Abstract.
Ozone
(O3)
deposition
is
closely
related
to
air
quality,
ecosystem
and
climate
changes.
Due
the
instrument
method
shortage,
O3
was
less
observed
investigated
in
China,
experiencing
significantly
increasing
exposure.
Here,
we
conducted
a
comprehensive
measurement
of
over
wheat
canopy
at
typical
polluted
agricultural
site
North
China
Plain
using
newly
developed
relaxed
eddy
accumulation
system.
For
main
growing
season
2023,
flux
velocity
(Vd)
averaged
-0.25
±
0.39
μg
m-2
s-1
0.29
0.33
cm
s-1,
respectively.
Daytime
Vd
(0.40
0.38
s-1)
obviously
higher
than
nighttime
(0.17
0.26
s-1).
The
temporal
changes
were
mainly
determined
by
crop
growth,
with
predominant
contribution
stomatal
uptake.
Both
daytime
exhibited
significant
increases
decreasing
relative
humidity,
friction
soil
water
content,
enhanced
leaf
area
index.
With
rapid
moisture,
simultaneous
following
overall
increments
detected,
attributed
remarkably
strengthening
uptake
under
increased
conductance
extended
opening
night,
more
non-stomatal
removal
night
resulted
from
strengthened
NO
emission
moist
conditions.
This
study
confirms
leading
effects
growth
on
modulated
environmental
conditions
non-negligible
influences
nocturnal
plant
activities,
emphasizes
needs
for
observation
different
surfaces
accurate
evaluation
impacts
based
fluxes.
Biogeosciences,
Год журнала:
2025,
Номер
22(1), С. 181 - 212
Опубликована: Янв. 10, 2025
Abstract.
A
substantial
body
of
empirical
evidence
exists
to
suggest
that
elevated
O3
levels
are
causing
significant
impacts
on
wheat
yields
at
sites
representative
highly
productive
arable
regions
around
the
world.
Here
we
extend
DO3SE
model
(designed
estimate
total
and
stomatal
deposition
for
risk
assessment)
incorporate
a
coupled
Anet–gsto
uptake;
an
damage
module
(that
instantaneous
Anet
timing
rate
senescence);
crop
phenology,
carbon
allocation,
growth
based
JULES-crop
model.
The
structure
allows
scaling
from
leaf
canopy
allow
multiple
populations
layers.
DO3SE-Crop
is
calibrated
parameterised
using
fumigation
data
Xiaoji,
China,
year
2008
O3-tolerant
sensitive
cultivar.
was
tested
different
years
(2007
2009)
two
additional
cultivars
found
simulate
key
physiological
variables,
development,
yield
with
good
level
accuracy.
simulated
phenological
stages
development
under
ambient
treatments
test
datasets
R2
0.95
RMSE
2.5
d.
also
able
O3-induced
losses
∼11
%–19
%
compared
observed
12
%–34
%,
0.68
(n=20)
76
g
m−2.
Additionally,
our
results
indicate
variance
in
reduction
primarily
attributed
premature
decrease
assimilation
grains
caused
by
accelerated
senescence,
which
brought
forward
3–5
d
treatments.
Atmospheric chemistry and physics,
Год журнала:
2025,
Номер
25(1), С. 347 - 366
Опубликована: Янв. 9, 2025
Abstract.
Due
to
considerable
reductions
in
nitrogen
oxides
(NOx),
ozone
trends
and
variations
eastern
China
remain
inadequately
understood.
Long-term
observations
of
precursors
were
conducted
explore
the
factors
influencing
this
region.
Combined
with
satellite
surface
measurements,
we
evaluated
low
(2nd
percentile),
typical
(50th
peak
(98th
percentile)
concentrations
detail.
Observations
indicate
a
significant
decrease
(−0.5
%
yr−1),
alongside
an
increase
(0.3
across
during
May–September
from
2017
2022.
The
decline
is
notably
slower
than
that
concentrations,
which
approximately
−0.02
ppb
yr−1
(−0.0
yr−1)
same
period.
Anthropogenic
emissions
primarily
drive
China,
though
meteorological
effects
also
play
role.
Ozone
formation
sensitivity
shifts
volatile
organic
compound
(VOC)-limited
or
transitional
regimes
morning
(08:00–11:00
local
time,
LT),
when
rise
sharply,
NOx-limited
around
(∼
14:00
LT).
reduction
NOx
identified
as
key
factor
driving
aiming
further
reduce
exceedance
days.
Thus,
controlling
emerges
crucial
for
mitigating
levels.
Moreover,
can
be
attributed
both
anthropogenic
factors.
Our
findings
underscore
beneficial
impacts
on
managing
Regular
changes
throughout
day
should
considered
formulating
effective
control
policies.
IEEE Transactions on Geoscience and Remote Sensing,
Год журнала:
2024,
Номер
62, С. 1 - 14
Опубликована: Янв. 1, 2024
The
escalating
surface
ozone
(O
3
)
pollution
in
urban
areas
throughout
China
has
raised
significant
concerns
due
to
its
detrimental
impacts
on
public
health,
local
environment
and
agriculture.
Despite
of
numerous
efforts
O
estimation,
intricate
geographical
spatiotemporal
interactions
the
potential
predictors
been
largely
overlooked.
This
limitation
significantly
constrained
estimation
accuracy.
To
address
this
issue,
we
proposed
a
novel
deep
neural
Network,
named
Geo-STO3Net,
effectively
integrate
adjacent
Geographical
SpatioTemporal
information
from
meteorological
data
satellite
observations
into
estimation.
Geo-STO3Net
model
used
spatial
encoder
based
Residual
temporal
Transformer,
feature
decoder
Deep
Neural
Networks
comprehensively
capture
dependencies
among
predictors.
Our
achieved
cross-validation
(CV)
R
2
value
0.95,
outperforming
popular
models.
demonstrated
robust
transferability,
as
evidenced
by
values
0.94
0.82
external
validation
monthly
scales,
respectively.
model's
proficiency
handling
led
substantial
performance
improvements
compared
models
lacking
feature,
with
improved
CV
ranging
0.01
0.18.
findings
also
highlighted
severe
over
Yangtze
River
Delta
(YRD)
region
2022,
average
concentrations
reaching
103.14
μg/m
xmlns:xlink="http://www.w3.org/1999/xlink">3
.
These
evidences
indicate
our
can
accurately
estimate
concentrations,
provide
valuable
insights
development
effective
control
policies.
