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Spatial Pattern Analysis of Heavy Metals in Beijing Agricultural Soils Based on Spatial Autocorrelation Statistics

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  • Xiao-Ni Huo

    (Beijing Academy of Agriculture and Forestry, Beijing 100097, China
    Department of Environmental Engineering, Taiyuan University, Taiyuan 030009, China)

  • Wei-Wei Zhang

    (Beijing Academy of Agriculture and Forestry, Beijing 100097, China)

  • Dan-Feng Sun

    (Department of Land Resources and Management, College of Natural Resources and Environment Science, China Agricultural University, Beijing 100193, China)

  • Hong Li

    (Beijing Academy of Agriculture and Forestry, Beijing 100097, China)

  • Lian-Di Zhou

    (Beijing Academy of Agriculture and Forestry, Beijing 100097, China)

  • Bao-Guo Li

    (Department of Land Resources and Management, College of Natural Resources and Environment Science, China Agricultural University, Beijing 100193, China)

Abstract

This study explored the spatial pattern of heavy metals in Beijing agricultural soils using Moran’s I statistic of spatial autocorrelation. The global Moran’s I result showed that the spatial dependence of Cr, Ni, Zn, and Hg changed with different spatial weight matrixes, and they had significant and positive global spatial correlations based on distance weight. The spatial dependence of the four metals was scale-dependent on distance, but these scale effects existed within a threshold distance of 13 km, 32 km, 50 km, and 29 km, respectively for Cr, Ni, Zn, and Hg. The maximal spatial positive correlation range was 57 km, 70 km, 57 km, and 55 km for Cr, Ni, Zn, and Hg, respectively and these were not affected by sampling density. Local spatial autocorrelation analysis detected the locations of spatial clusters and spatial outliers and revealed that the pollution of these four metals occurred in significant High-high spatial clusters, Low-high, or even High-low spatial outliers. Thus, three major areas were identified and should be receiving more attention: the first was the northeast region of Beijing, where Cr, Zn, Ni, and Hg had significant increases. The second was the southeast region of Beijing where wastewater irrigation had strongly changed the content of metals, particularly of Cr and Zn, in soils. The third area was the urban fringe around city, where Hg showed a significant increase.

Suggested Citation

  • Xiao-Ni Huo & Wei-Wei Zhang & Dan-Feng Sun & Hong Li & Lian-Di Zhou & Bao-Guo Li, 2011. "Spatial Pattern Analysis of Heavy Metals in Beijing Agricultural Soils Based on Spatial Autocorrelation Statistics," IJERPH, MDPI, vol. 8(6), pages 1-16, June.
    • Handle: RePEc:gam:jijerp:v:8:y:2011:i:6:p:2074-2089:d:12683
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    References listed on IDEAS

    as
    1. Luc Anselin, 2001. "Spatial Effects in Econometric Practice in Environmental and Resource Economics," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 705-710.
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    Cited by:

    1. Binwu Wang & Hong Li & Danfeng Sun, 2014. "Social-Ecological Patterns of Soil Heavy Metals Based on a Self-Organizing Map (SOM): A Case Study in Beijing, China," IJERPH, MDPI, vol. 11(4), pages 1-21, March.
    2. Peng Shi & Jun Xiao & Yafeng Wang & Liding Chen, 2014. "Assessment of Ecological and Human Health Risks of Heavy Metal Contamination in Agriculture Soils Disturbed by Pipeline Construction," IJERPH, MDPI, vol. 11(3), pages 1-17, February.
    3. Xiao-Ni Huo & Hong Li & Dan-Feng Sun & Lian-Di Zhou & Bao-Guo Li, 2012. "Combining Geostatistics with Moran’s I Analysis for Mapping Soil Heavy Metals in Beijing, China," IJERPH, MDPI, vol. 9(3), pages 1-23, March.

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