Life Cycle Assessment of renewable filler material (biochar) produced from perennial grass (Miscanthus)
Bibliographic record
Abstract
Biochar, a hydrophobic biomaterial produced from lignocellulosic biomass is a promising alternative to conventional filler materials. Although a variety of feedstocks have been analyzed for producing biomaterials to a limited extend, a complete LCA study of Miscanthus biochar is scarce. This study evaluates the life cycle of biochar produced from Miscanthus that is grown on the marginal land in Ontario, Canada. Life cycle environmental impacts are determined by using the SimaPro LCA software adopting the TRACI method. The global warming potential (GWP) of the life cycle of biochar is found to be 117.6 kg CO2eq/t. Miscanthus cultivation (93.0 kg CO2eq/t) is the main contributor in the life cycle of Miscanthus biochar followed by pyrolysis (23.3 kg CO2eq/t) and transportation (4.8 kg CO2eq/t). Miscanthus cultivation is also the main contributor to acidification potential and non-carcinogenic potential; however, transportation and pyrolysis are the hotspots in the case of eutrophication, smog and ecotoxicity, and carcinogenic potential, ozone depletion potential and fossil fuel depletion, respectively. The sensitivity analysis reveals that the environmental impacts decrease with an increase of Miscanthus yield. The study provides information on the life cycle environmental impacts of biomaterial which would facilitate in selecting environmentally favorable filler material to replace conventional filler materials to mitigate environmental impacts.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 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".