Review and Critical Analysis of International UHI Studies

Six studies were found that tried to quantify the energy savings associated with the
implementation of green roofs [192, 193, 194, 195, 196]; however, no studies that addressed the
peak power and CO2 savings for green roof were found. The savings were found to be dependent
upon a range of parameters including the climate, building characteristics (in terms of materials,
insulation, size, operation, etc). One Canadian study used Visual DOE model to evaluate the
heating and cooling energy savings for a one‐story office building with a 3,000m 2 green roof in
the city of Toronto, Ontario in Canada. This study found that the shading and insulation of the
green roof garden reduces the heating energy by 10% and cooling by 6% with an overall total
energy usage reduction of 5%. The low cooling reduction was attributed to 1) increased
insulation ode to green roof reduced the dissipation rate of internally generated heat and 2)
building insulation reduced the heat flow into the building at summertime and reduced heat
flow out in the wintertime. The exact same simulation was run in Santa Barbra, California, it
became evident that with lower amounts of insulation the cooling savings were increased to 10%
[195].
Fourteen studies existed that looked to monitor, model and simulate the temperature variations
attributed to trees and vegetation [002, 006, 007, 010, 040, 046, 048, 069, 082, 086, 088, 092, 109,
112]. Most were case studies examining the effects of trees and vegetation on either individual
buildings or specific city locations. Broadly, most studies indicated that temperature reductions
ode to trees and vegetation could be observed or simulated in the range of 0.28‐4K. During the
summer period shade factor was found to provide 80% of the cooling effect and that the cooling
effect on the site surroundings was narrow and detectable up to 100m from the site boundary
[109]. A study conducted in Taipei, Taiwan ruled that on average parks were cooler than their
surroundings at both day/night times in both the summer and winter months [006] – though this
should be treated with caution when making broader conclusions and transfers of experimental
results as this is based up on different characteristics, times, seasons and climates. An LBNL
study takes a comprehensive look at identifying the costs/benefits associated with planting urban
trees [080].
Fifteen studies were found that attempted to quantify the energy, peak power and CO2 savings
from trees and vegetation [007, 020, 021, 027, 028, 033, 039, 041, 046, 048, 066, 069, 080, 088, 112].
Of these nine looked at energy savings [007, 021, 027, 028, 033, 046, 066, 088, 112], seven looked at
peak power [021, 027, 039, 048, 066, 069, 112] and three looked at CO2 [020, 041, 080]. One study
that simulated the effects of irradiance and wind reductions on energy performance of residences
in four US cities indicated irradiance reduction measures would increase annual heating costs in
cold climates and reduce them in hot climates. This same study showed that shading could
reduce peak loads by up to 31‐49% and a 50% wind reduction was shown to lower annual
heating costs by up to 11% (in Madison) and increase annual cooling costs by 15% (in Miami) – it
concluded that the planting designs for cold climates should reduce winter winds and provide
solar access to south and east walls (also applies to temperate climates) and in hot climates high
branching shade trees and low ground covers should be used to promote both shade and wind
[039]. An LBNL study suggested that a tree planted in LA can avoid combustion of 19kg of
carbon annually even though it sequesters 4.5‐11kg [080]. These studies are very specific to
location and are attempting to model, measure and attribute data to a complex set of variables –
research is needed that better quantifies the effects of: tree cover ratio, tree size, healthy, type,
Review and Critical Analysis of International UHI Studies
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