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 (α-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.

Study of aluminium in groundwater using chemometric methods.

The field dataset including physico-chemical characteristics of Khibiny alkaline massif groundwater aquifer was analysed for the first time by applying chemometric methods to explore the relationships between investigated parameters in both time and frequency domains. Elevated Al concentration in water of this aquifer is described as a serious health concern when used for the household water supply. The time series of 12 physico-chemical parameters were examined by using Pearson correlation, multiple linear regression and spectral analysis based on fast Fourier transform (FFT) algorithm. Computed pairwise correlation coefficients matrix revealed that pH values, NO3-, SO42-, Cl- and TDS correlate with Al concentrations at a statistically significant level (α-level = 0.05). The multiple regression model including Cl-, NO3- and pH explains up to 54% of Al concentrations temporal variation in groundwater. Fourier coefficients, power spectral density (PSD) and cumulative spectral power (CSP) were calculated for Al, pH, NO3- and Cl- time series to identify and analyse the strength of their variations as a function of frequency. Calculations revealed the spectrums of these variables include three main frequency bands corresponding approximately to 5-7, 13-17 and 20-34 month periods. The fluctuations within these bands contribute mostly to the total temporal variation of Al, Cl-, NO3- concentrations and pH values.