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辽宁省污灌区土壤重金属污染特征与生态风险评价 被引量:23

Specificity and ecological risk of heavy metal pollution in Liaoning sewage irrigation district
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摘要 针对当前污灌区土壤污染研究中存在的问题,提出了一种模糊识别模型评价土壤综合环境质量,并对潜在生态风险指数法进行改进,用以计量重金属潜在生态风险。采用建立的方法对辽宁省污灌区土壤环境质量和重金属潜在生态风险进行了评价,结果显示:Cd是辽宁省污灌区首要重金属污染物,而Hg、Pb、Ni污染较为普遍;重金属的来源主要是灌溉污水和农田施肥;以工业废水为灌溉用水的灌区污染情况比以河水为灌溉用水的灌区污染严重;污灌区重金属元素污染程度大小依次为:Cd>Pb>Ni>Hg>Cu>Cr>As,而重金属潜在生态风险从大到小则依次为:Cd>Hg>Pb>Cu>Ni>As>Cr。总体来看,辽宁省污灌区存在一定程度的重金属污染,且具有较为明显的复合型污染特点,其潜在生态风险超出警戒水平,各灌区应根据各自污染特点和风险等级制定相应的污染防治对策。 To address the problems of sewage irrigation,fuzzy recognition model was developed to evaluate sewage irrigated soil environmental quality and improve potential ecological risk index used to assess potential ecological risk of heavy metals.The soil environment quality,heavy metal pollution characteristics and potential ecological risk of Liaoning sewage irrigation district were evaluated by the established model.Results show that the primary contaminant in sewage irrigation districts of Liaoning Province is Cd,whereas Hg,Pb and Ni constitute pervasive pollutants.Correlation analysis indicates that wastewater irrigation and fertilization of farmland are the main sources of heavy metal pollution in Liaoning sewage irrigated soils.Pollution is more serious in the regions irrigated with industrial wastewater than in regions irrigated with river water.The order of heavy metal pollution intensity is: Cd 〉 Pb 〉 Ni 〉 Hg 〉 Cu 〉 Cr 〉 As;and that for potential ecological risk is: Cd 〉 Hg 〉 Pb 〉 Cu 〉 Ni 〉 As 〉 Cr.On the whole,the sewage irrigation district of Liaoning Province is polluted and characterized as a complex pollution situation.The degree of ecological risk is somehow moderate.In the future,soil pollution countermeasures should take into account of pollution characteristics and risk level of every sewage irrigation region.
出处 《中国生态农业学报》 CAS CSCD 2008年第6期1517-1522,共6页 Chinese Journal of Eco-Agriculture
基金 国家自然科学基金项目(40571041) 国家自然科学基金重点项目(40635030)资助
关键词 辽宁省 污灌区 模糊识别模型 潜在生态风险 土壤重金属污染 毒性系数 Liaoning Province,Sewage irrigation district,Fuzzy recognition model,Potential ecological risk,Soil heavy metal pollution,Toxicity coefficient
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