Sustainability,
Journal Year:
2024,
Volume and Issue:
16(19), P. 8681 - 8681
Published: Oct. 8, 2024
The
synergistic
effect
of
pollution
and
carbon
reduction
can
alleviate
the
dual
pressure
improving
environmental
quality
reducing
greenhouse
gas
emissions
in
China.
emission
trading
scheme
(CETS)
is
a
crucial
market-based
tool
for
reduction,
understanding
its
impact
on
air
control
essential.
Based
data
from
30
provincial
panels
China
spanning
2007
to
2021,
we
employ
difference-in-differences
(DID)
method
analyze
effects
plan
power
industry
influence
mechanisms
are
examined.
We
observe
that
CETS
significantly
enhances
both
China’s
sector,
particularly
demonstrating
effective
synergy
CO2,
SO2,
PM2.5
emissions.
Furthermore,
mechanism
analysis
reveals
achieves
joint
reductions
by
lowering
energy
consumption,
influencing
industry’s
generation
structure,
promoting
technological
innovation
among
enterprises,
thereby
realizing
sector.
Heterogeneity
shows
regions
with
limited
facility,
low
electricity
generation,
small
economic
scale
exhibit
most
pronounced
benefits
efforts.
Frontiers in Marine Science,
Journal Year:
2025,
Volume and Issue:
12
Published: Jan. 31, 2025
Introduction
As
Digital
Industry
4.0
advances,
shipping
operators
are
progressively
implementing
digital
technologies
for
maritime
decarbonization
efforts.
Methods
This
review
employs
a
bibliometric
methodology
to
thoroughly
examine
and
analyze
the
application
of
technology
in
decarbonizing
from
2005
2024.
Examining
201
publications
SCI-EXPANDED
SSCI
databases
elucidates
present
condition,
challenges,
prospects
applications
this
domain.
Results
The
demonstrates
swift
expansion
research
on
within
sector
via
an
analysis
annual
publication
trends.
Subsequent
journal
metrics
collaborative
network
with
VOSviewer
identified
particularly
prolific
journals,
nations,
institutions,
authors.
Furthermore,
delineates
field's
principal
clusters
hotspots
keyword
co-occurrence
analysis,
offering
direction
future
investigations.
Ultimately,
it
examines
gaps
speed
optimization,
emission
prediction,
autonomous
ships
by
integrating
content
recent
publications,
then
proposes
prospective
options.
Discussions
Future
studies
ship
optimization
could
benefit
adopting
multi-objective
methods,
combining
more
machine-learning
techniques
FCP
model,
etc.
Concerning
efforts
focus
diverse
external
data
sources
into
prediction
models,
emerging
applications,
such
as
ship-based
carbon
capture
(SBCC),
introducing
blockchain
smart
monitoring
systems,
regarding
can
further
refine
optimizing
route
planning
navigation
safety,
energy
efficiency
control,
communications
electrification,
green
design.
Journal of Marine Engineering & Technology,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 14
Published: Aug. 30, 2024
Due
to
the
complex
geographical
conditions
within
port
waters,
it
is
necessary
take
pilotage
operations.
The
embarkation
and
disembarkation
(E&D)
of
marine
pilots
riskiest
phase
work,
with
accidents
occurring
frequently.
In
order
examine
key
Risk
Influential
Factors
(RIFs)
E&D
accident
pilots,
in
this
study,
a
novel
network
model
RIFs
during
process
proposed.
Firstly,
based
on
investigation
report
causal
chain
extracted,
leading
are
identified.
Secondly,
constructed
networks
theory,
reliability
verified.
Finally,
by
comprehensive
use
topology
characteristics
analysis,
robustness
analysis
module
pilot
research
results
show
that
management
factors
have
important
impact
safety,
'insufficient
ladder
strength'
most
critical
RIF.
It
should
be
focused
high
connectivity
between
modules
modules,
risk
evolution
can
blocked
through
control
those
RIFs.
Proceedings of the Institution of Mechanical Engineers Part M Journal of Engineering for the Maritime Environment,
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 27, 2025
The
identification
of
marine
traffic
complexity
is
critical
for
the
development
and
implementation
intelligent
maritime
transportation
systems.
Analyzing
extensive
data
on
ship
movements
enhances
situational
awareness
aids
Vessel
Traffic
Services
Operators
(VTSOs)
in
real-time
monitoring
complex
behaviors
waterways.
However,
predominant
systems-based
analysis
predominantly
utilizes
undirected
Marine
Situation
Complex
Network
(MTSCN),
which
inconsistent
with
actual
navigation
situation.
Firstly,
a
directed
MTSCN
constructed
this
study,
accounts
asymmetry
navigational
influences
between
ships.
Secondly,
Node
Importance
Evolution
Model
(NIEM)
developed
network
traffic,
employing
two
indicators:
comprehensive
degree
strength.
Finally,
evaluation
performance
NIEM
substantiated
through
case
studies
robustness
analysis.
research
results
show
that
construction
takes
into
account
differences
ships,
indicators
consider
transmission
contributions
nodes
within
network,
therefore
fits
nautical
situation
better
than
MTSCN.
findings
confirm
newly
model
significantly
VTSOs
identifying
high-complexity
ships
requiring
closer
supervision,
thereby
enhancing
management
improving
safety.
