Silver nano-particles deposited on bamboo-based activated carbon for removal of formaldehyde

被引:48
作者
Rengga, Wara Dyah Pita [1 ]
Chafidz, Achmad [1 ]
Sudibandriyo, Mahmud [2 ]
Nasikin, Mohammad [2 ]
Abasaeed, Ahmed E. [3 ]
机构
[1] Univ Negeri Semarang, Dept Chem Engn, Semarang 50229, Indonesia
[2] Univ Indonesia, Dept Chem Engn, Depok 16424, Indonesia
[3] King Saud Univ, Dept Chem Engn, POB 800, Riyadh 11421, Saudi Arabia
来源
JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING | 2017年 / 5卷 / 02期
关键词
Formaldehyde; Activated carbon; Bamboo; Silver nano-particles; Adsorption; HIGH-SURFACE-AREA; FIXED-BED; BASIC DYE; ADSORPTION; SHELL; PYROLYSIS; MICROWAVE; OXIDATION; MODEL; GAS;
D O I
10.1016/j.jece.2017.02.033
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Volatile organic compounds, e.g. formaldehyde, could pollute the indoor and outdoor air. Activated carbon (AC) is most widely used adsorbent for removal of this pollutant. In this work, an adsorbent made of silver nano-particles attached onto bamboo-based activated carbon (Ag-AC) was prepared. The adsorbent was characterized by FESEM, TEM, SEM-EDX, BET, and XRD. FESEM images showed that Ag-AC has less pores than the AC, indicating that the silver nano-particles were deposited on the pore structures of AC. TEM image showed that the silver nano-particles were well distributed on the bamboo-based activated carbon. The SEM-EDX results confirmed the presence of silver on Ag-AC, whereas the BET specific surface area measurements indicated that the nanoparticle deposits reduced the available surface area of the activated carbon. The adsorption experiments were conducted in a continuous fixedbed column. The effect of different influent flow rates and initial concentrations of formaldehyde were studied. The Ag-AC adsorbent exhibited much longer breakthrough times during column tests than AC at the same flow rate. The mass of formaldehyde removed by the Ag-AC column was 2.36 times greater than that observed in the AC column. The experimental breakthrough data agreed within 5% with the predictions of Thomas and Yoon-Nelson models. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1657 / 1665
页数:9
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