Exploring Spatiotemporal Dynamics of PM 2.5 Emission Based on Nighttime Light in China from 2012 to 2018

Deguang Li, Zhicheng Ding (), Jianghuan Liu, Qiurui He and Hamad Naeem
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Deguang Li: School of Information Technology, Luoyang Normal University, Luoyang 471934, China
Zhicheng Ding: College of Mechanical and Electrical Engineering, Zhengzhou University of Industrial Technology, Zhengzhou 451150, China
Jianghuan Liu: School of Information Technology, Luoyang Normal University, Luoyang 471934, China
Qiurui He: School of Information Technology, Luoyang Normal University, Luoyang 471934, China
Hamad Naeem: School of Computer Science and Technology, Zhoukou Normal University, Zhoukou 466001, China

Sustainability, 2022, vol. 14, issue 21, 1-19

Abstract: China’s coal-based energy structure and rapid economic expansion have resulted in significant air pollution, notably PM 2.5 pollution, which has harmed the environment, citizens’ health, and sustainable and cleaner development of China in recent years. Traditional ground monitoring stations have certain drawbacks, such as spatial distribution that is unequal. To better understand the spatial and temporal dynamic characteristics of PM 2.5 emissions, this article studied the temporal and spatial changes of night light data along PM 2.5 emission at the national, regional, and provincial scales. The Chinese Academy of Science’s Earth Luminous Data Set, Dalhousie University’s PM 2.5 emission dataset, and the basic national geographical dataset from National Geographic were used for analysis. We found a significant positive correlation between nightlight data and PM 2.5 emission data, which resulted in an accurate fitting of PM 2.5 emissions using the proposed linear regression model, and the results showed that the spatiotemporal dynamics of PM 2.5 emission and night light were different in various regions. In terms of spatial distribution, PM 2.5 emission over the intermediate level (44% of China’s total area) was concentrated in the Sichuan Basin, North China Plain, and Northwest China, whereas PM 2.5 emission below the middle level (55% of China’s total area) was concentrated in northeast China, Xizang, and West Sichuan. In terms of geographical and temporal dynamics, more than 65% of China’s total, area mainly located in the south of the Hu line, showed negative growth from 2012 to 2018, especially the North China Plain, the Sichuan Basin, and the Yangtze River’s Plains showed a lot of negative growth. The evolution of PM 2.5 emission in China from 2012 to 2018 was visually exhibited by examining spatiotemporal dynamics and the interaction linkages between PM 2.5 emission and nighttime light, which was useful for China’s air pollution control and sustainable development.

Keywords: PM 2.5 emission; Flint data; multiscale analysis; China (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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