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Record W4230107356 · doi:10.1039/d1ra06736b

Challenges and opportunities of hydrothermal carbonisation in the UK; case study in Chirnside

2021· article· en· W4230107356 on OpenAlexaff
Eloise Bevan, Jile Fu, Mauro Luberti, Ying Zheng

Bibliographic record

VenueRSC Advances · 2021
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsWestern University
Fundersnot available
KeywordsBiomass (ecology)Waste managementEnvironmental scienceFood wasteEnergy demandBusinessEnvironmental engineeringEngineeringNatural resource economicsEcology

Abstract

fetched live from OpenAlex

The latest research and development in hydrothermal carbonisation (HTC) processes are reviewed and the feasibility of application to small towns in the UK is assessed. The HTC process designed in this report is theoretically evaluated for the biodegradable municipal waste and sewage waste produced by the small town of Chirnside, in the Scottish Borders. Calculation of mass and energy balances of the process are carried out alongside the evaluation of challenges and environmental, social and economic opportunities presented. The hypothetical HTC plant is capable of processing 267.14 t per year of food waste and 105.12 t per year of faecal sludge produced by Chirnsides estimated 2250 residents in 2041. The plant would be capable of producing 99.08 t per year of hydrochar with an estimated total energy content of 540.26 MWh per year. When used in a Biomass Combined Heat and Power Plant, the hydrochar would be capable of supplying Chirnsides residents with 0.71% and 3.43% of its domestic thermal energy demand and domestic electrical energy demand in 2041, respectively. Both the expected opportunities and challenges for the application of HTC are discussed, shedding light on the associated research in regards to this sustainable technology.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score0.210

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)0.0000.000

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 head0.047
GPT teacher head0.263
Teacher spread0.216 · 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 designOther design
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

Citations32
Published2021
Admission routes1
Has abstractyes

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