Land,
Journal Year:
2024,
Volume and Issue:
13(9), P. 1421 - 1421
Published: Sept. 3, 2024
Exploring
the
low-carbon
transition
in
China
can
offer
profound
guidance
for
governments
to
develop
relevant
environmental
policies
and
regulations
within
context
of
2060
carbon
neutrality
target.
Previous
studies
have
extensively
explored
promotion
development
China,
yet
no
completely
explained
mechanisms
from
perspective
per
capita
emissions
(PCEs).
Based
on
statistics
data
367
prefecture
level
cities
2000
2020,
this
study
employed
markov
chain,
kernel
density
analysis,
hotspots
spatial
regression
models
reveal
spatiotemporal
distribution
patterns,
future
trends,
driving
factors
PCEs
China.
The
results
showed
that
China’s
2000,
2010,
2020
were
0.72
ton/persons,
1.72
1.91
respectively,
exhibiting
a
continuous
upward
trend,
with
evident
regional
heterogeneity.
northern
eastern
coastal
region
higher
than
those
southern
central
southwestern
regions.
obvious
clustering,
hot
spots
mainly
concentrated
Inner
Mongolia
Xinjiang,
while
cold
some
provinces
exhibited
strong
stability
‘club
convergence’
phenomenon.
A
analysis
revealed
urbanization
latitude
had
negative
effects
PCEs,
economic
level,
average
elevation,
slope,
longitude
positive
PCEs.
These
findings
important
implications
effective
achievement
“dual
carbon”
goal.
Atmosphere,
Journal Year:
2025,
Volume and Issue:
16(4), P. 449 - 449
Published: April 12, 2025
In
this
study,
based
on
high-resolution
online
monitoring
data
of
CO2
concentration
in
Nanning
City
the
spring
2024,
we
analyzed
characteristics
diurnal
and
monthly
changes
explored
influencing
factors
through
background
sieving
method
Lagrangian
Particle
Dispersion
Model
(LPDM)
traceability
simulations
combined
with
meteorological
factor
analysis.
The
results
demonstrates
that
variation
exhibits
a
bimodal
pattern
peak
afternoon
trough
early
morning,
mean
460
±
15
ppm.
Transportation
emissions
were
identified
as
dominant
source
variation.
trend
was
first
increasing
then
decreasing,
an
increase
February–March
decrease
April,
indicating
it
affected
by
effect
vegetation
photosynthesis
urban
human
activities.
simulation
analysis
showed
more
local
emission
sources
than
sinks,
industrial
transportation
north–south
direction
had
significant
concentration.
This
research
provides
critical
support
for
formulating
carbon
reduction
strategies
coordinated
atmospheric
environment
management
subtropical
cities.
Urban Science,
Journal Year:
2024,
Volume and Issue:
8(3), P. 104 - 104
Published: Aug. 1, 2024
Artificial
intelligence
(AI)
has
become
a
transformative
force
across
various
disciplines,
including
urban
planning.
It
unprecedented
potential
to
address
complex
challenges.
An
essential
task
is
facilitate
informed
decision
making
regarding
the
integration
of
constantly
evolving
AI
analytics
into
planning
research
and
practice.
This
paper
presents
review
how
methods
are
applied
in
studies,
focusing
particularly
on
carbon
neutrality
We
highlight
already
being
used
generate
new
scientific
knowledge
interactions
between
human
activities
nature.
consider
conditions
which
advantages
AI-enabled
studies
can
positively
influence
decision-making
outcomes.
also
importance
interdisciplinary
collaboration,
responsible
governance,
community
engagement
guiding
data-driven
suggest
contribute
supporting
carbon-neutrality
goals.
International Journal of Low-Carbon Technologies,
Journal Year:
2025,
Volume and Issue:
20, P. 580 - 589
Published: Jan. 1, 2025
Abstract
In
order
to
achieve
the
dual
carbon
goal,
a
prediction
method
of
industrial
emissions
based
on
CNN–LSTM
was
studied.
The
extended
Kaya
identity
is
used
measure
emissions,
and
LMDI
decomposition
determine
influencing
factors.
model
inputs
historical
emission
data,
extracts
spatial
features
through
CNN,
then
makes
time
series
by
LSTM,
finally
outputs
results.
Experiments
show
that
this
can
effectively
predict
in
different
scenarios
provide
support
for
goal
double
carbon.
