title: Heavy metal contamination assessment and partition for industrial and mining gathering areas.
abstract: Industrial and mining activities have been recognized as the major sources of soil heavy metal contamination. This study introduced an improved Nemerow index method based on the Nemerow and geo-accumulation index. Taking a typical industrial and mining gathering area in Tianjin (China) as example, this study then analyzed the contamination sources as well as the ecological and integrated risks. The spatial distribution of the contamination level and ecological risk were determined using Geographic Information Systems. The results are as follows: (1) Zinc showed the highest contaminant level in the study area; the contamination levels of the other seven heavy metals assessed were relatively lower. (2) The combustion of fossil fuels and emissions from industrial and mining activities were the main sources of contamination in the study area. (3) The overall contamination level of heavy metals in the study area ranged from heavily contaminated to extremely contaminated and showed an uneven distribution. (4) The potential ecological risk showed an uneven distribution, and the overall ecological risk level ranged from low to moderate. This study also emphasized the importance of partition in industrial and mining areas, the extensive application of spatial analysis methods, and the consideration of human health risks in future studies.
authors.affiliation: College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China. kiranedved@yeah.net.
authors.forename: Yang
authors.initials: Y
authors.lastname: Guan
authors.affiliation: College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China. shaocf@nankai.edu.cn.
authors.forename: Chaofeng
authors.initials: C
authors.lastname: Shao
authors.affiliation: College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China. jumeit@nankai.edu.cn.
authors.forename: Meiting
authors.initials: M
authors.lastname: Ju
mesh_terms: D001151:Arsenic / Q000032:analysis*; D002681:China; D016000:Cluster Analysis; D004784:Environmental Monitoring / Q000379:methods / Q000706:statistics & numerical data; D007221:Industry; D019216:Metals, Heavy / Q000032:analysis*; D008906:Mining; D018570:Risk Assessment; D012989:Soil Pollutants / Q000032:analysis*; D001335:Vehicle Emissions
chemical_list: D019216:Metals, Heavy; D012989:Soil Pollutants; D001335:Vehicle Emissions; D001151:Arsenic