Literature DB >> 25703617

Inactivation of Escherichia coli in fresh water with advanced oxidation processes based on the combination of O3, H2O2, and TiO2. Kinetic modeling.

Jorge Rodríguez-Chueca1, M Peña Ormad Melero, Rosa Mosteo Abad, Javier Esteban Finol, José Luis Ovelleiro Narvión.   

Abstract

The purpose of this work was to study the efficiency of different treatments, based on the combination of O3, H2O2, and TiO2, on fresh surface water samples fortified with wild strains of Escherichia coli. Moreover, an exhaustive assessment of the influence of the different agents involved in the treatment has been carried out by kinetic modeling of E. coli inactivation results. The treatments studied were (i) ozonation (O3), (ii) the peroxone system (O3/0.04 mM H2O2), (iii) catalytic ozonation (O3/1 g/L TiO2), and (iv) a combined treatment of O3/1 g/L TiO2/0.04 mM H2O2. It was observed that the peroxone system achieved the highest levels of inactivation of E. coli, around 6.80 log after 10 min of contact time. Catalytic ozonation also obtained high levels of inactivation in a short period of time, reaching 6.22 log in 10 min. Both treatments, the peroxone system (O3/H2O2) and catalytic ozonation (O3/TiO2), produced a higher inactivation rate of E. coli than ozonation (4.97 log after 10 min). While the combination of ozone with hydrogen peroxide or titanium dioxide thus produces an increase in the inactivation yield of E. coli regarding ozonation, the O3/TiO2/H2O2 combination did not enhance the inactivation results. The fitting of experimental values to the corresponding equations through non-linear regression techniques was carried out with Microsoft® Excel GInaFiT software. The inactivation results of E. coli did not respond to linear functions, and it was necessary to use mathematical models able to describe certain deviations in the bacterial inactivation processes. In this case, the inactivation results fit with mathematical models based on the hypothesis that the bacteria population is divided into two different subgroups with different degrees of resistance to treatments, for instance biphasic and biphasic with shoulder models. Graphical abstract ᅟ.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 25703617     DOI: 10.1007/s11356-015-4222-3

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  9 in total

1.  On calculating sterility in thermal preservation methods: application of the Weibull frequency distribution model.

Authors:  P Mafart; O Couvert; S Gaillard; I Leguerinel
Journal:  Int J Food Microbiol       Date:  2002-01-30       Impact factor: 5.277

2.  A modified Weibull model for bacterial inactivation.

Authors:  I Albert; P Mafart
Journal:  Int J Food Microbiol       Date:  2004-12-10       Impact factor: 5.277

3.  GInaFiT, a freeware tool to assess non-log-linear microbial survivor curves.

Authors:  A H Geeraerd; V P Valdramidis; J F Van Impe
Journal:  Int J Food Microbiol       Date:  2005-06-25       Impact factor: 5.277

4.  General model, based on two mixed weibull distributions of bacterial resistance, for describing various shapes of inactivation curves.

Authors:  L Coroller; I Leguerinel; E Mettler; N Savy; P Mafart
Journal:  Appl Environ Microbiol       Date:  2006-10       Impact factor: 4.792

Review 5.  Tailing of survival curves of bacterial spores.

Authors:  O Cerf
Journal:  J Appl Bacteriol       Date:  1977-02

6.  A kinetic study on the degradation of p-nitroaniline by Fenton oxidation process.

Authors:  Jian-Hui Sun; Sheng-Peng Sun; Mao-Hong Fan; Hui-Qin Guo; Li-Ping Qiao; Rui-Xia Sun
Journal:  J Hazard Mater       Date:  2007-02-15       Impact factor: 10.588

7.  Differentiating ozone direct and indirect reactions on decomposition of humic substances.

Authors:  Yen-Pei Chiang; Yung-Ying Liang; Cheng-Nan Chang; Allen C Chao
Journal:  Chemosphere       Date:  2006-06-19       Impact factor: 7.086

8.  Solar photocatalytic treatment of synthetic municipal wastewater.

Authors:  M Kositzi; I Poulios; S Malato; J Caceres; A Campos
Journal:  Water Res       Date:  2004-03       Impact factor: 11.236

9.  Trihalomethane occurrence in chlorinated reclaimed water at full-scale wastewater treatment plants in NE Spain.

Authors:  Víctor Matamoros; Rafael Mujeriego; Josep M Bayona
Journal:  Water Res       Date:  2007-05-01       Impact factor: 11.236

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.