融合多源信息的某农药车间地块土壤氯仿三维空间预测研究  

Three-dimensional Mapping of Soil Chloroform at a Pesticide Workshop Region by Integrating Multi-source Auxiliary Information

作　　者：彭雨璇 陈剑 韩春媚 张家铭 李书鹏 赵永存[1,2,6] PENG Yu-xuan;CHEN Jian;HAN Chun-mei;ZHANG Jiaming;LI Shu-peng;ZHAO Yong-cun(State Key Laboratory of Soil and Sustainable Agriculture,Institute of Soil Science,Chinese Academy of Sciences,Nanjing 210008,China;University of Chinese Academy of Sciences,Beijing 100049,China;Technical Centre for Soil,Agriculture and Rural Ecology and Environment,Ministry of Ecology and Environment,Beijing 100012,China;Beijing Construction Engineering Group Environmental Remediation Co.Ltd.,Beijing 100015,China;National Engineering Laboratory for Site Remediation Technologies,Beijing 100015,China;University of Chinese Academy of Sciences,Nanjing 211135,China)

机构地区：[1]土壤与农业可持续发展国家重点实验室/中国科学院南京土壤研究所,江苏南京210008 [2]中国科学院大学,北京100049 [3]生态环境部土壤与农业农村生态环境监管技术中心,北京100012 [4]北京建工环境修复股份有限公司,北京100015 [5]污染场地安全修复技术国家工程实验室,北京100015 [6]中国科学院大学南京学院,江苏南京211135

出　　处：《土壤通报》2024年第5期1229-1238,共10页Chinese Journal of Soil Science

基　　金：国家重点研发计划项目(2019YFC1804902)资助。

摘　　要：【目的】准确刻画场地土壤污染物的三维(3D)空间分布,克服稀疏钻孔条件下传统空间插值的平滑效应。【方法】在某农药厂农药车间地块,采用场地多源辅助信息和钻孔数据构建了土壤-景观推理-反距离加权(SoLIMIDW)3D混合模型,预测场地土壤氯仿浓度的3D空间分布,并与传统空间插值方法(IDW和OK)进行比较。通过地理探测器评估多源辅助数据对土壤氯仿空间预测的影响。【结果】该地块氯仿污染热点主要分布在中部的农药车间表层至深层土壤以及东南部废水处理区的上层土壤中。SoLIM-IDW方法比IDW和OK方法空间预测精度更高,融合各辅助变量集的SoLIM-IDW模型空间预测R^(2)为0.37~0.39,RMSE为83.15~84.48 mg kg^(–1),通过空间预测结果计算的超标土方量为7024~7980 m^(3)。多源辅助信息存在交互作用,整合多源场地辅助信息比单一辅助信息获得了更高的精度。【结论】在成本有限、稀疏钻孔的条件下,充分利用易于获取、成本低廉的多源污染辅助信息有利于提高场地污染物3D空间预测、风险评估准确性。[Objective]The aim was to accurately map the three-dimensional(3D)spatial distribution of soil pollutants and overcome the smoothing effects of traditional spatial interpolation and achieve precise characterization of the 3D spatial distribution of soil pollutants under sparse borehole data conditions.[Method]A Soil-Landscape Inference-Mixed Inverse Distance Weighting(SoLIM-IDW)3D hybrid model was constructed using multi-source auxiliary information and soil borehole data.This model was employed to predict the 3D distribution of chloroform concentrations in the soil within a pesticide workshop region.The performance was compared with traditional spatial interpolation methods such as IDW and OK.The impact of multi-source auxiliary data on the spatial prediction of soil chloroform was evaluated using a geographic detector.[Result]The results indicated that chloroform contamination hotspots were mainly distributed in the surface to deep layers of soil in the central pesticide workshop,and the upper layer of the southeast wastewater treatment area.The SoLIM-IDW method exhibited higher spatial prediction accuracy,with R^(2) ranging from 0.37 to 0.39,and RMSE ranging from 83.15 to 84.48 mg kg^(–1).The estimated volume of soil exceeding the standard through spatial prediction ranged from 7024 to 7980 m^(3).Multi-source auxiliary information interacted,and the integration of the multi-source auxiliary data yielded higher accuracy compared to relying on a single auxiliary data source.[Conclusion]This study demonstrated that making full use of easily accessible and low-cost multi-source pollution auxiliary information under the conditions of limited cost and sparse boreholes contributes to improve the accuracy of 3D spatial prediction and risk assessment of site pollutants.

关 键 词：三维插值 空间分布 污染场地 辅助信息 

分 类 号：X825[环境科学与工程—环境工程]