Defining Natural Background Levels for Groundwater in a Brazilian Coal Mining Region: A Statistical Assessment of Historical Data

Groundwater quality in coal-bearing regions is often compromised by natural and anthropogenic sulfide mineral oxidation, challenging the application of standard environmental limits. This study aims to define Natural Background Levels (NBLs) for groundwater of Transgressive Sand Sequence aquifer interval in the South Santa Catarina Coalfield, Brazil, and to evaluate the effectiveness of different statistical methods for this purpose. Using a historical database of 66 analyses from 19 unimpacted wells, we compared three outlier removal techniques: the interquartile range (IQR), the modified Z-score, and the iterative Grubbs' test. The resulting datasets were used to estimate NBLs for pH, Eh, electrical conductivity, sulfate, Fe, Al, and Mn, and were further assessed using Pearson correlation and Principal Component Analysis (PCA) to verify hydrogeochemical coherence. Results show the Grubbs' test was the most robust method, preserving natural data heterogeneity and providing the most geochemically consistent dataset. The NBLs estimated from the Grubbs' dataset revealed naturally acidic conditions (pH 4.43–6.25) and elevated concentrations of Al, Fe, and Mn, frequently exceeding Brazilian drinking water standards. PCA of the Grubbs’ data explained 60% of the total variance, effectively separating variables associated with sulfide oxidation. This study demonstrates that the Grubbs' test is a superior tool for establishing realistic NBLs in geologically complex areas, highlighting that generic water quality legislation may be inadequate for recovery and rehabilitation targets of regions with significant mineralization.