Predictability of Lead-210 in Surface Air Based on Multivariate Analysis

Dependence of the lead-210 activity concentration in surface air on meteorological variables and teleconnection indices is investigated using multivariate analysis, which gives the Boosted Decision Trees method as the most suitable for variable analysis. A mapped functional behaviour of the lead-210 activity concentration is further obtained, and used to test predictability of lead-210 in surface air. The results show an agreement between the predicted and measured values. The temporal evolution of the measured activities is satisfactorily matched by the prediction. The largest qualitative differences are obtained for winter months.3rd International Conference on Radiation and Applications in Various Fields of Research (RAD), Jun 08-12, 2015, Budva, Montenegr

Predictability of Lead-210 in Surface Air Based on Multivariate Analysis

Dependence of the lead-210 activity concentration in surface air on meteorological variables and teleconnection indices is investigated using multivariate analysis, which gives the Boosted Decision Trees method as the most suitable for variable analysis. A mapped functional behaviour of the lead-210 activity concentration is further obtained, and used to test predictability of lead-210 in surface air. The results show an agreement between the predicted and measured values. The temporal evolution of the measured activities is satisfactorily matched by the prediction. The largest qualitative differences are obtained for winter months.3rd International Conference on Radiation and Applications in Various Fields of Research (RAD), Jun 08-12, 2015, Budva, Montenegr

Novel approach to analysing large data sets of personal sun exposure measurements

Personal sun exposure measurements provide important information to guide the development of sun awareness and disease prevention campaigns. We assess the scaling properties of personal ultraviolet radiation (pUVR) sun exposure measurements using the wavelet transform (WT) spectral analysis to process long-range, high-frequency personal recordings collected by electronic UVR dosimeters designed to measure erythemal UVR exposure. We analysed the sun exposure recordings of school children, farmers, marathon runners and outdoor workers in South Africa, and construction workers and work site supervisors in New Zealand. We found scaling behaviour in all the analysed pUVR data sets. We found that the observed scaling changes from uncorrelated to long-range correlated with increasing duration of sun exposure. Peaks in the WT spectra that we found suggest the existence of characteristic times in sun exposure behaviour that were to some extent universal across our data set. Our study also showed that WT measures enable group classification, as well as distinction between individual UVR exposures, otherwise unattainable by conventional statistical methods