Quantitative Source Apportionment and Uncertainty Analysis of Heavy Metal(loid)s in the Topsoil of the Nansi Lake Nature Reserve

Di Zhao, Qiang Wu, Guodong Zheng, Yifan Zeng, Hanyuan Wang, Aoshuang Mei, Shuai Gao, Xiaohui Zhang and Yao Zhang
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Di Zhao: College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
Qiang Wu: College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
Guodong Zheng: Technology Innovation Center of Restoration and Reclamation in Mining Induced Subsidence Land, Ministry of Natural Resources, Jining 272000, China
Yifan Zeng: College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
Hanyuan Wang: Geological Survey Academy of Inner Mongolia Autonomous Region, Hohot 010010, China
Aoshuang Mei: College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
Shuai Gao: College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
Xiaohui Zhang: College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
Yao Zhang: College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China

Sustainability, 2022, vol. 14, issue 11, 1-20

Abstract: There are numerous coal mines around the Nansi Lake Provincial Nature Reserve, and the mineral resources are extremely rich. Therefore, it is necessary to effectively assess the impact of mining activities on the topsoil. Based on a focused investigation of the contamination status and ecological risks of the Nansi Lake Nature Reserve assisted by GIS, principal component analysis was combined with positive matrix factorization to quantitatively identify the sources and contributions of heavy metal(loid)s in the topsoil before conducting uncertainty analysis. The results showed that coal mining caused higher Cu, Zn, and As contamination levels, while Hg and Cd had higher eco-toxicity and biological sensitivity. Meanwhile, principal component analysis (PCA) and positive matrix factorization (PMF) modeling displayed that Hg (59.2%) was primarily generated by industrial sources (fossil fuel combustion and mercury-containing wastewater); As (70.2%), Ni (65.6%), Cr (63.5%), Pb (61.3%), Cu (60.3%), and Zn (55.8%) were generated mainly from coal mining and processing, coal fossil fuel combustion, and coal gangue dumps; Cd (79.8%) came mainly from agricultural sources. Through uncertainty analysis, the contribution of contamination sources to the heavy metal(loid)s in the topsoil, as estimated by the PMF model, was shown to be quite different. Moreover, heavy metal(loid)s with lower contributions had errors in source identification and factor quantification. This study innovatively warned management to control the hazards of heavy metal(loid)s caused by mining engineering to protect the environment of the Nansi Lake Nature Reserve and revealed the potential harmful pathways of heavy metal(loid)s.

Keywords: heavy metal(loid)s; contamination assessment; source apportionment; positive matrix factorization (PMF); uncertainty analysis; Nansi Lake Nature Reserve (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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