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1 Energes 2013, 6, ; do: /en Artcle OPEN ACCESS energes ISSN Comparson and Analyss of Macro Energy Scenaros n Chna and a Decomposton-Based Approach to Quantfyng the Impacts of Economc and Socal Development Lngyng Pan, Zheng Guo, Pe Lu *, Lnwe Ma and Zheng L State Key Lab of Power Systems, Department of Thermal Engneerng, Tsnghua Unversty, Bejng , Chna; E-Mals: [email protected] (L.P.); [email protected] (Z.G.); [email protected] (L.M); [email protected] (Z.L.) * Author to whom correspondence should be addressed; E-Mal: [email protected]; Tel.: (ext. 333); Fax: Receved: 21 May 2013; n revsed form: 8 July 2013 / Accepted: 8 July 2013 / Publshed: 15 July 2013 Abstract: Chna has been experencng a rapd urbanzaton and ndustralzaton progress wth contnuous ncrease n prmary energy consumpton. Meanwhle, Chna s changng economc and socety structure also ntroduces huge uncertanty to ts future energy demand. Many energy research nsttutes perodcally publsh projectons of macro energy scenaros of Chna up to 2030 and 2050, but these projectons dffer from one another n terms of total amount of energy consumpton and energy flows amongst sectors. In ths work, we frstly llustrate major dfferences between exstng scenaros based on a lterature survey. We then compare and analyze the dfferent projecton methods, key polcy assumptons, and other boundary condtons adopted n obtanng these scenaros. Then an ndex decomposton method s ntroduced wth the purpose of decouplng the mpacts of economc growth and populaton growth on the projecton to energy consumpton and greenhouse gas emssons. Our results llustrate that projectons from domestc research nsttutes tend to be more optmstc regardng clean and sustanable utlzaton of coal n the future. Also, projectons on energy consumpton n Chna are exclusvely lnearly dependent on projectons of economc and populaton growth n most scenaros, whlst n some other scenaros the mpacts of ol prce, nternatonal trade, and other drvers are also rather sgnfcant. Keywords: macro energy scenaro; Chna; ndex decomposton

2 Energes 2013, Introducton Macro Energy Scenaros of Chna n Publshed Reports Chna has been experencng a rapd economc growth durng the last decade, and ts energy consumpton has also been ncreasng n a proportonal manner. Durng the perod between 2000 and 2010, Chna s prmary energy ncreased by 123%, from 1019 mllon tonne ol equvalent (Mtoe) to 2275 Mtoe, when ts coal consumpton ncreased by 119%, ol consumpton ncreased by 91%, and natural gas consumpton ncreased by 342%, as shown n Fgure 1 [1]. In 2009, Chna s prmary energy consumpton accounted for 18.7% of the global energy consumpton, and ts coal, ol, natural gas consumpton accounted for 46.3%, 9.6%, and 3.1% respectvely [2]. Ths rapd ncreasng trend s wdely projected to contnue n a foreseeable future as a result of an optmstc expectaton of Chna s economy. Ths ndcates that energy consumpton s not only of great mportance to Chna, but also to the whole world n the aspect of energy-related greenhouse gas (GHG) emsson control. Fgure 1. Chna s prmary energy consumpton n 2000 and The projectons to energy consumpton and energy-related GHG emssons of Chna have already drawn the attenton of many energy research nsttutes. Partcularly, the U.S. Department of Energy and the Internatonal Energy Agency publshes and updates projectons to the World s energy consumpton, ncludng Chna s, n a regular manner. The projectons to Chna s energy consumpton have been a major part of ther reports, for nstance, Internatonal Energy Outlook (IEO) and World Energy Outlook (WEO) [3,4], ever snce 1990s. In 2000, both nsttutes publshed projectons to the total amount of prmary energy consumpton of Chna by 2010, but the accuracy of these projectons s not satsfactory compared wth the actual hstorcal data. In all the projected scenaros, even the one wth the hghest expectaton of economc growth, the projected prmary energy consumpton s much lower than the actual consumpton n 2010, as shown n Fgure 2 [3 5]. Ths s largely due to the naccurate estmates of economc growth rate, populaton growth rate, and fuel prces. The naccurate projectons to Chna s energy consumpton also led to the naccuracy of projectons to the world energy consumpton to a large extent. For nstance, n WEO 2009 [6], the dfference between the

3 Energes 2013, projected energy consumpton of Chna n 2010 and the actual one s 849 Mtoe, whlst ths value for the whole world s merely 900 Mtoe. Therefore, obtanng a more accurate projecton to Chna s energy consumpton s also of great sgnfcance to the whole world. Fgure 2. Projecton and actual prmary energy consumpton of Chna n However, due to varous projecton methods, polcy assumptons and other key scenaros settngs, these macro energy projectons of Chna dffer, sometmes greatly, from one another n terms of total energy consumpton, energy consumpton by sector, and energy flows between sectors. The exstng reports on macro energy scenaros dscussed n ths work nclude: World Energy Outlook 2010 (WEO 2010) [7], publshed by Internatonal Energy Agency (IEA); Internatonal Energy Outlook 2010 (IEO 2010) [8], publshed by U.S. Energy Informaton Admnstraton (EIA); BP Energy Outlook 2030 (BEO 2030) [9], publshed by BP; The Md-term and Long-term Energy Development Strategy of Chna (2030, 2050) (MLEC) [10], publshed by the Chnese Academy of Engneerng (CAE). In WEO 2010, the world energy trend up to 2035 s projected n three scenaros. In IEO 2010 [8], the world energy trend up to 2035 s projected n fve scenaros. In BEO 2030 [9], only one scenaro s set based on the best of knowledge rather than busness as usual extrapolaton, projectng the world energy trend to In the MLEC [10], projecton to Chna s energy consumpton up to 2050 s provded based on ntervews of experts. These projectons dffer from one another n a large scale, and a comparson of energy demand projectons n these scenaros are llustrated n Fgures 3 and 4 [7 10]. Fgures 3 and 4 llustrate the prmary energy demand of Chna n 2020 and 2035 n the afore-mentoned scenaros. The Current Polces Scenaro, New Polces Scenaro and 450 Scenaro are provded by WEO 2010 [7], the Reference Case, Hgh Economc Growth Case, Low Economc Growth Case, Hgh Ol Prce Case and Low Ol Prce Case are provded by IEO 2010 [8]. BEO 2030 [9] represents BP s projectons and MLEC represents CAE s projectons. It shows that the dfferences

4 Energes 2013, between varous projectons for 2020 are rather large, and these dfferences become larger when projectng Chna s energy demand n Fgure 3. A comparson of projectons of prmary energy demand of Chna, Fgure 4. A comparson of projectons of prmary energy demand of Chna, The methodologes, polcy assumptons, techncal accuraces and scenaro settngs adopted n generatng the scenaros are dscussed below. By comparng these crtera, major dfferences between these scenaros are llustrated.

5 Energes 2013, Methodology Descrptons 2.1. World Energy Outlook 2010 IEA provdes medum to long-term energy projectons usng a World Energy Model (WEM). The model s desgned to project how energy markets functon, and t s the major tool used to generate detaled sector-by-sector and regon-by-regon projectons n all scenaros [11]. The model conssts of sx man modules: fnal energy demand (wth sub-models coverng resdental, servces, agrculture, ndustry, transport and non-energy use), power generaton and heat, refnery/petrochemcals and other transformaton, fossl-fuel supply, CO 2 emssons and nvestment. The model s desgned to address the followng ssues: (1) Global energy prospects: ncludng trends of demand, supply avalablty and constrants, nternatonal trade and energy balances by sector and by fuel type to 2035; (2) Envronmental mpacts of energy use: CO 2 emssons are derved from detaled projectons of energy consumpton; (3) Effects of polcy and technology mprovement on both the supply and demand sdes; (4) Investment n the energy sector: evaluatng nvestment requred for the entre energy supply, converson, and consumpton chan to meet the energy demand up to Internatonal Energy Outlook 2010 In IEO2010 [8], projectons to the world energy supply and demand are obtaned usng EIA s World Energy Projectons Plus (WEPS+) model. WEPS+ conssts of sector-based energy sub-models, and t adopts an ntegrated teratve soluton process to converge energy demand and energy prce to an equlbrum soluton [12]. The sub-models of WEPS+ share the same database and communcate wth each other n an teratve manner. In WEPS+, end-use demand sub-models (resdental, commercal, ndustral, and transportaton) are used to project major prmary energy consumpton, ncludng petroleum, natural gas, coal, nuclear power, hydropower, wnd, geothermal, and other renewable sources. Projecton to electrcty demand s also provded by the end-use demand sectors. Polcy assumptons n IEO2010 [8] are manly based on the exstng laws, polces, and regulatons as of the begnnng of The mpacts of pendng or proposed legslaton, regulatons, and standards are not consdered n the projectons [12] BP Energy Outlook 2030 The BP Energy Outlook [9] s not a busness as usual extrapolaton, or an attempt to model polcy targets. Instead t s bult to the best of knowledge [9], reflectng the judgment of the lkely path of global energy markets to Assumptons on changes n polcy, technology and the economy are based on nternal and external consultatons. In BP Energy Outlook [9], an alternatve case s bult up to assess the mpact of possble polcy changes on energy producton and consumpton. Scenaros n the BP Energy Outlook are used to explore uncertanty of projectons, but they do not attempt to forecast long-term energy markets.

6 Energes 2013, The Md-Term and Long-Term Energy Development Strategy of Chna (2030, 2050) Ths program [10] was conducted by CAE wth the purpose of delverng md-term to long-term forecast of Chna s prmary energy consumpton. It comprses of sx work streams, ncludng energy savngs, coal, gas, nuclear, electrcty, and renewable energy. Dfferent from other scenaro studes, the program sets a seres of amount control targets for prmary energy consumpton. To meet these targets, the program takes nto account of constrans of resources and envronment, apples a CGE (Computable General Equlbrum) model to the modelng system, and provdes a suggeston of possble development rate, ndustral structure, power-generaton mx and consumpton style of the sustanable energy development pathway for Chna. 3. Polcy Assumptons Polces play a sgnfcant role n scenaro analyss, and have great mpacts both on demand sde and supply sde of energy, as well as the energy market. The four nsttutons set some rather dfferent polcy scenaros n ther projecton reports. The polcy settng n WEO 2010 s manly about carbon mtgaton, whlst n IEO 2010, polces are based to the extent possble on the U.S. and foregn laws, regulatons, and standards n effect as of the begnnng of In BEO 2030 and MLEC, the polcy change assumptons are based on nternal and external consultatons. The detaled polcy assumptons are lsted n Table 1. To compare these polcy assumptons wth the actual polcy mplemented n Chna, we nvestgated the newly ssued Twelfth Fve-Year Plan for Energy, where energy development targets of Chna durng 2010 to 2015 are offcally announced, as shown n Table 2. To meet these targets, the energy-ntensve ndustres should reduce ther energy consumpton n a consecutve manner, and an average annual reducton rate for each ndustry s llustrated n Fgure 5. Fgure 5 ndcates that paper ndustry and castng producton have the hghest ambton to reduce ther energy consumpton, at about 4.4% annually. Copper metallurgy, flat glass producton, household glass producton and polycrystallne slcon producton are also targeted to make sgnfcant mprovement n energy effcency, wth ther annual energy consumpton reducton rate hgher than 2%. Although the absolute amount of energy consumed n steel and cement ndustry s rather large (see Fgure 6, steel and cement producton accounted for 11% and 6% of the total energy consumpton n 2009, respectvely), ther energy effcences are not expected to have great mprovement durng the 12th Fve Year. Accordng to the 12th Fve-Year Plans of constructon materals and steel ndustry, the cement producton wll ncrease from 1.88 bllon tonne n 2010 to 2.2 bllon tonne n 2015, and steel producton wll ncrease from 630 mllon tonne n 2010 to 750 mllon tonne n From 2011 to 2015, a small ncrease (around 0.5% annually) n energy effcency of the cement ndustry s expected. However, due to the foreseeable large ncrease (around 17% by 2015) n the total producton of the cement sector, the overall energy consumpton n the sector s expected to ncrease by 14% by Smlarly, the energy effcency of the steel ndustry s expected to ncrease 0.8% annually. However, due to the foreseeable large ncrease (around 19% by 2015) n the total producton of the steel sector, the overall energy consumpton n the sector s expected to ncrease by 14% by 2015.

7 Energes 2013, In concluson, a number of energy-ntensve ndustres plan to mprove ther energy effcences, partcularly the paper ndustry, castng ndustry and copper metallurgy ndustry. Meanwhle, the largest energy-consumng ndustres, typcally steel ndustry and cement ndustry, are not expected to have great mprovements n energy effcency. Report Scenaro Polcy Assumptons WEO 2010 (IEA) [7] IEO 2010 (EIA) [8] BP Energy Outlook 2030 (BP) [9] Current Polces Scenaro New Polces Scenaro 450 Scenaro To the best of knowledge The Md-term and Long-term Energy Development Strategy of Chna ( MLEC for short) (CAE) [10] Table 1. Scenaro polcy assumptons. Serve as a baselne aganst whch the mpact of new polces can be assessed. No change n polces s assumed: Takes nto account those measures that governments had formally adopted by the mddle of 2010 n response to and n pursut of energy and envronmental polces. Takes no account of any future changes n government polces. Does not nclude measures to meet any energy or clmate polcy targets or commtments that have not yet been adopted or fully mplemented. Overall targets and polces: 40% reducton n CO 2 ntensty by 2020 compared wth 2005 (2009). Rebalancng of the economy from ndustry towards servces (2009). Further mplementaton of the drectves of the Renewable Energy Law (2005). Detaled sector polces of power, transport, ndustry and buldng sectors. Overall targets and polces: 45% reducton n CO 2 ntensty by 2020 compared wth % share of non-fossl energy n prmary energy consumpton by Detaled sector polces of power, transport, ndustry and buldng sectors. Based to the extent possble on U.S. and foregn laws, regulatons, and standards n effect at the start of The potental mpacts of pendng or proposed legslaton, regulatons, and standards are not reflected n the projectons, nor are the mpacts of legslaton for whch the mplementng mechansms have not yet been announced. Mechansms whose mplementaton cannot be modeled gven current capabltes or whose mpacts on the energy sector are unclear are not ncluded. IEO2010 [8] focuses exclusvely on marketed energy. Non-marketed energy sources, whch contnue to play an mportant role n some developng countres, are not ncluded n the estmates. Assumptons on changes n polcy, technology and the economy are based on extensve nternal and external consultatons. Save energy and control the total energy consumpton. Utlze coal n a scentfc, clean and hgh-effcent way. Assure the strategc postons of ol and natural gas, consder natural gas as one of the key resources to adjust the energy structure. Accelerate the development of hydro power and other renewable energy. Take great efforts to develop nuclear power. Develop smart-grd systems.

8 Energes 2013, Table 2. Energy consumpton targets for energy-ntensve ndustres. No. Industry Unt Steel producton kgce/t Copper metallurgy kgce/t Alumnum metallurgy kwh/t 14,013 13,300 4 Cement producton kgce/t Flat glass producton kgce/loaded van Ethylene producton kgce/t Synthetc ammona producton kgce/t 1,402 1,350 8 Sodum hydroxde producton (Membrane process, 30%) kgce/t Sodum carbonate producton kgce/t Calcum carbde producton kgce/t 1,105 1, Paper ndustry kgce/t 1, Household glass producton kgce/t Fermented product kgce/t Domestc ceramc producton kgce/t 1,190 1, Dyeng cloth kgce/10 4 m 2,298 2, Yarn producton kgce/t Cloth producton Kgce/10 4 m 1,817 1, Vscose fber producton (flament) kgce/t 4,713 4, Castng producton kgce/t qualfed castngs Polycrystallne slcon producton (hgh-temperature hydrogenaton) kgce/t 39,000 33, Polycrystallne slcon producton (low-temperature hydrogenaton) kgce/t 36,000 30,000 Fgure 5. Annual energy consumpton reducton rates needed by energy-ntensve ndustres.

9 Energes 2013, Fgure 6. Industral energy consumpton of Chna, 2009 (Data source: [1]). 4. Techncal Accuracy The four reports on macro energy scenaros dscussed above have rather dfferent techncal accuracy on prmary energy demand and consumpton categores, as shown n Fgures 7 and 8. Fgure 7. Prmary energy categores. Fgure 8. Energy consumpton categores. Fgure 7 llustrates the prmary energy categores n the aforementoned four scenaros. Coal, gas and nuclear are explctly categorzed. The three oversea nsttutes analyze ol (or lquds) and natural

10 Energes 2013, gas separately, whlst CAE [10] combnes ol and gas to analyze ther demand. Hydropower s explctly analyzed all scenaros except IEO 2010 [8]. Fgure 8 llustrates the energy consumpton categores n the four aforementoned scenaros. Besdes transport and ndustry, WEO 2010 also consders energy consumpton for buldngs, IEO 2010 [8] and MLEC [10] consder resdental energy consumpton, IEO 2010 [8] consders commercal energy consumpton, and MLEC [10] consders energy consumptons of agrculture and servce ndustry. 5. Scenaro Settngs The four reports dscussed above have rather complcated assumptons and scenaro settngs for ther scenaro desgns, ncludng populaton, economc growth, ol and carbon prce, technology development, as well as polcy assumptons. A detaled descrpton of these settngs s presented n ths secton General Scenaro Settngs n Dfferent Scenaros The key scenaro settngs that nfluence the scenaro analyss are lsted n Table 3. As shown n Fgure 9, the WEO 2010 [7], IEO 2010 [8] and MLEC [10] have set specfc populaton growth rates of Chna for the scenaro analyss. In WEO 2010 [7], the Chnese populaton s assumed to grow at a constant annual rate of 0.6% from 2008 to 2020, and 0.1% from 2020 to The annual average growth rate from 2008 to 2035 s 0.3%. The rates of populaton growth assumed n all the three scenaros are based on the most recent projectons by the Unted Natons [13]. Populaton growth slows down gradually, n lne wth past trends. In IEO 2010, Chna s populaton s projected to be 1421 mllon n 2020, 1452 mllon n 2035, and the annual growth rate s 0.3% from 2007 to In MLEC, the annual populaton growth rate of Chna s 4.5 from 2010 to 2030, nearly 0 from 2030 to 2040, and 2.5 from 2040 to The annual average growth rate s 0.36% from 2010 to 2035, and 0.16% from 2010 to Fgure 10 llustrates the GDP growth rates of Chna n all scenaros. In MLEC, the GDP of Chna grows much faster than that n WEO 2010 [7] and IEO 2010 [8]. In WEO 2010[7], Chna s GDP s assumed to grow at an annual average rate of 7.9% from 2008 to 2020, and 3.9% from 2020 to The annual average growth rate s 5.7% from 2008 to In IEO 2010, the annual average growth rates from 2007 to 2035 range from 5.7 to 6.2 dependng on dfferent scenaros, as lsted n Table 3. In MLEC, the annual growth rate s assumed to be 8% from 2010 to 2030, and hgher than 4% from 2030 to 2050.

11 Energes 2013, Table 3. Key scenaro settngs n scenaros of projecton energy consumpton of Chna. Crtera Year IEO 2010 (EIA) [8] BP Energy WEO 2010 MLEC (CAE) Hgh Economc Low Economc Hgh Ol Prce Low Ol Prce Outlook 2030 (IEA) [7] Reference Case [10] Growth Scenaro Growth Scenaro Scenaro Scenaro (BP) [9] Predcton horzon ,421 1,415-1,394 Populaton ,442 1,429-1,458 (mllons) ,452 1,437-1, , : 0.45 Annual growth rate : : : 0 (%) : ,969 17,353 18,264 16,483 17,204 17,499-18,136 GDP (Bllon ,344 24,709 27,418 22,362 24,627 24,936-39,155 dollars) ,898 32,755 37,039 28,950 32,493 33,056-47, ,793 Annual growth rate : : : : : : : (%) : 4

12 Energes 2013, Fgure 9. Populaton growth settng n all scenaros of projected energy consumpton of Chna. Fgure 10. GDP growth settng n all scenaros of projected energy consumpton of Chna. The WEO 2010 [7] and IEO 2010 [8] focus on mpacts of ol prces on the energy market, and the ol prce assumed n IEO 2010 [8] s hgher than that n WEO 2010 [7] scenaros. The WEO 2010 [7] also set carbon prces n ts scenaros, actng as emsson constrants for fossl energy consumptons. The CO 2 prces by regon and scenaro are lsted n Table 4. Table 4. CO 2 prces by man regon and scenaro ($2009 per tonne) [7]. Scenaro Regon European Unon New Polces Scenaro Japan n.a Other OECD n.a Current Polces Scenaro European Unon Scenaro OECD+ n.a Other Major Economes n.a

13 Energes 2013, Specfc Scenaro Settngs of the Chnese Academy of Engneerng Compared wth scenaros n WEO 2010 [7] and IEO 2010 [8], there are specfc scenaro settngs n the report of the Chnese Academy of Engneerng (CAE). Typcally, CAE consders energy savng potentals n several hgh-energy-consumpton sectors, thus proposes promsng energy demand reducton n the future, as shown n Fgure 11 [10]. Fgure 11. Energy savng potentals proposed by CAE. In Fgure 11, the energy savng potentals n 2020 are consdered to be 700 Mtoe. Systematcally, the energy savng potental s greatly related to macro economy development, buldng lfetme and steel producton peak. From a macro economy development aspect, to control the energy ntensty (energy consumpton/gdp) below 6.27%, the energy demand would be less than 2.8 bllon toe n If the buldng lfetme s extended from 25 to 50 years, the annual energy savng would be 105 Mtoe. If the steel producton peak drops from 0.6 t per capta to 0.5 t per capta, the stable steel producton from 0.4 t per capta to 0.3 t per capta, the annual energy savng would be 126 Mtoe. Resdental energy savng potental could be huge va controllng the total floor area, encouragng energy-savng lfe style and mprovng energy effcency. Sgnfcant breakthrough of operaton and management technologes can also contrbute to energy savng benefts. For nstance, huge amount of energy can be saved n the lghtng sector by shftng to LED technologes and usng more natural lght. For the prmary and secondary energy sectors, there are also detaled and specfc development strateges n the CAE report. For the coal ndustry, mnng safety and hgh effcency are consdered to project the mnng capacty n the future. The projected coal producton s bllon tonne n 2030, and the mnng death rate wll be 0.01/mllon tonne n Coal accounts for approxmately 40% of prmary energy n 2050, and clean coal technologes wll be wdely appled. The report also presents a clean ndex to classfy clean coal technologes, ncludng hghly-effcent combuston and advanced power generaton technologes, crculatng fludzed bed technology, pollutants emsson control

14 Energes 2013, technologes, CCS (Carbon Capture and Storage), IGCC (Integrated Gasfcaton Combned Cycle), coal gasfcaton and lquefacton, polygeneraton, and combned heat, coolng and power generaton. Fgure 12 llustrates the projected coal demand n 2030 n dfferent scenaros. The sold and slash flled columns represent projected coal demand and other prmary energy demand n 2030 respectvely. Fgure 12. Coal demand projectons n dfferent scenaros, Due to the low estmaton of coal mnng capacty and promoton of clean coal technologes, the Chnese Academy of Engneerng projects a relatvely smaller total prmary energy demand n 2030, compared wth most of the scenaro results of WEO 2010 [7] and IEO 2010 [8]. Meanwhle, the projected percentage of coal demand to total energy demand by CAE s hgher than that n other scenaros, ndcatng that n CAE s consderaton, coal wll contnue to play a domnant role n Chna s energy supply and demand system for a long term. In comparson, for scenaros n WEO 2010 [7], the energy-related CO 2 emsson s the most mportant constrant of energy consumpton. In these scenaros, coal demand s strctly controlled n order to acheve the total CO 2 emsson reducton targets. In the report of CAE, the strateges of the power ndustry can be generally stated as power demand and supply projectons, power grd development plans and advanced technologes and devces. Based on unt demand of electrcal applances and urban/rural dfferences, domestc power demand s projected. At the same tme, regonal analyss s made by consderng economy development, populaton, ndustry scales and ndustral power demand of sx regons (Northeast, North, East, Mddle, South and Northwest Chna). Power supply projecton s based on power generaton mx optmzaton, power generaton capacty and operatng hours, regonal dstrbuton, steam coal avalablty, envronmental and water resource lmts of coal-fred power generaton, and transmsson capablty. For ol and natural gas, ol demand s projected to be wthn 650 ± 50 mllon tonnes n 2030 and 750 ± 50 mllon tonnes n Domestc crude ol producton s estmated to be stablzed between 180 and 200 mllon tonnes per year from present to It also sets a target to control the degree of dependence on ol mport below 65%. To meet ths target, another 120 ± 30 mllon tonnes of alternatve lqud fuel would be needed, manly for the transport sector and chemcal plants. Natural

15 Energes 2013, gas demand s estmated to be around 550 bllon m 3 n 2050, and domestc natural gas producton s estmated to be 300 bllon m 3 per year after In summary, for the Chnese Academy of Engneerng s projectons, energy savng potental s consdered, leadng to smaller amount of total energy demand compared wth other scenaros. By carefully estmatng the energy resource avalabltes, promotng clean and effcent technologes and ncentve polces, t projects a lower absolute amount of coal demand and a hgher share of coal n the total energy demand n For scenaros n WEO 2010 [7], the energy-related CO 2 emsson s the most mportant external constrant of energy consumpton. In these scenaros, the CO 2 -ntensve energy demands are strctly controlled n order to acheve the total CO 2 emsson reducton targets, and renewable energy demand has greater shares of total than that n other scenaros. 6. Index Decomposton Analyss Index decomposton methodology was frst used n the 1970s to study the mpact of changes n product mx on ndustral energy demand [14 16]. Snce then, energy researchers have developed several decomposton methods, and reported some applcatons n energy-related envronmental analyss. By adoptng ndex decomposton analyss (IDA), researchers are able to have a better understandng of the drvers of energy use and energy-related emssons n a specfc energy consumpton sector, such as transportaton or ndustry. Smlarly, we apply ndex decomposton methodology to analyze the drvers of energy consumpton n dfferent scenaros of the selected reports Index Decomposton Methodology Amongst all decomposton methods, the Laspeyres and the arthmetc mean Dvsa ndex methods are frequently used [14]. We apply the arthmetc mean Dvsa ndex method to analyze energy consumpton and CO 2 emsson drvers n dfferent scenaros. The method and the concept of ndex decomposton of the aggregate energy ntensty of ndustry are ntroduced below. Assume that there are m dfferent sectors n ndustry. Defne the followng varables for tme t. E t = Total ndustral energy consumpton; E,t = Energy consumpton n ndustral sector ; Y t = Total ndustral producton; Y,t = Producton of ndustral sector ; S,t = Producton share of sector (= Y,t /Y t ); I t = Aggregate energy ntensty (= E t /Y t ); I,t = Energy ntensty of sector (= E,t /Y,t ); The aggregate energy ntensty s expressed n terms of sectoral energy ntensty multplyng producton share: I t = S,t I,t (1) Suppose the aggregate energy ntensty vares from I 0 n tme 0 to I T n tme T. Such a change can be expressed n two ways: D tot = I T /I 0 and ΔI tot = I T I 0 [14]. The frst s referred to as multplcatve decomposton:

16 Energes 2013, D tot = I T I 0 = D str D nt (2) In Equaton (2), D str and D nt respectvely represent the estmated mpacts of changes n structure and sectoral energy ntensty. The second way s addtve decomposton: I tot = I T I 0 = oi str + ti nt (3) In Equaton (3), the mpacts of changes n structure and sectoral energy ntensty are expressed n addtve form. The Laspeyres ndex method solates the mpact of a varable by changng the specfc varable whle keepng the other varables constant. The formulae for multplcatve decomposton are: D str = S,T I,0 S,0 I,0 (4) D nt = S,0 I,T S,0 I,0 D rsd = D tot (D str D nt ) (6) D rsd denotes the unexplaned part of D tot. The formulae for addtve decomposton are: (5) I str = S,T I,0 S,0 I,0 (7) I nt = S,0 I,T S,0 I,0 I rsd = I tot I str I nt (9) The arthmetc mean Dvsa ndex method apples natural logarthm to I t, and the dfferental equaton as follows: dln(i t ) dt = ω dln S,t dt + dln I,t dt In Equaton (10), ω = E,t /E t, s the sector share of energy consumpton. Integratng from tme 0 to tme T: Thus: T ln(i T /I 0 ) = ω dln S,t /dt 0 T T + ω dln I,t /dt 0 (8) (10) (11) D str = exp ω dln S,t /dt (12) 0 T D nt = exp ω dln I,t /dt (13) 0 In emprcal studes, only dscrete data are avalable. Therefore, Equatons (12) and (13) are often approxmated by the arthmetc mean of the weghts for tme 0 and tme T:

17 Energes 2013, and the addtve decomposton formulae are: D str = exp ω,t + ω,0 ln S 2,T /S,0 (14) D nt = exp ω,t + ω,0 ln I 2,T /I,0 (15) E,T + E,0 Y I str = T Y 0 ln S 2,T /S,0 E,T + E,0 Y I nt = T Y 0 ln I 2,T /I,0 (16) (17) 6.2. Index Decomposton Method of Natonal Energy Consumpton and CO 2 Emsson The ndex decomposton method s appled to analyze the external assumpton mpacts on the energy consumpton and CO 2 emsson n dfferent scenaros. The followngs are the calculaton example of ndex decomposton of energy demand, and the analyss on CO 2 emsson goes the same way. Before ndex decomposton, a lnear regresson s made to ft the trend of energy consumpton from the base year to the projecton year. We choose energy ntensty I t to ndcate the energy demand of year t, and I t s assumed to have lnear correlaton wth P 1t and P 2t, whch represent per capta GDP of year t and per capta energy demand of year t respectvely: I t = a 0 + a 1 P 1t + a 2 P 2t (18) where: I t : Energy ntensty of year t = Energy demand of year t/gdp of year t; P 1t : per capta GDP of year t = GDP of year t/populaton of year t; P 2t : per capta energy demand of year t = energy demand of year t/populaton of year t; a 0, a 1 and a 2 : regresson coeffcents. Based on the projected energy demands from the base year to the projecton year, a 0, a 1, a 2 can be calculated by lnear fttng method. We substtute the data of the energy demand, GDP, per capta GDP and per capta energy demand of the base year, 2020 and 2035 nto Equaton (18), respectvely, and get the followng equatons: I base year = a 0 + a 1 P 1,base year + a 2 P 2,base year (19) I 2020 = a 0 + a 1 P 1, a 2 P 2,2020 (20) I 2035 = a 0 + a 1 P 1, a 2 P 2,2035 (21) In Equatons (19 21), a 0, a 1 and a 2 are unknown varables. By solvng the three smultaneous equatons, we can have the value of a 0, a 1 and a 2. Then further analyss on the regresson coeffcents are made as follows:

18 Energes 2013, dln(i t ) dt = 1 I t a 1 dp 1t dt + a 2 dp 2t dt (22) dln(i t ) = 1 I t (a 1 dp 1t + a 2 dp 2t ) (23) Defne: ln I t I 0 = 1 I t [a 1 (P 1t P 10 ) + a 2 (P 2t P 20 )] (24) I t I 0 = exp a 1 I t (P 1t P 10 ) + a 2 I t (P 2t P 20 ) = exp a 1 I t (P 1t P 10 ) exp a 2 I t (P 2t P 20 ) (25) D e = I t /I 0 (26) D e1 = exp a 1 I t (P 1t P 10 ) (27) D e2 = exp a 2 I t (P 2t P 20 ) (28) Then D e ndcates the change of energy ntensty between the base year and the projecton year. By Equaton (25) to Equaton (28), D e = D e1 D e2, D e1 ndcates the mpact of GDP growth on energy demand, and D e2 ndcates the mpact of populaton growth on energy demand. Smlarly, we can make lnear regresson on CO 2 emsson ntensty as the functon of per capta GDP and per capta energy demand: C t = b 0 + b 1 P 1t + b 2 P 2t (29) In Equaton (29), C t represents the CO 2 emsson ntensty of year t, and C t = CO 2 emssons of year t/gdp of year t; b 0, b 1 and b 2 are the regresson coeffcents, whch can be calculated wth the same method used to calculate a 0, a 1 and a 2, as already stated. After ndex decomposton, defne: D c = C t /C 0 (30) D c1 = exp b 1 C t (P 1t P 10 ) (31) D c2 = exp b 2 C t (P 2t P 20 ) (32) D c ndcates the change of CO 2 emsson ntensty between the base year and the projecton year. And D c = D c1 D c2, D c1 ndcates the mpact of GDP growth on CO 2 emssons, and D c2 ndcates the mpact of populaton growth on CO 2 emssons. The decomposton process s carred out by Mcrosoft excel, and the results and dscussons wll be gven below Index Decomposton Results The ndex decomposton of energy demand and CO 2 emsson n dfferent scenaros are shown n Fgures 13 and 14.

19 Energes 2013, Fgure 13. Index decomposton of energy ntensty. Fgure 14. Index decomposton of CO 2 emsson ntensty. In Fgure 13, the horzontal axs represents the changes from the base year to projecton year, and the vertcal axs represents the rato of GDP and populaton mpacts on energy ntensty changes. When D e1 /D e2 s larger than one, t means that mpacts of per capta GDP are greater than per capta energy demand. Contrarly, when D e1 /D e2 s smaller than one, t means that mpacts of per capta energy demand are greater than per capta GDP. For energy demands n scenaros of WEO 2010 [7] and the Chnese Academy of Engneerng, most decomposed populaton ndexes are smaller than GDP ndexes, ndcatng that economy has greater mpacts than per capta energy demand on energy demand growth. At the same tme, both the ndexes have postve mpacts on energy demand growth.

20 Energes 2013, For energy demands n scenaros of IEO 2010 [8], D e1 /D e2 are mostly equals to zero, ndcatng that per capta energy demand has greater mpacts than economy on energy demand growth. Also, both the ndexes have postve mpacts on energy demand growth. However, the actual value of D e1 approaches 0 and D e2 approaches nfnty, ndcatng that n scenaros of IEO 2010 [8], energy demands are not approxmately lnearly dependent on populaton and GDP. Referred to the scenaro settngs, ol prce s a sgnfcant factor. In Fgure 14, the horzontal axs represents the changes from the base year to projecton year, and the vertcal axs represents the rato of GDP and populaton mpacts on CO 2 emsson ntensty changes. When D c1 /D c2 s larger than one, t means that mpacts of per capta GDP are greater than per capta energy demand. Contrarly, when D c1 /D c2 s smaller than one, t means that mpacts of per capta energy demand are greater than per capta GDP. For CO 2 emssons n scenaros of WEO 2010 [7] and the Chnese Academy of Engneerng, most decomposed populaton ndexes are smaller than GDP ndexes, ndcatng that economy has greater mpacts on CO 2 emsson than per capta energy demand. At the same tme, both the ndexes have postve mpacts on CO 2 emsson growth. For CO 2 emssons n scenaros of IEO 2010 [8], D c1 /D c2 are mostly equals to 0, ndcatng that per capta energy demand has greater mpacts than economy on CO 2 emsson growth. However, the actual value of D c1 approaches 0 and D c2 approaches nfnty, ndcatng that n scenaros of IEO 2010 [8], CO 2 emssons are not approxmately lnearly dependent on populaton and GDP. Referred to the scenaro settngs, ol prce s a sgnfcant factor. As there are no specfc ol prce data n the report, ndex decomposton on ol prce mpacts on energy demand and CO 2 emsson are not made here. The summary of the decomposton results s provded n Table 5. In concluson, by ndex decomposton on energy demand and CO 2 emsson ntensty changes from the base year to projecton year, we have better understandngs on how per capta GDP and per capta energy demand drve the total energy demand and CO 2 emsson n dfferent scenaros. For WEO 2010 and the Chnese Academy of Engneerng projectons: compared wth per capta energy demand, economy has greater mpacts on energy demand ntensty and CO 2 emsson ntensty. For IEO 2010 projectons, per capta energy demand has greater mpacts than economy growth, and ol prce s consdered as a sgnfcant factor of energy demand and CO 2 emsson changes. Index Decomposton of Energy Intensty Table 5. Summary of the decomposton results. 2020/base year 2035/base year 2035/2020 D e D e1 /D e2 D e D e1 /D e2 D e D e1 /D e2 CPS WEO 2010 NPS S RC HEGC IEO 2010 LEGC HOPC LOPC MLEC

21 Energes 2013, Index Decomposton of CO 2 Emsson Intensty Table 5. Cont. 2020/base year 2035/base year 2035/2020 D c D c1 /D c2 D c D c1 /D c2 D c D c1 /D c2 CPS WEO 2010 NPS S RC HEGC IEO 2010 LEGC HOPC LOPC MLEC , Notes: CS: Current Polces Scenaro; NS: New Polces Scenaro; 450S: 450 Scenaro; RC: Reference Case; HEGC: Hgh Economc Growth Case; LEGC: Low Economc Growth Case; HOPC: Hgh Ol Prce Case; LOPC: Low Ol Prce Case. 7. Conclusons By studyng and comparng fve exstng reports of macro energy scenaros of Chna, we llustrate the major dfferences of the scenaros, and nterpret reasons behnd these dfferences. By summarzng and revewng the crtera above, we show the dfferences n obtanng varous scenaros of the macro energy stuaton of Chna n the future. For the Chnese Academy of Engneerng s projectons, energy savng potental s consdered n a substantal way, leadng to smaller amount of total energy demand compared wth other scenaros. By carefully estmatng the energy resource avalabltes, makng technology development pathways and promotng ncentve polces, the Chnese Academy of Engneerng projects a relatvely lower range of coal demand and hgher share of total energy demand n 2030, and lower energy-related CO 2 emssons, compared wth other scenaros. For scenaros n WEO 2010 [7], the energy-related CO 2 emsson s the most mportant external lmt of energy consumpton. In these scenaros, the CO 2 -ntensve energy demands are strctly controlled n order to acheve the total CO 2 emsson reducton targets, and renewable energy demand has greater shares of total than that n other scenaros. To better understand the drvers of energy demand and CO 2 emsson trend, we ntroduce ndex decomposton method to analyze economc and populaton mpacts. For WEO 2010 [7] and the Chnese Academy of Engneerng projectons: compared wth per capta energy demand, economy has greater mpacts on energy demand ntensty and CO 2 emsson ntensty. For IEO 2010 projectons, per capta energy demand has greater mpacts than economy growth, and ol prce s consdered as a sgnfcant factor of energy demand and CO 2 emsson changes. Acknowledgments The authors gratefully acknowledge the fnancal support from Natonal Natural Scence Foundaton of Chna (project No.: ), from the IRSES ESE Project of FP7 (contract No.: PIRSES-GA ), and from BP company n the scope of the Phase II Collaboraton between BP and Tsnghua Unversty.

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