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Projecting 2100 urban growth to assess urban climate changes on Toulouse urban area (France): combining
scenarios and land change / climate models
T. Houet, Valéry Masson, Marie-Pierre Moine, Colette Marchadier, Marion Bonhomme, Geneviève Bretagne
To cite this version:
T. Houet, Valéry Masson, Marie-Pierre Moine, Colette Marchadier, Marion Bonhomme, et al.. Pro- jecting 2100 urban growth to assess urban climate changes on Toulouse urban area (France): combining scenarios and land change / climate models. GLP-OSM (Global Land Project Open Science Meeting), Mar 2014, Berlin, Germany. 159, pp.2180 - 2192, 2011. �hal-02158489�
P ROJECTING 2100 URBAN GROWTH TO ASSESS URBAN CLIMATE CHANGES ON T OULOUSE URBAN AREA (F RANCE )
COMBINING SCENARIOS AND LAND CHANGE /CLIMATE MODELS
T. Houet1, V. Masson2, M.-‐P. Moine2, C. Marchadier2, M. Bonhomme3, G. Bretagne4
1 GEODE – Geography of Environment, UMR 5602 CNRS/UTM, Université de Toulouse, 5 al. Machado, 31058 Toulouse, France
2 Météo-‐France, CNRM-‐GAME, 42, Av. G. Coriolis, 31057 Toulouse Cedex 1, France
3 LRA, ENSA Toulouse, 83, rue ArisSde Maillol, BP 10629, 31106 TOULOUSE CEDEX 1
4 Toulouse Urban Planning Agency, Le Belvédère -‐ 11 boulevard des Récollets, CS 97802 -‐ 31078 TOULOUSE Cedex 4
CONTEXT AND OBJECTIVES
Context
• Build a mulSdisciplinary and integrated modeling plaZorm to simulate urban processes over the XXIe century : the ACCLIMAT PlaZorm.
• Propose city projecSons under various urban scenarios and assess their impacts depending on the climate change.
• Produce relevant indicators to evaluate these city projecSons and support sustainable urban planning
Challenges
• MulRdisciplinary : ACCLIMAT project involves various research field areas: economy, geography, architecture, building materials, meteorology, climate, urban planning.
• Integrated : The PlaZorm connects models and. This requires to overcome some gaps:
scienSfic concepts, modeling approaches, compuSng languages, heterogeneous scales…
• Scenario-‐projecRons: Consistent scenarios are built based on worldwide economic trends, regional socio-‐economic context, urban planning, building regulaSons and technology
trends. These scenarios are simulated under different climate change context.
RESULTS
WEBSITE
hWp://www.cnrm.meteo.fr/acclimat/?lang=en
Comparison of the simulated scenarios
Impacts on energy consumpRon
REFERENCES
Houet T. and Pigeon G. (2011), Mapping Urban Climate Zones And QuanSfying Climate Behaviors -‐ An ApplicaSon On Toulouse Urban Area (France),
Environmental PolluSon, Vol 159, Iss 8-‐9, 2180-‐2192
Masson V., Marchadier C., Adolphe L., Aguejdad R., Avner P., Bonhomme M.,
Bretagne G., Brioier X., Bueno B., de Munck C., Doukari O., Hallegate S., Hidalgo J., Houet T., Lemonsu A., Moine M.P., Morel T., Pigeon G., Salagnac J.L., Zibouche K., (Submiied). AdapSng CiSes to Climate change: a systemic modelling
approach, Urban Climate.
Moine et al. (2012) A mulSdisciplinary modeling plaZorm to draw possible futures of urban climate, ICUC8 -‐ 8th InternaSonal Conference on Urban Climate –
Dublin, Ireland.
Marchadier C., Houet T., Bretagne G, (2012) How to define and assess city
adaptaSon strategies? ICUC8 -‐ 8th InternaSonal Conference on Urban Climate – Dublin, Ireland.
Project founded by RTRA STAE
CONCLUSION
A very ambiSous project (mulSdisciplinary and integrated) :
• Combining forescasSng and backcasSng images of the future to wider the diversity of the scenario
• Developping a plaZorm to couple all urban and physical models and assess quanStaSve impacts on urban climate
• Coupling economical, geographical and architectural models for simulaSng long-‐term futures urban growth.
Key-‐triggers and futures stakes
• Urban management and policies to miSgate urban climate – urban tools exist but depends on poliScal will
• Future pressure on water supply and electricity have been highlighted
• It is essenSal to act soon, to change inhabitants energy habits and improve energeSc performance of exisSng buildings.
STUDY SITE: Toulouse urban area
PROJECT METHODOLOGY
Do we need to act soon?
Global warming = net gain. Decrease of heaSng > increase of cooling
Change of uses / habits = -‐30% (from heaSng) and divided by 2 or 3 (from cooling) Current city = main cause of energy waste
SCENARIOS
World economy
Urban planning
Building technology
Uses and habits
SCENARIOS
City modelling Urban sprawl
NEDUM + SLEUTH*
Urban climate Indices
Urban heat island
Energy consumpSon
Others..
Physical models Meso-‐NH TEB
Climate forcing
MODELLING ASSESSMENT
Urban
morphology
GENIUS
Coupling models within an unique plaZorm (Moine et al. 2012)
Urban planners Architects
Scientists Modellers Imagined
city
Modelled city
Numerical model approach
Narrative approach
1996-2010
The most attractive city 1.25 M inhabitants
+20 000 inhabitants.year +1 300 ha.year of urban Aerospace industry
Spatial extent: 84 x 94 km Spatial resolution: 100m
Combining backcasRng/forecasRng scenarios
Highly imaginaSve and quanStaSve impacts
Marchadier et al. (2012)
•Peak oil Impact
•Gas emission reduction policy
High Yes
Low No
Worldwide economic trends
•Peak oil Impact
•Gas emission reduction policy
High Yes
Low No
Worldwide economic trends
•Population size
•Unemployment
•Household incomes
Stable Stable Average
æ
æ
High
è
è
Low
Local socio-economics trends
•Population size
•Unemployment
•Household incomes
Stable Stable Average
æ
æ
High
è
è
Low
Local socio-economics trends
•Urban planning
•Green cover
•Urban shape
Low governance Preservation
Megalopolis
Efficient governance
Extension Polycentric
Land use
•Urban planning
•Green cover
•Urban shape
Low governance Preservation
Megalopolis
Efficient governance
Extension Polycentric
Land use
•Transportation mode
•Building processes
•Energy savings
Public Innovative
High Private
Traditional Low
Technology trends
•Transportation mode
•Building processes
•Energy savings
Public Innovative
High Private
Traditional Low
Technology trends
Building integrated scenarios à Coherency of assump9ons!
Linking scenarios driving
forces to model(s) input data
A set of 7 scenarios
1: ReacSve city 2: Thinking city 3: Dynamic city 4: Green city 5: Harmful city 6: Passive city
7: Business as usual
Sc. 6 Sc. 1
N°1 Reactive N°2 Thinking N°3 Dynamic N°4 Green N°5 Harmful N°6 Passive N°7 BAU
+2 000
0 -500
Gain of urban areas (red)
compared to 2010 (grey)
Urban sprawl
Human density
Evolution of human density (2100-2010) in the city centre
Urban heat island
Transportation
Mean distance (per month / pers) done for working
Types of blocks
∆T° from 2010
Discontinuous pavilion Continuous pavilion Discontinuous block Continuous block Ancient center High-rise tower Industrial building
Present Sc. 3
Sc. 1, 2 and 4 Sc. 5
Sc. 6 and 7
N°1, 2, 3 et 4
N°5 Néfaste
N°6 Passif
N°7 Fil de l’eau
Future city (2100)
N°1, 2, 3 and 4
N°5
N°6 N°7
2010
Present Future : +2°C Future : +4°C Future : +6°C Present Future : +2°C Future : +4°C Future : +6°C Heating
Cooling
Climate change forcing
Kwh/m²/year
Urban sprawl = UHI from +1 to +3°C Global warming = +2 to 6°C
Future urban climate on Toulouse = from +3°c to +9°C
Impacts on urban climate
Growth GrowthCrisis
Nb of urban patches (x1000)
Urban areas in 2040 – 6 scenarios
Urban areas in 2100 – Sc. 1,2 & 5 (peak oil crisis in 40’s)
PotenSal urban areas in 2100 similar to those in 2040: importance of the 2010-‐40 period
Controlling the urban density (type of blocks) highly depends on urban acts during the
2010-‐2040 period (not shown)
