magic – managing air for green inner cities
TRANSCRIPT
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Managing Air for Green Inner CitiesUK Engineering and Physical Sciences
Research Council
Grand Challenge: Future Cities: engineering approaches that
restore the balance between engineered and natural systems
MAGIC
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The ‘zero-zero’ goal
Cities with no air pollution and no heat-island by 2050
Use natural ventilation to cool buildings
fromthis
tothis
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The ‘zero-zero’ goal
Cities with no air pollution and no heat-island by 2050
5 year, £4.1M programme, 2016-202130 Post-doctoral person years
Air quality and temperature are measurable and universal,providing clear metrics and proxies for urban ‘quality’; they areeconomically and socially important: health costs in theUK £10-20B p.a.
Results, capabilities (including code) will be made freelyavailable
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What MAGIC will deliver
A completely new tool for urban planners and regulatory authorities based on a unified system MAGIC– for long term planning, operational management, emergency
response– new generation computational modeling, adaptive
observation technologies, integrated cost benefit model
• System that harmonises the built and natural environment, providing estimates– for health, social & carbon costs, impacts of climate change
• Integrated user and research community with the capacity to continue after the end of the grant: MAGIC Circle
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Time and spatial resolution
Large domain, local detailEmergency response
Daily lives Planning
minutes - days hours - months years - decades
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Initial PDRA appointments2-year tenure
• Cambridge: – Building ventilation (DAMTP/CUED): Megan Davies Wykes– Building energy performance (DAMTP/Arch): Jiyun Song– Sensor deployment (Chemistry): Shiwei Fan– ATHAM Fluidity (Geography): James O’Neill
• Imperial:– Fluidity development: Fangxin Fang– Data assimilation and sensor optimisation: David Fairburn– Building modelling (ICL/CAM): Laetitia Mottet– Reduced order modelling: Dunhui Xiao– Street canyon and exposure modelling: Huw Woodward
• Surrey: – Wind tunnel and numerical modelling: William Lin
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System components
Management and decision support system
ATHAM - Fluidity Reduced order models
Economics - Cost-benefit model
Technical data Wind tunnel and salt bath experiments Socio-economic data
Integral models
Physics
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London South Bank University
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Sensor network
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Fluidity model
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The way forward• Aim to produce a beta version of the whole system by middle of
2018• To include– Fluidity model (ICL) supported by building ventilation studies (CAM) and
wind tunnel models (Surrey)– Validated against field measurements at one test site– Fast running models (reduced order and integral)– Cost-benefit model
• Work on deficient/additional aspects in second half of the project• Cost-benefit model• Decision support system
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MAGIC Partners2016-2021