Lead sorpion onto ferrihydrite. 2. Surface complexation modeling

Area of Science:

• Environmental Chemistry
• Geochemistry
• Surface Chemistry

Background:

• Predicting trace metal behavior in aqueous systems is crucial for environmental management.
• Surface complexation models (SCMs) are vital tools for understanding metal speciation and partitioning.
• Few studies integrate molecular and macroscopic data with SCM development for broad condition predictions.

Purpose of the Study:

• To assess the modified triple-layer model (TLM) for predicting lead(II) [Pb(II)] sorption on 2-line ferrihydrite.
• To evaluate the impact of pH, ionic strength, and concentration on Pb(II) sorption.
• To determine the efficacy of combining macroscopic and spectroscopic data for SCM development.

Main Methods:

• Extensive macroscopic and spectroscopic data collection.
• Regression analysis of constant-pH isotherm, potentiometric titration, and pH edge data.
• Development and testing of a modified triple-layer model (TLM) with various surface species and site types.

Main Results:

• A two-species, one-site model accurately fit isotherm data when combined with spectroscopic data.
• Regressing edge data alone yielded models that failed to predict isotherm behavior.
• Adjustments outside typical pH ranges and inclusion of a surface activity term were necessary for accurate fits.

Conclusions:

• Existing SCMs may be questionable for predicting Pb(II) sorption on ferrihydrite across diverse conditions.
• Integrating spectroscopic data significantly improves SCM predictive capabilities.
• Further refinement of SCM thermodynamic frameworks and databases is essential for accurate environmental predictions.