Catherine Stevens, Project manager and GIS expert, GIM

NACLIM annual meeting – 1/10/2013 1

North Atlantic Ocean climate variability and its impact on heat stress exposure in urban areas: case studies and user requirements

Catherine Stevens,Project manager and GIS expert, GIM

Agenda

• UHI and mapping heat impact on health: brief reminder

• Selection of 3 end users: short description

• June 2013 - 1st end user: Berlin and Antwerp

• September 2013 - Meeting the 3rd end user: Almada

• Work in progress and planning

NACLIM annual meeting – 1/10/2013 2

Agenda

• UHI and mapping heat impact on health: brief reminder

• Selection of 3 end users: short description

• June 2013 - 1st end user : Berlin and Antwerp

• September 2013 - Meeting the 3rd end user : Almada

• Work in progress and planning

NACLIM annual meeting – 1/10/2013 3

UHI prediction

CMIP5

UrbClim

socio-economic

health effectsheat stress exposurestratified by population, housing conditions, etc…

city selection

observations

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UHI and mapping heat impact on health

• Heat stress High temperatures and humidity stress the body's ability to cool itself, and heat illness becomes a special concern during hot weather.

• Some factors increase the risk of heat stress– Old people– Single– Sick– Being hospitalized– …

• Heat stress depends on several factors

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UHI and mapping heat impact on health

UHI and mapping heat impact on health

• Climatic parameters– Temperature (e.g. apparent max t°) and humidity– Temperature variability (day max t°, night min t°, interval, duration)– Wind speed and direction…

• Urban morphology parameters– City centre vs residential area– Green area and water place– Open space, street canyon– Buildings variables (material, albedo, orientation…)…

• Demographic, socio-economic and health parameters– Age and gender– Marital Status– Economic status and educational level– Health conditions, medication and disease…

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UHI and mapping heat impact on health

Results of Urban Heat Island model

+Exposure indicators

(Climatic, Urban morphology, Demographic / Socio-economic, Health)

Exposure Maps

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UHI and mapping heat impact on health

• Indoor thermal condition in urban heat island – development of a predictive tool, Parham A. Mirzaeia, Fariborz Haghighata

NACLIM annual meeting – 1/10/2013 8

UHI and mapping heat impact on health

• Map of the statistical district of Melbourne showing the weighted vulnerability index for each postal area, on hot days

– Combined demographic, socioeconomic, health, environmental variables vulnerability index

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http://www.hindawi.com/journals/ijpr/2012/518687

Agenda

• UHI and mapping heat impact on health: brief reminder

• Selection of 3 end users: short description

• June 2013 - 1st end user : Berlin and Antwerp

• September 2013 - Meeting the 3rd end user : Almada

• Work in progress and planning

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Selection of 3 end users

• Selection of number of relevant stakeholders– Interested in benefiting from an analysis of the impacts of

climate change on their urban dimension

Three European cities – Antwerp (BE) – Berlin (DE) – Almada (PT)

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Selection of 3 end users

• Antwerp (BE)− Major port − Population density 2,500/km2

− 20% green and blue urban areas − Maritime temperate climate

• Berlin (DE) − Metropolis counting 3.5 million inhabitants− Population density 3,700/km2

− 20-29 % green and blue urban areas − Warm-Summer Continental climate

• Almada (PT)− Small city densely populated− Nearby Lisbon metropolis − Population density is 2,355 / km2

− Mediterranean climate and close to Atlantic ocean

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Agenda

• UHI and mapping heat impact on health: brief reminder

• Selection of 3 end users: short description

• June 2013 - 1st end user : Berlin and Antwerp

• September 2013 - Meeting the 3rd end user : Almada

• Work in progress and planning

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June 2013 - 1st end user : Berlin and Antwerp

• Themes and services identified– Scenario linked to urban planning: the effect of UHI today and

in the future on urban planning– Scenario using existing urban plans/projects

• Impacts of green roofs linked to green roof potential map/plan (2030-2040)

• Impacts of change albedo (reflectivity) of buildings (roofs…)• …

– Scenario using projected population figures• Densification population and new settlements • Vulnerable population (school and old people)• …

– Impact of city expansion on climate change (e.g. projected LULC)

NACLIM: Almada end-user workshop - 24-25/09/2013 14

June 2013 - 1st end user : Berlin and Antwerp

• Time frame to be used in simulation are – Current situation (2000-2010)– Mid term (2030-2040) – Long term prediction (2100)

• Resolution vs extent– Larger extent (full city) with 250 m resolution– Smaller extent (part of city) with 100 m resolution

• Seasonal studies• Summer• “Winter”

NACLIM: Almada end-user workshop - 24-25/09/2013 15

June 2013 - 1st end user : Berlin and Antwerp

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Agenda

• UHI and mapping heat impact on health: brief reminder

• Selection of 3 end users: short description

• June 2013 - 1st end user : Berlin and Antwerp

• September 2013 - Meeting the 3rd end user : Almada

• Work in progress and planning

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September 2013 : Almada end user workshop

• Themes and services identified– Identify hotspots in city

– Population exposure to heat waves• For ex. Last summer heat wave (2013)

– Prediction/projection for 2100 as a help to downscale adaptation

– Possible to identify 3 spots in the city for high resolution study to make diagnose out of the scope of NACLIM

NACLIM: Almada end-user workshop report - 24-25/09/2013 18

September 2013 : Almada end user workshop

• Almada meteorological station visit

NACLIM: Almada end-user workshop report - 24-25/09/2013 19

Agenda

• UHI and mapping heat impact on health: brief reminder

• Selection of 3 end users: short description

• June 2013 - 1st end user: Berlin and Antwerp

• September 2013 - Meeting the 3rd end user: Almada

• Work in progress and planning

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Work in progress

• UHI modelling: UrbClim pre-processing input data– Variables/parameters

• Current work :– Planar area Index (PAI): proportion of area covered by buildings per

grid cell

– Frontal area indexes (FAI): area of buildings projected into the plane normal to the incoming wind direction and is a function of orientation per grid cell

– Average building height weighted with the building area and its variance

– Sky view factor (SVF)

• Outstanding work:% urban land use, land use type, % vegetation …

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Work in progress

• Berlin end-user case

– Available data• 3D building layers• Street network

– Study extent = Vito grid• Not full building coverage

– Extrapolation of PAI and FAI Evaluation of relationship at 1km resolution between EEA SS and PAI/FAI

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Work in progress

• PAI and EEA SS

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Work in progress

• EEA SS and PAI Relationship

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0 10 20 30 40 50 60 70 80 90 1000

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f(x) = 0.00153368397809504 x² + 0.203927167954814 xR² = 0.942332312061516

EEA SS

PA

I

Work in progress

• FAI and EEA SS

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Work in progress

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• EEA SS and PAI Relationship

0 10 20 30 40 50 60 70 80 90 1000

5

10

15

20

25

f(x) = − 0.000450697046580714 x² + 0.19289286380601 xR² = 0.896231835405797

EEA SS

FA

I

Work in progress

• PAI Extrapolation on the full coverage

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Planning

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NACLIM: Almada end-user workshop - 24-25/09/2013 29

Questions?

Don’t hesitate to ask!

GIM nv/saResearchpark Haasrode 1505

Interleuvenlaan 5B-3001 Leuven (Heverlee)

tel: +32 16 40 30 39fax: +32 16 40 69 39e-mail: [email protected]

website: www.gim.be

The research leading to these results has received funding from the European Union 7th Framework Programme (FP7 2007-2013), under grant agreement n.308299NACLIM www.naclim.eu

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