#1TUT PERTAN RTANIAN BOGOR TEKNOLOG INSTITUT 1920 BANDUNG LOW CARBON DEVELOPMENT: INDONESIA Rizaldi Boer Center for Climate Risk and Opportunity Management Bogor Agriculture University-INDONESIA and Retno Gumilang Gelang Center for Research on Energy Policy Institut Teknologi Bandung-INDONESIA CCROM Southeast Asia and Pacific CREP ITB#2☐ ◉ Background LCD is relatively new in Indonesia → Current GOI plans are not developed to achieve LCD but in lined with and supportive to LCD. Indonesia is the world's 10 largest GHG emitters: 1,377 MTon CO2eq (2000) and 1,991 MTon CO2-eq (2005) → growth rate 5.7%/year; About half the total national emission was from LULUCF and peat fire, while energy is the second with contribution of about 20% 'Non-binding' GHG reduction target of 26% lower than baseline of 2020 (domestic budget) and further increased to 41% (international support); GHG reduction primarily will be achieved through forestry (include peat emissions), followed by energy, waste, industry sectors. Indonesia is developing National Action Plan on GHG Reduction (2010-2020).#3Rate of Emission (Gt CO2e) Background: Historical Emission & BAU Projection 3.00 Waste Agriculture Energy 2.50 2.00 1.50 1.00 0.50 0.00 2000 LUCF and peat Industry Only from livestock and rice cultivation Projection of emission under BAU until 2020, LULUCF and peat land is still the major source of GHG emission. However after 2020, energy sector might take over the LULUCF position as the major source of the GHG emission 2011 2012 - 2013 2014 - Source: SNC (2010) 2019 2020#4Rate of Emission (Gt CO2e/y) BAU Projection has been adopted by Gol in defining the 26% and 41% ERT. By 2020, ERT through unilateral actions will be 26% of the BAU 2020 emission rate and additional 15% ER is targeted through supported actions 3.00 BAU Projection of emission under 2.85 26% BAU will be revised 41% 2.70 2.55 2.40 2.25 2.10 1.95 1.80 1.65 1.50 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 1.72 Gt 2.16 Gt 2.92 Gt#53.5 Peat Fire 3.0 LUCF Waste Agriculture Emission (Gt CO2e) 2.5 Rate of Emission under BAU Organic soils (peat) With 26% ERT, the expected emission in 2020 will be 74% above the 2000 Emission level or Industry 23% above the 74% 23% 2005 emission 2.0 26% level, 39% -2% while with 41% 41% 1.5 ERT,, the expected emission in 2020 1.0 0.5 0.0 2000 2005 2020 Source: Based on SNC (2010) will be 39% above 2000 Emission level or 2% below the 2005 emission level#6Sectors contribution to the 26% ERT Introduction of LEV, WUE etc. Agriculture Industry 1.04% Waste 6.26% 0.13% Energy efficiency, the use of RE etc Energy and Transportation 4.95% Use of biofuel, engine with improved energy efficiency, improve public transportation and road, demand side management, energy efficiency, development of renewable energy Establishment of final dumpsite (TPA), waste management with 3R (reduced, recycling and reuse), integrated city waste water management Expected cumulative emission reduction (2005-2020) is 5.6 Gt LULUCF and peatland 87.61% Peat/forest fire management, improving water management on peat, land and forest rehabilitations, combating illegal logging, reducing deforestation and community empowerment Forestry: 53.8% 2 1.56 Gt CO2e#7BAU Emission from Forestry Sector in the SNC Emission from biomass removal similar to historical emission 0.898 Gt CO2 per year (from MoFor, 2009). Emission from peat fire taken from van der Werf et al. (2008) Emission from peat (average over 2006-2025, with assumption that all forest in peatland outside forest area and inside convertible forest will be converted and in non-convertible forest follows historical rate, based on Bappenas 2009) Rate of sequestration occurs as a result of: Emission/Removal (Gt CO2e) Net : 0.82 1.12 1.55 2.5 2.0 1.5 1.0 0.5 0.0 -0.5 ☐ regeneration of secondary forests (5.32 tCO2/ha), tree planting (36.7 tCO2/ha), Rate of tree planting between 1996 and 2006 was 198 thousand ha/year. ☐ Regrowth of woody vegetation (13.5 tCO2/ha). -1.0 2000 2005 Peat Fire Biomass loss Organic Soil (Peat) ■C-Sequestration 2020 Source: SNC, 2010#8Emission projection under BAU and Mitigation scenarios developed by Policy Working Group on Forestry (for the Minister of Forestry-Pokja Kebijakan-Kementrian Kehutanan, 2010)#9urce: Baplan (2008) Indonesian Land Cover in 2007 Land cover condition Forested Non-Forested Unidentified Total Source: Baplan, 2008 Conserva- Protec- Produc- Con- Non- tion tion tion vertible Forest Forest Forest Forest Forest Area 14,365 22,102 38,805 10,693 7,960 4,009 5,622 18,404 11,057 44,163 1,502 2,328 3,706 981 2,216 19,876 30,052 60,915 22,732 54,339 Government Plans are to have permanent agriculture land for food crops of 15 Mha (additional 7 Mha is required) and thus forest areas available for agriculture plantation and other non forest activities will be about 15 Mha.#10Area (thousands ha) Use of lands for agriculture plantations in Indonesia (1986-2009) 8000 7000 Rubber • Coffee Coconut ▲ Oi palm 6000 Pepper Cacao Tea 5000 4000 3000 2000 1000 0 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006#1112 BAU 10 Cumulative Area (Mha) 2 4 6 CO 0 2007-2009 2010-2011 Planned Deforestation Scenario (only on Convertible Forest called HPK) Miti-1 Miti-2 2012-2015 2016-2020 2021-2025 BAU: All HPK will be converted for non-forest activities irrespective of forested or non-forested until 2025 Mitigation: Forested HPK will be maintained as forest area (Miti1: 50% and Miti2: 75%) Supporting Regulations PP. 10/2010 and PP11/2010; National forest policy for avoiding deforestation; establishment of forest management unit (FMU)#12Unplanned Deforestation Scenario 10 9 BAU Cumulative Area (Mha) 43 2 --Miti-1 <--Miti-2 1 0 2007-2009 2010-2011 2012-2015 2016-2020 2021-2025 BAU: Following historical deforestation rate that occurred between 2000-2006 (contribute to about 79% of total deforestasi rate) 210 FMU. Need to have 700 KPH 2 ■ Mitigation: Depend on the successfulness of establishing FMU, Human resources and fund Miti1: same as BAU and FMUS function effectively, Miti2: All FMUs established#13Forest Degradation due to logging Scenario 25 23 Sustainable Logging -BAU 21 -Miti-1 19 -Miti-2 17 15 22222 43 Rate of logging (Mm3/yr) 13 11 9 7 5 2007-2009 2010-2011 2012-2015 2016-2020 Assumption: Historically, amount of illegal logging is the same as legal logging ☐ Rate of from illegal logging decrease linearly with the establishment of FMU ■ BAU: Amount of logged wood decrease slightly following the FMU establishment 2021-2025 ■ Mitigation: Depend on the successfulness of establishing FMU, Human resources and fund Miti1: same as BAU but FMUS function effectively, Miti2: All FMUs established#14Industrial Timber Plantation Establishment Scenario 12 12 BAU 10 Miti-1 8 -Miti-2 Cumulative Area (Mha) st 9 2 0 2007-2009 2010-2011 2012-2015 2016-2020 2021-2025 • • BAU: Rate of timber plantation establishment followed historical rate (at present total timber plantation is about 4.8 Mha) Mitigation: • . Miti1: New timber plantation establishment is to meet the target of 10 Mha (Government scenario) Miti2: New timber plantation establishment is set up to make. Indonesia as the 3rd largest timber producer countries in the world, APHI scenario) Assumption: land tenure solved and climate for investment good#15Community based-Timber Plantation Establishment Scenario 4.5 BAU 4.0 3.5 --Miti-1 3.0 <--Miti-2 2.5 Cumulative Area (Mha) 2.0 1.5 1.0 0.5 0.0 2007-2009 2010-2011 2012-2015 2016-2020 • 2021-2025 BAU: Rate of timber plantation establishment followed historical rate Mitigation: • • • Miti1: Rate of planting meets part of the government target considering the biophysical feasibility of lands for the timber plantation Miti2: Rate of planting meets the government target Assumption: land tenure solved and climate for investment good#16Rate of planting for Land Rehabilitation program 12.0 -BAU 10.0 8.0 6.0 Cumulative Area (Mha) 80 00 4.0 40 2.0 20 0.0 -Miti-1 Miti-2 2007-2009 2010-2011 2012-2015 2016-2020 2021-2025 BAU: Rate of planting and survival rate followed historical condition Mitigation: Meet the government target and the survival rate increase following the • successfulness of FMU establishment • Miti1: same as BAU but FMUS function effectively, Miti2: All FMUs established Assumption: Institution work well, good seedling, fund available and good extension services#171.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 -0.2 Emission Projection from LULUCF BAU MIT1MIT2 BAU MIT1MIT2 BAU MIT1 MIT2 BAU MIT1MIT2 2010-2011 2012-15 2016-20 2021-25 Cumulative Net Emission (Gt CO2) 25 BAU 20 20 15 10 5 MITI1 MITI2 63% 83% 2009 2011 2013 2015 2017 2019 2021 2023 2025#18Concluding Remarks ■LULUCF and peat land can contribute significantly to the reduction of the GHG emissions ■ Conditions: Establishment of FMU should be accelerated. Available budget may be enough only for Budget available for this only for 30% Land tenure Climate investment Financial support for communities-forest- based-activities and extension services#19Low Carbon Development Strategy Toward 2050 in Indonesian Energy Sector Overview of Energy Sector and GHG Emissions Energy and GHG Emissions Projections (BAU) Future Visions for Achieving LCDS Toward 2050 Indonesian LCD Strategy in Energy Sector: It is not to achieve a certain target (i.e. world's target on GHG emission reduction); it is more to explore various possibilities of the Future Economic Development in a Low-carbon Way#20Overview of Energy Sector and GHG Emissions Energy consumption grows 5.45 %/year (2000-2005) at population growth 1.05%, energy elasticity 1.2, GDP growth 4.95% -5.5%. ■ The objective of energy development is energy supply security. Energy development is guided by ‘energy supply security' concern; energy investments is based on least cost and resources availability and are not related to climate change mitigation ■ Fossil fuels 90% in national energy mix, in which oil accounts to 51%; GHG increases 5%/year ■ There is potential to reduce GHG by deplyoment of renewable energy. ■ Indonesia relies on imported technology in all sectors. Current energy technologies are generally still inefficient, there are rooms for improvements on technology efficiency.#21Energy Resource Potential of Indonesia, 2008 Fossil Energy Resources Reserves (Proven + Possible) Annual Production R/P, year (*) Oil 56.6 BBarels 8.2BBarels (**) 357 MBarels 23 Natural Gas 334.5 TCF Coal 104.8 Btons 170 TCF 18.8 Btons 2.7 TSCF 229.2 Mtons 63 82 Coal Bed Methane 453 TCF (*) assuming no new discovery; (**) including Cepu Block New and Renewable Energy Resources 75.670 MW Installed Capacity 4.200 MW 27.510 MW 1.052 MW 500 MW 86,1 MW 49.810 MW 4,80 kWh/m2/day 9.290 MW 3 GW for 11 years*) (e.q. 24,112 ton) 445 MW 12,1 MW 1,1 MW 30 MW Hydro Geothermal Mini/Micro Hydro Biomass Solar Energy Wind Energy Uranium (***) ***) Only at Kalan - West Kalimantan Source: Data and Information Center, MEMR, 2009#22Final Energy Demand by Sector 2008 2006 2004 2002 2000 1998 ■Industry ■Residential ■Commercial ■Transportation ■Others (ACM) 1996 1994 1992 1990 MMBOE 0 100 200 300 400 500 600 700#23Final Energy Demand by Type of Energy 2008 2006 2004 Coal 2002 2000 1998 1996 Natural Gas Oil LPG Electricity 1994 1992 1990 MMBOE 0 100 200 300 400 500 600 700#24VISIONS Three conditions are used to figure the direction of future socio economic visions for achieving LCS goals toward 2050 ▪BAU assumes existing society orientation will continue until 2050. ▪Two countermeasures assume that there will be changes in society orientation in the future, namely: ☐ Moderate economic growth, which assumes that the society behavior is depicted as calmer, slower, nature oriented ones. ☐ High economic growth conditions assumes that the society is depicted as more active, quick changing, and technology oriented. This scenario has two long-term objectives: realizing full socio-economic potential of the country and creating a sustainable LCS.#25Development scenarios to 2050 with respect to LCDS Particular interest: socio-economic, energy use, and associated emission level Base year: 2005 Projection 2050 ☐ BaU (moderate scenario): current socio-economic development, society behavior, energy systems/structure will continue until 2050; ☐ CM1 (moderate scenario): economic growth is similar with BAU, more energy efficient and lower carbon emitting energy technology compared to BAU, slight change in society behavior (depicted as calmer, slower, and nature oriented) ☐ CM2 (high scenario): high economic growth, very energy efficient, lower carbon emitting technology, much better energy related infrastructure compared to BAU, with society behavior depicted as active, quick changing, and technology oriented#26Estimated socio economic indicators in the base year (2005) and the target year(2050) 2050 2050/2005 Socio Economic Parameter 2005 BaU CM1 CM2 BaU CM1 CM2 Population, Million 219 327 327 327 1.5 1.5 1.5 No. of households. Million 60 89 89 109 1.5 1.5 1.8 GDP, trillion rupiah 1,787 36,998 36,998 68,252 20.7 20.7 38.2 GDP per capita, million 8.2 113 113 209 13.9 13.9 25.6 rupiah Gross output, trillion rupiah 3,533 72,406 72,406 126,791 20.5 20.5 35.9 Primary Secondary 329 6,516 1,953 37,505 37,505 6,516 9,610 19.8 19.8 29.2 39,625 19.2 19.2 20.3 Tertiary 1,251 28,384 28,384 77,556 22.7 22.7 62.0 P-transport demand, billion psg km 1,763 3,407 2,965 2,195 1.9 1.7 1.2 F-transport demand, million 1.07 20.64 20.64 23.08 19.3 19.3 21.6 ton km#27Gross output (trillion rupiah) Change in GDP structure toward tertiary industry 140,000 120,000 100,000 80,000 60,000 40,000 20,000 0 2005 2050 2050 2050 BAU CM1 CM2 (trillion rupiah) GDP 80,000 60,000 40,000 20,000 BAU and CM1 CM2 BAPENAS Projection 0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 ■Commercial 400 GDP*/capita Million Rupiah Cement 350 Iron and Stel 300 Other Industries 250 Construction 200 150 Chemicals 100 ■Textile, Wood, Paper 50 Food and Beverage ■Mining and Quarying Agriculture Japan Singapore Brunei * at constant price 2000 Hong Kong South Korea Malaysia China - Base (2005) -BaU (2050) -CM1 (2050) -CM2 (2050) 2050#28Value of 2005 =1 45 40 35 30 25 20 15 10 ■Base BaU ■ CM1 ■CM2 5 0 Population GDP Final energy demand GHG emissions#29Estimation result of base year (2005) and target year (2050) 2005 2050 Energy Emission Parameter Base BaU CM1 CM2 Energy Demand, ktoe Passenger Transport 17,798 41,406 12,543 9,244 Freight Transport 6,562 126,510 45,623 42,056 Residential Industry 42,832 69,761 38,710 66,971 39,224 569,325 471,039 543,266 Commercial 3,704 111,952 68,039 129,068 Total 110,120 918,953 635,954 790,605 Energy demand per capita, toe 0.50 2.81 1.95 2.42 Energy intensity, toe/million rupiah 61.6 24.8 17.2 11.6 CO2 Emissions Total, million ton-C* 81 1,184 617 183 Per capita, ton-C 0.37 3.62 1.89 0.56 Total, million ton-CO2 299 4,341 2,263 670 Per capita, ton-CO2 Annual GDP Growth rate 1.4 13.3 6.9 2.0 6.9% 6.9% 8.3% Annual energy demand growth rate Energy elasticity 4.8% 4.0% 4.5% I 0.70 0.57 0.54#30~ HDI ( life expectancy at birth + adult literacy & school enrolment + GNP per capita at PPP) versus Primary Energy Demand per Capita (2002) in tonnes of oil equivalent (toe) pa [1 toe pa = 1.33 kWs] 1.0 0.9 0.8 0.7 0.6 모 0.5 3 toe = 22 boe Base 0.4 2005 0.3- CM 1 0.5 0.2 1.95 toe toel 2.42 CM 2 toe K 0.0 0 4 6 8 OECD Non-OECD 10 12 14 2.81 BAU toe 2050 Primary energy demand per capita (toe/cap) Sources: IEA analysis; UNDP (2004). Note: shoulder in HDI vs energy-use curve at - 3 toe pa [= 4.0 kWs] per capita 3 toe = 22 boe#31million to e million toe 1,000 800 600 400 200 0 1,000 800 600 400 200 0 1,500 Passenger Transport 1,200 Freight Transport ■Residential ■Commercial Industry 2005 2050 2050 2050 BaU CM1 CM2 Primary energy demand by sector million to e 900 600 ■Clean coal (IGCC + CCS) ■biomass (+biofuel) ■solar wind geothermal ■nuclear ■hydro natural gas 300 ■ oil ■coal 0 2005 2050 2050 2050 Base BaU CM1 CM2 1,400 ■Passenger Transport 1,200 Freight Transport 1,000 ■Residential ■Commercial ■Industry million ton-C 800 600 400 200 0 Final energy demand by type of energy ■Passenger transport Freight transport ■Residential ■Commercial Industry 2005 2050 2050 2050 BaU CM1 CM2 Final energy demand by sector 2005 2050 2050 2050 Base BAU CM1 CM2 CO2 emissions by sector, million ton C.#320 50 100 150 200 250 300 350 400 450 2050CM1 2050CM2 0 50 100 150 200 250 300 350 400 450 2050CM1 2050CM2 Potential of GHG emission reduction of demand side by energy demand sector Potential of GHG emission reduction of supply side by energy demand sector#33MITIGATION STRATEGIES#34Drivers of GHG Emissions can be identified from "IPAT identity": Impact = Population × Affluence × Technology CO2 Emissions = Population × (GDP/Population) × (Energy/GDP) × (CO2/Energy) ("Kaya" multiplicative identity) Net C = P (GDP) E - S GDP E | Energy Clean Energy Efficient and Technology Climate Change Mitigation Acions are to reduce Nett GHG Emisions#35LCS Actions Clean Energy (Residential and Commercial) Low Carbon Style (Residential and Commercial) Low Carbon Electricity Low carbon energy system in industry Sustainable transport Renewable energy or Less CO2 Emission Energy Less CO2 Emission Energy Technology Society Behavior in Residential/Commercial Efficient energy technology appliances Renewable energy & Less CO2 Emission Energy Efficient energy technology of power generation _Less CO2 Emission Energy Technology (Coal IGCC + CCS) Increasing Efficiency of T & D Renewable energy or Less CO2 Emission Energy Efficient energy technology appliances -Efficient energy process and processing technology -Renewable energy or Less CO2 Emission Energy modal shift (public/mass rapid transport utilization) Energy Efficiency Improvement Reduce trip generation and distance (improve Infrastructure, telecommunication, new urban design, traffic management#36Action 1 Clean Energy: Increase share of renewable/less carbon emitting fuels 100% 80% 60% 40% 20% (a) Residential sector 0% 2005 2050 2050 BaU CM1 2050 CM2 40 Value in 2005 = 1 30 50 20 10 Electricity Biomass Solar & Wind Natural gas ■ Oil Coal ■ 2005 ■ 2050 BAU ■ 2050 CM1 ■ 2050 CM2 (b) Commercial sector 100% 80% 60% 40% 20% 0% 2005 Base 2050 2050 2050 Bau CM1 CM2 0 Energy in Residential Emissions from Residential Energy in Commercial Emissions from Commercial sector sector sector sector#37Energy demand (million toe) 140 120 100 60 88220 40 Action 2 Low Carbon Lifestyle 80 80 Energy demand (million toe) 60 40 40 20 0 2005 2050 BaU 2050 CM1 2050 CM2 Other electric equipments Refrigerator ■Lighting ■ Kitchen Hot water ■Cooling Energy demand (million toe) 20 20 40 40 00 60 0 2005 2050 2050 2050 BaU CM1 CM2 Electricity ■Biomass ■ Solar & Wind Gas ■Oil Final energy demand by service (left) and by fuel (right) in residential sector 0 2005 2050 BaU 2050 CM1 2050 CM2 Other electric equipments Refrigerator ■Lighting ■ Kitchen ■ Hot water ■ Cooling 140 120 100 80 60 8820 40 20 Energy demand (million toe) 2005 2050 BaU 2050 CM1 2050 CM2 Electricity ■Biomass ■ Solar Gas ■ Oil Final energy demand by service (left) anu by fuel (nynt) in commercial sECION#38Energy demand (milion toe) Energy efficiency (%) Action3: Low Carbon Electricity 60% 100% 40% 20% 0% Coal Oil Gas Biomass IGCC + CCS Energy efficiency level of power generation in each scenario 700 600 500 400 300 200 100 0 2005 2050 BaU 2050 CM1 2050 2005, 2050BaU 80% 2050CM1 60% 2050CM2 Coal with CCS Gas ■Oil ■ Coal 40% 20% 0% 2005 2050 BaU 2050 CM1 2050 CM2 CO2 emission (million ton-C) IGCC+CCS Biomass Solar, wind, geothermal Nuclear Hydro ■Gas ■ Oil ■ Coal Share of power supply by energy type in each scenario g 500 400 300 200 100 CM2 Fuel consumption and CO2 emission of power generation sector in each scenario 0 2005 2050 2050 2050 BaU CM1 CM2 Gas ■ Oil ■ Coal#39Action 4: Low Carbon Energy System in Industry gggggg ŏ Energy demand (milion toe) 300 200 100 600 500 400 700 0 2005 2050 2050 2050 BaU CM1 CM2 500 ■ Coal with CCS 400 Gas ■ Oil Coal CO2 emission (million ton-C) 300 200 100 0 2005 2050 2050 2050 BaU CM1 CM2 Fuel consumption and CO2 emission of power generation sector in each scenario Gas ■ Oil ■ Coal#40Energy demand (million toe) 600 Others 500 ■Kiln 400 300 200 100 0 2005 2050 2050 2050 BaU CM1 CM2 ■Steal ■Motor Boyler Furnace Energy demand (million toe) 600 500 400 ■ Electricity ■Biomass ■Gas ■ Oil 300 200 100 0 2005 2050 2050 2050 BaU CM1 CM2 ■ Coal Energy demand in Industry by energy service and by type of fuel 25 25 ■Air Ship 4,000 3,500 3,000 2,500 2,000 1,500 1,000 500 0 2005 2050 2050 2050 BAU CM1 CM2 Bike ■Walk Air 20 Ship Two wheeler 15 ■Train Bus Large vehicle 10 ■Small vehicle 5 0 2005 2050 BAU 2050 2050 CM1 CM2 ■Train ■Large vehicle ■Small vehicle Transport demand by transport mode in passenger (right) and freight (left) transport#41Value in 2005 1 Transport demand (million passenger-km) 2.5 Action 5: Sustainable Transport 4,000 3,500 3,000 2,500 2,000 1,500 1,000 500 Bike ■Walk ■Air Ship Two wheeler Train Bus Large vehicle ■Small vehicle Transport demand (million t-km) 25 20 20 15 15 10 10 5 ■ Air Ship ■Train Large vehicle ■Small vehicle 0 2005 2050 BAU 2050 CM1 2050 CM2 0 2005 2050 2050 2050 BAU CM1 CM2 Transport demand by transport mode in passenger (right) and freight (left) transport 1.5 0.5 1 2 0 Passenger Transport Energy GHG Emissions Demand Demand ■ 2005 2050 BaU ■2050 CM1 ■2050 CM2 Value in 2005 = 1 25 20 15 10 5 0 Demand Freight Transport Energy Demand GHG Emissions Effect of passenger and freight transport demand to energy demand and CO2 emissions#42Policies and Regulations ■ There are numerous energy-climate policy initiatives, regulations, and actions in energy sector that could result in CO2 emission reduction. ■ The latest policy initiative is non-binding emission reduction target of 26% lower than baseline in 2020 using domestic budget and further increased to 41% with international support. ■ To implement non-binding commitment, GOI prepares National Actions Plan 2010 -2020 to Reduce CO2 Emissions. ■ In addition to the policy initiatives, most actions plan developed for achieving the LCS target will still need policy measures to support the implementations of five major actions → _#43a. Increasing share of new/renewable energy and less carbon emitting fuels (include less carbon emitting technology) in energy supply mix to support implementation of Presidential Regulation 5/2006. b. On-going programs considered to meet energy supply mix target are power generation crash program I and II (which include clean coal and geothermal), kerosene to LPG, mandatory of bio-fuel utilization in power plant, transportation, and industry (MEMR 32/2008); c. Increasing share of new/renewable (hydro, geothermal) and oil switch to natural gas as stated in the National Plan of Electricity Development (RUPTL) PLN 2008 - 2018; d. Regulations that lead to the formulation of national master plan on energy efficiency; e. Policies to support MRT development, diversification of fuels (CNG/LPG, bio-fuel, electricity) in transportation, and emissions. monitoring and control of local emission and combustion efficiency that has implication to the CO2 emissions generation.#44• • - - Conclussion If current economic growth and society behavior continues until 2050 in the BaU scenario, energy demand will increase 8.2 times and the associated emissions will increase 12.5 times (compared to 2005 levels). Moderate economic growth, with current policies/regulations on efficiency efforts will lead to 33% energy conservation and 53% emissions avoidance, both compared to the Bau levels Low energy conservation and emissions avoidance due to moderate economic growth will limit efforts in improving energy efficiency and investment in infrastructures related to energy supply - demand High economic, high energy demand, high emissions reduction LCS achievable in terms of emissions avoidance without sacrificing high economic development Requirement to achieve LCS (CM2) is high economic development that make investment in better infrastructure (with efficient and low carbon emitting energy systems) possible#45THANK YOU Dr. Takuro Kobashi Institute for Global Environmental Strategies (IGES) - Japan Prof Dr. Yuzuru Matsuoka and Dr. Kei Gomi Kyoto University - Japan Dr. Tomoki Ehara Mizuho Information & Research Institute - Japan Dr. Mikiko Kainuma and Dr Junichiro Fujino National Institute for Environmental Studies (NIES) – Japan Dr. Ucok Siagian Institut Teknologi Bandung (ITB) - Indonesia Dr. Toni Bakhtiar and Indra, MT Institut Pertanian Bogor (IPB) - Indonesia -