Impact of modelling choices on setting the reference levels for the EU forest carbon sinks: how do different assumptions affect the country-specific forest reference levels?

Abstract

Background: In 2018, the European Union (EU) adopted Regulation 2018/841, which sets the accounting rules for the land use, land use change and forestry (LULUCF) sector for the period 2021-2030. This regulation is part of the EU's commitments to comply with the Paris Agreement. According to the new regulation, emissions and removals for managed forest land are to be accounted against a projected forest reference level (FRL) that is estimated by each EU Member State based on the continuation of forest management practices of the reference period 2000-2009. The aim of this study is to assess how different modelling assumptions possible under the regulation may influence the FRL estimates. Applying the interlinked G4M and WoodCarbonMonitor modelling frameworks, we estimate potential FRLs for each individual EU Member State following a set of conceptual scenarios, each reflecting different modelling assumptions that are consistent with the regulation and the technical guidance document published by the European Commission. Results:The simulations of the conceptual scenarios show that differences in the underlying modelling assumptions may have a large impact on the projected FRL. Depending on the assumptions taken, the projected annual carbon sink on managed forest land in the EU varies from −319 MtCO 2 to −397 MtCO 2 during the first compliance period (2021-2025) and from −296 MtCO 2 to −376 MtCO 2 during the second compliance period (i.e. 2026-2030). These estimates can be compared with the 2017 national GHG inventories which estimated that the forest carbon sink for managed forest land was −373 MtCO 2 in 2015. On an aggregated EU level, the assumptions related to climate change and the allocation of forest management practices have the largest impacts on the FRL estimates. On the other hand, assumptions concerning the starting year of the projection, stratification of managed forest land, and timing of individual management activities are found to have relatively small impacts on the FRL estimates. Conclusions:We provide a first assessment of the level of uncertainty associated with the different assumptions discussed in the technical guidance document and the LULUCF regulation, and the impact of these assumptions on the country-specific FRL. The results highlight the importance of transparent documentation by the EU Member States on how their FRL has been calculated, and on the underlying assumptions.

Initial forest age distribution may generate computational sinks or sources of carbon: A generic approach to test assumptions underlying the EU LULUCF forest reference levels

“…Nabuurs et al [ 4 ], upon an analysis of harvesting possibilities based on the EFISCEN model, suggested that the 26 countries together can increase harvests complying the continuation of management practices criteria without creating debits. Forsell et al [ 5 ] examined the role of different computational assumptions, finding technicalities such as the starting year for the projection, stratification criteria for the area of managed forest land, and simulated timing of individual management activities to have less impact compared to assumptions on climate change or allocation of management practices. For their analyses, Forsell et al [ 5 ] coupled forest dynamics and GHG modelling based on the G4M and WoodCarbonMonitor frameworks.…”

“…Forsell et al [ 5 ] examined the role of different computational assumptions, finding technicalities such as the starting year for the projection, stratification criteria for the area of managed forest land, and simulated timing of individual management activities to have less impact compared to assumptions on climate change or allocation of management practices. For their analyses, Forsell et al [ 5 ] coupled forest dynamics and GHG modelling based on the G4M and WoodCarbonMonitor frameworks.…”

“…Then again, Nabuurs et al [ 4 ] noted that when combined with a progressing age class development over time, the continuation of forest management could lead to approaching or exceeding maximum sustained harvest amounts. As an alternative to constant management intensity derived from past data, Nabuurs et al [ 4 ] analyzed harvests cut off based on a removal/increment ratio that might not comply with regulation [ 5 ].…”

“…Second, challenges may be related to understanding these definitions and projecting forest resources, harvests, and FRLs accordingly. The EU member states differ in terms of forest characteristics, forestry practices, quality of forest inventory data, and modeling experience [ 5 ] that results to applying various methods and reduced comparability of the FRL proposals [ 2 ]. According to text above, many different projection models were used for studying the fundamentals of the FRL principles, even though such assessments would benefit from harmonized definitions and standardized modeling (cf., [ 8 ]).…”

Spatiotemporal Evolution and Features of Net Carbon Sink of Farmland Vegetation in Chongqing, China

“…Foreign scholars have paid more attention to carbon pools of forest [10][11][12] than carbon sources/sinks in agricultural or farmland system. But the latter is arousing a growing interest in the academic circle.…”