使用机器学习策略破译地质化学指纹和地下水化物污染在矿区的健康影响
Rupsha Nandi1, Sandip Mondal2, Jajati Mandal3
1Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, Jharkhand, 815301, India.
Environmental geochemistry and health
|August 27, 2024
概括
矿开采污染了地下水的化物,造成健康风险,特别是对儿童. 先进的分析显示,40%的样本含有高化物水平,需要紧急监测和干预采矿受影响的地区.
科学领域:
- 环境科学 环境科学
- 水文地质学 水文地质学
- 公共卫生 公共卫生
背景情况:
- 矿开采活动是地下水污染的潜在来源.
- 饮用水中的化物污染对健康构成重大风险,特别是非致癌效应.
研究的目的:
- 调查矿对地下水化物污染的贡献.
- 评估相关的健康危害,并确定影响污染的因素.
- 在受采矿影响的地区开发一个强大的地下水质量监测框架.
主要方法:
- 从矿区收集和分析地下水样本 (n=40).
- 经典含水层化学的应用,统计方法,自组织地图 (SOM) 和索波尔敏感度指数 (SSI).
- 使用危险系数 (HQ) 和水质指数 (WQI) 的健康风险评估 (HRA).
主要成果:
- 40%的地下水样本超过了世卫组织允许的化物限值 (1.5 ppm).
- 被化物污染的样本显示电导率显著提高,总溶解固体,总硬度,Na+和HCO3-.
- 卫生风险评估表明,大多数受污染的样本对儿童具有非致癌风险.
结论:
- 矿开采活动显著影响地下水质量,导致化物污染.
- 先进的建模技术 (SOM,SSI) 有效地识别污染源和健康风险.
- 地理空间分析和综合建模为矿业影响地区的积极地下水管理提供了坚实的框架.
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