AIMS environmental science,
Год журнала:
2023,
Номер
10(5), С. 644 - 676
Опубликована: Янв. 1, 2023
<abstract>
<p>Industries
face
many
challenges
when
emergencies
arise.
In
emergency,
there
is
an
increasing
demand
for
self-administered
products
that
are
easy
to
use.
The
decay
rate
of
these
decreases
with
time.
Moreover,
the
lack
disposal
used
increases
waste
and
carbon
emissions.
By
observing
scenario,
this
study
develops
a
closed-loop
supply
chain
management
considers
collection
remanufacturing
products.
manufacturing
linear
ramp-type
emissions
dependent.
model
solved
by
classical
optimization
calculates
optimal
total
cost.
results
show
retailer
can
handle
shortage
situation
becomes
stable
(Case
2)
cost
production
rate.
A
sensitivity
analysis
shows
changes
in
respect
parameters.</p>
</abstract>
Environmental Research Infrastructure and Sustainability,
Год журнала:
2024,
Номер
4(2), С. 025003 - 025003
Опубликована: Апрель 19, 2024
Abstract
Global
greenhouse
gas
emissions
from
the
built
environment
remain
high,
driving
innovative
approaches
to
develop
and
adopt
building
materials
that
can
mitigate
some
of
those
emissions.
However,
life-cycle
assessment
(LCA)
practices
still
lack
standardized
quantitative
uncertainty
frameworks,
which
are
urgently
needed
robustly
assess
mitigation
efforts.
Previous
works
emphasize
importance
accounting
for
three
types
uncertainties
may
exist
within
any
assessment:
parameter,
scenario,
model
uncertainty.
Herein,
we
a
framework
distinguishes
between
different
suggest
how
these
could
be
handled
systematically
through
scenario-aware
Monte
Carlo
simulation
(MCS).
We
demonstrate
framework’s
decision-informing
power
case
study
two
multilevel
ordinary
Portland
cement
(OPC)
manufacturing
scenarios.
The
MCS
utilizes
first-principles-based
OPC
inventory,
mitigates
in
other
empirical-based
models.
Remaining
by
scenario
specification
or
sampling
developed
probability
distribution
functions.
also
method
fitting
distributions
parameter
data
enumerating
implementing
based
on
Kolmogorov–Smirnov
test.
level
detail
brought
high-resolution
breakdown
allows
developing
emission
each
process
manufacturing.
This
approach
highlights
specific
parameters,
along
with
framing,
impact
overall
Another
key
takeaway
includes
relating
its
contributions
total
emissions,
guide
LCA
modelers
allocating
collection
refinement
efforts
processes
highest
contribution
cumulative
Ultimately,
aim
this
work
is
provide
robust
estimates
material
readily
integrated
assessment.
