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Record W4317721535 · doi:10.3389/frsus.2023.1125016

Editorial: Early-stage quantitative sustainability assessment: Approaches for policy, processes and materials

2023· editorial· en· W4317721535 on OpenAlex
Alessandro Dal Pozzo, Anna Björklund, Michael Carbajales‐Dale, Roland Hischier, Dwarakanath Ravikumar, Serena Righi

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

VenueFrontiers in Sustainability · 2023
Typeeditorial
Languageen
FieldEnvironmental Science
TopicEnvironmental Impact and Sustainability
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsStage (stratigraphy)SustainabilityEnvironmental planningEnvironmental resource managementManagement scienceProcess managementBusinessEnvironmental scienceEngineeringGeologyEcology

Abstract

fetched live from OpenAlex

still be relatively low. However, the lack of direct information and the uncertainty in forecasting technology development and market evolution makes this kind of anticipatory studies particularly challenging.In recent years, the research community has started a fruitful discussion on the methodological advances required by an ex-ante and anticipatory application of quantitative sustainability assessment (Adrianto et al., 2021;Bergerson et al., 2020;Buyle et al., 2019;Cucurachi et al., 2018).The 5 articles that form this Research Topic continue this discussion by offering methodological contributions on the development of prospective assessment frameworks.Main differences of a prospective LCA compared to its retrospective counterpart are the inclusion of future time considerations in the choice of emerging technological options, the projection of background systems, and the upscaling of foreground systems (Arvidsson et al., 2018). The work by Lai et al. exemplifies approaches to address those three aspects with reference to the assessment of alternative technology pathways to sustainable aviation fuels (SAF) in Sweden. The selection of alternative feedstocks for SAF was performed by applying a socio-technical system (STS) approach. The STS model traces the interdependencies between feedstocks, markets, and institutions in order to systematically identify relevant feedstock types for SAF by considering constraints to supply, the competition in the demand of feedstocks by different markets, and trends in availability of certain feedstocks owing to policy changes. Advanced biofuels obtained from forest residues and black liquor, and e-fuels derived from green hydrogen and biomass-enhanced CO2 capture were recognized as potential SAF feedstocks in the Swedish context. A filter based on TRL and economic considerations allowed screening of the technological options for the production of biofuels and e-fuels down to a selected number of processes, which were modelled prospectively using the upscaling framework proposed by Tsoy et al. (2020). Future background systems were modelled by adapting the approach by Steubing and de Koning (2021), i.e., by modifying the Ecoinvent database with information from integrated assessment modelling (IAM) scenarios.Ventura discusses the prospective application of LCA at a more fundamental level, focusing on the broader issue of transition. Her article describes a novel conceptual framework, called transition LCA (Tr-LCA). Tr-LCA aims at studying transition scenarios for entire geographical contexts, rather than focusing on single products or organizations. As such, a methodological implication is that, differently from conventional LCAs, in Tr-LCA multiple functional units can be included and they can vary, as a consequence of the deep structural changes to the economy that transitions might realize. The modelling of substitution is another crucial aspect. Ventura extensively discusses integration with material flow analysis as a way to solve this issue at the level of the broad system boundaries of Tr-LCA.Key for prospective LCA is its use as decision-support tool and, thus, its inclusion into multi-criteria decision-making frameworks. The most simple and widespread decision-support framework is the combination of LCA and techno-economic analysis (TEA). However, the lack of dedicated tools makes early-stage assessments a daunting task for technologists and practitioners. Faber et al.address this issue in the context of carbon capture and utilization (CCU), by presenting a series of ready-to-use, customizable, spreadsheet-based templates for the LCA/TEA of high-priority CCU pathways such as direct air capture, concrete/aggregates carbonation, chemical synthesis, and algae products. This streamlined approach enables an accelerated and standardized screening of CCU pathways, by providing reliable, order-of-magnitude estimates that allow discarding the less promising options and limiting the number of alternatives for which performing a comprehensive assessment.Another relevant area for early-stage LCA together with decarbonization technologies is the transition towards circular economy (CE). Maximizing recirculation of materials does not necessarily result in a greater sustainability. Thus, solid assessment is needed to certify the soundness of CE projects (Blum et al., 2020). Küpfer et al. touch upon this relevant issue with reference to the building sector. They propose a decision-making framework for reuse of structural components in new construction projects. The proposed approach identifies the optimal rate of reused components by generating design alternatives and evaluating them on a combination of criteria, including environmental (LCA), economic and technical (procurement risk and project complexity) considerations.More generally, the analysis of "end-of-life" scenarios is particularly critical in the context of novel products and emerging technologies, as very limited or no data are available on the potential impacts (see, e.g., the issues of microplastics and nanomaterials, or the dismantling of PV modules). Atabay et al. propose a top-down approach for the accounting of cradle-to-grave impacts of plastics based on the economic input-output life cycle assessment (EIO-LCA) method. The proposed model, named "Polluter Pays LCA", aims at covering all the direct and indirect impacts of the plastics value chain, taking a monetization approach akin to life cycle costing with social perspective and including in the system boundaries also the negative externalities in terms of additional burdens to the healthcare and social assistance sector. The mechanism considered to account for the damages of plastics EoL on human health combines emission factors of different toxic compounds from plastic waste management scenarios with a simplified quantification of the effect of microplastics (MPs) in enhancing the bioaccumulation of polycyclic aromatic compounds.The body of work presented in this Research Topic testifies the extensive and prolific activity currently devoted by the scientific community towards early-stage sustainability assessment. By proposing innovative frameworks and informative case studies, articles in this collection contribute to the ongoing development of quantitative methods for the anticipatory analysis of the impacts of emerging technologies and provide suggestions for future work.

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)0.006
metaresearch head score (Gemma)0.043
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.161
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0020.001
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 head0.015
GPT teacher head0.311
Teacher spread0.296 · 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