Radiative forcing of phytogenic aerosols
Bibliographic record
Abstract
The principal objective of this study is to investigate the radiative influences produced by phytogenic aerosols over a forested area in eastern Canada where measured aerosol concentrations resulted from α‐pinene and β‐pinene oxidation processes. The studied forest ecosystem produced moderate amounts of biogenic hydrocarbons, with isoprene and pinene mixing ratios reaching 1.6 parts per billion. Once oxidized, these pinene levels gave rise to maximum phytogenic aerosol concentrations of circa 5000 particles per cm3. The amount of diffuse and attenuated solar irradiance resulting from the interaction of aerosols with incoming irradiance was quantified using a one‐dimensional spectral radiative transfer model and measured aerosol sized distributions and concentrations. Results show that aerosols in the atmospheric boundary layer contributed to only moderate levels of diffuse irradiance but generated substantial attenuation of the incoming solar irradiance stream. For the irradiance levels measured in eastern Canada during cloudless days in July and with aerosol concentrations in the range of 2000 to 5000 particles per cm3, average daytime solar irradiance attenuation amounted to 0.04 W m−2 with a diffuse component of 0.01 W m−2. The maximum solar irradiance extinction reached 0.2 W m−2. Assuming a uniform spatial aerosol distribution, this negative radiative influence could offset substantial fractions of the regional thermal forcing resulting from increased levels of greenhouse gases such as carbon dioxide. It is concluded that greater radiative influences (cooling) could be present over regions dominated by hydrocarbon productive forest ecosystems.
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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 | 0.000 | 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".