Drivers of High Concentrations of Secondary Organic Aerosols in Northern China during the COVID-19 Lockdowns.

During the COVID-19 lockdown in early 2020, observations in Beijing indicate that secondary organic aerosol (SOA) concentrations increased despite substantial emission reduction, but the reasons are not fully explained. Here, we integrate the two-dimensional volatility basis set into a state-of-the-art chemical transport model, which unprecedentedly reproduces organic aerosol (OA) components resolved by the positive matrix factorization based on aerosol mass spectrometer observations. The model shows that, for Beijing, the emission reduction during the lockdown lowered primary organic aerosol (POA)/SOA concentrations by 50%/18%, while deteriorated meteorological conditions increased them by 30%/119%, resulting in a net decrease in the POA concentration and a net increase in the SOA concentration. Emission reduction and meteorological changes both led to an increased OH concentration, which accounts for their distinct effects on POA and SOA. SOA from anthropogenic volatile organic compounds and organics with lower volatility contributed 28 and 62%, respectively, to the net SOA increase. Different from Beijing, the SOA concentration decreased in southern Hebei during the lockdown because of more favorable meteorology. Our findings confirm the effectiveness of organic emission reductions and meanwhile reveal the challenge in controlling SOA pollution that calls for large organic precursor emission reductions to rival the adverse impact of OH increase.

Ambient fine particulate matter and ozone pollution in China: synergy in anthropogenic emissions and atmospheric processes

Since 2013, China has taken a series of actions to relieve serious PM2.5 pollution. As a result, the annual PM2.5 concentration decreased by more than 50% from 2013 to 2021. However, ozone pollution has become more pronounced, especially in the North China Plain. Here, we review the impacts of anthropogenic emissions, meteorology, and atmospheric processes on ambient PM2.5 loading and components and O3 pollution in China. The reported influence of interannual meteorological changes on PM2.5 and O3 pollution during 2013–2019 ranged from 10%–20% and 20%–40%, respectively. During the same period, the anthropogenic emissions of NOx, SO2, primary PM2.5, NMVOC and NH3 are estimated to decrease by 38%, 51%, 35%, 11% and 17%, respectively. Such emission reduction is the main cause for the decrease in PM2.5 concentration across China. However, the imbalanced reductions in various precursors also result in the variation in nitrate gas-particle partitioning and hence an increase in the nitrate fraction in PM2.5. The increase of ozone concentration and the enhancement of atmospheric oxidation capacity can also have substantial impact on the secondary components of PM2.5, which partly explained the growth of organic aerosols during haze events and the COVID-19 shutdown period. The uneven reduction in NOx and NMVOC is suggested to be the most important reason for the rapid O3 increase after 2013. In addition, the decrease in PM2.5 may also have affected O3 formation via radiation effects and heterogeneous reactions. Moreover, climate change is expected to influence both anthropogenic emissions and atmospheric processes. However, the extent and pathways of the PM2.5-O3 interplay and how it will be impacted by the changing emission and atmospheric conditions making the synergetic control of PM2.5 and O3 difficult. Further research on the interaction of PM2.5 and O3 is needed to provide basis for a scientifically-grounded and effective co-control strategy.

Non-negligible contributions to human health from increased household air pollution exposure during the COVID-19 lockdown in China.

BACKGROUND: Ambient and household air pollution are found to lead to premature deaths from all-cause or cause-specific death. The national lockdown measures in China during COVID-19 were found to lead to abrupt changes in ambient surface air quality, but indoor air quality changes were neglected. In this study, we aim to investigate the impacts of lockdown measures on both ambient and household air pollution as well as the short-term health effects of air pollution changes. METHODS: In this study, an up-to-date emission inventory from January to March 2020 in China was developed based on air quality observations in combination with emission-concentration response functions derived from chemical transport modeling. These emission inventories, together with the emissions data from 2017 to 2019, were fed into the state-of-the-art regional chemistry transport model to simulate the air quality in the North China Plain. A hypothetical scenario assuming no lockdown effects in 2020 was also performed to determine the effects of the lockdown on air quality in 2020. A difference-to-difference approach was adopted to isolate the effects on air quality due to meteorological conditions and long-term decreasing emission trends by comparing the PM2.5 changes during lockdown to those before lockdown in 2020 and in previous years (2017-2019). The short-term premature mortality changes from both ambient and household PM2.5 changes were quantified based on two recent epidemiological studies, with uncertainty of urban and rural population migration considerations. FINDINGS: The national lockdown measures during COVID-19 led to a reduction of 5.1 µg m-3 in ambient PM2.5 across the North China Plain (NCP) from January 25th to March 5th compared with the hypothetical simulation with no lockdown measures. However, a difference-to-difference method showed that the daily domain average PM2.5 in the NCP decreased by 9.7 µg m-3 between lockdown periods before lockdown in 2020, while it decreased by 7.9 µg m-3 during the same periods for the previous three-year average from 2017 to 2019, demonstrating that lockdown measures may only have caused a 1.8 µg m-3 decrease in the NCP. We then found that the integrated population-weighted PM2.5, including both ambient and indoor PM2.5 exposure, increased by 5.1 µg m-3 during the lockdown periods compared to the hypothetical scenario, leading to additional premature deaths of 609 (95% CI: 415-775) to 2,860 (95% CI: 1,436-4,273) in the short term, depending on the relative risk chosen from the epidemiological studies. INTERPRETATION: Our study indicates that lockdown measures in China led to abrupt reductions in ambient PM2.5 concentration but also led to significant increases in indoor PM2.5 exposure due to confined indoor activities and increased usages of household fuel for cooking and heating. We estimated that hundreds of premature deaths were added as a combination of decreased ambient PM2.5 and increased household PM2.5. Our findings suggest that the reduction in ambient PM2.5 was negated by increased exposure to household air pollution, resulting in an overall increase in integrated population weighted exposure. Although lockdown measures were instrumental in reducing the exposure to pollution concentration in cities, rural areas bore the brunt, mainly due to the use of dirty solid fuels, increased population density due to the large-scale migration of people from urban to rural areas during the Chinese New Year and long exposure time to HAP due to restrictions in outdoor movement.

Impacts of COVID-19 response actions on air quality in China

An outbreak of the novel coronavirus (COVID-19) was first reported in Wuhan, Hubei Province, China in December 2019. In late January 2020, the Chinese government implemented strict quarantine measures across Hubei Province and other parts of the country to limit the transmission of COVID-19. An effect of these quarantine measures was the reduction in economic activity and associated emissions that contribute to air pollution. In this study, we quantify the spatial extent and magnitude of changes in air pollution concentrations across China by comparing complementary satellite, ground-based, and modeled data from the first two months of 2019 and 2020. We find a 48% reduction in satellite-derived average fine particulate matter (PM2.5) concentrations in eastern China during a three-week period after the Lunar New Year (LNY) in 2020 compared to 2019, which follows significant declines in the pre-LNY period. We also observe a 49% and 11% decline in post-LNY satellite tropospheric column concentrations of nitrogen dioxide (NO2) and sulfur dioxide (SO2). These satellite-based results are in general agreement with data collected from ground monitoring stations across the country, which show a decline in post-LNY PM2.5, NO2, and SO2 concentrations. Our modeling analysis suggests that these observed air quality improvements are driven primarily by the reduction in NO2 emissions, which indicate reductions in transportation and industrial pollution sources during COVID-19, but unfavorable meteorological conditions weaken the role of emissions reduction. Finally, we estimate a reduction by 5%, 14%, and 18% of days in the post-LNY period for 2020 that exceed national PM2.5 air quality targets for the entire country, eastern China, and Hubei Province. As more information becomes available on population characteristics and air pollution exposure patterns, this analysis can be extended to quantify human health related impacts to sudden changes in air pollution in China and other locations around the world.

GCG inhibits SARS-CoV-2 replication by disrupting the liquid phase condensation of its nucleocapsid protein.

Lack of detailed knowledge of SARS-CoV-2 infection has been hampering the development of treatments for coronavirus disease 2019 (COVID-19). Here, we report that RNA triggers the liquid-liquid phase separation (LLPS) of the SARS-CoV-2 nucleocapsid protein, N. By analyzing all 29 proteins of SARS-CoV-2, we find that only N is predicted as an LLPS protein. We further confirm the LLPS of N during SARS-CoV-2 infection. Among the 100,849 genome variants of SARS-CoV-2 in the GISAID database, we identify that ~37% (36,941) of the genomes contain a specific trio-nucleotide polymorphism (GGG-to-AAC) in the coding sequence of N, which leads to the amino acid substitutions, R203K/G204R. Interestingly, NR203K/G204R exhibits a higher propensity to undergo LLPS and a greater effect on IFN inhibition. By screening the chemicals known to interfere with N-RNA binding in other viruses, we find that (-)-gallocatechin gallate (GCG), a polyphenol from green tea, disrupts the LLPS of N and inhibits SARS-CoV-2 replication. Thus, our study reveals that targeting N-RNA condensation with GCG could be a potential treatment for COVID-19.

Quantifying the emission changes and associated air quality impacts during the COVID-19 pandemic on the North China Plain: a response modeling study

Quantification of emission changes is a prerequisite for the assessment of control effectiveness in improving air quality. However, the traditional bottom-up method for characterizing emissions requires detailed investigation of emissions data (e.g., activity and other emission parameters) that usually takes months to perform and limits timely assessments. Here we propose a novel method to address this issue by using a response model that provides real-time estimation of emission changes based on air quality observations in combination with emission-concentration response functions derived from chemical transport modeling. We applied the new method to quantify the emission changes on the North China Plain (NCP) due to the COVID-19 pandemic shutdown, which overlapped the Spring Festival (also known as Chinese New Year) holiday. Results suggest that the anthropogenic emissions of NO2,SO2, volatile organic compound (VOC) and primary PM2.5 on the NCP were reduced by 51 %, 28 %, 67 % and 63 %, respectively, due to the COVID-19 shutdown, indicating longer and stronger shutdown effects in 2020 compared to the previous Spring Festival holiday. The reductions of VOC and primary PM2.5 emissions are generally effective in reducing O3 and PM2.5 concentrations. However, such air quality improvements are largely offset by reductions inNOx emissions. NOx emission reductions lead to increases inO3 and PM2.5 concentrations on the NCP due to the strongly VOC-limited conditions in winter. A strong NH3-rich condition is also suggested from the air quality response to the substantial NOx emission reduction. Well-designed control strategies are recommended based on the air quality response associated with the unexpected emission changes during the COVID-19 period. In addition, our results demonstrate that the new response-based inversion model can well capture emission changes based on variations in ambient concentrations and thereby illustrate the great potential for improving the accuracy and efficiency of bottom-up emission inventory methods.

Four-Month Changes in Air Quality during and after the COVID-19 Lockdown in Six Megacities in China

The pandemic of coronavirus disease 2019 (COVID-19) resulted in a stringent lockdown in China to reduce the infection rate. We adopted a machine learning technique to analyze the air quality impacts of the COVID-19 lockdown from January to April 2020 for six megacities with different lockdown durations. Compared with the scenario without lockdowns, we estimated that the lockdown reduced ambient NO2 concentrations by 36–53% during the most restrictive periods, which involved Level-1 public health emergency response control actions. Several cities lifted the Level-1 control actions during February and March, and the avoided NO2 concentrations subsequently dropped below 10% in late April. Traffic analysis during the same periods in Beijing and Chengdu confirmed that traffic emission changes were a major factor in the substantial NO2 reduction, but they were also associated with increased O3 concentrations. The lockdown also reduced PM2.5 concentrations, although heavy pollution episodes occurred on certain days due to the enhanced formation of secondary aerosols in association with the increased atmospheric oxidizing capacity. We also observed that the changes in air pollution levels decreased as the lockdown was gradually eased in various cities.