Study on the variation of air pollutant concentration and its formation mechanism during the COVID-19 period in Wuhan.

To prevent the spread of COVID-19 (2019 novel coronavirus), from January 23 to April 8 in 2020, the highest Class 1 Response was ordered in Wuhan, requiring all residents to stay at home unless absolutely necessary. This action was implemented to cut down all unnecessary human activities, including industry, agriculture and transportation. Reducing these activities to a very low level during these hard times meant that some unprecedented naturally occurring measures of controlling emissions were executed. Ironically, however, after these measures were implemented, ozone levels increased by 43.9%. Also worthy of note, PM2.5 decreased 31.7%, which was found by comparing the observation data in Wuhan during the epidemic from 8th Feb. to 8th Apr. in 2020 with the same periods in 2019. Utilizing CMAQ (The Community Multiscale Air Quality modeling system), this article investigated the reason for these phenomena based on four sets of numerical simulations with different schemes of emission reduction. Comparing the four sets of simulations with observation, it was deduced that the emissions should decrease to approximately 20% from the typical industrial output, and 10% from agriculture and transportation sources, attributed to the COVID-19 lockdown in Wuhan. More importantly, through the CMAQ process analysis, this study quantitatively analyzed differences of the physical and chemical processes that were affected by the COVID-19 lockdown. It then examined the differences of the COVID-19 lockdown impact and determined the physical and chemical processes between when the pollution increased and decreased, determining the most affected period of the day. As a result, this paper found that (1) PM2.5 decreased mainly due to the reduction of emission and the contrary contribution of aerosol processes. The North-East wind was also in favor of the decreasing of PM2.5. (2) O3 increased mainly due to the slowing down of chemical consumption processes, which made the concentration change of O3 pollution higher at about 4 p.m.-7 p.m. of the day, while increasing the concentration of O3 at night during the COVID-19 lockdown in Wuhan. The higher O3 concentration in the North-East of the main urban area also contributed to the increasing of O3 with unfavorable wind direction.

Drivers for the poor air quality conditions in North China Plain during the COVID-19 outbreak.

China's lockdown to control COVID-19 brought significant declines in air pollutant emissions, but haze was still a serious problem in North China Plain (NCP) during late-January to mid-February of 2020. We seek the potential causes for the poor air quality in NCP combining satellite data, ground measurements and model analyses. Efforts to constrain COVID-19 result in a drop-off of primary gaseous pollutants, e.g., -42.4% for surface nitrogen dioxide (NO2) and -38.9% for tropospheric NO2 column, but fine particulate matter (PM25) still remains high and ozone (O3) even increases sharply (+84.1%). Stagnant weather during COVID-19 outbreak, e.g., persistent low wind speed, frequent temperature inversion and wind convergence, is one of the major drivers for the poor air quality in NCP. The surface PM2.5 levels vary between -12.9~+15.1% in NCP driven by the varying climate conditions between the years 2000 and 2020. Besides, the persistent PM2.5 pollution might be maintained by the still intensive industrial and residential emissions (primary PM2.5), and increased atmospheric oxidants (+26.1% for ozone and +29.4% for hydroxyl radical) in response to the NO2 decline (secondary PM2.5). Further understanding the nonlinear response between atmospheric secondary aerosols and NOx emissions is meaningful to cope with the emerging air pollution problems in China.

Changes of air quality and its associated health and economic burden in 31 provincial capital cities in China during COVID-19 pandemic.

With outbreak of the novel coronavirus disease (COVID-19), immediate prevention and control actions were imposed in China. Here, we conducted a timely investigation on the changes of air quality, associated health burden and economic loss during the COVID-19 pandemic (January 1 to May 2, 2020). We found an overall improvement of air quality by analyzing data from 31 provincial cities, due to varying degrees of NO2, PM2.5, PM10 and CO reductions outweighing the significant O3 increase. Such improvement corresponds to a total avoided premature mortality of 9410 (7273-11,144) in the 31 cities by comparing the health burdens between 2019 and 2020. NO2 reduction was the largest contributor (55%) to this health benefit, far exceeding PM2.5 (10.9%) and PM10 (23.9%). O3 instead was the only negative factor among six pollutants. The period with the largest daily avoided deaths was rather not the period with strict lockdown but that during February 25 to March 31, due to largest reduction of NO2 and smallest increase of O3. Southwest, Central and East China were regions with relatively high daily avoided deaths, while for some cities in Northeast China, the air pollution was even worse, therefore could cause more deaths than 2019. Correspondingly, the avoided health economic loss attributable to air quality improvement was 19.4 (15.0-23.0) billion. Its distribution was generally similar to results of health burden, except that due to regional differences in willingness to pay to reduce risks of premature deaths, East China became the region with largest daily avoided economic loss. Our results here quantitatively assess the effects of short-term control measures on changes of air quality as well as its associated health and economic burden, and such information is beneficial to future air pollution control.