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基于GIS的上海城市灰尘重金属空间分布特征研究
引用本文:李海雯,陈振楼,王军,许世远,史贵涛,张菊,王利.基于GIS的上海城市灰尘重金属空间分布特征研究[J].环境科学学报,2007,27(5):803-809.
作者姓名:李海雯  陈振楼  王军  许世远  史贵涛  张菊  王利
作者单位:1. 华东师范大学地理信息科学教育部重点实验室,上海,200062
2. 聊城大学环境与规划学院,聊城,252059
基金项目:国家自然科学基金 , 上海市重点基础研究项目 , 上海市环保局招标项目 , 上海市科技攻关项目
摘    要:基于ArcGIS地统计分析模块,以上海市外环以内为研究区域,对上海城市道路和公园灰尘中重金属Pb、Cr、Cu、Ni、Zn含量水平和空间分布特征进行了研究.研究表明:上海城市灰尘重金属平均含量水平普遍较高,Pb、Cr、Cu、Ni、Zn平均含量分别为273.45、144.01、190.01、86.26、708.25 mg·kg-1,分别高出上海土壤背景值10.7、1.9、6.6、2.7、8.2倍;外环区域Pb、Zn、Ni污染严重,尤以工业区、商业区以及交通繁忙区最突出.地统计分析表明,Pb和Cu呈较弱的空间相关性,说明Pb和Cu的空间变异以人为影响为主;Zn、Cr和Ni为中等相关,说明随机性因素和结构因素对这3种元素都有较大影响;基于ArcGIS的地统计学分析工具能够较好地反映重金属污染的空间分布格局.

关 键 词:城市灰尘  重金属  地统计分析  克里格插值
文章编号:0253-2468(2007)05-0803-07
收稿时间:2006/5/12 0:00:00
修稿时间:05 12 2006 12:00AM

Research of spatial variability of heavy metal pollution of dust in Shanghai urban area based on the GIS
LI Haiwen,CHEN Zhenlou,WANG Jun,XU Shiyuan,SHI Guitao,ZHANG Ju and WANG Li.Research of spatial variability of heavy metal pollution of dust in Shanghai urban area based on the GIS[J].Acta Scientiae Circumstantiae,2007,27(5):803-809.
Authors:LI Haiwen  CHEN Zhenlou  WANG Jun  XU Shiyuan  SHI Guitao  ZHANG Ju and WANG Li
Institution:1. Key Laboratory of Geographic Information Science of Ministry of Education East China Normal University, Shanghai 200062 2. School of Environment and Planning, LiaoCheng University, Liaocheng 252059
Abstract:Based on the Geostatistical module of ArcGIS, heavy metal contents and their characteristics of spatial distributions were studied from the street dust and park dust in Shanghai urban area. Average contents of heavy metal are high. Values of Pb,Cr,Cu,Ni,Zn are 273.45,144.01,190.01,86.26,708.25 mg·kg-1 which are 10.7,1.9,6.6,2.7,8.2 times of the soil background values respectively. The urban dusts were polluted by Pb, Zn, Ni which were much higher in the industrial estate, sowntown and busy roads. The spatial correlations of Pb and Cu are low, which indicates that they were controlled by anthropic activities, whereas those of Zn, Cr, Ni and organic matter belong to the moderate class, which shows that they were produced by both random factor and structural factor. The method based on the geostatistical module in ArcGIS can exactly reflect the character of spatial variability of heavy metals.
Keywords:urban dust  heavy metal  geostatistical analysis  kriging
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