Thermal decomposition of struvite : a novel approach to recover ammonia from wastewater using struvite decomposition products
Bibliographic record
Abstract
Ammonia recovery technology, utilizing newberyite (MgHPO₄.3H₂O) as a struvite (MgNH₄PO₄.6H₂O) decomposition product, is gaining interest as usage of newberyite can significantly reduce the cost of commercial reagents, by providing readily available magnesium and phosphate for struvite reformation. In this study, the efficiency of ammonia removal from struvite, and a transformation process of struvite to newberyite, were investigated through performing oven dry, bench-scale and pilot-scale experiments. In the oven dry experiments, the structural and compositional changes of synthetic struvite, upon decomposition, were evaluated. Around 60-70% ammonia removal efficiency was achieved through struvite thermal decomposition above 60º±0.5ºC, with up to 71.1ºC with prolonged heating. The 2D amorphous layered structure, present in the decomposed solid phase, entrapped around 30-40% residual ammonia between the layers of magnesium and phosphate, inhibiting further ammonia removal. Subsequently, bench-scale experiments were conducted based on the hypothesis that humid air can prevent the formation of a layered structure including dittmarite (MgNH₄PO₄.H₂O) and an amorphous 2D layered structure. Struvite pellets of different sources and sizes were heated in a fluidized bed reactor in the presence of hot air and steam. Introduction of steam resulted in complete transformation of struvite pellets (<1mm) into newberyite at 80ºC, 95% relative humidity and 2 hours of heating. Finally, pilot-scale experiments were carried out to further optimize the operating conditions for industrial application. The smaller and softer pellets (size <1mm, hardness 300-500 g) were the best suited for struvite-to-newberyite conversion. The process was optimized further by narrowing down the relative humidity from 95% to 85% and reducing the heating duration from 2 to 1.5 hours. The operating cost of the pilot-scale process was estimated, which can be reduced through recycling the heat and moist air over the cycle. The number of cycles for which the decomposed product can be effectively reused depends on the required overall N-recovery efficiency, as well as the performance of the struvite recrystallization stage. The greatest advantage of the proposed technology, over other recovery methods, is that the operating costs can be turned into revenue by utilizing the recovered product as fertilizer or energy source.
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How this classification was reachedexpand
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 | 0.001 |
| 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 teacher head, 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".