Spatiotemporal Characteristics of Carbon Emissions from Construction Land and Their Decoupling Effects in the Yellow River Basin, China
Zhaoli Du,
Xiaoyu Ren,
Weijun Zhao
и другие.
Land,
Год журнала:
2025,
Номер
14(2), С. 320 - 320
Опубликована: Фев. 5, 2025
Carbon
emissions
(CE)
from
expanding
construction
land
(CL),
a
vital
territory
for
human
production
and
habitation,
have
contributed
to
climate
change
worldwide.
The
Yellow
River
Basin
(YRB),
an
essential
economic
region
energy
supply
base
in
China,
is
experiencing
rapid
urbanization,
the
contradiction
between
development
ecological
protection
increasingly
acute.
Consequently,
thorough
examination
of
spatial
temporal
features
carbon
(CECL)
its
decoupling
growth
(EG)
crucial
maintaining
region.
This
study
adopts
IPCC
emission
coefficient
approach
measuring
CECL
YRB
2010
2021.
variation
were
revealed
using
ArcGIS
software
standard
deviation
ellipse
(SDE)
model.
effect
EG
was
analyzed
Tapio
model
innovatively
combined
with
Logarithmic
Mean
Divisia
Index
(LMDI)
method
explore
influence
five
main
drivers
on
effect.
found
that:
(1)
rose
2.463
billion
tons
3.329
layout
“high
east
low
west”.
(2)
SDE
distributed
direction
“northeast
southwest”,
gravity
center’s
moving
path
“northwest
northeast
northwest”;
(3)
weak
(WD)
state
EG;
(4)
output
(CL)
scale
are
two
factors
inhibiting
CECL,
while
intensity
effect,
population
density
structure
elements
motivating
CECL.
provides
specific
references
bases
China
other
countries
regions
similar
levels
promoting
green
ecologically
friendly
initiatives
achieving
low-carbon
utilization
regional
sustainable
development.
Язык: Английский
Coupling Coordination Evaluation and Optimization of Water–Energy–Food System in the Yellow River Basin for Sustainable Development
Systems,
Год журнала:
2025,
Номер
13(4), С. 278 - 278
Опубликована: Апрель 10, 2025
Understanding
the
coupling
mechanisms
and
coordinated
development
dynamics
of
water–energy–food
(WEF)
system
is
crucial
for
sustainable
river
basin
development.
This
study
focuses
on
Yellow
River
Basin,
conducting
a
comprehensive
analysis
system’s
influencing
factors.
A
structured
evaluation
framework
established,
integrating
entropy
weight–TOPSIS
method,
coordination
degree
model,
spatial
correlation
analysis.
Empirical
conducted
using
data
from
nine
provinces
(regions)
along
2003
to
2022
assess
spatiotemporal
evolution
level.
The
Tobit
regression
model
employed
quantify
impact
various
factors
degree.
Results
indicate
that
index
WEF
in
Basin
exhibits
an
overall
upward
trend,
with
remaining
at
high
level
extended
period,
up
0.231
0.375.
interdependence
among
three
major
systems
strong
(0.881–0.939),
while
has
increased
over
time
despite
fluctuations,
qualitative
leap
not
yet
been
achieved.
follows
distribution
pattern
midstream
>
downstream
upstream,
characterized
by
predominantly
However,
frequently
remains
forced
or
below,
general
trend
upstream.
From
2008,
positive
autocorrelation
was
observed
across
provinces,
indicating
agglomeration
effect.
By
2022,
most
were
clustered
“high-high”
“low-low”
areas,
reflecting
minimal
regional
differences.
Key
positively
include
economic
levels,
industrial
structure
upgrading,
urbanization,
transportation
networks,
technological
innovation
negatively
affects
coordination.
Based
these
findings,
it
recommended
strengthen
balanced
development,
optimize
layout
structures,
improve
inter-regional
resource
circulation
mechanism,
promote
deep
integration
production
practices
address
bottlenecks
hindering
system.
Policy
recommendations
are
proposed
provide
strategic
references
socioeconomic
thereby
achieving
high-quality
growth
region.
Язык: Английский
Spatiotemporal Dynamic Evolution of PM2.5 Exposure from Land Use Changes: A Case Study of Gansu Province, China
Land,
Год журнала:
2025,
Номер
14(4), С. 795 - 795
Опубликована: Апрель 7, 2025
Air
pollution
is
a
major
trigger
for
chronic
respiratory
and
circulatory
diseases.
As
key
component
of
air
pollution,
fine
particulate
matter
(PM2.5)
exposure
largely
determined
by
land
use
type
population
density.
However,
simultaneous
consideration
their
spatiotemporal
distribution
lacking
in
existing
studies
on
PM2.5
exposure.
In
this
paper,
we
first
assess
the
dynamic
evolution
patterns
Gansu
Province,
China,
from
2000
to
2020,
using
transfer
matrix
degree.
Population-weighted
(PWE)
then
evaluated
each
at
provincial,
city,
county
levels,
with
seasonal
variations
analyzed.
Spatial
autocorrelation
analysis
finally
performed
explore
exposure,
whereas
standard
deviation
ellipses
gravity
center
migration
models
highlight
spatial
characteristics
shifting
trends.
Experimental
results
showed
that
2010
was
turning
point
annual
provincial
level
an
initial
increase
followed
decrease.
Construction
had
highest
forest
lowest
(except
2005).
Exposure
levels
pattern:
higher
winter
spring
lower
summer
autumn.
At
city
southern
indicated
continuous
decline
across
all
types
since
2000.
exhibited
strong
positive
correlation,
fluctuating
convergence.
This
study
comprehensively
analyzes
multi-scale
differences
various
types,
contributing
provide
scientific
evidence
decision-making
support
mitigating
enhancing
coordinated
control
administrative
levels.
Язык: Английский