Sustainability,
Год журнала:
2023,
Номер
16(1), С. 298 - 298
Опубликована: Дек. 28, 2023
The
growing
urban
population
and
increased
use
of
healthcare
services
have
brought
significant
attention
to
the
safe
sustainable
management
medical
waste.
Selecting
proper
technology
in
waste
(MWM)
represents
one
most
critical
challenges
for
decision-makers
ensure
public
health.
In
order
evaluate
choose
best
MWM
methodology,
current
research
provides
a
novel
multi-criteria
decision-making
(MCDM)
strategy
variety
social
stakeholders,
compute
criteria
weights,
alternative
ranking
algorithms.
suggested
structure
addresses
uncertain
assessments
alternatives
by
extending
weighting
methods
acquire
weight
rank
based
on
conditions.
It
also
uses
‘intuitionistic
fuzzy’
linguistic
variables
indicate
weights.
To
assess
all
factors
pertaining
sustainability
actions,
this
study
suggests
creation
decision
support
system
(DSS).
Our
DSS
is
built
upon
that
utilizes
collection
MCDM
models
are
grounded
contemporary
intuitionistic
fuzzy
logic
methodologies.
Alternative
scenarios
been
assessed
instance
Greece,
after
specialists
field
imposed
17
sub-criteria.
IF-MCDM
methodologies
used
were
Intuitionistic
Fuzzy
DEMATEL,
TOPSIS,
CORPAS.
ranged
from
prioritizing
safety
laws
regulations
acceptance
awareness,
with
handling
hazardous
risks
transportation
playing
crucial
part
process.
All
ensemble
produced
same
alternatives,
demonstrating
risk
avoidance
scenario
development
Journal of Environmental Management,
Год журнала:
2024,
Номер
364, С. 121440 - 121440
Опубликована: Июнь 13, 2024
Amid
the
urgent
global
imperatives
concerning
climate
change
and
resource
preservation,
our
research
delves
into
critical
domains
of
waste
management
environmental
sustainability
within
European
Union
(EU),
collecting
data
from
1990
to
2022.
The
Method
Moments
Quantile
Regression
(MMQR)
results
reveal
a
resounding
commitment
among
EU
member
states
diminish
their
reliance
on
incineration,
which
is
evident
through
adopting
green
technologies
environmentally
conscious
taxation
policies,
aligning
with
Union's
objectives.
However,
this
transition
presents
intricate
task
harmonizing
industrial
emissions
efficient
disposal.
Tailoring
strategies
accommodate
diverse
consumption
patterns
unique
circumstances
individual
becomes
imperative.
Cointegrating
regressions
highlighted
long-run
relationship
selected
variables,
while
Feasible
Generalized
Least
Squares
(FGLS)
Panel-Corrected
Standard
Errors
(PCSE)
estimates
roughly
confirmed
MMQR
results.
ML
analyses,
conducted
two
ensemble
methods
(Gradient
Boosting,
GB,
Extreme
Gradient
XGBoost)
shed
light
relative
importance
predictors:
in
particular,
taxation,
consumption-based
emissions,
production-based
greatly
contribute
determining
variation
combustible
renewables
waste.
This
study
recommends
that
countries
establish
monitoring
mechanisms
advance
technology
adoption,
enhance
accelerate
renewable
energy
transition.
Heliyon,
Год журнала:
2024,
Номер
10(5), С. e26997 - e26997
Опубликована: Март 1, 2024
The
COVID-19
pandemic
has
caused
a
surge
in
essential
medical
supplies
usage,
leading
to
notable
increase
waste
generation.
Consequently,
extensive
research
focused
on
sustainable
disposal
methods
handle
used
equipment
safely.
Given
the
necessity
evaluate
these
considering
qualitative
and
quantitative
criteria,
this
falls
within
realm
of
multi-criteria
decision-making
(MCDM).
This
study
introduces
framework
for
selecting
most
suitable
treatment
methods,
taking
into
account
economic,
technological,
environmental,
social
aspects.
Sixteen
criteria
were
assessed
using
Fuzzy
Preference
Selection
Index
(F-PSI)
determine
optimal
approach.
Additionally,
Compromise
Ranking
Alternatives
from
Distance
Ideal
Solution
(F-CRADIS)
method
was
employed
nine
technologies
disposal.
Notably,
disinfection
efficiency
emerged
as
crucial
criterion,
with
autoclaving
identified
preferred
treatment.
A
practical
case
conducted
Sivas,
Turkey,
validates
feasibility
strategies.
Multiple
sensitivity
analyses
performed
ensure
stability
reliability
proposed
Engineering Applications of Artificial Intelligence,
Год журнала:
2024,
Номер
133, С. 108465 - 108465
Опубликована: Май 3, 2024
The
coronavirus
pandemic
significantly
increased
the
use
of
essential
medical
supplies,
resulting
in
a
surge
waste
generation.
This
has
spurred
extensive
research
into
sustainable
disposal
methods
for
safe
and
environmentally
responsible
equipment
management.
Addressing
this
multifaceted
issue
falls
within
domain
multi-criteria
decision-making.
study
presents
comprehensive
framework
selecting
optimal
treatment
methods,
considering
economic,
technological,
environmental,
social
factors.
is
first
to
address
problem
technology
using
Fuzzy
Dombi
Bonferroni.
mean
operator
combine
expert
opinions,
fuzzy
preference
selection
index
method
evaluate
criteria
compromise
ranking
alternatives
from
distance
ideal
solution
rank
alternatives.
According
weightings,
dimension
holds
highest
significance
at
0.3217.
Disinfection
efficiency
ranks
as
most
critical
criterion,
weighing
0.0823.
autoclave
rated
top
technique,
with
utility
function
value
5.4579.
Sensitivity
analyses
ensured
stability
reliability
models.
adaptability
applied
model
practices
such
energy
conversion,
material
recycling,
resource
recovery
represents
an
aspect
policymaking
assessment
can
guide
policy
formulation
or
improvement
processes
disposal.
Climate
change
is
a
global
challenge,
caused
by
increasing
greenhouse
gas
(GHG)
emissions.
Dental
clinical
practice
contributes
to
these
emissions
through
patient
and
staff
travel,
waste,
energy
water
consumption
procurement.
Carbon
footprinting
quantifies
GHG
This
study
assessed
the
Footprint
(CFP)
of
private
dental
clinics
in
Egypt.
Data
were
collected
from
Alexandria
Elbeheira,
Northwestern
Egypt
July
August
2024
interview
questionnaires.
A
CFP
calculator
was
used
estimate
carbon
consumption,
To
determine
average
per
clinic
visit,
all
averaged,
both
with
without
considering
depreciation
equipment.
27
collected.
The
an
Egyptian
clinic,
which,
year,
received
3,322
visits,
where
5
personnel
worked
279
days
14,426.8
kg
CO2e,
or
4.3
CO2e
visit.
largest
contributor
travel
(45.6%),
followed
(19.6%),
(18%),
procurement
(12.4%),
waste
(4.2%),
(0.3%).
After
yearly
equipment,
year
increased
12.2%.
Private
produce
substantial
Patient
major
CFP.
While
there
high
electricity
zero.
likely
due
improper
segregation
lack
recycling.
Country-specific
calculators
are
needed
accurately
measure
various
settings.
Preventing
oral
diseases,
raising
public
awareness
sustainable
practices,
promoting
walking
cycling,
improving
transportation,
implementing
recycling,
shifting
renewable
sources
energy,
local
manufacturing
products
important
reduce
clinics.
Frontiers in Artificial Intelligence,
Год журнала:
2025,
Номер
8
Опубликована: Фев. 12, 2025
Modern
technologies,
particularly
artificial
intelligence,
play
a
crucial
role
in
improving
medical
waste
management
by
developing
intelligent
systems
that
optimize
the
shortest
routes
for
transport,
from
its
generation
to
final
disposal.
Algorithms
such
as
Q-learning
and
Deep
Q
Network
enhance
efficiency
of
transport
disposal
while
reducing
environmental
pollution
risks.
In
this
study,
intelligence
algorithms
were
trained
using
Homogeneous
agent
with
capacity
3
tons
between
hospitals
within
Closed
Capacitated
Vehicle
Routing
Problem
framework.
Integrating
AI
pathfinding
techniques,
especially
hybrid
A*-Deep
approach,
led
advanced
results
despite
initial
challenges.
K-means
clustering
was
used
divide
into
zones,
allowing
agents
navigate
paths
Network.
Analysis
revealed
agents’
not
fully
utilized.
This
application
Fractional
Knapsack
dynamic
programming
maximize
utilization
achieving
optimal
routes.
Since
criteria
compare
algorithms’
effectiveness
are
number
vehicles
total
vehicle
capacity,
it
found
DQN
stands
out
requiring
fewest
(4),
0%
loss
metric
matches
value.
Compared
other
require
5
or
7
vehicles,
reduces
fleet
size
20
42.86%,
respectively.
Additionally,
maximizes
at
100%,
unlike
methods,
which
utilize
only
33
66%
capacity.
However,
improvement
comes
cost
9%
increase
distance,
reflecting
longer
needed
serve
more
per
trip.
Despite
trade-off,
algorithm’s
ability
minimize
utilizing
makes
choice
scenarios
where
these
factors
critical.
approach
improved
performance
but
also
enhanced
sustainability,
making
most
effective
challenging
solution
among
all
study.
Advances in environmental engineering and green technologies book series,
Год журнала:
2024,
Номер
unknown, С. 126 - 140
Опубликована: Май 29, 2024
This
chapter
explores
the
challenges
and
risks
of
hospital
waste
management,
highlighting
potential
IoT
bioelectronics
to
improve
treatment
disposal.
The
integration
these
technologies
can
revolutionize
reducing
environmental
impact
meeting
regulatory
requirements.
monitor
generation
rates,
segregation,
disposal,
simplifying
operations
human
intervention.
Bioelectronics
enhances
by
sensing
analyzing
materials,
detecting
infections
other
hazards
in
medical
for
efficient
processing.
By
improving
disposal
processes,
systems
meet
requirements
reduce
health
concerns.
data
management
plans,
but
security,
infrastructure
integration,
cost
must
be
considered
during
installation.
Future
advancements
artificial
intelligence
machine
learning
could
enhance
through
predictive
analytics
optimization.
In
conclusion,
have
transform
efficiency,
sustainability,
compliance.
Further
research,
innovation,
cooperation
are
needed
fully
utilize
technologies.
Environmental Science and Pollution Research,
Год журнала:
2023,
Номер
unknown
Опубликована: Окт. 25, 2023
Suboptimal
management
of
healthcare
waste
poses
a
significant
concern
that
can
be
effectively
tackled
by
implementing
Internet
Things
(IoT)
solutions
to
enhance
trash
monitoring
and
disposal
processes.
The
potential
utilisation
the
in
addressing
requirements
associated
with
biomedical
within
Kaduna
area
was
examined.
study
included
selection
ten
hospitals,
chosen
based
on
criterion
having
access
wireless
connectivity.
issue
is
sector
since
it
accounts
for
considerable
amount
overall
generation,
estimates
ranging
from
43.62
52.47%
across
various
facilities.
Utilisation
sensors
resulted
activation
alarms
messages
facilitate
prompt
collection
waste.
Data
collected
these
subjected
analysis
discover
patterns
efficiency
practices.
revealed
positive
correlation
between
quantity
hospital
beds
daily
garbage
generated.
Notably,
hospitals
higher
number
were
observed
generate
much
greater
per
bed.
Hazardous
generated
varies
hospital,
one
leading
sharps
(10.98
kgd-1)
chemical
(21.06
kgd-1).
Other
amounts
radioactive
(0.60
kgd-1
0.50
kgd-1),
pharmaceuticals,
genotoxic
(16.19
indicating
need
specialised
approaches.
sheds
light
significance
IoT
efficient
tailored
hazardous