Concentrations and species composition of atmospheric volatile organic compounds (VOCs) as observed during the wet and dry season in Rondônia (Amazonia)
Bibliographic record
Abstract
We measured atmospheric gas‐phase volatile organic compounds (VOCs) at the end of the wet and end of the dry season at a tropical rainforest site in Rondônia, Brazil, using various sampling techniques such as trapping on different adsorbents or cryogenic trapping combined with appropriate analysis techniques. The measuring sites were located inside the forest of a biological reserve near Ji‐Paraná. Sampling was performed from 3 May 1999 to 17 May 1999 and from 24 September 1999 to 2 November 1999 during the “wet‐to‐dry season transition” and “dry‐to‐wet season transition” periods in Rondônia, respectively. Samples were obtained at the canopy top close to the potential sources/sinks for these compounds as well as above the forest. We report the measured concentrations of a large number of different VOCs and their oxidation products, such as isoprenoids, organic acids, carbonyls, aromatics, and alcohols. The most prominent VOCs present in air over the last part of the wet season were isoprene, formaldehyde, and formic acid, with mixing ratios of each ranging up to several parts per billion (ppb). Methyl vinyl ketone as well as methacrolein, both oxidation products of isoprene, ranged around 1 ppb. The sum of the measured monoterpene concentrations was below 1 ppb. At the end of the dry season, the amount of C1–C2organic acids and C1–C2aldehydes increased significantly up to 17 and 25 ppb, respectively, which is thought to result significantly from vegetation fire emissions. High methanol concentrations also support this scenario. At the same time, however, atmospheric mixing ratios of biogenic compounds such as isoprene increased up to 30 ppb near the crown region and well above 10 ppb at 10–20 m over the forest, whereas monoterpene species seem to decrease. We discuss seasonal development of the vegetation and climatological factors to be responsible for such concentration pattern. The results give an impression about the variability and concentration of VOCs during the different seasons.
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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 | 0.000 |
| 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) | 0.001 | 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".