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Evaluating the potential impacts of each policy on all sustainability dimensions (economic, social and environmental), as captured in the UN SDGs and their targets, requires system thinking and shifting away from single disciplinary projects towards multi- and inter- disciplinary approaches that recognize complexities and acknowledge uncertainties. Modelling is an essential tool to increase the understanding of qualitative and quantitative drivers of sustainability, contributing to the implementation of specific SDGs. The report presents the mapping of JRC models against SDGs, in order to identify links between model outputs and SDGs at target and indicator levels, and facilitate the use of models for sustainability assessment in support of EU policy making. The mapping considers 108 modelling tools listed in MIDAS, the Modelling Inventory and Knowledge Management System of the European Commission. A first analysis on the links between models and the SDG framework was carried out starting from the online description available in MIDAS. Modellers were further requested to validate the initial assessment, confirming the links identified and eventually proposing additional ones, through one survey and two workshops organised in 2019. This analysis offers a transparent mapping of how models outputs can be directly or indirectly linked to EU/UN SDGs indicators, how trade-offs and interplays can be assessed, therefore indicating to what extent JRC models can quantitatively evaluate the impacts of policy options on SDGs, targets and indicators., JRC.D.1-Bio-economy

The EU Recovery Plan represents a unique window of opportunity to restart the socioeconomic system after the Covid-19 crisis, fostering a shift towards sustainable development. The UN Agenda 2030, with its 17 goals and 169 targets, provides a compass to orientate the recovery in a sustainable way, considering together the economic, social and environmental dimensions. The political guidelines for European Commission 2020-2025 attribute a central role to the Agenda 2030 and its SDGs and frame sustainable development as the cornerstone of the national and European policies. Within this context, this report contributes to a better understanding of how the EU Recovery Plan relates to the SDG framework by applying a text mining approach that automatically maps key documents of the plan with the UN goals and targets. This textual analysis has been applied to a collection of documents publicly available up until July 2020, and provides a preliminary screening of SDGs and their targets in the Recovery Plan. The Recovery Plan is indeed in continuous evolution, with new legislative and non-legislative acts being drafted and adopted; therefore, these results represent a snapshot that may eventually change over time. However, identifying the link between the proposed Recovery Plan and SDGs upstream in early phase of the negotiations, can help to highlight areas that may boost SDG implementation along with areas that deserve more attention; further, it may also facilitate SDG mainstreaming in the implementation phase or monitoring changes in SDGs coverage during the implementation process (e.g. through a subsequent analysis of the Member States National Recovery and Resilience Plans, currently under preparation). Summarizing the results at the goal level, the Plan as a whole predominantly addresses SDG 3 on health and SDG 8 on economic growth and employment, but many others are identified. Overall, the Plan addresses all the 17 Goals, though some SDGs like SDG 6 on water resources are only marginally addressed. At target level, the text analysis detected 88 targets, described in detail in chapter 4. The distribution of SDGs and targets in the Plan shows a great variety. The first pillar (“Support Member States in Recovering”) pays particular attention to SDG 8, addressing many of its targets. This pillar has the largest financial allocation (about 90% of all funds of the Plan), and this is reflected by the broader coverage of all SDGs and their targets, compared to the other pillars. The second pillar (“Kick-start the economy and help private investment”) has also a relatively broad coverage of SDGs, and is mainly focused on SDG 9, regarding sustainable industrialization and foster innovation. The textual analysis of the third pillar (“Learning the lessons from the crisis”) evidenced that it focuses on fewer SDGs compared to the previous two, with a strong emphasis on SDG 3. The main target is 3.d, to strengthen the capacity for early warning, risk reduction and management of national and global health risks. The SDGs are a roadmap for sustainable development and should remain a framework for recovery in all countries. The mapping of SDGs in the proposed EU Recovery Plan carried out with our text mining technique provides a tool for tracking the implementation of the SDGs in the Plan, providing information on how specific initiatives included in the Plan address goals and related targets. Furthermore, potential policy gaps in SDGs coverage could be identified to allow policymakers to find adequate responses that can fill those gaps. A sustainable recovery should embrace as much as possible the principles of the Agenda 2030 and its SDGs, putting the EU in the right track to long-term sustainable growth. Our assessment of the recovery plan indicates that the Commissions is a frontrunner in pursuing the goals, and the Plan can further accelerate the transition towards a more sustainable, fair, just, and resilient EU., JRC.D.1-Bio-economy

The European Commission’s Science and Knowledge Service, the Joint Research Centre (JRC), decided to try working hand-in-hand with leading European science centres and museums. Behind this decision was the idea that the JRC could better support EU Institutions in engaging with the European public. The fact that European Union policies are firmly based on scientific evidence is a strong message which the JRC is uniquely able to illustrate. Such a collaboration would not only provide a platform to explain the benefits of EU policies to our daily lives but also provide an opportunity for European citizens to engage by taking a more active part in the EU policy making process for the future. A PILOT PROGRAMME To test the idea, the JRC launched an experimental programme to work with science museums: a perfect partner for three compelling reasons. Firstly, they attract a large and growing number of visitors. Leading science museums in Europe have typically 500 000 visitors per year. Furthermore, they are based in large European cities and attract local visitors as well as tourists from across Europe and beyond. The second reason for working with museums is that they have mastered the art of how to communicate key elements of sophisticated arguments across to the public and making complex topics of public interest readily accessible. That is a high-value added skill and a crucial part of the valorisation of public-funded research, never to be underestimated. Finally museums are, at present, undergoing something of a renaissance. Museums today are vibrant environments offering new techniques and technologies to both inform and entertain, and attract visitors of all demographics., JRC.H.2-Knowledge Management Methodologies, Communities and Dissemination

Directive EU 2018/2001 on the promotion of the use of energy from renewable sources has been officially ratified in December 2018 for the post-2020 framework. It is a new iteration of the Renewable Energy Directive RED, the so-called ‘recast’, work on which began in 2016. The Directive fixes a minimum requirement for greenhouse gas (GHG) savings for biofuels and bioliquids for the period from 2021 to 2030, and sets the rules for calculating the greenhouse impact of biofuels, bioliquids and their fossil fuels comparators. To help economic operators to declare the GHG emission savings of their products, default and typical values for a number of specific pathways are listed in the annexes of the RED-recast (Annex V). The EC Joint Research Center (JRC) is in charge of defining input values to be used for the calculation of default GHG emissions for biofuels, bioliquids, solid and gaseous biomass pathways. An update of the GHG emissions in Annex V has been carried out for the new Directive on the Promotion of the Use of Energy from Renewable Sources (Directive 2018/2001), for the post-2020 framework. This report describes the assumptions made by the JRC when compiling the new updated data set used to calculate default and typical GHG emissions for the different biofuels pathways as proposed in the new directive., JRC.C.2-Energy Efficiency and Renewables

The report delivers an assessment of EU biomass production, uses, flows and related environmental impacts for the sectors agriculture, forestry, fisheries and aquaculture, and algae. Quantitative estimates are derived from available data and current knowledge, yet highlighting the uncertainties and the remaining gaps. The work is framed within the JRC biomass study and is meant to support the EU bioeconomy and the related policies., JRC.D.1-Bio-economy

TRIMIS is an open-access transport information system. The TRIMIS database contains transport research and innovation projects and programmes that are arranged according to the seven Strategic Transport Research and Innovation Agenda (STRIA) roadmaps that were adopted by the European Commission in May 2017. The roadmaps cover: cooperative, connected and automated transport; transport electrification; vehicle design and manufacturing; low-emission alternative energy for transport; network and traffic management systems; smart mobility and services; infrastructure. This report provides the first overview and analyses of the TRIMIS database and identifies areas for further research., JRC.C.4-Sustainable Transport

First report providing horizontal analysis of the EU Bioeconomy • The Bioeconomy cuts across several economic sectors, academic disciplines and policy areas. • Bioeconomy R&I are heavily supported by EU funds • The EU bioeconomy provides more than 18 million jobs with overall decreasing tendency due to structural changes, e.g. in agriculture • The EU bioeconomy creates a turnover of 2 trillion € with increasing tendency, JRC.D.6-Knowledge for Sustainable Development and Food Security

The Commission's legislative proposal for a recast of the Renewable Energy Directive (RED-recast) (COM(2016) 767), in Art. 26(7), specifies the minimum greenhouse gas (GHG) emissions saving thresholds that bioenergy must comply with in order to count towards the renewables targets and to be eligible for public support. Annex V (liquid biofuels) and Annex VI (solid and gaseous biomass) of the RED-Recast describe the methodology for GHG savings calculations needed to comply with the GHG criteria. They also provide a list of Default GHG emission values, aggregated and disaggregated, that operators can use to demonstrate compliance of their product with the GHG criteria. This report describes the input data, assumptions and methodological approach applied by the JRC when compiling the updated dataset used to calculate GHG emissions for the different biomass pathways. The GHG emissions resulting from the application of the methodology from COM(2016) 767, and presented in Annex VI of the document, are also shown. The report aims to provide operators, stakeholders ,and the scientific community all the necessary information to explain the assumptions chosen as well as to guarantee reproducibility of the results. Additional analysis to test the sensitivity of the results to various assumptions is presented in the final section of the report., JRC.C.4-Sustainable Transport

The Renewable Energy Directive (RED) (2009/28/EC) and the Fuel Quality Directive (FQD) (2009/30/EC), amended in 2015 by Directive (EU) 2015/1513 (so called ‘ILUC Directive’), fix a minimum requirement for greenhouse gas (GHG) savings for biofuels and bioliquids for the period until 2020, and set the rules for calculating the greenhouse impact of biofuels, bioliquids and their fossil fuels comparators. To help economic operators to declare the GHG emission savings of their products, default and typical values for a number of spefic pathways are listed in the annexes of the RED and FQD. The EC Joint Research Center (JRC) is in charge of defining input values to be used for the calculation of default GHG emissions for biofuels, bioliquids, solid and gaseous biomass pathways. An update of the GHG emissions in Annex V has been carried out for the new Proposal of a Directive on the Promotion of the Use of Energy from Renewable Sources (COM(2016)767 - RED-2), for the post-2020 framework. This report describes the assumptions made by the JRC when compiling the new updated data set used to calculate default and typical GHG emissions for the different biofuels pathways as proposed in the new RED-2 document., JRC.C.4-Sustainable Transport

The Paris Agreement and the EU Climate and Energy Framework set ambitious but necessary targets. Reducing greenhouse gas (GHG) emissions by phasing out the technologies and infrastructures that cause fossil carbon emissions is one of today’s most important challenges. In the EU, bioenergy is currently the largest renewable energy source used. Most Member States have in absolute terms increased the use of forest biomass for energy to reach their 2020 renewable energy targets. In recent years, the issue of ‘carbon neutrality’ has been debated with regard to the bioenergy products that are produced from forest biomass. There is no clear consensus among scientists on the issue and their messages may even appear contradictory to decision-makers and citizens. Divergence arises because scientists address the issue from different points of view, which can all be valid. It is important to find agreement on some basic principles, to inform policy makers. Guidance is also needed on how the results should be interpreted. This report provides insights into the current scientific debate on forest biomass, carbon neutrality and climate change mitigation. It draws on the science literature to give a balanced and policy-relevant synthesis, from both an EU and global perspective., JRC.C.4-Sustainable Transport

The European Communication on Better regulation (CEC, 2015) has been complemented with a Better Regulation toolbox which lists models and methods for the impact assessment of policies. Life cycle analysis has been listed among the tools, aiming at supporting the assessment of impact and benefits associated to different policy options. While the use of LCA in the context of business can be easily identified (decision-making, communication towards consumers, customers and/or governmental bodies), the full range of LCA uses in policy making is not well known as it has never been overall investigated. This knowledge gap can limit the LCA use in the context of policy, in turn, contrasting with the European Commission’s objective of making smart the regulation. In this context, the present report pursues a two-fold aim: i) to provide a first framework of potential roles of the LCA in the whole policy cycle, with particular reference to the impact assessment, ii) to provide discussion elements and inputs for LCA enhancement in the context of policy cycle. The proposed framework and related discussion elements/inputs has been built through the review of existing environmental policies, the review of Staff Working Documents relating to policies on Energy, Climate action and Environment topics, the definition of the most advanced state-of-art of LCA methodology. Due to its main features (Life cycle perspective and systemic approach), the LCA plays a relevant role all along the policy cycle, from policy anticipation and problem definition, to the policy evaluation. LCT and LCA have been integrated in several EU environmental policies over the last two decades and LCA is mostly mentioned as implementation measure. In the path of the policy cycle, the steps in which LCT and LCA could add more value are theoretically the first ones (policy formulation and policy impact assessment) as a proactive analysis to develop, evaluate and compare the different policy options and, in turn, to support the policy-makers in the adoption of the most suitable option. The Impact Assessment of policy (IA) addresses all dimension of sustainability, i.e. economic, social and environmental. Some LCA elements are particularly relevant for addressing sustainability problems, such as the life cycle perspective, the identification of the most important burdens and most relevant life cycle stages contributing to environmental and social impacts, identification of environmental (and social) “hot spots” of goods/ services/ systems/ technologies/ innovations/ infrastructures, identification of unintended burdens shifting between environmental (social) impacts (reducing one impact while increasing another) and over life cycle stages. In the context of the challenges posed by environmental sustainability assessment, LCA play a key role as it can provide support to policy-makers towards more transparent and evidence-based decisions, as requested by the Better regulation. A broad and international discussion on the need of a guidance for the application of LCA in the policy is ongoing. Several elements may affect the final results and policy support, including: data quality, modelling approach, methodological choices, uncertainty analysis etc. Further guidance tailoring LCA for policy needs are of upmost important. In this context, methodologies for capitalising existing knowledge are needed as well as methodology for robust and systematic sensitivity analysis., JRC.D.1-Bio-economy

The Renewable Energy Directive (RED) (2009/28/EC) and the Fuel Quality Directive (FQD) (2009/30/EC) fix a threshold of savings of greenhouse gas (GHG) emissions for biofuels and bioliquids, and set the rules for calculating the greenhouse impact of biofuels, bioliquids and their fossil fuels comparators. To help economic operators to declare the GHG emission savings of their products, default and typical values are also listed in the annexes of the RED and FQD directives. The Commission recommended Member States to use the same approach for other bioenergy sources in the report from the Commission to the Council and the European Parliament on sustainability requirements for the use of solid and gaseous biomass sources in electricity, heating and cooling (COM(2010)11). Typical and default GHG emission values for solid and gaseousbioenergy pathways were reported in the report. SWD(2014)259 updates the values defined in the COM(2010)11 to account for the technogical and market developments in the bioenergy sector. This report describes the assumptions made by the JRC when compiling the updated data set used to calculate default and typical GHG emissions for the different solid and gaseous bioenergy pathways and the results of such calculations in terms of typical and default GHG emission values . In the annexes the comments/questions received from JRC as reaction to the presentation of the data in stakeholders/experts consultations are reported together with their relative answers/rebuttals. This report describes the assumptions made by the JRC when compiling the updated data set used to calculate default and typical GHG emissions for the different solid and gaseous bioenergy pathways and the results of such calculations in terms of typical and default GHG emission values . In the annexes the comments/questions received from JRC as reaction to the presentation of the data in stakeholders/experts consultations are reported together with their relative answers/rebuttals., JRC.F.8-Sustainable Transport

During the last decade(s), algal biomass received increasing interest as a potential source of advanced biofuels production resulting in a considerable attention from research, industry and policy makers. In fact, algae are expected to offer several advantages compared to land-based biomass crops, including: better photosynthetic efficiency; higher oil yield; growth on non-fertile land; tolerance to a variety of water sources (i.e. fresh, brackish, saline) and CO2 re-using potential. The algal growth can be also integrated in wastewater (WW) treatment systems to combine the nutrient streams removal with biofuels production. In addition, a wide range of marketable co-products can be extracted from algae (e.g. chemicals, pharmaceuticals, nutritionals) along with the production of biofuels, under a biorefinery system. Considering the potential benefits, several European-funded pilot projects, under science-business partnerships, have been dedicated to the development of algae technologies in the biofuels and bioenergy sectors. Despite the extensive research and investments in the last decade(s), no large-scale, commercial algae-to-biofuels facilities were implemented yet. In fact, in the current algae cultivation sites, the produced biomass is currently exploited for production of food and feed, combined with the extraction of high added-value products, such as proteins, nutritional supplements and chemicals. We report on the current-status of technology options for the potential exploitation of algae (of both macro- and microalgae species) in the biofuels and bioenergy sectors. We presents a comprehensive review of recent advances on promising algal biofuel production pathways, in terms of technological development, opportunities and limitations to their overall effectiveness. Furthermore, we analyse the main features, assumptions, modelling approaches and results of the algal biofuel pathways considered in the LCA literature. We highlight and interpret the energy and greenhouse gas (GHG) emissions balances resulting from examined LCA studies, in view of the key parameters mainly affecting the results. A comparison of the performance associated to the proposed algal biofuels pathways with that found for conventional fossil derived fuels is also reported., JRC.F.8-Sustainable Transport

ILUC emissions from biofuels are commonly estimated with sophisticated economic models of world agriculture. Because these are often complex, the JRC in collaboration with Overmars and PBL has evaluated and developed an alternative approach base on “historical” data. This approach gives simple and transparent estimates of ILUC emissions in recent years, even if the method is less rigorous in principle than estimates based on sophisticated economic models. ILUC emissions calculated by a methodology using historical data are generally in line with those of economic models, showing a lower impact of cereals and sugar crops compared to vegetable oils., JRC.F.8-Sustainable Transport

The Renewable Energy Directive (RED) (2009/28/EC) and the Fuel Quality Directive (FQD) (2009/30/EC) fix a threshold of savings of greenhouse gas (GHG) emissions for biofuels and bioliquids, and set the rules for calculating the greenhouse impact of biofuels, bioliquids and their fossil fuels comparators. To help economic operators to declare the GHG emission savings of their products, default and typical values are also listed in the annexes of the RED and FQD directives. The Commission recommended Member States to use the same approach for other bioenergy sources in the report from the Commission to the Council and the European Parliament on sustainability requirements for the use of solid and gaseous biomass sources in electricity, heating and cooling (COM(2010)11). Typical and default GHG emission values for solid and gaseousbioenergy pathways were reported in the report. SWD(2014)2014 updates the values defined in the COM(2010)11 to account for the technogical and market developments in the bioenergy sector. This report describes the assumptions made by the JRC when compiling the updated data set used to calculate default and typical GHG emissions for the different solid and gaseous bioenergy pathways and the results of such calculations in terms of typical and default GHG emission values . In the annexes the comments/questions received from JRC as reaction to the presentation of the data in stakeholders/experts consultations are reported together with their relative answers/rebuttals. This report describes the assumptions made by the JRC when compiling the updated data set used to calculate default and typical GHG emissions for the different solid and gaseous bioenergy pathways and the results of such calculations in terms of typical and default GHG emission values . In the annexes the comments/questions received from JRC as reaction to the presentation of the data in stakeholders/experts consultations are reported together with their relative answers/rebuttals., JRC.F.8-Sustainable Transport

The report presents an independent estimate of the part of LUC emissions due to deforestation, starting from the 29% of historical deforestation area (and estimated emissions) caused by expansion of different crops. The deforestation area and emissions per tonne of extra crop are converted to emissions per MJ biofuel from that crop. The average global deforestation caused by increase in production of a crop or biofuel is estimated, making no geographical differentiation in where the extra demand occurs or where that would provoke deforestation. The source of historical deforestation data is a report published by DG ENV [EC 2013] which estimates which areas of forest were lost to different crops and to other land uses (grazing, logged forest, urban and others) between 1990 and 2008. It used historical deforestation data from FAO’s Forest Resource Assessment 2010, interpreted with other FAO data. The emissions are calculated only from deforestation and peat forest drainage, attributed to each MJ biofuel. This does not include emissions from the grassland area converted to cropland. This method gives an independent verification of the general magnitude of LUC area and emissions which should be expected from bottom-up models of LUC for scenarios, and the results indicate that historical LUC emissions were higher than those estimated by most economic models., JRC.F.8-Sustainable Transport

JRC started in 2012 a collaboration with the International Food Policy Research Institute (IFPRI) to carry out further work with the economic model MIRAGE used to calculate the ILUC emissions included in the Commission policy proposal COM(2012)595.. Results are expected to further reduce uncertainties in ILUC estimates. This work presents and discusses the results of new runs of MIRAGE model delivered to the JRC-IET. In particular, IFPRI was asked to: - Evaluate GHG emissions by crop groups (sugar, cereals and oil crops), maintaining the same model assumptions/parameters as in the previous analysis. - Make new runs of the MIRAGE economic model, with improved assumptions/parameters as suggested by the JRC The changes brought by IFPRI to their model raise the ILUC emissions compared to 2011 values, especially for EU ethanol., JRC.F.8-Sustainable Transport

The EU legislation contains a set of mandatory targets specific for the EU transport sector which aims at achieving the overall objective of a European sustainably fuelled transport system. In particular, Directives 2009/28/EC (Renewable Energy Directive) and 2009/30/EC (Fuel Quality Directive) fix a threshold of 35% savings of GHG emissions for biofuels and bioliquids and set out the rules for calculating the greenhouse impact of biofuels, bioliquids and their fossil fuels comparators. Further, the Commission is working on a report and possible legislative proposal that could have similar or the same provisions for other bioenergy sources (biogas and biomass). To help economic operators in calculating GHG emission savings, default and typical values are also listed in the Annexes of the two directives, which were calculated on the basis of the JEC (JRC-EUCAR-CONCAWE consortium) database of input data in its version of 31 July 2008, following a consultation process with stakeholders launched by the Commission. According to article 19.7 in the Renewable Energy Directive and 7d.7 in the Fuel Quality Directive, the Commission can also adapt default values to technical and scientific progress by updating the existing values and by adding additional pathways. On request of the Commission’s DG ENER, the JRC worked on the update of the existing input database, and the list of pathways in the Directives will therefore likely be modified accordingly. This report aims at describing the JRC assumptions made to build-up the dataset used for the calculation of default GHG emissions for the different pathways in annexes of the Directives., JRC.F.8-Sustainable Transport

The article, “Indirect land use change for biofuels: Testing predictions and improving analytical methodologies” by S. Kim and B. Dale, presents a principal inference not supported by its results, rests on a fundamental conceptual error, and has no place in the current discussion of biofuels’ climate effects. As it is already receiving press attention as though its findings are considerable, it requires a detailed refutation. Briefly, the most important errors in the paper are • taking correlation between two variables in a system with many interacting factors to indicate (or contraindicate) causation, • drawing a completely incorrect inference from observed sample statistics and their significance levels, and • misunderstanding “the question” about ILUC, which is not whether biofuels production causes total deforestation to increase, but whether it causes it to increase more, or reforestation to increase less, than would happen without the biofuel program., JRC.F.7-Renewable Energy

Under request of DG ENER and CLIMA, the JRC organised in November 2010 an expert consultation, grouping world-recognised academics and experts in the field on Indirect Land Use Change (ILUC) effects caused by increased use of biofuels. This consultation aimed at discussing the main uncertainties related to ILUC estimations and to answer to the questions addressed in the public consultation. The two days discussions focused in particular on the following items: 1. Land use change and greenhouse gas emissions (methodologies, datasets and uncertainties to locate ILUC and calculate GHG emissions) 2. Agro-economic modelling and uncertainties 3. Policy options The final discussions addressed policy issues, in particular:- • Does the modelling provide a good basis for determining how significant indirect land use change is? • Are the impacts significant? • Can we differentiate between bioethanol/biodiesel, feedstocks, geographical areas, production methods? The experts unanimously agreed that, even when uncertainties are high, all indicators point towards the existence of a significant ILUC effect and the magnitude of this effect is crop-specific. The sustainability criteria in the Renewable Energy and Fuel quality Directives limit Direct Land Use Change, but they are ineffective to avoid ILUC, and therefore additional policy measures are necessary. The use of a factor which attributes a quantity of greenhouse gas emissions to crop-specific biofuels was the favourite option discussed, but it was also agreed that policies should incentivise good agricultural practices, land management C-mitigation strategies and intensification on pasture lands. On the other hand, the experts agreed that the increase of the GHG threshold will have only a limited effect on ILUC reduction., JRC.F.8-Renewable Energy (Ispra)

This study compares the ILUC results produced by different economic models for marginal increases in biofuel production from different feedstocks. The work is the result of a survey of marginal calculations launched by the JRC-IE during 2009, involving some of the best known models worldwid. The modellers were requested by JRC-IE to run scenarios corresponding as closely as possible to the following specification (e.g. marginal runs against existing baseline of the following scenarios): A marginal extra ethanol demand in EU B marginal extra biodiesel demand in EU C marginal extra ethanol demand in US D marginal extra palm oil demand in EU The results from the different models and various scenarios are compared in this report in terms of hectares of ILUC per Mtoe of biofuels produced (marginal land use change). In the EU ethanol scenarios, the total estimated ILUC (in the world) ranges from 223 to 743 kHa per Mtoe. For most of the EU ethanol scenarios the models project that the largest share of ILUC would occur outside the EU In the EU biodiesel scenarios, total ILUC ranges from 242 to 1928 kHa per Mtoe In all of the EU biodiesel scenarios the models project that the largest share of LUC would occur outside the EU Although this is not the main purpose of this report, the range of GHG emissions which one could expect to correspond to the areas of LUC reported by all the models has been rouglhy estimated. The report provides deep analysis of the resons of differences between models and gives fundamental indications to policy makers on how to address the issue of ILUC in legislation., JRC.DDG.F.8-Renewable Energy (Ispra)

This study is performed under request of DG CLIMA, in support to the preparation of the policy proposal on the assessment of the effects of Indirect Land Use Change (ILUC). Agro-economic models are used to provide estimates of how much cropland area increases in response to an increase in crop demand, but they often differ in their structure (i.e. partial or full equilibrium, agro-economic, bioenergy and biophysical models etc), in the input parameters, baseline and scenarios studied. The European Commission (EC) is debating internally how to address ILUC emissions in biofuels legislation. Legislators need to understand how ILUC differs between biofuels from different feedstocks and regions. In fact, if ILUC emissions are to be added to direct emissions in legislation, they need to be quantitatively assessed for all biofuels/feedstocks. Anyway, to compare model results it is necessary at least to compare the results vs. baseline per unit quantity of biofuel. For these reasons the JRC proposed to carry out a survey of marginal calculations from various models/methods developed by the relevant consortia in EU and US, to compare results from marginal shocks along the lines of recommended common scenarios discussed with the involved experts: A marginal extra ethanol demand in EU B marginal extra biodiesel demand in EU C marginal extra ethanol demand in US D marginal extra palm oil demand in EU (for biodiesel or pure plant oil use) For modelling the GHG efficiency of different feedstock, the experts agreed that the extra biofuels scenarios should optimally be marginal increases in demand for different biofuels-feedstock in different regions. These results would be relatively easy to compare between scenarios. Results of this survey were discussed during a workshop organized by the JRC in Ispra on 10th and 11th of February 2010, and this report presents the outcomes of the workshop, highlighting the main results of the studies and key points raised in the concluding discussion., JRC.DDG.F.8-Renewable Energy (Ispra)