Peak Flow Management Strategies to Support Wastewater Treatment Intensification: A Science and Regulatory Based Approach
Bibliographic record
Abstract
Peak Flow Management Strategies to Support Wastewater Treatment Intensification: A Science and Regulatory Based ApproachAbstractIn response to increasingly stringent effluent limits, The City of Calgary initiated a study in 2019 to explore treatment intensification at its Fish Creek WWTP using a defined Peak Flow Management (PFM) approach whereby flows up to a defined Threshold Peaking Factor (TPF) are directed through the mainstream treatment processes, with excess diverted via an approved PFM strategy. Implementation of PFM reduces the peak flows through mainstream treatment, supporting process intensification by maximizing reuse of existing infrastructure, however little guidance in terms of a formal regulatory framework has been available in North America. To overcome the absence of an existing framework, the Project Team developed a regulatory framework and assessment methodology to review potential impacts of such an approach. Through the assessment of results, The City was able to demonstrate to the regulator that incorporating a PFM approach for upgrades will not have a negative impact on the receiving water.The City of Calgary initiated a study in 2019 to explore treatment intensification at one of its WWTP facilities using a defined Peak Flow Management approach. To overcome the absence of an existing framework, the Project Team developed a regulatory framework and assessment methodology to review potential impacts of such approach. Through assessment of results, the team was able to demonstrate that incorporating a PFM approach for upgrades will not have a negative impact on the receiving water.SpeakerBerg, JeffPresentation time15:30:0016:00:00Session time15:30:0017:00:00SessionThinking Outside the Basin: Auxiliary Wet Weather TreatmentSession locationRoom S504a - Level 5TopicIntermediate Level, Municipal Wastewater Treatment Design, Wet WeatherTopicIntermediate Level, Municipal Wastewater Treatment Design, Wet WeatherAuthor(s)Berg, JeffAuthor(s)J. Berg 1; J. Patel 2 ; J. Xheko 3; A. Takyi 3; K. Mahmood 2; J. Patel 2; J. Berg 1; D. Morgan 4;Author affiliation(s)Stantec Consulting, Calgary, AB 1; City of Calgary, Calgary, AB 2 ; Stantec Consulting, Calgary, AB 3; City of Calgary, AB 3; City of Calgary, AB 2; City of Calgary, Calgary, AB 2; Stantec Consulting, Calgary, AB 1; 4;SourceProceedings of the Water Environment FederationDocument typeConference PaperPublisherWater Environment FederationPrint publication date Oct 2023DOI10.2175/193864718825159049Volume / Issue Content sourceWEFTECCopyright2023Word count16
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".