An Integrated Approach for Source Apportionment and Health Risk Assessment of Heavy Metals in Subtropical Agricultural Soils, Eastern China

Ping Li, Tao Wu, Guojun Jiang, Lijie Pu, Yan Li, Jianzhen Zhang, Fei Xu and Xuefeng Xie
Additional contact information
Ping Li: College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China
Tao Wu: College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China
Guojun Jiang: College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China
Lijie Pu: School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Yan Li: Co-Innovation Center for the Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing 210037, China
Jianzhen Zhang: College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China
Fei Xu: Institute of Land and Urban-Rural Development, Zhejiang University of Finance & Economics, Hangzhou 310018, China
Xuefeng Xie: College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China

Land, 2021, vol. 10, issue 10, 1-17

Abstract: Unreasonable human activities may cause the accumulation of heavy metals (HMs) in the agricultural soil, which will ultimately threaten the quality of soil environment, the safety of agricultural products, and human health. Therefore, the accumulation characteristics, potential sources, and health risks of HMs in agricultural soils in China’s subtropical regions were investigated. The mean Hg, Cu, Zn, Pb, and Cd concentrations of agricultural soil in Jinhua City have exceeded the corresponding background values of Zhejiang Province, while the mean concentrations of determined 8 HMs were less than their corresponding risk-screening values for soil contamination of agricultural land in China. The spatial distribution of As, Cr, Ni, Cu, and Pb were generally distributed in large patches, and Hg, Zn, and Cd were generally sporadically distributed. A positive definite matrix factor analysis (PMF) model had better performance than an absolute principal component–multiple linear regression (APCS-MLR) model in the identification of major sources of soil HMs, as it revealed higher R 2 value (0.81–0.99) and lower prediction error (−0.93–0.25%). The noncarcinogenic risks (HI) of the 8 HMs to adults and children were within the acceptable range, while the carcinogenic risk (RI) of children has exceeded the safety threshold, which needs to be addressed by relevant departments. The PMF based human health risk assessment model indicated that industrial sources contributed the highest risk to HI (32.92% and 30.47%) and RI (60.74% and 61.5%) for adults and children, followed by agricultural sources (21.34%, 29.31% and 32.94% 33.19%). Therefore, integrated environmental management should be implemented to control and reduce the accumulation of soil HMs from agricultural and industrial sources.

Keywords: soil heavy metals; positive definite matrix factor analysis; absolute principal component–multiple linear regression; health risk assessment (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2073-445X/10/10/1016/pdf (application/pdf)
https://www.mdpi.com/2073-445X/10/10/1016/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:10:y:2021:i:10:p:1016-:d:644704

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().