Assessing spatial and temporal variability of acid-extractable organics in oil sands process-affected waters. (October 2016) - Frank, Richard A.; Milestone, Craig B.; Rowland, Steve J.; Headley, John V.; Kavanagh, Richard J.; Lengger, Sabine K.; Scarlett, Alan G.; West, Charles E.; Peru, Kerry M.; Hewitt, L. Mark
Abstract: The acid-extractable organic compounds (AEOs), including naphthenic acids (NAs), present within oil sands process-affected water (OSPW) receive great attention due to their known toxicity. While recent progress in advanced separation and analytical methodologies for AEOs has improved our understanding of the composition of these mixtures, little is known regarding any variability (i.e., spatial, temporal) inherent within, or between, tailings ponds. In this study, 5 samples were collected from the same location of one tailings pond over a 2-week period. In addition, 5 samples were collected simultaneously from different locations within a tailings pond from a different mine site, as well as its associated recycling pond. In both cases, the AEOs were analyzed using SFS, ESI-MS, HRMS, GC×GC-ToF/MS, and GC- & LC-QToF/MS (GC analyses following conversion to methyl esters). Principal component analysis of HRMS data was able to distinguish the ponds from each other, while data from GC×GC-ToF/MS, and LC- and GC-QToF/MS were used to differentiate samples from within the temporal and spatial sample sets, with the greater variability associated with the latter. Spatial differences could be attributed to pond dynamics, including differences in inputs of tailings and surface run-off. Application of novel chemometric data analyses of unknown compounds detected by LC- and GC-QToF/MS allowed further differentiation of samples both within and between data sets, providing an innovative approach for future fingerprinting studies. Highlights: Spatial and temporal sample sets collected from two oil sands tailings ponds. Acid extractable organics analyzed by SFS, ESI-MS, HRMS, GC×GC-ToF, GC- & LC-QToF. Spatial sample set more variable than temporal samples; attributed to pond dynamics. Novel chemometric analyses of unknown compounds further differentiated samples. OSPW characterization requires water from multiple locations within a tailings pond.