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Radon is the second leading cause of lung cancer after smoking. While radon exposure is assessed by the annual average radon concentration, the radon entry rate, which is fundamental to understanding radon behavior and mitigation, has received less attention due to measurement challenges. Technological advancements over the past decade have led to the development of affordable and widely available consumer-grade electronic detectors that can provide time-resolved radon measurements. A novel method for estimating the radon entry rate from radon time series measured by fast-response, consumer-grade electronic monitors is presented. It was validated through experiments conducted in a primary metrology laboratory and test-bed studies. It was implemented in a three-year radon monitoring campaign in 36 occupied dwellings and workplaces located in both radon-priority and non-priority areas. During the campaign data on the dynamics of radon entry rate and air change rate was gathered remotely without interrupting the buildings usage cycle. A correlation between the radon entry rate and the air change rate at low ventilation was observed in about 80 % of the buildings, which demonstrates that the radon entry rate can be studied with relation to other dynamic parameters. This new approach can be used by scientists developing models for radon transport in buildings, as well as by remediation and mitigation professionals to provide smart and energy-efficient mitigation strategies. The method proposed herein provides insights into radon dynamics and can revolutionize our efforts to maintain healthy indoor environment with respect to radon. • Radon entry rate in buildings can be measured by affordable electronic monitors. • Radon time series allow parallel estimates of radon entry and air exchange rates. • The novel approach was verified in primary metrology lab and radon test beds. • Radon entry rate was followed remotely in 36 occupied homes and workplaces. • New dynamic data on radon entry rate can empower smart indoor environment control.
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Mitev et al. (2025) studied this question.
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