Effect of Process Parameters on Greenhouse Gas Generation by Wastewater Treatment Plants
Bibliographic record
Abstract
The effect of key process parameters on greenhouse gas (GHG) emission by wastewater treatment plants was evaluated, and the governing parameters that exhibited major effects on the overall on- and off-site GHG emissions were identified. This evaluation used aerobic, anaerobic, and hybrid anaerobic/aerobic treatment systems with food processing industry wastewater. The operating temperature of anaerobic sludge digester was identified to have the highest effect on GHG generation in the aerobic treatment system. The total GHG emissions of 2694 kg CO2e/d were increased by 72.5% with the increase of anaerobic sludge digester temperature from 20 to 40 degrees C. The operating temperature of the anaerobic reactor was the dominant controlling parameter in the anaerobic and hybrid treatment systems. Raising the anaerobic reactor's temperature from 25 to 40 degrees C increased the total GHG emissions from 5822 and 6617 kg CO2e/d by 105.6 and 96.5% in the anaerobic and hybrid treatment systems, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".