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

4. Globally Warming Future 4 出典： IPCC「Approved Summary for Policy Makers」 2013/09/27

5. Extreme Weather worldwide(2018,July) 5 ※1: https://www.data.jma.go.jp/gmd/cpd/monitor/weekly/ ※2: https://public.wmo.int/en/media/news/july-sees-extreme-weather-high- impacts

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 $

21. 21  2010年から2050年を対象に集約化計算を4シナリオを実施。  計算の結果、シナリオ β-1 の拠点数は 13箇所、シナリオ β-2の拠点数は3箇所と選定。  地域交通事業は、αからβ-2にかけて要件を達成するメッシュが増加するとともに対象となる人口・従業者も増加する。  地域エネルギー事業は、β-2が事業導入の対象床面積が最も大きい。 ① 2050年BAU ② 2050年α ③ 2050年β-1 ④ 2050年β-2 22 22 19 16 9 9 8 7 4 4 4 5 3 3 3 4 0 5 10 15 20 25 30 35 40 0 0 0 0 市街化区域内における地域交通事業導入の対象人口（万人）人口（対象）従業者数（対象）人口（対象外）従業者数（対象外） 69 21 241 33 281 112 382 738 586 531 0 200 400 600 800 1000 1200 2050年(β-2) 2050年(β-1) 2050年(α) 2050年(BAU) 13拠点地区内における地域エネルギー事業導入の対象延床面積（万m2）戸建（対象）集合（対象）業務（対象）対象外 Land Use and Transportation Management Model

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

27. 27 27 2011, 03.11, ＥａｓｔＪａｐａｎ Great Earthquake

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

35. 35 Shinchi Smart Energy Center as a Symbol of Fukushima Rebuilding as of Oct. 2018

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 ＤＲＢＥＭＳＤＲＢＥＭＳＤＲＢＥＭＳＤＲ Public Office Houses ＤＲＨＥＭＳ発電予測ＤＲＤＲ ●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ＡＢ 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ＢＥＭＳＤＲ ●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 ＤＲＨＥＭＳＤＲ 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

50. Data utilization for action: Touch Point 50

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

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