Ecological Risk Assessment of Heavy Metals in Contaminated Soil Based on Engineering Fuzzy Set Theory

2010 ◽  
Vol 113-116 ◽  
pp. 815-818
Author(s):  
Yao Guo Wu ◽  
You Ning Xu ◽  
Si Hai Hu ◽  
Jiang Hua Zhang ◽  
Jian Guo Li

It is not easy to handle relativities of metals toxicology and ecological risk grades, especially, fuzzy in realization of soil heavy metal pollution, when the method suggested by Hakanson was used to assess ecological risk. To explore a better way to solve this problem, certainty in ecological risk grades was fuzzed through engineering fuzzy set theory, and a fuzzy mathematic model was built. The model was then applied in Xiaoqinling gold mining regional, which was selected as case study and where soil was polluted by heavy metals over decades, and its results were compared with that from Hakanson method. The results showed that the fuzzy mathematic model was a better way for ecological risk assessment of heavy metals in contaminated soil.

RSC Advances ◽  
2021 ◽  
Vol 11 (14) ◽  
pp. 8080-8095
Author(s):  
Shahla Karimian ◽  
Sakine Shekoohiyan ◽  
Gholamreza Moussavi

The toxic effects of heavy metals in landfill soils have become a significant concern for human health.


Toxin Reviews ◽  
2021 ◽  
pp. 1-16
Author(s):  
Mir Mohammad Ali ◽  
Mohammad Lokman Ali ◽  
Md. Refat Jahan Rakib ◽  
Md. Saiful Islam ◽  
Ahasan Habib ◽  
...  

1996 ◽  
Vol 118 (1) ◽  
pp. 121-124 ◽  
Author(s):  
S. Quin ◽  
G. E. O. Widera

Of the quantitative approaches applied to inservice inspection, failure modes, effects,criticality analysis (FMECA) methodology is recommended. FMECA can provide a straightforward illustration of how risk can be used to prioritize components for inspection (ASME, 1991). But, at present, it has two limitations. One is that it cannot be used in the situation where components have multiple failure modes. The other is that it cannot be used in the situation where the uncertainties in the data of components have nonuniform distributions. In engineering practice, these two situations exist in many cases. In this paper, two methods based on fuzzy set theory are presented to treat these problems. The methods proposed here can be considered as a supplement to FMECA, thus extending its range of applicability.


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