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The impact of energy-intensive industries on air quality in China's industrial agglomerations
Zhang, Xiaoping1; Lin, Meihan1,2; Wang, Zhenbo2; Jin, Fengjun1,2
2021-04-01
Source PublicationJOURNAL OF GEOGRAPHICAL SCIENCES
ISSN1009-637X
Volume31Issue:4Pages:584-602
Corresponding AuthorWang, Zhenbo(wangzb@igsnrr.ac.cn)
AbstractUnderstanding the driving forces of regional air pollution and its mechanism has gained much attention in academic research, which can provide scientific policy-making basis for economy-environment sustainability in China. Being an important energy and industrial base, the North China Plain region has been experiencing severe air pollution. Therefore, understanding the relationship between industrialization and air quality in this region is of great importance for air quality improvement. In this study, the average annual concentrations of SO2, NO2 and PM10 in 47 sample cities at and above the prefecture level in the North China Plain region from 2007 to 2016 were used to illustrate the spatiotemporal characteristics of air pollution within this region. Furthermore, panel data model, panel vector autoregression model, and impulse response function were used to explore the correlation and driving mechanism between energy-intensive industries and regional air quality. The results show that: first, overall air quality improved in the study area between 2007 and 2016, with a significant greater fall in concentration of SO2 than that of NO2 and PM10; second, provincial border areas suffered from severe air pollution and showed an apparent spatial agglomeration trend of pollution; and third, the test results from different models all proved that energy-intensive industries such as the chemical, non-metallic mineral production, electric and thermal power production and supply industries, had a significant positive correlation with concentrations of air pollutants, and indicated an obvious short-term impulse response effect. It concludes that upgradation of industrial structure, especially that of energy-intensive industries, plays a very important role in the improvement of regional air quality, which is recommended to be put in top priority for authorities. Therefore, policies as increasing investments in technological innovation in energy-intensive industries, deepening cooperation in environmental governance between different provinces and cities, and strengthening supervision and entry restrictions are suggested.
Keywordenergy-intensive industries air pollution North China Plain industrial agglomeration
DOI10.1007/s11442-021-1860-x
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41771133] ; National Natural Science Foundation of China[41771181] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19040403]
Funding OrganizationNational Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences
WOS Research AreaPhysical Geography
WOS SubjectGeography, Physical
WOS IDWOS:000639845600007
PublisherSCIENCE PRESS
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/161693
Collection中国科学院地理科学与资源研究所
Corresponding AuthorWang, Zhenbo
Affiliation1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Reg Sustainable Dev Modeling, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Xiaoping,Lin, Meihan,Wang, Zhenbo,et al. The impact of energy-intensive industries on air quality in China's industrial agglomerations[J]. JOURNAL OF GEOGRAPHICAL SCIENCES,2021,31(4):584-602.
APA Zhang, Xiaoping,Lin, Meihan,Wang, Zhenbo,&Jin, Fengjun.(2021).The impact of energy-intensive industries on air quality in China's industrial agglomerations.JOURNAL OF GEOGRAPHICAL SCIENCES,31(4),584-602.
MLA Zhang, Xiaoping,et al."The impact of energy-intensive industries on air quality in China's industrial agglomerations".JOURNAL OF GEOGRAPHICAL SCIENCES 31.4(2021):584-602.
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