An omic approach for the identification of oil sands process-affected water compounds using multivariate statistical analysis of ultrahigh resolution mass spectrometry datasets.

Oil sands process-affected water (OSPW) is a major environmental issue due to its acute and chronic toxicity to aquatic life. Advanced oxidation processes are promising treatments to successfully degrade toxic OSPW compounds. This study applied high resolution mass spectrometry to detect over 1000 compounds in OSPW samples after treatments including general ozonation, and ozone with carbonate, tert-butyl-alcohol, carbonate/tert-butyl-alcohol, tetranitromethane, or iron. Hierarchal clustering analysis showed that samples clustered based on sampling time and principal component analysis corroborated these results while also providing information on significant markers responsible for the clustering. Some markers were uniquely present in certain treatment conditions, while others showed variable behaviors in two or more treatments due to the presence of scavengers/catalysts. This advanced approach to monitoring significant changes of markers by using multivariate analysis can be invaluable for future work on OSPW treatment by-products and their potential toxicity to receiving environment organisms.