Modeling exposure risk and prevention of mercury in drinking water for artisanal-small scale gold mining communities

被引:6
|
作者
Morgan, V. L. [1 ]
Casso-Hartmann, L. [2 ]
Velez-Torres, I. [2 ]
Vanegas, D. C. [3 ]
Munoz-Carpena, R. [4 ]
McLamore, E. S. [4 ]
Kiker, G. A. [4 ]
机构
[1] Univ Illinois, Urbana, IL 61801 USA
[2] Univ Valle, Cali, Colombia
[3] Clemson Univ, Clemson, SC USA
[4] Univ Florida, Gainesville, FL USA
来源
HUMAN AND ECOLOGICAL RISK ASSESSMENT | 2021年 / 27卷 / 06期
关键词
mercury; hazard quotient; artisanal small-scale gold mining; global sensitivity uncertainty analysis; Monte Carlo filtering;
D O I
10.1080/10807039.2020.1855576
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
The goal of this study was to evaluate the age-differentiated health risks associated with exposure to mercury in drinking water from artisanal small-scale gold mining (ASGM) sites on nearby communities in Yolombo, Colombia. In 2017, nine samples were collected from a local regulatory agency to report mercury concentrations in locations near mining sites. We performed a risk assessment to find 100% of the water samples collected downstream of mining sites exceed Hazard Quotient (HQ) risk thresholds (set by the US-Environmental Protection Agency and Health Canada). HQ model, coupled with global sensitivity and uncertainty analysis (GSUA), was used to conclude infants as the most vulnerable, with 50% of the population exceeding HQ thresholds. Length of exposure was the most significant input that contributed to risk variance, explaining 30-55% of risk across all age groups. Monte-Carlo filtering was used to identify effective strategies to reduce the number of individuals exceeding allowable HQ thresholds. After Monte-Carlo filtering intervention strategies, all individuals are below HQ thresholds. This work shows the importance of combining risk assessment tools with sensor data to inform the need for filters, stakeholder education, and alternative mining approaches to gain a multi-perspective risk approach. This work provides a valuable risk and decision modeling methodology and baseline information to gain a deeper understanding of the probability of experiencing detrimental health effects from water contamination in ASGM communities.
引用
收藏
页码:1492 / 1508
页数:17
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