Diesel passenger vehicle shares influenced COVID-19 changes in urban nitrogen dioxide pollution

Abstract

Diesel-powered vehicles emit several times more nitrogen oxides than comparable gasoline-powered vehicles, leading to ambient nitrogen dioxide (NO _2 ) pollution and adverse health impacts. The COVID-19 pandemic and ensuing changes in emissions provide a natural experiment to test whether NO _2 reductions have been starker in regions of Europe with larger diesel passenger vehicle shares. Here we use a semi-empirical approach that combines in-situ NO _2 observations from urban areas and an atmospheric composition model within a machine learning algorithm to estimate business-as-usual NO _2 during the first wave of the COVID-19 pandemic in 2020. These estimates account for the moderating influences of meteorology, chemistry, and traffic. Comparing the observed NO _2 concentrations against business-as-usual estimates indicates that diesel passenger vehicle shares played a major role in the magnitude of NO _2 reductions. European cities with the five largest shares of diesel passenger vehicles experienced NO _2 reductions ${\sim}2.5$ times larger than cities with the five smallest diesel shares. Extending our methods to a cohort of non-European cities reveals that NO _2 reductions in these cities were generally smaller than reductions in European cities, which was expected given their small diesel shares. We identify potential factors such as the deterioration of engine controls associated with older diesel vehicles to explain spread in the relationship between cities’ shares of diesel vehicles and changes in NO _2 during the pandemic. Our results provide a glimpse of potential NO _2 reductions that could accompany future deliberate efforts to phase out or remove passenger vehicles from cities.

Keywords

• urban air quality
• machine learning
• environmental modeling
• COVID-19
• nitrogen dioxide
• diesel