Quantitatively assessing the risks and possible sources of toxic metals in soil from an arid, coal-dependent industrial region in NW China

Highlights

• Obvious enrichment of Cr, Hg and As were found in the study area.

• Hg was the primary ecological risk contributor.

• As through ingestion was the primary exposure pathway.

• Five possible sources were quantified by PMF method.

• About 82.18% of soil pollution related to anthropogenic activities.

Abstract

Comprehensive studies on toxic metal pollution in the soils of arid coal-mining areas have not drawn the attention they deserve. In the present study, we investigated the concentrations of 6 pollutants (Zn, Cu, Cr, Pb, Hg, and As) in soils of an arid mining area, the Eastern Junggar Basin (EJB) of Xinjiang, Northwestern China. Noticeable concentrations were found for Cr, Hg, and As, whereas Zn, Cu, and Pb were lower than their provincial (Xinjiang) guideline values. The average enrichment of As exceeded both Quality Standards (I and II) for soil recommended by the Chinese Environmental Protection Administration, whereas other metals were found within the allowable values of Soil Quality Standard I. There were different degrees of comprehensive ecological risks in the area, and Hg was the major contributor to the PER. In health risk assessments, children seem to have a higher health risk hazards than adults, with As as the primary contributor, followed by Cr. The positive matrix factorization (PMF) model explains five possible sources, including coal combustion, vehicle emissions, atmospheric deposition, industrial discharge, and natural factors, which accounted for 20.79%, 16.83%, 16.83%, 27.72%, and 17.82% of the total contribution, respectively. The results will be informative for local authorities to establish more effective targeting policies to control the spread of contaminants and provide reference materials for soil quality protection and improvement and other research programs in this area.

Introduction

Soil toxic metals (TM) are considered the most severe pollutants of terrestrial ecosystems due to their toxicity, tendency towards biological accumulation, and potential threat to human and ecosystem health (Dai et al., 2017; Li et al., 2017). Many soil toxic metal contaminants have been identified in agricultural, auriferous, urban, and industrial areas (Lv and Liu, 2019; Naghipour et al., 2018; Mao et al., 2019; Gong et al., 2018; Ouyang et al., 2018). However, of the all areas threatened by toxic metal pollution, the soils around coal mining areas are typically the most severely polluted due to the consequences of frequent and high-intensity mining activities (Ding et al., 2017; Midhat et al., 2019; Edelstein and Ben-Hur, 2018). As the primary producer and consumer, it is estimated that, in China, coal represents 50%–70% of the whole country's energy consumption (De Souza et al., 2015; Zhang et al., 2015). It is well documented that in the mining areas, excessive accumulation of metal pollutants may cause significant human health risks and may have long-term adverse ecological effects (Liu et al., 2018b; Bano et al., 2018). Therefore, monitoring of the soil pollutants in the coal mining areas has drawn increasing attention as a globally recognized environmental issue.

In the mining areas, the soil TMs are regarded as the best option for the assessment of ecological-human risks because of the frequency of deposition (Agomuo and Amadi, 2017). The metals may have been introduced by natural sources associated with the geological background or anthropogenic origins, including agriculture, mining, atmospheric deposition, industry, and waste materials (Tagliani et al., 2017; Du et al., 2019; Sun et al., 2019). Quantifying the possible sources of soil pollutants is of great value, not only to control the pollution pathways, but also to protect environmental safety and human health (Guan et al., 2018; Liu et al., 2018a). Previous efforts on the identification of pollution sources of soil TMs in the Eastern Junggar Basin (EJB) coal-mining area were mainly focused on multivariate statistical approaches, principal component analysis (PCA) (Yang et al., 2018), and geostatistical methods (Abliz et al., 2018). However, these methods cannot interpret the quantitative contributions of each pollution source and may result in inaccuracies and uncertainties (Tian et al., 2018). Currently, optimized mathematical models, including principal component analysis integrated with multiple linear regression (PCA/MLR), absolute principal component score integrated with multiple linear regression (APCS/MLR), edge analysis (UNMIX), and positive matrix factorization (PMF), have been used in the source apportionment of soil contaminants (Lv and Liu, 2019; Lang et al., 2015), atmosphere pollutants (Liu et al., 2017; Taghvaee et al., 2018) and water pollutants (Gholizadeh et al., 2016). PMF can estimate the pollution sources according to the source profiles calculated by the model when local-specific source profiles are not available (Lu et al., 2018b). Many investigations have suggested that the PMF model provides better results than those of other methods (Jain et al., 2017; Salim et al., 2019; Zhang et al., 2019). Therefore, in the current study, we applied the PMF method to quantitatively identify the possible sources of 6 TMs in the soil from a typical coal-dependent industrial area, the Eastern Junggar Basin (EJB), NW China.

As the center of Chinese coal mining has shifted from central China to the northwest, large-scale, high-intensity coal-mining activities have further threatened the fragile eco-environment of northwestern China (Kang et al., 2018; Aerzuna et al., 2017). Industrial enterprises are attracted to the EJB open-pit coal mining area by the locational advantage and abundant coal resources; the area is located in the central part of the “Road-Belt” economic zone and possesses approximately 390 billion tons of coal reserves (http://zd.cj.cn/a/zwgk/). North of the study area is the Kalamaili national nature reserve, and the south includes residential areas. This area has an extremely arid climate with a weak and fragile ecosystem (Aerzuna et al., 2017). What is more, there are a number of power plants, as well as chemical, metal smelting, new material, and new energy industries that largely depend on coal energy. Once the soils of the area are polluted, it is hard to restore them and they can easily experience ecological degradation. Additionally, it has been reported that metal pollution and soil degradation from mining can induce adverse effects on residents living in or nearby the area (Kusin et al., 2018). Therefore, it is essential to obtain comprehensive and thorough information on soil contaminants in the mining area, which is of great importance for ecological safety, human health, and economic stability. The specific objectives of this work were to (1) estimate the pollution characteristics of soil TMs in the mining area; (2) assess the risks of metals for ecology and human health based on assessment models; and (3) quantify the proportions of various sources of pollutants using the positive matrix factorization (PMF) method.