通过非参数估计方法优化了含有大量化物和酸盐的地下水中人类健康风险 (HHR) 的新概率评估过程
Jiaheng Yan1, Jiansheng Chen2, Wenqing Zhang3
1College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, PR China; Faculty of Architecture and Civil Engineering, Huaiyin Institute of Technology, Huaian 223003, PR China.
Water research
|July 29, 2023
概括
这项研究引入了核密度估计 (KDE) 来评估地下水中的化物和酸盐对人类健康的风险. 精细的概率方法准确量化风险,有助于环境健康评估.
科学领域:
- 环境科学 环境科学
- 毒理学 毒理学 毒理学
- 水文地质学 水文地质学
背景情况:
- 地下水被化物 (F-) 和酸盐 (NO3-) 污染对人类健康构成重大风险.
- 目前,评估这些健康风险的定量方法有限.
- 现有的评估方法可能不能准确地反映污染物的复杂分布.
研究的目的:
- 开发和优化一种概率方法,用于评估地下水中的F-和NO3-相关的人类健康风险 (HHR).
- 在随机模拟中引入内核密度估计 (KDE),以提高风险评估的准确性.
- 通过结合概率学和确定学方法,评估元市的HHR.
主要方法:
- 核心密度估计 (KDE) 用于建模F和NO3度,克服了常见概率密度函数 (PDF) 的局限性.
- 使用随机模拟,包括蒙特卡洛,来评估超过污染物标准的可能性.
- 科尔莫戈罗夫-斯米尔诺夫测试验证了KDE方法的高准确度.
- 全球敏感性分析确定了影响HHR的关键因素.
主要成果:
- 在F和NO3度方面,KDE方法表现出高的适配精度,通过了科尔莫戈罗夫-斯米尔诺夫测试.
- 概率评估表明,儿童的酸盐标准超越的概率为21.95%,成人为15.14%.
- 由于过多的化物,儿童的HHR概率较低 (4.14%) 被概率方法强调.
- 对酸盐污染的敏感性分析显示,对HHR (>0.1) 的影响最大,其次是用水习惯 (>0.01).
结论:
- 该研究提出了一种精细的概率评估方法,用于从地下水污染物的HHR.
- 与随机模拟相结合,KDE提供了一个比传统方法更准确的方法来量化健康风险.
- 这些发现为了解地下水质量和管理相关健康风险提供了科学基础.
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