NSF/CONACyT: Integrated Air Modeling Approach to PM Source Apportionment at the USA/Mexico Border

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0220079 Lighty The University of Utah (UofU) and the Instituto Tecnologico y de Estudios Superiores de Monterrey (ITESM) are involved in a collaborative air quality modeling study of ambient particulate matter (PM) in selected areas of the Lower Rio Grande Valley (LRGV) section of the USA/Mexico border. Special attention is being given to the peculiar evening episodes with very high PM levels observed near several large border cities and reported to be associated with increased mortality risk in at least one region.The partners have recently participated in a comprehensive PM characterization and source attribution study of the Paso del Norte airshed and propose to use a novel, integrated approach to PM source apportionment by cross-validating the results of PM Receptor Modeling (using factor analysis of receptor and source characterization data to estimate major source contributions) with PM Source Modeling results (using area emission estimates and geography- plus meteorology-based dispersion models to predict evening PM concentrations at specific receptor sites). Successful integration of both methods should permit some degree of interpolation between the limited sampling locations and time points afforded by Receptor Modeling alone while enabling calibration of Source Modeling predictions. Other potential benefits include improved PM exposure risk assessment opportunities for various population groups and more detailed evaluation of the widely reported statistical association between 24-hr PM averages and urban mortality plus morbidity. Most of the PM receptor characterization and modeling tasks will be carried out by the Uof U team whereas primary responsibility for the source measurement and modeling tasks will be undertaken by the ITESM team. Integration of measurement, data fusion, evaluation, and interpretation tasks will require a highly coordinated effort by both teams, an International Collaboration being supported by the NSF-CONACyT Collaborative Research Opportunities Program.