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Record W2089591866 · doi:10.2495/wm060261

Waste incineration in Swedish municipal energy systems

2006· article· en· W2089591866 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.

Bibliographic record

VenueWIT transactions on ecology and the environment · 2006
Typearticle
Languageen
FieldEnergy
TopicEnergy Efficiency and Management
Canadian institutionsEngineering Link (Canada)
Fundersnot available
KeywordsIncinerationWaste managementMobile incineratorWaste-to-energyElectricity generationEnvironmental scienceElectricityCleaner productionCoalFossil fuelRefuse-derived fuelMunicipal solid wasteEngineeringEnvironmental engineeringWaste collectionPower (physics)

Abstract

fetched live from OpenAlex

Waste is widely used as a fuel in the Swedish district heating (DH) systems, thereby linking waste management and the energy system. This paper summarizes earlier studies by the author on the role of waste as a fuel in DH systems. The method used is case studies of three Swedish municipalities that utilise waste in their DH systems. Economic optimisations of the DH systems are made using the linear programming model MODEST, and environmental effects in terms of carbon dioxide emissions are assessed. It is economically advantageous to use waste as a fuel due to regulations in the waste management sector and high taxes on fossil fuels. There can be a conflict between combined heat and power (CHP) production in DH systems and waste incineration, since the latter can remove the heat sink for other CHP plants in combination with low electrical efficiency in waste incineration plants. CHP is the main measure to decrease carbon dioxide emissions in DH systems on the assumption that locally produced electricity replaces electricity in coal condensing plants. It can be difficult to design policy instruments for waste incineration due to conflicting goals for waste management and energy systems. To put costs on environmental effects, so called external costs, is one way to include them but the method has drawbacks, for example the limited range of environmental effects included. Comparing the energy efficiency of material recovery and energy recovery from waste incineration is one way to assess the resource efficiency of the waste treatment methods.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.466

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 head0.004
GPT teacher head0.165
Teacher spread0.161 · 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