Department of Earth and Environmental Sciences, School of Natural Sciences and Williamson Research Centre for Molecular Environmental Science, University of Manchester, Manchester, M13 9PL, UK.
Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600, Dübendorf, Switzerland.
Environ Geochem Health. 2021 Jul;43(7):2649-2664. doi: 10.1007/s10653-020-00655-7. Epub 2020 Jul 11.
Geogenic arsenic contamination in groundwaters poses a severe health risk to hundreds of millions of people globally. Notwithstanding the particular risks to exposed populations in the Indian sub-continent, at the time of writing, there was a paucity of geostatistically based models of the spatial distribution of groundwater hazard in India. In this study, we used logistic regression models of secondary groundwater arsenic data with research-informed secondary soil, climate and topographic variables as principal predictors generate hazard and risk maps of groundwater arsenic at a resolution of 1 km across Gujarat State. By combining models based on different arsenic concentrations, we have generated a pseudo-contour map of groundwater arsenic concentrations, which indicates greater arsenic hazard (> 10 μg/L) in the northwest, northeast and south-east parts of Kachchh District as well as northwest and southwest Banas Kantha District. The total number of people living in areas in Gujarat with groundwater arsenic concentration exceeding 10 μg/L is estimated to be around 122,000, of which we estimate approximately 49,000 people consume groundwater exceeding 10 µg/L. Using simple previously published dose-response relationships, this is estimated to have given rise to 700 (prevalence) cases of skin cancer and around 10 cases of premature avoidable mortality/annum from internal (lung, liver, bladder) cancers-that latter value is on the order of just 0.001% of internal cancers in Gujarat, reflecting the relative low groundwater arsenic hazard in Gujarat State.
地下水的地质成因砷污染对全球数亿人构成了严重的健康风险。尽管印度次大陆暴露人群面临特殊风险,但在撰写本文时,印度地下水危害空间分布的地质统计学模型仍然很少。在这项研究中,我们使用了二次地下水砷数据的逻辑回归模型,这些数据与研究中提供的土壤、气候和地形变量相结合,作为主要预测因子,生成了古吉拉特邦地下水砷的危害和风险图,分辨率为 1 公里。通过结合基于不同砷浓度的模型,我们生成了地下水砷浓度的伪等高线图,该图表明卡奇地区的西北部、东北部和东南部以及班纳萨坎塔地区的西北部和西南部的地下水砷危害更大(>10μg/L)。估计在古吉拉特邦,有超过 122000 人生活在地下水砷浓度超过 10μg/L 的地区,其中我们估计约有 49000 人饮用超过 10μg/L 的地下水。使用简单的先前发表的剂量反应关系,这估计导致了 700 例(患病率)皮肤癌病例和约 10 例因内部(肺、肝、膀胱)癌症而提前避免的死亡/年,后者的值约为古吉拉特邦内部癌症的 0.001%,反映了古吉拉特邦地下水砷危害相对较低。