Practical Implementation of Sensor Technologies for Process Monitoring, Optimization, and Control at BNR Facilities
Tuesday, September 29, 2026 3:00 PM to 4:30 PM · 1 hr. 30 min. (US/Central)
New Orleans Convention Center
Technology Spotlight
Hall H Booth 7249
Information
As utilities pursue tighter effluent limits and more efficient operations, online sensors have become essential tools for process monitoring and control at biological nutrient removal (BNR) facilities. However, successful implementation requires more than selecting and installing instrumentation-it depends on understanding differences between sensor technologies, selecting appropriate deployment locations, and prioritizing parameters that deliver actionable data. This session provides a practical, experience-based framework for optimizing sensor use in real-world wastewater systems.
Drawing on deployment and operation of a large installed base of nutrient sensors (75+ nutrient probes) -including UV nitrate (NOx), Ion selective electrode, wet chemistry orthophosphate analyzers, and emerging bioactivity and N₂O probes-this presentation includes insights from the use of nutrient probes across multiple types and manufacturers. Key distinctions in measurement principles (e.g., UV absorbance vs. ion-selective electrodes), accuracy, response time, fouling susceptibility, and maintenance requirements are evaluated. These experiences will highlight how technology selection impacts lifecycle cost, data reliability, and suitability for specific process environments and desired outcomes.
Strategic sensor placement is a central theme. Through case studies spanning various activated sludge configurations, MBBR, and tertiary filtration systems, attendees will learn how to align sensor locations with operational goals such as denitrification optimization, carbon dosing control, and biological or chemical phosphorus removal. The session demonstrates how hydraulic conditions, mixing regimes, solids concentration process variability influence measurement quality-and how improper placement can limit control effectiveness regardless of sensor quality.
The presentation also identifies the most impactful parameters for nutrient optimization, including nitrate, ammonia, orthophosphate, flow and emerging indicators of biological activity. Practical applications illustrate how these signals are used to implement automated control strategies, such as dynamic carbon dosing for denitrification and bio-P, and optimization of chemical phosphorus removal.
Innovative approaches combining "hard" sensor data with "soft" sensors and machine learning models are also introduced, demonstrating how advanced analytics can improve process visibility and control in complex systems. These soft sensors can be used to replace physical sensors in process locations where maintenance demands are high.
Lessons learned from field implementation, including maintenance challenges, calibration practices, probe set-up, and data integration-are discussed candidly to help utilities avoid common pitfalls.
Learning Objectives:
• Differentiate between major sensor technologies and understand their strengths, limitations, and appropriate applications.
• Identify optimal sensor placement strategies to support specific BNR process control objectives.
• Select key monitoring parameters that provide the greatest value for nutrient removal optimization.
• Apply practical insights to improve sensor reliability, reduce maintenance burden, and enhance control performance.
Drawing on deployment and operation of a large installed base of nutrient sensors (75+ nutrient probes) -including UV nitrate (NOx), Ion selective electrode, wet chemistry orthophosphate analyzers, and emerging bioactivity and N₂O probes-this presentation includes insights from the use of nutrient probes across multiple types and manufacturers. Key distinctions in measurement principles (e.g., UV absorbance vs. ion-selective electrodes), accuracy, response time, fouling susceptibility, and maintenance requirements are evaluated. These experiences will highlight how technology selection impacts lifecycle cost, data reliability, and suitability for specific process environments and desired outcomes.
Strategic sensor placement is a central theme. Through case studies spanning various activated sludge configurations, MBBR, and tertiary filtration systems, attendees will learn how to align sensor locations with operational goals such as denitrification optimization, carbon dosing control, and biological or chemical phosphorus removal. The session demonstrates how hydraulic conditions, mixing regimes, solids concentration process variability influence measurement quality-and how improper placement can limit control effectiveness regardless of sensor quality.
The presentation also identifies the most impactful parameters for nutrient optimization, including nitrate, ammonia, orthophosphate, flow and emerging indicators of biological activity. Practical applications illustrate how these signals are used to implement automated control strategies, such as dynamic carbon dosing for denitrification and bio-P, and optimization of chemical phosphorus removal.
Innovative approaches combining "hard" sensor data with "soft" sensors and machine learning models are also introduced, demonstrating how advanced analytics can improve process visibility and control in complex systems. These soft sensors can be used to replace physical sensors in process locations where maintenance demands are high.
Lessons learned from field implementation, including maintenance challenges, calibration practices, probe set-up, and data integration-are discussed candidly to help utilities avoid common pitfalls.
Learning Objectives:
• Differentiate between major sensor technologies and understand their strengths, limitations, and appropriate applications.
• Identify optimal sensor placement strategies to support specific BNR process control objectives.
• Select key monitoring parameters that provide the greatest value for nutrient removal optimization.
• Apply practical insights to improve sensor reliability, reduce maintenance burden, and enhance control performance.