I presented a new paper that has just been accepted (pre-print available at https://www.essoar.org/doi/10.1002/essoar.10503139.2) at two virtual conferences this summer: the Japanese Geophysical Union (JpGU)-American Geophysical Union (AGU) joint meeting and a special symposium on “Climatological, Meteorological and Environmental factors in the COVID-19 pandemic” sponsored by AGU and the World Meteorological Organization (WMO). Links to the posters and a blog post version of the content are included below.
JpGU-AGU joint meeting poster: https://jpgu-agu2020.ipostersessions.com/Default.aspx?s=0D-1A-03-2E-1B-8E-3B-11-6F-8C-2D-FB-1D-A9-63-38
WMO-AGU joint meeting poster: covid19covenv-agu.ipostersessions.com/Default.aspx?s=65-8E-E4-C6-B3-67-D0-AC-85-AF-19-9D-47-E7-26-17
Limited Regional Aerosol and Cloud Microphysical Changes Despite Unprecedented Decline in Nitrogen Oxide Pollution During the February 2020 COVID-19 Shutdown in China
Michael Diamond & Robert Wood
Department of Atmospheric Sciences, University of Washington, Seattle
Introduction
In late December 2019, cases of a pneumonia of unknown cause were reported in the city of Wuhan. By January 2020, the pathogen responsible—a novel zoonotic coronavirus—had already spread throughout China. To arrest the spread of COVID-19 (the disease caused by the novel coronavirus), a series of unprecedentedly strict restrictions on travel and other activities were adapted across China, slowing the spread of the epidemic in China even as the disease became a global pandemic. Unsurprisingly, this socio-economic “shutdown” had a catastrophic effect on the Chinese economy. Figure 1 shows the Purchasing Managers’ Index (PMI) for both manufacturing and non-manufacturing sectors as reported by the National Bureau of Statistics of China. The PMI is a survey-based estimate of economic activity, with values above 50% corresponding to growth and below to contraction. February 2020 stands out sharply, featuring a decline in manufacturing PMI deeper than any point during the aftermath of the 2008 financial crisis and the only period of contraction in non-manufacturing PMI since records for that index began in 2007, followed by a rapid recovery.

Methods
To assess how (and whether) pollution levels changed as a result of this abrupt February 2020 shutdown, we analyze satellite data from the Ozone Monitoring Instrument (OMI) on Aura and the Moderate Resolution Imaging Spectrometer (MODIS) on Aqua, which both take daytime measurements at ~13:30 local as part of NASA’s A-train constellation.
From OMI, we analyze tropospheric column NO2 (screened for cloud fractions below 30%). NO2 is a major component of air pollution and has been linked to health problems in humans.
From MODIS, we analyze aerosol optical depth (AOD) and liquid-phase cloud droplet effective radius (re). Aerosols are particles suspended in the atmosphere and are important for both human health and the climate. Particles with aerodynamic diameters below 2.5 µm (PM2.5) are known to have severe health effects, with some estimates of annual deaths due to outdoor PM2.5 pollution approaching 10 million people a year. At the same time, aerosols can change Earth’s energy balance by absorbing sunlight or reflecting it back to space. Aerosols can also indirectly affect the climate by changing cloud properties. When more aerosol particles are available, liquid clouds can form with a greater number of cloud droplets (for which aerosol particles act as “seeds”). If the total amount of water in the cloud doesn’t change, this leads to the droplets being smaller on average. This effect makes liquid clouds more reflective, which has a cooling effect.
To see if the COVID-19 shutdown in China led to pollution changes that are out of the ordinary, we fit an ordinary least squares linear regression model for each environmental variable using trends before and after a major clean air policy went into effect, a “holiday effect” to account for pollution changes associated with the Chinese Lunar New Year, and an idealized seasonal cycle. The model is fit independently at every 0.25 x 0.25 degree grid box for the natural logarithm of NO2 and at every 1 x 1 degree grid box for AOD and re. Data from January 2005 to December 2019 are used to train the model and then values for 2020 are predicted.
Pollution changes during the February 2020 shutdown
We find a very large and statistically significant decrease in NO2 pollution during February 2020 compared to what would otherwise have been expected (Figure 2, top row). Gray stippling in Figure 2 indicates that absolute differences do not exceed two root-mean-square (RMS) errors. We do not, however, see any similarly consistent results for the aerosol or cloud properties (Figure 2, middle and bottom rows).

To look at the differences between the observed and estimated values in greater historical perspective, we average the observed and estimated ln(NO2) and AOD over eastern China and re values over the East China Sea (boxes in the rightmost row of Figure 2). Results are displayed in Figure 3, with the RMS error in this case calculated using the differences between the spatially-averaged observed and expected values from January 2005 to December 2019. Like the PMI indices, ln(NO2) shows a pronounced and unprecedented decline in February 2020 followed by a rapid recovery. In contrast, AOD and re values during 2020 are not perceptibly distinct from the 2005-2019 record.

Factors affecting the pollution changes: Emissions
One explanation for the different NO2 and aerosol responses is that economic sectors which disproportionately emit one or the other pollutant may have been impacted differently by the shutdown. Figure 4 shows changes in passenger transportation, energy generation, and iron and steel production from 2005-2020. (Economic data is compiled from the National Bureau of Statistics of China.) Passenger transportation, in particular, was devastated by the shutdown. In contrast, total January-February power generation was down ~10% (similar to 2008-2009), implying a decrease of ~20% in February alone. Heavy industries like steel production (slightly up) were comparatively unaffected, with the remainder of the economy somewhere in between.

Anthropogenic emissions (in units of ng/m2/s) of NOx (NOx = NO + NO2), PM2.5, and SO2 (a precursor for sulfate aerosol, which is particularly good at seeding cloud droplets) for the year 2015 from the Emissions Database for Global Atmospheric Research (EDGAR) are combined to create aggregate “transportation” and “industry and power” sectors, with the remainder lumped into an “other” category primarily consisting of agriculture and waste management. Figure 5 shows maps of the contributions of the three pollutants by economic sector. Transportation is a major source of NOx pollution, comparable to the industry and power sectors, whereas the industry and power sectors dominate emissions of PM2.5 and SO2. Summed over the region highlighted in Figure 5, the transportation sector accounts for 26.2% of all NOx emissions but only 4.7% of PM2.5 and 3.6% of SO2 emissions, while the industry and power sectors account for 72.3% of NOx, 92.8% of PM2.5, and 95.1% of SO2 emissions.

Factors affecting the pollution changes: Meteorology
Of course, emissions changes may not have been the only difference between February 2020 and previous years. In particular, we know that meteorology can have a major effect on pollution concentrations and the occurence of severe haze events. Figure 6 shows 2-m temperature (T) and specific humidity (qv) and 10-m zonal and meridional winds (vectors; longest ~10 m/s) from the Modern‐Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). February 2020 was anomalously warm and humid (white to dark gray contours in the bottom row indicate anomalies exceeding -2, -1, 1, and 2 standard deviations). Such conditions contribute to the chemical loss of NO2 but could enhance secondary aerosol formation. Le et al. (2020) and Wang et al. (2020) argue such an effect was responsible for the haze events that occured in Beijing despite the lockdown. This effect would tend to amplify the decrease in NO2 but blunt any decreases in aerosol from emissions changes alone.

Factors affecting the pollution changes: Chemistry
As a further complication, meteorological anomalies, emissions changes, and their interactions influenced atmospheric chemistry and therefore pollution concentrations in February 2020.
During the winter, the atmospheric lifetime of NOx (~1 day) over eastern China decreases with decreasing emissions as higher ozone concentrations allow for more loss via reaction with hydrogen oxide radicals (HOx) during the day and via hydrolysis of N2O5 (an important NOx reservoir) within aerosols at night. We may therefore expect decreases in NO2 concentrations to exceed reductions in NOx emissions.
Shi & Brasseur (2020) and Huang et al. (2020) reported increasing ozone levels as NOx emissions fell during the shutdown. The increase in ozone increases OH concentrations and thus the atmospheric oxidizing capacity, which could further reduce NO2 but facilitate secondary aerosol formation. This in combination with the relatively warm and wet February 2020 meteorological conditions offers a compelling explanation for the apparent increase in aerosol surrounding Beijing, although the effect appears to be weaker in other regions, perhaps due to differences in background conditions.
Our results are consistent with either a negligible aerosol change or a moderate emissions-driven decrease that was compensated by increased secondary production.
Summary & Conclusions
Despite unprecedented declines in economic activity and NO2 concentrations during the February 2020 COVID-19 shutdown in China, we find no detectable perturbation in aerosol and related cloud properties. The severe curtailment of passenger transportation (a disproportionate NOx source) but comparatively muted changes in power generation and heavy industry (disproportionate PM2.5 and SO2 sources), along with meteorology and complex chemical interactions, help explain this discrepancy.
Further study of the environmental consequences of COVID-19 is warranted, not least because potential links between long-term and short-term air quality and vulnerability to the disease remain unresolved. There is some evidence that short-term exposure to air pollution increased the case fatality rate of the 2002-2003 Severe Acute Respiratory Syndrome (SARS) outbreak in several Chinese cities, which raises the possibility of feedbacks between containment measures that happen to reduce pollution and population-level resilience. Additionally, dramatically reduced transportation sector emissions without similar changes in other sectors could represent a plausible future emissions mix if widespread electrification of transportation is adopted but other sectors do not adopt similar pollution mitigation measures.
References
Diamond, M., & Wood, R. (in revision), Limited Regional Aerosol and Cloud Microphysical Changes Despite Unprecedented Decline in Nitrogen Oxide Pollution During the February 2020 COVID-19 Shutdown in China. Geophysical Research Letters. Pre-print available at: https://www.essoar.org/doi/10.1002/essoar.10503139.2
Huang, X., Ding, A., Gao, J., Zheng, B., Zhou, D., Qi, X., et al. (2020). Enhanced secondary pollution offset reduction of primary emissions during COVID-19 lockdown in China. National Science Review. https://doi.org/10.1093/nsr/nwaa137
Le, T., Wang, Y., Liu, L., Yang, J., Yung, Y. L., Li, G., & Seinfeld, J. H. (2020). Unexpected air pollution with marked emission reductions during the COVID-19 outbreak in China. Science, eabb7431.
Shi, X., & Brasseur, G. P. (2020). The Response in Air Quality to the Reduction of Chinese Economic Activities during the COVID-19 Outbreak. Geophysical Research Letters, 47, e2020GL088070.
Wang, P., Chen, K., Zhu, S., Wang, P., & Zhang, H. (2020). Severe air pollution events not avoided by reduced anthropogenic activities during COVID-19 outbreak. Resources, Conservation, & Recycling, 158, 104814.




