Evaluation of Removal and Adsorption Isotherms of Zinc and Copper from Municipal Solid Waste Leachate Using Clinoptilolite Adsorbent

来自 Ingenta

阅读量:

19

作者:

A ToolabiA AllahabadiM MiriHRK Sani

展开

摘要:

Introduction and Purpose: Heavy metals are among the most important pollutants in leachate waste, causing serious health risks for humans through entering the food chain and reaching the top of food pyramid. Therefore, this study aimed to evaluate the efficacy of modified clinoptilolite in the removal of copper and zinc ions from landfill leachate and modeling of adsorption isotherms and reactions.Methods: This cross-sectional in vitro study was conducted to test waste landfill leachate as a true sample for four seasons in 2014 in Bam, Iran. Natural zeolite (clinoptilolite), modified with 2 M HNO3 solution, was used to remove copper and zinc. Experiments were conducted as batch systems, in which the effects of pH, adsorbent dosage, and contact time on the adsorption of heavy metals in municipal waste landfill leachate by clinoptilolite (as soil amendment) were investigated. Afterwards, the adsorption isotherms of each adsorbent were demonstrated.Results: In total, the removal efficency of zinc in the optimum pH=5, equallied time=120 min and Adsorbent dosage of 120g/l was reached 92%. Adsorption isotherms indicated that the capacity of this adsorbent was higher in zinc, compared to copper, and adsorbents were absorbed with higher energy. The adsorption process was based on Langmuir's equations (isotherm type II) (R2=0.99).Conclusion: According to the results, adsorption capacity of clinoptilolite was high for copper and zinc and based on isotherm equations, adsorption took place with higher energy. It was concluded that this method could be used for the removal of these metals due to its high removal efficiency. Therefore, it is recommended that further studies be conducted to evaluate the possibility of removal of other heavy metals with this method.

展开

年份:

2016

通过文献互助平台发起求助,成功后即可免费获取论文全文。

相似文献

参考文献

引证文献

辅助模式

0

引用

文献可以批量引用啦~
欢迎点我试用!

关于我们

百度学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们保持学习的态度,不忘初心,砥砺前行。
了解更多>>

友情链接

百度云百度翻译

联系我们

合作与服务

期刊合作 图书馆合作 下载产品手册

©2025 Baidu 百度学术声明 使用百度前必读

引用