Nature-based solutions coupled with advanced technologies: An opportunity for decentralized water reuse in cities
Notice bibliographique
Résumé
Decentralized water reuse in cities is a prominent alternative to mainstream top-down models for urban water treatment, which are based on centralized, linear dynamics of resource management. In this sense, Nature-based Solutions (“green” technologies) coupled with advanced technologies (“grey” technologies) constitute a promising approach for fomenting onsite water treatment and reuse in cities, while also providing multiple co-benefits. This article puts forward a conceptual advancement by providing a better understanding of coupled “green-grey”/“grey-green” technologies (CGGT). To do this, we critically discuss the main reasons for pairing these technologies instead of using them separately, as well as their treatment performance and constraints regarding data reporting issues. Moreover, the article discloses the most common treatment configurations, water quality parameters being evaluated, potential reuse schemes, costs, and energy requirements. A systematic selection and analysis of scientific articles was carried out to this end. Of 395 pre-selected articles, only 17 addressed coupled (green-grey/grey-green) technologies in the treatment of urban wastewaters for further reuse or safe discharge onsite. Despite the relatively low number of articles, 80% were published in the past five years, showing the increased interest in this novel topic. The selected articles were analysed and here we present the resulting comprehensive Excel database (343 datasets) containing detailed information about the design, operation, and performance of such systems. Green-grey technologies were found to be predominant, the configuration constructed wetlands followed by advanced oxidation process and electrochemical process being the most studied. Grey technologies are normally applied at a second stage to remove pathogens in compliance with reuse standards (normally when green technologies alone cannot deliver the standards). Meanwhile, green technologies are commonly used at a second stage to break down slowly biodegradable substances that have not been completely removed by grey technologies (normally as a polishing step following grey technology). The design parameters for combining these technologies have not yet been fully optimized, since they were mainly designed as sole technologies and forcibly put together as a coupled treatment. Hence, further studies should focus on variables and parameters influencing the functioning of coupled technologies as a whole. Finally, due to the novelty and relevance of the topic, transparency and consistency in data reporting is essential to support the optimization and competitiveness of coupled green-grey/grey-green technologies against existing decentralized/centralized approaches.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,006 | 0,011 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».