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Correlation Assessment of Environmental and Energy Features of Wastewater Treatment Plants Towards Circular Economy

2023· article· en· W4323342185 on OpenAlex
A.V. Kiselev, Elena Magaril

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 Applied Economic Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Sustainability and Technology
Canadian institutionsUniversité Laval
FundersRussian Science Foundation
KeywordsSewage treatmentWastewaterEnvironmental economicsQuality (philosophy)SustainabilityCircular economyInvestment (military)Energy consumptionWork (physics)Environmental scienceBusinessEnvironmental resource managementOperations managementEnvironmental engineeringEngineeringEconomicsEcology

Abstract

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Wastewater treatment plays an important role in ensuring ecological safety for water bodies. The achievement of the standard quality of wastewater treatment is being fulfilled through the introduction of the best available techniques. However, the process of wastewater treatment and sludge utilization itself is quite energy intensive. In the course of investment program planning and implementation, corporate managers and local authorities often focus on individual tasks such as how to improve the wastewater treatment quality or to improve energy efficiency; these factors are, however, however interrelated. Achieving the standard quality of wastewater treatment through the introduction of best available techniques and an increase in the number of technological stages usually leads to an increase in the overall energy consumption of the facilities. The hypothesis of the research suggests that the performance assessment of wastewater treatment plants needs mutual accounting of two main factors: wastewater treatment quality and energy efficiency. The main purpose of this work is to develop a methodological approach for assessing the effectiveness of wastewater treatment plants on the way towards the implementation of circular economy principles, followed by its trial application. The authors proposed a methodological framework that consists of three stages: (1) assessing the quality of wastewater treatment, (2) assessing energy efficiency, and (3) constructing a sustainability index on a correlation matrix. The outputs of the operation activities of wastewater treatment plants in Yekaterinburg for 2015-2018 were used for methodological framework approbation. The results of the investigation develop existing knowledge regarding the assessment of the effectiveness of management at treatment facilities and confirm the research hypothesis: the obtained values of the sustainable index correlate with the technical condition of the facilities both in terms of the achievement of the standard treatment quality the energy efficiency of the technological process. The practical significance of the study lies in the creation of a convenient and simple management tool for assessing the current success of wastewater treatment plants and progress in implementing successful circular economy practices. The proposed approach can be used as an element of environmental and economic assessment in the energy sector.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.818

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 studies0.0000.001
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 head0.019
GPT teacher head0.286
Teacher spread0.268 · 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