Technological innovation, trade openness, natural resources, clean energy on environmental sustainably: a competitive assessment between CO2 emission, ecological footprint, load capacity factor and inverted load capacity factor in BRICS+T
Jie Sun,
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Md. Qamruzzaman
No information about this author
Frontiers in Environmental Science,
Journal Year:
2025,
Volume and Issue:
12
Published: Feb. 4, 2025
The
study
investigates
the
relationship
between
technological
innovation,
clean
energy,
trade
openness,
and
natural
resource
rents
on
environmental
sustainability
within
BRICS
+
T
nations.
Motivated
by
urgent
need
to
address
escalating
CO2
emissions—reaching
36.4
billion
metric
tons
in
2022—the
research
aims
understand
how
these
factors
influence
emissions,
ecological
footprint,
load
capacity
factor,
its
inverse,
contributing
Sustainable
Development
Goals
(SDGs).
uses
panel
data
from
countries
spanning
period
1990
2022.
Employing
advanced
econometric
techniques
such
as
Dynamic
Seemingly
Unrelated
Regression
(DSUR),
Cross-Sectionally
Augmented
Panel
Unit
Root
(CUP-FM,
CUP-BC),
nonlinear
autoregressive
distributed
lag
(ARDL)
models,
tests
Environmental
Kuznets
Curve
(EKC)
hypothesis
evaluates
asymmetric
effects
of
variables.
Key
findings
indicate
that
innovation
consistently
reduces
emissions
footprints,
reinforcing
role
promoting
through
cleaner
technologies
more
efficient
industrial
processes.
Clean
energy
adoption
has
also
been
shown
be
a
significant
driver
reducing
degradation,
with
consistent
negative
while
improving
factor.
However,
openness
exhibits
dual
effect.
While
it
enhances
use
efficiency,
simultaneously
increases
likely
due
heightened
activity.
Natural
display
mixed
results:
some
cases,
they
exacerbate
others,
contribute
funding
eco-friendly
initiatives.
recommends
nations
prioritize
investments
green
technologies,
strengthen
regulations,
enhance
international
collaboration
accelerate
transition
renewable
energy.
Policymakers
should
balance
benefits
stricter
standards
mitigate
adverse
sustainability.
These
integrated
strategies
are
essential
for
achieving
targets
outlined
SDGs.
Language: Английский
The Nexus Between Technological Innovations, Foreign Direct Investment, and Carbon Emissions: Evidence from Global Perspective
Haitao Fan,
No information about this author
Yulu Zheng,
No information about this author
Xingyu Li
No information about this author
et al.
Journal of the Knowledge Economy,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 9, 2025
Language: Английский
Leveraging AI for a Greener Future: Exploring the Economic and Financial Impacts on Sustainable Environment in the United States
Mohammad Ridwan,
No information about this author
Shewly Bala,
No information about this author
Sarder Abdulla Al Shiam
No information about this author
et al.
Journal of Environmental Science and Economics,
Journal Year:
2024,
Volume and Issue:
3(3), P. 1 - 30
Published: Aug. 25, 2024
In
response
to
increasing
environmental
challenges,
the
United
States
has
deliberately
adopted
technical
advancements
promote
sustainable
development.
This
includes
efforts
decrease
pollution,
improve
energy
efficiency,
and
encourage
use
of
environmentally
friendly
technology
in
different
industries.
study
investigates
role
Artificial
Intelligence
(AI)
promoting
sustainability
from
1990
2019.
It
also
examines
impacts
financial
development,
ICT
use,
economic
growth
on
Load
Capacity
Factor
(LCF).
Various
unit
root
tests
revealed
no
issues
mixed
integration
orders
among
variables.
The
Autoregressive
Distributive
Lag
(ARDL)
model
explored
cointegration,
indicating
long-run
relationships
ARDL
findings
confirm
Curve
hypothesis
for
States,
with
AI
positively
correlating
LCF
both
short
long
run.
Conversely,
development
population
significantly
reduce
LCF.
Robustness
checks
using
FMOLS,
DOLS,
CCR
estimation
approaches
align
results.
Granger
causality
reveal
unidirectional
growth,
AI,
bidirectional
between
Diagnostic
results
are
free
heterogeneity,
serial
correlation,
specification
errors.
underscores
importance
enhancing
while
highlighting
adverse
Language: Английский