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The heterogeneous effect of socioeconomic driving factors on PM2.5 in China's 30 province-level administrative regions: Evidence from Bayesian hierarchical spatial quantile regression
Zou, Qingrong1; Shi, Jian2,3
2020-09-01
Source PublicationENVIRONMENTAL POLLUTION
ISSN0269-7491
Volume264Pages:10
AbstractChina has become one of the most serious PM2.5-dominated air pollution country. Despite a great deal of research has focused on analysing the influence of social and economic driving forces of PM2.5 pollution in China, most research in existence either applying mean regression or failing to consider the spatial autocorrelation. Motivated by this, this paper utilizes a Bayesian hierarchical spatial quantile regression method to explore the effect of socioeconomic activity on PM2.5 air pollution. By introducing spatial random effects into the model, the spatial autocorrelations of residuals are significantly reduced. The empirical study demonstrated that the PM2.5 concentration levels were strongly correlated with total population, urbanization rate, industrialization level and energy efficiency at all quantiles. For upper quantiles, the impact of urbanization rate on the haze is the greatest among all the predictors, then followed by the total population; while for lower quantiles, industrialization has the greatest impact on the PM2.5 concentration. The impacts of energy efficiency in the lower 15% and upper 15% quantiles are higher compared to any of the other quantiles. (C) 2020 Elsevier Ltd. All rights reserved.
KeywordQuantile regression Spatial method Bayesian inference PM2.5 pollution Socioeconomic factors
DOI10.1016/j.envpol.2020.114690
Indexed BySCI
Language英语
WOS Research AreaEnvironmental Sciences & Ecology
WOS SubjectEnvironmental Sciences
WOS IDWOS:000540263400046
PublisherELSEVIER SCI LTD
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/51621
Collection中国科学院数学与系统科学研究院
Corresponding AuthorShi, Jian
Affiliation1.Beijing Informat Sci & Technol Univ, Sch Appl Sci, Beijing 100192, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100039, Peoples R China
Recommended Citation
GB/T 7714
Zou, Qingrong,Shi, Jian. The heterogeneous effect of socioeconomic driving factors on PM2.5 in China's 30 province-level administrative regions: Evidence from Bayesian hierarchical spatial quantile regression[J]. ENVIRONMENTAL POLLUTION,2020,264:10.
APA Zou, Qingrong,&Shi, Jian.(2020).The heterogeneous effect of socioeconomic driving factors on PM2.5 in China's 30 province-level administrative regions: Evidence from Bayesian hierarchical spatial quantile regression.ENVIRONMENTAL POLLUTION,264,10.
MLA Zou, Qingrong,et al."The heterogeneous effect of socioeconomic driving factors on PM2.5 in China's 30 province-level administrative regions: Evidence from Bayesian hierarchical spatial quantile regression".ENVIRONMENTAL POLLUTION 264(2020):10.
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