Development and testing of a nanobubble-based hydrodynamic cavitation system

Emerging pollutants pose a significant challenge to conventional water and wastewater treatment technologies, highlighting the need for targeted and energy-efficient advanced oxidation processes. Although hydrodynamic cavitation (HC) has shown promising results, the potential of nanobubble-assisted HC remains largely unexplored. In this study, a specialized Venturi tube designed for nanobubble generation was developed and implemented in a pilot-scale (14 L) HC system for the degradation of humic acid (HA) and five active pharmaceutical ingredients (APIs) (climbazole, sulfadiazine, sulfamethazine, sulfapyridine, and venlafaxine). A response surface methodology (RSM) framework was applied to optimize the Venturi geometry, resulting in a high nanobubble fraction (ca. 90% < 1 μm), with a mean diameter of approximately 151 nm and a zeta potential of −15.4 mV. To further explore the design space, neural network modelling based on 10 prototypes was employed. The analysis revealed that reducing the throat diameter (D t ) to 0.5 mm could decrease the mean bubble diameter to approximately 90 nm, but with a four-fold reduction in hydraulic throughput (20 vs. 80 L/h), highlighting a critical trade-off between bubble size minimization and treatment capacity. In degradation tests, sodium persulfate (PS) consistently outperformed hydrogen peroxide (H 2 O 2 ) as an auxiliary oxidant. PS-assisted HC achieved ca. 56–88% primary degradation of the tested APIs and ca. 60% mineralization for HA. This performance was governed via rapid oxidant activation within the first 5–15 min, followed by sustained hydroxyl radical generation driven by hydrodynamic cavitation. Notably, the system operated without external energy inputs such as UV irradiation or ultrasonic transducers. Consequently, nanobubble-assisted HC represents a scalable, reagent- and energy- efficient water and wastewater treatment process, capable of delivering performance comparable to more complex hybrid processes.