Organic and nitrogen pollutants in mine water could be removed effectively during the storage and transport of water in a coal mine underground reservoir packed with coal gangue through various water-rock interactions. However, little is known about the effect of the released dissolved organic matter (DOM) derived from the packed matrix on their removal. Column experiments were performed at a Darcy flux of 1.56 cm·h-1 at 25 °C to investigate the characteristics of DOM derived from Jurassic and Permian coal gangue individually packed in underground reservoirs of Bulianta (BL1) and Baode (BD2) coal mines. Chemical characteristics of the DOM were analyzed by using the ultraviolet and visible (UV-Vis) absorbance and fluorescence spectroscopy techniques. Results showed that the values of dissolved organic carbon (DOC) and electricity (EC) in the outlet of column packed with BL1 were obviously higher than those from BD2 due to the higher permeability of BL1 with more complex mineralogical and chemical compositions. The parallel factor analysis (PARAFAC) indicated that the fluorescence components in the DOM derived from BL1 and BD2 were individually dominated by the humic-like and tryptophan-like substances. Thus, the higher aromaticity, hydrophobicity, and humification indicated by the specific ultraviolet absorbance at 254 nm (SUVA254) and 260 nm (SUVA260) and humification index (HIX) were observed in the DOM from the younger Jurassic BL1, implying that the DOM may contain more plant-derived precursors. Meanwhile, the higher values of fluorescence index (FI) and biological/autochthonous index (BIX) confirmed the stronger autochthonous characterization of DOM originated from the earlier Permian BD2. The observed characterization of DOM will further extend the understanding of purification mechanism of mine water during its storage and transport in coal mine underground reservoirs packed with coal gangue of different geologic ages.
Keywords: Coal gangue; Coal mine underground reservoirs; Dissolved organic matter; Mine water; Parallel factor analysis (PARAFAC).