ArticleACS environmental Au2024
Long-Term Robustness and Failure Mechanisms of Electrochemical Stripping for Wastewater Ammonia Recovery.
Article in ACS environmental Au, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 30 citations in OpenAlex.
- Wastewater Management under Global Climate Change Conditions.ACS environmental Au · 2026Review
- Machine Learning Reveals Signatures of Promiscuous Microbial Amidases for Micropollutant Biotransformations.ACS environmental Au · 2025Article
- Concentrating Nitrogen Waste with Electrodialysis for Fertilizer Production.Environmental science & technology letters · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
Nitrogen in wastewater has negative environmental, human health, and economic impacts but can be recovered to reduce the costs and environmental impacts of wastewater treatment and chemical production. To recover ammonia/ammonium (total ammonia nitrogen, TAN) from urine, we operated electrochemical stripping (ECS) for over a month, achieving 83.4 ± 1.5% TAN removal and 73.0 ± 2.9% TAN recovery. With two reactors, we recovered sixteen 500-mL batches (8 L total) of ammonium sulfate (20.9 g/L TAN) approaching commercial fertilizer concentrations (28.4 g/L TAN) and often having >95% purity. While evaluating the operation and maintenance needs, we identified pH, full-cell voltage, product volume, and water flux into the product as informative process monitoring parameters that can be inexpensively and rapidly measured. Characterization of fouled cation exchange and omniphobic membranes informs cleaning and reactor modifications to reduce fouling with organics and calcium/magnesium salts. To evaluate the impact of urine collection and storage on ECS, we conducted experiments with urine at different levels of dilution with flush water, extents of divalent cation precipitation, and degrees of hydrolysis. ECS effectively treated urine under all conditions, but minimizing flush water and ensuring storage until complete hydrolysis would enable energy-efficient TAN recovery. Our experimental results and cost analysis motivate a multifaceted approach to improving ECS's technical and economic viability by extending component lifetimes, decreasing component costs, and reducing energy consumption through material, reactor, and process engineering. In summary, we demonstrated urine treatment as a foothold for electrochemical nutrient recovery from wastewater while supporting the applicability of ECS to seven other wastewaters with widely varying characteristics. Our findings will facilitate the scale-up and deployment of electrochemical nutrient recovery technologies, enabling a circular nitrogen economy that fosters sanitation provision, efficient chemical production, and water resource protection.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.