Deliverable 3.5: Biomass availability & supply analysis

Biomass role in achieving the Climate Change & Renewables EU policy targets. Demand and Supply dynamics under the perspective of stakeholders. IEE 08 653 SI2. 529 241 Deliverable 3.5: Biomass availability & supply analysis Summary of main outcomes for policy makers Authors: IIASA: Alterra: CRES: Hannes Böttcher, Stefan Frank Berien Elbersen Efthimia Alexopoulou March, 2012

Content Preface... 3 1 Introduction... 4 2 Methodology... 4 2.1 Review of previous studies (WP3.2 and 3.3)... 4 2.2 Predicting the availability of biomass and modelling biomass supply (WP3.4, 3.5)... 4 2.3 List of deliverables... 6 3 Findings... 6 3.1 Review of biomass studies... 6 3.2 Assessment of 4F crops... 6 3.3 Assessment of availability... 8 3.4 Assessment of supply... 15 4 Conclusions... 18 2

Preface This publication is part of the BIOMASS FUTURES project (Biomass role in achieving the Climate Change & Renewables EU policy targets. Demand and Supply dynamics under the perspective of stakeholders - IEE 08 653 SI2. 529 241, www.biomassfutures.eu) funded by the European Union s Intelligent Energy Programme. The sole responsibility for the content of this publication lies with authors. It does not necessarily reflect the opinion of the European Union. The European Commission is not responsible for any use that may be made of the information contained therein. 3

1 Introduction The aim of Work Package 3 (WP3) of the Biomass Futures project is to provide a comprehensive strategic analysis of biomass supply options and their availability in response to different demands in a timeframe from 2010-2030. This is achieved by making a comparative inventory of existing studies, and synthesising the results in terms of economic supply estimates that are most realistic and likely given various policy and development scenarios as specified in WP7. Supply of biomass as addressed by WP3 includes existing biomass streams (including waste) and potential new streams from non-food crops and 4F crops, i.e. crops for producing food, feed, fiber and fuel as raw materials for energy and industrial applications. This report concisely summarises the approach and results of the modelling of biomass supply under WP 3 for policy makers and other stakeholders 1. The output provided by WP3 can be summarised in four points: Overview of the main factors influencing the biomass potential and availability under different regional circumstances for a variety of feedstocks. Prediction and spatial distribution of biomass potentials for EU per region including economic supply curves as input for WP7. Competitive biomass supply patterns for different biomass chains and different scenarios. An assessment of impacts of biomass use under different scenarios on trade patterns and environmental parameters. 2 Methodology 2.1 Review of previous studies (WP3.2 and 3.3) Biomass Futures builds on the results of previous studies (EUBIONET, RENEW, REFUEL, BEE, Elobio, 4FCROPS, etc.). Biomass Futures reviews the main biomass potential studies performed at national, EU27 and global levels scrutinizing the existing assessment studies in terms of assumptions, data and definitions used. The methodology for the assessment of selected biomass studies foresees a categorization into different types of studies to make the studies more comparable. The assessment distinguishes further between technical, economic, competitive economic and implementation potentials given various policy and environmental constraints. As different sectors - food, feed, fibre and fuels compete for land, biomass crops have to be used as efficiently as possible in order to minimize the competition for land. Energy crops (or non-food crops) can be converted into a number of different products. Many crop species are multipurpose and yield more than one product, for example hemp (both oil and soil biomass or oil and fibres) and cereals (ethanol and soil biomass from straw or ethanol and straw as a feed product). Within Biomass Futures, we consider the following common energy crops: oil crops, cereals, starch and sugar crops, cellulose crops, and solid energy crops or lignocellulosic crops. The options of non-food crops in EU27 are reviewed in terms of land availability/ suitability, rotation possibilities, yields, biomass quality characteristics, and options of yield improvement through biotechnology. 2.2 Predicting the availability of biomass and modelling biomass supply (WP3.4, 3.5) Land availability and related biomass availability and the availability of by- and waste products are steered by a range of key factors, such as current and future land use, accessibility, recovery rates, costs, competing uses, etc. Taking such factors into account is essential for the estimation and mapping of potentials and the translation into realistic supplies. Biomass Futures identifies the main factors 1 Readers that are interested in more detailed descriptions of our work can find the extensive deliverables report summarised here at: http://www.biomassfutures.eu/work_packages/work_packages.html 4

determining potential and supply of different biomass sources and based on these quantifies biomass potentials and maps them spatially. As part of this process we consider basic sustainability constraints that are informed by work under WP4. This task is central for the completion of other tasks in WP3 but also other WPs. An iterative process with several steps of internal and external review ensures that maps and potential are not only realistic but also appropriate for further analyses and assessments within Biomass Futures. Following this methodology, Biomass Futures delivers a spatially detailed and quantified overview of EU biomass potentials mapping the technical potentials of the different feedstocks at Nuts 2 level and synthesising the results in terms of economic supply estimates (costsupply curves). The availability maps, cost information and basic sustainability constraints are fed into an integrated economic land use model (GLOBIOM). By doing this, the static supply curves of individual feedstocks are brought into competition and contrasted with the demand scenarios. Only by integrating the static supply curves into a dynamic model of land use, issues of future land use change, trade, leakage, indirect land use effects and economic viability related to biomass supply can be assessed. In addition to the basic (supply related) sustainability criteria that already underlie the static supply maps, more complex sustainability constraints can be assessed in the integrated land use model. These include economic indicators (such as the development of food price indices) and sustainability issues related to land use change. This approach builds an important bridge between the static supply maps and the energy demand models of WP5. Figure 1 describes this interplay between the different work packages. Figure 1: Flow chart of Biomass Futures modelling work. Legend: Steps of the analysis 1.Market and demand analysis (WP2), 2.Availability maps and technical potential (WP3.4), 3.Cost supply curves for biomass feedstocks (WP3.4), 4.Demand projection by feedstock (WP 5), 5.Assessment of technical impacts of technology mix (WP 5), 6.Assessment of technical potential (WP 3.4), 7.Assessment of economic potential (WP 3.5), 8.Assessment of sustainable potential (WP 4, 3.5), 9.Scenarios of bioenergy demand (WP 5). Exchange with stakeholders on model assumptions in workshops (WP6, 7) includes the topics Demand (A), Availability (B), Sustainability (C), Supply (D), and Scenarios (E). The brought white arrows between the models symbolise the harmonisation of model assumptions. 5

2.3 List of deliverables D 3.1 Database with a systematic overview of the main characteristics of the main biomass resource studies and their main differences and similarities in terms of types of biomass feedstock assessed, and type of assumptions made. D 3.2 Report on the role of 4F cropping options in determining future biomass potentials, including sustainability and policy related issues. D 3.3 Spatially detailed and quantified overview of EU biomass potential taking into account the main criteria determining biomass availability from different sources. D 3.4 Biomass supply patterns for the different biomass types at EU27 and Member States levels. D 3.5. Report summarizing the main outcomes of the WP relevant for policy makers. 3 Findings 3.1 Review of biomass studies The methodology for the assessment of selected biomass studies foresees a categorization into different types of studies to make the studies more comparable. The review of BEE and Biomass Futures of the selected studies resulted in categories for biomass types (Biomass from forestry, Energy crops, Biomass from agricultural residues, Biomass from waste, Total resource assessments) and potential types (Theoretical potential, Technical potential, Economic potential, Sustainable potential) and method types (Resource focussed statistical methods, Resource focussed spatially explicit methods, Demand driven cost supply methods, Demand driven energy and/or economic modelling methods and integrated assessments). After categorization remaining differences between studies are likely to originate from different input data used, scenario assumptions made and tools applied. More categories were planned for comparing scenarios assumptions (especially on markets, technologies etc.). However, no further categorizations for a detailed comparison of studies could be achieved. This is mainly due to the fact that detailed assumptions were not always displayed by the authors of the respective studies. If provided, the assumptions were too distinct for each study so that a categorization was not appropriate. A major conclusion of the Biomass Futures review of biomass assessments at EU country level is that parts of the differences between studies can be explained by an appropriate categorization of studies according to method, biomass type and potential types. Remaining discrepancies can be assessed by comparing individual studies only but not in a systematic manner due to lack of information provided by authors and individuality of assumptions. The original data base compiled in the review and a short description of methods and results con be found at the Biomass Futures webpage. 3.2 Assessment of 4F crops The current market demand for biofuels is covered by conventional crops like oilseeds and grains with limited quantities from lignocellulosic energy crops being used for heat and electricity, mainly in cofiring plants (UK, Finland, etc.). The REFUEL full chain analysis has concluded that the most cost-effective way to meet the overall EU 10% target for renewable energy in transport by 2020 is by strong reliance on conventional biofuels. It is expected that during the next decade, tailored crop solutions will be more dominant in the bioenergy and biofuels markets as they can provide bioenergy products with characteristics that match the conventional (i.e. fossil based) end-products they replace. In addition, systems will make better use of existing bio-based resources through increasing their added value for fuel and products. Lignocellulosic crops have been under research & development for a while. During the last two decades several lignocellulosic crops have been under research but so far only miscanthus and reed canary grass are being cultivated in EU27. Research has focused on improving specific traits and meeting specific ecological and technology related requirements (i.e. adapt to arid climates, provide certain quality outputs, etc.). In the REFUEL study mentioned above, it is stressed that the introduction of 2nd 6

generation biofuels from lignocellulosic feedstocks is hampered by the high initial investment costs and corresponding biofuel production costs of the first installations. In the 4FCROPS project five perennial lignocellulosic crops had been selected for EU27: reed canary grass, miscanthus, switchgrass, giant reed and cardoon (the land allocation of five selected perennial crops in Europe that prepared in 4FCROPS presented in Figure 2). Switchgrass is the only of the selected crops that can be successfully cultivated in all climatic zones apart from the Nemoral zone due to the fact that there is a large variety of cultivars suitable for northern Europe (upland varieties) and for southern Europe (lowland varieties). Miscanthus has also been proposed for most climatic zones apart from Nemoral and Mediterranean South. Giant reed and cardoon introduced as very promising energy crops for Mediterranean north and south, while reed canary grass is proposed as an appropriate crop for Nemoral and Continental climatic zone. Atlantic north: Miscanthus and switchgrass Nemoral: reed canary grass Continental: miscanthus, reed canary grass, switchgrass Lusitanian: miscanthus, switchgrass Atlantic central: Miscanthus and switchgrass Mediterranean north: miscanthus, giant reed, switchgrass Mediterranean south: Giant reed, cardoon, switchgrass Figure 2: Climatic zones and perennial energy crops (source: www.4fcrops.eu) Reed canary grass and miscanthus were introduced in European agriculture and the area of cultivation presented in detail in Figure 3. Reed canary grass is being cultivated in Finland and Sweden, while miscanthus is being cultivated in Austria, Germany, UK, France and Poland. In 4FCROPS the yields of the five selected crops had been estimated in both agricultural and marginal land as well as when they cultivated with high and low inputs (Figure 4). Based on this analysis, it is expected that these crops will have the major share of the market from 2020 to 2030 as genetic improvements and breeding take long time to become evident in crop production. Currently, the perennial grasses are being studied in the framework of three European research projects entitled OPTIMA (working on miscanthus, switchgrass, giant reed, and cardoon), OPTIMISC (focused on miscanthus only) and GRASSMARGIN (dealing with switchgrass and miscanthus). It is expected that important findings on genetic improvement of all the crops studied will be realised at the end of the projects (end of 2015). 7

Nemoral Continental Atlantic central Atlantic north Lusitanean Mediterranean north Atlantic central Atlantic north Mediterranean north Mediterranean south Meditteranean south Yields (t/ha) 30000 25000 20000 15000 miscanthus reed canary grass 10000 5000 0 Austria Germany UK France Poland Sweden Finland EU27 Figure 3: Current area of cultivation of miscanthus and reed canary grass in EU27. 40 36 32 28 24 reed canary grass Marginal land & high inputs Marginal land & low inputs Agricultural land & high inputs Agricultural land & low inputs Switchgrass Giant reed Cardoon 20 16 12 8 4 0 Climatic area Figure 4: Biomass yields (t/ha) of the selected perennial energy crops in each climatic zone (on both agricultural and marginal land as well as with high and low inputs). 3.3 Assessment of availability In the Biomass Futures project we have built as much as possible on the state-of-the-art biomass assessment studies provided by BEE, to make our own spatially detailed estimates of biomass potentials in the EU. We have also used as much as possible the same biomass classification, definitions and conversions. The estimates are made for three sectors under which the biomass categories have been classified: agriculture, forestry and waste. Under these main sectors there are categories of dedicated biomass production such as biofuel crops, woody and grassy crops, stem wood production and byproducts and waste categorized in primary, secondary and tertiary levels. The estimates were also made for different scenarios (taking account of sustainability constraints to various degrees) that were 8

developed in the Biomass Futures project (details can be found in Deliverable D5.2: Scenarios for the analysis of biomass use in the EU in the time frame 2010-2030). Figure 5 and Table 1 provide a summary of the relative contribution every category can make to the total potential in actual, 2020 and 2030 in 2 scenario situations. It becomes clear that the agricultural residues and the forest roundwood and additionally harvestable wood and residues contribute the lion share of the potential. Towards the future the waste sector potential is anticipated to decrease, driven primarily by anticipated reduction in the total volume of municipal solid waste and more specifically the MSW that is sent to landfill (anticipated to fall from 22.1 Mtoe in 2010 to 13.3 Mtoe and then 11.2 Mtoe by 2020 and 2030 respectively). Growth in the contribution to overall potential is expected to come from the agricultural sector both in terms of use of residues and primary crop production especially from dedicated perennial crops. Currently the agricultural sector contributes approximately 31% of the total potential but this is anticipated to rise to over 40% in both the reference and sustainability scenarios by 2020 and 2030. Within the agricultural group the largest contribution is anticipated to come from manure and straw. Cuttings and prunings are smaller, but can be of great importance at regional level particularly towards the south of the EU. Table 1: Potentials (Mtoe) per aggregate class compared based on time period and scenario. Class of bioenergy resource Wastes a Agricultural residues a Rotational crops b Perennial crops b Landscape care wood a Roundwood production b Additional harvestable roundwood b Primary forestry residues a Secondary forestry residues a Tertiary forestry residues a Description of class ie examples of biomass sources included Grass cuttings, residues from food processing, biodegradable municipal waste, sludges, used fats and oils and used paper and board Inter alia manure, straw, other residues including prunings and cuttings from permanent crops Crops grown meet bioenergy needs such as maize for biogas and crops used as biofuel feedstocks such as rape. Dedicated energy crops providing lingo cellulosic material Residues ie cuttings etc from landscaping and management activities Stem wood from forests currently harvested Additional potential for the harvesting of stem wood within sustainable limits Logging residues, early thinnings and extracted stumps Residues from the wood processing industry ie black liquor, sawmills and other industrial residues Post consumer wood waste ie from households, building sites Current Availability 2020 Use reference scenario 2020 Use sustainability scenario 2030 Use reference scenario 2030 Use sustainability scenario 42 36 36 33 33 89 106 106 106 106 9 17 0 20 0 0 58 52 49 37 9 15 11 12 11 57 56 56 56 56 41 38 35 39 36 20 41 19 42 19 14 15 15 17 17 32 45 45 38 38 Total 314 429 375 411 353 a Denotes potential resources that could be deemed as waste materials or residues b Denotes potentials based on primary production either through agriculture or forestry systems to deliver resource 9

For the estimates in the waste sector an estimate was made for competing use, for as far as data available, and this part was subtracted from the potential. For the forestry part it should be clear however that the roundwood production would certainly only be partly available for bioenergy production as competing use with wood use is very large. Prices are generally far too high for use of this resource for bioenergy generation. In spite of this, it is clear that this resource cannot be completely ignored as already at this moment it is estimated that part of the roundwood production is used directly for bioenergy especially in countries in Scandinavia. Figure 5: Summary of present and 2020 EU biomass potential (KTOE) over categories. Figure 6 shows how the total potential within the reference scenario is split between the 27 Member States in 2020. Countries with the largest potential are not only the biggest countries, e.g. Germany, UK, France, Poland, but also the ones with a large forest area, population and/or agricultural sector. It is, however, considered that into the future country potentials may shift with a decline in the contribution of big countries like Germany and Italy to the EU potential. Conversely an increase would be expected France, Spain, Poland and Romania. Particularly under the sustainability scenario the contribution of Poland could increase significantly. Aside from this differences between relative country contributions across the scenarios are limited. 10

SE 8% SI 1% SK 1% UK 5% BG 1% AT 3% BL 2% CY 0% CZ 3% PT 1% RO 5% DE 14% DK 2% EE 1% PL 9% EL 1% NL 2% ES 7% LV 1% MT 0% LU 0% LT 1% IT 7% IE 0% HU 3% FR 15% FI 7% Figure 6: Distribution of total potential over the EU-27 in 2020 based on the reference scenario Biomass Futures combines the findings from the potential analysis with cost levels at which these are expected to be available. After all, the price-supply combination will eventually determine what the most interesting potential categories are. Figure 7 and Table 2 demonstrates visually the cost curves for biomass potential at both 2020 and 2030 for the reference and sustainability scenarios. The further specifies the figures. The underlying nature of these cost dynamics is briefly explained here for the EU as a whole. A significant proportion of the potential can be seen to cost below 200 Eur/Toe, 66% in the reference and 68% in the sustainability 11

scenario in 2020 dropping to 53% and 51% respectively by 2030. This potential consists mostly of materials from the waste sector plus primary residues from the agricultural sector, limited dedicated cropping potential, secondary and tertiary residues from the forest sector. From 200 to 400 Euro/Toe the additional potential is still significant in all scenarios. This range mostly consists of primary and secondary forestry residues and dedicated perennial crops, with rotational crops for biogas and biofuels starting to enter. From 400 to 600 Euro/Toe there are still significant levels of potential resource available. At this level additional harvestable round wood and the round wood production start to contribute significantly to the potential by 2020. This highlights the relatively high cost of using dedicates round wood supplies for bioenergy. Under the reference scenarios above 400 Mtoe more significant quantities of rotational biofuel crops become available it should be noted that under the sustainability scenarios these crops are not produced explaining the more limited tail in the high price ranges for the sustainability scenarios in Figure 7. Above 600 Euro/Toe practically no additional potential is found in the 2020 sustainability scenario, while in the 2030 sustainability scenario there is still potential in the round wood and manure categories. Higher prices because of inflation correction explain these differences between the 2020 and 2030 sustainability scenarios. In the reference scenario 2020 the potential in the price above 600 Euro/Toe consists mainly of biofuel crops and some manure sourced from regions where there is only a limited quantity of manure available. For 2030 under the reference scenario biofuel crops, round wood potential and manure are all present. 12

Figure 7: Cost-supply of biomass potentials at EU-27 level. Table 2: Overview of biomass potential (MTOE) per price class for 2020 and 2030 in the reference and sustainability scenarios for EU-27. 2020 2030 Reference Sustainability Reference Sustainability 0-199 Euro/Toe 284 259 217 179 200-399 Euro/Toe 58 49 55 49 400-599 Euro/Toe 79 72 87 79 600-999 Euro/Toe 4 0 51 46 >=1000 Euro/Toe 5 0 1 0 Total 429 379 411 353 Importantly it should be noted that patterns of supply cost at the national and regional level differ significantly from the EU average. This is reflected in the country specific cost-supply curves provided in deliverable D3.3. When interpreting these it should be kept in mind that prices represent averages. In Austria, for example, the biofuel potentials are cheaper than the additionally harvestable roundwood, roundwood and primary residues potentials from forestry, while in the majority of countries this order reversed with biofuel crops being most expensive. At the national level perennials generally fall around the mid point in terms of cost, but it depends on the country whether woody or the grassy perennials are cheaper. These differences in price levels particularly apply to manure and straw prices whose levels are very much determined by scarcity, hence increasing in regions of limited supply while prices are zero or very low in regions of excess supply. In a country like e.g. Italy the average national price is still relatively high, while huge excess manure production exists in the Po-valley(See Figures 8 and 9 underneath). The same applies to potentials; these are usually not evenly spread over countries. Especially for large countries like France, Germany, Poland etc., the national totals and averages can provide a misleading picture. However, for almost all potentials presented regional data are also available in this project. 13

Figure 8 Distributions of potential for manure, straw and pruning from perennial crops (Ktoe) in 2020. Summarising the key classes of agricultural residues.

3.4 Assessment of supply Typical for this task compared to other tasks in WP 3 but also other WPs is an orientation towards impacts outside EU. Additionally, the model accounts for a wider scope of sustainability issues, addressing (direct and indirect) land use change, environmental variables (water, nitrogen, GHG emissions), and economic effects (e.g. food prices). GLOBIOM includes additional biodiversity constraints on highly biodiverse land outside the EU based on WCMC information. Besides general parameters which limit land use change (no grassland conversion and deforestation in EU27 etc.), conversion of cropland and other natural vegetation to short rotation tree plantations is restricted. Through sensitivity analyses by changing assumptions on biofuel trade and other mitigation policies such as avoiding deforestation, GLOBIOM results are used to investigate competition between major land-based sectors (bioenergy, agriculture and forestry), potential leakage effects through land use and land use change as well as effects on food security and GHG emissions in order to give policy advice taking into account such global impacts. GLOBIOM is a global economic model that includes a detailed representation of the agricultural, bioenergy and forestry sectors. Its purpose is to provide policy analysis on global issues concerning land use competition between the major land-based production sectors. The model computes the global agricultural and forest market equilibrium choosing the land use and use pathway that maximises welfare i.e. the sum of producer and consumer surplus, subject to resource, technological and policy constraints. Within the model there are six key categories of land represented: unmanaged forest; managed forest; short rotation tree plantations; cropland; grassland; and other natural vegetation. These can be processed to provide an array of products from wood, resources for bioenergy, crops for food or fibre and livestock feed. Two scenarios were analysed: reference and sustainability. Under the reference scenario current requirements in terms of the RED sustainability criteria are applied i.e. requirements in terms of land use change and GHG reductions are placed on biofuels and bioliquids. Under the sustainability scenario it is assumed that requirements for the protection of the environment are extended and strengthened with all bioenergy resources being required to deliver a GHG saving compared to fossil fuel use of 70% by 2020 and 80% by 2030. In addition it is assumed that there is no conversion of highly biodiverse or high carbon stock land for the purposes of bioenergy. While GLOBIOM provides a good basis for identifying additional emissions in a given region associated with additional biomass demand, it is not able to assign an emissions back pack to biomass produced on a given parcel of land or distinguish between commodities produced for bioenergy and other sectors. As a consequence it is not possible to distinguish which elements of imported commodities are utilised for bioenergy and for food or feed. Therefore, in addition to the two common Biomass Futures scenarios we consider three different sensitivity runs where we change assumptions on biofuel trade to the EU and we allow or prohibit any deforestation outside Europe. 1. Base run: Biofuel trade Rest of the world (RoW)-Europe and deforestation outside Europe allowed 2. No deforestation run: Biofuel trade RoW-Europe allowed but deforestation prohibited outside Europe 3. No trade run: Biofuel trade Rest of the world (RoW)-Europe prohibited but deforestation allowed outside Europe Patterns of biofuel use are dramatically altered across the two scenarios. Under the reference scenario 70% of European ethanol demand and 66% of the European biodiesel demand are refined in Europe with the remainder imported from the rest of the world. Corn/maize represents the key source of European based bioethanol, while European biodiesel is produced exclusively from rapeseed. While cellulosic ethanol is not anticipated to form a significant proportion of EU produced biofuels global production is anticipated to rise to 798 PJ in 2020 and 2,473 PJ by 2030 (19 Mtoe and 59 Mtoe, respectively) comprising over 50% of total global production of bioethanol by 2030. Under the sustainability scenario it is considered that none of the European based biofuel production pathways can deliver on the 70% and 80% savings for 2020 and 2030 respectively. This has the consequence that total biofuel demand is imported from the rest of the world. In essence the EU would be exporting its entire biofuel footprint to the rest of the world. Under this scenario sugar cane derived ethanol and biodiesel from both palm oil and soybeans become increasingly important in terms of

delivering the demand for biofuels, a consequence of reductions in rape and corn based fuels due to limitations placed on European production. It should, however, be noted that the land released from biofuel production within the EU, while products are no longer utilised for domestic biofuel production, there remains significant exports of other agricultural products. The outcomes from the GLOBIOM analysis can be used to help understand the land use consequences of changing demand collectively for biomass for food, feed and fuel between 2000 and 2030. Under the reference scenario it can be seen that the total shift in demand for agricultural commodities would lead to an increase in global cropland of 37 Mha and of grassland areas by 47 Mha due to rising demand for agricultural crops and livestock products. This change is driven by the interplay of demand for bioenergy, food, and increase in population and development in GDP. Under this scenario cropland expansion occurs primarily in Sub-Saharan Africa and South/South-East Asia. Meanwhile grassland increased in Latin America and Sub-Saharan Africa. This expansion takes place primarily through deforestation (-105 Mha) or conversion of other natural vegetation (-48 Mha). While the reference scenario does not limit land use change in terms of conversion of highly biodiverse lands outside the EU, the sustainability scenario does. It also increases requirements in terms of GHG reductions from bioenergy, as a consequence the production footprint for EU bioenergy is essentially exported to the rest of the world. This results in significant shifts in terms of land use change including the types of crops grown, the extent of grassland conversion and the intensity of production. Under the sustainability scenario the global area of cropland is anticipated to be greater, expanding by an additional 2.3 Mha. This is a consequence of biofuel production from rape and corn declining with other, non-eu focused, feedstocks favoured; however, there is simultaneously a decline in usable byproducts for animal feeds. As a consequence additional crops are grown as feed. The extent of loss of high biodiversity areas under the reference scenario is anticipated to be extensive. Up to 35.7 Mha of high biodiversity land would to be converted by 2030. This represents 7% of the total area identified as highly biodiverse in 2000. Losses are largely driven by deforestation and the loss of highly biodiverse primary forest (-19.2 Mha); although significant additional losses are anticipated from highly biodiverse grasslands (-6.8 Mha) and other natural land deemed high in biodiversity (-9.7 Mha). Almost one fifth of the total deforestation (105 Mha) anticipated up to 2030 would take place on highly biodiverse primary forest. While conversion to cropland is seen to contribute to loss of highly biodiverse primary forest, it is conversion to grassland that represents the most significant threat (responsible for approximately 80% of direct change). Key to understanding biodiversity consequences are the sensitivity runs preventing any deforestation globally. The prevention of deforestation precludes the conversion of highly biodiverse primary forest, but consequently there is a knock on impact in terms of conversion of other natural vegetation (+3.1 Mha). Despite this rebound impact, importantly the total loss of areas deemed highly biodiverse declines when deforestation is prevented a reduction of by 58% is seen meaning losses are reduced to 15.1 Mha. Global GHG emissions from agriculture and land use change are seen to steadily increase under the reference scenario, primarily as a result of rising emissions from deforestation and land use change (Figure 8). Under the reference scenario total emissions by 2030 reach 8,078 Mt CO 2 eq. The sustainability scenario places limits on land use change through the application of criteria protecting high biodiversity areas. As a consequence of this, differing patterns of crop use leading to less intensive production and reduced nitrogen inputs overall emission levels in 2030 are 381 Mt CO 2 eq. lower than under the reference scenario. It should, however, be noted that a rise in total emissions between 2000 and 2030 of over 2,000 Mt CO 2 eq is still anticipated under the sustainability scenario. The application of sustainability constraints, in terms of land use change in high biodiversity areas, had a relatively limited impact on global GHG emissions. In contrast preventing deforestation globally had by far the most profound impact on GHG emissions seen within the analysis. Under the reference and sustainability scenarios preventing deforestation reduced global GHG emissions by 19% and 20% respectively. Emissions from land use change fall from 1,306 to 219 Mt CO 2 eq. when deforestation is prevented under the reference scenario (Figure 9, this demonstrates the scale of reductions in GHG 16

Mt CO2 eq emissions between the base runs and no deforestation runs of both scenarios). It should, however, be noted that even under the no deforestation, sustainability scenario net GHG emissions increased by 18% compared to 2000 due to changes on the demand side. 9.000 8.000 7.000 6.000 5.000 4.000 3.000 2.000 1.000 Biofuels Livestock sector Crop sector other LUC Deforestation Total GHG 0-1.000 2000 2010 2020 2030 Figure 8: Development of annualized average GHG emissions in the Reference scenario in the rest of the world in Mt CO 2 eq. 105% 100% 95% 90% 85% 80% 75% 70% 2000 2010 2020 2030 Reference no biofuel trade Sustainability Reference no deforestation Sustainability no deforestation Figure 9: Development of total GHG emissions compared to the Reference scenario (100%) The graph demonstrates the scale of reductions in global GHG emissions associated with preventing deforestation globally compared to the base runs of both the reference and sustainability scenarios. 17

4 Conclusions Workpackage 3 of the Biomass Futures project looked at a wide range of biomass supply feedstocks, their production systems, sustainability constraints and resulting potentials and impacts. The following conclusions can be drawn from this work: Domestic potentials The waste potential for biomass will decline in the future. The largest increase in potential can be expected from agricultural residues and perennial crops on released agricultural lands. Largest cheap potential is currently in waste and residuals from agriculture. In sustainability scenario no 1st generation biofuel crops in EU (stricter GHG mitigation target not reached, because of iluc). Residuals from agriculture also have important potential, now still underutilized, especially in regions where there is much excess manure (no fit with technological development expectation). Perennial crops form potentially a large and not too expensive resource. Primary and secondary forestry residues potentials are very significant, but still expensive because they are not recovered and/or many competing uses already exist. Towards 2020 an increase in cheaper resources and towards 2030 overall decline of resources is expected. Domestic potentials under sustainability constraints Domestic perennial crops are potentially less affected by iluc, but are only to be utilised if 2nd generation technologies are to be utilised. Sustainability constraints on cropping are significant both inside and outside EU and will have important effects on availability of biofuels. Sustainable biofuels need stimulation of high efficient technologies based on woody biomass. Imports and sustainability constraints Satisfying European bioenergy targets in 2020 and 2030 will require a substantial increase in imports of agricultural commodities into the EU from the rest of the world. As a consequence EU mandates will have an effect on global land use patterns, both in terms of cropland and grassland area, with knock on impacts upon supply chains for the livestock sector. There is a clear need to focus studies on estimating the iluc per land type inside and outside EU. Global production and sustainability Global GHG emissions from agriculture and land use change are anticipated to rise significantly up to 2030 due to various drivers, among others: GDP and population, diet shifts and also bioenergy demand. The application of sustainability criteria purely to the biofuels or bioenergy sectors is considered to be insufficient to be able to avoid bioenergy related direct and indirect emissions. The most effective approach to mitigating land use change and associated GHG emissions is considered to be the application of direct land use policies that limit deforestation and biodiversity loss. To be effective these policies would need to target total agricultural production. 18