Citation:

Porter, P., E. Gego, V. Garcia, AND S. Rao. Benefits of using enhanced air quality information in human health studies. Chapter 12, Air Pollution Modeling and its Application XXII. Springer, Heidelburg, Germany, 2014:73-78, (2013).

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:

The ability of four (4) enhancements of gridded PM_2.5 concentrations derived from observations and air quality models to detect the relative risk of long-term exposure to PM_2.5 are evaluated with a simulation study. The four enhancements include nearest-neighbor (NN or central monitor), ordinary kriging (OK), FUSED (bias-adjusted model output), and direct use of model outputs (CMAQ). The methods are applied to the state of New York. After adjusting for PM estimation bias and range modification, FUSED PM and CMAQ had similar performance and were better than kriged and nearest neighbor PM.

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