Bhutan National Strategy and Action Plan for Low Carbon Development

2 — A separate document describes the developed model and functions

2. A separate document describes the developed model and functions as a user guide. LIMITATIONS AND OMISSIONS Data limitations The most comprehensive data set for energy consumption by sector and sub-sectors is from 2005, namely the ‘Energy Data Directory 2005’ and the ‘Integrated Energy Management Master Plan’. The values are however ﬂawed by uncertainty – Lack of access to certain energy types at certain times of the year or all year round and lack of affordability of energy colours the historic consumption patterns. When making projections 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW based on historical data, there is a risk that these limitations are not fully corrected for. Omissions Fuel prices are not explicitly included in the model. Changes in relative prices may affect real choices and priorities made by the local actors and hence the energy mix in sectors and in the country as a whole. The scenario model does not include an economic module that allows assessments of costs and beneﬁts related to the interventions. There is limited access to detailed data and therefore assessments of costs and beneﬁts are qualitative statements based on available studies. Limiting emissions The long-term national strategy for low carbon development presented in chapter 6 is primarily concerned with limiting the emissions (rather than increasing sequestration) and focuses on areas with a high volume of emissions and/or a signiﬁcantly increasing volume of emissions. The latter not only hints towards a potential future problem but also indicates a ‘window of opportunity’ to leverage the natural drivers for achieving sustainability and carbon goals. Other sectors are given a more cursory review. The threats and opportunities to sequestration capacity are, however, equally relevant. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW © Sonam Dagay, NEC 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW %DVHOLQHVFHQDULRV 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW ENERGY INTENSIVE INDUSTRIES Governing regulation The overall development targets for industrial development are outlined in Vision 20207 and substantiated in the Industrial Development Plan. Supporting legislation: % Industries and Investment Act % Foreign Investment Promotion Act. Production from the natural resource based processing industries has increased during the last years and captured large markets in India. Although Bhutan is known to possess deposits of lead, zinc, copper, tungsten, graphite, iron, phosphate, pyrite and gold, the commercial value of these deposits has not yet been explored and/or assessed. According to U.S. Geological Survey July 2011 the main industrial mineral products include cement, dolomite, granite, marble and sandstone. The new industries are mainly energy-intensive industries that take advantage of the cheap hydro power and the presence of mineral resources. Dungsam Cement is expected to start operation in the beginning of 2012 with a production capacity of one million tonnes per year. Several applications (18) for licenses for ferro-alloy plants are currently under consideration. If these are granted operating license and each have an average emission from production processes equivalent to the existing ferro-alloy plants, then they will have a signiﬁcant impact on the national emission level and thus the carbon balance. ENERGY RELATED BASELINE The analysis distinguishes between energy intensive industries and other industries. Only cement, ferro-alloy and carbide industries are counted in the category ‘Energy intensive industries’. Any other possibly energy intensive industries are counted under ‘Other industries’. For the energy intensive industries the energy service demand is linked directly to assumptions about production levels and establishment of new production units. For both energy intensive and other industries a fuel switch gradually takes place from fuel wood to electricity so that so that in 2040 about 80% of energy service demand in energy intensive industries is satisﬁed by electricity, 10% by coal, and the remainder by other energy. No detailed information on the composition of the various technologies applied in the industries and their conversion efﬁciencies exists. It is therefore assumed that the conversion efﬁciency is 75% for electricity, 25% for fuel wood and 50% for all other fuel types. Efﬁciency gains as result of replacing existing equipment with equipment of higher efﬁciency are assumed to be 10% over the period until 2040. 7 Vision 2020 – Bhutan 2020: A Vision for Peace, Prosperity and Happiness, Part I and II, Planning Commission, RGoB, May 1999. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW An overview of the assumptions is presented in Table 8. 7DEOH)LQDOHQHUJ\FRQVXPSWLRQPHWE\IXHODQGDSSOLHGFRQYHUVLRQHI¿FLHQFLHV HI¿FLHQF\JDLQVDQGIXHOPL[IRUHQHUJ\LQWHQVLYHLQGXVWULHV Conversion Conversion Fuel mix 2005 Fuel mix 2040 Energy service demand (toe) efﬁciency gain efﬁciency 2005 2005 2005-2040 Coal 13,101 50% 10% 24% 10% Electricity 23,622 75% 10% 43% 80% Fuel wood 14,881 25% 10% 27% 0% Gas/diesel oil 889 50% 10% 1.6% 6.6% Kerosene 242 50% 10% 0.4% 0.4% Residual fuel oil 1,638 50% 10% 3.0% 3.0% Total 54,373 100% 100% Figure 15 shows that the energy baseline development for the energy intensive industries shows an increase in energy service demand by a factor 4 (while the GDP growth factor is 8). This is due to the fact that it is assumed that production of the energy intensive industries reaches its limit in 2020 – see more on this in the section “Industrial processes” further ahead. Energy intensive industry 180000 160000 140000 120000 100000 80000 60000 40000 20000 0 Sum of ES Sum of FEC Sum of CO2e Sum of ES Sum of FEC Sum of CO2e 2005 2005 2005 (t) 2040 2040 2040 (t) Residual fuel oil 819 1638 5420 3568 6488 21467 Other biomass 0 0 0 0 0 0 Kerosene 121 242 731 476 865 2614 Gas/Diesel oil 445 889 2916 7850 14273 46823 Fuel wood (s) 3720 14881 0 0 0 0 Electricity 17716 23622 0 95152 115336 0 Coal 6551 13101 53296 11894 21625 87974 )LJXUH (QHUJ\ VHUYLFH GHPDQG WRH ¿QDO HQHUJ\ FRQVXPSWLRQ WRH DQG &2H HPLVVLRQV W DQGIRUHQHUJ\LQWHQVLYHLQGXVWULHV 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW The assumed phase out of fossil fuels and greater electriﬁcation of the energy intensive industries increase the total energy efﬁciency and impacts the emission level signiﬁcantly (see Figure 16). Energy intensive industries - Final energy consumpon (ktoe) Energy related emission (t CO2e) 221 250 189 200 159 150 100 69 62 50 - 2005 2010 2020 2030 2040 2005 2010 2020 2030 2040 Electricity Other RE Fossil energy )LJXUH 'HYHORSPHQW LQ ¿QDO HQHUJ\ FRQVXPSWLRQ NWRH DQG HQHUJ\ UHODWHG &2H HPLVVLRQV NW IRUHQHUJ\LQWHQVLYHLQGXVWULHV INDUSTRIAL PROCESSES Emissions from physical and chemical processes that transform industrial materials are considered by IPCC as process emissions under the industrial processes sector. These processes produce greenhouse gases such as carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). Cement Globally, cement production is the most important source of process CO2 emissions in the industrial processes sector (IPCC 1996). Calcium carbonate (CaCO3) from limestone is transformed into clinker (the major raw material in cement) by applying high-temperature heat in kilns. The end-product is lime or calcium oxide (CaO) and carbon dioxide (CO2). This lime is then mixed with other materials to form cement. The default emission factor is 0.507 t CO2e/t cement not including possible energy related emissions from producing the high- temperature heat. Since 2000 economic growth and large infrastructure projects have been the major driver for the growth in cement production in Bhutan. While there is still expectations of more infrastructure projects the future demand for cement production is expected to depend more on demand from the export market. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW )LJXUH+LVWRULFDOGHYHORSPHQWLQFHPHQWDQGFOLQNHUSURGXFWLRQ There are only four major cement plants producing clinkers from locally sourced limestone: Penden Cement Authority Ltd, Druk Cement Pvt Ltd, Lhaki Cement and Yangzom cement. By 2012 Dungsam Cement is expected to start production with an expected annual production of 1.36 million tonnes cement annually. Calcium carbide Bhutan Carbide and Chemicals Limited (BCCL) is the only industry manufacturing calcium carbide in Bhutan.The main raw materials used to manufacture calcium carbide are limestone and carbonaceous materials such as charcoal, petroleum coke, low ash metallurgical coke and coal. Manufacture of calcium carbide takes place in a three phase submerged electric arc furnace imported from Norway. )LJXUH+LVWRULFDOGHYHORSPHQWLQFDOFLXPFDUELGHSURGXFWLRQ Ferro-silicon The production of ferro-alloys results in emission of CO2. In ferro-alloy production raw ore, carbon materials and slag forming materials are 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW mixed and heated to carbon sources. Since charcoal and wood are based on renewable sources, they are not accounted for as an emission source. Ferro-alloys are most commonly produced by electric submerged arc furnaces.Typical reducing agents are coal and coke. Primary emissions in covered arc furnaces consist almost entirely of carbon-monoxide (CO)8. Data available for the national GHG inventory are national ferro- alloy production statistics and default emission factors. Besides quartzite, most of the raw materials required for ferro alloy industries are imported from India. Almost 90% of the ferro-alloys produced in the country are exported to Indian companies like TATA Steel and Mittal Steel, while the remaining is exported to Japan. )LJXUH+LVWRULFDOGHYHORSPHQWLQIHUURVLOLFRQSURGXFWLRQ However, there are different types of ferro-alloy production based on different compositions of reducing agents resulting in different amounts of emissions. BASELINE FOR NON-ENERGY RELATED EMISSIONS Calculation of baseline carbon emissions is based on the projected demand for the ﬁnal products multiplied by a default emission factor. Final products are export oriented. The baseline demand is partly demand driven and partly driven by environmental regulation. The availability of natural resources and the access to cheap electricity attracts energy intensive industries. Although industrial development is critical for employment generation and economic development, exploitation and processing of many natural resources puts pressure on the local and regional environment resulting 8 Greenhouse gas emissions from ferro-alloy production. Lindstad, Olsen, Tranell, Færden and Lubetsky, 2006 IPCC Guidelines for National Greenhouse Gas Inventory, Volume 3. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW in increased emissions. Therefore, baseline is designed in a pace that can be politically accepted with reference to availability of resources and the environment and social impacts (see Table 9). 7DEOH%DVHOLQHDVVXPSWLRQVE\VXEVHFWRU Sub sector Assumptions Production increase directly related to establishment of Industrial process general new production capacity1 Dungsam Cement starts production in 2012 with an annual production of 1.37 million tonnes cement. No Cement industry further capacity increase but existing capacity remains constant until 2040 No further increase in capacity due to resource and Calcium carbide environmental constraints but existing capacity remains constant until 2040 NEC has received a number of applications for new Ferro-silicon production. Capacity is increased by 30,000 tonnes per year until 2020 and then constant until 2040 Total non-energy related emissions are expected to increase from around 500 kt in 2010 to around 2,000 kt in 2040 as shown in Figure 20. )LJXUH %DVHOLQH SURMHFWLRQ RI QRQHQHUJ\ UHODWHG &2H HPLVVLRQV NW IRU HQHUJ\ LQWHQVLYHLQGXVWULHV OTHER INDUSTRIES Energy intensive industries dominate in size while other industries dominate in number. Some of the industries have been established in industrial estates among other to allow access to necessary facilities, minimise environmental impact and further clusters of industries which may be linked by commonalities or may complement each other. Medium and small scale industries include food processing industries textile, paper, resin and turpentine industries. Many industries are so- called”cottage industries”. Fuel wood, electricity and coal are the main sources of energy in other industries. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW ENERGY RELATED BASELINE The energy service demand of other industries is assumed to follow GDP development with an elasticity of 0.8. It is assumed that a fuel switch gradually takes place from fuel wood to electricity so that in 2040 the energy service demand is satisﬁed by 50% electricity, 25% fuel wood, 20% coal, and 5% other energy. No detailed information on the composition of the various technologies applied in the industries and their conversion efﬁciencies exists. It is therefore assumed that the conversion efﬁciency is 75% for electricity, 25% for fuel wood and 50% for all other fuel types. However, it must be stressed that conversion efﬁciencies only have an effect for the end-results in sectors where fuel switching take place. Where little fuel switch takes place over the years, energy efﬁciency gains are likely to have a higher impact on the development. Efﬁciency gains are results of replacing existing equipment with equipment of higher efﬁciencies and are in the other industries sector assumed to be 10% over the period until 2040. An overview of the assumptions is presented below (Table 10). 7DEOH )LQDO HQHUJ\ FRQVXPSWLRQ E\ IXHO DQG DSSOLHG FRQYHUVLRQ HI¿FLHQFLHV HI¿FLHQF\JDLQVDQGIXHOPL[IRURWKHULQGXVWULHV Energy service demand (toe) Conversion efﬁciency 2005 Conversion efﬁciency gain Fuel mix 2005 Fuel mix 2040 2005 2005-2040 Coal 14,397 50% 10% 31.2% 20% Electricity 12,783 75% 10% 27.7% 50% Fuel wood 15,437 25% 10% 33.4% 25% Gas/diesel oil 3,550 50% 10% 7.7% 5% Total 42,617 100% 100% The bar diagram in Figure 21 shows the change from 2005 to 2040 for three indicators, namely the energy service demand (ESD), the ﬁnal energy consumption (FEC), and the CO2e emission (CO2e). The ﬁrst three bars show the situation in 2005, the ﬁnal three bars the situation in 2040. The difference between energy service demand and the ﬁnal energy consumption expresses the efﬁciency of the conversion of energy. The difference between the ﬁnal energy consumption and the CO2e emission reﬂects the choice of energy type and the associated emission. If the ﬁnal energy consumption is fully based on renewable 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW energy sources, then the CO2e emission is zero. As shown in Figure 21, the baseline development for other industries experiences an increase in both energy service demand and the ﬁnal energy consumption by a factor 5. The fuel shift trend is assumed to be less strong in other industries than in energy intensive industries and fuel wood is not completely phased out in the baseline scenario. The development in CO2e emissions is a factor 3 from 2005 to 2040. Reason for the lower factor relative to energy service demand and ﬁnal energy consumption is that fuel wood is assumed to have zero CO2e emissions. Total emissions thus increase from around 70 kt in 2005 to 208 kt in 2040 as can be seen in Figure 22. Other industries 250000 200000 150000 100000 50000 0 Sum of ES Sum of FEC Sum of CO2e Sum of ES Sum of FEC Sum of CO2e 2005 2005 2005 (t) 2040 2040 2040 (t) Other biomass 0 0 0 0 0 0 Gas/Diesel oil 1775 3550 11646 5837 10613 34817 Fuel wood (s) 3859 15437 0 29186 106131 0 Electricity 9587 12783 0 58372 70754 0 Coal 7199 14397 58568 23349 42452 172700 )LJXUH (QHUJ\ VHUYLFH GHPDQG WRH ¿QDO HQHUJ\ FRQVXPSWLRQ WRH DQG &2H HPLVVLRQV W DQGIRURWKHULQGXVWULHV Other industries - Final energy consumpon (ktoe) Energy related emission (kt CO2e) 250 208 180 200 154 150 91 100 70 50 - 2005 2010 2020 2030 2040 2005 2010 2020 2030 2040 Electricity Other RE Fossil energy )LJXUH 'HYHORSPHQW LQ ¿QDO HQHUJ\ FRQVXPSWLRQ NWRH DQG HQHUJ\ UHODWHG &2H HPLVVLRQV NW IRURWKHULQGXVWULHV 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW DOMESTIC AVIATION AND INTERNATIONAL AVIATION BUNKERS Until recently Bhutan has only had one international airport and limited ﬂights. With the launch of domestic airports and services the ﬂeet of domestic and international helicopters and airplanes will increase. The domestic airports are intended for both passenger and cargo transport. Domestic air travel is counted in the GHG inventory while international aviation (“bunkers”) are merely a memo item based on IPCC guidelines. ENERGY RELATED BASELINE The energy service demand for international air trafﬁc is assumed to follow GDP development with an elasticity of 0.8 until 2020 where after the demand remains unchanged. A fuel shift towards 5% biofuel in international air trafﬁc is expected to take place. Domestic aviation is assumed to stabilise in 2020 at a level equal to half the 2005 level for international air trafﬁc, which was 957 toe9. The conversion efﬁciency of the various air planes and helicopters are as a whole assumed to be 30% and the energy conversion efﬁciency gains 10% over the period until 204010. In this sector only the efﬁciency gains have inﬂuence on the end results because no major fuel switching is taking place. International aviation is not counted towards the national CO2e emissions balance and is mentioned here only for the sake of completion. The resulting development in energy service demand, ﬁnal energy consumption and CO2e emission is shown in Figure 23. 9 toe = tonne oil equivalents. 10 The IEA has carried out a study of scenarios and strategies for technology develop- ment. In their baseline development scenario for the development from 2008-2025 and 2025-2050 the IEA assumes a 0.8% and 7% per year improvement, respectively, in technological energy efﬁciency due to the inherent competitiveness of the aviation industry (Energy Technology Perspectives 2008: Scenarios and Strategies to 2050, IEA, p457-458). An estimate of the gains due to improved operational efﬁciency and load factor is also made but this is judged irrelevant to the situation of Bhutan where there is climate, terrain, and modal-shifting constraints that limit the options available. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Aviaon 9000 8000 7000 6000 5000 4000 3000 2000 1000 0 Sum of Sum of Sum of ES Sum of FEC Sum of ES Sum of FEC CO2e 2005 CO2e 2040 2005 2005 2040 2040 (t) (t) Jet kerosene - Interna/onal avia/on 287 957 2905 643 1949 5917 Jet kerosene - Domes/c avia/on 0 0 0 164 498 1512 Biofuel (diesel) - Interna/onal avia/on 0 0 0 14 43 255 Biofuel (diesel) - Domes/c avia/on 0 0 0 0 0 0 )LJXUH (QHUJ\ VHUYLFH GHPDQG WRH ¿QDO HQHUJ\ FRQVXPSWLRQ WRH DQG &2H HPLVVLRQV W DQGE\IXHOIRUDYLDWLRQ Figure 24 shows that the total emission relating to aviation rise from about 3 kt CO2e in 2005 to about 8 kt CO2e in 2040. It is worth noting, that aviation related CO2e emissions are generally into the high atmosphere, and this is thought to have a larger greenhouse effect than CO2e released at sea level. Aviaon - Final energy consumpon (ktoe) Energy related emission (kt CO2e) 8,1 7,8 3,0 7,7 2,5 2,0 1,5 3,8 2,9 1,0 0,5 - 2005 2010 2020 2030 2040 2005 2010 2020 2030 2040 Other RE Fossil energy )LJXUH 'HYHORSPHQW LQ ¿QDO HQHUJ\ FRQVXPSWLRQ NWRH DQG HQHUJ\ UHODWHG &2H HPLVVLRQV NW IRUDYLDWLRQ ROAD TRANSPORT There has been a signiﬁcant increase in the number of private vehicles in Bhutan, especially in Thimphu. Between 2001 and 2009 the number of light vehicles increased at an average rate of around 15% per year. This increase is a result of growth in both urban population and income levels (and taxation schemes). According to RSTA there are approximately 37,000 light vehicles and taxis (81% of the stock of vehicles per end of April 2011) of which 74% use petrol. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW 7DEOH+LVWRULFDOGHYHORSPHQWLQQXPEHURIYHKLFOHVE\IXHOW\SH 567$ Petrol Diesel TOTAL Grand Light v Taxi Total Heavy Work Total total 2005 14.365 2.050 16.415 11.055 1.002 12.057 28.472 2006 17.355 2.038 19.393 12.610 578 13.188 32.581 2007 19.798 2.218 22.016 13.055 633 13.688 35.704 2008 24.244 2.511 26.755 13.779 744 14.523 41.278 2009 27.145 2.859 30.004 14.886 929 15.815 45.819 2010 31.162 3.599 34.761 17.361 1.260 18.621 53.382 With the exception of year 2008 there have been annual increases in fuel consumption of 10-14% in the period 2005-2009. There are only 3 companies importing fuel to Bhutan. 7DEOH)XHOLPSRUW 72( *+*,QYHQWRU\ Year Diesel Petrol 2005 47.055 11.127 2006 47.508 12.508 2007 52.988 13.895 2008 54.479 14.326 2009 60.256 16.291 The Bhutan Transport 2040 Integrated Strategic Vision (ADB, December 2010) identiﬁes the following critical challenges where improvements are required: % Poor regulation of number of cars (cost of cars and cost of fuel); % Poorly developed urban public transport; % Poorly regulated taxis – these constitute an important element of the urban transport, especially in Thimphu and Phuentsholing11; % Poorly regulated parking in Thimphu and Phuentsholing. These critical areas will form the basis for mitigation measures. ENERGY RELATED BASELINE There has historically been a close correlation between increase in GDP per capita and increase in the number of vehicles (see Figure 25 below). 11 Bhutan Urban Transport Study, International Finance Corporation, September 2011. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW )LJXUH &RPSDULVRQ RI UHDO *'3 PLOOLRQ 1X DQG QXPEHU RI YHKLFOHV The increase in road transport is in the baseline assumed to continue to increase with GDP with an elasticity factor of 0.8 for light duty vehicles and two wheelers until 2020 when the market is assumed saturated and the need for transport services stabilised. The same is assumed for heavy duty vehicles. In the baseline for road transport a small shift towards electricity is envisioned for light duty vehicles and two wheelers. Also a slight increase in transport with light duty vehicles based on gas/diesel oil is assumed at the expense of gasoline. Due to the global attention to reducing emissions from the transport sector a higher conversion efﬁciency gain is expected in road transport than in any of the other sectors of the economy, namely 15%. 7DEOH )LQDO HQHUJ\ FRQVXPSWLRQ E\ IXHO DQG DSSOLHG FRQYHUVLRQ HI¿FLHQFLHV HI¿FLHQF\JDLQVDQGIXHOPL[ Final energy Conversion Conversion efﬁciency Fuel mix Fuel mix consumption efﬁciency gain 2005- 2005 2040 (toe) 2005 2005 2040 Heavy duty vehicles Gas/Diesel oil 37,351 25% 15% 100% 100% Light duty vehicles Electricity 0 75% 15% 0% 10% Gas/Diesel oil 6,432 20% 15% 42,3% 50% Gasoline 8,787 15% 15% 57,7% 40% Two wheelers Electricity 0 75% 15% 0% 10% Gasoline 2,524 15% 15% 100% 90% TOTAL 55,094 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Road transport more than doubles over the period 2005-2020 where after it remains more or less constant and the CO2e emissions follow suit. In the course of the 35 year period 2005-2040, the emission increases from 178 kt CO2e to 347 kt CO2e (see Figure 26 and Figure 27). Road transport 400000 350000 300000 250000 200000 150000 100000 50000 0 Sum of Sum of Sum of ES Sum of FEC Sum of ES Sum of FEC CO2e 2005 CO2e 2040 2005 2005 2040 2040 (t) (t) Gasoline 1697 11311 33325 3819 22140 65230 Gas/Diesel oil 10624 43783 143634 24097 86179 282717 Electricity 0 0 0 293 339 0 Biofuel (diesel) 0 0 0 0 0 0 )LJXUH (QHUJ\ VHUYLFH GHPDQG WRH ¿QDO HQHUJ\ FRQVXPSWLRQ WRH DQG &2H HPLVVLRQV W DQGIRUURDGWUDQVSRUW Road transport - Final energy consumpon (ktoe) Energy related emission (kt CO2e) 376 361 348 140,0 120,0 100,0 228 80,0 177 60,0 40,0 20,0 - 2005 2010 2020 2030 2040 2005 2010 2020 2030 2040 Electricity Other RE Fossil energy )LJXUH 'HYHORSPHQW LQ ¿QDO HQHUJ\ FRQVXPSWLRQ NWRH DQG HQHUJ\ UHODWHG &2H HPLVVLRQV NW IRUURDGWUDQVSRUW TERTIARY SECTOR The tertiary sector is also often referred to as the commercial/ institutional sector. The tertiary sector includes both public and private enterprises. Examples are state and local government institutions, religious institutions, health & education sector, tourism sector including hotels and restaurants, and commerce. Within some there is already a noticeable awareness of environmental and climate issues and for example the tourist trade and the monasteries sectors are taking steps to increase sustainability of their activities – something which is very much in line with the idea of ”Brand Bhutan”. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW ENERGY RELATED BASELINE The development in energy service demand of the tertiary sector excluding cremation is assumed to follow the GDP development with an elasticity of 0.8 and to mimic the development of the urban households in terms of fuel mix and conversion efﬁciency gains. The demand for cremation is assumed to follow the population growth. Cremation will continue to rely on fuel wood but an efﬁciency gain of 10% over the period 2005-2040 is assumed. An overview of the baseline assumptions for the tertiary sector (excluding cremation) is presented below in Table14). A signiﬁcant shift away from fuel wood and kerosene is assumed. Gradual automatic efﬁciency gains reduce energy service demand by 10% in 2040 for all end-uses and fuels. 7DEOH )XHO PL[ DQG DVVXPHG IXHO PL[ LQ WKH WHUWLDU\ VHFWRU H[FOXGLQJ FUHPDWLRQ 7KHIXHOZRRGLVDVVXPHGSURGXFHGLQDVXVWDLQDEOHPDQQHU _ ] ` ] ^] ` ] ] ! ] ` ] \ ] Z [ Z [ Z [ Z [ Z [ 4 ¦ ¦ + ''% ¦ :¦ ¦ 99¦ ;:¦ 9#¦ ¦ ¦ :¦ . 0 1 7¦ 7¦ 997¦ ;¦ 7¦ 7¦ ¦ ¦ ;¦ $ 3 :¦ ¦ :¦ ¦ During the period 2005-2040 the demand for energy services in the tertiary sector increases with more than a factor 5. The ﬁnal energy consumption increases by less than a factor 4 mainly due to a shift towards electricity. The use of briquettes for space heating and LPG for cooking increases signiﬁcantly. However, since briquettes are assumed to have zero CO2e emission, the total increase in CO2e emissions is only by a factor 3. In absolute terms the CO2e emission increases from 18 kt CO2e in 2005, as shown below in Figure28, to 60 kt CO2e in 2040. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Terary sector 180000 160000 140000 120000 100000 80000 60000 40000 20000 0 Sum of Sum of Sum of ES Sum of FEC Sum of ES Sum of FEC CO2e 2005 CO2e 2040 2005 2005 2040 2040 (t) (t) Solar hea/ng 0 0 0 0 0 0 LPG 644 1074 2872 11331 17168 45912 Kerosene 2056 5140 15530 3227 4633 13999 Fuel wood (s) 12214 24038 0 8473 13162 0 Electricity 9172 10191 0 96556 99190 0 Brique¨es (s) 16 65 0 5547 20170 0 )LJXUH (QHUJ\ VHUYLFH GHPDQG WRH ¿QDO HQHUJ\ FRQVXPSWLRQ WRH DQG &2H HPLVVLRQV W DQGIRUWKHWHUWLDU\VHFWRU Terary sector - Final energy consumpon (ktoe) Energy related emission (kt CO2e) 180 60 60 56 160 140 120 35 100 80 60 18 40 20 - 2005 2010 2020 2030 2040 2005 2010 2020 2030 2040 Electricity Other RE Fossil energy )LJXUH 'HYHORSPHQW LQ ¿QDO HQHUJ\ FRQVXPSWLRQ NWRH DQG HQHUJ\ UHODWHG &2H HPLVVLRQV NW IRUWKHWHUWLDU\VHFWRU RESIDENTIAL SECTOR FRAMEWORK AND CHARACTERISTICS OF PRESENT SITUATION Residential carbon emissions have remained fairly constant y due to relatively low energy consumption and a higher share of the energy demand met by sustainable biomass and hydro power based electricity. Household energy consumption is governed by access to the various sources of energy and affordability. Residential energy consumption pattern thus depends on the household income and location; urban and 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW rural. In this report a distinction is therefore made between urban and rural households. As of 2005, more than 96% of urban households were electriﬁed while only 40% of rural household were electriﬁed. For an average urban household more than 60% of energy consumption in energy units is commercial energy like electricity, LPG and kerosene, while the consumption of commercial energy for an average rural electriﬁed household is 13% and for a non-electriﬁed household it’s less than 6%. This indicates that the non-electriﬁed households are low income households living in remote areas whereby commercial energy is unaffordable even if it’s available. As a result of the development strategy and increasing welfare among households in Bhutan it can be expected that: % Non-electriﬁed rural households will be electriﬁed and their consumption of commercial energy would increase either because they migrate to urban centres or because they gain inexpensive access to these energy types; % Electriﬁed rural households will increase their consumption of commercial energy towards a pattern known from the urban centres today. % Urban households will increase their consumption of commercial fuels especially electricity due to increasing number of electricity consuming appliances. 7DEOH1XPEHURIKRXVHKROGVE\DFFHVVWRHOHFWULFLW\LQ %KXWDQ/LYLQJ6WDQGDUG 6XUYH\16%'HFHPEHUS Urban households Rural households Total households Grid electricity 98,2% 56,6% 69,1% Other electricity 0,6% 3,6% 2,7% No electricity 1,3% 39,8% 28,2% Bhutan living standard survey 2007 with a sample of 125,500 households (NSB, December 2007, p. 80) shows the difference in energy consumption between urban and rural households (see Table 16). Worth noting is the fact that in 2007 a little more that 40% of the total number of surveyed households did not have dedicated space heating. This illustrates the challenge of interpretation of energy statistics. Apart from the fact that many households truly do not heat their living space, the technologies used for cooking and hot water heating in many of the households contributes to heating of the living space. Fodder cooking is prevalent in many rural households and equally contributes to space heating. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW 7DEOH1XPEHURIKRXVHKROGVE\DFFHVVWRHOHFWULFLW\LQ %KXWDQ/LYLQJ6WDQGDUG 6XUYH\16%'HFHPEHUS End-use Urban households Rural households Total households Ligh/ng Electricity 97,4% 56,1% 68,5% Kerosene/gas lamp 1,9% 37,4% 26,7% Candles 0,3% 0,7% 0,6% Other 0,5% 5,8% 4,2% Cooking Electricity 44,7% 13,0% 22,5% Gas 50,0% 27,4% 34,2% Wood 2,4% 57,2% 40,7% Kerosene 0,0% 0,1% 0,1% Other 1,6% 0,6% 0,9% Hea/ng No hea/ng 37,0% 44,1% 42,0% Wood/coal stove (bukhari) 21,2% 29,9% 27,3% Electric heater 36,0% 3,3% 13,1% Kerosene heater 2,6% 0,5% 1,1% Straw/brush/manure stove 0,8% 3,5% 2,7% Other 2,1% 18,7% 13,7% Similarly, in order to make projections on the future household energy consumption and understanding of the technologies available to each household is important. With an increase in household income and access to electricity an “electriﬁcation” of the consumption pattern naturally takes place. 7DEOH 'LVWULEXWLRQ RI WHFKQRORJLHV LQ KRXVHKROGV LQ %KXWDQ /LYLQJ 6WDQGDUG 6XUYH\16%'HFHPEHUS Urban households Rural households Total households Appliances Refrigerator 60,0% 11,3% 25,9% Microwave oven 9,2% 1,6% 3,9% Modern stove 50,9% 18,5% 28,3% Rice cooker 95,6% 47,5% 62,0% Curry cooker 83,5% 33,5% 48,5% Water boiler 86,4% 29,3% 46,5% Bukharies 23,4% 24,8% 24,4% Washing machine 12,7% 1,7% 5,0% TV 79,4% 19,8% 37,7% VCR/VCD 40,8% 12,6% 21,1% Radio 60,2% 62,8% 62,0% Computer 11,6% 1,8% 4,7% Heater 52,5% 10,0% 22,8% Fan 37,3% 9,8% 18,1% Electric iron 44,3% 8,0% 18,9% Sewing machine 8,1% 4,6% 5,6% Other Power-/ller 1,6% 3,9% 3,2% Grinding machine 3,8% 6,0% 5,3% Transport Bicycle 8,6% 3,1% 4,8% Motorbike, scooter 9,1% 2,7% 4,6% Family car 24,3% 4,2% 10,2% Other vehicle 5,4% 1,8% 2,9% Tractor 1,5% 0,9% 1,1% 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW The Energy Data Directory 2005 lists the speciﬁc household electricity consumption at 324 kWh/year for urban households and 341 kWh/year for rural households with access to electricity – a very low number (see Table 18 below). 7DEOH(OHFWULFLW\FRQVXPSWLRQOHYHOLQHOHFWUL¿HGKRXVHKROGV (''S Households Electriﬁed hh Electricity consumpon (kWh) kWh/household Urban 36923 11949649 324 Rural 35140 11998407 341 Total 72063 23948056 332 Although fuel wood and other biomass consumed in households do not contribute towards the national carbon emissions (assuming sustainable exploitation) there are other reasons that justify limiting the use of these such as health concerns and increasing pressure on possibly limited biomass resources. Furthermore, the social status associated with fossil fuels and electricity should not be underestimated as a driver for a development away from fuel wood and other biomass when opportunity arises. ENERGY RELATED BASELINE Table 19 (below) lists the baseline assumptions made for calculation of the future energy service demand of the residential sector.The migration from rural to urban areas is expected to reduce the share of the rural population from 69% in 2005 to 23% in 2040. The demand for energy services is assumed to increase with GDP/capita with an elasticity of 0.8. Gradual automatic efﬁciency gains reduce energy service demand by 10% in 2040 for all end-uses and fuels. 7DEOH)XHOPL[DQGHVWLPDWHGIXHOPL[LQWKHUHVLGHQWLDOVHFWRU _ ] ` ] ^] ` ] ] ! ] ` ] f !] ] Z [ Z [ Z [ Z [ Z [ 2. 4 ¦ 4. ¦ ;¦ + ''% ¦ ¦ ¦ 77¦ ¦ ¦ ¦ ¦ ;¦ . 0 1 9:¦ #¦ 9:¦ ¦ :¦ ¦ ¦ ¦ ¦ ¦ ¦ ;¦ $ 3 ¦ ;¦ ¦ ¦ , ¦ & 4. ;¦ + ''% ;¦ :¦ ¦ 99¦ 97¦ ¦ ¦ ¦ ¦ :¦ . 0 1 ¦ ;¦ 9¦ ¦ #¦ ¦ ;¦ $ 3 ¦ ¦ ¦ , ¦ 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW The results of the baseline projection of the residential sector are presented in the following Figure 30 and Figure 31. The energy service demand in 2040 is more than 4 times larger than in 2005. Due to efﬁciency gains but mainly due to fuel shift from fuel wood the ﬁnal energy consumption in 2040 is only twice the size of the consumption in 2005. The CO2e emissions increase by less than a factor 4 over the period in question and main contributors are briquettes and LPG. The speciﬁc ﬁnal energy consumption increases from 0.22 toe/capita in 2005 to 0.28 toe/capita in 2040 while the CO2e emissions grow from 0.04 t/capita to 0.20 t/capita. In absolute terms the emissions rise from 28 kt CO2e to 98 kt CO2e in the period 2005-2040. Residenal sector 300000 250000 200000 150000 100000 50000 0 Sum of Sum of Sum of ES Sum of FEC Sum of ES Sum of FEC CO2e 2005 CO2e 2040 2005 2005 2040 2040 (t) (t) Solar hea/ng 0 0 0 311 311 0 LPG 2388 3980 10643 20543 31126 83238 Kerosene 2236 5591 16893 2928 4344 13125 Fuel wood (s) 35071 123676 0 27019 83876 0 Electricity 3397 3807 0 119851 125520 0 Brique¨es (s) 0 0 0 6417 23336 0 Biogas 0 0 0 890 1471 1813 )LJXUH (QHUJ\ VHUYLFH GHPDQG WRH ¿QDO HQHUJ\ FRQVXPSWLRQ WRH DQG &2H HPLVVLRQV W DQGIRUWKHUHVLGHQWLDOVHFWRU Residenal sector - Final energy consumpon (ktoe) Energy related emission (kt CO2e) 300 106 98 91 250 200 150 42 100 28 50 - 2005 2010 2020 2030 2040 2005 2010 2020 2030 2040 Electricity Other RE Fossil energy )LJXUH 'HYHORSPHQW LQ ¿QDO HQHUJ\ FRQVXPSWLRQ NWRH DQG HQHUJ\ UHODWHG &2H HPLVVLRQV NW IRUWKHUHVLGHQWLDOVHFWRU 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW AGRICULTURE AND FORESTRY Although the agriculture share of GDP is decreasing to just below 20% in 2008, around 70% of the population are still dependent on agriculture for livelihood. Carbon emission from agricultural activity stems from husbandry, crop production, and energy consumption for tools and machinery. The non- energy related emissions within agriculture are signiﬁcant, primarily due to CH4 emissions from enteric fermentation and manure management. Agricultural soils and their cultivation are, however, also important contributors, namely below 450 kt CO2e in 2000 whereas enteric fermentation and manure contributed about 570 kt CO2e. Decisions on choice of crop and cultivation methods have a signiﬁcant impact on the level of emissions.The natural conditions and climate change place a limit on the expansion of crop areas but overall cultivation strategy (organic – not organic), reﬁnement of cultivation methods (including use of fertilisers), and deliberate selection of crops can increase the yield while curbing emissions.The non-energy related emission from agriculture and its future development paths are not included in the present analysis. Also, the non-energy related emissions from forestry or rather sequestration is not analysed in this project. Due to lack of data and time for analysis, the sequestration capacity calculated for year 2000 is assumed constant throughout the analysis period. Emissions from use of tools and machinery (small tractors, threshers, pumps etc.) are addressed in the following section on energy related baseline emissions. If agriculture increases in intensity, energy use for tools and machinery is likely to increase as is emission if no preventive actions are taken. The machinery is considered “off-road” and thus not part of the “on-road” transport addressed in section 3.4. Details on agricultural machinery and their energy consumption were not available for the present analysis. The analysis is therefore to be considered very preliminary. It is worth noting that such emissions in the GHG Inventory are lumped under total transport emissions as segregated data on consumption of diesel or petrol for agricultural purposes and for road transport were not available. ENERGY RELATED BASELINE With regard to the energy services needed within the agriculture and forestry sector, a distinction is made between fodder cooking and other production processes. Fodder cooking is assumed to be phased out while the energy service demand for other production processes is assumed to follow GDP development with an elasticity of 0.4. Fodder cooking is entirely based on fuel wood with a conversion efﬁciency of only 10% in 2005. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Other production processes see a fuel shift from near 90% fuel wood to in particular biogas but also electricity and gas/diesel oil. An overview of the assumptions is presented below. TDEOH )LQDO HQHUJ\ FRQVXPSWLRQ E\ IXHO DQG DSSOLHG FRQYHUVLRQ HI¿FLHQFLHV HI¿FLHQF\JDLQVDQGIXHOPL[IRUDJULFXOWXUHDQGIRUHVWU\ Conversion Energy service Conversion Fuel mix 2005 Fuel mix 2040 demand (toe) efﬁciency gain 2005 efﬁciency 2005 2005-2040 Production processes 4,554 Biogas 0 20% 10% 0% 40% Electricity 68 75% 10% 1.5% 20% Fuel wood 3,997 20% 10% 87.8% 20% Gas/diesel oil 489 20% 10% 10.7% 20% Fodder cooking 49,843 Fuel wood 49,843 10% 10% 100% 100% Total 108,794 The total energy service demand as well as the ﬁnal energy consumption is reduced signiﬁcantly in the baseline assuming that fodder cooking is phased out. Presently, fodder cooking is assumed to be solely based on fuel wood with very low efﬁciency. The energy service demand for production processes alone increases with a factor 11 over the considered period. On the other hand, assuming fuel wood is produced sustainably, there net zero impact on emission levels. Electricity is assumed to be produced by renewable energy and thus only biogas and gas/diesel oil consumption contribute to CO2e emissions in 2040. The emission level is less than 2 kt in 2005 (please see Figure 32) but increases by a factor 7 over the period and reaches 11 kt in 2040. Agriculture and forestry 60000 50000 40000 30000 20000 10000 0 Sum of Sum of )LJXUH (QHUJ\ VHUYLFH GHPDQG WRH Sum of ES 2005 Sum of FEC 2005 CO2e 2005 Sum of ES 2040 Sum of FEC 2040 CO2e 2040 (t) (t) ¿QDO HQHUJ\ FRQVXPSWLRQ WRH DQG &2H Gas/Diesel oil 98 489 1604 433 1967 6453 HPLVVLRQV W DQGIRUDJULFXOWXUH Fuel wood (s) 5784 53840 0 433 1967 0 Electricity 51 68 0 433 525 0 DQGIRUHVWU\ Biogas 0 0 0 865 3934 4850 Biofuel (diesel) 0 0 0 0 0 0 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Agriculture and forestry - Final energy consumpon (ktoe) Energy related emission (kt CO2e) 11,3 60,0 50,0 8,0 40,0 5,3 30,0 20,0 2,6 1,6 10,0 - 2005 2010 2020 2030 2040 2005 2010 2020 2030 2040 Electricity Other RE Fossil energy )LJXUH 'HYHORSPHQW LQ ¿QDO HQHUJ\ FRQVXPSWLRQ NWRH DQG HQHUJ\ UHODWHG &2H HPLVVLRQV NW IRUDJULFXOWXUHDQGIRUHVWU\ MUNICIPAL SOLID WASTE Government body The lead institutions in charge of implementation of the Waste Prevention and Management Act, 2009 are: % The National Environment Commission as the overall coordinating agency; % The Ministry for Works and Human Settlements in collaboration with the Thromdes – Ensuring waste prevention and management in the Thromdes; % The Dzongkhag Tshongdu and Gewog Tshongde supported by the Dzongkhag, Dungkhag and Gewog administration – Ensuring waste prevention and management at Dzongkhag, Dungkhag, Gewog and Chiwog12 level not covered by the above including rural human waste with guidance from the Ministry of Health. Amongst the various collaborating agencies, the most pertinent in relation to future carbon emissions development and energy production are the Department of Industry under the Ministry of Economic Affairs responsible for industrial waste and Tourism Council of Bhutan responsible for waste from hotels, restaurants, camp sites and trekking routes. Government regulation The ‘Waste Prevention and Management Act of Bhutan 2009’ is based on three guiding principles: % Precautionary actions; % Polluters pay principle and % Principle of reduce, reuse and recycle. The waste sector accounted for about 3% of the total carbon emissions in 2000. The dominant category in 2000 was by far solid waste disposal. 12 The administrative levels are: Thromde – urban area, Dzongkhag – district, Dungkhag, Gewog – block. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Two major sources of carbon emissions from waste management activity in the country are: % Solid waste from the ten urban areas, namely Thimphu, Phuentsholing, Samtse, Paro, Gelephu, Damphu, Samdrupjongkar, Bumthang, Trashigang, and Mongar. Residential and commercial waste water treatment plants in Thimphu and Phuentscholing, with centralised sewage treatment facilities. Compact eco-line sewage treatment plants that cover the commercial waste exist in Trashigang, Gelposhing, and Damphu (Tsirang). Thimphu generates about 50 tonnes of solid waste per day13. The total volume waste generated by the two major urban centres is assumed to be around 80 tonnes per day. NON-ENERGY RELATED BASELINE No trend data exists for solid waste and waste water production in Bhutan. In the second National GHG inventory it is assumed that increase in waste is directly proportional to the population growth (i.e. 1.9% per year till 2020). According to IEMMP 2010 Thimphu and Phuentsholing generated 37 and 25 tonnes of solid waste per day, respectively, and Bhutan 81,119 tonnes/year in 2005. This indicates that there is potential to sustain more than 3 MW power generation plant (TERI 2010, p54).The study by TERI suggests starting with a 1 tonne per day demonstration plant in Thimphu,treating organic waste from hotels and the vegetable market. It is assumed that generation of solid waste is directly linked to the income, i.e. determined by the increase in GDP/capita. The base year for the baseline is 2005 with solid waste generation of around 0.5 kg/day per capita. Methane emissions from municipal solid waste As presented below (Figure 800 34), the absolute emission from municipal waste increases from 700 approximately 300 kt CO2e in 600 2005 depending on the annual Gg CO2e/year 500 growth in the amount of waste. Gg CO2e 400 Gg CO2e/year if 1,5%/year growth 300 Gg CO2e/year if 200 5%/year growth 100 )LJXUH3URMHFWLRQRI&2HHPLVVLRQV 0 NW IURPPXQLFLSDOVROLGZDVWHIRUWKUHH 2005 2010 2015 2020 2030 2040 GLIIHUHQWJURZWKVFHQDULRV 13 Information from the Mayor of Thimphu, September 2011. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW However, in the GHG inventories rural municipal waste is not counted. An estimate of the baseline development of the urban municipal waste related emission is presented in Figure 35 below. The underlying assumption is that waste generation is assumed to have an elasticity of 0.10 to GDP/capita. The CO2e emission starts at less than 100 kt CO2e in 2005 and increases to 422 in 2040. Contributions from municipal waste from Thimphu alone are expected to increase from 38 to about 170 kt CO2e. Urban municipal waste 450 400 350 300 kt CO2e 250 All urban 200 Thimphu 150 100 50 0 2005 2010 2015 2020 2025 2030 2035 2040 )LJXUH3URMHFWLRQRI&2HHPLVVLRQV NW IURPXUEDQPXQLFLSDOZDVWH COMPARISON OF MODEL RESULTS AND GHG INVENTORY ENERGY RELATED EMISSIONS The approach applied for the baseline calculation of energy-related CO2e emissions does not strictly follow the approach applied in the GHG inventory. Instead the starting point is the energy service demand and the CO2e emission level is linked to the type of fuel consumed. A cross check is therefore carried out to verify that the modelled CO2e emissions 2005 (and 2010) do not differ signiﬁcantly from the values derived from the GHG inventory approach. A comparison between the carbon emissions calculated in the applied energy model and the ﬁgures from the 2nd National GHG inventory shows a reasonable consistency (see Table 21). The main difference deviation occurs for industry in 2009/2010 where the model arrives at 160 kt while the inventory estimate is 228 kt. The explanation is that excluding fuel wood and electricity ,the 2005 fuel consumption is 33,817 toe in the energy model and 42,380 toe in the GHG inventory. Also the emissions factors applied in the energy model are slightly higher. In 2010 the ﬁnal energy consumption calculated by the energy model is 40,838 toe excluding fuel wood and electricity while the 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW 2009 ﬁgure of the GHG inventory is 58,461 toe. The main reason for the difference is that the model assumes a larger share of electricity in the ﬁnal energy consumption. No attempt has been made to rectify this difference in the model since the primary concern is to portray the possible situation in 2020, 2030 and 2040. The energy related emissions increase from 360 kt in 2005 to 1,072 kt in 2040 which equals 0.57 t/capita and 1.1 t/capita, respectively. In comparison, the ﬁgures reported for 2008 for Bangladesh, India, and USA are 0.36 t/capita, 1.3 t/capita, and 19.7 t/capita (www.cdiac.ornl. gov) respectively. 7DEOH(QHUJ\UHODWHG&2HHPLVVLRQV NW FDOFXODWHGLQHQHUJ\PRGHODQGHVWLPDWHG IURP*+*LQYHQWRU\ !!]! _] "^ # Z Z { % ' . % 7 7 # (% 7 :# 2 :: # :7 ! \$\ |} [~ |Z Z| NON-ENERGY RELATED EMISSIONS A similar comparison is made concerning non-energy related emissions in Table 22. While agricultural emissions increase slightly in the model there is a small reduction in the GHG inventory. The difference can be ascribed to the fact that the model simulates a long-term trend while the GHG inventory shows that actual development from year to year and therefore the GHG inventory shows greater variation from year to year. The ﬁgures for emissions from industrial processes are quire consistent between the model and the GHG inventory. The growth in the waste related emissions is the same for the model and the GHG inventory, but the model starts at a lower level and continues to be lower than the GHG inventory ﬁgures. 7DEOH1RQHQHUJ\UHODWHG&2HHPLVVLRQV NW FDOFXODWHGLQPRGHODQGHVWLPDWHGIURP *+*LQYHQWRU\ _] !!]!"^ # Z Z { '. . : 79 # 9: =. ' 7; : ;; 9 : ; \$\ [Z[ ~}[ [[ Z[ 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW BASELINE SCENARIO RESULTS SUMMARISED Speciﬁc emissions The total speciﬁc ﬁnal energy consumption increases from 0.61 toe/ capita in 2005 to 0.97 toe/capita in 2040 while CO2e emissions grow from 0.57 t/capita to 1.1 t/capita. If the non-energy related emissions are considered then the CO2e emissions increase from 2.9 t/capita in 2005 to 5.1 t/capita in 2040. Energy mix Fuel wood is the main source of energy in 2005 constituting about 60% of the total ﬁnal energy consumption (see Table 23). In 2040 the fuel wood share is reduced to 22% and electricity takes the lead with 44%. A large share of the fuel wood consumption in 2005 is assumed to be gradually replaced by briquettes and briquettes grow to represent 5% of the total ﬁnal energy consumption. Other purposes of fuel wood consumption are assumed to be completely phased out, namely fodder cooking. 7DEOH)LQDOHQHUJ\FRQVXPSWLRQ WRH DQGE\HQHUJ\W\SH WDEOH ] ! ] " # "# ! ! Z [ Z [ 4 *. 0 1 ¦ ¦ 4 ;; ¦ ¦ 4. 0 1 7; ;: ¦ ;¦ :9# 7:# :¦ :¦ + ''% ;: 77 ¦ [[ . 0 1 #: ;7 } ¦ 3 < #: ¦ ¦ 3 ¦ ¦ > 9;: : ¦ ¦ 9: 9# ¦ ¦ $ 3 ;; #9; ¦ ;¦ 5 & ¦ ¦ 2 . *. 7# 7## ¦ ¦ , ¦ ¦ \$\ |ZZ {||Z In total, fossil fuel based energy consumption constitutes 27% in 2005 and it only increases slightly in share by 2040 as depicted in the pie charts in Figure 36. However, measured in absolute terms fossil fuel consumption increases from 106 ktoe to 266 ktoe. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW )LJXUH)LQDOHQHUJ\FRQVXPSWLRQ WRH DQGE\HQHUJ\W\SH WZRSLHFKDUWV Final energy consumpon 2005 (toe) Final energy consumpon 2040 (toe) Other RE Electricity Other RE 0% 13% 5% Fuel Electricity wood (s) 44% 22% Fossil Fuel energy wood (s) 27% 60% Fossil energy 29% Energy service demand Looking at the development in the energy service demand, different sectors behave quite differently from one another (Figure 37). Industries and road transport reach a plateau after 2020. The migration from rural to urban areas results in a break in the rural curve. The aviation and primary sector show a gradual reduction which is due to the assumed efﬁciency gains being the main driver for the development. The energy efﬁciency gain is assumed 19% for all sectors except road transport where it is 15%. Please note, that the graph below is “distorted” – the lapse of time is not same for each of the ﬁve measuring points and the development from 2005 to 2010 to 2020 therefore appears more abrupt than really is the case. Energy service demand (toe) 140000 120000 100000 80000 60000 40000 20000 0 Sum af ES Sum af ES Sum af ES Sum af ES Sum af ES 2005 2010 2020 2030 2040 All primary sector 5933 5283 4350 3234 2164 All ter/ary subsectors 24103 34156 66857 91463 125134 Avia/on 287 378 822 822 822 Energy intensive industries 29372 32209 118940 118940 118940 Other industries 22420 31802 62331 85304 116744 Road transport 12321 16243 28209 28209 28209 Rural 35152 45850 63775 56455 65522 Urban 7940 13965 42794 76034 112436 )LJXUH6XPPDU\RIEDVHOLQHVFHQDULR±SURMHFWHGHQHUJ\VHUYLFHGHPDQG WRH 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Final energy consumption The most marked difference between energy demand development and ﬁnal energy consumption occurs for the primary sector i.e. agriculture – energy demand decreases to 36% of 2005 demand while consumption decreases to only 15%. This is caused by a signiﬁcant fuel shift from fuel wood to biogas, electricity and gas/diesel oil (Please see Figure 38). All other sectors grow in terms of ﬁnal energy consumption. Due to migration, rural consumption only increase to double the 2005 level while urban consumption increases by a factor 14. Tertiary sector and other industries increase by a factor 5. Due to the restrictions placed on energy-intensive industries and road transport, in 2020 their increase is lower, namely by a factor 4 and 2, respectively. Final energy consumpon (toe) 1000000 900000 800000 700000 600000 500000 400000 300000 200000 100000 0 Sum of FEC Sum of FEC Sum of FEC Sum of FEC Sum of FEC 2005 2010 2020 2030 2040 Urban 14680 26739 72067 111445 141530 Rural 122374 153243 182168 135294 128455 Road transport 55094 71154 117409 112864 108658 Other industries 46167 76467 140343 179725 229951 Energy intensive industries 54373 68107 218833 187906 158587 Avia/on 957 1244 2626 2556 2490 All ter/ary subsectors 40508 63185 109102 130539 154323 All primary sector 54397 46349 33609 20622 8393 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Final energy consumpon (toe) 250000 200000 150000 100000 50000 0 Sum of FEC 2005 Sum of FEC 2010 Sum of FEC 2020 Sum of FEC 2030 Sum of FEC 2040 All primary sector All ter/ary subsectors Avia/on Energy intensive industries Other industries Road transport Rural Urban )LJXUH6XPPDU\RIEDVHOLQHVFHQDULR±SURMHFWHG¿QDOHQHUJ\FRQVXPSWLRQ WRH Energy related emission The ﬁnal energy consumption increases signiﬁcantly from 2010 to 2020 (see Figure 39) but only very slightly from 2020 through 2030 to 2040. Meanwhile the energy related CO2e emission increases signiﬁcantly from 2010 to 2020 but starts falling from 2030 to 2040. All sectors - Final energy consumpon (ktoe) Energy related emission (kt CO2e) 912 913 891 1.000 900 800 700 600 472 500 360 400 300 200 100 - 2005 2010 2020 2030 2040 2005 2010 2020 2030 2040 Electricity Other RE Fossil energy )LJXUH 'HYHORSPHQW LQ ¿QDO HQHUJ\ FRQVXPSWLRQ NWRH DQG HQHUJ\ UHODWHG &2H HPLVVLRQV NW IRUDOOHQHUJ\UHODWHGDFWLYLW\ Total carbon emissions In conclusion, the investigated baseline scenario shows that non-energy related emissions continue to make up 80% of the total emissions throughout the modelled period. While livestock husbandry in 2005 constituted a relatively larger share of the total emission, industrial production processes have taken the lead in

2040 — Urban municipal waste and road transport emissions are likewise

2040. Urban municipal waste and road transport emissions are likewise main contributors in 2040. It should be noted that the analysis overview in Table 24 does not include emissions resulting from international aviation. The activity is however included in the model and increases from 3 kt in 2005 to 7 kt in 2020 and down to 6 kt in 2040. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Without the emissions from international aviation the total emissions arrive at 4,723 kt CO2e in 2040. Given a sequestration level of approximately 6,300 kt CO2e the margin of emissions is more than 1,500 kt CO2e in 2040. Figure 40 illustrates that the energy related carbon emission continues to constitute a modest share in 2040, namely 19% of the total carbon emissions. 7DEOH6XPPDU\RIEDVHOLQHVFHQDULR WDEOH ±SURMHFWHGFDUERQHPLVVLRQVIURPHQHUJ\ UHODWHG DQG QRQHQHUJ\ UHODWHG HPLVVLRQV NW &2H 1RWH ,QWHUQDWLRQDO DYLDWLRQ LV QRW LQFOXGHGLQWKHQXPEHUV Z | [ +% 051 ;: 7# 9; 97 ##; '( ') ((* *+) *,) - /: )* *,; *+: (:+ < = > > ( ( ( ? @ *// ((+ A/' A'* A;+ B = *+ A, ,' ': ': ? D = (+ ;( )* *:' )+ =D E ( A , + ** ) % 051 ; :7 9 7:# #: F D @= (;A ;', *G);/ *G);/ *G);/ =H ,'/ ,'/ ,'/ ,'/ ,'/ @ ,,: ':A /A; +** ):A I <=@D D J ); *A: (;' A,A ;(( \$\"^ $ # | [|{ [ZZ [~| . 79# 79;# #99: ##7; 97## ( 5' 9 ; ; 9 Total GHG emission (kt CO2e) 5.000 4.500 4.000 3.500 3.000 2.500 2.000 1.500 1.000 500 - 2005 2010 2020 2030 2040 Energy related Non-energy related )LJXUH 6XPPDU\ RI EDVHOLQH VFHQDULR JUDSK ± GHYHORSPHQW RI SURMHFWHG FDUERQ HPLVVLRQV IURP HQHUJ\ UHODWHG DQG QRQHQHUJ\ UHODWHG HPLVVLRQV NW &2H 1RWH ,QWHUQDWLRQDODYLDWLRQLVQRWLQFOXGHGLQWKHQXPEHUV 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Electricity and CO2e Developing the hydropower industry for both domestic consumption and for export to India would substantially reduce the regional CO2e emission compared to a scenario without such a development. The regional electricity system is not described in any detail in this report, but it should be noted that the CO2e emission factor of electricity produced in India from new coal plants will be app. 1 t CO2e/MWh electricity14. 14 CO2 Baseline Database for the Indian Power Sector, User Guide Version 5.0, Central Electricity Authority, Ministry of Power, Government of India, November 2009. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW $OWHUQDWLYH HQHUJ\ VFHQDULRV © lachenillepekinoiz.deviantart.com 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Alternatives to the baseline scenario were modelled in order to assess the potential impacts of changes in the underlying assumptions of the baseline scenario on carbon emissions. These alternative scenarios are presented in the following. Please note that these scenarios represent variations in the assumptions concerning the energy related emissions and not variations in the assumptions concerning non-energy related emissions. Unsustainable fuel wood and briquette production Fuel wood is considered carbon neutral assuming that it is produced sustainably. If Otherwise, the additional emissions would amount to 205,136 toe * 4.0879 t/toe = 839 kt CO2e in 2040.15 Briquettes grow in the baseline scenario from 65 toe in 2005 to 43,507 toe in 2040. If unsustainable briquettes are assumed to emit 4.1525 t CO2e/toe, then the consequence of using such briquettes would add an extra emission of 181 t CO2e in 2040 as shown in Table 25. 7DEOH3RWHQWLDOLPSDFWRIQRQVXVWDLQDEOHIXHOZRRGDQGEULTXHWWHVZLWKUHJDUGWR&2H HPLVVLRQV NW LQWKHEDVHOLQHVFHQDULR ] ! + *' 05< 1 #:9 ;; . 0 1 ;7 ;: + 051 #9 # INCREASED ENERGY EFFICIENCY A focused effort aiming to achieve high energy efﬁciency in the industrial, tertiary and residential sector is assumed to be able to increase the energy efﬁciency gain for the period 2005-2040, from 10% to 20% for industry and from 10% to 15% for the other two sectors. Within road transport it is assumed that extraordinary efforts could achieve 35% increase in energy efﬁciency rather than the 15% assumed in the baseline scenario. The impact on the ﬁnal energy consumption and the CO2e emissions are shown in the table below in Figure 41. The combined impact would be reduction in ﬁnal energy consumption of approximately 51 ktoe and a reduction in CO2e emissions of 89 kt in 2040 which constitutes 5% and 10%, respectively of the total national baseline. The largest efﬁciency gains in absolute terms are naturally found in road transport, energy intensive industry, and other industries. Together they reduce emissions with 82 kt CO2e of which 52 kt CO2e is within road transport. 15 Emission factor is from : Annex 9 Wood logs scope 3 http://archive.defra.gov.uk/environment/business/reporting/pdf/110707-guidelines-ghg- conversion-factors.pdf 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW EE scenario 1000000 900000 800000 700000 600000 500000 400000 300000 200000 100000 0 CO2e FEC 2040 FEC 2040 CO2e CO2e FEC 2005 2040 baseline EE 2005 2040 EE baseline Urban 14680 141530 135385 18493 63467 60708 Rural 122374 128455 122816 9043 34709 33127 Road transport 55094 108658 92561 176959 347946 296399 Other industries 46167 229951 210788 70214 207518 190225 )LJXUH)LQDOHQHUJ\FRQVXPSWLRQ WRH Energy intensive industries 54373 158587 145371 62364 158878 145638 DQGHQHUJ\UHODWHG&2HHPLVVLRQV W E\ Interna/onal avia/on 957 1992 1992 2905 6172 6172 VHFWRU LQ DQ HQHUJ\ HI¿FLHQF\ VFHQDULR Domes/c avia/on 957 498 498 0 1512 1512 FRPSDUHG WR EDVHOLQH (( HQHUJ\ Ter/ary 40508 154323 147614 18402 59911 57306 HI¿FLHQF\ Agriculture and forestry 54397 8393 8393 1604 11303 11303 EE scenario 1000000 900000 800000 700000 600000 500000 400000 300000 200000 100000 0 FEC 2040 FEC 2040 CO2e 2040 CO2e 2040 FEC 2005 CO2e 2005 baseline EE baseline EE Solar hea/ng 0 311 311 0 0 0 Residual fuel oil 1638 6488 5947 5420 21467 19678 Other biomass 0 0 0 0 0 0 LPG 5054 48295 46195 13515 129149 123534 Kerosene 10973 9842 9380 33155 29738 28341 Jet kerosene 957 2447 2447 2905 7428 7428 Gasoline 11311 22140 18860 33325 65230 55566 Gas/Diesel oil 48711 113031 98190 159801 370810 322123 )LJXUH)LQDOHQHUJ\FRQVXPSWLRQ WRH Fuel wood (s) 231872 205136 192073 0 0 0 Electricity 50471 411663 386336 0 0 0 DQG HQHUJ\ UHODWHG &2H HPLVVLRQV W Coal 27498 64078 58738 111865 260675 238952 E\ IXHO LQ DQ HQHUJ\ HI¿FLHQF\ VFHQDULR Brique¨es (s) 65 43507 41615 0 0 0 FRPSDUHG WR EDVHOLQH (( HQHUJ\ Biogas 0 5405 5282 0 6663 6512 HI¿FLHQF\ Biofuel (diesel) 0 43 43 0 255 255 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Global value of energy One way to assess the international value of forced increases in energy efﬁciency efﬁciency is to consider any energy efﬁciency gains as a means to allow for larger export of hydropower to India (or other neighbouring countries) and thus displacing electricity generated from fossil fuels. If hydropower based electricity replaces electricity produced on modern coal ﬁred plants in India with a carbon emission of 1 ton/MWh (11.64 t CO2e /toe), then 25.3 ktoe electricity saving equals a displacement of 300 kt CO2e emission. This is in the same order of magnitude as the 2040 energy related baseline emissions from the industrial segments. HIGH SHARE OF RENEWABLE ENERGY A high degree of electriﬁcation exploiting large scale and small scale hydro power in combination with other renewable energy resources – in particular solar energy – can pave the way for replacement of fossil fuels. This in turn would help in reducing reliance on imported fuels and limiting CO2e emissions while allowing for the envisioned economic development of the country. In the renewable energy scenario the following assumptions have been made regarding the mix of fuels in 2040: Road transport: % Heavy duty – 5% electricity, 10% biodiesel, (85% diesel ); % Light duty – 50% electricity, 10% biodiesel, (30% diesel, 10% gasoline); % Motorised two wheelers – 50% electricity, (50% gasoline). Energy intensive industry – 90% electricity, 4% coal, 3% diesel, 3% residual fuel oil (assuming that a certain amount of coal and residual fuel oil cannot be replaced); Other industry – 80% electricity, 10% coal, 10% fuel wood (assuming that a certain amount of coal cannot be replaced). Rural households: % Cooking – 73% electricity, 10% solar, 10% wood, 5% briquettes, 2% biogas; % Hot water heating – 53% electricity, 30% solar, 10% wood, 5% briquettes, 2% biogas; % Space heating – 73% electricity, 12% solar, 10% wood, 5% briquettes. Urban households and tertiary sector: % Cooking – 100% electricity; % Hot water heating – 50% electricity, 50% solar; % Space heating – 80% electricity, 20% solar. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Aviation and primary sectors are assumed unchanged. No distinction is made as to which sustainable electricity production technology is applied for the grid based electricity supply.The main share will be hydro power whether large or micro now and in the future but with contribution from other renewable energy sources will thus diversifying the energy base and further enhancing energy security. The resulting impact is 16% reduction in ﬁnal energy consumption due to the better conversion efﬁciencies of the technologies involved and 42% reduction in CO2e emissions. In absolute terms the ﬁnal energy consumption is reduced by about 153 ktoe and CO2e emission by 372 kt in 2040 relative to the baseline. The energy service demand covered by solar energy is 42,402 toe (see Figure 44) – a demand that would otherwise have to be covered by electricity or other energy types. The intensiﬁed electriﬁcation of other industries alone brings about a 121 kt reduction of CO2e. Urban households and tertiary sector become carbon neutral. As was the case for the energy efﬁciency scenario, diversiﬁcation of the renewable energy base may be assumed to make room for larger export of hydropower. Solar energy could thus be interpreted as displacing 42,402 toe * 11.63 MWh/toe * 1.0 t CO2e/MWh = 493 kt CO2e of Indian emissions. RE scenario 1000000 900000 800000 700000 600000 500000 400000 300000 200000 100000 0 CO2e FEC 2040 FEC 2040 CO2e CO2e FEC 2005 2040 baseline RE 2005 2040 RE baseline Urban 14680 141530 116899 18493 63467 0 Rural 122374 128455 92118 9043 34709 2266 Road transport 55094 108658 102314 176959 347946 333706 Other industries 46167 229951 176885 70214 207518 86350 Energy intensive industries 54373 158587 151378 62364 158878 77940 Interna/onal avia/on 957 1992 1992 2905 6172 6172 Domes/c avia/on 957 498 498 0 1512 1512 Ter/ary 40508 154323 128834 18402 59911 0 Agriculture and forestry 54397 8393 8393 1604 11303 11303 )LJXUH )LQDO HQHUJ\ FRQVXPSWLRQ WRH DQG HQHUJ\ UHODWHG &2H HPLVVLRQV NW E\ VHFWRULQDUHQHZDEOHHQHUJ\VFHQDULRFRPSDUHGWREDVHOLQH5( UHQHZDEOHHQHUJ\ 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW RE scenario 1000000 900000 800000 700000 600000 500000 400000 300000 200000 100000 0 FEC 2040 FEC 2040 CO2e 2040 CO2e 2040 FEC 2005 CO2e 2005 baseline RE baseline RE Solar hea/ng 0 311 42402 0 0 0 Residual fuel oil 1638 6488 6488 5420 21467 21467 Other biomass 0 0 0 0 0 0 LPG 5054 48295 0 13515 129149 0 Kerosene 10973 9842 0 33155 29738 0 Jet kerosene 957 2447 2447 2905 7428 7428 Gasoline 11311 22140 16834 33325 65230 49598 Gas/Diesel oil 48711 113031 87631 159801 370810 287480 Fuel wood (s) 231872 205136 66422 0 0 0 Electricity 50471 411663 505738 0 0 0 Coal 27498 64078 29876 111865 260675 121540 Brique¨es (s) 65 43507 11582 0 0 0 Biogas 0 5405 5772 0 6663 7116 Biofuel (diesel) 0 43 4119 0 255 24620 )LJXUH)LQDOHQHUJ\FRQVXPSWLRQ WRH DQGHQHUJ\UHODWHG&2HHPLVVLRQV NW E\IXHOLQ DUHQHZDEOHHQHUJ\VFHQDULRFRPSDUHGWREDVHOLQH5( UHQHZDEOHHQHUJ\ ENERGY EFFICIENCY AND RENEWABLE ENERGY Combining the assumption of the energy efﬁciency scenario and the renewable energy scenario the result is as follows (see Figure 45): The ﬁnal energy consumption is reduced by 22% reaching about 724 ktoe in 2040 and the CO2e emissions is reduced by 49% reaching 456 kt in 2040. The absolute difference between baseline and the combined energy efﬁciency and renewable energy scenario is 208 ktoe and 435 kt CO2e emissions. The largest emitter is the category “Other industries” with 128 kt CO2e. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW EE and RE scenario 1000000 900000 800000 700000 600000 500000 400000 300000 200000 100000 0 CO2e CO2e FEC 2040 FEC 2040 CO2e FEC 2005 2040 2040 baseline EEandRE 2005 baseline EEandRE Urban 14680 141530 112593 18493 63467 0 Rural 122374 128455 88494 9043 34709 2168 )LJXUH)LQDOHQHUJ\FRQVXPSWLRQ WRH Road transport 55094 108658 87156 176959 347946 284268 DQG HQHUJ\ UHODWHG &2H HPLVVLRQV NW Other industries 46167 229951 162145 70214 207518 79154 E\ VHFWRU LQ D FRPELQHG HQHUJ\ HI¿FLHQF\ Energy intensive industries 54373 158587 138763 62364 158878 71445 DQGUHQHZDEOHHQHUJ\VFHQDULRFRPSDUHG Interna/onal avia/on 957 1992 1992 2905 6172 6172 Domes/c avia/on 957 498 498 0 1512 1512 WR EDVHOLQH (( HQHUJ\ HI¿FLHQF\ 5( Ter/ary 40508 154323 128834 18402 59911 0 UHQHZDEOHHQHUJ\ Agriculture and forestry 54397 8393 8393 1604 11303 11303 EE and RE scenario 1000000 900000 800000 700000 600000 500000 400000 300000 200000 100000 0 FEC 2040 FEC 2040 CO2e 2040 CO2e 2040 FEC 2005 CO2e 2005 baseline EEandRE baseline EEandRE Solar hea/ng 0 311 42402 0 0 0 Residual fuel oil 1638 6488 5947 5420 21467 19678 Other biomass 0 0 0 0 0 0 LPG 5054 48295 0 13515 129149 0 Kerosene 10973 9842 0 33155 29738 0 Jet kerosene 957 2447 2447 2905 7428 7428 Gasoline 11311 22140 14340 33325 65230 42250 )LJXUH)LQDOHQHUJ\FRQVXPSWLRQ WRH Gas/Diesel oil 48711 113031 75360 159801 370810 247226 DQG HQHUJ\ UHODWHG &2H HPLVVLRQV NW Fuel wood (s) 231872 205136 61928 0 0 0 E\ IXHO LQ D FRPELQHG HQHUJ\ HI¿FLHQF\ Electricity 50471 411663 473856 0 0 0 DQGUHQHZDEOHHQHUJ\VFHQDULRFRPSDUHG Coal 27498 64078 27387 111865 260675 111412 Brique¨es (s) 65 43507 11078 0 0 0 WR EDVHOLQH (( HQHUJ\ HI¿FLHQF\ 5( Biogas 0 5405 5692 0 6663 7018 UHQHZDEOHHQHUJ\ Biofuel (diesel) 0 43 3515 0 255 21010 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW OVERVIEW OF MODELLED ALTERNATIVE SCENARIOS A comparison of the modelled energy scenarios shows that the impact of energy efﬁciency efforts is a 25% reduction of the CO2e emissions (Figure 47). A deliberate shift from fossil fuels to renewable energy sources can reduce ﬁnal energy consumption by 16% and more than halve the CO2e emissions. Combining energy efﬁciency efforts with renewable energy efforts has limited additional impact relatively speaking compared to the baseline energy scenario – a 22% decrease is achieved in ﬁnal energy consumption and 57% reduction in emission.The absolute difference between the 2040 emission in the energy efﬁciency scenario and the renewable energy scenario is 63 kt CO2e. It should be noted that with the shift from fossil fuels to renewable energy there is an in-built energy efﬁciency gain as a result of the higher conversion efﬁciencies of the end-user technologies in question. Scenario comparison )LJXUH)LQDOHQHUJ\FRQVXPSWLRQ NWRH 1000 DQGHQHUJ\UHODWHG&2HHPLVVLRQV NW LQ 900 RIWKHIRXUPRGHOOHGHQHUJ\VFHQDULRV 800 FRPSDUHGWRWKHVWDUWLQJSRLQWLQ 700 Baseline 2005 600 Baseline 2040 500 400 EE scenario 2040 300 RE scenario 2040 200 RE and EE scenario 2040 100 0 Final energy consump/on Energy related emissions (ktoe) (kt CO2e) Baseline EE scenario 1.000 1.000 800 800 Figure 48 shows that in the 600 600 ‘RE scenario’ and the ‘RE and EE scenario’ the emission 400 400 development is gradually more 200 200 and more “de-coupled” from the - - 2005 2010 2020 2030 2040 2005 2010 2020 2030 2040 ﬁnal energy consumption. FEC (ktoe) Emission (kt CO2e) FEC (ktoe) Emission (kt CO2e) RE scenario RE and EE scenario 1.000 1.000 800 800 600 600 400 400 )LJXUH 'HYHORSPHQW LQ ¿QDO HQHUJ\ 200 200 FRQVXPSWLRQ NWRH DQG HQHUJ\ UHODWHG - - &2H HPLVVLRQV NW RI WKH IRXU PRGHOOHG 2005 2010 2020 2030 2040 2005 2010 2020 2030 2040 HQHUJ\VFHQDULRV FEC (ktoe) Emission (kt CO2e) FEC (ktoe) Emission (kt CO2e) 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW From 2005 to 2040 fodder cooking is phased out and thus the ﬁnal energy consumption of the primary sector falls drastically in the baseline (see Table 26). Some of the largest savings are achieved in the residential sector, tertiary sector and other industries – the key driver being a shift towards electricity. A strategy to provide access to sustainable electricity supply is thus consistent with a low carbon strategy. Final energy consumpon (toe) 1000000 900000 800000 700000 600000 500000 400000 300000 200000 100000 0 2040 2005 2040 baseline 2040 EE 2040 RE EEandRE Urban 14680 141530 135385 116899 112593 Rural 122374 128455 122816 92118 88494 Road transport 55094 108658 92561 102314 87156 Other industries 46167 229951 210788 176885 162145 Energy intensive industries 54373 158587 145371 151378 138763 Interna/onal avia/on 957 1992 1992 1992 1992 Domes/c avia/on 957 498 498 498 498 Ter/ary 40508 154323 147614 128834 123918 Agriculture and forestry 54397 8393 8393 8393 8393 )LJXUH )LQDO HQHUJ\ FRQVXPSWLRQ WRH RI WKH IRXU PRGHOOHG HQHUJ\ VFHQDULRV ± E\ VHFWRU 7DEOH)LQDOHQHUJ\FRQVXPSWLRQ WRH RIWKHIRXUPRGHOOHGHQHUJ\VFHQDULRV±E\VHFWRU ±EDVHOLQH LQGH[7KHOLJKWUHGFRORXULQGLFDWHVWKDWQRFKDQJHZDVPDGHLQ WKHDVVXPSWLRQVIRUWKHVHVHFWRUV Final energy consumpon (toe) 2005 2040 baseline 2040 EE 2040 RE 2040 EEandRE Agriculture and forestry 648% 100% 100% 100% 100% Ter/ary 26% 100% 96% 83% 80% Domes/c avia/on 192% 100% 100% 100% 100% Interna/onal avia/on 48% 100% 100% 100% 100% Energy intensive industries 34% 100% 92% 95% 88% Other industries 20% 100% 92% 77% 71% Road transport 51% 100% 85% 94% 80% Rural 95% 100% 96% 72% 69% Urban 10% 100% 96% 83% 80% TOTAL 42% 100% 93% 84% 78% 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Looking at the mix of fuels consumed, LPG and kerosene are completely phased out in the renewable energy scenario16. Electricity, fuel wood and gas/diesel oil remain dominant in all scenarios. Final energy consumpon (toe) 1000000 900000 800000 700000 600000 500000 400000 300000 200000 100000 0 2040 2040 2005 2040 EE 2040 RE baseline EEandRE Solar hea/ng 0 311 311 42402 42402 Residual fuel oil 1638 6488 5947 6488 5947 Other biomass 0 0 0 0 0 LPG 5054 48295 46195 0 0 Kerosene 10973 9842 9380 0 0 Jet kerosene 957 2447 2447 2447 2447 Gasoline 11311 22140 18860 16834 14340 Gas/Diesel oil 48711 113031 98190 87631 75360 Fuel wood (s) 231872 205136 192073 66422 61928 Electricity 50471 411663 386336 505738 473856 Coal 27498 64078 58738 29876 27387 Brique¨es (s) 65 43507 41615 11582 11078 Biogas 0 5405 5282 5772 5692 Biofuel (diesel) 0 43 43 4119 3515 )LJXUH)LQDOHQHUJ\FRQVXPSWLRQ WRH RIWKHIRXUPRGHOOHGHQHUJ\VFHQDULRV±E\IXHO 16 Currently LPG and kerosene are heavily subsidised by India. If a phase out were to be the target then the subsidies would have to be removed. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW As can be seen in Figure 50 above there are several substantial differences between the baseline development and a development with focus on energy efﬁciency and renewable energy. In all scenarios the electriﬁcation of the country is considered to be almost 100%. In the EE and RE scenarios the fuel switching towards electricity is radical. In addition to this, the focus on local small-scale energy production in the form of solar heating, biogas, ﬁrewood etc. is intensiﬁed in those scenarios. Electriﬁcation based on large renewable electricity production will increase the overall energy efﬁciency and reduce CO2e emission. As has been mentioned earlier the CO2e impact from saving electricity in a national perspective is quite small due to the fact that almost 100% of the electricity production is based on renewable energy (hydro power). However, in a regional context every saved kWh will have an impact in India since India imports hydropower based electricity from Bhutan. Increasing the efﬁciency of electricity consumption will in other words “make room” for more export to India which in turn supplants coal based electricity production in India. The marginal emission of Indian electricity production is 1.0 t CO2e/MWh17. So limiting the growth in electricity consumption in Bhutan can be claimed to increase export to India and thus to reduce the CO2e emission in India. The difference between the electricity consumption in the hypothetical RE scenario and the hypothetical combined EE and RE scenario is 32 ktoe (equivalent to 372 GWh). Such electricity savings would in the Indian system equal 372 kt CO2e emission savings. And the 25 ktoe electricity savings in the hypothetical EE scenario relative to the baseline scenario would spare the regional environment of 290 kt CO2e emissions. 17 CO2 Baseline Database for the Indian Power Sector, User Guide Version 5.0, Central Electricity Authority, Ministry of Power, Government of India, November 2009. The value (1.0 t CO2e/MWh) used in the calculation shown in the text above is the emis- sion value of the operating margin. The operating margin describes the average CO2 intensity of the existing stations in the grid which are most likely to reduce their output if another project supplies electricity to the grid (or reduces consumption of grid elec- tricity). 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW 7DEOH)LQDOHQHUJ\FRQVXPSWLRQ WRH RIWKHIRXUPRGHOOHGHQHUJ\VFHQDULRV±E\IXHO ±EDVHOLQH LQGH[ ] ! ]" # Z [! ] [ [f [ f 4 *. 0 1 ¦ ¦ ¦ 979¦ #¦ 4 ¦ ¦ 9#¦ :¦ ;¦ ¦ ¦ 97¦ :¦ ;¦ + ''% ¦ ¦ 9¦ :¦ ¦ . 0 1 ¦ ¦ 9¦ ¦ ;¦ 3 < ¦ ¦ 9¦ ¦ ¦ 3 ¦ ¦ #:¦ :#¦ 7:¦ > ;¦ ¦ #;¦ :7¦ 7;¦ 9¦ ¦ ¦ ¦ ¦ $3 ¦ ¦ 9;¦ ¦ ¦ 5 & ¦ ¦ 97¦ ¦ ¦ 2 . *. , ;¦ ¦ 9¦ ¦ 9¦ 4. 0 1 ¦ ¦ ¦ 7;¦ 7;¦ \$\ [ 9¦ [ ~ Emissions (t) 1000000 900000 800000 700000 600000 500000 400000 300000 200000 100000 0 2040 2040 2005 2040 EE 2040 RE baseline EEandRE Urban 18493 63467 60708 0 0 Rural 9043 34709 33127 2266 2168 Road transport 176959 347946 296399 333706 284268 Other industries 70214 207518 190225 86350 79154 Energy intensive industries 62364 158878 145638 77940 71445 Interna/onal avia/on 2905 6172 6172 6172 6172 Domes/c avia/on 0 1512 1512 1512 1512 Ter/ary 18402 59911 57306 0 0 Agriculture and forestry 1604 11303 11303 11303 11303 )LJXUH&2HHPLVVLRQV NW RIWKHIRXUPRGHOOHGHQHUJ\VFHQDULRV±E\VHFWRU 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW With regard to carbon emissions the baseline development leads to an increase in emissions by a factor 2.5 over the investigated period. Energy efﬁciency may limit the increase with 10% of 2040 baseline emissions. Renewable energy offers a 42% reduction and renewable energy combined with energy efﬁciency can achieve almost a 50% reduction. In the energy efﬁciency and renewable energy scenarios the 2040 emission is only 27% higher than the 2005 emission level. In the energy efﬁciency and renewable energy scenarios road transport makes up 62% of total emissions simply due to the fact that the possibility for a shift to renewable energy is difﬁcult. Emissions (t) 1000000 900000 800000 700000 600000 500000 400000 300000 200000 100000 0 2040 2040 2005 2040 EE 2040 RE baseline EEandRE Solar hea/ng 0 0 0 0 0 Residual fuel oil 5420 21467 19678 21467 19678 Other biomass 0 0 0 0 0 LPG 13515 129149 123534 0 0 Kerosene 33155 29738 28341 0 0 Jet kerosene 2905 7428 7428 7428 7428 Gasoline 33325 65230 55566 49598 42250 Gas/Diesel oil 159801 370810 322123 287480 247226 Fuel wood (s) 0 0 0 0 0 Electricity 0 0 0 0 0 Coal 111865 260675 238952 121540 111412 Brique¨es (s) 0 0 0 0 0 Biogas 0 6663 6512 7116 7018 Biofuel (diesel) 0 255 255 24620 21010 )LJXUH&2HHPLVVLRQV NW RIWKHIRXUPRGHOOHGHQHUJ\VFHQDULRV±E\IXHO 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW © Centre for Creative Design 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW $YDLODEOHÀQDQFLQJ PHFKDQLVPV 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Climate change is of global concern and international measures to mitigate and adapt to the climate change includes among others, ﬁnancing mechanisms. The Green Climate Fund was agreed in principle at COP15 in Copenhagen in 2009 and an agreement on the broader design was reached at COP17 in Durban in December 2011. The Green Climate Fund will start operating from 2013 with a fund of 100 billion USD that rich countries have promised to make available to poor countries by 2020 to help mitigate emissions and adapt to climate change. However, the ﬁnal document from COP17 does not clarify where the money will come from or how much cash, if any, is already there. At present there exists a number of ﬁnancing options under the international climate regime such as the project based Clean Development Mechanism (CDM), the sector approach like CDM’s Programme of Activities (PoAs) and broader approach like Nationally Appropriate Mitigation Actions (NAMAs). In addition there is the special programme for Reducing Emissions from Deforestation and Forest Degradation (REDD+). While CDM and PoA are part of the Kyoto Protocol the NAMA and REDD+ are mechanisms under the Climate Convention. CLEAN DEVELOPMENT MECHANISM The Clean Development Mechanism (CDM) is a ﬂexible mechanism under the Kyoto Protocol18.The CDM allows emission reduction projects in developing countries to earn Certiﬁed Emission Reductions (CERs) which can be sold and used by industrialised countries to meet part of their emission reduction target under the Kyoto Protocol. Although there have been several initiatives to register CDM projects in Bhutan so far only two projects has been registered. It seems to be a serious problem that the baseline for the energy sector in Bhutan is electricity generated from hydro power which has no CO2 emissions. Most of the electricity generated at the hydro power plants in Bhutan is exported to India and here replacing fossil fuels, but it has been very difﬁcult to have an Indian baseline approved for a CDM project in Bhutan. With few opportunities to have larger hydro power projects approved under the CDM scheme there should be opportunities for minor industrial or household based renewable energy and energy efﬁciency project. However, experience has shown that approval of methodologies requires a rather large effort and high transaction costs which cannot 18 Under the Kyoto Protocol, 37 industrialised countries – the so-called Annex I Parties – must meet their GHG emissions targets primarily through national measures. However, the Protocol offers them an additional means of meeting their targets by way of three market-based mechanisms: International Emissions Trading (IET), Joint Implementation (JI), and Clean Development Mechanism (CDM). CDM is deﬁned in Protocol’s Article 12. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW be made up for by the value of CERs. That is one of the reasons why the CDM is geographic and sector biased towards the larger developing countries and sectors with emissions of either very aggressive GHGs like landﬁll projects or large power plants in a coal baseline environment. CDM PROGRAMME OF ACTIVITIES The Programme of Activities (PoA) started in 2005. Worldwide there are almost 100 PoAs being developed with about half of it involving emission reductions at the household and community level. PoA requires less administrative effort to be registered which results in lower transaction costs and shorter time for implementation. The PoA can be seen as a stepping stone towards the sector approach. POST-2012 CARBON MARKET So far the carbon markets have been politically driven mainly under the framework of the Kyoto Protocol. The current commitment period of the Kyoto Protocol will end in 2012 and the post-2012 demand for CERs will depend on the outcome of negotiations to extend the commitment period and/or the development of existing carbon markets. There are many uncertainties related to the future demand for CERs. The biggest demand for carbon emission allowances and carbon credits on the global carbon market is from the European Emission Trading Scheme (EU ETS). The price of carbon credits, i.e. CERs, on the carbon market is closely linked to the prices of European carbon emission allowances (EUA) as long as CERs are in compliance with the unit for EU ETS participants. The EU ETS has already been extended with third phase from 2013 to 2020 but it is highly unclear which types of CERs will be accepted into the EU ETS. It is certain that CERs from least developed countries will be accepted into the post 2012 EU ETS. While investors so far have been focusing on projects in China and India, there has been an increasing interest in projects in South East Asia. This shift could reﬂect that CERs from the region are more likely to be accepted in the post 2012 phase of EU ETS. At the regional level there are emerging carbon markets in the United States and countries like Japan, Australia and New Zealand are developing carbon markets. NATIONALLY APPROPRIATE MITIGATION ACTIONS (NAMA) The rationale behind the Kyoto Protocol is that the developed countries are responsible for past emission. However, developing countries are increasing their contribution to the level of GHG and the main emitters today. Therefore developing countries will be integrated in a post- 2012 climate agreement with involvement at a lower level compared to developed countries. This is because they are in developing process where mitigation actions have to be integrated with general development 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW targets such as poverty eradication, health care and education. There are major differences between developing countries with respect to natural resources, population density, emitting sectors and demographic development. The Nationally Appropriate Mitigation Actions is an instrument that is foreseen to take these differences into consideration. NAMA is a new mechanism and the modalities and procedures for NAMAs are still evolving. NAMAs are often held at the level of aggregate targets and do not include much detail. NAMAs are part of the Bali Action Plan (BAP) but the BAP does not provide a speciﬁc deﬁnition of NAMAs. The provisions in the BAP can be broken down into the following elements19: % Developing countries are to undertake nationally tailored mitigation actions; % These actions shall be embedded in the broader national sustainable development strategy; % They are to be measurable, reportable and veriﬁable (MRV); % They are to be supported by developed countries. NAMAs can be in the form of projects, programmes or policies. Speciﬁc actions can consist of only one measure, a set of measures or implementation of a holistic action plan. On 5th February 2010, the Royal Government of Bhutan registered in the NAMA pipeline20a NAMA with a nationwide approach and carbon emission target to remain carbon neutral as emission reduction goal. REDD+ Although estimates showed that carbon emissions from deforestation and forest degradation accounted for 15-20% of global carbon emissions, an agreement to take actions against further deforestation and degradation was not reached until Bali Action Plan in 2007. At COP15 in 2009 a consensus was reached about collective commitment by developed countries for new and additional resources. It is predicted that ﬁnancial ﬂows for greenhouse gas emission reductions from REDD+ could reach up to 30 billion USD/year. This signiﬁcant North-South ﬂow of funds could reward a meaningful reduction of carbon emissions and could also support new, pro-poor development, help conserve biodiversity, and secure vital ecosystem services. 19 JIKO Policy Paper 01/2011, Wuppertal Institute, August 2011 20 UNEP Risoe NAMA pipeline 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW /RZFDUERQ VWUDWHJ\DQG DFWLRQSODQ © Karma C. Neydrup, NEC 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Long-term strategy The task of the long-term national strategy for low carbon development is to strike the difﬁcult balance of economic growth and sufﬁcient energy at reasonable cost while preserving the local environment and contributing to climate protection. More speciﬁcally the strategy shall enable Bhutan to fulﬁl the commitment to remain carbon neutral. In addition, the strategy will align with the Green Economy theme in the UN Conference on Sustainable Development (RIO+20) taking place in June 2012. The concept of Green Economy focuses on the intersection between environment and economy. Policy instruments With regard to portfolio of policy instruments, the government has three policy instruments, namely informative, normative and economic instruments, as illustrated in Figure 53. The informative instruments aim to inform the target group or inﬂuence the target group. The target group has a large degree of freedom regarding whether or not to act in accordance with the information. The economic instruments i.e. market based instruments give the target group an economic incentive to act as the regulator wishes and can be in form of a reward (“carrot”) or a punishment (“stick”). The normative instruments oblige the target group to do the wanted and often include sanctions in case of lack of adherence. &$f\& $f\& $$& )LJXUH7\SHVRISROLF\LQVWUXPHQWV Typically, a mix of instruments is the best choice – either used at the same time or consecutively. The most effective mix of instruments will depend on the case in question. Is it important that the entire target group acts as wanted or is a section sufﬁcient? How much freedom of choice is politically necessary? To what extent do personal/business interests coincide with societal interests? Is it possible to verify compliance? How soon are results required? 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW In addition to these three instruments, the government and local authorities may also choose to use their position to facilitate dialogue and public-private partnerships to further the intended socio-economic development. ASSUMPTIONS There are several studies on potential mitigation measures for various sectors in Bhutan. All relevant information for scenario analysis is based on information available as of November 2011 and consultations with stakeholders. Empirical studies were not undertaken to verify or add information. Assessments of costs and beneﬁts from the selected interventions are mainly qualitative as quantiﬁcation will require speciﬁc and detailed studies. However, in order to be able to proceed with project proposals for the NAMA, detailed studies will be required to substantiate costs and beneﬁts. INTERVENTIONS IDENTIFIED IN EXISTING DOCUMENTS The review of existing documents concerning intervention possibilities for reducing carbon emissions in Bhutan revealed the interventions listed below. Available documents The encountered studies on carbon reduction potential and intervention opportunities relevant to Bhutan are: % Integrated Energy Management Master Plan for Bhutan. TERI/ DoE 2010 (IEMMP); % ADB Capacity building of NEC. May 2011 (ADB/NEC); % Energy Intensive Sectors of the Indian Economy. Path to low carbon development. ESMAP 2010 (ESMAP-I); % CO2 Reductions in Transport Sector in Thailand: Some Insights, 2008 (THAI); % Capacity development for scaling up decentralised energy access programmes. Lessons from Nepal. UNDP 2010 (NEPAL); % Analysis of Energy-Efﬁcient Opportunities for Cement Industry in Shandung Province, China. Lawrence Berkley National Laboratory. October 2009 (Cement-China); % Bhutan: Economic Analysis of Cleaner Technologies and Options in the Non-Energy Sector. ADB. December 2010 (Non-energy); % Pathway to a Low-Carbon Economy. Version 2. McKinsey & Company. 2009 (McKinsey); 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW % Second National Communication from Bhutan to UNFCCC, 2011. The study ‘Bhutan: Economic Analysis of Cleaner Technologies and Options in the Non-Energy Sector’ comprises calculations of carbon reduction potentials and marginal abatement costs for a number of interventions in the non-energy sectors of Bhutan. Other reports present rough estimates of reduction potentials and rough estimates of costs. Table 28 shows a schematic overview of identiﬁed interventions and related reduction potential and costs. 7DEOH$YDLODEOHLQIRUPDWLRQDERXWUHGXFWLRQSRWHQWLDODQGDEDWHPHQWFRVWVLQ%KXWDQ Emission reduction Sector Opportunity Cost Source potential 2010- 2020/30 Energy 21-25% coal consumption General reduction (in 30 mill Nu. IEMMP in industry cement industry) 14% petrol and General No information IEMMP 10% diesel Tax/elimination 16.4% with CO2 of tax tax of100USD/t No information THAI exemption or Energy CO2e parking fees consumption in transport Fuel shift (bio 1% reduction ESMAP-I No information fuels) 0.8% THAI Technical 16% reduction No information ESMAP-I standards 3% reduction ESMAP-I Modal shift No information 2.2% THAI 1.75 tCO2e per Improved cook ICS per year Nepal 290 mill Nu. stoves Target: 40,000 IEMMP ICS Efﬁcient fodder Target: 1,000 150 mill Nu. IEMMP cooking Energy consumption LPG stoves Target: ? 30 mill Nu. IEMMP in residential 0.8 tCO2e per household per Solar PV 400 mill Nu. IEMMP year Target:? Energy efﬁcient Target: 5,000 by 1,000 mill Nu. IEMMP buildings 2020 Value of increased Limitation of Industrial electricity sales production of No information processes minus value of ferro- alloys lost ferro- alloys sales 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Clinkers substitution by 8% McKinsey Cement ﬂy ash industry 260 kt CO2e / 137 USD/ Non- CCS cement year tCO2e Energy Mineral No information No information There are alternative Metal reducing No information No information agents but no estimates 13.5 USD/ Non- Livestock 1.6 kt CO2e / year tCO2e Energy Agriculture 3.9 kt CO2e / 4.2 USD/ Non- Rice year tCO2e Energy 11.1 kt CO2e / Non- Recycling 1.2 USD/tCO2e year Energy Waste 16.2 kt CO2e / 0.4 USD/ Non- Composting year tCO2e Energy SELECTION CRITERIA The criteria applied for selecting the interventions included in the low carbon strategy and the ﬁrst action plan presented in this report are as follows: % The sector represents a large carbon reduction potential and/ or rapidly increasing carbon emissions in the baseline that holds potential for mitigation; % Potential interventions with relatively low economic barriers, i.e. abatement costs, exist; % There are few non-economic barriers i.e. conﬂicts with other policies; % There are signiﬁcant sustainability beneﬁts such as employment, reduced trafﬁc congestion, or health improvements; % There is a ‘window of opportunity’ such as an energy efﬁciency element in the building code regulating the boom in construction of new buildings. The baseline projection shows that the key emitting sectors in 2040 are likely to be the following ﬁve in order of carbon emissions: % Industrial processes and the related energy consumption; % Crop production and the related energy consumption; % Livestock raising and the related energy consumption; % Urban municipal waste; and % Road transport related energy consumption. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW While livestock related emissions in the baseline remain relatively constant in the period 2005-2040, the emissions of the other four sectors grow signiﬁcantly. In addition to the abovementioned sectors the energy consumption of the residential sector represents a ‘window of opportunity’ and high sustainability beneﬁts for households replacing fuel wood with hydro power based electricity. The recommended low carbon strategy is focused on these six areas and the realisation of the opportunities for carbon reduction that also provides additional beneﬁts such as increased economic self-reliance, employment, improved health, etc. Finally, a critical component for all decision-making is sufﬁcient and reliable data and analysis of these data. At present the information necessary to make an informed decision on an appropriate carbon strategy is hampered by insufﬁcient detail and lack of up-to-date information. Amending this is an important step towards steering the development of the nation as well as monitoring progress and efﬁciency of implemented policies. In other words the selected intervention areas included in the low carbon strategy and action plan are as follows: % Energy intensive industries’ non-energy related emissions % Crop production % Livestock raising % Municipal solid waste % Road transport % Residential sector % Data improvement R Sequestration capacity R Carbon footprint. Each individual area is described in more detail in the following section. INTERVENTIONS IN THE LOW CARBON STRATEGY AND ACTION PLAN The descriptions of the interventions of the low carbon strategy and short-term action plan address where relevant the following topics: % Mitigation measures % Reduction potential % Abatement costs % Non-economic barriers % Sustainability beneﬁts 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW % Actions % Suggested responsible entities % Time schedule. Energy intensive industries Industries are a major source of carbon emissions. Various fossil fuels are used for heating and mechanical functions in the industries but the emissions from the reducing agents (coke and coal) are even more. Mitigation measures The major mitigation option relating to use of fossil fuels is a requirement for new industries to apply the best available technology with respect to fuel type and energy efﬁciency. Two major options to limit emissions from use of reducing agents in industrial processes in the three major industries are to: % Limit the number of licences to exploit and process natural resources. % As limitations in the number of licenses may not be in accordance with Bhutan’s industry policy to attract new industries. Clear and transparent requirements to use best available technology could be an efﬁcient way to reduce the use of coal and coke as reducing agents in the production process. Reduction potential The industrial sector is a major source of emissions in Bhutan with a steep increase expected from 2010 to 2020. It is difﬁcult to ﬁnd valid ﬁgures about the potential for efﬁciency improvements but reductions in the size of 10-15% should not be unrealistic for the cement industry based on ﬁgures from China21. Abatement cost The abatement costs of limiting the number of licenses will be the lost opportunities for export and employment. Industries employ a large number of both national and non-national workers and villagers may beneﬁt economically from industries through employment22.These costs will be considerable but has to balance against alternative use of electricity and raw materials. The abatement costs of placing strict carbon reduction requirements on the applied technology will be considerable as new technology requires major investments. Investments are often a barrier to introducing new efﬁcient technology although lifetime calculations can justify the investment. Increased requirements to technical standards will be seen by investors as a barrier compared to other countries that also have low electricity prices and lower standards of requirements. 21 Analysis of Energy-Efﬁcient Opportunities for Cement Industry in Shandung Province, China. Lawrence Berkely National Laboratory. October 2009. 22 Audit of Industries on environmental compliance. Royal Audit Authority, October 2009 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Non-economic barriers The development will depend on a political decision on what is an acceptable level of exploitation of the national resources. There are already instances whereby local population and local authorities have opposed/rejected mining activities. Main action Today Bhutan exports natural resources such as electricity and raw material for chemical and ferro-alloy industries. The export generates income to the country. However, the main value addition takes place later in the value chain outside Bhutan. A moderate exploitation of the resources would create an opportunity for Bhutan to build up the capacity that makes it possible to exploit a larger share of the value chain. A slower exploitation would also be gentler towards the environmental and social impacts. Sustainability beneﬁts Controlled development of energy intensive industries so as to gain optimal societal beneﬁts from this economic activity. Outcomes in addition to carbon reduction: % The carbon emission of the energy-intensive industries naturally depends on the number of future licenses issued. Restricting the number of licenses may not be consistent with the strategies to diversify the economic base and to increase exports. A controlled development should therefore aim to ensure employment opportunities, to develop local capacity to exploit a larger share of value chain, to consider the available mineral resource base of the industrial production in a long term perspective, to limit local environmental impacts from mining and processing, and to off-set the carbon emission through sequestration efforts. Suggested responsible entity in cooperation with NEC: % Ministry of Economic Affairs Time schedule: % Immediate term (1-2 years): Further investigations on how international standards can be applied to Bhutan to reduce emissions and increase sustainability beneﬁts. % Medium term (2-5 years): Combine licensing with various obligations that limits carbon emissions and increases beneﬁts; for example obligation to provide data for assessing the carbon footprint more accurately, to implement energy management, to employ and train local work force etc. Investigate the possibility for the government to demand that the licensed factories are of a certain technological standard with highly qualiﬁed operation (e.g. through reward schemes and education programs for attracting and maintaining skilled labour). 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Crop production The assessment made by UN23 identiﬁes three main sources of carbon emissions from crop production. The largest emitter is rice cultivation followed by ﬁeld burning of residues and use of synthetic fertilizers. Mitigation options The key mitigation option is regulation of ﬂood through multiple aeration of areas previously under a single aeration regime. Reduction potential Regulating ﬂood in rice production is expected to have a total abatement potential of around 90 kt CO2e from 2006 to 2030. Abatement costs There are no detailed cost estimates for rice production in Bhutan but the UN report estimates the marginal abatement costs to be around 4 USD/t CO2e. Non-economic barriers The major non-economic barrier is a strong tradition combined with lack of information about these options. Sustainability beneﬁts New rice farming system would increase the yield while reducing emissions. Actions The Royal University of Bhutan has already undertaken studies of new rice farming systems. The experience from this research is being tested and should be expanded during the next years in combination with awareness campaigns. Livestock raising Mitigation options Energy-related mitigation measures such as a phase-out of fodder cooking and a fuel switch to biogas are included in the baseline projection. According to the Second National Communication to UNFCCC the main non-energy related emissions from livestock are mainly methane (CH4) emissions from enteric fermentation and nitrous oxide (NOX) emissions from manure. The stock of dairy and non-dairy cattle has almost been constant in the period 1994-2009 and it is in the baseline projection assumed that the stock will remain constant during the period 2010-2040. Emissions of CH4 and NOX are calculated per head of livestock per year as an average for the years 1994-2009 and then converted to emissions of CO2e/head/year.The annual emissions are determined by the number of livestock and the emission factors for enteric fermentation and manure management. The result is a constant emission of 567 kt CO2e per year for the period 2010-2040. 23 Bhutan: Economic Analysis of Cleaner Technologies and Options in the Non-Energy Sec- tor, Asian Development Bank, December 2010. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Mitigation options Second National Communication to UNFCCC presents a number of options for mitigating carbon emissions from enteric fermentation and manure management. Two key mitigation options are: % Enteric fermentation: Reduce livestock population by improving yak and cattle breed. The Department of Livestock has already initiated a program to reduce the number of cattle head and improvement of breed. % Manure management: Keeping livestock in pens or stalls (encouraging and promotion of stall feeding). ADB24 assesses that providing urea-molasses multi-nutrient block supplementation and urea-treatment of straw prior to feeding it to local dairy cattle in Bhutan has a potential of major reductions in emissions from livestock. Abatement cost ADB estimates that cost of using urea-molasses multi-nutrient block supplementation and urea-treatment of straw prior to feeding to local dairy will be around 6-7 USD/t CO2e which is rather a low cost. There are no estimates of the potential reduction impact available for the two other mitigation options. Non-economic barriers The major non-economic barrier is a strong tradition combined with lack of information about the options. Sustainability beneﬁts Through manure management farmers can utilise manure from the livestock for biogas production that could be used for cooking and lighting. The Ministry of Agriculture is currently managing a programme for promoting manure management and use of biogas. Actions Both identiﬁed mitigation options, reducing the number while improving the breed and manure management, are option already under preparation and implementation by Ministry of Agriculture. The efforts should be further pursued so as to obtain the beneﬁts from improved household income and reduced emissions. Municipal solid waste Methane emissions from landﬁlls must be captured and utilised and/or the volume of waste must be reduced either by recycling or composting. Till date no studies have been undertaken to assess the potential of utilising methane in Bhutan but ADB25 has studied two options of reducing volumes of solid waste: Recycling and composting. 24 Bhutan: Economic Analysis of Cleaner Technologies and Options in the Non-Energy Sector, Asian Development Bank, December 2010. 25 Bhutan: Economic Analysis of Cleaner Technologies and Options in the Non-Energy Sector, Asian Development Bank, December 2010 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW ADB calculates the reduction potential from recycling at around 18% per year and around 25% from composting. The government has taken some initiatives by building composting plants. The ADB study calculates abatement costs for recycling at 1.18 USD/t CO2e and 0.42 USD/t CO2e for composting. These are rather low abatement costs. No non-economic barriers have been identiﬁed. There will always be a potential risk of pollution from a landﬁll so reduction of volumes at the landﬁll will provide environmental and health beneﬁts. Actions Limiting the production of municipal solid waste and exploiting the waste efﬁciently through composting and capture of emissions for energy. Awareness and information campaigns should aim to limit waste production but also to further collection of waste for exploitation. Outcomes in addition to carbon reduction: % Reduced need for land ﬁll space for depositing waste % Compost for agricultural production % Reduced waste in the surroundings. % Additional energy source Suggested responsible entities in cooperation with NEC: % Ministry of Works and Human Settlement % Local authorities of the urban areas. Time schedule: % Immediate term (1-2 years): Establish system of composting of market waste (as in Thimphu) and municipal waste collection in all urban areas. % Subsequent term (3-5 years): Feasibility study of biogas possibilities in the largest cities. Road transport The emissions from the road transport are also expected to increase from 2010 to 2040 with the increasing demand for transport services following the economic development. Mitigation measures The following mitigation measures have been suggested in the 2040 Transport Strategy by ADB: % Decreasing the number of vehicles as a result of increasing prices of cars (elimination of tax exemption for public servants) and increasing fuel prices (CO2 tax). 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW % Time limitation and fee for parking in urban areas. % Regulation of taxis (highly efﬁcient and electric cars). % Improved efﬁciency in the stock of vehicles. % Upgrading pedestrian and cycling facilities. % Increased share of electrical cars in the stock of vehicles. % Improved public transport (safe, affordable and responsive to demand). % Improved trafﬁc engineering and management techniques Some of the measures could be implemented and enforced within a short time perspective while implementation of others will require longer time. The 2040 Transport Strategy also recommends strengthening the organisational structure and role distribution among the institutions of the transport sector. Given the mountainous terrain, transport of goods through ropeways must be explored. Especially in ecologically sensitive areas, ropeways should be considered for transport of both goods and people. Reduction potential According to the 2040 Transport Strategy it can be expected that a further reduction in carbon emissions of around 15% should be feasible up to 2040. Abatement costs Interventions such as taxes/fees and technical standards have relatively low abatement costs while fuel shift and modal shift have higher abatement costs. Non-economic barriers Non-economic barriers are relatively high including potential conﬂicts with the “access to quality transport service by all” policy and a general reluctance against taxes. Sustainability beneﬁts The sustainability beneﬁts are relatively high including reduced congestion and need for parking space in urban areas, reduced number of injuries and improved air quality. Curbing the increase in driving short distances to the beneﬁt of walking and bicycling is an important component of a transport solution that will also bring about health and social beneﬁts. Ropeways would besides reducing the number of heavy duty trucks also reduce the threats to loss of habitat and species especially in the ecologically sensitive areas. Other environmental damage associated with road construction can also be avoided. Actions A well functioning transport sector is vital to social cohesion and economic development of any nation. Transport system in the country has been expanding and with increased income levels the number of 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW vehicles too is increasing. . A wide portfolio of interventions is required in order to steer development in a sustainable direction: Minimum efﬁciency standards on imported vehicles, regular vehicle inspection, taxation on purchase of vehicles and fuel consistent with sustainability strategies, facilities for charging of electric vehicles, intelligent transport logistics, parking restrictions, safe and easy opportunities for walking and bicycling, and well-functioning, convenient and comfortable public transport. A pilot trial of electric vehicles for example in urban areas may pave the way for a wider dissemination. Feasibility studies on introduction of ropeways must also be initiated. Modal shift interventions may be combined with promotion campaigns to encourage a change in habit and prestige. Sustainability aims should be aligned with the overall aim of providing “access to quality transport services for all”. The demand for transport services can also be restrained through careful holistic urban planning that places transport of people and goods in focus instead of vehicle access and incentivises people to drive less and at the same time provides attractive alternatives. Furthermore, it should be kept in mind that a signiﬁcant amount of transport in rural areas today is non-motorised. Good access for people and goods to public transport or other affordable transport solutions in rural areas should also be given high priority in order to ensure rural development. Outcomes in addition to carbon reduction: % Improved air quality and health % Limitation of congestion % Improved live-ability. Suggested responsible entity in cooperation with NEC: % Ministry of Information and Communication % Municipalities of major urban areas % Ministry of works and Human Settlement (for environmentally friendly road construction) Time schedule: % Immediate term (1-2 years): Parking fees, tax revision with elimination of tax exemption on import of cars, and/or parking fees could increase government revenue which could be earmarked for a modal shift. Improvement of public transport offer. Promotion of walking and bicycling for short journeys. Fully integrating transport issues in urban planning work. % Subsequent term (3-5 years): Pilot test of electric vehicles – both cars and busses. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Residential sector Mitigation measures Existing reports list the following mitigation measures: % Promotion of efﬁcient/improved cook stoves % Promotion of efﬁcient LPG stoves % Promotion of solar PV % Promotion of solar water heating systems % Targeting building energy efﬁciency. Regarding energy demand for the residential sector IEMMP focuses on reducing fuel wood share in the residential sector by introducing high efﬁcient cook stoves and switching to modern fuels like LPG, electricity, solar and biogas. These are highly efﬁcient measures to reduce the fuel wood share of residential energy consumption but the impact on net CO2e emissions will depend on the changes in forest and other woody biomass stocks as recorded in the national communications. There are, however, other reasons that justify limiting the use of these such as health concerns and increasing pressure on possibly limited biomass resources. In 2005, the total consumption of fuel wood in the residential sector was 490 kt. In the Business as Usual regime, the study assessed that fuel switch will result in a reduction of 200 kt in 2020 or a reduction by almost 40%. This reduction in fuel switch is mainly due to rural electriﬁcation programme and a switch towards LPG. Improved cooking stoves would result in additional reduction of 100 kt fuel wood by 2020 or a further reduction of 20% in an energy efﬁciency scenario. -QTVSZIHGSSOMRKWXSZIW A very good example of the beneﬁts derived from improved cooking stove is as follows. Centre for Rural Technology, Nepal (CRT/N) is implementing an improved cooking stove programme in Nepal funded by DANIDA and Government of Nepal. The programme started more than 10 years ago and has resulted in more than 100,000 improved cooking stoves introduced in Nepal. Recently CRT/N has participated in a registered carbon offsets programme. Under this programme CRT/N has worked with local partners to install 1,500 improved cooking stoves. The total project grant was about 18,100 USD and estimated carbon reductions are 1.75 t CO2e per year per improved cooking stove. 4VSQSXMSRSJ04+WXSZIW Use of LPG as cooking fuel is common in urban areas. The main barriers to dissemination into rural areas are poor infrastructure and high cost of transportation. A rural household with an LPG cooking stove uses around 50 kg LPG per year which corresponds to 0.16 t CO2e. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW 4VSQSXMSRSJWSPEV4: Solar PV will mainly replace kerosene as a source of lighting. Today about 3,000 households have solar PV systems. A rural household uses around 300 litres of kerosene per year for lighting which corresponds to 0.8 t CO2e per year. If this consumption replaced by electricity from hydropower/solar PV the carbon reductions are 0.8 t CO2e per household connection per year. 4VSQSXMSRSJWSPEV[EXIVLIEXIVW Solar water heating systems save electricity and fuel wood used for heating water and space heating. While solar water heating for hot water is quite widely used in many countries, solar water heated space heating is relatively low or non-existent in Bhutan. Data on existing systems can together with pilot tests of various models form the basis for greater application. The possibilities for further expansion of use and organising local production of the technologies would provide new business and employment opportunities. )RIVK]IJ½GMIRXFYMPHMRKW Bhutan has a design code of buildings to secure and maintain a cultural building tradition but codes are lacking in terms of energy efﬁciency. Non-energy beneﬁts All of the listed mitigation opportunities (see Table 29) have an added beneﬁt in the form of improved living conditions and health. Higher energy efﬁciencies and electriﬁcation saves time for fuel collection and transportation. Solar PVs can provide access to electric end-uses for households otherwise without reach of the electric grid and further an informed and politically active population. Building regulations already exist that address e.g. the cultural heritage aspects of building construction. It would be a logic step to include energy efﬁciency as well as safety aspects in the building regulations. However, to create the necessary legislation is the easiest element – upgrading the skills of the building entrepreneurs and the building workers as well as equipping the inspectors with the necessary know- how to verify whether or not building regulations are met is quite a different and signiﬁcant task. Increased costs of energy efﬁcient measures also act as barriers to adopting the necessary measures. The challenge is augmented by the fact that urban areas at present experience a building boom which gives certain urgency if the ‘window of opportunity’ is to be exploited at lowest possible cost to society. A building will remain in function for many decades. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW 7DEOH2YHUYLHZRIRSSRUWXQLWLHVDQGWKHLUDGGHGEHQH¿WVDQGQRQHFRQRPLFEDUULHUV Opportunity Added beneﬁt Non-economic barriers Health Improved stoves Less time consuming Health Outlets and transport PV Less time consuming Maintenance Access to electric end-uses Health Outlets and transport Solar water heaters Less time consuming No fuel expenses Lack of skills Building regulation Health Lack of materials addressing energy Less time consuming Enforcement (especially efﬁciency during building boom) Actions Promote fuel shift from fossil fuels to hydro-power based electricity and other renewable energy sources; limit future need for energy; and facilitate energy efﬁcient choices within the tertiary and residential sector. A fuel shift is greatly helped by access to electricity whether from the national grid or smaller systems. Solar heating will in combination with sustainable fuel wood, sustainable briquettes and biogas be main contributors to a diversiﬁed supply. Minimum standards, labelling, information campaigns and access to best-available-technologies contribute to minimising future energy need. Here an important area is building regulations and enforcement of these. National or local authorities may for example require that certain building types be equipped with solar heating for hot water and/or space heating and that the structure be designed so as to minimise the need for space cooling. Studies on energy characteristics of buildings adhering to traditional elements in building design whilst accommodating a modern life style are needed to ensure a high quality building stock. Such studies could be linked to research on how to secure the buildings against earth quakes. Another important aspect is training and upgrading of the qualiﬁcations of the construction sector as well as those enforcing the building regulations. The efforts of the tourist industry could be used as a front runner. Outcomes in addition to carbon reduction: % Reduced vulnerability to changes in fossil fuel prices. % Limit dependence on import of energy (through higher share of local energy resources). % Contribute to minimising rural-urban migration. Improved living standards and business opportunities through affordable access to clean energy. % Improved health (reduced smoke). % Skilled construction workers. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW % A modern Bhutanese building tradition. % Visibility of Brand Bhutan to both guests and local inhabitants. Suggested responsible entities in cooperation with NEC: % Ministry of Works and Human Settlement % Municipalities of major urban cities % Division of Renewable Energy and Division of Energy Efﬁciency and Conservation under the Department of Energy, Ministry of Economic Affairs. Time schedule: % Immediate term (1-2 years): Intervention in particular in the building sector is urgent in order to use the window of opportunity that the building boom provides. Testing of solar hot water heating and solar space heating technologies in order to adapt these to the Bhutanese needs and prepare local production, installation and maintenance capacity of these technologies. % Subsequent term (3-5 years): Enforce minimum energy efﬁciency standards on electric appliances and cooking stoves. Information campaign to sensitise the population and businesses to energy efﬁcient purchase and use. Data on sequestration capacity Detailed mapping of sequestration capacity and development including both agriculture and forestry aspects is an important tool in managing the resources sustainably while contributing to economic development within these sectors. Such mapping is closely linked to the development possibilities of the agricultural and forestry productions. Outcomes in addition to carbon reduction: % Improved validity of the “upper limit” for carbon emission if carbon neutrality is to be maintained. % Identiﬁcation of possibilities for sustainable fuel wood exploitation. % Identiﬁcation of the need and possibilities for developing carbon efﬁcient crop production. Systemised monitoring at regular intervals Suggested responsible entity in cooperation with NEC: % Ministry of Agriculture and Forests Time schedule: % Immediate term (1-2 years): Complete the already planned and partially initiated National forest Inventory to enable the assessment of current and future sequestration capacity and 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW measures to realise this. Establish monitoring system and organisation. % Subsequent term (3-5 years): Information campaign and targeted education program targeting the rural population and those employed in the agricultural and forestry sectors. Data on carbon footprint Carbon emission must remain below the sequestration capacity as committed by the RGoB at COP15.In order to assess whether this is the case it is necessary to expand and improve the data on the carbon footprint of the various economic sectors, in particular the industrial sector and the tertiary sector. Inspiration can be found within the tourism industry. Of special interest to Bhutan would be the carbon footprint from import-export activities which could be given increased focus. This is due to the fact that the regional carbon impact from the planned increase in electricity exports by far outbalances the carbon footprint from the planned increase in industrial output. The carbon mapping can be devised in steps starting with a certain segment of the economy and then gradually expanding to include more. This will allow development of a method that can provide the necessary information with a minimum of bureaucracy. Important for the general acceptance of the need to provide data to the authorities is to use the collated data to analyse aspects of relevance to the contributors. Outcomes in addition to carbon reduction: % Sound foundation for informed decision-making and policy design. % Possibility for branding of sectors as “green”. Suggested responsible entity in cooperation with NEC: % National Statistics Bureau Time schedule: % Immediate term (1-2 years): Devise mapping system and conduct pilot test of the system. Further analysis of the interventions of the short term action plan among other with the aim to determine costs and speciﬁc impact targets. % Subsequent term (3-5 years): Establish sample data collection routines and for selected sectors data reporting obligation. Recommended next steps An overview of the recommended interventions of the short-term action plan can be found in Table 30. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Descriptions of the individual interventions could be further developed in the NAMAs. For the approval of NAMAs it is important that baseline assumptions, rationales, data and calculations are explicitly stated, justiﬁed with reasons. 7DEOH5HFRPPHQGHGVKRUWDQGPHGLXPWHUPDFWLRQV Immediate term Medium term (1-2 years) (2-5 years) Energy intensive industry Combine licensing with obligations Further investigations on how international that limit carbon emissions and standards can be applied to Bhutan increases beneﬁts (energy efﬁciency to reduce emissions and increase standard, data for carbon footprint, sustainability beneﬁts. energy management, employment of local work force, training, etc.). Crop production The Royal University of Bhutan already has undertaken studies of new rice farming systems. The experience from this research is being tested and should be expanded during the next years in combination with awareness campaigns and training. Livestock raising Both identiﬁed mitigation options – improved breeding and manure management – are already under preparation and implementation by the Ministry of Agriculture. The efforts should be further pursued during the next years in combination with awareness campaigns and training. Municipal solid waste Establish system of composting of market Feasibility study of biogas possibilities waste (as in Thimphu) and municipal in the largest cities and if relevant pilot waste collection in all urban areas. test. Road transport Parking fees and tax revision with elimination of tax exemption on import of cars could increase government revenue which could be earmarked for a modal shift. Pilot testing of electric vehicles. Improvement of public transport offer. Promotion of walking and bicycling for short journeys. Fully integrating transport issues in urban planning work. Residential sector Energy efﬁciency requirements in the building regulation and enforcement of Enforce minimum energy efﬁciency the regulation. Provision of training of standards on electric appliances and construction workers and enforcers. cooking stoves. Test and adaptation of solar water heating Information campaign to sensitise the and solar space heating technologies population and businesses to energy to the Bhutanese needs and build local efﬁcient purchase and use. production, installation, and maintenance capacity of these technologies. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Data on sequestration Complete the already planned and partially initiated National Forest Inventory Information campaign and education to enable the assessment of current program targeting the rural population and future sequestration capacity and and those employed in the agricultural measures to realise this. Establish and forestry sectors. monitoring system and organisation. Data on carbon footprint Devise mapping system and conduct pilot test of carbon footprint data system. Establish sample data collection Further analysis of the interventions of the routines and test for selected sectors a short-term action plan among other with data reporting obligation. the aim to determine costs and speciﬁc impact targets. Much of the required initiatives to drive the development of the country down a low carbon path are already in place or being discussed and negotiated. Substantial work in terms of creating the necessary legislative and organisational framework has been carried out. The greatest challenge that remains is probably the implementation of agreed legislation and projects while upholding strict enforcement of legislation and coordination of initiatives. Access to reliable, detailed and up-to-date information is critical for monitoring progress and cost-efﬁciency of policies and for underpinning NAMAs. A coordinated development of the data collection systems is required to avoid unnecessary bureaucracy and ensure a uniform quality. Such a task is best handled by a national institution such as NSB. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Reference list (SGYQIRXW % Eleventh round table meeting – turning vision into reality: The development challenges confronting Bhutan, 1-2 September 2011, Gross National Happiness Commission, 2011. % Bhutan Urban Transport Study, International Finance Corporation, September 2011. % Bhutan Transport 2040: Integrated Strategic Vision, Asian Development Bank, August 2011. % Draft 2nd GHG emissions inventory and explanatory notes, NEC, July 2011. % Bhutan renewable energy policy 2011, draft, RGoB, 2011. % Bhutan: Energy sector, Asian Development Bank, August 2010. % National forest policy of Bhutan 2010, Ministry of Agriculture and Forests, March 2010. % Various data sets from the National Statistics Bureau of Bhutan, 2010. % Economic development policy of the Kingdom of Bhutan, 2010, RGoB, 2010. % Historical and forecast GDP ﬁgures 2001-2020, Ministry of Finance, originally produced by National Statistics Bureau of Bhutan, 2010. % The Waste Prevention and Management Act of Bhutan 2009 % Bhutan Millennium Development Goals – Needs assessment and costing report (2006-2015), Planning Commission, RGoB, and November 2007. % Population Projections Bhutan 2005-2030, National Statistics Bureau of Bhutan, July 2007. % Energy Data Directory 2005, prepared by TERI for the Department of Energy, Ministry of Economic Affairs, 2005. % Integrated Energy Management Master Plan, prepared by TERI for the Department of Energy, Ministry of Economic Affairs, 2005. % Vision 2020 – Bhutan 2020: A Vision for Peace, Prosperity and Happiness, Part I and II, Planning Commission, RGoB, May 1999. % CO2 Baseline Database for the Indian Power Sector, User Guide Version 5.0, Central Electricity Authority, Ministry of Power, Government of India, November 2009. ;IFWMXIW % The UNFCCC CDM Website, http://cdm.unfccc.int/ % UNFCCC (2010), The Kyoto Protocol Mechanisms. Available at, http://cdm.unfccc.int/about/cdm_ kpm.pdf % The CDM/JI Pipeline Analysis and Database, http://cdmpipeline.org/ % UNFCCC, Report of the Conference of the Parties, on its thirteenth Session, Bali, 3-15 December

2007 — Available at, http://unfccc.int/resource/docs/2007/cop13/eng/06a01.pdf#page=3

2007. Available at, http://unfccc.int/resource/docs/2007/cop13/eng/06a01.pdf#page=3 % The Conference of Parties. Copenhagen Accord. Available at, http://www.denmark.dk/NR/rdonlyres/ C41B62AB-4688-4ACE-BB7B-F6D2C8AAEC20/0/copenhagen_accord.pdf % Intergovernmental Panel on Climate Change, http://www.ipcc.ch/publications_and_data/ar4/wg1/en/ ch2s2-10-2.html % UN programme for Reducing Emissions from Deforestation and Forest Degradation (REDD) http:// un-redd.com/AboutREDD/tabid/582/Default.html 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Abbreviations BTN – Bhutanese currency (Ngultrum) Carbon – Green house gases counted in CO2 equivalents CCD – Climate Change Division CER – Certiﬁed emission reductions COP15 – UNFCCC 15th session of Conference of Parties CO2e – CO2 equivalents DHMS – Department of Hydro-Met Services, Ministry of Economic Affairs DoR – Department of Roads, Ministry of Works and Human Settlement (www.dor.gov.bt) DUDES – Department of Urban Development & Engineering Services, Ministry of Works and Human Settlement FYP – Five Year Plan GDP – Gross domestic product Gg – Giga gram = 1,000 tonnes GHG – Green house gases GNHC – Gross National Happiness Commission (www.gnhc.gov.bt) kt – 1,000 tonnes ktoe – 1,000 tonnes oil equivalents LULUCF – Land use, land use change and forestry sector MoAF – Ministry of Agriculture and Forests (www.moaf.gov.bt) MoEA – Ministry of Economic Affairs (www.moea.gov.bt) MoF – Ministry of Finance (www.mof.gov.bt) MoIC – Ministry of Information & Communication (www.moic.gov.bt) MoLHR – Ministry of Labour and Human Resources MoWHS – Ministry of Works and Human Settlement (www.mowhs.gov.bt) MSTCCC – Multisectoral-Technical Committee for Climate Change NEC – National Environment Commission (www.nec.gov.bt) NSB – National Statistics Bureau (www.nsb.gov.bt) Nu. – Bhutanese currency Ngultrum, also abbreviated to BTN REDD+ – Reduction Emissions from Deforestation and Forest Degradation RGoB – Royal Government of Bhutan (www.bhutan.gov.bt) RSTA – Road Safety and Transport Authority, Ministry of Information & Communication (www.rsta. gov.bt) toe – tonne(s) oil equivalents ToR – Terms of reference UNFCCC – United Nations Framework Convention on Climate Change 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW

Annex 1 – Stakeholder Consultation — Stakeholder Consultation

Annex 1 – Stakeholder Consultation Early consultation – and active involvement where relevant – in strategy development is critical to stakeholder acceptance of the vision outlined in the national strategy and for the realisation of the ensuing projects. In accordance with the ToR two rounds of stakeholder consultations was carried out during the project with the aim to % identify possible data sources, % identify key concerns and interests of the stakeholders, % solicit ideas for short-term actions, % conﬁrm relevance of the chosen scenarios, % discuss modelling results, and % discuss recommendations. *MVWXWXEOILSPHIVGSRWYPXEXMSR Monday 5th September 2011 Dasho Dr. Ugyen Tshewang, Secretary, National Environment Commission (NEC) Ms. Peldon Tshering, Chief, PPS, NEC Mr. Wangchuk Namgay, Senior Planning Ofﬁcer, Gross National Happiness Commission (GNHC) Mr. Tashi Dorji, Chief Livestock Ofﬁcer, Department of Livestock Mr. Kinley Tshering, Chief Forestry Ofﬁcer, Forest Resources Development Division (FRDD), Department of Forest & Park Services, MoAF Mr. Chencho Norbu, Director, Department of Agriculture, MoAF Mr. Henrik A. Nielsen, Head of Representation Ofﬁce, Thimphu, Representation Ofﬁce of Denmark Tuesday 6th September 2011 H.E. Khandu Wangchuk, Minister, Ministry of Economic Affairs (MoEA) Dasho Sonam Tshering, Secretary, Ministry of Economic Affairs (MoEA) Mr. Mewang Gyeltshen, Offtg. Drector, Department of Energy, MoEA Mr. Tandin Tshering, Director, Department of Industry, MoEA Mr. Loknath Chhetri, Industry Specialist, MoEA Mr. Wangchuk Loday, Planning Ofﬁcer, MoEA Dasho Kinley Dorji, Secretary, Ministry of Information & Communication (MoIC) Mr. Bhimlal Subedi, Chief Planning Ofﬁcer, Ministry of Information & Communication (MoIC) Mr. Karma Pemba, Chief Transport Ofﬁcer, Road Safety & Transport Authority (RSTA) Mr. Namgay Wangchuk, Chief Engineer, Road Safety & Transport Authority (RSTA) Mr. Phub Tshering, Secretary General, Bhutan Chamber of Commerce & Industry 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Wednesday 7th September 2011 Dasho Sonam Tenzin, Secretary, Ministry of Works & Human Settlement Mr. Ichharam Dulal, Department of Urban Development & Engineering Services Mr. Tandin, Department of Urban Development & Engineering Services Dasho Kinlay Dorjee, Thrompon (Mayor), Thimphu Municipality Visit to DSB shop (solar appliances) Mr. Lekzang, Chief Planning Ofﬁcer, Policy & Planning Division, Ministry of Finance. Multisectoral Technical Committee on Climate Change: % Mr. Sonam Dendup, Sr. Planning Ofﬁcer, MOIC % Mr. Jamyang Phuntshok, Head, Climate & Water Section, Watershed Management Division, Dept. of Forest and Park Services % Mr. Karma P Dorji, Executive Engineer, Dept. of Energy % Ms. Peldon Tshering, Head, Policy & Planning Services, NEC % Mr. Thinley Namgyel, Head, Environment Monitoring Division, NEC % Mr. Phuntsho Pelgay, Geologist, Department of Geology & Mines (DGM) (On behalf of Ms. Pem Deki, Geologist, DGM) % Mr. Phuntsho Namgyal, Hydro-met Services Division (HMSD), Dept. of Energy (On behalf of Mr. Karma Dupchu, Head, HMSD) % Mr.Tandin, Ministry of Works & Human Settlement (MOWHS) (On behalf of Ms. Daw Zam, Dy. Chief Environment Ofﬁcer, PPD, MOWHS) UNDP, Bhutan Mr. Karma L. Rapten, Head of Unit, Energy, Environment and Disaster Cluster Ms. Anne Erica Larsen, Programme Analyst, Energy, Environment and Disaster Cluster Mr. Yeshey Penjor, Climate Change Policy Specialist Thursday 8th September 2011 Mr. Kuenga Tshering, Director, National Statistics Bureau (NSB) Mr. Dago Tshering, Environment Education Ofﬁcer, Royal Society for Protection of Nature (RSPN) Ms. Rinchen Wangmo, Program Manager, Royal Society for Protection of Nature (RSPN) Ofﬁciating Managing Director (Head of Civil Division), Construction Development Corporation Ltd Mr. H.P. Phuyel, Sr. Manager, Construction Development Corporation Ltd Mr. Cheku Drukpa, General Secretary, Construction Association of Bhutan Mr. Karma Lotey, Managing director, Yangphel Adventure Travel, on behalf of the Hotel Association of Bhutan Mr. Sonam Dorji, General Secretary, Association of Bhutanese Tour Operators (ABTO) 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW Monday 12th September 2011 H.E. Dr. Pema Gyamtsho, Minister-In-Charge, NECS & Minister, Ministry of Agriculture & Forest Sonam Tashi, Senior Planning Ofﬁcer, Policy & Planning Division, Ministry of Economic Affairs 7IGSRHWXEOILSPHIVGSRWYPXEXMSR Thursday 3rd November 2011 Dasho Dr. Ugyen Tshewang, Secretary, NEC Mr. Tandin Tshering, Director, Dept of Industry (DoI) Mr. Chencho Norbu, Director, Dept of Agriculture (DoA) Mr. Yonten Phuntsho, Forestry Ofﬁcer, Dept of Forest & Park Services (DoFPS) Mr. Phuntsho Namgyal, Deputy Executive Engineer, HMSD, Dept of Energy (DoE) Mr. Dago Tshering, RO, RSPN Mr. HP Phuyel, Sr. Manager, Construction Development Corporation Limited (CDCL) Mr. Phuntsho Pelgay, Geologist, Dept of Geology & Mines (DGM) Ms. Dechen Yangden, Executive Engineer, Dept of Urban Development & Engineering Services (DUDES) Mr. G.K Chhopel, Chief, Water Resources Coordination Division, NEC Ms. Peldon Tshering, Chief, PPS, NEC Mr. Sonam Dorji, General Secretary, Association of Bhutanese Tour Operator Mr. Sonam Tenzin, National Statistical Bureau Mr. Karma L Rapten, ARR (P), UNDP, Bhutan Mr. Chhimi Rinzin, Chief Agriculture Ofﬁcer, DoA Mr. Wangchuk Namgay, Sr. Planning Ofﬁcer, GNHC Mr. Karma Tshering, Planning Ofﬁcer, NEC Mr. Tshering Tashi, Communication Ofﬁcer, NEC Ms. Tshewang Zangmo, Planning Ofﬁcer, NEC Ms. Jigme Zangmo, Technician, NEC Ms. Sonam Lhaden Khandu, Climate Change Unit, NEC Mr. Sonam Dagay, Climate Change Unit, NEC 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW

Annex 2 – Scenario model training — Scenario model training

Annex 2 – Scenario model training It has been important that the experiences gained through the strategic planning process of the task outlined in the ToR is retained within NEC and that selected stakeholders so that relevant staff possess the capacity to operate and modify the economic and emissions model applied for the strategic planning. The aim of the scenario model training carried out in relation to the scenario modelling for the long-term national strategy and short-term action plan has thus been to enable Bhutanese experts to use, maintain, and expand the model. The topics covered during the training as part of the capacity building were: % Input data and assumptions; % Operation and maintenance of the model; % Scenario analysis construction and interpretation of output. The training took place Wednesday 2nd November 2011 and the persons that received training in the model were: % Mr. Naitan Wang Chek, Deputy Chief, Livestock Ofﬁcer, Ministry of Agriculture % Mr. Birkha B. Chheti, General Secretary, Association of Bhutan Industries % Ms. Sonam Pem, Project Director, Tarayana Foundation % Ms. Roseleen Gurung, Project Ofﬁcer, Tarayana Foundation % Mr. Dawa Chhoedron, Deputy Executive Engineer, Renewable Energy Division, Department of Energy, Ministry of Economic Affairs % Mr. Chhimi Dorji, Deputy Executive Engineer, Hydro Meteorological Service Division, Department of Energy, Ministry of Economic Affairs % Ms. Jigme Zangmo, NEC % Mr. Tshering Tashi, CCD, NEC % Mr. Karma Tshering, NEC % Ms. Sonam Lhaden Khandu, CCD, NEC % Mr. Sonam Dagay, CCD, NEC. 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW

Annex 3 – List of reviewers — List of reviewers

Annex 3 – List of reviewers % Mr. Wangchuk Namgay, Sr. Planning ofﬁcer, GNHC % Mr. Thinley Namgyel. Head, EMD, NECS % Mr. Sonam Dendup, Sr. Planning ofﬁcer, PPD, MoIC % Mr. Kinzang, Chief, International organizations Division, MFA % Mr. Birkha B Chhetri, General Secretary, Association of Bhutanese industries, P/ling % Mr. Jamyang Phuntshok, Sr. Meteorology Ofﬁcer, WMD, DoFPS, MoAF % Mr. Karchen Dorji, Environmental unit, DoI, MoEA % Mr. Chhimi Rinzin, Chief Agriculture Ofﬁcer, DoA, MoAF % Mr. Peldon Tshering, Head, PPS, NECS % Ms. Daw Zam, Dy. Chief Environment Ofﬁcer, PPD, MoWHS % Mr. Karma P Dorji, Offtg. Head, PCD, Dept. of Hydropower & Power Systems, MoEA % Mr. Dago Tshering, Research Ofﬁcer, RSPN % Mr. Karma Toeb, Glaciologist, DGM, MoEA % Ms. Chime Paden Wangdi, General Secretary, Tarayana Foundation % Mr. Tshering Wangchuk, Asst. Program Ofﬁcer, DDM, MoHCA % Mr. Karma Dupchu, Department of Hydro-meteorological Services, MoEA % Dr. Tashi Dorji, Chief, Diary Development Division, DoL, MoAF % Mr. Kado Zangpo, Chief Planning Ofﬁcer, PPD, MoH % Mr. Tandin Tshering, Director, Dept of Industry (DoI) % Mr. Chencho Norbu, Director, Dept of Agriculture (DoA) % Mr. Yonten Phuntsho, Forestry Ofﬁcer, Dept of Forest & Park Services (DoFPS) % Mr. Chhimi Dorji, Deputy Executive Engineer, Hydro Meteorological Service Division, Department of Energy, Ministry of Economic Affairs % Mr. Phuntsho Namgyal, Deputy Executive Engineer, HMSD, Dept of Energy (DoE) % Mr. Dago Tshering, RO, RSPN % Mr. HP Phuyel, Sr. Manager, Construction Development Corporation Limited (CDCL) % Mr. Phuntsho Pelgay, Geologist, Dept of Geology & Mines (DGM) % Mr. Ichharam Dulal, Department of Urban Development & Engineering Services % Ms. Dechen Yangden, Executive Engineer, Dept of Urban Development & Engineering Services (DUDES) % Mr. G.K Chhopel, Chief, Water Resources Coordination Division, NEC % Mr. Sonam Dorji, General Secretary, Association of Bhutanese Tour Operator 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW % Mr. Sonam Tenzin, National Statistical Bureau % Mr. Karma L Rapten, ARR (P), UNDP, Bhutan % Mr. Yeshey Penjor, Climate Change Policy Specialist, UNDP % Ms. Sonam Lhaden Khandu, CCD, NEC % Mr. Sonam Dagay, CCD, NEC % Mr. Tshering Tashi, CCD, NEC 1DWLRQDO6WUDWHJ\DQG$FWLRQ3ODQIRU/RZ&DUERQ'HYHORSPHQW