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Atmospheric Modeling
Citation:
SEIGNEUR, C. AND R. L. DENNIS. Atmospheric Modeling. 1st, Chapter 9, G.M. Hidy, J.R. Brooks, K.L. Demerjian, L.T. Molina, W. Pennell and R.D. Scheffe (ed.), Technical Challenges of Multipollutant Air Quality Management. Springer Science+Business Media B.V, Dordrecht, Netherlands, 1(1):299-337, (2011).
Impact/Purpose:
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 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:
Although air quality models have been applied historically to address issues specific to ambient air quality standards (i.e., one criteria pollutant at a time) or welfare (e.g.. acid deposition or visibility impairment). they are inherently multipollutant based. Therefore. in principle air quality models can be applied in the context of integrated emissions control programs that are designed to optimally address all of the above air quality issues simultaneously. Limitations arise. however. as additional chemical species of concern are identified that are not currently treated in air quality models. Such cases require the compilation of emission inventories and boundary conditions for these new chemical species and the addition of chemical and physical mechanisms in the model to treat their transformation and deposition.