Constructed Wetlands for Agricultural Wastewater Treatment in Northeastern North America: A Review
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.
Bibliographic record
Abstract
Constructed wetlands (CW) are a treatment option for agricultural wastewater. Their ability to adequately function in cold climates continues to be evaluated as they are biologically active systems that depend on microbial and plant activity. In order to assess their performance and to highlight regional specific design considerations, a review of CWs in Eastern Canada and the Northeastern USA was conducted. Here, we synthesize performance data from 21 studies, in which 25 full-scale wetlands were assessed. Where possible, data were separated seasonally to evaluate the climatic effects on treatment performance. The wastewater parameters considered were five-day biochemical oxygen demand (BOD5), total suspended solids (TSS), E. coli, fecal coliforms, total Kjeldahl nitrogen (TKN), ammonia/ammonium (NH3/NH4+-N), nitrate-nitrogen (NO3−-N), and total phosphorus (TP). Average concentration reductions were: BOD5 81%, TSS 83%, TKN 75%, NH4+-N 76%, NO3−-N 42%, and TP 64%. Average log reductions for E. coli and fecal coliforms were 1.63 and 1.93, respectively. Average first order areal rate constants (ka, m·y−1) were: BOD5 6.0 m·y−1, TSS 7.7 m·y−1, E. coli 7.0 m·y−1, fecal coliforms 9.7 m·y−1, TKN 3.1 m·y−1, NH4+-N 3.3 m·y−1, NO3−-N 2.5 m·y−1, and TP 2.9 m·y−1. In general, CWs effectively treated a variety of agricultural wastewaters, regardless of season.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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) | 0.003 | 0.003 |
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 it