Volume 8, Issue 1 (8-2015)                   ijhe 2015, 8(1): 89-96 | Back to browse issues page

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Jahangiri-rad M, Nabizadeh R, Nouri J, Yunesian M, Moattar F. Efficiency Assessment of Fixed Bed Adsorption Column for the Removal of nitrate using PAN-oxime-nano Fe2O3. ijhe. 2015; 8 (1) :89-96
URL: http://ijhe.tums.ac.ir/article-1-5354-en.html
1- Department of environment and energy, Science and research branch, Islamic azad university, Tehran, Iran
2- Department of environmental health engineering, Tehran university of medical sciences, Tehran, Iran
3- Department of environment and energy, Science and research branch, Islamic azad university, Tehran, Iran , nourijafar@gmail.com
Abstract:   (4856 Views)

Background and Objective: Nitrate is one of the dissolved anions having great health importance in water. Human activities and natural sources are considered as the main roots of nitrate intrusion in to water bodies. The main objective of this paper was to study nitrate removal by packed bed column filled with (PAN)-oxime-nano Fe2O3. Materials and Methods: PAN-oxime-nano Fe2O3 were synthesized and used as an adsorbent in glass column for the removal of nitrate from aqueous solution. Nitrate solution tank was set above the prepared column. The effect of factors, such as flow rate (2, 5, and 7 mL/min) and bed depth (5, 10, and 15 cm) were studied. Results: It was found that the data fit well with Thomas model and breakthrough curve was designed accordingly. The column performed well at lowest flow rate. As the flow rates and time increased, earlier breakthrough was observed. The column breakthrough time (Ce/C0 = 0.05) was reduced from 9 to 4 h, as the flow rates increased from2 to 7 mL/min. Conclusion: fixed-bed using PAN-oxime-nano Fe2O3 exhibited good removal of nitrate. The adsorption studies showed that at longer bed depth, better removal of nitrate would be achieved. Thomas model was suitable for the normal description of breakthrough curve at the experimental condition. The data also were in good agreement with logistic regression.

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Type of Study: Research | Subject: WATER
Received: 2014/12/4 | Accepted: 2015/07/28 | Published: 2015/07/28

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