Impact of industrial activities on heavy metal contamination in soils in three major urban agglomerations of China

被引:113
|
作者
Zhou, Xi-Yin [1 ]
Wang, Xiu-Ru [2 ]
机构
[1] Beijing Normal Univ, Sch Syst Sci, Beijing 100875, Peoples R China
[2] Beijing Forestry Univ, Sch Soil & Water Conservat, Beijing 100083, Peoples R China
基金
中国国家自然科学基金;
关键词
Heavy metal contamination; Status assessment; Sources identification; Random forest; Industrial activities; Urban agglomerations; HEALTH-RISK ASSESSMENT; SOURCE APPORTIONMENT; SOURCE IDENTIFICATION; SPATIAL-DISTRIBUTION; AGRICULTURAL SOILS; GUANGDONG PROVINCE; ROADSIDE SOILS; POLLUTION; MULTIVARIATE; CITY;
D O I
10.1016/j.jclepro.2019.05.098
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Heavy metal contamination in soils has worsened with rapid economic development. The combined method with principal component analysis/absolute principal component scores) and random forest models successfully reveals the total sources contribution structure and the specific influence process of industrial activities on heavy metals concentration in soils of the three urban agglomerations. Through statistical analysis, Cd in the Jing-Jin-Ji Metropolitan Region, Pb, Cu, Hg, Cd and As in the Yangtze River Delta, and Hg, As, Cd, Cu and Pb in the Pearl River Delta had relatively high mean concentrations and coefficient of variation (CV), which indicates that the contamination may be caused by human activities. Through PCA/APCS analysis, industrial activities contributed more than 60% of the Cd, Hg and Pb concentrations in soils in JJJ, YRD and PRD. A random forest simulation revealed that heavy metal pollution in soils is the combined result of natural processes and human activities in the three urban agglomerations. The heavy metals concentration in JJJ is mainly caused by industrial activities through land-based emission. The industrial activities presented more significant impact on heavy metals concentration in the soil of YRD compared with other two urban agglomerations. The elevation variation controlled the pattern of heavy metal concentration through influencing the spatial clustering feature of industrial activities. The distance from the sample location to the nearest industrial enterprise is the most important factor in determining the heavy metal concentration. The number of enterprises within a 5 km radius of the sample locations makes a greater contribution to the amount of Hg pollution than other heavy metals. The results of this study could provide support for better management of soil pollution prevention practices such as specific industrial governance and layout optimization. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1 / 10
页数:10
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