Contamination Characteristics and Source Apportionment of Heavy Metal in the Topsoil of a Small Watershed in South Taihang

Jiafu Liu, Yuxin Chen, Yingtao Shang, Hongbo Li, Quanlai Ma and Fengjie Gao ()
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Jiafu Liu: College of Economics and Management, Northeast Agricultural University, Harbin 150036, China
Yuxin Chen: School of Public Administration and Law, Northeast Agricultural University, Harbin 150036, China
Yingtao Shang: School of Public Administration and Law, Northeast Agricultural University, Harbin 150036, China
Hongbo Li: School of Public Administration and Law, Northeast Agricultural University, Harbin 150036, China
Quanlai Ma: The First Institute of Henan Provincial Resource Environment Survey, Zhengzhou 450016, China
Fengjie Gao: School of Public Administration and Law, Northeast Agricultural University, Harbin 150036, China

Land, 2024, vol. 13, issue 7, 1-13

Abstract: With the rapid development of industrialization and urbanization, the issue of soil environmental pollution is becoming more and more prominent, especially concerning heavy metal contamination, which has garnered significant scholarly attention. The surface watershed formed by waterline is influenced by various factors such as topography, industrial emissions, and agricultural runoff, resulting in a complex process of migration and accumulation of heavy metal elements from multiple sources. In this study, the pollution characteristics and sources of heavy metal elements Hg, As, Pb, Ni, Cd, Cr, Cu and Zn in 165 surface soil samples from the Manghe River watershed in Jiyuan City were comprehensively analyzed using a variety of methods, including statistics, geostatistics, enriched factor analysis and the Positive Matrix Factorization Model (PMF). The results showed that the concentrations of Hg, Cd, As, Cu, Pb and Zn exceeded their corresponding background values with varying degrees of enrichment. Notably, the average contents of Cd, Hg and Pb were 26.70 times, 3.69 times and 4.49 times higher than those in Chinese soils on average, respectively, showing obvious enrichment characteristics. Moreover, there were distinct spatial distribution patterns for each heavy metal element; Ni and Cr exhibited similar trends mainly controlled by the parent material, while human activities significantly affect the other six elements forming high-value areas around mining and related industries. It is noteworthy that Cu, Hg and Zn were influenced by dominant wind direction in autumn and winter, forming sub-high-value zones in southern forested areas; meanwhile, Cu and Zn were also influenced by agricultural fertilizer application as well as surface runoff, leading to secondary high-value areas in the dryland areas. Further analysis revealed a significant positive correlation among these heavy metal elements, suggesting that they may share common sources. Through the PMF Model, four main factors were identified, with factor 2 (36.25%), factor 1 (23.00%), factor 3 (21.20%) and factor 4 (19.55%) ranked in descending order of contribution rate. The heavy metal pollution in the study area was attributed to anthropogenic activities and natural factors, accounting for 63.75% and 36.25%, respectively. Coal mining, chemical industry smelting, vehicle emissions and excessive use of agrochemicals were identified as the main sources of heavy metal pollution. These pollutants entered the soil through direct emissions, atmospheric deposition, transportation and agricultural activities, exerting a significant impact on the soil environment. Therefore, delving into the spatial distribution pattern of soil heavy metal pollution and precise analysis of its sources are of great importance for effective treatment and remediation of soil heavy metal pollution in small watersheds, maintaining healthy soil ecology and safeguarding human health.

Keywords: heavy metal pollution; enrichment factor; PMF; spatial distribution characteristics; source apportionment; small watershed; South Taihang (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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