Chemometric methods for the optimization of the advanced oxidation processes for the treatment of drinking and wastewater

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Abstract

Advanced Oxidative Processes (AOP) have been successfully employed as efficient water treatment methods. The utilization of AOP on drinking and wastewater represents currently an alternative to costly, hazardous, and slow processes. In order to further establish the ground basis for AOP in water safety and security, reliable and consistent methods of analysis are required. As an alternative to basic statistical methods, which may not successfully describe and forecast the application of a given treatment methodology of water, the use of chemometrics has increased significantly over the past decades. Chemometric analyses are an intersection between analytical chemistry and applied statistical models in order to predict and extract information from a given condition. This chapter introduces the concepts of chemometrics in environmental engineering issues and the utilization of experimental design to efficiently analyze experimental data in environmental samples. Two case studies are presented to demonstrate the importance of chemometrics in water analyses: (1) considering a Taguchi L16 experimental design, and an optimization study using Response Surface Methodology, to evaluate photo-Fenton and ozone AOP-based treatment on an effluent with high concentration of organic matter; (2) using a Taguchi L9 array to evaluate the combination of photocatalytic degradation and AOP of an industrial effluent. The results showed in this chapter demonstrate how a given statistical method can be successfully employed within the intersection of environmental analyses and water issues.

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Silva, M. B., Reis, C. E. R., Gomes, F. M., Contesini, B. dal R., de Freitas, A. P. B. R., Izário Filho, H. J., … Loures, C. C. A. (2019). Chemometric methods for the optimization of the advanced oxidation processes for the treatment of drinking and wastewater. In Handbook of Environmental Chemistry (Vol. 67, pp. 405–422). Springer Verlag. https://doi.org/10.1007/698_2017_117

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