欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
基于54个土壤表层样品重金属全量浓度实验室测定数据,应用模糊c-均值算法对南京城市边缘带化工园附近20km^2样区内土壤重金属浓度进行了连续分类,对样点土壤的隶属度进行空间普通克里格插值,实现样区土壤重金属浓度和污染状况的空间预测.结果表明,样区土壤中重金属Cu、Zn、Cr、As和Cd的浓度均低于国家土壤环境质量标准,未发生污染;受工业、交通排放的影响,样区左侧和南部Cu、Zn、Cr、As较高,个别区域有Zn、Cr富集现象.Hg为样区主要的土壤重金属污染元素,土壤Hg污染主要发生在蔬菜基地及滁河流经区,较为严重的Hg污染土壤集中分布在样区中部的蔬菜基地.与利用样点测定数据直接插值的空间预测方法相比,基于模糊集理论的土壤污染空间预测方法可获得较好的预测效果.
英文摘要：
Based on the lab data of concentrations of total Cu, Zn, Cr, Cd, Hg, and As obtained through determination of 54 topsoil samples, continuous classification of heavy metal concentrations of the sampled soils was conducted with fuzzy c-mean algorithm （FCM）. And, membership values of the sampled soils in each class were interpolated using ordinary kriging to predict spatial distribution of soil heavy metal concentrations and pattern of soil heavy metal pollution of the investigated area. The obtained results show that the concentrations of Cu, Zn, Cr, As and Cd in soils in the area were below the national criteria for soil environment and even their background values, and that no accident of soil heavy metal pollution had ever occur. The concentrations of Cu, Zn, Cr and As, however, in the soils of the west and south parts of the investigated area were higher than that in the rest, and in a fewer plots enrichment of Zn and Cr was found, perhaps demonstrating influences of industrial activities and traffic on the soil environment. It was revealed that Hg was the dominant heavy metal pollutant, and soil Hg pollution occurred mainly in vegetable production bases and land on either side of Chuhe River, especially the vegetable production bases in the central part of the investigated area. Compared to the interpolation method, spatial prediction based on the fuzzy set theory could achieve a continuous output with significantly higher accuracy.
同期刊论文项目
同项目期刊论文
Spatial prediction of heavy metal pollution for soils in Peri-urban Beijing, China based on Fuzzy Se
期刊信息
位置：