Enrichment features, ecological risks assessment and quantitative sources appointment of sediment heavy metals: An example of the urbanized Xizhi River catchment, South China
Chao Yan,
No information about this author
Qirui Wu,
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Rui Li
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et al.
Environmental Chemistry and Ecotoxicology,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 1, 2025
Language: Английский
Biofilm-mediated Heavy Metal Bioaccumulation and Trophic Transfer in a Mining-contaminated River
Wen Chen,
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Qi Li,
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Dan Zhu
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et al.
Water Research,
Journal Year:
2024,
Volume and Issue:
267, P. 122487 - 122487
Published: Sept. 20, 2024
Language: Английский
Distributions and influencing factors of heavy metals in the coastal areas of the Yangtze River Estuary, China
Regional Studies in Marine Science,
Journal Year:
2025,
Volume and Issue:
86, P. 104216 - 104216
Published: April 30, 2025
Language: Английский
Sources, Contamination and Risk Assessment of Heavy Metals in Riparian Soils of the Weihe River Based on a Receptor Model and Monte Carlo Simulation
Wen Dong,
No information about this author
Bohan Niu,
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Huaien Li
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et al.
Sustainability,
Journal Year:
2024,
Volume and Issue:
16(23), P. 10779 - 10779
Published: Dec. 9, 2024
The
riparian
ecosystem
is
highly
susceptible
to
pollution,
particularly
heavy
metals
(HMs),
due
its
unique
spatial
position
and
landscape
characteristics.
Therefore,
assessing
the
risks
of
HM
pollution
identifying
potential
sources
are
crucial
for
formulating
effective
prevention
control
measures.
This
study
investigates
characteristics
HMs
(Ni,
Cr,
Zn,
Cd,
Cu,
Pb)
in
Weihe
River
zone,
identifies
their
sources,
assesses
associated
ecological
human
health
risks.
results
indicate
that
Ni,
Cd
primary
pollutants
soil,
with
average
concentration
being
5.64
times
higher
than
background
value,
indicating
a
high
risk.
Spatially,
concentrations
middle
upper
reaches
lower
reaches.
Vertically,
as
distance
from
increases,
content
exhibits
“U”-shaped
pattern
(increase-decrease-increase).
Absolute
principal
components
multiple
regression
(APCS-MLR)
receptor
model
identified
four
sources:
traffic
sources;
agricultural
industrial
natural
sources.
Additionally,
Monte
Carlo
simulation-based
risk
assessment
indicates
non-carcinogenic
indices
all
within
acceptable
ranges.
For
carcinogenic
indices,
there
1.14%
probability
children.
However,
vast
majority
fall
or
no-risk
categories.
Language: Английский
Enhanced remediation of organotin compounds and metal(loid)s in polluted sediments: Chemical stabilization with mining-wastes and nZVI versus physical soil washing
Journal of Environmental Management,
Journal Year:
2024,
Volume and Issue:
373, P. 123602 - 123602
Published: Dec. 12, 2024
Language: Английский