Spatial heterogeneity analysis and source identification of heavy metals in soil: a case study of Chongqing, Southwest China
Abstract Background Heavy metal pollution in urban soil is an important indicator of environmental pollution. Selecting the best interpolation method can accurately reflect the distribution characteristics of heavy metals in soil. In addition, source analysis can reveal heavy metal pollution of soil...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2022-07-01
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| Series: | Chemical and Biological Technologies in Agriculture |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40538-022-00313-3 |
| _version_ | 1818017922416640000 |
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| author | Wende Chen Yankun Cai Kun Zhu Jun Wei Yutian Lu |
| author_facet | Wende Chen Yankun Cai Kun Zhu Jun Wei Yutian Lu |
| author_sort | Wende Chen |
| collection | DOAJ |
| description | Abstract Background Heavy metal pollution in urban soil is an important indicator of environmental pollution. Selecting the best interpolation method can accurately reflect the distribution characteristics of heavy metals in soil. In addition, source analysis can reveal heavy metal pollution of soil and help manage and protect the soil environment. This study used a uniform sampling method and obtained a total of 342 sampling points. After acid reduction, the concentration of As, Cu, and Mn in each sample was determined by ICP-MS (Agilent VISTA, USA). The accuracy and results of different spatial interpolation methods were compared and the CATREG model was used to identify the sources of heavy metal pollution. Results The average concentration of As, Cu, and Mn were 5.802 mg kg −1, 23.992 mg kg−1, and 573.316 mg kg−1, respectively, lower than the soil background value of Chongqing. Compared to other Chinese cities and countries in the world, the concentration of As and Cu was lower in Chongqing, while the concentration of only Mn was higher. The interpolation results of inverse distance weighting (IDW) and radial basis function (RBF) largely retained the maximum information of element concentration. Soil source identification found that population density mainly affected Cu (0.539), slope Mn (0.206), and water quality As (0.453). The highest hotspot value (99% confidence interval), high hotspot value (95% confidence interval), and high hotspot value (90% confidence interval) of As were adjacent to the secondary water environment. Furthermore, the highest hotspot value of Cu was mainly located in the surrounding areas with population density > 3000/km2 and 1000–3000/km2. Mn was distributed along the slope direction and diffused from center to periphery. Conclusions Different spatial interpolation methods are significant for the analysis of soil properties. Heavy metals have a high degree of coincidence with environmental factors such as slope and population. The results of this research provide a reference for formulating effective control and management strategies for heavy metal pollution of soil. Graphical Abstract |
| first_indexed | 2024-04-14T07:33:12Z |
| format | Article |
| id | doaj.art-a9c0501ed7a6444181659ffba6b8a46c |
| institution | Directory Open Access Journal |
| issn | 2196-5641 |
| language | English |
| last_indexed | 2024-04-14T07:33:12Z |
| publishDate | 2022-07-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Chemical and Biological Technologies in Agriculture |
| spelling | doaj.art-a9c0501ed7a6444181659ffba6b8a46c2022-12-22T02:05:47ZengSpringerOpenChemical and Biological Technologies in Agriculture2196-56412022-07-019112110.1186/s40538-022-00313-3Spatial heterogeneity analysis and source identification of heavy metals in soil: a case study of Chongqing, Southwest ChinaWende Chen0Yankun Cai1Kun Zhu2Jun Wei3Yutian Lu4College of Tourism and Urban-Rural Planning, Chengdu University of TechnologyCollege of Tourism and Urban-Rural Planning, Chengdu University of TechnologyCollege of Tourism and Urban-Rural Planning, Chengdu University of TechnologyCollege of Tourism and Urban-Rural Planning, Chengdu University of TechnologyCollege of Tourism and Urban-Rural Planning, Chengdu University of TechnologyAbstract Background Heavy metal pollution in urban soil is an important indicator of environmental pollution. Selecting the best interpolation method can accurately reflect the distribution characteristics of heavy metals in soil. In addition, source analysis can reveal heavy metal pollution of soil and help manage and protect the soil environment. This study used a uniform sampling method and obtained a total of 342 sampling points. After acid reduction, the concentration of As, Cu, and Mn in each sample was determined by ICP-MS (Agilent VISTA, USA). The accuracy and results of different spatial interpolation methods were compared and the CATREG model was used to identify the sources of heavy metal pollution. Results The average concentration of As, Cu, and Mn were 5.802 mg kg −1, 23.992 mg kg−1, and 573.316 mg kg−1, respectively, lower than the soil background value of Chongqing. Compared to other Chinese cities and countries in the world, the concentration of As and Cu was lower in Chongqing, while the concentration of only Mn was higher. The interpolation results of inverse distance weighting (IDW) and radial basis function (RBF) largely retained the maximum information of element concentration. Soil source identification found that population density mainly affected Cu (0.539), slope Mn (0.206), and water quality As (0.453). The highest hotspot value (99% confidence interval), high hotspot value (95% confidence interval), and high hotspot value (90% confidence interval) of As were adjacent to the secondary water environment. Furthermore, the highest hotspot value of Cu was mainly located in the surrounding areas with population density > 3000/km2 and 1000–3000/km2. Mn was distributed along the slope direction and diffused from center to periphery. Conclusions Different spatial interpolation methods are significant for the analysis of soil properties. Heavy metals have a high degree of coincidence with environmental factors such as slope and population. The results of this research provide a reference for formulating effective control and management strategies for heavy metal pollution of soil. Graphical Abstracthttps://doi.org/10.1186/s40538-022-00313-3Heavy metals in soilSpatial heterogeneityClassification regression analysisSpatial analysis of hotspots |
| spellingShingle | Wende Chen Yankun Cai Kun Zhu Jun Wei Yutian Lu Spatial heterogeneity analysis and source identification of heavy metals in soil: a case study of Chongqing, Southwest China Chemical and Biological Technologies in Agriculture Heavy metals in soil Spatial heterogeneity Classification regression analysis Spatial analysis of hotspots |
| title | Spatial heterogeneity analysis and source identification of heavy metals in soil: a case study of Chongqing, Southwest China |
| title_full | Spatial heterogeneity analysis and source identification of heavy metals in soil: a case study of Chongqing, Southwest China |
| title_fullStr | Spatial heterogeneity analysis and source identification of heavy metals in soil: a case study of Chongqing, Southwest China |
| title_full_unstemmed | Spatial heterogeneity analysis and source identification of heavy metals in soil: a case study of Chongqing, Southwest China |
| title_short | Spatial heterogeneity analysis and source identification of heavy metals in soil: a case study of Chongqing, Southwest China |
| title_sort | spatial heterogeneity analysis and source identification of heavy metals in soil a case study of chongqing southwest china |
| topic | Heavy metals in soil Spatial heterogeneity Classification regression analysis Spatial analysis of hotspots |
| url | https://doi.org/10.1186/s40538-022-00313-3 |
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