基于Monte Carlo-Hakanson模型的土壤重金属生态风险评价研究

Reducing uncertainty in ecological risk assessment for heavy metal contamination based on Monte Carlo–Hakanson model

为了降低土壤重金属生态风险评价中的不确定性,以某实际搬迁后铅蓄电池场地的土壤中重金属Cr、As、Pb、Cu、Zn含量实测值为基础数据,将Monte Carlo模拟引入Hakanson生态危害指数法中,构建Monte Carlo-Hakanson模型,主要通过对重金属含量这一随机变量进行抽样,将得到的大量可靠预测值代入Hakanson指数模型,重复计算模型中的函数值,得到场地生态风险等级及处于各生态风险等级的概率,以此来降低生态风险评价中的不确定性。案例结果如下:研究区生态风险隶属于较高等级,概率为49.44%,Pb的敏感度最高,达到了99.7%,对场地的污染起主导作用。Monte Carlo-Hakanson模型的应用有效降低了类似场地的土壤重金属生态风险评估的不确定性,为获得土壤重金属生态风险评估结果的准确性提供了一个新的思路和方法。

A new analysis model is required to reduce the uncertainty in ecological risk assessment of heavy metals in soil. Based on the content data of heavy metals such as Cr, As, Pb, Cu, and Zn in the soil of the lead storage battery site after relocation, Monte Carlo simulation was introduced into the Hakanson ecological hazard index method to develop Monte Carlo –Hakanson model. The model primarily samples the random variable of heavy metal content, substitutes a large number of reliable prediction values in the Hakanson index model, and repeatedly calculates the function value in the model to obtain the ecological risk level of the site and the probability of being in different ecological risk levels, which reduce the uncertainty in ecological risk assessment. The results of the study are as follows:the ecological risk of the study area is at a higher level with the probability reaching 49.44%. The sensitivity of Pb is the highest, reaching99.3%, which plays a major role in polluting the site. The application of this method can effectively reduce the uncertainty in heavy metal ecological risk assessment of soil in similar sites and provide a new stratagem to obtain accurate results.