Abstract
The abatements of 89 pharmaceuticals in secondary effluent by ozonation and the electro-peroxone (E-peroxone) process were investigated. Based on the results, a quantitative structure-activity relationship (QSAR) model was developed to explore relationship between chemical structure of pharmaceuticals and their oxidation rates by ozone. The orthogonal projection to latent structure (OPLS) method was used to identify relevant chemical descriptors of the pharmaceuticals, from large number of descriptors, for model development. The resulting QSAR model, based on 44 molecular descriptors related to the ozone reactivity of the pharmaceuticals, showed high goodness of fit(R2 = 0.963) and predictive power (Q2 = 0.84). After validation, the model was used to predict second-order rate constants of 491 pharmaceuticals of special concern (\({k_{{{\rm{O}}_3}}}\)) including the 89 studied experimentally. The predicted \({k_{{{\rm{O}}_3}}}\) values and experimentally determined pseudo-first order rate constants of the pharmaceuticals’ abatement during ozonation (kOZ) and the E-peroxone process (kEP) were then used to assess effects of switching from ozonation to the E-peroxone process on removal of these pharmaceuticals. The results indicate that the E-peroxone process could accelerate the abatement of pharmaceuticals with relatively low ozone reactivity (\({k_{{{\rm{O}}_3}}} < \; \sim {10^2}{{\rm{M}}^{- 1}} \cdot {{\rm{s}}^{ - 1}}\)) than ozonation (3–10 min versus 5–20 min). The validated QSAR model predicted 66 pharmaceuticals to be highly O3-resistant. The developed QSAR model may be used to estimate the ozone reactivity of pharmaceuticals of diverse chemistry and thus predict their fate in ozone-based processes.
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Acknowledgements
This study was supported by the NSFC (Grant No. 51878370), the National Special Program of Water Pollution Control and Management (2017ZX07202), and the special fund of State Key Joint Laboratory of Environment Simulation and Pollution Control (18L01ESPC). The authors also thank the Industrial Doctoral School, Umeå University (Sweden), for financial support. The authors also acknowledge support from the Kempe Foundation (SJCKMS), Umeå University (Sweden) (for providing travel grants to conduct experiments at the School of Environment, Tsinghua University, Beijing, China), Ziye Zheng of Umeå University (Sweden), for descriptors calculations, and Dr. David Andersson of Umeå University (Sweden), for valuable guidance in QSAR model development.
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Highlights
• Effect of converting ozonation to E-peroxone was studied on pharmaceutical removal.
• A QSAR model was developed for selected 89 pharmaceuticals of special concern.
• Both processes abated the pharmaceuticals of moderate and high \({k_{{{\rm{O}}_3}}}\) quickly.
• E-peroxone process accelerated the elimination of pharmaceuticals with low \({k_{{{\rm{O}}_3}}}\).
• Developed QSAR model reliably predicted \({k_{{{\rm{O}}_3}}}\) of 418 out of 491 pharmaceuticals.
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Mustafa, M., Wang, H., Lindberg, R.H. et al. Identification of resistant pharmaceuticals in ozonation using QSAR modeling and their fate in electro-peroxone process. Front. Environ. Sci. Eng. 15, 106 (2021). https://doi.org/10.1007/s11783-021-1394-6
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DOI: https://doi.org/10.1007/s11783-021-1394-6