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Record W4311032289 · doi:10.18331/brj2022.9.4.5

Sustainability assessment of palm oil-based refinery systems for food, fuel, and chemicals

2022· article· en· W4311032289 on OpenAlexvenueno aff
Shabbir H. Gheewala, Ukrit Jaroenkietkajorn, Pariyapat Nilsalab, Thapat Silalertruksa, Thoranin Somkerd, Navadol Laosiripojana

Bibliographic record

VenueBiofuel Research Journal · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Palm Production and Sustainability
Canadian institutionsnot available
FundersAgricultural Research Development Agency
KeywordsBiorefineryLife-cycle assessmentBiodieselSustainabilityEnvironmental sciencePulp and paper industryBiodiesel productionRefineryBiofuelBioenergyWaste managementSuccinic acidValue addedProduction (economics)EngineeringEnvironmental engineeringChemistryBiology

Abstract

fetched live from OpenAlex

Palm-based biorefinery system has gained attention worldwide because of potentially high economic returns. However, environmental impacts also increase with the additional production. Therefore, this study aims to assess the sustainability of (1) current palm-based biorefinery system in Thailand, including cooking oil and biodiesel, and (2) palm-based biorefinery system with value-added products, i.e., succinic acid, lactic acid, bio-hydrogenated diesel (BHD), and epichlorohydrin (ECH) that represent biomaterial, biofuel, and biochemical products, respectively. Accordingly, seven palm-based biorefinery scenarios were designed, and their sustainability was assessed through life cycle assessment (LCA), net energy balance (NEB) and net energy ratio (NER), employment generation, and eco-efficiency. The results revealed that value-added production increased global warming impacts by around 3 – 79% compared with the current system. Although environmental impacts increased due to the additional processes related to the production of the value-added products, total product values also increased, especially for succinic acid, generally leading to higher eco-efficiency values. The current palm-based biorefinery system with succinic acid production had the highest eco-efficiency among all the scenarios considered. The BHD production scenario had the highest NEB and NER because the products were used for energy. Employment generation increased for all the scenarios between 2 – 86% compared with the current system.

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)0.011
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.675
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.380
Teacher spread0.329 · 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 designObservational
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

Citations30
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueBiofuel Research JournalSame topicOil Palm Production and SustainabilityFrench-language works237,207