Comparison of Relationship between Solubilization and Methane Productivity on Anaerobic Digestion of Pre-treated Waste Activated Sludge
Bibliographic record
Abstract
Objectives : Various pre-treatment methods have been applied to waste activated sludge(WAS) to improve the efficiency of anaerobic digestion(AD) by enhancing hydrolysis. The objective of this study was to find out the relationship between increased solubilization and AD efficiency in response to the application of different pretreatment methods(Acid+Heat and Alkali+Heat) to WAS.Methods : Acid+Heat(pH 2+130℃) and Alkali+Heat(pH 10+130℃) pretreatment processes were performed by adding HCl and KOH, respectively. A biochemical methane potential(BMP) test was subsequently conducted to determine the AD efficiency of pretreated WAS. Finally, the physicochemical characteristics in the effluent of AD of WAS, done by excitation-emission matrix(EEM) and size exclusion chromatography(SEC), were analyzed to investigate the degree of changed intermediates during microbial degradation of organic compounds.Results : Both Acid+Heat and Alkali+Heat pretreatments resulted in similar solubilization of WAS, reaching 34.1 and 36.3%, respectively. Meanwhile, it was found that the CH4 yield obtained from the Alkali+Heat pretreated sample was lower than the sample of Acid+Heat. The results of EEM analysis showed that the Alkali+Heat pretreated WAS had a higher portion of less biodegradable organic compounds with high- molecular weight in the soluble sample than that of the Alkali+Heat pretreated sample.Conclusion : This study was conducted to clarify the relationship by comparing the hydrolysis rate and AD efficiency according to the application of Acid+Heat and Alkali+Heat pretreatment. It was found that the amount of methane generated could vary depending on the properties of the dissolved substances in response to different pretreatment approaches.
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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 | 0.000 |
| 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 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".