Methane Release Rate Estimation using Model-based Gas Tomography

Gas leaks in industry and nature can cause harmful effects on the environment and human health. Knowing how much gas is emitted over time helps to assess potential damage, track pollution sources, and develop effective mitigation strategies. To address this challenge, we propose to estimate the source's release rate based on measured gas concentrations in a cross-section of the gas plume in the down-wind regions of the source. By combining wind information and the 2D gas distribution in the cross-section plane, we can infer the flow of gas through this plane, which is equal to the release rate of the source. We propose a Tunable Diode Laser Absorption Spectroscopy sensor (TDLAS) for remote, open-path gas sensing. By combining multiple TDLAS measurements with a gas tomography reconstruction algorithm, we obtain a 2D map of gas distribution. This letter introduces an improved novel approach for gas tomography by incorporating prior model assumptions into the algorithm. Our method significantly enhances the accuracy and robustness of release rate estimates. We validate our approach through wind tunnel experiments, demonstrating that our novel estimation method produces precise and reliable release rate estimations for methane gas. The results further encourage exploring how 3D gas tomography can improve our release rate estimations in the future.