Exploring the driving factors of haze events in Beijing during Chinese New Year holidays in 2020 and 2021 under the influence of COVID-19 pandemic.

Unexpected outbreak of the 2019 novel coronavirus (COVID-19) has profoundly altered the way of human life and production activity, which posed visible impacts on PM2.5 and its chemical species. The abruptly emergency reduction in human activities provided an opportunity to explore the synergetic impacts of multi-factors on shaping PM2.5 pollution. Here, we conducted two comprehensive observation measurements of PM2.5 and its chemical species from 1 January to 16 February in Beijing 2020 and the same lunar date in 2021, to investigate temporal variations and reveal the driving factors of haze before and after Chinese New Year (CNY). Results show that mean PM2.5 concentrations during the whole observation were 63.83 and 66.86 µg/m3 in 2020 and 2021, respectively. Higher secondary inorganic species were observed after CNY, and K+, Cl- showed three prominent peaks which associated closely with fireworks burnings from suburb Beijing and surroundings, verifying that they could be used as two representative tracers of fireworks. Further, we explored the impacts of meteorological conditions, regional transportation as well as chemical reactions on PM2.5. We found that unfavorable meteorological conditions accounted for 11.0 % and 16.9 % of PM2.5 during CNY holidays in 2020 and 2021, respectively. Regional transport from southwest and southeast (south) played an important role on PM2.5 during the two observation periods. Higher ratio of NO3-/SO42- were observed under high OX and low RH conditions, suggesting the major pathway of NO3- and SO42- formation could be photochemical process and aqueous-phase reaction. Additionally, nocturnal chemistry facilitated the formation of secondary components of both inorganic and organic. This study promotes understandings of PM2.5 pollution in winter under the influence of COVID-19 pandemic and provides a well reference for haze and PM2.5 control in future.

Variations and Sources of Organic Aerosol in Winter Beijing under Markedly Reduced Anthropogenic Activities During COVID-2019.

The COVID-19 outbreak provides a "controlled experiment" to investigate the response of aerosol pollution to the reduction of anthropogenic activities. Here we explore the chemical characteristics, variations, and emission sources of organic aerosol (OA) based on the observation of air pollutants and combination of aerosol mass spectrometer (AMS) and positive matrix factorization (PMF) analysis in Beijing in early 2020. By eliminating the impacts of atmospheric boundary layer and the Spring Festival, we found that the lockdown effectively reduced cooking-related OA (COA) but influenced fossil fuel combustion OA (FFOA) very little. In contrast, both secondary OA (SOA) and O3 formation was enhanced significantly after lockdown: less-oxidized oxygenated OA (LO-OOA, 37% in OA) was probably an aged product from fossil fuel and biomass burning emission with aqueous chemistry being an important formation pathway, while more-oxidized oxygenated OA (MO-OOA, 41% in OA) was affected by regional transport of air pollutants and related with both aqueous and photochemical processes. Combining FFOA and LO-OOA, more than 50% of OA pollution was attributed to combustion activities during the whole observation period. Our findings highlight that fossil fuel/biomass combustion are still the largest sources of OA pollution, and only controlling traffic and cooking emissions cannot efficiently eliminate the heavy air pollution in winter Beijing.

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.

The new CORSIA baseline has limited motivation to promote the green recovery of global aviation.

The Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) is the first programme to tackle carbon dioxide (CO2) emissions from a single industry at the global level, to realize the carbon-neutral growth of international flights from 2020 onwards. However, the COVID-19 pandemic has caused a drastic decline in the global aviation industry. The International Civil Aviation Organization (ICAO) has adjusted the CORSIA by removing 2020 emissions from the baseline, which now will only be based on 2019 emissions. We estimate that the total carbon dioxide (CO2) emissions from global international flights decreased by 70 % from February to July 2020 compared to those in 2019. Our analysis suggests that the annual CO2 emissions from international flights during the pilot stage of CORSIA (2021-2023) will be far below the revised baseline even if the global aviation industry could embrace an optimistic recovery. The major airline companies will have very limited motivations due to the CORSIA scheme to implement mitigation actions proactively. Therefore, more progressive actions are needed to align the industry recovery of global aviation and climate change mitigation during the post-COVID-19 period.

[Transmission of Coronavirus via Aerosols and Influence of Environmental Conditions on Its Transmission].

The COVID-19 pandemic has endangered human health and production since 2019. As an emerging disease caused by SARS-CoV-2, its potential transmissibility via aerosols has caused heated debate. This work summarizes the current research findings on virus aerosol generation, aerodynamic properties, and environmental influencing factors on their survivability in order to elucidate coronavirus transmission via aerosols. The occurrence and distinction of SARS-CoV-2, SARS-CoV-1, and MERS-CoV in real atmospheric environments are summarized. The deficiencies of existing research and directions for necessary future research on confirming the airborne transmission mechanism of coronavirus as well as the need for multidisciplinary research are discussed.

From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model.

The large fluctuations in traffic during the COVID-19 pandemic provide an unparalleled opportunity to assess vehicle emission control efficacy. Here we develop a random-forest regression model, based on the large volume of real-time observational data during COVID-19, to predict surface-level NO2, O3, and fine particle concentration in the Los Angeles megacity. Our model exhibits high fidelity in reproducing pollutant concentrations in the Los Angeles Basin and identifies major factors controlling each species. During the strictest lockdown period, traffic reduction led to decreases in NO2 and particulate matter with aerodynamic diameters <2.5 µm by -30.1% and -17.5%, respectively, but a 5.7% increase in O3 Heavy-duty truck emissions contribute primarily to these variations. Future traffic-emission controls are estimated to impose similar effects as observed during the COVID-19 lockdown, but with smaller magnitude. Vehicular electrification will achieve further alleviation of NO2 levels.

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.

Source-Receptor Relationship Revealed by the Halted Traffic and Aggravated Haze in Beijing during the COVID-19 Lockdown.

The COVID-19 outbreak greatly limited human activities and reduced primary emissions particularly from urban on-road vehicles but coincided with Beijing experiencing "pandemic haze," raising the public concerns about the effectiveness of imposed traffic policies to improve the air quality. This paper explores the relationship between local vehicle emissions and the winter haze in Beijing before and during the COVID-19 lockdown based on an integrated analysis framework, which combines a real-time on-road emission inventory, in situ air quality observations, and a localized numerical modeling system. We found that traffic emissions decreased substantially during the COVID-19 pandemic, but its imbalanced emission abatement of NOx (76%, 125.3 Mg/day) and volatile organic compounds (VOCs, 53%, 52.9 Mg/day) led to a significant rise of atmospheric oxidants in urban areas, resulting in a modest increase in secondary aerosols due to inadequate precursors, which still offset reduced primary emissions. Moreover, the enhanced oxidizing capacity in the surrounding regions greatly increased the secondary particles with relatively abundant precursors, which was transported into Beijing and mainly responsible for the aggravated haze pollution. We recommend that mitigation policies should focus on accelerating VOC emission reduction and synchronously controlling regional sources to release the benefits of local traffic emission control.

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.