A review on the removal of nitrogen oxides from polluted flow by bioreactors
Bibliographic record
Abstract
Nitric oxide (NO) and nitrogen dioxide (NO 2 ) are the main pollutants of nitrogen oxides (NO x ) released during a combustion process. They induce harmful effects both to the environment and human health, such as the formation of acid rain, an increase of the tropospheric ozone, global warming, etc. Selective catalytic reduction, selective non-catalytic reduction, adsorption and scrubbing (absorption) are the conventional technologies used to control NO x emission from exhaust gas. The bioreactor appears superior to conventional technologies in terms of simplicity and economy in operation, low process energy requirements, and easy treatment of residual products. This paper reviews two biologically-based NO x removal theories, i.e., nitrification and denitrification. The use of bacteria, fungi and microalgae are discussed and compared. The study indicates that the bioreactor is a promising technology that can be used to control NO x emitted during combustion processes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".