Observing the spatial heterogeneities of NO2 air pollution is an important first step in quantifying NOx emissions and exposures. This study investigates the capabilities of the Tropospheric Monitoring Instrument (TROPOMI) in observing the spatial and temporal patterns of NO2 pollution in the Continental United States (CONUS).  The high instrument sensitivity can differentiate the fine-scale spatial heterogeneities in urban areas, such as hotspots related to airport/shipping operations and high traffic areas, and the relatively small emission sources in rural areas, such as power plants and mining operations. We also examine NO2 columns by day-of-the-week and find that Saturday and Sunday concentrations are 16% and 24% lower respectively than during weekdays.  In cities with topographic features that inhibit dispersion, such as Los Angeles, there appears to be a pollution build-up from Monday through Friday, while cities which have better dispersion have more variability during weekdays. We also analyze the correlation of temperatures and NO2 column amounts and find that NO2 is larger on the hottest days (>32C) as compared to warm days (26C - 32C), which is in contrast to a general decrease in NO2 with increasing temperature at lower temperature bins. Finally, we compare column NO2 with estimates of surface PM2.5 and find fairly poor correlation, suggesting that NO2 and PM2.5 are becoming increasingly less correlated in CONUS. These new developments make TROPOMI NO2 satellite data advantageous for policymakers and public health officials, who request information at high spatial resolution and short timescales, in order to assess, devise, and evaluate regulations.

Satellite data show substantial drops in nitrogen dioxide (NO2) during COVID-19 physical distancing. To attribute NO2 changes to NOx emissions changes over short timescales, one must account for meteorological effects. We find that meteorological patterns were especially favorable for low NO2 in much of the U.S. in spring 2020, complicating comparisons with spring 2019. Meteorological variations between years can cause column NO2 differences of ~15% over monthly timescales. After accounting for sun angle and meteorological considerations, we calculate that NO2 drops ranged between 9.2 – 43.4% among twenty cities in North America, with a median of 21.6%. Of the studied cities, largest NO2 drops (>30%) were in San Jose, Los Angeles, and Toronto, and smallest drops (<12%) were in Miami, Minneapolis, and Dallas. These normalized NO2 changes can be used to highlight locations with greater activity changes and better understand the sources contributing to adverse air quality in each city.

Diesel-powered vehicles emit several times more nitrogen oxides than comparable gasoline-powered vehicles, leading to ambient nitrogen dioxide (NO2) pollution and adverse health impacts. The COVID-19 pandemic and ensuing changes in emissions provide a natural experiment to test whether NO2 reductions have been starker in Europe, a region with larger diesel passenger vehicle shares. Here we use a semi-empirical approach that combines in-situ NO2 observations from urban areas and an atmospheric composition model within a machine learning algorithm to estimate business-as-usual NO2 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 NO2 concentrations against business-as-usual estimates indicates that diesel passenger vehicle shares played a major role in the magnitude of NO2 reductions. European cities with the five largest shares of diesel passenger vehicles experienced NO2 reductions ~2.5 times larger than cities with the five smallest diesel shares. Extending our methods to a cohort of non-European cities from the C40 Cities network reveals that NO2 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 NO2 during the pandemic. Our results provide a glimpse of potential NO2 reductions that could accompany future deliberate efforts to phase out or remove passenger vehicles from cities.