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Record W3012395393 · doi:10.17660/ejhs.2020/85.1.1

Type of constructed wetlands influence nutrient removal and nitrous oxide emissions from greenhouse wastewater

2020· article· en· W3012395393 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEuropean Journal of Horticultural Science · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsAgriculture and Agri-Food CanadaMinistère de l'Agriculture, des Pêcheries et de l'AlimentationUniversité Laval
FundersAgriculture and Agri-Food CanadaUniversité Laval
KeywordsWastewaterEnvironmental scienceEffluentGreenhouseEnvironmental engineeringGreenhouse gasNitrous oxideConstructed wetlandTypha angustifoliaSewage treatmentWetlandEichhornia crassipesMacrophytePollutantAgronomyChemistryAquatic plantEcology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.677
Threshold uncertainty score0.439

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.212
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it