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Record W2054667859 · doi:10.2118/136887-pa

Carbon Sequestration From Waste Through Conversion to Charcoal: Equipment for a Small-Scale Operation

2011· article· en· W2054667859 on OpenAlexafffund
Subodh Gupta, Arnoud Struyk, Denis Gilbert

Bibliographic record

VenueSPE Projects Facilities & Construction · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsCenovus Energy (Canada)
FundersCenovus Energy
KeywordsCarbon sequestrationCharcoalFlexibility (engineering)Raw materialFossil fuelWaste managementContext (archaeology)Biomass (ecology)Offset (computer science)Scale (ratio)Environmental scienceEnvironmental economicsProcess engineeringComputer scienceEngineeringEconomicsChemistryCarbon dioxide

Abstract

fetched live from OpenAlex

Summary Carbon emitted on account of our continued use of fossil fuel can be offset using carbon capture and storage (CCS). The technology for this exists, but the economics of it is context dependent, and CCS has shown itself to be not very cost effective in oil sands. Committing to the large-scale sequestration projects needed without properly considering alternatives can prove costly at both the economic and social levels. Charcoal sequestration, discussed earlier by Gupta (2010), provides a few advantages, such as being less costly and lacking any post-operation liabilities. Above all, it is reversible, allowing flexibility of policy and operation and avoiding long-term or large-scale commitments. The economics of the charcoal approach mainly depend on two factors—the cost of the feed biomass and the cost of processing. The first of these is addressed by using municipal waste as feedstock, which can be available free of charge. Expectedly, the cost of processing, the second factor, depends on the apparatus and the scale of operation. In this paper, the authors discuss the benefits and drawbacks of prominent traditional and modern apparatus used for conversion of biomass to charcoal and describe a simple and pragmatic apparatus that could be assembled relatively easily for a small-scale operation such as processing industrial-camp-generated solid organic waste. Offsetting carbon in this manner obviously can be a good way to initiate demonstration projects for the charcoal-sequestration approach because it also helps with waste management. These demonstration projects in turn will help evaluate various aspects of this novel method of sequestration and enhance public awareness on the subject, which in turn will help society make an informed choice to embark on a correct course of action for atmospheric carbon abatement. Additionally, in light of the growing per capita waste worldwide, use of municipal waste as feedstock for charcoal sequestration can be a significant measure of carbon offset at global scale in its own right.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

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

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 head0.048
GPT teacher head0.225
Teacher spread0.176 · 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 designBench or experimental
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
Published2011
Admission routes2
Has abstractyes

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