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

doi:10.1016/j.envpol.2020.114690

CSpace

	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, Qingrong 1; Shi, Jian 2,3
	2020-09-01
发表期刊	ENVIRONMENTAL POLLUTION
ISSN	0269-7491
卷号	264 页码:10
摘要	China 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.
关键词	Quantile regression Spatial method Bayesian inference PM2.5 pollution Socioeconomic factors
DOI	10.1016/j.envpol.2020.114690
收录类别	SCI
语种	英语
WOS研究方向	Environmental Sciences & Ecology
WOS类目	Environmental Sciences
WOS记录号	WOS:000540263400046
出版者	ELSEVIER SCI LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/51621
专题	中国科学院数学与系统科学研究院
通讯作者	Shi, Jian
作者单位	1.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
推荐引用方式 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.