Sample records for air quality forecasters

  1. 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.

  2. 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

  3. 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.

  4. 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 ...

  5. 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...

  6. FORECASTING AIR QUALITY OVER THE UNITED STATES

    EPA Science Inventory

    Increased awareness of national air quality issues on the part of the media and the general public have recently led to more demand for short-term (1-2 day) air quality forecasts for use in assessing potential health impacts (e.g., on children, the elderly, and asthmatics) and po...

  7. IMPROVING NATIONAL AIR QUALITY FORECASTS WITH SATELLITE AEROSOL OBSERVATIONS

    EPA Science Inventory

    Air quality forecasts for major US metropolitan areas have been provided to the public through a partnership between the US Environmental Protection Agency and state and local air agencies since 1997. Recent years have witnessed improvement in forecast skill and expansion of fore...

  8. 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...

  9. 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.

  10. 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

  11. 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.

  12. Toward a US National Air Quality Forecast Capability: Current and Planned Capabilities

    EPA Science Inventory

    As mandated by Congress, NOAA is establishing a US national air quality forecast capability. This capability is being built with EPA, to provide air quality forecast information with enough accuracy and lead-time so that people can take actions to limit harmful effects of poor a...

  13. 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

  14. 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...

  15. 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

  16. 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.

  17. Forecasting air quality time series using deep learning.

    PubMed

    Freeman, Brian S; Taylor, Graham; Gharabaghi, Bahram; Thé, Jesse

    2018-04-13

    This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O 3 ) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O 3 exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours. Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution

  18. Ensemble Statistical Post-Processing of the National Air Quality Forecast Capability: Enhancing Ozone Forecasts in Baltimore, Maryland

    NASA Technical Reports Server (NTRS)

    Garner, Gregory G.; Thompson, Anne M.

    2013-01-01

    An ensemble statistical post-processor (ESP) is developed for the National Air Quality Forecast Capability (NAQFC) to address the unique challenges of forecasting surface ozone in Baltimore, MD. Air quality and meteorological data were collected from the eight monitors that constitute the Baltimore forecast region. These data were used to build the ESP using a moving-block bootstrap, regression tree models, and extreme-value theory. The ESP was evaluated using a 10-fold cross-validation to avoid evaluation with the same data used in the development process. Results indicate that the ESP is conditionally biased, likely due to slight overfitting while training the regression tree models. When viewed from the perspective of a decision-maker, the ESP provides a wealth of additional information previously not available through the NAQFC alone. The user is provided the freedom to tailor the forecast to the decision at hand by using decision-specific probability thresholds that define a forecast for an ozone exceedance. Taking advantage of the ESP, the user not only receives an increase in value over the NAQFC, but also receives value for An ensemble statistical post-processor (ESP) is developed for the National Air Quality Forecast Capability (NAQFC) to address the unique challenges of forecasting surface ozone in Baltimore, MD. Air quality and meteorological data were collected from the eight monitors that constitute the Baltimore forecast region. These data were used to build the ESP using a moving-block bootstrap, regression tree models, and extreme-value theory. The ESP was evaluated using a 10-fold cross-validation to avoid evaluation with the same data used in the development process. Results indicate that the ESP is conditionally biased, likely due to slight overfitting while training the regression tree models. When viewed from the perspective of a decision-maker, the ESP provides a wealth of additional information previously not available through the NAQFC alone

  19. 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.

  20. COMPUTATIONAL ASPECTS OF THE AIR QUALITY FORECASTING VERSION OF CMAQ (CMAQ-F)

    EPA Science Inventory

    The air quality forecast version of the Community Modeling Air Quality (CMAQ) model (CMAQ-F) was developed from the public release version of CMAQ (available from http://www.cmascenter.org), and is running operationally at the National Weather Service's National Centers for Envir...

  1. On The Usage Of Fire Smoke Emissions In An Air Quality Forecasting System To Reduce Particular Matter Forecasting Error

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

    Wildfires contribute to air quality problems not only towards primary emissions of particular matters (PM) but also emitted ozone precursor gases that can lead to elevated ozone concentration. Wildfires are unpredictable and can be ignited by natural causes such as lightning or accidently by human negligent behavior such as live cigarette. Although wildfire impacts on the air quality can be studied by collecting fire information after events, it is extremely difficult to predict future occurrence and behavior of wildfires for real-time air quality forecasts. Because of the time constraints of operational air quality forecasting, assumption of future day's fire behavior often have to be made based on observed fire information in the past. The United States (U.S.) NOAA/NWS built the National Air Quality Forecast Capability (NAQFC) based on the U.S. EPA CMAQ to provide air quality forecast guidance (prediction) publicly. State and local forecasters use the forecast guidance to issue air quality alerts in their area. The NAQFC fine particulates (PM2.5) prediction includes emissions from anthropogenic and biogenic sources, as well as natural sources such as dust storms and fires. The fire emission input to the NAQFC is derived from the NOAA NESDIS HMS fire and smoke detection product and the emission module of the US Forest Service BlueSky Smoke Modeling Framework. This study focuses on the error estimation of NAQFC PM2.5 predictions resulting from fire emissions. The comparisons between the NAQFC modeled PM2.5 and the EPA AirNow surface observation show that present operational NAQFC fire emissions assumption can lead to a huge error in PM2.5 prediction as fire emissions are sometimes placed at wrong location and time. This PM2.5 prediction error can be propagated from the fire source in the Northwest U.S. to downstream areas as far as the Southeast U.S. From this study, a new procedure has been identified to minimize the aforementioned error. An additional 24 hours

  2. 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...

  3. 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.

  4. 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

  5. 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

  6. 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...

  7. Improving Forecast Skill by Assimilation of Quality Controlled AIRS Version 5 Temperature Soundings

    NASA Technical Reports Server (NTRS)

    Susskind, Joel; Reale, Oreste

    2009-01-01

    The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains two significant improvements over Version 4: 1) Improved physics allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profile T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations are now used primarily in the generation of cloud cleared radiances R(sub i). This approach allows for the generation of accurate values of R(sub i) and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by-channel error estimates for R(sub i). These error estimates are used for Quality Control of the retrieved products. We have conducted forecast impact experiments assimilating AIRS temperature profiles with different levels of Quality Control using the NASA GEOS-5 data assimilation system. Assimilation of Quality Controlled T(p) resulted in significantly improved forecast skill compared to that obtained from analyses obtained when all data used operationally by NCEP, except for AIRS data, is assimilated. We also conducted an experiment assimilating AIRS radiances uncontaminated by clouds, as done operationally by ECMWF and NCEP. Forecast resulting from assimilated AIRS radiances were of poorer quality than those obtained assimilating AIRS temperatures.

  8. 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.

  9. 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...

  10. 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.

  11. Evaluation and intercomparison of air quality forecasts over Korea during the KORUS-AQ campaign

    NASA Astrophysics Data System (ADS)

    Lee, Seungun; Park, Rokjin J.; Kim, Soontae; Song, Chul H.; Kim, Cheol-Hee; Woo, Jung-Hun

    2017-04-01

    We evaluate and intercompare ozone and aerosol simulations over Korea during the KORUS-AQ campaign, which was conducted in May-June 2016. Four global and regional air quality models participated in the campaign and provided daily air quality forecasts over Korea to guide aircraft flight paths for detecting air pollution events over Korean peninsula and its nearby oceans. We first evaluate the model performance by comparing simulated and observed hourly surface ozone and PM2.5 concentrations at ground sites in Korea and find that the models successfully capture intermittent air pollution events and reproduce the daily variation of ozone and PM2.5 concentrations. However, significant underestimates of peak ozone concentrations in the afternoon are also found in most models. Among chemical constituents of PM2.5, the models typically overestimate observed nitrate aerosol concentrations and underestimate organic aerosol concentrations, although the observed mass concentrations of PM2.5 are seemingly reproduced by the models. In particular, all models used the same anthropogenic emission inventory (KU-CREATE) for daily air quality forecast, but they show a considerable discrepancy for ozone and aerosols. Compared to individual model results, the ensemble mean of all models shows the best performance with correlation coefficients of 0.73 for ozone and 0.57 for PM2.5. We here investigate contributing factors to the discrepancy, which will serve as a guidance to improve the performance of the air quality forecast.

  12. Operational air quality forecast guidance for the United States

    NASA Astrophysics Data System (ADS)

    Stajner, Ivanka; Lee, Pius; Tong, Daniel; Pan, Li; McQueen, Jeff; Huang, Jinaping; Djalalova, Irina; Wilczak, James; Huang, Ho-Chun; Wang, Jun; Stein, Ariel; Upadhayay, Sikchya

    2016-04-01

    NOAA provides operational air quality predictions for ozone and wildfire smoke over the United States (U.S.) and predictions of airborne dust over the contiguous 48 states at http://airquality.weather.gov. These predictions are produced using U.S. Environmental Protection Agency (EPA) Community Model for Air Quality (CMAQ) and NOAA's HYSPLIT model (Stein et al., 2015) with meteorological inputs from the North American Mesoscale Forecast System (NAM). The current efforts focus on improving test predictions of fine particulate matter (PM2.5) from CMAQ. Emission inputs for ozone and PM2.5 predictions include inventory information from the U.S. EPA and recently added contributions of particulate matter from intermittent wildfires and windblown dust that rely on near real-time information. Current testing includes refinement of the vertical grid structure in CMAQ and inclusion of contributions of dust transport from global sources into the U.S. domain using the NEMS Global Aerosol Capability (NGAC). The addition of wildfire smoke and dust contributions in CMAQ reduced model underestimation of PM2.5 in summertime. Wintertime overestimation of PM2.5 was reduced by suppressing emissions of soil particles when the terrain is covered by snow or ice. Nevertheless, seasonal biases and biases in the diurnal cycle of PM2.5 are still substantial. Therefore, a new bias correction procedure based on an analog ensemble approach was introduced (Djalalova et al., 2015). It virtually eliminates biases in monthly means or in the diurnal cycle, but it also reduces day-to-day variability in PM2.5 predictions. Refinements to the bias correction procedure are being developed. Upgrades for the representation of wildfire smoke emissions within the domain and from global sources are in testing. Another area of active development includes approaches to scale emission inventories for nitrogen oxides in order to reproduce recent changes observed by the AirNow surface monitoring network and by

  13. THE NEW ENGLAND AIR QUALITY FORECASTING PILOT PROGRAM: DEVELOPMENT OF AN EVALUATION PROTOCOL AND PERFORMANCE BENCHMARK

    EPA Science Inventory

    The National Oceanic and Atmospheric Administration recently sponsored the New England Forecasting Pilot Program to serve as a "test bed" for chemical forecasting by providing all of the elements of a National Air Quality Forecasting System, including the development and implemen...

  14. 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) ...

  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. 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

  17. 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...

  18. 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

  19. New smoke predictions for Alaska in NOAA’s National Air Quality Forecast Capability

    NASA Astrophysics Data System (ADS)

    Davidson, P. M.; Ruminski, M.; Draxler, R.; Kondragunta, S.; Zeng, J.; Rolph, G.; Stajner, I.; Manikin, G.

    2009-12-01

    Smoke from wildfire is an important component of fine particle pollution, which is responsible for tens of thousands of premature deaths each year in the US. In Alaska, wildfire smoke is the leading cause of poor air quality in summer. Smoke forecast guidance helps air quality forecasters and the public take steps to limit exposure to airborne particulate matter. A new smoke forecast guidance tool, built by a cross-NOAA team, leverages efforts of NOAA’s partners at the USFS on wildfire emissions information, and with EPA, in coordinating with state/local air quality forecasters. Required operational deployment criteria, in categories of objective verification, subjective feedback, and production readiness, have been demonstrated in experimental testing during 2008-2009, for addition to the operational products in NOAA's National Air Quality Forecast Capability. The Alaska smoke forecast tool is an adaptation of NOAA’s smoke predictions implemented operationally for the lower 48 states (CONUS) in 2007. The tool integrates satellite information on location of wildfires with weather (North American mesoscale model) and smoke dispersion (HYSPLIT) models to produce daily predictions of smoke transport for Alaska, in binary and graphical formats. Hour-by hour predictions at 12km grid resolution of smoke at the surface and in the column are provided each day by 13 UTC, extending through midnight next day. Forecast accuracy and reliability are monitored against benchmark criteria for accuracy and reliability. While wildfire activity in the CONUS is year-round, the intense wildfire activity in AK is limited to the summer. Initial experimental testing during summer 2008 was hindered by unusually limited wildfire activity and very cloudy conditions. In contrast, heavier than average wildfire activity during summer 2009 provided a representative basis (more than 60 days of wildfire smoke) for demonstrating required prediction accuracy. A new satellite observation product

  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

    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...

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

    EPA Science Inventory

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

  2. 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) ...

  3. Impact of AIRS Thermodynamic Profile on Regional Weather Forecast

    NASA Technical Reports Server (NTRS)

    Chou, Shih-Hung; Zavodsky, Brad; Jedlovee, Gary

    2010-01-01

    Prudent assimilation of AIRS thermodynamic profiles and quality indicators can improve initial conditions for regional weather models. AIRS-enhanced analysis has warmer and moister PBL. Forecasts with AIRS profiles are generally closer to NAM analyses than CNTL. Assimilation of AIRS leads to an overall QPF improvement in 6-h accumulated precipitation forecasts. Including AIRS profiles in assimilation process enhances the moist instability and produces stronger updrafts and a better precipitation forecast than the CNTL run.

  4. 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.

  5. Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

    NASA Astrophysics Data System (ADS)

    Mishra, D.; Goyal, P.

    2014-12-01

    Urban air pollution forecasting has emerged as an acute problem in recent years because there are sever environmental degradation due to increase in harmful air pollutants in the ambient atmosphere. In this study, there are different types of statistical as well as artificial intelligence techniques are used for forecasting and analysis of air pollution over Delhi urban area. These techniques are principle component analysis (PCA), multiple linear regression (MLR) and artificial neural network (ANN) and the forecasting are observed in good agreement with the observed concentrations through Central Pollution Control Board (CPCB) at different locations in Delhi. But such methods suffers from disadvantages like they provide limited accuracy as they are unable to predict the extreme points i.e. the pollution maximum and minimum cut-offs cannot be determined using such approach. Also, such methods are inefficient approach for better output forecasting. But with the advancement in technology and research, an alternative to the above traditional methods has been proposed i.e. the coupling of statistical techniques with artificial Intelligence (AI) can be used for forecasting purposes. The coupling of PCA, ANN and fuzzy logic is used for forecasting of air pollutant over Delhi urban area. The statistical measures e.g., correlation coefficient (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA) of the proposed model are observed in better agreement with the all other models. Hence, the coupling of statistical and artificial intelligence can be use for the forecasting of air pollutant over urban area.

  6. 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.

  7. An Evaluation of Real-time Air Quality Forecasts and their Urban Emissions over Eastern Texas During the Summer of 2006 Second Texas Air Quality Study Field Study

    EPA Science Inventory

    Forecasts of ozone (O3) and particulate matter (diameter less than 2.5 µm, PM2.5) from seven air quality forecast models (AQFMs) are statistically evaluated against observations collected during August and September of 2006 (49 days) through the AIRNow netwo...

  8. Simple statistical bias correction techniques greatly improve moderate resolution air quality forecast at station level

    NASA Astrophysics Data System (ADS)

    Curci, Gabriele; Falasca, Serena

    2017-04-01

    Deterministic air quality forecast is routinely carried out at many local Environmental Agencies in Europe and throughout the world by means of eulerian chemistry-transport models. The skill of these models in predicting the ground-level concentrations of relevant pollutants (ozone, nitrogen dioxide, particulate matter) a few days ahead has greatly improved in recent years, but it is not yet always compliant with the required quality level for decision making (e.g. the European Commission has set a maximum uncertainty of 50% on daily values of relevant pollutants). Post-processing of deterministic model output is thus still regarded as a useful tool to make the forecast more reliable. In this work, we test several bias correction techniques applied to a long-term dataset of air quality forecasts over Europe and Italy. We used the WRF-CHIMERE modelling system, which provides operational experimental chemical weather forecast at CETEMPS (http://pumpkin.aquila.infn.it/forechem/), to simulate the years 2008-2012 at low resolution over Europe (0.5° x 0.5°) and moderate resolution over Italy (0.15° x 0.15°). We compared the simulated dataset with available observation from the European Environmental Agency database (AirBase) and characterized model skill and compliance with EU legislation using the Delta tool from FAIRMODE project (http://fairmode.jrc.ec.europa.eu/). The bias correction techniques adopted are, in order of complexity: (1) application of multiplicative factors calculated as the ratio of model-to-observed concentrations averaged over the previous days; (2) correction of the statistical distribution of model forecasts, in order to make it similar to that of the observations; (3) development and application of Model Output Statistics (MOS) regression equations. We illustrate differences and advantages/disadvantages of the three approaches. All the methods are relatively easy to implement for other modelling systems.

  9. Air Quality Modeling and Forecasting over the United States Using WRF-Chem

    NASA Astrophysics Data System (ADS)

    Boxe, C.; Hafsa, U.; Blue, S.; Emmanuel, S.; Griffith, E.; Moore, J.; Tam, J.; Khan, I.; Cai, Z.; Bocolod, B.; Zhao, J.; Ahsan, S.; Gurung, D.; Tang, N.; Bartholomew, J.; Rafi, R.; Caltenco, K.; Rivas, M.; Ditta, H.; Alawlaqi, H.; Rowley, N.; Khatim, F.; Ketema, N.; Strothers, J.; Diallo, I.; Owens, C.; Radosavljevic, J.; Austin, S. A.; Johnson, L. P.; Zavala-Gutierrez, R.; Breary, N.; Saint-Hilaire, D.; Skeete, D.; Stock, J.; Salako, O.

    2016-12-01

    WRF-Chem is the Weather Research and Forecasting (WRF) model coupled with Chemistry. The model simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with the meteorology. The model is used for investigation of regional-scale air quality, field program analysis, and cloud-scale interactions between clouds and chemistry. The development of WRF-Chem is a collaborative effort among the community led by NOAA/ESRL scientists. The Official WRF-Chem web page is located at the NOAA web site. Our model development is closely linked with both NOAA/ESRL and DOE/PNNL efforts. Description of PNNL WRF-Chem model development is located at the PNNL web site as well as the PNNL Aerosol Modeling Testbed. High school and undergraduate students, representative of academic institutions throughout USA's Tri-State Area (New York, New Jersey, Connecticut), set up WRF-Chem on CUNY CSI's High Performance Computing Center. Students learned the back-end coding that governs WRF-Chems structure and the front-end coding that displays visually specified weather simulations and forecasts. Students also investigated the impact, to select baseline simulations/forecasts, due to the reaction, NO2 + OH + M → HOONO + M (k = 9.2 × 10-12 cm3 molecule-1 s-1, Mollner et al. 2010). The reaction of OH and NO2 to form gaseous nitric acid (HONO2) is among the most influential and in atmospheric chemistry. Till a few years prior, its rate coefficient remained poorly determined under tropospheric conditions because of difficulties in making laboratory measurements at 760 torr. These activities fosters student coding competencies and deep insights into weather forecast and air quality.

  10. Urban air quality forecasting based on multi-dimensional collaborative Support Vector Regression (SVR): A case study of Beijing-Tianjin-Shijiazhuang

    PubMed Central

    Liu, Bing-Chun; Binaykia, Arihant; Chang, Pei-Chann; Tiwari, Manoj Kumar; Tsao, Cheng-Chin

    2017-01-01

    Today, China is facing a very serious issue of Air Pollution due to its dreadful impact on the human health as well as the environment. The urban cities in China are the most affected due to their rapid industrial and economic growth. Therefore, it is of extreme importance to come up with new, better and more reliable forecasting models to accurately predict the air quality. This paper selected Beijing, Tianjin and Shijiazhuang as three cities from the Jingjinji Region for the study to come up with a new model of collaborative forecasting using Support Vector Regression (SVR) for Urban Air Quality Index (AQI) prediction in China. The present study is aimed to improve the forecasting results by minimizing the prediction error of present machine learning algorithms by taking into account multiple city multi-dimensional air quality information and weather conditions as input. The results show that there is a decrease in MAPE in case of multiple city multi-dimensional regression when there is a strong interaction and correlation of the air quality characteristic attributes with AQI. Also, the geographical location is found to play a significant role in Beijing, Tianjin and Shijiazhuang AQI prediction. PMID:28708836

  11. Improving Forecast Skill by Assimilation of Quality-controlled AIRS Temperature Retrievals under Partially Cloudy Conditions

    NASA Technical Reports Server (NTRS)

    Reale, O.; Susskind, J.; Rosenberg, R.; Brin, E.; Riishojgaard, L.; Liu, E.; Terry, J.; Jusem, J. C.

    2007-01-01

    The National Aeronautics and Space Administration (NASA) Atmospheric Infrared Sounder (AIRS) on board the Aqua satellite has been long recognized as an important contributor towards the improvement of weather forecasts. At this time only a small fraction of the total data produced by AIRS is being used by operational weather systems. In fact, in addition to effects of thinning and quality control, the only AIRS data assimilated are radiance observations of channels unaffected by clouds. Observations in mid-lower tropospheric sounding AIRS channels are assimilated primarily under completely clear-sky conditions, thus imposing a very severe limitation on the horizontal distribution of the AIRS-derived information. In this work it is shown that the ability to derive accurate temperature profiles from AIRS observations in partially cloud-contaminated areas can be utilized to further improve the impact of AIRS observations in a global model and forecasting system. The analyses produced by assimilating AIRS temperature profiles obtained under partial cloud cover result in a substantially colder representation of the northern hemisphere lower midtroposphere at higher latitudes. This temperature difference has a strong impact, through hydrostatic adjustment, in the midtropospheric geopotential heights, which causes a different representation of the polar vortex especially over northeastern Siberia and Alaska. The AIRS-induced anomaly propagates through the model's dynamics producing improved 5-day forecasts.

  12. A Performance Evaluation of the National Air Quality Forecast Capability for the Summer of 2007

    EPA Science Inventory

    This paper provides a performance evaluation of the real-time, CONUS-scale National Air Quality Forecast Capability (NAQFC), developed collaboratively by the National Oceanic and Atmospheric Administration (NOAA) and Environmental Protection Agency (EPA), that supported, in part,...

  13. Air Pollution Forecasts: An Overview

    PubMed Central

    Bai, Lu; Wang, Jianzhou; Lu, Haiyan

    2018-01-01

    Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies. PMID:29673227

  14. Air Pollution Forecasts: An Overview.

    PubMed

    Bai, Lu; Wang, Jianzhou; Ma, Xuejiao; Lu, Haiyan

    2018-04-17

    Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

  15. 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.

  16. Impact of chemical lateral boundary conditions in a regional air quality forecast model on surface ozone predictions during stratospheric intrusions

    NASA Astrophysics Data System (ADS)

    Pendlebury, Diane; Gravel, Sylvie; Moran, Michael D.; Lupu, Alexandru

    2018-02-01

    A regional air quality forecast model, GEM-MACH, is used to examine the conditions under which a limited-area air quality model can accurately forecast near-surface ozone concentrations during stratospheric intrusions. Periods in 2010 and 2014 with known stratospheric intrusions over North America were modelled using four different ozone lateral boundary conditions obtained from a seasonal climatology, a dynamically-interpolated monthly climatology, global air quality forecasts, and global air quality reanalyses. It is shown that the mean bias and correlation in surface ozone over the course of a season can be improved by using time-varying ozone lateral boundary conditions, particularly through the correct assignment of stratospheric vs. tropospheric ozone along the western lateral boundary (for North America). Part of the improvement in surface ozone forecasts results from improvements in the characterization of near-surface ozone along the lateral boundaries that then directly impact surface locations near the boundaries. However, there is an additional benefit from the correct characterization of the location of the tropopause along the western lateral boundary such that the model can correctly simulate stratospheric intrusions and their associated exchange of ozone from stratosphere to troposphere. Over a three-month period in spring 2010, the mean bias was seen to improve by as much as 5 ppbv and the correlation by 0.1 depending on location, and on the form of the chemical lateral boundary condition.

  17. 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.

  18. 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.

  19. 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.

  20. 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 ...

  1. Improving Forecast Skill by Assimilation of AIRS Temperature Soundings

    NASA Technical Reports Server (NTRS)

    Susskind, Joel; Reale, Oreste

    2010-01-01

    AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The AIRS Version 5 retrieval algorithm, is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates delta T(p) for retrieved quantities and the use of these error estimates for Quality Control. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 deg. latitude X 0.67 deg longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates delta (p) were used as the uncertainty for each measurement in the data assimilation process. We compared forecasts analyses generated from the analyses done by assimilation of AIRS temperature profiles with three different sets of thresholds; Standard, Medium, and Tight. Assimilation of Quality Controlled AIRS temperature profiles significantly improve 5-7 day forecast skill compared to that obtained without the benefit of AIRS data in all of the cases studied. In addition, assimilation of Quality Controlled AIRS temperature soundings performs better than assimilation of AIRS observed radiances. Based on the experiments shown, Tight Quality Control of AIRS temperature profile performs best

  2. Impact of Atmospheric Infrared Sounder (AIRS) Thermodynamic Profiles on Regional Weather Forecasting

    NASA Technical Reports Server (NTRS)

    Chou, Shih-Hung; Zavodsky, Bradley T.; Jedlovee, Gary J.

    2010-01-01

    In data sparse regions, remotely-sensed observations can be used to improve analyses and lead to better forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), provides temperature and moisture profiles with accuracy comparable to that of radiosondes. The purpose of this paper is to describe a procedure to assimilate AIRS thermodynamic profile data into a regional configuration of the Advanced Research Weather Research and Forecasting (WRF-ARW) model using its three-dimension variational (3DVAR) analysis component (WRF-Var). Quality indicators are used to select only the highest quality temperature and moisture profiles for assimilation in both clear and partly cloudy regions. Separate error characteristics for land and water profiles are also used in the assimilation process. Assimilation results indicate that AIRS profiles produce an analysis closer to in situ observations than the background field. Forecasts from a 37-day case study period in the winter of 2007 show that AIRS profile data can lead to improvements in 6-h cumulative precipitation forecasts due to instability added in the forecast soundings by the AIRS profiles. Additionally, in a convective heavy rainfall event from February 2007, assimilation of AIRS profiles produces a more unstable boundary layer resulting in enhanced updrafts in the model. These updrafts produce a squall line and precipitation totals that more closely reflect ground-based observations than a no AIRS control forecast. The location of available high-quality AIRS profiles ahead of approaching storm systems is found to be of paramount importance to the amount of impact the observations will have on the resulting forecasts.

  3. DEA-I: A Globally Configurable Open Source Software Package in Support of Air Quality Forecasts

    NASA Astrophysics Data System (ADS)

    Davies, J.; Strabala, K.; Pierce, R.; Huang, H.; Schiffer, E.

    2012-12-01

    During September 2003, a team of NASA, NOAA, and EPA researchers demonstrated a prototype for using Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth retrievals in daily air quality forecasts; this became known as IDEA (Infusing satellite Data into Environmental Applications). IDEA was part of the NASA Applied Sciences Program strategy to demonstrate practical uses of NASA-sponsored observations from space and predictions. Following its successful demonstration an export version of IDEA, known as IDEA International (IDEA-I), has now been released. IDEA-I supports the Global Earth Observation Systems of Systems (GEOSS) Group on Earth Observations (GEO) Health Societal Benefit Area (SBA) and is being developed within the framework of the GEO Earth Observations in Decision Support Call for Proposals. The vehicle for IDEA-I release is the International MODIS and AIRS (Atmospheric Infrared Sounder) Processing Package (IMAPP), developed at the Space Science and Engineering Center, University of Wisconsin-Madison (SSEC/UW-Madison). IMAPP is a NASA-funded and freely-distributed software package which allows any ground station capable of receiving direct broadcast from Terra or Aqua to produce calibrated and geolocated radiances, and a suite of environmental products, of which the IDEA-I 48-hour forward trajectory prediction of high aerosol events is now a part. IDEA-I provides a tool for linking ground-based and satellite capabilities to support international air quality forecasting activities and is to be demonstrated internationally through user training and impact evaluation via a series of IMAPP workshops. This presentation describes the IMAPP implementation of IDEA-I in terms of its simple installation and configuration, and through examples of its operation in several regions known for periodic high aerosol events.; Screen capture of the University of Wisconsin implementation of the real-time direct broadcast IDEA-I Air Quality monitoring

  4. P.88 Regional Precipitation Forecast with Atmospheric Infrared Sounder (AIRS) Profiles

    NASA Technical Reports Server (NTRS)

    Chou, Shih-Hung; Zavodsky, Bradley; Jedlovec, Gary

    2010-01-01

    Prudent assimulation of AIRS thermodynamic profiles and quality indicators can improve initial conditions for regional weather models. In general, AIRS-enhanced analysis more closely resembles radiosondes than the CNTL; forecasts with AIRS profiles are generally closer to NAM analyses than CNTL for sensible weather parameters (not shown here). Assimilation of AIRS leads to an overall QPF improvement in 6-h accumulated precipitation forecases. Including AIRS profiles in assimilation process enhances the low-level instability and produces stronger updrafts and a better precipitation forecast than the CNTL run.

  5. Survey of air cargo forecasting techniques

    NASA Technical Reports Server (NTRS)

    Kuhlthan, A. R.; Vermuri, R. S.

    1978-01-01

    Forecasting techniques currently in use in estimating or predicting the demand for air cargo in various markets are discussed with emphasis on the fundamentals of the different forecasting approaches. References to specific studies are cited when appropriate. The effectiveness of current methods is evaluated and several prospects for future activities or approaches are suggested. Appendices contain summary type analyses of about 50 specific publications on forecasting, and selected bibliographies on air cargo forecasting, air passenger demand forecasting, and general demand and modalsplit modeling.

  6. Real-Time Bias-Adjusted O3 and PM2.5 Air Quality Index Forecasts and their Performance Evaluations over the Continental United States

    EPA Science Inventory

    The National Air Quality Forecast Capacity (NAQFC) system, which links NOAA's North American Mesoscale (NAM) meteorological model with EPA's Community Multiscale Air Quality (CMAQ) model, provided operational ozone (O3) and experimental fine particular matter (PM2...

  7. Impact of Atmospheric Infrared Sounder (AIRS) Thermodynamic Profiles on Regional Precipitation Forecasting

    NASA Technical Reports Server (NTRS)

    Chou, S.-H.; Zavodsky, B. T.; Jedloved, G. J.

    2010-01-01

    In data sparse regions, remotely-sensed observations can be used to improve analyses and lead to better forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), provides temperature and moisture profiles in clear and cloudy regions with accuracy which approaches that of radiosondes. The purpose of this paper is to describe an approach to assimilate AIRS thermodynamic profile data into a regional configuration of the Advanced Research WRF (ARW) model using WRF-Var. Quality indicators are used to select only the highest quality temperature and moisture profiles for assimilation in clear and partly cloudy regions, and uncontaminated portions of retrievals above clouds in overcast regions. Separate error characteristics for land and water profiles are also used in the assimilation process. Assimilation results indicate that AIRS profiles produce an analysis closer to in situ observations than the background field. Forecasts from a 37-day case study period in the winter of 2007 show that AIRS profile data can lead to improvements in 6-h cumulative precipitation forecasts resulting from improved thermodynamic fields. Additionally, in a convective heavy rainfall event from February 2007, assimilation of AIRS profiles produces a more unstable boundary layer resulting in enhanced updrafts in the model. These updrafts produce a squall line and precipitation totals that more closely reflect ground-based observations than a no AIRS control forecast. The location of available high-quality AIRS profiles ahead of approaching storm systems is found to be of paramount importance to the amount of impact the observations will have on the resulting forecasts.

  8. 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...

  9. 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.

  10. Data Assimilation and Regional Forecasts Using Atmospheric InfraRed Sounder (AIRS) Profiles

    NASA Technical Reports Server (NTRS)

    Chou, Shih-Hung; Zavodsky, Bradley; Jedlovec, Gary

    2009-01-01

    In data sparse regions, remotely-sensed observations can be used to improve analyses, which in turn should lead to better forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), provides temperature and moisture profiles with an accuracy comparable to that of radiosondes. The purpose of this paper is to describe a procedure to optimally assimilate AIRS thermodynamic profiles--obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm-into a regional configuration of the Weather Research and Forecasting (WRF) model using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background field type, a methodology for ingesting AIRS profiles as separate over-land and over-water retrievals with different error characteristics, and utilization of level-by-level quality indicators to select only the highest quality data. The assessment of the impact of the AIRS profiles on WRF-Var analyses will focus on intelligent use of the quality indicators, optimized tuning of the WRF-Var, and comparison of analysis soundings to radiosondes. The analyses will be used to conduct a month-long series of regional forecasts over the continental U.S. The long-tern1 impact of AIRS profiles on forecast will be assessed against verifying radiosonde and stage IV precipitation data.

  11. Data Assimilation and Regional Forecasts using Atmospheric InfraRed Sounder (AIRS) Profiles

    NASA Technical Reports Server (NTRS)

    Zabodsky, Brad; Chou, Shih-Hung; Jedlovec, Gary J.

    2009-01-01

    In data sparse regions, remotely-sensed observations can be used to improve analyses, which in turn should lead to better forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which, together with the Advanced Microwave Sounding Unit (AMSU), provides temperature and moisture profiles with an accuracy comparable to that of radionsondes. The purpose of this poster is to describe a procedure to optimally assimilate AIRS thermodynamic profiles, obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm, into a regional configuration of the Weather Research and Forecasting (WRF) model using WRF-Var. The poster focuses on development of background error covariances for the regional domain and background field type, a methodology for ingesting AIRS profiles as separate over-land and over-water retrievals with different error characteristics, and utilization of level-by-level quality indicators to select only the highest quality data. The assessment of the impact of the AIRS profiles on WRF-Var analyses will focus on intelligent use of the quality indicators, optimized tuning of the WRF-Var, and comparison of analysis soundings to radiosondes. The analyses are used to conduct a month-long series of regional forecasts over the continental U.S. The long-term impact of AIRS profiles on forecast will be assessed against NAM analyses and stage IV precipitation data.

  12. Regional Precipitation Forecast with Atmospheric InfraRed Sounder (AIRS) Profile Assimilation

    NASA Technical Reports Server (NTRS)

    Chou, S.-H.; Zavodsky, B. T.; Jedloved, G. J.

    2010-01-01

    Advanced technology in hyperspectral sensors such as the Atmospheric InfraRed Sounder (AIRS; Aumann et al. 2003) on NASA's polar orbiting Aqua satellite retrieve higher vertical resolution thermodynamic profiles than their predecessors due to increased spectral resolution. Although these capabilities do not replace the robust vertical resolution provided by radiosondes, they can serve as a complement to radiosondes in both space and time. These retrieved soundings can have a significant impact on weather forecasts if properly assimilated into prediction models. Several recent studies have evaluated the performance of specific operational weather forecast models when AIRS data are included in the assimilation process. LeMarshall et al. (2006) concluded that AIRS radiances significantly improved 500 hPa anomaly correlations in medium-range forecasts of the Global Forecast System (GFS) model. McCarty et al. (2009) demonstrated similar forecast improvement in 0-48 hour forecasts in an offline version of the operational North American Mesoscale (NAM) model when AIRS radiances were assimilated at the regional scale. Reale et al. (2008) showed improvements to Northern Hemisphere 500 hPa height anomaly correlations in NASA's Goddard Earth Observing System Model, Version 5 (GEOS-5) global system with the inclusion of partly cloudy AIRS temperature profiles. Singh et al. (2008) assimilated AIRS temperature and moisture profiles into a regional modeling system for a study of a heavy rainfall event during the summer monsoon season in Mumbai, India. This paper describes an approach to assimilate AIRS temperature and moisture profiles into a regional configuration of the Advanced Research Weather Research and Forecasting (WRF-ARW) model using its three-dimensional variational (3DVAR) assimilation system (WRF-Var; Barker et al. 2004). Section 2 describes the AIRS instrument and how the quality indicators are used to intelligently select the highest-quality data for assimilation

  13. Intercomparison of air quality data using principal component analysis, and forecasting of PM₁₀ and PM₂.₅ concentrations using artificial neural networks, in Thessaloniki and Helsinki.

    PubMed

    Voukantsis, Dimitris; Karatzas, Kostas; Kukkonen, Jaakko; Räsänen, Teemu; Karppinen, Ari; Kolehmainen, Mikko

    2011-03-01

    In this paper we propose a methodology consisting of specific computational intelligence methods, i.e. principal component analysis and artificial neural networks, in order to inter-compare air quality and meteorological data, and to forecast the concentration levels for environmental parameters of interest (air pollutants). We demonstrate these methods to data monitored in the urban areas of Thessaloniki and Helsinki in Greece and Finland, respectively. For this purpose, we applied the principal component analysis method in order to inter-compare the patterns of air pollution in the two selected cities. Then, we proceeded with the development of air quality forecasting models for both studied areas. On this basis, we formulated and employed a novel hybrid scheme in the selection process of input variables for the forecasting models, involving a combination of linear regression and artificial neural networks (multi-layer perceptron) models. The latter ones were used for the forecasting of the daily mean concentrations of PM₁₀ and PM₂.₅ for the next day. Results demonstrated an index of agreement between measured and modelled daily averaged PM₁₀ concentrations, between 0.80 and 0.85, while the kappa index for the forecasting of the daily averaged PM₁₀ concentrations reached 60% for both cities. Compared with previous corresponding studies, these statistical parameters indicate an improved performance of air quality parameters forecasting. It was also found that the performance of the models for the forecasting of the daily mean concentrations of PM₁₀ was not substantially different for both cities, despite the major differences of the two urban environments under consideration. Copyright © 2011 Elsevier B.V. All rights reserved.

  14. Improving Air Quality Forecasts with AURA Observations

    NASA Technical Reports Server (NTRS)

    Newchurch, M. J.; Biazer, A.; Khan, M.; Koshak, W. J.; Nair, U.; Fuller, K.; Wang, L.; Parker, Y.; Williams, R.; Liu, X.

    2008-01-01

    Past studies have identified model initial and boundary conditions as sources of reducible errors in air-quality simulations. In particular, improving the initial condition improves the accuracy of short-term forecasts as it allows for the impact of local emissions to be realized by the model and improving boundary conditions improves long range transport through the model domain, especially in recirculating anticyclones. During the August 2006 period, we use AURA/OMI ozone measurements along with MODIS and CALIPSO aerosol observations to improve the initial and boundary conditions of ozone and Particulate Matter. Assessment of the model by comparison of the control run and satellite assimilation run to the IONS06 network of ozonesonde observations, which comprise the densest ozone sounding campaign ever conducted in North America, to AURA/TES ozone profile measurements, and to the EPA ground network of ozone and PM measurements will show significant improvement in the CMAQ calculations that use AURA initial and boundary conditions. Further analyses of lightning occurrences from ground and satellite observations and AURA/OMI NO2 column abundances will identify the lightning NOx signal evident in OMI measurements and suggest pathways for incorporating the lightning and NO2 data into the CMAQ simulations.

  15. Ensemble and Bias-Correction Techniques for Air-Quality Model Forecasts of Surface O3 and PM2.5 during the TEXAQS-II Experiment of 2006

    EPA Science Inventory

    Several air quality forecasting ensembles were created from seven models, running in real-time during the 2006 Texas Air Quality (TEXAQS-II) experiment. These multi-model ensembles incorporated a diverse set of meteorological models, chemical mechanisms, and emission inventories...

  16. 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').

  17. The Impact of Atmospheric InfraRed Sounder (AIRS) Profiles on Short-term Weather Forecasts

    NASA Technical Reports Server (NTRS)

    Chou, Shih-Hung; Zavodsky, Brad; Jedlovec, Gary J.; Lapenta, William

    2007-01-01

    The Atmospheric Infrared Sounder (AIRS), together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced spacebased atmospheric sounding systems. The combined AlRS/AMSU system provides radiance measurements used to retrieve temperature profiles with an accuracy of 1 K over 1 km layers under both clear and partly cloudy conditions, while the accuracy of the derived humidity profiles is 15% in 2 km layers. Critical to the successful use of AIRS profiles for weather and climate studies is the use of profile quality indicators and error estimates provided with each profile Aside form monitoring changes in Earth's climate, one of the objectives of AIRS is to provide sounding information of sufficient accuracy such that the assimilation of the new observations, especially in data sparse region, will lead to an improvement in weather forecasts. The purpose of this paper is to describe a procedure to optimally assimilate highresolution AIRS profile data in a regional analysis/forecast model. The paper will focus on the impact of AIRS profiles on a rapidly developing east coast storm and will also discuss preliminary results for a 30-day forecast period, simulating a quasi-operation environment. Temperature and moisture profiles were obtained from the prototype version 5.0 EOS science team retrieval algorithm which includes explicit error information for each profile. The error profile information was used to select the highest quality temperature and moisture data for every profile location and pressure level for assimilation into the ARPS Data Analysis System (ADAS). The AIRS-enhanced analyses were used as initial fields for the Weather Research and Forecast (WRF) system used by the SPORT project for regional weather forecast studies. The ADASWRF system will be run on CONUS domain with an emphasis on the east coast. The preliminary assessment of the impact of the AIRS profiles will focus on quality control issues associated with AIRS

  18. 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

  19. ManUniCast: A Community Weather and Air-Quality Forecasting Teaching Portal

    NASA Astrophysics Data System (ADS)

    Schultz, David M.; Anderson, Stuart; Fairman, Jonathan G.; Lowe, Douglas; McFiggans, Gordon; Lee, Elsa; Seo-Zindy, Ryo

    2014-05-01

    Manunicast was borne out of the needs of our teaching program: students were entering a world where environmental prediction via numerical model was an essential skill, but were not exposed to the production or output of such models. Our site is an educational testbed to explain to students and the public how weather, air-quality, and air-chemistry forecasts are made using real-time predictions as examples. As far as we know, this site provides the first freely available real-time predictions for the UK. We perform two simulations a day over three domains using the most popular, freely available, community atmospheric mesoscale and chemistry models WRF-ARW and WRF-Chem: 1. a WRF-ARW domain over the North Atlantic and western Europe (20-km horizontal grid spacing) 2. a WRF-ARW domain over the UK and Ireland (4-km grid spacing, nested within the 20-km domain) 3. a WRF-Chem domain over the UK and Ireland (12-km grid spacing) Called ManUniCast (Manchester University Forecast), we offer a suite of products from horizontal maps, time series at stations (meteograms), skew-T-logp charts, and cross sections to help students better visualize the weather and the relationships between the various fields more effectively, specifically through the ability to overlay and fade between different plotted products. This presentation discusses how we funded and built ManUniCast, the struggles we faced, and its use in our classes.

  20. A Study on the Potential Applications of Satellite Data in Air Quality Monitoring and Forecasting

    NASA Technical Reports Server (NTRS)

    Li, Can; Hsu, N. Christina; Tsay, Si-Chee

    2011-01-01

    In this study we explore the potential applications of MODIS (Moderate Resolution Imaging Spectroradiometer) -like satellite sensors in air quality research for some Asian regions. The MODIS aerosol optical thickness (AOT), NCEP global reanalysis meteorological data, and daily surface PM(sub 10) concentrations over China and Thailand from 2001 to 2009 were analyzed using simple and multiple regression models. The AOT-PM(sub 10) correlation demonstrates substantial seasonal and regional difference, likely reflecting variations in aerosol composition and atmospheric conditions, Meteorological factors, particularly relative humidity, were found to influence the AOT-PM(sub 10) relationship. Their inclusion in regression models leads to more accurate assessment of PM(sub 10) from space borne observations. We further introduced a simple method for employing the satellite data to empirically forecast surface particulate pollution, In general, AOT from the previous day (day 0) is used as a predicator variable, along with the forecasted meteorology for the following day (day 1), to predict the PM(sub 10) level for day 1. The contribution of regional transport is represented by backward trajectories combined with AOT. This method was evaluated through PM(sub 10) hindcasts for 2008-2009, using ohservations from 2005 to 2007 as a training data set to obtain model coefficients. For five big Chinese cities, over 50% of the hindcasts have percentage error less than or equal to 30%. Similar performance was achieved for cities in northern Thailand. The MODIS AOT data are responsible for at least part of the demonstrated forecasting skill. This method can be easily adapted for other regions, but is probably most useful for those having sparse ground monitoring networks or no access to sophisticated deterministic models. We also highlight several existing issues, including some inherent to a regression-based approach as exemplified by a case study for Beijing, Further studies will be

  1. 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.

  2. OPERATIONAL AND DIAGNOSTIC EVALUATION OF THE OZONE FORECASTS BY THE ETA-CMAQ MODEL SUITE DURING THE 2002 NEW ENGLAND AIR QUALITY STUDY (NEAQS)

    EPA Science Inventory

    Ozone (O3), a secondary pollutant, is created in part by emissions from anthropogenic and biogenic sources. It is necessary for local air quality agencies to accurately forecast ozone concentrations to warn the public of unhealthy air and to encourage people to volunta...

  3. Improving GEOS-5 seven day forecast skill by assimilation of quality controlled AIRS temperature profiles

    NASA Astrophysics Data System (ADS)

    Susskind, J.; Rosenberg, R. I.

    2016-12-01

    The GEOS-5 Data Assimilation System (DAS) generates a global analysis every six hours by combining the previous six hour forecast for that time period with contemporaneous observations. These observations include in-situ observations as well as those taken by satellite borne instruments, such as AIRS/AMSU on EOS Aqua and CrIS/ATMS on S-NPP. Operational data assimilation methodology assimilates observed channel radiances Ri for IR sounding instruments such as AIRS and CrIS, but only for those channels i in a given scene whose radiances are thought to be unaffected by clouds. A limitation of this approach is that radiances in most tropospheric sounding channels are affected by clouds under partial cloud cover conditions, which occurs most of the time. The AIRS Science Team Version-6 retrieval algorithm generates cloud cleared radiances (CCR's) for each channel in a given scene, which represent the radiances AIRS would have observed if the scene were cloud free, and then uses them to determine quality controlled (QC'd) temperature profiles T(p) under all cloud conditions. There are potential advantages to assimilate either AIRS QC'd CCR's or QC'd T(p) instead of Ri in that the spatial coverage of observations is greater under partial cloud cover. We tested these two alternate data assimilation approaches by running three parallel data assimilation experiments over different time periods using GEOS-5. Experiment 1 assimilated all observations as done operationally, Experiment 2 assimilated QC'd values of AIRS CCRs in place of AIRS radiances, and Experiment 3 assimilated QC'd values of T(p) in place of observed radiances. Assimilation of QC'd AIRS T(p) resulted in significant improvement in seven day forecast skill compared to assimilation of CCR's or assimilation of observed radiances, especially in the Southern Hemisphere Extra-tropics.

  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. Emissions Inventory of Anthropogenic PM2.5 and PM10 in Mega city, Delhi, India for Air Quality Forecasting during CWG- 2010

    NASA Astrophysics Data System (ADS)

    Sahu, S.; Beig, G.; Schultz, M.; Parkhi, N.; Stein, O.

    2012-04-01

    The mega city of Delhi is the second largest urban agglomeration in India with 16.7 mio. inhabitants. Delhi has the highest per capita power consumption of electricity in India and the demand has risen by more than 50% during the last decade. Emissions from commercial, power, domestic and industrial sectors have strongly increased causing more and more environmental problems due to air pollution and its adverse impacts on human health. Particulate matter (PM) of size less than 2.5-micron (PM2.5) and 10 micron (PM10) have emerged as primary pollutants of concern due to their adverse impact on human health. As part of the System of Air quality Forecasting and Research (SAFAR) project developed for air quality forecasting during the Commonwealth Games (CWG) - 2010, a high resolution Emission Inventory (EI) of PM10 and PM2.5 has been developed for the metropolitan city Delhi for the year 2010. The comprehensive inventory involves detailed activity data and has been developed for a domain of 70km×65km with a 1.67km×1.67km resolution covering Delhi and its surrounding region (i.e. National Capital Region (NCR)). In creating this inventory, Geographical Information System (GIS) based techniques were used for the first time in India. The major sectors considered are, transport, thermal power plants, industries, residential and commercial cooking along with windblown road dust which is found to play a major role for the megacity environment. Extensive surveys were conducted among the Delhi slum dwellers (Jhuggi) in order to obtain more robust estimates for the activity data related to domestic cooking and heating. Total emissions of PM10 and PM2.5 including wind blown dust over the study area are found to be 236 Gg/yr and 94 Gg/yr respectively. About half of the PM10 emissions stem from windblown road dust. The new emission inventory has been used for regional air quality forecasts in the Delhi region during the Commonwealth games (SAFAR project), and they will soon be

  6. Use of Quality Controlled AIRS Temperature Soundings to Improve Forecast Skill

    NASA Technical Reports Server (NTRS)

    Susskind, Joel; Reale, Oreste; Iredell, Lena

    2010-01-01

    on use of a Standard profile dependent threshold (Delta)T(p). These Standard thresholds were designed as a compromise between optimal use for data assimilation purposes, which requires highest accuracy (tighter Quality Control), and climate purposes, which requires more spatial coverage (looser Quality Control). Subsequent research using Version 5 sounding and error estimates showed that tighter Quality Control performs better for data assimilation proposes, while looser Quality Control better spatial coverage) performs better for climate purposes. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 degree latitude x 0.67 degree longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates (delta)T(p) were used as the uncertainty for each measurement in the data assimilation process.

  7. 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

  8. Improving Regional Forecast by Assimilating Atmospheric InfraRed Sounder (AIRS) Profiles into WRF Model

    NASA Technical Reports Server (NTRS)

    Chou, Shih-Hung; Zavodsky, Brad; Jedlovec, Gary J.

    2009-01-01

    In data sparse regions, remotely-sensed observations can be used to improve analyses and produce improved forecasts. One such source comes from the Atmospheric InfraRed Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced space-based atmospheric sounding systems. The purpose of this paper is to describe a procedure to optimally assimilate high resolution AIRS profile data into a regional configuration of the Advanced Research WRF (ARW) version 2.2 using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background type, and an optimal methodology for ingesting AIRS temperature and moisture profiles as separate overland and overwater retrievals with different error characteristics. The AIRS thermodynamic profiles are derived from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm and contain information about the quality of each temperature layer. The quality indicators were used to select the highest quality temperature and moisture data for each profile location and pressure level. The analyses were then used to conduct a month-long series of regional forecasts over the continental U.S. The long-term impacts of AIRS profiles on forecast were assessed against verifying NAM analyses and stage IV precipitation data.

  9. NCEP Air Quality Forecast(AQF) Graphics

    Science.gov Websites

    NAM-CMAQ Experimental Run predictions 00 03 06 09 12 15 18 21 24 27 30 33 36 39 42 45 48 Select experimental bias correction predictions NAM vs Nest forecasts Change Variable Type: Hourly CMAQ Forecasts

  10. Improving 7-Day Forecast Skill by Assimilation of Retrieved AIRS Temperature Profiles

    NASA Technical Reports Server (NTRS)

    Susskind, Joel; Rosenberg, Bob

    2016-01-01

    We conducted a new set of Data Assimilation Experiments covering the period January 1 to February 29, 2016 using the GEOS-5 DAS. Our experiments assimilate all data used operationally by GMAO (Control) with some modifications. Significant improvement in Global and Southern Hemisphere Extra-tropical 7-day forecast skill was obtained when: We assimilated AIRS Quality Controlled temperature profiles in place of observed AIRS radiances, and also did not assimilate CrISATMS radiances, nor did we assimilate radiosonde temperature profiles or aircraft temperatures. This new methodology did not improve or degrade 7-day Northern Hemispheric Extra-tropical forecast skill. We are conducting experiments aimed at further improving of Northern Hemisphere Extra-tropical forecast skill.

  11. Vegetation Exposure to Ozone over the Continental United States: Assessment of Exposure Indices by the Eta-CMAQ Air Quality Forecast Model

    EPA Science Inventory

    This study presents the first evaluation of the performance of the Eta-CMAQ air quality forecast model to predict a variety of widely used seasonal mean and cumulative O3 exposure indices associated with vegetation using the U.S. AIRNow O3 observations.

  12. 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

  13. Forecasting Foreign Currency Exchange Rates for Air Force Budgeting

    DTIC Science & Technology

    2015-03-26

    FORECASTING FOREIGN CURRENCY EXCHANGE RATES FOR AIR FORCE BUDGETING THESIS MARCH 2015...States. AFIT-ENV-MS-15-M-178 FORECASTING FOREIGN CURRENCY EXCHANGE RATES FOR AIR FORCE BUDGETING THESIS Presented to the Faculty...FORECASTING FOREIGN CURRENCY EXCHANGE RATES FOR AIR FORCE BUDGETING Nicholas R. Gardner, BS Captain, USAF Committee Membership: Lt Col Jonathan

  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. 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.

  16. The FireWork air quality forecast system with near-real-time biomass burning emissions: Recent developments and evaluation of performance for the 2015 North American wildfire season

    PubMed Central

    Pavlovic, Radenko; Chen, Jack; Anderson, Kerry; Moran, Michael D.; Beaulieu, Paul-André; Davignon, Didier; Cousineau, Sophie

    2016-01-01

    ABSTRACT Environment and Climate Change Canada’s FireWork air quality (AQ) forecast system for North America with near-real-time biomass burning emissions has been running experimentally during the Canadian wildfire season since 2013. The system runs twice per day with model initializations at 00 UTC and 12 UTC, and produces numerical AQ forecast guidance with 48-hr lead time. In this work we describe the FireWork system, which incorporates near-real-time biomass burning emissions based on the Canadian Wildland Fire Information System (CWFIS) as an input to the operational Regional Air Quality Deterministic Prediction System (RAQDPS). To demonstrate the capability of the system we analyzed two forecast periods in 2015 (June 2–July 15, and August 15–31) when fire activity was high, and observed fire-smoke-impacted areas in western Canada and the western United States. Modeled PM2.5 surface concentrations were compared with surface measurements and benchmarked with results from the operational RAQDPS, which did not consider near-real-time biomass burning emissions. Model performance statistics showed that FireWork outperformed RAQDPS with improvements in forecast hourly PM2.5 across the region; the results were especially significant for stations near the path of fire plume trajectories. Although the hourly PM2.5 concentrations predicted by FireWork still displayed bias for areas with active fires for these two periods (mean bias [MB] of –7.3 µg m−3 and 3.1 µg m−3), it showed better forecast skill than the RAQDPS (MB of –11.7 µg m−3 and –5.8 µg m−3) and demonstrated a greater ability to capture temporal variability of episodic PM2.5 events (correlation coefficient values of 0.50 and 0.69 for FireWork compared to 0.03 and 0.11 for RAQDPS). A categorical forecast comparison based on an hourly PM2.5 threshold of 30 µg m−3 also showed improved scores for probability of detection (POD), critical success index (CSI), and false alarm rate (FAR

  17. The FireWork air quality forecast system with near-real-time biomass burning emissions: Recent developments and evaluation of performance for the 2015 North American wildfire season.

    PubMed

    Pavlovic, Radenko; Chen, Jack; Anderson, Kerry; Moran, Michael D; Beaulieu, Paul-André; Davignon, Didier; Cousineau, Sophie

    2016-09-01

    Environment and Climate Change Canada's FireWork air quality (AQ) forecast system for North America with near-real-time biomass burning emissions has been running experimentally during the Canadian wildfire season since 2013. The system runs twice per day with model initializations at 00 UTC and 12 UTC, and produces numerical AQ forecast guidance with 48-hr lead time. In this work we describe the FireWork system, which incorporates near-real-time biomass burning emissions based on the Canadian Wildland Fire Information System (CWFIS) as an input to the operational Regional Air Quality Deterministic Prediction System (RAQDPS). To demonstrate the capability of the system we analyzed two forecast periods in 2015 (June 2-July 15, and August 15-31) when fire activity was high, and observed fire-smoke-impacted areas in western Canada and the western United States. Modeled PM2.5 surface concentrations were compared with surface measurements and benchmarked with results from the operational RAQDPS, which did not consider near-real-time biomass burning emissions. Model performance statistics showed that FireWork outperformed RAQDPS with improvements in forecast hourly PM2.5 across the region; the results were especially significant for stations near the path of fire plume trajectories. Although the hourly PM2.5 concentrations predicted by FireWork still displayed bias for areas with active fires for these two periods (mean bias [MB] of -7.3 µg m(-3) and 3.1 µg m(-3)), it showed better forecast skill than the RAQDPS (MB of -11.7 µg m(-3) and -5.8 µg m(-3)) and demonstrated a greater ability to capture temporal variability of episodic PM2.5 events (correlation coefficient values of 0.50 and 0.69 for FireWork compared to 0.03 and 0.11 for RAQDPS). A categorical forecast comparison based on an hourly PM2.5 threshold of 30 µg m(-3) also showed improved scores for probability of detection (POD), critical success index (CSI), and false alarm rate (FAR). Smoke from wildfires

  18. 78 FR 37757 - Revisions to the California State Implementation Plan, South Coast Air Quality Management District

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-06-24

    ... the California State Implementation Plan, South Coast Air Quality Management District AGENCY... the South Coast Air Quality Management District (SCAQMD) portion of the California State... Quality Index rather than on 1-hour ozone forecasted values; (b) forecast criteria for allowing a...

  19. A novel hybrid model for air quality index forecasting based on two-phase decomposition technique and modified extreme learning machine.

    PubMed

    Wang, Deyun; Wei, Shuai; Luo, Hongyuan; Yue, Chenqiang; Grunder, Olivier

    2017-02-15

    The randomness, non-stationarity and irregularity of air quality index (AQI) series bring the difficulty of AQI forecasting. To enhance forecast accuracy, a novel hybrid forecasting model combining two-phase decomposition technique and extreme learning machine (ELM) optimized by differential evolution (DE) algorithm is developed for AQI forecasting in this paper. In phase I, the complementary ensemble empirical mode decomposition (CEEMD) is utilized to decompose the AQI series into a set of intrinsic mode functions (IMFs) with different frequencies; in phase II, in order to further handle the high frequency IMFs which will increase the forecast difficulty, variational mode decomposition (VMD) is employed to decompose the high frequency IMFs into a number of variational modes (VMs). Then, the ELM model optimized by DE algorithm is applied to forecast all the IMFs and VMs. Finally, the forecast value of each high frequency IMF is obtained through adding up the forecast results of all corresponding VMs, and the forecast series of AQI is obtained by aggregating the forecast results of all IMFs. To verify and validate the proposed model, two daily AQI series from July 1, 2014 to June 30, 2016 collected from Beijing and Shanghai located in China are taken as the test cases to conduct the empirical study. The experimental results show that the proposed hybrid model based on two-phase decomposition technique is remarkably superior to all other considered models for its higher forecast accuracy. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Forecasting daily source air quality using multivariate statistical analysis and radial basis function networks.

    PubMed

    Sun, Gang; Hoff, Steven J; Zelle, Brian C; Nelson, Minda A

    2008-12-01

    It is vital to forecast gas and particle matter concentrations and emission rates (GPCER) from livestock production facilities to assess the impact of airborne pollutants on human health, ecological environment, and global warming. Modeling source air quality is a complex process because of abundant nonlinear interactions between GPCER and other factors. The objective of this study was to introduce statistical methods and radial basis function (RBF) neural network to predict daily source air quality in Iowa swine deep-pit finishing buildings. The results show that four variables (outdoor and indoor temperature, animal units, and ventilation rates) were identified as relative important model inputs using statistical methods. It can be further demonstrated that only two factors, the environment factor and the animal factor, were capable of explaining more than 94% of the total variability after performing principal component analysis. The introduction of fewer uncorrelated variables to the neural network would result in the reduction of the model structure complexity, minimize computation cost, and eliminate model overfitting problems. The obtained results of RBF network prediction were in good agreement with the actual measurements, with values of the correlation coefficient between 0.741 and 0.995 and very low values of systemic performance indexes for all the models. The good results indicated the RBF network could be trained to model these highly nonlinear relationships. Thus, the RBF neural network technology combined with multivariate statistical methods is a promising tool for air pollutant emissions modeling.

  1. NCEP Air Quality Forecast(AQF) Graphics

    Science.gov Websites

    Forecasts CMAQ PM Bias Corr. Forecasts Change Plot Type: Comparison plots Difference plots Year: 2018 2017 2016 2015 Month: Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Day: 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Select Cycle: 06Z 12Z Select Region

  2. Multi-pollutant surface objective analyses and mapping of air quality health index over North America.

    PubMed

    Robichaud, Alain; Ménard, Richard; Zaïtseva, Yulia; Anselmo, David

    2016-01-01

    Air quality, like weather, can affect everyone, but responses differ depending on the sensitivity and health condition of a given individual. To help protect exposed populations, many countries have put in place real-time air quality nowcasting and forecasting capabilities. We present in this paper an optimal combination of air quality measurements and model outputs and show that it leads to significant improvements in the spatial representativeness of air quality. The product is referred to as multi-pollutant surface objective analyses (MPSOAs). Moreover, based on MPSOA, a geographical mapping of the Canadian Air Quality Health Index (AQHI) is also presented which provides users (policy makers, public, air quality forecasters, and epidemiologists) with a more accurate picture of the health risk anytime and anywhere in Canada and the USA. Since pollutants can also behave as passive atmospheric tracers, they provide information about transport and dispersion and, hence, reveal synoptic and regional meteorological phenomena. MPSOA could also be used to build air pollution climatology, compute local and national trends in air quality, and detect systematic biases in numerical air quality (AQ) models. Finally, initializing AQ models at regular time intervals with MPSOA can produce more accurate air quality forecasts. It is for these reasons that the Canadian Meteorological Centre (CMC) in collaboration with the Air Quality Research Division (AQRD) of Environment Canada has recently implemented MPSOA in their daily operations.

  3. AIRS Impact on Analysis and Forecast of an Extreme Rainfall Event (Indus River Valley 2010) with a Global Data Assimilation and Forecast System

    NASA Technical Reports Server (NTRS)

    Reale, O.; Lau, W. K.; Susskind, J.; Rosenberg, R.

    2011-01-01

    A set of data assimilation and forecast experiments are performed with the NASA Global data assimilation and forecast system GEOS-5, to compare the impact of different approaches towards assimilation of Advanced Infrared Spectrometer (AIRS) data on the precipitation analysis and forecast skill. The event chosen is an extreme rainfall episode which occurred in late July 11 2010 in Pakistan, causing massive floods along the Indus River Valley. Results show that the assimilation of quality-controlled AIRS temperature retrievals obtained under partly cloudy conditions produce better precipitation analyses, and substantially better 7-day forecasts, than assimilation of clear-sky radiances. The improvement of precipitation forecast skill up to 7 day is very significant in the tropics, and is caused by an improved representation, attributed to cloudy retrieval assimilation, of two contributing mechanisms: the low-level moisture advection, and the concentration of moisture over the area in the days preceding the precipitation peak.

  4. 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.

  5. 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

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

    EPA Science Inventory

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

  8. Techniques for Forecasting Air Passenger Traffic

    NASA Technical Reports Server (NTRS)

    Taneja, N.

    1972-01-01

    The basic techniques of forecasting the air passenger traffic are outlined. These techniques can be broadly classified into four categories: judgmental, time-series analysis, market analysis and analytical. The differences between these methods exist, in part, due to the degree of formalization of the forecasting procedure. Emphasis is placed on describing the analytical method.

  9. Implementation of Real-Time Bias-Adjusted O3 and PM2.5 Air Quality Forecasts and their Performance Evaluations during 2008 over the Continental United States

    EPA Science Inventory

    The National Oceanic and Atmospheric Administration (NOAA), in partnership with the United States Environmental Protection Agency (EPA), is operationally implementing an Air Quality Forecast (AQF) system. This program, which couples NOAA's North American Mesoscale (NAM) weather p...

  10. Data Assimilation Experiments using Quality Controlled AIRS Version 5 Temperature Soundings

    NASA Technical Reports Server (NTRS)

    SUsskind, Joel

    2008-01-01

    The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains two significant improvements over Version 4: 1) Improved physics allows for use of AIRS observations in the entire 4.3 pm C02 absorption band in the retrieval of temperature profile T(p) during both day and night. Tropospheric sounding 15 pm C02 observations are now used primarily in the generation of cloud cleared radiances Ri. This approach allows for the generation of accurate values of Ri and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by- channel error estimates for Ri. These error estimates are used for quality control of the retrieved products. We have conducted forecast impact experiments assimilating AIRS temperature profiles with different levels of quality control using the NASA GEOS-5 data assimilation system. Assimilation of quality controlled T(p) resulted in significantly improved forecast skill compared to that obtained from analyses obtained when all data used operationally by NCEP, except for AIRS data, is assimilated. We also conducted an experiment assimilating AIRS radiances uncontaminated by clouds, as done Operationally by ECMWF and NCEP. Forecasts resulting from assimilated AIRS radiances were of poorer quality than those obtained assimilating AIRS temperatures.

  11. AIRS Impact on the Analysis and Forecast Track of Tropical Cyclone Nargis in a Global Data Assimilation and Forecasting System

    NASA Technical Reports Server (NTRS)

    Reale, O.; Lau, W.K.; Susskind, J.; Brin, E.; Liu, E.; Riishojgaard, L. P.; Rosenburg, R.; Fuentes, M.

    2009-01-01

    Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. Moreover, the automated analyses of cyclones over the northern Indian Ocean, produced by operational global data assimilation systems (DASs), are generally of inferior quality than in other basins. In this work it is shown that the assimilation of Atmospheric Infrared Sounder (AIRS) temperature retrievals under partial cloudy conditions can significantly impact the representation of the cyclone Nargis (which caused devastating loss of life in Myanmar in May 2008) in a global DAS. Forecasts produced from these improved analyses by a global model produce substantially smaller track errors. The impact of the assimilation of clear-sky radiances on the same DAS and forecasting system is positive, but smaller than the one obtained by ingestion of AIRS retrievals, possibly due to poorer coverage.

  12. Integrating Measurement Based New Knowledge on Wildland Fire Emissions and Chemistry into the AIRPACT Air Quality Forecasting for the Pacific Northwest

    NASA Astrophysics Data System (ADS)

    Nergui, T.; Lee, Y.; Chung, S. H.; Lamb, B. K.; Yokelson, R. J.; Barsanti, K.

    2017-12-01

    A number of chamber and field measurements have shown that atmospheric organic aerosols and their precursors produced from wildfires are significantly underestimated in the emission inventories used for air quality models for various applications such as regulatory strategy development, impact assessments of air pollutants, and air quality forecasting for public health. The AIRPACT real-time air quality forecasting system consistently underestimates surface level fine particulate matter (PM2.5) concentrations in the summer at both urban and rural locations in the Pacific Northwest, primarily result of errors in organic particulate matter. In this work, we implement updated chemical speciation and emission factors based on FLAME-IV (Fourth Fire Lab at Missoula Experiment) and other measurements in the Blue-Sky fire emission model and the SMOKE emission preprocessor; and modified parameters for the secondary organic aerosol (SOA) module in CMAQ chemical transport model of the AIRPACT modeling system. Simulation results from CMAQ version 5.2 which has a better treatment for anthropogenic SOA formation (as a base case) and modified parameterization used for fire emissions and chemistry in the model (fire-soa case) are evaluated against airborne measurements downwind of the Big Windy Complex Fire and the Colockum Tarps Fire, both of which occurred in the Pacific Northwest in summer 2013. Using the observed aerosol chemical composition and mass loadings for organics, nitrate, sulfate, ammonium, and chloride from aircraft measurements during the Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS) and the Biomass Burning Observation Project (BBOP), we assess how new knowledge gained from wildfire measurements improve model predictions for SOA and its contribution to the total mass of PM2.5 concentrations.

  13. 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.

  14. Air pollution forecasting in Ankara, Turkey using air pollution index and its relation to assimilative capacity of the atmosphere.

    PubMed

    Genc, D Deniz; Yesilyurt, Canan; Tuncel, Gurdal

    2010-07-01

    Spatial and temporal variations in concentrations of CO, NO, NO(2), SO(2), and PM(10), measured between 1999 and 2000, at traffic-impacted and residential stations in Ankara were investigated. Air quality in residential areas was found to be influenced by traffic activities in the city. Pollutant ratios were proven to be reliable tracers to differentiate between different sources. Air pollution index (API) of the whole city was calculated to evaluate the level of air quality in Ankara. Multiple linear regression model was developed for forecasting API in Ankara. The correlation coefficients were found to be 0.79 and 0.63 for different time periods. The assimilative capacity of Ankara atmosphere was calculated in terms of ventilation coefficient (VC). The relation between API and VC was investigated and found that the air quality in Ankara was determined by meteorology rather than emissions.

  15. Poor Air Quality Expected for New England on May 17-18, 2017

    EPA Pesticide Factsheets

    New England state air quality forecasters are predicting air quality that is unhealthy for sensitive groups, due to ground-level ozone, in much of CT, northern RI & portions of central and southeastern MA (excluding the Cape and the Islands) for May 17.

  16. EPA AirNow Satellite Data Processor (ASDP) for Improving Air Quality Information

    NASA Astrophysics Data System (ADS)

    White, J. E.; Dickerson, P.; Szykman, J.; Chu, D.; Kondragunta, S.; Zhang, H.; Martin, R. V.; van Donkelaar, A.; Pasch, A. N.; Dye, T. S.; Zahn, P. H.; Haderman, M. D.; DeWinter, J. L.

    2012-12-01

    The US Environmental Protection Agency (EPA) AirNow program provides Air Quality Index (AQI) information to the public, decision-makers, researchers and the media (data and forecasts) mainly for ozone and PM2.5 (particles smaller than 2.5 μm in median diameter). EPA wants to provide the best information available to the public and integrating NASA satellite-derived surface PM2.5 concentrations with ground-level PM2.5 observations has proved promising. The AirNow Satellite Data Processor (ASDP) uses daily PM2.5 estimates and uncertainties derived from average Aqua and Terra MODerate resolution Imaging Spectrometer (MODIS) AOD in near-real-time over the United States and fuses the results with observed PM2.5 measurements to create several air quality products for evaluation. In addition to the description of the AirNow program and the AirNow ASDP, several case studies will be presented to show the value that NASA satellite information adds to maps of air quality.

  17. Evaluation of Air Force and Navy Demand Forecasting Systems

    DTIC Science & Technology

    1994-01-01

    forecasting approach, the Air Force Material Command is questioning the adoption of the Navy’s Statistical Demand Forecasting System ( Gitman , 1994). The...Recoverable Item Process in the Requirements Data Bank System is to manage reparable spare parts ( Gitman , 1994). Although RDB will have the capability of...D062) ( Gitman , 1994). Since a comparison is made to address Air Force concerns, this research only limits its analysis to the range of Air Force

  18. 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 ...

  19. Summary Report for the Workshop on Integrating Climate Change Adaption into Air Quality Decision Making

    EPA Science Inventory

    Over the past few decades, air quality planners have forecasted future air pollution levels based on information about changing emissions from stationary and mobile sources, population trends, transportation demand, natural sources of emissions, and other pressures on air quality...

  20. 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...

  1. 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.

  2. International MODIS and AIRS Processing Package (IMAPP) Implementation of Infusion of Satellite Data into Environmental Applications-International (IDEA-I) for Air Quality Forecasts using Suomi-NPP, Terra and Aqua Aerosol Retrievals

    NASA Astrophysics Data System (ADS)

    Davies, J. E.; Strabala, K.; Pierce, R. B.; Huang, A.

    2016-12-01

    Fine mode aerosols play a significant role in public health through their impact on respiratory and cardiovascular disease. IDEA-I (Infusion of Satellite Data into Environmental Applications-International) is a real-time system for trajectory-based forecasts of aerosol dispersion that can assist in the prediction of poor air quality events. We released a direct broadcast version of IDEA-I for aerosol trajectory forecasts in June 2012 under the International MODIS and AIRS Processing Package (IMAPP). In January 2014 we updated this application with website software to display multi-satellite products. Now we have added VIIRS aerosols from Suomi National Polar-orbiting Partnership (S-NPP). IMAPP is a NASA-funded and freely-distributed software package developed at Space Science and Engineering Center of University of Wisconsin-Madison that has over 2,300 registered users worldwide. With IMAPP, any ground station capable of receiving direct broadcast from Terra or Aqua can produce calibrated and geolocated radiances and a suite of environmental products. These products include MODIS AOD required for IDEA-I. VIIRS AOD for IDEA-I can be generated by Community Satellite Processing Package (CSPP) VIIRS EDR Version 2.0 Software for Suomi NPP. CSPP is also developed and distributed by Space Science & Engineering Center. This presentation describes our updated IMAPP implementation of IDEA-I through an example of its operation in a region known for episodic poor air quality events.

  3. Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

    NASA Technical Reports Server (NTRS)

    Chatterji, Gano B.; Gyarfas, Brett; Chan, William N.; Meyn, Larry A.

    2006-01-01

    the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing

  4. THE SCIENTIFIC BASIS OF NOAA'S AIR QUALITY FORECASTING PROGRAM

    EPA Science Inventory

    For many years, the National Oceanic and Atmospheric Administration (NOAA) has conducted atmospheric research, including chemical and physical measurements, process studies, and the development and evaluation of experimental meteorological and photochemical air quality models. ...

  5. EMC: Air Quality Forecast Home page

    Science.gov Websites

    archive NAM Verification Meteorology Error Time Series EMC NAM Spatial Maps Real Time Mesoscale Analysis Precipitation verification NAQFC VERIFICATION CMAQ Ozone & PM Error Time Series AOD Error Time Series HYSPLIT Smoke forecasts vs GASP satellite Dust and Smoke Error Time Series HYSPLIT WCOSS Upgrade (July

  6. 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.

  7. Development of risk-based air quality management strategies under impacts of climate change.

    PubMed

    Liao, Kuo-Jen; Amar, Praveen; Tagaris, Efthimios; Russell, Armistead G

    2012-05-01

    Climate change is forecast to adversely affect air quality through perturbations in meteorological conditions, photochemical reactions, and precursor emissions. To protect the environment and human health from air pollution, there is an increasing recognition of the necessity of developing effective air quality management strategies under the impacts of climate change. This paper presents a framework for developing risk-based air quality management strategies that can help policy makers improve their decision-making processes in response to current and future climate change about 30-50 years from now. Development of air quality management strategies under the impacts of climate change is fundamentally a risk assessment and risk management process involving four steps: (1) assessment of the impacts of climate change and associated uncertainties; (2) determination of air quality targets; (3) selections of potential air quality management options; and (4) identification of preferred air quality management strategies that minimize control costs, maximize benefits, or limit the adverse effects of climate change on air quality when considering the scarcity of resources. The main challenge relates to the level of uncertainties associated with climate change forecasts and advancements in future control measures, since they will significantly affect the risk assessment results and development of effective air quality management plans. The concept presented in this paper can help decision makers make appropriate responses to climate change, since it provides an integrated approach for climate risk assessment and management when developing air quality management strategies. Development of climate-responsive air quality management strategies is fundamentally a risk assessment and risk management process. The risk assessment process includes quantification of climate change impacts on air quality and associated uncertainties. Risk management for air quality under the impacts of

  8. 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.

  9. Measuring the Air Quality and Transportation Impacts of Infill Development

    EPA Pesticide Factsheets

    This report summarizes three case studies. The analysis shows how standard forecasting tools can be modified to capture at least some of the transportation and air quality benefits of brownfield and infill development.

  10. Potential assessment of the "support vector machine" method in forecasting ambient air pollutant trends.

    PubMed

    Lu, Wei-Zhen; Wang, Wen-Jian

    2005-04-01

    Monitoring and forecasting of air quality parameters are popular and important topics of atmospheric and environmental research today due to the health impact caused by exposing to air pollutants existing in urban air. The accurate models for air pollutant prediction are needed because such models would allow forecasting and diagnosing potential compliance or non-compliance in both short- and long-term aspects. Artificial neural networks (ANN) are regarded as reliable and cost-effective method to achieve such tasks and have produced some promising results to date. Although ANN has addressed more attentions to environmental researchers, its inherent drawbacks, e.g., local minima, over-fitting training, poor generalization performance, determination of the appropriate network architecture, etc., impede the practical application of ANN. Support vector machine (SVM), a novel type of learning machine based on statistical learning theory, can be used for regression and time series prediction and have been reported to perform well by some promising results. The work presented in this paper aims to examine the feasibility of applying SVM to predict air pollutant levels in advancing time series based on the monitored air pollutant database in Hong Kong downtown area. At the same time, the functional characteristics of SVM are investigated in the study. The experimental comparisons between the SVM model and the classical radial basis function (RBF) network demonstrate that the SVM is superior to the conventional RBF network in predicting air quality parameters with different time series and of better generalization performance than the RBF model.

  11. Improving of local ozone forecasting by integrated models.

    PubMed

    Gradišar, Dejan; Grašič, Boštjan; Božnar, Marija Zlata; Mlakar, Primož; Kocijan, Juš

    2016-09-01

    This paper discuss the problem of forecasting the maximum ozone concentrations in urban microlocations, where reliable alerting of the local population when thresholds have been surpassed is necessary. To improve the forecast, the methodology of integrated models is proposed. The model is based on multilayer perceptron neural networks that use as inputs all available information from QualeAria air-quality model, WRF numerical weather prediction model and onsite measurements of meteorology and air pollution. While air-quality and meteorological models cover large geographical 3-dimensional space, their local resolution is often not satisfactory. On the other hand, empirical methods have the advantage of good local forecasts. In this paper, integrated models are used for improved 1-day-ahead forecasting of the maximum hourly value of ozone within each day for representative locations in Slovenia. The WRF meteorological model is used for forecasting meteorological variables and the QualeAria air-quality model for gas concentrations. Their predictions, together with measurements from ground stations, are used as inputs to a neural network. The model validation results show that integrated models noticeably improve ozone forecasts and provide better alert systems.

  12. Status of Air Quality in Central California and Needs for Further Study

    NASA Astrophysics Data System (ADS)

    Tanrikulu, S.; Beaver, S.; Soong, S.; Tran, C.; Jia, Y.; Matsuoka, J.; McNider, R. T.; Biazar, A. P.; Palazoglu, A.; Lee, P.; Wang, J.; Kang, D.; Aneja, V. P.

    2012-12-01

    Ozone and PM2.5 levels frequently exceed NAAQS in central California (CC). Additional emission reductions are needed to attain and maintain the standards there. Agencies are developing cost-effective emission control strategies along with complementary incentive programs to reduce emissions when exceedances are forecasted. These approaches require accurate modeling and forecasting capabilities. A variety of models have been rigorously applied (MM5, WRF, CMAQ, CAMx) over CC. Despite the vast amount of land-based measurements from special field programs and significant effort, models have historically exhibited marginal performance. Satellite data may improve model performance by: establishing IC/BC over outlying areas of the modeling domain having unknown conditions; enabling FDDA over the Pacific Ocean to characterize important marine inflows and pollutant outflows; and filling in the gaps of the land-based monitoring network. BAAQMD, in collaboration with the NASA AQAST, plans to conduct four studies that include satellite-based data in CC air quality analysis and modeling: The first project enhances and refines weather patterns, especially aloft, impacting summer ozone formation. Surface analyses were unable to characterize the strong attenuating effect of the complex terrain to steer marine winds impinging on the continent. The dense summer clouds and fog over the Pacific Ocean form spatial patterns that can be related to the downstream air flows through polluted areas. The goal of this project is to explore, characterize, and quantify these relationships using cloud cover data. Specifically, cloud agreement statistics will be developed using satellite data and model clouds. Model skin temperature predictions will be compared to both MODIS and GOES skin temperatures. The second project evaluates and improves the initial and simulated fields of meteorological models that provide inputs to air quality models. The study will attempt to determine whether a cloud

  13. Data Assimilation Experiments using Quality Controlled AIRS Version 5 Temperature Soundings

    NASA Technical Reports Server (NTRS)

    Susskind, Joel

    2008-01-01

    The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AlRS data. Version 5 contains accurate case-by-case error estimates for most derived products, which are also used for quality control. We have conducted forecast impact experiments assimilating AlRS quality controlled temperature profiles using the NASA GEOS-5 data assimilation system, consisting of the NCEP GSI analysis coupled with the NASA FVGCM. Assimilation of quality controlled temperature profiles resulted in significantly improved forecast skill in both the Northern Hemisphere and Southern Hemisphere Extra-Tropics, compared to that obtained from analyses obtained when all data used operationally by NCEP except for AlRS data is assimilated. Experiments using different Quality Control thresholds for assimilation of AlRS temperature retrievals showed that a medium quality control threshold performed better than a tighter threshold, which provided better overall sounding accuracy; or a looser threshold, which provided better spatial coverage of accepted soundings. We are conducting more experiments to further optimize this balance of spatial coverage and sounding accuracy from the data assimilation perspective. In all cases, temperature soundings were assimilated well below cloud level in partially cloudy cases. The positive impact of assimilating AlRS derived atmospheric temperatures all but vanished when only AIRS stratospheric temperatures were assimilated. Forecast skill resulting from assimilation of AlRS radiances uncontaminated by clouds, instead of AlRS temperature soundings, was only slightly better than that resulting from assimilation of only stratospheric AlRS temperatures. This reduction in forecast skill is most likely the result of significant loss of tropospheric information when only AIRS radiances unaffected by clouds are used in the data assimilation process.

  14. Combination of synoptical-analogous and dynamical methods to increase skill score of monthly air temperature forecasts over Northern Eurasia

    NASA Astrophysics Data System (ADS)

    Khan, Valentina; Tscepelev, Valery; Vilfand, Roman; Kulikova, Irina; Kruglova, Ekaterina; Tischenko, Vladimir

    2016-04-01

    Long-range forecasts at monthly-seasonal time scale are in great demand of socio-economic sectors for exploiting climate-related risks and opportunities. At the same time, the quality of long-range forecasts is not fully responding to user application necessities. Different approaches, including combination of different prognostic models, are used in forecast centers to increase the prediction skill for specific regions and globally. In the present study, two forecasting methods are considered which are exploited in operational practice of Hydrometeorological Center of Russia. One of them is synoptical-analogous method of forecasting of surface air temperature at monthly scale. Another one is dynamical system based on the global semi-Lagrangian model SL-AV, developed in collaboration of Institute of Numerical Mathematics and Hydrometeorological Centre of Russia. The seasonal version of this model has been used to issue global and regional forecasts at monthly-seasonal time scales. This study presents results of the evaluation of surface air temperature forecasts generated with using above mentioned synoptical-statistical and dynamical models, and their combination to potentially increase skill score over Northern Eurasia. The test sample of operational forecasts is encompassing period from 2010 through 2015. The seasonal and interannual variability of skill scores of these methods has been discussed. It was noticed that the quality of all forecasts is highly dependent on the inertia of macro-circulation processes. The skill scores of forecasts are decreasing during significant alterations of synoptical fields for both dynamical and empirical schemes. Procedure of combination of forecasts from different methods, in some cases, has demonstrated its effectiveness. For this study the support has been provided by Grant of Russian Science Foundation (№14-37-00053).

  15. Regional Air Quality forecAST (RAQAST) Over the U.S

    NASA Astrophysics Data System (ADS)

    Yoshida, Y.; Choi, Y.; Zeng, T.; Wang, Y.

    2005-12-01

    A regional chemistry and transport modeling system is used to provide 48-hour forecast of the concentrations of ozone and its precursors over the United States. Meteorological forecast is conducted using the NCAR/Penn State MM5 model. The regional chemistry and transport model simulates the sources, transport, chemistry, and deposition of 24 chemical tracers. The lateral and upper boundary conditions of trace gas concentrations are specified using the monthly mean output from the global GEOS-CHEM model. The initial and boundary conditions for meteorological fields are taken from the NOAA AVN forecast. The forecast has been operational since August, 2003. Model simulations are evaluated using surface, aircraft, and satellite measurements in the A'hindcast' mode. The next step is an automated forecast evaluation system.

  16. 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.

  17. AIR QUALITY FORECAST VERIFICATION USING SATELLITE DATA

    EPA Science Inventory

    NOAA 's operational geostationary satellite retrievals of aerosol optical depths (AODs) were used to verify National Weather Service (NWS) experimental (research mode) particulate matter (PM2.5) forecast guidance issued during the summer 2004 International Consortium for Atmosp...

  18. Influence of Boundary Conditions on Simulated U.S. Air Quality

    EPA Science Inventory

    One of the key inputs to regional-scale photochemical models frequently used in air quality planning and forecasting applications are chemical boundary conditions representing background pollutant concentrations originating outside the regional modeling domain. A number of studie...

  19. Improving short-term air quality predictions over the U.S. using chemical data assimilation

    NASA Astrophysics Data System (ADS)

    Kumar, R.; Delle Monache, L.; Alessandrini, S.; Saide, P.; Lin, H. C.; Liu, Z.; Pfister, G.; Edwards, D. P.; Baker, B.; Tang, Y.; Lee, P.; Djalalova, I.; Wilczak, J. M.

    2017-12-01

    State and local air quality forecasters across the United States use air quality forecasts from the National Air Quality Forecasting Capability (NAQFC) at the National Oceanic and Atmospheric Administration (NOAA) as one of the key tools to protect the public from adverse air pollution related health effects by dispensing timely information about air pollution episodes. This project funded by the National Aeronautics and Space Administration (NASA) aims to enhance the decision-making process by improving the accuracy of NAQFC short-term predictions of ground-level particulate matter of less than 2.5 µm in diameter (PM2.5) by exploiting NASA Earth Science Data with chemical data assimilation. The NAQFC is based on the Community Multiscale Air Quality (CMAQ) model. To improve the initialization of PM2.5 in CMAQ, we developed a new capability in the community Gridpoint Statistical Interpolation (GSI) system to assimilate Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals in CMAQ. Specifically, we developed new capabilities within GSI to read/write CMAQ data, a forward operator that calculates AOD at 550 nm from CMAQ aerosol chemical composition and an adjoint of the forward operator that translates the changes in AOD to aerosol chemical composition. A generalized background error covariance program called "GEN_BE" has been extended to calculate background error covariance using CMAQ output. The background error variances are generated using a combination of both emissions and meteorological perturbations to better capture sources of uncertainties in PM2.5 simulations. The newly developed CMAQ-GSI system is used to perform daily 24-h PM2.5 forecasts with and without data assimilation from 15 July to 14 August 2014, and the resulting forecasts are compared against AirNOW PM2.5 measurements at 550 stations across the U. S. We find that the assimilation of MODIS AOD retrievals improves initialization of the CMAQ model

  20. 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.

  1. 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

  2. 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

  3. 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

  4. Sensitivity of Short-Term Weather Forecasts to Assimilated AIRS Data: Implications for NPOESS Applications

    NASA Technical Reports Server (NTRS)

    Zavodsky, Bradley; McCarty, Will; Chou, Shih-Hung; Jedlovec, Gary

    2009-01-01

    The Atmospheric Infrared Sounder (AIRS) is acting as a heritage and risk reduction instrument for the Cross-track lnfrared Sounder (CrIS) to be flown aboard the NPP and NPOESS satellites. The hyperspectral nature of AIRS and CrIS provides high-quality soundings that, along with their asynoptic observation time over North America, make them attractive sources to fill the spatial and temporal data voids in upper air temperature and moisture measurements for use in data assimilation and numerical weather prediction. Observations from AlRS can be assimilated either as direct radiances or retrieved thermodynamic profiles, and the Short-Term Prediction Research and Transition (SPORT) Center at NASA's Marshall Space Flight Center has used both data types to improve short-term (0-48h), regional forecasts. The purpose of this paper is to share SPORT'S experiences using AlRS radiances and retrieved profiles in regional data assimilation activities by showing that proper handling of issues-including cloud contamination and land emissivity characterization-are necessary to produce optimal analyses and forecasts.

  5. 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.

  6. 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.

  7. 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.

  8. Eta-CMAQ Air Quality Forecasts for O3 and Related Species Using Three Different Photochemical Mechanisms (CB4, CB05, SAPRC-99): Comparisons with Measurements During the 2004 ICARTT Study

    EPA Science Inventory

    In this study, we compare the CB4, CB05 and SAPRC-99 mechanisms by examining the impact of these different chemical mechanisms on the Eta-CMAQ air quality forecast model simulations for O3 and its related precursors over the eastern US through comparisons with the inte...

  9. Space-Time Urban Air Pollution Forecasts

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    variograms. The dataset used consists of PM10 concentrations recorded hourly by 12 monitoring stations within the Lisbon's area, for the period 2002-2006. In addition, meteorological data recorded at 3 monitoring stations and boundary layer height (BLH) daily values from the ECMWF (European Centre for Medium Weather Forecast), ERA Interim, were also used. Based on the large-scale standard pressure fields from the ERA40/ECMWF, prevailing circulation patterns at regional scale where determined and used on the construction of the models. After the daily forecasts were produced, the difference between the average maps based on real observations and predicted values were determined and the model's performance was assessed. Based on the analysis of the results, we conclude that the proposed approach shows to be a very promising alternative for urban air quality characterization because of its good results and simplicity of application.

  10. 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

  11. Field validation of speed estimation techniques for air quality conformity analysis.

    DOT National Transportation Integrated Search

    2004-01-01

    The air quality conformity analysis process requires the estimation of speeds for a horizon year on a link-by-link basis where only a few future roadway characteristics, such as forecast volume and capacity, are known. Accordingly, the Virginia Depar...

  12. High-resolution visibility and air quality forecasting using multi-layer urban canopy model for highly urbanized Hong Kong and the Pearl River Delta

    NASA Astrophysics Data System (ADS)

    Piu NG, Chak; HAO, Song; Fat LAM, Yun

    2015-04-01

    Visibility is a universally critical element which affects the public in many aspects, including economic activities, health of local citizens and safety of marine transportation and aviation. The Interagency Monitoring of Protected Visual Environments (IMPROVE) visibility equation, an empirical equation developed by USEPA, has been modified by various studies to fit into the application upon the Asian continent including Hong Kong and China. Often these studies focused on the improvement of the existing IMPROVE equation by modifying its particulate speciation using local observation data. In this study, we developed an Integrated Forecast System (IFS) to predict the next-day air quality and visibility using Weather Research and Forecasting model with Building Energy Parameterization and Building Energy Model (WRF-BEP+BEM) and Community Multi-scale Air Quality Model (CMAQ). Unlike the other studies, the core of this study is to include detailed urbanization impacts with calibrated "IMPROVE equation for PRD" into the modeling system for Hong Kong's environs. The ultra-high resolution land cover information (~1km x 1km) from Google images, was digitized into the Geographic Information System (GIS) for preparing the model-ready input for IFS. The NCEP FNL (Final) Operation Global Analysis (FNL) and the Global Forecasting System (GFS) datasets were tested for both hind-cast and forecast cases, in order to calibrate the input of urban parameters in the WRF-BEP+BEM model. The evaluation of model performance with sensitivity cases was performed on sea surface temperature (SST), surface temperature (T), wind speed/direction with the major pollutants (i.e., PM10, PM2.5, NOx, SO2 and O3) using local observation and will be presented/discussed in this paper. References: 1. Y. L. Lee, R. Sequeira, Visibility degradation across Hong Kong its components and their relative contribution. Atmospheric Environment 2001, 35, 5861-5872. doi:10.1016/S1352-2310(01)00395-8 2. R. Zhang, Q

  13. 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.

  14. Data Assimilation Experiments Using Quality Controlled AIRS Version 5 Temperature Soundings

    NASA Technical Reports Server (NTRS)

    Susskind, Joel

    2009-01-01

    The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains a number of significant improvements over Version 4. Two very significant improvements are described briefly below. 1) The AIRS Science Team Radiative Transfer Algorithm (RTA) has now been upgraded to accurately account for effects of non-local thermodynamic equilibrium on the AIRS observations. This allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval algorithm during both day and night. Following theoretical considerations, tropospheric temperature profile information is obtained almost exclusively from clear column radiances in the 4.3 micron CO2 band in the AIRS Version 5 temperature profile retrieval step. These clear column radiances are a derived product that are indicative of radiances AIRS channels would have seen if the field of view were completely clear. Clear column radiances for all channels are determined using tropospheric sounding 15 micron CO2 observations. This approach allows for the generation of accurate values of clear column radiances and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by-channel clear column radiances. These error estimates are used for quality control of the retrieved products. Based on error estimate thresholds, each temperature profiles is assigned a characteristic pressure, pg, down to which the profile is characterized as good for use for data assimilation purposes. We have conducted forecast impact experiments assimilating AIRS quality controlled temperature profiles using the NASA GEOS-5 data assimilation system, consisting of the NCEP GSI analysis coupled with the

  15. 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

  16. 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.

  17. Performance of stochastic approaches for forecasting river water quality.

    PubMed

    Ahmad, S; Khan, I H; Parida, B P

    2001-12-01

    This study analysed water quality data collected from the river Ganges in India from 1981 to 1990 for forecasting using stochastic models. Initially the box and whisker plots and Kendall's tau test were used to identify the trends during the study period. For detecting the possible intervention in the data the time series plots and cusum charts were used. The three approaches of stochastic modelling which account for the effect of seasonality in different ways. i.e. multiplicative autoregressive integrated moving average (ARIMA) model. deseasonalised model and Thomas-Fiering model were used to model the observed pattern in water quality. The multiplicative ARIMA model having both nonseasonal and seasonal components were, in general, identified as appropriate models. In the deseasonalised modelling approach, the lower order ARIMA models were found appropriate for the stochastic component. The set of Thomas-Fiering models were formed for each month for all water quality parameters. These models were then used to forecast the future values. The error estimates of forecasts from the three approaches were compared to identify the most suitable approach for the reliable forecast. The deseasonalised modelling approach was recommended for forecasting of water quality parameters of a river.

  18. 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 ...

  19. Evaluating the Impact of Atmospheric Infrared Sounder (AIRS) Data On Convective Forecasts

    NASA Technical Reports Server (NTRS)

    Kozlowski, Danielle; Zavodsky, Bradley

    2011-01-01

    The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service (NWS) offices. SPoRT provides real-time NASA products and capabilities to its partners to address specific operational forecast challenges. The mission of SPoRT is to transition observations and research capabilities into operations to help improve short-term weather forecasts on a regional scale. Two areas of focus are data assimilation and modeling, which can to help accomplish SPoRT's programmatic goals of transitioning NASA data to operational users. Forecasting convective weather is one challenge that faces operational forecasters. Current numerical weather prediction (NWP) models that operational forecasters use struggle to properly forecast location, timing, intensity and/or mode of convection. Given the proper atmospheric conditions, convection can lead to severe weather. SPoRT's partners in the National Oceanic and Atmospheric Administration (NOAA) have a mission to protect the life and property of American citizens. This mission has been tested as recently as this 2011 severe weather season, which has seen more than 300 fatalities and injuries and total damages exceeding $10 billion. In fact, during the three day period from 25-27 April, 1,265 storms reports (362 tornado reports) were collected making this three day period one of most active in American history. To address the forecast challenge of convective weather, SPoRT produces a real-time NWP model called the SPoRT Weather Research and Forecasting (SPoRT-WRF), which incorporates unique NASA data sets. One of the NASA assets used in this unique model configuration is retrieved profiles from the Atmospheric Infrared Sounder (AIRS).The goal of this project is to determine the impact that these AIRS profiles have on the SPoRT-WRF forecasts by comparing to a current operational model and a control SPoRT-WRF model

  20. Air Quality Research and Applications Using AURA OMi Data

    NASA Technical Reports Server (NTRS)

    Bhartia, P.K.; Gleason, J.F.; Torres, O.; Levelt, P.; Liu, X.; Ziemke, J.; Chandra, S.; Krotkov, N.

    2007-01-01

    The Ozone Monitoring Instrument (OMI) on EOS Aura is a new generation of satellite remote sensing instrument designed to measure trace gas and aerosol absorption at the UV and blue wavelengths. These measurements are made globally at urban scale resolution with no inter-orbital gaps that make them potentially very useful for air quality research, such as the determination of the sources and processes that affect global and regional air quality, and to develop applications such as air quality forecast. However, the use of satellite data for such applications is not as straight forward as satellite data have been for stratospheric research. There is a need for close interaction between the satellite product developers, in-situ measurement programs, and the air quality research community to overcome some of the inherent difficulties in interpreting data from satellite-based remote sensing instruments. In this talk we will discuss the challenges and opportunities in using OMI products for air quality research and applications. A key conclusion of this work is that to realize the full potential of OMI measurements it will be necessary to combine OMI data with data from instruments such as MLS, MODIS, AIRS, and CALIPSO that are currently flying in the "A-train" satellite constellation. In addition similar data taken by satellites crossing the earth at different local times than the A-train (e.g., the recently MetOp satellite) would need to be processed in a consistent manner to study diurnal variability, and to capture the effects on air quality of rapidly changing events such as wild fires.

  1. An online air pollution forecasting system using neural networks.

    PubMed

    Kurt, Atakan; Gulbagci, Betul; Karaca, Ferhat; Alagha, Omar

    2008-07-01

    In this work, an online air pollution forecasting system for Greater Istanbul Area is developed. The system predicts three air pollution indicator (SO(2), PM(10) and CO) levels for the next three days (+1, +2, and +3 days) using neural networks. AirPolTool, a user-friendly website (http://airpol.fatih.edu.tr), publishes +1, +2, and +3 days predictions of air pollutants updated twice a day. Experiments presented in this paper show that quite accurate predictions of air pollutant indicator levels are possible with a simple neural network. It is shown that further optimizations of the model can be achieved using different input parameters and different experimental setups. Firstly, +1, +2, and +3 days' pollution levels are predicted independently using same training data, then +2 and +3 days are predicted cumulatively using previously days predicted values. Better prediction results are obtained in the cumulative method. Secondly, the size of training data base used in the model is optimized. The best modeling performance with minimum error rate is achieved using 3-15 past days in the training data set. Finally, the effect of the day of week as an input parameter is investigated. Better forecasts with higher accuracy are observed using the day of week as an input parameter.

  2. Selection and Classification Using a Forecast Applicant Pool.

    ERIC Educational Resources Information Center

    Hendrix, William H.

    The document presents a forecast model of the future Air Force applicant pool. By forecasting applicants' quality (means and standard deviations of aptitude scores) and quantity (total number of applicants), a potential enlistee could be compared to the forecasted pool. The data used to develop the model consisted of means, standard deviation, and…

  3. Statistical Correction of Air Temperature Forecasts for City and Road Weather Applications

    NASA Astrophysics Data System (ADS)

    Mahura, Alexander; Petersen, Claus; Sass, Bent; Gilet, Nicolas

    2014-05-01

    The method for statistical correction of air /road surface temperatures forecasts was developed based on analysis of long-term time-series of meteorological observations and forecasts (from HIgh Resolution Limited Area Model & Road Conditions Model; 3 km horizontal resolution). It has been tested for May-Aug 2012 & Oct 2012 - Mar 2013, respectively. The developed method is based mostly on forecasted meteorological parameters with a minimal inclusion of observations (covering only a pre-history period). Although the st iteration correction is based taking into account relevant temperature observations, but the further adjustment of air and road temperature forecasts is based purely on forecasted meteorological parameters. The method is model independent, e.g. it can be applied for temperature correction with other types of models having different horizontal resolutions. It is relatively fast due to application of the singular value decomposition method for matrix solution to find coefficients. Moreover, there is always a possibility for additional improvement due to extra tuning of the temperature forecasts for some locations (stations), and in particular, where for example, the MAEs are generally higher compared with others (see Gilet et al., 2014). For the city weather applications, new operationalized procedure for statistical correction of the air temperature forecasts has been elaborated and implemented for the HIRLAM-SKA model runs at 00, 06, 12, and 18 UTCs covering forecast lengths up to 48 hours. The procedure includes segments for extraction of observations and forecast data, assigning these to forecast lengths, statistical correction of temperature, one-&multi-days statistical evaluation of model performance, decision-making on using corrections by stations, interpolation, visualisation and storage/backup. Pre-operational air temperature correction runs were performed for the mainland Denmark since mid-April 2013 and shown good results. Tests also showed

  4. 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).

  5. Time Relevance of Convective Weather Forecast for Air Traffic Automation

    NASA Technical Reports Server (NTRS)

    Chan, William N.

    2006-01-01

    The Federal Aviation Administration (FAA) is handling nearly 120,000 flights a day through its Air Traffic Management (ATM) system and air traffic congestion is expected to increse substantially over the next 20 years. Weather-induced impacts to throughput and efficiency are the leading cause of flight delays accounting for 70% of all delays with convective weather accounting for 60% of all weather related delays. To support the Next Generation Air Traffic System goal of operating at 3X current capacity in the NAS, ATC decision support tools are being developed to create advisories to assist controllers in all weather constraints. Initial development of these decision support tools did not integrate information regarding weather constraints such as thunderstorms and relied on an additional system to provide that information. Future Decision Support Tools should move towards an integrated system where weather constraints are factored into the advisory of a Decision Support Tool (DST). Several groups such at NASA-Ames, Lincoln Laboratories, and MITRE are integrating convective weather data with DSTs. A survey of current convective weather forecast and observation data show they span a wide range of temporal and spatial resolutions. Short range convective observations can be obtained every 5 mins with longer range forecasts out to several days updated every 6 hrs. Today, the short range forecasts of less than 2 hours have a temporal resolution of 5 mins. Beyond 2 hours, forecasts have much lower temporal. resolution of typically 1 hour. Spatial resolutions vary from 1km for short range to 40km for longer range forecasts. Improving the accuracy of long range convective forecasts is a major challenge. A report published by the National Research Council states improvements for convective forecasts for the 2 to 6 hour time frame will only be achieved for a limited set of convective phenomena in the next 5 to 10 years. Improved longer range forecasts will be probabilistic

  6. California motor vehicle stock, travel and fuel forecast.

    DOT National Transportation Integrated Search

    2009-06-01

    This is the twenty-fourth in a series of reports that forecasts Vehicle Miles of Travel (VMT) in California. This report is intended for transportation planning, travel forecasting, air quality modeling, and fuel tax revenue projection. : This report...

  7. Time Series Forecasting of the Number of Malaysia Airlines and AirAsia Passengers

    NASA Astrophysics Data System (ADS)

    Asrah, N. M.; Nor, M. E.; Rahim, S. N. A.; Leng, W. K.

    2018-04-01

    The standard practice in forecasting process involved by fitting a model and further analysis on the residuals. If we know the distributional behaviour of the time series data, it can help us to directly analyse the model identification, parameter estimation, and model checking. In this paper, we want to compare the distributional behaviour data from the number of Malaysia Airlines (MAS) and AirAsia passenger’s. From the previous research, the AirAsia passengers are govern by geometric Brownian motion (GBM). The data were normally distributed, stationary and independent. Then, GBM was used to forecast the number of AirAsia passenger’s. The same methods were applied to MAS data and the results then were compared. Unfortunately, the MAS data were not govern by GBM. Then, the standard approach in time series forecasting will be applied to MAS data. From this comparison, we can conclude that the number of AirAsia passengers are always in peak season rather than MAS passengers.

  8. Comprehensive evaluation of multi-year real-time air quality forecasting using an online-coupled meteorology-chemistry model over southeastern United States

    NASA Astrophysics Data System (ADS)

    Zhang, Yang; Hong, Chaopeng; Yahya, Khairunnisa; Li, Qi; Zhang, Qiang; He, Kebin

    2016-08-01

    An online-coupled meteorology-chemistry model, WRF/Chem-MADRID, has been deployed for real time air quality forecast (RT-AQF) in southeastern U.S. since 2009. A comprehensive evaluation of multi-year RT-AQF shows overall good performance for temperature and relative humidity at 2-m (T2, RH2), downward surface shortwave radiation (SWDOWN) and longwave radiation (LWDOWN), and cloud fraction (CF), ozone (O3) and fine particles (PM2.5) at surface, tropospheric ozone residuals (TOR) in O3 seasons (May-September), and column NO2 in winters (December-February). Moderate-to-large biases exist in wind speed at 10-m (WS10), precipitation (Precip), cloud optical depth (COT), ammonium (NH4+), sulfate (SO42-), and nitrate (NO3-) from the IMPROVE and SEARCH networks, organic carbon (OC) at IMPROVE, and elemental carbon (EC) and OC at SEARCH, aerosol optical depth (AOD) and column carbon monoxide (CO), sulfur dioxide (SO2), and formaldehyde (HCHO) in both O3 and winter seasons, column nitrogen dioxide (NO2) in O3 seasons, and TOR in winters. These biases indicate uncertainties in the boundary layer and cloud process treatments (e.g., surface roughness, microphysics cumulus parameterization), emissions (e.g., O3 and PM precursors, biogenic, mobile, and wildfire emissions), upper boundary conditions for all major gases and PM2.5 species, and chemistry and aerosol treatments (e.g., winter photochemistry, aerosol thermodynamics). The model shows overall good skills in reproducing the observed multi-year trends and inter-seasonal variability in meteorological and radiative variables such as T2, WS10, Precip, SWDOWN, and LWDOWN, and relatively well in reproducing the observed trends in surface O3 and PM2.5, but relatively poor in reproducing the observed column abundances of CO, NO2, SO2, HCHO, TOR, and AOD. The sensitivity simulations using satellite-constrained boundary conditions for O3 and CO show substantial improvement for both spatial distribution and domain-mean performance

  9. Development of Water Quality Forecasting Models Based on the SOM-ANN on TMDL Unit Watershed in Nakdong River

    NASA Astrophysics Data System (ADS)

    KIM, M.; Kim, J.; Baek, J.; Kim, C.; Shin, H.

    2013-12-01

    It has being happened as flush flood or red/green tide in various natural phenomena due to climate change and indiscreet development of river or land. Especially, water being very important to man should be protected and managed from water quality pollution, and in water resources management, real-time watershed monitoring system is being operated with the purpose of keeping watch and managing on rivers. It is especially important to monitor and forecast water quality in watershed. A study area selected Nak_K as one site among TMDL unit watershed in Nakdong River. This study is to develop a water quality forecasting model connected with making full use of observed data of 8 day interval from Nakdong River Environment Research Center. When forecasting models for each of the BOD, DO, COD, and chlorophyll-a are established considering correlation of various water quality factors, it is needed to select water quality factors showing highly considerable correlation with each water quality factor which is BOD, DO, COD, and chlorophyll-a. For analyzing the correlation of the factors (reservoir discharge, precipitation, air temperature, DO, BOD, COD, Tw, TN, TP, chlorophyll-a), in this study, self-organizing map was used and cross correlation analysis method was also used for comparing results drawn. Based on the results, each forecasting model for BOD, DO, COD, and chlorophyll-a was developed during the short period as 8, 16, 24, 32 days at 8 day interval. The each forecasting model is based on neural network with back propagation algorithm. That is, the study is connected with self-organizing map for analyzing correlation among various factors and neural network model for forecasting of water quality. It is considerably effective to manage the water quality in plenty of rivers, then, it specially is possible to monitor a variety of accidents in water quality. It will work well to protect water quality and to prevent destruction of the environment becoming more and more

  10. Winter wheat quality monitoring and forecasting system based on remote sensing and environmental factors

    NASA Astrophysics Data System (ADS)

    Haiyang, Yu; Yanmei, Liu; Guijun, Yang; Xiaodong, Yang; Dong, Ren; Chenwei, Nie

    2014-03-01

    To achieve dynamic winter wheat quality monitoring and forecasting in larger scale regions, the objective of this study was to design and develop a winter wheat quality monitoring and forecasting system by using a remote sensing index and environmental factors. The winter wheat quality trend was forecasted before the harvest and quality was monitored after the harvest, respectively. The traditional quality-vegetation index from remote sensing monitoring and forecasting models were improved. Combining with latitude information, the vegetation index was used to estimate agronomy parameters which were related with winter wheat quality in the early stages for forecasting the quality trend. A combination of rainfall in May, temperature in May, illumination at later May, the soil available nitrogen content and other environmental factors established the quality monitoring model. Compared with a simple quality-vegetation index, the remote sensing monitoring and forecasting model used in this system get greatly improved accuracy. Winter wheat quality was monitored and forecasted based on the above models, and this system was completed based on WebGIS technology. Finally, in 2010 the operation process of winter wheat quality monitoring system was presented in Beijing, the monitoring and forecasting results was outputted as thematic maps.

  11. New Developments in Wildfire Pollution Forecasting at the Canadian Meteorological Centre

    NASA Astrophysics Data System (ADS)

    Pavlovic, Radenko; Chen, Jack; Munoz-Alpizar, Rodrigo; Davignon, Didier; Beaulieu, Paul-Andre; Landry, Hugo; Menard, Sylvain; Gravel, Sylvie; Moran, Michael

    2017-04-01

    Environment and Climate Change Canada's air quality forecast system with near-real-time wildfire emissions, named FireWork, was developed in 2012 and has been run by the Canadian Meteorological Centre Operations division (CMCO) since 2013. In June 2016 this system was upgraded to operational status and wildfire smoke forecasts for North America are now available to the general public. FireWork's ability to model the transport and diffusion of wildfire smoke plumes has proved to be valuable to regional air quality forecasters and emergency first responders. Some of the most challenging issues with wildfire pollution modelling concern the production of wildfire emission estimates and near-source dispersion within the air quality model. As a consequence, FireWork is undergoing constant development. During the massive Fort McMurray wildfire event in western Canada in May 2016, for example, different wildfire emissions processing approaches and wildfire emissions injection and dispersion schemes were tested within the air quality model. Work on various FireWork components will continue in order to deliver a new operational version of the forecasting system for the 2017 wildfire season. Some of the proposed improvements will be shown in this presentation along with current and planned FireWork post-processing products.

  12. How Clean is your Local Air? Here's an app for that

    NASA Astrophysics Data System (ADS)

    Maskey, M.; Yang, E.; Christopher, S. A.; Keiser, K.; Nair, U. S.; Graves, S. J.

    2011-12-01

    Air quality is a vital element of our environment. Accurate and localized air quality information is critical for characterizing environmental impacts at the local and regional levels. Advances in location-aware handheld devices and air quality modeling have enabled a group of UAHuntsville scientists to develop a mobile app, LocalAQI, that informs users of current conditions and forecasts of up to twenty-four hours, of air quality indices. The air quality index is based on Community Multiscale Air Quality Modeling System (CMAQ). UAHuntsville scientists have used satellite remote sensing products as inputs to CMAQ, resulting in forecast guidance for particulate matter air quality. The CMAQ output is processed to compute a standardized air quality index. Currently, the air quality index is available for the eastern half of the United States. LocalAQI consists of two main views: air quality index view and map view. The air quality index view displays current air quality for the zip code of a location of interest. Air quality index value is translated into a color-coded advisory system. In addition, users are able to cycle through available hourly forecasts for a location. This location-aware app defaults to the current air quality of user's location. The map view displays color-coded air quality information for the eastern US with an ability to animate through the available forecasts. The app is developed using a cross-platform native application development tool, appcelerator; hence LocalAQI is available for iOS and Android-based phones and pads.

  13. Air Quality Monitoring and Forecasting Applications of Suomi NPP VIIRS Aerosol Products

    NASA Astrophysics Data System (ADS)

    Kondragunta, Shobha

    The Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched on October 28, 2011. It provides Aerosol Optical Thickness (AOT) at two different spatial resolutions: a pixel level (~750 m at nadir) product called the Intermediate Product (IP) and an aggregated (~6 km at nadir) product called the Environmental Data Record (EDR), and a Suspended Matter (SM) EDR that provides aerosol type (dust, smoke, sea salt, and volcanic ash) information. An extensive validation of VIIRS best quality aerosol products with ground based L1.5 Aerosol Robotic NETwork (AERONET) data shows that the AOT EDR product has an accuracy/precision of -0.01/0.11 and 0.01/0.08 over land and ocean respectively. Globally, VIIRS mean AOT EDR (0.20) is similar to Aqua MODIS (0.16) with some important regional and seasonal differences. The accuracy of the SM product, however, is found to be very low (20 percent) when compared to Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) and AERONET. Several algorithm updates which include a better approach to retrieve surface reflectance have been developed for AOT retrieval. For dust aerosol type retrieval, a new approach that takes advantage of spectral dependence of Rayleigh scattering, surface reflectance, dust absorption in the deep blue (412 nm), blue (440 nm), and mid-IR (2.2 um) has been developed that detects dust with an accuracy of ~80 percent. For smoke plume identification, a source apportionment algorithm that combines fire hot spots with AOT imagery has been developed that provides smoke plume extent with an accuracy of ~70 percent. The VIIRS aerosol products will provide continuity to the current operational use of aerosol products from Aqua and Terra MODIS. These include aerosol data assimilation in Naval Research Laboratory (NRL) global aerosol model, verification of National Weather Service (NWS) dust and smoke forecasts, exceptional events monitoring by different states

  14. Impact of Ozone Radiative Feedbacks on Global Weather Forecasting

    NASA Astrophysics Data System (ADS)

    Ivanova, I.; de Grandpré, J.; Rochon, Y. J.; Sitwell, M.

    2017-12-01

    A coupled Chemical Data Assimilation system for ozone is being developed at Environment and Climate Change Canada (ECCC) with the goals to improve the forecasting of UV index and the forecasting of air quality with the Global Environmental Multi-scale (GEM) Model for Air quality and Chemistry (MACH). Furthermore, this system provides an opportunity to evaluate the benefit of ozone assimilation for improving weather forecasting with the ECCC Global Deterministic Prediction System (GDPS) for Numerical Weather Prediction (NWP). The present UV index forecasting system uses a statistical approach for evaluating the impact of ozone in clear-sky and cloudy conditions, and the use of real-time ozone analysis and ozone forecasts is highly desirable. Improving air quality forecasting with GEM-MACH further necessitates the development of integrated dynamical-chemical assimilation system. Upon its completion, real-time ozone analysis and ozone forecasts will also be available for piloting the regional air quality system, and for the computation of ozone heating rates, in replacement of the monthly mean ozone distribution currently used in the GDPS. Experiments with ozone radiative feedbacks were run with the GDPS at 25km resolution and 84 levels with a lid at 0.1 hPa and were initialized with ozone analysis that has assimilated total ozone column from OMI, OMPS, and GOME satellite instruments. The results show that the use of prognostic ozone for the computation of the heating/cooling rates has a significant impact on the temperature distribution throughout the stratosphere and upper troposphere regions. The impact of ozone assimilation is especially significant in the tropopause region, where ozone heating in the infrared wavelengths is important and ozone lifetime is relatively long. The implementation of the ozone radiative feedback in the GDPS requires addressing various issues related to model biases (temperature and humidity) and biases in equilibrium state (ozone mixing

  15. INTEGRATION OF SATELLITE, MODELED, AND GROUND BASED AEROSOL DATA FOR USE IN AIR QUALITY AND PUBLIC HEALTH APPLICATIONS ( AGU-BALTIMORE )

    EPA Science Inventory

    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 particulate matter on ...

  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

    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.

  17. 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

  18. 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.

  19. Impacts of air pollutants from fire and non-fire emissions on the regional air quality in Southeast Asia

    NASA Astrophysics Data System (ADS)

    Lee, Hsiang-He; Iraqui, Oussama; Gu, Yefu; Hung-Lam Yim, Steve; Chulakadabba, Apisada; Yiu-Ming Tonks, Adam; Yang, Zhengyu; Wang, Chien

    2018-05-01

    Severe haze events in Southeast Asia caused by particulate pollution have become more intense and frequent in recent years. Widespread biomass burning occurrences and particulate pollutants from human activities other than biomass burning play important roles in degrading air quality in Southeast Asia. In this study, numerical simulations have been conducted using the Weather Research and Forecasting (WRF) model coupled with a chemistry component (WRF-Chem) to quantitatively examine the contributions of aerosols emitted from fire (i.e., biomass burning) versus non-fire (including fossil fuel combustion, and road dust, etc.) sources to the degradation of air quality and visibility over Southeast Asia. These simulations cover a time period from 2002 to 2008 and are driven by emissions from (a) fossil fuel burning only, (b) biomass burning only, and (c) both fossil fuel and biomass burning. The model results reveal that 39 % of observed low-visibility days (LVDs) can be explained by either fossil fuel burning or biomass burning emissions alone, a further 20 % by fossil fuel burning alone, a further 8 % by biomass burning alone, and a further 5 % by a combination of fossil fuel burning and biomass burning. Analysis of an 24 h PM2.5 air quality index (AQI) indicates that the case with coexisting fire and non-fire PM2.5 can substantially increase the chance of AQI being in the moderate or unhealthy pollution level from 23 to 34 %. The premature mortality in major Southeast Asian cities due to degradation of air quality by particulate pollutants is estimated to increase from ˜ 4110 per year in 2002 to ˜ 6540 per year in 2008. In addition, we demonstrate the importance of certain missing non-fire anthropogenic aerosol sources including anthropogenic fugitive and industrial dusts in causing urban air quality degradation. An experiment of using machine learning algorithms to forecast the occurrence of haze events in Singapore is also explored in this study. All of these

  20. Experimental Forecasts of Wildfire Pollution at the Canadian Meteorological Centre

    NASA Astrophysics Data System (ADS)

    Pavlovic, Radenko; Beaulieu, Paul-Andre; Chen, Jack; Landry, Hugo; Cousineau, Sophie; Moran, Michael

    2016-04-01

    Environment and Climate Change Canada's Canadian Meteorological Centre Operations division (CMCO) has been running an experimental North American air quality forecast system with near-real-time wildfire emissions since 2014. This system, named FireWork, also takes anthropogenic and other natural emission sources into account. FireWork 48-hour forecasts are provided to CMCO forecasters and external partners in Canada and the U.S. twice daily during the wildfire season. This system has proven to be very useful in capturing short- and long-range smoke transport from wildfires over North America. Several upgrades to the FireWork system have been made since 2014 to accommodate the needs of operational AQ forecasters and to improve system performance. In this talk we will present performance statistics and some case studies for the 2014 and 2015 wildfire seasons. We will also describe current limitations of the FireWork system and ongoing and future work planned for this air quality forecast system.

  1. 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.

  2. 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/.

  3. Postprocessing for Air Quality Predictions

    NASA Astrophysics Data System (ADS)

    Delle Monache, L.

    2017-12-01

    In recent year, air quality (AQ) forecasting has made significant progress towards better predictions with the goal of protecting the public from harmful pollutants. This progress is the results of improvements in weather and chemical transport models, their coupling, and more accurate emission inventories (e.g., with the development of new algorithms to account in near real-time for fires). Nevertheless, AQ predictions are still affected at times by significant biases which stem from limitations in both weather and chemistry transport models. Those are the result of numerical approximations and the poor representation (and understanding) of important physical and chemical process. Moreover, although the quality of emission inventories has been significantly improved, they are still one of the main sources of uncertainties in AQ predictions. For operational real-time AQ forecasting, a significant portion of these biases can be reduced with the implementation of postprocessing methods. We will review some of the techniques that have been proposed to reduce both systematic and random errors of AQ predictions, and improve the correlation between predictions and observations of ground-level ozone and surface particulate matter less than 2.5 µm in diameter (PM2.5). These methods, which can be applied to both deterministic and probabilistic predictions, include simple bias-correction techniques, corrections inspired by the Kalman filter, regression methods, and the more recently developed analog-based algorithms. These approaches will be compared and contrasted, and strength and weaknesses of each will be discussed.

  4. 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.

  5. 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....

  6. PLAM - a meteorological pollution index for air quality and its applications in fog-haze forecasts in north China

    NASA Astrophysics Data System (ADS)

    Yang, Y.; Wang, J.; Gong, S.; Zhang, X.; Wang, H.; Wang, Y.; Wang, J.; Li, D.; Guo, J.

    2015-03-01

    Using surface meteorological observation and high resolution emission data, this paper discusses the application of PLAM/h Index (Parameter Linking Air-quality to Meteorological conditions/haze) in the prediction of large-scale low visibility and fog-haze events. Based on the two-dimensional probability density function diagnosis model for emissions, the study extends the diagnosis and prediction of the meteorological pollution index PLAM to the regional visibility fog-haze intensity. The results show that combining the influence of regular meteorological conditions and emission factors together in the PLAM/h parameterization scheme is very effective in improving the diagnostic identification ability of the fog-haze weather in North China. The correlation coefficients for four seasons (spring, summer, autumn and winter) between PLAM/h and visibility observation are 0.76, 0.80, 0.96 and 0.86 respectively and all their significance levels exceed 0.001, showing the ability of PLAM/h to predict the seasonal changes and differences of fog-haze weather in the North China region. The high-value correlation zones are respectively located in Jing-Jin-Ji (Beijing, Tianjin, Hebei), Bohai Bay rim and the southern Hebei-northern Henan, indicating that the PLAM/h index has relations with the distribution of frequent heavy fog-haze weather in North China and the distribution of emission high-value zone. Comparatively analyzing the heavy fog-haze events and large-scale fine weather processes in winter and summer, it is found that PLAM/h index 24 h forecast is highly correlated to the visibility observation. Therefore, PLAM/h index has better capability of doing identification, analysis and forecasting.

  7. PLAM - a meteorological pollution index for air quality and its applications in fog-haze forecasts in North China

    NASA Astrophysics Data System (ADS)

    Yang, Y. Q.; Wang, J. Z.; Gong, S. L.; Zhang, X. Y.; Wang, H.; Wang, Y. Q.; Wang, J.; Li, D.; Guo, J. P.

    2016-02-01

    Using surface meteorological observation and high-resolution emission data, this paper discusses the application of the PLAM/h index (Parameter Linking Air-quality to Meteorological conditions/haze) in the prediction of large-scale low visibility and fog-haze events. Based on the two-dimensional probability density function diagnosis model for emissions, the study extends the diagnosis and prediction of the meteorological pollution index PLAM to the regional visibility fog-haze intensity. The results show that combining the influence of regular meteorological conditions and emission factors together in the PLAM/h parameterization scheme is very effective in improving the diagnostic identification ability of the fog-haze weather in North China. The determination coefficients for four seasons (spring, summer, autumn, and winter) between PLAM/h and visibility observation are 0.76, 0.80, 0.96, and 0.86, respectively, and all of their significance levels exceed 0.001, showing the ability of PLAM/h to predict the seasonal changes and differences of fog-haze weather in the North China region. The high-value correlation zones are located in Jing-Jin-Ji (Beijing, Tianjin, Hebei), Bohai Bay rim, and southern Hebei-northern Henan, indicating that the PLAM/h index is related to the distribution of frequent heavy fog-haze weather in North China and the distribution of emission high-value zone. Through comparative analysis of the heavy fog-haze events and large-scale clear-weather processes in winter and summer, it is found that PLAM/h index 24 h forecast is highly correlated with the visibility observation. Therefore, the PLAM/h index has good capability in identification, analysis, and forecasting.

  8. 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.

  9. 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.

  10. 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

  11. Goals of Quality in Doctoral Studies and Forecasted Outcomes

    ERIC Educational Resources Information Center

    Zelvys, Rimantas

    2007-01-01

    This article discusses the quality assurance policy of doctoral studies implemented in Lithuania and its probable outcomes are forecasted. In scientific literature the quality of education is commonly defined as a holistic phenomenon composed of the quality of initial conditions, quality of process and quality of outputs. The accomplished document…

  12. 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.

  13. Quantifying automobile refinishing VOC air emissions - a methodology with estimates and forecasts

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

    Anderson, S.P.; Rubick, C.

    1996-12-31

    Automobile refinishing coatings (referred to as paints), paint thinners, reducers, hardeners, catalysts, and cleanup solvents used during their application, contain volatile organic compounds (VOCs) which are precursors to ground level ozone formation. Some of these painting compounds create hazardous air pollutants (HAPs) which are toxic. This paper documents the methodology, data sets, and the results of surveys (conducted in the fall of 1995) used to develop revised per capita emissions factors for estimating and forecasting the VOC air emissions from the area source category of automobile refinishing. Emissions estimates, forecasts, trends, and reasons for these trends are presented. Future emissionsmore » inventory (EI) challenges are addressed in light of data availability and information networks.« less

  14. 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.

  15. AIRS: Improving Weather Forecasting and Providing New Data on Greenhouse Gases

    NASA Technical Reports Server (NTRS)

    Chahine, Moustafa T.; Pagano, Thomas S.; Aumann, Hartmut H.; Atlas, Robert; Barnet, Christopher; Blaisdell, John; Chen, Luke; Divakarla, Murty; Fetzer, Eric J.; Goldberg, Mitch; hide

    2006-01-01

    This paper discusses the performance of AIRS and examines how it is meeting its operational and research objectives based on the experience of more than 2 yr with AIRS data. We describe the science background and the performance of AIRS in terms of the accuracy and stability of its observed spectral radiances. We examine the validation of the retrieved temperature and water vapor profiles against collocated operational radiosondes, and then we assess the impact thereof on numerical weather forecasting of the assimilation of the AIRS spectra and the retrieved temperature. We close the paper with a discussion on the retrieval of several minor tropospheric constituents from AIRS spectra.

  16. Simulation of air quality impacts from prescribed fires on an urban area.

    PubMed

    Hu, Yongtao; Odman, M Talat; Chang, Michael E; Jackson, William; Lee, Sangil; Edgerton, Eric S; Baumann, Karsten; Russell, Armistead G

    2008-05-15

    On February 28, 2007, a severe smoke event caused by prescribed forest fires occurred in Atlanta, GA. Later smoke events in the southeastern metropolitan areas of the United States caused by the Georgia-Florida wild forest fires further magnified the significance of forest fire emissions and the benefits of being able to accurately predict such occurrences. By using preburning information, we utilize an operational forecasting system to simulate the potential air quality impacts from two large February 28th fires. Our "forecast" predicts that the scheduled prescribed fires would have resulted in over 1 million Atlanta residents being potentially exposed to fine particle matter (PM2.5) levels of 35 microg m(-3) or higher from 4 p.m. to midnight. The simulated peak 1 h PM2.5 concentration is about 121 microg m(-3). Our study suggests that the current air quality forecasting technology can be a useful tool for helping the management of fire activities to protect public health. With postburning information, our "hindcast" predictions improved significantly on timing and location and slightly on peak values. "Hindcast" simulations also indicated that additional isoprenoid emissions from pine species temporarily triggered by the fire could induce rapid ozone and secondary organic aerosol formation during late winter. Results from this study suggest that fire induced biogenic volatile organic compounds emissions missing from current fire emissions estimate should be included in the future.

  17. NCEP Air Quality Forecast(AQF) Verification. NOAA/NWS/NCEP/EMC

    Science.gov Websites

    Southwest Desert All regions PROD All regions PARA Select averaged hour: 8 hr sfc average 1 hr sfc average Select forecast four: Diurnal period 01-24 hr by day 25-48 hr by day Select statistic type: BIAS RMSE

  18. Impact of AIRS Thermodynamic Profiles on Precipitation Forecasts for Atmospheric River Cases Affecting the Western United States

    NASA Technical Reports Server (NTRS)

    Zavodsky, Bradley T.; Jedlovec, Gary J.; Blakenship, Clay B.; Wick, Gary A.; Neiman, Paul J.

    2013-01-01

    This project is a collaborative activity between the NASA Short-term Prediction Research and Transition (SPoRT) Center and the NOAA Hydrometeorology Testbed (HMT) to evaluate a SPoRT Advanced Infrared Sounding Radiometer (AIRS: Aumann et al. 2003) enhanced moisture analysis product. We test the impact of assimilating AIRS temperature and humidity profiles above clouds and in partly cloudy regions, using the three-dimensional variational Gridpoint Statistical Interpolation (GSI) data assimilation (DA) system (Developmental Testbed Center 2012) to produce a new analysis. Forecasts of the Weather Research and Forecasting (WRF) model initialized from the new analysis are compared to control forecasts without the additional AIRS data. We focus on some cases where atmospheric rivers caused heavy precipitation on the US West Coast. We verify the forecasts by comparison with dropsondes and the Cooperative Institute for Research in the Atmosphere (CIRA) Blended Total Precipitable Water product.

  19. Forecasting asthma-related hospital admissions in London using negative binomial models.

    PubMed

    Soyiri, Ireneous N; Reidpath, Daniel D; Sarran, Christophe

    2013-05-01

    Health forecasting can improve health service provision and individual patient outcomes. Environmental factors are known to impact chronic respiratory conditions such as asthma, but little is known about the extent to which these factors can be used for forecasting. Using weather, air quality and hospital asthma admissions, in London (2005-2006), two related negative binomial models were developed and compared with a naive seasonal model. In the first approach, predictive forecasting models were fitted with 7-day averages of each potential predictor, and then a subsequent multivariable model is constructed. In the second strategy, an exhaustive search of the best fitting models between possible combinations of lags (0-14 days) of all the environmental effects on asthma admission was conducted. Three models were considered: a base model (seasonal effects), contrasted with a 7-day average model and a selected lags model (weather and air quality effects). Season is the best predictor of asthma admissions. The 7-day average and seasonal models were trivial to implement. The selected lags model was computationally intensive, but of no real value over much more easily implemented models. Seasonal factors can predict daily hospital asthma admissions in London, and there is a little evidence that additional weather and air quality information would add to forecast accuracy.

  20. 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 (...

  1. The Ozone Monitoring Instrument (OMI): towards a 14 Year Data Record and Applications in the Air Quality and Climate Domain

    NASA Astrophysics Data System (ADS)

    Levelt, P.; Joiner, J.; Tamminen, J.; Veefkind, P.; Bhartia, P. K.; Court, A. J.; Vlemmix, T.

    2017-12-01

    Keywords: emission monitoring, air quality, climate, atmospheric composition The Ozone Monitoring Instrument (OMI), launched on board of NASA's EOS-Aura spacecraft on July 15, 2004, provides unique contributions to the monitoring of the ozone layer, air quality and climate from space. With a data record of 13 years, OMI provides the longest NO2 and SO2 record from space, which is essential to understand the changes to emissions globally. The combination of urban scale resolution (13 x 24 km2 in nadir) and daily global coverage proved to be key features for the air quality community. Due to the operational Very Fast Delivery (VFD / direct readout) and Near Real Time (NRT) availability of the data, OMI also plays an important role in the early developments of operational services in the atmospheric chemistry domain. For example, OMI data is currently used operationally for improving air quality forecasts, for inverting high-resolution emission maps, the UV forecast and for volcanic plume warning systems for aviation. An overview of air quality applications, emission inventory inversions and trend analyses based on the OMI data record will be presented. An outlook will be given on the potentials of augmenting this record with the high resolution air quality measurements of TROPOMI (3,5 x 7 km2) and new satellite instrumentation entering the imaging domain, such as the TROPOLITE instrument ( 1 x 1 km2). Potential of imaging type of NO2 measurements in the the climate and air quality domain will be given, most notably on the use of high resolution NO2 measurements for pin-pointing anthropogenic CO2 emissions.

  2. A novel hybrid forecasting model for PM₁₀ and SO₂ daily concentrations.

    PubMed

    Wang, Ping; Liu, Yong; Qin, Zuodong; Zhang, Guisheng

    2015-02-01

    Air-quality forecasting in urban areas is difficult because of the uncertainties in describing both the emission and meteorological fields. The use of incomplete information in the training phase restricts practical air-quality forecasting. In this paper, we propose a hybrid artificial neural network and a hybrid support vector machine, which effectively enhance the forecasting accuracy of an artificial neural network (ANN) and support vector machine (SVM) by revising the error term of the traditional methods. The hybrid methodology can be described in two stages. First, we applied the ANN or SVM forecasting system with historical data and exogenous parameters, such as meteorological variables. Then, the forecasting target was revised by the Taylor expansion forecasting model using the residual information of the error term in the previous stage. The innovation involved in this approach is that it sufficiently and validly utilizes the useful residual information on an incomplete input variable condition. The proposed method was evaluated by experiments using a 2-year dataset of daily PM₁₀ (particles with a diameter of 10 μm or less) concentrations and SO₂ (sulfur dioxide) concentrations from four air pollution monitoring stations located in Taiyuan, China. The theoretical analysis and experimental results demonstrated that the forecasting accuracy of the proposed model is very promising. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. 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

  4. 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.

  5. Is the economic value of hydrological forecasts related to their quality? Case study of the hydropower sector.

    NASA Astrophysics Data System (ADS)

    Cassagnole, Manon; Ramos, Maria-Helena; Thirel, Guillaume; Gailhard, Joël; Garçon, Rémy

    2017-04-01

    The improvement of a forecasting system and the evaluation of the quality of its forecasts are recurrent steps in operational practice. However, the evaluation of forecast value or forecast usefulness for better decision-making is, to our knowledge, less frequent, even if it might be essential in many sectors such as hydropower and flood warning. In the hydropower sector, forecast value can be quantified by the economic gain obtained with the optimization of operations or reservoir management rules. Several hydropower operational systems use medium-range forecasts (up to 7-10 days ahead) and energy price predictions to optimize hydropower production. Hence, the operation of hydropower systems, including the management of water in reservoirs, is impacted by weather, climate and hydrologic variability as well as extreme events. In order to assess how the quality of hydrometeorological forecasts impact operations, it is essential to first understand if and how operations and management rules are sensitive to input predictions of different quality. This study investigates how 7-day ahead deterministic and ensemble streamflow forecasts of different quality might impact the economic gains of energy production. It is based on a research model developed by Irstea and EDF to investigate issues relevant to the links between quality and value of forecasts in the optimisation of energy production at the short range. Based on streamflow forecasts and pre-defined management constraints, the model defines the best hours (i.e., the hours with high energy prices) to produce electricity. To highlight the link between forecasts quality and their economic value, we built several synthetic ensemble forecasts based on observed streamflow time series. These inputs are generated in a controlled environment in order to obtain forecasts of different quality in terms of accuracy and reliability. These forecasts are used to assess the sensitivity of the decision model to forecast quality

  6. International Cooperative for Aerosol Prediction Workshop on Aerosol Forecast Verification

    NASA Technical Reports Server (NTRS)

    Benedetti, Angela; Reid, Jeffrey S.; Colarco, Peter R.

    2011-01-01

    The purpose of this workshop was to reinforce the working partnership between centers who are actively involved in global aerosol forecasting, and to discuss issues related to forecast verification. Participants included representatives from operational centers with global aerosol forecasting requirements, a panel of experts on Numerical Weather Prediction and Air Quality forecast verification, data providers, and several observers from the research community. The presentations centered on a review of current NWP and AQ practices with subsequent discussion focused on the challenges in defining appropriate verification measures for the next generation of aerosol forecast systems.

  7. 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.

  8. NCEP Air Quality Forecast(AQF) Verification. NOAA/NWS/NCEP/EMC

    Science.gov Websites

    average Select forecast four: Day 1 AOD skill for all thresholds Day 1 Time series for AOD GT 0 Day 2 AOD skill for all thresholds Day 2 Time series for AOD GT 0 Diurnal plots for AOD GT 0 Select statistic type

  9. 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.

  10. Feedbacks between Air-Quality, Meteorology, and the Forest Environment

    NASA Astrophysics Data System (ADS)

    Makar, Paul; Akingunola, Ayodeji; Stroud, Craig; Zhang, Junhua; Gong, Wanmin; Moran, Michael; Zheng, Qiong; Brook, Jeffrey; Sills, David

    2017-04-01

    The outcome of air quality forecasts depend in part on how the local environment surrounding the emissions regions influences chemical reaction rates and transport from those regions to the larger spatial scales. Forested areas alter atmospheric chemistry through reducing photolysis rates and vertical diffusivities within the forest canopy. The emitted pollutants, and their reaction products, are in turn capable of altering meteorology, through the well-known direct and indirect effects of particulate matter on radiative transfer. The combination of these factors was examined using version 2 of the Global Environmental Multiscale - Modelling Air-quality and CHemistry (GEM-MACH) on-line air pollution model. The model configuration used for this study included 12 aerosol size bins, eight aerosol species, homogeneous core Mie scattering, the Milbrandt-Yao two-moment cloud microphysics scheme with cloud condensation nuclei generated from model aerosols using the scheme of Abdul-Razzak and Ghan, and a new parameterization for forest canopy shading and turbulence. The model was nested to 2.5km resolution for a domain encompassing the lower Great Lakes, for simulations of a period in August of 2015 during the Pan American Games, held in Toronto, Canada. Four scenarios were carried out: (1) a "Base Case" scenario (the original model, in which coupling between chemistry and weather is not permitted; instead, the meteorological model's internal climatologies for aerosol optical and cloud condensation properties are used for direct and indirect effect calculations); (2) a "Feedback" scenario (the aerosol properties were derived from the internally simulated chemistry, and coupled to the meteorological model's radiative transfer and cloud formation modules); (3) a "Forest" scenario (canopy shading and turbulence were added to the Base Case); (4) a "Combined" scenario (including both direct and indirect effect coupling between meteorology and chemistry, as well as the forest

  11. Air Quality Science and Regulatory Efforts Require Geostationary Satellite Measurements

    NASA Technical Reports Server (NTRS)

    Pickering, Kenneth E.; Allen, D. J.; Stehr, J. W.

    2006-01-01

    Air quality scientists and regulatory agencies would benefit from the high spatial and temporal resolution trace gas and aerosol data that could be provided by instruments on a geostationary platform. More detailed time-resolved data from a geostationary platform could be used in tracking regional transport and in evaluating mesoscale air quality model performance in terms of photochemical evolution throughout the day. The diurnal cycle of photochemical pollutants is currently missing from the data provided by the current generation of atmospheric chemistry satellites which provide only one measurement per day. Often peak surface ozone mixing ratios are reached much earlier in the day during major regional pollution episodes than during local episodes due to downward mixing of ozone that had been transported above the boundary layer overnight. The regional air quality models often do not simulate this downward mixing well enough and underestimate surface ozone in regional episodes. Having high time-resolution geostationary data will make it possible to determine the magnitude of this lower-and mid-tropospheric transport that contributes to peak eight-hour average ozone and 24-hour average PM2.5 concentrations. We will show ozone and PM(sub 2.5) episodes from the CMAQ model and suggest ways in which geostationary satellite data would improve air quality forecasting. Current regulatory modeling is typically being performed at 12 km horizontal resolution. State and regional air quality regulators in regions with complex topography and/or land-sea breezes are anxious to move to 4-km or finer resolution simulations. Geostationary data at these or finer resolutions will be useful in evaluating such models.

  12. Studies of air traffic forecasts, airspace load and the effect of ADS-B via satellites on flight times

    NASA Astrophysics Data System (ADS)

    Zhong, Z. W.; Ridhwan Salleh, Saiful; Chow, W. X.; Ong, Z. M.

    2016-10-01

    Air traffic forecasting is important as it helps stakeholders to plan their budgets and facilities. Thus, three most commonly used forecasting models were compared to see which model suited the air passenger traffic the best. General forecasting equations were also created to forecast the passenger traffic. The equations could forecast around 6.0% growth from 2015 onwards. Another study sought to provide an initial work for determining a theoretical airspace load with relevant calculations. The air traffic was simulated to investigate the current airspace load. Logical and reasonable results were obtained from the modelling and simulations. The current utilization percentages for airspace load per hour and the static airspace load in the interested airspace were found to be 6.64% and 11.21% respectively. Our research also studied how ADS-B would affect the time taken for aircraft to travel. 6000 flights departing from and landing at the airport were studied. New flight plans were simulated with improved flight paths due to the implementation of ADS-B, and flight times of all studied flights could be improved.

  13. Potential assessment of a neural network model with PCA/RBF approach for forecasting pollutant trends in Mong Kok urban air, Hong Kong.

    PubMed

    Lu, Wei-Zhen; Wang, Wen-Jian; Wang, Xie-Kang; Yan, Sui-Hang; Lam, Joseph C

    2004-09-01

    The forecasting of air pollutant trends has received much attention in recent years. It is an important and popular topic in environmental science, as concerns have been raised about the health impacts caused by unacceptable ambient air pollutant levels. Of greatest concern are metropolitan cities like Hong Kong. In Hong Kong, respirable suspended particulates (RSP), nitrogen oxides (NOx), and nitrogen dioxide (NO2) are major air pollutants due to the dominant usage of diesel fuel by commercial vehicles and buses. Hence, the study of the influence and the trends relating to these pollutants is extremely significant to the public health and the image of the city. The use of neural network techniques to predict trends relating to air pollutants is regarded as a reliable and cost-effective method for the task of prediction. The works reported here involve developing an improved neural network model that combines both the principal component analysis technique and the radial basis function network and forecasts pollutant tendencies based on a recorded database. Compared with general neural network models, the proposed model features a more simple network architecture, a faster training speed, and a more satisfactory prediction performance. The improved model was evaluated with hourly time series of RSP, NOx and NO2 concentrations monitored at the Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000 and proved to be effective. The model developed is a potential tool for forecasting air quality parameters and is superior to traditional neural network methods.

  14. 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).

  15. Evaluation of the Community Multiscale Air Quality Model for Simulating Winter Ozone Formation in the Uinta Basin.

    EPA Science Inventory

    The Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models were used to simulate a 10 day high‐ozone episode observed during the 2013 Uinta Basin Winter Ozone Study (UBWOS). The baseline model had a large negative bias when compared to ozo...

  16. Improved Forecasting of Next Day Ozone Concentrations in the Eastern U.S.

    EPA Science Inventory

    There is an urgent need to provide accurate air quality information and forecasts to the general public. A hierarchical space-time model is used to forecast next day spatial patterns of daily maximum 8-hr ozone concentrations. The model combines ozone monitoring data and gridded...

  17. 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

  18. Water quality in the Schuylkill River, Pennsylvania: the potential for long-lead forecasts

    NASA Astrophysics Data System (ADS)

    Block, P. J.; Peralez, J.

    2012-12-01

    Prior analysis of pathogen levels in the Schuylkill River has led to a categorical daily forecast of water quality (denoted as red, yellow, or green flag days.) The forecast, available to the public online through the Philadelphia Water Department, is predominantly based on the local precipitation forecast. In this study, we explore the feasibility of extending the forecast to the seasonal scale by associating large-scale climate drivers with local precipitation and water quality parameter levels. This advance information is relevant for recreational activities, ecosystem health, and water treatment (energy, chemicals), as the Schuylkill provides 40% of Philadelphia's water supply. Preliminary results indicate skillful prediction of average summertime water quality parameters and characteristics, including chloride, coliform, turbidity, alkalinity, and others, using season-ahead oceanic and atmospheric variables, predominantly from the North Atlantic. Water quality parameter trends, including historic land use changes along the river, association with climatic variables, and prediction models will be presented.

  19. The Aura Mission and Its Application to Climate and Air Quality

    NASA Technical Reports Server (NTRS)

    Hilsenrath, Ernest; Schoeberl, Mark; Douglass, Anne

    2003-01-01

    NASA's Aura satellite is scheduled to launch in the second quarter of 2004 into a polar orbit. The Aura mission is designed to collect data to address three high priority environmental science questions: (1) Is the ozone layer recovering as expected? (2) What are the sources and processes that control tropospheric pollutants? And (3) what is the quantitative impact of constituents on climate change? Aura will answer these questions by globally measuring a comprehensive set of trace gases and aerosols in the troposphere and stratosphere. Aura data will also have applications for monitoring and predicting climate and air quality parameters. Aura s observations will continue the TOMS ozone trend record and provide an assessment as to whether the Montreal Protocol is achieving its objective. Aura will measure gases and aerosols in the upper troposphere and lower stratosphere that contribute to climate forcing. These data will be of sufficient coverage, vertical resolution, and accuracy to help constrain climate models. In addition, Aura observations of tropospheric ozone and its precursors will have regional as well as intercontinental coverage, which could improve emission inventories. Near real time data will tested for local air quality forecasts in collaboration with the US's Environmental Protection UV-B forecasts from Aura ozone and cloud cover data. An overview of Aura s instruments, data products, validation, and examples of data applications will be presented.

  20. 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

  1. 78 FR 21547 - Approval and Promulgation of Air Quality Implementation Plans; Oregon: Eugene-Springfield PM10

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-04-11

    ... revision as a direct final rule without prior proposal because EPA views this as a noncontroversial SIP... daily multi-stage advisory issued each winter from November through the end of February. The daily advisory, which is based upon forecast meteorology and air quality, provides a color-coded stage based on...

  2. Air Traffic Forecasting at the Port Authority of New York and New Jersey

    NASA Technical Reports Server (NTRS)

    Augustine, J. G.

    1972-01-01

    Procedures for conducting air traffic forecasts with specific application to the Port Authority of New York and New Jersey are discussed. The procedure relates air travel growth to detailed socio-economic and demographic characteristics of the U.S. population rather than to aggregate economic data such as Gross National Product, personal income, and industrial production. Charts are presented to show the relationship between various selected characteristics and the use of air transportation facilities.

  3. Air quality impact assessment of multiple open pit coal mines in northern Colombia.

    PubMed

    Huertas, José I; Huertas, María E; Izquierdo, Sebastián; González, Enrique D

    2012-01-01

    The coal mining region in northern Colombia is one of the largest open pit mining regions of the world. In 2009, there were 8 mining companies in operation with an approximate coal production of ∼70 Mtons/year. Since 2007, the Colombian air quality monitoring network has reported readings that exceed the daily and annual air quality standards for total suspended particulate (TSP) matter and particles with an equivalent aerodynamic diameter smaller than 10 μm (PM₁₀) in nearby villages. This paper describes work carried out in order to establish an appropriate clean air program for this region, based on the Colombian national environmental authority requirement for modeling of TSP and PM(10) dispersion. A TSP and PM₁₀ emission inventory was initially developed, and topographic and meteorological information for the region was collected and analyzed. Using this information, the dispersion of TSP was modeled in ISC3 and AERMOD using meteorological data collected by 3 local stations during 2008 and 2009. The results obtained were compared to actual values measured by the air quality monitoring network. High correlation coefficients (>0.73) were obtained, indicating that the models accurately described the main factors affecting particle dispersion in the region. The model was then used to forecast concentrations of particulate matter for 2010. Based on results from the model, areas within the modeling region were identified as highly, fairly, moderately and marginally polluted according to local regulations. Additionally, the contribution particulate matter to the pollution at each village was estimated. Using these predicted values, the Colombian environmental authority imposed new decontamination measures on the mining companies operating in the region. These measures included the relocation of three villages financed by the mine companies based on forecasted pollution levels. Copyright © 2011. Published by Elsevier Ltd.

  4. An analysis of effects of San Diego wildfire on ambient air quality.

    PubMed

    Viswanathan, Shekar; Eria, Luis; Diunugala, Nimal; Johnson, Jeffrey; McClean, Christopher

    2006-01-01

    The impact of major gaseous and particulate pollutants emitted by the wildfire of October 2003 on ambient air quality and health of San Diego residents before, during, and after the fire are analyzed using data available from the San Diego County Air Pollution Control District and California Air Resources Board. It was found that fine particulate matter (PM) levels exceeded the federal daily 24-hr average standard during the fire. There was a slight increase in some of the gaseous pollutants, such as carbon monoxide, which exceeded federal standards. Ozone (O3) precursors, such as total hydrocarbons and methane gases, experienced elevated concentration during the fire. Fortunately, the absence of sunlight because of the cloud of thick smoke that covered most of the county during the fire appears to have prevented the photochemical conversion of the precursor gases to harmful concentrations of O3. Statistical analysis of the compiled medical surveillance data has been used to establish correlations between pollutant levels in the region and the resultant health problems experienced by the county citizens. The study shows that the increased PM concentration above the federal standard resulted in a significant increase in hospital emergency room visits for asthma, respiratory problems, eye irritation, and smoke inhalation. On the basis of the findings, it is recommended that hospitals and emergency medical facilities engage in pre-event planning that would ensure a rapid response to an impact on the healthcare system as a result of a large wildfire and appropriate agencies engage in the use of all available meteorological forecasting resources, including real-time satellite imaging assets, to accurately forecast air quality and assist firefighting efforts.

  5. CAT (Clear Air Turbulence) Forecasting Using Transilient Turbulence Theory

    DTIC Science & Technology

    1988-02-20

    FILE COP.y AIOL-M-80106 CAT Fwmsft Using Transilient 00 % to, N - 0 William H. Raymond ) Rhad B. Stull O University of Wisconsin V CImSS/epannint...PROGRAM PROJECT TASK WORK UNIT ELEMENT NO. NO. NO ACCESSIO NO. 62101F 6670 10 DB 11. TITLE (Include Security Classification) CAT Forecasting Using...necessary and identify by block number) FIELD GROUP SUB-GROUP Clear Air Turbulence ( CAT ) Boundary Layer Turbulence parameterization Surface Fluxes 19

  6. 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.

  7. Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia.

    PubMed

    Crippa, P; Castruccio, S; Archer-Nicholls, S; Lebron, G B; Kuwata, M; Thota, A; Sumin, S; Butt, E; Wiedinmyer, C; Spracklen, D V

    2016-11-16

    Vegetation and peatland fires cause poor air quality and thousands of premature deaths across densely populated regions in Equatorial Asia. Strong El-Niño and positive Indian Ocean Dipole conditions are associated with an increase in the frequency and intensity of wildfires in Indonesia and Borneo, enhancing population exposure to hazardous concentrations of smoke and air pollutants. Here we investigate the impact on air quality and population exposure of wildfires in Equatorial Asia during Fall 2015, which were the largest over the past two decades. We performed high-resolution simulations using the Weather Research and Forecasting model with Chemistry based on a new fire emission product. The model captures the spatio-temporal variability of extreme pollution episodes relative to space- and ground-based observations and allows for identification of pollution sources and transport over Equatorial Asia. We calculate that high particulate matter concentrations from fires during Fall 2015 were responsible for persistent exposure of 69 million people to unhealthy air quality conditions. Short-term exposure to this pollution may have caused 11,880 (6,153-17,270) excess mortalities. Results from this research provide decision-relevant information to policy makers regarding the impact of land use changes and human driven deforestation on fire frequency and population exposure to degraded air quality.

  8. Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia

    PubMed Central

    Crippa, P.; Castruccio, S.; Archer-Nicholls, S.; Lebron, G. B.; Kuwata, M.; Thota, A.; Sumin, S.; Butt, E.; Wiedinmyer, C.; Spracklen, D. V.

    2016-01-01

    Vegetation and peatland fires cause poor air quality and thousands of premature deaths across densely populated regions in Equatorial Asia. Strong El-Niño and positive Indian Ocean Dipole conditions are associated with an increase in the frequency and intensity of wildfires in Indonesia and Borneo, enhancing population exposure to hazardous concentrations of smoke and air pollutants. Here we investigate the impact on air quality and population exposure of wildfires in Equatorial Asia during Fall 2015, which were the largest over the past two decades. We performed high-resolution simulations using the Weather Research and Forecasting model with Chemistry based on a new fire emission product. The model captures the spatio-temporal variability of extreme pollution episodes relative to space- and ground-based observations and allows for identification of pollution sources and transport over Equatorial Asia. We calculate that high particulate matter concentrations from fires during Fall 2015 were responsible for persistent exposure of 69 million people to unhealthy air quality conditions. Short-term exposure to this pollution may have caused 11,880 (6,153–17,270) excess mortalities. Results from this research provide decision-relevant information to policy makers regarding the impact of land use changes and human driven deforestation on fire frequency and population exposure to degraded air quality. PMID:27848989

  9. A FAST BAYESIAN METHOD FOR UPDATING AND FORECASTING HOURLY OZONE LEVELS

    EPA Science Inventory

    A Bayesian hierarchical space-time model is proposed by combining information from real-time ambient AIRNow air monitoring data, and output from a computer simulation model known as the Community Multi-scale Air Quality (Eta-CMAQ) forecast model. A model validation analysis shows...

  10. 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

  11. The role of a peri-urban forest on air quality improvement in the Mexico City megalopolis.

    PubMed

    Baumgardner, Darrel; Varela, Sebastian; Escobedo, Francisco J; Chacalo, Alicia; Ochoa, Carlos

    2012-04-01

    Air quality improvement by a forested, peri-urban national park was quantified by combining the Urban Forest Effects (UFORE) and the Weather Research and Forecasting coupled with Chemistry (WRF-Chem) models. We estimated the ecosystem-level annual pollution removal function of the park's trees, shrub and grasses using pollution concentration data for carbon monoxide (CO), ozone (O(3)), and particulate matter less than 10 microns in diameter (PM(10)), modeled meteorological and pollution variables, and measured forest structure data. Ecosystem-level O(3) and CO removal and formation were also analyzed for a representative month. Total annual air quality improvement of the park's vegetation was approximately 0.02% for CO, 1% for O(3,) and 2% for PM(10), of the annual concentrations for these three pollutants. Results can be used to understand the air quality regulation ecosystem services of peri-urban forests and regional dynamics of air pollution emissions from major urban areas. Copyright © 2011 Elsevier Ltd. All rights reserved.

  12. Solutions Network Formulation Report. NASA's Potential Contributions for Using Solar Ultraviolet Radiation in Conjunction with Photocatalysis for Urban Air Pollution Mitigation and Increasing Air Quality

    NASA Technical Reports Server (NTRS)

    Underwood, Lauren; Ryan, Robert E.

    2007-01-01

    This Candidate Solution is based on using NASA Earth science research on atmospheric ozone and aerosols data as a means to predict and evaluate the effectiveness of photocatalytically created surfaces (building materials like glass, tile and cement) for air pollution mitigation purposes. When these surfaces are exposed to near UV light, organic molecules, like air pollutants and smog precursors, will degrade into environmentally friendly compounds. U.S. EPA (Environmental Protection Agency) is responsible for forecasting daily air quality by using the Air Quality Index (AQI) that is provided by AIRNow. EPA is partnered with AIRNow and is responsible for calculating the AQI for five major air pollutants that are regulated by the Clean Air Act. In this Solution, UV irradiance data acquired from the satellite mission Aura and the OMI Surface UV algorithm will be used to help understand both the efficacy and efficiency of the photocatalytic decomposition process these surfaces facilitate, and their ability to reduce air pollutants. Prediction models that estimate photocatalytic function do not exist. NASA UV irradiance data will enable this capability, so that air quality agencies that are run by state and local officials can develop and implement programs that utilize photocatalysis for urban air pollution control and, enable them to make effective decisions about air pollution protection programs.

  13. Improve EPA's AIRNow Air Quality Index Maps with NASA/NOAA Satellite Data

    NASA Astrophysics Data System (ADS)

    Pasch, A.; Zahn, P. H.; DeWinter, J. L.; Haderman, M. D.; White, J. E.; Dickerson, P.; Dye, T. S.; Martin, R. V.

    2011-12-01

    The U.S. Environmental Protection Agency's (EPA) AIRNow program provides maps of real-time hourly Air Quality Index (AQI) conditions and daily AQI forecasts nationwide (http://www.airnow.gov). The public uses these maps to make decisions concerning their respiratory health. The usefulness of the AIRNow air quality maps depends on the accuracy and spatial coverage of air quality measurements. Currently, the maps use only ground-based measurements, which have significant gaps in coverage in some parts of the United States. As a result, contoured AQI levels have high uncertainty in regions far from monitors. To improve the usefulness of air quality maps, scientists at EPA and Sonoma Technology, Inc. are working in collaboration with the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and university researchers on a project to incorporate additional measurements into the maps via the AIRNow Satellite Data Processor (ASDP). These measurements include estimated surface PMAir Quality model. Once operational, the ASDP will be able to fuse multiple PM2.5 concentration data sets to generate AQI maps with improved spatial coverage. The goal of ASDP is to provide better AQI information in monitor-sparse locations and augment monitor-dense locations with more information. The methodology and evaluation of the data fusion will be presented, along with several case studies from fall 2009 through summer 2010.

  14. Impact of particulate air pollution on quality-adjusted life expectancy in Canada.

    PubMed

    Coyle, Douglas; Stieb, Dave; Burnett, Richard T; DeCivita, Paul; Krewski, Daniel; Chen, Yue; Thun, Michael J

    Air pollution and premature death are important public health concerns. Analyses have repeatedly demonstrated that airborne particles are associated with increased mortality and estimates have been used to forecast the impact on life expectancy. In this analysis, we draw upon data from the American Cancer Society (ACS) cohort and literature on utility-based measures of quality of life in relation to health status to more fully quantify the effects of air pollution on mortality in terms of quality-adjusted life expectancy. The analysis was conducted within a decision analytic model using Monte Carlo simulation techniques. Outcomes were estimated based on projections of the Canadian population. A one-unit reduction in sulfate air pollution would yield a mean annual increase in Quality-Adjusted Life Years (QALYs) of 20,960, with gains being greater for individuals with lower educational status and for males compared to females. This suggests that the impact of reductions in sulfate air pollution on quality-adjusted life expectancy is substantial. Interpretation of the results is unclear. However, the potential gains in QALYs from reduced air pollutants can be contrasted to the costs of policies to bring about such reductions. Based on a tentative threshold for the value of health benefits, analysis suggests that an investment in Canada of over 1 billion dollars per annum would be an efficient use of resources if it could be demonstrated that this would reduce sulfate concentrations in ambient air by 1 microg/m(3). Further analysis can assess the efficiency of targeting such initiatives to communities that are most likely to benefit.

  15. Workshop Summary: International Cooperative for Aerosol Prediction Workshop On Aerosol Forecast Verification

    NASA Technical Reports Server (NTRS)

    Benedetti, Angela; Reid, Jeffrey S.; Colarco, Peter R.

    2011-01-01

    The purpose of this workshop was to reinforce the working partnership between centers who are actively involved in global aerosol forecasting, and to discuss issues related to forecast verification. Participants included representatives from operational centers with global aerosol forecasting requirements, a panel of experts on Numerical Weather Prediction and Air Quality forecast verification, data providers, and several observers from the research community. The presentations centered on a review of current NWP and AQ practices with subsequent discussion focused on the challenges in defining appropriate verification measures for the next generation of aerosol forecast systems.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  17. 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...

  18. 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...

  19. 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...

  20. The impact of communicating information about air pollution events on public health.

    PubMed

    McLaren, J; Williams, I D

    2015-12-15

    Short-term exposure to air pollution has been associated with exacerbation of asthma and chronic obstructive pulmonary disease (COPD). This study investigated the relationship between emergency hospital admissions for asthma, COPD and episodes of poor air quality in an English city (Southampton) from 2008-2013. The city's council provides a forecasting service for poor air quality to individuals with respiratory disease to reduce preventable admissions to hospital and this has been evaluated. Trends in nitrogen dioxide, ozone and particulate matter concentrations were related to hospital admissions data using regression analysis. The impacts of air quality on emergency admissions were quantified using the relative risks associated with each pollutant. Seasonal and weekly trends were apparent for both air pollution and hospital admissions, although there was a weak relationship between the two. The air quality forecasting service proved ineffective at reducing hospital admissions. Improvements to the health forecasting service are necessary to protect the health of susceptible individuals, as there is likely to be an increasing need for such services in the future. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. ASSESSMENT OF ETA-CMAQ FORECASTS OF PARTICULATE MATTER DISTRIBUTIONS THROUGH COMPARISONS WITH SURFACE NETWORK AND SPECIALIZED MEASUREMENTS

    EPA Science Inventory

    An air-quality forecasting (AQF) system based on the National Weather Service (NWS) National Centers for Environmental Prediction's (NCEP's) Eta model and the U.S. EPA's Community Multiscale Air Quality (CMAQ) Modeling System is used to simulate the distributions of tropospheric ...

  2. PM2.5 forecasting using SVR with PSOGSA algorithm based on CEEMD, GRNN and GCA considering meteorological factors

    NASA Astrophysics Data System (ADS)

    Zhu, Suling; Lian, Xiuyuan; Wei, Lin; Che, Jinxing; Shen, Xiping; Yang, Ling; Qiu, Xuanlin; Liu, Xiaoning; Gao, Wenlong; Ren, Xiaowei; Li, Juansheng

    2018-06-01

    The PM2.5 is the culprit of air pollution, and it leads to respiratory system disease when the fine particles are inhaled. Therefore, it is increasingly significant to develop an effective model for PM2.5 forecasting and warnings that informs people to foresee the air quality. People can reduce outdoor activities and take preventive measures if they know the air quality is bad ahead of time. In addition, reliable forecasting results can remind the relevant departments to control and reduce pollutants discharge. According to our knowledge, the current hybrid forecasting techniques of PM2.5 do not take the meteorological factors into consideration. Actually, meteorological factors affect the concentrations of air pollution, but it is unclear whether meteorological factors are helpful for improving the PM2.5 forecasting results or not. This paper proposes a hybrid model called CEEMD-PSOGSA-SVR-GRNN, based on complementary ensemble empirical mode decomposition (CEEMD), particle swarm optimization and gravitational search algorithm (PSOGSA), support vector regression (SVR), generalized regression neural network (GRNN) and grey correlation analysis (GCA), for the daily PM2.5 concentrations forecasting. The main steps of proposed model are described as follows: the original PM2.5 data decomposition with CEEMD, optimal SVR selection with PSOGCA, meteorological factors selection with GCA, residual revision by GRNN and forecasting results analysis. Three cities (Chongqing, Harbin and Jinan) in China with different characteristics of climate, terrain and pollution sources are selected to verify the effectiveness of proposed model, and CEEMD-PSOGSA-SVR*, EEMD-PSOGSA-SVR, PSOGSA-SVR, CEEMD-PSO-SVR, CEEMD-GSA-SVR, CEEMD-GWO-SVR are considered to be compared models. The experimental results show that the hybrid CEEMD-PSOGSA-SVR-GRNN model outperforms other six compared models. Therefore, the proposed CEEMD-PSOGSA-SVR-GRNN model can be used to develop air quality forecasting and

  3. 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.

  4. Statistical Short-Range Guidance for Peak Wind Speed Forecasts at Edwards Air Force Base, CA

    NASA Technical Reports Server (NTRS)

    Dreher, Joseph; Crawford, Winifred; Lafosse, Richard; Hoeth, Brian; Burns, Kerry

    2008-01-01

    The peak winds near the surface are an important forecast element for Space Shuttle landings. As defined in the Shuttle Flight Rules (FRs), there are peak wind thresholds that cannot be exceeded in order to ensure the safety of the shuttle during landing operations. The National Weather Service Spaceflight Meteorology Group (SMG) is responsible for weather forecasts for all shuttle landings. They indicate peak winds are a challenging parameter to forecast. To alleviate the difficulty in making such wind forecasts, the Applied Meteorology Unit (AMTJ) developed a personal computer based graphical user interface (GUI) for displaying peak wind climatology and probabilities of exceeding peak-wind thresholds for the Shuttle Landing Facility (SLF) at Kennedy Space Center. However, the shuttle must land at Edwards Air Force Base (EAFB) in southern California when weather conditions at Kennedy Space Center in Florida are not acceptable, so SMG forecasters requested that a similar tool be developed for EAFB. Marshall Space Flight Center (MSFC) personnel archived and performed quality control of 2-minute average and 10-minute peak wind speeds at each tower adjacent to the main runway at EAFB from 1997- 2004. They calculated wind climatologies and probabilities of average peak wind occurrence based on the average speed. The climatologies were calculated for each tower and month, and were stratified by hour, direction, and direction/hour. For the probabilities of peak wind occurrence, MSFC calculated empirical and modeled probabilities of meeting or exceeding specific 10-minute peak wind speeds using probability density functions. The AMU obtained and reformatted the data into Microsoft Excel PivotTables, which allows users to display different values with point-click-drag techniques. The GUT was then created from the PivotTables using Visual Basic for Applications code. The GUI is run through a macro within Microsoft Excel and allows forecasters to quickly display and

  5. 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

  6. Extended-range forecasting of Chinese summer surface air temperature and heat waves

    NASA Astrophysics Data System (ADS)

    Zhu, Zhiwei; Li, Tim

    2018-03-01

    Because of growing demand from agricultural planning, power management and activity scheduling, extended-range (5-30-day lead) forecasting of summer surface air temperature (SAT) and heat waves over China is carried out in the present study via spatial-temporal projection models (STPMs). Based on the training data during 1960-1999, the predictability sources are found to propagate from Europe, Northeast Asia, and the tropical Pacific, to influence the intraseasonal 10-80 day SAT over China. STPMs are therefore constructed using the projection domains, which are determined by these previous predictability sources. For the independent forecast period (2000-2013), the STPMs can reproduce EOF-filtered 30-80 day SAT at all lead times of 5-30 days over most part of China, and observed 30-80 and 10-80 day SAT at 25-30 days over eastern China. Significant pattern correlation coefficients account for more than 50% of total forecasts at all 5-30-day lead times against EOF-filtered and observed 30-80 day SAT, and at a 20-day lead time against observed 10-80 day SAT. The STPMs perform poorly in reproducing 10-30 day SAT. Forecasting for the first two modes of 10-30 day SAT only shows useful skill within a 15-day lead time. Forecasting for the third mode of 10-30 day SAT is useless after a 10-day lead time. The forecasted heat waves over China are determined by the reconstructed SAT which is the summation of the forecasted 10-80 day SAT and the lower frequency (longer than 80-day) climatological SAT. Over a large part of China, the STPMs can forecast more than 30% of heat waves within a 15-day lead time. In general, the STPMs demonstrate the promising skill for extended-range forecasting of Chinese summer SAT and heat waves.

  7. 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...

  8. 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.

  9. Statistical Short-Range Guidance for Peak Wind Speed Forecasts at Edwards Air Force Base, CA

    NASA Technical Reports Server (NTRS)

    Dreher, Joseph G.; Crawford, Winifred; Lafosse, Richard; Hoeth, Brian; Burns, Kerry

    2009-01-01

    The peak winds near the surface are an important forecast element for space shuttle landings. As defined in the Flight Rules (FR), there are peak wind thresholds that cannot be exceeded in order to ensure the safety of the shuttle during landing operations. The National Weather Service Spaceflight Meteorology Group (SMG) is responsible for weather forecasts for all shuttle landings, and is required to issue surface average and 10-minute peak wind speed forecasts. They indicate peak winds are a challenging parameter to forecast. To alleviate the difficulty in making such wind forecasts, the Applied Meteorology Unit (AMU) developed a PC-based graphical user interface (GUI) for displaying peak wind climatology and probabilities of exceeding peak wind thresholds for the Shuttle Landing Facility (SLF) at Kennedy Space Center (KSC; Lambert 2003). However, the shuttle occasionally may land at Edwards Air Force Base (EAFB) in southern California when weather conditions at KSC in Florida are not acceptable, so SMG forecasters requested a similar tool be developed for EAFB.

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  11. The Impact of the Assimilation of AIRS Radiance Measurements on Short-term Weather Forecasts

    NASA Technical Reports Server (NTRS)

    McCarty, Will; Jedlovec, Gary; Miller, Timothy L.

    2009-01-01

    Advanced spaceborne instruments have the ability to improve the horizontal and vertical characterization of temperature and water vapor in the atmosphere through the explicit use of hyperspectral thermal infrared radiance measurements. The incorporation of these measurements into a data assimilation system provides a means to continuously characterize a three-dimensional, instantaneous atmospheric state necessary for the time integration of numerical weather forecasts. Measurements from the National Aeronautics and Space Administration (NASA) Atmospheric Infrared Sounder (AIRS) are incorporated into the gridpoint statistical interpolation (GSI) three-dimensional variational (3D-Var) assimilation system to provide improved initial conditions for use in a mesoscale modeling framework mimicking that of the operational North American Mesoscale (NAM) model. The methodologies for the incorporation of the measurements into the system are presented. Though the measurements have been shown to have a positive impact in global modeling systems, the measurements are further constrained in this system as the model top is physically lower than the global systems and there is no ozone characterization in the background state. For a study period, the measurements are shown to have positive impact on both the analysis state as well as subsequently spawned short-term (0-48 hr) forecasts, particularly in forecasted geopotential height and precipitation fields. At 48 hr, height anomaly correlations showed an improvement in forecast skill of 2.3 hours relative to a system without the AIRS measurements. Similarly, the equitable threat and bias scores of precipitation forecasts of 25 mm (6 hr)-1 were shown to be improved by 8% and 7%, respectively.

  12. Influence of Asian dust storms on air quality in Taiwan.

    PubMed

    Liu, Chung-Ming; Young, Chea-Yuan; Lee, Yen-Chih

    2006-09-15

    In each year, dust storms triggered by cold air masses passing through northern China and Mongolia enhance the PM10 concentration over Taiwan region during winter and spring. On average, there are four to five dust events and 6.1 dust days in a year in Taiwan. Each event lasts for 1 day or even longer. A procedure to identify a dust event is rationalized and exercised on data collected during 1994-2005. Also, a ranking method named as the dust intensity rank (DIR) is developed to distinguish the intensity of each event affecting the local air quality. About 86% of dust days belong to ranks 1 and 2. In general, poorer air quality is associated with higher ranks. Ranks 4 and 5 correspond to a PSI (Pollution Standard Index) larger than 100. Linking DIR with the popular PSI is useful for both the public and the official forecasting system. It is also useful for inter-comparison between dust influences on air quality at different downstream regions in Taiwan. Composite analyses of the temporal and spatial variation of the hourly PM10 level indicate that dust particles usually arrive 12 h before the time of the peak PM10 concentration and last for 36 h at northern Taiwan, while the time of the peak concentration at eastern or western Taiwan, due to the evolution of the synoptic weather system, is about 3-12 h later. It is noted that the increase of PM10 level at the western side of Taiwan results from a mixture of upstream Asian dust inputs and local pollutants.

  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. Evaluation and Quality Control for the Copernicus Seasonal Forecast Systems

    NASA Astrophysics Data System (ADS)

    Manubens, N.; Hunter, A.; Bedia, J.; Bretonnière, P. A.; Bhend, J.; Doblas-Reyes, F. J.

    2017-12-01

    The EU funded Copernicus Climate Change Service (C3S) will provide authoritative information about past, current and future climate for a wide range of users, from climate scientists to stakeholders from a wide range of sectors including insurance, energy or transport. It has been recognized that providing information about the products' quality and provenance is paramount to establish trust in the service and allow users to make best use of the available information. This presentation outlines the work being conducted within the Quality Assurance for Multi-model Seasonal Forecast Products project (QA4Seas). The aim of QA4Seas is to develop a strategy for the evaluation and quality control (EQC) of the multi-model seasonal forecasts provided by C3S. First, we present the set of guidelines the data providers must comply with, ensuring the data is fully traceable and harmonized across data sets. Second, we discuss the ongoing work on defining a provenance and metadata model that is able to encode such information, and that can be extended to describe the steps followed to obtain the final verification products such as maps and time series of forecast quality measures. The metadata model is based on the Resource Description Framework W3C standard, being thus extensible and reusable. It benefits from widely adopted vocabularies to describe data provenance and workflows, as well as from expert consensus and community-support for the development of the verification and downscaling specific ontologies. Third, we describe the open source software being developed to generate fully reproducible and certifiable seasonal forecast products, which also attaches provenance and metadata information to the verification measures and enables the user to visually inspect the quality of the C3S products. QA4Seas is seeking collaboration with similar initiatives, as well as extending the discussion to interested parties outside the C3S community to share experiences and establish global

  15. Study on the influence of ground and satellite observations on the numerical air-quality for PM10 over Romanian territory

    NASA Astrophysics Data System (ADS)

    Dumitrache, Rodica Claudia; Iriza, Amalia; Maco, Bogdan Alexandru; Barbu, Cosmin Danut; Hirtl, Marcus; Mantovani, Simone; Nicola, Oana; Irimescu, Anisoara; Craciunescu, Vasile; Ristea, Alina; Diamandi, Andrei

    2016-10-01

    The numerical forecast of particulate matter concentrations in general, and PM10 in particular is a theme of high socio-economic relevance. The aim of this study was to investigate the impact of ground and satellite data assimilation of PM10 observations into the Weather Research and Forecasting model coupled with Chemistry (WRF-CHEM) numerical air quality model for Romanian territory. This is the first initiative of the kind for this domain of interest. Assimilation of satellite information - e.g. AOT's in air quality models is of interest due to the vast spatial coverage of the observations. Support Vector Regression (SVR) techniques are used to estimate the PM content from heterogeneous data sources, including EO products (Aerosol Optical Thickness), ground measurements and numerical model data (temperature, humidity, wind, etc.). In this study we describe the modeling framework employed and present the evaluation of the impact from the data assimilation of PM10 observations on the forecast of the WRF-CHEM model. Integrations of the WRF-CHEM model in data assimilation enabled/disabled configurations allowed the evaluation of satellite and ground data assimilation impact on the PM10 forecast performance for the Romanian territory. The model integration and evaluation were performed for two months, one in winter conditions (January 2013) and one in summer conditions (June 2013).

  16. 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.

  17. 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...

  18. 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...

  19. Current Applications of OMI Tropospheric NO2 Data for Air Quality and a Look to the Future

    NASA Technical Reports Server (NTRS)

    Pickering, Kenneth E.; Bucsela, E.; Allen, D.; Prados, A.; Gleason, J.; Kondragunta, S.

    2010-01-01

    Ozone Monitoring Instrument (OMI) Tropospheric NO2 products are being used to enhance the ability to monitor changes in NO2 air quality, update emission inventories, and evaluate regional air quality models. Trends in tropospheric column NO2 have been examined over the eastern United States in relation to emissions changes mandated by regulatory actions. Decreases of 20 to 40 percent over the period 2005 to 2008 were noted, largely in response to major emission reductions at power plants. The OMI data have been used to identify regions in which the opposite trend has been found. We have also used OMI NO2 in efforts to improve emission inventories for NOx emissions from soil. Lightning NOx emissions have been added to CMAQ, the US Environmental Protection Agency's regional air quality model. Evaluation of the resulting NO2 columns in the model is being conducted using the OMI NO2 observations. Community Multiscale Air Quality (CMAQ) together with the OMI NO2 data comprise a valuable tool for monitoring and predicting air quality. Looking to the future, we expect that the combination of Global Ozone Monitoring Experiment-2 (GOME-2) (morning) and OMI (afternoon) data sets obtained through use of the same retrieval algorithms will substantially increase the possibility of successful integration of satellite information into regional air quality forecast models. Farther down the road, we anticipate the Geostationary Coastal and Air Pollution Events (GEO-CAPE) platform to supply data possibly on an hourly basis, allowing much more comprehensive analysis of air quality from space.

  20. 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...

  1. 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...

  2. Integrating Satellite Measurements from Polar-orbiting instruments into Smoke Disperson Forecasts

    NASA Astrophysics Data System (ADS)

    Smith, N.; Pierce, R. B.; Barnet, C.; Gambacorta, A.; Davies, J. E.; Strabala, K.

    2015-12-01

    The IDEA-I (Infusion of Satellite Data into Environmental Applications-International) is a real-time system that currently generates trajectory-based forecasts of aerosol dispersion and stratospheric intrusions. Here we demonstrate new capabilities that use satellite measurements from the Joint Polar Satellite System (JPSS) Suomi-NPP (S-NPP) instruments (operational since 2012) in the generation of trajectory-based predictions of smoke dispersion from North American wildfires. Two such data products are used, namely the Visible Infrared Imaging Radiometer Suite (VIIRS) Aerosol Optical Depth (AOD) and the combined Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) NOAA-Unique CrIS-ATMS Processing System (NUCAPS) carbon monoxide (CO) retrievals. The latter is a new data product made possible by the release of full spectral-resolution CrIS measurements since December 2014. Once NUCAPS CO becomes operationally available it will be used in real-time applications such as IDEA-I along with VIIRS AOD and meteorological forecast fields to support National Weather Service (NWS) Incident Meteorologist (IMET) and air quality management decision making. By combining different measurements, the information content of the IDEA-I transport and dispersion forecast is improved within the complex terrain features that dominate the Western US and Alaska. The primary user community of smoke forecasts is the Western regions of the National Weather Service (NWS) and US Environmental Protection Agency (EPA) due to the significant impacts of wildfires in these regions. With this we demonstrate the quality of the smoke dispersion forecasts that can be achieved by integrating polar-orbiting satellite measurements with forecast models to enable on-site decision support services for fire incident management teams and other real-time air quality agencies.

  3. THE NOAA - EPA NATIONAL AIR QUALITY FORECASTING SYSTEM

    EPA Science Inventory

    Building upon decades of collaboration in air pollution meteorology research, in 2003 the National Oceanic and Atmospheric Administration (NOAA) and the United States Environmental Protection Agency (EPA) signed formal partnership agreements to develop and implement an operationa...

  4. Application of an integrated Weather Research and Forecasting (WRF)/CALPUFF modeling tool for source apportionment of atmospheric pollutants for air quality management: A case study in the urban area of Benxi, China.

    PubMed

    Wu, Hao; Zhang, Yan; Yu, Qi; Ma, Weichun

    2018-04-01

    In this study, the authors endeavored to develop an effective framework for improving local urban air quality on meso-micro scales in cities in China that are experiencing rapid urbanization. Within this framework, the integrated Weather Research and Forecasting (WRF)/CALPUFF modeling system was applied to simulate the concentration distributions of typical pollutants (particulate matter with an aerodynamic diameter <10 μm [PM 10 ], sulfur dioxide [SO 2 ], and nitrogen oxides [NO x ]) in the urban area of Benxi. Statistical analyses were performed to verify the credibility of this simulation, including the meteorological fields and concentration fields. The sources were then categorized using two different classification methods (the district-based and type-based methods), and the contributions to the pollutant concentrations from each source category were computed to provide a basis for appropriate control measures. The statistical indexes showed that CALMET had sufficient ability to predict the meteorological conditions, such as the wind fields and temperatures, which provided meteorological data for the subsequent CALPUFF run. The simulated concentrations from CALPUFF showed considerable agreement with the observed values but were generally underestimated. The spatial-temporal concentration pattern revealed that the maximum concentrations tended to appear in the urban centers and during the winter. In terms of their contributions to pollutant concentrations, the districts of Xihu, Pingshan, and Mingshan all affected the urban air quality to different degrees. According to the type-based classification, which categorized the pollution sources as belonging to the Bengang Group, large point sources, small point sources, and area sources, the source apportionment showed that the Bengang Group, the large point sources, and the area sources had considerable impacts on urban air quality. Finally, combined with the industrial characteristics, detailed control measures

  5. 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.

  6. 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,…

  7. Data Assimilation of AIRS Water Vapor Profiles: Impact on Precipitation Forecasts for Atmospheric River Cases Affecting the Western of the United States

    NASA Technical Reports Server (NTRS)

    Blankenship, Clay; Zavodsky, Bradley; Jedlovec, Gary; Wick, Gary; Neiman, Paul

    2013-01-01

    Atmospheric rivers are transient, narrow regions in the atmosphere responsible for the transport of large amounts of water vapor. These phenomena can have a large impact on precipitation. In particular, they can be responsible for intense rain events on the western coast of North America during the winter season. This paper focuses on attempts to improve forecasts of heavy precipitation events in the Western US due to atmospheric rivers. Profiles of water vapor derived from from Atmospheric Infrared Sounder (AIRS) observations are combined with GFS forecasts by a three-dimensional variational data assimilation in the Gridpoint Statistical Interpolation (GSI). Weather Research and Forecasting (WRF) forecasts initialized from the combined field are compared to forecasts initialized from the GFS forecast only for 3 test cases in the winter of 2011. Results will be presented showing the impact of the AIRS profile data on water vapor and temperature fields, and on the resultant precipitation forecasts.

  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. A Peak Wind Probability Forecast Tool for Kennedy Space Center and Cape Canaveral Air Force Station

    NASA Technical Reports Server (NTRS)

    Crawford, Winifred; Roeder, William

    2008-01-01

    This conference abstract describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) in east-central Florida. The peak winds are an important forecast element for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a short-range peak-wind forecast tool to assist in forecasting LCC violatioas.The tool will include climatologies of the 5-minute mean end peak winds by month, hour, and direction, and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

  11. A computerized system to measure and predict air quality for emission control

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

    Crooks, G.; Ciccone, A.; Frattolillo, P.

    1997-12-31

    A Supplementary Emission Control (SEC) system has been developed on behalf of the Association Industrielle de l`Est de Montreal (AIEM). The objective of the SEC is to avoid exceedences of the Montreal Urban Community (MUC) 24 hour ambient Air Quality Standard (AQS) for sulphur dioxide in the industrial East Montreal area. The SEC system is comprised of: 3 continuous SO{sub 2} monitoring stations with data loggers and remote communications; a meteorological tower with data logger and modem for acquiring local meteorology; communications with Environment Canada to download meteorological forecast data; a polling PC for data retrieval; and Windows NT basedmore » software running on the AIEM computer server. The SEC software utilizes relational databases to store and maintain measured SO{sub 2} concentration data, emission data, as well as observed and forecast meteorological data. The SEC system automatically executes a numerical dispersion model to forecast SO{sub 2} concentrations up to six hours in the future. Based on measured SO{sub 2} concentrations at the monitoring stations and the six hour forecast concentrations, the system determines if local sources should reduce their emission levels to avoid potential exceedences of the AQS. The SEC system also includes a Graphical User Interface (GUI) for user access to the system. The SEC system and software are described, and the accuracy of the system at forecasting SO{sub 2} concentrations is examined.« less

  12. The impact of satellite temperature soundings on the forecasts of a small national meteorological service

    NASA Technical Reports Server (NTRS)

    Wolfson, N.; Thomasell, A.; Alperson, Z.; Brodrick, H.; Chang, J. T.; Gruber, A.; Ohring, G.

    1984-01-01

    The impact of introducing satellite temperature sounding data on a numerical weather prediction model of a national weather service is evaluated. A dry five level, primitive equation model which covers most of the Northern Hemisphere, is used for these experiments. Series of parallel forecast runs out to 48 hours are made with three different sets of initial conditions: (1) NOSAT runs, only conventional surface and upper air observations are used; (2) SAT runs, satellite soundings are added to the conventional data over oceanic regions and North Africa; and (3) ALLSAT runs, the conventional upper air observations are replaced by satellite soundings over the entire model domain. The impact on the forecasts is evaluated by three verification methods: the RMS errors in sea level pressure forecasts, systematic errors in sea level pressure forecasts, and errors in subjective forecasts of significant weather elements for a selected portion of the model domain. For the relatively short range of the present forecasts, the major beneficial impacts on the sea level pressure forecasts are found precisely in those areas where the satellite sounding are inserted and where conventional upper air observations are sparse. The RMS and systematic errors are reduced in these regions. The subjective forecasts of significant weather elements are improved with the use of the satellite data. It is found that the ALLSAT forecasts are of a quality comparable to the SAR forecasts.

  13. 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 ...

  14. Impacts of Energy Sector Emissions on PM2.5 Air Quality in Northern India

    NASA Astrophysics Data System (ADS)

    Karambelas, A. N.; Kiesewetter, G.; Heyes, C.; Holloway, T.

    2015-12-01

    India experiences high concentrations of fine particulate matter (PM2.5), and several Indian cities currently rank among the world's most polluted cities. With ongoing urbanization and a growing economy, emissions from different energy sectors remain major contributors to air pollution in India. Emission sectors impact ambient air quality differently due to spatial distribution (typical urban vs. typical rural sources) as well as source height characteristics (low-level vs. high stack sources). This study aims to assess the impacts of emissions from three distinct energy sectors—transportation, domestic, and electricity—on ambient PM2.5­­ in northern India using an advanced air quality analysis framework based on the U.S. EPA Community Multi-Scale Air Quality (CMAQ) model. Present air quality conditions are simulated using 2010 emissions from the Greenhouse Gas-Air Pollution Interaction and Synergies (GAINS) model. Modeled PM2.5 concentrations are compared with satellite observations of aerosol optical depth (AOD) from the Moderate Imaging Spectroradiometer (MODIS) for 2010. Energy sector emissions impacts on future (2030) PM2.5 are evaluated with three sensitivity simulations, assuming maximum feasible reduction technologies for either transportation, domestic, or electricity sectors. These simulations are compared with a business as usual 2030 simulation to assess relative sectoral impacts spatially and temporally. CMAQ is modeled at 12km by 12km and include biogenic emissions from the Community Land Model coupled with the Model of Emissions of Gases and Aerosols in Nature (CLM-MEGAN), biomass burning emissions from the Global Fires Emissions Database (GFED), and ERA-Interim meteorology generated with the Weather Research and Forecasting (WRF) model for 2010 to quantify the impact of modified anthropogenic emissions on ambient PM2.5 concentrations. Energy sector emissions analysis supports decision-making to improve future air quality and public health in

  15. Air Quality Index (AQI) -- A Guide to Air Quality and Your Health

    MedlinePlus

    ... Guide for Ozone Air Quality Guide for Particle Pollution Other AirNow Publications Other AirNow Publications En Español ... the Clean Air Act: ground-level ozone, particle pollution (also known as particulate matter), carbon monoxide, sulfur ...

  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. Forecasting forecast skill

    NASA Technical Reports Server (NTRS)

    Kalnay, Eugenia; Dalcher, Amnon

    1987-01-01

    It is shown that it is possible to predict the skill of numerical weather forecasts - a quantity which is variable from day to day and region to region. This has been accomplished using as predictor the dispersion (measured by the average correlation) between members of an ensemble of forecasts started from five different analyses. The analyses had been previously derived for satellite-data-impact studies and included, in the Northern Hemisphere, moderate perturbations associated with the use of different observing systems. When the Northern Hemisphere was used as a verification region, the prediction of skill was rather poor. This is due to the fact that such a large area usually contains regions with excellent forecasts as well as regions with poor forecasts, and does not allow for discrimination between them. However, when regional verifications were used, the ensemble forecast dispersion provided a very good prediction of the quality of the individual forecasts.

  18. Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service

    PubMed Central

    Berger, Uwe; Kmenta, Maximilian

    2017-01-01

    Background Pollen forecasts are highly valuable for allergen avoidance and thus raising the quality of life of persons concerned by pollen allergies. They are considered as valuable free services for the public. Careful scientific evaluation of pollen forecasts in terms of accurateness and reliability has not been available till date. Objective The aim of this study was to analyze 9 mobile apps, which deliver pollen information and pollen forecasts, with a focus on their accurateness regarding the prediction of the pollen load in the grass pollen season 2016 to assess their usefulness for pollen allergy sufferers. Methods The following number of apps was evaluated for each location: 3 apps for Vienna (Austria), 4 apps for Berlin (Germany), and 1 app each for Basel (Switzerland) and London (United Kingdom). All mobile apps were freely available. Today’s grass pollen forecast was compared throughout the defined grass pollen season at each respective location with measured grass pollen concentrations. Hit rates were calculated for the exact performance and for a tolerance in a range of ±2 and ±4 pollen per cubic meter. Results In general, for most apps, hit rates score around 50% (6 apps). It was found that 1 app showed better results, whereas 3 apps performed less well. Hit rates increased when calculated with tolerances for most apps. In contrast, the forecast for the “readiness to flower” for grasses was performed at a sufficiently accurate level, although only two apps provided such a forecast. The last of those forecasts coincided with the first moderate grass pollen load on the predicted day or 3 days after and performed even from about a month before well within the range of 3 days. Advertisement was present in 3 of the 9 analyzed apps, whereas an imprint mentioning institutions with experience in pollen forecasting was present in only three other apps. Conclusions The quality of pollen forecasts is in need of improvement, and quality control for pollen

  19. Multi-Scale Enviro-HIRLAM Forecasting of Weather and Atmospheric Composition over China and its Megacities

    NASA Astrophysics Data System (ADS)

    Mahura, Alexander; Amstrup, Bjarne; Nuterman, Roman; Yang, Xiaohua; Baklanov, Alexander

    2017-04-01

    Air pollution is a serious problem in different regions of China and its continuously growing megacities. Information on air quality, and especially, in urbanized areas is important for decision making, emergency response and population. In particular, the metropolitan areas of Shanghai, Beijing, and Pearl River Delta are well known as main regions having serious air pollution problems. The on-line integrated meteorology-chemistry-aerosols Enviro-HIRLAM (Environment - HIgh Resolution Limited Area Model) model adapted for China and selected megacities is applied for forecasting of weather and atmospheric composition (with focus on aerosols). The model system is running in downscaling chain from regional to urban scales at subsequent horizontal resolutions of 15-5-2.5 km. The model setup includes also the urban Building Effects Parameterization module, describing different types of urban districts (industrial commercial, city center, high density and residential) with its own morphological and aerodynamical characteristics. The effects of urbanization are important for atmospheric transport, dispersion, deposition, and chemical transformations, in addition to better quality emission inventories for China and selected urban areas. The Enviro-HIRLAM system provides meteorology and air quality forecasts at regional-subregional-urban scales (China - East China - selected megacities). In particular, such forecasting is important for metropolitan areas, where formation and development of meteorological and chemical/aerosol patterns are especially complex. It also provides information for evaluation impact on selected megacities of China as well as for investigation relationship between air pollution and meteorology.

  20. Domestic & International Air Cargo Activity: National and Selected Hub Forecasts.

    DTIC Science & Technology

    1979-11-01

    111371 1991 1887811 2?. 768 :297968 Forecast utilizes 1972 dollar GNP from Wharton’s annual model, December 6, 1978, Post-Meeting Control Solution...mile based on 1973 revenue ton-miles reported in the DOT/CAB, Air Carrier Traffic Statistics. South America - RSA - simple average of American (Latin...9518 F (2/11) = 129.347 DW = 1.41 (b) South America (ESA) 4 = 11.8926 + 18.2908* (GDPSA.C) - 8.94307* ( RSA ) 4 (0.14) (6.08) (-0.46) R2 .8717 F (2/11

  1. Blending forest fire smoke forecasts with observed data can improve their utility for public health applications

    NASA Astrophysics Data System (ADS)

    Yuchi, Weiran; Yao, Jiayun; McLean, Kathleen E.; Stull, Roland; Pavlovic, Radenko; Davignon, Didier; Moran, Michael D.; Henderson, Sarah B.

    2016-11-01

    Fine particulate matter (PM2.5) generated by forest fires has been associated with a wide range of adverse health outcomes, including exacerbation of respiratory diseases and increased risk of mortality. Due to the unpredictable nature of forest fires, it is challenging for public health authorities to reliably evaluate the magnitude and duration of potential exposures before they occur. Smoke forecasting tools are a promising development from the public health perspective, but their widespread adoption is limited by their inherent uncertainties. Observed measurements from air quality monitoring networks and remote sensing platforms are more reliable, but they are inherently retrospective. It would be ideal to reduce the uncertainty in smoke forecasts by integrating any available observations. This study takes spatially resolved PM2.5 estimates from an empirical model that integrates air quality measurements with satellite data, and averages them with PM2.5 predictions from two smoke forecasting systems. Two different indicators of population respiratory health are then used to evaluate whether the blending improved the utility of the smoke forecasts. Among a total of six models, including two single forecasts and four blended forecasts, the blended estimates always performed better than the forecast values alone. Integrating measured observations into smoke forecasts could improve public health preparedness for smoke events, which are becoming more frequent and intense as the climate changes.

  2. TEMPO Early Adopters in Air-Quality Forecasting, Planning and Assessment, Pollution Emissions, Health, Agriculture, and Environmental Impacts: Applications and Decision Support

    NASA Astrophysics Data System (ADS)

    Newchurch, M.; Zavodsky, B.; Chance, K.; Haynes, J.; Lefer, B. L.; Naeger, A.

    2016-12-01

    The AQ research community has a long legacy of using space-based observations (e.g., Solar Backscatter Ultraviolet Instrument [SBUV], Global Ozone Monitoring Experiment [GOME], Ozone Monitoring Instrument [OMI], and the Ozone Mapping & Profiler Suite [OMPS]) to study atmospheric chemistry. These measurements have been used to observe day-to-day and year-to-year changes in atmospheric constituents. However, they have not been able to capture the diurnal variability of pollution with enough temporal or spatial fidelity and a low enough latency for regular use by operational decision makers. As a result, the operational AQ community has traditionally relied on ground-based (e.g., collection stations, LIDAR) and airborne observing systems to study tropospheric chemistry. In order to maximize its utility for applications and decision support, there is a need to educate the community about the game-changing potential for the geostationary TEMPO mission well ahead of its expected launch date early in the third decade of this millinium. This NASA mission will engage user communities and enable science across the NASA Applied Science Focus Areas of Health and Air Quality, Disasters, Water Resources, and Ecological Forecasting, In addition, topics discussed will provide opportunities for collaborations extending TEMPO applications to future program areas in Agriculture, Weather and Climate (including Numerical Weather Prediction), Energy, and Oceans.

  3. A review of AirQ Models and their applications for forecasting the air pollution health outcomes.

    PubMed

    Oliveri Conti, Gea; Heibati, Behzad; Kloog, Itai; Fiore, Maria; Ferrante, Margherita

    2017-03-01

    Even though clean air is considered as a basic requirement for the maintenance of human health, air pollution continues to pose a significant health threat in developed and developing countries alike. Monitoring and modeling of classic and emerging pollutants is vital to our knowledge of health outcomes in exposed subjects and to our ability to predict them. The ability to anticipate and manage changes in atmospheric pollutant concentrations relies on an accurate representation of the chemical state of the atmosphere. The task of providing the best possible analysis of air pollution thus requires efficient computational tools enabling efficient integration of observational data into models. A number of air quality models have been developed and play an important role in air quality management. Even though a large number of air quality models have been discussed or applied, their heterogeneity makes it difficult to select one approach above the others. This paper provides a brief review on air quality models with respect to several aspects such as prediction of health effects.

  4. Quantifying the effect of air quality control measures during the 2010 Commonwealth Games at Delhi, India

    NASA Astrophysics Data System (ADS)

    Beig, Gufran; Chate, Dilip M.; Ghude, Sachin. D.; Mahajan, A. S.; Srinivas, R.; Ali, K.; Sahu, S. K.; Parkhi, N.; Surendran, D.; Trimbake, H. R.

    2013-12-01

    In 2010, the XIX Commonwealth Games (CWG-2010) were held in India for the first time at Delhi and involved 71 commonwealth nations and dependencies with more than 6000 athletes participating in 272 events. This was the largest international multi-sport event to be staged in India and strict emission controls were imposed during the games in order to ensure improved air quality for the participating athletes as a significant portion of the population in Delhi is regularly exposed to elevated levels of pollution. The air quality control measures ranged from vehicular and traffic controls to relocation of factories and reduction of power plant emissions. In order to understand the effects of these policy induced control measures, a network of air quality and weather monitoring stations was set-up across different areas in Delhi under the Government of India's System of Air quality Forecasting And Research (SAFAR) project. Simultaneous measurements of aerosols, reactive trace gases (e.g. NOx, O3, CO) and meteorological parameters were made before, during and after CWG-2010. Contrary to expectations, the emission controls implemented were not sufficient to reduce the pollutants, instead in some cases, causing an increase. The measured pollutants regularly exceeded the National Ambient Air Quality limits over the games period. The reasons for this increase are attributed to an underestimation of the required control measures, which resulted in inadequate planning. The results indicate that any future air quality control measures need to be well planned and strictly imposed in order to improve the air quality in Delhi, which affects a large population and is deteriorating rapidly. Thus, the presence of systematic high resolution data and realistic emission inventories through networks such as SAFAR will be directly useful for the future.

  5. Rural southeast Texas air quality measurements during the 2006 Texas Air Quality Study.

    PubMed

    Schade, Gunnar W; Khan, Siraj; Park, Changhyoun; Boedeker, Ian

    2011-10-01

    The authors conducted air quality measurements of the criteria pollutants carbon monoxide, nitrogen oxides, and ozone together with meteorological measurements at a park site southeast of College Station, TX, during the 2006 Texas Air Quality Study II (TexAQS). Ozone, a primary focus of the measurements, was above 80 ppb during 3 days and above 75 ppb during additional 8 days in summer 2006, suggestive of possible violations of the ozone National Ambient Air Quality Standard (NAAQS) in this area. In concordance with other air quality measurements during the TexAQS II, elevated ozone mixing ratios coincided with northerly flows during days after cold front passages. Ozone background during these days was as high as 80 ppb, whereas southerly air flows generally provided for an ozone background lower than 40 ppb. Back trajectory analysis shows that local ozone mixing ratios can also be strongly affected by the Houston urban pollution plume, leading to late afternoon ozone increases of as high as 50 ppb above background under favorable transport conditions. The trajectory analysis also shows that ozone background increases steadily the longer a southern air mass resides over Texas after entering from the Gulf of Mexico. In light of these and other TexAQS findings, it appears that ozone air quality is affected throughout east Texas by both long-range and regional ozone transport, and that improvements therefore will require at least a regionally oriented instead of the current locally oriented ozone precursor reduction policies.

  6. Air Quality Applications Based on Space Observations: The Role of the 11 Years OMI Data Record and the Potentials for TROPOMI

    NASA Astrophysics Data System (ADS)

    Levelt, P.; Veefkind, J. P.; Kleipool, Q.; Eskes, H.; A, R. V. D.; Mijling, B.; Tamminen, J.; Joiner, J.; Bhartia, P. K.

    2015-12-01

    In the last three decades the capabilities of measuring the atmospheric composition from space did grow tremendously with ESA's ENVISAT and NASA's Eos-Aura satellite programmes. The potential to operationally monitor the atmospheric composition, like the meteorological community is doing for the physical parameters, is now within reach. At the same time, the importance for society of operational environmental monitoring, related to the ozone layer, air quality and climate change, became apparent. The Ozone Monitoring Instrument (OMI), launched on board of NASA's EOS-Aura spacecraft in on July 15, 2004, provides unique contributions to air quality monitoring from Space. The combination of urban scale resolution (13 x 24 km2 in nadir) and daily global coverage proved to be key features for the air quality community. The OMI data is currently used for improving the air quality forecasts, for inverting high-resolution emission maps, for UV forecast and for volcanic plume warning systems for aviation. Due to its 11 year continuous operation OMI now provides the longest NO2 record from space, which is essential to understand the changes in emissions globally. In 2016 Tropospheric Monitoring Instrument (TROPOMI), will be launched on board ESA's Sentinel 5 Precursor satellite. TROPOMI will have a spatial resolution of 7x7 km2 in nadir; a more than 6 times improvement over OMI. The high spatial resolution serves two goals: (1) emissions sources can be detected with even better accuracy and (2) the number of cloud-free ground pixels will increase substantially. TROPOMI also adds additional spectral bands that allow for better cloud corrections, as well as the retrieval of carbon monoxide and methane. TROPOMI will be an important satellite mission for the Copernicus atmosphere service. TROPOMI will play a key role in the Air Quality Constellation, being the polar instruments that can link the 3 GEO UVN instruments, Sentinel 4, TEMPO and GEMS. Thus, TROPOMI can serve as a

  7. 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.

  8. Air Quality Management Process Cycle

    EPA Pesticide Factsheets

    Air quality management are activities a regulatory authority undertakes to protect human health and the environment from the harmful effects of air pollution. The process of managing air quality can be illustrated as a cycle of inter-related elements.

  9. 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).

  10. [Air quality surveillance in France].

    PubMed

    Téton, S; Robin, D; Genève, C

    2009-10-01

    As air quality has a direct impact on human health, its monitoring is imperative. In France, this task was entrusted by the government (Air Law of 1996) to organisations with territorial responsibility: the Registered Associations for the Surveillance of Air Quality. The type and level of pollution evolve: from industrial and sulphur pollution in the seventies, to urban and photochemical pollution today and to nanoparticles, pesticides and pollutants in buildings tomorrow. The tools, the skills and the roles of the different people involved in air quality control follow these sometimes rapid transitions in connection with an increasingly precise understanding of the relationship between health and the environment and of the considerable research on the subject. This article describes the mechanisms of air quality monitoring in France.

  11. Process air quality data

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

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

  12. Forecasting human exposure to atmospheric pollutants in Portugal - A modelling approach

    NASA Astrophysics Data System (ADS)

    Borrego, C.; Sá, E.; Monteiro, A.; Ferreira, J.; Miranda, A. I.

    2009-12-01

    Air pollution has become one main environmental concern because of its known impact on human health. Aiming to inform the population about the air they are breathing, several air quality modelling systems have been developed and tested allowing the assessment and forecast of air pollution ambient levels in many countries. However, every day, an individual is exposed to different concentrations of atmospheric pollutants as he/she moves from and to different outdoor and indoor places (the so-called microenvironments). Therefore, a more efficient way to prevent the population from the health risks caused by air pollution should be based on exposure rather than air concentrations estimations. The objective of the present study is to develop a methodology to forecast the human exposure of the Portuguese population based on the air quality forecasting system available and validated for Portugal since 2005. Besides that, a long-term evaluation of human exposure estimates aims to be obtained using one-year of this forecasting system application. Additionally, a hypothetical 50% emission reduction scenario has been designed and studied as a contribution to study emission reduction strategies impact on human exposure. To estimate the population exposure the forecasting results of the air quality modelling system MM5-CHIMERE have been combined with the population spatial distribution over Portugal and their time-activity patterns, i.e. the fraction of the day time spent in specific indoor and outdoor places. The population characterization concerning age, work, type of occupation and related time spent was obtained from national census and available enquiries performed by the National Institute of Statistics. A daily exposure estimation module has been developed gathering all these data and considering empirical indoor/outdoor relations from literature to calculate the indoor concentrations in each one of the microenvironments considered, namely home, office/school, and other

  13. 32 CFR 989.30 - Air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Air quality. 989.30 Section 989.30 National... ENVIRONMENTAL IMPACT ANALYSIS PROCESS (EIAP) § 989.30 Air quality. Section 176(c) of the Clean Air Act..., Air Quality Compliance. 10 10 See footnote 1 to § 989.1. ...

  14. 32 CFR 989.30 - Air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 32 National Defense 6 2012-07-01 2012-07-01 false Air quality. 989.30 Section 989.30 National... ENVIRONMENTAL IMPACT ANALYSIS PROCESS (EIAP) § 989.30 Air quality. Section 176(c) of the Clean Air Act..., Air Quality Compliance. 10 10 See footnote 1 to § 989.1. ...

  15. 32 CFR 989.30 - Air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 32 National Defense 6 2014-07-01 2014-07-01 false Air quality. 989.30 Section 989.30 National... ENVIRONMENTAL IMPACT ANALYSIS PROCESS (EIAP) § 989.30 Air quality. Section 176(c) of the Clean Air Act..., Air Quality Compliance. 10 10 See footnote 1 to § 989.1. ...

  16. 32 CFR 989.30 - Air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 32 National Defense 6 2013-07-01 2013-07-01 false Air quality. 989.30 Section 989.30 National... ENVIRONMENTAL IMPACT ANALYSIS PROCESS (EIAP) § 989.30 Air quality. Section 176(c) of the Clean Air Act..., Air Quality Compliance. 10 10 See footnote 1 to § 989.1. ...

  17. 32 CFR 989.30 - Air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 32 National Defense 6 2011-07-01 2011-07-01 false Air quality. 989.30 Section 989.30 National... ENVIRONMENTAL IMPACT ANALYSIS PROCESS (EIAP) § 989.30 Air quality. Section 176(c) of the Clean Air Act..., Air Quality Compliance. 10 10 See footnote 1 to § 989.1. ...

  18. 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

  19. Chemical weather forecasting for the Yangtze River Delta

    NASA Astrophysics Data System (ADS)

    Xie, Y.; Xu, J.; Zhou, G.; Chang, L.; Chen, B.

    2016-12-01

    Shanghai is one of the largest megacities in the world. With rapid economic growth of the city and its surrounding areas in recent years, air pollution has posed adverse effects on public health and ecosystem. In winter heavy pollution episodes are often associated with PM exceedances under stagnant conditions or transport events, whereas in summer the region frequently experiences elevated O3 levels. Chemical weather prediction systems with the WRF-Chem and CMAQ models are being developed to support air quality and haze forecasting for Shanghai and the Yangtze River Delta region. We will present main components of the modeling system, forecasting products, as well as evaluation results. Evaluation of the WRF-Chem forecasts show the model has generally good ability to capture the temporal variations of O3 and PM2.5. Substantial regional differences exist, with the best performance in Shanghai. Meanwhile, the forecasts tend to degrade during highly polluted episodes and transitional time periods, which highlights the need to improve model representation of key process (e.g. meteorological fields and formation of secondary pollutants). Recent work includes using the ECMWF global model forecasts as chemical boundary conditions for our regional model. We investigate the impact of chemical downscaling, and also compare the results from different models participated in the PANDA (PArtnership with chiNa on space Data) project. Results from ongoing efforts (e.g. chemical weather forecasting driven by SMS regional high resolution NWP) will also be presented.

  20. EVALUATION OF SEVERAL PM 2.5 FORECAST MODELS USING DATA COLLECTED DURING THE ICARTT/NEAQS 2004 FIELD STUDY

    EPA Science Inventory

    Real-time forecasts of PM2.5 aerosol mass from seven air-quality forecast models (AQFMs) are statistically evaluated against observations collected in the northeastern U.S. and southeastern Canada from two surface networks and aircraft data during the summer of 2004 IC...

  1. Operational forecast products and applications based on WRF/Chem

    NASA Astrophysics Data System (ADS)

    Hirtl, Marcus; Flandorfer, Claudia; Langer, Matthias; Mantovani, Simone; Olefs, Marc; Schellander-Gorgas, Theresa

    2015-04-01

    The responsibilities of the national weather service of Austria (ZAMG) 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 ZAMG conducts daily Air-Quality forecasts using the on-line coupled model WRF/Chem. The mother domain expands over Europe, North Africa and parts of Russia. The nested domain includes the alpine region and has a horizontal resolution of 4 km. Local emissions (Austria) are used in combination with European inventories (TNO and EMEP) for the simulations. The modeling system is presented and the results from the evaluation of the assimilation of pollutants using the 3D-VAR software GSI is shown. Currently observational data (PM10 and O3) from the Austrian Air-Quality network and from European stations (EEA) are assimilated into the model on an operational basis. In addition PM maps are produced using Aerosol Optical Thickness (AOT) observations from MODIS in combination with model data using machine learning techniques. The modeling system is operationally evaluated with different data sets. The emphasis of the application is on the forecast of pollutants which are compared to the hourly values (PM10, O3 and NO2) of the Austrian Air-Quality network. As the meteorological conditions are important for transport and chemical processes, some parameters like wind and precipitation are automatically evaluated (SAL diagrams, maps, …) with other models (e.g. ECMWF, AROME, …) and ground stations via web interface. The prediction of the AOT is also important for operators of solar power plants. In the past Numerical Weather Prediction (NWP) models were used to predict the AOT based on cloud forecasts at the ZAMG. These models do not consider the spatial and temporal variation of the aerosol distribution in the atmosphere with a consequent impact on the accuracy of forecasts especially during clear-sky days

  2. Development and implementation of a remote-sensing and in situ data-assimilating version of CMAQ for operational PM2.5 forecasting. Part 1: MODIS aerosol optical depth (AOD) data-assimilation design and testing.

    PubMed

    McHenry, John N; Vukovich, Jeffery M; Hsu, N Christina

    2015-12-01

    This two-part paper reports on the development, implementation, and improvement of a version of the Community Multi-Scale Air Quality (CMAQ) model that assimilates real-time remotely-sensed aerosol optical depth (AOD) information and ground-based PM2.5 monitor data in routine prognostic application. The model is being used by operational air quality forecasters to help guide their daily issuance of state or local-agency-based air quality alerts (e.g. action days, health advisories). Part 1 describes the development and testing of the initial assimilation capability, which was implemented offline in partnership with NASA and the Visibility Improvement State and Tribal Association of the Southeast (VISTAS) Regional Planning Organization (RPO). In the initial effort, MODIS-derived aerosol optical depth (AOD) data are input into a variational data-assimilation scheme using both the traditional Dark Target and relatively new "Deep Blue" retrieval methods. Evaluation of the developmental offline version, reported in Part 1 here, showed sufficient promise to implement the capability within the online, prognostic operational model described in Part 2. In Part 2, the addition of real-time surface PM2.5 monitoring data to improve the assimilation and an initial evaluation of the prognostic modeling system across the continental United States (CONUS) is presented. Air quality forecasts are now routinely used to understand when air pollution may reach unhealthy levels. For the first time, an operational air quality forecast model that includes the assimilation of remotely-sensed aerosol optical depth and ground based PM2.5 observations is being used. The assimilation enables quantifiable improvements in model forecast skill, which improves confidence in the accuracy of the officially-issued forecasts. This helps air quality stakeholders be more effective in taking mitigating actions (reducing power consumption, ride-sharing, etc.) and avoiding exposures that could otherwise

  3. Air Quality Analysis

    EPA Pesticide Factsheets

    This site provides information for air quality data analysts inside and outside EPA. Much of the information is in the form of documented analyses that support the review of the national air qualiyt standards.

  4. 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.

  5. ASSESSMENT OF AN ENSEMBLE OF SEVEN REAL-TIME OZONE FORECASTS OVER EASTERN NORTH AMERICA DURING THE SUMMER OF 2004

    EPA Science Inventory

    The real-time forecasts of ozone (O3) from seven air quality forecast models (AQFMs) are statistically evaluated against observations collected during July and August of 2004 (53 days) through the Aerometric Information Retrieval Now (AIRNow) network at roughly 340 mon...

  6. Developing a Peak Wind Probability Forecast Tool for Kennedy Space Center and Cape Canaveral Air Force Station

    NASA Technical Reports Server (NTRS)

    Lambert, WInifred; Roeder, William

    2007-01-01

    This conference presentation describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) in east-central Florida. The peak winds are an important forecast element for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a short-range peak-wind forecast tool to assist in forecasting LCC violations. The tool will include climatologies of the 5-minute mean and peak winds by month, hour, and direction, and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

  7. Toward Obtaining Reliable Particulate Air Quality Information from Satellites

    NASA Astrophysics Data System (ADS)

    Strawa, A. W.; Chatfield, R. B.; Legg, M.; Esswein, R.; Justice, E.

    2009-12-01

    factor. The relationships between the predictor and the response are discussed. Al-Saadi, J., J. Szykman, R.B. Pierce, C. Kittaka, D. Neil, D.A. Chu, L. Remer, L. Gumley, E. Prins, L. Weinstock, C. MacDonald, R. Wayland, F. Dimmick, and J. Fishman, Imporving national air quality forecasts with satellite aerosol observations, Bull. Amer, Met. Soc. (Sept), 1249-1261, 2005. Engle-Cox, J.A., C.H. Holloman, B.W. Coutant, and R.M. Hoff, Qualitative and quantitative evaluation of MODIS satellite sensor data for regional and urban scale air quality, Atmos. En., 38, 2495-2509, 2004. Hsu, N.C., S.-C. Tsay, M.D. King, and J.R. Herman, Deep blue retrievals of Asian Aerosol properties during ACE-Asia, IEEE Trans. on Geosci.a nd Remote Sensing, 44 (11), 3180, 2006. Pelletier, B., R. Santer, and J. Vidot, Retrieving of particulate matter from optical measurements: A semi-parametric approach, J. Geophys. Res., 112 (D06208), 2007.

  8. The forecasting research of early warning systems for atmospheric pollutants: A case in Yangtze River Delta region

    NASA Astrophysics Data System (ADS)

    Song, Yiliao; Qin, Shanshan; Qu, Jiansheng; Liu, Feng

    2015-10-01

    The issue of air quality regarding PM pollution levels in China is a focus of public attention. To address that issue, to date, a series of studies is in progress, including PM monitoring programs, PM source apportionment, and the enactment of new ambient air quality index standards. However, related research concerning computer modeling for PM future trends estimation is rare, despite its significance to forecasting and early warning systems. Thereby, a study regarding deterministic and interval forecasts of PM is performed. In this study, data on hourly and 12 h-averaged air pollutants are applied to forecast PM concentrations within the Yangtze River Delta (YRD) region of China. The characteristics of PM emissions have been primarily examined and analyzed using different distribution functions. To improve the distribution fitting that is crucial for estimating PM levels, an artificial intelligence algorithm is incorporated to select the optimal parameters. Following that step, an ANF model is used to conduct deterministic forecasts of PM. With the identified distributions and deterministic forecasts, different levels of PM intervals are estimated. The results indicate that the lognormal or gamma distributions are highly representative of the recorded PM data with a goodness-of-fit R2 of approximately 0.998. Furthermore, the results of the evaluation metrics (MSE, MAPE and CP, AW) also show high accuracy within the deterministic and interval forecasts of PM, indicating that this method enables the informative and effective quantification of future PM trends.

  9. Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service.

    PubMed

    Bastl, Katharina; Berger, Uwe; Kmenta, Maximilian

    2017-05-08

    Pollen forecasts are highly valuable for allergen avoidance and thus raising the quality of life of persons concerned by pollen allergies. They are considered as valuable free services for the public. Careful scientific evaluation of pollen forecasts in terms of accurateness and reliability has not been available till date. The aim of this study was to analyze 9 mobile apps, which deliver pollen information and pollen forecasts, with a focus on their accurateness regarding the prediction of the pollen load in the grass pollen season 2016 to assess their usefulness for pollen allergy sufferers. The following number of apps was evaluated for each location: 3 apps for Vienna (Austria), 4 apps for Berlin (Germany), and 1 app each for Basel (Switzerland) and London (United Kingdom). All mobile apps were freely available. Today's grass pollen forecast was compared throughout the defined grass pollen season at each respective location with measured grass pollen concentrations. Hit rates were calculated for the exact performance and for a tolerance in a range of ±2 and ±4 pollen per cubic meter. In general, for most apps, hit rates score around 50% (6 apps). It was found that 1 app showed better results, whereas 3 apps performed less well. Hit rates increased when calculated with tolerances for most apps. In contrast, the forecast for the "readiness to flower" for grasses was performed at a sufficiently accurate level, although only two apps provided such a forecast. The last of those forecasts coincided with the first moderate grass pollen load on the predicted day or 3 days after and performed even from about a month before well within the range of 3 days. Advertisement was present in 3 of the 9 analyzed apps, whereas an imprint mentioning institutions with experience in pollen forecasting was present in only three other apps. The quality of pollen forecasts is in need of improvement, and quality control for pollen forecasts is recommended to avoid potential harm to

  10. 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…

  11. Weather Research and Forecasting Model Wind Sensitivity Study at Edwards Air Force Base, CA

    NASA Technical Reports Server (NTRS)

    Watson, Leela R.; Bauman, William H., III

    2008-01-01

    NASA prefers to land the space shuttle at Kennedy Space Center (KSC). When weather conditions violate Flight Rules at KSC, NASA will usually divert the shuttle landing to Edwards Air Force Base (EAFB) in Southern California. But forecasting surface winds at EAFB is a challenge for the Spaceflight Meteorology Group (SMG) forecasters due to the complex terrain that surrounds EAFB, One particular phenomena identified by SMG is that makes it difficult to forecast the EAFB surface winds is called "wind cycling". This occurs when wind speeds and directions oscillate among towers near the EAFB runway leading to a challenging deorbit bum forecast for shuttle landings. The large-scale numerical weather prediction models cannot properly resolve the wind field due to their coarse horizontal resolutions, so a properly tuned high-resolution mesoscale model is needed. The Weather Research and Forecasting (WRF) model meets this requirement. The AMU assessed the different WRF model options to determine which configuration best predicted surface wind speed and direction at EAFB, To do so, the AMU compared the WRF model performance using two hot start initializations with the Advanced Research WRF and Non-hydrostatic Mesoscale Model dynamical cores and compared model performance while varying the physics options.

  12. Meteorological air quality forecasting using the WRF-Chem model during the LMOS2017 field campaign

    NASA Astrophysics Data System (ADS)

    Stanier, C. O.; Abdioskouei, M.; Carmichael, G. R.; Christiansen, M.; Sobhani, N.

    2017-12-01

    The Lake Michigan Ozone Study (LMOS 2017) occurred during May and June 2017 to address the high ozone episodes in coastal communities surrounding Lake Michigan. Aircraft, ship, mobile lab, and ground-based stations were used in this campaign to build an extensive dataset regarding ozone, its precursors, and particulate matter. The University of Iowa produced high-resolution (4x4 km2 horizontal resolution and 53 vertical levels) forecast products using the WRF-Chem modeling system in support of experimental planning during LMOS 2017. The base forecast system used WRF-Chem 3.6.1 and updated National Emission Inventory (NEI-2011v2). In the updated NEI-2011v2, we reduced the NOx emissions by 28% based on EPA's estimated NOx trends from 2011 to 2017. We ran another daily forecast (perturbed forecast) with 50% reduced NOx emission to capture the sensitivity of ozone to NOx emission and account for the impact of weekend emissions on ozone values. Preliminary in-field evaluation of model performance for clouds, on-shore flows, and surface and aircraft sampled ozone and NOx concentrations found that the model successfully captured much of the observed synoptic variability of onshore flows. The model captured the variability of O3 well, but underpredicted peak ozone during high O3 episodes. In post-campaign WRF-Chem simulations, we investigated the sensitivity of the model to the hydrocarbon emission.

  13. 77 FR 52277 - Approval of Air Quality Implementation Plans; California; South Coast Air Quality Management...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-29

    ... Quality Implementation Plans; California; South Coast Air Quality Management District; Prevention of... rule. SUMMARY: EPA is proposing approval of a permitting rule submitted for the South Coast Air Quality Management District (District) portion of the California State Implementation Plan (SIP). The State is...

  14. The Co-Benefits of Global and Regional Greenhouse Gas Mitigation on US Air Quality at Fine Resolution

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Bowden, J. H.; Adelman, Z.; Naik, V.; Horowitz, L. W.; Smith, S.; West, J. J.

    2014-12-01

    Reducing greenhouse gases (GHGs) not only slows climate change, but can also have co-benefits for improved air quality. In this study, we examine the co-benefits of global and regional GHG mitigation on US air quality at fine resolution through dynamical downscaling, using the latest Community Multi-scale Air Quality (CMAQ) model. We will investigate the co-benefits on US air quality due to domestic GHG mitigation alone, and due to mitigation outside of the US. We also quantity the co-benefits resulting from reductions in co-emitted air pollutants versus slowing climate change and its effects on air quality. Projected climate in the 2050s from the IPCC RCP4.5 and RCP8.5 scenarios is dynamically downscaled with the Weather Research and Forecasting model (WRF). Anthropogenic emissions projections from the RCP4.5 scenario and its reference (REF), are directly processed in SMOKE to provide temporally- and spatially-resolved CMAQ emission input files. Chemical boundary conditions (BCs) are obtained from West et al. (2013), who studied the co-benefits of global GHG reductions on global air quality and human health. Our preliminary results show that the global GHG reduction (RCP4.5 relative to REF) reduces the 1hr daily maximum ozone by 3.3 ppbv annually over entire US, as high as 6 ppbv in September. The west coast of California and the Northeast US are the regions that benefit most. By comparing different scenarios, we find that foreign countries' GHGs mitigation has a larger influence on the US ozone decreases (accounting for 77% of the total decrease), compared with 23% from domestic GHG mitigation only, highlighting the importance of methane reductions and the intercontinental transport of air pollutants. The reduction of global co-emitted air pollutants has a more pronounced effect on ozone decreasing, relative to the effect from slowing climate and its effects on air quality. We also plan to report co-benefits for PM2.5 in the US.

  15. Indoor Air Quality in Chemistry Laboratories.

    ERIC Educational Resources Information Center

    Hays, Steve M.

    This paper presents air quality and ventilation data from an existing chemical laboratory facility and discusses the work practice changes implemented in response to deficiencies in ventilation. General methods for improving air quality in existing laboratories are presented and investigation techniques for characterizing air quality are…

  16. Enhancing indoor air quality -The air filter advantage.

    PubMed

    Vijayan, Vannan Kandi; Paramesh, Haralappa; Salvi, Sundeep Santosh; Dalal, Alpa Anil Kumar

    2015-01-01

    Air pollution has become the world's single biggest environmental health risk, linked to around 7 million deaths in 2012 according to a recent World Health Organisation (WHO) report. The new data further reveals a stronger link between, indoor and outdoor air pollution exposure and cardiovascular diseases, such as strokes and ischemic heart disease, as well as between air pollution and cancer. The role of air pollution in the development of respiratory diseases, including acute respiratory infections and chronic obstructive pulmonary diseases, is well known. While both indoor and outdoor pollution affect health, recent statistics on the impact of household indoor pollutants (HAP) is alarming. The WHO factsheet on HAP and health states that 3.8 million premature deaths annually - including stroke, ischemic heart disease, chronic obstructive pulmonary disease (COPD) and lung cancer are attributed to exposure to household air pollution. Use of air cleaners and filters are one of the suggested strategies to improve indoor air quality. This review discusses the impact of air pollutants with special focus on indoor air pollutants and the benefits of air filters in improving indoor air quality.

  17. Colorado Air Quality Control Regulations and Ambient Air Quality Standards.

    ERIC Educational Resources Information Center

    Colorado State Dept. of Health, Denver. Div. of Air Pollution Control.

    Regulations and standards relative to air quality control in Colorado are defined in this publication. Presented first are definitions of terms, a statement of intent, and general provisions applicable to all emission control regulations adopted by the Colorado Air Pollution Control Commission. Following this, three regulations are enumerated: (1)…

  18. Indoor Air Quality in Schools: Clean Air Is Good Business.

    ERIC Educational Resources Information Center

    Guarneiri, Michele A.

    2003-01-01

    Describes the effect of poor indoor air quality (IAQ) on student health, the cost of safeguarding good IAQ, the cause of poor IAQ in schools, how to tell whether a school has an IAQ problem, and how the U.S. Environmental Protection Agency can help schools improve indoor air quality though the use of their free "Indoor Air Quality Tools for…

  19. Air-quality and Climatic Consequences of Bioenergy Crop Cultivation

    NASA Astrophysics Data System (ADS)

    Porter, William Christian

    Bioenergy is expected to play an increasingly significant role in the global energy budget. In addition to the use of liquid energy forms such as ethanol and biodiesel, electricity generation using processed energy crops as a partial or full coal alternative is expected to increase, requiring large-scale conversions of land for the cultivation of bioenergy feedstocks such as cane, grasses, or short rotation coppice. With land-use change identified as a major contributor to changes in the emission of biogenic volatile organic compounds (BVOCs), many of which are known contributors to the pollutants ozone (O 3) and fine particulate matter (PM2.5), careful review of crop emission profiles and local atmospheric chemistry will be necessary to mitigate any unintended air-quality consequences. In this work, the atmospheric consequences of bioenergy crop replacement are examined using both the high-resolution regional chemical transport model WRF/Chem (Weather Research and Forecasting with Chemistry) and the global climate model CESM (Community Earth System Model). Regional sensitivities to several representative crop types are analyzed, and the impacts of each crop on air quality and climate are compared. Overall, the high emitting crops (eucalyptus and giant reed) were found to produce climate and human health costs totaling up to 40% of the value of CO 2 emissions prevented, while the related costs of the lowest-emitting crop (switchgrass) were negligible.

  20. A Method for Forecasting the Commercial Air Traffic Schedule in the Future

    NASA Technical Reports Server (NTRS)

    Long, Dou; Lee, David; Gaier, Eric; Johnson, Jesse; Kostiuk, Peter

    1999-01-01

    This report presents an integrated set of models that forecasts air carriers' future operations when delays due to limited terminal-area capacity are considered. This report models the industry as a whole, avoiding unnecessary details of competition among the carriers. To develop the schedule outputs, we first present a model to forecast the unconstrained flight schedules in the future, based on the assumption of rational behavior of the carriers. Then we develop a method to modify the unconstrained schedules, accounting for effects of congestion due to limited NAS capacities. Our underlying assumption is that carriers will modify their operations to keep mean delays within certain limits. We estimate values for those limits from changes in planned block times reflected in the OAG. Our method for modifying schedules takes many means of reducing the delays into considerations, albeit some of them indirectly. The direct actions include depeaking, operating in off-hours, and reducing hub airports'operations. Indirect actions include using secondary airports, using larger aircraft, and selecting new hub airports, which, we assume, have already been modeled in the FAA's TAF. Users of our suite of models can substitute an alternative forecast for the TAF.

  1. Forecasting Lightning at Kennedy Space Center/Cape Canaveral Air Force Station, Florida

    NASA Technical Reports Server (NTRS)

    Lambert, Winfred; Wheeler, Mark; Roeder, William

    2005-01-01

    The Applied Meteorology Unit (AMU) developed a set of statistical forecast equations that provide a probability of lightning occurrence on Kennedy Space Center (KSC) I Cape Canaveral Air Force Station (CCAFS) for the day during the warm season (May September). The 45th Weather Squadron (45 WS) forecasters at CCAFS in Florida include a probability of lightning occurrence in their daily 24-hour and weekly planning forecasts, which are briefed at 1100 UTC (0700 EDT). This information is used for general scheduling of operations at CCAFS and KSC. Forecasters at the Spaceflight Meteorology Group also make thunderstorm forecasts for the KSC/CCAFS area during Shuttle flight operations. Much of the current lightning probability forecast at both groups is based on a subjective analysis of model and observational data. The objective tool currently available is the Neumann-Pfeffer Thunderstorm Index (NPTI, Neumann 1971), developed specifically for the KSCICCAFS area over 30 years ago. However, recent studies have shown that 1-day persistence provides a better forecast than the NPTI, indicating that the NPTI needed to be upgraded or replaced. Because they require a tool that provides a reliable estimate of the daily thunderstorm probability forecast, the 45 WS forecasters requested that the AMU develop a new lightning probability forecast tool using recent data and more sophisticated techniques now possible through more computing power than that available over 30 years ago. The equation development incorporated results from two research projects that investigated causes of lightning occurrence near KSCICCAFS and over the Florida peninsula. One proved that logistic regression outperformed the linear regression method used in NPTI, even when the same predictors were used. The other study found relationships between large scale flow regimes and spatial lightning distributions over Florida. Lightning, probabilities based on these flow regimes were used as candidate predictors in

  2. Sensitivity of the Community Multiscale Air Quality (CMAQ) Model v4.7 Results for the Eastern United States to MM5 and WRF Meteorological Drivers

    EPA Science Inventory

    This paper presents a comparison of the operational performance of two Community Multiscale Air Quality (CMAQ) model v4.7 simulations that utilize input data from the 5th generation Mesoscale Model MM5 and the Weather Research and Forecasting (WRF) meteorological models.

  3. AIRS associated accomplishments at the JCSDA: First use of full spatial resolution hyperspectral data show significant improvements in global forecasts

    NASA Astrophysics Data System (ADS)

    Le Marshall, J.; Jung, J.; Lord, S. J.; Derber, J. C.; Treadon, R.; Joiner, J.; Goldberg, M.; Wolf, W.; Liu, H. C.

    2005-08-01

    The National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Administration (NOAA), and Department of Defense (DoD), Joint Center for Satellite Data Assimilation (JCSDA) was established in 2000/2001. The goal of the JCSDA is to accelerate the use of observations from earth-orbiting satellites into operational numerical environmental analysis and prediction systems for the purpose of improving weather and oceanic forecasts, seasonal climate forecasts and the accuracy of climate data sets. As a result, a series of data assimilation experiments were undertaken at the JCSDA as part of the preparations for the operational assimilation of AIRS data by its partner organizations1,2. Here, for the first time full spatial resolution radiance data, available in real-time from the AIRS instrument, were used at the JCSDA in data assimilation studies over the globe utilizing the operational NCEP Global Forecast System (GFS). The radiance data from each channel of the instrument were carefully screened for cloud effects and those radiances which were deemed to be clear of cloud effects were used by the GFS forecast system. The result of these assimilation trials has been a first demonstration of significant improvements in forecast skill over both the Northern and Southern Hemisphere compared to the operational system without AIRS data. The experimental system was designed in a way that rendered it feasible for operational application, and that constraint involved using the subset of AIRS channels chosen for operational distribution and an analysis methodology close to the current analysis practice, with particular consideration given to time limitations. As a result, operational application of these AIRS data was enabled by the recent NCEP operational upgrade. In addition, because of the improved impact resulting from use of this enhanced data set compared to that used operationally to date, provision of a realtime "warmest field" of view data set

  4. NOAA's National Air Quality Prediction and Development of Aerosol and Atmospheric Composition Prediction Components for NGGPS

    NASA Astrophysics Data System (ADS)

    Stajner, I.; McQueen, J.; Lee, P.; Stein, A. F.; Wilczak, J. M.; Upadhayay, S.; daSilva, A.; Lu, C. H.; Grell, G. A.; Pierce, R. B.

    2017-12-01

    NOAA's operational air quality predictions of ozone, fine particulate matter (PM2.5) and wildfire smoke over the United States and airborne dust over the contiguous 48 states are distributed at http://airquality.weather.gov. The National Air Quality Forecast Capability (NAQFC) providing these predictions was updated in June 2017. Ozone and PM2.5 predictions are now produced using the system linking the Community Multiscale Air Quality model (CMAQ) version 5.0.2 with meteorological inputs from the North American Mesoscale Forecast System (NAM) version 4. Predictions of PM2.5 include intermittent dust emissions and wildfire emissions from an updated version of BlueSky system. For the latter, the CMAQ system is initialized by rerunning it over the previous 24 hours to include wildfire emissions at the time when they were observed from the satellites. Post processing to reduce the bias in PM2.5 prediction was updated using the Kalman filter analog (KFAN) technique. Dust related aerosol species at the CMAQ domain lateral boundaries now come from the NEMS Global Aerosol Component (NGAC) v2 predictions. Further development of NAQFC includes testing of CMAQ predictions to 72 hours, Canadian fire emissions data from Environment and Climate Change Canada (ECCC) and the KFAN technique to reduce bias in ozone predictions. NOAA is developing the Next Generation Global Predictions System (NGGPS) with an aerosol and gaseous atmospheric composition component to improve and integrate aerosol and ozone predictions and evaluate their impacts on physics, data assimilation and weather prediction. Efforts are underway to improve cloud microphysics, investigate aerosol effects and include representations of atmospheric composition of varying complexity into NGGPS: from the operational ozone parameterization, GOCART aerosols, with simplified ozone chemistry, to CMAQ chemistry with aerosol modules. We will present progress on community building, planning and development of NGGPS.

  5. ASSESSMENT OF THE WINTER-TIME PERFORMANCE OF DEVELOPMENTAL PARTICULATE MATTER FORECASTS WITH THE ETA-CMAQ MODELING SYSTEM

    EPA Science Inventory

    It is desirable for local air quality agencies to accurately forecast tropospheric PM2.5 concentrations to alert the sensitive population of the onset, severity and duration of unhealthy air, and to encourage the public and industry to reduce emissions-producing activi...

  6. Parents' Guide to School Indoor Air Quality.

    ERIC Educational Resources Information Center

    Healthy Schools Network, Inc., Albany, NY.

    This parents' guide presents articles on school indoor air pollution, children's health and the symptoms of indoor air pollution, and how schools can improve their air quality. Also included are tips on what to do if the school ignores air quality problems, and some examples of what school districts should be doing to improve their air quality.…

  7. Assessing the impacts of seasonal and vertical atmospheric conditions on air quality over the Pearl River Delta region

    NASA Astrophysics Data System (ADS)

    Tong, Cheuk Hei Marcus; Yim, Steve Hung Lam; Rothenberg, Daniel; Wang, Chien; Lin, Chuan-Yao; Chen, Yongqin David; Lau, Ngar Cheung

    2018-05-01

    Air pollution is an increasingly concerning problem in many metropolitan areas due to its adverse public health and environmental impacts. Vertical atmospheric conditions have strong effects on vertical mixing of air pollutants, which directly affects surface air quality. The characteristics and magnitude of how vertical atmospheric conditions affect surface air quality, which are critical to future air quality projections, have not yet been fully understood. This study aims to enhance understanding of the annual and seasonal sensitivities of air pollution to both surface and vertical atmospheric conditions. Based on both surface and vertical meteorological characteristics provided by 1994-2003 monthly dynamic downscaling data from the Weather and Research Forecast Model, we develop generalized linear models (GLMs) to study the relationships between surface air pollutants (ozone, respirable suspended particulates, and sulfur dioxide) and atmospheric conditions in the Pearl River Delta (PRD) region. Applying Principal Component Regression (PCR) to address multi-collinearity, we study the contributions of various meteorological variables to pollutants' concentration levels based on the loading and model coefficient of major principal components. Our results show that relatively high pollutant concentration occurs under relatively low mid-level troposphere temperature gradients, low relative humidity, weak southerly wind (or strong northerly wind) and weak westerly wind (or strong easterly wind). Moreover, the correlations vary among pollutant species, seasons, and meteorological variables at various altitudes. In general, pollutant sensitivity to meteorological variables is found to be greater in winter than in other seasons, and the sensitivity of ozone to meteorology differs from that of the other two pollutants. Applying our GLMs to anomalous air pollution episodes, we find that meteorological variables up to mid troposphere (∼700 mb) play an important role in

  8. 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.

  9. Performance assessment of retrospective meteorological inputs for use in air quality modeling during TexAQS 2006

    NASA Astrophysics Data System (ADS)

    Ngan, Fong; Byun, Daewon; Kim, Hyuncheol; Lee, Daegyun; Rappenglück, Bernhard; Pour-Biazar, Arastoo

    2012-07-01

    To achieve more accurate meteorological inputs than was used in the daily forecast for studying the TexAQS 2006 air quality, retrospective simulations were conducted using objective analysis and 3D/surface analysis nudging with surface and upper observations. Model ozone using the assimilated meteorological fields with improved wind fields shows better agreement with the observation compared to the forecasting results. In the post-frontal conditions, important factors for ozone modeling in terms of wind patterns are the weak easterlies in the morning for bringing in industrial emissions to the city and the subsequent clockwise turning of the wind direction induced by the Coriolis force superimposing the sea breeze, which keeps pollutants in the urban area. Objective analysis and nudging employed in the retrospective simulation minimize the wind bias but are not able to compensate for the general flow pattern biases inherited from large scale inputs. By using an alternative analyses data for initializing the meteorological simulation, the model can re-produce the flow pattern and generate the ozone peak location closer to the reality. The inaccurate simulation of precipitation and cloudiness cause over-prediction of ozone occasionally. Since there are limitations in the meteorological model to simulate precipitation and cloudiness in the fine scale domain (less than 4-km grid), the satellite-based cloud is an alternative way to provide necessary inputs for the retrospective study of air quality.

  10. Air quality remote sensing over alpine regions with METEOSAT SEVIRI

    NASA Astrophysics Data System (ADS)

    Emili, E.; Popp, C.; Petitta, M.; Riffler, M.; Wunderle, S.

    2009-04-01

    It is well demonstrated that small aerosol particles or particulate matter (PM10 and PM2.5) affect air quality and can have severe effects on human's health. Hence, it is of great interest for public institutions to have an efficient PM monitoring network. In the last decades this data has been provided from ground-based instruments. Moreover, due to the fast development of space-borne remote sensing instruments, we can now be able to take advantage of air pollution measurements from space, which bears the potential to fill up the gap of spatial coverage from ground-based networks. This also improves the capability to assess air pollutants transport properties together with a better implementation in forecasting data assimilation procedures. In this study we examine the possibility of using data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI), on-board of the geostationary Meteosat Second Generation (MSG) platform, to provide PM concentrations values over Switzerland. SEVIRI's high temporal resolution (15 minutes) could be very useful in investigating the daily behaviour of air pollutants and therefore be a good complement to measurements from polar orbiting sensors (e.g. MODIS). Switzerland is of particular interest because of its mountainous orography that hampers pollutants dispersion. Further, major transalpine connection routes, often characterised by high traffic load, act as a significant air pollution source. The south of Switzerland is also occasionally influenced by pollutants transported from the highly industrialised Po Valley in northern Italy. We investigate the existence of a linear relation between the SEVIRI retrieved AOD (Aerosol Optical Depth) and the PM concentration obtained from the ground-based air quality network NABEL (Nationales Beobachtungsnetz fuer Luftfremdstoffe). The temporal trend of this two quantities shows a significant relationship over various locations. The correlation coefficient is in some cases higher than 0

  11. Comparisons of Three-Dimensional Variational Data Assimilation and Model Output Statistics in Improving Atmospheric Chemistry Forecasts

    NASA Astrophysics Data System (ADS)

    Ma, Chaoqun; Wang, Tijian; Zang, Zengliang; Li, Zhijin

    2018-07-01

    Atmospheric chemistry models usually perform badly in forecasting wintertime air pollution because of their uncertainties. Generally, such uncertainties can be decreased effectively by techniques such as data assimilation (DA) and model output statistics (MOS). However, the relative importance and combined effects of the two techniques have not been clarified. Here, a one-month air quality forecast with the Weather Research and Forecasting-Chemistry (WRF-Chem) model was carried out in a virtually operational setup focusing on Hebei Province, China. Meanwhile, three-dimensional variational (3DVar) DA and MOS based on one-dimensional Kalman filtering were implemented separately and simultaneously to investigate their performance in improving the model forecast. Comparison with observations shows that the chemistry forecast with MOS outperforms that with 3DVar DA, which could be seen in all the species tested over the whole 72 forecast hours. Combined use of both techniques does not guarantee a better forecast than MOS only, with the improvements and degradations being small and appearing rather randomly. Results indicate that the implementation of MOS is more suitable than 3DVar DA in improving the operational forecasting ability of WRF-Chem.

  12. 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

  13. 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

  14. 30 CFR 75.321 - Air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Air quality. 75.321 Section 75.321 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.321 Air quality. (a)(1) The air in areas where... air current in these areas shall be sufficient to dilute, render harmless, and carry away flammable...

  15. 30 CFR 75.321 - Air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Air quality. 75.321 Section 75.321 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.321 Air quality. (a)(1) The air in areas where... air current in these areas shall be sufficient to dilute, render harmless, and carry away flammable...

  16. 30 CFR 75.321 - Air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Air quality. 75.321 Section 75.321 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.321 Air quality. (a)(1) The air in areas where... air current in these areas shall be sufficient to dilute, render harmless, and carry away flammable...

  17. 30 CFR 75.321 - Air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Air quality. 75.321 Section 75.321 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.321 Air quality. (a)(1) The air in areas where... air current in these areas shall be sufficient to dilute, render harmless, and carry away flammable...

  18. 30 CFR 75.321 - Air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Air quality. 75.321 Section 75.321 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.321 Air quality. (a)(1) The air in areas where... air current in these areas shall be sufficient to dilute, render harmless, and carry away flammable...

  19. Evaluating the Impact of AIRS Observations on Regional Forecasts at the SPoRT Center

    NASA Technical Reports Server (NTRS)

    Zavodsky, Bradley

    2011-01-01

    NASA Short-term Prediction Research and Transition (SPoRT) Center collaborates with operational partners of different sizes and operational goals to improve forecasts using targeted projects and data sets. Modeling and DA activities focus on demonstrating utility of NASA data sets and capabilities within operational systems. SPoRT has successfully assimilated the Atmospheric Infrared Sounder (AIRS) radiance and profile data. A collaborative project is underway with the Joint Center for Satellite Data Assimilation (JCSDA) to use AIRS profiles to better understand the impact of AIRS radiances assimilated within Gridpoint Statistical Interpolation (GSI) in hopes of engaging the operational DA community in a reassessment of assimilation methodologies to more effectively assimilate hyperspectral radiances.

  20. The Satellite based Monitoring Initiative for Regional Air quality (SAMIRA): Project summary and first results

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

    -resolution satellite products of air quality with the help of high-resolution model information. This will add value to existing earth observation products of air quality by bringing them to spatial scales that are more in line with what is generally required for studying urban and regional scale air quality. In a fifth activity, we implement robust and independent validation schemes for evaluating the quality of the generated products. Finally, in a sixth activity the consortium is working towards a pre-operational system for improved PM forecasts using observational (in situ and satellite) data assimilation. SAMIRA aims to maximize project benefits by liaison with national and regional environmental protection agencies and health institutions, as well as related ESA and European initiatives such as the Copernicus Atmosphere Monitoring Service (CAMS).

  1. 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

  2. Regression trees modeling and forecasting of PM10 air pollution in urban areas

    NASA Astrophysics Data System (ADS)

    Stoimenova, M.; Voynikova, D.; Ivanov, A.; Gocheva-Ilieva, S.; Iliev, I.

    2017-10-01

    Fine particulate matter (PM10) air pollution is a serious problem affecting the health of the population in many Bulgarian cities. As an example, the object of this study is the pollution with PM10 of the town of Pleven, Northern Bulgaria. The measured concentrations of this air pollutant for this city consistently exceeded the permissible limits set by European and national legislation. Based on data for the last 6 years (2011-2016), the analysis shows that this applies both to the daily limit of 50 micrograms per cubic meter and the allowable number of daily concentration exceedances to 35 per year. Also, the average annual concentration of PM10 exceeded the prescribed norm of no more than 40 micrograms per cubic meter. The aim of this work is to build high performance mathematical models for effective prediction and forecasting the level of PM10 pollution. The study was conducted with the powerful flexible data mining technique Classification and Regression Trees (CART). The values of PM10 were fitted with respect to meteorological data such as maximum and minimum air temperature, relative humidity, wind speed and direction and others, as well as with time and autoregressive variables. As a result the obtained CART models demonstrate high predictive ability and fit the actual data with up to 80%. The best models were applied for forecasting the level pollution for 3 to 7 days ahead. An interpretation of the modeling results is presented.

  3. 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

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

    NASA Astrophysics Data System (ADS)

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

    2009-03-01

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

  6. 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.

  7. Satellite Data of Atmospheric Pollution for U.S. Air Quality Applications: Examples of Applications, Summary of Data End-user Resources, Answers to Faqs, and Common Mistakes to Avoid

    NASA Technical Reports Server (NTRS)

    Duncan, Bryan Neal; Prados, Ana; Lamsal, Lok N.; Liu, Yang; Streets, David G.; Gupta, Pawan; Hilsenrath, Ernest; Kahn, Ralph A.; Nielsen, J. Eric; Beyersdorf, Andreas J.; hide

    2014-01-01

    Satellite data of atmospheric pollutants are becoming more widely used in the decision-making and environmental management activities of public, private sector and non-profit organizations. They are employed for estimating emissions, tracking pollutant plumes, supporting air quality forecasting activities, providing evidence for "exceptional event" declarations, monitoring regional long-term trends, and evaluating air quality model output. However, many air quality managers are not taking full advantage of the data for these applications nor has the full potential of satellite data for air quality applications been realized. A key barrier is the inherent difficulties associated with accessing, processing, and properly interpreting observational data. A degree of technical skill is required on the part of the data end-user, which is often problematic for air quality agencies with limited resources. Therefore, we 1) review the primary uses of satellite data for air quality applications, 2) provide some background information on satellite capabilities for measuring pollutants, 3) discuss the many resources available to the end-user for accessing, processing, and visualizing the data, and 4) provide answers to common questions in plain language.

  8. Satellite Data of Atmospheric Pollution for U.S. Air Quality Applications: Examples of Applications, Summary of Data End-User Resources, Answers to FAQs, and Common Mistakes to Avoid

    NASA Technical Reports Server (NTRS)

    Duncan, Bryan; Prados, Ana I.; Lamsal, Lok; Liu, Yang; Streets, David G.; Gupta, Pawan; Hilsenrath, Ernest; Kahn, Ralph A.; Nielsen, J. Eric; Beyersdorf, Andreas J.; hide

    2014-01-01

    Satellite data of atmospheric pollutants are becoming more widely used in the decision-making and environmental management activities of public, private sector and non-profit organizations. They are employed for estimating emissions, tracking pollutant plumes, supporting air quality forecasting activities, providing evidence for "exceptional event" declarations, monitoring regional long-term trends, and evaluating air quality model output. However, many air quality managers are not taking full advantage of the data for these applications nor has the full potential of satellite data for air quality applications been realized. A key barrier is the inherent difficulties associated with accessing, processing, and properly interpreting observational data. A degree of technical skill is required on the part of the data end-user, which is often problematic for air quality agencies with limited resources. Therefore, we 1) review the primary uses of satellite data for air quality applications, 2) provide some background information on satellite capabilities for measuring pollutants, 3) discuss the many resources available to the end-user for accessing, processing, and visualizing the data, and 4) provide answers to common questions in plain language.

  9. The AirQuality SenseBox

    NASA Astrophysics Data System (ADS)

    Demuth, Dustin; Nuest, Daniel; Bröring, Arne; Pebesma, Edzer

    2013-04-01

    In the past year, a group of open hardware enthusiasts and citizen scientists had large success in the crowd-funding of an open hardware-based sensor platform for air quality monitoring, called the Air Quality Egg. Via the kickstarter platform, the group was able to collect triple the amount of money than needed to fulfill their goals. Data generated by the Air Quality Egg is pushed to the data logging platform cosm.com, which makes the devices a part of the Internet of Things. The project aims at increasing the participation of citizens in the collection of data, the development of sensors, the operation of sensor stations, and, as data on cosm is publicly available, the sharing, visualization and analysis of data. Air Quality Eggs can measure NO2 and CO concentrations, as well as relative humidity and temperature. The chosen sensors are low-cost and have limited precision and accurracy. The Air Quality Egg consists of a stationary outdoor and a stationary indoor unit. Each outdoor unit will wirelessly transmit air quality measurements to the indoor unit, which forwards the data to cosm. Most recent versions of the Air Quality Egg allow a rough calibration of the gas sensors and on-the-fly conversion from raw sensor readings (impedance) to meaningful air quality data expressed in units of parts per billion. Data generated by these low-cost platforms are not intended to replace well-calibrated official monitoring stations, but rather augment the density of the total monitoring network with citizen sensors. To improve the usability of the Air Quality Egg, we present a new and more advanced concept, called the AirQuality SenseBox. We made the outdoor platform more autonomous and location-aware by adding solarpanels and rechargeable batteries as a power source. The AirQuality SenseBox knows its own position from a GPS device attached to the platform. As a mobile sensor platform, it can for instance be attached to vehicles. A low-cost and low-power wireless chipset

  10. 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.

  11. New Federal Air Quality Standards.

    ERIC Educational Resources Information Center

    Stopinski, O. W.

    The report discusses the current procedures for establishing air quality standards, the bases for standards, and, finally, proposed and final National Primary and Secondary Ambient Air Quality Standards for sulfur dioxide, particulate matter, carbon monoxide, nonmethane hydrocarbons, photochemical oxidants, and nitrogen dioxide. (Author/RH)

  12. Impacts of emission reduction and meteorological conditions on air quality improvement during the 2014 Youth Olympic Games in Nanjing, China

    NASA Astrophysics Data System (ADS)

    Huang, Qian; Wang, Tijian; Chen, Pulong; Huang, Xiaoxian; Zhu, Jialei; Zhuang, Bingliang

    2017-11-01

    As the holding city of the 2nd Youth Olympic Games (YOG), Nanjing is highly industrialized and urbanized, and faces several air pollution issues. In order to ensure better air quality during the event, the local government took great efforts to control the emissions from pollutant sources. However, air quality can still be affected by synoptic weather, not only emission. In this paper, the influences of meteorological factors and emission reductions were investigated using observational data and numerical simulations with WRF-CMAQ (Weather Research and Forecasting - Community Multiscale Air Quality). During the month in which the YOG were held (August 2014), the observed hourly mean concentrations of SO2, NO2, PM10, PM2.5, CO and O3 were 11.6 µg m-3, 34.0 µg m-3, 57.8 µg m-3, 39.4 µg m-3, 0.9 mg m-3 and 38.8 µg m-3, respectively, which were below China National Ambient Air Quality Standard (level 2). However, model simulation showed that the weather conditions, such as weaker winds during the YOG, were adverse for better air quality and could increase SO2, NO2, PM10, PM2.5 and CO by 17.5, 16.9, 18.5, 18.8, 7.8 and 0.8 %. Taking account of local emission abatement only, the simulated SO2, NO2, PM10, PM2.5 and CO decreased by 24.6, 12.1, 15.1, 8.1 and 7.2 %. Consequently, stringent emission control measures can reduce the concentrations of air pollutants in the short term, and emission reduction is very important for air quality improvement during the YOG. A good example has been set for air quality protection for important social events.

  13. Impacts of potential CO2-reduction policies on air quality in the United States.

    PubMed

    Trail, Marcus A; Tsimpidi, Alexandra P; Liu, Peng; Tsigaridis, Kostas; Hu, Yongtao; Rudokas, Jason R; Miller, Paul J; Nenes, Athanasios; Russell, Armistead G

    2015-04-21

    Impacts of emissions changes from four potential U.S. CO2 emission reduction policies on 2050 air quality are analyzed using the community multiscale air quality model (CMAQ). Future meteorology was downscaled from the Goddard Institute for Space Studies (GISS) ModelE General Circulation Model (GCM) to the regional scale using the Weather Research Forecasting (WRF) model. We use emissions growth factors from the EPAUS9r MARKAL model to project emissions inventories for two climate tax scenarios, a combined transportation and energy scenario, a biomass energy scenario and a reference case. Implementation of a relatively aggressive carbon tax leads to improved PM2.5 air quality compared to the reference case as incentives increase for facilities to install flue-gas desulfurization (FGD) and carbon capture and sequestration (CCS) technologies. However, less capital is available to install NOX reduction technologies, resulting in an O3 increase. A policy aimed at reducing CO2 from the transportation sector and electricity production sectors leads to reduced emissions of mobile source NOX, thus reducing O3. Over most of the U.S., this scenario leads to reduced PM2.5 concentrations. However, increased primary PM2.5 emissions associated with fuel switching in the residential and industrial sectors leads to increased organic matter (OM) and PM2.5 in some cities.

  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. 77 FR 30087 - Air Quality Designations for the 2008 Ozone National Ambient Air Quality Standards

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-05-21

    ...This rule establishes initial air quality designations for most areas in the United States, including areas of Indian country, for the 2008 primary and secondary national ambient air quality standards (NAAQS) for ozone. The designations for several counties in Illinois, Indiana, and Wisconsin that the EPA is considering for inclusion in the Chicago nonattainment area will be designated in a subsequent action, no later than May 31, 2012. Areas designated as nonattainment are also being classified by operation of law according to the severity of their air quality problems. The classification categories are Marginal, Moderate, Serious, Severe, and Extreme. The EPA is establishing the air quality thresholds that define the classifications in a separate rule that the EPA is signing and publishing in the Federal Register on the same schedule as these designations. In accordance with that separate rule, six nonattainment areas in California are being reclassified to a higher classification.

  16. A quality assessment of the MARS crop yield forecasting system for the European Union

    NASA Astrophysics Data System (ADS)

    van der Velde, Marijn; Bareuth, Bettina

    2015-04-01

    Timely information on crop production forecasts can become of increasing importance as commodity markets are more and more interconnected. Impacts across large crop production areas due to (e.g.) extreme weather and pest outbreaks can create ripple effects that may affect food prices and availability elsewhere. The MARS Unit (Monitoring Agricultural ResourceS), DG Joint Research Centre, European Commission, has been providing forecasts of European crop production levels since 1993. The operational crop production forecasting is carried out with the MARS Crop Yield Forecasting System (M-CYFS). The M-CYFS is used to monitor crop growth development, evaluate short-term effects of anomalous meteorological events, and provide monthly forecasts of crop yield at national and European Union level. The crop production forecasts are published in the so-called MARS bulletins. Forecasting crop yield over large areas in the operational context requires quality benchmarks. Here we present an analysis of the accuracy and skill of past crop yield forecasts of the main crops (e.g. soft wheat, grain maize), throughout the growing season, and specifically for the final forecast before harvest. Two simple benchmarks to assess the skill of the forecasts were defined as comparing the forecasts to 1) a forecast equal to the average yield and 2) a forecast using a linear trend established through the crop yield time-series. These reveal a variability in performance as a function of crop and Member State. In terms of production, the yield forecasts of 67% of the EU-28 soft wheat production and 80% of the EU-28 maize production have been forecast superior to both benchmarks during the 1993-2013 period. In a changing and increasingly variable climate crop yield forecasts can become increasingly valuable - provided they are used wisely. We end our presentation by discussing research activities that could contribute to this goal.

  17. Agriculture: Agriculture and Air Quality

    EPA Pesticide Factsheets

    Information on air emissions from agricultural practices, types of agricultural burning, air programs that may apply to agriculture, reporting requirements, and links to state and other federal air-quality information.

  18. 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...

  19. Indoor air quality: A psychosocial perspective

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

    Boxer, P.A.

    1990-05-01

    The incidence of indoor air quality problems has increased dramatically over the past decade. Investigation of these problems has yielded a definitive cause in only one third of the cases. Psychosocial factors may play a key role in the development and propagation of symptoms attributed to poor indoor air quality. Guidelines for managing indoor air quality problems from the organizational perspective are based upon psychosocial principles and elements of risk perception.

  20. Forecasting Cool Season Daily Peak Winds at Kennedy Space Center and Cape Canaveral Air Force Station

    NASA Technical Reports Server (NTRS)

    Barrett, Joe, III; Short, David; Roeder, William

    2008-01-01

    The expected peak wind speed for the day is an important element in the daily 24-Hour and Weekly Planning Forecasts issued by the 45th Weather Squadron (45 WS) for planning operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The morning outlook for peak speeds also begins the warning decision process for gusts ^ 35 kt, ^ 50 kt, and ^ 60 kt from the surface to 300 ft. The 45 WS forecasters have indicated that peak wind speeds are a challenging parameter to forecast during the cool season (October-April). The 45 WS requested that the Applied Meteorology Unit (AMU) develop a tool to help them forecast the speed and timing of the daily peak and average wind, from the surface to 300 ft on KSC/CCAFS during the cool season. The tool must only use data available by 1200 UTC to support the issue time of the Planning Forecasts. Based on observations from the KSC/CCAFS wind tower network, surface observations from the Shuttle Landing Facility (SLF), and CCAFS upper-air soundings from the cool season months of October 2002 to February 2007, the AMU created multiple linear regression equations to predict the timing and speed of the daily peak wind speed, as well as the background average wind speed. Several possible predictors were evaluated, including persistence, the temperature inversion depth, strength, and wind speed at the top of the inversion, wind gust factor (ratio of peak wind speed to average wind speed), synoptic weather pattern, occurrence of precipitation at the SLF, and strongest wind in the lowest 3000 ft, 4000 ft, or 5000 ft. Six synoptic patterns were identified: 1) surface high near or over FL, 2) surface high north or east of FL, 3) surface high south or west of FL, 4) surface front approaching FL, 5) surface front across central FL, and 6) surface front across south FL. The following six predictors were selected: 1) inversion depth, 2) inversion strength, 3) wind gust factor, 4) synoptic weather pattern, 5) occurrence of

  1. Clean air through transportation : challenges in meeting national air quality standards

    DOT National Transportation Integrated Search

    1993-08-01

    This report, required by Section 108(f)(3) of the Clean Air Act, as amended in 1990, addresses the issues of motor vehicles and air quality. The report discusses the challenges faced in attempting to improve air quality through transportation program...

  2. Statistical Short-Range Guidance for Peak Wind Forecasts on Kennedy Space Center/Cape Canaveral Air Force Station, Phase III

    NASA Technical Reports Server (NTRS)

    Crawford, Winifred

    2010-01-01

    This final report describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The peak winds are an important forecast element for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a short-range peak-wind forecast tool to assist in forecasting LCC violations.The tool includes climatologies of the 5-minute mean and peak winds by month, hour, and direction, and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

  3. Evaluation of a seven-year air quality simulation using the Weather Research and Forecasting (WRF)/Community Multiscale Air Quality (CMAQ) models in the eastern United States.

    PubMed

    Zhang, Hongliang; Chen, Gang; Hu, Jianlin; Chen, Shu-Hua; Wiedinmyer, Christine; Kleeman, Michael; Ying, Qi

    2014-03-01

    The performance of the Weather Research and Forecasting (WRF)/Community Multi-scale Air Quality (CMAQ) system in the eastern United States is analyzed based on results from a seven-year modeling study with a 4-km spatial resolution. For 2-m temperature, the monthly averaged mean bias (MB) and gross error (GE) values are generally within the recommended performance criteria, although temperature is over-predicted with MB values up to 2K. Water vapor at 2-m is well-predicted but significant biases (>2 g kg(-1)) were observed in wintertime. Predictions for wind speed are satisfactory but biased towards over-prediction with 0

  4. 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

  5. 78 FR 47191 - Air Quality Designations for the 2010 Sulfur Dioxide (SO2) Primary National Ambient Air Quality...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-08-05

    ... Air Quality Designations for the 2010 Sulfur Dioxide (SO[bdi2]) Primary National Ambient Air Quality... air quality designations for certain areas in the United States for the 2010 primary Sulfur Dioxide... of this document? III. What is sulfur dioxide? IV. What is the 2010 SO 2 NAAQS and what are the...

  6. Evaluation of WRF Parameterizations for Air Quality Applications over the Midwest USA

    NASA Astrophysics Data System (ADS)

    Zheng, Z.; Fu, K.; Balasubramanian, S.; Koloutsou-Vakakis, S.; McFarland, D. M.; Rood, M. J.

    2017-12-01

    Reliable predictions from Chemical Transport Models (CTMs) for air quality research require accurate gridded weather inputs. In this study, a sensitivity analysis of 17 Weather Research and Forecast (WRF) model runs was conducted to explore the optimum configuration in six physics categories (i.e., cumulus, surface layer, microphysics, land surface model, planetary boundary layer, and longwave/shortwave radiation) for the Midwest USA. WRF runs were initally conducted over four days in May 2011 for a 12 km x 12 km domain over contiguous USA and a nested 4 km x 4 km domain over the Midwest USA (i.e., Illinois and adjacent areas including Iowa, Indiana, and Missouri). Model outputs were evaluated statistically by comparison with meteorological observations (DS337.0, METAR data, and the Water and Atmospheric Resources Monitoring Network) and resulting statistics were compared to benchmark values from the literature. Identified optimum configurations of physics parametrizations were then evaluated for the whole months of May and October 2011 to evaluate WRF model performance for Midwestern spring and fall seasons. This study demonstrated that for the chosen physics options, WRF predicted well temperature (Index of Agreement (IOA) = 0.99), pressure (IOA = 0.99), relative humidity (IOA = 0.93), wind speed (IOA = 0.85), and wind direction (IOA = 0.97). However, WRF did not predict daily precipitation satisfactorily (IOA = 0.16). Developed gridded weather fields will be used as inputs to a CTM ensemble consisting of the Comprehensive Air Quality Model with Extensions to study impacts of chemical fertilizer usage on regional air quality in the Midwest USA.

  7. The Co-benefits of Domestic and Foreign GHG Mitigation on US Air Quality

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Bowden, J.; Adelman, Z.; Naik, V.; Horowitz, L. W.; West, J. J.

    2013-12-01

    Authors: Yuqiang Zhang1, Jared Bowden2 , Zachariah Adelman1,2, Vaishali Naik3, Larry W. Horowitz4 , J. Jason West1 1 University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 2 Institute for the Environment, Chapel Hill, NC 27599 3 UCAR/NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540 4 NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540 Abstract: Actions to mitigate greenhouse gas (GHG) emissions will reduce co-emitted air pollutants, which can immediately affect air quality; slowing climate change through GHG mitigation also influences air quality in the long term. We previously used a global model (MOZART-4) to show that global GHG mitigation will have significant co-benefits for air quality and human health. In doing so, we contrasted the Representative Concentration Pathway Scenario 4.5 (RCP4.5), treated as a GHG mitigation scenario, with its associated reference case scenario (REF). Using these same scenarios, we investigate here the air quality co-benefits due to domestic GHGs mitigation in the US alone at fine resolution, and compare these co-benefits with those resulting from foreign GHG mitigation. This work focuses on downscaling the meteorology and air pollutant chemistry to the US scale. We use the latest Weather Research and Forecasting (WRF) model as a Regional Climate Model (RCM) to dynamically downscale the GFDL AM3 Global Climate Model (GCM) over the US at 36 km resolution, in 2000 and 2050. The 2000 simulation will be compared with the multi-year surface observation data, satellite data, and all simulations with the GCM simulation. These simulations will be used as inputs for the newest Community Multiscale Air Quality (CMAQ) modeling system. Initial conditions (IC) and dynamic boundary conditions (BC) for CMAQ will be derived from the global MOZART-4 simulations. Anthropogenic emissions for the REF and RCP4.5 scenarios will be processed through SMOKE to prepare temporally- and spatially-resolved emission files

  8. Challenges in Understanding and Forecasting Winds in Complex Terrain.

    NASA Astrophysics Data System (ADS)

    Mann, J.; Fernando, J.; Wilczak, J. M.

    2017-12-01

    An overview will be given of some of the challenges in understanding and forecasting winds in complex terrain. These challenges can occur for several different reasons including 1) gaps in our understanding of fundamental physical boundary layer processes occurring in complex terrain; 2) a lack of adequate parameterizations and/or numerical schemes in NWP models; and 3) inadequate observations for initialization of NWP model forecasts. Specific phenomena that will be covered include topographic wakes/vortices, cold pools, gap flows, and mountain-valley winds, with examples taken from several air quality and wind energy related field programs in California as well as from the recent Second Wind Forecast Improvement Program (WFIP2) field campaign in the Columbia River Gorge/Basin area of Washington and Oregon States. Recent parameterization improvements discussed will include those for boundary layer turbulence, including 3D turbulence schemes, and gravity wave drag. Observational requirements for improving wind forecasting in complex terrain will be discussed, especially in the context of forecasting pressure gradient driven gap flow events.

  9. Time to harmonize national ambient air quality standards.

    PubMed

    Kutlar Joss, Meltem; Eeftens, Marloes; Gintowt, Emily; Kappeler, Ron; Künzli, Nino

    2017-05-01

    The World Health Organization has developed ambient air quality guidelines at levels considered to be safe or of acceptable risk for human health. These guidelines are meant to support governments in defining national standards. It is unclear how they are followed. We compiled an inventory of ambient air quality standards for 194 countries worldwide for six air pollutants: PM 2.5 , PM 10 , ozone, nitrogen dioxide, sulphur dioxide and carbon monoxide. We conducted literature and internet searches and asked country representatives about national ambient air quality standards. We found information on 170 countries including 57 countries that did not set any air quality standards. Levels varied greatly by country and by pollutant. Ambient air quality standards for PM 2.5 , PM 10 and SO 2 poorly complied with WHO guideline values. The agreement was higher for CO, SO 2 (10-min averaging time) and NO 2 . Regulatory differences mirror the differences in air quality and the related burden of disease around the globe. Governments worldwide should adopt science based air quality standards and clean air management plans to continuously improve air quality locally, nationally, and globally.

  10. Air Quality and Population Exposure in Urban Areas: Potential Co-Benefits of Alternative Strategies

    NASA Astrophysics Data System (ADS)

    Mikolajczyk, U.; Suppan, P.; Forkel, R.; Williams, M.

    2014-12-01

    Even though much progress has been achieved through dedicated approaches to improving air quality in many European cities, there are various threats which still remain unchanged. According to the World Health Organization, outdoor air pollution was linked to 3.7 million deaths in year 2012. As climate changes, the frequency of days with harmful levels of air pollutants may significantly increase causing exacerbation of cardiovascular and respiratory diseases. The aim of this study is to conduct health impact assessment by utilizing regionally and spatially specific data in order to assess the influence of alternative emission strategies on human health. In the first stage of this investigation, a modeling study was carried out using the Weather Research and Forecasting (WRF) model coupled with Chemistry (WRF/Chem; Grell et al., 2005) to estimate ambient concentrations of air pollutants. The model set-up included a nesting approach, where three domains with horizontal resolution of 18 km, 6 km and 2 km were defined. The investigation area included the city of Munich (1.5 million inhabitants). The model performance has been evaluated against available air quality observations from the monitoring database "AirBase". The chemical species including O3, NO, NO2 and PM10 simulated by WRF/Chem compare favorably with the observations. The model performs especially well in resolving the observed O3 concentrations. In the ongoing study, different emission reduction scenarios are compared to a baseline 2009 scenario based on Germany's National Emissions Inventory. To investigate health effects associated with air pollution concentrations a local-scale health impact assessment (HIA) will be conducted. Concentration-response functions (CRFs) link the change in mortality rates to the change in concentrations of air pollutants. CRFs are applied to population-weighted mean concentrations to estimate relative risks and hence estimate numbers of attributable deaths and associated

  11. Development of a method for comprehensive water quality forecasting and its application in Miyun reservoir of Beijing, China.

    PubMed

    Zhang, Lei; Zou, Zhihong; Shan, Wei

    2017-06-01

    Water quality forecasting is an essential part of water resource management. Spatiotemporal variations of water quality and their inherent constraints make it very complex. This study explored a data-based method for short-term water quality forecasting. Prediction of water quality indicators including dissolved oxygen, chemical oxygen demand by KMnO 4 and ammonia nitrogen using support vector machine was taken as inputs of the particle swarm algorithm based optimal wavelet neural network to forecast the whole status index of water quality. Gubeikou monitoring section of Miyun reservoir in Beijing, China was taken as the study case to examine effectiveness of this approach. The experiment results also revealed that the proposed model has advantages of stability and time reduction in comparison with other data-driven models including traditional BP neural network model, wavelet neural network model and Gradient Boosting Decision Tree model. It can be used as an effective approach to perform short-term comprehensive water quality prediction. Copyright © 2016. Published by Elsevier B.V.

  12. 40 CFR 52.2682 - Air quality surveillance.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 4 2010-07-01 2010-07-01 false Air quality surveillance. 52.2682... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Guam § 52.2682 Air quality... Pollution Control Standards and Regulations” (buffer zones—air quality sampling) are not in conformance with...

  13. 40 CFR 52.2682 - Air quality surveillance.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 5 2012-07-01 2012-07-01 false Air quality surveillance. 52.2682... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Guam § 52.2682 Air quality... Pollution Control Standards and Regulations” (buffer zones—air quality sampling) are not in conformance with...

  14. 40 CFR 52.2682 - Air quality surveillance.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 5 2013-07-01 2013-07-01 false Air quality surveillance. 52.2682... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Guam § 52.2682 Air quality... Pollution Control Standards and Regulations” (buffer zones—air quality sampling) are not in conformance with...

  15. 40 CFR 52.2682 - Air quality surveillance.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 5 2014-07-01 2014-07-01 false Air quality surveillance. 52.2682... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Guam § 52.2682 Air quality... Pollution Control Standards and Regulations” (buffer zones—air quality sampling) are not in conformance with...

  16. 40 CFR 52.2682 - Air quality surveillance.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 4 2011-07-01 2011-07-01 false Air quality surveillance. 52.2682... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Guam § 52.2682 Air quality... Pollution Control Standards and Regulations” (buffer zones—air quality sampling) are not in conformance with...

  17. Impact of Transpacific Aerosol on Air Quality over the United States: A Perspective from Aerosol-Cloud-Radiation Interactions

    NASA Technical Reports Server (NTRS)

    Tao, Zhining; Yu, Hongbin; Chin, Mian

    2015-01-01

    Observations have well established that aerosols from various sources in Asia, Europe, and Africa can travel across the Pacific and reach the contiguous United States (U.S.) at least on episodic bases throughout a year, with a maximum import in spring. The imported aerosol not only can serve as an additional source to regional air pollution (e.g., direct input), but also can influence regional air quality through the aerosol-cloud-radiation (ACR) interactions that change local and regional meteorology. This study assessed impacts of the transpacific aerosol on air quality, focusing on surface ozone and PM2.5, over the U.S. using the NASA Unified Weather Research Forecast model. Based on the results of 3- month (April to June of 2010) simulations, the impact of direct input (as an additional source) of transpacific aerosol caused an increase of surface PM2.5 concentration by approximately 1.5 micro-g/cu m over the west coast and about 0.5 micro-g/cu m over the east coast of the U.S. By influencing key meteorological processes through the ACR interactions, the transpacific aerosol exerted a significant effect on both surface PM2.5 (+/-6 micro-g/cu m3) and ozone (+/-12 ppbv) over the central and eastern U.S. This suggests that the transpacific transport of aerosol could either improve or deteriorate local air quality and complicate local effort toward the compliance with the U.S. National Ambient Air Quality Standards.

  18. Assessment and forecasting of lightning potential and its effect on launch operations at Cape Canaveral Air Force Station and John F. Kennedy Space Center

    NASA Technical Reports Server (NTRS)

    Weems, J.; Wyse, N.; Madura, J.; Secrist, M.; Pinder, C.

    1991-01-01

    Lightning plays a pivotal role in the operation decision process for space and ballistic launches at Cape Canaveral Air Force Station and Kennedy Space Center. Lightning forecasts are the responsibility of Detachment 11, 4th Weather Wing's Cape Canaveral Forecast Facility. These forecasts are important to daily ground processing as well as launch countdown decisions. The methodology and equipment used to forecast lightning are discussed. Impact on a recent mission is summarized.

  19. Air Quality Criteria for Ozone and Related Photochemical ...

    EPA Pesticide Factsheets

    In February 2006, EPA released the final document, Air Quality Criteria for Ozone and Other Photochemical Oxidants. Tropospheric or surface-level ozone (O3) is one of six major air pollutants regulated by National Ambient Air Quality Standards (NAAQS) under the U.S. Clean Air Act. As mandated by the Clean Air Act, the U.S. Environmental Protection Agency (EPA) must periodically review the scientific bases (or criteria) for the various NAAQS by assessing newly available scientific information on a given criteria air pollutant. This document, Air Quality Criteria for Ozone and Other Photochemical Oxidants, is an updated revision of the 1996 Ozone Air Quality Criteria Document (O3 AQCD) that provided scientific bases for the current O3 NAAQS set in 1997. The Clean Air Act mandates periodic review of the National Ambient Air Quality Standards (NAAQS) for six common air pollutants, also referred to as criteria pollutants, including ozone.

  20. Weather Research and Forecasting Model Wind Sensitivity Study at Edwards Air Force Base, CA

    NASA Technical Reports Server (NTRS)

    Watson, Leela R.; Bauman, William H., III; Hoeth, Brian

    2009-01-01

    This abstract describes work that will be done by the Applied Meteorology Unit (AMU) in assessing the success of different model configurations in predicting "wind cycling" cases at Edwards Air Force Base, CA (EAFB), in which the wind speeds and directions oscillate among towers near the EAFB runway. The Weather Research and Forecasting (WRF) model allows users to choose among two dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). There are also data assimilation analysis packages available for the initialization of the WRF model - the Local Analysis and Prediction System (LAPS) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS). Having a series of initialization options and WRF cores, as well as many options within each core, creates challenges for local forecasters, such as determining which configuration options are best to address specific forecast concerns. The goal of this project is to assess the different configurations available and determine which configuration will best predict surface wind speed and direction at EAFB.

  1. Air Quality Criteria for Particulate Matter.

    ERIC Educational Resources Information Center

    National Air Pollution Control Administration (DHEW), Washington, DC.

    To assist states in developing air quality standards, this book offers a review of literature related to atmospheric particulates and the development of criteria for air quality. It not only summarizes the current scientific knowledge of particulate air pollution, but points up the major deficiencies in that knowledge and the need for further…

  2. Update to the Lightning Probability Forecast Equations at Kennedy Space Center/Cape Canaveral Air Force Station, Florida

    NASA Technical Reports Server (NTRS)

    Lambert, Winifred; Roeder, William

    2007-01-01

    This conference presentation describes the improvement of a set of lightning probability forecast equations that are used by the 45th Weather Squadron forecasters for their daily 1100 UTC (0700 EDT) weather briefing during the warm season months of May-September. This information is used for general scheduling of operations at Cape Canaveral Air Force Station and Kennedy Space Center. Forecasters at the Spaceflight Meteorology Group also make thunderstorm forecasts during Shuttle flight operations. Five modifications were made by the Applied Meteorology Unit: increased the period of record from 15 to 17 years, changed the method of calculating the flow regime of the day, calculated a new optimal layer relative humidity, used a new smoothing technique for the daily climatology, and used a new valid area. The test results indicated that the modified equations showed and increase in skill over the current equations, good reliability, and an ability to distinguish between lightning and non-lightning days.

  3. Update to the Lightning Probability Forecast Equations at Kennedy Space Center/Cape Canaveral Air Force Station, Florida

    NASA Technical Reports Server (NTRS)

    Lambert, Winifred; Roeder, William

    2007-01-01

    This conference presentation describes the improvement of a set of lightning probability forecast equations that are used by the 45th Weather Squadron forecasters for their daily 1100 UTC (0700 EDT) weather briefing during the warm season months of May- September. This information is used for general scheduling of operations at Cape Canaveral Air Force Station and Kennedy Space Center. Forecasters at the Spaceflight Meteorology Group also make thunderstorm forecasts during Shuttle flight operations. Five modifications were made by the Applied Meteorology Unit: increased the period of record from 15 to 17 years, changed the method of calculating the flow regime of the day, calculated a new optimal layer relative humidity, used a new smoothing technique for the daily climatology, and used a new valid area. The test results indicated that the modified equations showed and increase in skill over the current equations, good reliability, and an ability to distinguish between lightning and non-lightning days.

  4. Update to the Objective Lightning Probability Forecast Tool in Use at Cape Canaveral Air Force Station, Florida

    NASA Technical Reports Server (NTRS)

    Lambert, Winifred; Roeder, William

    2008-01-01

    This conference presentation describes the improvement of a set of lightning probability forecast equations that are used by the 45th Weather Squadron forecasters for their daily 1100 UTC (0700 EDT) weather briefing during the warm season months of May-September. This information is used for general scheduling of operations at Cape Canaveral Air Force Station and Kennedy Space Center. Forecasters at the Spaceflight Meteorology Group also make thunderstorm forecasts during Shuttle flight operations. Five modifications were made by the Applied Meteorology Unit: increased the period of record from 15 to 17 years, changed the method of calculating the flow regime of the day, calculated a new optimal layer relative humidity, used a new smoothing technique for the daily climatology, and used a new valid area. The test results indicated that the modified equaitions showed and increase in skill over the current equations, good reliability, and an ability to distinguish between lightning and non-lightning days.

  5. Update to the Objective Lightning Probability Forecast Tool in use at Cape Canaveral Air Force Station, Florida

    NASA Technical Reports Server (NTRS)

    Lambert, Winifred; Roeder, William

    2013-01-01

    This conference poster describes the improvement of a set of lightning probability forecast equations that are used by the 45th Weather Squadron forecasters for their daily 1100 UTC (0700 EDT) weather briefing during the warm season months of May-September. This information is used for general scheduling of operations at Cape Canaveral Air Force Station and Kennedy Space Center. Forecasters at the Spaceflight Meteorology Group also make thunderstorm forecasts during Shuttle flight operations. Five modifications were made by the Applied Meteorology Unit: increased the period of record from 15 to 17 years, changed the method of calculating the flow regime of the day, calculated a new optimal layer relative humidity, used a new smoothing technique for the daily climatology, and used a new valid area. The test results indicated that the modified equations showed and increase in skill over the current equations, good reliability and an ability to distinguish between lightning and non-lightning days.

  6. Trends of multiple air pollutants emissions from residential coal combustion in Beijing and its implication on improving air quality for control measures

    NASA Astrophysics Data System (ADS)

    Xue, Yifeng; Zhou, Zhen; Nie, Teng; Wang, Kun; Nie, Lei; Pan, Tao; Wu, Xiaoqing; Tian, Hezhong; Zhong, Lianhong; Li, Jing; Liu, Huanjia; Liu, Shuhan; Shao, Panyang

    2016-10-01

    Residential coal combustion is considered to be an important source of air pollution in Beijing. However, knowledge regarding the emission characteristics of residential coal combustion and the related impacts on the air quality is very limited. In this study, we have developed an emission inventory for multiple hazardous air pollutants (HAPs) associated with residential coal combustion in Beijing for the period of 2000-2012. Furthermore, a widely used regional air quality model, the Community Multi-Scale Air Quality model (CMAQ), is applied to analyze the impact of residential coal combustion on the air quality in Beijing in 2012. The results show that the emissions of primary air pollutants from residential coal combustion have basically remained the same levels during the past decade, however, along with the strict emission control imposed on major industrial sources, the contribution of residential coal combustion emissions to the overall emissions from anthropogenic sources have increased obviously. In particular, the contributions of residential coal combustion to the total air pollutants concentrations of PM10, SO2, NOX, and CO represent approximately 11.6%, 27.5%, 2.8% and 7.3%, respectively, during the winter heating season. In terms of impact on the spatial variation patterns, the distributions of the pollutants concentrations are similar to the distribution of the associated primary HAPs emissions, which are highly concentrated in the rural-urban fringe zones and rural suburb areas. In addition, emissions of primary pollutants from residential coal combustion are forecasted by using a scenario analysis. Generally, comprehensive measures must be taken to control residential coal combustion in Beijing. The best way to reduce the associated emissions from residential coal combustion is to use economic incentive means to promote the conversion to clean energy sources for residential heating and cooking. In areas with reliable energy supplies, the coal used

  7. BASIS FOR PRIMARY AIR QUALITY CRITERIA AND STANDARDS

    EPA Science Inventory

    The Environmental Criteria and Assessment Office and the Office of Air Quality Planning and Standards are charged with responsibility for reviewing and assessing air quality criteria and air quality standards, respectively. Since adoption of the 1977 Clean Air Act Amendments, the...

  8. Enhancing indoor air quality –The air filter advantage

    PubMed Central

    Vijayan, Vannan Kandi; Paramesh, Haralappa; Salvi, Sundeep Santosh; Dalal, Alpa Anil Kumar

    2015-01-01

    Air pollution has become the world's single biggest environmental health risk, linked to around 7 million deaths in 2012 according to a recent World Health Organisation (WHO) report. The new data further reveals a stronger link between, indoor and outdoor air pollution exposure and cardiovascular diseases, such as strokes and ischemic heart disease, as well as between air pollution and cancer. The role of air pollution in the development of respiratory diseases, including acute respiratory infections and chronic obstructive pulmonary diseases, is well known. While both indoor and outdoor pollution affect health, recent statistics on the impact of household indoor pollutants (HAP) is alarming. The WHO factsheet on HAP and health states that 3.8 million premature deaths annually - including stroke, ischemic heart disease, chronic obstructive pulmonary disease (COPD) and lung cancer are attributed to exposure to household air pollution. Use of air cleaners and filters are one of the suggested strategies to improve indoor air quality. This review discusses the impact of air pollutants with special focus on indoor air pollutants and the benefits of air filters in improving indoor air quality. PMID:26628762

  9. 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...

  10. 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.

  11. Forest ecosystem services: Carbon and air quality

    Treesearch

    David J. Nowak; Neelam C. Poudyal; Steve G. McNulty

    2017-01-01

    Forests provide various ecosystem services related to air quality that can provide substantial value to society. Through tree growth and alteration of their local environment, trees and forests both directly and indirectly affect air quality. Though forests affect air quality in numerous ways, this chapter will focus on five main ecosystem services or disservices...

  12. Instrumentation for air quality measurements.

    NASA Technical Reports Server (NTRS)

    Loewenstein, M.

    1973-01-01

    Comparison of the new generation of air quality monitoring instruments with some more traditional methods. The first generation of air quality measurement instruments, based on the use of oxidant coulometric cells, nitrogen oxide colorimetry, carbon monoxide infrared analyzers, and other types of detectors, is compared with new techniques now coming into wide use in the air monitoring field and involving the use of chemiluminescent reactions, optical absorption detectors, a refinement of the carbon monoxide infrared analyzer, electrochemical cells based on solid electrolytes, and laser detectors.

  13. 40 CFR 52.1234 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.1234 Section 52.1234 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  14. 40 CFR 52.1884 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.1884 Section 52.1884 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  15. 40 CFR 52.499 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.499 Section 52.499 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  16. 40 CFR 52.1180 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.1180 Section 52.1180 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  17. 40 CFR 52.2827 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.2827 Section 52.2827 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  18. 40 CFR 52.1689 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.1689 Section 52.1689 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  19. 40 CFR 52.2676 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.2676 Section 52.2676 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  20. 40 CFR 52.2779 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.2779 Section 52.2779 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  1. 40 CFR 52.2729 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.2729 Section 52.2729 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  2. 40 CFR 52.2497 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.2497 Section 52.2497 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  3. 40 CFR 52.1603 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.1603 Section 52.1603 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  4. 40 CFR 52.1165 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.1165 Section 52.1165 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulation for preventing significant deterioration of air quality. The...

  5. 40 CFR 52.499 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.499 Section 52.499 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  6. 40 CFR 52.1884 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.1884 Section 52.1884 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  7. 40 CFR 52.1165 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.1165 Section 52.1165 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulation for preventing significant deterioration of air quality. The...

  8. 40 CFR 52.1165 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.1165 Section 52.1165 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulation for preventing significant deterioration of air quality. The...

  9. 40 CFR 52.1180 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.1180 Section 52.1180 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  10. 40 CFR 52.2729 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.2729 Section 52.2729 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  11. 40 CFR 52.1884 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.1884 Section 52.1884 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  12. 40 CFR 52.2779 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.2779 Section 52.2779 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  13. 40 CFR 52.499 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.499 Section 52.499 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  14. 40 CFR 52.1603 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.1603 Section 52.1603 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  15. 40 CFR 52.1234 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.1234 Section 52.1234 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  16. 40 CFR 52.2497 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.2497 Section 52.2497 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  17. 40 CFR 52.2497 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.2497 Section 52.2497 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  18. 40 CFR 52.1603 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.1603 Section 52.1603 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  19. 40 CFR 52.1884 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.1884 Section 52.1884 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  20. 40 CFR 52.2676 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.2676 Section 52.2676 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  1. 40 CFR 52.1603 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.1603 Section 52.1603 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  2. 40 CFR 52.499 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.499 Section 52.499 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  3. 40 CFR 52.2676 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.2676 Section 52.2676 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  4. 40 CFR 52.2779 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.2779 Section 52.2779 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  5. 40 CFR 52.1234 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.1234 Section 52.1234 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  6. 40 CFR 52.2676 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.2676 Section 52.2676 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  7. 40 CFR 52.1165 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.1165 Section 52.1165 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulation for preventing significant deterioration of air quality. The...

  8. 40 CFR 52.2827 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.2827 Section 52.2827 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  9. 40 CFR 52.1165 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.1165 Section 52.1165 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulation for preventing significant deterioration of air quality. The...

  10. 40 CFR 52.1180 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.1180 Section 52.1180 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  11. 40 CFR 52.2676 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.2676 Section 52.2676 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  12. 40 CFR 52.2497 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.2497 Section 52.2497 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  13. 40 CFR 52.499 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.499 Section 52.499 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  14. 40 CFR 52.2729 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.2729 Section 52.2729 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  15. 40 CFR 52.1180 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.1180 Section 52.1180 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  16. 40 CFR 52.2497 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.2497 Section 52.2497 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  17. 40 CFR 52.1234 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.1234 Section 52.1234 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  18. 40 CFR 52.2827 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.2827 Section 52.2827 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  19. 40 CFR 52.1180 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.1180 Section 52.1180 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  20. 40 CFR 52.1884 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.1884 Section 52.1884 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  1. 40 CFR 52.2729 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.2729 Section 52.2729 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  2. 40 CFR 52.2729 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.2729 Section 52.2729 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  3. 40 CFR 52.2827 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.2827 Section 52.2827 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  4. 40 CFR 52.2827 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.2827 Section 52.2827 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  5. 40 CFR 52.1234 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.1234 Section 52.1234 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  6. 40 CFR 52.2779 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.2779 Section 52.2779 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  7. 40 CFR 52.2779 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.2779 Section 52.2779 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  8. 40 CFR 52.1603 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.1603 Section 52.1603 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... deterioration of air quality. (b) Regulations for preventing significant deterioration of air quality. The...

  9. Importance of a Priori Vertical Ozone Profiles for TEMPO Air Quality Retrievals

    NASA Technical Reports Server (NTRS)

    Johnson, Matthew S.; Sullivan, John; Liu, Xiong; Zoogman, Peter; Newchurch, Mike; Kuang, Shi; McGee, Thomas; Leblanc, Thierry

    2017-01-01

    Ozone (O3) is a toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address the limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME (Global Ozone Monitoring Experiment), GOME-2, and OMI (Ozone Monitoring Instrument). This algorithm is suggested to use a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB-Clim) O3 climatology). This study evaluates the TB-Clim dataset and model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time data assimilation model products (NASA GMAO's (Global Modeling and Assimilation Office) operational GEOS-5 (Goddard Earth Observing System, Version 5) FP (Forecast Products) model and reanalysis data from MERRA2 (Modern-Era Retrospective analysis for Research and Applications, Version 2)) and a full chemical transport model (CTM), GEOS-Chem. In this study, vertical profile products are evaluated with surface (0-2 kilometers) and tropospheric (0-10 kilometers) TOLNet (Tropospheric Ozone Lidar Network) observations and the theoretical impact of individual a priori profile sources on the accuracy of TEMPO O3

  10. Strength of smoke-free air laws and indoor air quality.

    PubMed

    Lee, Kiyoung; Hahn, Ellen J; Robertson, Heather E; Lee, Seongjik; Vogel, Suzann L; Travers, Mark J

    2009-04-01

    Smoke-free air laws have been implemented in many Kentucky communities to protect the public from the harmful effects of secondhand smoke exposure. The impact of different strengths of smoke-free air laws on indoor air quality was assessed. Indoor air quality in hospitality venues was assessed in seven communities before and after comprehensive smoke-free air laws and in two communities only after partial smoke-free air laws. One community was measured three times: before any smoke-free air law, after the initial partial law, and after the law was strengthened to cover all workplaces and public places with few exemptions. Real-time measurements of particulate matters with 2.5 mum aerodynamic diameter or smaller (PM(2.5)) were obtained. When comprehensive smoke-free air laws were implemented, indoor PM(2.5) concentrations decreased significantly from 161 to 20 microg/m3. In one community that implemented a comprehensive smoke-free law after initially passing a partial law, indoor PM(2.5) concentrations were 304 microg/m3 before the law, 338 microg/m3 after the partial law, and 9 microg/m3 after the comprehensive law. The study clearly demonstrated that partial smoke-free air laws do not improve indoor air quality. A significant linear trend indicated that PM(2.5) levels in the establishments decreased with fewer numbers of burning cigarettes. Only comprehensive smoke-free air laws are effective in reducing indoor air pollution from secondhand tobacco smoke.

  11. The Value of Clean Air: Comparing Discounting of Delayed Air Quality and Money Across Magnitudes.

    PubMed

    Berry, Meredith S; Friedel, Jonathan E; DeHart, William B; Mahamane, Salif; Jordan, Kerry E; Odum, Amy L

    2017-06-01

    The detrimental health effects of exposure to air pollution are well established. Fostering behavioral change concerning air quality may be challenging because the detrimental health effects of exposure to air pollution are delayed. Delay discounting, a measure of impulsive choice, encapsulates this process of choosing between the immediate conveniences of behaviors that increase pollution and the delayed consequences of prolonged exposure to poor air quality. In Experiment 1, participants completed a series of delay-discounting tasks for air quality and money. We found that participants discounted delayed air quality more than money. In Experiment 2, we investigated whether the common finding that large amounts of money are discounted less steeply than small amounts of money generalized to larger and smaller improvements in air quality. Participants discounted larger improvements in air quality less steeply than smaller improvements, indicating that the discounting of air quality shares a similar process as the discounting of money. Our results indicate that the discounting of delayed money is strongly related to the discounting of delayed air quality and that similar mechanisms may be involved in the discounting of these qualitatively different outcomes. These data are also the first to demonstrate the malleability of delay discounting of air quality, and provide important public health implications for decreasing delay discounting of air quality.

  12. 40 CFR 52.632 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.632 Section 52.632 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  13. 40 CFR 52.793 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.793 Section 52.793 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  14. 40 CFR 52.738 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.738 Section 52.738 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  15. 40 CFR 52.738 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.738 Section 52.738 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  16. 40 CFR 52.632 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.632 Section 52.632 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  17. 40 CFR 52.793 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.793 Section 52.793 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  18. 40 CFR 52.632 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.632 Section 52.632 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  19. 40 CFR 52.632 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.632 Section 52.632 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  20. 40 CFR 52.738 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.738 Section 52.738 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  1. 40 CFR 52.632 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.632 Section 52.632 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  2. 40 CFR 52.738 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.738 Section 52.738 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  3. 40 CFR 52.738 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.738 Section 52.738 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  4. 40 CFR 52.793 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.793 Section 52.793 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  5. 40 CFR 52.793 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.793 Section 52.793 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  6. 40 CFR 52.793 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.793 Section 52.793 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulations for preventing significant deterioration of air quality. The provisions...

  7. Air travel forecasting : 1965-1975

    DOT National Transportation Integrated Search

    1957-01-01

    The forecast presented herein illustrates methods developed by The Port of New York Authority for measuring the market for travel by application of national survey findings to the census : of population and national population projections furnished b...

  8. Peak Wind Forecasts for the Launch-Critical Wind Towers on Kennedy Space Center/Cape Canaveral Air Force Station, Phase IV

    NASA Technical Reports Server (NTRS)

    Crawford, Winifred

    2011-01-01

    This final report describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The peak winds arc an important forecast clement for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to update the statistics in the current peak-wind forecast tool to assist in forecasting LCC violations. The tool includes onshore and offshore flow climatologies of the 5-minute mean and peak winds and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

  9. 40 CFR 52.432 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.432 Section 52.432 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulation for preventing significant deterioration of air quality. The provisions of...

  10. 40 CFR 52.96 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.96 Section 52.96 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The State of Alaska Department of Environmental Conservation Air Quality... deterioration of air quality. (b) The requirements of sections 160 through 165 of the Clean Air Act are not met...

  11. 40 CFR 52.432 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.432 Section 52.432 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulation for preventing significant deterioration of air quality. The provisions of...

  12. 40 CFR 52.432 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.432 Section 52.432 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air Act are not met... air quality. (b) Regulation for preventing significant deterioration of air quality. The provisions of...

  13. A domain analysis approach to clear-air turbulence forecasting using high-density in-situ measurements

    NASA Astrophysics Data System (ADS)

    Abernethy, Jennifer A.

    Pilots' ability to avoid clear-air turbulence (CAT) during flight affects the safety of the millions of people who fly commercial airlines and other aircraft, and turbulence costs millions in injuries and aircraft maintenance every year. Forecasting CAT is not straightforward, however; microscale features like the turbulence eddies that affect aircraft (100m) are below the current resolution of operational numerical weather prediction (NWP) models, and the only evidence of CAT episodes, until recently, has been sparse, subjective reports from pilots known as PIREPs. To forecast CAT, researchers use a simple weighted sum of top-performing turbulence indicators derived from NWP model outputs---termed diagnostics---based on their agreement with current PIREPs. However, a new, quantitative source of observation data---high-density measurements made by sensor equipment and software on aircraft, called in-situ measurements---is now available. The main goal of this thesis is to develop new data analysis and processing techniques to apply to the model and new observation data, in order to improve CAT forecasting accuracy. This thesis shows that using in-situ data improves forecasting accuracy and that automated machine learning algorithms such as support vector machines (SVM), logistic regression, and random forests, can match current performance while eliminating almost all hand-tuning. Feature subset selection is paired with the new algorithms to choose diagnostics that predict well as a group rather than individually. Specializing forecasts and choice of diagnostics by geographic region further improves accuracy because of the geographic variation in turbulence sources. This work uses random forests to find climatologically-relevant regions based on these variations and implements a forecasting system testbed which brings these techniques together to rapidly prototype new, regionalized versions of operational CAT forecasting systems.

  14. SPATIAL PREDICTION OF AIR QUALITY DATA

    EPA Science Inventory

    Site-specific air quality monitoring data have been used extensively in both scientific and regulatory programs. As such, these data provide essential information to the public, environmental managers, and the atmospheric research community. Currently, air quality management prac...

  15. Aviation Forecasting in ICAO

    NASA Technical Reports Server (NTRS)

    Mcmahon, J.

    1972-01-01

    Opinions or plans of qualified experts in the field are used for forecasting future requirements for air navigational facilities and services of international civil aviation. ICAO periodically collects information from Stators and operates on anticipated future operations, consolidates this information, and forecasts the future level of activity at different airports.

  16. Exploration of OMI Products for Air Quality Applications Through Comparisons with Models and Observations

    NASA Technical Reports Server (NTRS)

    Pickering, K. E.; Ziemke, J.; Bucsela, E.; Gleason, J.; Marufu, L.; Dickerson, R.; Mathur, R.; Davidson, P.; Duncan, B.; Bhartia, P. K.

    2006-01-01

    The Ozone Monitoring Instrument (OMI) on board NASA s Aura satellite was launched in July 2004, and is now providing daily global observations of total column ozone, NO2, and SO2, as well as aerosol information. Algorithms have also been developed to produce daily tropospheric ozone and NO2 products. The tropospheric ozone product reported here is a tropospheric residual computed through use of Aura Microwave Limb Sounder (MLS) ozone profile data to quantify stratospheric ozone. We are investigating the applicability of OMI products for use in air quality modeling, forecasting, and analysis. These investigations include comparison of the OMI tropospheric O3 and NO2 products with global and regional models and with lower tropospheric aircraft observations. Large-scale transport of pollution seen in the OM1 tropospheric O3 data is compared with output from NASA's Global Modeling Initiative global chemistry and transport model. On the regional scale we compare the OMI tropospheric O3 and NO2 with fields from the National Oceanic and Atmospheric Administration and Environmental Protection Agency (NOAA/EPA) operational Eta/CMAQ air quality forecasting model over the eastern United States. This 12-km horizontal resolution model output is roughly of equivalent resolution to the OMI pixel data. Correlation analysis between lower tropospheric aircraft O3 profile data taken by the University of Maryland over the Mid-Atlantic States and OMI tropospheric column mean volume mixing ratio for O3 will be presented. These aircraft data are representative of the lowest 3 kilometers of the atmosphere, the region in which much of the locally-generated and regionally-transported ozone exists.

  17. Improved Space-Time Forecasting of next Day Ozone Concentrations in the Eastern U.S.

    EPA Science Inventory

    There is an urgent need to provide accurate air quality information and forecasts to the general public and environmental health decision-makers. This paper develops a hierarchical space-time model for daily 8-hour maximum ozone concentration (O3) data covering much of the easter...

  18. Evaluating ammonia (NH3) predictions in the NOAA National Air Quality Forecast Capability (NAQFC) using in-situ aircraft and satellite measurements from the CalNex2010 campaign

    NASA Astrophysics Data System (ADS)

    Bray, Casey D.; Battye, William; Aneja, Viney P.; Tong, Daniel; Lee, Pius; Tang, Youhua; Nowak, John B.

    2017-08-01

    Atmospheric ammonia (NH3) is not only a major precursor gas for fine particulate matter (PM2.5), but it also negatively impacts the environment through eutrophication and acidification. As the need for agriculture, the largest contributing source of NH3, increases, NH3 emissions will also increase. Therefore, it is crucial to accurately predict ammonia concentrations. The objective of this study is to determine how well the U.S. National Oceanic and Atmospheric Administration (NOAA) National Air Quality Forecast Capability (NAQFC) system predicts ammonia concentrations using their Community Multiscale Air Quality (CMAQ) model (v4.6). Model predictions of atmospheric ammonia are compared against measurements taken during the NOAA California Nexus (CalNex) field campaign that took place between May and July of 2010. Additionally, the model predictions were also compared against ammonia measurements obtained from the Tropospheric Emission Spectrometer (TES) on the Aura satellite. The results of this study showed that the CMAQ model tended to under predict concentrations of NH3. When comparing the CMAQ model with the CalNex measurements, the model under predicted NH3 by a factor of 2.4 (NMB = -58%). However, the ratio of the median measured NH3 concentration to the median of the modeled NH3 concentration was 0.8. When compared with the TES measurements, the model under predicted concentrations of NH3 by a factor of 4.5 (NMB = -77%), with a ratio of the median retrieved NH3 concentration to the median of the modeled NH3 concentration of 3.1. Because the model was the least accurate over agricultural regions, it is likely that the major source of error lies within the agricultural emissions in the National Emissions Inventory. In addition to this, the lack of the use of bidirectional exchange of NH3 in the model could also contribute to the observed bias.

  19. The Value of Clean Air: Comparing Discounting of Delayed Air Quality and Money Across Magnitudes

    PubMed Central

    Friedel, Jonathan E.; DeHart, William B.; Mahamane, Salif; Jordan, Kerry E.; Odum, Amy L.

    2018-01-01

    The detrimental health effects of exposure to air pollution are well established. Fostering behavioral change concerning air quality may be challenging because the detrimental health effects of exposure to air pollution are delayed. Delay discounting, a measure of impulsive choice, encapsulates this process of choosing between the immediate conveniences of behaviors that increase pollution and the delayed consequences of prolonged exposure to poor air quality. In Experiment 1, participants completed a series of delay-discounting tasks for air quality and money. We found that participants discounted delayed air quality more than money. In Experiment 2, we investigated whether the common finding that large amounts of money are discounted less steeply than small amounts of money generalized to larger and smaller improvements in air quality. Participants discounted larger improvements in air quality less steeply than smaller improvements, indicating that the discounting of air quality shares a similar process as the discounting of money. Our results indicate that the discounting of delayed money is strongly related to the discounting of delayed air quality and that similar mechanisms may be involved in the discounting of these qualitatively different outcomes. These data are also the first to demonstrate the malleability of delay discounting of air quality, and provide important public health implications for decreasing delay discounting of air quality. PMID:29606776

  20. 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

  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. Strength of smoke-free air laws and indoor air quality

    PubMed Central

    Hahn, Ellen J.; Robertson, Heather E.; Vogel, Suzann L.; Travers, Mark J.

    2009-01-01

    Introduction: Smoke-free air laws have been implemented in many Kentucky communities to protect the public from the harmful effects of secondhand smoke exposure. The impact of different strengths of smoke-free air laws on indoor air quality was assessed. Methods: Indoor air quality in hospitality venues was assessed in seven communities before and after comprehensive smoke-free air laws and in two communities only after partial smoke-free air laws. One community was measured three times: before any smoke-free air law, after the initial partial law, and after the law was strengthened to cover all workplaces and public places with few exemptions. Real-time measurements of particulate matters with 2.5 μm aerodynamic diameter or smaller (PM2.5) were obtained. Results: When comprehensive smoke-free air laws were implemented, indoor PM2.5 concentrations decreased significantly from 161 to 20 μg/m3. In one community that implemented a comprehensive smoke-free law after initially passing a partial law, indoor PM2.5 concentrations were 304 μg/m3 before the law, 338 μg/m3 after the partial law, and 9 μg/m3 after the comprehensive law. Discussion: The study clearly demonstrated that partial smoke-free air laws do not improve indoor air quality. A significant linear trend indicated that PM2.5 levels in the establishments decreased with fewer numbers of burning cigarettes. Only comprehensive smoke-free air laws are effective in reducing indoor air pollution from secondhand tobacco smoke. PMID:19346510

  3. Air Quality Monitoring: Risk-Based Choices

    NASA Technical Reports Server (NTRS)

    James, John T.

    2009-01-01

    Air monitoring is secondary to rigid control of risks to air quality. Air quality monitoring requires us to target the credible residual risks. Constraints on monitoring devices are severe. Must transition from archival to real-time, on-board monitoring. Must provide data to crew in a way that they can interpret findings. Dust management and monitoring may be a major concern for exploration class missions.

  4. Cleaner Air through Cooperation: Progress under the Air Quality Agreement- 2003

    EPA Pesticide Factsheets

    Read a brochure that provides an overview of the air quality agreement between the U.S. and Canada, followed by key commitments and progress, including air quality programs and scientific cooperation between the two nations.

  5. 78 FR 63933 - Approval and Promulgation of Air Quality Implementation Plans; Virginia; Revised Ambient Air...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-25

    ...] Approval and Promulgation of Air Quality Implementation Plans; Virginia; Revised Ambient Air Quality... of Virginia adding ambient air quality standards and associated reference conditions for Fine Particulate Matter (PM 2.5 ) that are consistent with the 2013 National Ambient Air Quality Standards (NAAQS...

  6. The Impact of Residential Combustion Emissions on Air Quality and Human Health in China

    NASA Astrophysics Data System (ADS)

    Archer-Nicholls, S.; Wiedinmyer, C.; Baumgartner, J.; Brauer, M.; Cohen, A.; Carter, E.; Frostad, J.; Forouzanfar, M.; Xiao, Q.; Liu, Y.; Yang, X.; Hongjiang, N.; Kun, N.

    2015-12-01

    Solid fuel cookstoves are used heavily in rural China for both residential cooking and heating purposes. Their use contributes significantly to regional emissions of several key pollutants, including carbon monoxide, volatile organic compounds, oxides of nitrogen, and aerosol particles. The residential sector was responsible for approximately 36%, 46% and 81% of China's total primary PM2.5, BC and OC emissions respectively in 2005 (Lei et al., 2011). These emissions have serious consequences for household air pollution, ambient air quality, tropospheric ozone formation, and the resulting population health and climate impacts. This paper presents initial findings from the modeling component of a multi-disciplinary energy intervention study currently being conducted in Sichuan, China. The purpose of this effort is to quantify the impact of residential cooking and heating emissions on regional air quality and human health. Simulations with varying levels of residential emissions have been carried out for the whole of 2014 using the Weather Research and Forecasting model with Chemistry (WRF-Chem), a fully-coupled, "online" regional chemical transport model. Model output is evaluated against surface air quality measurements across China and compared with seasonal (winter and summer) ambient air pollution measurements conducted at the Sichuan study site in 2014. The model output is applied to available exposure—response relationships between PM2.5 and cardiopulmonary health outcomes. The sensitivity in different regions across China to the different cookstove emission scenarios and seasonality of impacts are presented. By estimating the mortality and disease burden risk attributable to residential emissions we demonstrate the potential benefits from large-scale energy interventions. Lei Y, Zhang Q, He KB, Streets DG. 2011. Primary anthropogenic aerosol emission trends for China, 1990-2005. Atmos. Chem. Phys. 11:931-954.

  7. Classification of air quality using fuzzy synthetic multiplication.

    PubMed

    Abdullah, Lazim; Khalid, Noor Dalina

    2012-11-01

    Proper identification of environment's air quality based on limited observations is an essential task to meet the goals of environmental management. Various classification methods have been used to estimate the change of air quality status and health. However, discrepancies frequently arise from the lack of clear distinction between each air quality, the uncertainty in the quality criteria employed and the vagueness or fuzziness embedded in the decision-making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies when describing integrated air quality conditions with respect to various pollutants. Therefore, this paper presents two fuzzy multiplication synthetic techniques to establish classification of air quality. The fuzzy multiplication technique empowers the max-min operations in "or" and "and" in executing the fuzzy arithmetic operations. Based on a set of air pollutants data carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, and particulate matter (PM(10)) collected from a network of 51 stations in Klang Valley, East Malaysia, Sabah, and Sarawak were utilized in this evaluation. The two fuzzy multiplication techniques consistently classified Malaysia's air quality as "good." The findings indicated that the techniques may have successfully harmonized inherent discrepancies and interpret complex conditions. It was demonstrated that fuzzy synthetic multiplication techniques are quite appropriate techniques for air quality management.

  8. 40 CFR 52.931 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.931 Section 52.931 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... deterioration of air quality. (a) Regulations for preventing significant deterioration of air quality. The..., the Kentucky Division for Air Quality has determined that the application complies with the applicable...

  9. 40 CFR 52.2451 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.2451 Section 52.2451 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... Quality Deterioration. (b) Regulations for preventing significant deterioration of air quality. The...

  10. 40 CFR 52.2528 - Significant deterioration of air quality.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... quality. 52.2528 Section 52.2528 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of Sections 160 through 165 of the Clean Air... Quality Deterioration. (b) Regulations for Preventing Significant Deterioration of Air Quality, the...

  11. 40 CFR 52.2528 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.2528 Section 52.2528 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of Sections 160 through 165 of the Clean Air... Quality Deterioration. (b) Regulations for Preventing Significant Deterioration of Air Quality, the...

  12. 40 CFR 52.2451 - Significant deterioration of air quality.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... quality. 52.2451 Section 52.2451 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... Quality Deterioration. (b) Regulations for preventing significant deterioration of air quality. The...

  13. 40 CFR 52.2451 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.2451 Section 52.2451 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... Quality Deterioration. (b) Regulations for preventing significant deterioration of air quality. The...

  14. 40 CFR 52.2451 - Significant deterioration of air quality.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... quality. 52.2451 Section 52.2451 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... Quality Deterioration. (b) Regulations for preventing significant deterioration of air quality. The...

  15. 40 CFR 52.2528 - Significant deterioration of air quality.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... quality. 52.2528 Section 52.2528 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of Sections 160 through 165 of the Clean Air... Quality Deterioration. (b) Regulations for Preventing Significant Deterioration of Air Quality, the...

  16. 40 CFR 52.2451 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.2451 Section 52.2451 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of sections 160 through 165 of the Clean Air... Quality Deterioration. (b) Regulations for preventing significant deterioration of air quality. The...

  17. 40 CFR 52.2528 - Significant deterioration of air quality.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... quality. 52.2528 Section 52.2528 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Significant deterioration of air quality. (a) The requirements of Sections 160 through 165 of the Clean Air... Quality Deterioration. (b) Regulations for Preventing Significant Deterioration of Air Quality, the...

  18. 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

  19. 78 FR 63878 - Approval and Promulgation of Air Quality Implementation Plans; Virginia; Revised Ambient Air...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-25

    ...] Approval and Promulgation of Air Quality Implementation Plans; Virginia; Revised Ambient Air Quality... State Implementation Plan (SIP). The revisions add ambient air quality standards and associated... Ambient Air Quality Standards (NAAQS) for PM 2.5 . EPA is approving these revisions in accordance with the...

  20. 76 FR 76048 - Air Quality Designations for the 2008 Lead (Pb) National Ambient Air Quality Standards

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-06

    ... ENVIRONMENTAL PROTECTION AGENCY 40 CFR Part 81 [EPA-HQ-OAR-2009-0443; FRL-9492-3] RIN 2060-AR17 Air Quality Designations for the 2008 Lead (Pb) National Ambient Air Quality Standards Correction In rule document 2011-29460 appearing on pages 72097-72120 in the issues of Tuesday, November 22, 2011...