Innovating Wastewater Treatment: Harnessing AI For Energy Efficiency And Enhanced Performance

By Lauren Harrington

In the realm of wastewater treatment, aeration plays a critical role in the fight against pollution and contamination and in the effort to protect communities and comply with new contamination regulatory requirements. This fundamental step serves as the cornerstone of wastewater treatment facilities worldwide, essential for purifying water by breaking down organic pollutants and ensuring its safety for reuse or discharge back into the environment. However, its voracious appetite for energy, accounting for 60% of facility power requirements, poses a considerable challenge to the operational costs and sustainability of wastewater treatment plants.

The Vital Role Of Aeration In Wastewater Treatment

Aeration, simply put, is the process of infusing oxygen into wastewater to stimulate the growth of beneficial microorganisms. These microorganisms, in turn, devour organic matter, effectively cleansing the water of harmful pollutants such as pathogens, nitrogen compounds, and organic chemicals. Without adequate aeration, the microbial activity essential for wastewater treatment would grind to a halt, resulting in compromised water quality and environmental hazards.

The Energy Dilemma: The High Cost Of Aeration

Aeration is a crucial process in wastewater treatment, but it comes with a significant operational cost - energy consumption. Aeration systems require motors to constantly pump air into large basins, sustaining the microbial population essential for treating wastewater. As a result, energy costs can account for up to 30% of a utility's total operation and maintenance (O&M) expenses, with aeration systems being the primary energy consumers within wastewater treatment plants.

Due to the substantial energy demand of aeration systems, many wastewater facilities across North America are still obligated to inform their local power utility before activating these systems. The sudden surge in energy usage can strain the power grid, making advance notice necessary to prevent potential disruptions. According to the International Energy Agency (IEA), the demand for energy in water and wastewater utilities is expected to continue rising, further emphasizing the need for efficient energy management and communication with power providers.

The Promise Of AI: Revolutionizing Aeration For Energy Efficiency

Artificial Intelligence (AI) offers a promising solution to the challenges posed by energy-intensive aeration processes and the consequent escalation of operational costs in wastewater treatment. AI's unparalleled ability to analyze vast amounts of data and make real-time adjustments has proven to be a game-changer in optimizing aeration systems, reducing energy consumption while simultaneously improving process efficiency. Here are a few ways that AI optimizes aeration for energy efficiency: 

• Predictive Analytics: AI algorithms analyze historical data on wastewater flow rates, pollutant levels, and weather patterns to predict optimal aeration requirements. By forecasting demand and adjusting aeration rates accordingly, AI minimizes energy waste and maximizes treatment effectiveness.
• Dynamic Control Systems: AI-powered control systems continuously monitor and adjust aeration rates based on real-time conditions, optimizing energy usage without compromising treatment performance. By dynamically responding to changes in effluent quality and flow, these systems ensure efficient operation while reducing energy consumption.
• Machine Learning Algorithms: Through machine learning algorithms, AI learns and adapts to the unique characteristics of each wastewater treatment plant. By continuously optimizing aeration parameters based on feedback loops, these algorithms achieve significant energy savings over time while improving treatment efficiency.
• Fault Detection and Diagnostics: AI-enabled analytics identify inefficiencies or malfunctions in aeration equipment, enabling proactive maintenance and minimizing energy losses due to equipment downtime or suboptimal performance.

AI: Empowering Operators For Better Outcomes

AI's transformative potential in wastewater treatment extends beyond optimizing aeration for energy efficiency; it also serves as a powerful tool for empowering plant operators. By harnessing the real-time insights and predictive capabilities offered by AI, operators can make informed decisions, optimize resource allocation, and ensure the plant performs at its best. AI-driven automation streamlines processes and reduces the burden of manual tasks, freeing up operators to focus on higher-level strategic initiatives and problem-solving.

The Ripple Effect: Energy Savings And Beyond

Improving the aeration process in wastewater treatment is not only crucial for removing conventional pollutants but also holds promise for addressing emerging contaminants like per- and polyfluoroalkyl substances (PFAS). These “forever chemicals,” widely used in industrial and consumer products for their water- and grease-resistant properties, have garnered increasing attention due to their persistence in the environment and potential health risks. With the first federal mandate recently signed to further restrict PFAS levels in water and wastewater, there is urgency to develop a plan for compliance. The importance of reducing, if not eliminating, these chemicals is unanimous; however, implementing solutions solely at the utility level is ambitious and costly.

An optimized aeration system could offer avenues for mitigating PFAS contamination through both direct and indirect mechanisms. One direct pathway involves the enhancement of aerobic biodegradation, wherein microorganisms metabolize organic matter, including certain PFAS compounds, as a source of energy and carbon. By optimizing aeration conditions such as dissolved oxygen levels, temperature, and pH, treatment plants can promote the growth and activity of microbial consortia capable of breaking down PFAS molecules. This is not proven for all PFAS species but has worked well for some. 

Indirectly, aeration can serve as a pre-treatment step, introducing oxygen into the water matrix and promoting the formation of reactive species through mechanisms such as ozonation or photolysis. Consequently, subsequent treatment stages can benefit from the presence of these oxidants, accelerating the degradation of PFAS and improving overall treatment efficiency.

Leveraging AI to optimize aeration in wastewater treatment can contribute to broader strategies aimed at reducing PFAS inputs into the environment. By enhancing the removal efficiency of treatment processes, fewer PFAS compounds are discharged into receiving water bodies, minimizing the risk of contamination and ecosystem exposure. However, continued research and innovation are essential to refining these strategies and ensuring their efficacy in diverse wastewater treatment contexts.

Pioneering A Sustainable Future With AI

The integration of AI into critical wastewater treatment processes represents a transformative leap forward in the journey towards a more sustainable future. By harnessing the power of AI to optimize aeration for energy efficiency and enhanced performance, wastewater treatment plants can achieve significant cost savings and reduce their environmental footprint. Moreover, AI-optimized aeration systems may offer new avenues for mitigating the impact of persistent pollutants such as "forever chemicals," contributing to a more comprehensive approach to water quality management. As we continue to innovate and refine these technologies, the integration of AI in wastewater treatment holds immense promise for ensuring the provision of clean, safe water for reuse and discharge, benefiting generations to come.

Lauren Harrington works as an Industry Director at Rockwell Automation, overseeing a North America team focused on optimizing city public works automation and power control solutions to meet sustainability and energy transition initiatives. Throughout her career, she has held various roles, including project engineer, proposal specialist, and market access channel partner within fortune 500 companies.

She has over 25 years of experience and a diverse educational background encompassing engineering, organizational leadership, and an MBA with a business analytics minor. Her ambition is to be a catalyst for change and innovation, leveraging technology and data-driven strategies to achieve urban optimization and environmental stewardship.