ORIGINAL RESEARCH
Heavy Metals in the Surface Soil around a Coalmine: Pollution Assessment and Source Identification
Sun Linhua 1, 2  
,  
Feng Songbao 1, 2  
 
 
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1
School of Resources and Civil Engineering, Suzhou University, Anhui, China
2
National Engineering Research Center of Coal Mine Water Hazard Controlling, Anhui, China
CORRESPONDING AUTHOR
Sun Linhua   

Suzhou University, 49# Bianhe Road, Suzhou City, Anhui Province, China, 234000 Suzhou, China
Online publish date: 2019-03-05
Publish date: 2019-04-09
Submission date: 2018-05-04
Final revision date: 2018-07-28
Acceptance date: 2018-08-07
 
Pol. J. Environ. Stud. 2019;28(4):2717–2724
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ABSTRACT
Coal mining in northern Anhui Province of China has led to a series of environmental problems. In this study, a total of 68 surface soil samples around a representative coalmine (the Haizi coalmine) in the area have been collected and then analyzed for seven kinds of heavy metal concentrations (Cu, Fe, Zn, Co, Ni, Mn and Pb) for getting information about their pollution degrees and sources. The results indicate that the metal concentrations are Fe>Mn>Zn>Pb>Cu>Ni>Co, and all of them have coefficients of variation ranging between 0.13 and 0.75, and low p-values (<0.01) of normal distribution test except for Fe, Co and Ni, which suggests that their concentrations have been affected by multiple factors. The single pollution index and geo-accumulation index imply that zinc and lead are light pollution, and the Nemerow composite index and the potential ecological risk index suggest that the soils in this study are slightly polluted and with low potential ecological risk. The spatial distributions of the metal concentrations, along with the statistical analyses (including correlation, cluster and factor analyses) indicate that all of the metals can be classified to be two groups, the Fe-Co-Mn and Cu-Zn-Pb-Ni, which mean geogenic and anthropogenic sources, respectively, and their mean contributions for the heavy metal concentrations in the study area are 57.1% and 42.9%, respectively, as calculated by the Unmix model.
eISSN:2083-5906
ISSN:1230-1485