Spatial spillover heterogeneity and moderated effects of the digital economy on agricultural carbon emissions: evidence from 30 Chinese provinces
Environment Development and Sustainability,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 23, 2025
Язык: Английский
Evaluation and improvement of agricultural green total factor energy efficiency: the perspective of the closest target
Socio-Economic Planning Sciences,
Год журнала:
2025,
Номер
unknown, С. 102179 - 102179
Опубликована: Фев. 1, 2025
Язык: Английский
Spatial Complex Correlation Characteristics of Carbon Emissions and Carbon Transboundary Transfer: Assessment of the Carbon Footprint in Four Mega-Urban Agglomerations in China
YU Cheng-xue,
Hongbo Zheng,
Tong Xu
и другие.
Опубликована: Янв. 1, 2025
Язык: Английский
Structural characteristics and influencing factors of agricultural carbon emissions spatial correlation network: evidence from Shandong Province
Frontiers in Sustainable Food Systems,
Год журнала:
2025,
Номер
9
Опубликована: Апрель 2, 2025
Introduction
With
the
development
of
agricultural
industry
clustering
and
scale
expansion,
carbon
emissions
(ACEs)
have
gradually
formed
a
spatial
association
network.
Clarifying
correlation
network
(ACESCN)
its
influencing
factors
in
Shandong
Province
is
crucial
for
advancing
low-carbon
development.
Methods
Based
on
ACE
16
cities
Province,
this
study
uses
Social
Network
Analysis
(SNA)
Quadratic
Assignment
Procedure
(QAP)
to
investigate
spillover
effects
driving
ACESCN
from
2010
2022.
Results
discussion
The
findings
show
that
following:
(1)
overall,
has
shown
trend
initially
increasing
then
decreasing.
(2)
improved
both
connectivity
robustness,
forming
structure
centered
around
Weifang,
Jinan,
Tai’an.
However,
degree
remains
relatively
loose,
indicating
needs
optimization.
Within
network,
there
are
significant
agglomeration
effects.
(3)
Geographical
proximity,
economic
level,
industrial
structure,
opening-up
impact
correlation.
Therefore,
suggests
associations
should
be
fully
utilized
enhance
cross-regional
production
interactions
cooperation.
This
approach
will
help
form
rational
providing
scientific
basis
achieve
regional
coordinated
emission
reductions.
Язык: Английский
A New Endogenous Direction Selection Mechanism for the Direction Distance Function Method Applied to Different Economic–Environmental Development Modes
Sustainability,
Год журнала:
2025,
Номер
17(7), С. 3151 - 3151
Опубликована: Апрель 2, 2025
As
a
direction
selection
in
the
distance
function
(DDF),
endogenous
DDF
can
accurately
reflect
numerical
characteristics
of
inputs/outputs,
but
it
is
difficult
to
effectively
popularize.
And
also
combine
with
reality.
To
solve
those
problems,
this
paper
introduces
slack
variables
construct
new
direction-setting
mechanism,
which
makes
model
have
conditions
be
popularized.
Based
on
original
DDF,
we
consider
environmental
concern,
economic
coordinated
development,
and
priority
then
six
extended
models
variables.
further
propose
models.
These
not
only
realize
complete
internalization
determination
overcome
limitations
traditional
Combined
actual
case,
emission
reduction
potential
different
areas
revealed,
improved
path
proposed.
The
results
show
that
development
modes
carbon
emissions,
significant
impact
potential.
In
addition,
compared
concern
are
most
beneficial
reduction,
mode
better
reveal
development.
Язык: Английский
Characteristics of agricultural carbon emissions in arid zones, drivers and decoupling effects: evidence from Xinjiang, China
Energy,
Год журнала:
2025,
Номер
unknown, С. 136373 - 136373
Опубликована: Апрель 1, 2025
Язык: Английский
The carbon emission reduction benefits of the transformation of the intensive use of cultivated land in China
Journal of Environmental Management,
Год журнала:
2024,
Номер
370, С. 122978 - 122978
Опубликована: Окт. 25, 2024
Язык: Английский
Nonlinear Associations and Threshold Effects Between Agricultural Industrial Development and Carbon Emissions: Insights from China
Environmental Research Communications,
Год журнала:
2024,
Номер
6(10), С. 105038 - 105038
Опубликована: Окт. 1, 2024
Abstract
With
the
inevitability
of
global
climate
change,
it
has
become
increasingly
important
to
understand
relationship
between
Agro-industrial
Development
(AID)
and
Agricultural
Carbon
Emissions
(ACE)
promote
development
low
carbon
production
in
agriculture.
Using
a
panel
datasets,
as
based
on
‘element-structure-function’
framework
30
Chinese
provinces
over
period
from
2011–2021,
entropy
weight
method
was
used
calculate
level
AID
each
province.
this
approach,
possible
assess
correlations
mechanisms
ACE.
Here,
with
use
fixed-effect,
regulatory
threshold
models,
we
determined
some
critical
factors
contributing
effects
Our
findings
revealed:
(1)
displays
an
inverse
U-shape
ACE,
verified
through
endogeneity
robustness
assessment,
(2)
A
review
suggests
that
crossing
turning
point
inverted
u-curve
can
be
accelerated
by
moderating
effect
agricultural
finance.
(3)
As
analysis,
two-tier
digital
economy,
rural
human
capital
farmers’
net
income
AID,
facilitating
emission
reductions
obtained
after
crossing.
The
significance
increases
function
post-threshold
interval.
Taken
together,
these
demonstrate
long-standing
interplay
Thus,
additional
insights
empirical
evidence
inform
ongoing
sustainable
practices
realized.
Язык: Английский