Looking deeper - exploring hidden patterns in reactor data of N-removal systems through clustering analysis.

Area of Science:

• Environmental Engineering
• Microbiology
• Wastewater Treatment

Background:

• Partial nitritation-anammox (PN-A) processes are crucial for nitrogen removal in wastewater treatment.
• Moving bed biofilm reactors (MBBR) are effective for PN-A due to biofilm carrier materials.
• Understanding operational patterns is key to optimizing PN-A performance.

Purpose of the Study:

• To identify operational patterns and conditions benefiting PN-A MBBR performance using clustering analysis.
• To explore correlations between monitored parameters and reactor performance.
• To uncover non-obvious relationships within PN-A system data.

Main Methods:

• Clustering analysis applied to two-year operational data from PN-A MBBRs with different carriers.
• Inclusion of online and laboratory monitored parameters, alongside ex situ batch activity tests.
• Analysis of systems operated under fluctuating temperature and organic matter loads.

Main Results:

• Correlation identified between oxidation reduction potential (ORP) and anaerobic ammonium oxidizing bacteria (AnAOB) activity.
• ORP decrease observed upon exposure to real wastewater containing organic matter.
• Clustering identified operating conditions favoring nitrite accumulation and anammox inhibition at low nitrite levels.

Conclusions:

• Clustering analysis provides valuable insights into complex PN-A MBBR dynamics.
• ORP is a potential indicator for AnAOB activity and organic matter presence.
• Low nitrite concentrations can inhibit anammox bacteria, impacting nitrogen removal efficiency.