Deciphering the dynamic interactions among ammonia emissions and composting parameters in sewage sludge composting
Jie Liu1, Weiguang Li1, Guangchun Shan2
1National Engineering Research Center for Safe Disposal and Resources Recovery of Sludge, Harbin Institute of Technology, Harbin, 150090, China; State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, China.
Machine learning models accurately predict ammonia emissions during sewage sludge composting. Stage-specific analysis reveals key factors like time, aeration, and pH for targeted mitigation strategies.
Area of Science:
- Environmental Science
- Waste Management
- Computational Science
Background:
- Ammonia (NH3) emissions during sewage sludge composting are complex and challenging to control with traditional methods.
- Nonlinear interactions between composting parameters hinder effective, stage-specific mitigation of NH3 emissions.
Purpose of the Study:
- To apply multi-stage machine learning for analyzing the relationship between composting parameters and cumulative ammonia-nitrogen (cNH3) emissions.
- To develop stage-specific models for predicting and understanding NH3 emissions throughout the composting process.
Main Methods:
- Utilized multi-stage machine learning models to predict cumulative NH3-N emissions (cNH3).
- Employed Shapley Additive Explanations (SHAP) analysis to identify key influencing parameters.
- Generated bivariate partial dependence plots to visualize parameter interactions and optimal ranges.
Main Results:
- Stage-specific models achieved high predictive accuracy (R² = 0.85–0.91) on independent test sets.
- Composting time, aeration rate, and pH were critical during mesophilic/thermophilic stages.
- Aeration rate, pH, and organic matter were dominant during cooling/maturation stages.
- Identified a synergistic effect between organic matter and nitrate levels, correlating with reduced cNH3.
Conclusions:
- Machine learning effectively models the dynamic relationship between composting parameters and NH3 emissions.
- Findings provide a basis for developing targeted, stage-specific strategies to minimize ammonia emissions in sewage sludge composting.
- Understanding evolving parameter influences is key to optimizing composting efficiency and environmental impact.
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