99

Methodology for Designing Quantitative Roadmaps towards
Low-Carbon Societies using a Backcasting Approach
Shuichi ASHINA* and Junichi FUJINONational Institute for Environmental Studies,
16-2 Onogawa, Tsukuba 305-8506, Japan*e-mail: ashina.shuichi@nies.go.jp

Abstract
Drastic socioeconomic transformation is expected in the course of realizing a low-carbon society in
Asian countries, and it will be essential to establish quantitative roadmaps that indicate which options (technologies and policies) need to be introduced or implemented, at what intensity, and by when. The backcasting
approach can be an effective means of designing future roadmaps. This approach involves drawing up a target
vision to be realized (or avoided), then formulating a roadmap and pathways to satisfy the future target conditions. In this paper, we propose a methodology to create quantitative roadmaps towards a low-carbon societyin Asian countries based on the backcasting approach. Our methodology consists of two main steps: (1)formulation of a qualitative roadmap, and (2) design of a quantitative roadmap using a simulation model. In
the first step, through an analysis of the barriers that need to be overcome towards realizing the target vision,
the required options in the roadmap are specified and mutual relationships among the options are establishedin temporal order. In the second step, using the AIM/Backcasting Model, CO2 emission pathways, energy
composition and investment profiles are quantitatively determined, and a Gantt chart can also be designed.
Finally, in this paper we examine the effectiveness of this approach by describing some results of its
application to Japan.
Key words: backcasting, CO2 emissions, low-carbon society scenario, roadmaps

1. Introduction
This paper describes a methodology for designing aquantitative roadmap based on a low-carbon society(LCS) vision in a target year, and demonstrates its effectiveness through its application to Japan. The methodology consists of two main steps: (1) formulation of aqualitative roadmap, and (2) design of a quantitativeroadmap using a backcasting model. The first step,
formulation of a qualitative roadmap, consists of threestages: (i) determination of the barriers to achieving agiven LCS vision; (ii) development of strategies including policies, technologies and social reforms for overcoming these barriers; and (iii) identification of sequential combinations in the implementation of each strategy.
The second step, design of a quantitative roadmap using a
backcasting model, consists of two stages: (i) development of quantitative data for each of the technologies andpolicies, and (ii) investigation and selection of technologies and policies to be introduced, and when and at what
intensity, using a backcasting model based on certain
criteria.
Either of two approaches can be used when designinga future roadmap; namely, forecasting and backcasting. A
Global Environmental Research
17/2013: 99-107
printed in Japan

forecasting approach describes a future roadmap byextending the situation of current socioeconomic conditions. Such a roadmap may include the effects of futurechanges in technology levels, industrial structures andsocioeconomic transitions, as well as proposed actions
that aim to improve the current situation, such as CO2
mitigation actions. In the backcasting approach, on theother hand, a target image to be realized (or avoided) is
first drawn up, then a roadmap and pathways to satisfy
the future target conditions are formulated. A future
roadmap developed using the forecasting approach canbe explained as a consequence of the present situation,but, without any appropriate additional constraints, sucha roadmap does not provide assurance that the target
future vision can be achieved. In contrast, the backcasting approach makes it possible to develop a roadmap
towards a target vision in the future, or may sometimes
clarify infeasibilities in the target vision. This type ofroadmap is strictly bound by the given target vision andconditions, and does not facilitate discussions as towhether or not the vision and the roadmap provide theoptimal solutions. These approaches are therefore complementary to each other, and it can be useful to discuss
the feasibility of a designed roadmap by means of the©2013 AIRIES

100

S. ASHINA and J. FUJINO

forecasting approach. Both steps of the methodology
should be carried out repeatedly in order to design qualitative and quantitative roadmaps with consistency.
In the past, various studies have been conducted toanalyze CO2 mitigation pathways (or pathways towards
an LCS), at both the global and regional/national scale.
Akimoto et al. (2004) discussed importance of CO2
mitigation options and their regional impacts by using the
Dynamic New Earth 21 (DNE21) Model, a type of
integrated assessment model that considers economy,energy and climate systems combined. Calvin et al.
(2009) discussed the impacts of technology assumptions
on global and regional CO2 mitigation pathways under
several policy scenarios by using the Second Generation
Model (SGM model), a type of computable generalequilibrium (CGE) Model. They also investigated carbon
leakage of the industrial sector and concluded thatdelayed action would decrease near-term mitigation costs
but lead to increased long-term mitigation costs. Ekholm
et al. (2010) and Syri et al. (2008) investigated global andregional pros and cons of various types of effort-sharing
schemes such as the Triptych approach and a multistage
approach for reducing global CO2 emissions by applying
the ETSAP TIMES Integrated Assessment Model(ETSAP-TIAM) model. Gurney et al. (2009) revealed
global and sectoral economic impacts of various global
mitigation scenarios and transition pathways of electricity and transport sectors to a low-carbon world. Several
studies such as Aki et al. (2006), Dagoumas and Barker(2010), Kannan (2009), and Wu et al. (1994) put theiremphasis on regional impacts of GHG mitigation actions
on GHG pathways and economic and energy transitions.
These studies reported impacts on the energy mix andeconomic activities as a consequence of imposing CO2
emission targets. Some studies have proposed methodologies for the development of quantitative roadmaps
using simulation models. For example, Pugh et al. (2011)
described future energy research and development(R&D) portfolios in order to support funding decisions
by U.S. Department of Energy (USDOE). Chen et al.
(2011) put their emphasis on the power sector in China
and discussed future transitions of types of power plants
by applying a power mix planning tool. Whereas roadmaps in these past studies are described as changes inenergy and/or technology compositions, Ashina et al.
(2010, 2012) drew up future roadmaps not only for technologies but also for policies and optimal investment
timing towards the achievement of a drastic reduction of
CO2 emissions in Japan. Here, based on studies such as
Ashina et al. (2010, 2012), Fujino et al. (2008) and Gomi
et al (2010a, 2010b), we propose a methodology for designing a target vision for future technologies and/or
socioeconomic conditions towards the realization of an
LCS and a methodology for designing both qualitativeand quantitative roadmaps with consistency based on thattarget vision.

2. Prerequisites for Designing a Roadmap by
Backcasting Approach: Depicting Future
LCS Visions
Before designing a roadmap, a backcasting approachrequires creation of a target vision of what is to be realized or avoided. The vision is described as consistently as
possible in both a qualitative and quantitative manner,
but it does not always have to satisfy certain optimization
criteria such as cost minimization or CO2 minimization.
LCS visions have been studied for several Asian countries at the national and sub-national levels. For example,
Fujino et al. (2008) examined quantitative LCS visions inJapan, which aims to achieve a 70% reduction of CO2
emissions by 2050; Gomi et al. (2010a, 2010b) designed
LCS visions for the Japanese city of Kyoto; and Shukla
et al. (2010) investigated the possibility of a low-carbon
economy transition in India. National and sub-national
LCS visions have also been studied for other countries,
such as for Bangladesh by Jilani et al. (2011), Bhopal in
India by Deshpande et al. (2011), Iskandar in Malaysia
by Ho et al. (2009), Putrajaya in Malaysia by Ho et al.
(2011), Thailand by Limmeechokchai et al. (2010),
Vietnam by Hoa et al. (2010), Ahmedabad in India by
Shukla et al. (2009), and Jilin in China by Jiang et al.
(2009).

3. Formulation of a Qualitative Roadmap
The formulation of a qualitative roadmap towards an
LCS begins with identification of the necessary elements,
including technologies, policies and socioeconomic
reforms. Then, when and how such elements should be
implemented and what types of measures and policies
will be effective to realize them are discussed (Fig. 1).
3.1 Determination of barriers to the achievement ofa given LCS vision
Socioeconomic reforms for achieving an LCS are noteasy to accomplish. There are many social as well as
technological barriers to be overcome. Such barriers canbe identified through a comparison between the current
situation and the LCS vision. Among the various types ofbarriers that can be cited are initiation barriers; limits on
the dissemination speed; and physical, social and technological limits. Taking the installation of photovoltaic(PV) systems in houses as an example, the initiation
barrier is the installation cost; the limits on the dissemination speed are the supply capacity of PV manufacturers and the number of workers for construction; andthe physical, social and technological limits include roof
areas, frame strengths of houses, climate conditions,consumer preferences for energy-efficient appliances andlifestyle behavioural changes. Strategies for overcoming
these barriers, therefore, could accelerate transition to
LCS visions.
A lack of technological progress can also become abarrier to the realization of an LCS vision. For example,
Fujino et al. (2008) reported that, in order for Japan toMethodology for Designing LCS Roadmaps using a Backcasting Approach

101

Fig. 1 Identification of the elements of a roadmap (modified from 2050 Japan Low-Carbon Society
Scenario Team (2008)).

achieve a 70% reduction in CO2 emissions by 2050, thecoefficient of performance (COP) of household air
conditioners would need to improve to COP 8 on a stockbasis. In 2007, the COP for household air conditioners on
a stock basis was 4.26 for heating and 3.85 for cooling(Energy Conservation Center Japan, 2011). Technological advances to double these figures will be needed inorder to achieve the required performance by 2050.
In order to formulate strategies for an LCS, two types
of key information should be included: the sequential
order and timing of implementation of each strategy. The
strategies should be executed in the proper sequence;
actions to overcome barriers cannot be taken spontaneously. Before implementing the strategies, public acceptance must be gained in many cases, and without public
acceptance, the strategies will not become rooted insociety. The timing of implementation also needs to beconsidered when formulating strategies for removing
barriers. Some options (technologies and policies) can be
introduced and implemented immediately, such as theestablishment of institutional systems, while others may
take several years and/or decades, such as the construction of well-insulated houses and railroad systems. Technologies also require time for deployment, except forsome examples such as a fuel shift to imported biofuels
and co-firing of woody biomass in coal-fired power
plants. Dissemination may also require from several
years to several decades. Infrastructure such as roads,
railways, power plants and buildings takes a long time tointroduce and/or replace, and such infrastructure built
now will continue to be used through 2050. If newly built
infrastructure is not low-carbon, a part of future society
will remain high-carbon. This situation is called the“lock-in effect.” Therefore, it is important to draw astrategy for a transition to a low-carbon society, considering time for implementation and dissemination while
avoiding lock-in effects.
3.2 Development of strategies including policies,
technologies, and social reforms for overcoming
identified barriers
Many options (technologies and policies) cannot
begin to be introduced (or are infeasible) unless otheroptions are introduced or established before them. These
preliminary options are referred to as prerequisite options.
For example, electricity supply stations must be established and popularized before electric vehicles become
widespread; otherwise, electric vehicles will not be able
to be recharged at locations distant from their garage. As
another example, two conditions must be satisfied before
the diffusion of well-insulated houses suited to local
climate conditions can be achieved to minimize energy
consumption. One is that the current insulation standards
must be replaced by new standards with detailed regionalclassifications that make adjustments possible to match
each area’s climate conditions. The other is the construction of a third-party assessment system to assess theinsulation performance of houses.
Even for the same technology, there are several steps
involved in achieving the technological performancerequired in an LCS vision. Taking the example of air
conditioners again, an air conditioner with a COP of 8 isunlikely to enter the market immediately following
models with a COP of 4.26/3.85; rather, air conditioners
with a gradual improvement in efficiency of COP 6 and
COP 7 will first appear in the market, and COP 8 air
conditioners will then be introduced in the market as aconsequence of their success.

102

S. ASHINA and J. FUJINO

3.3 Seeking sequential combinations in
the implementation of each strategy
Technologies and policies undertaken in a particularsector for achieving an LCS not only affect that sector but
also promote carbon reduction in other sectors. For
example, well-insulated houses and buildings and thedissemination of solar energy systems are direct andeffective low-carbonizing options for the residential andcommercial sectors. Low-carbon options implemented
by energy suppliers, especially electricity suppliers, suchas increased use of renewables for power generation, mayalso contribute to the reduction of CO2 emissions ofbuildings. On the other hand, to expand the use of renewables, it is necessary to encourage their use in
end-use sectors including the industrial, residential,commercial and transport sectors. Widespread publicity
and environmental education also underpin all measures.
In addition to these examples, there are various technological and social barriers to achieving reduction goals,
and time is required to remove all of these barriers.
Proper steps must therefore be taken in due sequence. An
action denotes a set of technological measures, social
system reform programs and stimulatory policies that are
combined appropriately by also considering mutual relationships.

The 2050 Japan Low-Carbon Society Scenario Team(2008) has proposed the following twelve actions forrealizing an LCS in Japan: (1) comfortable and greenbuilt environment; (2) anytime, anywhere appropriate
appliances; (3) promoting seasonal local food; (4)sustainable building materials; (5) environmentallyenlightened business and industry; (6) swift and smoothlogistics; (7) pedestrian- friendly city design; (8) lowcarbon electricity; (9) local renewable resources for local
demand; (10) next- generation fuels; (11) labelling toencourage smart and rational choices; and (12) lowcarbon society leadership. The principal target fields ofthe actions are the residential and commercial sectors (1and 2), agriculture and forestry (3 and 4), industry (5),transport (6 and 7) and energy (8, 9 and 10). Actions 11
and 12 are cross-sectional actions.
Each action consists of three parts: (1) future objectives, (2) identifying implementation barriers andstrategic steps, and (3) procedure of actions. ‘Futureobjectives’ describes the social systems desired in 2050.
Concrete figures for the targets, such as CO2 emissions,
technological levels and penetration levels, are indicatedquantitatively as much as possible. ‘Identifying implementation barriers and strategic steps’ sets forth whichbarriers need to be overcome and the strategic steps forFig. 2 Example of the components of an action (Action 1) (modified from 2050 Japan Low-Carbon
Society Scenario Team (2008)).

Methodology for Designing LCS Roadmaps using a Backcasting Approachremoving them, including approaches, technologies andpolicies. ‘Procedure of actions’ incorporates elements ofboth (1) and (2) with a timeline in the form of a Gantt
chart. The Gantt chart shows timing and periods for eachaction in a bar chart format. Various actions, technologies,
and policies for overcoming the barriers, and theirimplementation orders and timings to achieve the goals,
are denoted in this part. Figure 2 shows the componentsof Action 1 as an example.

4. Design of a Quantitative Roadmap usinga Backcasting Model
A quantitative roadmap needs to satisfy several
conditions and/or certain constraints need to be followed,
such as maintaining the feasibility of the target vision (asmentioned in Section 2), mutual relationships between
options (as mentioned in Section 3), limitations on
costs/investments, CO2 emission reduction targets in theinterim years, and so on. A computer simulation model isuseful for formulating a roadmap quantitatively under
given conditions and constraints while satisfying certain
criteria, such as minimizing costs.
The AIM/Backcasting Model (AIM/BCM), developed by Ashina et al. (2010, 2012), is a simulation modelthat can evaluate possible options (technologies andpolicies) from which to choose and possible timings forinvesting in them, in order to achieve a target vision in
the future at a minimized total cost. Mixed integer programming is used for formulation and the CPLEX solver
with the General Algebraic Modeling System (GAMS) is
used for deriving the optimal solution.
The AIM/BCM model has two characteristics: inclusion of endogenous learning-by-doing effects, andmodelling of technology innovation and market penetration processes.
Technologies in general have a learning-by-doing
effect. This effect can be seen in the reduction in cost that
accompanies the expanding introduction of a technology.
The learning rate of PV systems, for example, is estimated to be about 80% (EPIA, 2009). Various othertechnologies, both in end-use and energy-supply sectors,
also have learning-by-doing effects, as reported by
McDonald and Schrattenholzer (2001). In designing aroadmap, the fixed costs of low-carbon technologies are
assumed to decrease as the cumulative level of introduction increases (i.e., as learning progresses). The AIM/BCM has built-in parameters for performance improvements due to future technical innovations and thelearning-by-doing effects gained as the cumulative levelof introduction increases.
Technology innovation and market penetration processes occur through public and/or private funding ofresearch and development activities as well as the support of consumers (including companies) through themarket. Although innovative technologies can be successfully launched in the market with such support and/or
policies, if consumers do not choose them, it becomesless certain whether subsequent technological innova-

103

tions will take place and whether even more innovativetechnologies will be able to appear in the market. Using
the AIM/Backcasting Model, an analysis was conductedwith the condition that, if the current best available technology (BAT) does not acquire a certain degree of market
share, the future BAT will not be introduced in the market.
Moreover, there is not necessarily only one future BAT.
4.1 Development of quantitative data for eachtechnology and policy
Before evaluation by AIM/BCM, quantitative data foreach technology and policy need to be collected andestablished. The data include technological characteristics, such as initial stock, equipment usage rate and efficiency, period of time needed for introduction both oftechnologies and policies, and outlay needed for introduction. In the Japan LCS roadmap study by Ashina et al.
(2010, 2012), a total of about 600 technologies and policies were evaluated, then the necessary implementation
period for and cost of each option were estimated basedon the literature, expert judgments and market surveys.
4.2 Investigation and selection of which technologies
and policies to introduce, and when and at what
intensity, using the backcasting model based on
certain criteria
In AIM/BCM, the socioeconomic conditions, energybalance and technology composition in both the baseline
year and target year are given. The baseline year can be
set arbitrarily. The energy consumption, industrial structure and composition of CO2 emissions for the base year
and target year are needed for the estimation and should
be obtained using other models or tools before carryingout the analysis with AIM/BCM. In order to achieve thetarget vision, the model seeks to identify the types oftechnology that must be introduced and when and at what
intensity they should be introduced, while satisfying
energy service demands. The volume of activity in eachsector in the interim years is established taking into account social changes, changes in population compositionand other factors in each scenario, and is provided as an
exogenous condition. However, energy consumption, thecomposition of technologies and CO2 emission pathways
in the interim years are estimated endogenously throughoptimization by minimizing the sum of total costs during
the period being analyzed. Compared with some bottom-up-type models such as AIM/Enduse (Kainuma
et al., 2003), which employ a recursive dynamic optimization, the AIM/Backcasting Model as well as the backcasting approach itself is based on simultaneous optimization
during the analyzed period.
By using AIM/BCM, pathways for achieving the target vision while satisfying service demands can bevisualized with the objective function of minimizing total
costs during the period. Pathways include CO2 emissions,primary and secondary energy composition, the electricity generation mix, technology diffusion in each sector
and additional investment. The model also shows thescheduling for the introduction of the assumed options,

104

S. ASHINA and J. FUJINO

organized in the form of a Gantt chart.
Examples of results obtained by the Japan LCS roadmap study conducted by Ashina et al. (2010) are shownin Figs. 3 to 5. Figure 3 shows CO2 emission pathways
towards a 70% reduction by 2050. Scenarios A and B
denote an assumed target vision for reducing CO2 emissions by 70% in 2050 compared with the 1990 level. It
can be seen that when no CO2 reduction goal is established, the estimated CO2 emissions peak in 2020 andthen begin to decrease due to changes in the industrial
structure and number of households; while in contrast,
when the CO2 target for 2050 is set at 70% lower than the1990 level, the pathways to reach this target in Scenarios
A and B are quite similar, and the introduction of measures begins as early as 2010.
Figure 4 shows changes in additional investments
under Scenario A. The implication here is that, in order toachieve an LCS in Japan by 2050, taking early action
requires an additional investment of about 5 trillion JPY
annually at the initial stage, even when reduced fuel costs

are modelled in. The necessary additional fixed costs in2010 are 2.5 trillion JPY in the residential and commercial sectors and 2.5 trillion JPY in the transport sector.
Thereafter, the additional fixed costs in the transport
sector fall sharply as a consequence of learning-by-doing
effects and reductions in the demand for transport services due to changes in the structure of cities.
Figure 5 summarizes the results as a Gantt chart. Theenergy-efficient household appliances mentioned in the
figure are analyzed by preparing data for specific technologies separately, such as air conditioners and kerosene
heaters. The figure summarizes them together, however,as the analysis results for the technologies are similar.
Through this process, the order of priority for each action
and/or strategy can be clarified. This information becomes useful when stakeholders formulate a plan in linewith the actions and/or strategies for achieving an LCS.
Stakeholders do not spend their capacity at once; forexample, citizens usually do not replace all of theirappliances such as air-conditioners, TV sets and refrig-

Fig. 3 CO2 emission pathways towards a 70% reduction by 2050
(modified from Ashina et al., 2010).

Fig. 4 Changes in additional investments for achieving an LCS (Scenario A)(modified from Ashina et al., 2010).

Methodology for Designing LCS Roadmaps using a Backcasting Approach

Fig. 5 Gantt chart of options towards a 70% reduction of CO2 emissions in Japan(modified from Ashina et al., 2010).

105

106

S. ASHINA and J. FUJINO

erators. As another example, the number of government
personnel is generally limited and this constrains theestablishment of institutional systems and/or laws withina given year. Thus, information on the priorities of actions and strategies is useful to stakeholders in the
preparation of their strategies to meet the long-termtarget of an LCS.

5. Summary
The shift to a low-carbon society needs a large-scaletransformation of technologies, policies, infrastructures
and the entire socioeconomic system, such as through thewidespread dissemination of super-insulated houses,
installation of home energy management systems(HEMS) and building energy management systems(BEMS), popularization of LED lighting, creation ofcompact and pedestrian-friendly cities, and so on. Suchtransformation sometimes requires countries and cities,
especially in the case of developing countries, to review
and restructure their current development plans on abroad scale from a zero basis.
This paper proposes a methodology for designing aquantitative roadmap based on a backcasting approachand demonstrates its effectiveness through its application
to Japan. The challenges towards achieving an LCS include not only short- to medium-term targets, such as thetargets set forth in the Kyoto Protocol and mid-term targets for CO2 emissions, but also long-term and broadranging stakeholders’ actions. Stakeholders include
governments and the energy industry as well as citizens
and the overall industrial sector. In order to stimulate
appropriate action with the proper timing by all stakeholders, a well-organized strategy is needed. A roadmap
is an important guideline for leading stakeholder’sactions, and we believe that an effective roadmap can be
designed by using the methodology proposed here.

Acknowledgements
This study was conducted through a grant from theEnvironment Research and Technology Development
Fund (S-6) of the Ministry of the Environment, Japan.
References
2050 Japan Low-Carbon Society Scenario Team (2008) Japan
Scenarios and Actions towards Low-Carbon Societies.
<http://2050.nies.go.jp/report/file/lcs_japan/2050_LCS_Scenari
os_Actions_English_080715.pdf>
Aki, H., T. Oyama and K. Tsuji (2006) Analysis of energy service
systems in urban areas and their CO2 mitigations and economic
impacts. Applied Energy, 83: 1076-1088.
Akimoto, K., T. Tomoda, Y. Fujii and K. Yamaji (2004) Assessment of global warming mitigation options with integrated
assessment model DNE21. Energy Economics, 26: 635-653.
Ashina, S., J. Fujino, T. Masui, T. Ehara and G. Hibino (2012) A
roadmap towards a low-carbon society in Japan using backcasting methodology: Feasible pathways for achieving an 80%
reduction in CO2 emissions by 2050. Energy Policy, 41:584-598.
Ashina, S., J. Fujino, T. Masui, K., Fujiwara, G. Hibino, M.
Kainuma and Y. Matsuoka (2010) Japan roadmaps toward
low-carbon society by backcasting: Optimal CO2 reduction
pathways and investment timing for low-carbon technologies.
Journal of Renewable and Sustainable Energy, 2: 031001031017.
Calvin, K., P. Patel, A. Fawcett, L. Clarke, K. Fisher-Vanden, J.
Edmonds, S.H. Kim, R. Sands and M. Wise (2009) The
distribution and magnitude of emissions mitigation costs in climate stabilization under less than perfect international cooperation: SGM results. Energy Economics, 31: S187-S197.
Chen, Q., C. Kang, Q. Xia and D. Guan (2011) Preliminary
exploration on low-carbon technology roadmap of China’s
power sector. Energy, 36: 1500-1512.
Dagoumas, A.S. and T.S. Barker (2010) Pathways to a low-carbon
economy for the UK with the macro-econometric E3MG model.
Energy Policy, 38: 3067-3077.
Deshpande, A., M. Kapshe, S. Mitra and K. Puntambekar (2011)
Low-Carbon Society Scenario Bhopal 2035. Retrieved from<http://2050.nies.go.jp/report/file/lcs_asialocal/Bhopal.pdf>.
Ekholm, T., S. Soimakallio, S. Moltmann, N. Hohne, S. Syri and I.
Savolainen (2010) Effort sharing in ambitious, global climatechange mitigation scenarios. Energy Policy, 38: 1797-1810.
Energy Conservation Center Japan (2011) Residential Energy
Statistics Yearbook 2010.
European Photovoltaic Industry Association (EPIA) (2009) Set for2020 Solar Photovoltaic Electricity: A Mainstream Power
Source to Europe by 2020.
Fujino, J., G. Hibino, T. Ehara, Y. Matsuoka, T. Masui and M.
Kainuma (2008) Back-casting analysis for 70% emission
reduction in Japan by 2050. Climate Policy, 8: S108-S124.
Gomi, K., Y. Ochi and Y. Matsuoka (2010a) A concrete roadmap
toward a low-carbon society in case of Kyoto City. Journal of
Renewable and Sustainable Energy, 2: 031004.
Gomi, K., K. Shimada and Y. Matsuoka (2010b) A low-carbon
scenario creation method for a local-scale economy and its
application in Kyoto city. Energy Policy, 38: 4783-4796.
Gurney, A., H. Ahammad and M. Ford (2009) The economics ofgreenhouse gas mitigation: Insights from illustrative global
abatement scenarios modeling. Energy Economics, 31: S174S186.
Ho, C.S., A.Z. Abidin, O. Hashim, A.A. Termizi, Y. Matsuoka, T.
Fujiwara, G. Kurata and J. Fujino (2011) Putrajaya Green City
2025. Retrieved from <http://2050.nies.go.jp/report/file/lcs_
asialocal/Putrajaya_2012.pdf>.
Ho, C.S., S. Ahmad, M.Z.S.M. Hussein, L/W. Chau, Y., Matsuoka,
G. Kurata, T. Fujiwara, K. Shimada, K. Gomi, K. Yoshimoto and
J.J. Simson (2009) Low-Carbon City 2025: Sustainable
Iskandar Malaysia.
<http://2050.nies.go.jp/report/file/lcs_asialocal/iskandarlcs.pdf>
Hoa, N.T., K. Gomi, Y. Matsuoka, T.T. Tu, J. Fujino, M. Kainuma
and R.M. Shrestha (2010) Preliminary Study on Sustainable
Low-Carbon Development towards 2030 in Vietnam.
<http://2050.nies.go.jp/report/file/lcs_asia/Vietnam_Brochure_20100415.pdf>
Jiang. K., X. Zhuang and X. Hu (2009) Scenario Analysis on
Low-Carbon Economy Development of Jilin City. Retrieved
from <http://2050.nies.go.jp/report/file/lcs_asialocal/Jilin.pdf>.
Jilani, T., K. Gomi and Y. Matsuoka (2011) Low-Carbon Society
Development towards 2025 in Bangladesh. Retrieved from<http://2050.nies.go.jp/report/file/lcs_asia/Bangladesh_2012.pdf>
Kainuma, M., Y. Matsuoka and T. Morita, eds. (2003) Climate
Policy Assessment: Asia-Pacific Integrated Modeling. Tokyo,
Springer-Verlag.
Kannan, R. (2009) Uncertainties in key low-carbon power generation technologies – Implication for UK decarbonization targets.
Applied Energy, 86: 1873-1886.
Limmeechokchai, B., S. Chungpaibulpatana, R. Nitisoravut, P.

Methodology for Designing LCS Roadmaps using a Backcasting Approach
Winyuchakrit, A. Pattanapongchai, R.M. Shrestha, S. Pradhan,
M. Kainuma, T. Masui, J. Fujino, S. Ashina, M. Matsuoka, K.
Gomi, G. Hibino and T. Ehara (2010) Low-Carbon Society
Vision 2030 Thailand. Retrieved from <http://2050.nies.go.jp/
report/file/lcs_asia/Thailand.pdf>.
McDonald, A. and L. Schrattenholzer (2001) Learning rates forenergy technologies. Energy Policy, 29(4): 255-261.
Pugh, G., L. Clarke, R. Marlay, P. Kyle, M. Wise, H. McJeon and G.
Chan (2011) Energy R&D portfolio analysis based on climatechange mitigation. Energy Economics, 33: 634-643.
Shukla, P.R., S. Dhar and J Fujino (2010) Renewable energy andlow-carbon economy transition in India. Journal of Sustainable
Energy, 2: 031005.
Shukla, P.R., P. Pangotra, A.M. Bazaz, P. Agarwal, N. Agarwal, Y.
Matsuoka, K. Gomi, T. Ehara, K. Fujiwara, M. Kainuma and J.
Fujino (2009) Low-Carbon Society Vision 2035: Ahmedabad.
Retrieved from <http://2050.nies.go.jp/report/file/lcs_asialocal/
ahmedabad_2010.pdf>.
Syri, S., A. Lehtila, T. Ekholm, I. Savolainen, H. Holttinen and E.
Peltola (2008) Global energy and emissions scenarios for effective climate change mitigation–Deterministic and stochastic
scenarios with the TIAM model. International Journal ofGreenhouse Gas Control, 2: 274-285.
Wu Z., J. He, A. Zhang, Q. Xu, S. Zhang and J. Sathaye (1994) A
macro-assessment of technology options for CO2 mitigation in
China’s energy system. Energy Policy, 22(11): 907-913.

107

Shuichi ASHINA
Shuichi ASHINA has been a researcher in the
Sustainable Society System Section, Center forSocial and Environmental Systems Research,
National Institute for Environmental Studies fromthe year 2009. His research focuses on the field ofenergy-economy-environmental system modelingand its application to designing Asian low-carbon
societies. He received his B.S., M.S. and Ph.D. degrees in Mechanical andSystem Engineering from Tohoku University.

Junichi FUJINO
Junichi FUJINO is a Senior Researcher at NIES,
Japan, in the Sustainable Social Systems Section,
Center for Social and Environmental Systems
Research. He is also a Visiting Associate Professor
at the Japan Advanced Institute of Science andTechnology (JAIST). His fields of research include environmental modeling analysis, especiallyfor energy-economy system modeling and bioenergy studies. He is
involved in the development of the Asia-Pacific Integrated Model (AIM) toestimate climate change impact and to assess policy options for stabilizing
the global climate. He has been fully engaged in the “Japan Low-Carbon
Society Scenario Project” since 2004 and the “Asia Low-Carbon Society
Scenario Project” since 2009. He received his B.S., M.S and Ph.D. inElectrical Engineering from the University of Tokyo, Japan. He has beenworking in his current position since April 2000.

(Received 31 May 2012, Accepted 16 January 2013)