Applied Sciences,
Год журнала:
2024,
Номер
14(17), С. 7560 - 7560
Опубликована: Авг. 27, 2024
The
dry
beach
length
determines
the
hydraulic
boundary
of
tailings
impoundments
and
significantly
impacts
infiltration
line,
which
is
crucial
for
dam.
A
deep
learning
method
utilizing
satellite
images
presented
to
recognize
area
accurately
measure
beaches
in
tailing
ponds.
Firstly,
various
ponds
were
gathered
collection
was
enlarged
create
a
dataset
Then,
created
using
YOLOv5-seg
identify
from
images.
mask
region
segmented
contour
extraction
then
carried
out.
Finally,
crest
line
fitted
based
on
extracted
contour.
pixel
distance
between
measured
translated
into
real
by
ground
resolution.
This
paper’s
case
study
compared
calculated
with
obtained
field
monitoring.
results
showed
that
minimum
error
2.10%,
maximum
3.46%,
average
2.70%,
indicating
high
precision
calculating
The Science of The Total Environment,
Год журнала:
2024,
Номер
937, С. 173407 - 173407
Опубликована: Май 24, 2024
Following
the
B1
dam
collapse
at
Córrego
do
Feijão
Mine,
actions
were
taken
to
address
environmental
damage
and
enhance
quality
of
water
in
Paraopeba
River.
Natural
processes
river
involve
gradual
reduction
contamination
through
dispersion
downstream
transportation
tailings—a
slow,
nature-driven
process.
Dredging,
a
human
intervention,
aimed
expedite
recovery.
Hence,
this
study
explore
dredging's
role
reducing
impacted
River
zone.
Analysis
revealed
direct
link
between
dredging
post-collapse
turbidity,
though
recent
trends
suggest
lessening
impact
on
pre-collapse
conditions.
Distinct
seasonal
variations
observed
iron
manganese
concentrations,
peaking
during
wet
seasons
displaying
notable
upstream-downstream
disparities.
An
analysis
ratios
(downstream/upstream)
was
conducted
understand
even
predict
return
Wet
season
averages
for
decreased
by
around
90
%
over
time,
with
standard
deviations
about
48
58
%,
respectively.
In
dry
season,
100
indicating
improvements
surpassing
levels.
Standard
also
significantly,
approximately
67
79
Employing
an
exponential
decay
model
that
contribution
period
is
negligible,
but
can
be
estimated
28.6
case
25
manganese.
While
models
performed
well
based
extensive
data,
some
limitations
occur
estimating
rates.
The
model's
sensitivity
might
overlook
influential
factors,
underscoring
importance
considering
sediment
nature
dredged
area
extent
understanding
dynamics.
Despite
these
potential
limitations,
investigation
provides
crucial
insights
into
intricate
relationship
These
findings
pave
way
future
studies
deeper
exploration
more
accurate
assessments
association.
The Science of The Total Environment,
Год журнала:
2024,
Номер
949, С. 174970 - 174970
Опубликована: Июль 26, 2024
Tailings
dams'
disasters
begin
a
stage
of
river
water
contamination
with
no
endpoint
at
first
sight.
But
when
the
was
formerly
used
for
public
supply
and
use
suspended
as
consequence
dam
break,
time
window
safe
suspension
lift
must
be
anticipated
to
help
managers.
The
purpose
this
study
seek
that
moment
in
case
Brumadinho
disaster
which
occurred
2019
injected
millions
cubic
meters
iron-
manganese-rich
tailings
into
Paraopeba
River,
leading
Belo
Horizonte
metropolitan
region
resource,
until
now.
To
accomplish
proposed
goal,
an
assemblage
artificial
intelligence
socio-economic
development
models
were
anticipate
precipitation,
discharge
metal
concentrations
(iron,
manganese)
2033.
Then,
ratios
between
impacted
non-impacted
sites
determined
values
representing
extreme
events
selected
further
assessment.
A
ratio
≈1
generally
indicates
similarity
areas
or,
put
another
way,
return
pre-rupture
condition.
Moreover,
is
estimated
under
influence
peak
flows,
then
value
conditions
most
unfavorable
hydrologic
regimes,
thus
return.
So,
plotted
against
fitted
straight
line
intercept-x
requested
time.
results
pointed
6.57
years
after
accident,
while
using
iron
contaminant
indicator,
or
8.71
manganese
considered.
Despite
being
relatively
low-risk
timeframe,
should
implemented
phases
monitored
precaution
potential
sporadic
events,
dredging
from
continue
accelerated.
Engenharia Sanitaria e Ambiental,
Год журнала:
2024,
Номер
29
Опубликована: Янв. 1, 2024
ABSTRACT
The
objective
of
this
work
was
to
evaluate
the
physicochemical
and
adsorptive
characterization
Fe
tailing
collected
in
district
Brumadinho;
verify
its
effect
on
Raphanus
sativus
germination.
material
surface
layer
(0-20
cm)
disintegrated
for
pH,
redox
potential
–
Eh,
electrical
conductivity
EC,
OM,
cation
exchange
capacity
CEC,
specific
area
SSA
functional
groups
characterization.
Adsorption
studies
were
conducted
using
methylene
blue
(MB).
results
adsorption
analyzed
kinetic
models
(Elovich,
pseudo-first
order
PFO
pseudo-second
PSO)
isotherm
(Freundlich,
Langmuir
Sips).
has
an
acidic
pH
(5.60),
negative
ΔpH
(-0.30)
low
CEC
(1.85
cmolc
g-1).
A
high
MB
efficiency
(96%)
verified.
Elovich
model
(0.9248<R2<0.9858)
best
represented
chemical
kinetics,
Freundlich
describes
process
(R2
=
0.9609).
maximum
(qm)
equal
15.08
mg
g-1.
presence
positively
influenced
germination
R.
seeds
(73.8%),
but
stem
root
growth
inferior
when
compared
seedlings
cultivated
compost
substrate.
It
is
concluded
that
favorable
cationic
capacity,
which
can
benefit
soil
fertilization.
However,
development
minor
substrate,
probably
due
OM
nutrient
availability.
Sustainability,
Год журнала:
2024,
Номер
16(19), С. 8686 - 8686
Опубликована: Окт. 8, 2024
The
failure
of
tailings
pond
dams
represents
a
complex
coupled
system
involving
various
risk
factors,
including
human,
governance,
facilities,
and
environmental
aspects.
It
is
crucial
to
identify
key
factors
at
the
level
enhance
safety
management
ponds.
We
analyzed
74
cases
dam
accidents,
both
domestically
internationally,
from
perspectives
facility,
environment.
employed
2–4
Model
extract
causes
failures,
summarizing
these
into
four
primary
40
secondary
while
constructing
coupling
mechanism
model.
natural
killing
(N–K)
model
was
implemented
analyze
values
quantify
couplings.
N–K
facilitated
an
analysis
first-level
social
network
(SNA)
visualize
relationships
among
second-level
assess
centrality
accessibility
nodes
within
factor
network.
out-degree
corrected
by
integrating
with
SNA,
leading
identification
associated
failures
formulation
corresponding
prevention
control
strategies.
findings
indicate
that
managing
multi-risk
effective
approach
mitigating
occurrence
accidents.
Notably,
unfavorable
significantly
contribute
human–governance–facility–environmental
risks,
necessitating
targeted
Furthermore,
inadequate
supervision,
weak
awareness,
receipt
inspection,
irregular
operation
represent
additional
requiring
focused
efforts.
Bulletin of D Serikbayev EKTU,
Год журнала:
2024,
Номер
1, С. 126 - 142
Опубликована: Март 1, 2024
Modern
industrial
production
is
one
of
the
main
sources
environmental
pollution,
actively
consuming
natural
resources.
The
construction
industry,
in
turn,
despite
significant
impact
on
envi-
ronment,
not
an
exception
to
this
trend.
authors
analyze
theoretical
aspects
research
problems
tailings
management,
review
regulatory
and
legal
regulation,
as
well
development
project
accident
elimination,
example
a
company
"Kazzinc".
In
addition,
implementation
similar
projects
real
practice
analyzed.
Thus,
scientific
significance
expressed
systematization
study
methodological
risk
management
case
accidents
at
facilities.
This
key
importance
for
improving
safety
industry
effective
technological
solutions
area.
Applied Sciences,
Год журнала:
2024,
Номер
14(17), С. 7560 - 7560
Опубликована: Авг. 27, 2024
The
dry
beach
length
determines
the
hydraulic
boundary
of
tailings
impoundments
and
significantly
impacts
infiltration
line,
which
is
crucial
for
dam.
A
deep
learning
method
utilizing
satellite
images
presented
to
recognize
area
accurately
measure
beaches
in
tailing
ponds.
Firstly,
various
ponds
were
gathered
collection
was
enlarged
create
a
dataset
Then,
created
using
YOLOv5-seg
identify
from
images.
mask
region
segmented
contour
extraction
then
carried
out.
Finally,
crest
line
fitted
based
on
extracted
contour.
pixel
distance
between
measured
translated
into
real
by
ground
resolution.
This
paper’s
case
study
compared
calculated
with
obtained
field
monitoring.
results
showed
that
minimum
error
2.10%,
maximum
3.46%,
average
2.70%,
indicating
high
precision
calculating
