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| Reducing uncertainty in ecological risk assessment for heavy metal contamination based on Monte Carlo–Hakanson model |
| Received:January 11, 2020 |
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| KeyWord:Monte Carlo-Hakanson model;assessment of ecological risk;uncertainty;heavy metal |
| Author Name | Affiliation | | XIONG Hong-bin | School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 230009, China | | CHEN Shen-jian | School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 230009, China |
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| Abstract: |
| 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, reaching 99.3%, 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. |
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