<jats:title>Abstract</jats:title>
          <jats:p>Activation of peroxymonosulfate (PMS) by Co and Cu doped zeolitic imidazolate framework, ZIF-8 s for degradation of sulfamethazine (SMZ) was investigated. It was observed that combination of the two metals increased the PMS activation efficiency by using the activity of both metal redox pairs to increase the production of sulfate and hydroxyl radicals. Different characterization techniques, including nitrogen (N<jats:sub>2</jats:sub>) adsorption, Fourier-transform infrared (FTIR), scanning electron microscopy energy-dispersive spectroscopy (SEM–EDS mapping), X-ray photoelectron spectroscopy (XPS), and thermogravimetric analysis (TGA), were used to characterize the synthesized catalysts, ZIF-8, Cu/ZIF-8, and Co/ZIF-8. No structural differences were observed in catalysts obtained after bimetallic synthesis. The BET surface area was calculated as 1145, 742, 945 m<jats:sup>2</jats:sup>/g for ZIF-8, Cu/ZIF-8, and Co/ZIF-8, respectively. Under reaction conditions of 0.1 g/L PMS dosage, 0.5 g/L catalyst dosage, and original pH, sulfamethazine degradation after 30 min was 10.5% with PMS alone (no catalyst), 28.0% with ZIF-8, 33.9% with Cu/ZIF-8, and 58.4% with Co/ZIF-8, clearly demonstrating the superior catalytic performance of Co/ZIF-8. Using Box–Behnken design and response surface methodology, reaction parameters were optimized in the presence of the most efficient catalyst, Co/ZIF-8. The sulfamethazine removal was optimized at 0.55 g/L catalyst dosage, pH 5.2 and 0.15 g/L PMS dosage. Under the optimal reaction conditions 67.3% sulfamethazine removal was achieved within 30 min in the presence of Co/ZIF-8 as catalyst. Scavenging experiments showed that the dominant reactive oxygen species was hydroxyl radicals. According to the phytotoxicity test performed by using <jats:italic>L. sativum,</jats:italic> 35.9% growth inhibition was evaluated.</jats:p>

Cobalt/Copper Doped Bimetallic Zeolitic Imidazolate Frameworks as Peroxymonosulfate Activators for the Removal of Veterinary Antibiotics: Response Surface Modeling and Optimization of Reaction Parameters