Seasonal Aerosol Acidity, Liquid Water Content and Their Impact on Fine Urban Aerosol in SE Canada
Bibliographic record
Abstract
This study explores the drivers of aerosol pH and their impact on the inorganic fraction and mass of aerosol in the S.E. Canadian urban environments of Hamilton and Toronto, Ontario. We find that inter-seasonal pH variability is mostly driven by temperature changes, which cause variations of up to one pH unit. Wintertime acidity is reduced, compared to summertime values. Because of this, the response of aerosol to precursors fundamentally changes between seasons, with a strong sensitivity of aerosol mass to levels of HNO3 in the wintertime. Liquid water content (LWC) fundamentally influences the aerosol sensitivity to NH3 and HNO3 levels. In the summertime, organic aerosol is mostly responsible for the LWC at Toronto, and ammonium sulfate for Hamilton; in the winter, LWC was mostly associated with ammonium nitrate at both sites. The combination of pH and LWC in the two sites also affects N dry deposition flux; NO3− fluxes were comparable between the two sites, but NH3 deposition flux at Toronto is almost twice what was seen in Hamilton; from November to March N deposition flux slows down leading to an accumulation of N as NO3− in the particle phase and an increase in PM2.5 levels. Given the higher aerosol pH in Toronto, aerosol masses at this site are more sensitive to the emission of HNO3 precursors compared to Hamilton. For both sites, NOx emissions should be better regulated to improve air quality during winter; this is specifically important for the Toronto site as it is thermodynamically more sensitive to the emissions of HNO3 precursors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.016 | 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 teacher head, 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".