基于随机模拟与三角模糊数耦合的重金属污染评价模型

基于河流环境系统中随机性、模糊性等多种不确定信息共存的特性,采用蒙特卡罗方法模拟三角模糊数,并将其应用到沉积物重金属污染评价领域,通过将各重金属实测含量及地球化学背景值三角模糊化,然后进行随机模拟,并结合各等级概率水平加权进行综合污染等级分析,建立了基于随机模拟与三角模糊数(SS-TFN)理论的沉积物重金属地累积指数评价模型.采用该模型对湘江长沙段沉积物中重金属污染状况进行评价.结果表明,Cd的污染程度最大,处于严重污染级别;其次为Zn和Hg,处于重度污染级别,并有向严重污染恶化的趋势;而其他重金属污染程度则较低.相对于确定性评价方法,该模型能够得出评价区域重金属地累积指数的可能值区间及其相应的概率水平,客观真实地综合表征沉积物中重金属分布及污染情况,为科学决策提供更多全面合理的信息.

A heavy metal pollution assessment model of river sediment by coupling stochastic simulation with triangular fuzzy numbers

Based on the coexistence of stochastic and fuzziness river environment system, the triangular fuzzy numbers simulated by Monte Carlo method were introduced to the heavy metal pollution assessment in sediment. The concentrations of each heavy metal and geochemical background values were expressed as triangular fuzzy numbers and then were stochastically simulated for pollution analysis by combining the weighting of the probability of each grade. The model of geoaccumulation index was established on the basis of the stochastic simulation and triangular fuzzy numbers (SS-TFN) theory. This model was used to evaluate the heavy metal pollution in the sediment of Xiangjiang River in Changsha. The results showed that Cd level was highest and in the serious pollution level. Zn and Hg levels were lower and in the serious pollution level. Pollution levels of other heavy metals were low. Compared with the deterministic method, both the possible ranges and their probabilities of the heavy metal geoaccumulation index can be calculated conveniently and quickly using this model. Therefore, this model characterizes the distribution and pollution status of heavy metal in sediment objectively and accurately, and provides more comprehensive information for scientific decision-making.