小尺度多来源多介质土壤重金属污染估算模型构建

The identification and apportionment of pollution sources is a necessary prerequisite for pollution prevention and control and risk management of heavy metals in soils. Modelling approach of source identification and apportionment including multivariate statistical analysis, GIS-based spatial analysis methods and geostatistics have been extensively studied. However, mature analyzing methods are shortage aiming at multi-source and multi-media pollution of heavy metals in soils. The difficulty lies in that a universal method for meeting different regional scales and pollution properties is not able to be established. This study will assess the pollution of heavy metals in soils under different pathways and media from three dimensions, physical geography, soil geochemistry and socio-economy. We will identify the main pathway, the range and the extent of heavy metal (lead and cadmium) pollution in agricultural soils at a town scale. Stochastic gradient boosting is used in combination with regional pollution features and the characteristics of pollution sources. Random forest model and cross validation are applied for the validation and optimization of prediction results. A model for estimating the multi-source and multi-media pollution of heavy metals in agricultural soils is developed. Multi-channel pollution sources in agricultural soils are identified and apportioned quantitatively. This will provide a scientific basis for the rational prevention and the draft of management measures of heavy metal pollution in soils. The innovation of this study is: A model for estimating the multi-source and multi-media pollution of heavy metals in agricultural soils is developed based on stochastic gradient boosting in combination with regional pollution features and characteristics of pollution sources.

污染源解析是土壤重金属污染防控和风险管理的必要前提，多变量统计分析、基于GIS空间分析和地统计学方法的源解析模型方法已有广泛的研究，但针对小尺度多来源多介质土壤重金属污染缺乏成熟的解析方法，其难点在于无法建立针对不同区域尺度和污染特性的普适性方法。本项目从自然地理、土壤地球化学及社会经济三个维度，研究不同污染途径和污染相态下的土壤重金属污染。通过识别镇域尺度农田土壤重金属铅和镉的主要污染途径、范围和程度，基于随机梯度提升模型结合区域土壤重金属污染特征与来源特性，应用交叉检验和随机森林模型进行验证与优化，建立小尺度多来源多介质农田土壤重金属污染估算模型, 实现农田土壤多途径污染源解析及其贡献率的定量分析，为合理防控土壤重金属污染及制定管理措施提供科学依据。其创新在于：通过应用随机梯度提升模型结合区域土壤重金属污染特征与来源特性，建立小尺度多来源多介质农田土壤重金属污染估算模型。

污染源解析是土壤重金属污染防控和风险管理的必要前提，但针对小尺度多来源多介质土壤重金属污染缺乏成熟的解析方法，其难点在于无法建立针对不同区域尺度和污染特性的普适性方法。本项目从自然地理、土壤地球化学及社会经济三个维度，研究了不同污染途径和污染相态下的土壤重金属污染。基于随机梯度提升模型结合区域土壤重金属污染特征与来源特性，应用交叉检验和随机森林模型进行验证与优化，建立了小尺度多来源多介质农田土壤重金属污染估算模型, 实现了农田土壤多途径污染源解析及其贡献率的定量分析，结果表明董塘镇土壤、大气和水体重金属Pb和Cd污染空间分布以点源污染为主，污染集中在以丹霞和凡口冶炼厂为中心，6500米为半径的区域。涉重金属企业凡口矿、丹霞冶炼厂和华粤电厂对董塘镇土壤Pb含量的贡献最大，贡献率超过60%，自然源土壤Pb的背景值对董塘镇土壤Pb含量的贡献次之，为12%。人类源对董塘镇土壤Cd含量的贡献最大，其中人口密度的贡献率为17.5%，丹霞冶炼厂的贡献率为15%，水源中Cd的含量的贡献率为13.8%。自然源土壤Cd的背景值的贡献率为13%。本研究为合理防控土壤重金属污染及制定管理措施提供了科学依据。