Potential Ecological Risk Assessment For Heavy Metal Of Urban Dusts By Coupling Stochastic Simulation With Triangular Fuzzy Numbers

In this paper, with the characteristics of the coexistence of a variety of uncertain information in the potential ecological risk assessment of heavy metals in urban dust, including fuzziness, randomness and uncertainties, the theory of stochastic simulation and triangular fuzzy numbers was introduced to regional potential ecological risk assessment of heavy metals in urban dust in order to reduce the uncertainties in the evaluation and improve the confidence level. Source analysis was also combined with to identify heavy metal pollution sources and provide more scientific and comprehensive evaluation results for policymakers.Traditional pollution evaluation methods of heavy metals in urban dust and the comparative analysis of these methods were summarized in this article. Four kinds of main uncertainty theory were also summarized and the main sources of uncertainties in the evaluation process were illustrated. Aiming to decrease these uncertainties, triangular fuzzy numbers of the actual measurement concentration and the geochemical background values of heavy mental were developed, and then the corresponding stochastic simulation processes were performed. Afterwards, with the developed membership function, the results combined with the level of evidence were calculated. Finally, the potential ecological risk assessment method of heavy metals in urban dust was established by coupling stochastic simulation with triangular fuzzy numbers (SS-TFN, the stochastic simulation and triangular fuzzy numbers). In order to test and verify the developed assessment method, this method was applied to the potential ecological risk assessment of heavy metal in urban dust in Xiandao district of Changsha city. The results showed that the heavy metals of Cd, Cr, and Zn belonged to strong potential ecological risk level, slight potential ecological risk level, and slight potential ecological risk level, respectively. And99.7%of the potential ecological index simulation values of As belonged to slight potential ecological risk level. However, the membership degree distribution of the potential ecological index simulation values of Hg revealed certain existence of uncertainties in the potential ecological risk assessment of heavy metal in the area which may mislead the policymakers. The possibility of Hg belonging to the medium potential ecological risk level was77.04%, and the strong potential ecological risk level was22.89%. But the credibility of Hg belong to the slight potential ecological risk was relatively low (0.07%). Therefore, Cd and Hg should be listed as the priority control factor of the potential ecological risk in this area. But given the timeliness of country published related background values was finite and Cd pollution was spatial heterogeneity, it is suggested that the Cd pollution of urban dust in this area should be further investigated and rechecked in different regional. Source analysis was showed that the key pollution factors of heavy metal pollution in urban dust in Xiandao district were Cd and Hg, the pilot area of pollution was western and southern, the main sources of pollution were the industrial and mining production, transportation and living pollution emissions.The possible values range of heavy metal potential ecological risk index can be obtained with this developed method and the credibility of potential ecological risk degree that heavy metal belonged to can also be quantitative calculated. Through the example verification and contrastive analysis, it was found that the developed method made up for the deficiency of traditional deterministic method, and more comprehensive information about the urban dust was contained in the evaluation results. Besides, the computational efficiency of this method was higher than that of evaluation method solely based on triangular fuzzy numbers. Compared with the evaluation method solely based on stochastic simulation theory, this method was more suitable for little and poor data, and characterized the potential ecological risk degree of heavy metal in urban dust in evaluation region more actually and objectively. Therefore, this method can provide more comprehensive and scientific information for policy-making.