Archetypal analysis of activated sludge microbiomes from two WRRFs identifies three archetypes whose state space aligns with binary N2O emission states in an unsupervised manner.
and Van Voorthuizen, Ellen M
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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Machine learning soft-sensor models predict N2O emissions in wastewater plants with high accuracy but remain limited by measurement location and dataset uncertainty, while mechanistic analysis reveals pathway interactions that bias N2O estimates.
citing papers explorer
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Archetypal Microbiome Profiles as Indicators of Nitrous Oxide Emission States in Activated Sludge
Archetypal analysis of activated sludge microbiomes from two WRRFs identifies three archetypes whose state space aligns with binary N2O emission states in an unsupervised manner.
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Enhancing the interpretability of spatially variable N2O model predictions with soft sensors during wastewater treatment
Machine learning soft-sensor models predict N2O emissions in wastewater plants with high accuracy but remain limited by measurement location and dataset uncertainty, while mechanistic analysis reveals pathway interactions that bias N2O estimates.