Scavenging ratio of polycyclic aromatic compounds in rain and snow at the Athabasca oil sands region
Bibliographic record
Abstract
Abstract. Athabasca oil sands industry in northern Alberta, Canada is a possible source of polycyclic aromatic compounds (PACs). Monitored PACs, including polycyclic aromatic hydrocarbons (PAHs), alkylated PAHs, and dibenzothiophenes, in precipitation and in air at three near-source sites in the Fort MacKay and Fort McMurray area during May 2011 to August 2012 were analyzed to generate a database of scavenging (or washout) ratios (Wt) for PACs scavenged by both snow and rain. Median precipitation and air concentrations of parent PAHs over the May 2011 to August 2012 period ranged from 0.3–184.9 (chrysene) ng L−1 and 0.01–3.9 (naphthalene) ng m−3, respectively, which were comparable to literature values. Higher concentrations in precipitation and air were observed for alkylated PAHs and dibenzothiophenes. The median precipitation and air concentrations were 11.3–646.7 (C3-fluoranthene/pyrene) ng L−1 and 0.21–16.9 (C3-naphthalene) ng m−3, respectively, for alkylated PAHs, and 8.5–530.5 (C4-dibenzothiophene) ng L−1 and 0.13–6.6 (C2-dibenzothiophene) ng m−3 for dibenzothiophenes and their alkylated derivatives. Median Wt over the measurement period were 6100–1.1 × 106 from snow scavenging and 350–2.3 × 105 from rain scavenging depending on the PAC species. Median Wt for parent PAHs were within the range of those observed at other urban and suburban locations. But Wt for acenaphthylene in snow samples was 2–7 times higher. Some individual snow and rain samples exceeded literature values by a factor of 10. Wt for benzo(a)pyrene, dibenz(a,h)anthracene, and benzo(g,h,i)perylene in snow samples had reached 107, which is the maximum for PAH snow scavenging ratios reported in literature. From the analysis of data subsets, Wt for particulate-phase dominant PACs were 14–20 times greater than gas-phase dominant PACs in snow samples and 7–20 times greater than gas-phase dominant PACs in rain samples. Wt from snow scavenging was ∼9 times greater than rain scavenging for particulate-phase dominant PACs and 4–9.6 times greater than rain scavenging for gas-phase dominant PACs. Gas-particle fractions of each PAC, particle size distributions of particulate-phase dominant PACs, and Henry's Law constant of gas-phase dominant PACs explained, to a large extent, the different Wt values among the different PACs and precipitation types. This study verified findings from a previous study of Wang et al. (2014) which suggested that snow scavenging is more efficient than rain scavenging of particles for equivalent precipitation amount, and also provided new knowledge on the scavenging of gas-phase PACs by snow and rain.
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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 | 0.000 | 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".