Physics of Fluids,
Journal Year:
2024,
Volume and Issue:
36(7)
Published: July 1, 2024
Climate
change
has
heightened
the
frequency
and
intensity
of
extreme
heat
events
in
cities,
greatly
impacting
human
health,
environment,
socio-economic
activities,
particularly
densely
populated
areas.
Canopy
temperature
(T2m)
is
a
key
indicator
whether
urban
area
occurring,
with
significant
implications
for
public
energy
consumption,
pollution
levels.
However,
diverse
topography,
functional
layout,
activities
contribute
to
variations
distribution
T2m.
While
computational
fluid
dynamics
(CFD)
models
offer
high-resolution
T2m
simulations,
complexities
spatial
temporal
make
accurately
defining
boundary
conditions
challenging,
potentially
leading
large
simulation
errors.
This
study
addressed
challenge
determining
precise
CFD
simulations
by
employing
Weather
Research
Forecasting
model
integrate
meteorological
reanalysis
data.
Different
datasets
used
simulate
were
compared,
including
Final
Operational
Global
Analysis,
Forecast
System,
European
Centre
Medium-Range
Forecasts
Reanalysis
v5.
When
combined
data,
minimum
mean
relative
error
simulated
was
4%,
which
threefold
improvement
accuracy
compared
traditional
conditions.
provides
technical
support
refined
zoning
risk
management
context
climate
change.
Buildings,
Journal Year:
2025,
Volume and Issue:
15(6), P. 865 - 865
Published: March 10, 2025
As
global
climate
change
intensifies,
the
frequency
and
severity
of
extreme
weather
events
continue
to
rise.
However,
research
on
semi-outdoor
transitional
spaces
remains
limited,
transportation
stations
are
typically
not
fully
enclosed.
Therefore,
it
is
crucial
gain
a
deeper
understanding
environmental
needs
users
in
these
spaces.
This
study
employs
machine
learning
(ML)
algorithms
SHAP
(SHapley
Additive
exPlanations)
methodology
identify
rank
critical
factors
influencing
outdoor
thermal
comfort
at
tram
stations.
We
collected
microclimatic
data
from
Guangzhou,
along
with
passenger
feedback,
construct
comprehensive
dataset
encompassing
parameters,
individual
perceptions,
design
characteristics.
A
variety
ML
models,
including
Extreme
Gradient
Boosting
(XGB),
Light
Machine
(LightGBM),
Categorical
(CatBoost),
Random
Forest
(RF),
K-Nearest
Neighbors
(KNNs),
were
trained
validated,
analysis
facilitating
ranking
significant
factors.
The
results
indicate
that
LightGBM
CatBoost
models
performed
exceptionally
well,
identifying
key
determinants
such
as
relative
humidity
(RH),
air
temperature
(Ta),
mean
radiant
(Tmrt),
clothing
insulation
(Clo),
gender,
age,
body
mass
index
(BMI),
location
space
occupied
past
20
min
prior
waiting
(SOP20).
Notably,
significance
physical
parameters
surpassed
physiological
behavioral
provides
clear
strategic
guidance
for
urban
planners,
public
transport
managers,
designers
enhance
while
offering
data-driven
approach
optimizing
promoting
sustainable
development.
Urban Climate,
Journal Year:
2024,
Volume and Issue:
55, P. 101982 - 101982
Published: May 1, 2024
Cities
are
considered
local
"hotspots"
of
climate
change,
therefore,
the
improvement
urban
present
description
as
well
future
projections
is
paramount
for
designing
adaptation
and
mitigation
strategies.
Physically-based
numerical
models
often
have
coarse
resolutions
do
not
parametrisations
to
adequately
represent
physical
processes
at
scale.
This
article
presents
an
innovative
application
XGBoost
(a
machine
learning
approach)
alternative
explore
improve
Madrid.
XGBoost's
ability
reproduce
2-m
air
temperature
land
surface
(LST),
heat
island
(UHI)
effect,
was
assessed.
trained
with
a
set
ERA5
predictors
(0.25°)
calibrated
observations
from
ground
stations
(2000−2022)
remote
sensing
data
(2004–2022).
Several
sensitivity
cases
were
performed
assess
results
dependency
their
resolution.
evaluated
daily
scale
maximum
minimum
temperatures
(Tmax
Tmin,
respectively)
LST,
hourly
LST.
Overall,
reveals
good
performance
significant
added
value
against
all
variables
both
UHI
UHI.
study
promising
technology
describe
climate.
Energy and Built Environment,
Journal Year:
2024,
Volume and Issue:
unknown
Published: June 1, 2024
Extreme
heat
due
to
changing
climate
poses
a
new
challenge
for
temperate
climates.
The
is
further
aggravated
by
inadequate
research,
policy,
or
preparedness
effectively
respond
and
recover
from
its
impacts.
While
urban
morphology
plays
crucial
role
in
mitigating
heat,
it
has
received
limited
attention
planning,
highlighting
the
need
exploration,
particularly
regions.
To
illustrate
potential
mitigations,
we
use
example
of
coastal
city
Cardiff.
establish
interrelations
between
island
patterns,
explored
spatiotemporal
variations
land
surface
temperature
(LST),
normalised
difference
vegetation
index
(NDVI),
(SUHI)
local
zone
(LCZ)
classification
Results
showed
significant
variation
SUHI
LCZ
zones.
Both
LST
NDVI
were
found
vary
significantly
across
zones
demonstrating
their
association
with
form
locality.
For
built-up
areas,
more
compact
built-environment
smaller
cover
larger
building
density
was
2.0°C
warmer
than
open
when
comparing
mean
summer
LSTs.
On
average,
natural
classes
exhibit
that
8.0°C
lower
6.0°C
built-environment.
Consequently,
high-density,
LCZs
have
greater
effect
compared
classes.
Therefore,
cities
will
benefit
incorporating
an
sufficient
greenery
spaces.
These
findings
help
determine
optimal
climates
develop
mitigation
strategies
while
designing,
improving
existing
areas.
In
addition,
map
applied
this
study
Cardiff
enable
international
comparison
testing
proven
change
adaptation
techniques
similar
Applied Sciences,
Journal Year:
2024,
Volume and Issue:
14(6), P. 2473 - 2473
Published: March 15, 2024
Nowadays,
the
growing
concern
about
improving
thermal
comfort
in
different
structures
(textiles,
buildings,
and
pavements,
among
others)
has
stimulated
research
into
phase
change
materials
(PCMs).
The
direct
incorporation
of
PCMs
composite
can
cause
mechanical
impacts.
Therefore,
this
study
focuses
on
design
coaxial
fibres
(PCFs),
using
commercial
cellulose
acetate
(CA)
or
recycled
CA
obtained
from
cotton
fabrics
(CAt)
as
sheath
polyethylene
glycol
(PEG)
2000
core,
via
wet
spinning
method;
vary
molecular
weight,
concentration
ejection
velocity.
were
assessed
for
their
optical,
chemical,
thermal,
properties.
presence
PEG2000
is
confirmed
core
fibres.
Thermal
analyses
revealed
a
mass
loss
at
high
temperatures,
attributable
to
PEG2000.
Notably,
with
(Mn
30,000)
showed
superior
performance.
melting
point
incorporated
these
PCFs
coincided
pure
(about
55
°C),
slight
deviation,
indicating
that
obtained.
Finally,
results
application
civil
engineering
requiring
between
50
60
°C,
providing
promising
prospects
use
applications
thermoregulatory
