摘要
在南京10个国家空气质量监测站点附近采集桂花、樟树和雪松树叶,测试其磁性参数和重金属含量,分析监测站大气颗粒物浓度、树叶重金属与磁性参数的相互关系.结果表明:3种树叶中重金属含量较高的是Fe、Mn、Cu和Pb,As、Cd和Sb较低.Pb、Cu和Sb在交通密集区含量较高;Ni、Cd和Mn在工业区含量较高;V、Cr和Fe在靠近建筑工地的地区含量较高.V、Fe、As、Pb、Sb和Cr与树叶附尘中磁性矿物具有相似来源.对比3种树叶,雪松更易富集颗粒物,其磁性参数和重金属含量均较高,同时,雪松树叶附尘中大部分重金属含量与其磁性参数的相关性较高;而桂花树叶的SIRM值与监测站大气颗粒物浓度高低具有较好一致性.常绿树叶的磁性参数有潜力用来评估城市大气污染.
Samples of dust-loaded leaves of Osmanthus,Camphor and ceder were collected around ten air quality monitoring stations in Nanjing.The magnetic parameters and heavy metal contents of leaf samples were measured.The correlations were analyzed between magnetic parameters of leaves and concentrations of airborne particulate matter obtained by the air quality monitoring stations,as well as heavy metal contents of leaves.Results showed that the contents of Fe,Mn,Cu and Pb in three kinds of leaves were all higher,whereas the contents of As,Cd and Sb were relatively lower.Contents of Pb,Cu and Sb were higher in traffic concentrated areas,whereas the contents of Ni,Cd and Mn were higher in industrial areas.Contents of V,Cr and Fe were enhanced in areas close to urban construction areas.Elements including V,Fe,As,Pb,Sb and Cr shared the similar sources with magnetic minerals on dust-loaded leaves.Among the three kinds of trees,ceder leaves enriched particulate matter more easily,resulting in higher magnetic parameter values and heavy metal contents of leaf samples.The Pearson's coefficients between most heavy metal contents and magnetic parameters of leaves were also higher for ceder than Osmanthus and Camphor.Meanwhile,good consistency was found between SIRM values of Osmanthus leaves and the airborne particulate matter concentrations at the10sampling sites.The magnetic parameters of dust-loaded leaves of evergreen trees have the potential to be used for evaluating urban air pollution.
出处
《中国环境科学》
EI
CAS
CSSCI
CSCD
北大核心
2017年第7期2414-2423,共10页
China Environmental Science
基金
国家自然科学基金青年项目(41501549)
关键词
大气重金属
大气颗粒物
磁性参数
树叶
南京
atmospheric heavy metals
airborne particulate matter
magnetic parameters
leaves
Nanjing