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Record W7060857645

Ozonation for the improvement of wastewater quality in lagoons

2019· dissertation· en· W7060857645 on OpenAlexaffabout

Bibliographic record

VenueeScholarship@McGill (McGill) · 2019
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsMcGill University
Fundersnot available
KeywordsEffluentWastewaterTotal suspended solidsChemical oxygen demandSuspended solidsBiochemical oxygen demandSewage treatment
DOInot available

Abstract

fetched live from OpenAlex

Concerns over environmental sustainability in Canada have increased in recent years leading to changes to the discharge limits of certain contaminants like biological oxygen demand (25 mg/L), ammonia (1.25 mg NH3-N/L), and total suspended solids (25 mg/L) in effluent from wastewater treatment facilities collecting an average daily influent volume of 100 m 3 or more.Contaminants of emerging concern (CECs) like pharmaceuticals, hormones, pesticides, herbicides, and other natural and synthetic compounds found in effluent from wastewater treatment facilities remain unregulated in Canada but may persist in the environment and lead to negative environmental outcomes.Given the number of Canadians who rely upon lagoons for their wastewater treatment in small, rural, and remote communities, there is a need to investigate and develop new, cost-effective strategies to improve the quality of wastewater treated in lagoons.Ozonation has been shown to improve the removal of a variety of wastewater contaminants (including CECs) from real wastewater through direct means (oxidation of compounds) and indirect means (increased dissolved oxygen, enhanced biodegradability) and was investigated in the present thesis as a potential strategy to improve wastewater treatment in lagoons.Two pilot tests were conducted to investigate the effects of ozonation on contaminant removal in lagoons.Samples of wastewater were collected from several locations in each lagoon prior to ozonation, during ozonation, and after ozonation and analyzed to determine the effect of ozonation on the removal of conventional contaminants and CECs.The samples were analyzed for biological oxygen demand (BOD), chemical oxygen demand (COD), total ammonia, unionized ammonia, total dissolved solids (TDS), total suspended solids (TSS), nitrite, nitrate, toxicity to Vibrio fischeri, and for the presence of fifteen CECs. RésuméLes préoccupations environnementales au Canada ont augmenté au cours des dernières années, ce qui a entraîné des changements aux limites de rejet concernant la demande biochimique en oxygène (25 mg/L), de l'ammoniac (1,25 mg NH3-N), et des matières en suspension (25 mg/L) pour les effluent des stations de traitement dont le volume moyen quotidien est de 100 m 3 ou plus.Les contaminants d'intérêt émergent (CIE) comme les produits pharmaceutiques, les hormones, les pesticides, les herbicides et d'autres composés naturels et synthétiques présents dans les eaux usées ne sont pas réglementés au Canada.Ceux-ci peuvent persister dans l'environnement et entraîner des effets négatifs sur l'environnement.Étant donné le nombre de Canadiens qui dépendent d'étangs pour le traitement de leurs eaux usées, surtout dans les petites communautés rurales et éloignées, il est nécessaire d'étudier et de développer de nouvelles stratégies peu couteuses pour améliorer la qualité des eaux usées traitées dans ces étangs.Il a été démontré que l'ozonation améliore l'élimination d'une variété de contaminants (y compris les CIE) des eaux usées réelles par des moyens directs (oxydation des composés) et indirects (augmentation de l'oxygène dissous, biodégradabilité accrue) et a été étudiée dans la présente thèse comme une stratégie possible pour améliorer le traitement d'eau usée dans les étangs.Deux essais pilotes ont été réalisés pour étudier les effets de l'ozonation sur l'élimination des contaminants dans les étangs.Des échantillons d'eaux usées ont été prélevés à plusieurs endroits dans chaque étang avant, pendant et après l'ozonation et analysés pour déterminer l'effet de l'ozonation sur l'élimination des contaminants classiques et des CIE.Les échantillons ont été analysés pour la demande biochimique en oxygène (DBO), la demande chimique en oxygène (DCO), l'ammoniac total, l'ammoniac non ionisé, les matières dissous totales (MDT), les matières en suspension totales (MST), le nitrite, le nitrate, la toxicité envers Vibrio fischeri et la présence de quinze CIEs.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.022
GPT teacher head0.294
Teacher spread0.272 · 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 designBench or experimental
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
Published2019
Admission routes2
Has abstractyes

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