Priority sources identification and risks assessment of heavy metal(loid)s in agricultural soils of a typical antimony mining watershed

被引:7
作者
Liu, Lianhua [1 ]
Li, You [2 ]
Gu, Xiang [3 ]
Tulcan, Roberto Xavier Supe [3 ]
Yan, Lingling [4 ]
Lin, Chunye [3 ]
Pan, Junting [5 ]
机构
[1] Chinese Acad Agr Sci, Inst Environm & Sustainable Dev Agr, Beijing 100081, Peoples R China
[2] Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
[3] Beijing Normal Univ, Sch Environm, Beijing 100875, Peoples R China
[4] Yiyang Acad Agr Sci, Yiyang 413099, Peoples R China
[5] Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China
来源
JOURNAL OF ENVIRONMENTAL SCIENCES | 2025年 / 147卷
基金
中国国家自然科学基金;
关键词
Antimony; Heavy metal(loid); Risk assessment; Pollution sources; Mining and smelting; SPATIAL-DISTRIBUTION; METAL POLLUTION; APPORTIONMENT; PROVINCE; CHINA; HUNAN; SB;
D O I
10.1016/j.jes.2023.11.007
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Heavy metal(loid) (HM) pollution in agricultural soils has become an environmental concern in antimony (Sb) mining areas. However, priority pollution sources identification and deep understanding of environmental risks of HMs face great challenges due to multiple and complex pollution sources coexist. Herein, an integrated approach was conducted to distinguish pollution sources and assess human health risk (HHR) and ecological risk (ER) in a typical Sb mining watershed in Southern China. This approach combines absolute principal component score -multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models with ER and HHR assessments. Four pollution sources were distinguished for both models, and APCS-MLR model was more accurate and plausible. Predominant HM concentration source was natural source (39.1%), followed by industrial and agricultural activities (23.0%), unknown sources (21.5%) and Sb mining and smelting activities (16.4%). Although natural source contributed the most to HM concentrations, it did not pose a significant ER. Industrial and agricultural activities predominantly contributed to ER, and attention should be paid to Cd and Sb. Sb mining and smelting activities were primary anthropogenic sources of HHR, particularly Sb and As contaminations. Considering ER and HHR assessments, Sb mining and smelting, and industrial and agricultural activities are critical sources, causing serious ecological and health threats. This study showed the advantages of multiple receptor model application in obtaining reliable source identification and providing better source -oriented risk assessments. HM pollution management, such as regulating mining and smelting and implementing soil remediation in polluted agricultural soils, is strongly recommended for protecting ecosystems and humans. (c) 2024 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.
引用
收藏
页码:153 / 164
页数:12
相关论文
共 54 条
  • [51] Assessment of heavy metal contamination, distribution and source identification in the sediments from the Zijiang River, China
    Zhang, Zhaoxue
    Lu, Yi
    Li, Haipu
    Tu, Yi
    Liu, Boyu
    Yang, Zhaoguang
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2018, 645 : 235 - 243
  • [52] Identification and hazard analysis of heavy metal sources in agricultural soils in ancient mining areas: A quantitative method based on the receptor model and risk assessment'
    Zhou, Hao
    Chen, Yong
    Yue, Xuemei
    Ren, Dajun
    Liu, Yanzhong
    Yang, Ke
    [J]. JOURNAL OF HAZARDOUS MATERIALS, 2023, 445
  • [53] Farmers? adaptation to heavy metal pollution in farmland in mining areas: The effects of farmers? perceptions, knowledge and characteristics
    Zhou, Hao
    Chen, Yong
    Liu, Yanzhong
    Wang, Qiaozhi
    Liang, Yaqi
    [J]. JOURNAL OF CLEANER PRODUCTION, 2022, 365
  • [54] Identification priority source of soil heavy metals pollution based on source-specific ecological and human health risk analysis in a typical smelting and mining region of South China
    Zhou, Lingfeng
    Zhao, Xiaoli
    Meng, Yaobin
    Fei, Yang
    Teng, Miaomiao
    Song, Fanhao
    Wu, Fengchang
    [J]. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY, 2022, 242