Njayou Martin Mozer, Ngounouno Ayiwouo Mouhamed, Ngounouno Ismaila
Department of Mining and Geology, School of Geology and Mining Engineering, University of Ngaoundere, P.O. BOX 115, Meiganga, Cameroon.
Department of Mining Engineering, School of Geology and Mining Engineering, University of Ngaoundere, P.O. BOX 115, Meiganga, Cameroon.
J Environ Health Sci Eng. 2023 Jan 23;21(1):143-155. doi: 10.1007/s40201-023-00849-y. eCollection 2023 Jun.
In this study, contamination by trace metals (TMs) such as Cr, Ni, Cu, As, Pb and Sb in the soils of the Bindiba mining district was assessed. This study aims to reveal the current status of the soil quality of the abandoned gold mining district of Bindiba and provide a scientific basis for its future remediation and overall management. 89 soil samples were systematically collected and characterized in order to determine the concentration of TMs (Cr, Ni, Cu, As, Pb and Sb). To assess the degree of metallic contamination, pollution indices were employed. Both multivariate statistical analysis (MSA) and geostatistical modelling (GM) were used to identify the potential sources of TMs elements and to determine the values of the modified contamination degree (mCd), the Nemerow Pollution Index (NPI) and the potential ecological risk index (RI) at un-sampled points. The results of trace metals (TMEs) characterization showed that the concentration of Cr, Ni, Cu, As, Pb and Sb ranged from 22.15-442.44 mg/kg, 9.25-360.37 mg/kg, 1.28-320.86 mg/kg, 0-46.58 mg/kg, 0-53.27 mg/kg and 0-6.33 mg/kg, respectively. The mean concentration of Cr, Cu and Ni exceeds the continental geochemical background values. The Enrichment Factor (EF) assessment indicates two categories of enrichment: moderately to extremely enrichment for Cr, Ni, and Cu and deficiency to minimal enrichment of Pb, As and Sb. Multivariate statistical analysis shows weak linear correlations between the studied heavy metals and suggests that these metals could not come from the same origins. The geostatistical modelling based on the values of mCd, NI and RI suggests a potential high pollution risk existed in the study area. The mCd, NPI and RI interpolation maps showed that the Northern part of the gold mining district was characterized by a high degree of contamination, heavy pollution, and considerable ecological risk. The dispersion of TMs in soils could mainly be attributed to anthropogenic activities and natural phenomena (chemical weathering or erosion). Appropriate measures should be taken to manage and remediate the TMs pollution in this abandoned gold mining district in order to reduce its negative effects on the environment and health of the local population.
The online version contains supplementary material available at 10.1007/s40201-023-00849-y.
在本研究中，对宾迪巴矿区土壤中铬、镍、铜、砷、铅和锑等痕量金属（TMs）的污染情况进行了评估。本研究旨在揭示宾迪巴废弃金矿区土壤质量的现状，并为其未来的修复和整体管理提供科学依据。系统采集并分析了89个土壤样本，以确定痕量金属（铬、镍、铜、砷、铅和锑）的浓度。为评估金属污染程度，采用了污染指数。多元统计分析（MSA）和地统计建模（GM）均用于识别痕量金属元素的潜在来源，并确定未采样点的修正污染程度（mCd）、内梅罗污染指数（NPI）和潜在生态风险指数（RI）值。痕量金属（TMEs）表征结果表明，铬、镍、铜、砷、铅和锑的浓度分别为22.15 - 442.44mg/kg、9.25 - 360.37mg/kg、1.28 - 320.86mg/kg、0 - 46.58mg/kg、0 - 53.27mg/kg和0 - 6.33mg/kg。铬、铜和镍的平均浓度超过了大陆地球化学背景值。富集因子（EF）评估表明存在两类富集情况：铬、镍和铜为中度至极高度富集，铅、砷和锑为缺乏至最低程度富集。多元统计分析表明，所研究的重金属之间线性相关性较弱，表明这些金属并非来自同一来源。基于mCd、NI和RI值的地统计建模表明，研究区域存在潜在的高污染风险。mCd、NPI和RI插值图显示，金矿区北部污染程度高、污染严重且生态风险较大。土壤中痕量金属的扩散主要归因于人为活动和自然现象（化学风化或侵蚀）。应采取适当措施管理和修复该废弃金矿区的痕量金属污染，以减少其对当地环境和居民健康的负面影响。
在线版本包含可在10.1007/s40201 - 023 - 00849 - y获取的补充材料。
