured with WRF meteorology, global boundary conditions from GEOS-Chem, and a locally produced emission inventory. Preliminary results from simulations show promising performance of CMAQ in Bogota. Anticipated results include a systematic performance evaluation of ozone and PM10, characterization of photochemical sensitivity, and air

  18. NASA Earth Observation Systems and Applications for Public Health and Air Quality Models and Decisions Support

    NASA Astrophysics Data System (ADS)

    Estes, S. M.; Haynes, J. A.; Omar, A. H.

    2012-12-01

    Health and Air Quality providers and researchers need environmental data to study and understand the geographic, environmental, and meteorological differences in disease. Satellite remote sensing of the environment offers a unique vantage point that can fill in the gaps of environmental, spatial, and temporal data for tracking disease. This presentation will demonstrate the need for collaborations between multi-disciplinary research groups to develop the full potential of utilizing Earth Observations in studying health. Satellite earth observations present a unique vantage point of the earth's environment from space, which offers a wealth of health applications for the imaginative investigator. The presentation is directly related to Earth Observing systems and Global Health Surveillance and will present research results of the remote sensing environmental observations of earth and health applications, which can contribute to the public health and air quality research. As part of NASA approach and methodology they have used Earth Observation Systems and Applications for Public Health and Air Quality Models to provide a method for bridging gaps of environmental, spatial, and temporal data for tracking disease. This presentation will provide an overview of projects dealing with infectious diseases, water borne diseases and air quality and how many environmental variables effect human health. This presentation will provide a venue where the results of both research and practice using satellite earth observations to study weather and it's role in public health research.

  19. NASA Earth Observation Systems and Applications for Public Health and Air Quality Models and Decisions Support

    NASA Technical Reports Server (NTRS)

    Estes, Sue; Haynes, John; Omar, Ali

    2013-01-01

    Health and Air Quality providers and researchers need environmental data to study and understand the geographic, environmental, and meteorological differences in disease. Satellite remote sensing of the environment offers a unique vantage point that can fill in the gaps of environmental, spatial, and temporal data for tracking disease. This presentation will demonstrate the need for collaborations between multi-disciplinary research groups to develop the full potential of utilizing Earth Observations in studying health. Satellite earth observations present a unique vantage point of the earth's environment from space, which offers a wealth of health applications for the imaginative investigator. The presentation is directly related to Earth Observing systems and Global Health Surveillance and will present research results of the remote sensing environmental observations of earth and health applications, which can contribute to the public health and air quality research. As part of NASA approach and methodology they have used Earth Observation Systems and Applications for Public Health and Air Quality Models to provide a method for bridging gaps of environmental, spatial, and temporal data for tracking disease. This presentation will provide an overview of projects dealing with infectious diseases, water borne diseases and air quality and how many environmental variables effect human health. This presentation will provide a venue where the results of both research and practice using satellite earth observations to study weather and it's role in public health research.

  20. NASA Earth Observation Systems and Applications for Public Health and Air Quality Models and Decisions Support

    NASA Technical Reports Server (NTRS)

    Estes, Sue; Haynes, John; Omar, Ali

    2012-01-01

    Health and Air Quality providers and researchers need environmental data to study and understand the geographic, environmental, and meteorological differences in disease. Satellite remote sensing of the environment offers a unique vantage point that can fill in the gaps of environmental, spatial, and temporal data for tracking disease. This presentation will demonstrate the need for collaborations between multi-disciplinary research groups to develop the full potential of utilizing Earth Observations in studying health. Satellite earth observations present a unique vantage point of the earth's environment from space, which offers a wealth of health applications for the imaginative investigator. The presentation is directly related to Earth Observing systems and Global Health Surveillance and will present research results of the remote sensing environmental observations of earth and health applications, which can contribute to the public health and air quality research. As part of NASA approach and methodology they have used Earth Observation Systems and Applications for Public Health and Air Quality Models to provide a method for bridging gaps of environmental, spatial, and temporal data for tracking disease. This presentation will provide an overview of projects dealing with infectious diseases, water borne diseases and air quality and how many environmental variables effect human health. This presentation will provide a venue where the results of both research and practice using satellite earth observations to study weather and it's role in public health research.

  1. Air quality data systems integration

    SciTech Connect

    Row, V.K.; Wilson, J.F.

    1998-12-31

    Traditionally, data used for compliance with air quality programs are obtained from various sources within the plant, on site lab, or perhaps from a product movement accounting program. For the most part, the data processing and subsequent calculations and reports were handled individually, thus generating huge spreadsheets and mounds of process data in paper format. The natural reaction to this overwhelming data management problem is to search for an off-the-shelf software package that will hopefully cover all of the plant`s needs for compliance with air quality regulations. Rather than searching for or trying to custom build a single electronic system, the authors suggest using internet browsing software to create links between existing repositories of air quality data and related information.

  2. Monitoring Air Quality over China: Evaluation of the modeling system of the PANDA project

    NASA Astrophysics Data System (ADS)

    Bouarar, Idir; Katinka Petersen, Anna; Brasseur, Guy; Granier, Claire; Xie, Ying; Wang, Xuemei; Fan, Qi; Wang, Lili

    2015-04-01

    Air pollution has become a pressing problem in Asia and specifically in China due to rapid increase in anthropogenic emissions related to growth of China's economic activity and increasing demand for energy in the past decade. Observed levels of particulate matter and ozone regularly exceed World Health Organization (WHO) air quality guidelines in many parts of the country leading to increased risk of respiratory illnesses and other health problems. The EU-funded project PANDA aims to establish a team of European and Chinese scientists to monitor air pollution over China and elaborate air quality indicators in support of European and Chinese policies. PANDA combines state-of-the-art air pollution modeling with space and surface observations of chemical species to improve methods for monitoring air quality. The modeling system of the PANDA project follows a downscaling approach: global models such as MOZART and MACC system provide initial and boundary conditions to regional WRF-Chem and EMEP simulations over East Asia. WRF-Chem simulations at higher resolution (e.g. 20km) are then performed over a smaller domain covering East China and initial and boundary conditions from this run are used to perform simulations at a finer resolution (e.g. 5km) over specific megacities like Shanghai. Here we present results of model simulations for January and July 2010 performed during the first year of the project. We show an intercomparison of the global (MACC, EMEP) and regional (WRF-Chem) simulations and a comprehensive evaluation with satellite measurements (NO2, CO) and in-situ data (O3, CO, NOx, PM10 and PM2.5) at several surface stations. Using the WRF-Chem model, we demonstrate that model performance is influenced not only by the resolution (e.g. 60km, 20km) but also the emission inventories used (MACCity, HTAPv2), their resolution and diurnal variation, and the choice of initial and boundary conditions (e.g. MOZART, MACC analysis).

  3. Further investigations of automated surface observing system (ASOS) winds used in air quality modeling applications

    SciTech Connect

    Brower, R.P.; Jones, W.B.; Sherwell, J.

    1999-07-01

    Since 1992, a significant shift in the way standard surface meteorological data are observed and collected has occurred across the country. The National Weather Service, the Federal Aviation Administration, and the Department of Defense have been deploying the Automated Surface Observing System (ASOS) at nearly one thousand sites. Prior to ASOS, manual observation and recordation were the norm. With the advent of ASOS, an unprecedented level of meteorological data is now available; observations of standard meteorological variables are available almost real-time at more sites. However, with ASOS, meteorological data are being gathered in a fundamentally different way. New automated instruments sample, analyze, and record meteorological observations without human intervention. Many of these meteorological observations are key inputs to predictive air quality models. Reliable estimates of plume transport and dispersion require reliable and available meteorological data. The effect of the ASOS method of data collection on the dispersion modeling community is not clear. Because the hourly data now being reported at most stations across the country are being gathered in a fundamentally different way than previously, it is prudent to examine the differences between hourly meteorological observations gathered before and after ASOS. A preliminary analysis1 of pre-ASOS and ASOS data suggested that the differences in the observations could impact the data's application to air quality models. This expanded study examines more thoroughly the differences between wind data gathered before and after ASOS implementation in order to identify potential ramifications for air quality modeling. Pre-ASOS and ASOS data, from five stations in and around Maryland that represent the diversity of urbanization and topography of the region and that have a reasonably long record of ASOS observations, are examined.

  4. APPLICATION OF THE MODELS-3 COMMUNITY MULTI-SCALE AIR QUALITY (CMAQ) MODEL SYSTEM TO SOS/NASHVILLE 1999

    EPA Science Inventory

    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...

  5. Air quality and future energy system planning

    NASA Astrophysics Data System (ADS)

    Sobral Mourao, Zenaida; Konadu, Dennis; Lupton, Rick

    2016-04-01

    Ambient air pollution has been linked to an increasing number of premature deaths throughout the world. Projected increases in demand for food, energy resources and manufactured products will likely contribute to exacerbate air pollution with an increasing impact on human health, agricultural productivity and climate change. Current events such as tampering emissions tests by VW car manufacturers, failure to comply with EU Air Quality directives and WHO guidelines by many EU countries, the problem of smog in Chinese cities and new industrial emissions regulations represent unique challenges but also opportunities for regulators, local authorities and industry. However current models and practices of energy and resource use do not consider ambient air impacts as an integral part of the planing process. Furthermore the analysis of drivers, sources and impacts of air pollution is often fragmented, difficult to understand and lacks effective visualization tools that bring all of these components together. This work aims to develop a model that links impacts of air quality on human health and ecosystems to current and future developments in the energy system, industrial and agricultural activity and patterns of land use. The model will be added to the ForeseerTM tool, which is an integrated resource analysis platform that has been developed at the University of Cambridge initially with funding from BP and more recently through the EPSRC funded Whole Systems Energy Modeling (WholeSEM) project. The basis of the tool is a set of linked physical models for energy, water and land, including the technologies that are used to transform these resources into final services such as housing, food, transport and household goods. The new air quality model will explore different feedback effects between energy, land and atmospheric systems with the overarching goal of supporting better communication about the drivers of air quality and to incorporate concerns about air quality into

  6. Air quality forecast of PM10 in Beijing with Community Multi-scale Air Quality Modeling (CMAQ) system: emission and improvement

    NASA Astrophysics Data System (ADS)

    Wu, Q.; Xu, W.; Shi, A.; Li, Y.; Zhao, X.; Wang, Z.; Li, J.; Wang, L.

    2014-10-01

    The MM5-SMOKE-CMAQ model system, which was developed by the United States Environmental Protection Agency (US EPA) as the MODELS-3 system, has been used for daily air quality forecasts in the Beijing Municipal Environmental Monitoring Center (Beijing MEMC), as a part of the Ensemble air quality Modeling forecast System for Beijing (EMS-Beijing) since the 2008 Olympic Games. According to the daily forecast results for the entire duration of 2010, the model shows good performance in the PM10 forecast on most days but clearly underestimates PM10 concentration during some air pollution episodes. A typical air pollution episode from 11-20 January 2010 was chosen, in which the observed air pollution index of particulate matter (PM10-API) reached 180 while the forecast PM10-API was about 100. In this study, three numerical methods are used for model improvement: first, by enhancing the inner domain with 3 km resolution grids, and expanding the coverage from only Beijing to an area including Beijing and its surrounding cities; second, by adding more regional point source emissions located at Baoding, Landfang and Tangshan, to the south and east of Beijing; third, by updating the area source emissions, including the regional area source emissions in Baoding and Tangshan and the local village/town-level area source emissions in Beijing. The last two methods are combined as the updated emissions method. According to the model sensitivity testing results by the CMAQ model, the updated emissions method and expanded model domain method can both improve the model performance separately. But the expanded model domain method has better ability to capture the peak values of PM10 than the updated emissions method due to better reproduction of the pollution transport process in this episode. As a result, the hindcast results ("New(CMAQ)"), which are driven by the updated emissions in the expanded model domain, show a much better model performance in the national standard station

  7. Episode simulation of Asian dust storms with an air quality modeling system

    NASA Astrophysics Data System (ADS)

    Ge, Cui; Zhang, Meigen; Han, Zhiwei; Liu, Yanju

    2011-05-01

    A dust deflation module was developed and coupled with the air quality modeling system RAMS-CMAQ to simultaneously treat all the major tropospheric aerosols (i.e., organic and black carbons, sulfate, nitrate, ammonia, soil dust, and sea salt). Then the coupled system was applied to East Asia to simulate Asian dust aerosol generation, transport and dry/wet removal processes during 14-25 March 2002 when two strong dust storms occurred consecutively. To evaluate model performance and to analyze the observed features of dust aerosols over the East Asian region, model results were compared to concentrations of suspended particulate matter of 10 µm or less (PM10; 1-h intervals) at four remote Japanese stations and daily air pollution index (API) values for PM10 at four large Chinese cities. The modeled values were generally in good agreement with observed data, and the model reasonably reproduced two dust storm outbreaks and generally predicted the dust onset and cessation times at each observation site. In addition, hourly averaged values of aerosol optical thickness (AOT) were calculated and compared with observations at four Aerosol Robotic Network (AERONET) stations to assess the model's capability of estimating dust aerosol column burden. Analysis shows that modeled and observed AOT values were generally comparable and that the contribution of dust aerosols to AOT was significant only with regard to their source regions and their transport paths.

  8. The air quality forecast of PM10 in Beijing with Community Multi-scale Air Quality Modeling (CMAQ) system: emission and improvement

    NASA Astrophysics Data System (ADS)

    Wu, Q.; Xu, W.; Shi, A.; Li, Y.; Zhao, X.; Wang, Z.; Li, J.; Wang, L.

    2014-05-01

    The MM5-SMOKE-CMAQ model system, which was developed by the United States Environmental Protection Agency (US EPA) as the Models-3 system, has been used for daily air quality forecasts 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 2008. According to the daily forecast results for the entire duration of 2010, the model shows good model performances in the PM10 forecast on most days but clearly underestimates some air pollution episodes. A typical air pollution episode from 11-20 January 2010 was chosen, where the observed air pollution index of particulate matter (PM10-API) reached to 180 while the forecast's PM10-API was about 100. In this study, three numerical methods are used for model improvement: first, enhance the inner domain with 3 km resolution grids: the coverage is expanded from only Beijing to the area including Beijing and its surrounding cities; second, add more regional point source emissions located at Baoding, Landfang and Tangshan, which is to the south and east of Beijing; third, update the area source emissions, which includes the regional area source emissions in Baoding and Tangshan and the local village-town level area source emissions in Beijing. As a result, the hindcast shows a much better model performance in the national standard station-averaged PM10-API, whereas the daily hindcast PM10-API reaches 180 and is much closer to the observation and has a correlation coefficient of 0.93. The correlation coefficient of the PM10-API in all Beijing MEMC stations between the hindcast and observation is 0.82, obviously higher than the forecast's 0.54, and the FAC2 increases from 56% in the forecast to 84% in the hindcast, while the NMSE decreases from 0.886 to 0.196. The hindcast also has better model performance in PM10 hourly concentrations during the typical air pollution episode, the correlation coefficient

  9. Regional Air Quality Under Climate Change Using a Nested Global-Regional Modeling System

    NASA Astrophysics Data System (ADS)

    Dawson, J.; Racherla, P.; Lynn, B.; Adams, P.; Pandis, S.

    2006-12-01

    Strong links between climate, particulate matter and ozone make it likely that climate change will have impacts on air quality. This study examines the effects that climate change will have on concentrations of PM2.5 and ozone in the Eastern US. The changes examined are between the present day and the 2050s. This is accomplished by developing the Global-Regional Climate Air Pollution Modeling System (GRE-CAPS). GRE-CAPS couples a general circulation model (GCM) / global chemical transport model (CTM), a regional meteorological model, and a regional chemical transport model. Present and future climates are simulated by the GISS-II' GCM with an embedded gas-phase and aerosol chemistry model. Meteorology generated by the GCM is downscaled to the regional modeling domain using the MM5 regional climate model. The downscaled meteorology is passed to the regional chemical transport model PMCAMx. In addition to the downscaled meteorology, chemical boundary conditions for the regional model are derived from the global model. The coupled model system is evaluated for the present day by comparing model-predicted concentrations of O3 and PM2.5 to measured concentrations during the last decade. This comparison between typical present- day measurements and model predictions is made for three modeled present-day Julys (both PM2.5 and O3) and three modeled Januaries (PM2.5). Future concentrations (using the IPCC A2 scenario) are compared to present-day concentrations. Concentrations in specific sites and statistical distributions of concentrations will be examined.

  10. Observing System Simulation Experiments for air quality

    NASA Astrophysics Data System (ADS)

    Timmermans, R. M. A.; Lahoz, W. A.; Attié, J.-L.; Peuch, V.-H.; Curier, R. L.; Edwards, D. P.; Eskes, H. J.; Builtjes, P. J. H.

    2015-08-01

    This review paper provides a framework for the application of the Observing System Simulation Experiment (OSSE) methodology to satellite observations of atmospheric constituents relevant for air quality. The OSSEs are experiments used to determine the potential benefit of future observing systems using an existing monitoring or forecasting system and by this can help to define optimal characteristics of future instruments. To this end observations from future instruments are simulated from a model representing the realistic state of the atmosphere and an instrument simulator. The added value of the new observations is evaluated through assimilation into another model or model version and comparison with the simulated true state and a control run. This paper provides an overview of existing air quality OSSEs focusing on ozone, CO and aerosol. Using illustrative examples from these studies we present the main elements of an air quality OSSE and associated requirements based on evaluation of the existing studies and experience within the meteorological community. The air quality OSSEs performed hitherto provide evidence of their usefulness for evaluation of future observations although most studies published do not meet all the identified requirements. Especially the evaluation of the OSSE set-up requires more attention; the differences between the assimilation model and the simulated truth should approximate differences between models and real observations. Although this evaluation is missing in many studies, it is required to ensure realistic results. Properly executed air quality OSSEs are a valuable and cost effective tool to space agencies and instrument builders when applied at the start of the development stage to ensure future observations provide added value to users of Earth Observation data.

  11. REVIEW OF THE GOVERNING EQUATIONS, COMPUTATIONAL ALGORITHMS, AND OTHER COMPONENTS OF THE MODELS-3 COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODELING SYSTEM

    EPA Science Inventory

    This article describes the governing equations, computational algorithms, and other components entering into the Community Multiscale Air Quality (CMAQ) modeling system. This system has been designed to approach air quality as a whole by including state-of-the-science capabiliti...

  12. ENSEMBLE and AMET: Two Systems and Approaches to a Harmonized, Simplified and Efficient Facility for Air Quality Models Development and Evaluation

    EPA Science Inventory

    The complexity of air quality modeling systems, air quality monitoring data make ad-hoc systems for model evaluation important aids to the modeling community. Among those are the ENSEMBLE system developed by the EC-Joint Research Center, and the AMET software developed by the US-...

  13. Satellite data driven modeling system for predicting air quality and visibility during wildfire and prescribed burn events

    NASA Astrophysics Data System (ADS)

    Nair, U. S.; Keiser, K.; Wu, Y.; Maskey, M.; Berendes, D.; Glass, P.; Dhakal, A.; Christopher, S. A.

    2012-12-01

    The Alabama Forestry Commission (AFC) is responsible for wildfire control and also prescribed burn management in the state of Alabama. Visibility and air quality degradation resulting from smoke are two pieces of information that are crucial for this activity. Currently the tools available to AFC are the dispersion index available from the National Weather Service and also surface smoke concentrations. The former provides broad guidance for prescribed burning activities but does not provide specific information regarding smoke transport, areas affected and quantification of air quality and visibility degradation. While the NOAA operational air quality guidance includes surface smoke concentrations from existing fire events, it does not account for contributions from background aerosols, which are important for the southeastern region including Alabama. Also lacking is the quantification of visibility. The University of Alabama in Huntsville has developed a state-of-the-art integrated modeling system to address these concerns. This system based on the Community Air Quality Modeling System (CMAQ) that ingests satellite derived smoke emissions and also assimilates NASA MODIS derived aerosol optical thickness. In addition, this operational modeling system also simulates the impact of potential prescribed burn events based on location information derived from the AFC prescribed burn permit database. A lagrangian model is used to simulate smoke plumes for the prescribed burns requests. The combined air quality and visibility degradation resulting from these smoke plumes and background aerosols is computed and the information is made available through a web based decision support system utilizing open source GIS components. This system provides information regarding intersections between highways and other critical facilities such as old age homes, hospitals and schools. The system also includes satellite detected fire locations and other satellite derived datasets

  14. Regional/Urban Air Quality Modeling Assessment over China Using the Models-3/CMAQ System

    NASA Astrophysics Data System (ADS)

    Fu, J. S.; Jang, C. C.; Streets, D. G.; Li, Z.; Wang, L.; Zhang, Q.; Woo, J.; Wang, B.

    2004-12-01

    simulations in the Beijing, Shanghai areas are presented with sensitivity analysis. A comparison against available ozone and PM measurement data in Beijing, Shanghai is presented. The local emission inventory improvement in China is to be suggested to investigate. The modeling configuration of the Beijing 4-km x 4-km domain is to demonstrate the development of cost-effective control strategies for the air pollution control such as 2008 Olympic Game air quality management plan.

  15. MODEL ENGINEERING CONCEPTS FOR AIR QUALITY MODELS IN AN INTEGRATED ENVIRONMENTAL MODELING SYSTEM

    EPA Science Inventory

    Models 3 is an extensible environmental modeling system designed to meet the research and regulatory needs of the EPA and other users into the twenty-first century. s such, it must deal with a number of problems. hese problems include (1) the scientific correctness, flexibility, ...

  16. EMISSIONS PROCESSING FOR THE ETA/ CMAQ AIR QUALITY FORECAST SYSTEM

    EPA Science Inventory

    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...

  17. Impact of inherent meteorology uncertainty on air quality model predictions

    EPA Science Inventory

    It is well established that there are a number of different classifications and sources of uncertainties in environmental modeling systems. Air quality models rely on two key inputs, namely, meteorology and emissions. When using air quality models for decision making, it is impor...

  18. High-resolution modeling and evaluation of ozone air quality of Osaka using MM5-CMAQ system.

    PubMed

    Shrestha, Kundan Lal; Kondo, Akira; Kaga, Akikazu; Inoue, Yoshio

    2009-01-01

    High-resolution modeling approach is increasingly being considered as a necessary step for improving the monitoring and predictions of regional air quality. This is especially true for highly urbanized region with complex terrain and land-use. This study uses Community Multiscale Air Quality (CMAQ) model coupled with MM5 mesoscale model for a comprehensive analysis to assess the suitability of such high-resolution modeling system in predicting ozone air quality in the complex terrains of Osaka, Japan. The 1-km and 3-km grid domains were nested inside a 9-km domain and the domain with 1-km grid covered the Osaka region. High-resolution Grid Point Value-Mesoscale Model (GPV-MSM) data were used after suitable validation. The simulated ozone concentrations were validated and evaluated using statistical metrics using performance criteria set for ozone. Daily maxima of ozone were found better simulated by the 1-km grid domain than the coarser 9-km and 3-km domains, with the maximum improvement in the mean absolute gross error about 3 ppbv. In addition, 1-km grid results fared better than other grids at most of the observation stations that showed noticeable differences in gross error as well as correlation. These results amply justify the use of the integrated high-resolution MMS-CMAQ modeling system in the highly urbanized region, such as the Osaka region, which has complex terrain and land-use. PMID:19803083

  19. Applications of Satellite Remote Sensing Products to Enhance and Evaluate the AIRPACT Regional Air Quality Modeling System

    NASA Astrophysics Data System (ADS)

    Herron-Thorpe, F. L.; Mount, G. H.; Emmons, L. K.; Lamb, B. K.; Jaffe, D. A.; Wigder, N. L.; Chung, S. H.; Zhang, R.; Woelfle, M.; Vaughan, J. K.; Leung, F. T.

    2013-12-01

    The WSU AIRPACT air quality modeling system for the Pacific Northwest forecasts hourly levels of aerosols and atmospheric trace gases for use in determining potential health and ecosystem impacts by air quality managers. AIRPACT uses the WRF/SMOKE/CMAQ modeling framework, derives dynamic boundary conditions from MOZART-4 forecast simulations with assimilated MOPITT CO, and uses the BlueSky framework to derive fire emissions. A suite of surface measurements and satellite-based remote sensing data products across the AIRPACT domain are used to evaluate and improve model performance. Specific investigations include anthropogenic emissions, wildfire simulations, and the effects of long-range transport on surface ozone. In this work we synthesize results for multiple comparisons of AIRPACT with satellite products such as IASI ammonia, AIRS carbon monoxide, MODIS AOD, OMI tropospheric ozone and nitrogen dioxide, and MISR plume height. Features and benefits of the newest version of AIRPACT's web-interface are also presented.

  20. Application of a scenario-based modeling system to evaluate the air quality impacts of future growth

    NASA Astrophysics Data System (ADS)

    Kahyaoğlu-Koračin, Jülide; Bassett, Scott D.; Mouat, David A.; Gertler, Alan W.

    The structure and design of future urban development can have significant adverse effects on air pollutant emissions as well as other environmental factors. When considering the future impact of growth on mobile source emissions, we generally model the increase in vehicle kilometers traveled (VKT) as a function of population growth. However, diverse and poorly planned urban development (i.e., urban sprawl) can force higher rates of motor vehicle use and in return increase levels of pollutant emissions than alternative land-use scenarios. The objective of this study is to develop and implement an air quality assessment tool that takes into account the influence of alternative growth and development scenarios on air quality. The use of scenario-based techniques in land use planning has been around since the late 1940s and been tested in many different applications to aid in decision-making. In this study, we introduce the development of an advanced interactive scenario-based land use and atmospheric chemistry modeling system coupled with a GIS (Geographical Information System) framework. The modeling system is designed to be modular and includes land use/land cover information, transportation, meteorological, emissions, and photochemical modeling components. The methods and modularity of the developed system allow its application to both broad areas and applications. To investigate the impact of possible land use change and urbanization, we evaluated a set of alternative future patterns of land use developed for a study area in Southwest California. Four land use and two population variants (increases of 500k and 1M) were considered. Overall, a Regional Low-Density Future was seen to have the highest pollutant emissions, largest increase in VKT, and the greatest impact on air quality. On the other hand, a Three-Centers Future appeared to be the most beneficial alternative future land-use scenario in terms of air quality. For all cases, the increase in population was

  1. Development of a Micro-scale Air Monitoring and Modeling System for a Urban District Air Quality Management

    NASA Astrophysics Data System (ADS)

    Yoo, Seung Heon; Woo, Jung-Hun; Ryoo, Rina; Jung, Bujeon; Seo, Jun Seong; Kim, Jae-Jin; Boem Lim, Sang; Kim, Hyungseok

    2010-05-01

    As the city is urbanized, its landscape is getting more complex due to the construction of high-rise buildings. The smaller scale wind-field in an urban district may change frequently due to the complex terrain, the diverse landuse, and high-rise buildings. It also leads to dynamic changes of air pollution in that area. The conventional urban scale air quality management system, however, is too coarse to effectively manage such a small area. In this study, we set up a micro-scale air quality management testbed near Konkuk University, Seoul, Korea. A ubiquities sensor monitoring network, high resolution emission database, and CFD-based air quality modeling system were developed, and then applied to the testbed. A sensor data management system using wireless technology and multi-modal scientific visualization module were combined in support of the management system. The sensor based monitoring system shows reasonably good performance for wind speed, temperature, and carbon dioxide from inter-comparison study against conventional large format analyzers. The sensor data have been successfully collected using a wireless sensor data collection network during a 6months operation period from July, 2009. The fire pollution event simulation using the CFD model reveals the effect of high rise buildings in the testbed.

  2. AIR QUALITY MODELING FOR THE TWENTY-FIRST CENTURY

    EPA Science Inventory

    This presentation describes recent and evolving advances in the science of numerical air quality simulation modeling. Emphasis is placed on new developments in particulate matter modeling and atmospheric chemistry, diagnostic modeling tools, and integrated modeling systems. New...

  3. Eastern Texas Air Quality Forecasting System to Support TexAQS-II and 8-hour Ozone Modeling

    NASA Astrophysics Data System (ADS)

    Byun, D. W.

    2005-12-01

    The main objective of the Second Texas Air Quality Study (TexAQS-II) for 2005 and 2006 is to understand emissions and processes associated with the formation and transport of ozone and regional haze in Texas. The target research area is the more populated eastern half of the state, roughly from Interstate 35 eastward. Accurate meteorological and photochemical modeling efforts are essential to support this study and further enhance modeling efforts for establishing the State Implementation Plan (SIP) by Texas Commission on Environmental Quality (TCEQ). An air quality forecasting (AQF) system for Eastern Texas has been developed to provide these data and to further facilitate retrospective simulations to allow for model improvement and increased understanding of ozone episodes and emissions. We perform two-day air quality forecasting simulations with the 12-km Eastern Texas regional domain, and the 4-km Houston-Galveston area (HGA) domain utilizing a 48-CPU Beowulf Linux computer system. The dynamic boundary conditions are provided by the 36-km resolution conterminous US (CONUS) domain CMAQ simulations. Initial meteorological conditions are provided by the daily ETA forecast results. The results of individual runs are stored and made available to researchers and state and local officials via internet to study the patterns of air quality and its relationship to weather conditions and emissions. The data during the pre- and post-processing stages are in tens of gigabytes and must be managed efficiently during both the actual real-time and the subsequent computation periods. The nature of these forecasts and the time at which the initial data is available necessitates that models be executed within tight deadlines. A set of complex operational scripts is used to allow automatic operation of the data download, sequencing processors, performing graphical analysis, building database archives, and presenting on the web.

  4. Recent Advances in WRF Modeling for Air Quality Applications

    EPA Science Inventory

    The USEPA uses WRF in conjunction with the Community Multiscale Air Quality (CMAQ) for air quality regulation and research. Over the years we have added physics options and geophysical datasets to the WRF system to enhance model capabilities especially for extended retrospective...

  5. GUIDANCE FOR THE PERFORMANCE EVALUATION OF THREE-DIMENSIONAL AIR QUALITY MODELING SYSTEMS FOR PARTICULATE MATTER AND VISIBILITY

    EPA Science Inventory

    The National Ambient Air Quality Standards for particulate matter (PM) and the federal regional haze regulations place some emphasis on the assessment of fine particle (PM; 5) concentrations. Current air quality models need to be improved and evaluated against observations to a...

  6. COMPUTATIONAL MODELING ISSUES IN NEXT GENERATION AIR QUALITY MODELS

    EPA Science Inventory

    EPA's Atmospheric Research and Exposure Assessment Laboratory is leading a major effort to advance urban/regional multi-pollutant air quality modeling through development of a third-generation modeling system, Models-3. he Models-3 system is being developed within a high-performa...

  7. APPLICATION OF A NEW LAND-SURFACE, DRY DEPOSITION, AND PBL MODEL IN THE MODELS-3 COMMUNITY MULTI-SCALE AIR QUALITY (CMAQ) MODEL SYSTEM

    EPA Science Inventory

    Like most air quality modeling systems, CMAQ divides the treatment of meteorological and chemical/transport processes into separate models run sequentially. A potential drawback to this approach is that it creates the illusion that these processes are minimally interdependent an...

  8. A Community-Scale Modeling System to Assess Port-Related Air Quality Impacts

    EPA Science Inventory

    Near-port air pollution has been identified by numerous organizations as a potential public health concern. Based upon multiple near-road and near-source monitoring studies, both busy roadways and large emission sources at the ports may impact local air quality within several hun...

  9. Sensitivity of the Weather Research and Forecast/Community Multiscale Air Quality modeling system to MODIS LAI, FPAR, and albedo

    NASA Astrophysics Data System (ADS)

    Ran, Limei; Gilliam, Robert; Binkowski, Francis S.; Xiu, Aijun; Pleim, Jonathan; Band, Larry

    2015-08-01

    This study aims to improve land surface processes in a retrospective meteorology and air quality modeling system through the use of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation and albedo products for more realistic vegetation and surface representation. MODIS leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FPAR), and albedo are incorporated into the Pleim-Xiu land surface model (PX LSM) used in a combined meteorology and air quality modeling system. The current PX LSM intentionally exaggerates vegetation coverage and LAI in western dry lands so that its soil moisture nudging scheme is more effective in simulating surface temperature and mixing ratio. Reduced vegetation coverage from the PX LSM with MODIS input results in hotter and dryer daytime conditions with reduced ozone dry deposition velocities in much of western North America. Evaluations of the new system indicate greater error and bias in temperature, but reduced error and bias in moisture with the MODIS vegetation input. Hotter daytime temperatures and reduced dry deposition result in greater ozone concentrations in the western arid regions even with deeper boundary layer depths. MODIS albedo has much less impact on the meteorology simulations than MODIS LAI and FPAR. The MODIS vegetation and albedo input does not have much influence in the east where differences in vegetation and albedo parameters are less extreme. Evaluation results showing increased temperature errors with more accurate representation of vegetation suggests that improvements are needed in the model surface physics, particularly the soil processes in the PX LSM.

  10. INDOOR AIR QUALITY MODELING (CHAPTER 58)

    EPA Science Inventory

    The chapter discussses indoor air quality (IAQ) modeling. Such modeling provides a way to investigate many IAQ problems without the expense of large field experiments. Where experiments are planned, IAQ models can be used to help design experiments by providing information on exp...

  11. Simulation of air quality over Central-Eastern Europe - Performance evaluation of WRF-CAMx modelling system

    NASA Astrophysics Data System (ADS)

    Maciejewska, Katarzyna; Juda-Rezler, Katarzyna; Reizer, Magdalena

    2013-04-01

    The main goal of presented work is to evaluate the accuracy of modelling the atmospheric transport and transformation on regional scale, performed with 25 km grid spacing. The coupled Mesoscale Weather Model - Chemical Transport Model (CTM) has been applied for Europe under European-American AQMEII project (Air Quality Modelling Evaluation International Initiative - http://aqmeii.jrc.ec.europa.eu/). The modelling domain was centered over Denmark (57.00°N, 10.00°E) with 172 x 172 grid points in x and y direction. The map projection choice was Lambert conformal. In the applied modelling system the Comprehensive Air Quality Model with extensions (CAMx) from ENVIRON International Corporation (Novato, California) was coupled off-line to the Weather Research and Forecasting (WRF), developed by National Center for Atmospheric Research (NCAR). WRF-CAMx simulations have been carried out for 2006. The anthropogenic emisions database has been provided by TNO (Netherlands Organisation for Applied Scientific Research) under AQMEII initiative. Area and line emissions were proceeded by emission model EMIL (Juda-Rezler et al., 2012) [1], while for the point sources the EPS3 model (Emission Processor v.3 from ENVIRON) was implemented in order to obtain vertical distribution of emission. Boundary conditions were acquired from coupling the GEMS (Global and regional Earth-system Monitoring using Satellite and in-situ data) modelling system results with satellite observations. The modelling system has been evaluated for the area of Central-Eastern Europe, regarding ozone and particulate matter (PM) concentrations. For each pollutant measured data from rural background AirBase and EMEP stations, with more than 75% of daily data, has been used. Original 'operational' evaluation methodology, proposed by Juda-Rezler et al. (2012) was applied. Selected set of metrics consists of 5 groups: bias measures, error measures, correlation measures, measures of model variance and spread, which

  12. AIR QUALITY MODELING OF AMMONIA: A REGIONAL MODELING PERSPECTIVE

    EPA Science Inventory

    The talk will address the status of modeling of ammonia from a regional modeling perspective, yet the observations and comments should have general applicability. The air quality modeling system components that are central to modeling ammonia will be noted and a perspective on ...

  13. Meteorological Processes Affecting Air Quality – Research and Model Development Needs

    EPA Science Inventory

    Meteorology modeling is an important component of air quality modeling systems that defines the physical and dynamical environment for atmospheric chemistry. The meteorology models used for air quality applications are based on numerical weather prediction models that were devel...

  14. Photochemical plume-in-grid simulations of major point sources in the community multiscale air quality (CMAQ) modeling system

    SciTech Connect

    Godowitch, J.M.; Gillani, N.V.; Biazar, A.; Wu, Y.; Imhoff, R.E.

    1998-12-31

    A cooperative research and development effort has been conducted to design and implement a plume-in-grid (PinG) modeling techniques into the Models-3 Community Multiscale Air Quality (CMAQ) modeling system in order to address the need for an improved modeling approach to treat major point source emissions. Objectives are to provide an improved characterization of the near-source concentration field and a better far-field regional pollutant pattern due to the impact of the plume-in-grid approach. The conceptual design and an overview of the science processes contained in the PDM in PinG algorithms are briefly presented. Test simulations with and without the PinG treatment for a major NO{sub x} point source are described, and an O{sub 3} concentration pattern from the grid model reveals the impact of the plume-in-grid approach. Subgrid scale plume cell O{sub 3} concentrations are also shown.

  15. Uncertainty in Regional Air Quality Modeling

    NASA Astrophysics Data System (ADS)

    Digar, Antara

    Effective pollution mitigation is the key to successful air quality management. Although states invest millions of dollars to predict future air quality, the regulatory modeling and analysis process to inform pollution control strategy remains uncertain. Traditionally deterministic ‘bright-line’ tests are applied to evaluate the sufficiency of a control strategy to attain an air quality standard. A critical part of regulatory attainment demonstration is the prediction of future pollutant levels using photochemical air quality models. However, because models are uncertain, they yield a false sense of precision that pollutant response to emission controls is perfectly known and may eventually mislead the selection of control policies. These uncertainties in turn affect the health impact assessment of air pollution control strategies. This thesis explores beyond the conventional practice of deterministic attainment demonstration and presents novel approaches to yield probabilistic representations of pollutant response to emission controls by accounting for uncertainties in regional air quality planning. Computationally-efficient methods are developed and validated to characterize uncertainty in the prediction of secondary pollutant (ozone and particulate matter) sensitivities to precursor emissions in the presence of uncertainties in model assumptions and input parameters. We also introduce impact factors that enable identification of model inputs and scenarios that strongly influence pollutant concentrations and sensitivity to precursor emissions. We demonstrate how these probabilistic approaches could be applied to determine the likelihood that any control measure will yield regulatory attainment, or could be extended to evaluate probabilistic health benefits of emission controls, considering uncertainties in both air quality models and epidemiological concentration-response relationships. Finally, ground-level observations for pollutant (ozone) and precursor

  16. Fundamentals of air quality systems

    SciTech Connect

    Noll, K.E.

    1999-08-01

    The book uses numerous examples to demonstrate how basic design concepts can be applied to the control of air emissions from industrial sources. It focuses on the design of air pollution control devices for the removal of gases and particles from industrial sources, and provides detailed, specific design methods for each major air pollution control system. Individual chapters provide design methods that include both theory and practice with emphasis on the practical aspect by providing numerous examples that demonstrate how air pollution control devices are designed. Contents include air pollution laws, air pollution control devices; physical properties of air, gas laws, energy concepts, pressure; motion of airborne particles, filter and water drop collection efficiency; fundamentals of particulate emission control; cyclones; fabric filters; wet scrubbers; electrostatic precipitators; control of volatile organic compounds; adsorption; incineration; absorption; control of gaseous emissions from motor vehicles; practice problems (with solutions) for the P.E. examination in environmental engineering. Design applications are featured throughout.

  17. MODELING THE FORMATION OF SECONDARY ORGANIC AEROSOL WITHIN A COMPREHENSIVE AIR QUALITY MODEL SYSTEM

    EPA Science Inventory

    The aerosol component of the CMAQ model is designed to be an efficient and economical depiction of aerosol dynamics in the atmosphere. The approach taken represents the particle size distribution as the superposition of three lognormal subdistributions, called modes. The proces...

  18. High resolution operational air quality forecast for Poland and Central Europe with the GEM-AQ model - EcoForecast System

    NASA Astrophysics Data System (ADS)

    Kaminski, Jacek W.; Struzewska, Joanna

    2013-04-01

    The air quality forecast is an important component of the environmental assessment system. The "Clean Air for Europe" (CAFE) Directive 2008/50/EC stipulates a need for numerical modelling in order to support public information services to interpret measurements of pollutants concentrations and to prepare and evaluate air quality plans. Most European countries have developed model-based air quality modelling and information services. We will present the design strategy, development and implementation of a regional high resolution forecasting system that was implemented in Poland. The new national high resolution air quality forecasting system has evolved from a semi-operational chemical weather system EcoForecast.EU which is based on the GEM-AQ model (Kaminski et al., 2008). GEM-AQ is a comprehensive chemical weather model where air quality processes (chemistry and aerosols), troposphere and stratospheric chemistry are implemented on-line in the operational weather prediction model, the Global Environmental Multiscale (GEM) model (Cote et al, 1998), developed at Environment Canada. For these applications, the model is run on a global variable resolution grid with horizontal spacing of 15 km over Europe. In the vertical there are 28 hybrid levels, with the top at 10 hPa. A high resolution nested forecast at 5 km resolution over Poland (and surrounding countries) was implemented in December 2012. The forecast is published once a day at www.EcoForecast.EU. The air quality forecast is presented for ozone, nitrogen dioxide, sulphur dioxide, carbon monoxide, PM10 and PM2.5 as maps of daily maxima and daily averages. We will present results from the on-going model evaluation study over Central Europe (2010-2012). Modelling results were evaluated and compared with available observation of ozone and primary pollutants from air quality monitoring stations and from meteorological synoptic stations. Ozone exposure indices, as defined in the CAFE Directive, will be shown for the

  19. The Impact of Physical Atmosphere on Air Quality and the Utility of Satellite Observations in Air Quality Models

    NASA Astrophysics Data System (ADS)

    Pour Biazar, A.; McNider, R. T.; Park, Y. H.; Doty, K.; Khan, M. N.; Dornblaser, B.

    2012-12-01

    Physical atmosphere significantly impacts air quality as it regulates production, accumulation, and transport of atmospheric pollutants. Consequently, air quality simulations are greatly influenced by the uncertainties that emanates from the simulation of physical atmosphere. Since air quality model predictions are increasingly being used in health studies, regulatory applications, and policy making, reducing such uncertainties in model simulations is of outmost importance. This paper describes some of the critical aspects of physical atmosphere affecting air quality models that can be improved by utilizing satellite observations. Retrievals of skin temperature, surface albedo, surface insolation, cloud top temperature and cloud reflectance obtained from the Geostationary Operational Environmental Satellite (GOES) by NASA/MSFC GOES Product Generation System (GPGS) have been utilized to improve the air quality simulations used in the State Implementation Plan (SIP) attainment demonstrations. Satellite observations of ground temperature are used to recover surface moisture and heat capacity and thereby improving model simulation of air temperature. Observations of clouds are utilized to improve the photochemical reaction rates within the photochemical model and also to assimilate clouds in the meteorological model. These techniques have been implemented and tested in some of the widely used air quality decision modeling systems such as MM5/WRF/CMAQ/CAMx. The results from these activities show significant improvements in air quality simulations.

  20. DIAGNOSTIC EVALUATION OF NUMBERICAL AIR QUALITY MODELS WITH SPECIALIZED AMBIENT OBSERVATIONS: TESTING THE COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM (CMAQ) AT SELECTED SOS 95 GROUND SITES

    EPA Science Inventory

    Three probes for diagnosing photochemical dynamics are presented and applied to specialized ambient surface-level observations and to a numerical photochemical model to better understand rates of production and other process information in the atmosphere and in the model. Howeve...

  1. Experiences in evaluating regional air quality models

    NASA Astrophysics Data System (ADS)

    Liu, Mei-Kao; Greenfield, Stanley M.

    Any area of the world concerned with the health and welfare of its people and the viability of its ecological system must eventually address the question of the control of air pollution. This is true in developed countries as well as countries that are undergoing a considerable degree of industrialization. The control or limitation of the emissions of a pollutant can be very costly. To avoid ineffective or unnecessary control, the nature of the problem must be fully understood and the relationship between source emissions and ambient concentrations must be established. Mathematical models, while admittedly containing large uncertainties, can be used to examine alternatives of emission restrictions for achieving safe ambient concentrations. The focus of this paper is to summarize our experiences with modeling regional air quality in the United States and Western Europe. The following modeling experiences have been used: future SO 2 and sulfate distributions and projected acidic deposition as related to coal development in the northern Great Plains in the U.S.; analysis of regional ozone and sulfate episodes in the northeastern U.S.; analysis of the regional ozone problem in western Europe in support of alternative emission control strategies; analysis of distributions of toxic chemicals in the Southeast Ohio River Valley in support of the design of a monitoring network human exposure. Collectively, these prior modeling analyses can be invaluable in examining a similar problem in other parts of the world as well, such as the Pacific rim in Asia.

  2. TESTING PHYSICS AND CHEMISTRY SENSITIVITIES IN THE U.S. EPA COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM (CMAQ)

    EPA Science Inventory

    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...

  3. EPA THIRD-GENERATION AIR QUALITY MODELING SYSTEM - VOLUME 1: CONCEPT

    EPA Science Inventory

    A flexible environmental modeling and decision support system is being developed by the Office of Research and Development as part of EPA's High Performance Computing and Communications (HPCC) program. his report is Volume 1 of a multiple volume sat describing the development pro...

  4. Air quality modeling`s brave new world

    SciTech Connect

    Appleton, E.L.

    1996-05-01

    Since 1992, EPA has been creating a new generation of software - Models-3 - that is widely regarded as the next-generation air quality modeling system. The system has a modular framework that allows users to integrate a broad variety of air quality models. In the future, users will also be able to plug in economic decision support tools. A prototype version of Models-3 already exists in the Atmospheric Modeling Division of EPA`s National Exposure Research Laboratory in Research Triangle Park. EDSS was developed as a raid prototype of Models-3 under a three-year, $7.8 million cooperative agreement with EPA. An operational version of Models-3 may be in the hands of scientists and state air quality regulators by late 1997. Developers hope the new, more user-friendly system will make it easier to run models and present information to policy makers in graphical ways that are easy to understand. In addition, Models-3 will ultimately become a so-called `comprehensive modeling system` that enables users to simulate pollutants in other media, such as water. EPA also plans to include models that simulate health effects and other pollution consequences. 6 refs.

  5. Development and application of a high resolution hybrid modelling system for the evaluation of urban air quality

    NASA Astrophysics Data System (ADS)

    Pepe, N.; Pirovano, G.; Lonati, G.; Balzarini, A.; Toppetti, A.; Riva, G. M.; Bedogni, M.

    2016-09-01

    A hybrid modelling system (HMS) was developed to provide hourly concentrations at the urban local scale. The system is based on the combination of a meteorological model (WRF), a chemical and transport eulerian model (CAMx), which computes concentration levels over the regional domains, and a lagrangian dispersion model (AUSTAL2000), accounting for dispersion phenomena within the urban area due to local emission sources; a source apportionment algorithm is also included in the HMS in order to avoid the double counting of local emissions. The HMS was applied over a set of nested domains, the innermost covering a 1.6 × 1.6 km2 area in Milan city center with 20 m grid resolution, for NOX simulation in 2010. For this paper the innermost domain was defined as "local", excluding usual definition of urban areas. WRF model captured the overall evolution of the main meteorological features, except for some very stagnant situations, thus influencing the subsequent performance of regional scale model CAMx. Indeed, CAMx was able to reproduce the spatial and temporal evolution of NOX concentration over the regional domain, except a few episodes, when observed concentrations were higher than 100 ppb. The local scale model AUSTAL2000 provided high-resolution concentration fields that sensibly mirrored the road and traffic pattern in the urban domain. Therefore, the first important outcome of the work is that the application of the hybrid modelling system allowed a thorough and consistent description of urban air quality. This result represents a relevant starting point for future evaluation of pollution exposure within an urban context. However, the overall performance of the HMS did not provide remarkable improvements with respect to stand-alone CAMx at the two only monitoring sites in Milan city center. HMS results were characterized by a smaller average bias, that improved about 6-8 ppb corresponding to 12-13% of the observed concentration, but by a lower correlation, that

  6. Three-Dimensional Air Quality System (3D-AQS)

    NASA Astrophysics Data System (ADS)

    Engel-Cox, J.; Hoff, R.; Weber, S.; Zhang, H.; Prados, A.

    2007-12-01

    The 3-Dimensional Air Quality System (3DAQS) integrates remote sensing observations from a variety of platforms into air quality decision support systems at the U.S. Environmental Protection Agency (EPA), with a focus on particulate air pollution. The decision support systems are the Air Quality System (AQS) / AirQuest database at EPA, Infusing satellite Data into Environmental Applications (IDEA) system, the U.S. Air Quality weblog (Smog Blog) at UMBC, and the Regional East Atmospheric Lidar Mesonet (REALM). The project includes an end user advisory group with representatives from the air quality community providing ongoing feedback. The 3DAQS data sets are UMBC ground based LIDAR, and NASA and NOAA satellite data from MODIS, OMI, AIRS, CALIPSO, MISR, and GASP. Based on end user input, we are co-locating these measurements to the EPA's ground-based air pollution monitors as well as re-gridding to the Community Multiscale Air Quality (CMAQ) model grid. These data provide forecasters and the scientific community with a tool for assessment, analysis, and forecasting of U.S Air Quality. The third dimension and the ability to analyze the vertical transport of particulate pollution are provided by aerosol extinction profiles from the UMBC LIDAR and CALIPSO. We present examples of a 3D visualization tool we are developing to facilitate use of this data. We also present two specific applications of 3D-AQS data. The first is comparisons between PM2.5 monitor data and remote sensing aerosol optical depth (AOD) data, which show moderate agreement but variation with EPA region. The second is a case study for Baltimore, Maryland, as an example of 3D-analysis for a metropolitan area. In that case, some improvement is found in the PM2.5 /LIDAR correlations when using vertical aerosol information to calculate an AOD below the boundary layer.

  7. THE EMERGENCE OF NUMERICAL AIR QUALITY FORCASTING MODELS AND THEIR APPLICATIONS

    EPA Science Inventory

    In recent years the U.S. and other nations have begun programs for short-term local through regional air quality forecasting based upon numerical three-dimensional air quality grid models. These numerical air quality forecast (NAQF) models and systems have been developed and test...

  8. THE EMERGENCE OF NUMERICAL AIR QUALITY FORECASTING MODELS AND THEIR APPLICATION

    EPA Science Inventory

    In recent years the U.S. and other nations have begun programs for short-term local through regional air quality forecasting based upon numerical three-dimensional air quality grid models. These numerical air quality forecast (NAQF) models and systems have been developed and test...

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

    PubMed

    Xu, Ye; Huang, Guohe; Qin, Xiaosheng

    2010-07-01

    Regional air pollution is a major concern for almost every country because it not only directly relates to economic development, but also poses significant threats to environment and public health. In this study, an inexact fuzzy-chance-constrained air quality management model (IFAMM) was developed for regional air quality management under uncertainty. IFAMM was formulated through integrating interval linear programming (ILP) within a fuzzy-chance-constrained programming (FCCP) framework and could deal with uncertainties expressed as not only possibilistic distributions but also discrete intervals in air quality management systems. Moreover, the constraints with fuzzy variables could be satisfied at different confidence levels such that various solutions with different risk and cost considerations could be obtained. The developed model was applied to a hypothetical case of regional air quality management. Six abatement technologies and sulfur dioxide (SO2) emission trading under uncertainty were taken into consideration. The results demonstrated that IFAMM could help decision-makers generate cost-effective air quality management patterns, gain in-depth insights into effects of the uncertainties, and analyze tradeoffs between system economy and reliability. The results also implied that the trading scheme could achieve lower total abatement cost than a nontrading one. PMID:20681428

  10. AQMEII: A New International Initiative on Air Quality Model Evaluation

    EPA Science Inventory

    We provide a conceptual view of the process of evaluating regional-scale three-dimensional numerical photochemical air quality modeling system, based on an examination of existing approached to the evaluation of such systems as they are currently used in a variety of application....

  11. Testing of a PC-based regional air quality modeling system

    SciTech Connect

    Tran, K.T.; Cuq, F.

    1998-12-31

    Current regional modeling practice requires the use of a mesoscale model such as CSUMM or MM5 to generate the windfields and other meteorological inputs, and a photochemical grid model such as UAM or SAQM-AERO to predict ozone and PM concentrations. These models require extensive resources and are frequently operational on supercomputers and Unix workstations. Costs for running them on these computers are prohibitive, especially the analysis of different control strategies that may require dozens of model simulations. This paper describes the development and adaptation of regional models for running on inexpensive Pentium PCs. Benchmark tests using actual episodes are also compared against Cray supercomputers and Unix workstations.

  12. Aerosol Optical Depth over Europe: Evaluation of the CALIOPE air quality modelling system with direct-sun AERONET observations

    NASA Astrophysics Data System (ADS)

    Basart, Sara; Pay, María. Teresa; Pérez, Carlos; Cuevas, Emilio; Jorba, Oriol; Piot, Matthias; María Baldasano, Jose

    2010-05-01

    In the frame of the CALIOPE project (Baldasano et al., 2008), the Barcelona Supercomputing Center (BSC-CNS) currently operates a high-resolution air quality forecasting system based on daily photochemical forecasts in Europe (12km x 12km resolution) with the WRF-ARW/HERMES/CMAQ modelling system (http://www.bsc.es/caliope) and desert dust forecasts over Southern Europe with BSC-DREAM8b (Pérez et al., 2006; http://www.bsc.es/projects/earthscience/DREAM). High resolution simulations and forecasts are possible through their implementation on MareNostrum supercomputer at BSC-CNS. As shown in previous air quality studies (e.g. Rodríguez et al., 2001; Jiménez-Guerrero et al., 2008), the contribution of desert dust on particulate matter levels in Southern Europe is remarkable due to its proximity to African desert dust sources. When considering only anthropogenic emissions (Baldasano et al., 2008) and the current knowledge about aerosol physics and chemistry, chemistry-transport model simulations underestimate the PM10 concentrations by 30-50%. As a first approach, the natural dust contribution from BSC-DREAM8b is on-line added to the anthropogenic aerosol output of CMAQ. The aim of the present work is the quantitative evaluation of the WRF-ARW/HERMES/ CMAQ/BSC-DREAM8b forecast system to simulate the Aerosol Optical Depth (AOD) over Europe. The performance of the modelled AOD has been quantitatively evaluated with discrete and categorical (skill scores) statistics by a comparison to direct-sun AERONET observations for 2004. The contribution of different types of aerosols will be analyzed by means of the O'Neill fine mode AOD products (O'Neill et al., 2001). A previous aerosol characterization of AERONET data was performed (Basart et al., 2009) in order to discriminate the different aerosol source contributions within the study region. The results indicate a remarkable improvement in the discrete and skill-scores evaluation (accuracy, critical success index and

  13. The evaluation of the air quality impact of an incinerator by using MM5-CMAQ-EMIMO modeling system: North of Spain case study.

    PubMed

    San José, R; Pérez, J L; González, R M

    2008-07-01

    The use of sophisticated air pollution modeling systems to evaluate the impact of different industrial plant emissions is currently done in an extensive way. MM5-CMAQ (PSU/NCAR and EPA, USA) is one of the most applicable air quality modeling systems to evaluate those impacts. In this contribution we present the methodology and results obtained when applying the MM5-CMAQ air quality modeling system for evaluating the potential impact of an incinerator in San Sebastián (Basque Country, Spain). We have used the EMIMO (UPM, Spain) emission model to simulate the emissions from biogenic and anthropogenic sources including traffic and tertiary sector sources. The study includes the air quality impact of a highway located near the incinerator named A8 and 6 industrial plants which already exist. The impact study has been compared with the results obtained from this highway impact and the 6 industrial plants which are normally operating during the last 30 years. The system has been prepared to simulate also Cadmium, Arsenic, Nickel, Lead and Benzo(a)pyrene air quality impacts. The PCDD/F air concentrations have been determined for the 16 toxic dioxins and furans as determined in the bibliography. The criteria pollutants such as CO, NOx, SO(2), PM(10) and O(3) have also been determined according to the different EU Directives which limit the values of such a pollutants for different periods of time. PMID:18436306

  14. Diagnostic Evaluation of Ozone Production and Horizontal Transport in a Regional Photochemical Air Quality Modeling System

    EPA Science Inventory

    A diagnostic model evaluation effort has been performed to focus on photochemical ozone formation and the horizontal transport process since they strongly impact the temporal evolution and spatial distribution of ozone (O3) within the lower troposphere. Results from th...

  15. Impact of inherent meteorology uncertainty on air quality model predictions

    NASA Astrophysics Data System (ADS)

    Gilliam, Robert C.; Hogrefe, Christian; Godowitch, James M.; Napelenok, Sergey; Mathur, Rohit; Rao, S. Trivikrama

    2015-12-01

    It is well established that there are a number of different classifications and sources of uncertainties in environmental modeling systems. Air quality models rely on two key inputs, namely, meteorology and emissions. When using air quality models for decision making, it is important to understand how uncertainties in these inputs affect the simulated concentrations. Ensembles are one method to explore how uncertainty in meteorology affects air pollution concentrations. Most studies explore this uncertainty by running different meteorological models or the same model with different physics options and in some cases combinations of different meteorological and air quality models. While these have been shown to be useful techniques in some cases, we present a technique that leverages the initial condition perturbations of a weather forecast ensemble, namely, the Short-Range Ensemble Forecast system to drive the four-dimensional data assimilation in the Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) model with a key focus being the response of ozone chemistry and transport. Results confirm that a sizable spread in WRF solutions, including common weather variables of temperature, wind, boundary layer depth, clouds, and radiation, can cause a relatively large range of ozone-mixing ratios. Pollutant transport can be altered by hundreds of kilometers over several days. Ozone-mixing ratios of the ensemble can vary as much as 10-20 ppb or 20-30% in areas that typically have higher pollution levels.

  16. ADAPTATION AND APPLICATION OF THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODELING SYSTEM FOR REAL-TIME AIR QUALITY FORECASTING DURING THE SUMMER OF 2004

    EPA Science Inventory

    The ability to forecast local and regional air pollution events is challenging since the processes governing the production and sustenance of atmospheric pollutants are complex and often non-linear. Comprehensive atmospheric models, by representing in as much detail as possible t...

  17. Urban compaction or dispersion? An air quality modelling study

    NASA Astrophysics Data System (ADS)

    Martins, Helena

    2012-07-01

    Urban sprawl is altering the landscape, with current trends pointing to further changes in land use that will, in turn, lead to changes in population, energy consumption, atmospheric emissions and air quality. Urban planners have debated on the most sustainable urban structure, with arguments in favour and against urban compaction and dispersion. However, it is clear that other areas of expertise have to be involved. Urban air quality and human exposure to atmospheric pollutants as indicators of urban sustainability can contribute to the discussion, namely through the study of the relation between urban structure and air quality. This paper addresses the issue by analysing the impacts of alternative urban growth patterns on the air quality of Porto urban region in Portugal, through a 1-year simulation with the MM5-CAMx modelling system. This region has been experiencing one of the highest European rates of urban sprawl, and at the same time presents a poor air quality. As part of the modelling system setup, a sensitivity study was conducted regarding different land use datasets and spatial distribution of emissions. Two urban development scenarios were defined, SPRAWL and COMPACT, together with their new land use and emission datasets; then meteorological and air quality simulations were performed. Results reveal that SPRAWL land use changes resulted in an average temperature increase of 0.4 °C, with local increases reaching as high as 1.5 °C. SPRAWL results also show an aggravation of PM10 annual average values and an increase in the exceedances to the daily limit value. For ozone, differences between scenarios were smaller, with SPRAWL presenting larger concentration differences than COMPACT. Finally, despite the higher concentrations found in SPRAWL, population exposure to the pollutants is higher for COMPACT because more inhabitants are found in areas of highest concentration levels.

  18. THE EMISSION PROCESSING SYSTEM FOR THE ETA/CMAQ AIR QUALITY FORECAST SYSTEM

    EPA Science Inventory

    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...

  19. Evaluating NOx emission inventories for regulatory air quality modeling using satellite and air quality model data

    NASA Astrophysics Data System (ADS)

    Kemball-Cook, Susan; Yarwood, Greg; Johnson, Jeremiah; Dornblaser, Bright; Estes, Mark

    2015-09-01

    The purpose of this study was to assess the accuracy of NOx emissions in the Texas Commission on Environmental Quality's (TCEQ) State Implementation Plan (SIP) modeling inventories of the southeastern U.S. We used retrieved satellite tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI) together with NO2 columns from the Comprehensive Air Quality Model with Extensions (CAMx) to make top-down NOx emissions estimates using the mass balance method. Two different top-down NOx emissions estimates were developed using the KNMI DOMINO v2.0 and NASA SP2 retrievals of OMI NO2 columns. Differences in the top-down NOx emissions estimates made with these two operational products derived from the same OMI radiance data were sufficiently large that they could not be used to constrain the TCEQ NOx emissions in the southeast. The fact that the two available operational NO2 column retrievals give such different top-down NOx emissions results is important because these retrievals are increasingly being used to diagnose air quality problems and to inform efforts to solve them. These results reflect the fact that NO2 column retrievals are a blend of measurements and modeled data and should be used with caution in analyses that will inform policy development. This study illustrates both benefits and challenges of using satellite NO2 data for air quality management applications. Comparison with OMI NO2 columns pointed the way toward improvements in the CAMx simulation of the upper troposphere, but further refinement of both regional air quality models and the NO2 column retrievals is needed before the mass balance and other emission inversion methods can be used to successfully constrain NOx emission inventories used in U.S. regulatory modeling.

  20. Incorporation of the Wind Erosion Prediction System (WEPS) for dust into a regional air quality modeling system

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Wind erosion of soil is a major concern of the agricultural community as it removes the most fertile part of the soil and thus degrades soil productivity. Furthermore, suspension of eroded soil particles results in dust emissions into the atmosphere, contributing to poor air quality, reduced visibi...

  1. EPA RESEARCH HIGHLIGHTS -- MODELS-3/CMAQ OFFERS COMPREHENSIVE APPROACH TO AIR QUALITY MODELING

    EPA Science Inventory

    Regional and global coordinated efforts are needed to address air quality problems that are growing in complexity and scope. Models-3 CMAQ contains a community multi-scale air quality modeling system for simulating urban to regional scale pollution problems relating to troposphe...

  2. Establishment of urban air quality prediction system

    SciTech Connect

    Ben-Jei Tsuang; Jime-Ming Huang

    1996-12-31

    By using the data of Taipei metropolitan and Taichung city, it was found that the concentrations of the PM{sub 10} and SO{sub 2} were strongly associated with wind speed, rain, surface layer stability and their initial concentrations. Among these factors, stability in the atmospheric surface layer was not fully addressed in traditional box model. A new box model formula was derived to include the stability parameter. After analysis of exchange/removal mechanisms operating in the PBL by using this new model, we find that the near ground pollutant concentration after reaching steady state is dose to q{sub 0}l/2ul{sub e} under stable, low wind speed and rainless day, where q{sub 0} is emission rate, 1 length of a city, u wind speed and l{sub e} stability scale length. Under calm wind speed in addition to the aforementioned conditions, the air quality became most deteriorated and close to q{sub 0}/V{sub d}, where V{sub d} is dry deposition rate. This formula works well in simulating PM{sub 10} and SO{sub 2} concentration of Pancho and Taichung city. In addition, this formula also can handle most of the deteriorated days.

  3. THE ATMOSPHERIC MODEL EVALUATION TOOL (AMET); AIR QUALITY MODULE

    EPA Science Inventory

    This presentation reviews the development of the Atmospheric Model Evaluation Tool (AMET) air quality module. The AMET tool is being developed to aid in the model evaluation. This presentation focuses on the air quality evaluation portion of AMET. Presented are examples of the...

  4. 77 FR 4808 - Conference on Air Quality Modeling

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-01-31

    ... when we issued supplement B. We republished the Guideline in August 1996 (61 FR 41838) to adopt the CFR... AGENCY Conference on Air Quality Modeling AGENCY: U.S. Environmental Protection Agency (EPA). ACTION: Notice of conference. SUMMARY: The EPA will be hosting the Tenth Conference on Air Quality Modeling...

  5. Modeling human judgments of urban visual air quality

    NASA Astrophysics Data System (ADS)

    Middleton, Paulette; Stewart, Thomas R.; Dennis, Robin L.

    The overall approach to establishing a complete predictive model link between pollutant emissions and human judgments of urban visual air quality (UVAQ) is presented. The field study design and data analysis procedures developed for analyzing the human components of visual air quality assessment are outlined. The air quality simulation model which relates pollutant emissions to human judgments of visual cues which comprise visual air quality judgments is described. Measured and modeled cues are compared for five typical visual air quality days in the winter of 1981 for Denver, Colorado. The comparisons suggest that the perceptual cue model, based on dispersion and radiative transfer theory, does not adequately predict human judgments of UVAQ cues. Analysis of the limits of predictability of the human judgments and the predictive capability of the model components indicates that the greatest improvements toward achieving a predictive UVAQ model lie in a reformulation of the theoretical descriptions of visual cues.

  6. Modeling air quality over China: Results from the Panda project

    NASA Astrophysics Data System (ADS)

    Katinka Petersen, Anna; Bouarar, Idir; Brasseur, Guy; Granier, Claire; Xie, Ying; Wang, Lili; Wang, Xuemei

    2015-04-01

    China faces strong air pollution problems related to rapid economic development in the past decade and increasing demand for energy. Air quality monitoring stations often report high levels of particle matter and ozone all over the country. Knowing its long-term health impacts, air pollution became then a pressing problem not only in China but also in other Asian countries. The PANDA project is a result of cooperation between scientists from Europe and China who joined their efforts for a better understanding of the processes controlling air pollution in China, improve methods for monitoring air quality and elaborate indicators in support of European and Chinese policies. A modeling system of air pollution is being setup within the PANDA project and include advanced global (MACC, EMEP) and regional (WRF-Chem, EMEP) meteorological and chemical models to analyze and monitor air quality in China. The poster describes the accomplishments obtained within the first year of the project. Model simulations for January and July 2010 are evaluated with satellite measurements (SCIAMACHY NO2 and MOPITT CO) and in-situ data (O3, CO, NOx, PM10 and PM2.5) observed at several surface stations in China. Using the WRF-Chem model, we investigate the sensitivity of the model performance to emissions (MACCity, HTAPv2), horizontal resolution (60km, 20km) and choice of initial and boundary conditions.

  7. DESIGN REQUIREMENTS FOR MULTISCALE AIR QUALITY MODELS

    EPA Science Inventory

    Society (as mandated by the clean Air Act) requires that we protect our environment and minimize human exposure to harmful air pollutants with National Ambient Air Quality Standards (NAAQS). e al:o seek to minimize the economic costs of the necessary pollution control to meet the...

  8. The avian respiratory system: a unique model for studies of respiratory toxicosis and for monitoring air quality.

    PubMed Central

    Brown, R E; Brain, J D; Wang, N

    1997-01-01

    There are many distinct differences (morphologic, physiologic, and mechanical) between the bird's lung-air-sac respiratory system and the mammalian bronchoalveolar lung. In this paper, we review the physiology of the avian respiratory system with attention to those mechanisms that may lead to significantly different results, relative to those in mammals, following exposure to toxic gases and airborne particulates. We suggest that these differences can be productively exploited to further our understanding of the basic mechanisms of inhalant toxicology (gases and particulates). The large mass-specific gas uptake by the avian respiratory system, at rest and especially during exercise, could be exploited as a sensitive monitor of air quality. Birds have much to offer in our understanding of respiratory toxicology, but that expectation can only be realized by investigating, in a wide variety of avian taxa, the pathophysiologic interactions of a broad range of inhaled toxicants on the bird's unique respiratory system. Images p188-a Figure 1. Figure 2. Figure 3. Figure 4. Figure 5. A Figure 5. B Figure 5. C Figure 6. Figure 7. Figure 8. PMID:9105794

  9. DESCRIPTION OF ATMOSPHERIC TRANSPORT PROCESSES IN EULERIAN AIR QUALITY MODELS

    EPA Science Inventory

    Key differences among many types of air quality models are the way atmospheric advection and turbulent diffusion processes are treated. Gaussian models use analytical solutions of the advection-diffusion equations. Lagrangian models use a hypothetical air parcel concept effecti...

  10. Evaluation of emission control strategies to reduce ozone pollution in the Paso del Norte region using a photochemical air quality modeling system

    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

  11. Dynamic Evaluation of Long-Term Air Quality Model Simulations Over the Northeastern U.S.

    EPA Science Inventory

    Dynamic model evaluation assesses a modeling system's ability to reproduce changes in air quality induced by changes in meteorology and/or emissions. In this paper, we illustrate various approaches to dynamic mode evaluation utilizing 18 years of air quality simulations perform...

  12. PROTOTYPING AND IMPLEMENTATION OF MULTISCALE AIR QUALITY MODELS FOR HIGH PERFORMANCE COMPUTING

    EPA Science Inventory

    Important missions of the U.S. EPA are to enhance understanding of the global environmental system and to develop tools to help environmental policy decision making. hree-dimensional air quality models used by EPA are examples of such tools. lthough current air quality models are...

  13. Diagnostic Analysis of Ozone Concentrations Simulated by Two Regional-Scale Air Quality Models

    EPA Science Inventory

    Since the Community Multiscale Air Quality modeling system (CMAQ) and the Weather Research and Forecasting with Chemistry model (WRF/Chem) use different approaches to simulate the interaction of meteorology and chemistry, this study compares the CMAQ and WRF/Chem air quality simu...

  14. Bayesian Analysis of a Reduced-Form Air Quality Model

    EPA Science Inventory

    Numerical air quality models are being used for assessing emission control strategies for improving ambient pollution levels across the globe. This paper applies probabilistic modeling to evaluate the effectiveness of emission reduction scenarios aimed at lowering ground-level oz...

  15. INTERCOMPARISON OF ALTERNATIVE VEGETATION DATABASES FOR REGIONAL AIR QUALITY MODELING

    EPA Science Inventory

    Vegetation cover data are used to characterize several regional air quality modeling processes, including the calculation of heat, moisture, and momentum fluxes with the Mesoscale Meteorological Model (MM5) and the estimate of biogenic volatile organic compound and nitric oxide...

  16. USER MANUAL FOR THE EPA THIRD-GENERATION AIR QUALITY MODELING SYSTEM (MODELS-3 VERSION 3.0)

    EPA Science Inventory

    Models-3 is a flexible software system designed to simplify the development and use of environmental assessment and other decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of atmospheri...

  17. Assessment and prediction of air quality using fuzzy logic and autoregressive models

    NASA Astrophysics Data System (ADS)

    Carbajal-Hernández, José Juan; Sánchez-Fernández, Luis P.; Carrasco-Ochoa, Jesús A.; Martínez-Trinidad, José Fco.

    2012-12-01

    In recent years, artificial intelligence methods have been used for the treatment of environmental problems. This work, presents two models for assessment and prediction of air quality. First, we develop a new computational model for air quality assessment in order to evaluate toxic compounds that can harm sensitive people in urban areas, affecting their normal activities. In this model we propose to use a Sigma operator to statistically asses air quality parameters using their historical data information and determining their negative impact in air quality based on toxicity limits, frequency average and deviations of toxicological tests. We also introduce a fuzzy inference system to perform parameter classification using a reasoning process and integrating them in an air quality index describing the pollution levels in five stages: excellent, good, regular, bad and danger, respectively. The second model proposed in this work predicts air quality concentrations using an autoregressive model, providing a predicted air quality index based on the fuzzy inference system previously developed. Using data from Mexico City Atmospheric Monitoring System, we perform a comparison among air quality indices developed for environmental agencies and similar models. Our results show that our models are an appropriate tool for assessing site pollution and for providing guidance to improve contingency actions in urban areas.

  18. Incorporating principal component analysis into air quality model evaluation

    EPA Science Inventory

    The efficacy of standard air quality model evaluation techniques is becoming compromised as the simulation periods continue to lengthen in response to ever increasing computing capacity. Accordingly, the purpose of this paper is to demonstrate a statistical approach called Princi...

  19. SYSTEMATIC SENSITIVITY ANALYSIS OF AIR QUALITY SIMULATION MODELS

    EPA Science Inventory

    This report reviews and assesses systematic sensitivity and uncertainty analysis methods for applications to air quality simulation models. The discussion of the candidate methods presents their basic variables, mathematical foundations, user motivations and preferences, computer...

  20. A FEDERATED PARTNERSHIP FOR URBAN METEOROLOGICAL AND AIR QUALITY MODELING

    EPA Science Inventory

    Recently, applications of urban meteorological and air quality models have been performed at resolutions on the order of km grid sizes. This necessitated development and incorporation of high resolution landcover data and additional boundary layer parameters that serve to descri...

  1. On the design of distributed air quality monitoring systems

    NASA Astrophysics Data System (ADS)

    Velasco, Alejandro; Ferrero, Renato; Gandino, Filippo; Montrucchio, Bartolomeo; Rebaudengo, Maurizio

    2015-12-01

    Nowadays, the air quality is considered a key point, and its monitoring is not only suggested but it is even required in many countries. Since traditional standard monitors for air quality are very expensive, the use of a low-cost distributed network of sensors represents a valid complementary approach. This paper discusses the benefits of a distributed approach and analyzes the main elements that should be taken into account during the design of a distributed system for the air quality monitoring. This paper aims at representing a valuable aid for researchers and practitioners interested in the topic.

  2. 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.

  3. An airborne remote sensing system for urban air quality

    NASA Technical Reports Server (NTRS)

    Duncan, L. J.; Friedman, E. J.; Keitz, E. L.; Ward, E. A.

    1974-01-01

    Several NASA sponsored remote sensors and possible airborne platforms were evaluated. Outputs of dispersion models for SO2 and CO pollution in the Washington, D.C. area were used with ground station data to establish the expected performance and limitations of the remote sensors. Aircraft/sensor support requirements are discussed. A method of optimum flight plan determination was made. Cost trade offs were performed. Conclusions about the implementation of various instrument packages as parts of a comprehensive air quality monitoring system in Washington are presented.

  4. Development of an Agricultural Fertilizer Modeling System for Bi-Directional Ammonia Fluxes in the Community Multiscale Air Quality (CMAQ) Model

    EPA Science Inventory

    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...

  5. ONE ATMOSPHERE MODELING FOR AIR QUALITY: BUILDING PARTNERSHIPS THAT TRANSITION RESEARCH INTO APPLICATIONS

    EPA Science Inventory

    The Community Miultiscale Air Quality (CMAQ) modeling system is a "one atmosphere" chemical transport model that simulates the transport and fate of air pollutants from urban to continental scales and from daily to annual time intervals.

  6. Efficient sensitivity computations in 3D air quality models

    NASA Astrophysics Data System (ADS)

    Kioutsioukis, Ioannis; Melas, Dimitrios; Zerefos, Christos; Ziomas, Ioannis

    2005-04-01

    The prediction of ground level ozone for air quality monitoring and assessment is simulated through an integrated system of gridded models (meteorological, photochemical), where the atmosphere is represented with a three-dimensional grid that may include thousands of grid cells. The continuity equation solved by the Photochemical Air Quality Model (PAQM) reproduces the atmospheric processes (dynamical, physical, chemical and radiative), such as moving and mixing air parcels from one grid cell to another, calculating chemical reactions, injecting new emissions. The whole modeling procedure includes several sources of uncertainty, especially in the large data sets that describe the status of the domain (boundary conditions, emissions, chemical reaction rates and several others). The robustness of the photochemical simulation is addressed in this work through the deterministic approach of sensitivity analysis. The automatic differentiation tool ADIFOR is applied on the 3D PAQM CAMx and augments its Fortran 77 code by introducing new lines of code that additionally calculate, in only one run, the gradient of the solution vector with respect to its input parameters. The applicability of the approach is evaluated through a sensitivity study of the modeled concentrations to perturbations at the boundary conditions and the emissions, for three essentially dissimilar European Metropolises of the Auto-Oil II programme (Athens, Milan, and London).

  7. An Air Quality Data Analysis System for Interrelating Effects, Standards and Needed Source Reductions

    ERIC Educational Resources Information Center

    Larsen, Ralph I.

    1973-01-01

    Makes recommendations for a single air quality data system (using average time) for interrelating air pollution effects, air quality standards, air quality monitoring, diffusion calculations, source-reduction calculations, and emission standards. (JR)

  8. DEVELOPMENT OF MESOSCALE AIR QUALITY SIMULATION MODELS. VOLUME 5. USER'S GUIDE TO THE MESOFILE POSTPROCESSING PACKAGE

    EPA Science Inventory

    The MESOscale FILE management and analysis package (MESOFILE) is a highly flexible postprocessing system designed especially for interface with the MESOPLUME, MESOPUFF, and MESOGRID regional-scale air quality models, and the MESOPAC meteorology package. The MESOFILE package is co...

  9. The air quality forecast about PM2.5 before and during APEC 2014 in Beijing by WRF-CMAQ model system

    NASA Astrophysics Data System (ADS)

    Wu, Qizhong; Xu, Wenshuai; Wang, Zifa

    2015-04-01

    In the past year 2014, the APEC meeting was hold in Beijing, where the particulate matter (PM2.5) concentration is high and worried. In such a heavily air-polluted environment, people want access to reasonable air quality predictions, that the government can take necessary short-term emissions reduction measures to improve air quality. According to Wu et al. (2014), the enhanced model domain and the updated emissions inventory will improve the model performance of particulate matter concentration obviously, a new model system, with the enhanced 9km-domain and latest emission inventory in WRF-SMOKE-CMAQ model, was established in October 2014, before APEC. As a result, the model system plays good performance in the whole October: 1) the model catches four air pollution episodes in October, and has a high correlation coefficient of 0.89, 2) the daily forecast of PM2.5 concentration reaches 277 \\unit{{μ}g m-3} and close to the observed value (320 \\unit{{μ}g m-3}), but still a little underestimated, 3) the mean bias(MB) of the forecast to observed is 1.03 \\unit{{μ}g m-3} and the normalized mean bias(NMB) is 24.9{%}, 4) the normalized mean square error (NMSE) between the forecast and observed is 0.137 in October. The forecast results, with well performance, indicate the emissions inventory used in the model system is reasonable as baseline scenario, which scenario without any emission-sources reduction. From 3 to 12 November, the emission-sources reduction measures(e.g. the traffic restriction, factory cut production and closures) are carried step by step in Beijing and its surrounding areas. Those measures information is collected and used in the SMOKE model with growth/project module, to prepared as a reduced emissions inventory as APEC scenario. The same WRF-CMAQ model system, but be driven by the emission inventory of APEC scenario, was added from 3 November, to forecast the air quality under such emission-sources reduction measures, and evaluate the effect of

  10. Incorporating the Wind Erosion Prediction System (WEPS) Into a Regional Air Quality Modeling System for the Pacific Northwest

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In the Pacific Northwest, wind storms intermittently cause massive dust events that reduce visibility along roadways and jeopardize health as a result of extremely high concentrations of PM10 (particulate matter less than or equal to 10µm in diameter). An early warning dust forecast system is needed...

  11. Mining Environmental Data from a Coupled Modelling System to Examine the Impact of Agricultural Management Practices on Groundwater and Air Quality

    NASA Astrophysics Data System (ADS)

    Garcia, V.; Cooter, E. J.; Hayes, B.; Murphy, M. S.; Bash, J. O.

    2014-12-01

    Excess nitrogen (N) resulting from current agricultural management practices can leach into sources of drinking water as nitrate, increasing human health risks of 'blue baby syndrome', hypertension, and some cancers and birth defects. Nitrogen also enters the atmosphere from land surfaces forming air pollution increasing human health risks of pulmonary and cardio-vascular disease. Characterizing and attributing nitrogen from agricultural management practices is difficult due to the complex and inter-related chemical and biological reactions associated with the nitrogen cascade. Coupled physical process-based models, however, present new opportunities to investigate relationships among environmental variables on new scales; particularly because they link emission sources with meteorology and the pollutant concentration ultimately found in the environment. In this study, we applied a coupled meteorology (NOAA-WRF), agricultural (USDA-EPIC) and air quality modelling system (EPA-CMAQ) to examine the impact of nitrogen inputs from corn production on ecosystem and human health and wellbeing. The coupled system accounts for the nitrogen flux between the land surface and air, and the soil surface and groundwater, providing a unique opportunity to examine the effect of management practices such as type and timing of fertilization, tilling and irrigation on both groundwater and air quality across the conterminous US. In conducting the study, we first determined expected relationships based on literature searches and then identified model variables as direct or surrogate variables. We performed extensive and methodical multi-variate regression modelling and variable selection to examine associations between agricultural management practices and environmental condition. We then applied the regression model to predict and contrast pollution levels between two corn production scenarios (Figure 1). Finally, we applied published health functions (e.g., spina bifida and cardio

  12. Space-Time Analysis of the Air Quality Model Evaluation International Initiative (AQMEII) Phase 1 Air Quality Simulations

    EPA Science Inventory

    This study presents an evaluation of summertime daily maximum ozone concentrations over North America (NA) and Europe (EU) using the database generated during Phase 1 of the Air Quality Model Evaluation International Initiative (AQMEII). The analysis focuses on identifying tempor...

  13. Development of fuzzy system and nonlinear regression models for ozone and PM2.5 air quality forecasts

    NASA Astrophysics Data System (ADS)

    Lin, Yiqiu

    2007-12-01

    Ozone forecast models using nonlinear regression (NLR) have been successfully applied to daily ozone forecast for seven metro areas in Kentucky, including Ashland, Bowling Green, Covington, Lexington, Louisville, Owensboro, and Paducah. In this study, the updated 2005 NLR ozone forecast models for these metro areas were evaluated on both the calibration data sets and independent data sets. These NLR ozone forecast models explained at least 72% of the variance of the daily peak ozone. Using the models to predict the ozone concentrations during the 2005 ozone season, the metro area mean absolute errors (MAEs) of the model hindcasts ranged from 5.90 ppb to 7.20 ppb. For the model raw forecasts, the metro area MAEs ranged from 7.90 ppb to 9.80 ppb. Based on previously developed NLR ozone forecast models for those areas, Takagi-Sugeno fuzzy system models were developed for the seven metro areas. The fuzzy "c-means" clustering technique coupled with an optimal output predefuzzification approach (least square method) was used to train the Takagi-Sugeno fuzzy system. Two types of fuzzy models, basic fuzzy and NLR-fuzzy system models, were developed. The basic fuzzy and NLR-fuzzy models exhibited essentially equivalent performance to the existing NLR models on 2004 ozone season hindcasts and forecasts. Both types of fuzzy models had, on average, slightly lower metro area averaged MAEs than the NLR models. Among the seven Kentucky metro areas Ashland, Covington, and Louisville are currently designated nonattainment areas for both ground level O 3 and PM2.5. In this study, summer PM2.5 forecast models were developed for providing daily average PM2.5 forecasts for the seven metro areas. The performance of the PM2.5 forecast models was generally not as good as that of the ozone forecast models. For the summer 2004 model hindcasts, the metro-area average MAE was 5.33 mug/m 3. Exploratory research was conducted to find the relationship between the winter PM2.5 concentrations and

  14. INDOOR AIR QUALITY MODEL VERSION 1.0 DOCUMENTATION

    EPA Science Inventory

    The report presents a multiroom model for estimating the impact of various sources on indoor air quality (IAQ). The model is written for use on IBM-PC and compatible microcomputers. It is easy to use with a menu-driven user interface. Data are entered using a fill-in-a-form inter...

  15. A PHOTOCHEMICAL BOX MODEL FOR URBAN AIR QUALITY SIMULATION

    EPA Science Inventory

    A simple 'box-approach' to air quality simulation modeling has been developed in conjunction with a newly formulated photochemical kinetic mechanism to produce an easily applied Photochemical Box Model (PBM). This approach represents an urban area as a single cell 20 km in both l...

  16. Scale Issues in Air Quality Modeling

    EPA Science Inventory

    This presentation reviews past model evaluation studies investigating the impact of horizontal grid spacing on model performance. It also presents several examples of using a spectral decomposition technique to separate the forcings from processes operating on different time scal...

  17. Evaluation of the Community Multiscale Air Quality (CMAQ) modeling system against size-resolved measurements of inorganic particle composition across sites in North America

    EPA Science Inventory

    This work evaluates particle size-composition distributions simulated by the Community Multiscale Air Quality (CMAQ) model using Micro-Orifice Uniform Deposit Impactor (MOUDI) measurements at 18 sites across North America. Size-resolved measurements of particulate SO4<...

  18. A particle-grid air quality modeling approach

    SciTech Connect

    Chock, D.P.; Winkler, S.L.

    1996-12-31

    A particle-grid air quality modeling approach that can incorporate chemistry is proposed as an alternative to the conventional PDF-grid air quality modeling. The particle trajectory model can accurately describe advection of air pollutants without introducing artificial diffusion, generating negative concentrations or distorting the concentration distributions. It also accurately describes the dispersion of emissions from point sources and is capable of retaining subgrid-scale information. Inhomogeneous turbulence necessitates use of a small timestep, say, 10 s to describe vertical dispersion of particles in convective conditions. A timestep as large as 200 s can be used to simulate horizontal dispersion. A time-splitting scheme can be used to couple the horizontal and vertical dispersion in a 3D simulation, and about 2000-3000 particles per cell of size 5 km x 5 km X 50 m is sufficient to yield a highly accurate simulation of 3D dispersion. Use of an hourly-averaged concentration further reduces the demand of particle per cell to 500. The particle-grid method is applied to a system of ten reacting chemical species in a two-dimensional rotating flow field with and without diffusion. A chemistry grid within which reactions are assumed to take place can be decoupled from the grid describing the flow field. Two types of chemistry grids are used to describe the chemical reactions: a fixed coarse grid and a moving (the advection case) or stationary (the advection plus diffusion case) fine grid. Two particle-number densities are also used: 256 and 576 particles per fixed coarse grid cell. The species mass redistributed back to the particle after each reaction step is assumed to be proportional to the species mass in the particle before the reaction. The simulation results are very accurate, especially in the advection-chemistry case. Accuracy improves with the use of a fine grid.

  19. Atmospheric Modelling for Air Quality Study over the complex Himalayas

    NASA Astrophysics Data System (ADS)

    Surapipith, Vanisa; Panday, Arnico; Mukherji, Aditi; Banmali Pradhan, Bidya; Blumer, Sandro

    2014-05-01

    An Atmospheric Modelling System has been set up at International Centre for Integrated Mountain Development (ICIMOD) for the assessment of Air Quality across the Himalaya mountain ranges. The Weather Research and Forecasting (WRF) model version 3.5 has been implemented over the regional domain, stretching across 4995 x 4455 km2 centred at Ichhyakamana , the ICIMOD newly setting-up mountain-peak station (1860 m) in central Nepal, and covering terrains from sea-level to the Everest (8848 m). Simulation is carried out for the winter time period, i.e. December 2012 to February 2013, when there was an intensive field campaign SusKat, where at least 7 super stations were collecting meteorology and chemical parameters on various sites. The very complex terrain requires a high horizontal resolution (1 × 1 km2), which is achieved by nesting the domain of interest, e.g. Kathmandu Valley, into 3 coarser ones (27, 9, 3 km resolution). Model validation is performed against the field data as well as satellite data, and the challenge of capturing the necessary atmospheric processes is discussed, before moving forward with the fully coupled chemistry module (WRF-Chem), having local and regional emission databases as input. The effort aims at finding a better understanding of the atmospheric processes and air quality impact on the mountain population, as well as the impact of the long-range transport, particularly of Black Carbon aerosol deposition, to the radiative budget over the Himalayan glaciers. The higher rate of snowcap melting, and shrinkage of permafrost as noticed by glaciologists is a concern. Better prediction will supply crucial information to form the proper mitigation and adaptation strategies for saving people lives across the Himalayas in the changing climate.

  20. CFD Modeling For Urban Air Quality Studies

    SciTech Connect

    Lee, R L; Lucas, L J; Humphreys, T D; Chan, S T

    2003-10-27

    The computational fluid dynamics (CFD) approach has been increasingly applied to many atmospheric applications, including flow over buildings and complex terrain, and dispersion of hazardous releases. However there has been much less activity on the coupling of CFD with atmospheric chemistry. Most of the atmospheric chemistry applications have been focused on the modeling of chemistry on larger spatial scales, such as global or urban airshed scale. However, the increased attentions to terrorism threats have stimulated the need of much more detailed simulations involving chemical releases within urban areas. This motivated us to develop a new CFD/coupled-chemistry capability as part of our modeling effort.

  1. QUANTIFYING SUBGRID POLLUTANT VARIABILITY IN EULERIAN AIR QUALITY MODELS

    EPA Science Inventory

    In order to properly assess human risk due to exposure to hazardous air pollutants or air toxics, detailed information is needed on the location and magnitude of ambient air toxic concentrations. Regional scale Eulerian air quality models are typically limited to relatively coar...

  2. Scale Issues in Air Quality Modeling Policy Support

    EPA Science Inventory

    This study examines the issues relating to the use of regional photochemical air quality models for evaluating their performance in reproducing the spatio-temporal features embedded in the observations and for designing emission control strategies needed to achieve compliance wit...

  3. QUEST FOR AN ADVANCED REGIONAL AIR QUALITY MODEL

    EPA Science Inventory

    Organizations interested in advancing the science and technology of regional air quality modeling on the "grand challenge" scale have joined to form CAMRAQ. hey plan to leverage their research finds by collaborating on the development and evaluation of CMSs so ambitious in scope ...

  4. MODELED MESOSCALE METEOROLOGICAL FIELDS WITH FOUR-DIMENSIONAL DATA ASSIMILATION IN REGIONAL SCALE AIR QUALITY MODELS

    EPA Science Inventory

    This paper addresses the need to increase the temporal and spatial resolution of meteorological data currently used in air quality simulation models, AQSMs. ransport and diffusion parameters including mixing heights and stability used in regulatory air quality dispersion models a...

  5. Evaluating the CALIOPE air quality modelling system: dynamics and chemistry over Europe and Iberian Peninsula for 2004 at high horizontal resolution

    NASA Astrophysics Data System (ADS)

    Piot, M.; Pay, M. T.; Jorba, O.; Baldasano, J. M.; Jiménez-Guerrero, P.; López, E.; Pérez, C.; Gassó, S.

    2009-04-01

    Often in Europe, population exposure to air pollution exceeds standards set by the EU and the World Health Organization (WHO). Urban/suburban areas are predominantly impacted upon, although exceedances of particulate matter (PM10 and PM2.5) and Ozone (O3) also take place in rural areas. In the frame of the CALIOPE project (Baldasano et al., 2008a), a high-resolution air quality forecasting system, WRF-ARW/HERMES/CMAQ/DREAM, has been developed and applied to the European domain (12km x 12km, 1hr) as well as to the Iberian Peninsula domain (4km x 4km, 1hr) to provide air quality forecasts for Spain (http://www.bsc.es/caliope/). The simulation of such high-resolution model system has been made possible by its implementation on the MareNostrum supercomputer. To reassure potential users and reduce uncertainties, the model system must be evaluated to assess its performances in terms of air quality levels and dynamics reproducibility. The present contribution describes a thorough quantitative evaluation study performed for a reference year (2004). The CALIOPE modelling system is configured with 38 vertical layers reaching up to 50 hPa for the meteorological core. Atmospheric initial and boundary conditions are obtained from the NCEP final analysis data. The vertical resolution of the CMAQ chemistry-transport model for gas-phase and aerosols has been increased from 8 to 15 layers in order to simulate vertical exchanges more accurately. Gas phase boundary conditions are provided by the LMDz-INCA2 global climate-chemistry model (see Hauglustaine et al., 2004). The DREAM model simulates long-range transport of mineral dust over the domains under study. For the European simulation, emissions are disaggregated from the EMEP expert emission inventory for 2004 to the utilized resolution using the criteria implemented in the HERMES emission model (Baldasano et al., 2008b). The HERMES model system, using a bottom-up approach, was adopted to estimate emissions for the Iberian

  6. Guideline on air-quality models (revised). Supplement A

    SciTech Connect

    Not Available

    1987-07-01

    This guideline recommends air quality modeling techniques that may be applied to air-pollution-control strategy evaluations and new source reviews, including prevention of significant deterioration. It is intended for use by EPA Regional Offices in judging the adequacy of modeling analyses performed by EPA, by State and local agencies, and by industry and its consultants. It also identifies modeling techniques and data bases that EPA considers acceptable. The guideline makes specific recommendations concerning air-quality models, data bases, and general requirements for concentration estimates. This is Supplement A to the guideline. It contains: (1) addition of a specific version of the Rough Terrain Diffusion Model (RTDM) as a screening model; (2) modification of the downwash algorithm in the Industrial Source Complex (ISC) model; (3) addition of the Offshore and Coastal Dispersion (OCD) model to Appendix A; and, (4) addition of the AVACTA II model to Appendix B.

  7. Joint space-time geostatistical model for air quality surveillance

    NASA Astrophysics Data System (ADS)

    Russo, A.; Soares, A.; Pereira, M. J.

    2009-04-01

    Air pollution and peoples' generalized concern about air quality are, nowadays, considered to be a global problem. Although the introduction of rigid air pollution regulations has reduced pollution from industry and power stations, the growing number of cars on the road poses a new pollution problem. Considering the characteristics of the atmospheric circulation and also the residence times of certain pollutants in the atmosphere, a generalized and growing interest on air quality issues led to research intensification and publication of several articles with quite different levels of scientific depth. As most natural phenomena, air quality can be seen as a space-time process, where space-time relationships have usually quite different characteristics and levels of uncertainty. As a result, the simultaneous integration of space and time is not an easy task to perform. This problem is overcome by a variety of methodologies. The use of stochastic models and neural networks to characterize space-time dispersion of air quality is becoming a common practice. The main objective of this work is to produce an air quality model which allows forecasting critical concentration episodes of a certain pollutant by means of a hybrid approach, based on the combined use of neural network models and stochastic simulations. A stochastic simulation of the spatial component with a space-time trend model is proposed to characterize critical situations, taking into account data from the past and a space-time trend from the recent past. To identify near future critical episodes, predicted values from neural networks are used at each monitoring station. In this paper, we describe the design of a hybrid forecasting tool for ambient NO2 concentrations in Lisbon, Portugal.

  8. HVAC system performance and indoor air quality

    SciTech Connect

    Newman, J.L. )

    1991-01-01

    This paper reports that in the mid-seventies, the American Society of Heating, Refrigerating and Air Conditioning Engineers (ASHRAE) promulgated ASHRAE Standard 90-75 Energy Conservation in New Building Design, which called for revised minimum ventilation rates and the elimination of energy-wasting HVAC systems. Most building codes which cover energy conservation in the late seventies and eighties referred to this standard. This lowering of ventilation rates, coupled with the tighter building envelope (walls, windows, doors and roof) led to a reduction in outside air, both by engineering design and by minimizing infiltration through the structure. The minimum ventilation rates are based on the assumption that average concentrations of tobacco smoke exist in all enclosed spaces (30 percent of the population being smokers at two cigarettes per hour), rather than having separate rates for smoking and nonsmoking areas, as in the 1981 revision of the Standard. If tobacco smoke is ever declared a carcinogen, it will undoubtedly prompt a review of Standard 62-1989, as well as hasten totally smoke-free buildings.

  9. Merging Air Quality and Public Health Decision Support Systems

    NASA Astrophysics Data System (ADS)

    Hudspeth, W. B.; Bales, C. L.

    2003-12-01

    The New Mexico Air Quality Mapper (NMAQM) is a Web-based, open source GIS prototype application that Earth Data Analysis Center is developing under a NASA Cooperative Agreement. NMAQM enhances and extends existing data and imagery delivery systems with an existing Public Health system called the Rapid Syndrome Validation Project (RSVP). RSVP is a decision support system operating in several medical and public health arenas. It is evolving to ingest remote sensing data as input to provide early warning of human health threats, especially those related to anthropogenic atmospheric pollutants and airborne pathogens. The NMAQM project applies measurements of these atmospheric pollutants, derived from both remotely sensed data as well as from in-situ air quality networks, to both forecasting and retrospective analyses that influence human respiratory health. NMAQM provides a user-friendly interface for visualizing and interpreting environmentally-linked epidemiological phenomena. The results, and the systems made to provide the information, will be applicable not only to decision-makers in the public health realm, but also to air quality organizations, demographers, community planners, and other professionals in information technology, and social and engineering sciences. As an accessible and interactive mapping and analysis application, it allows environment and health personnel to study historic data for hypothesis generation and trend analysis, and then, potentially, to predict air quality conditions from daily data acquisitions. Additional spin off benefits to such users include the identification of gaps in the distribution of in-situ monitoring stations, the dissemination of air quality data to the public, and the discrimination of local vs. more regional sources of air pollutants that may bear on decisions relating to public health and public policy.

  10. Uncertainty, ensembles and air quality dispersion modeling: applications and challenges

    NASA Astrophysics Data System (ADS)

    Dabberdt, Walter F.; Miller, Erik

    The past two decades have seen significant advances in mesoscale meteorological modeling research and applications, such as the development of sophisticated and now widely used advanced mesoscale prognostic models, large eddy simulation models, four-dimensional data assimilation, adjoint models, adaptive and targeted observational strategies, and ensemble and probabilistic forecasts. Some of these advances are now being applied to urban air quality modeling and applications. Looking forward, it is anticipated that the high-priority air quality issues for the near-to-intermediate future will likely include: (1) routine operational forecasting of adverse air quality episodes; (2) real-time high-level support to emergency response activities; and (3) quantification of model uncertainty. Special attention is focused here on the quantification of model uncertainty through the use of ensemble simulations. Application to emergency-response dispersion modeling is illustrated using an actual event that involved the accidental release of the toxic chemical oleum. Both surface footprints of mass concentration and the associated probability distributions at individual receptors are seen to provide valuable quantitative indicators of the range of expected concentrations and their associated uncertainty.

  11. Impact of increased vehicle emissions on the ozone concentrations around beach areas in summer using air quality modeling system

    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).

  12. Modeling Regional Air Quality Impacts from Indonesian Biomass Burning

    NASA Astrophysics Data System (ADS)

    Jumbam, L.; Raffuse, S. M.; Wiedinmyer, C.; Larkin, N.

    2012-12-01

    Smoke from thousands of forest-clearing burns in Indonesia cause widespread air quality impacts in cities across southeastern Asia. These fires, which can produce significant smoke due to peat burning, are readily detected by polar orbiting satellites. Widespread smoke can be seen in satellite imagery, and high concentrations of particulate matter are detected by ground based sensors. Here we present results of a pilot modeling study focusing on the September 2011 Indonesian smoke episode. In the study, fire location information was collected from the National Aeronautics and Space Administration's (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS). The BlueSky modeling framework, which links information about fire locations with smoke emissions and meteorological models, was used to pass the fire location information from MODIS through the Fire INventories from NCAR (FINN) methodology to estimate emissions of aerosol and gaseous pollutants from the fires. These emissions were further directed by BlueSky through the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, which predicted the dispersion and transport of PM2.5 from the fires. The resulting regional PM2.5 concentration maps from BlueSky were compared with satellite imagery and urban ground stations, where available. This work demonstrates the extension of a system developed for producing daily smoke predictions in the United States outside of North America for the first time. We discuss the implications of regional smoke impacts and possibilities for predictive smoke modeling to protect public health in southeastern Asia.

  13. New Methods for Air Quality Model Evaluation with Satellite Data

    NASA Astrophysics Data System (ADS)

    Holloway, T.; Harkey, M.

    2015-12-01

    Despite major advances in the ability of satellites to detect gases and aerosols in the atmosphere, there remains significant, untapped potential to apply space-based data to air quality regulatory applications. Here, we showcase research findings geared toward increasing the relevance of satellite data to support operational air quality management, focused on model evaluation. Particular emphasis is given to nitrogen dioxide (NO2) and formaldehyde (HCHO) from the Ozone Monitoring Instrument aboard the NASA Aura satellite, and evaluation of simulations from the EPA Community Multiscale Air Quality (CMAQ) model. This work is part of the NASA Air Quality Applied Sciences Team (AQAST), and is motivated by ongoing dialog with state and federal air quality management agencies. We present the response of satellite-derived NO2 to meteorological conditions, satellite-derived HCHO:NO2 ratios as an indicator of ozone production regime, and the ability of models to capture these sensitivities over the continental U.S. In the case of NO2-weather sensitivities, we find boundary layer height, wind speed, temperature, and relative humidity to be the most important variables in determining near-surface NO2 variability. CMAQ agreed with relationships observed in satellite data, as well as in ground-based data, over most regions. However, we find that the southwest U.S. is a problem area for CMAQ, where modeled NO2 responses to insolation, boundary layer height, and other variables are at odds with the observations. Our analyses utilize a software developed by our team, the Wisconsin Horizontal Interpolation Program for Satellites (WHIPS): a free, open-source program designed to make satellite-derived air quality data more usable. WHIPS interpolates level 2 satellite retrievals onto a user-defined fixed grid, in effect creating custom-gridded level 3 satellite product. Currently, WHIPS can process the following data products: OMI NO2 (NASA retrieval); OMI NO2 (KNMI retrieval); OMI

  14. Modeling ozone and aerosol formation and transport in the pacific northwest with the community Multi-Scale Air Quality (CMAQ) modeling system.

    PubMed

    O'Neill, Susan M; Lamb, Brian K; Chen, Jack; Claiborn, Candis; Finn, Dennis; Otterson, Sally; Figueroa, Cristiana; Bowman, Clint; Boyer, Mike; Wilson, Rob; Arnold, Jeff; Aalbers, Steven; Stocum, Jeffrey; Swab, Christopher; Stoll, Matt; Dubois, Mike; Anderson, Mary

    2006-02-15

    The Community Multi-Scale Air Quality (CMAQ) modeling system was used to investigate ozone and aerosol concentrations in the Pacific Northwest (PNW) during hot summertime conditions during July 1-15, 1996. Two emission inventories (El) were developed: emissions for the first El were based upon the National Emission Trend 1996 (NET96) database and the BEIS2 biogenic emission model, and emissions for the second El were developed through a "bottom up" approach that included biogenic emissions obtained from the GLOBEIS model. The two simulations showed that elevated PM2.5 concentrations occurred near and downwind of the Interstate-5 corridor along the foothills of the Cascade Mountains and in forested areas of central Idaho. The relative contributions of organic and inorganic aerosols varied by region, but generally organic aerosols constituted the largest fraction of PM2.5. In wilderness areas near the 1-5 corridor, organic carbon from anthropogenic sources contributed approximately 50% of the total organic carbon with the remainder from biogenic precursors, while in wilderness areas in Idaho, biogenic organic carbon accounted for 80% of the total organic aerosol. Regional analysis of the secondary organic aerosol formation in the Columbia River Gorge, Central Idaho, and the Olympics/Puget Sound showed that the production rate of secondary organic carbon depends on local terpene concentrations and the local oxidizing capacity of the atmosphere, which was strongly influenced by anthropogenic emissions. Comparison with observations from 12 IMPROVE sites and 21 ozone monitoring sites showed that results from the two El simulations generally bracketed the average observed PM parameters and that errors calculated for the model results were within acceptable bounds. Analysis across all statistical parameters indicated that the NW-AIRQUEST El solution performed better at predicting PM2.5, PM1, and beta(ext) even though organic carbon PM was over-predicted, and the NET96 El

  15. Design of a complex terrain meteorological monitoring program for real-time air quality modeling analysis

    SciTech Connect

    Militana, L.M.; Karpovich, R.; Cimorelli, A.; Scire, J.S.

    1998-12-31

    A multi-station meteorological monitoring program has been designed and developed for a complex terrain air quality modeling study. The purpose of the program is to collect representative on site data as input to complex terrain air quality models and to predict in real-time the potential air quality impact of a rotary kiln incinerator The program is a state-of the science design using the best science air quality dispersion models (CALMET/CALPUFF) and meteorological monitoring equipment (RASS/SODAR Systems monostatic and phased array and multiple towers). The real-time meteorological monitoring program consisted of two monitoring stations using meteorological towers and Doppler SODAR and phased array RASS systems to determine the temperature and wind profile of the atmospheric boundary layer. The primary station were located adjacent to the site and consisted of a 150 ft meteorological tower and RASS/SODAR system. The secondary station was located approximately 1,600 meters northeast of the site and consisted of a 10 meter tower and a SODAR system. These monitoring stations provided 15-minute values of wind speed, wind direction, ambient temperature, and thermal and mechanical turbulence measurements for use in a complex terrain air quality modeling study and a real-time modeling system.

  16. Examination of the Community Multiscale Air Quality (CMAQ) Model Performance over the North American and European Domains

    EPA Science Inventory

    The CMAQ modeling system has been used to simulate the air quality for North America and Europe for the entire year of 2006 as part of the Air Quality Model Evaluation International Initiative (AQMEII) and the operational model performance of O3, fine particulate matte...

  17. A fuzzy fractional chance-constrained programming model for air quality management under uncertainty

    NASA Astrophysics Data System (ADS)

    Liu, Feng; Wen, Zhi; Xu, Ye

    2016-01-01

    A fuzzy fractional chance-constrained programming model (FFCCPM) was developed for dealing with air quality management under uncertainty. FFCCPM integrates a fractional programming model and a double-sided fuzzy chance-constrained programming model. It considers the ratio between total treated pollutant amounts and system cost in the objective function; the constraints with fuzzy variables can be satisfied under some predetermined confidence levels and reliability scenarios. The air quality management system in Fengrun district, Tangshan City, China, was used to demonstrate the applicability of the proposed method. The obtained results indicated that the proposed model was suitable in describing and providing an overview of a studied management system for decision makers, generating various cost-effective air pollution-abatement alternatives. The strategy with a balance between system economy and reliability was recommended for decision makers. The successful application of FFCCPM in Fengrun district provides a good example of real-world regional air quality management.

  18. APPLICATION OF AUTOMATIC DIFFERENTIATION FOR STUDYING THE SENSITIVITY OF NUMERICAL ADVECTION SCHEMES IN AIR QUALITY MODELS

    EPA Science Inventory

    In any simulation model, knowing the sensitivity of the system to the model parameters is of utmost importance. s part of an effort to build a multiscale air quality modeling system for a high performance computing and communication (HPCC) environment, we are exploring an automat...

  19. Local-scale variability in regional air quality modelling: Implications on temporal distribution of emissions

    NASA Astrophysics Data System (ADS)

    Bergemann, Christoph; Meyer-Arnek, Julian

    2010-05-01

    In the field of air quality modeling, the comparison of model results with ground-based measurements is essential for validation purposes. The usefulness of these measurements for regional air quality modeling is however limited by the extremely local nature of station measurements. This is especially true for short-lived species like NO2, which is of high importance for public health. Nevertheless station observations are the only continuously available source of data on ground level air quality besides model results. Uncertainties in air quality models mainly arise from the lack of precise knowledge of the spatial and temporal distribution of pollutants. Most emission inventories provide aggregated values for long periods of time and yield no information on the temporal (diurnal) distribution of emissions. By applying ground-based measurements, our study yields optimized diurnal variations of anthropogenic emissions for different urban regions of Germany. In the course of the study the variability of air pollution on the urban scale (the model's subgrid scale) is also addressed. The study applies the newly established POLYPHEMUS/DLR model at a moderate resolution. In the framework of the GMES project "PROMOTE", this model system operationally analyzes and forecasts air quality in Bavaria, Germany. The model employs the latest version of the EMEP emission register in combination with high-resolution emission data provided by Bavarian authorities.

  20. Future prediction of surface ozone over east Asia using Models-3 Community Multiscale Air Quality Modeling System and Regional Emission Inventory in Asia

    NASA Astrophysics Data System (ADS)

    Yamaji, Kazuyo; Ohara, Toshimasa; Uno, Itsushi; Kurokawa, Jun-Ichi; Pochanart, Pakpong; Akimoto, Hajime

    2008-04-01

    Present and future tropospheric ozone (O3) concentrations over east Asia have been simulated by the Models-3 Community Multiscale Air Quality Modeling System (CMAQ) coupled with the Regional Emission Inventory in Asia (REAS) to predict surface O3 variations caused by future anthropogenic emissions changes. For future prediction, REAS provides three emission scenarios for China (the reference (REF), the policy succeed case (PSC), and the policy failure case (PFC) scenarios) and one emission scenario (the REF scenario) for the other countries. Simulated O3 concentration in summer was relatively high (70-80 ppbv in June and 65-75 ppbv in August) over the North China Plain in 2000. The projected REF emissions for 2020 (2020REF) enhance the monthly averaged O3 to 75-90 ppbv in June and 75-85 ppbv in August. The projected PSC emissions for 2020 (2020PFC), including a slight NOx reduction of -0.2 Tg (-2%) and a large NMVOC increase of 14.3 Tg (97%) for total Chinese emissions during 2000-2020, cause the monthly and annually averaged O3 concentrations to decrease by less than 2 ppbv in northeastern and central China. Over the North China Plain, the projected PFC emissions for 2020 (2020PFC) cause significant increases, more than 20 ppbv in the monthly averaged O3, and the O3 will be 85-105 ppbv in June and 80-95 ppbv in August for 2020. The 2020PFC also affect O3 increases in early summer in South Korea (14-18 ppbv increase for monthly average) and Japan (2-14 ppbv increase for monthly average) during 2000-2020 despite the slight NOx increase of 0.4 Tg (25%) in South Korea and the slight NOx reduction of -0.2 Tg (-10%) in Japan during 2000-2020. The pollutant in these regions seems to be transport from upwind source regions. These experiments show that over central eastern China at midday in June, the O3 concentration is largely affected by NOx emission increases but is insensitive to NMVOC emission increases.

  1. Evaluation of the meteorological forcing used for the Air Quality Model Evaluation International Initiative (AQMEII) air quality simulations

    NASA Astrophysics Data System (ADS)

    Vautard, Robert; Moran, Michael D.; Solazzo, Efisio; Gilliam, Robert C.; Matthias, Volker; Bianconi, Roberto; Chemel, Charles; Ferreira, Joana; Geyer, Beate; Hansen, Ayoe B.; Jericevic, Amela; Prank, Marje; Segers, Arjo; Silver, Jeremy D.; Werhahn, Johannes; Wolke, Ralf; Rao, S. T.; Galmarini, Stefano

    2012-06-01

    Accurate regional air pollution simulation relies strongly on the accuracy of the mesoscale meteorological simulation used to drive the air quality model. The framework of the Air Quality Model Evaluation International Initiative (AQMEII), which involved a large international community of modeling groups in Europe and North America, offered a unique opportunity to evaluate the skill of mesoscale meteorological models for two continents for the same period. More than 20 groups worldwide participated in AQMEII, using several meteorological and chemical transport models with different configurations. The evaluation has been performed over a full year (2006) for both continents. The focus for this particular evaluation was meteorological parameters relevant to air quality processes such as transport and mixing, chemistry, and surface fluxes. The unprecedented scale of the exercise (one year, two continents) allowed us to examine the general characteristics of meteorological models' skill and uncertainty. In particular, we found that there was a large variability between models or even model versions in predicting key parameters such as surface shortwave radiation. We also found several systematic model biases such as wind speed overestimations, particularly during stable conditions. We conclude that major challenges still remain in the simulation of meteorology, such as nighttime meteorology and cloud/radiation processes, for air quality simulation.

  2. IMPLEMENTATION OF AN URBAN CANOPY PARAMETERIZATION IN MM5 FOR MESO-GAMMA-SCALE AIR QUALITY MODELING APPLICATIONS

    EPA Science Inventory

    The U.S. Environmental Protection Agency (U.S. EPA) is extending its Models-3/Community Multiscale Air Quality (CMAQ) Modeling System to provide detailed gridded air quality concentration fields and sub-grid variability characterization at neighborhood scales and in urban areas...

  3. A diagnostic model for studying daytime urban air quality trends

    NASA Technical Reports Server (NTRS)

    Brewer, D. A.; Remsberg, E. E.; Woodbury, G. E.

    1981-01-01

    A single cell Eulerian photochemical air quality simulation model was developed and validated for selected days of the 1976 St. Louis Regional Air Pollution Study (RAPS) data sets; parameterizations of variables in the model and validation studies using the model are discussed. Good agreement was obtained between measured and modeled concentrations of NO, CO, and NO2 for all days simulated. The maximum concentration of O3 was also predicted well. Predicted species concentrations were relatively insensitive to small variations in CO and NOx emissions and to the concentrations of species which are entrained as the mixed layer rises.

  4. A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS

    EPA Science Inventory

    This paper discusses a framework for fine-scale CFD modeling that may be developed to complement the present Community Multi-scale Air Quality (CMAQ) modeling system which itself is a computational fluid dynamics model. A goal of this presentation is to stimulate discussions on w...

  5. Dynamic evaluation of air quality models over European regions

    NASA Astrophysics Data System (ADS)

    Thunis, P.; Pisoni, E.; Degraeuwe, B.; Kranenburg, R.; Schaap, M.; Clappier, A.

    2015-06-01

    Chemistry-transport models are increasingly used in Europe for estimating air quality or forecasting changes in pollution levels. But with this increased use of modeling arises the need of harmonizing the methodologies to determine the quality of air quality model applications. This is complex for planning applications, i.e. when models are used to assess the impact of realistic or virtual emission scenarios. In this work, the methodology based on the calculation of potencies proposed by Thunis and Clappier (2014) to analyze the model responses to emission reductions is applied on three different domains in Europe (Po valley, Southern Poland and Flanders). This methodology is further elaborated to facilitate the inter-comparison process and bring in a single diagram the possibility of differentiating long-term from short-term effects. This methodology is designed for model users to interpret their model results but also for policy-makers to help them defining intervention priorities. The methodology is applied to both daily PM10 and 8 h daily maximum ozone.

  6. AIR QUALITY MODELING AT NEIGHBORHOOD SCALES TO IMPROVE HUMAN EXPOSURE ASSESSMENT

    EPA Science Inventory

    Air quality modeling is an integral component of risk assessment and of subsequent development of effective and efficient management of air quality. Urban areas introduce of fresh sources of pollutants into regional background producing significant spatial variability of the co...

  7. AN OPERATIONAL EVALUATION OF THE ETA-CMAQ AIR QUALITY FORECAST MODEL

    EPA Science Inventory

    The National Oceanic and Atmospheric Administration (NOAA), in collaboration with the Environmental Protection Agency (EPA), are developing an Air Quality Forecasting Program that will eventually result in an operational Nationwide Air Quality Forecasting System. The initial pha...

  8. A PILOT STUDY FOR NEAR REAL-TIME AEROSOL MODELING AND AIR QUALITY CHARACTERIZATION

    EPA Science Inventory

    The primary objectives of this study are to implement, operate, and evaluate an automated, numerical, model-based air quality forecast system to provide daily predictions of O3 and PM2.5 and to assess the integrated use of modeled and observed concentrations to better ...

  9. A stochastic simulation model to predict future air quality in protected areas

    NASA Astrophysics Data System (ADS)

    Stavros, E.; McKenzie, D.; Larkin, N.; Strand, T.; Lamb, B. K.

    2010-12-01

    It is widely accepted in both scientific and political communities such as the Intergovernmental Panel on Climate Change (IPCC) and the Environmental Protection Agency (EPA), that climate is changing. Previous studies have shown that expected changes in climate will increase the severity of wild fire. It is necessary to assess the impact of global climate change on wildfire and consequent effects on air quality in order to meet existing air quality regulations such as the Regional Haze Rule, which regulates visibility in Class 1 or “pristine areas”, and the National Ambient Air Quality Standards (NAAQS). The challenge in such an assessment lies in not only integrating disciplines (climatology, fire ecology, air chemistry), but also in bridging knowledge across temporal (hourly to decadal) and spatial scales (local to global). In response to this challenge, we are integrating a stochastic model to simulate fire events, the Fire Scenario Builder (FSB), and the BlueSky Modeling Framework, which has a strong record of successfully linking wildfire emissions to air quality. FSB integrates fuel information and meteorological data to estimate regional fire season summary statistics such as total area burned and number of fire starts. The Blue Sky Modeling Framework then simulates total fuel consumption and smoke emissions both in local air sheds and downwind. Emissions are then fed into the Community Multiscale Air Quality (CMAQ) model through Sparse Matrix Operator Kernel Emissions Modeling System (SMOKE). The goal of this research is threefold: 1) to compare emission results from the FSB-Blue Sky integration for current vs. future decades; 2) to assess model uncertainty, by comparing model output to observations, analyzing parameter sensitivity, and verifying the theoretical basis of FSB model structure; and, 3) prepare data files for analysis on air quality.

  10. Caenorhabditis elegans: a model to monitor bacterial air quality

    PubMed Central

    2011-01-01

    Background Low environmental air quality is a significant cause of mortality and morbidity and this question is now emerging as a main concern of governmental authorities. Airborne pollution results from the combination of chemicals, fine particles, and micro-organisms quantitatively or qualitatively dangerous for health or for the environment. Increasing regulations and limitations for outdoor air quality have been decreed in regards to chemicals and particles contrary to micro-organisms. Indeed, pertinent and reliable tests to evaluate this biohazard are scarce. In this work, our purpose was to evaluate the Caenorhaditis elegans killing test, a model considered as an equivalent to the mouse acute toxicity test in pharmaceutical industry, in order to monitor air bacterial quality. Findings The present study investigates the bacterial population in dust clouds generated during crop ship loading in harbor installations (Rouen harbor, Normandy, France). With a biocollector, airborne bacteria were impacted onto the surface of agar medium. After incubation, a replicate of the colonies on a fresh agar medium was done using a velvet. All the replicated colonies were pooled creating the "Total Air Sample". Meanwhile, all the colonies on the original plate were isolated. Among which, five representative bacterial strains were chosen. The virulence of these representatives was compared to that of the "Total Air Sample" using the Caenorhaditis elegans killing test. The survival kinetic of nematodes fed with the "Total Air Sample" is consistent with the kinetics obtained using the five different representatives strains. Conclusions Bacterial air quality can now be monitored in a one shot test using the Caenorhaditis elegans killing test. PMID:22099854

  11. Assessing The Policy Relevance of Regional Air Quality Models

    NASA Astrophysics Data System (ADS)

    Holloway, T.

    This work presents a framework for discussing the policy relevance of models, and regional air quality models in particular. We define four criteria: 1) The scientific status of the model; 2) Its ability to address primary environmental concerns; 3) The position of modeled environmental issues on the political agenda; and 4) The role of scientific input into the policy process. This framework is applied to current work simulating the transport of nitric acid in Asia with the ATMOS-N model, to past studies on air pollution transport in Europe with the EMEP model, and to future applications of the United States Environmental Protection Agency (US EPA) Models-3. The Lagrangian EMEP model provided critical input to the development of the 1994 Oslo and 1999 Gothenburg Protocols to the Convention on Long-Range Transbound- ary Air Pollution, as well as to the development of EU directives, via its role as a component of the RAINS integrated assessment model. Our work simulating reactive nitrogen in Asia follows the European example in part, with the choice of ATMOS-N, a regional Lagrangian model to calculate source-receptor relationships for the RAINS- Asia integrated assessment model. However, given differences between ATMOS-N and the EMEP model, as well as differences between the scientific and political cli- mates facing Europe ten years ago and Asia today, the role of these two models in the policy process is very different. We characterize the different aspects of policy relevance between these models using our framework, and consider how the current generation US EPA air quality model compares, in light of its Eulerian structure, dif- ferent objectives, and the policy context of the US.

  12. Model development of dust emission and heterogeneous chemistry within the Community Multiscale Air Quality modeling system and its application over East Asia

    NASA Astrophysics Data System (ADS)

    Dong, Xinyi; Fu, Joshua S.; Huang, Kan; Tong, Daniel; Zhuang, Guoshun

    2016-07-01

    The Community Multiscale Air Quality (CMAQ) model has been further developed in terms of simulating natural wind-blown dust in this study, with a series of modifications aimed at improving the model's capability to predict the emission, transport, and chemical reactions of dust. The default parameterization of initial threshold friction velocity constants are revised to correct the double counting of the impact of soil moisture in CMAQ by the reanalysis of field experiment data; source-dependent speciation profiles for dust emission are derived based on local measurements for the Gobi and Taklamakan deserts in East Asia; and dust heterogeneous chemistry is also implemented. The improved dust module in the CMAQ is applied over East Asia for March and April from 2006 to 2010. The model evaluation result shows that the simulation bias of PM10 and aerosol optical depth (AOD) is reduced, respectively, from -55.42 and -31.97 % by the original CMAQ to -16.05 and -22.1 % by the revised CMAQ. Comparison with observations at the nearby Gobi stations of Duolun and Yulin indicates that applying a source-dependent profile helps reduce simulation bias for trace metals. Implementing heterogeneous chemistry also results in better agreement with observations for sulfur dioxide (SO2), sulfate (SO42-), nitric acid (HNO3), nitrous oxides (NOx), and nitrate (NO3-). The investigation of a severe dust storm episode from 19 to 21 March 2010 suggests that the revised CMAQ is capable of capturing the spatial distribution and temporal variation of dust. The model evaluation also indicates potential uncertainty within the excessive soil moisture used by meteorological simulation. The mass contribution of fine-mode particles in dust emission may be underestimated by 50 %. The revised CMAQ model provides a useful tool for future studies to investigate the emission, transport, and impact of wind-blown dust over East Asia and elsewhere.

  13. Improving UK Air Quality Modelling Through Exploitation of Satellite Observations

    NASA Astrophysics Data System (ADS)

    Pope, R.; Chipperfield, M.; Savage, N.

    2012-12-01

    The Met Office's operational regional Air Quality Unified Model (AQUM) contains a description of atmospheric chemistry/aerosols which allows for the short-term forecast of chemical weather (e.g. high concentrations of ozone or nitrogen dioxide, which can trigger warnings of poor air quality). AQUM's performance has so far only been tested against a network of surface monitoring stations. Therefore, with recent improvements in the quality and quantity of satellite measurements, data products (e.g. tropospheric columns, vertical profiles) from several satellite instruments will be used to test the performance of the model. First comparisons between an AQUM simulation for the UK heatwave event of July 2006 and data from OMI, TES (both on AURA) and MODIS (on AQUA) have identified multiple model-satellite biases. The chemical/aerosol species investigated for this simulation include nitrogen dioxide (NO2), ozone (O3), formaldehyde (HCHO), carbon monoxide (CO) and aerosol optical depth (AOD) at 0.55 microns wavelength. NO2 spatial positive mean biases (AQUM-OMI July 2006 monthly mean tropospheric columns) over north- east England suggest model overestimation in the area's urban regions. Currently, sensitivity tests of the NOx emission datasets are investigating these biases and the model's represent of urban pollution. In the UK O3 monthly mean vertical profile comparisons (AQUM-TES), strong positive mean biases are detected in the upper troposphere/lower stratosphere. Since the AQUM does not use a stratospheric chemistry scheme, the satellite climatological vertical boundary conditions will be investigated (e.g. test the model with new boundary conditions using multiple satellite instruments or perturb existing climatologies). Comparisons of HCHO (AQUM-OMI monthly mean tropospheric columns) biases highlight strong negative biases over continental Europe and sporadic positive biases in the south-east lateral boundary conditions. Therefore, evaluation and development of

  14. INTERDEPENDENCIES OF MULTI-POLLUTANT CONTROL SIMULATIONS IN AN AIR QUALITY MODEL

    EPA Science Inventory

    In this work, we use the Community Multi-Scale Air Quality (CMAQ) modeling system to examine the effect of several control strategies on simultaneous concentrations of ozone, PM2.5, and three important HAPs: formaldehyde, acetaldehyde and benzene.

  15. DEVELOPMENT AND ANALYSIS OF AIR QUALITY MODELING SIMULATIONS FOR HAZARDOUS AIR POLLUTANTS

    EPA Science Inventory

    The concentrations of five hazardous air pollutants were simulated using the Community Multi Scale Air Quality (CMAQ) modeling system. Annual simulations were performed over the continental United States for the entire year of 2001 to support human exposure estimates. Results a...

  16. Model development of dust emission and heterogeneous chemistry within the Community Multiscale Air Quality modeling system and its application over East Asia

    NASA Astrophysics Data System (ADS)

    Dong, X.; Fu, J. S.; Huang, K.; Tong, D.

    2015-12-01

    The Community Multiscale Air Quality (CMAQ) model has been further developed in terms of simulating natural wind-blown dust in this study, with a series of modifications aimed at improving the model's capability to predict the emission, transport, and chemical reactions of dust aerosols. The default parameterization of threshold friction velocity constants in the CMAQ are revised to avoid double counting of the impact of soil moisture based on the re-analysis of field experiment data; source-dependent speciation profiles for dust emission are derived based on local measurements for the Gobi and Taklamakan deserts in East Asia; and dust heterogeneous chemistry is implemented to simulate the reactions involving dust aerosol. The improved dust module in the CMAQ was applied over East Asia for March and April from 2006 to 2010. Evaluation against observations has demonstrated that simulation bias of PM10 and aerosol optical depth (AOD) is reduced from -55.42 and -31.97 % in the original CMAQ to -16.05 and -22.1 % in the revised CMAQ, respectively. Comparison with observations at the nearby Gobi stations of Duolun and Yulin indicates that applying a source-dependent profile helps reduce simulation bias for trace metals. Implementing heterogeneous chemistry is also found to result in better agreement with observations for sulfur dioxide (SO2), sulfate (SO42-), nitric acid (HNO3), nitrous oxides (NOx), and nitrate (NO3-). Investigation of a severe dust storm episode from 19 to 21 March 2010 suggests that the revised CMAQ is capable of capturing the spatial distribution and temporal variations of dust aerosols. Model evaluation indicates potential uncertainties within the excessive soil moisture fraction used by meteorological simulation. The mass contribution of fine mode aerosol in dust emission may be underestimated by 50 %. The revised revised CMAQ provides a useful tool for future studies to investigate the emission, transport, and impact of wind-blown dust over East

  17. An application of a meteorological data assimilation system to an air quality simulation

    SciTech Connect

    Moon, D.; Pai, P.

    1999-07-01

    The need to calculate air pollutant exposure metrics for longer time periods, i.e., seasonal and annual, has generated a need to conduct long-term simulations using regional-scale Eulerian air quality models. Hourly-resolved meteorological and micro-meteorological fields for an entire year are required as input to the air quality models. In this paper, the authors describe the application of a meteorological data assimilation system to provide high-quality fields to drive a regional air quality model. The process of assimilation blends multiple data sources (large-scale gridded data, surface and upper air observations, satellite imagery, and radar data) into a unified atmospheric representation. The authors have used an assimilation system developed at the Center for the Analysis and Prediction of Storms at the University of Oklahoma. The modeling domain covers most of North America and 1995 was chosen as the simulation year. The data used in the assimilation include the NCAR/NCEP global reanalysis fields combined with North American surface and radiosonde data. The authors will describe modifications made to the assimilation system to enable estimation of a number of air-quality related quantities not normally calculated, such as Monin-Obhukov length and friction velocity. While the system supports a state-of-the-art three-dimensional cloud and hydrometeor field analysis based on background fields, surface observations, satellite, and radar; a simpler approach was developed in this study to estimate cloud fractional coverage based on the gridded relative humidity values.

  18. An operational system for the assimilation of satellite information on wild-land fires for the needs of air quality modelling and forecasting

    NASA Astrophysics Data System (ADS)

    Sofiev, M.; Vankevich, R.; Lanne, M.; Prank, M.; Petukhov, V.; Ermakova, T.; Kukkonen, J.

    2009-03-01

    This paper investigates a potential of two remotely sensed wild-land fire characteristics: 4-μm Brightness Temperature Anomaly (TA) and Fire Radiative Power (FRP) for the needs of operational chemical transport modelling and the short-term forecasting of the atmospheric composition and air quality. Two treatments of the TA and FRP data are presented and a methodology for evaluating the emission fluxes is described. The method does not contain a complicated analysis of vegetation state, fuel load, burning efficiency and related factors, which are comparatively uncertain but inevitably involved in approaches based on burnt-area scars or similar products. The core of the current methodology is based on the empirical emission factors that have been derived from the analysis of several fire episodes in Europe (28 April-5 May 2006, 15-25 August 2006, August 2008 etc.). These episodes were characterised by: (i) well-identified FRP and TA values, and (ii) available independent observations of aerosol concentrations and optical thickness for the regions where fire smoke was dominant in comparison with contributions of other pollution sources. The emission factors were determined separately for the forested and grassland areas; in case of mixed-type land use an intermediate scaling was assumed. Despite significant difference between the TA and FRP products, an accurate non-linear fitting between the approaches was found. The agreement was comparatively weak only for small fires where the accuracy of both products is low. The re-analysis and forecasting applications of the Fire Assimilation System (FAS) showed that both TA and FRP products are suitable for evaluation of the emission fluxes from the wild-land fires. The concentrations of aerosols predicted by the regional dispersion modelling system SILAM appear within a factor of 2-3 from observations. The main areas of improvement include further refining the emission factors over the globe, explicit determination and

  19. An operational system for the assimilation of the satellite information on wild-land fires for the needs of air quality modelling and forecasting

    NASA Astrophysics Data System (ADS)

    Sofiev, M.; Vankevich, R.; Lotjonen, M.; Prank, M.; Petukhov, V.; Ermakova, T.; Koskinen, J.; Kukkonen, J.

    2009-09-01

    This paper investigates a potential of two remotely sensed wild-land fire characteristics: 4-μm Brightness Temperature Anomaly (TA) and Fire Radiative Power (FRP) for the needs of operational chemical transport modelling and short-term forecasting of atmospheric composition and air quality. The treatments of the TA and FRP data are presented and a methodology for evaluating the emission fluxes of primary aerosols (PM2.5 and total PM) is described. The method does not include the complicated analysis of vegetation state, fuel load, burning efficiency and related factors, which are uncertain but inevitably involved in approaches based on burnt-area scars or similar products. The core of the current methodology is based on the empirical emission factors that are used to convert the observed temperature anomalies and fire radiative powers into emission fluxes. These factors have been derived from the analysis of several fire episodes in Europe (28.4-5.5.2006, 15.8-25.8.2006 and in August 2008). These episodes were characterised by: (i) well-identified FRP and TA values, and (ii) available ground-based observations of aerosol concentrations, and optical thickness for the regions where the contribution of the fire smoke to the concentrations of PM2.5 was dominant, in comparison with those of other pollution sources. The emission factors were determined separately for the forested and grassland areas; in case of mixed-type land use, an intermediate scaling was assumed. Despite significant differences between the TA and FRP methodologies, an accurate non-linear fitting was found between the predictions of these approaches. The agreement was comparatively weak only for small fires, for which the accuracy of both products is expected to be low. The applications of the Fire Assimilation System (FAS) in combination with the dispersion model SILAM showed that both the TA and FRP products are suitable for the evaluation of the emission fluxes from wild-land fires. The fire

  20. SYSTEM INSTALLATION AND OPERATION MANUAL FOR THE EPA THIRD-GENERATION AIR QUALITY MODELING SYSTEM (MODELS-3) VERSION 3.0

    EPA Science Inventory

    Models-3 is a flexible software system designed to simplify the development and use of environmental assessment and other decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of atmospheri...

  1. Development of a GIS-based decision support system for urban air quality management in the city of Istanbul

    NASA Astrophysics Data System (ADS)

    Elbir, Tolga; Mangir, Nizamettin; Kara, Melik; Simsir, Sedef; Eren, Tuba; Ozdemir, Seda

    2010-02-01

    A decision support system has been developed for urban air quality management in the metropolitan area of Istanbul. The system is based on CALMET/CALPUFF dispersion modeling system, digital maps, and related databases to estimate the emissions and spatial distribution of air pollutants with the help of a GIS software. The system estimates ambient air pollution levels at high temporal and spatial resolutions and enables mapping of emissions and air quality levels. Mapping and scenario results can be compared with air quality limits. Impact assessment of air pollution abatement measures can also be carried out.

  2. Determination of background concentrations for air quality models using spectral analysis and filtering of monitoring data

    NASA Astrophysics Data System (ADS)

    Tchepel, O.; Costa, A. M.; Martins, H.; Ferreira, J.; Monteiro, A.; Miranda, A. I.; Borrego, C.

    2010-01-01

    The use of background concentrations in air pollution modelling is usually a critical issue and a source of errors. The current work proposes an approach for the estimation of background concentrations using air quality measured data decomposed on baseline and short-term components. For this purpose, the spectral density was obtained for air quality monitoring data based on the Fourier series analysis. After, short-term fluctuations associated with the influence of local emissions and dispersion conditions were extracted from the original measurements using an iterative moving-average filter and taking into account the contribution of higher frequencies determined from the spectral analysis. The deterministic component obtained by the filtering is characterised by wider spatial and temporal representativeness than original monitoring data and is assumed to be appropriate for establishing the background values. This methodology was applied to define background concentrations of particulate matter (PM 10) used as input data for a local scale CFD model, and compared with an alternative approach using background concentrations provided by a mesoscale air quality modelling system. The study is focused on a selected domain within the Lisbon urban area (Portugal). The results present a better performance for the microscale model when initialised by decomposed time series and demonstrate the importance of the proposed methodology in reducing the uncertainty of the model predictions. The decomposition of air quality measurements and the removal of short-term fluctuations discussed in the work is a valuable technique to determine representative background concentrations.

  3. Extending the Applicability of the Community Multiscale Air Quality Model to Hemispheric Scales: Motivation, Challenges, and Progress

    EPA Science Inventory

    The adaptation of the Community Multiscale Air Quality (CMAQ) modeling system to simulate O3, particulate matter, and related precursor distributions over the northern hemisphere is presented. Hemispheric simulations with CMAQ and the Weather Research and Forecasting (...

  4. Validation of two air quality models for Indian mining conditions.

    PubMed

    Chaulya, S K; Ahmad, M; Singh, R S; Bandopadhyay, L K; Bondyopadhay, C; Mondal, G C

    2003-02-01

    All major mining activity particularly opencast mining contributes to the problem of suspended particulate matter (SPM) directly or indirectly. Therefore, assessment and prediction are required to prevent and minimize the deterioration of SPM due to various opencast mining operations. Determination of emission rate of SPM for these activities and validation of air quality models are the first and foremost concern. In view of the above, the study was taken up for determination of emission rate for SPM to calculate emission rate of various opencast mining activities and validation of commonly used two air quality models for Indian mining conditions. To achieve the objectives, eight coal and three iron ore mining sites were selected to generate site specific emission data by considering type of mining, method of working, geographical location, accessibility and above all resource availability. The study covers various mining activities and locations including drilling, overburden loading and unloading, coal/mineral loading and unloading, coal handling or screening plant, exposed overburden dump, stock yard, workshop, exposed pit surface, transport road and haul road. Validation of the study was carried out through Fugitive Dust Model (FDM) and Point, Area and Line sources model (PAL2) by assigning the measured emission rate for each mining activity, meteorological data and other details of the respective mine as an input to the models. Both the models were run separately for the same set of input data for each mine to get the predicted SPM concentration at three receptor locations for each mine. The receptor locations were selected such a way that at the same places the actual filed measurement were carried out for SPM concentration. Statistical analysis was carried out to assess the performance of the models based on a set measured and predicted SPM concentration data. The value of coefficient of correlation for PAL2 and FDM was calculated to be 0.990-0.994 and 0

  5. Air quality modelling using the Met Office Unified Model (AQUM OS24-26): model description and initial evaluation

    NASA Astrophysics Data System (ADS)

    Savage, N. H.; Agnew, P.; Davis, L. S.; Ordóñez, C.; Thorpe, R.; Johnson, C. E.; O'Connor, F. M.; Dalvi, M.

    2013-03-01

    The on-line air quality model AQUM (Air Quality in the Unified Model) is a limited-area forecast configuration of the Met Office Unified Model which uses the UKCA (UK Chemistry and Aerosols) sub-model. AQUM has been developed with two aims: as an operational system to deliver regional air quality forecasts and as a modelling system to conduct air quality studies to inform policy decisions on emissions controls. This paper presents a description of the model and the methods used to evaluate the performance of the forecast system against the automated UK surface network of air quality monitors. Results are presented of evaluation studies conducted for a year-long period of operational forecast trials and several past cases of poor air quality episodes. The results demonstrate that AQUM tends to over-predict ozone (~8 μg m-3 mean bias for the year-long forecast), but has a good level of responsiveness to elevated ozone episode conditions - a characteristic which is essential for forecasting poor air quality episodes. AQUM is shown to have a negative bias for PM10, while for PM2.5 the negative bias is much smaller in magnitude. An analysis of speciated PM2.5 data during an episode of elevated particulate matter (PM) suggests that the PM bias occurs mainly in the coarse component. The sensitivity of model predictions to lateral boundary conditions (LBCs) has been assessed by using LBCs from two different global reanalyses and by comparing the standard, single-nested configuration with a configuration having an intermediate European nest. We conclude that, even with a much larger regional domain, the LBCs remain an important source of model error for relatively long-lived pollutants such as ozone. To place the model performance in context we compare AQUM ozone forecasts with those of another forecasting system, the MACC (Monitoring Atmospheric Composition and Climate) ensemble, for a 5-month period. An analysis of the variation of model skill with forecast lead time is

  6. Urban scale air quality modelling using detailed traffic emissions estimates

    NASA Astrophysics Data System (ADS)

    Borrego, C.; Amorim, J. H.; Tchepel, O.; Dias, D.; Rafael, S.; Sá, E.; Pimentel, C.; Fontes, T.; Fernandes, P.; Pereira, S. R.; Bandeira, J. M.; Coelho, M. C.

    2016-04-01

    The atmospheric dispersion of NOx and PM10 was simulated with a second generation Gaussian model over a medium-size south-European city. Microscopic traffic models calibrated with GPS data were used to derive typical driving cycles for each road link, while instantaneous emissions were estimated applying a combined Vehicle Specific Power/Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (VSP/EMEP) methodology. Site-specific background concentrations were estimated using time series analysis and a low-pass filter applied to local observations. Air quality modelling results are compared against measurements at two locations for a 1 week period. 78% of the results are within a factor of two of the observations for 1-h average concentrations, increasing to 94% for daily averages. Correlation significantly improves when background is added, with an average of 0.89 for the 24 h record. The results highlight the potential of detailed traffic and instantaneous exhaust emissions estimates, together with filtered urban background, to provide accurate input data to Gaussian models applied at the urban scale.

  7. Fine-resolution model simulations of California air quality

    NASA Astrophysics Data System (ADS)

    Kim, S.; Trainer, M.; Angevine, W. M.; Lee, S.; Alvarez, R. J., II; Baidar, S.; Frost, G. J.; Hardesty, R.; Langford, A. O.; McKeen, S. A.; Oetjen, H.; Pollack, I. B.; Ryerson, T. B.; Senff, C. J.; Sinreich, R.; Volkamer, R.

    2010-12-01

    The purpose of our study is to improve the understanding of tropospheric ozone, its precursors, and their temporal changes over California. We simulate California air quality using the Weather Research and Forecasting - Chemistry (WRF-Chem) model with input from the US EPA's 2005 National Emission Inventory (NEI05) for July 2009 and spring-summer 2010. The model’s nested domain includes all of California at 4 x 4 km2 horizontal resolution. These simulation periods were chosen because of the availability of measurements from the pre-CalNex and CalNex field campaigns. The WRF-Chem simulations are evaluated with observations of ozone curtains by the TOPAZ lidar and in-situ measurements of numerous trace species collected on NOAA aircraft during these deployments. The WRF-Chem meteorological predictions are also compared with surface stations and wind profiler data. These model-measurement comparisons allow us to test the sensitivity of WRF-Chem to initial and boundary conditions, land-surface models, grid configurations, and emission inventory. Using the model evaluated with these observations, we investigate the importance of transport mechanisms and emission changes on tropospheric ozone levels above California.

  8. Coupled Monitoring and Modeling of Air Quality and Regional Climate during the 2008 Beijing Olympic Games

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Smith, J. A.; Michel, A. P.; Baeck, M. L.; Wang, Z.; Fast, J. D.; Gmachl, C.

    2009-12-01

    The 2008 Summer Olympic Games focused attention on the air quality of Beijing, China, especially through emission reduction measures designed to improve air quality for the 2008 Games. The Quantum Cascade Laser Open-Path System (QCLOPS) is a mid-infrared laser absorption spectrometer that uses a tunable, thermoelectrically cooled, and pulsed quantum cascade laser for continuous measurement of multiple trace gases. QCLOPS was used in a field campaign from July to September 2008 in Beijing to study trace gas concentrations before, during, and after the Olympic Games to examine changes induced by emissions reduction methods. Jointly, numerical simulation experiments were carried out with the Weather Research and Forecasting Model with chemistry module (WRF-Chem) for the same time period to examine the air quality, regional climate, and aerosol-cloud-precipitation interactions in the Beijing metropolitan region, by taking advantage of high-resolution emission inventories developed by the Institute of Atmospheric Physics - Chinese Academy of Sciences to represent the effects of emission reduction policies for the Olympic period. Intercomparisons between QCLOPS observations and WRF-Chem simulations were performed, and results are presented. Furthermore we present detailed analyses on the atmospheric environment and air quality variables during the first week of August in 2008 followed by the opening ceremony of the 2008 Summer Olympics.

  9. Improving ammonia emissions in air quality modelling for France

    NASA Astrophysics Data System (ADS)

    Hamaoui-Laguel, Lynda; Meleux, Frédérik; Beekmann, Matthias; Bessagnet, Bertrand; Génermont, Sophie; Cellier, Pierre; Létinois, Laurent

    2014-08-01

    We have implemented a new module to improve the representation of ammonia emissions from agricultural activities in France with the objective to evaluate the impact of such emissions on the formation of particulate matter modelled with the air quality model CHIMERE. A novel method has been set up for the part of ammonia emissions originating from mineral fertilizer spreading. They are calculated using the one dimensional 1D mechanistic model “VOLT'AIR” which has been coupled with data on agricultural practices, meteorology and soil properties obtained at high spatial resolution (cantonal level). These emissions display high spatiotemporal variations depending on soil pH, rates and dates of fertilization and meteorological variables, especially soil temperature. The emissions from other agricultural sources (animal housing, manure storage and organic manure spreading) are calculated using the national spatialised inventory (INS) recently developed in France. The comparison of the total ammonia emissions estimated with the new approach VOLT'AIR_INS with the standard emissions provided by EMEP (European Monitoring and Evaluation Programme) used currently in the CHIMERE model shows significant differences in the spatiotemporal distributions. The implementation of new ammonia emissions in the CHIMERE model has a limited impact on ammonium nitrate aerosol concentrations which only increase at most by 10% on the average for the considered spring period but this impact can be more significant for specific pollution episodes. The comparison of modelled PM10 (particulate matter with aerodynamic diameter smaller than 10 μm) and ammonium nitrate aerosol with observations shows that the use of the new ammonia emission method slightly improves the spatiotemporal correlation in certain regions and reduces the negative bias on average by 1 μg m-3. The formation of ammonium nitrate aerosol depends not only on ammonia concentrations but also on nitric acid availability, which

  10. Modelling air quality in street canyons: a review

    NASA Astrophysics Data System (ADS)

    Vardoulakis, Sotiris; Fisher, Bernard E. A.; Pericleous, Koulis; Gonzalez-Flesca, Norbert

    High pollution levels have been often observed in urban street canyons due to the increased traffic emissions and reduced natural ventilation. Microscale dispersion models with different levels of complexity may be used to assess urban air quality and support decision-making for pollution control strategies and traffic planning. Mathematical models calculate pollutant concentrations by solving either analytically a simplified set of parametric equations or numerically a set of differential equations that describe in detail wind flow and pollutant dispersion. Street canyon models, which might also include simplified photochemistry and particle deposition-resuspension algorithms, are often nested within larger-scale urban dispersion codes. Reduced-scale physical models in wind tunnels may also be used for investigating atmospheric processes within urban canyons and validating mathematical models. A range of monitoring techniques is used to measure pollutant concentrations in urban streets. Point measurement methods (continuous monitoring, passive and active pre-concentration sampling, grab sampling) are available for gaseous pollutants. A number of sampling techniques (mainly based on filtration and impaction) can be used to obtain mass concentration, size distribution and chemical composition of particles. A combination of different sampling/monitoring techniques is often adopted in experimental studies. Relatively simple mathematical models have usually been used in association with field measurements to obtain and interpret time series of pollutant concentrations at a limited number of receptor locations in street canyons. On the other hand, advanced numerical codes have often been applied in combination with wind tunnel and/or field data to simulate small-scale dispersion within the urban canopy.

  11. Beta test of models-3 with Community Multiscale Air Quality (CMAQ) model

    SciTech Connect

    LeDuc, S.

    1997-12-31

    The Models-3 framework for advanced air quality modeling, developed by the Environmental Protection Agency, Office of Research and Development (EPA/ORD), was provided to a limited number of beta test sites during the summer of 1997. Tutorial datasets and the Community Multiscale Air Quality (CMAQ) model were also provided. Valuable feedback on framework installation, performance, functionality, intuitiveness, user friendliness resulted from the beta test. This information will be used to guide framework improvements preparatory to public release in June 1998.

  12. Evaluation of the Community Multiscale Air Quality model version 5.1

    EPA Science Inventory

    The Community Multiscale Air Quality model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Atmospheric Modeling and Analysis Division (AMAD) of the U.S. Environment...

  13. SENSITIVITY OF OZONE AND AEROSOL PREDICTIONS TO THE TRANSPORT ALGORITHMS IN THE MODELS-3 COMMUNITY MULTI-SCALE AIR QUALITY (CMAQ) MODELING SYSTEM

    EPA Science Inventory

    EPA's Models-3 CMAQ system is intended to provide a community modeling paradigm that allows continuous improvement of the one-atmosphere modeling capability in a unified fashion. CMAQ's modular design promotes incorporation of several sets of science process modules representing ...

  14. Dynamic Evaluation of a Regional Air Quality Model: Assessing the Emissions-Induced Weekly Ozone Cycle

    EPA Science Inventory

    Air quality models are used to predict changes in pollutant concentrations resulting from envisioned emission control policies. Recognizing the need to assess the credibility of air quality models in a policy-relevant context, we perform a dynamic evaluation of the community Mult...

  15. SIMULATION OF AEROSOL DYNAMICS: A COMPARATIVE REVIEW OF ALGORITHMS USED IN AIR QUALITY MODELS

    EPA Science Inventory

    A comparative review of algorithms currently used in air quality models to simulate aerosol dynamics is presented. This review addresses coagulation, condensational growth, nucleation, and gas/particle mass transfer. Two major approaches are used in air quality models to repres...

  16. EMERGING AIR QUALITY MODELING TECHNOLOGY FOR HIGH PERFORMANCE COMPUTING AND COMMUNICATION ENVIRONMENTS

    EPA Science Inventory

    To demonstrate applications of the HPCC technologies in air quality models, we organized the Specialty Evening Session 1, "Emerging Air Quality Modeling Technologies for High Performance Computing and Communication Environment" as a part of the Twenty First NATO/CCMS Internationa...

  17. Urban Landscape Characterization Using Remote Sensing Data For Input into Air Quality Modeling

    NASA Technical Reports Server (NTRS)

    Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood

    2005-01-01

    The urban landscape is inherently complex and this complexity is not adequately captured in air quality models that are used to assess whether urban areas are in attainment of EPA air quality standards, particularly for ground level ozone. This inadequacy of air quality models to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well these models predict ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to meteorological and air quality models focusing on the Atlanta, Georgia metropolitan area as a case study. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality.

  18. VERIFICATION OF SURFACE LAYER OZONE FORECASTS IN THE NOAA/EPA AIR QUALITY FORECAST SYSTEM IN DIFFERENT REGIONS UNDER DIFFERENT SYNOPTIC SCENARIOS

    EPA Science Inventory

    An air quality forecast (AQF) system has been established at NOAA/NCEP since 2003 as a collaborative effort of NOAA and EPA. The system is based on NCEP's Eta mesoscale meteorological model and EPA's CMAQ air quality model (Davidson et al, 2004). The vision behind this system is ...

  19. Identifying Optimal Temporal Scale for the Correlation of AOD and Ground Measurements of PM2.5 to Improve the Modeling Performance in a Real-Time Air Quality Estimation System

    NASA Technical Reports Server (NTRS)

    Li,Hui; Faruque, Fazlay; Williams, Worth; Al-Hamdan, Mohammad; Luvall, Jeffrey; Crosson, William; Rickman, Douglas; Limaye, Ashutosh

    2008-01-01

    Aerosol optical depth (AOD), derived from satellite measurements using Moderate Resolution Imaging Spectrometer (MODIS), offers indirect estimates of particle matter. Research shows a significant positive correlation between satellite-based measurements of AOD and ground-based measurements of particulate matter with aerodynamic diameter less than or equal to 2.5 micrometers (PM2.5). In addition, satellite observations have also shown great promise in improving estimates of PM2.5 air quality surface. Research shows that correlations between AOD and ground PM2.5 are affected by a combination of many factors such as inherent characteristics of satellite observations, terrain, cloud cover, height of the mixing layer, and weather conditions, and thus might vary widely in different regions, different seasons, and even different days in a same location. Analysis of correlating AOD with ground measured PM2.5 on a day-to-day basis suggests the temporal scale, a number of immediate latest days for a given run's day, for their correlations needs to be considered to improve air quality surface estimates, especially when satellite observations are used in a real-time pollution system. The second reason is that correlation coefficients between AOD and ground PM2.5 cannot be predetermined and needs to be calculated for each day's run for a real-time system because the coefficients can vary over space and time. Few studies have been conducted to explore the optimal way to apply AOD data to improve model accuracies of PM2.5 surface estimation in a real-time air quality system. This paper discusses the best temporal scale to calculate the correlation of AOD and ground particle matter data to improve the results of pollution models in real-time system.

  20. Performance and diagnostic evaluation of ozone predictions by the Eta-Community Multiscale Air Quality Forecast System during the 2002 New England Air Quality Study.

    PubMed

    Yu, Shaocai; Mathur, Rohit; Kang, Daiwen; Schere, Kenneth; Eder, Brian; Pleim, Jonathan

    2006-10-01

    A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O3) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O3 was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O3 on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O3 concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O3 very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within +/- 20%. The model reproduced 53.3% of the observed hourly O3 within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites. The comparison of modeled and observed lidar O3 vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64-77% of observed NO2 photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O3/nitrogen oxide (NOx) ratios suggests that the site is mainly under strongly NOx-sensitive conditions (>53%). It was found that the modeled lower limits of the O3 production efficiency values (inferred from O3-CO correlation) are close to the observations. PMID:17063868

  1. VALIDATION OF THE EKMA MODEL USING HISTORICAL AIR QUALITY DATA

    EPA Science Inventory

    Historical air quality and emissions trend data for the Los Angeles region were used to check the EKMA isopleth method of relating ozone concentration changes to precursor emission changes. Trends in ozone and ozone precursors (NMHC and NOx) were estimated from data for the perio...

  2. The Atlanta Urban Heat Island Mitigation and Air Quality Modeling Project: How High-Resoution Remote Sensing Data Can Improve Air Quality Models

    NASA Technical Reports Server (NTRS)

    Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William L.; Khan, Maudood N.

    2006-01-01

    The Atlanta Urban Heat Island and Air Quality Project had its genesis in Project ATLANTA (ATlanta Land use Analysis: Temperature and Air quality) that began in 1996. Project ATLANTA examined how high-spatial resolution thermal remote sensing data could be used to derive better measurements of the Urban Heat Island effect over Atlanta. We have explored how these thermal remote sensing, as well as other imaged datasets, can be used to better characterize the urban landscape for improved air quality modeling over the Atlanta area. For the air quality modeling project, the National Land Cover Dataset and the local scale Landpro99 dataset at 30m spatial resolutions have been used to derive land use/land cover characteristics for input into the MM5 mesoscale meteorological model that is one of the foundations for the Community Multiscale Air Quality (CMAQ) model to assess how these data can improve output from CMAQ. Additionally, land use changes to 2030 have been predicted using a Spatial Growth Model (SGM). SGM simulates growth around a region using population, employment and travel demand forecasts. Air quality modeling simulations were conducted using both current and future land cover. Meteorological modeling simulations indicate a 0.5 C increase in daily maximum air temperatures by 2030. Air quality modeling simulations show substantial differences in relative contributions of individual atmospheric pollutant constituents as a result of land cover change. Enhanced boundary layer mixing over the city tends to offset the increase in ozone concentration expected due to higher surface temperatures as a result of urbanization.

  3. Developing air quality forecasts

    NASA Astrophysics Data System (ADS)

    Lee, Pius; Saylor, Rick; Meagher, James

    2012-05-01

    Third International Workshop on Air Quality Forecasting Research; Potomac, Maryland, 29 November to 1 December 2011 Elevated concentrations of both near-surface ozone (O3) and fine particulate matter smaller than 2.5 micrometers in diameter have been implicated in increased mortality and other human health impacts. In light of these known influences on human health, many governments around the world have instituted air quality forecasting systems to provide their citizens with advance warning of impending poor air quality so that they can take actions to limit exposure. In an effort to improve the performance of air quality forecasting systems and provide a forum for the exchange of the latest research in air quality modeling, the International Workshop on Air Quality Forecasting Research (IWAQFR) was established in 2009 and is cosponsored by the U.S. National Oceanic and Atmospheric Administration (NOAA), Environment Canada (EC), and the World Meteorological Organization (WMO). The steering committee for IWAQFR's establishment was composed of Véronique Bouchet, Mike Howe, and Craig Stoud (EC); Greg Carmichael (University of Iowa); Paula Davidson and Jim Meagher (NOAA); and Liisa Jalkanen (WMO). The most recent workshop took place in Maryland.

  4. Development and testing of an air quality model for Mexico City

    SciTech Connect

    Williams, M.D.; Streit, G.; Cruz, X.; Ruiz, M.; Sosa, G.; Russell, A.G.; McNair, L.A.

    1992-03-02

    Los Alamos National Laboratory and Instituto Mexicano del Petroleo have embarked on a joint study of options for improving air quality in Mexico City. The intent is to develop a modeling system which can address the behavior of pollutants in the region so that option for improving Mexico City air quality can be properly evaluated. In February of 1991, the project conducted a field program which yielded a variety of data which is being used to evaluate and improve the models. Normally the worst air quality for both primary and photochemical pollutants occurs in the winter Mexico City. During the field program, measurements included: (1) lidar measurements of aerosol transport and dispersion, (2) aircraft measurements of winds, turbulence, and chemical species aloft, (3) aircraft measurements of earth surface skin temperatures, and (4) tethersonde measurements of wind, temperature and ozone vertical profiles. A three-dimensional, prognostic, higher order turbulence meteorological model (HOTMAC) was modified to include an urban canopy and urban heat sources. HOTMAC is used to drive an Monte-Carlo kernel dispersion code (RAPTAD). HOTMAC also provides winds and mixing heights for the CIT photochemical model which was developed by investigators at the California Institute of Technology and Carnegie Mellon University.

  5. Factors controlling air quality in different European subway systems.

    PubMed

    Martins, Vânia; Moreno, Teresa; Mendes, Luís; Eleftheriadis, Konstantinos; Diapouli, Evangelia; Alves, Célia A; Duarte, Márcio; de Miguel, Eladio; Capdevila, Marta; Querol, Xavier; Minguillón, María Cruz

    2016-04-01

    Sampling campaigns using the same equipment and methodology were conducted to assess and compare the air quality at three South European subway systems (Barcelona, Athens and Oporto), focusing on concentrations and chemical composition of PM2.5 on subway platforms, as well as PM2.5 concentrations inside trains. Experimental results showed that the mean PM2.5 concentrations widely varied among the European subway systems, and even among different platforms within the same underground system, which might be associated to distinct station and tunnel designs and ventilation systems. In all cases PM2.5 concentrations on the platforms were higher than those in the urban ambient air, evidencing that there is generation of PM2.5 associated with the subway systems operation. Subway PM2.5 consisted of elemental iron, total carbon, crustal matter, secondary inorganic compounds, insoluble sulphate, halite and trace elements. Of all metals, Fe was the most abundant, accounting for 29-43% of the total PM2.5 mass (41-61% if Fe2O3 is considered), indicating the existence of an Fe source in the subway system, which could have its origin in mechanical friction and wear processes between rails, wheels and brakes. The trace elements with the highest enrichment in the subway PM2.5 were Ba, Cu, Mn, Zn, Cr, Sb, Sr, Ni, Sn, Co, Zr and Mo. Similar PM2.5 diurnal trends were observed on platforms from different subway systems, with higher concentrations during subway operating hours than during the transport service interruption, and lower levels on weekends than on weekdays. PM2.5 concentrations depended largely on the operation and frequency of the trains and the ventilation system, and were lower inside the trains, when air conditioning system was operating properly, than on the platforms. However, the PM2.5 concentrations increased considerably when the train windows were open. The PM2.5 levels inside the trains decreased with the trains passage in aboveground sections. PMID:26717078

  6. ANALYSIS OF AIR QUALITY DATA NEAR ROADWAYS USING A DISPERSION MODEL

    EPA Science Inventory

    A dispersion model was used to analyze measurements made during a field study conducted by the U.S. EPA in July and August 2006, to estimate the impact of highway emissions on air quality at distances of tens of meters from an eight-lane highway. The air quality measurements con...

  7. INDOOR AIR QUALITY MODELING (INDOOR ENVIRONMENT MANAGEMENT BRANCH, AIR POLLUTION PREVENTION AND CONTROL DIVISION, NRMRL)

    EPA Science Inventory

    The Indoor Environment Management Branch of NRMRL's Air Pollution Prevention and Control Division in Research Triangle Park, NC, has developed an indoor air quality (IAQ) model for analyzing the impact of sources, sinks, ventilation, and air cleaners on indoor air quality. Early ...

  8. Characterization of urban air quality using GIS as a management system.

    PubMed

    Puliafito, E; Guevara, M; Puliafito, C

    2003-01-01

    Keeping the air quality acceptable has become an important task for decision makers as well as for non-governmental organizations. Particulate and gaseous emissions of pollutant from industries and auto-exhausts are responsible for rising discomfort, increasing airway diseases, decreasing productivity and the deterioration of artistic and cultural patrimony in urban centers. A model to determine the air quality in urban areas using a geographical information system will be presented here. This system permits the integration, handling, analysis and simulation of spatial and temporal data of the ambient concentration of the main pollutant. It allows the users to characterize and recognize areas with a potential increase or improvement in its air pollution situation. It is also possible to compute past or present conditions by changing basic input information as traffic flow, or stack emission rates. Additionally the model may be used to test the compliance of local standard air quality, to study the environmental impact of new industries or to determine the changes in the conditions when the vehicle circulation is increased. PMID:12535599

  9. Identifying Optimal Temporal Scale for the Correlation of AOD and Ground Measurements of PM2.5 to Improve the Model Performance in a Real-time Air Quality Estimation System

    NASA Technical Reports Server (NTRS)

    Li, Hui; Faruque, Fazlay; Williams, Worth; Al-Hamdan, Mohammad; Luvall, Jeffrey C.; Crosson, William; Rickman, Douglas; Limaye, Ashutosh

    2009-01-01

    Aerosol optical depth (AOD), an indirect estimate of particle matter using satellite observations, has shown great promise in improving estimates of PM 2.5 air quality surface. Currently, few studies have been conducted to explore the optimal way to apply AOD data to improve the model accuracy of PM 2.5 surface estimation in a real-time air quality system. We believe that two major aspects may be worthy of consideration in that area: 1) the approach to integrate satellite measurements with ground measurements in the pollution estimation, and 2) identification of an optimal temporal scale to calculate the correlation of AOD and ground measurements. This paper is focused on the second aspect on the identifying the optimal temporal scale to correlate AOD with PM2.5. Five following different temporal scales were chosen to evaluate their impact on the model performance: 1) within the last 3 days, 2) within the last 10 days, 3) within the last 30 days, 4) within the last 90 days, and 5) the time period with the highest correlation in a year. The model performance is evaluated for its accuracy, bias, and errors based on the following selected statistics: the Mean Bias, the Normalized Mean Bias, the Root Mean Square Error, Normalized Mean Error, and the Index of Agreement. This research shows that the model with the temporal scale of within the last 30 days displays the best model performance in this study area using 2004 and 2005 data sets.

  10. “A Reduced-form Model to Estimate Near-road Air Quality for Communities: the Community Line Source modeling system (C-LINE)”

    EPA Science Inventory

    The paper presents the Community Line Source (C-LINE) modeling system that estimates toxic air pollutant (air toxics) concentration gradients within 500 meters of busy roadways for community-sized areas on the order of 100 km2. C-LINE accesses publicly available datasets with nat...

  11. IMPACTS OF CHANGES IN LAND USE AND LAND COVER ON U.S. AIR QUALITY: DEVELOPMENT AND APPLICATION OF AN INTEGRATED CLIMATE-VEGETATION-CHEMISTRY MODELING SYSTEM

    EPA Science Inventory

    (a). We have developed an integrated climate-vegetation-chemistry modeling system that incorporates a global chemical transport model model (GEOS-Chem CTM), a general circulation model (GISS GCM), and a global dynamic vegetation model (the LPJ model). This modeling system...

  12. Improving UK Air Quality Modelling Through Exploitation of Satellite Observations

    NASA Astrophysics Data System (ADS)

    Pope, Richard; Chipperfield, Martyn; Savage, Nick

    2014-05-01

    In this work the applicability of satellite observations to evaluate the operational UK Met Office Air Quality in the Unified Model (AQUM) have been investigated. The main focus involved the AQUM validation against satellite observations, investigation of satellite retrieval error types and of synoptic meteorological-atmospheric chemistry relationships simulated/seen by the AQUM/satellite. The AQUM is a short range forecast model of atmospheric chemistry and aerosols up to 5 days. It has been designed to predict potentially hazardous air pollution events, e.g. high concentrations of surface ozone. The AQUM has only been validated against UK atmospheric chemistry recording surface stations. Therefore, satellite observations of atmospheric chemistry have been used to further validate the model, taking advantage of better satellite spatial coverage. Observations of summer and winter 2006 tropospheric column NO2 from both OMI and SCIAMACHY show that the AQUM generally compares well with the observations. However, in northern England positive biases (AQUM - satellite) suggest that the AQUM overestimates column NO2; we present results of sensitivity experiments on UK emissions datasets suspected to be the cause. In winter, the AQUM over predicts background column NO2 when compared to both satellite instruments. We hypothesise that the cause is the AQUM winter night-time chemistry, where the NO2 sinks are not substantially defined. Satellite data are prone to errors/uncertainty such as random, systematic and smoothing errors. We have investigated these error types and developed an algorithm to calculate and reduce the random error component of DOAS NO2 retrievals, giving more robust seasonal satellite composites. The Lamb Weather Types (LWT), an objective method of classifying the daily synoptic weather over the UK, were used to create composite satellite maps of column NO2 under different synoptic conditions. Under cyclonic conditions, satellite observed UK column NO2 is

  13. Initial Application of the MM5-MEGAN-SMOKE-CMAQ System for Simulating Air Quality in Brazil

    NASA Astrophysics Data System (ADS)

    De Souza, L. S.; Adelman, Z.; Moraes, N. O.; Da Silva, R. M.; Landau, L.; Pimentel, L. G.

    2011-12-01

    Most of the recent air quality modeling studies in Brazil have been focused on the main Metropolitan Areas (MAs) located in the south-central region of the country. Studies over Sao Paulo and Rio de Janeiro are the most frequent and are usually focused on ozone and its precursors. Other MAs that have been the subject of air quality studies include Porto Alegre and Curitiba in the south and Belo Horizonte and Vitoria in the southeast. According to the last official figures from the Brazilian Institute of Geography and Statistics (IBGE - www.ibge.gov.br), Brazil has 36 metropolitan areas with more than 250,000 inhabitants and less than 30% of them have publically-accessible air quality management programs. In this study we examine ozone and its precursors on a national level using a modeling system composed of MM5-MEGAN-SMOKE-CMAQ. The goal of this study is to identify areas with emissions and ozone concentrations that may require air quality management programs. MM5 provided hourly meteorological estimates. SMOKE was used to process global emission data from EDGAR version 3.2 for anthropogenic sources and GFED for biomass burning sources. MEGAN was used to estimate biogenic emissions. The modeling system was run on a 37x37 km grid with 32 vertical levels for august 2005 for a domain that covers all of Brazil. The model period was selected to identify air pollution over the Amazonian area during one of the most intense dry seasons of the past 40 years. Analysis was conducted on the air quality predictions over Amazonia and in the northeast of Brazil to study the influence of different inventory sectors in MAs in these regions. The global emission inventories were assimilated to provide a national emission profile that was able to reproduce important air quality trends, such as peak concentrations in Sao Paulo for almost all pollutants and high ozone for Rio de Janeiro. In northern Brazil, both emissions and ozone peaks were simulated in the region known as the "arch

  14. AIR QUALITY MODELING OF PM AND AIR TOXICS AT NEIGHBORHOOD SCALES

    EPA Science Inventory

    The current interest in fine particles and toxics pollutants provide an impetus for extending air quality modeling capability towards improving exposure modeling and assessments. Human exposure models require information on concentration derived from interpolation of observati...

  15. The role of Environmental Health System air quality monitors in Space Station Contingency Operations

    NASA Technical Reports Server (NTRS)

    Limero, Thomas F.; Wilson, Steve; Perlot, Susan; James, John

    1992-01-01

    This paper describes the Space Station Freedom (SSF) Environmental Health System's air-quality monitoring strategy and instrumentation. A two-tier system has been developed, consisting of first-alert instruments that warn the crew of airborne contamination and a volatile organic analyzer that can identify volatile organic contaminants in near-real time. The strategy for air quality monitoring on SSF is designed to provide early detection so that the contamination can be confined to one module and so that crew health and safety can be protected throughout the contingency event. The use of air-quality monitors in fixed and portable modes will be presented as a means of following the progress of decontamination efforts and ensuring acceptable air quality in a module after an incident. The technology of each instrument will be reviewed briefly; the main focus of this paper, however, will be the use of air-quality monitors before, during, and after contingency incidents.

  16. Toward an integrated quasi-operational air quality analysis and prediction system for South America

    NASA Astrophysics Data System (ADS)

    Hoshyaripour, Gholam Ali; Brasseur, Guy; Petersen, Katinka; Bouarar, Idiir; Andrade, Maria de Fatima

    2015-04-01

    Recent industrialization and urbanization in South America (SA) have notably exacerbated the air pollution with adverse impacts on human health and socio-economic systems. Consequently, there is a strong demand for developing ever-better assessment mechanisms to monitor the air quality at different temporal and spatial scales and minimize its damages. Based on previous achievements (e.g., MACC project in Europe and PANDA project in East Asia) we aim to design and implement an integrated system to monitor, analyze and forecast the air quality in SA along with its impacts upon public health and agriculture. An initiative will be established to combine observations (both satellite and in-situ) with advanced numerical models in order to provide a robust scientific basis for short- and long-term decision-making concerning air quality issues in SA countries. The main objectives of the project are defined as 3E: Enhancement of the air quality monitoring system through coupling models and observations, Elaboration of comprehensive indicators and assessment tools to support policy-making, Establishment of efficient information-exchange platforms to facilitate communication among scientists, authorities, stockholders and the public. Here we present the results of the initial stage, where a coarse resolution (50×50 km) set up of Weather Research and Forecast model with Chemistry (WRF-Chem) is used to simulate the air quality in SA considering anthropogenic, biomass-burning (based on MACCity, FINN inventories, respectively) and biogenic emissions (using MEGAN model). According to the availability of the observation data for Metropolitan Area of São Paulo, August 2012 is selected as the simulation period. Nested domains with higher resolution (15×15 km) are also embedded within the parent domain over the megacities (Sao Paolo and Rio de Janeiro in Brazil and Buenos Aires in Argentina), which account for the major anthropogenic emission sources located along coastal regions

  17. MODELS-3 COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL AEROSOL COMPONENT 1: MODEL DESCRIPTION

    EPA Science Inventory

    The aerosol component of the Community Multiscale Air Quality (CMAQ) model is designed to be an efficient and economical depiction of aerosol dynamics in the atmosphere. The approach taken represents the particle size distribution as the superposition of three lognormal subdis...

  18. Real Time Air Quality Forecasting System for a Large Industrial Facility

    NASA Astrophysics Data System (ADS)

    Radonjic, Z.; Chambers, D.; Telenta, B.; Janjic, Z.

    2012-04-01

    Forecasts of air quality are provided using a weather forecasting model coupled with an air dispersion model. The advanced mesoscale WRF- NMM (Weather Research and Forecasting - Nonhydrostatic Mesoscale Model) is set up to provide meteorological forecasts initially over a larger domain with resolution 3 by 3 km which is subsequently nested down to a smaller domain of 1 by 1 km horizontal resolution around a copper smelter in Serbia. The refined meteorological forecast is used as input to drive the CALMET/CALPUFF modeling system to predict hour by hour concentrations of the facility's key pollutant (SO2). CALMET/CALPUFF is the U.S. EPA's regulatory model for long-range transport and on a case by case basis is applied in complex terrain and shore-line settings. The CALMET/CALPUFF modeling system is accepted as a regulatory model for short-range applications in several jurisdictions in Canada. The main goal of this paper is to demonstrate the good performance of the weather model in forecasting mode with fine resolution and in complex terrain, as well as the comparison of predicted SO2 air concentrations with measurements taken at four nearby air quality ambient monitoring stations. The forecasts of SO2 concentrations are used by the facility to adjust the production schedule to avoid high level concentrations in the city and maximize production during favourable meteorological conditions. Since the facility is located in a valley, during stagnant meteorological conditions there is a potential for the build up of high concentrations of SO2. With the use of this air quality forecasting system, the facility can avoid the worst meteorological situations and reduce concentrations in the populated areas.

  19. Air quality simulations for North America - MM5-CAMx modelling performance for main gaseous pollutants

    NASA Astrophysics Data System (ADS)

    Ferreira, J.; Rodriguez, A.; Monteiro, A.; Miranda, A. I.; Dios, M.; Souto, J. A.; Yarwood, G.; Nopmongcol, U.; Borrego, C.

    2012-06-01

    In the scope of the Air Quality Model Evaluation International Initiative (AQMEII) the air quality modelling system MM5-CAMx was applied to the North American (NA) domain for calendar year 2006. The simulation domain was defined according to the spatial resolution and the coordinate system of the emission databases provided and the common grid required by AQMEII for ensemble analysis. A Lambert Conformal Projection grid of around 5500 km by 3580 km with 24 × 24 km2 horizontal resolution was defined. Emissions available through AQMEII have been prepared to feed the CAMx model. Meteorological inputs were developed by the application of the meteorological model MM5, which was initialized by 1° resolution NCEP-FNL global data and run for the whole year of 2006. A spatial and temporal analysis of results based on the 2D surface fields and time series for regional monitoring stations was performed for the main gaseous pollutants. A detailed statistical analysis and evaluation against observations was carried out, considering three different sub-domains over North America, in order to comprehend the differences between the East, West and Central part. The exploitation of modelling results was based on the capabilities and analysis tools available through the ENSEMBLE software, developed and upgraded for AQMEII. Results have shown a good agreement between observed and modelled concentrations of O3 (especially regarding peaks) and NO2 and a weaker performance of the air quality model for CO and SO2. However, the model tends to underestimate O3 and overestimate NO2 and CO at night as a consequence of meteorology (weak vertical mixing due to underestimation of the Planetary Boundary Layer (PBL) height). This paper intends to be a valuable contribution to the overall AQMEII exercise since it aims to evaluate the performance of individual models to be used in the ensemble approach for the areas of interest.

  20. Development of Gridded Fields of Urban Canopy Parameters for Advanced Urban Meteorological and Air Quality Models

    EPA Science Inventory

    Urban dispersion and air quality simulation models applied at various horizontal scales require different levels of fidelity for specifying the characteristics of the underlying surfaces. As the modeling scales approach the neighborhood level (~1 km horizontal grid spacing), the...

  1. Developing and Transitioning Numerical Air Quality Models to Improve Air Quality and Public Health Decision-Making in El Salvador and Costa Rica As Part of the Servir Applied Sciences Team

    NASA Astrophysics Data System (ADS)

    Thomas, A.; Huff, A. K.; Gomori, S. G.; Sadoff, N.

    2014-12-01

    In order to enhance the capacity for air quality modeling and improve air quality monitoring and management in the SERVIR Mesoamerica region, members of SERVIR's Applied Sciences Team (AST) are developing national numerical air quality models for El Salvador and Costa Rica. We are working with stakeholders from the El Salvador Ministry of the Environment and Natural Resources (MARN); National University of Costa Rica (UNA); the Costa Rica Ministry of the Environment, Energy, and Telecommunications (MINAET); and Costa Rica National Meteorological Institute (IMN), who are leaders in air quality monitoring and management in the Mesoamerica region. Focusing initially on these institutions will build sustainability in regional modeling activities by developing air quality modeling capability that can be shared with other countries in Mesoamerica. The air quality models are based on the Community Multi-scale Air Quality (CMAQ) model and incorporate meteorological inputs from the Weather Research and Forecasting (WRF) model, as well as national emissions inventories from El Salvador and Costa Rica. The models are being optimized for urban air quality, which is a priority of decision-makers in Mesoamerica. Once experimental versions of the modeling systems are complete, they will be transitioned to servers run by stakeholders in El Salvador and Costa Rica. The numerical air quality models will provide decision support for stakeholders to identify 1) high-priority areas for expanding national ambient air monitoring networks, 2) needed revisions to national air quality regulations, and 3) gaps in national emissions inventories. This project illustrates SERVIR's goal of the transition of science to support decision-making through capacity building in Mesoamerica, and it aligns with the Group on Earth Observations' health societal benefit theme. This presentation will describe technical aspects of the development of the models and outline key steps in our successful

  2. Evaluation of the 2006 Canadian Air Quality Modelling Platform for Policy Scenarios

    NASA Astrophysics Data System (ADS)

    Davignon, D.; Chen, J.; Cousineau, S.; Crevier, L.; Duhamel, A.; Gilbert, S.; Pavlovic, R.; Racine, J.; Samaali, M.; Sassi, M.

    2009-12-01

    A modelling platform for the purposes of air quality policy scenario assessments is being setup and evaluated at Environment Canada. The main modelling system within the platform is the Environment Canada AURAMS (A Unified Regional Air quality Modelling System) which has explicit treatments of gaseous and particulate matter chemistry and physics. Additional components of the platform include the Global Environmental Model (GEM) for meteorology, the Sparse Matrix Operating Kernel Emissions (SMOKE) processing system, and a set of tools and models to diagnose and bridge results for health benefit and environmental impact analyses. In order to capture the seasonality and the distributions of the atmospheric conditions at different regions in Canada, the platform is applied for an annual simulation with a large domain encompassing the North American continent at 45-km grid resolution. The coarse resolution results are then refined with two nested domains for the east and west Canada at 22.5-km grid resolution. To evaluate of the modelling platform, the annual simulation results for 2006 are compared against ambient measurements for ozone and PM2.5. Measurement data are from both routine observational networks in Canada and United States (NAPS, IMPROVE, AQS), as well as non-routine measurement campaigns in 2006, which include vertical ozone profiles at selected locations in the domain. The presentation provides an overview of the current modelling platform setup and configurations, as well as discussions on the preliminary evaluation results from the annual simulations.

  3. Air quality modeling in the Valley of Mexico: meteorology, emissions and forecasting

    NASA Astrophysics Data System (ADS)

    Garcia-Reynoso, A.; Jazcilevich, A. D.; Diaz-Nigenda, E.; Vazquez-Morales, W.; Torres-Jardon, R.; Ruiz-Suarez, G.; Tatarko, J.; Bornstein, R.

    2007-12-01

    The Valley of Mexico presents important challenges for air quality modeling: complex terrain, a great variety of anthropogenic and natural emissions sources, and high altitude and low latitude increasing the amount of radiation flux. The modeling group at the CCA-UNAM is using and merging state of the art models to study the different aspects that influence the air quality phenomenon in the Valley of Mexico. The air quality model MCCM that uses MM5 as its meteorological input has been a valuable tool to study important features of the complex and intricate atmospheric flows on the valley, such as local confluences and vertical fumigation. Air quality modeling has allowed studying the interaction between the atmospheres of the valleys surrounding the Valley of Mexico, prompting the location of measurement stations during the MILAGRO campaign. These measurements confirmed the modeling results and expanded our knowledge of the transport of pollutants between the Valleys of Cuernavaca, Puebla and Mexico. The urban landscape of Mexico City complicates meteorological modeling. Urban-MM5, a model that explicitly takes into account the influence of buildings, houses, streets, parks and anthropogenic heat, is being implemented. Preliminary results of urban-MM5 on a small area of the city have been obtained. The current emissions inventory uses traffic database that includes hourly vehicular activity in more than 11,000 street segments, includes 23 area emissions categories, more than 1,000 industrial sources and biogenic emissions. To improve mobile sources emissions a system consisting of a traffic model and a car simulator is underway. This system will allow for high time and space resolution and takes into account motor stress due to different driving regimes. An important source of emissions in the Valley of Mexico is erosion dust. The erosion model WEPS has been integrated with MM5 and preliminary results showing dust episodes over Mexico City have been obtained. A

  4. Study on an air quality evaluation model for Beijing City under haze-fog pollution based on new ambient air quality standards.

    PubMed

    Li, Li; Liu, Dong-Jun

    2014-09-01

    Since 2012, China has been facing haze-fog weather conditions, and haze-fog pollution and PM2.5 have become hot topics. It is very necessary to evaluate and analyze the ecological status of the air environment of China, which is of great significance for environmental protection measures. In this study the current situation of haze-fog pollution in China was analyzed first, and the new Ambient Air Quality Standards were introduced. For the issue of air quality evaluation, a comprehensive evaluation model based on an entropy weighting method and nearest neighbor method was developed. The entropy weighting method was used to determine the weights of indicators, and the nearest neighbor method was utilized to evaluate the air quality levels. Then the comprehensive evaluation model was applied into the practical evaluation problems of air quality in Beijing to analyze the haze-fog pollution. Two simulation experiments were implemented in this study. One experiment included the indicator of PM2.5 and was carried out based on the new Ambient Air Quality Standards (GB 3095-2012); the other experiment excluded PM2.5 and was carried out based on the old Ambient Air Quality Standards (GB 3095-1996). Their results were compared, and the simulation results showed that PM2.5 was an important indicator for air quality and the evaluation results of the new Air Quality Standards were more scientific than the old ones. The haze-fog pollution situation in Beijing City was also analyzed based on these results, and the corresponding management measures were suggested. PMID:25170682

  5. Study on an Air Quality Evaluation Model for Beijing City Under Haze-Fog Pollution Based on New Ambient Air Quality Standards

    PubMed Central

    Li, Li; Liu, Dong-Jun

    2014-01-01

    Since 2012, China has been facing haze-fog weather conditions, and haze-fog pollution and PM2.5 have become hot topics. It is very necessary to evaluate and analyze the ecological status of the air environment of China, which is of great significance for environmental protection measures. In this study the current situation of haze-fog pollution in China was analyzed first, and the new Ambient Air Quality Standards were introduced. For the issue of air quality evaluation, a comprehensive evaluation model based on an entropy weighting method and nearest neighbor method was developed. The entropy weighting method was used to determine the weights of indicators, and the nearest neighbor method was utilized to evaluate the air quality levels. Then the comprehensive evaluation model was applied into the practical evaluation problems of air quality in Beijing to analyze the haze-fog pollution. Two simulation experiments were implemented in this study. One experiment included the indicator of PM2.5 and was carried out based on the new Ambient Air Quality Standards (GB 3095-2012); the other experiment excluded PM2.5 and was carried out based on the old Ambient Air Quality Standards (GB 3095-1996). Their results were compared, and the simulation results showed that PM2.5 was an important indicator for air quality and the evaluation results of the new Air Quality Standards were more scientific than the old ones. The haze-fog pollution situation in Beijing City was also analyzed based on these results, and the corresponding management measures were suggested. PMID:25170682

  6. Neuro-fuzzy and neural network systems for air quality control

    NASA Astrophysics Data System (ADS)

    Carnevale, Claudio; Finzi, Giovanna; Pisoni, Enrico; Volta, Marialuisa

    In order to define efficient air quality plans, Regional Authorities need suitable tools to evaluate both the impact of emission reduction strategies on pollution indexes and the costs of such emission reductions. The air quality control can be formalized as a two-objective nonlinear mathematical problem, integrating source-receptor models and the estimate of emission reduction costs. Both aspects present several complex elements. In particular the source-receptor models cannot be implemented through deterministic modelling systems, that would bring to a computationally unfeasible mathematical problem. In this paper we suggest to identify source-receptor statistical models (neural network and neuro-fuzzy) processing the simulations of a deterministic multi-phase modelling system (GAMES). The methodology has been applied to ozone and PM10 concentrations in Northern Italy. The results show that, despite a large advantage in terms of computational costs, the selected source-receptor models are able to accurately reproduce the simulation of the 3D modelling system.

  7. 75 FR 4070 - Science Advisory Board Staff Office; Notification of a Public Meeting of the Air Quality Modeling...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-01-26

    ... AGENCY Science Advisory Board Staff Office; Notification of a Public Meeting of the Air Quality Modeling... public meeting of the Air Quality Modeling Subcommittee (AQMS) of the Advisory Council on Clean Air... air quality modeling results for scenarios with and without EPA's regulatory programs...

  8. Linking agricultural crop management and air quality models for regional to national-scale nitrogen assessments

    NASA Astrophysics Data System (ADS)

    Cooter, E. J.; Bash, J. O.; Benson, V.; Ran, L.

    2012-10-01

    While nitrogen (N) is an essential element for life, human population growth and demands for energy, transportation and food can lead to excess nitrogen in the environment. A modeling framework is described and implemented to promote a more integrated, process-based and system-level approach to the estimation of ammonia (NH3) emissions which result from the application of inorganic nitrogen fertilizers to agricultural soils in the United States. The United States Department of Agriculture (USDA) Environmental Policy Integrated Climate (EPIC) model is used to simulate plant demand-driven fertilizer applications to commercial cropland throughout the continental US. This information is coupled with a process-based air quality model to produce continental-scale NH3 emission estimates. Regional cropland NH3 emissions are driven by the timing and amount of inorganic NH3 fertilizer applied, soil processes, local meteorology, and ambient air concentrations. Initial fertilizer application often occurs when crops are planted. A state-level evaluation of EPIC-simulated, cumulative planted area compares well with similar USDA reported estimates. EPIC-annual, inorganic fertilizer application amounts also agree well with reported spatial patterns produced by others, but domain-wide the EPIC values are biased about 6% low. Preliminary application of the integrated fertilizer application and air quality modeling system produces a modified geospatial pattern of seasonal NH3 emissions that improves current simulations of observed atmospheric particle nitrate concentrations. This modeling framework provides a more dynamic, flexible, and spatially and temporally resolved estimate of NH3 emissions than previous factor-based NH3 inventories, and will facilitate evaluation of alternative nitrogen and air quality policy and adaptation strategies associated with future climate and land use changes.

  9. Linking agricultural crop management and air quality models for regional to national-scale nitrogen assessments

    NASA Astrophysics Data System (ADS)

    Cooter, E. J.; Bash, J. O.; Benson, V.; Ran, L.

    2012-05-01

    While nitrogen (N) is an essential element for life, human population growth and demands for energy, transportation and food can lead to excess nitrogen in the environment. A modeling framework is described and implemented, to promote a more integrated, process-based and system-level approach to the estimation of ammonia (NH3) emissions resulting from the application of inorganic nitrogen fertilizers to agricultural soils in the United States. The United States Department of Agriculture (USDA) Environmental Policy Integrated Climate (EPIC) model is used to simulate plant demand-driven fertilizer applications to commercial cropland throughout the continental US. This information is coupled with a process-based air quality model to produce continental-scale NH3 emission estimates. Regional cropland NH3 emissions are driven by the timing and amount of fertilizer applied, local meteorology, and ambient air concentrations. An evaluation of EPIC-simulated crop management activities associated with fertilizer application at planting compared with similar USDA state-level event estimates shows temporally progressive spatial patterns that agree well with one another. EPIC annual inorganic fertilizer application amounts also agree well with reported spatial patterns produced by others, but domain-wide the EPIC values are biased about 6 % low. Preliminary application of the integrated fertilizer application and air quality modeling system produces a modified geospatial pattern of seasonal NH3 emissions that improves current simulations of observed atmospheric nitrate concentrations. This modeling framework provides a more dynamic, flexible, and spatially and temporally resolved estimate of NH3 emissions than previous factor-based NH3 inventories, and will facilitate evaluation of alternative nitrogen and air quality policy and adaptation strategies associated with future climate and land use changes.

  10. A NEW COMBINED LOCAL AND NON-LOCAL PBL MODEL FOR METEOROLOGY AND AIR QUALITY MODELING

    EPA Science Inventory

    A new version of the Asymmetric Convective Model (ACM) has been developed to describe sub-grid vertical turbulent transport in both meteorology models and air quality models. The new version (ACM2) combines the non-local convective mixing of the original ACM with local eddy diff...

  11. Regional air quality in the four corners studys region: modeling approach

    SciTech Connect

    Nochumson, D.

    1982-01-01

    A two-dimensional Eulerian air pollutant transport model was used in an air quality study of the Four Corners region conducted for the National Commission on Air Quality. The regional modeling methodology and some sample results from the regional air quality analysis are presented. One major advantage of the regional transport model that was employed is that its solution involves the calculation of transfer coefficients that relate emissions to ambient concentrations and deposition and which can be used repeatedly to evaluate alternative scenarios and regulatory policies which represent different emission source configurations. The regional transport model was used in the calculation of the concentration and deposition of SO/sub 2/, SO/sub 4/, and primary fine particulates; and these estimates were used as inputs to regional atmospheric visibility and mass budget calculations. Previous studies have shown that the methods used in the regional air quality analysis give good agreement when comparing observed and estimated values.

  12. DEVELOPMENT OF MESOSCALE AIR QUALITY SIMULATION MODELS. VOLUME 6. USER'S GUIDE TO MESOPAC (MESOSCALE METEOROLOGY PACKAGE)

    EPA Science Inventory

    MESOPAC is a mesoscale meteorological preprocessor program; it is designed to provide meteorological data to regional-scale air quality simulation models. Radiosonde data routinely available from National Weather Service (NWS) radiosonde ('upper air') and surface stations are use...

  13. A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS

    EPA Science Inventory

    Fine-scale Computational Fluid Dynamics (CFD) simulation of pollutant concentrations within roadway and building microenvironments is feasible using high performance computing. Unlike currently used regulatory air quality models, fine-scale CFD simulations are able to account rig...

  14. APPLICATION OF BAYESIAN MONTE CARLO ANALYSIS TO A LAGRANGIAN PHOTOCHEMICAL AIR QUALITY MODEL. (R824792)

    EPA Science Inventory

    Uncertainties in ozone concentrations predicted with a Lagrangian photochemical air quality model have been estimated using Bayesian Monte Carlo (BMC) analysis. Bayesian Monte Carlo analysis provides a means of combining subjective "prior" uncertainty estimates developed ...

  15. Evaluation of the United States National Air Quality Forecast Capability experimental real-time predictions in 2010 using Air Quality System ozone and NO2 measurements

    NASA Astrophysics Data System (ADS)

    Chai, T.; Kim, H.-C.; Lee, P.; Tong, D.; Pan, L.; Tang, Y.; Huang, J.; McQueen, J.; Tsidulko, M.; Stajner, I.

    2013-05-01

    The National Air Quality Forecast Capability (NAQFC) project provides the US with operational and experimental real-time ozone predictions using two different versions of the three-dimensional Community Multi-scale Air Quality (CMAQ) Modeling System. Routine evaluation using near-real-time AIRNow ozone measurements through 2011 showed better performance of the operational ozone predictions. In this work, quality-controlled and -assured Air Quality System (AQS) ozone and nitrogen dioxide (NO2) observations are used to evaluate the experimental predictions in 2010, with a view towards their improvement. It is found that both ozone and NO2 are overestimated over the contiguous US (CONUS), with annual biases of +5.6 ppbv and +5.1 ppbv, respectively. The annual root mean square errors (RMSEs) are 15.4 ppbv for ozone and 13.4 ppbv for NO2. For both species the over-predictions are most pronounced in the summer. The locations of the AQS monitoring sites are also utilized to stratify comparisons by the degree of urbanization. Comparisons for six predefined US regions show the highest annual biases for ozone predictions in Southeast (+10.5 ppbv) and for NO2 in the Lower Middle (+8.1 ppbv) and Pacific Coast (+7.1 ppbv) regions. The spatial distributions of the NO2 biases in July and August show distinctively high values in Los Angeles, Houston, and New Orleans areas. In addition to the standard statistics metrics, daily maximum eight-hour ozone categorical statistics are calculated using the current US ambient air quality standard (75 ppbv) and another lower threshold (70 ppbv). Using the 75 ppbv standard, the hit rate and proportion of correct over CONUS for the entire year are 0.64 and 0.96, respectively. Summertime biases show distinctive weekly patterns for ozone and NO2. Diurnal comparisons show that ozone overestimation is most severe in the morning, from 07:00 to 10:00 local time. For NO2, the morning predictions agree with the AQS observations reasonably well, but

  16. Development and evaluation of an ammonia bidirectional flux parameterization for air quality models

    NASA Astrophysics Data System (ADS)

    Pleim, Jonathan E.; Bash, Jesse O.; Walker, John T.; Cooter, Ellen J.

    2013-05-01

    is an important contributor to particulate matter in the atmosphere and can significantly impact terrestrial and aquatic ecosystems. Surface exchange between the atmosphere and biosphere is a key part of the ammonia cycle. New modeling techniques are being developed for use in air quality models that replace current ammonia emissions from fertilized crops and ammonia dry deposition with a bidirectional surface flux model including linkage to a detailed biogeochemical and farm management model. Recent field studies involving surface flux measurements over crops that predominate in North America have been crucial for extending earlier bidirectional flux models toward more realistic treatment of NH3 fluxes for croplands. Comparisons of the ammonia bidirection flux algorithm to both lightly fertilized soybeans and heavily fertilized corn demonstrate that the model can capture the magnitude and dynamics of observed ammonia fluxes, both net deposition and evasion, over a range of conditions with overall biases on the order of the uncertainty of the measurements. However, successful application to the field experiment in heavily fertilized corn required substantial modification of the model to include new parameterizations for in-soil diffusion resistance, ground quasi-laminar boundary layer resistance, and revised cuticular resistance that is dependent on in-canopy NH3 concentration and RH at the leaf surface. This new bidirectional flux algorithm has been incorporated in an air quality modeling system, which also includes an implementation of a soil nitrification model.

  17. Past, Present, and Future Anthropogenic Emissions over Asia: a Regional Air Quality Modeling Perspective

    NASA Astrophysics Data System (ADS)

    Woo, Jung-Hun; Jung, Bujeon; Choi, Ki-Chul; Seo, Ji-Hyun; Kim, Tae Hyung; Park, Rokjin J.; Youn, Daeok; Jeong, Jaein; Moon, Byung-Kwon; Yeh, Sang-Wook

    2010-05-01

    Climate change will also affect future regional air quality which has potential human health, ecosystem, and economic implications. To analyze the impacts of climate change on Asian air quality, the NIER (National Institute of Environmental Research, Korea) integrated modeling framework was developed based on global-to-regional climate and atmospheric chemistry models. In this study, we developed emission inventories for the modeling framework for 1980~2100 with an emphasis on Asia emissions. Two emission processing systems which have functions of emission projection, spatial/temporal allocation, and chemical speciation have been also developed in support of atmospheric chemistry models including GEOS-Chem and Models-3/CMAQ. Asia-based emission estimates, projection factors, temporal allocation parameters were combined to improve regional modeling capability of past, present and future air quality over Asia. The global CO emissions show a 23% decrease from the years 1980 to 2000. For the future CO (from year 2000 to 2100), the A2 scenario shows a 95% increase due to the B40 (Residential-Biofuel) sector of Western Africa, Eastern Africa and East Asia and the F51 (Transport Road-Fossil fuel) sector of Middle East, USA and South Asia. The B1 scenario, however, shows a 79% decrease of emissions due to B40 and F51 sectors of East Asia, South Asia and USA for the same period. In many cases, Asian emissions play important roles for global emission increase or decrease depending on the IPCC scenarios considered. The regional ozone forming potential will be changed due to different VOC/NOx emission ratio changes in the future. More similarities and differences of Asian emission characteristics, in comparison with its global counterpart, are investigated.

  18. The NASA Lightning Nitrogen Oxides Model (LNOM): Application to Air Quality Modeling

    NASA Technical Reports Server (NTRS)

    Koshak, William; Peterson, Harold; Khan, Maudood; Biazar, Arastoo; Wang, Lihua

    2011-01-01

    Recent improvements to the NASA Marshall Space Flight Center Lightning Nitrogen Oxides Model (LNOM) and its application to the Community Multiscale Air Quality (CMAQ) modeling system are discussed. The LNOM analyzes Lightning Mapping Array (LMA) and National Lightning Detection Network(TradeMark)(NLDN) data to estimate the raw (i.e., unmixed and otherwise environmentally unmodified) vertical profile of lightning NO(x) (= NO + NO2). The latest LNOM estimates of lightning channel length distributions, lightning 1-m segment altitude distributions, and the vertical profile of lightning NO(x) are presented. The primary improvement to the LNOM is the inclusion of non-return stroke lightning NOx production due to: (1) hot core stepped and dart leaders, (2) stepped leader corona sheath, K-changes, continuing currents, and M-components. The impact of including LNOM-estimates of lightning NO(x) for an August 2006 run of CMAQ is discussed.

  19. Central California coastal air-quality model validation study: Data analysis and model evaluation

    SciTech Connect

    Dabberdt, W.F.; Johnson, W.B.; Brodzinsky, R.; Ruff, R.E.

    1984-08-01

    The objectives of the study were: to obtain a comprehensive experimental data base of overwater and inland dispersion along the central California coast; to evaluate air-quality models presently being used by MMS for determining air-quality impacts from offshore emission sources; to evaluate various schemes for determining atmospheric stability and methods of determining atmospheric stability and methods of determining dispersion parameters (sigma-y and sigma-z) overwater; and to provide data needed for an overwater dispersion model presently under development by MMS.

  20. AN OPERATIONAL EVALUATION OF THE ETA - CMAQ AIR QUALITY FORECAST MODEL

    EPA Science Inventory

    The National Oceanic and Atmospheric Administration (NOAA), in partnership with the United States Environmental Protection Agency (EPA), are developing an operational, nationwide Air Quality Forecasting (AQF) system. An experimental phase of this program, which couples NOAA's Et...

  1. HVAC SYSTEMS AS EMISSION SOURCES AFFECTING INDOOR AIR QUALITY: A CRITICAL REVIEW

    EPA Science Inventory

    The study evaluates heating, ventilating, and air-conditioning (HVAC) systems as contaminant emission sources that affect indoor air quality (IAQ). Various literature sources and methods for characterizing HVAC emission sources are reviewed. Available methods include in situ test...

  2. Evaluation of the United States National Air Quality Forecast Capability experimental real-time predictions in 2010 using Air Quality System ozone and NO2 measurements

    NASA Astrophysics Data System (ADS)

    Chai, T.; Kim, H.-C.; Lee, P.; Tong, D.; Pan, L.; Tang, Y.; Huang, J.; McQueen, J.; Tsidulko, M.; Stajner, I.

    2013-10-01

    The National Air Quality Forecast Capability (NAQFC) project provides the US with operational and experimental real-time ozone predictions using two different versions of the three-dimensional Community Multi-scale Air Quality (CMAQ) modeling system. Routine evaluation using near-real-time AIRNow ozone measurements through 2011 showed better performance of the operational ozone predictions. In this work, quality-controlled and -assured Air Quality System (AQS) ozone and nitrogen dioxide (NO2) observations are used to evaluate the experimental predictions in 2010. It is found that both ozone and NO2 are overestimated over the contiguous US (CONUS), with annual biases of +5.6 and +5.1 ppbv, respectively. The annual root mean square errors (RMSEs) are 15.4 ppbv for ozone and 13.4 ppbv for NO2. For both species the overpredictions are most pronounced in the summer. The locations of the AQS monitoring sites are also utilized to stratify comparisons by the degree of urbanization. Comparisons for six predefined US regions show the highest annual biases for ozone predictions in Southeast (+10.5 ppbv) and for NO2 in the Lower Middle (+8.1 ppbv) and Pacific Coast (+7.1 ppbv) regions. The spatial distributions of the NO2 biases in August show distinctively high values in the Los Angeles, Houston, and New Orleans areas. In addition to the standard statistics metrics, daily maximum eight-hour ozone categorical statistics are calculated using the current US ambient air quality standard (75 ppbv) and another lower threshold (70 ppbv). Using the 75 ppbv standard, the hit rate and proportion of correct over CONUS for the entire year are 0.64 and 0.96, respectively. Summertime biases show distinctive weekly patterns for ozone and NO2. Diurnal comparisons show that ozone overestimation is most severe in the morning, from 07:00 to 10:00 local time. For NO2, the morning predictions agree with the AQS observations reasonably well, but nighttime concentrations are overpredicted by around

  3. The Use of Regulatory Air Quality Models to Develop Successful Ozone Attainment Strategies

    NASA Astrophysics Data System (ADS)

    Canty, T. P.; Salawitch, R. J.; Dickerson, R. R.; Ring, A.; Goldberg, D. L.; He, H.; Anderson, D. C.; Vinciguerra, T.

    2015-12-01

    The Environmental Protection Agency (EPA) recently proposed lowering the 8-hr ozone standard to between 65-70 ppb. Not all regions of the U.S. are in attainment of the current 75 ppb standard and it is expected that many regions currently in attainment will not meet the future, lower surface ozone standard. Ozone production is a nonlinear function of emissions, biological processes, and weather. Federal and state agencies rely on regulatory air quality models such as the Community Multi-Scale Air Quality (CMAQ) model and Comprehensive Air Quality Model with Extensions (CAMx) to test ozone precursor emission reduction strategies that will bring states into compliance with the National Ambient Air Quality Standards (NAAQS). We will describe various model scenarios that simulate how future limits on emission of ozone precursors (i.e. NOx and VOCs) from sources such as power plants and vehicles will affect air quality. These scenarios are currently being developed by states required to submit a State Implementation Plan to the EPA. Projections from these future case scenarios suggest that strategies intended to control local ozone may also bring upwind states into attainment of the new NAAQS. Ground based, aircraft, and satellite observations are used to ensure that air quality models accurately represent photochemical processes within the troposphere. We will highlight some of the improvements made to the CMAQ and CAMx model framework based on our analysis of NASA observations obtained by the OMI instrument on the Aura satellite and by the DISCOVER-AQ field campaign.

  4. PREFACE SPECIAL ISSUE ON MODEL EVALUATION: EVALUATION OF URBAN AND REGIONAL EULERIAN AIR QUALITY MODELS

    EPA Science Inventory

    The "Preface to the Special Edition on Model Evaluation: Evaluation of Urban and Regional Eulerian Air Quality Models" is a brief introduction to the papers included in a special issue of Atmospheric Environment. The Preface provides a background for the papers, which have thei...

  5. 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.

  6. Satellite Models for Global Environmental Change in the NASA Health and Air Quality Programs

    NASA Astrophysics Data System (ADS)

    Haynes, J.; Estes, S. M.

    2015-12-01

    Satellite remote sensing of the environment offers a unique vantage point that can fill in the gaps of environmental, spatial, and temporal data for tracking disease. Health and Air Quality providers and researchers are effective by the global environmental changes that are occurring and they need environmental data to study and understand the geographic, environmental, and meteorological differences in disease. This presentation maintains a diverse constellation of Earth observing research satellites and sponsors research in developing satellite data applications across a wide spectrum of areas including environmental health; infectious disease; air quality standards, policies, and regulations; and the impact of climate change on health and air quality. Successfully providing predictions with the accuracy and specificity required by decision makers will require advancements over current capabilities in a number of interrelated areas. These areas include observations, modeling systems, forecast development, application integration, and the research to operations transition process. This presentation will highlight many projects on which NASA satellites have been a primary partner with local, state, Federal, and international operational agencies over the past twelve years in these areas. Domestic and International officials have increasingly recognized links between environment and health. Health providers and researchers need environmental data to study and understand the geographic, environmental, and meteorological differences in disease. The presentation is directly related to Earth Observing systems and Global Health Surveillance and will present research results of the remote sensing environmental observations of earth and health applications, which can contribute to the health research. As part of NASA approach and methodology they have used Earth Observation Systems and Applications for Health Models to provide a method for bridging gaps of environmental

  7. PM2.5 analog forecast and Kalman filter post-processing for the Community Multiscale Air Quality (CMAQ) model

    NASA Astrophysics Data System (ADS)

    Djalalova, Irina; Delle Monache, Luca; Wilczak, James

    2015-10-01

    A new post-processing method for surface particulate matter (PM2.5) predictions from the National Oceanic and Atmospheric Administration (NOAA) developmental air quality forecasting system using the Community Multiscale Air Quality (CMAQ) model is described. It includes three main components: A real-time quality control procedure for surface PM2.5 observations; Model post-processing at each observational site using historical forecast analogs and Kalman filtering; Spreading the forecast corrections from the observation locations to the entire gridded domain.

  8. Global ozone and air quality: a multi-model assessment of risks to human health and crops

    NASA Astrophysics Data System (ADS)

    Ellingsen, K.; Gauss, M.; van Dingenen, R.; Dentener, F. J.; Emberson, L.; Fiore, A. M.; Schultz, M. G.; Stevenson, D. S.; Ashmore, M. R.; Atherton, C. S.; Bergmann, D. J.; Bey, I.; Butler, T.; Drevet, J.; Eskes, H.; Hauglustaine, D. A.; Isaksen, I. S. A.; Horowitz, L. W.; Krol, M.; Lamarque, J. F.; Lawrence, M. G.; van Noije, T.; Pyle, J.; Rast, S.; Rodriguez, J.; Savage, N.; Strahan, S.; Sudo, K.; Szopa, S.; Wild, O.

    2008-02-01

    Within ACCENT, a European Network of Excellence, eighteen atmospheric models from the U.S., Europe, and Japan calculated present (2000) and future (2030) concentrations of ozone at the Earth's surface with hourly temporal resolution. Comparison of model results with surface ozone measurements in 14 world regions indicates that levels and seasonality of surface ozone in North America and Europe are characterized well by global models, with annual average biases typically within 5-10 nmol/mol. However, comparison with rather sparse observations over some regions suggest that most models overestimate annual ozone by 15-20 nmol/mol in some locations. Two scenarios from the International Institute for Applied Systems Analysis (IIASA) and one from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) have been implemented in the models. This study focuses on changes in near-surface ozone and their effects on human health and vegetation. Different indices and air quality standards are used to characterise air quality. We show that often the calculated changes in the different indices are closely inter-related. Indices using lower thresholds are more consistent between the models, and are recommended for global model analysis. Our analysis indicates that currently about two-thirds of the regions considered do not meet health air quality standards, whereas only 2-4 regions remain below the threshold. Calculated air quality exceedances show moderate deterioration by 2030 if current emissions legislation is followed and slight improvements if current emissions reduction technology is used optimally. For the "business as usual" scenario severe air quality problems are predicted. We show that model simulations of air quality indices are particularly sensitive to how well ozone is represented, and improved accuracy is needed for future projections. Additional measurements are needed to allow a more quantitative assessment of the risks to

  9. NEW DEVELOPMENTS IN THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL

    EPA Science Inventory

    CMAQ model research and development is currently following two tracks at the Atmospheric Modeling Division of the USEPA. Public releases of the community model system for research and policy analysis is continuing on an annual interval with the latest release scheduled for Augus...

  10. Assimilation of surface and satellite observations with the Lotos-Euros air quality model and the ensemble Kalman filter technique

    NASA Astrophysics Data System (ADS)

    Eskes, H.; Curier, L.; Segers, A.

    2012-04-01

    LOTOS-EUROS is a chemistry transport model developed in the Netherlands, and is used for air quality assessments and forecasts. Operational air quality forecasts for the Netherlands concerning ozone and PM10 are made available on the RIVM webpage (http://www.lml.rivm.nl/) and are used to warn the population in case of predicted exceedances of air quality standards. Lotos-Euros is also contributing to the model-ensemble based air quality forecasts for Europe (MACC project, http://macc-raq.gmes-atmosphere.eu/index.php?op=get). Currently, the system is expanded to assimilate routine observations from European networks for ozone and PM10, as well as OMI NO2 satellite observations, based on the ensemble Kalman filter technique. This work is done in the context of the MACC project and contributes to the MACC air quality reanalyses for the years 2008 and 2009. The Ozone Monitoring Instrument (OMI) is a Dutch-Finnish instrument on the NASA EOS-Aura mission, and has a capability to detect boundary-layer NO2 with a unique resolution of about 20 km. In our contribution we will discuss the assimilation of NO2 tropospheric columns from the OMI instrument, the derivation of emissions and the changes in the emissions and concentrations over Europe for the period 2004-2010.

  11. Two-stage fuzzy-stochastic robust programming: a hybrid model for regional air quality management.

    PubMed

    Li, Yongping; Huang, Guo H; Veawab, Amornvadee; Nie, Xianghui; Liu, Lei

    2006-08-01

    In this study, a hybrid two-stage fuzzy-stochastic robust programming (TFSRP) model is developed and applied to the planning of an air-quality management system. As an extension of existing fuzzy-robust programming and two-stage stochastic programming methods, the TFSRP can explicitly address complexities and uncertainties of the study system without unrealistic simplifications. Uncertain parameters can be expressed as probability density and/or fuzzy membership functions, such that robustness of the optimization efforts can be enhanced. Moreover, economic penalties as corrective measures against any infeasibilities arising from the uncertainties are taken into account. This method can, thus, provide a linkage to predefined policies determined by authorities that have to be respected when a modeling effort is undertaken. In its solution algorithm, the fuzzy decision space can be delimited through specification of the uncertainties using dimensional enlargement of the original fuzzy constraints. The developed model is applied to a case study of regional air quality management. The results indicate that reasonable solutions have been obtained. The solutions can be used for further generating pollution-mitigation alternatives with minimized system costs and for providing a more solid support for sound environmental decisions. PMID:16933639

  12. Two-stage fuzzy-stochastic robust programming: a hybrid model for regional air quality management

    SciTech Connect

    Yongping Li; Guo H. Huang; Amornvadee Veawab; Xianghui Nie; Lei Liu

    2006-08-15

    In this study, a hybrid two-stage fuzzy-stochastic robust programming (TFSRP) model is developed and applied to the planning of an air-quality management system. As an extension of existing fuzzy-robust programming and two stage stochastic programming methods, the TFSRP can explicitly address complexities and uncertainties of the study system without unrealistic simplifications. Uncertain parameters can be expressed as probability density and/or fuzzy membership functions, such that robustness of the optimization efforts can be enhanced. Moreover, economic penalties as corrective measures against any infeasibilities arising from the uncertainties are taken into account. This method can, thus, provide a linkage to predefined policies determined by authorities that have to be respected when a modeling effort is undertaken. In its solution algorithm, the fuzzy decision space can be delimited through specification of the uncertainties using dimensional enlargement of the original fuzzy constraints. The developed model is applied to a case study of regional air quality management at two coal-fired power plants considered as major sulfur dioxide emission sources. The results indicate that reasonable solutions have been obtained. The solutions can be used for further generating pollution-mitigation alternatives with minimized system costs and for providing a more solid support for sound environmental decisions. 61 refs., 7 figs., 6 tabs.

  13. Modeling Study on Air Quality Improvement due to Mobile Source Emission control Plan in Seoul Metropolitan Area

    NASA Astrophysics Data System (ADS)

    Kim, Y. J.; Sunwoo, Y.; Hwang, I.; Song, S.; Sin, J.; Kim, D.

    2015-12-01

    A very high population and corresponding high number of vehicles in the Seoul Metropolitan Area (SMA) are aggravating the air quality of this region. The Korean government continues to make concerted efforts to improve air quality. One of the major policies that the Ministry of Environment of Korea enforced is "The Special Act for Improvement of Air Quality in SMA" and "The 1st Air Quality Management Plan of SMA". Mobile Source emission controls are an important part of the policy. Thus, it is timely to evaluate the air quality improvement due to the controls. Therefore, we performed a quantitative analysis of the difference in air quality using the Community Multiscale Air Quality (CMAQ) model and December, 2011 was set as the target period to capture the impact of the above control plans. We considered four fuel-type vehicle emission scenarios and compared the air quality improvement differences between them. The scenarios are as follows: no-control, gasoline vehicle control only, diesel vehicle control only, and control of both; utilizing the revised mobile source emissions from the Clean Air Policy Support System (CAPSS), which is the national emission inventory reflecting current policy.In order to improve the accuracy of the modeling data, we developed new temporal allocation coefficients based on traffic volume observation data and spatially reallocated the mobile source emissions using vehicle flow survey data. Furthermore, we calculated the PM10 and PM2.5 emissions of gasoline vehicles which is omitted in CAPSS.The results of the air quality modeling shows that vehicle control plans for both gasoline and diesel lead to a decrease of 0.65ppb~8.75ppb and 0.02㎍/㎥~7.09㎍/㎥ in NO2 and PM10 monthly average concentrations, respectively. The large percentage decreases mainly appear near the center of the metropolis. However, the largest NO2 decrease percentages are found in the northeast region of Gyeonggi-do, which is the province that surrounds the

  14. Space-Time Fusion Under Error in Computer Model Output: An Application to Modeling Air Quality

    EPA Science Inventory

    In the last two decades a considerable amount of research effort has been devoted to modeling air quality with public health objectives. These objectives include regulatory activities such as setting standards along with assessing the relationship between exposure to air pollutan...

  15. MODELING THE TRANSPORT AND CHEMICAL EVOLUTION OF ONSHORE AND OFFSHORE EMISSIONS AND THEIR IMPACT ON LOCAL AND REGIONAL AIR QUALITY USING A VARIABLE-GRID-RESOLUTION AIR QUALITY MODEL

    SciTech Connect

    Kiran Alapaty

    2003-12-01

    This document, the project's first semiannual report, summarizes the research performed from 04/17/2003 through 10/16/2003. Portions of the research in several of the project's eight tasks were completed, and results obtained are briefly presented. We have tested the applicability of two different atmospheric boundary layer schemes for use in air quality model simulations. Preliminary analysis indicates that a scheme that uses sophisticated atmospheric boundary physics resulted in better simulation of atmospheric circulations. We have further developed and tested a new surface data assimilation technique to improve meteorological simulations, which will also result in improved air quality model simulations. Preliminary analysis of results indicates that using the new data assimilation technique results in reduced modeling errors in temperature and moisture. Ingestion of satellite-derived sea surface temperatures into the mesoscale meteorological model led to significant improvements in simulated clouds and precipitation compared to that obtained using traditional analyzed sea surface temperatures. To enhance the capabilities of an emissions processing system so that it can be used with our variable-grid-resolution air quality model, we have identified potential areas for improvements. Also for use in the variable-grid-resolution air quality model, we have tested a cloud module offline for its functionality, and have implemented and tested an efficient horizontal diffusion algorithm within the model.

  16. Technology Needs Assessment of an Atmospheric Observation System for Multidisciplinary Air Quality/Meteorology Missions, Part 2

    NASA Technical Reports Server (NTRS)

    Alvarado, U. R.; Bortner, M. H.; Grenda, R. N.; Brehm, W. F.; Frippel, G. G.; Alyea, F.; Kraiman, H.; Folder, P.; Krowitz, L.

    1982-01-01

    The technology advancements that will be necessary to implement the atmospheric observation systems are considered. Upper and lower atmospheric air quality and meteorological parameters necessary to support the air quality investigations were included. The technology needs were found predominantly in areas related to sensors and measurements of air quality and meteorological measurements.

  17. The development and implementation of a mesoscale modeling system for simulating the meteorology and air quality situation in the Mae Moh Valley

    NASA Astrophysics Data System (ADS)

    Kowalewsky, Karen Jean

    2001-08-01

    The Mae Moh Valley region of northern Thailand experiences frequent pollutant fumigation events during the annual cool season. The onset and magnitude of these events are driven by the synoptic scale and mesoscale conditions that develop over the Valley during the cool season. A conclusion from previous studies conducted in the Valley was that to properly predict the onset and magnitude of the fumigation events, a three dimensional wind field generated using a mesoscale meteorological model needed to be used in a mesoscale transport and dispersion model. The results of the previous studies led to the modeling analysis presented in this dissertation. The research hypothesis was that it would be possible to develop a mesoscale dispersion modeling system that could simulate the Valley fumigation events. The null hypothesis was that the air dispersion modeling system could not simulate the fumigation events. The Penn State/NCAR Mesoscale Meteorological Model, Version 5 (MM5) was used to generate the mesoscale meteorological parameters used as input to the United States Environmental Protection Agency (USEPA) CALMET/CALPUFF mesoscale dispersion and transport model. These models were used to forecast one fumigation event observed in 1997. Three model scenarios were considered for the fumigation event. The differences in the model scenarios were a function of modifications to terrain and horizontal and vertical grid resolutions used by MM5. Output from the combined MM5/CALMET/CALPUFF was compared with observations to document the modeling system's strengths and limitations. The results from this study indicated that MM5 appeared to be capable of simulating the temperature profile required to produce a fumigation event in the Valley. However, due to errors in the input meteorological data, MM5 was not capable of forecasting the light and variable wind conditions present within the Valley prior to and during the fumigation events. These wind field errors contributed to

  18. Advances in Linked Air Quality, Farm Management and Biogeochemistry Models to Address Bidirectional Ammonia Flux in CMAQ

    EPA Science Inventory

    Recent increases in anthropogenic inputs of nitrogen to air, land and water media pose a growing threat to human health and ecosystems. Modeling of air-surface N flux is one area in need of improvement. Implementation of a linked air quality and cropland management system is de...

  19. "Advances in Linked Air Quality, Farm Management and Biogeochemistry Models to Address Bidrectional Ammonia Flux in CMAQ"

    EPA Science Inventory

    Recent increases in anthropogenic inputs of nitrogen to air, land and water media pose a growing threat to human health and ecosystems. Modeling of air-surface N flux is one area in need of improvement. Implementation of a linked air quality and cropland management system is de...

  20. An integrated computer modeling environment for regional land use, air quality, and transportation planning

    SciTech Connect

    Hanley, C.J.; Marshall, N.L.

    1997-04-01

    The Land Use, Air Quality, and Transportation Integrated Modeling Environment (LATIME) represents an integrated approach to computer modeling and simulation of land use allocation, travel demand, and mobile source emissions for the Albuquerque, New Mexico, area. This environment provides predictive capability combined with a graphical and geographical interface. The graphical interface shows the causal relationships between data and policy scenarios and supports alternative model formulations. Scenarios are launched from within a Geographic Information System (GIS), and data produced by each model component at each time step within a simulation is stored in the GIS. A menu-driven query system is utilized to review link-based results and regional and area-wide results. These results can also be compared across time or between alternative land use scenarios. Using this environment, policies can be developed and implemented based on comparative analysis, rather than on single-step future projections. 16 refs., 3 figs., 2 tabs.

  1. Use of air quality modeling results as exposure estimates in health studies

    NASA Astrophysics Data System (ADS)

    Holmes, H. A.; Ivey, C.; Friberg, M.; Zhai, X.; Balachandran, S.; Hu, Y.; Russell, A. G.; Mulholland, J. A.; Tolbert, P. E.; Sarnat, S. E.

    2013-12-01

    Air pollutant measurements from regulatory monitoring networks are commonly utilized in combination with spatial averaging techniques to develop air quality metrics for use in epidemiologic studies. While these data provide useful indicators for air pollution in a region, their temporal and spatial information are limited. The growing availability of spatially resolved health data sets (i.e., resident and county level patient records) provides an opportunity to develop and apply corresponding spatially resolved air quality metrics as enhanced exposure estimates when investigating the impact of air pollution on health outcomes. Additionally, the measured species concentrations from monitoring networks cannot directly identify specific emission sources or characterize pollutant mixtures. However, these observations in combination with chemical transport models (e.g., CMAQ) and source apportionment methods (e.g., CMB and PMF) can be used to characterize pollutant mixtures, sources and species impacting both individual locations and wider areas. Extensive analysis using a combination of air quality modeling approaches and observations may be beneficial for health studies whose goal is to assess the health impacts of pollutant mixtures, in both spatially resolved and time-series health analyses. As part of the Southeastern Center for Air Pollution and Epidemiology (SCAPE) unique methods have been developed to effectively analyze air pollution and air quality modeling data to better understand how emission sources combine to impact air quality and to provide air quality metrics for use in health assessments. This presentation will discuss the air quality modeling techniques being utilized in SCAPE investigations that are aimed at providing enhanced exposure metrics for use in spatially resolved (state of Georgia) and time-series epidemiologic analyses (St. Louis and Atlanta). To generate spatially resolved daily air quality estimates of species concentrations and source

  2. Multiscale air quality modeling of the Northeastern United States

    NASA Astrophysics Data System (ADS)

    Kumar, Naresh; Russell, Armistead G.

    The Urban and Regional Multiscale (URM) model has been used to study the ozone problem in the northeastern United States. The model was applied to a multiday ozone episode extending from 2 July 1988 to 8 July 1988. The URM model is particularly suitable for application to the Northeast as there is a dense network of urban centers along with large rural areas, and the model allows the use of variable grid sizes to effectively capture the pollutant dynamics while being computationally efficient. This study particularly concentrates on how spatial grid resolution affects results, particularly in the Northeast Corridor, a string of urban centers extending from Washington D.C. to Boston. Three different grid systems are employed in the model simulations to examine this issue. The most dynamic grid system uses grid sizes varying from 4.625 to 74 km, with the finest grids concentrated in the Northeast Corridor. The uniform grid system uses a uniform grid size of 18.5 km similar to that used in the regional oxidant model (ROM). The intermediate grid system uses grid sizes varying from 4.625 to 18.5 km. When finer grids are used over the urban areas, as in the intermediate and the most dynamic grid systems, the model predicted higher peak ozone concentrations with greater detail. Sensitivity calculations were performed to quantify the effect of various inputs on the predicted ozone. Effects of zeroing the initial conditions persisted until 7 July 1988. When using background levels of species concentrations as initial conditions, the effect lasted only for two days of simulation. Boundary conditions impacted the ozone concentrations near the boundary cells only. Emission inputs were the major factor in producing the large concentrations of ozone predicted in the Northeast Corridor. The URM model was also used to study ozone control strategy issues in the Northeast Corridor. A suite of simulations was performed where anthropogenic NO x and VOC emission levels were reducd

  3. The effects of advection solvers on the performance of air quality models

    SciTech Connect

    Tanrikulu, S.; Odman, M.T.

    1996-12-31

    The available numerical solvers for the advection term in the chemical species conservation equation have different properties, and consequently introduce different types of errors. These errors can affect the performance of air quality models and lead to biases in model results. In this study, a large number of advection solvers have been studied and six of them were identified as having potential for use in photochemical models. The identified solvers were evaluated extensively using various numerical tests that are relevant to air quality simulations. Among the solvers evaluated, three of them showed better performance in terms of accuracy and some other characteristics such as conservation of mass and positivity. They are the solvers by Bott, Yuamartino, and Dabdub and Seinfeld. These three solvers were incorporated into the SARMAP Air Quality Model (SAQM) and the August 3-6, 1990 ozone episode in the San Joaquin Valley of California was simulated with each. A model performance analysis was conducted for each simulation using the rich air quality database of the 1990 San Joaquin Valley Air Quality Study. The results of the simulations were compared with each other and the effects of advection solvers on the performance of the model are discussed.

  4. Evaluation of the operational Air-Quality forecast model for Austria ALARO-CAMx

    NASA Astrophysics Data System (ADS)

    Flandorfer, Claudia; Hirtl, Marcus

    2016-04-01

    The Air-Quality model for Austria (AQA) is operated at ZAMG by order of the regional governments of Vienna, Lower Austria, and Burgenland since 2005. The emphasis of this modeling system is on predicting ozone peaks in the North-east Austrian flatlands. The modeling system is currently a combination of the meteorological model ALARO and the photochemical dispersion model CAMx. Two modeling domains are used with the highest resolution (5 km) in the alpine region. Various extensions with external data sources have been conducted in the past to improve the daily forecasts of the model, e.g. data assimilation of O3- and PM10-observations from the Austrian measurement network (with optimum interpolation method technique), MACC-II boundary conditions; combination of high resolved emission inventories for Austria with TNO and EMEP data. The biogenic emissions are provided by the SMOKE model. The model runs 2 times per day for a period of 48 hours. ZAMG provides daily forecasts of O3, PM10 and NO2 to the regional governments of Austria. The evaluation of these forecasts is done for January to September 2015, with the main focus on the summer peaks of ozone. The measurements of the Air-Quality stations are compared with the punctual forecasts at the sites of the stations and the area forecasts for every province of Austria. Several heat waves occurred between June and September 2015 (new temperature records for St. Pölten and Linz). During these periods the information threshold for ozone has been exceeded 19 times, mostly in the Eastern regions of Austria. Values above the alert threshold have been measured at some stations in Lower Austria and Vienna at the beginning of July. For the evaluation, the results for the periods with exceedances in Eastern Austria will be discussed in detail.

  5. Simulating smoke transport from wildland fires with a regional-scale air quality model: Sensitivity to uncertain wind fields

    NASA Astrophysics Data System (ADS)

    Garcia-Menendez, Fernando; Hu, Yongtao; Odman, Mehmet Talat

    2013-06-01

    Uncertainties associated with meteorological inputs which are propagated through atmospheric chemical transport models may constrain their ability to replicate the effects of wildland fires on air quality. Here, we investigate the sensitivity of predicted fine particulate matter (PM2.5) levels to uncertain wind fields by simulating the air quality impacts of two fires on an urban area with the Community Multiscale Air Quality modeling system (CMAQ). Brute-force sensitivity analyses show that modeled concentrations at receptors downwind from the fires are highly sensitive to variations in wind speed and direction. Additionally, uncertainty in wind fields produced with the Weather Research and Forecasting model was assessed by evaluating meteorological predictions against surface and upper air observations. Significant differences between predicted and observed wind fields were identified. Simulated PM2.5 concentrations at urban sites displayed large sensitivities to wind perturbations within the error range of meteorological inputs. The analyses demonstrate that normalized errors in CMAQ predictions attempting to model the regional impacts of fires on PM2.5 levels could be as high as 100% due to inaccuracies in wind data. Meteorological drivers may largely account for the considerable discrepancies between monitoring site observations and predicted concentrations. The results of this study demonstrate that limitations in fire-related air quality simulations cannot be overcome by solely improving emission rates.

  6. Mexico City air quality research initiative, volume 3, modeling and simulation

    SciTech Connect

    Mauzy, A.

    1994-06-01

    The objective of the modeling and simulation task was to develop, test, and apply an appropriate set of models that could translate emission changes into air quality changes. Specifically, we wanted to develop models that could describe how existing measurements of ozone (O{sub 3}), carbon monoxide (CO), and sulfur dioxide (SO{sub 2}) would be expected to change if their emissions were changed. The modeling must be able to address the effects of difference in weather conditions and changes in land use as well as the effects of changes in emission levels. It must also be able to address the effects of changes in the nature and distribution of the emissions as well as changes in the total emissions. A second objective was to provide an understanding of the conditions that lead to poor air quality in Mexico City. We know in a general sense that Mexico City`s poor air quality is the result of large quantities of emissions in a confined area that is subject to light winds, but we did not know much about many aspects of the problem. For example, is the air quality on a given day primarily the result of emissions on that day...or is there an important carryover from previous nights and days? With a good understanding of the important meteorological circumstances that lead to poor air quality, we learn what it take duce an accurate forecast of impending quality so that we can determine the advisability of emergency measures.

  7. Remote Sensing Characterization of the Urban Landscape for Improvement of Air Quality Modeling

    NASA Technical Reports Server (NTRS)

    Quattrochi, Dale A.; Estes, Maurice G., Jr.; Khan, Maudood

    2005-01-01

    The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, in moderating ground-level ozone and air temperature, compared to "business as usual" simulations in which heat island mitigation strategies are not applied. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data has been found to better characterize low densityhburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for fiture scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the state Environmental Protection agency to evaluate how these

  8. Modeling air quality during the California Regional PM 10/PM 2.5 Air Quality Study (CPRAQS) using the UCD/CIT Source Oriented Air Quality Model - Part II. Regional source apportionment of primary airborne particulate matter

    NASA Astrophysics Data System (ADS)

    Ying, Qi; Lu, Jin; Kaduwela, Ajith; Kleeman, Michael

    A comprehensive air quality modeling project was carried out to simulate regional source contributions to primary airborne particle concentrations in California's central Valley. A 3-week stagnation episode lasting from December 15, 2000 to January 7, 2001, was chosen for study using the air quality and meteorological data collected during the California Regional PM 10/PM 2.5 Air Quality Study (CRPAQS). The UCD/CIT source oriented air quality model was applied to this episode using both the source-oriented external mixture configuration and an internal mixture with artificial tracers so that source contribution information could be retrieved in less time. The majority of the predicted and measured primary airborne particulate matter mass was composed of elemental carbon (EC) and organic carbon (OC). Previous work has shown that base case EC and OC predictions made by the UCD/CIT model are in good agreement with observations. Model results from the current study show that the highest EC and OC concentrations occur in urban areas and along transportation corridors where primary emissions are largest. Lower concentrations of primary EC and OC are predicted at rural locations in the San Joaquin Valley (SJV). Source contributions predicted by the UCD/CIT air quality model were compared to receptor-oriented source apportionment results produced by the Chemical Mass Balance (CMB) model at Fresno and Angiola. The relative contributions from major sources predicted by the UCD/CIT model agree with the CMB model results, building confidence in the accuracy of the UCD/CIT model predictions at locations where the CMB results are not available. Wood smoke was identified as the major regional source of primary OC in airborne particles in the winter SJV episode, accounting for approximately 50% of the total PM 2.5. Diesel engines were also found to be a significant contributor to primary PM 2.5 OC and the largest contributor to the predicted PM 2.5 EC averaged over a typical day

  9. Dynamic evaluation of a regional air quality model: Assessing the emissions-induced weekly ozone cycle

    NASA Astrophysics Data System (ADS)

    Pierce, Thomas; Hogrefe, Christian; Trivikrama Rao, S.; Porter, P. Steven; Ku, Jia-Yeong

    2010-09-01

    Air quality models are used to predict changes in pollutant concentrations resulting from envisioned emission control policies. Recognizing the need to assess the credibility of air quality models in a policy-relevant context, we perform a dynamic evaluation of the Community Multiscale Air Quality (CMAQ) modeling system for the "weekend ozone effect" to determine if observed changes in ozone due to weekday-to-weekend (WDWE) reductions in precursor emissions can be accurately simulated. The weekend ozone effect offers a unique opportunity for dynamic evaluation, as it is a widely documented phenomenon that has persisted since the 1970s. In many urban areas of the Unites States, higher ozone has been observed on weekends than weekdays, despite dramatically reduced emissions of ozone precursors (nitrogen oxides [NO x] and volatile organic compounds [VOCs]) on weekends. More recent measurements, however, suggest shifts in the spatial extent or reductions in WDWE ozone differences. Using 18 years (1988-2005) of observed and modeled ozone and temperature data across the northeastern United States, we re-examine the long-term trends in the weekend effect and confounding factors that may be complicating the interpretation of this trend and explore whether CMAQ can replicate the temporal features of the observed weekend effect. The amplitudes of the weekly ozone cycle have decreased during the 18-year period in our study domain, but the year-to-year variability in weekend minus weekday (WEWD) ozone amplitudes is quite large. Inter-annual variability in meteorology appears to influence WEWD differences in ozone, as well as WEWD differences in VOC and NO x emissions. Because of the large inter-annual variability, modeling strategies using a single episode lasting a few days or a few episodes in a given year may not capture the WEWD signal that exists over longer time periods. The CMAQ model showed skill in predicting the absolute values of ozone concentrations during the

  10. 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.

  11. Simulating present-day and future air quality as climate changes: Model evaluation

    NASA Astrophysics Data System (ADS)

    Dawson, John P.; Racherla, Pavan N.; Lynn, Barry H.; Adams, Peter J.; Pandis, Spyros N.

    The global-regional climate-air pollution modeling system (GRE-CAPS) has been developed, coupling an existing general circulation model/chemical transport model (GCM/CTM), a regional meteorological model, and a regional chemical transport model. This system is intended to enable studies of the effects of changes in climate, intercontinental transport, and emissions on regional and urban air quality. The GRE-CAPS system consists of the GISS II' GCM/CTM, the MM5 regional meteorological model, and the PMCAMx regional CTM. The modeling system is evaluated for the present day, with comparisons between model-predicted, measured ozone, and speciated PM 2.5 concentrations. The ability of the model to predict present-day concentrations of ozone and PM 2.5 is compared to that of PMCAMx when used for retrospective modeling. Comparisons between model-predicted temperatures and precipitation are also made. The model was used to simulate five present-day Januaries and six present-day Julys. The biases and errors in GRE-CAPS-predicted ozone concentrations were similar to those of PMCAMx when used for standard retrospective modeling. The fractional biases in mean daily peak ozone concentration and mean daily maximum 8-h average ozone concentration are both <10%. The model-predicted distribution of peak hourly and daily maximum 8-h average values agreed rather well with the measured distribution. There is less agreement between the model and measurements in the number of hours with ozone mixing ratios >70 or 80 ppb, though this is also the case with standard PMCAMx modeling. The predictions of PM 2.5 concentrations by GRE-CAPS were also of similar quality to those of PMCAMx driven by historical meteorology. The fractional biases in the predictions of total PM 2.5, sulfate, ammonium, and nitrate were all <25% in both January and July. The model agrees well with organic PM 2.5 measurements from the IMPROVE network, though there is less agreement with measurements from the STN network

  12. VERIFICATION AND USES OF THE ENVIRONMENTAL PROTECTION AGENCY (EPA) INDOOR AIR QUALITY MODEL

    EPA Science Inventory

    The paper describes a set of experiments used to verify an indoor air quality (IAQ) model for estimating the impact of various pollution sources on IAQ in a multiroom building. he model treats each room as a well-mixed chamber that contains pollution sources and sinks. he model a...

  13. Impact of HONO sources on the performance of mesoscale air quality models

    NASA Astrophysics Data System (ADS)

    Gonçalves, M.; Dabdub, D.; Chang, W. L.; Jorba, O.; Baldasano, J. M.

    2012-07-01

    Nitrous acid (HONO) photolysis constitutes a primary source of OH in the early morning, which leads to changes in model gas-phase and particulate matter concentrations. However, state-of-the-art models of chemical mechanisms share a common representation of gas-phase chemistry leading to HONO that fails in reproducing the observed profiles. Hence, there is a growing interest in improving the definition of additional HONO sources within air quality models, i.e. direct emissions or heterogeneous reactions. In order to test their feasibility under atmospheric conditions, the WRF-ARW/HERMES/CMAQ modeling system is applied with high horizontal resolution (4 × 4 km2) to Spain for November 24-27, 2008. HONO modeled sources include: (1) direct emissions from on-road transport; NO2 hydrolysis on aerosol and ground surfaces, the latter with (2) kinetics depending exclusively on available surfaces for reaction and (3) refined kinetics considering also relative humidity dependence; and (4) photoenhanced NO2 reduction on ground surfaces. The DOMINO measurement campaign performed in El Arenosillo (Southern Spain) provides valuable HONO observations. Modeled HONO results are consistently below observations, even when the most effective scenario is assessed, corresponding to contributions of direct emissions and NO2 hydrolysis with the simplest kinetics parameterization. With the additional sources of HONO, PM2.5 predictions can be up to 14% larger in urban areas. Quantified impacts on secondary pollutants have to be taken as a low threshold, due to the proven underestimation of HONO levels. It is fundamental to improve HONO sources definition within air quality models, both for the scientific community and decision makers.

  14. Local-Scale Air Quality Modeling in Support of Human Health and Exposure Research (Invited)

    NASA Astrophysics Data System (ADS)

    Isakov, V.

    2010-12-01

    Spatially- and temporally-sparse information on air quality is a key concern for air-pollution-related environmental health studies. Monitor networks are sparse in both space and time, are costly to maintain, and are often designed purposely to avoid detecting highly localized sources. Recent studies have shown that more narrowly defining the geographic domain of the study populations and improvements in the measured/estimated ambient concentrations can lead to stronger associations between air pollution and hospital admissions and mortality records. Traditionally, ambient air quality measurements have been used as a primary input to support human health and exposure research. However, there is increasing evidence that the current ambient monitoring network is not capturing sharp gradients in exposure due to the presence of high concentration levels near, for example, major roadways. Many air pollutants exhibit large concentration gradients near large emitters such as major roadways, factories, ports, etc. To overcome these limitations, researchers are now beginning to use air quality models to support air pollution exposure and health studies. There are many advantages to using air quality models over traditional approaches based on existing ambient measurements alone. First, models can provide spatially- and temporally-resolved concentrations as direct input to exposure and health studies and thus better defining the concentration levels for the population in the geographic domain. Air quality models have a long history of use in air pollution regulations, and supported by regulatory agencies and a large user community. Also, models can provide bidirectional linkages between sources of emissions and ambient concentrations, thus allowing exploration of various mitigation strategies to reduce risk to exposure. In order to provide best estimates of air concentrations to support human health and exposure studies, model estimates should consider local-scale features

  15. Construction and application of an intelligent air quality monitoring system for healthcare environment.

    PubMed

    Yang, Chao-Tung; Liao, Chi-Jui; Liu, Jung-Chun; Den, Walter; Chou, Ying-Chyi; Tsai, Jaw-Ji

    2014-02-01

    Indoor air quality monitoring in healthcare environment has become a critical part of hospital management and policy. Manual air sampling and analysis are cost-inhibitive and do not provide real-time air quality data and response measures. In this month-long study over 14 sampling locations in a public hospital in Taiwan, we observed a positive correlation between CO(2) concentration and population, total bacteria, and particulate matter concentrations, thus monitoring CO(2) concentration as a general indicator for air quality could be a viable option. Consequently, an intelligent environmental monitoring system consisting of a CO(2)/temperature/humidity sensor, a digital plug, and a ZigBee Router and Coordinator was developed and tested. The system also included a backend server that received and analyzed data, as well as activating ventilation and air purifiers when CO(2) concentration exceeded a pre-set value. Alert messages can also be delivered to offsite users through mobile devices. PMID:24487985

  16. RAQ-A Random Forest Approach for Predicting Air Quality in Urban Sensing Systems.

    PubMed

    Yu, Ruiyun; Yang, Yu; Yang, Leyou; Han, Guangjie; Move, Oguti Ann

    2016-01-01

    Air quality information such as the concentration of PM2.5 is of great significance for human health and city management. It affects the way of traveling, urban planning, government policies and so on. However, in major cities there is typically only a limited number of air quality monitoring stations. In the meantime, air quality varies in the urban areas and there can be large differences, even between closely neighboring regions. In this paper, a random forest approach for predicting air quality (RAQ) is proposed for urban sensing systems. The data generated by urban sensing includes meteorology data, road information, real-time traffic status and point of interest (POI) distribution. The random forest algorithm is exploited for data training and prediction. The performance of RAQ is evaluated with real city data. Compared with three other algorithms, this approach achieves better prediction precision. Exciting results are observed from the experiments that the air quality can be inferred with amazingly high accuracy from the data which are obtained from urban sensing. PMID:26761008

  17. RAQ–A Random Forest Approach for Predicting Air Quality in Urban Sensing Systems

    PubMed Central

    Yu, Ruiyun; Yang, Yu; Yang, Leyou; Han, Guangjie; Move, Oguti Ann

    2016-01-01

    Air quality information such as the concentration of PM2.5 is of great significance for human health and city management. It affects the way of traveling, urban planning, government policies and so on. However, in major cities there is typically only a limited number of air quality monitoring stations. In the meantime, air quality varies in the urban areas and there can be large differences, even between closely neighboring regions. In this paper, a random forest approach for predicting air quality (RAQ) is proposed for urban sensing systems. The data generated by urban sensing includes meteorology data, road information, real-time traffic status and point of interest (POI) distribution. The random forest algorithm is exploited for data training and prediction. The performance of RAQ is evaluated with real city data. Compared with three other algorithms, this approach achieves better prediction precision. Exciting results are observed from the experiments that the air quality can be inferred with amazingly high accuracy from the data which are obtained from urban sensing. PMID:26761008

  18. Air quality monitoring system using lichens as bioindicators in Central Argentina.

    PubMed

    Estrabou, Cecilia; Filippini, Edith; Soria, Juan Pablo; Schelotto, Gabriel; Rodriguez, Juan Manuel

    2011-11-01

    Air quality studies with bioindicators have not been well developed in South America. In the city of Córdoba, there are not permanent air pollutant measurements by equipment. In order to develop an air quality biomonitoring system using lichens, we applied a systematic sampling in the city of Córdoba, Argentina. A total of 341 plots were sampled in the area of the city which is a square of 24 × 24 km. In each sample plot we selected three phorophytes and estimated the frequency and cover of lichen species growing at 1.5 m on trunks. We also calculated the Index of Atmospheric Purity (IAP) using lichen frequencies. Maps with number of lichen species, cover values, and IAP were performed. The lichen community was described with nine species where Physcia undulata and Physcia endochryscea were the most frequent. Moreover, these two species were dominant in the community with the highest cover index. The central area of the city is considered a lichen desert with poor air quality. The southeast and northwest areas of the city showed the highest IAP values and number of species. In general, the city shows fair air quality and few areas with good and very good air quality. PMID:21336488

  19. Evaluation of a unified regional air-quality modeling system (AURAMS) using PrAIRie2005 field study data: The effects of emissions data accuracy on particle sulphate predictions

    NASA Astrophysics Data System (ADS)

    Cho, S.; Makar, P. A.; Lee, W. S.; Herage, T.; Liggio, J.; Li, S. M.; Wiens, B.; Graham, L.

    The effects of the accuracy of major-point source emissions input data on the predictions of a regional air-quality model (AURAMS) were investigated through a series of scenario simulations. The model domain and time period were chosen to correspond to that of PrAIRie2005, an air-quality field study with airborne and ground-based mobile measurement platforms that took place between August 12th and September 7th, 2005, over the city of Edmonton, Alberta, Canada. The emissions data from standard sources for three coal-fired power-plants located west (typically upwind) of the city were compared to the continuous emissions monitoring system (CEMS) taking place at the time of the study - the latter showed that the original emissions inventory data considerably overestimated NO x, SO 2, and primary particulate emissions during the study period. Further field investigation (stack sampling) in the fall of 2006 showed that the measured primary particle size distribution and chemical speciation for the emissions were strikingly different from the distribution and speciation originally used in the model. The measured emissions were used to scale existing emissions data in accord with the CEMS and in-stack measurements. The effects of these improvements to the emissions data were examined sequentially in nested AURAMS simulations (finest horizontal resolution 3 km), and were compared to airborne aerosol mass spectrometer (Aerodyne AMS) measurements of particle sulphate, and particle distributions from an airborne passive cavity aerosol spectrometer probe (PCASP). The emissions of SO 2 had the greatest impact on predicted PM 1 sulphate, while the primary particle size distribution and chemical speciation had a smaller role. The revised emissions data greatly improved the comparisons between observations and model values, though over-predictions of fine-mode sulphate still occur near the power-plants, with the use of the revised emissions data. The modified emissions also had a

  20. Seasonal versus Episodic Performance Evaluation for an Eulerian Photochemical Air Quality Model

    SciTech Connect

    Jin, Ling; Brown, Nancy J.; Harley, Robert A.; Bao, Jian-Wen; Michelson, Sara A; Wilczak, James M

    2010-04-16

    This study presents detailed evaluation of the seasonal and episodic performance of the Community Multiscale Air Quality (CMAQ) modeling system applied to simulate air quality at a fine grid spacing (4 km horizontal resolution) in central California, where ozone air pollution problems are severe. A rich aerometric database collected during the summer 2000 Central California Ozone Study (CCOS) is used to prepare model inputs and to evaluate meteorological simulations and chemical outputs. We examine both temporal and spatial behaviors of ozone predictions. We highlight synoptically driven high-ozone events (exemplified by the four intensive operating periods (IOPs)) for evaluating both meteorological inputs and chemical outputs (ozone and its precursors) and compare them to the summer average. For most of the summer days, cross-domain normalized gross errors are less than 25% for modeled hourly ozone, and normalized biases are between {+-}15% for both hourly and peak (1 h and 8 h) ozone. The domain-wide aggregated metrics indicate similar performance between the IOPs and the whole summer with respect to predicted ozone and its precursors. Episode-to-episode differences in ozone predictions are more pronounced at a subregional level. The model performs consistently better in the San Joaquin Valley than other air basins, and episodic ozone predictions there are similar to the summer average. Poorer model performance (normalized peak ozone biases <-15% or >15%) is found in the Sacramento Valley and the Bay Area and is most noticeable in episodes that are subject to the largest uncertainties in meteorological fields (wind directions in the Sacramento Valley and timing and strength of onshore flow in the Bay Area) within the boundary layer.

  1. Using aircraft and satellite observations to improve regulatory air quality models

    NASA Astrophysics Data System (ADS)

    Canty, T. P.; Vinciguerra, T.; Anderson, D. C.; Carpenter, S. F.; Goldberg, D. L.; Hembeck, L.; Montgomery, L.; Liu, X.; Salawitch, R. J.; Dickerson, R. R.

    2014-12-01

    Federal and state agencies rely on EPA approved models to develop attainment strategies that will bring states into compliance with the National Ambient Air Quality Standards (NAAQS). We will describe modifications to the Community Multi-Scale Air Quality (CMAQ) model and Comprehensive Air Quality Model with Extensions (CAMx) frameworks motivated by analysis of NASA satellite and aircraft measurements. Observations of tropospheric column NO2 from OMI have already led to the identification of an important deficiency in the chemical mechanisms used by models; data collected during the DISCOVER-AQ field campaign has been instrumental in devising an improved representation of the chemistry of nitrogen species. Our recent work has focused on the use of: OMI observations of tropospheric O3 to assess and improve the representation of boundary conditions used by AQ models, OMI NO2 to derive a top down NOx emission inventory from commercial shipping vessels that affect air quality in the Eastern U.S., and OMI HCHO to assess the C5H8 emission inventories provided by bioegenic emissions models. We will describe how these OMI-driven model improvements are being incorporated into the State Implementation Plans (SIPs) being prepared for submission to EPA in summer 2015 and how future modeling efforts may be impacted by our findings.

  2. Air Quality Model Evaluation International Initiative (AQMEII) - Utrecht, Netherlands The May 8, 2012

    EPA Science Inventory

    The 4th workshop of the Air Quality Model Evaluation International Initiative (AQMEII) was held on May 8 in Utrecht, The Netherlands, in conjunction with the NATO/SPS International Technical Meeting on Air Pollution Modeling and Its Application. AQMEII was launched in 2009 as a l...

  3. The AQMEII Two-Continent Regional Air Quality Model Evaluation Study: Fueling Ideas with Unprecedented Data

    EPA Science Inventory

    Although strong collaborations in the air pollution field have existed among the North American (NA) and European (EU) countries over the past five decades, regional-scale air quality model developments and model performance evaluations have been carried out independently unlike ...

  4. CASE STUDIES IN THE APPLICATION OF AIR QUALITY MODELING IN ENVIRONMENTAL DECISION MAKING: SUMMARY AND RECOMMENDATIONS

    EPA Science Inventory

    Eleven case studies of the application of air quality models were undertaken in order to examine the problems encountered when trying to use these models in making environmental policy decisions. The case studies of air pollution control decisions describe the decision process, t...

  5. Measuring the value of air quality: application of the spatial hedonic model.

    PubMed

    Kim, Seung Gyu; Cho, Seong-Hoon; Lambert, Dayton M; Roberts, Roland K

    2010-03-01

    This study applies a hedonic model to assess the economic benefits of air quality improvement following the 1990 Clean Air Act Amendment at the county level in the lower 48 United States. An instrumental variable approach that combines geographically weighted regression and spatial autoregression methods (GWR-SEM) is adopted to simultaneously account for spatial heterogeneity and spatial autocorrelation. SEM mitigates spatial dependency while GWR addresses spatial heterogeneity by allowing response coefficients to vary across observations. Positive amenity values of improved air quality are found in four major clusters: (1) in East Kentucky and most of Georgia around the Southern Appalachian area; (2) in a few counties in Illinois; (3) on the border of Oklahoma and Kansas, on the border of Kansas and Nebraska, and in east Texas; and (4) in a few counties in Montana. Clusters of significant positive amenity values may exist because of a combination of intense air pollution and consumer awareness of diminishing air quality. PMID:20376167

  6. NESTED GRID MODELING APPROACH FOR ASSESSING URBAN OZONE AIR QUALITY

    EPA Science Inventory

    This paper describes an effort to interface the modeled concentrations and other outputs of the Regional Oxidant Model (ROM) as an alternative set of input files to apply in Urban Airshed Model (UAM) simulations. ive different days exhibiting high ozone concentrations during the ...

  7. HVAC SYSTEMS AS A TOOL IN CONTROLLING INDOOR AIR QUALITY: A LITERATURE REVIEW

    EPA Science Inventory

    The report gives results of a review of literature on the use of heating, ventilating, and air-conditioning (HVAC) systems to control indoor air quality (IAQ). Although significant progress has been made in reducing the energy consumption of HVAC systems, their effect on indoor a...

  8. Improvement of the multilayer perceptron for air quality modelling through an adaptive learning scheme

    NASA Astrophysics Data System (ADS)

    Hoi, K. I.; Yuen, K. V.; Mok, K. M.

    2013-09-01

    Multilayer perceptron (MLP), normally trained by the offline backpropagation algorithm, could not adapt to the changing air quality system and subsequently underperforms. To improve this, the extended Kalman filter is adopted into the learning algorithm to build a time-varying multilayer perceptron (TVMLP) in this study. Application of the TVMLP to model the daily averaged concentration of the respirable suspended particulates with aerodynamic diameter of not more than 10 µm (PM10) in Macau shows statistically significant improvement on the performance indicators over the MLP counterpart. In addition, the adaptive learning algorithm could also address explicitly the uncertainty of the prediction so that confidence intervals can be provided. More importantly, the adaptiveness of the TVMLP gives prediction improvement on the region of higher particulate concentrations that the public concerns.

  9. Photochemical Air Quality Modeling for California By U.S. EPA and Carb

    NASA Astrophysics Data System (ADS)

    Kelly, J.; Cai, C.; Baker, K. R.; Avise, J.; Kaduwela, A. P.

    2014-12-01

    Multiple areas of California have been designated as nonattainment of the National Ambient Air Quality Standards (NAAQS) for ozone and PM2.5 (particulate matter with aerodynamic diameter < 2.5 microns). Air quality modeling plays a key role in developing emission control strategies for attaining the NAAQS in these regions and for estimating the incremental costs and benefits of meeting new NAAQS levels. The complex terrain, meteorology, emissions, and chemistry in California present challenges to such air quality modeling. In this study, we improve understanding of modeling approaches for California by comparing and evaluating predictions of the Community Multiscale Air Quality (CMAQ) model as configured by the California Air Resources Board (CARB) and the U.S. Environmental Protection Agency (EPA). Both simulations were conducted at 4-km horizontal resolution and cover the May-June 2010 period when special study measurements were made. Despite differences in emissions, meteorology, boundary conditions, and chemical mechanisms, the CMAQ predictions by EPA and CARB were generally similar with good model performance for ozone at key monitors. Differences in predictions for PM2.5 components were identified in some locations and attributed to differences in emissions and other platform elements. Our results suggest areas where model development would be beneficial.

  10. SENSITIVITY ANALYSIS OF A NESTED OZONE AIR QUALITY MODEL

    EPA Science Inventory

    A series of Urban Airshed Model (UAM) simulations were performed using inputs derived from Regional Oxidant Model (ROM) data files. The gridded ROM results employed in the UAM simulations included concentrations for specifying initial and boundary conditions, wind fields, other m...

  11. REGIONAL-SCALE AIR QUALITY MODELING USING CMAQ

    EPA Science Inventory

    This presentation provides an overview of the technical competencies within the Atmospheric Modeling Division as well as our current research. Following a brief description of PM2.5 modeling activities, the presentation closes with a list of areas in which our Divisio...

  12. NEW CATEGORICAL METRICS FOR AIR QUALITY MODEL EVALUATION

    EPA Science Inventory

    Traditional categorical metrics used in model evaluations are "clear-cut" measures in that the model's ability to predict an exceedance is defined by a fixed threshold concentration and the metrics are defined by observation-forecast sets that are paired both in space and time. T...

  13. Simulating gas and particulate pollution over the Middle East and the state of Qatar using a 3-D regional air quality modeling system

    NASA Astrophysics Data System (ADS)

    Fountoukis, Christos; Gladich, Ivan; Ayoub, Mohammed; Kais, Sabre; Ackermann, Luis; Skillern, Adam

    2016-04-01

    The rapid urbanization, industrialization and economic expansion in the Middle East have led to increased levels of atmospheric pollution with important implications for human health and climate. We applied the online-coupled meteorological and chemical transport Weather Research and Forecasting/Chemistry (WRF-Chem) model over the Middle Eastern domain, to simulate the concentration of gas and aerosols with a special focus over the state of Qatar. WRF-Chem was set to simulate pollutant concentrations along with the meteorology-chemistry interactions through the related direct, indirect and semi-direct feedback mechanisms. A triple-nested domain configuration was used with a high grid resolution (1x1 km2) over the region of Qatar. Model predictions are evaluated against intensive measurements of meteorological parameters (temperature, relative humidity and wind speed) as well as ozone and particulate matter taken from various measurement stations throughout Doha, Qatar during summer 2015. The ability of the model to capture the temporal and spatial variability of the observations is assessed and possible reasons for the model bias are explored through sensitivity tests. Emissions of both fine and coarse mode particles from construction activities in large urban Middle Eastern environments comprise a major pollution source that is unaccounted for in emission inventories used so far in large scale models for this part of the world.

  14. A novel air quality analysis and prediction system for São Paulo, Brazil to support decision-making

    NASA Astrophysics Data System (ADS)

    Hoshyaripour, Gholam Ali; Brasseur, Guy; Andrade, Maria Fatima; Gavidia-Calderón, Mario; Bouarar, Idir

    2016-04-01

    The extensive economic development and urbanization in southeastern Brazil (SEB) in recent decades have notably degraded the air quality with adverse impacts on human health. Since the Metropolitan Area of São Paulo (MASP) accommodates the majority of the economic growth in SEB, it overwhelmingly suffers from the air pollution. Consequently, there is a strong demand for developing ever-better assessment mechanisms to monitor the air quality and to assist the decision makers to mitigate the air pollution in MASP. Here we present the results of an air quality modeling system designed for SEB with focuses on MASP. The Weather Research and Forecast model with Chemistry (WRF-Chem) is used considering the anthropogenic, biomass-burning and biogenic emissions within a 1000×1500 km domain with resolution of 10 km. FINN and MEGAN are used for the biomass-burning and biogenic emissions, respectively. For the anthropogenic emissions we use a local bottom-up inventory for the transport sector and the HTAPv2 global inventory for all other sectors. The bottom-up inventory accounts for the traffic patterns, vehicle types and their emission factors in the area and thus could be used to evaluate the effect of changes in these parameters on air quality in MASP. The model outputs are compered to the satellite and ground-based observations for O3 and NOx. The results show that using the bottom-up or top-down inventories individually can result in a huge deviation between the predictions and observations. On the other hand, combining the inventories significantly enhances the forecast accuracy. It also provides a powerful tool to quantify the effects of traffic and vehicle emission policies on air quality in MASP.

  15. SUMMARY REPORT OF AIR QUALITY MODELING RESEARCH ACTIVITIES FOR 2006

    EPA Science Inventory

    Through a Memorandum of Understanding (MOU) and Memorandum of Agreement (MOA) between the Department of Commerce (DOC) and U.S. Environmental Protection Agency (EPA), the Atmospheric Sciences Modeling Division (ASMD) of National Oceanic and Atmospheric Administration's (NOAA's) ...

  16. Modeling study on the factors affecting regional air quality during the Beijing 2008 Olympic Games

    NASA Astrophysics Data System (ADS)

    Wei, C.; Carmichael, G. R.; Adhikary, B.; D'Allura, A.; Cheng, Y.; Tang, Y.; Zhang, Q.; Streets, D. G.; Pierce, R.; Al-Saadi, J. A.; Flowers, B. A.; Dubey, M. K.; Krotkov, N. A.; Pickering, K. E.; Ramanathan, V.

    2009-12-01

    Chinese government took measures to control emissions of pollutants before and during the Beijing 2008 Olympic Games in order to get better air quality for the event. A 3-dimensional regional chemical transport model, the University of Iowa’s Sulfur Transport and dEposition Model (STEM), is used to evaluate the effects of emission reductions on regional air quality by this event. The emission inventories with and without the consideration of emission reductions are used in case studies. Impacts of the emissions from different regions and sectors on Beijing and regional air quality are discussed in this study. Meteorological factor on the improvement of air quality during this event is also assessed by using the meteorological conditions from different years to drive the model. Model performance is evaluated by comparing the modeled trace gases and aerosols with the surface measurements from Beijing, the field observations from the Cheju ABC Plume-Asian Monsoon Experiment (CAPMEX) during this summer, and satellite data from NASA.

  17. Using global aerosol models and satellite data for air quality studies: Challenges and data needs

    NASA Technical Reports Server (NTRS)

    Chin, Mian

    2006-01-01

    Aerosol particles, also known as PM2.5 (particle diameter less than 2.5 pm) and PM10 (particle diameter less than 10 pm), are one of the key atmospheric components that determines air quality. Yet, air quality forecasts for PM are still in their infancy and remain a challenging task. It is difficult to simply relate PM levels to local meteorological conditions, and large uncertainties exist in regional air quality model emission inventories and initial and boundary conditions. Especially challenging are periods when a significant amount of aerosol comes from outside the regional modeling domain through long-range transport. In the past few years, NASA has launched several satellites with global aerosol measurement capabilities, providing large-scale chemical weather pictures. NASA has also supported development of global models which simulate atmospheric transport and transformation processes of important atmospheric gas and aerosol species. I will present the current modeling and satellite capabilities for PM2.5 studies, the possibilities and challenges in using satellite data for PM2.5 forecasts, and the needs of future remote sensing data for improving air quality monitoring and modeling.

  18. AIR QUALITY DATA ANALYSIS SYSTEM FOR INTERRELATING EFFECTS, STANDARDS, AND NEEDED SOURCE REDUCTIONS: PART 7. AN O3-SO2 LEAF INJURY MATHEMATICAL MODEL

    EPA Science Inventory

    Leaf injury data from acute and chronic exposure studies of Dare soybean were regressed against the logarithms of exposure time and O3 and SO2 concentrations to develop a new two-pollutant leaf injury model (which explains 88% of the variance) and to calculate the parameters of b...

  19. AIR QUALITY DATA ANALYSIS SYSTEM FOR INTERRELATING EFFECTS, STANDARDS, AND NEEDED SOURCE REDUCTION: PART II - A LOGNORMAL MODEL OF LUNG FUNCTION DECREASED BY O3 EXPOSURE

    EPA Science Inventory

    Forced expiratory volume in 1 second (FEV1) was measured in 21 men exercising while exposed to four O3 concentrations (0.0, 0.08, 0.10, and 0.12 ppm). ognormal multiple linear regression model was fitted to their mean FEV1 measurements to predict FEV1 percent decrease as a functi...

  20. Ventilation System Effectiveness and Tested Indoor Air Quality Impacts

    SciTech Connect

    Rudd, A.; Bergey, D.

    2014-02-01

    Ventilation system effectiveness testing was conducted at two unoccupied, single-family, detached lab homes at the University of Texas - Tyler. Five ventilation system tests were conducted with various whole-building ventilation systems. Multizone fan pressurization testing characterized building and zone enclosure leakage. PFT testing showed multizone air change rates and interzonal airflow. Cumulative particle counts for six particle sizes, and formaldehyde and other Top 20 VOC concentrations were measured in multiple zones. The testing showed that single-point exhaust ventilation was inferior as a whole-house ventilation strategy. It was inferior because the source of outside air was not direct from outside, the ventilation air was not distributed, and no provision existed for air filtration. Indoor air recirculation by a central air distribution system can help improve the exhaust ventilation system by way of air mixing and filtration. In contrast, the supply and balanced ventilation systems showed that there is a significant benefit to drawing outside air from a known outside location, and filtering and distributing that air. Compared to the Exhaust systems, the CFIS and ERV systems showed better ventilation air distribution and lower concentrations of particulates, formaldehyde and other VOCs. System improvement percentages were estimated based on four System Factor Categories: Balance, Distribution, Outside Air Source, and Recirculation Filtration. Recommended System Factors could be applied to reduce ventilation fan airflow rates relative to ASHRAE Standard 62.2 to save energy and reduce moisture control risk in humid climates. HVAC energy savings were predicted to be 8-10%, or $50-$75/year.

  1. Ventilation System Effectiveness and Tested Indoor Air Quality Impacts

    SciTech Connect

    Rudd, Armin; Bergey, Daniel

    2014-02-01

    In this project, Building America research team Building Science Corporation tested the effectiveness of ventilation systems at two unoccupied, single-family, detached lab homes at the University of Texas - Tyler. Five ventilation system tests were conducted with various whole-building ventilation systems. Multizone fan pressurization testing characterized building and zone enclosure leakage. PFT testing showed multizone air change rates and interzonal airflow. Cumulative particle counts for six particle sizes, and formaldehyde and other Top 20 VOC concentrations were measured in multiple zones. The testing showed that single-point exhaust ventilation was inferior as a whole-house ventilation strategy. This was because the source of outside air was not direct from outside, the ventilation air was not distributed, and no provision existed for air filtration. Indoor air recirculation by a central air distribution system can help improve the exhaust ventilation system by way of air mixing and filtration. In contrast, the supply and balanced ventilation systems showed that there is a significant benefit to drawing outside air from a known outside location, and filtering and distributing that air. Compared to the exhaust systems, the CFIS and ERV systems showed better ventilation air distribution and lower concentrations of particulates, formaldehyde and other VOCs. System improvement percentages were estimated based on four system factor categories: balance, distribution, outside air source, and recirculation filtration. Recommended system factors could be applied to reduce ventilation fan airflow rates relative to ASHRAE Standard 62.2 to save energy and reduce moisture control risk in humid climates. HVAC energy savings were predicted to be 8-10%, or $50-$75/year.

  2. Toronto area ozone: Long-term measurements and modeled sources of poor air quality events

    NASA Astrophysics Data System (ADS)

    Whaley, C. H.; Strong, K.; Jones, D. B. A.; Walker, T. W.; Jiang, Z.; Henze, D. K.; Cooke, M. A.; McLinden, C. A.; Mittermeier, R. L.; Pommier, M.; Fogal, P. F.

    2015-11-01

    The University of Toronto Atmospheric Observatory and Environment Canada's Centre for Atmospheric Research Experiments each has over a decade of ground-based Fourier transform infrared (FTIR) spectroscopy measurements in southern Ontario. We present the Toronto area FTIR time series from 2002 to 2013 of two tropospheric trace gases—ozone and carbon monoxide—along with surface in situ measurements taken by government monitoring programs. We interpret their variability with the GEOS-Chem chemical transport model and determine the atmospheric conditions that cause pollution events in the time series. Our analysis includes a regionally tagged O3 model of the 2004-2007 time period, which quantifies the geographical contributions to Toronto area O3. The important emission types for 15 pollution events are then determined with a high-resolution adjoint model. Toronto O3, during pollution events, is most sensitive to southern Ontario and U.S. fossil fuel NOx emissions and natural isoprene emissions. The sources of Toronto pollution events are found to be highly variable, and this is demonstrated in four case studies representing local, short-, middle-, and long-range transport scenarios. This suggests that continental-scale emission reductions could improve air quality in the Toronto region. We also find that abnormally high temperatures and high-pressure systems are common to all pollution events studied, suggesting that climate change may impact Toronto O3. Finally, we quantitatively compare the sensitivity of the surface and column measurements to anthropogenic NOx emissions and show that they are remarkably similar. This work thus demonstrates the usefulness of FTIR measurements in an urban area to assess air quality.

  3. Modelling the impacts of ammonia emissions reductions on North American air quality

    NASA Astrophysics Data System (ADS)

    Makar, P. A.; Moran, M. D.; Zheng, Q.; Cousineau, S.; Sassi, M.; Duhamel, A.; Besner, M.; Davignon, D.; Crevier, L.-P.; Bouchet, V. S.

    2009-03-01

    A unified regional air-quality modelling system (AURAMS) was used to investigate the effects of reductions in ammonia emissions on regional air quality, with a focus on particulate-matter formation. Three simulations of one-year duration were performed for a North American domain: (1) a base-case simulation using 2002 Canadian and US national emissions inventories augmented by a more detailed Canadian emissions inventory for agricultural ammonia; (2) a 30% North-American-wide reduction in agricultural ammonia emissions; and (3) a 50% reduction in Canadian beef-cattle ammonia emissions. The simulations show that a 30% continent-wide reduction in agricultural ammonia emissions lead to reductions in median hourly ±2.5 mass of <1 μg m-3 on an annual basis. The atmospheric response to these emission reductions displays marked seasonal variations, and on even shorter time scales the impacts of the emissions reductions are highly episodic: 95-percentile hourly ±2.5 mass decreases can be up to a factor of six larger than the median values. A key finding of the modelling work is the linkage between gas and aqueous chemistry and transport; reductions in ammonia emissions affect gaseous ammonia concentrations close to the emissions site, but substantial impacts on particulate matter and atmospheric deposition often occur at considerable distances downwind, with particle nitrate being the main vector of ammonia/um transport. Ammonia emissions reductions therefore have trans-boundary and possibly trans-oceanic consequences downwind. Calculations of critical-load exceedances for sensitive ecosystems in Canada suggest that ammonia emission reductions will have a minimal impact on current ecosystem acidification within Canada, but may have a substantial impact on future ecosystem acidification. The 50% Canadian beef-cattle ammonia emissions reduction scenario was used to examine model sensitivity to uncertainties in the new Canadian agricultural ammonia emissions inventory, and

  4. A photochemical box model for urban air quality study

    SciTech Connect

    Jin, Shengxin.

    1991-01-01

    The photochemical box model (PBM) is based on the principle of mass conservation. The concentration of any pollutant is determined by horizontal advection, vertical entrainment, source emissions, and chemical reactions. A one dimensional high resolution boundary layer model by Blackadar has been further developed by considering the effect of urban heat islands to simulate the variation of the mixed layer height and incorporated in the PBM. The model predicted mixed layer height is a significant improvement over the characteristic mixed layer growth curve used in the original PBM by Schere and Demerjian. The gas phase chemical kinetic mechanism used in the Regional Acid Deposition Study II (RADM2) and Demerjian chemical mechanism have been used to calculate the contributions of chemical reactions to the changes of pollutant concentrations. Detailed analysis and comparisons of the two chemical mechanisms have been made. The simulated pollutant concentration using both chemical mechanisms are in very good agreement with observations. A radiative transfer model developed by Madronich has been incorporated in the PBM for the calculation of actinic flux and photolytic rate constants. Height averaged and radiation corrected photolytic rate constant are used for the photochemical reactions. The simulated pollutant concentrations for CO, NO, NO[sub 2] and O[sub s] are in very good agreement with observations. Sensitivities of model results to the variation of photolytic rate constants, boundary conditions, hydrocarbon speciation factors, and thermal rate constant have been tested.

  5. Impacts of contaminant storage on indoor air quality: Model development

    SciTech Connect

    Sherman, Max H.; Hult, Erin L.

    2013-02-26

    A first-order, lumped capacitance model is used to describe the buffering of airborne chemical species by building materials and furnishings in the indoor environment. The model is applied to describe the interaction between formaldehyde in building materials and the concentration of the species in the indoor air. Storage buffering can decrease the effect of ventilation on the indoor concentration, compared to the inverse dependence of indoor concentration on the air exchange rate that is consistent with a constant emission rate source. If the exposure time of an occupant is long relative to the time scale of depletion of the compound from the storage medium, however, the total exposure will depend inversely on the air exchange rate. This lumped capacitance model is also applied to moisture buffering in the indoor environment, which occurs over much shorter depletion timescales of the order of days. This model provides a framework to interpret the impact of storage buffering on time-varying concentrations of chemical species and resulting occupant exposure. Pseudo-steady state behavior is validated using field measurements. Model behavior over longer times is consistent with formaldehyde and moisture concentration measurements in previous studies.

  6. Assimilation of Satellite Data in Regional Air Quality Models

    NASA Technical Reports Server (NTRS)

    Mcnider, Richard T.; Norris, William B.; Casey, Daniel; Pleim, Jonathan E.; Roselle, Shawn J.; Lapenta, William M.

    1997-01-01

    In terms of important uncertainty in regional-scale air-pollution models, probably no other aspect ranks any higher than the current ability to specify clouds and soil moisture on the regional scale. Because clouds in models are highly parameterized, the ability of models to predict the correct spatial and radiative characteristics is highly suspect and subject to large error. The poor representation of cloud fields from point measurements at National Weather Services stations and the almost total absence of surface moisture availability observations has made assimilation of these variables difficult to impossible. Yet, the correct inclusion of clouds and surface moisture are of first-order importance in regional-scale photochemistry.

  7. Summary Report of Air Quality Modeling Research Activities for 2007

    EPA Science Inventory

    Through a Memorandum of Understanding (MOU) and Memorandum of Agreement (MOA) between the U.S. Department of Commerce (DOC) and the U.S. Environmental Protection Agency (EPA), the Atmospheric Sciences Modeling Division (ASMD) of the National Oceanic and Atmospheric Administration...

  8. A Novice-Expert Study of Modeling Skills and Knowledge Structures about Air Quality

    ERIC Educational Resources Information Center

    Hsu, Ying-Shao; Lin, Li-Fen; Wu, Hsin-Kai; Lee, Dai-Ying; Hwang, Fu-Kwun

    2012-01-01

    This study compared modeling skills and knowledge structures of four groups as seen in their understanding of air quality. The four groups were: experts (atmospheric scientists), intermediates (upper-level graduate students in a different field), advanced novices (talented 11th and 12th graders), and novices (10th graders). It was found that when…

  9. 40 CFR Appendix W to Part 51 - Guideline on Air Quality Models

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... clear from the needs expressed by the States and EPA Regional Offices, by many industries and trade... 51—Guideline on Air Quality Models Preface a. Industry and control agencies have long expressed a....0Bibliography 12.0References Appendix A to Appendix W of 40 CFR Part 51—Summaries of Preferred Air...

  10. 40 CFR Appendix W to Part 51 - Guideline on Air Quality Models

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... clear from the needs expressed by the States and EPA Regional Offices, by many industries and trade... 51—Guideline on Air Quality Models Preface a. Industry and control agencies have long expressed a....0Bibliography 12.0References Appendix A to Appendix W of 40 CFR Part 51—Summaries of Preferred Air...

  11. 40 CFR Appendix W to Part 51 - Guideline on Air Quality Models

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... clear from the needs expressed by the States and EPA Regional Offices, by many industries and trade... 51—Guideline on Air Quality Models Preface a. Industry and control agencies have long expressed a....0Bibliography 12.0References Appendix A to Appendix W of 40 CFR Part 51—Summaries of Preferred Air...

  12. 40 CFR Appendix W to Part 51 - Guideline on Air Quality Models

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... clear from the needs expressed by the States and EPA Regional Offices, by many industries and trade... 51—Guideline on Air Quality Models Preface a. Industry and control agencies have long expressed a....0Bibliography 12.0References Appendix A to Appendix W of 40 CFR Part 51—Summaries of Preferred Air...

  13. Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model

    EPA Science Inventory

    Sea spray aerosols (SSA) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. In this study, the Community Multiscale Air Quality (CMAQ) model is updated to enhance fine mode SSA emissions,...

  14. FINAL EVALUATION OF URBAN-SCALE PHOTOCHEMICAL AIR QUALITY SIMULATION MODELS

    EPA Science Inventory

    The research study discussed here is a continuation of previous work whose goal was to determine the accuracy of several selected urban photochemical air quality simulation models using data from the Regional Air Pollution Study in St. Louis. This work reports on the testing of t...

  15. (AMD) ANALYSIS OF AIR QUALITY DATA NEAR ROADWAYS USING A DISPERSION MODEL

    EPA Science Inventory

    We used a dispersion model to analyze measurements made during a field study conducted by the U.S. EPA in July-August 2006, to estimate the impact of traffic emissions on air quality at distances of tens of meters from an 8 lane highway located in Raleigh, North Carolina. The air...

  16. CHOOSING A CHEMICAL MECHANISM FOR REGULATORY AND RESEARCH AIR QUALITY MODELING APPLICATIONS

    EPA Science Inventory

    There are numerous, different chemical mechanisms currently available for use in air quality models, and new mechanisms and versions of mechanisms are continually being developed. The development of Morphecule-type mechanisms will add a near-infinite number of additional mecha...

  17. Path Forward for the Air Quality Model Evaluation International Initiative (AQMEII)

    EPA Science Inventory

    This article lays out the objectives for Phase 2 of the Air Quality Model Evaluation International Initiative (AQMEII). The inhalation of air pollutants such as ozone and fine particles has been linked to adverse impacts on human health, and the atmospheric deposition of pollutan...

  18. CONCENTRATIONS OF TOXIC AIR POLLUTANTS IN THE U.S. SIMULATED BY AN AIR QUALITY MODEL

    EPA Science Inventory

    As part of the US National Air Toxics Assessment, we have applied the Community Multiscale Air Quality Model, CMAQ, to study the concentrations of twenty gas-phase, toxic, hazardous air pollutants (HAPs) in the atmosphere over the continental United States. We modified the Carbo...

  19. REGIONAL AIR QUALITY AND ACID DEPOSITION MODELING AND THE ROLE FOR VISUALIZATION

    EPA Science Inventory

    The U.S Environmental Protection Agency (EPA) uses air quality and deposition models to advance the scientific understanding of basic physical and chemical processes related to air pollution, and to assess the effectiveness of alternative emissions control strategies. his paper p...

  20. A regional air quality forecasting system over Europe: the MACC-II daily ensemble production

    NASA Astrophysics Data System (ADS)

    Marécal, V.; Peuch, V.-H.; Andersson, C.; Andersson, S.; Arteta, J.; Beekmann, M.; Benedictow, A.; Bergström, R.; Bessagnet, B.; Cansado, A.; Chéroux, F.; Colette, A.; Coman, A.; Curier, R. L.; Denier van der Gon, H. A. C.; Drouin, A.; Elbern, H.; Emili, E.; Engelen, R. J.; Eskes, H. J.; Foret, G.; Friese, E.; Gauss, M.; Giannaros, C.; Guth, J.; Joly, M.; Jaumouillé, E.; Josse, B.; Kadygrov, N.; Kaiser, J. W.; Krajsek, K.; Kuenen, J.; Kumar, U.; Liora, N.; Lopez, E.; Malherbe, L.; Martinez, I.; Melas, D.; Meleux, F.; Menut, L.; Moinat, P.; Morales, T.; Parmentier, J.; Piacentini, A.; Plu, M.; Poupkou, A.; Queguiner, S.; Robertson, L.; Rouïl, L.; Schaap, M.; Segers, A.; Sofiev, M.; Tarasson, L.; Thomas, M.; Timmermans, R.; Valdebenito, Á.; van Velthoven, P.; van Versendaal, R.; Vira, J.; Ung, A.

    2015-09-01

    This paper describes the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in the MACC-II (Monitoring Atmospheric Composition and Climate: Interim Implementation) European projects to provide air quality services for the European continent. This system is based on seven state-of-the art models developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE and SILAM). These models are used to calculate multi-model ensemble products. The paper gives an overall picture of its status at the end of MACC-II (summer 2014) and analyses the performance of the multi-model ensemble. The MACC-II system provides daily 96 h forecasts with hourly outputs of 10 chemical species/aerosols (O3, NO2, SO2, CO, PM10, PM2.5, NO, NH3, total NMVOCs (non-methane volatile organic compounds) and PAN+PAN precursors) over eight vertical levels from the surface to 5 km height. The hourly analysis at the surface is done a posteriori for the past day using a selection of representative air quality data from European monitoring stations. The performance of the system is assessed daily, weekly and every 3 months (seasonally) through statistical indicators calculated using the available representative air quality data from European monitoring stations. Results for a case study show the ability of the ensemble median to forecast regional ozone pollution events. The seasonal performances of the individual models and of the multi-model ensemble have been monitored since September 2009 for ozone, NO2 and PM10. The statistical indicators for ozone in summer 2014 show that the ensemble median gives on average the best performances compared to the seven models. There is very little degradation of the scores with the forecast day but there is a marked diurnal cycle, similarly to the individual models, that can be related partly to the prescribed diurnal variations of anthropogenic emissions in the models

  1. Insights into future air quality: Analysis of future emissions scenarios using the MARKAL model

    EPA Science Inventory

    This presentation will provide an update on the development and evaluation of four Air Quality Futures (AQF) scenarios. These scenarios represent widely different assumptions regarding the evolution of the U.S. energy system over the next 40 years. The primary differences between...

  2. Insights into future air quality: a multipollutant analysis of future scenarios using the MARKAL model

    EPA Science Inventory

    In this presentation, we will provide an update on the development and evaluation of the Air Quality Futures (AQF) scenarios. These scenarios represent widely different assumptions regarding the evolution of the U.S. energy system over the next 40 years. The four AQF scenarios di...

  3. Exploiting GRID for Model Estimates of Regional Climate Changes and Its Impact on the Air Quality of Bulgaria

    NASA Astrophysics Data System (ADS)

    Syrakov, D.; Spiridonov, V.; Ganev, K.; Prodanova, M.; Bogatchev, A.; Miloshev, N.; Slavov, K.; Katragkou, E.; Melas, D.; Poupkou, A.; Markakis, K.

    2010-11-01

    Intensive long-term meteorological modeling took place over an area covering Bulgaria with resolution of 10 km. The climatic version of the operational weather forecast model ALADIN was applied for simulating 3 time slices: 1960-2000, 2020-2050 and 2070-2100, following the IPCC scenario A1B. The differences of climatic fields for the 3 periods are presented and interpreted. The created met-data base is used to estimate the impact of climate changes on air quality, as well. A respective modeling System was created on the base of US EPA Models-3 tool (MM5, CMAQ and SMOKE). Calculations for the last 10 years of each time slice are performed. Grid technology in the frame of SEE-GRID-SCI project is used to perform this enormous volume of calculations as an application abbreviated to CCIAQ (Climate Change Impact on Air Quality). The results are presented and interpreted in the study.

  4. HVAC SYSTEMS AS EMISSION SOURCES AFFECTING INDOOR AIR QUALITY: A CRITICAL REVIEW

    EPA Science Inventory

    The paper discusses results of an evaluation of literature on heating, ventilating, and air-conditioning (HVAC) systems as contaminant emission sources that affect indoor air quality (IAQ). The various literature sources and methods for characterizing HVAC emission sources are re...

  5. Models and error analyses in urban air quality estimation

    NASA Technical Reports Server (NTRS)

    Englar, T., Jr.; Diamante, J. M.; Jazwinski, A. H.

    1976-01-01

    Estimation theory has been applied to a wide range of aerospace problems. Application of this expertise outside the aerospace field has been extremely limited, however. This paper describes the use of covariance error analysis techniques in evaluating the accuracy of pollution estimates obtained from a variety of concentration measuring devices. It is shown how existing software developed for aerospace applications can be applied to the estimation of pollution through the processing of measurement types involving a range of spatial and temporal responses. The modeling of pollutant concentration by meandering Gaussian plumes is described in some detail. Time averaged measurements are associated with a model of the average plume, using some of the same state parameters and thus avoiding the problem of state memory. The covariance analysis has been implemented using existing batch estimation software. This usually involves problems in handling dynamic noise; however, the white dynamic noise has been replaced by a band-limited process which can be easily accommodated by the software.

  6. CMAQ (Community Multi-Scale Air Quality) atmospheric distribution model adaptation to region of Hungary

    NASA Astrophysics Data System (ADS)

    Lázár, Dóra; Weidinger, Tamás

    2016-04-01

    For our days, it has become important to measure and predict the concentration of harmful atmospheric pollutants such as dust, aerosol particles of different size ranges, nitrogen compounds, and ozone. The Department of Meteorology at Eötvös Loránd University has been applying the WRF (Weather Research and Forecasting) model several years ago, which is suitable for weather forecasting tasks and provides input data for various environmental models (e.g. DNDC). By adapting the CMAQ (Community Multi-scale Air Quality) model we have designed a combined ambient air-meteorological model (WRF-CMAQ). In this research it is important to apply different emission databases and a background model describing the initial distribution of the pollutant. We used SMOKE (Sparse Matrix Operator Kernel Emissions) model for construction emission dataset from EMEP (European Monitoring and Evaluation Programme) inventories and GEOS-Chem model for initial and boundary conditions. Our model settings were CMAQ CB05 (Carbon Bond 2005) chemical mechanism with 108 x 108 km, 36 x 36 km and 12 x 12 km grids for regions of Europe, the Carpathian Basin and Hungary respectively. i) The structure of the model system, ii) a case study for Carpathian Basin (an anticyclonic weather situation at 21th September 2012) are presented. iii) Verification of ozone forecast has been provided based on the measurements of background air pollution stations. iv) Effects of model attributes (f.e. transition time, emission dataset, parameterizations) for the ozone forecast in Hungary are also investigated.

  7. Measurement results obtained from air quality monitoring system

    SciTech Connect

    Turzanski, P.K.; Beres, R.

    1995-12-31

    An automatic system of air pollution monitoring operates in Cracow since 1991. The organization, assembling and start-up of the network is a result of joint efforts of the US Environmental Protection Agency and the Cracow environmental protection service. At present the automatic monitoring network is operated by the Provincial Inspection of Environmental Protection. There are in total seven stationary stations situated in Cracow to measure air pollution. These stations are supported continuously by one semi-mobile (transportable) station. It allows to modify periodically the area under investigation and therefore the 3-dimensional picture of creation and distribution of air pollutants within Cracow area could be more intelligible.

  8. Assessment of the MACC reanalysis and its influence as chemical boundary conditions for regional air quality modeling in AQMEII-2

    EPA Science Inventory

    The Air Quality Model Evaluation International Initiative (AQMEII) has now reached its second phase which is dedicated to the evaluation of online coupled chemistry-meteorology models. Sixteen modeling groups from Europe and five from North America have run regional air quality m...

  9. A regional air quality forecasting system over Europe: the MACC-II daily ensemble production

    NASA Astrophysics Data System (ADS)

    Marécal, V.; Peuch, V.-H.; Andersson, C.; Andersson, S.; Arteta, J.; Beekmann, M.; Benedictow, A.; Bergström, R.; Bessagnet, B.; Cansado, A.; Chéroux, F.; Colette, A.; Coman, A.; Curier, R. L.; Denier van der Gon, H. A. C.; Drouin, A.; Elbern, H.; Emili, E.; Engelen, R. J.; Eskes, H. J.; Foret, G.; Friese, E.; Gauss, M.; Giannaros, C.; Guth, J.; Joly, M.; Jaumouillé, E.; Josse, B.; Kadygrov, N.; Kaiser, J. W.; Krajsek, K.; Kuenen, J.; Kumar, U.; Liora, N.; Lopez, E.; Malherbe, L.; Martinez, I.; Melas, D.; Meleux, F.; Menut, L.; Moinat, P.; Morales, T.; Parmentier, J.; Piacentini, A.; Plu, M.; Poupkou, A.; Queguiner, S.; Robertson, L.; Rouïl, L.; Schaap, M.; Segers, A.; Sofiev, M.; Thomas, M.; Timmermans, R.; Valdebenito, Á.; van Velthoven, P.; van Versendaal, R.; Vira, J.; Ung, A.

    2015-03-01

    This paper describes the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in MACC-II (Monitoring Atmospheric Composition and Climate: Interim Implementation) European projects to provide air quality services for the European continent. The paper gives an overall picture of its status at the end of MACC-II (summer 2014). This system is based on seven state-of-the art models developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE and SILAM). These models are used to calculate multi-model ensemble products. The MACC-II system provides daily 96 h forecasts with hourly outputs of 10 chemical species/aerosols (O3, NO2, SO2, CO, PM10, PM2.5, NO, NH3, total NMVOCs and PAN + PAN precursors) over 8 vertical levels from the surface to 5 km height. The hourly analysis at the surface is done a posteriori for the past day using a selection of representative air quality data from European monitoring stations. The performances of the system are assessed daily, weekly and 3 monthly (seasonally) through statistical indicators calculated using the available representative air quality data from European monitoring stations. Results for a case study show the ability of the median ensemble to forecast regional ozone pollution events. The time period of this case study is also used to illustrate that the median ensemble generally outperforms each of the individual models and that it is still robust even if two of the seven models are missing. The seasonal performances of the individual models and of the multi-model ensemble have been monitored since September 2009 for ozone, NO2 and PM10 and show an overall improvement over time. The change of the skills of the ensemble over the past two summers for ozone and the past two winters for PM10 are discussed in the paper. While the evolution of the ozone scores is not significant, there are improvements of PM10 over the past two winters

  10. Assessment of air quality management policies in China with integrated model framework: Case study for Hebei province

    NASA Astrophysics Data System (ADS)

    Zhang, Q.; Zhao, Q.; Zheng, B.; Hong, C.; Tong, D.; Yang, W.; He, K.

    2015-12-01

    The Chinese government has pledged to clean urban air within five years from 2013 to 2017, to promote annual average PM2.5 concentration decline by 25%, 20% and 15% in the North China Plain, Yangtze River Delta and Pearl River Delta, respectively. The national targets are disaggregated into provinces, where region-specific action plan is designed and implemented by local government. It is particularly important to timely assess the effectiveness of local emission control measures and guarantee local efforts are in line with the national goal. We develop an integrated model framework for air quality management and policy evaluation, by integrating a dynamic high-resolution emission model, an emission scenarios analysis tool, and a 3-D air quality model. We then put the model system into pilot use in Hebei province for policy making to achieve the air quality target of 2017. We first integrate over 3000 point source facilities into this system to develop a high-resolution emission inventory. Upon the base emission dataset, the efforts to mitigate emissions with current and enacted measures are tracked and quantified to dynamic account of emission changes monthly. Strict policies are designed within the model framework through analyzing the potential to cut emissions for each point source. The finalized policy package can reduce emissions of major air pollutants by 20%-40%, respectively, leading to large decrease of ambient PM2.5 concentration.

  11. Modeling air quality during the California Regional PM 10/PM 2.5 Air Quality Study (CPRAQS) using the UCD/CIT source-oriented air quality model - Part III. Regional source apportionment of secondary and total airborne particulate matter

    NASA Astrophysics Data System (ADS)

    Ying, Qi; Lu, Jin; Kleeman, Michael

    A comprehensive air quality modeling project was carried out to simulate regional source contributions to secondary and total (=primary + secondary) airborne particle concentrations in California's Central Valley. A three-week stagnation episode lasting from December 15, 2000 to January 7, 2001, was chosen for study using the air quality and meteorological data collected during the California Regional PM 10/PM 2.5 Air Quality Study (CRPAQS). The UCD/CIT mechanistic air quality model was used with explicit decomposition of the gas phase reaction chemistry to track source contributions to secondary PM. Inert artificial tracers were used with an internal mixture representation to track source contributions to primary PM. Both primary and secondary source apportionment calculations were performed for 15 size fractions ranging from 0.01 to 10 μm particle diameters. Primary and secondary source contributions were resolved for fugitive dust, road dust, diesel engines, catalyst equipped gasoline engines, non-catalyst equipped gasoline engines, wood burning, food cooking, high sulfur fuel combustion, and other anthropogenic sources. Diesel engines were identified as the largest source of secondary nitrate in central California during the study episode, accounting for approximately 40% of the total PM 2.5 nitrate. Catalyst equipped gasoline engines were also significant, contributing approximately 20% of the total secondary PM 2.5 nitrate. Agricultural sources were the dominant source of secondary ammonium ion. Sharp gradients of PM concentrations were predicted around major urban areas. The relative source contributions to PM 2.5 from each source category in urban areas differ from those in rural areas, due to the dominance of primary OC in urban locations and secondary nitrate in the rural areas. The source contributions to ultra-fine particle mass PM 0.1 also show clear urban/rural differences. Wood smoke was found to be the major source of PM 0.1 in urban areas while

  12. Verification and uses of the Environmental Protection Agency (EPA) indoor air quality model

    SciTech Connect

    Sparks, L.E.; Tichenor, B.A.; Jackson, M.D.; White, J.B.

    1989-01-01

    The paper describes a set of experiments used to verify an indoor air quality (IAQ) model for estimating the impact of various pollution sources on IAQ in a multiroom building. The model treats each room as a well-mixed chamber that contains pollution sources and sinks. The model allows analysis of the impact of room-to-room air flows, HVAC (heating, ventilating, and air-conditioning) systems, and air cleaners on IAQ. The model is written for personal computers. The experiments were conducted in a test house. Three pollution sources were used: moth crystals, kerosene heaters, and dry cleaned cloths. The model predictions were in good agreement with the experimental data, especially when a sink term was included in the model. The paper gives a brief discussion of the theory on which the model is based. Preliminary data and theory of sources and sinks are also discussed. Examples demonstrating the use of the model to analyze IAQ options and to estimate exposure from a pollutant are included.

  13. Assessment of the AMS-MINNI system capabilities to simulate air quality over Italy for the calendar year 2005

    NASA Astrophysics Data System (ADS)

    Mircea, M.; Ciancarella, L.; Briganti, G.; Calori, G.; Cappelletti, A.; Cionni, I.; Costa, M.; Cremona, G.; D'Isidoro, M.; Finardi, S.; Pace, G.; Piersanti, A.; Righini, G.; Silibello, C.; Vitali, L.; Zanini, G.

    2014-02-01

    This paper presents a comprehensive evaluation of AMS-MINNI modelling system for the year 2005, over Italian peninsula and major islands Sicily and Sardinia, for gas-phase species ozone (O3) and nitrogen dioxide (NO2), and particulate matter with an aerodynamic diameter less than or equal to 10 μm (PM10), against surface measurements from the Italian air quality database. Statistical indicators currently used in air quality models performance assessment and recommended by European Union (EU) guidelines were calculated at rural, urban and suburban background air quality monitoring stations, on purpose of understanding the model behaviour in areas not directly affected by anthropogenic pollution sources. Results show that measured O3 concentrations are generally well reproduced by the model, with the best agreement between model and observations at rural stations. Simulated PM10 annual average concentrations are generally lower than those observed but simulated and observed variabilities are comparable at urban and suburban stations. As for NO2, the model underestimates concentrations at all stations but gives similar variability to the observed one. Overall, the values of the statistical indicators comply with the acceptance criteria requested by EU legislation and are similar with those published by previous studies for the three pollutants investigated in this study. Further work will be carried out to evaluate the impact of uncertainties in input data (meteorology, emissions and boundary conditions) and in description of gaseous and aerosol chemical and physical processes on the simulated concentrations.

  14. Evaluating the capability of regional-scale air quality models to capture the vertical distribution of pollutants

    EPA Science Inventory

    This study is conducted in the framework of the Air Quality Modelling Evaluation International Initiative (AQMEII) and aims at the operational evaluation of an ensemble of 12 regional-scale chemical transport models used to predict air quality over the North American (NA) and Eur...

  15. ESTIMATION OF EMISSION ADJUSTMENTS FROM THE APPLICATION OF FOUR-DIMENSIONAL DATA ASSIMILATION TO PHOTOCHEMICAL AIR QUALITY MODELING. (R826372)

    EPA Science Inventory

    Four-dimensional data assimilation applied to photochemical air quality modeling is used to suggest adjustments to the emissions inventory of the Atlanta, Georgia metropolitan area. In this approach, a three-dimensional air quality model, coupled with direct sensitivity analys...

  16. MELSAR: a mesoscale air quality model for complex terrain. Volume 2. Appendices

    SciTech Connect

    Allwine, K.J.; Whiteman, C.D.

    1985-04-01

    This final report is submitted as part of the Green River Ambient Model Assessment (GRAMA) project conducted at the US Department of Energy's Pacific Northwest Laboratory for the US Environmental Protection Agency. The GRAMA Program has, as its ultimate goal, the development of validated air quality models that can be applied to the complex terrain of the Green River Formation of western Colorado, eastern Utah and southern Wyoming. The Green River Formation is a geologic formation containing large reserves of oil shale, coal, and other natural resources. Development of these resources may lead to a degradation of the air quality of the region. Air quality models are needed immediately for planning and regulatory purposes to assess the magnitude of these regional impacts. This report documents one of the models being developed for this purpose within GRAMA - specifically a model to predict short averaging time (less than or equal to 24 h) pollutant concentrations resulting from the mesoscale transport of pollutant releases from multiple sources. MELSAR has not undergone any rigorous operational testing, sensitivity analyses, or validation studies. Testing and evaluation of the model are needed to gain a measure of confidence in the model's performance. This report consists of two volumes. This volume contains the Appendices, which include listings of the FORTRAN code and Volume 1 contains the model overview, technical description, and user's guide. 13 figs., 10 tabs.

  17. Utilizing Operational and Improved Remote Sensing Measurements to Assess Air Quality Monitoring Model Forecasts

    NASA Astrophysics Data System (ADS)

    Gan, Chuen-Meei

    Air quality model forecasts from Weather Research and Forecast (WRF) and Community Multiscale Air Quality (CMAQ) are often used to support air quality applications such as regulatory issues and scientific inquiries on atmospheric science processes. In urban environments, these models become more complex due to the inherent complexity of the land surface coupling and the enhanced pollutants emissions. This makes it very difficult to diagnose the model, if the surface parameter forecasts such as PM2.5 (particulate matter with aerodynamic diameter less than 2.5 microm) are not accurate. For this reason, getting accurate boundary layer dynamic forecasts is as essential as quantifying realistic pollutants emissions. In this thesis, we explore the usefulness of vertical sounding measurements on assessing meteorological and air quality forecast models. In particular, we focus on assessing the WRF model (12km x 12km) coupled with the CMAQ model for the urban New York City (NYC) area using multiple vertical profiling and column integrated remote sensing measurements. This assessment is helpful in probing the root causes for WRF-CMAQ overestimates of surface PM2.5 occurring both predawn and post-sunset in the NYC area during the summer. In particular, we find that the significant underestimates in the WRF PBL height forecast is a key factor in explaining this anomaly. On the other hand, the model predictions of the PBL height during daytime when convective heating dominates were found to be highly correlated to lidar derived PBL height with minimal bias. Additional topics covered in this thesis include mathematical method using direct Mie scattering approach to convert aerosol microphysical properties from CMAQ into optical parameters making direct comparisons with lidar and multispectral radiometers feasible. Finally, we explore some tentative ideas on combining visible (VIS) and mid-infrared (MIR) sensors to better separate aerosols into fine and coarse modes.

  18. Examples of scale interactions in local, urban, and regional air quality modelling

    NASA Astrophysics Data System (ADS)

    Mensink, C.; De Ridder, K.; Deutsch, F.; Lefebre, F.; Van de Vel, K.

    2008-09-01

    Air quality modeling can help to improve understanding of scale interactions related to meteorology, transport, emissions, formation, removal, and other processes taking place at local, urban, and regional scales. For the local scale, we used the coupling of a street canyon model with a Gaussian dispersion model to study the interactions of emissions and concentrations in urban streets and surrounding urban neighborhoods. The model combination was applied to a city quarter in Ghent, Belgium, and showed that up to 40% of the PM 2.5 concentrations inside street canyons were caused by emissions from the surrounding streets. For the urban scale, the AURORA model has been used successfully in assessments of urban air quality for entire cities or urbanized areas. It has been applied to the Ruhr area in Germany to evaluate the impact of compact or polycentric cities versus the impact of urban sprawl developments. Results for ozone and PM 10 showed that compact city structures may have more adverse effects in terms of air pollution exposure. For the regional scale, the EUROS model was used to study the urban and regional-scale interactions that are important in simulating concentrations of ozone, PM 2.5, and PM 10. It has been applied to study seasonal changes in aerosol concentrations in Flanders. High secondary aerosol concentrations were found during summer. This contribution was related to large contributions from outside the region, showing the importance of the continental scale when studying regional air quality problems.

  19. Evaluation of the GEM-AQ simulations for the Air Quality Model Evaluation International Initiative (AQMEII)

    NASA Astrophysics Data System (ADS)

    Lobocki, Lech; Gawuc, Lech; Jefimow, Maciej; Kaminski, Jacek; Porebska, Magdalena; Struzewska, Joanna; Zdunek, Malgorzata

    2013-04-01

    A multiscale, on-line meteorological and air quality model GEM-AQ was used to simulate ozone and particulate matter over the European continent in 2006, as a part of the Air Quality Model Evaluation International Initiative (AQMEII). In contrast to the majority of models participating in the Phase I of AQMEII, the GEM-AQ configuration employed here utilized neither external meteorological fields nor lateral boundary conditions, owing to the global-extent and variable grid resolution of the model setup. We will present evaluation results for global model performance statistics calculated for the entire year and more detailed performance analysis of pollution episodes. Evaluation of meteorological parameters includes comparisons of model-predicted wind, temperature and cloudiness with hourly observations at surface weather stations, daily maxima, and comparison with upper-air soundings at selected sites. Frequency distribution of principal boundary layer parameters and its spatial structure will be presented. Air quality predictions are assessed in terms of ground-level daily mean ozone concentrations and its daily peak values, vertical structure as inferred from ozone soundings, and particulate matter daily mean concentrations at the surface.

  20. Air quality modeling for the urban Jackson, Mississippi Region using a high resolution WRF/Chem model.

    PubMed

    Yerramilli, Anjaneyulu; Dodla, Venkata B; Desamsetti, Srinivas; Challa, Srinivas V; Young, John H; Patrick, Chuck; Baham, Julius M; Hughes, Robert L; Yerramilli, Sudha; Tuluri, Francis; Hardy, Mark G; Swanier, Shelton J

    2011-06-01

    In this study, an attempt was made to simulate the air quality with reference to ozone over the Jackson (Mississippi) region using an online WRF/Chem (Weather Research and Forecasting-Chemistry) model. The WRF/Chem model has the advantages of the integration of the meteorological and chemistry modules with the same computational grid and same physical parameterizations and includes the feedback between the atmospheric chemistry and physical processes. The model was designed to have three nested domains with the inner-most domain covering the study region with a resolution of 1 km. The model was integrated for 48 hours continuously starting from 0000 UTC of 6 June 2006 and the evolution of surface ozone and other precursor pollutants were analyzed. The model simulated atmospheric flow fields and distributions of NO2 and O3 were evaluated for each of the three different time periods. The GIS based spatial distribution maps for ozone, its precursors NO, NO2, CO and HONO and the back trajectories indicate that all the mobile sources in Jackson, Ridgeland and Madison contributing significantly for their formation. The present study demonstrates the applicability of WRF/Chem model to generate quantitative information at high spatial and temporal resolution for the development of decision support systems for air quality regulatory agencies and health administrators. PMID:21776240

  1. Development of an empirical model to estimate real-world fine particulate matter emission factors: the traffic air quality model.

    PubMed

    Soliman, Ahmed S M; Jacko, Robert B; Palmer, George M

    2006-11-01

    The purpose of the study was to quantify the impact of traffic conditions, such as free flow and congestion, on local air quality. The Borman Expressway (I-80/94) in Northwest Indiana is considered a test bed for this research because of the high volume of class 9 truck traffic traveling on it, as well as the existing and continuing installation of the Intelligent Transportation System (ITS) to improve traffic management along the highway stretch. An empirical traffic air quality (TAQ) model was developed to estimate the fine particulate matter (PM2.5) emission factors (grams per kilometer) based solely on the measured traffic parameters, namely, average speed, average acceleration, and class 9 truck density. The TAQ model has shown better predictions that matched the measured emission factor values more than the U.S. Environmental Protection Agency (EPA)-PART5 model. During congestion (defined as flow-speeds < 50 km/hr [30 mi/hr]), the TAQ model, on average, overpredicted the measured values only by a factor of 1.2, in comparison to a fourfold underprediction using the EPA-PART5 model. On the other hand, during free flow (defined as flow-speeds > 80 km/hr [50 mi/hr]), the TAQ model was conservative in that it overpredicted the measured values by 1.5-fold. PMID:17117739

  2. Air Quality Modeling for the Urban Jackson, Mississippi Region Using a High Resolution WRF/Chem Model

    PubMed Central

    Yerramilli, Anjaneyulu; Dodla, Venkata B.; Desamsetti, Srinivas; Challa, Srinivas V.; Young, John H.; Patrick, Chuck; Baham, Julius M.; Hughes, Robert L.; Yerramilli, Sudha; Tuluri, Francis; Hardy, Mark G.; Swanier, Shelton J.

    2011-01-01

    In this study, an attempt was made to simulate the air quality with reference to ozone over the Jackson (Mississippi) region using an online WRF/Chem (Weather Research and Forecasting–Chemistry) model. The WRF/Chem model has the advantages of the integration of the meteorological and chemistry modules with the same computational grid and same physical parameterizations and includes the feedback between the atmospheric chemistry and physical processes. The model was designed to have three nested domains with the inner-most domain covering the study region with a resolution of 1 km. The model was integrated for 48 hours continuously starting from 0000 UTC of 6 June 2006 and the evolution of surface ozone and other precursor pollutants were analyzed. The model simulated atmospheric flow fields and distributions of NO2 and O3 were evaluated for each of the three different time periods. The GIS based spatial distribution maps for ozone, its precursors NO, NO2, CO and HONO and the back trajectories indicate that all the mobile sources in Jackson, Ridgeland and Madison contributing significantly for their formation. The present study demonstrates the applicability of WRF/Chem model to generate quantitative information at high spatial and temporal resolution for the development of decision support systems for air quality regulatory agencies and health administrators. PMID:21776240

  3. Evaluation of a regional air-quality model with bidirectional NH3 exchange coupled to an agroecosystem model

    NASA Astrophysics Data System (ADS)

    Bash, J. O.; Cooter, E. J.; Dennis, R. L.; Walker, J. T.; Pleim, J. E.

    2013-03-01

    Atmospheric ammonia (NH3) is the primary atmospheric base and an important precursor for inorganic particulate matter and when deposited NH3 contributes to surface water eutrophication, soil acidification and decline in species biodiversity. Flux measurements indicate that the air-surface exchange of NH3 is bidirectional. However, the effects of bidirectional exchange, soil biogeochemistry and human activity are not parameterized in air quality models. The US Environmental Protection Agency's (EPA) Community Multiscale Air-Quality (CMAQ) model with bidirectional NH3 exchange has been coupled with the United States Department of Agriculture's (USDA) Environmental Policy Integrated Climate (EPIC) agroecosystem model. The coupled CMAQ-EPIC model relies on EPIC fertilization timing, rate and composition while CMAQ models the soil ammonium (NH4+) pool by conserving the ammonium mass due to fertilization, evasion, deposition, and nitrification processes. This mechanistically coupled modeling system reduced the biases and error in NHx (NH3 + NH4+) wet deposition and in ambient aerosol concentrations in an annual 2002 Continental US (CONUS) domain simulation when compared to a 2002 annual simulation of CMAQ without bidirectional exchange. Fertilizer emissions estimated in CMAQ 5.0 with bidirectional exchange exhibits markedly different seasonal dynamics than the US EPA's National Emissions Inventory (NEI), with lower emissions in the spring and fall and higher emissions in July.

  4. Air quality modelling for the mid-21th century in the greater Paris area under 2 climate scenarios

    NASA Astrophysics Data System (ADS)

    Markakis, Konstantinos; Valari, Mytro; Colette, Augustin; Sanchez, Olivier; Perrussel, Olivier

    2013-04-01

    There has been an increasing interest on the impact of climate change on future air quality at both global and regional scales. The largest amount of research up to now used global-scale modelling tools to address the issue, while few recent papers use regional scale models to assess the impact of climate change on large urban agglomerations. The main issues of concern related to a regional scale set-up focusing on a city are the representativeness of the emission estimates of a regional inventory for the city as well as uncertainties in the emission projections. Regional scale projections, may be consistent with global scale climate scenarios but they are not representative of the future trend of a specific city. In this study we modelled air quality in the city of Paris, France at a mid-21st century horizon (2045-2055) under two emission and climate scenarios. The emission scenarios were developed for Europe from the Global Energy Assessment (GEA) to be consistent with the IPCCs recently developed Representative Concentration Pathways (RCPs) which incorporate only climate change actions. The emission scenarios include both climate (RCP consistent) and regional air quality policies. To cope with the aforementioned problems we combined two sources of information to project emissions for the city of Paris to the mid-century horizon. The first stems from a local agency (AIRPARIF) and includes a bottom-up high resolution emission inventory compiled for the year 2008 based on information on local activity and statistics. This inventory is projected by AIRPARIF to the year 2020 based on various air-quality policies already in place or planned for the next years. The second is a set of projection coefficients extracted from the two GEA scenarios for France and applied to the 2020 local inventory in order to obtain an emission inventory for 2050. Global scale concentrations were modelled with the coupled LMDz-INCA system and then downscaled with the regional scale air-quality

  5. Air quality modelling of vehicular emissions under GIS environment, for Coimbatore Corporation (west zone).

    PubMed

    Meenambal, T; Palani, P K; Dhandapani, N; Manikumar, R

    2005-07-01

    Environment pollution is simply a consequence of the anthropogenic activities of mankind. Emissions from the motor vehicles have been shown to be the major contribution to air pollution in the urban environment. The major pollutants are SO2, No(x) and CO. Of these pollutants carbon monoxide is of utmost importance as the pollutant has serious toxicological effects and proves fatal on mankind. In this study, the concentration of Carbon-Monoxide (CO) along and near the major roads at Coimbatore west zone due to vehicular emission is predicted using the Air Quality Modelling Software Called CALINE4 model. Using MAPINFO GIS environment, thematic maps of the CO pollution at different receptor heights were prepared. Also, the concentration of CO for the year 2004 at 1.8 m height and 5 m height were predicted. In addition, to create awareness about the air quality, suggestions had been given to take suitable measures from engineering and environmental point of view. PMID:16841458

  6. Modelling the impacts of ammonia emissions reductions on North American air quality

    NASA Astrophysics Data System (ADS)

    Makar, P. A.; Moran, M. D.; Zheng, Q.; Cousineau, S.; Sassi, M.; Duhamel, A.; Besner, M.; Davignon, D.; Crevier, L.-P.; Bouchet, V. S.

    2009-09-01

    A unified regional air-quality modelling system (AURAMS) was used to investigate the effects of reductions in ammonia emissions on regional air quality, with a focus on particulate-matter formation. Three simulations of one-year duration were performed for a North American domain: (1) a base-case simulation using 2002 Canadian and US national emissions inventories augmented by a more detailed Canadian emissions inventory for agricultural ammonia; (2) a 30% North-American-wide reduction in agricultural ammonia emissions; and (3) a 50% reduction in Canadian beef-cattle ammonia emissions. The simulations show that a 30% continent-wide reduction in agricultural ammonia emissions lead to reductions in median hourly PM2.5 mass of <1 μg m-3 on an annual basis. The atmospheric response to these emission reductions displays marked seasonal variations, and on even shorter time scales, the impacts of the emissions reductions are highly episodic: 95th-percentile hourly PM2.5 mass decreases can be up to a factor of six larger than the median values. A key finding of the modelling work is the linkage between gas and aqueous chemistry and transport; reductions in ammonia emissions affect gaseous ammonia concentrations close to the emissions site, but substantial impacts on particulate matter and atmospheric deposition often occur at considerable distances downwind, with particle nitrate being the main vector of ammonia/um transport. Ammonia emissions reductions therefore have trans-boundary consequences downwind. Calculations of critical-load exceedances for sensitive ecosystems in Canada suggest that ammonia emission reductions will have a minimal impact on current ecosystem acidification within Canada, but may have a substantial impact on future ecosystem acidification. The 50% Canadian beef-cattle ammonia emissions reduction scenario was used to examine model sensitivity to uncertainties in the new Canadian agricultural ammonia emissions inventory, and the simulation results

  7. Diagnosis of air quality through observation and modeling of volatile organic compounds (VOCs) as pollution tracers

    NASA Astrophysics Data System (ADS)

    Liu, Wen-Tzu; Hsieh, Hsin-Cheng; Chen, Sheng-Po; Chang, Julius S.; Lin, Neng-Huei; Chang, Chih-Chung; Wang, Jia-Lin

    2012-08-01

    This study used selected ambient volatile organic compounds (VOCs) as pollution tracers to study the effects of meteorology on air quality. A remote coastal site was chosen as a receptor to monitor pollutants transported upwind from urban traffic and industrial sources. Large concentration variability in VOC concentrations was observed at the coastal site due to rapid changes in meteorology, which caused periodic land-sea exchange of air masses. To assure the quality of the on-line measurements, uniform concentrations of chlorofluorocarbon-113 (CFC-113) were exploited as an internal check of the instrument's stability and the resulting data quality. A VOC speciated air quality model was employed to simulate both temporal and spatial distributions of VOC plumes. The model successfully captured the general features of the variations of toluene as a pollution tracer, which suggests that emissions and meteorology were reasonably well simulated in the model. Through validation by observation, the model can display both the temporal and spatial distribution of air pollutants in a dynamic manner. Thus, a more insightful understanding of how local air quality is affected by meteorology can be obtained.

  8. High Resolution Air Quality Modeling for the Southeast US During SENEX-2013

    NASA Astrophysics Data System (ADS)

    McKeen, S. A.; Ahmadov, R.; Angevine, W. M.; Trainer, M.; Aikin, K. C.; Brock, C. A.; Brown, S. S.; Edwards, P.; De Gouw, J. A.; Gilman, J.; Holloway, J. S.; Lerner, B. M.; Liao, J.; Middlebrook, A. M.; Markovic, M. Z.; Neuman, J. A.; Nowak, J. B.; Olson, J. B.; Schwarz, J. P.; Peischl, J.; Pollack, I. B.; Roberts, J. M.; Veres, P. R.; Warneke, C.; Ryerson, T. B.; Yuan, B.

    2014-12-01

    An intensive measurement campaign - Studying the Interactions Between Natural and Anthropogenic Emissions at the Nexus of Climate Change and Air Quality (SENEX) was carried out by NOAA and other research institutes over the Southeast US during June-July, 2013. A large quantity of meteorological and in-situ chemical composition in-situ measurements were obtained on board the NOAA WP-3D research aircraft, with additional surface monitoring network observations. Results from fully coupled meteorology/air-quality simulations using the WRF-Chem model on 12km grid resolution covering the Eastern continental US during the SENEX time period are presented here. We focus on simulations of ozone and its precursors, related oxidants, particulate matter mass and composition. A recent US EPA anthropogenic emission inventory, NEI-2011 (version 1), is used in the base model simulation. Comparison of model results with the observations are used to quantify model biases and correlations under different emission scenarios, evaluate current estimates of biogenic hydrocarbon fluxes and their impact on air quality over the Southeast US.

  9. A fully coupled regional atmospheric numerical model for integrated air quality and weather forecasting.

    NASA Astrophysics Data System (ADS)

    Freitas, S. R.; Longo, K. M.; Marecal, V.; Pirre, M.; Gmai, T.

    2012-04-01

    A new numerical modelling tool devoted to local and regional studies of atmospheric chemistry from surface to the lower stratosphere designed for both operational and research purposes will be presented. This model is based on the limited-area model CATT-BRAMS (Coupled Aerosol-Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System, Freitas et al. 2009, Longo et al. 2010) which is a meteorological model (BRAMS) including transport processes of gaseous and aerosols (CATT model). BRAMS is a version of the RAMS model (Walko et al. 2000) adapted to better represent tropical and subtropical processes and several new features. CATT-BRAMS has been used operationally at CPTEC (Brazilian Center for Weather Prediction and Climate Studies) since 2003 providing coupled weather and air quality forecast. In the Chemistry-CATT-BRAMS (called hereafter CCATT-BRAMS) a chemical module is fully coupled to the meteorological/tracer transport model CATT-BRAMS. This module includes gaseous chemistry, photochemistry, scavenging and dry deposition. The CCATT-BRAMS model takes advantages of the BRAMS specific development for the tropics/subtropics and of the recent availability of preprocessing tools for chemical mechanisms and of fast codes for photolysis rates. Similarly to BRAMS this model is conceived to run for horizontal resolutions ranging from a few meters to more than a hundred kilometres depending on the chosen scientific objective. In the last decade CCATT-BRAMS has being broadly (or extensively) used for applications mainly over South America, with strong emphasis over the Amazonia area and the main South American megacities. An overview of the model development and main applications will be presented.

  10. Reformulated and alternative fuels: modeled impacts on regional air quality with special emphasis on surface ozone concentration.

    PubMed

    Schell, Benedikt; Ackermann, Ingmar J; Hass, Heinz

    2002-07-15

    The comprehensive European Air Pollution and Dispersion model system was used to estimate the impacts of the usage of reformulated and alternative fuels on regional air quality with special emphasis on surface ozone concentrations. A severe western European summer smog episode in July 1994 has been used as a reference, and the model predictions have been evaluated for this episode. A forecast simulation for the year 2005 (TREND) has been performed, including the future emission development based on the current legislation and technologies available. The results of the scenario TREND are used as a baseline for the other 2005 fuel scenarios, including fuel reformulation, fuel sulfur content, and compressed natural gas (CNG) as an alternative fuel. Compared to the year 1994, significant reductions in episode peak ozone concentrations and ozone grid hours are predicted for the TREND scenario. These reductions are even more pronounced within the investigated alternative and reformulated fuel scenarios. Especially, low sulfur fuels are appropriate for an immediate improvement in air quality, because they effect the emissions of the whole fleet. Furthermore, the simulation results indicate that the introduction of CNG vehicles would also enhance air quality with respect to ozone. PMID:12141497

  11. Development of particulate matter transfer coefficients using a three-dimensional air quality model

    SciTech Connect

    Seigneur, C.; Tonne, C.; Vijayaraghavan, K.; Pai, P.; Levin, L.

    1999-07-01

    Air quality model simulations constitute an effective approach to develop source-receptor relationships (so-called transfer coefficients in the risk analysis framework) because a significant fraction of particulate matter (particularly PM{sub 2.5}) is secondary and, therefore, depends on the atmospheric chemistry of the airshed. These source-receptor relationships can be made specific to source regions and major pollutants. In this study, the authors have used a comprehensive three-dimensional air quality model for PM (SAQM-AERO) to generate episodic transfer coefficients for several source regions in the Los Angeles basin (i.e., surface coastal region, elevated coastal region, central basin, and downwind region). Transfer coefficients were developed by conducting PM air quality simulations with reduced emissions of one of the four precursors (i.e., primary PM, SO{sub 2}, NO{sub x}, and VOC) from each source region. The authors have also compared the transfer coefficients generated from explicit modeling with those based on expert judgment, which were obtained by integrating information from the development of the baseline simulation and across-the-board emission reduction simulations.

  12. A particle grid air quality modeling approach. 1: The dispersion aspect

    SciTech Connect

    Chock, D.P.; Winkler, S.L. )

    1994-01-01

    A particle grid air quality modeling approach that can incorporate chemistry is proposed an an alternative to the conventional partial differential equation (PDE) grid air quality modeling approach. In this approach, each particle is tagged with different species masses and particles in the same grid participate in chemical reactions. The approach is flexible and removes the advection and point source problems encountered in the PDE approach. For a typical grid size of 5 km x 5 km x 50 m used in the lowest layer of an urban air quality model, use of 2000-3000 particles of unequal masses per grid cell will yield a highly accurate grid-averaged instantaneous concentration field that undergoes eddy diffusion for a period of about 1 day. Use of an hourly averaged concentration reduces the demand of particle per cell to about 500. Increasing the grid size also reduces the demand on the number of particles per cell. For the choice of our Lagrangian integral time scales, the time step must be small (10 s) for vertical dispersion simulation but can be large (200 s) for horizontal dispersion simulation. To reduce computation time, a time-splitting scheme is proposed to simulate the horizontal and vertical dispersion simulations in an alternating sequence. The present study also shows that the oft-used second-order-accurate finite difference scheme for solving the diffusion equation tends to overpredict the peak of a sharply peaked concentration.

  13. A database and tool for boundary conditions for regional air quality modeling: description and evaluation

    NASA Astrophysics Data System (ADS)

    Henderson, B. H.; Akhtar, F.; Pye, H. O. T.; Napelenok, S. L.; Hutzell, W. T.

    2014-02-01

    Transported air pollutants receive increasing attention as regulations tighten and global concentrations increase. The need to represent international transport in regional air quality assessments requires improved representation of boundary concentrations. Currently available observations are too sparse vertically to provide boundary information, particularly for ozone precursors, but global simulations can be used to generate spatially and temporally varying lateral boundary conditions (LBC). This study presents a public database of global simulations designed and evaluated for use as LBC for air quality models (AQMs). The database covers the contiguous United States (CONUS) for the years 2001-2010 and contains hourly varying concentrations of ozone, aerosols, and their precursors. The database is complemented by a tool for configuring the global results as inputs to regional scale models (e.g., Community Multiscale Air Quality or Comprehensive Air quality Model with extensions). This study also presents an example application based on the CONUS domain, which is evaluated against satellite retrieved ozone and carbon monoxide vertical profiles. The results show performance is largely within uncertainty estimates for ozone from the Ozone Monitoring Instrument and carbon monoxide from the Measurements Of Pollution In The Troposphere (MOPITT), but there were some notable biases compared with Tropospheric Emission Spectrometer (TES) ozone. Compared with TES, our ozone predictions are high-biased in the upper troposphere, particularly in the south during January. This publication documents the global simulation database, the tool for conversion to LBC, and the evaluation of concentrations on the boundaries. This documentation is intended to support applications that require representation of long-range transport of air pollutants.

  14. Downscaling a Global Climate Model to Simulate Climate Change Impacts on U.S. Regional and Urban Air Quality

    NASA Technical Reports Server (NTRS)

    Trail, M.; Tsimpidi, A. P.; Liu, P.; Tsigaridis, K.; Hu, Y.; Nenes, A.; Russell, A. G.

    2013-01-01

    Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12km by 12km resolution, as well as the effect of evolving climate conditions on the air quality at major U.S. cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the U.S. during fall (Western U.S., Texas, Northeastern, and Southeastern U.S), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). We also find that daily peak temperatures tend to increase in most major cities in the U.S. which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

  15. Intercomparison of the community multiscale air quality model and CALGRID using process analysis.

    PubMed

    O'Neill, Susan M; Lamb, Brian K

    2005-08-01

    This study was designed to examine the similarities and differences between two advanced photochemical air quality modeling systems: EPA Models-3/CMAQ and CALGRID/CALMET. Both modeling systems were applied to an ozone episode that occurred along the I-5 urban corridor in western Washington and Oregon during July 11-14, 1996. Both models employed the same modeling domain and used the same detailed gridded emission inventory. The CMAQ model was run using both the CB-IV and RADM2 chemical mechanisms, while CALGRID was used with the SAPRC-97 chemical mechanism. Outputfrom the Mesoscale Meteorological Model (MM5) employed with observational nudging was used in both models. The two modeling systems, representing three chemical mechanisms and two sets of meteorological inputs, were evaluated in terms of statistical performance measures for both 1- and 8-h average observed ozone concentrations. The results showed that the different versions of the systems were more similar than different, and all versions performed well in the Portland region and downwind of Seattle but performed poorly in the more rural region north of Seattle. Improving the meteorological input into the CALGRID/CALMET system with planetary boundary layer (PBL) parameters from the Models-3/CMAQ meteorology preprocessor (MCIP) improved the performance of the CALGRID/CALMET system. The 8-h ensemble case was often the best performer of all the cases indicating that the models perform better over longer analysis periods. The 1-h ensemble case, derived from all runs, was not necessarily an improvement over the five individual cases, but the standard deviation about the mean provided a measure of overall modeling uncertainty. Process analysis was applied to examine the contribution of the individual processes to the species conservation equation. The process analysis results indicated that the two modeling systems arrive at similar solutions by very different means. Transport rates are faster and exhibit

  16. MEGAPOLI: concept of multi-scale modelling of megacity impact on air quality and climate

    NASA Astrophysics Data System (ADS)

    Baklanov, A.; Lawrence, M.; Pandis, S.; Mahura, A.; Finardi, S.; Moussiopoulos, N.; Beekmann, M.; Laj, P.; Gomes, L.; Jaffrezo, J.-L.; Borbon, A.; Coll, I.; Gros, V.; Sciare, J.; Kukkonen, J.; Galmarini, S.; Giorgi, F.; Grimmond, S.; Esau, I.; Stohl, A.; Denby, B.; Wagner, T.; Butler, T.; Baltensperger, U.; Builtjes, P.; van den Hout, D.; van der Gon, H. D.; Collins, B.; Schluenzen, H.; Kulmala, M.; Zilitinkevich, S.; Sokhi, R.; Friedrich, R.; Theloke, J.; Kummer, U.; Jalkinen, L.; Halenka, T.; Wiedensholer, A.; Pyle, J.; Rossow, W. B.

    2010-11-01

    The EU FP7 Project MEGAPOLI: "Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation" (http://megapoli.info) brings together leading European research groups, state-of-the-art scientific tools and key players from non-European countries to investigate the interactions among megacities, air quality and climate. MEGAPOLI bridges the spatial and temporal scales that connect local emissions, air quality and weather with global atmospheric chemistry and climate. The suggested concept of multi-scale integrated modelling of megacity impact on air quality and climate and vice versa is discussed in the paper. It requires considering different spatial and temporal dimensions: time scales from seconds and hours (to understand the interaction mechanisms) up to years and decades (to consider the climate effects); spatial resolutions: with model down- and up-scaling from street- to global-scale; and two-way interactions between meteorological and chemical processes.

  17. Combining regression analysis and air quality modelling to predict benzene concentration levels

    NASA Astrophysics Data System (ADS)

    Vlachokostas, Ch.; Achillas, Ch.; Chourdakis, E.; Moussiopoulos, N.

    2011-05-01

    State of the art epidemiological research has found consistent associations between traffic-related air pollution and various outcomes, such as respiratory symptoms and premature mortality. However, many urban areas are characterised by the absence of the necessary monitoring infrastructure, especially for benzene (C 6H 6), which is a known human carcinogen. The use of environmental statistics combined with air quality modelling can be of vital importance in order to assess air quality levels of traffic-related pollutants in an urban area in the case where there are no available measurements. This paper aims at developing and presenting a reliable approach, in order to forecast C 6H 6 levels in urban environments, demonstrated for Thessaloniki, Greece. Multiple stepwise regression analysis is used and a strong statistical relationship is detected between C 6H 6 and CO. The adopted regression model is validated in order to depict its applicability and representativeness. The presented results demonstrate that the adopted approach is capable of capturing C 6H 6 concentration trends and should be considered as complementary to air quality monitoring.

  18. Air quality modeling of interpollutant trading for ozone precursors in an urban area.

    PubMed

    Wang, Linlin; Allen, David T; McDonald-Buller, Elena C

    2005-10-01

    Emission trading is a market-based approach designed to improve the efficiency and economic viability of emission control programs; emission trading has typically been confined to trades among single pollutants. Interpollutant trading (IPT), as described in this work, allows for trades among emissions of different compounds that affect the same air quality end point, in this work, ambient ozone (O3) concentrations. Because emissions of different compounds impact air quality end points differently, weighting factors or trading ratios (tons of emissions of nitrogen oxides (NO(x)) equivalent to a ton of emissions of volatile organic compounds [VOCs]) must be developed to allow for IPT. In this work, IPT indices based on reductions in O3 concentrations and based on reductions in population exposures to O3 were developed and evaluated using a three-dimensional gridded photochemical model for Austin, TX, a city currently on the cusp of nonattainment with the National Ambient Air Quality Standards for O3 concentrations averaged over 8 hr. Emissions of VOC and NO(x) from area and mobile sources in Austin are larger than emissions from point sources. The analysis indicated that mobile and area sources exhibited similar impacts. Trading ratios based on maximum O3 concentration or population exposure were similar. In contrast, the trading ratios did exhibit significant (more than a factor of two) day-to-day variability. Analysis of the air quality modeling indicated that the daily variability in trading ratios could be attributed to daily variations in both emissions and meteorology. PMID:16295279

  19. CANFIS: A non-linear regression procedure to produce statistical air-quality forecast models

    SciTech Connect

    Burrows, W.R.; Montpetit, J.; Pudykiewicz, J.

    1997-12-31

    Statistical models for forecasts of environmental variables can provide a good trade-off between significance and precision in return for substantial saving of computer execution time. Recent non-linear regression techniques give significantly increased accuracy compared to traditional linear regression methods. Two are Classification and Regression Trees (CART) and the Neuro-Fuzzy Inference System (NFIS). Both can model predict and distributions, including the tails, with much better accuracy than linear regression. Given a learning data set of matched predict and predictors, CART regression produces a non-linear, tree-based, piecewise-continuous model of the predict and data. Its variance-minimizing procedure optimizes the task of predictor selection, often greatly reducing initial data dimensionality. NFIS reduces dimensionality by a procedure known as subtractive clustering but it does not of itself eliminate predictors. Over-lapping coverage in predictor space is enhanced by NFIS with a Gaussian membership function for each cluster component. Coefficients for a continuous response model based on the fuzzified cluster centers are obtained by a least-squares estimation procedure. CANFIS is a two-stage data-modeling technique that combines the strength of CART to optimize the process of selecting predictors from a large pool of potential predictors with the modeling strength of NFIS. A CANFIS model requires negligible computer time to run. CANFIS models for ground-level O{sub 3}, particulates, and other pollutants will be produced for each of about 100 Canadian sites. The air-quality models will run twice daily using a small number of predictors isolated from a large pool of upstream and local Lagrangian potential predictors.

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

    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

  1. Applications of the three-dimensional air quality system to western U.S. air quality: IDEA, smog blog, smog stories, airquest, and the remote sensing information gateway.

    PubMed

    Hoff, Raymond; Zhang, Hai; Jordan, Nikisa; Prados, Ana; Engel-Cox, Jill; Huff, Amy; Weber, Stephanie; Zell, Erica; Kondragunta, Shobha; Szykman, James; Johns, Brad; Dimmick, Fred; Wimmers, Anthony; Al-Saadi, Jay; Kittaka, Chieko

    2009-08-01

    A system has been developed to combine remote sensing and ground-based measurements of aerosol concentration and aerosol light scattering parameters into a three-dimensional view of the atmosphere over the United States. Utilizing passive and active remote sensors from space and the ground, the system provides tools to visualize particulate air pollution in near real time and archive the results for retrospective analyses. The main components of the system (Infusing satellite Data into Environmental Applications [IDEA], the U.S. Air Quality Weblog [Smog Blog], Smog Stories, U.S. Environmental Protection Agency's AIRQuest decision support system, and the Remote Sensing Information Gateway [RSIG]) are described, and the relationship of how data move from one system to another is outlined. To provide examples of how the results can be used to analyze specific pollution episodes, three events (two fires and one wintertime low planetary boundary layer haze) are discussed. Not all tools are useful at all times, and the limitations, including the sparsity of some data, the interference caused by overlying clouds, etc., are shown. Nevertheless, multiple sources of data help a state, local, or regional air quality analyst construct a more thorough picture of a daily air pollution situation than what one would obtain with only surface-based sensors. PMID:19728492

  2. "Developing a multi hazard air quality forecasting model for Santiago, Chile"

    NASA Astrophysics Data System (ADS)

    Mena, M. A.; Delgado, R.; Hernandez, R.; Saide, P. E.; Cienfuegos, R.; Pinochet, J. I.; Molina, L. T.; Carmichael, G. R.

    2013-05-01

    Santiago, Chile has reduced annual particulate matter from 69ug/m3 (in 1989) to 25ug/m3 (in 2012), mostly by forcing industry, the transport sector, and the residential heating sector to adopt stringent emission standards to be able to operate under bad air days. Statistical forecasting has been used to predict bad air days, and pollution control measures in Santiago, Chile, for almost two decades. Recently an operational PM2.5 deterministic model has been implemented using WRF-Chem. The model was developed by the University of Iowa and is run at the Chilean Meteorological Office. Model configuration includes high resolution emissions gridding (2km) and updated population distribution using 2008 data from LANDSCAN. The model is run using a 2 day spinup with a 5 day forecast. This model has allowed a preventive approach in pollution control measures, as episodes are the results of multiple days of bad dispersion. Decreeing air pollution control measures in advance of bad air days resulted in a reduction of 40% of alert days (80ug/m3 mean 24h PM2.5) and 66% of "preemergency days" (110ug/m3 mean 24h PM2.5) from 2011 to 2012, despite similar meteorological conditions. This model will be deployed under a recently funded Center for Natural Disaster Management, and include other meteorological hazards such as flooding, high temperature, storm waves, landslides, UV radiation, among other parameters. This paper will present the results of operational air quality forecasting, and the methodology that will be used to transform WRF-Chem into a multi hazard forecasting system.

  3. Air quality modeling with WRF-Chem v3.5 in East Asia: sensitivity to emissions and evaluation of simulated air quality

    NASA Astrophysics Data System (ADS)

    Zhong, Min; Saikawa, Eri; Liu, Yang; Naik, Vaishali; Horowitz, Larry W.; Takigawa, Masayuki; Zhao, Yu; Lin, Neng-Huei; Stone, Elizabeth A.

    2016-04-01

    We conducted simulations using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.5 to study air quality in East Asia at a spatial resolution of 20 km × 20 km. We find large discrepancies between two existing emissions inventories: the Regional Emission Inventory in ASia version 2 (REAS) and the Emissions Database for Global Atmospheric Research version 4.2 (EDGAR) at the provincial level in China, with maximum differences of up to 500 % for CO emissions, 190 % for NO, and 160 % for primary PM10. Such discrepancies in the magnitude and the spatial distribution of emissions for various species lead to a 40-70 % difference in surface PM10 concentrations, 16-20 % in surface O3 mixing ratios, and over 100 % in SO2 and NO2 mixing ratios in the polluted areas of China. WRF-Chem is sensitive to emissions, with the REAS-based simulation reproducing observed concentrations and mixing ratios better than the EDGAR-based simulation for July 2007. We conduct additional model simulations using REAS emissions for January, April, July, and October of 2007 and evaluate simulations with available ground-level observations. The model results illustrate clear regional variations in the seasonal cycle of surface PM10 and O3 over East Asia. The model meets the air quality model performance criteria for both PM10 (mean fractional bias, MFB ⩽ ±60 %) and O3 (MFB ⩽ ±15 %) at most of the observation sites, although the model underestimates PM10 over northeastern China in January. The model predicts the observed SO2 well at sites in Japan, while it tends to overestimate SO2 in China in July and October. The model underestimates observed NO2 in all 4 months. Our study highlights the importance of constraining emissions at the provincial level for regional air quality modeling over East Asia. Our results suggest that future work should focus on the improvement of provincial-level emissions especially estimating primary PM, SO2, and NOx.

  4. Statistical Downscaling of WRF-Chem Model: An Air Quality Analysis over Bogota, Colombia

    NASA Astrophysics Data System (ADS)

    Kumar, Anikender; Rojas, Nestor

    2015-04-01

    Statistical downscaling is a technique that is used to extract high-resolution information from regional scale variables produced by coarse resolution models such as Chemical Transport Models (CTMs). The fully coupled WRF-Chem (Weather Research and Forecasting with Chemistry) model is used to simulate air quality over Bogota. Bogota is a tropical Andean megacity located over a high-altitude plateau in the middle of very complex terrain. The WRF-Chem model was adopted for simulating the hourly ozone concentrations. The computational domains were chosen of 120x120x32, 121x121x32 and 121x121x32 grid points with horizontal resolutions of 27, 9 and 3 km respectively. The model was initialized with real boundary conditions using NCAR-NCEP's Final Analysis (FNL) and a 1ox1o (~111 km x 111 km) resolution. Boundary conditions were updated every 6 hours using reanalysis data. The emission rates were obtained from global inventories, namely the REanalysis of the TROpospheric (RETRO) chemical composition and the Emission Database for Global Atmospheric Research (EDGAR). Multiple linear regression and artificial neural network techniques are used to downscale the model output at each monitoring stations. The results confirm that the statistically downscaled outputs reduce simulated errors by up to 25%. This study provides a general overview of statistical downscaling of chemical transport models and can constitute a reference for future air quality modeling exercises over Bogota and other Colombian cities.

  5. DIAGNOSTIC EVALUATION OF AIR QUALITY MODELS USING ADVANCED METHODS WITH SPECIALIZED OBSERVATIONS OF SELECTED AMBIENT SPECIES -PART II

    EPA Science Inventory

    This is Part 2 of "Diagnostic Evaluation of Air Quality Models Using Advanced Methods with Specialized Observations of Selected Ambient Species". A limited field campaign to make specialized observations of selected ambient species using advanced and innovative instrumentation f...

  6. TEMPORAL SIGNATURES OF AIR QUALITY OBSERVATIONS AND MODEL OUTPUTS: DO TIME SERIES DECOMPOSITION METHODS CAPTURE RELEVANT TIME SCALES?

    EPA Science Inventory

    Time series decomposition methods were applied to meteorological and air quality data and their numerical model estimates. Decomposition techniques express a time series as the sum of a small number of independent modes which hypothetically represent identifiable forcings, thereb...

  7. Air Quality Modeling in Support of the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS)

    EPA Science Inventory

    A major challenge in traffic-related air pollution exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related a...

  8. Contribution of Oil and Natural Gas Emissions on Summertime Air Quality over the Continental US from an Air Quality Modeling Perspective

    NASA Astrophysics Data System (ADS)

    Ahmadov, R.; McKeen, S. A.; Angevine, W. M.; De Gouw, J. A.; Frost, G. J.; Gilman, J.; Peischl, J.; Ryerson, T. B.; Warneke, C.; Brown, S. S.; Trainer, M.; Middlebrook, A. M.; Lerner, B. M.

    2015-12-01

    The rapid development of the oil and natural gas production across the United States in recent decade has been associated with significant amounts of methane and other volatile organic compounds (VOCs) released to the atmosphere. It is challenging for the existing emission inventories to adequately represent the rapidly evolving oil and natural gas production sector emissions. Hence, their contribution on air quality, especially summertime ozone and particulate matter pollution is not well characterized. We present methane and air quality simulations for summer of 2013 over the continental US by using a coupled meteorology-chemistry model WRF-Chem on 12km resolution grid over the CONUS domain. In the model we used VOCs and nitrogen oxides (NOx) emission estimates constrained by the in-situ measurements for a number of the shale basins obtained by NOAA's multiple fields campaigns. Also, a bottom-up emission dataset for the oil/gas sector, based on EPA's National Emission Inventory 2011 version 2 release was used in this modeling study. Here, we discuss the differences in the NOx and VOC emissions for the oil/gas sector in the top-down and bottom-up emission estimates. We modeled the contribution of the oil/gas sector emissions in the US to ozone, several oxidants, PM2.5 mass and composition. For the model evaluations, detailed observations of meteorology, gaseous and aerosol species within several oil/gas producing basins obtained during NOAA sponsored aircraft SENEX-2013 field study were utilized. In addition, continuous ozone and PM2.5 measurements from hundreds of surface stations within the US EPA AQS data archive were used to evaluate the model simulations during summer of 2013.

  9. Diagnostic air quality model evaluation of source-specific primary and secondary fine particulate carbon.

    PubMed

    Napelenok, Sergey L; Simon, Heather; Bhave, Prakash V; Pye, Havala O T; Pouliot, George A; Sheesley, Rebecca J; Schauer, James J

    2014-01-01

    Ambient measurements of 78 source-specific tracers of primary and secondary carbonaceous fine particulate matter collected at four midwestern United States locations over a full year (March 2004-February 2005) provided an unprecedented opportunity to diagnostically evaluate the results of a numerical air quality model. Previous analyses of these measurements demonstrated excellent mass closure for the variety of contributing sources. In this study, a carbon-apportionment version of the Community Multiscale Air Quality (CMAQ) model was used to track primary organic and elemental carbon emissions from 15 independent sources such as mobile sources and biomass burning in addition to four precursor-specific classes of secondary organic aerosol (SOA) originating from isoprene, terpenes, aromatics, and sesquiterpenes. Conversion of the source-resolved model output into organic tracer concentrations yielded a total of 2416 data pairs for comparison with observations. While emission source contributions to the total model bias varied by season and measurement location, the largest absolute bias of -0.55 μgC/m(3) was attributed to insufficient isoprene SOA in the summertime CMAQ simulation. Biomass combustion was responsible for the second largest summertime model bias (-0.46 μgC/m(3) on average). Several instances of compensating errors were also evident; model underpredictions in some sectors were masked by overpredictions in others. PMID:24245475

  10. Satellite Characterization of Fire Emissions of Aerosols and Gases Relevant to Air-Quality Modeling

    NASA Astrophysics Data System (ADS)

    Ichoku, C. M.; Ellison, L.; Yue, Y.; Wang, J.

    2015-12-01

    Because of the transient and widespread nature of wildfires and other types of open biomass burning, satellite remote sensing has become an indispensable technique for characterizing their smoke emissions for modeling applications, especially at regional to global scales. Fire radiative energy (FRE), whose instantaneous rate of release or fire radiative power (FRP) is measurable from space, has been found to be proportional to both the biomass consumption and emission of aerosol particulate matter. We have leveraged this relationship to generate a global, gridded smoke-aerosol emission coefficients (Ce) dataset based on FRP and aerosol optical thickness (AOT) measurements from the MODIS sensors aboard the Terra and Aqua satellites. Ce is a simple coefficient to convert FRE to smoke aerosol emissions, in the same manner as traditional emission factors are used to convert burned biomass to emissions. The first version of this Fire Energetics and Emissions Research (FEER.v1) global gridded Ce product at 1°x1° resolution is available at http://feer.gsfc.nasa.gov/. Based on published emission ratios, the FEER.v1 Ce product for total smoke aerosol has also been used to generate similar products for specific fire-emitted aerosols and gases, including those that are regulated as 'criteria pollutants' under the US Environmental Protection Agency's National Ambient Air Quality Standards (NAAQS), such as particulate matter (PM) and carbon monoxide (CO). These gridded Ce products were used in conjunction with satellite measurements of FRP to derive emissions of several smoke constituents, which were applied to WRF-Chem fully coupled meteorology-chemistry-aerosol model simulations, with promising results. In this presentation, we analyze WRF-Chem simulations of surface-level concentrations of various pollutants based on FEER.v1 emission products to illustrate their value for air-quality modeling, particularly in parts of Africa and southeast Asia where ground-based air-quality

  11. Process air quality data

    NASA Technical Reports Server (NTRS)

    Butler, C. M.; Hogge, J. E.

    1978-01-01

    Air quality sampling was conducted. Data for air quality parameters, recorded on written forms, punched cards or magnetic tape, are available for 1972 through 1975. Computer software was developed to (1) calculate several daily statistical measures of location, (2) plot time histories of data or the calculated daily statistics, (3) calculate simple correlation coefficients, and (4) plot scatter diagrams. Computer software was developed for processing air quality data to include time series analysis and goodness of fit tests. Computer software was developed to (1) calculate a larger number of daily statistical measures of location, and a number of daily monthly and yearly measures of location, dispersion, skewness and kurtosis, (2) decompose the extended time series model and (3) perform some goodness of fit tests. The computer program is described, documented and illustrated by examples. Recommendations are made for continuation of the development of research on processing air quality data.

  12. Finite element simulation of a local scale air quality model over complex terrain

    NASA Astrophysics Data System (ADS)

    Oliver, A.; Montero, G.; Montenegro, R.; Rodríguez, E.; Escobar, J. M.; Perez-Foguet, A.

    2012-05-01

    In this paper we propose a finite element method approach for modelling the air quality in a local scale over complex terrain. The area of interest is up to tens of kilometres and it includes pollutant sources. The proposed methodology involves the generation of an adaptive tetrahedral mesh, the computation of an ambient wind field, the inclusion of the plume rise effect in the wind field, and the simulation of transport and reaction of pollutants. We apply our methodology to simulate a fictitious pollution episode in La Palma island (Canary Island, Spain).

  13. Rocket exhaust effluent modeling for tropospheric air quality and environmental assessments

    NASA Technical Reports Server (NTRS)

    Stephens, J. B.; Stewart, R. B.

    1977-01-01

    The various techniques for diffusion predictions to support air quality predictions and environmental assessments for aerospace applications are discussed in terms of limitations imposed by atmospheric data. This affords an introduction to the rationale behind the selection of the National Aeronautics and Space Administration (NASA)/Marshall Space Flight Center (MSFC) Rocket Exhaust Effluent Diffusion (REED) program. The models utilized in the NASA/MSFC REED program are explained. This program is then evaluated in terms of some results from a joint MSFC/Langley Research Center/Kennedy Space Center Titan Exhaust Effluent Prediction and Monitoring Program.

  14. Application of a three-dimensional, prognostic model to Mexico City air quality studies

    SciTech Connect

    Williams, M.D.; Porch, W.M.

    1991-01-01

    Los Alamos National Laboratory and Instituto Mexicano del Petroleo have embarked on a joint study of options for improving air quality in Mexico City. One of the first steps in the process is to develop an understanding of the existing air quality situation. In this context we have begun by modifying a three-dimensional, prognostic, higher order turbulence model for atmospheric circulation (HOTMAC) to threat domains which include an urbanized area. This sophisticated meteorological model is required because of the complexity of the terrain and the relative paucity of meteorological data. The basic model (HOTMAC) was modified to include an urban canopy and urban heat sources. HOTMAC has been used to drive a Monte-Carlo kernel dispersion code (RAPTAD). RAPTAD was used to model the flow of carbon monoxide and sulfur dioxide, and the results have been compared to measurements. In addition the modeled wind fields which are based on upper-level winds from the airport are compared to the measured low-level winds. Also, a four year history of temperature structure obtained from the rawinsode at the airport has been related to mixing parameters and less reactive pollutant measurements (such as carbon monoxide). 10 refs., 15 figs.

  15. A WebGIS-based system for analyzing and visualizing air quality data for Shanghai Municipality

    NASA Astrophysics Data System (ADS)

    Wang, Manyi; Liu, Chaoshun; Gao, Wei

    2014-10-01

    An online visual analytical system based on Java Web and WebGIS for air quality data for Shanghai Municipality was designed and implemented to quantitatively analyze and qualitatively visualize air quality data. By analyzing the architecture of WebGIS and Java Web, we firstly designed the overall scheme for system architecture, then put forward the software and hardware environment and also determined the main function modules for the system. The visual system was ultimately established with the DIV + CSS layout method combined with JSP, JavaScript, and some other computer programming languages based on the Java programming environment. Moreover, Struts, Spring, and Hibernate frameworks (SSH) were integrated in the system for the purpose of easy maintenance and expansion. To provide mapping service and spatial analysis functions, we selected ArcGIS for Server as the GIS server. We also used Oracle database and ESRI file geodatabase to store spatial data and non-spatial data in order to ensure the data security. In addition, the response data from the Web server are resampled to implement rapid visualization through the browser. The experimental successes indicate that this system can quickly respond to user's requests, and efficiently return the accurate processing results.

  16. The statistical evaluation and comparison of ADMS-Urban model for the prediction of nitrogen dioxide with air quality monitoring network.

    PubMed

    Dėdelė, Audrius; Miškinytė, Auksė

    2015-09-01

    In many countries, road traffic is one of the main sources of air pollution associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered to be a measure of traffic-related air pollution, with concentrations tending to be higher near highways, along busy roads, and in the city centers, and the exceedances are mainly observed at measurement stations located close to traffic. In order to assess the air quality in the city and the air pollution impact on public health, air quality models are used. However, firstly, before the model can be used for these purposes, it is important to evaluate the accuracy of the dispersion modelling as one of the most widely used method. The monitoring and dispersion modelling are two components of air quality monitoring system (AQMS), in which statistical comparison was made in this research. The evaluation of the Atmospheric Dispersion Modelling System (ADMS-Urban) was made by comparing monthly modelled NO2 concentrations with the data of continuous air quality monitoring stations in Kaunas city. The statistical measures of model performance were calculated for annual and monthly concentrations of NO2 for each monitoring station site. The spatial analysis was made using geographic information systems (GIS). The calculation of statistical parameters indicated a good ADMS-Urban model performance for the prediction of NO2. The results of this study showed that the agreement of modelled values and observations was better for traffic monitoring stations compared to the background and residential stations. PMID:26293894

  17. Characterizing Emissions from Prescribed Fires and Assessing Impacts to Air Quality in the Lake Tahoe Basin Using Dispersion Modeling

    NASA Astrophysics Data System (ADS)

    Malamakal, Tom M.

    A PM2.5 monitoring network was established around Lake Tahoe during fall 2011, which, in conjunction with measurements at prescribed burns and smoke dispersion modeling based on the Fire Emission Production Simulator and the Hybrid Single Particle Lagrangian Integrated Trajectory (FEPS-HYSPLIT) Model, served to evaluate the prescribed burning impacts on air quality. Emissions from pile and understory prescribed burns were characterized using a mobile air monitoring system. In field PM2.5 emission factors showed ranges consistent with laboratory combustion of wet and dry fuels. Measurements in the smoke plume showed progression from flaming to smoldering phase consistent with FEPS and PM2.5 emission factors generally increased with decreasing combustion efficiency. Model predicted smoke contributions are consistent with elevated ambient PM2.5 concentrations in three case studies, and high meteorological model resolution (2km x 2 km) seems to produce accurate smoke arriving times. In other cases, the model performance is difficult to evaluate due to low predicted smoke contributions relative to the typical ambient PM2.5 level. Synergistic assessment of modeling and measurement can be used to determine basin air quality impact. The findings from this study will help land management agencies better understand the implications of managing fire at the wildland-urban interface.

  18. An inexact double-sided chance-constrained model for air quality management in Nanshan District, Shengzhen, China

    NASA Astrophysics Data System (ADS)

    Shao, Liguo; Xu, Ye; Huang, Guohe

    2014-12-01

    In this study, an inexact double-sided fuzzy-random-chance-constrained programming (IDSFRCCP) model was developed for supporting air quality management of the Nanshan District of Shenzhen, China, under uncertainty. IDSFRCCP is an integrated model incorporating interval linear programming and double-sided fuzzy-random-chance-constrained programming models. It can express uncertain information as both fuzzy random variables and discrete intervals. The proposed model was solved based on the stochastic and fuzzy chance-constrained programming techniques and an interactive two-step algorithm. The air quality management system of Nanshan District, including one pollutant, six emission sources, six treatment technologies and four receptor sites, was used to demonstrate the applicability of the proposed method. The results indicated that the IDSFRCCP was capable of helping decision makers to analyse trade-offs between system cost and risk of constraint violation. The mid-range solutions tending to lower bounds with moderate αh and qi values were recommended as decision alternatives owing to their robust characteristics.

  19. FIRST RESULTS FROM OPERATIONAL TESTING OF THE U.S. EPA MODELS-3 COMMUNITY MULTISCALE MODEL FOR AIR QUALITY (CMAQ)

    EPA Science Inventory

    The Models 3 / Community Multiscale Model for Air Quality (CMAQ) has been designed for one-atmosphere assessments for multiple pollutants including ozone (O3), particulate matter (PM10, PM2.5), and acid / nutrient deposition. In this paper we report initial results of our evalu...

  20. DEVELOPMENT OF AN AGGREGATION AND EPISODE SELECTION SCHEME TO SUPPORT THE MODELS-3 COMMUNITY MULTISCALE AIR QUALITY MODEL

    EPA Science Inventory

    The development of an episode selection and aggregation approach, designed to support distributional estimation of use with the Models-3 Community Multiscale Air Quality (CMAQ) model, is described. The approach utilized cluster analysis of the 700-hPa east-west and north-south...

  1. Air quality modeling in the Oviedo urban area (NW Spain) by using multivariate adaptive regression splines.

    PubMed

    Nieto, P J García; Antón, J C Álvarez; Vilán, J A Vilán; García-Gonzalo, E

    2015-05-01

    The aim of this research work is to build a regression model of air quality by using the multivariate adaptive regression splines (MARS) technique in the Oviedo urban area (northern Spain) at a local scale. To accomplish the objective of this study, the experimental data set made up of nitrogen oxides (NO x ), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3), and dust (PM10) was collected over 3 years (2006-2008). The US National Ambient Air Quality Standards (NAAQS) establishes the limit values of the main pollutants in the atmosphere in order to ensure the health of healthy people. Firstly, this MARS regression model captures the main perception of statistical learning theory in order to obtain a good prediction of the dependence among the main pollutants in the Oviedo urban area. Secondly, the main advantages of MARS are its capacity to produce simple, easy-to-interpret models, its ability to estimate the contributions of the input variables, and its computational efficiency. Finally, on the basis of these numerical calculations, using the MARS technique, conclusions of this research work are exposed. PMID:25414030

  2. AQA-PM: Extension of the Air-Quality model for Austria with satellite based Particulate Matter estimates

    NASA Astrophysics Data System (ADS)

    Hirtl, M.; Mantovani, S.; Krüger, B. C.; Triebnig, G.

    2012-04-01

    Air quality is a key element for the well-being and quality of life of European citizens. Air pollution measurements and modeling tools are essential for assessment of air quality according to EU legislation. The responsibilities of ZAMG as the national weather service of Austria include the support of the federal states and the public in questions connected to the protection of the environment in the frame of advisory and counseling services as well as expert opinions. The Air Quality model for Austria (AQA) is operated at ZAMG in cooperation with the University of Natural Resources and Applied Life Sciences in Vienna (BOKU) by order of the regional governments since 2005. AQA conducts daily forecasts of gaseous and particulate (PM10) air pollutants over Austria. In the frame of the project AQA-PM (funded by FFG), satellite measurements of the Aerosol Optical Thickness (AOT) and ground-based PM10-measurements are combined to highly-resolved initial fields using assimilation techniques. It is expected that the assimilation of satellite measurements will significantly improve the quality of AQA. Currently no observations are considered in the modeling system. At the current stage of the project, different datasets have been collected (ground measurements, satellite measurements, fine resolved regional emission inventories) and are analyzed and prepared for further processing. This contribution gives an overview of the project working plan and the upcoming developments. The goal of this project is to improve the PM10-forecasts for Austria with the integration of satellite based measurements and to provide a comprehensive product-platform.

  3. CALIPSO Satellite Lidar Identification Of Elevated Dust Over Australia Compared With Air Quality Model PM60 Forecasts

    NASA Technical Reports Server (NTRS)

    Young, Stuart A.; Vaughan, Mark; Omar, Ali; Liu, Zhaoyan; Lee, Sunhee; Hu, Youngxiang; Cope, Martin

    2008-01-01

    Global measurements of the vertical distribution of clouds and aerosols have been recorded by the lidar on board the CALIPSO (Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations) satellite since June 2006. Such extensive, height-resolved measurements provide a rare and valuable opportunity for developing, testing and validating various atmospheric models, including global climate, numerical weather prediction, chemical transport and air quality models. Here we report on the initial results of an investigation into the performance of the Australian Air Quality Forecast System (AAQFS) model in forecasting the distribution of elevated dust over the Australian region. The model forecasts of PM60 dust distribution are compared with the CALIPSO lidar Vertical Feature Mask (VFM) data product. The VFM classifies contiguous atmospheric regions of enhanced backscatter as either cloud or aerosols. Aerosols are further classified into six subtypes. By comparing forecast PM60 concentration profiles to the spatial distribution of dust reported in the CALIPSO VFM, we can assess the model s ability to predict the occurrence and the vertical and horizontal extents of dust events within the study area.

  4. Ozone-vegetation interaction in the Earth system: implications for air quality, ecosystems and agriculture

    NASA Astrophysics Data System (ADS)

    Tai, A. P. K.; Lombardozzi, D.; Val Martin, M.; Heald, C. L.

    2015-12-01

    Surface ozone is one of the most significant air pollutants due to its damaging effects not only on human health, but also on vegetation and crop productivity. Chronic ozone exposure has been shown to reduce photosynthesis and interfere with gas exchange in plants, which in turn affect the surface energy balance, carbon sink and other biogeochemical fluxes. Ozone damage on vegetation can thus have major ramifications on climate and atmospheric composition, including possible feedbacks onto ozone itself (see figure) that are not well understood. The damage of ozone on crops has been well documented, but a mechanistic understanding is not well established. Here we present several results pertaining to ozone-vegetation interaction. Using the Community Earth System Model, we find that inclusion of ozone damage on plants reduces the global land carbon sink by up to 5%, while simulated ozone is modified by -20 to +4 ppbv depending on the relative importance of competing mechanisms in different regions. We also perform a statistical analysis of multidecadal global datasets of crop yields, agroclimatic variables and ozone exposures to characterize the spatial variability of crop sensitivity to ozone and temperature extremes, specifically accounting for the confounding effect of ozone-temperature covariation. We find that several crops exhibit stronger sensitivity to ozone than found by previous field studies, with a strong anticorrelation between the sensitivity and average ozone levels that reflects biological adaptive ozone resistance. Our results show that a more complete understanding of ozone-vegetation interaction is necessary to derive more realistic future projections of climate, air quality and agricultural production, and thereby to formulate optimal strategies to safeguard public health and food security.

  5. Evaluation of a seven-year air quality simulation using the Weather Research and Forecasting (WRF)/Community Multiscale Air Quality (CMAQ) models in the eastern United States.

    PubMed

    Zhang, Hongliang; Chen, Gang; Hu, Jianlin; Chen, Shu-Hua; Wiedinmyer, Christine; Kleeman, Michael; Ying, Qi

    2014-03-01

    The performance of the Weather Research and Forecasting (WRF)/Community Multi-scale Air Quality (CMAQ) system in the eastern United States is analyzed based on results from a seven-year modeling study with a 4-km spatial resolution. For 2-m temperature, the monthly averaged mean bias (MB) and gross error (GE) values are generally within the recommended performance criteria, although temperature is over-predicted with MB values up to 2K. Water vapor at 2-m is well-predicted but significant biases (>2 g kg(-1)) were observed in wintertime. Predictions for wind speed are satisfactory but biased towards over-prediction with 0

  6. A computationally-efficient secondary organic aerosol module for three-dimensional air quality models

    NASA Astrophysics Data System (ADS)

    Liu, P.; Zhang, Y.

    2008-04-01

    Accurately simulating secondary organic aerosols (SOA) in three-dimensional (3-D) air quality models is challenging due to the complexity of the physics and chemistry involved and the high computational demand required. A computationally-efficient yet accurate SOA module is necessary in 3-D applications for long-term simulations and real-time air quality forecasting. A coupled gas and aerosol box model (i.e., 0-D CMAQ-MADRID 2) is used to optimize relevant processes in order to develop such a SOA module. Solving the partitioning equations for condensable volatile organic compounds (VOCs) and calculating their activity coefficients in the multicomponent mixtures are identified to be the most computationally-expensive processes. The two processes can be speeded up by relaxing the error tolerance levels and reducing the maximum number of iterations of the numerical solver for the partitioning equations for organic species; turning on organic-inorganic interactions only when the water content associated with organic compounds is significant; and parameterizing the calculation of activity coefficients for organic mixtures in the hydrophilic module. The optimal speed-up method can reduce the total CPU cost by up to a factor of 29.7 with ±15% deviation from benchmark results. These speedup methods are applicable to other SOA modules that are based on partitioning theories.

  7. A computationally-efficient secondary organic aerosol module for three-dimensional air quality models

    NASA Astrophysics Data System (ADS)

    Liu, P.; Zhang, Y.

    2008-07-01

    Accurately simulating secondary organic aerosols (SOA) in three-dimensional (3-D) air quality models is challenging due to the complexity of the physics and chemistry involved and the high computational demand required. A computationally-efficient yet accurate SOA module is necessary in 3-D applications for long-term simulations and real-time air quality forecasting. A coupled gas and aerosol box model (i.e., 0-D CMAQ-MADRID 2) is used to optimize relevant processes in order to develop such a SOA module. Solving the partitioning equations for condensable volatile organic compounds (VOCs) and calculating their activity coefficients in the multicomponent mixtures are identified to be the most computationally-expensive processes. The two processes can be speeded up by relaxing the error tolerance levels and reducing the maximum number of iterations of the numerical solver for the partitioning equations for organic species; conditionally activating organic-inorganic interactions; and parameterizing the calculation of activity coefficients for organic mixtures in the hydrophilic module. The optimal speed-up method can reduce the total CPU cost by up to a factor of 31.4 from benchmark under the rural conditions with 2 ppb isoprene and by factors of 10 71 under various test conditions with 2 10 ppb isoprene and >40% relative humidity while maintaining ±15% deviation. These speed-up methods are applicable to other SOA modules that are based on partitioning theories.

  8. Development of algorithms and approximations for rapid operational air quality modelling

    NASA Astrophysics Data System (ADS)

    Barrett, Steven R. H.; Britter, Rex E.

    In regulatory and public health contexts the long-term average pollutant concentration in the vicinity of a source is frequently of interest. Well-developed modelling tools such as AERMOD and ADMS are able to generate time-series air quality estimates of considerable accuracy, applying an up-to-date understanding of atmospheric boundary layer behaviour. However, such models incur a significant computational cost with runtimes of hours to days. These approaches are often acceptable when considering a single industrial complex, but for widespread policy analyses the computational cost rapidly becomes intractable. In this paper we present some mathematical techniques and algorithmic approaches that can make air quality estimates several orders of magnitude faster. We show that, for long-term average concentrations, lateral dispersion need not be accounted for explicitly. This is applied to a simple reference case of a ground-level point source in a neutral boundary layer. A scaling law is also developed for the area in exceedance of a regulatory limit value.

  9. Comparison of boundary conditions from Global Chemistry Model (GCM) for regional air quality application

    NASA Astrophysics Data System (ADS)

    Lam, Yun Fat; Cheung, Hung Ming; Fu, Joshua; Huang, Kan

    2015-04-01

    Applying Global Chemistry Model (GCM) for regional Boundary Conditions (BC) has become a common practice to account for long-range transport of air pollutants in the regional air quality modeling. The limited domain model such as CMAQ and CAMx requires a global BC to prescribe the real-time chemical flux at the boundary grids, in order to give a realistic estimate of boundary impacts. Several GCMs have become available recently for use in regional air quality studies. In this study, three GCM models (i.e., GEOS-chem, CHASER and IFS-CB05 MACC provided by Seoul National University, Nagoya University and ECWMF, respectively) for the year of 2010 were applied in CMAQ for the East Asia domain under the framework of Model Inter-comparison Study Asia Phase III (MISC-Asia III) and task force on Hemispheric Transport of Air Pollution (HTAP) jointed experiments. Model performance evaluations on vertical profile and spatial distribution of O3 and PM2.5 have been made on those three models to better understand the model uncertainties from the boundary conditions. Individual analyses on various mega-cities (i.e., Hong Kong, Guangzhou, Taipei, Chongqing, Shanghai, Beijing, Tianjin, Seoul and Tokyo) were also performed. Our analysis found that the monthly estimates of O3 for CHASER were a bit higher than GEOS-Chem and IFS-CB05 MACC, particularly in the northern part of China in the winter and spring, while the monthly averages of PM2.5 in GEOS-Chem were the lowest among the three models. The hourly maximum values of PM2.5 from those three models (GEOS-Chem, CHASER and IFS-CB05 MACC are 450, 321, 331 μg/m3, while the maximum O3 are 158, 212, 380 ppbv, respectively. Cross-comparison of CMAQ results from the 45 km resolution were also made to investigate the boundary impacts from the global GCMs. The results presented here provide insight on how global GCM selection influences the regional air quality simulation in East Asia.

  10. Modeling air quality in main cities of Peninsular Malaysia by using a generalized Pareto model.

    PubMed

    Masseran, Nurulkamal; Razali, Ahmad Mahir; Ibrahim, Kamarulzaman; Latif, Mohd Talib

    2016-01-01

    The air pollution index (API) is an important figure used for measuring the quality of air in the environment. The API is determined based on the highest average value of individual indices for all the variables which include sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and suspended particulate matter (PM10) at a particular hour. API values that exceed the limit of 100 units indicate an unhealthy status for the exposed environment. This study investigates the risk of occurrences of API values greater than 100 units for eight urban areas in Peninsular Malaysia for the period of January 2004 to December 2014. An extreme value model, known as the generalized Pareto distribution (GPD), has been fitted to the API values found. Based on the fitted model, return period for describing the occurrences of API exceeding 100 in the different cities has been computed as the indicator of risk. The results obtained indicated that most of the urban areas considered have a very small risk of occurrence of the unhealthy events, except for Kuala Lumpur, Malacca, and Klang. However, among these three cities, it is found that Klang has the highest risk. Based on all the results obtained, the air quality standard in urban areas of Peninsular Malaysia falls within healthy limits to human beings. PMID:26718946

  11. Spatially-varying surface roughness and ground-level air quality in an operational dispersion model.

    PubMed

    Barnes, M J; Brade, T K; MacKenzie, A R; Whyatt, J D; Carruthers, D J; Stocker, J; Cai, X; Hewitt, C N

    2014-02-01

    Urban form controls the overall aerodynamic roughness of a city, and hence plays a significant role in how air flow interacts with the urban landscape. This paper reports improved model performance resulting from the introduction of variable surface roughness in the operational air-quality model ADMS-Urban (v3.1). We then assess to what extent pollutant concentrations can be reduced solely through local reductions in roughness. The model results suggest that reducing surface roughness in a city centre can increase ground-level pollutant concentrations, both locally in the area of reduced roughness and downwind of that area. The unexpected simulation of increased ground-level pollutant concentrations implies that this type of modelling should be used with caution for urban planning and design studies looking at ventilation of pollution. We expect the results from this study to be relevant for all atmospheric dispersion models with urban-surface parameterisations based on roughness. PMID:24212233

  12. An Immersed Boundary Method in WRF for High Resolution Urban Air Quality Modeling

    NASA Astrophysics Data System (ADS)

    Wiersema, D. J.; Lundquist, K. A.; Martien, P. T.; Rivard, T.; Chow, F. K.

    2013-12-01

    Urban air quality modeling at the neighborhood scale has potential to become an important tool for long term exposure studies, regulation, and urban planning. Current generation models for urban flow or air quality are limited by laborious mesh creation, terrain slope restrictions due to coordinate transformations, lack of atmospheric physics, and/or omission of regional meteorological effects. To avoid these limitations we have extended the functionality of an existing model, IBM-WRF, a modified version of the Weather Research and Forecasting model (WRF) which uses an immersed boundary method (IBM) (Lundquist et al. 2010, 2012). The immersed boundary method used in our model allows for the evaluation of flow over complex urban geometries including vertical surfaces, sharp corners, and local topographic variations. Lateral boundaries in IBM-WRF can be prescribed using output from the standard WRF model, allowing for realistic meteorological input. IBM-WRF is being used to investigate transport and trapping of vehicle emissions around a proposed affordable housing development located adjacent to a major freeway which transports 250,000+ vehicles per day. Urban topography is created using high-resolution airborne LIDAR building data combined with ground elevation data. Emission locations and strengths are assigned using data provided by the Bay Area Air Quality Management District. Development is underway to allow for meteorological input to be created using the WRF model configured to use nested domains. This will allow for synoptic scale phenomena to affect the neighborhood scale IBM-WRF domain, which has a horizontal resolution on the order of one meter. Initial results from IBM-WRF are presented here and will ultimately be used to assist planning efforts to reduce local air pollution exposure and minimize related associated adverse health effects. Lundquist, K., F. Chow, and J. Lundquist, 2010: An immersed boundary method for the weather research and forecasting

  13. Urban air quality simulation in a high-rise building area using a CFD model coupled with mesoscale meteorological and chemistry-transport models

    NASA Astrophysics Data System (ADS)

    Kwak, Kyung-Hwan; Baik, Jong-Jin; Ryu, Young-Hee; Lee, Sang-Hyun

    2015-01-01

    An integrated urban air quality modeling system is established by coupling a computational fluid dynamics (CFD) model with mesoscale meteorological and chemistry-transport models. The mesoscale models used are the weather research and forecasting (WRF) model and the community multiscale air quality (CMAQ) model, which provide the initial and time-dependent boundary conditions for the CFD model. For the consistency of chemical processes in the CFD and CMAQ models, the same chemical mechanism used in the CMAQ model is implemented in the CFD model. Urban air quality simulations are performed from 0900 to 1800 LT on 3 June 2010 in a high-rise building area of Seoul, Republic of Korea, where mobile emission sources are concentrated. The NO2 and O3 concentrations in the CFD simulation are evaluated with data measured at a roadside air quality monitoring station, showing better agreements than those in the CMAQ simulation. The NO2 and O3 concentration fields exhibit high spatial variabilities in the high-rise building area. The spatial variabilities near the surfaces are strongly associated with the heterogeneity of mobile emission on roads, whereas the spatial variabilities near the top of high-rise buildings are strongly associated with the heterogeneity of building geometry. The average NO2 and O3 concentrations (46 and 30 ppb, respectively, at z = 30 m) near the surfaces are considerably different from the NO2 and O3 concentrations in the CMAQ simulation (17 and 44 ppb, respectively, at z = 30 m), implying the insufficient urban surface representation in the CMAQ simulation. The heterogeneity of building geometry is found to enhance the vertical pollutant transport, whereas the heterogeneity of mobile emission is found to confine emitted pollutants near the surfaces. When the vertical mixing is efficient, the O3 concentration decreases in substantial vertical ranges with the same amount of NOx emission. The integrated urban air quality modeling system realistically

  14. A REVIEW OF REGIONAL-SCALE AIR QUALITY MODELS FOR LONG DISTANCE DISPERSION MODELING IN THE FOUR CORNERS REGION

    EPA Science Inventory

    This document presents a review (ca. April 1977) of available air quality simulation models that are appropriate to long-range transport (e.g., 100-1000 km) of atmospheric pollutants. This review has been prepared as part of an effort to select, modify and apply long-range atmosp...

  15. FINE SCALE AIR QUALITY MODELING USING DISPERSION AND CMAQ MODELING APPROACHES: AN EXAMPLE APPLICATION IN WILMINGTON, DE

    EPA Science Inventory

    Characterization of spatial variability of air pollutants in an urban setting at fine scales is critical for improved air toxics exposure assessments, for model evaluation studies and also for air quality regulatory applications. For this study, we investigate an approach that su...

  16. Incorporating Detailed Chemical Characterization of Biomass Burning Emissions into Air Quality Models

    NASA Astrophysics Data System (ADS)

    Barsanti, K.; Hatch, L. E.; Yokelson, R. J.; Stockwell, C.; Orlando, J. J.; Emmons, L. K.; Knote, C. J.; Wiedinmyer, C.

    2015-12-01

    Approximately 500 Tg/yr of non-methane organic compounds (NMOCs) are emitted by biomass burning (BB) to the global atmosphere, leading to the photochemical production of ozone (O3) and secondary particulate matter (PM). Until recently, in studies of BB emissions, a significant mass fraction of NMOCs (up to 80%) remained uncharacterized or unidentified. Models used to simulate the air quality impacts of BB thus have relied on very limited chemical characterization of the emitted compounds. During the Fourth Fire Lab at Missoula Experiment (FLAME-IV), an unprecedented fraction of emitted NMOCs were identified and quantified through the application of advanced analytical techniques. Here we use FLAME-IV data to improve BB emissions speciation profiles for individual fuel types. From box model simulations we evaluate the sensitivity of predicted precursor and pollutant concentrations (e.g., formaldehyde, acetaldehyde, and terpene oxidation products) to differences in the emission speciation profiles, for a range of ambient conditions (e.g., high vs. low NOx). Appropriate representation of emitted NMOCs in models is critical for the accurate prediction of downwind air quality. Explicit simulation of hundreds of NMOCs is not feasible; therefore we also investigate the consequences of using existing assumptions and lumping schemes to map individual NMOCs to model surrogates and we consider alternative strategies. The updated BB emissions speciation profiles lead to markedly different surrogate compound distributions than the default speciation profiles, and box model results suggest that these differences are likely to affect predictions of PM and important gas-phase species in chemical transport models. This study highlights the potential for further BB emissions characterization studies, with concerted model development efforts, to improve the accuracy of BB predictions using necessarily simplified mechanisms.

  17. A spatially varying coefficient model for mapping PM10 air quality at the European scale

    NASA Astrophysics Data System (ADS)

    Hamm, N. A. S.; Finley, A. O.; Schaap, M.; Stein, A.

    2015-02-01

    Particulate matter (PM) air quality in Europe has improved substantially over the past decades, but it still poses a significant threat to human health. Accurate regional scale maps of PM10 concentrations are needed for monitoring progress in mitigation strategies and monitoring compliance with statutory limit values. Chemistry transport models (CTM) use emission databases and simulate the transport and deposition of pollutants. They deliver such maps but are known to be inaccurate. A promising approach is to use geostatistics to model the relationship between the in situ observations and the CTM. This has been shown to be more accurate than using either observations or CTM's alone. This paper presents a spatially varying coefficients (SVC) geostatistical model as an extension of the standard spatially varying intercept (SVI) geostatistical model. SVC allowed the regression coefficient to vary spatially according to a covariance function, the parameters of which were estimated from the data. It was built as a Bayesian hierarchical model and implemented using Markov chain Monte Carlo. The procedure was applied to Airbase PM10 observations and LOTOS-EUROS simulated PM10 for central, southern and eastern Europe. Model-fit diagnostics showed that SVC delivered a better fit to the data than SVI. Mapping the spatially varying coefficients allowed identification of the locations where the CTM performed well or poorly. This could be used for objective CTM evaluation purposes. The posterior predictive simulations were also used to map median PM10 concentrations as well as the probability of exceeding the 50 μg m-3 EU daily PM10 concentration threshold. Although posterior median prediction accuracy was similar for SVI and SVC, SVC better modelled the process and yielded narrower credible intervals. As such, SVC was more appropriate for quantifying uncertainty and for mapping threshold exceedances. The resulting maps may be used to guide air quality assessment and mitigation

  18. Southern california offshore air quality model validation study. Volume I: executive summary. Final report

    SciTech Connect

    Zannetti, P.; Wilbur, D.M.; Baxter, R.A.

    1981-11-01

    This volume summarizes the significant results of a BLM-funded study conducted jointly by AeroVironment Inc. and the Naval Postgraduate School to validate and/or modify screening models commonly used to predict onshore air quality impacts from outer continental shelf (OCS) emission sources. The study involved both field experiments and computer modeling analysis to give a better understanding of dispersion over water and at the land/sea interface. Two field experiments were performed releasing SF6 tracer gas from a research vessel offshore the Ventura-Oxnard, California coastal area in September, 1980 and January, 1981. Modifications are discussed for standard Gaussian models to predict peak plume concentration values, the horizontal and vertical shape of the plume, and peak ground-level impacts from OCS emission sources.

  19. Southern california offshore air quality model validation study. Volume II: synthesis of findings. Final report

    SciTech Connect

    Zannetti, P.; Wilbur, D.M.; Baxter, R.A.

    1981-11-01

    This volume describes the significant results of a BLM-funded study conducted jointly by AeroVironment Inc. and the Naval Postgraduate School to validate and/or modify screening models commonly used to predict onshore air quality impacts from outer continental shelf (OCS) emission sources. The study involved both field experiments and computer modeling analysis to give a better understanding of dispersion over water and at the land/sea interface. Two field experiments were performed releasing SF tracer gas from a research vessel offshore the Ventura-Oxnard, California coastal area in September, 1980 and January, 1981. Modifications are discussed for standard Gaussian models to predict peak plume concentration values, the horizontal and vertical shape of the plume, and peak ground-level impacts from OCS emission sources.

  20. Exploration of OMI Products for Air Quality Applications Through Comparisons with Models and Observations

    NASA Technical Reports Server (NTRS)

    Pickering, K. E.; Ziemke, J.; Bucsela, E.; Gleason, J.; Marufu, L.; Dickerson, R.; Mathur, R.; Davidson, P.; Duncan, B.; Bhartia, P. K.

    2006-01-01

    The Ozone Monitoring Instrument (OMI) on board NASA s Aura satellite was launched in July 2004, and is now providing daily global observations of total column ozone, NO2, and SO2, as well as aerosol information. Algorithms have also been developed to produce daily tropospheric ozone and NO2 products. The tropospheric ozone product reported here is a tropospheric residual computed through use of Aura Microwave Limb Sounder (MLS) ozone profile data to quantify stratospheric ozone. We are investigating the applicability of OMI products for use in air quality modeling, forecasting, and analysis. These investigations include comparison of the OMI tropospheric O3 and NO2 products with global and regional models and with lower tropospheric aircraft observations. Large-scale transport of pollution seen in the OM1 tropospheric O3 data is compared with output from NASA's Global Modeling Initiative global chemistry and transport model. On the regional scale we compare the OMI tropospheric O3 and NO2 with fields from the National Oceanic and Atmospheric Administration and Environmental Protection Agency (NOAA/EPA) operational Eta/CMAQ air quality forecasting model over the eastern United States. This 12-km horizontal resolution model output is roughly of equivalent resolution to the OMI pixel data. Correlation analysis between lower tropospheric aircraft O3 profile data taken by the University of Maryland over the Mid-Atlantic States and OMI tropospheric column mean volume mixing ratio for O3 will be presented. These aircraft data are representative of the lowest 3 kilometers of the atmosphere, the region in which much of the locally-generated and regionally-transported ozone exists.

  1. The web system for operative description of air quality in the city

    NASA Astrophysics Data System (ADS)

    Barth, A. A.; Starchenko, A. V.; Fazliev, A. Z.

    2009-04-01

    Development and implementation of information-computational system (ICS) is described. The system is oriented on the collective usage of the calculation's facilities in order to determine the air quality on the basis of photochemical model. The ICS has been implemented on the basis of the middleware of ATMOS web-portal [1, 2]. The data and calculation layer of this ICS includes: Mathematical model of pollution transport based on transport differential equations. The model describes propagation, scattering and chemical transformation of the pollutants in the atmosphere [3]. The model may use averaged data value for city or forecast results obtained with help of the Chaser model.[4] Atmospheric boundary layer model (ABLM) [3] is used for operative numerical prediction of the meteorological parameters. These are such parameters as speed and direction of the wind, humidity and temperature of the air, which are necessary for the transport impurity model to operate. The model may use data assimilation of meteorological measurements data (including land based observations and the results of remote sensing of vertical structure of the atmosphere) or the weather forecast results obtained with help of the Semi-Lagrange model [5]. Applications for manipulation of data: An application for downloading parameters of atmospheric surface layer and remote sensing of vertical structure of the atmosphere from the web sites (http://meteo.infospace.ru and http://weather.uwyo.edu); An application for uploading these data into the ICS database; An application for transformation of the uploaded data into the internal data format of the system. At present this ICS is a part of "Climate" web site located in ATMOS portal [5]. The database is based on the data schemes providing the calculation in ICS workflow. The applications manipulated with the data are working in automatic regime. The workflow oriented on computation of physical parameters contains: The application for the calculation of

  2. Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

    NASA Technical Reports Server (NTRS)

    Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Johnson, Hoyt; Khan, Maudood

    2006-01-01

    The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared

  3. Remote Sensing and Spatial Growth Modeling Coupled With Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

    NASA Astrophysics Data System (ADS)

    Quattrochi, D. A.; Estes, M. G.; Crosson, W. L.; Johnson, H.; Khan, M.

    2006-05-01

    The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world's population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as

  4. Source apportionment of visibility impairment using a three-dimensional source-oriented air quality model.

    PubMed

    Ying, Qi; Mysliwiec, Mitchell; Kleeman, Michael J

    2004-02-15

    A three-dimensional source-oriented Eulerian air quality model is developed that can predict source contributions to the visibility reduction. Particulate matter and precursor gases from 14 different sources (crustal material, paved road dust, diesel engines, meat cooking, noncatalyst-equipped gasoline engines, catalyst-equipped gasoline engines, high-sulfur fuel, sea salt, refrigerant losses, residential production, animals, soil and fertilizer application, other anthropogenic sources, and background sources) are tracked though a mathematical simulation of emission, chemical reaction, gas-to-particle conversion, transport, and deposition. A visibility model based on Mie theory is modified to use the calculated source contributions to airborne particulate matter size and composition as well as gas-phase pollutant concentrations to quantify total source contributions to visibility impairment. The combined air quality-visibility model is applied to predict source contributions to visibility reduction in southern California for a typical air pollution episode (September 23-25, 1996). The model successfully predicts a severe visibility reduction in the eastern portion of the South Coast Air Basin where the average daytime visibility is measured to be less than 10 km. In the relatively clean coastal portion of the domain, the model successfully predicts that the average daytime visibility is greater than 65 km. Transportation-related sources directly account for approximately 50% of the visibility reduction (diesel engines approximately 15-20%, catalyst-equipped gasoline engines approximately 10-20%, noncatalyst-equipped gasoline engines approximately 3-5%, crustal and paved road dust approximately 5%) in the region with the most severe visibility impairment. Ammonia emissions from animal sources account for approximately 10-15% of the visibility reduction. PMID:14998023

  5. Indoor Air Quality (IAQ) model for windows, risk (version 1.0) (for microcomputers). Model-Simulation

    SciTech Connect

    1995-07-01

    A computer model, called RISK, for calculating individual exposure to indoor air pollutants from sources is presented. The model is designed to calculate exposure due to individual, as opposed to population, activities patterns and source use. The model also provides the capability to calculate risk due to the calculated exposure. RISK is the third in a series of indoor air quality (IAQ) models developed by the Indoor Environment Management Branch of U.S. EPA`s National Risk Management Research Laboratory. The model uses data on source emissions, room-to-room air flows, air exchange with the outdoors, and indoor sinks to predict concentration-time profiles for all rooms. The concentration-time profiles are then combined with individual activity patterns to estimate exposure. Risk is calculated using a risk calculation using a risk calculation framework developed by Naugle and Pierson (1991). The model allows analysis of the effects of air cleaners located in either/or both the central air circulating system or individual rooms on IAQ and exposure. The model allows simulation of a wide range of sources including long term steady state sources, on/off sources, and decaying sources. Several sources are allowed in each room. The model allows the analysis of the effects of sinks and sink re-emissions on IAQ. The results of test house experiments are compared with model predictions. The agreement between predicted concentration-time profiles and the test house data is good.

  6. Sensitivity and Uncertainty Analysis in Chemical Mechanisms for Air Quality Modeling

    NASA Astrophysics Data System (ADS)

    Gao, Dongfen

    1995-01-01

    Ambient ozone in urban and regional air pollution is a serious environmental problem. Air quality models can be used to predict ozone concentrations and explore control strategies. One important component of such air quality models is a chemical mechanism. Sensitivity and uncertainty analysis play an important role in the evaluation of the performance of air quality models. The uncertainties associated with the RADM2 chemical mechanism in predicted concentrations of O_3, HCHO, H _2rm O_2, PAN, and HNO _3 were estimated. Monte Carlo simulations with Latin Hypercube Sampling were used to estimate the overall uncertainties in concentrations of species of interest, due to uncertainties in chemical parameters. The parameters that were treated as random variables were identified through first-order sensitivity and uncertainty analyses. Recent estimates of uncertainties in rate parameters and product yields were used. The results showed the relative uncertainties in ozone predictions are +/-23-50% (1sigma relative to the mean) in urban cases, and less than +/-20% in rural cases. Uncertainties in HNO_3 concentrations are the smallest, followed by HCHO, O_3 and PAN. Predicted H_2rm O_2 concentrations have the highest uncertainties. Uncertainties in the differences of peak ozone concentrations between base and control cases were also studied. The results show that the uncertainties in the fractional reductions in ozone concentrations were 9-12% with NO_{rm x} control at an ROG/NO_{rm x} ratio of 24:1 and 11-33% with ROG control at an ROG/NO _{rm x} ratio of 6:1. Linear regression analysis of the Monte Carlo results showed that uncertainties in rate parameters for the formation of HNO_3, for the reaction of HCHO + hv to 2HO _2 + CO, for PAN chemistry and for the photolysis of NO_2 are most influential to ozone concentrations and differences of ozone. The parameters that are important to ozone concentrations also tend to be relatively influential to other key species

  7. Dual fan, dual-duct system meets air quality, energy-efficiency needs

    SciTech Connect

    Schuler, M.

    1996-03-01

    Canada`s Space Centre in Saint-Hubert Quebec is a 300,000 ft{sup 2} (27,871 m{sup 2}) complex that houses the headquarters of the Canadian Space Agency, the Canadian Astronaut Training Centre, mission ground control installations, research facilities, offices and the required support facilities. A comfortable, pleasant research environment was a primary concern for the Space Centre, given its elite clientele. The objectives were high indoor-air quality, design flexibility, energy efficiency and low capital costs. Dual duct systems which are the heart of the mechanical concept allowed the designers to meet these objectives. The Space Centre`s offices, laboratories and conference center are all served by dual-duct systems. All operate using an air economizer cycle. Gas boilers provide them with hot water for heating and steam for humidification while centrifugal chillers provide chilled water for cooling. This article describes the design.

  8. Integration of Satellite, Modeled, and Ground Based Aerosol Data for use in Air Quality and Public Health Applications

    NASA Astrophysics Data System (ADS)

    Garcia, V.; Kondragunta, S.; Holland, D.; Dimmick, F.; Boothe, V.; Szykman, J.; Chu, A.; Kittaka, C.; Al-Saadi, J.; Engel-Cox, J.; Hoff, R.; Wayland, R.; Rao, S.; Remer, L.

    2006-05-01

    Advancements in remote sensing over the past decade have been recognized by governments around the world and led to the development of the international Global Earth Observation System of Systems 10-Year Implementation Plan. The plan for the U.S. contribution to GEOSS has been put forth in The Strategic Plan for the U.S. Integrated Earth Observation System (IEOS) developed under IWGEO-CENR. The approach for the development of the U.S. IEOS is to focus on specific societal benefits that can be achieved by integrating the nation's Earth observation capabilities. One such challenge is our ability to understand the impact of poor air quality on human health and well being. Historically, the air monitoring networks put in place for the Nations air quality programs provided the only aerosol air quality data on an ongoing and systematic basis at national levels. However, scientific advances in the remote sensing of aerosols from space have improved dramatically. The MODIS sensor and GOES Imager aboard NASA and NOAA satellites, respectively, provide synoptic-scale measurements of aerosol optical depth (AOD) which have been demonstrated to correlate with high levels of PM10 and PM2.5 at the surface. The MODIS sensor has been shown to be capable of a 1 km x 1 km (at nadir) AOD product, while the GOES Imager can provide AOD at 4 km x 4 km every 30 minutes. Within the next several years NOAA and EPA will begin to issue PM2.5 air quality forecasts over the entire domain of the eastern United States, eventually extending to national coverage. These forecasts will provide continuous estimated values of PM2.5 on a daily basis. A multi-agency collaborative project among government and academia is underway to improve the spatial prediction of fine particulate matter through the integration of multi-sensor and multi-platform aerosol observations (MODIS and GOES), numerical model output, and air monitoring data. By giving more weight to monitoring data in monitored areas and relying

  9. Evaluation of observation-fused regional air quality model results for population air pollution exposure estimation.

    PubMed

    Chen, Gang; Li, Jingyi; Ying, Qi; Sherman, Seth; Perkins, Neil; Rajeshwari, Sundaram; Mendola, Pauline

    2014-07-01

    In this study, Community Multiscale Air Quality (CMAQ) model was applied to predict ambient gaseous and particulate concentrations during 2001 to 2010 in 15 hospital referral regions (HRRs) using a 36-km horizontal resolution domain. An inverse distance weighting based method was applied to produce exposure estimates based on observation-fused regional pollutant concentration fields using the differences between observations and predictions at grid cells where air quality monitors were located. Although the raw CMAQ model is capable of producing satisfying results for O3 and PM2.5 based on EPA guidelines, using the observation data fusing technique to correct CMAQ predictions leads to significant improvement of model performance for all gaseous and particulate pollutants. Regional average concentrations were calculated using five different methods: 1) inverse distance weighting of observation data alone, 2) raw CMAQ results, 3) observation-fused CMAQ results, 4) population-averaged raw CMAQ results and 5) population-averaged fused CMAQ results. It shows that while O3 (as well as NOx) monitoring networks in the HRRs are dense enough to provide consistent regional average exposure estimation based on monitoring data alone, PM2.5 observation sites (as well as monitors for CO, SO2, PM10 and PM2.5 components) are usually sparse and the difference between the average concentrations estimated by the inverse distance interpolated observations, raw CMAQ and fused CMAQ results can be significantly different. Population-weighted average should be used to account for spatial variation in pollutant concentration and population density. Using raw CMAQ results or observations alone might lead to significant biases in health outcome analyses. PMID:24747248

  10. Evaluation of Observation-Fused Regional Air Quality Model Results for Population Air Pollution Exposure Estimation

    PubMed Central

    Chen, Gang; Li, Jingyi; Ying, Qi; Sherman, Seth; Perkins, Neil; Rajeshwari, Sundaram; Mendola, Pauline

    2014-01-01

    In this study, Community Multiscale Air Quality (CMAQ) model was applied to predict ambient gaseous and particulate concentrations during 2001 to 2010 in 15 hospital referral regions (HRRs) using a 36-km horizontal resolution domain. An inverse distance weighting based method was applied to produce exposure estimates based on observation-fused regional pollutant concentration fields using the differences between observations and predictions at grid cells where air quality monitors were located. Although the raw CMAQ model is capable of producing satisfying results for O3 and PM2.5 based on EPA guidelines, using the observation data fusing technique to correct CMAQ predictions leads to significant improvement of model performance for all gaseous and particulate pollutants. Regional average concentrations were calculated using five different methods: 1) inverse distance weighting of observation data alone, 2) raw CMAQ results, 3) observation-fused CMAQ results, 4) population-averaged raw CMAQ results and 5) population-averaged fused CMAQ results. It shows that while O3 (as well as NOx) monitoring networks in the HRR regions are dense enough to provide consistent regional average exposure estimation based on monitoring data alone, PM2.5 observation sites (as well as monitors for CO, SO2, PM10 and PM2.5 components) are usually sparse and the difference between the average concentrations estimated by the inverse distance interpolated observations, raw CMAQ and fused CMAQ results can be significantly different. Population-weighted average should be used to account spatial variation in pollutant concentration and population density. Using raw CMAQ results or observations alone might lead to significant biases in health outcome analyses. PMID:24747248

  11. Urban Heat Island Versus Air Quality - a Numerical Modelling Study for a European City

    NASA Astrophysics Data System (ADS)

    Fallmann, J.; Forkel, R.; Emeis, S.

    2014-12-01

    In 2050 70% of the global population is expected to live in urban areas. Climate change will render these areas more vulnerable to heat waves, which often are accompanied by severe air pollution problems. The Urban Heat Island (UHI) is a feature that adds to the general temperature increase that is expected. Decreasing the UHI can impact air quality as well, because heat influences atmospheric dynamics and accelerates air chemical processes and often also increases the emission of primary pollutants due to increased demand of energy. The goal of this study is to investigate the effect of, e.g., high reflective surfaces and urban greening on mitigating the UHI and the related impact on air quality. A multi-layer urban canopy model is coupled to the mesoscale model WRF-Chem and the urban area of Stuttgart (South-West Germany) is taken as one example. Different scenario runs are executed for short time periods and are compared to a control run. The results show that the UHI effect can be substantially reduced when changing the albedo of roof surfaces, whereas the effect of urban greening is minor. Both scenarios have in common, that they evoke changes in secondary circulation patterns. The effects of these mitigation strategies on chemical composition of the urban atmosphere are complex, attributed to both chemical and dynamical features. Increasing the reflectivity of roof surfaces in the model results in a net decrease of the surface ozone concentration, because ozone formation is highly correlated to temperature. With regard to primary pollutants, e.g. NO, CO and PM10 concentrations are increased when increasing reflectivity. This effect primarily can be ascribed to a reduction of turbulent motion, convection and a decrease of the boundary layer height, coming along with lower temperatures in the urban canopy layer due to increased reflectivity. The table below shows the effect on grid cell mean concentrations for different chemical species and scenarios.

  12. Particulate and gaseous organic receptor modeling for the southern California Air Quality Study. Final report

    SciTech Connect

    Watson, J.G.; Chow, J.G.; Lu, Z.; Gertler, A.W.

    1993-11-01

    The Chemical Mass Balance (CMB) receptor model was applied to the chemically-speciated diurnal particulate matter samples and volatile organic compound (VOC) acquired during the summer and fall campaigns of the Southern California Air Quality Study (SCAQS). Source profiles applicable to the Los Angeles area were used to apportion PM[sub (2.5)] and PM[sub (10)] to primary paved road dust, primary construction dust, primary motor vehicle exhaust, primary marine aerosol, secondary ammonium nitrate, and secondary ammonium sulfate. Nonmethane hydrocarbon was apportioned to motor vehicle exhaust, liquid fuel, gasoline vapor, gas leaks, architectural and industrial coatings, and biogenic emissions. Suspended dust was the major contributor to PM(10) during the summer, while secondary ammonium nitrate and primary motor vehicle exhaust contributions were high in the fall. Motor vehicle exhaust was the major contributor to nonmethane hydrocarbons, ranging from 30% to 70% of the total.

  13. Model assessing the impact of biomass burning on air quality and photochemistry in Mexico City

    NASA Astrophysics Data System (ADS)

    Lei, W.; Li, G.; Wiedinmyer, C.; Yokelson, R. J.; Molina, L. T.

    2010-12-01

    Biomass burning is a major global emission source for trace gases and particulates. Various multi-platform measurements during the Mexico City Metropolitan Area (MCMA)-2003 and Megacity Initiative: Local and Global Research Observations (MILAGRO)-2006 campaigns suggest significant influences of biomass burning (BB) on air quality in Mexico City during the dry season, and the observations show emissions from BB impose viable yet highly variable impacts on organic aerosols (OA) in and around Mexico City. We have developed emission inventories for forest fires surrounding Mexico City based on measurement-estimated emission factors and MODIS fire counts, and for garbage fires in Mexico City based on in situ-measured emission factors and the population distribution and socioeconomic data. In this study, we will comprehensively assess the impact of biomass burning on the aerosol loading, chemical composition, OA formation and photochemistry in Mexico City using WRF-Chem. Analysis of the model results, in conjunction with concurrent field measurements, will be presented.

  14. Environmental assessment of three egg production systems--Part I: Monitoring system and indoor air quality.

    PubMed

    Zhao, Y; Shepherd, T A; Li, H; Xin, H

    2015-03-01

    To comprehensively assess conventional vs. some alternative laying-hen housing systems under U.S. production conditions, a multi-institute and multi-disciplinary project, known as the Coalition for Sustainable Egg Supply (CSES) study, was carried out at a commercial egg production farm in the Midwestern United States over two single-cycle production flocks. The housing systems studied include a conventional cage house (200,000 hen capacity), an aviary house (50,000 hen capacity), and an enriched colony house (50,000 hen capacity). As an integral part of the CSES project, continual environmental monitoring over a 27-month period described in this paper quantifies indoor gaseous and particulate matter concentrations, thermal environment, and building ventilation rate of each house. Results showed that similar indoor thermal environments in all three houses were maintained through ventilation management and environmental control. Gaseous and particulate matter concentrations of the enriched colony house were comparable with those of the conventional cage house. In comparison, the aviary house had poorer indoor air quality, especially in wintertime, resulting from the presence of floor litter (higher ammonia levels) and hens' activities (higher particulate matter levels) in it. Specifically, daily mean indoor ammonia concentrations had the 95% confidence interval values of 3.8 to 4.2 (overall mean of 4.0) ppm for the conventional cage house; 6.2 to 7.2 (overall mean of 6.7) ppm for the aviary house; and 2.7 to 3.0 (overall mean of 2.8) ppm for the enriched colony house. The 95% confidence interval (overall mean) values of daily mean indoor carbon dioxide concentrations were 1997 to 2170 (2083) ppm for the conventional cage house, 2367 to 2582 (2475) ppm for the aviary house, and 2124 to 2309 (2216) ppm for the enriched colony house. Daily mean indoor methane concentrations were similar for all three houses, with 95% confidence interval values of 11.1 to 11.9 (overall

  15. Modeling the Transport and Chemical Evolution of Onshore and Offshore Emissions and their Impact on Local and Regional Air Quality Using a Variable-Grid-Resolution Air Quality Model

    SciTech Connect

    Kiran Alapaty; Adel Hanna

    2006-10-16

    This research project has two primary objectives: (1) to further develop and refine the Multiscale Air Quality Simulation Platform-Variable Grid Resolution (MAQSIP-VGR) model, an advanced variable-grid-resolution air quality model, to provide detailed, accurate representation of the dynamical and chemical processes governing the fate of anthropogenic emissions in coastal environments; and (2) to improve current understanding of the potential impact of onshore and offshore oil and gas exploration and production (E&P) emissions on O{sub 3} and particulate matter nonattainment in the Gulf of Mexico and surrounding states.

  16. Multi-model estimates of fire emissions and air quality degradation in Southeast Asia

    NASA Astrophysics Data System (ADS)

    Marlier, M. E.; DeFries, R. S.; Kasibhatla, P. S.; Voulgarakis, A.; Kinney, P. L.; Shindell, D. T.; Randerson, J. T.

    2011-12-01

    Like fossil fuel pollution, fire emissions affect both climate change and air quality. In this study, we combine satellite-derived fire estimates and atmospheric modeling to quantify potential population exposure to particulate matter and ozone from fires in Southeast Asia from 1997 to 2007. This region has large interannual variability in fire activity due to El Niño-induced droughts and anthropogenic drivers. Though typically too wet to combust, increased sources of deforestation and degradation are enhancing the susceptibility of forests and underlying carbon-rich peat deposits to fire during drought, as documented in the extreme fires of the 1997-98 El Niño. Concerns of a positive feedback between fire activity and a warming climate would further increase the influence of fires on air quality degradation. Monthly fire emissions are estimated from the Global Fire Emissions Database (GFED version 3) and transported in two atmospheric models to assess population exposure. We show that during strong El Niño years, fires contribute to daily fine particulate matter and afternoon maximum ozone surface concentrations over 150 μg/m3 and 240 μg/m3, respectively. Exposure to these two types of pollutants increases mortality and hospital admissions from respiratory and cardiovascular diseases, even at low concentrations. This fire pollutant burden corresponds to 200 added days per year exceeding the World Health Organization fine particulate matter guideline and exposes up to 50 million additional people to more than 25 days above the most extreme pollutant concentrations. Our results indicate that substantial health and economic co-benefits would result from reducing fires in locations where transported emissions lead to enhanced exposure to air pollution during high fire years.

  17. Updating Sea Spray Aerosol Emissions in the Community Multiscale Air Quality Model

    NASA Astrophysics Data System (ADS)

    Gantt, B.; Bash, J. O.; Kelly, J.

    2014-12-01

    Sea spray aerosols (SSA) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. In this study, the Community Multiscale Air Quality (CMAQ) model is updated to enhance fine mode SSA emissions, include sea surface temperature (SST) dependency, and revise surf zone emissions. Based on evaluation with several regional and national observational datasets in the continental U.S., the updated emissions generally improve surface concentrations predictions of primary aerosols composed of sea-salt and secondary aerosols affected by sea-salt chemistry in coastal and near-coastal sites. Specifically, the updated emissions lead to better predictions of the magnitude and coastal-to-inland gradient of sodium, chloride, and nitrate concentrations at Bay Regional Atmospheric Chemistry Experiment (BRACE) sites near Tampa, FL. Including SST-dependency to the SSA emission parameterization leads to increased sodium concentrations in the southeast U.S. and decreased concentrations along the Pacific coast and northeastern U.S., bringing predictions into closer agreement with observations at most Interagency Monitoring of Protected Visual Environments (IMPROVE) and Chemical Speciation Network (CSN) sites. Model comparison with California Research at the Nexus of Air Quality and Climate Change (CalNex) observations will also be discussed, with particular focus on the South Coast Air Basin where clean marine air mixes with anthropogenic pollution in a complex environment. These SSA emission updates enable more realistic simulation of chemical processes in coastal environments, both in clean marine air masses and mixtures of clean marine and polluted conditions.

  18. Manipulating ship fuel sulfur content and modeling the effects on air quality and climate

    NASA Astrophysics Data System (ADS)

    Partanen, Antti-Ilari; Laakso, Anton; Schmidt, Anja; Kokkola, Harri; Kuokkanen, Tuomas; Kerminen, Veli-Matti; Lehtinen, Kari E. J.; Laakso, Lauri; Korhonen, Hannele

    2013-04-01

    Aerosol emissions from international shipping are known to cause detrimental health effects on people mainly via increased lung cancer and cardiopulmonary diseases. On the other hand, the aerosol particles from the ship emissions modify the properties of clouds and are believed to have a significant cooling effect on the global climate. In recent years, aerosol emissions from shipping have been more strictly regulated in order to improve air quality and thus decrease the mortality due to ship emissions. Decreasing the aerosol emissions from shipping is projected to decrease their cooling effect, which would intensify the global warming even further. In this study, we use a global aerosol-climate model ECHAM5.5-HAM2 to test if continental air quality can be improved while still retaining the cooling effect from shipping. The model explicitly resolves emissions of aerosols and their pre-cursor gases. The model also calculates the interaction between aerosol particles and clouds, and can thus predict the changes in cloud properties due to aerosol emissions. We design and simulate a scenario where ship fuel sulfur content is strictly limited to 0.1% near all coastal regions, but doubled in the open oceans from the current global mean value of 2.7% (geo-ships). This scenario is compared to three other simulations: 1) No shipping emissions at all (no-ships), 2) present-day shipping emissions (std-ships) and 3) a future scenario where sulfur content is limited to 0.1% in the coastal zones and to 0.5% in the open ocean (future-ships). Global mean radiative flux perturbation (RFP) in std-ships compared to no-ships is calculated to be -0.4 W m-2, which is in the range of previous estimates for present-day shipping emissions. In the geo-ships simulation the corresponding global mean RFP is roughly equal, but RFP is spatially distributed more on the open oceans, as expected. In future-ships the decreased aerosol emissions provide weaker cooling effect of only -0.1 W m-2. In

  19. Indoor air quality impacts of residential HVAC systems. Phase 2.a report: Baseline and preliminary simulations

    SciTech Connect

    Emmerich, S.J.; Persily, A.K.

    1995-01-01

    NIST is performing whole building airflow and contaminant dispersal computer simulations with the program CONTAM93 to assess the ability of modifications of central forced-air heating and cooling systems to control pollutant sources relevant to the residential environment. The report summarizes the results of Phase II.A of this project, which consisted of three major efforts: baseline simulations of contaminant levels without indoor air quality (IAQ) controls, design of the IAQ control retrofits, and preliminary simulations of contaminant levels with the IAQ control retrofits. In Phase II.B of the study, all of the baseline cases will be modified to incorporate the IAQ control retrofits. The retrofit results will then be compared to the baseline results to evaluate the effectiveness of the retrofits.

  20. Douglas Battery Mfg. Co. achieves outstanding air quality, energy savings - with dust collection/recirculating system

    SciTech Connect

    Not Available

    1988-08-01

    Douglas Battery Manufacturing Company of Winston-Salem, NC has engineered a filtration system that not only delivers excellent air quality - it also reduces heating costs in the plant, since the filtered air is recirculated through the work area after it leaves the dust-collection unit. Douglas engineers reviewed several alternatives, including pulse jet baghouses, before selecting a Tenkay aspirated cartridge dust collection from Farr Company, El Segundo, CA. At present, Douglas is operating four Tenkay collectors. The average air to filter surface ratio of a Farr cartridge is 1.5:1. Two of the units handle 21,500 cfm each, the others handle 25,000 cfm each. Testing by U.S. EPA Reference Method 12 confirmed that the unit's emissions are significantly lower than those established by federal New Source Performance Standards.

  1. [A method for resolving spectra shift in the urban air quality monitoring system (DOAS)].

    PubMed

    Liu, Shi-Sheng; Wei, Qing-Nong; Feng, Wei-Wei; Zhan, Kai; Wang, Feng-Ping

    2009-06-01

    In the urban air quality monitoring system, there is spectra shift which is caused by environment factors on the optical part (temperature and optic fiber position), or by the self-change of Xe-lamp. Relative spectra shift will occur if the shift of lamp-spectrum and air-spectrum is inconsistent which has direct influences on the accuracy of the measurement results. So the match of wavelength between lamp-spectrum and air-spectrum should be considered when we retrieve pollutants concentration measurement of trace gas in the atmosphere through DOAS method. Based on the study of the unique structures for Xe-lamp emitting spectrum, a method for the calibration of two signal spectra using Xe-lamp emitting peak and least square fitting is given. The results show that, the impact of spectrum shift can be reduced by this method for retrieving results. PMID:19810506

  2. Modeled Trends in Impacts of Landing and Takeoff Aircraft Emissions on Surface Air-Quality in U.S for 2005, 2010 and 2018

    NASA Astrophysics Data System (ADS)

    Vennam, L. P.

    2014-12-01

    Understanding the present-day impacts of aircraft emissions on surface air quality is essential to plan potential mitigation policies for future growth. Stringent regulation on mobile source-related emissions in the recent past coupled with anticipated rise in the growth in aviation activity can increase the relative impacts of aviation-attributable surface air quality if adequate measures for reducing aviation emissions are not implemented. Though aircraft emissions during in-flight mode (at upper altitudes) contribute a significant (70 - 80%) proportion of the total aviation emissions, landing and takeoff (LTO) related emissions can have immediate impact on surface air quality, as most of the large airports are located in urban areas, specifically those that are designated in nonattainment for O3 and/or PM2.5. In this study, we modeled impacts of aircraft emissions during LTO cycles on surface air quality using the latest version of the CMAQ model for two contemporary years (2005, 2010) and one future year (2018). For this regional scale modeling study, we used highly resolved aircraft emissions from the FAA's Aviation Environmental Design Tool (AEDT), meteorology from NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) downscaled with the WRF model, dynamically varying chemical boundary conditions from the CAM-Chem global model (which also used the same AEDT emissions but at the global scale), and spatio-temporally resolved lightning NOx emissions estimated using National Lightning Detection Network (NLDN) flash density data. We evaluated our model results with air quality observations from surface-based networks and in-situ aircraft observation data for the contemporary years. We will present results from model evaluation using this enhanced modeling system, as well as the trajectories in aviation- related air quality (focusing on O3, NO2 and PM2.5) for the three modeling years considered in this study. These findings will help plan

  3. Assessing Scales of Variability for Constituents Relevant to Future Geostationary Satellite Observations and Models of Air Quality

    NASA Astrophysics Data System (ADS)

    Crawford, J. H.; Ryerson, T. B.; Weinheimer, A. J.; Cohen, R. C.; Diskin, G. S.; Sachse, G. W.; Holloway, J.; Chen, G.

    2009-12-01

    Establishing appropriate specifications for satellite observations of atmospheric composition is a difficult and inexact task since neither models nor field observations can provide both the resolution and spatial coverage required. Despite shortcomings in temporal and spatial coverage, field observations are unique in capturing atmospheric variability on scales down to and below those of satellite observations. Airborne field observations from NOAA and NASA-sponsored field campaigns offer dense observations focused on air quality across North America. Here we use variogram analyses to assess spatial variability in key constituents (NO2, O3, CO, and SO2) for a number of air quality focused field campaigns (ICARTT, TEXAQS2000 and 2006, ARCTAS-CARB). The resulting variograms provide a useful metric for evaluating resolution requirements for future geostationary satellite observations. Variograms also provide an assessment of subgrid variability expected to influence nonlinear ozone photochemistry within air quality models based on a chosen model resolution.

  4. Influence of air quality model resolution on uncertainty associated with health impacts

    NASA Astrophysics Data System (ADS)

    Thompson, T. M.; Selin, N. E.

    2012-10-01

    We use regional air quality modeling to evaluate the impact of model resolution on uncertainty associated with the human health benefits resulting from proposed air quality regulations. Using a regional photochemical model (CAMx), we ran a modeling episode with meteorological inputs simulating conditions as they occurred during August through September 2006 (a period representative of conditions leading to high ozone), and two emissions inventories (a 2006 base case and a 2018 proposed control scenario, both for Houston, Texas) at 36, 12, 4 and 2 km resolution. The base case model performance was evaluated for each resolution against daily maximum 8-h averaged ozone measured at monitoring stations. Results from each resolution were more similar to each other than they were to measured values. Population-weighted ozone concentrations were calculated for each resolution and applied to concentration response functions (with 95% confidence intervals) to estimate the health impacts of modeled ozone reduction from the base case to the control scenario. We found that estimated avoided mortalities were not significantly different between the 2, 4 and 12 km resolution runs, but the 36 km resolution may over-predict some potential health impacts. Given the cost/benefit analysis requirements motivated by Executive Order 12866 as it applies to the Clean Air Act, the uncertainty associated with human health impacts and therefore the results reported in this study, we conclude that health impacts calculated from population weighted ozone concentrations obtained using regional photochemical models at 36 km resolution fall within the range of values obtained using fine (12 km or finer) resolution modeling. However, in some cases, 36 km resolution may not be fine enough to statistically replicate the results achieved using 2, 4 or 12 km resolution. On average, when modeling at 36 km resolution, an estimated 5 deaths per week during the May through September ozone season are avoided

  5. A COMPARISON OF THE UCD/CIT AIR QUALITY MODEL AND THE CMB SOURCE-RECEPTOR MODEL FOR PRIMARY AIRBORNE PARTICULATE MATTER. (R831082)

    EPA Science Inventory

    Source contributions to primary airborne particulate matter calculated using the source-oriented UCD/CIT air quality model and the receptor-oriented chemical mass balance (CMB) model are compared for two air quality episodes in different parts of California. The first episode ...

  6. VOLATILE ORGANIC COMPOUND EMISSIONS FROM LATEX PAINT-PART 2. TEST HOUSE STUDIES AND INDOOR AIR QUALITY (IAQ) MODELING

    EPA Science Inventory

    Emission models developed using small chamber data were combined with an Indoor Air Quality (IAQ) model to analyze the impact of volatile organic compound (VOC) emissions from latex paint on indoor environments. Test house experiments were conducted to verify the IAQ model's pred...

  7. European air quality modelled by CAMx including the volatility basis set scheme

    NASA Astrophysics Data System (ADS)

    Ciarelli, G.; Aksoyoglu, S.; Crippa, M.; Jimenez, J. L.; Nemitz, E.; Sellegri, K.; Äijälä, M.; Carbone, S.; Mohr, C.; O'Dowd, C.; Poulain, L.; Baltensperger, U.; Prévôt, A. S. H.

    2015-12-01

    Four periods of EMEP (European Monitoring and Evaluation Programme) intensive measurement campaigns (June 2006, January 2007, September-October 2008 and February-March 2009) were modelled using the regional air quality model CAMx with VBS (Volatility Basis Set) approach for the first time in Europe within the framework of the EURODELTA-III model intercomparison exercise. More detailed analysis and sensitivity tests were performed for the period of February-March 2009 and June 2006 to investigate the uncertainties in emissions as well as to improve the modelling of organic aerosols (OA). Model performance for selected gas phase species and PM2.5 was evaluated using the European air quality database Airbase. Sulfur dioxide (SO2) and ozone (O3) were found to be overestimated for all the four periods with O3 having the largest mean bias during June 2006 and January-February 2007 periods (8.93 and 12.30 ppb mean biases, respectively). In contrast, nitrogen dioxide (NO2) and carbon monoxide (CO) were found to be underestimated for all the four periods. CAMx reproduced both total concentrations and monthly variations of PM2.5 very well for all the four periods with average biases ranging from -2.13 to 1.04 μg m-3. Comparisons with AMS (Aerosol Mass Spectrometer) measurements at different sites in Europe during February-March 2009, showed that in general the model over-predicts the inorganic aerosol fraction and under-predicts the organic one, such that the good agreement for PM2.5 is partly due to compensation of errors. The effect of the choice of volatility basis set scheme (VBS) on OA was investigated as well. Two sensitivity tests with volatility distributions based on previous chamber and ambient measurements data were performed. For February-March 2009 the chamber-case reduced the total OA concentrations by about 43 % on average. On the other hand, a test based on ambient measurement data increased OA concentrations by about 47 % for the same period bringing model

  8. Selecting HVAC Systems for Schools To Balance the Needs for Indoor Air Quality, Energy Conservation and Maintenance. Technical Bulletin.

    ERIC Educational Resources Information Center

    Wheeler, Arthur E.; Kunz, Walter S., Jr.

    Although poor air quality in a school can have multiple causes, the heating, ventilating, and air-conditioning (HVAC) system plays a major role. Suggestions that architects, facilities managers, school board members, and administrators can use in selecting HVAC systems are discussed. Focus is on the performance criteria for classroom systems, and…

  9. Impacts of cool cities on air quality: A preliminary modeling assessment for Nashville TN, Dallas TX and Atlanta GA

    SciTech Connect

    Taha, Haider

    1998-06-15

    Previous atmospheric modeling efforts that concentrated on the Los Angeles Basin suggested beneficial and significant air quality impacts from cool cities strategies. This paper discusses an extension of similar modeling efforts to three regions, Atlanta GA, Dallas - Ft. Worth TX, and Nashville TN, that experience smog and air quality problems. According to the older ozone air quality standard (120 ppb), these regions were classified as serious, moderate, and marginal, respectively, but may be out of compliance with respect to the newer, 80-ppb/8-hours standard. Results from this exploratory modeling work suggest a range of possible impacts on meteorological and air quality conditions. For example, peak ozone concentrations during each region's respective episode could be decreased by 1-6 ppb (conservative and optimistic scenarios, respectively) in Nashville, 5-15 ppb in Dallas - Fort Worth, and 5-12 ppb in Atlanta following implementation of cool cities. The reductions are generally smaller than those obtained from simulating the Los Angeles Basin but are still significant. In all regions, the simulations suggest, the net, domain-wide effects of cool cities are reductions in ozone mass and improvements in air quality. In Atlanta, Nashville, and Dallas, urban areas benefiting from reduced smog reach up to 8460, 7350, and 12870 km{sup 2} in area, respectively. Results presented in this paper should be taken as exploratory and preliminary. These will most likely change during a more comprehensive modeling study to be started soon with the support of the US Environmental Protection Agency. The main purpose of the present project was to obtain the initial data (emission inventories) for these regions, simulate meteorological conditions, and perform preliminary sensitivity analysis. In the future, additional regions will be simulated to assess the potential of cool cities in improving urban air quality.

  10. Microscale obstacle resolving air quality model evaluation with the Michelstadt case.

    PubMed

    Rakai, Anikó; Kristóf, Gergely

    2013-01-01

    Modelling pollutant dispersion in cities is challenging for air quality models as the urban obstacles have an important effect on the flow field and thus the dispersion. Computational Fluid Dynamics (CFD) models with an additional scalar dispersion transport equation are a possible way to resolve the flowfield in the urban canopy and model dispersion taking into consideration the effect of the buildings explicitly. These models need detailed evaluation with the method of verification and validation to gain confidence in their reliability and use them as a regulatory purpose tool in complex urban geometries. This paper shows the performance of an open source general purpose CFD code, OpenFOAM for a complex urban geometry, Michelstadt, which has both flow field and dispersion measurement data. Continuous release dispersion results are discussed to show the strengths and weaknesses of the modelling approach, focusing on the value of the turbulent Schmidt number, which was found to give best statistical metric results with a value of 0.7. PMID:24027450

  11. Microscale Obstacle Resolving Air Quality Model Evaluation with the Michelstadt Case

    PubMed Central

    Rakai, Anikó; Kristóf, Gergely

    2013-01-01

    Modelling pollutant dispersion in cities is challenging for air quality models as the urban obstacles have an important effect on the flow field and thus the dispersion. Computational Fluid Dynamics (CFD) models with an additional scalar dispersion transport equation are a possible way to resolve the flowfield in the urban canopy and model dispersion taking into consideration the effect of the buildings explicitly. These models need detailed evaluation with the method of verification and validation to gain confidence in their reliability and use them as a regulatory purpose tool in complex urban geometries. This paper shows the performance of an open source general purpose CFD code, OpenFOAM for a complex urban geometry, Michelstadt, which has both flow field and dispersion measurement data. Continuous release dispersion results are discussed to show the strengths and weaknesses of the modelling approach, focusing on the value of the turbulent Schmidt number, which was found to give best statistical metric results with a value of 0.7. PMID:24027450

  12. Seamless Meteorology-Chemistry Modelling: Status and Relevance for Numerical Weather Prediction, Air Quality and Climate Research

    NASA Astrophysics Data System (ADS)

    Baklanov, Alexander; EuMetChem Team

    2015-04-01

    Online coupled meteorology atmospheric chemistry models have undergone a rapid evolution in recent years. Although mainly developed by the air quality modelling community, these models are also of interest for numerical weather prediction and climate modelling as they can consider not only the effects of meteorology on air quality, but also the potentially important effects of atmospheric composition on weather. Two ways of online coupling can be distinguished: online integrated and online access coupling. Online integrated models simulate meteorology and chemistry over the same grid in one model using one main timestep for integration. Online access models use independent meteorology and chemistry modules that might even have different grids, but exchange meteorology and chemistry data on a regular and frequent basis. This paper is an overall outcome of the European COST Action ES1004: European Framework for Online Integrated Air Quality and Meteorology Modelling (EuMetChem) and conclusions from the recently organized Symposium on Coupled Chemistry-Meteorology/Climate Modelling: Status and Relevance for Numerical Weather Prediction, Air Quality and Climate Research. It offers a review of the current research status of online coupled meteorology and atmospheric chemistry modelling, a survey of processes relevant to the interactions between atmospheric physics, dynamics and composition; and highlights selected scientific issues and emerging challenges that require proper consideration to improve the reliability and usability of these models for the three scientific communities: air quality, numerical meteorology modelling (including weather prediction) and climate modelling. It presents a synthesis of scientific progress and provides recommendations for future research directions and priorities in the development, application and evaluation of online coupled models.

  13. Hybrid Air Quality Modeling Approach for use in the Hear-road Exposures to Urban air pollutant Study(NEXUS)

    EPA Science Inventory

    The paper presents a hybrid air quality modeling approach and its application in NEXUS in order to provide spatial and temporally varying exposure estimates and identification of the mobile source contribution to the total pollutant exposure. Model-based exposure metrics, associa...

  14. DYNAMIC EVALUATION OF REGIONAL AIR QUALITY MODELS: ASSESSING CHANGES TO O 3 STEMMING FROM CHANGES IN EMISSIONS AND METEOROLOGY

    EPA Science Inventory

    Regional-scale air quality models are used to estimate the response of air pollutants to potential emission control strategies as part of the decision-making process. Traditionally, the model predicted pollutant concentrations are evaluated for the “base case” to assess a model’s...

  15. COMPARISON OF EPA (ENVIRONMENTAL PROTECTION AGENCY) TEST HOUSE DATA WITH PREDICTIONS OF AN INDOOR AIR QUALITY MODEL

    EPA Science Inventory

    An easy-to-use indoor air quality (IAQ) model is described. It is multi-compartmented and based on a well-mixed mixing model. Sources and sinks are allowed in each compartment. A menu-driven fill-in-the-form user interface controls program flow and is used to obtain data from the...

  16. STATISTICAL MODELS FOR ESTIMATING THE HEALTH IMPACT OF AIR QUALITY REGULATIONS

    EPA Science Inventory

    Despite increasingly stringent national and local air quality regulations in the last three decades, adverse health effects associated with ambient exposure to air pollution persist. Not surprisingly, regulators, regulated industries, and the public are looking for evidence...

  17. A Database and Tool for Boundary Conditions for Regional Air Quality Modeling: Description and Evaluation

    EPA Science Inventory

    Transported air pollutants receive increasing attention as regulations tighten and global concentrations increase. The need to represent international transport in regional air quality assessments requires improved representation of boundary concentrations. Currently available ob...

  18. URBAN SPRAWL MODELING, AIR QUALITY MONITORING AND RISK COMMUNICATION: THE NORTHEAST OHIO PROJECT

    EPA Science Inventory

    The Northeast Ohio Urban Sprawl, Air Quality Monitoring, and Communications Project (hereafter called the Northeast Ohio Project) provides local environmental and health information useful to residents, local officials, community planners, and others in a 15 county region in the ...

  19. Letter Report Yucca Mountain Environmental Monitoring Systems Initiative - Air Quality Scoping Study for Crater Flat, Nye County, Nevada

    SciTech Connect

    J. Engelbrecht; I. Kavouras; D. Campbell; S.Campbell; S. Kohl; D. Shafer

    2009-04-02

    The Desert Research Institute (DRI) is performing a scoping study as part of the U.S. Department of Energy's Yucca Mountain Environmental Monitoring Systems Initiative (EMSI). The main objective is to obtain baseline air quality information for Yucca Mountain and an area surrounding the Nevada Test Site (NTS). Air quality and meteorological monitoring and sampling equipment housed in a mobile trailer (shelter) (cover page figure) is collecting data at eight sites outside the NTS, including Ash Meadows National Wildlife Refuge (NWR), Beatty, Sarcobatus Flats, Rachel, Caliente, Pahranagat NWR, Crater Flat, and Tonopah Airport, and at four sites on the NTS (Engelbrecht et al., 2007a-d). The trailer is stationed at any one site for approximately eight weeks at a time. This letter report provides a summary of air quality and meteorological data, on completion of the site's sampling program.

  20. Letter Report: Yucca Mountain Environmental Monitoring Systems Initiative - Air Quality Scoping Study for Crater Flat, Nye County, Nevada

    SciTech Connect

    J. Engelbrecht; I. Kavouras; D. Campbell; S. Campbell; S. Kohl; D. Shafer

    2008-08-01

    The Desert Research Institute (DRI) is performing a scoping study as part of the U.S. Department of Energy's Yucca Mountain Environmental Monitoring Systems Initiative (EMSI). The main objective is to obtain baseline air quality information for Yucca Mountain and an area surrounding the Nevada Test Site (NTS). Air quality and meteorological monitoring and sampling equipment housed in a mobile trailer (shelter) (cover page figure) is collecting data at eight sites outside the NTS, including Ash Meadows National Wildlife Refuge (NWR), Beatty, Sarcobatus Flats, Rachel, Caliente, Pahranagat NWR, Crater Flat, and Tonopah Airport, and at four sites on the NTS (Engelbrecht et al., 2007a-d). The trailer is stationed at any one site for approximately eight weeks at a time. This letter report provides a summary of air quality and meteorological data, on completion of the site's sampling program.

  1. Letter Report: Yucca Mountain Environmental Monitoring Systems Initiative - Air Quality Scoping Study for Pahranagat National Wildlife Refuge, Lincoln County, Nevada

    SciTech Connect

    J. Englebrecht; I. Kavouras; D. Campbell; S. Campbell; S. Kohl; D. Shafer

    2008-08-01

    The Desert Research Institute (DRI) is performing a scoping study as part of the U.S. Department of Energy's Yucca Mountain Environmental Monitoring Systems Initiative (EMSI). The main objective is to obtain baseline air quality information for Yucca Mountain and an area surrounding the Nevada Test Site (NTS). Air quality and meteorological monitoring and sampling equipment housed in a mobile trailer (shelter) is collecting data at eight sites outside the NTS, including Ash Meadows National Wildlife Refuge (NWR), Pahranagat NWR, Beatty, Rachel, Caliente, Crater Flat, and Tonopah Airport, and at four sites on the NTS (Engelbrecht et al., 2007a-d). The trailer is stationed at any one site for approximately eight weeks at a time. This letter report provides a summary of air quality and meteorological data on completion of the site's sampling program.

  2. Letter Report: Yucca Mountain Environmental Monitoring Systems Initiative - Air Quality Scoping Study for Caliente, Lincoln County, Nevada

    SciTech Connect

    J. Englebrecht; I. Kavouras; D. Campbell; S. Campbell; S. Kohl; D. Shafer

    2008-08-01

    The Desert Research Institute (DRI) is performing a scoping study as part of the U.S. Department of Energy's Yucca Mountain Environmental Monitoring Systems Initiative (EMSI). The main objective is to obtain baseline air quality information for Yucca Mountain and an area surrounding the Nevada Test Site (NTS). Air quality and meteorological monitoring and sampling equipment housed in a mobile trailer (shelter) is collecting data at eight sites outside the NTS, including Ash Meadows National Wildlife Refuge (NWR), Beatty, Sarcobatus Flats, Rachel, Caliente, Pahranagat NWR, Crater Flat, and Tonopah Airport, and at four sites on the NTS (Engelbrecht et al., 2007a-d). The trailer is stationed at any one site for approximately eight weeks at a time. This letter report provides a summary of air quality and meteorological data, on completion of the site's sampling program.

  3. Letter Report Yucca Mountain Environmental Monitoring Systems Initiative - Air Quality Scoping Study for Pahranagat National Wildlife Refuge, Lincoln County, Nevada

    SciTech Connect

    J. Engelbrecht; I. Kavouras; D. Campbell; S. Campbell; S. Kohl; D. Shafer

    2009-04-02

    The Desert Research Institute (DRI) is performing a scoping study as part of the U.S. Department of Energy's Yucca Mountain Environmental Monitoring Systems Initiative (EMSI). The main objective is to obtain baseline air quality information for Yucca Mountain and an area surrounding the Nevada Test Site (NTS). Air quality and meteorological monitoring and sampling equipment housed in a mobile trailer (shelter) is collecting data at eight sites outside the NTS, including Ash Meadows National Wildlife Refuge (NWR), Pahranagat NWR, Beatty, Rachel, Caliente, Crater Flat, and Tonopah Airport, and at four sites on the NTS (Engelbrecht et al., 2007a-d). The trailer is stationed at any one site for approximately eight weeks at a time. This letter report provides a summary of air quality and meteorological data on completion of the site's sampling program.

  4. Letter Report: Yucca Mountain Environmental Monitoring Systems Initiative - Air Quality Scoping Study for Tonopah Airport, Nye County, Nevada

    SciTech Connect

    J. Engelbrecht; I. Kavouras; D Campbell; S. Campbell; S. Kohl, D. Shafer

    2008-08-01

    The Desert Research Institute (DRI) is performing a scoping study as part of the U.S. Department of Energy's Yucca Mountain Environmental Monitoring Systems Initiative (EMSI). The main objective is to obtain baseline air quality information for Yucca Mountain and an area surrounding the Nevada Test Site (NTS). Air quality and meteorological monitoring and sampling equipment housed in a mobile trailer (shelter) is collecting data at eight sites outside the NTS, including Ash Meadows National Wildlife Refuge (NWR), Tonopah Airport, Beatty, Rachel, Caliente, Pahranagat NWR, Crater Flat, and the Tonopah Airport, and at four sites on the NTS (Engelbrecht et al., 2007a-d). The trailer is stationed at any one site for approximately eight weeks at a time. This letter report provides a summary of air quality and meteorological data, on completion of the site's sampling program.

  5. Letter Report Yucca Mountain Environmental Monitoring Systems Initiative - Air Quality Scoping Study for Tonopah Airport, Nye County, Nevada

    SciTech Connect

    J. Engelbrecht; I. Kavouras; D. Campbell; S. Campbell; S. Kohl; D. Shafer

    2009-04-02

    The Desert Research Institute (DRI) is performing a scoping study as part of the U.S. Department of Energy's Yucca Mountain Environmental Monitoring Systems Initiative (EMSI). The main objective is to obtain baseline air quality information for Yucca Mountain and an area surrounding the Nevada Test Site (NTS). Air quality and meteorological monitoring and sampling equipment housed in a mobile trailer (shelter) is collecting data at eight sites outside the NTS, including Ash Meadows National Wildlife Refuge (NWR), Tonopah Airport, Beatty, Rachel, Caliente, Pahranagat NWR, Crater Flat, and the Tonopah Airport, and at four sites on the NTS (Engelbrecht et al., 2007a-d). The trailer is stationed at any one site for approximately eight weeks at a time. This letter report provides a summary of air quality and meteorological data, on completion of the site's sampling program.

  6. Regional photochemical air quality modeling in the Mexico-US border area

    SciTech Connect

    Mendoza, A.; Russell, A.G.; Mejia, G.M.

    1998-12-31

    The Mexico-United States border area has become an increasingly important region due to its commercial, industrial and urban growth. As a result, environmental concerns have risen. Treaties like the North American Free Trade Agreement (NAFTA) have further motivated the development of environmental impact assessment in the area. Of particular concern are air quality, and how the activities on both sides of the border contribute to its degradation. This paper presents results of applying a three-dimensional photochemical airshed model to study air pollution dynamics along the Mexico-United States border. In addition, studies were conducted to assess how size resolution impacts the model performance. The model performed within acceptable statistic limits using 12.5 x 12.5 km{sup 2} grid cells, and the benefits using finer grids were limited. Results were further used to assess the influence of grid-cell size on the modeling of control strategies, where coarser grids lead to significant loss of information.

  7. Modeling the impact of solid noise barriers on near road air quality

    NASA Astrophysics Data System (ADS)

    Venkatram, Akula; Isakov, Vlad; Deshmukh, Parikshit; Baldauf, Richard

    2016-09-01

    Studies based on field measurements, wind tunnel experiments, and controlled tracer gas releases indicate that solid, roadside noise barriers can lead to reductions in downwind near-road air pollutant concentrations. A tracer gas study showed that a solid barrier reduced pollutant concentrations as much as 80% next to the barrier relative to an open area under unstable meteorological conditions, which corresponds to typical daytime conditions when residents living or children going to school near roadways are most likely to be exposed to traffic emissions. The data from this tracer gas study and a wind tunnel simulation were used to develop a model to describe dispersion of traffic emissions near a highway in the presence of a solid noise barrier. The model is used to interpret real-world data collected during a field study conducted in a complex urban environment next to a large highway in Phoenix, Arizona, USA. We show that the analysis of the data with the model yields useful information on the emission factors and the mitigation impact of the barrier on near-road air quality. The estimated emission factors for the four species, ultrafine particles, CO, NO2, and black carbon, are consistent with data cited in the literature. The results suggest that the model accounted for reductions in pollutant concentrations from a 4.5 m high noise barrier, ranging from 40% next to the barrier to 10% at 300 m from the barrier.

  8. Predicting Air Quality Impacts Associated with Oil and Gas Development in the Uinta Basin Using EPA’s Photochemical Air Quality Model

    EPA Science Inventory

    Rural areas with close proximity to oil and natural gas operations in Utah have experienced winter ozone levels that exceed EPA’s National Ambient Air Quality Standards (NAAQS). Through a collaborative effort, EPA Region 8 – Air Program, ORD, and OAQPS used the Commun...

  9. Indoor air quality impacts of residential hvac systems phase II.B report: IAQ control retrofit simulations and analysis

    SciTech Connect

    Emmerich, S.J.; Persily, A.K.

    1995-09-01

    The National Institute of Standards and Technology (NIST) performed a preliminary study of the potential for using central forced-air heating and cooling system modifications to control indoor air quality (IAQ) in residential buildings. The objective of this effort was to provide insight into the use of state-of-the-art IAQ models to evaluate such modifications, the potential of these modifications to mitigate residential IAQ problems, the pollutant sources they are most likely to impact, and their potential limitations. This study was not intended to determine definitively whether the IAQ control options studied are reliable and cost-effective. The report summarizes the results on Phase II.B of this project, which consisted of three main efforts: computer simulations of contaminant levels with IAQ control retrofits, evaluation of the effectiveness of the IAQ control retrofits, and development of recommendations for future research.

  10. Air quality modelling : effects of emission reductions on concentrations of particulate matter

    NASA Astrophysics Data System (ADS)

    Girault, L.; Roustan, Y.; Seigneur, C.

    2012-04-01

    Atmospheric particulate matter (PM) has adverse effects on human health. PM acts primarily on respiratory and cardiovascular (due to their small size they can penetrate deep into the lungs), but they are also known effects on the skin. In France, the "Particulate Plan" - developed as part of the second National Environmental Health Plan - aims to reduce by 30% fine PM (noted PM2.5because these particles have an aerodynamic diameter of 2.5 micrometers or less) by 2015. A recent study by Airparif (the organization in charge of monitoring air quality in the Paris region, the Île-de-France) and LSCE (Laboratory of climate and the environmental science, France) has allowed, through a large measurement campaign conducted between 2009 and 2011, to quantify the proportion of PM produced in Île-de-France and those transported from the surrounding areas. The study by numerical modelling of air pollution presented here complements these results by investigating future emission scenarios. The CEREA develops and uses an air quality model which simulates the concentrations of pollutants from an emission inventory, meteorological data and boundary conditions of the area studied. After an evaluation of simulation results for the year 2005, the model is used to assess the effects of various scenarios of reductions in NOx and NH3 emissions on the concentrations of PM2.5in Île-de-France. The effects of the controls on the local pollution and the long-range pollution are considered separately. For each emitted species, three scenarios of emission reductions are identified: an emission reduction at the local level (Île-de-France), a reduction at the regional scale (France) and a reduction at the continental scale (across Europe). In each case, a 15% reduction is applied. The comparison of the results allows us to assess the respective contributions of local emissions and long-range transport to PM2.5 concentrations. For instance, the reduction of NOx emissions in Europe leads to a

  11. Investigating Indoor Air Quality Using a Community-based Participatory Research Model

    NASA Astrophysics Data System (ADS)

    Collier, A. M.; Ware, G. E.; Iwasaki, P. G.; Main, D.; Billingsley, L. R.; Pandya, R.; Hannigan, M.

    2015-12-01

    Our project seeks to expand scientific knowledge of air pollutant screening methods while also gathering data a community group can use to improve local health outcomes. Working with Taking Neighborhood Health to Heart (TNH2H), a Denver-based neighborhood group with significant experience doing community-based participatory research (CBPR) related to improving individual and community health, we designed a project to help residents test their homes for two contaminants of interest: radon and perchloroethylene. Radon is naturally occurring and commonly found across Colorado. Perchloroethylene contamination has been discovered in other parts of Denver and residents of Northeast Denver would like to learn more about its possible presence in their neighborhood. Additionally while radon is simple to test for, the same cannot be said for perchloroethylene. This project provides an opportunity to pilot a low-cost sampling method for perchloroethylene, apply TNH2H's CBPR model to an environmental health issue, adapt it for the geosciences, and engage the community in education around air quality issues. Data collected during the project will be shared with participating homes and the larger community. Community members will also participate in understanding and interpreting the data, and together community members and scientists will plan possible next steps, which may involve conducting further research, taking community action, or recommending changes in policy and practice. Beyond the local impacts, we are testing an air quality sampling method that could make sampling more accessible to a broader range of communities. We are also learning more about how communities and scientists can best work together and what additional resources can help facilitate and ensure successful implementation of these types of projects. Our partner, the Thriving Earth Exchange, will use what we learn to facilitate scientist-community partnerships like this in other communities around the

  12. AQUIS: A PC-based air quality and permit information system

    SciTech Connect

    Smith, A.E.; Huber, C.C.; Tschanz, J. ); Ryckman, J.S. Jr. )

    1992-01-01

    The Air Quality Utility Information System (AQUIS) was developed to calculate and track emissions, permits, and related information. The system runs on IBM-compatible personal computers using dBASE IV. AQUIS tracks more than 900 data items distributed among various source categories and allows the user to enter specific information on permit control devices, stacks, and related regulatory requirements. The system is currently operating at seven US Air Force Materiel Command facilities, large industrial operations involved in the repair and maintenance of aircraft. Environmental management personnel are responsible for the compliance status of as many as l,000 sources at each facility. The usefulness of the system has been enhanced by providing a flexible reporting capability that permits users who are unfamiliar with database structure to design and prepare reports containing specified information. In addition to the standard six pollutants, AQUIS calculates compound-specific emissions and allows users to enter their own emission estimates. This capability will be useful in developing air toxics inventories and control plans.

  13. AQUIS: A PC-based air quality and permit information system

    SciTech Connect

    Smith, A.E.; Huber, C.C.; Tschanz, J.; Ryckman, J.S. Jr.

    1992-09-01

    The Air Quality Utility Information System (AQUIS) was developed to calculate and track emissions, permits, and related information. The system runs on IBM-compatible personal computers using dBASE IV. AQUIS tracks more than 900 data items distributed among various source categories and allows the user to enter specific information on permit control devices, stacks, and related regulatory requirements. The system is currently operating at seven US Air Force Materiel Command facilities, large industrial operations involved in the repair and maintenance of aircraft. Environmental management personnel are responsible for the compliance status of as many as l,000 sources at each facility. The usefulness of the system has been enhanced by providing a flexible reporting capability that permits users who are unfamiliar with database structure to design and prepare reports containing specified information. In addition to the standard six pollutants, AQUIS calculates compound-specific emissions and allows users to enter their own emission estimates. This capability will be useful in developing air toxics inventories and control plans.

  14. Prediction of Indoor Air Exposure from Outdoor Air Quality Using an Artificial Neural Network Model for Inner City Commercial Buildings.

    PubMed

    Challoner, Avril; Pilla, Francesco; Gill, Laurence

    2015-12-01

    NO₂ and particulate matter are the air pollutants of most concern in Ireland, with possible links to the higher respiratory and cardiovascular mortality and morbidity rates found in the country compared to the rest of Europe. Currently, air quality limits in Europe only cover outdoor environments yet the quality of indoor air is an essential determinant of a person's well-being, especially since the average person spends more than 90% of their time indoors. The modelling conducted in this research aims to provide a framework for epidemiological studies by the use of publically available data from fixed outdoor monitoring stations to predict indoor air quality more accurately. Predictions are made using two modelling techniques, the Personal-exposure Activity Location Model (PALM), to predict outdoor air quality at a particular building, and Artificial Neural Networks, to model the indoor/outdoor relationship of the building. This joint approach has been used to predict indoor air concentrations for three inner city commercial buildings in Dublin, where parallel indoor and outdoor diurnal monitoring had been carried out on site. This modelling methodology has been shown to provide reasonable predictions of average NO₂ indoor air quality compared to the monitored data, but did not perform well in the prediction of indoor PM2.5 concentrations. Hence, this approach could be used to determine NO₂ exposures more rigorously of those who work and/or live in the city centre, which can then be linked to potential health impacts. PMID:26633448

  15. Prediction of Indoor Air Exposure from Outdoor Air Quality Using an Artificial Neural Network Model for Inner City Commercial Buildings

    PubMed Central

    Challoner, Avril; Pilla, Francesco; Gill, Laurence

    2015-01-01

    NO2 and particulate matter are the air pollutants of most concern in Ireland, with possible links to the higher respiratory and cardiovascular mortality and morbidity rates found in the country compared to the rest of Europe. Currently, air quality limits in Europe only cover outdoor environments yet the quality of indoor air is an essential determinant of a person’s well-being, especially since the average person spends more than 90% of their time indoors. The modelling conducted in this research aims to provide a framework for epidemiological studies by the use of publically available data from fixed outdoor monitoring stations to predict indoor air quality more accurately. Predictions are made using two modelling techniques, the Personal-exposure Activity Location Model (PALM), to predict outdoor air quality at a particular building, and Artificial Neural Networks, to model the indoor/outdoor relationship of the building. This joint approach has been used to predict indoor air concentrations for three inner city commercial buildings in Dublin, where parallel indoor and outdoor diurnal monitoring had been carried out on site. This modelling methodology has been shown to provide reasonable predictions of average NO2 indoor air quality compared to the monitored data, but did not perform well in the prediction of indoor PM2.5 concentrations. Hence, this approach could be used to determine NO2 exposures more rigorously of those who work and/or live in the city centre, which can then be linked to potential health impacts. PMID:26633448

  16. Verifiable emission reductions in European urban areas with air-quality models.

    PubMed

    Skouloudis, A N; Rickerby, D G

    2016-07-18

    The first and second AutoOil programmes were conducted since 1992 as a partnership between the European Commission and the automobile and oil industries. These have introduced emission reductions in Europe based on numerical modelling for a target year. They aimed to identify the most cost-effective way to meet desired future air quality over the whole European Union. In their time, these regulatory efforts were considered an important step towards a new approach for establishing European emission limits. With this work, we review the effectiveness of forecasts carried out with numerical modelling and compare these with the actual measurements at the target year, which was the year 2010. Based on these comparisons and new technological innovations these methodologies can incorporate new sectorial assessments for improving the accuracy of the modelling forecasts and for examining the representativeness of emissions reductions, as well as for the simultaneous assessment of population exposure to cocktails of toxic substances under realistic climatological conditions. We also examined at the ten AutoOil domains the geographical generalisation of the forecasts for CO and NO2 at 1065 European urban areas on the basis of their population and the local population density. PMID:27117117

  17. Air quality models and unusually large ozone increases: Identifying model failures, understanding environmental causes, and improving modeled chemistry

    NASA Astrophysics Data System (ADS)

    Couzo, Evan A.

    radical budgets can shift chemical pathways. The mechanism additions increase the concentrations of nitrous acid, especially right after sunrise. The overall effect on O3 is small (up to three ppb), but we demonstrate the successful implementation of a surface sub-model that chemically processes adsorbed compounds. To our knowledge, this is the first time that chemical processing on surfaces has been used in a three-dimensional regulatory air quality model.

  18. Linking Air Quality and Watershed Models for Environmental Assessments: Analysis of the Effects of Model-Specific Precipitation Estimates on Calculated Water Flux

    EPA Science Inventory

    Directly linking air quality and watershed models could provide an effective method for estimating spatially-explicit inputs of atmospheric contaminants to watershed biogeochemical models. However, to adequately link air and watershed models for wet deposition estimates, each mod...

  19. Evaluation of data assimilation techniques for a mesoscale meteorological model and their effects on air quality model results

    NASA Astrophysics Data System (ADS)

    Amicarelli, A.; Gariazzo, C.; Finardi, S.; Pelliccioni, A.; Silibello, C.

    2008-05-01

    Data assimilation techniques are methods to limit the growth of errors in a dynamical model by allowing observations distributed in space and time to force (nudge) model solutions. They have become common for meteorological model applications in recent years, especially to enhance weather forecast and to support air-quality studies. In order to investigate the influence of different data assimilation techniques on the meteorological fields produced by RAMS model, and to evaluate their effects on the ozone and PM10 concentrations predicted by FARM model, several numeric experiments were conducted over the urban area of Rome, Italy, during a summer episode.

  20. FACILITATING ADVANCED URBAN METEOROLOGY AND AIR QUALITY MODELING CAPABILITIES WITH HIGH RESOLUTION URBAN DATABASE AND ACCESS PORTAL TOOLS

    EPA Science Inventory

    Information of urban morphological features at high resolution is needed to properly model and characterize the meteorological and air quality fields in urban areas. We describe a new project called National Urban Database with Access Portal Tool, (NUDAPT) that addresses this nee...

  1. An open-source software package for multivariate modeling and clustering: applications to air quality management.

    PubMed

    Wang, Xiuquan; Huang, Guohe; Zhao, Shan; Guo, Junhong

    2015-09-01

    This paper presents an open-source software package, rSCA, which is developed based upon a stepwise cluster analysis method and serves as a statistical tool for modeling the relationships between multiple dependent and independent variables. The rSCA package is efficient in dealing with both continuous and discrete variables, as well as nonlinear relationships between the variables. It divides the sample sets of dependent variables into different subsets (or subclusters) through a series of cutting and merging operations based upon the theory of multivariate analysis of variance (MANOVA). The modeling results are given by a cluster tree, which includes both intermediate and leaf subclusters as well as the flow paths from the root of the tree to each leaf subcluster specified by a series of cutting and merging actions. The rSCA package is a handy and easy-to-use tool and is freely available at http://cran.r-project.org/package=rSCA . By applying the developed package to air quality management in an urban environment, we demonstrate its effectiveness in dealing with the complicated relationships among multiple variables in real-world problems. PMID:25966889

  2. Challenges in modeling the impact of biomass burning on air quality in megacities

    NASA Astrophysics Data System (ADS)

    Lei, W.; Li, G.; Molina, L. T.

    2013-05-01

    Biomass burning (BB) is the largest source of primary carbonaceous aerosols and the second largest source of trace gases in the global troposphere. The trace gases and particulates emitted by or formed in the biomass burning plumes adversely affect human health and have important impacts on atmospheric chemistry, air quality, and climate change in megacities. Chemical transport models provide an independent tool to assess the BB impacts, and more importantly they can be used to assess the impacts during periods when and with large spatial coverage where measurements are not available. However due to the high variable nature of the BB impacts, the uncertainties in the BB emission estimates arising from the emission factors, biomass assumption estimates, spatial and temporal distributions, the bias in predicted dynamic mixing and transport, and the limited availability of measurements, a modeling evaluation of the BB impacts is a difficult and challenging task. In this study we use Mexico City as a case study to illustrate the challenges in simulating the impacts from open fires, biofuel use and trash burning.

  3. Economic damages of ozone air pollution to crops using combined air quality and GIS modelling

    NASA Astrophysics Data System (ADS)

    Vlachokostas, Ch.; Nastis, S. A.; Achillas, Ch.; Kalogeropoulos, K.; Karmiris, I.; Moussiopoulos, N.; Chourdakis, E.; Banias, G.; Limperi, N.

    2010-09-01

    This study aims at presenting a combined air quality and GIS modelling methodological approach in order to estimate crop damages from photochemical air pollution, depict their spatial resolution and assess the order of magnitude regarding the corresponding economic damages. The analysis is conducted within the Greater Thessaloniki Area, Greece, a Mediterranean territory which is characterised by high levels of photochemical air pollution and considerable agricultural activity. Ozone concentration fields for 2002 and for specific emission reduction scenarios for the year 2010 were estimated with the Ozone Fine Structure model in the area under consideration. Total economic damage to crops turns out to be significant and estimated to be approximately 43 M€ for the reference year. Production of cotton presents the highest economic loss, which is over 16 M€, followed by table tomato (9 M€), rice (4.2 M€), wheat (4 M€) and oilseed rape (2.8 M€) cultivations. Losses are not spread uniformly among farmers and the major losses occur in areas with valuable ozone-sensitive crops. The results are very useful for highlighting the magnitude of the total economic impacts of photochemical air pollution to the area's agricultural sector and can potentially be used for comparison with studies worldwide. Furthermore, spatial analysis of the economic damage could be of importance for governmental authorities and decision makers since it provides an indicative insight, especially if the economic instruments such as financial incentives or state subsidies to farmers are considered.

  4. Indoor Air Quality in Schools.

    ERIC Educational Resources Information Center

    Torres, Vincent M.

    Asserting that the air quality inside schools is often worse than outdoor pollution, leading to various health complaints and loss of productivity, this paper details factors contributing to schools' indoor air quality. These include the design, operation, and maintenance of heating, ventilating, and air conditioning (HVAC) systems; building…

  5. An update to the ambient ratio method for 1-h NO2 air quality standards dispersion modeling

    NASA Astrophysics Data System (ADS)

    Podrez, Mark

    2015-02-01

    Nitrogen oxide (NOX) gases are typically emitted by fuel combustion sources in the form of nitric oxide (NO), which then reacts with ozone and other oxidants in the atmosphere to convert a portion of the NO to nitrogen dioxide (NO2). EPA has promulgated a 1-h average National Ambient Air Quality Standard (NAAQS) for NO2, and major sources of NOX emissions must estimate their NO2 air quality impacts as part of EPA's air quality permitting programs. The AERMOD dispersion model has been developed by EPA for these air quality impact analyses, and AERMOD contains three different NO to NO2 conversion methods for estimating the ambient concentrations of NO2. This paper describes a refinement to one of the methods, the Ambient Ratio Method version 2 (ARM2). ARM2 is an empirical approach that uses a variable conversion factor, based on an analysis of ambient air measurements of NO and NO2, to estimate the portion of the AERMOD predicted air concentration of total NOX species that is in the form of NO2. The performance of ARM2 has been evaluated and found to compare well to actual ambient measurements and to other more complex EPA conversion methods. EPA has included ARM2 as a "beta-testing" option in AERMOD version 14134, and provided guidance on the use of ARM2 for regulatory modeling analyses in a September 2014 memorandum. This paper also discusses this recent EPA guidance.

  6. Evaluation of operational online-coupled regional air quality models over Europe and North America in the context of AQMEII phase 2. Part II: Particulate Matter

    EPA Science Inventory

    The second phase of the Air Quality Model Evaluation International Initiative (AQMEII) brought together seventeen modeling groups from Europe and North America, running eight operational online-coupled air quality models over Europe and North America on common emissions and bound...

  7. Evaluation of operational online-coupled regional air quality models over Europe and North America in the context of AQMEII phase 2. Part 1: Ozone”

    EPA Science Inventory

    The second phase of the Air Quality Model Evaluation International Initiative (AQMEII) brought together sixteen modeling groups from Europe and North America, running eight operational online-coupled air quality models over Europe and North America on common emissions and boundar...

  8. Isoprene Emission Factors for Subtropical Street Trees for Regional Air Quality Modeling.

    PubMed

    Dunn-Johnston, Kristina A; Kreuzwieser, Jürgen; Hirabayashi, Satoshi; Plant, Lyndal; Rennenberg, Heinz; Schmidt, Susanne

    2016-01-01

    Evaluating the environmental benefits and consequences of urban trees supports their sustainable management in cities. Models such as i-Tree Eco enable decision-making by quantifying effects associated with particular tree species. Of specific concern are emissions of biogenic volatile organic compounds, particularly isoprene, that contribute to the formation of photochemical smog and ground level ozone. Few studies have quantified these potential disservices of urban trees, and current models predominantly use emissions data from trees that differ from those in our target region of subtropical Australia. The present study aimed (i) to quantify isoprene emission rates of three tree species that together represent 16% of the inventoried street trees in the target region; (ii) to evaluate outputs of the i-Tree Eco model using species-specific versus currently used, generic isoprene emission rates; and (iii) to evaluate the findings in the context of regional air quality. Isoprene emission rates of (Myrtaceae) and (Proteaceae) were 2.61 and 2.06 µg g dry leaf weight h, respectively, whereas (Sapindaceae) was a nonisoprene emitter. We substituted the generic isoprene emission rates with these three empirical values in i-Tree Eco, resulting in a 182 kg yr (97%) reduction in isoprene emissions, totaling 6284 kg yr when extrapolated to the target region. From these results we conclude that care has to be taken when using generic isoprene emission factors for urban tree models. We recommend that emissions be quantified for commonly planted trees, allowing decision-makers to select tree species with the greatest overall benefit for the urban environment. PMID:26828179

  9. A neural network based ensemble approach for improving the accuracy of meteorological fields used for regional air quality modeling.

    PubMed

    Cheng, Shuiyuan; Li, Li; Chen, Dongsheng; Li, Jianbing

    2012-12-15

    A neural network based ensemble methodology was presented in this study to improve the accuracy of meteorological input fields for regional air quality modeling. Through nonlinear integration of simulation results from two meteorological models (MM5 and WRF), the ensemble approach focused on the optimization of meteorological variable values (temperature, surface air pressure, and wind field) in the vertical layer near ground. To illustrate the proposed approach, a case study in northern China during two selected air pollution events, in 2006, was conducted. The performances of the MM5, the WRF, and the ensemble approach were assessed using different statistical measures. The results indicated that the ensemble approach had a higher simulation accuracy than the MM5 and the WRF model. Performance was improved by more than 12.9% for temperature, 18.7% for surface air pressure field, and 17.7% for wind field. The atmospheric PM(10) concentrations in the study region were also simulated by coupling the air