A Characteristic Analysis of Various Air Pollutants and Their Correlation with O 3 in the Jiangsu, Shandong, Henan, and Anhui Provinces of China

Tianzhen Ju (), Bingyu Pan, Bingnan Li, Jiwei Wang, Shuya Liu, Shuai Peng and Meng Li
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Tianzhen Ju: College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China
Bingyu Pan: College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China
Bingnan Li: Faculty of Atmospheric Remote Sensing, Shaanxi Normal University, Xi’an 710062, China
Jiwei Wang: College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China
Shuya Liu: College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China
Shuai Peng: College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China
Meng Li: College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China

Sustainability, 2022, vol. 14, issue 21, 1-16

Abstract: Using a series of characteristic analyses of HCHO, SO 2 , NO 2 , O 3 , and absorptive aerosols (ultraviolet aerosol index—UVAI) in the atmosphere of the study area from 2011 to 2021, this paper reviews the pollutants present in Jiangsu, Shandong, Henan, and Anhui provinces, which are the key regions for air pollution control in China. Furthermore, the correlation between various air pollutants and O 3 is also examined. The results obtained show the following: (1) Within the research areas, temporal pollutant variations can be observed from 2011 to 2021. NO 2 and HCHO only modestly decrease, SO 2 sharply declines, while UVAI remains stable. During the study period, HCHO and O 3 first increase and subsequently decline, whereas the other three pollutants exhibit the opposite behavior. (2) Among the examined pollutants, SO 2 is the most unstable. (3) Our research discovered that the atmospheric transport paths at high-value points significantly vary between seasons using the public backward trajectory model. (4) Through the correlation analysis we performed, this research reveals the different degrees of spatial correlations between O 3 and other pollutants. (5) Using the FNR index method, the sensitivity of O 3 to its precursors (NOx and VOCs) is investigated. Based on the results, we provide some suggestions concerning the primary control pollutants and relative control strategies in different seasons and regions.

Keywords: OMI; spatiotemporal distribution; backward trajectory; O 3 sensitivity (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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