3B.3 Exploring the Spatial Variation of Volatile Organic Compounds in Louisiana’s Industrial corridor and Impacts to Community Exposures and Health Risk (Invited Presentation)

Monday, 13 January 2025: 2:15 PM
229 (New Orleans Ernest N. Morial Convention Center)
Peter Francis DeCarlo, Johns Hopkins Univ., Baltimore, MD; and E. Robinson, A. Yassine, M. Tehrani, A. Chiger, C. Gigot, S. Lupolt, B. A. Nault, Ph.D., E. Fortner, M. Canagaratna, C. Daube, B. Werden, J. R. Roscioli, H. Stark, S. Herndon, A. Rule, K. Koehler, T. Yacovitch, M. Claflin, T. Burke, and K. Nachman

Fenceline communities frequently bear the brunt of environmental pollution, and current regulatory monitoring approaches fail to generate the data needed to document these disproportionate exposures. We addressed this critical data gap by combining state-of-the-art analytical instrumentation deployed on a mobile laboratory combined with stationary sampling to characterize spatial concentration gradients for hazardous air pollutants (I.e. VOCs, particulate matter, and metals) in a highly industrialized in the Mississippi River corridor in Louisiana. We quantified the pollutant burden contributed by petrochemical and other industrial activity by calculating average spatial concentrations of air pollutants measured from the mobile laboratory in the study area. Gradients in hazardous air pollutants, including ethylene oxide and chloroprene, were observed with higher levels, and consequently higher exposure risk, found near facility fencelines. Observed differences in concentration and therefore exposure for a suite of hazardous air pollutants were then placed in a cumulative risk framework to show the health risks in the study area and at the neighborhood scale. This required linking approximately 45 measured hazardous air pollutants to cancer and non-cancer health endpoints and determination of cumulative cancer burden and non-cancer health endpoints. This presentation will provide an overview of the HAP-MAP Louisiana study design and results and compare to regulatory based models.
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