MétaCan
Menu
Back to cohort
Record W2313644766 · doi:10.11159/jbb.2015.001

Neem Biodiesel - A Sustainability Study

2015· article· en· W2313644766 on OpenAlexvenueno aff
A. C. Lokesh, N. S. Mahesh, Balakrishna Gowda, Rajesh Kumar, Peter White

Bibliographic record

VenueJournal of Biomass to Biofuel · 2015
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsBiodieselJatrophaEnvironmental scienceDiesel fuelLife-cycle assessmentNeem oilBioenergyFossil fuelAzadirachtaBiofuelWaste managementChemistryToxicologyBiologyEngineeringBotanyProduction (economics)

Abstract

fetched live from OpenAlex

Azadiractha Indica (Neem) is one of the promising tree species suitable for providing oil for biodiesel production. This paper addresses the life cycle assessment (LCA) with respect to, global warming potential, acidification potential and energy balance of a small scale biodiesel system using Neem oil as feedstock, in rural Karnataka (a southern state in India). The environmental impacts have been bench marked with the life cycle impacts of fossil diesel system and Jatropha. Global warming potential of Neem biodiesel life cycle (338 gCO2-eq Functional Unit -1* ) was found be 1.2 times higher than fossil diesel system (280 gCO2-eq Functional Unit -1 ) and 2.7 times higher than Jatropha biodiesel system(123.7 gCO2-eq Functional Unit -1 ). Acidification potential of Neem system was found to be negligible. It is observed that one hectare of Neem plantation is capable of sequestering the 1.35t of biogenic CO2 released during the Neem biodiesel life cycle, with additional sequestration potential of 8.65 t CO2 ha -1 . Net energy ratio of Neem biodiesel life cycle (22.06) has been found to be 26 times higher than fossil Diesel system and twelve times higher than Jatropha system (1.85). This life cycle study revealed that producing biodiesel from Neem oil is ecologically sustainable.

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.

How this classification was reachedexpand

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.030
GPT teacher head0.278
Teacher spread0.248 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Biomass to BiofuelSame topicBiodiesel Production and ApplicationsFrench-language works237,207