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

Abstract

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, PM 2.5 decreased 31.7%, which was found by comparing the observation data in Wuhan during the epidemic from 8 th Feb. to 8 th 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) PM 2.5 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 PM 2.5 . (2) O 3 increased mainly due to the slowing down of chemical consumption processes, which made the concentration change of O 3 pollution higher at about 4 P.M.∼7 P.M. of the day, while increasing the concentration of O 3 at night during the COVID-19 lockdown in Wuhan. The higher O 3 concentration in the North-East of the main urban area also contributed to the increasing of O 3 with unfavorable wind direction.

Quantifying Air Pollutant Variations during COVID-19 Lockdown in a Capital City in Northwest China

“…Among all the national controlled air pollutants, NO 2 decreased the most during the COVID-19 lockdown to 52% in a statistically significant way. Travel restrictions during the lockdown caused the most significant reduction in NO 2 , consistent with previous studies [39,40,[61][62][63].…”

The effects of air pollution, meteorological parameters, and climate change on COVID-19 comorbidity and health disparities: A systematic review

“…A wide array of meteorological factors including particulate matter, air pollution, and heat were identified as positively associated with the spread of COVID-19. Studies identified that reported on the relationship between meteorological parameters and COVID-19 spread in different regions of the world [ [21] , [22] , [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] , [46] , [47] , [48] , [49] , [50] , [51] , [52] , [53] , [54] , [55] , [56] , [57] , [58] , [59] , [60] , [61] , [62] , [63] , [64] , [65] , [66] , [67] , [68] , [69] , [70] , [71] , [72] , [73] , [74] , [75] , [76] , [77] , [78] , [79] ] are shown in Table 1 . The interplay among meteorological factors (air pollution, meteorological parameters, and climate change) ...…”

“…The Community Multiscale Air Quality modeling system of USEPA was used to simulate the spatial and temporal variation of air pollutants during lockdown period. PM 2.5 concentration showed a significant decrease during lockdown, while O 3 levels were found to increase which was attributed to wind direction [ 46 ] Fourteen (14) provinces in China PM 2.5 , PM 10 , SO 2 , NO 2 , and O 3 concentrations and COVID-19 cases Pollutant data were obtained from the China Air Quality Online Monitoring and Analysis Platform. The number of COVID cases, discharges, and deaths during the epidemic period were obtained from the Urban Health Commission.…”

Four-dimensional variational assimilation for SO2 emission and its application around the COVID-19 lockdown in the spring 2020 over China

“…Subsequently, all provinces in China successively implemented a national emergency to respond to major public health emergencies. The pollutant emissions decreased because human activities reduced during the lockdown (Filonchyk et al, 2020;Forster et al, 2020;Ghahremanloo et al, 2021;Keller et al, 2021;Li et al, 2020Li et al, , 2021Miyazaki et al, 2020;Huang et al, 2021a;Zhan and Xie, 2022;. For example, Huang et al (2021b) estimated NO x emissions over China during this period, and found a decreased trend owing to human activity reduction.…”