Stable isotope method for tracing oil sands bitumen sources, differentiating δ13C in four carbon fractions in water and acid-extractable organics

This study was conducted at an oil-sands operation in the North Athabasca Oil Sands Region, Alberta, Canada to identify suitable isotopic tracers for differentiating between processed (anthropogenic) and non-processed bitumen residues in water. A combination of isotopes of water, solutes, and acid-extractable organics (AEO) were measured in tailings ponds containing oil-sands process water (OSPW), groundwater from the basal McMurray Formation, and a variety of on-lease groundwater monitoring wells and mitigation structures, the latter designed to intercept potentially contaminated runoff. This study provides supporting evidence that tailings ponds are well-contained and are not hydraulically connected with monitoring wells in local Quaternary aquifers or underlying formations at the investigated site. Testing included individual isotopic tracers and dual isotope pairs, as well as comprehensive suites of both isotopes and naphthenic-acid (NA) species. An isotopic approach using δ<sup>13</sup>C in four distinct carbon fractions emerges from our assessment as a promising method for operational fingerprinting of processed and non-processed bitumen residues in water for tracking potential OSPW seepage at oil sands operations.

Authors

Institutions

Publication Details

Journal
The Science of The Total Environment
Published
2025-08-20
DOI
https://doi.org/10.1016/j.scitotenv.2025.180146
Citations
2
Primary Topic
Petroleum Processing and Analysis
Type
article
Field-Weighted Citation Impact
1.50

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Stable isotope method for tracing oil sands bitumen sources, differentiating δ13C in four carbon fractions in water and acid-extractable organics

Tamara Sîrbu, J. J. Gibson, P. Eby, Aprami Jaggi
2 citations
The Science of The Total Environment
Petroleum Processing and Analysis
1.50
article

Stable isotope method for tracing oil sands bitumen sources, differentiating δ13C in four carbon fractions in water and acid-extractable organics

Tamara Sîrbu, J. J. Gibson, P. Eby, Aprami Jaggi
article en
2 citations

Abstract

This study was conducted at an oil-sands operation in the North Athabasca Oil Sands Region, Alberta, Canada to identify suitable isotopic tracers for differentiating between processed (anthropogenic) and non-processed bitumen residues in water. A combination of isotopes of water, solutes, and acid-extractable organics (AEO) were measured in tailings ponds containing oil-sands process water (OSPW), groundwater from the basal McMurray Formation, and a variety of on-lease groundwater monitoring wells and mitigation structures, the latter designed to intercept potentially contaminated runoff. This study provides supporting evidence that tailings ponds are well-contained and are not hydraulically connected with monitoring wells in local Quaternary aquifers or underlying formations at the investigated site. Testing included individual isotopic tracers and dual isotope pairs, as well as comprehensive suites of both isotopes and naphthenic-acid (NA) species. An isotopic approach using δ<sup>13</sup>C in four distinct carbon fractions emerges from our assessment as a promising method for operational fingerprinting of processed and non-processed bitumen residues in water for tracking potential OSPW seepage at oil sands operations.

The Science of The Total EnvironmentVol. 998
Apotex (Canada) (CA)
Innotech Alberta
Openalex Percentile: Top 17%
Petroleum Processing and Analysis
1.50
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.