摘要
在分析聚合硅酸铁多相UV-Fenton体系降解橙Ⅱ过程的基础上,比较了全过程拟合和两段拟合两种方法计算橙Ⅱ脱色动力学常数的精度,建立并验证了以催化剂用量和H2O2初始浓度为变量的橙Ⅱ脱色动力学模型。结果表明,聚合硅酸铁多相UV-Fenton体系中,橙Ⅱ的脱色以15/min为时间节点分为快速和慢速脱色两个阶段。快速脱色阶段主要以N=N断裂为主,发色体降解为辅;慢速脱色阶段主要以发色体矿化为主,N=N断裂为辅。两段拟合法得到的橙Ⅱ脱色动力学模型精度更高、误差更小,能够为聚合硅酸铁多相UV-Fenton降解橙Ⅱ提供更为精确的理论计算。本研究将为聚合硅酸铁多相UV-Fenton体系的应用提供理论依据和技术支持。
Based on the analysis of OrangeⅡdegradation in the heterogeneous UV-Fenton system with poly-silicate-ferric as catalyst,the accuracy between full-process linear fitting method and piecewise linear fitting method in calculating kinetic constant were compared.A kinetic model of OrangeⅡdecoloration was established and verified in terms of catalyst amount and hydrogen peroxide concentration.The results showed that in this heterogeneous UV-Fenton system,the decolorization process of OrangeⅡcould be divided into two stages:rapid and slow decolorization stages using 15 min as the dividing line.The rapid decolorization stage was mainly dominated by nitrogen double bonds breaking,and chromophore degradation as a supplement.While the slow decolorization stage was mainly dominated by chromophore mineralization,and nitrogen double bonds breaking as a supplement.The kinetic model based on two-stage linear fitting method had higher accuracy and smaller error in simulation,which could successfully predict OrangeⅡdegradation in this heterogeneous UV-Fenton system through theoretical calculation.This study would provide theoretical basis and technical support for the application of heterogeneous UV-Fenton system with poly-silicate-ferric as catalyst.
作者
陈建新
刘治庆
李献众
姜自立
刘力章
CHEN Jianxin;LIU Zhiqing;LI Xianzhong;JIANG Zili;LIU Lizhang(School of Resources,Environmental and Chemical Engineering,Nanchang University,Nanchang 330031,China;The Key Laboratory of Poyang Lake Environment and Resource Utilization of Ministry of Education,Nanchang 330031,China;Jiangxi Academy of Environmental Sciences,Nanchang 330077,China)
出处
《南昌大学学报（理科版）》
CAS
北大核心
2020年第3期254-261,共8页
Journal of Nanchang University(Natural Science)
基金
国家自然科学基金资助项目(21966021,21367021)
广东省科技计划项(2017B030314175)。
