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Volume 35 Issue 3
Jun.  2016
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Article Contents
SUN Xiao-tao, ZHOU Zhong-fa, HUANG Zhi-ling, CHEN Sheng-zi, ZHANG Shao-yun. An optimized fuzzy comprehensive evaluation model for assessment of soil heavy metal contamination in tea production parks of karst mountainous regions[J]. CARSOLOGICA SINICA, 2016, 35(3): 282-290. doi: 10.11932/karst20160306
Citation: SUN Xiao-tao, ZHOU Zhong-fa, HUANG Zhi-ling, CHEN Sheng-zi, ZHANG Shao-yun. An optimized fuzzy comprehensive evaluation model for assessment of soil heavy metal contamination in tea production parks of karst mountainous regions[J]. CARSOLOGICA SINICA, 2016, 35(3): 282-290. doi: 10.11932/karst20160306

An optimized fuzzy comprehensive evaluation model for assessment of soil heavy metal contamination in tea production parks of karst mountainous regions

doi: 10.11932/karst20160306
  • Publish Date: 2016-06-25
  • An optimized fuzzy comprehensive evaluation model can facilitate to clarify the surface soil (0 ~ -20 cm) heavy metal contamination of tea producing park areas. Using Hg-Cd-Pb-Cr-Cu as evaluation factors and the principle of minimum relative information entropy, this study employed the "pollutant exceeding standard method" and "double weight method" to form a set of combined weight factors, which hence optimized the traditional fuzzy comprehensive evaluation model. Then we evaluated the soil heavy metal pollution in a tea producing park area and compared the evaluation results. We emphasize that the optimized evaluation model that integrates the soil heavy metal concentration and toxicity is much more suitable in the calculation of weights of evaluation factors and subsequent assessment result. The result shows that in the tea park area the soil clean ratio is up to 38.81% and moderately clean ratio is 61.19%. These data suggests that the overall soil environmental quality of this tea park area is fairly good, which meets the requirements of pollution-free tea production. Comparing the evaluation results shows that the optimized model is more scientific in grade classification, which can make the assessment more objective, and provide a reference for optimizing the layouts of tea production in karst mountainous regions.

     

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