Health risk assessment of heavy metal(loid)s in park soils of the largest megacity in China by using Monte Carlo simulation coupled with Positive matrix factorization model

被引:360
作者
Huang, Jingling [1 ]
Wu, Yuying [1 ]
Sun, Jiaxun [1 ]
Li, Xiao [1 ]
Geng, Xiaolei [1 ]
Zhao, Menglu [1 ]
Sun, Ting [1 ]
Fan, Zhengqiu [1 ]
机构
[1] Fudan Univ, Dept Environm Sci & Engn, Shanghai 200433, Peoples R China
关键词
Pollution assessment; Source apportionment; Probabilistic health risk; Urban park; HISTORICAL URBAN PARK; SOURCE APPORTIONMENT; SPATIAL-DISTRIBUTION; ECOLOGICAL RISK; COMPREHENSIVE ASSESSMENT; CHILDRENS PLAYGROUNDS; SOURCE IDENTIFICATION; AGRICULTURAL SOILS; CIGARETTE BUTTS; HENAN PROVINCE;
D O I
10.1016/j.jhazmat.2021.125629
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Urban Parks are important places for residents to engage in outdoor activities, and whether heavy metal(loid)s (HMs) in park soils are harmful to human health has aroused people's concern. A total of 204 topsoil samples containing nine HMs were collected from 78 urban parks of Shanghai in China, and used to assess the health risks caused by HMs in soils. The results revealed that the Hg, Cd and Pb were the main enriched pollutants and posed higher ecological risks than the other HMs. Four HM sources (including natural sources, agricultural activities, industrial production and traffic emissions) were identified by combining the Positive matrix factorization model and Correlation analysis, with the contribution rate of 48.24%, 7.03%, 13.04% and 31.69%, respectively. The assessment of Probabilistic health risks indicated that the Non-carcinogenic risks for all populations were negligible. However, the Total carcinogenic risk cannot be negligible and children were more susceptible than adults. The assessment results of source-oriented health risks showed that industrial production and traffic emissions were estimated to be the most important anthropogenic sources of health risks for all populations. Our results provide scientific support needed for the prevention and control of HM pollution in urban parks.
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页数:11
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[71]   Associations between renal functions and exposure of arsenic and polycyclic aromatic hydrocarbon in adults living near a petrochemical complex [J].
Yuan, Tzu-Hsuen ;
Ke, Deng-Yuan ;
Wang, Joyce En-Hua ;
Chan, Chang-Chuan .
ENVIRONMENTAL POLLUTION, 2020, 256
[72]   Distribution and Accumulation of Heavy Metals in Sediments of the Northern Part of Mangrove in Hara Biosphere Reserve, Qeshm Island (Persian Gulf) [J].
Zarezadeh, Rezvan ;
Rezaee, Peyman ;
Lak, Razyeh ;
Masoodi, Mehdi ;
Ghorbani, Mansoor .
SOIL AND WATER RESEARCH, 2017, 12 (02) :86-95
[73]   Using multivariate analyses and GIS to identify pollutants and their spatial patterns in urban soils in Galway, Ireland [J].
Zhang, Chaosheng .
ENVIRONMENTAL POLLUTION, 2006, 142 (03) :501-511
[74]   Health risk assessment of heavy metals in agricultural soils and identification of main influencing factors in a typical industrial park in northwest China [J].
Zhang, Rui ;
Tao, Chen ;
Zhang, Yu ;
Hou, Yuhao ;
Chang, Qingrui .
CHEMOSPHERE, 2020, 252
[75]   Source identification and spatial distribution of arsenic and heavy metals in agricultural soil around Hunan industrial estate by positive matrix factorization model, principle components analysis and geo statistical analysis [J].
Zhang, Xiaowen ;
Wei, Shuai ;
Sun, Qianqian ;
Wadood, Syed Abdul ;
Guo, Boli .
ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY, 2018, 159 :354-362
[76]   Arsenic in agricultural soils across China: Distribution pattern, accumulation trend, influencing factors, and risk assessment [J].
Zhou, Yuting ;
Niu, Lili ;
Liu, Kai ;
Yin, Shanshan ;
Liu, Weiping .
SCIENCE OF THE TOTAL ENVIRONMENT, 2018, 616 :156-163
[77]   A new ecological risk assessment index for metal elements in sediments based on receptor model, speciation, and toxicity coefficient by taking the Nansihu Lake as an example [J].
Zhuang, Wen ;
Wang, Qian ;
Tang, Lebin ;
Liu, Jinhu ;
Yue, Wen ;
Liu, Yongxia ;
Zhou, Fengxia ;
Chen, Qing ;
Wang, Mantang .
ECOLOGICAL INDICATORS, 2018, 89 :725-737