Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Department of Land Resource Management, School of Tourism and Urban Management, Jiangxi University of Finance and Economics, 330013, Nanchang, China.
Environ Geochem Health. 2022 Feb;44(2):579-602. doi: 10.1007/s10653-021-00881-7. Epub 2021 Apr 2.
The source identification and apportionment of heavy metals (HMs) is a vital issue for restoring contaminated soil. In this study, qualitative approaches [a finite mixture distribution model (FMDM) and raster-based principal components analysis (RB-PCA)] and a quantitative approach [positive matrix factorization (PMF)] were composed to identify and apportion the sources of five HMs (Cd, Hg, As, Pb, Cr) in Wenzhou City, China, using several crucial auxiliary variables. An initial ecological risk assessment suggested that the ecological risk level in the study area was generally considered low, with the greatest contamination contributions coming from Cd and Hg. The result of the FMDM showed that Cd and Pb fit a single log-normal distribution, Hg fit a double log-normal mixed distribution, and As and Cr presented a triple log-normal distribution. Each element was identified and separated from its natural or anthropogenic sources. A map of RB-PCA combined with an analysis of corresponding auxiliary variables suggested that the three main contribution sources in the entire study area were parental materials, industrial and agricultural mixed pollution, and mining exploration activities. Each element was discussed, using the PMF model, with regard to its quantitative contributions. Parental materials contributed to all elements (Cd, Hg, As, Pb, Cr) at 89.22%, 7.31%, 35.84%, 84.81% and 27.42%, respectively. Industrial emissions and agricultural inputs mixed pollution contributed 2.94%, 80.77%, 15.93%, 4.79%, and 25.63%, respectively. Mining activities contributed 7.84%,11.92%, 48.23%, 10.40% and 46.95%, respectively, to the five HMs. Such result could be used efficiently to generate scientific decisions and strategies in terms of decision-making on regulating HM pollution in soils.
重金属(HM)的来源识别与分配对于污染土壤的修复至关重要。本研究采用定性方法[有限混合分布模型(FMDM)和基于栅格的主成分分析(RB-PCA)]和定量方法[正定矩阵因子分解(PMF)],结合多个关键辅助变量,识别并分配中国温州市五种重金属(Cd、Hg、As、Pb、Cr)的来源。初步的生态风险评估表明,研究区域的生态风险水平普遍较低,Cd 和 Hg 对污染的贡献最大。FMDM 的结果表明,Cd 和 Pb 符合单对数正态分布,Hg 符合双对数正态混合分布,As 和 Cr 呈现三重对数正态分布。每个元素都从其自然或人为来源中被识别和分离出来。RB-PCA 图谱结合相应辅助变量的分析表明,整个研究区域的三个主要贡献源是母质、工农业混合污染和矿业勘探活动。利用 PMF 模型,讨论了每个元素的定量贡献。母质对所有元素(Cd、Hg、As、Pb、Cr)的贡献分别为 89.22%、7.31%、35.84%、84.81%和 27.42%。工业排放和农业投入混合污染分别贡献 2.94%、80.77%、15.93%、4.79%和 25.63%。矿业活动分别贡献 7.84%、11.92%、48.23%、10.40%和 46.95%。这些结果可以有效地用于制定科学决策和战略,为调节土壤中重金属污染提供决策依据。