基于模拟方法的城市土壤重金属污染风险评估及不确定性分析

Environment and health of the soil are closely linked with the developments of industrialization, agriculture, tranpotation and urbanization. It is important to identify the resources of heavy metal pollution to control and phytoremediation.Firstly, the spatil distribution of soil heavy metal will be realized, Especially the maximum and minimum values will be reserved. Currently, geostatistical interpolation, Kriging, is increasingly used to estimate pollutant concentrations in soils. However, the traditional method - - kriging-based approach will bring the smoothing effect in the result. The detailed spatial patterns of pollutants could, therefore, be lost. The simulation method, Sequential indicator simulation(SIS), which has the ability to model not only single, but also multi-location uncertainties will be introduced to get the ideal results. Based on the SIS realizations, the local uncertainty of heavy metal concentrations at a specific location, refers to the probability of heavy metal concentration being higher than the defined threshold, representing the probability of contamination on single point can be found. Moreover, the multi-location uncertainty of an area, refers to the probability of heavy metal concentrations in several locations in a certain area, being higher than the threshold can be calculated. It can be used to assess the reliability of delineation for regions suspected of contamination, which has been delineated as contaminated. Then, the health risks of heavy metals were assessed independently by the RBCA model. The uncertainty of the input variable will transfer to the result of resources. It will facilitate the decision making progress in determing which areas are contaminated and require cleanup action.

在工业、农业、交通及城市生活多重环境压力下，城市土壤受重金属污染，质量明显下降。对城市土壤重金属污染进行生态风险分析，从源头上加以控制，对实施污染治理具有十分重要的意义。研究的主要内容包括：土壤重金属空间分布多重模拟、污染"极值点"的探测、土壤重金属污染生态风险分析及定量不确定性分析。课题采取的技术路线包括基于实地采样数据的空间分布模拟与验证，基于美国RBVA模型的土壤重金属污染风险评价，及其对评价结果的定量不确定性分析。课题目标拟通过引入序贯指示模拟方法获取等概率土壤重金属空间分布，一方面避免传统的克里格插值方法平滑效应掩盖重金属分布的极值点，另一方面获取城市土壤重金属分布的各种可能结果。将该结果传递到城市土壤重金属风险评价结果，对风险等级配以定量不确定性分析，为决策者进行土壤治理提供科学的依据。

项目以山东省聊城市8个县作为研究区域，进行2Km格网的土壤表层20cm重金属元素采样数据研究。共获得样本数据2180个，在每个样点基础上，提取As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn共8种土壤重金属污染数据。项目首先以县域为单位进行采样点变异函数分析，得出8个县的重金属元素Hg均分布异常。仅茌平、阳谷、临清除Hg以外的其他土壤重金属分布变异正常。其他县均存在较多重金属的变异函数分布异常情况。在此基础上，项目利用高斯序列模拟方法完成8个县变异函数相对正常的土壤重金属元素空间分布模拟，并以山东省土壤环境背景值为阈值，进行各县土壤重金属元素的概率分布。鉴于数据的完备性，对茌平、阳谷两县模拟结果进行分析得出：茌平的重金属元素Zn和Ni的污染中度，而Cd, Hg 和As的污染情况非常严重，几乎整个县城80%的区域有90%的概率会超过阈值。高污染区集中在研究区域的中东部及南部。阳谷的重金属元素Zn, As, 及Ni的污染中度，而重金属元素Cd的污染在研究区域非常严重，几乎整个县城80%的区域有90%的概率会超过阈值。高污染区域主要集中在东部及南部区域。其次，项目以茌平重金属元素As为研究目标，进行不同模拟次数的极值区域识别。分析表明，不同模拟次数在四分之一分位，二分之一分位相对变化较大，但在定义为极大值区域的四分之三分位，基本稳定在1.8%左右。极大值的重污染区域，最终都集中在1000次模拟结果的两簇红色斑块内。模拟预测结果共有8736个像元点，其中大概有160个像元属性值超过四分之三分位，构成了本县的重度污染区域。最后，项目以茌平，阳谷两县为例进行生态风险评估。得出重金属元素Hg是茌平的主要生态风险引发因子，其潜在风险评估指数高达200。所有重金属元素引发的综合生态风险评价为中度，其指数为278.34。与土地利用类型叠加分析表明，高污染区域集中在耕地，傍徒骇河沿岸，与工业分布无关。而对于阳谷，重金属元素Cd为主要生态风险引发因子，潜在风险评估指数接近80。所有重金属元素引发的综合生态风险为轻度等级。