<figure><img src="image_9.png" /><figcaption>**Fig. 7.** Possible chemical reaction pathways for the formation of oligomers and other higher-MW products observed in SOA.</figcaption></figure>

It is reasonable to assume that the range of proposed oligomeric species and reaction pathways listed in Table 8 are a direct result of the wide range of VOC oxidation products generated from the different SOA precursors. However, the experimental conditions also play a major role in influencing the chemical pathways. For example, Surratt et al. (2006) showed that SOA generated from the photooxidation of isoprene under low-NOₓ conditions contained organic peroxides (possible peroxyhemiacetals) and hemiacetals as the higher-MW products, whilst under high-NOₓ conditions, oligoesters were identified as the main higher-MW species. Thus, even for the same SOA precursor, changes in NOₓ can significantly influence the types of oligomers formed.

A major problem for the unambiguous identification of the oligomeric products, and hence the unambiguous identification of the chemical processes leading to oligomers, is the lack of reference compounds. Biogenic alkenes, for example, possess complicated structures and the synthesis of potential products, especially larger products (e.g., dimers) or very reactive products (e.g., peroxides), is extremely time consuming and demanding. Recently, the individual dimeric oxidation products (esters) of cyclohexene were synthesized and their mass spectra and retention behavior compared with oligomers formed in chamber experiments (Müller et al., 2008). When reference compounds are not available the application of soft ionization MS/MS techniques can give clues to the chemical nature of the products, however, the fragmentation pathways of even-electron ions (as typically formed with soft ionization) can often be quite similar for different analytes, hence restricting the capability of such studies for structural elucidation. Here the detailed interpretation of EI mass spectra in combination with derivatization GC/MS can be helpful, e.g., in the identification of esters as oligomers

formed from isoprene oxidation under high-NOₓ conditions (Szmigielski et al., 2007a). Obviously, the explicit identification of the other suggested products of acid-catalyzed chemistry (e.g., aldol condensation products) would be extremely valuable for the final evaluation of these SOA formation pathways but again appropriate reference compounds are lacking. Another group of SOA related accretion reaction products which could recently be identified in laboratory and field experiments are organosulfates, as outlined in Sect. 5.1.

Light-induced chemical reactions are another possible formation pathway for oligomers in SOA. A number of species in organic aerosols absorb light in the visible and UVA wavelength range and photosensitized chemical processes leading to a change in the MW distribution of SOA components are possible. However, laboratory investigations into such reactions are just beginning and at the present time, not even preliminary conclusions about their significance can be made. It is also unclear which oligomerization processes take place exclusively in the atmospheric aqueous phase and how far cloud processing of water-soluble organics can explain the formation of higher-MW species. This topic is discussed in more detail in Sect. 5.4.

### 5.2.4 Quantification

Quantification of the relative mass contribution of oligomers to SOA is made difficult by a lack of reference compounds and universal measurement techniques. Nevertheless, for laboratory experiments several estimates have been made which indicate that, depending on the type of precursor, precursor concentrations and duration of the experiments, between 25 and 70% of the SOA mass can be made up of oligomeric products (Gao et al., 2004a, b; Kalberer et al.,
2004; Dommen et al., 2006; Surratt et al., 2006; Hu et al., 2007; Müller et al., 2007). However, many of these estimates were made indirectly, e.g., based on a change of the volatility (increase of the remaining volume fraction after thermal treatment), and are therefore subject to a high level of uncertainty. Considering that the experimental conditions (precursor concentrations, seed aerosols etc.) probably have a major influence on oligomer formation (Chan et al., 2007; Kroll et al., 2007), there is insufficient data for an extrapolation of laboratory data to the ambient atmosphere to be made.

### 5.2.5 Time scale

A further remarkable characteristic is the time scale for oligomer formation. Laboratory studies have shown that at least some of the oligomers are formed quite rapidly (Hoffmann et al., 1998; Heaton et al., 2007). In fact, the chemistry of reactive intermediates, such as peroxides, ozonides or radicals, could be responsible for this observed temporal behavior of oligomer formation. In addition to this almost instantaneous build-up of oligomers, several chamber studies of the chemical composition, volatility and hydroscopicity of SOA indicate that accretion reactions also take place on a longer time scale (vanReken et al., 2005; Gross et al., 2006; Kalberer et al., 2006; Paulsen et al., 2006; Varutbangkul et al., 2006). These somehow contradictory results are probably one reason why no clear picture of oligomerization currently exists, since it indicates the existence of several different chemical pathways which happen on different time scales that lead to a diverse range of higher-MW products – one rapid formation pathway involving reactive intermediates (closed shell or radical intermediates) and one much slower pathway (e.g., involving the reaction of carbonyls, alcohols or acids). While knowledge about the latter processes is essential for the evaluation of the role of oligomerization for organic aerosol aging, the first process could be important for the understanding of new particle formation, both in the laboratory and the field.

It has been demonstrated that the time scale of SOA formation is particularly important for reactive small molecules like glyoxal, for which the rate of aerosol loss directly competes with rapid gas-phase losses. Volkamer et al. (2009) found the rate of SOA formation from glyoxal in a photochemical reaction was enhanced by a factor of 500 compared to a dark reaction system. The SOA formation rate was also strongly dependent on the chemical composition of seed aerosol. Volkamer et al. (2009) concluded that organic photochemical reactions of glyoxal in aerosol water form low volatility products at a rate that can exceed the rate of organosulfate formation; the presence of nucleophiles and sulfuric acid can reduce the rate of SOA formation in the photochemical system compared to that observed in a dark system (see also Table 9).

Obviously the time scale of oligomer formation is also important when repartitioning and the reversibility of oligomer

formation is discussed. Grieshop et al. (2007) observed that SOA from alpha-pinene ozonolysis repartitions reversibly upon dilution, but on a much longer time scale than has been observed in single component aerosols of similar size. It is suggested that the surprisingly slow evaporation rate may be due to mixture effects, mass transfer limitations, or the decomposition of weakly bound oligomers. However the mechanism could not be determined from the experimental data.

### 5.2.6 Theoretical approaches

Several modeling approaches have been developed in which heterogeneous reactions including oligomer formation are treated explicitly. One of the theoretical treatments of oligomer formation involves evaluation of the thermodynamic favorability of their formation from different precursors. Barsanti and Pankow published a series of papers on the thermodynamics of accretion reactions dealing with different monomer functionalities (Barsanti and Pankow, 2004, 2005, 2006), concluding that, for example, accretion reactions involving certain aldehydes and carboxylic acids can be thermodynamically favorable in the condensed phase. The first attempts to include a simplified representation of condensed organic phase accretion reactions (peroxyhemiacetal adduct formation from aromatic VOC oxidation) into detailed chemical models showed a reduced requirement for the otherwise necessary scaling of the physico-chemical parameters (partitioning coefficients) and a better description of the temporal behavior of SOA formation in simulation chambers (Johnson et al., 2005). In addition to providing a better description of chamber data (Capouet et al., 2008), models have also been used to estimate the relative contribution of oligomers to SOA generated from the photooxidation of toluene (Hu et al., 2007) and calculate the most stable oligomeric structures formed from glyoxal (Kua et al., 2008). Another major motivation for the incorporation of particle-phase chemistry is again the evaluation of the influence of particle acidity on SOA formation (Jang et al., 2006a; Pun and Seigneur, 2007). Based on pseudo-first-order approaches, in which the first-order equilibrium constants of the reacting monomers exhibit a semi-empirically derived pH dependence, both studies show that oligomer formation can increase SOA formation by orders of magnitude and consequently conclude that pH is a critical parameter. Condensational growth models have also been used to show qualitatively that even relatively volatile VOC oxidation products can induce condensation growth of aerosols by the formation of non-volatile oligomers (Vesterinen et al., 2007). Certainly all modeling exercises are limited by the incomplete knowledge of the chemistry of oligomer formation. However, theoretical models of gas- and particle-phase processes can provide a framework for the evaluation of laboratory data and allow conclusions to be drawn about the relevance under atmospheric conditions (Chan et al., 2007; Vesterinen et al., 2007; Kroll and Seinfeld, 2008).
<table><caption>Table 9. Summary of laboratory studies of the impact of acidic inorganic sulfates on SOA yields.</caption><thead><tr><th>Precursor (HC)</th><th>Reaction</th><th><sup>a</sup>Seed aerosol</th><th>RH (%)</th><th>Temp (K)</th><th><sup>b</sup>ΔHC/seed</th><th><sup>c,d</sup>Increase in SOA yields (%)</th><th>Reference</th></tr></thead><tbody><tr><td>α-pinene</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=7:3</td><td>15 and 51</td><td>299–302</td><td>not applicable</td><td>+30% at RH=15%<br>+21% at RH=51%<br>unknown</td><td>Czoschke et al. (2003)</td></tr><tr><td>α-pinene</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=7:3</td><td>40</td><td>295–300</td><td>unknown</td><td></td><td>Czoschke et al. (2003)</td></tr><tr><td>α-pinene</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>H<sub>2</sub>SO<sub>4</sub></td><td>41–52</td><td>293</td><td>unknown</td><td>40%</td><td>Inuma et al. (2004)</td></tr><tr><td>α-pinene</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=3:2</td><td>55</td><td>293</td><td>unknown</td><td>+37% (ΔHC=12 ppb)<br>−7% (ΔHC=135 ppb)<br>+10% (with no scavenger)<br>+18% (with 2-butanol)<br>−8% (with cyclohexane)</td><td>Gao et al. (2004b)</td></tr><tr><td>α-pinene</td><td>Ozonolysis</td><td>Na<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=3:2</td><td>45–54</td><td>293–298</td><td>unknown</td><td>+87% (high acid, RH: 13–40%)<br>+71% (mid-acid, RH: 18–42%)<br>+22% (weak acid, RH: 14–61%)<br>(compared to (NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub> at RH> 40%)</td><td>Czoschke and Jang (2006a)</td></tr><tr><td>α-pinene</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=0:1, 3:7 (high); 7:3 (medium), 1:0 (weak)</td><td>Various<br>13–68</td><td>294–302</td><td>3.3–11.8<br>(avg. 6.9)</td><td>+79% without glyoxal<br>(RH: 10–47%)<br>+92% with glyoxal<br>(RH: 10–52%)<br>+37% (avg.)</td><td>Jang et al. (2006a)</td></tr><tr><td>α-pinene</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:<br>H<sub>2</sub>SO<sub>4</sub>=1:1 with and without glyoxal</td><td>Various<br>10–52</td><td>294–301</td><td>2.8–13.2<br>(avg. 6.2)<br>5–16 with glyoxal (avg. 9.2)</td><td></td><td></td></tr><tr><td>α-pinene</td><td>Photooxidation in presence of NO<sub>x</sub></td><td>SO<sub>2</sub> present in gas phase</td><td>30</td><td>298</td><td>27</td><td></td><td>Kleindienst et al. (2006)</td></tr><tr><td>α-pinene</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=3:2</td><td>22–53</td><td>297</td><td>avg. 6.3</td><td>+62% (RH=20%)<br>+69% (RH=40%)<br>+40% (RH=20%)<br>−21% (RH=40%)<br>+36% (RH=20%)<br>+12% (RH=40%)<br>+84% (RH=20%)<br>+16% (RH=40%)<br>+76% (RH=20%)<br>+12% (RH=40%)<br>+12% (RH=40%)<br>+75%</td><td>Northcross and Jang (2007)</td></tr><tr><td>β-pinene</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=3:2</td><td>21–48</td><td>297</td><td>avg. 6.3</td><td></td><td>Northcross and Jang (2007)</td></tr><tr><td>d-limonene</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=3:2</td><td>20–48</td><td>297</td><td>avg. 5.5</td><td></td><td>Northcross and Jang (2007)</td></tr><tr><td>Δ<sup>2</sup>-carene</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=3:2</td><td>21–46</td><td>297</td><td>avg. 2.4</td><td></td><td>Northcross and Jang (2007)</td></tr><tr><td>Terpinolene</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=3:2</td><td>19–46</td><td>297</td><td>avg. 3.9</td><td></td><td>Northcross and Jang (2007)</td></tr><tr><td>Isoprene</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=3:7</td><td>40</td><td>297</td><td>unknown</td><td></td><td>Jang et al. (2002)</td></tr><tr><td>Isoprene</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=3:2</td><td>40</td><td>297</td><td>unknown</td><td>+260%</td><td>Czoschke et al. (2003)</td></tr><tr><td>Isoprene</td><td>Photooxidation in presence of NO<sub>x</sub></td><td>SO<sub>2</sub> present in gas phase</td><td>30</td><td>298</td><td>71.5</td><td>+550%</td><td>Kleindienst et al. (2006)</td></tr><tr><td>Isoprene</td><td>Photooxidation in presence of NO<sub>x</sub></td><td>15 mM (NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub>(neutral)<br>15/15 mM (NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub>/<br>H<sub>2</sub>SO<sub>4</sub>(acidified)</td><td>&lt;9</td><td>293–298</td><td>unknown</td><td>0% (under high-NO<sub>x</sub>)<br>+72% (under low-NO<sub>x</sub>)</td><td>Suratt et al. (2006)</td></tr><tr><td>Isoprene</td><td>Photooxidation in presence of NO<sub>x</sub></td><td>15/15 mM (NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub>/<br>H<sub>2</sub>SO<sub>4</sub>(acidified)<br>0.92 mM H<sub>2</sub>SO<sub>4</sub> (highly acidified)</td><td>30</td><td>302</td><td>unknown</td><td>+33%</td><td>Suratt et al. (2007a, b)</td></tr><tr><td>Acrolein</td><td>Ozonolysis</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=3:7</td><td>40</td><td>297</td><td>unknown</td><td>+18%</td><td>Jang et al. (2002)</td></tr><tr><td>Toluene/ 2-methylbutene</td><td>OH radical induced from ozonolysis of 2-methylbutene</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=17:3 (weak), 7:3 (medium), 1:1 (high)</td><td>Various<br>20–65</td><td>294–297</td><td>2.8–4.9 (dark)<br>2.4–3.0 (light)</td><td>+36%(dark, weak acidic)<br>+60% (dark, medium)<br>+88% (dark, high)<br>+14% (UV light, weak)<br>+35% (UV light, high)</td><td>Cao and Jang (2007)</td></tr><tr><td>Toluene</td><td>Photooxidation using H<sub>2</sub>O<sub>2</sub></td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub></td><td>5</td><td>296–299</td><td>9.5</td><td>No increase</td><td>Ng et al. (2007a)</td></tr><tr><td>Toluene</td><td>Photooxidation in presence of NO<sub>x</sub></td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub></td><td>5</td><td>296–299</td><td>14.8</td><td>−9.8%</td><td>Ng et al. (2007a)</td></tr><tr><td>Toluene</td><td>Photooxidation using H<sub>2</sub>O<sub>2</sub></td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=1:1</td><td>Various<br>17–49</td><td>295–299</td><td>0.2–0.65</td><td>+36% (RH=18%)<br>+25% (RH=48%)<br>+12% (high NO<sub>x</sub>/low NO)</td><td>Cao and Jang (2008)</td></tr><tr><td>Toluene</td><td>Photooxidation in presence of NO<sub>x</sub></td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=1:1</td><td>Various<br>14–43</td><td>295–299</td><td>2.0 (high NO<sub>x</sub>)<br>1.5 (mid NO<sub>x</sub>)</td><td>No increase (high NO<sub>x</sub> and NO)<br>+115% (mid-NO<sub>x</sub>, RH=19%)<br>+44% (NO<sub>x</sub>, RH=40%)<br>+22%(dark, weak)<br>+25% (dark, medium)<br>+47% (dark, high)<br>+24% (UV light, weak)<br>+79% (UV light, high)</td><td>Cao and Jang (2008)</td></tr><tr><td>1,3,5-trimethylbenzene/ 2-methylbutene</td><td>OH radical induced from ozonolysis of 2-methylbutene</td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub>:H<sub>2</sub>SO<sub>4</sub>=17:3 (weak), 7:3 (medium), 1:1 (high)</td><td>Various<br>18–66</td><td>294–297</td><td>4.4–7.0 (dark)<br>4.2–4.8 (light)</td><td>+4.7%</td><td>Cao and Jang (2007)</td></tr><tr><td>m-xylene</td><td>Photooxidation using H<sub>2</sub>O<sub>2</sub></td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub></td><td>4</td><td>297</td><td>17.4</td><td>No increase</td><td>Ng et al. (2007a)</td></tr><tr><td>m-xylene</td><td>Photooxidation in presence of NO<sub>x</sub></td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub></td><td>5</td><td>298</td><td>20</td><td></td><td>Ng et al. (2007a)</td></tr><tr><td>Acetylene</td><td>Photooxidation in presence of NO<sub>x</sub></td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>NH<sub>4</sub>HSO<sub>4</sub></td><td>10–90<sup>e</sup></td><td>298–303</td><td>5–35</td><td>+76%</td><td>Volkamer et al. (2009)</td></tr><tr><td>Acetylene</td><td>Photooxidation in presence of NO<sub>x</sub></td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub>/Fulvic acid</td><td>10–90<sup>e</sup></td><td>298–303</td><td>5–35</td><td>+244%</td><td>Volkamer et al. (2009)</td></tr><tr><td>Acetylene</td><td>Photooxidation in presence of NO<sub>x</sub></td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub>/Fulvic acid/H<sub>2</sub>SO<sub>4</sub></td><td>10–90<sup>e</sup></td><td>298–303</td><td>5–35</td><td>−66%</td><td>Volkamer et al. (2009)</td></tr><tr><td>Acetylene</td><td>Photooxidation in presence of NO<sub>x</sub></td><td>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub><br>(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub>/Fulvic acid/Amino acids</td><td>10–90<sup>e</sup></td><td>298–303</td><td>5–35</td><td>−81%</td><td>Volkamer et al. (2009)</td></tr></tbody></table>

<footnote>a The description of the seed aerosol composition was based on the aqueous inorganic seed solution prior to nebulization of the inorganic solution to the chamber. b The mass ratio of the consumed hydrocarbon (ΔHC) to inorganic seed aerosol (no unit). c The SOA yield is defined as SOA mass/ΔHC. d The increased SOA yield is estimated by (SOA yield with acidic seed – SOA yield with non-acidic seed)/SOA yield with non-acidic seed ×100. e Yield demonstrated to scale with liquid water content; acid effect quantified at a liquid water content of 10 µg m⁻³.</footnote>
### 5.2.7 Atmospheric significance

Although oligomers have been observed in numerous laboratory studies of SOA formation, the relevance of these higher-MW compounds to ambient atmospheric aerosol remains uncertain as the available data appears to be ambiguous. Several studies have detected oligomers in ambient aerosol using off-line mass spectrometry (Baltensperger et al., 2005; Samburova et al., 2005b; Kalberer et al., 2006; Streibel et al., 2006) while Denkenberger et al. (2007) observed oligomers in airborne particles in California using on-line aerosol mass spectrometry. In contrast, oligomers were not detected by LC/(-)ESI-MS analysis of fine organic aerosol collected from the southeastern USA and Europe, although a number of organosulfates/nitrooxy organosulfates, polyacids, and hydroxyacids were identified in the samples (Gao et al., 2006; Iinuma et al., 2007b; Surratt et al., 2007a, 2008; Gómez-González et al., 2008). Clearly, more data is needed before the atmospheric significance of oligomer formation can be assessed. Quantitative information about the amount and relative contribution of these higher-MW compounds to the organic fraction of tropospheric aerosols is also required. The situation is further complicated by the fact that the organic aerosol fraction also undergoes oxidative chemical processing through degradation and chemical modification of the particle-phase constituents by atmospheric oxidants (Rudich et al., 2007). These processes are expected to result in alterations of the physical (volatility, light absorption, light scattering) and physico-chemical properties (water solubility, CCN activity) of atmospheric aerosols and the evaluation of the relative importance of these processes (i.e., oligomerization, oxidative processing, change in hygroscopicity etc.) has to be addressed in future research on organic aerosols.

## 5.3 Interaction of atmospheric organic compounds with sulfuric acid

A number of laboratory studies have shown that atmospheric organics, such as carbonyls, can be transformed to higher-MW products via heterogeneous acid-catalyzed reactions between the gas and particle phases (Jang and Kamens, 2001; Jang et al., 2002, 2003a, b, 2004, 2005; Garland et al., 2006; Liggio and Li, 2006a, b; Iinuma et al., 2007a, b; Surratt et al., 2007a, 2008; Gómez-González et al., 2008). These laboratory studies suggest that heterogeneous acid-catalyzed reactions in the particle phase are important mechanisms for SOA formation and that particle acidity has an impact on SOA yield.

#### 5.3.1 Homogeneous nucleation

There is evidence to suggest that the interaction of sulfuric acid with atmospheric organics is expected to play an important role in the nucleation of new particles in the atmosphere. For example, Zhang et al. (2004) showed co-nucleation of

sulfuric acid and aromatic acids to be a mechanism for forming atmospheric new organic particles. A theory that provides a mechanistic explanation for new particle formation through activation of stable sulfate clusters by organic vapors has also been proposed (Anttila et al., 2004; Kermi nen et al., 2004; Kulmala et al., 2006). It is suggested that the nucleation mechanism involves an activation mode which can initiate spontaneous and rapid growth of clusters through heterogeneous acid-catalyzed reactions and polymerization. Verheggen et al. (2007) observed enhancement of the nucleation rate of sulfuric acid by organic species through empirically determining the nucleation rate of α-pinene SOA in the presence of acidic sulfate aerosol created by SO₂ oxidation. The theoretical study by Nadykto and Yu (2007) also shows that the interaction between sulfuric acid and atmospheric carboxylic acids, such as acetic acid and formic acid, leads to the formation of stable hydrogen-bonded complexes. Citing the recent simulation study using the US EPA's Community Multiscale Air Quality (CMAQ) model for ground-based and aircraft aerosol measurements, Fan et al. (2006) report that the enhanced nucleation effect of secondary condensable organics is important in nucleation when sulfate and organics are abundant.

#### 5.3.2 Laboratory studies of aerosol growth by acid-catalyzed reactions of carbonyls

In order to evaluate the potential importance of carbonyl heterogeneous chemistry and understand the reaction mechanisms of carbonyls in the aerosol phase, a range of carbonyls have been exposed to acidic sulfate either as an acidic film or a pre-existing acidic inorganic seed using either flow reactors (Jang et al., 2003a; Nozière and Riemer, 2003; Zhao et al., 2005, 2006; Nozière et al., 2006) or a Teflon film chamber (Jang and Kamens, 2001; Kroll et al., 2005a). The majority of studies showed that, in general, aldehydes, such as hexanal and octanal, resulted in higher aerosol yields via heterogeneous acid-catalyzed reactions than ketones such as 2-octanone and 2,4-pentanedione (Jang et al., 2003). Specifically, α, β-unsaturated aldehydes (e.g., 2,4-hexadienal and 2-hexenal) and α-oxocarbonyls (e.g., glyoxal) were more reactive than aliphatic carbonyls in heterogeneous reactions (Jang et al., 2003b, 2005). Particle acidity, together with both humidity and inorganic seed aerosol composition, affect the aerosol growth of aldehydes to varying degrees. Overall, the aerosol production via acid-catalyzed reactions appears to be increased at low humidity and when the seed aerosol contains a high fraction of sulfuric acid. Liggio and Li (2006a, b) showed that the reactive uptake of pinonaldehyde, a principal oxidation product of α-pinene, was highly dependent upon the aerosol acidity and did not occur on neutral ammonium sulfate aerosols. Kroll et al. (2005a) also investigated the reactive uptake of a series of small carbonyls onto aqueous seed particles containing ammonium sulfate and mixed ammonium sulfate/sulfuric acid and only found significant
aerosol growth for glyoxal. Furthermore, no major enhance-
ment in particle growth was observed for the acidic seed, sug-
gesting that the large glyoxal uptake was not a result of par-
ticle acidity but rather of ionic strength of the seed. These
results are in contrast to those reported by Jang et al. (2006a)
and further work is clearly required to resolve this discre-
tancy.

The proposed reaction mechanisms for acid-catalyzed re-
actions of aldehydes include hydration, hemiacetal/acetal
formation, trioxane formation, aldol condensation, carboca-
tionic rearrangement, and cross-linking in aerosol media, as
shown in Fig. 7. In the presence of strong acids, further re-
actions of hemiacetals lead to acetals, which are compara-
tively stable and can be isolated by neutralization (Deyrup,
1934). Such hemiacetals/acetals are easily decomposed dur-
ing conventional GC/MS analysis. In a recent study, Garland
et al. (2006) used NMR spectroscopy to characterize the a-
cetal and trioxane resulting from the exposure of hexanal to
submicron sulfuric acid aerosol. In addition to acid-catalyzed
reactions of atmospheric organic compounds, organosulfate
formation has been demonstrated to be an important mecha-
nism in SOA formation, as discussed in Sect. 5.1.

**5.3.3 Laboratory studies of the impact of acidic inorganic sulfate on SOA yields**

A number of laboratory studies have investigated the effects
of acidic inorganic sulfate on the yield of SOA, Table 9. The
majority of studies have focussed on α-pinene and isoprene
and typically show an increase in SOA yield when the seed
aerosol is acidified. Kleindienst et al. (2006) also reported
that the SOA yields from the photooxidation of α-pinene and
isoprene are significantly enhanced in the presence of gas-
phase SO2, which produces acidic aerosol. The effect of rela-
tive humidity and composition of seed aerosol on SOA yields
from the ozonolysis of α-pinene was investigated by Czoschke
and Jang (2006a). Their study showed that higher yields are
obtained when seed composition has either a higher H2SO4
fraction or a higher acidity due to lower relative humidity.
Northcross and Jang (2007) studied SOA formation from
the ozonolysis of various terpenes (α-pinene, β-pinene, Δ³-
carene, terpinolene and d-limonene) in the presence of inor-
ganic seed. The results indicated that the impact of acidity on
SOA yields is also influenced by the molecular structure of
SOA products: for example, oxidation products with multi-
functional carbonyls significantly increase SOA yields in the
presence of acidic sulfate aerosols.

The effects of particle acidity on SOA yields from aro-
matics have received considerably less attention. Ng et
al. (2007a) reported negligible increases in SOA yields from
the photooxidation of toluene and m-xylene in the presence
of acidified sulfate seed aerosol, as shown in Table 9. In con-
trast, recent work by Cao and Jang (2007, 2008) reported that
SOA yields from toluene and 1,3,5-trimethylbenzene were
enhanced by acidified sulfate seed aerosols, not only for ex-

periments without photoirradiation but also for those with
UV-Visible irradiation. A possible explanation for such a
discrepancy between the two laboratories is due to the dif-
ference in available proton concentrations used in the expe-
riments; however, this requires further investigation. Using
a new colorimetric technique for the measurement of parti-
cle acidity, Jang et al. (2008) showed that the acidity of the
submicron acidic sulfate aerosol coated with α-pinene ozone
SOA significantly decreases over time, possibly due to or-
ganic sulfate formation. The mass ratio of organic aerosol to
acidic inorganic seed in the chamber experiments performed
by Cao and Jang (2007, 2008) is nearly one order of mag-
nitude lower than those used by Ng et al. (2007a), i.e., 0.5–
1.0 in the former and 2.5–6.9 in the latter. The mass ratio
of available organic products to acidic sulfates obviously en-
hances heterogeneous acid-catalyzed reactions in aerosol. In
the ambient aerosol, the mass ratios of particle organic car-
bon to inorganic species vary from 0.3 to >1 (Hughes et al.,
1999; Drewnick et al., 2004; Russell et al., 2004; Zhang
et al., 2007a). In addition, the interpretation of acidity ef-
fects on SOA yields should also consider humidity and in-
organic seed compositions, especially the neutralization of
sulfuric acid by ammonia. Table 9 lists the mass ratio of the
consumed hydrocarbon (ΔHC) to inorganic seed along with
relative humidity and seed composition. These parameters
have recently been incorporated into a SOA model and cou-
pled with inorganic and organic thermodynamic parameters
(Jang et al., 2006a; Pun and Seigneur, 2007). However, or-
ganic acidity generated in the same photochemical process
by which SOA is formed may be sufficient to catalyze these
heterogeneous reactions. Takahama et al. (2006) reported
from the Pittsburgh Air Quality Study that they were not able
to detect significant enhancements of SOA production due to
inorganic acidity in Western Pennsylvania most of the time.

**5.3.4 Effects of particle acidity on partitioning of semivolatile organic compounds**

Particle acidity may also affect gas-particle partitioning
by the formation of higher-MW products in aerosols.
Cao (2008) showed that the gas-particle partitioning co-
efficients for deuterated alkanes (d40-nonadecane and d42-
eicosane) on acidic SOA were considerably lower than those
for neutral SOA. The oligomeric matter in aerosol can in-
crease the activity coefficient of hydrophobic semivolatile
compounds and also the average MW of organic matter in
aerosol, thus leading to less favorable partitioning of alka-
nes to SOA. A similar effect has been observed in outdoor
simulation chamber experiments (Lee et al., 2004) where
SOA produced from the photooxidation of α-pinene in the
presence of pre-existing diesel soot induces the off-gassing
of long-chain surrogate deuterated alkanes (d40-nonadecane
and d42-eicosane), by significantly reducing their partition-
ing coefficients. The partitioning coefficients of deuterated
long-chain alkanes decrease by one order of magnitude as
diesel exhaust is photochemically aged both with and without α-pinene. Such studies imply that aging of ambient aerosols can enrich highly oxidized and oligomerized organic species by atmospheric oxidation as well as off-gassing of hydrophobic compounds. However, the concentrations of the latter could also be reduced by reactions in the aerosol phase and should be the subject of future investigations.

## 5.4 Chemical and photochemical processing of organics in the atmospheric aqueous phase

A number of studies have been performed on the chemical processing of organic compounds in the atmospheric aqueous phase (i.e., rain, clouds, fogs and aqueous aerosol particles), in order to determine their impact on atmospheric chemistry. They have shown that the aqueous phase processing of organics yields products with lower volatility than those obtained from analogous gas phase reactions. Aqueous phase processes are, therefore, potentially important sources of higher-MW compounds and may contribute to the formation of organic matter in the particle phase. It was suggested that SOA can be produced through cloud and fog processing of carbonyls, monocarboxylic acids, alcohols and organic peroxides to form dicarboxylic acids, functionalized acids, functionalized carbonyls, esters, polyols, amines, amino acids, and organosulfur compounds. Subsequently, a number of studies have been performed on the transformation of various oxygenated organic species in the aqueous phase and at its interface in order to elucidate the key processes and mechanisms involved (Blando and Turpin, 2000; Warneck, 2003; Ervens et al., 2004a, b, 2008; Herrmann et al., 2005; Altieri et al., 2006, 2008, 2009; Carlton et al., 2006; Lim et al., 2005; Poulain et al., 2007; Tilgner et al., 2008; El Haddad et al., 2009; Liu et al., 2009).

### 5.4.1 Aqueous phase oxidation of organic compounds

A number of field studies have shown that the high amount of organic acids (such as oxalic, malonic, malic, succinic, glutaric, formic and acetic acids) found in atmospheric waters and aerosols originate from aqueous phase processes (Legrand et al., 2003, 2005, 2007; Yao et al., 2003; Crahhan et al., 2004; Yu et al., 2005; Sorooshian et al., 2007b). It has also been suggested that in-cloud biological activity is an important process (Yao et al., 2003; Amato et al., 2005), but its contribution has not yet been quantified. A larger number of studies have focused on the aqueous phase chemistry. The processing of organic compounds in atmospheric waters can be initiated by numerous oxidizing radicals, including OH, NO₃, HO₂, and also radical anions such as O₂⁻, Cl₂⁻, Br₂⁻, SO₄⁻, and finally, non-radical reactants such as ozone and H₂O₂. The OH radical is one of the major sinks for organic compounds, and its presence in atmospheric waters has been confirmed in numerous studies (e.g., Faust and Allen, 1993; Arakaki and Faust, 1998; Anastasio and McGregor,

2001; Arakaki et al., 2006). The major sources for aqueous phase OH radicals are highly dependent on the surrounding air masses (Herrmann et al., 2000; Deguillaume et al., 2004). For the anthropogenically influenced boundary layer, due to the significant presence of HONO, Anastasio and McGregor (2001) showed that nitrite photolysis in the aqueous phase was a major source of OH compared to other sources, including gas-to-droplet partitioning,

$$NO_2^- + H_2O + h\nu(\lambda < 400 \text{ nm}) \rightarrow OH + NO + OH^- \quad (6)$$

However, for clouds in the free troposphere this formation pathway is of minor importance compared to the aqueous phase photolysis of nitrate ions (Arakaki et al., 2006)

$$NO_3^- + H_2O + h\nu(\lambda < 355 \text{ nm}) \rightarrow OH + NO_2 + OH^- \quad (7)$$

the photo-Fenton reaction (at pH≤4), which is a photochemical cycle (Arakaki and Faust, 1998)

$$FeOH^{2+} + h\nu(\lambda < 370 \text{ nm}) \rightarrow OH + Fe^{2+} \quad (8)$$

$$Fe^{2+} + H_2O_2 \rightarrow OH + FeOH^{2+} \quad (9)$$

and, to a lesser extent, the aqueous phase photolysis of H₂O₂ (Arakaki and Faust, 1998; Parazols et al., 2006)

$$H_2O_2 + (\lambda < 320 \text{ nm}) \rightarrow 2OH \quad (10)$$

Experimental and theoretical studies confirm that dissolved organic compounds play a major role in the cycling of OH radicals to HO₂/O₂⁻ radicals and/or H₂O₂ (Lelieveld and Crutzen, 1990; Arakaki and Faust, 1998; Monod and Carlier, 1999; Blando and Turpin, 2000; Herrmann et al., 2000, 2005; Anastasio and McGregor, 2001; Herrmann, 2003; Deguillaume et al., 2004; Ervens et al., 2003a, 2004a; Arakaki et al., 2006; and references therein).

The kinetics of the oxidation of more than 100 organic compounds by different radicals and anions (OH, NO₃, Cl, Cl₂⁻, Br₂⁻, SO₄⁻; CO₃⁻) have been extensively studied in the aqueous phase. The reviews by Buxton et al. (1988) and Herrmann (2003) have confirmed that the OH radical is the most efficient oxidizing agent under atmospheric conditions. Arguing that the ionic strength can vary widely from rain drops and cloud/fog droplets to deliquescent aerosols, Herrmann (2003) showed that the ionic strength has a significant effect on the oxidation rate constants and depends on different parameters such as the type of salt, the oxidizing radical, and the chemical structure of organics. However, very few studies have investigated this effect, although it should be an important parameter for oligomerization. The aqueous phase oxidation of organic compounds has mainly been investigated at 298 K, which is not relevant to the temperatures encountered in cloud/fog waters, and only a limited number of studies have explored the temperature dependence of the rate constants for reaction of OH with organic compounds at low ionic strength, representative of cloud/fog droplets (Chin and Wine, 1994; Buxton et al., 1997; Ervens
et al., 2003b; Gligorovski and Herrmann, 2004; Monod et al., 2005; Poulain et al., 2007; Gligorovski et al., 2009). Based on these studies, structure activity relationships have been proposed to predict rate constants for the reaction of OH radicals with organic compounds at 298 K (Gligorovski and Herrmann, 2004; Monod et al., 2005; Monod and Doussin, 2008; Morozov et al., 2008; Gligorovski et al., 2009). Nevertheless, many aqueous phase oxidation reactions have yet to be investigated, especially for non-aliphatic compounds, and therefore are not considered in current models. This results in large uncertainties in the contribution of aqueous phase oxidation processes to organic matter.

A number of laboratory studies have investigated the reaction products and mechanisms of aqueous phase oxidation of a number of organic compounds. Although most of these were aimed at studying water treatment methods, or the behavior of sugars in living cells, a few were carried out under atmospheric conditions, i.e., at pH≤7, O₂ saturated, under UV-visible irradiation (>290 nm), and at concentrations relevant to the atmosphere. Not surprisingly, most of these studies revealed that all precursors are transformed more or less directly into carboxylic acids (Table 10). Apart from gaseous CO₂, formic, acetic and oxalic acids appear to be the most often encountered end products, in good agreement with field observations. Some studies also showed the importance of intermediate compounds, such as hydroperoxides (Schuchmann and von Sonntag, 1982, 1988; Schuchmann et al., 1989, 1990; Zuo and Hoigné, 1992; Stemmler et al., 2000a, b; Chevallier et al., 2004; Monod et al., 2007; Poulain et al., 2007), which have been scarcely measured in atmospheric waters (Sauer et al., 1996), despite their importance in tropospheric chemistry (Reeves and Penkett, 2003).

A number of photochemical studies observed the formation of higher-MW organic compounds (called here oligomers) in the aqueous phase and are summarized in Table 10. These observations indicate that photochemical processing of organics followed by cloud/fog evaporation is a possible pathway for SOA formation. As shown in Table 10, it appears that oligomers are only formed from complex precursors, i.e., ≥C₂ polyfunctional compounds. However, further studies are needed to confirm this, as other parameters can be of importance for oligomerization, such as the presence of transition metal ions (TMI). In the studies of Gelenscér et al. (2003) and Hoffer et al. (2004), the presence of transition metals may have influenced the formation of light absorbing species that were assimilated to oligomers.

The role of transition metals is complex. Iron is the most ubiquitous transition metal in atmospheric waters (Deguil-laume et al., 2005), and its photochemical reactivity has been shown to significantly influence the reactivity of organic compounds. Ionic forms of iron and copper increase the amount of hydroperoxides formed from the OH oxidation of 2-butoxyethanol (Stemmler et al., 2000b); the presence of FeII in aqueous solutions enhances the decomposition of methyl- and ethyl-hydroperoxides (Chevallier et al.,

2004); the organic acids-FeIII complexes catalyze the photochemical decomposition of oxalic, glyoxalic and pyruvic acids (Zuo and Hoigné, 1994). The formation of organic-iron complexes is likely the reason for the light absorbing species observed by Gelenscér et al. (2003) and Hoffer et al. (2004) during the OH-initiated oxidation of 3,5-dihydroxybenzoic acid. Finally, Parazols et al. (2006) suggested that organic-iron complexes present in clouds may inhibit, under specific environmental circumstances, the natural Fenton reaction to produce OH radicals.

Table 10 shows that the number of investigations is limited, and almost none of the studied reactions were duplicated by different groups, except for the OH-initiated oxidation of glyoxal and direct photolysis of pyruvic acid. A reasonable agreement was obtained for the reaction products of OH oxidation of glyoxal using two very different techniques (Buxton et al., 1997; Carlton et al., 2007). Studying the photolysis of pyruvic acid with very different techniques, Guzmán et al. (2006) and Altieri et al. (2006) both obtained oligomers, but the proposed structures of the products were different, as well as the possible mechanisms explaining their formation. This highlights the need for further experimental work employing a variety of different techniques to identify oligomers and their formation mechanisms.

In general, two different kinds of mechanisms are proposed to explain the formation of oligomers in the aqueous phase; (i) acid catalyzed chemical processes (as described in Sect. 5.2), and (ii) radical processes. Loeffler et al. (2006) observed hemiacetal/acetal formation from semi-hydrated glyoxal and methylglyoxal and showed that acids have little effect on the oligomerization of glyoxal, but bases interrupt oligomer formation by catalyzing glyoxal hydration and disproportionation to glycolic acid. Holmes and Petrucci (2006) showed that oligomers up to 1458 Da were obtained from acid catalyzed processes such as hydration, hemiacetal/acetal formation, aldol condensation, and polymerization from levoglucosan in the aqueous phase. Studying the photolysis of pyruvic acid and the OH oxidation of methylglyoxal, Altieri et al. (2006, 2008) showed the formation of similar oligomers (up to 600 Da). This was explained by the fact that the oxidation of methylglyoxal leads to pyruvic acid and other acids that were also observed during the photolysis of pyruvic acid. A detailed study of the oligomeric structure showed the repeated contribution of a monomer C₃H₄O₂, which was attributed to hydroxyacrylic acid. Altieri et al. (2008) proposed acid catalyzed esterification involving the addition of hydroxyacrylic acid to each organic acid formed photochemically to explain the observed oligomers.

Alternatively, there is evidence that radical processes may also contribute to the formation of oligomers in the aqueous phase. Guzmán et al. (2006) reported that the photolysis of pyruvic acid leads to the formation of dimers and trimers from combination reactions of the nascent alkyl radicals (Fig. 8), even under oxygen concentrations relevant to those of the atmosphere.
<table><caption>**Table 10.** A summary of aqueous phase oxidation processes that result in oligomer formation.</caption><thead><tr><th rowspan="2">Reaction</th><th colspan="3">Conditions<sup>a</sup></th><th rowspan="2">pH</th><th rowspan="2">Primary and secondary products</th><th rowspan="2">Reaction products<sup>b</sup><br>oligomers</th><th rowspan="2">Reference</th></tr><tr><th>Radical generation</th><th>[organic]<sub>0</sub><br>(mM)</th><th>pH</th></tr></thead><tbody><tr><td>Pyruvic acid+h<sub>ν</sub><sup>c</sup></td><td>—</td><td>5–100</td><td>1.0<sup>d</sup></td><td>CO<sub>2</sub>g</td><td></td><td>Dimers and trimers observed<br>by UV-VIS spectroscopy</td><td>Guzmán et al. (2006)</td></tr><tr><td>Pyruvic acid+h<sub>ν</sub></td><td>—</td><td>5 and 10</td><td>2.7–3.1</td><td></td><td></td><td>Observed by LC/ESI-MS<br>(up to 400 Da)</td><td>Altieri et al. (2006)</td></tr><tr><td>Methylglyoxal+OH</td><td>H<sub>2</sub>O<sub>2</sub>+h<sub>ν</sub></td><td>2</td><td>4.2–4.5<sup>f</sup></td><td>Pyruvic, glyoxylic, formic,<br>acetic and oxalic acids</td><td></td><td>Observed by LC/ESI-MS and<br>FT-ICR-MS (up to 600 Da)</td><td>Altieri et al. (2008)</td></tr><tr><td>Glyoxal+OH</td><td>H<sub>2</sub>O<sub>2</sub>+h<sub>ν</sub></td><td>2</td><td>4.1–4.8<sup>f</sup></td><td>glyoxylic and formic<br>acids, oxalic acids</td><td></td><td>Observed by LC/ESI-MS<br>(up to 600 Da)</td><td>Carlton et al. (2007)</td></tr><tr><td>Glyoxal+OH</td><td>Pulse radiolysis<sup>e</sup></td><td>1</td><td>2.0–6.0</td><td>glyoxylic acid, H<sub>2</sub>O<sub>2</sub></td><td></td><td>Not measured</td><td>Buxton et al. (1997)</td></tr><tr><td>Methacrolein+OH</td><td>H<sub>2</sub>O<sub>2</sub>+h<sub>ν</sub><sup>g</sup></td><td>0.4 and 5</td><td>4.5–5.6<sup>f</sup></td><td>Methylglyoxal, formaldehyde,<br>hydroxyacetone, methacrylic<br>and acetic acids, pyruvic,<br>glyoxylic, and oxalic acids</td><td></td><td>Observed by LC/ESI-MS<br>(up to 400 Da)</td><td>Liu et al. (2009),<br>El Haddad et al. (2009)</td></tr><tr><td>Pyruvic acid+OH</td><td>H<sub>2</sub>O<sub>2</sub>+h<sub>ν</sub><sup>h</sup></td><td>5 and 10</td><td>2.7–3.1</td><td>Glyoxylic acid, acetic<br>acid, oxalic acids</td><td>4-methylcatechol</td><td>Observed by LC/ESI-MS<br>(up to 500 Da)</td><td>Carlton et al. (2006),<br>Altieri et al. (2006)</td></tr><tr><td>P-methylphenol+OH/NO<sub>3</sub></td><td>Laser Flash Photolysis</td><td>0.002</td><td>0.5</td><td></td><td></td><td>Dimers and trimers<br>Observed by SPE-LC/MS</td><td>Hoffmann (2007)</td></tr><tr><td>N-methylpyrrolidone+OH</td><td>H<sub>2</sub>O<sub>2</sub>+h<sub>ν</sub><sup>i</sup></td><td>0.5</td><td>Free<sup>f</sup></td><td>N-Methylsuccinimide,<br>5-hydroxy-N-methylpyrrolidone,<br>formylpyrrolidone,<br>N-hydroxymethylpyrrolidone,<br>2-pyrrolidone,<br>methylamine,<br>acetamide,<br>N-methylformamide,<br>NHPMP,<br>2-hydroxy-N-methylsuccinimide,<br>formamide,<br>N-methylacetamide,<br>dimethylacetamide,<br>butanoic acid</td><td></td><td>Observed by LC/ESI-MS<br>(up to 300 Da)</td><td>Poulain et al. (2007)</td></tr><tr><td>3,5-dihydroxybenzoic<br>acid+OH</td><td>Fenton<sup>j</sup></td><td>0.02</td><td>4.5<sup>k</sup></td><td>Not measured</td><td></td><td>Observed by UV-VIS spectroscopy</td><td>Gelencsér et al. (2003),<br>Hoffer et al. (2004)</td></tr><tr><td>Levoglucosan</td><td>Fenton<sup>j</sup></td><td>1</td><td>4.5<sup>k</sup></td><td>D-glucose</td><td></td><td>Observed by MALDI/TOF-MS and<br>ATR-FTIR (up to 1458 Da)</td><td>Holmes and Petrucci<br>(2006)</td></tr></tbody></table>

<sup>a</sup> Unless specified, all the studies were carried out in steady state photochemical experiments, under aerated conditions, at 25°C. [organic]<sub>0</sub> = initial organic concentrations. <sup>b</sup> For simplification, only non-hydrated forms are noted (although formaldehyde is totally hydrated in the aqueous phase), and only neutral forms of the acids are noted (although their forms depend on pH and pK<sub>a</sub>). <sup>c</sup> Photolysis at λ=313 and 320 nm, at 20°C. <sup>d</sup> Buffered with perchloric acid. <sup>e</sup> Pulse radiolysis in N<sub>2</sub>O/O<sub>2</sub> aqueous solutions. <sup>f</sup> Unbuffered solutions. <sup>g</sup> Photolysis using simulated solar spectrum at λ>300 nm. <sup>h</sup> Photolysis at λ=254 nm. <sup>i</sup> Photolysis using spectrum λ>250 nm. <sup>j</sup> Fenton reaction was operated using 0.1 and 0.005 mM of H<sub>2</sub>O<sub>2</sub> and FeCl<sub>3</sub> respectively. <sup>k</sup> Buffered with sulfuric acid.

Dimers and trimers were observed by Hoffmann (2007) during the OH-oxidation of p-methylphenol (Table 10). This can be explained by the fact that phenoxy radicals formed during H-abstraction or addition of OH radicals to phenolic compounds are stabilized by mesomeric effects, their reactivity towards O<sub>2</sub> is very low, and the recombination of two radicals (Fig. 9) is possible (von Sonntag and Schuchmann, 1997).

Liu et al. (2009) also suggested that oligomers produced during the OH-initiated oxidation of methacrolein were formed via organic radical processes. Furthermore, Michaud et al. (2009) evaporated droplets containing oligomers derived from photooxidized methacrolein and obtained significant amounts of stable organic aerosols. These experiments

showed for the first time that oligomers formed in the aqueous phase can result in SOA under atmospheric conditions, and that the resulting SOA has properties slightly different from those obtained from the gas-phase photooxidation of biogenic compounds (Michaud et al., 2009).

Aqueous phase photochemistry may lead to the formation of polyfunctional organic compounds in diluted droplets, which play an important role in condensation reactions leading to oligomers and SOA when the organic concentrations increase during cloud evaporation. However, the scientific knowledge of photochemical processes of organics, and especially polyfunctional compounds, in the atmospheric aqueous phases is still quite limited and needs further investigation.
## 5.4.2 Gas-liquid interactions leading to SOA production

Processes at the air-water interface can play a key role in the uptake and reactions of atmospheric gases with liquid droplets. Atmospheric species may react at the interface without actually being taken up into the bulk (Finlayson-Pitts and Pitts, 2000). The uptake and oxidation of SO₂ cannot be explained by liquid-phase chemistry alone (Jayne et al., 1990; Donaldson, et al., 1995; Finlayson-Pitts and Pitts, 2000; Knipping et al., 2000) and it proceeds via the formation of a bound complex at the air-water interface (Jayne et al., 1990; Donaldson et al., 1995; Finlayson-Pitts and Pitts, 2000). Similarly, the atmospheric uptake of acetaldehyde (Jayne et al., 1992; Davidovits et al., 1995) and glyoxal (Schweitzer et al., 1998) cannot be described solely by liquid-phase chemistry and are best explained in terms of enhanced reactivity at the gas-liquid interface.

In particular, the presence of light has recently been shown to enhance the reactivity at the gas-liquid interface. George et al. (2005) studied the effect of light (in the range 300–500 nm) on the uptake kinetics of NO₂ on various surfaces taken as proxies for organic surfaces encountered in the troposphere. Based on these experiments a mechanism was suggested, in which photosensitized electron transfer is occurring. This photoenhancement is stronger on humic acids, on which the light-activated reduction of NO₂ was observed to be a major source of gaseous HONO (Stemmler et al., 2006). Soil and other humic acid containing surfaces exhibit a hitherto unaccounted organic surface photochemistry in producing reductive surface species which react selectively with NO₂. The interactions of aerosols consisting of humic acids with gaseous NO₂ were also investigated under different light conditions in aerosol flow tube experiments at ambient pressure and temperature. The results show that NO₂ is also converted on the humic acid aerosol into HONO, and that this reaction produces volatile products from the aerosol that can be detected in the gas phase at the reactor exit. The formation of HONO on the humic acid aerosol is strongly activated by light.

Similarly, a significant photoenhancement of the uptake of ozone on benzophenone and phenol solid films was also observed under simulated atmospheric conditions with respect to relative humidity, pressure, temperature and O₃ concentration using a coated flow tube reactor (Jammoul et al., 2008). As a consequence of the photoenhanced heterogeneous chemistry, the contact angle increased, showing an increase of the organic film hydrophobicity for the benzophenone-phenol mixture upon combined exposure to light and ozone along with the appearance of a new absorption band up to 450 nm. Appearance (or red-shifting) of UV-visible features during SOA formation and aging was also observed during the processing of particles obtained by the oxidation of limonene where solar radiation may play a significant role in the processing of SOA in the atmosphere (Walser et al., 2007, 2008). Light absorbing

oligomers were also observed from the aldol condensation of carbonyls in sulfuric acid solutions (Nozière and Esteve, 2005, 2007). Amino acid- and ammonium sulfate-catalyzed reactions in water and ionic solutions were also suggested to produce light-absorbing “humic-like” compounds (Nozière et al., 2007).

## 5.4.3 Evaluation of the importance of in-cloud processed SOA

A number of models have been used to investigate multiphase organic chemistry, including gas- and aqueous-phase photochemistry and gas/aqueous phase transfer. In good agreement with field studies, simulating several evaporation-condensation cycles, these multiphase models showed that, compared to cloudless conditions, significant additional amounts of SOA containing carboxylic acids are formed after the cloud dissipates. For example, Warneck (2003, 2005) proposed that oxalic acid, present in aerosols in the remote marine atmosphere (in particular Central Pacific Ocean), mainly originates from multiphase photooxidation of ethane, ethene and acetylene. This source of oxalic acid includes gas phase photooxidation of the VOCs, followed by gas/aqueous phase transfer of the oxygenated products (glyoxal, glycolaldehyde) in cloud droplets, which then are photooxidized in the aqueous phase, leading to oxalic acid, which remains in the condensed phase after cloud evaporation, thus forming SOA. Due to the absence of other sources in the remote marine atmosphere, SOA formation from in-cloud processing may be the only pathway for oxalic acid occurrence in aerosols at such sites (Warneck, 2003, 2005). In the same way, simulating sulfate and organic multiphase chemistry (up to C₆) through several cloud processing cycles (up to 8 cycles), Ervens et al. (2004a) showed that significant amounts of SOA containing sulfate and organic acids are formed after the cloud dissipates. In both clean and polluted atmospheres, oxalic, glutaric, adipic, and pyruvic acids are the main contributors to the organic acid fraction of the aerosol mass. In agreement with observations, the oxalate fraction in processed particles exceeds the fractions of other dicarboxylic acids since it represents an end product in the oxidation of several organic gas phase species. The study suggests that cloud processing may act as a significant source of small functionalized mono- and dicarboxylic acids, some fraction of which can be retained in the aerosol phase following droplet evaporation.

Gelencsér and Varga (2005) and Chen et al. (2007) investigated the multiphase behavior of organic compounds up to C₁₀ polyfunctional compounds. Gelencsér and Varga (2005) determined an aerosol yield parameter for multiphase SOA formation as a function of the Henry's Law constant and found that the SOA yield is significant above H=1000 M atm⁻¹. Among the potential precursors for this process are oxygenated compounds such as primary oxidation products of biogenic and anthropogenic hydrocarbons,
<figure><img src="image_10.png" /><figcaption>**Fig. 8.** Radical processes explaining the formation of oligomers during the photolysis of pyruvic acid in the aqueous phase under atmospheric conditions (Guzmán et al., 2006). PA = pyruvic acid; ISC = intersystem crossing; K· = ketyl radical; A = 2,3-dimethyltartaric acid; D = multifunctional dicarboxylic acid. The rapid decarboxylation of D may form two products, B1 and B2.</figcaption></figure>

including, for example, pinonaldehyde. Multiphase SOA
formation was found to be less efficient than in-cloud sul-
fate production per unit mass concentration of the precur-
sor. However, considering the vast amounts of VOCs that
are emitted by vegetation and oxidized in the troposphere,
in-cloud SOA formation may significantly contribute to at-
mospheric SOA production on a global scale (Gelencsér and
Varga, 2005). Chen et al. (2007) applied 0-D and 3-D models
which both showed a significant increase of SOA formation
when the aqueous-phase organic chemistry in clouds is con-
sidered. A 27% increase was obtained using the 0-D model
in a rural scenario with strong monoterpene emissions. Over-
all, this study suggests that SOA formation due to aqueous-
phase organic chemistry in clouds could be important at loca-
tions that are strongly influenced by monoterpene emissions.
However, key limitations of this study were the simple treat-
ment of organic reactions in the aqueous phase for organic
compounds of carbon number greater than four (only based
on their phase transfer). Another limitation was the lack
of treatment of aqueous phase oligomerization processes for
both biogenic and anthropogenic compounds. This should
therefore amplify the importance of SOA formation due to
aqueous-phase organic chemistry in clouds.

<figure><img src="image_11.png" /><figcaption>**Fig. 9.** Formation of dimers by recombination of two phenoxyl radicals during the OH-initiated oxidation of phenolic compounds (von Sonntag and Schuchmann, 1997).</figcaption></figure>

Lim et al. (2005) and Ervens et al. (2008) investigated the
multiphase behavior of isoprene. Lim et al. (2005) studied
cloud processing of isoprene in an air parcel transported for
5 days over the tropical Amazon, followed by 5 days over
the Atlantic Ocean where cloud and cloudless periods alter-
nated. Following each cloud period, aqueous-phase species
continued evaporating from cloud droplets. In particular, the
low volatility organic acids (i.e., glycolic, pyruvic, glyoxylic,
and oxalic acid) remained in the aerosol phase during the
cloudless period. Under these conditions, Lim et al. (2005)
found that the contribution of cloud processing to the global
SOA budget is considerable, with an important contribution
of oxalic acid, in good agreement with observations. By tak-
ing into account the SOA yields obtained in the model, a
global isoprene emission flux of 500 Tg/yr results in an SOA
source strength from cloud processing of 1.6 Tg/yr, which is a significant contribution to global biogenic SOA, as described in Sect. 2.1. Moreover, Fu et al. (2008) calculated the global source of SOA from the irreversible uptake of dicarbonyls (glyoxal and methylglyoxal), yielding contributions of 11 Tg C/yr, including 2.6 Tg C/yr from glyoxal and 8 Tg C/yr from methylglyoxal whereas 90% of this source takes place in clouds.

Ervens et al. (2008) developed a parcel model where an exhaustive multiphase chemical mechanism was complemented by the oligomer formation from glyoxal described by Altieri et al. (2006) and Carlton et al. (2006, 2007). It was shown that substantial amounts of SOA were formed from isoprene through in-cloud processes. Sensitivity tests of liquid water content, cloud contact-time, aerosol/droplet number concentration, pH, and gas-particle partitioning of semivolatile organics showed that the NOₓ levels are most influential in the control of the carbon yield of the in-cloud processed SOA. Ervens et al. (2008) concluded that in regions with high NOₓ and isoprene emissions, together with abundant clouds (e.g., Northeastern US or Southeast Asia) the additional SOA formed through in-cloud processes might significantly contribute to SOA. However, the authors only considered the oligomer formation from glyoxal. Other potential oligomerization processes from polyfunctional compounds such as pyruvic acid (Guzmán et al., 2006; Altieri et al., 2008), or methacrolein (El Haddad et al., 2009; Liu et al., 2009) were not considered. This should result in an underestimation of the total SOA formed. Furthermore, the model calculations by Ervens et al. (2008) did not take into account the photochemical degradation of diacids and particularly oxalate and its complexes with TMI (Deguillaume et al., 2005), and therefore, probably overestimate the SOA formation.

Despite large uncertainties, the above mentioned models indicate that in-cloud aqueous phase processes of organics are probably largely contributing to the global sources of SOA. Photochemical reactions play an important role in the processing of organics. However, the scientific knowledge of photochemical processes of organics in the atmospheric aqueous phases and at the surface of droplets and aerosols is still quite limited and needs further investigations. In particular, the radical photochemistry occurring at the surface and in the bulk diluted aqueous solutions should be further studied for polyfunctional organic compounds. Special attention should be paid to radical photochemistry occurring in concentrated media where the activity coefficients are different from unity, in order to simulate the conditions of evaporating droplets and/or deliquescent aerosols. The influence of parameters relevant to the atmosphere such as pH, TMI content and ionic strength, which are likely to be highly variable in the atmospheric aqueous phases and greatly affect oligomerization processes, should also be examined.

## 5.5 Aerosol formation from real plant emissions

The importance of BSOA is discussed in Sect. 2 and has been further demonstrated in several studies (Szidat et al., 2006; Lanz et al., 2007; Simpson et al., 2007; Schichtel et al., 2008) which reported that up to 90% of the total SOA in many regions of the European continent during summer months originates from biogenic sources. Long-term studies in the boreal forests in Finland show that biogenic oxidation products aid the formation of new particles and thus contribute not only to atmospheric particle mass but also to atmospheric particle number (O'Dowd et al., 2002). Similarly, in coastal regions biogenic organo-iodine compounds and biogenic iodine emissions contribute significantly to new particle formation (O'Dowd et al., 2002; Laaksonen et al., 2008). Kerminen et al. (2005) estimated that new particle formation over boreal forests could currently exert a cooling of 0.2–0.9 W m⁻² via the effect on cloud formation. Increase of tree emissions under conditions of rising temperature and CO₂ concentrations and subsequent enhanced particle formation, could thus constitute an important negative feedback of vegetation on climate change via the direct and indirect effects of aerosols (Kulmala et al., 2004). Using a vegetation model Lathiere et al. (2005) predicted the future expansion of boreal and temperate forests that may lead to an increase of monoterpene emissions by a factor of 1.5. Based on the same vegetation scenario, Tsigaridis and Kanakidou (2007) predict an increase of the future biogenic SOA burden of 0.94 Tg, i.e., the same order of magnitude as the present anthropogenic sulfate burden. The effects of climate change on vegetation emissions and biogenic SOA formation of these model studies would be in accordance with the negative feedback hypothesis of Kulmala et al. (2004). Nevertheless, large uncertainties in the SOA source strength and the tendency to strongly underestimate SOA concentration in many recent model studies point to a severe lack in the understanding of biogenic SOA sources, despite its obvious importance for climate issues (Kanakidou et al., 2005 and references therein; Fuzzi et al., 2006).

The oxidation of a single monoterpene like α-pinene leads to a complex mixture of long-chain and short-chain products, which may or may not contribute to SOA formation. However, the natural atmosphere is an even more highly mixed system (Goldstein and Galbally, 2007), and plant emissions contain a mixture of monoterpenes, sesquiterpenes, and other long- and short-chain compounds, partly containing oxygen. Moreover, these compounds cover a wide range of reactivity towards the atmospheric oxidants OH, O₃ and NO₃ (e.g., Atkinson and Arey, 2003). Because of their complexity, such reaction systems cannot be easily simulated in the laboratory. As a result, several recent investigations of biogenic SOA formation have utilized emissions from real plants. These experiments complement laboratory studies of SOA formation from single compounds, and enable the interaction and synergic effects of the different components in the emission
mixture to be investigated. Moreover, such experiments will
yield SOA formation potentials for emissions from individ-
ual plant species or plant groups, which can be characteristic
of particular eco-systems. Such studies may serve to estimate
the total flux of organic carbon into the particulate phase on
an eco-system level (Mentel et al., 2009).

McFiggans et al. (2004) oxidized the emissions of macroalgae at elevated ozone levels to generate particles in order to obtain information on new particle formation in coastal areas. According to their findings molecular iodine directly released into the atmosphere from macroalgae may be more important for nucleation than organo-iodine compounds. Joutsensaari et al. (2005) studied particle formation using VOC emissions from white cabbage. In this experiment elevated ozone levels were added directly to the chamber that contained the plants, and enhanced VOC emissions were triggered by exposing the plants to methyl jasmonate. The observed particle formation rates were similar to atmospheric nucleation events, but growth rates were clearly larger. From this observation Joutsensaari et al. (2005) concluded that the condensing species should not significantly contribute to nucleation in the atmosphere and suggested that stress-induced plant emissions may be an important factor in new particle formation. In a second set of experiments the plant chamber was separated from the reaction chamber and enhanced monoterpane emissions were triggered by infesting the cabbage plants with herbivores (Pinto et al., 2007). It was concluded that the monoterpane mixing ratio (ca. 30 ppb) arising from the cabbage, which contained limonene (30%) as the main component, was too low to induce new particle formation at ozone levels of less than 100 ppb.

Generally, trees are expected to be the major source of VOC that contribute to SOA formation. VanReken et al. (2006) investigated particle formation from ozonolysis of holm oak and loblolly pine emissions using a twin chamber approach. The biogenic emissions were generated in a typical plant chamber and transferred into a second, dark reactor, where ozonolysis and subsequent particle formation took place. The VOC mixing ratios (several ppb) entering the aerosol chamber during these experiments were lower than those used in most chamber studies, and approached the natural canopy levels. Ozone levels were around 50 ppb. Particle formation from holm oak and loblolly pine emissions was compared to that obtained in a control experiment performed using α-pinene (6 ppb). VanReken et al. (2006) found that holm oak emissions were the least efficient particle source whereas emissions from loblolly pine produced more particles than α-pinene. However, the amount of particles formed during the events was variable for the same pine tree and a simple relation between emission pattern and event strength was not evident. This study demonstrated that particle formation from biogenic emissions could be investigated under conditions that approach the ambient atmosphere.

The studies discussed above applied O₃ as the main oxidant for particle formation but oxidation by OH is also an

important loss process for VOCs. Mentel et al. (2009) investigated particle formation from emissions of boreal forest species in a twin chamber system using O₃ (50–80 ppb) and OH radicals ((3±2)×10⁷ cm⁻³) as oxidants. At total VOC mixing ratios of less than 10 ppb, OH radicals were needed to generate new particles under the conditions in the plant/reaction chamber, although almost all sesquiterpenes were already consumed by O₃ before OH generation. An average nucleation rate, j₃nm, of 40 cm⁻³ s⁻¹ and an average condensational growth rate of 20 nm h⁻¹ were observed, which are larger than those over a boreal forest, but commensurable with the factor of 10 increase in OH concentrations. Thresholds for new particle formation were significantly lower for the tree emissions than for pure α-pinene. The measured SOA volume, average nucleation and condensational growth rates were linearly dependent on the carbon mixing ratio in the reactor. The SOA mass fractional yields obtained for tree emissions were in good quantitative agreement (within 5–10%) with the data obtained for boreal forests by Tunved et al. (2006).

All studies described above suggest that atmospheric aerosol formation from real plant emissions is different from that observed for the oxidation of single compounds. Studies using plants as an integral VOC source can help to confirm if the simple additivity of single compounds holds for prediction of SOA formation and where more detailed understanding is needed. Moreover, if the plants are stressed, emission strength and emission patterns change and this especially may play a role in threshold controlled processes like new particle formation. These types of results cannot intrinsically be produced by laboratory experiments with single precursors, but of course in field studies. However, in field experiments the stability of conditions is limited and long observation times are needed to reproduce findings. This gap can be filled by controlled simulation experiments with real plants, which reflect the highly mixed natural states, and approach natural VOC concentrations and oxidant levels. The achievement of quantitative results in such simulation experiments is still complicated by the natural, biological variability of plant emissions. However, separation of the plant enclosure and reaction chamber (VanReken et al., 2006) combined with thoroughly controlled conditions for plants and stable parameters in the reaction chamber, can lead to reproducible, quantitative results (Mentel et al., 2009). It seems that plant chamber studies as described above will provide an important additional tool for laboratory and field studies directed toward understanding and quantifying natural processes of particle formation.

## 5.6 Interaction of atmospheric organic components with water

Water vapor in the moist atmosphere may interact with organic aerosol components and their precursors in a number of ways. Ignoring the potential dependence of the kinetics
of gas phase reactions in the oxidative pathways of organic species on water vapor, these interactions may be classified as:

1. Impact on the loading of organic aerosol by influence of relative humidity on the partitioning of SOA components between the gas and aerosol.

2. Changes in the ambient water content and size of aerosol particles in the sub-saturated moist atmosphere with varying relative humidity.

3. Nucleation of cloud droplets on aerosol particles containing organic material as water vapor concentration increases above a critical threshold and the growing droplet successfully competes for available water vapor.

4. Nucleation of ice crystals on organic aerosol behaving as ice nuclei, or freezing of aerosol containing organic material that had previously activated into liquid droplets.

Of course, these processes will overlap to varying degrees such that hygroscopic growth or cloud droplet activation of aerosol particles will increase the liquid water content and hence the equilibrium concentration of soluble aqueous organic components, for example. However, these classifications will first be considered in turn, before addressing such complications.

### 5.6.1 The effect of relative humidity on secondary organic aerosol formation

Seinfeld et al. (2001) and Seinfeld and Pankow (2003) considered the means by which water vapor may impact on the equilibrium concentration of SOA mass by reference to the conventional formulation of the equilibrium coefficient in absorptive partitioning, $K_p$, used in Eqs. (1)–(3). An increase in each component present in the aerosol phase can be accomplished by decreasing the average molecular weight of all condensed species, $MW_{om}$, decreasing the component activity coefficient $\zeta_i$ or increasing the absorptive particulate mass, $C_{om}$. Since water has a very low MW it will always tend to increase $K_p$ by decreasing $MW_{om}$. However, the activity coefficient variation with RH will be more complex and depend largely on the hydrophilic nature of the partitioning organic components.

If water is incorporated as a partitioning component into the standard partitioning theories, with an assumed activity coefficient of one, changes in RH are found to have profound effects on aerosol mass. This is simply a result of water being the most abundant semivolatile component in the atmosphere by many orders of magnitude. For example, Fig. 10 shows calculations for a test system of two compounds, B and C interacting with water. The resulting RH dependence is large owing to the low molecular mass of water (i.e., the high atmospheric molar abundance compared with the $C^*$ value of

water expressed in molar terms compared with the lower molar abundance of the higher MW organic components relative to their $C^*$ values). It is clear in Fig. 10 that there is a much stronger relative dependence of condensed organic mass on RH at low organic molecular abundance ($2 \mu g m^{-3}$ B and $1 \mu g m^{-3}$ C) than at high abundance ($200 \mu g m^{-3}$ B and $100 \mu g m^{-3}$ C) and therefore that the precursor concentration at which SOA formation experiments are conducted will influence the observed RH dependence.

In contrast to these predictions, chamber studies have only reported modest RH effects on SOA mass (Cocker et al., 2001a, b), though substantial effects on particle mass and number have been reported in flow-tube studies (Jonsson et al., 2006). A challenge in these studies is that water can participate as a reactant in the gas-phase chemistry leading to SOA formation, so deconvolving RH effects on the phase-partitioning thermodynamics and water effects on the chemistry can be a challenge. Hygroscopic growth experiments provide an important additional constraint, as it is the presence of water in the organic phase that suppresses the organic vapor pressures in the theoretical calculations. To the extent that hygroscopic growth of pure organics is relatively low, the activity coefficient of water in the organic phase is greater than unity. Not only does this reduce the water fraction in the organic phase, but, via the Gibbs-Duhem relationship, it raises the organic vapor pressures as well. For example, the 1,3,5-trimethylbenzene SOA experiments reported by Baltensperger et al. (2005) show much lower hygroscopic growth at 85% RH than one would predict for water forming an ideal solution with $MW_{organic} = 180 g mol^{-1}$, especially early in the experiment, consistent with an activity coefficient for water in the SOA of considerably more than 1. That in turn means that there will be less water in the organic mixture at a given RH, which finally will reduce the effect of RH on the organic vapor pressures. The generality of such results should be investigated. A broader discussion of the role of water in absorptive partitioning through its effects on condensed molar mass and its contribution to the overall condensed mass may be found in Barley et al. (2009) and of the effects of non-ideality and phase separation of hydrophobic and hydrophilic components in absorptive partitioning in Erdakos and Pankow (2004).

### 5.6.2 Hygroscopic growth

The hygroscopicity of a particle describes its equilibrium water content at a known humidity. Hygroscopicity is an absolute quantity, referenced to the known dry state. In the laboratory, it may be measured with a hygroscopicity tandem differential mobility analyzer (HTDMA) or by single particle techniques such as the electrodynamic balance (EDB) or optical tweezers (Hanford et al., 2008). The HTDMA compares the mobility diameter at dry conditions with that at enhanced RH, from which a (diameter related) hygroscopic growth factor (GF) is determined. The water fraction of the
particle is then calculated assuming particle sphericity (and volume additivity on dissolution or adsorption of water). In the EDB the particle is levitated by adjusting a voltage for compensating the increase in gravitational force on water up-take; this method thus determines a mass related water up-take. The EDB requires particles with a diameter of at least about 5 µm, and is thus only suited for the laboratory. The HTDMA is used both in the laboratory and in the field. Swi-tlicki et al. (2008) provided a recent review on HTDMA measurements in the field. Zardini et al. (2008) reported a comparison of HTDMA and EDB data for mixtures of amonium sulfate and different carboxylic acids.

Soluble inorganic particles exhibit a distinct deliquescence RH, where particles suddenly change their state from a dry particle to a saturated solution, associated with a sudden change in the diameter. On further increase of RH the particle becomes more diluted, resulting in a further increase in the diameter. On decreasing the RH the particle does not crystallize at the deliquescence RH (DRH) but rather stays liquid in a supersaturated solution, exhibiting hysteresis, until it crystallizes at lower RH known as the efflorescence RH (ERH).

Marcolli et al. (2004), Marcolli and Krieger (2006) and Meyer et al. (2009) showed that organic compounds can reduce the DRH of mixed particles compared with particles containing only inorganic components, thus enabling the inorganic components to be partly solubilized below their DRH. The ERH of particles mixed of ammonium sulfate and limonene or α-pinene SOA have been found not to differ significantly from the ERH of pure ammonium sulfate particles (Takahama et al., 2007). However, aged ambient aerosol particles, as typically found at remote sites such as the high-Alpine site Jungfraujoch, do not show efflorescence at RH as low as 10% (Weingartner et al., 2002). From such field measurements it may be implied that, for atmospheric aerosols, the presence of SOA will enable the water uptake of the inorganic fraction at RH values lower than the DRH of the inorganic component.

The hygroscopic growth of SOA has recently been investigated in several simulation chamber studies (Baltensperger et al., 2005; Varutbankul et al., 2006; Duplissy et al., 2008). No efflorescence or deliquescence has been found in these studies. Hygroscopic growth has been found to increase with aging time under the chamber conditions (Baltensperger et al., 2005; Duplissy et al., 2008), with such an increase being consistent with oxidation of the SOA particles during aging. Oligomerization is another process thought to take place during aging. In chamber experiments, dimers and trimers have a lower O/C ratio than monomers (Reinhardt et al., 2007). In line with this observation, Altieri et al. (2008) reported that the ratio of organic matter to organic carbon (OM/OC) in the oligomers (1.0–2.5) was lower than the OM/OC in the organic acid monomers formed, suggesting that the oligomers are less hygroscopic than the organic acid monomers in the investigated system. An increase in hygroscopicity with time

<figure><img src="image_12.png" /><figcaption>**Fig. 10.** Condensed mass predicted in the partitioning of water and two organic components, B and C, assuming ideality. B and C have molar-based $C^*$ values of 0.4 and 0.004 µmol m⁻³. Using molar masses of 250 g mol⁻¹ for both B and C, this is equivalent to mass-based $C^*$ values of 100 and 1 µgm⁻³ (log $C^*$ mass based bins 2 and 0). The three pairs of curves show the effect of varying the total organic abundances of 0.008, 0.08, 0.8 µmol m⁻³ (2, 20 and 200 µgm⁻³) of component B and 0.004, 0.04, 0.4 µmol m⁻³ (1, 10 and 100 µgm⁻³) of component C (low, medium and high cases).</figcaption></figure>

may indicate that oxidation overwhelms oligomerization in the aging of particles formed by self-nucleation. Furthermore, an increased hygroscopic growth was found for a decreasing chamber VOC precursor concentration (Duplissy et al., 2008). This may be explained by partitioning of higher volatility (less polar) compounds into the aerosol at high concentrations, as described in Sect. 4.3.2. Decreasing the VOC precursor, hence molecular abundance of partitioning organics and aerosol loading down to atmospherically relevant values thus results in an increase of the hygroscopic growth factor.

Hygroscopic growth has also been investigated for HULIS, which are frequently used as model compounds for SOA. Both HULIS extracted from atmospheric aerosols and standard material such as SRFA have been investigated (GySEL et al., 2004; Baltensperger et al., 2005; Dinar et al., 2007; Ziese et al., 2008). In general, these samples showed similar hygroscopic growth.

The water content can be calculated by accounting for the ionic and molecular interactions (solving the water equation within an energy minimization) or can be evaluated by use of relationships derived from mixing rules, such as that of Zdanovskii, Stokes and Robinson (ZSR) (Stokes and Robinson, 1966). Whichever method is used to evaluate multi-component water content, the prediction must include the water associated with all components. Such binary aqueous solution data may be readily available for inorganic
systems of atmospheric importance, but are seldom available for atmospherically-representative organic compounds, necessitating the use of models to predict the water activity in the aqueous organic solution. A number of approaches have been used, including; (i) explicit considerations of compound interactions requiring compound specific laboratory data, e.g., the extended ZSR approach of Clegg and Simonson (2001); (ii) empirically-fitted approaches such as UNIQUAC (Ming and Russell, 2002); (iii) more generalized group contribution techniques such as UNIFAC (Topping et al., 2005a, b). Various developments have been made to UNIFAC in order to most appropriately treat atmospherically relevant components through development of new group interaction parameters (Peng et al., 2001), based on emerging laboratory data. The contribution to the water content by a number of organic components may be directly evaluated within the organic activity coefficient model, and combined with the water associated with the inorganic components in a coupled model (Topping et al., 2005b). Such models may (Ming and Russell, 2002; Erdakos et al., 2006a, b) or may not (Topping et al., 2005b) explicitly account for interactions between inorganic and organic solutes. The AIOMFAC model reported by Zuend et al. (2008) is based on LIFAC with improved treatments of the mid-range interaction terms enabling superior treatment of inorganic and a limited number of organic components (alcohols and polyols) in multicomponent aerosol. A recent detailed comparison with laboratory measurements has shown that both coupled and uncoupled treatments of inorganic and organic components capture water uptake behavior adequately (Hanford et al., 2008). Alternatively, the contributions may be lumped and treated in an additive manner as in the ZSR technique, which may be applied as outlined below.

The hygroscopic growth factor of a mixture ($GF_{\text{mixed}}$) is estimated from the growth factors of the individual components of the aerosol and their respective volume fractions, $\varepsilon$:

$$GF_{\text{mixed}} = \left( \sum_{k} \varepsilon_{k} GF_{k}^{3} \right)^{1/3} \qquad (11)$$

where the summation is performed over all compounds present in the particles. The model assumes that the particles are spherical, there is ideal mixing behavior (i.e., no volume change upon mixing) and independent water uptake by the organic and inorganic components. The volume fractions $\varepsilon_i$ of the components in the particles are calculated as

$$\varepsilon_i = \frac{(w_i)/(\rho_i)}{\sum_k (w_k/\rho_k)} \qquad (12)$$

where $w_i$ is the measured mass fraction and $\rho_i$ the density of component i.

A number of laboratory studies have shown that the ZSR relationship is generally valid within experimental error (e.g., Choi and Chan, 2002; Svenningsson et al., 2006; Varutbangkul et al., 2006; Moore and Raymond, 2008; Sjogren et al., 2008). Relatively few field studies are reported

where HTDMA measurements were accompanied by detailed chemical measurements sufficient to perform a hygroscopicity closure (McFiggans et al., 2005; Aklilu et al., 2006; Gysel et al., 2007; Sjogren et al., 2008). McFiggans et al. (2005) and Gysel et al. (2007) showed that, in atmospheric particles, water uptake is to a great extent determined by the inorganic constituents. It was found to be more important that the chemistry and instrumental behavior of the inorganic compounds was well-characterized, e.g., if sulfate was present as ammonium sulfate or ammonium bisulfate and whether ammonium nitrate was present, than if the hygroscopic growth factor chosen for the organic components was accurate.

### 5.6.3 Cloud condensation nucleation behavior

The activation of an aerosol particle into a cloud droplet is determined by the size of the particle and its composition. A complete discussion of the processes controlling warm cloud droplet activation is provided by McFiggans et al. (2006). With respect to the effect of organic components on CCN behavior of atmospheric aerosol, there are several considerations. Organic molecules may influence both the Raoult and Kelvin terms of the Köhler equation by their effect on the water activity and surface tension of the activating aerosol particle.

The cloud forming potential is closely related to the hygroscopic properties of the aerosol, and is typically probed with a cloud condensation nuclei counter (VanReken et al., 2005; Prenni et al., 2007; Duplissy et al., 2008; Engelhart et al., 2008). VanReken et al. (2005) found a decreasing hygroscopicity (increased supersaturation required for activation at a given size) with aging time for SOA from several biogenic precursors and attributed this to an increased degree of oligomerization, while Duplissy et al. (2008) reported a decreasing required supersaturation with aging time, in line with the simultaneously observed increasing hygroscopic growth determined with an HTDMA. Similarly, Engelhart et al. (2008) reported that $\alpha$-pinene SOA experienced a decrease of the particle activation diameter of approximately $3 \text{ nm h}^{-1}$ during aging.

Recently the semi-empirical “$\kappa$-Köhler theory” (Petters and Kreidenweis, 2007 and references therein) was introduced to describe the hygroscopic growth as a function of relative humidity (so-called humidograms). Here, $\kappa$ is a single free parameter of the “$\kappa$-Köhler theory”, capturing all compound properties as well as the degree of dissociation and deviations from ideal behavior as a function of water activity, thus determining the hygroscopic growth. Whilst it is unlikely that general agreement may be obtained with this approach to link sub-saturated and supersaturated behavior, it may have value under well-defined conditions. Several studies have found that, within error, reconciliation of growth factor and CCN activation from chamber studies of SOA can be achieved using such an approach with the surface
tension of water (e.g., Duplissy et al., 2008). Engelhart et al. (2008) reported that the CCN activity of α-pinene and mixed monoterpane SOA can be modeled by a very simple implementation of Köhler theory, assuming complete dissolution of the particles, no dissociation into ions, a molecular weight of 180 g mol⁻¹, a density of 1.5 g cm⁻³, and a surface tension to within 10–15% of water. However, Prenni et al. (2007) found that measured droplet activation conditions were inconsistent with hygroscopicity measured below water saturation and Köhler theory expressions based on Raoult’s law for several parameterizations of water activity for SOA formed in ozonolysis of α-pinene and other precursors. Dinar et al. (2007) found that the approach works reasonably well for SRFA samples but is limited in use for the HULIS extracts from smoke- and pollution-derived aerosol particles, stating that the difficulties arose from uncertainties with the GF measurements at high relative humidity, leading to large errors in the predicted CCN activity. It is also possible that surface tension could have played a role in the activation of the HULIS extracts. More research is needed to elucidate the reasons for these different observations.

Surface-active compounds may have a significant potential to increase the predicted cloud number concentration and thus radiative forcing in cloud simulations, when compared with simplified simulations assuming the properties of ammonium sulfate (Ervens et al., 2005; McFiggans et al., 2006) and may thus be of high atmospheric relevance. Cloud activation behavior prediction using theoretical calculation of surface tension was shown to give reasonable agreement with laboratory measurements for pure component organic particles generated in the laboratory (Rissman et al., 2007). However, recent developments in the theory of partitioning of surface active materials between the bulk and surface of growing aqueous droplets (Kokkola et al., 2006; Sorjamaa and Laaksonen, 2006) indicate that, when agreement is achieved in such studies using the simplified approach, this is likely to result from cancellation of errors in the underlying assumptions. Such complete cancellation cannot generally be assumed. In addition, although the critical supersaturation of a particle may be correctly predicted using the simplified approach, there may be significant differences in the prediction of critical diameter. McFiggans et al. (2006) provide a discussion of the potential effects of component-limited solubility and the possible effects of film-forming compounds on CCN behavior relevant to organic aerosol components. More recent modification of Köhler theory to account for adsorption to wettable but largely insoluble compounds (Sorjamaa and Laaksonen, 2006) has predicted that such processes may account for activation of such components at atmospherically-reasonable supersaturations and further theoretical and laboratory work is needed to investigate this behavior.

Two recent studies have investigated the CCN behavior of mixed inorganic/organic particles from different perspectives. Dinar et al. (2008a) suggested that the formation of

ammonium salts due to reaction of ammonia with slightly soluble organic acids (such as adipic acid) can affect the CCN activity and hygroscopic growth of aerosols with a significant organic component. The findings are relevant to organic components containing carboxylic groups and require the presence of water in the aerosol. It was also found that the effects are stronger for less soluble organic acids. Prisle et al. (2008) showed that it was necessary to consider partitioning of organic molecules between the bulk and surface of an activating cloud droplet to correctly predict measured CCN behavior of the sodium salts of C₈ to C₁₄ fatty acids, confirming the predictions made by surface partitioning theory.

### 5.6.4 Ice nucleation

In general ice nucleation can occur in the atmosphere in two fundamental ways: through homogeneous freezing of liquid solution droplets and through heterogeneous interaction on a particulate nucleus. Homogeneous nucleation, or freezing, occurs at temperatures below about 240 K, while heterogeneous freezing may occur at much higher temperatures and just slightly below 273 K. For both processes, nucleating efficiency not only depends on temperature but also on the chemical composition of the droplets or particles. On the other hand, when the nucleation of ice from supercooled aqueous solutions is described as a function of the water activity of a solution, the ice nucleation process becomes independent of the chemical composition (Koop, 2004), indicating the nature of the solute is unimportant for the freezing process. There is further evidence that a similar dependence is also true for heterogeneous ice nucleation in the immersion mode (Zobrist et al., 2008a) and for dust particles with soluble coatings in the deposition/immersion model (Archuleta et al., 2005).

The majority of work on organic aerosol components and their influence on homogeneous freezing has mainly focussed on small organic acids. While some laboratory studies indicate that low molecular weight dicarboxylic acids exhibit identical freezing behavior as sulfate (Wise et al., 2004), others have indicated that homogeneous freezing of low molecular weight dicarboxylic acids is not as efficient as for inorganic aerosol components (Prenni et al., 2001). Also field measurements indicate that organics could impede ice nucleation since these measurements have revealed that organic containing aerosols are less abundant than sulfate aerosols in ice cloud particles when compared to interstitial aerosols (DeMott et al., 2003; Cziczo et al., 2004a, b). Based on a modeling approach, Kärcher and Koop (2005) explain this poor partitioning of certain organics into the ice phase primarily by a disparate water uptake and resulting size differences that occur between organic and inorganic particles prior to freezing. The situation is less clear with respect to the influence of organic aerosol components on heterogeneous ice nucleation processes. Zobrist et al. (2006)
measured the heterogeneous freezing points with several im-
mersed dicarboxylic acids and found that only oxalic acid, in
the form of its dihydrate, acts as a heterogeneous ice nucleus
with an increase in freezing temperature between 2 and 5 K.
Long-chain alcohols have also been found to catalyze the
freezing of solutions of ammonium sulfate and sodium chlo-
ride (Popovitz-Biro et al., 1994; Seeley and Seidler, 2001;
Cantrell and Robinson, 2006; Zobrist et al., 2008a). For
the alcohol systems, it is believed that the organic molecules
self-assemble at the air-water interface into two-dimensional
crystals with a structure similar to the basal plane of ice. In
the case of oxalic acid the crystallization of the oxalic acid
hydrate within the aqueous solution is assumed to result in
organic crystals, which act as immersion mode freezing ice
nuclei. Further interesting results with respect to the influ-
ence of organics on ice formation were recently published
by Beaver et al. (2006), who studied the effects of carbonyl
compounds on the ice nucleation of sulfuric acid in the la-
boratory and observed that the physical properties of the or-
ganic compounds (primarily the solubility and melting point)
play a dominant role in determining the inferred mode of
nucleation (homogeneous or heterogeneous) and the specific
freezing temperatures. Highly soluble, low-melting point or-
ganics caused a decrease in aerosol ice nucleation tempera-
tures when compared with aqueous sulfuric acid aerosol –
in agreement with the homogeneous freezing experiments
mentioned above. In contrast, sulfuric acid particles exposed
to organic compounds of higher molecular weight, of much
lower solubility and higher melting temperatures, nucleate
ice at temperatures above aqueous sulfuric acid aerosols. Ap-
parently, partial crystallization of organic molecules changes
the freezing mode from homogeneous to heterogeneous. The
precipitated crystal, possibly an organic solid, might then in-
duce heterogeneous ice nucleation at the liquid/solid inter-
face.

Finally, there is another potential effect of organic aerosol
components on ice cloud formation – the influence of organic
surface layers. For example, organic films on the aerosol sur-
face have been used as one explanation for supersaturations
with respect to ice exceeding 100% observed in the tropical
tropopause (Jensen et al., 2005). The idea is that dense or-
ganic films might reduce the accommodation coefficient for
the uptake of water, resulting in aerosols with more concen-
trated solutions, with lower activities, and correspondingly
inhibited homogeneous freezing. Alternatively, if water rich
aerosols were fully covered with organic surfactants, nucle-
ation might be suppressed if it started preferentially at the
surface (Tabazadeh et al., 2003; Peter et al., 2006). In ad-
dition, there have been recent studies on ice nucleation on
pure SOA particles as well as on mineral dust particles coated
with SOA (Möhler et al., 2008). SOA significantly reduced
the ice nucleation efficiency in both the homogeneous and the
heterogeneous ice nucleation case, requiring very large
supersaturations before ice particles could be observed. Si-
milar results were obtained for soot particles covered by or-

ganic carbon (Möhler et al., 2005). These effects were very
recently interpreted by the possible presence of a highly vis-
cous or glassy state in solutions of larger organic molecules
(Murray, 2008; Zobrist et al., 2008b). Furthermore, Prenni
et al. (2009) investigated the ice nucleation behavior of SOA
particles generated by the ozonolysis of 25 different alkenes.
None of these SOA particles showed measurable signatures
of heterogeneous ice nucleation at a temperature of 243 K.
However, the laboratory studies mentioned above are per-
formed at precursor concentrations significantly greater than
those commonly occurring in the atmosphere, influencing the
chemical composition of SOA. As already mentioned above,
in Sects. 3.2. and 4.1.2, as the mass concentration of organic
aerosol rises in a chamber experiment, compounds of higher
volatility (and different chemical functionalities) progres-
sively partition into the aerosol phase, potentially changing
the physico-chemical behavior of the organic phase. Such
effects have already been observed experimentally for the
cloud activation potential of SOA for atmospheric mass load-
ings (King et al., 2009) and it remains to be explored if they
also play a role for the ice-forming properties of organics.
Similarly, changes of chemical functionalities of organics as
a consequence of homogeneous or heterogeneous aging or
organic aerosol components are not covered in conventional
chamber experiments.

In summary, it remains unclear how important the chemi-
cal nature of the organic compounds is with respect to their
ability to serve as ice nuclei or their potential to impede or
even inhibit ice formation, since the implications of individ-
ual solubility, melting temperature, surface activity or glass-
forming properties of organics are not quantitatively under-
stood. Certainly additional laboratory work and field mea-
surements in clouds in the upper troposphere are needed in
the future to understand the role of organics in ice nucleation.

5.7 Thermodynamics and mixtures in atmospheric models

Under the non-ideal conditions expected to be encountered
under self-nucleating conditions in simulation chambers, or
in organic component condensation in chambers or the at-
mosphere, the activity coefficients of the condensing organic
compounds, γᵢ, are required in the calculation of the Kp,i
(or Cᵢ*) values. The UNIFAC group contribution method is
widely used for calculating activity coefficients in liquid non-
electrolyte mixtures, including organic compounds and wa-
ter. Several studies have made use of UNIFAC in calculating
the formation and hygroscopic properties of organic partic-
ulates (e.g., Jang et al., 1997; Pankow et al., 2001; Peng et
al., 2001; Seinfeld et al., 2001; Erdakos and Pankow, 2004;
Erdakos et al., 2006a, b). Semi-empirical group contribu-
tion methods such as UNIFAC are broadly suitable for atmo-
spheric applications because a small number of functional
groups can be used to represent a large number of organic
components. The group interaction parameters account for
differences in the molecular interactions between pairs of
functional groups in solution under the assumption that their
contributions to the component activity coefficients are addi-
tive and independent.

Because field evidence suggests that organic aerosol com-
ponents invariably do not exist in the absence of inorganic
components, a wide variety of approaches have been used
to treat multicomponent particles. The models of Clegg et
al. (2001) and Ming and Russell (2002) may be used if the
concentrations of organic compounds in mixed aqueous salt
aerosol are so low that water may be considered the sol-
vent. Similarly, if the particles comprise organic and water
solutions with inorganic salts present at concentrations suf-
ficiently low for the organic/water mixture to be considered
the solvent, the formulations of Kikic et al. (1991) or Erdakos
et al. (2006a, b) may be appropriate.

Raatikainen and Laaksonen (2005) presented an evalua-
tion of the capabilities of multi-component activity coeffi-
cient models for atmospheric applications. These included:
(i) models combining group contribution models for organic
components and ionic interaction models for inorganics:
Ming and Russell (2002) combining UNIFAC (including
modifications to account for differences in molecule polar-
ity) and the Pitzer, Simonsen, Clegg (PSC) mole fraction ion
interaction model and Topping et al. (2005a, b) combining
UNIFAC and the PSC model, (ii) an extension of UNIFAC
to include group interaction parameters for ions and (iii) a
modified version of LIFAC (Yan et al., 1999), a group con-
tribution version of the LIQUAC model of Li et al. (1994).

The Raatikainen and Laaksonen (2005) version contains
optimized interaction parameters for atmospherically rele-
vant components such as dicarboxylic acids and hydroxy-
carboxylic acids. All the above models are capable of pre-
dicting activity coefficients in single-phase multicomponent
mixtures with reasonable but varying degrees of skill. How-
ever, phase separation is not easily treated in these formula-
tions. A general method for predicting activity coefficients
for solutions containing significant amounts of organic com-
pounds, inorganic electrolytes and water does not exist; nor
do the data require the construction of such a general frame-
work applicable across the full range of atmospheric organic
compounds.

It has been assumed in some studies that two stable li-
quid phases are present in the ambient aerosol (equivalent to
fully externally mixed particle populations): one hydrophilic
containing mostly water and inorganic electrolytes, the other
hydrophobic comprising mainly organic components. This
assumption allows the hydrophilic phase to be treated as an
aqueous electrolyte solution, and the less polar hydrophobic
phase as a non-electrolyte solution. The system can then be
treated by previously-reported activity coefficient methods,
e.g., in line with Griffin et al. (2003). The model of Griffin et
al. (2003) does not include inorganic components in the non-
aqueous phase and allows organics to partition to both con-
densed phases. However, it does not account adequately for

the interaction of organics and inorganics within this phase.
Consequently, the validity of this assumption is not general
and it is desirable to develop approaches that do not rely on
such a priori conditions. In general, all components may be
present to some degree in all phases. In particular, high po-
larity organic components may be present at significant con-
centrations in an aqueous phase (e.g., Meyer et al., 2009)
and salts may be present in a predominantly organic phase at
concentrations that affect all component activities.

Clegg and Seinfeld (2006a) demonstrated that the
extended-ZSR approach first proposed in Clegg et al. (2001)
is reasonably accurate when carboxylic acids are not allowed
to dissociate. When carboxylic acids are allowed to dissoci-
ate, the extended-ZSR only yielded reasonable results when
the non-dissociating support ion is present at medium to high
concentrations (Clegg and Seinfeld, 2006b). This was bench-
marked against a complex Pitzer-type model based on all
multicomponent equilibrium data.

The X-UNIFAC.3 model of Erdakos et al. (2006b) enables
consideration of phase separation by applying correction to
the model terms and constraint on parameters in predicting
component activity coefficients to avoid activity coefficient
re-expression relative to the same reference state in each
phase, which would otherwise be necessary. The model is
applicable to carboxylic acids and hydroxycarboxylic acids
and was demonstrated for a limited number of mixed systems
with these compounds, salts and water. There are severe data
limitations in the approach limiting the specific model appli-
cability, but the generality of the approach is encouraging.

It can be seen that there are a number of modeling
tools capable of making activity coefficient predictions in
single phase and multiphase solely organic or mixed or-
ganic/inorganic and aqueous solution particles. There is,
as yet, no generally applicable model, but appropriate care-
ful selection of model and laboratory SOA formation sys-
tems should allow reasonable representation of activity coef-
ficients in partitioning calculations.

6 Future research directions

The topics discussed in this review demonstrate the immense
progress made in our understanding of SOA over the past
10 years. We now possess much better knowledge of detailed
processes and how they affect SOA formation, properties and
possible environmental impacts. Despite this, there are still
significant gaps in our knowledge which places limitations
on our ability to quantify and predict SOA in the ambient at-
mosphere. In light of the progress made and problems iden-
tified, several emerging issues pose challenges which need to
be addressed via a combination of laboratory, field and mod-
eling studies. These key issues are discussed below. They
are not listed in order of priority but rather as a guide for
future research directions. In general, it is pointed out that
many of the items on this list require faster and more accurate
analytical tools which may open avenues for exploring a wider range of phenomena. Other major challenges include an improved understanding of the fundamental processes responsible for SOA formation and how they affect composition, and the design of simulation experiments which more closely reflect the conditions and complexity of the real atmosphere.

## 6.1 SOA budget

Further research in the following areas should help to reduce the large uncertainty associated with the SOA budget.

**Missing BVOC** – It is plausible that large sources of organic compounds are yet to be identified. This may be a result of current limitations associated with detection and analysis tools and may be addressed, for example, by measuring the entire reactivity of radicals towards organics in order to estimate the total organic burden in the atmosphere in different environments. A complementary approach would be to use less specific detectors in order to detect unidentified compounds in ambient and in plant chamber studies in order to assess the amount and the main functional groups of these species. 2-D separation methods may provide such an avenue for these investigations.

**Improved quantification of BSOA in the field** – The quantification of BSOA in the field using highly time-resolved techniques has remained a challenge due to the difficulty in separating the relatively low formation rates from variations due to advection and other OA sources. Future highly time-resolved studies (e.g., using AMS, PILS-WSOC) should be performed at locations that are expected to be dominated by BSOA to evaluate the biogenic signal more clearly. New techniques that eliminate the influence of the background OA, such as flux measurements, or that use more specific biogenic tracers such as carbonyl sulfide uptake, may prove to be effective.

**Improved quantification of SOA formation from biomass burning** – Very recent results indicate that SOA formation from biomass burning emissions can be very important under some circumstances and minor in others. The observed variability is likely to stem from the high variability of the gas, semivolatile, and particle emissions from BB due to combustion conditions (flaming vs. smoldering) and fuel burned, as well as atmospheric variables (injection height, wet removal in pyroconvection). Additional field studies are needed to characterize this potentially important SOA source.

**Addressing the discrepancy between ¹⁴C analysis and highly time-resolved studies** – The apparent contradiction between results based on ¹⁴C analysis that attribute most SOA to modern sources and those from highly time-resolved studies that point to anthropogenic pollution as the dominant source of SOA needs to be a focus of future work. New field studies should strive to include both types of measurements to allow a more direct comparison and to address the possibility that the different findings are due to different geo-

graphical locations or times. The potential enhancement of BSOA by anthropogenic pollution needs to be evaluated in the field by analyzing BSOA formation during periods of high and low pollution.

**Use of data from simulation chambers** – Bottom-up estimates of SOA formation fluxes rely on data generated from simulation chamber experiments. However, the yields of SOA from individual precursors appear to be highly dependent on experimental conditions. Further work is clearly required to establish the most appropriate parameters for inclusion in global models. Despite the complexities involved, these data need to be understood in terms of chemical and gas-particle partitioning mechanisms before reliable extrapolation to the ambient atmosphere can be placed on a sound basis. This will require substantial improvements in our understanding of the chemical mechanisms and the thermodynamics of such complex gas-particle mixtures.

**Additional SOA precursors** – The potential importance of additional sources of SOA (newly discovered and previously unconsidered precursors, such as acetylene and oxygenated BVOCs) should be explored. A large source of missing biogenic VOCs that result in SOA likely also includes plant leaf volatiles (Hamilton et al., 2009) and oxidation products of primary plant material containing unsaturated fatty acid residues.

## 6.2 Fundamental understanding of processes leading to SOA formation

**Improved understanding of VOC oxidation** – The atmospheric degradation mechanisms for many established SOA precursors (e.g., monoterpenes, aromatics) contain a high level of uncertainty, particularly in relation to the reactivity of certain oxidation products. There is a general lack of information on the degradation reactions of multifunctional oxygenates containing combinations of the key functional groups (i.e., -C(=O)H, -C(=O)-, -OH, -ONO₂, -C(=O)OONO₂, -C(=O)OH, -OOH and -C(=O)OOH) and the further degradation of organic nitrates and hydroperoxides is particularly poorly characterized, even though these are comparatively significant product classes which potentially play a role in SOA formation. The role of NO₃-initiated chemistry in SOA formation has largely been neglected and the chemical mechanisms for the atmospheric degradation of other potential SOA precursors, such as sesquiterpenes, long-chain alkanes and oxygenated BVOC, are also in need of improvement.

**Gas-particle partitioning** – The link between the fundamental understanding of gas-particle partitioning and its application to atmospheric or laboratory generated SOA is complex. Several factors complicate the interpretation of data such as the nature of the condensed phase, effect of temperature and the validity of thermodynamics and solution theory for non-ideal partitioning. In addition, the application of fundamental data, such as vapor pressures, molar
activity coefficients and the mean MW of the condensing phase has proven to be difficult. Further improvements in the use of gas-particle partitioning theory to interpret experimental data, obtained in both laboratory and field studies, are required.

**Condensed phase reactions** – The wide range of higher-MW products detected in laboratory-generated SOA have resulted in many proposed reactions occurring in the condensed phase. Further work is required to investigate the key processes (e.g., oligomerization, organosulfate formation) under conditions relevant to the atmosphere.

**Aqueous phase reactions** – Chemical and photochemical processes in the atmospheric aqueous phase may lead to the formation of polyfunctional organic compounds in diluted droplets, which play an important role in condensation reactions leading to oligomers and SOA when the organic concentrations increase during cloud evaporation. However, the scientific knowledge of photochemical processes of organics, especially polyfunctional compounds, in the atmospheric aqueous phases is still quite limited and needs further investigation. Future studies should take into account the influence of different parameters relevant to the atmosphere such as pH, TMI content and ionic strength, which are likely to be highly variable in evaporating droplets, and could greatly affect the oligomerization processes.

**Detection and quantification of nanoparticles** – Nucleation of new particles is recognized as a widespread phenomenon but the exact mechanisms of initiation and growth are not well-known. A major challenge is posed by the minute mass of the nucleation mode particles. Standing issues include identification of the main nucleating agents, the possible role of organics in nucleation, and the contribution of organics to the growth mechanism. New instrumentation dedicated to these issues is urgently required. The missing parameters need to be studied in different environments (urban, rural, remote locations) in order to be able to include nucleation in a meaningful manner in models.

## 6.3 Measurements of aerosol composition

**Characterization of water insoluble organic matter (WIOM)** – SOA contains both water soluble (WSOM) and water insoluble organic matter (WIOM). Due to availability of separation methods, analytical tools and the importance of WSOM in CCN activation, much of the effort in speciation and microphysical studies has focused on WSOM but mostly neglected the WIOM, which may constitute a large fraction of the mass in some aerosol types and hence may significantly affect the microphysical, optical and chemical properties. WIOM is left mostly under-characterized. Tools for isolation, characterization and process studies of this important fraction are therefore encouraged.

**Organosulfates, HULIS, oligomers and other higher-MW species** – Recent field and chamber studies suggest that complex organic matter may consist of organosulfates, amines,

organic nitrates, oligomers and other higher-MW compounds. Many of these species remain poorly characterized. Missing information includes the identity, concentration, formation pathways and possible roles in affecting surface tension, optical properties, reactivity and CCN activity of SOA. New analytical methods should be developed to extract, identify and quantify these compounds. While the formation of oligomers has been firmly established in laboratory experiments, it is still uncertain whether they are formed under ambient conditions. There are still abundant unknown SOA constituents, even first-generation products detected in laboratory chamber studies, which are present in ambient and plant chamber aerosol and need to be structurally elucidated. Given their chemical complexity, efforts should be made to isolate and purify key species and to establish their chemical structures, where use could be made of available advanced multidimensional MS and NMR techniques.

**High time resolution techniques** – The development of measurement techniques with high time resolution would be very beneficial for mobile platforms by providing fast measurements of more components, e.g., tracers or functional groups. The recent methods providing data at high time resolution like mass spectrometry should be developed further to allow for less costly and labor-intensive deployments over longer time periods, a key issue for long-term monitoring. Methods that could be easily deployed and operated at multiple locations are beneficial for field campaigns or for longer-term monitoring. This would allow for better possibilities to evaluate and validate Eulerian type models.

**Characterization of SOA formation and aging processes** – Recent field results, mostly from anthropogenic pollution, suggest that SOA formation occurs in a timescale of one day after emission of the precursors, while aging of the SOA is rapid at first and continues at a slower rate for at least a week. Measurements of organic aerosol density could be used to provide information on atmospheric processing and aging of particles. Description of transformations (such as kinetics of specific processes, e.g., oligomerization, liquid phase diffusion, water interaction, surface reactions) relevant to SOA formation should be better characterized. Confirmation of this model at other locations and the investigation of whether the processes are similar for biogenic SOA are needed.

**Setup of field campaigns** – As already done to some extent, large field campaigns need to be specifically designed for the analysis of SOA. This often involves a Lagrangian type approach that allows for the analysis of the airmasses after different time of aging. Mobile platforms (aircraft, Zeppelins, ships, and mobile on-road laboratories) seem to be especially suited for such an approach.

## 6.4 Dealing with complexity

**Complex simulation systems** – Many laboratory studies employ simplified experimental conditions which neglect the environmental complexity. Important factors often
overlooked are presence of water, complex reactant mixture and composition, and temperature dependence. This limits the ability to extrapolate laboratory-based data to the atmosphere. With regards to simulation chambers, more complex VOC mixes could be employed. An important future development would be to describe the effect on SOA formation when going from the oxidation of a single precursor to the oxidation of complex mixtures.

**Combination of laboratory and field studies** – In the field, SOA from different precursors are mixed. The laboratory allows for the analysis of specific precursors and thus SOA detection by different methods can be tested. Future laboratory studies should therefore be performed under conditions that are closer to ambient conditions. The study of SOA from automobile engine exhausts, wood burning, and whole plants in addition to studies of individual precursor gases seems very promising. However, these laboratory studies need to be made at concentrations relevant to the atmosphere.

**Data interpretation** – As high complexity methods reach maturity it is likely that data interpretation will become the rate-determining step in the analytical procedure. This may require the adoption of data handling technologies associated with image processing and statistical methods, such as principal component analysis, to find ways in which useful and timely information can be extracted from chemical methods with such high levels of detail.

## 6.5 Modeling of SOA

It is obvious that modeling activities must follow experimental and mechanistic understanding, and the most basic problem regarding modeling of SOA is therefore the uncertainty surrounding the main formation mechanisms. However, the mechanistic details obtained from experimental and theoretical work need to be tested in models against ambient data in order to be considered reliable.

**Reflecting the latest findings** – It is essential that models reflect the latest findings as well as possible, and it can be noted that much of the understanding that has emerged over the past several years concerning the formation of SOA still needs to be incorporated in the SOA models embedded in atmospheric chemical transport models. The new developments that need to be reflected in any class of models include sufficiently detailed gas-phase chemistry, especially the role of $NO_x$ level, leading to formation of semivolatile products, particulate-phase chemistry, identification of the volatility range of oxidation products, and the roles of organic aerosol level in determining aerosol water content.

**Empirical vs. fundamental modeling** – A fundamental model would be based on detailed gas-phase mechanisms of VOC oxidation leading to explicit products that are then allowed to partition between the gas and particulate phases according to theoretically predicted partitioning coefficients. This class of models would account for the nature of the condensed phase and include, to the extent we understand such

chemistry, particulate-phase reactions, as well as aerosol aging over time scales beyond those accessible in chamber studies. The oxidation products explicitly identified would ideally be the predominant ones that have been identified in laboratory studies. Models of this type, which simulate the time-dependent course of SOA formation as a VOC is oxidized, are well-suited for simulation of chamber experiments, as they test the level of understanding of the fundamental processes involved. While such models have been formulated theoretically, a drawback to their use is that in many cases the majority of semivolatile oxidation products for a particular VOC may not yet have been fully identified. Even if well validated based on chamber data, they may not be the optimal choice for a three-dimensional atmospheric chemical transport model because of their computational demands. Despite increased understanding, the point has not been reached where SOA models can be formulated purely on the basis of chemical reaction mechanisms and thermodynamic predictions, in the absence of laboratory data. Therefore, formulation and testing of SOA models must continue to be based firmly on laboratory chamber data, and tested against real-world ambient data under a wide range of conditions.

**Availability of relevant data input** – It is evident that laboratory data should preferably reflect conditions either as close to ambient as possible or which allow confident extrapolation to ambient conditions. Ambient data must provide information which can be used for source apportionment, to evaluate the models emissions and chemical processing, which will require some combination of chemical speciation, radiocarbon data and/or functional group analysis. It is important to note that even in their present state or with modest improvements, chemical transport models can still be used to evaluate emission inventories of primary emissions of both particle and precursor VOC – such evaluations are a pre-requisite to any attempt to understand SOA formation in the ambient atmosphere.

## 6.6 Impacts of SOA on health and climate

**Health impacts** – A recent epidemiological study reveals a stronger association between daily mortality and fine particulate air pollution in summer than in winter (Nawrot et al., 2007). As high PM levels in summer are typically associated with the production of SOA, this finding suggests that SOA may substantially contribute to the observed effect on mortality. However, there are very few studies of the health effects of SOA. This is mainly due to the lack of suitable particle exposure techniques for studies of in vitro toxicity effects of SOA. Techniques that directly investigate the interaction of SOA material with lung cells are just emerging (e.g., Jang et al., 2006b; Baltensperger et al., 2008; De Bruijne et al., 2009). Another possible approach to unravelling the possible health-related aspects of SOA is to identify markers for SOA sources and also for allergens and other inducers of health problems. Reactions occurring at the surfaces of SOA, such
as nitration, should be studied in relation to these possible health impacts. Studies that combine bio assays and such markers could shed new light on the topic.

*Participation of organics in new particle formation – Several studies strongly suggest that biogenic VOCs may be involved in new particle formation in forested environments. This phenomenon has important implications for climate-biosphere interactions, and should be further investigated, including the application of recently developed nanoparticle composition techniques such as NAMS and TDCIMS in forested areas.*

*Optical properties – The optical properties (scattering and absorption) of fresh and aged SOA (pure or in combination with other species) are not well constrained, hindering assessment of their possible contribution to the aerosol direct effect. New sensitive techniques should be sought to measure these missing properties.*

*Cloud formation and properties – The complex interaction and influence of SOA in the formation of clouds could be essential. One crucial point is to establish the influence of SOA on the kinetics and thermodynamics of water uptake. In addition, ice nucleation and evaporation of water are two processes where the complex mixtures of SOA are expected to have an impact.*

## 7 Abbreviations

<table><tr><td>AMS</td><td>Aerosol Mass Spectrometry</td></tr><tr><td>APCI</td><td>Atmospheric Pressure Chemical Ionization</td></tr><tr><td>ASOA</td><td>Anthropogenic Secondary Organic Aerosol</td></tr><tr><td>ATOFMS</td><td>Aerosol Time-of-Flight Mass Spectrometry</td></tr><tr><td>BB</td><td>Biomass Burning</td></tr><tr><td>BSOA</td><td>Biogenic Secondary Organic Aerosol</td></tr><tr><td>BSOC</td><td>Biogenic Secondary Organic Carbon</td></tr><tr><td>BVOC</td><td>Biogenic Volatile Organic Compound</td></tr><tr><td>CACM</td><td>Caltech Atmospheric Chemistry Mechanism</td></tr><tr><td>CCN</td><td>Cloud condensation Nuclei</td></tr><tr><td>CE</td><td>Capillary Electrophoresis</td></tr><tr><td>CI</td><td>Chemical Ionization</td></tr><tr><td>CIMS</td><td>Chemical Ionization Mass Spectrometry</td></tr><tr><td>CMB</td><td>Chemical Mass Balance</td></tr><tr><td>DMA</td><td>Differential Mobility Analyzer</td></tr><tr><td>DRH</td><td>Deliquescence Relative Humidity</td></tr><tr><td>EC</td><td>Elemental Carbon</td></tr><tr><td>EDB</td><td>Electrodynamic Balance</td></tr><tr><td>EI</td><td>Electron Ionization</td></tr><tr><td>EMEP</td><td>European Monitoring and Evaluation Programme</td></tr><tr><td>ERH</td><td>Efflorescence Relative Humidity</td></tr><tr><td>ESI</td><td>Electrospray Ionization</td></tr><tr><td>FTICRMS</td><td>Fourier Transform Ion Cyclotron Resonance Mass Spectrometry</td></tr><tr><td>FTIR</td><td>Fourier Transform Infrared Spectroscopy</td></tr><tr><td>GC</td><td>Gas Chromatography</td></tr></table>

<table><tr><td>GC/MS</td><td>Gas Chromatography/ Mass Spectrometry</td></tr><tr><td>GF</td><td>Growth Factor</td></tr><tr><td>HOA</td><td>Hydrocarbon-like Organic Aerosol</td></tr><tr><td>HPLC</td><td>High Performance Liquid Chromatography</td></tr><tr><td>HR</td><td>High Resolution</td></tr><tr><td>HRMS</td><td>High Resolution Mass Spectrometry</td></tr><tr><td>HTDMA</td><td>Hygroscopicity Tandem Differential Mobility Analyzer</td></tr><tr><td>HULIS</td><td>Humic-like Substances</td></tr><tr><td>IC</td><td>Ion Chromatography</td></tr><tr><td>ITMS</td><td>Ion Trap Mass Spectrometry</td></tr><tr><td>LC</td><td>Liquid Chromatography</td></tr><tr><td>LC/MS</td><td>Liquid Chromatography/ Mass Spectrometry</td></tr><tr><td>LDI-MS</td><td>Laser Desorption Ionization- Mass Spectrometry</td></tr><tr><td>MALDI</td><td>Matrix-Assisted Laser Desorption Ionization</td></tr><tr><td>MS</td><td>Mass Spectrometry</td></tr><tr><td>MW</td><td>Molecular Weight</td></tr><tr><td>NAMS</td><td>Nano Aerosol Mass Spectrometer</td></tr><tr><td>NMR</td><td>Nuclear Magnetic Resonance</td></tr><tr><td>OA</td><td>Organic Aerosol</td></tr><tr><td>OC</td><td>Organic Carbon</td></tr><tr><td>OM</td><td>Organic Matter</td></tr><tr><td>OOA</td><td>Oxygenated Organic Aerosol</td></tr><tr><td>PAN</td><td>Peroxyacyl Nitrate</td></tr><tr><td>PILS</td><td>Particle into Liquid Sampler</td></tr><tr><td>PIXE</td><td>Particle-Induced X-ray Emission spectrometry</td></tr><tr><td>PM<sub>1</sub>, PM<sub>2.5</sub>, PM<sub>10</sub></td><td>Particulate Matter with an aerodynamic diameter &lt;1, 2.5 and 10 µm, respectively</td></tr><tr><td>POA</td><td>Primary Organic Aerosol</td></tr><tr><td>PTR/MS</td><td>Proton Transfer Reaction/ Mass Spectrometry</td></tr><tr><td>Q-TOF</td><td>Quadrupole-Time-of-Flight</td></tr><tr><td>RH</td><td>Relative Humidity</td></tr><tr><td>SCI</td><td>Stabilized Criegee Intermediate</td></tr><tr><td>SEC</td><td>Size-Exclusion Chromatography</td></tr><tr><td>SFA</td><td>Size-Fractionated Aerosol</td></tr><tr><td>SOA</td><td>Secondary Organic Aerosol</td></tr><tr><td>SOC</td><td>Secondary Organic Carbon</td></tr><tr><td>SRFA</td><td>Suwannee River Fulvic Acid</td></tr><tr><td>TA</td><td>Total Aerosol</td></tr><tr><td>TDCIMS</td><td>Thermal Desorption Chemical Ionization Mass Spectrometry</td></tr><tr><td>TMI</td><td>Transition Metal Ion</td></tr><tr><td>TOF</td><td>Time-of-Flight</td></tr><tr><td>UNIFAC</td><td>Universal Functional Activity Coefficient</td></tr></table>
<table><tr><td>VBS</td><td>Volatility Basis Set</td></tr><tr><td>VOC</td><td>Volatile Organic Compound</td></tr><tr><td>XRF</td><td>X-ray Fluorescence</td></tr><tr><td>WIOC</td><td>Water Insoluble Organic Compounds</td></tr><tr><td>WIOM</td><td>Water Insoluble Organic Matter</td></tr><tr><td>WSOC</td><td>Water Soluble Organic Compounds</td></tr><tr><td>WSOM</td><td>Water Soluble Organic Matter</td></tr></table>

*Acknowledgements.* This review is the result of presentations and discussions during the joint VOCBAS-INTROP conference on Biogenic Volatile Organic Compounds: Sources and Fates in a Changing World. The authors would like to thank M. Staudt and his colleagues at the Centre for Evolutionary and Functional Ecology in Montpellier, France, for hosting the event. Financial support from the European Science Foundation INTROP programme is gratefully acknowledged. The authors would also like to acknowledge funding received from; the European Commission (EUROCHAMP, RII3-CT-2004-505968; EUCAARI, 036833-2; POLYSOA, 12709; Marie Curie postdoctoral fellowship to R.S.); European Monitoring and Evaluation Programme (EMEP); the Swedish Research Council Formas (contract 214-2006-1204); Science Foundation Ireland; the Swiss National Science Foundation; the Israel Science Foundation (grants 1527/07 and 196/08) and the Helen and Martin Kimmel Award for Innovative Investigation; Belgian Federal Science Policy Office (BIOSOL project); the Fund for Scientific Research – Flanders (FWO); DOE BER/ASP (DEFG0208ER64627); the UK Department for Environment, Food and Rural Affairs (contract AQ0704); NOAA OGP (NA08OAR4310565); US EPA (STAR R833746, RD-83374901); DOE (DEFG02-05ER63983); US National Science Foundation (ATM-0703914).

Edited by: R. MacKenzie

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