A virtual–physical hybrid digital twin of an integrated catalytic purification and CO ₂ capture system

This paper presents a virtual–physical hybrid digital twin for sustainable operation and optimization of an integrated catalytic purification and CO₂ capture system. The twin continuously links a real emission treatment installation with its digital representation to improve energy efficiency, emission reduction, and adaptability under variable operating conditions. The framework integrates physics-based models of electrostatic particulate removal, catalytic conversion of gaseous pollutants, and thermodynamic CO₂ capture in a unified virtual environment. Data-driven components enable real-time synchronization between the physical system and its digital counterpart for transient regimes and load fluctuations. Validation against laboratory and operational data shows strong agreement between virtual and physical behaviour, including particulate removal accuracy of 94.7%, catalytic conversion deviations below 2.3%, and CO₂ capture performance exceeding 92%. Integrated optimization resulted in a 17.2% reduction in energy consumption compared to conventional operation. The results demonstrate the suitability of the proposed digital twin for improving sustainability and environmental performance of industrial emission purification and decarbonization systems.