Evolution of Urban Ventilation in Warsaw: CFD Modeling Analysis and the Impact of Urban Development

Urban air movement represents a fundamental factor in assessing thermal balance and pollutant dispersion in cities.

This issue is gaining increasing importance in the context of ongoing climate change and the rapid expansion of urban areas and their suburbs. The presentation introduces a study investigating the evolution of urban ventilation in Warsaw between 1986 and 2024, utilizing Computational Fluid Dynamics (CFD) modeling techniques.

Based on historical and contemporary orthophoto maps, detailed land use and building coverage maps were built for selected periods. These maps formed the basis for a series of CFD simulations designed to analyze airflow patterns under various synoptic conditions. The synoptic situations were selected through climatological statistical analysis derived from the existing meteorological monitoring network, which also served as a validation source for the CFD model outputs. Importantly, areas characterized by significant vegetation cover were also incorporated into the simulation environment to enhance the realism and accuracy of the airflow modeling.

The simulation results were compared across time intervals to evaluate how urban development has influenced the efficiency of natural ventilation. Particular focus was placed on urban sectors designated by municipal authorities as ventilation corridors—zones of strategic importance for maintaining air quality and mitigating urban heat island effects. Unfortunately, in several of these key areas, pressure from real estate development has narrowed the ventilation corridors, potentially resulting in degraded airflow and reduced dispersion of pollutants.

The presented research seeks to address the critical question of whether new urban development has had a measurable impact on the quality of air circulation within the city. In addition to advanced CFD tools, the study extensively employed Geographic Information System (GIS) software and the Python programming for data processing, visualization, and model integration.