Tropospheric ozone change from 1980 to 2010 dominated by equatorward redistribution of emissions

Abstract

Ozone is an important air pollutant at the surface, and the third most important anthropogenic greenhouse gas in the troposphere. Since 1980, anthropogenic emissions of ozone precursors - methane, non-methane volatile organic compounds, carbon monoxide and nitrogen oxides (NO x) - have shifted from developed to developing regions. Emissions have thereby been redistributed equatorwards, where they are expected to have a stronger effect on the tropospheric ozone burden due to greater convection, reaction rates and NO x sensitivity. Here we use a global chemical transport model to simulate changes in tropospheric ozone concentrations from 1980 to 2010, and to separate the influences of changes in the spatial distribution of global anthropogenic emissions of short-lived pollutants, the magnitude of these emissions, and the global atmospheric methane concentration. We estimate that the increase in ozone burden due to the spatial distribution change slightly exceeds the combined influences of the increased emission magnitude and global methane. Emission increases in Southeast, East and South Asia may be most important for the ozone change, supported by an analysis of statistically significant increases in observed ozone above these regions. The spatial distribution of emissions dominates global tropospheric ozone, suggesting that the future ozone burden will be determined mainly by emissions from low latitudes.

Full text

LETTERS
PUBLISHED ONLINE: 7 NOVEMBER 2016 | DOI: 10.1038/NGEO2827
Tropospheric ozone change from 1980 to 2010
dominated by equatorward redistribution
of emissions
Yuqiang Zhang1†, Owen R. Cooper2,3, Audrey Gaudel2,3, Anne M. Thompson4, Philippe Nédélec5,
Shin-Ya Ogino6and J. Jason West1*
Ozone is an important air pollutant at the surface1, and
the third most important anthropogenic greenhouse gas in
the troposphere2. Since 1980, anthropogenic emissions of
ozone precursors—methane, non-methane volatile organic
compounds, carbon monoxide and nitrogen oxides (NOx)—
have shifted from developed to developing regions. Emissions
have thereby been redistributed equatorwards3–6, where they
are expected to have a stronger eect on the tropospheric
ozone burden due to greater convection,reaction rates and NOx
sensitivity7–11. Here we use a global chemical transport model
to simulate changes in tropospheric ozone concentrations
from 1980 to 2010, and to separate the influences of
changes in the spatial distribution of global anthropogenic
emissions of short-lived pollutants, the magnitude of these
emissions, and the global atmospheric methane concentration.
We estimate that the increase in ozone burden due to the
spatial distribution change slightly exceeds the combined
influences of the increased emission magnitude and global
methane. Emission increases in Southeast, East and South Asia
may be most important for the ozone change, supported by an
analysis of statistically significant increases in observed ozone
above these regions. The spatial distribution of emissions
dominates global tropospheric ozone, suggesting that the
future ozone burden will be determined mainly by emissions
from low latitudes.
Ozone (O3) production in the troposphere, by the oxidation of
carbon monoxide (CO), non-methane volatile organic compounds
(NMVOCs) and methane (CH4) in the presence of nitrogen
oxides (NOx) and sunlight, exceeds the stratosphere-to-troposphere
exchange by a factor of 5–7 (ref. 12). O3is an urban and regional
air pollutant, but is also sufficiently long-lived (∼22 days globally
averaged12) that its baseline concentrations are elevated over the
entire Northern Hemisphere13 (NH). Observations14 and models15,16
have associated emission increases in Asia with increasing O3above
western North America. The tropospheric O3burden (BO3) is an
important quantity that is related to radiative forcing (RF), as O3
is more effective as a greenhouse gas in the middle and upper
troposphere than near the surface2, and to surface air quality because
it influences both urban and rural baseline ozone.
From 1940 to 1980, global anthropogenic emissions of O3
precursors increased, but the spatial distribution remained fairly
unchanged, with the greatest emissions in the NH middle and high
latitudes. Starting in 1980, emissions began to shift equatorward as
China and low-latitude nations became more industrialized. From
1980 to 2010, global anthropogenic emissions of CO, NOxand
NMVOCs are estimated to have increased by 6.4%, 21.2% and 6.0%
(ref. 5,17), and the global CH4mixing ratio increased by 14.7%
(231 ppbv, Methods). During the same period, emissions of CO
and NMVOCs increased south of 30◦N but decreased north of
this latitude, while NOxemissions increased south of 40◦N but
decreased to the north (Supplementary Figs 1 and 2).
Here we investigate the influences of global emission changes
from 1980 to 2010 on BO3and surface O3, separating the influences
of changes in: the spatial distribution of anthropogenic short-
lived emissions; the global magnitude of emissions; and the
global CH4mixing ratio. Simulations are conducted with the
CAM-chem18 global chemical transport model for 1980 and 2010,
and sensitivity simulations alter these three parameters individually
to 1980 conditions, relative to the 2010 simulation (Methods and
Supplementary Table 1).
The global BO3is modelled to have increased by 28.12 Tg
(8.9%) from 1980 to 2010 (four-year averages), with 57% of the
total increase in the NH (Fig. 1). The largest BO3increases are
over 30◦S–30◦N (17.93 Tg, Figs 1 and 2). The influence of the
change in the spatial distribution of global anthropogenic emissions
contributes 16.39Tg of the total tropospheric O3burden change
(1BO3), also with a greater influence in the NH than in the Southern
Hemisphere (SH), slightly greater than the combined influences of
the change in emission magnitude (8.59Tg) and the global CH4
change (7.48 Tg) (Fig. 2). The influence of the change in spatial
distribution is greater than the sum of the other two influences
in three of four years modelled, with the interannual variability in
1BO3being much smaller than the overall change (Supplementary
Table 2). The sensitivity of BO3to CH4here (0.123 Tg BO3per Tg
CH4a−1) is within the range of other models (0.11–0.16 Tg BO3per
Tg CH4a−1, ref. 19). Note that the total 1BO3from the sum of the
three sensitivity simulations (32.46Tg) is larger than the difference
between S_2010 (Supplementary Table 1) and S_1980 (28.12 Tg), as
only one variable is changed to 1980 conditions in each simulation.
Over 30◦S–30◦N, the 1BO3from the emission spatial distribution
change is much greater than the other influences. In extratropical
regions, the 1BO3from the emission spatial distribution change
is only slightly greater or comparable to 1BO3from the other
influences. North of 60◦N, the 1BO3due to the emission spatial
1Environmental Sciences and Engineering Department, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA.
2Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado 80309, USA. 3Chemical Sciences Division, NOAA
Earth System Research Laboratory, Boulder, Colorado 80305, USA. 4NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA. 5Laboratoire
d’Aérologie, CNRS, Université Paul Sabatier Toulouse III, FR-31062 Toulouse, France. 6Japan Agency for Marine-Earth Science and Technology, Yokosuka
237-0061, Japan. †Present address: Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA. *e-mail: jjwest@email.unc.edu
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LETTERS NATURE GEOSCIENCE DOI: 10.1038/NGEO2827
28.1216.398.597.48
0 6 12 18 24 30
Burden change (Tg O3)
Burden change (Tg O3)
Total
Spatial pattern
Magnitude
Global CH4
Total
Spatial pattern
Magnitude
Global CH4
Global
NH
SH
0246810
>60° N
30°–60° N
0°–30° N
30°–0° S
60°–30° S
90°–60° S
Figure 1 | Tropospheric O3burden change (1BO3) from 1980 to 2010.
1BO3is shown globally, in each hemisphere, and in dierent latitudinal
bands. The estimated components of 1BO3due to the emission spatial
distribution change (red square), magnitude change (blue triangle) and
global CH4change (purple circle) are also seen.
distribution change is lowest, as lower amounts of O3and its
precursors are transported from North America and Europe.
Between 1980 and 2010, the greatest modelled increases in
O3burden are over 10◦–35◦N from the surface to the upper
troposphere (Fig. 3). Sixty-eight per cent of 1BO3is below 500 hPa,
although the greatest changes in mixing ratio are in the middle
and upper troposphere (Supplementary Fig. 4). Notable O3
increases are also seen over 30◦S–10◦N. Over 35◦–60◦N, O3
increases at all altitudes, even though anthropogenic emissions
from North America and Europe decreased between 1980 and 2010
(Supplementary Figs 1–3). The influences of the global emission
magnitude change and the global CH4change both increase O3
over 30◦S–35◦N, but the emission spatial distribution change best
explains the overall O3change, particularly the regions with greatest
ozone increases. Increases in O3precursor emissions south of 35◦N
are transported efficiently to the middle and upper troposphere,
from strong convection in the Hadley cell, whereas emission
decreases north of 35◦N stay at high latitudes and low elevation in
Ferrell cell circulation (Fig. 4). When global emissions shift equator-
ward, strong convective mixing over the tropics and subtropics lifts
O3and its precursor NOyto higher altitudes (Figs 3b and 4b and
Supplementary Figs 4 and 5), where the O3lifetime is longer, favour-
ing O3accumulation. When emission increases occur in NH mid-
latitudes, less NOyis lofted to high altitudes (Fig. 4c). O3increases
at high altitudes over middle and high latitudes are affected by the
transport of pollutants from the tropics and subtropics16,20 (Fig. 3b).
In addition to strong convection, the tropics and subtropics have
faster chemical reaction rates than other regions (Supplementary
Fig. 6), due to the strong sunlight and warm temperatures.
Therefore, changes in the O3chemical production (PO3), and loss
(LO3) rates are greater for the spatial distribution change than
for the magnitude change, due to greater low-latitude emissions
(Supplementary Fig. 7). Similarly, the distribution change increases
the global ozone production efficiency, whereas the magnitude
change decreases it. In addition, strong NOxsensitivity prevails
over the tropics and subtropics, especially in the middle and upper
troposphere (Supplementary Figs 8 and 9), and emission trends
show greater increases of NOxthan of NMVOCs (Supplementary
Fig. 1). Finally, O3lifetime is lower over the tropics, due to
destruction from water vapour and dry deposition to vegetated
surfaces20. However, this effect is clearly not dominant as we see
larger O3increases over the tropics.
In Fig. 2, the largest modelled 1BO3occurs over South and
Southeast Asia, suggesting a strong influence of emission increases
in these regions. We estimate the importance of different regions
for BO3by multiplying the change in NOxemissions in each of nine
90° N
a
60° N
30° N
0°
30° S
60° S
90° S
180°120° W60° W
Longitude
Latitude
0°
28.12 Tg 16.39 Tg
8.59 Tg 7.48 Tg
60° E 120° E 180°
90° N
60° N
30° N
0°
30° S
60° S
90° S
180°120° W60° W
Longitude
Latitude
0°60° E 120° E 180°
90° N
60° N
30° N
0°
30° S
60° S
90° S
180°120° W60° W
Longitude
Latitude
0°
−0.10 −0.06 −0.02
Tons km−2
0.02 0.06 0.10
−0.08 −0.04 0.00 0.04 0.08
60° E 120° E 180°
90° N
60° N
30° N
0°
30° S
60° S
90° S
180°120° W60° W
Longitude
Latitude
0°60° E 120° E 180°
b
cd
Figure 2 | Spatial distributions for 1BO3(tons km−2) from 1980 to 2010. a, Total changes from 1980 to 2010. b–d, Influences of changes in the global
emissions spatial distribution (b), the global emissions magnitude (c), and global CH4mixing ratio (d).
2
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NATURE GEOSCIENCE DOI: 10.1038/NGEO2827 LETTERS
1,000
850
700
500
400
300
Pressure (mb)
Height (km)
250
200
150
100
a
2
2
2
2
2
4
4
4
6
1,000
850
0°30° S60° S90° S30° N
−9 −7 −5 −3 −1 1 3 5 7 9−8 −6 −4 −2 0 2 4 6 8
60° N90° N0°30° S60° S90° S30° N60° N90° N
0°
Latitude Latitude
Latitude Latitude
30° S60° S90° S30° N60° N90° N0°30° S60° S90° S
4
8
12
16
Height (km)
4
8
12
16
30° N60° N90° N
700
500
400
300
Pressure (mb)
250
200
150
100
Tons km−3
b
cd
Figure 3 | Zonal annual average O3change. a, Total change from 1980 to 2010. b–d, Influences of changes in the global emissions spatial distribution (b),
the global emissions magnitude (c), and global CH4mixing ratio (d).
world regions by the sensitivity of BO3per unit NOxemissions from
ref. 9 (Supplementary Table 3). Doing so, we find that emissions
changes from Southeast Asia are most important for the 1980–2010
global 1BO3, followed by East Asia and South Asia. Southeast Asia
emerges as most important—although its emission increase is only
22% that from East Asia—because of the very large sensitivity of
BO3to NOx. Strong convection over Southeast Asia contributes
to this large sensitivity. Convection over the Himalayas in the
NH summer, when the intertropical convergence zone is farthest
north, also suggests a pathway for South Asian emissions to the
upper troposphere20 (Supplementary Figs 10 and 11). Future work
should model the contributions of emissions changes from each
region individually.
Surface O3changes, using the three-month O3-season maximum
daily 8-h average O3(MDA8) (Supplementary Fig. 12), are
dominated by regional emission trends: decreases within Europe
and North America, and increases over East and Southeast Asia,
consistent with observations1,21. Similar regional variations of
MDA8 O3are also seen from the influence of the global emission
spatial pattern change. The MDA8 change between 1980 and
2010 is therefore also dominated by the global emission spatial
pattern change, with smaller contributions from the global emission
magnitude and CH4changes.
These modelled ozone changes are broadly consistent with ob-
served changes over recent decades that show strong increases in
South, East and Southeast Asia (Supplementary Information)21.
In particular, our analyses of ozone observations from IAGOS
commercial aircraft22 and SHADOZ ozonesondes23 in these re-
gions show good agreement with the model, and changes from
1994–2004 to 2005–2014 that are similar to the modelled 1980–2010
changes (Supplementary Figs 13–15 and Supplementary Table 4);
over Southeast Asia and southern India, we show for the first time
statistically significant ozone increases at most elevations, whereas
for northeastern China, we show that the positive trends detected
earlier24 have continued. We also find that S_1980 compares well
with the global ozonesonde climatology of ref. 25, and S_2010 with
that of ref. 26 (Supplementary Figs 16 and 17), but is biased high
at 200 mb in S_1980 between 30◦S and the Equator, and that bias
increases in S_2010 between 30◦S and 30◦N. Given that most of the
modelled 1BO3is below 500 mb, the bias at 200 mb is probably not
very important for our main findings. Comparing the 1980–2010
ozone trends at long-term observation sites, the model overesti-
mates the 1980–2010 ozone change at two of three NH-midlatitude
long-term ozonesonde sites (Supplementary Fig. 18), and captures
well the 1980–2010 O3trend at five of six rural or remote surface
sites, although tending to overestimate the trend and to overestimate
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3

LETTERS NATURE GEOSCIENCE DOI: 10.1038/NGEO2827
−0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5
Tons km−3
1,000
850
700
500
400
300
Pressure (mb)
250
200
150
100
a
0°
Latitude Latitude
Latitude Latitude
30° S60° S90° S30° N60° N90° N
1,000
850
700
500
400
300
Pressure (mb)
250
200
150
100
0°30° S60° S90° S30° N60° N90° N 0°30° S60° S90° S30° N60° N90° N
90° N0°30° S60° S90° S
4
8
12
16
4
8
12
16
30° N60° N
0.1
0.1
0.1
0.1
0.1
b
cd
Figure 4 | Zonal annual average NOychange. a, Total changes from 1980 to 2010. b–d, Influences of changes in the global emissions spatial
distribution (b), the global emissions magnitude (c), and global CH4mixing ratio (d). See Methods for the NOydefinition.
O3in the NH and underestimate in the SH (Supplementary Fig. 19
and Supplementary Table 5). Compared with OMI/MLS satellite ob-
servations27, S_2010 has high biases for BO3, particularly in the trop-
ics and subtropics including over Africa (Supplementary Fig. 20),
that are comparable to the simulated 1980–2010 burden change
(Supplementary Tables 6 and 7), and thus the model may overstate
the magnitude of the tropical and subtropical ozone changes. How-
ever, OMI/MLS trends in ozone columns from 2004 to 2015 show
the greatest growth over South and Southeast Asia (Supplementary
Fig. 21), consistent with the model (Fig. 2). Despite model biases,
these observations provide strong evidence for ozone increases
where the model predicts the greatest increases.
Observations have also shown that the ozone peak has shifted
earlier in the year at rural NH sites, and emissions moving equator-
ward has been hypothesized as an explanation21,28. However, S_2010
does not show the observed shift in the timing of ozone peaks
relative to S_1980, nor does S_Distribution (Supplementary Fig. 22).
Uncertainty in historical emissions and seasonal distributions, or
inaccuracies in model chemistry or physics29, may be the reasons
for our inability to explain these observations.
By using the same meteorology in 1980 and 2010, we neglect the
possible effects of climate change or climate variability on 1BO3.
We also evaluate the contributions of each parameter by simulating
1980 conditions for each parameter individually, relative to the 2010
simulation, and 1BO3would probably be smaller had we evaluated
relative to 1980. However, we expect that the relative contributions
would be similar.
These results are expected to have important implications for
the RF of O3. However, increasing NOxmay cause a negative RF,
due mainly to decreases in CH4, and regions with high sensitivity
of BO3to NOxemissions also have a high sensitivity of CH4to
NOx, with the two RFs roughly cancelling over all source regions7,10.
CO is sufficiently long-lived that the sensitivity of BO3does not
vary strongly with the location of CO emissions30. The effect of the
equatorward emission shift on RF should be investigated further.
The change in the spatial distribution of the global anthropogenic
emissions from 1980 to 2010 dominates the BO3change, and is
slightly greater than the combined effects of changes in the global
emission magnitude and global CH4. In particular, increases in
O3precursor emissions in the tropics and subtropics significantly
influence the global BO3, and our findings suggest that emissions
increases from Southeast, East and South Asia have been most
important for the BO3increase. This can be attributed to the strong
photochemical reaction rates, convection and NOxsensitivity in the
4
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NATURE GEOSCIENCE DOI: 10.1038/NGEO2827 LETTERS
tropics and subtropics. As a result, the global BO3might continue to
increase due to a continued equatorward shift of emissions, even if
global anthropogenic emissions remain unchanged or decrease. The
location of emissions and the dominant role of emissions from the
tropics and subtropics deserve greater emphasis in future research
and projections of global tropospheric ozone.
Methods
Methods, including statements of data availability and any
associated accession codes and references, are available in the
online version of this paper.
Received 29 March 2016; accepted 27 September 2016;
published online 7 November 2016
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Acknowledgements
Y.Z. and J.J.W. were funded by National Institute of Environmental Health Sciences grant
no. 1 R21 ES022600-01 and Environmental Protection Agency STAR grants no. 834285
and RD83587801, and O.R.C. and A.G. were funded by NOAA’s Health of the
Atmosphere and Atmospheric Chemistry and Climate Programs. The contents are solely
the responsibility of the grantee and do not necessarily represent the official views of the
US EPA or other funding sources. We thank the NCAR AMWG for developing and
maintaining the diagnostic package for the model evaluation. We acknowledge the free
use of O3observation data from NOAA GMD for the remote sites of Barrow, Mauna Loa,
Samoa and South Pole; Global Atmosphere Watch World Data Centre for Greenhouse
Gases for Hohenpeissenberg, J. Schwab from University at Albany-SUNY for Whiteface
Mountain, and P. Young of Lancaster University for processed ozonesonde climatology
of ref. 25.
Author contributions
Y.Z., J.J.W. and O.R.C. designed the study and Y.Z. and J.J.W. planned the model
experiments. Y.Z. prepared the emission inputs, performed the model simulations, and
prepared the figures. Y.Z. and A.G. conducted data analysis for observations, and J.J.W.
and O.R.C. assisted with the data analysis. P.N., S.-Y.O. and A.M.T. provided
observational data. Y.Z., J.J.W. and O.R.C. wrote the paper with comments from A.M.T
and A.G.
Additional information
Supplementary information is available in the online version of the paper. Reprints and
permissions information is available online at www.nature.com/reprints.
Correspondence and requests for materials should be addressed to J.J.W.
Competing financial interests
The authors declare no competing financial interests.
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5

LETTERS NATURE GEOSCIENCE DOI: 10.1038/NGEO2827
Methods
Global emissions spatial pattern change. Here we use anthropogenic emissions
including biomass burning in 1980 from the Atmospheric Chemistry and Climate
Model Intercomparison Project (ACCMIP, ref. 5), and in 2010 from the
representative concentration pathways 8.5 (RCP8.5) scenario17,31, which are
downloaded from the RCP database (http://tntcat.iiasa.ac.at:8787/RcpDb/dsd?
Action=htmlpage&page=download, accessed 10/31/2014) to analyse emission
trends and drive the global model (Supplementary Figs 1 and 2). RCP8.5 2010
emissions are self-consistent with the ACCMIP historical emissions, and are
considered to be the most reasonable scenario to extend ACCMIP emissions
beyond 2000 (ref. 6) as they track the GAINS current legislation scenario for
several decades17. The 2010 global total anthropogenic emissions of CO, NOxand
non-methane volatile organic compounds (NMVOCs) are 1030 Tg, 82 Tg NO and
180 Tg, respectively. As with other global emission estimates for short-lived species,
emissions are uncertain and may be especially uncertain in some developing
regions29,32–34. The rapid growth of emissions in the tropics and subtropics is seen in
global emission inventories5,6 as well as regional ones35,36. These inventories are
supported by observations from satellites3,4,37,38 and from surface and airborne
observations29,39 that show that NO2in developed regions, such as Europe and
North America, have greatly diminished emissions since 1980, but the emissions
are increasing in developing countries, especially China and India, shifting global
emissions equatorward.
CAM-chem model configuration. We use the global chemistry–climate model
CAM-chem, which is based on the global Community Atmosphere Model (CAM)
version 4, the atmospheric component of the Community Earth System Model
(CESM, v1.2.2) (refs 18,40). The model has a horizontal resolution of 1.9◦(latitude)
×2.5◦(longitude), and 56 vertical levels between the surface and 4 hPa (≈40 km)
with a time step of 1,800 s. We use the NASA Global Modeling and Assimilation
Office GEOS-5 meteorology to drive the model as a chemical transport model. For
all simulations, we run CAM-chem for five consecutive years, with the first year as
spin-up and results are shown as a four-year average. Monthly mean distributions
of chemically active stratospheric species (such as O3, NO, NO2and N2O5) are
prescribed using the climatology from the Whole Atmospheric Community
Climate Model simulations41, following ref. 18. We use a single global chemical
transport model, and results with other models may differ, particularly due to
different reaction mechanisms.
NMVOC species from ACCMIP (1980) and RCP8.5 (2010) are both
re-speciated to match the CAM-chem VOC categories following previous
studies30,42,43. Monthly temporal variations for all anthropogenic emission sectors
are also added based on the monthly time dependence of emissions from
RETRO30,42–44, except for aircraft, shipping and biomass burning for which seasonal
variations were provided. The Model of Emissions of Gases and Aerosols from
Nature (MEGAN-v2.1, ref. 45) simulates biogenic emissions for 150 compounds
online within CAM-chem, yielding four-year average global biogenic emissions of
isoprene, monoterpene, methanol and acetone of 420.69 Tgyr−1, 133.23 Tg yr−1,
91.99 Tg yr−1and 42.67 Tg yr−1. Lightning NOxemissions are calculated online as
3.21 TgN yr−1(four-year average), which is lower than the average of ACCMIP
models for 2000, but within the range12; lower lightning NOxemissions may affect
the sensitivity of ozone to NOxand VOCs, particularly in the tropics and
mid-troposphere where lightning emissions are greatest. Other natural emissions
(ocean, volcano and soil) are from the standard CAM-chem emission files (for
2000), and remain the same for all of the simulations, with soil NOxat 8.0 TgN yr−1
(refs 18,46). The CH4volume mixing ratio (ppb) is fixed at uniform global values of
1,567 and 1,798 ppbv for 1980 and 2010 (ref. 47).
In addition to simulating 1980 and 2010, we conduct three sensitivity
simulations in which the spatial distribution of global anthropogenic emissions
(S_Distribution), the magnitude of the global emissions (S_Magnitude), and the
global CH4mixing ratio (S_CH4) are individually set to 1980 levels and all other
parameters stay the same as the 2010 simulation (Supplementary Table 1). Here
global anthropogenic emissions refer to all short-lived species, including ozone
precursors and other species such as aerosols, from anthropogenic sources
including biomass burning. The differences between S_2010 and S_1980 reflect the
total emission changes from 1980 to 2010. Each of the other three simulations is
subtracted from S_2010 to isolate individual influences. We use meteorology from
2009–2012 with 2008 as a spin-up for all simulations, isolating the effects of
changes in emissions and neglecting possible effects of climate variability or change
from 1980 to 2010.
Tropospheric O3burden (BO3) is defined as the total below the chemical
tropopause of 150 ppbv ozone in the S_2010 simulation, with the same tropopause
applied to all simulations. The four-year average BO3in S_2010 is 342.7 Tg, within
the range of ACCMIP models (337 ±23 Tg for 1995–2005), and the 1980–2010
1BO3of 28.12 Tg is similar to the ACCMIP 15 ±6 Tg for 1980–2000, and 41 ±12
for 1980–2030 (RCP8.5) (ref. 12). The three-month ozone season average MDA8 is
found for the consecutive three-month period with the highest MDA8 in each grid
cell. NOy(total reactive nitrogen) is calculated as NO +NO2+NO3+HNO3+
HO2NO2+2×N2O5+CH3CO3NO2(PAN) +CH2CCH3CO3NO2(MPAN,
methacryloyl peroxynitrate) +CH2CHCCH3OOCH2ONO2(ISOPNO3, peroxy
radical from NO3+isoprene) from CAM-chem output.
CAM-chem evaluation. A comprehensive evaluation of S_2010 is performed using
a present-day climatology of O3data from multi-year observations from
ozonesondes, satellites, aircraft campaigns, and ground-based observations,
compared with the four-year average of CAM-chem output. Our model captures
the vertical distribution of O3in ozonesondes26 very well, although it is biased high
between 30◦S and 30◦N, particularly in the upper troposphere (Supplementary
Fig. 23 and Supplementary Table 8). The seasonal cycles of O3at specific pressure
levels from the ozonesonde data are also captured well by the model
(Supplementary Fig. 24), with a correlation coefficient between the observed and
simulated monthly regional O3average that is usually greater than 0.8
(Supplementary Fig. 25). When evaluating model performance with aircraft
campaign observations, we focus on the regional average over the campaign areas,
and analyse the data at different altitudes. Generally, the model performs better in
the NH than the SH (Supplementary Fig. 26 and Supplementary Table 9). When
evaluated with multi-year satellite data27, the model overestimates O3between
20◦S and 40◦N, which is common for global models12, with a modelled global BO3
that is 23.8 Tg higher (Supplementary Fig. 20). Compared with surface O3
observations, S_2010 overestimates O3by 5.75 ppbv averaged over all stations in
the US (Supplementary Fig. 27), and 0.65 ppbv over Europe (Supplementary
Fig. 28), but captures well the seasonal cycles.
Code availability. The CAM-chem model code used to perform all the simulations
is available at: https://www2.cesm.ucar.edu/models.
The diagnostic package used to perform the model evaluation is developed and
maintained by the NCAR AMWG, and code can be found at:
https://www2.cesm.ucar.edu/working-groups/amwg/amwg-diagnostics-
package/find-code.
Data availability. Hourly O3observations for the remote sites of Barrow,
Mauna Loa, Samoa and South Pole are maintained by the NOAA Global
Monitoring Division (GMD) and can be found at: ftp://aftp.cmdl.noaa.gov/data/
ozwv/SurfaceOzone.
Hourly ozone data from Hohenpeissenberg for the years 1971–2010 were
downloaded from the Global Atmosphere Watch (GAW) World Data Centre for
Greenhouse Gases: http://ds.data.jma.go.jp/gmd/wdcgg. The Meteorological
Observatory Hohenpeissenberg is operated and financed by the German
Meteorological Service (DWD).
The Whiteface Mountain Summit ozone data were collected by the University
at Albany-SUNY with instrumentation provided by the New York State
Department of Environmental Conservation. The data set was provided by
J. J. Schwab, Atmospheric Sciences Research Center, University at Albany-SUNY,
and is archived by the United States Environmental Protection Agency:
http://www.epa.gov/ttn/airs/aqsdatamart.
Ozone profiles from commercial aircraft were collected and made freely
available by the Measurement of Ozone and water vapour on Airbus In-service
airCraft – In-service Aircraft for a Global Observing System (MOZAIC-IAGOS)
programme (www.iagos.org). The data were made possible by: the European
Commission’s support for the MOZAIC project (1994–2003) and the preparatory
phase of IAGOS (2005–2012); the partner institutions of the IAGOS Research
Infrastructure (FZJ, DLR, MPI, KIT in Germany, CNRS, CNES, Météo-France in
France and the University of Manchester in the UK); ETHER (CNES-CNRS/INSU)
for hosting the database; and the participating airlines (Lufthansa, Air France,
Austrian, China Airlines, Iberia, Cathay Pacific) for the transport free of charge of
the instrumentation.
The Hanoi, Vietnam ozonesondes were made freely available by the
NASA Southern Hemisphere ADditional OZonesondes (SHADOZ) project23.
The processed ozonesonde climatology of ref. 25 was shared by P. Young of
Lancaster University.
Monthly OMI/MLS tropospheric column ozone data27 were provided by
J. Ziemke, Morgan State University, Baltimore, and downloaded from:
http://acd-ext.gsfc.nasa.gov/Data_services/cloud_slice. The OMI/MLS
tropospheric column ozone product is derived from the Ozone Monitoring
Instrument (OMI) and Microwave Limb Sounder (MLS) remote sensors onboard
NASA’s polar orbiting Aura satellite. MLS retrievals are the latest available,
version 4.2.
The data that support the findings of this study are available from the
corresponding author on request.
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