Type of constructed wetlands influence nutrient removal and nitrous oxide emissions from greenhouse wastewater
Bibliographic record
Abstract
In the current study, three constructed wetlands (CWs) were tested as a sustainable method of treating highly ion charged greenhouse wastewater before disposal.Because of their anaerobic conditions, it was hypothesized that free water surface flow (FWS) and horizontal-subsurface flow (HSS) CWs would be more efficient at removing NO 3 -and SO 4 2-from greenhouse wastewater than the vertical-flow (VSS) CW, but that FWS and HSS would emit more greenhouse gases.To test this hypothesis and propose the most sustainable CW for the greenhouse industry, this study compared three types of CWs (FWS, HSS and VSS) for their nutrient removal performance and nitrous oxide (N 2 O) emissions.The experiment was conducted in a greenhouse and consisted of 36 wetland units (12 replicates) of 0.8 m 3 operated with reconstituted greenhouse wastewater enriched with sucrose (C:N ratio of 2.9) at a 10-day hydraulic retention time, corresponding to the effluent loading rate coming from commercial greenhouse vegetable crops.The CWs were filled with water (FWS), gravel (HSS), or sand (VSS) and planted with Eichhornia crassipes (FWS) or Typha latifolia (HSS, VSS), two macrophytes largely used to treat wastewaters heavily loaded in nutriment.Results showed that HSS performed better than the FWS and VSS at reducing pollutants from the greenhouse wastewater, with 45% total N load removed.Although 59% of the NO 3 -N load was removed in the FWS and HSS, a high accumulation of NO 2 -(1.28 g N m -2 d -1 ) occurred in FWS.The removal of ammonium (NH 4 -N) (~26%) loadings was similar in all CWs.Only 4% of the SO 4 -S load was removed in the FWS and HSS, and no SO 4 -S reduction was observed in VSS.Mean cumulative N 2 O emissions were 7 and 59 times higher in FWS (1.59 g m -2 d -1 ) than in HSS and VSS, respectively.Although VSS emitted less N 2 O than the other CWs tested in this study, HSS was the best option in terms of reducing CO 2 emissions and nutrient pollutants from greenhouse wastewater before disposal.
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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 | 0.001 |
| 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) | 0.000 | 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".