A methodology for modeling photocatalytic reactors for indoor pollution control using previously estimated kinetic...

Area of Science:

• Environmental Engineering
• Chemical Engineering
• Photocatalysis

Background:

• Indoor air pollution is a significant health concern.
• Photocatalytic oxidation (PCO) is a promising technology for air purification.
• Accurate modeling of PCO reactors is crucial for effective design and application.

Purpose of the Study:

• To develop and validate a comprehensive methodology for modeling photocatalytic reactors for indoor air pollution control.
• To determine intrinsic reaction kinetics for formaldehyde removal.
• To apply these kinetics to a complex reactor configuration and compare with experimental results.

Main Methods:

• Determined intrinsic reaction kinetics under steady-state conditions using a continuous reactor.
• Employed nonlinear optimization to estimate kinetic parameters from experimental data.
• Modeled radiative transfer using ray tracing and view factors in a corrugated wall reactor.
• Utilized computational fluid dynamics (CFD) with an external radiation model to simulate velocity and concentration fields.

Main Results:

• Successfully applied determined kinetic parameters to a corrugated wall photoreactor.
• Achieved good agreement between model predictions and experimental data for overall pollutant conversion.
• Reported a root mean square error of less than 4% for model predictions.

Conclusions:

• The developed methodology provides a reliable approach for modeling photocatalytic reactors for indoor air purification.
• The study demonstrates the effectiveness of TiO(2) photocatalysis for formaldehyde removal.
• Validated CFD simulations are essential tools for optimizing PCO reactor performance.