カテゴリー Ⅰ 日本建築学会計画系論文集第 82 巻第 737 号, ,2017 年 7 月 J. Archit. Plann., AIJ, Vol. 82 No. 737, , Jul., 2017 DOI

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1 カテゴリー Ⅰ 日本建築学会計画系論文集第 82 巻第 737 号, ,2017 年 7 月 J. Archit. Plann., AIJ, Vol. 82 No. 737, , Jul., 2017 DOI 集約型都市構造シナリオの概要と温熱環境評価の導入将来の人口縮退下における集約型都市構造シナリオの設定とその評価その1 IMPACT OF FUTURE COMPACT CITY SCENARIOS ON THERMAL ENVIRONMENT Evaluation of compact city scenarios under future population decline Part 1 高取千佳 *, 五十嵐千寛 **, 中浦寛介 *** *, 玄英麗 Chika TAKATORI, Chihiro IKARASHI, Hirosuke NAKAURA and Yingli XUAN Towards a population decline society along with the progress of low birthrate and longevity, the concept of a compact city is gathering attention for urban sustainability and a higher quality of life. However, there are no guidelines available for the specific population size and density. Several compact city scenarios for Aichi Prefecture were developed by considering population structure, disaster prevention/mitigation and infrastructure condition. This study is particularly to evaluate the impacts of urban compactification from the viewpoint of urban thermal environment in the summer of the 2050s by using a regional atmospheric model, WRF. Keywords : Population Decline, Hierarchical Urban Core, Compact City, Thermal Environment,,, 1) (1) (2) (3) 2) 3) 4),5) 6) ) 8) * ** *** 名古屋大学大学院環境学研究科助教博士 ( 工学 ) 大林新星和不動産修士 ( 工学 ) 名古屋大学大学院環境学研究科大学院生 Assist. Prof., Graduate School of Environmental Studies, Nagoya University, Dr. Eng. Obayashi-Shinseiwa Real Estate Co, LTD., M. Eng. Grad. Student, Graduate School of Environmental Studies, Nagoya University 1735

ࡉ ࡓ㒔ᕷ ẚ ศᯒࠊ ᐹ ࠋ ࠊ ᐦᗘ 㝵ᒙ Table 1 Hierarchical classification of urban core ᛶ ᇶ ࡋ 1㸧 ഛ ἣ㸦 Ỉ㐨 බඹ タ㸧ࠊ Urban 2㸧 ᆅಖ ᗘࠊ3㸧 ᐖ 㝤ᗘ ࡘ ホ౯ ࡓ ࠊᑗ Core Introduce the complex functions such as residential, commercial,

(Konan City Togo Cho) Central Commercial Base (Higashi-Ura Cho Akuhi Cho) Urban Zone (Okazaki City) Urban Interchange Base (Kasugai City) Central Residential Zone (Ofu City) Central Residential Base

タᐃࡋࡓ ࢩ 㒔ᕷᵓ㐀ࡀࠊᑗ᮶ ᬮ 㐍 క ᗈᇦ ᬬ ቃ ᙳ㡪ࡍ ࠊ㡿ᇦẼ WRF ࡓ ࢩ ࢩ ゎᯒ ホ౯ ࠋ Complement of urban cores/ main station and commercial facilities are located/ the functions such as medical care, welfare, and commerce which

2 ࡉ ࡓ㒔ᕷ ẚ ศᯒࠊ ᐹ ࠋ ࠊ ᐦᗘ 㝵ᒙ Table 1 Hierarchical classification of urban core ᛶ ᇶ ࡋ 1㸧 ഛ ἣ㸦 Ỉ㐨 බඹ タ㸧ࠊ Urban 2㸧 ᆅಖ ᗘࠊ3㸧 ᐖ 㝤ᗘ ࡘ ホ౯ ࡓ ࠊᑗ Core Introduce the complex functions such as residential, commercial, office, culture and inter change, and administrative functions/ Induce the intensive use of land Other expressions㸸symbol Core (Nagakute City) Central Base (Mihama Cho Matsukuwa Cho) Central Core (Konan City Togo Cho) Central Commercial Base (Higashi-Ura Cho Akuhi Cho) Urban Zone (Okazaki City) Urban Interchange Base (Kasugai City) Central Residential Zone (Ofu City) Central Residential Base (Ama City) Vitality Base (Owari Asahi City) Turnout Base (Iwakura City) Turnout Interchange Base (Yatomi City) Area Service District (Oguchi Cho) Lide Base (Seto City) ᮶ 2050 ᖺ௦ ᑐ ࡋ 㞟 ᆺ ࢩ タᐃࡍ ࠋ ࠊ௨ タᐃࡋࡓ ࢩ 㒔ᕷᵓ㐀ࡀࠊᑗ᮶ ᬮ 㐍 క ᗈᇦ ᬬ ቃ ᙳ㡪ࡍ ࠊ㡿ᇦẼ WRF ࡓ ࢩ ࢩ ゎᯒ ホ౯ ࠋ Complement of urban cores/ main station and commercial facilities are located/ the functions such as medical care, welfare, and commerce which are necessary for citizen s daily life are promoted/ Induce the intensive use of land District Core 㸰㸬ᑐ ᆅ ᮏ ឡ ᇦ ᑐ ᆅ ࡋࡓ㸦ᅗ 1㸧ࠋឡ ໃ Other expressions㸸associate City Base and City Area Base (Tahara City) Base Area Core (Toyota City) Turnout Base (Nagakute City Nisshin City) Secondary Urban Base (Chita City Ichinomiya City) District Base (Tokai City Inuyama City) Sub Core (Konan City) Local Commercial Base (Higashi Ura Cho) Local Service Base (Ama City) Citizen Information Service Vase (Miyoshi City),etc Ἑ ᥋ࡋࠊ ᮾ㒊 ᒣᓅᆅᖏࡀከ ᪉ࠊす㒊 ᖹᆠᆅ ࡀ㞟 ࡋ ࠋኴᖹὒ Ẽ ࡓ ࠊኟ 㧗 ᚩ ࡋ ࠊᑗ᮶ ᛂ ࡀồ 8) ᬮ క 㒔ᕷ㧗 ከ Ẽ ᑐࡍ 㐺 ࠋ ࡓࠊ ᒇᕷ 㒊ᆅ᪉ ࡍ 㒔ᕷ ࠊឡ ᒇ 㒔ᕷᅪ㒔ᚰ㒊 ᆅ᪉㒔 ᕷ ᚰ㒊ࠊ 㒊 ᒣ㛫㒊 38 ᕷ 7 㒆 14 2 Community Core Complement of District Cores/ functions such as the local self-government, welfare, interchange, and administrative facilities are promoted which is the center of the communities Other expressions㸸area Base (Okazaki City) Area Core (Toyota City) Life Interchange Base (Nagakute City Inasawa City 㸧 Community Base (Toyoyama Cho), etc యࡀ ࠋ య ࡋ 2020 ᖺ 7495 ࢡ 9)ࠊ2050 ᖺ 6856 ῶᑡ ࡎ ࡇ ࡀண ࡉ ࠊ ᅾ ῶᑡ ࡌ ᕷ ࡀᏑᅾࡋࠊ ῶᑡ ᑐ ࡋ ᣢ 㒔ᕷᵓ㐀 ࡀồ ࠋ Fig. 3 Histogram of urban cores and population density Table 2 Number of urban cores in each population density Fig. 1 Topography of Aichi prefecture 㸱㸬 ᐦᗘ 㝵ᒙᵓ㐀㒔ᕷ ẚ ศᯒ ࡌ ࠊ ᐦᗘ 㝵ᒙᛶ ࠊ ᕷ 㒔 ᕷィ ࢫࢱ タᐃࡉ 㒔ᕷ ẚ ศᯒ ᅗ 2 ᡭ㡰 ࡗࡓ ࠋឡ ࠊ2016 ᖺᗘ 6 Ⅼ 38 ᕷ 12 1 㒔ᕷィ ᇦ ࢫࢱ ࡀ ᐃ ࡉ ࠊࡑ ᑗ᮶ ᶆ ࠕᑗ᮶㒔ᕷᵓ㐀ᅗ ෆ 㒔ᕷ ഛ ᣐⅬ 㒔ᕷ (㒔ᕷᣐⅬ)ࡀ ࡉ ࠋ Fig. g 2 Flowchart of comparative analysis between urban core and population density 1736 Fig. 4 Distribution of urban cores and population density

1 ArcGIS 3 (1 km) 10) 2010 ( 3 2) ( 4) 3 2 10~40 /ha 54.

1 % ( 2) 4 100 /ha 50~100 /ha 40 /ha ( 3)40-100 /ha 60 %10-40 /ha 36.

40-50 /ha 50-100 /ha 100 /ha 110 /ha 1~40 /ha Table 3 Population

10~40 Center of Local District Core 40~50 City Urban Core 50~100

3 1 ArcGIS 3 (1 km) 10) 2010 ( 3 2) ( 4) ~40 /ha 54.9 % 40 /ha DID /ha 57.1 %100 /ha 16.1 % ( 2) /ha 50~100 /ha 40 /ha ( 3) /ha 60 %10-40 /ha 36.0 % ( 2) (DID /ha (DID )10-40 /ha ( 3) /ha /ha /ha /ha 100 /ha 110 /ha 1~40 /ha Table 3 Population density classification Types Density (people/ha) 1~10 Community Core 10~40 Center of Local District Core 40~50 City Urban Core 50~100 Center of Metropolitan Area 100~ Number Number Fig. 5 Number of stations Fig. 6 Number of interchanges in each mesh in each mesh Number Fig. 7 Number of bus stops Fig. 8 Area ratio of sewage system in each mesh in each mesh Number Level Fig. 9 Number of public Fig. 10 Level of green facilities in each mesh preservation in each mesh Fig. 11 Max immersion depth Fig. 12 Area ratio of landslide of Tsunami in each mesh danger zone in each mesh Fig. 13 Seismic Intensity Max seismic intensity in each mesh in each mesh 1737

4.1 ArcGIS 3 (1) 11) ( 5)( 6)( 7) ArcGIS 50( 8) 11) 1 ( 9) (2) 11) ( 2: 50 1: 50 )( 10) (3) 23 25 3: 3.0 m / 2: 1.7-3.0 m / 1: 0.3-1.7 m / 0: -0.

4 4.1 ArcGIS 3 (1) 11) ( 5)( 6)( 7) ArcGIS 50( 8) 11) 1 ( 9) (2) 11) ( 2: 50 1: 50 )( 10) (3) : 3.0 m / 2: m / 1: m / 0: -0.3 m( 11) 11) 50 ( 12) : 7- / 2: 6-7 / 1:5-6 / 0:-5( 13) 4.2 (1) (Case 1 4 (Case 2Case 5 (2050 ) 10) (Case 1) 1 1~10 /ha (Case 2 Case ( 14) Fig. 14 Methodology of population induction (Active Population Withdrawal Mesh ( AW)) (Passive Population Withdrawal Mesh ( PW)) (Population Induction Mesh ( PI)) AW PW PI 2050 AW PI (2) Case AWPWPI (Case 2) ~10 /ha (AW)10~40 /ha (PI) 0 0 1~10 /ha (AW) 3 2 (Case 3) ~40 /ha (AW) 40~100 /ha (PI) Case 3 Case (Case 4) (AW)

Table 4 Urban Compact Scenarios in Each Case 1~10 (people/ha) 10~40 (people/ha) 40~50 (people/ha) 50~100 (people/ha) 100~ (people/ha) Future Scenarios Viewpoints of aggregation Conservation Level 1

5 Table 4 Urban Compact Scenarios in Each Case 1~10 (people/ha) 10~40 (people/ha) 40~50 (people/ha) 50~100 (people/ha) 100~ (people/ha) Future Scenarios Viewpoints of aggregation Conservation Level 1 Infrastructure Development Situation Level 2 Green 3 Danger level of Disasters Stations Interchanges Sewage System Public Facilities Forest and Natural Park Tsunami Landslide Earthquake Number of Wasteland Meshes (Conversion Ratio from Urban Meshes to Wasteland Meshes) (Case 1) Present land use Population predicted value in (Case 2) Aggregation of people more than in community core level People in the area of 1~10 people/ha in 2050 are aggregated more than in the community core level If the number of the bus stops or interchanges is 0, mesh is not selected as the population destination If the sewage system is not developed, mesh is If the number of public facilities is 0, mesh is If the green conservation level is (Case 3) Aggregation of people more than in district core level People in the area of 1~40 people/ha in 2050 are aggregated more than in the district core level If the number of the train stations is 0, mesh is (Case 4) Disaster prevention/ mitigation People in the disaster danger area are aggregated in the safe area If the number of the train stations is 0, mesh is If the sewage system is not developed, mesh is If the green conservation level is If the sewage system is not developed, mesh is If the green conservation level is more than 2, population in the mesh are moved (AW) (Case 5) Prioritization of infrastructure and green conservation In addition to Case2, people in the lack of infrastructure and green preservation area are moved If the number of the train stations is 0, population in the mesh are moved (AW) If the sewage system is not developed, population in the mesh are moved (AW) If the number of public facilities is 0, population in the mesh are moved (AW) If the green conservation level is more than 1, population in the mesh are moved (AW) 1472 (10 %) 2938 (52 %) 1466 (31 %) 2683 (36 %) 1739

6 0 2 (Case 5)Case ~10 /ha (AW) 10~40 /ha (PI) (AW) Case 15 WRF 1 RCPRepresentative Concentration Pathways8.5 14) GFDL-CM3 RCP IPCC 5 15) RCP2.6RCP4.5 RCP6.0RCP8.5 4 RCP8.5 WRF 5 WRF ,13) WRF 120 km 120 km 3 1 km 1 km WRF Kusaka 16) Fig. 15 Number of meshes in population density WRF (Weather Research and Forecasting) WRF (NCAR National Center for Atmospheric Research) (NCEPNational Centers for Environment Projection) (NMM: Nonhydrostatic Mesoscale Model) (ARW: Advanced Research WRF) 12) WRF ver ARW Fig. 16 Flowchart of future projections (8 Kimura 13) Fig. 17 Computational domains 1740

7 5.2 11) 100 /ha 100 /ha 3 (Case 1) (36.6 /ha) (Case 1) (15 W/m 2 )(9 m) (Case 1) (15 W/m 2 ) ( 15 / 9 m) cal/cm 2 K s 1/2 ) ( ) (Case 0) 5.3 (1) (WRF ) WRF (Case 0) 1.5mWRF 2.0m WRF 2.72 Fig. 18 Case 2Case 1 Comparison of the diurnal variation in the monthly averaged air temperature at Nagoya between observation and WRF simulation (2) ( 2 m)case 0 (2010 ) Case 1 (2050 ) 1 Case 1 Case Fig. 19 Case 2Case 1 Diurnal variations of the space and monthly averaged air temperature in Aichi at 2 m height (3) ( 2 mcase 2Case 5 (2050 ) Case 1 (2050 ) Case 1 ( 8 1 ) Case 2 (2050 ) Case 3 (2050 ) Case 4 ( Case 5 (2050 ) Case 2Case 4Case 5Case 3 ( 4 ) Case 2Case 1 Case 4Case 1 Fig. 20 Diurnal variations of the differences in the space and monthly averaged air temperature in Aichi at 2 m height from Case1 (4) ( 2 m)case 2Case 5 Case 1 Case

Case 2Case 1 Case 4Case 1 Fig. 21 Diurnal variations of the differences in the space and monthly averaged air temperature in Nagoya at 2 m height from Case 1 Case 3Case 4Case 5 0.26 0.17 0.

2 (Case 3 ) (40-50 /ha 50-100 /ha ) Case 1 Case 2 32 Case 3Case 5 32 Case 4 32 Case 1 Case 2 - Case 1 Case 1 Case 2 - Case 1 Case 3 Case 1 Case 4 - Case 1 Case 3 Case 1 Case 4 - Case 1 Case5

8 Case 2Case 1 Case 4Case 1 Fig. 21 Diurnal variations of the differences in the space and monthly averaged air temperature in Nagoya at 2 m height from Case 1 Case 3Case 4Case (2)Case 3 Case 5 ( ( )Case 3 ( )Case 4 Case (5) 24 Case 1 Case ( 2 m ( /ha Case % Case 2 Case 5 Case (Case 3 ) (40-50 /ha /ha ) Case 1 Case 2 32 Case 3Case 5 32 Case 4 32 Case 1 Case 2 - Case 1 Case 1 Case 2 - Case 1 Case 3 Case 1 Case 4 - Case 1 Case 3 Case 1 Case 4 - Case 1 Case5 - Case 1 Fig. 22 Differences in the monthly averaged air temperature at 2 m height from Case 1 Case5 - Case 1 Fig. 23 Differences in the monthly averaged wind velocity at 2 m height from Case

9 case1 case2 case4 case5 Community Core Level (1040 people/ha) case1 case2 case3 case4 case5 Fig. 25 Histogram of population corresponding to air temperature at 2 m height 3132 Case 3Case /ha Case Case 2Case 5 Case 1 Case % District Core Level (4050 people/ha) case1 case2 case3 case4 case5 Urban Core Level (50100 people/ha) case1 case2 case3 case4 case5 Center of Metropolitan Area (100 people/ha) Case 4 Case 3 8) Case 3Case 5 Case Case 3 Case Case 1~Case ( 2 ( 25Case 3 Case 4 Case 1Case 2Case 5 Case Case 4. 1) 2) 3) 2050 WRF (1) Fig. 24 Frequency percentage of meshes by temperature at 2 m height (2)

10 2) 3) (3) 2050 WRF Case 2~Case 5 Case 3 Case ) 2) 3) 4) 5) 6) 7) 8) 9) 10) 11) 12) 13) 14) 15) 16) 17) 18) 1744

11 IMPACT OF FUTURE COMPACT CITY SCENARIOS ON THERMAL ENVIRONMENT Evaluation of compact city scenarios under future population decline Part 1 Chika TAKATORI *, Chihiro IKARASHI **, Hirosuke NAKAURA *** and Yingli XUAN * * Assist. Prof., Graduate School of Environmental Studies, Nagoya University, Dr. Eng. ** Obayashi-Shinseiwa Real Estate Co, LTD., M. Eng. *** Grad. Student, Graduate School of Environmental Studies, Nagoya University Towards a population decline society along with the progress of low birthrate and longevity, the concept of a compact city is gathering attention for urban sustainability and a higher quality of life. However, there are some problems: there are no guidelines available for the specific population size and density. And various evaluation points such as infrastructure development, green conservation, and disaster mitigation/prevention are not considered enough in the policy level. And the regional.environmental impact of the compact city policy is not thoroughly verified. In this study, the following three points were conducted. First, the hierarchical population density in prefecture level was examined by comparing to urban cores shown in the city planning master plans made in the local government of municipalities. The focused site is Aichi prefecture. The urban cores in the master plans had different scales from each other according to the scale of municipalities in the prefecture. As a result, four hierarchical population densities were obtained (10-40 people/ha: Community Core, 40-50: District Core, : Urban Core, and 100-: Center of Metropolitan area). According to this classification, to make the compact scenarios in prefecture level was enabled. Secondly, the methodology of setting several compact city scenarios for Aichi Prefecture were developed by considering evaluation indexes: population hierarchical structure, infrastructure condition, green conservation situation, and disaster prevention/mitigation. According to them, all meshes in Aichi prefecture were classified into Active Population Withdrawal Meshes (AW), Passive Population Withdrawal Meshes, and Population Induction Meshes (PI) and the population was moved from AW to PI on condition that the total number of population in 2050 was constant. As a result, five scenarios were set: (Case 1) Present land use, (Case 2) Aggregation of people more than in community core level, (Case 3) Aggregation of people more than in district core level, (Case 4) Disaster prevention/ mitigation, and (Case 5) Prioritization of infrastructure and green conservation. In the next phase of this study, the improvement of evaluation indexes such as industrial structure, farmland conservation, and preservation of historic city and the weighting processing between the evaluation indexes should be considered. Thirdly, the impacts of five urban compact scenarios were evaluated from the viewpoint of urban thermal environment in the summer of the 2050s by using a regional atmospheric model, WRF. As a result, the space and monthly averaged air temperature in Aichi at 2m height was lower in case 2~5 than case 1. However, the global warming impact was still stronger impact on thermal environment than that of compact scenarios. The meshes which have 100-people/ha: Center of Metropolitan area Level had the lowest air temperature in (Case 3) Aggregation of people more than in district core level scenario, in which the sea breeze from Ise bay had a cool effect on Nagoya city because the southern area of Nagoya city was set as grassland in case3. On the other hands, the meshes which had people/ha: Community Core Level or people/ha: Center of Local City Level had the lowest air temperature in (Case 4) Disaster prevention/ mitigation scenario and the ratio of population also had the lowest air temperature in Case 4. This showed that the scenario for disaster prevention and mitigation also had the effect of the improvement of hot environment. In the next phase of this study, the more integrated evaluation of regional environmental impact of compact city scenarios should be conducted. (2016 年 9 月 10 日原稿受理,2017 年 4 月 4 日採用決定 ) 1745

カテゴリー Ⅰ 日本建築学会計画系論文集第 81 巻第 721 号, ,2016 年 3 月 J. Archit. Plann., AIJ, Vol. 81 No. 721, , Mar., 2016 DOI

カテゴリー Ⅰ 日本建築学会計画系論文集第 81 巻第 721 号,667-674,2016 年 3 月 J. Archit. Plann., AIJ, Vol. 81 No. 721, 667-674, Mar., 2016 DOI http://doi.org/10.3130/aija.81.667 東日本大震災の被災市街地における新規着工建物による市街地空間形成と空間的特徴岩手県および宮城県の沿岸