Journal of Cleaner Production,
Journal Year:
2024,
Volume and Issue:
445, P. 141262 - 141262
Published: Feb. 16, 2024
The
process
of
estimating
the
carbon
footprint
(CF)
has
become
a
key
method
for
managing
greenhouse
gas
(GHG)
emissions,
guiding
strategies
emission
reduction
and
validating
those
strategies.
Given
complexity
quantifying
total
lifecycle
emissions
in
residential
buildings,
this
study
delves
into
assessing
CF
focusing
on
water
electricity
consumption
two
types
buildings:
mainly
villas
flats.
This
assessment
was
carried
out
Doha
City,
Qatar,
using
data
from
2017
to
2020.
employs
Multi-Regional
Input-Output
Life
Cycle
Assessment
(MRIO-LCA)
model
calculate
convert
these
buildings.
Further,
various
methods
statistical
spatial
analysis
including
geographically
weighted
regression
(GWR),
Ordinary
Least
Squares
(OLS),
hotspot
cold
spot
assessments.
annual
buildings
are
approximately
7
MtCO2
equivalent,
with
contributing
about
83%
total.
Concurrently,
average
is
around
0.06
predominantly
attributed
villas.
findings
highlight
substantial
impact
structures,
particularly
villas,
city's
overall
emissions.
Furthermore,
underscore
significant
especially
Doha's
revealing
marked
seasonal
increase,
during
summer
months
notable
spike
reveals
consistent
clustering
patterns
across
different
seasons
Elevated
concentrated
central,
northern,
northeastern
regions,
while
spots
eastern
southern
areas.
Understanding
settings
crucial
developing
reduce
enhance
energy
efficiency,
address
climate
change.
research
helps
inform
targeted
interventions
more
sustainable
use,
aligning
broader
environmental
goals.
Sustainable Cities and Society,
Journal Year:
2021,
Volume and Issue:
68, P. 102784 - 102784
Published: Feb. 21, 2021
Since
December
2019,
the
world
has
witnessed
stringent
effect
of
an
unprecedented
global
pandemic,
coronavirus
disease
2019
(COVID-19),
caused
by
severe
acute
respiratory
syndrome
2
(SARS-CoV-2).
As
January
29,2021,
there
have
been
100,819,363
confirmed
cases
and
2,176,159
deaths
reported.
Among
countries
affected
severely
COVID-19,
United
States
tops
list.
Research
conducted
to
discuss
causal
associations
between
explanatory
factors
COVID-19
transmission
in
contiguous
States.
However,
most
these
studies
focus
more
on
spatial
estimated
parameters,
yet
exploring
time-varying
dimension
econometric
modeling
appears
be
utmost
essential.
This
research
adopts
various
relevant
approaches
explore
potential
effects
driving
counts
A
total
three
regression
models
two
local
models,
latter
including
geographically
weighted
(GWR)
multiscale
GWR
(MGWR),
are
performed
at
county
scale
take
into
account
effects.
For
cases,
ethnicity,
crime,
income
found
strongest
covariates
explain
variance
estimation.
deaths,
migration
(domestic
international)
play
a
critical
role
explaining
differences
across
counties.
Such
also
exhibit
temporal
variations
from
March
July,
as
supported
better
performance
MGWR
than
GWR.
Both
among
parameters
vary
highly
over
space
change
time.
Therefore,
time
should
paid
attention
epidemiological
analysis.
performs
accurately,
it
slightly
higher
Adj.
R