The OPTIFANGS project develops a tool called Agroresources that allows to calculate an estimate sufficiently accurate the agronomic and environmental composition of WWTP sludge through the measurement of the NIR fingerprint. This allows to model the behavior of the sludge in different conditions and to optimize its dosage in agricultural soils. In this way, the tool allows to take decisions for the dosage almost in real time.
Modeling of the analyzed sludge in different conditions facilitates management and dosing decisions in real time and significantly improves process optimization. For this analysis, chemometrics is used, which is a discipline of artificial intelligence (AI) that merges the value of 'chemical' and 'analytical' intelligences and allows the extraction of features based on model optimization.
The development of these tools will allow decentralized management of sludge, which will help to have a lower environmental impact. Likewise, the expected results point to a 25% reduction in excess nutrients that are not absorbed by crops linked to WWTP sludge, a 12% increase in carbon sequestered in amended soils, the mitigation of emissions and odors at low cost; as well as the hope of the implementation of this Optifangs system in neighboring countries.
The first OPTIFANGS Living Lab is operational on the campus of the Miguel Hernández University (UMH) in Elche. Specifically, it is located in the UMH Composting plant in Orihuela (Alicante).
In the Living Lab, advanced sensorization work is carried out through specific development prototypes for OPTIFANGS. With them, emissions linked to water treatment stations are monitored, identifying different emission sources in the plant for odors and greenhouse gases.
