Societal shifts due to COVID-19 reveal large-scale complexities and feedbacks between atmospheric chemistry and climate change.

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NO x emissions. Second, the response of O3 to decreased NO x emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.

Consistent weekly cycles of atmospheric NO2, CO, and CO2 in a North American megacity from ground-based, mountaintop, and satellite measurements

The weekday-weekend effect of anthropogenic emissions in cities, driven by the associated weekly changes in human activities, provides a unique opportunity to assess the sensitivity of observation networks (e.g., ground-based and space-borne instruments) on urban emissions. In this study, we focus on the weekly cycle amplitudes of nitrogen dioxide (NO2), carbon monoxide (CO), and carbon dioxide (CO2) in the Los Angeles (LA) megacity, where a significant weekly cycle of human activities exists. In addition, abundant observations are being produced continuously from existing ground-based, mountaintop, and satellite platforms to monitor carbon emissions and air quality in LA. From our analysis, significant agreement can be found in observations from different platforms. For NO2, a 30%–35% Sunday decline relative to mid-week mixing ratios can be observed from both ground-based and satellite observations. For CO, the Sunday drops from ground-based, mountain-top and satellite observations are 13%–20%. The TROPOMI instrument with its high spatial resolution provides detailed spatial information on the reduction of tropospheric NO2 and CO columns on Sundays. The spatial pattern is in good agreement with traffic density in LA. Impact due to the prevailing winds from the coast in the afternoon can also be observed. For anthropogenic CO2, we show that the weekly cycle of XCO2 enhancement above background from OCO-2 observations has a Sunday decline (15%–20%) consistent with ground-based observations and TCCON. This weekly pattern of CO2 in a megacity directly detected by OCO-2 is reported for the first time. In addition, we also investigate the weekly cycles in the stable carbon isotopic composition of CO2 (δ13C) from ground-based observations, which demonstrates the weekly variation in fossil fuel usage in LA. Finally, using the COVID-19 lockdown period as an example of a short-term perturbation on anthropogenic emissions, we found that the weekly cycle amplitude became larger during the lockdown period primarily because of the traffic volume changes in light-duty vehicles. This study highlights the consistencies and effectiveness of existing observing platforms in monitoring the anthropogenic emissions of the LA megacity.

Detecting the Responses of CO2 Column Abundances to Anthropogenic Emissions from Satellite Observations of GOSAT and OCO-2

The continuing increase in atmospheric CO2 concentration caused by anthropogenic CO2 emissions significantly contributes to climate change driven by global warming. Satellite measurements of long-term CO2 data with global coverage improve our understanding of global carbon cycles. However, the sensitivity of the space-borne measurements to anthropogenic emissions on a regional scale is less explored because of data sparsity in space and time caused by impacts from geophysical factors such as aerosols and clouds. Here, we used global land mapping column averaged dry-air mole fractions of CO2 (XCO2) data (Mapping-XCO2), generated from a spatio-temporal geostatistical method using GOSAT and OCO-2 observations from April 2009 to December 2020, to investigate the responses of XCO2 to anthropogenic emissions at both global and regional scales. Our results show that the long-term trend of global XCO2 growth rate from Mapping-XCO2, which is consistent with that from ground observations, shows interannual variations caused by the El Niño Southern Oscillation (ENSO). The spatial distributions of XCO2 anomalies, derived from removing background from the Mapping-XCO2 data, reveal XCO2 enhancements of about 1.5–3.5 ppm due to anthropogenic emissions and seasonal biomass burning in the wintertime. Furthermore, a clustering analysis applied to seasonal XCO2 clearly reveals the spatial patterns of atmospheric transport and terrestrial biosphere CO2 fluxes, which help better understand and analyze regional XCO2 changes that are associated with atmospheric transport. To quantify regional anomalies of CO2 emissions, we selected three representative urban agglomerations as our study areas, including the Beijing-Tian-Hebei region (BTH), the Yangtze River Delta urban agglomerations (YRD), and the high-density urban areas in the eastern USA (EUSA). The results show that the XCO2 anomalies in winter well capture the several-ppm enhancement due to anthropogenic CO2 emissions. For BTH, YRD, and EUSA, regional positive anomalies of 2.47 ± 0.37 ppm, 2.20 ± 0.36 ppm, and 1.38 ± 0.33 ppm, respectively, can be detected during winter months from 2009 to 2020. These anomalies are slightly higher than model simulations from CarbonTracker-CO2. In addition, we compared the variations in regional XCO2 anomalies and NO2 columns during the lockdown of the COVID-19 pandemic from January to March 2020. Interestingly, the results demonstrate that the variations of XCO2 anomalies have a positive correlation with the decline of NO2 columns during this period. These correlations, moreover, are associated with the features of emitting sources. These results suggest that we can use simultaneously observed NO2, because of its high detectivity and co-emission with CO2, to assist the analysis and verification of CO2 emissions in future studies.