Methodology for Designing Quantitative Roadmaps towards

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Global Environmental Research ©2013 AIRIES 17/2013: 99-107 printed in Japan

Methodology for Designing Quantitative Roadmaps towards

Low-Carbon Societies using a Backcasting Approach

Shuichi ASHINA* and Junichi FUJINO

National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba 305-8506, Japan

*e-mail: [email protected]

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 (tech-nologies 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 condi-tions. In this paper, we propose a methodology to create quantitative roadmaps towards a low-carbon society in 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 established in 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 a

quantitative roadmap based on a low-carbon society (LCS) vision in a target year, and demonstrates its effec-tiveness through its application to Japan. The methodol-ogy consists of two main steps: (1) formulation of a qualitative roadmap, and (2) design of a quantitative roadmap using a backcasting model. The first step, formulation of a qualitative roadmap, consists of three stages: (i) determination of the barriers to achieving a given LCS vision; (ii) development of strategies includ-ing policies, technologies and social reforms for over-coming these barriers; and (iii) identification of sequen-tial combinations in the implementation of each strategy. The second step, design of a quantitative roadmap using a backcasting model, consists of two stages: (i) develop-ment of quantitative data for each of the technologies and policies, and (ii) investigation and selection of technolo-gies 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 designing a future roadmap; namely, forecasting and backcasting. A

forecasting approach describes a future roadmap by extending the situation of current socioeconomic condi-tions. Such a roadmap may include the effects of future changes in technology levels, industrial structures and socioeconomic transitions, as well as proposed actions that aim to improve the current situation, such as CO2 mitigation actions. In the backcasting approach, on the other 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 can be explained as a consequence of the present situation, but, without any appropriate additional constraints, such a roadmap does not provide assurance that the target future vision can be achieved. In contrast, the backcast-ing 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 of roadmap is strictly bound by the given target vision and conditions, and does not facilitate discussions as to whether or not the vision and the roadmap provide the optimal solutions. These approaches are therefore com-plementary to each other, and it can be useful to discuss the feasibility of a designed roadmap by means of the

100 S. ASHINA and J. FUJINO

forecasting approach. Both steps of the methodology should be carried out repeatedly in order to design quali-tative and quantitative roadmaps with consistency.

In the past, various studies have been conducted to analyze 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 general equilibrium (CGE) Model. They also investigated carbon leakage of the industrial sector and concluded that delayed 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 and regional 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 electric-ity 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 their emphasis on regional impacts of GHG mitigation actions on GHG pathways and economic and energy transitions. These studies reported impacts on the energy mix and economic activities as a consequence of imposing CO2 emission targets. Some studies have proposed method-ologies 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 road-maps in these past studies are described as changes in energy and/or technology compositions, Ashina et al. (2010, 2012) drew up future roadmaps not only for tech-nologies 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 de-signing a target vision for future technologies and/or socioeconomic conditions towards the realization of an LCS and a methodology for designing both qualitative and quantitative roadmaps with consistency based on that target vision.

2. Prerequisites for Designing a Roadmap by Backcasting Approach: Depicting Future LCS Visions Before designing a roadmap, a backcasting approach

requires creation of a target vision of what is to be real-ized 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 coun-tries at the national and sub-national levels. For example, Fujino et al. (2008) examined quantitative LCS visions in Japan, 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 of

a given LCS vision Socioeconomic reforms for achieving an LCS are not

easy to accomplish. There are many social as well as technological barriers to be overcome. Such barriers can be identified through a comparison between the current situation and the LCS vision. Among the various types of barriers that can be cited are initiation barriers; limits on the dissemination speed; and physical, social and tech-nological limits. Taking the installation of photovoltaic (PV) systems in houses as an example, the initiation barrier is the installation cost; the limits on the dis-semination speed are the supply capacity of PV manu-facturers and the number of workers for construction; and the physical, social and technological limits include roof areas, frame strengths of houses, climate conditions, consumer preferences for energy-efficient appliances and lifestyle behavioural changes. Strategies for overcoming these barriers, therefore, could accelerate transition to LCS visions.

A lack of technological progress can also become a barrier 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

achieve a 70% reduction in CO2 emissions by 2050, the coefficient of performance (COP) of household air conditioners would need to improve to COP 8 on a stock basis. 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). Technologi-cal advances to double these figures will be needed in order 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 spontane-ously. Before implementing the strategies, public accep-tance must be gained in many cases, and without public acceptance, the strategies will not become rooted in society. The timing of implementation also needs to be considered when formulating strategies for removing barriers. Some options (technologies and policies) can be introduced and implemented immediately, such as the establishment of institutional systems, while others may take several years and/or decades, such as the construc-tion of well-insulated houses and railroad systems. Tech-nologies also require time for deployment, except for some 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 to introduce 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 a

strategy for a transition to a low-carbon society, consid-ering 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 other options are introduced or established before them. These preliminary options are referred to as prerequisite options. For example, electricity supply stations must be estab-lished 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 regional classifications that make adjustments possible to match each area’s climate conditions. The other is the construc-tion of a third-party assessment system to assess the insulation performance of houses.

Even for the same technology, there are several steps involved in achieving the technological performance required in an LCS vision. Taking the example of air conditioners again, an air conditioner with a COP of 8 is unlikely 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 a consequence of their success.

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

Scenario Team (2008)).


3.3 Seeking sequential combinations in the implementation of each strategy

Technologies and policies undertaken in a particular sector 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 the dissemination of solar energy systems are direct and effective low-carbonizing options for the residential and commercial sectors. Low-carbon options implemented by energy suppliers, especially electricity suppliers, such as increased use of renewables for power generation, may also contribute to the reduction of CO2 emissions of buildings. On the other hand, to expand the use of re-newables, 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 techno-logical 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 rela-tionships.

The 2050 Japan Low-Carbon Society Scenario Team (2008) has proposed the following twelve actions for realizing an LCS in Japan: (1) comfortable and green- built environment; (2) anytime, anywhere appropriate appliances; (3) promoting seasonal local food; (4) sustainable building materials; (5) environmentally enlightened business and industry; (6) swift and smooth logistics; (7) pedestrian- friendly city design; (8) low- carbon electricity; (9) local renewable resources for local demand; (10) next- generation fuels; (11) labelling to encourage smart and rational choices; and (12) low- carbon society leadership. The principal target fields of the actions are the residential and commercial sectors (1 and 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 objec-tives, (2) identifying implementation barriers and strategic steps, and (3) procedure of actions. ‘Future objectives’ describes the social systems desired in 2050. Concrete figures for the targets, such as CO2 emissions, technological levels and penetration levels, are indicated quantitatively as much as possible. ‘Identifying imple-mentation barriers and strategic steps’ sets forth which barriers need to be overcome and the strategic steps for

Fig. 2 Example of the components of an action (Action 1) (modified from 2050 Japan Low-Carbon

Society Scenario Team (2008)).


removing them, including approaches, technologies and policies. ‘Procedure of actions’ incorporates elements of both (1) and (2) with a timeline in the form of a Gantt chart. The Gantt chart shows timing and periods for each action in a bar chart format. Various actions, technologies, and policies for overcoming the barriers, and their implementation orders and timings to achieve the goals, are denoted in this part. Figure 2 shows the components of Action 1 as an example.

4. Design of a Quantitative Roadmap using

a 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 (as mentioned in Section 2), mutual relationships between options (as mentioned in Section 3), limitations on costs/investments, CO2 emission reduction targets in the interim years, and so on. A computer simulation model is useful for formulating a roadmap quantitatively under given conditions and constraints while satisfying certain criteria, such as minimizing costs.

The AIM/Backcasting Model (AIM/BCM), devel-oped by Ashina et al. (2010, 2012), is a simulation model that can evaluate possible options (technologies and policies) from which to choose and possible timings for investing in them, in order to achieve a target vision in the future at a minimized total cost. Mixed integer pro-gramming 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: inclu-sion of endogenous learning-by-doing effects, and modelling of technology innovation and market penetra-tion 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 esti-mated to be about 80% (EPIA, 2009). Various other technologies, both in end-use and energy-supply sectors, also have learning-by-doing effects, as reported by McDonald and Schrattenholzer (2001). In designing a roadmap, the fixed costs of low-carbon technologies are assumed to decrease as the cumulative level of introduc-tion increases (i.e., as learning progresses). The AIM/ BCM has built-in parameters for performance improve-ments due to future technical innovations and the learning-by-doing effects gained as the cumulative level of introduction increases.

Technology innovation and market penetration proc-esses occur through public and/or private funding of research and development activities as well as the sup-port of consumers (including companies) through the market. Although innovative technologies can be suc-cessfully launched in the market with such support and/or policies, if consumers do not choose them, it becomes less certain whether subsequent technological innova-

tions will take place and whether even more innovative technologies will be able to appear in the market. Using the AIM/Backcasting Model, an analysis was conducted with the condition that, if the current best available tech-nology (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 each

technology and policy Before evaluation by AIM/BCM, quantitative data for

each technology and policy need to be collected and established. The data include technological characteris-tics, such as initial stock, equipment usage rate and effi-ciency, period of time needed for introduction both of technologies and policies, and outlay needed for intro-duction. In the Japan LCS roadmap study by Ashina et al. (2010, 2012), a total of about 600 technologies and poli-cies were evaluated, then the necessary implementation period for and cost of each option were estimated based on 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, energy balance and technology composition in both the baseline year and target year are given. The baseline year can be set arbitrarily. The energy consumption, industrial struc-ture 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 carrying out the analysis with AIM/BCM. In order to achieve the target vision, the model seeks to identify the types of technology that must be introduced and when and at what intensity they should be introduced, while satisfying energy service demands. The volume of activity in each sector in the interim years is established taking into ac-count social changes, changes in population composition and other factors in each scenario, and is provided as an exogenous condition. However, energy consumption, the composition of technologies and CO2 emission pathways in the interim years are estimated endogenously through optimization by minimizing the sum of total costs during the period being analyzed. Compared with some bot-tom-up-type models such as AIM/Enduse (Kainuma et al., 2003), which employ a recursive dynamic optimiza-tion, the AIM/Backcasting Model as well as the backcast-ing approach itself is based on simultaneous optimization during the analyzed period.

By using AIM/BCM, pathways for achieving the tar-get vision while satisfying service demands can be visualized with the objective function of minimizing total costs during the period. Pathways include CO2 emissions, primary and secondary energy composition, the electric-ity generation mix, technology diffusion in each sector and additional investment. The model also shows the scheduling for the introduction of the assumed options,


organized in the form of a Gantt chart. Examples of results obtained by the Japan LCS road-

map study conducted by Ashina et al. (2010) are shown in 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 emis-sions by 70% in 2050 compared with the 1990 level. It can be seen that when no CO2 reduction goal is estab-lished, the estimated CO2 emissions peak in 2020 and then 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 the 1990 level, the pathways to reach this target in Scenarios A and B are quite similar, and the introduction of meas-ures begins as early as 2010.

Figure 4 shows changes in additional investments under Scenario A. The implication here is that, in order to achieve 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 in 2010 are 2.5 trillion JPY in the residential and commer-cial 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 ser-vices due to changes in the structure of cities.

Figure 5 summarizes the results as a Gantt chart. The energy-efficient household appliances mentioned in the figure are analyzed by preparing data for specific tech-nologies 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 be-comes useful when stakeholders formulate a plan in line with the actions and/or strategies for achieving an LCS. Stakeholders do not spend their capacity at once; for example, citizens usually do not replace all of their appliances 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).


Fig. 5 Gantt chart of options towards a 70% reduction of CO2 emissions in Japan

(modified from Ashina et al., 2010).


erators. As another example, the number of government personnel is generally limited and this constrains the establishment of institutional systems and/or laws within a given year. Thus, information on the priorities of ac-tions and strategies is useful to stakeholders in the preparation of their strategies to meet the long-term target of an LCS.

5. Summary

The shift to a low-carbon society needs a large-scale

transformation of technologies, policies, infrastructures and the entire socioeconomic system, such as through the widespread dissemination of super-insulated houses, installation of home energy management systems (HEMS) and building energy management systems (BEMS), popularization of LED lighting, creation of compact and pedestrian-friendly cities, and so on. Such transformation sometimes requires countries and cities, especially in the case of developing countries, to review and restructure their current development plans on a broad scale from a zero basis.

This paper proposes a methodology for designing a quantitative roadmap based on a backcasting approach and demonstrates its effectiveness through its application to Japan. The challenges towards achieving an LCS in-clude not only short- to medium-term targets, such as the targets set forth in the Kyoto Protocol and mid-term tar-gets for CO2 emissions, but also long-term and broad- ranging 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 stake-holders, a well-organized strategy is needed. A roadmap is an important guideline for leading stakeholder’s actions, 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 the

Environment Research and Technology Development Fund (S-6) of the Ministry of the Environment, Japan.

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Shuichi ASHINA Shuichi ASHINA has been a researcher in the Sustainable Society System Section, Center for Social and Environmental Systems Research, National Institute for Environmental Studies from the year 2009. His research focuses on the field of energy-economy-environmental system modeling and its application to designing Asian low-carbon

societies. He received his B.S., M.S. and Ph.D. degrees in Mechanical and System 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 and Technology (JAIST). His fields of research in-clude environmental modeling analysis, especially

for energy-economy system modeling and bioenergy studies. He isinvolved in the development of the Asia-Pacific Integrated Model (AIM) to estimate 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. in Electrical Engineering from the University of Tokyo, Japan. He has been working in his current position since April 2000.

(Received 31 May 2012, Accepted 16 January 2013)

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Methodology for Designing Quantitative Roadmaps towards