Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/287099 
Year of Publication: 
2021
Citation: 
[Journal:] Mitigation and Adaptation Strategies for Global Change [ISSN:] 1573-1596 [Volume:] 26 [Issue:] 6 [Publisher:] Springer Netherlands [Place:] Dordrecht [Year:] 2021
Publisher: 
Springer Netherlands, Dordrecht
Abstract: 
Germany, as an Annex I Party is expected to prepare and submit annual Greenhouse Gas (GHG) Inventories of emissions and removals, including Land Use, Land-Use Change, and Forestry (LULUCF) sector. Uganda, a non-Annex 1 party, is institutionalizing a sustainable national GHG inventory system. The LULUCF sector is a key emission source and plays a vital role in these two countries' GHG inventories. This research analyzes the differences between applied LULUCF methodologies in Uganda as a developing country and Germany as a developed country with a particular focus on the forestry sector. It further analyzes the root cause factors for the different approaches, existing gaps and gives recommendations for future inventory improvement. The intricate institutional, policy framework, expertise, and applied methodological approaches for carbon change estimations in biomass pools are analyzed. Uncertainty analysis and time-series consistency process is reviewed with regard to how the countries' quality assurance/control (QA/QC) and verification approaches adhere to the transparency framework. Resource limitations and data collection challenges dictate that Uganda uses the tier 1 methodological approach for emissions inventory. Consolidation and institutionalization of the GHG process will improve inventory accuracy while enhancing adherence to climate commitments. Germany uses higher tiers. Besides, government support for planned improvements using the recently developed country-specific biomass functions for estimating belowground biomass of silver birch, oak, and Scotch pine tree species will be essential for improving inventory quality. Operationalization of the inventory plan (IP) will be critical in driving inventory improvements geared towards time-series consistency, comparability, and transparency.
Subjects: 
Biomass stock
Emission factor
Uncertainty analysis
Allometric equations
National Forest Inventory
Stock-difference method
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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