Remote sensing of trace gases with optical correlation spectroscopy and lidar: theoretical and numerical approach

Abstract

In this paper, we propose a new active remote sensing methodology, based on laser spectroscopy, to evaluate the content of atmospheric trace gases. Its principle consists in coupling a lidar with optical correlation spectroscopy (OCS-lidar). Our theoretical and numerical studies show that OCS-lidar is a robust measurement methodology allowing trace gases environmental, agricultural, and industrial plants surveys. The novelty of this work is threefold. Firstly, we develop a new formalism to remotely evaluate the target gas concentration from optical correlation spectroscopy. Secondly, an acousto-optical programmable dispersive filter has been used to ensure that the lidar signal be spectrally correlated with the target gas of interest. It avoids using a hazardous gas reference cell, as operated in conventional OCS devices. Moreover, a clever spectral correlation is achieved since the contribution of absorption interfering species can then be minimized. Thirdly, to evaluate the performance of the OCS-lidar methodology, a numerical study of methane greenhouse gas is presented to evidence that atmospheric methane mixing ratios are retrievable over two orders of magnitude, from background level up to 100 ppb, within 100-m range resolution. Evaluation of the accuracy and the detection limit, including statistical and systematic errors assessment, are then objectively presented and discussed.