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dc.contributor.authorGao, H. Oliver
dc.date.accessioned2020-10-16T15:02:20Z
dc.date.available2020-10-16T15:02:20Z
dc.date.issued2020-02-28
dc.identifier.urihttps://hdl.handle.net/1813/72906
dc.descriptionProject Descriptionen_US
dc.description.abstractSignificant emissions from transportation contribute to the formation of O3 and fine particulate matter (PM2.5), exacerbating both air quality and health. In this study, we analyze multiple scenarios to understand how future fleet electrification and turnover of both gasoline and diesel vehicles affect air quality and health in the Houston area. For each scenario, we examine increased vehicle activity and various configurations of emissions controls. To capture urban features in significant detail, we model each scenario using the high-resolution (1km) WRF-SMOKE-CMA Q-BenMAP air quality and health modeling framework. Model predictions for 2040, compared to a base year of 2013, indicate a ~50% increase in emissions in the Business As Usual (BAU) scenario, and ~50%, ~75%, and ~95% reductions in the Moderate Electrification (ME), Aggressive Electrification (AE), and Complete Turnover (CT) scenarios, respectively. The emissions control cases show an increase in maximum 8h O3 of 1-4 ppb along highways but reductions in two regions—those enclosed by the highways and those downwind—and a decrease in simulated PM2.5 concentrations of between 0.5-2 μg m-3. The associated health impacts and economic benefits will be studied. The analytical framework developed in this study can be applied to other metropolitan areas.en_US
dc.description.sponsorshipU.S. Department of Transportation 69A3551747119en_US
dc.language.isoen_USen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titlePotential impacts of electric vehicles on air quality and health endpoints in the Greater Houston Area in 2040en_US
dc.typefact sheeten_US
schema.accessibilityFeaturealternativeTexten_US
schema.accessibilityFeaturereadingOrderen_US
schema.accessibilityFeaturestructuralNavigationen_US
schema.accessibilityFeaturetaggedPDFen_US
schema.accessibilityHazardunknownen_US


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