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Examining the Impact of Regional-Scale Air Quality Regulations on Human Health Outcomes
Citation:
GARCIA, V., E. Gego, R. Jones, S. Lin, C. Pantea, S. T. RAO, AND A. Wootten. Examining the Impact of Regional-Scale Air Quality Regulations on Human Health Outcomes. Chapter 7, Douw G. Steyn and S.T. Rao (ed.), Air Pollution Modeling and its Applications XX. Springer Netherlands, , Netherlands, 7.5(C):545-548, (2010).
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:
The NOx State Implementation Plan Call was issued by the U.S. Environmental Protection Agency to reduce the emissions of nitrogen oxides from the electric power sector to curtail the regional transport of the secondarily-formed pollutant, ozone. As emission control actions often come at a significant economic cost, it is important to understand whether such regulations have reduced air pollution and improved public health and the environment as originally anticipated. In this paper, we examine the relationships among meteorological transport patterns, ozone concentration levels and respiratory-related hospital admissions across New York State using trajectory analysis and other spatial and statistical approaches. Preliminary results from this analysis are presented in this paper.