A novel method for characterising the inter- and intra-lake variability of CH4 emissions: validation and application across a latitudinal transect in the Alpine region

bioRxiv, January 2023

Enrico Tomelleri, Katharina Scholz, Sylvie Pighini, Federico Carotenuto, Beniamino Gioli, Franco Miglietta, Ruben Sommaruga, Giustino Tonon, Alessandro Zaldei, Georg Wohlfahrt

Lakes in the Alpine region are recognised as critical CH4 emitters, but a robust characterisation of the magnitude and variability of CH4 fluxes is still needed. We developed a mobile platform for CH4 eddy covariance (EC) flux measurements to tackle this gap. Our approach was shown to be well suited to catch all CH4 emission pathways and overcome the limitations of other methods (e.g., gradient-based). This is by surpassing their local nature and thus being suited for characterising the variability of the within-lake emissions, primarily because of CH4 emissions by ebullition stochasticity. The mobile system was deployed at nine lakes across a latitudinal transect in the Alps and validated by comparing the measured fluxes with a fixed EC station and to chambers and boundary layer estimates. Methane fluxes were explained by water turbidity, dissolved organic carbon, dissolved nitrogen, elevation, particulate organic carbon, and total phosphorus. The highest fluxes and most substantial seasonal variability were found in a shallow low-altitude lake in the Southern Alps. Additionally, the mobile EC permitted to resolve the spatial structure of fluxes at the selected lakes. Finally, we demonstrated the usability of our novel mobile system to characterise intra- and inter-lake variability of fluxes. We suggest that characterising the intra-lake emission heterogeneity and a deeper understanding of inter-lake emission magnitude differences is fundamental for a solid estimate of freshwater CH4 budgets. Key PointsO_LICH4 emissions from alpine lakes are recognised to be an important component to the global methane budget but they are poorly characterized C_LIO_LIWe developed and validated a mobile eddy covariance platform for capturing CH4 fluxes across lakes in the alpine region for two years C_LIO_LIA robust statistical model based on a few in-situ physicochemical and biological parameters can be generally used to predict CH4 fluxes C_LI