在采矿区的土壤重金属的三维定量来源分配
Mengyao Jia1, Lina Dang1, Yong Yang1
1College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China; Hubei Key Laboratory of Soil Environment and Pollution Remediation, China; Key Laboratory of Arable Land Conservation (Middle and Lower Reaches of Yangtze River), Ministry of Agriculture, China.
Journal of hazardous materials
|December 19, 2025
概括
这项研究在3D中绘制了土壤重金属的地图,确定了矿山和尾矿池作为主要的人为来源. 这些发现有助于控制采矿区的污染.
科学领域:
- 环境科学 环境科学
- 地质化学 地质化学
- 空间分析 空间分析
背景情况:
- 土壤重金属化物 (HM) 构成重大环境风险,特别是在采矿地区.
- 了解HM的3D空间分布和来源对于有效的环境管理至关重要.
研究的目的:
- 使用混合3D kriging与深度函数 (3DK_DF) 方法生成土壤HM的3D空间分布.
- 通过使用绝对主要组件得分和神经网络模型进行主要组件分析,对HM进行3D源分配.
- 确定和量化特定人为来源对土壤HM污染的贡献.
主要方法:
- 采用混合3D kriging与深度功能 (3DK_DF) 进行空间插值.
- 使用主要组件分析与初始来源分配的绝对主要组件分数.
- 应用神经网络模型,进一步量化特定人为来源的贡献.
主要成果:
- 作为,Cd,Co,Cu,Pb和Zn主要是人为的;Cr和Ni主要是天然的.
- 矿山和尾矿池是0-80厘米深度内的土壤HM的主要贡献者 (26.50%-31.78%和23.48%-30.38%).
- HM迁移显示出外向和下降的趋势,其度变化取决于来源类型和HM物种.
结论:
- 集成的3D空间插值和源分配模型有效地区分了主要的人为HM污染源.
- 为准确识别和控制采矿区污染类型提供关键数据.
- 在复杂的工业环境中提供了一个管理土壤污染的框架.
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