Life‐cycle assessment of torrefied coppice willow co‐firing with lignite coal in an existing pulverized coal boiler
Bibliographic record
Abstract
Abstract Coal‐fired electricity generation is a major emitter of greenhouse gases (GHGs) in Canada and the Federal Government has taken steps toward mandated reduction in GHG emissions. One pathway to reduced emissions is via co‐firing of coal with short‐rotation coppice (SRC) willow grown on marginal land in Saskatchewan. This study uses a life‐cycle inventory model to investigate the GHG emissions from nine scenarios for electricity generation with willow pellets at a retrofitted generating station in Saskatchewan. Torrefied and non‐torrefied willow pellets from SRC plantations in the Prairie and Boreal Plains ecozones are considered. Direct co‐firing of pellets and indirect co‐firing via a circulating fluidized bed gasifier are modeled. The model output shows cumulative, levelized, and disaggregated GHG emissions. The scenarios account for the plantation establishment period required to reach a co‐firing ratio of 40% by energy input. Torrefied and non‐torrefied willow pellets grown in the Prairie ecozone indirectly co‐fired with lignite coal result in 43% and 47% net cumulative GHG emissions reduction compared to the existing coal fired pathway. Direct co‐firing of the same feedstocks results in a 34% and 31% reduction in GHG emissions, respectively. The biomass‐based portion of all scenarios was found to produce negative net cumulative GHG emissions on a life‐cycle basis with willow grown in the Prairies ecozone (i.e., GHG emissions from the willow plantation to the combustion of the pellet with coal). Co‐firing is therefore a viable option for reducing GHG emissions from electricity generation. © 2017 Society of Chemical Industry and John Wiley & Sons, Ltd
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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 | 0.001 | 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".