eprintid: 1713
rev_number: 13
eprint_status: archive
userid: 6
dir: disk0/00/00/17/13
datestamp: 2016-09-15 11:09:22
lastmod: 2017-02-08 12:21:33
status_changed: 2016-09-15 11:09:22
type: article
metadata_visibility: show
creators_name: Chen, Yuan
creators_name: McPhedran, Kerry N.
creators_name: Perez-Estrada, Leonidas
creators_name: Gamal El-Din, Mohamed
corp_creators: Department of Civil and Environmental Engineering, Natural Resources Engineering Facility, University of Alberta,Canada
corp_creators: Department of Civil and Environmental Engineering, Natural Resources Engineering Facility, University of Alberta,Canada
corp_creators: Department of Civil and Environmental Engineering, Natural Resources Engineering Facility, University of Alberta,Canada
corp_creators: Department of Civil and Environmental Engineering, Natural Resources Engineering Facility, University of Alberta,Canada
title: An omic approach for the identification of oil sands process-affected water compounds using multivariate statistical analysis of ultrahigh resolution mass spectrometry datasets
subjects: O
subjects: RCA
subjects: SHC
subjects: SHU
divisions: SHEER
full_text_status: none
keywords: Oil sands process-affected water; Naphthenic acids; Advanced oxidation processes; High resolution mass spectrometry; Multivariate analysis
abstract: 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 behaviours 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.
date: 2015-11
date_type: published
publication: Science of The Total Environment
volume: 511
publisher: Elsevier
pagerange: 230-237
id_number: doi:10.1016/j.scitotenv.2014.12.045
issn: 0048-9697
official_url: http://doi.org/10.1016/j.scitotenv.2014.12.045
access_IS-EPOS: limited
owner: Publisher
citation:   Chen, Yuan and McPhedran, Kerry N. and Perez-Estrada, Leonidas and Gamal El-Din, Mohamed  (2015) An omic approach for the identification of oil sands process-affected water compounds using multivariate statistical analysis of ultrahigh resolution mass spectrometry datasets.  Science of The Total Environment, 511.  pp. 230-237. DOI: https://doi.org/10.1016/j.scitotenv.2014.12.045 <https://doi.org/10.1016/j.scitotenv.2014.12.045>