Potential of low carbon city - - PowerPoint PPT Presentation

都市の低炭素化のポテンシャ ルと その解析 Potential of low carbon city formation and its analysis

Department of Urban Engineering

Integrated Research System for Sustainability Science (IR3S) The University of Tokyo

Keisuke Hanaki

hanaki@env.t.u-tokyo.ac.jp

14.5 4.9 10.0 7.6 3.7 3.7

5 10 15 Kitakyushu (2002) Tokyo (2004) Japan (2004) Shanghai (1998) China (2004) Thailand (2004)

t-CO2/person

Future per capita CO2 emission target

Per capita CO2 emission in Asian countries and cities. 2

Strategy for Low Carbon City

Energy supply side and Demand side management

Energy supply side

Fuel selection, Renewable energy (forest,

agriculture and urban sector)

Electricity technology

Demand side

Household, Office & commercial,

transportation

Urban form change

3

Approach of analysis of urban activity

GIS is useful, but not always necessary and convenient.

Spatial distribution of land/buildings Statistics (Amount of buildings, land) Basic information Analysis using GIS Number of buildings, building use, floor area

○○市 111 34 23 005 98725 ○○市 111 34 23 345 98785

Analysis scale District Town, city, prefecture Example of analysis Effect of district heating using solid waste incineration heat Biomass utilization of solid wastes Building improvement, Photovoltaic cell

4

Interaction between power demand and power supply

6 12 18 24 Oil LNG Nuclear Coal Hydro Power Generation (MW) Time (h)

Impact of demand change on fuel composition of power generation Effect of fuel composition of power generation

• n CO2 reduction

5

Target cities

Cold Moderate Hot Mega Sapporo Tokyo Large Sendai Hiroshima middle Hakodate Utsunomiya Kagoshima/Naha

C i t y n a m e A r e a P

• p

u l a t i

• n S
• l

a r r a d i a t i

• n

t i m e H e a t i n g d e g r e e d a y s C

• l

i n g d e g r e e d a y s k m 2 I n 1 H

• u

r s / y D e g r e e

• d

a y D e g r e e

• d

a y S a p p

• r
• 1

1 2 1 1 8 2 3 1 7 7 4 . 8 2 5 7 4 U t s u n

• m

i y a 3 1 2 4 4 3 1 9 3 8 1 4 1 6 4 7

T

• k

y

• (

2 3 d i s t r i c t s )

6 1 7 8 2 6 1 8 4 7 . 2 8 5 5 1 4 8 H i r

• s

h i m a 7 4 2 1 1 1 4 2 4 . 9 1 3 3 1 5 N a h a 4 9 1 2 6 1 8 2 . 9 4 4 4

6

CO2 reduction potential in residential buildings

• 60% reduction from 1990 level in all Japan

Contribution of electricity sector

7

住宅対策 電力対策 20 40 60 80 100 120 140 160 180 200 220 1990 2000 2010 2020 2030 2040 2050 年間CO2排出量［ 百万t-CO2/年］ 1.00 1.31 1.26 1.11 0.39 0.56 1.00 1.32 0% 20% 40% 60% 80% 100% 2010 2050

太陽光 太陽熱 照明 家事衛生 娯楽情報 冷蔵庫 厨房 給湯 冷房 暖房

Contribution of residential buildings

Hot water Heating

Solar

Prefectural difference in reduction from residential buildings

CO2 emission reduction varies among prefectures depending on climate, population, etc. 8

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 海道 森県 手県 城県 田県 形県 島県 城県 木県 馬県 玉県 葉県 京都 川県 潟県 山県 川県 井県 梨県 野県 阜県 岡県 知県 重県 賀県 都府 阪府 庫県 良県 山県 取県 根県 山県 島県 口県 島県 川県 媛県 知県 岡県 賀県 崎県 本県 分県 崎県 島県 縄県

[100万t-CO2]

1990年 2050年(無対策) 2050年(電力対策) 2050年(電力＋建築対策） 北海道 青森県 岩手県 宮城県 秋田県 山形県 福島県 茨城県 栃木県 群馬県 埼玉県 千葉県 東京都 神奈川県 新潟県 富山県 石川県 福井県 山梨県 長野県 岐阜県 静岡県 愛知県 三重県 滋賀県 京都府 大阪府 兵庫県 奈良県 和歌山県 鳥取県 島根県 岡山県 広島県 山口県 徳島県 香川県 愛媛県 高知県 福岡県 佐賀県 長崎県 熊本県 大分県 宮崎県 鹿児島県 沖縄県

1990 2050 (BAU) 2050 (Electricity effect) 2050 (Electricity + building effect)

Tokyo Osaka Fukuoka

Office and Commercial buildings

36% reduction by construction, 71% by construction + Electricity

9

5 E + 1 1 E + 1 1 1 . 5 E + 1 1 2 E + 1 1 2 . 5 E + 1 1 1 9 9 2 2 1 2 2 2 3 2 4 2 5

CO2排出量（ 億t‐CO2/年） 0.5 1.0 1.5 2.0 2.5 1990 2000 2010 2020 2030 2040 2050年

運用時 新築時 削減量 改修時 自然ケース 建築・ 電力対策

+9% ‐71%

（ 1990年比） （ 1990年比）

建築対策

‐36%

（ 1990年比）

BAU +9% from 1990 Building effect

• 36% from 1990

Building + electricity effect

• 71% from 1990

Operation Construction Construction Repair

Regionally estimated PV electricity generation

• 3.5 kW residential roof-top PV system
• poly-Si solar cell and a module efficiency of 14 %
• solar radiation data of prefectural capital cities from METPV-2
• correction of PV output using monthly averaged air temperature
• 3.5 kW residential roof-top PV system
• poly-Si solar cell and a module efficiency of 14 %
• solar radiation data of prefectural capital cities from METPV-2
• correction of PV output using monthly averaged air temperature

1000 2000 3000 4000 5000 6000 Hokkaido Aomori Iwate Miyagi Akita Yamagata Fukushima Ibaraki Tochigi Gunma Saitama Chiba Tokyo Kanagawa Niigata Toyama Ishikawa Fukui Yamanashi Nagano Gifu Shizuoka Aichi Mie Shiga Kyoto Osaka Hyogo Nara Wakayama Tottori Shimane Okayama Hiroshima Yamaguchi Tokushima Kagawa Ehime Kochi Fukuoka Saga Nagasaki Kumamoto Oita Miyazaki Kagoshim Okinawa Annual PV generation [kWh/y]

Maximum-Yamanashi : 5,700 kWh/y Minimum -Ishikawa : 4,500 kWh/y

24 % difference 24 % difference 10

Ratio of PV electricity generation to electricity consumption

0% 5% 10% 15% 20% 25% 30% Hokkaido Aomori Iwate Miyagi Akita Yamagata Fukushima Ibaraki Tochigi Gunma Saitama Chiba Tokyo Kanagawa Niigata Toyama Ishikawa Fukui Yamanashi Nagano Gifu Shizuoka Aichi Mie Shiga Kyoto Osaka Hyogo Nara Wakayama Tottori Shimane Okayama Hiroshima Yamaguchi Tokushima Kagawa Ehime Kochi Fukuoka Saga Nagasaki Kumamoto Oita Miyazaki Kagoshim Okinawa PV electricity generation ／Electric consumption

annual PV electricity generation estimated annual electricity consumption (2004) annual PV electricity generation estimated annual electricity consumption (2004)

Maximum-Kagoshima : 20 % Minimum -Osaka : 9.0 %

The ratio depends upon industrial and urban The ratio depends upon industrial and urban structures as well as degree of urbanization structures as well as degree of urbanization 11

District heating/cooling system using sewage heat in Shibaura zone, Tokyo Biogas and heat supply from kitchen waste & sludge In Kawasaki City

1 2 3 4 5 6 7 8 9 10 皇居 四谷 田町 麻布 芝浦水再生 センタ ー 虎ノ 門 赤坂 500m 1 2 3 4 5 6 7 8 9 10

Royal palace Yotsuya

T a m a c h i K a s u m i g a s e k i A z a b u S h i b a u r a T r e a t m e n t P l a n t

Amount of kitchen waste (kg/day)

T

• r

a n

• m
• n

A k a s a k a Heat demand is calculated based on building GIS data. 500m 500m

Potential: 11,000 t-CO2/y Potential: 12,000 t-CO2/y

Green line: Major sewer line Brown line: Railway Red: DHC installed

12

排熱利用地域冷暖房導入可能な 管 単

×

District heating/cooling using solid waste incineration heat

Potential: 1,550,000 – 2,800,000 t-CO2/y

CO2 emission reduction calculated surrounding each incineration plant

13

Potential CO2 emission reduction from base case

0% 5% 10% 15% 20% 25% 30% 35% 40%

R e s i d e n t i a l z

• n

e

• 1

R e s i d e n t i a l z

• n

e

• 2

R e s i d e n t i a l z

• n

e

• 3

R e s i d e n t i a l z

• n

e

• 4

C

• m

m e r c i a l z

• n

e 1 R e s i d e n t i a l z

• n

e

• 5

C

• m

m e r c i a l z

• n

e 2

Potential CO2 reduction

case-HP case-CGS w/o export case-CGS w. export case-DHC w/o export case-DHC w. export case-full option

Introduction of CGS/DHC, HP

• Comparison of Seven Districts in Utsunomiya

14

Relationship between the ratio of commercial building floor area to total building floor area and potential CO2 reduction (Sapporo+Naha+Utsunomiya)

. % 5 . % 1 . % 1 5 . % 2 . % 2 5 . % 3 . % 3 5 . % 4 . % % 1 % 2 % 3 % 4 % 5 % 6 % 7 % 8 % 9 % 1 % F r a c t i

• n
• f

c

• m

m e r c i a l b u i l d i n g a r e a P

• t

e n t i a l C O 2 e m i s s i

• n

r e d u c t i

• n

Ｈ Ｐ Ｃ Ｇ Ｓ Ｃ Ｇ Ｓ ( w . w h e e l i n g ) Ｄ Ｈ Ｃ Ｄ Ｈ Ｃ ( w . w h e e l i n g ) Ｆ Ｕ Ｌ Ｌ

• U

t s u n

• m

i y a Ｆ Ｕ Ｌ Ｌ

• S

a p p

• r
• Ｆ

Ｕ Ｌ Ｌ

• N

a h a

R2=0.906 R2=0.882

Summary for Potential CO2 Reduction Sapporo, Utsunomiya and Naha

15

Estimated results on potential CO2 emission reduction in the urban area by HP, CGS and DHC with wheeling (aggregated by prefecture)

Prefecture Potential CO2 reduction rate Prefecture Potential CO2 reduction rate Prefecture Potential CO2 reduction rate Hokkaido 16.6% Ishikawa 18.1% Okayama 18.1% Aomori 17.5% Fukui 17.5% Hiroshima 18.6% Iwate 16.0% Yamanasi 17.9% Yamaguti 18.0% Miyagi 18.7% Nagano 17.9% Toskushima 18.0% Akita 15.9% Gifu 16.5% Kagawa 21.7% Yamagata 17.1% Shizuoka 21.0% Ehime 18.8% Hukusima 18.2% Aichi 23.7% Kochi 16.7% Ibaragi 20.9% Mie 19.3% Fukuoka 24.3% Tochigi 18.1% Shiga 19.7% Saga 19.6% Gunma 20.7% Kyoto 19.0% Nagasaki 19.1% Saitama 25.3% Oosaka 30.0% Kumamoto 18.5% Chiba 21.6% Hyogo 19.8% Oita 17.0% Tokyo 30.4% Nara 22.2% Miyazaki 17.5% Kanagawa 29.5% Wakayama 18.6% Kagoshima 17.9% Niigata 17.5% Tottori 18.7% Okinawa 21.9% Toyama 18.4% Shimane 16.3% Japan 18.6%

16

Distributed energy supply network system

In this study region, the introduction of gas engine cogeneration systems (CGSs) to commercial buildings and the introduction of PV systems to residential buildings was evaluated. Case Study Area (Utsunomiya)

Residential buildin (with PV) Residential building(Noｎ

• PV)

Large scale building(with CGS)

PV

Urb Urban D n Dist strict

PV CGS CGS

Electricty Network Heat Heat Net Network Large scale building(with CGS) Small scale buildings(Non-CGS)

PV

17

Central district in Utsunomiya

• Interminglement of residential buildings and commerce buildings.

Utsunomiya Red, Purple : Commerce building Blue : Residential buildings

Case study - Utsunomiya

18

Reduction Rate of Primary Energy CO2

• 6

. %

• 4

. %

• 2

. % . % 2 . % 4 . % 6 . % 8 . % 1 . % 1 2 . % 87 870 4350 8700 13050 Number

• f

House Reduction Rate of Primary Energy Energy Network Energy NetWork(Minimize Electricity Sale)

The energy saving rate was the maximum when the number

• f residential buildings was under approximately 4000.

19

Simulation results of CO2 emissions for all of Japan (except Okinawa)

5 1 1 5 2 2 5 3 3 5 2 5 2 1 2 1 5 2 2 2 2 5 2 3 2 3 5 2 4 2 4 5 2 5 CO2

Carbon Tax PV cells yen /t-C no yes 10000 50000

emissions (million t-C/y）

20

5 1 1 5 2 2 5 2 1 2 1 5 2 2 2 2 5 2 3 2 3 5 2 4 2 4 5 2 5 n u c l e a r c

• a

l L N G

• i

l G C C I G C C p u m p

Generation Capacity [GW]

Combined Cycle Nuclear Coal Oil Natural Gas Hydro

Optimized generation capacities for each power generation type (no PV Cells, Carbon tax = 0 yen)

21

5 1 1 5 2 2 5 2 1 2 1 5 2 2 2 2 5 2 3 2 3 5 2 4 2 4 5 2 5 n u c l e a r c

• a

l L N G

• i

l G C C I G C C p u m p

Generation Capacity [GW]

Combined Cycle Nuclear Coal Oil Natural Gas Hydro

Optimized generation capacities for each power generation type (no PV Cells, Carbon tax = 10,000 yen)

22

Impact of Introduction of PHEV (Plug-in Hybrid Electric Vehicle) on electricity generation

Electricity City gas (hot water + CGS) Automobiles Marginal cost Marginal cost with PHEV

CO2 emission (Mt-C/y) 10

20 30

40 50 60 70 80

50 100 150 200 250

Marginal CO2 reduction cost In electricity sector (1000Yen/t-C) BAU 70% cut in electricity 70% cut in Electricity + PHEV

10 20 30 40 50 60 70 80 90

0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 00:00

PHEV Demand Grid Demand

Time Power demand of summer peak (Kanto, 2050)

• Electricity demand by PHEV (max

range 30 km) was calculated based

• n transportation data.
• Cost minimum operation of power

plants.

23

Calculation Method of Derived Physical Distribution

Output Matrix S Intermediate product N Final demand X:Derived physical distribution matrix Processing industry Consumers S＝Xe N=AS Processing N to S A： Input coefficient matrix

(I-O table)

X=RN R： Interregional transport matrix

(From which prefecture is the intermediate product supplied?)

24

Output weight by product and by prefecture when 1000 kg

• f farm and marine product is demanded in Hokkaido

25

4 k m 2 t ･k m 1 農水産品 林産品 鉱産品 金属機械工業品 化学工業品 軽工業品 雑工業品 特殊品 Farm and marine product Forest product Mineral product Metal and machinery product Chemical product Light industry product Miscellaneous industry product Specialty product

Output weight by product and by prefecture when 1000 kg

• f farm and marine product is demanded in Tokyo

4 k m 1 2 t ･k m 6 農水産品 林産品 鉱産品 金属機械工業品 化学工業品 軽工業品 雑工業品 特殊品 Farm and marine product Forest product Mineral product Metal and machinery product Chemical product Light industry product Miscellaneous industry product Specialty product

26

CO2 emission reduction by compact city

Reduction from building

Effective heating/cooling by

District heating system

<Compact district>

Reduction from transportation

Modal shift to railway Short trips

<Compact urban structure>

Compact district Utsunomiya

27

Strategy for low carbon city with various scales

28

2005 Large Cities Medium cities

Small town with

• agril. hinterland

2050

High-efficiency Compact city Biomass town

Hi-tech Office District Heating & Cooling

Apartment house Policy: Economic incentive Cap & trade City center dwelling & commerce Policy: City center activation

Formation of high efficient city

Apartment house

Biomass technol.

Policy: Business model Attraction

• f

industry

Formation of Compact city Penetration of business model

Planning strategy for each size

Economical independen cy

Public Transp.

Land planning

Land planning of LCS