Selective degradation of endogenous organic metabolites in acidified fresh human urine using sulphate radical-based advanced oxidation
Bibliographic record
Abstract
The human urine metabolome is complex, containing a wide range of organic metabolites that affect treatment of urine collected in resource-oriented sanitation systems. In this study, an advanced oxidation process involving heat-activated peroxydisulphate was used to selectively oxidise organic metabolites in urine over urea and chloride. Initial experiments evaluated optimal conditions (peroxydisulphate dose, temperature, time, pH) for activation of peroxydisulphate in unconcentrated, non-hydrolysed synthetic urine and real urine acidified to pH 3.0. Subsequent experiments determined the fate of 268 endogenous organic metabolites (OMs) and removal of COD from unconcentrated and concentrated real urine (80-90% mass reduced by evaporation). The results revealed >90% activation of 60 mM peroxydisulphate in real unconcentrated urine heated to 90°C for 1 h, resulting in 43% ΣOMs degradation, 22% COD removal and 56% total organic carbon removal, while >94% of total nitrogen and >97% of urea in real unconcentrated urine were recovered. The mechanism of urea degradation was identified to be chemical hydrolysis to ammonia, with the rate constant for this reaction determined to be 1.9 × 10−6 s−1 at pH 3.0 and 90°C. Treating concentrated real urine resulted in similar removal of COD, ΣOMs degradation and total nitrogen loss as observed for unconcentrated urine, but with significantly higher chloride oxidation and chemical hydrolysis of urea. Targeted metabolomic analysis revealed that peroxydisulphate treatment degraded 157 organic metabolites in urine, of which 67 metabolites were degraded by >80%. The rate constant for the reaction of sulphate radicals with oxidisable endogenous organic metabolites in urine was estimated to exceed 108 M−1 s−1. These metabolites were preferentially oxidised over chloride and urea in acidified, non-hydrolysed urine treated with peroxydisulphate. Overall, the findings support the development of emerging urine recycling technologies, including alkaline/acid dehydration and reverse osmosis, where the presence of endogenous organic urine metabolites significantly influences treatment parameters such as energy demand and product purity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 source (direct Gemma or distilled Codex), 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".