Climate change substitution factors for Canadian forest-based products and bioenergy
Why this work is in the frame
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Bibliographic record
Abstract
Evaluating the climate change mitigation potential of the forest sector requires a holistic approach based on forest carbon (C) sequestration, C storage in harvested wood products (HWP) and substitution on markets. High uncertainty is associated with substitution factors, that express avoided fossil greenhouse gas (GHG) emissions from the use of forest-based products in replacement of GHG-intensive materials and fossil fuels. Few studies have focused on the development of substitution factors in Canada, resulting in the use of unrepresentative generic data. Here, we provide a framework to reduce uncertainties related to substitution factors for primary wood products in a Canadian context. A life cycle assessment framework is used to quantify fossil GHG emissions for a baseline and a wood-intensive scenario. For solid product substitution, we focused on the construction sector and analyzed a range of innovative wood buildings with steel and reinforced concrete as alternative materials. We found non-weighted averages of 0.80 tC/tC for sawnwood and 0.81 tC/tC for panels. For energy substitution, we analyzed cases with different specifications on biomass product, facility type and alternative fossil fuel source in non-residential heat production and biofuel transportation sectors. We found a non-weighted average of 0.80 tC/tC for non-residential heat production and 0.51 tC/tC for biofuel transportation, that can be interpreted as 0.91 tC/tC for heavy fuel oil, 0.69 tC/tC for light fuel oil and 0.68 tC/tC for natural gas substitution. These results provide a benchmark for substitution factors in Canada, to help guide forest management strategies for climate change mitigation.
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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 | 0.000 | 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) | 0.001 | 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 it