THE COST OF MEETING A 30% EMISSION REDUCTION TARGET IN EUROPE

Transcription

1 THE COST OF MEETING A 30% EMISSION REDUCTION TARGET IN EUROPE 16 March 2012 / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / Strictly no copying, forwarding, shared passwords or redistribution allowed without prior written permission of Bloomberg New Energy Finance. For more information on terms of use, please contact sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout.

2 CONTE EXECUTIVE SUMMARY 1 SECTION 1. INTRODUCTION Scope of report EU emissions target... 3 SECTION 2. RESULTS Overview of emissions reduction target Scenarios... 8 SECTION 3. METHODOLOGY Simplifications used in analysis Modelling approach Calibration of key sectors of the renewable energy target Allowances and trading Caps and burden shares cost Fuel prices APPENDIX: DETAILED RESULTS BY COUNTRY 26 ABOUT US 49 Strictly no copying, forwarding, shared passwords or redistribution allowed without prior written permission of Bloomberg New Energy Finance. sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout.

3 EXECUTIVE SUMMARY Current European Union policy sets out targets and mechanisms to achieve a 20% reduction in greenhouse gas emissions from 1990 levels by In recent years however there have been strong calls for increasing this target to 30%, with deeper cuts beyond The purpose of this report is to calculate the costs for the EU as a whole and each member state of moving to tighter emission reduction targets under different scenarios, taking into account the position of member states in the EU Emissions Scheme. Importantly, the work does not attempt to quantify the benefits of reducing greenhouse gas emissions in Europe. The analysis uses Bloomberg New Energy Finance s model of the European energy and emissions system, which assesses the first and second-order economic effects that arise through carbon markets, technology improvements and electricity prices. The model uses exogenous forecasts for individual sectors and simulates the uptake of low carbon technologies through the least cost option to achieve the emissions target for the EU as whole. The model assumes that abatement occurs when and where it is cheapest subject to policy or regulatory constraints - so that Member States will only undertake abatement if the marginal cost of the abatement is less than the cost of purchasing allowances from elsewhere. Main results In the simplest scenario, we estimate that a change from a 20% to a 30% emissions reduction target for the EU as a whole would result in an additional cost of 3.5bn per year up to This figure represents the additional cost over and above existing policies that are in place, for example renewable energy targets and building standards, and assumes that both the Emissions Scheme () and Non-Traded Sector () make maximum use of their allowances to import CERs under the 30% target. s vary significantly between Member States but remain a small proportion of GDP at only 0.03% for the EU Including the cost of meeting the renewable energy target, the average annual cost of meeting the 20% target is 23.3bn and 26.7bn for a 30% target. Our cost estimates include investment in clean technologies between 2011 and 2020 compared to a baseline business-as-usual (BAU) scenario with no emissions reductions targets. Our estimates also do not include any co-benefits of emissions reductions such as improvements in resource efficiency, energy security or air quality. In general, the wealthiest fifteen Member States pay the vast majority of the costs of meeting targets. By selling emissions allowances, several of the lowest-income Member States are able to generate net profits. Under the burden sharing assumption proposed by the European Commission (COM (2010) 265) which assumes some 65% of the burden of moving to a 30% target is placed on the sector, abatement costs in the increase more than those in the non-traded sectors. Emissions caps in addition to the renewable energy target cause the power sector to switch from carbon-intensive coal to efficient gas power, whose higher operating costs increase wholesale electricity prices. Countries with established and carbon-intensive power sectors will have to spend the most in order to meet the emissions target in particular Germany, Italy, Spain and the UK. Higher electricity prices then cause abatement in other sectors, such as buildings, and a slight shift away from electrically powered vehicles. Without additional policy frameworks, vehicles 1 See European Commission documents COM(2010) 86 and COM(2010) 265 for details of underlying policy 2 All costs in this report are presented as annual averages for in 2011 Euros average GDP figures, source: European Commission sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 1 of 49

4 and heating systems will remain largely dependent on fossil fuels until after 2020, though a modest rise in fuel efficiency is projected. The renewable energy target alone is projected to deliver around 55% of the emissions reduction required for a 20% target. The remaining annual cost of meeting the 20% emissions target will be about 4.6bn, only 0.04% of GDP for the EU The majority of this cost will be borne by the power, buildings and transport sectors. The importing of carbon credits from outside Europe and purchasing of allowances from surplus countries is a significant part of the total costs of higher-income Member States, such as Germany, Italy, France, Spain and the UK. Lower-income Member States such as Romania, Bulgaria and the Czech Republic are likely to gain significant revenues from selling allowances to other States. Note that when the total trading costs are summed across the whole EU-27, the net value of allowances traded between countries is zero. At the EU level cost of emissions trading is only the value of imported CERs. Under a 30% target the carbon price in the rises to 33/t, from 11/t under a 20% target. 5 The equivalent prices in the are 8/t under both targets. The carbon price in the is unchanged under the 30% target because an additional CER import limit for the of 866Mt is assumed up to No additional CER import limit is assumed under the 25% target which increases the carbon price in the in this scenario. Table 1: EU-27 annual average cost of the EU renewable energy and emissions targets for the period (2011 billion) Emissions Reduction Target annual cost (including renewable energy target) as % of GDP relative to 20% target Carbon Price ( / tco2e) 20% % N/A % % % % Sensitivities A key assumption in the modelling is the degree to which the market foresees the future costs of compliance under a declining cap. A later clearing date results in higher EUA prices and hence more abatement as the has foresight of more ambitious targets after This effectively raises the level of abatement effort and investment required before 2020, with annual abatement costs for the and to meet a 20% target increasing from 3.2 billion to 4.4 billion as the clearing date is extended from 2020 to Another key assumption is fuel prices. As fuel prices rise, abatement costs in the increase while those in the decrease. Overall, tightening the target is slightly more expensive for lower fuel prices. Achieving the renewable energy target by 2020 will cost the EU-27 around 18.7 billion each year ( ). This cost will rise if fossil fuel prices fall, and vice versa. For consistency the analysis has used GDP forecasts in line with the European Commission s PRIMES model in If the analysis used more recent (lower) projections of GDP growth, the costs of meeting both 20% and 30% targets, along with carbon prices would be lower than those shown in this report average GDP figures, source: European Commission 5 Carbon prices are presented as 2020 forecast prices in 2011 Euros sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 2 of 49

5 SECTION 1. INTRODUCTION 1.1. Scope of report This report presents emissions and cost projections for the European Union (EU) in meeting its greenhouse gas reduction target over the years The analysis has been conducted by Bloomberg New Energy Finance using its model of abatement costs and carbon markets covering the EU Emissions System () and non-traded sectors (). The abatement costs presented in this report include both the direct and indirect impacts of emissions reductions targets. The analysis also includes the effects of emissions trading, which significantly alters the cost burden across Member States. The main objective of this analysis is to assess the impact of increasing the EU greenhouse gas emissions target from a 20% reduction from a 1990 baseline by 2020 to a 30% reduction 6. There are currently few detailed estimates of the cost to the European economy of meeting the 2020 target. In this report costs are defined as the incremental costs of meeting the emissions reduction target compared to a business-as-usual ( BAU ) case where the target does not exist. The cost of meeting the EU renewable energy target has been separated from the other abatement costs as it is the same for most scenarios. This analysis also assesses the impact of a number of other parameters on the emissions and costs to Member States: allowances clearing date (2020, 2028) Fossil fuel prices (low, central, high) burden share between countries (current, alternative 1, alternative 2) It is important to note that this analysis does not consider the long-term costs or benefits of emissions reduction policies beyond The EU policies and targets which are analysed in this report have been implemented in order to minimise the overall costs of climate change over the long term. For consistency the analysis has used GDP forecasts for European countries taken from the European Commission s analysis using the PRIMES model in The European average GDP growth rate assumed is 2.29% between 2011 and 2015 and 2.13% from 2016 to More recent projections show lower growth than these earlier projections. For example, Bloomberg New Energy Finance s latest projections assume a growth rate of only 1.7% between 2011 and If the analysis used these more recent projections the costs of meeting a 30% reduction target by 2020 would be lower than those shown in this report EU emissions target The 27-country EU is, as a bloc, one of the world s largest emitters of greenhouse gases, both in terms of annual emissions today and in historic total emissions. As part of its climate and energy policy, the European Commission has legislated to reduce EU greenhouse gas emissions by 20% by 2020 from a 1990 baseline, potentially as part of a long-term framework to reduce carbon emissions by 80% by The cornerstone of the EU s carbon-reduction policy is a cap-and-trade programme, which started in This Emissions System () currently covers the power and heavy industry sectors, which today account for approximately 40% of EU greenhouse gas emissions, and was 6 See European Commission documents COM(2010) 86 and COM(2010) 265 for details of underlying policy Climate and Energy Package: European Council documents 17271/1/08 Rev 1, 17215/08 sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 3 of 49

6 expanded in 2012 to include flights to and from Europe. The cap-and-trade programme imposes pollution limits on more than 11,000 installations in the region and allows those who emit less carbon dioxide to sell their surplus allowances. The EU includes Norway, Iceland and Liechtenstein in addition to the EU-27. These three countries are included for modelling purposes but do not otherwise feature in this report. For sectors not covered by the EU, referred to as "Non-Traded Sectors" (), the emission targets are laid out in the 2009 Effort Sharing Decision which will take effect from We assume here that some extent of cross-border and cross-sector trading of emissions between will become possible in due course. Emissions associated with land use, land use change and forestry (LULUCF) are not bound by any targets and are beyond the scope of this report. Although 1990 is the baseline year for the Kyoto Protocol, 2005 is used for setting detailed targets due to the improved quality and scope of data available for that year. The 20% greenhouse gas emissions reduction target equates to a 14% reduction compared to 2005 due to a drop in carbon emissions between 1990 and To achieve a 14% reduction from 2005 levels by 2020, the European Commission has set reductions at 20% for the stationary sources in the and 9% for the emissions, taking account of the changes in sector coverage occurring in 2012 and 2013 (see Table 2). If the EU target were increased to 30% from 1990 levels, equivalent to a 25% reduction from 2005 levels, then the EU and reductions for static installations would be 34% and 16% respectively, assuming abatement is undertaken in the same proportions. Table 3 shows the equivalent emissions caps for these percentage reductions split between the and. Note that these numbers are based on a simplified treatment of the sector coverage. Aviation joins the from the in 2012, as do many non-co2 greenhouse gases such as perfluorocarbons (PFCs) from aluminium production in 2013, but in our analysis these sectors are assumed not to be in the prior to this year. Overall targets for the have been adjusted to account for this simplification and ensure that the overall economy-wide targets are met. Table 2: Summary of EU 2020 emissions targets (adjusted to account for simplified coverage) Overall Target (1990 Baseline) Overall Reduction Target (2005 Baseline) Reduction Target (2005 Baseline) Reduction Target (2005 Baseline) 20% -14% -20% -9% 25% -19% -27% -12% 30% -25% -34% -16% Table 3: EU-27 Emissions and 2020 Caps Annual emissions (Mt CO2e) * % change from Emissions N/A 2020 BAU projection % 2020 cap for 20% target % 2020 cap for 25% target % 2020 cap for 30% target % Source: European Commission / Bloomberg New Energy Finance *EU and total emissions figures include a broader scope of aviation emissions than the overall EU emissions reduction targets. However, as they are part of the EU, these emissions and the costs associated with reducing them have been assigned to the EU. sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 4 of 49

7 SECTION 2. RESULTS 2.1. Overview The Results section shows the key data produced by the model at an EU level, with data at a Member State level shown in the Appendix. We first show the cost of increasing the EU greenhouse gas emissions target from a 20% reduction by 2020 to a 30% reduction (from a 1990 baseline). We define the cost of meeting the emissions reduction target as the incremental cost compared to a business-as-usual ( BAU ) case where there are no emissions targets and no trading. The BAU includes the effect of existing policies and the EU renewable energy target. A number of parameters on the emissions and costs to Member States are also assessed by modelling a range of scenarios: allowances clearing date (2020, 2028) Under the later clearing date of 2028, an evertightening emissions cap after 2020 is assumed. The market s foresight of tighter annual caps after 2020 causes a greater level of abatement to be undertaken before this date, in order to bank credits into the future and minimise costs overall. The 2020 case therefore models a market with less foresight, compared to the 2028 case. Fossil fuel prices (low, central, high) The impact of fuel prices (coal, oil and gas) on the cost of increasing the emissions reduction target is assessed. burden share between countries (current, alternative 1, alternative 2) - Burden Sharing Agreements are varied, which changes the balance of effort required between countries in the. For each scenario, three main costs are shown: Internal abatement costs are defined as the sum of the annualised capital costs and the operational costs compared to the BAU, including fuel, power, labour and other costs of production. They include the difference in capital cost of lower-emitting technologies, such as from coal to gas power generation, and changes in operational costs, for example due to changes in electricity prices or choice of fuel. When calculating abatement costs, the price of carbon is excluded because it is assumed to be a transfer within the country. Similarly, electricity costs are netted out of operational costs because we assume they flow from one sector to another within a Member State. costs for individual Member States as shown in the Appendix may be positive or negative, depending on the technology choices made in each scenario compared to the baseline. Over the whole EU-27, abatement costs are always positive. costs are based on the number of allowances traded between Member States multiplied by the carbon price. States may also import CERs into the in all scenarios, up to a pre-defined limit. Imports into the are only used for the more ambitious 30% targets, as we assume lower targets can be met solely through internal abatement. When summed over the whole EU-27, the total trading cost is equal to the value of CER imports, as the net cost of trading allowances between member states is zero. The cost of meeting the renewable energy target (EU-27 annual average of 18.7 billion) has been separated from the other abatement costs, in order to see more clearly the effect on costs of moving to a tighter emissions target. The cost of meeting the renewable energy target increases by about 15% overall in the low fuel price case and decreases by 20% overall for high fuel prices. These costs are taken into account in our individual scenario figures. The percountry costs of the target are shown in the Appendix Table 17. All costs are shown in real 2011 Euros, assuming an inflation rate of 2.5%. sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 5 of 49

8 For each year in any given scenario, the model calculates the carbon price that would create equilibrium between the demand for abatement (the difference, over the eight-year market horizon, between expected emissions and emissions targets) and the supply of abatement, which is determined by the relative cost and emission intensity of technologies. The carbon price is usually higher than that of the, reflecting the tighter targets in the. In addition to costs, we also show projected greenhouse gas emissions, alongside historical and BAU values for comparison. Our modelling assumes that the annual emissions caps are always achieved, but due to the ability to bank unused allowances for future use the actual emissions in a given year may be higher or lower than the cap level. When discussing groups of countries, we refer to the group of 15 higher-income Member States (H-15) and 12 lower-income Member States (L-12). H-15 is defined as Austria, Belgium, Germany, Ireland, Greece, Spain, France, Italy, Luxembourg, the Netherlands, Cyprus, Finland, Sweden and the UK. L-12 includes Bulgaria, Romania, Latvia, Lithuania, Poland, Slovakia, Estonia, Hungary, Czech Republic, Malta, Slovenia and Portugal of emissions reduction target Summary The summary results of the analysis are shown in Table 4. This shows relatively little additional effort will be required to meet a 20% emissions reduction target in addition to that required for the renewable energy target, around 4.5 billion per year in addition to the renewable energy cost of 18.7 billion. The use of surplus Phase II allowances in all scenarios reduces the need to make emission reductions, so actual abatement is lower than it might be otherwise. Table 4: EU-27 annual average cost of the EU renewable energy and emissions targets for the period (2011 billion) Emissions Reduction Target annual cost (including renewable energy target) as % of GDP relative to 20% target Carbon Price ( / tco2e) 20% % N/A % % % % As the emissions reduction target increases from 20% to a 30%, the annual average cost increases by about 15% from 23.2 billion to 26.7 billion, including the cost of the renewable energy target, due to changes in the abatement and trading costs. Much of the additional cost of abatement originates in the power, buildings and transport sectors. These costs are a relatively small proportion of GDP; 0.21% for a 20% target increasing to 0.24% for a 30% target. Excluding the cost of the renewable energy target, the annual average abatement and trading cost is 4.5 billion for the 20% target and 8.0 billion for the 30% target. As the emissions reduction target increases, the carbon prices for and rise in order to meet the greater demand for abatement (from 11 at a 20% target to 33 for a 30% target in the ), driving low carbon investment. Figure 1 shows emissions in 2020 for scenarios with different emission reduction targets, along with BAU (which includes the renewable energy target) and historical emissions for comparison. Between 2010 and 2020, the reduction in emissions is small in the BAU case while the emission reduction targets cause a major improvement on the BAU over this period. Annual emissions in 2020 may exceed emissions caps in that year due to the use of banked credits and offsets (CERs). sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 6 of 49

9 Figure 1: EU-27 emissions for different reduction targets (MtCO2e, % reduction from 1990 emissions, excluding CER imports) 6,000 5,000 Historic 2020 Annual Projection 10% 13% 17% 20% 21% 4,000 3,000 2,000 1, BAU 20% target 25% target 30% target /UNFCCC. Figures include international aviation. In the following results sections, the cost of meeting the renewable energy target is separated from the other costs. breakdown As the emissions reduction target increases from 20% to 30%, abatement costs increase more than those of the (see Table 5). Much of the expense of meeting the targets is already captured in the cost of the renewable energy target, which is part of our BAU. Also, most sectors (industry and power) have a surplus of EUAs from the recent economic downturn which they can bank forward and use to meet their targets. However, when these banked credits are exhausted under more stringent targets, abatement must be undertaken, causing costs to rise. The tightening of the emissions target prompts a rise in carbon price for the, whose sectors undertake more abatement as a result. The abatement costs for the scenarios increase from 1.5 billion (20%) to 2.6billion (25%) and 3.4 billion (30%). in the power sector involves building gas power stations rather than cheaper but more carbon-intense coal or oil. This increases the operating costs of the power sector, and therefore the price of electricity. Countries with established and carbon-intensive power sectors will have to spend the most in order to meet the emissions target, particularly Germany, the UK, Italy and Spain. The is dominated by the buildings sector, where electricity forms a large part of the operational costs compared to sectors. As electricity prices rise, the operational costs rise. Despite electric heating being more efficient than fossil fuel options such as oil and gas, the buildings sector favours abatement options such as insulation and double glazing due to the higher electricity price. The sector is not typically exposed to a high enough carbon price to encourage a switch to electric heating. It is a similar story in the transport sector, where relative operating costs mean hybrid cars are favoured over purely electric vehicles. The 30% case is the only one for which the target for total abatement exceeds the number of CERs it may import. As a result, we only model CER imports in scenarios with 30% overall targets. This means that abatement costs decrease in the bottom row of Table 5 due to the ability to offset emissions instead of undertaking abatement. The imports CERs to a value of 569 million per year, bringing the total cost to about 8.0 billion per year. sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 7 of 49

10 Table 5: Breakdown of EU-27 annual average costs for 20%, 25% and 30% emissions reduction targets (2011 billion) Emissions Reduction Target abatement costs abatement costs costs* Buildings Power Industry Subtotal Transport Other Sub-total & trading total Renewable energy target 20% % % Note * only includes importing of carbon credits from outside Europe. Assumes 2020 market clearing date, and central fuel price projections. costs Because of the relatively easy targets in the 20% case, the carbon prices for both and are fairly low ( 11 and 8 respectively). On a country level, there are large trading deficits for Germany, the UK and Italy in particular, while Romania, Bulgaria and the Czech Republic have the biggest trading windfalls, in part due to surplus Phase II allowances. We calculate that the total annualised cost as a percentage of GDP 9 varies considerably between the high income and low income Member States. Including the renewable energy target the costs are 0.22% for H-15 and 0.06% for L-12, at a 20% target (see Table 6). By raising the target to 30%, the cost as a proportion of GDP only rises moderately for the H-15 to 0.24%, while the L-12 actually benefit from tighter targets mainly due to the selling of allowances (see tables in Appendix for a breakdown by Member State). Table 6: Annual average cost as a percentage of GDP for the H-15 higher income and L-12 lower income Member States for the period Emissions Reduction Target cost (incl. Renewable Energy Target) H-15 L-12 relative to 20% target cost (incl. Renewable Energy Target) relative to 20% target 20% 0.21% N/A 0.06% N/A 25% 0.23% 0.02% 0.08% 0.02% 30% 0.24% 0.03% -0.02% -0.08% 2.3. Scenarios allowances clearing date The tables below show the difference in costs between 20% and 30% targets for an clearing date of 2020 (Table 7) and 2028 (Table 8). A later clearing date means that even though the model does not run past 2020, the has foresight of more ambitious targets in those years. In order to minimise total costs, installations in the undertake more abatement prior to 2020 in order to bank allowances for the post-2020 period, softening the requirement to make emission reductions in those later years. This effectively raises the level of abatement effort and investment required before 2020, so we see greater total abatement costs for scenarios with a later clearing date, with abatement costs increasing from 1.5 billion (2020) to 2.9 billion (2028) at a 20% target. Our analysis shows that the average carbon price would increase as the clearing date is extended, from about 11 (2020) to 26 (2028) at a 20% target, and from 33 (2020) to 44 (2028) for a 30% target. Since there is no market after 2020, the difference in costs between Table 7 and Table 8 is prompted by behaviour only. As the clearing date becomes later, the cost difference of average GDP figures, source: European Commission sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 8 of 49

11 abatement between 20% and 30% targets increases. The slightly higher carbon prices in scenarios with later clearing dates (Table 8) drive a greater level of abatement. At a Member State level, when the carbon price is lower, most abatement takes place in L-12 Member States. These countries have the cheapest options available to them for reducing emissions over the period , both by improving existing dirty installations and by building ones cleaner than they might have done in the BAU. This cheap abatement is limited, however, so as the carbon price rises, a larger proportion of abatement comes from members of the H-15 Member States. Countries with a substantial fraction of electrically heated buildings such as Italy and France have a greater increase in operating costs as the market horizon lengthens to As the carbon price rises it also becomes more cost effective for Poland and the Czech Republic to reduce their emissions and, overall, profit from selling allowances. Table 7: EU-27 annual average cost for 20% and 30% emissions reductions, 2020 clearing (2011 billion) Emissions Reduction Target trading trading Renewable energy target Annual (% of GDP) Carbon Price ( / tco2e) 20% % % % 33 8 Difference % 22 - Table 8: EU-27 annual average cost for 20% and 30% emissions reductions, 2028 clearing (2011 billion) Emissions Reduction Target trading trading Renewable energy target Annual (% of GDP) Carbon Price ( / tco2e) 20% % % % Difference % 18 - When calculating trading costs we count the value of credits banked into the Phase IV (post- 2020) period as revenue, since they are effectively sold into the future. As the clearing date is extended from 2020 to 2028, the volume of trading increases between countries because of the increased pressure on abatement. As mentioned previously, the sum of trading costs over the EU-27 is equal to the value of CER imports less the value of banked allowances in Under the 2028 clearing date assumption, both and import a higher value of CER credits due to the higher carbon price. In the, however, this extra cost is offset by the value of allowances banked for use after For a 2028 clearing date and 30% target, a net 550Mt of allowances are banked in Phase IV, which exceeds the value of CERs bought before 2020, therefore the average annual trading cost for the EU-27 is negative, at million. Figure 2 shows the emissions in 2020 for scenarios with different clearing dates. The scenario figures are broadly indicative of the level of abatement undertaken in annual emissions by 2020 the emissions are lower (percentage reductions are higher) for scenarios with later clearing dates, since installations here are banking allowances for use beyond sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 9 of 49

12 Figure 2: EU-27 emissions for different reductions targets and clearing dates (MtCO2e, % reduction from 1990 emissions, excluding CER imports) 6,000 5,000 Historic 2020 Annual Projection 10% 13% 17% 21% 19% 23% 4,000 3,000 2,000 1, BAU 20% target, clearing % target, clearing % target, clearing % target, clearing 2028 /UNFCCC. Figures include international aviation. Fossil fuel prices This section looks at scenarios in three fossil fuel price cases (low, medium and high) with emission reduction targets of 20% and 30%. As explained in the Methodology section, we match the fossil fuel prices for the scenarios with those for the respective BAUs. This allows the abatement costs due to the emissions reductions policies to be distinguished from changes that would be prompted by the fuel price alone. Central price projections for gas, coal and oil are based on European Commission data. For details as to how high and low fossil fuel prices have been generated, see section 3.8. The cost of moving from a 20% to 30% target is a balance of several factors which are sensitive to targets and fuel prices. The difference between abatement costs for 20% and 30% targets is slightly lower for the central fuel price case than for high or low fuel prices. This is because of the trade-off between the various forms of abatement in the, and is partly a result of our modelling assumptions. In all three fuel price cases, the same respective emissions caps are met, but overall an increase in fuel price naturally steers choices away from fossil fuels. This means total costs decrease with an increase in fuel price. This difference is a relatively small proportion of total costs since we assume a certain amount of renewable power build to meet the renewable energy target in the BAU. abatement costs increase as the fuel price increases (from 584 million at low fuel prices to 2189 million for at high fuel prices for a 20% target), while abatement costs decrease. In the scenarios we have considered, the price of gas is more volatile than those of oil and coal. As fossil fuel prices rise, it becomes less cost-effective to switch to gas for power generation, so there is a higher proportion of more carbon-intensive coal and oil generation. As a result, abatement must be provided by alternative means, pushing up the abatement cost in the industry sectors. On the other hand, this means electricity prices are marginally lower, so in the, electricity-intensive abatement measures are more attractive with high fuel prices leading to a slight fall in abatement cost. We see a greater penetration of electric vehicles and electric heating in these cases. sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 10 of 49

13 Table 9: EU-27 annual average costs, low fossil fuel prices (2011 billion) Emissions Reduction Target abatement cost abatement cost trading trading Renewable energy target annual cost (% of GDP) Carbon price ( / tco2e) 20% % % % Difference % 21 2 Table 10: EU-27 annual average costs, central fossil fuel prices (2011 billion) Emissions Reduction Target trading trading Renewable energy target annual cost as % of GDP Carbon Price ( / tco2e) 20% % % % 33 8 Difference % 22 - Table 11: EU-27 annual average costs, high fossil fuel prices (2011 billion) Emissions Reduction Target abatement cost abatement cost trading trading Renewable energy target annual cost as % of GDP Carbon price ( / tco2e) 20% % % % 36 4 Difference % Note all the above results assume a 2020 market clearing date. An extreme case is seen in Table 9 (low fuel prices), where for the 20% target the carbon price ( 9) exceeds the price ( 7). In the, the low gas price means caps are relatively easy to meet as gas fired power stations are run in preference to higher carbon emitting coal stations. In the, by contrast, gas is the higher carbon emitting fuel source other options include electric heating or investing in more efficient buildings. In the buildings sector therefore lower gas prices relative the central case, cause a rise in carbon emissions, so a more aggressive carbon price is needed to drive abatement. As the fuel prices increase, the higher carbon price prompts a greater volume and value of carbon trading. distributions between Member States also change with fuel prices. The biggest changes are seen in countries for which the choice of fuel switching in the power sector is marginal and therefore easily tipped in favour of gas by a relative change in prices. Changes are greatest for Germany and the UK and also for power sectors with much coal and oil generation such as those of Poland and Italy. France, Austria and Sweden exhibit smaller differences in abatement cost with fuel price because these countries are, at the outset, less carbon-intensive in both their power and buildings sectors. The cost of meeting the renewable energy target is also affected by the fuel prices, being marginally more expensive at lower fossil fuel prices. The total trading cost, summed over the EU-27, is equal to the annual average value of imported CERs. As mentioned in the Methodology section, we assume for all scenarios with CER imports to the that the CER price scales with the carbon price. Therefore the total trading costs are a function of that scenario s carbon price. Individual Member States trading costs change substantially between scenarios, based on the carbon price and the energy mix used by each Member State, which affects the amount of costeffective abatement available at that fuel price. Germany, Italy and the UK typically have higher trading costs, as their industrial sectors are already relatively efficient, so to meet targets it is sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 11 of 49

14 usually more cost-effective to buy EUAs from other countries. Poland and Romania, by contrast, may reduce the carbon intensity of industry for more modest costs so a high carbon price allows them to sell EUAs for a profit. It is worth noting that we only investigate the costs of abatement incurred up to Investment decisions made during this time will, however, affect overall costs over a longer time-frame. Over longer periods, there is a possibility that higher fossil fuel prices may lead to lower carbon prices and vice versa. Note that the relationship between fossil fuel prices and abatement costs is also dependent on the relative changes in fuel prices as much as absolute prices. If coal or oil prices increased at a faster rate than gas prices, switching to gas from coal would require a lower carbon price to become cost-effective. Note also that the lack of demand elasticity in our model may result in an over-estimate of abatement costs for higher fossil fuel prices. burden share These scenarios are based on varying the burden sharing agreements so that a different percentage reduction in emissions is required from the Member States Non Traded Sectors. The standard burden share used in the analysis is in line with the European Commission s Effort Sharing Decision of 2009, which we therefore term the ESD burden shares. In the Alternative 1 scenario, the burden share is in proportion with the GDP per capita for the Member States. This broadly forces countries with a greater share of current emissions to abate more. In the Alternative 2 scenario, the burden share is stricter for countries with a lower GDP. All three of these scenarios have identical carbon prices, abatement costs and trading costs, since it is assumed that changing the burden share will only affect the trading of allowances. The sum of the trading cost over the EU-27 is also the same, since it is equal to the value of CER imports. The burden share only affects trading between countries because abatement is undertaken wherever in the EU it happens to be cost-effective for the carbon price. will occur when it is the cheaper option regardless of other factors. The only difference between alternative burden shares is the value of trading to each Member State. This is illustrated in Figure 3 below. The countries are ordered by their trading costs based on the even burden share scenario, and the costs for the scenarios with alternative burden shares are shown (sticks). In general the top half of the list is populated by H- 15 States, which bear a greater share of the burden in line with their larger economies. When the burden is redistributed in Alternative 1, H-15 Member States have tighter targets and therefore pay more. Meanwhile the L-12 have larger revenues to match, most of which goes to the six Central and Eastern European Member States. This different distribution causes the order of Member States by cost to change between the scenarios. Hungary and Bulgaria gain larger revenues, overtaking Slovenia, and Italy and Austria s costs rise above those of Belgium. The trend is in the opposite direction for Alternative 2. L-12 States gain lower revenues from trading, with Romania s coming close to zero, while the costs to H-15 States fall. sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 12 of 49

15 Figure 3: Annual average trading costs by country for 30% reduction targets according to Effort Sharing Decision (ESD) and two alternative burden shares ( million per year) France Germany UK Netherlands Italy Belgium Ireland Austria Spain Finland Denmark Sweden Greece Luxembourg Latvia Lithuania Cyprus Malta Slovakia Portugal Estonia Slovenia Hungary Bulgaria Romania Czech Republic Poland Alternative 1 Alternative 2 ESD sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 13 of 49

16 SECTION 3. METHODOLOGY The analysis presented in this report uses Bloomberg New Energy Finance's model of the European energy system, the Global Energy and Emissions Model (GE²M). The model incorporates medium and long-term projections of energy demand based on economic, demographic and technological drivers as well as projections of technologies used to meet that demand. GE 2 M is a partial equilibrium model covering the main European industry sectors (outlined later) Simplifications used in analysis The analysis presented in this report seeks to provide as robust an estimate as possible of the likely costs of moving to tougher emission reductions targets in the EU. In order to make this task more achievable we have made a number of simplifications, of which we list the most significant below: Carbon prices: The carbon prices in this report do not necessarily reflect current market prices, as we calculate the price based on the value that incentivises the required emission reduction over a period of time. We therefore exclude many factors that impact the carbon price such as fuel price shocks, market speculation and geopolitics. Carbon leakage: No estimate has been made of the extent to which carbon leakage occurs as a result of EU climate change policies. Any carbon leakage will raise the economic costs of the targets. Nuclear power: New build nuclear plants are only allowed by the model if they have already been identified in In reality, some additional nuclear plants may be built by 2020, depending on the impact of policies and targets. The decommissioning date of nuclear plants is also included, if known, or estimated if not. Future technologies: We assume that the technologies that are prevalent in 2020 already exist today, although they may currently have a small penetration. Technologies are not likely to significantly affect the energy mix within ten years of their invention. Note that the analysis does not take into account drivers of technology deployment other than cost and policy, such as innovation or pathway dependency. s: We have attempted to evaluate costs in terms of investment and changes to operational costs for both old and new technologies. The numbers that we have used to calibrate the model reflect extensive research by Bloomberg New Energy Finance. The investment and operational costs theoretically include the cost of changing production processes, such as new factories for electric cars, but these costs have not been specifically researched. In addition, it has been challenging to find country-specific values for some technology costs, so many costs are assumed to be similar across the EU-27. Regional differences in labour costs or the extent of existing transport infrastructure, for example, may have a significant impact on total costs of abatement in industrial or transport sectors respectively. Second-order effects: The extent to which changes in consumption or investment may create feedback loops, reducing or increasing costs or affecting demand, is not explicitly modelled, but there may be implicit effects. For example, increased electricity costs may reduce consumer and industrial disposable income, which may in turn reduce consumption elsewhere in the economy with a corresponding effect on GDP. On the other hand, the more capital intensive nature of low carbon technology is likely to result in an increase in investment, which may increase economic growth. sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 14 of 49

17 Elasticity and substitutions: We model demand as being completely inelastic: the projected demand is an input and, for example, an oversupply does not affect costs. There is also no facility for substitution of similar goods. It might be conceivable that demand in the cattle sector might be met by production of poultry, or that aluminium could be substituted for steel for some applications; such phenomena are not included in the model and must be preempted as inputs. Despite these restrictions, we believe the model has considerable value, since it can relatively easily assimilate real-world data and meaningful conclusions can be drawn from its outputs Modelling approach The model is designed to forecast output exogenously for individual sectors and then simulate the uptake of low carbon technologies in the optimal way to achieve the aggregate emissions target for the EU as whole. The sector breakdown used in the model is shown in Table 12 below. Table 12: List of top-level sectors included in the model Sectors included in the EU Emissions System () Non-Traded Sectors () as of 2012 Power & heat Cement & lime Steel (sintering, coking) Oil refining Ceramics Pulp & paper Glass Chemicals Aluminium Other non ferrous metals Aviation (from 2012) Buildings Transport (road, rail & shipping, less international freight shipping) Water and waste treatment Fugitive (eg. coal mine methane) Agriculture (livestock & crops) In most sectors the demand forecasts are obtained by extrapolating the relationship between historical GDP and demand data onto GDP growth projections. We use GDP forecasts consistent with those of the European Commission. Population growth forecasts from the United Nations are used for calculating future demand in sectors including buildings and road transport. The model builds combinations of sector technologies each year to meet the demand. Each technology has a particular set of figures for cost, lifetime, energy consumption, emissions and so on. The figures for total costs and emissions for the sector can then be calculated from the mix of technologies. The choice of which new technologies are built is simulated on the basis of their net present value in the year that new capacity is needed. For example, if demand for steel production in Germany rises in a given year, the capital and operational costs of the available furnace technologies, including associated fuel and power costs, are taken into account such that demand is met with lowest overall annual cost (see Figure 4). Annual capital costs include a percentage weighted average cost of capital (WACC) for each sector and country, to account for the cost of paying back the loan on the capital. We use the Bloomberg Terminal to obtain WACC data for the model, with data taken from mid Numerical constraints are built into the model to restrict or accelerate build rates depending on policy or real world constraints, including all key policies which have already been legislated. For example, EU building standards require a minimum level of building insulation for new-builds, so sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 15 of 49

18 the model is not permitted to build poorly insulated buildings to meet demand. Other constraints are imposed on the model to take account of the availability or lack of certain resources or capabilities, such as the availability of wind or wave power, or the speed with which new nuclear plants can be built relative to other power plants. A carbon price, quoted in Euros per ton of carbon dioxide equivalent, changes the balance of which technologies are cost-effective. The model calculates the carbon price in a given year by finding the price which incentivises the required emission reduction over a period of time. The model includes the carbon price as an operational cost, raising the relative costs of more carbonintense technologies at the point of purchase. The price on carbon therefore encourages the construction of lower-emitting technologies. Figure 4: Projecting new capacity evolution in the power sector Demand in sector A in yr 1 Change in demand Demand in sector A in yr 2 Output/ capacity yr 1 Capacity Net new + Closures + + = replacements capacity Output/ capacity yr 2 Energy use emissions Energy use emissions Closures occur as plants reach end of natural life OR forced shutdowns due to policy intervention Lost capacity is replaced by new plants that more efficient model creates mix of plants favouring least-cost technologies New capacity built to meet demand using same least-cost technology selection Over time this results in diffusion of more energy-efficient/ low-carbon technologies. The diffusion rate is accelerated by higher energy prices/ policy intervention 3.3. Calibration of key sectors The four highest greenhouse gas emitting sectors (power & heat, transport, agriculture and buildings) account for nearly 70% of total EU emissions. Their calibration is described in detail below. Other sectors were calibrated using combinations of real industrial data and in-house analysis and forecasting. Industrial and power sectors are calibrated based on data from mid 2011, while others use data from late Power & heat Annual power demand in our model is based on two factors. A static projection, calculated in advance, is added to components from technologies such as electric vehicles and heating which are calculated dynamically for each year. This allows us to create a causal link in the model between growth (or otherwise) of electricity intensive industries and annual power demand. We calculated base projections for power and heat demand by extrapolating the relationship between demand and gross domestic product (GDP) and population for each country using a multiple logarithmic ( log-log ) function. Independent forecasts of GDP and population growth are used to drive the base case projections. Fossil fuel prices are based on central-case fuel price projections as used by the European Commission. These outputs are compared both to the countries' own projections of their power demand and to historical trends from a range of countries at similar stages of development. From this, we sales.bnef@bloomberg.net. Copyright and Disclaimer notice on page 51 applies throughout. Page 16 of 49