Climate Exchange

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rban

ssues

the behaviours of the associated household/developer agents

using parameters such as the spatial distribution of households,

land rent, building rent, land demand and supply, and build-

ing floor demand and supply.

The model has been calibrated

with recent socioeconomic data at the district level (around 1

km grid). Next, we projected two different land-use scenarios:

compact city and dispersion. The two scenarios were produced by

calculating the equilibrium of housing location due to the change

of land-use policies (incentive) in both compact and dispersion

directions. For the two scenarios, we estimated the CO

emis-

sions, heat emissions from buildings and transport (road), the

green space ratio, building density and so on.

Following this, we simulated and compared the heat island

effect for the compact and dispersion scenarios by inputting all

the parameters of the two scenarios into an urban climate model.

Interestingly, the results showed that in the compact city case,

the urban heat island effect will decrease by 0.5 of a degree if the

suburban areas, where housing is moved from, are re-vegetated.

However in the dispersed city case, the heat island effect will

worsen, with a 0.5 degree increase due to both urbanization and

a decrease in vegetation in the suburban areas. Spatially explicit

land-use scenarios were only recently introduced as a part of

the Intergovernmental Panel on Climate Change’s global climate

modelling. However, as our preliminary modelling attempt

suggests, such scenarios would be more important for urban and

regional planners who need to look at specific local adaptation

measures against climate change. For achieving sustainabil-

ity, nothing is more important than the need for stakeholders

to come up with an appropriate plan with scientific knowledge

about possible risks.

Possible synergies between scenarios

Using the urban simulation model, we also analysed the possible

synergies between climate change mitigation and adaptation. We

considered a case where, as a climate change adaptation measure,

houses in the high flood risk area are moved. Then, in addition

to the compact city scenario, we assumed that electric vehicles

replace conventional cars and photovoltaic panels are introduced

as climate change mitigation measures.

The CO

emissions for the current business as usual (BAU)

and the above-mentioned adaptation/mitigation scenario suggest

that potential for a large reduction in CO

emissions exists in the

adaptation/mitigation scenario if a solar power plant could be

constructed in the high flood risk area that houses are moved from.

A sustainable future

We have created future land-use change scenarios with geographi-

cal distribution in Tokyo and tested them for climate change

measures. To support designing future sustainable cities, it will

be important to:

• Create an urban simulation platform that offers climate

risk information required for making cities more resilient

to climate extreme events with more advanced

meteorological modeling

• Support integrated assessments to deal with

complex impacts of extreme climate events and

other risks including earthquakes

• Provide policymakers with the implications of different

land-use scenarios based on various sustainability indicators.

Source: Yamagata et al. (2012)

The spatial distribution of CO

emissions showing

(a) BAU and (b) the mitigation/adaptation scenario

A comparison of the flooding risk between (left)

BAU and (right) the adaptation/mitigation scenario

Scenario (a) is ‘business as usual’. In the mitigation and

adaptation scenario (b), people avoid the high-risk areas,

achieving ‘compactness’ of the city

(b)

(a)

(b)

(a)