Skip to main content
SpringerLink
Log in

Heavy metal pollution and ecological risk assessment: A study on Linli County soils based on self-organizing map and positive factorization approaches

重金属污染与生态风险评价—基于自组织地图和正矩阵分解的临澧县土壤研究

  • Published:
Journal of Central South University Aims and scope Submit manuscript

Abstract

This study analyzed the pollution level, distribution, sources, and ecological impact of six heavy metals (As, Cd, Cr, Cu, Zn and Pb) in soil from Linli County, China. The concentration analysis showed that the concentration of Cd in all samples exceeded the background value, and the exceeding rate reached 100%, while the average concentrations of other elements were similar to the background value, and the exceeding rate was under 15%. The pollution level of Cd was the most severe according to geo-accumulation index and enrichment factor, while other elements were under mild pollution level. The results of self-organizing map (SOM) and positive matrix factorization (PMF) analysis showed that agricultural activities were one of the main sources of heavy metal elements in soil, and natural weathering and industrial pollution could also lead to soil pollution. Cd appeared to be the most significant pollutant element in the soil of Linli County, and it had the largest impact on the ecological environment. Overall, this study provides guidance for soil pollution control and related policies, aiming to reduce the pollution of heavy metal elements in soil and the hazards to the ecological system caused by agricultural production and industrial activities.

摘要

土壤重金属污染一直是环境科学中备受关注的问题。本文对中国临澧县土壤中六种重金属(As、 Cd、Cr、Cu、Zn和Pb)的污染水平、分布、来源及其对生态环境的影响进行了分析。样本浓度分析结 果显示Cd的浓度均超过背景值,超标率达到100%,其余元素的平均浓度与背景值相近,超标率均在 13.5%以下。地累计指数和富集因子指数均显示Cd是污染最严重的元素,其他元素则处于轻度污染级 别以下。自组织地图(SOM)和正矩阵分解(PMF)的分析结果显示农业活动是土壤中重金属元素主要来 源之一,而自然风化和工业污染也会导致土壤污染。Cd是临澧县土壤中污染最显著的元素,对生态环 境造成的影响最大,达到较高风险等级。本研究为降低土壤重金属污染和生态环境风险提供了重要参 考,同时也为相关部门制定有效的污染防治、生态环境保护政策提供了理论指导。

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. DODD M, AMPONSAH L O, GRUNDY S, et al. Human health risk associated with metal exposure at Agbogbloshie e-waste site and the surrounding neighbourhood in Accra, Ghana [J]. Environmental Geochemistry and Health, 2023, 45(7): 4515–4531. DOI: https://doi.org/10.1007/s10653-023-01503-0.

    Article  Google Scholar 

  2. ZHANG Chao, WANG Xing, JIANG Shi-hao, et al. Heavy metal pollution caused by cyanide gold leaching: A case study of gold tailings in central China [J]. Environmental Science and Pollution Research International, 2021, 28(23): 29231–29240. DOI: https://doi.org/10.1007/s11356-021-12728-w.

    Article  Google Scholar 

  3. GAO Jing, WANG Lu-cang. Ecological and human health risk assessments in the context of soil heavy metal pollution in a typical industrial area of Shanghai, China [J]. Environmental Science and Pollution Research International, 2018, 25(27): 27090–27105. DOI: https://doi.org/10.1007/s11356-018-2705-8.

    Article  Google Scholar 

  4. LONG Zhi-jie, HUANG Yi, ZHANG Wei, et al. Effect of different industrial activities on soil heavy metal pollution, ecological risk, and health risk [J]. Environmental Monitoring and Assessment, 2021, 193(1): 20. DOI: https://doi.org/10.1007/s10661-020-08807-z.

    Article  Google Scholar 

  5. XIANG Ming-tao, LI Yan, YANG Jia-yu, et al. Assessment of heavy metal pollution in soil and classification of pollution risk management and control zones in the industrial developed city [J]. Environmental Management, 2020, 66(6): 1105–1119. DOI: https://doi.org/10.1007/s00267-020-01370-w.

    Article  Google Scholar 

  6. SOLGI E, ESMAILI-SARI A, RIYAHI-BAKHTIARI A, et al. Soil contamination of metals in the three industrial estates, Arak, Iran [J]. Bulletin of Environmental Contamination and Toxicology, 2012, 88(4): 634–638. DOI: https://doi.org/10.1007/s00128-012-0553-7.

    Article  Google Scholar 

  7. SPRAGUE D D, VERMAIRE J C. Legacy arsenic pollution of lakes near cobalt, Ontario, Canada: Arsenic in lake water and sediment remains elevated nearly a century after mining activity has ceased [J]. Water, Air, & Soil Pollution, 2018, 229(3): 87. DOI: https://doi.org/10.1007/s11270-018-3741-1.

    Article  Google Scholar 

  8. OUYANG Wei, WANG Yi-di, LIN Chun-ye, et al. Heavy metal loss from agricultural watershed to aquatic system: A scientometrics review [J]. The Science of the Total Environment, 2018, 637 – 638: 208–220. DOI: https://doi.org/10.1016/j.scitotenv.2018.04.434.

    Article  Google Scholar 

  9. WU Hui-hui, XU Cong-bin, WANG Jin-hang, et al. Health risk assessment based on source identification of heavy metals: A case study of Beiyun River, China [J]. Ecotoxicology and Environmental Safety, 2021, 213: 112046. DOI: https://doi.org/10.1016/j.ecoenv.2021.112046.

    Article  Google Scholar 

  10. WANG Zhan, XIAO Jun, WANG Ling-qing, et al. Elucidating the differentiation of soil heavy metals under different land uses with geographically weighted regression and self-organizing map [J]. Environmental Pollution, 2020, 260: 114065. DOI: https://doi.org/10.1016/j.envpol.2020.114065.

    Article  Google Scholar 

  11. NAKAGAWA K, YU Zhi-qiang, BERNDTSSON R, et al. Temporal characteristics of groundwater chemistry affected by the 2016 Kumamoto earthquake using self-organizing maps [J]. Journal of Hydrology, 2020, 582: 124519. DOI: https://doi.org/10.1016/j.jhydrol.2019.124519.

    Article  Google Scholar 

  12. HOSSAIN BHUIYAN M A, CHANDRA KARMAKER S, BODRUD-DOZA M, et al. Enrichment, sources and ecological risk mapping of heavy metals in agricultural soils of Dhaka district employing SOM, PMF and GIS methods [J]. Chemosphere, 2021, 263: 128339. DOI: https://doi.org/10.1016/j.chemosphere.2020.128339.

    Article  Google Scholar 

  13. DAI Li-jun, WANG Ling-qing, LI Lian-fang, et al. Multivariate geostatistical analysis and source identification of heavy metals in the sediment of Poyang Lake in China [J]. The Science of the Total Environment, 2018, 621: 1433–1444. DOI: https://doi.org/10.1016/j.scitotenv.2017.10.085.

    Article  Google Scholar 

  14. ZHANG Yao-bin, ZHANG Qiu-lan, CHEN Wen-fang, et al. Hydrogeochemical analysis and groundwater pollution source identification based on self-organizing map at a contaminated site [J]. Journal of Hydrology, 2023, 616: 128839. DOI: https://doi.org/10.1016/j.jhydrol.2022.128839.

    Article  Google Scholar 

  15. BIGDELI A, MAGHSOUDI A, GHEZELBASH R. Application of self-organizing map (SOM) and K-means clustering algorithms for portraying geochemical anomaly patterns in Moalleman district, NE Iran [J]. Journal of Geochemical Exploration, 2022, 233: 106923. DOI: https://doi.org/10.1016/j.gexplo.2021.106923.

    Article  Google Scholar 

  16. ZOU Hao, REN Bo-zhi. Analyzing topsoil heavy metal pollution sources and ecological risks around antimony mine waste sites by a joint methodology [J]. Ecological Indicators, 2023, 154: 110761. DOI: https://doi.org/10.1016/j.ecolind.2023.110761

    Article  Google Scholar 

  17. WANG Ya-zhu, DUAN Xue-jun, WANG Lei. Spatial distribution and source analysis of heavy metals in soils influenced by industrial enterprise distribution: Case study in Jiangsu Province [J]. The Science of the Total Environment, 2020, 710: 134953. DOI: https://doi.org/10.1016/j.scitotenv.2019.134953.

    Article  Google Scholar 

  18. XIANG Long, LIU Ping-hui, JIANG Xing-fu, et al. Health risk assessment and spatial distribution characteristics of heavy metal pollution in rice samples from a surrounding hydrometallurgy plant area in No. 721 uranium mining, East China [J]. Journal of Geochemical Exploration, 2019, 207: 106360. DOI: https://doi.org/10.1016/j.gexplo.2019.106360.

    Article  Google Scholar 

  19. XUE Sheng-guo, WANG Yuan-yuan, JIANG Jun, et al. Groundwater heavy metal(loid)s risk prediction based on topsoil contamination and aquifer vulnerability at a zinc smelting site [J]. Environmental Pollution, 2024, 341: 122939. DOI: https://doi.org/10.1016/j.envpol.2023.122939.

    Article  Google Scholar 

  20. RUI Xuan, GONG Hua-bo, YUAN Hai-ping, et al. Distribution, removal and ecological risk assessment of antibiotics in leachate from municipal solid waste incineration plants in Shanghai, China [J]. The Science of the Total Environment, 2023, 900: 165894. DOI: https://doi.org/10.1016/j.scitotenv.2023.165894.

    Article  Google Scholar 

  21. LIU Fu-tian, WANG Xue-qiu, DAI Shuang, et al. Impact of different industrial activities on heavy metals in floodplain soil and ecological risk assessment based on bioavailability: A case study from the Middle Yellow River Basin, northern China [J]. Environmental Research, 2023, 235: 116695. DOI: https://doi.org/10.1016/j.envres.2023.116695

    Article  Google Scholar 

  22. JIANG Feng, REN Bo-zhi, HURSTHOUSE A, et al. Distribution, source identification, and ecological-health risks of potentially toxic elements (PTEs) in soil of thallium mine area (southwestern Guizhou, China) [J]. Environmental Science and Pollution Research International, 2019, 26(16): 16556–16567. DOI: https://doi.org/10.1007/s11356-019-04997-3.

    Article  Google Scholar 

  23. ZOU Hao, REN Bo-zhi, DENG Xin-ping, et al. Geographic distribution, source analysis, and ecological risk assessment of PTEs in the topsoil of different land uses around the antimony tailings tank: A case study of Longwangchi tailings pond, Hunan, China [J]. Ecological Indicators, 2023, 150: 110205. DOI: https://doi.org/10.1016/j.ecolind.2023.110205.

    Article  Google Scholar 

  24. NAZZAL Y, ZAIDI F K, ABUAMARAH B A, et al. Evaluation of metals that are potentially toxic to agricultural surface soils, using statistical analysis, in northwestern Saudi Arabia [J]. Environmental Earth Sciences, 2016, 75(2): 171. DOI: https://doi.org/10.1007/s12665-015-4800-1.

    Article  Google Scholar 

  25. LI Chu-xuan, LI Mu, ZENG Jia-qing, et al. Migration and distribution characteristics of soil heavy metal(loid)s at a lead smelting site [J]. Journal of Environmental Sciences, 2024, 135: 600–609. DOI: https://doi.org/10.1016/j.jes.2023.02.007.

    Article  Google Scholar 

  26. RASHED M N. Monitoring of contaminated toxic and heavy metals, from mine tailings through age accumulation, in soil and some wild plants at Southeast Egypt [J]. Journal of Hazardous Materials, 2010, 178(1 – 3): 739–746. DOI: https://doi.org/10.1016/j.jhazmat.2010.01.147.

    Article  Google Scholar 

  27. XIE Qing, REN Bo-zhi, SHI Xi-yang, et al. Factors on the distribution, migration, and leaching of potential toxic metals in the soil and risk assessment around the zinc smelter [J]. Ecological Indicators, 2022, 144: 109502. DOI: https://doi.org/10.1016/j.ecolind.2022.109502.

    Article  Google Scholar 

  28. MAO Ling-chen, LIU Li-bo, YAN Nan-xia, et al. Factors controlling the accumulation and ecological risk of trace metal(loid)s in river sediments in agricultural field [J]. Chemosphere, 2020, 243: 125359. DOI: https://doi.org/10.1016/j.chemosphere.2019.125359.

    Article  Google Scholar 

  29. KEBONYE N M, EZE P N, JOHN K, et al. Self-organizing map artificial neural networks and sequential Gaussian simulation technique for mapping potentially toxic element hotspots in polluted mining soils [J]. Journal of Geochemical Exploration, 2021, 222: 106680. DOI: https://doi.org/10.1016/j.gexplo.2020.106680.

    Article  Google Scholar 

  30. WU Jia-jun, HUANG Zheng, QIAO Hong-chao, et al. Prediction about residual stress and microhardness of material subjected to multiple overlap laser shock processing using artificial neural network [J]. Journal of Central South University, 2022, 29(10): 3346–3360. DOI: https://doi.org/10.1007/s11771-022-5158-7.

    Article  Google Scholar 

  31. LI Tao, SUN Gui-hua, YANG Chu-peng, et al. Using self-organizing map for coastal water quality classification: Towards a better understanding of patterns and processes [J]. The Science of the Total Environment, 2018, 628–629: 1446–1459. DOI: https://doi.org/10.1016/j.scitotenv.2018.02.163.

    Article  Google Scholar 

  32. FEI Jiang-chi, MIN Xiao-bo, WANG Zhen-xing, et al. Health and ecological risk assessment of heavy metals pollution in an antimony mining region: A case study from South China [J]. Environmental Science and Pollution Research International, 2017, 24(35): 27573–27586. DOI: https://doi.org/10.1007/s11356-017-0310-x.

    Article  Google Scholar 

  33. CHEN Zhen-yu, ROAD D, ZHAO Yuan-yi, et al. Ecological risk assessment and cumulative early warning of heavy metals in the soils near the Luanchuan molybdenum polymetallic ore concentration area, Henan [J]. China Geology, 2023. DOI: https://doi.org/10.31035/cg2023003

  34. VICTOR T L, DAVID M. Ecological risk of trace metals in soil from gold mining region in South Africa [J]. Journal of Hazardous Materials Advances, 2022, 7: 100118. DOI: https://doi.org/10.1016/J.HAZADV.2022.100118.

    Article  Google Scholar 

  35. CAO Jie, XIE Cheng-yu, HOU Zhi-ru. Ecological evaluation of heavy metal pollution in the soil of Pb-Zn mines [J]. Ecotoxicology, 2022, 31(2): 259–270. DOI: https://doi.org/10.1007/s10646-021-02505-3.

    Article  Google Scholar 

  36. LV Jian-shu, LIU Yang, ZHANG Zu-lu, et al. Factorial Kriging and stepwise regression approach to identify environmental factors influencing spatial multi-scale variability of heavy metals in soils [J]. Journal of Hazardous Materials, 2013, 261: 387–397. DOI: https://doi.org/10.1016/j.jhazmat.2013.07.065.

    Article  Google Scholar 

  37. DENG Yan, JIANG Lu-hua, XU Liang-feng, et al. Spatial distribution and risk assessment of heavy metals in contaminated paddy fields - A case study in Xiangtan City, Southern China [J]. Ecotoxicology and Environmental Safety, 2019, 171: 281–289. DOI: https://doi.org/10.1016/j.ecoenv.2018.12.060.

    Article  Google Scholar 

  38. FENG Zhao-hui, DENG Li, GUO Yi-kai, et al. The spatial analysis, risk assessment and source identification for mercury in a typical area with multiple pollution sources in Southern China [J]. Environmental Geochemistry and Health, 2023, 45(6): 4057–4069. DOI: https://doi.org/10.1007/s10653-022-01436-0.

    Article  Google Scholar 

  39. LIU Hai-wei, ZHANG Yan, YANG Jia-shuo, et al. Quantitative source apportionment, risk assessment and distribution of heavy metals in agricultural soils from southern Shandong Peninsula of China [J]. Science of the Total Environment, 2021, 767: 144879. DOI: https://doi.org/10.1016/j.scitotenv.2020.144879.

    Article  Google Scholar 

  40. HAO Xin-rui, YI Xiao-yun, DANG Zhi, et al. Heavy metal sources, contamination and risk assessment in legacy Pb/Zn mining tailings area: Field soil and simulated rainfall [J]. Bulletin of Environmental Contamination and Toxicology, 2022, 109(4): 636–642. DOI: https://doi.org/10.1007/s00128-022-03555-x.

    Article  Google Scholar 

  41. HE Ying-ping, HAN Zhi-wei, WU Fu-zhong, et al. Spatial distribution and environmental risk of arsenic and antimony in soil around an antimony smelter of Qinglong County [J]. Bulletin of Environmental Contamination and Toxicology, 2021, 107(6): 1043–1052. DOI: https://doi.org/10.1007/s00128-021-03118-6.

    Article  Google Scholar 

  42. JIANG Feng, REN Bo-zhi, HURSTHOUSE A, et al. Evaluating health risk indicators for PTE exposure in the food chain: Evidence from a thallium mine area [J]. Environmental Science and Pollution Research, 2020, 27(19): 23686–23694. DOI: https://doi.org/10.1007/s11356-020-08733-0.

    Article  Google Scholar 

  43. REHMAN M Z U, RIZWAN M, HUSSAIN A, et al. Alleviation of cadmium (Cd) toxicity and minimizing its uptake in wheat (Triticum aestivum) by using organic carbon sources in Cd-spiked soil [J]. Environmental Pollution, 2018, 241: 557–565. DOI: https://doi.org/10.1016/j.envpol.2018.06.005.

    Article  Google Scholar 

  44. XUE Sheng-guo, KE Wen-shun, ZENG Jia-qing, et al. Pollution prediction for heavy metals in soil-groundwater systems at smelting sites [J]. Chemical Engineering Journal, 2023, 473: 145499. DOI: https://doi.org/10.1016/j.cej.2023.145499.

    Article  Google Scholar 

  45. KE Wen-shun, LI Chu-xuan, ZHU Feng, et al. The assembly process and co-occurrence patterns of soil microbial communities at a lead smelting site [J]. The Science of the Total Environment, 2023, 894: 164932. DOI: https://doi.org/10.1016/j.scitotenv.2023.164932.

    Article  Google Scholar 

  46. LUO Lei, MA Yi-bing, ZHANG Shu-zhen, et al. An inventory of trace element inputs to agricultural soils in China [J]. Journal of Environmental Management, 2009, 90(8): 2524–2530. DOI: https://doi.org/10.1016/j.jenvman.2009.01.011.

    Article  Google Scholar 

  47. XIAO Ran, GUO Di, ALI A, et al. Accumulation, ecological-health risks assessment, and source apportionment of heavy metals in paddy soils: A case study in Hanzhong, Shaanxi, China [J]. Environmental Pollution, 2019, 248: 349–357. DOI: https://doi.org/10.1016/j.envpol.2019.02.045.

    Article  Google Scholar 

  48. TIAN He-zhong, ZHOU Jun-rui, ZHU Chuan-yong, et al. A comprehensive global inventory of atmospheric Antimony emissions from anthropogenic activities, 1995–2010 [J]. Environmental Science & Technology, 2014, 48(17): 10235–10241. DOI: https://doi.org/10.1021/es405817u.

    Article  Google Scholar 

  49. CHEN Chao, ZHOU Jian. A new empirical chart for coal burst liability classification using Kriging method [J]. Journal of Central South University, 2023, 30(4): 1205–1216. DOI: https://doi.org/10.1007/s11771-023-5294-8.

    Article  Google Scholar 

Download references

Author information

Author notes

  1. ZOU Hao and LI Wu-qing contributed equally to this work.

Authors and Affiliations

  1. School of Civil Engineering, Hunan University of Science and Technology, Xiangtan, 411201, China

    Hao Zou  (邹昊) & Bo-zhi Ren  (任伯帜)

  2. Institute of Geological Survey of Hunan Province, Changsha, 410083, China

    Wu-qing Li  (李武清)

  3. School of Resource Security, Hunan University of Science and Technology, Xiangtan, 411201, China

    Qing Xie  (谢青)

  4. School of Earth Science and Spatial Information, Hunan University of Science and Technology, Xiangtan, 411201, China

    Bo-zhi Ren  (任伯帜), Zhao-qi Cai  (蔡昭奇) & Lu-yuan Chen  (陈禄源)

  5. College of Foreign Languages, Hunan University, Changsha, 410082, China

    Jin Wang  (王瑾)

Authors
  1. Hao Zou  (邹昊)
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wu-qing Li  (李武清)
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bo-zhi Ren  (任伯帜)
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Qing Xie  (谢青)
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhao-qi Cai  (蔡昭奇)
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Lu-yuan Chen  (陈禄源)
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jin Wang  (王瑾)
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

ZOU Hao: Methodology, Formal analysis, Data curation, Writing-original draft & Editing and Visualization, Investigation. LI Wu-qing: Methodology, Writing-Original, Investigation, Data curation. REN Bo-zhi: Conceptualization, Supervision. XIE Qing: Methodology. CHEN Lu-yuan: Data curation; CAI Zhao-qi: Investigation, Resources. WANG Jin: Language censorship.

Corresponding author

Correspondence to Bo-zhi Ren  (任伯帜).

Ethics declarations

ZOU Hao, LI Wu-qing, REN Bo-zhi, XIE Qing, CHEN Lu-yuan, CAI Zhao-qi and WANG Jin declare that they have no conflict of interest.

Additional information

Foundation item: Project(41973078) supported by the National Natural Science Foundation of China; Project(2022SK2073) supported by the Hunan Provincial Natural Science Foundation of China

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zou, H., Li, Wq., Ren, Bz. et al. Heavy metal pollution and ecological risk assessment: A study on Linli County soils based on self-organizing map and positive factorization approaches. J. Cent. South Univ. (2024). https://doi.org/10.1007/s11771-024-5624-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11771-024-5624-5

Key words

关键词

Search

Navigation