Japan Low -Carbon Society Scenarios Study - Feasibility of 70% CO2 - - PowerPoint PPT Presentation

Japan Low -Carbon Society Scenarios Study

• Feasibility of 70% CO2 emissions

20 0 reductions tow ards 2050 - 1 If we cannot go to LCS

• 1. If we cannot go to LCS,…
• 2. LCS offers higher QOL with

less energy demand and lower-carbon energy supply

• 3. LCS needs good design,

l ti d i ti

Junichi Fujino

early action, and innovations

National Institute for Environmental Studies (NIES)

Junichi Fujino

(fuji@nies.go.jp)

1

National Institute for Environmental Studies (NIES) AIM Training Workshop, Tsukuba, Oct 27, 2008

Surface Air Temperature Change (1900=0 oC)

CCSR/NIES/FRCGC, Japan

p g ( )

2

http://2050.nies.go.jp

3 http://www.kantei.go.jp/foreign/abespeech/2007/05/24speech_e.html

7

Current per capita

US 6 /cap)

CO2 emissions and Target

$200/t-C scenario

Canada 5

• ns (t-C/

g

US: delay for tech development, global warming business

UK 4 emissio Germany

EU: Initiatives toward LCS Japan: Need long-term vision

F 2 3 er capita y METI, Japan 2030 scenario Developing countries: earlier

guidance toward LCS is key

France World 1 2 CO2 pe

Japan 2050 scenario g y

China India 1

Target for Low Carbon Society

IB1 IA2

4

1970 1980 1990 2000 2010 2020 2030 2040 2050

Shuzo Nishioka, Junichi Fujino; NIES COP11 and COP/MOP1 side event Global Challenges Toward Low-Carbon Economy (LCE), Dec.3, 2005

P it E C b

How fast we need to reduce GHG emissions

Activity Energy CO

Total amount

Per capita activity Energy Intensity Carbon Intensity CO2 emissions＝Pop Activity Energy CO2 × Pop Activity Energy × × 60-80% reductions Chan rat differe int To 60 80% reductions Kaya identity nge e ential egral

• tal

Change rate＝speed

Kaya identity ＋ ＋ ＋ CO2emission Change rate Pop Change rate Activity Pop Energy Activity CO2 Energy

＝

Change rate＝speed

Change rate Change rate p change rate y change rate gy change rate 0 5%/year 1 5%/year 2~3%/year Y%/year X%/year

5

• 0.5%/year 1.5%/year
• 2~3%/year

1%/year Y%/year X%/year

• 3~4%/year

The case of Japan LCS

Required improvement rate of carbon and energy intensity to achieve LCS carbon and energy intensity to achieve LCS

Energy Intensity Carbon Intensity (w/o CCS) C b I t it (CCS l )

Historical trend

Carbon Intensity (CCS only)

ScenarioB Scenario A Japan Japan France U.K. Japan 60-80% reductions towards 2050 Germany France

0.0 1.0 2.0 3.0 4.0 5.0

Improvement rate of carbon and energy intensity (%/y)

6

Keep double speed to improve carbon and energy intensity compared as that of the historical record!

Japan Low Carbon Society Scenarios toward 2050

[FY2004-2008, Global Environmental Research Program, MOE] [FY2004 2008, Global Environmental Research Program, MOE]

Study environmental options toward low carbon society in Japan d b d

Green buildings Self-sustained city Decentralized services Eco awareness Effective communication Dematerialization Next generation vehicles Efficient transportation system Advanced logistics

Techno-Socio Innovation study Advisory board： advice to project

Decentralized services Dematerialization Advanced logistics

BaU scenario

E i h

Urban structure IT-society

Development of socio- economic scenarios ion

Transportation system

Reduction Target study

BaU scenario

EE improvement New energy Energy saving Structure change Life-style h

• Tech. innovation

economic scenarios, evaluating counter- measures with social- economic-technology models GHG emissi

• 1

1 3 5 Valid Equity Effective

990 000 020 050 010 Intervention scenario

change

GHG reduction target

（eg. 60-80% reduction by 1990 level） Evaluate feasibility of GHG reduction target

Integration Team

Suitable

19 20 20 20 20 Middle-term Target year Loge-term Target year

5 teams 60 Researchers

7

60 Researchers

Propose options of long-term global warming policy

Japan LCS (Low-Carbon Society) (FY2004-2008)

8

Japan LCS (Low Carbon Society) (FY2004 2008) Research Project supported by Global Environmental Research Fund, MOEJ

Scenario Approach to Develop Japan Low Carbon Society (LCS)

Depicting Ch ki

Japan Low -Carbon Society (LCS)

socio- economic visions Estimating energy Exploring Checking potentials for energy supply in 2050 gy service demands innovations for energy demands Quantifying energy d d supply Step1 Step5 and energy supplies demand and supply to estimate CO Step2 Step3 p CO2 emissions Step3 Achieving energy- Step4

9

g gy related CO2 emissions target

Visions Visions

we prepared two different we prepared two different

Vision A Vision B

we prepared two different we prepared two different but likely future societies for Japan but likely future societies for Japan

Vision A Vision B Vivid, Technology-driven Slow, Natural-oriented Urban/Personal Decentralized/Community Technology breakthrough Centralized production /recycle Self-sufficient Produce locally, consume locally Comfortable and Convenient Social and Cultural Values 2%/yr GDP per capita growth 1%/yr GDP per capita growth

10

Akemi Imagawa

We prepared models to quantify the LCSs We prepared models to quantify the LCSs We prepared models to quantify the LCSs We prepared models to quantify the LCSs

Element models; Element models; 1) Snapshot models; Inter-sector and Macro Economic model Energy technology bottom-up models Energy supply model Transportation demand model 2) Transition models; P l ti d h h ld d l Population and household model Building dynamics model Integration tool; Integration tool; Snapshot Integration Tool (SSI)

11 11

Population and Household Model Population and Household Model

• Drastic change is projected in Japan’s population structure by 2050.

g p j p p p y Downturn in birthrate, depopulation and aging will continue until 2050, and they affect greatly the future vision.

• A cohort component model for population, a household headship rate model

l l l l for household types, with spatial resolution of provinces, land-use types and climate zones and five family types was developed, and is used to analyze effects of depopulation and changes in family composition on the li ti f LCS

Total population (Period T-1) [Sex, Age] Province-wise Population (Period T-1) [Sex, Age] Life table [Sex Age]

Consistency Adjustment

Province-wise life table [S A ]

realization of LCS.

[Sex, Age] International Net-migration Fertility rate [Age] Province-wise fertility rate [Age]

Consistency Consistency Adjustment Adjustment

[Sex, Age] Total population (Period T) [Sex, Age] Province-wise Population (Period T) [Sex, Age] Net migration (Japanese) International net-migration (Outsider) Province-wise headship rate [Sex Age Family]

Consistency j

Province-wise net-migration [Sex, Age] T t l b f Headship rate [Sex, Age, Family] [Sex, Age, Family] L d Cl i Province-wise landuse Cls. share Province-wise climatic division share P i i Cli ti

12

Total number of Household (Period T) [Family-wise] Landuse Cls.-wise Population (Period T) [Sex, Age] share Province-wise household (Period T) [Family] Climatic zone

• wise household

(Period T) [ Family] : Data flow : Exogenous variable : Endogenous variable

Flowchart of PHM

12

Population 2000年 2050年

80-84 85- 80-84 85-

127billion scenario A: 94bil scenarioB:100bil

60 64 65-69 70-74 75-79 65-69 70-74 75-79 45-49 50-54 55-59 60-64 45 49 50-54 55-59 60-64 30-34 35-39 40-44 30-34 35-39 40-44 45-49 15-19 20-24 25-29 15-19 20-24 25-29 30 34 A 男 0-4 5-9 10-14 0-4 5-9 10-14 B 男 A 女 B 女

13

6,000 4,000 2,000 2,000 4,000 6,000

女 （ 千 人 ） 男 （ 千 人 ）

6,000 4,000 2,000 2,000 4,000 女 （ 千 人 ） 男 （ 千 人 ）

Projection Japan population and households in Projection Japan population and households in i i

120 140

100%

%)

age

scenario A scenario A

80 100 housand) 80- 60-79 40-59

60% 80% Others Parent- Child

usehold (%

llion)

40 60 pulation (Th 20-39 0-19

40% Children One-Person Couple-Only

pe of hou

(Mi

20 2000 2010 2020 2030 2040 2050 Pop

0% 20% 00 05 10 15 20 25 30 35 40 45 50 Couple- Children

Typ

2000 2010 2020 2030 2040 2050

200 200 201 201 202 202 203 203 204 204 205

year 2000 2050 A B A B Population (million) 126.9 94.5 100.3 Aged population ratio (%) 17.4 53.7 35.8 Average number of household 2.71 2.19 2.38

14

Single-person households (%) 27.6 42.6 35.1

14

Labor Force and Working time

M F 2000年 2050年A 2050年B

3 000 4,000 5,000 20 00 20 50 A 20 50 B 3 000 4,000 5,000 2000 2050A 2050B

Employee (1000)

Employee (1000)

2050年B

1,000 2,000 3,000 19 24 29 34 39 44 49 54 59 64 69 74 79 84 5~ 1,000 2,000 3,000 19 24 29 34 39 44 49 54 59 64 69 74 79 84 5~ 15~ 1 20~ 2 25~ 2 30~ 3 35~ 3 40~ 4 45~ 4 50~ 5 55~ 5 60~ 6 65~ 6 70~ 7 75~ 7 80~ 8 85 15~ 1 20~ 2 25~ 2 30~ 3 35~ 3 40~ 4 45~ 4 50~ 5 55~ 5 60~ 6 65~ 6 70~ 7 75~ 7 80~ 8 85

Working time (men, hour/day)

Working time (men, hour/day)

4 5 6 7 8 2000 2050A 2050B 4 5 6 7 8 2000 2050A 2050B 1 2 3 ~ 19 ~ 24 ~ 29 ~ 34 ~ 39 ~ 44 ~ 49 ~ 54 ~ 59 ~ 64 ~ 69 ~ 74 ~ 79 ~ 84 85~

u

1 2 3 ~ 19 ~ 24 ~ 29 ~ 34 ~ 39 ~ 44 ~ 49 ~ 54 ~ 59 ~ 64 ~ 69 ~ 74 ~ 79 ~ 84 85~ 15~ 20~ 25~ 30~ 35~ 40~ 45~ 50~ 55~ 60~ 65~ 70~ 75~ 80~ 8 15~ 20~ 25~ 30~ 35~ 40~ 45~ 50~ 55~ 60~ 65~ 70~ 75~ 80~ 8

age

15

Projection of urbanization Projection of urbanization

140 120 140 Forest-rural Forest-central city 80 100 n (mill.) Forest-Metropolitan Agricultural-rural Agricultural-central city

Rural

40 60 Populatio Agricultural central city Agricultural-metropolitan Urban-Regional 20 40 Urban-Central Urban-Core U b M t lit

Urban

2 2 1 2 2 2 3 2 4 2 5 Urban-Metropolitan

year 2000 2050 A B A B A B A B A B A B A B A B A B A B A B year 2000 2050 A B Population (million) 126.9 94.5 100.3 Urban population(%) 78.1 84.2 76.7

16

Agricultural area population(%) 8.2 7.1 8.5 Forest area population(%) 13.7 8.7 14.8

16

Building Dynamics Model Building Dynamics Model

• Enhancement of building insulation is very effective countermeasures.

60% of the heating demand from the residential sector can be cut down, g , if appropriate insulation systems are installed. Besides, configuration of buildings in urban and rural area affects social energy efficiency greatly.

Number of dwelling stock (year T-1)

[Region, types of buildings, construction material, insulation level, construction year]

Number of households Unoccupied rate Population and Household Model

• In order to take account

these factors, a model of b ildin d n mi s (BDM)

Number of new dwellings (year T) Share by type of building

Share by

Share by region Survival rat

building dynamics (BDM) was developed. h d l h

Survived number of dwellings (year T)

[Region, types of buildings, construction material, insulation level construction year]

Share by construction material

Share by insulation level Number of new dwellings (year T)

[Region, types of buildings, construction material, insulation level]

• It is a cohort model with a

spatial resolution of climate zones, four heat

insulation level, construction year]

Household production and lifestyle model Renovation rate Number of dwelling stock (year T)

[Region, types of buildings, construction material

Bottom-up

insulation levels, four residential building types, and six commercial

17

construction material, insulation level, construction year]

：endogenous variable ：exogenous variable Bottom-up engineering model

Flowchart of BDM (residential)

and six commercial building types.

17

Projection of residential building stock by Projection of residential building stock by insulation level Scenario A insulation level Scenario A insulation level, Scenario A insulation level, Scenario A

50 60

1999 standard 1992 standard

Projection

40

uses

1992 standard 1980 standard

j based on enhanced policy (Scenario A)

20 30

Million hou

Without insulation 1999 standard

(Scenario A)

10 20

1992 standard 1980 standard

Projection based on present

2003 2008 2013 2018 2023 2028 2033 2038 2043 2048 1980 standard Without insulation

policy

18 18

Passenger Transportation Demand Model Passenger Transportation Demand Model

• Many effective countermeasures exist related with transportation. Modal shift

from private motor vehicles to mass transit systems, urban planning towards compact cities, transportation substitution with diffusions of teleworking and

Population Population Dynamic Model Macro Economic Model

compact cities, transportation substitution with diffusions of teleworking and virtual communication systems and so on.

• Passenger Transportation Demand

Model (PTDM) can simulate

Population [Attribute, Area] Population Dynamic Model License [Attribute] Employment [Attribute]

( ) transportation demand associated with changes in population distribution, people’s activity patterns modal shares and average

Population [Attribute, Area] Trip Generation Coefficient [Attribute, Day, Area, Objective] M d l Sh Population [Attribute] Trip Generation Coefficient [Attribute, Objective, Mode] M d l Sh

patterns, modal shares and average trip distances.

• The demands in this model are

Average Trip Distance (km/Trip) [Day, Area, Mode] Modal Share (%) [Day, Area, Mode] Average Trip Distance (km/Trip) [Mode] Modal Share (%) [Attribute, Objective, Mode]

divided into two types, 1)Intra-regional transportation within the daily living area

Intra-Area Transportation (person-km) [Mode] Inter-Area Transportation (person-km) [Mode] Net-Total Conversion ratio Passenger Transportation ：Data Flow ：Endogenous Variables ：Exogenous Variables

within the daily living area, 2)Inter-region transportation between the daily living areas,

19

Passenger Transportation [Persons-km]

Intra-Area Transportation Inter-Area Transportation

and they are calculated separately.

19

Passenger Transportation Demand Model (2) Passenger Transportation Demand Model (2) Scenario A Scenario A Sc nar o Sc nar o

350,000 400,000 450,000 1,000,000 1,200,000 150,000 200,000 250,000 300,000 400,000 600,000 800,000 50,000 100,000 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 200,000 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Inter-region transportation demand by mode

• f transportation (mil. person-km)

Intra-region transportation demand by mode

• f transportation (mil. person-km)

Buses Aviation Pass cars Maritime Railways Walk&Bike

• Coupled with population decrease, and intensive decreasing policy of average trip

distance such as the compaction of neighborhood communities causes significant

Buses Aviation Pass.cars Maritime Railways Walk&Bike

distance, such as the compaction of neighborhood communities causes significant decrease of intra-regional transportation demand.

• In addition, the share of railways transportation will increase rapidly due to the

promotion of modal shift from car to train.

20 20

Inter Inter-

• sector and Macro Economic Model

sector and Macro Economic Model

• Projecting macro economic activity, sectoral production, and also taking account the

countermeasures proposed in the individual models, we developed “Inter-sector and Macro Economic Model (IMEM)”, which consists of a sequential dynamic general equilibrium module and a macroeconomic module. Th d l b d t ti t ti l d t l i ti iti th i t

• The model can be used to estimate national and sectoral economic activities, the impacts
• f energy efficient and dematerialization technologies in industrial sectors, development
• f informatization, and increase of service sectors.

Macroeconomic module energy balance table (input) ergy production sector final demand sector mand t SNA economic growth

• ext. trnsact.

account account of

• inc. & expnd.

Input coefficient

• n energy

① ⑤ ⑦ ⑧ tech

① production function ② commodity market ③ capital market ④ labor market

(input) input matrix ene non- energy value added commodity dem labor capital final cons investment import&export input coefficient

• n non-energy

tech&preference IO table in 2000 intermediate demand energy balance table in 2000 ① ② ④ ⑦ CO2 ⑫ ⑫

④ labor market ⑤ calculation of GDE ⑥ expenditure and income in production sector ⑦ expenditure and income

energy balance table (output) v a energy

• utput coefficient
• n energy

production and cost ty supply capital fixed capital formation matrix in 2000 tech ② ③ ⑥ ⑥ ⑩ ① ② tech

⑦ expenditure and income in household and government ⑧ assumption of import and export

• utput matrix

non energy production and income commodit fixed capital stock matrix production social cap. goods mpensation

• cap. goods
• utput coefficient
• n non-energy

capital profile in sector V matrix ⑥ ① ⑩ ⑪ ⑨

export ⑨ fixed capital stock matrix ⑩ investment goods market ⑪ capital stock 21

capital stock com

• f c

tech V matrix in 2000

input data in 2000 assumption balance condition

⑪ ⑪

• utput

CGE module

⑪ capital stock ⑫ CO2 emissions Structure of Inter-sector Module 21

Projected sector productions in year 2050 Projected sector productions in year 2050

200

• n JPY

2000

100 150

ducts, trillio

2050A 2050B

50

mestic prod

nd Fishing Mining beverages Textiles n products r products & printing l materials dicaments al products al products Cement c products el products rous metal al products Machiery & supplies equipment nstruments nufacturing

• nstruction

as supplies ater supply retail trade insurance Real estate Transport unications ministration d research al security ic services ss services al services king places ing places al services e supplies e classified

Dom

ure, Forestry an

• d products & b

er and Wooden Paper & pape Publishing ganic chemica Med Other chemica finary and Coa Other ceramic Stee Non-ferr abricated meta chine, equip. & Transport e Precision in Other man Co Power & ga Wa Wholesale & r Finance & R Comm Public adm education and ealth and Soci Other publi Other busines nd recreationa ating and drink and other lodg Other persona Offic not elsewhere Agricultu Foo Timbe Pump. Org O Petroleum ref Fa Elec.Ma W School Medical, He O Amusement a Ea Hotel a Activities

22 22

A

Quantification of Scenario A and B in 2050 Quantification of Scenario A and B in 2050 Quant f cat on of Sc nar o an n 5 Quant f cat on of Sc nar o an n 5

( %) ( %) year unit 2000 A B model 2050 Population Mil. 127 94 (74%) 100 (79%) Household Mil. 47 43 (92%) 42 (90%) Average number of person per household 2.7 2.2 2.4 Population and Household model GDP Tril.JPY 519 1,080 (208%) 701 (135%) Share of production primary % 2% 1% 2% secondary % 28% 18% 20% tertiary % 71% 80% 79% Inter-sector and Macro Economic Model tertiary % 71% 80% 79% Office floor space Mil.m2 1654 1,934 (117%) 1,718 (104%) Building dynamics Model & Inter-sector and Macro Economic Model Travel Passenger volume

• bill. p・km

1,297 1045 (81%) 963 (74%) Private car % 53% 32% 51% Public transport % 34% 52% 38% Walk/bycycle % 7% 7% 8% Freight transport volume bill t・km 570 608 (107%) 490 (86%) Transportation demand model & Inter-sector and Macro Economic Model Freight transport volume

• bill. t・km

570 608 (107%) 490 (86%) 100 126 (126%) 90 (90%) Steel production Mil.t 107 67 (63%) 58 (54%) Etylen production Mil.t 8 5 (60%) 3 (40%) C d i Mil 82 51 (62%) 47 (57%) Inter-sector and Macro Economic Model Industrial production index

23

Cement production Mil.t 82 51 (62%) 47 (57%) Paper production Mil.t 32 18 (57%) 26 (81%)

( %) is a percentage compared with year 2000

23

LCS house in 2050

Comfortable and

Utilizing solar power

Visions Visions and and Innovations Innovations

Photovoltaic Eco-life education

34-69MW

energy-saving house

rooftop 10-20% energy d d d ti High efficiency lighting

【eg LED lighting】 (25-47% house has PV on roof (now 1%)) and develop high efficiency (<30%) PV

Solar heating p gardening demand reduction

Monitoring system Diffusion rate: 20-60%

（currently 8%）

Reduce 1/2 energy demand Share 100% Monitoring system

equipped with appliances

Reduce 60% warming energy demand,

Super high efficiency air High-insulation

share 100% COP (coefficients of performance=8),

efficiency air conditioner Heat-pump heating Fuel cell

share 0-20% share 100%

p p g

COP＝5 share 30-70% share 0 20%

Stand-by energy reduction

R d 1/3

High efficiency appliances Good information for economy and environment

24 Reduce 1/3 energy demand, share 100% 5

g e c e cy app a ces reduce energy demand and support comfortable and safe lifestyle economy and environment makes people’s behavior low-carbon

Projected energy efficiency improvement: Projected energy efficiency improvement: Air Air-conditioners for cooling and heating conditioners for cooling and heating

9.0

Air Air conditioners for cooling and heating conditioners for cooling and heating

MOE 7.0 8.0 ance) Historical AIST 6.0 performa Best METI METI

2050s Target

4.0 5.0 ficient of Average 2 0 3.0 OP (Coeff Average Worst 1.0 2.0 CO

Top-runner approach

25

0.0 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055

Energy supplied from 45% 80% 60% Total energy demand 1.5 times 2.1 times 1 time

2100 2050 2030 2000

Res/Com

Residential gy pp transformation sector* 45% reduction 35% 80% reduction 80% 60% reduction 55% CO2 intensity 3.5 t-CO2/household (1 time) 118 kg-CO2/m2 (1 time) 1.9 t-CO2/household (1/2 times) 77 kg-CO2/m2 (2/3 times) 1.1 t-CO2/household (1/3 times) 40 kg-CO2/m2 (1/3 times) 0 t-CO2/household 0 kg-CO2/m2

*The percentage of reduction of energy per unit should be supplied from the transformation sector, compared with total energy demand increases in proportion to GDP

Commercial Residential Commercial

Energy saving

Efficiency improvement of equipment Lighting with less heat loss Equipment with less heat loss

GDP.

Improving thermal performance Improving electric power conversion efficiency Electric power conversion with least loss →

Self-sustaining

Efficient heating Efficient heat transfer, preheating by unused energy → → Active control of sun shading and thermal insulation Improving thermal performance

• f housing and building

Utilization of ubiquitous energy Food storage at room temperature Energy saving enables equipment using little energy Energy creation from ubiquitous energy

(minute pressure, temperature difference, vibration, radiowaves, etc.)

0 t-CO2/household

E ti

Photovoltaic generation Installation facilitation Installation in curved surfaces Installation in windows Installation in all places such as PV paint

2

0 kg-CO2/m2

Energy creation Energy management

Efficiency improvement and increase of durability BEMS•HEMS Self-sustainable housing and building

26

Demand management Management of demand and energy creation Energy accommodation in community (Energy supply in community) Supply and demand management in community TEMS Self-sustainable community → → → Supply and storage management in community →

Energy Technology Roadmap 2100 (METI, Japan)

http://www.iae.or.jp/2100.html

Residential sector Energy reduction potential: 40-50% Innovations Innovations

70 Change of the numbers

• f households

Change of service

Energy reduction potential: 40 50%

12 9 3 4 3 4 50 60 Mtoe) Change of service demand per household Change of service demand per household Improvement of energy

Hi-Insulated housing

17 12 23 40 sumption (M p gy efficiency Electricity consumption H2 consumption

Hi Insulated housing Energy Effiency

17 20 30 nergy Cons Solar consumption Biomass consumption

Energy Effiency

10 En Gas consumption Oil consumption 2000 2050A 2050B Energy consumption in 2000

Change of the number of households: the number of households decrease both in scenario A and B 27 Change of the number of households: the number of households decrease both in scenario A and B Change of service demand per household: convenient lifestyle increases service demand per household Change of energy demand per household: high insulated dwellings, Home Energy Management System (HEMS) Improvement of energy efficiency: air conditioner, water heater, cooking stove, lighting and standby power

UK, February 2005 Japan, June 2005

28

, y “40% House” 60% reductions p , Guidance for Self-sustained Residential, 50% reductions

How to reduce CO2 emissions from t t ti t

http://www.ukerc.ac.uk/TheMeetingPlace/Activities/Activities2007/0706AchievingSustainableLCS.aspx

passenger transportation sector

Demand management e g by information e.g. by information- communication technology [transport-service per capita] (1-0.2)x(1-0.2)x(1-0.2)x(1-0.2)x(1-0.2)x(1-0.2)=0.26 Modal shift to reduce CO2 EF per passenger-km or ton-km Improve fuel economy [Fuel consumption per vehicle-km]

∑

⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ × × × × =

Mode

Fuel EF Vkm Fuel Tkm Pkm Vkm TransServ Tkm km P capita TransServ capita

2 2

CO ) ( ) ( CO

Improve load factor [ hi l k Pk (Tk )]

⎠ ⎝

Mode

Fuel Vkm Tkm Pkm TransServ capita capita ) (

Improve accessibility [ k t k [vehicle-km per Pkm(Tkm)] Introduce low carbon energy [CO emission factor per fuel 29 [passenger-km or ton-km per transport-service] [CO2 emission factor per fuel consumption] Yuichi Moriguchi, 2nd Japan-UK joint research project workshop (2007.6)

2 50

Estimated regional automotive CO2 emissions

2.00 2.50 Tokyo Met. Osaka Met. Nagoya Met. Other Areas 1.00 1.50

Freight vehicles

0.00 0.50

Passenger cars

2000 4000 6000 8000 10000 12000 14000

Each Area is categorized in 1 Major cities

Accumulated population [million]

CO2 per capita [t/year]

• 1. Major cities
• 2. Cities with a pop of 0.5 million and above
• 3. Cities with a pop of 0.3 and above
• 4. Cities with a pop of 0.1 and above
• 5. Cities with a pop less than 0.1 million

C

• 6. Counties

Passenger car emissions (t-CO2/capita) 30 Yuichi Moriguchi, 2nd Japan-UK joint research project workshop (2007.6)

Passenger transportation E d d d ti t ti l 80% Energy demand reduction potential: 80%

7 1 4 6 4

50 60

Change of total transportation amount Change of structure of transportation D f i

Decrease of demand Modal shift

6 7 4

40 50 ds (Mtoe)

Decrease of service demand Improvement of energy efficiency Electricity

Land use Change

Modal shift

32 28

30 y demand

Electricity H2 Solar

Energy Efficiency 10 20 Energy

Solar Biomass Gas

10 2000 2050A 2050B

Gas Oil Energy demands in

31

2000 2050A 2050B

2000

New concepts for personal mobility

Yamaha EC-02 the Segway Human Transporter a spo te Toyota i-Swing

32

Toyota i Swing

(catalog information)

Kawamura cycle KE

Seconday Energy Consumption (Mtoe) 50 100 150 200 250 300 350 400 Industrial

Residential Commercial

• Trans. Prv.

Trans Frg

2000(Actual)

Commercial

• Trans. Frg.

2050(Scenario A) 2050(Scenario A) 2050(Scenario B)

Decrease of energy demand

2050(Scenario B) Industrial Residential Commercial Trans Prv Trans Frg Industrial Residential Commercial

• Trans. Prv.
• Trans. Frg.
• Trans. Prv.: Transportation (Private), Trans. Frg.: Transportation (Freight)

Possible energy demands reductions for each sector: Industry：structural change and introduction of saving energy tech. 30～40％ Passenger Transport :land use, saving energy, carbon-intensity change 80％

33

Freight Transport :efficient transportation system, energy efficient 50％ Residential: high-insulated and energy-saving houses 40-50％ Commercial: high-insulated building and energy saving devices 40％

What is Low Carbon What is Low Carbon Energy Supply System? Energy Supply System?

Large scale

Large-scale St Small-scale

Energy Supply System? Energy Supply System?

Consumer

Large-scale Supplier

Storage Small scale Storage

And we need low-carbon energy.

Electricity Large-scale Renewables Distributed Grid Electricity

gy How to mix with Renewable energy

Nuclear Renewables Renewables Heat Pump Electrolysis Stationary

• Renewable energy
• Nuclear energy

Fuel Cell Renewables Fossil Fuel Heat Electrolysis Hydrogen y Fuel Cell

• Fossil fuel + CCS

Vehicle Trans portation Hydrogen Bi f l CCS (Carbon

34

portation Biofuel CCS (Carbon Capture and Storage)

Fujino (2005)

http://2050.nies.go.jp

Energy supply for achieving 70% reduction Energy supply for achieving 70% reduction

• f CO
• f CO2 emissions

emissions

Primary Energy Consumption (Mtoe) 100 200 300 400 500 600 a y e gy Co su pt o ( toe) Coal Oil Gas 2000(Actural) Nuclear 2050(Scenario A) Biomass Solar and Wind 2050(Scenario B)

35

Coal Oil Gas Biomass Nuclear Hydro Solar and Wind

GHG 70% reduction in 2050 Scenario A: Vivid Techno-driven Society

Demand side energy -40% ＋ Low carbonization of primary energy＋ＣＣＳ with moderate cost of technological options as 0.3% of GDP in the year of 2050

Change of activity

Change

• f activity

・High economic growth, Increase of service demand per household, Increase of office floor (increase) ・Servicizing of industry, Decline in number of households, Increase of public transportation (decrease)

with moderate cost of technological options as 0.3% of GDP in the year of 2050

6 21 6 1 24 10 13

• f

y Reduction

• f demand

ector

Industry

Reduction of service demand Improvement of energy intensity Improvement of ・Farm products produced and consumed in season

• n

90 13 38 9 7 Improvement o energy intensit

• f end‐use

nergy demand se

dential & mmercial

Improvement of carbon intensity Reduction of service demand Improvement of ・Fuel switch from coal and oil to natural gas ・Insulation ・Energy use management (HEMS/BEMS) ・Efficient heat pump air‐conditioner, Efficient water heater, 70% reductio

36 7 28 17

Emission Emission

Improvement of carbon intensity

• f end‐use

E tor

ation Resid com

Improvement of energy intensity Improvement of carbon intensity Efficient heat pump air conditioner, Efficient water heater, Efficient lighting equipment ・Development and widespread use of fuel cell ・All‐electric house ・Photovoltaic

77 41 36 CCS

1990 CO2 E 2000 CO2 E

mprovement of arbon intensity f energy supply nergy supply sect

Transporta

Reduction of service demand Improvement of energy intensity ・Advanced land use / Aggregation of urban function ・Modal shift to public transportation service ・Widespread use of motor‐driven vehicle such as electric vehicle and fuel‐cell electric vehicle

CCS

2 Emission

Im ca

• f

E

nergy supply

gy y Improvement of carbon intensity Improvement of ・High efficiency freight vehicle ・Improvement of energy efficiency (train/ship/airplane) ・Fuel mix change to low carbon energy sources such as natural gas, nuclear energy, and renewable energy

36

Carbon Capture Storage 2050 CO

En

Improvement of carbon intensity ・Power generation without CO2 emission ・Hydrogen production without CO2 emission ・Effective use of night power / Electricity storage ・Hydrogen (derived from renewable energy) supply

GHG 70% reduction in 2050 Scenario B: Slow Nature-oriented Society

Demand side energy -40% ＋ Low carbonization of primary energy＋Renewables with moderate cost of technological options as 0.3% of GDP in the year of 2050 with moderate cost of technological options as 0.3% of GDP in the year of 2050

Change of activity

・High economic growth, Increase of service demand per household, Increase of office floor (increase) ・Slowing of final demand by breaking away from physical affluence mind‐set, Reduction of war material production,

21 24 21 4 21 4 Change

• f activity

stry

Reduction of service demand Improvement of ・Significant improvement in energy efficiency of production , p , Servicizing of industry, Decline in number of households, Increase of public transportation (decrease) ・Promoting seasonal local food

24 63 24 13 14 16 24 13 14 16 provement of ergy intensity

• f end‐use

mand sector

Indus l & ial

energy intensity Improvement of carbon intensity Reduction of service demand equipment ・Fuel switch from coal and oil to natural gas ・Insulation ・Energy use management (HEMS/BEMS)

82 35 23 5 35 23 5 rovement of

• n intensity

f end‐use Imp ene

• Energy dem

0% reduction ssion ssion

n Residential commerci

service demand Improvement of energy intensity Improvement of carbon intensity Energy use management (HEMS/BEMS) ・Efficient heat pump air‐conditioner, Efficient water heater, Efficient lighting equipment ・Expanding biomass energy use in home ・Diffusion of solar water heating and photovoltaic on the roof

82 34 34

• vement of

n intensity ergy supply Impr carb

• f

gy supply sector

70 1990 CO2 Emis 2000 CO2 Emis

Transportation

Reduction of service demand Improvement of g p ・Shortening trip distances for commuting through intensive land use ・Infrastructure for pedestrians and bicycle riders (sidewalk, bikeway, cycle parking)

40 40 40 Impro carbo

• f ene

Energ

mission

gy supply

Improvement of energy intensity Improvement of carbon intensity ・Widespread use of hybrid vehicle ・Expanding biofuels ・Improvement of energy efficiency (train/ship/airplane)

37

2050 CO2 Em

Ener

Improvement of carbon intensity ・Expanding share of both advanced gas combined cycle and biomass generation ・Decrease of electricity demand

38

• 7. Pedestrian Friendly City Design

A Dozen of Actions towards Low-Carbon Societies

Residential/commercial sector actions

Press release

• n May 22, 2008
• 1. Comfortable and Green Built Environment

Efficiently use of sunlight and energy efficient built environment design. Intelligent buildings. City design requiring short trips and pedestrian (and bicycle) friendly transport, augmented by efficient public transport

• 2. Anytime, Anywhere Appropriate Appliances

Use of Top-runner and Appropriate appliances. Initial cost reduction by rent and release system resulting in improved availability

• 8. Low-Carbon Electricity Supplying low carbon

electricity by large-scale renewables, nuclear power and CCS equipped fossil (and biomass) fired plants Energy supply sector actions resulting in improved availability.

• 3. Promoting Seasonal Local Food

Supply of seasonal and safe low-carbon local and CCS-equipped fossil (and biomass) fired plants

• 9. Local Renewable Resources for Local Demand

Enhancing local renewables use, such as solar, wind, biomass and others Industrial sector actions foods for local cuisine

• 4. Sustainable Building Materials Using local and

renewable buildings materials and products. biomass and others.

• 10. Next Generation Fuels Development of carbon

free hydrogen- and/or biomass-based energy supply system with required infrastructure

• 5. Environmentally Enlightened Business and

Industry Businesses aiming at creating and

• perating in low carbon market. Supplying low

carbon and high value added goods and services system with required infrastructure

• 11. Labeling to Encourage Smart and Rational Choices

Visualizing of energy use and CO2 costs information Cross-sector actions carbon and high value-added goods and services through energy efficient production systems.

• 6. Swift and Smooth Logistics

Visualizing of energy use and CO2 costs information for smart choices of low carbon goods and service by consumers, and public acknowledgement of such consumers Transportation sector actions

39

• 12. Low-Carbon Society Leadership Human resource

development for building “Low-Carbon Society” and recognizing extraordinary contributions.

• 6. Swift and Smooth Logistics

Networking seamless logistics systems with supply chain management, using both transportation and ICT infrastructure

7

Current per capita

US 6 /cap)

CO2 emissions and Target

$200/t-C scenario

Canada 5

• ns (t-C/

g

US: delay for tech development, global warming business

UK 4 emissio Germany

EU: Initiatives toward LCS Japan: Need long-term vision

F 2 3 er capita y METI, Japan 2030 scenario Developing countries: earlier

guidance toward LCS is key

France World 1 2 CO2 pe

Japan 2050 scenario g y

China India 1

Target for Low Carbon Society

IB1 IA2

40

1970 1980 1990 2000 2010 2020 2030 2040 2050

Shuzo Nishioka, Junichi Fujino; NIES COP11 and COP/MOP1 side event Global Challenges Toward Low-Carbon Economy (LCE), Dec.3, 2005

Reduction Targets

8,000 9,000

g

6,000 7,000 , f CO2-e 4,000 5,000

• ns, mmt of

2,000 3,000 Emissio 1,000 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Bingaman-Specter Draft 2007 Lieberman-McCain 2007* Udall-Petri 2006 Waxman 2007 Sanders-Boxer 2007 Kerry-Snowe 2007

41

Feinstein August 2006

web.mit.edu/globalchange/www/reports.html#pubs

CO2 Emission from Energy Activities in China

1 4 1.6 1.8 2.0 0 8 1.0 1.2 1.4 Gt-C

LCS Scenario

0.2 0.4 0.6 0.8 0.0 0.2 2000 2010 2020 2030 2040 2050 Year Year

Jiang Kejun (Energy Research Institute, China),

42

Jiang Kejun (Energy Research Institute, China), Low-Carbon Options in China EMF 22, Tsukuba, Dec 12-14, 2006

Japan-UK Joint Research Project LCS through Sustainable Development LCS through Sustainable Development for Global Participation

Th Fi k h h ld The First workshop was held in Tokyo, June14-16, 2006. G8 Gleneagles 2005

Participants from 19 countries;

G8 Japan

Participants from 19 countries; Asia: Japan, China, India, Thailand, Taiwan (China) Africa: South Africa, Nigeria Europe: UK France Germany

G8 Japan July 2008

Europe: UK, France, Germany, Denmark, Spain, Netherlands, Russia Latin America: Brazil, Mexico, Chile North America: US, Canada

The Second workshop was held in London, June13-15, 2007. The Third workshop was held in Japan, Feb13-15, 2008.

43

http://2050.nies.go.jp http://2050.nies.go.jp

Developing and Diffusing Innovations for our good life and LCS through SD

P.R. SHUKLA et al., Low-carbon society scenarios for India, CLIMATE POLICY 8 (2008) S156–S176 ( )

44

Transition of energy intensity: Start of new innovation race Start of new innovation race

0.5

U.S. EU-15 UK Germany

Start of new innovation race Start of new innovation race

4

CO2/Capita CO2/Capita

0.4 nd$]

U.K. Germany France Japan Korea

3.5 4 / 人 ）

ドイツ イギリス

Ger Ger p

0.3 /thousan

Korea

2.5 3 量 （ t C /

イギリス

2 22 C／人

Ger Ger Japan Japan

0.2 GDP [toe/

Korea U.S.

1 5 2 C O

2 排

出

フランス

2.22ｔC／人

UK UK

0.1 Energy/G

U.K.

?

1 1.5 人 あ た り

日本

0.82ｔC／人

Fr Fr

0.0 E

Japan

0.5 一 人

日本 実績値 計画値

0.5 tC/人

Plan Plan Past Past

1970 1980 1990 2000 2010 2020 2030 Year

(Based on IEA Energy Statistics) By S.Nishioka and S.Ashina 1940 1960 1980 2000 2020 2040 2060 2080

LCS is not only to avoid dangerous li t h b t t climate change, but to…

• Avoid energy resource battles by using

resources in efficient ways resources in efficient ways

• Develop many innovations to support

l b l t i bl d l t global sustainable development

• Build safe and sound society considering

y g appropriate land-use and city planning We need good systems to pledge

46

We need good systems to pledge people’s activity for LCS

LCS (Low-Carbon Society) is Risk Management

• We always face to risks if we are alive.
• Global warming is one of risks in our daily life, but

g y it might become one of the huge/ biggest risks in some future…

• Short-term Sweet (Benefit) / Long-term Legality
• Market Failure -> Smart Regulation
• Market Failure -> Smart Regulation
• Crisis = 危(danger) + 機(chance)

創 新

• 創(create) 新(something new) = Innovation
• Sense of Urgency for Good Design of our Society

47 Junichi Fujino, à l’Iddri - 6, rue du Général Clergerie - 75116 Paris (Mo Victor Hugo) Vendredi 12 janvier 2007, de 11 heures à 13 heures

What gift can you provide What gift can you provide for our future? for our future?

48

Christmas Concert of Yoko Fujino’s Piano Class on Dec 23, 2005