Current Analytical Chemistry,
Journal Year:
2024,
Volume and Issue:
20(2), P. 125 - 132
Published: Feb. 1, 2024
Background:
Rutin
is
a
natural
flavonol
that
showed
excellent
antiglycation
activity
with
an
IC50
value
of
294.5
±
1.5
μM.
In
the
current
study,
three
selected
plant
species
Euphorbia,
i.e.,
Euphorbia
helioscopia,
larica,
and
wallichii,
were
analyzed
for
quantification
rutin.
Methods:
The
was
done
through
newly
developed
method
Emission
spectroscopy
coupled
Partial
Least
Square
Regression
(PLSR)
UV-visible
as
parallel
cross-validation
method.
Results:
spectroscopic
results
indicated
highest
rutin
concentration
in
roots
E.
helioscopia
(11.25
mg/100
g)
followed
by
wallichii
(9.93
g),
leaves
whole
larica
(9.41
g).
(8.66
found
to
contain
lowest
among
all
tested
samples.
Conclusion:
present
one
simple,
robust,
non-destructive
methods
carry
out
quantitative
estimation
plants.
Groundwater for Sustainable Development,
Journal Year:
2023,
Volume and Issue:
23, P. 101049 - 101049
Published: Nov. 1, 2023
Groundwater
plays
a
pivotal
role
as
global
source
of
drinking
water.
To
meet
sustainable
development
goals,
it
is
crucial
to
consistently
monitor
and
manage
groundwater
quality.
Despite
its
significance,
there
are
currently
no
specific
tools
available
for
assessing
trace/heavy
metal
contamination
in
groundwater.
Addressing
this
gap,
our
research
introduces
an
innovative
approach:
the
Quality
Index
(GWQI)
model,
developed
tested
Savar
sub-district
Bangladesh.
The
GWQI
model
integrates
ten
water
quality
indicators,
including
six
heavy
metals,
collected
from
38
sampling
sites
study
area.
enhance
precision
assessment,
employed
established
machine
learning
(ML)
techniques,
evaluating
model's
performance
based
on
factors
such
uncertainty,
sensitivity,
reliability.
A
major
advancement
incorporation
metals
into
framework
index
model.
best
authors
knowledge,
marks
first
initiative
develop
encompassing
heavy/trace
elements.
Findings
assessment
revealed
that
area
ranged
'good'
'fair,'
indicating
most
indicators
met
standard
limits
set
by
Bangladesh
government
World
Health
Organization.
In
predicting
scores,
artificial
neural
networks
(ANN)
outperformed
other
ML
models.
Performance
metrics,
root
mean
square
error
(RMSE),
(MSE),
absolute
(MAE)
training
(RMSE
=
0.361;
MSE
0.131;
MAE
0.262),
testing
0.001;
0.00;
0.001),
prediction
evaluation
statistics
(PBIAS
0.000),
demonstrated
superior
effectiveness
ANN.
Moreover,
exhibited
high
sensitivity
(R2
1.0)
low
uncertainty
(less
than
2%)
rating
These
results
affirm
reliability
novel
monitoring
management,
especially
regarding
metals.
Heliyon,
Journal Year:
2024,
Volume and Issue:
10(7), P. e28860 - e28860
Published: March 29, 2024
Protected
areas
are
significant
due
to
the
high
value
of
natural
resources
they
shelter.
This
study's
primary
objective
is
assess
quality
status
water
(13
lakes
and
Tisa
River)
localized
in
protected
area
River
on
territory
Romania.
A
number
13
surface
(Tisa
situated
through
Natura
2000
ecological
network
studied.
The
chemistry
potential
pollution
were
analyzed
by
measuring
analyzing
a
set
twenty
elements
sixteen
physico-chemical
parameters.
impact
anthropogenic
activities
was
settled
applied
analysis
obtained
results.
human
health
risk
noticed.
Results
indicated
that
waters
rich
Ni
Fe
probably
interaction
with
groundwater
Ni.
Waters
characterized
contamination,
which
if
directly
or
food
chain
consumed
could
negatively
influence
health.
Piper
Gibbs
plots
studied
divided
into
three
categories
based
water-rock
interactions:
mixed
Ca2+-Na+-HCO3-,
CaCO3-,
Na+-HCO3-.
Likewise,
indices
(Heavy
metal
Pollution
Index,
HPI
Heavy
Evaluation
HEI)
correlated
As,
amounts.
findings
this
research
imply
influenced
geogenic
origin
emergence
activities.
significance
related
understanding
mechanisms
quality,
improving
conserving
resources,
correspondingly
any
risks
be
identified.
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: Jan. 2, 2025
Pollution
monitoring
in
surface
water
using
field
observational
procedure
is
a
challenging
matter
as
it
time
consuming,
and
needs
lot
of
efforts.
This
study
addresses
the
challenge
efficiently
predicting
pollution
GIS-based
artificial
neural
network
(ANN)
to
detect
heavy
metal
(HM)
effect
wastewater
required
discharge
on
Euphrates
River
Al-Diwaniyah
City,
Iraq.
The
established
40
sampling
stations
incorporates
Inductively
Coupled
Plasma
Atomic
Emission
Spectrometry
(ICP-OES)
assess
HM
levels.
An
ANN
model
suggested
estimate
Heavy
Metal
Index
(HPI)
considering
physiological
chemical
factors.
It
formulates
six
scenarios
enhance
HPI
prediction
accuracy,
utilizing
MATLAB
for
modeling
GIS
statistical
tools
with
inverse
distance
weighted
(IDW)
methods
comprehensive
assessment.
developed
approach
predicted
HP
concentration
basin
an
actual
case
study.
validation
predictive
maps
between
theoretical
practical
part
performed
by
16
conducting
laboratory
analyses,
resulting
acceptable
coefficients
determination
(R2),
observations
standard
deviation
ratio
(RSR),
Nash–Sutcliffe
efficiency
0.999,
1,
0.99,
respectively
indicates
that
reliable
forecast
results
closely
match
observed
data
from
stations.
identifies
nickel,
iron,
cadmium
concentrations
exceeded
Iraqi
World
Health
Organization
(WHO)
standards,
leading
index
peak
150.38
branch.
In
this
study,
used
identify
areas
high
levels,
validate
accuracy
prediction,
generate
map
visualize
Analytical Chemistry Letters,
Journal Year:
2024,
Volume and Issue:
14(1), P. 29 - 47
Published: Jan. 2, 2024
AbstractRiver
systems
are
vital
for
both
civilization
and
biodiversity.
The
rising
threats
to
it
is
due
the
rapid
industrialization
urbanization,
resulting
in
heightened
wastewater
discharge.
This
study
delves
into
Ramganga
River
watershed
India,
conducting
a
comprehensive
assessment
of
its
water
quality
drinking
irrigation
purposes.
A
total
84
samples
were
collected
from
three
streams,
further
categorized
two
clusters,
involving
evaluation
30
characteristics.
To
measure
suitability,
CCME-WQI
was
computed,
revealing
distinct
categorizations
during
Dry
Season
(DS)
Wet
(WS)
year
2019-20.
Cluster
1,
comprising
Sampling
Sites-1
(S-1),
Sites-3
(S-3),
Sites-5
(S-5),
fell
within
fair
category
DS,
shifting
marginal
WS.
2,
encompassing
S-2,
S-4,
S-6,
S-7,
remained
poor
transitioning
IWQI
employed
assess
irrigation.
Notably,
S-1
S-3
consistently
under
high
suitability
category,
while
S-2
exhibited
DS
medium
S-4
seasons.
In
contrast,
S-5,
S-7
demonstrated
Cations
anions
unveiled
an
alkaline
dominance
Calcium
(Ca2+)
Magnesium
(Mg2+)
exceeding
alkalis
Sodium
(Na+)
Potassium
(K+),
depicted
weak
acid
Bicarbonates
(HCO3-)
Carbonates
(CO3-)
surpassing
strong
Sulphate
(SO42-)
Chloride
(Cl2-),
with
exception
at
DS.
USSL
diagram
indicated
medium-high
salinity
low
sodium
levels,
signifying
potential
suitability.
extends
heavy
metal
concentrations,
indicating
adherence
standard
limits,
except
elevated
iron
levels.
These
findings
furnish
invaluable
insights
policymakers
stakeholders
resource
management,
providing
nuanced
understanding
challenges
opportunities
sustaining
watershed.Display
full
sizeKeywords:
Surface
waterRamgangaPhysiyo-chemicalPollution,
Piper
Water,
Journal Year:
2025,
Volume and Issue:
17(7), P. 934 - 934
Published: March 22, 2025
Given
the
increasing
threat
of
groundwater
pollution,
comprehending
trends
and
influencing
factors
quality
variation
is
essential
for
effective
mitigation
strategies.
This
study
addresses
variations
in
Beichuan
River,
a
critical
area
China’s
arid
region.
Using
hydrochemical
analysis
multivariate
statistics,
we
identified
key
quality.
Groundwater
mildly
alkaline,
with
HCO3−-Ca
as
dominant
type.
The
concentrations
major
ions
increase
during
high-flow
period
due
to
rainfall
effects.
dissolution
rock
salt
primarily
contributes
presence
Na+
Cl−
ions.
Meanwhile,
weathering
silicate
carbonate
rocks
main
origin
Ca2+,
Mg2+,
HCO3−
Additionally,
evaporite
principal
source
SO42−.
Human
activities,
particularly
sewage
discharge
fertilization,
significantly
contribute
nitrate
contamination.
Principal
component
revealed
that
industrial
activities
are
controlling
season,
while
hydrochemistry
low-flow
season
mainly
influenced
by
rocks,
salt.
Our
findings
provide
scientific
basis
preventing
deterioration
ecological
environmental
protection
regions.