在易受污染的农业城市解开综合地下水管理:一种结合概率风险,来源分配和人工智能的协同方法
Xiao Yang1, Jiayi Du2, Chao Jia1
1Institute of Marine Science and Technology, Shandong University, Qingdao 266237, China; Shandong Engineering Research Center for Environmental Protection and Remediation on Groundwater, Jinan 250014, China.
Journal of hazardous materials
|November 20, 2024
概括
来自农业的地下水污染对健康构成风险. 化物和酸盐是关键的非致癌危害,农业被确定为主要的污染源,需要针对性的人工智能驱动的战略.
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:
- 地下水对于农业城市至关重要.
- 强化农业和使用肥料会增加污染风险,特别是非致癌性健康危害.
- 了解污染源和影响对于保护水资源至关重要.
研究的目的:
- 确定地下水污染源及其对农业城市健康的影响.
- 通过综合环境水质指数 (CEWQI) 评估地下水质量.
- 利用基于人工智能的区分制定有针对性的预防和控制策略.
主要方法:
- 分析了115个地下水样本.
- 蒙特卡洛风险评估的应用对健康危害的评估.
- 使用正矩阵因子化 (PMF) 模型来识别污染源.
- 在战略规划中采用基于人工智能的区分.
主要成果:
- 地下水化学类型主要是HCO3-Na·Ca.
- 在Mg2+,HCO3-,F-,总硬度 (TH) 和Mn的显著超标.
- 平均CEWQI表明地下水的整体质量良好,尽管城市和东部地区的质量较差.
- 化物 (F−) 和化物 (NO3−) 构成非致癌风险,而NO3−更为令人担忧.
- 自然地质过程和农业活动是污染的主要来源.
- 人工智能区划确定了工业和高化物区域作为关键区域.
结论:
- 地下水质量一般很好,但特定的污染物会给健康带来风险.
- 农业是地下水污染的一个重要的人为因素.
- 人工智能驱动的区分为有针对性的水资源管理和污染控制提供了有效的策略.
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