背景异常区土壤重金属修复目标值合理确定的方法研究:以浙江省某化工厂退役地块为例

Research on the Method for Reasonably Determining the Target Value of Soil Heavy Metal Anomaly Remediation:A Case Study of a Chemical Factory Decommissioning Site in Zhejiang Province

浙江某化工厂退役地块土壤砷检出明显异常(较多数据超GB 36600—2018《土壤环境质量建设用地土壤污染风险管控标准(试行)》第一类用地土壤砷评价筛选值20 mg·kg^(-1)),但其与该地块历史上生产过程中可能存在的人为砷污染的相关性较低,与自然地质高背景导致的局部土壤砷异常的相关性更高,需要系统开展地质地球化学背景调查后合理确定修复目标值。本文基于区域地质背景特征,系统开展背景调查与采样监测,识别出区域地层形成后的热液活动为土壤砷异常主导因素。运用数据统计方法,在剔除异常值后,选取95%置信区间〔即几何平均值(X g)乘除几何标准差(S),X_(g)/S_(2)~X_(g)S^(2)〕上限值(83.63 mg·kg^(-1))代表背景值。经分析验证,用该统计背景值作为修复目标值合理可行,且较常规方法可较大程度地减少需修复土壤方量(本地块达6.5万m^(3))。本文形成的背景调查和背景值确定方法适用于高背景异常区土壤调查和治理工作,可有效避免过度调查和过度修复。

The soil arsenic detected at a decommissioned chemical plant site in Zhejiang Province is significantly high than the screening value of 20 mg·kg^(-1).However,the correlation with potential anthropogenic arsenic contamination from historical industrial activities is low,whereas the correlation with local soil arsenic anomalies,attributed to the high natural geological background,is higher.It is necessary to systematically determine the restoration target value after the geological and geochemical background survey.Based on the regional geological background features,this study conducted background investigations and sampling,and identified that hydrothermal activity as the predominant factor for soil arsenic anomalies in the region.Statistical methods were employed to determine the upper limit of the 95%confidence interval(mean±3 standard deviations)at 83.63 mg·kg^(-1),representing the background value after outlier removal.Analysis and verification indicate that using this statistical background value as a remediation target is reasonable and feasible,and can potentially reduce the volume of soil requiring remediation by up to 65000 m^(3)compared to conventional methods.The proposed method for background investigation and value determination is applicable to soil investigation and treatment in areas with high natural background anomalies,effectively avoiding over-investigation and over-remediation.