Feasibility Study of Applying Anaerobic Step-Feeding Mode for the Treatment of High-Strength Wastewater in Granular Sequencing Batch Reactors (GSBRs)
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Bibliographic record
Abstract
This study investigated the feasibility of applying an anaerobic step-feeding strategy to enhance the performance of granular sequencing batch reactors (GSBRs) in terms of operational stability of the cultivated mature granules and nutrient removal efficiencies. Two identical 5 L reactors were operated with a total cycle time of 8 h. GSBRs were operated with high-strength synthetic wastewater (COD = 1250 ± 43, ammonium (NH4-N) = 115.2 ± 4.6, and orthophosphate (PO4-P) = 17.02 ± 0.9 mg/L) for 360 days through three stages: (1) Cultivation, 125 days (>2.1 mm); (2) Maturation, 175 days (>3 mm); (3) alternate feed loading strategy for R2 only for 60 days (anaerobic step-feeding). The granulation process, the physical properties of the granules, the nutrients, and the substrate removal performance were recorded during the entire operational period. For the cultivation and maturation stages, both reactors followed the fast single feeding mode followed by anaerobic mixing, and the results indicated a strong correlation between R1 and R2 due to the same working conditions. During the cultivation stage, adopting high organic loading rate (OLR) at the reactor start-up did not accelerate the formation of granules. Removal efficiency of PO4-P was less than 76% during the maturation period, while it exceeded 90% for COD, and was higher than 80% for NH4-N without effect of nitrite or nitrate accumulations due to simultaneous nitrification–denitrification. After changing filling mode for R2 only, there was unexpected deterioration in the performance and a rapid disintegration of the matured granules (poor settleability) accompanied by poor effluent quality due to high content of suspended solids because of applying selection pressure of short settling time. Consequently, GSBRs operation under the effect of fast single feeding mode followed by anaerobic mixing favors stable long-term granule stability.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it