Preprints
https://doi.org/10.5194/egusphere-2024-1953
https://doi.org/10.5194/egusphere-2024-1953
29 Jul 2024
 | 29 Jul 2024

Partitioning anthropogenic and natural methane emissions in Finland during 2000–2021 by combining bottom-up and top-down estimates

Maria K. Tenkanen, Aki Tsuruta, Hugo Denier van der Gon, Lena Höglund-Isaksson, Antti Leppänen, Tiina Markkanen, Ana Maria Roxana Petrescu, Maarit Raivonen, and Tuula Aalto

Abstract. Accurate national methane (CH4) emission estimates are essential for tracking progress towards climate goals. This study investigated Finnish CH4 emissions from 2000–2021 using bottom-up and top-down approaches. We evaluated a global atmospheric inversion model’s ability to estimate CH4 emissions within a single country, focusing on how the choice of priors and uncertainties affected optimised emissions. The optimised anthropogenic and natural CH4 emissions strongly depended on the prior emissions. While the range of CH4 estimates was large, the optimised emissions were more constrained than the bottom-up estimates. Further analysis of CarbonTracker Europe - CH4 results showed that optimisation aligned the trends of anthropogenic and natural CH4 emission and improved modelled seasonal cycles of natural emissions. Comparison of atmospheric CH4 observations with model results showed no clear preference between anthropogenic inventories (EDGAR v6 and CAMS-REG), but results using the largest natural prior (JSBACH-HIMMELI) best agreed with observations, suggesting that process-based models may underestimate CH4 emissions from Finnish peatlands or unaccounted sources such as freshwater emissions. Additionally, using a process-model spread-based uncertainty estimate for natural CH4 emissions seemed advantageous compared to the standard constant estimate. The average total posterior emission of the ensemble from one inversion model with different priors was similar to the average of the ensemble including different inversion models but similar priors. Thus, a range of priors can be used to reliably estimate CH4 emissions when an ensemble of different models is unavailable.

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Maria K. Tenkanen, Aki Tsuruta, Hugo Denier van der Gon, Lena Höglund-Isaksson, Antti Leppänen, Tiina Markkanen, Ana Maria Roxana Petrescu, Maarit Raivonen, and Tuula Aalto

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1953', Anonymous Referee #1, 05 Aug 2024
    • AC1: 'Reply on RC1', Maria Tenkanen, 05 Dec 2024
  • RC2: 'Comment on egusphere-2024-1953', Anonymous Referee #2, 02 Sep 2024
    • AC2: 'Reply on RC2', Maria Tenkanen, 05 Dec 2024
Maria K. Tenkanen, Aki Tsuruta, Hugo Denier van der Gon, Lena Höglund-Isaksson, Antti Leppänen, Tiina Markkanen, Ana Maria Roxana Petrescu, Maarit Raivonen, and Tuula Aalto
Maria K. Tenkanen, Aki Tsuruta, Hugo Denier van der Gon, Lena Höglund-Isaksson, Antti Leppänen, Tiina Markkanen, Ana Maria Roxana Petrescu, Maarit Raivonen, and Tuula Aalto

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Short summary

Accurate national methane (CH4) emission estimates are essential for tracking progress towards climate goals. This study compares estimates from Finland, which use different methods and scales, and shows how well a global model estimates emissions within a country. The bottom-up estimates vary a lot but constraining them with atmospheric CH4 measurements brought the estimates closer together. We also highlight the importance of quantifying natural emissions alongside anthropogenic emissions.