Describing the effects of ozonation on the different fractions of biosolids to support mathematical model development: a lab-scale study
Bibliographic record
Abstract
Waste biosolids disposal is an important environmental and economic burden to wastewater treatment plants, and the commercialization of new technologies to reduce biosolids production has been rising over the last decade.Ozonation of activated sludge (AS) biosolids is one of the main technologies commercialized; however, inadequate knowledge of the ozonation process restrains our capacity to predict the performance of future installations and refrains commercialization of the technology in North America.This research aimed at describing the ozone effects on the inactivation of the biomass fraction of the biosolids and the transformation of non-degradable fractions to support the development of a mechanistically-based mathematical model to predict process performances.First, inactivation of biomass was studied with five pure culture stains to remove the effects of tightly bound non-degradable solids found in the biosolids matrix.Inactivation constants (the first order rate of the heterotrophic oxygen uptake rate or cellular ATP against the ozone dose) of pure cultures were higher when compared with the inactivation constants of biosolids.Moreover, sonication of the biosiolids samples did not reveal significant changes in inactivation constants due to the changes in particle sizes.Second, COD solubilization yields upon ozonation were compared between pure cultures and biosolids.The ozone doses necessary to inactivate 50% of the pure culture biomass resulted in a much lower COD solubilization (8% of the inactivated biomass Pinar Ozdural Ozcer, Mohammad Tajparast, and Jing Li in laboratory.Theresa Luby drove me to the sampling plant at times and proofreaded my writing.Mauhamad Shameem Jauffur and Bing Guo offered advice on my presentationslides,
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".