何土凤, 韦青妙, 李京泽, 韦三进, 章一帆, 钟秋安. 广西柳州市某典型废矿区重金属暴露健康风险及其空间分布特征[J]. 环境与职业医学, 2023, 40(2): 190-195. DOI: 10.11836/JEOM22347
引用本文: 何土凤, 韦青妙, 李京泽, 韦三进, 章一帆, 钟秋安. 广西柳州市某典型废矿区重金属暴露健康风险及其空间分布特征[J]. 环境与职业医学, 2023, 40(2): 190-195. DOI: 10.11836/JEOM22347
HE Tufeng, WEI Qingmiao, LI Jingze, WEI Sanjin, ZHANG Yifan, ZHONG Qiu’an. Health risk and spatial distribution characteristics of heavy metal exposure in typical abandoned mining area in Liuzhou, Guangxi[J]. Journal of Environmental and Occupational Medicine, 2023, 40(2): 190-195. DOI: 10.11836/JEOM22347
Citation: HE Tufeng, WEI Qingmiao, LI Jingze, WEI Sanjin, ZHANG Yifan, ZHONG Qiu’an. Health risk and spatial distribution characteristics of heavy metal exposure in typical abandoned mining area in Liuzhou, Guangxi[J]. Journal of Environmental and Occupational Medicine, 2023, 40(2): 190-195. DOI: 10.11836/JEOM22347

广西柳州市某典型废矿区重金属暴露健康风险及其空间分布特征

Health risk and spatial distribution characteristics of heavy metal exposure in typical abandoned mining area in Liuzhou, Guangxi

  • 摘要: 背景

    重金属暴露对机体健康存在潜在危害,而废矿区域重金属含量仍可能高于一般地区,开展该区域健康风险评估工作不可忽视。

    目的

    探讨某典型废矿区重金属暴露健康风险及引起风险的主要金属的空间分布特征。

    方法

    于2019年11—12月在广西柳州市某典型废矿区所在乡镇的13个自然村落分别采集灌溉土壤、大米、生活饮用水环境样本,最终共采集13份灌溉土壤样本、11份大米样本和13份生活饮用水样本。采用电感耦合等离子体质谱(ICP-MS)检测各环境样本6种金属与类金属元素浓度,包括镉(Cd)、砷(As)、铅(Pb)、铬(Cr)、铜(Cu)、锌(Zn)。同时征募251名当地居民作为健康风险评估的研究对象。通过现场调查获取当地居民体重、大米摄入量、生活饮用水摄入量等模型参数,并以各环境样本金属检测浓度中位数作为该区域风险评估参数,参考美国环境保护署经口途径健康风险评估模型评估当地居民重金属暴露健康风险,利用地理信息系统(GIS)技术,运用经验贝叶斯插值法对引起健康风险的主要重金属进行空间插值,探讨其空间分布特征。

    结果

    灌溉土壤样本Cd、As、Pb、Cr、Cu、Zn六种金属检出率均为100.00%;大米样本Pb检出率为63.64%,其余金属检出率为100.00%;生活饮用水Cd、As、Pb、Cr、Cu、Zn的检出率分别为53.85%、76.92%、92.31%、15.38%、84.62%、100.00%。经口途径重金属暴露非致癌风险评估结果提示,引起非致癌风险的重金属贡献率由高到低为As(70.52%)>Cd(18.03%)>Zn(6.63%)>Cu(4.12%)>Pb(0.64%)>Cr(0.06%),其非致癌风险分别为3.54×100、9.05×10−1、3.33×10−1、2.07×10−1、3.23×10−2、5.42×10−4;经口途径重金属暴露致癌风险评估结果提示,引起致癌风险的重金属贡献率由高到低为Cd(87.00%)>As(10.24%)>Cr(2.60%)>Pb(0.16%),其致癌风险分别为4.35×10−3、5.12×10−4、1.30×10−4、3.08×10−7。大米是引起非致癌风险和致癌风险升高的主要环境介质(分别为99.4%和99.8%)。GIS空间分布特征显示,金属As在灌溉土壤、大米、生活饮用水的分布无明显规律;重金属Cd在大米、灌溉土壤明显表现出矿区附近村落含量高于其他村落,在生活饮用水则表现距矿区较远村落高于矿区附近村落。

    结论

    引起当地居民健康风险升高的主要重金属为As和Cd,两重金属在不同环境介质分布规律并不完全一致。

     

    Abstract: Background

    Exposure to heavy metals has potential adverse impacts on human health, and the concentration of heavy metals in abandoned mining areas may still be higher than that in general areas, so the health risk assessment in such areas cannot be ignored.

    Objective

    To explore the health risk of heavy metal exposure and the spatial distribution characteristics of associated main metals in a typical abandoned mining area.

    Methods

    Environmental samples of irrigated soil, rice, and drinking water were collected from 13 natural villages under the jurisdiction of a township in Liuzhou, Guangxi from November to December 2019, where a typical abandoned mining was located. Finally, 13 irrigation soil samples, 11 rice samples, and 13 drinking water samples were collected. The concentrations of six metals and metalloid elements in each environmental sample were detected by inductively coupled-plasma mass spectrometry (ICP-MS), including cadmium (Cd), arsenic (As), lead (Pb), chromium (Cr), copper (Cu), and zinc (Zn). At the same time, 251 local residents were recruited for health risk assessment. Model parameters such as body weight, rice intake, and drinking water intake of local residents were obtained through field survey, and the median metal concentration of each environmental sample was taken as the risk assessment parameter of the region. The health risk of heavy metal exposure of local residents was assessed by using oral health risk assessment model of U.S. Environmental Protection Agency. The spatial distribution characteristics of health risks associated with heavy metals were evaluated by empirical Bayes interpolation method using Geographic Information System (GIS) technology.

    Results

    The positive rates of Cd, As, Pb, Cr, Cu, and Zn in the irrigated soil samples were 100.00%. The positive rate of Pb was 63.64% in the rice samples, while the rates of other metals were 100.00%. The positive rates of Cd, As, Pb, Cr, Cu, and Zn in the drinking water samples were 53.85%, 76.92%, 92.31%, 15.38%, 84.62%, and 100.00%, respectively. The results of non-carcinogenic risk assessment of oral exposure to heavy metals suggested that the contribution of heavy metals causing non-carcinogenic risk from high to low was As (70.52%) > Cd (18.03%) > Zn (6.63%) > Cu (4.12%) > Pb (0.64%) > Cr (0.06%), and the corresponding estimated non-carcinogenic risk values were 3.54 × 100, 9.05 × 10−1, 3.33 × 10−1, 2.07 × 10−1, 3.23 × 10−2, and 5.42 × 10−4, respectively. The results of carcinogenic risk assessment of oral exposure to heavy metals suggested that the contribution of studied metals from high to low was Cd (87.00%) > As (10.24%) > Cr (2.60%) > Pb (0.16%), and the estimated carcinogenic risks were 4.35× 10−3, 5.12 × 10−4, 1.30 × 10−4, and 3.08 × 10−7, respectively. Rice was the leading media associated with non-carcinogenic risk and carcinogenic risk (99.4% and 99.8% respectively). The spatial distribution characteristics of GIS showed no obvious regularity in the distribution of As in irrigated soil, rice, and drinking water. In rice and irrigated soil, the content of Cd in the villages adjacent to the mining area was obviously higher than that in the other villages, while in drinking water, the content in the villages far away from the mining area was higher.

    Conclusion

    As and Cd are the main heavy metals that increase the health risk of local residents in a typical abandoned mining area, and the distribution characteristics of the two heavy metals in different environmental media are not completely consistent.

     

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