Modeling and optimization of process variables for HCl gas removal by response surface methodology

Area of Science:

• Chemical Engineering
• Environmental Engineering
• Process Optimization

Background:

• Hydrochloric acid (HCl) gas is a toxic industrial pollutant requiring efficient removal.
• Venturi scrubbers are commonly used for gas absorption processes.
• Optimization of scrubber performance is crucial for environmental protection.

Purpose of the Study:

• To maximize the removal efficiency of toxic HCl gas using a submerged self-priming venturi scrubber.
• To identify the optimal process variables for HCl gas removal.

Main Methods:

• Response surface methodology (RSM) with a central composite design (CCD) was employed.
• Statistical analysis, including ANOVA and regression analysis, was used to evaluate model significance and suitability.
• Experimental data were used to develop a predictive quadratic model for removal efficiency.

Main Results:

• A quadratic model was developed to predict HCl removal efficiency, with a high coefficient of determination (R² = 0.9717).
• Optimal operating conditions were determined as 55.18 m/s throat gas velocity, 405.10 ppm inlet HCl concentration, and 0.0038 N NaOH concentration.
• These conditions yielded a maximum HCl removal efficiency of 90.80%.

Conclusions:

• The developed RSM model accurately predicts venturi scrubber performance for HCl removal.
• The identified optimal conditions provide a practical guideline for maximizing HCl gas removal efficiency in industrial applications.
• This optimization contributes to improved air pollution control and environmental safety.