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      Application of response surface methodology for optimization of natural organic matter degradation by UV/H 2O 2 advanced oxidation process

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          Abstract

          Background

          In this research, the removal of natural organic matter from aqueous solutions using advanced oxidation processes (UV/H 2O 2) was evaluated. Therefore, the response surface methodology and Box-Behnken design matrix were employed to design the experiments and to determine the optimal conditions. The effects of various parameters such as initial concentration of H 2O 2 (100–180 mg/L), pH (3–11), time (10–30 min) and initial total organic carbon (TOC) concentration (4–10 mg/L) were studied.

          Results

          Analysis of variance (ANOVA), revealed a good agreement between experimental data and proposed quadratic polynomial model (R 2 = 0.98). Experimental results showed that with increasing H 2O 2 concentration, time and decreasing in initial TOC concentration, TOC removal efficiency was increased. Neutral and nearly acidic pH values also improved the TOC removal. Accordingly, the TOC removal efficiency of 78.02% in terms of the independent variables including H 2O 2 concentration (100 mg/L), pH (6.12), time (22.42 min) and initial TOC concentration (4 mg/L) were optimized. Further confirmation tests under optimal conditions showed a 76.50% of TOC removal and confirmed that the model is accordance with the experiments. In addition TOC removal for natural water based on response surface methodology optimum condition was 62.15%.

          Conclusions

          This study showed that response surface methodology based on Box-Behnken method is a useful tool for optimizing the operating parameters for TOC removal using UV/H 2O 2 process.

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          Most cited references 24

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          Box-Behnken design: an alternative for the optimization of analytical methods.

          The present paper describes fundamentals, advantages and limitations of the Box-Behnken design (BBD) for the optimization of analytical methods. It establishes also a comparison between this design and composite central, three-level full factorial and Doehlert designs. A detailed study on factors and responses involved during the optimization of analytical systems is also presented. Functions developed for calculation of multiple responses are discussed, including the desirability function, which was proposed by Derringer and Suich in 1980. Concept and evaluation of robustness of analytical methods are also discussed. Finally, descriptions of applications of this technique for optimization of analytical methods are presented.
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            Removal of natural organic matter from drinking water by advanced oxidation processes.

            Over the past 10-20years the amount of the natural organic matter (NOM) has been increased in raw water supplies on several areas. The presence of NOM causes many problems in drinking water treatment processes, including: (i) negative effect on water quality by colour, taste and odor problems, (ii) increased coagulant and disinfectant dose requirements (which in turn results increased sludge and potential harmful disinfection by-product formation), (iii) promoted biological growth in distribution system, and (iv) increased levels of complexed heavy metals and adsorbed organic pollutants. Thus, more efficient methods for the removal of NOM have emerged. Among these are advanced oxidation processes (AOPs). These include O(3)/H(2)O(2), O(3)/UV, UV/H(2)O(2), TiO(2)/UV, H(2)O(2)/catalyst, Fenton and photo-Fenton prosesses as well as ultrasound. In the present work, an overview of the recent research studies dealing with AOP methods for the removal of NOM and related compounds from drinking water is presented.
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              An overview of the methods used in the characterisation of natural organic matter (NOM) in relation to drinking water treatment.

              Natural organic matter (NOM) is found in all surface, ground and soil waters. During recent decades, reports worldwide show a continuing increase in the color and NOM of the surface water, which has an adverse affect on drinking water purification. For several practical and hygienic reasons, the presence of NOM is undesirable in drinking water. Various technologies have been proposed for NOM removal with varying degrees of success. The properties and amount of NOM, however, can significantly affect the process efficiency. In order to improve and optimise these processes, the characterisation and quantification of NOM at different purification and treatment processes stages is important. It is also important to be able to understand and predict the reactivity of NOM or its fractions in different steps of the treatment. Methods used in the characterisation of NOM include resin adsorption, size exclusion chromatography (SEC), nuclear magnetic resonance (NMR) spectroscopy, and fluorescence spectroscopy. The amount of NOM in water has been predicted with parameters including UV-Vis, total organic carbon (TOC), and specific UV-absorbance (SUVA). Recently, methods by which NOM structures can be more precisely determined have been developed; pyrolysis gas chromatography-mass spectrometry (Py-GC-MS), multidimensional NMR techniques, and Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The present review focuses on the methods used for characterisation and quantification of NOM in relation to drinking water treatment. Copyright © 2011 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                Journal
                J Environ Health Sci Eng
                J Environ Health Sci Eng
                Journal of Environmental Health Science and Engineering
                BioMed Central
                2052-336X
                2014
                15 April 2014
                : 12
                : 67
                Affiliations
                [1 ]Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
                [2 ]Kurdistan Environmental Health Research Center, Kurdistan University of Medical Sciences, Sanandaj, Iran
                [3 ]Center for Solid Waste Research, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran
                [4 ]National Institute of Health Research, Tehran University of Medical Sciences, Tehran, Iran
                Article
                2052-336X-12-67
                10.1186/2052-336X-12-67
                3999503
                24735555
                Copyright © 2014 Rezaee et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.

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