Methane emissions at high northern latitudes estimated by an atmospheric inversion model - Tenkanen, Maria (Helsingin yliopisto, 2025)
Methane (CH4), which is emitted both from anthropogenic and biospheric sources, is a potent greenhouse gas responsible for approximately 20% of anthropogenic global warming. In this thesis, we investigated CH4 emissions estimated by the global atmospheric inverse model CarbonTracker Europe - CH4 (CTE-CH4), focusing on the northern high latitudes, in particular Fennoscandia and Finland. We analysed both anthropogenic and biospheric emissions and their seasonal, interannual and long-term variations from 2000 to 2021. At high northern latitudes, we calculated seasonal CH4 emissions in thaw, freezing and frozen periods, which were defined by remotely sensed freeze/thaw soil state. Depending on the permafrost zone studied, CH4 emissions were 88-95% of annual emissions during thaw, 1-5% during freezing and 4-7% during frozen periods. Analysis based on the Boreal-Arctic Wetland and Lake Dataset showed that fens had the highest CH4 flux during the thaw period, while bogs had greater CH4 flux during the freezing and frozen periods. Using the Corine land cover to detect CH4 emissions related to land use, land use change and forestry (LULUCF) in Finland, most of the CH4 emissions were attributed to open peatlands and forests with thin tree cover. We were also able to identify which process-based ecosystem models were more temperature- or precipitation-driven in Fennoscandia, and showed that biospheric emissions from CTE-CH4 were co-dependent on temperature and precipitation. The way CTE-CH4 partitioned anthropogenic and biospheric CH4 emissions was strongly dependent on the prior emissions used as the initial estimates, especially in smaller regions such as Finland and Fennoscandia. However, the emissions from CTE-CH4 were more robust than the prior emissions in terms of absolute magnitude, seasonal cycle and long-term trend. Furthermore, the average total emissions of the CTE-CH4 ensemble using different priors were close to the average of the inverse model ensemble from a model intercomparison project. This suggests that ...