Biosolids minimization by partial ozonation of return activated sludge: Model development and bacterial population dynamics
Bibliographic record
Abstract
Although ozonation of return activated sludge (RAS) has been used for some time at full-scale biological wastewater treatment plants and a substantive body of literature exists with respect to biosolids minimization, little work has been done on the modeling of the process to predict biosolids reduction. Furthermore, the impact of RAS-ozonation on the microbial community composition in biological treatment systems has rarely been studied. Therefore, the first goal of this study was to develop a new model to predict biosolids reduction based on the International Water Association Activated Sludge Model 3 (IWA-ASM3). The second goal of this study was to investigate the bacterial community structure subjected to RAS-ozonation. To achieve these goals, two pilot-scale wastewater treatment reactors were operated over a three- year period: one control reactor and one RAS-ozonated reactor. The operational results were used to validate the model, and the population structures of ordinary heterotrophic organisms and nitrifiers were determined by high-throughput pyrosequencing of 16S rRNA genes and two functional genes (amoA and nxrB ) targeting autotrophic nitrifying organisms Finally, additional laboratory-scale experiments were conducted to complement the pilot-scale study.The proposed mathematical model of RAS-ozonation assumed that two groups of reactions occurred: (i) the transformation/mineralization of non-biomass solids and (ii) the inactivation of biomass. Laboratory-scale experiments were conducted to parameterize the biomass inactivation process during exposure to ozone. The model was calibrated against the data of Year 1 of the study. Once calibrated, the model satisfactorily simulated the operational data from all three years of the study. After model validation, a global sensitivity analysis was performed. In general, the model outputs were sensitive to operational and ozone reaction parameters, but not to biochemical parameters.. Our findings also imply that the stability of the nitrification process in ozonated systems should be enhanced at constant mixed liquor volatile suspended solids for warm temperatures, but could be reduced at temperatures below 12 °C and aerated SRTs below 10 days.With respect to the composition of the bacterial community, the results suggest that RAS-ozonation does not really influence the structure of the community. Instead, the parallel drifts and slight convergence of the two community structures (in the control and in the RAS-ozonated reactors) during the first and third years indicate that other environmental factors such as influent wastewater composition, temperature, and reactor operation (configuration and SRT) may be more important environmental factors. This study also provides new insights on the importance of environmental variables on community structures of activated sludge systems.To put the data obtained with the pilot-scale study in a more general context, the heterotrophic community assemblies at eight full-scale activated sludge wastewater treatment plants were also determined by high-throughput pyrosequencing of 16S rRNA genes. Observed differences in community compositions and structures were partitioned with respect to a range of key environmental variables, namely reactor size (pilot- vs. full-scale reactors), chemical stress induced by a higher mortality upon exposure to ozone (RAS-ozonated vs. non-ozonated control reactors), seasonal temperature variation (winter vs. summer), inter-annual variation, geographical locations, treatment process types (conventional, oxidation ditch, and sequence batch reactor and influent characteristics. The results suggest that, among the range of environmental variables assessed, influent composition and geographic location contributed approximately 26% of the observed differences in the activated sludge bacterial community structures. The remaining variation (74%) could not be explained by any of the factors that were considered.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".