Estimating current CO2 emissions and removals from changes in soil organic carbon stocks

For the purpose of reporting GHG emissions and removals from anthropogenic activities in Agriculture, Forestry and Other Land Use (AFOLU) under the UNFCCC, the Intergovernmental Panel on Climate Change (IPCC) provides in the 2006 IPCC Guidelines that it is good practice to use managed land as a proxy for anthropogenic emissions and removals. For the years 2013-2020 Decision No 529/2013/EU of the European Parliament and of the Council extended mandatory accounting for Greenhouse Gas (GHG) emissions and removals to the activities Cropland Management (CM) and Grazing Land Management (GM) for the Member States of the European Union. The 2006 IPCC Guidelines distinguish three tiers of methods, of which Tier 1 is the most generic. Tier 1 uses general default values and national data for estimating carbon stock changes and non-CO2 GHG emissions. For the purpose of accounting under the Kyoto Protocol land use conversions leading to GHG emissions from the soil should be spatially explicit (Approach 3). A processing environment following the IPCC guidelines for a Tier 1 method and Approach 3 was developed at the JRC to estimate CO2 emissions and removals from changes in soil organic carbon (SOC) stocks as a consequence of changes in land use, management practice and input level. The implementation uses statistical data to establish the annual status and a range of ancillary data to estimate transitions between years. A comparison between the results obtained and the trends related in the annual reports provided by EU Member States led to the conclusion that the data on land use was a major source of differences between the estimated and reported in the trends of CO2 emissions and removals from the soil. These differences will decide the trend of any estimates, regardless of the IPCC Tier used. As a consequence, the procedure implemented to generate a complete time-series of statistical data was investigated and revised. Particular attention was paid to the process of integrating data coming from different sources into a single set. The degree to which data from different sources agree varies from complete agreement to opposing trends. The procedure for generating a more consistent single time-series combines a hierarchical structure for combining data with a statistical analysis for detecting outliers, but not changing any trends. The new input data was employed to re-process changes in soil organic carbon stocks from 1970 to the statistical data available on land use in 2018. Although all EU Member States are processed starting with 1970, the publicly available source data on land use would allow a 1990 baseline for reporting CO2 emissions and removals for 18 countries using national data, but only 8 countries using data at NUTS Level 2. In the sources used 5 countries are reported with detailed data only for 2005 later years.JRC.D.3-Land Resource

Reporting of Biomass Burning under the LULUCF sector. Comparative assessment of data reported under the UNFCCC and EFFIS.

The land use, Land use Change and forestry (LULUCF) sector is one of the six sector included in the Greenhouse Gas (GHG) Inventories that Annex I Parties to the United Nations Framework Convention on Climate Change (UNFCCC) and its Kyoto Protocol (KP) must submit annually. The sector covers anthropogenic emissions of GHGs and their removals by terrestrial carbon pool: living biomass, dead organic matter and soil organic carbon, disaggregated into six main land use categories: Forest land, Cropland, Grassland, Wetlands, Settlements and Other land. Moreover, additional sources of emissions - as those resulting from Biomass burning have also to be reported. The GHG inventories prepared by the Parties should use comparable methodologies provided by the Intergovernmental Panel on Climate Change (IPCC) and the information provided should be Transparent, Accurate, Comparable, Consistency and Complete. In addition, the IPCC Guidelines considers, as integral parts of the GHG inventory process, the implementation of quality control / quality assurance (QA/QC) and verification procedures that are intended to establish the reliability of the information contained in the inventory. This reports contains a comparative assessment of Biomass burning data reported to the UNFCCC by 5 selected Member States with the information contained in the European Forest Fires Information System (EFFIS). The aim is to verify data reported to UNFCCC and to test the utility and feasibility of the use of EFFIS as a tool for the verification of EU MS GHG inventories. Noticeable differences among the data reported in the data sets were found and they would need to be explained. But, in overall, the findings raised in this report suggest that EFFIS data has a good potential as a tool for developing verification procedures of the Biomass burning data and even, it may be used to support the estimates of burned areas in the case that this information is not available at country level.JRC.H.3-Forest Resources and Climat

LULUCF MRV - Analysis and proposals for enhancing Monitoring, Reporting and Verification of greenhouse gases from Land Use, Land Use Change and Forestry in the EU

Land use land use change and forestry sector (LULUCF) is a greenhouse gas inventory (GHG) sector that covers anthropogenic emissions and removals from terrestrial carbon stocks living biomass dead organic matter and soil organic carbon following six main land use categories, Forest land, Cropland, Grassland, Wetlands, Settlements and Other land. According to the United Nation Framework Contract on Climate Change (UNFCCC) all Parties shall report periodically an update inventory of anthropogenic emissions and removals of GHG using comparable methodologies provided by the Intergovernmental Panel on Climate Change (IPCC). Additional requirements exist for reporting and accounting emissions/removals from related direct-human induced activities under the Kyoto Protocol (KP), because its accounting quantities are counted towards an international commitment reduction target. International negotiations have resulted in recent years in the adoption of new rules (e.g. mandatory accounting of Forest management) for the second commitment period of the KP (CP2: 2013-2020). Furthermore, Decision 529/2013/EU, going beyond the international negotiation, added the mandatory accounting of Cropland management and Grassland management. All these changes pose new challenges that MS will need to face from 2015 (i.e. for starting to report during CP2). This report describes the actions undertaken in the context of the Administrative Arrangement “LULUCF MRV” (Monitoring, Reporting, Verification) with DG CLIMA, trough a sequence of tasks (described in detailed in the Annexes). The aim of the AA is to support MS in improving the quality and comparability of LULUCF reporting during CP2, in line with IPCC methods and the new rules at UNFCCC and EU level.JRC.H.3-Forest Resources and Climat

Forest reference levels under Regulation (EU) 2018/841 for the period 2021-2025: Overview and main findings of the technical assessment

Regulation (EU) 2018/841 (‘LULUCF regulation’) sets the accounting rules for the Land Use, Land-Use Change and Forestry (LULUCF) sector in the EU for 2021–2030, i.e. how the emissions and removals of greenhouse gases from LULUCF will be counted towards the climate targets. The LULUCF regulation is part of the EU’s commitment to reduce overall emissions by at least 40% by 2030 under the Climate and Energy framework. Every Member State must balance its accounted greenhouse gas emissions on the LULUCF sector by an equal amount of accounted greenhouse gas removals. Possible surplus removals, under certain conditions and up to an overall total of 280 Mt CO2e, may be used to compensate emissions from the sectors covered by the Effort Sharing Regulation. The technically most complex part of the LULUCF regulation is the set of accounting rules for managed forest land, which are based on a projected Forest Reference Level (FRL), estimated nationally by each EU Member State. The FRL is a benchmark level against which future net emissions from forests are accounted for. In its essence, the FRL is a projection of the net emissions from managed forest land in 2021—2030 (divided into two compliance periods, 2021—2025 and 2026—2030), assuming that the forest management practices had continued similar to the practices in the reference period 2000—2009. This way, the FRL provides a means to account for the impact of policy changes on the emissions and removals from forests, while factoring out the impact of age-related dynamics in the forests. The FRLs for the 2021—2025 period are reported as a part of National Forestry Accounting Plans (NFAPs). After a thorough assessment by the European Commission and a dedicated Expert Group in 2019 and 2020, these FRLs are due to be laid down in a delegated act adopted by the Commission by the end of October 2020. This report outlines the main technical findings of the assessment of the Member States’ proposed FRLs, and complements the forthcoming Commission Staff Working Document (2020) accompanying the delegated act. The assessment found that the Member States had generally followed the principles and criteria laid out in the LULUCF regulation. The NFAPs provide a wealth of information on the forests and forest management practices in the Member States – some of which has not been available for the international community before – and in general include the elements required by the LULUCF regulation. All Member States projected the development of the forest net emissions for 2021—2025 as a continuation of the historical management practices, therefore excluding assumptions on policy development. While the submissions by the Member States were in general detailed and carefully prepared, the assessment identified in several cases minor issues that will need to be amended before the compliance check. The most common issues are related to methodological inconsistencies between carbon pools, greenhouse gases or forest area included in the FRL and those reported in the national greenhouse gas inventories. Some of these mismatches have already been amended by the Member States through Addenda or Corrigenda to the NFAPs. The remaining inconsistencies will be addressed through technical corrections to the FRLs at the end of the compliance period and therefore do not impair the reliability of the FRL as an accounting baseline. For five Member States, the assessment resulted in a recalculation of the Member State-proposed FRL by the Commission. In numerical terms, the sum of the Member States’ FRLs (incl. the United Kingdom) in the delegated act is a projected sink of -337 Mt CO2 y-1 for the period 2021–2025. This projection is about 18% lower than the sink of -413 Mt CO2 y-1 reported by the EU 2019 greenhouse gas inventory on managed forest land for the period 2000—2009 (EEA 2019). The FRL projection is associated with a projected increase of harvest by about 19% over the same period, due to age-related effects. It is noteworthy that the FRLs project sustainable forest management practices as documented in the period 2000–2009, taking into account dynamic age-related forest characteristics, and do not represent an expected sink or expected harvest levels. Instead, the FRLs laid out in the delegated act provide a robust and trustworthy counterfactual for accounting the impact of mitigation actions on emissions and removals from managed forest land in the first compliance period 2021—2025.JRC.D.1-Bio-econom

Options and implications for agricultural production - Report of Task 7: Final Report

CAPRESE has led to a better understanding of the potential of using specific land management practices in preserving and increasing the stock of organic carbon in the agricultural soils of the EU. The scientific literature relating to a range of carbon sequestration measures has been synthesised and evaluated for their potential applicability. Land management has a significant impact on SOC stocks with a number of measures clearly leading to carbon emissions. Conversely, a number of practices can be used to preserve and increase SOC levels. A novel modelling platform suggests that existing assessments of the SOC stock associated with agricultural topsoil in the EU may be over-estimating the current pool by around 24%. The project shows a topsoil SOC pool of 16 Gt., 7.4 and 5.4 Gt respectively between arable and pasture. The model shows that grassland conversion to cropland can have a strong negative impact on the overall C balance in the EU and consequently should be preserved (together with peatlands). Promising management practices for sequestering SOC include cover crops, complex rotation including residue management and reduced tillage. Such measures give C sequestration rates of up to 0.5 t C ha-1 yr-1. However, their effect was strongly dependent on the spatial and temporal extent considered and the scenarios clearly show strong regional differences in the performance of measures. An integrated approach in which measures are combined, could have a significant impact. An implementation scenario of a 12% uptake of mitigation measures gave a cumulated sequestration value of 101 Mt by 2020. Increased areas and variation in implementation patterns could give rise to higher values. Extensive and comparable data on the financial aspects of the implementation and cost-benefit of measures are limited or absent. Substantial effort is required to address these issues. Simplistic scenario analysis shows that on the basis of a conservative implementation of mitigation measures, a SOC stock with a perceived trading value of €500 million could be established by 2020. Such values imply that the implementation of the practices considered would be cost efficient compared to non-agricultural mitigation measures While calculations at farm-scale are difficult, agricultural systems and proportion of land that could be made available to SOC management schemes, there is a perceived positive cost-benefit to C preservation and mitigation measures. Return for grasslands where sequestration and preservation rates are higher would clearly be greater. A cost benefit calculated with the CAPRI (FT) model. Indicated no loss in agricultural income from a 5% conversion to grassland with in turn resulted in a value of the CO2 sequestered in the soil as €20.98 t-1 CO2. Comprehensive data on the impact of the implementation of the measures on production and the market are difficult to define as these macro-scale models do not consider the technical details associated with the specific measures that need to be applied to sequester SOC. However, the studies tend to indicate that that impacts on production could occur but these would be of low magnitude and regionally variable. From an economic perspective, the financial implications of the grassland scenario implemented in CAPRI (FT) model, it can be stated that the CAP premium implications are negligible. This is derived from the fact that as most of the direct payments premiums are now decoupled from production the change in the land use derived from the scenario setting is not affecting the total amount of the direct payments. From a policy perspective, it is important that existing good stewardship of land for maintaining existing SOC stocks should be recognised as a premium in comparison to simply sequestration of OC. Such an approach would be an incentive not to engage in conversion of organic-rich soils to other uses which could lead to a decrease in SOC stocks.JRC.H.5-Land Resources Managemen

Mapping and Assessment of Ecosystems and their Services: An EU ecosystem assessment

This report presents an ecosystem assessment covering the total land area of the EU as well as the EU marine regions. The assessment is carried out by Joint Research Centre, European Environment Agency, DG Environment, and the European Topic Centres on Biological Diversity and on Urban, Land and Soil Systems. This report constitutes a knowledge base which can support the evaluation of the 2020 biodiversity targets. It also provides a data foundation for future assessments and policy developments, in particular with respect to the ecosystem restoration agenda for the next decade (2020-2030). The report presents an analysis of the pressures and condition of terrestrial, freshwater and marine ecosystems using a single, comparable methodology based on European data on trends of pressures and condition relative to the policy baseline 2010. The following main conclusions are drawn: - Pressures on ecosystems exhibit different trends. - Land take, atmospheric emissions of air pollutants and critical loads of nitrogen are decreasing but the absolute values of all these pressures remain too high. - Impacts from climate change on ecosystems are increasing. - Invasive alien species of union concern are observed in all ecosystems, but their impact is particularly high in urban ecosystems and grasslands. - Pressures from overfishing activities and marine pollution are still high. - In the long term, air and freshwater quality is improving. - In forests and agroecosystems, which represent over 80% of the EU territory, there are improvements in structural condition indicators (biomass, deadwood, area under organic farming) relative to the baseline year 2010 but some key bio-indicators such as tree-crown defoliation continue to increase. This indicates that ecosystem condition is not improving. - Species-related indicators show no progress or further declines, particularly in agroecosystems. The analysis of trends in ecosystem services concluded that the current potential of ecosystems to deliver timber, protection against floods, crop pollination, and nature-based recreation is equal to or lower than the baseline value for 2010. At the same time, the demand for these services has significantly increased. A lowered potential in combination with a higher demand risks to further decrease the condition of ecosystems and their contribution to human well-being. Despite the wide coverage of environmental legislation in the EU, there are still large gaps in the legal protection of ecosystems. On land, 76% of the area of terrestrial ecosystems, mainly forests, agroecosystems and urban ecosystems, are excluded from a legal designation under the Bird and Habitat Directives. Freshwater and marine ecosystems are subject to specific protection measures under the Water Framework and Marine Strategy Framework Directives. The condition of ecosystems that are under legal designation is unfavourable. More efforts are needed to bend the curve of biodiversity loss and ecosystem degradation and to put ecosystems on a path to recovery. The progress that is made in certain areas such as pollution reduction, increasing air and water quality, increasing share of organic farming, the expansion of forests, and the efforts to maintain marine fish stocks at sustainable levels show that a persistent implementation of policies can be effective. These successes should encourage us to act now and to put forward an ambitious plan for the restoration of Europe’s ecosystems.JRC.D.3-Land Resource

The EU greenhouse gas inventory for LULUCF sector: I. Overview and comparative analysis of methods used by EU member states

Reporting national greenhouses gas inventories for the Land Use, Land Use Change and Forestry (LULUCF) under the United Nations Framework Convention for Climate Change (UNFCCC) has been driving significant development of national data. Lands classification and definitions for C pools are very different across the 28 EU member states, as are the methods used for data collection and processing. Even when definitions or sampling methods were in substance the same, specifications were-different. However, member states’ inventories are assumed to be fully comparable and consistent with reporting principles. For forest, data collection rely on forest inventory repeated measurements (both statistical sampling and standwise), while for most important contributor, the biomass, there is no preference for “gain-loss” or “stock-change” method. For cropland and grasslands, operational records information is equally important to statistical sampling and aerial photography sources for area estimation, while default emission factors are used less and less as they are being replaced by countryspecific data. The obvious trend is the move toward statistical sampling covering all land categories within national territory and slight increasing use of models. Such heterogeneity requires a better harmonization of data collection and processing as to increase the credibility of the EU GHG inventory.JRC.H.3-Forest Resources and Climat

Global estimates of carbon stock changes in living forest biomass: EDGARv4.3 – time series from 1990 to 2010

While the Emissions Database for Global Atmospheric Research (EDGAR) focuses on global estimates for the full set of anthropogenic activities, the Land Use, Land-Use Change and Forestry (LULUCF) sector might be the most diverse and most challenging to cover consistently for all countries of the world. Parties to United Nations Framework Convention on Climate Change (UNFCCC) are required to provide periodic estimates of greenhouse gas (GHG) emissions, following the latest approved methodological guidance by the International Panel on Climate Change (IPCC). The current study aims to consistently estimate the carbon (C) stock changes from living forest biomass for all countries of the world, in order to complete the LULUCF sector in EDGAR. In order to derive comparable estimates for developing and developed countries, it is crucial to use a single methodology with global applicability. Data for developing countries are generally poor, such that only the Tier 1 methods from either the IPCC Good Practice Guide for Land Use, Land-Use Change and Forestry (GPG-LULUCF) 2003 or the IPCC 2006 Guidelines can be applied to these countries. For this purpose, we applied the IPCC Tier 1 method at global level following both IPCC GPG-LULUCF 2003 and IPCC 2006, using spatially coarse activity data (i.e. area, obtained combining two different global forest maps: the Global Land Cover map and the eco-zones subdivision of the Global Ecological Zone (GEZ) map) in combination with the IPCC default C stocks and C stock change factors. Results for the C stock changes were calculated separately for gains, harvest, fires (Global Fire Emissions Database version 3, GFEDv.3) and net deforestation for the years 1990, 2000, 2005 and 2010. At the global level, results obtained with the two sets of IPCC guidance differed by about 40 %, due to different assumptions and default factors. The IPCC Tier 1 method unavoidably introduced high uncertainties due to the "globalization" of parameters. When the results using IPCC 2006 for Annex I Parties are compared to other international datasets such as (UNFCCC, Food and Agriculture Organization of the United Nations (FAO)) or scientific publications, a significant overestimation of the sink emerges. For developing countries, we conclude that C stock change in forest remaining forest can hardly be estimated with the Tier 1 method especially for calculating the C losses, mainly because wood removal data are not separately available on harvesting or deforestation. Overall, confronting the IPCC GPG-LULUCF 2003 and IPCC 2006 methodologies, we conclude that IPCC 2006 suits best the needs of EDGAR and provide a consistent global picture of C stock changes from living forest biomass independent of country estimates.JRC.H.2-Air and Climat

Global estimates of C stock changes in living forest biomass: EDGARv4.3 –5FL1 time series from 1990 to 2010

While the Emissions Database for Global Atmospheric Research (EDGAR) focuses on global estimates for the full set of anthropogenic activities, the Land-Use, Land-Use Change and Forestry (LULUCF) sector might be the most diverse and most challenging to cover consistently for all world countries. Parties to UNFCCC are required to provide periodic estimates of GHG emissions, following the latest approved methodological guidance by the International Panel on Climate Change (IPCC). The aim of the current study is comparing the IPCC GPG 2003 and the IPCC AFOLU 2006 by calculating the C stock changes in living forest biomass, and then using computed results to extend the EDGAR database. For this purpose, we applied the IPCC Tier 1 method at global level, i.e. using spatially coarse activity data (i.e. area, obtained combining two different global forest maps: the Global Land Cover map and the eco-zones subdivision of the GEZ Ecological Zone map) in combination with the IPCC default C stocks and C stock change factors. Results for the C stock changes were calculated separately for Gains, Harvest, Net Deforestation and Fires (GFED3), for the years 1990, 2000, 2005 and 2010. At the global level, results obtained with the two set of IPCC guidance differed by about 40%, due to different assumptions and default factors. The IPCC Tier 1 method unavoidably introduced high uncertainties due to the "globalization" of parameters. When the results using IPCC AFOLU 2006 for Annex I countries are compared to other international datasets (UNFCCC, FAO) or scientific publications, it emerges a significant overestimation of the sink. For developing countries, we conclude that C stock change in forest remaining forest can hardly be estimated with Tier 1 method. Overall, confronting the IPCC 2003 and 2006 methodologies we conclude that IPCC 2006 suits best the needs of EDGAR and provide a consistent global picture of C stock changes in living forest biomass independent of country estimates.JRC.H.2-Air and Climat

Modelling forest carbon stock changes as affected by harvest and natural disturbances. I. Comparison with countries’ estimates for forest management

According to the post-2012 rules under the Kyoto Protocol, developed countries that are signatories to the protocol have to estimate, report, and account the greenhouse gas (GHG) emissions and removals from forest management (FM), with the option to exclude the emissions and subsequent removals associated to natural disturbances. The general aim of this study is to implement a single consistent methodological approach using the Carbon Budget Model (CBM) for the period 2000-2012 to estimate the carbon (C) stock changes from FM in 26 European Union (EU) countries. All forest carbon pools were considered, and the impacts of natural disturbances (mainly storms and fires) and forest management were represented. We then compared the CBM results with the data reported by countries in their GHG inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC). The match between the CBM results and the GHG inventories was good (i.e. same trend and same level) in 9 cases and partially good (either for the trend or the level) in 10 cases. When the comparison was not satisfactory, in most cases we identified possible reasons for the discrepancies, including: (i) a different representation of the interannual variability due to harvest and natural disturbances (e.g. when GHG inventories use the stock-change approach); (ii) different assumptions for non-biomass pools (not reported by several countries) and for CO2 emissions from fires and harvest residues. In few cases – e.g. where the GHG inventory reports an increasing biomass sink associated with an increasing trend in harvest rates – a closer analysis is needed to identify any possible inappropriate data used by the CBM (e.g. old statistics) or problems in the GHG inventory. Finally, implementation of consistent methodology using a model is challenging because of ongoing updates to data and methods used by countries and, also in the light of the frequent recalculations and the high uncertainties reported by countries on forest C stock changes. This study indicates opportunities to use the CBM as tool to assist countries in estimating forest C dynamics (e.g., in case of natural disturbances) through the use of a consistent methodology that meets the objectives of the IPCC Guidelines. On the other hand, the CBM may be seen as potential verification tool of GHG inventories at the EU level. A systematic comparison of the CBM with the GHG inventories will certainly require additional efforts – including close cooperation between modelers and country experts – and caution in interpreting the results. Nevertheless, this approach should be seen as a necessary step in the process of continuous improvement of GHG inventories, because it may help in identifying possible errors and ultimately in building trust in the estimates reported by the countries.JRC.H.3-Forest Resources and Climat