Ammonia Emissions from Surface Flow and Subsurface Flow Constructed Wetlands Treating Dairy Wastewater
Bibliographic record
Abstract
Agricultural wastewater treatment is important for maintaining water quality, and constructed wetlands (CW) can be an effective treatment option. However, some of the N that is removed during treatment can be volatilized to the atmosphere as ammonia (NH(3)). This removal pathway is not preferred because it negatively impacts air quality. The objective of this study was to assess NH(3) volatilization from surface flow (SF) and subsurface flow (SSF) CWs. Six CWs (3 SF and 3 SSF; 6.6 m(2) each) were loaded with dairy wastewater ( approximately 300 mg L(-1) total ammoniacal nitrogen, TAN = NH(3)-N + NH(4)(+)-N) in Nova Scotia, Canada. From June through September 2006, volatilization of NH(3) during 12 or 24 h periods was measured using steady-state chambers. No differences (p > 0.1) between daytime and nighttime fluxes were observed, presumably due in part to the constant airflow inside the chambers. Changes in emission rates and variability within and between wetland types coincided with changes in the vegetative canopy (Typha latifolia L.) and temperature. In SSF wetlands, the headspace depth also appeared to affect emissions. Overall, NH(3) emissions from SF wetlands were significantly higher than from SSF wetlands. The maximum flux densities were 974 and 289 mg NH(3)-N m(-2) d(-1) for SF and SSF wetlands, respectively. Both wetland types had similar TAN mass removal. On average, volatilization contributed 9 to 44% of TAN removal in SF and 1 to 18% in SSF wetlands. Results suggest volatilization plays a larger role in N removal from SF wetlands.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".