Source Apportionment of Heavy Metal Pollution in Agricultural Soils around the Poyang Lake Region Using UNMIX Model

被引:24
|
作者
Li, Yanhong [1 ,2 ]
Kuang, Huifen [1 ]
Hu, Chunhua [1 ]
Ge, Gang [1 ]
机构
[1] Nanchang Univ, Sch Resource Environm & Chem Engn, Minist Educ, Key Lab Poyang Lake Environm & Resource Utilizat, Nanchang 330029, Jiangxi, Peoples R China
[2] Jiangxi Inst Water Sci, Jiangxi Prov Key Lab Water Resources & Environm P, Nanchang 330029, Jiangxi, Peoples R China
基金
中国国家自然科学基金;
关键词
heavy metals; agricultural soil; UNMIX model; source apportionment; POSITIVE MATRIX FACTORIZATION; GEOSTATISTICAL ANALYSES; SOURCE IDENTIFICATION; SPATIAL-DISTRIBUTION; SURFACE SOILS; URBAN SOILS; MULTIVARIATE; SEDIMENTS; WETLAND; RISK;
D O I
10.3390/su13095272
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Rapid urbanization and industrialization have caused the continuous discharge of heavy metals into the soils of China's Poyang Lake region, where they pose a major threat to human health. Yet, the spatial characteristics of these heavy metals in farmland soils and their pollution sources in this region remain unclear. This study was conducted to document the pollution caused by heavy metals in the Poyang Lake region through sampling that consisted of the collection of 215 soil samples from agricultural fields. The UNMIX model provided identification of the sources causing heavy metal pollution and source contributions to soil pollution. ArcGIS was used to study the spatial distribution of the eleven heavy metals and to validate the apportionment of pollution sources provided by the UNMIX model. Soil concentrations of heavy metals were above the local background concentrations. The average content of eight heavy metals, including Cd, Mo, Zn, Cu, Sb, W, Pb, and Ni, was approximately 1-6 times greater than natural background levels (6.91, 2.0, 1.67, 1.53, 1.23, 1.38, 1.11, and 1.24, respectively), while the average content of V, Cr, and Co was lower than natural background levels. The average contents of Cr, Ni, Cu, Zn, Cd, and Pb were all lower than the screening levels for unacceptable risks in agricultural land soils. The percentage of Cd content exceeded the risk screening value in all sampling sites, up to 55%, indicating that agricultural soils may significantly be affected by cadmium contamination. Five pollution sources of heavy metals were identified: natural sources, copper mine tailings, agricultural activities, atmospheric depositions, and industrial activities. The contribution rates of the pollution sources were 7%, 13%, 20%, 29%, and 31%, respectively. The spatial pattern of heavy metals was closely aligned with the outputs of the UNMIX model. The foregoing supports the utility of the UNMIX model for the identification of pollution sources of heavy metals, apportionment study, and its implementation in agricultural soils in the Poyang Lake region.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Source Apportionment of Heavy Metals in Farmland Soils Around Mining Area Based on UNMIX Model
    Lu, Xin
    Hu, Wen-You
    Huang, Biao
    Li, Yuan
    Zu, Yan-Qun
    Zhan, Fang-Dong
    Kuang, Rong-Xi
    [J]. Huanjing Kexue/Environmental Science, 2018, 39 (03): : 1421 - 1429
  • [2] Quantitative source apportionment of heavy metal(loid)s in the agricultural soils of an industrializing region and associated model uncertainty
    Hu, Yuanan
    He, Kailing
    Sun, Zehang
    Chen, Gang
    Cheng, Hefa
    [J]. JOURNAL OF HAZARDOUS MATERIALS, 2020, 391
  • [3] Sources apportionment and spatial prediction of soil heavy metal pollution using UNMIX model and multivariate statistical simulation
    Yang, Qingke
    Wang, Lei
    Li, Pingxing
    Lyu, Ligang
    Fan, Yeting
    Zhu, Gaoli
    Wang, Yazhu
    [J]. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2024, 40 (04): : 224 - 234
  • [4] The quantitative source apportionment of heavy metals in peri-urban agricultural soils with UNMIX and input fluxes analysis
    Liao, Shiyan
    Jin, Gaoqi
    Khan, Muhammad Aman
    Zhu, Youwei
    Duan, Lili
    Luo, Wenxuan
    Jia, Junwei
    Zhong, Bin
    Ma, Jiawei
    Ye, Zhengqian
    Liu, Dan
    [J]. ENVIRONMENTAL TECHNOLOGY & INNOVATION, 2021, 21 (21)
  • [5] Source Apportionment of Groundwater Pollution using Unmix and Positive Matrix Factorization
    Gulgundi, Mohammad Shahid
    Shetty, Amba
    [J]. ENVIRONMENTAL PROCESSES-AN INTERNATIONAL JOURNAL, 2019, 6 (02): : 457 - 473
  • [6] Source Apportionment of Groundwater Pollution using Unmix and Positive Matrix Factorization
    Mohammad Shahid Gulgundi
    Amba Shetty
    [J]. Environmental Processes, 2019, 6 : 457 - 473
  • [7] Combination of UNMIX, PMF model and Pb-Zn-Cu isotopic compositions for quantitative source apportionment of heavy metals in suburban agricultural soils
    Chen, Zhifan
    Ding, Yongfeng
    Jiang, Xingyuan
    Duan, Haijing
    Ruan, Xinling
    Li, Zhihong
    Li, Yipeng
    [J]. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY, 2022, 234
  • [8] Source Analysis of Heavy Metal Pollution Using UNMIX and PMF Models in Soils along the Shuimo River in Urumqi, China
    Zang, Honggang
    Zhang, Yidan
    Yao, Junqin
    Ma, Huiying
    [J]. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (22)
  • [9] An integrated method for source apportionment of heavy metal(loid)s in agricultural soils and model uncertainty analysis
    Wang, Yuntao
    Guo, Guanghui
    Zhang, Degang
    Lei, Mei
    [J]. ENVIRONMENTAL POLLUTION, 2021, 276
  • [10] Improved heavy metal mapping and pollution source apportionment in Shanghai City soils using auxiliary information
    Fei, Xufeng
    Christakos, George
    Xiao, Rui
    Ren, Zhouqiao
    Liu, Yue
    Lv, Xiaonan
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 661 : 168 - 177