Observations of OM/OC and specific attenuation coefficients (SAC) in ambient fine PM at a rural site in central Ontario, Canada
Bibliographic record
Abstract
Abstract. Ambient particulate matter (PM) samples were collected on quartz filters at a rural site in central Ontario during an intensive study in 2007. The concentrations of organic carbon (OC), pyrolysis organic carbon (POC), and elemental carbon (EC) were determined by thermal analysis. The concentrations are compared to the organic aerosol mass concentration (OM) measured with an Aerodyne C-ToF Aerosol Mass Spectrometer (AMS) and to the particle absorption coefficient (basp) obtained from a Radiance Research Particle Soot Absorption Photometer (PSAP). The total organic mass to organic carbon ratios (OM/OC) and specific attenuation coefficients (SAC=basp/EC) are derived. Proportionality of the POC mass with the oxygen mass in the aerosols estimated from the AMS offers a potential means to estimate OM/OC from thermal measurements only. The mean SAC for the study is 3.8±0.3 m2 g−1. It is found that the SAC is independent of or decrease with increasing particle mass loading, depending on whether or not the data are separated between aerosols dominated by more recent anthropogenic input and aerosols dominated by longer residence time or biogenic components. There is no evidence to support an enhancement of light absorption by the condensation of secondary material to particles, suggesting that present model simulations built on such an assumption may overestimate atmospheric warming by BC.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".