Enhanced Removal of Common Wastewater-Derived Trace Organic Contaminants in Vertical-Flow Constructed Wetlands Amended with Fe(III)-EDTA
Why this work is in the frame
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Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Constructed wetlands (CWs) have gained scholarly attention in the last two decades as promising technologies for the attenuation of trace organic contaminants (TrOCs) from municipal wastewater effluent and combined sewer overflow discharge. Using lab-scale vertical flow constructed wetlands, we investigated amending these systems with Fe-EDTA to improve CW degradation of five representative trace organic contaminants. The study combined a 7-month monitoring campaign, 3 different hydraulic regimes, and soil extraction data to elucidate the effects of the amendment on the fate of the TrOCs within the systems. Our results indicate that Fe-EDTA contributed to the degradation of carbamazepine and sulfamethoxazole under the studied flow regimes. Iron-amended soil columns ( n = 5/9 columns fed for 7 months with synthetic domestic wastewater) removed 12 ± 19% of influent carbamazepine (the most recalcitrant TrOC included in the study), 18% higher than the control columns. Operating the columns with periods of retention and discharge further improved carbamazepine and sulfamethoxazole removal efficiency (removal increased to 49 ± 7.6% and 81 ± 9.2% of influent concentrations, respectively). The more readily degradable compounds atenolol and trimethoprim were removed with >97% efficiency in both control and amended columns, regardless of flow. This column study positively correlates Fe-EDTA with improved removal efficiencies of environmentally recalcitrant TrOCs without affecting readily degradable TrOCs.
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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) | 0.000 | 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) | 0.001 | 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 it