Diurnally resolved particulate and VOC measurements at a rural site: indication of significant biogenic secondary organic aerosol formation
Bibliographic record
Abstract
Abstract. We report simultaneous measurements of volatile organic compound (VOC) mixing ratios including C6 to C8 aromatics, isoprene, monoterpenes, acetone and organic aerosol mass loadings at a rural location in southwestern Ontario, Canada by Proton-Transfer-Reaction Mass Spectrometry (PTR-MS) and Aerosol Mass Spectrometry (AMS), respectively. During the three-week-long Border Air Quality and Meteorology Study in June–July 2007, air was sampled from a range of sources, including aged air from the polluted US Midwest, direct outflow from Detroit 50 km away, and clean air with higher biogenic input. After normalization to the diurnal profile of CO, a long-lived tracer, diurnal analyses show clear photochemical loss of reactive aromatics and production of oxygenated VOCs and secondary organic aerosol (SOA) during the daytime. Biogenic VOC mixing ratios increase during the daytime in accord with their light- and temperature-dependent sources. Long-lived species, such as hydrocarbon-like organic aerosol and benzene show little to no photochemical reactivity on this timescale. From the normalized diurnal profiles of VOCs, an estimate of OH concentrations during the daytime, measured O3 concentrations, and laboratory SOA yields, we calculate integrated local organic aerosol production amounts associated with each measured SOA precursor. Under the assumption that biogenic precursors are uniformly distributed across the southwestern Ontario location, we conclude that such precursors contribute significantly to the total amount of SOA formation, even during the period of Detroit outflow. The importance of aromatic precursors is more difficult to assess given that their sources are likely to be localized and thus of variable impact at the sampling location.
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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 | 0.000 | 0.000 |
| 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".