MARATTO

article · Emerging contaminants

Application of Ethiopian bentonite for water treatment containing zinc

202224 citationsOpen accessDebre Berhan University

Abstract

The raw bentonite has low specific surface area and cation exchange potential. Thus, it needs change of its surface properties to increase its adsorption potential. To achieve this aim, the study was conducted by (1) Thermal modification and (2) characterisation, adsorption, isothermal and kinetics study of Ethiopia's bentonite for removal of Zinc. Characterisation of both the raw and thermally treated bentonite clay for specific surface area and cation exchange capacity, surface functional groups, crystallinity and differential thermal analysis were studied using Methylene blue test, Fourier transform infrared radiation, X-ray diffraction and differential scanning calorimetry respectively. The surface area was increased from 147.1 m2/g to 310.2 m2/g as change in temperature increases from 300 °C to 500 °C. The x-ray diffraction analysis confirms that the mineral is consists of montmorillonite and other impurities such as quartz, feldspar, muscovite, cristobalite and hematite. Thermal stability of bentonite was confirmed that its stable up to 500 °C. The effect of time, initial Zinc ion concentration and adsorbent dosage were experimentally studied using response surface methodology. Thus, the amount of adsorption of Zinc ion increases with increasing contact time and adsorbent dosage and decreasing with increasing Zinc ion concentration. The optimum design parameters were obtained 74.62 mg/l, 90min and 1.35 g and the percentage removal was 99.77% at this condition. The Langmuir isotherm and pseudo-second order kinetics provided best fits of the aggregation. Therefore, thermally treated bentonite provides the large surface area and adsorption potential and can be successfully applied for the removal of Zinc from wastewater.

Research topics

  • Clay minerals and soil interactions

Sustainable Development Goals

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.1016/j.emcon.2022.02.002

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.