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New concepts for water treatment with membrane technology: From ideas to large pilot scale tests

2024· article· en· W7124517964 sur OpenAlexaboutno aff
Frank Lipnizki, Tobias Hey, Giampaolo Manzolini, Irena Petrinić, Muhammad Suleman, Ahmet H. Avci, Therese Jephson, Henrik Aspegren

Notice bibliographique

RevueLund University Publications (Lund University) · 2024
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueMembrane Separation Technologies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWater treatmentReverse osmosisStormwaterNanofiltrationDesalinationUltrafiltration (renal)Produced waterWastewaterMembrane technologyRaw water
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

IntroductionGlobal water scarcity requires new approaches for water treatment. Membrane technology has proven itself as key technology for water treatment from seawater desalination with reverse osmosis to wastewater treatment with membrane bioreactors. In this presentation three new water treatment concepts based on membrane technology and their development from idea to pilot scale testing will be presented. The concepts cover rainstorm water harvesting with micro-/ultrafiltration (MF/UF), direct membrane filtration (DMF) for wastewater treatment and an integrated concept of forward osmosis (FO) and membrane distillation (MD) and nanofiltration (NF) for seawater desalination. Rain and stormwater harvesting with MF/UFThe EU-Horizon 2020 project REWAISE (Resilient Water Innovation for Smart Water Economy) aims to reduce drinking water consumption by 30%. In Sweden, where the average consumption is 140 liters per person per day, this would mean a reduction to around 100 liters [1]. About 45 liters per person per day are used for toilets and washing machines, which don't require drinking water quality. The project proposes using membrane technology to upgrade stormwater for these purposes. The initial trails of this concept were conducted at stormwater pond in Lund, Sweden, using a unit with 5 m² submerged ceramic membranes, specifically silicon carbide membranes (Liqtech, Denmark) with a 0.2 micron pore size and a 400 kDalton molecular weight cut-off. These membranes remove microplastics and micropollutants larger than 0.2 microns from stormwater. The results showed efficient removal of micropollutants, microplastics, and some heavy metals, producing water close to EU class 'A' quality for agricultural use. Based on the successful trails, a full-scale unit was then installed at the Röda Oasen apartment building in Malmö, Sweden. This unit uses 13.8 m² of ceramic silicon carbide membranes (Cembrane, Denmark) with a 0.1 micron pore size and 200 kDalton molecular weight cut-off. Operational since February 2024, it produces about 1,300 liters of water daily for 22 toilets and 4 washing machines, using stormwater from the roof and an underground tank. The installation saves the property owner approximately 40% of drinking water consumption, or 475,000 liters annually.DMF for wastewater treatmentThe DMF concept, an abiotic alternative for municipal wastewater treatment, uses coagulation, flocculation, and microsieving before membrane treatment. It has high carbon rejection, enhancing biogas production for a potentially energy-neutral or positive process. The concept was successfully tested on pilot scale in Lund, Sweden using 0.2 μm PVDF microfiltration membranes (Alfa Laval, Denmark) with coagulation, polymer addition, and 100 µm micro-screening as pre-treatment. Based on the positive results from the tests larger unit treating over 90 m3 of wastewater per day was installed in Fredrikstad, Norway, and is so far one of the largest DMF plants for wastewater treatment. The two cases show that DMF can achieve high rejection rates of carbon (COD, SS) and total phosphorus, and its high carbon rejection can boost biogas production, moving towards energy-neutral or positive wastewater treatment.Membrane-based seawater desalinationIn the EU-Horizon 2020 project DESOLINATION project (Demonstration of Concentrated Solar Power Coupled with Advanced Desalination System in the Gulf Region) the aims is to develop the efficient integration of a concentrated solar power (CSP) system with a membrane-based desalination system on a pilot-scale in a real-world setting. Waste heat from the CSP system will power the desalination process, reducing costs—a major barrier to CSP deployment. The concept is based on using a thermo-responsive polymer as FO draw solution with NF and MD plus a coalescer. A key success factor is the draw solution which needs to provide sufficient osmotic pressure to desalinate seawater with 3.5% salt and has to be compatible with the membranes as well as the modules used. Initial trials of the individual units are currently ongoing in the pilot plant hall at Lund University, Sweden and based on the results, a large scale pilot will be installed at CSP plant of King Saud University in Riyadh, Saudi Arabia. Outlook and conclusionsThese innovative water treatment concepts demonstrate the significant potential of membrane technology to address global water scarcity. By advancing from pilot studies to full-scale implementations, these projects pave the way for more sustainable and efficient water management solutions worldwide.AcknowledgmentsThe research is partly funded by the REWAISE “Resilient Water Innovation for Smart Economy” (Project No. 869496) and DESOLINATION (Project No. 101022686) under the European Horizon 2020 programme.References[1] Svenskt Vatten (2017). Värt att veta om vatten. https://www.svensktvatten.se/globalassets/fakta-om-vatten/dricksvattenfakta/vart-att-veta-om-vatten_2017.pdf

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,004
Score d'incertitude au seuil0,020

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,002
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,002
Communication savante0,0020,003
Science ouverte0,0010,002
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,013
Tête enseignante GPT0,232
Écart entre enseignants0,219 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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