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Record W1576456462 · doi:10.4271/2005-01-1551

Life Cycle Analysis of Biomass Transportation: Trains vs. Trucks

2005· article· en· W1576456462 on OpenAlex
Hamed Mahmudi, Peter C. Flynn, M. David Checkel

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2005
Typearticle
Languageen
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTruckTrainBiomass (ecology)Automotive engineeringTransport engineeringComputer scienceEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">Biomass is regarded as a renewable resource for upgrading to solid or liquid fuels or for electricity generation. Because its energy density is very low compared to petroleum or coal, the cost of transporting biomass is a significant part of the total biomass cost. For this reason it is usually regarded as a local resource. However, appropriate logistic systems may allow collection of biomass over a large geographical area, thus making it possible to consider efficient, large scale energy conversion systems. For areas without significant water transportation, the basic choices are between truck-based, train-based and pipeline transportation. Previous work has shown that pipeline transport is not effective for biomass delivery due to uptake of carrier fluid (water or oil) by the biomass. Hence, the choice becomes one between train and truck transport.</div> <div class="htmlview paragraph">Western Canada has large resources of wood, forest harvest residues (limbs and tops of trees harvested for pulp or lumber), and agricultural residues such as wheat and barley straw. Effective use of these resources requires an economic plant size, determined by a previous study to be 250 MW for a straw-fired power plant or 130 MW for a forest residues plant. For typical Alberta biomass production densities, the collection radius for these bio-energy plants is 495 km for forest residues and 125 km for straw. This study uses a published life cycle analysis (LCA) results to investigate the environmental load for biomass transport to these optimum-sized plants. All biomass starts the journey from field to plant on a truck; this study evaluates the choice between truck-only or a combination of truck plus train transport for this sort of bulky, low value commodity.</div> <div class="htmlview paragraph">The study results favor train over truck, with reductions in emissions of 70% or more per tonne km. European economic studies suggest a transition distance at which truck and train transport is more economic than truck only. As an added feature, train transport alleviates a potential problem in truck congestion at biomass processing plants. While this study focuses on biomass-for-energy, a similar approach may be useful for other bulky comodities which requiere transportation from a distributed region to a central plant.</div>

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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