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Record W4214626306 · doi:10.18331/brj2022.9.1.5

Exergy sustainability analysis of biomass gasification: a critical review

2022· review· en· W4214626306 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueBiofuel Research Journal · 2022
Typereview
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsExergyBiomass (ecology)Exergy efficiencySustainabilityEnvironmental scienceWood gas generatorBiomass gasificationCarbon neutralityGreenhouse gasWaste managementProcess engineeringBiofuelEngineeringEcology

Abstract

fetched live from OpenAlex

Biomass gasification technology is a promising process to produce a stable gas with a wide range of applications, from direct use to the synthesis of value-added biochemicals and biofuels. Due to the high capital/operating costs of the technology and the necessity for prudent management of thermal energy exchanges in the biomass gasification process, it is important to use advanced sustainability metrics to ensure that environmental and other sustainability factors are addressed beneficially. Consequently, various engineering techniques are being used to make decisions on endogenous and exogenous parameters of biomass gasification processes to find the most efficient, viable, and sustainable operations and conditions. Among available approaches, exergy methods have attracted much attention due to their scientific rigor in accounting for the performance, cost, and environmental impact of biomass gasification systems. Therefore, this review is devoted to critically reviewing and numerically scrutinizing the use of exergy methods in analyzing biomass gasification systems. First, a bibliometric analysis is conducted to systematically identify research themes and trends in exergy-based sustainability assessments of biomass gasification systems. Then, the effects of biomass composition, reactor type, gasifying agent, and operating parameters on the exergy efficiency of the process are thoroughly investigated and mechanistically discussed. Unlike oxygen, nitrogen, and ash contents of biomass, the exergy efficiency of the gasification process is positively correlated with the carbon and hydrogen contents of biomass. A mixed gasifying medium (CO2 and steam) provides higher exergy efficiency values. The downdraft fixed-bed gasifier exhibits the highest exergy efficiency among biomass gasification systems. Finally, opportunities and limitations of exergy methods for analyzing sustainability aspects of biomass gasification systems are outlined to guide future research in this domain.

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)0.005
metaresearch head score (Gemma)0.007
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.008
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.167
GPT teacher head0.442
Teacher spread0.276 · 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