Une première mesure lidar combinée d'ozone et de vent, à partir d'une instrumentation et d'une méthodologie coup par coup
During these last decades, air pollution has drawn the attention of scientists because of the deterioration of the human environment that it has caused. Unfortunately, the study of this dynamic phenomenon is very complex and requires the use of models that compute the evolution of the physico-chemical parameters of the atmosphere. Moreover, the predictions of the numerical simulations have to be validated by range- and time-resolved measurements, carried out continuously up to the top of the planetary boundary layer. Only the optical radar or lidar satisfies these specifications: for this reason the Laboratory for Air and Soil Pollution (LPAS) of the Swiss Federal Institute of Technology (EPFL) has developed such a system in order to provide the modellers with information complementary to that given by the ground measurements. This instrument, after mounting on a mobile platform, has determined the concentration of the key molecule ozone during several field campaigns, demonstrating its reliability and precision. Moreover, the EPFL system is a shot per shot lidar, able to record each detected signal and not only its average in a time interval. This feature is innovative to lidar determinations of tropospheric ozone and allows one to measure accurately the statistical error, to correct for the effect of systematic biases and to observe the dynamic behaviour of the atmosphere: the measurement of the statistical error has been used to build a model of the signal and of its noise, useful in the design of future lidar systems and for the comparison of the various data processing algorithms. the correction of the bias caused by the artificial deformation of the statistical distribution of the signal at long distance has led to a considerable increase of the range of the retrieved ozone profiles, the observation of the dynamic behaviour of the atmosphere has resulted in the first simultaneous measurement of a pollutant concentration and of the wind velocity with the same data set recorded by a lidar.