The forest filter effect for semi-volatile organic compounds and implications for their long range transport
Bibliographic record
Abstract
Semi-volatile organic compounds (SOCs), such as the polychlorinated biphenyls (PCBs), can undergo long range transport and accumulation in arctic regions. Because of differences in their partitioning and degradation properties, PCB congeners differ in their transport behaviour leading to compositional changes with latitude. The global transport model Globo-POP has been used to reproduce these fractionation patterns in atmosphere and soils, to identify the major factors controlling their appearance, and to understand their spatial and temporal variability. The same model has been modified and used to quantify the effect of forests on the ability of SOCs to reach and accumulate in the Arctic. The model suggests that the concentrations of some highly persistent SOCs in the Arctic would be higher by as much as a factor of 2 were it not for the filter effect of global forests, especially boreal deciduous forests. Degradability in the canopy could further enhance this effect. Forests also increase the overall persistence of SOCs by enhancing their transfer to soil with slow degradation rates. The calculations identified the dry gaseous deposition velocity to boreal deciduous forest as one of the most important parameters. A value of 2.8 ł 0.46cmʺs -1 for this velocity, derived from measurements of PCBs and polybrominated diphenyl ethers (PBDEs) in air and bulk deposition in a forest in Southern Canada, is very similar to the only other reported value for a deciduous canopy, as is the relationship between the canopy/air partition coefficient and the octanol/air partition coefficient K OA . Particle-bound deposition velocities to the canopy due to diffusion/impaction are 0.77 cmʺs -1 for PBDEs and 0.12 ł 0.020 cmʺs -1 for polycyclic aromatic hydrocarbons (PAHs). The remarkable similarity between the forests studied here and in Germany lends credibility to the suggestion that high SOC uptake in deciduous forest is wide-spread. The air concentration measurements further provide insight into the temporal variability and gas/particle partitioning behaviour of PAHs, and can serve to calibrate an XAD-based passive air sampling system under field conditions. Determination of K OA -values for numerous polychlorinated naphthalenes from gas chromatographic retention times allows the prediction of their uptake behaviour in forest canopies and passive air samplers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".