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Spatial distribution characteristics and prediction of fluorine concentration in groundwater based on driving factors analysis

Mu-Yuan Lu, Yuan Liu*, Gui-Jian Liu*, Yong-Li Li, Jin-Zhao Xu, Guan-Yu Wang

*Corresponding author for this work

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Abstract

    Excess fluoride (F) in groundwater can be hazardous to human health. A total of 360 ground water samples was collected from northern Anhui, China, to study the levels, distribution, and source of F. And on this basis, predicting the spatial distribution of F in a wider scale space. The range of F was 0.1–5.8 mg/L, with a mean value of 1.2 mg/L, and 26.4 % of the samples exceeded the acceptable level of 1.5 mg/L. Moreover, the water-rock interaction (fluorite dissolution) and cation alternate adsorption were considered to be two main driving factors of high F in groundwater. To further illustrate the spatial effects, the BME-RF model was established by combining the main environmental factors. The spatial distribution of F was quantitatively predicted, and the response to environmental variables was analyzed. The R2 of BME-RF model reached 0.93, the prediction results showed that the region with 1.0–1.5 mg/L of F accounts for 47.2 % of the total area. The predicted F content of nearly 70 % of groundwater in this area has exceeded 1.0 mg/L, which was dominated by Na+ and HCO3 type. The spatial variability of F in the study area was mainly affected by hydrogeological conditions, and the vertical distribution characteristics were related to the spatial variation of slope, distance from runoff, and hydrochemical types. The results of the study provide new insights into the F concentration prediction in underground environment, especially in the borehole gap area.
    Original languageEnglish
    Article number159415
    JournalScience of the Total Environment
    Volume857
    Issue numberPart 1
    Online published13 Oct 2022
    DOIs
    Publication statusPublished - 20 Jan 2023

    Research Keywords

    • Bayesian maximum entropy
    • Fluoride
    • Hydrochemical type
    • Vertical distribution

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