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Record W6997326125

Water quality management in chlorinated distribution systems under changing climate and demand patterns

2023· other· fr· W6997326125 on OpenAlexaboutno aff

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2023
Typeother
Languagefr
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPotable waterWater qualityPublicsAquatic environment
DOInot available

Abstract

fetched live from OpenAlex

RÉSUMÉ: «RÉSUMÉ: Cette étude porte sur l’impact des changements climatiques et des activités humaines sur la qualité de l’eau potable en milieu urbain en mettant l’accent sur le réseau de distribution. Il souligne la nécessité pour les services publics des eaux de se préparer aux perturbations potentielles de la qualité de l’eau et de la santé publique dues à des facteurs tels que le réchauffement climatique, les événements météorologiques extrêmes, les économies d’eau et l’urbanisation. Ces changements affectent des paramètres cruciaux tels que la température, la teneur en carbone organique dissous (COD) et l’âge de l’eau, qui influencent considérablement les niveaux de chlore libre et de trihalométhanes (THM) dans l’eau. La gestion du chlore et des THM dans les réseaux de distribution (RD) est essentielle pour garantir la qualité de l’eau et la conformité réglementaire. Les études précédentes ont exploré séparément les effets des événements climatiques sur la qualité de l'eau potable à la source , mais il existe un manque de connaissances sur l'impact combiné de la matière organique, des variations de température et de la réduction de la demande en eau dans les RD. De plus, malgré l'augmentation des températures du sol, on dispose de peu de connaissances sur la manière dont les îlots de chaleur urbains (ICU) et les vagues de chaleur estivales affectent la température de l'eau potable dans les RD, en particulier pendant les périodes de chaleur. Il est essentiel de comprendre si les espaces verts en ville peuvent atténuer les effets de cette hausse de température. Cette question est cruciale compte tenu de la profondeur à laquelle les canalisations des réseaux de distribution sont enfouies au Canada (au minimum 1,8 mètre), ce qui pourrait minimiser l'impact des conditions de surface sur la température de l'eau. Aborder ces questions pourrait améliorer notre compréhension de la gestion de l’eau en milieu urbain pour mieux faire face aux défis d’origine climatique ou humaine» ABSTRACT: «ABSTRACT: This study comprehensively examines the impact of climate change and human activities on urban drinking water quality. It emphasizes the need for water utilities to prepare for potential disruptions to water safety and public health due to factors like global warming, extreme weather events, water-saving policies, and urbanization. These changes affect crucial parameters like temperature, dissolved organic carbon (DOC), and water age, which significantly influence the levels of free chlorine and trihalomethanes (THMs) in water. Managing chlorine and THMs in distribution systems (DS) is vital for ensuring water safety and regulatory compliance. Previous studies have separately explored the effects of climatic events on downstream drinking water quality, but a knowledge gap exists regarding the combined impact of organic matter, temperature variations, and reduced water demand within DS. Furthermore, despite reports of increasing soil temperatures, there's limited knowledge about how urban heat islands (UHI) and summer heatwaves affect drinking water temperature in DS, especially during hot periods. It's unclear whether green spaces in cities can mitigate this temperature rise. This issue is crucial given that Canadian distribution network pipes are buried deep (minimum 1.8 meters), potentially minimizing the impact of surface conditions on water temperature. Addressing these questions enhances our understanding of urban water management in the face of natural and human-induced challenges.»

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.017
GPT teacher head0.257
Teacher spread0.240 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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