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PUBLISHED ONLINE: 28 APRIL 2013 | DOI: 10.1038/NGEO1800
Warming-induced increase in aerosol number
concentration likely to moderate climate change
Pauli Paasonen1,2 *† , Ari Asmi1† , Tuukka Petäjä1 , Maija K. Kajos1 , Mikko Äijälä1 , Heikki Junninen1 ,
Thomas Holst3 , Jonathan P. D. Abbatt4 , Almut Arneth5 , Wolfram Birmili6 , Hugo Denier van der Gon7 ,
Amar Hamed8 , András Hoffer9 , Lauri Laakso10,11 , Ari Laaksonen8,10 , W. Richard Leaitch12 ,
Christian Plass-Dülmer13 , Sara C. Pryor14 , Petri Räisänen10 , Erik Swietlicki15 , Alfred Wiedensohler6 ,
Douglas R. Worsnop1,8,10,16 , Veli-Matti Kerminen1 and Markku Kulmala1
Atmospheric aerosol particles influence the climate system
directly by scattering and absorbing solar radiation, and
indirectly by acting as cloud condensation nuclei1–4 . Apart
from black carbon aerosol, aerosols cause a negative radiative
forcing at the top of the atmosphere and substantially mitigate
the warming caused by greenhouse gases1 . In the future,
tightening of controls on anthropogenic aerosol and precursor
vapour emissions to achieve higher air quality may weaken
this beneficial effect5–7 . Natural aerosols, too, might affect
future warming2,3,8,9 . Here we analyse long-term observations
of concentrations and compositions of aerosol particles and
their biogenic precursor vapours in continental mid- and
high-latitude environments. We use measurements of particle
number size distribution together with boundary layer heights
derived from reanalysis data to show that the boundary layer
burden of cloud condensation nuclei increases exponentially
with temperature. Our results confirm a negative feedback
mechanism between the continental biosphere, aerosols and
climate: aerosol cooling effects are strengthened by rising
biogenic organic vapour emissions in response to warming,
which in turn enhance condensation on particles and their
growth to the size of cloud condensation nuclei. This natural
growth mechanism produces roughly 50% of particles at
the size of cloud condensation nuclei across Europe. We
conclude that biosphere–atmosphere interactions are crucial
for aerosol climate effects and can significantly influence the
effects of anthropogenic aerosol emission controls, both on
climate and air quality.
Climate feedback mechanisms are phenomena that originate
from climate warming and either amplify or moderate warming.
Common to practically all the proposed climate feedback mechanisms involving natural aerosols is that the estimation of their
magnitude, or even existence, is based on a very limited amount of
observational evidence. The feedback mechanism focused on in this
study can be summarized as follows9 : (i) increasing temperatures
increase emissions of biogenic volatile organic vapours (BVOCs),
(ii) after rapid atmospheric oxidation these vapours condense on
aerosol particles, thus enhancing particle growth, (iii) the number
concentration of particles large enough to act as cloud condensation
nuclei (CCN) increases, (iv) the cloud droplet number concentration and thus cloud albedo increases, which decreases the fraction of
solar radiation penetrating the atmosphere and thus suppresses the
climate warming. The validity of stages (i), (ii) and (iv) is commonly
accepted1,10–15 , although the quantitative impact remains uncertain.
Stage (iii), linking atmospheric CCN and organic vapour concentrations, has been demonstrated in modelling and conceptual
studies16,17 , but the corresponding observations are scarce and
reported only in local or regional scale studies14,18 . The long-term
average number concentration of CCN-sized aerosol particles has
been found to correlate with the time the air mass has spent over
forests in Scandinavia14 . This suggests that the condensation of
biogenic organic vapours affects not only the total particle mass but
also the number concentrations of CCN-sized particles, indicated
also in a case study at Whistler Mountain in North America18 .
Although the above-mentioned experimental studies suggest a
connection between condensable organic vapours and CCN number concentration, they do not demonstrate increasing CCN concentrations with increasing temperature. To investigate this dependence, we analysed data from eleven continental measurement stations, from clean semi-Arctic to polluted agricultural areas (Fig. 1,
more information in Supplementary Methods). Number concentrations of particles with dry diameters larger than 100 nm (N100 )
were used as a proxy of CCN number concentrations19–21 to analyse
how this quantity is associated with air temperature and concentrations of precursor vapours in both the gas and aerosol phase.
The functional dependence of N100 on air temperature is
depicted in Fig. 2a. The lines show the median concentrations
in each 5 ◦ C temperature class at each site, and the shading
1 Department
of Physics, University of Helsinki, FI-00014, Finland, 2 International Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria,
for Geo Biosphere Science, Lund University, S-22362 Lund, Sweden, 4 Department of Chemistry, University of Toronto, Ontario, M5S 3H6, Canada,
5 Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research/Atmospheric Environmental Research, 82467 Garmisch-Partenkirchen,
Germany, 6 Leibniz Institute for Tropospheric Research, 04318 Leipzig, Germany, 7 TNO Built Environment and Geosciences, 3584 CB Utrecht,
The Netherlands, 8 Department of Applied Physics, University of Eastern Finland, 70210 Kuopio, Finland, 9 MTA-PE Air Chemistry Research Group, 8200
Veszprém, Hungary, 10 Finnish Meteorological Institute (FMI), FI-00101 Helsinki, Finland, 11 School of Physical and Chemical Sciences, North-West
University, Potchefstroom 2520, South Africa, 12 Science and Technology Branch, Environment Canada, Toronto, Ontario, M3H 5T4, Canada, 13 Deutscher
Wetterdienst, Meteorologisches Observatorium Hohenpeissenberg, 82383 Hohenpeissenberg, Germany, 14 Department of Geological Sciences, Indiana
University, Bloomington, Indiana 47405, USA, 15 Division of Nuclear Physics, Lund University, S-221 00 Lund, Sweden, 16 Aerodyne Research, Inc., Billerica,
Massachusetts 01821-3976, USA. † These authors contributed equally to this work. *e-mail: [email protected].
3 Centre
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1
NATURE GEOSCIENCE DOI: 10.1038/NGEO1800
LETTERS
Hohenpeissenberg
(DE)
Egbert (CA)
1998¬2000, Vavihill (SE)
2007¬2008
2007¬2008 2008
.. ..
Hyytiala (FI)
1996¬2010
.. ..
Varrio (FI)
1996¬2008
Melpitz (DE)
2003¬2008
Yakutsk (RU)
2009 (summer)
1
2
3
4
5
6 Woodland
Forests
60° N
60° W
Morgan
Monroe (US)
2007¬2008
30° W
San Pietro
Capofiume (IT)
2002¬2006
10° S
30° E
10 Grassland
11 Cropland
12 Urban/built
K-Puszta (HU)
2006¬2008
Botsalano
(ZA)
2006¬2007
30° S
Shrublands
7
8
9
0 Water
Figure 1 | Measurement locations and data periods. The colours and numbers indicate the primary land use as described in ref. 28.
2
a
N100 concentration (cm¬3)
10,000
Yakutsk
.. ..
Varrio
.. ..
Hyytiala
Egbert
Botsalano
Vavihill
1,000
100
10
¬40
Hohenpeiss.
Morgan M.
Melpitz
K-Puszta
S.Pietr.C.
¬30
¬20
¬10
0
10
20
30
40
20
30
40
Air temperature (°C)
b
1 × 1013
1 × 1012
1 × 1011
1 × 1010
1 × 109
¬40
Variability of anthopogenic
primary emission inventory burdens
Mixed boundary layer burden B100 (m¬2)
denotes the 95% range of data from four example stations from
distinctly different environments (95% areas for the other sites are
shown in Supplementary Fig. S1). The number concentrations N100
exhibited clear increases with increasing temperatures (p-values
below 0.01 for 8 sites out of 11, see Supplementary Methods
and Table S1), especially in colder and cleaner environments
(Värriö, Hyytiälä and Yakutsk). By contrast, the most polluted
and the warmest environments (K-Puszta, San Pietro Capofiume
and Botsalano) showed either constant or slightly decreasing N100
with increasing temperature. Notably, at T > 0 ◦ C there was a
common temperature-dependent minimum of N100 , approximately
◦
at N100 = 101+0.05T / C cm−3 (dashed line in Fig. 2a).
Our aim was to study the temperature dependence of the
sources of CCN-sized particles. This cannot be done directly by
investigating their measured concentrations, because the height of
the boundary layer (BL), within which the aerosols are efficiently
mixed, is also a strong function of temperature22 . We calculated the
columnar BL aerosol number burden (B100 ), which is the number
of >100 nm particles within a presumed well-mixed BL column, by
multiplying the measured concentration with the boundary layer
height (BLH) computed from the NCEP/DOE AMIP-II Reanalysis
2 database (Supplementary Methods). Although the BLH obtained
from the reanalysis data is only an approximation, it has been
shown to give reasonable estimates of the real BLH, including its
seasonal and diurnal variation22 . B100 increased with increasing
air temperature at all the sites over the observed temperature
range (Fig. 2b and Supplementary Fig. S1) with a high level of
statistical significance (p-value below 0.001 at all the sites at
T > 5 ◦ C, see Supplementary Methods and Table S1). However,
the temperature response was less evident at colder temperatures.
At low temperatures, B100 at the four representative European
stations agreed with the anthropogenic primary emission burdens
(depicted as bars on the left hand side of Fig. 2b) calculated using a
number emission inventory for primary anthropogenic particles23
(Supplementary Methods). The point at which a clear temperature
dependence becomes evident varied, depending on anthropogenic
emissions, clearly dividing B100 into regionally varying temperatureindependent and uniform temperature-dependent regimes. The
uniform temperature dependency followed roughly the logto-linear least squares fit for burdens at T > 15 ◦ C, B100 =
◦
1010.82+0.05T / C m−2 (dashed line in Fig. 2b). In addition to the
3-hour averages presented in Fig. 2, the temperature dependency
was clear for the daily averages. Our budget estimation, based on the
anthropogenic emission inventory and yearly temperature profiles,
suggests that almost 50% of CCN-sized particles over the European
continental area were formed through the temperature-dependent
mechanism (Supplementary Methods).
The marked increase in B100 with increasing temperatures is
assumed to be due to the growth of smaller particles via secondary
¬30
¬20
¬10
0
10
Air temperature (°C)
Figure 2 | The relationship between air temperature and the number
concentration and burden of CCN-sized aerosol particles. a,b, The panels
present 3-hour-mean number concentration (N100 ) (a) and boundary layer
number burden (B100 ) (b) of CCN-sized particles as functions of
temperature. Median values for each temperature are shown for all stations
(lines) and the densest distribution of observations for four stations
(shaded areas). The dotted line in a approximates the lower boundary of
concentrations and the dotted line in b approximates the fit to median
burdens at T > 15 ◦ C. The bars on the left in b show the calculated ranges of
anthropogenic primary emission burdens in the regions of the highlighted
stations (thick lines).
aerosol formation (that is, condensation of vapours) associated
with biological activity. Nevertheless, it might, in principle, also
be related to reduced particle wet deposition by precipitation, as
warm and dry conditions often coincide, or to increased primary
particle emissions. In our data sets, however, precipitation had no
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N100 (cm¬3)
104
N100 (cm¬3)
NATURE GEOSCIENCE DOI: 10.1038/NGEO1800
LETTERS
significant impact on the relationship between temperature and
B100 (Supplementary Fig. S2). Emissions related to wildfires or
biological activities (for example, spores and pollen) are the only
primary aerosol sources expected to be positively correlated with
the air temperature. However, an increase in wildfire emissions
does not cause as pronounced an increase in median number
concentrations as is evident in our observations24 , and primary
biological emissions contribute minimally to continental total
particle number concentrations25 . Thus, we postulate that the
ambient temperature exerts a control over the concentration
of CCN-sized particles by limiting the particle growth through
biogenic secondary organic aerosol (SOA) formation11,12 . This
inference is supported by aerosol particle chemical composition
measurements at Hyytiälä during 2008–200923 and at Egbert in
200713 (Fig. 3, insert). At both locations, the number concentration
N100 is directly proportional to the mass concentration of organic
compounds in particles with diameters between approximately 70
and 800 nm (mOA ), which explains 73% of the variability in N100 .
The formation of SOA occurs via condensation of the oxidation
products of BVOCs, for example monoterpenes, sesquiterpenes
and/or isoprene11 . We investigated the relative importance of
temperature-dependent precursor emissions and atmospheric oxidation chemistry in CCN formation by comparing the relationships
between B100 , temperature and radiation (Supplementary Fig. S3).
Our analysis shows a clear dominance of temperature (and thus precursor emissions) over radiation (and thus photochemical oxidation), which is consistent with a recent modelling study26 . Figure 3
shows close to direct proportionality between N100 and monoterpene concentration ([MT]) at the two sites with simultaneous
Egbert
.. ..
Hyytiala
Yakutsk
Hohenpeissenberg
103
102
10¬1
100
101
mOA (µg m¬3)
103
4)
0)
102
:
pe
Slo
84
0.
(0
.70
1.0
e:
op
Sl
108
5
.6
4
1.0
(0
e:
op
Sl
7)
1.0
3
1.0
9
.8
(0
1.0
109
1010
1011
[MT] (cm¬3)
Figure 3 | Concentration N100 as a function of gas phase monoterpene
concentration ([MT]) and organic aerosol mass mOA (inset) at T > 5 ◦ C.
The data for N100 versus [MT] cover 21 months at Hyytiälä and 15 months
at Hohenpeissenberg from all the seasons, and two months at Yakutsk
between May and August. The lines present bivariate regression fits, 95%
confidence intervals are given in parenthesis (Supplementary Information).
The data for N100 versus mOA (inset) cover four measurement campaigns
(one month each) during spring, summer and autumn at Hyytiälä and one
month in spring and summer at Egbert. The line in the insert represents
direct proportionality.
a
Emission
Oxidation
Particle formation
and growth
Cloud
activation
SOA
BVOC
CCN
Gas
Aerosol
Cloud albedo
Air temperature
Biosphere
Radiation balance
Biogenic effects
b
Moderately polluted
Polluted
background
Morgan M.
Hohenpeis.
Vavihill Melpitz
Botsalano
S.Pietr.C.
K-Puszta
.. ..
Hyytiala
.. ..
Varrio
Egbert
Yakutsk
(only summer)
Clean background
Annual
mean
Tdaily > 5 °C
¬0.8
¬0.6
¬0.4
¬0.2
0.0
0.2
Mean
Mean local cloud albedo feedback (W m¬2 K¬1)
Range of mean local direct effect
feedbacks from the same stations
Figure 4 | Schematic and estimated regional strengths of the proposed climate feedback mechanism. a, Proposed feedback mechanism, in which the
biosphere reacts to warming climate by emitting more organic compounds, leading to enhanced growth of aerosols and to an increase in the cloud droplet
concentrations, thus diminishing the net radiative forcing9 . b, Calculated approximate local annual and growing-season mean (the latter determined as the
daily mean temperature >5 ◦ C) cloud albedo effect feedbacks for the stations. Green stations are located in different kinds of forest environments, orange
in polluted forest or savannah environments and pink in croplands or built environments. BVOC: Biogenic volatile organic compounds; SOA: secondary
organic aerosols; CCN: cloud condensation nuclei.
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NATURE GEOSCIENCE DOI: 10.1038/NGEO1800
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A'
A
High primary emissions
d2
d1
B
B'
Low primary emissions
Primary emissions
dominate
ns
o
Bi
n
ge
e
ic
at
in
io
iss
m
d
om
e
Reduction from high to low aerosol emissions
Log of aerosol number burden (dp > 100 nm)
Climate warming
(exaggerated)
0
Air temperature (°C)
Figure 5 | Schematic summarizing the implications of the temperature
dependence of CCN-sized particle burdens (B100 ). The thick black line
indicates the natural aerosol background. If a similar warming happens in
two regions A and B (the pink and yellow areas show idealized distributions
of B100 ), the aerosol concentrations in less polluted region B will increase
(B0 , light yellow area) and reduce the warming (maximum temperatures in
B’ are lower than in A0 , light pink area) through the discussed feedback
mechanism. If primary aerosol emissions are reduced similarly in cooler
(d1 ) and warmer (d2 ) environments (initial and final primary emission
burdens depicted with dashed lines), the resulting reduction in B100 will be
smaller in the warmer environment (red arrows).
long-term particle number and MT measurements (Hyytiälä and
Hohenpeissenberg) and in data from a shorter campaign at Yakutsk
(for proportionality analysis see Supplementary Methods). Less
uniform proportionality was observed between N100 and isoprene
concentrations (Supplementary Fig. S4). The linear dependency between [MT] and N100 , together with the similarity of the exponential
temperature dependencies of [MT], mOA and N100 (Supplementary
Methods, Fig. S5 and Table S2), as well as other evidence presented
above, indicates BVOC emissions as the foremost factor driving the
observed temperature dependency of N100 and B100 .
Assuming the observed temperature dependence will remain
in a warming climate, our findings indicate the existence of a
negative aerosol–climate feedback mechanism in the continental
biosphere9 (Figs 4a and 5). This feedback is conceptually similar
to the widely investigated CLAW hypothesis27 related to marine
sulphur emissions: in both cases, warming temperatures increase
biogenic aerosol precursor emissions and subsequently enhance
cloud albedo and negative climate forcing. The CLAW feedback
originated mainly from theoretical reasoning and is difficult to
validate8 . In contrast, the climate feedback considered here is
strongly supported by direct observations.
An order-of-magnitude estimate of the strength of the investigated aerosol–climate feedback can be calculated based on the
change in direct and the first indirect (cloud albedo) aerosol effects.
The cloud albedo effect was estimated directly from changes in
measured concentrations N100 with respect to changes in temperature, whereas the direct effect was calculated based on the
changes in the total volume of measured particle populations
and in modelled BLH with respect to changes in temperature
(Supplementary Methods and Fig. S5). Our calculations resulted
in regional mean annual feedbacks of up to −0.3 W m−2 K−1 and
demonstrated a clear dominance of the cloud albedo effect over the
direct effect (Fig. 4b and Supplementary Table S3). The negative
4
feedbacks were strongest at the most northern and remote sites.
At the most polluted sites of this study the calculated feedback
values were positive (that is, enhancement of warming) because
N100 decreased with increasing temperature at T < 15 ◦ C (Fig. 2a).
This decrease seems to originate mainly from the more efficient
dilution of anthropogenic emissions in deeper BL at warmer
temperatures, because in B100 the corresponding decreases are
either absent or far less prominent (Fig. 2b). Notably, during the
growing season (T > 5 ◦ C) the negative feedback values are roughly
doubled, whereas the positive values remain constant (Fig. 4b and
Supplementary Table S3). As forests (excluding rainforests) and
croplands cover about 10% of the total global area28 , we estimate
that the overall order of magnitude of the feedback in the global
atmosphere is around −0.01 W m−2 K−1 (Supplementary Methods). For more exact estimates, the temperature dependence of N100
needs to be studied further, especially in tropics, subtropics and
isoprene-rich environments.
As well as providing a negative feedback mechanism, the
biogenic contribution of B100 has distinct consequences for
the outcomes of anthropogenic emission abatement policies,
potentially reducing the expected climate warming impact of the
lowered anthropogenic emissions5–7 . According to our analysis,
the formation of biogenic SOA sets a minimum level for B100
and thus maintains part of the aerosol cooling effect regardless of
the reductions in anthropogenic aerosol and precursor emissions
(Fig. 5). Because the biogenic contribution of B100 increases with
temperature, the reductions in anthropogenic emissions will have a
lesser impact on CCN concentrations in warmer regions.
Our results indicate that the biogenic continental aerosol attenuates air temperature changes via a negative organic aerosol–climate
feedback mechanism. However, at more polluted locations the
levels of anthropogenic aerosol emissions exceed, at least for most
parts of the year, the natural production of CCN-sized particles,
thus inducing an anthropogenic cooling effect and partly surpassing
the biogenic feedback. Estimating the full scale of the effects of
this feedback requires understanding of the sources, processes
and evolution of natural and anthropogenic organic aerosols in
the atmosphere12,29,30 , and of the processes taking place in the
biosphere3 . This understanding is based on long-term, comprehensive, multi-platform observations23 . In estimates of the anthropogenic climate change and the effects of aerosol-related air quality
directives, the response of the biosphere has to be considered.
Received 1 October 2012; accepted 14 March 2013;
published online 28 April 2013
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Acknowledgements
This work was funded by European Research Council (ATMNUCLE, 227463), Academy
of Finland (Center of Excellence Program project 1118615; projects 11750, 127210,
132640 and 139656), European Commission sixth Framework program (EUCAARI,
contract no 036833-2; EUSAAR, contract no 026140), European Commission seventh
Framework program (ACTRIS, contract no 262254; PEGASOS, contract no 265148),
Maj and Tor Nessling Foundation (projects 2010143, 2011200, 2012443 and 2013325)
and the Otto A. Malm foundation. For providing data, we acknowledge the Physical
Sciences Division, Earth System Research Laboratory, NOAA, Boulder, Colorado (for
the boundary layer height data acquired from their web site at http://www.esrl.noaa.gov/
psd/), the Hungarian Meteorological Service, Gerald Spindler, Pasi P. Aalto and Harald
Flentje. We thank Ville Vakkari for help in quality assurance of Botsalano data and
students and staff of North-West University (Mafikeng Campus), RSA, for weekly
maintenance. The various measurements were supported by the German Federal
Ministry for the Environment (FE 370343200), Environment Canada, NSERC,
CFCAS-CAFC, the National Science Foundation (#0544745 and supplement, and
1102309), the Swedish Research Council (projects 2007-3745, 2007-4619 and
2010-4683) and the Swedish Research Council for Environment, Agricultural Sciences
and Spatial Planning (Formas, project 2009-615).
Author contributions
P.P. had the original idea; P.P. and A. Asmi made the data analysis; A. Asmi made the
figures; M.K.K., T.H. and C.P-D. made the monoterpene concentration measurements
and the data pre-analysis; M.Ä., H.J. and J.P.D.A. made the aerosol mass concentration
measurements; A. Asmi, V-M.K., A.L. and P.R. made the calculations of the feedback
strength; A. Arneth, W.B., A. Hamed, A. Hoffer, T.H., L.L., W.R.L., S.C.P., E.S., A.W.
and T.P. provided the particle number size distribution and meteorological data;
H.D.v.d.G. provided the anthropogenic emission inventory data; T.P., D.R.W. and M.K.
supervised the analysis and writing; P.P., A. Asmi and V-M.K. wrote the paper; All
authors contributed with their comments to the paper.
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. The processed
data for this manuscript can be found in the ACTRIS database (http://actris.nilu.no/
Content/Products/). Correspondence and requests for materials should be addressed
to P.P.
Competing financial interests
The authors declare no competing financial interests.
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