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

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...

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Autores principales: Zhang, Weiwei, Han, Jigang, Molla, Abiot, Zuo, Shudi, Ren, Yin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124676/
https://www.ncbi.nlm.nih.gov/pubmed/33946486
http://dx.doi.org/10.3390/ijerph18094820
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author Zhang, Weiwei
Han, Jigang
Molla, Abiot
Zuo, Shudi
Ren, Yin
author_facet Zhang, Weiwei
Han, Jigang
Molla, Abiot
Zuo, Shudi
Ren, Yin
author_sort Zhang, Weiwei
collection PubMed
description 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.
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spelling pubmed-81246762021-05-17 The Optimization Strategy of the Existing Urban Green Space Soil Monitoring System in Shanghai, China Zhang, Weiwei Han, Jigang Molla, Abiot Zuo, Shudi Ren, Yin Int J Environ Res Public Health Article 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. MDPI 2021-04-30 /pmc/articles/PMC8124676/ /pubmed/33946486 http://dx.doi.org/10.3390/ijerph18094820 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Weiwei
Han, Jigang
Molla, Abiot
Zuo, Shudi
Ren, Yin
The Optimization Strategy of the Existing Urban Green Space Soil Monitoring System in Shanghai, China
title The Optimization Strategy of the Existing Urban Green Space Soil Monitoring System in Shanghai, China
title_full The Optimization Strategy of the Existing Urban Green Space Soil Monitoring System in Shanghai, China
title_fullStr The Optimization Strategy of the Existing Urban Green Space Soil Monitoring System in Shanghai, China
title_full_unstemmed The Optimization Strategy of the Existing Urban Green Space Soil Monitoring System in Shanghai, China
title_short The Optimization Strategy of the Existing Urban Green Space Soil Monitoring System in Shanghai, China
title_sort optimization strategy of the existing urban green space soil monitoring system in shanghai, china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124676/
https://www.ncbi.nlm.nih.gov/pubmed/33946486
http://dx.doi.org/10.3390/ijerph18094820
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