Apportioning radon contamination sources in underground spaces using a grey-box model

Area of Science:

• Environmental Science
• Indoor Air Quality
• Radiological Health

Background:

• Indoor radon poses a significant carcinogenic risk, originating from gaseous advection and aqueous degassing.
• Current methods for source apportionment are limited by discrepancies between theoretical models and empirical data.
• Effective management requires accurate identification and quantification of indoor radon sources.

Purpose of the Study:

• To propose and validate a novel grey-box modeling approach for apportioning indoor radon sources.
• To integrate physical principles with data-driven insights for enhanced radon management.
• To assess the primary sources contributing to high indoor radon concentrations.

Main Methods:

• Development of a grey-box model combining signal processing and physical-based modeling.
• Monitoring of indoor air conditioning systems to collect relevant data.
• Optimization of the grey-box model for accurate prediction of indoor radon levels.

Main Results:

• The average indoor radon concentration measured was 1104 Bq/m³, significantly exceeding the EPA action level of 148 Bq/m³.
• The developed grey-box model demonstrated strong predictive performance for indoor radon concentrations.
• Degassing of aqueous radon was identified as the predominant source of indoor radon contamination.

Conclusions:

• Grey-box modeling provides a robust framework for apportioning indoor radon sources and understanding transport mechanisms.
• This approach offers a promising solution for bridging data gaps in site investigations and conceptual models.
• Accurate source apportionment facilitates the development of optimized radon mitigation strategies.