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城市区域土壤铅含量空间变异的多尺度研究进展
引用本文:杨孟,李凤英,刁一伟,吴丹. 城市区域土壤铅含量空间变异的多尺度研究进展[J]. 环境科学, 2014, 35(4): 1586-1596
作者姓名:杨孟  李凤英  刁一伟  吴丹
作者单位:南京信息工程大学环境科学与工程学院,江苏省大气环境监测与污染控制高技术研究重点实验室,南京 210044;南京信息工程大学环境科学与工程学院,江苏省大气环境监测与污染控制高技术研究重点实验室,南京 210044;南京信息工程大学大气物理学院,南京 210044;南京信息工程大学环境科学与工程学院,江苏省大气环境监测与污染控制高技术研究重点实验室,南京 210044
基金项目:南京信息工程大学科研启动基金项目(S8112067001);国家自然科学基金青年科学基金项目(41301581);江苏省高校自然科学研究项目(12KJB610004);江苏高校优势学科建设工程项目
摘    要:我国城市土壤仍存在Pb的严重富集,准确地评价土壤Pb污染水平和范围是进行科学的土壤Pb污染风险评估和管理的基础.城市土壤Pb含量的空间变异性强且结构复杂,现有的大多数研究在单一空间尺度上开展,不足以全面揭示空间结构特征,不利于促进更加科学的风险评估和管理.因此,探寻一种能够全面揭示城市土壤Pb含量的空间结构信息的方法尤为重要.为了实现这一目的,本文首先分析了造成城市土壤Pb含量高空间变异性的主要因素:污染源的多样性、污染过程的层次性,以及城市景观的异质性.在此基础上归纳出城市土壤Pb含量的空间变异特征——由3个空间层次嵌套而成的等级结构.在此概念性的空间结构之上提出一个基于地统计学理论、以线性混合效应模型为核心的方法框架,可以将城市土壤Pb含量的空间结构划分为3个层次:全局趋势、具有空间自相关的随机变异以及异常高值点.最后,提出完善城市土壤Pb含量空间变异多尺度研究的重点是:探讨更加高效的空间抽样策略;确定特征尺度.

关 键 词:重金属  大气沉降  地统计  空间自相关  多尺度
收稿时间:2013-08-04
修稿时间:2013-10-23

A Review of Multi-Scale Studies on Spatial Variation of the Lead (Pb) Concentration in Urban Soils
YANG Meng,LI Feng-ying,DIAO Yi-wei and WU Dan. A Review of Multi-Scale Studies on Spatial Variation of the Lead (Pb) Concentration in Urban Soils[J]. Chinese Journal of Environmental Science, 2014, 35(4): 1586-1596
Authors:YANG Meng  LI Feng-ying  DIAO Yi-wei  WU Dan
Affiliation:Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China;Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China;School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China;Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Abstract:The accumulation of Pb in urban soils is still apparent in China, and scientific assessment and management of risks from Pb-contaminated soils is necessarily based on contamination levels and extent evaluated accurately. Lead concentration in urban soils has a strong spatial variation and complex spatial structures. Carried out in a single spatial scale, most current investigations cannot comprehensively reveal characteristics of spatial structures, and did not promote more scientific assessment and management of risk. Exploring a new method which can help identify the overall spatial structures is needed. To achieve this aim, this paper firstly investigated the factors linked to the spatial variability of Pb concentration in urban soils, and three major factors were identified: various pollution sources, hierarchical pollution processes and heterogeneous urban landscape. These factors were form a nested hierarchical spatial structure with three spatial levels. Based on the conceptual spatial structure, we proposed a method framework guided by geostatistical theory and focused on linear mixed model (LMM). This proposed framework can divide the nested hierarchical spatial structures of Pb concentration in urban soils into three levels: global trend, random variation with spatial autocorrelation, and outliers. Two recommendations were given to promote the multiple-scale investigation in spatial variation of soil Pb contamination in urban area including: finding more efficient sampling strategy and determining the characteristic scale.
Keywords:heavy metal  atmospheric deposition  geostatistics  spatial autocorrelation  multi-scale
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