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Distribution of some potentially toxic elements in the soils of the Jharia Coalfield: A probabilistic approach for source identification and risk assessment
Land Degradation & Development ( IF 3.6 ) Pub Date : 2021-11-26 , DOI: 10.1002/ldr.4155
Azeem Uddin Siddiqui 1 , Manish Kumar Jain 1 , Reginald Ebhin Masto 2
Affiliation  

Potentially toxic elements (PTEs) in coal mining soil degrade soil quality and adversely affect people's health. The increasing mining activities in the Jharia Coalfield (JCF) may increase the concentration of PTEs in soils. Therefore, it is vital to have an in-depth analysis of land degradation caused by them, but there is a lack of accurate and efficient methods to estimate land degradation and health risk analysis in JCF. Therefore, finite mixture distribution model (FMDM), positive matrix factorization (PMF), and Monte Carlo simulation were applied to Jharia's PTEs dataset. The FMDM was employed to distinguish the background concentration and the contamination due to anthropogenic activity. In addition, the contribution of the source was determined through PMF. The FMDM suggested two possible sources of PTEs, while the PMF defines the influence of PTEs more broadly and identifies three sources of PTEs in soil. The results showed that PTEs contribution by a natural source, coal mining, and atmospheric deposition accounted for 45.72%, 27.34%, and 26.94%, respectively. Based on health risk results, this region does not pose a noncarcinogenic risk, but it does pose a carcinogenic risk, especially to infants. JCF comprises a relatively low concentration of PTEs as compared with other possible values for India. Probabilistic health risk assessment studies are scarce for Indian soils, especially in mining areas. In combination, these approaches will provide deeper insights and help identify potential solutions for PTEs contamination in these areas.

中文翻译:

Jharia 煤田土壤中一些潜在有毒元素的分布:来源识别和风险评估的概率方法

煤矿土壤中的潜在有毒元素 (PTE) 会降低土壤质量并对人们的健康产生不利影响。Jharia 煤田 (JCF) 不断增加的采矿活动可能会增加土壤中 PTE 的浓度。因此,对其造成的土地退化进行深入分析至关重要,但JCF缺乏准确有效的土地退化估计和健康风险分析方法。因此,有限混合分布模型 (FMDM)、正矩阵分解 (PMF) 和蒙特卡罗模拟被应用于 Jharia 的 PTEs 数据集。FMDM 用于区分背景浓度和人为活动造成的污染。此外,源的贡献是通过 PMF 确定的。FMDM 提出了两种可能的 PTE 来源,而 PMF 更广泛地定义了 PTE 的影响,并确定了土壤中 PTE 的三种来源。结果表明,自然来源、煤炭开采和大气沉降对PTEs的贡献分别占45.72%、27.34%和26.94%。根据健康风险结果,该区域不存在非致癌风险,但确实存在致癌风险,尤其是对婴儿而言。与印度的其他可能值相比,JCF 包含的 PTE 浓度相对较低。印度土壤的概率健康风险评估研究很少,尤其是在矿区。结合起来,这些方法将提供更深入的见解并帮助确定这些领域中 PTE 污染的潜在解决方案。结果表明,自然来源、煤炭开采和大气沉降对PTEs的贡献分别占45.72%、27.34%和26.94%。根据健康风险结果,该区域不存在非致癌风险,但确实存在致癌风险,尤其是对婴儿而言。与印度的其他可能值相比,JCF 包含的 PTE 浓度相对较低。印度土壤的概率健康风险评估研究很少,尤其是在矿区。结合起来,这些方法将提供更深入的见解并帮助确定这些领域中 PTE 污染的潜在解决方案。结果表明,自然来源、煤炭开采和大气沉降对PTEs的贡献分别占45.72%、27.34%和26.94%。根据健康风险结果,该区域不存在非致癌风险,但确实存在致癌风险,尤其是对婴儿而言。与印度的其他可能值相比,JCF 包含的 PTE 浓度相对较低。印度土壤的概率健康风险评估研究很少,尤其是在矿区。结合起来,这些方法将提供更深入的见解并帮助确定这些领域中 PTE 污染的潜在解决方案。但它确实存在致癌风险,尤其是对婴儿。与印度的其他可能值相比,JCF 包含的 PTE 浓度相对较低。印度土壤的概率健康风险评估研究很少,尤其是在矿区。结合起来,这些方法将提供更深入的见解并帮助确定这些领域中 PTE 污染的潜在解决方案。但它确实存在致癌风险,尤其是对婴儿。与印度的其他可能值相比,JCF 包含的 PTE 浓度相对较低。印度土壤的概率健康风险评估研究很少,尤其是在矿区。结合起来,这些方法将提供更深入的见解并帮助确定这些领域中 PTE 污染的潜在解决方案。
更新日期:2022-01-19
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