This
study
investigates
the
performance
of
real-time
data
processing
systems
in
smart
cities,
with
a
focus
on
implementation
autonomous
decision-making
processes
for
urban
management.
The
research
collects
sets
from
Aarhus
(Denmark)
and
Surrey
(Canada)
to
analyze
using
traffic,
parking,
pollution
water
consumption
datasets.
timeframe
passage
rates
benefit
implementing
min-max
normalization
technique
together
other
filtration
methods.
BDA-based
city
architecture
shows
positive
effect
decision
efficiency
which
benefits
traffic
congestion
control
parking
space
tracking
assessment.
Through
independent
event-driven
notifications
system
helps
management
as
well
improves
service
quality
delivered
dwellers.
Application
Hadoop
Spark-based
framework
large
dataset
according
demonstrates
better
time
throughput
results.
Engineering Reports,
Год журнала:
2025,
Номер
7(2)
Опубликована: Фев. 1, 2025
ABSTRACT
Solar
energy,
a
renewable
resource,
is
essential
for
the
efficiency
of
solar
photovoltaic
(PV)
panels.
However,
meteorological
factors,
such
as
irradiation,
weather
patterns,
precipitation,
and
overall
climate
conditions,
pose
challenges
to
seamless
integration
energy
production
into
power
grid.
Accurate
prediction
PV
system
output
necessary
enhance
The
study
focuses
on
utilizing
machine
learning
(ML)
methodologies
accurate
forecasting
generation,
addressing
related
integrating
By
analyzing
generation
data
employing
advanced
ML
models,
research
aims
predictability
systems.
significance
this
lies
in
its
potential
optimize
production,
improve
grid
stability,
contribute
transition
towards
sustainable
sources.
This
assesses
appropriateness
approaches
accurately
projecting
half‐hourly
cycles
next
day.
consists
many
analytical
phases,
including
exploratory
analysis,
inverter
which
are
carried
out
two
separate
plants.
following
step
conduct
comparative
analyses.
analyzed
using
models
like
gradient
boosting
classifiers
linear
regressions.
first
plant
produces
best
results,
with
an
amazing
0.97%
accuracy
classifier
regression
classifier.
Contrarily,
second
achieved
0.61%
0.62%
models.
study's
techniques
insights
can
help
operators
electricity
market
stakeholders
make
informed
decisions
use
generated
power,
minimize
waste,
plan
preservation,
reduce
costs,
facilitate
widespread
Frontiers in Environmental Science,
Год журнала:
2025,
Номер
13
Опубликована: Март 21, 2025
Economic
growth
must
be
balanced
with
ecological
sustainability
as
G20
nations
face
mounting
environmental
concerns
and
challenges.
These
countries
account
for
the
majority
of
global
economic
output
emissions,
making
them
pivotal
in
efforts
to
reduce
footprints
while
fostering
innovation
progress.
This
study
introduces
a
novel
approach
by
integrating
advanced
econometric
methods
such
Cross-Sectional
Augmented
ARDL
(CS-ARDL),
Mean
Group
(AMG),
Common
Correlated
Effects
(CCEMG),
Granger
causality
tests
comprehensively
analyze
dynamic
relationships
between
footprint
(EFP),
policies
(EP),
renewable
energy
consumption
(REC),
capital
formation
(CF),
(INN)
from
1990
2023.
The
key
novelty
this
lies
its
methodological
rigor
ability
address
cross-sectional
dependence
heterogeneity
within
economies.
Unlike
prior
research,
simultaneously
examines
linear,
nonlinear,
interaction
effects,
providing
holistic
understanding
how
factors
interact
over
time.
CS-ARDL
results
highlight
that
policies,
innovation,
drive
sustainability,
REC
playing
most
significant
role
reducing
EFP
findings
on
further
emphasize
sustainable
development
hinges
strategic
investments
human
physical
capital.
By
leveraging
AMG
CCEMG
methodologies,
research
strengthens
robustness
findings,
ensuring
their
validity
across
diverse
contexts.
analysis
reveals
bidirectional
relationship
unidirectional
link
EP,
underscoring
critical
shaping
policy.
offers
groundbreaking
empirical
insights
into
economic,
environmental,
dynamics
nations,
advocating
prioritize
energy,
technological
advancements,
investments.
Future
should
explore
sector-specific
socio-political
dimensions
pathways.
Water,
Год журнала:
2025,
Номер
17(7), С. 923 - 923
Опубликована: Март 22, 2025
The
Zhuxihe
River
has
faced
significant
water
quality
challenges
in
recent
years.
Although
control
measures
have
been
implemented,
the
pollution
levels
remain
concerning.
This
paper
aims
to
investigate
spatio-temporal
variations
of
through
field
sampling,
chemical
testing,
and
synthetic
evaluation.
We
collected
52
samples
both
dry
wet
seasons
along
main
river
its
tributaries.
evaluation,
which
utilized
integrated
SFE-FCE
method,
identified
MnO42−,
NH3-N,
TP,
TFe
as
primary
pollutants.
In
season,
MnO42−
concentrations
ranged
from
1.6
mg/L
19.8
mg/L,
NH3-N
0.12
2.04
TP
varied
0.1
5.61
mg/L.
4.9
13.9
0.27
1.73
0.07
1.31
results
indicate
are
higher
show
seasonal
fluctuations.
Spatially,
downstream
section
faces
highest
levels.
study
provides
insights
into
dynamics
River,
offering
a
scientific
foundation
for
future
research
management
strategies.
F1000Research,
Год журнала:
2025,
Номер
14, С. 384 - 384
Опубликована: Апрель 2, 2025
Background
The
Ichu
River
serves
as
the
primary
water
source
for
urban
and
agricultural
use
industrial
operations,
but
anthropogenic
pollution
has
a
serious
negative
impact
on
its
quality.
Methods
investigation
measured
quality
health-related
risks
by
analyzing
physicochemical
parameters,
heavy
metals,
microbial
pollutants
at
eight
sampling
points,
site
1
(S1)
through
(S8).
Results
research
data
showed
that
worsened
progressively
from
upstream
to
downstream
locations
such
turbidity,
TDS,
conductivity,
BOD
levels
increased.
Oil
oxygen
depletion
arose
reduction
in
dissolved
6.3
4.5
mg/L
different
sites
(S1
S8).
Heavy
metals
(As,
Pb,
Cd,
Cr)
samples
exceeded
standards
established
World
Health
Organization
(WHO)
because
of
mining
wastewater
local
discharge.
presence
excessive
Escherichia
coli
(E.
coli)
total
coliforms
tests
proved
was
severely
contaminated
fecal
matter.
Principal
Component
Analysis
exist
with
organic
load
main
sources
decline,
indicators
were
found
establish
powerful
relationships
depleted
levels.
Conclusion
severe
contamination
this
study
justify
immediate
control
measures,
treatment
enforcement,
sustainable
watershed
management
practices.
Urgent
action
is
necessary
vital
parameters
surpass
set
WHO
(United
States
Environmental
Protection
Agency
(USEPA)
avoid
enduring
environmental
damage
health
problems.
This
demonstrates
value
continuing
assessments
while
enforcing
policies
raising
public
awareness
improve
River.
Water,
Год журнала:
2025,
Номер
17(7), С. 1076 - 1076
Опубликована: Апрель 4, 2025
This
study
proposes
an
innovative
framework
integrating
geographic
information
systems
(GISs),
water
quality
index
(WQI)
analysis,
and
advanced
machine
learning
(ML)
models
to
evaluate
the
prevalence
impact
of
organic
inorganic
pollutants
across
urban–industrial
confluence
zones
(UICZ)
surrounding
National
Capital
Territory
(NCT)
India.
Surface
samples
(n
=
118)
were
systematically
collected
from
Gautam
Buddha
Nagar,
Ghaziabad,
Faridabad,
Sonipat,
Gurugram,
Jhajjar,
Baghpat
districts
assess
physical,
chemical,
microbiological
parameters.
The
application
spatial
interpolation
techniques,
such
as
kriging
inverse
distance
weighting
(IDW),
enhances
WQI
estimation
in
unmonitored
areas,
improving
regional
assessments
remediation
planning.
GIS
mapping
highlighted
stark
disparities,
with
industrial
hubs,
like
Faridabad
exhibiting
values
exceeding
600
due
untreated
discharges
wastewater,
while
rural
regions,
Jhajjar
Baghpat,
recorded
below
200,
reflecting
minimal
anthropogenic
pressures.
employed
four
ML
models—linear
regression
(LR),
random
forest
(RF),
Gaussian
process
(GPR_PUK),
support
vector
machines
(SVM_Poly)—to
predict
high
precision.
SVM_Poly
emerged
most
effective
model,
achieving
testing
CC,
RMSE,
MAE
0.9997,
11.4158,
5.6085,
respectively,
outperforming
RF
(0.9925,
29.8107,
21.7398)
GPR_PUK
(0.9811,
68.4466,
54.0376).
By
leveraging
models,
this
prediction
beyond
conventional
computation,
enabling
extrapolation
early
contamination
detection
data-scarce
regions.
Sensitivity
analysis
identified
total
suspended
solids
critical
predictor
influencing
WQI,
underscoring
its
relevance
monitoring
programs.
research
uniquely
integrates
algorithms
analytics,
providing
a
novel
methodological
contribution
assessment.
findings
emphasize
urgency
mitigating
fate
transport
protect
Delhi’s
hydrological
ecosystems,
presenting
robust
decision-support
system
for
policymakers
environmental
managers.
Separations,
Год журнала:
2025,
Номер
12(4), С. 88 - 88
Опубликована: Апрель 4, 2025
In
the
context
of
sustainable
human
development
and
depletion
petroleum
resources,
lignin
has
received
widespread
attention
as
a
carbon-rich,
low-cost,
renewable
resource.
Owing
to
their
distinctive
physical
chemical
properties,
carbon
materials
are
extensively
applied
in
fields
adsorption
separation.
The
conversion
into
diverse
multifunctional
materials,
such
porous
carbon,
activated
fibers,
foams,
aerogels,
emerged
pivotal
strategy
for
high-value
utilization
lignin.
this
paper,
representative
examples
various
lignin-based
utilized
field
separation
over
past
decade
reviewed
categorized
according
type
preparation
methods
effects
described.
