Passive evaporation of source-separated urine from dry toilets: prototype design and field testing using municipal water
Bibliographic record
Abstract
A prototype urine evaporation unit (UEU) that removes water from human urine produced from a urine-diverting dry toilet using passive solar evaporation was designed and field-tested at a meteorological station. Municipal water was evaporated on vertically stacked plastic cafeteria-style trays that create a large evaporation surface with a small land-area footprint. The trays were located inside a Plexiglas® enclosure exposed to UV light while passively heating the UEU like a solar oven. A metal black chimney also heated up in the sun, causing air to enter the UEU at the front of the UEU through a louvered vent, flow across each tray, and then exit at the back up through the chimney. The UEU was field-tested in a semi-arid temperate climate (Calgary, Canada) from 22 August to 5 November 2013. The average UEU evaporation rate was 3.2 L/day (0.66 mm), varying from 0.4 L/day (0.08 mm/day) on a cloudy day to 8.8 L/day (1.82 mm) on a sunny day. A multiple-regression analysis indicates that 63% of the UEU evaporation rate can be explained by changes in air temperature, wind speed and incoming solar radiation, thus allowing for predictions of the UEU's relative evaporation potential in other climates.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".