Urban
water
bodies
play
a
critical
role
in
regulating
urban
climate,
mitigating
the
heat
island
effect,
and
enhancing
ecological
environments.
This
study
focuses
on
five
typical
cities
Zhejiang
Province,
systematically
analyzing
cooling
effects
of
bodies.
Specifically,
divides
buffer
zones
into
basic
analytical
units
based
road
network
performs
land
surface
temperature
inversion
use
classification
using
Google
Earth
Engine
platform.
Six
representative
morphology
indicators
are
selected,
contributions
these
to
evaluated
Gradient
Boosting
Decision
Tree
regression
model.
Additionally,
optimization
strategies
for
different
proposed.
The
results
show
following:
(1)
Water
central
areas
generally
exhibit
significant
effects,
with
average
reduction
exceeding
5.13
°C
compared
built-up
all
cities.
(2)
is
higher
than
that
areas,
difference
at
least
0.63
°C.
(3)
In
Huzhou
Jiaxing,
high-temperature
low-temperature
relatively
concentrated,
while
Jinhua,
Quzhou,
Shaoxing,
more
interspersed
distribution
observed,
reflecting
spatial
heterogeneity.
(4)
Among
body
indicators,
edge
density,
proportion
landscape
area
occupied
by
patches,
largest
patch
index
water,
shape
exert
larger
impact
effects.
These
findings
provide
scientific
guidance
optimizing
layout
improving
thermal
Sustainable Cities and Society,
Год журнала:
2024,
Номер
112, С. 105597 - 105597
Опубликована: Июнь 20, 2024
Climate
changes
have
led
to
increasing
global
energy
consumption,
detrimental
the
sustainable
development
of
society.
Urban
blue-green
infrastructure
(UBGI)
can
improve
urban
microclimate.
However,
influence
intensity
UBGI
on
microclimate
has
not
been
quantified
deeply
use
efficiency
water
and
greenery
resources.
To
solve
research
deficiencies,
this
study
numerically
simulated
for
44
scenarios
with
different
resource
configurations
(various
body
areas
coverages)
in
summer.
Based
simulations,
developed
novel
mathematical
models
thermo-environment
(BGTE)
quantify
UBGI.
The
results
indicated
that
daytime
synergies
first
increased
then
decreased
time.
significance
time
(t),
area
(Sw),
tree
coverage
rate
(TCR),
shrub
(SCR),
grassland
(GLCR)
synergy
was
by
artificial
neural
network:
t
(39.4%),
Sw
(22.6%),
TCR
(22.0%),
SCR
(13.2%),
GLCR
(2.8%).
make
overall
effect
relatively
efficient,
should
be
less
than
10000
m2,
greater
65%,
close
15%.
This
provides
practical
ideas
efficient
The
cooling
effect
of
urban
parks
(PCE)
is
widely
recognized
as
an
effective
way
to
improve
the
thermal
environment.
While
influence
various
background
meteorological
factors
(BMFs)
on
PCE
has
been
increasingly
documented,
further
understanding
these
impacts,
particularly
across
different
types
parks,
remains
insufficient.
Here,
we
selected
two
typical
fifteen
with
green
space
(PG)
and
blue-green
(PB&G)
in
Shanghai,
China
for
comparative
studies.
impact
BMFs
threshold
value
efficiency
(TVoE)
sampled
under
six
dates
were
quantified
through
descriptive
statistics
correlation
analysis.
results
showed
that:
(1)
Compared
PG,
PB&G
had
a
stronger
effect,
stable
conditions
(BMCs).
(2)
enable
significant
PCE,
both
PG
better
higher
air
temperature
(Ta).
(3)
blue
ratio
(RBS)
presented
than
(RGS)
BMCs,
especially
BMCs
lower
relative
humidity
(Rh);
thus,
regulation
RBS
should
be
firstly
considered
PCE.
(4)
TVoE
fitting
was
also
less
affected
by
area
0.93
ha
encouraged
optimal
from
cost-benefit
perspective
study
area.
These
findings
are
essential
decision-makers
can
provide
actionable
knowledge
climate
adaptation
planning.
