Speciated measurements of semivolatile and intermediate volatility organic compounds (S/IVOCs) in a pine forest during BEACHON-RoMBAS 2011
Bibliographic record
Abstract
Understanding organic composition of gases and particles is essential to identifying sources and atmospheric processing leading to organic aerosols (OA), but atmospheric chemical complexity and the analytical techniques available often limit such analysis. Here we present speciated measurements of semivolatile and intermediate volatility organic compounds (S/IVOCs) using a novel dual-use instrument (SV-TAG-AMS) deployed at Manitou Forest, CO, during the Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H 2 O, Organics & Nitrogen – Rocky Mountain Biogenic Aerosol Study (BEACHON-RoMBAS) 2011 campaign. This instrument provides on-line speciation of ambient organic compounds with 2 h time resolution. The species in this volatility range are complex in composition, but their chemical identities reveal potential sources. Observed compounds of biogenic origin include sesquiterpenes with molecular formula C 15 H 24 (e.g., β -caryophyllene and longifolene), which were most abundant at night. A variety of other biogenic compounds were observed, including sesquiterpenoids with molecular formula C 15 H 22 , abietatriene and other terpenoid compounds. Many of these compounds have been identified in essential oils and branch enclosure studies but were observed in ambient air for the first time in our study. Semivolatile polycyclic aromatic hydrocarbons (PAHs) and alkanes were observed with highest concentrations during the day and the dependence on temperature suggests the role of an evaporative source. Using statistical analysis by positive matrix factorization (PMF), we classify observed S/IVOCs by their likely sources and processes, and characterize them based on chemical composition. The total mass concentration of elutable S/IVOCs was estimated to be on the order of 0.7 µg m −3 and their volatility distributions are estimated for modeling aerosol formation chemistry.
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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".