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Energy Economics 34 (2012) S410–S420
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Energy Economics
j ourna l homepage: www.e lsev ie r .com/ locate /eneco
The impact of residential, commercial, and transport energy demand uncertainties inAsia on climate change mitigation
Tiina Koljonen ⁎, Antti LehtiläVTT Technical Research Centre of Finland, P.O.Box 1000, FI-02044 VTT, Finland
⁎ Corresponding author. Tel.: +358 20 722 5806; faxE-mail address: [email protected] (T. Koljonen).
0140-9883/$ – see front matter © 2012 Elsevier B.V. Alldoi:10.1016/j.eneco.2012.05.003
a b s t r a c t
a r t i c l e i n f oArticle history:Received 1 June 2011Received in revised form 11 May 2012Accepted 31 May 2012Available online 23 June 2012
Keywords:Asian Modeling ExerciseTIMES modelGreenhouse gas mitigationChinaIndiaSouth-East Asia
Energy consumption in residential, commercial and transport sectors have been growing rapidly in thenon-OECD Asian countries over the last decades, and the trend is expected to continue over the coming de-cades as well. However, the per capita projections for energy demand in these particular sectors often seemto be very low compared to the OECD average until 2050, and it is clear that the scenario assessments of finalenergy demands in these sectors include large uncertainties. In this paper, a sensitivity analysis have beencarried out to study the impact of higher rates of energy demand growths in the non-OECD Asia on globalmitigation costs. The long term energy and emission scenarios for China, India and South-East Asia havebeen contributed as a part of Asian Modeling Exercise (AME). The scenarios presented have been modeledby using a global TIMES-VTT energy system model, which is based on the IEA-ETSAP TIMES energy systemmodeling framework and the global ETSAP-TIAM model. Our scenario results indicate that the impacts ofaccelerated energy demand in the non-OECD Asia has a relatively small impact on the global marginalcosts of greenhouse gas abatement. However, with the accelerated demand projections, the average percapita greenhouse gas emissions in the OECD were decreased while China, India, and South-East Asia in-creased their per capita greenhouse gas emissions. This indicates that the costs of the greenhouse gas abate-ment would especially increase in the OECD region, if developing Asian countries increase their final energyconsumption more rapidly than expected.
© 2012 Elsevier B.V. All rights reserved.
1. Introduction
With rapid economic development China, India, and othernon-OECD Asian countries face a great challenge in meeting their in-creasing energy demand. On the other hand, global climate changemitigation requires significant reduction of greenhouse gas emissionsfrom the Asian economies. To cope simultaneously with climatechange mitigation, economic growth and the need for energy securi-ty, adoption of low carbon economy would be needed, which meanslarge investments in low carbon technologies in energy conversion,industry, and other energy end-use sectors. This paper presents ener-gy and emission scenarios for China, India and South-East Asia, whichhave been contributed as a part of Asian Modeling Exercise (AME). Aparticular focus of the scenario assessments has been on impacts ofresidential, commercial and transport energy demand uncertaintiesin these Asian regions on climate change mitigation. The AME scenar-ios presented in this paper include Baseline (i.e. AME Reference Sce-nario 1a), Tax-2a, Tax-2b, and Tax-2c (i.e. AME scenarios 2a “CO2.Price $10 (5% p.a.)”, 2b “CO2. Price $30 (5% p.a.)”, and 2c “CO2. Price$50 (5% p.a.)” respectively), radiative forcing scenarios F-3.7W andF-2.6W (i.e. AME scenarios 3a “3.7W/m2 NTE” and 3b “2.6W/m2 OS”
: +358 20 722 7026.
rights reserved.
respectively), and three additional scenarios Baseline-S, F-3.7W, andF-2.6W–S with accelerated energy demand projections. This studyalso presents the role of energy efficiency and other low carbon policiesin residential, commercial and vehicle road transport sectors intransitioning China, India and South-East Asia to a low emission society.These sectors are currently undergoing rapid expansion of energy usealong with rapid urbanization and economic development. It has beenevaluated that in China over 470million additional people could beurban residents by 2050 (Zhou et al., 2011). China's vehicle populationhas been estimated to increase from 63million in 2010 to 360–400mil-lion in 2040 and 600million in 2050 (Hao et al., 2011; Hu et al., 2010). Es-pecially, consumption of electricity in the residential sector in China hasrisen faster than all other energy forms in China over the last 20years(Brockett et al., 2002). Earlier studies focused on China's energy scenariosindicate very different growth rates of the residential, commercial andtransport sectors by the year 2050. The IEA's (2010a) Reference scenarioindicates 70% increase in energy consumption by 2050 in China com-pared to the 2005 level and in the Bluemap scenario the increase isonly 4%. The more recent study, which focused on China's developmentto 2050 by the Lawrence Berkeley National Laboratory (LBNL, 2011), in-dicates about 220% increase in the Baseline and 120% increase in the Ac-celerated Improvement Scenario (AIS) by 2050 respectively. Even thoughthe above mentioned and some other studies for India (de Vries et al.,2007; IEA, 2007, 2011; Shukla et al., 2008) have analyzed national
Table 2Projection of the annual growth in GDP for the model regions (OECD aggregated).
2005–2010 2011–2020 2021–2030 2031–2040 2041–2050
AsiaChina 9.4% 6.6% 4.4% 3.7% 2.8%India 8.4% 8.0% 4.9% 4.7% 4.3%ODA 6.0% 6.0% 4.8% 4.2% 3.5%Africa 3.8% 4.1% 3.2% 4.0% 4.8%Latin America 4.1% 4.0% 3.0% 3.0% 3.0%Middle East 4.6% 5.0% 4.4% 3.9% 3.4%CIS 4.7% 4.6% 3.3% 3.0% 2.7%OECD 2.3% 2.4% 2.1% 1.9% 1.8%World 4.5% 4.4% 3.4% 3.2% 2.9%
Table 1Regions in the global TIMES-VTT model.
Acronym Description
AFR AfricaAUS Australia+New ZealandCAN CanadaCHI China (including Hong Kong and Macao)CIS Former FSU, but excluding the Baltic statesEEU Eastern Europe (including the Baltic States)IND IndiaJPK Japan+South KoreaLAM Latin America (including Mexico and Central America)MEA Middle EastODA Other developing AsiaUSA United States of AmericaWEU Western EuropeDNK DenmarkFIN FinlandNOR NorwaySWE Sweden
S411T. Koljonen, A. Lehtilä / Energy Economics 34 (2012) S410–S420
pathways to low carbon economies and the long term development ofresidential or transport sectors, none of these studies have assessedthe impact of the development of these sectors on the global climatechange mitigation effort.
In this paper, we study the transition to low carbon energy sys-tems in China, India and South-East Asia with an especial focus onresidential, commercial, and transport sectors. The development ofclean energy systems of the studied Asian regions is compared tothe average OECD development to show the differences in technologymix and energy demand projections. Finally, the impacts of accelerateddemands in residential, commercial and transport sectors on per capitaprimary energy consumption, electricity consumption and greenhousegas emissions in China, India, and South-East Asia are shown to studythe impacts of higher rates of energy demand growths in the non-OECDAsia on global mitigation costs.
2. Methods
The scenarios have been modeled by using the global TIMES-VTTenergy system model, which is based on the TIMES energy systemmodeling framework developed under the IEA Energy TechnologySystems Analysis Programme (ETSAP), and the global ETSAP-TIAMmodel that has been available to all ETSAP members for some years(Loulou and Labriet, 2007; Loulou et al., 2005). Below, a short over-view of the TIMES-VTT is given and more detailed description of themodel is included in the Inline supplement of this paper.
The TIMES-VTT model is a global long-termmodel consisting of 17world regions, which are listed in Table 1. Within each region, theentire energy system is described and calibrated to the base year(2005) according to the IEA Energy Statistics (IEA, 2010b). Althoughthe model is originally based on the ETSAP-TIAM model, the modeldatabase has been updated and improved extensively at VTT, con-cerning for instance the regional potentials of bioenergy, wind powerand waste for energy, as well as the technology characterizations inmost sectors (see Inline supplement of this paper and Savolainen etal., 2008; Syri et al., 2008; Teir et al., 2010; VTT, 2009).
In the TIMES-VTT model crude oil, refined petroleum products,natural gas, liquefied natural gas, hard coal, nuclear fuel, bio-pellets,liquid biofuels, and electricity are endogenously traded between themodel regions. The prices of all these energy carriers are thus fully en-dogenous in the model, and the impacts of energy and environmentalpolicies are reflected in those prices. In addition to energy commodi-ties, also emissions (or emission permits) may be traded in the model.However, for the purpose of the AME scenario runs, emissions tradingwas not explicitly included in the model. Instead, global emissionstrading was simulated by setting bounds on the global mean radiativeforcing, as defined in the common AME scenario assumptions. More-over, trading in carbon storage services has been explicitly includedin the TIMES-VTT model, although at the moment only between theEuropean regions. The additional costs of CO2 transportation betweenthe trading regions was of course also applied to these trade flows(Teir et al., 2010).
Carbon capture and storage (CCS) technologies applied to biomassutilization in energy production, 2nd generation bio-refineries as wellin pulp and paper industries have also been included in the model.For power plants bio-CCS may become a significant option only in re-gions with a high density of biomass resources, although it may bequite viable also in biomass co-firing plants and in special niche mar-kets. Therefore, also co-firing of biomass with fossil fuels has been in-cluded in the model with a CCS option.
The assumptions used in the model concerning the main demanddrivers, population and economic growth, are in good agreementwith those used in e.g. the IEA scenarios (IEA, 2010a). With regardto climate change, the model includes the anthropogenic sources andmitigation measures of all greenhouse gas emissions included in theKyoto Protocol.
In the ETSAP-TIAM model, both the GEM-E3 and, more recently,the GEMINI-E3 model have been utilized for deriving the economicdriver projections (GDP and sector outputs), while the populationprojections have been taken from the medium variant published inthe UN World Population Prospects (UN, 2007). In the TIMES-VTTmodel, the older GEM-E3 model estimates were originally used forconstructing the economic drivers, but have later been adjusted tosomewhat higher levels for the rapidly developing economies onthe basis of the actual development in recent years. The GDP projec-tions used in AME scenarios are shown in Table 2.
In China, industrial energy use accounted for about 52% of the totalfinal energy consumption in 2005. According to the driver projec-tions, the total industrial output would increase in China aboutfive-fold between 2005 and 2050, while the total output in serviceswould increase about six-fold. In India, the corresponding growthwould be in industry 8.5-fold and in services about 10.5-fold. The pro-jections thus estimate rather high and steady growth for the industri-al sectors of China and India. Comparing these projections with otherrecent estimates (e.g. Kejun, 2011; LBNL, 2011; Zhou et al., 2011) in-dicates that the projections used in the AME scenario runs may have,indeed, been overestimating the growth in industrial output whileunderestimating the growth in the tertiary sector. In addition, the driverelasticities for both the tertiary and residential sectors may also havebeen underestimated. The impacts of these underestimations havebeen studied by sensitivity analysis, and the distortions compared toother estimates will be taken into account in the futuremodeling work.
Nonetheless, the projections used in the model correspond to percapita GDP values that are in China already about 80% and in Indiaabout 45% of the level in Western Europe in 2050. Using higher GDPgrowth assumptions for the rapidly developing Asian economiesmight thus lead even to a higher per capita GDP in China than theaverage in OECD countries already by 2050.
0
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Woodbiomass
Nuclear
Otherrenew.
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Electricityimports
Fig. 1. The development of total primary energy consumption in the OECD between 2005 and 2050 in the AME scenarios. Section “Other” is mainly solar energy.
S412 T. Koljonen, A. Lehtilä / Energy Economics 34 (2012) S410–S420
The AME model runs included two important scenarios in whichthe total radiative forcing was constrained. For the purpose of analyz-ing such climate impacts, the TIMES model includes a simple ClimateModule, comprising of models for the atmospheric concentrations ofthe most important greenhouse gases and the corresponding radia-tive forcing, as well as for the global temperature change. The math-ematical representation of the climate module of the TIMES-VTTmodel is presented in the Inline supplement of the paper.
3. Scenario results
3.1. Primary energy consumption
In all of the AME scenarios presented below, primary energyconsumption will rise continuously in the rapidly developing Asian
2020202005
Bas
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.7W
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.6W
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J (C
hin
a)
Fig. 2. The development of total primary energy consumption in China between
regions by 2050, while in the OECD countries the consumption staysroughly at the present level and may even slightly decrease. The re-sults for primary energy are illustrated in Fig. 1 for the OECD, and inFigs. 2, 3 and 4 for China, India and ODA, respectively.
The Baseline results for total primary energy consumption indicatea growth of 110% in China, 200% in India and 190% in ODA by 2050.Coal would continue to have a dominating role in both China andIndia, whereas the supply structure remained more balanced in theODA region. In the climate policy scenarios, the total use of coal mayeven decrease from the present levels, while all renewable energy car-riers and nuclear would increase their contribution significantly. Thepresent use of wood biomass is estimated to somewhat exceed the sus-tainable utilization levels in the newly industrialized Asian regions(China, India, other developing Asia), and therefore the results showa decrease in the future consumption, most notably in the Baseline.
205030
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Nuclear
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Hydro
Electricityimports
2005 and 2050 in the AME scenarios. Section “Other” is mainly solar energy.
2050203020202005
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J (I
nd
ia)
Other
Coal
Gas
Oil
Otherbiofuels
Woodbiomass
Nuclear
Otherrenew.Hydro
Electricityimports
Fig. 3. The development of total primary energy consumption in India between 2005 and 2050 in the AME scenarios. Section “Other” is mainly solar energy.
S413T. Koljonen, A. Lehtilä / Energy Economics 34 (2012) S410–S420
On the other hand, the potential for other bioenergy production is esti-mated to be considerable, approximately 25EJ in 2050, and it will beutilized to full extent in the strictest policy scenarios.
For the newly industrialized Asian economies, the potential to re-duce future energy demand is greatest in the industry sector. Thelarge use of traditional biomass, which is still at present very signifi-cant in the residential sector, also represents a considerable potentialfor efficiency improvements, especially in China. However, the shift tomore efficient technologies and fuels in the residential sector alreadyoccurs in the model to a large extent in the Baseline due to increasingfossil fuel prices. In the policy scenarios, the results indicate reduc-tions in the total primary energy consumption of up to 30% by 2050in China, compared to the Baseline. However, one should note that alarge part of the reduction is due to the increase in non-biomass re-newables (hydro, wind, solar).
2020202005
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J (O
DA
)
Fig. 4. The development of total primary energy consumption in the ODA region betw
3.2. Electricity supply
The electricity sector accounts for a large and growing proportionof the energy use and related CO2 emissions of the newly industrial-ized Asian economies. At present, coal power is by far the most im-portant power supply option in both China and India, while in ODAalso gas-fired power has a significant contribution. The future devel-opment of the electricity supply in these regions is depicted in Fig. 5.
In China, the total electricity supply increases almost five-fold by2050 in the Baseline, with coal power accounting for most of the in-crease. In the policy scenarios, the total electricity demand is up to25% lower, yet it exhibits a 3.5-fold increase compared to 2005.According to the scenario results, by 2050 wind power could have a15% share in the total supply of China and 10% share in India. InIndia, the 10% wind share would make the estimated wind power
205030
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Woodbiomass
Nuclear
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Hydro
Electricityimports
een 2005 and 2050 in the AME scenarios. Section “Other” is mainly solar energy.
2005
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su
pp
ly, T
Wh
China India ODA
Net imports
Other
Pub.CHP
Ind. power
Gas+oil
Coal fuels
Biofuels
Wind
Hydro
Nuclear
Fig. 5. Electricity supply by main category in China, India and the ODA region in 2005 and 2050. Section “Other” is mainly solar electricity.
S414 T. Koljonen, A. Lehtilä / Energy Economics 34 (2012) S410–S420
potential practically exhausted, giving an indication that the poten-tials may be underestimated. Also the contribution of solar powerwould become notable by 2050, in China up to 8% and in India up to13% of the total supply. In China, hydropower expansion and com-bined heat and power may also have a significant role in thebuild-up the future electricity supply.
3.3. Final energy consumption
Fig. 6 illustrates the development of the total final energy consump-tion bymain sector in China, India and the ODA region. According to theBaseline results, in China the industrial sectors would cover over 60% ofthe total final energy consumption in 2050 and in India about 40%.However, as mentioned above, the projections for the drivers of
2005
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China India
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gy,
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Fig. 6. Final energy consumption by main end-use sector i
industrial energy services may have been overestimated, and the pro-jections for the tertiary and residential demands underestimated inthe model for the rapidly developing Asian economies. In the Chapter3, the results of the sensitivity analysis for the accelerated developmentof energy service demands has shown to assess impacts of these de-mand uncertainties on climate change mitigation.
The demands in the tertiary and residential sectors were also as-sumed to grow rapidly in the Asian regions. According to the Baselineprojections, for example, the demand for residential lighting andcooling services are both projected to increase roughly ten-fold by2050 in China and even somewhat further in India. Roughly similardemand growths were also projected also in the tertiary sector. Suchimmense growth in the demand for energy services can also make thepotential penetration of new, high efficiency end-use technologies
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n China, India and the ODA region in 2005 and 2050.
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Fig. 7. Total net carbon dioxide emissions (including land-use change and CCS) in the AME scenarios between 2005 and 2100.
S415T. Koljonen, A. Lehtilä / Energy Economics 34 (2012) S410–S420
larger in the rapidly developing regions, compared to the OECD. On theother hand, for example, the total floor area of service buildings wasprojected to more than double in China between 2005 and 2050, butthe total floor area of residential buildings by only about 30%.
One should also point out that the ambient heat utilized by heatpumps in residential and commercial heating and cooling is not in-cluded in the energy balance but is reflected as an efficiency im-provement. According to the results, particularly in the tertiarysector, heat-pumps would indeed dominate the heating and cooling
Table 3Per capita scenario results for the heat and electricity demands (GJ per capita) of theresidential and commercial sectors with base and accelerated demand drivers.
Scenario Region CategoryGJ/capita
2005 2020base
2020acceler.
2050base
2050acceler.
Reference OECD Res-Heat 19.0 17.1 17.6 16.0 15.7Reference OECD Com-Heat 9.8 7.7 8.4 9.1 8.7Reference OECD Res-Other 9.6 10.4 10.4 13.7 13.7Reference OECD Com-Other 11.6 13.4 13.4 17.0 17.2Reference CHI Res-Heat 6.1 4.1 5.3 4.0 4.1Reference CHI Com-Heat 0.6 0.9 0.9 1.4 1.4Reference CHI Res-Other 4.5 5.5 6.2 8.4 10.9Reference CHI Com-Other 2.2 3.2 4.8 4.7 14.3Reference IND Res-Heat 2.1 1.5 1.8 1.3 1.2Reference IND Com-Heat 0.1 0.2 0.2 0.4 0.3Reference IND Res-Other 3.9 4.1 5.6 5.9 10.9Reference IND Com-Other 0.9 1.5 3.0 2.9 13.8Reference ODA Res-Heat 3.3 1.8 2.8 1.8 1.9Reference ODA Com-Heat 0.2 0.3 0.3 0.5 0.5Reference ODA Res-Other 4.4 4.7 6.0 6.6 10.8Reference ODA Com-Other 1.1 1.7 3.3 3.3 14.53B OECD Res-Heat 19.0 17.0 17.5 14.4 14.23B OECD Com-Heat 9.8 8.0 8.4 6.5 5.93B OECD Res-Other 9.6 10.4 10.4 13.2 13.23B OECD Com-Other 11.6 12.5 12.5 15.6 15.63B CHI Res-Heat 6.1 4.4 5.4 2.7 2.73B CHI Com-Heat 0.6 0.9 0.9 1.0 1.13B CHI Res-Other 4.5 5.4 6.1 7.3 9.43B CHI Com-Other 2.2 3.1 4.5 4.0 12.23B IND Res-Heat 2.1 1.5 1.8 1.3 1.33B IND Com-Heat 0.1 0.2 0.2 0.3 0.23B IND Res-Other 3.9 4.1 5.5 5.1 9.33B IND Com-Other 0.9 1.5 2.9 2.6 12.13B ODA Res-Heat 3.3 2.2 2.8 2.1 1.83B ODA Com-Heat 0.2 0.3 0.3 0.4 0.43B ODA Res-Other 4.4 4.6 5.9 6.1 9.83B ODA Com-Other 1.1 1.6 3.2 2.7 11.6
market in Asia by 2050. Consequently, the demand of energy servicesand the final energy demand are strongly decoupled in the resultsfor the rapidly developing Asian regions. The impact of possiblyunderestimating the tertiary and residential demands are analyzedfurther in the sensitivity analysis section below.
3.4. Greenhouse gas emissions
In the Baseline, the total global greenhouse gas emissions will in-crease to approximately 68Pg(CO2 eq.) by the year 2050 and to 92Pgby 2100. In the climate policy scenario 3b with the forcing target of2.6W/m2 the, emissions will be reduced to approximately 28Pg bythe year 2050 and to as low as 5.4Pg in the year 2100, correspondingto a 94% reduction from the Baseline. Because some of the non-CO2
emissions are extremely difficult and expensive to reduce, such a dra-matic cut in the global emissions can only be achieved by utilizing car-bon sequestration, both through afforestation programmes and byutilizing bio-CCS technologies where economically feasible.
The development of total global CO2 emissions is illustrated inFig. 7. The results indicate that achieving the strict target of 2.6W/m2
for radiative forcingwould require practically zero carbon dioxide emis-sions in the last decades of the century. With the less stringent target of3.7W/m2, a reduction of 88% in the global emissions by the end of thecentury would be sufficient.
3.5. Sensitivity analysis for the development of energy service demands
Table 3 shows the scenario results for the heat and electricitydemands for the residential and commercial sectors assessed withthe demand drivers described in Chapter 2.6 and with accelerateddrivers for the Baseline and the AME policy scenarios 2a, 2b, 2c, 3aand 3b. The corresponding scenario results are shown for vehicleroad transport in Table 4. Results for the accelerated climate policyscenarios for the Baseline (Base-S scenario) and radiative forcing sce-nario 3b (F-2.6W–S scenario) are shown in Figs. 8 and 9 and com-pared to the average OECD values.
Our scenarios with base drivers for energy consumption in theresidential and commercial sectors in China and India 2050 are verywell in line with the IEA Reference and Bluemap scenarios (IEA,2010a). On the other hand, the corresponding energy consumptionfor China with the accelerated demand drivers are still somewhatlower than in the LBLN (2011) study for the Baseline but for the
Table 4Per capita scenario results for the vehicle road transport (1000km per capita) withbase and accelerated demand drivers.
Scenario Region 2005 2020base
2020acceler.
2050base
2050acceler.
1000km/capita
Reference OECD 7.85 9.41 9.13 13.97 12.77Reference CHI 0.28 0.73 1.35 1.83 3.00Reference IND 0.11 0.24 0.48 0.59 2.00Reference ODA 0.45 0.99 1.04 2.39 3.003B OECD 7.85 9.41 9.13 13.95 12.763B CHI 0.28 0.72 1.33 1.76 2.893B IND 0.11 0.24 0.48 0.56 1.923B ODA 0.45 0.99 1.04 2.34 2.94
S416 T. Koljonen, A. Lehtilä / Energy Economics 34 (2012) S410–S420
policy scenarios, the accelerated demand of energy services is veryclose to LBLN (2011) AIS scenario. However, even with accelerateddemand drivers the per capita results shown in the Fig. 8 are farbelow the OECD average. The heat demands for residential and com-mercial sectors seem to be especially low, which can partly beexplained with warm climatic conditions. In our assessments, sensi-ble heat produced by lighting, electrical appliances, etc. are alsotaken into account in modeling.
In the Baseline scenario, energy use in transportation increased byover 260% by the year 2050 in developing Asia and with the acceler-ated demand drivers the increase was as high as 520% even though alarge part of the energy saving potential was realized in the Baselinescenarios. On the other hand, as shown in Table 4, even with the ac-celerated demand drivers, the per capita scenarios for vehicle trans-port are far below the OECD average. In the 2.6W/m2 radiativeforcing scenario 3b, the increase in energy use was not so high dueto the penetration of electric vehicles and alternative low carbonfuels. However, the penetration of these technologies seems to bevery low compared to the development of the OECD-countries, asshown in Fig. 9. Our results for the Asian transportation sector alsoshow very different trend compared to the studies shown by Zhouet al. (2011), where the maximum penetration of electric vehicleswas assumed to be as high as 70% of urban private cars by 2050.
Finally, we show the impact of accelerated demand in the residen-tial, commercial and transport sectors on per capita primary energyconsumption (Fig. 10), electricity consumption (Fig. 11) and green-house gas emissions (Fig. 12). The sensitivity analysis for the residentialand transport sectors indicate that increased demands in these sectors
0
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Fig. 8. Energy consumption per capita in the residential and commercial sectors in the OECDaccelerated demand drivers.
would especially increase the consumption of oil and natural gasresulting in higher greenhouse gas emissions per capita in China,India, and ODA. However, the scenario results for marginal costs ofgreenhouse gas abatement indicate (see e.g. Fig. 13) that the impactof increased energy consumption in residential and transport sectorsis relatively low on the direct cost of global greenhouse gas mitigation.
4. Discussion and conclusions
This paper has addressed the uncertainties related to the gradualclosure of the large gaps in the present day energy intensities be-tween the rapidly developing Asian regions and the OECD countries,which present a challenge for long-term energy systems modelling.In the current urbanization and economic growth patterns of China,India, and South-East Asia, there will be a striking increase in energydemands in the residential, commercial and transport sectors. Thesecountries are also putting increasing effort to cope with energy secu-rity and climate change mitigation. For example, China is promotingalternative fuels and vehicles by new standards and other policies.On the other hand, the starting point of the development is still at avery low level compared to the average per capita energy consump-tion of the OECD countries. According to the AME scenarios runwith the TIMES-VTT model it seems that per capita consumptionwould stay at a rather low level, even in the long term. Assumingthat there would still be notable differences in the per capita GDP be-tween the rapidly growing Asian countries and the OECD in 2050 andlater, the demand for energy services would also likely remain muchsmaller in the Asian countries, and this was indeed the case in ourBase case model runs. However, according to several studies (for ex-ample, Hao et al., 2011; LBNL, 2011) the per capita demand for resi-dential, tertiary and transport sector energy services in these Asiancountries are projected to be much higher already by 2050. Suchhigher demand projections imply that the exogenous assumptionsof the GDP or income growths in our Base case model runs mayhave been considerably underestimated, which called for the sensi-tivity analysis that we subsequently carried out for this paper. Thespeed of increase in electricity demand in residential and commercialsectors is particularly uncertain. Also, the driver elasticities of the de-mand drivers should better reflect the income elasticities to describeelectricity consumption of these rapidly evolving Asian economies.Therefore there is a need for developing parameters, such as incomeelasticity for electrical appliances, to better describe the dynamic
OECD2.6 W/m2
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and developing Asian countries (DEAS) including China, India and South-East Asia with
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Fig. 9. Transport final energy and bymain fuel or energy source for OECD (abovefigure) and developing Asia (China, India and South-East Asia). In the scenarios Base-S and F-2.6W/m2-S,accelerated energy demands for the residential and transport sectors are assumed.
S417T. Koljonen, A. Lehtilä / Energy Economics 34 (2012) S410–S420
drivers of soaring Asian energy demand. On the other hand, the LBNL(2011) study assumed that saturation in ownership of appliances, in-crease in floor area, etc. will peak around 2030 in China.
Compared to the AME scenario results of the other modelingteams, it seems that our scenarios for primary energy and electricityconsumption are somewhat below the average both in the Baselinescenario and in the policy scenarios for Asia. As a further test on sen-sitivity to the assumptions of the energy demand drivers, accelerateddemands for energy services in Asian private households and com-mercial sector as well as in vehicle road transport were alternativelyassumed in our study. Our base drivers for energy consumption inresidential and commercial sectors in China and India up to 2050seemed to be well in line with the IEA Reference and Bluemap scenar-ios (IEA, 2010a). On the other hand, our accelerated demand drivers
for China resulted in a 130% increase in energy consumption from2005 to 2050 in the residential and commercial sectors in the Baselinescenario, while in the LBNL (2011) study the corresponding increasewas above 220%. In the policy scenarios both our and LBNL study in-dicated approximately 100% increase by 2050. However, althoughthe resulting growth rates in final energy use were much higherwith accelerated demand drivers, they had a relatively small impacton the marginal costs of greenhouse gas emission abatement. Evenwith very high growth in the Asian energy intensities, the global cli-mate change mitigation target of a forcing of at most 3.7W/m3 stillappears to remain feasible marginal cost levels, but the stricter targetof 2.6W/m2 is beyond reasonable costs even with our base assump-tions. On the other hand, with the accelerated demand projectionsthe average per capita greenhouse gas emissions in the OECD were
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Fig. 10. Per capita primary energy consumption in China, India and South-East Asia (ODA) in 2005 and 2050. In the scenarios Base-S and F-2.6W/m2-S, accelerated energy demandsfor the residential and transport sectors are assumed. Section “Other” is mainly solar energy.
S418 T. Koljonen, A. Lehtilä / Energy Economics 34 (2012) S410–S420
decreased while China, India, and South-East Asia increased their percapita greenhouse gas emissions. This result indicates that the costs ofthe greenhouse gas abatement would especially increase in the OECDregion if developing Asian countries increase their final energy con-sumption more rapidly than expected.
All of the scenarios discussed in this paper require extensivechanges in technologies across economies and energy sectors. TheTIMES-VTT model includes a comprehensive database of new lowcarbon technologies, which has been developed in collaborationwith national and international technology developers and experts.However, economic restructuring and innovation in higher valueadded industries are examples which are not considered in our model-ling. These factors may limit the speed of penetration of new technolo-gies. For example, due to the complex systems of sustainable energy
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Fig. 11. Per capita electricity consumption in China, India and South-East Asia (ODA) in 200the residential and transport sectors are assumed.
supply for road transportation energy, our scenario results indicatethat the penetration of new vehicle technologies can be largelyunderestimated in our scenarios. On the other hand, the time delayin the penetration of high-efficiency and low carbon technologieswould result in much higher growth in energy demand than pres-ented in this paper.
Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.eneco.2012.05.003.
Acknowledgments
VTT's contribution to the Asian modeling exercise was based on fi-nancing and support of the national project SALKKU. The authorsgreatly acknowledge the financial support from Tekes—the Finnish
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5 and 2050. In the scenarios Base-S and F-2.6W/m2-S, accelerated energy demands for
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Fig. 12. Per capita greenhouse gas emissions in China, India and South-East Asia (ODA) in 2005 and 2050. In the scenarios Base-S and F-2.6W/m2-S, accelerated energy demands forthe residential and transport sectors are assumed.
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Fig. 13. Marginal costs of greenhouse gas emission abatement in the forcing target scenarios. In the scenarios F-3.7W/m2-S and F-2.6W/m2-S, accelerated energy demands for theresidential and transport sectors are assumed.
S419T. Koljonen, A. Lehtilä / Energy Economics 34 (2012) S410–S420
Funding Agency for Technology and Innovation, Gasum, HelsinginEnergia, Metso Power, the Technology Industries of Finland, and VTT.
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