Partitioning Eddy-Covariance Methane Fluxes from a Shallow Lake into Diffusive and Ebullitive Fluxes

Methane (CH4) is known to be emitted from lakes to the atmosphere via processes such as diffusion and ebullition (i. e., bubble emission). We developed a practical method for partitioning eddy-covariance CH4 fluxes from a shallow lake into diffusive and ebullitive fluxes using awavelet analysis based on local scalar similarity between theCH(4) concentration and other reference scalars, such as the air temperature or water vapour concentration, in the wavelet time-scale domain, with the hypothesis that similar and dissimilar fluctuation components are related to diffusive and ebullitive CH4 fluxes, respectively. Our method is applied to approximately two weeks of data obtained at a shallow mid-latitude lake. The partitioned diffusive flux has a physically sound relationship with wind speed, supporting the validity of the method. The ratio of the diffusive flux to the total flux is typically 0.11 with flow from an area of steady bubble emission, but otherwise 0.36. Further validation is required using a larger dataset and data from other lakes. The proposed method can be easily applied to historical data because it requires only 10-Hz data of CH4 concentration and other reference scalars, along with an empirical parameter.