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The Optimization Strategy of the Existing Urban Green Space Soil Monitoring System in Shanghai, China

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  • Weiwei Zhang

    (Key Laboratory of National Forestry and Grassland Administration on Ecological Landscaping of Challenging Urban Sites, Shanghai Academy of Landscape Architecture Science and Planning, Shanghai 200232, China
    Shanghai Engineering Research Center of Landscaping on Challenging Urban Sites, Shanghai 200232, China)

  • Jigang Han

    (Key Laboratory of National Forestry and Grassland Administration on Ecological Landscaping of Challenging Urban Sites, Shanghai Academy of Landscape Architecture Science and Planning, Shanghai 200232, China
    Shanghai Engineering Research Center of Landscaping on Challenging Urban Sites, Shanghai 200232, China)

  • Abiot Molla

    (Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Shudi Zuo

    (Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China)

  • Yin Ren

    (Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China)

Abstract

High concentrations of potentially toxic elements (PTE) create global environmental stress due to the crucial threat of their impacts on the environment and human health. Therefore, determining the concentration levels of PTE and improving their prediction accuracy by sampling optimization strategy is necessary for making sustainable environmental decisions. The concentrations of five PTEs (Pb, Cd, Cr, Cu, and Zn) were compared with reference values for Shanghai and China. The prediction of PTE in soil was undertaken using a geostatistical and spatial simulated annealing algorithm. Compared to Shanghai’s background values, the five PTE mean concentrations are much higher, except for Cd and Cr. However, all measured values exceeded the reference values for China. Pb, Cu, and Zn levels were 1.45, 1.20, and 1.56 times the background value of Shanghai, respectively, and 1.57, 1.66, 1.91 times the background values in China, respectively. The optimization approach resulted in an increased prediction accuracy (22.4% higher) for non-sampled locations compared to the initial sampling design. The higher concentration of PTE compared to background values indicates a soil pollution issue in the study area. The optimization approach allows a soil pollution map to be generated without deleting or adding additional monitoring points. This approach is also crucial for filling the sampling strategy gap.

Suggested Citation

  • Weiwei Zhang & Jigang Han & Abiot Molla & Shudi Zuo & Yin Ren, 2021. "The Optimization Strategy of the Existing Urban Green Space Soil Monitoring System in Shanghai, China," IJERPH, MDPI, vol. 18(9), pages 1-14, April.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:9:p:4820-:d:547229
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    1. Arthur Getis & J. Keith Ord, 2010. "The Analysis of Spatial Association by Use of Distance Statistics," Advances in Spatial Science, in: Luc Anselin & Sergio J. Rey (ed.), Perspectives on Spatial Data Analysis, chapter 0, pages 127-145, Springer.
    2. Wu, Zhen & Chen, Ruishan & Meadows, Michael E. & Sengupta, Dhritiraj & Xu, Di, 2019. "Changing urban green spaces in Shanghai: trends, drivers and policy implications," Land Use Policy, Elsevier, vol. 87(C).
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