Abstract.
Long-term
PM2.5
data
are
needed
to
study
the
atmospheric
environment,
human
health,
and
climate
change.
measurements
sparsely
distributed
of
short
duration.
In
this
study,
daily
concentrations
estimated
from
1959
2022
using
a
machine
learning
method
at
4011
terrestrial
sites
in
Northern
Hemisphere
based
on
hourly
visibility
data,
which
extracted
Meteorological
Terminal
Aviation
Routine
Weather
Report
(METAR).
monitoring
is
target
learning,
other
related
variables
inputs.
The
training
results
show
that
slope
between
concentration
monitored
0.946±
0.0002
within
95
%
confidence
interval
(CI),
coefficient
determination
(R2)
0.95,
root
mean
square
error
(RMSE)
7.0
μg/m3,
absolute
(MAE)
3.1
μg/m3.
test
predicted
0.862
±
0.0010
CI,
R2
0.80,
RMSE
13.5
MAE
6.9
multiyear
United
States,
Canada,
Europe,
China,
India
11.2
8.2
20.1
51.3
μg/m3
88.6
respectively.
low
continues
decrease
2022.
States
increases
slightly
rate
0.38
μg/m3/decade
1990
decreases
-1.32
1991
Trends
Europe
positive
(5.69
μg/m3/decade)
1972
negative
(-1.91
1973
China
increasing
(3.04
3.35
μg/m3/decade,
respectively)
2012
decreasing
(-38.82
-42.84
2013
dataset
available
National
Tibetan
Plateau
/
Third
Pole
Environment
Data
Center
(https://doi.org/10.11888/Atmos.tpdc.301127)
(Hao
et
al.,
2024).
Ecological Indicators,
Journal Year:
2023,
Volume and Issue:
146, P. 109924 - 109924
Published: Jan. 20, 2023
Rapid
urbanization
has
led
to
economic
growth
with
inevitable
air
pollution.
There
are
significant
differences
in
the
dominant
factors
of
different
pollutants.
However,
influencing
mechanism
on
pollutants
is
still
unclear.
Therefore,
exploring
differential
effects
various
great
significance
for
accelerating
local
collaborative
treatment
and
improving
regional
quality.
Based
analysis
spatial–temporal
pattern
evolution,
spatial
agglomeration,
internal
correlation
six
mainland
China
during
2013–2020,
namely
PM2.5,
PM10,
SO2,
NO2,
O3
CO,
we
combined
environmental
Kuznets
theory
build
a
panel
regression
model
Except
NO2
O3,
concentrations
other
four
all
decreased
degrees,
among
which,
SO2
concentration
most.
The
pollution
showed
that
typical
areas
significantly,
while
which
higher
population
density
or
development
was
relatively
higher.
As
key
factor
affecting
quality,
aspects
have
direction
intensity
effect
relationship
between
conforms
curve
(EKC).
nonlinear
relationships
CO
concentrations,
inverted
"U-shaped",
"N-shaped",
"U-shaped"
respectively.
In
addition,
spillover
whose
reflects
phased
change.
Environment International,
Journal Year:
2023,
Volume and Issue:
174, P. 107889 - 107889
Published: March 21, 2023
In
the
context
of
serious
urban
air
pollution
and
limited
land
resources,
it
is
important
to
understand
environmental
value
ecological
land.
Previous
studies
focused
mostly
on
effectiveness
a
particular
type
green
space
or
total
amount
PM2.5
have
rarely
analyzed
association
between
structure
systematically
quantitatively.
Therefore,
we
took
277
cities
in
China
as
an
example,
comprehensively
compared
results
different
models,
selected
spatial
Durbin
model
using
time-fixed
effects
dissect
degree
influence
types
within
PM2.5.
The
use
was
closely
related
PM2.5,
higher
proportion
was,
lower
direction
functions
differed,
with
forests,
shrubs,
grasslands
causing
weakening
impact
while
wetlands
waters
did
not
role.
reduction
by
single
significantly
smaller
than
that
composite
Green
should
be
considered,
designed
adjusted
planning
continuously
optimize
structure,
increase
landscape
diversity
maximize
benefits.
findings
this
study
help
exploring
under
goal-oriented
control
provide
theoretical
reference
decision-making
support
for
formulating
precise
policies
optimizing
development
national
Atmospheric Pollution Research,
Journal Year:
2024,
Volume and Issue:
15(11), P. 102266 - 102266
Published: July 26, 2024
With
rapid
urbanisation
in
China,
PM2.5
has
become
a
limiting
factor
for
the
sustainable
development
of
cities.
Taking
Yangtze
River
Delta
as
experimental
area,
this
study
analysed
spatial
and
temporal
changes
concentrations
from
2001
to
2020.
It
also
examined
variations,
dispersion,
correlation
with
NDVI
different
vegetation
zones
at
scales.
The
results
showed
that:
(1)
concentration
an
overall
decreasing
trend
during
2001–2020,
change
was
divided
into
two
phases,
starting
increasing
phase
entering
after
2013.
(2)
In
terms
distribution,
show
pattern
low
south
high
north,
focus
shifting
north
over
time.
There
is
levels
particulate
matter
Hefei-Nanjing-Wuxi
area.
(3)
effect
natural
on
reduction
stabilization
atmospheric
better
than
that
artificial
vegetation.
(4)
Needleleaf
forests,
broadleaf
shrubs
are
more
capable
reducing
stabilizing
grasses.
can
provide
reference
regional
air
pollution
control
plant
system
construction.
Sustainability,
Journal Year:
2025,
Volume and Issue:
17(4), P. 1742 - 1742
Published: Feb. 19, 2025
Over
the
past
decade,
China’s
air
quality
has
improved
significantly.
To
further
mitigate
concentration
levels
of
fine
particulate
matter
(PM2.5),
this
study
analyzed
spatio-temporal
evolution
PM2.5
concentrations
from
2012
to
2022.
Furthermore,
integrated
generalized
additive
model
(GAM)
and
GeoDetector
investigate
main
driving
factors
explored
complex
response
relationships
between
these
concentrations.
The
results
showed
following:
(1)
annual
average
in
China
peaked
2013.
reductions
each
city
ranged
1.48
7.33
μg/m3.
In
year,
were
always
consistently
higher
north
east
lowest
northeast
southwest
China.
(2)
terms
spatial
distribution,
North
Plain,
Middle
Lower
Yangtze
River
Sichuan
Basin
exhibited
highest
high
aggregation
characteristics.
(3)
analysis
identified
SO2,
NO2,
CO
meteorological
conditions
as
important
influencing
differentiation
PM2.5.
GAM
that
factors,
such
temperature,
atmospheric
pressure,
wind
speed,
precipitation,
generally
had
specific
inflection
points
their
effects
on
levels.
relationship
with
gross
domestic
product
population
density
followed
an
inverted
U
shape.
under
land
use
types
cropland,
barren,
impervious,
water
than
others.
decreased
significantly
all
types.
Our
work
can
be
used
a
strong
basis
for
providing
insights
crucial
developing
long-term
pollution
control
strategies
promoting
environmental
sustainability.
