Coupling and Coordination Relationship Between Carbon Emissions from Land Use and High-Quality Economic Development in Inner Mongolia, China
Land,
Год журнала:
2025,
Номер
14(2), С. 354 - 354
Опубликована: Фев. 8, 2025
Taking
Inner
Mongolia
as
a
case,
this
study
systematically
analyzes
the
coupling
and
coordination
relationship
between
carbon
emissions
from
land
use
(CELU)
high-quality
economic
development
(HQED).
The
aim
is
to
provide
empirical
support
policy
inspiration
for
archiving
“dual
carbon”
goal
HQED
strategy
in
border
areas.
Panel
data
12
cities
2000
2020
were
selected.
We
established
an
evaluation
index
system
CELU
using
entropy-weight
TOPSIS
method
scientifically
evaluated
level
of
HQED.
applied
exploratory
spatial
analysis,
topic
decoupling,
degree
(CCD),
geographic
detector
models
comprehensively
analyze
status
heterogeneity
driving
factors
affecting
CCD
explored
detail.
Although
total
has
increased,
its
growth
rate
slowed
significantly.
was
low,
obvious
disequilibrium
observed.
Seven
key
factors,
including
land-use
structure,
efficiency,
energy
intensity,
have
significant
effects
on
CCD.
To
supply-side
structural
reform,
promote
HQED,
achieve
emission
reduction
green
goals,
we
offer
series
recommendations:
transformation
resource-based
cities,
optimize
industrial
structure
upgrading,
strengthen
scientific
technological
innovation
technology
applications,
improve
regional
cooperation
coordination.
This
reveals
internal
provides
practical
instructive
countermeasures
suggestions
sustainable
areas,
such
Mongolia,
which
important
reference
value
promoting
economies
achieving
goal.
Язык: Английский
Spatial-temporal evolution of land use carbon emissions and influencing factors in Zibo, China
Frontiers in Environmental Science,
Год журнала:
2024,
Номер
12
Опубликована: Ноя. 5, 2024
The
global
climate
crisis
is
escalating,
and
how
to
reduce
land
use
carbon
emission
(LUCE)
while
promoting
social
economic
development
a
issue.
purpose
of
this
study
was
investigate
the
spatio-temporal
evolution
characteristics
influencing
factors
LUCE
at
county
scale.
To
accomplish
goal,
based
on
Zibo
County
data
societal
energy
consumption
statistics,
for
predicting
net
in
2010,
2015,
2020.
GIS
spatial
analysis
autocorrelation
model
were
utilized
LUCE.
geographical
temporal
weighted
regression
(GTWR)
used
differences.
findings
demonstrate
that:
(1)
rate
change
City
decreased
between
2010
2020,
with
overall
motivation
falling
from
0.14%
0.09%.
area
arable
land,
forest
grassland
decreased,
amount
water,
developed
unutilized
increased.
Between
emissions
increased
significantly,
3.011
×
10
7
tC
3.911
tC.
distribution
followed
clear
pattern
“elevated
east
diminished
west,
elevated
south
north.”
agglomeration
are
obvious,
trend
Moran
I
value
falling,
0.219
0.212.
elements
that
determine
vary
greatly
by
location,
most
major
influences
being,
descending
order,
per
unit
GDP,
urbanization
rate,
land-use
efficiency,
population
size.
GDP
has
greatest
impact
Linzi
District,
coefficients
ranging
55.4
211.5.
clearly
depicts
resulting
contribute
them.
Simultaneously,
it
provides
scientific
framework
improving
structure
implementing
low-carbon
programs
throughout
region.
Язык: Английский