Nitrogen pollution in wastewater is an increasingly prevalent environmental challenge due to industrial, urban, and agricultural activities. Conventional nitrogen removal processes require intensive energy and a sufficient amount of organic matter that is not always available. 

To improve this process and make it more efficient, we are innovating with the Denitox project, which we are developing together with the University of Granada.

"With Denitox, we managed to reduce nitrogen by up to 80% and save energy by up to 50%," explains Elena Campos, head of Technical Support for Sacyr Agua's Treatment Area.

The nitrogen present in surface water bodies can promote uncontrolled algae growth, which can lead to high fish mortality, as has happened in the Mar Menor.

More restrictive European directive

The new European Wastewater Treatment Directive (TARU) drastically reduces the limits of nitrogen in discharge, which in many cases implies a real technological challenge. 

The runoff stream in plants with anaerobic sludge digestion can reach up to 20% of the total nitrogen load that reaches the plant and needs to be retreated after removal. Hence the importance of treating these return streams that have a high nitrogen content, but a low organic matter content. 

With our Denitox technology we can achieve lower nitrogen emissions in the discharge, with high polluting potential, economic savings and the reduction of greenhouse gas emissions.

Pilot test

"We have carried out a pilot test in the Guadalajara treatment plant, which was applied to the return stream of the sludge line, which has a lot of nitrogen. If wastewater normally has between 60 and 80 mg per liter, that stream has 500-1,000 mg per liter. In this study, which was carried out with real water and variable conditions, an 80% reduction was achieved in a stable way," explains Elena.

"Now, the main challenge is to maintain these high efficiencies at room temperature and shorter hydraulic retention times. If we manage to bring it to an industrial scale, Denitox would be a competitive solution for wastewater treatment applicable in many treatment plants to meet nitrogen removal targets," concludes Elena Campos.

Before this test, a stopover was made in the laboratory at the University of Granada, with which we have developed this technology.

"We have optimized the operating conditions, but we need to scale up to a larger size and see how to control the conditions well.

International award in Saudi Arabia

Recently, the Denitox project has won the Global Prize for Innovation in Water (GPIW), organized by the Saudi Water Agency, in the Sustainable Water Production and Environmental Conservation category.

This category values the balance in water supply with the protection of the ecosystem and the reduction of emissions.

At Sacyr Water, we have a new system trained with artificial intelligence to detect damage in its collector networks. 
"We believe that AI can achieve very low error rate functionality by training a model that learns from common defects detected by the human eye, such as cracks, fissures, and blockages in the sewerage network.

This Machine Learning model helps us reduce the error rate in detecting these common defects. Additionally, Artificial Intelligence has been implemented to interpret text and generate final reports", explains Miguel Cebrián, head of digital transformation at Sacyr Water.

VIDIA is an asset intelligence platform developed by Sacyr for critical sanitation infrastructure management. 

This system transforms the traditional network inspection process into an automated, data-driven workflow. It doesn't just identify damage; it classifies it according to standardized typologies.

VIDIA utilizes generative artificial intelligence, advanced analytics, and integrated visualization, converting raw data into strategic information for decision-making. It is a tool that unifies everything: people, processes, and technology, providing a 360º view of the service. 

"First, camera footage is captured, which can be done via a drone or a robot within the sewage network. Then, this video is fed into our VIDIA system which, thanks to ML technologies, identifies images, and with Generative AI, analyzes texts and automatically generates reports," states Miguel Cebrián.

Furthermore, VIDIA is integrated with the GIS system. This means all alerts are georeferenced on a city map, allowing for the prioritization of actions in strategic or sensitive areas.

This machine learning model, trained with generative AI, has been jointly developed by Sacyr Water's technical department and the company's IT department. 

VIDIA differs from all similar systems in the water sector because it automates the entire workflow. It not only identifies damage but also contextualizes it: classifying it according to standardized typologies and precisely geolocating it within the collector.

VIDIA is positioned as a key tool to anticipate incidents, reduce operational costs, and ensure service continuity. 

"Digital transformation in sewage network management is no longer an option, but a necessity. This tool transforms a traditionally slow and costly process into an automated, intelligent, and results-oriented workflow", concludes Cebrián.