Search

An active device for radon detection in air has been developed in the frame of a project carried out by the Physics Department of the University of Torino with the aim to create a monitoring network of radon concentration in the University workplaces. The device uses a commercial planar photodiode, sensitive to alpha particles, and a dedicated electronic chain integrated in an approx. 30 mm by 50 mm printed circuit board (PCB), designed in order to minimize the power consumption. The device can be used not only as alpha particles counter (using the digital output) but also for alpha spectroscopy, connecting the analog signal output from the shaper amplifier to a Multichannel Analyzer (MCA). In this paper, the first prototype of the detector will be presented with the preliminary experimental results. The spectroscopic performances of the device were tested, integrating the sensor in a commercial aluminum box and acquiring the alpha particle spectrum from a calibration source and from rock samples used as radon sources. The radon sensitivity of the detector, in terms of (Counts per hour)/(Bq m−3), was assessed by the comparison with a calibrated commercial radon detector (RAD7 Durridge Inc.). In conclusion, the final prototype will be presented. It is characterized by a new 3d printed plastic case in black PA12 for light shielding, covered by a conductive paint in order to minimize the electromagnetic noise.

This work aims to implement a forecast model that, combined with the use of active instrumentation for a rather limited time, and with the knowledge of a set of data referring to the environmental parameters of the place to be monitored, can estimate the concentration of indoor radon activity for longer time periods. This model has been built through the MATLAB program, exploiting the theories of time series and, in particular, ARMAX models, to reproduce the variation in the concentration of radon activity. The model validation has been carried out by comparing real vs. simulated values. In addition, analytic treatment of input data, such as temperature, pressure, and relative humidity, can reduce the influence of sudden transients allowing for better stability of the model. The final goal is to estimate the annual radon activity concentration on the basis of spot measurements carried out by active instrumentation, such to avoid the need to measure for an entire calendar year by the use of passive detectors. The first experimental results obtained in conjunction with active radon measurement demonstrates the applicability of the method not only for forecasting future average concentrations, but also for optimizing remedial actions.