最大熵模糊综合评价法在污灌区土壤重金属污染等级划分中的应用

以开封市化肥河污灌区为例,运用最大熵模糊综合评价法开展了土壤重金属(Cu、Zn、Cr、Pb、Cd、Ni、As)污染评价.结果表明: 在污灌区13个样点中,属于3级重污染的样点达11个,占总样点数的84.62%,只有位于化肥河上游的两个样点属于2级水平,污染较轻;在所有污染因子中,Cd和As的污染最为突出,其中Cd平均权重值为0.541 9,是最主要的污染因子.与内梅罗法综合指数法评价的结果相比较,最大熵模糊综合评价法能够显示更多的土壤污染信息,引入目标函数和隶属度,重视不同污染因子的权重,具有更高的准确性.

Application of the maximal comprehensive entropy fuzzy evaluation method to the contaminated soil gradation in the sewage irrigated areas

The present paper is aimed to introduce its authors' study on how to apply the maximal comprehensive entropy fuzzy evaluation theory to the contaminated soil gradation in the sewage irrigated areas by taking the sewage irrigated area of Huafei River in Kaifeng as a case study, In our study, we have tested and measured 7 heavy metals (Cu, Zn, Cr, Pb, Cd, Ni, As) in 13 soil samples from our samples. Besides, we have also done a number of investigations on the chemistry of metals in soils in our country with the concentrations of heavy metals measured for the prepared soil samples by using G-AAS for Cu, Zn, Cr, Ni, F-AAS for Pb, Cd, and silver diethydithiocarbamate spectrophotometry for As. The results of our research show that: 11 soils, 84.62% of all the soils from all the testing sites, belong to the third pollution grade, the sufferers of the heaviest heavy metal pollution. Only two sites, No.1 and No.9, which are located at the upriver, belong to the second level, the middle degree pollution. The irrigation with the swage from Huafei River has thus proved to bring serious effect on the contamination of the soils of the tested areas, By far the greatest attention in this work has been paid to farming soils, but the contamination due to the 7 heavy metals, particularly the effect of Cd and As remains unsolved, with the average pollution weight of Cd being 0.541 9, the highest of the 7 heavy metals. What is more essential, the theory of maximum entropy has been proved a more practical method for soil pollution assessment, as compared with that of Nemerow pollution index, for the former attaches importance to the weights of different factors by objective functions and fuzzy membership, which help to reveal more details on the soil pollution information, and make it more accurate in measurement and evaluation with less uncertainty of the evaluated results.