Numerical Investigation of Air Quality Improvement in Mechanically Ventilated Green Buildings
DOI:
https://doi.org/10.63503/j.ijssic.2025.121Keywords:
Indoor Air Quality (IAQ), Computational Fluid Dynamics (CFD), Airflow Dynamics, Green Buildings, Predicted Mean Vote(PMV), Mechanical VentilationAbstract
Improvement of indoor air quality is a necessity for sustainable green building design. Mechanically ventilated systems are a viable alternative to pollutant control, but careful optimization of the configuration system is required to assess these effects: airflow dynamics, pollutant dispersion, and temperature comfort performance. This study is an extensive numerical study of the effectiveness of mechanical ventilation in ensuring IAQ in green buildings, via Computational Fluid Dynamics (CFD). A mathematical model containing mass flow, momentum, energy, and species transport equations is used to model airflow and pollutant disposition. Supporting parameters include air exchange rate, ventilation effectiveness, pollutant purge efficiency, and Predictive Mean Vote (PMV), all of which determine both IAQ and comfort levels of occupants. A series of ventilation case studies is solved serially by an optimization algorithm, changing the flow rates and boundaries to determine the optimal structure. Simulation results are given in plots that demonstrate the trends of the pollutant concentration, airflow distribution, and comfort index. In the best case, the pollutant removal efficiency obtained approaches 95.2% with an airflow of 100 m ³ /h and marked improvements in thermal comfort. The results show that within properly designed mechanical ventilation, it is possible to achieve substantially improved IAQ and satisfy thermal comfort goals. This methodology presents a scalable, simulation-driven methodology for designing efficient ventilation systems in green buildings. Possible future works may investigate dynamic indoor environments concerning real-time adaptive control strategies.
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