Loading…

Optimization of oxidative desulfurization of gas condensate via response surface methodology approach

In the present research, modeling and optimization of a new method of oxidative desulfurization (ODS) of sour gas condensate has been done. In the ODS process, combination of H2SO4, HNO3, and NO2 as oxidizing agents at varying concentrations followed by extraction, was applied. A response surface me...

Full description

Saved in:
Bibliographic Details
Published in:Journal of cleaner production 2019-02, Vol.209, p.965-977
Main Authors: Pouladi, Babak, Fanaei, Mohammad Ali, Baghmisheh, Gholamreza
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In the present research, modeling and optimization of a new method of oxidative desulfurization (ODS) of sour gas condensate has been done. In the ODS process, combination of H2SO4, HNO3, and NO2 as oxidizing agents at varying concentrations followed by extraction, was applied. A response surface methodology (RSM) was deployed for the experimental design, model development, and testing the validity of the model using Design-Expert® software. Moreover, investigation of the main effects as well as the combined effects of the process parameters on the response was also carried out. For the first time in a gas-liquid ODS system, a mixing-assisted oxidative desulfurization (MAOD) approach was considered by applying a shear mixer. The value greater than 0.9 for R2 of the sulfur removal data confirmed that the quadratic equation properly fitted the experimental data. Optimization results predicted that the implementation of the process at 0.593, 0.682, and 0.264 mol of H2SO4, HNO3, and NO2, respectively, for a sample of 1500 gr gas condensate, would result in the minimum residual sulfur content of 100.9 ppmw (95.61% sulfur removal) while the actual value of sulfur removal at the predicted optimized conditions was determined as 102 ppmw (95.56% sulfur removal). With respect to the obtained results, the developed model was in good agreement with the experimental results.
ISSN:0959-6526
1879-1786
DOI:10.1016/j.jclepro.2018.10.283