Countering the porcelain dream: key findings from an evaluation of the global nitrogen cycle, a fundamental characterization of fresh faeces, and a campus composting toilet
Bibliographic record
Abstract
When we consider global sanitation from within the framework of sustainable development, we are both failing to meet the needs of the present and are jeopardizing the capacity of future generations to do so. The primary function of sanitation and waste treatment is the protection of public health, but it is urgent that we also consider the long-term sustainability of sanitation and waste treatment systems. Our choice of sanitation and waste treatment systems is intimately connected to the greatest equity and sustainability challenges of our time, and we need something better than the Porcelain Dream (i.e. flush toilets, sewerage, and centralized conventional wastewater treatment). This thesis explores the design of sustainable sanitation systems from three different but complementary perspectives: \n1.\tIn a material flow analysis (MFA), I evaluate the positive impact of ecological sanitation (or the reuse of nutrients in excreta for agriculture) as an intervention to mitigate nitrogen pollution and improve stewardship of the global nitrogen cycle. I find that ecological sanitation can substitute 51% of nitrogenous fertilizer use, reduce discharge of nitrogen to waterways by 71%, decrease nitrous oxide (N2O) emissions by 34%, and improve the circularity of the agricultural-sanitation nitrogen cycle by 22%. \n2.\tThrough environmental engineering research, I derive fundamental drying characteristics of fresh faeces to support the development of ecological and sustainable sanitation. Based on this characterization, I propose the use of the Guggenheim, Anderson, and de Boer (GAB) model for predicting the relationship between water activity (aw) and equilibrium moisture content, calculating the heat of sorption, and estimating the corresponding energy requirements for drying of fresh faeces. Given an anticipated range of initial moisture contents of 63 to 86%, I estimate an energy requirement of 0.05 to 0.4 kJ/mol to inactivate pathogens in fresh faeces. \n3.\tVia an evaluation of the composting toilet project at the University of Victoria (UVic), I explore factors critical to promoting a paradigm shift from the conventional to more ecological and sustainable systems. I identify the following as factors that facilitated implementation in the Exploration and Adoption/Preparation phases: supportive and self-reinforcing research and outcomes, favorable adopter characteristics, and the technology’s beneficial features. \nThe overall objective of the research is to communicate that the design of sustainable sanitation systems is urgent, with implications both locally and globally, and to provide information to support a shift towards more sustainable sanitation systems.
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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 | 0.001 | 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 | 0.001 | 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 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".