通过多变量统计方法和制定基于PCA的污染指数来评估饮用水质量
Srishti Srivastava1, Abdul Malik1
1Department of Agricultural Microbiology, Faculty of Agricultural Sciences, Aligarh Muslim University, Aligarh 202002, UP, India.
Journal of contaminant hydrology
|October 31, 2025
概括
在城市地区,安全饮用水是一个挑战. 这项研究使用先进的统计数据来评估水质,发现表面和地下水中存在严重污染,细菌具有高抗生素耐药性.
科学领域:
- 环境科学 环境科学
- 公共卫生 公共卫生
- 水质管理水质管理
背景情况:
- 确保安全饮用水是一个关键的全球挑战,特别是在快速城市化,地下水压力和半干旱地区.
- 传统的水质监测方法往往缺乏统计整合和整体风险评估能力.
- 半干旱地区面临着对水资源的独特压力,加剧了公众健康和可持续性问题.
研究的目的:
- 评估水压地区饮用水源的物理化学,重金属和细菌学污染.
- 评估来自受污染饮用水的细菌分离物的抗生素耐药性概况.
- 应用先进的多变量统计框架,以加强水质评估和风险分层.
主要方法:
- 来自地表和地下水源的167个饮用水样本的分析.
- 对物理化学参数,重金属,细菌学指标 (大肠杆菌,大肠杆菌) 和抗生素耐药性的评估.
- 主要组件分析 (PCA) 用于饮用水污染指数 (DWCI),马哈拉诺比斯距离 (MD) 用于异常值检测和K-平均集群的应用.
主要成果:
- 检测到严重的污染,多个样本超过了世卫组织对TDS,化物,和的限制.
- 高微生物负载和频繁超越大肠杆菌和大肠杆菌总体安全值,表明便污染.
- 93.6%的大肠杆菌分离物表现出多种药物耐药性,具有高的多种抗生素耐药性指数 (MARI),地下水污染率始终较高.
结论:
- 综合的多变量统计技术有效地描述了饮用水中复杂的污染模式.
- 开发的DWCI框架为水质监测和基于风险的监管提供了一种可复制和具有成本效益的方法.
- 研究结果支持实现可持续发展目标6 (SDG-6) 的努力,即在水资源紧张的环境中获得安全饮用水.
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