气候变化领域集成服务门户(CCPortal): Spatio-temporal data mining and modeling: Distribution pattern and governance input efficiency of heavy metal emission in industrial wastewater; China

CCPortal

DOI	10.2166/wcc.2018.132
	Spatio-temporal data mining and modeling: Distribution pattern and governance input efficiency of heavy metal emission in industrial wastewater; China
	Li X.; Qiao H.; Wang R.; Li F.; Li X.
发表日期	2018
ISSN	20402244
起始页码	307
结束页码	321
卷号	9 期号:2
英文摘要	Heavy metal (HM) in industrial wastewater has been one of the serious environmental issues in China for a long time. This paper analyzes the distribution of HMs and governance input efficiency in industrial wastewater based on the archival data of China Statistical Yearbook on Environment from 2001 to 2014. The empirical analysis shows that the concentrations of Hg, Cd, Pb, As, and Cr(VI) generally decreased from 2001 to 2014. The emissions of Hg, Cd, Pb, and As are mostly concentrated in the central provinces (i.e., Hunan, Hubei, Jiangxi), the southern provinces (i.e., Guangxi and Guangdong), and the northern provinces (i.e., Gansu and Inner Mongolia). The distribution pattern is closely related to local industry due to resources dependence, such as mining and processing of non-ferrous metal ores, smelting and pressing of ferrous or non-ferrous metals. Cr(VI) is mainly located in the eastern coastal provinces, including Zhejiang and Jiangsu, and caused by manufacturing industries such as automobile, metal products, leather, fur, feather and related products, and footware. Furthermore, we find that the annual expenditure on and the capacity to deal with industrial wastewater play significant negative effects on reducing HM concentrations in industrial wastewater. © IWA Publishing 2018.
英文关键词	Distribution pattern; Governance input efficiency; Heavy metal; Industrial wastewater
语种	英语
scopus关键词	Cadmium compounds; Data mining; Efficiency; Heavy metals; Industrial emissions; Lead compounds; Mercury compounds; Metal pressing; Smelting; Annual expenditure; Distribution patterns; Environmental issues; Heavy metal emissions; Industrial wastewaters; Input efficiencies; Manufacturing industries; Spatio-temporal data mining; Chromium compounds; data mining; emission; environmental issue; governance approach; heavy metal; modeling; spatiotemporal analysis; wastewater; China
来源期刊	Journal of Water and Climate Change
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/148052
作者单位	School of Management, Chongqing Technology and Business University, Chongqing, China; College of Science, Huazhong Agricultural University, Wuhan, China; Guanghua School of Management, Peking University, Beijing, China; Research Center for Environment and Health, Zhongnan University of Economics and Law, Wuhan, China; School of Economics and Business Administration, Chongqing University, Chongqing, China
推荐引用方式 GB/T 7714	Li X.,Qiao H.,Wang R.,et al. Spatio-temporal data mining and modeling: Distribution pattern and governance input efficiency of heavy metal emission in industrial wastewater; China[J],2018,9(2).
APA	Li X.,Qiao H.,Wang R.,Li F.,&Li X..(2018).Spatio-temporal data mining and modeling: Distribution pattern and governance input efficiency of heavy metal emission in industrial wastewater; China.Journal of Water and Climate Change,9(2).
MLA	Li X.,et al."Spatio-temporal data mining and modeling: Distribution pattern and governance input efficiency of heavy metal emission in industrial wastewater; China".Journal of Water and Climate Change 9.2(2018).