Unbalanced emission reductions of different species and sectors in China during COVID-19 lockdown derived by multi-species surface observation assimilation

The unprecedented lockdown of human activities during the COVID-19 pandemic has significantly influenced social life in China. However, understanding the impact of this unique event on the emissions of different species is still insufficient, prohibiting the proper assessment of the environmental impacts of COVID-19 restrictions. Here we developed a multi-air-pollutant inversion system to simultaneously estimate the emissions of NOx, SO2, CO, PM2.5 and PM10 in China during COVID-19 restrictions with high temporal (daily) and horizontal (15 km) resolutions. Subsequently, contributions of emission changes versus meteorological variations during the COVID-19 lockdown were separated and quantified. The results demonstrated that the inversion system effectively reproduced the actual emission variations in multi-air pollutants in China during different periods of COVID-19 lockdown, which indicate that the lockdown is largely a nationwide road traffic control measure with NOx emissions decreasing substantially by ∼40 %. However, emissions of other air pollutants were found to only decrease by∼10% because power generation and heavy industrial processes were not halted during lockdown, and residential activities may actually have increased due to the stay-at-home orders. Consequently, although obvious reductions of PM2.5 concentrations occurred over the North China Plain (NCP) during the lockdown period, the emission change only accounted for 8.6 % of PM2.5 reductions and even led to substantial increases in O3. The meteorological variation instead dominated the changes in PM2.5 concentrations over the NCP, which contributed 90 % of the PM2.5 reductions over most parts of the NCP region. Meanwhile, our results suggest that the local stagnant meteorological conditions, together with inefficient reductions of PM2.5 emissions, were the main drivers of the unexpected PM2.5 pollution in Beijing during the lockdown period. These results highlighted that traffic control as a separate pollution control measure has limited effects on the coordinated control of O3 and PM2.5 concentrations under current complex air pollution conditions in China. More comprehensive and balanced regulations for multiple precursors from different sectors are required to address O3 and PM2.5 pollution in China.

Changes in primary and secondary aerosols during a controlled Chinese New Year.

Large reductions in anthropogenic emissions during the Chinese New Year (CNY) holiday in Beijing have been well reported. However, the changes during the CNY of 2021 are different because most people stayed in Beijing to control the spread of coronavirus disease (COVID-19). Here a high-resolution aerosol mass spectrometer (HR-AMS) was deployed for characterization of the changes in size-resolved aerosol composition and sources during the CNY. We found that the reductions in traffic-related NOx and fossil fuel-related organic aerosol (OA), and cooking OA (1.3-12.7%) during the CNY of 2021 were much smaller than those in previous CNY holidays of 2013, 2015, and 2020. In contrast, the mass concentrations of secondary aerosol species except nitrate showed ubiquitous increases (17.6-30.4%) during the CNY of 2021 mainly due to a 4-day severe haze episode. OA composition also changed substantially during the CNY of 2021. In particular, we observed a large increase by nearly a factor of 2 in oxidized primary OA likely from biomass burning, and a decrease of 50.1% in aqueous-phase secondary OA. A further analysis of the severe haze episode during the CNY illustrated a rapid transition of secondary formation from photochemical to aqueous-phase processing followed by a scavenging process, leading to significant changes in aerosol composition, size distributions, and oxidation degree of OA. A parameterization relationship between oxygen-to-carbon (O/C) and f44 (fraction of m/z 44 in OA) from a collocated capture vaporizer aerosol chemical speciation monitor (CV-ACSM) was developed, which has a significant implication for characterization of OA evolution and the impacts on hygroscopicity due to the rapidly increased deployments of CV-ACSM worldwide.

Machine learning elucidates the impact of short-term emission changes on air pollution in Beijing

The Chinese Spring Festival (CSF) is the most solemn traditional festival in China, and the substantial changes in anthropogenic activities in megacities provide a unique natural experiment to assess the influence of short-term emission changes on air quality. Here we applied a machine learning based random forest algorithm to six-year aerosol composition measurements in urban Beijing during the CSFs of 2012–2020 to quantify the relative contributions of meteorology and emission changes to air quality. Our results demonstrate large variabilities of air pollutants during the CSF due to the meteorological changes and holiday effect. By removing the meteorological effect, we found that the reduced emissions during CSF caused an average decrease of 5.1% for non-refractory PM2.5 with chloride and primary organic aerosol being the largest (8.8–18.7%) while the changes in secondary species were small. The COVID-19 lockdown during 2020 led to additional reductions of primary species by 16.3–36.8%, yet increases in nitrate and secondary organic aerosol due to enhanced secondary production. Our study has a significant implication that reducing local traffic and cooking emissions is far from enough for mitigating air pollution in winter in megacities due to the nonlinear effect of secondary production and regional transport. A synergetic control of multiple precursors, e.g., NOx and ammonia, is of great importance to reduce secondary aerosol and improve air quality.

Nitrate and secondary organic aerosol dominated particle light extinction in Beijing due to clean air action

Air quality in China has been continuously improved since clean air action in 2013, yet the visibility was not improved simultaneously. Here we employed a new method by integrating highly-time resolved aerosol compositions with particle light extinction (bext) into positive matrix factorization to quantify the different contributors to visibility degradation during four seasons in Beijing. Our results show that ammonium nitrate-related factor contributed dominantly to bext during all seasons (31–48%) and played more significant roles during low-visibility periods. Secondary organic aerosol (SOA) was an important contributor of bext (27–35%) in autumn and spring while primary OA related sources were more important in winter (37%). An increase in aerosol mass extinction efficiency and similarly important roles of ammonium nitrate and SOA in visibility degradation were also observed during COVID-19 lockdown. Our results point towards a future challenge in improving visibility in China due to the increased contributions of nitrate and SOA in PM2.5. Future emission controls with a priority to decrease nitrate would benefit both air quality and visibility.

Sources of PM2.5 and its responses to emission reduction strategies in the Central Plains Economic Region in China: Implications for the impacts of COVID-19.

The Central Plains Economic Region (CPER) located along the transport path to the Beijing-Tianjin-Hebei area has experienced severe PM2.5 pollution in recent years. However, few modeling studies have been performed on the sources of PM2.5, especially the impacts of emission reduction strategies. In this study, the Nested Air Quality Prediction Model System (NAQPMS) with an online tracer-tagging module was adopted to investigate source sectors of PM2.5 and a series of sensitivity tests were conducted to investigate the impacts of different sector-based mitigation strategies on PM2.5 pollution. The response surfaces of pollutants to sector-based emission changes were built. The results showed that resident-related sector (resident and agriculture), fugitive dust, traffic and industry emissions were the main sources of PM2.5 in Zhengzhou, contributing 49%, 19%, 15% and 13%, respectively. Response surfaces of pollutants to sector-based emission changes in Henan revealed that the combined reduction of resident-related sector and industry emissions efficiently decreased PM2.5 in Zhengzhou. However, reduced emissions in only the Henan region barely satisfied the national air quality standard of 75 µg/m3, whereas a 50%-60% reduction in resident-related sector and industry emissions over the whole region could reach this goal. On severely polluted days, even a 60% reduction in these two sectors over the whole region was insufficient to satisfy the standard of 75 µg/m3. Moreover, a reduction in traffic emissions resulted in an increase in the O3 concentration. The results of the response surface method showed that PM2.5 in Zhengzhou decreased by 19% in response to the COVID-19 lockdown, which approached the observed reduction of 21%, indicating that the response surface method could be employed to study the impacts of the COVID-19 lockdown on air pollution. This study provides a scientific reference for the formulation of pollution mitigation strategies in the CPER.

Numerical study of COVID-19 spatial-temporal spreading in London.

A recent study reported that an aerosolized virus (COVID-19) can survive in the air for a few hours. It is highly possible that people get infected with the disease by breathing and contact with items contaminated by the aerosolized virus. However, the aerosolized virus transmission and trajectories in various meteorological environments remain unclear. This paper has investigated the movement of aerosolized viruses from a high concentration source across a dense urban area. The case study looks at the highly air polluted areas of London: University College Hospital (UCH) and King's Cross and St Pancras International Station (KCSPI). We explored the spread and decay of COVID-19 released from the hospital and railway stations with the prescribed meteorological conditions. The study has three key findings: the primary result is that the concentration of viruses decreases rapidly by a factor of 2-3 near the sources although the virus may travel from meters up to hundreds of meters from the source location for certain meteorological conditions. The secondary finding shows viruses released into the atmosphere from entry and exit points at KCSPI remain trapped within a small radial distance of < 50 m. This strengthens the case for the use of face coverings to reduce the infection rate. The final finding shows that there are different levels of risk at various door locations for UCH; depending on which door is used there can be a higher concentration of COVID-19. Although our results are based on London, since the fundamental knowledge processes are the same, our study can be further extended to other locations (especially the highly air polluted areas) in the world.

Impacts of COVID-19 lockdown, Spring Festival and meteorology on the NO2 variations in early 2020 over China based on in-situ observations, satellite retrievals and model simulations.

The lockdown measures due to COVID-19 affected the industry, transportation and other human activities within China in early 2020, and subsequently the emissions of air pollutants. The decrease of atmospheric NO2 due to the COVID-19 lockdown and other factors were quantitively analyzed based on the surface concentrations by in-situ observations, the tropospheric vertical column densities (VCDs) by different satellite retrievals including OMI and TROPOMI, and the model simulations by GEOS-Chem. The results indicated that due to the COVID-19 lockdown, the surface NO2 concentrations decreased by 42% ± 8% and 26% ± 9% over China in February and March 2020, respectively. The tropospheric NO2 VCDs based on both OMI and high quality (quality assurance value (QA) ≥ 0.75) TROPOMI showed similar results as the surface NO2 concentrations. The daily variations of atmospheric NO2 during the first quarter (Q1) of 2020 were not only affected by the COVID-19 lockdown, but also by the Spring Festival (SF) holiday (January 24-30, 2020) as well as the meteorology changes due to seasonal transition. The SF holiday effect resulted in a NO2 reduction from 8 days before SF to 21 days after it (i.e. January 17 - February 15), with a maximum of 37%. From the 6 days after SF (January 31) to the end of March, the COVID-19 lockdown played an important role in the NO2 reduction, with a maximum of 51%. The meteorology changes due to seasonal transition resulted in a nearly linear decreasing trend of 25% and 40% reduction over the 90 days for the NO2 concentrations and VCDs, respectively. Comparisons between different datasets indicated that medium quality (QA ≥ 0.5) TROPOMI retrievals might suffer large biases in some periods, and thus attention must be paid when they are used for analyses, data assimilations and emission inversions.

A chemical cocktail during the COVID-19 outbreak in Beijing, China: Insights from six-year aerosol particle composition measurements during the Chinese New Year holiday.

The rapidly spread coronavirus disease (COVID-19) has limited people's outdoor activities and hence caused substantial reductions in anthropogenic emissions around the world. However, the air quality in some megacities has not been improved as expected due to the complex responses of aerosol chemistry to the changes in precursors and meteorology. Here we demonstrate the responses of primary and secondary aerosol species to the changes in anthropogenic emissions during the COVID-19 outbreak in Beijing, China along with the Chinese New Year (CNY) holiday effects on air pollution by using six-year aerosol particle composition measurements. Our results showed large reductions in primary aerosol species associated with traffic, cooking and coal combustion emissions by 30-50% on average during the CNY, while the decreases in secondary aerosol species were much small (5-12%). These results point towards a future challenge in mitigating secondary air pollution because the reduced gaseous precursors may not suppress secondary aerosol formation efficiently under stagnant meteorological conditions. By analyzing the long-term measurements from 2012 to 2020, we found considerable increases in the ratios of nitrate to sulfate, secondary to primary OA, and sulfur and nitrogen oxidation capacity despite the overall decreasing trends in mass concentrations of most aerosol species, suggesting that the decreases in anthropogenic emissions have facilitated secondary formation processes during the last decade. Therefore, a better understanding of the mechanisms driving the chemical responses of secondary aerosol to the changes in anthropogenic emissions under complex meteorological environment is essential for future mitigation of air pollution in China.