Impact of Wastewater Temperature & Influent Flow as the Indicators of Climate Change on Wastewater Treatment Systems
Bibliographic record
Abstract
Wastewater treatment systems are essential for the safety of people and the wellness of the environment.Climate change has caused significant changes in precipitation patterns, surface temperatures, snowmelt and surface runoff events that also change wastewater characteristics.Change in wastewater temperature and influent flow (indicators of climate change) can affect the physical, chemical, and biological processes in wastewater treatment plants (WWTP) and wastewater treatment performance.This study focused on the impact of wastewater temperatures on secondary / biological activated sludge (AS) systems including conventional AS and Ludzack-Ettinger, using BioWin as a WWTP modeling software.For each treatment system, a wide range of wastewater temperatures and solids retention time (SRT) values were assessed, and removal efficiencies of total chemical oxygen demand (COD), carbonaceous biochemical oxygen demand (cBOD), total suspended solids (TSS), and total ammonia were evaluated.Bush, E., & Lemmen, D. (2019).Canada's Changing Climate Report.www.ChangingClimate.ca/CCCR2019
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".