Atmospheric impacts and potential for regulation of current and emerging technologies in transportation

Abstract

Although it is an integral part of everyday life and a key driver of economic growth, road transportation is also associated with negative externalities: it is a contributor to global greenhouse gases emissions, and is responsible for the emission of air pollutants. In this dissertation, I evaluate the atmospheric impacts of existing and emerging technologies in transportation, and examine regulatory options to limit negative externalities. This work develops methods to quantify and reduce the public health impacts of atmospheric emissions from road transportation. I focus on three case studies: the regulation of on-road emissions from diesel cars in Europe; the air quality impacts of electric vehicles in China; and the effect of the largest short-term decreases in global anthropogenic emissions in modern history, the COVID-19 related lockdowns.

In the first part of this thesis, I analyze the public health impacts in Europe of nitrogen oxides (NO[subscript x]) emissions from diesel cars in excess of the regulatory limits. Drawing on recent on-road measurement campaigns, fleet inventory data and driving behaviors, I estimate linearized sensitivities to changes in road transportation NO[subscript x] emissions in Europe using a state-of-the-art chemical transport model. My findings suggest that excess NO[subscript x] emissions cause 2,700 premature mortalities in Europe in 2015. 70% of these impacts occur in a different country than the emissions, suggesting that suggesting that effective strategies to reduce transportation-related air quality impacts in European countries require international cooperation. The second part of this thesis addresses the deployment of electric vehicles in China.

Although it reduces CO₂ and air pollutant emissions from transportation and refineries, substituting gasoline cars with electric vehicles (EVs) requires increased power generation. To quantify the resulting climate and air quality trade-off, I develop a high-resolution power grid model that estimates, for each unit, hourly generation and emissions under four EV charging scenarios in 2020. Using the GEOS-Chem atmospheric chemistry transport model, I find that the projected growth in EV usage by the end of 2020 would result in ~1,900 (95% CI: 1,600-2,200) avoided premature mortalities and a 2.4 Tg decrease in CO₂ emissions with the current power grid. By 2022, the benefits of EV deployment with regards to air quality and CO₂ emissions are expected to increase by 26% and 4% nationally, respectively. However, as regulations governing emissions from the oil refining sector tighten, the benefits of EV deployment for air quality will become more dependent on a cleaner power grid.

Finally, the last part of this thesis focuses on the largest short-term decreases in anthropogenic emissions in modern history. It is a comprehensive assessment of the impact of COVID-19-related lockdowns on air quality and human health. Although all sectors of activity have been impacted by the lockdowns, transportation emissions fell most, and the COVID-19-related lockdowns provide a natural experiment to quantify the air quality impacts of short-term decreases in transportation emissions in the context of decreasing emissions in all sectors. Using global satellite observations and ground measurements from 36 countries in Europe, North America, and East Asia, I find that lockdowns led to statistically significant reductions in NO₂ concentrations globally, resulting in ~26,000 avoided premature mortalities, including ~19,000 in China. However, I do not find corresponding reductions in PM₂.₅ and ozone globally.

Using satellite measurements, I show that the disconnect between NO2 and ozone changes is the result of low chemical sensitivity to NO₂. The COVID-19-related lockdowns demonstrate the need for targeted air quality policies to reduce the global burden of air pollution, especially related to secondary pollutants.