Xi Gong1, F Benjamin Zhan2, Jean D Brender3, Peter H Langlois4, Yan Lin5. 1. Texas State University, Texas Center for Geographic Information Science, Department of Geography, San Marcos, TX 78666, USA. Electronic address: gong@txstate.edu. 2. Texas State University, Texas Center for Geographic Information Science, Department of Geography, San Marcos, TX 78666, USA. Electronic address: zhan@txstate.edu. 3. Texas A&M Health Science Center School of Public Health, Department of Epidemiology & Biostatistics, College Station, TX 77843-1266, USA. Electronic address: jdbrender@sph.tamhsc.edu. 4. Birth Defects Epidemiology and Surveillance Branch, Texas Department of State Health Services, PO Box 149347, MC 1964, Austin, TX 78714-9347, USA. Electronic address: peter.langlois@dshs.state.tx.us. 5. South Dakota State University, Department of Geography, Brookings, SD 57007, USA. Electronic address: yan.lin@sdstate.edu.
Abstract
BACKGROUND: Accurate estimates of air pollution exposure intensities are important to support environmental epidemiology analyses that require data covering large geographic areas over multiple years. The Emission Weighted Proximity Model (EWPM) and the National-Scale Air Toxics Assessment (NATA) are two viable approaches for obtaining estimate exposure intensities. The advantages of the EWPM include its simplicity and significantly lower costs of implementation. However, very limited data are available regarding the validity of the results from the EWPM and how these results would fare when compared with those from the NATA. METHODS: This study evaluates the validity of the estimated exposure intensities from the EWPM through a correlation analysis with ground monitoring data obtained by the Texas Commission on Environmental Quality (TCEQ). The monitoring data used in the comparison included 27 non-criteria air pollutants at 48 monitoring sites in Texas in 2005. In addition, this study compares the results from the EWPM with those from NATA using the TCEQ data as a gold standard. RESULTS: Analysis results suggest that estimated exposure intensities from the EWPM and the NATA were comparable when the intensities from both approaches are used to categorize environmental exposure intensities into different levels in relative terms. CONCLUSION: These findings suggest that the EWPM is a valid alternative approach to the NATA in situations where epidemiological analysis requires both environmental data and health outcome data that cover a large geographic area over multiple years.
BACKGROUND: Accurate estimates of air pollution exposure intensities are important to support environmental epidemiology analyses that require data covering large geographic areas over multiple years. The Emission Weighted Proximity Model (EWPM) and the National-Scale Air Toxics Assessment (NATA) are two viable approaches for obtaining estimate exposure intensities. The advantages of the EWPM include its simplicity and significantly lower costs of implementation. However, very limited data are available regarding the validity of the results from the EWPM and how these results would fare when compared with those from the NATA. METHODS: This study evaluates the validity of the estimated exposure intensities from the EWPM through a correlation analysis with ground monitoring data obtained by the Texas Commission on Environmental Quality (TCEQ). The monitoring data used in the comparison included 27 non-criteria air pollutants at 48 monitoring sites in Texas in 2005. In addition, this study compares the results from the EWPM with those from NATA using the TCEQ data as a gold standard. RESULTS: Analysis results suggest that estimated exposure intensities from the EWPM and the NATA were comparable when the intensities from both approaches are used to categorize environmental exposure intensities into different levels in relative terms. CONCLUSION: These findings suggest that the EWPM is a valid alternative approach to the NATA in situations where epidemiological analysis requires both environmental data and health outcome data that cover a large geographic area over multiple years.