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Record W2040722220 · doi:10.1111/gcbb.12198

Carbon debt repayment or carbon sequestration parity? Lessons from a forest bioenergy case study in Ontario, Canada

2014· article· en· W2040722220 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGCB Bioenergy · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsEnvironment and Climate Change CanadaUniversity of TorontoCanadian Sport Centre PacificFPInnovationsPembina InstituteOntario Forest Research Institute
FundersOffice of Energy Research and DevelopmentMinistry of Natural ResourcesNatural Resources CanadaFPInnovationsGovernment of CanadaNational Council for Air and Stream Improvement
KeywordsCarbon sequestrationGreenhouse gasEnvironmental scienceBioenergyBiomass (ecology)CoalCarbon accountingAtmospheric carbon cycleClimate change mitigationCarbon neutralityAgroforestryCarbon fibersBiofuelCarbon dioxideAgronomyWaste managementEcologyEngineeringBiology

Abstract

fetched live from OpenAlex

Abstract Forest bioenergy can contribute to climate change mitigation by reducing greenhouse gas ( GHG ) emissions associated with energy production. We assessed changes in GHG emissions resulting from displacement of coal with wood pellets for the Atikokan Generating Station located in Northwestern Ontario, Canada. Two contrasting biomass sources were considered for continuous wood pellet production: harvest residue from current harvest operations (residue scenario) and fibre from expanded harvest of standing live trees (stemwood scenario). For the stemwood scenario, two metrics were used to assess the effects of displacing coal with forest biomass on GHG emissions: (i) time to carbon sequestration parity, defined as the time from the beginning of harvest to when the combined GHG benefit of displacing coal with biomass and the amount of carbon in regenerating forest equalled the amount of forest carbon without harvest for energy production; and (ii) time to carbon debt repayment, defined as the time from the beginning of harvest to when the combined GHG benefit of displacing coal with biomass and the amount of carbon in the regenerating forest equalled forest carbon at the time of harvest. Only time to carbon sequestration parity was used for the residue scenario. In the residue scenario, carbon sequestration parity was achieved within 1 year. In the stemwood scenario, times to carbon sequestration parity and carbon debt repayment were 91 and 112 years, respectively. Sensitivity analysis showed that estimates were robust when parameter values were varied. Modelling experiments showed that increasing growth rates for regenerating stands in the stemwood scenario could substantially reduce time to carbon sequestration parity. We discuss the use of the two metrics (time to carbon sequestration parity and time to carbon debt repayment) for assessing the effects of forest bioenergy projects on GHG emissions and make recommendations on terminology and methodologies for forest bioenergy studies.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.232
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it