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Record W4403259652 · doi:10.1016/j.jenvman.2024.122537

Between green hills and green bills: Unveiling the green shades of sustainability and burden shifting through multi-objective optimization in Swiss energy system planning

2024· article· en· W4403259652 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

VenueJournal of Environmental Management · 2024
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsPolytechnique Montréal
FundersInnosuisse - Schweizerische Agentur für Innovationsförderung
KeywordsSustainabilityEnvironmental planningEnergy (signal processing)Environmental resource managementBusinessNatural resource economicsEnvironmental economicsEnvironmental protectionGeographyEnvironmental scienceEconomicsEcology

Abstract

fetched live from OpenAlex

The Paris Agreement is the first-ever universally accepted and legally binding agreement on global climate change. It is a bridge between today’s and climate-neutrality policies and strategies before the end of the century. Critical to this endeavor is energy system modeling, which, while adept at devising cost-effective carbon-neutral strategies, often overlooks the broader environmental and social implications. This study introduces an innovative methodology that integrates life-cycle impact assessment indicators into energy system modeling, enabling a comprehensive assessment of both economic and environmental outcomes. Focusing on Switzerland’s energy system as a case study, the model reveals that optimizing key environomic indicators can lead to significant economic advantages, with system costs potentially decreasing by 15 % to 47 % by minimizing potential impacts from the current system still operating with fossil technologies to an alternative only relying on renewable and where the impact are mainly related to the construction of the infrastructure. However, a system optimized solely for economic efficiency, despite achieving 63 % reduction in carbon footprint compared to 2020, shows a potential risk of burden shift to other environmental issues. The adoption of multi-objective optimization in this approach nuances the exploration of the complex interplay between environomic objectives and technological choices. The results illuminate pathways towards more holistically optimized energy systems, effectively addressing trade-offs across environmental problems and enhancing societal acceptance of the solutions to this century’s defining challenge. • Integration of LCA indicators into MILP energy models for environmental optimization. • Multi-objective optimization to balance LCA and economic factors in energy systems. • Tailored LCA modeling for the Swiss energy system’s specific needs. • Development of new LCA characterization techniques and integration strategies in energy modeling. • Analysis of environmental-economic trade-offs in Swiss energy system transitions using MOO. • Environmental Optimization leads to economic and environmental improvements compared to the current 2020 Swiss energy 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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.007
GPT teacher head0.212
Teacher spread0.204 · 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