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Record W4291582963 · doi:10.1021/acsestengg.2c00184

Assessing Advances in Anti-fouling Membranes to Improve Process Economics and Sustainability of Water Treatment

2022· article· en· W4291582963 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueACS ES&T Engineering · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsnot available
FundersAzrieli FoundationNancy and Stephen Grand Technion Energy ProgramTechnion-Israel Institute of TechnologyBIRD Foundation
KeywordsFoulingDesalinationMembrane foulingReverse osmosisEnvironmental scienceEnvironmental engineeringSewage treatmentWastewaterWaste managementMembraneEnergy consumptionWater treatmentMembrane technologyForward osmosisEngineeringChemistry

Abstract

fetched live from OpenAlex

Membrane fouling in desalination and wastewater treatment increases operating costs and energy consumption. Accordingly, research efforts have focused on developing new membrane materials and surface treatments that can resist fouling. Due to the case-specific nature of fouling, there is limited quantification of the impacts these novel anti-fouling membranes can have on water treatment systems. To address this gap, we report results of high-level analyses that evaluated savings in cost, energy consumption, and life-cycle greenhouse gas emissions when membranes with improved fouling resistance are used in brackish water desalination with reverse osmosis and wastewater treatment with anaerobic membrane bioreactors. To carry out these analyses, we used models Water-TAP3 and GPS-X for desalination and wastewater treatment, respectively. We considered the influence of the membrane replacement rate and clean-in-place frequency in both scenarios. In the case of desalination, we also considered the influence of fouling factor and antiscalant dosage. In both scenarios, we determined that increasing membrane lifetime was the most influential factor in reducing operating expenses. Less influential factors included energy associated with increased pumping pressure to maintain a constant flux in the face of fouling and the frequency of clean-in-place events. Overall, desalination energy consumption was insensitive to the parameters we evaluated. Reducing energy associated with sparging in anaerobic membrane bioreactors offered the best opportunity to reduce AnMBR energy consumption in the wastewater treatment plant configuration we modeled. Greenhouse gas emissions were largely unaffected by the adoption of fouling-resistant membranes. Membranes made with new anti-fouling materials could be more expensive than current membranes. For the case studies we evaluate, depending on key variables such as membrane lifetime, the cost of desalination membranes could increase by 1.2–2.9 times, and the cost of anaerobic membrane bioreactor membranes could increase by up to 43% without operating costs increasing above our calculated baseline. This analysis highlights the promise of fouling-resistant membrane materials to reduce costs and energy consumption in water treatment systems. It also underscores a significant need for improved empirical data and multi-scale modeling to improve estimates of these savings.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.890
Threshold uncertainty score0.365

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 communication0.0000.001
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 head0.006
GPT teacher head0.243
Teacher spread0.237 · 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