Water,
Год журнала:
2024,
Номер
16(21), С. 3154 - 3154
Опубликована: Ноя. 4, 2024
The
present
study
focuses
on
a
site
contaminated
with
halogenated
hydrocarbons,
utilizing
detailed
inventory
of
contamination
data
to
achieve
the
precise
characterization
groundwater
pollution.
Employing
MOFLOW-2000
software,
flow
model
was
established
for
area.
In
conjunction
MT3DMS,
predictive
constructed
simulate
and
forecast
spatiotemporal
distribution
contaminant
migration
attenuation
following
remediation.
simulation
area
delineated
based
geographical
features,
vertical
range
strata
also
determined.
To
establish
hydrogeological
conceptual
target
remediation
site,
comprehensive
were
collected,
encompassing
geological
structures,
hydrological
parameters,
rainfall
information.
Model
calibration
six
layers
low-permeability
aquifer
intervals
revealed
by
exploration
wells
MW1–5,
as
well
groundwater-level
contours
data.
Based
from
September
2010,
an
initial
three-dimensional
tetrachloroethylene
(PCE)
generated.
Subsequently,
solute
transport
PCE
established,
incorporating
various
enhanced
reductive
dechlorination
(ERD)
strategies
applied
at
different
times
locations.
Calibration
against
actual
monitoring
presence
unmonitored
dense
non-aqueous
phase
liquids
(DNAPLs)
contributing
continuous
release
elevation
concentrations.
By
accounting
DNAPL
release,
calibrated
closely
matched
observed
concentration
decay
patterns,
effectively
capturing
dynamics
within
system.
modeling
approach
proposed
in
this
provides
important
support
current
it
is
applicable
simulating
predicting
pollution
scenarios
similar
sites.
Water,
Год журнала:
2024,
Номер
16(19), С. 2748 - 2748
Опубликована: Сен. 27, 2024
Groundwater
salinization
poses
a
critical
threat
to
sustainable
development
in
arid
and
semi-arid
rurbanizing
regions,
exemplified
by
Kerman
Province,
Iran.
This
region
experiences
groundwater
ecosystem
degradation
as
result
of
the
rapid
conversion
rural
agricultural
land
urban
areas
under
chronic
drought
conditions.
study
aims
enhance
Pollution
Risk
(GwPR)
mapping
integrating
DRASTIC
index
with
machine
learning
(ML)
models,
including
Random
Forest
(RF),
Boosted
Regression
Trees
(BRT),
Generalized
Linear
Model
(GLM),
Support
Vector
Machine
(SVM),
Multivariate
Adaptive
Splines
(MARS),
alongside
hydrogeochemical
investigations,
promote
water
management
Province.
The
RF
model
achieved
highest
accuracy
an
Area
Under
Curve
(AUC)
0.995
predicting
GwPR,
outperforming
BRT
(0.988),
SVM
(0.977),
MARS
(0.951),
GLM
(0.887).
RF-based
map
identified
new
high-vulnerability
zones
northeast
northwest
showed
expanded
moderate
vulnerability
zone,
covering
48.46%
area.
Analysis
revealed
exceedances
WHO
standards
for
total
hardness
(TH),
sodium,
sulfates,
chlorides,
electrical
conductivity
(EC)
these
areas,
indicating
contamination
from
mineralized
aquifers
unsustainable
practices.
findings
underscore
model’s
effectiveness
prediction
highlight
need
stricter
monitoring
management,
regulating
extraction
improving
use
efficiency
riverine
aquifers.
Toxics,
Год журнала:
2024,
Номер
12(12), С. 894 - 894
Опубликована: Дек. 9, 2024
The
rapid
development
of
the
global
chemical
industry
has
led
to
widespread
groundwater
contamination,
with
frequent
pollution
incidents
posing
severe
threats
water
safety.
However,
there
been
insufficient
assessment
health
risks
posed
by
chlorinated
hydrocarbon
contamination
in
around
industrial
parks.
This
study
evaluates
at
a
park
and
conducts
multi-pathway
risk
assessment,
identifying
key
pollutants.
In
addition,
sensitivity
analysis
primary
exposure
pathways
was
performed
using
Monte
Carlo
method.
results
indicate
exceedance
pollutant
concentrations
diffusion.
Carcinogenic
were
mainly
driven
vinyl
chloride,
whose
oral
cancer
slope
factor
significantly
higher
than
that
other
substances,
while
non-carcinogenic
dominated
trichloro-ethylene,
which
had
lowest
reference
dose.
Both
carcinogenic
through
drinking
pathway
accounted
for
approximately
90%
total
risk,
whereas
contribution
from
dermal
contact
negligible.
Although
boiling
can
partially
reduce
risks,
its
effect
on
high-concentration
pollutants
is
limited.
Additionally,
showed
concentration
influencing
values,
followed
duration.
findings
this
provide
scientific
basis
effectively
formulating
control
measures
ensuring
safety
nearby
residents.
Groundwater
in
karst
regions
is
of
immense
value
due
to
its
vital
support
for
regional
ecosystems
and
residents'
livelihoods.
However,
it
simultaneously
threatened
by
multi-source
pollution
from
agricultural
non-point
sources,
industrial
domestic
point
mining
activities.
This
study
focuses
on
the
Guangxi
China,
which
features
typical
topography,
aiming
thoroughly
assess
groundwater
quality
related
health
risks
Guangxi,
especially
identifying
impacts
various
key
sources
environment.
A
total
1,912
samples
were
collected,
covering
an
area
approximately
237,600
square
kilometers.
The
spatial
distribution
pollutants
was
analyzed
using
Nemeroww
index
method
Kriging
interpolation,
while
multivariate
statistical
cluster
analysis
methods
employed
identify
main
types
sources.
Furthermore,
based
human
risk
assessment
model
U.S.
Environmental
Protection
Agency
(US
EPA),
a
conducted
pollutants.
results
revealed
widespread
heavy
metal
contamination
Guangxi's
groundwater,
particularly
with
concentrations
Mn,
As,
Al,
Pb
reaching
up
9.4
mg/L,
2.483
37.95
4.761
respectively,
significantly
exceeding
China's
national
Class
III
standards.
Cluster
indicated
that
activities
are
primary
pollution.
demonstrated
these
pose
significant
public
health.
aim
this
provide
scientific
basis
protection
environment
other
areas,
formulation
prevention
control
strategies,
optimization
urban
land
use
layouts.
Future
research
should
focus
advanced
isotopic
molecular
biological
techniques
trace
more
precisely
evaluate
effectiveness
measures.
