Efficiency and Driving Factors of Agricultural Carbon Emissions: A Study in Chinese State Farms
Agriculture,
Год журнала:
2024,
Номер
14(9), С. 1454 - 1454
Опубликована: Авг. 26, 2024
Promoting
low-carbon
agriculture
is
vital
for
climate
action
and
food
security.
State
farms
serve
as
crucial
agricultural
production
bases
in
China
are
essential
reducing
China’s
carbon
emissions
boosting
emission
efficiency.
This
study
calculates
the
of
state
across
29
Chinese
provinces
using
IPCC
method
from
2010
to
2022.
It
also
evaluates
efficiency
with
Super-Slack-Based
Measure
(Super-SBM
model)
analyzes
influencing
factors
Logarithmic
Mean
Divisia
Index
(LMDI)
method.
The
findings
suggest
that
three
largest
sources
rice
planting,
chemical
fertilizers,
land
tillage.
Secondly,
initially
surge,
stabilize
fluctuations,
ultimately
decline,
higher
observed
northern
eastern
China.
Thirdly,
rise
driven
primarily
by
technological
progress.
Lastly,
economic
development
industry
structure
promote
emissions,
while
labor
scale
reduce
them.
To
improve
efficiency,
following
measures
can
be
taken:
(1)
Improve
all
links;
(2)
Optimize
industrial
coordinated
agriculture;
(3)
Reduce
specialization,
professionalization,
high-quality
labor;
(4)
Accelerate
green
technology
innovation
guide
transformation
farms.
enriches
theoretical
foundation
develops
a
framework
assessing
farms,
offering
guidance
future
research
policy
sustainable
agriculture.
Язык: Английский
Review of Challenges and Key Enablers in Energy Systems towards Net Zero Target: Renewables, Storage, Buildings, & Grid Technologies.
Heliyon,
Год журнала:
2024,
Номер
10(23), С. e40691 - e40691
Опубликована: Ноя. 26, 2024
Язык: Английский
Study on Carbon Emission Influencing Factors and Carbon Emission Reduction Potential in China's Food Production Industry
Environmental Research,
Год журнала:
2024,
Номер
261, С. 119702 - 119702
Опубликована: Июль 31, 2024
Язык: Английский
Analysis of Influencing Factors and Prediction of the Peak Value of Industrial Carbon Emission in the Sichuan-Chongqing Region
Sustainability,
Год журнала:
2024,
Номер
16(11), С. 4532 - 4532
Опубликована: Май 27, 2024
The
greenhouse
effect
has
a
negative
impact
on
social
and
economic
development.
Analyzing
the
factors
influencing
industrial
carbon
emissions
accurately
predicting
peak
of
to
achieve
neutrality
is
therefore
vital.
annual
data
from
2000
2022
were
used
study
emission
path
reduction.
In
this
study,
gray
correlation
method
stepwise
regression
explore
effective
that
met
significance
test
STIRPAT
expansion
model
was
constructed
analyze
characteristics
in
Sichuan-Chongqing
region.
Finally,
changing
trend
regional
predicted
by
scenario
analysis
four
development
scenarios
are
set
up,
which
show
(1)
2022,
change
total
Sichuan
Province
Chongqing
Municipality
presents
an
inverted
U-shaped
trend,
reaching
phased
2013
2014,
respectively,
then
declining
rising
again
after
2018.
(2)
Industrial
scale
foreign
trade
dependence
population
Sichuan,
all
have
positive
effects.
Energy
structure
per
capita
income
Chongqing,
showing
effects,
respectively.
(3)
Analysis
shows
time
range
region
2030–2035
its
height
ranges
81.98
million
tons
87.64
tons.
Among
them,
green
most
consistent
as
soon
possible;
case,
will
2030,
line
with
national
target
time,
lowest
level
suggestions
paper
continuously
optimizing
energy
structure,
adjusting
scale,
accelerating
scientific
technological
progress
sustainable
Язык: Английский
Making Decisions on the Development of County-Level Agricultural Industries through Comprehensive Evaluation of Environmental and Economic Benefits of Agricultural Products: A Case Study of Hancheng City
Agriculture,
Год журнала:
2024,
Номер
14(6), С. 888 - 888
Опубликована: Июнь 4, 2024
This
study
aims
to
provide
a
scientific
basis
for
the
development
of
county-level
agricultural
industries
through
comprehensive
evaluation
environmental
and
economic
benefits
products.
Focusing
on
Hancheng
City
in
Shaanxi
Province,
this
paper
calculates
analyzes
carbon
emission
intensity
per
unit
output
value
major
products,
assessing
their
advantage
indices.
The
research
methods
include
data
collection,
processing,
model
construction,
utilizing
bi-factor
matrix
analysis
explore
balance
between
sustainability
profitability
different
results
indicate
that
pepper
vegetables
have
highest
advantages,
demonstrating
significant
benefits,
while
soybeans
show
lower
requiring
improvements
cultivation
techniques
management
practices.
Based
findings,
proposes
policy
recommendations
including
focusing
high-comprehensive-advantage
improving
low-comprehensive-advantage
promoting
green
technologies,
establishing
footprint
monitoring
system
strengthening
infrastructure
construction.
study’s
conclusions
theoretical
support
practical
guidance
strategies
similar
regions,
contributing
achievement
sustainable
reduction
goals.
Язык: Английский