The global atmospheric environment for the next generation.
ABSTRACT Air quality, ecosystem exposure to nitrogen deposition, and climate change are intimately coupled problems: we assess changes in the global atmospheric environment between 2000 and 2030 using 26 state-of-the-art global atmospheric chemistry models and three different emissions scenarios. The first (CLE) scenario reflects implementation of current air quality legislation around the world, while the second (MFR) represents a more optimistic case in which all currently feasible technologies are applied to achieve maximum emission reductions. We contrast these scenarios with the more pessimistic IPCC SRES A2 scenario. Ensemble simulations for the year 2000 are consistent among models and show a reasonable agreement with surface ozone, wet deposition, and NO2 satellite observations. Large parts of the world are currently exposed to high ozone concentrations and high deposition of nitrogen to ecosystems. By 2030, global surface ozone is calculated to increase globally by 1.5 +/- 1.2 ppb (CLE) and 4.3 +/- 2.2 ppb (A2), using the ensemble mean model results and associated +/-1 sigma standard deviations. Only the progressive MFR scenario will reduce ozone, by -2.3 +/- 1.1 ppb. Climate change is expected to modify surface ozone by -0.8 +/- 0.6 ppb, with larger decreases over sea than over land. Radiative forcing by ozone increases by 63 +/- 15 and 155 +/- 37 mW m(-2) for CLE and A2, respectively, and decreases by -45 +/- 15 mW m(-2) for MFR. We compute that at present 10.1% of the global natural terrestrial ecosystems are exposed to nitrogen deposition above a critical load of 1 g N m(-2) yr(-1). These percentages increase by 2030 to 15.8% (CLE), 10.5% (MFR), and 25% (A2). This study shows the importance of enforcing current worldwide air quality legislation and the major benefits of going further. Nonattainment of these air quality policy objectives, such as expressed by the SRES-A2 scenario, would further degrade the global atmospheric environment.
- SourceAvailable from: Donatella ZonaEnvironmental Pollution 01/2014; 184. · 3.73 Impact Factor
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ABSTRACT: Within the European Space Agency's Climate Change Initiative, total ozone column records from GOME (Global Ozone Monitoring Experiment), SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY), and GOME-2 have been reprocessed with GODFIT version 3 (GOME-type Direct FITting). This algorithm is based on the direct fitting of reflectances simulated in the Huggins bands to the observations. We report on new developments in the algorithm from the version implemented in the operational GOME Data Processor v5. The a priori ozone profile database TOMSv8 is now combined with a recently compiled OMI/MLS tropospheric ozone climatology to improve the representativeness of a priori information. The Ring procedure that corrects simulated radiances for the rotational Raman inelastic scattering signature has been improved using a revised semi-empirical expression. Correction factors are also applied to the simulated spectra to account for atmospheric polarization. In addition, the computational performance has been significantly enhanced through the implementation of new radiative transfer tools based on principal component analysis of the optical properties. Furthermore, a soft-calibration scheme for measured reflectances and based on selected Brewer measurements has been developed in order to reduce the impact of level-1 errors. This soft-calibration corrects not only for possible biases in backscattered reflectances, but also for artificial spectral features interfering with the ozone signature. Intersensor comparisons and ground-based validation indicate that these ozone data sets are of unprecedented quality, with stability better than 1% per decade, a precision of 1.7%, and systematic uncertainties less than 3.6% over a wide range of atmospheric states.Journal of Geophysical Research 02/2014; · 3.17 Impact Factor
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ABSTRACT: Bryophyte establishment represents a positive feedback process that enhances soil development in newly exposed terrain. Further, biological nitrogen (N) fixation by cyanobacteria in association with mosses can be an important supply of N to terrestrial ecosystems, however the role of these associations during post-glacial primary succession is not yet fully understood. Here, we analyzed chronosequences in front of two receding glaciers with contrasting climatic conditions (wetter vs drier) at Cordillera Darwin (Tierra del Fuego) and found that most mosses had the capacity to support an epiphytic flora of cyanobacteria and exhibited high rates of N2 fixation. Pioneer moss-cyanobacteria associations showed the highest N2 fixation rates (4.60 and 4.96 µg N g-1 bryo. d-1) very early after glacier retreat (4 and 7 years) which may help accelerate soil development under wetter conditions. In drier climate, N2 fixation on bryophyte-cyanobacteria associations was also high (0.94 and 1.42 µg N g-1 bryo. d-1) but peaked at intermediate-aged sites (26 and 66 years). N2 fixation capacity on bryophytes was primarily driven by epiphytic cyanobacteria abundance rather than community composition. Most liverworts showed low colonization and N2 fixation rates, and mosses did not exhibit consistent differences across life forms and habitat (saxicolous vs terricolous). We also found a clear relationship between cyanobacteria genera and the stages of ecological succession, but no relationship was found with host species identity. Glacier forelands in Tierra del Fuego show fast rates of soil transformation which imply large quantities of N inputs. Our results highlight the potential contribution of bryophyte-cyanobacteria associations to N accumulation during post-glacial primary succession and further describe the factors that drive N2-fixation rates in post-glacial areas with very low N deposition.PLoS ONE 01/2014; 9(5):e96081. · 3.73 Impact Factor
The Global Atmospheric Environment
for the Next Generation
F . D E N T E N E R , *, †D . S T E V E N S O N ,‡
K . E L L I N G S E N ,§T . V A N N O I J E ,|
M . S C H U L T Z ,¶M . A M A N N ,⊥
C . A T H E R T O N ,×N . B E L L ,∇
D . B E R G M A N N ,×I . B E Y ,OL . B O U W M A N ,#
T . B U T L E R ,+J . C O F A L A ,⊥B . C O L L I N S ,b
J . D R E V E T ,OR . D O H E R T Y ,‡
B . E I C K H O U T ,#H . E S K E S ,|A . F I O R E ,∞
M . G A U S S ,§D . H A U G L U S T A I N E ,]
L . H O R O W I T Z ,∞I . S . A . I S A K S E N ,§
B . J O S S E ,fM . L A W R E N C E ,+M . K R O L ,†
J . F . L A M A R Q U E ,)V . M O N T A N A R O ,@
J . F . M U ¨ L L E R ,[V . H . P E U C H ,f
G . P I T A R I ,@J . P Y L E ,£S . R A S T ,¶
J . R O D R I G U E Z ,° , ¢M . S A N D E R S O N ,b
N . H . S A V A G E ,£D . S H I N D E L L ,∇
S . S T R A H A N ,4S . S Z O P A ,]K . S U D O ,X
R . V A N D I N G E N E N ,†O . W I L D ,XA N D
G . Z E N G£
Joint Research Centre, Institute for Environment and
Sustainability, via E. Fermi 1, I-21020, Ispra, Italy, School of
Geosciences, University of Edinburgh, Edinburgh, United
Kingdom, Department of Geosciences, University of Oslo, Oslo,
Norway, Royal Netherlands Meteorological Institute (KNMI),
De Bilt, The Netherlands, IIASA, International Institute for
Applied Systems Analysis, Laxenburg, Austria, Netherlands
Environmental Assessment Agency (RIVM/MNP), Bilthoven,
The Netherlands, Frontier Research Center for Global Change,
JAMSTEC, Yokohama, Japan, Swiss Federal Institute of
Technology (EPFL), Lausanne, Switzerland, NASA-Goddard
Institute for Space Studies, New York, Goddard Earth Science
& Technology Center (GEST), Baltimore, Maryland, Belgian
Institute for Space Aeronomy, Brussels, Belgium, Lawrence
Livermore National Laboratory, Atmospheric Science Division,
Livermore, California, CEA/CNRS, Laboratoire des Sciences du
Climat et de l’Environnement, Gif-sur-Yvette, France, Max
Planck Institute for Chemistry, Mainz, Germany,
Meteo-France, CNRM/GMGEC/CATS, Toulouse, France, NOAA
GFDL, Princeton, New Jersey, National Center of Atmospheric
Research, Atmospheric Chemistry Division, Boulder,
Colorado,Max Planck Institute for Meteorology, Hamburg,
Germany, Centre of Atmospheric Science, University of
Cambridge, Cambridge, United Kingdom, Met Office, Exeter,
United Kingdom, Dipartimento di Fisica, Universita `
L’Aquila, L’Aquila, Italy, and University of Miami, Coral
Gables, Florida, NASA-Goddard Space Flight Center,
Air quality, ecosystem exposure to nitrogen deposition,
and climate change are intimately coupled problems: we
assess changes in the global atmospheric environment
between 2000 and 2030 using 26 state-of-the-art global
scenarios. The first (CLE) scenario reflects implementation
of current air quality legislation around the world, while
all currently feasible technologies are applied to achieve
maximum emission reductions. We contrast these scenarios
with the more pessimistic IPCC SRES A2 scenario.
Ensemble simulations for the year 2000 are consistent
among models and show a reasonable agreement with
Large parts of the world are currently exposed to high
ozone concentrations and high deposition of nitrogen to
ecosystems. By 2030, global surface ozone is calculated to
increase globally by 1.5 ( 1.2 ppb (CLE) and 4.3 ( 2.2
ppb (A2), using the ensemble mean model results and
associated (1 σ standard deviations. Only the progressive
MFR scenario will reduce ozone, by -2.3 ( 1.1 ppb.
Climate change is expected to modify surface ozone by
-0.8 ( 0.6 ppb, with larger decreases over sea than over
land. Radiative forcing by ozone increases by 63 ( 15
and 155 ( 37 mW m-2for CLE and A2, respectively, and
decreases by -45 ( 15 mW m-2for MFR. We compute that
are exposed to nitrogen deposition above a critical
load of 1 g N m-2yr-1. These percentages increase by
2030 to 15.8% (CLE), 10.5% (MFR), and 25% (A2). This study
shows the importance of enforcing current worldwide
air quality legislation and the major benefits of going further.
Nonattainment of these air quality policy objectives,
such as expressed by the SRES-A2 scenario, would further
degrade the global atmospheric environment.
Emissions of reactive trace gases, generated in the burning
of fossil- and biofuels and volatilized from agricultural
processes, cause a number of environmental problems.
Ozone (O3) forms from the photochemical oxidation of
components (NMVOC) in the presence of nitrogen oxides
(NOx)NO+NO2). O3is an important greenhouse gas and is
also toxic to humans, animals, and plants. The IPCC Third
Assessment Report (1) recognized that conventional air
pollutant emissions affect climate directly (through O3and
aerosol production) and indirectly through their influence
on the CH4 lifetime. An evaluation of the high-emissions
O3increases of about 5 ppb by 2030 and 20 ppb by 2100 (2).
Enhanced emissions of sulfur dioxide (SO2), NOx, and
ammonia (NH3) lead to increased long-range transport and
* Correspondingauthorphone: +390332786392;fax+390332786291;
†Joint Research Centre, Institute for Environment and Sustain-
‡University of Edinburgh.
§University of Oslo.
|Royal Netherlands Meteorological Institute (KNMI).
⊥IIASA, International Institute for Applied Systems Analysis.
#Netherlands Environmental Assessment Agency (RIVM/MNP).
XFrontier Research Center for Global Change, JAMSTEC.
OSwiss Federal Institute of Technology (EPFL).
∇NASA-Goddard Institute for Space Studies.
4Goddard Earth Science & Technology Center (GEST).
[Belgian Institute for Space Aeronomy.
×Lawrence Livermore National Laboratory.
+Max Planck Institute for Chemistry.
)National Center of Atmospheric Research.
¶Max Planck Institute for Meteorology.
£University of Cambridge.
bMet Office, Exeter.
@Universita ` L’Aquila.
°University of Miami.
¢NASA-Goddard Space Flight Center.
Environ. Sci. Technol. 2006, 40, 3586-3594
35869ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 40, NO. 11, 200610.1021/es0523845 CCC: $33.50
2006 American Chemical Society
Published on Web 04/19/2006
deposition of nitrogen and sulfur, damaging eutrophication
and acidification of ecosystems and loss of biodiversity (3,
In this work we evaluate the effect of changing emissions
and climate on ozone air quality, radiative forcing, and
nitrogen deposition to ecosystems for the year 2030. We use
a recently developed set of emission scenarios (5) for CH4,
NOx, NH3, CO, SO2, and NMVOC, which differ substantially
from the previous SRES scenarios (6). In the past few years
many of the major rapidly developing countries in Asia and
Latin America have issued legislation requiring emission
controls. Upon implementation, these regulations will sig-
scenario. Further, we evaluate the effects of the emissions
of a MFR (maximum technologically feasible reduction)
These emission scenarios were used internationally, by 26
(CTMs) driven by analyzed meteorological fields or general
circulation models (GCMs). Although some models share
broad to estimate uncertainties resulting from the various
relevant for the year 2000; a subset of models repeated the
2030 CLE scenario but with a changed climate. In this paper
we give an integrative overview of the findings; other
publications (7-10) present more detailed results from this
large model exercise.
and A2 assessed the year 2030. We show in the Supporting
Information the importance of emission controls in the CLE
mixing ratios, using consistent values from earlier transient
simulations for 1990-2030 described in refs 5 and 11. GCMs
performed 5-10 years of simulations, using a climate
appropriate for the time period 1995-2004. To evaluate the
impacts of climate change, an additional simulation
the IS92a climate scenario associated with a global mean
surface warming of about 0.7 K between 2000 and 2030. In
the Supporting Information we present the 26 participating
models, including characteristics of their resolution, chem-
istry and transport parametrizations, and key publications.
Compared to earlier IPCC modeling exercises (2, 12) twice
(inclusion of NMVOC chemistry) and resolutions have
increased: half of the models had horizontal resolutions of
around 4°-5°. In the following discussion we focus on the
the variability of the results as the (1 σ standard deviation.
We note that the (1 σ interval should be interpreted as a
annual average surface O3for B2000 and O3differences for
CLE, MFR, and A2 in 2030. Figure 1a shows that calculated
annual average ensemble mean surface O3ranges from 40
and Asia. Background values are 15-25 ppb in large parts of
are 33.7 ( 3.8 ppb and 23.7 ( 3.7 ppb (Table 2), for the
Northern Hemisphere (NH) and SH, respectively. In Figure
1a we also give averaged measurements for the year 2000.
Our analysis reveals that our mean model results are within
5 ppb of the measurements in the United States, China, and
Central Europe and may overestimate the measured annual
The reason for this overestimate is not clear but may be
regions. Also, the regional representativeness of the sparse
measurements may be poor, and measurement precision
The CLE scenario (Figure 1b, Table 2) would approxi-
mately stabilize O3in 2030 at 2000 levels in parts of North
America, Europe, and Asia. However, O3 may increase by
more than 10 ppb in areas anticipated to experience large
emission increases in the transport and power generation
sectors (e.g. India). Background O3increases by 2-4 ppb in
the tropical and mid-latitude NH related to worldwide
changes in CH4, NOx, CO, and NMVOC emissions. The
increases are most consistently predicted in Asia, whereas
the ensemble predictions have large standard deviations in
North and South America, Southern Africa, and the Middle
East. A cleaner future is possible, if all currently available
technologies are used to abate O3precursor emissions. In
this MFR case (Figure 1c; Table 2) O3decreases by 5-10 ppb
in the most polluted regions. The models are consistent in
their prediction of surface ozone reductions with relative
standard deviations of 30-40%. Finally, consistent with
previous studies (2), in the A2 scenario (Figure 1d), annual
average surface O3 increases by 4 ppb worldwide and by
5-15 ppb in Latin America, Africa, and Asia.
How is climate change expected to influence these O3
scenario shown in Figure 1e indicate that climate change
may reduce surface O3by 1-2 ppb over the oceans and by
as the Eastern United States, may experience increases.
TABLE 1. Overview of Simulations, Prescribed Methane Volume Mixing Ratios, and Global Anthropogenic Emissions of CO, NMVOC,
NOx, SO2, and NH3a
CTM 2000 GCM SSTs 1990s baseline
CTM 2000 GCM SSTs 1990s IIASA CLE 2030, current legislation scenario 2088
CTM 2000 GCM SSTs 1990s IIASA MFR 2030, maximum feasible
CTM 2000 GCM SSTs 1990s SRES A2 2030, the most ‘pessimistic’
IPCC SRES scenario
S5c-CLE2030c only GCM SSTs 2030s IIASA CLE 2030 + climate change
124.8 111.1 64.8
141.1 117.6 84.8
76.0 35.8 84.81760
S4-A2 2163 1268.2 206.7206.7 202.3 89.2
2012904.1145.5141.1 117.6 84.8
aEmissions in Tg full molecular weight/year. Additional information is found in the Supporting Information
VOL. 40, NO. 11, 2006 / ENVIRONMENTAL SCIENCE & TECHNOLOGY93587
35889ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 40, NO. 11, 2006
Climate-driven increases in temperature and water vapor
tend to decrease surface O3in the cleanest regions but tend
to increase O3 in more polluted areas. A larger influx of
stratospheric O3 into the troposphere leads to a general
increase of free tropospheric O3. Note that many feedbacks,
e.g. from natural emission changes, were generally not
included in the models. We further note the large variability
in the calculated climate impacts [Table 2].
O3air quality limits, with threshold values of 60-80 ppb, are
On the basis of epidemiological studies of O3related health
effects (13), the World Health Organization (WHO) recom-
is defined as the daily maximum of an 8-h running average
a 35 ppb “background” level:
O3toxicity to have a lower threshold and is more suited to
FIGURE 1. Ensemble mean (a) ozone in the year 2000 and ozone differences between scenarios (b) CLE, (c) MFR, (d) A2 with 2000, and
(e) impact of climate change, comparing CLEc and CLE. Regionally averaged measurements (upper: mean, lower left mean + 1σ, lower
right mean - 1σ) are given in circles. Measurements are taken from taken from the WMO-GAW World Data Centre for surface ozone,
EMEP/AIRBASE in Europe, and CASTNet in the United States. Measurements for India, China, and Africa are from various scientific studies
TABLE 2: Area Weighted Regional and Global Annual Mean Surface O3[ppb], SOMO35 [ppb days], and Tropospheric O3Column
[DU] in 2000 and Increases for Various Scenarios at Selected Regionsa
n ) 26/17/26
n ) 26/14/26
n ) 21/14/21
n ) 21/14/21
n ) 10/-/10
38.7 ( 4.9
4145 ( 1378
37.0 ( 5.0
27.9 ( 4.7
1681 ( 865
35.2 ( 5.5
34.8 ( 5.0
3207 ( 1304
35.2 ( 5.5
36.6 ( 4.2
3056 ( 1084
37.3 ( 4.9
43.5 ( 6.4
5388 ( 1917
42.4 ( 5.6
45.0 ( 6.9
6093 ( 2266
42.7 ( 6.0
31.5 ( 4.4
2096 ( 937
32.3 ( 5.6
33.7 ( 3.8
2336 ( 950
35.8 ( 5.4
23.7 ( 3.7
486 ( 330
29.4 ( 5.1
28.7 ( 3.6
1411 ( 608
32.6 ( 5.3
1.3 ( 2.4
583 ( 280
2.1 ( 0.6
0.5 ( 2.0
140 ( 74
1.3 ( 0.4
1.4 ( 3.9
553 ( 190
1.7 ( 0.4
1.8 ( 1.5
384 ( 335
2.0 ( 0.6
1.7 ( 2.4
2.68 ( 0.7
7.2 ( 1.9
3094 ( 791
4.0 ( 0.8
3.8 ( 0.7
945 ( 329
2.9 ( 0.7
2.3 ( 0.5
615 ( 254
2.2 ( 0.6
0.6 ( 2.1
111 ( 85
1.2 ( 0.4
1.5 ( 1.23
63 ( 160
1.7 ( 0.5
-4.9 ( 1.8
-1788 ( 525
-2.5 ( 0.6
-2.4 ( 2.3
-231 ( 106
-1.2 ( 0.3
-2.5 ( 4.5
-332 ( 126
-1.1 ( 0.3
-2.8 ( 1.1
-1071 ( 2 92
-2.1 ( 0.5
-6.6 ( 2.2
-2195 ( 668
-2.7 ( 0.7
-5.9 ( 1.6
-1976 ( 560
-2.5 ( 0.6
-3.6 ( 0.5
-703 ( 276
-1.8 ( 0.5
-2.9 ( 0.6
-786 ( 208
-1.9 ( 0.5
-1.7 ( 2.3
-79 ( 55
-0.9 ( 0.3
-2.3 ( 1.1
-433 ( 118
-1.4 ( 0.4
1911 ( 797
5.2 ( 1.2
5.7 ( 2.7
1247 ( 597
4.9 ( 1.1
7.0 ( 4.2
2084 ( 666
5.7 ( 1.3
3.9 (q 3.8
1417 ( 823
4.7 ( 1.2
8.7 ( 6.0
3692 ( 1523
7.1 ( 1.5
11.8 ( 4.3
4914 ( 1435
7.9 ( 1.6
7.7 ( 1.8
2222 ( 563
5.6 ( 1.5
5.9 ( 2.1
1738 ( 704
5.3 ( 1.4
2.7 ( 2.6
394 ( 229
3.4 ( 1.0
4.3 ( 2.2
1066 ( 426
4.3 ( 1.2
-0.4 ( 1.2
0.1 ( 0.7
-0.5 ( 0.8
-0.2 ( 0.4
-0.4 ( 0.7
0.1 ( 0.4
-0.4 ( 0.7
-0.1 ( 0.4
-0.6 ( 0.9
0.0 ( 0.7
-0.7 ( 0.9
-0.2 ( 0.6
-0.6 ( 1.0
-0.3 ( 0.6
-0.8 ( 0.7
-0.2 ( 0.7
-0.7 ( 0.6
-0.2 ( 0.6
-0.8 ( 0.6
-0.2 ( 0.6
South East Asia
aRegions are defined according to IMAGE2.2 (http://arch.rivm.nl/image/). Standard deviations are calculated from ‘n’ models (not all models
submitted data for SOMO35). The (1σ standard deviations reflect the variation of the regional average of the ensemble members. Ozone changes
larger than 1σ are indicated in bold.
VOL. 40, NO. 11, 2006 / ENVIRONMENTAL SCIENCE & TECHNOLOGY93589
assess the effect of large scale changes of ozone background
concentrations calculated with global models. Note that
SOMO35 is also rather similar to the widely used metric,
AOT40, which evaluates the accumulated exposure of
vegetation to ozone levels above 40 ppb.
in Table 2 we give a regional analysis of SOMO35. No limit
values have been established for SOMO35, but a threshold
of ∼3000 ppb days is consistent with air quality limits
to our model calculations this threshold (yellow and red
colors) is exceeded in large parts of the world in the year
2000, most notably in the United States, the Middle East,
and South Asia. In the CLE scenario this situation is
aggravated especially in South Asia due to a large growth of
emissions from the transport sector. Our model results
indicate that the more polluting SRES A2 scenario would
compromise attainment of any existing air quality standard
in most industrialized parts of the world by 2030. Only the
MFR scenario predicts that ozone in all regions will be at or
below the current air quality standards. The large scale
Radiative Forcing from Tropospheric Ozone. In Table 2
we present regional changes in tropospheric column ozone
[Dobson units; DU] resulting from the emission scenarios.
The current global average tropospheric ozone column is
calculated to be 33 ( 5 DU in close agreement with IPCC(1),
with regional averaged values in the Northern Hemisphere
FIGURE 2. Ensemble mean SOMO35 [ppb days] (a) in the year 2000; (b) 2030 CLE; and (c) 2030 MFR.
35909ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 40, NO. 11, 2006
and 4.3 ( 1.2 DU for CLE and A2 and decreases by -1.4 (
of -0.2 ( 0.6 DU. The impact of emission reductions and
increases is relatively uniform for MFR and A2, whereas the
CLE scenario amplifies the regional contrast in the ozone
radiative forcings increments of 63 ( 15 and 155 ( 37 mW
m-2for CLE and A2, respectively, and reductions of -45 (
as 300 mW m-2in Asia. We calculate that the sum of the O3
and CH4radiative forcings, in the CLE and A2 simulations,
contributes 23% and 29%, respectively, to the forcings of
Nitrogen Deposition. It is currently thought that 1000
14). So far most studies have focused on the effects of NOy
deposition (15), since it is intimately associated with O3
FIGURE 3. Ensemble mean (a) NOytotal deposition [mg N m-2yr-1] in 2000, (b) total reactive nitrogen (dNOy+NHx) deposition [mg N m-2
yr-1] in 2000, and (c) MFR 2030 NOytotal deposition.
VOL. 40, NO. 11, 2006 / ENVIRONMENTAL SCIENCE & TECHNOLOGY93591
(NOy) NO + NO2+ NO3+ 2N2O5+ HNO3+ particulate
that NOy deposition alone leads to an exceedance of this
threshold in parts of the Northeast United States, Europe,
and food production systems, may double the deposition
from NOy. In 2000 the deposition of total reactive nitrogen
(dNOy+NHx) exceeds 2000 mg Nm-2yr-1in extended parts
of the world, including biodiversity hotspots (Figure 3b). To
suggested that increased nitrogen deposition will play an
important future role in the decrease of plant diversity
Europe, Southeast Asia, Africa, and South America yields
agreement within a factor of 2 for 70-80% of the measure-
underestimate NOy deposition by up to 60%, and South
America, where almost no measurement data were found.
In 2030, considering the CLE scenario NOy deposition
in North America, and strongly increases in Asia by 30-
100%. NHxdeposition increases almost everywhere by 50-
which was evaluated only for NOy, considerably improves
500 mg N m-2yr-1. In contrast, the A2 scenario in the year
2030 leads to extended regions exposed to NOydeposition
larger than 1000 mg N m-2yr-1. The CLE and A2 scenarios
project further increases in nitrogen critical loads, with
particularly large impacts in Asia where nitrogen emissions
and deposition are forecast to increase by a factor of 1.4
(CLE) to 2 (A2). We calculate (7) that at present 10% of the
natural terrestrial ecosystems receive nitrogen inputs above
1000 mg N m-2yr-1. These percentages increase by 2030 to
16% (CLE), 11% (MFR), and 25% (A2). We note that we did
not determine maximum feasible emissions reductions for
NH3; instead we used in scenario S3-MFR the CLE NH3
Comparison with Satellite Observations of NO2 Col-
umns. Recent satellite observations allow us to evaluate
nitrogen pollution on near global scales. For the year 2000,
the GOME instrument aboard the ERS-2 satellite pro-
vides a unique opportunity to compare model calculated
NO2 columns with measurements. We sample model
NO2 columns at the satellite overpass time (10:30 LT).
Daily tropospheric NO2 column densities were calculated
by 17 different models; uncertainties in the retrievals are
quantified by using three different retrieval algorithms (9).
FIGURE 4. (a) Modeled and (b) GOME measured annual average NO2columns for the year 2000. Modeled data represent an average of
17 models, and the GOME retrieval is an average of three retrieval products. For a consistent comparison, the data in both cases have
been smoothed to a horizontal resolution of 5° × 5°.
35929ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 40, NO. 11, 2006
Low tropospheric NO2columns of <1 × 1015molec cm-2are
calculated and observed by GOME in marine regions. Over
the continents, three regions of dominant NO2pollution are
found in North America, Western Europe, and China,
are also indicated in the model ensemble mean, but the
averaged model maxima of 6-8 × 1015molec cm-2under-
estimates the GOME observed values, which exceed 10 ×
1015molec cm-2. The discrepancy between models and
measurements is particularly pronounced over the rapidly
that the assumed NOxemissions may be unrealistically low
in these regions. In regions dominated by biomass burning,
such as in Africa and South America, the models tend to
overestimate the observed seasonal cycle.
We note that the discrepancy in the NO2column in e.g.
North America and Europe does not seem consistent with
the general agreement in NO3wet deposition. In the rapidly
developing parts of China and Southern Africa, the model-
satellite discrepancy indicates an underestimate of NOx
emissions, consistent with underestimates of N-deposition,
but not corroborated by similar discrepancies in surface
of the GOME retrievals are in many instances as large as the
spread in model results, meaning that in only a few cases
(i.e. in China) robust statements on underprediction of NOx
emissions can be made.
observations confirm our assessment of the present-day
pollution. We show that by 2030 the present worldwide
legislation on air pollutant emissions is not sufficient to
stabilize or reduce the current problems related to ozone
and eutrophication. Moreover we note that the current lack
of experience with the introduction of air pollution policies
in developing countries, which may delay the actual imple-
mentation of such legislation. The SRES A2 scenario, as-
sociated with strong increases in surface ozone, radiative
of stringent NOx, CO, NMVOC, and CH4 abatement tech-
nologies (MFR) prevents additional climate forcing by O3
and may bring surface O3and eutrophication of ecosystems
to more acceptable levels. Our MFR scenario, however, was
constructed without considering the implementation costs
of these technical measures. Further integrated analysis of
the costs and benefits of reducing NH3, NOx, CO, NMVOC,
and CH4emissions (5, 17, 18) in the context of climate and
air pollution policies is needed to guarantee a cleaner
atmospheric environment for the next generation.
This model exercise was organized under the umbrella of
the EC FP6 Network of Excellence ACCENT.
Supporting Information Available
Details on the participating models and assumptions made
in the emissions scenarios are presented. This material is
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Received for review November 28, 2005. Revised manuscript
received March 7, 2006. Accepted March 16, 2006.
35949ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 40, NO. 11, 2006