Derivation of greenhouse gas emission factors for peatlands managed for extraction in the Republic of Ireland and the United Kingdom
Bibliographic record
Abstract
Abstract. Drained peatlands are significant hotspots of carbon dioxide (CO2) emissions and may also be more vulnerable to fire with its associated gaseous emissions. Under the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol, greenhouse gas (GHG) emissions from peatlands managed for extraction are reported on an annual basis. However, the Tier 1 (default) emission factors (EFs) provided in the IPCC 2013 Wetlands Supplement for this land use category may not be representative in all cases and countries are encouraged to move to higher-tier reporting levels with reduced uncertainty levels based on country- or regional-specific data. In this study, we quantified (1) CO2-C emissions from nine peat extraction sites in the Republic of Ireland and the United Kingdom, which were initially disaggregated by land use type (industrial versus domestic peat extraction), and (2) a range of GHGs that are released to the atmosphere with the burning of peat. Drainage-related methane (CH4) and nitrous oxide (N2O) emissions as well as CO2-C emissions associated with the off-site decomposition of horticultural peat were not included here. Our results show that net CO2-C emissions were strongly controlled by soil temperature at the industrial sites (bare peat) and by soil temperature and leaf area index at the vegetated domestic sites. Our derived EFs of 1.70 (±0.47) and 1.64 (±0.44) t CO2-C ha−1 yr−1 for the industrial and domestic sites respectively are considerably lower than the Tier 1 EF (2.8 ± 1.7 t CO2-C ha−1 yr−1) provided in the Wetlands Supplement. We propose that the difference between our derived values and the Wetlands Supplement value is due to differences in peat quality and, consequently, decomposition rates. Emissions from burning of the peat (g kg−1 dry fuel burned) were estimated to be approximately 1346 CO2, 8.35 methane (CH4), 218 carbon monoxide (CO), 1.53 ethane (C2H6), 1.74 ethylene (C2H4), 0.60 methanol (CH3OH), 2.21 hydrogen cyanide (HCN) and 0.73 ammonia (NH3), and this emphasises the importance of understanding the full suite of trace gas emissions from biomass burning. Our results highlight the importance of generating reliable Tier 2 values for different regions and land use categories. Furthermore, given that the IPCC Tier 1 EF was only based on 20 sites (all from Canada and Fennoscandia), we suggest that data from another 9 sites significantly expand the global data set, as well as adding a new region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.000 | 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".