Market and design considerations of the 37 larger MBR plants in Europe
Bibliographic record
Abstract
By the end of 2007, 10 years after the commissioning of the first full-scale municipal MBR plant in Europe, 37 large MBR plants with a nominal capacity greater than 5,000m3/d were in operation in the region, demonstrating the maturity of the technology. This article presents a review of these large MBR plants, not only in terms of market expectation, but also with regards to specific design considerations such as filtration flux, filtration layout, plant ‘retrofit’ and the inclusion of primary clarification. Due to the low operation costs (energy demand) as compared to side-stream membranes, submerged low-pressure filtration technologies will remain the standard for large MBR applications in the near future. At the time of the study, all the plants within this size segment in Europe were equipped by the two MBR filtration leaders GE/Zenon and Kubota, but other technologies should penetrate this market segment in the coming years.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".