Statistical study of Khibiny Alkaline Massif (Kola Peninsula) groundwater quality with respect to elevated aluminum concentrations

Current study addresses a problem of elevated aluminum concentrations deteriorating Khibiny Alkaline Massif groundwater quality. The application of chemometric methods to the field dataset 1999-2018 allows to quantitatively describe the groundwater quality, reveal variability patterns and potential sources of elevated aluminum level in the groundwater. The field dataset contains almost 40% more observations of 12 physicochemical groundwater quality parameters than the dataset analyzed in our previous studies on Khibiny groundwater quality assessment reported in the literature. The results revealed statistically significant (a-level=0.05) associations between Al and pH, Cl-, NO3-, SO42- according to the calculated matrix using distance correlation method. The mathematical models developed with the application of multiple regression and factor/principal component analysis elucidate up to 55.5% Al concentration variability and up to 68.3% of total dataset variance. Calculated for the 19-year period the water quality index values, which changed in early 2000s from fair to a marginal category, still belongs to this category reflecting unsatisfactory water quality conditions. Comparing the current study results to the conclusions drawn in our previous publications it is assumed that the main factors determining substandard groundwater quality have remained the same since last groundwater quality assessment reported in the literature. The examined combination of chemometric methods allows to gain insight into the main features of variability patterns of water quality characteristics and the potential sources of groundwater contamination. This approach forms a reliable foundation for enhancing groundwater quality monitoring and control in the Arctic region of interest and other locations experiencing similar problems. [GRAPHICS] .

Automated summary

Current study addresses the issue of elevated aluminum concentrations deteriorating groundwater quality in the Khibiny Alkaline Massif. By applying chemometric methods to a dataset spanning from 1999 to 2018, the study quantitatively describes groundwater quality, identifies patterns of variability, and potential sources of aluminum contamination. Results show significant associations between aluminum and pH, Cl-, NO3-, SO42-, as well as developed mathematical models elucidating variability in aluminum concentration and dataset variance. The study highlights the importance of this approach for enhancing groundwater quality monitoring and control in the Arctic region and other areas facing similar issues.