Source apportionment of an epiphytic lichen biomonitor to elucidate the sources and spatial distribution of polycyclic aromatic hydrocarbons in the Athabasca Oil Sands Region, Alberta, Canada
Bibliographic record
Abstract
The sources and spatial distribution of polycyclic aromatic hydrocarbons (PAHs) atmospheric deposition in the boreal forests surrounding bitumen production operations in the Athabasca Oil Sands Region (AOSR), Alberta, Canada were investigated as part of a 2014 passive in-situ bioindicator source apportionment study. Epiphytic lichen species Hypogymnia physodes samples (n = 127) were collected within a 150 km radius of the main surface oil sand production operations and analyzed for total sulfur, total nitrogen, forty-three elements, twenty-two PAHs, ten groups of C1-C2-alkyl PAHs and dibenzothiophenes (polycyclic aromatic compounds; PACs), five C1- and C2-alkyldibenzothiophenes, and retene. The ΣPAH + PAC in H. physodes ranged from 54 to 2778 ng g −1 with a median concentration of 317 ng g −1 . Source apportionment modeling found an eight-factor solution that explained 99% of the measured ΣPAH + PAC lichen concentrations from four anthropogenic oil sands production sources (Petroleum Coke, Haul Road Dust, Stack Emissions, Raw Oil Sand), two local/regional sources (Biomass Combustion, Mobile Source), and two lichen biogeochemical factors. Petroleum Coke and Raw Oil Sand dust were identified as the major contributing sources of ΣPAH + PAC in the AOSR. These two sources accounted for 63% (43.2 μg g −1 ) of ΣPAH + PAC deposition to the entire study domain. Of this overall 43.2 μg g −1 contribution, approximately 90% (39.9 μg g −1 ) ΣPAH + PAC was deposited within 25 km of the closest oil sand production facility. Regional sources (Biomass Combustion and Mobile Sources) accounted for 19% of ΣPAH + PAC deposition to the entire study domain, of which 46% was deposited near-field to oil sand production operations. Source identification was improved over a prior lichen-based study in the AOSR through incorporation of PAH and PAC analytes in addition to inorganic analytes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".