Sample records for air-quality modeling system

  1. Towards the Next Generation Air Quality Modeling System ...

    EPA Pesticide Factsheets

    The community multiscale air quality (CMAQ) model of the U.S. Environmental Protection Agency is one of the most widely used air quality model worldwide; it is employed for both research and regulatory applications at major universities and government agencies for improving understanding of the formation and transport of air pollutants. It is noted, however, that air quality issues and climate change assessments need to be addressed globally recognizing the linkages and interactions between meteorology and atmospheric chemistry across a wide range of scales. Therefore, an effort is currently underway to develop the next generation air quality modeling system (NGAQM) that will be based on a global integrated meteorology and chemistry system. The model for prediction across scales-atmosphere (MPAS-A), a global fully compressible non-hydrostatic model with seamlessly refined centroidal Voronoi grids, has been chosen as the meteorological driver of this modeling system. The initial step of adapting MPAS-A for the NGAQM was to implement and test the physics parameterizations and options that are preferred for retrospective air quality simulations (see the work presented by R. Gilliam, R. Bullock, and J. Herwehe at this workshop). The next step, presented herein, would be to link the chemistry from CMAQ to MPAS-A to build a prototype for the NGAQM. Furthermore, the techniques to harmonize transport processes between CMAQ and MPAS-A, methodologies to connect the chemis

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

    EPA Science Inventory

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

  3. Development of the Next Generation Air Quality Modeling System

    EPA Science Inventory

    A next generation air quality modeling system is being developed at the U.S. EPA to enable modeling of air quality from global to regional to (eventually) local scales. We envision that the system will have three configurations: 1. Global meteorology with seamless mesh refinemen...

  4. Community Multiscale Air Quality Modeling System (CMAQ)

    EPA Pesticide Factsheets

    CMAQ is a computational tool used for air quality management. It models air pollutants including ozone, particulate matter and other air toxics to help determine optimum air quality management scenarios.

  5. A new air quality monitoring and early warning system: Air quality assessment and air pollutant concentration prediction.

    PubMed

    Yang, Zhongshan; Wang, Jian

    2017-10-01

    Air pollution in many countries is worsening with industrialization and urbanization, resulting in climate change and affecting people's health, thus, making the work of policymakers more difficult. It is therefore both urgent and necessary to establish amore scientific air quality monitoring and early warning system to evaluate the degree of air pollution objectively, and predict pollutant concentrations accurately. However, the integration of air quality assessment and air pollutant concentration prediction to establish an air quality system is not common. In this paper, we propose a new air quality monitoring and early warning system, including an assessment module and forecasting module. In the air quality assessment module, fuzzy comprehensive evaluation is used to determine the main pollutants and evaluate the degree of air pollution more scientifically. In the air pollutant concentration prediction module, a novel hybridization model combining complementary ensemble empirical mode decomposition, a modified cuckoo search and differential evolution algorithm, and an Elman neural network, is proposed to improve the forecasting accuracy of six main air pollutant concentrations. To verify the effectiveness of this system, pollutant data for two cities in China are used. The result of the fuzzy comprehensive evaluation shows that the major air pollutants in Xi'an and Jinan are PM 10 and PM 2.5 respectively, and that the air quality of Xi'an is better than that of Jinan. The forecasting results indicate that the proposed hybrid model is remarkably superior to all benchmark models on account of its higher prediction accuracy and stability. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Air Quality Modeling | Air Quality Planning & Standards | US ...

    EPA Pesticide Factsheets

    2016-06-08

    The basic mission of the Office of Air Quality Planning and Standards is to preserve and improve the quality of our nation's air. One facet of accomplishing this goal requires that new and existing air pollution sources be modeled for compliance with the National Ambient Air Quality Standards (NAAQS).

  7. 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

  8. 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...

  9. Human-model hybrid Korean air quality forecasting system.

    PubMed

    Chang, Lim-Seok; Cho, Ara; Park, Hyunju; Nam, Kipyo; Kim, Deokrae; Hong, Ji-Hyoung; Song, Chang-Keun

    2016-09-01

    The Korean national air quality forecasting system, consisting of the Weather Research and Forecasting, the Sparse Matrix Operator Kernel Emissions, and the Community Modeling and Analysis (CMAQ), commenced from August 31, 2013 with target pollutants of particulate matters (PM) and ozone. Factors contributing to PM forecasting accuracy include CMAQ inputs of meteorological field and emissions, forecasters' capacity, and inherent CMAQ limit. Four numerical experiments were conducted including two global meteorological inputs from the Global Forecast System (GFS) and the Unified Model (UM), two emissions from the Model Intercomparison Study Asia (MICS-Asia) and the Intercontinental Chemical Transport Experiment (INTEX-B) for the Northeast Asia with Clear Air Policy Support System (CAPSS) for South Korea, and data assimilation of the Monitoring Atmospheric Composition and Climate (MACC). Significant PM underpredictions by using both emissions were found for PM mass and major components (sulfate and organic carbon). CMAQ predicts PM2.5 much better than PM10 (NMB of PM2.5: -20~-25%, PM10: -43~-47%). Forecasters' error usually occurred at the next day of high PM event. Once CMAQ fails to predict high PM event the day before, forecasters are likely to dismiss the model predictions on the next day which turns out to be true. The best combination of CMAQ inputs is the set of UM global meteorological field, MICS-Asia and CAPSS 2010 emissions with the NMB of -12.3%, the RMSE of 16.6μ/m(3) and the R(2) of 0.68. By using MACC data as an initial and boundary condition, the performance skill of CMAQ would be improved, especially in the case of undefined coarse emission. A variety of methods such as ensemble and data assimilation are considered to improve further the accuracy of air quality forecasting, especially for high PM events to be comparable to for all cases. The growing utilization of the air quality forecast induced the public strongly to demand that the accuracy of the

  10. 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

  11. Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1

    EPA Science Inventory

    The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was ...

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

    EPA Science Inventory

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

  13. 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

  14. 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...

  15. Air Quality Modeling

    EPA Pesticide Factsheets

    In this technical support document (TSD) EPA describes the air quality modeling performed to support the Environmental Protection Agency’s Transport Rule proposal (now known as the Cross-State Air Pollution Rule).

  16. Air Quality System (AQS)

    EPA Pesticide Factsheets

    The Air Quality System (AQS) database contains measurements of air pollutant concentrations from throughout the United States and its territories. The measurements include both criteria air pollutants and hazardous air pollutants.

  17. Air quality early-warning system for cities in China

    NASA Astrophysics Data System (ADS)

    Xu, Yunzhen; Yang, Wendong; Wang, Jianzhou

    2017-01-01

    Air pollution has become a serious issue in many developing countries, especially in China, and could generate adverse effects on human beings. Air quality early-warning systems play an increasingly significant role in regulatory plans that reduce and control emissions of air pollutants and inform the public in advance when harmful air pollution is foreseen. However, building a robust early-warning system that will improve the ability of early-warning is not only a challenge but also a critical issue for the entire society. Relevant research is still poor in China and cannot always satisfy the growing requirements of regulatory planning, despite the issue's significance. Therefore, in this paper, a hybrid air quality early-warning system was successfully developed, composed of forecasting and evaluation. First, a hybrid forecasting model was proposed as an important part of this system based on the theory of "decomposition and ensemble" and combined with the advanced data processing technique, support vector machine, the latest bio-inspired optimization algorithm and the leave-one-out strategy for deciding weights. Afterwards, to intensify the research, fuzzy evaluation was performed, which also plays an indispensable role in the early-warning system. The forecasting model and fuzzy evaluation approaches are complementary. Case studies using daily air pollution concentrations of six air pollutants from three cities in China (i.e., Taiyuan, Harbin and Chongqing) are used as examples to evaluate the efficiency and effectiveness of the developed air quality early-warning system. Experimental results demonstrate that both the accuracy and the effectiveness of the developed system are greatly superior for air quality early warning. Furthermore, the application of forecasting and evaluation enables the informative and effective quantification of future air quality, offering a significant advantage, and can be employed to develop rapid air quality early-warning systems.

  18. 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...

  19. 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.

  20. Development of the Next Generation Air Quality Modeling System (20th Joint Conference on the Applications of Air Pollution Meteorology with the A&WMA)

    EPA Science Inventory

    A next generation air quality modeling system is being developed at the U.S. EPA to enable modeling of air quality from global to regional to (eventually) local scales. We envision that the system will have three configurations: 1. Global meteorology with seamless mesh refinemen...

  1. 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...

  2. 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...

  3. Community Multiscale Air Quality Model

    EPA Science Inventory

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

  4. 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...

  5. Reduced-form air quality modeling for community-scale ...

    EPA Pesticide Factsheets

    Transportation plays an important role in modern society, but its impact on air quality has been shown to have significant adverse effects on public health. Numerous reviews (HEI, CDC, WHO) summarizing findings of hundreds of studies conducted mainly in the last decade, conclude that exposures to traffic emissions near roads are a public health concern. The Community LINE Source Model (C-LINE) is a web-based model designed to inform the community user of local air quality impacts due to roadway vehicles in their region of interest using a simplified modeling approach. Reduced-form air quality modeling is a useful tool for examining what-if scenarios of changes in emissions, such as those due to changes in traffic volume, fleet mix, or vehicle speed. Examining various scenarios of air quality impacts in this way can identify potentially at-risk populations located near roadways, and the effects that a change in traffic activity may have on them. C-LINE computes dispersion of primary mobile source pollutants using meteorological conditions for the region of interest and computes air-quality concentrations corresponding to these selected conditions. C-LINE functionality has been expanded to model emissions from port-related activities (e.g. ships, trucks, cranes, etc.) in a reduced-form modeling system for local-scale near-port air quality analysis. This presentation describes the Community modeling tools C-LINE and C-PORT that are intended to be used by local gove

  6. Spatial Allocator for air quality modeling

    EPA Pesticide Factsheets

    The Spatial Allocator is a set of tools that helps users manipulate and generate data files related to emissions and air quality modeling without requiring the use of a commercial Geographic Information System.

  7. 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...

  8. 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 ...

  9. Air Quality System (AQS) Metadata

    EPA Pesticide Factsheets

    The U.S. Environmental Protection Agency compiles air quality monitoring data in the Air Quality System (AQS). Ambient air concentrations are measured at a national network of more than 4,000 monitoring stations and are reported by state, local, and tribal

  10. 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...

  11. 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...

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

    EPA Science Inventory

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

  13. 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-...

  14. 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

  15. Innovations in projecting emissions for air quality modeling

    EPA Science Inventory

    Air quality modeling is used in setting air quality standards and in evaluating their costs and benefits. Historically, modeling applications have projected emissions and the resulting air quality only 5 to 10 years into the future. Recognition that the choice of air quality mana...

  16. 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...

  17. 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...

  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. 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).

  20. 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...

  1. 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

  2. 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

  3. 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]....

  4. Air Quality Forecasts Using the NASA GEOS Model

    NASA Technical Reports Server (NTRS)

    Keller, Christoph A.; Knowland, K. Emma; Nielsen, Jon E.; Orbe, Clara; Ott, Lesley; Pawson, Steven; Saunders, Emily; Duncan, Bryan; Follette-Cook, Melanie; Liu, Junhua; hide

    2018-01-01

    We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). The resolution of the forecasts is the highest resolution compared to current, publically-available global composition forecasts. Evaluation and validation of modeled trace gases and aerosols compared to surface and satellite observations will be presented for constituents relative to health air quality standards. Comparisons of modeled trace gases and aerosols against satellite observations show that the model produces realistic concentrations of atmospheric constituents in the free troposphere. Model comparisons against surface observations highlight the model's capability to capture the diurnal variability of air pollutants under a variety of meteorological conditions. The GEOS-5 composition forecasting system offers a new tool for scientists and the public health community, and is being developed jointly with several government and non-profit partners. Potential applications include air quality warnings, flight campaign planning and exposure studies using the archived analysis fields.

  5. Four-dimensional evaluation of regional air quality models

    EPA Science Inventory

    We present highlights of the results obtained in the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3). Activities in AQMEII3 were focused on evaluating the performance of global, hemispheric and regional modeling systems over Europe and North Ame...

  6. An integrated bi-level optimization model for air quality management of Beijing's energy system under uncertainty.

    PubMed

    Jin, S W; Li, Y P; Nie, S

    2018-05-15

    In this study, an interval chance-constrained bi-level programming (ICBP) method is developed for air quality management of municipal energy system under uncertainty. ICBP can deal with uncertainties presented as interval values and probability distributions as well as examine the risk of violating constraints. Besides, a leader-follower decision strategy is incorporated into the optimization process where two decision makers with different goals and preferences are involved. To solve the proposed model, a bi-level interactive algorithm based on satisfactory degree is introduced into the decision-making processes. Then, an ICBP based energy and environmental systems (ICBP-EES) model is formulated for Beijing, in which air quality index (AQI) is used for evaluating the integrated air quality of multiple pollutants. Result analysis can help different stakeholders adjust their tolerances to achieve the overall satisfaction of EES planning for the study city. Results reveal that natural gas is the main source for electricity-generation and heating that could lead to a potentially increment of imported energy for Beijing in future. Results also disclose that PM 10 is the major contributor to AQI. These findings can help decision makers to identify desired alternatives for EES planning and provide useful information for regional air quality management under uncertainty. Copyright © 2018 Elsevier B.V. All rights reserved.

  7. Innovations in projecting emissions for air quality modeling ...

    EPA Pesticide Factsheets

    Air quality modeling is used in setting air quality standards and in evaluating their costs and benefits. Historically, modeling applications have projected emissions and the resulting air quality only 5 to 10 years into the future. Recognition that the choice of air quality management strategy has climate change implications is encouraging longer modeling time horizons. However, for multi-decadal time horizons, many questions about future conditions arise. For example, will current population, economic, and land use trends continue, or will we see shifts that may alter the spatial and temporal pattern of emissions? Similarly, will technologies such as building-integrated solar photovoltaics, battery storage, electric vehicles, and CO2 capture emerge as disruptive technologies - shifting how we produce and use energy - or will these technologies achieve only niche markets and have little impact? These are some of the questions that are being evaluated by researchers within the U.S. EPA’s Office of Research and Development. In this presentation, Dr. Loughlin will describe a range of analytical approaches that are being explored. These include: (i) the development of alternative scenarios of the future that can be used to evaluate candidate management strategies over wide-ranging conditions, (ii) the application of energy system models to project emissions decades into the future and to assess the environmental implications of new technologies, (iii) and methodo

  8. National strategic plan: modeling and data systems for wildland fire and air quality.

    Treesearch

    David V. Sandberg; Colin C. Hardy; Roger D. Ottmar; J.A. Kendall Snell; Ann Acheson; Janice L. Peterson; Paula Seamon; Peter Lahm; Dale Wade

    1999-01-01

    This strategic plan is a technical discussion of the implementation and development of models and data systems used to manage the air quality impacts of wildland and prescribed fires. Strategies and priorities in the plan were generated by the Express Team (chartered by the National Wildfire Coordinating Group) and a diverse group of 86 subject matter experts who...

  9. Air Quality Response Modeling for Decision Support | Science ...

    EPA Pesticide Factsheets

    Air quality management relies on photochemical models to predict the responses of pollutant concentrations to changes in emissions. Such modeling is especially important for secondary pollutants such as ozone and fine particulate matter which vary nonlinearly with changes in emissions. Numerous techniques for probing pollutant-emission relationships within photochemical models have been developed and deployed for a variety of decision support applications. However, atmospheric response modeling remains complicated by the challenge of validating sensitivity results against observable data. This manuscript reviews the state of the science of atmospheric response modeling as well as efforts to characterize the accuracy and uncertainty of sensitivity results. The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being use

  10. 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

  11. 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.

  12. 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.

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

    EPA Science Inventory

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

  14. 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.

  15. Canadian Operational Air Quality Forecasting Systems: Status, Recent Progress, and Challenges

    NASA Astrophysics Data System (ADS)

    Pavlovic, Radenko; Davignon, Didier; Ménard, Sylvain; Munoz-Alpizar, Rodrigo; Landry, Hugo; Beaulieu, Paul-André; Gilbert, Samuel; Moran, Michael; Chen, Jack

    2017-04-01

    ECCC's Canadian Meteorological Centre Operations (CMCO) division runs a number of operational air quality (AQ)-related systems that revolve around the Regional Air Quality Deterministic Prediction System (RAQDPS). The RAQDPS generates 48-hour AQ forecasts and outputs hourly concentration fields of O3, PM2.5, NO2, and other pollutants twice daily on a North-American domain with 10-km horizontal grid spacing and 80 vertical levels. A closely related AQ forecast system with near-real-time wildfire emissions, known as FireWork, has been run by CMCO during the Canadian wildfire season (April to October) since 2014. This system became operational in June 2016. The CMCO`s operational AQ forecast systems also benefit from several support systems, such as a statistical post-processing model called UMOS-AQ that is applied to enhance forecast reliability at point locations with AQ monitors. The Regional Deterministic Air Quality Analysis (RDAQA) system has also been connected to the RAQDPS since February 2013, and hourly surface objective analyses are now available for O3, PM2.5, NO2, PM10, SO2 and, indirectly, the Canadian Air Quality Health Index. As of June 2015, another version of the RDAQA has been connected to FireWork (RDAQA-FW). For verification purposes, CMCO developed a third support system called Verification for Air QUality Models (VAQUM), which has a geospatial relational database core and which enables continuous monitoring of the AQ forecast systems' performance. Urban environments are particularly subject to AQ pollution. In order to improve the services offered, ECCC has recently been investing efforts to develop a high resolution air quality prediction capability for urban areas in Canada. In this presentation, a comprehensive description of the ECCC AQ systems will be provided, along with a discussion on AQ systems performance. Recent improvements, current challenges, and future directions of the Canadian operational AQ program will also be discussed.

  16. On Regional Modeling to Support Air Quality Policies

    EPA Science Inventory

    We examine the use of the Community Multiscale Air Quality (CMAQ) model in simulating the changes in the extreme values of air quality that are of interest to the regulatory agencies. Year-to-year changes in ozone air quality are attributable to variations in the prevailing mete...

  17. Combined comfort model of thermal comfort and air quality on buses in Hong Kong.

    PubMed

    Shek, Ka Wing; Chan, Wai Tin

    2008-01-25

    Air-conditioning settings are important factors in controlling the comfort of passengers on buses. The local bus operators control in-bus air quality and thermal environment by conforming to the prescribed levels stated in published standards. As a result, the settings are merely adjusted to fulfill the standards, rather than to satisfy the passengers' thermal comfort and air quality. Such "standard-oriented" practices are not appropriate; the passengers' preferences and satisfaction should be emphasized instead. Thus a "comfort-oriented" philosophy should be implemented to achieve a comfortable in-bus commuting environment. In this study, the achievement of a comfortable in-bus environment was examined with emphasis on thermal comfort and air quality. Both the measurement of physical parameters and subjective questionnaire surveys were conducted to collect practical in-bus thermal and air parameters data, as well as subjective satisfaction and sensation votes from the passengers. By analyzing the correlation between the objective and subjective data, a combined comfort models were developed. The models helped in evaluating the percentage of dissatisfaction under various combinations of passengers' sensation votes towards thermal comfort and air quality. An effective approach integrated the combined comfort model, hardware and software systems and the bus air-conditioning system could effectively control the transient in-bus environment. By processing and analyzing the data from the continuous monitoring system with the combined comfort model, air-conditioning setting adjustment commands could be determined and delivered to the hardware. This system adjusted air-conditioning settings depending on real-time commands along the bus journey. Therefore, a comfortable in-bus air quality and thermal environment could be achieved and efficiently maintained along the bus journey despite dynamic outdoor influences. Moreover, this model can help optimize air

  18. 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...

  19. 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...

  20. Development of visibility forecasting modeling framework for the Lower Fraser Valley of British Columbia using Canada's Regional Air Quality Deterministic Prediction System.

    PubMed

    So, Rita; Teakles, Andrew; Baik, Jonathan; Vingarzan, Roxanne; Jones, Keith

    2018-05-01

    Visibility degradation, one of the most noticeable indicators of poor air quality, can occur despite relatively low levels of particulate matter when the risk to human health is low. The availability of timely and reliable visibility forecasts can provide a more comprehensive understanding of the anticipated air quality conditions to better inform local jurisdictions and the public. This paper describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada's operational Regional Air Quality Deterministic Prediction System (RAQDPS) for the Lower Fraser Valley of British Columbia. A baseline model (GM-IMPROVE) was constructed using the revised IMPROVE algorithm based on unprocessed forecasts from the RAQDPS. Three additional prototypes (UMOS-HYB, GM-MLR, GM-RF) were also developed and assessed for forecast performance of up to 48 hr lead time during various air quality and meteorological conditions. Forecast performance was assessed by examining their ability to provide both numerical and categorical forecasts in the form of 1-hr total extinction and Visual Air Quality Ratings (VAQR), respectively. While GM-IMPROVE generally overestimated extinction more than twofold, it had skill in forecasting the relative species contribution to visibility impairment, including ammonium sulfate and ammonium nitrate. Both statistical prototypes, GM-MLR and GM-RF, performed well in forecasting 1-hr extinction during daylight hours, with correlation coefficients (R) ranging from 0.59 to 0.77. UMOS-HYB, a prototype based on postprocessed air quality forecasts without additional statistical modeling, provided reasonable forecasts during most daylight hours. In terms of categorical forecasts, the best prototype was approximately 75 to 87% correct, when forecasting for a condensed three-category VAQR. A case study, focusing on a poor visual air quality yet low Air Quality Health Index episode

  1. Urban air quality measurements using a sensor-based system

    NASA Astrophysics Data System (ADS)

    Ródenas, Mila; Hernández, Daniel; Gómez, Tatiana; López, Ramón; Muñoz, Amalia

    2017-04-01

    Air pollution levels in urban areas have increased the interest, not only of the scientific community but also of the general public, and both at the regional and at the European level. This interest has run in parallel to the development of miniaturized sensors, which only since very recently are suitable for air quality measurements. Certainly, their small size and price allows them to be used as a network of sensors capable of providing high temporal and spatial frequency measurements to characterize an area or city and with increasing potential, under certain considerations, as a complement of conventional methods. Within the frame of the LIFE PHOTOCITYTEX project (use of photocatalytic textiles to help reducing air pollution), CEAM has developed a system to measure gaseous compounds of importance for urban air quality characterization. This system, which allows an autonomous power supply, uses commercial NO, NO2, O3 and CO2 small sensors and incorporates measurements of temperature and humidity. A first version, using XBee boards (Radiofrequency) for communications has been installed in the urban locations defined by the project (tunnel and school), permitting the long-term air quality characterization of sites in the presence of the textiles. An improved second version of the system which also comprises a sensor for measuring particles and which uses GPRS for communications, has been developed and successfully installed in the city center of Valencia. Data are sent to a central server where they can be accessed by citizens in nearly real time and online and, in general, they can be utilized in the air quality characterization, for decision-making related to decontamination (traffic regulation, photocatalytic materials, etc.), in air quality models or in mobile applications of interest for the citizens. Within this work, temporal trends obtained with this system in different urban locations will be shown, discussing the impact of the characteristics of the

  2. Indoor Air Quality Building Education and Assessment Model

    EPA Pesticide Factsheets

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM), released in 2002, is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  3. Towards the Next Generation Air Quality Modeling System: Current Progress on Implementing Chemistry into MPAS-A

    EPA Science Inventory

    The community multiscale air quality (CMAQ) model of the U.S. Environmental Protection Agency is one of the most widely used air quality model worldwide; it is employed for both research and regulatory applications at major universities and government agencies for improving under...

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

    PubMed

    Puliafito, E; Guevara, M; Puliafito, C

    2003-01-01

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

  5. 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.

  6. 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.

  7. 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.

  8. Implementing subgrid-scale cloudiness into the Model for Prediction Across Scales-Atmosphere (MPAS-A) for next generation global air quality modeling

    EPA Science Inventory

    A next generation air quality modeling system is being developed at the U.S. EPA to enable seamless modeling of air quality from global to regional to (eventually) local scales. State of the science chemistry and aerosol modules from the Community Multiscale Air Quality (CMAQ) mo...

  9. Recent Enhancements to the Community Multiscale Air Quality Modeling System (CMAQ)

    EPA Science Inventory

    EPA’s Office of Research and Development, Computational Exposure Division held a webinar on January 31, 2017 to present the recent scientific and computational updates made by EPA to the Community Multi-Scale Air Quality Model (CMAQ). Topics covered included: (1) Improveme...

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

    EPA Science Inventory

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

  11. 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.

  12. Preparing the Model for Prediction Across Scales (MPAS) for global retrospective air quality modeling

    EPA Science Inventory

    The US EPA has a plan to leverage recent advances in meteorological modeling to develop a "Next-Generation" air quality modeling system that will allow consistent modeling of problems from global to local scale. The meteorological model of choice is the Model for Predic...

  13. 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...

  14. 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...

  15. AIR QUALITY SIMULATION MODEL PERFORMANCE FOR ONE-HOUR AVERAGES

    EPA Science Inventory

    If a one-hour standard for sulfur dioxide were promulgated, air quality dispersion modeling in the vicinity of major point sources would be an important air quality management tool. Would currently available dispersion models be suitable for use in demonstrating attainment of suc...

  16. Atmospheric Model Evaluation Tool for meteorological and air quality simulations

    EPA Pesticide Factsheets

    The Atmospheric Model Evaluation Tool compares model predictions to observed data from various meteorological and air quality observation networks to help evaluate meteorological and air quality simulations.

  17. Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

    EPA Science Inventory

    The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modeled processes were examined and enhanced to suitably represent the extended space and timesca...

  18. ROLE OF MODELS IN AIR QUALITY MANAGEMENT DECISIONS

    EPA Science Inventory

    Within the frame of the US-India bilateral agreement on environmental cooperation, a team of US scientists have been helping India in designing emission control policies to address urban air quality problems. This presentation discusses how air quality models need to be used for ...

  19. Evaluating Regional-Scale Air Quality Models

    EPA Science Inventory

    Numerical air quality models are being used to understand the complex interplay among emission loading meteorology, and atmospheric chemistry leading to the formation and accumulation of pollutants in the atmosphere. A model evaluation framework is presented here that considers ...

  20. Developing air quality forecasts

    NASA Astrophysics Data System (ADS)

    Lee, Pius; Saylor, Rick; Meagher, James

    2012-05-01

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

  1. Indoor Air Quality Building Education and Assessment Model Forms

    EPA Pesticide Factsheets

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  2. An Overview of Atmospheric Chemistry and Air Quality Modeling

    NASA Technical Reports Server (NTRS)

    Johnson, Matthew S.

    2017-01-01

    This presentation will include my personal research experience and an overview of atmospheric chemistry and air quality modeling to the participants of the NASA Student Airborne Research Program (SARP 2017). The presentation will also provide examples on ways to apply airborne observations for chemical transport (CTM) and air quality (AQ) model evaluation. CTM and AQ models are important tools in understanding tropospheric-stratospheric composition, atmospheric chemistry processes, meteorology, and air quality. This presentation will focus on how NASA scientist currently apply CTM and AQ models to better understand these topics. Finally, the importance of airborne observation in evaluating these topics and how in situ and remote sensing observations can be used to evaluate and improve CTM and AQ model predictions will be highlighted.

  3. Evaluating Air-Quality Models: Review and Outlook.

    NASA Astrophysics Data System (ADS)

    Weil, J. C.; Sykes, R. I.; Venkatram, A.

    1992-10-01

    Over the past decade, much attention has been devoted to the evaluation of air-quality models with emphasis on model performance in predicting the high concentrations that are important in air-quality regulations. This paper stems from our belief that this practice needs to be expanded to 1) evaluate model physics and 2) deal with the large natural or stochastic variability in concentration. The variability is represented by the root-mean- square fluctuating concentration (c about the mean concentration (C) over an ensemble-a given set of meteorological, source, etc. conditions. Most air-quality models used in applications predict C, whereas observations are individual realizations drawn from an ensemble. For cC large residuals exist between predicted and observed concentrations, which confuse model evaluations.This paper addresses ways of evaluating model physics in light of the large c the focus is on elevated point-source models. Evaluation of model physics requires the separation of the mean model error-the difference between the predicted and observed C-from the natural variability. A residual analysis is shown to be an elective way of doing this. Several examples demonstrate the usefulness of residuals as well as correlation analyses and laboratory data in judging model physics.In general, c models and predictions of the probability distribution of the fluctuating concentration (c), (c, are in the developmental stage, with laboratory data playing an important role. Laboratory data from point-source plumes in a convection tank show that (c approximates a self-similar distribution along the plume center plane, a useful result in a residual analysis. At pmsent,there is one model-ARAP-that predicts C, c, and (c for point-source plumes. This model is more computationally demanding than other dispersion models (for C only) and must be demonstrated as a practical tool. However, it predicts an important quantity for applications- the uncertainty in the very high and

  4. Linking Air Quality and Human Health Effects Models: An Application to the Los Angeles Air Basin.

    PubMed

    Stewart, Devoun R; Saunders, Emily; Perea, Roberto A; Fitzgerald, Rosa; Campbell, David E; Stockwell, William R

    2017-01-01

    Proposed emission control strategies for reducing ozone and particulate matter are evaluated better when air quality and health effects models are used together. The Community Multiscale Air Quality (CMAQ) model is the US Environmental Protection Agency's model for determining public policy and forecasting air quality. CMAQ was used to forecast air quality changes due to several emission control strategies that could be implemented between 2008 and 2030 for the South Coast Air Basin that includes Los Angeles. The Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) was used to estimate health and economic impacts of the different emission control strategies based on CMAQ simulations. BenMAP-CE is a computer program based on epidemiologic studies that link human health and air quality. This modeling approach is better for determining optimum public policy than approaches that only examine concentration changes.

  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. 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...

  7. An enhanced PM 2.5 air quality forecast model based on nonlinear regression and back-trajectory concentrations

    NASA Astrophysics Data System (ADS)

    Cobourn, W. Geoffrey

    2010-08-01

    An enhanced PM 2.5 air quality forecast model based on nonlinear regression (NLR) and back-trajectory concentrations has been developed for use in the Louisville, Kentucky metropolitan area. The PM 2.5 air quality forecast model is designed for use in the warm season, from May through September, when PM 2.5 air quality is more likely to be critical for human health. The enhanced PM 2.5 model consists of a basic NLR model, developed for use with an automated air quality forecast system, and an additional parameter based on upwind PM 2.5 concentration, called PM24. The PM24 parameter is designed to be determined manually, by synthesizing backward air trajectory and regional air quality information to compute 24-h back-trajectory concentrations. The PM24 parameter may be used by air quality forecasters to adjust the forecast provided by the automated forecast system. In this study of the 2007 and 2008 forecast seasons, the enhanced model performed well using forecasted meteorological data and PM24 as input. The enhanced PM 2.5 model was compared with three alternative models, including the basic NLR model, the basic NLR model with a persistence parameter added, and the NLR model with persistence and PM24. The two models that included PM24 were of comparable accuracy. The two models incorporating back-trajectory concentrations had lower mean absolute errors and higher rates of detecting unhealthy PM2.5 concentrations compared to the other models.

  8. Sensor-Based Optimization Model for Air Quality Improvement in Home IoT.

    PubMed

    Kim, Jonghyuk; Hwangbo, Hyunwoo

    2018-03-23

    We introduce current home Internet of Things (IoT) technology and present research on its various forms and applications in real life. In addition, we describe IoT marketing strategies as well as specific modeling techniques for improving air quality, a key home IoT service. To this end, we summarize the latest research on sensor-based home IoT, studies on indoor air quality, and technical studies on random data generation. In addition, we develop an air quality improvement model that can be readily applied to the market by acquiring initial analytical data and building infrastructures using spectrum/density analysis and the natural cubic spline method. Accordingly, we generate related data based on user behavioral values. We integrate the logic into the existing home IoT system to enable users to easily access the system through the Web or mobile applications. We expect that the present introduction of a practical marketing application method will contribute to enhancing the expansion of the home IoT market.

  9. NASA Earth Observation Systems and Applications for Health and Air Quality

    NASA Technical Reports Server (NTRS)

    Omar, Ali H.

    2015-01-01

    There is a growing body of evidence that the environment can affect human health in ways that are both complex and global in scope. To address some of these complexities, NASA maintains a diverse constellation of Earth observing research satellites, and sponsors research in developing satellite data applications across a wide spectrum of areas. These include environmental health; infectious disease; air quality standards, policies, and regulations; and the impact of climate change on health and air quality in a number of interrelated efforts. The Health and Air Quality Applications fosters the use of observations, modeling systems, forecast development, application integration, and the research to operations transition process to address environmental health effects. NASA has been a primary partner with Federal operational agencies over the past nine years in these areas. This talk presents the background of the Health and Air Quality Applications program, recent accomplishments, and a plan for the future.

  10. Linking Air Quality and Human Health Effects Models: An Application to the Los Angeles Air Basin

    PubMed Central

    Stewart, Devoun R; Saunders, Emily; Perea, Roberto A; Fitzgerald, Rosa; Campbell, David E; Stockwell, William R

    2017-01-01

    Proposed emission control strategies for reducing ozone and particulate matter are evaluated better when air quality and health effects models are used together. The Community Multiscale Air Quality (CMAQ) model is the US Environmental Protection Agency’s model for determining public policy and forecasting air quality. CMAQ was used to forecast air quality changes due to several emission control strategies that could be implemented between 2008 and 2030 for the South Coast Air Basin that includes Los Angeles. The Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP-CE) was used to estimate health and economic impacts of the different emission control strategies based on CMAQ simulations. BenMAP-CE is a computer program based on epidemiologic studies that link human health and air quality. This modeling approach is better for determining optimum public policy than approaches that only examine concentration changes. PMID:29162976

  11. On Regional Modeling to Support Air Quality Policies (book chapter)

    EPA Science Inventory

    We examine the use of the Community Multiscale Air Quality (CMAQ) model in simulating the changes in the extreme values of air quality that are of interest to the regulatory agencies. Year-to-year changes in ozone air quality are attributable to variations in the prevailing meteo...

  12. Linking Meteorology, Air Quality Models and Observations to ...

    EPA Pesticide Factsheets

    Epidemiologic studies are critical in establishing the association between exposure to air pollutants and adverse health effects. Results of epidemiologic studies are used by U.S. EPA in developing air quality standards to protect the public from the health effects of air pollutants. A major challenge in environmental epidemiology is adequate exposure characterization. Numerous health studies have used measurements from a few central-site ambient monitors to characterize air pollution exposures. Relying solely on central-site ambient monitors does not account for the spatial-heterogeneity of ambient air pollution patterns, the temporal variability in ambient concentrations, nor the influence of infiltration and indoor sources. Central-site monitoring becomes even more problematic for certain air pollutants that exhibit significant spatial heterogeneity. Statistical interpolation techniques and passive monitoring methods can provide additional spatial resolution in ambient concentration estimates. In addition, spatio-temporal models, which integrate GIS data and other factors, such as meteorology, have also been developed to produce more resolved estimates of ambient concentrations. Models, such as the Community Multi-Scale Air Quality (CMAQ) model, estimate ambient concentrations by combining information on meteorology, source emissions, and chemical-fate and transport. Hybrid modeling approaches, which integrate regional scale models with local scale dispersion

  13. ONE-ATMOSPHERE DYNAMICS DESCRIPTION IN THE MODELS-3 COMMUNITY MULTI-SCALE QUALITY (CMAQ) MODELING SYSTEM

    EPA Science Inventory

    This paper proposes a general procedure to link meteorological data with air quality models, such as U.S. EPA's Models-3 Community Multi-scale Air Quality (CMAQ) modeling system. CMAQ is intended to be used for studying multi-scale (urban and regional) and multi-pollutant (ozon...

  14. Evaluation of regional climate simulations for air quality modelling purposes

    NASA Astrophysics Data System (ADS)

    Menut, Laurent; Tripathi, Om P.; Colette, Augustin; Vautard, Robert; Flaounas, Emmanouil; Bessagnet, Bertrand

    2013-05-01

    In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional "climate modeling" source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.

  15. Quantifying Co-benefits of Renewable Energy through Integrated Electricity and Air Quality Modeling

    NASA Astrophysics Data System (ADS)

    Abel, D.

    2016-12-01

    This work focuses on the coordination of electricity sector changes with air quality and health improvement strategies through the integration of electricity and air quality models. Two energy models are used to calculate emission perturbations associated with changes in generation technology (20% generation from solar photovoltaics) and demand (future electricity use under a warmer climate). Impacts from increased solar PV penetration are simulated with the electricity model GridView, in collaboration with the National Renewable Energy Laboratory (NREL). Generation results are used to scale power plant emissions from an inventory developed by the Lake Michigan Air Directors Consortium (LADCO). Perturbed emissions and are used to calculate secondary particulate matter with the Community Multiscale Air Quality (CMAQ) model. We find that electricity NOx and SO2 emissions decrease at a rate similar to the total fraction of electricity supplied by solar. Across the Eastern U.S. region, average PM2.5 is reduced 5% over the summer, with highest reduction in regions and on days of greater PM2.5. A similar approach evaluates the air quality impacts of elevated electricity demand under a warmer climate. Meteorology is selected from the North American Regional Climate Change Assessment Program (NARCCAP) and input to a building energy model, eQUEST, to assess electricity demand as a function of ambient temperature. The associated generation and emissions are calculated on a plant-by-plant basis by the MyPower power sector model. These emissions are referenced to the 2011 National Emissions Inventory to be modeled in CMAQ for the Eastern U.S. and extended to health impact evaluation with the Environmental Benefits Mapping and Analysis Program (BenMAP). All results focus on the air quality and health consequences of energy system changes, considering grid-level changes to meet climate and air quality goals.

  16. EVALUATING AND USING AIR QUALITY MODELS

    EPA Science Inventory

    Grid-based models are being used to assess the magnitude of the pollution problem and to design emission control strategies to achieve compliance with the relevant air quality standards in the United States.

  17. 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...

  18. Air Quality Modeling Technical Support Document for the Final Cross State Air Pollution Rule Update

    EPA Pesticide Factsheets

    In this technical support document (TSD) we describe the air quality modeling performed to support the final Cross State Air Pollution Rule for the 2008 ozone National Ambient Air Quality Standards (NAAQS).

  19. 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

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

    PubMed

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

    2006-10-01

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

  1. [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.

  2. COMMUNITY MULTISCALE AIR QUALITY ( CMAQ ) MODEL - QUALITY ASSURANCE AND VERSION CONTROL

    EPA Science Inventory

    This presentation will be given to the EPA Exposure Modeling Workgroup on January 24, 2006. The quality assurance and version control procedures for the Community Multiscale Air Quality (CMAQ) Model are presented. A brief background of CMAQ is given, then issues related to qual...

  3. 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.

  4. 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...

  5. One multi-media environmental system with linkage between meteorology/ hydrology/ air quality models and water quality model

    NASA Astrophysics Data System (ADS)

    Tang, C.; Lynch, J. A.; Dennis, R. L.

    2016-12-01

    The biogeochemical processing of nitrogen and associated pollutants is driven by meteorological and hydrological processes in conjunction with pollutant loading. There are feedbacks between meteorology and hydrology that will be affected by land-use change and climate change. Changes in meteorology will affect pollutant deposition. It is important to account for those feedbacks and produce internally consistent simulations of meteorology, hydrology, and pollutant loading to drive the (watershed/water quality) biogeochemical models. In this study, the ecological response to emission reductions in streams in the Potomac watershed was evaluated. Firstly, we simulated the deposition by using the fully coupled Weather Research & Forecasting (WRF) model and the Community Multiscale Air Quality (CAMQ) model; secondly, we created the hydrological data by the offline linked Variable Infiltration Capacity (VIC) model and the WRF model. Lastly, we investigated the water quality by one comprehensive/environment model, namely the linkage of CMAQ, WRF, VIC and the Model of Acidification of Groundwater In Catchment (MAGIC) model from 2002 to 2010.The simulated results (such as NO3, SO4, and SBC) fit well to the observed values. The linkage provides a generally accurate, well-tested tool for evaluating sensitivities to varying meteorology and environmental changes on acidification and other biogeochemical processes, with capability to comprehensively explore strategic policy and management design.

  6. 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...

  7. 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...

  8. 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.

  9. Sensor-Based Optimization Model for Air Quality Improvement in Home IoT

    PubMed Central

    Kim, Jonghyuk

    2018-01-01

    We introduce current home Internet of Things (IoT) technology and present research on its various forms and applications in real life. In addition, we describe IoT marketing strategies as well as specific modeling techniques for improving air quality, a key home IoT service. To this end, we summarize the latest research on sensor-based home IoT, studies on indoor air quality, and technical studies on random data generation. In addition, we develop an air quality improvement model that can be readily applied to the market by acquiring initial analytical data and building infrastructures using spectrum/density analysis and the natural cubic spline method. Accordingly, we generate related data based on user behavioral values. We integrate the logic into the existing home IoT system to enable users to easily access the system through the Web or mobile applications. We expect that the present introduction of a practical marketing application method will contribute to enhancing the expansion of the home IoT market. PMID:29570684

  10. 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...

  11. Development and analysis of air quality modeling simulations for hazardous air pollutants

    NASA Astrophysics Data System (ADS)

    Luecken, D. J.; Hutzell, W. T.; Gipson, G. L.

    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 are shown for formaldehyde, acetaldehyde, benzene, 1,3-butadiene and acrolein. Photochemical production in the atmosphere is predicted to dominate ambient formaldehyde and acetaldehyde concentrations, and to account for a significant fraction of ambient acrolein concentrations. Spatial and temporal variations are large throughout the domain over the year. Predicted concentrations are compared with observations for formaldehyde, acetaldehyde, benzene and 1,3-butadiene. Although the modeling results indicate an overall slight tendency towards underprediction, they reproduce episodic and seasonal behavior of pollutant concentrations at many monitors with good skill.

  12. Importance and Challenges in Use and Uptake of Air Quality Modelling in Developing Countries: Use of CAMx for Air Quality Management in the City of Johannesburg.

    NASA Astrophysics Data System (ADS)

    Garland, R. M.; Naidoo, M.; Sibiya, B.; Naidoo, S.; Bird, T.; von Gruenewaldt, R.; Liebenberg-Enslin, H.; Nekhwalivhe, M.; Netshandama, J.; Mahlatji, M.

    2017-12-01

    Ambient air pollution levels are regulated in South Africa; however in many areas pollution concentrations exceed these levels. The South African Air Quality Act also stipulates that government across all levels must have Air Quality Management Plans (AQMP) in place that outline the current state of air quality and emissions, as well as the implementable plan to manage, and where necessary improve, air quality. Historically, dispersion models have been used to support air quality management decisions, including in AQMPs. However, with the focus of air quality management shifting from focusing on industrial point sources to a more integrated and holistic management of all sources, chemical transport models are needed. CAMx was used in the review and development of the City of Johannesburg's AQMP to simulate hot spots of air pollution, as well as to model intervention scenarios. As the pollutants of concern in Johannesburg are ozone and particulate matter, it is critical to use a model that can simulate chemistry. CAMx was run at 1 km with a locally derived emissions inventory for 2014. The sources of pollution in the City are diverse (including, industrial, vehicles, domestic burning, natural), and many sources have large uncertainties in estimating emissions due to lack of necessary data and local emission factors. These uncertainties, together with a lack of measurements to validate the model against, hinder the performance of the model to simulate air quality and thus inform air quality management. However, as air quality worsens in Africa, it is critical for decision makers to have a strong evidence base on the state of air quality and impact of interventions in order to improve air quality effectively. This presentation will highlight the findings from using a chemical transport model for air quality management in the largest city in South Africa, the use and limitations of these for decision-makers, and proposed way forward.

  13. 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...

  14. Hybrid Air Quality Modeling Approach For Use in the Near ...

    EPA Pesticide Factsheets

    The Near-road EXposures to Urban air pollutant Study (NEXUS) investigated whether children with asthma living in close proximity to major roadways in Detroit, MI, (particularly near roadways with high diesel traffic) have greater health impacts associated with exposure to air pollutants than those living farther away. A major challenge in such health and 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 air pollutants and adverse health outcomes. This 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, associated with local variations of emissions and meteorology, were estimated using a combination of the AERMOD and R-LINE dispersion models, local emission source information from the National Emissions Inventory, detailed road network locations and traffic activity, and meteorological data from the Detroit City Airport. The regional background contribution was estimated using a combination of the Community Multiscale Air Quality (CMAQ) model and the Space/Time Ordinary Kriging (STOK) model. To capture the near-road pollutant gradients, refined “mini-grids” of model recep

  15. 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.

  16. Development and application of air quality models at the US ...

    EPA Pesticide Factsheets

    Overview of the development and application of air quality models at the U.S. EPA, particularly focused on the development and application of the Community Multiscale Air Quality (CMAQ) model developed within the Computation Exposure Division (CED) of the National Exposure Research Laboratory (NERL). This presentation will provide a simple overview of air quality model development and application geared toward a non-technical student audience. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

  17. Evaluation of Day and Nighttime Lower Tropospheric Ozone from Air Quality Models using TES and Ozonesondes

    NASA Astrophysics Data System (ADS)

    Osterman, G. B.; Neu, J. L.; Eldering, A.; Pinder, R. W.; Tang, Y.; McQueen, J.

    2012-12-01

    At night, ozone can be transported long distances above the surface inversion layer without chemical destruction or deposition. As the boundary layer breaks up in the morning, this nocturnal ozone can be mixed down to the surface and rapidly increase ozone concentrations at a rate that can rival chemical ozone production. Most regional scale models that are used for air quality forecasts and ozone source attribution do not adequately capture nighttime ozone concentrations and transport. We combine ozone profile data from the NASA Earth Observing System (EOS) Tropospheric Emission Spectrometer (TES) and other sensors, ozonesonde data collected during the INTEX Ozonesonde Network Study (IONS), EPA AirNow ground station ozone data, the Community Multi-Scale Air Quality (CMAQ) model, and the National Air Quality Forecast Capability (NAQFC) model to examine air quality events during August 2006. We present both aggregated statistics and case-study analyses that assess the relationship between the models' ability to reproduce surface air quality events and their ability to capture the vertical distribution of ozone both during the day and at night. We perform the comparisons looking at the geospatial dependence in the differences between the measurements and models under different surface ozone conditions.

  18. A multi-model assessment of the co-benefits of climate mitigation for global air quality

    NASA Astrophysics Data System (ADS)

    Rao, Shilpa; Klimont, Zbigniew; Leitao, Joana; Riahi, Keywan; van Dingenen, Rita; Aleluia Reis, Lara; Calvin, Katherine; Dentener, Frank; Drouet, Laurent; Fujimori, Shinichiro; Harmsen, Mathijs; Luderer, Gunnar; Heyes, Chris; Strefler, Jessica; Tavoni, Massimo; van Vuuren, Detlef P.

    2016-12-01

    We present a model comparison study that combines multiple integrated assessment models with a reduced-form global air quality model to assess the potential co-benefits of global climate mitigation policies in relation to the World Health Organization (WHO) goals on air quality and health. We include in our assessment, a range of alternative assumptions on the implementation of current and planned pollution control policies. The resulting air pollution emission ranges significantly extend those in the Representative Concentration Pathways. Climate mitigation policies complement current efforts on air pollution control through technology and fuel transformations in the energy system. A combination of stringent policies on air pollution control and climate change mitigation results in 40% of the global population exposed to PM levels below the WHO air quality guideline; with the largest improvements estimated for India, China, and Middle East. Our results stress the importance of integrated multisector policy approaches to achieve the Sustainable Development Goals.

  19. Merging Air Quality and Public Health Decision Support Systems

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

  20. 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.

  1. Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.2

    EPA Science Inventory

    The Community Multiscale Air Quality (CMAQ) 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 Computational Exposure Division (CED) of the U.S. Environmental Pr...

  2. Evaluation of the Community Multi-scale Air Quality Model Version 5.2

    EPA Science Inventory

    The Community Multiscale Air Quality (CMAQ) 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 Computational Exposure Division (CED) of the U.S. Environmental Pr...

  3. Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

    PubMed Central

    Mathur, Rohit; Xing, Jia; Gilliam, Robert; Sarwar, Golam; Hogrefe, Christian; Pleim, Jonathan; Pouliot, George; Roselle, Shawn; Spero, Tanya L.; Wong, David C.; Young, Jeffrey

    2018-01-01

    The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modelled processes were examined and enhanced to suitably represent the extended space and time scales for such applications. Hemispheric scale simulations with CMAQ and the Weather Research and Forecasting (WRF) model are performed for multiple years. Model capabilities for a range of applications including episodic long-range pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution-climate interactions are evaluated through detailed comparison with available surface, aloft, and remotely sensed observations. The expansion of CMAQ to simulate the hemispheric scales provides a framework to examine interactions between atmospheric processes occurring at various spatial and temporal scales with physical, chemical, and dynamical consistency. PMID:29681922

  4. NASA Tropospheric Composition Program field campagins as prototypes to advance the Integrated Observing System for Air Quality

    NASA Astrophysics Data System (ADS)

    Lefer, B. L.; Crawford, J. H.; Pierce, R. B.; Berkoff, T.; Swap, R.; Janz, S. J.; Ahn, J.; Al-Saadi, J. A.

    2017-12-01

    With the launch over the virtual constellation of earth observing satellites for atmospheric composition (e.g., TROPOMI, GEMS, TEMPO, and Sentinel-4) over the next several years, we have a unique opportunity to develop an Integrated Observing System (IOS) for air quality in the northern hemisphere. Recently, NASA's Tropospheric Composition Program (TCP) has participated in several different air quality related field campaigns as an effort to explore various prototypes of the IOS for Air Quality. The IOS for air quality could be a system were space-based observations of air quality (generally, column abundances of NO2, HCHO, O3, SO2, and AOD) are given added "value" by being integrated with: a) long-term ground-based observations;b) regional and global air quality and chemical transport models; as well as c) measurements from targeted airborne field campaigns. The recent Korea-US Air Quality Study (KORUS-AQ), the Lake Michigan Ozone Study 2017 (LMOS), and the Ozone Water-Land Environmental Transition Study (OWLETS) field campaigns were held in different locations and made measurements over different scale. However, all of these provide an opportunity to learn about how a future integrated air quality observing system can be implemented to serve a variety of air quality related objectives. NASA TCP is also exploring enchancements to our routine observations to strengthen the IOS for air quality in the future.

  5. 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...

  6. 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.

  7. 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...

  8. 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

  9. Air Quality Modeling Technical Support Document for the 2008 Ozone NAAQS Cross-State Air Pollution Rule Proposal

    EPA Pesticide Factsheets

    In this technical support document (TSD) we describe the air quality modeling performed to support the proposed Cross-State Air Pollution Rule for the 2008 ozone National Ambient Air Quality Standards (NAAQS)

  10. Bibliography for the Indoor Air Quality Building Education and Assessment Model

    EPA Pesticide Factsheets

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  11. Ambient air pollution and semen quality.

    PubMed

    Nobles, Carrie J; Schisterman, Enrique F; Ha, Sandie; Kim, Keewan; Mumford, Sunni L; Buck Louis, Germaine M; Chen, Zhen; Liu, Danping; Sherman, Seth; Mendola, Pauline

    2018-05-01

    Ambient air pollution is associated with systemic increases in oxidative stress, to which sperm are particularly sensitive. Although decrements in semen quality represent a key mechanism for impaired fecundability, prior research has not established a clear association between air pollution and semen quality. To address this, we evaluated the association between ambient air pollution and semen quality among men with moderate air pollution exposure. Of 501 couples in the LIFE study, 467 male partners provided one or more semen samples. Average residential exposure to criteria air pollutants and fine particle constituents in the 72 days before ejaculation was estimated using modified Community Multiscale Air Quality models. Generalized estimating equation models estimated the association between air pollutants and semen quality parameters (volume, count, percent hypo-osmotic swollen, motility, sperm head, morphology and sperm chromatin parameters). Models adjusted for age, body mass index, smoking and season. Most associations between air pollutants and semen parameters were small. However, associations were observed for an interquartile increase in fine particulates ≤2.5 µm and decreased sperm head size, including -0.22 (95% CI -0.34, -0.11) µm 2 for area, -0.06 (95% CI -0.09, -0.03) µm for length and -0.09 (95% CI -0.19, -0.06) µm for perimeter. Fine particulates were also associated with 1.03 (95% CI 0.40, 1.66) greater percent sperm head with acrosome. Air pollution exposure was not associated with semen quality, except for sperm head parameters. Moderate levels of ambient air pollution may not be a major contributor to semen quality. Published by Elsevier Inc.

  12. Application of OMI NO2 for Regional Air Quality Model Evaluation

    NASA Astrophysics Data System (ADS)

    Holloway, T.; Bickford, E.; Oberman, J.; Scotty, E.; Clifton, O. E.

    2012-12-01

    To support the application of satellite data for air quality analysis, we examine how column NO2 measurements from the Ozone Monitoring Instrument (OMI) aboard the NASA Aura satellite relate to ground-based and model estimates of NO2 and related species. Daily variability, monthly mean values, and spatial gradients in OMI NO2 from the Netherlands Royal Meteorological Institute (KNMI) are compared to ground-based measurements of NO2 from the EPA Air Quality System (AQS) database. Satellite data is gridded to two resolutions typical of regional air quality models - 36 km x 36 km over the continental U.S., and 12 km x 12 km over the Upper Midwestern U.S. Gridding is performed using the Wisconsin Horizontal Interpolation Program for Satellites (WHIPS), a publicly available software to support gridding of satellite data to model grids. Comparing daily OMI retrievals (13:45 daytime local overpass time) with ground-based measurements (13:00), we find January and July 2007 correlation coefficients (r-values) generally positive, with values higher in the winter (January) than summer (July) for most sites. Incidences of anti-correlation or low-correlation are evaluated with model simulations from the U.S. EPA Community Multiscale Air Quality Model version 4.7 (CMAQ). OMI NO2 is also used to evaluate CMAQ output, and to compare performance metrics for CMAQ relative to AQS measurements. We compare simulated NO2 across both the U.S. and Midwest study domains with both OMI NO2 (total column CMAQ values, weighted with the averaging kernel) and with ground-based observations (lowest model layer CMAQ values). 2007 CMAQ simulations employ emissions from the Lake Michigan Air Directors Consortium (LADCO) and meteorology from the Weather Research and Forecasting (WRF) model. Over most of the U.S., CMAQ is too high in January relative to OMI NO2, but too low in January relative to AQS NO2. In contrast, CMAQ is too low in July relative to OMI NO2, but too high relative to AQS NO2. These

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

    NASA Astrophysics Data System (ADS)

    Dabberdt, Walter F.; Miller, Erik

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

  14. Development of a Next Generation Air Quality Modeling System

    EPA Science Inventory

    In the presentation we will describe our modifications to MPAS to improve its suitability for retrospective air quality applications and show evaluations of global and regional meterological simulations. Our modifications include addition of physics schemes that we developed for...

  15. 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 ...

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

    EPA Science Inventory

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

  17. 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

  18. Overview and Evaluation of the Community Multiscale Air Quality (CMAQ) Modeling System Version 5.2

    EPA Science Inventory

    A new version of the Community Multiscale Air Quality (CMAQ) model, version 5.2 (CMAQv5.2), is currently being developed, with a planned release date in 2017. The new model includes numerous updates from the previous version of the model (CMAQv5.1). Specific updates include a new...

  19. 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

  20. A model for predicting air quality along highways.

    DOT National Transportation Integrated Search

    1973-01-01

    The subject of this report is an air quality prediction model for highways, AIRPOL Version 2, July 1973. AIRPOL has been developed by modifying the basic Gaussian approach to gaseous dispersion. The resultant model is smooth and continuous throughout...

  1. 40 CFR Appendix W to Part 51 - Guideline on Air Quality Models

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 2 2010-07-01 2010-07-01 false Guideline on Air Quality Models W Appendix W to Part 51 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS REQUIREMENTS FOR PREPARATION, ADOPTION, AND SUBMITTAL OF IMPLEMENTATION PLANS Pt. 51, App. W Appendix W to Part 51—Guideline on Air Quality Models...

  2. Evaluating the Vertical Distribution of Ozone and its Relationship to Pollution Events in Air Quality Models using Satellite Data

    NASA Astrophysics Data System (ADS)

    Osterman, G. B.; Neu, J. L.; Eldering, A.; Pinder, R. W.; Tang, Y.; McQueen, J.

    2014-12-01

    Most regional scale models that are used for air quality forecasts and ozone source attribution do not adequately capture the distribution of ozone in the mid- and upper troposphere, but it is unclear how this shortcoming relates to their ability to simulate surface ozone. We combine ozone profile data from the NASA Earth Observing System (EOS) Tropospheric Emission Spectrometer (TES) and a new joint product from TES and the Ozone Monitoring Instrument along with ozonesonde measurements and EPA AirNow ground station ozone data to examine air quality events during August 2006 in the Community Multi-Scale Air Quality (CMAQ) and National Air Quality Forecast Capability (NAQFC) models. We present both aggregated statistics and case-study analyses with the goal of assessing the relationship between the models' ability to reproduce surface air quality events and their ability to capture the vertical distribution of ozone. We find that the models lack the mid-tropospheric ozone variability seen in TES and the ozonesonde data, and discuss the conditions under which this variability appears to be important for surface air quality.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  5. 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.

  6. CMAQ Involvement in Air Quality Model Evaluation International Initiative

    EPA Pesticide Factsheets

    Description of Air Quality Model Evaluation International Initiative (AQMEII). Different chemical transport models are applied by different groups over North America and Europe and evaluated against observations.

  7. 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; hide

    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.

  8. Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.1

    EPA Science Inventory

    The Community Multiscale Air Quality (CMAQ) 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 Computational Exposure Division (CED) of the U.S. Environmental Pr...

  9. Overview and Evaluation of the Community Multiscale Air Quality Model Version 5.2

    EPA Science Inventory

    The Community Multiscale Air Quality (CMAQ) 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 Computational Exposure Division (CED) of the U.S. Environmental Pr...

  10. Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.2

    EPA Science Inventory

    The Community Multiscale Air Quality (CMAQ) 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 Computational Exposure Division (CED) of the U.S. Environmental Pr...

  11. Impacts of Climate Policy on Regional Air Quality, Health, and Air Quality Regulatory Procedures

    NASA Astrophysics Data System (ADS)

    Thompson, T. M.; Selin, N. E.

    2011-12-01

    Both the changing climate, and the policy implemented to address climate change can impact regional air quality. We evaluate the impacts of potential selected climate policies on modeled regional air quality with respect to national pollution standards, human health and the sensitivity of health uncertainty ranges. To assess changes in air quality due to climate policy, we couple output from a regional computable general equilibrium economic model (the US Regional Energy Policy [USREP] model), with a regional air quality model (the Comprehensive Air Quality Model with Extensions [CAMx]). USREP uses economic variables to determine how potential future U.S. climate policy would change emissions of regional pollutants (CO, VOC, NOx, SO2, NH3, black carbon, and organic carbon) from ten emissions-heavy sectors of the economy (electricity, coal, gas, crude oil, refined oil, energy intensive industry, other industry, service, agriculture, and transportation [light duty and heavy duty]). Changes in emissions are then modeled using CAMx to determine the impact on air quality in several cities in the Northeast US. We first calculate the impact of climate policy by using regulatory procedures used to show attainment with National Ambient Air Quality Standards (NAAQS) for ozone and particulate matter. Building on previous work, we compare those results with the calculated results and uncertainties associated with human health impacts due to climate policy. This work addresses a potential disconnect between NAAQS regulatory procedures and the cost/benefit analysis required for and by the Clean Air Act.

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

    NASA Astrophysics Data System (ADS)

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

    2010-09-01

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

  13. Development and application of air quality models at the U.S. EPA

    EPA Science Inventory

    Overview of the development and application of air quality models at the U.S. EPA, particularly focused on the development and application of the Community Multiscale Air Quality (CMAQ) model developed within the Computation Exposure Division (CED) of the National Exposure Resear...

  14. 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...

  15. The Simulations of Wildland Fire Smoke PM25 in the NWS Air Quality Forecasting Systems

    NASA Astrophysics Data System (ADS)

    Huang, H. C.; Pan, L.; McQueen, J.; Lee, P.; ONeill, S. M.; Ruminski, M.; Shafran, P.; Huang, J.; Stajner, I.; Upadhayay, S.; Larkin, N. K.

    2017-12-01

    The increase of wildland fire intensity and frequency in the United States (U.S.) has led to property loss, human fatality, and poor air quality due to elevated particulate matters and surface ozone concentrations. The NOAA/National Weather Service (NWS) built the National Air Quality Forecast Capability (NAQFC) based on the U.S. Environmental Protection Agency (EPA) Community Multi-scale Air Quality (CMAQ) Modeling System driven by the NCEP North American Mesoscale Forecast System meteorology to provide ozone and fine particulate matter (PM2.5) forecast guidance publicly. State and local forecasters use the NWS air quality forecast guidance to issue air quality alerts in their area. The NAQFC PM2.5 predictions include emissions from anthropogenic and biogenic sources, as well as natural sources such as dust storms and wildland fires. The wildland fire emission inputs to the NAQFC is derived from the NOAA National Environmental Satellite, Data, and Information Service Hazard Mapping System fire and smoke detection product and the emission module of the U.S. Forest Service (USFS) BlueSky Smoke Modeling Framework. Wildland fires are unpredictable and can be ignited by natural causes such as lightning or be human-caused. It is extremely difficult to predict future occurrences and behavior of wildland fires, as is the available bio-fuel to be burned for real-time air quality predictions. Assumptions of future day's wildland fire behavior often have to be made from older observed wildland fire information. The comparisons between the NAQFC modeled PM2.5 and the EPA AirNow surface observation show that large errors in PM2.5 prediction can occur if fire smoke emissions are sometimes placed at the wrong location and/or time. A configuration of NAQFC CMAQ-system to re-run previous 24 hours, during which wildland fires were observed from satellites has been included recently. This study focuses on the effort performed to minimize the error in NAQFC PM2.5 predictions

  16. 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...

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

    EPA Pesticide Factsheets

    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

  18. 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

  19. Heating, Ventilation and Air-Conditioning Systems, Part of Indoor Air Quality Design Tools for Schools

    EPA Pesticide Factsheets

    The main purposes of a Heating, Ventilation, and Air-Conditioning system are to help maintain good indoor air quality through adequate ventilation with filtration and provide thermal comfort. HVAC systems are among the largest energy consumers in schools.

  20. 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)

  1. Utility of NCEP Operational and Emerging Meteorological Models for Driving Air Quality Prediction

    NASA Astrophysics Data System (ADS)

    McQueen, J.; Huang, J.; Huang, H. C.; Shafran, P.; Lee, P.; Pan, L.; Sleinkofer, A. M.; Stajner, I.; Upadhayay, S.; Tallapragada, V.

    2017-12-01

    Operational air quality predictions for the United States (U. S.) are provided at NOAA by the National Air Quality Forecasting Capability (NAQFC). NAQFC provides nationwide operational predictions of ozone and particulate matter twice per day (at 06 and 12 UTC cycles) at 12 km resolution and 1 hour time intervals through 48 hours and distributed at http://airquality.weather.gov. The NOAA National Centers for Environmental Prediction (NCEP) operational North American Mesoscale (NAM) 12 km weather prediction is used to drive the Community Multiscale Air Quality (CMAQ) model. In 2017, the NAM was upgraded in part to reduce a warm 2m temperature bias in Summer (V4). At the same time CMAQ was updated to V5.0.2. Both versions of the models were run in parallel for several months. Therefore the impact of improvements from the atmospheric chemistry model versus upgrades with the weather prediction model could be assessed. . Improvements to CMAQ were related to improvements to improvements in NAM 2 m temperature bias through increasing the opacity of clouds and reducing downward shortwave radiation resulted in reduced ozone photolysis. Higher resolution operational NWP models have recently been introduced as part of the NCEP modeling suite. These include the NAM CONUS Nest (3 km horizontal resolution) run four times per day through 60 hours and the High Resolution Rapid Refresh (HRRR, 3 km) run hourly out to 18 hours. In addition, NCEP with other NOAA labs has begun to develop and test the Next Generation Global Prediction System (NGGPS) based on the FV3 global model. This presentation also overviews recent developments with operational numerical weather prediction and evaluates the ability of these models for predicting low level temperatures, clouds and capturing boundary layer processes important for driving air quality prediction in complex terrain. The assessed meteorological model errors could help determine the magnitude of possible pollutant errors from CMAQ if used

  2. Links Related to the Indoor Air Quality Building Education and Assessment Model

    EPA Pesticide Factsheets

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  3. The statistical evaluation and comparison of ADMS-Urban model for the prediction of nitrogen dioxide with air quality monitoring network.

    PubMed

    Dėdelė, Audrius; Miškinytė, Auksė

    2015-09-01

    In many countries, road traffic is one of the main sources of air pollution associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered to be a measure of traffic-related air pollution, with concentrations tending to be higher near highways, along busy roads, and in the city centers, and the exceedances are mainly observed at measurement stations located close to traffic. In order to assess the air quality in the city and the air pollution impact on public health, air quality models are used. However, firstly, before the model can be used for these purposes, it is important to evaluate the accuracy of the dispersion modelling as one of the most widely used method. The monitoring and dispersion modelling are two components of air quality monitoring system (AQMS), in which statistical comparison was made in this research. The evaluation of the Atmospheric Dispersion Modelling System (ADMS-Urban) was made by comparing monthly modelled NO2 concentrations with the data of continuous air quality monitoring stations in Kaunas city. The statistical measures of model performance were calculated for annual and monthly concentrations of NO2 for each monitoring station site. The spatial analysis was made using geographic information systems (GIS). The calculation of statistical parameters indicated a good ADMS-Urban model performance for the prediction of NO2. The results of this study showed that the agreement of modelled values and observations was better for traffic monitoring stations compared to the background and residential stations.

  4. 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

  5. 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

  6. Increasing the Use of Earth Science Data and Models in Air Quality Management.

    PubMed

    Milford, Jana B; Knight, Daniel

    2017-04-01

    In 2010, the U.S. National Aeronautics and Space Administration (NASA) initiated the Air Quality Applied Science Team (AQAST) as a 5-year, $17.5-million award with 19 principal investigators. AQAST aims to increase the use of Earth science products in air quality-related research and to help meet air quality managers' information needs. We conducted a Web-based survey and a limited number of follow-up interviews to investigate federal, state, tribal, and local air quality managers' perspectives on usefulness of Earth science data and models, and on the impact AQAST has had. The air quality managers we surveyed identified meeting the National Ambient Air Quality Standards for ozone and particulate matter, emissions from mobile sources, and interstate air pollution transport as top challenges in need of improved information. Most survey respondents viewed inadequate coverage or frequency of satellite observations, data uncertainty, and lack of staff time or resources as barriers to increased use of satellite data by their organizations. Managers who have been involved with AQAST indicated that the program has helped build awareness of NASA Earth science products, and assisted their organizations with retrieval and interpretation of satellite data and with application of global chemistry and climate models. AQAST has also helped build a network between researchers and air quality managers with potential for further collaborations. NASA's Air Quality Applied Science Team (AQAST) aims to increase the use of satellite data and global chemistry and climate models for air quality management purposes, by supporting research and tool development projects of interest to both groups. Our survey and interviews of air quality managers indicate they found value in many AQAST projects and particularly appreciated the connections to the research community that the program facilitated. Managers expressed interest in receiving continued support for their organizations' use of

  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. INDOOR AIR QUALITY MODEL VERSION 1.0 DOCUMENTATION

    EPA Science Inventory

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

  9. Air quality over Europe and Iberian Peninsula for 2004 at high horizontal resolution: evaluation of the CALIOPE modelling system

    NASA Astrophysics Data System (ADS)

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

    2009-09-01

    In the frame of the CALIOPE project (Baldasano et al., 2008a), a high-resolution air quality forecasting system, WRF-ARW/HERMES/CMAQ/DREAM, is under development 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 is 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). CALIOPE is a complex system that integrates a variety of environmental models. WRF-ARW provides high-resolution meteorological fields to the system. It is configured with 38 vertical layers reaching up to 50 hPa. Meteorological initial and boundary conditions are obtained from the NCEP final analysis data. The HERMES emission model (Baldasano et al., 2008b) computes the emissions for the Iberian Peninsula simulation at 4 km horizontal resolution every hour using a bottom-up approach. For the European domain, HERMES disaggregates the EMEP expert emission inventory for 2004. The CMAQ chemical transport model solves the physico-chemical processes in the system. The vertical resolution of CMAQ for gas-phase and aerosols has been increased from 8 to 15 layers in order to simulate vertical exchanges more accurately. Chemical boundary conditions are provided by the LMDz-INCA2 global climate-chemistry model (see Hauglustaine et al., 2004). Finally, the DREAM model simulates long-range transport of mineral dust over the domains under study. In order to evaluate the performances of the CALIOPE system, model simulations were compared with ground-based measurements from the EMEP and Spanish air quality networks. For the European

  10. "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...

  11. 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...

  12. A rapid response air quality analysis system for use in projects having stringent quality assurance requirements

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bowman, A.W.

    1990-04-01

    This paper describes an approach to solve air quality problems which frequently occur during iterations of the baseline change process. From a schedule standpoint, it is desirable to perform this evaluation in as short a time as possible while budgetary pressures limit the size of the staff available to do the work. Without a method in place to deal with baseline change proposal requests the environment analysts may not be able to produce the analysis results in the time frame expected. Using a concept called the Rapid Response Air Quality Analysis System (RAAS), the problems of timing and cost becomemore » tractable. The system could be adapted to assess other atmospheric pathway impacts, e.g., acoustics or visibility. The air quality analysis system used to perform the EA analysis (EA) for the Salt Repository Project (part of the Civilian Radioactive Waste Management Program), and later to evaluate the consequences of proposed baseline changes, consists of three components: Emission source data files; Emission rates contained in spreadsheets; Impact assessment model codes. The spreadsheets contain user-written codes (macros) that calculate emission rates from (1) emission source data (e.g., numbers and locations of sources, detailed operating schedules, and source specifications including horsepower, load factor, and duty cycle); (2) emission factors such as those published by the U.S. Environmental Protection Agency, and (3) control efficiencies.« less

  13. 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.

  14. Method, system and apparatus for monitoring and adjusting the quality of indoor air

    DOEpatents

    Hartenstein, Steven D.; Tremblay, Paul L.; Fryer, Michael O.; Hohorst, Frederick A.

    2004-03-23

    A system, method and apparatus is provided for monitoring and adjusting the quality of indoor air. A sensor array senses an air sample from the indoor air and analyzes the air sample to obtain signatures representative of contaminants in the air sample. When the level or type of contaminant poses a threat or hazard to the occupants, the present invention takes corrective actions which may include introducing additional fresh air. The corrective actions taken are intended to promote overall health of personnel, prevent personnel from being overexposed to hazardous contaminants and minimize the cost of operating the HVAC system. The identification of the contaminants is performed by comparing the signatures provided by the sensor array with a database of known signatures. Upon identification, the system takes corrective actions based on the level of contaminant present. The present invention is capable of learning the identity of previously unknown contaminants, which increases its ability to identify contaminants in the future. Indoor air quality is assured by monitoring the contaminants not only in the indoor air, but also in the outdoor air and the air which is to be recirculated. The present invention is easily adaptable to new and existing HVAC systems. In sum, the present invention is able to monitor and adjust the quality of indoor air in real time by sensing the level and type of contaminants present in indoor air, outdoor and recirculated air, providing an intelligent decision about the quality of the air, and minimizing the cost of operating an HVAC system.

  15. Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model.

    PubMed

    Wang, Jianzhou; Niu, Tong; Wang, Rui

    2017-03-02

    The worsening atmospheric pollution increases the necessity of air quality early warning systems (EWSs). Despite the fact that a massive amount of investigation about EWS in theory and practicality has been conducted by numerous researchers, studies concerning the quantification of uncertain information and comprehensive evaluation are still lacking, which impedes further development in the area. In this paper, firstly a comprehensive warning system is proposed, which consists of two vital indispensable modules, namely effective forecasting and scientific evaluation, respectively. For the forecasting module, a novel hybrid model combining the theory of data preprocessing and numerical optimization is first developed to implement effective forecasting for air pollutant concentration. Especially, in order to further enhance the accuracy and robustness of the warning system, interval forecasting is implemented to quantify the uncertainties generated by forecasts, which can provide significant risk signals by using point forecasting for decision-makers. For the evaluation module, a cloud model, based on probability and fuzzy set theory, is developed to perform comprehensive evaluations of air quality, which can realize the transformation between qualitative concept and quantitative data. To verify the effectiveness and efficiency of the warning system, extensive simulations based on air pollutants data from Dalian in China were effectively implemented, which illustrate that the warning system is not only remarkably high-performance, but also widely applicable.

  16. Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model

    PubMed Central

    Wang, Jianzhou; Niu, Tong; Wang, Rui

    2017-01-01

    The worsening atmospheric pollution increases the necessity of air quality early warning systems (EWSs). Despite the fact that a massive amount of investigation about EWS in theory and practicality has been conducted by numerous researchers, studies concerning the quantification of uncertain information and comprehensive evaluation are still lacking, which impedes further development in the area. In this paper, firstly a comprehensive warning system is proposed, which consists of two vital indispensable modules, namely effective forecasting and scientific evaluation, respectively. For the forecasting module, a novel hybrid model combining the theory of data preprocessing and numerical optimization is first developed to implement effective forecasting for air pollutant concentration. Especially, in order to further enhance the accuracy and robustness of the warning system, interval forecasting is implemented to quantify the uncertainties generated by forecasts, which can provide significant risk signals by using point forecasting for decision-makers. For the evaluation module, a cloud model, based on probability and fuzzy set theory, is developed to perform comprehensive evaluations of air quality, which can realize the transformation between qualitative concept and quantitative data. To verify the effectiveness and efficiency of the warning system, extensive simulations based on air pollutants data from Dalian in China were effectively implemented, which illustrate that the warning system is not only remarkably high-performance, but also widely applicable. PMID:28257122

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

    EPA Science Inventory

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

  18. Evolution of Air Quality Model at the US EPA

    EPA Science Inventory

    At the US EPA, we have developed an air quality model, CMAQ, in the past 20+ years. Throughout the years, the model has been upgraded with respect to advancement of science. We have extended the model from regional to hemispheric. We have coupled it with meteorological model, WR...

  19. 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...

  20. Experiences in evaluating regional air quality models

    NASA Astrophysics Data System (ADS)

    Liu, Mei-Kao; Greenfield, Stanley M.

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

  1. 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

  2. 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.

  3. Application of uncertainty and sensitivity analysis to the air quality SHERPA modelling tool

    NASA Astrophysics Data System (ADS)

    Pisoni, E.; Albrecht, D.; Mara, T. A.; Rosati, R.; Tarantola, S.; Thunis, P.

    2018-06-01

    Air quality has significantly improved in Europe over the past few decades. Nonetheless we still find high concentrations in measurements mainly in specific regions or cities. This dimensional shift, from EU-wide to hot-spot exceedances, calls for a novel approach to regional air quality management (to complement EU-wide existing policies). The SHERPA (Screening for High Emission Reduction Potentials on Air quality) modelling tool was developed in this context. It provides an additional tool to be used in support to regional/local decision makers responsible for the design of air quality plans. It is therefore important to evaluate the quality of the SHERPA model, and its behavior in the face of various kinds of uncertainty. Uncertainty and sensitivity analysis techniques can be used for this purpose. They both reveal the links between assumptions and forecasts, help in-model simplification and may highlight unexpected relationships between inputs and outputs. Thus, a policy steered SHERPA module - predicting air quality improvement linked to emission reduction scenarios - was evaluated by means of (1) uncertainty analysis (UA) to quantify uncertainty in the model output, and (2) by sensitivity analysis (SA) to identify the most influential input sources of this uncertainty. The results of this study provide relevant information about the key variables driving the SHERPA output uncertainty, and advise policy-makers and modellers where to place their efforts for an improved decision-making process.

  4. The Air Quality Model Evaluation International Initiative (AQMEII)

    EPA Science Inventory

    This presentation provides an overview of the Air Quality Model Evaluation International Initiative (AQMEII). It contains a synopsis of the three phases of AQMEII, including objectives, logistics, and timelines. It also provides a number of examples of analyses conducted through ...

  5. 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...

  6. Towards an operational high-resolution air quality forecasting system at ECCC

    NASA Astrophysics Data System (ADS)

    Munoz-Alpizar, Rodrigo; Stroud, Craig; Ren, Shuzhan; Belair, Stephane; Leroyer, Sylvie; Souvanlasy, Vanh; Spacek, Lubos; Pavlovic, Radenko; Davignon, Didier; Moran, Moran

    2017-04-01

    Urban environments are particularly sensitive to weather, air quality (AQ), and climatic conditions. Despite the efforts made in Canada to reduce pollution in urban areas, AQ continues to be a concern for the population, especially during short-term episodes that could lead to exceedances of daily air quality standards. Furthermore, urban air pollution has long been associated with significant adverse health effects. In Canada, the large percentage of the population living in urban areas ( 81%, according to the Canada's 2011 census) is exposed to elevated air pollution due to local emissions sources. Thus, in order to improve the services offered to the Canadian public, Environment and Climate Change Canada has launched an initiative to develop a high-resolution air quality prediction capacity for urban areas in Canada. This presentation will show observed pollution trends (2010-2016) for Canadian mega-cities along with some preliminary high-resolution air quality modelling results. Short-term and long-term plans for urban AQ forecasting in Canada will also be described.

  7. 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.

  8. A state of the art regarding urban air quality prediction models

    NASA Astrophysics Data System (ADS)

    Croitoru, Cristiana; Nastase, Ilinca

    2018-02-01

    Urban pollution represents an increasing risk to residents of urban regions, particularly in large, over-industrialized cities knowing that the traffic is responsible for more than 25% of air gaseous pollutants and dust particles. Air quality modelling plays an important role in addressing air pollution control and management approaches by providing guidelines for better and more efficient air quality forecasting, along with smart monitoring sensor networks. The advances in technology regarding simulations, forecasting and monitoring are part of the new smart cities which offers a healthy environment for their occupants.

  9. 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

  10. Highway Air Pollution Dispersion Modeling : Preliminary Evaluation of Thirteen Models

    DOT National Transportation Integrated Search

    1978-06-01

    Thirteen highway air pollution dispersion models have been tested, using a portion of the Airedale air quality data base. The Transportation Air Pollution Studies (TAPS) System, a data base management system specifically designed for evaluating dispe...

  11. Highway Air Pollution Dispersion Modeling : Preliminary Evaluation of Thirteen Models

    DOT National Transportation Integrated Search

    1977-01-01

    Thirteen highway air pollution dispersion models have been tested, using a portion of the Airedale air quality data base. The Transportation Air Pollution Studies (TAPS) System, a data base management system specifically designed for evaluating dispe...

  12. Deep learning architecture for air quality predictions.

    PubMed

    Li, Xiang; Peng, Ling; Hu, Yuan; Shao, Jing; Chi, Tianhe

    2016-11-01

    With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.

  13. 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...

  14. Modelling and analysis of ozone concentration by artificial intelligent techniques for estimating air quality

    NASA Astrophysics Data System (ADS)

    Taylan, Osman

    2017-02-01

    High ozone concentration is an important cause of air pollution mainly due to its role in the greenhouse gas emission. Ozone is produced by photochemical processes which contain nitrogen oxides and volatile organic compounds in the lower atmospheric level. Therefore, monitoring and controlling the quality of air in the urban environment is very important due to the public health care. However, air quality prediction is a highly complex and non-linear process; usually several attributes have to be considered. Artificial intelligent (AI) techniques can be employed to monitor and evaluate the ozone concentration level. The aim of this study is to develop an Adaptive Neuro-Fuzzy inference approach (ANFIS) to determine the influence of peripheral factors on air quality and pollution which is an arising problem due to ozone level in Jeddah city. The concentration of ozone level was considered as a factor to predict the Air Quality (AQ) under the atmospheric conditions. Using Air Quality Standards of Saudi Arabia, ozone concentration level was modelled by employing certain factors such as; nitrogen oxide (NOx), atmospheric pressure, temperature, and relative humidity. Hence, an ANFIS model was developed to observe the ozone concentration level and the model performance was assessed by testing data obtained from the monitoring stations established by the General Authority of Meteorology and Environment Protection of Kingdom of Saudi Arabia. The outcomes of ANFIS model were re-assessed by fuzzy quality charts using quality specification and control limits based on US-EPA air quality standards. The results of present study show that the ANFIS model is a comprehensive approach for the estimation and assessment of ozone level and is a reliable approach to produce more genuine outcomes.

  15. 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...

  16. AIR CLEANING FOR ACCEPTABLE INDOOR AIR QUALITY

    EPA Science Inventory

    The paper discusses air cleaning for acceptable indoor air quality. ir cleaning has performed an important role in heating, ventilation, and air-conditioning systems for many years. raditionally, general ventilation air-filtration equipment has been used to protect cooling coils ...

  17. Applying air pollution modelling within a multi-criteria decision analysis framework to evaluate UK air quality policies

    NASA Astrophysics Data System (ADS)

    Chalabi, Zaid; Milojevic, Ai; Doherty, Ruth M.; Stevenson, David S.; MacKenzie, Ian A.; Milner, James; Vieno, Massimo; Williams, Martin; Wilkinson, Paul

    2017-10-01

    A decision support system for evaluating UK air quality policies is presented. It combines the output from a chemistry transport model, a health impact model and other impact models within a multi-criteria decision analysis (MCDA) framework. As a proof-of-concept, the MCDA framework is used to evaluate and compare idealized emission reduction policies in four sectors (combustion in energy and transformation industries, non-industrial combustion plants, road transport and agriculture) and across six outcomes or criteria (mortality, health inequality, greenhouse gas emissions, biodiversity, crop yield and air quality legal compliance). To illustrate a realistic use of the MCDA framework, the relative importance of the criteria were elicited from a number of stakeholders acting as proxy policy makers. In the prototype decision problem, we show that reducing emissions from industrial combustion (followed very closely by road transport and agriculture) is more advantageous than equivalent reductions from the other sectors when all the criteria are taken into account. Extensions of the MCDA framework to support policy makers in practice are discussed.

  18. Air quality modeling for effective environmental management in the mining region.

    PubMed

    Asif, Zunaira; Chen, Zhi; Han, Yi

    2018-04-18

    Air quality in the mining sector is a serious environmental concern and associated with many health issues. The air quality management in mining region has been facing many challenges due to lack of understanding of atmospheric factors and physical removal mechanism. A modeling approach called mining air dispersion model (MADM) is developed to predict air pollutants concentration in the mining region while considering the deposition effect. The model is taken into account through the planet's boundary conditions and assuming that the eddy diffusivity depends on the downwind distance. The developed MADM is applied to a mining site in Canada. The model provides values as the predicted concentrations of PM 10 , PM 2.5 , TSP, NO 2 and six heavy metals (As, Pb, Hg, Cd, Zn, Cr) at various receptor locations. The model shows that neutral stability conditions are dominant for the study site. The maximum mixing height is achieved (1280 m) during the evening of summer, and minimum mixing height (380 m) is attained during the evening of winter. The dust fall (PM coarse) deposition flux is maximum during February and March with the deposition velocity of 4.67 cm/s. The results are evaluated with the monitoring field values, revealing a good agreement for the target air pollutants with R-squared ranging from 0.72 to 0.96 for PM 2.5 ; 0.71 to 0.82 for PM 10 and from 0.71 to 0.89 for NO 2 . The analyses illustrate that presented algorithm in this model can be used to assess air quality for the mining site in a systematic way. The comparison of MADM and CALPUFF modeling values are made for four different pollutants (PM 2.5 , PM 10 , TSP, and NO 2 ) under three different atmospheric stability classes (stable, neutral and unstable). Further, MADM results are statistically tested against CALPUFF for the air pollutants and model performance is found satisfactory.

  19. 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

  20. 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...

  1. Indoor Air Nuclear, Biological, and Chemical Health Modeling and Assessment System

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Stenner, Robert D.; Hadley, Donald L.; Armstrong, Peter R.

    2001-03-01

    Indoor air quality effects on human health are of increasing concern to public health agencies and building owners. The prevention and treatment of 'sick building' syndrome and the spread of air-borne diseases in hospitals, for example, are well known priorities. However, increasing attention is being directed to the vulnerability of our public buildings/places, public security and national defense facilities to terrorist attack or the accidental release of air-borne biological pathogens, harmful chemicals, or radioactive contaminants. The Indoor Air Nuclear, Biological, and Chemical Health Modeling and Assessment System (IA-NBC-HMAS) was developed to serve as a health impact analysis tool for usemore » in addressing these concerns. The overall goal was to develop a user-friendly fully functional prototype Health Modeling and Assessment system, which will operate under the PNNL FRAMES system for ease of use and to maximize its integration with other modeling and assessment capabilities accessible within the FRAMES system (e.g., ambient air fate and transport models, water borne fate and transport models, Physiologically Based Pharmacokinetic models, etc.). The prototype IA-NBC-HMAS is designed to serve as a functional Health Modeling and Assessment system that can be easily tailored to meet specific building analysis needs of a customer. The prototype system was developed and tested using an actual building (i.e., the Churchville Building located at the Aberdeen Proving Ground) and release scenario (i.e., the release and measurement of tracer materials within the building) to ensure realism and practicality in the design and development of the prototype system. A user-friendly "demo" accompanies this report to allow the reader the opportunity for a "hands on" review of the prototype system's capability.« less

  2. Indicators to support the dynamic evaluation of air quality models

    NASA Astrophysics Data System (ADS)

    Thunis, P.; Clappier, A.

    2014-12-01

    Air quality models are useful tools for the assessment and forecast of pollutant concentrations in the atmosphere. Most of the evaluation process relies on the “operational phase” or in other words the comparison of model results with available measurements which provides insight on the model capability to reproduce measured concentrations for a given application. But one of the key advantages of air quality models lies in their ability to assess the impact of precursor emission reductions on air quality levels. Models are then used in a dynamic mode (i.e. response to a change in a given model input data) for which evaluation of the model performances becomes a challenge. The objective of this work is to propose common indicators and diagrams to facilitate the understanding of model responses to emission changes when models are to be used for policy support. These indicators are shown to be useful to retrieve information on the magnitude of the locally produced impacts of emission reductions on concentrations with respect to the “external to the domain” contribution but also to identify, distinguish and quantify impacts arising from different factors (different precursors). In addition information about the robustness of the model results is provided. As such these indicators might reveal useful as first screening methodology to identify the feasibility of a given action as well as to prioritize the factors on which to act for an increased efficiency. Finally all indicators are made dimensionless to facilitate the comparison of results obtained with different models, different resolutions, or on different geographical areas.

  3. Air carrier operations system model

    DOT National Transportation Integrated Search

    2001-03-01

    Representatives from the Federal Aviation Administration (FAA) and several 14 Code of Federal Regulations (CFR) Part 121 air carriers met several times during 1999-2000 to develop a system engineering model of the generic functions of air carrier ope...

  4. Ambient Air Quality Data Inventory

    EPA Pesticide Factsheets

    The Office of Air and Radiation's (OAR) Ambient Air Quality Data (Current) contains ambient air pollution data collected by EPA, other federal agencies, as well as state, local, and tribal air pollution control agencies. Its component data sets have been collected over the years from approximately 10,000 monitoring sites, of which approximately 5,000 are currently active. OAR's Office of Air Quality Planning and Standards (OAQPS) and other internal and external users, rely on this data to assess air quality, assist in Attainment/Non-Attainment designations, evaluate State Implementation Plans for Non-Attainment Areas, perform modeling for permit review analysis, and other air quality management functions. Air quality information is also used to prepare reports for Congress as mandated by the Clean Air Act. This data covers air quality data collected after 1980, when the Clean Air Act requirements for monitoring were significantly modified. Air quality data from the Agency's early years (1970s) remains available (see OAR PRIMARY DATA ASSET: Ambient Air Quality Data -- Historical), but because of technical and definitional differences the two data assets are not directly comparable. The Clean Air Act of 1970 provided initial authority for monitoring air quality for Conventional Air Pollutants (CAPs) for which EPA has promulgated National Ambient Air Quality Standards (NAAQS). Requirements for monitoring visibility-related parameters were added in 1977. Requiremen

  5. Air Quality Forecasts Using the NASA GEOS Model: A Unified Tool from Local to Global Scales

    NASA Technical Reports Server (NTRS)

    Knowland, E. Emma; Keller, Christoph; Nielsen, J. Eric; Orbe, Clara; Ott, Lesley; Pawson, Steven; Saunders, Emily; Duncan, Bryan; Cook, Melanie; Liu, Junhua; hide

    2017-01-01

    We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (approximately 25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). The resolution of the forecasts is the highest resolution compared to current, publically-available global composition forecasts. Evaluation and validation of modeled trace gases and aerosols compared to surface and satellite observations will be presented for constituents relative to health air quality standards. Comparisons of modeled trace gases and aerosols against satellite observations show that the model produces realistic concentrations of atmospheric constituents in the free troposphere. Model comparisons against surface observations highlight the model's capability to capture the diurnal variability of air pollutants under a variety of meteorological conditions. The GEOS-5 composition forecasting system offers a new tool for scientists and the public health community, and is being developed jointly with several government and non-profit partners. Potential applications include air quality warnings, flight campaign planning and exposure studies using the archived analysis fields.

  6. Indoor Air Quality and Energy Efficiency

    EPA Pesticide Factsheets

    EPA completed an extensive modeling study to assess the compatibilities and trade-offs between energy, indoor air quality, and thermal comfort objectives for HVAC systems and to formulate strategies for superior performance across all areas.

  7. The microbiological quality of air improves when using air conditioning systems in cars.

    PubMed

    Vonberg, Ralf-Peter; Gastmeier, Petra; Kenneweg, Björn; Holdack-Janssen, Hinrich; Sohr, Dorit; Chaberny, Iris F

    2010-06-01

    Because of better comfort, air conditioning systems are a common feature in automobiles these days. However, its impact on the number of particles and microorganisms inside the vehicle--and by this its impact on the risk of an allergic reaction--is yet unknown. Over a time period of 30 months, the quality of air was investigated in three different types of cars (VW Passat, VW Polo FSI, Seat Alhambra) that were all equipped with a automatic air conditioning system. Operation modes using fresh air from outside the car as well as circulating air from inside the car were examined. The total number of microorganisms and the number of mold spores were measured by impaction in a high flow air sampler. Particles of 0.5 to 5.0 microm diameter were counted by a laser particle counter device. Overall 32 occasions of sampling were performed. The concentration of microorganisms outside the cars was always higher than it was inside the cars. Few minutes after starting the air conditioning system the total number of microorganisms was reduced by 81.7%, the number of mold spores was reduced by 83.3%, and the number of particles was reduced by 87.8%. There were no significant differences neither between the types of cars nor between the types of operation mode of the air conditioning system (fresh air vs. circulating air). All parameters that were looked for in this study improved during utilization of the car's air conditioning system. We believe that the risk of an allergic reaction will be reduced during use also. Nevertheless, we recommend regular maintenance of the system and replacement of older filters after defined changing intervals.

  8. 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

  9. 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.

  10. An emission processing system for air quality modelling in the Mexico City metropolitan area: Evaluation and comparison of the MOBILE6.2-Mexico and MOVES-Mexico traffic emissions.

    PubMed

    Guevara, M; Tena, C; Soret, A; Serradell, K; Guzmán, D; Retama, A; Camacho, P; Jaimes-Palomera, M; Mediavilla, A

    2017-04-15

    This article describes the High-Elective Resolution Modelling Emission System for Mexico (HERMES-Mex) model, an emission processing tool developed to transform the official Mexico City Metropolitan Area (MCMA) emission inventory into hourly, gridded (up to 1km 2 ) and speciated emissions used to drive mesoscale air quality simulations with the Community Multi-scale Air Quality (CMAQ) model. The methods and ancillary information used for the spatial and temporal disaggregation and speciation of the emissions are presented and discussed. The resulting emission system is evaluated, and a case study on CO, NO 2 , O 3 , VOC and PM 2.5 concentrations is conducted to demonstrate its applicability. Moreover, resulting traffic emissions from the Mobile Source Emission Factor Model for Mexico (MOBILE6.2-Mexico) and the MOtor Vehicle Emission Simulator for Mexico (MOVES-Mexico) models are integrated in the tool to assess and compare their performance. NO x and VOC total emissions modelled are reduced by 37% and 26% in the MCMA when replacing MOBILE6.2-Mexico for MOVES-Mexico traffic emissions. In terms of air quality, the system composed by the Weather Research and Forecasting model (WRF) coupled with the HERMES-Mex and CMAQ models properly reproduces the pollutant levels and patterns measured in the MCMA. The system's performance clearly improves in urban stations with a strong influence of traffic sources when applying MOVES-Mexico emissions. Despite reducing estimations of modelled precursor emissions, O 3 peak averages are increased in the MCMA core urban area (up to 30ppb) when using MOVES-Mexico mobile emissions due to its VOC-limited regime, while concentrations in the surrounding suburban/rural areas decrease or increase depending on the meteorological conditions of the day. The results obtained suggest that the HERMES-Mex model can be used to provide model-ready emissions for air quality modelling in the MCMA. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  12. 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.

  13. The microbiological quality of air improves when using air conditioning systems in cars

    PubMed Central

    2010-01-01

    Background Because of better comfort, air conditioning systems are a common feature in automobiles these days. However, its impact on the number of particles and microorganisms inside the vehicle - and by this its impact on the risk of an allergic reaction - is yet unknown. Methods Over a time period of 30 months, the quality of air was investigated in three different types of cars (VW Passat, VW Polo FSI, Seat Alhambra) that were all equipped with a automatic air conditioning system. Operation modes using fresh air from outside the car as well as circulating air from inside the car were examined. The total number of microorganisms and the number of mold spores were measured by impaction in a high flow air sampler. Particles of 0.5 to 5.0 μm diameter were counted by a laser particle counter device. Results Overall 32 occasions of sampling were performed. The concentration of microorganisms outside the cars was always higher than it was inside the cars. Few minutes after starting the air conditioning system the total number of microorganisms was reduced by 81.7%, the number of mold spores was reduced by 83.3%, and the number of particles was reduced by 87.8%. There were no significant differences neither between the types of cars nor between the types of operation mode of the air conditioning system (fresh air vs. circulating air). All parameters that were looked for in this study improved during utilization of the car's air conditioning system. Conclusions We believe that the risk of an allergic reaction will be reduced during use also. Nevertheless, we recommend regular maintenance of the system and replacement of older filters after defined changing intervals. PMID:20515449

  14. Webinar: Clean Air in the Classroom: Improve Air Quality, Extend HVAC System Life with Preventive Maintenance

    EPA Pesticide Factsheets

    A page to register to view the May 17, 2018, webinar in the IAQ Knowledge-to-Action Professional Training Webinar Series: Clean Air in the Classroom: Improve Air Quality, Extend HVAC System Life with Preventive Maintenance

  15. 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...

  16. 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...

  17. 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

  18. 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

  19. Diagnostic Air Quality Model Evaluation of Source-Specific ...

    EPA Pesticide Factsheets

    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/m3 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/m3 on average). Several instances of compensating errors were also evident; model underpredictions in some sectors were masked by overpredictions in others. The National Exposure Research L

  20. 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.

  1. 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...

  2. 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.

  3. 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...

  4. DYNAMIC ELECTRICITY GENERATION FOR ADDRESSING DAILY AIR QUALITY EXCEEDANCES IN THE US

    EPA Science Inventory

    We will design, demonstrate, and evaluate a dynamic management system for managing daily air quality, exploring different elements of the design of this system such as how air quality forecasts can best be used, and decision rules for the electrical dispatch model. We will ...

  5. AIR QUALITY FORECAST DATABASE AND ANALYSIS

    EPA Science Inventory

    In 2003, NOAA and EPA signed a Memorandum of Agreement to collaborate on the design and implementation of a capability to produce daily air quality modeling forecast information for the U.S. NOAA's ETA meteorological model and EPA's Community Multiscale Air Quality (CMAQ) model ...

  6. 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.

  7. 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

  8. The Benefits of Internalizing Air Quality and Greenhouse Gas Externalities in the US Energy System

    NASA Astrophysics Data System (ADS)

    Brown, Kristen E.

    The emission of pollutants from energy use has effects on both local air quality and the global climate, but the price of energy does not reflect these externalities. This study aims to analyze the effect that internalizing these externalities in the cost of energy would have on the US energy system, emissions, and human health. In this study, we model different policy scenarios in which fees are added to emissions related to generation and use of energy. The fees are based on values of damages estimated in the literature and are applied to upstream and combustion emissions related to electricity generation, industrial energy use, transportation energy use, residential energy use, and commercial energy use. The energy sources and emissions are modeled through 2055 in five-year time steps. The emissions in 2045 are incorporated into a continental-scale atmospheric chemistry and transport model, CMAQ, to determine the change in air quality due to different emissions reduction scenarios. A benefit analysis tool, BenMAP, is used with the air quality results to determine the monetary benefit of emissions reductions related to the improved air quality. We apply fees to emissions associated with health impacts, climate change, and a combination of both. We find that the fees we consider lead to reductions in targeted emissions as well as co-reducing non-targeted emissions. For fees on the electric sector alone, health impacting pollutant (HIP) emissions reductions are achieved mainly through control devices while Greenhouse Gas (GHG) fees are addressed through changes in generation technologies. When sector specific fees are added, reductions come mainly from the industrial and electricity generation sectors, and are achieved through a mix of energy efficiency, increased use of renewables, and control devices. Air quality is improved in almost all areas of the country with fees, including when only GHG fees are applied. Air quality tends to improve more in regions with

  9. 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

  10. Co-benefits of air quality and climate change policies on air quality of the Mediterranean

    NASA Astrophysics Data System (ADS)

    Pozzoli, Luca; Mert Gokturk, Ozan; Unal, Alper; Kindap, Tayfun; Janssens-Maenhout, Greet

    2015-04-01

    The Mediterranean basin is one of the regions of the world where significant impacts due to climate changes are predicted to occur in the future. Observations and model simulations are used to provide to the policy makers scientifically based estimates of the necessity to adjust national emission reductions needed to achieve air quality objectives in the context of a changing climate, which is not only driven by GHGs, but also by short lived climate pollutants, such as tropospheric ozone and aerosols. There is an increasing interest and need to design cost-benefit emission reduction strategies, which could improve both regional air quality and global climate change. In this study we used the WRF-CMAQ air quality modelling system to quantify the contribution of anthropogenic emissions to ozone and particulate matter concentrations in Europe and the Eastern Mediterranean and to understand how this contribution could change in different future scenarios. We have investigated four different future scenarios for year 2050 defined during the European Project CIRCE: a "business as usual" scenario (BAU) where no or just actual measures are taken into account; an "air quality" scenario (BAP) which implements the National Emission Ceiling directive 2001/81/EC member states of the European Union (EU-27); a "climate change" scenario (CC) which implements global climate policies decoupled from air pollution policies; and an "integrated air quality and climate policy" scenario (CAP) which explores the co-benefit of global climate and EU-27 air pollution policies. The BAP scenario largely decreases summer ozone concentrations over almost the entire continent, while the CC and CAP scenarios similarly determine lower decreases in summer ozone but extending all over the Mediterranean, the Middle East countries and Russia. Similar patterns are found for winter PM concentrations; BAP scenario improves pollution levels only in the Western EU countries, and the CAP scenario determines

  11. 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…

  12. 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.

  13. 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...

  14. 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.

  15. 75 FR 71033 - Air Quality Designations for the 2008 Lead (Pb) National Ambient Air Quality Standards

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-22

    .... These include damage to the central nervous system, cardiovascular function, kidneys, immune system, and... growth); (5) Meteorology (weather/transport patterns); (6) Geography/topography (mountain ranges or other... Air Quality Designations for the 2008 Lead (Pb) National Ambient Air Quality Standards AGENCY...

  16. 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...

  17. Enabling Mobile Air Quality App Development with an AirNow API

    NASA Astrophysics Data System (ADS)

    Dye, T.; White, J. E.; Ludewig, S. A.; Dickerson, P.; Healy, A. N.; West, J. W.; Prince, L. A.

    2013-12-01

    The U.S. Environmental Protection Agency's (EPA) AirNow program works with over 130 participating state, local, and federal air quality agencies to obtain, quality control, and store real-time air quality observations and forecasts. From these data, the AirNow system generates thousands of maps and products each hour. Each day, information from AirNow is published online and in other media to assist the public in making health-based decisions related to air quality. However, an increasing number of people use mobile devices as their primary tool for obtaining information, and AirNow has responded to this trend by publishing an easy-to-use Web API that is useful for mobile app developers. This presentation will describe the various features of the AirNow application programming interface (API), including Representational State Transfer (REST)-type web services, file outputs, and RSS feeds. In addition, a web portal for the AirNow API will be shown, including documentation on use of the system, a query tool for configuring and running web services, and general information about the air quality data and forecasts available. Data published via the AirNow API includes corresponding Air Quality Index (AQI) levels for each pollutant. We will highlight examples of mobile apps that are using the AirNow API to provide location-based, real-time air quality information. Examples will include mobile apps developed for Minnesota ('Minnesota Air') and Washington, D.C. ('Clean Air Partners Air Quality'), and an app developed by EPA ('EPA AirNow').

  18. APPLICATION OF BIAS AND ADJUSTMENT TECHNIQUES TO THE ETA-CMAQ AIR QUALITY FORECAST

    EPA Science Inventory

    The current air quality forecast system, based on linking NOAA's Eta meteorological model with EPA's Community Multiscale Air Quality (CMAQ) model, consistently overpredicts surface ozone concentrations, but simulates its day-to-day variability quite well. The ability of bias cor...

  19. Ozone deposition modelling within the Air Quality Model Evaluation International Initiative (AQMEII)

    EPA Science Inventory

    This presentation provides an overview of the Air Quality Model Evaluation International Initiative (AQMEII). It contains a synopsis of the three phases of AQMEII, including objectives, logistics, and timelines. It also provides a number of examples of analyses conducted through ...

  20. The Air Quality Model Evaluation International Initiative ...

    EPA Pesticide Factsheets

    This presentation provides an overview of the Air Quality Model Evaluation International Initiative (AQMEII). It contains a synopsis of the three phases of AQMEII, including objectives, logistics, and timelines. It also provides a number of examples of analyses conducted through AQMEII with a particular focus on past and future analyses of deposition. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    PubMed

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

    2011-06-01

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

  3. Research and application of a novel hybrid air quality early-warning system: A case study in China.

    PubMed

    Li, Chen; Zhu, Zhijie

    2018-06-01

    As one of the most serious meteorological disasters in modern society, air pollution has received extensive attention from both citizens and decision-makers. With the complexity of pollution components and the uncertainty of prediction, it is both critical and challenging to construct an effective and practical early-warning system. In this paper, a novel hybrid air quality early-warning system for pollution contaminant monitoring and analysis was proposed. To improve the efficiency of the system, an advanced attribute selection method based on fuzzy evaluation and rough set theory was developed to select the main pollution contaminants for cities. Moreover, a hybrid model composed of the theory of "decomposition and ensemble", an extreme learning machine and an advanced heuristic algorithm was developed for pollution contaminant prediction; it provides deterministic and interval forecasting for tackling the uncertainty of future air quality. Daily pollution contaminants of six major cities in China were selected as a dataset to evaluate the practicality and effectiveness of the developed air quality early-warning system. The superior experimental performance determined by the values of several error indexes illustrated that the proposed early-warning system was of great effectiveness and efficiency. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. 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...

  5. The Economic Value of Air Quality Forecasting

    NASA Astrophysics Data System (ADS)

    Anderson-Sumo, Tasha

    Both long-term and daily air quality forecasts provide an essential component to human health and impact costs. According the American Lung Association, the estimated current annual cost of air pollution related illness in the United States, adjusted for inflation (3% per year), is approximately $152 billion. Many of the risks such as hospital visits and morality are associated with poor air quality days (where the Air Quality Index is greater than 100). Groups such as sensitive groups become more susceptible to the resulting conditions and more accurate forecasts would help to take more appropriate precautions. This research focuses on evaluating the utility of air quality forecasting in terms of its potential impacts by building on air quality forecasting and economical metrics. Our analysis includes data collected during the summertime ozone seasons between 2010 and 2012 from air quality models for the Washington, DC/Baltimore, MD region. The metrics that are relevant to our analysis include: (1) The number of times that a high ozone or particulate matter (PM) episode is correctly forecasted, (2) the number of times that high ozone or PM episode is forecasted when it does not occur and (3) the number of times when the air quality forecast predicts a cleaner air episode when the air was observed to have high ozone or PM. Our collection of data included available air quality model forecasts of ozone and particulate matter data from the U.S. Environmental Protection Agency (EPA)'s AIRNOW as well as observational data of ozone and particulate matter from Clean Air Partners. We evaluated the performance of the air quality forecasts with that of the observational data and found that the forecast models perform well for the Baltimore/Washington region and the time interval observed. We estimate the potential amount for the Baltimore/Washington region accrues to a savings of up to 5,905 lives and 5.9 billion dollars per year. This total assumes perfect compliance with

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

    PubMed

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

    2014-02-01

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

  7. 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

  8. GNAQPMS v1.1: accelerating the Global Nested Air Quality Prediction Modeling System (GNAQPMS) on Intel Xeon Phi processors

    NASA Astrophysics Data System (ADS)

    Wang, Hui; Chen, Huansheng; Wu, Qizhong; Lin, Junmin; Chen, Xueshun; Xie, Xinwei; Wang, Rongrong; Tang, Xiao; Wang, Zifa

    2017-08-01

    The Global Nested Air Quality Prediction Modeling System (GNAQPMS) is the global version of the Nested Air Quality Prediction Modeling System (NAQPMS), which is a multi-scale chemical transport model used for air quality forecast and atmospheric environmental research. In this study, we present the porting and optimisation of GNAQPMS on a second-generation Intel Xeon Phi processor, codenamed Knights Landing (KNL). Compared with the first-generation Xeon Phi coprocessor (codenamed Knights Corner, KNC), KNL has many new hardware features such as a bootable processor, high-performance in-package memory and ISA compatibility with Intel Xeon processors. In particular, we describe the five optimisations we applied to the key modules of GNAQPMS, including the CBM-Z gas-phase chemistry, advection, convection and wet deposition modules. These optimisations work well on both the KNL 7250 processor and the Intel Xeon E5-2697 V4 processor. They include (1) updating the pure Message Passing Interface (MPI) parallel mode to the hybrid parallel mode with MPI and OpenMP in the emission, advection, convection and gas-phase chemistry modules; (2) fully employing the 512 bit wide vector processing units (VPUs) on the KNL platform; (3) reducing unnecessary memory access to improve cache efficiency; (4) reducing the thread local storage (TLS) in the CBM-Z gas-phase chemistry module to improve its OpenMP performance; and (5) changing the global communication from writing/reading interface files to MPI functions to improve the performance and the parallel scalability. These optimisations greatly improved the GNAQPMS performance. The same optimisations also work well for the Intel Xeon Broadwell processor, specifically E5-2697 v4. Compared with the baseline version of GNAQPMS, the optimised version was 3.51 × faster on KNL and 2.77 × faster on the CPU. Moreover, the optimised version ran at 26 % lower average power on KNL than on the CPU. With the combined performance and energy

  9. 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.

  10. Study of Regional Downscaled Climate and Air Quality in the United States

    NASA Astrophysics Data System (ADS)

    Gao, Y.; Fu, J. S.; Drake, J.; Lamarque, J.; Lam, Y.; Huang, K.

    2011-12-01

    Due to the increasing anthropogenic greenhouse gas emissions, the global and regional climate patterns have significantly changed. Climate change has exerted strong impact on ecosystem, air quality and human life. The global model Community Earth System Model (CESM v1.0) was used to predict future climate and chemistry under projected emission scenarios. Two new emission scenarios, Representative Community Pathways (RCP) 4.5 and RCP 8.5, were used in this study for climate and chemistry simulations. The projected global mean temperature will increase 1.2 and 1.7 degree Celcius for the RCP 4.5 and RCP 8.5 scenarios in 2050s, respectively. In order to take advantage of local detailed topography, land use data and conduct local climate impact on air quality, we downscaled CESM outputs to 4 km by 4 km Eastern US domain using Weather Research and Forecasting (WRF) Model and Community Multi-scale Air Quality modeling system (CMAQ). The evaluations between regional model outputs and global model outputs, regional model outputs and observational data were conducted to verify the downscaled methodology. Future climate change and air quality impact were also examined on a 4 km by 4 km high resolution scale.

  11. Air Quality Modeling Using the NASA GEOS-5 Multispecies Data Assimilation System

    NASA Technical Reports Server (NTRS)

    Keller, Christoph A.; Pawson, Steven; Wargan, Krzysztof; Weir, Brad

    2018-01-01

    The NASA Goddard Earth Observing System (GEOS) data assimilation system (DAS) has been expanded to include chemically reactive tropospheric trace gases including ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). This system combines model analyses from the GEOS-5 model with detailed atmospheric chemistry and observations from MLS (O3), OMI (O3 and NO2), and MOPITT (CO). We show results from a variety of assimilation test experiments, highlighting the improvements in the representation of model species concentrations by up to 50% compared to an assimilation-free control experiment. Taking into account the rapid chemical cycling of NO2 when applying the assimilation increments greatly improves assimilation skills for NO2 and provides large benefits for model concentrations near the surface. Analysis of the geospatial distribution of the assimilation increments suggest that the free-running model overestimates biomass burning emissions but underestimates lightning NOx emissions by 5-20%. We discuss the capability of the chemical data assimilation system to improve atmospheric composition forecasts through improved initial value and boundary condition inputs, particularly during air pollution events. We find that the current assimilation system meaningfully improves short-term forecasts (1-3 day). For longer-term forecasts more emphasis on updating the emissions instead of initial concentration fields is needed.

  12. 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...

  13. Assessment of environmental co-benefits of energy system decarbonisation - the case of UK air quality using Remote Sensing and Model simulations

    NASA Astrophysics Data System (ADS)

    Sobral Mourao, Z.; Konadu, D. D.; Damoah, R.

    2016-12-01

    The UK has a binding obligation to reduce GHG emission by 80% (based on 1990 levels) by 2050. Meeting this target requires extensive decarbonisation of the UK energy system. Different pathways that achieve this target at the lowest system costs are being explored at different levels of policy and decisions on future energy infrastructure. Whilst benefits of decarbonisation are mainly focused on the impacts on climate change, there are other potential environmental and health impacts such as air-quality. In particular, a decrease in fossil fuel use by directly substituting current systems with low-carbon technologies could lead to significant reductions in the concentrations of SO2, NOX, CO and other atmospheric pollutants. So far, the proposed decarbonisation pathways tend to target the electricity sector first, followed by a transition in transport and heating technologies and use. However, the spatial dimension of where short term changes in the energy sector occur in relation to high density population areas is not taken into account when defining the energy transition strategies. This may lead to limited short-term improvements in air quality within urban areas, where use of fossil fuels for heating and transport is the main contribution to overall atmospheric pollutant levels. It is therefore imperative to explore decarbonisation strategies that prioritise transition in sectors of the energy system that produce immediate improvements in air quality in key regions of the UK. This study aims to use a combination of Remote Sensing observations and atmospheric chemistry/transport modelling approaches to estimate and map the atmospheric pollutants impact of the traditional approach of decarbonising electricity first compared to a slower transition in the electricity sector, but faster change in end use sectors (heating and transport). This would provide an additional standard to compare future energy system pathways beyond the traditional metrics of cost and GHG

  14. An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning

    PubMed Central

    Jo, ByungWan

    2018-01-01

    The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH4, CO, SO2, and H2S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R2 and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality. PMID:29561777

  15. An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning.

    PubMed

    Jo, ByungWan; Khan, Rana Muhammad Asad

    2018-03-21

    The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH₄, CO, SO₂, and H₂S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R ² and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality.

  16. Progress on Implementing Additional Physics Schemes into MPAS-A v5.1 for Next Generation Air Quality Modeling

    EPA Science Inventory

    The U.S. Environmental Protection Agency (USEPA) has a team of scientists developing a next generation air quality modeling system employing the Model for Prediction Across Scales – Atmosphere (MPAS-A) as its meteorological foundation. Several preferred physics schemes and ...

  17. 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

  18. [Assessment of the air quality improment of cleaning and disinfection on central air-conditioning ventilation system].

    PubMed

    Liu, Hongliang; Zhang, Lei; Feng, Lihong; Wang, Fei; Xue, Zhiming

    2009-09-01

    To assess the effect of air quality of cleaning and disinfection on central air-conditioning ventilation systems. 102 air-conditioning ventilation systems in 46 public facilities were sampled and investigated based on Hygienic assessment criterion of cleaning and disinfection of public central air-conditioning systems. Median dust volume decreased from 41.8 g/m2 to 0.4 g/m2, and the percentage of pipes meeting the national standard for dust decreased from 17.3% (13/60) to 100% (62/62). In the dust, median aerobic bacterial count decreased from 14 cfu/cm2 to 1 cfu/cm2. Median aerobic fungus count decreased from 10 cfu/cm2 to 0 cfu/cm2. The percentage of pipes with bacterial and fungus counts meeting the national standard increased from 92.4% (171/185) and 82.2% (152/185) to 99.4% (165/166) and 100% (166/166), respectively. In the ventilation air, median aerobic bacterial count decreased from 756 cfu/m3 to 229 cfu/m3. Median aerobic fungus count decreased from 382 cfu/m3 to 120 cfu/m3. The percentage of pipes meeting the national standard for ventilation air increased from 33.3% (81/243) and 62.1% (151/243) to 79.8% (292/366) and 87.7% (242/276), respectively. But PM10 rose from 0.060 mg/m3 to 0.068 mg/m3, and the percentage of pipes meeting the national standard for PM10 increased from 74.2% (13/60) to 90.2% (46/51). The cleaning and disinfection of central air-conditioning ventilation systems could have a beneficial effect of air quality.

  19. 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...

  20. 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.

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

    EPA Science Inventory

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

  2. Air Quality Modeling Technical Support Document for the 2015 Ozone NAAQS Preliminary Interstate Transport Assessment

    EPA Pesticide Factsheets

    In this technical support document (TSD) EPA describes the air quality modeling performed to support the 2015 ozone National Ambient Air Quality Standards (NAAQS) preliminary interstate transport assessment Notice of Data Availability (NODA).

  3. Recent Enhancements to the Community Multiscale Air Quality Model (CMAQ)

    EPA Science Inventory

    This presentation overviews recent updates to the CMAQ modeling system. The presentation will be given as part of the information exchange session on Regional Air Pollution Modeling at the UK-US Collaboration Meeting on Air Pollution Exposure Science.

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

    PubMed

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

    2010-03-01

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

  5. Daily air quality index forecasting with hybrid models: A case in China.

    PubMed

    Zhu, Suling; Lian, Xiuyuan; Liu, Haixia; Hu, Jianming; Wang, Yuanyuan; Che, Jinxing

    2017-12-01

    Air quality is closely related to quality of life. Air pollution forecasting plays a vital role in air pollution warnings and controlling. However, it is difficult to attain accurate forecasts for air pollution indexes because the original data are non-stationary and chaotic. The existing forecasting methods, such as multiple linear models, autoregressive integrated moving average (ARIMA) and support vector regression (SVR), cannot fully capture the information from series of pollution indexes. Therefore, new effective techniques need to be proposed to forecast air pollution indexes. The main purpose of this research is to develop effective forecasting models for regional air quality indexes (AQI) to address the problems above and enhance forecasting accuracy. Therefore, two hybrid models (EMD-SVR-Hybrid and EMD-IMFs-Hybrid) are proposed to forecast AQI data. The main steps of the EMD-SVR-Hybrid model are as follows: the data preprocessing technique EMD (empirical mode decomposition) is utilized to sift the original AQI data to obtain one group of smoother IMFs (intrinsic mode functions) and a noise series, where the IMFs contain the important information (level, fluctuations and others) from the original AQI series. LS-SVR is applied to forecast the sum of the IMFs, and then, S-ARIMA (seasonal ARIMA) is employed to forecast the residual sequence of LS-SVR. In addition, EMD-IMFs-Hybrid first separately forecasts the IMFs via statistical models and sums the forecasting results of the IMFs as EMD-IMFs. Then, S-ARIMA is employed to forecast the residuals of EMD-IMFs. To certify the proposed hybrid model, AQI data from June 2014 to August 2015 collected from Xingtai in China are utilized as a test case to investigate the empirical research. In terms of some of the forecasting assessment measures, the AQI forecasting results of Xingtai show that the two proposed hybrid models are superior to ARIMA, SVR, GRNN, EMD-GRNN, Wavelet-GRNN and Wavelet-SVR. Therefore, the

  6. 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...

  7. A Context-Aware Indoor Air Quality System for Sudden Infant Death Syndrome Prevention

    PubMed Central

    De Paz, Juan F.; Barriuso, Alberto L.

    2018-01-01

    Context-aware monitoring systems designed for e-Health solutions and ambient assisted living (AAL) play an important role in today’s personalized health-care services. The majority of these systems are intended for the monitoring of patients’ vital signs by means of bio-sensors. At present, there are very few systems that monitor environmental conditions and air quality in the homes of users. A home’s environmental conditions can have a significant influence on the state of the health of its residents. Monitoring the environment is the key to preventing possible diseases caused by conditions that do not favor health. This paper presents a context-aware system that monitors air quality to prevent a specific health problem at home. The aim of this system is to reduce the incidence of the Sudden Infant Death Syndrome, which is triggered mainly by environmental factors. In the conducted case study, the system monitored the state of the neonate and the quality of air while it was asleep. The designed proposal is characterized by its low cost and non-intrusive nature. The results are promising. PMID:29498653

  8. A Context-Aware Indoor Air Quality System for Sudden Infant Death Syndrome Prevention.

    PubMed

    De La Iglesia, Daniel H; De Paz, Juan F; Villarrubia González, Gabriel; Barriuso, Alberto L; Bajo, Javier

    2018-03-02

    Context-aware monitoring systems designed for e-Health solutions and ambient assisted living (AAL) play an important role in today's personalized health-care services. The majority of these systems are intended for the monitoring of patients' vital signs by means of bio-sensors. At present, there are very few systems that monitor environmental conditions and air quality in the homes of users. A home's environmental conditions can have a significant influence on the state of the health of its residents. Monitoring the environment is the key to preventing possible diseases caused by conditions that do not favor health. This paper presents a context-aware system that monitors air quality to prevent a specific health problem at home. The aim of this system is to reduce the incidence of the Sudden Infant Death Syndrome, which is triggered mainly by environmental factors. In the conducted case study, the system monitored the state of the neonate and the quality of air while it was asleep. The designed proposal is characterized by its low cost and non-intrusive nature. The results are promising.

  9. 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.

  10. Indoor Air Quality in the Metro System in North Taiwan.

    PubMed

    Chen, Ying-Yi; Sung, Fung-Chang; Chen, Mei-Lien; Mao, I-Fang; Lu, Chung-Yen

    2016-12-02

    Indoor air pollution is an increasing health concern, especially in enclosed environments such as underground subway stations because of increased global usage by urban populations. This study measured the indoor air quality of underground platforms at 10 metro stations of the Taipei Rapid Transit system (TRTS) in Taiwan, including humidity, temperature, carbon monoxide (CO), carbon dioxide (CO₂), formaldehyde (HCHO), total volatile organic compounds (TVOCs), ozone (O₃), airborne particulate matter (PM 10 and PM 2.5 ), bacteria and fungi. Results showed that the CO₂, CO and HCHO levels met the stipulated standards as regulated by Taiwan's Indoor Air Quality Management Act (TIAQMA). However, elevated PM 10 and PM 2.5 levels were measured at most stations. TVOCs and bacterial concentrations at some stations measured in summer were higher than the regulated standards stipulated by Taiwan's Environmental Protection Administration. Further studies should be conducted to reduce particulate matters, TVOCs and bacteria in the air of subway stations.

  11. Indoor Air Quality in the Metro System in North Taiwan

    PubMed Central

    Chen, Ying-Yi; Sung, Fung-Chang; Chen, Mei-Lien; Mao, I-Fang; Lu, Chung-Yen

    2016-01-01

    Indoor air pollution is an increasing health concern, especially in enclosed environments such as underground subway stations because of increased global usage by urban populations. This study measured the indoor air quality of underground platforms at 10 metro stations of the Taipei Rapid Transit system (TRTS) in Taiwan, including humidity, temperature, carbon monoxide (CO), carbon dioxide (CO2), formaldehyde (HCHO), total volatile organic compounds (TVOCs), ozone (O3), airborne particulate matter (PM10 and PM2.5), bacteria and fungi. Results showed that the CO2, CO and HCHO levels met the stipulated standards as regulated by Taiwan’s Indoor Air Quality Management Act (TIAQMA). However, elevated PM10 and PM2.5 levels were measured at most stations. TVOCs and bacterial concentrations at some stations measured in summer were higher than the regulated standards stipulated by Taiwan’s Environmental Protection Administration. Further studies should be conducted to reduce particulate matters, TVOCs and bacteria in the air of subway stations. PMID:27918460

  12. Ensemble prediction of air quality using the WRF/CMAQ model system for health effect studies in China

    NASA Astrophysics Data System (ADS)

    Hu, Jianlin; Li, Xun; Huang, Lin; Ying, Qi; Zhang, Qiang; Zhao, Bin; Wang, Shuxiao; Zhang, Hongliang

    2017-11-01

    Accurate exposure estimates are required for health effect analyses of severe air pollution in China. Chemical transport models (CTMs) are widely used to provide spatial distribution, chemical composition, particle size fractions, and source origins of air pollutants. The accuracy of air quality predictions in China is greatly affected by the uncertainties of emission inventories. The Community Multiscale Air Quality (CMAQ) model with meteorological inputs from the Weather Research and Forecasting (WRF) model were used in this study to simulate air pollutants in China in 2013. Four simulations were conducted with four different anthropogenic emission inventories, including the Multi-resolution Emission Inventory for China (MEIC), the Emission Inventory for China by School of Environment at Tsinghua University (SOE), the Emissions Database for Global Atmospheric Research (EDGAR), and the Regional Emission inventory in Asia version 2 (REAS2). Model performance of each simulation was evaluated against available observation data from 422 sites in 60 cities across China. Model predictions of O3 and PM2.5 generally meet the model performance criteria, but performance differences exist in different regions, for different pollutants, and among inventories. Ensemble predictions were calculated by linearly combining the results from different inventories to minimize the sum of the squared errors between the ensemble results and the observations in all cities. The ensemble concentrations show improved agreement with observations in most cities. The mean fractional bias (MFB) and mean fractional errors (MFEs) of the ensemble annual PM2.5 in the 60 cities are -0.11 and 0.24, respectively, which are better than the MFB (-0.25 to -0.16) and MFE (0.26-0.31) of individual simulations. The ensemble annual daily maximum 1 h O3 (O3-1h) concentrations are also improved, with mean normalized bias (MNB) of 0.03 and mean normalized errors (MNE) of 0.14, compared to MNB of 0.06-0.19 and

  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. Analyzing the efficiency of short-term air quality plans in European cities, using the CHIMERE air quality model.

    PubMed

    Thunis, P; Degraeuwe, B; Pisoni, E; Meleux, F; Clappier, A

    2017-01-01

    Regional and local authorities have the obligation to design air quality plans and assess their impacts when concentration levels exceed the limit values. Because these limit values cover both short- (day) and long-term (year) effects, air quality plans also follow these two formats. In this work, we propose a methodology to analyze modeled air quality forecast results, looking at emission reduction for different sectors (residential, transport, agriculture, etc.) with the aim of supporting policy makers in assessing the impact of short-term action plans. Regarding PM 10 , results highlight the diversity of responses across European cities, in terms of magnitude and type that raises the necessity of designing area-specific air quality plans. Action plans extended from 1 to 3 days (i.e., emissions reductions applied for 24 and 72 h, respectively) point to the added value of trans-city coordinated actions. The largest benefits are seen in central Europe (Vienna, Prague) while major cities (e.g., Paris) already solve a large part of the problem on their own. Eastern Europe would particularly benefit from plans based on emission reduction in the residential sectors; while in northern cities, agriculture seems to be the key sector on which to focus attention. Transport is playing a key role in most cities whereas the impact of industry is limited to a few cities in south-eastern Europe. For NO 2 , short-term action plans focusing on traffic emission reductions are efficient in all cities. This is due to the local character of this type of pollution. It is important, however, to stress that these results remain dependent on the selected months available for this study.

  15. Modeling prescribed burning experiments and assessing the fire impacts on local to regional air quality

    NASA Astrophysics Data System (ADS)

    Zhou, L.; Baker, K. R.; Napelenok, S. L.; Elleman, R. A.; Urbanski, S. P.

    2016-12-01

    Biomass burning, including wildfires and prescribed burns, strongly impact the global carbon cycle and are of increasing concern due to the potential impacts on ambient air quality. This modelling study focuses on the evolution of carbonaceous compounds during a prescribed burning experiment and assesses the impacts of burning on local to regional air quality. The Community Multiscale Air Quality (CMAQ) model is used to conduct 4 and 2 km grid resolution simulations of prescribed burning experiments in southeast Washington state and western Idaho state in summer 2013. The ground and airborne measurements from the field experiment are used to evaluate the model performance in capturing surface and aloft impacts from the burning events. Phase partitioning of organic compounds in the plume are studied as it is a crucial step towards understanding the fate of carbonaceous compounds. The sensitivities of ambient concentrations and deposition to emissions are conducted for organic carbon, elemental carbon and ozone to estimate the impacts of fire on air quality.

  16. 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...

  17. 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...

  18. Future directions of meteorology related to air-quality research.

    PubMed

    Seaman, Nelson L

    2003-06-01

    Meteorology is one of the major factors contributing to air-pollution episodes. More accurate representation of meteorological fields has been possible in recent years through the use of remote sensing systems, high-speed computers and fine-mesh meteorological models. Over the next 5-20 years, better meteorological inputs for air quality studies will depend on making better use of a wealth of new remotely sensed observations in more advanced data assimilation systems. However, for fine mesh models to be successful, parameterizations used to represent physical processes must be redesigned to be more precise and better adapted for the scales at which they will be applied. Candidates for significant overhaul include schemes to represent turbulence, deep convection, shallow clouds, and land-surface processes. Improvements in the meteorological observing systems, data assimilation and modeling, coupled with advancements in air-chemistry modeling, will soon lead to operational forecasting of air quality in the US. Predictive capabilities can be expected to grow rapidly over the next decade. This will open the way for a number of valuable new services and strategies, including better warnings of unhealthy atmospheric conditions, event-dependent emissions restrictions, and now casting support for homeland security in the event of toxic releases into the atmosphere.

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

    PubMed Central

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

    2011-01-01

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

  20. 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...

  1. Use of Air Quality Observations by the National Air Quality Forecast Capability

    NASA Astrophysics Data System (ADS)

    Stajner, I.; McQueen, J.; Lee, P.; Stein, A. F.; Kondragunta, S.; Ruminski, M.; Tong, D.; Pan, L.; Huang, J. P.; Shafran, P.; Huang, H. C.; Dickerson, P.; Upadhayay, S.

    2015-12-01

    The National Air Quality Forecast Capability (NAQFC) operational predictions of ozone and wildfire smoke for the United States (U.S.) and predictions of airborne dust for continental U.S. are available at http://airquality.weather.gov/. NOAA National Centers for Environmental Prediction (NCEP) operational North American Mesoscale (NAM) weather predictions are combined with the Community Multiscale Air Quality (CMAQ) model to produce the ozone predictions and test fine particulate matter (PM2.5) predictions. The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model provides smoke and dust predictions. Air quality observations constrain emissions used by NAQFC predictions. NAQFC NOx emissions from mobile sources were updated using National Emissions Inventory (NEI) projections for year 2012. These updates were evaluated over large U.S. cities by comparing observed changes in OMI NO2 observations and NOx measured by surface monitors. The rate of decrease in NOx emission projections from year 2005 to year 2012 is in good agreement with the observed changes over the same period. Smoke emissions rely on the fire locations detected from satellite observations obtained from NESDIS Hazard Mapping System (HMS). Dust emissions rely on a climatology of areas with a potential for dust emissions based on MODIS Deep Blue aerosol retrievals. Verification of NAQFC predictions uses AIRNow compilation of surface measurements for ozone and PM2.5. Retrievals of smoke from GOES satellites are used for verification of smoke predictions. Retrievals of dust from MODIS are used for verification of dust predictions. In summary, observations are the basis for the emissions inputs for NAQFC, they are critical for evaluation of performance of NAQFC predictions, and furthermore they are used in real-time testing of bias correction of PM2.5 predictions, as we continue to work on improving modeling and emissions important for representation of PM2.5.

  2. Using the HOMER Model in Air Quality Analysis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Not Available

    2004-08-01

    HOMER, the micropower optimization model created by the National Renewable Energy Laboratory (NREL), helps design and analyze off-grid and grid-connected power systems. One of HOMER's newest features is its enhanced ability to estimate air emissions for different micropower systems.

  3. Pragmatic estimation of a spatio-temporal air quality model with irregular monitoring data

    NASA Astrophysics Data System (ADS)

    Sampson, Paul D.; Szpiro, Adam A.; Sheppard, Lianne; Lindström, Johan; Kaufman, Joel D.

    2011-11-01

    Statistical analyses of health effects of air pollution have increasingly used GIS-based covariates for prediction of ambient air quality in "land use" regression models. More recently these spatial regression models have accounted for spatial correlation structure in combining monitoring data with land use covariates. We present a flexible spatio-temporal modeling framework and pragmatic, multi-step estimation procedure that accommodates essentially arbitrary patterns of missing data with respect to an ideally complete space by time matrix of observations on a network of monitoring sites. The methodology incorporates a model for smooth temporal trends with coefficients varying in space according to Partial Least Squares regressions on a large set of geographic covariates and nonstationary modeling of spatio-temporal residuals from these regressions. This work was developed to provide spatial point predictions of PM 2.5 concentrations for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) using irregular monitoring data derived from the AQS regulatory monitoring network and supplemental short-time scale monitoring campaigns conducted to better predict intra-urban variation in air quality. We demonstrate the interpretation and accuracy of this methodology in modeling data from 2000 through 2006 in six U.S. metropolitan areas and establish a basis for likelihood-based estimation.

  4. 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...

  5. 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 (...

  6. Predictive Techniques for Spacecraft Cabin Air Quality Control

    NASA Technical Reports Server (NTRS)

    Perry, J. L.; Cromes, Scott D. (Technical Monitor)

    2001-01-01

    As assembly of the International Space Station (ISS) proceeds, predictive techniques are used to determine the best approach for handling a variety of cabin air quality challenges. These techniques use equipment offgassing data collected from each ISS module before flight to characterize the trace chemical contaminant load. Combined with crew metabolic loads, these data serve as input to a predictive model for assessing the capability of the onboard atmosphere revitalization systems to handle the overall trace contaminant load as station assembly progresses. The techniques for predicting in-flight air quality are summarized along with results from early ISS mission analyses. Results from groundbased analyses of in-flight air quality samples are compared to the predictions to demonstrate the technique's relative conservatism.

  7. Evaluation of the Community Multi-scale Air Quality (CMAQ) ...

    EPA Pesticide Factsheets

    The Community Multiscale Air Quality (CMAQ) 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 Computational Exposure Division (CED) of the U.S. Environmental Protection Agency develops the CMAQ model and periodically releases new versions of the model that include bug fixes and various other improvements to the modeling system. In the fall of 2015, CMAQ version 5.1 was released. This new version of CMAQ will contain important bug fixes to several issues that were identified in CMAQv5.0.2 and additionally include updates to other portions of the code. Several annual, and numerous episodic, CMAQv5.1 simulations were performed to assess the impact of these improvements on the model results. These results will be presented, along with a base evaluation of the performance of the CMAQv5.1 modeling system against available surface and upper-air measurements available during the time period simulated. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, proces

  8. Improving and monitoring air quality.

    PubMed

    DuPont, André

    2018-05-01

    Since the authorization of the Clean Air Act Amendments of 1990, the air quality in the USA has significantly improved because of strong public support. The lessons learned over the last 25 years are being shared with the policy analysts, technical professionals, and scientist who endeavor to improve air quality in their communities. This paper will review how the USA has achieved the "high" standard of air quality that was envisioned in the early 1990s. This document will describe SO 2 gas emission reduction technology and highlight operation of emission monitoring technology. This paper describes the basic process operation of an air pollution control scrubber. A technical review of measures required to operate and maintain a large-scale pollution control system will be described. Also, the author explains how quality assurance procedures in performance of continuous emission monitoring plays a significant role in reducing air pollution.

  9. 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.

  10. WSN based indoor air quality monitoring in classrooms

    NASA Astrophysics Data System (ADS)

    Wang, S. K.; Chew, S. P.; Jusoh, M. T.; Khairunissa, A.; Leong, K. Y.; Azid, A. A.

    2017-03-01

    Indoor air quality monitoring is essential as the human health is directly affected by indoor air quality. This paper presents the investigations of the impact of undergraduate students' concentration during lecture due to the indoor air quality in classroom. Three environmental parameters such as temperature, relative humidity and concentration of carbon dioxide are measured using wireless sensor network based air quality monitoring system. This simple yet reliable system is incorporated with DHT-11 and MG-811 sensors. Two classrooms were selected to install the monitoring system. The level of indoor air quality were measured and students' concentration was assessed using intelligent test during normal lecturing section. The test showed significant correlation between the collected environmental parameters and the students' level of performances in their study.

  11. 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

  12. What Air Quality Models Tell Us About Sources and Sinks of Atmospheric Aldehydes

    NASA Astrophysics Data System (ADS)

    Luecken, D.; Hutzell, W. T.; Phillips, S.

    2010-12-01

    Atmospheric aldehydes play important roles in several aspects of air quality: they are critical radical sources that drive ozone formation, they are hazardous air pollutants that are national drivers for cancer risk, they participate in aqueous chemistry and potentially aerosol formation, and are key species for evaluating the accuracy of isoprene emissions. For these reasons, it is important to accurately understand their sources and sinks, and the sensitivity of their concentrations to emission controls. While both compounds have been included in air quality modeling for many years, current, state-of-the-science chemical mechanisms have difficulty reproducing measured values of aldehydes, which calls into question the robustness of ozone, HAPs and aerosol predictions. In the past, we have attributed discrepancies to measurement errors, inventory errors, or the focus on high-NOx urban regimes. Despite improvements in all of these areas, the measurements still diverge from model predictions, with formaldehyde often underpredicted by 50% and acetaldehyde showing a large degree of scatter - from 20% overprediction to 50% underprediction. To better examine the sources of aldehydes, we implemented the new SAPRC07T mechanism in the Community Multi-Scale Air Quality (CMAQ) model. This mechanism incorporates current recommendations for kinetic data and has the most detailed representation of product formation under a wide variety of conditions of any mechanism used in regional air quality models. We use model simulations to pinpoint where and when aldehyde concentrations tend to deviate from measurements. We demonstrate the role of secondary production versus primary emissions in aldehdye concentrations and find that secondary sources produce the largest deviations from measurements. We identify which VOCs are most responsible for aldehyde secondary production in the areas of the U.S. where the largest health effects are seen, and discuss how this affects consideration of

  13. Microenvironmental air quality impact of a commercial-scale biomass heating system.

    PubMed

    Tong, Zheming; Yang, Bo; Hopke, Philip K; Zhang, K Max

    2017-01-01

    Initiatives to displace petroleum and climate change mitigation have driven a recent increase in space heating with biomass combustion. However, there is ample evidence that biomass combustion emits significant quantities of health damaging pollutants. We investigated the near-source micro-environmental air quality impact of a biomass-fueled combined heat and power system equipped with an electrostatic precipitator (ESP) in Syracuse, NY. Two rooftop sampling stations with PM 2.5 and CO 2 analyzers were established in such that one could capture the plume while the other one served as the background for comparison depending on the wind direction. Four sonic anemometers were deployed around the stack to quantify spatially and temporally resolved local wind patterns. Fuel-based emission factors were derived based on near-source measurement. The Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry (CTAG) model was then applied to simulate the spatial variations of primary PM 2.5 without ESP. Our analysis shows that the absence of ESP could lead to an almost 7 times increase in near-source primary PM 2.5 concentrations with a maximum concentration above 100 μg m -3 at the building rooftop. The above-ground "hotspots" would pose potential health risks to building occupants since particles could penetrate indoors via infiltration, natural ventilation, and fresh air intakes on the rooftop of multiple buildings. Our results demonstrated the importance of emission control for biomass combustion systems in urban area, and the need to take above-ground pollutant "hotspots" into account when permitting distributed generation. The effects of ambient wind speed and stack temperature, the suitability of airport meteorological data on micro-environmental air quality were explored, and the implications on mitigating near-source air pollution were discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. DataFed: A Federated Data System for Visualization and Analysis of Spatio-Temporal Air Quality Data

    NASA Astrophysics Data System (ADS)

    Husar, R. B.; Hoijarvi, K.

    2017-12-01

    DataFed is a distributed web-services-based computing environment for accessing, processing, and visualizing atmospheric data in support of air quality science and management. The flexible, adaptive environment facilitates the access and flow of atmospheric data from provider to users by enabling the creation of user-driven data processing/visualization applications. DataFed `wrapper' components, non-intrusively wrap heterogeneous, distributed datasets for access by standards-based GIS web services. The mediator components (also web services) map the heterogeneous data into a spatio-temporal data model. Chained web services provide homogeneous data views (e.g., geospatial, time views) using a global multi-dimensional data model. In addition to data access and rendering, the data processing component services can be programmed for filtering, aggregation, and fusion of multidimensional data. A complete application software is written in a custom made data flow language. Currently, the federated data pool consists of over 50 datasets originating from globally distributed data providers delivering surface-based air quality measurements, satellite observations, emissions data as well as regional and global-scale air quality models. The web browser-based user interface allows point and click navigation and browsing the XYZT multi-dimensional data space. The key applications of DataFed are for exploring spatial pattern of pollutants, seasonal, weekly, diurnal cycles and frequency distributions for exploratory air quality research. Since 2008, DataFed has been used to support EPA in the implementation of the Exceptional Event Rule. The data system is also used at universities in the US, Europe and Asia.

  15. EVALUATION OF THE REAL-TIME AIR-QUALITY MODEL USING THE RAPS (REGIONAL AIR POLLUTION STUDY) DATA BASE. VOLUME 1. OVERVIEW

    EPA Science Inventory

    The theory and programming of statistical tests for evaluating the Real-Time Air-Quality Model (RAM) using the Regional Air Pollution Study (RAPS) data base are fully documented in four report volumes. Moreover, the tests are generally applicable to other model evaluation problem...

  16. 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

  17. A cost-efficiency and health benefit approach to improve urban air quality.

    PubMed

    Miranda, A I; Ferreira, J; Silveira, C; Relvas, H; Duque, L; Roebeling, P; Lopes, M; Costa, S; Monteiro, A; Gama, C; Sá, E; Borrego, C; Teixeira, J P

    2016-11-01

    When ambient air quality standards established in the EU Directive 2008/50/EC are exceeded, Member States are obliged to develop and implement Air Quality Plans (AQP) to improve air quality and health. Notwithstanding the achievements in emission reductions and air quality improvement, additional efforts need to be undertaken to improve air quality in a sustainable way - i.e. through a cost-efficiency approach. This work was developed in the scope of the recently concluded MAPLIA project "Moving from Air Pollution to Local Integrated Assessment", and focuses on the definition and assessment of emission abatement measures and their associated costs, air quality and health impacts and benefits by means of air quality modelling tools, health impact functions and cost-efficiency analysis. The MAPLIA system was applied to the Grande Porto urban area (Portugal), addressing PM10 and NOx as the most important pollutants in the region. Four different measures to reduce PM10 and NOx emissions were defined and characterized in terms of emissions and implementation costs, and combined into 15 emission scenarios, simulated by the TAPM air quality modelling tool. Air pollutant concentration fields were then used to estimate health benefits in terms of avoided costs (external costs), using dose-response health impact functions. Results revealed that, among the 15 scenarios analysed, the scenario including all 4 measures lead to a total net benefit of 0.3M€·y(-1). The largest net benefit is obtained for the scenario considering the conversion of 50% of open fire places into heat recovery wood stoves. Although the implementation costs of this measure are high, the benefits outweigh the costs. Research outcomes confirm that the MAPLIA system is useful for policy decision support on air quality improvement strategies, and could be applied to other urban areas where AQP need to be implemented and monitored. Copyright © 2016. Published by Elsevier B.V.

  18. Predicting indoor pollutant concentrations, and applications to air quality management

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lorenzetti, David M.

    Because most people spend more than 90% of their time indoors, predicting exposure to airborne pollutants requires models that incorporate the effect of buildings. Buildings affect the exposure of their occupants in a number of ways, both by design (for example, filters in ventilation systems remove particles) and incidentally (for example, sorption on walls can reduce peak concentrations, but prolong exposure to semivolatile organic compounds). Furthermore, building materials and occupant activities can generate pollutants. Indoor air quality depends not only on outdoor air quality, but also on the design, maintenance, and use of the building. For example, ''sick building'' symptomsmore » such as respiratory problems and headaches have been related to the presence of air-conditioning systems, to carpeting, to low ventilation rates, and to high occupant density (1). The physical processes of interest apply even in simple structures such as homes. Indoor air quality models simulate the processes, such as ventilation and filtration, that control pollutant concentrations in a building. Section 2 describes the modeling approach, and the important transport processes in buildings. Because advection usually dominates among the transport processes, Sections 3 and 4 describe methods for predicting airflows. The concluding section summarizes the application of these models.« less

  19. Improvement of Meteorological Inputs for TexAQS-II Air Quality Simulations

    NASA Astrophysics Data System (ADS)

    Ngan, F.; Byun, D.; Kim, H.; Cheng, F.; Kim, S.; Lee, D.

    2008-12-01

    An air quality forecasting system (UH-AQF) for Eastern Texas, which is in operation by the Institute for Multidimensional Air Quality Studies (IMAQS) at the University of Houston, uses the Fifth-Generation PSU/NCAR Mesoscale Model MM5 model as the meteorological driver for modeling air quality with the Community Multiscale Air Quality (CMAQ) model. While the forecasting system was successfully used for the planning and implementation of various measurement activities, evaluations of the forecasting results revealed a few systematic problems in the numerical simulations. From comparison with observations, we observe some times over-prediction of northerly winds caused by inaccurate synoptic inputs and other times too strong southerly winds caused by local sea breeze development. Discrepancies in maximum and minimum temperature are also seen for certain days. Precipitation events, as well as clouds, are simulated at the incorrect locations and times occasionally. Model simulatednrealistic thunderstorms are simulated, causing sometimes cause unrealistically strong outflows. To understand physical and chemical processes influencing air quality measures, a proper description of real world meteorological conditions is essential. The objective of this study is to generate better meteorological inputs than the AQF results to support the chemistry modeling. We utilized existing objective analysis and nudging tools in the MM5 system to develop the MUltiscale Nest-down Data Assimilation System (MUNDAS), which incorporates extensive meteorological observations available in the simulated domain for the retrospective simulation of the TexAQS-II period. With the re-simulated meteorological input, we are able to better predict ozone events during TexAQS-II period. In addition, base datasets in MM5 such as land use/land cover, vegetation fraction, soil type and sea surface temperature are updated by satellite data to represent the surface features more accurately. They are key

  20. Design and Development of a Nearable Wireless System to Control Indoor Air Quality and Indoor Lighting Quality.

    PubMed

    Salamone, Francesco; Belussi, Lorenzo; Danza, Ludovico; Galanos, Theodore; Ghellere, Matteo; Meroni, Italo

    2017-05-04

    The article describes the results of the project "open source smart lamp" aimed at designing and developing a smart object able to manage and control the indoor environmental quality (IEQ) of the built environment. A first version of this smart object, built following a do-it-yourself (DIY) approach using a microcontroller, an integrated temperature and relative humidity sensor, and techniques of additive manufacturing, allows the adjustment of the indoor thermal comfort quality (ICQ), by interacting directly with the air conditioner. As is well known, the IEQ is a holistic concept including indoor air quality (IAQ), indoor lighting quality (ILQ) and acoustic comfort, besides thermal comfort. The upgrade of the smart lamp bridges the gap of the first version of the device providing the possibility of interaction with the air exchange unit and lighting system in order to get an overview of the potential of a nearable device in the management of the IEQ. The upgraded version was tested in a real office equipped with mechanical ventilation and an air conditioning system. This office was occupied by four workers. The experiment is compared with a baseline scenario and the results show how the application of the nearable device effectively optimizes both IAQ and ILQ.

  1. Design and Development of a Nearable Wireless System to Control Indoor Air Quality and Indoor Lighting Quality

    PubMed Central

    Salamone, Francesco; Belussi, Lorenzo; Danza, Ludovico; Galanos, Theodore; Ghellere, Matteo; Meroni, Italo

    2017-01-01

    The article describes the results of the project “open source smart lamp” aimed at designing and developing a smart object able to manage and control the indoor environmental quality (IEQ) of the built environment. A first version of this smart object, built following a do-it-yourself (DIY) approach using a microcontroller, an integrated temperature and relative humidity sensor, and techniques of additive manufacturing, allows the adjustment of the indoor thermal comfort quality (ICQ), by interacting directly with the air conditioner. As is well known, the IEQ is a holistic concept including indoor air quality (IAQ), indoor lighting quality (ILQ) and acoustic comfort, besides thermal comfort. The upgrade of the smart lamp bridges the gap of the first version of the device providing the possibility of interaction with the air exchange unit and lighting system in order to get an overview of the potential of a nearable device in the management of the IEQ. The upgraded version was tested in a real office equipped with mechanical ventilation and an air conditioning system. This office was occupied by four workers. The experiment is compared with a baseline scenario and the results show how the application of the nearable device effectively optimizes both IAQ and ILQ. PMID:28471398

  2. (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...

  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. Evaluating and improving the results of air quality models in Texas using TES, AIRS and other satellite data

    NASA Astrophysics Data System (ADS)

    Osterman, G.; Harper, C.; Estes, M.; Zhao, W.; Bowman, K.; Pierce, B.; Irion, B.; Kahn, B.; Al-Saadi, J.

    2008-05-01

    The Houston/Galveston/Brazoria (HGB) area of Texas has been classified as in moderate nonattainment of the Environmental Protection Agency (EPA) 8-hour standard for ground level ozone since April 30, 2004. The Texas Commission on Environmental Quality uses photochemical model results as one of its primary tools to develop strategies to bring the HGB area into attainment with the EPA standard. The state of Texas then includes the strategies into a revised version of its State Implementation Plan (SIP). We will discuss efforts that have been or soon will be underway to use satellite data to evaluate and improve the meteorological and photochemical modeling efforts at TCEQ. In particular we will show the use of GOES, AIRS and TES data to improve the ability to model, using the MM5 model, the meteorological conditions over Texas and the Gulf of Mexico. The meteorological fields are then used as one of the inputs to the CAMx air quality model used at TCEQ. We will discuss the use of chemical transport model results as initial and boundary conditions which are a key uncertainty in the modeling of the air above Houston. We will also discuss the use of TES data to assist in the evaluation of preliminary model results generated by TCEQ for time periods in 2005. The satellite data will provide key information on ozone and carbon monoxide concentrations away from surface monitors in the troposphere. We will show how satellite data is becoming a key tool in the effort to improve air quality in the HGB area and one that can easily applied for use in other regions of the country.

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  6. 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.

  7. 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...

  8. Using Intel's Knight Landing Processor to Accelerate Global Nested Air Quality Prediction Modeling System (GNAQPMS) Model

    NASA Astrophysics Data System (ADS)

    Wang, H.; Chen, H.; Chen, X.; Wu, Q.; Wang, Z.

    2016-12-01

    The Global Nested Air Quality Prediction Modeling System for Hg (GNAQPMS-Hg) is a global chemical transport model coupled Hg transport module to investigate the mercury pollution. In this study, we present our work of transplanting the GNAQPMS model on Intel Xeon Phi processor, Knights Landing (KNL) to accelerate the model. KNL is the second-generation product adopting Many Integrated Core Architecture (MIC) architecture. Compared with the first generation Knight Corner (KNC), KNL has more new hardware features, that it can be used as unique processor as well as coprocessor with other CPU. According to the Vtune tool, the high overhead modules in GNAQPMS model have been addressed, including CBMZ gas chemistry, advection and convection module, and wet deposition module. These high overhead modules were accelerated by optimizing code and using new techniques of KNL. The following optimized measures was done: 1) Changing the pure MPI parallel mode to hybrid parallel mode with MPI and OpenMP; 2.Vectorizing the code to using the 512-bit wide vector computation unit. 3. Reducing unnecessary memory access and calculation. 4. Reducing Thread Local Storage (TLS) for common variables with each OpenMP thread in CBMZ. 5. Changing the way of global communication from files writing and reading to MPI functions. After optimization, the performance of GNAQPMS is greatly increased both on CPU and KNL platform, the single-node test showed that optimized version has 2.6x speedup on two sockets CPU platform and 3.3x speedup on one socket KNL platform compared with the baseline version code, which means the KNL has 1.29x speedup when compared with 2 sockets CPU platform.

  9. Source Apportionment of Final Particulate Matterin North China Plain based on Air Quality Modeling

    NASA Astrophysics Data System (ADS)

    Xing, J.; Wu, W.; Chang, X.; Wang, S.; Hao, J.

    2016-12-01

    Most Chinese cities in North China Plain are suffering from serious air pollution. To develop the regional air pollution control policies, we need to identify the major source contributions to such pollution and to design the control policy which is accurate, efficient and effective. This study used the air quality model with serval advanced technologies including ISAM and ERSM, to assess the source contributions from individual pollutants (incl. SO2, NOx, VOC, NH3, primary PM), sectors (incl. power plants, industry, transportation and domestic), and regions (Beijing, Hebei, Tianjing and surrounding provinces). The modeling period is two months in 2012 as January and July which represent winter and summer respectively. The non-linear relationship between air pollutant emissions and air quality will be addressed, and the integrated control of multi-pollutants and multi-regions in China will be suggested.

  10. A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

    EPA Science Inventory

    This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used t...

  11. Air Quality Improvements of Increased Integration of Renewables: Solar Photovoltaics Penetration Scenarios

    NASA Astrophysics Data System (ADS)

    Duran, P.; Holloway, T.; Brinkman, G.; Denholm, P.; Littlefield, C. M.

    2011-12-01

    Solar photovoltaics (PV) are an attractive technology because they can be locally deployed and tend to yield high production during periods of peak electric demand. These characteristics can reduce the need for conventional large-scale electricity generation, thereby reducing emissions of criteria air pollutants (CAPs) and improving ambient air quality with regard to such pollutants as nitrogen oxides, sulfur oxides and fine particulates. Such effects depend on the local climate, time-of-day emissions, available solar resources, the structure of the electric grid, and existing electricity production among other factors. This study examines the air quality impacts of distributed PV across the United States Eastern Interconnection. In order to accurately model the air quality impact of distributed PV in space and time, we used the National Renewable Energy Lab's (NREL) Regional Energy Deployment System (ReEDS) model to form three unique PV penetration scenarios in which new PV construction is distributed spatially based upon economic drivers and natural solar resources. Those scenarios are 2006 Eastern Interconnection business as usual, 10% PV penetration, and 20% PV penetration. With the GridView (ABB, Inc) dispatch model, we used historical load data from 2006 to model electricity production and distribution for each of the three scenarios. Solar PV electric output was estimated using historical weather data from 2006. To bridge the gap between dispatch and air quality modeling, we will create emission profiles for electricity generating units (EGUs) in the Eastern Interconnection from historical Continuous Emissions Monitoring System (CEMS) data. Via those emissions profiles, we will create hourly emission data for EGUs in the Eastern Interconnect for each scenario during 2006. Those data will be incorporated in the Community Multi-scale Air Quality (CMAQ) model using the Sparse Matrix Operator Kernel Emissions (SMOKE) model. Initial results indicate that PV

  12. Comparison of exposure estimation methods for air pollutants: ambient monitoring data and regional air quality simulation.

    PubMed

    Bravo, Mercedes A; Fuentes, Montserrat; Zhang, Yang; Burr, Michael J; Bell, Michelle L

    2012-07-01

    Air quality modeling could potentially improve exposure estimates for use in epidemiological studies. We investigated this application of air quality modeling by estimating location-specific (point) and spatially-aggregated (county level) exposure concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM(2.5)) and ozone (O(3)) for the eastern U.S. in 2002 using the Community Multi-scale Air Quality (CMAQ) modeling system and a traditional approach using ambient monitors. The monitoring approach produced estimates for 370 and 454 counties for PM(2.5) and O(3), respectively. Modeled estimates included 1861 counties, covering 50% more population. The population uncovered by monitors differed from those near monitors (e.g., urbanicity, race, education, age, unemployment, income, modeled pollutant levels). CMAQ overestimated O(3) (annual normalized mean bias=4.30%), while modeled PM(2.5) had an annual normalized mean bias of -2.09%, although bias varied seasonally, from 32% in November to -27% in July. Epidemiology may benefit from air quality modeling, with improved spatial and temporal resolution and the ability to study populations far from monitors that may differ from those near monitors. However, model performance varied by measure of performance, season, and location. Thus, the appropriateness of using such modeled exposures in health studies depends on the pollutant and metric of concern, acceptable level of uncertainty, population of interest, study design, and other factors. Copyright © 2012 Elsevier Inc. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

    Transported air pollutants receive increasing attention as regulations tighten and global concentrations increase. The need to represent international transport in regional air quality assessments requires improved representation of boundary concentrations. Currently available observations are too sparse vertically to provide boundary information, particularly for ozone precursors, but global simulations can be used to generate spatially and temporally varying Lateral Boundary Conditions (LBC). This study presents a public database of global simulations designed and evaluated for use as LBC for air quality models (AQMs). The database covers the contiguous United States (CONUS) for the years 2000-2010 and contains hourly varying concentrations of ozone, aerosols, and their precursors. The database is complimented by a tool for configuring the global results as inputs to regional scale models (e.g., Community Multiscale Air Quality or Comprehensive Air quality Model with extensions). This study also presents an example application based on the CONUS domain, which is evaluated against satellite retrieved ozone vertical profiles. The results show performance is largely within uncertainty estimates for the Tropospheric Emission Spectrometer (TES) with some exceptions. The major difference shows a high bias in the upper troposphere along the southern boundary in January. This publication documents the global simulation database, the tool for conversion to LBC, and the fidelity of concentrations on the boundaries. This documentation is intended to support applications that require representation of long-range transport of air pollutants.

  14. 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

  15. The Use of Remote Sensing Data for Modeling Air Quality in the Cities

    NASA Astrophysics Data System (ADS)

    Putrenko, V. V.; Pashynska, N. M.

    2017-12-01

    Monitoring of environmental pollution in the cities by the methods of remote sensing of the Earth is actual area of research for sustainable development. Ukraine has a poorly developed network of monitoring stations for air quality, the technical condition of which is deteriorating in recent years. Therefore, the possibility of obtaining data about the condition of air by remote sensing methods is of great importance. The paper considers the possibility of using the data about condition of atmosphere of the project AERONET to assess the air quality in Ukraine. The main pollution indicators were used data on fine particulate matter (PM2.5) and nitrogen dioxide (NO2) content in the atmosphere. The main indicator of air quality in Ukraine is the air pollution index (API). We have built regression models the relationship between indicators of NO2, which are measured by remote sensing methods and ground-based measurements of indicators. There have also been built regression models, the relationship between the data given to the land of NO2 and API. To simulate the relationship between the API and PM2.5 were used geographically weighted regression model, which allows to take into account the territorial differentiation between these indicators. As a result, the maps that show the distribution of the main types of pollution in the territory of Ukraine, were constructed. PM2.5 data modeling is complicated with using existing indicators, which requires a separate organization observation network for PM2.5 content in the atmosphere for sustainable development in cities of Ukraine.

  16. 77 FR 38239 - Partial Approval and Disapproval of Air Quality Implementation Plans; Arizona; Infrastructure...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-27

    ... anonymous access system, and EPA will not know your identity or contact information unless you provide it in... control measures. Section 110(a)(2)(B): Ambient air quality monitoring/data system. Section 110(a)(2)(C... significant deterioration (PSD) and visibility protection. Section 110(a)(2)(K): Air quality modeling and...

  17. The climate-wildfire-air quality system: interactions and feedbacks across spatial and temporal scales

    Treesearch

    E. Natasha Stavros; Donald McKenzie; Narasimhan Larkin

    2014-01-01

    Future climate change and its effects on social and ecological systems present challenges for preserving valued ecosystem services, including local and regional air quality. Wildfire is a major source of air-quality impact in some locations, and a substantial contributor to pollutants of concern, including nitrogen oxides and particulate matter, which are regulated to...

  18. Experiments with data assimilation in comprehensive air quality models: Impacts on model predictions and observation requirements (Invited)

    NASA Astrophysics Data System (ADS)

    Mathur, R.

    2009-12-01

    Emerging regional scale atmospheric simulation models must address the increasing complexity arising from new model applications that treat multi-pollutant interactions. Sophisticated air quality modeling systems are needed to develop effective abatement strategies that focus on simultaneously controlling multiple criteria pollutants as well as use in providing short term air quality forecasts. In recent years the applications of such models is continuously being extended to address atmospheric pollution phenomenon from local to hemispheric spatial scales over time scales ranging from episodic to annual. The need to represent interactions between physical and chemical atmospheric processes occurring at these disparate spatial and temporal scales requires the use of observation data beyond traditional in-situ networks so that the model simulations can be reasonably constrained. Preliminary applications of assimilation of remote sensing and aloft observations within a comprehensive regional scale atmospheric chemistry-transport modeling system will be presented: (1) A methodology is developed to assimilate MODIS aerosol optical depths in the model to represent the impacts long-range transport associated with the summer 2004 Alaskan fires on surface-level regional fine particulate matter (PM2.5) concentrations across the Eastern U.S. The episodic impact of this pollution transport event on PM2.5 concentrations over the eastern U.S. during mid-July 2004, is quantified through the complementary use of the model with remotely-sensed, aloft, and surface measurements; (2) Simple nudging experiments with limited aloft measurements are performed to identify uncertainties in model representations of physical processes and assess the potential use of such measurements in improving the predictive capability of atmospheric chemistry-transport models. The results from these early applications will be discussed in context of uncertainties in the model and in the remote sensing

  19. Modelling the urban air quality in Hamburg with the new city-scale chemistry transport model CityChem

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

    Air quality modelling plays an important role by providing guidelines for efficient air pollution abatement measures. Currently, most urban dispersion models treat air pollutants as passive tracer substances or use highly simplified chemistry when simulating air pollutant concentrations on the city-scale. The newly developed urban chemistry-transport model CityChem has the capability of modelling the photochemical transformation of multiple pollutants along with atmospheric diffusion to produce pollutant concentration fields for the entire city on a horizontal resolution of 100 m or even finer and a vertical resolution of 24 layers up to 4000 m height. CityChem is based on the Eulerian urban dispersion model EPISODE of the Norwegian Institute for Air Research (NILU). CityChem treats the complex photochemistry in cities using detailed EMEP chemistry on an Eulerian 3-D grid, while using simple photo-stationary equilibrium on a much higher resolution grid (receptor grid), i.e. close to industrial point sources and traffic sources. The CityChem model takes into account that long-range transport contributes to urban pollutant concentrations. This is done by using 3-D boundary concentrations for the city domain derived from chemistry-transport simulations with the regional air quality model CMAQ. For the study of the air quality in Hamburg, CityChem was set-up with a main grid of 30×30 grid cells of 1×1 km2 each and a receptor grid of 300×300 grid cells of 100×100 m2. The CityChem model was driven with meteorological data generated by the prognostic meteorology component of the Australian chemistry-transport model TAPM. Bottom-up inventories of emissions from traffic, industry, households were based on data of the municipality of Hamburg. Shipping emissions for the port of Hamburg were taken from the Clean North Sea Shipping project. Episodes with elevated ozone (O3) were of specific interest for this study, as these are associated with exceedances of the World

  20. 40 CFR 52.60 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.60 Section 52.60 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) All applications and other information required pursuant to § 52.21 from... “Guideline on Air Quality Models (Revised)” or other models approved by EPA. [42 FR 22869, May 5, 1977, as...

  1. 40 CFR 52.60 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.60 Section 52.60 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) All applications and other information required pursuant to § 52.21 from... “Guideline on Air Quality Models (Revised)” or other models approved by EPA. [42 FR 22869, May 5, 1977, as...

  2. 40 CFR 52.60 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.60 Section 52.60 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) All applications and other information required pursuant to § 52.21 from... “Guideline on Air Quality Models (Revised)” or other models approved by EPA. [42 FR 22869, May 5, 1977, as...

  3. 40 CFR 52.60 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.60 Section 52.60 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) All applications and other information required pursuant to § 52.21 from... “Guideline on Air Quality Models (Revised)” or other models approved by EPA. [42 FR 22869, May 5, 1977, as...

  4. 40 CFR 52.60 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.60 Section 52.60 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) All applications and other information required pursuant to § 52.21 from... “Guideline on Air Quality Models (Revised)” or other models approved by EPA. [42 FR 22869, May 5, 1977, as...

  5. A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

    EPA Science Inventory

    This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosen...

  6. 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...

  7. EVALUATION OF THE REAL-TIME AIR-QUALITY MODEL USING THE RAPS (REGIONAL AIR POLLUTION STUDY) DATA BASE. VOLUME 4. EVALUATION GUIDE

    EPA Science Inventory

    The theory and programming of statistical tests for evaluating the Real-Time Air-Quality Model (RAM) using the Regional Air Pollution Study (RAPS) data base are fully documented in four volumes. Moreover, the tests are generally applicable to other model evaluation problems. Volu...

  8. Air quality in passenger cars of the ground railway transit system in Beijing, China.

    PubMed

    Li, Tian-Tian; Bai, Yu-Hua; Liu, Zhao-Rong; Liu, Jin-Feng; Zhang, Guang-Shan; Li, Jin-Long

    2006-08-15

    This study examined the concentrations of carbon monoxide, carbon dioxide, TVOC, TSP, PM(10), PM(2.5), PM(1), benzene, toluene and xylene in passenger cars of the Beijing Ground Railway Transit System (Line No. 13). This system connects the northern suburb and downtown, and is equipped with air-conditioned passenger cars. In-train air quality monitoring was performed in both summer (July and August) and winter (December). To obtain representative data, the sampling design considered both rush and regular hours, urban and suburban areas, as well as the number of passengers. Meanwhile, questionnaires were distributed to the passengers. The monitoring results indicated that, overall, the air quality in the passenger cars was acceptable with a few exceptions, which is consistent with the passengers' perception. Concentrations of some air pollutants showed significant seasonal variations and had the significant difference between rush hour and regular hour. Furthermore, the in-train air quality was greatly influenced by the number of passengers. This paper describes the experimental design, and presents the preliminary results.

  9. 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 ...

  10. Improving AirNow Air Quality Products with NASA Near-Real-Time Remote Sensing Data (Invited)

    NASA Astrophysics Data System (ADS)

    Dye, T.; Pasch, A. N.; DeWinter, J. L.; Haderman, M.; Szykman, J.; White, J. E.; van Donkelaar, A.; Martin, R.

    2013-12-01

    The U.S. Environmental Protection Agency's (EPA) AirNow program provides the public with real-time and forecasted air quality conditions. Millions of people each day use it to protect their health. The AirNow program (http://www.airnow.gov), reports ground-level ozone (O3) and fine particulate matter (PM2.5) in a standardized index called the Air Quality Index (AQI). AirNow aggregates information from over 130 state, local, and federal air quality agencies and provides tools for over 2,000 agency staff responsible for monitoring, forecasting, and communicating local air quality. Each hour, AirNow systems generate thousands of maps and products. This presentation will describe how AirNow is benefiting from NASA's remote sensing data. We will describe two applications of NASA near-real-time remote sensing data within AirNow through case studies, focusing specifically on days when large spatial gradients in AQI and wildfire smoke impacts were observed. The first case study will show how AirNow is merging satellite-estimated PM2.5 concentrations into the AQI maps via the AirNow Satellite Data Processor (ASDP). AirNow derives these satellite estimates using NASA/NOAA satellite aerosol optical depth (AOD) retrievals and GEOS-Chem modeled ratios of surface PM2.5 concentrations to AOD. The second case study will show how NASA's Global Image Browse Services (GIBS) provides a near-real-time satellite product in AirNow-Tech for agency users to quickly identify smoke plumes and access air quality conditions in data-sparse areas during wildland fires.

  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. 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...

  13. A description and evaluation of an air quality model nested within global and regional composition-climate models using MetUM

    NASA Astrophysics Data System (ADS)

    Neal, Lucy S.; Dalvi, Mohit; Folberth, Gerd; McInnes, Rachel N.; Agnew, Paul; O'Connor, Fiona M.; Savage, Nicholas H.; Tilbee, Marie

    2017-11-01

    There is a clear need for the development of modelling frameworks for both climate change and air quality to help inform policies for addressing these issues simultaneously. This paper presents an initial attempt to develop a single modelling framework, by introducing a greater degree of consistency in the meteorological modelling framework by using a two-step, one-way nested configuration of models, from a global composition-climate model (GCCM) (140 km resolution) to a regional composition-climate model covering Europe (RCCM) (50 km resolution) and finally to a high (12 km) resolution model over the UK (AQUM). The latter model is used to produce routine air quality forecasts for the UK. All three models are based on the Met Office's Unified Model (MetUM). In order to better understand the impact of resolution on the downscaling of projections of future climate and air quality, we have used this nest of models to simulate a 5-year period using present-day emissions and under present-day climate conditions. We also consider the impact of running the higher-resolution model with higher spatial resolution emissions, rather than simply regridding emissions from the RCCM. We present an evaluation of the models compared to in situ air quality observations over the UK, plus a comparison against an independent 1 km resolution gridded dataset, derived from a combination of modelling and observations, effectively producing an analysis of annual mean surface pollutant concentrations. We show that using a high-resolution model over the UK has some benefits in improving air quality modelling, but that the use of higher spatial resolution emissions is important to capture local variations in concentrations, particularly for primary pollutants such as nitrogen dioxide and sulfur dioxide. For secondary pollutants such as ozone and the secondary component of PM10, the benefits of a higher-resolution nested model are more limited and reasons for this are discussed. This study

  14. Assessment of air quality benefits from national air pollution control policies in China. Part II: Evaluation of air quality predictions and air quality benefits assessment

    NASA Astrophysics Data System (ADS)

    Wang, Litao; Jang, Carey; Zhang, Yang; Wang, Kai; Zhang, Qiang; Streets, David; Fu, Joshua; Lei, Yu; Schreifels, Jeremy; He, Kebin; Hao, Jiming; Lam, Yun-Fat; Lin, Jerry; Meskhidze, Nicholas; Voorhees, Scott; Evarts, Dale; Phillips, Sharon

    2010-09-01

    Following the meteorological evaluation in Part I, this Part II paper presents the statistical evaluation of air quality predictions by the U.S. Environmental Protection Agency (U.S. EPA)'s Community Multi-Scale Air Quality (Models-3/CMAQ) model for the four simulated months in the base year 2005. The surface predictions were evaluated using the Air Pollution Index (API) data published by the China Ministry of Environmental Protection (MEP) for 31 capital cities and daily fine particulate matter (PM 2.5, particles with aerodiameter less than or equal to 2.5 μm) observations of an individual site in Tsinghua University (THU). To overcome the shortage in surface observations, satellite data are used to assess the column predictions including tropospheric nitrogen dioxide (NO 2) column abundance and aerosol optical depth (AOD). The result shows that CMAQ gives reasonably good predictions for the air quality. The air quality improvement that would result from the targeted sulfur dioxide (SO 2) and nitrogen oxides (NO x) emission controls in China were assessed for the objective year 2010. The results show that the emission controls can lead to significant air quality benefits. SO 2 concentrations in highly polluted areas of East China in 2010 are estimated to be decreased by 30-60% compared to the levels in the 2010 Business-As-Usual (BAU) case. The annual PM 2.5 can also decline by 3-15 μg m -3 (4-25%) due to the lower SO 2 and sulfate concentrations. If similar controls are implemented for NO x emissions, NO x concentrations are estimated to decrease by 30-60% as compared with the 2010 BAU scenario. The annual mean PM 2.5 concentrations will also decline by 2-14 μg m -3 (3-12%). In addition, the number of ozone (O 3) non-attainment areas in the northern China is projected to be much lower, with the maximum 1-h average O 3 concentrations in the summer reduced by 8-30 ppb.

  15. Modeling green infrastructure land use changes on future air ...

    EPA Pesticide Factsheets

    Green infrastructure can be a cost-effective approach for reducing stormwater runoff and improving water quality as a result, but it could also bring co-benefits for air quality: less impervious surfaces and more vegetation can decrease the urban heat island effect, and also result in more removal of air pollutants via dry deposition with increased vegetative surfaces. Cooler surface temperatures can also decrease ozone formation through the increases of NOx titration; however, cooler surface temperatures also lower the height of the boundary layer resulting in more concentrated pollutants within the same volume of air, especially for primary emitted pollutants (e.g. NOx, CO, primary particulate matter). To better understand how green infrastructure impacts air quality, the interactions between all of these processes must be considered collectively. In this study, we use a comprehensive coupled meteorology-air quality model (WRF-CMAQ) to simulate the influence of planned land use changes that include green infrastructure in Kansas City (KC) on regional meteorology and air quality. Current and future land use data was provided by the Mid-America Regional Council for 2012 and 2040 (projected land use due to population growth, city planning and green infrastructure implementation). These land use datasets were incorporated into the WRF-CMAQ modeling system allowing the modeling system to propagate the changes in vegetation and impervious surface coverage on meteoro

  16. 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 ...

  17. Global Air Quality and Climate

    NASA Technical Reports Server (NTRS)

    Fiore, Arlene M.; Naik, Vaishali; Steiner, Allison; Unger, Nadine; Bergmann, Dan; Prather, Michael; Righi, Mattia; Rumbold, Steven T.; Shindell, Drew T.; Skeie, Ragnhild B.; hide

    2012-01-01

    Emissions of air pollutants and their precursors determine regional air quality and can alter climate. Climate change can perturb the long-range transport, chemical processing, and local meteorology that influence air pollution. We review the implications of projected changes in methane (CH4), ozone precursors (O3), and aerosols for climate (expressed in terms of the radiative forcing metric or changes in global surface temperature) and hemispheric-to-continental scale air quality. Reducing the O3 precursor CH4 would slow near-term warming by decreasing both CH4 and tropospheric O3. Uncertainty remains as to the net climate forcing from anthropogenic nitrogen oxide (NOx) emissions, which increase tropospheric O3 (warming) but also increase aerosols and decrease CH4 (both cooling). Anthropogenic emissions of carbon monoxide (CO) and non-CH4 volatile organic compounds (NMVOC) warm by increasing both O3 and CH4. Radiative impacts from secondary organic aerosols (SOA) are poorly understood. Black carbon emission controls, by reducing the absorption of sunlight in the atmosphere and on snow and ice, have the potential to slow near-term warming, but uncertainties in coincident emissions of reflective (cooling) aerosols and poorly constrained cloud indirect effects confound robust estimates of net climate impacts. Reducing sulfate and nitrate aerosols would improve air quality and lessen interference with the hydrologic cycle, but lead to warming. A holistic and balanced view is thus needed to assess how air pollution controls influence climate; a first step towards this goal involves estimating net climate impacts from individual emission sectors. Modeling and observational analyses suggest a warming climate degrades air quality (increasing surface O3 and particulate matter) in many populated regions, including during pollution episodes. Prior Intergovernmental Panel on Climate Change (IPCC) scenarios (SRES) allowed unconstrained growth, whereas the Representative

  18. Global air quality and climate.

    PubMed

    Fiore, Arlene M; Naik, Vaishali; Spracklen, Dominick V; Steiner, Allison; Unger, Nadine; Prather, Michael; Bergmann, Dan; Cameron-Smith, Philip J; Cionni, Irene; Collins, William J; Dalsøren, Stig; Eyring, Veronika; Folberth, Gerd A; Ginoux, Paul; Horowitz, Larry W; Josse, Béatrice; Lamarque, Jean-François; MacKenzie, Ian A; Nagashima, Tatsuya; O'Connor, Fiona M; Righi, Mattia; Rumbold, Steven T; Shindell, Drew T; Skeie, Ragnhild B; Sudo, Kengo; Szopa, Sophie; Takemura, Toshihiko; Zeng, Guang

    2012-10-07

    Emissions of air pollutants and their precursors determine regional air quality and can alter climate. Climate change can perturb the long-range transport, chemical processing, and local meteorology that influence air pollution. We review the implications of projected changes in methane (CH(4)), ozone precursors (O(3)), and aerosols for climate (expressed in terms of the radiative forcing metric or changes in global surface temperature) and hemispheric-to-continental scale air quality. Reducing the O(3) precursor CH(4) would slow near-term warming by decreasing both CH(4) and tropospheric O(3). Uncertainty remains as to the net climate forcing from anthropogenic nitrogen oxide (NO(x)) emissions, which increase tropospheric O(3) (warming) but also increase aerosols and decrease CH(4) (both cooling). Anthropogenic emissions of carbon monoxide (CO) and non-CH(4) volatile organic compounds (NMVOC) warm by increasing both O(3) and CH(4). Radiative impacts from secondary organic aerosols (SOA) are poorly understood. Black carbon emission controls, by reducing the absorption of sunlight in the atmosphere and on snow and ice, have the potential to slow near-term warming, but uncertainties in coincident emissions of reflective (cooling) aerosols and poorly constrained cloud indirect effects confound robust estimates of net climate impacts. Reducing sulfate and nitrate aerosols would improve air quality and lessen interference with the hydrologic cycle, but lead to warming. A holistic and balanced view is thus needed to assess how air pollution controls influence climate; a first step towards this goal involves estimating net climate impacts from individual emission sectors. Modeling and observational analyses suggest a warming climate degrades air quality (increasing surface O(3) and particulate matter) in many populated regions, including during pollution episodes. Prior Intergovernmental Panel on Climate Change (IPCC) scenarios (SRES) allowed unconstrained growth, whereas

  19. Incorporating wind availability into land use regression modelling of air quality in mountainous high-density urban environment.

    PubMed

    Shi, Yuan; Lau, Kevin Ka-Lun; Ng, Edward

    2017-08-01

    Urban air quality serves as an important function of the quality of urban life. Land use regression (LUR) modelling of air quality is essential for conducting health impacts assessment but more challenging in mountainous high-density urban scenario due to the complexities of the urban environment. In this study, a total of 21 LUR models are developed for seven kinds of air pollutants (gaseous air pollutants CO, NO 2 , NO x , O 3 , SO 2 and particulate air pollutants PM 2.5 , PM 10 ) with reference to three different time periods (summertime, wintertime and annual average of 5-year long-term hourly monitoring data from local air quality monitoring network) in Hong Kong. Under the mountainous high-density urban scenario, we improved the traditional LUR modelling method by incorporating wind availability information into LUR modelling based on surface geomorphometrical analysis. As a result, 269 independent variables were examined to develop the LUR models by using the "ADDRESS" independent variable selection method and stepwise multiple linear regression (MLR). Cross validation has been performed for each resultant model. The results show that wind-related variables are included in most of the resultant models as statistically significant independent variables. Compared with the traditional method, a maximum increase of 20% was achieved in the prediction performance of annual averaged NO 2 concentration level by incorporating wind-related variables into LUR model development. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Sensitivity of air quality simulation to smoke plume rise

    Treesearch

    Yongqiang Liu; Gary Achtemeier; Scott Goodrick

    2008-01-01

    Plume rise is the height smoke plumes can reach. This information is needed by air quality models such as the Community Multiscale Air Quality (CMAQ) model to simulate physical and chemical processes of point-source fire emissions. This study seeks to understand the importance of plume rise to CMAQ air quality simulation of prescribed burning to plume rise. CMAQ...

  1. Air quality in Delhi during the Commonwealth Games

    NASA Astrophysics Data System (ADS)

    Marrapu, P.; Cheng, Y.; Beig, G.; Sahu, S.; Srinivas, R.; Carmichael, G. R.

    2014-10-01

    Air quality during the Commonwealth Games (CWG, held in Delhi in October 2010) is analyzed using a new air quality forecasting system established for the games. The CWG stimulated enhanced efforts to monitor and model air quality in the region. The air quality of Delhi during the CWG had high levels of particles with mean values of PM2.5 and PM10 at the venues of 111 and 238 μg m-3, respectively. Black carbon (BC) accounted for ~ 10% of the PM2.5 mass. It is shown that BC, PM2.5 and PM10 concentrations are well predicted, but with positive biases of ~ 25%. The diurnal variations are also well captured, with both the observations and the modeled values showing nighttime maxima and daytime minima. A new emissions inventory, developed as part of this air quality forecasting initiative, is evaluated by comparing the observed and predicted species-species correlations (i.e., BC : CO; BC : PM2.5; PM2.5 : PM10). Assuming that the observations at these sites are representative and that all the model errors are associated with the emissions, then the modeled concentrations and slopes can be made consistent by scaling the emissions by 0.6 for NOx, 2 for CO, and 0.7 for BC, PM2.5, and PM10. The emission estimates for particles are remarkably good considering the uncertainty in the estimates due to the diverse spread of activities and technologies that take place in Delhi and the rapid rates of change. The contribution of various emission sectors including transportation, power, domestic and industry to surface concentrations are also estimated. Transport, domestic and industrial sectors all make significant contributions to PM levels in Delhi, and the sectoral contributions vary spatially within the city. Ozone levels in Delhi are elevated, with hourly values sometimes exceeding 100 ppb. The continued growth of the transport sector is expected to make ozone pollution a more pressing air pollution problem in Delhi. The sector analysis provides useful inputs into the design of

  2. Real-time dissemination of air quality information using data streams and Web technologies: linking air quality to health risks in urban areas.

    PubMed

    Davila, Silvije; Ilić, Jadranka Pečar; Bešlić, Ivan

    2015-06-01

    This article presents a new, original application of modern information and communication technology to provide effective real-time dissemination of air quality information and related health risks to the general public. Our on-line subsystem for urban real-time air quality monitoring is a crucial component of a more comprehensive integrated information system, which has been developed by the Institute for Medical Research and Occupational Health. It relies on a StreamInsight data stream management system and service-oriented architecture to process data streamed from seven monitoring stations across Zagreb. Parameters that are monitored include gases (NO, NO2, CO, O3, H2S, SO2, benzene, NH3), particulate matter (PM10 and PM2.5), and meteorological data (wind speed and direction, temperature and pressure). Streamed data are processed in real-time using complex continuous queries. They first go through automated validation, then hourly air quality index is calculated for every station, and a report sent to the Croatian Environment Agency. If the parameter values exceed the corresponding regulation limits for three consecutive hours, the web service generates an alert for population groups at risk. Coupled with the Common Air Quality Index model, our web application brings air pollution information closer to the general population and raises awareness about environmental and health issues. Soon we intend to expand the service to a mobile application that is being developed.

  3. 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...

  4. 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

  5. Methodology for Air Quality Forecast Downscaling from Regional- to Street-Scale

    NASA Astrophysics Data System (ADS)

    Baklanov, Alexander; Nuterman, Roman; Mahura, Alexander; Amstrup, Bjarne; Hansen Saas, Bent; Havskov Sørensen, Jens; Lorenzen, Thomas; Weismann, Jakob

    2010-05-01

    The most serious air pollution events occur in cities where there is a combination of high population density and air pollution, e.g. from vehicles. The pollutants can lead to serious human health problems, including asthma, irritation of the lungs, bronchitis, pneumonia, decreased resistance to respiratory infections, and premature death. In particular air pollution is associated with increase in cardiovascular disease and lung cancer. In 2000 WHO estimated that between 2.5 % and 11 % of total annual deaths are caused by exposure to air pollution. However, European-scale air quality models are not suited for local forecasts, as their grid-cell is typically of the order of 5 to 10km and they generally lack detailed representation of urban effects. Two suites are used in the framework of the EC FP7 project MACC (Monitoring of Atmosphere Composition and Climate) to demonstrate how downscaling from the European MACC ensemble to local-scale air quality forecast will be carried out: one will illustrate capabilities for the city of Copenhagen (Denmark); the second will focus on the city of Bucharest (Romania). This work is devoted to the first suite, where methodological aspects of downscaling from regional (European/ Denmark) to urban scale (Copenhagen), and from the urban down to street scale. The first results of downscaling according to the proposed methodology are presented. The potential for downscaling of European air quality forecasts by operating urban and street-level forecast models is evaluated. This will bring a strong support for continuous improvement of the regional forecast modelling systems for air quality in Europe, and underline clear perspectives for the future regional air quality core and downstream services for end-users. At the end of the MACC project, requirements on "how-to-do" downscaling of European air-quality forecasts to the city and street levels with different approaches will be formulated.

  6. The Contribution of Marine Organics to the Air Quality of the Western United States

    EPA Science Inventory

    The contribution of marine organic emissions to the air quality in coastal areas of the western United States is studied using the latest version of the US Environmental Protection Agency (EPA) regional-scale Community Multiscale Air Quality (CMAQv4.7) modeling system. Emissions ...

  7. 76 FR 72097 - Air Quality Designations for the 2008 Lead (Pb) National Ambient Air Quality Standards

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-11-22

    ... broad range of adverse health effects. These may include damage to the central nervous system...) Meteorology (weather/transport patterns); (6) Geography/topography (mountain ranges or other air basin... to the EPA's Air Quality System (AQS), or otherwise available to the EPA, and meeting the...

  8. Monitoring Indoor Air Quality for Enhanced Occupational Health.

    PubMed

    Pitarma, Rui; Marques, Gonçalo; Ferreira, Bárbara Roque

    2017-02-01

    Indoor environments are characterized by several pollutant sources. Because people spend more than 90% of their time in indoor environments, several studies have pointed out the impact of indoor air quality on the etiopathogenesis of a wide number of non-specific symptoms which characterizes the "Sick Building Syndrome", involving the skin, the upper and lower respiratory tract, the eyes and the nervous system, as well as many building related diseases. Thus, indoor air quality (IAQ) is recognized as an important factor to be controlled for the occupants' health and comfort. The majority of the monitoring systems presently available is very expensive and only allow to collect random samples. This work describes the system (iAQ), a low-cost indoor air quality monitoring wireless sensor network system, developed using Arduino, XBee modules and micro sensors, for storage and availability of monitoring data on a web portal in real time. Five micro sensors of environmental parameters (air temperature, humidity, carbon monoxide, carbon dioxide and luminosity) were used. Other sensors can be added for monitoring specific pollutants. The results reveal that the system can provide an effective indoor air quality assessment to prevent exposure risk. In fact, the indoor air quality may be extremely different compared to what is expected for a quality living environment. Systems like this would have benefit as public health interventions to reduce the burden of symptoms and diseases related to "sick buildings".

  9. 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.

  10. EVALUATION OF THE REAL-TIME AIR-QUALITY MODEL USING THE RAPS (REGIONAL AIR POLLUTION STUDY) DATA BASE. VOLUME 3. PROGRAM USER'S GUIDE

    EPA Science Inventory

    The theory and programming of statistical tests for evaluating the Real-Time Air-Quality Model (RAM) using the Regional Air Pollution Study (RAPS) data base are fully documented in four volumes. Moreover, the tests are generally applicable to other model evaluation problems. Volu...

  11. Notification: Evaluation of EPA’s Approval Process for Air Quality Dispersion Models

    EPA Pesticide Factsheets

    Project #OPE-FY17-0016, June 5, 2017. The EPA OIG plans to begin preliminary research to assess the effectiveness of EPA's process for reviewing and approving air quality dispersion models it recommends for use.

  12. A Risk-based Assessment And Management Framework For Multipollutant Air Quality

    PubMed Central

    Frey, H. Christopher; Hubbell, Bryan

    2010-01-01

    The National Research Council recommended both a risk- and performance-based multipollutant approach to air quality management. Specifically, management decisions should be based on minimizing the exposure to, and risk of adverse effects from, multiple sources of air pollution and that the success of these decisions should be measured by how well they achieved this objective. We briefly describe risk analysis and its application within the current approach to air quality management. Recommendations are made as to how current practice could evolve to support a fully risk- and performance-based multipollutant air quality management system. The ability to implement a risk assessment framework in a credible and policy-relevant manner depends on the availability of component models and data which are scientifically sound and developed with an understanding of their application in integrated assessments. The same can be said about accountability assessments used to evaluate the outcomes of decisions made using such frameworks. The existing risk analysis framework, although typically applied to individual pollutants, is conceptually well suited for analyzing multipollutant management actions. Many elements of this framework, such as emissions and air quality modeling, already exist with multipollutant characteristics. However, the framework needs to be supported with information on exposure and concentration response relationships that result from multipollutant health studies. Because the causal chain that links management actions to emission reductions, air quality improvements, exposure reductions and health outcomes is parallel between prospective risk analyses and retrospective accountability assessments, both types of assessment should be placed within a single framework with common metrics and indicators where possible. Improvements in risk reductions can be obtained by adopting a multipollutant risk analysis framework within the current air quality management

  13. The Impacts of Policies To Meet The UK Climate Change Act Target on Air Quality - An Explicit Modelling Study

    NASA Astrophysics Data System (ADS)

    Williams, M.; Beevers, S.; Lott, M. C.; Kitwiroon, N.

    2016-12-01

    This paper presents a preliminary analysis of different pathways to meet the UK Climate Change Act target for 2050, of an 80% reduction in carbon dioxide equivalent emissions on a base year of 1990. The pathways can result in low levels of air pollution emissions through the use of renewables and nuclear power. But large increases in biomass burning and the continued use of diesel cars they can result in larger air quality impacts. The work evaluated the air quality impacts in several pathways using an energy system optimisation model (UK TIMES) and a chemical transport model (CMAQ). The work described in this paper goes beyond the `damage cost' approach where only emissions in each are assessed. In this work we used scenarios produced by the UK TIMES model which we converted into air pollution emissions. Emissions of ammonia from agriculture are not attributed to the energy system and are thus not captured by energy system models, yet are crucial in forming PM2.5, acknowledged to be currently the most important pollutant associated with premature deaths. Our model includes these emissions and other non-energy sources of hydrocarbons which lead to the formation of ozone, another significant cause of air pollution health impacts. A key policy issue is how much biogenic hydrocarbons contribute to ozone formation compared with man-made emissions. We modelled pollution concentrations at a resolution of 7 km across the UK and at 2km in urban areas. These results allow us to estimate changes in premature mortality and morbidity associated with the changes in air pollution and subsequently the economic cost of the impacts on public health. The work shows that in the `clean' scenario, urban exposures to particles (PM2.5) and NO2 could decrease by very large amounts, but ozone exposures are likely to increase without further significant reductions world-wide. Large increases in biomass use however could lead to increases in urban levels of carcinogens and primary PM.

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

  15. Enhanced data validation strategy of air quality monitoring network.

    PubMed

    Harkat, Mohamed-Faouzi; Mansouri, Majdi; Nounou, Mohamed; Nounou, Hazem

    2018-01-01

    Quick validation and detection of faults in measured air quality data is a crucial step towards achieving the objectives of air quality networks. Therefore, the objectives of this paper are threefold: (i) to develop a modeling technique that can be used to predict the normal behavior of air quality variables and help provide accurate reference for monitoring purposes; (ii) to develop fault detection method that can effectively and quickly detect any anomalies in measured air quality data. For this purpose, a new fault detection method that is based on the combination of generalized likelihood ratio test (GLRT) and exponentially weighted moving average (EWMA) will be developed. GLRT is a well-known statistical fault detection method that relies on maximizing the detection probability for a given false alarm rate. In this paper, we propose to develop GLRT-based EWMA fault detection method that will be able to detect the changes in the values of certain air quality variables; (iii) to develop fault isolation and identification method that allows defining the fault source(s) in order to properly apply appropriate corrective actions. In this paper, reconstruction approach that is based on Midpoint-Radii Principal Component Analysis (MRPCA) model will be developed to handle the types of data and models associated with air quality monitoring networks. All air quality modeling, fault detection, fault isolation and reconstruction methods developed in this paper will be validated using real air quality data (such as particulate matter, ozone, nitrogen and carbon oxides measurement). Copyright © 2017 Elsevier Inc. All rights reserved.

  16. 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.

  17. Urban air quality estimation study, phase 1

    NASA Technical Reports Server (NTRS)

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

    1976-01-01

    Possibilities are explored for applying estimation theory to the analysis, interpretation, and use of air quality measurements in conjunction with simulation models to provide a cost effective method of obtaining reliable air quality estimates for wide urban areas. The physical phenomenology of real atmospheric plumes from elevated localized sources is discussed. A fluctuating plume dispersion model is derived. Individual plume parameter formulations are developed along with associated a priori information. Individual measurement models are developed.

  18. Evaluation of air quality zone classification methods based on ambient air concentration exposure.

    PubMed

    Freeman, Brian; McBean, Ed; Gharabaghi, Bahram; Thé, Jesse

    2017-05-01

    Air quality zones are used by regulatory authorities to implement ambient air standards in order to protect human health. Air quality measurements at discrete air monitoring stations are critical tools to determine whether an air quality zone complies with local air quality standards or is noncompliant. This study presents a novel approach for evaluation of air quality zone classification methods by breaking the concentration distribution of a pollutant measured at an air monitoring station into compliance and exceedance probability density functions (PDFs) and then using Monte Carlo analysis with the Central Limit Theorem to estimate long-term exposure. The purpose of this paper is to compare the risk associated with selecting one ambient air classification approach over another by testing the possible exposure an individual living within a zone may face. The chronic daily intake (CDI) is utilized to compare different pollutant exposures over the classification duration of 3 years between two classification methods. Historical data collected from air monitoring stations in Kuwait are used to build representative models of 1-hr NO 2 and 8-hr O 3 within a zone that meets the compliance requirements of each method. The first method, the "3 Strike" method, is a conservative approach based on a winner-take-all approach common with most compliance classification methods, while the second, the 99% Rule method, allows for more robust analyses and incorporates long-term trends. A Monte Carlo analysis is used to model the CDI for each pollutant and each method with the zone at a single station and with multiple stations. The model assumes that the zone is already in compliance with air quality standards over the 3 years under the different classification methodologies. The model shows that while the CDI of the two methods differs by 2.7% over the exposure period for the single station case, the large number of samples taken over the duration period impacts the sensitivity

  19. Evaluation of CMAQ and CAMx Ensemble Air Quality Forecasts during the 2015 MAPS-Seoul Field Campaign

    NASA Astrophysics Data System (ADS)

    Kim, E.; Kim, S.; Bae, C.; Kim, H. C.; Kim, B. U.

    2015-12-01

    The performance of Air quality forecasts during the 2015 MAPS-Seoul Field Campaign was evaluated. An forecast system has been operated to support the campaign's daily aircraft route decisions for airborne measurements to observe long-range transporting plume. We utilized two real-time ensemble systems based on the Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emissions (SMOKE)-Comprehensive Air quality Model with extensions (CAMx) modeling framework and WRF-SMOKE- Community Multi_scale Air Quality (CMAQ) framework over northeastern Asia to simulate PM10 concentrations. Global Forecast System (GFS) from National Centers for Environmental Prediction (NCEP) was used to provide meteorological inputs for the forecasts. For an additional set of retrospective simulations, ERA Interim Reanalysis from European Centre for Medium-Range Weather Forecasts (ECMWF) was also utilized to access forecast uncertainties from the meteorological data used. Model Inter-Comparison Study for Asia (MICS-Asia) and National Institute of Environment Research (NIER) Clean Air Policy Support System (CAPSS) emission inventories are used for foreign and domestic emissions, respectively. In the study, we evaluate the CMAQ and CAMx model performance during the campaign by comparing the results to the airborne and surface measurements. Contributions of foreign and domestic emissions are estimated using a brute force method. Analyses on model performance and emissions will be utilized to improve air quality forecasts for the upcoming KORUS-AQ field campaign planned in 2016.

  20. 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.

  1. Adding spatial flexibility to source-receptor relationships for air quality modeling.

    PubMed

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

    2017-04-01

    To cope with computing power limitations, air quality models that are used in integrated assessment applications are generally approximated by simpler expressions referred to as "source-receptor relationships (SRR)". In addition to speed, it is desirable for the SRR also to be spatially flexible (application over a wide range of situations) and to require a "light setup" (based on a limited number of full Air Quality Models - AQM simulations). But "speed", "flexibility" and "light setup" do not naturally come together and a good compromise must be ensured that preserves "accuracy", i.e. a good comparability between SRR results and AQM. In this work we further develop a SRR methodology to better capture spatial flexibility. The updated methodology is based on a cell-to-cell relationship, in which a bell-shape function links emissions to concentrations. Maintaining a cell-to-cell relationship is shown to be the key element needed to ensure spatial flexibility, while at the same time the proposed approach to link emissions and concentrations guarantees a "light set-up" phase. Validation has been repeated on different areas and domain sizes (countries, regions, province throughout Europe) for precursors reduced independently or contemporarily. All runs showed a bias around 10% between the full AQM and the SRR. This methodology allows assessing the impact on air quality of emission scenarios applied over any given area in Europe (regions, set of regions, countries), provided that a limited number of AQM simulations are performed for training.

  2. USE OF REMOTE SENSING AIR QUALITY INFORMATION IN REGIONAL SCALE AIR POLLUTION MODELING: CURRENT USE AND REQUIREMENTS

    EPA Science Inventory

    In recent years the applications of regional air quality models are continuously being extended to address atmospheric pollution phenomenon from local to hemispheric spatial scales over time scales ranging from episodic to annual. The need to represent interactions between physic...

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

    EPA Science Inventory

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

  4. 78 FR 8485 - Approval and Promulgation of Air Quality Implementation Plans; Michigan

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-06

    ... Promulgation of Air Quality Implementation Plans; Michigan AGENCY: Environmental Protection Agency (EPA... control), R336.1240 (Required air quality models), R336.1241 (Air quality modeling demonstration... nonattainment air quality permitting regulations found in 40 CFR 51.165(a) and (b). EPA has found that the rules...

  5. Korea-United States Air Quality (KORUS-AQ) Campaign

    NASA Technical Reports Server (NTRS)

    Castellanos, Patricia; Da Silva, Arlindo; Longo-De Freitas, Karla

    2017-01-01

    The Korea-United States Air Quality (KORUS-AQ) campaign was an international cooperative field study based out of Osan Air Base, Songtan, South Korea (about 60 kilometers south of Seoul) in April-June 2016. A comprehensive suite of instruments capable of measuring atmospheric composition was deployed around the Korean peninsula on aircrafts, ships, and at ground sites in order to characterize local and transboundary pollution. The NASA Goddard Earth Observing System, version 5 (GEOS-5) forecast model was used for near real time meteorological and aerosol forecasting and flight planning during the KORUS-AQ campaign. Evaluation of GEOS-5 against observations from the campaign will help to identify inaccuracies in the models physical and chemical processes in this region within East Asia and lead to further developments of the modeling system.

  6. Air quality real-time forecast before and during the G-20 ...

    EPA Pesticide Factsheets

    The 2016 G-20 Hangzhou summit, the eleventh annual meeting of the G-20 heads of government, will be held during September 3-5, 2016 in Hangzhou, China. For a successful summit, it is important to ensure good air quality. To achieve this goal, governments of Hangzhou and its surrounding provinces will enforce a series of emission reductions, such as a forced closure of major highly-polluting industries and also limiting car and construction emissions in the cities and surroundings during the 2016 G-20 Hangzhou summit. Air quality forecast systems consisting of the two-way coupled WRF-CMAQ and online-coupled WRF-Chem have been applied to forecast air quality in Hangzhou regularly. This study will present the results of real-time forecasts of air quality over eastern China using 12-km grid spacing and for Hangzhou area using 4-km grid spacing with these two modeling systems using emission inventories for base and 2016 G-20 scenarios before and during the 2016 G-20 Hangzhou summit. Evaluations of models’ performance for both cases for PM2.5, PM10, O3, SO2, NO2, CO, air quality index (AQI), and aerosol optical depth (AOD) are carried out by comparing them with observations obtained from satellites, such as MODIS, and surface monitoring networks. The effects of the emission reduction efforts on expected air quality improvements during the2016 G-20 Hangzhou summit will be studied in depth. This study provides insights on how air quality will be improved by a plan

  7. Assessment of air quality microsensors versus reference methods: The EuNetAir joint exercise

    NASA Astrophysics Data System (ADS)

    Borrego, C.; Costa, A. M.; Ginja, J.; Amorim, M.; Coutinho, M.; Karatzas, K.; Sioumis, Th.; Katsifarakis, N.; Konstantinidis, K.; De Vito, S.; Esposito, E.; Smith, P.; André, N.; Gérard, P.; Francis, L. A.; Castell, N.; Schneider, P.; Viana, M.; Minguillón, M. C.; Reimringer, W.; Otjes, R. P.; von Sicard, O.; Pohle, R.; Elen, B.; Suriano, D.; Pfister, V.; Prato, M.; Dipinto, S.; Penza, M.

    2016-12-01

    The 1st EuNetAir Air Quality Joint Intercomparison Exercise organized in Aveiro (Portugal) from 13th-27th October 2014, focused on the evaluation and assessment of environmental gas, particulate matter (PM) and meteorological microsensors, versus standard air quality reference methods through an experimental urban air quality monitoring campaign. The IDAD-Institute of Environment and Development Air Quality Mobile Laboratory was placed at an urban traffic location in the city centre of Aveiro to conduct continuous measurements with standard equipment and reference analysers for CO, NOx, O3, SO2, PM10, PM2.5, temperature, humidity, wind speed and direction, solar radiation and precipitation. The comparison of the sensor data generated by different microsensor-systems installed side-by-side with reference analysers, contributes to the assessment of the performance and the accuracy of microsensor-systems in a real-world context, and supports their calibration and further development. The overall performance of the sensors in terms of their statistical metrics and measurement profile indicates significant differences in the results depending on the platform and on the sensors considered. In terms of pollutants, some promising results were observed for O3 (r2: 0.12-0.77), CO (r2: 0.53-0.87), and NO2 (r2: 0.02-0.89). For PM (r2: 0.07-0.36) and SO2 (r2: 0.09-0.20) the results show a poor performance with low correlation coefficients between the reference and microsensor measurements. These field observations under specific environmental conditions suggest that the relevant microsensor platforms, if supported by the proper post processing and data modelling tools, have enormous potential for new strategies in air quality control.

  8. “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...

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

    EPA Science Inventory

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

  10. A novel, fuzzy-based air quality index (FAQI) for air quality assessment

    NASA Astrophysics Data System (ADS)

    Sowlat, Mohammad Hossein; Gharibi, Hamed; Yunesian, Masud; Tayefeh Mahmoudi, Maryam; Lotfi, Saeedeh

    2011-04-01

    The ever increasing level of air pollution in most areas of the world has led to development of a variety of air quality indices for estimation of health effects of air pollution, though the indices have their own limitations such as high levels of subjectivity. Present study, therefore, aimed at developing a novel, fuzzy-based air quality index (FAQI ) to handle such limitations. The index developed by present study is based on fuzzy logic that is considered as one of the most common computational methods of artificial intelligence. In addition to criteria air pollutants (i.e. CO, SO 2, PM 10, O 3, NO 2), benzene, toluene, ethylbenzene, xylene, and 1,3-butadiene were also taken into account in the index proposed, because of their considerable health effects. Different weighting factors were then assigned to each pollutant according to its priority. Trapezoidal membership functions were employed for classifications and the final index consisted of 72 inference rules. To assess the performance of the index, a case study was carried out employing air quality data at five different sampling stations in Tehran, Iran, from January 2008 to December 2009, results of which were then compared to the results obtained from USEPA air quality index (AQI). According to the results from present study, fuzzy-based air quality index is a comprehensive tool for classification of air quality and tends to produce accurate results. Therefore, it can be considered useful, reliable, and suitable for consideration by local authorities in air quality assessment and management schemes. Fuzzy-based air quality index (FAQI).

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

    PubMed Central

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

    1997-01-01

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

  12. 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...

  13. Air quality in Delhi during the CommonWealth Games

    NASA Astrophysics Data System (ADS)

    Marrapu, P.; Cheng, Y.; Beig, G.; Sahu, S.; Srinivas, R.; Carmichael, G. R.

    2014-04-01

    Air quality during The CommonWealth Games (CWG, held in Delhi in October 2010) is analyzed using a new air quality forecasting system established for the Games. The CWG stimulated enhanced efforts to monitor and model air quality in the region. The air quality of Delhi during the CWG had high levels of particles with mean values of PM2.5 and PM10 at the venues of 111 and 238 μg m-3, respectively. Black carbon (BC) accounted for ∼10% of the PM2.5 mass. It is shown that BC, PM2.5 and PM10 concentrations are well predicted, but with positive biases of ∼25%. The diurnal variations are also well captured, with both the observations and the modeled values showing nighttime maxima and daytime minima. A new emissions inventory, developed as part of this air quality forecasting initiative, is evaluated by comparing the observed and predicted species-species correlations (i.e., BC : CO; BC : PM2.5; PM2.5 : PM10). Assuming that the observations at these sites are representative and that all the model errors are associated with the emissions, then the modeled concentrations and slopes can be made consistent by scaling the emissions by: 0.6 for NOx, 2 for CO, and 0.7 for BC, PM2.5 and PM10. The emission estimates for particles are remarkably good considering the uncertainty in the estimates due to the diverse spread of activities and technologies that take place in Delhi and the rapid rates of change. The contribution of various emission sectors including transportation, power, domestic and industry to surface concentrations are also estimated. Transport, domestic and industrial sectors all make significant contributions to PM levels in Delhi, and the sectoral contributions vary spatially within the city. Ozone levels in Delhi are elevated, with hourly values sometimes exceeding 100 ppb. The continued growth of the transport sector is expected to make ozone pollution a more pressing air pollution problem in Delhi. The sector analysis provides useful inputs into the

  14. 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

  15. Development of an Aura Chemical Reanalysis in support Air Quality Applications

    NASA Astrophysics Data System (ADS)

    Pierce, R. B.; Lenzen, A.; Schaack, T.

    2015-12-01

    We present results of chemical data assimilation experiments utilizing the NOAA National Environmental Satellite, Data, and Information Service (NESDIS), University of Wisconsin Space Science and Engineering (SSEC) Real-time Air Quality Modeling System (RAQMS) in conjunction with the NOAA National Centers for Environmental Prediction (NCEP) Operational Gridpoint Statistical Interpolation (GSI) 3-dimensional variational data assimilation system. The impact of assimilating NASA Ozone Monitoring Instrument (OMI) total column ozone, OMI tropospheric nitrogen dioxide columns, and Microwave Limb Sounder (MLS) stratospheric ozone profiles on background ozone is assessed using measurements from the 2010 NSF High-performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observation (HIPPO) and NOAA California Nexus (CalNex) campaigns. Results show that the RAQMS/GSI Chemical Reanalysis is able to provide very good estimates of background ozone and large-scale ozone variability and is suitable for use in constraining regional air quality modeling activities. These experiments are being used to guide the development of a multi-year global chemical and aerosol reanalysis using NASA Aura and A-Train measurements to support air quality applications.

  16. Examining the impacts of increased corn production on groundwater quality using a coupled modeling system

    EPA Science Inventory

    This study demonstrates the value of a coupled chemical transport modeling system for investigating groundwater nitrate contamination responses associated with nitrogen (N) fertilizer application and increased corn production. The coupled Community Multiscale Air Quality Bidirect...

  17. Modeling, Monitoring and Fault Diagnosis of Spacecraft Air Contaminants

    NASA Technical Reports Server (NTRS)

    Ramirez, W. Fred; Skliar, Mikhail; Narayan, Anand; Morgenthaler, George W.; Smith, Gerald J.

    1996-01-01

    Progress and results in the development of an integrated air quality modeling, monitoring, fault detection, and isolation system are presented. The focus was on development of distributed models of the air contaminants transport, the study of air quality monitoring techniques based on the model of transport process and on-line contaminant concentration measurements, and sensor placement. Different approaches to the modeling of spacecraft air contamination are discussed, and a three-dimensional distributed parameter air contaminant dispersion model applicable to both laminar and turbulent transport is proposed. A two-dimensional approximation of a full scale transport model is also proposed based on the spatial averaging of the three dimensional model over the least important space coordinate. A computer implementation of the transport model is considered and a detailed development of two- and three-dimensional models illustrated by contaminant transport simulation results is presented. The use of a well established Kalman filtering approach is suggested as a method for generating on-line contaminant concentration estimates based on both real time measurements and the model of contaminant transport process. It is shown that high computational requirements of the traditional Kalman filter can render difficult its real-time implementation for high-dimensional transport model and a novel implicit Kalman filtering algorithm is proposed which is shown to lead to an order of magnitude faster computer implementation in the case of air quality monitoring.

  18. An Integrated Computer Modeling Environment for Regional Land Use, Air Quality, and Transportation Planning

    DOT National Transportation Integrated Search

    1997-04-01

    The Land Use, Air Quality, and Transportation Integrated Modeling Environment (LATIME) represents an integrated approach to computer modeling and simulation of land use allocation, travel demand, and mobile source emissions for the Albuquerque, New M...

  19. 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.

  20. Assimilation of Quality Controlled AIRS Temperature Profiles using the NCEP GFS

    NASA Technical Reports Server (NTRS)

    Susskind, Joel; Reale, Oreste; Iredell, Lena; Rosenberg, Robert

    2013-01-01

    We have previously conducted a number of data assimilation experiments using AIRS Version-5 quality controlled temperature profiles as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The data assimilation and forecast system we used was the Goddard Earth Observing System Model , Version-5 (GEOS-5) Data Assimilation System (DAS), which represents a combination of the NASA GEOS-5 forecast model with the National Centers for Environmental Prediction (NCEP) operational Grid Point Statistical Interpolation (GSI) global analysis scheme. All analyses and forecasts were run at a 0.5deg x 0.625deg spatial resolution. Data assimilation experiments were conducted in four different seasons, each in a different year. Three different sets of data assimilation experiments were run during each time period: Control; AIRS T(p); and AIRS Radiance. In the "Control" analysis, all the data used operationally by NCEP was assimilated, but no AIRS data was assimilated. Radiances from the Aqua AMSU-A instrument were also assimilated operationally by NCEP and are included in the "Control". The AIRS Radiance assimilation adds AIRS observed radiance observations for a select set of channels to the data set being assimilated, as done operationally by NCEP. In the AIRS T(p) assimilation, all information used in the Control was assimilated as well as Quality Controlled AIRS Version-5 temperature profiles, i.e., AIRS T(p) information was substituted for AIRS radiance information. The AIRS Version-5 temperature profiles were presented to the GSI analysis as rawinsonde profiles, assimilated down to a case-by-case appropriate pressure level p(sub best) determined using the Quality Control procedure. Version-5 also determines case-by-case, level-by-level error estimates of the temperature profiles, which were used as the uncertainty of each temperature measurement. These experiments using GEOS-5 have shown that forecasts

  1. 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...

  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. 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.

  4. 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.

  5. SAMIRA - SAtellite based Monitoring Initiative for Regional Air quality

    NASA Astrophysics Data System (ADS)

    Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nicolae, Doina; Stachlewska, Iwona; Zehner, Claus

    2016-04-01

    Here, we present a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellites, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. Despite considerable improvements in the past decades, Europe is still far from achieving levels of air quality that do not pose unacceptable hazards to humans and the environment. Main concerns in Europe are exceedances of particulate matter (PM), ground-level ozone, benzo(a)pyrene (BaP) and nitrogen dioxide (NO2). While overall sulfur dioxide (SO2) emissions have decreased in recent years, regional concentrations can still be high in some areas. The objectives of SAMIRA are to improve algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from SEVIRI, and to develop robust methods for deriving column- and near-surface PM maps for the study area by combining satellite AOD with information from regional models. The benefit to existing monitoring networks (in situ, models, satellite) by combining these datasets using data fusion methods will be tested for satellite-based NO2, SO2, and PM/AOD. Furthermore, SAMIRA will test and apply techniques for downscaling air quality-related EO products to a spatial resolution that is more in line with what is generally required for studying urban and regional scale air quality. This will be demonstrated for a set of study sites that include the capitals of the four countries and the highly polluted areas along the border of Poland and the

  6. [Effectiveness of the maintenance operations on the air conditioning systems of a university building in relation to the microbiological quality of the air indoor].

    PubMed

    De Filippis, Patrizia; Spinaci, Anna; Coia, Maura; Maggi, Oriana; Panà, Augusto

    2003-01-01

    The microbiological quality of the air indoor is influenced from various factors and one of the most important is represented from the maintenance of the conditioning systems. In this study it has been estimated the effectiveness of an intervention of cleaning and maintenance on the systems of conditioning of an university building executing sampling before and after such intervention. The two results were confronted and it is observed as the maintenance of the air conditioners has influenced on the quality of the air indoor.

  7. NOAA's National Air Quality Predictions and Development of Aerosol and Atmospheric Composition Prediction Components for the Next Generation Global Prediction System

    NASA Astrophysics Data System (ADS)

    Stajner, I.; Hou, Y. T.; McQueen, J.; Lee, P.; Stein, A. F.; Tong, D.; Pan, L.; Huang, J.; Huang, H. C.; Upadhayay, S.

    2016-12-01

    NOAA provides operational air quality predictions using the National Air Quality Forecast Capability (NAQFC): ozone and wildfire smoke for the United States and airborne dust for the contiguous 48 states at http://airquality.weather.gov. NOAA's predictions of fine particulate matter (PM2.5) became publicly available in February 2016. Ozone and PM2.5 predictions are produced using a system that operationally links the Community Multiscale Air Quality (CMAQ) model with meteorological inputs from the North American mesoscale forecast Model (NAM). Smoke and dust predictions are provided using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Current NAQFC focus is on updating CMAQ to version 5.0.2, improving PM2.5 predictions, and updating emissions estimates, especially for NOx using recently observed trends. Wildfire smoke emissions from a newer version of the USFS BlueSky system are being included in a new configuration of the NAQFC NAM-CMAQ system, which is re-run for the previous 24 hours when the wildfires were observed from satellites, to better represent wildfire emissions prior to initiating predictions for the next 48 hours. In addition, NOAA is developing the Next Generation Global Prediction System (NGGPS) to represent the earth system for extended weather prediction. NGGPS will include a representation of atmospheric dynamics, physics, aerosols and atmospheric composition as well as coupling with ocean, wave, ice and land components. NGGPS is being developed with a broad community involvement, including community developed components and academic research to develop and test potential improvements for potentially inclusion in NGGPS. Several investigators at NOAA's research laboratories and in academia are working to improve the aerosol and gaseous chemistry representation for NGGPS, to develop and evaluate the representation of atmospheric composition, and to establish and improve the coupling with radiation and microphysics

  8. 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.

  9. 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.

  10. Windblown Dust and Air Quality Under a Changing Climate in the Pacific Northwest

    NASA Astrophysics Data System (ADS)

    Sharratt, B. S.; Tatarko, J.; Abatzoglou, J. T.; Fox, F.; Huggins, D. R.

    2016-12-01

    Wind erosion is a concern for sustainable agriculture and societal health in the US Pacific Northwest. Indeed, wind erosion continues to cause exceedances of the National Ambient Air Quality Standard for PM10 in the region. Can we expect air quality to deteriorate or improve as climate changes? Will wind erosion escalate in the future under a warmer and drier climate as forecast for Australia, southern prairies of Canada, northern China, and United States Corn Belt and Colorado Plateau? To answer these questions, we used 18 global climate models, cropping systems simulation model (CropSyst), and the Wind Erosion Prediction System (WEPS) to simulate the complex interactions among climate, crop production, and wind erosion. These simulations were carried out in eastern Washington where wind erosion of agricultural lands contribute to poor air quality in the region. Our results suggest that an increase in temperature and CO2 concentration, coupled with nominal increases in precipitation, will enhance biomass production and reduce soil and PM10 losses by the mid-21st century. This study reveals that climate change may reduce the risk of wind erosion and improve air quality in the Inland Pacific Northwest.

  11. Role of future scenarios in understanding deep uncertainty in long-term air quality management.

    PubMed

    Gamas, Julia; Dodder, Rebecca; Loughlin, Dan; Gage, Cynthia

    2015-11-01

    The environment and its interactions with human systems, whether economic, social, or political, are complex. Relevant drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions. This kind of "deep uncertainty" presents a challenge to organizations faced with making decisions about the future, including those involved in air quality management. Scenario Planning is a structured process that involves the development of narratives describing alternative future states of the world, designed to differ with respect to the most critical and uncertain drivers. The resulting scenarios are then used to understand the consequences of those futures and to prepare for them with robust management strategies. We demonstrate a novel air quality management application of Scenario Planning. Through a series of workshops, important air quality drivers were identified. The most critical and uncertain drivers were found to be "technological development" and "change in societal paradigms." These drivers were used as a basis to develop four distinct scenario storylines. The energy and emissions implications of each storyline were then modeled using the MARKAL energy system model. NOx emissions were found to decrease for all scenarios, largely a response to existing air quality regulations, whereas SO2 emissions ranged from 12% greater to 7% lower than 2015 emissions levels. Future-year emissions differed considerably from one scenario to another, however, with key differentiating factors being transition to cleaner fuels and energy demand reductions. Application of scenarios in air quality management provides a structured means of sifting through and understanding the dynamics of the many complex driving forces affecting future air quality. Further, scenarios provide a means to identify opportunities and challenges for future air quality management, as well as a platform for testing the efficacy and robustness of particular management

  12. 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.

  13. Estimating emissions from fires in North America for air quality modeling.

    Treesearch

    Christine Wiedinmyer; Brad Quayle; Chris Geron; Angie Belote; Don McKenzie; Xiaoyang Zhang; Susan O' Neill; Kristina Klos Wynne

    2006-01-01

    Fires contribute substantial emissions of trace gases and particles to the atmosphere. These emissions can impact air quality and even climate. We have developed a modeling framework to estimate the emissions from fires in North and parts of Central America (10-71 ˚N and 55-175 ˚W) by taking advantage of a combination of complementary satellite and...

  14. TESTS OF INDOOR AIR QUALITY SINKS

    EPA Science Inventory

    Experiments were conducted in a room-size test chamber to determine the sink effects of selected materials on indoor air concentrations of p-dichlorobenzene (PDCB). hese effects might alter pollutant behavior from that predicted using similar indoor air quality models, by reducin...

  15. 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.

  16. Evaluation of the Community Multiscale Air Quality (CMAQ) ...

    EPA Pesticide Factsheets

    The Community Multiscale Air Quality (CMAQ) 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 Computational Exposure Division (CED) of the U.S. Environmental Protection Agency develops the CMAQ model and periodically releases new versions of the model that include bug fixes and various other improvements to the modeling system. In the fall of 2016, CMAQ version 5.1.1 will be released. This new version of CMAQ will contain important bug fixes to several issues that were identified in CMAQv5.1 (the current public release version of the CMAQ model), and additionally include updates to other portions of the code. Some specific model updates include a new implementation of the wind-blown dust calculation in CMAQv5.1.1 which fixes several bugs that were identified in the current implementation of wind-blown dust in CMAQv5.1. Several other major updates to the model include an update to the calculation of aerosols; implementation of full halogen chemistry (CMAQv5.1 contains a partial implementation of halogen chemistry), which is particularly important for hemispheric applications of the CMAQ model, as halogen chemistry is need to accurately simulation the destruction of ozone over the ocean; and the new carbon bond 6 (CB6) chemical mechanism. Several annual, and numerous episodic, CMAQv5.1.1 simulations will be performed to assess the impact of these

  17. REGIONAL AIR POLLUTION STUDY, QUALITY ASSURANCE AUDITS

    EPA Science Inventory

    RAPS Quality Assurance audits were conducted under this Task Order in continuation of the audit program previously conducted under Task Order No. 58. Quantitative field audits were conducted of the Regional Air Monitoring System (RAMS) Air Monitoring Stations, Local Air Monitorin...

  18. 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...

  19. Air quality impacts of projections of natural gas-fired distributed generation

    NASA Astrophysics Data System (ADS)

    Horne, Jeremy R.; Carreras-Sospedra, Marc; Dabdub, Donald; Lemar, Paul; Nopmongcol, Uarporn; Shah, Tejas; Yarwood, Greg; Young, David; Shaw, Stephanie L.; Knipping, Eladio M.

    2017-11-01

    This study assesses the potential impacts on emissions and air quality from the increased adoption of natural gas-fired distributed generation of electricity (DG), including displacement of power from central power generation, in the contiguous United States. The study includes four major tasks: (1) modeling of distributed generation market penetration; (2) modeling of central power generation systems; (3) modeling of spatially and temporally resolved emissions; and (4) photochemical grid modeling to evaluate the potential air quality impacts of increased DG penetration, which includes both power-only DG and combined heat and power (CHP) units, for 2030. Low and high DG penetration scenarios estimate the largest penetration of future DG units in three regions - New England, New York, and California. Projections of DG penetration in the contiguous United States estimate 6.3 GW and 24 GW of market adoption in 2030 for the low DG penetration and high DG penetration scenarios, respectively. High DG penetration (all of which is natural gas-fired) serves to offset 8 GW of new natural gas combined cycle (NGCC) units, and 19 GW of solar photovoltaic (PV) installations by 2030. In all scenarios, air quality in the central United States and the northwest remains unaffected as there is little to no DG penetration in those states. California and several states in the northeast are the most impacted by emissions from DG units. Peak increases in maximum daily 8-h average ozone concentrations exceed 5 ppb, which may impede attainment of ambient air quality standards. Overall, air quality impacts from DG vary greatly based on meteorological conditions, proximity to emissions sources, the number and type of DG installations, and the emissions factors used for DG units.

  20. Updating Sea Spray Aerosol Emissions in the Community Multiscale Air Quality Model

    NASA Astrophysics Data System (ADS)

    Gantt, B.; Bash, J. O.; Kelly, J.

    2014-12-01

    Sea spray aerosols (SSA) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. In this study, the Community Multiscale Air Quality (CMAQ) model is updated to enhance fine mode SSA emissions, include sea surface temperature (SST) dependency, and revise surf zone emissions. Based on evaluation with several regional and national observational datasets in the continental U.S., the updated emissions generally improve surface concentrations predictions of primary aerosols composed of sea-salt and secondary aerosols affected by sea-salt chemistry in coastal and near-coastal sites. Specifically, the updated emissions lead to better predictions of the magnitude and coastal-to-inland gradient of sodium, chloride, and nitrate concentrations at Bay Regional Atmospheric Chemistry Experiment (BRACE) sites near Tampa, FL. Including SST-dependency to the SSA emission parameterization leads to increased sodium concentrations in the southeast U.S. and decreased concentrations along the Pacific coast and northeastern U.S., bringing predictions into closer agreement with observations at most Interagency Monitoring of Protected Visual Environments (IMPROVE) and Chemical Speciation Network (CSN) sites. Model comparison with California Research at the Nexus of Air Quality and Climate Change (CalNex) observations will also be discussed, with particular focus on the South Coast Air Basin where clean marine air mixes with anthropogenic pollution in a complex environment. These SSA emission updates enable more realistic simulation of chemical processes in coastal environments, both in clean marine air masses and mixtures of clean marine and polluted conditions.

  1. Assesment of longwave radiation effects on air quality modelling in street canyons

    NASA Astrophysics Data System (ADS)

    Soucasse, L.; Buchan, A.; Pain, C.

    2016-12-01

    Computational Fluid Dynamics is widely used as a predictive tool to evaluate people's exposure to pollutants in urban street canyons. However, in low-wind conditions, flow and pollutant dispersion in the canyons are driven by thermal effects and may be affected by longwave (infrared) radiation due to the absorption and emission of water vapor contained in the air. These effects are mostly ignored in the literature dedicated to air quality modelling at this scale. This study aims at quantifying the uncertainties due to neglecting thermal radiation in air quality models. The Large-Eddy-Simulation of air flow in a single 2D canyon with a heat source on the ground is considered for Rayleigh and Reynolds numbers in the range of [10e8-10e10] and [5.10e3-5.10e4] respectively. The dispersion of a tracer is monitored once the statistically steady regime is reached. Incoming radiation is computed for a mid-latitude summer atmosphere and canyon surfaces are assumed to be black. Water vapour is the only radiating molecule considered and a global model is used to treat the spectral dependancy of its absorption coefficient. Flow and radiation fields are solved in a coupled way using the finite element solvers Fluidity and Fetch which have the capability of adapting their space and angular resolution according to an estimate of the solution error. Results show significant effects of thermal radiation on flow patterns and tracer dispersion. When radiation is taken into account, the air is heated far from the heat source leading to a stronger natural convection flow. The tracer is then dispersed faster out of the canyon potentially decreasing people's exposure to pollution within the street canyon.

  2. 40 CFR 52.13 - Air quality surveillance; resources; intergovernmental cooperation.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Air quality surveillance; resources... § 52.13 Air quality surveillance; resources; intergovernmental cooperation. Disapproved portions of the plan related to the air quality surveillance system, resources, and intergovernmental cooperation are...

  3. 40 CFR 52.13 - Air quality surveillance; resources; intergovernmental cooperation.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 3 2012-07-01 2012-07-01 false Air quality surveillance; resources... § 52.13 Air quality surveillance; resources; intergovernmental cooperation. Disapproved portions of the plan related to the air quality surveillance system, resources, and intergovernmental cooperation are...

  4. 40 CFR 52.13 - Air quality surveillance; resources; intergovernmental cooperation.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 3 2013-07-01 2013-07-01 false Air quality surveillance; resources... § 52.13 Air quality surveillance; resources; intergovernmental cooperation. Disapproved portions of the plan related to the air quality surveillance system, resources, and intergovernmental cooperation are...

  5. 40 CFR 52.13 - Air quality surveillance; resources; intergovernmental cooperation.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 3 2014-07-01 2014-07-01 false Air quality surveillance; resources... § 52.13 Air quality surveillance; resources; intergovernmental cooperation. Disapproved portions of the plan related to the air quality surveillance system, resources, and intergovernmental cooperation are...

  6. 40 CFR 52.13 - Air quality surveillance; resources; intergovernmental cooperation.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Air quality surveillance; resources... § 52.13 Air quality surveillance; resources; intergovernmental cooperation. Disapproved portions of the plan related to the air quality surveillance system, resources, and intergovernmental cooperation are...

  7. Air quality impacts of distributed power generation in the South Coast Air Basin of California 1: Scenario development and modeling analysis

    NASA Astrophysics Data System (ADS)

    Rodriguez, M. A.; Carreras-Sospedra, M.; Medrano, M.; Brouwer, J.; Samuelsen, G. S.; Dabdub, D.

    Distributed generation (DG) is generally defined as the operation of many small stationary power generators throughout an urban air basin. Although DG has the potential to supply a significant portion of the increased power demands in California and the rest of the United States, it may lead to increased levels of in-basin pollutants and adversely impact urban air quality. This study focuses on two main objectives: (1) the systematic characterization of DG installation in urban air basins, and (2) the simulation of potential air quality impacts using a state-of-the-art three-dimensional computational model. A general and systematic approach is devised to construct five realistic and 21 spanning scenarios of DG implementation in the South Coast Air Basin (SoCAB) of California. Realistic scenarios reflect an anticipated level of DG deployment in the SoCAB by the year 2010. Spanning scenarios are developed to determine the potential impacts of unexpected outcomes. Realistic implementations of DG in the SoCAB result in small differences in ozone and particulate matter concentrations in the basin compared to the baseline simulations. The baseline accounts for population increase, but does not consider any future emissions control measures. Model results for spanning implementations with extra high DG market penetration show that domain-wide ozone peak concentrations increase significantly. Also, air quality impacts of spanning implementations when DG operate during a 6-h period are larger than when the same amount of emissions are introduced during a 24-h period.

  8. 78 FR 53270 - Revision of Air Quality Implementation Plan; California; Sacramento Metropolitan Air Quality...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-08-29

    ... Quality Implementation Plan; California; Sacramento Metropolitan Air Quality Management District... to the Sacramento Metropolitan Air Quality Management District (SMAQMD or District) portion of the..., Sacramento Metropolitan Air Quality Management District, Rule 214 (Federal New Source Review), Rule 203...

  9. Regional photochemical air quality modeling in the Mexico-US border area

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mendoza, A.; Russell, A.G.; Mejia, G.M.

    1998-12-31

    The Mexico-United States border area has become an increasingly important region due to its commercial, industrial and urban growth. As a result, environmental concerns have risen. Treaties like the North American Free Trade Agreement (NAFTA) have further motivated the development of environmental impact assessment in the area. Of particular concern are air quality, and how the activities on both sides of the border contribute to its degradation. This paper presents results of applying a three-dimensional photochemical airshed model to study air pollution dynamics along the Mexico-United States border. In addition, studies were conducted to assess how size resolution impacts themore » model performance. The model performed within acceptable statistic limits using 12.5 x 12.5 km{sup 2} grid cells, and the benefits using finer grids were limited. Results were further used to assess the influence of grid-cell size on the modeling of control strategies, where coarser grids lead to significant loss of information.« less

  10. Biodiversity, air quality and human health

    Treesearch

    David J. Nowak; Sarah Jovan; Christina Branquinho; Sofia Augusto; Manuel C. Ribeiro; Conor E. Kretsch

    2015-01-01

    Air pollution is a significant problem in cities across the world. It affects human health and well-being, ecosystem health, crops, climate, visibility and human-made materials. Health effects related to air pollution include its impact on the pulmonary, cardiac, vascular and neurological systems (Section 2). Trees affect air quality through a number of means (Section...

  11. MODELING AIR TOXICS AND PM 2.5 CONCENTRATION FIELDS AS A MEANS FOR FACILITATING HUMAN EXPOSURE ASSESSMENTS

    EPA Science Inventory

    The capability of the US EPA Models-3/Community Multiscale Air Quality (CMAQ) modeling system is extended to provide gridded ambient air quality concentration fields at fine scales. These fields will drive human exposure to air toxics and fine particulate matter (PM2.5) models...

  12. A proof-of-concept for linking the global meteorological model, MPAS-A with the air quality model, CMAQ

    EPA Science Inventory

    Researchers who perform air quality modeling studies usually do so on a regional scale. Typically, the boundary conditions are generated by another model which might have a different chemical mechanism, spatial resolution, and/or map projection. Hence, a necessary conversion/inte...

  13. Local Air Quality Conditions and Forecasts

    MedlinePlus

    ... Monitor Location Archived Maps by Region Canada Air Quality Air Quality on Google Earth Links A-Z About AirNow AirNow International Air Quality Action Days / Alerts AirCompare Air Quality Index (AQI) ...

  14. 78 FR 30770 - Approval and Promulgation of Air Quality Implementation Plans; Illinois; Air Quality Standards...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-05-23

    ... Promulgation of Air Quality Implementation Plans; Illinois; Air Quality Standards Revision AGENCY... Illinois state implementation plan (SIP) to reflect current National Ambient Air Quality Standards (NAAQS... Implementation Plan at 35 Illinois Administrative Code part 243, which updates National Ambient Air Quality...

  15. Identifying pollution sources and predicting urban air quality using ensemble learning methods

    NASA Astrophysics Data System (ADS)

    Singh, Kunwar P.; Gupta, Shikha; Rai, Premanjali

    2013-12-01

    In this study, principal components analysis (PCA) was performed to identify air pollution sources and tree based ensemble learning models were constructed to predict the urban air quality of Lucknow (India) using the air quality and meteorological databases pertaining to a period of five years. PCA identified vehicular emissions and fuel combustion as major air pollution sources. The air quality indices revealed the air quality unhealthy during the summer and winter. Ensemble models were constructed to discriminate between the seasonal air qualities, factors responsible for discrimination, and to predict the air quality indices. Accordingly, single decision tree (SDT), decision tree forest (DTF), and decision treeboost (DTB) were constructed and their generalization and predictive performance was evaluated in terms of several statistical parameters and compared with conventional machine learning benchmark, support vector machines (SVM). The DT and SVM models discriminated the seasonal air quality rendering misclassification rate (MR) of 8.32% (SDT); 4.12% (DTF); 5.62% (DTB), and 6.18% (SVM), respectively in complete data. The AQI and CAQI regression models yielded a correlation between measured and predicted values and root mean squared error of 0.901, 6.67 and 0.825, 9.45 (SDT); 0.951, 4.85 and 0.922, 6.56 (DTF); 0.959, 4.38 and 0.929, 6.30 (DTB); 0.890, 7.00 and 0.836, 9.16 (SVR) in complete data. The DTF and DTB models outperformed the SVM both in classification and regression which could be attributed to the incorporation of the bagging and boosting algorithms in these models. The proposed ensemble models successfully predicted the urban ambient air quality and can be used as effective tools for its management.

  16. Analysis of air quality management with emphasis on transportation sources

    NASA Technical Reports Server (NTRS)

    English, T. D.; Divita, E.; Lees, L.

    1980-01-01

    The current environment and practices of air quality management were examined for three regions: Denver, Phoenix, and the South Coast Air Basin of California. These regions were chosen because the majority of their air pollution emissions are related to mobile sources. The impact of auto exhaust on the air quality management process is characterized and assessed. An examination of the uncertainties in air pollutant measurements, emission inventories, meteorological parameters, atmospheric chemistry, and air quality simulation models is performed. The implications of these uncertainties to current air quality management practices is discussed. A set of corrective actions are recommended to reduce these uncertainties.

  17. Speed estimation for air quality analysis.

    DOT National Transportation Integrated Search

    2005-05-01

    Average speed is an essential input to the air quality analysis model MOBILE6 for emission factor calculation. Traditionally, speed is obtained from travel demand models. However, such models are not usually calibrated to speeds. Furthermore, for rur...

  18. 78 FR 10589 - Revision of Air Quality Implementation Plan; California; Sacramento Metropolitan Air Quality...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-14

    ... Quality Implementation Plan; California; Sacramento Metropolitan Air Quality Management District... Sacramento Metropolitan Air Quality Management District (SMAQMD or District) portion of the California State... sources within the areas covered by the plan as necessary to assure that the National Ambient Air Quality...

  19. Potential impact of a US climate policy and air quality regulations on future air quality and climate change

    NASA Astrophysics Data System (ADS)

    Lee, Yunha; Shindell, Drew T.; Faluvegi, Greg; Pinder, Rob W.

    2016-04-01

    We have investigated how future air quality and climate change are influenced by the US air quality regulations that existed or were proposed in 2013 and a hypothetical climate mitigation policy that aims to reduce 2050 CO2 emissions to be 50 % below 2005 emissions. Using the NASA GISS ModelE2 general circulation model, we look at the impacts for year 2030 and 2055. The US energy-sector emissions are from the GLIMPSE project (GEOS-Chem LIDORT Integrated with MARKAL (MARKet ALlocation) for the Purpose of Scenario Exploration), and other US emissions data sets and the rest of the world emissions data sets are based on the RCP4.5 scenario. The US air quality regulations are projected to have a strong beneficial impact on US air quality and public health in year 2030 and 2055 but result in positive radiative forcing. Under this scenario, no more emission constraints are added after 2020, and the impacts on air quality and climate change are similar between year 2030 and 2055. Surface particulate matter with a diameter smaller than 2.5 µm (PM2.5) is reduced by ˜ 2 µg m-3 on average over the USA, and surface ozone by ˜ 8 ppbv. The improved air quality prevents about 91 400 premature deaths in the USA, mainly due to the PM2.5 reduction (˜ 74 200 lives saved). The air quality regulations reduce the light-reflecting aerosols (i.e., sulfate and organic matter) more than the light-absorbing species (i.e., black carbon and ozone), leading to a strong positive radiative forcing (RF) over the USA by both aerosols' direct and indirect forcing: the total RF is ˜ 0.04 W m-2 over the globe, and ˜ 0.8 W m-2 over the USA. Under the hypothetical climate policy, a future CO2 emissions cut is achieved in part by relying less on coal, and thus SO2 emissions are noticeably reduced. This provides air quality co-benefits, but it could lead to potential climate disbenefits over the USA. In 2055, the US mean total RF is +0.22 W m-2 due to positive aerosol direct and indirect forcing

  20. Potential Impact of a US Climate Policy and Air Quality Regulations on Future Air Quality and Climate Change

    NASA Technical Reports Server (NTRS)

    Lee, Y. H.; Faluvegi, Gregory S.

    2016-01-01

    We have investigated how future air quality and climate change are influenced by the US air quality regulations that existed or were proposed in 2013 and a hypothetical climate mitigation policy that aims to reduce 2050 CO2 emissions to be 50% below 2005 emissions. Using the NASA GISS ModelE2 general circulation model, we look at the impacts for year 2030 and 2055. The US energy-sector emissions are from the GLIMPSE project (GEOS-Chem LIDORT Integrated with MARKAL (MARKet ALlocation) for the Purpose of Scenario Exploration), and other US emissions data sets and the rest of the world emissions data sets are based on the RCP4.5 scenario. The US air quality regulations are projected to have a strong beneficial impact on US air quality and public health in year 2030 and 2055 but result in positive radiative forcing. Under this scenario, no more emission constraints are added after 2020, and the impacts on air quality and climate change are similar between year 2030 and 2055. Surface particulate matter with a diameter smaller than 2.5 micron PM(sub 2:5) is reduced by 2 approximately µg/m(sup -3) on average over the USA, and surface ozone by approximately 8 ppbv. The improved air quality prevents about 91 400 premature deaths in the USA, mainly due to the PM(sub 2:5) reduction approximately (74 200 lives saved). The air quality regulations reduce the light-reflecting aerosols (i.e., sulfate and organic matter) more than the light-absorbing species (i.e., black carbon and ozone), leading to a strong positive radiative forcing (RF) over the USA by both aerosols' direct and indirect forcing: the total RF is approximately 0.04 W m(sup -2) over the globe, and approximately 0.8 W m(sup -2) over the USA. Under the hypothetical climate policy, a future CO2 emissions cut is achieved in part by relying less on coal, and thus SO2 emissions are noticeably reduced. This provides air quality co-benefits, but it could lead to potential climate disbenefits over the USA. In 2055, the US

  1. APPLICATION OF FINE SCALE AIR TOXICS MODELING WITH CMAQ TO HAPEM5

    EPA Science Inventory

    This paper provides a preliminary demonstration of the EPA neighborhood scale modeling paradigm for air toxics by linking concentration from the Community Multiscale Air Quality (CMAQ) modeling system to the fifth version of the Hazardous Pollutant Exposure Model (HAPEM5). For t...

  2. Aerosols in the CALIOPE air quality modelling system: validation and analysis of PM levels, optical depths and chemical composition over Europe

    NASA Astrophysics Data System (ADS)

    Basart, S.; Pay, M. T.; Jorba, O.; Pérez, C.; Jiménez-Guerrero, P.; Schulz, M.; Baldasano, J. M.

    2011-07-01

    The CALIOPE high-resolution air quality modelling system is developed and applied to Europe (12 km × 12 km, 1 h). The modelled daily to seasonal aerosol variability over Europe in 2004 have been evaluated and analysed. The aerosols are estimated from two models, CMAQv4.5 (AERO4) and BSC-DREAM8b. CMAQv4.5 calculates biogenic, anthropogenic and sea salt aerosol and BSC-DREAM8b provides the natural mineral dust contribution from North African deserts. For the evaluation, we use daily PM10/PM2.5 and chemical composition data from 54 stations of the EMEP/CREATE network and coarse and fine aerosol optical depth (AOD) data from 35 stations of the AERONET sun photometer network. The model achieves daily PM10 and PM2.5 correlations of 0.57 and 0.47, respectively, and total, coarse and fine AOD correlations of 0.51, 0.63, and 0.53, respectively. The higher correlations of the PM10 and the coarse mode AOD are largely due to the accurate representation of the African dust influence in the forecasting system. Overall PM and AOD levels are underestimated. The evaluation of the chemical composition highlights underestimations of the modelled fine fractions particularly for carbonaceous matter (EC and OC) and secondary inorganic aerosols (SIA; i.e. nitrates, sulphates and ammonium). The scores of the bulk parameters are significantly improved after applying a simple model bias correction based on the chemical composition observations. SIA are dominant in the fine fractions representing up to 80 % of the aerosol budget in latitudes beyond 40° N. The highest aerosol concentrations are found over the industrialized and populated areas of the Po Valley and the Benelux regions. High values in southern Europe are linked to the transport of coarse particles from the Sahara desert which contributes up to 40 % of the total aerosol mass. Close to the surface, maxima dust seasonal concentrations (>30 μg m-3) are found between spring and early autumn. We estimate that desert dust causes

  3. 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...

  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. 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...

  6. The Copernicus Atmosphere Monitoring Service: facilitating the prediction of air quality from global to local scales

    NASA Astrophysics Data System (ADS)

    Engelen, R. J.; Peuch, V. H.

    2017-12-01

    The European Copernicus Atmosphere Monitoring Service (CAMS) operationally provides daily forecasts of global atmospheric composition and regional air quality. The global forecasting system is using ECMWF's Integrated Forecasting System (IFS), which is used for numerical weather prediction and which has been extended with modules for atmospheric chemistry, aerosols and greenhouse gases. The regional forecasts are produced by an ensemble of seven operational European air quality models that take their boundary conditions from the global system and provide an ensemble median with ensemble spread as their main output. Both the global and regional forecasting systems are feeding their output into air quality models on a variety of scales in various parts of the world. We will introduce the CAMS service chain and provide illustrations of its use in downstream applications. Both the usage of the daily forecasts and the usage of global and regional reanalyses will be addressed.

  7. Air Pollution Monitoring | Air Quality Planning & Standards ...

    EPA Pesticide Factsheets

    2016-06-08

    The basic mission of the Office of Air Quality Planning and Standards is to preserve and improve the quality of our nation's air. To accomplish this, OAQPS must be able to evaluate the status of the atmosphere as compared to clean air standards and historical information.

  8. 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.

  9. Mapping air quality zones for coastal urban centers.

    PubMed

    Freeman, Brian; Gharabaghi, Bahram; Thé, Jesse; Munshed, Mohammad; Faisal, Shah; Abdullah, Meshal; Al Aseed, Athari

    2017-05-01

    This study presents a new method that incorporates modern air dispersion models allowing local terrain and land-sea breeze effects to be considered along with political and natural boundaries for more accurate mapping of air quality zones (AQZs) for coastal urban centers. This method uses local coastal wind patterns and key urban air pollution sources in each zone to more accurately calculate air pollutant concentration statistics. The new approach distributes virtual air pollution sources within each small grid cell of an area of interest and analyzes a puff dispersion model for a full year's worth of 1-hr prognostic weather data. The difference of wind patterns in coastal and inland areas creates significantly different skewness (S) and kurtosis (K) statistics for the annually averaged pollutant concentrations at ground level receptor points for each grid cell. Plotting the S-K data highlights grouping of sources predominantly impacted by coastal winds versus inland winds. The application of the new method is demonstrated through a case study for the nation of Kuwait by developing new AQZs to support local air management programs. The zone boundaries established by the S-K method were validated by comparing MM5 and WRF prognostic meteorological weather data used in the air dispersion modeling, a support vector machine classifier was trained to compare results with the graphical classification method, and final zones were compared with data collected from Earth observation satellites to confirm locations of high-exposure-risk areas. The resulting AQZs are more accurate and support efficient management strategies for air quality compliance targets effected by local coastal microclimates. A novel method to determine air quality zones in coastal urban areas is introduced using skewness (S) and kurtosis (K) statistics calculated from grid concentrations results of air dispersion models. The method identifies land-sea breeze effects that can be used to manage local air

  10. Linking Global and Regional Models to Simulate U.S. Air Quality in the Year 2050

    EPA Science Inventory

    The potential impact of global climate change on future air quality in the United States is investigated with global and regional-scale models. Regional climate model scenarios are developed by dynamically downscaling the outputs from a global chemistry and climate model and are...

  11. Advances in air quality prediction with the use of integrated systems

    NASA Astrophysics Data System (ADS)

    Dragani, R.; Benedetti, A.; Engelen, R. J.; Peuch, V. H.

    2017-12-01

    Recent years have seen the rise of global operational atmospheric composition forecasting systems for several applications including climate monitoring, provision of boundary conditions for regional air quality forecasting, energy sector applications, to mention a few. Typically, global forecasts are provided in the medium-range up to five days ahead and are initialized with an analysis based on satellite data. In this work we present the latest advances in data assimilation using the ECMWF's 4D-Var system extended to atmospheric composition which is currently operational under the Copernicus Atmosphere Monitoring Service of the European Commission. The service is based on acquisition of all relevant data available in near-real-time, the processing of these datasets in the assimilation and the subsequent dissemination of global forecasts at ECMWF. The global forecasts are used by the CAMS regional models as boundary conditions for the European forecasts based on a multi-model ensemble. The global forecasts are also used to provide boundary conditions for other parts of the world (e.g., China) and are freely available to all interested entities. Some of the regional models also perform assimilation of satellite and ground-based observations. All products are assessed, validated and made publicly available on https://atmosphere.copernicus.eu/.

  12. Ventilation System Effectiveness and Tested Indoor Air Quality Impacts

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rudd, Armin; Bergey, Daniel

    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, themore » 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.« less

  13. Effects of building roof greening on air quality in street canyons

    NASA Astrophysics Data System (ADS)

    Baik, Jong-Jin; Kwak, Kyung-Hwan; Park, Seung-Bu; Ryu, Young-Hee

    2012-12-01

    Building roof greening is a successful strategy for improving urban thermal environment. It is of theoretical interest and practical importance to study the effects of building roof greening on urban air quality in a systematic and quantitative way. In this study, we examine the effects of building roof greening on air quality in street canyons using a computational fluid dynamics (CFD) model that includes the thermodynamic energy equation and the transport equation of passive, non-reactive pollutants. For simplicity, building roof greening is represented by specified cooling. Results for a simple building configuration with a street canyon aspect ratio of one show that the cool air produced due to building roof greening flows into the street canyon, giving rise to strengthened street canyon flow. The strengthened street canyon flow enhances pollutant dispersion near the road, which decreases pollutant concentration there. Thus, building roof greening improves air quality near the road. The degree of air quality improvement near the road increases as the cooling intensity increases. In the middle region of the street canyon, the air quality can worsen when the cooling intensity is not too strong. Results for a real urban morphology also show that building roof greening improves air quality near roads. The degree of air quality improvement near roads due to building roof greening depends on the ambient wind direction. These findings provide a theoretical foundation for constructing green roofs for the purpose of improving air quality near roads or at a pedestrian level as well as urban thermal environment. Further studies using a CFD model coupled with a photochemistry model and a surface energy balance model are required to evaluate the effects of building roof greening on air quality in street canyons in a more realistic framework.

  14. Modeling the Dynamic Change of Air Quality and its Response to Emission Trends

    NASA Astrophysics Data System (ADS)

    Zhou, Wei

    This thesis focuses on evaluating atmospheric chemistry and transport models' capability in simulating the chemistry and dynamics of power plant plumes, evaluating their strengths and weaknesses in predicting air quality trends at regional scales, and exploring air quality trends in an urban area. First, the Community Mutlti-scale Air Quality (CMAQ) model is applied to simulate the physical and chemical evolution of power plant plumes (PPPs) during the second Texas Air Quality Study (TexAQS) in 2006. SO2 and NOy were observed to be rapidly removed from PPPs on cloudy days but not on cloud-free days, indicating efficient aqueous processing of these compounds in clouds, while the model fails to capture the rapid loss of SO2 and NOy in some plumes on the cloudy day. Adjustments to cloud liquid water content (QC) and the default metal concentrations in the cloud module could explain some of the SO 2 loss while NOy in the model was insensitive to QC. Second, CMAQ is applied to simulate the ozone (O3) change after the NO x SIP Call and mobile emission controls in the eastern U.S. from 2002 to 2006. Observed downward changes in 8-hour O3 concentrations in the NOx SIP Call region were under-predicted by 26%--66%. The under-prediction in O3 improvements could be alleviated by 5%--31% by constraining NOx emissions in each year based on observed NOx concentrations while temperature biases or uncertainties in chemical reactions had minor impact on simulated O3 trends. Third, changes in ozone production in the Houston area is assessed with airborne measurements from TexAQS 2000 and 2006. Simultaneous declines in nitrogen oxides (NOx=NO+NO2) and highly reactive Volatile Organic Compounds (HRVOCs) were observed in the Houston Ship Channel (HSC). The reduction in HRVOCs led to the decline in total radical concentration by 20-50%. Rapid ozone production rates in the Houston area declined by 40-50% from 2000 to 2006, to which the reduction in NOx and HRVOCs had the similar

  15. A Multiplatform Observations of Air Quality in Korea as the Pre-campaign of Korea and US Air Quality (KORUS-AQ) Study.

    NASA Astrophysics Data System (ADS)

    Park, J. H.; Hong, J.; Hong, Y.; Song, C. K.; Kim, S. K.; Chang, L. S.; Lim, J.; Ahn, J.; Kim, J. Y.; Han, Y. J.; Kim, J.; Park, R.; Lee, G.; Park, J.

    2015-12-01

    Despite the Korea government's efforts to regulate air pollutant emission for attaining the national air quality standard, current serious dust events and high ozone episodes in summer time remain important societal issues in Korea. In order to make effective policy for air quality attainment, it is contingent upon a thorough understanding of chemical production/loss mechanism of air pollutants and their precursors which drive air quality such as nitrogen oxides (NOX), volatile organic compounds (VOCs), and oxidants (e.g. OH, HO2, RO, RO2, etc.). At present, policy development is constrained by a lack of data for broad suite of chemical species which significantly affect on air quality.During 4 weeks between May and June 2013, the pre-campaign for the Korea and U.S. Air Quality (KORUS-AQ) study took place in multiplatform including fifteen ground sites, one mobile laboratory, and one small air crafts. An integrated research activity covering field observations, chemical transport models, and remote sensing has been intensively conducted. This study was focused on studying photochemistry and nighttime chemistry in urban area and transboundary transport of air pollutants from upwind. Scientific overview and outcomes from the campaign will be presented.

  16. Phase I Recommendations by the Air Quality Management Work Group to the Clean Air Act Advisory Committee

    EPA Pesticide Factsheets

    Recommendations to the Clean Air Act Advisory Committee by Air Quality Management Work Group addressing the recommendations made by the National Research Council to improve the U.S. air quality management system.

  17. Modeling crop residue burning experiments and assessing the fire impacts on air quality

    EPA Science Inventory

    Prescribed burning is a common land management practice that results in ambient emissions of a variety of primary and secondary pollutants with negative health impacts. The community Multiscale Air Quality (CMAQ) model is used to conduct 2 km grid resolution simulations of prescr...

  18. Synchronic interval Gaussian mixed-integer programming for air quality management.

    PubMed

    Cheng, Guanhui; Huang, Guohe Gordon; Dong, Cong

    2015-12-15

    To reveal the synchronism of interval uncertainties, the tradeoff between system optimality and security, the discreteness of facility-expansion options, the uncertainty of pollutant dispersion processes, and the seasonality of wind features in air quality management (AQM) systems, a synchronic interval Gaussian mixed-integer programming (SIGMIP) approach is proposed in this study. A robust interval Gaussian dispersion model is developed for approaching the pollutant dispersion process under interval uncertainties and seasonal variations. The reflection of synchronic effects of interval uncertainties in the programming objective is enabled through introducing interval functions. The proposition of constraint violation degrees helps quantify the tradeoff between system optimality and constraint violation under interval uncertainties. The overall optimality of system profits of an SIGMIP model is achieved based on the definition of an integrally optimal solution. Integer variables in the SIGMIP model are resolved by the existing cutting-plane method. Combining these efforts leads to an effective algorithm for the SIGMIP model. An application to an AQM problem in a region in Shandong Province, China, reveals that the proposed SIGMIP model can facilitate identifying the desired scheme for AQM. The enhancement of the robustness of optimization exercises may be helpful for increasing the reliability of suggested schemes for AQM under these complexities. The interrelated tradeoffs among control measures, emission sources, flow processes, receptors, influencing factors, and economic and environmental goals are effectively balanced. Interests of many stakeholders are reasonably coordinated. The harmony between economic development and air quality control is enabled. Results also indicate that the constraint violation degree is effective at reflecting the compromise relationship between constraint-violation risks and system optimality under interval uncertainties. This can

  19. 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)

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    McMillan, W. W.; Pierce, R.; Sparling, L. C.

    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 presentmore » 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.« less

  20. 78 FR 63934 - Approval of Air Quality Implementation Plans; California; El Dorado County Air Quality Management...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-25

    ...] Approval of Air Quality Implementation Plans; California; El Dorado County Air Quality Management District... California for the El Dorado County Air Quality Management District (EDAQMD) portion of the California SIP... 24, 1987 Federal Register, May 25, 1988, U.S. EPA, Air Quality Management Division, Office of Air...

  1. Air quality management in Mexico.

    PubMed

    Fernández-Bremauntz, Adrián

    2008-01-01

    Several significant program and policy measures have been implemented in Mexico over the past 15 yr to improve air quality. This article provides an overview of air quality management strategies in Mexico, including (1) policy initiatives such as vehicle use restrictions, air quality standards, vehicle emissions, and fuel quality standards, and (2) supporting programs including establishment of a national emission inventory, an air pollution episodes program, and the implementation of exposure and health effects studies. Trends in air pollution episodes and ambient air pollutant concentrations are described.

  2. Ventilation System Effectiveness and Tested Indoor Air Quality Impacts

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rudd, Armin; Bergey, Daniel

    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 sourcemore » 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.« less

  3. Application of Satellite and Ozonesonde Data to the Study of Nighttime Tropospheric Ozone Impacts and Relationship to Air Quality

    NASA Astrophysics Data System (ADS)

    Osterman, G. B.; Eldering, A.; Neu, J. L.; Tang, Y.; McQueen, J.; Pinder, R. W.

    2011-12-01

    To help protect human health and ecosystems, regional-scale atmospheric chemistry models are used to forecast high ozone events and to design emission control strategies to decrease the frequency and severity of ozone events. Despite the impact that nighttime aloft ozone can have on surface ozone, regional-scale atmospheric chemistry models often do not simulate the nighttime ozone concentrations well and nor do they sufficiently capture the ozone transport patterns. Fully characterizing the importance of the nighttime ozone has been hampered by limited measurements of the vertical distribution of ozone and ozone-precursors. The main focus of this work is to begin to utilize remote sensing data sets to characterize the impact of nighttime aloft ozone to air quality events. We will describe our plans to use NASA satellite data sets, transport models and air quality models to study ozone transport, focusing primarily on nighttime ozone and provide initial results. We will use satellite and ozonesonde data to help understand how well the air quality models are simulating ozone in the lower free troposphere and attempt to characterize the impact of nighttime ozone to air quality events. Our specific objectives are: 1) Characterize nighttime aloft ozone using remote sensing data and sondes. 2) Evaluate the ability of the Community Multi-scale Air Quality (CMAQ) model and the National Air Quality Forecast Capability (NAQFC) model to capture the nighttime aloft ozone and its relationship to air quality events. 3) Analyze a set of air quality events and determine the relationship of air quality events to the nighttime aloft ozone. We will achieve our objectives by utilizing the ozone profile data from the NASA Earth Observing System (EOS) Tropospheric Emission Spectrometer (TES) and other sensors, ozonesonde data collected during the Aura mission (IONS), EPA AirNow ground station ozone data, the CMAQ continental-scale air quality model, and the National Air Quality

  4. CityAir app: Mapping air-quality perception using people as sensors

    NASA Astrophysics Data System (ADS)

    Castell, Nuria; Fredriksen, Mirjam; Cole-Hunter, Thomas; Robinson, Johanna; Keune, Hans; Nieuwenhuijsen, Mark; Bartonova, Alena

    2016-04-01

    Outdoor air pollution is a major environmental health problem affecting all people in developed and developing countries alike. Ambient (outdoor) air pollution in both cities and rural areas was estimated to cause 3.7 million premature deaths worldwide in 2012. In modern society, people are expending an increasing amount of time in polluted urban environments, thus increasing their exposure and associated health responses. Some cities provide information about air pollution levels to their citizens using air quality monitoring networks. However, due to their high cost and maintenance, the density of the monitoring networks is very low and not capable to capture the high temporal and spatial variability of air pollution. Thus, the citizen lacks a specific answer to the question of "how the air quality is in our surroundings". In the framework of the EU-funded CITI-SENSE project the innovative concept of People as Sensors is being applied to the field of outdoor air pollution. This is being done in eight European cities, including Barcelona, Belgrade, Edinburgh, Haifa, Ljubljana, Oslo, Ostrava and Vienna. People as Sensors defines a measurement model, in which measurements are not only taken by hardware sensors, but in which also humans can contribute with their individual "measurements" such as their subjective perception of air quality and other personal observations. In order to collect the personal observations a mobile app, CityAir, has been developed. CityAir allows citizens to rate the air quality in their surroundings with colour at their current location: green if air quality is very good, yellow if air quality is good, orange if air quality is poor and red if air quality is very poor. The users have also the possibility of indicating the source of pollution (i.e. traffic, industry, wood burning) and writing a comment. The information is on-line and accessible for other app users, thus contributing to create an air-quality map based on citizens' perception

  5. Development of indoor environmental index: Air quality index and thermal comfort index

    NASA Astrophysics Data System (ADS)

    Saad, S. M.; Shakaff, A. Y. M.; Saad, A. R. M.; Yusof, A. M.; Andrew, A. M.; Zakaria, A.; Adom, A. H.

    2017-03-01

    In this paper, index for indoor air quality (also known as IAQI) and thermal comfort index (TCI) have been developed. The IAQI was actually modified from previous outdoor air quality index (AQI) designed by the United States Environmental Protection Agency (US EPA). In order to measure the index, a real-time monitoring system to monitor indoor air quality level was developed. The proposed system consists of three parts: sensor module cloud, base station and service-oriented client. The sensor module cloud (SMC) contains collections of sensor modules that measures the air quality data and transmit the captured data to base station through wireless. Each sensor modules includes an integrated sensor array that can measure indoor air parameters like Carbon Dioxide, Carbon Monoxide, Ozone, Nitrogen Dioxide, Oxygen, Volatile Organic Compound and Particulate Matter. Temperature and humidity were also being measured in order to determine comfort condition in indoor environment. The result from several experiments show that the system is able to measure the air quality presented in IAQI and TCI in many indoor environment settings like air-conditioner, chemical present and cigarette smoke that may impact the air quality. It also shows that the air quality are changing dramatically, thus real-time monitoring system is essential.

  6. 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. Copyright © 2015

  7. Aerosols in the CALIOPE air quality modelling system: evaluation and analysis of PM levels, optical depths and chemical composition over Europe

    NASA Astrophysics Data System (ADS)

    Basart, S.; Pay, M. T.; Jorba, O.; Pérez, C.; Jiménez-Guerrero, P.; Schulz, M.; Baldasano, J. M.

    2012-04-01

    The CALIOPE air quality modelling system is developed and applied to Europe with high spatial resolution (12 km × 12 km). The modelled daily-to-seasonal aerosol variability over Europe in 2004 is evaluated and analysed. Aerosols are estimated from two models, CMAQv4.5 (AERO4) and BSC-DREAM8b. CMAQv4.5 calculates biogenic, anthropogenic and sea salt aerosol and BSC-DREAM8b provides the natural mineral dust contribution from North African deserts. For the evaluation, we use daily PM10, PM2.5 and aerosol components data from 55 stations of the EMEP/CREATE network and total, coarse and fine aerosol optical depth (AOD) data from 35 stations of the AERONET sun photometer network. Annual correlations between modelled and observed values for PM10 and PM2.5 are 0.55 and 0.47, respectively. Correlations for total, coarse and fine AOD are 0.51, 0.63, and 0.53, respectively. The higher correlations of the PM10 and the coarse mode AOD are largely due to the accurate representation of the African dust influence in the forecasting system. Overall PM and AOD levels are underestimated. The evaluation of the aerosol components highlights underestimations in the fine fraction of carbonaceous matter (EC and OC) and secondary inorganic aerosols (SIA; i.e. nitrate, sulphate and ammonium). The scores of the bulk parameters are significantly improved after applying a simple model bias correction based on the observed aerosol composition. The simulated PM10 and AOD present maximum values over the industrialized and populated Po Valley and Benelux regions. SIA are dominant in the fine fraction representing up to 80% of the aerosol budget in latitudes north of 40° N. In southern Europe, high PM10 and AOD are linked to the desert dust transport from the Sahara which contributes up to 40% of the aerosol budget. Maximum seasonal ground-level concentrations (PM10 > 30 μg m-3) are found between spring and early autumn. We estimate that desert dust causes daily exceedances of the PM10 European

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    NONE

    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 thismore » 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.« less

  9. A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring

    NASA Astrophysics Data System (ADS)

    Zimmerman, Naomi; Presto, Albert A.; Kumar, Sriniwasa P. N.; Gu, Jason; Hauryliuk, Aliaksei; Robinson, Ellis S.; Robinson, Allen L.; Subramanian, R.

    2018-01-01

    Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16-19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that

  10. Metrics for the Evaluation the Utility of Air Quality Forecasting

    NASA Astrophysics Data System (ADS)

    Sumo, T. M.; Stockwell, W. R.

    2013-12-01

    Global warming is expected to lead to higher levels of air pollution and therefore the forecasting of both long-term and daily air quality is an important component for the assessment of the costs of climate change and its impact on human health. Some of the risks associated with poor air quality days (where the Air Pollution Index is greater than 100), include hospital visits and mortality. Accurate air quality forecasting has the potential to allow sensitive groups to take appropriate precautions. This research builds metrics for evaluating the utility of air quality forecasting in terms of its potential impacts. Our analysis of air quality models focuses on the Washington, DC/Baltimore, MD region over the summertime ozone seasons between 2010 and 2012. The metrics that are relevant to our analysis include: (1) The number of times that a high ozone or particulate matter (PM) episode is correctly forecasted, (2) the number of times that high ozone or PM episode is forecasted when it does not occur and (3) the number of times when the air quality forecast predicts a cleaner air episode when the air was observed to have high ozone or PM. Our evaluation of the performance of air quality forecasts include those forecasts of ozone and particulate matter and data available from the U.S. Environmental Protection Agency (EPA)'s AIRNOW. We also examined observational ozone and particulate matter data available from Clean Air Partners. Overall the forecast models perform well for our region and time interval.

  11. Urban-rural variations in air quality and health impacts in northern India

    NASA Astrophysics Data System (ADS)

    Karambelas, A. N.; Holloway, T.; Fiore, A. M.; Kinney, P.; DeFries, R. S.; Kiesewetter, G.; Heyes, C.

    2017-12-01

    Ambient air pollution in India is a severe problem, contributing to negative health impacts and early death. Ground-based monitors often used to quantify health impacts are often located in urban regions, however approximately 70% of India's population resides in rural areas. We use high-resolution concentrations from the regional Community Multi-scale Air Quality (CMAQ) model over densely-populated northern India to estimate air quality and health impacts due to anthropogenic emission sectors separately for urban and rural regions. Modeled concentrations inform relative risk calculations and exposure estimates as performed in the Global Burden of Disease. Anthropogenic emissions from the International Institute for Applied Systems Analysis (IIASA) Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) model following version 5a of the Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants project gridding structure are updated to reflect urban- and rural-specific activity information for transportation and residential combustion, and industrial and electrical generating unit location and magnitude information. We estimate 314,000 (95% Confidence Interval: 304,000—323,000) and 58,000 (CI: 39,000—70,000) adults (25 years or older) die prematurely each year from PM2.5 and O3 respectively in northern India, with the greatest impacts along the Indo-Gangetic Plain. Using urban and rural population distributions, we estimate that the majority of premature deaths resulting from PM2.5 and O3 are in rural (292,000) as opposed to urban (79,000) regions. These findings indicate the need for designing monitoring networks and ground-based health studies in rural areas of India to more accurately quantify the true health implications of ambient air pollution, in addition to supporting model evaluation. Using this urban-versus-rural emissions framework, we are assessing anthropogenic contributions to regional air quality and health impacts, and

  12. Characterizing the "Time of Emergence" of Air Quality Climate Penalties

    NASA Astrophysics Data System (ADS)

    Rothenberg, D. A.; Garcia-Menendez, F.; Monier, E.; Solomon, S.; Selin, N. E.

    2017-12-01

    By driving not only local changes in temperature, but also precipitation and regional-scale changes in seasonal circulation patterns, climate change can directly and indirectly influence changes in air quality and its extremes. These changes - often referred to as "climate penalties" - can have important implications for human health, which is often targeted when assessing the potential co-benefits of climate policy. But because climate penalties are driven by slow, spatially-varying, temporal changes in the climate system, their emergence in the real world should also have a spatio-temporal component following regional variability in background air quality. In this work, we attempt to estimate the spatially-varying "time of emergence" of climate penalty signals by using an ensemble modeling framework based on the MIT Integrated Global System Model (MIT IGSM). With this framework we assess three climate policy scenarios assuming three different underlying climate sensitivities, and conduct a 5-member ensemble for each case to capture internal variability within the model. These simulations are used to drive offline chemical transport modeling (using CAM-Chem and GEOS-Chem). In these simulations, we find that the air quality response to climate change can vary dramatically across different regions of the globe. To analyze these regionally-varying climate signals, we employ a hierarchical clustering technique to identify regions with similar seasonal patterns of air quality change. Our simulations suggest that the earliest emergence of ozone climate penalties would occur in Southern Europe (by 2035), should the world neglect climate change and rely on a "business-as-usual" emissions policy. However, even modest climate policy dramatically pushes back the time of emergence of these penalties - to beyond 2100 - across most of the globe. The emergence of climate-forced changes in PM2.5 are much more difficult to detect, partially owing to the large role that changes in

  13. 78 FR 30829 - Approval and Promulgation of Air Quality Implementation Plans; Illinois; Air Quality Standards...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-05-23

    ... Promulgation of Air Quality Implementation Plans; Illinois; Air Quality Standards Revision AGENCY... the Illinois State Implementation Plan (SIP) to reflect current national ambient air quality standards...) 692-2450. 4. Mail: Pamela Blakley, Chief, Control Strategies Section, Air Programs Branch (AR-18J), U...

  14. A comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian Peninsula

    NASA Astrophysics Data System (ADS)

    Borge, Rafael; Alexandrov, Vassil; José del Vas, Juan; Lumbreras, Julio; Rodríguez, Encarnacion

    Meteorological inputs play a vital role on regional air quality modelling. An extensive sensitivity analysis of the Weather Research and Forecasting (WRF) model was performed, in the framework of the Integrated Assessment Modelling System for the Iberian Peninsula (SIMCA) project. Up to 23 alternative model configurations, including Planetary Boundary Layer schemes, Microphysics, Land-surface models, Radiation schemes, Sea Surface Temperature and Four-Dimensional Data Assimilation were tested in a 3 km spatial resolution domain. Model results for the most significant meteorological variables, were assessed through a series of common statistics. The physics options identified to produce better results (Yonsei University Planetary Boundary Layer, WRF Single-Moment 6-class microphysics, Noah Land-surface model, Eta Geophysical Fluid Dynamics Laboratory longwave radiation and MM5 shortwave radiation schemes) along with other relevant user settings (time-varying Sea Surface Temperature and combined grid-observational nudging) where included in a "best case" configuration. This setup was tested and found to produce more accurate estimation of temperature, wind and humidity fields at surface level than any other configuration for the two episodes simulated. Planetary Boundary Layer height predictions showed a reasonable agreement with estimations derived from routine atmospheric soundings. Although some seasonal and geographical differences were observed, the model showed an acceptable behaviour overall. Despite being useful to define the most appropriate setup of the WRF model for air quality modelling over the Iberian Peninsula, this study provides a general overview of WRF sensitivity and can constitute a reference for future mesoscale meteorological modelling exercises.

  15. A photosynthesis-based two-leaf canopy stomatal conductance model for meteorology and air quality modeling with WRF/CMAQ PX LSM

    NASA Astrophysics Data System (ADS)

    Ran, Limei; Pleim, Jonathan; Song, Conghe; Band, Larry; Walker, John T.; Binkowski, Francis S.

    2017-02-01

    A coupled photosynthesis-stomatal conductance model with single-layer sunlit and shaded leaf canopy scaling is implemented and evaluated in a diagnostic box model with the Pleim-Xiu land surface model (PX LSM) and ozone deposition model components taken directly from the meteorology and air quality modeling system - WRF/CMAQ (Weather Research and Forecast model and Community Multiscale Air Quality model). The photosynthesis-based model for PX LSM (PX PSN) is evaluated at a FLUXNET site for implementation against different parameterizations and the current PX LSM approach with a simple Jarvis function (PX Jarvis). Latent heat flux (LH) from PX PSN is further evaluated at five FLUXNET sites with different vegetation types and landscape characteristics. Simulated ozone deposition and flux from PX PSN are evaluated at one of the sites with ozone flux measurements. Overall, the PX PSN simulates LH as well as the PX Jarvis approach. The PX PSN, however, shows distinct advantages over the PX Jarvis approach for grassland that likely result from its treatment of C3 and C4 plants for CO2 assimilation. Simulations using Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) rather than LAI measured at each site assess how the model would perform with grid averaged data used in WRF/CMAQ. MODIS LAI estimates degrade model performance at all sites but one site having exceptionally old and tall trees. Ozone deposition velocity and ozone flux along with LH are simulated especially well by the PX PSN compared to significant overestimation by the PX Jarvis for a grassland site.

  16. QUALITY ASSURANCE HANDBOOK FOR AIR POLLUTION MEASUREMENT SYSTEMS: VOLUME IV - METEOROLOGICAL MEASUREMENTS (REVISED - AUGUST 1994)

    EPA Science Inventory

    Procedures on installing, acceptance testing, operating, maintaining and quality assuring three types of ground-based, upper air meteorological measurement systems are described. he limitations and uncertainties in precision and accuracy measurements associated with these systems...

  17. Potential impact of a US climate policy and air quality regulations on future air quality and climate change

    NASA Astrophysics Data System (ADS)

    Lee, Y. H.; Shindell, D. T.; Faluvegi, G.; Pinder, R. W.

    2015-11-01

    We have investigated how future air quality and climate change are influenced by the US air quality regulations that existed or were proposed in 2013 and a hypothetical climate mitigation policy that reduces 2050 CO2 emissions to be 50 % below 2005 emissions. Using NASA GISS ModelE2, we look at the impacts in year 2030 and 2055. The US energy-sector emissions are from the GLIMPSE project (GEOS-Chem LIDORT Integrated with MARKAL for the Purpose of Scenario Exploration), and other US emissions and the rest of the world emissions are based on the RCP4.5 scenario. The US air quality regulations are projected to have a strong beneficial impact on US air quality and public health in the future but result in positive radiative forcing. Surface PM2.5 is reduced by ~ 2 μg m-3 on average over the US, and surface ozone by ~ 8 ppbv. The improved air quality prevents about 91 400 premature deaths in the US, mainly due to the PM2.5 reduction (~ 74 200 lives saved). The air quality regulations reduces the light-reflecting aerosols (i.e., sulfate and organic matter) more than the light-absorbing species (i.e., black carbon and ozone), leading a strong positive radiative forcing (RF) by both aerosols direct and indirect forcing: total RF is ~ 0.04 W m-2 over the globe; ~ 0.8 W m-2 over the US. Under the hypothetical climate policy, future US energy relies less on coal and thus SO2 emissions are noticeably reduced. This provides air quality co-benefits, but it leads to climate dis-benefits over the US. In 2055, the US mean total RF is +0.22 W m-2 due to positive aerosol direct and indirect forcing, while the global mean total RF is -0.06 W m-2 due to the dominant negative CO2 RF (instantaneous RF). To achieve a regional-scale climate benefit via a climate policy, it is critical (1) to have multi-national efforts to reduce GHGs emissions and (2) to target emission reduction of light-absorbing species (e.g., BC and O3) on top of long-lived species. The latter is very desirable as the

  18. 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.

  19. Southern Nevada air quality study

    DOT National Transportation Integrated Search

    2007-01-01

    The Southern Nevada Air Quality Study (SNAQS) created cross-plume and in-plume measurement systems to quantify emissions distributions and source profiles from transportation emissions, specifically gasoline and diesel powered vehicles. The cross-plu...

  20. Persistence of initial conditions in continental scale air quality simulations

    NASA Astrophysics Data System (ADS)

    Hogrefe, Christian; Roselle, Shawn J.; Bash, Jesse O.

    2017-07-01

    This study investigates the effect of initial conditions (IC) for pollutant concentrations in the atmosphere and soil on simulated air quality for two continental-scale Community Multiscale Air Quality (CMAQ) model applications. One of these applications was performed for springtime and the second for summertime. Results show that a spin-up period of ten days commonly used in regional-scale applications may not be sufficient to reduce the effects of initial conditions to less than 1% of seasonally-averaged surface ozone concentrations everywhere while 20 days were found to be sufficient for the entire domain for the spring case and almost the entire domain for the summer case. For the summer case, differences were found to persist longer aloft due to circulation of air masses and even a spin-up period of 30 days was not sufficient to reduce the effects of ICs to less than 1% of seasonally-averaged layer 34 ozone concentrations over the southwestern portion of the modeling domain. Analysis of the effect of soil initial conditions for the CMAQ bidirectional NH3 exchange model shows that during springtime they can have an important effect on simulated inorganic aerosols concentrations for time periods of one month or longer. The effects are less pronounced during other seasons. The results, while specific to the modeling domain and time periods simulated here, suggest that modeling protocols need to be scrutinized for a given application and that it cannot be assumed that commonly-used spin-up periods are necessarily sufficient to reduce the effects of initial conditions on model results to an acceptable level. What constitutes an acceptable level of difference cannot be generalized and will depend on the particular application, time period and species of interest. Moreover, as the application of air quality models is being expanded to cover larger geographical domains and as these models are increasingly being coupled with other modeling systems to better represent

  1. 75 FR 65572 - Approval and Promulgation of Air Quality Implementation Plans; Ohio; Ohio Ambient Air Quality...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-26

    ... Promulgation of Air Quality Implementation Plans; Ohio; Ohio Ambient Air Quality Standards AGENCY... Ohio Administrative Code (OAC) relating to the consolidation of Ohio's Ambient Air Quality Standards... apply to Ohio's SIP. Incorporating the air quality standards into Ohio's SIP helps assure that...

  2. Multi-year downscaling application of two-way coupled WRF v3.4 and CMAQ v5.0.2 over east Asia for regional climate and air quality modeling: model evaluation and aerosol direct effects

    NASA Astrophysics Data System (ADS)

    Hong, Chaopeng; Zhang, Qiang; Zhang, Yang; Tang, Youhua; Tong, Daniel; He, Kebin

    2017-06-01

    In this study, a regional coupled climate-chemistry modeling system using the dynamical downscaling technique was established by linking the global Community Earth System Model (CESM) and the regional two-way coupled Weather Research and Forecasting - Community Multi-scale Air Quality (WRF-CMAQ) model for the purpose of comprehensive assessments of regional climate change and air quality and their interactions within one modeling framework. The modeling system was applied over east Asia for a multi-year climatological application during 2006-2010, driven with CESM downscaling data under Representative Concentration Pathways 4.5 (RCP4.5), along with a short-term air quality application in representative months in 2013 that was driven with a reanalysis dataset. A comprehensive model evaluation was conducted against observations from surface networks and satellite observations to assess the model's performance. This study presents the first application and evaluation of the two-way coupled WRF-CMAQ model for climatological simulations using the dynamical downscaling technique. The model was able to satisfactorily predict major meteorological variables. The improved statistical performance for the 2 m temperature (T2) in this study (with a mean bias of -0.6 °C) compared with the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-models might be related to the use of the regional model WRF and the bias-correction technique applied for CESM downscaling. The model showed good ability to predict PM2. 5 in winter (with a normalized mean bias (NMB) of 6.4 % in 2013) and O3 in summer (with an NMB of 18.2 % in 2013) in terms of statistical performance and spatial distributions. Compared with global models that tend to underpredict PM2. 5 concentrations in China, WRF-CMAQ was able to capture the high PM2. 5 concentrations in urban areas. In general, the two-way coupled WRF-CMAQ model performed well for both climatological and air quality applications. The coupled

  3. 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

  4. 77 FR 73320 - Approval of Air Quality Implementation Plans; California; South Coast Air Quality Management...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-10

    ... Quality Implementation Plans; California; South Coast Air Quality Management District; Prevention of... Implementation Plan (SIP) revision for the South Coast Air Quality Management District (SCAQMD or District... in a August 15, 2012 letter from the South Coast Air Quality Management District regarding specific...

  5. AIRQino, a low-cost air quality mobile platform

    NASA Astrophysics Data System (ADS)

    Zaldei, Alessandro; Vagnoli, Carolina; Di Lonardo, Sara; Gioli, Beniamino; Gualtieri, Giovanni; Toscano, Piero; Martelli, Francesca; Matese, Alessandro

    2015-04-01

    Recent air quality regulations (Directive 2008/50/EC) enforce the transition from point-based monitoring networks to new tools that must be capable of mapping and forecasting air quality on the totality of land area, and therefore the totality of citizens. This implies new technologies such as models and additional indicative measurements, are needed in addition to accurate fixed air quality monitoring stations, that until now have been taken as reference by local administrators for the enforcement of various mitigation strategies. However, due to their sporadic spatial distribution, they cannot describe the highly resolved spatial pollutant variations within cities. Integrating additional indicative measurements may provide adequate information on the spatial distribution of the ambient air quality, also allowing for a reduction of the required minimum number of fixed sampling points, whose high cost and complex maintenance still remain a crucial concern for local administrators. New low-cost and small size sensors are becoming available, that could be employed in air quality monitoring including mobile applications. However, accurate assessment of their accuracy and performance both in controlled and real monitoring conditions is crucially needed. Quantifying sensor response is a significant challenge due to the sensitivity to ambient temperature and humidity and the cross-sensitivity to others pollutant species. This study reports the development of an Arduino compatible electronic board (AIRQino) which integrates a series of low-cost metal oxide and NDIR sensors for air quality monitoring, with sensors to measure air temperature, relative humidity, noise, solar radiation and vertical acceleration. A comparative assessment was made for CO2, CO, NO2, CH4, O3, VOCs concentrations, temperature and relative humidity. A controlled climatic chamber study (-80°C / +80°C) was performed to verify temperature and humidity interference using reference gas cylinders and

  6. Associations Between Air Quality Changes and Biomarkers of Systemic Inflammation During the 2014 Nanjing Youth Olympics: A Quasi-Experimental Study.

    PubMed

    Li, Huichu; Zhou, Lian; Wang, Cuicui; Chen, Renjie; Ma, Xiaoying; Xu, Bin; Xiong, Lilin; Ding, Zhen; Chen, Xiaodong; Zhou, Yun; Xu, Yan; Kan, Haidong

    2017-06-15

    There is increasing interest in quasi-experimental research to evaluate whether actions taken to improve air quality will benefit public health. We conducted a quasi-experimental study to evaluate inflammatory response to changes in air quality during the 2014 Nanjing Youth Olympics in China. We repeatedly measured 8 biomarkers of systemic inflammation in 31 healthy adults and obtained hourly air pollutant concentrations from a nearby fixed-site monitoring station. We used linear mixed-effect models to examine the associations between air quality changes and blood biomarkers. Air pollutant concentrations decreased apparently during the Youth Olympics. Concomitantly, we observed significant decreases in levels of soluble cluster of differentiation 40 (CD40) ligand and interleukin 1β (geometric means ratios were 0.45 and 0.24, respectively) from the pre-Olympic period to the intra-Olympic period. Afterwards, levels of C-reactive protein and vascular cell adhesion molecule 1 increased significantly (geometric means ratios were 2.22 and 1.29, respectively) in the post-Olympic period. Fine particulate matter and ozone were significantly associated with soluble CD40 ligand, P-selectin, interleukin 1β, intercellular adhesion molecule 1, and vascular cell adhesion molecule 1. Other pollutants showed positive but nonsignificant associations. Our study indicated that reduced air pollution, especially fine particulate matter and ozone, during the 2014 Nanjing Youth Olympics was associated with alleviated systemic inflammation in healthy adults. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  7. Air Pollution Data for Model Evaluation and Application

    EPA Science Inventory

    One objective of designing an air pollution monitoring network is to obtain data for evaluating air quality models that are used in the air quality management process and scientific discovery.1.2 A common use is to relate emissions to air quality, including assessing ...

  8. Monitoring and analysis of air quality in Riga

    NASA Astrophysics Data System (ADS)

    Ubelis, Arnolds; Leitass, Andris; Vitols, Maris

    1995-09-01

    Riga, the capital of Latvia is a city with nearly 900,000 inhabitants and various highly concentrated industries. Air pollution in Riga is a serious problem affecting health and damaging valuable buildings of historical importance, as acid rain and smog take their toll. Therefore the Air Quality Management System with significant assistance from Swedish Government and persistent efforts from Riga City Council was arranged in Riga. It contains INDIC AIRVIRO system which simulates and evaluates air pollution levels at various locations. It then processes the data in order to predict air quality based on a number of criteria and parameters, measured by OPSIS differential absorption instruments, as well as data from the Meteorological Service and results of episodic measurements. The analysis of the results provided by Riga Air Quality Management System for the first time allows us to start comprehensive supervision of troposphere physical, chemical, and photochemical processes in the air of Riga as well as to appreciate the influence of lcoal pollution and transboundary transfer. The report contains the actual results of this work and first attempts of analysis as well as overview about activities towards research and teaching in the fields of spectroscopy and photochemistry of polluted atmospheres.

  9. 78 FR 19990 - Approval and Promulgation of Air Quality Implementation Plans; Ohio; Ohio Ambient Air Quality...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-04-03

    ... Promulgation of Air Quality Implementation Plans; Ohio; Ohio Ambient Air Quality Standards; Correction AGENCY... approved revisions to Ohio regulations that consolidated air quality standards in a new chapter of rules... State's air quality standards into Ohio Administrative Code (OAC) 3745-25 and modifying an assortment of...

  10. 77 FR 12482 - Approval and Promulgation of Air Quality Implementation Plans; Indiana; Lead Ambient Air Quality...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-03-01

    ... Promulgation of Air Quality Implementation Plans; Indiana; Lead Ambient Air Quality Standards AGENCY... incorporates the National Ambient Air Quality Standards (NAAQS) for Pb promulgated by EPA in 2008. DATES: This... FR 66964) and codified at 40 CFR 50.16, ``National primary and secondary ambient air quality...

  11. China's Air Quality and Respiratory Disease Mortality Based on the Spatial Panel Model.

    PubMed

    Cao, Qilong; Liang, Ying; Niu, Xueting

    2017-09-18

    Background : Air pollution has become an important factor restricting China's economic development and has subsequently brought a series of social problems, including the impact of air pollution on the health of residents, which is a topical issue in China. Methods : Taking into account this spatial imbalance, the paper is based on the spatial panel data model PM 2.5 . Respiratory disease mortality in 31 Chinese provinces from 2004 to 2008 is taken as the main variable to study the spatial effect and impact of air quality and respiratory disease mortality on a large scale. Results : It was found that there is a spatial correlation between the mortality of respiratory diseases in Chinese provinces. The spatial correlation can be explained by the spatial effect of PM 2.5 pollutions in the control of other variables. Conclusions : Compared with the traditional non-spatial model, the spatial model is better for describing the spatial relationship between variables, ensuring the conclusions are scientific and can measure the spatial effect between variables.

  12. Assessing air quality in Aksaray with time series analysis

    NASA Astrophysics Data System (ADS)

    Kadilar, Gamze Özel; Kadilar, Cem

    2017-04-01

    Sulphur dioxide (SO2) is a major air pollutant caused by the dominant usage of diesel, petrol and fuels by vehicles and industries. One of the most air-polluted city in Turkey is Aksaray. Hence, in this study, the level of SO2 is analyzed in Aksaray based on the database monitored at air quality monitoring station of Turkey. Seasonal Autoregressive Integrated Moving Average (SARIMA) approach is used to forecast the level of SO2 air quality parameter. The results indicate that the seasonal ARIMA model provides reliable and satisfactory predictions for the air quality parameters and expected to be an alternative tool for practical assessment and justification.

  13. 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.

  14. A multi-model assessment of the co-benefits of climate mitigation for global air quality

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rao, Shilpa; Klimont, Zbigniew; Leitao, Joana

    The recent International Panel on Climate change (IPCC) report identifies significant co-benefits from climate policies on near-term ambient air pollution and related human health outcomes [1]. This is increasingly relevant for policy making as the health impacts of air pollution are a major global concern- the Global Burden of Disease (GBD) study identifies outdoor air pollution as the sixth major cause of death globally [2]. Integrated assessment models (IAMs) are an effective tool to evaluate future air pollution outcomes across a wide range of assumptions on socio-economic development and policy regimes. The Representative Concentration Pathways (RCPs) [3] were the firstmore » set of long-term global scenarios developed across multiple integrated assessment models that provided detailed estimates of a number of air pollutants until 2100. However these scenarios were primarily designed to cover a defined range of radiative forcing outcomes and thus did not specifically focus on the interactions of long-term climate goals on near-term air pollution impacts. More recently, [4] used the RCP4.5 scenario to evaluate the co-benefits of global GHG reductions on air quality and human health in 2030. [5-7] have further examined the interactions of more diverse pollution control regimes with climate policies. This paper extends the listed studies in a number of ways. Firstly it uses multiple IAMs to look into the co-benefits of a global climate policy for ambient air pollution under harmonized assumptions on near-term air pollution control. Multi-model frameworks have been extensively used in the analysis of climate change mitigation pathways, and the structural uncertainties regarding the underlying mechanisms (see for example [8-10]. This is to our knowledge the first time that a multi-model evaluation has been specifically designed and applied to analyze the co-benefits of climate change policy on ambient air quality, thus enabling a better understanding of at a

  15. Ozone - Current Air Quality Index

    MedlinePlus

    GO! Local Air Quality Conditions Zip Code: State : My Current Location Current AQI Forecast AQI Loop More Maps AQI: Good (0 - 50) ... resources for Hawaii residents and visitors more announcements Air Quality Basics Air Quality Index | Ozone | Particle Pollution | Smoke ...

  16. Thermal conditions and perceived air quality in an air-conditioned auditorium

    NASA Astrophysics Data System (ADS)

    Polednik, Bernard; Guz, Łukasz; Skwarczyński, Mariusz; Dudzińska, Marzenna R.

    2016-07-01

    The study reports measurements of indoor air temperature (T) and relative humidity (RH), perceived air quality (PAQ) and CO2, fine aerosol particle number (PN) and mass (PM1) concentrations in an air conditioned auditorium. The measurements of these air physical parameters have been carried out in the unoccupied auditorium with the air conditioning system switched off (AC off mode) and in the unoccupied and occupied auditorium with the air conditioning system switched off during the night and switched on during the day (AC on/off mode). The average indoor air thermal parameters, CO2 concentration and the PAQ value (in decipols) were elevated, while average PM1 concentration was lower in the AC on/off mode. A statistically significant (p < 0.001) positive correlation has been observed between T and PAQ values and CO2 concentrations (r = 0.66 and r = 0.59, respectively) in that AC mode. A significant negative correlation has been observed between T and PN and PM1 concentrations (r = -0.38 and r = -0.49, respectively). In the AC off mode the above relations between T and the particle concentrations were not that unequivocal. These findings may be of importance as they indicate that in certain AC operation modes the indoor air quality deteriorates along with the variation of the indoor air microclimate and room occupation. This, in turn, may adversely affect the comfort and productivity of the users of air conditioned premises.

  17. Modeling urban air pollution with optimized hierarchical fuzzy inference system.

    PubMed

    Tashayo, Behnam; Alimohammadi, Abbas

    2016-10-01

    Environmental exposure assessments (EEA) and epidemiological studies require urban air pollution models with appropriate spatial and temporal resolutions. Uncertain available data and inflexible models can limit air pollution modeling techniques, particularly in under developing countries. This paper develops a hierarchical fuzzy inference system (HFIS) to model air pollution under different land use, transportation, and meteorological conditions. To improve performance, the system treats the issue as a large-scale and high-dimensional problem and develops the proposed model using a three-step approach. In the first step, a geospatial information system (GIS) and probabilistic methods are used to preprocess the data. In the second step, a hierarchical structure is generated based on the problem. In the third step, the accuracy and complexity of the model are simultaneously optimized with a multiple objective particle swarm optimization (MOPSO) algorithm. We examine the capabilities of the proposed model for predicting daily and annual mean PM2.5 and NO2 and compare the accuracy of the results with representative models from existing literature. The benefits provided by the model features, including probabilistic preprocessing, multi-objective optimization, and hierarchical structure, are precisely evaluated by comparing five different consecutive models in terms of accuracy and complexity criteria. Fivefold cross validation is used to assess the performance of the generated models. The respective average RMSEs and coefficients of determination (R (2)) for the test datasets using proposed model are as follows: daily PM2.5 = (8.13, 0.78), annual mean PM2.5 = (4.96, 0.80), daily NO2 = (5.63, 0.79), and annual mean NO2 = (2.89, 0.83). The obtained results demonstrate that the developed hierarchical fuzzy inference system can be utilized for modeling air pollution in EEA and epidemiological studies.

  18. 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.

  19. 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.

  20. FIRST RESULTS FROM OPERATIONAL TESTING OF THE U.S. EPA MODELS-3 COMMUNITY MULTISCALE MODEL FOR AIR QUALITY (CMAQ)

    EPA Science Inventory

    The Models 3 / Community Multiscale Model for Air Quality (CMAQ) has been designed for one-atmosphere assessments for multiple pollutants including ozone (O3), particulate matter (PM10, PM2.5), and acid / nutrient deposition. In this paper we report initial results of our evalu...

  1. Psychosocial and demographic predictors of adherence and non-adherence to health advice accompanying air quality warning systems: a systematic review.

    PubMed

    D'Antoni, Donatella; Smith, Louise; Auyeung, Vivian; Weinman, John

    2017-09-22

    Although evidence shows that poor air quality can harm human health, we have a limited understanding about the behavioural impact of air quality forecasts. Our aim was to understand to what extent air quality warning systems influence protective behaviours in the general public, and to identify the demographic and psychosocial factors associated with adherence and non-adherence to the health advice accompanying these warnings. In August 2016 literature was systematically reviewed to find studies assessing intended or actual adherence to health advice accompanying air quality warning systems, and encouraging people to reduce exposure to air pollution. Predictors of adherence to the health advice and/or self-reported reasons for adherence or non-adherence were also systematically reviewed. Studies were included only if they involved participants who were using or were aware of these warning systems. Studies investigating only protective behaviours due to subjective perception of bad air quality alone were excluded. The results were narratively synthesised and discussed within the COM-B theoretical framework. Twenty-one studies were included in the review: seventeen investigated actual adherence; three investigated intended adherence; one assessed both. Actual adherence to the advice to reduce or reschedule outdoor activities during poor air quality episodes ranged from 9.7% to 57% (Median = 31%), whereas adherence to a wider range of protective behaviours (e.g. avoiding busy roads, taking preventative medication) ranged from 17.7% to 98.1% (Median = 46%). Demographic factors did not consistently predict adherence. However, several psychosocial facilitators of adherence were identified. These include knowledge on where to check air quality indices, beliefs that one's symptoms were due to air pollution, perceived severity of air pollution, and receiving advice from health care professionals. Barriers to adherence included: lack of understanding of the indices

  2. 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 ...

  3. Air quality high resolution simulations of Italian urban areas with WRF-CHIMERE

    NASA Astrophysics Data System (ADS)

    Falasca, Serena; Curci, Gabriele

    2017-04-01

    The new European Directive on ambient air quality and cleaner air for Europe (2008/50/EC) encourages the use of modeling techniques to support the observations in the assessment and forecasting of air quality. The modelling system based on the combination of the WRF meteorological model and the CHIMERE chemistry-transport model is used to perform simulations at high resolution over the main Italian cities (e.g. Milan, Rome). Three domains covering Europe, Italy and the urban areas are nested with a decreasing grid size up to 1 km. Numerical results are produced for a winter month and a summer month of the year 2010 and are validated using ground-based observations (e.g. from the European air quality database AirBase). A sensitivity study is performed using different physics options, domain resolution and grid ratio; different urban parameterization schemes are tested using also characteristic morphology parameters for the cities considered. A spatial reallocation of anthropogenic emissions derived from international (e.g. EMEP, TNO, HTAP) and national (e.g. CTN-ACE) emissions inventories and based on the land cover datasets (Global Land Cover Facility and GlobCover) and the OpenStreetMap tool is also included. Preliminary results indicate that the introduction of the spatial redistribution at high-resolution allows a more realistic reproduction of the distribution of the emission flows and thus the concentrations of the pollutants, with significant advantages especially for the urban environments.

  4. Impacts of Residential Biofuel Emissions on Air Quality and Climate

    NASA Astrophysics Data System (ADS)

    Huang, Y.; Unger, N.; Harper, K.; Storelvmo, T.

    2016-12-01

    The residential biofuel sector is defined as fuelwood, agricultural residues and dung used for household cooking and heating. Aerosol emissions from this human activity play an important role affecting local, regional and global air quality, climate and public health. However, there are only few studies available that evaluate the net impacts and large uncertainties persist. Here we use the Community Atmosphere Model version 5.3 (CAM v5.3) within the Community Earth System Model version 1.2.2, to quantify the impacts of cook-stove biofuel emissions on air quality and climate. The model incorporates a novel advanced treatment of black carbon (BC) effects on mixed-phase/ice clouds. We update the global anthropogenic emission inventory in CAM v5.3 to a state-of-the-art emission inventory from the Greenhouse Gas-Air Pollution Interactions and Synergies integrated assessment model. Global in-situ and aircraft campaign observations for BC and organic carbon are used to evaluate and validate the model performance. Sensitivity simulations are employed to assess the impacts of residential biofuel emissions on regional and global direct and indirect radiative forcings in the contemporary world. We focus the analyses on several key regions including India, China and Sub-Saharan Africa.

  5. 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<...

  6. Simulating smoke transport from wildland fires with a regional-scale air quality model: sensitivity to spatiotemporal allocation of fire emissions.

    PubMed

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

    2014-09-15

    Air quality forecasts generated with chemical transport models can provide valuable information about the potential impacts of fires on pollutant levels. However, significant uncertainties are associated with fire-related emission estimates as well as their distribution on gridded modeling domains. In this study, we explore the sensitivity of fine particulate matter concentrations predicted by a regional-scale air quality model to the spatial and temporal allocation of fire emissions. The assessment was completed by simulating a fire-related smoke episode in which air quality throughout the Atlanta metropolitan area was affected on February 28, 2007. Sensitivity analyses were carried out to evaluate the significance of emission distribution among the model's vertical layers, along the horizontal plane, and into hourly inputs. Predicted PM2.5 concentrations were highly sensitive to emission injection altitude relative to planetary boundary layer height. Simulations were also responsive to the horizontal allocation of fire emissions and their distribution into single or multiple grid cells. Additionally, modeled concentrations were greatly sensitive to the temporal distribution of fire-related emissions. The analyses demonstrate that, in addition to adequate estimates of emitted mass, successfully modeling the impacts of fires on air quality depends on an accurate spatiotemporal allocation of emissions. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. 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,…

  8. 75 FR 65594 - Approval and Promulgation of Air Quality Implementation Plans; Ohio; Ohio Ambient Air Quality...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-26

    ... Promulgation of Air Quality Implementation Plans; Ohio; Ohio Ambient Air Quality Standards AGENCY... the Ohio Administrative Code (OAC) relating to the consolidation of Ohio's Ambient Air Quality Standards (AAQS) into Ohio's State Implementation Plan (SIP) under the Clean Air Act. On April 8, 2009, and...

  9. 77 FR 12524 - Approval and Promulgation of Air Quality Implementation Plans; Indiana; Lead Ambient Air Quality...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-03-01

    ... Promulgation of Air Quality Implementation Plans; Indiana; Lead Ambient Air Quality Standards AGENCY... Indiana State Implementation Plan (SIP) for lead (Pb) under the Clean Air Act (CAA). This submittal incorporates the National Ambient Air Quality Standards (NAAQS) for Pb promulgated by EPA in 2008. DATES...

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

    USDA-ARS?s Scientific Manuscript database

    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 ...

  11. Using satellite observations in performance evaluation for regulatory air quality modeling: Comparison with ground-level measurements

    NASA Astrophysics Data System (ADS)

    Odman, M. T.; Hu, Y.; Russell, A.; Chai, T.; Lee, P.; Shankar, U.; Boylan, J.

    2012-12-01

    Regulatory air quality modeling, such as State Implementation Plan (SIP) modeling, requires that model performance meets recommended criteria in the base-year simulations using period-specific, estimated emissions. The goal of the performance evaluation is to assure that the base-year modeling accurately captures the observed chemical reality of the lower troposphere. Any significant deficiencies found in the performance evaluation must be corrected before any base-case (with typical emissions) and future-year modeling is conducted. Corrections are usually made to model inputs such as emission-rate estimates or meteorology and/or to the air quality model itself, in modules that describe specific processes. Use of ground-level measurements that follow approved protocols is recommended for evaluating model performance. However, ground-level monitoring networks are spatially sparse, especially for particulate matter. Satellite retrievals of atmospheric chemical properties such as aerosol optical depth (AOD) provide spatial coverage that can compensate for the sparseness of ground-level measurements. Satellite retrievals can also help diagnose potential model or data problems in the upper troposphere. It is possible to achieve good model performance near the ground, but have, for example, erroneous sources or sinks in the upper troposphere that may result in misleading and unrealistic responses to emission reductions. Despite these advantages, satellite retrievals are rarely used in model performance evaluation, especially for regulatory modeling purposes, due to the high uncertainty in retrievals associated with various contaminations, for example by clouds. In this study, 2007 was selected as the base year for SIP modeling in the southeastern U.S. Performance of the Community Multiscale Air Quality (CMAQ) model, at a 12-km horizontal resolution, for this annual simulation is evaluated using both recommended ground-level measurements and non-traditional satellite

  12. Impact of WRF model PBL schemes on air quality simulations over Catalonia, Spain.

    PubMed

    Banks, R F; Baldasano, J M

    2016-12-01

    Here we analyze the impact of four planetary boundary-layer (PBL) parametrization schemes from the Weather Research and Forecasting (WRF) numerical weather prediction model on simulations of meteorological variables and predicted pollutant concentrations from an air quality forecast system (AQFS). The current setup of the Spanish operational AQFS, CALIOPE, is composed of the WRF-ARW V3.5.1 meteorological model tied to the Yonsei University (YSU) PBL scheme, HERMES v2 emissions model, CMAQ V5.0.2 chemical transport model, and dust outputs from BSC-DREAM8bv2. We test the performance of the YSU scheme against the Assymetric Convective Model Version 2 (ACM2), Mellor-Yamada-Janjic (MYJ), and Bougeault-Lacarrère (BouLac) schemes. The one-day diagnostic case study is selected to represent the most frequent synoptic condition in the northeast Iberian Peninsula during spring 2015; regional recirculations. It is shown that the ACM2 PBL scheme performs well with daytime PBL height, as validated against estimates retrieved using a micro-pulse lidar system (mean bias=-0.11km). In turn, the BouLac scheme showed WRF-simulated air and dew point temperature closer to METAR surface meteorological observations. Results are more ambiguous when simulated pollutant concentrations from CMAQ are validated against network urban, suburban, and rural background stations. The ACM2 scheme showed the lowest mean bias (-0.96μgm -3 ) with respect to surface ozone at urban stations, while the YSU scheme performed best with simulated nitrogen dioxide (-6.48μgm -3 ). The poorest results were with simulated particulate matter, with similar results found with all schemes tested. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  13. Cabin Air Quality Dynamics On Board the International Space Station

    NASA Technical Reports Server (NTRS)

    Perry, J. L.; Peterson, B. V.

    2003-01-01

    Spacecraft cabin air quality is influenced by a variety of factors. Beyond normal equipment offgassing and crew metabolic loads, the vehicle s operational configuration contributes significantly to overall air quality. Leaks from system equipment and payload facilities, operational status of the atmospheric scrubbing systems, and the introduction of new equipment and modules to the vehicle all influence air quality. The dynamics associated with changes in the International Space Station's (ISS) configuration since the launch of the U.S. Segment s laboratory module, Destiny, is summarized. Key classes of trace chemical contaminants that are important to crew health and equipment performance are emphasized. The temporary effects associated with attaching each multi-purpose logistics module (MPLM) to the ISS and influence of in-flight air quality on the post-flight ground processing of the MPLM are explored.

  14. PREMAQ: A NEW PRE-PROCESSOR TO CMAQ FOR AIR-QUALITY FORECASTING

    EPA Science Inventory

    A new pre-processor to CMAQ (PREMAQ) has been developed as part of the national air-quality forecasting system. PREMAQ combines the functionality of MCIP and parts of SMOKE in a single real-time processor. PREMAQ was specifically designed to link NCEP's Eta model with CMAQ, and...

  15. The development of effects-based air quality management regimes

    NASA Astrophysics Data System (ADS)

    Longhurst, J. W. S.; Irwin, J. G.; Chatterton, T. J.; Hayes, E. T.; Leksmono, N. S.; Symons, J. K.

    This paper considers the evolution of attempts to control and manage air pollution, principally but not exclusively focussing upon the challenge of managing air pollution in urban environments. The development and implementation of a range of air pollution control measures are considered. Initially the measures implemented primarily addressed point sources, a small number of fuel types and a limited number of pollutants. The adequacy of such a source-control approach is assessed within the context of a changing and challenging air pollution climate. An assessment of air quality management in the United Kingdom over a 50-year timeframe exemplifies the range of issues and challenges in contemporary air quality management. The need for new approaches is explored and the development and implementation of an effects-based, risk management system for air quality regulation is evaluated.

  16. Mathematical model of one-man air revitalization system

    NASA Technical Reports Server (NTRS)

    1976-01-01

    A mathematical model was developed for simulating the steady state performance in electrochemical CO2 concentrators which utilize (NMe4)2 CO3 (aq.) electrolyte. This electrolyte, which accommodates a wide range of air relative humidity, is most suitable for one-man air revitalization systems. The model is based on the solution of coupled nonlinear ordinary differential equations derived from mass transport and rate equations for the processes which take place in the cell. The boundary conditions are obtained by solving the mass and energy transport equations. A shooting method is used to solve the differential equations.

  17. Research and application of a hybrid model based on dynamic fuzzy synthetic evaluation for establishing air quality forecasting and early warning system: A case study in China.

    PubMed

    Xu, Yunzhen; Du, Pei; Wang, Jianzhou

    2017-04-01

    As the atmospheric environment pollution has been becoming more and more serious in China, it is highly desirable to develop a scientific and effective early warning system that plays a great significant role in analyzing and monitoring air quality. However, establishing a robust early warning system for warning the public in advance and ameliorating air quality is not only an extremely challenging task but also a public concerned problem for human health. Most previous studies are focused on improving the prediction accuracy, which usually ignore the significance of uncertainty information and comprehensive evaluation concerning air pollutants. Therefore, in this paper a novel robust early warning system was successfully developed, which consists of three modules: evaluation module, forecasting module and characteristics estimating module. In this system, a new dynamic fuzzy synthetic evaluation is proposed and applied to determine air quality levels and primary pollutants, which can be regarded as the research objectives; Moreover, to further mine and analyze the characteristics of air pollutants, four different distribution functions and interval forecasting method are also employed that can not only provide predictive range, confidence level and the other uncertain information of the pollutants future values, but also assist decision-makers in reducing and controlling the emissions of atmospheric pollutants. Case studies utilizing hourly PM 2.5 , PM 10 and SO 2 data collected from Tianjin and Shanghai in China are applied as illustrative examples to estimate the effectiveness and efficiency of the proposed system. Experimental results obviously indicated that the developed novel early warning system is much suitable for analyzing and monitoring air pollution, which can also add a novel viable option for decision-makers. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Modeling and optimization of the air system in polymer exchange membrane fuel cell systems

    NASA Astrophysics Data System (ADS)

    Bao, Cheng; Ouyang, Minggao; Yi, Baolian

    Stack and air system are the two most important components in the fuel cell system (FCS). It is meaningful to study their properties and the trade-off between them. In this paper, a modified one-dimensional steady-state analytical fuel cell model is used. The logarithmic mean of the inlet and the outlet oxygen partial pressure is adopted to avoid underestimating the effect of air stoichiometry. And the pressure drop model in the grid-distributed flow field is included in the stack analysis. Combined with the coordinate change preprocessing and analog technique, neural network is used to treat the MAP of compressor and turbine in the air system. Three kinds of air system topologies, the pure screw compressor, serial booster and exhaust expander are analyzed in this article. A real-code genetic algorithm is programmed to obtain the global optimum air stoichiometric ratio and the cathode outlet pressure. It is shown that the serial booster and expander with the help of exhaust recycling, can improve more than 3% in the FCS efficiency comparing to the pure screw compressor. As the net power increases, the optimum cathode outlet pressure keeps rising and the air stoichiometry takes on the concave trajectory. The working zone of the proportional valve is also discussed. This presented work is helpful to the design of the air system in fuel cell system. The steady-state optimum can also be used in the dynamic control.

  19. Perceived indoor air quality and its relationship to air pollutants in French dwellings.

    PubMed

    Langer, S; Ramalho, O; Le Ponner, E; Derbez, M; Kirchner, S; Mandin, C

    2017-11-01

    Perception of indoor air quality (PIAQ) was evaluated in a nationwide survey of 567 French dwellings, and this survey was combined with measurements of gaseous and particulate matter (PM 10 and PM 2.5 ) indoor air pollutants and indoor climate parameters. The perception was assessed on a nine-grade scale by both the occupants of the dwellings and the inspectors who performed the measurements. The occupants perceived the air quality in their homes as more pleasant than the inspectors. The inspectors perceived the air quality as more unpleasant in dwellings in which the residents smoked indoors. Significant associations between PIAQ and indoor air pollutant concentrations were observed for both the inspectors and, to a lesser extent, the occupants. Introducing confounding parameters, such as building and personal characteristics, into a multivariate model suppressed most of the observed bivariate correlations and identified the tenure status of the occupants and their occupation as the parameters that most influenced their PIAQ. For the inspectors, perceived air quality was affected by the presence of smokers, the season, the type of ventilation, retrofitting, and the concentrations of acetaldehyde and acrolein. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  20. Mapping urban air quality in near real-time using observations from low-cost sensors and model information.

    PubMed

    Schneider, Philipp; Castell, Nuria; Vogt, Matthias; Dauge, Franck R; Lahoz, William A; Bartonova, Alena

    2017-09-01

    The recent emergence of low-cost microsensors measuring various air pollutants has significant potential for carrying out high-resolution mapping of air quality in the urban environment. However, the data obtained by such sensors are generally less reliable than that from standard equipment and they are subject to significant data gaps in both space and time. In order to overcome this issue, we present here a data fusion method based on geostatistics that allows for merging observations of air quality from a network of low-cost sensors with spatial information from an urban-scale air quality model. The performance of the methodology is evaluated for nitrogen dioxide in Oslo, Norway, using both simulated datasets and real-world measurements from a low-cost sensor network for January 2016. The results indicate that the method is capable of producing realistic hourly concentration fields of urban nitrogen dioxide that inherit the spatial patterns from the model and adjust the prior values using the information from the sensor network. The accuracy of the data fusion method is dependent on various factors including the total number of observations, their spatial distribution, their uncertainty (both in terms of systematic biases and random errors), as well as the ability of the model to provide realistic spatial patterns of urban air pollution. A validation against official data from air quality monitoring stations equipped with reference instrumentation indicates that the data fusion method is capable of reproducing city-wide averaged official values with an R 2 of 0.89 and a root mean squared error of 14.3 μg m -3 . It is further capable of reproducing the typical daily cycles of nitrogen dioxide. Overall, the results indicate that the method provides a robust way of extracting useful information from uncertain sensor data using only a time-invariant model dataset and the knowledge contained within an entire sensor network. Copyright © 2017 The Authors. Published

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