ESAMUR uses artificial intelligence to optimize water treatment in Murcia
In the Region of Murcia, water management has taken a technological leap forward. The Sanitation and Treatment Authority of the Region of Murcia (ESAMUR) has begun incorporating artificial intelligence (AI) systems in its wastewater treatment plants, with the aim of optimizing processes, reducing costs, and increasing operational efficiency. This advance places Murcia at the forefront of water treatment, improving both plant performance and the quality of the treated water.
Context: ESAMUR and water management in Murcia
ESAMUR is the public body responsible for wastewater treatment in the Region of Murcia. The entity currently operates 100 wastewater treatment plants (WWTPs), serving 99.3% of the Murcian population. Thanks to this network, approximately 121 cubic hectometers (hm³) of water are regenerated annually, of which nearly 98% is reused, a percentage much higher than the reuse average in Spain (11%) and Europe (5%). This commitment to reuse makes Murcia an example of the circular water economy, giving water a “second life” before returning it to the environment.
ESAMUR’s history has been characterized by the continuous search for technical improvements in treatment. In fact, many of its plants feature advanced tertiary and even quaternary treatment, additional purification stages that allow for water quality that exceeds current regulatory requirements. In recent years, the entity has participated in European research projects aimed at implementing cutting-edge technologies to eliminate emerging contaminants and improve the sustainability of WWTPs, including the use of artificial intelligence and big data tools. Based on this solid technical foundation, the introduction of AI appears to be a natural step to continue raising the standard of wastewater treatment in Murcia.
AI applied to debugging: what system is used?
The artificial intelligence that ESAMUR is deploying in its wastewater treatment plants is not a single device, but rather a set of software applications and intelligent control systems integrated into the plants’ operations. These include predictive models that analyze historical and real-time data to anticipate failures or maintenance needs in critical equipment, preventing unexpected breakdowns. Automated monitoring systems have also been implemented that adjust process parameters (for example, aeration, dissolved oxygen levels, or reagent dosing) in real time, constantly maintaining the quality of the treated water within optimal ranges.
Another branch of applied AI is the creation of “virtual sensors”: machine learning algorithms capable of estimating indicators of water quality or plant operation that would traditionally require slow or costly measurements. Relying on these virtual sensors and decision-support systems, ESAMUR technicians can optimize the wastewater treatment plant configuration at all times. These tools enable increasing automation of operations: many decisions that previously relied exclusively on human experience and expertise are now supported by real-time data analytics, reducing dependence on manual intervention and enabling a faster and more accurate response to any change.
Benefits: greater efficiency, lower costs, and cleaner water
The implementation of artificial intelligence in water treatment is yielding several concrete benefits:
- Cost and energy savings: Predictive algorithms help optimize the use of equipment and infrastructure. By anticipating maintenance needs, major damage and unscheduled downtime are avoided, reducing repair costs. Additionally, dynamically adjusting aerators, pumps, and other systems to the exact level required results in lower energy consumption, which translates into lower electricity bills.
- Increased operational efficiency: AI helps improve facility utilization. By constantly adjusting the process, treatment plants can treat more water without losing effluent quality, increasing treatment capacity without the need for infrastructure investments.
- Improved treated water quality: One of the most notable impacts is the reduction of contaminants in treated water. Smart monitoring enables more complete removal of nutrients such as nitrogen and phosphorus (which cause eutrophication) and so-called emerging pollutants—microparticles, microplastics, pharmaceuticals, personal hygiene products, and others—to be eliminated. AI-guided technologies, such as those tested at Life Pristine, make it possible to remove substances that were previously impossible to remove using conventional methods. The final effluent discharged into rivers or the sea, or used for irrigation, is cleaner and safer for the environment and human health.
Technological innovation and environmental sustainability
The introduction of artificial intelligence into the water cycle is part of a broader digital transformation and sustainability strategy promoted by the Region of Murcia. ESAMUR plans to equip all its WWTPs with smart sensors and control. With these digital foundations, the successes of current pilots can be scaled to the entire network.
A prominent example is the TRINEFLEX project, a European project in which ESAMUR participates, focused on achieving nearly zero-energy WWTPs. A pilot plant will be installed at the Alcantarilla WWTP that will combine AI with solar energy and sludge co-digestion to produce biogas. TRINEFLEX seeks more sustainable wastewater treatment plants, significantly reducing energy consumption and emissions associated with the process. Initiatives like this, combined with the extremely high rate of reuse of treated water in Murcia, help minimize the environmental impact: drinking water is saved, the extraction of new water resources is reduced, and local aquatic ecosystems are better protected.
Reactions from authorities and experts
Sara Rubira, Regional Minister of Water for the Region of Murcia, emphasized that “we discovered some time ago that AI could help us optimize processes, reduce costs, and improve efficiency.” The regional minister added that the technology will allow us to better address new water quality demands, especially the removal of nutrients and emerging contaminants.
On the technical side, Pedro Simón, Technical Director of ESAMUR, noted that they already use AI algorithms in treatment plants to monitor water quality in real time and prevent incidents before they occur. This translates, he indicated, into more reliable operations and the peace of mind that the treated water meets international standards and can be safely reused.
In short, the incorporation of AI is turning Murcia’s treatment plants into smarter, more sustainable, and safer facilities. Murcia is consolidating its position as a benchmark in water innovation, demonstrating that every drop of wastewater can cease to be waste and, thanks to technology, become a valuable resource harnessed for the benefit of society as a whole.