CO <sub>2</sub> emitted from peat use in horticulture supports a lower emission factor
Bibliographic record
Abstract
Peat extracted for horticulture is used for growing food, ornamental plants and for soil augmentation. Peatlands are large carbon (C) stores, and the use of extracted peat in aerobic, off-site conditions have implications on the accounting of CO2 emissions. The IPCC (2006, 2013) emission factor for peat use assumes instant oxidation i.e., all extracted peat is mineralized to CO2 in the same year. This is reasonable for peat used for fuel, but horticultural peat takes several decades to decompose. Using historical and present peat extraction data in Canada we calculate a time-integrated emission based on a first-order decomposition model of peat since 1940; when horticultural peat extraction approximately started. Our data compilation shows 36 Mt of peat C has been removed from peatlands (1994–2022) for horticultural use with extraction increasing at the rate of 10.93Kt/year. We calculate approximately 11.9 Mt CO2-C (95% CI= 10.7-12.7) has been released into the atmosphere from the decomposition of the extracted peat between 1940–2022, an estimate that is 2.8 to 3.4 times lower than what the IPCC default would suggest. Our findings have implications for comparing the impacts of peat-based growing media to other alternatives and to C taxes that could apply to horticultural peat users.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".