Estimating the Influence of Forests on the Overall Fate of Semivolatile Organic Compounds Using a Multimedia Fate Model
Bibliographic record
Abstract
On the basis of recently reported measurements of semivolatile organic compound (SOC) uptake in forest canopies, simple expressions are derived that allow the inclusion of a canopy compartment into existing non-steady-state multimedia fate models based on the fugacity approach. One such model is used to assess how the inclusion of the canopy compartment in the model affects the calculated overall behavior of SOCs with specific physical--chemical properties. The primary effect of the forest is an increase in the net atmospheric deposition to the terrestrial environment, reducing atmospheric concentrations and accordingly the extent of deposition to the agricultural and aquatic environments. This effect was most pronounced for chemicals with log KOA around 9-10 and log KAW -2 to -3; their average air concentrations during the growing season decreased by a factor of 5 when the canopy compartment was included. Concentration levels in virtually all compartments are decreased at the expense of increased concentrations in the forest soil. The effect of the forest lies not in a large capacity for these chemicals but in the efficiency of pumping the chemicals from the atmosphere to the forest soil, a storage reservoir with high capacity from which the chemicals can return to the atmosphere only with difficulty. Because of seasonal variability of canopy size and atmospheric stability, uptake into forests is higher during spring and summer than in winter. The model suggests that this may dampen temperature-driven seasonal fluctuations of air concentrations and in regions with large deciduous forests may lead to a temporary, yet notable dip in air concentrations during leaf development in spring. A sensitivity analysis revealed a strong effect of forest cover, forest composition, and degradation half-lives. A high degradation loss on the plant surface has the effect of preventing the saturation of the small plant reservoir and can cause very significant reductions in atmospheric concentrations of those SOCs for which uptake in the canopy is limited by the size of the reservoir.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".