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GO AQS held its 1st General Assembly Webinar across two sessions on December 11, 2025

GO AQS held its 1st General Assembly Webinar across two sessions on December 11, 2025, bringing together international experts and academics to discuss foundational steps and future directions for Indoor Air Quality (IAQ) worldwide. The sessions highlighted a consensus that IAQ must fundamentally shift from being a marginalized technical detail to a primary public health concern, supported by unified metrics, innovative technology, and strong governance.

Dr. Christos D. Argyropoulos dives into the power of computational modeling to tackle indoor air quality challenges. From dust storms in Saudi Arabia to the impact of pollutants on vulnerable groups, Chris explains why 'clean air is a human right, not a luxury.'

Key takeaways from Dr Argyropoulos:

The Power of Prediction: Using Computational Fluid Dynamics (CFD) and multizone models, we can predict airflow patterns and how contaminants disperse inside buildings.
Targeted Mitigation: These models aren't just for show—they help us evaluate HVAC systems and ventilation strategies to find the most effective ways to reduce indoor pollution.
Local Challenges: Current global models often lack data from high-particulate areas like Saudi Arabia. Chris emphasizes the need to validate models using local sensor data and tracer gas experiments to account for heavy dust events.
The Future is AI: By combining massive datasets with Machine Learning (AI), we can move toward faster, more efficient simulations to find real-world solutions for healthier indoor environments.
Collaboration is Key. Dr Argyropoulos calls for a global effort to share data, improve modeling, and ensure that every person on the planet has access to clean air.

GO AQS held its 1st General Assembly Webinar across two sessions on December 11, 2025

Key takeaways from Dr Argyropoulos:

The Power of Prediction: Using Computational Fluid Dynamics (CFD) and multizone models, we can predict airflow patterns and how contaminants disperse inside buildings.
Targeted Mitigation: These models aren't just for show—they help us evaluate HVAC systems and ventilation strategies to find the most effective ways to reduce indoor pollution.
Local Challenges: Current global models often lack data from high-particulate areas like Saudi Arabia. Chris emphasizes the need to validate models using local sensor data and tracer gas experiments to account for heavy dust events.
The Future is AI: By combining massive datasets with Machine Learning (AI), we can move toward faster, more efficient simulations to find real-world solutions for healthier indoor environments.
Collaboration is Key. Dr Argyropoulos calls for a global effort to share data, improve modeling, and ensure that every person on the planet has access to clean air.