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Barriers to Energy Efficiency for Residential Space-heating Appliances in Japan

by

Ken-ichiro Nishio, Researcher

Socio-economic Research Center, Central Research Institute of Electric Power Industry (CRIEPI) 2-11-1, Iwado-kita, Komae-shi, Tokyo 201-8511, JAPAN

Phone: +81 3 3480 2111/Fax: +81 3 3480 3492/Email: nishio@criepi.denken.or.jp and

Yumiko Iwafune Institute of Industrial Science (IIS), The University of Tokyo

Abstract

The actual level of market penetration of cost-effective, energy-efficient technologies is often below their optimal level of market penetration; the gap between the actual and optimal levels of market penetration is known as the “energy efficiency gap,” and it arises due to various hindering factors known as “energy efficiency (EE) barriers.” This is particularly true for heat-pump room air-conditioners (RACs), which are an alternative to boilers for use as space-heating appliances. Although several scenarios proposed for the development of a low-carbon society has led to the recognition of the potential of RACs, there have not been many discussions on policies to improve the diffusion of these appliances. The purpose of this study is to conduct a case study on RACs in Japan to determine if EE barriers exist, identify the barriers if they exist, and discuss appropriate measures for the removal of these barriers; the study is based on a questionnaire survey of approximately 2500 consumers. First, we examine the impact of each of the six EE barriers—imperfect information, split incentives, access to capital, bounded rationality, hidden costs, and risks—in discouraging consumers from using RACs; these barriers have been identified on the basis of theoretical investigations by previous studies. Next, CO2 emission reduction potential curves, which show the relationship between the reduction amount and the marginal cost of reduction, are drawn using the questionnaire data and taking the EE barriers into account. The result shows that about two-thirds of the economic CO2 emission reduction potential in residential space heating and cooling possibly becomes unavailable due to the influence of EE barriers. This implies that appropriate measures to remove the EE barriers are as important as the development of cost-effective, energy-efficient technologies. Finally, policy implications for promoting energy-efficient space-heating appliances are discussed.

1. Introduction 1.1 Barriers to energy efficiency The actual level of market penetration of cost-effective, energy-efficient technologies is often below their optimal level of market penetration. It is widely recognized that the market penetration potential of technology depends on the extent to which constraints such as technical, social, economic, and market factors are considered (IPCC, 2001[1], etc.; Figure 1). From an optimistic standpoint, we can consider the theoretical potential on the basis of the assumption that innovative technologies are successfully developed and diffused. The potential decreases with an increase in the number of constraints taken into consideration. It is fairly common for policymakers to refer to the economic potential since this parameter is more relevant to economic activities. However, it is apparent that the actual penetration is often below the market potential due to the absence of appropriate measures. This gap between the ideal and actual levels of market penetration is known as the “energy efficiency gap,” and it is caused by various hindering factors known as “energy efficiency (EE) barriers;” for example, “imperfect information” and “risks” (IEA, 2008[2]; Sorrell et al., 2004[3]; SPRU, 2000[4], etc.). Since a significant decrease in CO2 emissions is realized by maximizing the EE potential, it is vital to take appropriate measures for the removal of EE barriers.

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Socio-economic potentialCost-effective technologies are diffused from the long-term view point.

Theoretical potentialInnovative technologies are successfully developed and diffused.

Market potentialTechnologies are diffused under the current market status.

Technical potentialAssumed technologies are diffused regardless of economics.

Economic potentialCost-effective technologies are diffused from the mid/short-term viewpoint.

Technology diffusion, CO2 reduction, etc.

Energy EfficiencyGap

Energy EfficiencyBarriers

Idea

lImperfect information,

Split incentives,Bounded rationality,Access to capital,

Hidden costs,Risks,Etc.

Figure 1: Diffusion potential and barriers to energy efficiency

A “CO2 emission reduction potential curve,” which shows the relationship between the reduction amount and the marginal cost of the reduction, is widely used to present a broad overview of the various options for reducing CO2 (McKinsey & Company, 2007[5], etc.). As indicated by OECD/IEA (2008) [6] (Figure 2), a most cost-effective measure to reduce CO2 widely known is to promote energy efficiency in residential and commercial sectors (“end-use efficiency”). This implies that even the cost-effective EE potential may remain untouched for some reasons, or the influence of EE barriers. This further justifies the significance of elaborating on EE barriers.

Figure 2: Example of a CO2 emission reduction potential curve

(Source: OECD/IEA, 2008)

1.2 Heat-pump room air-conditioners (RACs) The constraints posed by EE barriers are particularly true for heat-pump room air-conditioners (RACs), which are an alternative to boilers for use as space-heating appliances. (1) Current status of CO2 emissions from space heating In recent years, the annual CO2 emissions from residential space-heating appliances have been approximately 40 Mt-CO2 in Japan; this value corresponds to approximately 20% of the total CO2 emission from residential sector and to approximately 3% of the total CO2 emission in the country. The breakdown of the sources of energy used for space heating in 2006 is as follows: kerosene accounted for 69%; city gas, 16%; electricity, 11%; and liquid propane gas, 4% (EDMC, 2008[7]). (2) Efficiency improvement of RACs In Japan, the efficiency of RACs improved considerably in the late 1990s when considerable research and development (R&D) efforts were made in response to the appliance efficiency standard called the “Top Runner” approacha that was adopted for RACs in 1999. The average coefficient of performance (COP) of appliance stocks improved from below 3 in the mid-1990s to 4.26 in 2007 (Figure 3; Jyukankyo Research Institute, 2009[8]). As to the efficiency of market flow, many models sold in 2008 showed an annual performance factor (APF) of over 6, which corresponds to a total primary energy efficiency of over 200% even after taking the

a See the website of EECJ (The Energy Conservation Center, Japan), e.g., http://www.eccj.or.jp/index_e.html, http://www.eccj.or.jp/top_runner/index.html.

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conversion efficiency of electricity into consideration. This provides a theoretical background to promote the substitution of conventional combustion boilers with heat pump RACs.

0

1

2

3

4

5

6

1985 1990 1995 2000 2005

Rated efficiency

RAC heating COP(Stocks)

RAC heating COP(Flows; sales base)

(Source：Jyukankyo Research Institute)

"Top Runner" standard(1999‐)

Figure 3: Efficiency of space heating by RACs

Figure 4 compares the energy cost (Japanese Yen, JPYb) per thermal energy unit (megajoule, MJ), which is derived by dividing the residential energy price by the efficiency of each appliance. Before 2000, the most economical method of space heating in terms of the running cost was oil combustion boilers. In recent years, however, space heating using RACs has became cheaper mainly due to the improvement in the efficiency of RACs after the mid-1990s and the oil price hike in recent years. It is to be noted that although the actual energy cost widely varies with climatic conditions and usage style of appliances, this simple comparison implies that the use of RACs is advantageous to consumers too.

01

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1985 1990 1995 2000 2005

Ene

rgy

cost

per

meg

ajou

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Y/M

J）

Electric heater (Efficiency 100%)

Kerosene heating(Est. efficiency 90%)

RAC heating (Stocks*)

City gas heating (Est. efficiency 90%)

LPG heating (Est. efficiency 90%)

RAC heating (Flow*)

*2007 heating COP: Stocks 4.26, Flow 5.35(Source: Jyukankyo Research Institute, etc.)

Figure 4: Comparison of energy costs (cost per megajoule)

(3) RACs in low-carbon society scenarios HPTC (2007) [9] estimates that by promoting the use of RACs, a CO2 emission of 3 Mt-CO2 can be potentially reduced in the domain of residential space heating; by the year 2030, a reduction of 1 Mt-CO2 is expected to be achieved. Electrification is a vital measure to reduce CO2 emissions provided the carbon intensity of power generation is maintained at the current levels; moreover, it would be even more effective in reducing CO2 emissions in the future when the carbon intensity of power generation shall improve (Nishio and Nagano, 2008[10]). In Japan, several mid- and long-term scenarios of CO2 emission reduction have been proposed (METI, 2008[11], etc.), and most of them are based on the assumption that the diffusion of EE technology is successful. In the case of commercialized products such as RACs, the scenarios of CO2 emission reduction are based on ideal assumptions such as “the product is used in all houses,” or “the maximum level of penetration is achieved.” In reality, however, the percentage of households using RAC as the main space-heating appliance is approximately 30%, and many consumers still have a negative impression about its energy-cost-saving potential and performance (HPTC, 2009[12]). In order to achieve a significant decrease in CO2 emissions as proposed in

b 1 JPY (Japanese yen) = approximately 1 US cent, or 0.01 US dollars as of April 2009.

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the scenarios, it is essential to recognize the existence of EE barriers and take appropriate measures for their removal.

1.3 Objectives This study aims to (1) identify the effect of EE barriers on RACs, (2) analyze the impact of EE barriers on the CO2 emission reduction potential in the case of RACs, and (3) identify the policy implications of possible measures to accelerate the EE. In order to empirically take into consideration the complexity and diversity of the consumers’ behavior, a questionnaire survey on the procurement and use of space-heating appliances was conducted. Thus, we aim to maximize the benefits of the methods and implications obtained in previous studies; we also aim to realize the case of RACs in a systematic way. The contents of this paper are as follows: the empirical analysis of EE barriers related to consumers’ choice of space-heating appliances is discussed in Chapter 2, the impact of EE barriers on CO2 emission reduction potential is quantitatively analyzed in Chapter 3, and finally, policy recommendation is discussed in Chapter 4. 2. Identifying energy efficiency barriers involved with the use of RACs This chapter empirically identifies the EE barriers to the use of RACs. A theoretical framework for classifying EE barriers (Section 2.1) is incorporated into the analysis of the results of the questionnaire survey (Section 2.2).

2.1 Classification of EE barriers A number of previous studies attempted to identify EE barriers through various case studies. Table 1 presents an overview of the classification in this study; the classification is based on the framework used by Sorrell et al. (2004). The six barriers are neither completely mutually exclusive c nor collectively exhaustive d ; more importantly, this framework covers the principal EE barriers so that we can systematically understand the EE barriers and discuss measures for their removal.

Table 1: Overview of the energy efficiency barriers associated with the use of RACs

Energy Efficiency Barriers

Examples in case study ofroom air-conditioners in residential sector

Imperfect information Failure to understand which appliance is EE.- Incorrect estimation of energy costs.

Split incentivesMismatch of incentives to promote EE.- Appliances preinstalled by others.- Not accountable for energy bills.

Bounded rationality Limited time, attention, and ability to process information.- Interested in EE, but not proactive.

Access to capital Severe financial conditions.- Budget constraints on initial cost.

Hidden costs Costs other than initial and running costs.- Loss of benefits, etc.

Risks Little information on future prospects.- High discount rate (short pay-back time).

2.2 Empirical analysis of EE barriers We conducted a questionnaire survey of 2534 consumers; this survey, which was conducted in December 2008, dealt with questions on choices of space-heating appliances and their use. In the following section, we empirically analyze the impact of each EE barrier on the basis of the data collected in the survey.

2.2.1 Imperfect information (1) Concept In order to make economically effective decisions, information on current energy use, appliance efficiency, energy price and so force is required. In reality, however, “imperfect information” could lead to missing out on EE opportunities, which could have been implemented with sufficient information (2) Methodology We estimate the percentage of households who do not use RACs due to the impression that the energy costs incurred would increase (condition I) and those who may incorrectly estimate the energy cost (condition II)e. c For example, the impact of “imperfect information” can be interpreted as a part of “hidden costs,” or costs associated with acquiring, understanding, and applying correct information. d For example, a previous paper by Sorrell et al. (SPRU, 2000) covered more than ten barriers. e Without condition II, the result might include those who have a proper understanding of energy costs. Likewise, without condition I, the result might include those who are unwilling to use RACs even if they had a proper understanding of energy costs.

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Condition I: Energy cost as the reason behind appliance choice The questionnaire survey reveals that 74% of those who do not use RACs as the main space-heating appliance choose “using RAC is likely to increase energy cost” as one of the reasons. Condition II: Misunderstanding the energy costs incurred by RACs We estimate the percentage of households wherein there may be a potentially large gap between the respondent’s view of the change in the energy cost upon shifting to RAC and the actual change in the energy cost. First, with regard to the respondent’s view, we asked the following question: “To what extent do you think the energy cost for space heating would change if RAC is used as the main space-heating appliance?” Figure 5 shows that currently, more than 80% of the households who do not use RACs fears an increase in the energy costs incurred.

20%

23%

12%

21%

18%

21%

23%

17%

12%

20%

47%

43%

53%

53%

50%

11%

10%

17%

12%

11%

1%

1%

1%

1%

1%

0% 20% 40% 60% 80% 100%

Object households*(100%)

Kerosene heating(54%)

Gas heating(14%)

Floor heating(5%)

Electric heater(26%)(*

Hou

seho

lds

who

don

't use

R

AC

as

a m

ain

spac

e-he

atin

g ap

plia

nce

in th

eir l

ivin

g ro

om)

Cur

rent

mai

n sp

ace-

heat

ing

appl

ianc

e:More than 2 times About 2 times About 1.5 timesAbout the same About half

To what extent do you think the energy cost for space heating would changeif RAC is used as the main space-heating appliance?:

Figure 5: Change in energy costs as a result of shifting to RACs

Next, we compare the response to the above-mentioned question with the expected change calculated on the basis of energy cost statistics and appliance efficiencyf for 2006. In order to avoid overestimating the gap, we do not consider those who rarely use space-heating appliances. This is because their energy cost could increase to a large extent by shifting from spot heating to space heating, and this increase cannot be considered as a consequence of imperfect information. The comparison reveals that out of the total number of households who do not use RACs as the main space-heating appliance, the percentage of households who potentially misunderstand the energy costs incurred by RACs (condition II) are estimated to be 57%. (3) Result By consolidating condition I and II, it is estimated that 28% of all households may be under the influence of “imperfect information” (Figure 6). The percentage of households using electric heaters is fairly low, whereas the percentage of households using other appliances exceeds 40%.

28%

46%

44%

45%

30%

0% 10% 20% 30% 40% 50%

All households(100%)

Kerosene heating(36%)

Gas heating(9%)

Floor heating(4%)

Electric heater(32%)B

y cu

rrent

mai

n sp

ace-

heat

ing

appl

ianc

e:

Influence of "imperfect information" (% of households)

Figure 6: Influence of “imperfect information”

f The COP of RACs is assumed to be 4 in warm regions and 2 in cold regions on the basis of stock data.

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2.2.2 Split incentives (1) Concept “Split incentives” is the barrier that is encountered when an individual or organization does not have the appropriate incentives to promote EE under some conditions, as outlined in Figure 7 (IEA, 2007[13]; Meier and Eide, 2007[14]). The incentive for promoting EE is expected to be effective only in Case A, wherein the consumer is directly involved in choosing the technology and energy payment. However, Case B may lead to an “efficiency problem” due to the installation of energy-inefficient appliances by individuals (or organizations) who are not accountable for energy bills (e.g., landlords, house sellers). In Case D, although the individuals responsible for installing the appliances would have a reasonable incentive to choose EE technologies, the users may be unaware of the advantages of using these technologies; this is called the “usage problem.” In Case C, wherein the users can choose a technology without worrying about energy bills, an energy-inefficient and inexpensive technology may be chosen for use in an energy-consumptive way; this is termed the “usage and efficiency problem.”

Source: Meier and Eide (2007), etc.

Case A:Proper

incentivefor EE

Case B:Efficiency Problem

Case D:Usage

problem

Case C:Usage and Efficiencyproblem

Can choose technologiesYes No

Pays

ene

rgy

bills

No

Yes

From standpointof energy user:

Figure 7: Mechanism of “split incentives”

(2) Methodology We estimate the percentage of households who are likely to be reluctant in using appliances (other than RACs) chosen by others (condition I), or those who are not accountable for paying variable energy bills (condition II)g. Condition I: Who chooses the appliances? Condition I covers households without RACs in their living rooms; this corresponds to 30% of all households. Figure 8 indicates the installation history of the main space-heating appliances at these households. Two groups are potentially influenced by “split incentives”: 1) in 5.1% of the households, space-heating appliances were “already installed as standard equipment when buying or rebuilding the house,” and 2) in 7.2% of the households, space-heating appliances were “installed in the house before renting it out.” 85% of the former group did not use RACs partly because they want to continue using the already-installed appliances as long as possible, and 65% of the latter group did not procure RACs partly due to issues related to building structures or rental contracts. In total, 2.7% of all the households (30% × 5.1% × 85% + 30% × 7.2% × 65% = 2.7%; condition I) are estimated to continue using pre-installed appliances

g Condition I corresponds to Case B plus D, whereas condition II corresponds to Case C plus D in Figure 7.

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Used in previous residence

(25%)

Already installed as standard

equipment when buying or rebuilding

house(5%)

Purchased as optional

equipment when buying or rebuilding

house(4%)

Installed in house before renting it out

(7%)

Purchased when renting it

out(10%)

Purchased as new appliance

at current residence

(27%)

Purchased as replacement

at current residence

(20%)

Purchased when

remodeling house(1%)

Others(2%)

Installation history of main space-

heating appliances other than RACs

Figure 8: Installation history of main space-heating appliances other than RACs

Condition II: Who pays energy bills? In Japan, where almost all households are accountable for energy payment, approximately 1% of the households (Condition II) are estimated to be under the influence of the “usage problem.” In other words, households who are not accountable for paying energy bills or who are not charged on the basis of actual energy usage comprise only 1% of the total number of households. The percentage of rented houses is relatively high at 3%; it is 16% for company house, official house and dormitory. (3) Result By consolidating condition I and II, it is estimated that 3.1% of all households may be under the influence of “split incentives” (Figure 9). It is notable that rented apartments are the most affected by “split incentives.”

3.1%

2.0%

1.1%

3.3%

4.3%

0% 1% 2% 3% 4% 5%

All households(100%)

Owned, detached house(44%)

Rented, detached house(4%)

Owned, apartment(12%)

Rented, apartment(41%)B

y ow

ners

hip

& b

uild

ing

type

:

Influence of "split incentives" (% of households)

Figure 9: Influence of “split incentives”

2.2.3 Bounded rationality (1) Concept “Bounded rationality” refers to decisions made by individuals or organizations being subject to constraints in terms of time, attention, and the ability to process information; these constraints could lead one to miss out on EE opportunities. From the viewpoint of neoclassical economics, a consumer arrives at a decision to buy or rent a house on the basis of reasonable thinking; in reality, however, misunderstanding information or making compromises is inevitable while making decisions. This is due to the tremendous amount of information that needs to be processed, such as information on budget, building structures, surrounding environment, equipments, and procedures. (2) Methodology It is estimated that 17% of the households without RACs in their living rooms have not procured RAC, although they may be interested in RACs, partly because they are not proactive. (3) Result It is estimated that 5% of all households may be under the influence of “bounded rationality” (Figure 10). It is

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notable that the younger generation is most affected by “bounded rationality.”

5.0%

6.2%

5.2%

4.5%

4.2%

0% 1% 2% 3% 4% 5% 6% 7%

All households(100%)

20s(17%)

30s(37%)

40s(29%)

50s-(16%)

By

resp

onde

nt a

ge:

Influence of "bounded rationality" (% of households)

Figure 10: Influence of “bounded rationality”

2.2.4 Access to capital (1) Concept Limited “access to capital” may prevent households from investing in EE technologies, which usually requires a larger initial investment when compared to that required by conventional technologies. “Access to capital” specifically refers to the budget constraint for investing in EE technologies and is independent of energy-cost-saving potential, while the influence of “risks” (see Section 2.2.6) would weaken as there would be considerable savings in the running costs of EE appliances. (2) Methodology We estimate the percentage of households who cannot afford EE appliances (condition I), and those who have not procured RAC partly due to its high initial cost (condition II)h. Condition I: Cannot afford EE appliances due to financial reasons It is estimated that 60% of the households without RACs in their living rooms find it difficult to invest in EE appliances due to severe financial conditions. Condition II: Not procured RAC due to its high initial cost It is estimated that 55% of the households without RACs in their living rooms have not procured the RACs partly due to its high initial cost. (3) Result The percentage of households under the influence of “access to capital” is estimated to be 3.7%. Figure 11 shows that the lower income segment is most affected by “access to capital.”

3.7%

9.9%

7.1%

2.3%

1.9%

0.6%

0.7%

2.8%

0% 2% 4% 6% 8% 10%

All househods(100%)

< 2 mill. JPY(9%)

2-4 mill JPY(21%)

4-6 mill. JPY(26%)

6-8 mill. JPY(17%)

8-10 mill. JPY(10%)

10 mill. JPY <=(10%)

Not available(6%)By

hous

ehol

d an

nual

inco

me:

Influence of "access to capital" (% of households)

Figure 11: Influence of “access to capital”

h Without condition II, the result might include those who have actually procured EE appliances. Likewise, without condition I, the result might include those who are not seriously influenced by initial costs and actually have a high discount rate as a result of the influence of risks.

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2.2.5 Hidden costs (1) Concept The two main parameters in traditional engineering-economic analyses are initial cost and running cost. Previous studies have revealed that in addition to such apparent parameters, “hidden costs” also exist. SPRU (2000) [4] has divided hidden cost into three categories: general overhead costs, costs specific to technology investment, and loss of benefits. (2) Methodology Since a part of the “hidden costs” is taken into consideration as other EE barriersi, in this section, we focus on loss of benefits, e.g., in terms of comfort, convenience, and portability. In order to obtain accurate results, it would be preferable to take these factors into consideration in the economic analysis as incremental costs; however, since it is difficult to quantify the impact in terms of costs, in this study, they are quantified on the basis of their impact as a decrease in the diffusion potential. The percentage of households who would be unwilling to use RACs even after being aware of the fact that switching to RAC saves running costs is estimated to be 18% of the households who do not use RAC as a main space-heating appliance in their living rooms. It can be inferred that these consumers assume that a large amount of “hidden costs” are associated with loss of benefits. (3) Result The percentage of households under the influence of “hidden costs” is estimated to be 12% of all households (Figure 12). The influence is strongest in Hokkaido, which has the coldest climate.

12%29%

14%11%11%9%12%11%

9%11%

0% 5% 10% 15% 20% 25% 30%

All households(100%)Hokkaido(5%)

Tohoku(7%)Kanto(37%)

Chubu(11%)Hokuriku(4%)Kansai(17%)

Chugoku(6%)Shikoku(3%)Kyushu(11%)

By

regi

on:

Influence of "hidden costs" (% of households)

Figure 12: Influence of “hidden costs”

2.2.6 Risks (1) Concept EE opportunities tend to be neglected by taking decisions on the basis of achieving the short pay-back times (PBTs) or obtaining high discount rates; these decisions are arrived at by considering many “risks” associated with the internal/external environment. In the context of EE, it is important to distinguish between different types of discount rates. Figure 13 presents three cases applicable to discount rates. First, from a long-term standpoint, the environment policy recommends a relatively low social time preference rate of 0% or around. On the basis of this low discount rate, it would be reasonable to promote EE technologies in cases where the PBT is as long as the lifetime of investment. Second, it is well known that an implicit discount rate in the real world is often considerably high. Implicit discount rates depend on technologies (Sanstad et al., 1995[15]), and even among the same kinds of technologies, they depend on the individuals and organizations using the technologies. In the context of EE, it can be inferred that such a high discount rate is a consequence of various EE barriers. Therefore, it is important to remove the EE barriers in order to decrease the discount rate. Third, the public policy recommends a relatively low discount rate of approximately 4–8% (Geller and Attali, 2005[16]) from the standpoint that cost-benefit analyses should be harmonized with ongoing economic activities. In this case, the PBT is required to be little shorter than the lifetime of investment.

i For example, the transaction cost to acquire and process information overlap the impact of “imperfect information.”

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Discount rate induced by appropriate

measures

Discount rateobserved in

actual market

Discount rate recommended by

public policyRisks

Non-risks

Can be reducedHard to reduceCan be reducedHard to reduce

Measures toremove EE barriers

Influence ofEE barriers

Discount rate

Figure 13: Definitions of discount rates in the context of EE

(2) Methodology We attempt to measure the acceptable pay-back time (PBT) for each household. The questionnaire is designed to specifically measure the PBT under the influence of “risks” and after removing the influence of other EE barriersj. In order to achieve this goal, the respondents are asked to imagine a case where they are required to choose either “normal” or “EE” RACs for their living rooms—the two being different only in terms of efficiency and initial cost. The questionnaire determines the willingness of the respondents to buy the EE model, which costs 30,000 JPY more than the normal model. In Figure 14, the average acceptable PBT is estimated to be approximately 4 years; this corresponds to a discount rate of approximately 20% when the lifetime of RACs is assumed to be 10 years.

0%10%20%30%40%50%60%70%80%90%

100%

Will

ing

to b

uy

rega

rdle

ss o

f PB

Ts

10 y

ears

8 ye

ars

6 ye

ars

5 ye

ars

4 ye

ars

3 ye

ars

2 ye

ars

1 ye

ar

Unw

illin

g to

buy

re

gard

less

of P

BTs

Pro

babi

lity

Cumulative probability distribution

Probability distribution

Acceptable pay-back times (PBTs) ofEnergy efficient RAC models

Figure 14: Acceptable pay-back times of EE RAC models

(3) Result As a consequence of “risks,” the acceptable average pay-back time is estimated to be about 4 years in the case of RACs; this corresponds to a discount rate of approximately 20%. 3. Impact of energy efficiency barriers on CO2 emission reduction potential In this chapter, an analysis of the impact of EE barriers on the CO2 emission reduction potential of RACs is carried out by considering the six EE barriers derived in the previous chapter.

3.1 Concept of CO2 emission reduction potential Figure 15 presents the basic concept of the CO2 emission reduction potential curve, which is derived by sorting

j In order to verify whether this aim is achieved, we compared the PBTs of each segment. The result shows that the average PBT is 4.1 years for those using RACs and 3.8 years for those not using RACs under the influence of other EE barriers. The difference between these two values is negligibly small; this implies that the influence of other EE barriers is almost absent. The observed PBT of each household is used in the data analysis in the following chapter. To increase the accuracy of the analysis, the PBT of each household that is under the influence of other EE barriers is adjusted such that the average PBT is 4.1years.

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the reduction amount in the order of marginal reduction cost. In this study, the CO2 emission reduction potential (tons of CO2 per year) is determined by taking into account space heating and space cooling in the Japanese residential sector, where existing appliances are replaced by RACs at the end of the lifetime of the appliances. The data collected from the questionnaire survey of approximately 2500 respondents is plotted, and the resulting curve is considered to represent the 49 million households in the residential sector in Japan. By taking both emission reduction and cost reduction into account, the cost-effective reduction potential is determined from the point of intersection between the resulting curve and the assumed marginal reduction cost. In order to simplify the discussion, we assume a marginal costk of 3000 JPY/t-CO2 (approx. 30 USD/t-CO2).

Opt

ion

2 CO2 reduction(t-CO2)

Mar

gina

l cos

t of

CO

2 em

issi

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ion

(JPY

/t-C

O2)

0・・・

CO2 emission reduction potential curve

Opt

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Miti

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n op

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1

afterbefore

beforeafteremissionsemissions

costcostcost Marginal

−

−=

afterbefore emissionsemissionsreduction CO2 −=

p

Better Economics of mitigation options WorseEmission reduction Emission reduction and cost reduction but cost increase

Increase in effortto reduce CO2

Reduction potential with negative marginal cost

Reduction potential at or below marginal cost of p

Figure 15: Concept of CO2 emission reduction potential curve

The shape of the CO2 emission reduction potential curves varies with the assumed amount and cost of CO2 reduction. We obtain four types of potential curves, i.e., theoretical, technical, economic, and market potential (Table 2). Theoretical potential is defined to be equal to the current CO2 emissions. This assumption corresponds to the case where all households use RACs powered by carbon-free electricity. Technical potential assumes that RACs are introduced into all households without taking economic factors into account. Economic potential also assumes that RACs are introduced in all households, but it considers the economics for a discount rate of 6%l. Only market potential takes the EE barriers into account for both the amount and cost of CO2 reduction. In other words, we assume that RACs cannot be introduced in the households that are under the influence of EE barriers, except for the barrier of “risks,” and also use the PBT data of each household as the proxy for the influence of “risks.”

Table 2: Definition of CO2 reduction potential

CO2 reduction Marginal costTheoretical potentialInnovative technologies are successfully developed and diffused.

Total amount of current CO2emissions. Economics not

considered.Technical potentialAssumed technologies are diffused regardless of economics. Diffused to

all households.Economic potentialCost-effective technologies are diffused from the mid/short-term viewpoint.

Comparison of economics withdiscount rate of 6%.

Market potentialTechnologies are diffusedunder the current market status.

Impact of EE barriers (non-risks).Diffused only tonon-influenced households.

Impact of EE barriers (risks).Comparison of economicswith discount rate for each household (approx. 20% on average)..

3.2 Overview of methodology Although this study aims to understand the EE barriers in the space-heating domain, the calculation covers space cooling as well. This is because the initial cost of RACs could be overestimated when the space-cooling function of RACs is ignored. The effect of considering space cooling on the results and implications obtained is negligible

k The marginal cost rises with the effort required to reduce CO2. l Geller and Attali (2005) recommend that policy makers consider a discount rate of 4–8% for EE. In this study, we adopt the mean value.

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because the energy used for space cooling is only about one-tenth of that used for space heating. The space heating/cooling demand of each household is determined by fitting the data surveyed with the multiple regression equation obtained by AIJ (2006) [17]. Thus, the analysis can consider household diversity associated with climatic conditions in each region, building type, insulation property, floor space, space heating/cooling hours, and indoor temperature. The standardized pattern of hourly demand is also taken into consideration to decide the unit capacity of appliances. The initial cost and appliance efficiency are determined on the basis of energy statistics and appliance database (Table 3), and sensitivity analyses of the appliance efficiency and unit cost of RACs are conducted. The energy prices and carbon intensity of electricity are obtained by referring to the data for FY2006; changes in the parameters in future years are not considered.

Table 3: Assumed characteristics of appliances

Energy Appliance EfficiencyUnit cost

(thousandJPY/kW)

Remarks

Kerosene/Gas

Fan heater 90% 4 Ventilation loss 10%.Stove 90% 3 Ventilation loss 10%.FF/central 85% 30 FF: forced draft balanced flue.Floor heating 80% 150 Includes cost of panels, piping, etc.

Electricity

RAC (Before replacement) 400%* 40 Heat-pump type.

*200% for cold regions.RAC (Afterreplacement) 600%* 40 Heat-pump type.

*300% for cold regions.Heater 100% 15 Includes kotatsu, electric carpets.

Floor heating 100% 150 Heater type.Includes cost of panels, etc.

Other Stove 90% --- Use of biomass, etc.Not assume switching.

3.3 Results Figure 16 shows CO2 emission reduction potential curves of RACs, and Figure 17 compares the reduction potential up to 3,000 JPY/t-CO2 (approx. 30 USD/t-CO2) in terms of the ratio to the current amount of CO2 emissions (38.5 Mt-CO2). The technical potential, which assumes that RACs are introduced in all households, is estimated to be 62% (23.9 Mt-CO2). The economic potential is 53% (20.4 Mt-CO2), while the market potential is limited to 20% (77 Mt-CO2). The gap between the economic and market potential corresponds to 33% of the current level of CO2 emissions. In other words, this implies that two-thirds of the potential, which can be economically achieved, would be possibly lost in cases wherein EE barriers are not removed.

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CO2 emission reduction potentialof residential space heating & cooling (Mt-CO2/yr)

Removal of energy efficiency barriers

Theoretical potential

Technical potential

MarketpotentialEconomicpotential

e.g.marginal cost of3000 JPY/t‐CO2

Figure 16: CO2 emission reduction curves of

RACs

0% 20% 40% 60% 80% 100%

Theoretical potential.

Technical potential.

Economic potential.

Market potential.

CO2 emission reduction potential up to 3,000 JPY/t‐CO2(100% = Total CO2 emissions  from residential space heating & cooling (Approx. 40 Mt‐CO2/yr))

Impact ofenergy efficiency barriers

Technologies are diffusedunder the current market status.

Cost‐effective technologies are diffusedfrom the mid/short‐term viewpoint.

Assumed technologies are diffusedregardless of economics.

Innovative technologies aresuccessfully developed and diffused.

Figure 17: CO2 emission reduction potential up to

3,000 JPY/t-CO2

Figure 18 shows the impact of each EE barrier; the impact is determined from the gap between the economic potential and the potential obtained by taking each EE barrier into consideration. It is to be noted that the summation of the impacts exceeds the total impact of all EE barriers; this is because there are households under the influence of more than one EE barrier. “Imperfect information” is estimated to have the highest impact; by this barrier, there would be a decrease of 21% in the theoretical reduction potential, or the current amount of emissions. The barrier with the second highest impact is estimated to be “hidden costs,” which can contribute to a decrease of 8.1%. “Risks” have an impact of 5.2%, while “bounded rationality,” “split incentives,” and “access to capital” each have an impact of 2–3% in the case of RACs.

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0% 10% 20% 30%

Imperfect information- Incorrect estimation of energy costs.

Split incentives- App. preinstalled; not accountable for bills.

Bounded rationality- Interested in EE, but not proactive.

Access to capital- Budget constraints on initial cost.

Hidden costs- Loss of benefits.

Risks- High discount rate = short pay-back times.

CO2 emission reduction potential up to 3000 JPY/t-CO2affected by energy efficiency barriers

(100% = Total CO2 emissions from residential space heating & cooling; approx. 40 Mt-CO2/yr)

Impact ofenergy effieicncybarriers

Energy Efficiency barriers(total)

Figure 18: Impact of each EE barrier on CO2 emission reduction potential

Lastly, the effectiveness of promotion policy in removing EE barriers is preliminarily compared to the effectiveness of R&D. We compare the increase in the emission reduction potential with respect to the market potential in each of the following cases:

“Removal of EE barriers:” if all the EE barriers are removed, the potential corresponds to the economic potential.

“Efficiency improvement:” the COP of RACs is improved from 6 to 10 in warm regions and from 3 to 8 in cold regions.

“Cost reduction:” the unit cost of RACs is reduced from 40,000 JPY/kW (approx. 400 USD) to 30,000 JPY/kW.

“Efficiency improvement & cost reduction:” both assumptions are taken into consideration. Figure 19 shows the variations in the CO2 emission reduction potential curves. “Efficiency improvement” contributes to an increase in the reduction potential, whereas “cost reduction” contributes to a decrease in the reduction cost. In the case of “efficiency improvement & cost reduction,” the curve shifts toward the bottom right, thereby leading to an increase in the cost-effective potential. Figure 20 compares increment in CO2 emission reduction potential up to 3,000 JPY/t-CO2 (approx. 30 USD). “Removal of all EE barriers” is estimated to increase the potential by 33% points, which is larger than the increase in potential due to “efficiency improvement” and “cost reduction.” As discussed in the following chapter, it should be noted that (1) R&D is expected to contribute more to the removal of EE barriers, (2) some of the EE barriers are difficult to be removed by implementing the promotion policy, and (3) the promotion policy should be implemented on the basis of the findings of a cost-effectiveness analysis. Therefore, further considerations are necessary before deciding which of the two—promotion policy or R&D—should be given greater priority. However, the result implies that promotion policy can play a significant role in mitigating CO2.

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Market potential

+Efficiency improvement*

+Removal of EE barriers(=Economic potential)

+Cost reduction*

+ Efficiency improvement& cost reduction*

* R&D is expected to contributemore to the removal of EE barriers,but that is not taken into consideration.

e.g.Marginal cost of3000 JPY/t-CO2

Figure 19: CO2 emission reduction curves of RACs (effectiveness of promotion policy and

R&D)

0% 10% 20% 30% 40% 50% 60%

＋Removal ofenergy efficiency barriers

＋Efficiency improvement

＋Cost reduction

＋Efficiency improvement & cost reduction

CO2 emission reduction potential up to 3000 JPY/t-CO2

Marketpotential

Potential for expansion

＋α

＋αreduce the impact of "risks" and "access to capital"

＋α

(100% = Total CO2 emissions from residential space heating & cooling; approx. 40 Mt-CO2/yr)

reduce the impact of "imperfect info."

Figure 20: CO2 emission reduction potential up to

3,000 JPY/t-CO2 (effectiveness of promotion policy and R&D)

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4. Conclusions 4.1 Key findings This study was aimed at revealing whether EE barriers exist and determining the barriers if they do exist. A case study on heat-pump room air-conditioners (RACs) was conducted in the residential sector in Japan. The key findings empirically obtained from the questionnaire survey are as follows:

Approximately 60% of the CO2 emissions resulting from space heating and space cooling can be reduced if all households use currently available RACs. Even after taking cost-effectiveness into consideration, approximately 50% of the emissions can be reduced.

However, two-thirds of the cost-effective potential may be neglected due to the influence of various EE barriers. Among the EE barriers, “imperfect information” on energy costs and appliance efficiency is estimated to have the largest impact on the economic potential.

Appropriate measures to remove EE barriers are as important as the development of cost-effective, energy-efficient technologies.

4.2 Discussion

4.2.1 Measures to remove EE barriers in the case of space-heating appliances Table 4 summarizes the possible measures to remove each of the EE barriers in the case of space-heating appliances.

Table 4: Measures to remove EE barriers in the case of space-heating appliances

EE barriers Measures

Imperfectinformation

- Provide accurate, trustworthy, easily assimilated information.- Field surveys of usage styles and actual efficiency.- R&D for efficiency improvement.

Split incentives- Appliance efficiency standard- Building efficiency standard- Indirect effect by information

Boundedrationality - Indirect effect by efficiency standard and information.

Accessto capital

- Subsidy, tax reduction and preferred loan rate for installation.- R&D for unit cost reduction.

Hidden costs- R&D for reducing loss of benefit and increasing additional non-energy benefits.- Indirect effect by information.

Risks- Specification of risk factors and appropriate measures for removing each factor.- R&D for unit cost reduction.

(1) Imperfect information “Imperfect information” is the EE barrier with the largest impact in the case of RACs. Accurate, trustworthy, and easily assimilated information is expected to help overcome this problem (Sorrell et al., 2004[3]). The objectives of information can be categorized into two approaches: (1) to help compare products in the same category in terms of energy efficiency and economics, and (2) to help compare products between different categories. In order to realize the former objective, EE labeling in point of sales of RACs is being implemented in Japan. However, there seems to be no effective tool to realize the latter objective—partly because it is not easy to design the same standard to help compare products with different styles of usage and partly because it is difficult to get competitors from different industries involved in a discussion. However, the realization of the latter objective is becoming increasingly important, especially because the substitution of conventional appliances with RACs is expected to be a realistic mitigation option. Needless to say, providing such information requires consensus building on what is more efficient. In building a consensus, the government, research institutes, and the industry can play a role in promoting a better understanding of EE by conducting field surveys of usage styles and actual efficiencies. Information display of energy cost and energy used, which several models of RACs shipped in 2008 were already equipped with, is a unique way to realize the above-mentioned objectives. In addition to implementing the promotion policy mentioned above, efficiency improvement by R&D is expected to reduce the impact of “imperfect information,” especially in cold regions where the climatic conditions lead to a decrease in the efficiency of heat-pump units as well as to a loss in energy in order to escape from freezing temperatures. (2) Split incentives “Split incentives” are estimated to have a relatively small impact in the case of RACs in Japan. A possible policy intervention is by imposing direct regulation.

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One of the direct regulations is the appliance efficiency standard. The “Top Runner” approach was introduced in 1999, and it was aimed at improving the average efficiency of models available in the market. Therefore, theoretically, the influence of “split incentives” in the case of RACs would be negligible. However, the effect of the appliance efficiency standard is limited to RACs. In practice, it is not easy to develop a uniform appliance efficiency standard for all types of appliances, the reason being the same as that discussed in the case of “imperfect information.” By implementing a building efficiency standard, which is another method of imposing direct regulation, it is expected that such limitations can be overcome. In April 2009, the energy conservation law in Japan was revised with the aim of encouraging large- and medium-sized construction companies and builders of rented houses to take appliance efficiency into consideration. It is essential to review the effectiveness of such policies. Moreover, the indirect effect of information is expected to potentially urge people to choose their appliances rationally. (3) Bounded rationality “Bounded rationality” is a somewhat vague concept, but often important from the viewpoint of consumer behavior. Although there seems to be no silver-bullet measures, the impact of this concept may be reduced through the indirect effect of efficiency standard and information. For example, if direct regulation can successfully transform the market structure, consumers would eventually shift toward EE appliances. Likewise, if appropriate information is available, consumers could easily consider taking advantage of EE opportunities. (4) Access to capital Subsidies, tax concessions, and low-rate loans for installation are expected to reduce the barriers on initial investment. However, the financial support provided by the government is justified only when private-sector funds are insufficient. In other words, technologies already commercialized, such as RACs, may require unconventional policy intervention methods. From the technical viewpoint, R&D for unit cost reduction could reduce the impact of “access to capital” and “risks” to some extent. (5) Hidden costs It is important to recognize that “hidden costs” exist in many EE opportunities, although they are difficult to measure in terms of monetary value. R&D for the reducing loss in benefits and thereby increasing benefits is expected to promote EE technologies. Also, the transaction costs for acquiring and processing information etc. may be eliminated through the indirect effect of information. (6) Risks “Risks,” which are often due to a combination of various factors, may lead to a short pay-back time. It is essential to specify the fundamental factors contributing to an increase in risks because some risk factors can be removed while others may be difficult to remove. Although not elaborated in this study, the discount rate is presumably increased as mixed results of pure time preference and specific factors related to RACs, such as technical reliability, portability, etc. For example, people living in rented houses might hesitate to procure RACs in case they have no idea of when they would be asked to move out. Supposing that this factor has been estimated to have a large impact, we should consider appropriate measures such as developing easily portable models, providing financial incentives for transporting appliances, developing mechanisms that allow the next occupant to use the appliance left behind by the previous tenant, and promoting the installation of EE models in rented houses. Thus, to reduce the impact of “risks,” it is necessary to specify the important risk factors and the appropriate measures to remove these factors. Further, from a technical standpoint, R&D for unit cost reduction could reduce the impact of “access to capital” and “risks” to a certain extent. The average discount rate in the case of RACs is estimated to be approximately 20%, which corresponds to an acceptable pay-back time of approximately 4 years. There are three points to be noted. First, the consumers’ implicit discount rate varies with the type of technology. For example, the discount rate for photovoltaics is likely to be lower (hence, resulting in a longer pay-back time) than that for RACs. Secondly, even for the same appliance, the discount rate observed varies with the methodology used for its measurement. For example, the discount rate observed in the real market includes the impact of other EE barriers in addition to that of “risks.” Therefore, from an analytical viewpoint, it is essential to specify the definition of the discount rate analyzed. Thirdly, we should not deny EE opportunities from calculations based on high discount rate (Geller and Attali, 2005[16]). Instead, it is important to introduce appropriate measures to transform the market run by low discount rates by removing the EE barriers.

4.2.2 Implications for climate change policy There are two important factors to be considered while devising appropriate measures to remove EE barriers. Firstly, every measure needs to be well designed from the point of view of cost-benefit and adequately implemented by checking and reviewing the processes. Otherwise, ineffective measures might lead to additional transaction costs, or in the worst case, distort the market. Secondly, some of the EE barriers cannot be completely removed by policy intervention. In such cases, R&D is expected to play a supportive role; for example, significant efficiency improvement could reduce the impact of “imperfect information,” massive cost reduction could mitigate the impact of “access to capital” and “risk,” and other performance improvements could

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potentially transform negative “hidden costs” into positive non-energy benefits. The balance between promotion policy and R&D varies with the phase of the product life cycle as well as the external environment. In Japan, considerable emphasis is laid on the technical viewpoint than the market viewpoint in the context of climate change policies. Although several scenarios have been proposed on low-carbon societies, many of them are based on the hypothetical assumptions that the technical potential can be fully harnessed without considering the EE barriers. However, as can been seen in the case study of RACs, even apparently cost-effective technologies may be confronted with many barriers. In order to accelerate CO2 mitigation, there is a need for research on methods to remove the EE barriers. References [1] Intergovernmental Panel on Climate Change, 2001. “Climate Change 2001: Mitigation,” A Report of

Working Group III. [2] International Energy Agency, 2008. “Promoting Energy Efficiency Investments- Case Studies in the

Residential Sector.” [3] Sorrell, S., O'Malley, E., Schleich, J., and Scott, S., 2004. “The Economics of Energy Efficiency: Barriers to

Cost Effective Investment,” Edward Elgar, Cheltenham. [4] Science and Technology Policy Research, 2000. “Reducing barriers to energy efficiency in public and

private organizations,” University of Sussex, Final Report, Joule III Project, EU, 2000. [5] McKinsey & Company, 2007. “Reducing U.S. Greenhouse Gas Emissions: How much at What Cost?,”

2007.11. [6] Organization for Economic Co-operation and Development / International Energy Agency, 2008. “Energy

Technology Perspectives 2008 - Scenarios and Strategies to 2050,” 2008.6. [7] The Energy Data and Modeling Center, 2008. “Handbook of Energy & Economic Statistics in Japan.” [8] Jyukankyo Research Institute, 2009．“Energy handbook for residential sector.” (in Japanese only). [9] Heat Pump and Thermal Storage Technology Center of Japan, 2007. “Break Through for dramatic GHG

reduction,” IEA Deploying Demand Side Energy Technologies Workshop, 2007.10. [10] Nishio and Nagano, 2008. “An Analysis of Demand Side Measures towards a Large-scale Reduction of CO2

Emissions,” CRIEPI Report Y08001. (in Japanese only) [11] Ministry of Economy Trade and Industry, 2008. “Long-term Energy Supply/Demand Outlook.” (in Japanese

only) [12] Heat Pump and Thermal Storage Technology Center of Japan, 2009. “Survey on Use of Space-heating

Appliances in Winter.” (in Japanese only) [13] International Energy Agency, 2007. “Mind the Gap- Quantifying Principal-Agent Problems in Energy

Efficiency.” [14] Meier, A. and Eide, A., 2007．“How many people actually see the price signal? Quantifying market failures

in the end use of energy,” Lawrence Berkeley National Laboratory, Paper LBNL-63384, 2007.9. [15] Sanstad, A. H., Blumstein, C., and Stoftm, S. E., 1995. “How high are option values in energy-efficiency

investments?,” Energy Policy, Volume 23, Issue 9, September 1995, pp.739–743. [16] Geller, H. and Attali, S., 2005．“The Experience with Energy Efficiency Policies and Programmes in IEA

Countries: Learning from the Critics,” IEA Information Paper, 2005. [17] Architectural Institute of Japan, 2006. “Energy Consumption in Residential Houses in Japan.” (in Japanese

only)