Tritium (T) behavior in a breeder blanket is a key design issue because of its impact on safety and fuel-cycle best performance. Considering the difficulty in handling T, the validation of an alternative method is an issue. In an attempt to simulate T residence time (or T diffusion) in a DEMO-like ionizing environment, gas sorption-desorption experiments of deuterium (D) during ionizing radiation in breeder ceramics were carried out to elucidate the involved D2 or T trapping centers. A deconvolution method is here proposed for the identification of the release processes occurring at the different temperatures, therefore providing the basic information for identifying the nature of they-associated defects acting as D or T-trapping centers. The deuterium release in the EU-BB solid candidate material is studied in Li4 Si04 ceramics with variable LizTi03 content (pebble samples fabricated by KIT). The samples, previously dehydrated, are exposed to a deuterium atmosphere inside a pressurized steel capsule (I bar) during 25 days and immersed in the 6°Co Nayade facility located at CIEMAT. Deuterium desorption curves are then registered by means of Thermal Induced Desorption (TID) technique. ... mehrA low temperature process of low activation energy occurs below 300°C suggesting that surface defects are acting as trapping centers for D2. D2 is also trapped in deeper centers being released at temperatures above 600°C. Selected optical measurements (cathodoluminescence, thermoluminescence) were also carried out in irradiated materials, the resultant curves contributing to the explanation of the radiation-induced surface defects involved in D trapping. A deconvolution method for a better interpretation of the obtained enveloping curves was implemented in Matlab© and tested in this set of measurements. It is based on a Levenberg Marquardt iterative fitting routine that minimizes the difference between an experimental TID spectrum and a model spectmm given by the sum of Gaussian bands. The methodology used to solve non-linear least squares problems, allows a complete deconvolution of the overlapping peaks with good precision.