Nutrient Recovery for Fertilizer Production and Wastewater Treatment for a Circular Economy
Why this work is in the frame
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Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The recovery of nutrients, particularly nitrogen (N) and phosphorus (P), from wastewater plays a crucial role in mitigating eutrophication and advancing sustainability. This paper introduces a novel approach for recovering these essential elements from municipal wastewater (MWW) using an innovative composite, calcined magnetic layered double hydroxide/hydroxyapatite (CMLDH-HAP). The adsorbent was synthesized by precipitating hydroxyapatite onto magnetic layered double hydroxides derived from agricultural waste, followed by calcination. The adsorption behaviors, characterized by heterogeneous monolayer chemisorption adsorption, and the underlying mechanisms, including interlayer cation and ligand exchange and surface precipitation, demonstrated sustainable recovery of NH 4 + -N and P from real wastewater treatment plant effluent in column experiments, with a breakthrough time of 15 min. The N- and P-adsorbed CMLDH-HAP was then utilized as an eco-friendly, slow-release fertilizer to enhance the germination, growth, and blooming of Madagascar periwinkle ( Catharanthus roseus ). Furthermore, the desorption of N and P using a 0.5 M NaHCO 3 solution enabled the regeneration of CMLDH-HAP, rendering it suitable for recycling N and P from wastewater. Economic viability considerations explored more cost-effective wastewater treatment options, underscoring the potential of CMLDH-HAP. This study thus presents a sustainable solution that integrates the reuse of agricultural waste, effective wastewater treatment, and the recovery of N and P nutrients as fertilizer sources. Implementing the demonstrated technologies can help minimize the environmental impact of wastewater and promote circular economy principles.
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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) | 0.000 | 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 it