Exploring GHG emissions in the mainstream SCEPPHAR configuration during wastewater resource recovery
Bibliographic record
Abstract
The wastewater sector paradigm is shifting from wastewater treatment to resource recovery. In addition, concerns regarding sustainability during the operation have increased. In this sense, many water utilities have become aware of the potential GHG emissions during the operation of wastewater treatment. This study assesses the nitrous oxide and methane emissions during the long-term operation of a novel wastewater resource recovery facility (WRRF) configuration: the mainstream SCEPPHAR. The long-term N2O and CH4 emission factors calculated were in the low range of the literature, 1 % and 0.1 %, respectively, even with high nitrite accumulation in the case of N2O. The dynamics and possible sources of production of these emissions are discussed. Finally, different aeration strategies were implemented to study the impact on the N2O emissions in the nitrifying reactor. Results showed that operating the pilot-plant under different dissolved oxygen concentrations (between 1 and 3 g O2 m−3) did not have an effect on the N2O emission factor. Intermittent aeration was the aeration strategy that most mitigated the N2O emissions in the nitrifying reactor, obtaining a reduction of 40 % compared to the normal operation of the pilot plant.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".