Jang Cheng-shin, Liu Chen-wuing, Lu Kuang-liang, Lin Ching-chieh
Department of Leisure and Recreation Management, Kainan University, Luzhu, Taoyuan, Taiwan 338, Republic of China.
Environ Monit Assess. 2007 Nov;134(1-3):293-304. doi: 10.1007/s10661-007-9620-7. Epub 2007 Apr 25.
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 groundwater. According to a risk assessment model established in our previous research, the standard was set to 250 microg/l for aquacultural use, corresponding to the 77.1th percentile of observed concentrations. Misclassification 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.
本研究采用基于风险的指标分类方法,确定了台湾南部黑脚病高发地区砷污染地下水的范围。首先使用指示克里格法在每个单元格建立条件累积分布函数。然后采用三种方法——p分位数估计、E型估计和预期损失最小化——来划定符合地下水砷浓度监管标准的污染区域。根据我们之前研究建立的风险评估模型,水产养殖用水的标准设定为250微克/升,对应于观测浓度的第77.1百分位数。对分类方法的误分类风险和不确定性进行了检验。分析结果表明,使用0.771分位数估计时污染面积最大,而使用预期损失最小化时污染面积最小。对于这些分类方法,低风险可信污染区域与误报区域的比例保持恒定,为12.9% - 13.2%。为减少对人类健康的重大影响,在可信污染区应严格禁止使用受砷污染的地下水养殖鱼类,并对存在高误报风险的污染区进行持续监测。