| 基于多元统计学和地统计学的土壤重金属源解析 |
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| 作者姓名： | QU Ming-Kai LI Wei-Dong ZHANG Chuan-Rong WANG Shan-Qin YANG Yong HE Li-Yuan |
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| 摘 要： | The main objectives of this study were to introduce an integrated method for effectively identifying soil heavy metal pollution sources and apportioning their contributions, and apply it to a case study. The method combines the principal component analysis/absolute principal component scores (PCA/APCS) receptor model and geostatistics. The case study was conducted in an area of 31 km2 in the urban-rural transition zone of Wuhan, a metropolis of central China. 124 topsoil samples were collected for measuring the concentrations of eight heavy metal elements (Mn, Cu, Zn, Pb, Cd, Cr, Ni and Co). PCA results revealed that three major factors were responsible for soil heavy metal pollution, which were initially identified as “steel production”, “agronomic input” and “coal consumption”. The APCS technique, combined with multiple linear regression analysis, was then applied for source apportionment. Steel production appeared to be the main source for Ni, Co, Cd, Zn and Mn, agronomic input for Cu, and coal consumption for Pb and Cr. Geostatistical interpolation using ordinary kriging was finally used to map the spatial distributions of the contributions of pollution sources and further confirm the result interpretations. The introduced method appears to be an effective tool in soil pollution source apportionment and identification, and might provide valuable reference information for pollution control and environmental management.
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| 收稿时间： | 9 January 2013 |
Source apportionment of heavy metals in soils using multivariate statistics and geostatistics |
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| QU Ming-Kai,LI Wei-Dong,ZHANG Chuan-Rong,WANG Shan-Qin,YANG Yong,HE Li-Yuan.Source apportionment of heavy metals in soils using multivariate statistics and geostatistics[J].Pedosphere,2013,23(4):437-444. |
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| Authors: | QU Ming-Kai LI Wei-Dong ZHANG Chuan-Rong WANG Shan-Qin YANG Yong and HE Li-Yuan |
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| Institution: | 1. Department of Resource and Environmental Information, College of Resources and Environment, Huazhong Agricultural University,Wuhan 430070 China
2. Department of Geography and Center for Environmental Sciences and Engineering, University of Connecticut, Storrs, Connecticut 06269 USA |
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| Abstract: | The main objectives of this study were to introduce an integrated method for effectively identifying soil heavy metal pollution sources and apportioning their contributions, and apply it to a case study. The method combines the principal component analysis/absolute principal component scores (PCA/APCS) receptor model and geostatistics. The case study was conducted in an area of 31 km2 in the urban-rural transition zone of Wuhan, a metropolis of central China. 124 topsoil samples were collected for measuring the concentrations of eight heavy metal elements (Mn, Cu, Zn, Pb, Cd, Cr, Ni and Co). PCA results revealed that three major factors were responsible for soil heavy metal pollution, which were initially identified as “steel production”, “agronomic input” and “coal consumption”. The APCS technique, combined with multiple linear regression analysis, was then applied for source apportionment. Steel production appeared to be the main source for Ni, Co, Cd, Zn and Mn, agronomic input for Cu, and coal consumption for Pb and Cr. Geostatistical interpolation using ordinary kriging was finally used to map the spatial distributions of the contributions of pollution sources and further confirm the result interpretations. The introduced method appears to be an effective tool in soil pollution source apportionment and identification, and might provide valuable reference information for pollution control and environmental management. |
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| Keywords: | pollution source receptor model source identification steel production |
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