创新的湖泊污染分析:通过先进的多变量聚类技术揭示污染源
Minakshi Mishra1,2, Anupam Singhal1, Srinivas Rallapalli3
1Birla Institute of Technology and Science, Pilani, Rajasthan, 333031, India.
Environmental management
|July 29, 2024
概括
这项研究引入了一种新的多变量分析方法,用于识别污染的湖泊和关键污染物,如导电性,酸盐,BOD,便和总大肠杆菌. 这些发现支持可持续湖泊管理的有针对性的污染控制.
科学领域:
- 环境科学 环境科学
- 水质管理水质管理
- 生态系统健康 生态系统健康
背景情况:
- 湖泊是重要的饮用水源,日益受到人为污染的威胁.
- 污染的湖泊通过水传播疾病损害生态系统和人类健康.
- 需要有效的方法来识别受污染的湖泊及其特定污染物.
研究的目的:
- 开发一种新的多变量方法来识别受污染的湖泊和关键污染物.
- 分析物理,化学和生物水质参数之间的相关性.
- 用印度湖泊的案例研究来证明该方法的有效性.
主要方法:
- 采用先进的层次聚类和多变量分析 (R模式和Q模式).
- 生成旋转组件矩阵,树状图,单图和双图.
- 对印度班加罗尔的五个湖泊和一个位于印度查和克什米尔的湖泊进行了案例研究.
主要成果:
- 确定导电性,酸盐,生物氧需求 (BOD),总胆固醇菌 (TC) 和便胆固醇菌 (FC) 作为关键污染物.
- 因子分析揭示了四个主要组成部分,解释了85%的差异.
- 成功确定了污染热点和污染源.
结论:
- 拟议的方法有效地识别污染的湖泊和关键污染物.
- 建议以源控制污染和综合流域管理为湖泊的恢复.
- 强调持续监测可持续湖泊开发和改善水质.
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