Ecological Indicators,
Journal Year:
2024,
Volume and Issue:
159, P. 111662 - 111662
Published: Jan. 31, 2024
Carbon
emissions
and
air
pollutant
in
China
share
common
sources.
A
thorough
examination
of
carbon
is
imperative
for
a
comprehensive
understanding.
This
study
aims
to
assess
carbon-pollutant
efficiency
(CPEE)
30
Chinese
provinces
from
2006
2020,
focusing
on
the
integration
emissions.
Previous
research
CPEE
limited,
this
article
addresses
gap
by
investigating
its
spatiotemporal
characteristics
identifying
potential
influencing
factors.
Our
employs
super-efficiency
data
envelopment
analysis
model,
social
network
analysis,
spatial
econometric
models.
The
results
indicate
that:
(1)
During
period,
provincial
follows
"W-shaped"
trend
exhibits
"bimodal"
asymmetric
distribution,
indicating
notable
regional
heterogeneity.
(2)
Although
correlations
are
unstable
do
not
adhere
strict
hierarchical
structure,
positive
spillover
effects
evident
CPEE.
(3)
correlation
displays
various
characteristics,
including
Matthew
effect,
external
preference,
siphoning
altruistic
tendency.
(4)
Apart
technical
input,
explanatory
variables
affecting
exert
significantly
negative
direct
impact.
Furthermore,
indirect
effect
energy
intensity
contradicts
when
economic
distance
considered
weight
setting.
These
findings
provide
valuable
theoretical
insights
practical
guidance
improving
synergistic
effects.
Sustainability,
Journal Year:
2024,
Volume and Issue:
16(13), P. 5331 - 5331
Published: June 22, 2024
Faced
with
the
dual
challenges
of
environmental
pollution
and
climate
change,
it
is
great
significance
to
study
impact
relevant
regulations
on
synergistic
effect
reduction
carbon
emission
their
influence
mechanisms.
Based
a
theoretical
analysis
using
panel
data
30
provinces
in
China,
spatial
econometric
model
an
intermediary
are
used
investigate
transmission
mechanisms
potentially
responsible
for
these
effects.
The
empirical
results
show
following:
(1)
three
kinds
regulation
effectively
facilitate
reduction,
taking
following
order
when
ranked
according
intensity
effects:
command-type
(ER1)
>
market-based
(ER2)
voluntary
(ER3).
(2)
Environmental
promotes
through
stimulating
technological
innovation
(TI),
industrial
structure
upgrading
(ISU),
restricting
foreign
direct
investment
(FDI),
which
take
effectiveness
order:
TI
FDI
ISU.
study,
policy
suggestions
synergies
proposed
help
China’s
green
low-carbon
development.
