Abstract
Substantial evidence indicates that prolonged exposure to radon and its decay products in homes increases the risk of lung cancer. Indoor radon concentrations in some regions of high background radiation areas (HBRAs) of Ramsar are much higher than the recommended action level of 148 Bq/m−3. This study aimed at developing simple mathematical models for prediction of radon concentration in homes located in normal and HBRAs of Ramsar. The levels of gamma background radiation and indoor radon were measured in 75 dwellings located in normal and HBRAs (30 dwellings from HBRAs and 45 dwellings from normal background radiation areas of Ramsar). Our findings showed that in normal and HBRAs of Ramsar the majority of confounding factors such as the type of building materials and ventilation in different dwellings are so close to each other that gamma radiation level can be used as a strong predictive tool for radon concentration. As radon concentration in indoor air strongly varies with time, this simple mathematical method can provide an estimate of the mean radon level in large-scale radon screening programs for homes. We are also developing mathematical models which can predict the levels of tumor markers such as CEA and CYFRA 21 based on gamma background radiation level and indoor radon concentration.
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Mortazavi, S.M.J., Zamani, A., Tavakkoli-Golpayegani, A., Taeb, S. (2016). Development of a Preliminary Mathematical Model to Predict the Indoor Radon Concentration in Normal and High Background Radiation Areas of Ramsar. In: Balas, V., C. Jain, L., Kovačević, B. (eds) Soft Computing Applications. SOFA 2014. Advances in Intelligent Systems and Computing, vol 356. Springer, Cham. https://doi.org/10.1007/978-3-319-18296-4_31
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DOI: https://doi.org/10.1007/978-3-319-18296-4_31
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