BTEXS Removal From Aqueous Phase by MCM-۴۱ Green Synthesis Using Rice Husk Silica

Publish Year: 1402
نوع سند: مقاله ژورنالی
زبان: English
View: 181

This Paper With 15 Page And PDF Format Ready To Download

  • Certificate
  • من نویسنده این مقاله هستم

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این Paper:

شناسه ملی سند علمی:

JR_IJEE-14-4_002

تاریخ نمایه سازی: 20 فروردین 1402

Abstract:

Large volumes of contaminated industrial wastewater have caused growing concern among researchers and environmentalists. Benzene, toluene, ethylbenzene, xylene, and styrene (BTEXS) cyclic hydrocarbons in industrial effluents are often completely stable to biodegradation and must be treated before disposal. In this context, using adsorption processes is a potential alternative for treating a wide range of organic pollutants, especially aromatic compounds in industrial wastewater. This study investigated the preparation of MCM-۴۱ from silica; extracted from rice husk ash; MCM-۴۱ was green synthesized to evaluate the effect of mesoporous used in BTEXS removal of an aqueous medium using the Taguchi method. The aqueous solution contains cyclic hydrocarbons was synthetically prepred based on real industrial effluent in concentrations of ۵۰, ۱۰۰, and ۱۵۰ mg/l using MCM-۴۱ catalysts, in doses of ۰.۱, ۰.۵, and ۱g, at different pH values. In the present study, the optimum results obtained by Taguchi method analysis were pH =۱۱, for duration of ۶۰ minutes, the concentration of cyclic hydrocarbon solution BTEXS ۱۰۰ mg/l, and nanoparticle dose of ۰.۵ g. The maximum BTEXS removal of ۷۷.۳۶% was achieved by the use of hydrogen peroxide.

Authors

M. Heydari

Department of Environment, Bushehr Branch, Islamic Azad University, Bushehr, Iran

T. Tabatabaie

Department of Environment, Bushehr Branch, Islamic Azad University, Bushehr, Iran

F. Amiri

Department of Environment, Bushehr Branch, Islamic Azad University, Bushehr, Iran

S. E. Hashemi

Department of Environment, Bushehr Branch, Islamic Azad University, Bushehr, Iran

مراجع و منابع این Paper:

لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :