Simulation of sorption processes of wastewater treatment by modified zeolites

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Abstract

Based on the results of experimental studies of sorption wastewater treatment, a regression-type mathematical model has been developed that adequately describes the effect of all parameters of the ongoing process on the sorption activity of zeolite: initial concentration, sorption time, process temperature, and medium pH. For the first time in research, a generalized criterion for the consistency of behavior and the width of the domain of definition of the model was used. The processes of involving large-tonnage wastes of chemical production to obtain adsorption materials effective for the extraction of heavy metal ions from industrial wastewater have been studied. Natural zeolites were used as the initial matrix, the main component of which is klinoptilolite. A sulfur polymer obtained from epichlorohydrin production wastes with the main component 1,2,3-trichloropropane is proposed as a modifier. Fixation of the modifier on the surface of the zeolite, as well as the effective adsorption of metal ions, have been proven by IR spectroscopy and energy dispersive analysis.

About the authors

Marina V. Obuzdina

Irkutsk State Transport University

Author for correspondence.
Email: obuzdina_mv@mail.ru
ORCID iD: 0000-0002-4956-0063

Candidate of Technical Sciences, Assistant Professor of Department for Technosphere Safety

15 Chernyshevsky St, Irkutsk, 664074, Russian Federation

Elena A. Rush

Irkutsk State Transport University

Email: lrush@mail.ru
Doctor of Engineering Sciences, Professor, Heard of Department for Technosphere Safety 15 Chernyshevsky St, Irkutsk, 664074, Russian Federation

References

  1. Inamuddin D, Mohammad L. Ion Exchange Technology. Theory and Materials. Springer Science & Business Media Springer. Dordrecht. Heidelberg. New York. London; 2012.
  2. Dabrowski A, Hubicki Z, Podkoscielny P, Robens E. Selective removal of the heavy metal ions from waters and wastewaters byion-exchange method. Chemosphere. 2004;56(2);91–106.
  3. Obuzdina М, Rush E. Intensification the features of interaction between components of pollutants of industrial waste waters with modified zeolites based on the results of integrated physical and chemical researches. Ecology and industry of Russia. 2021;25(3);36–40. (In Russ.)
  4. Ross J. Microelectronics Failure Analysis Desc Reference. Sixth Edition. USA: ASMInternational; 2011.
  5. Shindo D, Oikawa T. Analytical transmission electron microscopy. Moscow: Technosphere; 2006. (In Russ.)
  6. Noskov SI. The method of anti-robust estimation of linear regression parameters: the number of maximum approximation errors in modulus. South Siberian Scientific Bulletin. 2020;1;51–54. (In Russ.)
  7. Aivazyan SA, Enyukov IS, Meshalkin LD. Applied Statistics. Classification and dimension reduction. Moscow: Finance and statistics; 1989. (In Russ.)
  8. Statkus M, Tsysin GI. Mathematical modeling of sorption preconcentration in flow analysis system. Moscow University Chemistry Bulletin. 2009;64(4);192–197.

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