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Modeling nitrogen removal performance based on novel microbial activity indicators in WWTP by machine learning and
Yadan Yu1, Hao Zeng2, Liyun Wang2
1CAS Key Laboratory of Environmental and Applied Microbiology, Environmental Microbiology Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
This study introduces a new microbial activity indicator, specific oxygen uptake rate with adenosine triphosphate (SOURATP), for wastewater treatment. SOURATP accurately predicts pollutant removal, improving plant operations and reducing costs.
Area of Science:
- Environmental Science
- Microbiology
- Chemical Engineering
Background:
- Wastewater treatment plant (WWTP) performance modeling is key for operational efficiency and cost reduction.
- Current models lack accuracy in characterizing pollutant removal based on microbial activity indicators.
- Limited understanding exists on reliable microbial indicators for predicting WWTP performance.
Purpose of the Study:
- To propose and validate a novel microbial activity indicator, specific oxygen uptake rate with adenosine triphosphate (SOURATP), for WWTPs.
- To develop and compare predictive models for total nitrogen (TN) removal rate using microbial activity.
- To interpret the relationship between the novel indicator and microbial community structure/metabolic pathways.
Main Methods:
- Introduced SOURATP as a biomass indicator, distinct from traditional SOURMLSS.
- Developed and evaluated machine learning models (SVR, KNR, LR, RF) for TN removal rate prediction.
- Employed a model fusion (MF) algorithm to enhance prediction accuracy.
- Analyzed correlations between SOURATP, microbial community composition, and metabolic pathways.
Main Results:
- SOURATP demonstrated a stronger correlation with TN removal rate than SOURMLSS.
- Models using SOURATP outperformed those using SOURMLSS, achieving an RMSE of 2.25 mg/L/h with the MF algorithm.
- SOURATP showed significant correlations with nitrifier proportions and key metabolic enzymes.
- SOURATP effectively indicated nitrogen removal bacteria composition and metabolic activity.
Conclusions:
- SOURATP is a reliable indicator for predicting WWTP pollutant removal performance.
- The developed models offer enhanced accuracy for operational optimization.
- This research provides insights into microbial activity regulation for improved WWTP management.
