(Digital Presentation) Electrochemical Recovery of Ammonium and Phosphate from Municipal Wastewater Sources: Kinetics and Water Chemistry
Bibliographic record
Abstract
Water contamination is ubiquitous and persists across our water resources and supply. Much attention is given to newly identified and emerging contaminants, but we also struggle to successfully mitigate “old”, or well-known, contaminants, which have included ammonia, nitrate, and, more recently, phosphate in municipal wastewaters. However, these compounds are also critical nutrients used to support the global industrialized agriculture sector. Phosphate is of particular importance and concern because phosphate-based fertilizers are currently produced through the mining of phosphate rock, a limited resource mineral. The world’s known available supply of phosphate rock is predicted to become limited within the range of 30 – 200 years, and the flow of phosphorus through the agricultural food cycle is unidirectional, with large portions of mined phosphorus ending up in the environment and landfill. Ammonia is produced for fertilizer and other chemical uses via the Haber-Bosch process, which, annually, uses 2% of global fossil fuel energy demand and contributes 450 M metric tons of CO 2 to global emissions. Meanwhile, the technical treatment train for municipal wastewater treatment facilities targets removal of ammonia and phosphate as contaminants, enabling this one-way flow of nutrients from mineral sources and energy-intensive processes through food to waste. This scenario is no longer tenable as we face limited phosphorus world-wide, as well as energy and food security challenges. In our research, we focus on a magnesium anode-based electrochemical system for the precipitation and recovery of ammonium and phosphate nutrients from municipal wastewater sources. In this study, we have evaluated four different natural wastewater sources, three municipal and one industrial meat processing source to understand how differences in wastewater source water composition affect phosphate and ammonium recovery, and inversely, how the electrochemical treatment process affects resulting wastewater chemistry post-treatment. In this talk, I will discuss our recent results that have shown that phosphate removal kinetics are affected by key water chemistry parameters of chloride concentration, ammonium concentration, calcium concentration, and total organic carbon. Phosphate removal through precipitation showed a two-stage kinetic behavior, with a fast kinetic regime prior to 1 min, and a zeroth order rate from 1 min to 30 min. Corrosion rates of the magnesium anode varied over an order of magnitude and are correlated with the differences in water chemistry. Experimental Mg consumption during the electrochemical process is greater than theoretical Mg consumption resulting in an underestimate of costs, highlighting the importance of experimentally-measured Mg consumption as the more appropriate measure of treatment cost.
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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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".