Geographic distribution of heavy metals and identification of their sources in soils near large, open-pit coal mines using positive matrix factorization

• Published in: Journal of hazardous materials 2020-04, Vol.387, p.121666, Article 121666
• Main Authors: Cheng, Wei, Lei, Shaogang, Bian, Zhengfu, Zhao, Yibo, Li, Yuncong, Gan, Yandong
• Format: Article
• Language: English
• Subjects: Grassland; Heavy metal; Identification of sources; Large-scale coal base; Positive matrix factorizing model
• ISSN: 0304-3894; 1873-3336
• DOI: 10.1016/j.jhazmat.2019.121666

[Display omitted] •Study of high-intensity mining impacts on the distribution of heavy metals in steppe.•Integration of field study, hyperspectral imagery, GIS and environment model.•Concentrated distribution Ge and As should be paid attention near the germanium mine.•Spatial distribution and contribution of main sources were identified and quantified. Mining activities are considered the most important factor causing heavy metal accumulation in surface soil and it is important to understand the spatial distribution and source of heavy metals in typical steppes. In this study, the contents, spatial distribution, and sources of heavy metals were determined using geostatistical analyses, multivariate statistical analyses, and a positive matrix factorization (PMF) model using 152 soil samples collected from a grassland near the Sheng-Li coal base. The results shows that the mean concentration of heavy metals is low and does not threaten the quality of the local soil. However, the concentrations of eight heavy metals (Cu 15.04 mg kg-1, Zn 49.30 mg kg-1, Cd 0.11 mg kg-1, Pb 20.00 mg kg-1, Se 0.12 mg kg-1, Ge 1.45 mg kg-1, As 9.06 mg kg-1, and Sn 2.52 mg kg-1) are higher than their mean background values in soil in Inner Mongolia. High coefficients of variation for the heavy metals, especially Ge (1.03), and As (0.56), indicate that the concentrations of the elements are affected by the presence of the open-pit mines. Multivariate statistical and geo-statistical analyses show that Ge and As are highly correlated (R2 = 0.67, P