基于复合模型的河流沉积物重金属污染源解析及不确定性研究

项目名称： 基于复合模型的河流沉积物重金属污染源解析及不确定性研究

项目编号： No.41303069

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 天文学、地球科学

项目作者： 陈海洋

作者单位： 北京师范大学

项目金额： 25万元

中文摘要： 面对河流重金属污染的严峻形势，开展污染源解析研究，准确识别重金属的自然和人为来源及其贡献程度，是当前流域重金属污染防控领域具有挑战的热点问题之一。受体模型是一类较为通用的源解析技术，然而，鉴于河流环境系统的开放性，以及重金属化学行为的复杂性，单一受体模型应用于河流重金属源解析的适应性、可靠性及不确定性值得深入研究。本研究拟从环境科学、地球化学、水力学、概率统计学以及人工智能的交叉视角，在辨识河流沉积物重金属污染的源排放特征及迁移转化的基础上，开展基于"非负约束因子分析-化学质量平衡/支持向量机"复合模型的河流沉积物重金属污染源解析研究，系统阐明复合模型源解析的逻辑机理，深入揭示影响复合模型解析不确定性的关键因素，并以鄱阳湖流域乐安河沉积物重金属源解析为例进行研究验证。项目成果将为河流重金属污染控制、生态修复、总量减排、污染事故调查提供科技支撑，也能为乐安河重金属污染防控提供科学依据。

中文关键词： 重金属；源解析；受体模型；不确定性；乐安河

英文摘要： Due to their environmental persistence and biogeochemical recycling and ecological risks, heavy metal pollution become a major problem related to aquatic environmental safe. Thus, according to the contamination features of heavy metals, using quantitative methods to accurately identify natural and anthropogenic sources and apportion their contributions is one of the challenging and hot issues in the fields of pollution prevention and control of heavy metals in the aquatic environment. Receptor model is a general approach for source apportionment. However, due to the openness of water environment system, as well as the complexitiess of the chemical behavior of heavy metals, the adaptabilities, accuracies and uncertainties of receptor model for source apportionment of heavy metals in aquatic environment are worthy of to further study. In the cross-view point of environmental science, geochemistry, hydrogeology, statistics probability and artificial intelligence, the present research will identify the emission and transport mechanism of heavy metals in river sediments, and establish a methodological framework based on factor analysis with nonnegative constraint and chemical mass balance combined support vector machines for source apportionment of heavy metals. The critical problems of this study will concentrated o

英文关键词： Heavy metal；Source apportionment；Receptor model；Uncertainty；Le’An River