Innovation and Green Development,
Journal Year:
2024,
Volume and Issue:
3(3), P. 100134 - 100134
Published: Jan. 22, 2024
The
COP26
Glasgow
conference
stressed
the
importance
of
all
nations
committing
to
more
ambitious
targets
for
reducing
emissions
keep
global
temperatures
from
rising
than
1.5
°C
above
pre-industrial
levels.
This
is
crucial
since
any
temperature
greater
that
will
have
grave
and
irreversible
climatic
repercussions.
research,
utilizing
data
Ghana
1980
2018,
investigates
role
green
innovation,
energy
consumption,
human
capital
in
mitigating
carbon
dioxide
(CO2)
achieve
neutrality
within
environmental
Kuznets
curve
(EKC)
framework
while
using
natural
resources
industrialization
as
additional
variables
study
model.
Current
econometric
techniques
are
employed
accurate
reliable
analyses,
findings
reveal
stationary
co-integrated
long
run.
novel
quantile-on-quantile
regression
adopted,
empirical
discoveries
mitigate
CO2
emissions.
However,
indicate
escalate
country.
also
validate
N-shape
EKC
hypothesis
between
economic
growth
Ghana.
Policy
recommendations
offered
based
on
these
insights.
Frontiers in Psychology,
Journal Year:
2022,
Volume and Issue:
13
Published: July 26, 2022
Compared
with
traditional
technological
innovation
modes,
green
technology
is
more
targeted
for
low
carbon
development
and
critical
support
countries
worldwide
to
combat
climate
change.
The
impact
of
on
emissions
considered
in
terms
fixed
effect
mediating
models
through
industrial
structure
upgrading.
For
this
purpose,
the
sample
dataset
30
provincial
administrative
areas
China
from
2008
2020
employed.
results
demonstrate
that
exerts
significantly
inhibitory
effects
emissions,
whose
conclusion
still
holds
after
removing
municipalities
replacing
dependent
variable.
Industrial
upgrading
vital
diminish
emissions.
There
significant
regional
heterogeneity
i.e.,
direct
indirect
emission
reduction
eastern-central
area,
but
its
insignificant
western
region.
Therefore,
it
essential
realize
by
further
bolstering
accelerating
fulfill
synergy
structure.
Humanities and Social Sciences Communications,
Journal Year:
2024,
Volume and Issue:
11(1)
Published: Aug. 14, 2024
Abstract
This
study
examines
the
multifaceted
impact
of
artificial
intelligence
(AI)
on
environmental
sustainability,
specifically
targeting
ecological
footprints,
carbon
emissions,
and
energy
transitions.
Utilizing
panel
data
from
67
countries,
we
employ
System
Generalized
Method
Moments
(SYS-GMM)
Dynamic
Panel
Threshold
Models
(DPTM)
to
analyze
complex
interactions
between
AI
development
key
metrics.
The
estimated
coefficients
benchmark
model
show
that
significantly
reduces
footprints
emissions
while
promoting
transitions,
with
most
substantial
observed
in
followed
by
footprint
reduction
reduction.
Nonlinear
analysis
indicates
several
insights:
(i)
a
higher
proportion
industrial
sector
diminishes
inhibitory
effect
but
enhances
its
positive
transitions;
(ii)
increased
trade
openness
amplifies
AI’s
ability
reduce
promote
(iii)
benefits
are
more
pronounced
at
levels
development,
enhancing
(iv)
as
transition
process
deepens,
effectiveness
reducing
increases,
role
further
transitions
decreases.
enriches
existing
literature
providing
nuanced
understanding
offers
robust
scientific
foundation
for
global
policymakers
develop
sustainable
management
frameworks.
