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首页> 外文期刊>Environmental Monitoring and Assessment >Delimitation of arsenic-contaminated groundwater using risk-based indicator approaches around blackfoot disease hyperendemic areas of southern Taiwan
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Delimitation of arsenic-contaminated groundwater using risk-based indicator approaches around blackfoot disease hyperendemic areas of southern Taiwan

机译:台湾南部黑脚病高流行地区周围地区基于风险的指标方法对砷污染地下水的划界

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摘要

This work determined scopes of arsenic (As)-contaminated groundwater using risk-based indicator classification approaches in blackfoot disease hyperendemic areas of southern Taiwan. Indicator kriging was first used to establish a conditional cumulative distribution function at each cell. Three approaches - the p-quantile estimate, the E-type estimate and the minimization of the expected loss -were then adopted to delimit contaminated regions for a regulated standard of As concentrations in ground-water. According to a risk assessment model established in our previous research, the standard was set to 250 μg/l for aquacultural use, corresponding to the 77.1th percentile of observed concentrations. Misclas sification risks and uncertainty were examined for the classification approaches. The analyzed results reveal that contaminated areas are the largest using the 0.771-quantile estimate, whereas they are the smallest using the minimization of the expected loss. Proportions of credible polluted areas with low risks to false positives maintain a constant, 12.9-13.2%, for the classification approaches. To reduce a great impact on human health, As-polluted groundwater should be strictly prohibited to cultivate fish in credible polluted zones and monitored persistently in polluted zones with high risks to false positives.
机译:这项工作使用基于风险的指标分类方法,在台湾南部的黑脚病高流行地区确定了被砷污染的地下水的范围。指标克里金法首先用于在每个单元格上建立条件累积分布函数。然后采用了三种方法-p分位数估计,E型估计和预期损失的最小化-划定了地下水中砷浓度标准的污染区域。根据我们先前研究中建立的风险评估模型,将水产养殖标准定为250μg/ l,相当于观察到浓度的77.1%。分类方法检查了错误分类的风险和不确定性。分析结果表明,使用0.771分位数的估算值,污染面积最大,而使用预期损失的最小值,污染面积最小。对于分类方法,具有低误报率的可信污染区域比例保持恒定,为12.9-13.2%。为了减少对人体健康的重大影响,应严格禁止砷污染的地下水在可信的污染区养殖鱼类,并在污染率高的地区进行持续监测,极有可能导致假阳性。

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