Impact of anaerobically digested biosolids characteristics and handling conditions on dewatering performance at multiple facilities
Bibliographic record
Abstract
-N), and mono- and divalent cation concentrations in ADB. Capillary suction time (CST) and a modified centrifugal technique were used to determine optimum polymer doses and to assess the impact of handling conditions on dewatering performance. Both techniques indicated that polymer dosing between 15 and 20 kg/dry tonne was optimal for all facilities and that biosolids mixing and pumping did not significantly impact dewaterability. The CST values of anaerobically digested biosolids decreased as temperature increased, but no significant difference was found for either temperature or location of dewatering facilities. Sludge viscosity and rheological properties that vary with temperature appeared to have influenced CST values. Modified centrifugal technique results indicated cake solids were not affected by polymer make-up water or ADB temperature when emulsion polymer was used. This study shows the value of laboratory testing of biosolids under controlled conditions to identify and correct potential problems in full-scale operations. PRACTITIONER POINTS: Capillary suction time and a modified centrifugal technique were used to assess the impact of different process-related and environmental factors on dewatering. Higher concentrations of soluble COD (potentially extracellular polymeric substances - EPS) and low calcium (Ca) in anaerobically digested biosolids align with reduced dewaterability. Cell disruption and break down of floc structures due to storage/mixing and pumping of biosolids did not appear to negatively impact dewatering. Modified centrifugal test results did not provide conclusive evidence of whether dewatering of anaerobically digested biosolids could be significantly impacted by temperature over the range 15-30°C, especially when emulsion polymer is used. This study shows the value of laboratory testing of biosolids under controlled conditions to identify potential problems in the full-scale operations.
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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 | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; both teacher heads agree on what is shown here.
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".