Techno-economic evaluation of UV light technologies in water remediation

Disinfection commonly follows conventional treatments in wastewater treatment and remediation plants aiming at reducing the presence of pathogens. However, the presence of the so called "micropollutants" has emerged as a serious concern, therefore developing tertiary treatments that are not only able to remove pathogens but also to degrade micropollutants is worth investigating. Nowadays, UV-C photo-degradation processes are widely used for disinfection due to their simplicity and easy operation; additionally, they have shown potential for the removal of contaminants of emerging concern. Conventional mercury lamps are being replaced by light-emitting diodes (LEDs) that avoid the use of toxic mercury and can be switched on and off with no effect on the lamp lifetime. This work aims to comparatively evaluate the performance of several photo-degradation technologies for the removal of two targeted micropollutants, the pharmaceutical dexamethasone (DXMT) and the herbicide S-metolachlor (MTLC), using UV irradiation doses typical of disinfection processes. To this end, the technical performance of UV-A/UV-C photolysis, UV-A/UV-C photocatalysis, UV-C/H2O2 and UV-C/NaOCl has been compared. The influence of operating conditions such as the initial concentration of the pollutants (3 mg L-1 - 30 mg L-1, concentrations found in membrane or adsorption remediation steps), pH (3-10), and water matrix (WWTP secondary effluent, and ultrapure water) on the degradation efficiency has been studied. The economic evaluation in terms of electricity and chemicals consumption and the carbon footprint has been evaluated. UV-C photolysis and UV-C photocatalysis appear as the most suitable technologies for the degradation of DXMT and MTLC, respectively, in terms of kinetics (1.53·10-1 min-1 for DXMT and 1.96·10-2 min-1 for MTLC), economic evaluation (1 € m-3 for DXMT and 32 € m-3 for MTLC) and environmental indicators (0.5 g-CO2 for DXMT and 223.1 g-CO2 for MTLC).

These results are part of the R&D project RTC2019-006820-5 funded by MCIN/AEI/10.13039/501100011033.