Modeling As(V) removal by a iron oxide impregnated activated carbon using the surface complexation approach

Area of Science:

• Environmental Chemistry
• Adsorption Science
• Water Treatment Technologies

Background:

• Arsenic(V) contamination poses significant risks to water quality and human health.
• Iron oxide-based adsorbents show promise for arsenic removal, but their adsorption mechanisms require detailed modeling.
• Understanding the role of pH and adsorbent properties is crucial for optimizing arsenic remediation.

Purpose of the Study:

• To model Arsenic(V) removal using iron oxide impregnated activated carbon (FeAC) via the surface complexation model (SCM).
• To compare the efficacy of two-monoprotic and diprotic site models in describing Arsenic(V) adsorption.
• To establish a foundation for predicting Arsenic(V) adsorption in dynamic systems.

Main Methods:

• Utilized the surface complexation model (SCM) approach to analyze Arsenic(V) adsorption data.
• Employed two-monoprotic and diprotic site models to describe pH-dependent adsorption behavior.
• Determined adsorption constants (K(As)) from single adsorption experiments for predictive modeling.

Main Results:

• Arsenic(V) removal is attributed to the impregnated iron oxide, not the activated carbon support.
• The two-monoprotic site-triple layer model provided an adequate description of Arsenic(V) removal with fewer parameters.
• Both models successfully predicted Arsenic(V) removal across different adsorbent/adsorbate ratios.

Conclusions:

• The two-monoprotic model is preferred for modeling Arsenic(V) removal by FeAC due to its simplicity and mechanistic relevance.
• Fewer adsorption experiments are needed to model Arsenic(V) removal in equilibrium and column systems.
• This research provides a basis for developing dynamic models for fixed-bed adsorber systems.