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Improvements to the WRF-CMAQ modeling system for fine-scale air quality simulations
Citation:
Appel, W., R. Gilliam, Jon Pleim, G. Pouliot, David-C Wong, C. Hogrefe, S. Roselle, AND R. Mathur. Improvements to the WRF-CMAQ modeling system for fine-scale air quality simulations. EM: AIR AND WASTE MANAGEMENT ASSOCIATION'S MAGAZINE FOR ENVIRONMENTAL MANAGERS. Air & Waste Management Association, Pittsburgh, PA, , 16-21, (2014).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL′s)Atmospheric Modeling 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 used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Description:
Despite significant reductions in atmospheric pollutants such as ozone (O3) and fine particulate matter (PM2.5) over the past several decades, air pollution continues to pose a threat to the health of humans and sensitive ecosystems. A number of areas across the U.S. remain in violation of the National Ambient Air Quality Standards (NAAQS; http://www.epa.gov/airquality/greenbook). Numerical air quality modeling systems designed to simulate the emissions, transport and fate of atmospheric pollutants are a critical part of the regulatory process in designing abatement strategies to reduce these pollutants. Air quality models are also used to forecast “next day” air quality conditions so as to allow citizens to modify their activities accordingly to avoid potential health issues (e.g. asthma attacks). Eulerian air quality models, such as the Community Multiscale Air Quality (CMAQ; Foley et al. 2010) model, discretize large simulation domains into smaller sized grid cells in order to better represent spatial heterogeneities, with smaller-sized grid cells in theory providing a truer representation of fine-scale processes and near-field impacts. While utilizing larger-sized grid cells has the advantage of minimizing computation resources, it does have several disadvantages. Since Eulerian air quality models instantly dilute point emissions across the entire volume of the grid cell, decisions on grid resolution should be made with consideration of the spatial scale of the air quality problem, meteorology, and emissions being modeled while also recognizing the increased computation resources required as grid cell size is decreased. The smaller the dimensions of the grid cells used, the more representative the model may be of the actual point source emissions. Additionally, meteorological fields (e.g. wind and temperature) are also likely to be better represented with smaller grid cells, particularly in areas with diverse and complex geography (e.g. coastal and mountainous regions).
