Assessment of geothermal waters in Yunnan, China: Distribution, quality and driving factors

被引:0
|
作者
Zeng, Zhaojun [1 ]
Yang, Li [3 ]
Cui, Yueju [1 ]
Zhou, Xiaocheng [1 ,2 ]
He, Miao [1 ]
Wang, Yuwen [1 ]
Yan, Yucong [1 ]
Yao, Bingyu [2 ]
Hu, Xiaojing [3 ]
Shao, Weiye [3 ]
Li, Jian [3 ]
Fu, Hong [3 ]
机构
[1] China Earthquake Adm, Inst Earthquake Forecasting, United Lab High Pressure Phys & Earthquake Sci, Beijing 100036, Peoples R China
[2] China Univ Geosci, Sch Earth Sci & Resources, Beijing 100083, Peoples R China
[3] Yunnan Earthquake Agcy, Kunming 650224, Peoples R China
基金
中国国家自然科学基金;
关键词
Self-Organizing Map; Yunnan province; Geothermal water; Water quality; Health risk assessment; SELF-ORGANIZING MAPS; HYDROCHEMICAL CHARACTERISTICS; GROUNDWATER QUALITY; RIVER WATER; HOT-SPRINGS; GEOCHEMISTRY; OXIDATION; CLASSIFICATION; IDENTIFICATION; PROVINCE;
D O I
10.1016/j.geothermics.2025.103323
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Geothermal energy is a vital renewable resource widely used for various applications, including drinking water, domestic supply, irrigation, and industrial purposes. However, the utilization of geothermal water for drinking can expose individuals to toxic elements, particularly arsenic, which poses significant health risks. Despite the growing interest in geothermal water, there has been a lack of systematic analysis regarding the spatial variability of its quality and health risk. This study aims to address this gap by evaluating the spatial variability of the water quality characteristics and health risks in Yunnan Province using a combination of hydrochemical and isotopic methods, Principal Component Analysis (PCA), Self-Organizing Maps (SOM) and integrated tools such as Water Quality Index (WQI) and Human Health Risk Assessment (HHRA). According to this study, atmospheric precipitation serves as the primary recharge source with Na-HCO3, Ca-HCO3, Na-Cl and Ca-Cl as the dominant geothermal water hydrochemical in Yunnan Province. While most samples exhibit good water quality, those from the northwestern regions (e.g., Lijiang, Lincang, Kunming, Baoshan, Jinghong, Pu'er, and Dali) show poorer water quality and significant health risks. PCA analysis reveals that the spatial variability of geothermal water quality is largely influenced by deep hydrological cycles and magma-tectonic interactions, resulting in arsenic enrichment in high-risk areas. This study addresses the research gap regarding the spatial variability of geothermal water quality and health risk assessment in Yunnan Province and provides a scientific foundation for sustainable development and management.
引用
收藏
页数:14
相关论文
共 50 条
  • [41] Mismatch distribution of population and industry in China: Pattern, problems and driving factors
    Guan, Xingliang
    Wei, Houkai
    Lu, Shasha
    Su, Hongjian
    APPLIED GEOGRAPHY, 2018, 97 : 61 - 74
  • [42] A study on the spatial distribution of the renewable energy industries in China and their driving factors
    Wang, Qiang
    Kwan, Mei-Po
    Fan, Jie
    Zhou, Kan
    Wang, Ya-Fei
    RENEWABLE ENERGY, 2019, 139 : 161 - 175
  • [43] Analysis of Spatial Distribution of Ecosystem Services and Driving Factors in Northeast China
    Wang, Jia-Qi
    Xing, Yan-Qiu
    Chang, Xiao-Qing
    Yang, Hong
    Huanjing Kexue/Environmental Science, 2024, 45 (09): : 5385 - 5394
  • [44] Overwintering Distribution of Fall Armyworm (Spodoptera frugiperda) in Yunnan, China, and Influencing Environmental Factors
    Huang, Yanru
    Dong, Yingying
    Huang, Wenjiang
    Ren, Binyuan
    Deng, Qiaoyu
    Shi, Yue
    Bai, Jie
    Ren, Yu
    Geng, Yun
    Ma, Huiqin
    INSECTS, 2020, 11 (11)
  • [45] Spatial-Temporal Distribution and the Influencing Factors of Water Conservation Function in Yunnan, China
    Qin, Zhuo
    Yang, Jiameng
    Qiu, Mengyuan
    Liu, Zhiyong
    APPLIED SCIENCES-BASEL, 2023, 13 (21):
  • [46] Delineating the controlling mechanisms of geothermal waters quality and suitability zoning in the Lower Yellow River Basin, China
    Dong, Fangying
    Yin, Huiyong
    Yang, Zhibing
    Zhou, Wanfang
    Cheng, Wenju
    Liu, Yongming
    ENVIRONMENTAL TECHNOLOGY & INNOVATION, 2025, 38
  • [47] Risk assessment and key driving factors of phosphorus loss in farmland of China
    Zheng B.
    Liu H.
    Wu H.
    Wu Z.
    Liu Z.
    Zhu J.
    Wan W.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2024, 40 (02): : 332 - 343
  • [48] Mapping the spatial distribution of fossil geothermal manifestations and assessment of geothermal potential of the Tangyin rift, Southeast of Taihang Mountain in China
    Joshua Mahwa
    Da-jiang Li
    Jian-hua Ping
    Wei Leng
    Jia-bo Tang
    Dong-yun Shao
    Journal of Mountain Science, 2022, 19 : 2241 - 2259
  • [49] Mapping the spatial distribution of fossil geothermal manifestations and assessment of geothermal potential of the Tangyin rift, Southeast of Taihang Mountain in China
    MAHWA Joshua
    LI Da-jiang
    PING Jian-hua
    LENG Wei
    TANG Jia-bo
    SHAO Dong-yun
    JournalofMountainScience, 2022, 19 (08) : 2241 - 2259
  • [50] Mapping the spatial distribution of fossil geothermal manifestations and assessment of geothermal potential of the Tangyin rift, Southeast of Taihang Mountain in China
    Mahwa, Joshua
    Li Da-jiang
    Ping Jian-hua
    Leng Wei
    Tang Jia-bo
    Shao Dong-yun
    JOURNAL OF MOUNTAIN SCIENCE, 2022, 19 (08) : 2241 - 2259