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Assessing the Future Vehicle Fleet Electrification: The Impacts on Regional and Urban Air Quality.

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There have been significant advancements in electric vehicles (EVs) in recent years. However, the different changing patterns in emissions at upstream and on-road stages and complex atmospheric chemistry of pollutants… Click to show full abstract

There have been significant advancements in electric vehicles (EVs) in recent years. However, the different changing patterns in emissions at upstream and on-road stages and complex atmospheric chemistry of pollutants lead to uncertainty in the air quality benefits from fleet electrification. This study considers the Yangtze River Delta (YRD) region in China to investigate whether EVs can improve future air quality. The Community Multiscale Air Quality model enhanced by the two-dimensional volatility basis set module is applied to simulate the temporally, spatially, and chemically resolved changes in PM2.5 concentrations and the changes of other pollutants from fleet electrification. A probable scenario (Scenario EV1) with 20% of private light-duty passenger vehicles and 80% of commercial passenger vehicles (e.g., taxis and buses) electrified can reduce average PM2.5 concentrations by 0.4 to 1.1 μg m-3 during four representative months for all urban areas of YRD in 2030. The seasonal distinctions of the air quality impacts with respect to concentration reductions in key aerosol components are also identified. For example, the PM2.5 reduction in January is mainly attributed to the nitrate reduction, whereas the secondary organic aerosol reduction is another essential contributor in August. EVs can also effectively assist in mitigating NO2 concentrations, which would gain greater reductions for traffic-dense urban areas (e.g., Shanghai). This paper reveals that the fleet electrification in the YRD region could generally play a positive role in improving regional and urban air quality.

Keywords: air; regional urban; fleet electrification; air quality

Journal Title: Environmental science & technology
Year Published: 2017

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