Distinguishing Natural from Anthropogenic Sources of Acid Extractable Organics in Groundwater near Oil Sands Tailings Ponds
Author(s) -
Jason M. E. Ahad,
Hooshang Pakdel,
P Gammon,
Bernhard Mayer,
Martine M. Savard,
Kerry M. Peru,
John V. Headley
Publication year - 2020
Publication title -
environmental science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.851
H-Index - 397
eISSN - 1520-5851
pISSN - 0013-936X
DOI - 10.1021/acs.est.9b06875
Subject(s) - oil sands , tailings , environmental chemistry , groundwater , environmental science , diamondoid , isotope analysis , geology , asphalt , chemistry , oceanography , geotechnical engineering , cartography , organic chemistry , molecule , geography
Distinguishing between naphthenic acids (NAs) associated with oil sands process-affected water (OSPW) and those found naturally in groundwaters in contact with the bituminous McMurray Formation poses a considerable analytical challenge to environmental research in Canada's oil sands region. Previous work addressing this problem combined high-resolution Orbitrap mass spectrometry with carbon isotope values generated by online pyrolysis (δ 13 C pyr ) to characterize and quantify the acid extractable organics (AEOs) fraction containing NAs in the subsurface near an oil sands tailings pond. Here, we build upon this work through further development and application of these techniques at two different study sites near two different tailings ponds, in conjunction with the use of an additional isotopic tool-sulfur isotope analysis (δ 34 S) of AEOs. The combined use of both δ 13 C pyr and δ 34 S allowed for discrimination of AEOs into the three end-members relevant to ascertaining the NA environmental footprint within the region: (1) OSPW; (2) McMurray Formation groundwater (i.e., naturally occurring bitumen), and; (3) naturally occurring non-bitumen. A Bayesian isotopic mixing model was used to determine the relative proportions of these three sources in groundwater at both study sites. Although background levels of OSPW-derived AEOs were generally low, one sample containing 49-99% (95% credibility interval) OSPW-derived AEOs was detected within an inferred preferential flow-path, highlighting the potential for this technique to track tailings pond seepage.
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