Abstract
During wet complexation denitrification of flue gas,FeⅡEDTA regeneration,also known as reducing FeⅢEDTA and FeⅡEDTA-nitric oxide(NO)to FeⅡEDTA,is crucial.In this paper,ultraviolet(UV)light was used for the first time to reduce FeⅡEDTA-NO.The experimental result demonstrated that FeⅡEDTA-NO reduction rate increased with UV power increasing,elevated temperature,and initial FeⅡEDTA-NO concentration decreasing.FeⅡEDTA-NO reduction rate increased first and then decreased as pH value increased(2.0-10.0).FeⅡEDTA-NO reduction with UV irradiation presented a first order reaction with respect to FeⅡEDTA-NO.Compared with other FeⅡEDTA regeneration methods,FeⅡEDTA regeneration with UV show more superiority through comprehensive consideration of regeneration rate and pro-cedure.Subsequently,NO absorption experiment by FeⅡEDTA solution with UV irradiation confirmed that UV can significantly promote the NO removal performance of FeⅡEDTA.Appropriate oxygen concentra-tion(3％(vol))and acidic environment(pH=4)was favorable for NO removal.With UV power increasing as well as temperature decreasing,NO removal efficiency rose.In addition,the mechanism research indicates that NO from flue gas is mostly converted to NO2,NO3,NH4,N2,and N2O with FeⅡEDTA ab-sorption liquid with UV irradiation.UV strengthens NO removal in FeⅡEDTA absorption liquid by forming a synergistic effect of oxidation-reduction-complexation.Finally,compared with NO removal methods with FeⅡEDTA,FeⅡEDTA combined UV system shows prominent technology advantage in terms of economy and secondary pollution.
基金项目
National Natural Science Foundation of China(52260012)
Natural Science Foundation of Jiangxi Province(20232BAB203053)
Natural Science Foundation of Jiangxi Province(20212ACB213001)
Natural Science Foundation of Jiangxi Province(20232BAB203033)
General Project of Jiangxi Province Key Research and Development Program(20192BBG70008)
Training Plan for Academic and Technical Leaders of Major Disciplines in Jiangxi Provinceyouth Talent Project(20232BCJ23047)
NETL
NSTL
万方数据