Hydrothermal processing of primary, waste-activated, and digested sewage sludge: Products characterisation, fate of heavy metals and nutrients, and process integration
Bibliographic record
Abstract
• Hydrothermal treatment of various sewage sludges was conducted at 180–270 °C. • Temperature was the most influential factor on product yield and composition. • Hydrochar produced from primary sludge had attractive bioenergy properties. • Aqueous phase products had high N, P, K but low heavy metals contents. • Process configurations for potential integration with WWTPs were proposed. Sewage sludges, such as primary sludge (PS), thickened waste-activated sludge (TWAS), and digested sludge (DS), are generated at different stages during the wastewater treatment process. The intrinsic difference in the biochemical and physicochemical properties of these sludge materials may impact their transformation during hydrothermal treatment. This study comprehensively investigated the hydrothermal processing of PS, TWAS, and DS over a range of hydrothermal carbonisation to liquefaction temperatures (180–270 °C). Organic matter conversion increased with temperature but varied with sludge types. The physicochemical, thermal, and textural properties of the produced hydrochar varied substantially with temperature and sludge types. Hydrochar produced from PS at 270 °C had a higher fuel ratio (0.80), calorific value (20.8 MJ/kg), carbon content (48.2 %), and lower ash content (24.4 %) compared to hydrochar produced from other sludge feedstocks. Heavy metals in the feed materials were largely retained in the hydrochar with more than 95 % recovery at all temperatures. Bio-oil products were fractionated into heavy and light bio-oil, and their compositions differed greatly. The aqueous phase product from TWAS and DS had total N, P, K content reaching 5000 mg/L. The findings of this work demonstrate the potential of hydrothermal processing for the valorisation of wastewater sludges into value-added products.
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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".