Characterizing the regional, sectoral and species-specific sources of pollution exposure and its associated health impacts in urban environments: case studies in Washington, D.C. and Santiago, Chile

Abstract:

Cities bear significant health impacts from poor air quality due to high levels of pollution and large exposed populations. Municipal governments are uniquely suited for addressing local air quality as they can implement pollution mitigation interventions informed by their familiarity of local emissions. We work alongside local stakeholders to characterize the sources of pollution in two urban environments: Washington D.C. and Santiago, Chile. A chemical transport model, GEOS-Chem, and its adjoint is run across multiple years and two distinct domains: the United States at 0.5° x 0.667° resolution and a new domain in Central South America at 0.25° x 0.3125° resolution. We incorporate fine resolution satellite-derived pollution to better resolve pollution exposures in both of these regions. For PM_2.5 we use products at the 0.1° x 0.1° resolution which combine AOD retrievals with chemical transport models, geostatistical information, and in situ measurements. For NO₂, we use TROPOMI NO₂ column retrievals at 3.5 x 7.0 km resolution regridded to the 0.1° x 0.1° resolution. From these simulations, we identify the regions, chemical species and sectors most responsible for the health impacts of three pollutant exposures, PM_2.5, O_3, and NO₂ and quantify the temporal and interannual changes in health burden contributions from these different sources. In D.C., we find 190 premature deaths and 1400 hospitalization occur due to pollution exposure in 2011, driven primarily from transportation NO_x and energy SO₂ emissions from outside of the region. Between 2011 and 2016, health impacts in D.C. have decreased driven by reduced contributions from energy and residential emissions despite some increases in transportation emissions. Additionally, we present the development of the new Central South American domain and its performance in comparison to in-situ data. Results from these analyses can be used to inform decision making for D.C. and Santiago and the framework developed here can be implemented for any city within available modeling domains. We also discuss plans to conduct similar analyses in the cities of Paris, Accra, and Jakarta.