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根据正矩阵因子分解 (PMF) 和同位素指纹识别,土壤中的重金属 (化物) 的分配

Junhao Cao¹, Jing Guo¹, Huading Shi²

¹School of Environment, Tsinghua University, Beijing, 100084, China.

Journal of environmental management

|November 16, 2025

概括

识别土壤中的重金属来源对于污染控制至关重要. 这项研究使用地质统计学,正矩阵因子化 (PMF) 和同位素分析来确定中国农村的污染来源,为补救提供了可靠的框架.

科学领域:

环境科学环境科学
地质化学地质化学
土壤科学土壤科学

背景情况:

土壤中的重金属化物污染对生态系统和人类健康构成重大风险.
准确的来源识别对于有效的污染控制和风险管理策略至关重要.
中国的农村地区,如田县,面临着严重的土壤污染挑战.

研究的目的:

确定和量化来自中国一个污染的农村地区土壤中的19种重金属化物来源.
为了整合地缘统计分析,正矩阵分解 (PMF) 和 (Pb) 同位素指纹,以实现稳健的来源分配.
为了解复杂的土壤污染源提供一个透明和可重复的框架.

主要方法:

收集和分析了120个环境样本,包括70个表面土壤.
应用地质统计分析来描述重金属的空间分布.
利用正矩阵分解 (PMF) 来解决污染源和 (Pb) 同位素指纹用于验证.

主要成果:

PMF确定了四个主要来源:母体材料,灌,大气沉积和农业活动.
农田土壤显示 (As) 和 (Cd) 的丰富;林地土壤在和 (Sb).
灌是Cd的主要来源,而大气沉积对Sb和Pb有很大的贡献. Pb同位素验证证实了PMF的结果,差异≤2.2%.

结论:

综合的PMF-Pb同位素方法有效地解开重叠的土壤污染源.
这种方法在复杂的农村环境中提高了来源分配的可靠性.
这些发现为指导污染土壤的污染控制和修复工作提供了可行的证据.

关键词:

重金属的化物 (loid) 类型同位素追踪是一种同位素追踪.在PMF中,PMF是指PMF.土壤污染土壤污染源标识来源的标识

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