Emissions of nitrogen oxides (NOx = NO + NO2) in the United States have declined significantly during the past three decades. However, satellite observations since 2009 indicate total column NO2 is no longer declining even as bottom-up inventories suggest continued decline in emissions. Multiple explanations have been proposed for this discrepancy including 1) the increasing relative importance of non-urban NOx to total column NO2, 2) differences between background and urban NOx lifetimes, and 3) that the actual NOx emissions are declining more slower after 2009. Here we use a deep learning model trained by NOx emissions and surface observations of ozone to assess consistency between the reported NOx trends between 2005-2014 and observations of surface ozone. We find that the 2005-2014 trend from older satellite-derived emission estimates produced at low spatial resolution best reproduce ozone in low NOx emission (background) regions, reflecting the blending of urban and background NOx in these low-resolution top-down analyses. The trend from higher resolution satellite-based estimates, which are more capable of capturing the urban emission signature, is in better agreement with ozone in high NOx emission regions, and is consistent with the trend based on surface observations of NO2. In contrast, the 2005-2014 trend from the US Environmental Protection Agency (EPA) National Emission Inventory (NEI) results in an underestimate of ozone. Our results confirm that the satellite-derived trends reflect anthropogenic and background influences and that the 2005-2014 trend in the NEI inventory is overestimating recent reductions in NOx emissions.

This study compares recent CO, NO, NMVOC, SO, BC and OC anthropogenic emissions from several state-of-the-art top-down estimates to global and regional bottom-up inventories and projections from five SSPs in several regions. Results show that top-down emissions exhibit similar uncertainty as bottom-up inventories in most regions, and even less in some such as China. In general, for all species the largest discrepancies are found outside of regions such as the U.S., Europe and Japan where the most accurate and detailed information on emissions is available. In some regions such as China, which has undergone dynamical economic growth and changes in air quality regulations during the last several years, the top-down estimates better capture recent emission trends than global bottom-up inventories. These results show the potential of top-down estimates to complement bottom-up inventories and to aide in the development of emission scenarios, particularly in regions where global inventories lack the necessary up-to-date and accurate information regarding regional activity data and emission factors such as Africa and India. Areas of future work aimed at quantifying and reducing uncertainty are also highlighted. A regional comparison of recent CO and NO trends in the five SSPs indicate that SSP126, a strong-pollution control scenario, best represents the trends from the from top-down and regional bottom-up inventories in the U.S., Europe and China, while SSP460, a low-pollution control scenario, lies closest to actual trends in West Africa. This analysis can be a useful guide for air quality forecasting and near-future pollution control/mitigation policy studies.

Efforts to stem the spread of COVID-19 in China hinged on severe restrictions to human movement starting January 23rd, 2020 in Wuhan and subsequently to other provinces. Here, we quantify the ancillary impacts on air pollution and human health using inverse emissions estimates based on multiple satellite observations. We find that Chinese NOx emissions were reduced by 36% from early January to mid-February, with more than 80% of reductions occurring after their respective lockdown in most provinces. These emissions declines increased surface ozone by up to 16 ppb over northern China but decreased PM2.5 by up to 23 µgm nationwide. Air pollution appears to have substantially offset hospital admissions related to COVID-19, augmenting mitigation efforts, such as in the Hubei province with ~400 reduced admissions. Changes in human exposure are associated with about 2,100 increased ozone-related morbidity incidences and avoidance of at least 60,000 PM2.5-related morbidity incidences.