Atmospheric Research,
Journal Year:
2024,
Volume and Issue:
304, P. 107353 - 107353
Published: March 19, 2024
Since
the
Clean
Air
Act
amendments
of
1970,
various
efforts
have
been
made
in
United
States
to
control
ambient
particulate
matter
and
improve
air
quality.
Although
substantial
progress
had
by
end
1990s,
further
reductions
were
needed
meet
National
Ambient
Quality
Standards.
To
assess
effectiveness
regulations
impacts
economic
drivers,
we
investigated
PM2.5
source
trends
at
11
sites
New
York
Jersey
for
2010–2019
period.
Dispersion-normalized
positive
matrix
factorization
(DN-PMF)
was
used
reduce
meteorological
on
apportionment.
The
Theil-Sen
nonparametric
estimator
piecewise
linear
regression
applied
resolved
contributions
quantify
trends.
While
there
is
a
consistent
overall
decrease
all
sites,
increases
observed
some
specific
PM
sources.
Secondary
Sulfate
increased
after
2017
most
based
analysis.
Similarly,
recent-year
Diesel
concentrations
likely
due
increasing
vehicle
miles
traveled
heavy-duty
vehicles.
Back
trajectory
analysis
OP-Rich
identified
southeastern
U.S.
as
major
area,
while
Biomass
Burning
has
mixed
from
local
domestic
heating
well
transported
proscribed
wildfires
Remote Sensing,
Journal Year:
2024,
Volume and Issue:
16(3), P. 467 - 467
Published: Jan. 25, 2024
Long-term
exposure
to
high
concentrations
of
fine
particles
can
cause
irreversible
damage
people’s
health.
Therefore,
it
is
extreme
significance
conduct
large-scale
continuous
spatial
particulate
matter
(PM2.5)
concentration
prediction
for
air
pollution
prevention
and
control
in
China.
The
distribution
PM2.5
ground
monitoring
stations
China
uneven
with
a
larger
number
southeastern
China,
while
the
sites
also
insufficient
quality
control.
Remote
sensing
technology
obtain
information
quickly
macroscopically.
possible
predict
based
on
multi-source
remote
data.
Our
study
took
as
research
area,
using
Pearson
correlation
coefficient
GeoDetector
select
auxiliary
variables.
In
addition,
long
short-term
memory
neural
network
random
forest
regression
model
were
established
estimation.
We
finally
selected
(R2
=
0.93,
RMSE
4.59
μg
m−3)
our
by
evaluation
index.
across
2021
was
estimated,
then
influence
factors
high-value
regions
explored.
It
clear
that
not
only
related
local
geographical
meteorological
conditions,
but
closely
economic
social
development.
Air Quality Atmosphere & Health,
Journal Year:
2024,
Volume and Issue:
unknown
Published: June 5, 2024
Abstract
PM
2.5
pollution
is
problematic
in
megacities
on
the
western
coast
South
Korea
(Seoul,
Incheon,
and
Gwangju).
As
these
are
located
downwind
of
China,
their
air
quality
easily
affected
by
local
long-range
transport
sources.
samples
collected
Seoul
(
n
=
222),
Incheon
221),
Gwangju
224)
from
September
2020
to
March
2022,
were
chemically
characterized.
Dispersion
normalized
positive
matrix
factorization
was
applied
speciated
data
provide
source
apportionments.
Nine
common
sources
(including
secondary
nitrate,
sulfate,
biomass
burning,
mobile,
waste
incinerator)
identified
at
all
sites.
The
conditional
bivariate
probability
function
helped
identify
each
site’s
Joint
potential
contribution
analysis
northeast
China
Inner
Mongolia
as
areas
pollutants
affecting
Forced
lifestyle
changes
due
pandemic
such
limited
gatherings
while
increased
recreational
activities
may
have
caused
different
patterns
burning
source.
constraints
old
vehicles
during
policy
implementation
periods
likely
reduced
mobile
contributions
cities
that
adopted
policy.
Secondary
nitrate
accounted
for
40%
mass
sites,
implying
a
significant
impact
NO
X
While
current
focuses
primarily
controlling
primary
emission
sources,
it
should
include
well
which
precursor
emissions
control.
Healthier
would
be
achieved
if
effects
not
local,
but
also
foreign
regions
upwind
intergovernmental
collaboration.
npj Climate and Atmospheric Science,
Journal Year:
2023,
Volume and Issue:
6(1)
Published: Dec. 20, 2023
Abstract
Traditional
statistical
methods
(TSM)
and
machine
learning
(ML)
have
been
widely
used
to
separate
the
effects
of
emissions
meteorology
on
air
pollutant
concentrations,
while
their
performance
compared
chemistry
transport
model
has
less
fully
investigated.
Using
Community
Multiscale
Air
Quality
Model
(CMAQ)
as
a
reference,
series
experiments
was
conducted
comprehensively
investigate
TSM
(e.g.,
multiple
linear
regression
Kolmogorov–Zurbenko
filter)
ML
random
forest
extreme
gradient
boosting)
approaches
in
quantifying
trends
fine
particulate
matter
(PM
2.5
)
during
2013−2017.
evaluation
metrics
suggested
that
can
explain
variations
PM
with
highest
from
ML.
The
showed
insignificant
differences
(
p
>
0.05)
for
both
emission-related
$${{\rm{PM}}}_{2.5}^{{\rm{EMI}}}$$
PM2.5EMI
meteorology-related
components
between
TSM,
ML,
CMAQ
modeling
results.
estimated
least
difference
CMAQ.
Considering
medium
computing
resources
low
biases,
method
is
recommended
weather
normalization
.
Sensitivity
analysis
further
optimized
hyperparameters
exclusion
temporal
variables
produce
reasonable
results
Journal of Geophysical Research Atmospheres,
Journal Year:
2023,
Volume and Issue:
128(15)
Published: July 15, 2023
Abstract
Reducing
ambient
black
carbon
(BC)
relies
on
the
targeted
control
of
anthropogenic
emissions.
Measuring
emission
changes
in
source‐specific
BC
aerosol
is
essential
to
assess
effectiveness
regulatory
policies
but
difficult
due
presence
meteorology
and
multiple
co‐existing
Herein,
we
propose
a
data‐driven
approach,
combining
dispersion‐normalized
factor
analysis
(DN‐PMF)
with
machine
learning
weather
adjustment
(deweathering)
technique,
decompose
into
source
emissions
meteorological
drivers.
Six
refined
sources
were
extracted
from
aethalometer
multi‐wavelength
concurrent
observational
datasets.
In
addition
widely
reported
dominant
sources,
such
as
vehicular
(VE)
coal/biomass
burning
(BB),
discernible
port
shipping
identified
potential
impacts
coastal
air
quality.
The
showed
abrupt
response
interventions
(e.g.,
holidays)
after
separating
weather‐related
confounders.
Significant
reductions
deweathered
coal
BB,
VE,
local
dust
verified
policies,
clean
winter‐heating
support
for
Clean
Air
Actions.
As
revealed
by
post‐hoc
model
explanation
evolution
boundary
layer
was
predominant
driver
exerting
opposite
impact
respect
distant
regional‐wide
that
is,
Environment International,
Journal Year:
2025,
Volume and Issue:
unknown, P. 109394 - 109394
Published: March 1, 2025
Atmospheric
particulate
nitrate
(pNO3-),
a
crucial
component
of
fine
matter,
significantly
contributes
to
haze
pollution.
The
formation
pNO3-
is
driven
by
multiple
factors
including
meteorology,
emissions,
and
atmospheric
chemistry.
Understanding
the
key
drivers
developing
an
accurate
physically
meaningful
method
for
timely
assessment
direct
causes
pollution
are
essential.
In
this
study,
we
propose
multi-module
data-driven
integrated
framework
that
incorporates
improves
four
distinct
machine
learning
modules.
This
enhances
physical
interpretability
statistical
outcomes
driving
pNO3-,
quantifies
impacts
on
reveals
emission
reduction
trends.
Our
findings
show
meteorology
emissions
affect
35.3
%
64.7
%,
respectively,
while
chemistry
(48.0
%)
humidity
(17.1
its
formation.
Photochemistry
promotes
in
summer,
whereas
liquid-phase
reactions
dominate
winter
at
higher
levels
(>60
%).
industry
source
(IS)
(14.3
%),
combustion
(CS)
(12.8
transportation
(TS)
(11.8
main
sources.
primary
transformation
NOx
emitted
from
CS
TS
more
sensitive
changes
meteorological
conditions,
controlling
has
greater
benefits
reduce
pNO3-.
proposed
could
provide
reliable
identifying
different
events,
supporting
formulation
control
measures.
Aerosol and Air Quality Research,
Journal Year:
2025,
Volume and Issue:
25(1-4)
Published: April 1, 2025
Abstract
Introduction
Various
studies
were
conducted
focused
on
the
coal-to-gas
(CTG)
impacts
urban
PM
2.5
during
its
implementation.
However,
continuity
of
CTG
effectiveness
control
in
post
remained
unclear,
especially
rural
area,
retarding
further
emission-control
policy
optimization.
To
address
this
gap,
we
examined
wintertime
variations
within
Beijing–Tianjin–Hebei
non-epidemic-lockdown
period
winter
2020–2022.
Of
which,
2020
holds
most
stringent
enforcement,
2021
marks
conclusion
CTG,
and
2022
represents
CTG.
Methods
In
study,
levels
areas
region
monitored
winters
2020,
2021,
2022.
Meanwhile,
multiple
chemical
analysis
methods
employed
to
determine
components.
The
Positive
Matrix
Factorization
(PMF)
modeling
Potential
source
contribution
function
(PSCF)
analyze
contributions
different
sources
.
Results
Discussion
exhibited
an
average
decrease
30.4%,
PMF
indicated
coal
combustion
(CC)
fell
from
22.4%
17.8%
10.8%
by
2022,
highlighting
enduring
effectiveness.
continuously
decreasing
CC-specific
As,
Pb,
SO
4
2–
was
another
evidence
for
scattered
prohibition.
Reluctantly,
biomass
burning
(BB)
held
higher
increase
17.2%
2021–2022
than
8.86%
2020–2021,
it
has
leapt
be
largest
contributor
(25.4%)
natural
gas
shortage
subsidy
reduction
as
well
man,
forced
demolition
coal-stoves
should
main
inducements.
Contrary
recent
upward
trend
secondary
aerosols,
,
NO
3
–
NH
+
showed
a
downward
trend,
with
annual
dropped
52.6%,
23.4%,
53.8%,
respectively.
This
ascribed
enhanced
primary
emissions
BB
vehicle
exhaust
(VE).
Increments
VE
fraction
might
related
gradually
unblocking
COVID-19.
Correspondingly,
fractions
BB-dependent
K
/Cl
VE-specific
Cu/Zn/NO
obviously
rose
Conclusions
work
highlighted
that
priorities
given
emission
BB,
guarantee
supply
certain
financial
subsidies
basis
retaining
original
pollution
policies,
air
quality
improvement
period.
Graphical
abstract
