Identifying causal pathways and risk-decision rules for nitrous oxide emission hot moments in wastewater treatment plants using probabilistic causal machine learning

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The dataset analyzed in this study originates from a full-scale wastewater treatment plant in Denmark, where online sensors installed along the flow path continuously monitored key process variables, including influent flowrate, dissolved oxygen (DO), ammonium (NH₄⁺), nitrate (NO₃⁻), temperature, and N₂O. Monitoring was conducted from 14 June 2018 to 1 March 2019, with measurements recorded every 5 minutes, yielding a total of 74,173 observations.

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