Atmospheric pollution and green house effects are now one of the major preoccupations to improve the general quality of life. With an electronic nose application we propose a system dedicated to the main detection of refrigerant Forane 134a (R134a) gas leakage in air conditioned systems and atmospheres. For our application based on a metal oxide type gas sensor array (six TGS elements) mainly coupled with discriminant factorial analysis (DFA) for the pattern recognition, we propose to study the effect of the relative humidity and an antagonist gas carbon dioxide as interfering gases on the R134a gas and concentration discrimination. We show that the relative humidity in a wide range (18-85%) has a more important influence on the target gas and concentrations discrimination than carbon dioxide. We present the discrimination results for the gases and afterwards for the R134a concentrations. Then we show the ability of our system to identify correctly a test data set composed of unknown gas samples. For the gases concentrations identification we also show that a correct identification rate can be obtained specially when the relative humidity rate range is reduced.