Pollution Assessment and Source Apportionment of Soil Heavy Metals in a Coastal Industrial City, Zhejiang, Southeastern China

Shiyi Wang, Yanbin Zhang, Jieliang Cheng, Yi Li, Feng Li, Yan Li and Zhou Shi
Additional contact information
Shiyi Wang: School of Public Affairs, Institute of Land Science and Property, Zhejiang University, Hangzhou 310058, China
Yanbin Zhang: Zhejiang Land Consolidation and Rehabilitation Center, Hangzhou 310007, China
Jieliang Cheng: Zhejiang Cultivated Land Quality and Fertilizer Management Station, Hangzhou 310020, China
Yi Li: School of Public Affairs, Institute of Land Science and Property, Zhejiang University, Hangzhou 310058, China
Feng Li: College of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou 310058, China
Yan Li: School of Public Affairs, Institute of Land Science and Property, Zhejiang University, Hangzhou 310058, China
Zhou Shi: Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China

IJERPH, 2022, vol. 19, issue 6, 1-19

Abstract: In this research, Ningbo City, a typical industrial city in southeastern China, was selected as the study area, and the concentrations of 12 heavy metals (Cd, Cr, Ni, Pb, Zn, Cu, Hg, As, Co, V, Se, and Mn) were measured at 248 sampling points. Pollution index methods were used to assess the status of soil heavy metal contamination, and the Positive Matrix Factorization (PMF) model and Unmix model were integrated to identify and apportion the sources of heavy metal contamination. The results indicated that nearly 70% of the study area was polluted by heavy metals, and that Ni, Cr, and Zn were the main enriched heavy metals. The five sources identified using the PMF model were a geological source, an atmospheric deposition source, a transportation emissions source, a mixed source of agriculture and industry, and a mixed source of geology and industry. The four sources identified using the Unmix model were a mixed source of geology, agriculture, and industry (14.27%); a transportation emissions source (4.76%); a geological source (14.7%); and a mixed source of geology and industry (66.28%). These results have practical significance, as they can help to carry out pollution source risk assessment and give priority to the management of pollution source control.

Keywords: soil heavy metals; pollution assessment; source apportionment; industrial city (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://www.mdpi.com/1660-4601/19/6/3335/pdf (application/pdf)
https://www.mdpi.com/1660-4601/19/6/3335/ (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:jijerp:v:19:y:2022:i:6:p:3335-:d:769443

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

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