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BACKGROUND: In June 2018, the European Parliament and Council of the European Union adopted a legislative regulation for incorporating greenhouse gas emissions and removals from Land Use, Land Use Change and Forestry (EU-LULUCF) under its 2030 Climate and Energy Framework. The LULUCF regulation aim to incentivise EU Member States to decrease greenhouse gas emissions and increase removals in the LULUCF sector. The regulation, however, does not set a target for increasing the LULUCF carbon sink, but rather includes a 'no net debit' target for LULUCF (Forests and Agricultural soils). For Managed Forest Land (MFL) an accounting framework with capped credits for additional mitigation against a set forest reference level (FRL) was agreed for 2021–2030. The FRL gives the projected future carbon sink in the two compliance periods 2021–2025 and 2026–2030 under "continuation of forest management practices as they were in the reference period 2000–2009". This FRL was disputed by some Member States as it was perceived to put a limit on their future wood harvesting from MFL. Here we simulated with the EFISCEN European forest model the "continuation of forest management practices" and determined the corresponding wood harvest for 26 EU countries under progressing age classes. RESULTS: The simulations showed that under "continuation of forest management practices" the harvest (wood removals) in the 26 EU countries as a whole can increase from 420 million m3/year in 2000–2009 to 560 million m3/year in 2050 due to progressing age classes. This implies there is a possibility to increase absolute wood harvests without creating debits compared to the forest reference level. However, the manner in which 'continuation of forest management' developed with a progressing age class development over time, meant that in some countries the future harvesting exceeded 90% of the increment. Since this generally is considered to be unsustainable we additionally set a harvesting cut-off as max 90% of increment to be harvested for each individual country as a possible interpretation of sustainability criteria that are included in the regulation. Using this additional limit the projected harvest will only increase to 493 million m3/year. CONCLUSIONS: The worry from Member States (MS) that the FRL will prevent any additional harvesting seems unwarranted. Due to differences between Member States concerning the state of their forest resources, the FRL as a baseline for harvesting works out very differently for the different Member States. The FRL may have other unforeseen consequences which we discuss. Under all scenarios the living forest biomass sink shows a decline. This can be counteracted through incentivising measures under Climate Smart Forestry.

In July 2016, the European Commission (EC) published a legislative proposal for incorporating greenhouse gas emissions and removals due to Land Use, Land Use Change and Forestry (LULUCF) into its 2030 Climate and Energy Framework. The Climate and Energy Framework aims at a total emission reduction of 40% by 2030 for all sectors together as part of the Paris Agreement. The LULUCF proposal regulates a "no debit" target for LULUCF (Forests and Agricultural soils), and regulates the accounting of any additional mitigation potential that might be expected of it. We find that the forest share of the LULUCF sector can achieve much more than what is in the regulation now. We elaborate a strategy for unlocking European Union (EU) forests and forest sector potential based on the concept of "climate smart forestry" (CSF). We find that to-date, European policy has not firmly integrated forest potential into the EU climate policy framework. Nor have climate objectives been firmly integrated into those of the forest and forest sector at either the EU or national level. Yet a wide range of measures can be applied to provide positive incentives for more firmly integrating these climate objectives into the forest and forest sector framework. With the right set of incentives in place at EU and Member States levels, we find the current literature supports the view that the EU has the potential to achieve an additional combined mitigation impact through CSF of 441 Mt CO2/year by 2050. In addition, CSF, through reducing and/or removing greenhouse gas emissions, adapting and building forest resilience, and sustainably increasing forest productivity and incomes, tackles multiple policy goals.

Abstract Background The 27 countries in the European Union have a combined total of 177 million ha of forested and other wooded land. These are mainly characterised as semi-natural, multi-functional forests. Only about 13 million ha are characterised as plantations i , although an additional 47 million ha are regarded as planted forests (Forest Europe 2011) . European forests are highly diverse due to centuries of management in countries with different cultural objectives. Often the current management is nature oriented and so forests may not be used primarily for wood production. Wood provides only a small part of the income for many of the 16 million private owners according to the Confédération Européenne des Propriétaires Forestiers (CEPF 2013) . These circumstances, plus sluggish demand for wood brought about by the current economic crisis, have generated challenges for the forestry sector. Demand for wood is expected to increase with expansion of the green economy and an increased emphasis on the use of bioenergy. Methods Three forest management scenarios (analysed with the EFISCEN model) were used to project supply in response to demand for wood from EU forests over the next 50 years. Results Shortening of broadleaved forest rotation length and planting 50% of the felled area with fast-growing coniferous species could increase coniferous wood supply from 473 to 561 million m 3 y -1 . Demand could reach more than 1200 million m 3 y -1 by 2065. Conclusions Conversion of 50% of broadleaved forest in EU27 countries to coniferous forest is not likely to satisfy the increased demand for wood expected by 2065.

Under the United Nations Framework Convention for Climate Change all Parties have to report on carbon emissions and removals from the forestry sector. Each Party can use its own approach and country specific data for this. Independently, large-scale models exist (e.g. EFISCEN and G4M as used in this study) that assess emissions and removals from this sector by applying a unified approach to each country, still often based on country specific data. Differences exist between the national reported values and the calculations from the large scale models. This study compares these models with national reporting efforts for 24 EU countries for the period 2000–2008, and identifies the most likely causes for differences. There are no directly identifiable single input parameters that could be targeted to fully close the gap between country and model estimates. We found that the method applied by the country (i.e. stock-difference or gain-loss) contributes significantly to differences for EFISCEN and was the best explaining variable for G4M, although for the latter it was not significant. Other variables (biomass expansion factors, harvest volumes and the way harvest losses are treated) were not found to provide a conclusive explanation for the differences between the model estimations and the country submissions in an over-all.

This report demonstrates the application of recreational scores, obtained through a pan-European Delphi survey as part of EFORWOOD, to model the impacts of changes in forest management on the recreational value of European forests. Changes in the level of implementation of the Natura 2000 policy is used as an example. Currently, about 8% of the EU forest area is allocated to biodiversity conservation (MCPFE class 1; MCPFE 2007). According to the Natura 2000 Agenda, 15% of the territory of the EU should be designated as conservation area by 2025. It is to be expected, therefore, that the forest conservation area will increase considerably in the near future. The impact of different nature conservation implementation levels on the recreational value of forests in Europe was explored using recreational scores derived from the Delphi survey, and combined with outputs from the forest scenario model EFISCEN. Changes in recreational value were considered against two background futures (A1 and B2 from the SRES scenarios) and three different nature conservation implementation levels. The results suggest that overall an increase in forest area managed for conservation would cause a slight net increase the recreational value per hectare of forests in Europe, although there is considerable variation between countries.

This report demonstrates the application of recreational scores, obtained through a pan-European Delphi survey as part of EFORWOOD, to model the impacts of changes in forest management on the recreational value of European forests. Changes in the level of implementation of the Natura 2000 policy is used as an example. Currently, about 8% of the EU forest area is allocated to biodiversity conservation (MCPFE class 1; MCPFE 2007). According to the Natura 2000 Agenda, 15% of the territory of the EU should be designated as conservation area by 2025. It is to be expected, therefore, that the forest conservation area will increase considerably in the near future. The impact of different nature conservation implementation levels on the recreational value of forests in Europe was explored using recreational scores derived from the Delphi survey, and combined with outputs from the forest scenario model EFISCEN. Changes in recreational value were considered against two background futures (A1 and B2 from the SRES scenarios) and three different nature conservation implementation levels. The results suggest that overall an increase in forest area managed for conservation would cause a slight net increase the recreational value per hectare of forests in Europe, although there is considerable variation between countries.

Live woody vegetation is the largest reservoir of biomass carbon, with its restoration considered one of the most effective natural climate solutions. However, terrestrial carbon fluxes remain the largest uncertainty in the global carbon cycle. Here, we develop spatially explicit estimates of carbon stock changes of live woody biomass from 2000 to 2019 using measurements from ground, air, and space. We show that live biomass has removed 4.9 to 5.5 PgC year −1 from the atmosphere, offsetting 4.6 ± 0.1 PgC year −1 of gross emissions from disturbances and adding substantially (0.23 to 0.88 PgC year −1 ) to the global carbon stocks. Gross emissions and removals in the tropics were four times larger than temperate and boreal ecosystems combined. Although live biomass is responsible for more than 80% of gross terrestrial fluxes, soil, dead organic matter, and lateral transport may play important roles in terrestrial carbon sink ; This study was funded by NASA Interdisciplinary Science Program (NNH16ZDA001N-IDS). M.L. and Y. Yang have been supported by the NASA Postdoctoral Program, administered by Universities Space Research Association under contract with NASA.G.-J.N. was supported by the European Union H2020-VERIFY project (776810).

Abstract Low‐cost sustainable biomass availability in the European Union may not be able to meet increasing demand; exploring the option of importing biomass is therefore imperative for the years to come. This article assesses sustainable biomass export potential from Brazil, Colombia, Indonesia, Kenya, Ukraine, and the United States by applying a number of sustainability criteria. Only biomass types with the highest potential are selected, to take advantage of economies of scale, e.g. pulpwood, wood waste, and residues in the United States, and agricultural residues in Ukraine. This study found that, except for the United States, pellet markets in the sourcing regions are largely undeveloped. The export potential depends strongly on pellet mill capacity and assumed growth rates in the pellet industry. Results show that the United States, Ukraine, Indonesia, and Brazil offer the highest biomass export potential. In the Business As Usual 2030 scenario, up to 204 PJ could potentially be mobilized; in the High Export scenario this could increase to 1423 PJ, with 89% of the potential being available for costs ranging from 6.4 to 15 €/GJ. These potentials meet the European Commission requirements for a 70% reduction in greenhouse gas emissions set in the Renewable Energy Directive. The total export potentials do not reflect the net possible import potentials to the European Union, as biomass could be imported to other countries where there is a demand for it, where less strict sustainability requirements are applied, and which are proximate to the sourcing regions, notably South Korea, Japan, and China. © 2018 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Chemical Industry and John Wiley Sons, Ltd.

International audience ; Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthro-pogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU28 1). The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models and summarize GHG emissions and removals over the period 1990-2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGIs), with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for the EU28 provide consistent quantification of uncertainty following the established IPCC Guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred to here as activity data (AD) and methodologies (tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualized at https://doi.org/10.

International audience ; Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthro-pogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU28 1). The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models and summarize GHG emissions and removals over the period 1990-2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGIs), with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for the EU28 provide consistent quantification of uncertainty following the established IPCC Guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred to here as activity data (AD) and methodologies (tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualized at https://doi.org/10.

International audience ; Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthro-pogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU28 1). The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models and summarize GHG emissions and removals over the period 1990-2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGIs), with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for the EU28 provide consistent quantification of uncertainty following the established IPCC Guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred to here as activity data (AD) and methodologies (tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualized at https://doi.org/10.