A comprehensive assessment of Integrating anaerobic digestion and hydrothermal liquefaction Processes: Harnessing energy from sewage sludge
Bibliographic record
Abstract
• Assessed energy recovery in two schemes: HTL-AD and AD-HTL in integrated systems. • Analyzed HTL operating conditions impacts’ on product yield in an integrated system. • Explored process efficiency at 250–350 °C and retention times of 30 & 60 min. • Achieved maximum energy recovery at 300 °C for 60 min with HTL-AD configuration. • Optimized operating conditions enhanced energy recovery in integrated systems. Integrating anaerobic digestion (AD) and hydrothermal liquefaction (HTL) offers a promising approach for efficient sewage sludge management and enhanced energy recovery. This study systematically evaluates the energy recovery efficiency of two sequencing configurations: HTL followed by AD and AD followed by HTL, at varying HTL operating conditions of 250, 300, and 350 °C for 30 and 60 min each. Our results demonstrate that the HTL-AD sequence yields higher energy recovery in the form of biocrude, with a significant concentration of fatty acids due to the high lipid content in primary sludge. Conversely, the AD-HTL sequence recovers more energy in the form of biomethane, attributed to the easily degradable nature of primary sludge with lower nitrogen content. Energy recovery for the HTL-AD sequence ranges from 47.2 % to 84.5 %, while the AD-HTL sequence ranges from 57.2 % to 77.3 %. The HTL-AD system recovers the highest energy at 300 °C for 60 min, whereas at other operating conditions, the AD-HTL system achieves higher energy recovery than the HTL-AD system. These findings provide valuable insights for optimizing sewage sludge valorization processes and advancing toward a sustainable circular bioeconomy. Future research should focus on long-term stability, economic feasibility, and scalability assessments of these integrated systems.
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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".