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Sample records for air-quality modeling system

  1. Air Quality Model System For The Vienna/bratislava Region

    NASA Astrophysics Data System (ADS)

    Krüger, B. C.; Schmittner, W.; Kromp-Kolb, H.

    A model system has been build up, consisting of the mesoscale meteorological fore- cast model MM5 and the chemical air-quality model CAMx. The coarse grid covers central Europe. By nesting, a spatial resolution of 3 km is reached for the core area, which includes the cities of Vienna (Austria) and Bratislava (Slovakia). In a first approach, the model system has been applied to a 6-day period in Febru- ary 1997, which was characterized by stagnant meteorological conditions. During this episode, primary pollutants like CO and NO2 have been compared with ambient mea- surements for the validation of the new model system. In the future it is foreseen to improve the spatial resolution, to apply the model system also for ozone and particulates, and to utilize it for a short-time forecast of air-quality parameters.

  2. Culture systems: air quality.

    PubMed

    Thomas, Theodore

    2012-01-01

    Poor laboratory air quality is a known hazard to the culture of human gametes and embryos. Embryologists and chemists have employed analytical methods for identifying and measuring bulk and select air pollutants to assess the risk they pose to the embryo culture system. However, contaminant concentrations that result in gamete or embryotoxicity are poorly defined. Combating the ill effects of poor air quality requires an understanding of how toxicants can infiltrate the laboratory, the incubator, and ultimately the culture media. A further understanding of site-specific air quality can then lead to the consideration of laboratory design and management strategies that can minimize the deleterious effects that air contamination may have on early embryonic development in vitro.

  3. 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...

  4. 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

  5. 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...

  6. Incremental Testing of the Community Multiscale Air Quality (CMAQ) Modeling System Version 4.7

    EPA Science Inventory

    This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 (v4.7) and points the reader to additional resources for further details. The model updates were evaluated relative to obse...

  7. 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

  8. 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.

  9. 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.

  10. Uncertainty in Air Quality Modeling.

    NASA Astrophysics Data System (ADS)

    Fox, Douglas G.

    1984-01-01

    Under the direction of the AMS Steering Committee for the EPA Cooperative Agreement on Air Quality Modeling, a small group of scientists convened to consider the question of uncertainty in air quality modeling. Because the group was particularly concerned with the regulatory use of models, its discussion focused on modeling tall stack, point source emissions.The group agreed that air quality model results should be viewed as containing both reducible error and inherent uncertainty. Reducible error results from improper or inadequate meteorological and air quality data inputs, and from inadequacies in the models. Inherent uncertainty results from the basic stochastic nature of the turbulent atmospheric motions that are responsible for transport and diffusion of released materials. Modelers should acknowledge that all their predictions to date contain some associated uncertainty and strive also to quantify uncertainty.How can the uncertainty be quantified? There was no consensus from the group as to precisely how uncertainty should be calculated. One subgroup, which addressed statistical procedures, suggested that uncertainty information could be obtained from comparisons of observations and predictions. Following recommendations from a previous AMS workshop on performance evaluation (Fox. 1981), the subgroup suggested construction of probability distribution functions from the differences between observations and predictions. Further, they recommended that relatively new computer-intensive statistical procedures be considered to improve the quality of uncertainty estimates for the extreme value statistics of interest in regulatory applications.A second subgroup, which addressed the basic nature of uncertainty in a stochastic system, also recommended that uncertainty be quantified by consideration of the differences between observations and predictions. They suggested that the average of the difference squared was appropriate to isolate the inherent uncertainty that

  11. Towards a forecasting system of air quality for Asia using the WRF-Chem model

    NASA Astrophysics Data System (ADS)

    Katinka Petersen, Anna; Kumar, Rajesh; Brasseur, Guy; Granier, Claire

    2013-04-01

    The degradation of air quality in Asia resulting from the intensification of human activities, and the related impacts on the health of billions of people have become an urgent matter of concern. The World Health Organization states that each year nearly 3.3 million people die worldwide prematurely because of air pollution. The situation is particularly acute in Asia. Improving air quality over the Asian continent has become a major challenge for national, regional and local authorities. A prerequisite for air quality improvement is the development of a reliable monitoring system with surface instrumentation and space platforms as well as an analysis and prediction system based on an advanced chemical-meteorological model. The aim is to use the WRF-Chem model for the prediction of daily air quality for the Asian continent with spatial resolution that will be increased in densely populated areas by grid nesting. The modeling system covers a nearly the entire Asian continent so that transport processes of chemical compounds within the continent are simulated and analyzed. To additionally account for the long-range effects and assess their relative importance against regional emissions, the regional chemical transport modeling system uses information from a global modeling system as boundary conditions. The first steps towards a forecasting system over Asia are to test the model performance over this large model domain and the different emissions inventories available for Asia. In this study, the WRF-Chem model was run for a domain covering 60°E to 150°E, 5°S to 50°N at a resolution of 60 km x 60 km for January 2006 with three alternative emission inventories available for Asia (MACCITY, INTEX-B and REAS). We present an intercomparison of the three different simulations and evaluate the simulations with satellite and in situ observations, with focus on ozone, particulate matter, nitrogen oxides and carbon monoxide. The differences between the simulations using

  12. Development of the GEM-MACH-FireWork System: An Air Quality Model with On-line Wildfire Emissions within the Canadian Operational Air Quality Forecast System

    NASA Astrophysics Data System (ADS)

    Pavlovic, Radenko; Chen, Jack; Beaulieu, Paul-Andre; Anselmp, David; Gravel, Sylvie; Moran, Mike; Menard, Sylvain; Davignon, Didier

    2014-05-01

    A wildfire emissions processing system has been developed to incorporate near-real-time emissions from wildfires and large prescribed burns into Environment Canada's real-time GEM-MACH air quality (AQ) forecast system. Since the GEM-MACH forecast domain covers Canada and most of the U.S.A., including Alaska, fire location information is needed for both of these large countries. During AQ model runs, emissions from individual fire sources are injected into elevated model layers based on plume-rise calculations and then transport and chemistry calculations are performed. This "on the fly" approach to the insertion of the fire emissions provides flexibility and efficiency since on-line meteorology is used and computational overhead in emissions pre-processing is reduced. GEM-MACH-FireWork, an experimental wildfire version of GEM-MACH, was run in real-time mode for the summers of 2012 and 2013 in parallel with the normal operational version. 48-hour forecasts were generated every 12 hours (at 00 and 12 UTC). Noticeable improvements in the AQ forecasts for PM2.5 were seen in numerous regions where fire activity was high. Case studies evaluating model performance for specific regions and computed objective scores will be included in this presentation. Using the lessons learned from the last two summers, Environment Canada will continue to work towards the goal of incorporating near-real-time intermittent wildfire emissions into the operational air quality forecast system.

  13. Air-quality-model update

    SciTech Connect

    Penner, J.E.; Walton, J.J.

    1982-01-15

    The Livermore Regional Air Quality Model (LIRAQ) has been updated and improved. This report describes the changes that have been made in chemistry, species treatment, and boundary conditions. The results of smog chamber simulations that were used to verify the chemistry as well as simulations of the entire air quality model for two prototype days in the Bay Area are reported. The results for the prototype day simulations are preliminary due to the need for improvement in meteorology fields, but they show the dependence and sensitivity of high hour ozone to changes in selected boundary and initial conditions.

  14. An annual assessment of air quality with the CALIOPE modeling system over Spain.

    PubMed

    Baldasano, J M; Pay, M T; Jorba, O; Gassó, S; Jiménez-Guerrero, P

    2011-05-01

    The CALIOPE project, funded by the Spanish Ministry of the Environment, aims at establishing an air quality forecasting system for Spain. With this goal, CALIOPE modeling system was developed and applied with high resolution (4km×4km, 1h) using the HERMES emission model (including emissions of resuspended particles from paved roads) specifically built up for Spain. The present study provides an evaluation and the assessment of the modeling system, coupling WRF-ARW/HERMES/CMAQ/BSC-DREAM8b for a full-year simulation in 2004 over Spain. The evaluation focuses on the capability of the model to reproduce the temporal and spatial distribution of gas phase species (NO(2), O(3), and SO(2)) and particulate matter (PM10) against ground-based measurements from the Spanish air quality monitoring network. The evaluation of the modeling results on an hourly basis shows a strong dependency of the performance of the model on the type of environment (urban, suburban and rural) and the dominant emission sources (traffic, industrial, and background). The O(3) chemistry is best represented in summer, when mean hourly variability and high peaks are generally well reproduced. The mean normalized error and bias meet the recommendations proposed by the United States Environmental Protection Agency (US-EPA) and the European regulations. Modeled O(3) shows higher performance for urban than for rural stations, especially at traffic stations in large cities, since stations influenced by traffic emissions (i.e., high-NO(x) environments) are better characterized with a more pronounced daily variability. NO(x)/O(3) chemistry is better represented under non-limited-NO(2) regimes. SO(2) is mainly produced from isolated point sources (power generation and transformation industries) which generate large plumes of high SO(2) concentration affecting the air quality on a local to national scale where the meteorological pattern is crucial. The contribution of mineral dust from the Sahara desert through

  15. 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).

  16. A Stochastic Deterministic Air Quality Forecasting System : Combining Time Series Models with Data-Assimilation

    NASA Astrophysics Data System (ADS)

    Kumar, U.; De Ridder, K.; Lefebvre, W.; Janssen, S.

    2012-04-01

    A new air quality forecast system has been developed in which all the corrections for the air quality model output by assimilating observations have been carried out in post-processing mode. In order to make more accurate forecasts of the air pollutants, time series models have been used in combination with data-assimilation. The approach has been validated for one day ahead forecasts of daily mean PM10 and daily mean NO2. First, the air quality model AURORA has been applied over the domain Belgium including part of its neighbouring areas with grid resolution of 3×3 km2 for a total of 121×71 grids. The observations data from AIRBASE archive has been used for the assimilation purpose. Only the background stations (urban or rural) data has been used. For data-assimilation, optimal interpolation in conjunction with Hollingsworth-Lönnberg method has been applied. The time series of the residuals, i.e., observations minus model output (for the daily mean PM10 and NO2) has been collected for the grids where monitoring stations were available. These time series were tested for their suitability for time series modelling applications. We applied the ARIMA(p,d,q) (Autoregressive Integrated Moving Average) as time series modelling technique to forecast the residuals in the future (one day ahead). In the next step, these forecasted residuals were assimilated with forecasted AURORA model output in order to get improved forecasted fields. The validation was carried out by leaving three stations out in one run of data-assimilation/time series forecasting. Thus, the validation results for one day ahead forecasts at the 15 stations for the duration 1-Mar-07 to 31-Dec-07 reveal that there has been substantial improvement in root mean square error (RMSE), a reduction ranging from 2% to 30%, has been observed. Similarly, correlation has also increased upto 30%. The results show that the approach presented here has tremendous potential to be applied in air quality forecasts.

  17. Prediction Models are Basis for Rational Air Quality Control

    ERIC Educational Resources Information Center

    Daniels, Anders; Bach, Wilfrid

    1973-01-01

    An air quality control scheme employing meteorological diffusion, time averaging and frequency, and cost-benefit models is discussed. The methods outlined provide a constant feedback system for air quality control. Flow charts and maps are included. (BL)

  18. 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...

  19. 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

  20. INTEGRATION OF THE BIOGENIC EMISSIONS INVENTORY SYSTEM (BEIS3) INTO THE COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM

    EPA Science Inventory

    The importance of biogenic emissions for regional air quality modeling is generally recognized [Guenther et al., 2000]. Since the 1980s, biogenic emission estimates have been derived from algorithms such as the Biogenic Emissions Inventory System (BEIS) [Pierce et. al., 1998]....

  1. 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

  2. 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.

  3. 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

  4. 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...

  5. 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-...

  6. 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

  7. 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.

  8. 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...

  9. 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...

  10. 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.

  11. 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...

  12. 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.

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. Application of the Wind Erosion Prediction System in the AIRPACT regional air quality modeling framework

    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, dust emissions due to wind erosion contribute to poor air quality, reduce visibility, and cause perturbations to regional radiation ...

  18. 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.

  19. 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...

  20. 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

  1. 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 ...

  2. 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...

  3. 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

  4. 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...

  5. 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.

  6. 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...

  7. A full year evaluation of the CALIOPE-EU air quality modeling system over Europe for 2004

    NASA Astrophysics Data System (ADS)

    Pay, M. T.; Piot, M.; Jorba, O.; Gassó, S.; Gonçalves, M.; Basart, S.; Dabdub, D.; Jiménez-Guerrero, P.; Baldasano, J. M.

    The CALIOPE-EU high-resolution air quality modeling system, namely WRF-ARW/HERMES-EMEP/CMAQ/BSC-DREAM8b, is developed and applied to Europe (12 km × 12 km, 1 h). The model performances are tested in terms of air quality levels and dynamics reproducibility on a yearly basis. The present work describes a quantitative evaluation of gas phase species (O 3, NO 2 and SO 2) and particulate matter (PM2.5 and PM10) against ground-based measurements from the EMEP (European Monitoring and Evaluation Programme) network for the year 2004. The evaluation is based on statistics. Simulated O 3 achieves satisfactory performances for both daily mean and daily maximum concentrations, especially in summer, with annual mean correlations of 0.66 and 0.69, respectively. Mean normalized errors are comprised within the recommendations proposed by the United States Environmental Protection Agency (US-EPA). The general trends and daily variations of primary pollutants (NO 2 and SO 2) are satisfactory. Daily mean concentrations of NO 2 correlate well with observations (annual correlation r = 0.67) but tend to be underestimated. For SO 2, mean concentrations are well simulated (mean bias = 0.5 μg m -3) with relatively high annual mean correlation ( r = 0.60), although peaks are generally overestimated. The dynamics of PM2.5 and PM10 is well reproduced (0.49 < r < 0.62), but mean concentrations remain systematically underestimated. Deficiencies in particulate matter source characterization are discussed. Also, the spatially distributed statistics and the general patterns for each pollutant over Europe are examined. The model performances are compared with other European studies. While O 3 statistics generally remain lower than those obtained by the other considered studies, statistics for NO 2, SO 2, PM2.5 and PM10 present higher scores than most models.

  8. 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...

  9. 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

  10. 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.

  11. 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...

  12. 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...

  13. 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....

  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. Evaluation of the chemically speciated particulate matter from a high-resolution air quality modeling system over the Iberian Peninsula

    NASA Astrophysics Data System (ADS)

    Pay, M. T.; Piot, M.; Jimenez-Guerrero, P.; Jorba, O.; Perez, C.; Baldasano, J. M.

    2009-04-01

    Particulate matter (PM) is a complex mixture of many compounds, both natural and anthropogenic; that determines its compositions and size. In addition, it is influenced by multiple atmospheric physico-chemical processes that can affect this matter from its release point, as a primary aerosol, or via gas-to-particle conversion processes that give rise to secondary aerosols. Inter-comparisons of European air quality models at regional and urban scales show that models tend to underestimate the observed concentrations of PM10 and PM2.5. Definitely, an accurate representation of the chemically speciated aerosols compounds is required in order to adequately simulate PM concentrations. The Barcelona Supercomputing Center-Centro Nacional de Supercomputacion (BSC-CNS) currently operates high-resolution air quality forecasts for Europe (12km, 1hr) and the Iberian Peninsula (4km, 1hr) with WRF-ARW/HERMES/CMAQ/DREAM modelling system under the umbrella of the CALIOPE project (http://www.bsc.es/caliope/) and Saharan dust forecasts with BSC-DREAM (http://www.bsc.es/projects/earthscience/DREAM/). In this framework, PM10 and PM2.5 products in both domains are achieved adding the Saharan dust contribution from DREAM (8 bins version) to the anthropogenic output of CMAQ. Furthermore, the CMAQ version used for this modelling system includes the contribution of sea salt aerosols. Eleven different chemical aerosol components can be distinguished, namely nitrates, sulphates, ammonium, elemental carbon, organic carbon with three subcomponents: primary, secondary anthropogenic and secondary biogenic, soil, sodium, chlorine and mineral dust. This study is focused on the evaluation of these aforementioned aerosol compounds from WRF-ARW/HERMES/CMAQ/DREAM over the Iberian Peninsula domain for the year 2004. The model evaluation with respect to the individual aerosol components has been performed for the domains of study. Albeit PM composition evaluation is presently hampered by the lack of

  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. 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...

  19. 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...

  20. 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.

  1. European Air Quality and Climate Change: a numerical modeling study

    NASA Astrophysics Data System (ADS)

    Lacressonniere, G.

    2011-12-01

    In the context of climate change, the evolution of air quality in Europe is a challenging scientific question, despite the political measures taken to limit and reduce anthropogenic emissions. Heat waves, changes in transport pathways or synoptic patterns, increase of emissions in other areas in the world, or for instance possible increase of biogenic emissions or changes in deposition and land use may affect adversely future Air Quality levels in Europe. In the context of a project co-funded by the French environment agency ADEME, a numerical modeling study has begun relying on the tools used by Météo-France for its contribution to the 5th IPCC assessment report, to GMES atmospheric services (MACC FP7 project) and to the French national operational Air Quality platform Prév'Air (http://www.prevair.org). In particular, the MOCAGE 3-D chemical transport model (CTM) is used with a configuration comprising a global (2°) and a European domain (0.2°), allowing representation of both long-range transport of pollutants and European Air Quality at relevant resolutions and with a two-ways coupling. MOCAGE includes 47 layers from the surface to 5hPa. The first step of this project was to assess the impact of meteorological forcings, either analyses ("best" meteorology available for the recent past) or climate runs for the current atmosphere, on air quality hindcasts with MOCAGE over Europe. For these climate runs, we rely on Météo-France Earth-System model CNRM-CM, and particularly the ARPEGE-climate general circulation model for the atmosphere. By studying several key variables for Air Quality (surface and low troposphere concentrations of ozone, nitrogen oxides, volatile organic compounds, radicals, PM,...), we investigated the indicators that are robust, through averages over several years, (monthly averages, frequency of exceedances, AOTs, ...) for a given climate when using climatological forcings instead of analyses, which constitutes the reference. Both

  2. 77 FR 4808 - Conference on Air Quality Modeling

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-01-31

    ... 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 on...; suggest alternatives and substitute language for your requested changes. Describe any assumptions...

  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. 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.

  5. 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

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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.

  13. Operational air quality forecasting system for Spain: CALIOPE

    NASA Astrophysics Data System (ADS)

    Baldasano, J. M.; Piot, M.; Jorba, O.; Goncalves, M.; Pay, M.; Pirez, C.; Lopez, E.; Gasso, S.; Martin, F.; García-Vivanco, M.; Palomino, I.; Querol, X.; Pandolfi, M.; Dieguez, J. J.; Padilla, L.

    2009-12-01

    The European Commission (EC) and the United States Environmental Protection Agency (US-EPA) have shown great concerns to understand the transport and dynamics of pollutants in the atmosphere. According to the European directives (1996/62/EC, 2002/3/EC, 2008/50/EC), air quality modeling, if accurately applied, is a useful tool to understand the dynamics of air pollutants, to analyze and forecast the air quality, and to develop programs reducing emissions and alert the population when health-related issues occur. The CALIOPE project, funded by the Spanish Ministry of the Environment, has the main objective to establish an air quality forecasting system for Spain. A partnership of four research institutions composes the CALIOPE project: the Barcelona Supercomputing Center (BSC), the center of investigation CIEMAT, the Earth Sciences Institute ‘Jaume Almera’ (IJA-CSIC) and the CEAM Foundation. CALIOPE will become the official Spanish air quality operational system. This contribution focuses on the recent developments and implementation of the integrated modelling system for the Iberian Peninsula (IP) and Canary Islands (CI) with a high spatial and temporal resolution (4x4 sq. km for IP and 2x2 sq. km for CI, 1 hour), namely WRF-ARW/HERMES04/CMAQ/BSC-DREAM. The HERMES04 emission model has been specifically developed as a high-resolution (1x1 sq. km, 1 hour) emission model for Spain. It includes biogenic and anthropogenic emissions such as on-road and paved-road resuspension production, power plant generation, ship and plane traffic, airports and ports activities, industrial and agricultural sectors as well as domestic and commercial emissions. The qualitative and quantitative evaluation of the model was performed for a reference year (2004) using data from ground-based measurement networks. The products of the CALIOPE system will provide 24h and 48h forecasts for O3, NO2, SO2, CO, PM10 and PM2.5 at surface level. An operational evaluation system has been developed

  14. Urban Air Quality Modelling with AURORA: Prague and Bratislava

    NASA Astrophysics Data System (ADS)

    Veldeman, N.; Viaene, P.; De Ridder, K.; Peelaerts, W.; Lauwaet, D.; Muhammad, N.; Blyth, L.

    2012-04-01

    The European Commission, in its strategy to protect the health of the European citizens, states that in order to assess the impact of air pollution on public health, information on long-term exposure to air pollution should be available. Currently, indicators of air quality are often being generated using measured pollutant concentrations. While air quality monitoring stations data provide accurate time series information at specific locations, air quality models have the advantage of being able to assess the spatial variability of air quality (for different resolutions) and predict air quality in the future based on different scenarios. When running such air quality models at a high spatial and temporal resolution, one can simulate the actual situation as closely as possible, allowing for a detailed assessment of the risk of exposure to citizens from different pollutants. AURORA (Air quality modelling in Urban Regions using an Optimal Resolution Approach), a prognostic 3-dimensional Eulerian chemistry-transport model, is designed to simulate urban- to regional-scale atmospheric pollutant concentration and exposure fields. The AURORA model also allows to calculate the impact of changes in land use (e.g. planting of trees) or of emission reduction scenario's on air quality. AURORA is currently being applied within the ESA atmospheric GMES service, PASODOBLE (http://www.myair-eu.org), that delivers information on air quality, greenhouse gases, stratospheric ozone, … At present there are two operational AURORA services within PASODOBLE. Within the "Air quality forecast service" VITO delivers daily air quality forecasts for Belgium at a resolution of 5 km and for the major Belgian cities: Brussels, Ghent, Antwerp, Liege and Charleroi. Furthermore forecast services are provided for Prague, Czech Republic and Bratislava, Slovakia, both at a resolution of 1 km. The "Urban/regional air quality assessment service" provides urban- and regional-scale maps (hourly resolution

  15. 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...

  16. 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...

  17. 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.

  18. 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.

  19. 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...

  20. Innovation of Ozone Initial Concentration and Boundary Condition for Models-3 Community Multi-scale Air Quality (CMAQ) Modeling System Using Ozone Climatology and Its Impacts

    NASA Astrophysics Data System (ADS)

    He, S.; Vukovich, F. M.; Ching, J.; Gilliland, A.

    2002-05-01

    Models-3/CMAQ system is designed to provide a comprehensive and flexible modeling tool for states and other government agencies, and for scientific studies. The current setting of initial concentrations and boundary condition (ICBC) of air species for CMAQ system represents clean ambient condition in the eastern-half of the US, and as such. The ozone ICBC differed from observational values, significantly at upper troposphere. Because of the stratosphere-troposphere exchange, the upper troposphere may contain high concentrations of ozone (hundreds of ppbv). However the current ICBC artificially set ozone level as 70ppbv in upper troposphere throughout model domain. The large difference of standard ozone ICBC from realistic situation becomes considerable uncertainty source of CMAQ system. The purpose of this research is to improve ICBC setting for Models-3/CMAQ modeling system, and to assess the influence of introducing stratospheric ozone into troposphere on regional and urban air quality and on the tropospheric ozone budget. The approach taken is to perform a series of sensitivity studies on ICBC with CMAQ. The simulation covers the entire US with 108km grid resolution from July 2 to 12 of 1988. The domain divide in 34 layers vertically up to 40mbar. In addition to the base case with standard ICBC, ozone initial concentration and boundary condition are generated based on ozone climatology (Logan, 1999), which was derived from surface, satellite, and ozonesonde data across the globe. This new ICBC enables CMAQ model to study ozone cross-tropopause flux transporting to lower troposphere, and to analyze the impact of intercontinental ozone transport. The tropospheric ozone residue (TOR) data is used to compare with modeling tropospheric ozone budget for evaluation of CMAQ performance. Since ozone climatology was based on observation, the derived ozone ICBC are in better agreement with the ``real'' atmosphere than standard ICBC. CMAQ simulations with ozone climatology

  1. 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.

  2. 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)

  3. 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

  4. Air Quality Modeling of Ozone Radical Precursors in Houston

    NASA Astrophysics Data System (ADS)

    Rappenglueck, B.; Czader, B.; Li, X.

    2013-05-01

    The Houston-Galveston area has one of the highest ozone concentrations in the U.S., often exceeding the U.S. National Ambient Air Quality Standard for ozone. Photochemical modeling of ozone formation in the Houston area generally underestimates the concentrations of free radical precursors contributing to ozone formation. Here we present modeling results using the Weather Research Forecast - Community Multiscale Air Quality (WRF-CMAQ) modeling system for the Houston-Galveston area. Meteorological parameters predicted by WRF are well simulated most of the time, including planetary boundary layer heights. Air quality simulations for the Houston-Galveston-Brazoria area using the combined WRF-SMOKE-CMAQ system showed overall good results for ozone and many other trace gases. HONO morning peaks are no longer underpredicted, on some occasions they are slightly overpredicted, which can be linked to NO2 overprediction. However, CMAQ mispredicts other trace gases like HO2, H2O2 and CH3OOH concentrations. The WRF-SMOKE-CMAQ system was also used to elucidate the relative importance of various photolysis processes as radical sources in the Houston atmosphere. Morning HOx formation is dominated by HONO while ozone contributes the most during midday. HONO contribution to HOx formation is more pronounced at the surface layer where most of it is formed. On the other hand, radical production from ozone is more important at elevated levels where higher concentrations of ozone are observed. Formaldehyde contributes up to 40% and also peaks during mid-day, but on days when high morning concentrations of formaldehyde are observed its contribution to HOx in the morning exceeds that of ozone. Photolysis of H2O2 is a minor contributor to radical levels. The process analysis tool available in CMAQ was utilized to analyze photochemical processes leading to ozone production and chemical transformations along trajectories linking a site at the Houston Ship Channel and the University of

  5. 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...

  6. AN INDOOR AIR QUALITY MODEL FOR PARTICULATE MATTER

    EPA Science Inventory

    Thye paper discusses an indoor air quality (IAQ) model for particulate matter (PM). The standard for PM < 2.5 micrometers in aerodynamic diameter (PM 2.5) proposed by the U.S. EPA has produced considerable interest in indoor exposures to PM. IAQ models provide a useful tool for...

  7. 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...

  8. Air-quality modelling in the Lake Baikal region.

    PubMed

    Van de Vel, Karen; Mensink, Clemens; De Ridder, Koen; Deutsch, Felix; Maes, Joachim; Vliegen, Jo; Aloyan, Artash; Yermakov, Alexander; Arutyunyan, Vardan; Khodzher, Tamara; Mijling, Bas

    2010-06-01

    In this paper, we assess the status of the air quality in the Lake Baikal region which is strongly influenced by the presence of anthropogenic pollution sources. We combined the local data, with global databases, remote sensing imagery and modelling tools. This approach allows to inventorise the air-polluting sources and to quantify the air-quality concentration levels in the Lake Baikal region to a reasonable level, despite the fact that local data are scarcely available. In the simulations, we focus on the month of July 2003, as for this period, validation data are available for a number of ground-based measurement stations within the Lake Baikal region.

  9. 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

  10. [Air quality control systems: heating, ventilating, and air conditioning (HVAC)].

    PubMed

    Bellucci Sessa, R; Riccio, G

    2004-01-01

    After a brief illustration of the principal layout schemes of Heating, Ventilating, and Air Conditioning (HVAC), the first part of this paper summarizes the standards, both voluntary and compulsory, regulating HVAC facilities design and installation with regard to the question of Indoor Air Quality (IAQ). The paper then examines the problem of ventilation systems maintenance and the essential hygienistic requirements in whose absence HVAC facilities may become a risk factor for people working or living in the building. Lastly, the paper deals with HVAC design strategies and methods, which aim not only to satisfy comfort and air quality requirements, but also to ensure easy and effective maintenance procedures.

  11. 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<...

  12. 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.

  13. 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...

  14. 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...

  15. PERFORMANCE AND DIAGNOSTIC EVALUATION OF OZONE PREDICTIONS BY THE ETA-COMMUNITY MULTISCALE AIR QUALITY FORECAST SYSTEM DURING THE 2002 NEW ENGLAND AIR QUALITY STUDY

    EPA Science Inventory

    A real-time air quality forecasting system (Eta-CMAQ model suite) has been developed by linking the NCEP Eta model to the U.S. EPA CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting O3 over the northeastern U.S d...

  16. AQA - Air Quality model for Austria - Evaluation and Developments

    NASA Astrophysics Data System (ADS)

    Hirtl, M.; Krüger, B. C.; Baumann-Stanzer, K.; Skomorowski, P.

    2009-04-01

    The regional weather forecast model ALADIN of the Central Institute for Meteorology and Geodynamics (ZAMG) is used in combination with the chemical transport model CAMx (www.camx.com) to conduct forecasts of gaseous and particulate air pollution over Europe. The forecasts which are done in cooperation with the University of Natural Resources and Applied Life Sciences in Vienna (BOKU) are supported by the regional governments since 2005 with the main interest on the prediction of tropospheric ozone. The daily ozone forecasts are evaluated for the summer 2008 with the observations of about 150 air quality stations in Austria. In 2008 the emission-model SMOKE was integrated into the modelling system to calculate the biogenic emissions. The anthropogenic emissions are based on the newest EMEP data set as well as on regional inventories for the core domain. The performance of SMOKE is shown for a summer period in 2007. In the frame of the COST-action 728 „Enhancing mesoscale meteorological modelling capabilities for air pollution and dispersion applications", multi-model ensembles are used to conduct an international model evaluation. The model calculations of meteorological- and concentration fields are compared to measurements on the ensemble platform at the Joint Research Centre (JRC) in Ispra. The results for 2 episodes in 2006 show the performance of the different models as well as of the model ensemble.

  17. Influence of grid resolution and meteorological forcing on simulated European air quality: A sensitivity study with the modeling system COSMO-MUSCAT

    NASA Astrophysics Data System (ADS)

    Wolke, Ralf; Schröder, Wolfram; Schrödner, Roland; Renner, Eberhard

    2012-06-01

    Model evaluation studies are essential for determining model performance as well as assessing model deficiencies, and are the focus of the Air Quality Model Evaluation International Initiative (AQMEII). The chemistry-transport model system COSMO-MUSCAT participates in this initiative. In this paper the robustness and variability of the model results against changes in the model setup are analyzed. Special focus is given to the formation of secondary particulate matter and the ability to reproduce unusually high levels of PM10 in Central Europe caused by long-range transported smoke of fires in western Russia. Seven different model configurations are investigated in this study. The COSMO-MUSCAT results are evaluated in comparison with ground-based measurements in Central Europe. The analysis is performed for two selected periods in April/May 2006 and October 2006 which are characterized by elevated concentrations of PM. Furthermore, the sensitivity of the results is studied against the used grid resolution and the meteorological forcing. Here, COSMO-MUSCAT is applied with different horizontal grid sizes and, alternatively, forced by reanalysis data with finer resolution. The use of finer grid resolutions in COSMO-MUSCAT has direct consequences on the meteorological forcing as well as on the calculated emission and deposition rates. The presented results suggest a large impact of the meteorological effects on the PM concentrations. The more accurate spatial appointment of the emissions and deposition fluxes seems to be of little consequence compared to the meteorological forcing.

  18. 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.

  19. 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.

  20. 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

  1. Likelihood of achieving air quality targets under model uncertainties.

    PubMed

    Digar, Antara; Cohan, Daniel S; Cox, Dennis D; Kim, Byeong-Uk; Boylan, James W

    2011-01-01

    Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses. PMID:21138291

  2. Likelihood of achieving air quality targets under model uncertainties.

    PubMed

    Digar, Antara; Cohan, Daniel S; Cox, Dennis D; Kim, Byeong-Uk; Boylan, James W

    2011-01-01

    Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses.

  3. 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

  4. 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

  5. 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...

  6. Inverse modelling of air quality data through a neural network approach

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    Air quality is usually driven by a complex combination of factors where meteorology, physical obstacles and interaction between pollutants play significant roles. Considering the characteristics of the atmospheric circulation and also the residence times of certain pollutants in the atmosphere, air pollution is, nowadays, considered to be a global problem that affects everyone. As a result, 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. 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 neural network modelling. In this paper, we describe the development of a neural network tool to forecast the daily average NO2 concentrations in Lisbon, Portugal, one day ahead. This research is based upon measurements from 22 air quality monitoring stations during the period 2001-2005. The analysis revealed that the most significant variable in predicting NO2 daily concentration is the previous day value of NO2 concentration followed by the 5a.m. NO2 concentration. This approach shows to be very promising for urban air quality characterization, allowing further developments in order to produce an integrated air quality and health surveillance/monitoring system in the area of Lisbon.

  7. The Evaluation of the Spanish Air Quality Modelling System: CALIOPE. Dynamics and Chemistry over Europe and Iberian Peninsula for 2004 at high horizontal resolution

    NASA Astrophysics Data System (ADS)

    Piot, M.; Pay, M.; Jorba, O.; Lopez, E.; Pirez, C.; Gasso, S.; Baldasano, J. M.

    2009-12-01

    In Europe, human exposure to air pollution often exceeds standards set by the EU commission (Directives 1996/62/EC, 2002/3/EC, 2008/50/EC) 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. Within the CALIOPE project, a high-resolution air quality forecasting system, namely WRF-ARW/HERMES04/CMAQ/BSC-DREAM, has been developed and applied to the European domain (12x12 sq. km, 1hr) as well as the Spanish domain (4x4 sq. km, 1hr). The simulation of such high-resolution model system has been made possible by its implementation on the MareNostrum supercomputer. This contribution describes a thorough quantitative evaluation study performed for the reference year 2004. The WRF-ARW meteorological model contains 38 vertical layers reaching up to 50 hPa. 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. For the European simulation, emissions are disaggregated from the EMEP emission inventory for 2004 to the utilized resolution using the criteria implemented in the HERMES04 emission model. The HERMES04 model system, running through a bottom-up approach, is used to estimate emissions for Spain at a 1x1 sq. km horizontal resolution, every hour. In order to evaluate the performances of the CALIOPE system, the model simulation for Europe was compared with ground-based measurements from the EMEP and the Spanish air quality networks (total of 60 stations for O3, 43 for NO2, 31 for SO2, 25 for PM10 and 16 for PM2.5). The model simulation for Europe satisfactorily reproduces O3 concentrations throughout the year (annual correlation: 0.66) with relatively small errors: MNGE values range from 13% to 26%, and MNBE

  8. 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...

  9. 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.

  10. 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...

  11. 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...

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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

  19. 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...

  20. Choosing the Appropriate Model Resolution for Public-Health-Relevant Air Quality Simulations

    NASA Astrophysics Data System (ADS)

    Holloway, T.; Kinney, P. L.

    2002-05-01

    Atmospheric chemistry models offer a powerful tool for assessing health impacts of air pollution. They may be used to estimate air quality away from monitoring stations, consider future scenarios of energy use or climate change, and examine how individual components of emissions, chemistry, and transport contribute to observed patterns. However, the scales necessary for evaluating health impacts of air pollution are not well-defined. What model resolution is needed to capture variability in ozone or PM concentrations associated with variability in respiratory disease? The current study addresses this question by examining spatial patterns in the correlation of air quality and morbidity data in New York State. Here, we present initial results based on data from New York Statewide Planning and Research Cooperative System (SPARCS) and US EPA Aerometric Information Retrieval System (AIRS). Timeseries correlations between air quality (ozone and PM) and respiratory disease are evaluated on different scales of data aggregation. We examine how correlation depends on the level of spatial averaging and on the timescale over which correlations are considered. These results will inform modeling studies, in part defining what model resolution is appropriate for simulating air quality relevant to public health assessments.

  1. 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 (...

  2. Evaluation of the Models-3 Community Multi-scale Air Quality (CMAQ) modeling system with observations obtained during the TRACE-P experiment: Comparison of ozone and its related species

    NASA Astrophysics Data System (ADS)

    Zhang, Meigen; Uno, Itsushi; Zhang, Renjian; Han, Zhiwei; Wang, Zifa; Pu, Yifen

    The Models-3 Community Multi-scale Air Quality (CMAQ) modeling system with meteorological fields calculated by the Regional Atmospheric Modeling System (RAMS) was applied to East Asia to investigate the transport and photochemical transformation of tropospheric ozone during the Transport and Chemical Evolution over the Pacific (TRACE-P) field campaign. Modeled concentrations of hydroxyl radical, hydroperoxyl radical, nitric oxide, nitrogen dioxide, ethene, ethane, carbon monoxide, and ozone were compared with observations obtained onboard of two aircrafts in order to evaluate the model performance. Comparison indicates that the model reproduced the tempo-spatial distributions of ozone and its related chemical species reasonably well, and most model results were within a factor of 2 of the observations.

  3. 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

  4. Performance criteria to evaluate air quality modeling applications

    NASA Astrophysics Data System (ADS)

    Thunis, P.; Pederzoli, A.; Pernigotti, D.

    2012-11-01

    A set of statistical indicators fit for air quality model evaluation is selected based on experience and literature: The Root Mean Square Error (RMSE), the bias, the Standard Deviation (SD) and the correlation coefficient (R). Among these the RMSE is proposed as the key one for the description of the model skill. Model Performance Criteria (MPC) to investigate whether model results are 'good enough' for a given application are calculated based on the observation uncertainty (U). The basic concept is to allow for model results a similar margin of tolerance (in terms of uncertainty) as for observations. U is pollutant, concentration level and station dependent, therefore the proposed MPC are normalized by U. Some composite diagrams are adapted or introduced to visualize model performance in terms of the proposed MPC and are illustrated in a real modeling application. The Target diagram, used to visualize the RMSE, is adapted with a new normalization on its axis, while complementary diagrams are proposed. In this first application the dependence of U on concentrations level is ignored, and an assumption on the pollutant dependent relative error is made. The advantages of this new approach are finally described.

  5. Mathematical models for predicting indoor air quality from smoking activity.

    PubMed Central

    Ott, W R

    1999-01-01

    Much progress has been made over four decades in developing, testing, and evaluating the performance of mathematical models for predicting pollutant concentrations from smoking in indoor settings. Although largely overlooked by the regulatory community, these models provide regulators and risk assessors with practical tools for quantitatively estimating the exposure level that people receive indoors for a given level of smoking activity. This article reviews the development of the mass balance model and its application to predicting indoor pollutant concentrations from cigarette smoke and derives the time-averaged version of the model from the basic laws of conservation of mass. A simple table is provided of computed respirable particulate concentrations for any indoor location for which the active smoking count, volume, and concentration decay rate (deposition rate combined with air exchange rate) are known. Using the indoor ventilatory air exchange rate causes slightly higher indoor concentrations and therefore errs on the side of protecting health, since it excludes particle deposition effects, whereas using the observed particle decay rate gives a more accurate prediction of indoor concentrations. This table permits easy comparisons of indoor concentrations with air quality guidelines and indoor standards for different combinations of active smoking counts and air exchange rates. The published literature on mathematical models of environmental tobacco smoke also is reviewed and indicates that these models generally give good agreement between predicted concentrations and actual indoor measurements. PMID:10350523

  6. European Air Quality and Climate Change: first steps of a numerical modeling study

    NASA Astrophysics Data System (ADS)

    Lacressonnière, Gwendoline; Peuch, Vincent-Henri; Josse, Béatrice; Joly, Mathieu; Martet, Maud

    2010-05-01

    In the context of climate change, the evolution of air quality in Europe is a challenging scientific question, despite the political measures taken to limit and reduce anthropogenic emissions. Heat waves, changes in transport pathways or synoptic patterns, increase of emissions in other areas in the world (in particular in Asia), or for instance possible increase of biogenic emissions may affect adversely future Air Quality levels in Europe. In the context of a project co-funded by the French environment agency ADEME, a numerical modeling study has begun relying on the tools used by Météo-France for its contribution to the 5th IPCC assessment report, to GMES atmospheric services (MACC FP7 project) and to the French national operational Air Quality platform Prév'Air (http://www.prevair.org). In particular, the MOCAGE 3-D chemical transport model (CTM) is used with a configuration comprising a global (2°) and a European domain (0.2°), allowing representation of both long-range transport of pollutants and European Air Quality at relevant resolutions and with a two-ways coupling. MOCAGE includes 47 layers from the surface to 5hPa. The first step of this project is to assess the impact of meteorological forcings, either analyses ("best" meteorology available for the recent past) or climate runs for the current atmosphere (interpolated on the same high resolution grid), on air quality hindcasts with MOCAGE over Europe. For these climate runs, we rely on Météo-France Earth-System model CNRM-CM, and particularly the ARPEGE-climate general circulation model for the atmosphere. By studying several key variables for Air Quality (surface and low troposphere concentrations of ozone, nitrogen oxides, volatile organic compounds, radicals, PM,…) we aim at investigating the indicators that are robust or not (monthly averages, frequency of exceedances, AOTs,…) for a given climate when using climatological forcings instead of analyses (reference), all the rest in the CTM

  7. 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.

  8. 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

  9. 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.

  10. 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...

  11. 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 ...

  12. Daily air quality forecast (gases and aerosols) over Switzerland. Modeling tool description and first results analysis.

    NASA Astrophysics Data System (ADS)

    Couach, O.; Kirchner, F.; Porchet, P.; Balin, I.; Parlange, M.; Balin, D.

    2009-04-01

    Map3D, the acronym for "Mesoscale Air Pollution 3D modelling", was developed at the EFLUM laboratory (EPFL) and received an INNOGRANTS awards in Summer 2007 in order to move from a research phase to a professional product giving daily air quality forecast. It is intended to give an objective base for political decisions addressing the improvement of regional air quality. This tool is a permanent modelling system which provides daily forecast of the local meteorology and the air pollutant (gases and particles) concentrations. Map3D has been successfully developed and calculates each day at the EPFL site a three days air quality forecast over Europe and the Alps with 50 km and 15 km resolution, respectively (see http://map3d.epfl.ch). The Map3D user interface is a web-based application with a PostgreSQL database. It is written in object-oriented PHP5 on a MVC (Model-View-Controller) architecture. Our prediction system is operational since August 2008. A first validation of the calculations for Switzerland is performed for the period of August 2008 - January 2009 comparing the model results for O3, NO2 and particulates with the results of the Nabel measurements stations. The subject of air pollution regimes (NOX/VOC) and specific indicators application with the forecast will be also addressed.

  13. 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...

  14. 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...

  15. 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.

  16. 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 ...

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. APPLICATION AND EVALUATION OF CMAQ IN THE UNITED STATES: AIR QUALITY FORECASTING AND RETROSPECTIVE MODELING

    EPA Science Inventory

    Presentation slides provide background on model evaluation techniques. Also included in the presentation is an operational evaluation of 2001 Community Multiscale Air Quality (CMAQ) annual simulation, and an evaluation of PM2.5 for the CMAQ air quality forecast (AQF) ...

  4. The chemistry CATT-BRAMS model (CCATT-BRAMS 4.5): a regional atmospheric model system for integrated air quality and weather forecasting and research

    NASA Astrophysics Data System (ADS)

    Longo, K. M.; Freitas, S. R.; Pirre, M.; Marécal, V.; Rodrigues, L. F.; Panetta, J.; Alonso, M. F.; Rosário, N. E.; Moreira, D. S.; Gácita, M. S.; Arteta, J.; Fonseca, R.; Stockler, R.; Katsurayama, D. M.; Fazenda, A.; Bela, M.

    2013-02-01

    The Coupled Chemistry Aerosol-Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CCATT-BRAMS, version 4.5) is an online regional chemical transport model designed for local and regional studies of atmospheric chemistry from surface to the lower stratosphere suitable both for operational and research purposes. It includes gaseous/aqueous 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. BRAMS includes state-of-the-art physical parameterizations and dynamic formulations to simulate atmospheric circulations of scales down to meters. The online coupling between meteorology and chemistry allows the system to be used for simultaneous atmospheric weather and chemical composition forecasts as well as potential feedbacks between them. The entire system comprises three preprocessing software tools for chemical mechanism (which are user defined), aerosol and trace gases emission fields and atmospheric and chemistry fields for initial and boundary conditions. In this paper, the model description is provided along evaluations performed using observational data obtained from ground-based stations, instruments aboard of aircrafts and retrieval from space remote sensing. The evaluation takes into account model application on different scales from megacities and Amazon Basin up to intercontinental region of the Southern Hemisphere.

  5. The Chemistry CATT-BRAMS model (CCATT-BRAMS 4.5): a regional atmospheric model system for integrated air quality and weather forecasting and research

    NASA Astrophysics Data System (ADS)

    Longo, K. M.; Freitas, S. R.; Pirre, M.; Marécal, V.; Rodrigues, L. F.; Panetta, J.; Alonso, M. F.; Rosário, N. E.; Moreira, D. S.; Gácita, M. S.; Arteta, J.; Fonseca, R.; Stockler, R.; Katsurayama, D. M.; Fazenda, A.; Bela, M.

    2013-09-01

    Coupled Chemistry Aerosol-Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CCATT-BRAMS, version 4.5) is an on-line regional chemical transport model designed for local and regional studies of atmospheric chemistry from the surface to the lower stratosphere suitable both for operational and research purposes. It includes gaseous/aqueous chemistry, photochemistry, scavenging and dry deposition. The CCATT-BRAMS model takes advantage of BRAMS-specific development for the tropics/subtropics as well as the recent availability of preprocessing tools for chemical mechanisms and fast codes for photolysis rates. BRAMS includes state-of-the-art physical parameterizations and dynamic formulations to simulate atmospheric circulations down to the meter. This on-line coupling of meteorology and chemistry allows the system to be used for simultaneous weather and chemical composition forecasts as well as potential feedback between the two. The entire system is made of three preprocessing software tools for user-defined chemical mechanisms, aerosol and trace gas emissions fields and the interpolation of initial and boundary conditions for meteorology and chemistry. In this paper, the model description is provided along with the evaluations performed by using observational data obtained from ground-based stations, instruments aboard aircrafts and retrieval from space remote sensing. The evaluation accounts for model applications at different scales from megacities and the Amazon Basin up to the intercontinental region of the Southern Hemisphere.

  6. 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.

  7. “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...

  8. 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...

  9. 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.

  10. 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

  11. 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...

  12. 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...

  13. 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

  14. 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.

  15. 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

    2014-08-28

    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.

  16. 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

  17. Fuzzy-GA modeling in air quality assessment.

    PubMed

    Yadav, Jyoti; Kharat, Vilas; Deshpande, Ashok

    2015-04-01

    In this paper, the authors have suggested and implemented the defined soft computing methods in air quality classification with case studies. The first study relates to the application of Fuzzy C mean (FCM) clustering method in estimating pollution status in cities of Maharashtra State, India. In this study, the computation of weighting factor using a new concept of reference group is successfully demonstrated. The authors have also investigated the efficacy of fuzzy set theoretic approach in combination with genetic algorithm in straightway describing air quality in linguistic terms with linguistic degree of certainty attached to each description using Zadeh-Deshpande (ZD) approach. Two metropolitan cities viz., Mumbai in India and New York in the USA are identified for the assessment of the pollution status due to their somewhat similar geographical features. The case studies infer that the fuzzy sets drawn on the basis of expert knowledge base for the criteria pollutants are not much different from those obtained using genetic algorithm. Pollution forecast using various methods including fuzzy time series forms an integral part of the paper.

  18. 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.

  19. 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.

  20. 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...

  1. 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 ...

  2. 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...

  3. 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.

  4. 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...

  5. 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...

  6. A PERFORMANCE EVALUATION OF THE ETA- CMAQ AIR QUALITY FORECAST SYSTEM FOR THE SUMMER OF 2005

    EPA Science Inventory

    This poster presents an evaluation of the Eta-CMAQ Air Quality Forecast System's experimental domain using O3 observations obtained from EPA's AIRNOW program and a suite of statistical metrics examining both discrete and categorical forecasts.

  7. 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.

  8. 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...

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. 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...

  14. 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

  15. 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.

  16. 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.

  17. Implementation of plume rise and its impacts on emissions and air quality modelling

    NASA Astrophysics Data System (ADS)

    Guevara, Marc; Soret, Albert; Arévalo, Gustavo; Martínez, Francesc; Baldasano, José M.

    2014-12-01

    This work analyses the impact of implementing hourly plume rise calculations over Spain in terms of: i) vertical emission allocations and ii) modelled air quality concentrations. Two air quality simulations (4 km × 4 km, 1 h) were performed for February and June 2009, using the CALIOPE-AQFS system (WRF-ARW/HERMESv2.0/CMAQ/BSC-DREAM8b) differing only by the vertical allocation of point source emissions: i) using fixed vertical profiles based on the stack height of each facility and ii) using an hourly bottom-up calculations of effective emission heights. When using plume rise calculations, emissions are generally allocated to lower altitudes than when using the fixed vertical profiles, showing significant differences depending on source sector and air pollutant (up to 75% between estimated average effective emission heights). In terms of air quality, it is shown that hourly plume rise calculations lead to improved simulation of industrial SO2 concentrations, thus increasing modelled concentrations (1.4 μg m-3 increase in February, 1.5 μg m-3 increase in June) and reducing the model biases for both months (31.1% in February, 73.7% in June). The increase of SO2 concentrations leads to an increase of SO4-2 surface levels that varies according to the season and location (4.3% in February and 0.4% in June, on average). On the other hand, the impact on NO2 and PM10 concentrations is less significant, leading to average changes of a few μg·m3 at most (0.4 μg m-3 for NO2 and 0.2 μg m-3 for PM10). In order to maximize the precision of plume rise calculations, the use of stack parameters based on real-world data is mandatory.

  18. 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

  19. 3D-AQS: a three-dimensional air quality system

    NASA Astrophysics Data System (ADS)

    Hoff, Raymond M.; Engel-Cox, Jill A.; Dimmick, Fred; Szykman, James J.; Johns, Brad; Kondragunta, Shobha; Rogers, Raymond; McCann, Kevin; Chu, D. Allen; Torres, Omar; Prados, Ana; Al-Saadi, Jassim; Kittaka, Chieko; Boothe, Vickie; Ackerman, Steve; Wimmers, Anthony

    2006-08-01

    In 2006, we began a three-year project funded by the NASA Integrated Decisions Support program to develop a three-dimensional air quality system (3D-AQS). The focus of 3D-AQS is on the integration of aerosol-related NASA Earth Science Data into key air quality decision support systems used for air quality management, forecasting, and public health tracking. These will include the U.S. Environmental Protection Agency (EPA)'s Air Quality System/AirQuest and AIRNow, Infusing satellite Data into Environmental Applications (IDEA) product, U.S. Air Quality weblog (Smog Blog) and the Regional East Atmospheric Lidar Mesonet (REALM). The project will result in greater accessibility of satellite and lidar datasets that, when used in conjunction with the ground-based particulate matter monitors, will enable monitoring across horizontal and vertical dimensions. Monitoring in multiple dimensions will enhance the air quality community's ability to monitor and forecast the geospatial extent and transboundary transport of air pollutants, particularly fine particulate matter. This paper describes the concept of this multisensor system and gives current examples of the types of products that will result from it.

  20. 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...

  1. 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.

  2. Photochemical modeling of the Ozark isoprene volcano: MEGAN, BEIS, and their impacts on air quality predictions.

    PubMed

    Carlton, Annmarie G; Baker, Kirk R

    2011-05-15

    Biogenic volatile organic compounds (BVOCs) contribute substantially to atmospheric carbon, exerting influence on air quality and climate. Two widely used models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emission Inventory System (BEIS) are employed to generate emissions for application in the CMAQ air quality model. Predictions of isoprene, monoterpenes, ozone, formaldehyde, and secondary organic carbon (SOC) are compared to surface and aloft measurements made during an intensive study in the Ozarks, a large isoprene emitting region. MEGAN and BEIS predict spatially similar emissions but magnitudes differ. The total VOC reactivity of the emissions, as developed for the CB05 gas-phase chemical mechanism, is a factor of 2 different between the models. Isoprene estimates by CMAQ-MEGAN are higher and more variable than surface and aloft measurements, whereas CMAQ-BEIS predictions are lower. CMAQ ozone predictions are similar and compare well with measurements using either MEGAN or BEIS. However, CMAQ-MEGAN overpredicts formaldehyde. CMAQ-BEIS SOC predictions are lower than observational estimates for every sample. CMAQ-MEGAN underpredicts SOC ∼ 80% of the time, despite overprediction of precursor VOCs. CMAQ-MEGAN isoprene predictions improve when prognostically predicted solar radiation is replaced with the GEWEX satellite product. CMAQ-BEIS does not exhibit similar photosensitivity. PMID:21520901

  3. 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.

  4. 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...

  5. "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...

  6. Emission inventories and modeling requirements for the development of air quality plans. Application to Madrid (Spain).

    PubMed

    Borge, Rafael; Lumbreras, Julio; Pérez, Javier; de la Paz, David; Vedrenne, Michel; de Andrés, Juan Manuel; Rodríguez, Ma Encarnación

    2014-01-01

    Modeling is an essential tool for the development of atmospheric emission abatement measures and air quality plans. Most often these plans are related to urban environments with high emission density and population exposure. However, air quality modeling in urban areas is a rather challenging task. As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable and sophisticated modeling tools are needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large urban areas across Europe, particularly for NO₂. This also implies that emission inventories must satisfy a number of conditions such as consistency across the spatial scales involved in the analysis, consistency with the emission inventories used for regulatory purposes and versatility to match the requirements of different air quality and emission projection models. This study reports the modeling activities carried out in Madrid (Spain) highlighting the atmospheric emission inventory development and preparation as an illustrative example of the combination of models and data needed to develop a consistent air quality plan at urban level. These included a series of source apportionment studies to define contributions from the international, national, regional and local sources in order to understand to what extent local authorities can enforce meaningful abatement measures. Moreover, source apportionment studies were conducted in order to define contributions from different sectors and to understand the maximum feasible air quality improvement that can be achieved by reducing emissions from those sectors, thus targeting emission reduction policies to the most relevant activities. Finally, an emission scenario reflecting the effect of such policies was developed and the associated air quality was modeled.

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. Towards an agent based traffic regulation and recommendation system for the on-road air quality control.

    PubMed

    Sadiq, Abderrahmane; El Fazziki, Abdelaziz; Ouarzazi, Jamal; Sadgal, Mohamed

    2016-01-01

    This paper presents an integrated and adaptive problem-solving approach to control the on-road air quality by modeling the road infrastructure, managing traffic based on pollution level and generating recommendations for road users. The aim is to reduce vehicle emissions in the most polluted road segments and optimizing the pollution levels. For this we propose the use of historical and real time pollution records and contextual data to calculate the air quality index on road networks and generate recommendations for reassigning traffic flow in order to improve the on-road air quality. The resulting air quality indexes are used in the system's traffic network generation, which the cartography is represented by a weighted graph. The weights evolve according to the pollution indexes and path properties and the graph is therefore dynamic. Furthermore, the systems use the available pollution data and meteorological records in order to predict the on-road pollutant levels by using an artificial neural network based prediction model. The proposed approach combines the benefits of multi-agent systems, Big data technology, machine learning tools and the available data sources. For the shortest path searching in the road network, we use the Dijkstra algorithm over Hadoop MapReduce framework. The use Hadoop framework in the data retrieve and analysis process has significantly improved the performance of the proposed system. Also, the agent technology allowed proposing a suitable solution in terms of robustness and agility.

  12. Towards an agent based traffic regulation and recommendation system for the on-road air quality control.

    PubMed

    Sadiq, Abderrahmane; El Fazziki, Abdelaziz; Ouarzazi, Jamal; Sadgal, Mohamed

    2016-01-01

    This paper presents an integrated and adaptive problem-solving approach to control the on-road air quality by modeling the road infrastructure, managing traffic based on pollution level and generating recommendations for road users. The aim is to reduce vehicle emissions in the most polluted road segments and optimizing the pollution levels. For this we propose the use of historical and real time pollution records and contextual data to calculate the air quality index on road networks and generate recommendations for reassigning traffic flow in order to improve the on-road air quality. The resulting air quality indexes are used in the system's traffic network generation, which the cartography is represented by a weighted graph. The weights evolve according to the pollution indexes and path properties and the graph is therefore dynamic. Furthermore, the systems use the available pollution data and meteorological records in order to predict the on-road pollutant levels by using an artificial neural network based prediction model. The proposed approach combines the benefits of multi-agent systems, Big data technology, machine learning tools and the available data sources. For the shortest path searching in the road network, we use the Dijkstra algorithm over Hadoop MapReduce framework. The use Hadoop framework in the data retrieve and analysis process has significantly improved the performance of the proposed system. Also, the agent technology allowed proposing a suitable solution in terms of robustness and agility. PMID:27652177

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. Development and evaluation of the operational Air-Quality forecast model for Austria ALARO-CAMx

    NASA Astrophysics Data System (ADS)

    Flandorfer, Claudia; Hirtl, Marcus; Krüger, Bernd C.

    2014-05-01

    The Air-Quality model for Austria (AQA) is operated at ZAMG in cooperation with the University of Natural Resources and Life Sciences (BOKU) in Vienna by order of the regional governments since 2005. 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. Since 2013 O3- and PM10-observations from the Austrian measurement network have been assimilated daily using optimum interpolation. Dynamic chemical boundary conditions are obtained from Air-Quality forecasts provided by ECMWF in the frame of MACC-II. Additionally the latest available high resolved emission inventories for Austria are combined with TNO and EMEP data. The biogenic emissions are provided by the SMOKE model. ZAMG provides daily forecasts of O3, PM10 and NO2 to the regional governments of Austria. The evaluation of these forecasts is done for the summer 2013 with the main focus on the forecasts of ozone. The measurements of the Air-Quality stations are compared with the punctual forecasts at the sites of the station and with the area forecasts for every province of Austria. In the summer of 2013, two heat waves occurred. The first very short heat wave was in June 2013. During this period one exceedance of the alert threshold value for ozone occurred. The second heat wave took place from the end of July to the mid of August. Due to very high temperatures (new temperature record for Austria measured in Bad Deutsch-Altenburg with 40.5°C) and long dryness episodes the information threshold value has been exceeded several times in the eastern regions of Austria. The alert threshold value has been exceeded one time in this period. For the evaluation, the results for the second heat wave episode in Eastern Austria will be discussed

  18. MULTIPOLLUTANT MODEL FOR ESTIMATING THE IMPACT OF POLLUTANTS ON INDOOR AIR QUALITY

    EPA Science Inventory

    The paper discusses a multipollutant model for estimating the impact of pollutant on indoor air quality (IAQ). [NOTE: Most existing IAQ models are not well suited for analysis of the impacts of sources that emit several pollutants into the indoor environment. These models are als...

  19. 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.

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. 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 ...

  7. 40 CFR Appendix W to Part 51 - Guideline on Air Quality Models

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality models in response to regulatory requirements and the expanded requirements for models to cover....0Bibliography 12.0References Appendix A to Appendix W of 40 CFR Part 51—Summaries of Preferred Air Quality... assessing source impact and in evaluating control strategies. i. Appendix W to 40 CFR Part 51...

  8. 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...

  9. Meteorological analyses data set for air quality assessment modelling from national to local scale: verification and applications.

    NASA Astrophysics Data System (ADS)

    Finardi, S.; Pace, G.; Tinarelli, G.; Vitali, C.

    2009-09-01

    Since 2002, on behalf of the Italian Ministry of the Environment, ENEA has been leading a national Project, named MINNI (National Integrated Modelling system for International Negotiation), for the development of an Integrated Assessment Modelling system. The objective of the project is to support policy makers in the elaboration and assessment of air pollution policies at international, national and local level, by means of the more recent understandings of the atmospheric processes. The project activities include the realisation of air quality analysis and assessment at national and sub-national scale through model simulations with space resolution of 20x20 and 4x4 km2 and hourly time step on different target years. A Eulerian Atmospheric Modelling System (AMS), built around the chemical transport model FARM, has been applied to years 1999 and 2005 during the first phase of the project, while a second phase is presently ongoing and foresees simulations for years 2003 and 2007. The meteorological analyses used to drive the quality model have been produced by means of the meteorological models RAMS (http://atmet.com/) and LAPS (http://laps.noaa.gov/) using ECMWF synoptic analyses and surface observations as main input data. The meteorological data set is being used for MINNI project but also distributed to Regional Environmental Protection Agencies and other users to support air quality simulations at local scale employing different air quality model types. To verify the meteorological fields reliability and possibly define the usability limits of the dataset, model results have been compared with independent observations over different areas of the country (Friuli, Piedmont, Sardinia, Lazio and Puglia). The comparison confirmed that analysed meteorological fields can be considered representative over most part of the country, even if some critical areas emerged mainly due to the limited density of the input observations network and to the coarse resolution of

  10. 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...

  11. 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.

  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. 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.

  16. 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) ...

  17. 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.

  18. 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.

  19. 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.

  20. Air-quality data analysis system for interrelating effects, standards, and needed source reductions: Part 11. A lognormal model relating human lung function decrease to O3 exposure

    SciTech Connect

    Larsen, R.I.; McDonnell, W.F.; Horstman, D.H.; Folinsbee, L.J.

    1991-01-01

    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). A lognormal multiple linear regression model was fitted to their mean FEV1 measurements to predict FEV1 percent decrease as a function of O3 concentration and exposure duration. The exercise level used was probably comparable to heavy manual labor. The longest O3 exposure studied was 6 h. Extrapolating cautiously to an 8-h workday of heavy manual labor, the model predicts that O3 concentrations of 0.08, 0.10, and 0.12 ppm would decrease FEV1 by 9, 15, and 20 percent respectively.

  1. 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.

  2. 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.

  3. (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...

  4. 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,...

  5. 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…

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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

  11. 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...

  12. 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...

  13. 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...

  14. 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.

  15. 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.

  16. 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...

  17. 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

  18. 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.

  19. 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.

  20. 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...

  1. 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.

  2. A genetic-algorithm-aided stochastic optimization model for regional air quality management under uncertainty.

    PubMed

    Qin, Xiaosheng; Huang, Guohe; Liu, Lei

    2010-01-01

    A genetic-algorithm-aided stochastic optimization (GASO) model was developed in this study for supporting regional air quality management under uncertainty. The model incorporated genetic algorithm (GA) and Monte Carlo simulation techniques into a general stochastic chance-constrained programming (CCP) framework and allowed uncertainties in simulation and optimization model parameters to be considered explicitly in the design of least-cost strategies. GA was used to seek the optimal solution of the management model by progressively evaluating the performances of individual solutions. Monte Carlo simulation was used to check the feasibility of each solution. A management problem in terms of regional air pollution control was studied to demonstrate the applicability of the proposed method. Results of the case study indicated the proposed model could effectively communicate uncertainties into the optimization process and generate solutions that contained a spectrum of potential air pollutant treatment options with risk and cost information. Decision alternatives could be obtained by analyzing tradeoffs between the overall pollutant treatment cost and the system-failure risk due to inherent uncertainties.

  3. 40 CFR Appendix W to Part 51 - Guideline on Air Quality Models

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... and Deposition 7.2.8Complex Winds 7.2.9Calibration of Models 8.0Model Input Data 8.1Source Data 8.1....0Bibliography 12.0References Appendix A to Appendix W of 40 CFR Part 51—Summaries of Preferred Air Quality... Times for Site Specific Wind and Turbulence Measurements. 1.0 Introduction a. The Guideline...

  4. 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.

  5. 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.

  6. Emerging Approaches to the Integration of Autonomous Heterogeneous Air Quality Information Systems

    NASA Astrophysics Data System (ADS)

    Husar, R. B.; Scheffe, R.

    2006-12-01

    Data on atmospheric composition relevant to air quality are collected by numerous organizations through a variety of surface and based and remote sensors. The users of such data include managers, scientist and educators, also spread over the many organizations as they participate in broad programs and pursue specific projects. Emerging IS architectures, and technologies now offer the opportunity to augment the traditional end- to-end `stovepipe' information systems. Standards-based data access opens the data flow for networking and leads to reuse. Modularizing data processing components encourages broader participation and software reuse by lowering the entry threshold. The use of workflow software for the creation of applications tends to at `flatten' information systems by ignoring organizational boundaries. The full value of these emerging developments is hard to evaluate at this time but in principle they offer the possibilities for integrating future air quality information systems. Application examples and major impediments will be discussed.

  7. 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

  8. 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.

  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. 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.

  11. 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

  12. 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

  13. 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.

  14. Modelled air pollution levels versus EC air quality legislation - results from high resolution simulation.

    PubMed

    Chervenkov, Hristo

    2013-12-01

    An appropriate method for evaluating the air quality of a certain area is to contrast the actual air pollution levels to the critical ones, prescribed in the legislative standards. The application of numerical simulation models for assessing the real air quality status is allowed by the legislation of the European Community (EC). This approach is preferable, especially when the area of interest is relatively big and/or the network of measurement stations is sparse, and the available observational data are scarce, respectively. Such method is very efficient for similar assessment studies due to continuous spatio-temporal coverage of the obtained results. In the study the values of the concentration of the harmful substances sulphur dioxide, (SO2), nitrogen dioxide (NO2), particulate matter - coarse (PM10) and fine (PM2.5) fraction, ozone (O3), carbon monoxide (CO) and ammonia (NH3) in the surface layer obtained from modelling simulations with resolution 10 km on hourly bases are taken to calculate the necessary statistical quantities which are used for comparison with the corresponding critical levels, prescribed in the EC directives. For part of them (PM2.5, CO and NH3) this is done for first time with such resolution. The computational grid covers Bulgaria entirely and some surrounding territories and the calculations are made for every year in the period 1991-2000. The averaged over the whole time slice results can be treated as representative for the air quality situation of the last decade of the former century.

  15. 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

  16. 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.

  17. "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.

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-01-01

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

  1. 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.

  2. 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...

  3. 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...

  4. An air quality modeling study comparing two possible sites for the new international airport for Mexico City.

    PubMed

    Jazcilevich, Aron D; García, Agustín R; Ruiz-Suárez, L Gerardo; Cruz-Nuñez, Xóchitl; Delgado, Javier C; Tellez, Carlos; Chias, Luis B

    2003-03-01

    Using an air quality model, two future urban scenarios induced by the construction of the new international airport for Mexico City are compared at a regional level. The air quality model couples the meteorology model MM5 and state-of-the-art photochemistry. The air quality comparison is made using metrics for the criterion gases selected for the study. From the two urban scenarios compared, the option for Tizayuca is moderately better than the option for Texcoco, because relative reductions in O3 and other photochemical pollutants are achieved over highly populated areas. Regardless of the site, the air quality for the central region of Mexico in the future will deteriorate. In the region of central Mexico, SO2 and NO2 will become important pollutants.

  5. 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.

  6. 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

  7. 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

  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. 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.

  10. 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.

  11. 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.

  12. 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...

  13. 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.

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

    PubMed

    Wang, Y Jason; Zhang, K Max

    2009-10-15

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

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. 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

  1. Calculating Air Quality and Climate Co-Benefits Metrics from Adjoint Elasticities in Chemistry-Climate Models

    NASA Astrophysics Data System (ADS)

    Spak, S.; Henze, D. K.; Carmichael, G. R.

    2013-12-01

    The science and policy communities both need common metrics that clearly, comprehensively, and intuitively communicate the relative sensitivities of air quality and climate to emissions control strategies, include emissions and process uncertainties, and minimize the range of error that is transferred to the metric. This is particularly important because most emissions control policies impact multiple short-lived climate forcing agents, and non-linear climate and health responses in space and time limit the accuracy and policy value of simple emissions-based calculations. Here we describe and apply new second-order elasticity metrics to support the direct comparison of emissions control policies for air quality and health co-benefits analyses using adjoint chemical transport and chemistry-climate models. Borrowing an econometric concept, the simplest elasticities in the atmospheric system are the percentage changes in concentrations due to a percentage change in the emissions. We propose a second-order elasticity metric, the Emissions Reduction Efficiency, which supports comparison across compounds, to long-lived climate forcing agents like CO2, and to other air quality impacts, at any temporal or spatial scale. These adjoint-based metrics (1) possess a single uncertainty range; (2) allow for the inclusion of related health and other impacts effects within the same framework; (3) take advantage of adjoint and forward sensitivity models; and (4) are easily understood. Using global simulations with the adjoint of GEOS-Chem, we apply these metrics to identify spatial and sectoral variability in the climate and health co-benefits of sectoral emissions controls on black carbon, sulfur dioxide, and PM2.5. We find spatial gradients in optimal control strategies on every continent, along with differences among megacities.

  2. Development of an air quality model for fugitive dust from mining

    SciTech Connect

    Winges, K.D.

    1982-06-01

    This paper describes a new air quality model, the EMAQ model, and compares it with the standard ISC model. The performance of the EMAQ model is discussed and its accuracy is commented upon. It is not yet determined if the EMAQ model can accurately simulate fugitive dust and a thorough evaluation is yet to be made which would determine if it has the ability to simulate changing wind directions and wind speeds with downwind distance, the ability to simulate pit-retention, the effect of meteorology and other factors on the deposition parameters. The hope is that the tools presented here are a step in the right direction which will eventually lead to reliable fugitive dust impact prediction.

  3. 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

  4. A modelling study on the effects of air quality on cloud processes and precipitation

    NASA Astrophysics Data System (ADS)

    Solomos, Stavros; Kushta, Jonilda; Kallos, George

    2010-05-01

    Aerosol particles are well known climate and weather regulators since they alter the radiative properties of the atmosphere as well as the microphysical properties of clouds. In the Mediterranean area, desert dust, sea salt spray and particles of anthropogenic origin are the dominant components of the aerosol burden. The chemical composition of the aerosol particles is important for the nucleation of cloud droplets. This composition is determined from the corresponding mineralogy of their sources and their transportation pathways. Desert dust particles are usually slightly hygroscopic during the early steps after their mobilization. However, along their transportation paths, these particles may interact with other atmospheric components, thus producing sulfate or salt - coated dust particles which have been reported to be very effective cloud condensation nuclei (CCN). On the other hand, mineral dust particles are known to be effective ice nuclei (IN), thus contributing to the formation of high clouds. The newly developed Integrated Community Limited Area Modeling system (ICLAMS) is used to investigate the possible links and feedbacks between aerosol concentration, chemical composition and rain formation processes. The new model is developed on the well established Regional Atmospheric Modeling System (RAMS) which has been used in the field of cloud research for several years. ICLAMS includes also soil dust, sea salt, gas, aqueous and aerosol phase chemistry, radiative transfer scheme with aerosols effects on longwave and shortwave bands, prognostic ozone radiation feedbacks and explicit cloud droplets nucleation scheme based on meteorology and aerosol properties. Selected test cases are analyzed for the greater Mediterranean area and model results are compared to available observational data. Several scenarios for the type of aerosol are performed. The interaction between dust, sea salt and anthropogenic pollution may lead in the formation of mixed particles with

  5. 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...

  6. Development of a comprehensive air quality modeling framework for a coastal urban airshed in south Texas

    NASA Astrophysics Data System (ADS)

    Farooqui, Mohmmed Zuber

    Tropospheric ozone is one of the major air pollution problems affecting urban areas of United States as well as other countries in the world. Analysis of surface observed ozone levels in south and central Texas revealed several days exceeding 8-hour average ozone National Ambient of Air Quality Standards (NAAQS) over the past decade. Two major high ozone episodes were identified during September of 1999 and 2002. A photochemical modeling framework for the high ozone episodes in 1999 and 2002 were developed for the Corpus Christi urban airshed. The photochemical model was evaluated as per U.S. Environmental Protection Agency (EPA) recommended statistical methods and the models performed within the limits set by EPA. An emission impact assessment of various sources within the urban airshed was conducted using the modeling framework. It was noted that by nudging MM5 with surface observed meteorological parameters and sea-surface temperature, the coastal meteorological predictions improved. Consequently, refined meteorology helped the photochemical model to better predict peak ozone levels in urban airsheds along the coastal margins of Texas including in Corpus Christi. The emissions assessment analysis revealed that Austin and San Antonio areas were significantly affected by on-road mobile emissions from light-duty gasoline and heavy-duty diesel vehicles. The urban areas of San Antonio, Austin, and Victoria areas were estimated to be NOx sensitive. Victoria was heavily influenced by point sources in the region while Corpus Christi was influenced by both point and non-road mobile sources and was identified to be sensitive to VOC emissions. A rise in atmospheric temperature due to climate change potentially increase ozone exceedances and the peak ozone levels within the study region and this will be a major concern for air quality planners. This study noted that any future increase in ambient temperature would result in a significant increase in the urban and regional

  7. 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.

  8. A Detailed Process Based Evaluation of Photochemical Air Quality Model Simulations of Houston, TX

    NASA Astrophysics Data System (ADS)

    Vizuete, W.; Kioumourtzoglou, M.; Jeffries, H.

    2006-12-01

    This work will present a process based evaluation of several modeling attempts of the Houston, TX non- attainment area. These modeling attempts include efforts by the Texas state agency, private consultants, and several Universities, resulting in multiple simulations of the same modeling episode and domain. These simulations were performed with the Comprehensive Air quality Model with extensions (CAMx) under a variety of meteorological and emission inputs. Through an initial comparison of model and ambient data the model underpredicts ozone concentrations in nearly every modeling attempt. This observation held true even when a large artificial imputation of ozone precursors, specifically ethylene and propylene, were added to some modeling simulations. An examination of the level of agreement between model predictions and observations of ozone concentrations, however, is not a sufficient method to understand the reasons for this inaccuracy. This is especially true in a non-linear feedback system such as ozone formation where the same ozone prediction can be reached through the combination of various physical and chemical processess. A more meaningful method of model analysis that focuses on theses processes lead to the development of the pyPA (Process Analysis in python) tool. This tool provides a framework for an in-depth analysis of modeling data by quantifying radical budgets, source and fate of ozone precursors, and the physical processes that effect each species. The pyPA tool was used to analyze each simulation scenario of the Houston airshed allowing for a process based intercomparison. An analysis of the radical budget revealed a deficient source of organically derived free radicals (HO2 and OH.) in the modeling system. Atmospheric reactivity and consequently ozone formation was limited by lack of radical sources; regardless of the levels of ethylene or propylene introduced into the system. NOx overpredictions by a factor of two further depleted the limited

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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.

  15. 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

  16. Web Information Systems for Monitoring and Control of Indoor Air Quality at Subway Stations

    NASA Astrophysics Data System (ADS)

    Choi, Gi Heung; Choi, Gi Sang; Jang, Joo Hyoung

    In crowded subway stations indoor air quality (IAQ) is a key factor for ensuring the safety, health and comfort of passengers. In this study, a framework for web-based information system in VDN environment for monitoring and control of IAQ in subway stations is suggested. Since physical variables that describing IAQ need to be closely monitored and controlled in multiple locations in subway stations, concept of distributed monitoring and control network using wireless media needs to be implemented. Connecting remote wireless sensor network and device (LonWorks) networks to the IP network based on the concept of VDN can provide a powerful, integrated, distributed monitoring and control performance, making a web-based information system possible.

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. 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

  5. Quantification of non-linearities as a function of time averaging in regional air quality modeling applications

    NASA Astrophysics Data System (ADS)

    Thunis, P.; Clappier, A.; Pisoni, E.; Degraeuwe, B.

    2015-02-01

    Air quality models which are nowadays used for a wide range of scopes (i.e. assessment, forecast, planning) see their intrinsic complexity progressively increasing as better knowledge of the atmospheric chemistry processes is gained. As a result of this increased complexity potential non-linearities are implicitly and/or explicitly incorporated in the system. These non-linearities represent a key and challenging aspect of air quality modeling, especially to assess the robustness of the model responses. In this work the importance of non-linear effects in air quality modeling is quantified, especially as a function of time averaging. A methodology is proposed to decompose the concentration change resulting from an emission reduction over a given domain into its linear and non-linear contributions for each precursor as well as in the contribution resulting from the interactions among precursors. Simulations with the LOTOS-EUROS model have been performed by TNO over three regional geographical areas in Europe for this analysis. In all three regions the non-linear effects for PM10 and PM2.5 are shown to be relatively minor for yearly and monthly averages whereas they become significant for daily average values. For Ozone non-linearities become important already for monthly averages in some regions. An approach which explicitly deals with monthly variations seems therefore more appropriate for O3. In general non-linearities are more important at locations where concentrations are the lowest, i.e. at urban locations for O3 and at rural locations for PM10 and PM2.5. Finally the impact of spatial resolution (tested by comparing coarse and fine resolution simulations) on the degree of non-linearity has been shown to be minor as well. The conclusions developed here are model dependent and runs should be repeated with the particular model of interest but the proposed methodology allows with a limited number of runs to identify where efforts should be focused in order to

  6. 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.

  7. [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

  8. 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.

  9. 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 ...

  10. 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...

  11. Regional Modelling of Air Quality in the Canadian Arctic: Impact of marine shipping and North American wild fire emissions

    NASA Astrophysics Data System (ADS)

    Gong, W.; Beagley, S. R.; Zhang, J.; Cousineau, S.; Sassi, M.; Munoz-Alpizar, R.; Racine, J.; Menard, S.; Chen, J.

    2015-12-01

    Arctic atmospheric composition is strongly influenced by long-range transport from mid-latitudes as well as processes occurring in the Arctic locally. Using an on-line air quality prediction model GEM-MACH, simulations were carried out for the 2010 northern shipping season (April - October) over a regional Arctic domain. North American wildfire emissions and Arctic shipping emissions were represented, along with other anthropogenic and biogenic emissions. Sensitivity studies were carried out to investigate the principal sources and processes affecting air quality in the Canadian Northern and Arctic regions. In this paper, we present an analysis of sources, transport, and removal processes on the ambient concentrations and atmospheric loading of various pollutants with air quality and climate implications, such as, O3, NOx, SO2, CO, and aerosols (sulfate, black carbon, and organic carbon components). Preliminary results from a model simulation of a recent summertime Arctic field campaign will also be presented.

  12. Evaluation of European air quality modelled by CAMx including the volatility basis set scheme

    NASA Astrophysics Data System (ADS)

    Ciarelli, Giancarlo; Aksoyoglu, Sebnem; Crippa, Monica; Jimenez, Jose-Luis; Nemitz, Eriko; Sellegri, Karine; Äijälä, Mikko; Carbone, Samara; Mohr, Claudia; O'Dowd, Colin; Poulain, Laurent; Baltensperger, Urs; Prévôt, André S. H.

    2016-08-01

    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 aerosol (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 (8.9 pbb and 12.3 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 for all the four periods with average biases ranging from -2.1 to 1.0 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 overpredicts the inorganic aerosol fraction and underpredicts the organic one, such that the good agreement for PM2.5 is partly due to compensation of errors. The effect of the choice of VBS scheme 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 42 % on average. In contrast, a test based on ambient measurement data increased OA concentrations by about 42 % for the same period bringing model and observations into better agreement

  13. 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…

  14. 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.

  15. 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

  16. Evaluation of regional air quality models in the presence of moderate to strong aerosol events

    NASA Astrophysics Data System (ADS)

    O'Neill, N. T.; Thulasiraman, S.; Pancrati, O.; Aube, M.; Lupu, A.; Neary, L.; Strawbridge, K.; Freemantle, J.; Kaminski, J.; McConnell, J.

    2006-12-01

    During the 2004 to 2006 period a program of synchronized sunphotometry and lidar backscatter measurements were carried out at Egbert, Ontario (70 km north of Toronto). A variety of events, ranging from moderate to strong pollution events, long and short distance smoke transport, long distance dust transport and the presence of thin homogeneous clouds were registered and optically analyzed. These data were employed to help evaluate the performance of the Canadian GEM-AQ air quality model as well an aerosol optical assimilation model (NOMAD). The evaluations were based on optical indicators of integrated aerosol content (aerosol optical depth), particle size indicators such as Angstrom exponent, and vertical profiles of the aerosol backscatter ratio. Some preliminary analyses will be presented; the focus will be on the problems associated with emissions modelling, the influence of cloud screening algorithms in the data and in the model, the robustness of particle size information in the passive optical data and the ability of the models to capture subtle variations, and the vertical performance of the models relative to the lidar backscatter data.

  17. 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.

  18. 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...

  19. 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...

  20. 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 ...

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Technical and Non-Technical Measures for air pollution emission reduction: The integrated assessment of the regional Air Quality Management Plans through the Italian national model

    NASA Astrophysics Data System (ADS)

    D'Elia, I.; Bencardino, M.; Ciancarella, L.; Contaldi, M.; Vialetto, G.

    2009-12-01

    The Italian Air Quality legislation underwent sweeping changes with the implementation of the 1996 European Air Quality Framework Directive when the Italian administrative Regions were entrusted with air quality management tasks. The most recent Regional Air Quality Management Plans (AQMPs) highlighted the importance of Non-Technical Measures (NTMs), in addition to Technical Measures (TMs), in meeting environmental targets. The aim of the present work is to compile a list of all the TMs and NTMs taken into account in the Italian Regional AQMPs and to give in the target year, 2010, an estimation of SO 2, NO x and PM 10 emission reductions, of PM 10 concentration and of the health impact of PM 2.5 concentrations in terms of Life Expectancy Reduction. In order to do that, RAINS-Italy, as part of the National Integrated Modeling system for International Negotiation on atmospheric pollution (MINNI), has been applied. The management of TMs and NTMs inside RAINS have often obliged both the introduction of exogenous driving force scenarios and the control strategy modification. This has inspired a revision of the many NTM definitions and a clear choice of the definition adopted. It was finally highlighted that only few TMs and NTMs implemented in the AQMPs represent effective measures in reaching the environmental targets.

  10. 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.

  11. 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...

  12. 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

  13. 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

  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.

  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. 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

  17. An intercomparison of several diagnostic meteorological processors used in mesoscale air quality modeling

    SciTech Connect

    Vimont, J.C.; Scire, J.S.

    1994-12-31

    A major component, and area of uncertainty, in mesoscale air quality modeling, is the specification of the meteorological fields which affect the transport and dispersion of pollutants. Various options are available for estimating the wind and mixing depth fields over a mesoscale domain. Estimates of the wind field can be obtained from spatial and temporal interpolation of available observations or from diagnostic meteorological models, which estimate a meteorological field from available data and adjust those fields based on parameterizations of physical processes. A major weakness of these processors is their dependence on spatially and temporally sparse input data, particularly upper air data. These problems are exacerbated in regions of complex terrain and along the shorelines of large bodies of water. Similarly, the estimation of mixing depth is also reliant upon sparse observations and the parameterization of the convective and mechanical processes. The meteorological processors examined in this analysis were developed to drive different Lagrangian puff models. This paper describes the algorithms these processors use to estimate the wind fields and mixing depth fields.

  18. 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

  19. Assessment of microbiological indoor air quality in an Italian office building equipped with an HVAC system.

    PubMed

    Bonetta, Sa; Bonetta, Si; Mosso, S; Sampò, S; Carraro, E

    2010-02-01

    The purpose of this study was to evaluate the level and composition of bacteria and fungi in the indoor air of an Italian office building equipped with a heating, ventilation and air conditioning (HVAC) system. Airborne bacteria and fungi were collected in three open-space offices during different seasons. The microbial levels in the outdoor air, supply air diffusers, fan coil air flow and air treatment unit humidification water tank were used to evaluate the influence of the HVAC system on indoor air quality (IAQ). A medium-low level of bacterial contamination (50-500 CFU/m(3)) was found in indoor air. Staphylococcus and Micrococcus were the most commonly found genera, probably due to human presence. A high fungal concentration was measured due to a flood that occurred during the winter. The indoor seasonal distribution of fungal genera was related to the fungal outdoor distribution. Significant seasonal and daily variation in airborne microorganisms was found, underlining a relationship with the frequency of HVAC system switching on/off. The results of this monitoring highlight the role of the HVAC system on IAQ and could be useful to better characterise bacterial and fungal population in the indoor air of office buildings.

  20. 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.

  1. 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.

  2. 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...

  3. 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...

  4. 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.

  5. Comparison of Lagrangian Process Analysis tools for Eulerian air quality models

    NASA Astrophysics Data System (ADS)

    Henderson, Barron H.; Kimura, Yosuke; McDonald-Buller, Elena; Allen, David T.; Vizuete, William

    2011-09-01

    Air quality models (AQM) are used to understand the complex relationships between sources of air pollutants and ambient concentrations. Two new AQM diagnostic tools, the Lagrangian Process Analysis (LPA) tool and the Python-based Process Analysis (pyPA), have recently been created that allow users to track a plume within the AQM, and then calculate the chemical and physical process rates that occur within it. These two new process analysis tools perform their functions differently. The LPA in-model algorithm operates at the computational timestep of the AQM, and pyPA is a post-processor tool dependent on the temporal resolution of the AQM output, typically 1 h. This work compares process rates calculated by these tools, using as a case study the simulation of a rapidly evolving plume that resulted from an industrial hydrocarbon release. Releases from industrial sources are of regulatory significance in Houston and their accurate simulation of great importance. Results show that the largest differences in the outputs of the tools occur early in the life of the plume when it is rapidly expanding. During this time, the plume encounters NO x sources that significantly impact chemical and physical process rates that are not seen in the pyPA post-processing of hourly AQM output.

  6. 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.

  7. 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…

  8. Application of model output statistics to the GEM-AQ high resolution air quality forecast

    NASA Astrophysics Data System (ADS)

    Struzewska, J.; Kaminski, J. W.; Jefimow, M.

    2016-11-01

    The aim of the presented work was to analyse the impact of data stratification on the efficiency of the Model Output Statistics (MOS) methodology as applied to a high-resolution deterministic air quality forecast carried out with the GEM-AQ model. The following parameters forecasted by the GEM-AQ model were selected as predictors for the MOS equation: pollutant concentration, air temperature in the lowest model layer, wind speed in the lowest model layer, temperature inversion and the precipitation rate. A representative 2-year series were used to construct regression functions. Data series were divided into two subsets. Approximately 75% of the data (first 3 weeks of each month) were used to estimate the regression function parameters. Remaining 25% (last week of each month) were used to test the method (control period). The subsequent 12 months were used for method verification (verification period). A linear model fitted the function based on forecasted parameters to the observations. We have assumed four different temperature-based data stratification methods (for each method, separate equations were constructed). For PM10 and PM2.5, SO2 and NO2 the best correction results were obtained with the application of temperature thresholds in the cold season and seasonal distribution combined with temperature thresholds in the warm season. For the PM10, PM2.5 and SO2 the best results were obtained using a combination of two stratification methods separately for cold and warm seasons. For CO, the systematic bias of the forecasted concentrations was partly corrected. For ozone more sophisticated methods of data stratification did not bring a significant improvement.

  9. 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...

  10. 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...

  11. 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.

  12. 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

  13. Climate-forced air-quality modeling at the urban scale: sensitivity to model resolution, emissions and meteorology

    NASA Astrophysics Data System (ADS)

    Markakis, K.; Valari, M.; Perrussel, O.; Sanchez, O.; Honore, C.

    2015-07-01

    While previous research helped to identify and prioritize the sources of error in air-quality modeling due to anthropogenic emissions and spatial scale effects, our knowledge is limited on how these uncertainties affect climate-forced air-quality assessments. Using as reference a 10-year model simulation over the greater Paris (France) area at 4 km resolution and anthropogenic emissions from a 1 km resolution bottom-up inventory, through several tests we estimate the sensitivity of modeled ozone and PM2.5 concentrations to different potentially influential factors with a particular interest over the urban areas. These factors include the model horizontal and vertical resolution, the meteorological input from a climate model and its resolution, the use of a top-down emission inventory, the resolution of the emissions input and the post-processing coefficients used to derive the temporal, vertical and chemical split of emissions. We show that urban ozone displays moderate sensitivity to the resolution of emissions (~ 8 %), the post-processing method (6.5 %) and the horizontal resolution of the air-quality model (~ 5 %), while annual PM2.5 levels are particularly sensitive to changes in their primary emissions (~ 32 %) and the resolution of the emission inventory (~ 24 %). The air-quality model horizontal and vertical resolution have little effect on model predictions for the specific study domain. In the case of modeled ozone concentrations, the implementation of refined input data results in a consistent decrease (from 2.5 up to 8.3 %), mainly due to inhibition of the titration rate by nitrogen oxides. Such consistency is not observed for PM2.5. In contrast this consistency is not observed for PM2.5. In addition we use the results of these sensitivities to explain and quantify the discrepancy between a coarse (~ 50 km) and a fine (4 km) resolution simulation over the urban area. We show that the ozone bias of the coarse run (+9 ppb) is reduced by ~ 40 % by adopting

  14. Assessing the Influence of Western Boundary Ozone Inflow for the Pacific Northwest Using the AIRPACT-4 Air-Quality Forecast System

    NASA Astrophysics Data System (ADS)

    Vaughan, J. K.; Chung, S. H.; Herron-Thorpe, F. L.; Lamb, B. K.; Zhang, R.; Mount, G. H.; Emmons, L. K.

    2013-12-01

    The AIRPACT project has provided state, local and tribal air quality managers in the Pacific and Inland Northwest with state-of-the-art near-real time air quality forecasts, beginning in 2001 (Vaughan et al., 2004). Air-quality modeling is also an important tool for evaluating strategies for complying with the NAAQS, especially as the ozone standard is likely to be tightened from 75 ppb to 60 - 70 ppb. For the Pacific Northwest a perennial issue is the significance of trans-boundary transport effects on air quality. Under the EPA Exceptional Events Policy, for example, a nominal exceedance can be excluded from design value calculation if it can be credibly ascribed to long-range transport (LRT); air-quality modeling is an accepted tool for making a case that LRT contributes to an exceedance, and thus qualifies as an Exceptional Event. Also, evidence is accumulating that local air pollution should sometimes be viewed in the context of baseline pollution levels, and that these baseline levels are influenced by LRT (Wigder et al., 2013). AIRPACT4, a WRF-SMOKE-CMAQ air quality modeling system, uses chemical boundary conditions from global MOZART4 model runs that assimilate MOPITT/TERRA satellite CO (Herron-Thorpe et al., 2012). Here we use a non-reactive tracer species version of CMAQv4.7.1 to develop a chemical climatology describing trans-boundary ozone contributions (across the western boundary only) to the ozone background of the Pacific Northwest, including ozone input to the domain from trans-Pacific transport originating in Asia. Discrete tracers are assigned to the boundary condition ozone from each of the 21 model layers. The modeling results are analyzed for ozone-season months to determine: 1) monthly statistics on the ratio of trans-boundary tracer ozone to standard AIRPACT4 ground level ozone, and 2) the contribution of trans-boundary tracer ozone to episodes of high ozone concentration. Preliminary results will be presented along with discussion of

  15. Modeling the impacts of biomass burning on air quality in and around Mexico City

    NASA Astrophysics Data System (ADS)

    Lei, W.; Li, G.; Molina, L.

    2012-09-01

    The local and regional impacts of open fires and trash burning on ground-level ozone (O3) and fine carbonaceous aerosols in the Mexico City Metropolitan Area (MCMA) and surrounding region during two high fire periods in March 2006 have been evaluated using WRF-CHEM model. The model captured reasonably well the measurement-derived magnitude and temporal variation of the biomass burning organic aerosol (BBOA), and the simulated impacts of open fires on organic aerosol (OA) were consistent with many observation-based estimates. We did not detect significant effects of open fires and trash burning on surface O3 concentrations in the MCMA and surrounding region. In contrast, they had important influences on OA and elemental carbon (EC), contributing about 60, 22, 33, and 22% to primary OA (POA), secondary OA (SOA), total OA (TOA), and EC, respectively, on both the local and regional scales. Although the emissions of trash burning are substantially lower than those from open fires, trash burning made slightly smaller but comparable contributions to OA as open fires did, and exerted an even higher influence on EC. SOA formation due to the open fires and trash burning enhanced the OA concentration by about 10 and 5% in the MCMA, respectively. On the annual basis and taking the biofuel use emissions into consideration, we estimated that biomass burning contributed about 60, 30, and 25%, respectively, to the loadings of POA, SOA and EC in both the MCMA and its surrounding region, with about 35, 18, and 15% from open fires and trash burning. The estimates of biomass burning impacts in this study may contain considerable uncertainties due to the uncertainties in their emission estimates, extrapolations and the nature of spot comparison. More observation and modeling studies are needed to accurately assess the impacts of biomass burning on tropospheric chemistry, regional and global air quality, and climate change.

  16. Engineering Strategies and Methods for Avoiding Air-Quality Externalities: Dispersion Modeling, Home Energy Conservation, and Scenario Planning

    NASA Astrophysics Data System (ADS)

    Knox, Andrew James

    Energy conservation can improve air quality by reducing emissions from fuel combustion. The human health value retained through better air quality can then offset the cost of energy conservation. Through this thesis' innovative yet widely-accessible combination of air pollution dispersion modeling and atmospheric chemistry, it is estimated that the health value retained by avoiding emissions from Ontario's former coal-fired generating stations is 5.74/MWh (using an upper-bound value of 265,000 per year of life lost). This value is combined with energy modeling of homes in the first-ever assessment of the air-quality health benefits of low-energy buildings. It is shown that avoided health damages can equal 7% of additional construction costs of energy efficient buildings in Ontario. At 7%, health savings are a significant item in the cost analysis of efficient buildings. Looking to energy efficiency in the context of likely future low-resource natural gas scenarios, building efficient buildings today is shown to be more economically efficient than any building retrofit option. Considering future natural gas scarcity in the context of Ontario's Long-Term Energy Plan reveals that Ontario may be forced to return to coal-fired electricity. Projected coal use would result in externalities greater than $600 million/year; 80% more than air-quality externalities from Ontario's electricity in 1985. Radically aggressive investment in electricity conservation (75% reduction per capita by 2075) is one promising path forward that keeps air-quality externalities below 1985 levels. Non-health externalities are an additional concern, the quantification, and ultimately monetization, of which could be practical using emerging air pollution monitoring technologies. Energy, conservation, energy planning, and energy's externalities form a complex situation in which today's decisions are critical to a successful future. It is clear that reducing the demand for energy is essential and

  17. Application of Kolomogorov-Zurbenko Filter and the decoupled direct 3D method for the dynamic evaluation of a regional air quality model

    EPA Science Inventory

    Regional air quality models are being used in a policy-setting to estimate the response of air pollutant concentrations to changes in emissions and meteorology. Dynamic evaluation entails examination of a retrospective case(s) to assess whether an air quality model has properly p...

  18. MODELING ASSESSMENT OF THE IMPACT OF NITROGEN OXIDES EMISSION REDUCTIONS ON OZONE AIR QUALITY IN THE EASTERN UNITED STATES: OFFSETTING INCREASES IN ENERGY USE

    EPA Science Inventory

    The objective of this study is to examine changes in ambient ozone concentrations estimated by a photochemical air quality model in response to the NOx emission reductions imposed on the utility sector. To accomplish this task, CMAQ air quality model simulations were performe...

  19. Energy and air quality

    NASA Astrophysics Data System (ADS)

    Orgill, M. M.; Thorp, J. M.

    Many coal, oil shale, and geothermal energy sources are located in areas where atmospheric transport and dispersion processes are dominated by the complexity of the terrain. The U.S. Department of Energy (DOE), responsible for developing new energy technologies that meet air-quality regulations, developed a program aimed specifically at Atmospheric Studies in Complex Terrain (ASCOT) in 1978. The program uses theoretical atmospheric physics research, mathematical models, field experiments, and physical models. The goal is to develop a modeling and measurement methodology to (1) improve fundamental knowledge of transport and dispersion processes in complex terrain and (2) build on this improvement to provide a methodology for performing air quality assessments. The ASCOT team, managed by Marvin Dickerson and Paul Gudiksen of Lawrence Livermore Laboratory, Livermore, Calif., is composed of scientists from DOE supported research laboratories and university programs.

  20. Urban airshed modeling of air quality impacts of alternative transportation fuel use in Los Angeles and Atlanta

    SciTech Connect

    1997-12-01

    The main objective of NREL in supporting this study is to determine the relative air quality impact of the use of compressed natural gas (CNG) as an alternative transportation fuel when compared to low Reid vapor pressure (RVP) gasoline and reformulated gasoline (RFG). A table lists the criteria, air toxic, and greenhouse gas pollutants for which emissions were estimated for the alternative fuel scenarios. Air quality impacts were then estimated by performing photochemical modeling of the alternative fuel scenarios using the Urban Airshed Model Version 6.21 and the Carbon Bond Mechanism Version IV (CBM-IV) (Geary et al., 1988) Using this model, the authors examined the formation and transport of ozone under alternative fuel strategies for motor vehicle transportation sources for the year 2007. Photochemical modeling was performed for modeling domains in Los Angeles, California, and Atlanta, Georgia.

  1. Impact of aviation emissions on UTLS and air quality in current and future climate - GEM-AC model simulations

    NASA Astrophysics Data System (ADS)

    Kaminski, J. W.

    2015-12-01

    The objective of this study is to investigate the potential impacts of aviation emissions on the upper troposphere and lower stratosphere (UTLS) and surface air quality. The tool that was used in our study is the GEM-AC (Global Environmental Multiscale with Atmospheric Chemistry) chemical weather model where air quality, free tropospheric and stratospheric chemistry processes are on-line and interactive in a weather forecast model of Environment Canada. In vertical, the model domain is defined on 70 hybrid levels from the surface to ~60km. The gas-phase chemistry includes a comprehensive set of reactions for Ox, NOx, HOx, CO, CH4, NMVOCs, halocarbons, ClOx and BrO. Also, the model can address aerosol microphysics and gas-aerosol partitioning. Aircraft emissions are provided by the AEDT 2006 database developed by the Federal Aviation Administration. Results from model simulations on a global variable grid with 1 degree uniform resolution in the northern hemisphere will be presented.

  2. Modeling the Complex Photochemistry of Biomass Burning Plumes in Plume-Scale, Regional, and Global Air Quality Models

    NASA Astrophysics Data System (ADS)

    Alvarado, M. J.; Lonsdale, C. R.; Yokelson, R. J.; Travis, K.; Fischer, E. V.; Lin, J. C.

    2014-12-01

    Forecasting the impacts of biomass burning (BB) plumes on air quality is difficult due to the complex photochemistry that takes place in the concentrated young BB plumes. The spatial grid of global and regional scale Eulerian models is generally too large to resolve BB photochemistry, which can lead to errors in predicting the formation of secondary organic aerosol (SOA) and O3, as well as the partitioning of NOyspecies. AER's Aerosol Simulation Program (ASP v2.1) can be used within plume-scale Lagrangian models to simulate this complex photochemistry. We will present results of validation studies of the ASP model against aircraft observations of young BB smoke plumes. We will also present initial results from the coupling of ASP v2.1 into the Lagrangian particle dispersion model STILT-Chem in order to better examine the interactions between BB plume chemistry and dispersion. In addition, we have used ASP to develop a sub-grid scale parameterization of the near-source chemistry of BB plumes for use in regional and global air quality models. The parameterization takes inputs from the host model, such as solar zenith angle, temperature, and fire fuel type, and calculates enhancement ratios of O3, NOx, PAN, aerosol nitrate, and other NOy species, as well as organic aerosol (OA). We will present results from the ASP-based BB parameterization as well as its implementation into the global atmospheric composition model GEOS-Chem for the SEAC4RS campaign.

  3. Model study of the ship emissions impact on the air quality in the Adriatic/Ionian area

    NASA Astrophysics Data System (ADS)

    Karagiannidis, Athanasios; Poupkou, Anastasia; Liora, Natalia; Dimopoulos, Spiros; Giannaros, Christos; Melas, Dimitrios; Argiriou, Athanassios

    2015-04-01

    The increase of the ship traffic for touristic and commercial purposes is one of the EU Blue Growth targets. The Adriatic/Ionian is one of the sea-basin strategic areas for this target. The purpose of the study is the examination of the impact of the ship emissions on the gaseous and particulate pollutants concentrations in the Adriatic/Ionian area for which the current scientific knowledge is limited. The impact is simulated over a domain covering the Central and Eastern Mediterranean in 10 km resolution during a summer period (July) and a winter period (January) of the year 2012. The modeling system used consists of the photochemical model CAMx off line coupled with the meteorological model WRF. The zero-out modeling method is implemented involving CAMx simulations performed while including and omitting the ship emission data. The simulations are based on the European scale anthropogenic emission inventory of The Netherlands Organisation (TNO) for the reference year 2009. Natural emissions (NMVOCs from the vegetation, sea salt, wind-blown dust), estimated with the use of the Natural Emission MOdel (NEMO) developed by the Aristotle University of Thessaloniki, are accounted for in the photochemical model runs. The spatial distribution of the resulting differences in the gaseous and particulate pollutant concentration fields for both emission scenarios are presented and discussed, providing an estimation of the contribution of ship emissions on the determination of the air quality in the Adriatic/Ionian countries

  4. Synergy between Emissions Verification for Climate and Air Quality: Results from Modeling Analysis over the Contiguous US using CMAQ

    NASA Astrophysics Data System (ADS)

    Liu, Z.; Bambha, R.; Pinto, J. P.; Zeng, T.; Michelsen, H. A.

    2013-12-01

    The synergy between emissions-verification exercises for fossil-fuel CO2 and traditional air pollutants (TAPs, e.g., NOx, SO2, CO, and PM) stems from the common physical processes underlying the generation, transport, and perturbations of their emissions. Better understanding and characterizing such a synergetic relationship are of great interest and benefit for science and policy. To this end, we have been developing a modeling framework that allows for studying CO2 along with TAPs on regional-through-urban scales. The framework is based on the EPA Community Multi-Scale Air Quality (CMAQ) modeling system and has been implemented on a domain over the contiguous US, where abundant observational data and complete emissions information is available. In this presentation, we will show results from a comprehensive analysis of atmospheric CO2 and an array of TAPs observed from multiple networks and platforms (in situ and satellite observations) and those simulated by CMAQ over the contiguous US for a full year of 2007. We will first present the model configurations and input data used for CMAQ CO2 simulations and the results from model evaluations [1]. In light of the unique properties of CO2 compared to TAPs, we tested the sensitivity of model-simulated CO2 to different initial and boundary conditions, biosphere-atmosphere bidirectional fluxes and fossil-fuel emissions. We then examined the variability of CO2 and TAPs simulated by CMAQ and observed from the NOAA ESRL tall-tower network, the EPA AQS network, and satellites (e.g., SCIAMACHY and OMI) at various spatial and temporal scales. Finally, we diagnosed in CMAQ the roles of fluxes and transport in regulating the covariance between CO2 and TAPs manifested in both surface concentrations and column-integrated densities. We will discuss the implications from these results on how to understand trends and characteristics fossil-fuel emissions by exploiting and combining currently available observational and modeling

  5. 40 CFR Appendix W to Part 51 - Guideline on Air Quality Models

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ....0Bibliography 12.0References Appendix A to Appendix W of 40 CFR Part 51—Summaries of Preferred Air Quality... assessing source impact and in evaluating control strategies. i. Appendix W to 40 CFR Part 51 itself... to Appendix A to Appendix W to 40 CFR Part 51. Appendix A contains summaries of refined air...

  6. 40 CFR Appendix W to Part 51 - Guideline on Air Quality Models

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ....0Bibliography 12.0References Appendix A to Appendix W of 40 CFR Part 51—Summaries of Preferred Air Quality... assessing source impact and in evaluating control strategies. i. Appendix W to 40 CFR Part 51 itself... to Appendix A to Appendix W to 40 CFR Part 51. Appendix A contains summaries of refined air...

  7. USING MM5V3 WITH ETA ANALYSES FOR AIR-QUALITY MODELING AT THE EPA

    EPA Science Inventory

    Efforts have been underway since MM5v3 was released in July 1999 to set up air-quality simulations using Eta analyses as background fields. Our previous simulations used a one-way quadruple-nested set of domains with horizontal grid spacing of 108, 36, 12 and 4 km. With Eta a...

  8. 40 CFR Appendix W to Part 51 - Guideline on Air Quality Models

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ....0Bibliography 12.0References Appendix A to Appendix W of 40 CFR Part 51—Summaries of Preferred Air Quality... assessing source impact and in evaluating control strategies. i. Appendix W to 40 CFR Part 51 itself... to Appendix A to Appendix W to 40 CFR Part 51. Appendix A contains summaries of refined air...

  9. MELSAR: a mesoscale air quality model for complex terrain. Volume 1. Overview, technical description and user's guide

    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) program 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. Volume 1 contains the model overview, technical description, and user's guide, and Volume 2 contains the Appendices which include listings of the FORTRAN code. 51 refs., 31 figs., 35 tabs.

  10. Improving the Representation of Near Source and Downwind Smoke Plume Chemistry in Regional and Global Air Quality Models

    NASA Astrophysics Data System (ADS)

    Alvarado, M. J.; Lonsdale, C. R.; Yokelson, R. J.; Travis, K.; Lin, J. C.; McNeill, V. F.; Blake, D. R.; Griffith, D. W. T.; Johnson, T. J.; Kreidenweis, S. M.; Lee, T.; May, A.; McMeeking, G. R.; Meinardi, S.; Simpson, I. J.; Sullivan, A.; Urbanski, S. P.; Weise, D.

    2015-12-01

    The complex photochemistry within a biomass burning smoke plume can cause large changes in the concentration, size distribution, composition, and optical properties of the fine particles (PM2.5) emitted by the fires, as well as significant formation of ozone (O3) and organic nitrate species like peroxyacetyl nitrate (PAN). The Aerosol Simulation Program (ASP) is designed to simulate this chemical evolution of biomass burning plumes under a wide variety of conditions, and can be used to parameterize this chemistry in regional and global air quality models. Here we present ASP simulations of the evolution of biomass burning aerosol from South Carolina prescribed fires in October and November of 2011. This data set contains more detailed measurements of the non-methane organic compounds (NMOCs) in the smoke than the data sets previously used to develop and test ASP, allowing for a more detailed evaluation of the model's gas- and particle-phase chemistry. We also assess the potential impact of secondary organic aerosol (SOA) from glyoxal and isoprene epoxydiols (IEPOX) on the growth of biomass burning aerosols by incorporating the simpleGAMMA (Gas-Aerosol Model for Mechanism Analysis) model into ASP. Finally, we will discuss our efforts to use the ASP model to build a sub-grid scale parameterization of the near-source chemistry of biomass burning plumes for use in regional and global air quality models, using examples from the global chemical transport model GEOS-Chem and the stochastic Lagrangian air quality model STILT-Chem.

  11. Project ATLANTA (Atlanta Land use Analysis: Temperature and Air Quality): Use of Remote Sensing and Modeling to Analyze How Urban Land Use Change Affects Meteorology and Air Quality Through Time

    NASA Technical Reports Server (NTRS)

    Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G., Jr.

    1999-01-01

    This paper presents an overview of Project ATLANTA (ATlanta Land use ANalysis: Temperature and Air-quality) which is an investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta, Georgia metropolitan area since the early 1970's has impacted the region's climate and air quality. The primary objectives for this research effort are: (1) To investigate and model the relationships between land cover change in the Atlanta metropolitan, and the development of the urban heat island phenomenon through time; (2) To investigate and model the temporal relationships between Atlanta urban growth and land cover change on air quality; and (3) To model the overall effects of urban development on surface energy budget characteristics across the Atlanta urban landscape through time. Our key goal is to derive a better scientific understanding of how land cover changes associated with urbanization in the Atlanta area, principally in transforming forest lands to urban land covers through time, has, and will, effect local and regional climate, surface energy flux, and air quality characteristics. Allied with this goal is the prospect that the results from this research can be applied by urban planners, environmental managers and other decision-makers, for determining how urbanization has impacted the climate and overall environment of the Atlanta area. Multiscaled remote sensing data, particularly high resolution thermal infrared data, are integral to this study for the analysis of thermal energy fluxes across the Atlanta urban landscape.

  12. Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model

    NASA Astrophysics Data System (ADS)

    Jathar, S. H.; Cappa, C. D.; Wexler, A. S.; Seinfeld, J. H.; Kleeman, M. J.

    2015-08-01

    Multi-generational gas-phase oxidation of organic vapors can influence the abundance, composition and properties of secondary organic aerosol (SOA). Only recently have SOA models been developed that explicitly represent multi-generational SOA formation. In this work, we integrated the statistical oxidation model (SOM) into SAPRC-11 to simulate the multi-generational oxidation and gas/particle partitioning of SOA in the regional UCD/CIT (University of California, Davis/California Institute of Technology) air quality model. In the SOM, evolution of organic vapors by reaction with the hydroxyl radical is defined by (1) the number of oxygen atoms added per reaction, (2) the decrease in volatility upon addition of an oxygen atom and (3) the probability that a given reaction leads to fragmentation of the organic molecule. These SOM parameter values were fit to laboratory smog chamber data for each precursor/compound class. SOM was installed in the UCD/CIT model, which simulated air quality over 2-week periods in the South Coast Air Basin of California and the eastern United States. For the regions and episodes tested, the two-product SOA model and SOM produce similar SOA concentrations but a modestly different SOA chemical composition. Predictions of the oxygen-to-carbon ratio qualitatively agree with those measured globally using aerosol mass spectrometers. Overall, the implementation of the SOM in a 3-D model provides a comprehensive framework to simulate the atmospheric evolution of organic aerosol.

  13. Environmental assessment of three egg production systems–Part I: Monitoring system and indoor air quality

    PubMed Central

    Zhao, Y.; Shepherd, T. A.; Li, H.; Xin, H.

    2015-01-01

    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

  14. 3D Air Quality and the Clean Air Interstate Rule: Lagrangian Sampling of CMAQ Model Results to Aid Regional Accountability Metrics

    NASA Technical Reports Server (NTRS)

    Fairlie, T. D.; Szykman, Jim; Pierce, Robert B.; Gilliland, A. B.; Engel-Cox, Jill; Weber, Stephanie; Kittaka, Chieko; Al-Saadi, Jassim A.; Scheffe, Rich; Dimmick, Fred; Tikvart, Joe

    2008-01-01

    The Clean Air Interstate Rule (CAIR) is expected to reduce transport of air pollutants (e.g. fine sulfate particles) in nonattainment areas in the Eastern United States. CAIR highlights the need for an integrated air quality observational and modeling system to understand sulfate as it moves in multiple dimensions, both spatially and temporally. Here, we demonstrate how results from an air quality model can be combined with a 3d monitoring network to provide decision makers with a tool to help quantify the impact of CAIR reductions in SO2 emissions on regional transport contributions to sulfate concentrations at surface monitors in the Baltimore, MD area, and help improve decision making for strategic implementation plans (SIPs). We sample results from the Community Multiscale Air Quality (CMAQ) model using ensemble back trajectories computed with the NASA Langley Research Center trajectory model to provide Lagrangian time series and vertical profile information, that can be compared with NASA satellite (MODIS), EPA surface, and lidar measurements. Results are used to assess the regional transport contribution to surface SO4 measurements in the Baltimore MSA, and to characterize the dominant source regions for low, medium, and high SO4 episodes.

  15. Is a Complex Neural Network Based Air Quality Prediction Model Better Than a Simple One? A Bayesian Point of View

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

    In this study the neural network based air quality prediction model was tested in a typical coastal city, Macau, with Latitude 22° 10'N and Longitude 113° 34'E. By using five years of air quality and meteorological data recorded at an ambient air quality monitoring station between 2001 and 2005, it was found that the performance of the ANN model was generally improved by increasing the number of hidden neurons in the training phase. However, the performance of the ANN model was not sensitive to the change in the number of hidden neurons during the prediction phase. Therefore, the improvement in the error statistics for a complex ANN model in the training phase may be only caused by the overfitting of the data. In addition, the posterior PDF of the parameter vector conditional on the training dataset was investigated for different number of hidden neurons. It was found that the parametric space for a simple ANN model was globally identifiable and the Levenberg-Marquardt backpropagation algorithm was able to locate the optimal parameter vector. However, the parameter vector might contain redundant parameters and the parametric space was not globally identifiable when the model class became complex. In addition, the Levenberg-Marquardt backpropagation algorithm was unable to locate the most optimal parameter vector in this situation. Finally, it was concluded that the a more complex MLP model, that fits the data better, is not necessarily better than a simple one.

  16. Modeling the Impacts of Global Climate and Regional Land Use Change on Regional Climate, Air Quality and Public Health in the New York Metropolitan Region

    NASA Astrophysics Data System (ADS)

    Rosenthal, J. E.; Knowlton, K. M.; Kinney, P. L.

    2002-12-01

    exposures and responses to heat stress and air quality differ as a function of socio-economic status and race/ethnicity across the region? The model systems used for this study are the Goddard Institute for Space Studies (GISS) Global Atmosphere-Ocean Model; the Regional Atmospheric Modeling System (RAMS) and PennState/NCAR MM5 mesoscale meteorological models; the SLEUTH land use model; the Sparse Matrix Operator Kernel Emissions Modeling System (SMOKE); the Community Multiscale Air Quality (CMAQ) and Comprehensive Air Quality Model with Extensions (CAMx) models for simulating regional air quality; and exposure-risk coefficients for assessing population health impacts based on exposure to extreme heat, fine particulates (PM2.5) and ozone. Two different IPCC global emission scenarios and two different regional land use growth scenarios are considered in the simulations, spanning a range of possible futures. In addition to base simulations for selected time periods in the decade 1990 - 2000, the integrated model is used to simulate future scenarios in the 2020s, 2050s, and 2080s. Predictions from both the meteorological models and the air quality models are compared against available observations for the simulations in the 1990s to establish baseline model performance. A series of sensitivity tests will address whether changes in meteorology due to global climate change, changes in regional land use, or changes in emissions have the largest impact on predicted ozone and particulate matter concentrations.

  17. Observations and modeling of air quality trends over 1990-2010 across the northern hemisphere: China, the United States and Europe

    EPA Science Inventory

    Trends in air quality across the Northern Hemisphere over a 21-year period (1990–2010) were simulated using the Community Multiscale Air Quality (CMAQ) multiscale chemical transport model driven by meteorology from Weather Research and Forecasting WRF) simulations and internally ...

  18. On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model

    SciTech Connect

    Grell, Georg; Fast, Jerome D.; Gustafson, William I.; Peckham, Steven E.; McKeen, Stuart A.; Salzmann, Marc; Freitas, Saulo

    2010-01-01

    This is a conference proceeding that is now being put together as a book. This is chapter 2 of the book: "INTEGRATED SYSTEMS OF MESO-METEOROLOGICAL AND CHEMICAL TRANSPORT MODELS" published by Springer. The chapter title is "On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model." The original conference was the COST-728/NetFAM workshop on Integrated systems of meso-meteorological and chemical transport models, Danish Meteorological Institute, Copenhagen, May 21-23, 2007.

  19. Application of SIM-air modeling tools to assess air quality in Indian cities

    NASA Astrophysics Data System (ADS)

    Guttikunda, Sarath K.; Jawahar, Puja

    2012-12-01

    A prerequisite to an air quality management plan for a city is some idea of the main sources of pollution and their contributions for a city. This paper presents the results of an application of the SIM-air modeling tool in six Indian cities - Pune, Chennai, Indore, Ahmedabad, Surat, and Rajkot. Using existing and publicly available data, we put together a baseline of multi-pollutant emissions for each of the cities and then calculate concentrations, health impacts, and model alternative scenarios for 2020. The measured annual PM10 (particulate matter with aerodynamic diameter less than 10 micron meter) concentrations in μg m-3 averaged 94.7 ± 45.4 in Pune, 73.1 ± 33.7 in Chennai, 118.8 ± 44.3 in Indore, 94.0 ± 20.4 in Ahmedabad, 89.4 ± 12.1 in Surat, and 105.0 ± 25.6 in Rajkot, all exceeding the annual standard of 60 μg m-3. The PM10 inventory in tons/year for the year 2010 of 38,400 in Pune, 50,200 in Chennai, 18,600 in Indore, 31,900 in Ahmedabad, 20,000 in Surat, and 14,000 in Rajkot, is further spatially segregated into 1 km grids and includes all known sources such as transport, road dust, residential, power plants, industries (including the brick kilns), waste burning, and diesel generator sets. We use the ATMoS chemical transport model to validate the emissions inventory and estimate an annual premature mortality due to particulate pollution of 15,200 for the year 2010 for the six cities. Of the estimated 21,400 premature deaths in the six cities in 2020, we estimate that implementation of the six interventions in the transport and brick kiln sectors, can potentially save 5870 lives (27%) annually and result in an annual reduction of 16.8 million tons of carbon dioxide emissions in the six cities.

  20. Modeling the impacts of biomass burning on air quality in and around Mexico City

    NASA Astrophysics Data System (ADS)

    Lei, W.; Li, G.; Molina, L. T.

    2013-03-01

    impacts of biomass burning on tropospheric chemistry, regional and global air quality, and climate change.

  1. Volatile organic compound emissions from latex paint--Part 2. Test house studies and indoor air quality (IAQ) modeling.

    PubMed

    Sparks, L E; Guo, Z; Chang, J C; Tichenor, B A

    1999-03-01

    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 predictions. The agreement between model predictions and experimental measurements met the American Society for Testing and Materials criteria for model verification in the room with the source and met most of the requirements in other rooms. The major cause of disagreement between the model predictions and the experimental data in the test house appears to be an inadequate sink model.

  2. Visual air quality simulation techniques

    NASA Astrophysics Data System (ADS)

    Molenar, John V.; Malm, William C.; Johnson, Christopher E.

    Visual air quality is primarily a human perceptual phenomenon beginning with the transfer of image-forming information through an illuminated, scattering and absorbing atmosphere. Visibility, especially the visual appearance of industrial emissions or the degradation of a scenic view, is the principal atmospheric characteristic through which humans perceive air pollution, and is more sensitive to changing pollution levels than any other air pollution effect. Every attempt to quantify economic costs and benefits of air pollution has indicated that good visibility is a highly valued and desired environmental condition. Measurement programs can at best approximate the state of the ambient atmosphere at a few points in a scenic vista viewed by an observer. To fully understand the visual effect of various changes in the concentration and distribution of optically important atmospheric pollutants requires the use of aerosol and radiative transfer models. Communication of the output of these models to scientists, decision makers and the public is best done by applying modern image-processing systems to generate synthetic images representing the modeled air quality conditions. This combination of modeling techniques has been under development for the past 15 yr. Initially, visual air quality simulations were limited by a lack of computational power to simplified models depicting Gaussian plumes or uniform haze conditions. Recent explosive growth in low cost, high powered computer technology has allowed the development of sophisticated aerosol and radiative transfer models that incorporate realistic terrain, multiple scattering, non-uniform illumination, varying spatial distribution, concentration and optical properties of atmospheric constituents, and relative humidity effects on aerosol scattering properties. This paper discusses these improved models and image-processing techniques in detail. Results addressing uniform and non-uniform layered haze conditions in both

  3. Photochemical Grid Modelling Study to Assess Potential Air Quality Impacts Associated with Energy Development in Colorado and Northern New Mexico.

    NASA Astrophysics Data System (ADS)

    Parker, L. K.; Morris, R. E.; Zapert, J.; Cook, F.; Koo, B.; Rasmussen, D.; Jung, J.; Grant, J.; Johnson, J.; Shah, T.; Pavlovic, T.

    2015-12-01

    The Colorado Air Resource Management Modeling Study (CARMMS) was funded by the Bureau of Land Management (BLM) to predict the impacts from future federal and non-federal energy development in Colorado and Northern New Mexico. The study used the Comprehensive Air Quality Model with extensions (CAMx) photochemical grid model (PGM) to quantify potential impacts from energy development from BLM field office planning areas. CAMx source apportionment technology was used to track the impacts from multiple (14) different emissions source regions (i.e. field office areas) within one simulation, as well as to assess the cumulative impact of emissions from all source regions combined. The energy development emissions estimates were for the year 2021 for three different development scenarios: (1) low; (2) high; (3) high with emissions mitigation. Impacts on air quality (AQ) including ozone, PM2.5, PM10, NO2, SO2, and air quality related values (AQRVs) such as atmospheric deposition, regional haze and changes in Acid Neutralizing Capacity (ANC) of lakes were quantified, and compared to establish threshold levels. In this presentation, we present a brief summary of the how the emission scenarios were developed, we compare the emission totals for each scenario, and then focus on the ozone impacts for each scenario to assess: (1). the difference in potential ozone impacts under the different development scenarios and (2). to establish the sensitivity of the ozone impacts to different emissions levels. Region-wide ozone impacts will be presented as well as impacts at specific locations with ozone monitors.

  4. Exploring the applicability of future air quality predictions based on synoptic system forecasts.

    PubMed

    Yuval; Broday, David M; Alpert, Pinhas

    2012-07-01

    For a given emissions inventory, the general levels of air pollutants and the spatial distribution of their concentrations are determined by the physiochemical state of the atmosphere. Apart from the trivial seasonal and daily cycles, most of the variability is associated with the atmospheric synoptic scale. A simple methodology for assessing future levels of air pollutants' concentrations based on synoptic forecasts is presented. At short time scales the methodology is comparable and slightly better than persistence and seasonal forecasts at categorical classification of pollution levels. It's utility is shown for air quality studies at the long time scale of a changing climate scenario, where seasonality and persistence cannot be used. It is demonstrated that the air quality variability due to changes in the pollution emissions can be expected to be much larger than that associated with the effects of climatic changes.

  5. CARETS: A prototype regional environmental information system. Volume 7: Land use information and air quality planning. [Norfolk and Portsmouth, Virginia

    NASA Technical Reports Server (NTRS)

    Alexander, R. H. (Principal Investigator); Reed, W. E.; Lewis, J. E.

    1975-01-01

    The author has identified the following significant results. The pilot air quality system provided data for updating information on the sources of point and area emissions of SO2 and particulate matter affecting the Norfolk-Portsmouth area of Virginia for 1971-72 winter and the annual 1972 period. During the 1971-72 winter, estimated SO2 amounts over an area with a SW-NE axis in the central section of Norfolk exceeded both primary and secondary levels.

  6. A low-cost sensing system for cooperative air quality monitoring in urban areas.

    PubMed

    Brienza, Simone; Galli, Andrea; Anastasi, Giuseppe; Bruschi, Paolo

    2015-01-01

    Air quality in urban areas is a very important topic as it closely affects the health of citizens. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring, so as to allow appropriate and timely decisions. In this paper, we present uSense, a low-cost cooperative monitoring tool that allows knowing, in real-time, the concentrations of polluting gases in various areas of the city. Specifically, users monitor the areas of their interest by deploying low-cost and low-power sensor nodes. In addition, they can share the collected data following a social networking approach. uSense has been tested through an in-field experimentation performed in different areas of a city. The obtained results are in line with those provided by the local environmental control authority and show that uSense can be profitably used for air quality monitoring. PMID:26016912

  7. A Low-Cost Sensing System for Cooperative Air Quality Monitoring in Urban Areas

    PubMed Central

    Brienza, Simone; Galli, Andrea; Anastasi, Giuseppe; Bruschi, Paolo

    2015-01-01

    Air quality in urban areas is a very important topic as it closely affects the health of citizens. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring, so as to allow appropriate and timely decisions. In this paper, we present uSense, a low-cost cooperative monitoring tool that allows knowing, in real-time, the concentrations of polluting gases in various areas of the city. Specifically, users monitor the areas of their interest by deploying low-cost and low-power sensor nodes. In addition, they can share the collected data following a social networking approach. uSense has been tested through an in-field experimentation performed in different areas of a city. The obtained results are in line with those provided by the local environmental control authority and show that uSense can be profitably used for air quality monitoring. PMID:26016912

  8. A low-cost sensing system for cooperative air quality monitoring in urban areas.

    PubMed

    Brienza, Simone; Galli, Andrea; Anastasi, Giuseppe; Bruschi, Paolo

    2015-05-26

    Air quality in urban areas is a very important topic as it closely affects the health of citizens. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring, so as to allow appropriate and timely decisions. In this paper, we present uSense, a low-cost cooperative monitoring tool that allows knowing, in real-time, the concentrations of polluting gases in various areas of the city. Specifically, users monitor the areas of their interest by deploying low-cost and low-power sensor nodes. In addition, they can share the collected data following a social networking approach. uSense has been tested through an in-field experimentation performed in different areas of a city. The obtained results are in line with those provided by the local environmental control authority and show that uSense can be profitably used for air quality monitoring.

  9. Combining regional- and local-scale air quality models with exposure models for use in environmental health studies.

    PubMed

    Isakov, Vlad; Touma, Jawad S; Burke, Janet; Lobdell, Danelle T; Palma, Ted; Rosenbaum, Arlene; Ozkaynak, Halûk

    2009-04-01

    Population-based human exposure models predict the distribution of personal exposures to pollutants of outdoor origin using a variety of inputs, including air pollution concentrations; human activity patterns, such as the amount of time spent outdoors versus indoors, commuting, walking, and indoors at home; microenvironmental infiltration rates; and pollutant removal rates in indoor environments. Typically, exposure models rely upon ambient air concentration inputs from a sparse network of monitoring stations. Here we present a unique methodology for combining multiple types of air quality models (the Community Multi-Scale Air Quality [CMAQ] chemical transport model added to the AERMOD dispersion model) and linking the resulting hourly concentrations to population exposure models (the Hazardous Air Pollutant Exposure Model [HAPEM] or the Stochastic Human Exposure and Dose Simulation [SHEDS] model) to enhance estimates of air pollution exposures that vary temporally (annual and seasonal) and spatially (at census-block-group resolution) in an urban area. The results indicate that there is a strong spatial gradient in the predicted mean exposure concentrations near roadways and industrial facilities that can vary by almost a factor of 2 across the urban area studied. At the high end of the exposure distribution (95th percentile), exposures are higher in the central district than in the suburbs. This is mostly due to the importance of personal mobility factors whereby individuals living in the central area often move between microenvironments with high concentrations, as opposed to individuals residing at the outskirts of the city. Also, our results indicate 20-30% differences due to commuting patterns and almost a factor of 2 difference because of near-roadway effects. These differences are smaller for the median exposures, indicating the highly variable nature of the reflected ambient concentrations. In conjunction with local data on emission sources

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

    NASA Astrophysics Data System (ADS)

    Giordano, L.; Brunner, D.; Flemming, J.; Hogrefe, C.; Im, U.; Bianconi, R.; Badia, A.; Balzarini, A.; Baró, R.; Chemel, C.; Curci, G.; Forkel, R.; Jiménez-Guerrero, P.; Hirtl, M.; Hodzic, A.; Honzak, L.; Jorba, O.; Knote, C.; Kuenen, J. J. P.; Makar, P. A.; Manders-Groot, A.; Neal, L.; Pérez, J. L.; Pirovano, G.; Pouliot, G.; San José, R.; Savage, N.; Schröder, W.; Sokhi, R. S.; Syrakov, D.; Torian, A.; Tuccella, P.; Werhahn, J.; Wolke, R.; Yahya, K.; Žabkar, R.; Zhang, Y.; Galmarini, S.

    2015-08-01

    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 models to simulate the year 2010 over one European and one North American domain. The MACC re-analysis has been used as chemical initial (IC) and boundary conditions (BC) by all participating regional models in AQMEII-2. The aim of the present work is to evaluate the MACC re-analysis along with the participating regional models against a set of ground-based measurements (O3, CO, NO, NO2, SO2, SO42-) and vertical profiles (O3 and CO). Results indicate different degrees of agreement between the measurements and the MACC re-analysis, with an overall better performance over the North American domain. The influence of BC on regional air quality simulations is analyzed in a qualitative way by contrasting model performance for the MACC re-analysis with that for the regional models. This approach complements more quantitative approaches documented in the literature that often have involved sensitivity simulations but typically were limited to only one or only a few regional scale models. Results suggest an important influence of the BC on ozone for which the underestimation in winter in the MACC re-analysis is mimicked by the regional models. For CO, it is found that background concentrations near the domain boundaries are rather close to observations while those over the interior of the two continents are underpredicted by both MACC and the regional models over Europe but only by MACC over North America. This indicates that emission differences between the MACC re-analysis and the regional models can have a profound impact on model performance and points to the need for harmonization of inputs in future linked global/regional modeling studies.

  11. Design and demonstration of a next-generation air quality attainment assessment system for PM2.5 and O3.

    PubMed

    Wang, Hua; Zhu, Yun; Jang, Carey; Lin, Che-Jen; Wang, Shuxiao; Fu, Joshua S; Gao, Jian; Deng, Shuang; Xie, Junping; Ding, Dian; Qiu, Xuezhen; Long, Shicheng

    2015-03-01

    Due to the increasingly stringent standards, it is important to assess whether the proposed emission reduction will result in ambient concentrations that meet the standards. The Software for Model Attainment Test-Community Edition (SMAT-CE) is developed for demonstrating attainment of air quality standards of O3 and PM2.5. SMAT-CE improves computational efficiency and provides a number of advanced visualization and analytical functionalities on an integrated GIS platform. SMAT-CE incorporates historical measurements of air quality parameters and simulated air pollutant concentrations under a number of emission inventory scenarios to project the level of compliance to air quality standards in a targeted future year. An application case study of the software based on the U.S. National Ambient Air Quality Standards (NAAQS) shows that SMAT-CE is capable of demonstrating the air quality attainment of annual PM2.5 and 8-hour O3 for a proposed emission control policy.

  12. Design and demonstration of a next-generation air quality attainment assessment system for PM2.5 and O3.

    PubMed

    Wang, Hua; Zhu, Yun; Jang, Carey; Lin, Che-Jen; Wang, Shuxiao; Fu, Joshua S; Gao, Jian; Deng, Shuang; Xie, Junping; Ding, Dian; Qiu, Xuezhen; Long, Shicheng

    2015-03-01

    Due to the increasingly stringent standards, it is important to assess whether the proposed emission reduction will result in ambient concentrations that meet the standards. The Software for Model Attainment Test-Community Edition (SMAT-CE) is developed for demonstrating attainment of air quality standards of O3 and PM2.5. SMAT-CE improves computational efficiency and provides a number of advanced visualization and analytical functionalities on an integrated GIS platform. SMAT-CE incorporates historical measurements of air quality parameters and simulated air pollutant concentrations under a number of emission inventory scenarios to project the level of compliance to air quality standards in a targeted future year. An application case study of the software based on the U.S. National Ambient Air Quality Standards (NAAQS) shows that SMAT-CE is capable of demonstrating the air quality attainment of annual PM2.5 and 8-hour O3 for a proposed emission control policy. PMID:25766027

  13. A Procedure for Inter-Comparing the Skill of Regional-Scale Air Quality Model Simulations of Daily Maximum 8-Hour Ozone Concentrations

    EPA Science Inventory

    An operational model evaluation procedure is described to quantitatively assess the relative skill among several regionalscale air quality models simulating various percentiles of the cumulative frequency distribution of observed daily maximum 8-h ozone concentrations. Bootstrap ...

  14. Ozone distributions over southern Lake Michigan: comparisons between ferry-based observations, shoreline-based DOAS observations and air quality forecast models

    NASA Astrophysics Data System (ADS)

    Cleary, P. A.; Fuhrman, N.; Schulz, L.; Schafer, J.; Fillingham, J.; Bootsma, H.; Langel, T.; Williams, E. J.; Brown, S. S.

    2014-09-01

    Air quality forecast models typically predict large ozone abundances over water relative to land in the Great Lakes region. While each state bordering Lake Michigan has dedicated monitoring systems, offshore measurements have been sparse, mainly executed through specific short-term campaigns. This study examines ozone abundances over Lake Michigan as measured on the Lake Express ferry, by shoreline Differential Optical Absorption Spectroscopy (DOAS) observations in southeastern Wisconsin, and as predicted by the National Air Quality Forecast System. From 2008-2009 measurements of O3, SO2, NO2 and formaldehyde were made in the summertime by DOAS at a shoreline site in Kenosha, WI. From 2008-2010 measurements of ambient ozone conducted on the Lake Express, a high-speed ferry that travels between Milwaukee, WI and Muskegon, MI up to 6 times daily from spring to fall. Ferry ozone observations over Lake Michigan were an average of 3.8 ppb higher than those measured at shoreline in Kenosha with little dependence on position of the ferry or temperature but with highest differences during evening and night. Concurrent ozone forecast images from National Weather System's National Air Quality Forecast System in the upper Midwestern region surrounding Lake Michigan were saved over the ferry ozone sampling period in 2009. The bias of the model O3 forecast was computed and evaluated with respect to ferry-based measurements. The model 1 and 8 h ozone mean biases were both 12 ppb higher than observed ozone, and maximum daily 1 h ozone mean bias was 10 ppb, indicating substantial ozone over-prediction over water. Trends in the bias with respect to location and time of day or month were also explored showing non-uniformity in model bias. Extreme ozone events were predicted by the model but not observed by ferry measurements.

  15. Aerosol Health Impact Source Attribution Studies with the CMAQ Adjoint Air Quality Model

    NASA Astrophysics Data System (ADS)

    Turner, M. D.

    , reductions in emissions from large industrial combustion sources that are not classified as EGUs (i.e., non-EGU) are estimated to have up to triple the benefits per unit emission of reductions to onroad diesel sectors, and provide similar benefits per unit of reduced emission to that of onroad gasoline emissions in the region. While a majority of vehicle emission controls that regulate PM focus on diesel emissions, our analysis shows the most efficient target for stricter controls is actually onroad gasoline emissions. From an analysis of the health impacts of BC emissions on specific demographic populations, we find that emissions in the southern half of the US tend to disproportionally affect persons with a below high school education and persons below 50% of the poverty level. Analysis of national risk (independent of population and mortality rates) shows that the largest risks are associated with drier climates, due to the increased atmospheric lifetime resulting from less wet removal of aerosols. Lastly, analysis of the impacts of BC emissions on maximum individual risk shows that contributions to maximum individual risk are weakly to strongly correlated with emissions (R2 ranging from 0.23 in the San Joaquin Valley to 0.93 in the Dallas region). Overall, this thesis shows the value of high-resolution, adjoint-based source attribution studies for determining the locations, seasons, and sectors that have the greatest estimated impact on human health in air quality models.

  16. Integrated Modeling to Assess the Ecological and Air Quality Trade-offs of Agricultural Burning in the Flint Hills of Eastern Kansas

    NASA Astrophysics Data System (ADS)

    Barnhart, B. L.; Mckane, R.; Brookes, A.; Schumaker, N.; Papenfus, M.; Pettus, P.; Halama, J.; Powers, B.; Djang, K.; Groskinsky, B.; Grier, G.; Hawkins, A.; Tapp, J.; Watson, D.; Gross, T.; Goodin, D.; Mohler, R.

    2015-12-01

    The Flint Hills of eastern Kansas and northern Oklahoma is home to the largest remaining contiguous grassland prairie in the United States. Throughout the prairie, burning is a common practice used to preserve the prairie from encroachment of woody species such as eastern Red Cedar, and to enhance the quantity and quality of the grass grown for cattle grazing in the region. However, widespread annual burning in early spring has led to air quality exceedances and pollution impacts in urban areas such as Kansas City, Topeka, and Wichita. Our research effort focuses on developing a modelling environment that simulates the effects of burning in the Flint Hills using an integrated modeling system, including an eco-hydrological model, an air quality and dispersion model, an economic and health effects model, and a terrestrial-species model. Using this integrated system, we can model historical burning practices as well as hypothetical variations in timing and quantity of burns. Then, we can investigate the relative trade-offs between farm productivity, ecological effects, urban health effects, and habitat diversity for terrestrial species given different burning scenarios. The results from this systems approach will provide land managers with information about the relative trade-offs associated with burning considering multiple elements of sustainability throughout the Flint Hills.

  17. AQA-PM: Extension of the Air-Quality Model For Austria with Satellite based Particulate Matter Estimates

    NASA Astrophysics Data System (ADS)

    Hirtl, Marcus; Mantovani, Simone; Krüger, Bernd C.; Triebnig, Gerhard; Flandorfer, Claudia

    2013-04-01

    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 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 regression- and assimilation techniques. For the model simulations WRF/Chem is used with a resolution of 3 km over the alpine region. Interfaces have been developed to account for the different measurements as input data. The available local emission inventories provided by the different Austrian regional governments were harmonized and used for the model simulations. An episode in February 2010 is chosen for the model evaluation. During that month exceedances of PM10-thresholds occurred at many measurement stations of the Austrian network. Different model runs (only model/only ground stations assimilated/satellite and ground stations assimilated) are compared to the respective measurements. 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.

  18. A Comparison of Statistical Techniques for Combining Modeled and Observed Concentrations to Create High-Resolution Ozone Air Quality Surfaces

    EPA Science Inventory

    Air quality surfaces representing pollutant concentrations across space and time are needed for many applications, including tracking trends and relating air quality to human and ecosystem health. The spatial and temporal characteristics of these surfaces may reveal new informat...

  19. EVALUATING THE USE OF OUTPUTS FROM COMPREHENSIVE METEOROLOGICAL MODELS IN AIR QUALITY MODELING APPLICATIONS

    EPA Science Inventory

    Currently used dispersion models, such as the AMS/EPA Regulatory Model (AERMOD), process routinely available meteorological observations to construct model inputs. Thus, model estimates of concentrations depend on the availability and quality of Meteorological observations, as we...

  20. 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

    2006-04-16

    This Annual report summarizes the research performed from 17 April 2005 through 16 April 2006. Major portions of the research in several of the project's current eight tasks have been completed. We have successfully developed the meteorological inputs using the best possible modeling configurations, resulting in improved representation of atmospheric processes. The development of the variable-grid-resolution emissions model, SMOKE-VGR, is also completed. The development of the MAQSIP-VGR has been completed and a test run was performed to ensure the functionality of this air quality model. We have incorporated new emission data base to update the offshore emissions. However, we have faced some bottleneck problems in the testing the integrity of the new database. For this reason, we have asked for a no cost extension of this project to tackle these scientific problems. Thus, the project is on a one-year delay schedule. During the reporting period, we solved all problems related to the new emission database. We are ready to move to developing the final product, implementation and testing of the variable grid technology into the Community Multiscale Air Quality Model (CMAQ) to develop the CMAQ-VGR. During the upcoming months we will perform the first CMAQ-VGR simulations over the Houston-Galveston region to study the roles of the meteorology, offshore emissions, and chemistry-transport interactions that determine the temporal and spatial evolution of ozone and its precursors.

  1. Air quality at Santiago, Chile: a box modeling approach—I. Carbon monoxide, nitrogen oxides and sulfur dioxide

    NASA Astrophysics Data System (ADS)

    Jorquera, Héctor

    Ambient monitored data at Santiago, Chile, are analyzed using box models with the goal of assessing contributions of different economic activities to air pollution levels. The period analyzed is 1990-2000, characterized by the introduction of air pollution emissions standards, shift to unleaded gasoline and compressed natural gas, and steady growth of the private and public fleet and the associated fuel consumption growth. The box models explicitly include the seasonal behavior of meteorological variables; the results show that dispersion conditions in fall and winter seasons are 20-30% of the summertime values. This result explains the poor air quality in those seasons and shows that significant emissions reductions are required in order to improve air quality in wintertime. Emissions of CO, NO x and SO 2 are estimated from data on fuel consumption in the city; the estimated parameters are thus fleet-average or industry-average emission factors. In terms of contributions to ambient concentrations, older cars and diesel vehicles are the major contributors to CO and NO x impacts, with more than 60% and 50%, respectively. Ambient concentrations of SO 2 are largely dominated by stationary sources, although long range contributions are not negligible. By contrast, CO and NO x pollution is dominated by local sources within the city boundaries. The box models can be used for forecasting purposes, and they can predict annual average concentrations within 20% of the observed values. The methodology requires data on ambient air quality measurements and fuel consumption statistics, and produces quantitative results, which can be combined with economic models to analyze environmental regulation and public policies.

  2. An Observational and modeling strategy to investigate the impact of remote sources on local air quality: A Houston, Texas case study from the Second Texas Air Quality Study (TEXAQS II)

    SciTech Connect

    McMillan, W. W.; Pierce, R.; Sparling, L. C.; Osterman, G.; McCann, K.; Fischer, M. L.; Rappengluck, B.; Newsom, Rob K.; Turner, David D.; Kittaka, C.; Evans, K.; Biraud, S.; Lefer, Barry; Andrews, A.; Oltmans, S.

    2010-01-05

    Quantifying the impacts of remote sources on individual air quality exceedances remains a significant challenge for air quality forecasting. One goal of the 2006 Texas Air Quality Study (TEXAQS II) was to assess the impact of distant sources on air quality in east Texas. From 23-30 August 2006, retrievals of tropospheric carbon monoxide (CO) from NASA’s Atmospheric InfraRed Sounder (AIRS) reveal the transport of CO from fires in the United States Pacific Northwest to Houston, Texas. This transport occurred behind a cold front and contributed to the worst ozone exceedance period of the summer in the Houston area. We present supporting satellite observations from the NASA A-Train constellation of the vertical distribution of smoke aerosols and CO. Ground-based in situ CO measurements in Oklahoma and Texas track the CO plume as it moves south and indicate mixing of the aloft plume to the surface by turbulence in the nocturnal boundary layer and convection during the day. Ground-based aerosol speciation and lidar observations do not find appreciable smoke aerosol transport for this case. However, MODIS aerosol optical depths and model simulations indicate some smoke aerosols were transported from the Pacific Northwest through Texas to the Gulf of Mexico. Chemical transport and forward trajectory models confirm the three major observations: (1) the AIRS envisioned CO transport, (2) the satellite determined smoke plume height, and (3) the timing of the observed surface CO increases. Further, the forward trajectory simulations find two of the largest Pacific Northwest fires likely had the most significant impact.

  3. HVAC systems as emission sources affecting indoor air quality: A critical review. Final report, September 1993-June 1994

    SciTech Connect

    Batterman, S.; Burge, H.

    1995-02-01

    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 tests, longitudinal and cross-sectional studies, and laboratory studies. Based on the available literature, several HVAC components are cited fairly frequently as emission sources, and there is broad agreement regarding their significance. IAQ problems appear to be exacerbated by dust accumulation and by the presence of fibrous insulation. Other problems include entrainment, migration, and infiltration of indoor and outdoor contaminants that are distributed to indoor spaces by the HVAC system.

  4. Modeled Effectiveness of Ventilation with Contaminant Control Devices on Indoor Air Quality in a Swine Farrowing Facility

    PubMed Central

    Anthony, T. Renée; Altmaier, Ralph; Park, Jae Hong; Peters, Thomas M.

    2016-01-01

    Because adverse health effects experienced by swine farm workers in concentrated animal feeding operations (CAFOs) have been associated with exposure to dust and gases, efforts to reduce exposures are warranted, particularly in winter seasons when exposures increase due to decreased ventilation. Simulation of air quality and operating costs for ventilating swine CAFO, including treating and recirculating air through a farrowing room, was performed using mass and energy balance equations over a 90-day winter season. System operation required controlling heater operation to achieve room temperatures optimal to ensure animal health (20 to 22.5°C). Five air pollution control devices, four room ventilation rates, and five recirculation patterns were examined. Inhalable dust concentrations were easily reduced using standard industrial air pollution control devices, including a cyclone, filtration, and electrostatic precipitator. Operating ventilation systems at 0.94 m3 s−1 (2000 cfm) with 75 to 100% recirculation of treated air from cyclone, electrostatic precipitator, and shaker dust filtration system achieves adequate particle control with operating costs under $1.00 per pig produced ($0.22 to 0.54), although carbon dioxide (CO2) concentrations approach 2000 ppm using in-room ventilated gas fired heaters. In no simulation were CO2 concentrations below industry recommended concentrations (1540 ppm), but alternative heating devices could reduce CO2 to acceptable concentrations. While this investigation does not represent all production swine farrowing barns, which differ in characteristics including room dimensions and swine occupancy, the simulation model and ventilation optimization methods can be applied to other production sites. This work shows that ventilation may be a cost-effective control option in the swine industry to reduce exposures. PMID:24433305

  5. Modeled effectiveness of ventilation with contaminant control devices on indoor air quality in a swine farrowing facility.

    PubMed

    Anthony, T Renée; Altmaier, Ralph; Park, Jae Hong; Peters, Thomas M

    2014-01-01

    Because adverse health effects experienced by swine farm workers in concentrated animal feeding operations (CAFOs) have been associated with exposure to dust and gases, efforts to reduce exposures are warranted, particularly in winter seasons when exposures increase due to decreased ventilation. Simulation of air quality and operating costs for ventilating swine CAFO, including treating and recirculating air through a farrowing room, was performed using mass and energy balance equations over a 90-day winter season. System operation required controlling heater operation to achieve room temperatures optimal to ensure animal health (20 to 22.5 °C). Five air pollution control devices, four room ventilation rates, and five recirculation patterns were examined. Inhalable dust concentrations were easily reduced using standard industrial air pollution control devices, including a cyclone, filtration, and electrostatic precipitator. Operating ventilation systems at 0.94 m3 s(-1) (2000 cfm) with 75 to 100% recirculation of treated air from cyclone, electrostatic precipitator, and shaker dust filtration system achieves adequate particle control with operating costs under $1.00 per pig produced ($0.22 to 0.54), although carbon dioxide (CO2) concentrations approach 2000 ppm using in-room ventilated gas fired heaters. In no simulation were CO2 concentrations below industry recommended concentrations (1540 ppm), but alternative heating devices could reduce CO2 to acceptable concentrations. While this investigation does not represent all production swine farrowing barns, which differ in characteristics including room dimensions and swine occupancy, the simulation model and ventilation optimization methods can be applied to other production sites. This work shows that ventilation may be a cost-effective control option in the swine industry to reduce exposures. PMID:24433305

  6. Modeled effectiveness of ventilation with contaminant control devices on indoor air quality in a swine farrowing facility.

    PubMed

    Anthony, T Renée; Altmaier, Ralph; Park, Jae Hong; Peters, Thomas M

    2014-01-01

    Because adverse health effects experienced by swine farm workers in concentrated animal feeding operations (CAFOs) have been associated with exposure to dust and gases, efforts to reduce exposures are warranted, particularly in winter seasons when exposures increase due to decreased ventilation. Simulation of air quality and operating costs for ventilating swine CAFO, including treating and recirculating air through a farrowing room, was performed using mass and energy balance equations over a 90-day winter season. System operation required controlling heater operation to achieve room temperatures optimal to ensure animal health (20 to 22.5 °C). Five air pollution control devices, four room ventilation rates, and five recirculation patterns were examined. Inhalable dust concentrations were easily reduced using standard industrial air pollution control devices, including a cyclone, filtration, and electrostatic precipitator. Operating ventilation systems at 0.94 m3 s(-1) (2000 cfm) with 75 to 100% recirculation of treated air from cyclone, electrostatic precipitator, and shaker dust filtration system achieves adequate particle control with operating costs under $1.00 per pig produced ($0.22 to 0.54), although carbon dioxide (CO2) concentrations approach 2000 ppm using in-room ventilated gas fired heaters. In no simulation were CO2 concentrations below industry recommended concentrations (1540 ppm), but alternative heating devices could reduce CO2 to acceptable concentrations. While this investigation does not represent all production swine farrowing barns, which differ in characteristics including room dimensions and swine occupancy, the simulation model and ventilation optimization methods can be applied to other production sites. This work shows that ventilation may be a cost-effective control option in the swine industry to reduce exposures.

  7. Evaluation of the Community Multiscale Air Quality Model for Simulating Winter Ozone Formation in the Uinta Basin with Intensive Oil and Gas Production

    NASA Astrophysics Data System (ADS)

    Matichuk, R.; Tonnesen, G.; Luecken, D.; Roselle, S. J.; Napelenok, S. L.; Baker, K. R.; Gilliam, R. C.; Misenis, C.; Murphy, B.; Schwede, D. B.

    2015-12-01

    The western United States is an important source of domestic energy resources. One of the primary environmental impacts associated with oil and natural gas production is related to air emission releases of a number of air pollutants. Some of these pollutants are important precursors to the formation of ground-level ozone. To better understand ozone impacts and other air quality issues, photochemical air quality models are used to simulate the changes in pollutant concentrations in the atmosphere on local, regional, and national spatial scales. These models are important for air quality management because they assist in identifying source contributions to air quality problems and designing effective strategies to reduce harmful air pollutants. The success of predicting oil and natural gas air quality impacts depends on the accuracy of the input information, including emissions inventories, meteorological information, and boundary conditions. The treatment of chemical and physical processes within these models is equally important. However, given the limited amount of data collected for oil and natural gas production emissions in the past and the complex terrain and meteorological conditions in western states, the ability of these models to accurately predict pollution concentrations from these sources is uncertain. Therefore, this presentation will focus on understanding the Community Multiscale Air Quality (CMAQ) model's ability to predict air quality impacts associated with oil and natural gas production and its sensitivity to input uncertainties. The results will focus on winter ozone issues in the Uinta Basin, Utah and identify the factors contributing to model performance issues. The results of this study will help support future air quality model development, policy and regulatory decisions for the oil and gas sector.

  8. Establishment of a high-resolution emission inventory and its impact assessment on air quality modeling in Jiangsu Province, China

    NASA Astrophysics Data System (ADS)

    Zhou, Y.; Zhao, Y.

    2015-12-01

    A high-resolution emission inventory of Jiangsu Province was developed for 2012, using the bottom-up method with the best available domestic emission factors and activity data incorporated. Information of over 6,000 point sources including geographical location, fuel type, burner type and removal efficiency were investigated from various available data sources. The point sources were estimated to account for 83.9%, 71.2%, 63.7% and 54.5% of the total SO2, NOx, PM2.5 and VOCs emissions respectively. Improvement of this provincial emission inventory was assessed by comparisons with emission estimation at national level. For SO2 from power plants, NOx from transportation and PM2.5 from industry, correlation coefficients were 0.703, 0.814 and 0.335, indicated other than power plants and transportation, there was an improvement in estimation of small industrial pollution sources which were usually estimated as area sources in national emission inventory. Correlation analysis of NOx emission and tropospheric NO2 vertical column density measured by Ozone Monitoring Instrument (OMI) were also conducted. The correlation coefficient rose from 0.52 to 0.57 after revisions on geographical locations of 20 large point sources. Such result indicated the local source information from Environmental Statistics should be carefully examined before it can be applied for emission inventory development. In order to assess the improvement in spatial distribution and emission estimation on air quality modeling, the provincial and national emission inventory were input to Community Multi-scale Air Quality Model (CMAQ) simulations. Simulations performed better when emissions were updated from Multi-resolution Emission Inventory for China (MEIC) to provincial inventory, indicating the necessity of improved spatial and temporal distribution of emissions on air quality modeling, especially for gaseous pollutants. For SO2, the normalized mean bias (NMB) and normalized mean error (NME) decreased

  9. The Application of Satellite-Derived, High-Resolution Land Use/Land Cover Data to Improve Urban Air Quality Model Forecasts

    NASA Technical Reports Server (NTRS)

    Quattrochi, D. A.; Lapenta, W. M.; Crosson, W. L.; Estes, M. G., Jr.; Limaye, A.; Kahn, M.

    2006-01-01

    Local and state agencies are responsible for developing state implementation plans to meet National Ambient Air Quality Standards. Numerical models used for this purpose simulate the transport and transformation of criteria pollutants and their precursors. The specification of land use/land cover (LULC) plays an important role in controlling modeled surface meteorology and emissions. NASA researchers have worked with partners and Atlanta stakeholders to incorporate an improved high-resolution LULC dataset for the Atlanta area within their modeling system and to assess meteorological and air quality impacts of Urban Heat Island (UHI) mitigation strategies. The new LULC dataset provides a more accurate representation of land use, has the potential to improve model accuracy, and facilitates prediction of LULC changes. Use of the new LULC dataset for two summertime episodes improved meteorological forecasts, with an existing daytime cold bias of approx. equal to 3 C reduced by 30%. Model performance for ozone prediction did not show improvement. In addition, LULC changes due to Atlanta area urbanization were predicted through 2030, for which model simulations predict higher urban air temperatures. The incorporation of UHI mitigation strategies partially offset this warming trend. The data and modeling methods used are generally applicable to other U.S. cities.

  10. Evidence for an increase in the ozone photochemical lifetime in the eastern United States using a regional air quality model

    NASA Astrophysics Data System (ADS)

    Goldberg, Daniel L.; Vinciguerra, Timothy P.; Hosley, Kyle M.; Loughner, Christopher P.; Canty, Timothy P.; Salawitch, Ross J.; Dickerson, Russell R.

    2015-12-01

    Measures to control surface ozone rely on quantifying production attributable to local versus regional (upwind) emissions. Here we simulate the relative contribution of local (i.e., within a particular state) and regional sources of surface ozone in the eastern United States (66-94°W longitude) for July 2002, 2011, and 2018 using the Comprehensive Air-quality Model with Extensions (CAMx). To determine how emissions and chemistry within the domain affect the production, loss, lifetime, and transport of trace gases, we initialize our model with identical boundary conditions in each simulation. We find that the photochemical lifetime of ozone has increased as emissions have decreased. The contribution of ozone from outside the domain (boundary condition ozone, BCO3) to local surface mixing ratios increases in an absolute sense by 1-2 ppbv between 2002 and 2018 due to the longer lifetime of ozone. The photochemical lifetime of ozone lengthens because the two primary gas phase sinks for odd oxygen (Ox ≈ NO2 + O3)—attack by hydroperoxyl radicals (HO2) on ozone and formation of nitrate—weaken with decreasing pollutant emissions. The relative role of BCO3 will also increase. For example, BCO3 represents 34.5%, 38.8%, and 43.6% of surface ozone in the Baltimore, MD, region during July 2002, 2011, and 2018 means, respectively. This unintended consequence of air quality regulation impacts attainment of the National Ambient Air Quality Standard for surface ozone because the spatial and temporal scales of photochemical smog increase; the influence of pollutants transported between states and into the eastern U.S. will likely play a greater role in the future.

  11. Modelin 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

    Adel Hanna

    2008-10-16

    evaluated this new system. We completed the development of our variable-grid-resolution air quality model (MAQSIP-VGR) and performed various diagnostic tests related to an enhanced cloud parameterization scheme. We also developed an important tool for variable-grid graphics using Google Earth. We ran the MAQSIP-VGR for the Houston-Galveston and southern Louisiana domains for an August 23 to September 2, 2002, episode. Results of the modeling simulations highlighted the usefulness of the variable-grid modeling approach when simulating complex terrain processes related to land and sea close to an urban area. Our results showed that realistic SST patterns based on remote sensing are critical to capturing the land-sea breeze, in particular the inland intrusion of the reversed mesoscale circulation that is critical for simulating air pollution over urban areas near coastal regions. Besides capturing the correct horizontal gradient between land and sea surface temperatures, it is important to use an adequate ABL scheme in order to quantify correctly the vertical profiles of various parameters. The ABL scheme should capture the dynamics of the marine boundary layer, which is not often considered in a typical simulation over land. Our results further showed the effect of using satellite-derived SSTs on the horizontal and vertical extent of the modeled pollution pattern, and the increase in hourly ozone concentrations associated with changes in ABL characteristics resulting from the enhanced mesoscale circulation in the lower troposphere.

  12. Inter-comparison between HERMESv2.0 and TNO-MACC-II emission data using the CALIOPE air quality system (Spain)

    NASA Astrophysics Data System (ADS)

    Guevara, Marc; Pay, María Teresa; Martínez, Francesc; Soret, Albert; Denier van der Gon, Hugo; Baldasano, José M.

    2014-12-01

    This work examines and compares the performance of two emission datasets on modelling air quality concentrations for Spain: (i) the High-Elective Resolution Modelling Emissions System (HERMESv2.0) and (ii) the TNO-MACC-II emission inventory. For this purpose, the air quality system CALIOPE-AQFS (WRF-ARW/CMAQ/BSC-DREAM8b) was run over Spain for February and June 2009 using the two emission datasets (4 km × 4 km and 1 h). Nitrogen dioxide (NO2), sulphur dioxide (SO2), Ozone (O3) and particular matter (PM10) modelled concentrations were compared with measurements at different type of air quality stations (i.e. rural background, urban, suburban industrial). A preliminary emission comparison showed significant discrepancies between the two datasets, highlighting an overestimation of industrial emissions in urban areas when using TNO-MACC-II. However, simulations showed similar performances of both emission datasets in terms of air quality. Modelled NO2 concentrations were similar between both datasets at the background stations, although TNO-MACC-II presented lower underestimations due to differences in industrial, other mobile sources and residential emissions. At Madrid urban stations NO2 was significantly underestimated in both cases despite the fact that HERMESv2.0 estimates traffic emissions using a more local information and detailed methodology. This NO2 underestimation problem was not found in Barcelona due to the influence of international shipping emissions located in the coastline. An inadequate characterization of some TNO-MACC-II's point sources led to high SO2 biases at industrial stations, especially in northwest Spain where large facilities are grouped. In general, surface O3 was overestimated regardless of the emission dataset used, depicting the problematic of CMAQ on overestimating low ozone at night. On the other hand, modelled PM10 concentrations were less underestimated in urban areas when applying HERMESv2.0 due to the inclusion of road dust

  13. Comparison of EPA (Environmental Protection Agency) test house data with predictions of an indoor-air-quality model

    SciTech Connect

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

    1988-07-01

    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 user. On-screen graphical output is provided. The model estimates the effects of heating, ventilation, and air conditioning (HVAC), air cleaning, room-to-room air movement, and natural ventilation on pollutant concentrations. Experiments conducted in the EPA test house using moth crystal cakes for model verification are described. The agreement between small chamber emission factors, model predictions, and test house data is very good. Predicted weight loss of the moth crystal cakes was within 5% of the measured weight loss. Predicted room concentrations of p-dichlorobenzene are within 20% of the measured values. Future directions for model development and experimental studies are discussed.

  14. Evaluation of COSMO-ART in the Framework of the Air Quality Model Evaluation International Initiative (AQMEII)

    NASA Astrophysics Data System (ADS)

    Giordano, Lea; Brunner, Dominik; Im, Ulas; Galmarini, Stefano

    2014-05-01

    The Air Quality Model Evaluation International Initiative (AQMEII) coordinated by the EC-JRC and US-EPA, promotes since 2008 research on regional air quality model evaluation across the atmospheric modelling communities of Europe and North America. AQMEII has now reached its Phase 2 that is dedicated to the evaluation of on-line coupled chemistry-meteorology models as opposed to Phase 1 where only off-line models were considered. At European level, AQMEII collaborates with the COST Action "European framework for on-line integrated air quality and meteorology modelling" (EuMetChem). All European groups participating in AQMEII performed simulations over the same spatial domain (Europe at a resolution of about 20 km) and using the same simulation strategy (e.g. no nudging allowed) and the same input data as much as possible. The initial and boundary conditions (IC/BC) were shared between all groups. Emissions were provided by the TNO-MACC database for anthropogenic emissions and the FMI database for biomass burning emissions. Chemical IC/BC data were taken from IFS-MOZART output, and meteorological IC/BC from the ECWMF global model. Evaluation data sets were collected by the Joint Research Center (JRC) and include measurements from surface in situ networks (AirBase and EMEP), vertical profiles from ozone sondes and aircraft (MOZAIC), and remote sensing (AERONET, satellites). Since Phase 2 focuses on on-line coupled models, a special effort is devoted to the detailed speciation of particulate matter components, with the goal of studying feedback processes. For the AQMEII exercise, COSMO-ART has been run with 40 levels of vertical resolution, and a chemical scheme that includes the SCAV module of Knote and Brunner (ACP 2013) for wet-phase chemistry and the SOA treatment according to VBS (volatility basis set) approach (Athanasopoulou et al., ACP 2013). The COSMO-ART evaluation shows that, next to a good performance in the meteorology, the gas phase chemistry is well

  15. Constraining Ammonia in Air Quality Models with Remote Sensing Observations and Inverse Modeling

    NASA Astrophysics Data System (ADS)

    Zhu, Liye

    Ammonia is an important species in the atmosphere as it contributes to air pollution, climate change and environmental health. Ammonia emissions are known to be primarily from agricultural sources, however there is persistent uncertainty in the magnitudes and seasonal trends of these sources, as ammonia has not traditionally been routinely monitored. The first detection of boundary layer ammonia from space by the NASA Tropospheric Emissions Spectrometer (TES) satellite has provided an exciting new means of reducing this uncertainty. In this thesis, I explore how forward and inverse modeling can be used with satellite observations to constrain ammonia emissions. Model simulations are used to build and validate the TES ammonia retrieval product. TES retrievals are then used to characterize global ammonia distributions and model estimates. Correlations between ammonia and carbon monoxide, observed simultaneously by TES, provide additional insight into observed and modeled ammonia from biomass burning. Next, through inverse modeling, I show that ammonia emissions are broadly underestimated throughout the U.S., particularly in the West. Optimized model simulations capture the range and variability of in-situ observation in April and October, while estimates in July are biased high. To understand these adjustments, several aspects of the retrieval are considered, such as spatial and temporal sampling biases. These investigations lead to revisions of fundamental aspects of how ammonia emissions are modeled, such as the diurnal variability of livestock ammonia emissions. While this improves comparison to hourly in situ measurements in the SE U.S., ammonia concentrations decrease throughout the globe, up to 17 ppb in India and Southeastern China. Lastly, the bi-directional air-surface exchange of ammonia is implemented for the first time in a global model and its adjoint. Ammonia bi-directional exchange generally increases ammonia gross emissions (10.9%) and surface

  16. Development and Evaluation of Land-Use Regression Models Using Modeled Air Quality Concentrations

    EPA Science Inventory

    Abstract Land-use regression (LUR) models have emerged as a preferred methodology for estimating individual exposure to ambient air pollution in epidemiologic studies in absence of subject-specific measurements. Although there is a growing literature focused on LUR evaluation, fu...

  17. 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

    2005-05-13

    This second annual report summarizes the research performed from 17 April 2004 through 16 April 2005. Major portions of the research in several of the project's current eight tasks have been completed. We have successfully developed the meteorological inputs using the best possible modeling configurations, resulting in improved representation of atmospheric processes. The development of the variable-grid-resolution emissions model, SMOKE-VGR, is also completed. The development of the MAQSIP-VGR has been completed and a test run was performed to ensure the functionality of this air quality model. Thus, the project is on schedule as planned. During the upcoming reporting period, we expect to perform the first MAQSIP-VGR simulations over the Houston-Galveston region to study the roles of the meteorology, offshore emissions, and chemistry-transport interactions that determine the temporal and spatial evolution of ozone and its precursors.

  18. EVALUATION OF THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL VERSION 4.5: UNCERTAINTIES AND SENSITIVITIES IMPACTING MODEL PERFORMANCE: PART I - OZONE

    EPA Science Inventory

    This study examines ozone (O3) predictions from the Community Multiscale Air Quality (CMAQ) model version 4.5 and discusses potential factors influencing the model results. Daily maximum 8-hr average O3 levels are largely underpredicted when observed O...

  19. Prediction of fire smoke exposure and air quality degradation: toward a high resolution coupled fire-atmosphere model

    NASA Astrophysics Data System (ADS)

    Mari, Céline; Strada, Susanna; Filippi, Jean-Baptiste; Bosseur, Frederic; Pialat, Xavier; Humberto Amorin, Jorge; Borrego, Carlos; Freitas, Saulo; Longo, Karla; Martins, Vera; Miranda, Ana Isabel; Monteiro, Alexandra; Paugam, Ronan

    2013-04-01

    Wildfires release significant amounts of trace gas and aerosols into the atmosphere. Firefighters are exposed to wildland fire smoke with adverse health effects. At larger scale, depending on meteorological conditions and fire characteristics, fire emissions can efficiently reduce air quality and visibility, even far away from emission sources. Uncertainties in fire emissions and fire plume dynamics are two important factors which substantially limit the capability of current models to predict smoke exposure and air quality degradation. A collaborative effort recently started in France to develop a coupled fire-atmosphere model based on the fire propagation model ForeFire, developed at the University of Corsica, and the mesoscale non-hydrostatic meteorological model Meso-NH, developed by the University of Toulouse and Meteo-France. ForeFire is a semi-physical model based on an analytical estimation of the rate of spread and an integration with a front tracking method. The fire model is used to provide gridded heating, water vapor and chemical fluxes at high temporal and spatial resolutions to Meso-NH. The coupled model was used in two configurations depending on the spatial resolution: with or without the feedback of the atmosphere on the fire propagation. At kilometric resolution, the model is used off-line to simulate two Mediterranean fires: an arson wildfire that burned in 2005 near Lancon-de-Provence, south-eastern France, and a well documented episode of the Lisbon 2003 fires (in collaboration with the University of Aveiro, Portugal). The question of the injection height is treated with an adaptation of the eddy-diffusivity/mass flux approach for convective boundary layer and compared to the 1D Plume Rise Model (developed at INPE) in contrasted meteorological scenarios. At higher resolution, the two-way coupled model is tested on idealized and real fire cases including ozone chemistry. Future required developments on surface emissions and combustion chemistry

  20. BaP (PAH) air quality modelling exercise over Zaragoza (Spain) using an adapted version of WRF-CMAQ model.

    PubMed

    San José, Roberto; Pérez, Juan Luis; Callén, María Soledad; López, José Manuel; Mastral, Ana

    2013-12-01

    Benzo(a)pyrene (BaP) is one of the most dangerous PAH due to its high carcinogenic and mutagenic character. Because of this reason, the Directive 2004/107/CE of the European Union establishes a target value of 1 ng/m(3) of BaP in the atmosphere. In this paper, the main aim is to estimate the BaP concentrations in the atmosphere by using last generation of air quality dispersion models with the inclusion of the transport, scavenging and deposition processes for the BaP. The degradation of the particulated BaP by the ozone has been considered. The aerosol-gas partitioning phenomenon in the atmosphere is modelled taking into a count that the concentrations in the gas and the aerosol phases. If the pre-existing organic aerosol concentrations are zero gas/particle equilibrium is established. The model has been validated at local scale with data from a sampling campaign carried out in the area of Zaragoza (Spain) during 12 weeks.

  1. Field assessment of the Village Green Project: an autonomous community air quality monitoring system.

    PubMed

    Jiao, Wan; Hagler, Gayle S W; Williams, Ronald W; Sharpe, Robert N; Weinstock, Lewis; Rice, Joann

    2015-05-19

    Continuous, long-term, and time-resolved measurement of outdoor air pollution has been limited by logistical hurdles and resource constraints. Measuring air pollution in more places is desired to address community concerns regarding local air quality impacts related to proximate sources, to provide data in areas lacking regional air monitoring altogether, or to support environmental awareness and education. This study integrated commercially available technologies to create the Village Green Project (VGP), a durable, solar-powered air monitoring park bench that measures real-time ozone, PM2.5, and meteorological parameters. The data are wirelessly transmitted via cellular modem to a server, where automated quality checks take place before data are provided to the public nearly instantaneously. Over 5500 h of data were successfully collected during the first ten months of pilot testing in Durham, North Carolina, with about 13 days (5.5%) of downtime because of low battery power. Additional data loss (4-14% depending on the measurement) was caused by infrequent wireless communication interruptions and instrument maintenance. The 94.5% operational time via solar power was within 1.5% of engineering calculations using historical solar data for the location. The performance of the VGP was evaluated by comparing the data to nearby air monitoring stations operating federal equivalent methods (FEM), which exhibited good agreement with the nearest benchmark FEMs for hourly ozone (r(2) = 0.79) and PM2.5 (r(2) = 0.76).

  2. Field assessment of the Village Green Project: an autonomous community air quality monitoring system.

    PubMed

    Jiao, Wan; Hagler, Gayle S W; Williams, Ronald W; Sharpe, Robert N; Weinstock, Lewis; Rice, Joann

    2015-05-19

    Continuous, long-term, and time-resolved measurement of outdoor air pollution has been limited by logistical hurdles and resource constraints. Measuring air pollution in more places is desired to address community concerns regarding local air quality impacts related to proximate sources, to provide data in areas lacking regional air monitoring altogether, or to support environmental awareness and education. This study integrated commercially available technologies to create the Village Green Project (VGP), a durable, solar-powered air monitoring park bench that measures real-time ozone, PM2.5, and meteorological parameters. The data are wirelessly transmitted via cellular modem to a server, where automated quality checks take place before data are provided to the public nearly instantaneously. Over 5500 h of data were successfully collected during the first ten months of pilot testing in Durham, North Carolina, with about 13 days (5.5%) of downtime because of low battery power. Additional data loss (4-14% depending on the measurement) was caused by infrequent wireless communication interruptions and instrument maintenance. The 94.5% operational time via solar power was within 1.5% of engineering calculations using historical solar data for the location. The performance of the VGP was evaluated by comparing the data to nearby air monitoring stations operating federal equivalent methods (FEM), which exhibited good agreement with the nearest benchmark FEMs for hourly ozone (r(2) = 0.79) and PM2.5 (r(2) = 0.76). PMID:25905923

  3. An air quality data analysis system for interrelating effects, standards and needed source reductions: Part 11. A lognormal model relating human lung function decrease to O sub 3 exposure

    SciTech Connect

    Larsen, R.I.; McDonnell, W.F.; Horstman, D.H. )

    1991-04-01

    Forced expiratory volume in 1 second (FEV1) was measured in 121 men exercising while exposed to four O{sub 3} concentrations (0.0, 0.08, 0.10, and 0.12 ppm). A lognormal multiple linear regression model was fitted to their mean FEV1 measurements to predict REV1 percent decrease as a function of O{sub 3} concentration and exposure duration. The exercise level used was probably comparable to heavy manual labor. The longest O{sub 3} exposure studies was 6 h. Extrapolating cautiously to an 8-h workday of heavy manual labor, the model predicts that O{sub 3} concentrations of 0.08, 0.10, and 0.12 ppm would decrease FEV1 by 9, 15, and 20 percent, respectively.

  4. Estimating cost effectiveness of residential yard trees for improving air quality in Sacramento, California, using existing models

    SciTech Connect

    Nowak, David J.; Cardelino, C.A.; Rao, S.T.; Taha, Haider

    1998-10-05

    This paper presents results from energy, meteorological, and photochemical (air quality) modeling for the Los Angeles Basin, one of the largest and smoggiest urban regions in the U.S. and the world. Our simulations suggest that by mitigating urban heat islands, savings of 5 to 10 percent in peak utility load may be possible. In addition, heat island mitigation can reduce smog formation by 10-20 percent in summer, which is as effective as controlling emissions from all mobile sources in the region. For a typical late-August episode, our simulations suggest that implementing cool cities in the Los Angeles Basin would have a net effect of reducing ozone concentrations. Peak concentrations at 3 pm decrease by up to 7 percent (from 220 down to 205 ppb) while the total ozone mass in the mixed layer decreases by up to 460 metric tons (a decrease of 4.7 percent). Largest reductions in concentration at 3 pm are on the order of 50 ppb whereas the largest increases are on the order of 20 ppb. With respect to the National Ambient Air Quality Standard, domain-wide population-weighted exceedance exposure to ozone decreases by up to 20 percent during peak afternoon hours and by up to 10 percent during the daytime.

  5. AirNow Information Management System - Global Earth Observation System of Systems Data Processor for Real-Time Air Quality Data Products

    NASA Astrophysics Data System (ADS)

    Haderman, M.; Dye, T. S.; White, J. E.; Dickerson, P.; Pasch, A. N.; Miller, D. S.; Chan, A. C.

    2012-12-01

    Built upon the success of the U.S. Environmental Protection Agency's (EPA) AirNow program (www.AirNow.gov), the AirNow-International (AirNow-I) system contains an enhanced suite of software programs that process and quality control real-time air quality and environmental data and distribute customized maps, files, and data feeds. The goals of the AirNow-I program are similar to those of the successful U.S. program and include fostering the exchange of environmental data; making advances in air quality knowledge and applications; and building a community of people, organizations, and decision makers in environmental management. In 2010, Shanghai became the first city in China to run this state-of-the-art air quality data management and notification system. AirNow-I consists of a suite of modules (software programs and schedulers) centered on a database. One such module is the Information Management System (IMS), which can automatically produce maps and other data products through the use of GIS software to provide the most current air quality information to the public. Developed with Global Earth Observation System of Systems (GEOSS) interoperability in mind, IMS is based on non-proprietary standards, with preference to formal international standards. The system depends on data and information providers accepting and implementing a set of interoperability arrangements, including technical specifications for collecting, processing, storing, and disseminating shared data, metadata, and products. In particular, the specifications include standards for service-oriented architecture and web-based interfaces, such as a web mapping service (WMS), web coverage service (WCS), web feature service (WFS), sensor web services, and Really Simple Syndication (RSS) feeds. IMS is flexible, open, redundant, and modular. It also allows the merging of data grids to create complex grids that show comprehensive air quality conditions. For example, the AirNow Satellite Data Processor

  6. Modeling Urban Air Quality in the Berlin-Brandenburg Region: Evaluation of a WRF-Chem Setup

    NASA Astrophysics Data System (ADS)

    Kuik, F.; Churkina, G.; Butler, T. M.; Lauer, A.; Mar, K. A.

    2015-12-01

    Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenging issue, especially in urban areas. For studying air quality in the Berlin-Brandenburg region of Germany the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014 (incl. black carbon, VOCs as well as mobile measurements of particle size distribution and particle mass). The model setup includes 3 nested domains with horizontal resolutions of 15km, 3km, and 1km, online biogenic emissions using MEGAN 2.0, and anthropogenic emissions from the TNO-MACC-II inventory. This work serves as a basis for future studies on different aspects of air pollution in the Berlin-Brandenburg region, including how heat waves affect emissions of biogenic volatile organic compounds (BVOC) from urban vegetation (summer 2006) and the impact of selected traffic measures on air quality in the Berlin-Brandenburg area (summer 2014). The model represents the meteorology as observed in the region well for both periods. An exception is the heat wave period in 2006, where the temperature simulated with 3km and 1km resolutions is biased low by around 2°C for urban built-up stations. First results of simulations with chemistry show that, on average, WRF-Chem simulates concentrations of O3 well. However, the 8 hr maxima are underestimated, and the minima are overestimated. While NOx daily means are modeled reasonably well for urban stations, they are overestimated for suburban stations. PM10 concentrations are underestimated by the model. The biases and correlation coefficients of simulated O3, NOx, and PM10 in comparison to surface observations do not show improvements for the 1km domain in comparison to the 3km domain. To improve the model performance of the 1km domain we will include an

  7. Correlating MODIS aerosol optical thickness data with ground-based PM 2.5 observations across Texas for use in a real-time air quality prediction system

    NASA Astrophysics Data System (ADS)

    Hutchison, Keith D.; Smith, Solar; Faruqui, Shazia J.

    Investigations have been conducted at the Center for Space Research (CSR) into approaches to correlate MODIS aerosol optical thickness (AOT) values with ground-based, PM 2.5 observations made at continuous air monitoring station locations operated by the Texas Commission on Environmental Quality (TCEQ). These correlations are needed to more fully utilize real-time MODIS AOT analyses generated at CSR in operational air quality forecasts issued by TCEQ using a trajectory-based forecast model developed by NASA. Initial analyses of two data sets collected during 3 months in 2003 and all of 2004 showed linear correlations in the 0.4-0.5 range in the data collected over Texas. Stronger correlations (exceeding 0.9) were obtained by averaging these same data over longer timescales but this approach is considered unsuitable for use in issuing air quality forecasts. Peculiarities in the MODIS AOT analyses, referred to as hot spots, were recognized while attempting to improve these correlations. It is demonstrated that hot spots are possible when pixels that contain surface water are not detected and removed from the AOT retrieval algorithms. An approach to reduce the frequency of hot spots in AOT analyses over Texas is demonstrated by tuning thresholds used to detect inland water surfaces and remove pixels that contain them from the analysis. Finally, the potential impact of hot spots on MODIS AOT-PM 2.5 correlations is examined through the analysis of a third data set that contained sufficient levels of aerosols to mask inland water surfaces from the AOT algorithms. In this case, significantly stronger correlations, that exceed the 0.9 value considered suitable for use in a real-time air quality prediction system, were observed between the MODIS AOT observations and ground-based PM 2.5 measurements.

  8. Indoor Air Quality Manual.

    ERIC Educational Resources Information Center

    Baldwin Union Free School District, NY.

    This manual identifies ways to improve a school's indoor air quality (IAQ) and discusses practical actions that can be carried out by school staff in managing air quality. The manual includes discussions of the many sources contributing to school indoor air pollution and the preventive planning for each including renovation and repair work,…

  9. Air Dispersion Modeling for the INL Application for a Synthetic Minor Sitewide Air Quality Permit to Construct with a Facility Emission Cap Component

    SciTech Connect

    Sondrup, Andrus Jeffrey

    2015-10-01

    The Department of Energy Idaho Operations Office (DOE-ID) is applying for a synthetic minor, Sitewide, air quality permit to construct (PTC) with a facility emission cap (FEC) component from the Idaho Department of Environmental Quality (DEQ) for Idaho National Laboratory (INL) to limit its potential to emit to less than major facility limits for criteria air pollutants (CAPs) and hazardous air pollutants (HAPs) regulated under the Clean Air Act. This document is supplied as an appendix to the application, Idaho National Laboratory Application for a Synthetic Minor Sitewide Air Quality Permit to Construct with a Facility Emissions Cap Component, hereafter referred to as “permit application” (DOE-ID 2015). Air dispersion modeling was performed as part of the permit application process to demonstrate pollutant emissions from the INL will not cause a violation of any ambient air quality standards. This report documents the modeling methodology and results for the air dispersion impact analysis. All CAPs regulated under Section 109 of the Clean Air Act were modeled with the exception of lead (Pb) and ozone, which are not required to be modeled by DEQ. Modeling was not performed for toxic air pollutants (TAPs) as uncontrolled emissions did not exceed screening emission levels for carcinogenic and non-carcinogenic TAPs. Modeling for CAPs was performed with the EPA approved AERMOD dispersion modeling system (Version 14134) (EPA 2004a) and five years (2000-2004) of meteorological data. The meteorological data set was produced with the companion AERMET model (Version 14134) (EPA 2004b) using surface data from the Idaho Falls airport, and upper-air data from Boise International Airport supplied by DEQ. Onsite meteorological data from the Grid 3 Mesonet tower located near the center of the INL (north of INTEC) and supplied by the local National Oceanic and Atmospheric Administration (NOAA) office was used for surface wind directions and wind speeds. Surface data (i

  10. Linking Agricultural Crop Management and Air Quality Models for Regional to National-Scale Nitrogen Assessments

    EPA Science Inventory

    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 le...

  11. Modelling the emissions from ships in ports and their impact on air quality in the metropolitan area of Hamburg

    NASA Astrophysics Data System (ADS)

    Ramacher, Martin; Karl, Matthias; Aulinger, Armin; Bieser, Johannes; Matthias, Volker; Quante, Markus

    2016-04-01

    Exhaust emissions from shipping contribute significantly to the anthropogenic burden of air pollutants such as nitrogen oxides (NOX) and particulate matter (PM). Ships emit not only when sailing on open sea, but also when approaching harbors, during port manoeuvers and at berth to produce electricity and heat for the ship's operations. This affects the population of harbor cities because long-term exposure to PM and NOX has significant effects on human health. The European Union has therefore has set air quality standards for air pollutants. Many port cities have problems meeting these standards. The port of Hamburg with around 10.000 ship calls per year is Germany's largest seaport and Europe's second largest container port. Air quality standard reporting in Hamburg has revealed problems in meeting limits for NO2 and PM10. The amount and contribution of port related ship emissions (38% for NOx and 17% for PM10) to the overall emissions in the metropolitan area in 2005 [BSU Hamburg (2012): Luftreinhalteplan für Hamburg. 1. Fortschreibung 2012] has been modelled with a bottom up approach by using statistical data of ship activities in the harbor, technical vessel information and specific emission algorithms [GAUSS (2008): Quantifizierung von gasförmigen Emissionen durch Maschinenanlagen der Seeschiffart an der deutschen Küste]. However, knowledge about the spatial distribution of the harbor ship emissions over the city area is crucial when it comes to air quality standards and policy decisions to protect human health. Hence, this model study examines the spatial distribution of harbor ship emissions (NOX, PM10) and their deposition in the Hamburg metropolitan area. The transport and chemical transformation of atmospheric pollutants is calculated with the well-established chemistry transport model TAPM (The Air Pollution Model). TAPM is a three-dimensional coupled prognostic meteorological and air pollution model with a condensed chemistry scheme including

  12. 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 Technical Reports Server (NTRS)

    Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; 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, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. 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 spatial growth modeling (SGM) 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, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat

  13. Hvac systems as a tool in controlling indoor air quality: A literature review. Final report, May-August 1993

    SciTech Connect

    Samfield, M.M.

    1995-12-01

    The report gives results of a review of literature on the use of heating, ventilation, and air-conditioning (HVAC) systems to control indoor air quality (IAQ). One conclusion of the review is that HVAC systems very often contribute to the indoor air pollution because of (1) poor system maintenance, (2) overcrowding or the introduction of new pollution-generating sources with buildings, and (3) the location of outdoor air near ambient pollution sources. Another conclusion is that failure to trade off between energy conservation and employee productivity may result in increased IAQ problems. The report contents are based on literature survey covering the years 1988 through 1993, involving 60 references, 32 of which are cited in the report.

  14. Computer software and hardware requirements for a CTDMPLUS air quality modeling study

    SciTech Connect

    Karpovich, R.A.; Holland, D.; Barone, J.B.; Eichinger, M.

    1994-12-31

    The Complex Terrain Dispersion Model (CTDMPLUS) is an atmospheric dispersion model for sources that are located in complex terrain settings. The model requires detailed information about the meteorological conditions and topographic terrain features surrounding the source. The authors have completed a 1-year on-site meteorological data program using a 100-meter tower and a Doppler radar system (SODAR). This paper presents the steps required to process the on-site meteorological data and the hardware and software requirements necessary for regulatory use of CTDMPLUS (in conjunction with the Industrial Source Complex Short Term (ISCST) model). The paper also presents software and data sources that can be used to generate CTDMPLUS terrain and receptor input information.

  15. Air Quality Monitor

    NASA Technical Reports Server (NTRS)

    1996-01-01

    The Stak-Tracker CEM (Continuous Emission Monitor) Gas Analyzer is an air quality monitor capable of separating the various gases in a bulk exhaust stream and determining the amounts of individual gases present within the stream. The monitor is produced by GE Reuter- Stokes, a subsidiary of GE Corporate Research & Development Center. The Stak-Tracker uses a Langley Research Center software package which measures the concentration of a target gas by determining the degree to which molecules of that gas absorb an infrared beam. The system is environmental-friendly, fast and has relatively low installation and maintenance costs. It is applicable to gas turbines and various industries including glass, paper and cement.

  16. Observations and modeling of air quality trends over 1990-2010 across the Northern Hemisphere: China, the United States and Europe

    NASA Astrophysics Data System (ADS)

    Xing, J.; Mathur, R.; Pleim, J.; Hogrefe, C.; Gan, C.-M.; Wong, D. C.; Wei, C.; Gilliam, R.; Pouliot, G.

    2015-03-01

    Trends in air quality across the Northern Hemisphere over a 21-year period (1990-2010) were simulated using the Community Multiscale Air Quality (CMAQ) multiscale chemical transport model driven by meteorology from Weather Research and Forecasting (WRF) simulations and internally consistent historical emission inventories obtained from EDGAR. Thorough comparison with several ground observation networks mostly over Europe and North America was conducted to evaluate the model performance as well as the ability of CMAQ to reproduce the observed trends in air quality over the past 2 decades in three regions: eastern China, the continental United States and Europe. The model successfully reproduced the observed decreasing trends in SO2, NO2, 8 h O3 maxima, SO42- and elemental carbon (EC) in the US and Europe. However, the model fails to reproduce the decreasing trends in NO3- in the US, potentially pointing to uncertainties of NH3 emissions. The model failed to capture the 6-year trends of SO2 and NO2 in CN-API (China - Air Pollution Index) from 2005 to 2010, but reproduced the observed pattern of O3 trends shown in three World Data Centre for Greenhouse Gases (WDCGG) sites over eastern Asia. Due to the coarse spatial resolution employed in these calculations, predicted SO2 and NO2 concentrations are underestimated relative to all urban networks, i.e., US-AQS (US - Air Quality System; normalized mean bias (NMB) = -38% and -48%), EU-AIRBASE (European Air quality data Base; NMB = -18 and -54%) and CN-API (NMB = -36 and -68%). Conversely, at the rural network EU-EMEP (European Monitoring and Evaluation Programme), SO2 is overestimated (NMB from 4 to 150%) while NO2 is simulated well (NMB within ±15%) in all seasons. Correlations between simulated and observed O3 wintertime daily 8 h maxima (DM8) are poor compared to other seasons for all networks. Better correlation between simulated and observed SO42- was found compared to that for SO2. Underestimation of summer SO42- in

  17. Modelling aerosol-cloud-meteorology interaction: A case study with a fully coupled air quality model (GEM-MACH)

    NASA Astrophysics Data System (ADS)

    Gong, W.; Makar, P. A.; Zhang, J.; Milbrandt, J.; Gravel, S.; Hayden, K. L.; Macdonald, A. M.; Leaitch, W. R.

    2015-08-01

    A fully coupled on-line air quality forecast model, GEM-MACH, was used to study aerosol-cloud interactions for a case of an urban-industrial plume impacting stratocumulus. The aerosol effect on the cloud microphysics was achieved by the use of parameterization of cloud droplet nucleation predicted from the on-line size- and composition-resolved aerosols and coupled with a double-moment cloud microphysics parameterization. The model simulations with and without the on-line aerosol effect on cloud microphysics were compared and evaluated against in-situ aerosol and cloud observations from ICARTT 2004. Inclusion of the on-line aerosol interaction with cloud resulted in an increase in modelled cloud amount and cloud liquid water content (LWC) due to increased cloud droplet number concentration (Nd), a decrease in cloud droplet size and a reduction in warm precipitation. The modelled LWC and Nd agreed more closely with the observations when the on-line aerosol was allowed to affect the cloud than when aerosol effects on cloud were not explicitly simulated. The increased cloud amount due to the aerosol effects reduced the modelled downward shortwave radiative flux and air temperature at the surface, contributing to a decrease in ozone over the region of enhanced cloud and an increase in particle sulphate from an increased capacity for aqueous-phase production. Aerosol activation is shown to have a significant influence on the cloud microphysics and cloud processing of trace gases and aerosols. The importance of reasonable parameterization of cloud updraft speed is demonstrated.

  18. Accuracy and reliability of Chile's National Air Quality Information System for measuring particulate matter: Beta attenuation monitoring issue.

    PubMed

    Toro A, Richard; Campos, Claudia; Molina, Carolina; Morales S, Raul G E; Leiva-Guzmán, Manuel A

    2015-09-01

    A critical analysis of Chile's National Air Quality Information System (NAQIS) is presented, focusing on particulate matter (PM) measurement. This paper examines the complexity, availability and reliability of monitoring station information, the implementation of control systems, the quality assurance protocols of the monitoring station data and the reliability of the measurement systems in areas highly polluted by particulate matter. From information available on the NAQIS website, it is possible to confirm that the PM2.5 (PM10) data available on the site correspond to 30.8% (69.2%) of the total information available from the monitoring stations. There is a lack of information regarding the measurement systems used to quantify air pollutants, most of the available data registers contain gaps, almost all of the information is categorized as "preliminary information" and neither standard operating procedures (operational and validation) nor assurance audits or quality control of the measurements are reported. In contrast, events that cause saturation of the monitoring detectors located in northern and southern Chile have been observed using beta attenuation monitoring. In these cases, it can only be concluded that the PM content is equal to or greater than the saturation concentration registered by the monitors and that the air quality indexes obtained from these measurements are underestimated. This occurrence has been observed in 12 (20) public and private stations where PM2.5 (PM10) is measured. The shortcomings of the NAQIS data have important repercussions for the conclusions obtained from the data and for how the data are used. However, these issues represent opportunities for improving the system to widen its use, incorporate comparison protocols between equipment, install new stations and standardize the control system and quality assurance.

  19. Source apportionment of airborne particulate matter in Southeast Texas using a source-oriented 3D air quality model

    NASA Astrophysics Data System (ADS)

    Zhang, Hongliang; Ying, Qi

    2010-09-01

    A nested version of the source-oriented externally mixed UCD/CIT model was developed to study the source contributions to airborne particulate matter (PM) during a two-week long air quality episode during the Texas 2000 Air Quality Study (TexAQS 2000). Contributions to primary PM and secondary ammonium sulfate in the Houston-Galveston Bay (HGB) and Beaumont-Port Arthur (BPA) areas were determined. The predicted 24-h elemental carbon (EC), organic compounds (OC), sulfate, ammonium ion and primary PM 2.5 mass are in good agreement with filter-based observations. Predicted concentrations of hourly sulfate, ammonium ion, and primary OC from diesel and gasoline engines and biomass burning organic aerosol (BBOA) at La Porte, Texas agree well with measurements from an Aerodyne Aerosol Mass Spectrometer (AMS). The UCD/CIT model predicts that EC is mainly from diesel engines and majority of the primary OC is from internal combustion engines and industrial sources. Open burning contributes large fractions of EC, OC and primary PM 2.5 mass. Road dust, internal combustion engines and industries are the major sources of primary PM 2.5. Wildfire dominates the contributions to all primary PM components in areas near the fires. The predicted source contributions to primary PM are in general agreement with results from a chemical mass balance (CMB) model. Discrepancy between the two models suggests that further investigations on the industrial PM emissions are necessary. Secondary ammonium sulfate accounts for the majority of the secondary inorganic PM. Over 80% of the secondary sulfate in the 4 km domain is produced in upwind areas. Coal combustion is the largest source of sulfate. Ammonium ion is mainly from agriculture sources and contributions from gasoline vehicles are significant in urban areas.

  20. Potential significance of photoexcited NO2 on global air quality with the NMMB/BSC chemical transport model

    NASA Astrophysics Data System (ADS)

    Jorba, O.; Dabdub, D.; Blaszczak-Boxe, C.; PéRez, C.; Janjic, Z.; Baldasano, J. M.; Spada, M.; Badia, A.; GonçAlves, M.

    2012-07-01

    Atmospheric chemists have recently focused on the relevance of the NO2* + H2O → OH + HONO reaction to local air quality. This chemistry has been considered not relevant for the troposphere from known reaction rates until nowadays. New experiments suggested a rate constant of 1.7 × 10-13 cm3 molecule-1 s-1, which is an order of magnitude faster than the previously estimated upper limit of 1.2 × 10-14 cm3 molecule-1 s-1, determined by Crowley and Carl (1997). Using the new global model, NMMB/BSC Chemical Transport Model (NMMB/BSC-CTM), simulations are presented that assess the potential significance of this chemistry on global