Occurrence of Single- and Double-Peaked Emission Profiles of Synthetic Chemicals
Bibliographic record
Abstract
This work aims to elucidate the circumstances that can lead to two peaks in the temporal emission profile of synthetic chemicals. Using a simplified substance flow model, we explore how emission factors, product lifespan, and degradation half-life in waste stock influence the (i) relative importance of emissions from three lifecycle stages (industrial processes, use phase, and waste disposal), and (ii) the resulting composite emission profile. A double-peaked emission profile occurs if the lifespan of products containing the chemical is longer than its production history, and the gross emission factor from waste disposal exceeds that from the use phase. Since most chemicals fail to meet these two conditions, it is reasonable to use single-peaked emission profile as the default in environmental studies. On the basis of their emission profiles and contributions from individual lifecycle stages, we can categorize chemicals into "simple single-peakers", "composite single-peakers", and "double-peakers". Our simplified model derived emission profiles for five real chemicals that agree well with earlier, more sophisticated calculations, indicating the model's ability to capture the essential features of actual emissions. It is hoped that the model and conclusions in this work will benefit both environmental modelers and decision makers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".