Carbonaceous Fractions Contents and Carbon Stable Isotope Compositions of Aerosols Collected in the Atmosphere of Montreal (Canada): Seasonality, Sources, and Implications
Bibliographic record
Abstract
With the objective of better understanding the sources and dynamics of carbonaceous fractions of the aerosols present in the atmosphere of Montreal, we implemented here an online wet oxidation/isotope ratio mass spectrometry (IRMS) method to simultaneously measure both water-soluble organic carbon (WSOC) content and the corresponding δ13C of aerosol samples collected at four monitoring stations over a 1-year period representing distinct types of environmental conditions (i.e., background, road traffic, industrial, and downtown). We coupled these data with the corresponding concentrations of other carbon fractions: total carbon (TC), elemental carbon plus organic carbon (EC + OC), and carbonates. Results show that TC (6.64 ± 2.88 μg m–3), EC + OC (4.98 ± 2.23 μg m–3), and carbonates (1.71 ± 1.09 μg m–3) were characterized by lower concentrations in winter and higher ones between spring and early autumn, with all fractions expectedly showing significantly lower concentrations for aerosols collected at the background station. We observed a seasonal dependence of the δ13CEC+OC (−25.31 ± 0.94‰) with the EC + OC/total suspended particles (TSP) ratio: (i) an increase of the ratio during late spring, summer and early autumn associated to road traffic emissions characterized by a δ13C of ∼−25‰ and (ii) lower ratios during the winter months indicating the influence of two distinct emission sources, a first one with a δ13C ∼−27‰, suggesting the local influence of combined biomass burning from residential heating and of fossil fuel combustion, and a second one with a δ13C ∼−21‰, likely related to more regional emissions. WSOC (1.14 ± 0.67 μg m–3) presented a similar seasonal pattern for all monitoring stations, with low concentrations in winter, early spring and late autumn that rapidly increased until summer. Our results indicate that this seasonality is controlled by higher anthropogenic contributions from southern Canada and northeastern United States regions and probably from biogenic emissions during the warm months. Moreover, δ13CWSOC (−25.08 ± 1.47‰) showed a 13C-depletion in summer, indicating higher fossil fuel and biogenic contributions, whereas the higher isotope compositions observed in winter may result from the photochemical aging of regional aerosols. Ultimately, we identified the influence of local industrial emissions late in 2013 as well as the impact of aerosol emissions associated to the Lac-Mégantic rail disaster that occurred on July 6, ∼200 km east of Montreal.
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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) | 0.001 | 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".