Analysis of spatio-temporal distribution characteristics and socioeconomic drivers of urban air quality in China

Yazhu Wang; Xuejun Duan; Tao Liang; Lei Wang; Lingqing Wang

doi:10.1016/j.chemosphere.2021.132799

Analysis of spatio-temporal distribution characteristics and socioeconomic drivers of urban air quality in China

Chemosphere. 2022 Mar;291(Pt 2):132799. doi: 10.1016/j.chemosphere.2021.132799. Epub 2021 Nov 10.

Authors

Yazhu Wang¹, Xuejun Duan², Tao Liang³, Lei Wang¹, Lingqing Wang⁴

Affiliations

¹ Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China.
² Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China. Electronic address: xjduan@niglas.ac.cn.
³ Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
⁴ Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. Electronic address: wanglq@igsnrr.ac.cn.

PMID: 34774610
DOI: 10.1016/j.chemosphere.2021.132799

Abstract

Having high spatio-temporal resolution data of pollutants is critical to understand environmental pollution patterns and their mechanisms. Our research employs the hourly average concentration data on the air quality index (AQI) and its six component pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃) in 336 Chinese cities from 2014 to 2019. We analyze annual, seasonal, monthly, hourly, and spatial variations of different air pollutants and their socioeconomic factors. The results are as follows. (1) Air pollutants' concentration in Chinese cities decreased year by year during 2014-2019. Among the primary pollutants, PM_2.5 dominated pollution days, accounting for 38.46%, followed by PM₁₀. Monthly concentration curves of AQI, PM_2.5, NO₂, SO₂, and CO showed a U-shaped trend from January to December, while that of O₃ presented an inverted U-shaped unimodal pattern. Regarding daily variation, urban air quality tended to be worse around sunrise compared with sunset. (2) Chinese cities' air quality decreased from north to south and from inland to coastal areas. Recently, air quality has improved, and polluted areas have shrunk. The six pollutant types showed different spatial agglomeration characteristics. (3) Industrial pollution emissions were the main source of urban air pollutants. Energy-intensive industries, dominated by coal combustion, had the greatest impact on SO₂ concentration. A "pollution shelter" was established in China because foreign investment introduced more pollution-intensive industries. Thus, China has crossed the Kuznets U-curve inflection point. In addition, population agglomeration contributed the most to PM_2.5 concentration, increasing the PM_2.5 exposure risk and causing disease, and vehicle exhaust aggravated the pollution of NO₂ and CO. The higher China's per capita gross domestic product, the more significant the effect of economic development is on reducing pollutant concentration.

Keywords: Air quality; China; Socioeconomic; Spatio-temporal distribution; Urban.

MeSH terms

Air Pollutants* / analysis
Air Pollution* / analysis
China
Cities
Environmental Monitoring
Particulate Matter / analysis
Socioeconomic Factors

Substances

Air Pollutants
Particulate Matter