基于PMF和Pb同位素的农田土壤中重金属分布及来源解析

为阐明九龙江中下游沿岸农田土壤中重金属分布特征、污染现状及来源,测定了该区域土壤中Cr、Ni、Cu、Zn、As、Cd、Pb的含量及Pb同位素比值。结果显示研究区域过去20年土壤中重金属含量呈现上升趋势,其中Cd增长幅度最大;空间上,除Cd外,不同功能区组间重金属差异显著,反映出研究区域受到了人为活动的显著影响,高Cd浓度现象可能是农业污染造成的一种普遍的共有现象;潜在危害指数评价法显示该区域大部分站点属于中等生态风险区域,主要贡献因子为Cd;主成分分析法(PCA)和正定矩阵因子分析法(PMF)分析结果均显示土壤重金属主要来自5种污染源,PMF法得出这些污染源的贡献率大小依次为工业源(26.3%)交通源(23.2%)自然源(22.0%)农业源(16.2%)其他混合源(12.0%);三端源混合模型结合Pb同位素示踪法得到交通源、燃煤和工业源对九龙江土壤中重金属Pb的贡献率分别为57%、34%和9%。三种源解析方法所得结果吻合,三者均能较好地解析土壤中重金属,可以构成互补的多元源解析体系。

Distribution and source apportionment of heavy metals in farmland soils using PMF and lead isotopic composition

To identify the distribution characteristics, pollution status, and pollution sources of heavy metals in farmland soils of the Jiulong River Watershed, the concentrations of Cr, Ni, Cu, Zn, As, Cd, and Pb, along with the lead isotope ratios in the soils, were measured. The results showed that the concentrations of heavy metals in the soils have increased significantly in the studied region over the past two decades. Among all the heavy metals, the rate of increase in concentration was largest for Cd. Pronounced spatial gradients were observed in the concentrations of soil heavy metals at different functional areas, thereby indicating that human activities have important effects on soils in the Jiulong River Watershed. High concentrations of soil Cd associated with agricultural pollution were observed at all stations. The results of the potential hazard index assessment indicated that most studied areas were moderate ecological risk zones, with Cd being the major contributing factor. Principal component analysis (PCA) and positive matrix factorization (PMF) revealed five primary factors (pollution sources) with the following contribution rates:industrial emissions (26.3%), vehicle emissions (23.2%), natural sources (22.0%), agricultural activities (16.2%), and other mixed sources (12.0%). The results of the Pb isotopic mixing model demonstrated that Pb mainly originated from vehicle exhaust (57%), coal combustion (34%), and industrial emissions (9%). The results of the three methods used for source apportionment were in good agreement. Thus, these methods can be used complimentarily to effectively constrain heavy metals pollution sources.