"Academic Challenge for Regional Transition toward Sustainable Carbon Neutral Future", presented by Prof. Tsuyoshi Fujita (University of Tokyo) at the 2022 ProSPER.Net Leadership Programme, 7 December, 2022.
High Class Call Girls Bangalore Komal 7001305949 Independent Escort Service B...
Academic Challenge for Regional Transition toward Sustainable Carbon Neutral Future
1. Academic Challenge for Regional Transition
toward Sustainable Carbon Neutral Future
Prof. Tsuyoshi Fujita
University of Tokyo
Graduate School of Engineering,
Department of Urban Engineering, Japan
fujita77@env.t.u-tokyo.ac.jp
Prosper. Net Leadership Programme 2022
Shifting to Net Zero: Implementation strategies for net-zero
transitions,5-8, 16 December
by the United Nations University – Institute for the Advanced
Study of Sustainability (UNU-IAS)
1
2. Personal Background
- Doctorate in Environmental Engineering, Tokyo University
- Master of City Planning, University of Pennsylvania
- Former Director of Socio-environmental Research Center, National
Institute for Environmental Studies
- Appointed Professor of Tokyo Institute of Technology
- Member of SDGs Future City Initiative Committee, National Cabinet
Secretariat Office
- Member of Eco-City Promotion Committee, National Cabinet
Secretariat Office
- Expert Member of Environmental Information Committee, National
Environmental Commission Inquiry, MOE
- Expert Member of National Infrastructure Commission Inquiry,
Ministry of Land, Infrastructure, Transportation and Tourism
- Councilor of International Society of Industrial Ecology etc. 2
3. 3
OUTLINE
1) Challenges for cities and metropolises
low carbon society, circularization of resources
resilience, rapidly aging society
cultural preservation
2) Quantification models for sustainable
urban planning
integration of different environmental flow
technology and social solution system
circularization city, smart city, compact city
green growth innovation
3) Cases and future targets
6. Electricity Business Act
Agricultural Land Act
City Planning Act
Local industry
Disappearance of the traditional
home-town relations
Present
2011.3.11 Future to be
aiming at
Dynamic stability Special-case regime for
destabilization
[Technology regime]
Renewable energy
technology development,
smart grid, new transport
system: driving force of
Japanese-style
innovation
[Window of
opportunity] Niche
innovation triggered by
pioneering effort to
build a low-carbon
community
[New niche]
District energy business, town
district energy business,
industrial city business
collaboration, community
energy management district
network
New social pressure from the Great East Japan
Earthquake
Significance of the environmental city based on
social innovation theory
Resilient national land, distributed generation energy
Past
Conventional
pressure
Connection to changes in the new regime
Modification of Electricity Business Act
Modification of Agricultural Land Act
Modification of City Planning Act
Low-carbon city development project
Reestablishment of local bonds
FIT system
Comprehensive Special
Zone system
Environmental
city’s pioneering
effort as a
window of
opportunity
Environmental
City system
established
Change of social system
Socio-technical
landscape
Socio-technical
regime
Niche
innovation
6
7. New Challenges for Modelling and Monitoring Research
Research challenge to compile innovative modelling and monitoring approach
Long Term
Integrated
Model for
Future Vision
Normative Targets
by General
Equilibrium Model
Technology and
policy Solution
Design Adapting to
Local
Characteristics
Future
Targets
Low Carbon
Solutions on
Local Contents
0
200
400
600
800
1000
1200
1400
2005 2010 2015 2020 2025 2030
CO
2
emissions
(MtCO
2
)
Agriculture, Forestry andFish
Transport, Energy
Transport, Freight
Transport, Passenger
Commercial
Residential
Other Manufacturing
Construction
Machinery
Non-Ferrous Metals
Other Non-Metallic Minerals
Glass Products
Other Chemical Products
Textiles, Wearing Apparel and
FoodProduct, Beverage andT
Paper, Pulpand Printing
Petrochemicals
Cement
Ironand steal
Electricity andHeat Productio
Energy Conversion
Back
Casting
環境負荷
BaU
Social Transition
8. Funded by Ministry of Environment,
Japan (GERF, S-6) and NIES
GHG
emissions
per
capita
High
Carbon
Locked in
Society
Low
Carbon
Locked in
Society
Development of Asia LCS Scenarios
Policy Packages for Asia LCS
Low Carbon
Society
Backcasting
Leapfrog-
Development
Scenario Approach to Low Carbon Society in Asia
High Carbon
Locked-in type
Development
Climate
catastrophe:
Significant
Damage to
Economy and
Eco- System
Time
(1) Depicting narrative scenarios for LCS
(2) Quantifying future LCS visions
(3) Developing robust roadmaps by backcasting
8
9. 1930 1960
1990 2013 2030 2050
GHGs
Demonstration Projects and Cities for Social Transition
Bau Future
Technology Improvement
Social System Transition
9
46%
Reduction標
Carbon Neutral
Demonstration
Projects
10. IntegratedAssessment Model for the Global Socio economic Loss
AIM Applied Equilibrium Model
Global Scenario
• Population
• GDP
AIM Economic Model
Economic impacts
• GDP loss
• Consumption loss
• Energy cost
Grid Info.
• temperature
• population
Global GDP Loss
Air conditioning days
Climate condition represents 1.5, 2.5, 3.5, 4.5℃
increase of global average temperture from 18th
Century
Hasegawa et al. (2016)
11. 11
OUTLINE
1) Challenges for cities and metropolises
low carbon society, circularization of resources
resilience, rapidly aging society
cultural preservation
2) Quantification models for sustainable
urban planning
integration of different environmental flow
technology and social solution system
circularization city, smart city, compact city
green growth innovation
3) Cases and future targets
12. M
Modeling
Structure of AIM model
Dr. Masui
Impact/Adaptation
Model
Emission Model
【Country】
【Global】
【sequential
dynamics】
【dynamic
optimization】
【Local/City】
Agriculture
Water
Human health
Climate Model
Other Models
future society
Population Transportation Residential
GHG emissions
temperature
【Global】 【National/Local】
feedback
AIM/Impact
[Policy]
Burden share Stock-flow
mid-term target
IPCC/WG3
IPCC/WG2
IPCC/integrated scenario
carbon tax
long-term vision
Accounting
adaptation
low carbon scenario
Mitigation Target, Climate Policy, Capacity building, ...
What are assessed and how?
Economic model
Enduse model
Account model
AIM (Asia-Pacific Integrated Model) is an integrated
assessment model to assess mitigation options to reduce
GHG emissions and impact/adaptation to avoid severe
climate change damages.
12
13. Contribution to Climate Policy in Japan
▲8%
▲19%
▲25%
▲15%
▲25%
▲31%
▲17%
▲27%
▲33%
▲20%
▲30%
▲35%
1,261
1,351
1,256
1,427
1,156
1,025
952
1,349
1,074
943
874
1,324
1,046
917
849
1,294
1,013
886
820
0
200
400
600
800
1,000
1,200
1,400
1,600
固
定
低
位
中
位
○
高
位
固
定
低
位
○
中
位
○
高
位
固
定
低
位
○
中
位
高
位
固
定
低
位
○
中
位
高
位
0% 15% 20% 25%
90 05 10 2030
温室効果ガス排出量(百万トンCO2)
GHG emissions in 2030, Low growth case
GHG
emission
(MtCO2)
Fixed
Low
Middle
High
Fixed
Low
Middle
High
Fixed
Low
Middle
High
Fixed
Low
Middle
High
Non Energy
Energy
Transport
Commercial
Residential
Industry
mitigation options
share of nuclear
13
14. Environment-Economy-Society Integration Research Program
• Increased food production would lead adverse side-effects on the environment.
• Explore alternative policies toward hunger eradications while protecting the
environment.
• If hunger policies focused on the undernourished only by targeted support, and if
overeating or wasting food were simultaneously reduced, necessary food could
even decrease, decreasing cropland area and GHG emissions.
Hasegawa et al. (2019) Nature Sustainability, 2, 826–833
Ending hunger while reducing food production
Possible food distribution transformation to achieve the eradication of hunger Global agricultural impacts on the environment under different hunger eradication policies in 2030
MFA (More Food for All): Increasing food production and the overall level of food availability
FFP (Food For the Poor): Additional food supply targeting only the under nourished population
FFP + HigherYield: FFP with assumption of enhanced yield growth
FFP + NoWaste: FFP with assumption of less food waste
FFP + NoOvercons: FFP with food distribution improvement for alleviating over-consumption
FFP + ALL: FFP + HigherYield + NoOvercons + NoWaste
14
15. ● Eco-Model Cities since 2008; 23cities
Low-carbon Unification Initiatives for Cities/Regions
● Future Cities since 2011; 11 cities
The creation of successful examples to be spread
throughout Japan and internationally
●SDGs Future Cities
2018;29 2019;31 2020;33 Cities
Autonomous SDGs Plans
and Model Project Cities
15
Eco-cities, Smart Cities and SDGs Future Cities
16. Eco Growth Modules
Spatial Policy/ Tech. Process Packages
Development of Regional Integrated Models (Regional AIM) and Spatial
Planning Model to design sustainable regions and cities
Design of Vision and Road Map for National Scale
Forestry Eco System Service Model
Low Carbon Industrial System
Local Heat/Energy Management
National
End Use Model
*CGE model National
Targets
National
Road Maps
Analysis for Fukushima Pref. Scale
End
Use
Model
Fukushima
CGE
Model
Fukushima
Targets
Regional Rebuilding Parameter
【Population】 Policies for aging
【Industries】 Policies for low carbon
【Bio-Sys】 Natural habitat restoration
【Land Use】 Compact city Policies
Planning for Local Scale
Snap
Shot
Models
Policy
Support
Tools
Local
Targets
Strategic Spatial Zoning System Local Startistics and Project Data
Buildings Industries
Agriculture/ Forestory
Life Style
Regional
Parame-
ters
*Computational General Equilibrium
Integrated Model (AIM)
Fukushima
R. Maps
Spatial Planning Model
17. Environment-Economy-Society Integration Research Program
Integrative Eco-city Simulation Model
for Municipal Governments
• Local energy
• FEMS
• Industrial Symbiosis
Land Use
Scenario
Regional Future Scenario
(Local GDP, Population Land area)
Spatial
Distribution
(Residential)
Spatial
Distribution
(Industrial)
Future Spatial Scenario
Local Energy
Management
System
Transportation
Management
System
Industrial
Energy
Management
System
• Eco Finance / Behavior Science
• Location theory
• Regional science
(Weber, Alonso, etc.)
• CEMS
• ADR
Industrial
Location
Scenario
Built
Environment
Transition
Waste
Management
System
Recycle and
Industrial symbiosis
17
Population
2010 2020
18. 18
Decision Planning for
Stakeholders
Integrative Model Application toward Low Carbon Cities and Regions
NIES Dr. Gomi
18
Low carbon
planning
Citizen
participation
Technology
Inventory and
Suitability
Analysis
環境共生型まちづくりの進展
Feed back
toward the Sub
module
mondelling
AIM Region Model
Priority setting
for the focal
policy targets
and scope
Future Scenario
Life Industry Planning Energy
政策分析
Energy Model Population
Model
pds
=
( (1- ))
outin
pds
pds
LNtot
LHD AAWH DER
× ×
∑
agg
WR
work
Pop
tot
POP _
/
_
_ =
pds
( )
inin
pds
pds
LNtot
LHD AAWH DER
=
× ×
∑
Transportation
, ,
6
, , 365 (1/10 )
ptm age hht age td
td age hht
td ptm td ptm
PTD Pop Ptg
Pts Ptad
= ×
× × × ×
∑∑∑
,
6
, , (1/10 )
ftm pss pss td
pss td
td ftm td ftm
FTD PD Ftg
Fts Ftad
= ×
× × ×
∑∑
Local Economy
X Ainv(I-(I-Mr)F+Ex)
=
[ ] 1
Ainv Imat 1 IMR Amat
( )
−
= − − ×
_ _
inin inout
Income LNtot WagePP LNtot
WperL inout POP tot SSget
= × +
× + ×
Policy Options
MUL
et et et
x IMP2 f f IMP1 f
= ⋅ ⋅ + ⋅
(0.5)
, 1 1 , 1 1 1
et et et et et et et
imp1 f l b f
⋅ = ⋅ ⋅
, 2, 1 2 1
(1) (0)
1 , 2 2, 3 3, 1 2 1
3
0.5
MUL
et et et et et
MUL
et et et et et et et et et
et
imp2 f f
b l a l f f
⋅ ⋅
= ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
∑
Land Use
Model
,
lu lup lu
lup
Area LUCM
= ∑
, ,
_
lup lu lup lu
lup
LUCM Area prev LCC
= ⋅
,
,
, lup,lu
log min
lup lu
lup lu
lup lu
LCC
RLCC
RLCC
⋅ →
∑
,
,
, / crp cropl
crp cropl
crp cropland crp
HA DP CRPS YLD
= ⋅
19. Multi Stage Approach for Eco-City and EIP Planning
③Project Design
②Spatial-scope
Land use zoning
/network design
・ land use distribution
patterns
・ local energy network
・location of core
developments
①Macro-scope ・ population, industries
・ core developments
・ energy locality
Alternative
future vision
・ zoning and regulation
・ district planning
・key industries
Core projects for
revitalization
( )
なりゆきシナリオ
LNG立地シナリオ
産業振興シナリオ
環境産業共生シナリオ
Feasibility Study
Future frame
19
20. 20
Future Simulation for Alternative Scenarios
20
0
100
200
300
400
500
600
700
2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
億円
Local GDP
なりゆき
LNG立地
産業振興
環境産業共生
Temporary growth
for construction
100 mil US$ by LNG base
construction and operation
Additional 110 mil US$ by
industrial locations
Additional 70 mil US$
effects by green growth
0
2,000
4,000
6,000
8,000
10,000
2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
人
Population
なりゆき
LNG立地
産業振興
環境産業共生
Limited population
effects by LNG base
Population keeping with
industrial locations
Population recovery by
green growth
なりゆきでは2050年
に5千人を割る
Bau
LNG Base
Indus.Location
Green Growth
Bau
LNG Base
Indus.Location
Green Growth
Mil
US
$
22. 22
SDG Piliot Projects from Local Energy Policies
Forestory Restoration
)
Energy education
Local Energy
Governance
Low carbon
town planning
Stadt Werke
23. OUTLINE
1) Challenges for cities and metropolises
low carbon society, circularization of resources
resilience, rapidly aging society
cultural preservation
2) Quantification models for sustainable
urban planning
integration of different environmental flow
technology and social solution system
circularization city, smart city, compact city
green growth innovation
3) Cases and future targets 23
24. 24
Newest Smart Community underway in Fukushima
JAPAN
Fukushima
Shinchi Town
Shinchi Town,
Soma-FutabaRegion, FukushimaPrefecture
Population:8,247 / Households:2,754 /
Area: 46.35km2 (AsofJan.1st,2017)
24
SDGs from Local Energy Business
25. 25
1. Outline of Shinchi Town and Damage by the Earthquake
JAPAN
Fukushima
Shinchi Town
Shinchi Town, Soma-FutabaRegion, FukushimaPrefecture
Population:8,247 / Households:2,754 / Area: 46.35km2
(AsofJan.1st,2017)
2
5
26. 26
1. Outline of Shinchi Town and Damage by the Earthquake
Shinchi Town
Shinchi Town, Soma-Futaba Region, Fukushima Prefecture
Population: 8,200 / Households: 2,800 / Area: 46 km2 (Asof Jan.1st,2017)
2
6
Coal Power
Plant 200mil kw
28. 28
November 29th , 2013,
Basic agreement
among Petroleum
Resources Development
Co., Fukushima
Prefecture, and Shinchi
Town Government
Soma LNG base
Site: 20 ha
Tank: ground type
230,000 KL
storage tank 1 uni
Construction of National Project LNG base
29. LNG Power Plant
LNG base
Soma city
Newly located
industries
Plant
factories
Mega solar
Energy
managemen
t
BaU scenario in Shinchi town in 2030
Komagamine
To Natori
New town
around Station
Electricity
Heat
Cool
Gas(LNG)
29
30. x
Food industries
Data center
LNG Power Plant
LNG base
Soma city
Newly located
industries
Newly
located
industries
Plant
factories
To Natori
Energy
managemen
t
Electricity
Heat
Cool
Gas(LNG)
Integrative Energy System in Fukushima Shinchi town in 2030
Komagamine
Mega solar
Plant
factories
New town
around Station
30
31. 0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
Estimation of Alternative Future Recovery Scenarios
Urban
Industry
野菜
工場
[Mt-CO
2
/年]
50%減
Quantification of Impacts and Costs
Effects
of
Local
Energy
Management
Alternative Spatial Scenario
31
Estimation of CO2 Emission
Urban Agri-
cuilt.
+Green
Growth
BAU
+Compact
City
Green growth can double
the Carbon Efficiency
Industry
32. Environment-Economy-Society Integration Research Program
Socio Economic Environmental Forecast of Future Scenarios
8,218
8,060
7,302
6,401
6,027
5,619
5,229
4,842
8,218
8,122
8,039
8,214 8,279
8,075 8,033 8,030
3000
4000
5000
6000
7000
8000
9000
2015 2020 2025 2030 2035 2040 2045 2050
Population
(persons)
Total
Single
Spill
over
Local Schools
and Education
662 427 235
Sustainable Food
Industry and
Faming
621 558 62
ICT Industries 602 413 189
Local Energy
and Service
263 184 80
In-Migration to
the Town
415 386 29
Birth and Child
Care Support
303 219 84
Present Business 321 199 122
Social Growth Effects from BAU (in 2050)
BAU
Scenario
SDGs Scenario(tent.)
(population)
32
33. GHG emissions by sectors and contribution by LC measures
• Result of the sample scenario shows GHG emissions in Bogor City will be 2.3 times greater in
2030 BaU compared to 2013 level.
• The examples of low-carbon measures can reduce the emission by 25% in LCS scenario.
• The model can also shows contribution of the low-carbon measures in different sectors.
33
0
500
1000
1500
2000
2500
3000
3500
2013 2030
BaU
2030
LCS
Waste
Land-use change
Agriculture
EN Transport
EN Industry
EN Commercial
EN Residential
Monitoring
24%
EE device
29%
Modal shift
21%
Biofuel
14%
Recycling
12%
x 2.3
25%
reductions
34. Local Energy Based Urban Rebuilding Project in Fukushima
34
LNG Plant
Sustainable rebuilding projects through collaborative planning among
town planning, industrial development and local energy system
熱
電気
Strategic land
use transition
targets
Efficient local energy
management for a
local scale system
施設農業
都市
LNG
•Smart thermal and
electricity management
Energy Center
Multi sectoral energy management
/housing/commertial/agriculture
36. Green Innovation System from Local Energy Center
①
Communication Center
・ガラスの機械室 ・サイネージ設備
(イベント情報、まちのPRなども掲載)
②
〇Signs for Networks
・地中の熱導管を見せる
③Eco-City Innovation
Research(NIES and
Universities
・エネルギーまちづくりの社会イノベーション研究拠
点の運営
・模型、パネル・写真展示
、環境教育設備等の設置
・サイネージ設備
(商業施設テナント情報なども掲載)
②Local Infrastructure
Innovation;Pipe,
Wire, Fiver
・舗装(ルートライ
ン、サインプレート、
ハンドホール、な
ど)
〇Signs for Bldgs
・エネルギー供給・消費量や状況を
視覚的に分かりやすく説明
③ ④
⑤
⑥
熱導管・自営線ルート
36
①Visible Local Energy Center
➡Smart Local Information Center
地域エネループラント、計測装置
の見える化による実践教育機会と
しての活用・エネルギー消費モニ
ター・壁面太陽光パネル、緑化
37. Environment-Economy-Society Integration Research Program
Local Information
Staristics
・GIS Population,
Industries, (500mgrid)
<2010年、2015年>
Diagnoses of
Cities and
Regions
Goods/ Bads
Policy Scenario Design Process
for SDGs Model Cities and Regions
Dialogue
with
Local
Govern-
ments
Resea-
rch
Conso-
rtium
SDGs Local
Indicators138
37
Global SDGs
Indicators
BAU
Scenarios
Scoping
Focal Policy
Area /
Pilot Project
Design
Future
Scenario
Simulation
Policy
Inventory
SDGs Policy
Key
Indicators
38. エネルギーセンター
Regional Network
地域発電事業者
DR
Event Design of ADR
DR
BEMS
DR
BEMS
DR
BEMS
DR
Public Office Houses
DR HEMS
発電予測
DR
DR
●Collective Energy
Cloud Storage and
Control System
クラウド蓄電池制御
●Efficient Energy
Demand Management
複雑な法則や
パターンの抽出
消費電力データ
天気、イベント情報
大量データ・
情報の収集
A
B
C
D
分析
予
測
制
御
ガス消費グラフ
電力推移グラフ
熱量推移グラフ
発電機の
経済的運転に寄与
●Compact low
carbon neighborhood
transition
●Networking with
regional and locale
energy supply system
発電管理
設備管理
需給管理
Agricultureリ
学校
BEMS
DR
●Electric and Thermal
Energy Management
Toward Smart Urban and Industrial Energy Management
(Smart Electric and Thermal Demand Management System)
Hotel
Action Incentive
Price Control
FEMS
Demand Management
再生可能エネルギー
FEMS
House
DR
HEMS
DR
Agriculture
DR
House
HEMS
House
HEMS
38
39. 39
New Challenges for Modelling and Monitoring Research
Research challenge to compile innovative modelling and monitoring approach
Long Term
Integrated
Model for
Future Vision
Normative Targets
by General
Equilibrium Model
Technology and
policy Solution
Design Adapting
to Local
Characteristics
Future
Targets
Low Carbon
Solutions on
Local Contents
0
200
400
600
800
1000
1200
1400
2005 2010 2015 2020 2025 2030
CO
2
emissions
(MtCO
2
)
Agriculture, Forestry andFish
Transport, Energy
Transport, Freight
Transport, Passenger
Commercial
Residential
Other Manufacturing
Construction
Machinery
Non-Ferrous Metals
Other Non-Metallic Minerals
Glass Products
Other Chemical Products
Textiles, Wearing Apparel and
FoodProduct, Beverage andT
Paper, Pulpand Printing
Petrochemicals
Cement
Ironand steal
Electricity andHeat Productio
Energy Conversion
Environmental
Emission
BaU
Environmental Monitoring Information System
40. 40
Fukushima Shinchi Tablet Network
as a Social Monitoring and Activity Support System
役場
Local Energy Assist
Electricity senor:sensor
networked with server
and tablets
distributer
Energy
Consumtion
Activity
Ranking
Local Life Assist
Community
Information Assist
Emergency
Public
Service
Health
Bulletin
Board
GIS
Maps
Survey
Function
Dual-direction
information
sharing
system
Dual Direction ICT
Communication System
Electric Message
Multi user
information
sharing system
Frequent
questionnaire
system
Real time monitoring
Incentives for efficient
energy saving activities
Local
Event Information
sharing
among uses
41. 41
Monitoring sites of Bogor City in 2014-2015
Shopping mall is targeted in 2015FY
50 monitoring points in Bogor city
Sector Number of facilities Number of point
Government building 3 30
Residential house 3 12
Commercial facilities 2 8
Bogor city
42. ・Advanced internet security technologies effectively manage and protect the data
・Excellent recovery data collection capability
・Relationship analysis between human behavior and energy use
Production Line
AC
Lightings
Monitoring Electricity Data
1
Energy Meters
Collecting Electricity Data
2
Promoting Low Carbon
Activities/Behavior
4
Tablets
Data Center
(Indonesia/ Japan)
Analysis of collected data
3
Industrial
Residential Commercial Green Room
(Management center)
Visualization
Robust Data Traffic under
Uncertain Condition
System Design through
User Participation
Data access・ Analysis
Action framework of urban monitoring system in Asia
Sensor for human activity
Integrative Analysis of
Multi- Sectoral Data
42
43. -2
2
6
10
AC prediction Lighting prediction Receptacle prediction Refrigerator prediction
Sever prediction Monitoring total
CCROM BAPPEDA
Electricity
consumption
[kWh/hour]
Electricity
consumption
[kWh/hour]
-2
2
6
10
R² = 0.8909 R² = 0.9297
7 electricity consumption
peak in one week
During daytime
(on/off duty hour),
AC electricity is high
BAPPEDA was had only
3 peak in one week
Other week have 5peak
(weekday)
Electricity consumption
during holidays is lower
than during weekdays
Electricity Consumption by
server is high throughout
the monitoring period
2015/8/1 2015/8/2 2015/8/3 2015/8/4 2015/8/5 2015/8/6 2015/8/7 2016/5/1 2016/5/2 2016/5/3 2016/5/4 2016/5/5 2016/5/6 2016/5/7
Holiday
(Sunday)
Holiday
(Saturday)
Holiday
(Saturday-Sunday)
AC consumes a lot of
electricity
Analysis Status – Prediction result for Commercial and Public
43
44. 5
0
1000
2000
3000
4000
5000
6000
2013 2025
BaU
2025
CM
GHG
emissions
(ktCO2eq)
Land use change Waste management
Energy - Transport Energy - Industry
Energy - Commercial Energy - Residential
Projected GHG emissions
Contribution
to emission
reduction
Conversion of Fuel Oil to Gas for
Public Transportation: 21ktCO2eq
Bus Rapid Transportation System,
Pedestrian Facilities, and
Bicycle Track: 398ktCO2eq
City Of Park: 57ktCO2eq
LED for Street Lamp,
Green Building Concept, and
Eco-campus: 343ktCO2eq
Renewable energy: 250ktCO2eq
Waste collection and recycling:
47ktCO2eq
Industry energy efficiency
improvement: 47ktCO2eq
From “Model Low Emission City”
-21%
技術モニタリングシステムの活用①低炭素シナリオ
• Conventionally, local scenarios are developed with limited statistical data and “default”
parameters from national or international information.
• Our approach combines monitoring of local activity and modeling so that we can propose
the most suitable mitigation scenario and Action plans for the city/region.
Mitigation
potential
in 2030
Roadmap and
investment
towards 2030
Actions to
introduce the
measures in 2030
The model to project future scenarios: ExSS/AFOLUA
Population
Industry
Transport
Agriculture
Waste
Energy
Demand
Energy
Supply
Land use
and
Forestry
GHG
emissions
Energy
technologies
Statistical information Current environmental initiative
Locally suitable
mitigation scenarios
Energy Monitoring
Transport Monitoring
• Transport structure
• Vehicle speed
• Fuel efficiency etc.
• Current and future
energy consumption
pattern
• Energy saving
potential
44
44
45. Green Solutions for Sustainable Future
45
Smart Local Energy Smart Mobility
Smart Healthy
46. Visualize traffic congestion and travel time data
by using several smart phones as GPS sensor on vehicle.
Goal: Eco-friendly and More Comfortable City
46Traffic monitoring plan
Phase1
Phase2 : Calculate traffic volume Phase3 : Suggest Environ impact in traffic congestion
Visualize traffic congestion
With CCTV With environment sensor
Data Oriented
Innovation Center
Smartphone
(Android)
・Public Bus (TransPakuan)
■Schedule (Tentative)
1.Preparation (~Feb,2015)
2.App. Installation
3.Monitoring (Mid. of Mar)
4.1st Report (End of Mar)
App.
Smartphone App.
GPS
sensor
The target: 20 vehicles
<Target Vehicle>
<Sensing> <Collection and output > <View>
・Positioning info.
・Time and speed
※to be arranged
Traffic data
with GHG info.
46
47. Future Smart City Design for Fukushima
新地駅周辺スマートコミュニティ事業(2019年構築
イノベーションによる脱炭素地域エネルギーモデル(~2022年)
将来ビジョン:持続可能な環境エネルギーまちづくり: 脱低炭素地域エネルギーモデル(ユーティリティ3.0)(2023年~)
(3)Wind /solar power generation (Main source of power
generation) Micro grid and use in Shichi Station area
(2)Low carbon regional mobility model (CASE)
(1)CEMS depends on
DR·optimized energy system (AI)
Shinchi Energy Center
Shinchi
Station
47
48. Future Design for Fukushima Circulating
Ecological Sphere
新地駅周辺スマートコミュニティ事業(2019年構築
イノベーションによる脱炭素地域エネルギーモデル(~2022年)
将来ビジョン:持続可能な環境エネルギーまちづくり: 脱低炭素地域エネルギーモデル(ユーティリティ3.0)(2023年~)
(3)Wind /solar power
generation Micro grid and use in
Shichi Station area
(2)Low carbon regional
mobility model (CASE)
(1)CEMS with AI
support Demand
Optimization Energy
System
Shinchi Energy Center
Shinchi
Station
48
49. 49
Customer
benefits
Copyright 2015 FUJITSU LIMITED
Any particle data can be stored in a centralized DB and visualized.
Environmental Monitoring : GREENAGES
Flexible system design enables the system operators to easily add the parameters
by themselves.
Accumulated data enables business owners to predict the causes of exceedance
trend and/or specific situation and to begin working on it.
DB
Sensing
smell
air
water
Analysis
Visualization
Collection
51. Interactive Eco-policy Planning System in Asia
Fukushima Shinchi
Township National Institute for Env. Studies
Simulation for
recovery roadmap
復興まちづくりの
シミュレーション
Planning for
Sustainable Future
51
Energy Assist
Community
Information Assist
Life Assist
Community Assist Tablet Network
Local
Needs
Regional
Environment
Information
Urban Spatial
Analysis
Local
environment
diagnosis
Integrated
Modelling
Future scenario
assessment
Tech. and policy
inventory
-low carbon tech
-circulation tech
-industrial symbiosis
-policy / regulation
-land use control
52. Environment-Economy-Society Integration Research Program
Discussion materials for Interactive Simulation
2019 4-
Preparation
Stakeholder Meeting Research Team
2019 9
1st Stakeholder
Meeting
2019 10-11
2nd Stakeholder
Meeting
2019 12-2020 1
3rd Stakeholder
Meeting
2020 1-2 Green City Symposium focusing citizen participation
•Sharing scenario storylines and
quantification tools
•Local data base design
・Preparatory discussion
• Definition of Scenario Scope
• Choice of Focal Policy Area and Tech
• Participation Design
2019 07 Revision of Localized Green Future Scenarios for Bogor City 2030, 2050
-08 Preparation of Stakeholder Workshops, Planning of Participation and Scope
•Model Simulation
(BAU)future
•Focal Scope and
Technology spectrum の検討
• BAU Future scenario output
• Focal Policy Area Options (Household
Energy/ Transportation / Waste)
• SDGs Future Scenario
•Quantification of alternative
scenario simulations for focal
policy fields and technology
options
•Alternative Scenario design and
simulation for quantification
• Sustainable future scenarios
• Priority setting among scenarios
• Extension toward action plans
Interactive Scenario Simulation in Fukushima
52
53. 53
Innovative Modelling and Monitoring Research Project
Dual Direction Low Carbon Monitoring
Information System
Long Term
Short Term
Integrated
Model for
Future Vision
Normative Targets
by General
Equilibrium Model
Technology and
policy Solution
Design Adapting
to Local
Characteristics
Future
Targets
Low Carbon
Solutions on
Local Contents
0
200
400
600
800
1000
1200
1400
2005 2010 2015 2020 2025 2030
CO
2
emissions
(MtCO
2
)
Agriculture, Forestry andFish
Transport, Energy
Transport, Freight
Transport, Passenger
Commercial
Residential
Other Manufacturing
Construction
Machinery
Non-Ferrous Metals
Other Non-Metallic Minerals
Glass Products
Other Chemical Products
Textiles, Wearing Apparel and
FoodProduct, Beverage andT
Paper, Pulpand Printing
Petrochemicals
Cement
Ironand steal
Electricity andHeat Productio
Energy Conversion
Back
Casting
Environmental
load
BaU
・・・
Present
Low Carbon Monitoring System
54. 54
Quantification System of Cities
for
Smarter Planning to Compile
Green Technologies, Social
Systems with Local Resources
To bring
Creativity and Sustainability
to the Society
55. 55
List or related publications
• Yong Geng, Fujita Tsuyoshi, Xudong Chen; Evaluation of Innovative Municipal Solid Waste Management
through Urban Symbiosis: A Case Study of Kawasaki, Environmental Sci and Tech., 2009 (revised)
• Rene Van Berkel, Tsuyoshi Fujita, Shizuka Hashimoto, Minoru Fujii;Quantitative Assessment of Urban and
Industrial Symbiosis in Kawasaki, Japan, Environmental Science & Technology , Vol.43, No.5, 2009 ,pp.1271-
1281,0129.2009
• Rene van Berkel, Tsuyoshi Fujita, Shizuka Hashimoto, Yong Geng;Industrial and Urban Symbiosis in Japan :
Analysis of the Eco-Town Program 1997-2006;Journal of Environmental Management, vol.90,pp.1544-
1556,2009
• Shizuka Hashimoto, Tsuyoshi Fujita, Yong Geng, Emiri Nagasawa; Achieving CO2 Emission Reduction
through Industrial Symbiosis: A Case of Kawasaki , Journal of Environmental Management, 2008 (submitted)
• Yong Geng,Qinghua Zhu, Brent Doberstein,Tsuyoshi Fujita; Implementing China’s Circular Economy
Concept at the Regional Level: a review of progress in Dalian, China, Journal of Waste Management,
vol.29,pp996-1002,2009
• Yong Geng, Rene Van Berkel , Tsuyoshi Fujita ;Regional Initiatives on Promoting Cleaner Production in
China: A Case of Liaoning, Journal of Cleaner Production, 2008 (submitted)
• Zhu Qinghua, Yong Geng, Tsuyoshi Fujita , Shizuka Hashimoto ;Green supply chain management in leading
manufacturers: Case studies in Japanese large companies, International Journal of Sustainable Development
and World Ecology, 2008 (submitted)
• Yong Geng, Pang Zhang, Raymond P. Cote, Tsuyoshi Fujita;Assessment of the National Eco-industrial Park
Standards for Promoting Industrial Symbiosis in China, J. of Industrial Ecology, Vol.13, No.1, pp.15-26, 2008
• Looi-Fang Wong, Tsuyoshi Fujita, Kaiquin Xu; Evaluation of regional bio-energy recovery by local methane
fermentation thermal recycling systems, Journal of Waste Management,vol.28, pp.2259-2270, 2008
Thank you for your Attention