AerationAI-SND
Governed Low-DO Simultaneous Nitrification and Denitrification for Energy-Efficient Nitrogen Removal.
AerationAI-SND™ is a proprietary, patent-pending wastewater-treatment application that applies site-specific predictive and engineering methods, trusted operational information, biological safeguards, and governed control to support reliable simultaneous nitrification and denitrification under low-DO conditions.
Built on McC AI Group’s Engineering Intelligence architecture, AerationAI-SND is designed to balance:
- Nitrification protection
- Denitrification opportunity
- Treatment reliability
- Aeration energy efficiency
- Effluent-quality requirements
- Equipment protection
- Operator authority
AerationAI-SND is designed to integrate with existing plant instrumentation, PLC/SCADA systems, aeration equipment, and biological treatment infrastructure.
Low-DO nitrogen removal. Predictive aeration. Governed biological control.
Why Low-DO Simultaneous Nitrification and Denitrification?
Simultaneous nitrification and denitrification—SND—creates conditions that can support aerobic ammonia oxidation and oxygen-limited nitrate reduction within the same biological treatment environment.
Under appropriate operating conditions, SND can improve nitrogen removal while reducing the aeration required compared with conventional operation at higher dissolved oxygen levels.
The Energy Opportunity
Aeration is typically one of the largest energy demands in biological wastewater treatment.
Operating with more aeration than the process requires can increase blower energy consumption while reducing the oxygen-limited conditions needed for effective denitrification.
AerationAI-SND addresses this problem by seeking the appropriate oxygen condition for reliable treatment rather than simply maintaining an unnecessarily high DO target.
Potential energy savings depend on the individual facility, including its baseline operation, process configuration, aeration equipment, biological conditions, instrumentation, and existing control strategy.
The objective is not minimum airflow. The objective is the aeration required for reliable nitrogen removal—no more and no less.
The Nitrogen-Removal Opportunity
Conventional biological nitrogen removal often uses separate aerobic and anoxic environments.
SND can create opportunities for nitrification and denitrification to occur concurrently where the biological process, carbon availability, operating conditions, and treatment configuration are suitable.
This can improve process flexibility and reduce unnecessary aeration while preserving the biological conditions required for treatment.
Not Simply “Lower DO”
AerationAI-SND is not designed to force dissolved oxygen to the lowest possible concentration.
Excessive oxygen limitation can reduce nitrification reliability, destabilize biological treatment, increase ammonia breakthrough risk, and jeopardize permit compliance.
AerationAI-SND instead seeks a site-appropriate and governable low-DO condition that balances:
- Nitrification Protection ↔ Denitrification Opportunity
Energy optimization remains subordinate to biological stability, effluent performance, and approved operating requirements.
Conceptual DO Conditions for SND Performance. Appropriate low-DO operation can preserve nitrification while creating oxygen-limited regions favorable to denitrification; excessive oxygen reduces opportunities for denitrification, while insufficient oxygen increases nitrification risk.
The Low-DO SND Control Challenge
Low-DO nitrogen removal presents a more demanding control problem than conventional aeration.
The useful operating region can be relatively narrow, process response may be delayed, biological requirements change with operating conditions, and measurements become increasingly important as the process approaches sensitive operating boundaries.
A Narrow, Site-Specific Operating Region
There is no universal low-DO operating condition suitable for every wastewater treatment plant.
Appropriate operation depends on factors such as:
- Process configuration
- Treatment objectives
- Influent characteristics
- Biological condition
- Temperature
- Carbon availability
- Mixing and aeration characteristics
- Instrumentation
- Operating history
AerationAI-SND therefore uses site-specific engineering and biological boundaries rather than applying a universal low-DO target.
Reliable Information Becomes More Important
Low-DO operation places greater demands on instrumentation and process interpretation.
Measurement uncertainty, fouling, calibration condition, spatial variability, and delayed process response can become significant relative to the operating range.
AerationAI-SND therefore evaluates information quality and process context rather than relying on any single measurement as an unquestioned control signal.
Biological Conditions Continue to Change
The oxygen conditions appropriate for nitrogen removal can change with loading, temperature, biomass condition, seasonal operation, hydraulic conditions, treatment objectives, and other plant-specific factors.
AerationAI-SND is designed to adapt to these changing conditions while protecting biological performance.
Low-DO SND requires predictive control, trusted operational information, biological safeguards, and governed authority working together.
Compatibility With Existing Plant Infrastructure
AerationAI-SND is designed to operate through suitable existing plant systems, which may include:
- Process instrumentation
- PLC and SCADA systems
- Plant historians and operational databases
- Blowers and variable-frequency drives
- Airflow-control valves and dampers
- Aeration basins
- Existing biological-treatment processes
- Existing plant alarms, interlocks, and control systems
New process hardware is normally not required when suitable instrumentation, operational information, connectivity, and control interfaces are already available.
Where information or instrumentation gaps exist, they are identified during the initial facility assessment.
The objective is to add an Engineering Intelligence supervisory layer without requiring wholesale replacement of the plant’s existing automation or treatment infrastructure.
Beyond a Single DO Measurement
Conventional aeration control often relies heavily on measured dissolved oxygen as the primary indication of process condition.
For governed low-DO operation, a single measurement may not provide enough information to characterize biological requirements or determine whether the current condition remains appropriate.
AerationAI-SND therefore evaluates broader process conditions, biological treatment requirements, aeration capability, information quality, and treatment response.
This provides a more complete basis for deciding whether low-DO operation should be maintained, adjusted, restricted, or returned toward a more conservative condition.
Where physical measurements become uncertain, validated alternative information may support monitoring or restricted supervisory operation subject to site-approved safeguards.
DO remains important—but it is evaluated within the broader biological and engineering context of the process.
What AerationAI-SND Does
AerationAI-SND translates available plant information into site-specific aeration recommendations and governed operational actions through four high-level functions.
- Understand the Current and Anticipated Condition: AerationAI-SND uses available plant and operating information to characterize current conditions and anticipate changing treatment requirements.
- Determine Appropriate Aeration: Proprietary site-specific predictive and engineering methods determine the aeration appropriate for reliable low-DO biological treatment as operating conditions change.
- Apply Engineering and Biological Safeguards: Proposed recommendations are evaluated against approved treatment requirements, equipment limitations, information quality, biological safeguards, operating boundaries, and facility authority.
- Recommend or Govern Action: Depending on the approved deployment stage, AerationAI-SND can provide operator recommendations or bounded supervisory actions while treatment, equipment, energy, and effluent performance continue to be monitored.
Understand. Predict. Protect. Govern.
Core AerationAI-SND Capabilities
AerationAI-SND combines predictive aeration, trusted operational information, biological-process evaluation, engineering constraints, and governed supervisory authority to support low-DO simultaneous nitrification and denitrification.
1. Site-Specific Predictive Aeration
Estimates changing aeration requirements using facility-specific operating conditions, process behavior, loading, equipment response, and available biological information rather than relying solely on a fixed DO setpoint.
2. Biological-Process Evaluation
Evaluates whether current and anticipated conditions remain consistent with nitrification protection, denitrification opportunity, treatment stability, and the intended low-DO operating envelope.
3. Trusted Operational Information and Process Verification
Assesses the reliability and relevance of available measurements and operating signals before they are used for consequential decisions, while considering process-response behavior and measurement uncertainty.
4. Engineering and Biological Safeguards
Applies site-specific operating limits, biological protection criteria, equipment constraints, information-confidence requirements, and other approved safeguards before recommendations or actions are advanced.
5. Governed Supervisory Operation
Generates recommendations or, where specifically authorized, bounded supervisory actions within approved operating limits, existing control protections, cybersecurity requirements, and facility authority.
Better Nitrogen Removal With Governed Energy Use
AerationAI-SND is designed to help facilities pursue the biological and energy advantages of low-DO operation without treating reduced oxygen concentration as an objective by itself.
1. Reduced Aeration Demand
Supports lower aeration where biological conditions and treatment requirements permit, reducing unnecessary energy use.
2. Improved Nitrogen-Removal Opportunity
Maintains operating conditions that can support simultaneous nitrification and denitrification where the facility configuration and biological process are suitable.
3. Nitrification Protection
Evaluates biological and operating conditions to reduce the risk of excessive oxygen limitation and loss of reliable ammonia oxidation.
4. More Stable Low-DO Operation
Uses predictive methods, process-response evaluation, and safeguards to reduce unnecessary oscillation and improve operation near sensitive biological boundaries.
5. Efficient Use of Existing Instrumentation
Uses available plant information and validated relationships where suitable, while keeping instrumentation requirements specific to the facility and intended level of authority.
6. Governed Operational Authority
Allows facilities to begin with analysis or recommendations and expand authority only after performance, readiness, and operating safeguards have been demonstrated.
AerationAI-SND Within the Engineering Intelligence Platform
AerationAI-SND is built on McC AI Group’s proprietary, patent-pending Engineering Intelligence Platform.
The platform provides complementary capabilities for trusted operational information, site-specific engineering knowledge and evidence-based reasoning, facility-specific operational intelligence, and governed decisions and actions.
- SensorAI™ — Trusted Operational Information: Determines whether measurements and operational information are sufficiently reliable, timely, representative, and appropriate for the intended prediction, recommendation, or action.
- WisdomAI™ — Site-Specific Engineering Knowledge & Evidence-Based Reasoning: Applies site-specific engineering knowledge, approved practices, operating history, treatment requirements, and relevant evidence to interpret conditions, evaluate their operational significance, and develop technically supported responses.
- OperationsAI™ — Facility-Specific Operational Intelligence: Applies facility-specific process models, optimization strategies, operating objectives, equipment relationships, engineering constraints, and performance logic to determine the aeration response appropriate for current and anticipated conditions.
- PilotAI™ — Governed Decisions & Actions: Evaluates whether a recommendation or action may be modified, constrained, held, blocked, escalated, authorized, or executed within approved operating boundaries and organizational authority.
Trusted Information → Engineering Knowledge → Evidence-Based Reasoning → Operational Intelligence → Governed Automation
Integration With Existing Plant Systems
AerationAI-SND operates as a supervisory Engineering Intelligence layer above suitable existing plant instrumentation, automation, and aeration equipment.
Operational Information May Include
Depending on the facility, available information may include:
- Plant flow and loading information
- Aeration and treatment measurements
- Equipment operating information
- Nutrient and biological information where available
- Treatment and effluent results
- Historical operating records
- Operator and engineering information
The exact information requirements are site-specific.
McC AI Group begins with the information already available and identifies any significant gaps during the facility assessment.
Recommendations and Outputs May Include
Depending on the approved application and deployment stage, AerationAI-SND may provide:
- Aeration recommendations
- Operator guidance
- Operational alerts
- Treatment-performance information
- Energy-performance information
- Governed supervisory actions
- Decision and performance records
Performance Validation Before Expanding Authority
AerationAI-SND is introduced progressively so that operational authority expands only after demonstrated performance, treatment stability, information confidence, engineering review, organizational readiness, and explicit facility authorization.
1. Historical Analysis: Evaluate Data & Opportunity
Available historical information is used to understand facility behavior, treatment objectives, operating patterns, instrumentation, aeration performance, and potential opportunities for low-DO nitrogen removal.
2. Shadow Mode: Validate in Parallel
AerationAI-SND operates alongside the existing plant control system without changing its physical operation.
Recommendations and system behavior are evaluated against actual plant performance and operator experience.
3. Advisory Operation: Recommend With Operator Review
Validated recommendations are presented to plant personnel for review.
Operators retain responsibility for deciding whether and how recommendations are implemented.
4. Governed Control: Authorized Bounded Actions
Following successful validation and explicit facility authorization, AerationAI-SND may execute specifically authorized, bounded supervisory actions within approved biological, engineering, equipment, cybersecurity, operational, and organizational limits.
Authority can be restricted or withdrawn when required conditions are no longer satisfied.
Authority expands only as evidence, performance, information quality, engineering review, and site authorization justify it.
Progression between stages is not automatic. A facility may remain indefinitely in advisory operation if that best meets its operational or organizational requirements.
Adaptive Governance and Protective Response
AerationAI-SND does not unconditionally pursue low-DO or energy optimization.
When information quality declines, biological conditions become less favorable, treatment performance changes, or approved operating conditions are no longer satisfied, the system can become progressively more conservative.
Depending on the authorized implementation, AerationAI-SND may:
- Hold or constrain recommendations
- Request operator review
- Restrict automated authority
- Invoke protective operation
- Alert plant personnel
- Return control toward approved plant fallback logic
Biological stability, effluent performance, equipment protection, and operator authority remain ahead of energy optimization.
Preservation of Existing Plant Control
AerationAI-SND operates as a supervisory Engineering Intelligence layer and does not require elimination of the facility’s existing PLC-based aeration-control strategy.
Authorized personnel can pause AerationAI-SND, reject recommendations, restrict authority, override governed actions, and return to existing plant control according to the approved site configuration.
Existing plant control is preserved. Authorized personnel remain in authority.
Relationship to AerationAI™
AerationAI and AerationAI-SND share a site-specific, predictive, and governed Engineering Intelligence foundation, but they address different operating objectives.
AerationAI™
AerationAI provides predictive aeration optimization for a broader range of activated sludge and water recycling applications.
It seeks to provide the aeration required for reliable biological treatment while reducing unnecessary energy use.
AerationAI-SND™
AerationAI-SND extends this foundation to the more demanding low-DO conditions required for simultaneous nitrification and denitrification.
It adds specialized biological safeguards and governed low-DO operation for facilities seeking improved nitrogen removal and aeration efficiency.
AerationAI optimizes aeration broadly. AerationAI-SND governs the narrow biological boundary required for low-DO nitrogen removal.
Proprietary Technology and Intellectual Property
AerationAI incorporates proprietary and patent-pending technologies for facility-specific aeration prediction, optimization, information validation, process-response evaluation, engineering safeguards, and governed operational use.
The core predictive aeration technology is described in U.S. Patent Application Serial No. 18/414,566, published as U.S. Publication No. 2025/0231538, Methods of Optimizing Aeration in Wastewater Treatment.
AerationAI’s protected technical value is not based on a single generic AI model. It integrates facility-specific operational information, predictive aeration requirements, process response, engineering constraints, and governed decision-making within a deployable wastewater-treatment application.
Additional implementation methods, facility-specific models, configuration practices, validation procedures, and deployment methodologies remain proprietary.
AerationAI-SND — Technology Evaluation
An initial AerationAI-SND evaluation examines whether the facility’s biological process, aeration system, treatment objectives, operational information, and existing controls provide a suitable basis for evaluating low-DO simultaneous nitrification and denitrification.
Evaluation may consider:
- Treatment Objectives — Nitrogen-removal requirements, treatment-performance objectives, operating priorities, and applicable constraints.
- Biological and Process Conditions — Process configuration, biological operating conditions, historical treatment performance, and factors relevant to SND potential.
- Aeration System — Aeration zones, blowers, air distribution, controllability, existing operating practices, and applicable equipment constraints.
- Operational Information — Available DO, airflow, influent and effluent information, nitrogen-related measurements, operating history, and other relevant process information.
- Implementation Environment — Instrumentation suitability, information quality, existing controls, PLC/SCADA integration, cybersecurity requirements, safeguards, and operator oversight.
Performance Qualification and Implementation Readiness
AerationAI performance and implementation readiness should be established using actual facility data, engineering analysis, and prospective operating evaluation rather than assumptions based solely on performance at other facilities.
Qualification may consider historical analysis, prediction-versus-measured comparison, airflow and DO response, treatment performance, information and instrumentation reliability, Shadow Mode validation, operator review, energy performance, and validation across representative operating conditions.
Implementation readiness is evaluated through four areas:
1. Facility and Process Assessment
Evaluate treatment configuration, aeration infrastructure, instrumentation, operating history, equipment capability, treatment objectives, engineering constraints, and existing controls.
2. Information and Integration Assessment
Evaluate required plant information, historian and PLC/SCADA interfaces, information quality, cybersecurity requirements, safeguards, and material information gaps.
3. Historical Opportunity Assessment
Evaluate facility-specific evidence of unnecessary aeration, operating inefficiency, or performance improvement opportunities while protecting treatment performance.
4. Pilot Validation
Establish a facility-specific pathway through Historical Analysis and Shadow Mode, followed where appropriate by Advisory Operation or Governed Control.
McC AI Group does not assume that results from one facility will automatically transfer to another.
Performance claims should be based on documented, facility-specific validation.
PREDICT the Requirement → VALIDATE the Information → UNDERSTAND the Response → GOVERN the Action
Technology and Deployment Partnerships
AerationAI can be evaluated, validated, and deployed through collaboration with wastewater treatment facilities, engineering organizations, control-system integrators, technology providers, and qualified implementation partners.
- Municipal wastewater treatment facilities
- Industrial wastewater facilities
- Consulting engineers
- Control-system integrators
- Equipment manufacturers
- Engineering contractors
- Research organizations
- Qualified technology and commercialization partners
Each engagement is structured around the facility’s process configuration, treatment objectives, available information, engineering constraints, cybersecurity requirements, and approved level of operational authority.
Understand the facility. Validate the opportunity. Protect treatment. Govern the operation.
McC AI Group, Inc. 