Environmental Epidemiology Group, Centre for Radiation, Chemical and Environmental Hazards, Public Health England (PHE), Chilton, Oxfordshire OX11 0RQ, UK.
London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK.
Int J Environ Res Public Health. 2017 Dec 1;14(12):1490. doi: 10.3390/ijerph14121490.
Approximately one million people in the UK are served by private water supplies (PWS) where main municipal water supply system connection is not practical or where PWS is the preferred option. Chronic exposure to contaminants in PWS may have adverse effects on health. South West England is an area with elevated arsenic concentrations in groundwater and over 9000 domestic dwellings here are supplied by PWS. There remains uncertainty as to the extent of the population exposed to arsenic (As), and the factors predicting such exposure. We describe a hazard assessment model based on simplified geology with the potential to predict exposure to As in PWS. Households with a recorded PWS in Cornwall were recruited to take part in a water sampling programme from 2011 to 2013. Bedrock geologies were aggregated and classified into nine Simplified Bedrock Geological Categories (SBGC), plus a cross-cutting "mineralized" area. PWS were sampled by random selection within SBGCs and some 508 households volunteered for the study. Transformations of the data were explored to estimate the distribution of As concentrations for PWS by SBGC. Using the distribution per SBGC, we predict the proportion of dwellings that would be affected by high concentrations and rank the geologies according to hazard. Within most SBGCs, As concentrations were found to have log-normal distributions. Across these areas, the proportion of dwellings predicted to have drinking water over the prescribed concentration value (PCV) for As ranged from 0% to 20%. From these results, a pilot predictive model was developed calculating the proportion of PWS above the PCV for As and hazard ranking supports local decision making and prioritization. With further development and testing, this can help local authorities predict the number of dwellings that might fail the PCV for As, based on bedrock geology. The model presented here for Cornwall could be applied in areas with similar geologies. Application of the method requires independent validation and further groundwater-derived PWS sampling on other geological formations.
英国约有 100 万人使用私人供水系统（PWS），这些人主要由于市政供水系统连接不实际或 PWS 是首选而使用。慢性接触 PWS 中的污染物可能对健康产生不良影响。英格兰西南部是地下水砷浓度升高的地区，这里有超过 9000 处住宅通过 PWS 供水。目前仍不确定有多少人接触到砷（As），以及预测这种接触的因素。我们描述了一种基于简化地质的危害评估模型，该模型有可能预测 PWS 中的砷暴露情况。2011 年至 2013 年，康沃尔郡记录有私人供水系统的家庭被招募参加一个水样采集计划。基岩地质被聚合并分为九个简化基岩地质类别（SBGC），加上一个横切的“矿化”区。在 SBGC 内随机选择采集 PWS 样本，大约 508 户家庭自愿参加了这项研究。通过探索数据变换来估计 SBGC 内 PWS 的砷浓度分布。根据每个 SBGC 的分布，我们预测会受到高浓度影响的住宅比例，并根据危害程度对地质进行排名。在大多数 SBGC 中，发现砷浓度呈对数正态分布。在这些地区，预计饮用水中砷浓度超过规定浓度值（PCV）的住宅比例从 0%到 20%不等。根据这些结果，开发了一个预测模型，计算了超过砷 PCV 的 PWS 比例和危害等级，支持当地决策和优先级排序。通过进一步的开发和测试，这可以帮助地方当局根据基岩地质预测可能超过砷 PCV 的住宅数量。这里为康沃尔提出的模型可以应用于具有类似地质的地区。该方法的应用需要独立验证和进一步对其他地质地层的地下水衍生的 PWS 采样。
