10 m wind speed, which govern the area available for sea-salt production and the amount of sea-salt produced respectively. These changes in sea-ice and the corresponding decreases in wind speed (possibly related to the increased roughness length over sea-ice) lead to a reduction in sea-salt around the sea-ice edges in these experiments. The Carslaw et al. (2010) review highlighted recent work of the Leeds group showing that decadal trends in wind speed in parts of the Southern Hemisphere may have led to more than 20% changes in CCN between the 1980s and 2000. These changes are likely to have induced changes in clouds and a negative feedback on climate.

CEA-LSCE has further shown that the temporal variability in dust deposition has little impact on the ocean productivity. However, long term changes in dust deposition are demonstrated to have the potential to exhibit a considerable change to oceanic ecosystems (Aumont et al., 2008).

# 4 Discussion and conclusions

## 4.1 Main achievements

In 2006 when planning the EUCAARI project we realized that the baseline for the uncertainty in aerosol radiative forcing was typically greater than 100%, and for some aerosol components even much higher. Furthermore, the regional scale forcing can be significantly greater than the global average values, as can be uncertainties. As a whole, the contributions of various aerosol sources, the role of primary and secondary particulate matter to the ambient aerosol concentrations over Europe were largely unknown. Therefore we performed studies presented in this overview using methods presented in Sect. 2 and obtaining results presented in Sect. 3. Kulmala et al. (2009) described a set of 12 key questions of EUCAARI. The answers of the project to these key research questions are included in Appendix E.

### 4.1.1 Aerosols and climate: reducing uncertainty

Our first objective was the reduction of the uncertainty (2006 level) of the impact of aerosol particles on climate by 50% and quantification of the relationship between anthropogenic aerosol particles and regional air quality. To achieve this objective EUCAARI concentrated on the areas of greatest uncertainty to:

a. identify and quantify the processes and sources governing global and regional aerosol concentrations;

b. quantify the physico-chemical properties of atmospheric aerosols;

c. quantify the feedback processes that link climate change and atmospheric aerosol concentrations with emphasis on the production and loading of natural aerosols and their precursors.

Answers to the points (a), (b) and (c) are given in Sect. 3. Answers related to point (a) are mainly considered in Sects. 3.1 and 3.2 where both natural and anthropogenic sources, along with various formation and transformation mechanisms are considered and in Sect. 3.4 where modeled regional and global distributions and concentration fields are presented. Answers related to point (b) are given in Sects. 3.2 and 3.3. In Sect. 3.3, the most comprehensive set of physico-chemical aerosol properties are reported, not only extensively over Europe but also in some key developing countries, using the most advanced instrumentation and techniques available. In particular, significant advances were made in quantifying the organic fraction of the atmospheric aerosol. Answers related to point (c) are given in Sects. 3.4 and 3.5 primarily with respect to biogenic SOA, natural dust and the marine sulphate cycle. Our achievements towards a 50% reduction in the uncertainty associated with aerosol radiative forcing is outlined below.

The First Assessment Report (FAR) IPCC report was published in 1990, after which it was followed by the second (SAR) in 1995; the third (TAR) in 2001; and the fourth (AR4) in 2007. At the beginning of the assessment reports, the uncertainty related to aerosol forcing increased as both a better knowledge of aerosol properties and sources emerged as well as an increasing number of aerosol species and processes were implemented in the climate models. It was not only until the AR4 in 2007 that the uncertainty started to get reduced as seen in Table 4 and in Fig. 20.

In 1990/1992 the assessment report authors concluded that the effect for (the then) current emission levels, averaged over the Northern Hemisphere, corresponded to a negative forcing at the Earth's surface of about $1 \text{ W m}^{-2}$, with about a factor of two uncertainty. This was comparable (but of opposite sign) to the forcing due to anthropogenic $CO_2$ ($+1.5 \text{ W m}^{-2}$). In addition to the direct effect on climate of sulphate aerosols, there was an indirect effect – via changes in CCN and cloud albedo – which tended to act in the same direction (i.e. towards a cooling) with a magnitude that has not yet been reliably quantified (Charlson et al., 1990 and 1992; Kaufman et al., 1991). In the AR4, the range of estimates for the direct effect spanned $-0.8 \text{ W m}^{-2}$ while the indirect effect spanned $-1.5 \text{ W m}^{-2}$. For the direct effect, this represents a reduction in span of plausible results from ca $1.4 \text{ W m}^{-2}$ (SAR), ca $2.7 \text{ W m}^{-2}$ (TAR) to $0.8 \text{ W m}^{-2}$ (AR4), while in between these three reports no reduction in span was found for the indirect effect; however, the SAR only handled sulphate aerosol while the AR4 handled many more aerosol species. It should be noted that the range for the indirect effect was $(-2 \text{ W m}^{-2}$ in the TAR.

Preliminary analysis from EUCAARI model analyses of the direct radiative forcing by the aerosols ranges from $-0.049$ and $-0.311 \text{ W m}^{-2}$. In Quaas et al. (2009) several additional global models were used to derive the direct ($-0.4 \pm 0.2 \text{ W m}^{-2}$) and indirect effect ($-0.7 \pm 0.5 \text{ W m}^{-2}$) radiative forcings for atmospheric aerosols. We caution that
the EUCAARI results are only from the three models par-
ticipating in the project, and more complete and comparable
results will be available later for IPCC AR5 analyses.

The interactions and feedbacks between aerosols and
clouds, aerosols/clouds and climate, as well as air pollution
and climate are many and intricate. The study of them re-
quires a multidisciplinary approach. The research chain con-
cept has to be followed to develop a deeper science under-
standing. Comparing number and mass we are able to find
out several good research chains which we can utilize (a) nu-
cleation/emissions – parametrisations – regional and global
model results, (b) comparison of (a) with 2008–2009 ground
base data and comparison with satellite data, and (c) vapour
pressures – SOA formation – emissions – regional and global
models, comparison like in (b).

One example of the used research chain is given in Fig. 21. That figure shows the main processes and parameters which contribute to the indirect radiative climate forcing of aerosols. It summarizes the interplay of meteorological and dynamical parameters with microphysical and chemical parameters of aerosols and clouds that lead to changes in cloud optical depth and thus to radiative climate forcing, i.e. the first indirect effect of aerosols on climate (Twomey effect). Table 5 provides quantitative estimates for the relative uncertainties and sensitivities of individual parameters and their effect on the uncertainty of cloud optical depth (Heintzenberg and Charlson, 2009). It can be seen that following EUCAARI, the uncertainty in many of the key parameters in the aerosol-cloud system are reduced by 50%, for example, the hygroscopicity parameter kappa, updraft velocities, CCN concentrations, etc.

4.1.2 Air quality and climate

Our second objective was to quantify the side effects of Euro-
pean air quality directives on global and regional climate, and
to provide tools for future quantifications for different stake-
holders. Our answer to this objective is given in Sects. 3.4
and 3.6. The interconnections between climate change and
air quality are clearly significant.

Future climate predictions were conducted for the Special
Report on Emissions Scenarios (SRES) A1B and the interac-
tions between air quality and climate change was evaluated
for the years 1950–1959, 2000–2009 and 2040–2049. The
climate induced variability, or variability due to meteorology
between years within each decade gives rise to variability in
the annual average of the surface PM2.5 concentrations of
typically 10%. The 2040s generally have the highest con-
centrations of PM2.5, consistent with the previous conclu-
sion that the PM2.5 lifetime increases under the 2040s climate
when it is much drier and warmer around the Mediterranean.
The differences in annual average PM2.5 concentrations be-
tween the decades are also typically 10%. The exception
here is BSOA and BSOA precursors, where the difference
between the decades is larger than 10% as the source func-

tion for BSOA is temperature-dependent, with larger emis-
sions as temperature rises.

For emission scenarios, the following four scenarios were
used: Frozen legislation (FLE), reference case with Current
Legislation (CLE), sustainable policy with CLE, sustainable
policy with SLE. The difference in annual average PM2.5
concentrations are much larger when the emission changes
are taken into account compared to when only meteorolog-
ical changes were taken into account. This shows that the
climatology of PM2.5 and its composition for the coming
decades can be expected to be largely controlled by the emis-
sion changes, while the climate changes mainly will affect
the level of biogenic secondary organic pollutants forcing
them to go up. Emission changes dominate over the effect
of intradecadal climate variability in annual average surface
PM2.5 concentrations over the EMEP domain including its
chemical components. The ranking of the scenario results
for the 2040s also follow the ranking of the emissions, with
the highest concentrations for the FLE case, followed by the
reference case with CLE, sustainable policy with CLE and
sustainable policy with SLE. The results of the two latter
scenarios are very close, as are also the emissions for these
two scenarios. The latter two scenarios result in the order of
40% reduction in PM2.5 mass while FLE scenario results in
a marginal increase in PM2.5.

In terms of specific emissions reductions, the reduction in
ammonia emissions is one of the most effective ways to re-
duce aerosol mass concentrations in Europe. Reduction in
NOx is also effective for PM, but might lead to higher ozone
levels. Reduction in SO2 emissions will reduce particulate
air pollution especially in the Eastern Mediterranean area.
Reduction of organic aerosol concentrations is a lot more
challenging and will require reductions of gas and aerosol
emissions e.g. from transportation and biomass burning.

4.2 Policy relevance

The development of policy strategies generally has often
built on a bottom-up process starting in basic research that
provided the scientific knowledge needed to address ques-
tions of societal importance. Applied research was then
developed to find answers to these questions. The policy
strategies for robust mitigation programmes were developed
through the interaction of policy making bodies and applied
researchers. The Convention on Long-Range Transport of
Air Pollution and the IPCC are successful examples using
such a process to include science into policy making.

EUCAARI focused mainly on basic research concerning
processes on all scales aiming at a new generation of air
quality and climate models based on sound physical and
chemical understanding of processes influenced by atmo-
spheric aerosols and gases. EUCAARI contributed new
and/or enhanced understanding of processes from micro to
global scale, leading to the improvement of models (includ-
ing EMEP) that are crucial in developing policies. The
<table><caption>**Table 4.** Aerosol forcing according to different IPCC reports: Forcing (W m⁻²), BB = Biomass Burning aerosols, FF = Fossil Fuel burning aerosols.</caption><thead><tr><th></th><th>Aerosol direct</th><th>Aerosol indirect (first indirect)</th></tr></thead><tbody><tr><td>SAR:</td><td>-0.5 (0.1 to -1.3) sulfate+BB+FF(EC)</td><td>(-0.0 to -1.5) sulfate only</td></tr><tr><td>TAR:</td><td>-0.6 (0.5 to -2.2) SAR+dust+FF(OC)</td><td>(-0.0 to -2.0) all aerosols</td></tr><tr><td>AR4:</td><td>-0.5 (-0.1 to -0.9) all aerosols</td><td>-0.8 (-0.3 to -1.8) all aerosols</td></tr><tr><td>EUCAARI:</td><td>-0.2 (-0.05 to -0.31) all aerosols</td><td>-0.7 (-0.2 to -1.2) all aerosols</td></tr></tbody></table>

<figure><img src="image_23.png" /><figcaption>**Fig. 20.** The upper and lower limit and the best estimate for radiative forcing based on IPCC results and our own estimate denoted by 2010 for direct effect (left) and for 1st indirect effect (right).</figcaption></figure>

<figure><img src="image_24.png" /><figcaption>**Fig. 21.** Major processes and parameters contributing to the first indirect effect of aerosols on climate (Twomey effect).</figcaption></figure>

improvements have already affected the policy work and will do so for at least the next 5 yr period. Through its strategy EUCAARI has moved basic research closer to the policy work.

### 4.2.1 Updated emissions inventories and their evaluation

A major contribution of EUCAARI was the creation of the first ever inventory of number resolved particle emissions for Europe (see Sect. 3.1 and Denier van der Gon et al., 2009). Most emission databases express the emissions in terms of mass, while modern regional and global models need a size resolved input as particle size is decisive in most aerosol dynamic processes, particularly concerning the impacts on climate. Therefore, size-resolved particle emission information is needed in order to connect policies related to climate and air quality. The lack of information on particle sizes means that most models have included assumptions about the particle size distribution, which has been shown in EUCAARI to be a major source of uncertainty in regional aerosol assessments (Reddington et al., 2011). Introduction of size resolved emissions will give a unified input to all models and facilitate more transparent model comparisons. Another crucial improvement is the chemical speciation of PM emissions as the chemistry strongly influences particle behaviour. EUCAARI made a new inventory of European elemental carbon (EC) and organic carbon (OC) emissions. EC and OC are important components of PM₁₀ and PM₂.₅ and are important particulate components affecting human health and climate. In line with the PN emission inventory, a size-distribution for
<table><caption>**Table 5.** Range, variability, uncertainty, and relative sensitivity estimates for major parameters describing the first indirect effect of aerosols on climate (Twomey effect).</caption><thead><tr><th rowspan="2">Parameter</th><th rowspan="2">Effective Range</th><th rowspan="2">Varia-bility Factor</th><th colspan="2">Relative Uncertainty<br>(dX/X = dlnX)</th><th rowspan="2">Relative Sensitivity<br>(dlnY/dlnX = (dY/Y)/(dX/X))</th></tr><tr><th>Pre-EUCAARI</th><th>Post-EUCAARI</th></tr></thead><tbody><tr><td>Aerosol Hygroscopicity, κ</td><td>0.1–1.0</td><td>10</td><td>1</td><td>0.5</td><td>1/3 dln N<sub>CCN</sub>/dln κ</td></tr><tr><td>Aerosol Particle Number & Size, N<sub>CN</sub>(D) (cm<sup>-3</sup>)</td><td>10<sup>2</sup>–10<sup>4</sup></td><td>100</td><td>2</td><td>1</td><td>1 dln N<sub>CCN</sub>/dln N<sub>CCN</sub></td></tr><tr><td>CCN Concentration, N<sub>CCN</sub> (cm<sup>-3</sup>)</td><td>10<sup>1</sup>–10<sup>4</sup></td><td>1000</td><td>2.3</td><td>1.2</td><td>1 dln N<sub>act</sub>/dln N<sub>CCN</sub></td></tr><tr><td>Updraft velocity, w (m s<sup>-1</sup>)</td><td>0.5–20</td><td>40</td><td>2</td><td>1</td><td>1 dln S/dln w</td></tr><tr><td>Supersaturation, S (%)</td><td>0.1–1</td><td>10</td><td>3</td><td>2</td><td>1 dln N<sub>act</sub>/dln S</td></tr><tr><td>Initial Cloud Droplet Number Concentration, N<sub>act</sub> (cm<sup>-3</sup>)</td><td>10<sup>1</sup>–10<sup>3</sup></td><td>100</td><td>7.3</td><td>4.2</td><td>1 dln N<sub>CD</sub>/N<sub>act</sub></td></tr><tr><td>Dilution Ratio, N<sub>CD</sub>/N<sub>act</sub></td><td>0.4–0.9</td><td>2</td><td>1</td><td>0.3</td><td>1 dln N<sub>CD</sub>/dln k<sub>act</sub></td></tr><tr><td>Effective Cloud Droplet Number Conc., N<sub>CD</sub> (cm<sup>-3</sup>)</td><td>10<sup>1</sup>–10<sup>3</sup></td><td>100</td><td>8.3</td><td>4.5</td><td>1/3 dln COD/dln N<sub>CD</sub></td></tr><tr><td>Effective radius correction, k*</td><td>0.5–1</td><td>2</td><td>0.3</td><td>0.1</td><td>1/3 dln COD/dln k*</td></tr><tr><td>Spatial heterogeneity, SH</td><td>0.1–1</td><td>10</td><td>1</td><td>1</td><td>1/5 dln COD/dln SH</td></tr><tr><td>Microphys. inhomogeneity, MI</td><td>0.1–1</td><td>10</td><td>1</td><td>1</td><td>1/5 dln COD/dln MI</td></tr><tr><td>Liquid Water Path, LWP (g m<sup>-2</sup>)</td><td>20–400</td><td>20</td><td>1</td><td>1</td><td>5/6 dln COD/dln LWP</td></tr><tr><td>Cloud Optical Depth, COD</td><td></td><td></td><td>4.1</td><td>2.8</td><td></td></tr></tbody></table>

the major source categories was provided to the modellers. Effective EC mitigation strategies and scope for regulations have been recently discussed at a regional and global level e.g. UNEP and EMEP (UNEP, 2011; ECE, 2010). Errors and uncertainties in the emission estimates propagates into the modelling results on air quality and climate. Further the mitigation strategies generally focus on emission reductions making the negotiations focused on finding the most cost effective reduction strategy (see Fig. 22). Accurate emission data are thus fundamental to developing the best possible abatement program.

Aerosol source apportionment was based on about 30 field campaigns all over Europe with most advanced instrumentation and shows the strong presence of organic components dominating the fine aerosol. The major fraction is modern carbon coming from biogenic emissions and biomass combustion (Prévôt et al. 2011). The biomass combustion contribution is strongly varying with season and site. Application of the new emission inventory in the PMCAMx model reveals inconsistencies in the emission database, such as too low wood combustion emissions in Sweden and Eastern Europe, calling for a review of the national emission reports. Preliminary analyses of the new emissions in the GLOMAP global aerosol model show reasonable agreement with EU-ISAAR observations at some locations, but overall discrepancies between models and observations are still considerable at many other locations in Europe, in particular for high altitude sites and Scandinavia.

### 4.2.2 Atmospheric composition: new findings of importance for policy development

Efforts are now focused on establishing an integrated air quality and climate mitigation policy. One major air quality issue is the health effects caused by particles (Pope and Dockery, 2006). The risk estimates recommended by the World Health Organisation (WHO) are based on PM₁₀ or

PM₂.₅. Even though some particle components may be associated with higher risks there is no recommendation due to insufficient epidemiological evidence. Several investigations suggest that exposure to combustion particles is associated with higher health effect risks (Hoek et al., 2002). In EUCAARI, extensive efforts have been made to unravel the organic chemistry of aerosol particles, thereby facilitating a more mechanistic chemical process description in the models, which from a policy point of view is important for a better understanding of the contribution of the different sources, natural and anthropogenic, to the total aerosol load. A major coordinated effort was launched in cooperation with EMEP together with the observational network EUSAAR and extended with highly specialized instrumentation such as the Aerosol Mass Spectrometers at about 10 sites in three month-long campaigns. The aim was to collect detailed data on how emissions mix with and age with pre-existing aerosol and how these particles interact with clouds. Several research aircrafts were deployed in a major airborne measurement campaign (Roberts et al., 2011). The extensive database of detailed information on the atmospheric composition, especially the organic components, is instrumental in developing an accurate quantitative description of the anthropogenic contribution to PM (Nemitz et al., 2011).

Short-lived climate forcing components (SLCF) such as black carbon, sulphate, organic carbon, ozone and methane affect the climate significantly. Abatement of air pollution is associated with considerable costs but also major savings in health and ecosystem effects. However, as major greenhouse gas emission originates from the same sources as air pollutants, a coordinated abatement strategy is needed. Such a strategy needs to balance reductions of cooling and warming SLCFs and therefore focuses on limited number of sources but when done hand in hand with CO₂ reductions helps to achieve climate targets. However, the uncertainties are considerable because the indirect effects of aerosols on clouds are not included, and the focus is in radiative forcing rather
<figure><img src="image_25.png" /><figcaption>**Fig. 22.** EC and OC annual emission (tonnes) for Europe in 2005 by source sector.</figcaption></figure>

than the climate response itself. The present total aerosol forcing is not well known, giving a large uncertainty in the quantification of the actual temperature increase at double CO₂ concentration (Schwartz et al., 2010; Hansson, 2010). The atmospheric concentrations of these components and the chemical composition of the particles strongly affect not only their radiative properties but also the potential for cloud droplet formation. EUCAARI, partly through the use of data from infrastructure network such as EUSAAR, has put major efforts into analysing concentrations and properties of importance for calculations of the aerosol total forcing effect (see e.g. Swietlicki et al., 2008; Asmi et al., 2011). The distribution of the different chemical components over the particle size distribution and thus their influence on the particle properties are most important for the total effect of the given compounds. Long term measurements of the particle size distribution have been performed all over Europe in collaboration with EUSAAR, extended by EUCAARI to 4 international sites in Africa, India, China and Brazil. Further EUCAARI undertook a major month-long campaign including measurements of chemically resolved size distributions. In total the major achievements on measuring the chemical composition and properties influencing climate forcing have affected and will continue to affect the policy development as it will give a much stronger basis for estimating the effect of emission reductions.

Coupled photochemistry and aerosol microphysics simulations for the period 1980–2005 using the aerosol-chemistry-climate model ECHAM5-HAMMOZ have been performed, to assess the understanding of long-term changes and inter-annual variability of the chemical composition of

the troposphere, and in particular of ozone and sulphate concentrations. In order to separate the impact of the anthropogenic emissions and meteorology on atmospheric chemistry, two model experiments have been compared, driven by the same ECMWF re-analysis data, but with varying and constant anthropogenic emissions, respectively (Pozzoli et al., 2011). The model analysis indicates an average increase of 1 ppbv in global average surface ozone concentrations due to anthropogenic emissions, but this trend is largely masked by natural variability (0.63 ppbv), corresponding to 75 % of the total variability (0.83 ppbv). Regionally, annual mean surface O₃ concentrations increased by 1.3 and 1.6 ppbv over Europe and North America, respectively, despite the large anthropogenic emission reductions between 1980 and 2005. Global average sulphate surface concentrations are largely controlled by anthropogenic emissions. Globally natural emissions are an important driver determining the AOD (Aerosol Optical Depth) variations, regionally AOD decreased by 28 % over Europe, while it increased by 19 % and 26 % in East and South Asia. The global radiative perturbation calculated in our model for the period 1980–2005 was rather small.

### 4.2.3 Model development, new parametrizations, feedback processes and evaluations

The basic foundation of EUCAARI is implementing scientifically investigated parametrization of processes into mechanistic models. The climate is controlled by a very complex web of processes on all scales, from the nano to the global scale, interacting with each other. Simultaneous studies of
these processes aiming at improving our understanding will improve models considerably. In AR4 the uncertainty in climate sensitivity due to poorly quantified aerosol processes results in a very large uncertainty in global mean temperatures in a double CO₂ climate (Schwartz et al., 2010). Obviously this uncertainty gave considerable difficulty in setting generally acceptable abatement goals.

As the atmospheric particle size distribution is strongly dependent on the formation of new particles in the atmosphere, i.e. nucleation, EUCAARI focused on the crucial question of how the natural particle formation, growth and ageing processes are affected by anthropogenic emissions, and thus how changes in emissions will affect climate forcing. EUCAARI has put emphasis on both warm and cold clouds, investigating how different properties affect the cloud droplet or ice nuclei formation, all in an attempt to get better estimates of the indirect effects as well as of their contribution to the total uncertainty (e.g. Hoose et al., 2010a). Feed-back processes in the interaction between the atmosphere and the natural ecosystem and/or the natural oceans in a changing climate have been investigated using models updated with new parametrizations developed in EUCAARI (e.g. Collins et al., 2010).

An evaluation process of regional and global aerosol models was developed to document modelling progress made during EUCAARI. A platform was developed, which helps constructing successful modelling studies within EUCAARI and outside of the consortium, making a link to the international AEROCOM model inter-comparison. This initiative allows a quantification of actual uncertainties in our prediction of aerosol impact on climate and air quality. Benchmark test tools were developed and applied to analyse model biases with respect to processes that govern aerosol concentrations and physico-chemical properties of the aerosol.

Upgrading an operational model requires significant effort including scientific investigations and evaluation of the effects of changes on the general performance of the model. Thus the full upgrading of the operational models has been lagging behind. The just started AR5 in the IPCC process stops the upgrading processes of the operational models for a period of 2 yr for the IPCC simulations. This delays the implementation of new parametrizations and the upgrading based on EUCAARI results for a period of approximately 2 yr.

### 4.2.4 Developing and evaluating policy strategies

Several scenarios were developed in EUCAARI in which available technical and non-technical reduction measures of short lived climate forcing components and air pollutants were combined to find the best integrated strategy for co-beneficial climate and air quality mitigation. The developed approaches were used in the UNEP Integrated Assessment of Black Carbon and Tropospheric Ozone (UNEP, 2011) and were the basis for work in the Arctic Council Task Force

and the Arctic Monitoring and Assessment (AMAP) Expert Group to assess the climate effects on the Arctic. Developments to identify the contribution to air pollution as well as radiative forcing from individual member states in the OECD was also made within the EUCAARI, which have been used in the work within different task forces and expert committees in EMEP/CLRTAP.

A first assessment, performed within EUCAARI showed that balanced reduction strategies of short-lived climate forcers and atmospheric pollutant can enhance the climate mitigation and simultaneously improve air quality (see also Fig. 23). A baseline was developed based on current and planned emission regulation for the period 2000–2030. Three control scenarios adding well known standard reduction measures on BC and methane were investigated together with one scenario were maximum feasible reductions were applied on all substances involved.

During 2010 UNEP performed an assessment of BC and ozone that recently was published using the same scenarios (www.unep.org/dewa/). The evaluation by two GCMs (GISS and ECHAM) found the global temperature increase could be reduced by about 0.5° from 2030 and onwards with the suggested measures, at the same time considerable improvements in adverse health and ecosystem effects were achieved.

Similarly, runs with ECHAM using IIASA air quality mitigation scenarios were made with the following air quality mitigation scenarios: Current Legislation Emissions (CLE), Maximum Feasible Reductions (MFR) and CLEMFR where the MFR was applied for Europe and CLE for the rest of the world. When the MFR scenario is applied only to Europe the study shows a substantial warming effect and increase in precipitation. But these effects are almost double, both over Europe and globally, when the MFR scenario is adopted globally. In the case of CLEMFR the temperature response in Europe is +2.2°C while in the case of MFR the temperature increase in Europe is 4.1°C. It is the difference in reduction of SO₂ emissions that causes this fairly large difference in global climate response. The global temperature response in 2030 due to the greenhouse gas emissions in both scenarios was found to be about 1.2°C.

The development of the EMEP model has facilitated a first implementation of forcing as an element in the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model. This allows the use of GAINS for an integrated assessment of climate and air quality, in order to develop cost effective and thus co-beneficial mitigation strategies for climate and air quality. The development also facilitates evaluation of Europe's influence on the global air quality and climate. The investigated scenarios were found to significantly affect the climate of the whole of the Northern Hemisphere. The different member states' contributions to the climate effect in Europe vary to some extent with their geographical location while the Arctic rim countries have a larger effect on the Arctic compared to the European countries further south. Climate change does affect air quality, but it was
<figure><img src="image_26.png" /><figcaption>**Fig. 23.** Radiative forcing (integrated over 100 yr for the baseline, three control scenarios and the MFR on Air Quality regulation, global assessment by substance (UNEP, 2011).</figcaption></figure>

found that air quality mitigation scenarios will give a clearly significantly better and noticeable improvement in air quality in spite of the variations induced by climate change and natural variability in the climate.

EUCAARI has already had an considerable effect on the production of key documents for the policy process, developing new air quality and climate mitigation policies, e.g. the UNEP report, answering the most pertinent, relevant and most recent policy related questions. In this work only some of the new developments in relevant knowledge and implementations of that in the models have been used. One reason for this is the limited duration of EUCAARI making it impossible to actually fully implement all new parametrizations in the operational models in the course of the project itself. Also, the complexity both in terms of organization and the science content of current climate modelling research and as well as the supporting operational infrastructure does not facilitate a systematic implementation of the model improvements that may arise from new parametrizations developed through EUCAARI and subsequent operational use for policy development, implementation and monitoring.

## 4.3 Impact

EUCAARI had and will continue to have a significant impact on atmospheric aerosol and climate research, on aerosol measurement technologies and techniques, on knowledge transfer, and on mitigation strategies relating to air pollution-climate change interactions. The scientific impact has mainly described in Sect. 3 and also partly in Sect. 4.1. The EUCAARI legacy is described in Sect. 4.4; however, the main impact has come via quantification the effect of aerosols on the planet's radiative balance to understand future climate change (see Sect. 4.1.). As an underpinning and critical issue, during EUCAARI, the integration of European atmospheric research, with a particular focus on aerosols, air pollution, atmospheric composition and climate change has improved

over and above the sum of the individual parts of the programme. This underpinning paves the way for more critically and informed research and assessments into the future.

From a technological perspective, EUCAARI has developed new aerosol measurement instruments and has deployed some of the most complex research instruments world-wide in, more or less, an operational manner. Such instruments include the cluster spectrometer, deployed over extended periods at numerous sites including airborne platforms (Mirme et al., 2010). Besides the aforementioned instrument, several new instrumental techniques have been developed and utilized in filed and laboratory studies (see Sect. 2) with annual observation of different properties of atmospheric aerosol having been performed at between 12–24 different sites to different degrees. The measurements additionally include, size distribution measurements (Asmi et al., 2011), hygroscopicity of atmospheric aerosols (Swietlicki et al., 2011), optical properties, and significantly aerosol mass spectrometer (AMS) measurements (e.g. the longest world-wide record of high-resolution AMS measurements were enabled at Mace Head, Ireland, where they continue to date since May 2008). In summary, EUCAARI has moved highly complex and labour-intensive aerosol measurement techniques from research mode to close-to-operational measurements delivering important data, previously lacking, to stakeholders.

In terms of knowledge transfer, the list is too exhaustive to be listed in this document, but includes extensive workshops, seminars, winter and summer schools as well as daily mentoring of graduate students and post doctoral researchers from Europe but also a number of developing countries and other regions around the world. More than 230 Ph.D. students have been involved in EUCAARI.

EUCAARI has produced more than 420 papers published in peer reviewed literature by 31 March 2011 (9 of them in Nature or Science). EUCAARI outcome has disseminated also via (i) EUCAARI-platform, (ii) meetings, conferences, web pages, publications, reports and (iii) different networks.

The baseline in global air pollution point of view was that information was very sparse in 2006 in 3rd world countries. EUCAARI set up a ground-site measurement network in developing countries and ensured the continuity of the work by providing a special training program for the scientists representing developing countries. In practice, EUCAARI covered the polluted regions in China and South Africa as well as the Amazon area in Brazil and rural areas in India. These regions extended EUCAARI to different ecosystems and economic areas, providing a useful reference for evaluating European conditions, and they are valuable for the design of control strategies at the local, national and European level, providing also information for international negotiations. The reduction in uncertainty regarding the aerosol role in climate change allows the EU to achieve a better balance between sustainable economic development and minimal environmental impacts. The involvement of developing
countries in the EUCAARI consortium was important both for the quantification of the pollution effects on a global scale but also for helping these countries to develop practical solutions to pollution problems.

The improved understanding of regional aerosol concentrations and emissions applies directly for the planning of the European mitigation strategies estimating the cost-efficiency of future emission controls, and the risk-analysis of long-term investments. In EUCAARI we have provided more informed tools compared to this previously existing, to perform an improved pollution-impact assessment with a particular emphasis on atmospheric aerosols. However, while the EUCAARI advances are significant, there is a still long road ahead to assess future climate change and interactions with air quality. The complexity of atmospheric aerosols, and their interactions with clouds, going forward, are still highly complex and warrant significant investment into the future.

Health effects due to air pollution and the potential damage from climate change are probably the two most important environmental problems facing the EU. EUCAARI has quantified the contributions of different anthropogenic and natural sources to the PM₁₀, PM₂.₅, and ultrafine particle concentrations. Additionally, EUCAARI provided new information on particle hygroscopicity and composition, along with the source apportionment. The project quantified the responses of the aerosol concentrations to changes in emissions of particles and their precursors within and outside Europe. The EUCAARI data base provides knowledge on regional aerosol loadings, hygroscopicity (related to dose of the exposed population) and composition (related to toxicity of the particles) and estimates of how much of the loading is due to long-range transport. EUCAARI also contributed the scientific requirements relating to the European Thematic strategy on Air Pollution, where it was stated that it is necessary to reduce the uncertainties in (i) the knowledge about the sources of PM including their physical and chemical characterization, and whether they are of natural or anthropogenic origin. (ii) the formation of secondary aerosols and how different sources contribute, (iii) the role of long-range transport including intra-hemispheric and global transport for the aerosol load over e.g. Europe; (iv) the links between air pollution and climate change; and (v) the modelling and monitoring of air pollution.

The developed models and knowledge on sources and emission scenarios came directly in to use in providing assessments evaluating the possibilities of co-beneficial measures improving air quality simultaneously mitigating climate change. These assessments have and certainly will affect ongoing policy in e.g. the National Emission Cellings Directive with in the Convention of Long-Range Transboundary Air Pollution (CLRTAP).

EUCAARI has during its four year made considerable advances on all scales of science and made it useful in the policy for better air quality and mitigating climate change.

## 4.4 Legacy and future research needs

EUCAARI leaves a legacy to be used in future projects and investigations. The key issue is EUCAARI way of integrating individual efforts to join efforts from process level understanding to global scientific and socio-etal problems. The legacy contains advanced models from process level understanding to global climate models (see EUCAARI arrow Fig. 1), new developed and tested instruments, emission inventories, data banks etc. The data banks include e.g. atmospheric nucleation data from 12 different sites, data from Intensive Observation Period (IOP), size distribution data obtained in co-operation with EUSAAR, hygroscopicity data etc.

During EUCAARI, leading European groups started to work together more systemically than ever before. 48 partners had common objectives and their work 48 months towards fulfilling those objectives. During the project several benefits from supradisciplinary work have been seen. E.g. experimentalists and modellers start to work together. The real use of EUCAARI arrow is a big benefit and shows the power of joint work in all scales. This legacy will hopefully continue into future projects.

EUCAARI established a data exchange protocol (a) to ensure rapid dissemination of data and results within the project consortium, (b) to protect the data ownership of the contributing scientists and (c) to ensure that project data are preserved and made available after the end of the project. All measurement data had to be submitted to a central database (http://ebasnilu.no), which is shared with EUSAAR and other projects, so that the EUCAARI data became part of a large established database system containing data from multiple research campaigns and monitoring activities. Some of these data are publicly available while for others the access is restricted. As of now, the database contains data from the 1970s up to 2010. It is essential that links established between the data production and storage system and the users developed within the EUCAARI framework is maintained for future studies.

Furthermore, EUCAARI supported the interpretation of EUCAARI and EUSAAR data by running a Lagrangian particle dispersion model, FLEXPART (Stohl et al., 2005), in backward mode from all EUCAARI and EUSAAR measurement data points. Backward modelling products for the years 2006–2010 are available for these locations: Aspvreten, BEO Moussala, Birkenes, Cabauw, Finokalia, Harwell, Junfraujoch, JRC-Ispra, K-puszta, Mace Head, Melpitz, Montseny, Mt. Cimone, Kosetice, Pallas, Puy de Dôme, Preila, Hyytiälä, Vavihill, as well as for Capo Fiume and Barcelona. Furthermore, products are available for all EUCAARI airborne observations. All products are freely available at http://transportnilu.no/projects/eucaari/ and are also linked via the EUCAARI database.

In future it is good to continue from EUCAARI achievements. It will be important to find out
- key processes and thermodynamics related to ice nucleation and both ice and mixed phase clouds;

- thermodynamics of key aerosol systems;

- better parametrisations to include new process understanding in global and regional models;

- effect of climate stress on vegetation and secondary aerosol formation Properties;

- interlinks between biospheric and anthropogenic aerosols and their precursors;

and to perform

- pollutant impact assessments, based on both aerosol mass and number concentrations;

- continuous and comprehensive measurements including aerosol, reactive trace gases and greenhouse gases at the same supersites;

- maintenance and extension of the observation network outside of the European political boundaries, in collaboration within strong international partnership;

- develop more detailed emissions inventories;

and to include

- EUCAARI findings in future air quality directives.

One of very important future research topic with a certain policy relevance is the quantification of the side effects of possible air quality directives on aerosol concentrations. Actually the roadmap for future analysis is to (1) obtain regional size segregated mass and number concentration using EUCAARI/EUSAAR data plus EUCAARI model results, (2) perform model runs using the emissions related or given by air quality directives, (3) analyse the results and (4) give assessments based on the results.

## 4.5 Summary

The EU-FP6 EUCAARI project (2007–2010) is an Integrated Project (IP) of the 6th Framework Programme of the European Commission. The goals of EUCAARI are to quantify the effect of aerosols on cloud, climate and air quality interactions, to understand future climate change, and to develop strategies and implementation plans for global air quality monitoring. EUCAARI is a consortium of 48 partners coordinated by the University of Helsinki. The project has been motivated by the urgent need to quantify the effect of aerosols on our planet’s radiative balance to understand future climate change. The uncertainty in aerosol radiative forcing has been typically greater than 100% and for some aerosol components it is more than 200%.

The project was organized into elements studying the emission and formation of aerosols, their evolution and transformation during their atmospheric lifetime and their impact on clouds. This approach maximized the integration of methodologies and scales and ultimately our understanding of the effects of aerosols on air quality and climate. Ground-based, aircraft and satellite measurements were integrated with existing data to produce a global consistent dataset with the highest possible accuracy. The EUCAARI intensive measurement campaign in May 2008, was designed around simultaneous airborne measurements together with measurements from several “super-site” stations around Europe. Furthermore, during EUCAARI, a hierarchy of new-generation models was developed based on the results of the laboratory and theoretical investigations. This new research concept of “all scales research chain” was the basis of the EUCAARI mission. The EUCAARI work followed several research chains, in which small-scale models were used to interpret measurements and then integrated into regional air quality and global climate models. In the end of the project this new knowledge was incorporated in policy-orientated models to analyze climate change and air quality for a range of global emission scenarios using updated economic and technological information.

One crucial task of EUCAARI was the quantification of the impact of aerosols and trace gases on clouds. The influence of aerosols on clouds depends on particle properties and cloud microphysics as well as on meteorological conditions. Before EUCAARI, the uncertainties related to aerosol properties were similarly high as those related to cloud microphysics and meteorology. Synthesizing the EUCAARI and related studies results, the uncertainty of key parameters in aerosol properties (aerosol particle hygroscopicity, size distribution, number concentration, etc.) and cloud microphysics (dilution ratio, effective radius, etc.) was reduced by about 50%. New formulations of turbulence in global models derived from EUCAARI observations give much better agreement with observations, yielding an overall 36% increase in predicted cloud droplet number concentrations and significantly reducing the model negative bias. With regard to climate modeling and air quality, aerosol properties and cloud microphysics appear now, after EUCAARI, well constrained relative to the uncertainties of meteorological conditions.

EUCAARI focused on the scientific questions related to aerosols with the greatest uncertainty at all relevant scales; from nanometers to global scale, from milliseconds to tens of years. The resulting improved understanding of the aerosol life cycle enabled us to also improve significantly the corresponding climate and air quality models. An example of such an improvement is the partitioning of complex organic compounds between the gas and the particulate phase. The work was based on laboratory experiments focusing on the micro scale. New models were then developed which greatly reduced the complexity of the organic aerosol (OA)
partitioning problem to the point where they can be included
in global OA models.

EUCAARI developed a set of new emission inventories and scenarios for Europe. For example the particle number emission inventory developed for Europe within EUCAARI is the first of its kind in the world. These inventories together with new knowledge on long-range transport of aerosol pollution provide valuable tools for air pollution policy making. The EUCAARI conclusions are also valuable inputs for future European air quality directives. Based on EUCAARI results the reduction in ammonia emissions is one of the most effective ways to reduce aerosol mass concentrations in Europe. Reduction in NOₓ is also effective, but might lead to higher ozone levels in several areas. Reduction in SO₂ emissions will reduce particulate air pollution especially in the Eastern Mediterranean area. Reduction of organic aerosol concentrations is a lot more challenging and will require reductions of gas and aerosol emissions from transportation and biomass burning.

EUCAARI has also performed measurements, which provide new insights of the role of different types of aerosols on air quality and climate. EUCAARI has made significant progress in understanding the formation of biogenic secondary organic aerosol (BSOA). It has now shown that a large fraction of the OA in Europe is of modern origin, for which the main sources are BSOA (boreal forests), biomass burning and primary biogenic aerosol particles. These compounds have also been shown to contribute to the growth of newly formed particles into cloud condensation nuclei and are therefore important for the indirect radiative forcing. All these sources are expected to respond to climate change, although we are presently unable to gauge accurately the strength of the multitude of feedback mechanisms involved.

The large-scale interactions between air quality and climate have been largely unknown, although some links have been identified or even quantified. EUCAARI results highlight the potential impact of future climate change on air pollution and vice versa.

Good quality long-term data sets of physical, chemical, and optical characteristics of aerosols are rare. Long-term data sets are needed to estimate the effect of emission reductions and underpin European strategy on air pollution. EUCAARI leaves a legacy of data and advanced aerosol and cloud computer codes, which are available via the EUCAARI Platform (http://transport nilu no/projects/eucaari/). The EUCAARI database, hosted by the Norwegian Institute for Air Research (NILU), builds on the efforts of the EMEP program and utilizes the developments of EU-FP6 infrastructure project EUSAAR (European Supersites for Atmospheric Aerosol Research). The construction of the European Research Area for the atmospheric science will require in the future that the strong connections between science and infrastructure programs be maintained. The database contains observation data of atmospheric chemical composition and physical properties in a common format. It also makes avail-

able transport modelling products (Lagrangian particle dis-
persion model FLEXPART) suitable for the identification of
source regions of measured aerosols for the case studies. In
order to expand the European activities of aerosol monitor-
ing EUCAARI has built new field stations outside Europe:
in polluted regions in China and South-Africa, in Amazon
area in Brazil and rural areas in India. This selection of sites
provides useful reference for evaluating European conditions
and providing information for international negotiations.

EUCAARI contributed to expand the European activities of aerosol monitoring outside Europe: in polluted regions in China and South-Africa, in Amazon area in Brazil and rural areas in India. This selection of sites not only provides useful reference for evaluating European conditions and information for international negotiations but it also strengthened the positioning of Europe as an attractive place for advanced education in the atmospheric science. Support of the European Commission for extending long-term observing network in emerging and developing countries outside of Europe is an essential and unique contribution to Global Climate Observing System (GCOS).

The most important technical achievement of EUCAARI was the development of a new prototype of cluster spectrometer for measuring sub-3 nm size particle and cluster ion concentrations and thus allowing us to follow the initial steps of growth of new aerosol particles. This breakthrough will enable Europe to take a leading role in developing and applying environmental technologies and mobilize all stakeholders in the area of air pollution management.

In order to efficiently disseminate and ensure the continu-
ity of EUCAARI measurement techniques, use of the instru-
mentation and running of the new stations the project has or-
ganized several workshops and training events for young sci-
entist as an integral part of the research activity. EUCAARI
has clearly strengthened the European research community
working in different disciplines of aerosol research: physics,
chemistry, meteorology and biology. The project has also
set up the stage for further studies such as the continued de-
velopment of global and regional models using EUCAARI
findings and also the incorporation of its results in future air
quality directives.

**Appendix A**

Details of methodologies used, related to 2.
scientific approach
<table><caption>**Table A1.** Laboratory infrastructures used in EUCAARI.</caption><thead><tr><th>Methodology</th><th>Description</th><th>Scale</th><th>Reference</th><th>Used in</th></tr></thead><tbody><tr><td>FMI Laminar flow-tube</td><td>Homogenous nucleation experiment tube</td><td>Nanoscale</td><td>Brus et al. (2010)</td><td>Nucleation and growth</td></tr><tr><td>IfT Atmospheric pressure flow-tube</td><td>Homogenous nucleation experiment tube</td><td>Nanoscale</td><td>Berndt et al. (2005); Sipilä et al. (2010)</td><td>Nucleation and growth</td></tr><tr><td>Vienna Size Ananlysing Nucleation Chamber</td><td>Expansion Chamber</td><td>Nanoscale</td><td>Winkler et al. (2008)</td><td>Heterogeneous nucleation, cluster activation, condensation growth</td></tr><tr><td>Zurich Ice Nucleation Chamber (ZINC)</td><td>Ice Nucleation Chamber</td><td>Nanoscale</td><td>Stetzer et al. (2008)</td><td>Ice nucleation</td></tr><tr><td>Portable ice nucleation chamber (PINC)</td><td>Ice Nucleation chamber</td><td>Nanoscale</td><td>Chou et al. (2010)</td><td>Ice nucleation</td></tr><tr><td>Immersion mode cooling chamber (IMCA)</td><td>Ice Nucleation chamber</td><td>Nanoscale</td><td>Niedermeier et al. (2010)</td><td>Ice nucleation</td></tr><tr><td>JPAC Juelich Plant atmosphere chamber</td><td>Two temperature controlled, continuously stirred flow reactors, housing the plants and the photochemical studies.</td><td>Microscale</td><td>Mentel et al. (2009); Kiendler-Scharr et al. (2009a, b); Lang-Yona et al. (2010)</td><td>SOA formation and OA partitioning</td></tr><tr><td>PSI Environmental smog chamber</td><td>Temperature controled 27-m<sup>3</sup></td><td>Nanoscale</td><td>Paulsen et al. (2005); Duplissy et al. (2008); Metzger et al. (2010); Chirico et al. (2010)</td><td>Nucleation and growth; aging of SOA and of combustion emissions</td></tr><tr><td>Teflon bag with artificial lights</td><td>Nanoscale</td><td>Microscale</td><td>Bohn et al. (2005); Rohrer et al. (2005); Wegener et al. (2007); Spindler (2010); Buchholz (2010)</td><td>SOA formation and OA; partitioning</td></tr><tr><td>SAPHIR Simulation of Atmospheric PHotochemistry In a large Reaction Chamber</td><td>Long-term photo-chemical aging of BSOA formed from a representative mixture of Boreal BVOCs</td><td>Microscale</td><td>Bohn et al. (2005); Rohrer et al. (2005); Wegener et al. (2007); Spindler (2010); Buchholz (2010)</td><td>SOA formation and OA; partitioning</td></tr><tr><td>UEF Kuopio plant chamber</td><td>A 6 m<sup>3</sup> teflon chamber where</td><td>Nano/microscale</td><td>Hao et al. (2009); Hao et al. (2011)</td><td>Nucleation and growth, SOA formation</td></tr><tr><td>VOC's from a plant enclosure are mixed with oxidants</td><td>Nano/microscale</td><td>Nano/microscale</td><td>Hao et al. (2009); Hao et al. (2011)</td><td>Nucleation and growth, SOA formation</td></tr></tbody></table>

<table><caption>**Table A2.** Field infrastructures used in EUCAARI.</caption><thead><tr><th>Methodology</th><th>Description</th><th>Scale</th><th>Reference</th><th>Used in</th></tr></thead><tbody><tr><td>Shangdianzi Station station</td><td>Station in China, near Beijing</td><td>Regional: China</td><td>Shen et al. (2011)</td><td>Long term measurements outside Europe</td></tr><tr><td>Elandsfontein station and Botsalano</td><td>Station in South Africa</td><td>Regional: South Africa</td><td>Laakso et al. (2010); Collett et al. (2010)</td><td>Long term measurements outside Europe</td></tr><tr><td>EUSAAR station network</td><td>24 stations in Europe</td><td>Regional: Europe</td><td>Philippin et al. (2009)</td><td>Intensive measurement period, Ground based measurements inside Europe</td></tr><tr><td>Gual Pahari station</td><td>Station in India, near New Delhi</td><td>Regional: India</td><td>Hyvärinen et al. (2010)</td><td>Long term measurements outside Europe</td></tr><tr><td>Manaus station</td><td>Station in Amazon Basin</td><td>Regional: Brazil</td><td>Martin et al. (2010)</td><td>Long term measurements outside Europe</td></tr><tr><td>Hohenpeissenberg</td><td>Station in Germany</td><td>Regional</td><td>Fricke et al. (2007)</td><td>Intensive measurement period, Ground based measurements inside Europe</td></tr><tr><td>CESAR site (part of EUSAAR)</td><td>Station in Netherlands</td><td>Local/Regional</td><td>Russchenberg et al. (2005)</td><td>Intensive measurement period</td></tr><tr><td>SMEAR II (part of EUSAAR)</td><td>Station in Finland</td><td>Local/Regional</td><td>Hari and Kulmala (2005)</td><td>Atmospheric nucleation studies, Biomass burning experiment</td></tr><tr><td>Jungfraujoch (Part of EUSAAR)</td><td>Station in Switzerland (free troposphere):</td><td>Regional Europe</td><td>Kammermann et al. (2010); Fierz-Schmidhauser et al. (2010); Juranyi et al. (2010)</td><td>Long-term measurements, Intensive measurement period</td></tr><tr><td>Puy de Dôme (Part of EUSAAR)</td><td>Station in Central France (free troposphere/Boundary layer)</td><td>Local/Regional</td><td>Venzac et al. (2009); Sellegri et al. (2003)</td><td>Long-term measurements, Intensive measurement period</td></tr></tbody></table>
<table><caption>**Table A3.** Airborne infrastructures used in EUCAARI.</caption><thead><tr><th>Methodology</th><th>Description</th><th>Scale</th><th>Reference</th><th>Used in</th></tr></thead><tbody><tr><td>ATR-42 SAFIRE</td><td>Aerosol-cloud interactions</td><td>Regional</td><td>Crumeyrolle et al. (2010)</td><td>Aerosol and cloud characterization, IOP</td></tr><tr><td>BAe-146 FAAM</td><td>Aerosols, boundary layer, lower FT</td><td>Regional</td><td>(McMeeking et al. (2010); Morgan et al. (2010a, b))</td><td>Aerosol characterization, IOP</td></tr><tr><td>DLR Falcon</td><td>Aerosols, free troposphere, lidar remote sensing</td><td>Regional</td><td>Hamburger et al. (2011)</td><td>Aerosol characterization, IOP</td></tr><tr><td>IFT Helicopter</td><td>Aerosols, clouds, and radiation, boundary layer</td><td>Local</td><td>Wehner et al. (2010); Henrich et al. (2010)</td><td>Aerosol characterisation Intensive measurement period, IOP</td></tr><tr><td>NERC Dornier 228</td><td>Cloud characterization, remote sensing</td><td>Regional</td><td>http://arsf.nerc.ac.uk/</td><td>Cloud characterisation IOP</td></tr></tbody></table>

<table><caption>**Table A4.** Main computational methods used in EUCAARI (small scale).</caption><thead><tr><th>Methodology</th><th>Description</th><th>Scale</th><th>Reference</th><th>Used in</th></tr></thead><tbody><tr><td>Ion-UHMA<br>PRA kinetic model framework</td><td>Ion-Particle interaction simulations<br>Universally applicable rate equations and parameters for mass transport and chemical reactions at the surface and in the bulk of aerosol particles</td><td>Local<br>Nanoscale</td><td>Leppä et al., 2009<br>Pöschl et al. (2007); Ammann and Pöschl (2007)</td><td>Nucleation<br>Aerosol transformation</td></tr><tr><td>K2-SURF, K2-SUB KM-SUB</td><td>Modular kinetic flux models of particle chemistry</td><td>Nanoscale</td><td>Shiraiwa et al. (2009, 2010); Pfrang et al. (2010)</td><td>Organic aerosol ageing</td></tr><tr><td>Benchmark thermodynamic model</td><td>The state-of-the-science multicomponent activity coefficient code</td><td>Microscale</td><td>Clegg et al. (2008b)</td><td>Thermodynamics</td></tr><tr><td rowspan="2">Equilibrium absorptive partitioning<br>Absorptive partitioning evaluator</td><td>Method to calculate aerosol partitioning automated methodology for evaluation of the sensitivities of absorptive partitioning to vapour pressure and activity coefficient estimation</td><td>Microscale<br>Microscale</td><td>Barley et al. (2009)<br>McFiggans et al. (2010)</td><td>Thermodynamics<br>Thermodynamics</td></tr><tr><td>Sectional multicomponent aerosol microphysics code for large scale applications</td><td>Microscale, global scale</td><td>Kokkola et al. (2008); Bergman et al. (2011).</td><td>Aerosol dynamics</td></tr><tr><td>SALSA, ECHAM-SALSA</td><td>Simulations of nanocluster behaviour</td><td>nanoscale</td><td>Kurten et al. (2008)<br>Su et al. (2010); Reutter et al. (2011)</td><td>Nucleation<br>Secondary organic aerosol formation</td></tr><tr><td>Quantum mechanics calculation<br>Hygroscopicity distribution concept</td><td>Data analysis and simulation of aerosol particle properties and mixing state with regard to CCN activation</td><td>microscale</td><td>Arabas and Pawlowska (2011)</td><td>CCN activation</td></tr><tr><td>Adaptive method of lines</td><td>Multi-component aerosol condensational growth and CCN activation</td><td>microscale</td><td></td><td></td></tr></tbody></table>

<table><caption>**Table A5.** Main computational methods used in EUCAARI (large scale).</caption><thead><tr><th>Methodology</th><th>Description</th><th>Scale</th><th>Reference</th><th>Used in</th></tr></thead><tbody><tr><td>CAM-Oslo</td><td>global community atmospheric model, with aerosol lifecycling with parameterized size-distributions and interactions with clouds and radiation, coupled to a slab-ocean model</td><td>Global</td><td>Boville et al. (2006); Iversen et al. (2010); Kirkevåg et al. (2008); Seland et al. (2008); Hoose et al. (2009)</td><td>Interactions between aerosol-driven climate effects with CO<sub>2</sub>-driven Equilibrium Climate Sensitivity Modelling, Model inter-comparison</td></tr><tr><td>ECHAM5-HAM</td><td>Global community Earth System Model, including the modal aerosol microphysics scheme M7 (Vignati et al., 2004) and water-and ice-cloud-aerosol interactions</td><td>Global</td><td>Roeckner et al. (2003); Stier et al. (2005); Lohmann et al. (2007); Makkonen et al. (2009); Kazil et al. (2010)</td><td>Natural vs anthropogenic origin of aerosol particles, climate projections, Earth system feedbacks, Model intercomparison</td></tr><tr><td>GLOMAP</td><td>Global aerosol chemical transport model</td><td>Global</td><td>Spracklen et al. (2006); Mann et al. (2010)</td><td>Natural vs. anthropogenic origin of aerosol particles, Modelling, Model intercomparison</td></tr><tr><td>HadGEM2-ES</td><td>Climate and Earth system model</td><td>Global</td><td>Collins et al. (2010), Jones et al. (2007); Bellouin et al. (2008)</td><td>Natural vs. anthropogenic origin of aerosol particles, climate projections, Earth system feedbacks</td></tr><tr><td>TM4-ECPL</td><td>3-dimensional chemistry transport model with coupled gas/aerosol chemistry</td><td>Global</td><td>Myriokefalitakis et al. (2008, 2010, 2011)<br>Kanakidou et al. (2008)</td><td>Natural vs. anthropogenic origin of aerosol particles, Modelling OA multiphase chemistry</td></tr><tr><td>TM5<br>IPSL-INCA</td><td>Chemistry- Transport model<br>Climate model</td><td>Global<br>Global</td><td>Krol et al. (2005)<br>Textor et al. (2006); Schulz (2007); Balkanski et al. (2006)</td><td>Interaction with policy<br>Model intercomparison</td></tr><tr><td>European scale EMEP model</td><td>Community regional and global chemical transport model</td><td>primarily regional (10–50 km), but local (5 km) and global possible</td><td>Simpson et al. (2007, 2011)</td><td>Air quality modelling, for policy support to EU and UNECE. Natural and anthropogenic aerosols.</td></tr><tr><td>FLEXPART</td><td>Atmospheric trajectory and particle dispersion model</td><td>Regional</td><td>Stohl et al. (2005)</td><td>Natural vs anthropogenic origin of aerosol particles, Modelling</td></tr><tr><td>PMCAMx-2008<br>CALM</td><td>Three dimensional chemical transport model<br>Lagrangian transport model</td><td>Regional<br>Local to regional</td><td>Gaydos et al. (2007)<br>Tunved et al. (2010)</td><td>Modelling<br>Natural vs anthropogenic origin of aerosol particles, new particle formation</td></tr><tr><td>PMCAMx-UF</td><td>Regional chemical transport model</td><td>Regional</td><td>Jung et al. (2008)</td><td>Natural vs. anthropogenic origin of aerosol particles</td></tr><tr><td>Number-emissions pre-processor for Chemical Transport Models</td><td>Module for emission scaling</td><td>Regional</td><td>Pierce et al. (2007)</td><td>Emissions pre-processing</td></tr></tbody></table>
<table><caption>**Table A6.** Databases and inventories used in EUCAARI.</caption><thead><tr><th>Methodology</th><th>Description</th><th>Scale</th><th>Reference</th><th>Used in</th></tr></thead><tbody><tr><td>PM<sub>0.3</sub> inventory</td><td>A further size split in the CEP-MEIP PM<sub>1</sub> inventory</td><td>Regional</td><td>Visschedijk et al. (2004)</td><td></td></tr><tr><td>EBAS data base</td><td>Comprehensive observation data base</td><td>Global</td><td>Philippin et al. (2009)</td><td>Data bank</td></tr><tr><td>Emission inventories</td><td>Spatially distributed emissions of air pollutants and PM precursors</td><td>Regional</td><td>Denier van der Gon et al. (2010)</td><td></td></tr><tr><td>Optical properties</td><td>Aeronet/GAW/SKYNET photometers</td><td>Global</td><td>Dubovik et al. (2002); Holben et al. (2001)</td><td>Model evaluation</td></tr><tr><td>Particle Number (PN) emission factors</td><td>Literature derived PN emission factors for key sources complemented with PM<sub>0.3</sub>-to-number conversions for sources with no PN emission data</td><td>Regional</td><td>Denier van der Gon et al. (2009)</td><td>Emissions</td></tr><tr><td>IIASA GAINS</td><td>Particulate matter (PM) inventories</td><td>Regional</td><td>Kupiainen and Klimont (2007); http://gains.iiasa.ac.at</td><td>Emissions</td></tr><tr><td>Carbonaceous emission inventory</td><td>New inventory on European carbonaceous aerosol</td><td>Regional</td><td>Denier van der Gon et al. (2011a, in prep.)</td><td>Emissions</td></tr><tr><td>Particle number emission inventory</td><td>New inventory of European particle number emissions</td><td>Regional</td><td>Denier van der Gon et al. (2011b, in prep.)</td><td>Emissions</td></tr><tr><td>Vapour pressure compilation and evaluation of vapour pressure estimation techniques available measurements</td><td>Evaluation of vapour pressure predictive techniques against</td><td>Barley and McFiggans (2010)</td><td>Thermodynamics</td><td></td></tr><tr><td>Gridded satellite products</td><td>Microscale</td><td></td><td></td><td></td></tr><tr><td>MODIS and OMI aerosol products</td><td>Gridded POLDER, MISR, Global</td><td>Deuze et al. (2000); Levy et al. (2010); Kahn et al. (2009)</td><td>Satellite retrievals</td><td></td></tr></tbody></table>

<table><caption>**Table A7.** Critical instrumentation used in EUCAARI.</caption><thead><tr><th>Methodology</th><th>Description</th><th>Scale</th><th>Reference</th><th>Used in</th></tr></thead><tbody><tr><td>APCI-MS</td><td>On-line atmospheric pressure chemical ionization MS-MS (analysis of particulate organics)</td><td>In-situ</td><td>Warscheid et al. (2003)</td><td>Secondary organic aerosol formation.</td></tr><tr><td>AMS (Aerodyne Aerosol Mass Spectrometer) q-AMS, c-ToF-AMS, HR-ToF-AMS</td><td>PM<sub>1</sub> composition, organic aerosol sources, fingerprints, and oxidation state</td><td>In-situ</td><td>Jayne et al. (2000); De Carlo et al. (2006); Drennick et al. (2005); Jimenez et al. (2009)</td><td>Secondary organic aerosol formation; Natural vs. anthropogenic origin of aerosol particles, Chemical Ageing of secondary aerosols, photoenhancement studies</td></tr><tr><td>ANAIS Airborne Neutral cluster and Air Ion Spectrometer</td><td>Measures particles and clusters also below 3 nm</td><td>In-situ</td><td>Mirme et al. (2010)</td><td>Nucleation; Airborne experiments</td></tr><tr><td>API-TOF (Atmospheric Pressure Interface Time of Flight Mass Spectrometer)</td><td>Composition of atmospheric ions</td><td>In-situ</td><td>Junninen et al. (2010); Ehn et al. (2010)</td><td>Nucleation</td></tr><tr><td><sup>14</sup>C</td><td>Carbon-14 analyses</td><td>Filter</td><td>Szidat et al. (2006, 2007)</td><td>Natural vs. anthropogenic origin of aerosol particles</td></tr><tr><td>CPCB Condensation Particle Counter Battery</td><td>Measures particles below 3 nm</td><td>In-situ</td><td>Kulmala et al. (2007b)</td><td>Nucleation</td></tr><tr><td>Direct measurements of OH radicals</td><td>DOAS long path absorption, absolute method to determine OH concentrations</td><td>In-situ</td><td>Schlosser et al. (2007)</td><td>OH-dose in secondary organic aerosol ageing studies</td></tr><tr><td>CCNC</td><td>Measures CCN number concentration</td><td>In-situ</td><td>Roberts and Nenes. (2005)</td><td>Secondary organic aerosol formation, intensive measurement period, ground based measurements inside Europe, long term measurements outside Europe, airborne experiments, cloud characterisation IOP</td></tr><tr><td>Cloud Condensation Nuclei Counter</td><td>Direct measurements of H<sub>2</sub>SO<sub>4</sub> and OH</td><td>In-situ</td><td>Berresheim et al. (2000); Paasonen et al. (2010); Petäjä et al. (2009)</td><td>Nucleation</td></tr><tr><td>H-NMR</td><td>Functional group analysis of water-soluble OC</td><td>In-situ</td><td>Decesari et al. (2007,2010b)</td><td>Natural vs. anthropogenic origin of aerosol particles</td></tr><tr><td>H-NMR and LC-MS</td><td>Analysis methods for filter samples</td><td>filter samples</td><td>Kiss et al. (2003); Müller et al. (2011)</td><td>HULIS detection and speciation in SOA formation and ageing</td></tr><tr><td>HPLC/ESI-TOFMS</td><td>Sensitive analysis method for gas and filter samples</td><td>In-situ</td><td>Kahnt et al. (2011)</td><td>Specification in secondary organic aerosol formation</td></tr><tr><td>Ion-DMPS</td><td>Measures particles and ions</td><td>In-situ</td><td>Laakso et al. (2007)</td><td>Nucleation</td></tr><tr><td>KEMS Knudsen Effusion Mass Spectrometry</td><td>Vapour pressure measurement</td><td>In-situ</td><td>Booth et al. (2009, 2010, 2011a (in prep.)), 2011b</td><td>Thermodynamics</td></tr><tr><td>NAIS (Neutral cluster and Air Ion Spectrometer)</td><td>Neutral cluster and ion concentrations and size distribution</td><td>In-situ</td><td>Kulmala et al. (2007a)</td><td>Nucleation; Intensive measurement period</td></tr><tr><td>Nano-CPCs</td><td>Measures particles below 3 nm</td><td>In-situ</td><td>Sipilä et al. (2008, 2009); Vanhanen et al. (2011)</td><td>Nucleation</td></tr><tr><td>TDMA system with laminar flow tube</td><td>Evaporation rates of particles at different RH; Vapour pressure measurement</td><td>In-situ</td><td>Riipinen et al. (2006); Bilde et al. (2003); Riipinen et al. (2006); Koponen et al. (2007)</td><td>Thermodynamics</td></tr><tr><td>NAIPOF-TDMA</td><td>Ultrafine particle organic fraction detection</td><td>In-situ</td><td>Vaattovaara et al., 2005</td><td>Nucleation</td></tr></tbody></table>
# Appendix B

## Modelling and experiments of thermodynamics and ageing of organic aerosols, related to Sect. 3.2.2

The ageing of BSOA from typical Boreal forest emissions during a day-night-day cycle in the SAPHIR chamber was correlated to the OH dose. Ageing was manifested as a distinctive increase of the O/C ratio in the particles and a change in the condensation growth of the particles, indicating the photo-chemical formation of condensible material. Factor analysis of the AMS times series (PMF, Ulbrich et al., 2009) revealed that in the long term BSOA accumulates in a final factor (group of species) with the kinetic characteristics of a product which is formed with OH and has no significant chemical losses. Interestingly, this factor has an O/C-ratio of 0.75 and shows the same concentration profile as 3-methyl-1,2,3-butanetricarboxylic acid (3-MBTCA, Zhang et al., 2010), as measured simultaneously by APCI-MS (Müller, 2010; Müller et al., 2011). 3-MBTCA was shown before to represent a unique biogenic aging marker formed by OH-radical oxidation of semivolatile oxidation products (Müller, 2010; Müller et al., 2011; Szmigielski et al., 2007). Three other factors have the characteristics of intermediate products, with either ozonolysis or OH reactions as a source and OH reactions acting as a sink. In sum they represent the semi-volatile organic aerosol fraction with O/C < 0.5 (Jimenez et al., 2009). Tracers like hydroxy pinonic acid and pinic acid correlate with the intermediate factors quite well (Müller, 2010). The correlation between tracers and AMS factors was surprisingly good as the molecular tracers represented only a very small mass fraction of the factors (Mentel et al., 2011). The time dependent ratio of the tracers pinic acid/3-MBTCA and pinonic acid/3-MBTCA indicated that the aerosol aged for about 30 h had similar characteristics as that observed in field studies in boreal forests (Müller, 2010; Müller et al., 2011). Analysis of 16 filter samples by H-NMR spectroscopy provided confirmation of the changing composition of BSOA with photochemical aging. Factor analysis showed that the variability in H-NMR composition can be reduced to two or three components, with one characteristic of fresh SOA and exhibiting a maximum during the ozonolysis experiments, and the other two factors being produced by reaction with OH and being enriched in aged samples. This is in strikingly good agreement with the AMS results (Finessi et al., 2011a). H-NMR and APCI-MS analysis indicated that the original cyclic structure of the first-generations products of α-pinene, β-pinene and carene oxidation is retained in fresh SOA. There the oxidation proceeded first on the lateral chains, while aged BSOA are largely depleted of methylated cyclic structures indicating that a more thorough oxidation has occurred. ESI-LC-MS and LC-APCI-MS (both in negative mode) analyses revealed numerous dicarboxylic acids already in the first day of chamber experiments in agreement with the online APCI-MS

observations in SAPHIR. Periodic spectral lines ($\Delta m/z = 14$) in a range between $m/z$ 300 to 800 with maximum intensity around $m/z$ 350 and 550 increased when sesquiterpenes were present. The complexity, periodicity and the wide range of ions resembled those of humic-like substances found in rural aerosol although the maximum in ambient samples was around $m/z$ 250–300 (Kiss et al., 2003). UV and Visible absorption of the samples were in accordance with HULIS formation.

In the analysis of the particle-phase with respect to carbonyls, a series of carbonyl group containing oxidation products was identified in the filter samples from Boreal mixture experiments. Among these, the elemental composition of $C_{15}H_{24}O_4$ (MW 268) was identified as a sesquiterpene oxidation product based on the number of carbons. The relative intensity of this compound decreased dramatically after the photochemical aging process, suggesting photochemical degradation of this compound in the particle phase. In the experiment with 50 ppb VOC load no significant change in the carbonyl compound concentrations originating from the monoterpenes (pinonaldehyde and endolim) in the particle-phase was observed for these experiments. On the other hand, much higher concentrations of pinonaldehyde and endolim were observed after the photochemical aging process in the experiment with higher VOC loads of 100 ppb and the corresponding aging experiment, indicating the continuous production of pinonaldehyde and endolim during the photochemical aging process in presence of higher VOC level. When no sesquiterpenes are present in the VOC mixture, lower concentrations of pinonaldehyde and endolim are observed in the particle phase than the comparable experiment with sesquiterpenes, indicating that sesquiterpenes react fast with OH radicals acting as an OH radical scavenger in these experiments.

CCN measurements of the aged particles showed an effective hygroscopicity parameter $\kappa$ of $0.1 \pm 0.02$ (Buchholz, 2010). This is in agreement with the average $\kappa$ of $0.08 \pm 0.03$ for the BSOA from Mediterranen and Boreal tree species (Buchholz, 2010) and with results of CCN field measurements of SOA particles in tropical as well as in mid-latitude environments (Gunthe et al., 2009; Dusek et al., 2010; Pöschl et al., 2010). With regard to the CCN properties of organic and mixed organic-inorganic aerosol particles, measurement data analyses and sensitivity studies using the new hygroscopicity distribution concept and cloud parcel model suggest that a simple $\kappa$-Köhler model approach can be used for efficient approximation and prediction of CCN concentrations in the atmosphere (Gunthe et al., 2009; Reutter et al., 2009; Pöschl et al., 2010; Su et al., 2010).

Photo-enhanced aging was observed in terms of different observables: Soot, humic acids and proxy components of biomass burning aerosols showed enhanced uptake of nitrogen dioxide and ozone under UV-A or visible light (Stemmler et al., 2007; Monge et al., 2010; Zelenay et al., 2011; Sosedova et al., 2011). The initial step is energy, electron
or hydrogen atom transfer from a partially oxidized organic precursor (which thereby gets oxidized) to an acceptor, catalyzed by an activated chromophore as a photosensitizer. This drives direct production of radicals, e.g. singlet oxygen (Styler et al., 2009), $O_2^-$ or $O_3^-$ (D'Anna et al., 2009), which then react further with the organic substrate or hydrolyse to $HO_2$ and OH, respectively. In the case of $NO_2$ as acceptor, this leads to release of HONO to the gas phase, which is a precursor of OH there. In terms of particle aging, this photochemistry leads to enhanced rates for the initial oxidation process but also initiates secondary, radical chain reactions that lead to high molecular weight products (Rouviere et al., 2009). Depending on the substrate the hydrophilicity of organic surfaces changes, which is important for CCN activation of organic particles (Nieto-Gligorovski et al., 2008; Zelenay et al., 2011). Related to these effects, on inorganic substrates, similar photochemistry supports renoxification of nitrate lost through heterogeneous reaction of $HNO_3$ with mineral dust (Vlasenko et al., 2009) via its photocatalytic reduction induced by titanium and iron oxides (Ndour et al., 2009a, b). Similar to the case of HONO above, these light induced reactions also feed back to gas-phase chemistry (Monge et al., 2010b).

A set of models and chemical mechanisms have been developed that enable a consistent description of the chemical transformation and aging of organic aerosol components under a wide range of different conditions, including a kinetic double-layer surface model (K2-SURF) and a chemical master mechanism (Shiraiwa et al., 2009); a kinetic double-layer model coupling aerosol surface and bulk chemistry (K2-SUB), in which mass transport and chemical reactions in the particle are represented by a reacto-diffusive flux (Pfrang et al., 2010); and a kinetic multi-layer model (KM-SUB) that explicitly resolves mass transport and chemical reaction at the surface and in the particle bulk (Shiraiwa et al., 2010). The formation and effects of amorphous solid phases in organic aerosol particles were investigated in laboratory and field experiments conducted in parallel to the model development (Mikhailov et al., 2009; Virtanen et al., 2010; Shiraiwa et al., 2011a; Pfrang et al., 2011; Koop et al., 2011). Moreover, studies employing the new models provided unprecedented insights into the molecular mechanisms and kinetics of aerosol-ozone interactions. They showed that long-lived reactive oxygen intermediates (ROIs) are formed. The ROIs explain and resolve apparent discrepancies between earlier quantum mechanical calculations and kinetic experiments. They play a key role in the chemical transformation and adverse health effects of toxic and allergenic air particulate matter, such as soot, polycyclic aromatic hydrocarbons and proteins. Moreover, ROIs may contribute to the coupling of atmospheric and biospheric multiphase processes (Shiraiwa et al., 2011b).

Following the method described in (Riipinen et al., 2006), temperature dependent sub-cooled liquid and solid state vapour pressures and enthalpies of vaporisation for malonic,

succinic, glutaric and adipic acid (Riipinen et al., 2007b; Kopenen et al., 2007) and vapour pressures of dried oxosuccinic, 2-oxoglutaric, 3-oxoglutaric and 4-oxopimelic acids (Frosch et al., 2010) have been derived from evaporation rate of binary aqueous or dried particles using the TDMA technique. Furthermore, uncertainties in inorganic/organic interactions in aqueous succinic acid/NaCl system have been explored using evaporation rates of the ternary mixed particles (Zardini et al., 2010). We also studied solid state vapour pressure from a levitated single organic crystal using optical techniques (an application to succinic acid can be found in Zardini et al., 2009).

Booth et al. (2009) reported vapour pressures for oxalic, malonic, succinic, glutaric and adipic acids measured by KEMS. Further vapour pressures and enthalpies and entropies of sublimation have been reported for the substituted dicarboxylic acids 2-methyl- and 2-hydroxy-malonic acid, 2-methyl-, 2-methyl-1,2-hydroxy-, 2-hydroxy-, 2,3-dihydroxy-, 2-amino- and 2-keto-succinic acid, 2-methyl-, 3-methyl-, 3-carboxylic-3-hydroxy-, 2-amino-, 2-keto- and 3-keto-glutaric acid (Booth et al., 2010). Similarly, measurements of cyclic aliphatic compounds (1,1-cyclopropane-, 1,1-cyclobutane-, 1,2-cyclopentane- and 1,3- and 1,4-cyclohexane-dicarboxylic acids, levoglucosan and cis-pinonic acid; Booth et al., 2011b) and mono- and di-substituted aromatic compound (phthalic-, isophthalic-, terephthalic-, vanillic-, syringic- and p-anisic acids and nitrocatechol) vapour pressures and enthalpies of sublimation have been made (Booth et al., 2011a).

The best estimation techniques for vapour pressure estimation not requiring properties at the critical point were evaluated against available literature data (Barley et al., 2010a). It was clearly demonstrated that the combination of the boiling point and vapour pressure estimation methods of Nannoolal et al. (2004 and 2008 respectively) had the best skill in predicting the vapour pressures of low volatility multifunctional organic compounds as known to occur in the atmosphere. Several vapour pressure estimation methods have been further evaluated against the newly measured values, reaffirming the skill of the Nannoolal et al. (2004, 2008) method, but highlighting a number of substantial discrepancies, even in the best techniques.

A reformulated molar absorptive partitioning model (Barley and McFiggans, 2010) has been used to evaluate the sensitivity of the total predicted mass, component O:C ratios, molar masses, volatilities and aerosol properties (densities, GF, CCN, forcing) to estimated properties. The sensitivities to vapour pressure are much greater than to component activity coefficient irrespective of whether the initialisations are randomly generated or predicted using a near-explicit model of oxidative VOC degradation (McFiggans et al., 2010; Barley et al., 2011; Topping et al., 2011a). The sensitivities are increased when trying to represent the complex multicomponent mixture by fewer components. This leads to a requirement to more accurately represent the volatility of, and
interactions between, all components with increasingly simple representations.

Suitably initialised and constrained, the predictions from equilibrium absorptive partitioning can be compared with suitable ambient measurements where available. At its broadest and most direct, this would be the mole fraction of all components with molecular identification. Such mass balanced characterisation is not practical and the total OA mass, averaged according to O:C ratio, molar mass spectrum, volatility distribution and relative POA/SOA contributions are accessible to comparison. Across a broad range of organic vapour and OA mass initialisations, the first four of the above metrics are predicted to fall in a relatively narrow range using the best available property estimation techniques. These metrics have been compared from absorptive partitioning predictions and literature-reported field measurements using output from the near-explicit MCM model (Bloss et al., 2005; Jenkin et al., 2003). Further comparison of this range with ambient measurements emerging from EUCAARI can be used to evaluate limitations with the equilibrium approach and discrepancies used to provide guidance for use of models incorporating the partitioning module developed.

The hybrid Partial Derivative Fitted Taylor Expansion (PD-FiTE) framework was introduced for inorganic compounds by Topping et al. (2009) and for organic compounds by Topping et al. (2011b), the latter based on the sensitivities described in Barley et al. (2011). PD-FiTE is a reduced complexity generalised thermodynamic framework for calculating activity coefficients in solution using optimised parameters to describe component interactions with improved computational performance and comparable accuracy to more complete thermodynamic models. A methodology for the automated generation, optimisation and benchmark evaluation of PD-FiTE has been developed based on the best available property estimation techniques from the sensitivity evaluations described above. Code can be generated to include any number of organic and inorganic compounds to accommodate the chemical mechanism of the host model. All component activities and vapour pressures over particles of given component mole fractions are calculated at the input RH and temperature. Though the skill in reproducing SOA loading will obviously be determined by the ability of the oxidation mechanism to produce the SOA precursors, PD-FiTE will ensure that minimal error is introduced in the thermodynamic calculation.

The state-of-the-science multicomponent activity coefficient code published on the E-AIM website (http://www.aim.env.uea.ac.uk/aim/aim.php/) was developed as the benchmark code for evaluation of the activity coefficients in the partitioning module. Combination of inorganic and organic activity coefficients was implemented (Clegg et al., 2008b) as well as user specification of organic compounds/surrogate properties and vapour pressure estimation. The E-AIM model can now calculate densities (Clegg and Wexler, 2011a,

b) and particle surface tensions (Dutcher et al., 2010) and reference thermodynamic data for inclusion of amines (Ge et al., 2011) has been compiled.

PD-FiTE compares well with E-AIM for inorganic components ($H^+-$NH$_4^+$-$Na^+$-$SO_4^{2-}$-$HSO_4^-$-$NO_3^-$-$Cl^-$) at 298 K and for organic components for various example mechanisms. Comparisons are presented in Topping et al. (2009) and Topping et al. (2011b) for inorganics and organics respectively. The linear additive framework readily allows inclusion of organic components with the interaction between inorganic and organic components where appropriate data exists.

The first version of a partitioning module has been incorporated into a coupled model of gaseous photochemistry and explicit multicomponent aerosol microphysics (Topping et al., 2009, 2011b), demonstrating its stability, accuracy and efficiency. The explicit incorporation of the representation of mass transfer into the non-equilibrium treatment of aerosol transformation allows investigation of the roles of kinetic limitations (through, for example, condensed phase diffusion in highly viscous amorphous solid particles) or enhancements (through condensed phase reactions, rapidly forming less volatile components from more volatile ones). This is not possible using equilibrium partitioning treatments.

## Appendix C

### Method-specific results of aerosol source apportionment related to Sect. 3.3.3

#### C1 Modern/fossil carbon

The analysis of the ¹⁴C/¹²C ratio in aerosol samples collected at various locations across Europe indicates that a major fraction of the organic aerosol mass originates from sources of modern carbon. The fraction of modern carbon ($f_M$) in TC (total carbon) for the time of year for which ¹⁴C data was available at the sites were going from north to south, for Vavihill (SE) 74%, Melpitz (DE) 75%, K-puszta (HU) 78%, San Pietro Capofiume (IT) 54%, and Ispra (IT) 52%. For the background site at Montseny outside Barcelona (ES) samples from two seasons were analyzed for ¹⁴C in OC and EC separately. The fraction of modern carbon ($f_M$) in these Montseny samples were for OC: 60–83% in winter and 71–93% in summer. The $f_M$ for EC was much lower, 25–46% in winter and 23% in summer. These values clearly indicate the importance of sources of modern carbon in European background continental air, most notably biomass combustion sources and biogenic SOA. A clear annual variability in the carbon $f_M$(TC) was observed at the Ispra site in northern Italy, with $f_M$ = 90% in winter and $f_M$ = 50% in summer. Residential wood combustion for heating purposes clearly has a major impact on the organic wintertime aerosol at Ispra (Gilardoni et al., 2011). At Montseny (ES) and Vavihill in
Southern Sweden (Genberg et al., 2011), $f_M$ was more constant over the year. The $f_M$ were high also at two urban sites studied. In Barcelona, OC-$f_M$ was 51–73 % in winter and 41–83 % in summer. Again, $f_M$(EC) was considerably lower with 11–24 % in winter and 5–20 % in summer. At an urban site in Zürich, $f_M$(TC) was 69–94 % in winter.

Ceburnis et al. (2011) showed, by utilising combinations of dual carbon isotope analysis, conclusive evidence of a dominant biogenic organic fraction to organic aerosol over biologically active oceans. In particular, the NE Atlantic, which is also subjected to notable anthropogenic influences via pollution transport processes, was found to contain 80 % organic aerosol matter of biogenic origin directly linked to plankton emissions.

Other OA complementary analytical techniques show that the major sources of modern OA are combustion and burning of biomass in winter and biogenic POA (primary OA) and SOA in summer. All of these have source strengths that are expected to vary in response to climate change. Since OA is a major component of the sub-micrometer aerosol over Europe, these sources of modern carbon may constitute important feedbacks mechanisms in the climate system.

## C2 Aerosol mass spectrometer (AMS) datasets

A unique OA data set was obtained from 30 AMS campaigns across Europe conducted within the EMEP/EUCAARI framework, mainly from three coordinated campaigns in April/May 2008, September/October 2008 and Febru ary/March 2009. The AMS data was acquired at 17 sites around Europe: Auchencorth/Bush (GB), Har well/Chilbolton (GB), Hyytiälä (FI), Puijo (FI), Helsinki (FI), Vavihill (SE), Cabauw (NL), Jungfraujoch (CH), Pay erne (CH), Melpitz (D), Puy de Dome (FR), San Pietro Capofiume (IT), Finokalia (GR), Mace Head (IE), Barcelona (ES), Montseny (ES), K-puszta (HU).

The AMS data clearly show that a large mass fraction of the sub-micrometer aerosol mass in Europe is organic. The average OA concentrations ranged from 1 µg m⁻³ at elevated sites to 8 µg m⁻³ in downtown Barcelona. Organic mass frac tions (in non-refractory PM₁) range between 20 % to 60 %. Temporal variability is typically high at each site.

Positive Matrix Factorization (PMF) was used to examine the OA nature and ageing state, and to identify OA sources. The OA PMF analysis of the 30 AMS data sets yielded 1- to 4-factor PMF solutions, with 2 and 3 factors being most common. The most frequently observed OA compo nent was for all cases OOA (oxygenated OA), followed by HOA (hydrocarbon-like, more fresh OA), BBOA (biomass- burning OA), and in one case (Finokalia, Crete) amine-like OA. In Barcelona, the only real city site in this compilation, an additional cooking factor was identified. OOA as derived from the PMF analysis is probably mostly SOA, and domi nated OA mass (55–100 % of total OA). POA (if defined as HOA and BBOA) ranged between 0 % (observed in many

datasets) and 45 % (Barcelona) of OA. In several data sets affected by biomass combustion and burning, the AMS PMF apportionment of BBOA (biomass-burning OA) agreed well with that derived from levoglucosan analysis on filter sam ples. Most sites and data sets showed a clear diurnal vari ability for the various OA PMF factors. As an example, the continental polluted site Melpitz, had the highest concentra tions of LV-OOA (low-volatility OOA) during the afternoon hours (mixing down of aged residual air from aloft), a max imum in SV-OOA (semi-volatile OOA) during night (parti tioning from gas to particle phase at lower nighttime temper atures), a biomass burning OA maximum in late evening due to residential wood combustion, and HOA peaking during the morning rush hours.

Attempts were also made to estimate the nitrate mass frac tion that could be ascribed to organic nitrates, based on unit mass and high resolution AMS data. Average concentra tions ranged from below detection limit at remote and el evated sites to 1.6 µg m⁻³ in San Pietro Capofiume. The fraction of sub-micrometer nitrate that was estimated to be non-NH₄NO₃ ranged from 20 % to 60 % with typical values around 30 %.

## C3 Gas Chromatography-Mass Spectrometry – organic tracers

Analyses of organic tracers using GC-MS analysis of fil ter samples were used for OA source apportionment at five background sites on a campaign basis (Hyytiälä, San Pietro Capofiume, K-puszta, Melpitz, and Montseny). n-Alkanes and polycyclic aromatic hydrocarbons (PAH) in aerosols were chemically characterized, along with source attribution based on the carbon preference index (CPI), the ratios be tween the unresolved and the chromatographically resolved aliphatics (U/R), the contribution of wax *n*-alkanes from plants (WNA = $C_n$-[$C_{n+1}$+$C_{n-1}$]/2]) and diagnostic ratios of PAH. For two other European sites, Vavihill (background site in southern SE) and Ispra (IT), OA source apportionment was performed for a full seasonal cycle on less extensive OA data sets.

The presence of petroleum residues was confirmed by the low CPI values and high ratio of resolved to unresolved aliphatic components, particularly in Hyytiälä and San Pietro Capofiume. The input of primary biogenic sources was sig nificant in K-puszta and Melpitz, where 60 % and about 50 %, respectively, of the total *n*-alkanes were attributable to plant waxes. This biogenic contribution represented only 15 and 23 % of the total *n*-alkanes found in the boreal and Mediterranean aerosol, respectively. Diagnostic ratios be tween PAH suggest that vehicular emissions and biomass burning also influence the aerosol constitution in the Hungar ian site. Long range transport of air masses contributed with anthropogenic components to the atmospheric aerosol in the boreal forest. In spite of transboundary pollution, Hyytiälä registered the lowest hydrocarbon levels among all locations.
Aliphatic and aromatic hydrocarbons in samples from San Pietro Capofiume reveal that both vehicular and industrial emissions are major sources influencing the diurnal pattern of concentrations. The average benzo(a)pyrene equivalent concentration (BaPE) concentrations obtained for every EU-CAARI site were far lower than the mandatory limit value (1 ng m⁻³).

The organic characterization of submicron aerosols from Barcelona, Zürich and Montseny pointed out that traffic is one of the main sources in the urban locations. CPI values close to 1 for the aliphatic fraction of the Montseny aerosol suggest that the anthropogenic input may be associated with the transport of aged air masses from the surrounding industrial/urban areas, which superimpose the local hydrocarbons with biogenic origin. Aerosols from the urban area of Zürich presented a much higher PAH content, and BaPE concentrations sometimes exceeding the mandatory limit. Besides traffic, residential wood burning was found to be another dominant emission source contributing to the atmospheric aerosol at the Swiss urban location, confirming the results obtained by AMS for Zurich and in general in Central Europe during winter (Lanz et al., 2008, 2010).

## C4 Nuclear Magnetic Resonance (NMR) spectroscopy

H-NMR spectroscopy was employed for the off-line analysis of fine aerosol samples (Decesari et al., 2007) collected at the six European sites in 2008–2009, in parallel with AMS measurements. The evaluation of the HNMR data used positive matrix factorization (PMF) techniques and other chemometric methods (Decesari et al., 2011b). Factor analysis was applied to NMR spectral datasets for the following field sites: Hyytiälä, San Pietro Capofiume, Mace Head, Cabauw, Melpitz, K-puzsta, Zürich, and Barcelona-Montseny.

The analysis of the NMR spectra by factor analysis provided a split between four factors: (1) biomass burning products, showing a spectrum containing levoglucosan, but also other polyols and abundant aromatic compounds; (2) biogenic SOA generated by vegetation emissions (terpenes); (3) organic aerosol generated by compounds formed by the degradation of biological material (e.g. alkylamines); and (4) more generic HULIS-like OOA type, with oxidized aliphatic moieties and a smaller contribution from aromatics. The NMR biomass burning factor concentration in the Po Valley correlated well with the concentration of wood burning tracers (levoglucosan) and are also positively correlated with the AMS factors for fresh and aged biomass burning products. The biogenic SOA source type appeared for the March–April 2007 campaign in the Hyytiälä boreal forest site. A high degree of similarity was found between this spectrum and that of biogenic SOA formed from terpene oxidation in the reaction chambers of PSI and FZJ. The amine source type was also found at Hyytiälä. These findings suggest that biogenic organic aerosols in the boreal forest originate from at least two independent sources: condensation of amines and the

oxidation of reactive terpenes, with the first process being relatively more important in the low aerosol concentration regime. These results are important since they offer a possible method by which biogenic SOA can be accurately apportioned (Finessi et al., 2011b).

## Appendix D

### Organic aerosol modeling in the regional scale related to Sect. 3.4.5

The EMEP MSC-W chemical transport model (Simpson et al., 2007, 2011) is a key tool for policy support within both the LRTAP Convention and the European Union Clean Air for Europe Programme (CAFE). Improved predictions of especially the organic aerosol component (OA) of PM are urgently required to support these policy fora, as OA typically accounts for 10–40 % of PM₁₀ in Europe.

In order to improve the EMEP MSC-W chemical transport model, the SOA module (Simpson et al., 2007, 2011) has been extended by incorporating a new organic aerosol (OA) scheme based on the Volatility Basis Set (VBS) approach (Robinson et al., 2007). For primary organic aerosol (POA) emissions, the EUCAARI anthropogenic carbonaceous aerosol emission inventory (Denier van der Gon et al., 2010; Visschedijk et al., 2009, Sect. 3.1) was used, which includes improved estimates of residential wood combustion and has high spatial resolution (1/8° × 1/16°).

The VBS scheme has recently been introduced to help models cope with the wide range of aerosol concentrations and the ongoing oxidation of semi-volatile organics in the atmosphere. VBS models are computationally efficient and are therefore interesting candidates for 3-D modelling. However, they are sensitive to assumptions regarding emissions, the (semi-) volatility of anthropogenic VOC-emissions, and chemical ageing of SOA. Given the lack of theoretical constraints on these SOA models, and general difficulties with the understanding of SOA, comparison and indeed calibration of the model against observational data is essential before models such as EMEP can be used for reliable policy guidance.

The OA model outputs from these and other set-ups have been compared to measurement data and especially source-apportionment results from several European campaigns, including EUCAARI. As discussed in more detail in Bergström et al. (2011), the model performance varies between stations. It seems clear that the VBS-PAPS version overestimates OC in summer at most locations. The VBS-PAPS model assumes partitioning of POA emissions, and includes gas phase ageing of both anthropogenic and biogenic SOA as well as POA. This version uses an order of magnitude slower OH-reaction rate for SOA (4 × 10⁻¹² cm³ molecule⁻¹ s⁻¹) than for POA. The other VBS model versions give lower OC concentrations, closer
to observed levels. For the winter months, all model versions give similar (fairly low) OC concentrations. For two of the measurement sites, Ispra and Illmitz, the EMEP VBS models underestimate winter and early spring concentrations of OC severely. Similar under predictions were noted also in earlier versions of the EMEP OA model (Simpson et al., 2007), and were then shown to result from problems with significant contributions of wood-burning to OA.

Residential wood combustion was shown to be a major source of wintertime OA at Ispra in northern Italy (Gilardoni et al., 2011) in Oslo and a nearby background site in southern Norway (Yttri et al., 2011a, b), as well as at Vavihill in southern Sweden (Genberg et al., 2011). Despite these congruent observations, it is not possible to say at this stage if such contributions are a local problem or reflect more widespread problems with the wood-burning inventories.

# Appendix E

## Answers to specific problems described in chapter 1 and also in Kulmala et al. (2009)

### E1 In-situ formation (nucleation) of aerosols

The most important technical achievement in the nucleation area was the development of new instruments for measuring sub-3 nm particle populations, along with the extensive application of these instruments in both laboratory and field studies. These instruments include the Neutral cluster and Air Ion Spectrometer (NAIS, Kulmala et al., 2007a), Ion-Differential Mobility Particle Sizer (Laakso et al., 2007), Condensation Particle Counter Battery (Kulmala et al., 2007b), various other CPC techniques (Sipilä et al., 2008; Vanhanen et al., 2011), and the Atmospheric Pressure Interface Time of Flight Mass Spectrometer (API-ToF-MS, Junninen et al., 2010; Ehn et al., 2010).

Ion spectrometers were continuously operated for roughly a full year at 13 field sites during the EUCAARI Intensive Observation Period (IOP) (Manninen et al., 2010), and the air-borne version of the NAIS was used in the EUCAARI long range experiment (Mirme et al., 2010). Based on NAIS measurements, we obtained the first quantitative estimate of the concentrations of neutral sub-3 nm particles in the continental boundary layer (Kulmala et al., 2007a) and the free troposphere (Mirme et al., 2010). The concentrations of neutral sub-3 nm particles exceed those of charged particles in the same size range in the lower troposphere (Lehtipalo et al., 2009; Manninen et al., 2010). The average formation rates of 2-nm particles were found to vary by almost two orders of magnitude between the different EUCAARI sites, whereas the formation rates of charged 2-nm particles varied very little between the sites (Manninen et al., 2010). Overall, our observations are indicative of frequent, yet moderate, ion-induced nucleation usually outweighed by much

stronger neutral nucleation events in the continental lower troposphere.

All the scientific results obtained during EUCAARI indicate that sulphuric acid plays a central role in atmospheric nucleation (Kerminen et al., 2010; Sipilä et al., 2010). However, also vapours other than sulphuric acid are needed to explain the nucleation and the subsequent growth particle processes. Candidate vapours include various organic compounds and very likely also ammonia or amines (Berndt et al., 2010; Paasonen et al., 2010). Field and laboratory data demonstrate that the nucleation rate scales to the first or second power of the nucleating vapour concentration(s) (Riipinen et al., 2007a; Metzger et al., 2010; Paasonen et al., 2010; Sipilä et al., 2010). This finding agrees with the few earlier field observations, but is in stark contrast with classical thermodynamic nucleation theories.

By using different quantum mechanics methods, atmospherically relevant molecular clusters were studied to elucidate the molecular mechanism behind observed atmospheric nucleation. Our main findings from quantum chemical calculations were that: (i) ammonia can enhance neutral sulphuric acid-water nucleation to some extent, but has a smaller role in corresponding ion-induced nucleation (Ortega et al., 2008), (ii) dimethylamine enhances neutral and ion-induced sulphuric acid-water nucleation in the atmosphere more effectively than ammonia (Kurtén et al., 2008; Loukonen et al., 2010), (iii) some of the organic acids resulting from monoterpenes oxidation can form very stable clusters with sulphuric acid, being good candidates to explain the pool of neutral clusters found in field measurements, and (iv) organosulphates can be involved in ion-induced nucleation.

A major outcome of the EUCAARI nucleation studies is the new semi-empirical nucleation rate parametrizations for neutral and ion-induced nucleation based on field observations (Riipinen et al., 2007a; Paasonen et al., 2010; Nieminen et al., 2010). These parametrizations, while compatible with the atmospheric measurements made during the EUCAARI project, probably need further refinements to become more accurate at varying atmospheric conditions, especially at conditions encountered outside the continental boundary layer. Refining the existing parametrizations requires additional field and laboratory measurement data, such as those coming from the on-going CLOUD experiment (Kirkby et al., 2011).

Direct application of nucleation rate parametrizations is not possible, or at least not desirable, in large-scale modelling frameworks (see Kerminen et al., 2010). As a result, an additional aerosol formation rate parametrization is needed. In EUCAARI, the existing and widely-applied aerosol formation rate parametrization by Kerminen and Kulmala (2002) was further improved (Lehtinen et al., 2007; Anttila et al., 2010).
## E2 Number and mass emissions of primary aerosol from natural and anthropogenic sources at urban, regional, and global scales

Emission inventories for primary particle mass, the distribution of organic and elemental carbon and anthropogenic aerosol particle number emission inventories were developed for Europe within EUCAARI. In particular, the particle number emission inventories developed for Europe were the first of their kind in the world. (see Sect. 3.1, Johansson et al., 2008; Denier van der Gon et al., 2011).

The particle number emissions in Europe are dominated by sub-micron particles. The most important anthropogenic sources of these particles vary considerably depending on country and region: while in the EU countries transport makes about half of the fine particle emissions, in non-EU parts of Europe industrial processes along with residential and commercial combustion dominate the fine particle emission inventories. Fossil fuel production, on the other hand, is not a relevant source of fine particles in any parts of Europe.

Emissions from diesel engines dominate the transport-related particle number emissions. The particle number emissions from residential combustion are dominated by coal burning emissions, whereas wood burning dominates the particulate mass emissions. A remarkable feature of residential coal burning is the large amount of very fine PN (<25 nm) which is related to the sulfur content of the fuel. The transport-related emissions are highest in the densely populated Central and Western Europe, the Moscow region standing out as a single hotspot outside Central Europe. Emissions from road-transport in Eastern Europe are much more allocated to urban centers than in the Western or Central Europe. Particle number emissions from residential combustion are concentrated in Eastern Europe, particularly Poland, Czech Republic, Slovakia, Ukraine and former Yugoslavian countries.

## E3 Formation of secondary organic aerosol and the partitioning of semi-volatile compounds between the gas and aerosol phases

Since the onset of EUCAARI in January 2007, there has been substantial progress regarding our ability to describe the formation of secondary organic aerosol and the partitioning of semi-volatile compounds between the gas and aerosol phases. In 2007, most models seriously underestimated the regional-scale concentrations of secondary organic aerosols (Volkamer et al., 2006) while often overestimating the concentrations of primary organic particulate matter. This deficiency was in part remedied by the realization that a large fraction of the primary organic aerosol (POA) may indeed be semi-volatile, evaporating partially during the rapid dilution that takes place when fresh combustion emissions enter the atmosphere. These semi-volatile gas-phase compounds are subsequently oxidized in the atmosphere and, to a large

extent, partition back to the particle phase as oxidized organic compounds (Robinson et al., 2007). The result is that OA mass is shifted from the immediate vicinity of the POA sources – often urban – to further downstream, thus increasing the OA concentrations on a regional scale. For all but the initial oxidation steps, it is evident that, in order to handle OA in regional and global scale models, it is necessary to simplify the complexity of OA, including the POA volatility behaviour and SOA formation and gas-particle partitioning.

Several OA models, also those within EUCAARI (PM-CAMx and EMEP) have been updated using the volatility basis set (VBS) concept (Donahue et al., 2006). Alternative descriptions to simplify the wide range of OA properties have been proposed, such as that by Kroll et al. (2011) that uses average oxidation state versus carbon number, that of Pankow and Barsanti (2009) that maps OA according to polarity and carbon number and that of Donahue et al., 2011) (the 2-D VBS) in which the SOA volatility and O/C ratio span a space wherein all SOA can be categorized.

EUCAARI has also contributed to the improvement of our description of OA and SOA formation by providing a model framework for the gas-particle partitioning of semi-volatile OA. The modules that were developed reduce the complexity of the OA partitioning problem, even to an extent where they can be included in global OA models. The OA can be mapped onto a variety of simplified OA spaces, such as O/C ratio versus molecular weight or those described above. In addition, the framework can be used to predict a wide range of important OA properties (O/C ratio, molar mass, volatility, density, hygroscopic growth, CCN activity) that are directly verifiable against laboratory and field measurements. This ability is essential for the evaluation of the codes. The modules that were developed within EUCAARI offer a link that did not previously exist between the explicit reaction kinetics as described by the Master Chemical Mechanism and various OA descriptions of reduced complexity.

Another important EUCAARI contribution is the progress with respect to the formation of biogenic SOA. EUCAARI has shown that a large fraction of the OA in Europe is of modern origin, for which the main sources are BSOA, biomass burning and primary biogenic aerosol particles. All these sources are expected to respond to climate change, although we are presently unable to gauge the strength of the multitude of feedback mechanisms involved. For instance, laboratory studies showed that BSOA production from monoterpenene precursors increased with temperature, which may constitute a climate cooling effect (negative feedback). On the other hand, increased isoprene emissions, which are to be expected at raising temperatures, was demonstrated to hinder the formation of new particles, which may instead be a positive feedback mechanism (Kiendler-Scharr et al., 2009b). The identification of specific BSOA molecular markers that are representative of various stages of BVOC ageing offers a direct way to apportion the SOA to its various sources and, perhaps even more important, to estimate the state of OA
ageing that can be compared to other methods, such as those offered by the AMS and HNMR techniques. Another important aspect of SOA formation that received further attention during EUCAARI is the multiphase oxidation reactions. Myriokefalitakis et al. (2011) performed the first global modelling study that explicitly parametrized and evaluated the impact of multiphase chemistry on organic aerosol formation, in particular through oxalic acid formation. Their results have been supported by extensive comparison with observations and demonstrated that multiphase reactions in the global atmosphere can produce significant amounts of water soluble organic aerosol (5–10 Tg-C yr⁻¹ of oxalate).

## E4 Ageing of aerosols and evolution of their properties during their atmospheric lifetime

EUCAARI field measurements suggested that chemical aging of OA reduces its volatility of OA by approximately 2 or more orders of magnitude compared to fresh laboratory-generated monoterpane SOA (Lee et al., 2010). Field measurements suggest that the atmospheric ageing of OA over Europe drives the OA to a state with an almost constant AMS mass spectrum (Hildebrandt et al., 2010) and a fairly narrow range of hygroscopic properties.

Aging of aerosols modifies all properties of aerosols and occurs mostly via coagulation, condensation, or sedimentation. Concerning inorganic aerosols, condensation mainly relates to the condensation of sulfuric acid (through oxidation of SO₂) and nitric acid (through oxidation of NOₓ), where the latter typically requires the presence of NH₃. While the formation of inorganic aerosols is understood rather well, the condensation of organic components is much less known. An important mechanism in the latter case is the evaporation – gas phase reaction – condensation cycle, as outlined in the answer to question D.3.

Aging of organic compounds may occur either by functionalization, fragmentation, or oligomerization (Jimenez et al., 2009). Functionalization and fragmentation mainly occur in the gas phase, while oligomerization is likely to proceed largely in the aqueous phase and produces HULIS (humic-like substances). Functionalization will increase the oxidation state and decrease the volatility. Fragmentation will increase both oxidation state and volatility, and will ultimately lead to CO₂. These conflicting rates are currently not well described, although various estimates can be evaluated and constrained in OA models using the VBS approach. Oligomerization will decrease the volatility, with marginal positive or negative changes in the oxidation state, depending on the actual mechanism. Oligomerization may also be accelerated by photoenhancement (Rouviere et al., 2009) or by cloud processing (Michaud et al., 2009). The actual rates of all these oligomerization mechanisms are still poorly known, but the model framework will in the future have to incorporate the rates at which this oligomerization proceeds, including their

relative importance compared to functionalization and fragmentation.

EUCAARI has identified specific BSOA molecular markers that are representative of various stages of BVOC ageing. BSOA ages related to the experienced OH dose, leading eventually to highly oxidized compounds. BSOA observed in chambers is characterized by 2–4 different ageing states, which can be mapped to the two OOA classes observed in the atmosphere (Jimenez et al., 2009) and related to certain molecular markers like pinic acid or 3-MBTCA. Overall, the ageing processes over 2–3 days lead to a mass increase and more persistent organic aerosols with increased hygroscopicity. The ratios of such markers characterize the BSOA age, applicable in field studies. They also offer a way to apportion the SOA to its various sources and, perhaps even more important, to estimate the state of OA ageing that can be compared to other methods, such as those offered by the AMS and HNMR techniques.

In the *f*₄₄ vs. *f*₄₃ space of AMS fragments (Ng et al., 2010) the OOA (which mostly represents SOA in the absence of considerable amounts of biomass burning aerosol) spans a characteristic triangle, where fresh SOA is found at the bottom and moves upwards during aging. The larger diversity of compositions observed for fresh OOA reflects the multiple fingerprints of anthropogenic (e.g. biomass burning) and biogenic (e.g. terpene SOA) sources, while the aged OOA exhibits a consistent composition dominated by humic-like substances (HULIS) and related compounds. Each area can be related to H-NMR spectra obtained by simultaneous sampling during various EUCAARI campaigns, where the latter can be tentatively interpreted to correspond to the various AMS OA source types.

Low-volatility oxidized organic aerosol (LV-OOA, which includes the HULIS fraction) is the end-product of OA ageing, and is found in the upper apex of the triangle. It is the most common constituent of the European regional continental polluted background under clear sky and stable meteorological conditions (from May 2008 IOP).

## E5 Attribution of the different aerosol mass components in Europe to specific sources

The sources of sulphate, nitrate, ammonium, sodium, chloride, and crustal elements are relatively well understood in Europe so EUCAARI focused on OA and EC sources. OA is the most important component of fine PM in Europe (with the exception of Southeast Europe). A large fraction of this OA (more than half in most areas and seasons) is of modern origin, for which the main sources are biogenic SOA and biomass burning. Biogenic SOA dominates during the summer, while residential biomass burning is the major modern OA source during the winter.

The most important anthropogenic primary OA source according to the EUCAARI European inventory is non-industrial combustion followed by agriculture and road
transport. Significant contributions to primary OA emissions are also made by production processes, other mobile sources and machinery and waste treatment and disposal. However, most of this POA is rapidly transformed to oxidized OA through atmospheric chemistry. POA concentrations are very low in Europe outside the major urban areas. Wood burning emissions appear to be underestimated in at least some European countries.

Road transport and non-industrial combustion are the two major EC emission sources followed by other mobile sources. Significant contributions to the EC levels are also made by production processes, waste disposal and agricultural sources.

The reduction in ammonia emissions is one of the most effective ways to reduce aerosol mass concentrations in Europe. Reduction in NOₓ is also effective, but might lead to higher ozone levels. Reduction in SO₂ emissions will reduce particulate air pollution especially in the Eastern Mediterranean area. Reduction of organic aerosol concentrations is a lot more challenging and will require reductions of gas and aerosol emissions from transportation and biomass burning.

## E6 Current and future contributions of natural versus anthropogenic, and primary versus secondary sources to particle number concentrations

The contributions of primary versus secondary and natural versus anthropogenic contributions to particle number concentrations have been studied with models simulating atmospheric transport and composition in both European and global scales (Jung et al., 2008; Spracklen et al., 2010; Merikanto et al., 2009, 2010; Fountoukis et al., 2011b).

The particle number concentrations are typically dominated by sub-micron particles, and a large fraction, usually several tens of percents, of these particles have originated from condensation of atmospheric vapours (Spracklen et al., 2006; Makkonen et al., 2009; Merikanto et al., 2009; Jung et al., 2010; Spracklen et al., 2010). Typically roughly every second aerosol particle in the European boundary layer is of secondary origin. This highlights the need for combined emission inventories and regulations for gas phase compounds and aerosol particles, instead of treating them as separate and non-interactive constituents of the atmosphere.

Because of the large contribution of secondary particles, the natural and anthropogenic contributions to particle number concentrations are difficult to quantify exactly. We have shown that often both natural (e.g. biogenic organic compounds) and anthropogenic (e.g. sulphuric acid or anthropogenic organics) vapours participate in the formation of secondary aerosol particles (Spracklen et al., 2008b; Metzger et al., 2010). While anthropogenic sulphate emissions are a major factor governing formation of new particles, natural emissions of biogenic organic vapours play an important role in defining the aerosol size distributions and the climatic

impact of aerosols. Indications on the sensitivity of particle number concentrations to anthropogenic and natural gas emissions can be obtained with model studies (Spracklen et al., 2008a; Makkonen et al., 2011). The results suggest that a decrease of 50% in SO₂ emissions will result in a moderate (15–20%) decrease in particle number concentrations in all size classes (see Kerminen et al., 2010 and Sect. 3.2.1). A corresponding reduction in primary particle emissions, on the other hand, would have only a minor effect on the smallest particles or total number concentrations, but a moderate one (around 20%) on the particles larger than 100 nm in diameter. Additionally, we have shown that biogenic organic emissions from vegetation are an important factor driving the concentrations of climate-relevant aerosols over remote continental regions. Spracklen et al. (2008a) found that inclusion of biogenic emissions from forests roughly doubled the climate-relevant aerosol number concentrations over the boreal region.

To assess the effect of air quality regulations on particle number concentrations, the effect of primary particle emissions along with secondary particle formation on global particle number in pre-industrial, present and future conditions (years 1850, 2000 and 2100 – using the IPCC scenario A1B) was studied (Makkonen et al., 2011). It was found that the future air quality improvements are likely to considerably decrease aerosol number concentrations and thus the cooling effect of aerosols on climate. According to these first results, the probability that any reasonable changes in natural emissions could counteract this effect is very small (Tunved et al., 2008).

Although our results shed light on the sensitivity of aerosol number concentrations to anthropogenic pollutants and natural emissions, the future forecasts are challenging due to the multitude of atmospheric processes affecting the modelling results. This highlights the need to maintain and possibly extend the provision of long-term data for atmospheric composition and gas-aerosol distributions (Reddington et al., 2011).

Overall, EUCAARI has shown clearly that particle formation processes from anthropogenic and natural gaseous precursors are a major source of cloud drop-forming aerosol over Europe. The process needs to be accurately described in climate models so that the link between climate and air quality can be established reliably. EUCAARI therefore provides a clear plan for the future development of regional and global air quality and climate models.

## E7 Long-range transport of aerosol particles and their precursors from and to Europe as well as their transport within Europe

Birmili et al. (2008) showed that dust emissions in the southern Ukraine during a drought can cause very high PM₁₀ concentrations (between 200 and 1400 µg m⁻³) over Central Europe. While such strong long-range transport events are probably not very frequent, this shows that dust transport
models need to account for this dust source, in addition to
the more frequently studied Saharan dust events. Saharan
dust has been shown repeatedly to be an important source of
coarse-mode particles (PM₁₀) in Southern Europe (e.g. Pikri-
das et al., 2010). However, it was also shown that the concen-
trations of sub-micron particles (PM₁) on Crete are lowest
in marine air masses and highest in air masses transported
from the Balkans, Turkey and Eastern Europe (Pikridas et
al., 2010), showing that the export of pollution from Eastern
Europe can influence large areas of the Mediterranean and
likely beyond.

Transport of aerosol pollution from Eastern Europe also
affects Scandinavia. Virkkula et al. (2010) found that the
highest values of the aerosol light absorption coefficient at
a remote site in Finland were associated with transport of
air masses from Eastern Europe. Furthermore, Saarikoski
et al. (2008) have shown that long-range transport can play
a role even in urban areas in Scandinavia. They found that
24 % of the OC found in Helsinki can result from long-range
transport into the urban area, including a contribution from
agricultural or wild fires.

During the EUCAARI-LONG Range Experiment (EUCAARI-LONGREX), a sustained anticyclonic situation over Central Europe caused accumulation of aerosol pollution in the boundary layer and its subsequent export to the west and north-west (Hamburger et al., 2011). This allowed studying both the accumulation as well as the export of aerosol pollution from Europe and the changes in chemical composition occurring en route. Substantial amounts of pollution were observed by aircraft far downwind of continental Europe, with OA and ammonium nitrate being the major constituents of the sub-micron aerosol burden (Morgan et al., 2010a). Refractory black carbon concentrations were enhanced, too (McMeeking et al., 2010). At Mace Head on the Irish west coast, large differences were found between marine air masses arriving from the west and European polluted air masses arriving from the east. While organic matter dominated the sub-micron aerosol mass in the European pollution outflow, sulphate was dominant in the marine air masses. While polluted-continental aerosol concentrations were of the order of 3000 cm⁻³, background marine air aerosol concentrations were between 400–600 cm⁻³. Recirculation in the high-pressure system during EUCAARI-LONGREX also caused the return of some of the exported pollution from the North Atlantic into Northern Europe (Hamburger et al., 2011).

In summary, EUCAARI has shown that long-range trans-
port of aerosol pollution from Central and Eastern Europe
can exert a large influence in the Mediterranean, over the
North Atlantic and over Scandinavia. On the other hand,
Central Europe is influenced by long-range transport of dust
from the Sahara but occasionally also from Eastern Eu-
rope, and is also influenced by transport of biomass burning
plumes.

E8 Seasonal behaviour of aerosol particles in economically developing countries

South-Africa: the seasonal variation of the aerosol near Jo-
hannesburg is significantly affected by domestic and biomass
burning especially during the dry and cold winter season.
Furthermore, the aerosol fine and coarse mass concentra-
tions showed clear seasonal variation. PM2.5 was on aver-
age 28 µg m⁻³ during the winter and spring, and as low as
13 µg m⁻³ during the summer. PM2.5–10 was highest during
the fall, 29 µg m⁻³ and lowest during the summer, 11 µg m⁻³.
The aerosol scattering coefficient at 520 nm wavelength was
highest during the winter period (80.7 Mm⁻¹) accompa-
nied by an absorption coefficient of 8.5 Mm⁻¹ (~1.3 µg m⁻³
black carbon). Particle number concentrations (20–800 nm)
were highest (5900 cm⁻³) due to strong new particle forma-
tion during the summer season, while the lowest concen-
trations (3300 cm⁻³) were observed during autumn, when
nucleation was reduced. The fine fraction consisted of OC
(45 % during the spring, 14 % during the summer), sulphates
(44 % during the summer, 20 % during the spring) and am-
monia (20 % during the summer, 8 % during the spring).

The local summer (December–February) had the most dis-
tinct planetary boundary layer (PBL) evolution on most days.
A very shallow aerosol layer was observed during the night
and an increase up to 2–3 km during the day on average. The
maximum layer thickness was about 5 km. This period was
the cloudiest period of the year and in contrast winter (June–
August) was almost totally unclouded. Strong and complex
multi-layered structure of the aerosol was observed through-
out the year, most frequently in autumn (March–May). Win-
ter and partly spring (September–November) showed mostly
a stable aerosol layer up to 1–3 km height and also the diurnal
variation was the weakest in winter.

India: the seasonal variation of the aerosol charac-
teristics was very distinct in Gual Pahari. The high-
est concentrations were observed during the winter (PM₁₀
mean = 322 µg m⁻³) and the lowest during the rainy sea-
son (PM₁₀ mean = 93 µg m⁻³). During the pre-monsoon
(March–June) surface concentrations began to decrease as
the temperatures increased thus intensifying the natural con-
vection. The coarse mode contribution increased to 40–
50 % due to dust events. During the monsoon season (July–
September), aerosol concentrations decreased by 50–70 %
compared to the pre-monsoon season, depending on the total
seasonal rainfall. OM, EC, nitrate, sulphate, and ammonium
had highest concentrations during the dry season. OM dom-
inated the fine mass; it represented 60 % of the fine mass
during the wet season and around 50 % during the dry sea-
son. During the wet season higher relative contributions of
EC and sulphate were observed. During the dry season the
contribution of ammonium and nitrate increased. Equivalent
black carbon concentrations alone averaged to 17.7 µg m⁻³.
In the post-monsoon season (October–November) the fine
fraction started to dominate the aerosol characteristics with
total aerosol number concentration averaging $24\,000\,\text{cm}^{-3}$. During winter the night- and day time temperatures had their lowest values, thus decreasing natural convection and the boundary layer height.

Brazil: aerosol physical properties were measured at a pristine Amazonian forest site from February 2008 to January 2011. A strong seasonal behaviour was observed, with greater aerosol loadings during the dry season (July–November) as compared to the wet season (December–June). During the wet season, aerosol scattering (450 nm) and absorption (637 nm) coefficients averaged, respectively, $14 \pm 22$ and $0.9 \pm 0.8\,\text{Mm}^{-1}$, increasing to $58 \pm 58\,\text{Mm}^{-1}$ and $4.1 \pm 3.8\,\text{Mm}^{-1}$ during the dry season, correspondingly. From wet to dry season, integrated aerosol number concentrations increased approximately by a factor of two. During the wet season, the Aitken mode (~30–100 nm) was prominent, suggesting the presence of secondary aerosol. In contrast, during the dry season the accumulation mode (100–500 nm) dominates the aerosol size spectra, indicating the presence of primary and/or aged aerosol.

PM$_{2.5}$ and PM$_{2.5-10}$ samples were taken from February to June (wet season) and from August to September (dry season) in 2008. The mass of fine particles averaged $2.4\,\mu\text{g m}^{-3}$ during the wet season and $4.2\,\mu\text{g m}^{-3}$ during the dry season. The average coarse aerosol mass concentration during wet and dry periods was 7.9 and $7.6\,\mu\text{g m}^{-3}$, respectively. The overall chemical composition of fine and coarse mass did not show any seasonality, with the largest fraction of fine and coarse aerosol mass explained by organic carbon (OC). The average OC to mass ratio was 0.4 and 0.6 in fine and coarse aerosol modes, respectively. 44% of fine total carbon mass was assigned to biomass burning, 43% to secondary organic aerosol (SOA), and 13% to volatile species that are difficult to apportion. The carbon fraction represented by biomass burning and SOA were 35% and 49% during the wet season, and 71% and 25% during the dry season, respectively. In the coarse mode, primary biogenic aerosol particles (PBAP) dominated the carbonaceous aerosol mass. The PBAP concentration averaged $2.4–1.6\,\mu\text{g m}^{-3}$, with higher values during the wet season, up to $7\,\mu\text{g m}^{-3}$.

China: The number concentration of nucleation mode particles showed a clear monthly variation with the minimum mean value of about $1000\,\text{cm}^{-3}$ in July and August 2008 and a maximum mean value of $10\,000\,\text{cm}^{-3}$ in March 2008. The nucleation events peaked in spring and early summer and reached a minimum in summertime. During these particle formation events, the number concentration of the nucleation mode rose up to $10\,000\,\text{cm}^{-3}$. Due to particles growth, the mean number concentration of Aitken mode particles was higher during spring and early summer. The total particle number concentration was higher in spring months and lower in summer months, and the monthly mean concentration varied from about 6000 to $20\,000\,\text{cm}^{-3}$.

Lidar measurements revealed that the top height of the aerosol layer was around 900 m above ground for all seasons,

only slightly higher during the summer months. Frequently, elevated aerosol layers were observed, especially during winter and spring. A mean aerosol optical depth (AOD) of 0.95 was observed for air masses arriving from the North China Plain. In contrast, the mean AOD was only about 0.42 for northerly air masses.

### E9 Air quality and local climate interactions inside and outside Europe

Applying a mix of available technical and non-technical reduction measures of short-lived climate forcing components and air pollutants can give a co-beneficial climate and air quality mitigation. These measures used in several assessments on global and regional scale, e.g. for Europe and the Arctic, gave a 50% reduction in integrated forcing from short-lived climate forcing components by applying maximum feasible reductions while even lower forcing can be reached by less stringent sulphur emission reductions outside Europe.

When stringent air pollution control measures are implemented worldwide, the present-day negative total aerosol top-of-the-atmosphere radiative forcing will be reduced by 50% by 2030. Climate change thereafter will be controlled to a larger extent by changes in greenhouse gas emissions. The net effect of increasing GHG concentrations and lower aerosol concentrations is a global annual mean equilibrium temperature increase of approximately 2.2 K. If additional emission controls are applied only to the industrial sources including power plants but not on the domestic and transportation sectors the predicted temperature increase is 1.9 K. Increasing GHG concentrations alone leads to a temperature response of 1.2 K. As aerosols strongly impact surface forcings the consequences for precipitation increases associated with global warming are even stronger.

By 2100, the response of natural aerosol to changes in climate could cause a direct radiative forcing feedback of up to $1\,\text{Wm}^{-2}$. This feedback includes changes in dust, wildfires, biogenic secondary organic aerosol, and sulphate aerosols formed from marine biota emissions of dimethyl sulphide (DMS) gas. At present there is not enough information to allow an estimate of the indirect radiative effect of these changes in natural aerosols. However, local effects have been estimated, and could be several Watts per square meter. Thus, the response of natural aerosol emissions to changes in climate could have significant effects on local climate and air quality.

Large averaged July $O_3$ changes of +8.9 ppb and -3.5 ppb are predicted for the IPCC A2 and B1 emissions scenarios, respectively, under present-day climate for Europe for 2050. Climate change (IPCC SRES A2 2050s) alone causes July-average $O_3$ increases of up to 2 ppb in western and southern Europe, due largely to increased isoprene emissions.

Substantial fine PM decreases are predicted for the B1 emissions scenario in both summer and winter.
Contrastingly, large localized PM increases are predicted for the A2 emissions scenario due to increases in nitrate, POA and BC, with a strong seasonal and regional dependence. Climate change alone causes small domain-average PM changes, but notable local increases in some PM species due to reduced precipitation and increase in biogenic SOA.

These results highlight the potential impact of future climate change on air pollution and vice versa of air-quality-driven mitigation strategies on climate.

## E10 The impact of aerosols and trace gases on cloud droplet activation, cloud lifetime, and extent (the aerosol indirect effects)

The aerosol indirect effects on climate, i.e. their influence on cloud properties and precipitation, depend on aerosol properties and cloud microphysics as well as on meteorological conditions. Before EUCAARI, the uncertainties related to aerosol properties were similarly high as those related to cloud microphysics and meteorology. By synthesis of EUCAARI project results and related studies, the uncertainty of key parameters in aerosol properties and cloud microphysics could be reduced by about 50% (aerosol particle hygroscopicity, size distribution, number concentration, dilution ratio, effective radius, etc.).

With regard to cloud droplet activation, cloud lifetime, and extent, aerosol properties and cloud microphysics appear now well constrained relative to the uncertainties of meteorological conditions (updraft velocities, spatial inhomogeneity, etc.). In particular, the effective hygroscopicity of aerosol particles, i.e. their ability to absorb water vapour and to form cloud droplets, can be efficiently approximated by a single hygroscopicity parameter (κ). This parameter is easy to calculate from aerosol chemical composition data. EUCAARI extensive observations have been extremely useful to constrain κ values for air mass conditions in Europe. We showed that, on average, it is limited to fairly narrow value ranges for continental and marine boundary layer aerosols (0.3 ± 0.2 vs. 0.7 ± 0.2; Pringle et al., 2010). Thus, the current knowledge of CCN properties can be used as a constraint rather than a tuning parameter in climate models (Heintzenberg and Charlson, 2009).

One of the key questions in current research on air quality – climate interactions are the direct and indirect climate effects of black carbon in carbonaceous combustion aerosols. Reductions in black carbon emissions are often perceived as an attractive global warming mitigation option (e.g. Bond and Sun, 2005; Jacobson, 2010; Kopp and Mauzerall, 2010). However, carbonaceous combustion aerosol can also act as cloud condensation nuclei and thus cool the climate by increasing cloud albedo (Koch et al., 2011). Recent studies suggest that that carbonaceous combustion aerosol accounts for a large portion of the increase in the atmospheric abundance of cloud condensation nuclei since pre-industrial times (Bauer et al., 2010; Spracklen et al., 2011). This aspect must

be considered to ensure that black carbon emissions controls have the desired net effect on climate.

## E11 Interactions between the aerosol cycle, the water cycle, and the biosphere

The precipitation response and thus the hydrological sensitivity differ strongly for greenhouse gas (GHG) forcing and aerosol (AE) forcings. We find a hydrological sensitivity for the GHG simulation of 1.96%/K and 2.81%/K for the AE simulation. As a result the precipitation increase is strongly enhanced when aerosol forcings are considered (e.g. GHG: +0.07 mm d⁻¹; GHG+AE: +0.15 mm d⁻¹). However, expected future air pollution mitigations, as considered in this study, will reverse this. Decreasing aerosol emissions in the future can lead to an even stronger increase in precipitation as can be expected from GHG forcing alone. This effect is estimated to be strengthened by further feedbacks between GHG driven precipitation increase and aerosol wet removal (Iversen et al., 2010). The implied reduced atmospheric residence time of aerosols is estimated larger for the present-day (year 2000) aerosol emissions than it would have been if aerosols were kept at pre-industrial levels. The aerosol cooling effect is thus reduced by the increased GHG, causing reinforcement of the GHG driven global warming.

Changes in climate extremes may have severe implications for food supply and human security. The type, frequency and intensity of extreme events are expected to change as climate changes. In a warmer future climate, there will be an increased risk of more intense, more frequent and longer-lasting heat waves. Summer drying and more intense precipitation in winter is expected as well. This trend might be enhanced by future reduction in aerosol emissions. Aerosols reduce solar insolation and thus cool the surface during daytime and exert a warming effect during nighttime, damping temperature extremes and the diurnal amplitude. Aerosols decrease the evaporation rate and increase the stability in the boundary layer (Paeth and Feichter, 2006). This affects precipitation amount and distribution. In addition, aerosol particles influence cloud microphysics and precipitation formation. As shown by Paeth and Feichter (2006), high aerosol loading damps extreme values of temperature and precipitation, so we expect more extreme conditions if applying stricter air pollution measures and reducing aerosol emissions.

Results were analyzed focusing on extreme values of temperature and precipitation. Indicators for moderate weather extremes have been introduced which take place on larger temporal and spatial scales and are, therefore, suitable for analyses of global model results (Sillmann, 2009). We conducted simulations in which only GHG concentrations are changed or only aerosol emissions are changed to disentangle the importance of both individual forcing agents.
A future reduction of aerosol pollutants results in:

- warmer temperature minima in higher latitudes;

- higher temperature maxima over continents and NH oceans;

- the occurrence of tropical nights extends polewards;

- dry spells decrease slightly in the desert belt, the Sahara and Arabian peninsula, but increase significantly over Amazonia, southern Africa and Australia.

- 5-day precipitation increases in Monsoon regions and higher NH latitudes.

- Wet days decrease over Amazonas region, southern Africa and Australia and increase over Indian and West-African monsoon regions and over high- and mid-latitudes of the NH.

## E12 Aerosol interactions in the Earth System

EUCAARI has advanced our understanding of the interactions and feedbacks in the Earth System, which involve aerosol processes and properties. We have assessed the role of climate change as a driver of changes in anthropogenic aerosols as well as the strength of climate feedbacks involving aerosol species. The uncertainties in these feedbacks have partly been quantified through a multi-model approach and by undertaking the first ever review and synthesis of the available literature covering observational and modeling studies.

Our review of aerosol feedbacks in the Earth system concludes that by 2100, the response of natural aerosol to changes in climate could cause a direct radiative forcing feedback of up to $1 W m^{-2}$ (Carslaw et al., 2010). This feedback includes changes in dust, wildfires, biogenic secondary organic aerosol, and sulphate aerosols formed from marine biota emissions of dimethyl sulphide (DMS) gas. At present there is not enough information to allow an estimate of the indirect radiative effect of these changes in natural aerosols. However, local effects have been estimated, and could be several Watts per square metre. Thus, the response of natural aerosol emissions to changes in climate could have significant effects on local climate.

Advances have been made during the EUCAARI project concerning the impact of changes in marine and terrestrial biogenic emissions. The ECHAM and HadGEM2-ES climate models have been updated and used to simulate the climate response to these changing emissions. The results suggest that any thermostat involving DMS or biogenic volatile organic compound emissions in a future climate is weaker than suggested by previous studies. Although ECHAM and HadGEM2-ES disagree on many aspects of the DMS feedback, both models suggest that DMS emissions respond to climate change in a limited way. Moreover the change in

cloud condensation nucleus concentrations associated with a change in DMS may also be small.

Changes in sea-spray aerosol are likely to occur in regions of sea ice retreat at high northern latitudes. In the Southern Hemisphere the acceleration of wind speeds, due most likely to the appearance of the Antarctic ozone hole, has been predicted in a model to cause large increases in sea spray aerosol production, causing a localized cooling that may have counteracted greenhouse gas-induced warming over the past 2–3 decades. The climate feedback associated with changes in dust emissions remains ambiguous, but is likely to be an important factor in local changes in climate, and possibly in nutrient supply to the ocean biota.

## Appendix F

### EUCAARI Partners

<table><thead><tr><th>Partner</th><th>Country</th></tr></thead><tbody><tr><td>HELSINGIN YLIOPISTO</td><td>Finland</td></tr><tr><td>CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE (CNRS)</td><td>France</td></tr><tr><td>MAX PLANCK GESELLSCHAFT ZUR FOERDERUNG DER WISSENSCHAFTEN E.V.</td><td>Germany</td></tr><tr><td>LEIBNIZ INSTITUT FUER TROPOSPHAERENFORSCHUNG e.V.</td><td>Germany</td></tr><tr><td>CONSIGLIO NAZIONALE DELLE RICERCHE</td><td>Italy</td></tr><tr><td>EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH</td><td>Switzerland</td></tr><tr><td>NEDERLANDSE ORGANISATIE VOOR TOEGEPAST NATUURWETENSCHAPPELIJK ONDERZOEK - TNO</td><td>The Netherlands</td></tr><tr><td>KONINKLIJK NEDERLANDS METEOROLOGISCH INSTITUUT (KNMI)</td><td>The Netherlands</td></tr><tr><td>UNIVERSITY OF LEEDS</td><td>United Kingdom</td></tr><tr><td>LUNDS UNIVERSITET</td><td>Sweden</td></tr><tr><td>PANNON EGYETEM</td><td>Hungary</td></tr><tr><td>ILMATIETEEN LAITOS</td><td>Finland</td></tr><tr><td>European Community represented by the European Commission - Directorate General JRC</td><td>EU</td></tr><tr><td>MET OFFICE</td><td>United Kingdom</td></tr><tr><td>NORSK INSTITUTT FOR LUFTFORSKNING</td><td>Norway</td></tr><tr><td>METEOROLOGISK INSTITUTT</td><td>Norway</td></tr><tr><td>NATIONAL UNIVERSITY OF IRELAND, GALWAY</td><td>Ireland</td></tr><tr><td>PAUL SCHERRER INSTITUT</td><td>Switzerland</td></tr><tr><td>UNIVERSITETET I OSLO</td><td>Norway</td></tr><tr><td>FOUNDATION FOR RESEARCH AND TECHNOLOGY HELLAS</td><td>Greece</td></tr><tr><td>USTAV CHEMICKYCH PROCESU - AKADEMIE VED CESKE REPUBLIKY</td><td>Czech Republic</td></tr><tr><td>CENTRE NATIONAL DE RECHERCHES METEOROLOGIQUES METEOFRANCE</td><td>France</td></tr><tr><td>FORSCHUNGSZENTRUM JUELICH GMBH</td><td>Germany</td></tr><tr><td>NORTH-WEST UNIVERSITY</td><td>South Africa</td></tr><tr><td>THE ENERGY AND RESOURCES INSTITUTE</td><td>India</td></tr><tr><td>KOBENHAVNS UNIVERSITET</td><td>Denmark</td></tr><tr><td>UNIVERSITY OF EAST ANGLIA</td><td>United Kingdom</td></tr><tr><td>ITÄ-SUOMEN YLIOPISTO</td><td>Finland</td></tr><tr><td>THE UNIVERSITY OF MANCHESTER</td><td>United Kingdom</td></tr><tr><td>ASSOCIACAO DOS PESQUISADORES DO EXPERIMENTO DE GRANDE ESCALA DA BIOSFERA-ATMOSFERA NA AMAZONIA - APLBA</td><td>Brazil</td></tr><tr><td>AKTSIAELTS AIREL</td><td>Estonia</td></tr><tr><td>UNIVERSITY OF BIRMINGHAM</td><td>United Kingdom</td></tr><tr><td>DEUTSCHES ZENTRUM FUER LUFT- UND RAUMFAHRT E.V.</td><td>Germany</td></tr><tr><td>UNIVERSITY OF CRETE</td><td>Greece</td></tr><tr><td>THE HEBREW UNIVERSITY OF JERUSALEM</td><td>Israel</td></tr><tr><td>INTERNATIONAL INSTITUTE FOR APPLIED SYSTEM ANALYSIS - IIASA</td><td>Austria</td></tr><tr><td>STOCKHOLMS UNIVERSITET</td><td>Sweden</td></tr><tr><td>UNIWERSYTET WARSZAWSKI</td><td>Poland</td></tr><tr><td>UNIVERSIDADE DE AVEIRO</td><td>Portugal</td></tr><tr><td>TARTU UELIKOOL</td><td>Estonia</td></tr></tbody></table>
JOHANNES GUTENBERG UNIVERSITAET MAINZ
PEKING UNIVERSITY
CHINESE ACADEMY OF METEOROLOGICAL SCIENCES
PANEPISTIMIO AIGAIOU
COMMISSARIAT A L'ENERGIE ATOMIQUE
FORSKNINGSCENTER RISOE
DEUTSCHER WETTERDIENST

Germany
China
China
Greece
France
Denmark
Germany

*Acknowledgements.* Main part of the work in this paper has been funded with FP6 project EUCAARI (Contract 34684). This work was performed in the framework of the Research Infrastructure Action under the FP6 "Structuring the European Research Area" Programme, EUSAAR Contract No. RII3-CT-2006-026140. The financial support by the Academy of Finland Centre of Excellence program (project No. 1118615) is gratefully acknowledged. CNRS and Mét France partners acknowledge the financial support of Agence Nationale de la Recherche under the AEROCLOUDS proposal. This research has received funding from ERC Advanced Grant ATMNUCLE No. 227463.

Edited by: W. T. Sturges

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