Impact of external carbon source addition on methane emissions from a vertical subsurface‐flow constructed wetland
Bibliographic record
Abstract
Abstract In this study, different concentrations of urea (0, 12.1, 30, 45, 61 and 80 mmol·L−1) were added separately, as external carbon sources, to a two‐stage vertical subsurface‐flow constructed wetland (VSSF CW) where Cyperus alternifolius L. was planted, with the aim of understanding methane (CH4) emissions driven by urea. Results indicate that the average CH4 emissions from a two‐stage VSSF CW were 6.88, 7.11, 6.22, 7.45, 5.06 and 2.80 mol·m−2·day−1, corresponding to urea concentrations of 0, 12.1, 30, 45, 61 and 80 mmol·L−1 added in the VSSF CW, respectively. Urea as a carbon source had an average of 31.57% of influent total organic carbon (TOC). It was transformed into CH4‐C, of which CH4‐C/TOCinfluent may be be considered as an important component when anthropogenic methanogenesis from treatment wetlands was driven by carbon sources or carbon loading. Methane emissions were at their lowest when the C/N ratio was 5.89, at a urea concentration of 80 mmol·L−1. Principal component analysis (PCA) indicates that CH4 correlated positively with temperature and redox conditions (Eh). Methane emissions driven by urea in the two‐stage VSSF CW were found to be in accordance with the second‐rate dynamics kinetic model (kinetic constant = 22.94 mg CH4·h−1, R2 = 0.99), which can be considered as a high level of CH4 emissions. It indicates that external carbon sources can influence CH4 emissions from two‐stage VSSF CW significantly. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.
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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) | 0.000 | 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) | 0.001 | 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".