Radon and climatic multiparameter analysis: an effective tool for optimization and verification of radon-reduction techniques

Radon-reduction in private and public buildings is a current issue. Research has opened our eyes for the enormous fluctuation of the indoor radon level over longer observation periods. Normally, the time sequence of the radon concentration can be characterized as a mixture of (periodic) circadian variations overlayed with (aperiodic) seasonal fluctuations. Other factors may be attributed to the activities of the inhabitants. Today, different expert groups are proposing mathematical models to describe the radon level in a building. Due to the great number of entry parameters in these equations, analytical approaches have not yet been used widely. This study has two objectives: To demonstrate, how convenient a multiparameter study can be implemented in a house by using a computer-oriented system, To extract a mathematical model out of the experimental data. Thus a better understanding of the factors that dominate the radon entry is gained. As far as we know, the dominating entry-mechanisms are diffusion and convection. Therefore, it is necessary to perform long-term multiparameter studies on radon, together with those climatic parameters that might have influence on diffusion barriers or on convective transport mechanisms. A long-term observation was started, precisely logging up the radon level in a single family home. Six portable multiparameter monitors equipped with a PIC-detector (= pulse ionization chamber), have been installed at different locations within the building and outdoors (incl. soil gas probe). The monitor is equipped with a DSP-MCA (DSP = digital signal processing), covering a range from 2 to 2 000 000 Bq/m. Besides the radon concentration, in the same instruments the following
parameters are logged continuously: in- and outdoor air~, soil~, temperature of central water heating, atmospheric and differential pressure between basement and sub-slab area, relative humidity and wind speed on the roof. Correlations between radon and different climatic parameters are pointed out by using classical regression methods as well as graphical charts. Details on the quality assurance program of the study are given: linearity check for the PIC-detector, analysis of its transient response funtion, parallel tracking of all six instruments and a procedure for a NISTtraceable radon calibration on-site. Results from RMP qualification at EPA/Las Vegas will be
included.