Cross-cutting issues in the preparation of GHG projections: Lithuanian experience D. Štreimikienė Lithuanian energy institute Workshop on emission projections, Bonn, Germany, 6-8 September 2004

LITHUANIA Territory: 64 thou km 2 Capital: Vilnius Population: 3.7 mln. Population density: 57 inhab/km 2 PPP GDP in 2000: 7500 TPES in 2002: 8.61 Mtoe The share of renewables in TPES: 8.3% Electricity production in 2002: TWh

General situation in energy sector& comparison with EU Low energy consumption and CO 2 emissions per capita and high energy and carbon intensity per GDP: Final energy consumption/capita, CO 2 emissions per kWh and per capita is 2 times (electricity and GDP per capita more than 3 times) lower than in EU; Final energy use per GDP is 1,6 time higher, TPES/GDP is 2 times higher and CO 2 intensity of GDP is more than 3 times higher than in EU; CO 2 /TPES 1.5 times lower than in EU;

The ways to reduce GHG emissions There are only 2 main ways to reduce GHG emissions from fuel combustion: decrease of energy consumption by decreasing energy intensity and increase of energy supply efficiency; switching to fuels with less energy content. The main policy measures to attain this are: CO 2 taxes or emission trading schemes; FM; Feed in prices for electricity produced from renewables and Green certificate trading; Tax allowances or subsidies for renewables; Excise taxes on fuels etc.

Energy intensity is crucial for GHG emission Final energy consumption has significantly decreased in all sectors since 1990 in Lithuania (about 3 times); Final energy intensity has decreased in all sectors of economy: in manufacturing sector more than twice; in agriculture - 4 times. Since 1990 the share of value added increased in commercial sector and significantly decreased in manufacturing and agriculture. All these trends have an impact on the decrease of final energy intensity of GDP in Lithuania.

Lithuanian final energy intensities and shares of value added (1990, 2000)

The main direct driving forces for GHG emissions Energy intensity of GDP; The structure of GDP; Energy intensity of branches of economy; Energy supply efficiency (Final energy/TPES); Efficiency of power & heat production; The share of carbon intensive fossil fuels in the structure of energy supply and final energy consumption; Assessment of these driving force impact on GHG emission reductions requires decomposition analysis; Indirect driving forces for GHG emission reduction or policies and measures having impact on driving forces are: liberalization of energy prices, pollution taxes, emission trading schemes, subsidies for renewables etc. Assessment of these measures impact can be evaluated by ex-post evaluations of future changes in fuel consumption structure driven by these measures.

Linkages between driving forces and policy actions

Decomposition analysis of GHG emissions Z – carbon intensity of GDP; C – GHG emissions; Y – GDP; Y i – production of sector i; E ij – fuel j consumption in sector j; E i – final energy consumption in sector i; U ij – GHG emissions from fuel j in sector i; e ij – consumption share of fuel j in sector i; y i - GDP share of sector i; I i – energy intensity of sector i;

Results of decomposition analyses/evaluation of the direct driving force impact The biggest impact on GHG emission reduction in Lithuania had structural changes in economy y i (increase of commercial sector and decrease of energy intensive manufacturing sector) and Decrease of final energy intensities I i in manufacturing, transport etc. The impact of changes of fuel mix e ij and emission coefficients U ij had negligible impact on GHG emission reduction

Projections of GHG emissions

Projections of GHG emissions from fuel combustion Projections of GHG emissions from fuel combustion are based on: Final energy demand projections according sectors and fuels (MAED model was used). Energy saving potential was evaluated in this projections. GHG emissions from final energy consumption were evaluated using IPCC emission factors. Primary energy supply projections were estimated based on final demand forecast and applying MESSAGE or BALANCE models. GHG mitigation measures foreseen in National energy strategy were integrated in energy projections. From perspective primary energy balances data about fuel combustion in electricity and heat production and for refinery own needs were used to evaluate GHG emission using IPCC emission factors

Uncertainties in energy projections based on certain assumptions Forecast of GDP growth rates include some uncertainties; Final energy demand forecast is related with uncertainties in foreseen energy efficiency improvements; The future prices of energy resources are very uncertain and they are the main driving forces in selection of generation sources in least cost power sector development plan. The level of the primary energy demand is based on internal factors (GDP growth rates, growth of the energy efficiency, losses of the fuels and energy, own use of the energy sector, fuel consumption for production of fertiliser and other non energy use) as well as volumes of the surplus electricity used for export. Sensitivity analysis indicated that the biggest impact on energy demand was caused by GDP growth rates, structural changes of economy and energy intensity decrease.

Forecast of TPES

Final energy demand forecast

GHG emission projections according sectors

GHG emission projections in energy sector Kyoto limit – 34.3 Mt

GHG emissions in energy sector

Development of ‘with measures” scenario or ex-post evaluation of policies and measures effects

The main GHG mitigation policies and measures The requirements for EU integration are the key driver for the implementation of PaMs. Climate Change mitigation is only a secondary benefit: Increase use of renewable energy sources: White Paper on Renewable Energy (1997); Renewable electricity directive (2001/77/EC); Biofuels directive (2003/30/EC) Increase energy supply and transformation efficiency: promotion of CHP (2004/8/EC), rehabilitation of centralized heat system; Increase energy use efficiency: Energy Performance of Buildings directive (2002/91);Energy efficiency programmes; Housing strategy (2004). Promotion of low carbon intensive, more clean fuels: GHG emission trading directive (2003/87/EC); Directive on taxation of energy products (2003/96/EC), CO 2 tax under consideration.

Energy efficiency programme According Energy Efficiency Programme (2001) the total energy saving potential makes 20-50% of the total energy consumed in Energy saving potential in industry makes 2.3 TWh. Final energy demand in 2005 will make 15 TWh and GHG emissions -3.3 Mt. Each TWh of energy consumed caused Mt of GHG. Energy savings will help to reduce CO 2 emissions by 2.3 TWh*0.22=0.51 Mt in Energy saving potential in residential and commercial sector buildings – 1.2 TWh. Final energy demand in TWh and GHG Mt. One TWh of energy consumed would result in Mt of GHG emissions. Energy savings will help to reduce GHG emissions by 1,2*0,097= 0.12 Mt in 2005.

Evaluation of energy saving potential in Energy efficiency programme SectorConsumed in 2000, PJ Total saving potential, PJ Investmen ts needed, bill. Lt Industry Transport Agriculture Residential (electricity) Service (electricity) Full modernisation of district heating Total

Housing strategy One of the objectives laid down in the Lithuanian Housing Strategy (21 January 2004 Resolution No 60 of the Government of the Republic of Lithuania) is to ensure efficient use of energy sources. In order to achieve this goal, heating systems of multi- family buildings will be modernized, roof structures will be renovated and insulated, windows and external doors will be replaced or renovated, and joint defects of large-block construction buildings will be remedied. These measures will make it possible to achieve an up to 30% reduction in relative heat and fuel costs calculated per one unit of area by 2020.

The main policies to reduce GHG emission set in National energy strategy Implementation of Directive 2001/77/EC on the promotion of electricity produced from renewable energy sources in the internal electricity market, Lithuania has committed itself to increase the share of electricity produced from renewable energy sources to 7% by 2010 ; Implementation of National Energy Strategy which requires that by 2010 the share of renewable energy sources account for 12% of all primary energy structure; Implementation of National Energy Strategy which requires that by 2020 the share of CHP will account for 35% in electricity generation structure.

Instruments applied to promote renewables Feed-in prices for electricity produced using RES: 5.8 EURct/kWh for hydro 6.4 EURct/kWh for wind 5.8 EURct/kWh for power plants using biomass; Since 1 January 2003 on denaturated dehydrated ethyl alcohol and methyl and ethyl ester will be exempted from VAT). Legal and natural persons using biofuels and which present the documents proving the use of biofuels are exempted from the tax for pollution from mobile pollution which is based on the fuel consumption and is levied per tone of fuel consumed.

Policies impact on GHG emission reduction in Lithuania, Mt of CO 2 e Policies Total in energy generation Implementation of RES-E directive 2001/77/EC by guaranteed purchase and feed-in prices Implementation of White paper on RES strategy by VAT, Excise tax exemptions for biofuels, Feed-in prices Implementation of CHP directive 2004/8/EC Total in transport Implementation of energy efficiency programme Implementation of biofuels directive 2003/30/EC by VAT, excise and pollution tax exemptions for biofuels Total in industry Implementation of energy efficiency programme Total in households0.12 Implementation of energy efficiency programme0.12 Total impact

GHG emissions according with measures scenario

Additional measures

New GHG mitigation policies or additional measures GHG emission trading; EU taxation framework for energy products; JI; CO 2 tax in non-trading sectors; GCT since 2010.

EU emission trading scheme Lithuania is going to implement EU emission trading scheme since 1 January The law implementing under preparation The scheme will has significant impact on increase of energy use efficiency in industries covered by the scheme (refinery, pulp and paper, ceramics and cement production, chemical industry etc.); The scheme will promote CHP and use of biofuels; Lithuanian environmental investment fund (LEIF) is the main institution responsible for the Implementation of EU emission trading scheme; Draft National allocation plan was prepared by LEIF; GHG register pre –study was prepared by Norway register Development A/S in 2004.

EU framework for taxation of energy products The Directive 2003/96/EC is implemented in Lithuania by Excise law amended in The excise taxes will be increased since 1 April Only exemptions are applied for electricity until 1 January 2010, coal and coke – January and orimulsion – 1 January Natural gas is exempted from excise taxes. The Danish energy authority study on Enhancement of use of RES in Lithuania indicated that introduction of excise tax on orimulsion (13.1 EUR/t) reduces CO 2 with about 6% and SO 2 with about 4%, leads to significant additional income to the state budget but, at the same time the price of electricity will increase by 1.8% and heat – 0.7%.

JI The Order “On the Approval of the Interinstitutional Allocation of Functions Relating to the JI, Strategic Directions for the Implementation of this Mechanism and Recommendations for the Realization of JI” of the Ministry of Environment and Ministry of Economy sets the criteria and priority areas for JI. JI will be implemented in the sectors not covered by the EU emission trading scheme: Introduction of technologies for electricity and heat (cogeneration) from renewable energy sources; replacing one type of fuel with renewable and/or less pollutant fuels; increasing energy efficiency, including energy saving methods; production of energy from methane generated in agriculture and from flaring gas.

New policies under consideration Investigated possibilities for CO2 tax: Swedish Environmental Research Institute, IVL, Economic Instruments in the Lithuanian Energy Sector, Draft Final Report Danish Energy Authority. Enhancement of the Use of Local and Renewable Energy Sources-Lithuania, CO 2 tax (13.3 t/EUR) causes energy price increase (8.4% - electricity; 13.4% – heat). No impact on RES because of their low availability; Great shift from oil to natural gas and import of electricity and consequently to more negative trade balance; Negative for security of supply; Reduction of CO 2 emissions by 21%; Supplementary income to the state budget.

Conclusions Policies and measures foreseen in CC mitigation policies should be incorporated in GHG emission projections; Based on the changes of perspective consumption and structure of energy supply ex-post evaluation of implemented measures can be assesed. In order to assess the effect of implemented policies and measures on GHG emission reduction the decomposition analysis of GHG emission is necessary allowing to evaluate effect of structural changes, energy intensity changes and changes in fuel mix. Than the impact of direct driving forces (structural changes, energy intensities, fuel mix) should be related with policies on targeted driving forces; Based on this approach new policies on targeted driving forces should be formulated than efficiency of already implemented measures is too low.

Reccomendations to enhance comparability Preparation of GHG emission projections and evaluation of effect of policies requires to strengthen analytical tools or develop new comprehensive methodological approach (guidelines and tables) to be applied for all Parties; This enables: to apply the same energy and GHG performance indicators (ISED framework developed by IAEA can be applied); to assess the effect of driving forces on GHG emissions applying the decomposition analysis approach developed by IEA; To use the same framework for linking energy and GHG performance indicators with policy actions on targeting driving force indicators (ISED framework); To use the similar assessment (ex-post) approach for already implemented CC mitigation policies. Some recommendations for models application and development of assumptions influencing on uncertainties is also necessary.

Projections of GHG emissions from FC To provide list of compatible models applicable for GHG emission projections and provide some training on their application, integration of already foreseen CC mitigation measures, development of assumptions and uncertainties assessment; To develop list of energy and GHG performance indicators enabling to identify driving forces and response actions or policies and measures on targeting indicators; To present the decomposition analysis of GHG emissions and provide training for the assessment of the effect of various driving forces; To link driving forces with already implemented policies and measures and assess their impact on GHG emission reductions using perspective data on driving forces (energy mix, energy intensity, energy supply efficiency). To propose new policies or response actions on targeted indicators based on conducted analysis