《环境物理化学》教学案例：吸湿增长与表面现象 The effect of physical and chemical aerosol properties on warm cloud droplet activation

Atmos. Chem. Phys., 6, 2593-2649, 2006 www.atmos-chem-phys.net/6/2593/2006 Atmospheri C Author(s)2006. This work is licensed Chemistry under a Creative Commons License and Physics The effect of physical and chemical aerosol properties on warm cloud droplet activation G. MeFiggans', P. Artaxo, U. Baltensperger, H. Coe, M. C. Facchini, G. Feingold, S. Fuzzi, M. Gysel 3, A. Laaksonen, U. Lohmann, T. F Mentel, D. M. Murphy, CD.O'Dowd0, J.R. Snider,and E Weingartner I Atmospheric Sciences Group, SEAES, University of Manchester, P.O. Box 88, Manchester, M60 1QD, UK iNstituto de Fisica, Universidade de Sao Paulo, Rua do Matao, TravessaR, 187, CEP 05508-900 Sao Paulo, Brazil SPaul Scherrer Institut, Labor fur Atmospharenchemie, 5232 Villigen PSI,Switzerland 4Istituto di Scienze dell'Atmosfera e del Clima, CNR, 40129 Bologna, Italy NOAA Environmental Technology Laboratory, 325 Broadway, Boulder, Colorado 80305, USA b Department of Applied Physics, University of Kuopio, P.O. Box 1627, 70211 Kuopio, Finland "Institute for Atmospheric and Climate Science, Schafmattstr. 30, ETH Zurich, 8093 Zurich, Switzerland 8Forschungszentrum Julich GmbH, ICG-II: Troposphare, 52425 Julich, Germany 9NOAA Aeronomy Laboratory, 325 Broadway, Boulder, Colorado 80305, USA 10 Department of Physics, National University of Ireland, Galway, Ireland I University of Wyoming, Department of Atmospheric Science, Laramie, WY82071,USA Received: 7 June 2005- Published in Atmos. Chem. Phys. Discuss: 12 September 2005 Revised: 13 January 2006-Accepted: 29 May 2006- Published: 5 July 2006 Abstract. The effects of atmospheric aerosol on climate coming shortwave radiation and absorb outgoing longwave forcing may be very substantial but are quantified poorly at radiation(the"aerosol direct effect" Mc Cormick and lud- present; in particular, the effects of aerosols on cloud radia- wig, 1967, Charlson and Pilat, 1969; Hay wood and Boucher, tive properties, or theindirect effects"are credited with the 2000, Charlson et al., 1992). Aerosol particles that act as greatest range of uncertainty amongst the known causes of cloud condensation nuclei hanges in droplet number radiative forcing. This manuscript explores the effects that affecting the albedo and persistence of clouds; these are re- ne composition and properties of atmospheric aerosol can spectively termed theTwomey(first) and the cloud lifetime have on the activation of droplets in warm clouds, so poten- (second) aerosol indirect effects"(Warner, 1968: Twomey tially influencing the magnitude of the indirect effect. The 1974; Albrecht, 1989; Liou and Ou, 1989; Lohmann and effects of size, composition, mixing state and various derived Feichter, 2005). The Twomey effect refers to the aerosol properties are assessed and a range of these properties pro- induced increase in cloud number droplet for vided by atmospheric measurements in a variety of locations uid water content whereas the cloud lifetime effect is a result is briefly reviewed. The suitability of a range of process-level of the reduced precipitation efficiency of the more numer- descriptions to capture these aerosol effects is investigated ous smaller cloud droplets. Absorbing aerosol has also been by assessment of their sensitivities to uncertainties in aerosol shown to cause local warming of the atmosphere, which may properties and by their performance in closure studies. The result in stabilisation of the sub-cloud layer, and large-scale treatment of these effects within global models is reviewed burn-off of clouds. This has been termed the"semi-direct and suggestions for future investigations are made. effect(Fischer and Grassl, 1975; Hansen et al. 1997, Ack erman et al 2000, Johnson et al., 2004) The aerosol indirect effect is currently credited with the 1 Introduction greatest range of uncertainty amongst the known causes of radiative forcing(Ramaswamy et al., 2001); this range Aerosol particles affect the radiation balance of the atmo- stated as being around 4 times the uncertainty associated with sphere in a number of ways. They scatter and absorb in- forcing by radiatively active gases. That its absolute magni- tude may be comparable to that from radiatively active gases Correspondence to: G. Mcl necessitates greatly improved quantification of the factors af- (g. mcfiggans(@ manchester.a fecting and contributing to the aerosol indirect effect Published by Copernicus GmbH on behalf of the European Geosciences Union

Atmos. Chem. Phys., 6, 2593–2649, 2006 www.atmos-chem-phys.net/6/2593/2006/ © Author(s) 2006. This work is licensed under a Creative Commons License. Atmospheric Chemistry and Physics The effect of physical and chemical aerosol properties on warm cloud droplet activation G. McFiggans1 , P. Artaxo2 , U. Baltensperger3 , H. Coe1 , M. C. Facchini4 , G. Feingold5 , S. Fuzzi4 , M. Gysel1,3 , A. Laaksonen6 , U. Lohmann7 , T. F. Mentel8 , D. M. Murphy9 , C. D. O’Dowd10, J. R. Snider11, and E. Weingartner3 1Atmospheric Sciences Group, SEAES, University of Manchester, P.O. Box 88, Manchester, M60 1QD, UK 2 Instituto de Fisica, Universidade de Sao Paulo, Rua do Matao, Travessa R, 187, CEP 05508-900 Sao Paulo, Brazil 3Paul Scherrer Institut, Labor fur Atmosph ¨ arenchemie, 5232 Villigen PSI, Switzerland ¨ 4 Istituto di Scienze dell’Atmosfera e del Clima, CNR, 40129 Bologna, Italy 5NOAA Environmental Technology Laboratory, 325 Broadway, Boulder, Colorado 80305, USA 6Department of Applied Physics, University of Kuopio, P.O. Box 1627, 70211 Kuopio, Finland 7 Institute for Atmospheric and Climate Science, Schafmattstr. 30, ETH Zurich, 8093 Zurich, Switzerland 8Forschungszentrum Julich GmbH, ICG-II: Troposph ¨ are, 52425 J ¨ ulich, Germany ¨ 9NOAA Aeronomy Laboratory, 325 Broadway, Boulder, Colorado 80305, USA 10Department of Physics, National University of Ireland, Galway, Ireland 11University of Wyoming, Department of Atmospheric Science, Laramie, WY 82071, USA Received: 7 June 2005 – Published in Atmos. Chem. Phys. Discuss.: 12 September 2005 Revised: 13 January 2006 – Accepted: 29 May 2006 – Published: 5 July 2006 Abstract. The effects of atmospheric aerosol on climate forcing may be very substantial but are quantified poorly at present; in particular, the effects of aerosols on cloud radia￾tive properties, or the “indirect effects” are credited with the greatest range of uncertainty amongst the known causes of radiative forcing. This manuscript explores the effects that the composition and properties of atmospheric aerosol can have on the activation of droplets in warm clouds, so poten￾tially influencing the magnitude of the indirect effect. The effects of size, composition, mixing state and various derived properties are assessed and a range of these properties pro￾vided by atmospheric measurements in a variety of locations is briefly reviewed. The suitability of a range of process-level descriptions to capture these aerosol effects is investigated by assessment of their sensitivities to uncertainties in aerosol properties and by their performance in closure studies. The treatment of these effects within global models is reviewed and suggestions for future investigations are made. 1 Introduction Aerosol particles affect the radiation balance of the atmo￾sphere in a number of ways. They scatter and absorb in￾Correspondence to: G. McFiggans (g.mcfiggans@manchester.ac.uk) coming shortwave radiation and absorb outgoing longwave radiation (the “aerosol direct effect” McCormick and Lud￾wig, 1967; Charlson and Pilat, 1969; Haywood and Boucher, 2000, Charlson et al., 1992). Aerosol particles that act as cloud condensation nuclei cause changes in droplet number affecting the albedo and persistence of clouds; these are re￾spectively termed the “Twomey (first) and the cloud lifetime (second) aerosol indirect effects” (Warner, 1968; Twomey, 1974; Albrecht, 1989; Liou and Ou, 1989; Lohmann and Feichter, 2005). The Twomey effect refers to the aerosol￾induced increase in cloud number droplet for a constant liq￾uid water content whereas the cloud lifetime effect is a result of the reduced precipitation efficiency of the more numere￾ous smaller cloud droplets. Absorbing aerosol has also been shown to cause local warming of the atmosphere, which may result in stabilisation of the sub-cloud layer, and large-scale burn-off of clouds. This has been termed the “semi-direct effect” (Fischer and Grassl, 1975; Hansen et al., 1997; Ack￾erman et al., 2000; Johnson et al., 2004). The aerosol indirect effect is currently credited with the greatest range of uncertainty amongst the known causes of radiative forcing (Ramaswamy et al., 2001); this range is stated as being around 4 times the uncertainty associated with forcing by radiatively active gases. That its absolute magni￾tude may be comparable to that from radiatively active gases necessitates greatly improved quantification of the factors af￾fecting and contributing to the aerosol indirect effect. Published by Copernicus GmbH on behalf of the European Geosciences Union

2594 G. McFiggans et al. aerosol effects on warm cloud activation The primary tool at our disposal for assessing aerosol ef- fluence(certainly in the Northern Hemisphere)-and cloud fects on clouds and future climate states is the general circu- formation in these regions may be particularly sensitive to lation model (GCM). These models are required to describe such input. In addition, the variety of natural primary and a large number of coupled processes which, because of the secondary sources can also lead to a complexity, not broadly enormous range of spatial and temporal scales that need to appreciated until recent years largely resulting from the nu- be addressed, and the associated computational burden, must merous organic species contributing to the aerosol burden to a large extent be simplified (e.g. Lohmann and Feichter, (Kanakidou et al., 2005). More obviously polluted air suc 2005 ). The difficulty in meaningfully incorporating a re- as that originating from densely-populated continental alistic description of aerosol-cloud interactions into GCMs gions(or regions otherwise influenced by human activity, e.g should not be underestimated. Large scale models have dif- biomass burning) are frequently heavily laden with an exter- ficulty in representing convection and clouds, which are typ- nal mixture of internally-mixed multicomponent aerosol dis- ically parameterised as subgrid processes. Therefore, their tributions(see Sect. 3.2.3) ability to represent the macroscale features of clouds(spatial It might be expected that cloud droplets forming in ris- coverage,depth, hydrometeor content )is itself a challenge ing air parcels containing such burdens of multicomponent In addition, they cannot represent the magnitude of the up- aerosol may not behave in the same way as those formed by draught velocities which may have an important bearing on the activation of simple salt particles. A range of techniques the local microphysical cloud properties(droplet number, ef- have been used to describe how aerosol particles behave as fective radius etc. ) The cloud-scale updraught velocity rele- relative humidity approaches and then exceeds saturation. A vant for cloud droplet activation is usually approximated, ei- summary of the fundamental theoretical approaches used to her by assuming a Gaussian distribution or relating subgrid- investigate droplet activation is presented, ranging from rel- scale fluctuations to the turbulent kinetic energy( Ghan et al atively well-established conventional application of Kohler 1997; Lohmann et al., 1999). It is not the intent of this arti- theory to recently developed theoretical and laboratory-based cle to investigate the broad question of dynamical cloud sys- extensions reflecting the increased aerosol complexity(Shul- tems, their effect on radiation and the incorporation of these, man et al. 1996: Kulmala et al., 1997). The effects of such and other coupled effects into large-scale models. Neglect extensions are discussed and the relative importance under a of these problems is not a reflection of their relative impor- range of conditions assessed( Sect. 4) tance in cloud radiative forcing. The main purpose of this There have been recent attempts to reconcile field obser- review is to identify one particular and important aspect of the aerosol indirect effect, namely, the properties of aerosol vations of aerosol composition with those of derived proper ties related to cloud activation. Such studies may be broadly which dominate their activation in warm clouds. This aspect categorised as"hygroscopic growth closure","CCN closure" of the indirect effect is accessible to investigation by obser and"droplet number closure"investigations. The difficulties tions alone. For example, the relationships between droplet associated with each level of closure are different and the number (Nd) and aerosol number(Na)and between effec- droplet number closure is significantly more difficult. An ap- tive droplet radius (refr)and Na may both be directly probed Should all dynamical considerations remain relatively con- praisal of these difficulties and the current status of progress stant, such observations can be used to derive relationships in such studies are reviewed in Sect. 5 between the aerosol distribution and cloud distribution prop- This paper therefore aims to examine the state-of-the- science to establish i) the dominant characteristics of the at- This article will review the currently-available observa- mospheric aerosol(in so far as they may influence cloud ac- tional evidence for the compositional complexity of atmo- tivation) n) which aerosol properties should be most accu spheric aerosol and the derived properties of their size and rately captured to investigate cloud formation in)how these composition distributions that are thought to affect their abil- properties can be represented at a detailed process level iv) ity to act as cloud condensation nuclei(CCN). An increas- whether current representations of these properties in larger ing body of evidence suggests that the complexity of atmo- scale models can adequately capture the important behaviour spheric aerosol may preclude realistic treatment of cloud for- of the aerosol and v)how improved representations may be mation using the levels of simplification incorporated into developed to investigate aerosol effects on cloud formation. all large-scale models(and even most process-level descrip- Suggestions of which properties should be captured to enable tions). The frequent assumptions of an externally mixed accurate representation of aerosol effects on cloud formation organic salt aerosol appear not to be applicable even in the follow from this examination most pristine regions. Even this description is more co A final note on the scope of this article: whilst the effects plex than that employed in many climate models( Wilson of atmospheric aerosol properties on warm cloud activation et al., 2001; Gong and Barrie, 2003). Long-range transport are subject to significant uncertainties, those surrounding the of polluted plumes lofted into the free troposphere followed roles of aerosol particles as ice nuclei (IN) are much greater by sporadic re-entrainment( Clarke et al., 1999)ensures that still. The article will therefore be limited to warm clouds and remote regions are not always free from anthropogenic in- will not attempt to consider mixed-phase or cold clouds tmos.Chem.Phys,6,2593-2649,2006 www.atmos-chem-phys.net/6/2593/2006/

2594 G. McFiggans et al.: Aerosol effects on warm cloud activation The primary tool at our disposal for assessing aerosol ef￾fects on clouds and future climate states is the general circu￾lation model (GCM). These models are required to describe a large number of coupled processes which, because of the enormous range of spatial and temporal scales that need to be addressed, and the associated computational burden, must to a large extent be simplified (e.g. Lohmann and Feichter, 2005). The difficulty in meaningfully incorporating a re￾alistic description of aerosol-cloud interactions into GCMs should not be underestimated. Large scale models have dif- ficulty in representing convection and clouds, which are typ￾ically parameterised as subgrid processes. Therefore, their ability to represent the macroscale features of clouds (spatial coverage, depth, hydrometeor content) is itself a challenge. In addition, they cannot represent the magnitude of the up￾draught velocities which may have an important bearing on the local microphysical cloud properties (droplet number, ef￾fective radius etc.). The cloud-scale updraught velocity rele￾vant for cloud droplet activation is usually approximated, ei￾ther by assuming a Gaussian distribution or relating subgrid￾scale fluctuations to the turbulent kinetic energy (Ghan et al., 1997; Lohmann et al., 1999). It is not the intent of this arti￾cle to investigate the broad question of dynamical cloud sys￾tems, their effect on radiation and the incorporation of these, and other coupled effects into large-scale models. Neglect of these problems is not a reflection of their relative impor￾tance in cloud radiative forcing. The main purpose of this review is to identify one particular and important aspect of the aerosol indirect effect, namely, the properties of aerosol which dominate their activation in warm clouds. This aspect of the indirect effect is accessible to investigation by observa￾tions alone. For example, the relationships between droplet number (Nd ) and aerosol number (Na) and between effec￾tive droplet radius (reff) and Na may both be directly probed. Should all dynamical considerations remain relatively con￾stant, such observations can be used to derive relationships between the aerosol distribution and cloud distribution prop￾erties. This article will review the currently-available observa￾tional evidence for the compositional complexity of atmo￾spheric aerosol and the derived properties of their size and composition distributions that are thought to affect their abil￾ity to act as cloud condensation nuclei (CCN). An increas￾ing body of evidence suggests that the complexity of atmo￾spheric aerosol may preclude realistic treatment of cloud for￾mation using the levels of simplification incorporated into all large-scale models (and even most process-level descrip￾tions). The frequent assumptions of an externally mixed in￾organic salt aerosol appear not to be applicable even in the most pristine regions. Even this description is more com￾plex than that employed in many climate models (Wilson et al., 2001; Gong and Barrie, 2003). Long-range transport of polluted plumes lofted into the free troposphere followed by sporadic re-entrainment (Clarke et al., 1999) ensures that remote regions are not always free from anthropogenic in- fluence (certainly in the Northern Hemisphere) – and cloud formation in these regions may be particularly sensitive to such input. In addition, the variety of natural primary and secondary sources can also lead to a complexity, not broadly appreciated until recent years largely resulting from the nu￾merous organic species contributing to the aerosol burden (Kanakidou et al., 2005). More obviously polluted air such as that originating from densely-populated continental re￾gions (or regions otherwise influenced by human activity, e.g. biomass burning) are frequently heavily laden with an exter￾nal mixture of internally-mixed multicomponent aerosol dis￾tributions (see Sect. 3.2.3). It might be expected that cloud droplets forming in ris￾ing air parcels containing such burdens of multicomponent aerosol may not behave in the same way as those formed by the activation of simple salt particles. A range of techniques have been used to describe how aerosol particles behave as relative humidity approaches and then exceeds saturation. A summary of the fundamental theoretical approaches used to investigate droplet activation is presented, ranging from rel￾atively well-established conventional application of Kohler ¨ theory to recently developed theoretical and laboratory-based extensions reflecting the increased aerosol complexity (Shul￾man et al., 1996; Kulmala et al., 1997). The effects of such extensions are discussed and the relative importance under a range of conditions assessed (Sect. 4). There have been recent attempts to reconcile field obser￾vations of aerosol composition with those of derived proper￾ties related to cloud activation. Such studies may be broadly categorised as “hygroscopic growth closure”, “CCN closure” and “droplet number closure” investigations. The difficulties associated with each level of closure are different and the droplet number closure is significantly more difficult. An ap￾praisal of these difficulties and the current status of progress in such studies are reviewed in Sect. 5. This paper therefore aims to examine the state-of-the￾science to establish i) the dominant characteristics of the at￾mospheric aerosol (in so far as they may influence cloud ac￾tivation) ii) which aerosol properties should be most accu￾rately captured to investigate cloud formation iii) how these properties can be represented at a detailed process level iv) whether current representations of these properties in larger scale models can adequately capture the important behaviour of the aerosol and v) how improved representations may be developed to investigate aerosol effects on cloud formation. Suggestions of which properties should be captured to enable accurate representation of aerosol effects on cloud formation follow from this examination. A final note on the scope of this article: whilst the effects of atmospheric aerosol properties on warm cloud activation are subject to significant uncertainties, those surrounding the roles of aerosol particles as ice nuclei (IN) are much greater still. The article will therefore be limited to warm clouds and will not attempt to consider mixed-phase or cold clouds. Atmos. Chem. Phys., 6, 2593–2649, 2006 www.atmos-chem-phys.net/6/2593/2006/

G. McFiggans et al. Aerosol effects on warm cloud activation 2595 2 Theory of activation of aerosol particles in warm activating particles which may be more or less accurate de pending on the supersaturation, there are numerical approxi- mations such as that associated with the Taylor series expan- The description of the equilibrium size of a droplet with wa- sion of the exponential which limit the range of applicability ter saturation ratio, founded on the early work of Kohler of Eq (2). Figure 1 shows the contribution of the Kelv (1936), is now well-established and can be readily derived and Raoult terms to the activation behaviour of a 200 nm dry from the Clausius-Clapeyron equation modified to give a diameter ammonium sulphate particle general equilibrium relation between an aqueous salt sol This form of the expression shows a single characteris- tion droplet and water vapour tic maximum in supersaturation for a given dry composition and size, known as the critical supersaturation, Sc, associated =awexpKe = awexp with a unique size, denoted the critical radius, rc or diame- RTr (1) ter, De. Using the simplified expression(2), solutions for the critical quantities are the vapour pressure of wa es is the saturation vapour pressure of water, 3B12 (e/es=S, is known as the saturation ratio), A aw is the water activity Ke is the Kelvin factor Ww is the partial molar volume of water, S 27B sol/v is the surface tension of the solution at the composition of the droplet, R is the universal gas constant, For an increasing environmental value of s below Sc there T is the droplet temperature, is a unique equilibrium droplet size. Once the droplet grows is the particle radius beyond its critical size (i.e. as the environmental S increases above Sc) the droplet will exhibit unimpeded growth unless the environmental S reduces below the equilibrium value of This form of the Kohler equation is not generally accessi- S at the instantaneous value of r. In this case, with no fur- Yau, 1989; Pruppacher and Klett, 1997; Chylek and Wong, ther change in S, the droplet will evaporate to its sub-critical 1998: Seinfeld and Pandis, 1998) provide standard deriva- equilibrium size tions to yield the simplified form of the Kohler equation The Kohler expression can be envisaged as the compet tion between the two expressions of component properties a B determining activation of particles; the curvature term and (2) the solute term. The solute terms depends first on the number of solution molecules and then on the dissociation of these where A==dule and B= where v is the num- molecules. The effect can be illustrated for two frequently as- er of dissociated ions per so cule, ms is thethe se sumed cloud condensation nuclei types: ammonium sulphate lute mass and subscripts s and w relate to solute and water and sodium chloride.(NH4)2SO4 has a molecular weight properties, respectively. The term in A is denoted the Kelvin of 132 gMol- while that of NaCl is 58.5 gMol-1. Thus, in or curvature term and that in b. the raoult or solute term the absence of dissociation, a given mass of Nacl in solu- This latter form of the equation assumes that the droplet tion would yield 2. 26 times more dissolved molecules than behaves ideally, i.e. that the practical osmotic coefficient of (NH4)2SO4. Assuming full dissociation(infinite dilution) the salt, =l, where (NH4) SO4 yields 3 ions while NaCl yields 2, so the net effect of the molecular mass and dissociation is that nacl is 2. 26/1.5=1.5 times more active than(NH4)2SO4 for the ( same dry mass of particle(the Se ratio is around 1.22 due to the square root dependence). This is illustrated in Fig. 2 and that the number of ions in solution is independent of so- where the peak supersaturation is plotted versus dry diameter lution concentration. Equation(2)further assumes that the for particles comprising each electrolyte. This figure directly solute is completely soluble and it implicitly follows that the illustrates the significant differences in the critical supersat- solution droplet is assumed homogeneous-that the compo- uration as a function of both the chemical composition and sition is independent of distance from droplet centre. It is dry size of a particle(raoult and Kelvin effect further assumed that the surface tension and density of the The atmospheric aerosol does not solely com growing droplet are equal to those of water. In addition to the pended completely soluble inorganic salt solution assumptions relating to physico-chemical properties of the A modification to the Raoult term was reported www.atmos-chem-phys.net/6/2593/2006/ Atmos. Chem. Phys., 6, 2593-2649, 2006

G. McFiggans et al.: Aerosol effects on warm cloud activation 2595 2 Theory of activation of aerosol particles in warm clouds The description of the equilibrium size of a droplet with wa￾ter saturation ratio, founded on the early work of Kohler ¨ (1936), is now well-established and can be readily derived from the Clausius-Clapeyron equation modified to give a general equilibrium relation between an aqueous salt solu￾tion droplet and water vapour: e es = awexpKe = awexp 2vwσsol/v RT r  (1) where e is the vapour pressure of water, es is the saturation vapour pressure of water, (e/es=S, is known as the saturation ratio), aw is the water activity, Ke is the Kelvin factor, vw is the partial molar volume of water, σsol/v is the surface tension of the solution at the composition of the droplet, R is the universal gas constant, T is the droplet temperature, r is the particle radius. This form of the Kohler equation is not generally accessi- ¨ ble to analytical solution and a number of texts (Rogers and Yau, 1989; Pruppacher and Klett, 1997; Chylek and Wong ´ , 1998; Seinfeld and Pandis, 1998) provide standard deriva￾tions to yield the simplified form of the Kohler equation: ¨ S = e es ≈ 1 + A r − B r 3 (2) where A= 2Mwσw/v RT ρw and B= νmsMw Ms(4/3πρw) , where ν is the num￾ber of dissociated ions per solute molecule, ms is the the so￾lute mass and subscripts s and w relate to solute and water properties, respectively. The term in A is denoted the Kelvin or curvature term, and that in B, the Raoult or solute term. This latter form of the equation assumes that the droplet behaves ideally, i.e. that the practical osmotic coefficient of the salt, φ=1, where aw = exp − νns nw φs  (3) and that the number of ions in solution is independent of so￾lution concentration. Equation (2) further assumes that the solute is completely soluble and it implicitly follows that the solution droplet is assumed homogeneous – that the compo￾sition is independent of distance from droplet centre. It is further assumed that the surface tension and density of the growing droplet are equal to those of water. In addition to the assumptions relating to physico-chemical properties of the activating particles which may be more or less accurate de￾pending on the supersaturation, there are numerical approxi￾mations such as that associated with the Taylor series expan￾sion of the exponential which limit the range of applicability of Eq. (2). Figure 1 shows the contribution of the Kelvin and Raoult terms to the activation behaviour of a 200 nm dry diameter ammonium sulphate particle. This form of the expression shows a single characteris￾tic maximum in supersaturation for a given dry composition and size, known as the critical supersaturation, Sc, associated with a unique size, denoted the critical radius, rc or diame￾ter, Dc. Using the simplified expression (2), the analytical solutions for the critical quantities are: rc =  3B A 1/2 (4) Sc = 4A3 27B !1/2 (5) For an increasing environmental value of S below Sc there is a unique equilibrium droplet size. Once the droplet grows beyond its critical size (i.e. as the environmental S increases above Sc) the droplet will exhibit unimpeded growth unless the environmental S reduces below the equilibrium value of S at the instantaneous value of r. In this case, with no fur￾ther change in S, the droplet will evaporate to its sub-critical equilibrium size. The Kohler expression can be envisaged as the competi- ¨ tion between the two expressions of component properties determining activation of particles; the curvature term and the solute term. The solute terms depends first on the number of solution molecules and then on the dissociation of these molecules. The effect can be illustrated for two frequently as￾sumed cloud condensation nuclei types: ammonium sulphate and sodium chloride. (NH4)2SO4 has a molecular weight of 132 gMol−1 while that of NaCl is 58.5 gMol−1 . Thus, in the absence of dissociation, a given mass of NaCl in solu￾tion would yield 2.26 times more dissolved molecules than (NH4)2SO4. Assuming full dissociation (infinite dilution), (NH4)2SO4 yields 3 ions while NaCl yields 2, so the net effect of the molecular mass and dissociation is that NaCl is 2.26/1.5=1.5 times more active than (NH4)2SO4 for the same dry mass of particle (the Sc ratio is around 1.22 due to the square root dependence). This is illustrated in Fig. 2 where the peak supersaturation is plotted versus dry diameter for particles comprising each electrolyte. This figure directly illustrates the significant differences in the critical supersat￾uration as a function of both the chemical composition and dry size of a particle (Raoult and Kelvin effects). The atmospheric aerosol does not solely comprise sus￾pended completely soluble inorganic salt solution particles. A modification to the Raoult term was reported by Hanel ¨ www.atmos-chem-phys.net/6/2593/2006/ Atmos. Chem. Phys., 6, 2593–2649, 2006

2596 G. McFiggans et al. aerosol effects on warm cloud activation 0.06 Raoult term 0.04 9 0.04 0° plet radius, ,, um Fig. 1. The Kohler equation can be envisaged as the competition between the curvature(Kelvin) and solute(Raoult)terms fractions. a discussion of more rigorous treatments of lim- NH42504 ited subility is presented in Sect. 4.1 3 The composition and properties of atmospheric relevant to the indirect effect Suspended particulate material in the atmosphere is highly variable. Atmospheric aerosol particles cover four or five decades in size from a few nanometers to several tens or even hundreds of microns and the loading and composition are ex- tremely source and location dependent. Studies of cloud for- mation invariably rely on a simplified model of input aerosol composition distributions. The specific description is depen dent on the particular atmospheric scenario. This section Dry Diameter (um) presents an overview of the characteristics of atmospheric aerosol as they relate to cloud droplet activation. Fig. 2. Critical supersaturation as a function of dry size for NacI d(NH4)) SO4 particles 3.1 Characteristic size and composition of atmospheric (1976)to allow explicit consideration of internally mixed 3.1.1 Size distributions of ambient aeros completely insoluble inclusions It can be seen from Figs. 2 and 3 that the activation of aerosol B=Evms M particles is strongly dependent on the dry size. For any given (6) composition and supersaturation(which, around cloud base where E is the soluble mass fraction of the dry particle ticle activates is solely dependent on its dry size. At constant Figure 3 shows the form of activation curves for a range updraught velocity, a distribution of such particles of vary of particles of varying dry diameter and initial soluble mass ing sizes will activate if their corresponding critical radius is tmos.Chem.Phys,6,2593-2649,2006 www.atmos-chem-phys.net/6/2593/2006/

2596 G. McFiggans et al.: Aerosol effects on warm cloud activation 10−1 100 101 102 −0.04 −0.02 0 0.02 0.04 0.06 wet droplet radius, r, µm Supersaturation % = 100 x (S −1) Kelvin term Raoult term Total S c r c Fig. 1. The Kohler equation can be envisaged as the competition between the curvature (Kelvin) and solute (Raoult) terms. ¨ Fig. 2. Critical supersaturation as a function of dry size for NaCl and (NH4)2SO4 particles. (1976) to allow explicit consideration of internally mixed completely insoluble inclusions: B = ενmsMw Ms( 4/3πρw) (6) where ε is the soluble mass fraction of the dry particle. Figure 3 shows the form of activation curves for a range of particles of varying dry diameter and initial soluble mass fractions. A discussion of more rigorous treatments of lim￾ited component solubility is presented in Sect. 4.1. 3 The composition and properties of atmospheric aerosol relevant to the indirect effect Suspended particulate material in the atmosphere is highly variable. Atmospheric aerosol particles cover four or five decades in size from a few nanometers to several tens or even hundreds of microns and the loading and composition are ex￾tremely source and location dependent. Studies of cloud for￾mation invariably rely on a simplified model of input aerosol composition distributions. The specific description is depen￾dent on the particular atmospheric scenario. This section presents an overview of the characteristics of atmospheric aerosol as they relate to cloud droplet activation. 3.1 Characteristic size and composition of atmospheric aerosol 3.1.1 Size distributions of ambient aerosol It can be seen from Figs. 2 and 3 that the activation of aerosol particles is strongly dependent on the dry size. For any given composition and supersaturation (which, around cloud base, is directly proportional to updraught velocity), whether a par￾ticle activates is solely dependent on its dry size. At constant updraught velocity, a distribution of such particles of vary￾ing sizes will activate if their corresponding critical radius is Atmos. Chem. Phys., 6, 2593–2649, 2006 www.atmos-chem-phys.net/6/2593/2006/

G. McFiggans et al. Aerosol effects on warm cloud activation 2597 1.004 1 1.002 1001 50nmNH小28O4 097 200 nm(NH ).so 20m:A H2so4 50% insol 200 nm NacL. 50% insol 0.95 0° Droplet Diameter um Fig 3. Activation curves for a range of dry diameter of salt((NH4)2SO4-solid, NaCI-dashed) particles (red, green and blue curves)and for 200 nm particles containing 50% by mass insoluble core(magenta) reached. As more particles activate and grow, they will com- altitude with the maximum just above cloud base. Numer- te for available water vapour. The water supersaturation ous implementations of simple adiabatic cloud parcel mod- will continue to rise above cloud base but will slow as grow- els exist which describe heat transfer and mass transfer of g droplets scavenge the water vapour and relatively fewer water vapour between an adiabatically cooling air parcel and additional (smaller) aerosol particles will activate. When the aerosol/droplet population based on fundamental thermo- supersaturation sources and sinks balance, the peak super- dynamic principles(see Howell, 1949, Mordy, 1959, Prup- saturation is reached - usually within a few 10s of metres pacher and Klett, 1997; Seinfeld and Pandis, 1998 above cloud base. Following this point, the growing droplet Figure 4 demonstrates the predicted behaviour of an ide- population will lead to a reduction in supersaturation. No alised lognormal(NH4) SO4 aerosol population with height new particles will activate and the most recently activated above cloud base at an updraught velocity of 0.5 ms-using droplets may evaporate. Some particles will not have suf- such a model. It clearly shows how the droplets activated ficient time to reach their critical radius even though their from the larger classes of aerosol continue to grow above critical supersaturation is reached. This results from water the supersaturation maximum at the expense of the smaller vapour scavenging by the larger droplets reducing supersatu- classes of activated particle which evaporate to below their ration to below the critical value of the smaller particles be- critical radius. The model uses the form of the Kohler equa- fore sufficient water vapour can condense(such kinetic limi- tion shown in Eq(1) tations are discussed further in Sect. 4). Only particles reach- Given this behaviour, it can be seen that both the number ing a certain size will survive and grow. Some of the largest of particles in a given size range and the gradient of the dis- particles may not actually activate, but may be large enough tribution in certain critical size ranges will determine its acti- to be considered as droplets since even at their subcritical vation behaviour moving into supersaturation. The Twomey sizes they will often be greater than 10 or 20 microns in ra-(1959)analytical solution to this problem dius, deplete water vapour, and even act as collector drops A pseudosteady-state or quasi-equilibrium is eventually =c(100s)ands=/4(7,P)m232)l/+ reached for a constant updraught velocity where the decrease kB(3/2,k/2) in saturation ratio by condensation to the droplet population and the increase in saturation ratio owing to the updraught where c is proportional to the CCN concentration at 1%su- maintains a broadly constant supersaturation with increasing persaturation, w is the updraught velocity, k is the slope parameter of the CCN size spectrum and N is the number www.atmos-chem-phys.net/6/2593/20 Atmos. Chem. Phys., 6, 2593-2649, 2006

G. McFiggans et al.: Aerosol effects on warm cloud activation 2597 10−1 100 101 102 0.95 0.96 0.97 0.98 0.99 10−1 100 101 102 1 1.001 1.002 1.003 1.004 1.005 Droplet Diameter µm Saturation Ratio 50 nm (NH4 ) 2 SO4 50 nm NaCl 100 nm (NH4 ) 2 SO4 100 nm NaCl 200 nm (NH4 ) 2 SO4 200 nm NaCl 200 nm (NH4 ) 2 SO4 , 50% insol 200 nm NaCl, 50% insol Fig. 3. Activation curves for a range of dry diameter of salt ((NH4)2SO4 – solid, NaCl – dashed) particles (red, green and blue curves) and for 200 nm particles containing 50% by mass insoluble core (magenta). reached. As more particles activate and grow, they will com￾pete for available water vapour. The water supersaturation will continue to rise above cloud base but will slow as grow￾ing droplets scavenge the water vapour and relatively fewer additional (smaller) aerosol particles will activate. When supersaturation sources and sinks balance, the peak super￾saturation is reached - usually within a few 10’s of metres above cloud base. Following this point, the growing droplet population will lead to a reduction in supersaturation. No new particles will activate and the most recently activated droplets may evaporate. Some particles will not have suf- ficient time to reach their critical radius even though their critical supersaturation is reached. This results from water vapour scavenging by the larger droplets reducing supersatu￾ration to below the critical value of the smaller particles be￾fore sufficient water vapour can condense (such kinetic limi￾tations are discussed further in Sect. 4). Only particles reach￾ing a certain size will survive and grow. Some of the largest particles may not actually activate, but may be large enough to be considered as droplets since even at their subcritical sizes they will often be greater than 10 or 20 microns in ra￾dius, deplete water vapour, and even act as collector drops. A pseudo “steady-state” or quasi-equilibrium is eventually reached for a constant updraught velocity where the decrease in saturation ratio by condensation to the droplet population and the increase in saturation ratio owing to the updraught maintains a broadly constant supersaturation with increasing altitude with the maximum just above cloud base. Numer￾ous implementations of simple adiabatic cloud parcel mod￾els exist which describe heat transfer and mass transfer of water vapour between an adiabatically cooling air parcel and the aerosol/droplet population based on fundamental thermo￾dynamic principles (see Howell, 1949; Mordy, 1959; Prup￾pacher and Klett, 1997; Seinfeld and Pandis, 1998). Figure 4 demonstrates the predicted behaviour of an ide￾alised lognormal (NH4)2SO4 aerosol population with height above cloud base at an updraught velocity of 0.5 ms−1 using such a model. It clearly shows how the droplets activated from the larger classes of aerosol continue to grow above the supersaturation maximum at the expense of the smaller classes of activated particle which evaporate to below their critical radius. The model uses the form of the Kohler equa- ¨ tion shown in Eq. (1). Given this behaviour, it can be seen that both the number of particles in a given size range and the gradient of the dis￾tribution in certain critical size ranges will determine its acti￾vation behaviour moving into supersaturation. The Twomey (1959) analytical solution to this problem: N = c(100 + S ∗ ) k and S ∗ = A(T , P )w3/2 ckβ(3/2, k/2) !1/(k+2) (7) where c is proportional to the CCN concentration at 1% su￾persaturation, w is the updraught velocity, k is the slope parameter of the CCN size spectrum and N is the number www.atmos-chem-phys.net/6/2593/2006/ Atmos. Chem. Phys., 6, 2593–2649, 2006

2598 G. McFiggans et al. aerosol effects on warm cloud activation fully soluble particles of greater than 40 nm diameter may 0.950.960.970.980.991.00 1400 activate under certain atmospheric circumstances. Studies of low clouds have found minimum activated diameters ranging from 40 to 140 nm( Hoppel et al., 1996; Leaitch et al., 1996 Flynn et al., 2000; Komppula et al., 2005). Smaller particles might be activated in the strong updrafts of vigorous convec- tion, especially in unpolluted environments. The activation E of particles above this dry size threshold is a strong function of both the supersaturation and the form of the size and com- position distribution. A primary limitation of the approach of Twomey is that it does not account for the multi-component size and composition of the CCn population 3.1.2 A practical illustration of the dynamic competition effects of a simple multi-component aerosol popula- 1000 0.01 0.10 1.00 The Twomey equation, and most others developed to link radius, um number of activated droplets to a sub-cloud aerosol con- centration(either mass or number), usually assume that the Fig 4. Simulation showing the change in droplet radius with height aerosol type is relatively homogeneous. Some parameterisa- in a simulation initialised with an ammonium sulphate aerosol with tions yield a monotonic increase in cloud droplet concentra- a geometric mean diameter of 140 nm, a geometric standard de- viation, g of 1.7 and aerosol number concentration of 300cm<3 tion(e. g, Boucher and Lohmann, 1995)whereas others show (corresponding to a total mass loading of 0. 76 ugm ). The simu- 1994). In general they are well approximated by power ation was started at an RH of% at 1000 m. Solid lines represent law dependence of Na on Na or the mass concentration of clected aerosol size classes. The dashed line is the saturation ratio aerosols. The parameterisations of Ghan et al.(1998)and Feingold (2001), exhibit similar behaviour but, following sat- uration, show a decrease in Nd with further increases with Na nuclei activated at peak supersaturation $, indicates the at very high aerosol concentrations(order 10000 cm relative sensitivity of activated drop number to aerosol size distribution parameters. A(T, P)is a function of temper- aerosol but not for an aerosol of significantly different multi- ature T and pressure P and B is the complete beta func le components. The breakdown of these assumptions was tion. This expression works well for modest values of k well illustrated by Ghan et al. (1998)and O'Dowd et al and was evaluated for southern-hemisphere cumulus clouds. ( 1999) for typical maritime cloud conditions Although the analysis assumes a Junge power-law distribu- O Dowd et al. (1999)conducted parcel model simulations tion, the essential features of sensitivity to size parameters of the impact of increasing CCN concentrations on cloud and updraught is evident. For example, drop activation is in- droplet concentration using typical marine sulphate and sea- creasingly more sensitive to updraught velocity when size salt size distributions and found that an increase in cloud distributions have larger values of k(steeper decreases in droplet concentration did not necessarily follow as the CCN concentration with increasing size). Conversely, at smaller values of k, N is determined primarily by c(Twomey 7 Population increases. The aerosol properties were described by three modes, one sulphate mode with a modal diameter Jaenicke( 1988)pointed out that the power-law representa- of 150 nm and a geometric standard deviation, ag of 1.4,a tion of the CCN spectrum may not be realistic, particularly film drop sea-salt mode with modal diameter of 200 nm and for a multi-component aerosol population. Theoretical and og of 1. 9 and a super micron mode of 2 um and og of 2. The model-based analyses of activation in terms of lognormal amplitude of each mode was varied within the frequently ob- size distributions have been reported by Cohard et al. (1998): served constraints that the amplitude of the sulphate mode is Feingold (2001, 2003), Rissman et al. (2004) Abdul-Razzak typically greater than those of the sea-salt modes and the am- and ghan(2000) Nenes and Seinfeld(2003), Fountoukis plitude of the film drop mode is always significantly greater than that of the jet drop mode. Simulations were conducted tinsson et al 1999) for scenarios where the sulphate aerosol The updraught velocity can range from around 0. 1 ms- varied under a range of fixed sea-salt conditions.Sea-salt in stratiform clouds to in excess of 15 ms- in deep convec- CCN were added to the population with the base case of tive or orographically-forced clouds. The supersaturations 3 cm-3, increasing to a maximum of 57 cm-3 sea-salt par associated with such a range in updraught velocity mean that ticles tmos.Chem.Phys,6,2593-2649,2006 www.atmos-chem-phys.net/6/2593/2006/

2598 G. McFiggans et al.: Aerosol effects on warm cloud activation Fig. 4. Simulation showing the change in droplet radius with height in a simulation initialised with an ammonium sulphate aerosol with a geometric mean diameter of 140 nm, a geometric standard de￾viation, σg of 1.7 and aerosol number concentration of 300 cm−3 (corresponding to a total mass loading of 0.76 µgm−3 ). The simu￾lation was started at an RH of 95% at 1000 m. Solid lines represent selected aerosol size classes. The dashed line is the saturation ratio. of nuclei activated at peak supersaturation S ∗ , indicates the relative sensitivity of activated drop number to aerosol size distribution parameters. A(T , P ) is a function of temper￾ature T and pressure P and β is the complete beta func￾tion. This expression works well for modest values of k and was evaluated for southern-hemisphere cumulus clouds. Although the analysis assumes a Junge power-law distribu￾tion, the essential features of sensitivity to size parameters and updraught is evident. For example, drop activation is in￾creasingly more sensitive to updraught velocity when size distributions have larger values of k (steeper decreases in concentration with increasing size). Conversely, at smaller values of k, N is determined primarily by c (Twomey, 1977). Jaenicke (1988) pointed out that the power-law representa￾tion of the CCN spectrum may not be realistic, particularly for a multi-component aerosol population. Theoretical and model-based analyses of activation in terms of lognormal size distributions have been reported by Cohard et al. (1998); Feingold (2001, 2003); Rissman et al. (2004); Abdul-Razzak and Ghan (2000); Nenes and Seinfeld (2003); Fountoukis and Nenes (2005); and experimentally determined (e.g. Mar￾tinsson et al., 1999). The updraught velocity can range from around 0.1 ms−1 in stratiform clouds to in excess of 15 ms−1 in deep convec￾tive or orographically-forced clouds. The supersaturations associated with such a range in updraught velocity mean that fully soluble particles of greater than ∼40 nm diameter may activate under certain atmospheric circumstances. Studies of low clouds have found minimum activated diameters ranging from 40 to 140 nm (Hoppel et al., 1996; Leaitch et al., 1996; Flynn et al., 2000; Komppula et al., 2005). Smaller particles might be activated in the strong updrafts of vigorous convec￾tion, especially in unpolluted environments. The activation of particles above this dry size threshold is a strong function of both the supersaturation and the form of the size and com￾position distribution. A primary limitation of the approach of Twomey is that it does not account for the multi-component size and composition of the CCN population. 3.1.2 A practical illustration of the dynamic competition effects of a simple multi-component aerosol popula￾tion The Twomey equation, and most others developed to link number of activated droplets to a sub-cloud aerosol con￾centration (either mass or number), usually assume that the aerosol type is relatively homogeneous. Some parameterisa￾tions yield a monotonic increase in cloud droplet concentra￾tion (e.g., Boucher and Lohmann, 1995) whereas others show a tendency to saturate (for example Hegg, 1984; Jones et al., 1994). In general they are well approximated by power￾law dependence of Nd on Na or the mass concentration of aerosols. The parameterisations of Ghan et al. (1998) and Feingold (2001), exhibit similar behaviour but, following sat￾uration, show a decrease in Nd with further increases with Na at very high aerosol concentrations (order 10 000 cm−3 ). Such assumptions may hold for a single component aerosol but not for an aerosol of significantly different multi￾ple components. The breakdown of these assumptions was well illustrated by Ghan et al. (1998) and O’Dowd et al. (1999) for typical maritime cloud conditions. O’Dowd et al. (1999) conducted parcel model simulations of the impact of increasing CCN concentrations on cloud droplet concentration using typical marine sulphate and sea￾salt size distributions and found that an increase in cloud droplet concentration did not necessarily follow as the CCN population increases. The aerosol properties were described by three modes; one sulphate mode with a modal diameter of 150 nm and a geometric standard deviation, σg of 1.4; a film drop sea-salt mode with modal diameter of 200 nm and σg of 1.9 and a super micron mode of 2 µm and σg of 2. The amplitude of each mode was varied within the frequently ob￾served constraints that the amplitude of the sulphate mode is typically greater than those of the sea-salt modes and the am￾plitude of the film drop mode is always significantly greater than that of the jet drop mode. Simulations were conducted for scenarios where the sulphate aerosol concentration was varied under a range of fixed sea-salt conditions. Sea-salt CCN were added to the population with the base case of 3 cm−3 , increasing to a maximum of 57 cm−3 sea-salt par￾ticles. Atmos. Chem. Phys., 6, 2593–2649, 2006 www.atmos-chem-phys.net/6/2593/2006/

G. McFiggans et al. Aerosol effects on warm cloud activation 2599 300 200 100 draft=0. 1 draft=0. 175 m s 0 01002003004000100200300400 Sub-cloud aerosol (cm Fig. 5. Cloud droplet concentration as a function of sub-cloud aerosol where the sub-cloud aerosol comprises an extemal mix of sulphate nd sea-salt CCN The simulations results are shown in Fig. 5 for updraughts sation of these properties(e. g. Whitby, 1978; Van Dingenen of 0. I ms- and 0. 175 ms. For low sulphate CCN concen- et al., 2004) trations, the addition of sea-salt CCN increases the number of Figure 6 shows representative average distributions in a activated droplets significantly while for high sulphate con- variety of locations. Most particles greater than 200 nm di- centrations, the number of activated droplets decreases sig- ameter with moderate amounts of soluble material will acti- nificantly. For the higher updraught, the point at which the vate under reasonable supersaturations. Assuming that those result of the addition of sea-salt nuclei switches from an in- particles greater than 200 nm in Fig. 6 are moderately sol- crease to a decrease in droplet concentration reduces for the uble, it can be seen that the sizes critical to determining the gher updraught and the impact of the reduction in droplet droplet number in an aerosol population fall in the range with concentration increases for increasing updraught significant contributions from both Aitken and accumulation The main processes driving this phenomenon are(1)sea- mode particles(around 100 nm diameter). It is therefore nec- salt CCN are typically larger than sulphate CCN; (2)for a essary to capture the features of the aerosol size distribu- en size, sea-salt is more active as a CCn than sulphate, tion in both modes in order to realistically describe cloud ()although the relative concentration of larger sea-salt CCn activation behaviour, (Martinsson et al., 1999). The follow is significantly lower than sulphate CCN, they contribute to ing sections investigate further properties of real atmospheric a significant reduction in the peak supersaturation reached in aerosol and the potential impacts of these properties on cloud cloud and thus inhibit the activation of sulphate nuclei. This activation example demonstrates that for even simple two-component It should be noted that, the critical size range for cloud aerosol systems the dynamic competition is quite complex activation of about 50 to 150 nm is not accessible to most and non-linear and that the effect of increasing the availabil- optical sizing instruments, but may be probed by mobility ity of ccn does not necessarily lead to an increase in cloud instruments. This significantly reduces the amount of data droplet concentration. Similar non-linearities are evident in available at cloud altitudes because mobility analyses can be the effects of composition on droplet activation and caution challenging on aircraft due to the time required to scan a size should be exercised in translating a composition change to distribution an equivalent change in drop number concentration(Ervens et al., 2005). The results of such responses are strongly de- 3.1.3 Relative importance of size distribution, composition pendent on water vapour supply (i.e. updraught)and conden sation rates(dependent on size distribution and composition) The activation of seasalt and sulphate in marine stratiform Feingold (2003) performed a sensitivity anal cloud described in this section is a particularly simple case in aspects of the relative importance of aerosol size and compo- terms of both composition and the limited range of updraught sition, in so far as both properties affect activation, using a velocity. Ambient aerosol size distributions are highly vari- cloud parcel model. Input aerosol size distributions(parame- able from location to location. The reader is referred to a terised as lognormal functions described by Na, rg, g), and range of review articles for a broad and detailed characteri- prescribed updraught velocities, w, were varied over a large www.atmos-chem-phys.net/6/2593/2006/ Atmos. Chem. Phys., 6, 2593-2649, 2006

G. McFiggans et al.: Aerosol effects on warm cloud activation 2599 Fig. 5. Cloud droplet concentration as a function of sub-cloud aerosol where the sub-cloud aerosol comprises an external mix of sulphate and sea-salt CCN. The simulations results are shown in Fig. 5 for updraughts of 0.1 ms−1 and 0.175 ms−1 . For low sulphate CCN concen￾trations, the addition of sea-salt CCN increases the number of activated droplets significantly while for high sulphate con￾centrations, the number of activated droplets decreases sig￾nificantly. For the higher updraught, the point at which the result of the addition of sea-salt nuclei switches from an in￾crease to a decrease in droplet concentration reduces for the higher updraught and the impact of the reduction in droplet concentration increases for increasing updraught. The main processes driving this phenomenon are (1) sea￾salt CCN are typically larger than sulphate CCN; (2) for a given size, sea-salt is more active as a CCN than sulphate; (3) although the relative concentration of larger sea-salt CCN is significantly lower than sulphate CCN, they contribute to a significant reduction in the peak supersaturation reached in cloud and thus inhibit the activation of sulphate nuclei. This example demonstrates that for even simple two-component aerosol systems the dynamic competition is quite complex and non-linear and that the effect of increasing the availabil￾ity of CCN does not necessarily lead to an increase in cloud droplet concentration. Similar non-linearities are evident in the effects of composition on droplet activation and caution should be exercised in translating a composition change to an equivalent change in drop number concentration (Ervens et al., 2005). The results of such responses are strongly de￾pendent on water vapour supply (i.e. updraught) and conden￾sation rates (dependent on size distribution and composition). The activation of seasalt and sulphate in marine stratiform cloud described in this section is a particularly simple case in terms of both composition and the limited range of updraught velocity. Ambient aerosol size distributions are highly vari￾able from location to location. The reader is referred to a range of review articles for a broad and detailed characteri￾sation of these properties (e.g. Whitby, 1978; Van Dingenen et al., 2004). Figure 6 shows representative average distributions in a variety of locations. Most particles greater than 200 nm di￾ameter with moderate amounts of soluble material will acti￾vate under reasonable supersaturations. Assuming that those particles greater than 200 nm in Fig. 6 are moderately sol￾uble, it can be seen that the sizes critical to determining the droplet number in an aerosol population fall in the range with significant contributions from both Aitken and accumulation mode particles (around 100 nm diameter). It is therefore nec￾essary to capture the features of the aerosol size distribu￾tion in both modes in order to realistically describe cloud activation behaviour, (Martinsson et al., 1999). The follow￾ing sections investigate further properties of real atmospheric aerosol and the potential impacts of these properties on cloud activation. It should be noted that, the critical size range for cloud activation of about 50 to 150 nm is not accessible to most optical sizing instruments, but may be probed by mobility instruments. This significantly reduces the amount of data available at cloud altitudes because mobility analyses can be challenging on aircraft due to the time required to scan a size distribution. 3.1.3 Relative importance of size distribution, composition and updraught Feingold (2003) performed a sensitivity analysis comparing aspects of the relative importance of aerosol size and compo￾sition, in so far as both properties affect activation, using a cloud parcel model. Input aerosol size distributions (parame￾terised as lognormal functions described by Na, rg, σg), and prescribed updraught velocities, w, were varied over a large www.atmos-chem-phys.net/6/2593/2006/ Atmos. Chem. Phys., 6, 2593–2649, 2006

2600 G. McFiggans et al. aerosol effects on warm cloud activation Background Near-city Urban marylebone(GB) 0oo10010.1 1E·5 E+5 E+5 Mept (Dj 010101 Jungtaujoch (CH pra(n 0o010011 Fig. 6. Median particle number size distributions during summer, during morning hours(black dashed line), afternoon(grey full line) and night(black full line). From Van Dingenen et al. (2004) Table 1. Table of s(Xi)=aIn Na/aln Xi where Xi is one of Na mately the same(although opposite in sign) whereas S(w is small. Under polluted conditions, the relative influence indicates Na>1000 cm-3. The ranges of x are w: 20 cms-I to of rg, Og and w on Na increases significantly while S(Na) 300, Na: 20 cm-3 to 3000 cm-3, rg: 0.03 to 0. 1 um, a: 1.3 decreases in importance. S(e) is relatively small compared to2.2,E:0.10to1.00 to the other terms. although we caution that this term only reflects composition changes associated with the fraction all Clean polluted of soluble material. The signs of S(Xi) are as expected specific mention is made of S(og) which is negative because Na0.880.92 0.7 rg0.320.280.39 the tail of the distribution at large sizes results in activation a-0.39-0.310.53 of larger drops, and suppression of supersaturation which tends to suppress Nd. This combination of effects makes E0.110.09 0.13 S(og) quite large, particularly under polluted conditions when the larger particles are abundant (e.g. O Dowd et al 1999, Sect. 3.1.2). Rissman et al.(2004)performed a more detailed analysis of the effect of various composition ange of parameter space. Aerosol composition was repre factors such as solubility and surface tension, as well as size sented in a simplified fashion by considering an ammonium distribution parameters. Their results were derived from sulphate and insoluble mix, and varying the mass fraction analytical solutions, and presented in terms of a sensitivity of ammonium sulphate, over the range 0. 1 to 1.0. The out- relative to the sensitivity of drop number concentration to put was then used to examine the relative sensitivity of cloud updraft velocity (x)=(x/w)(aNa/a x)/(aNa/aw),where drop size to the various input parameters using the model of x is a composition factor such as organic mass fraction Feingold(2003). Here we repeat this analysis for sensitiv- Eo. The authors concluded that when defined this way, ity of drop number concentration Na. The sensitivities defined as S(Xi)=aIn Nd/aIn Xi where Xi is one of Na,r sensitivity to composition factors (x) is highest for aerosol e). In this form, values of S(Xi) can be compared updraught velocity. However, these are conditions under with one-another to assess their relative importance. Values which supersaturation and activated fractions of S(Xi) for conditions similar to Feingold (2003)are given an increase in w does not add many new drops(aNa/dw in Table 1 is small). The appea of aNd/aw in the denominator Under clean conditions, arbitrarily defined as tends to increase (x). Thus at high S, even though Na<1000 cm -', S(Na) is close to its theoretical upper o(x) is large, composition effects may not be important limit of 1, indicating a high level of in-cloud activation in an absolute sense. Because the individual sensitivities Sensitivity to rg and og under clean conditions is approxi tmos.Chem.Phys,6,2593-2649,2006 www.atmos-chem-phys.net/6/2593/2006/

2600 G. McFiggans et al.: Aerosol effects on warm cloud activation Fig. 6. Median particle number size distributions during summer, during morning hours (black dashed line), afternoon (grey full line) and night (black full line). From Van Dingenen et al. (2004); van Din￾genen et al. (2004). 125 Fig. 6. Median particle number size distributions during summer, during morning hours (black dashed line), afternoon (grey full line) and night (black full line). From Van Dingenen et al. (2004). Table 1. Table of S(Xi )=∂lnNd /∂lnXi where Xi is one of Na, rg, σg, w, ε. “Clean” indicates Na1000 cm−3 . The ranges of Xi are w: 20 cm s−1 to 300 cm s−1 , Na: 20 cm−3 to 3000 cm−3 , rg: 0.03 to 0.1µm, σ: 1.3 to 2.2, ε: 0.10 to 1.00. All Clean Polluted Na 0.88 0.92 0.73 rg 0.32 0.28 0.39 σ −0.39 −0.31 −0.53 w 0.29 0.18 0.47 ε 0.11 0.09 0.13 range of parameter space. Aerosol composition was repre￾sented in a simplified fashion by considering an ammonium sulphate and insoluble mix, and varying the mass fraction of ammonium sulphate, over the range 0.1 to 1.0. The out￾put was then used to examine the relative sensitivity of cloud drop size to the various input parameters using the model of Feingold (2003). Here we repeat this analysis for sensitiv￾ity of drop number concentration Nd . The sensitivities are defined as S(Xi)=∂lnN d/∂lnXi where Xi is one of Na, rg, σg, w or ε). In this form, values of S(Xi) can be compared with one-another to assess their relative importance. Values of S(Xi) for conditions similar to Feingold (2003) are given in Table 1. Under clean conditions, arbitrarily defined as Na<1000 cm−3 , S(Na) is close to its theoretical upper limit of 1, indicating a high level of in-cloud activation. Sensitivity to rg and σg under clean conditions is approxi￾mately the same (although opposite in sign) whereas S(w) is small. Under polluted conditions, the relative influence of rg, σg and w on Nd increases significantly while S(Na) decreases in importance. S(ε) is relatively small compared to the other terms, although we caution that this term only reflects composition changes associated with the fraction of soluble material. The signs of S(Xi) are as expected; specific mention is made of S(σg) which is negative because the tail of the distribution at large sizes results in activation of larger drops, and suppression of supersaturation which tends to suppress Nd . This combination of effects makes S(σg) quite large, particularly under polluted conditions when the larger particles are abundant (e.g. O’Dowd et al., 1999, Sect. 3.1.2). Rissman et al. (2004) performed a more detailed analysis of the effect of various composition factors such as solubility and surface tension, as well as size distribution parameters. Their results were derived from analytical solutions, and presented in terms of a sensitivity relative to the sensitivity of drop number concentration to updraft velocity φ(χ )=(χ/w)(∂Nd /∂χ )/(∂Nd /∂w), where χ is a composition factor such as organic mass fraction o. The authors concluded that when defined this way, sensitivity to composition factors φ(χ ) is highest for aerosol typical of marine condition, and increases with increasing updraught velocity. However, these are conditions under which supersaturation and activated fractions are high, and an increase in w does not add many new drops (∂Nd /∂w is small). The appearance of ∂Nd /∂w in the denominator tends to increase φ(χ ). Thus at high S, even though φ(χ ) is large, composition effects may not be important in an absolute sense,. Because the individual sensitivities Atmos. Chem. Phys., 6, 2593–2649, 2006 www.atmos-chem-phys.net/6/2593/2006/

G. McFiggans et al. Aerosol effects on warm cloud activation d/ax and aNa/aw or their logarithmic equivalents) Some online instruments provide single particle composition not reported, it is difficult to compare their results to information and hence information about which components those of Feingold(2003) for overlapping parameter space. co-exist in the same particles; their chemical mixing state Both studies do however agree that Nd is more sensitive to Others may provide component mass loadings with high size the size parameter rg, and that Nd is more sensitive to rg and time resolution. However, online techniques cannot cur- under polluted conditions rently provide as much detailed speciation information c The greater sensitivity of cloud droplet number to size may be available from offline techniques mpared to composition illustrates that the aerosol size must be captured as a primary pre-requisite. The sensitivity to the 3. 1. 4. I Offline bulk measurements showing the complexity compositional complexities should only be investigated in of the atmospheric aerosol composition e knowledge that the size and number information is likely to be equally important(or moreso). It should be noted that This section presents such features of aerosol composition the treatment of composition does not address the sensitivity (organic and inorganic)which may be gained from offline to composition changes with size and to varied composition analyses as relate to cloud activation, without attempting an at any one size; evidence for the prevalence of both being exhaustive review. A summary of some available size segre- provided in the forthcoming sections. The sensitivity of acti- gated chemical compositions is also provided in a form suit vation and cloud droplet number to more detailed aspects of able for cloud modelling purposes aerosol composition is discussed in Sect. 4.2 Despite the wide range of sampling and analytical tech- niques that have been employed, characterisation of aerosol 3.1. 4 The composition of ambient aerosol chemical composition as a function of size is often still in- Until recently, the vast majority of cloud modelling studies is diverse, complex and variable with location and condi- have conventionally assumed, implicitly or explicitly, that tion. The particles comprise many inorganic and organic the soluble material in aerosol particles comprises inorganic compounds ranging in solubility, density and, surface ten- components. The emerging complexity of ambient aerosol sion. Thus, comprehensive papers about the aspects of the equires that this description is revisited chemical composition relevant to cloud formation are rare It must be remembered that number of activated droplets is In order to use Eq.(2), the chemical composition must be dependent on the number distribution of particles of a given"translated"for cloud modelling purposes into concentra type and not directly on the mass loading. Although the acti- tion of molecules(organic and inorganic)dissolved in cloud vation of an individual particle is dependent on its(soluble) droplets, total insoluble mass and, if present, the concen- mass, techniques which coarsely probe component distribu- tration of some"critical" species with limited solubility(or tion loadings by mass will not provide adequate insight to slightly soluble species). The degree of dissociation and ph predict droplet number. Composition is likely to be impor- may also be needed (Laaksonen et al., 1998; Lohmann et al tant only in a limited size range: particles smaller than about 2004); this is addressed further in Sect. 4. It should be noted 40 nm diameter are unlikely to activate into cloud droplets that there are exceptions to these requirements when Eq (1) regardless of their composition and sufficiently large parti- is used, depending on how water activity is evaluated, see cles will almost always contain enough soluble material to Sect. 4.4 activate. To predict droplet activation it is necessary to de- Soluble inorganic components are relatively well un- termine size-resolved composition in the 40 to 200 nm size derstood; the majority comprising a few inorganic range coupled to information about the mixing-state of the salts (Heintzenberg, 1989), which are relatively well- population. No single technique can currently provide all characterised in terms of their hygroscopic properties( Clegg this information. This section reviews the available evidence et al., 1998; Ansari and Pandis, 2000). The insoluble inor- for the composition of ambient particles from a range of ganic fraction can also be important(as in the case of dust studies and techniques From combinations of these sources aerosol from urban or natural sources)and many different it should eventually be possible to adequately describe the component or element measurements are available. How- aerosol composition distribution for purposes of CCN and ever, this information is difficult to directly interpret in terms possibly droplet number prediction of total insoluble mass Offline analyses of bulk particulate material collected by Organic matter has been shown to represent an important filter pack and impactor sampling have conventionally been fraction of the aerosol mass in different environments, and is used to determine aerosol mass composition. Applied ana- routinely measured by means of thermal techniques liousse lytical techniques can provide information ranging from de- et al., 1996, Jacobson et al., 2000; Putaud et al., 2004) tailed molecular speciation to aggregate lumped chemical ganic carbon(OC)and Elemental carbon(EC)(or black car- functionality. These techniques have recently been supple- bon(BC)are reported in terms of carbon mass and the trans- mented by online instrumentation which may provide addi- formation to aerosol mass is problematic without knowing tional information to that available from offline techniques. the main chemical C structure( Turpin and Lim, 2001; Rus- www.atmos-chem-phys.net/6/2593/2006/ Atmos. Chem. Phys., 6, 2593-2649, 2006

G. McFiggans et al.: Aerosol effects on warm cloud activation 2601 (∂Nd /∂χ and ∂Nd /∂w or their logarithmic equivalents) were not reported, it is difficult to compare their results to those of Feingold (2003) for overlapping parameter space. Both studies do however agree that Nd is more sensitive to the size parameter rg, and that Nd is more sensitive to rg under polluted conditions. The greater sensitivity of cloud droplet number to size compared to composition illustrates that the aerosol size must be captured as a primary pre-requisite. The sensitivity to the compositional complexities should only be investigated in the knowledge that the size and number information is likely to be equally important (or moreso). It should be noted that the treatment of composition does not address the sensitivity to composition changes with size and to varied composition at any one size; evidence for the prevalence of both being provided in the forthcoming sections. The sensitivity of acti￾vation and cloud droplet number to more detailed aspects of aerosol composition is discussed in Sect. 4.2. 3.1.4 The composition of ambient aerosol Until recently, the vast majority of cloud modelling studies have conventionally assumed, implicitly or explicitly, that the soluble material in aerosol particles comprises inorganic components. The emerging complexity of ambient aerosol requires that this description is revisited. It must be remembered that number of activated droplets is dependent on the number distribution of particles of a given type and not directly on the mass loading. Although the acti￾vation of an individual particle is dependent on its (soluble) mass, techniques which coarsely probe component distribu￾tion loadings by mass will not provide adequate insight to predict droplet number. Composition is likely to be impor￾tant only in a limited size range: particles smaller than about 40 nm diameter are unlikely to activate into cloud droplets regardless of their composition and sufficiently large parti￾cles will almost always contain enough soluble material to activate. To predict droplet activation it is necessary to de￾termine size-resolved composition in the 40 to 200 nm size range coupled to information about the mixing-state of the population. No single technique can currently provide all this information. This section reviews the available evidence for the composition of ambient particles from a range of studies and techniques. From combinations of these sources it should eventually be possible to adequately describe the aerosol composition distribution for purposes of CCN and possibly droplet number prediction. Offline analyses of bulk particulate material collected by filter pack and impactor sampling have conventionally been used to determine aerosol mass composition. Applied ana￾lytical techniques can provide information ranging from de￾tailed molecular speciation to aggregate lumped chemical functionality. These techniques have recently been supple￾mented by online instrumentation which may provide addi￾tional information to that available from offline techniques. Some online instruments provide single particle composition information and hence information about which components co-exist in the same particles; their chemical mixing state. Others may provide component mass loadings with high size and time resolution. However, online techniques cannot cur￾rently provide as much detailed speciation information as may be available from offline techniques. 3.1.4.1 Offline bulk measurements showing the complexity of the atmospheric aerosol composition This section presents such features of aerosol composition (organic and inorganic) which may be gained from offline analyses as relate to cloud activation, without attempting an exhaustive review. A summary of some available size segre￾gated chemical compositions is also provided in a form suit￾able for cloud modelling purposes. Despite the wide range of sampling and analytical tech￾niques that have been employed, characterisation of aerosol chemical composition as a function of size is often still in￾complete (Putaud et al., 2004). The chemical composition is diverse, complex and variable with location and condi￾tion. The particles comprise many inorganic and organic compounds ranging in solubility, density and, surface ten￾sion. Thus, comprehensive papers about the aspects of the chemical composition relevant to cloud formation are rare. In order to use Eq. (2), the chemical composition must be “translated” for cloud modelling purposes into concentra￾tion of molecules (organic and inorganic) dissolved in cloud droplets, total insoluble mass and, if present, the concen￾tration of some “critical” species with limited solubility (or slightly soluble species). The degree of dissociation and pH may also be needed (Laaksonen et al., 1998; Lohmann et al., 2004); this is addressed further in Sect. 4. It should be noted that there are exceptions to these requirements when Eq. (1) is used, depending on how water activity is evaluated, see Sect. 4.4. Soluble inorganic components are relatively well un￾derstood; the majority comprising a few inorganic salts (Heintzenberg, 1989), which are relatively well￾characterised in terms of their hygroscopic properties (Clegg et al., 1998; Ansari and Pandis, 2000). The insoluble inor￾ganic fraction can also be important (as in the case of dust aerosol from urban or natural sources) and many different component or element measurements are available. How￾ever, this information is difficult to directly interpret in terms of total insoluble mass. Organic matter has been shown to represent an important fraction of the aerosol mass in different environments, and is routinely measured by means of thermal techniques (Liousse et al., 1996; Jacobson et al., 2000; Putaud et al., 2004). Or￾ganic carbon (OC) and Elemental carbon (EC) (or black car￾bon (BC)) are reported in terms of carbon mass and the trans￾formation to aerosol mass is problematic without knowing the main chemical C structure (Turpin and Lim, 2001; Rus￾www.atmos-chem-phys.net/6/2593/2006/ Atmos. Chem. Phys., 6, 2593–2649, 2006

2602 G. McFiggans et al. aerosol effects on warm cloud activation sell, 2003). The assumption that BC belong to the insoluble Functional group analytical techniques provide an alter fraction of the aerosol has been questioned by recent experi- native approach to traditional individual compound specia- ments showing that thermally refractory fractions of TC can tion methods. These techniques analyse the different types of be efficiently extracted with water (Yu et al., 2004, Mayol- chemical structures(as for example total carboxylic groups, Bracero et al., 2002). Furthermore, OC/BC concentrations total carbonyls, etc. ) but provide little or no information on the individual molecules(Decesari et al., 2000; Maria Experimental studies indicate that, in addition to the et al., 2002). Functional group methods have sometime inorganic components, water-soluble organic compounds been coupled to extraction-classification or separation tech wSOC)in atmospheric aerosol particles are also potentially niques, providing a more comprehensive description of oC important in clouds, and an understanding of organic par- and being able to account for up to 90% of the wSoc titioning in cloud droplets(whether dissolved or present as mass(Decesari et al., 2001; Varga et al., 2001). In partic insoluble inclusions) is crucial to our understanding of their ular, in the functional group analysis approach proposed by possible effects on cloud activation(see for example Fac- Decesari et al. (2000), wsoC is separated into three main chini et al. 1999b Jacobson et al. 2000: Kiss et al.. 200 classes of compounds: neutral compounds Maria et al., 2003). WSOC, as opposed to inorganic aerosol /di-carboxylic acid(MDA)and polycarboxylic acids(Pa) components, comprise hundreds(or even thousands) of in- Quantitative measurements of wsoc by Total Organic Ca dividual species(Saxena and Hildemann, 1996: Maria et al., bon(ToC) analyser and of proton concentration of the 2004, Hamilton et al., 2004, Murphy, 2005; Kanakidou et al., main functional groups contained in each of the three above 2005), each contributing a small fraction of the mass. Sev- mentioned classes by Proton Nuclear Magnetic Resonance eral studies of aerosol WSOC concentration and composition (HNMR)can be used to formulate a set of a few "model have been carried out(Zappoli et al., 1999; Facchini et al., compounds representative of the whole wSoC (Fuzzi et al 1999b, Kiss et al., 2001, 2002; Mayol- Bracero et al., 2002; 2001). A systematic technique for deriving model com Cavalli et al., 2004a, b, Putaud et al., 2004, Sullivan et al., pounds for biomass burning aerosol collected in the Ama- 2004: Xiao and Liu, 2004). Molecular level identification zon has recently been submitted for publication(Decesari and analysis is the traditional goal of aerosol organic analysis et al., 2006). Since the model compounds derived in this (for example IC: Falkovich et al., 2005; IEC-UV: Schkolnik way reproduce quantitatively the average chemical structure et al., 2005; GC-MS: Graham et al., 2002; Pashynska et al., of wSoc it can be argued that they may be used as best 2002; Carvalho et al., 2003; lon et al., 2005), but such indi- guess surrogates in microphysical models involving biomass vidual component approaches only account for a small frac- burning aerosol. Likewise, model mixtures of wSoc for tion of the total aerosol and a long list of compounds present many different types of aerosol in a range of locations are in very small concentration is usually provided. In addition available or their definition is in progress to the analytical procedure, bulk sampling techniques which are frequently employed for such analyses are inappropriate Urban aerosol, Bologna, Italy(Matta et al., 2003; Fuzzi for cloud activation purposes and size-segregated determin etal,2001), tion is necessary( Carvalho et al., 2003; Matta et al., 2003 Dust aerosol, Monte Cimone, Italy(Putaud et al., 2004) Cavalli et al. 2004b: Putaud et al.. 2004: Falkovich et al 2005) Clean marine aerosol, Mace Head, Ireland(Cavalli The representation of aerosol composition therefore et al., 2004b) presents a dilemma; it is evident that the aerosol wSoc Biomass burning aerosol, Rondonia, Brazil (Decesari cannot be correctly represented by molecules accounting fo etal,2006), only a small fraction of the total carbon mass, but a repre- sentation of participating species is required for a fundamen ACE Asia, Chinese outflow, Gosan, Jeju Island, Korea tal prediction of cloud activation. Frequently, due to the Topping et al., 2004), complexity, the wSoC chemical composition is reduced fo modelling purposes to one or two"representative"species or Boreal forest aerosol, Hyytiala, Finland( Cavalli et al surrogate molecules selected from the long list of compounds 2004a, Decesari et al., 2006) Ity of wSOC and the wide range of physical properties rele- tion concerning both inw studies have provided informa- and organic aerosol chemi vant to activation, an arbitrary choice of representative com- cal composition which can be directly used by cloud mod- pounds can fail in reproducing relevant physical and chemi- els. These papers provide a comprehensive description of the al properties. For the above reasons, a"realistic"represen- chemical composition of different aerosol types as a function tation of wsoc is necessary for cloud modelling purposes, of size( Chan et al., 1999; Zappoli et al., 1999, Pakkanen but it is difficult to achieve through any individual analyti- et al., 2001; Putaud et al., 2000; Temesi et al., 2001; Maria cal methodology or by choosing surrogate chemical compo- et al., 2003; Sellegri et al., 2003; Cabada et al., 2004, Chic sitions from a list of compounds detected in the aerosols et al., 2004; Sardar et al., 2005) tmos.Chem.Phvs.6.2593-26492006 www.atmos-chem-phys.net/6/2593/2006/

2602 G. McFiggans et al.: Aerosol effects on warm cloud activation sell, 2003). The assumption that BC belong to the insoluble fraction of the aerosol has been questioned by recent experi￾ments showing that thermally refractory fractions of TC can be efficiently extracted with water (Yu et al., 2004; Mayol￾Bracero et al., 2002). Furthermore, OC/BC concentrations are strongly size dependent. Experimental studies indicate that, in addition to the inorganic components, water-soluble organic compounds (WSOC) in atmospheric aerosol particles are also potentially important in clouds, and an understanding of organic par￾titioning in cloud droplets (whether dissolved or present as insoluble inclusions) is crucial to our understanding of their possible effects on cloud activation (see for example Fac￾chini et al., 1999b; Jacobson et al., 2000; Kiss et al., 2001; Maria et al., 2003). WSOC, as opposed to inorganic aerosol components, comprise hundreds (or even thousands) of in￾dividual species (Saxena and Hildemann, 1996; Maria et al., 2004; Hamilton et al., 2004; Murphy, 2005; Kanakidou et al., 2005), each contributing a small fraction of the mass. Sev￾eral studies of aerosol WSOC concentration and composition have been carried out (Zappoli et al., 1999; Facchini et al., 1999b; Kiss et al., 2001, 2002; Mayol-Bracero et al., 2002; Cavalli et al., 2004a,b; Putaud et al., 2004; Sullivan et al., 2004; Xiao and Liu, 2004). Molecular level identification and analysis is the traditional goal of aerosol organic analysis (for example IC: Falkovich et al., 2005; IEC-UV: Schkolnik et al., 2005; GC-MS: Graham et al., 2002; Pashynska et al., 2002; Carvalho et al., 2003; Ion et al., 2005), but such indi￾vidual component approaches only account for a small frac￾tion of the total aerosol and a long list of compounds present in very small concentration is usually provided. In addition to the analytical procedure, bulk sampling techniques which are frequently employed for such analyses are inappropriate for cloud activation purposes and size-segregated determina￾tion is necessary (Carvalho et al., 2003; Matta et al., 2003; Cavalli et al., 2004b; Putaud et al., 2004; Falkovich et al., 2005). The representation of aerosol composition therefore presents a dilemma; it is evident that the aerosol WSOC cannot be correctly represented by molecules accounting for only a small fraction of the total carbon mass, but a repre￾sentation of participating species is required for a fundamen￾tal prediction of cloud activation. Frequently, due to the its complexity, the WSOC chemical composition is reduced for modelling purposes to one or two “representative” species or surrogate molecules selected from the long list of compounds detected in the atmosphere. However, due to the complex￾ity of WSOC and the wide range of physical properties rele￾vant to activation, an arbitrary choice of representative com￾pounds can fail in reproducing relevant physical and chemi￾cal properties. For the above reasons, a “realistic” represen￾tation of WSOC is necessary for cloud modelling purposes, but it is difficult to achieve through any individual analyti￾cal methodology or by choosing surrogate chemical compo￾sitions from a list of compounds detected in the aerosols. Functional group analytical techniques provide an alter￾native approach to traditional individual compound specia￾tion methods. These techniques analyse the different types of chemical structures (as for example total carboxylic groups, total carbonyls, etc.), but provide little or no information on the individual molecules (Decesari et al., 2000; Maria et al., 2002). Functional group methods have sometime been coupled to extraction-classification or separation tech￾niques, providing a more comprehensive description of OC and being able to account for up to 90% of the WSOC mass (Decesari et al., 2001; Varga et al., 2001). In partic￾ular, in the functional group analysis approach proposed by Decesari et al. (2000), WSOC is separated into three main classes of compounds: neutral compounds (NC), mono- /di-carboxylic acid (MDA) and polycarboxylic acids (PA). Quantitative measurements of WSOC by Total Organic Car￾bon (TOC) analyser and of proton concentration of the main functional groups contained in each of the three above mentioned classes by Proton Nuclear Magnetic Resonance (HNMR) can be used to formulate a set of a few “model” compounds representative of the whole WSOC (Fuzzi et al., 2001). A systematic technique for deriving model com￾pounds for biomass burning aerosol collected in the Ama￾zon has recently been submitted for publication (Decesari et al., 2006). Since the model compounds derived in this way reproduce quantitatively the average chemical structure of WSOC it can be argued that they may be used as best￾guess surrogates in microphysical models involving biomass burning aerosol. Likewise, model mixtures of WSOC for many different types of aerosol in a range of locations are available or their definition is in progress: . Urban aerosol, Bologna, Italy (Matta et al., 2003; Fuzzi et al., 2001), . Dust aerosol, Monte Cimone, Italy (Putaud et al., 2004), . Clean marine aerosol, Mace Head, Ireland (Cavalli et al., 2004b), . Biomass burning aerosol, Rondonia, Brazil (Decesari et al., 2006), . ACE Asia, Chinese outflow, Gosan, Jeju Island, Korea (Topping et al., 2004), . Boreal forest aerosol, Hyytial¨ a, Finland ( ¨ Cavalli et al., 2004a; Decesari et al., 2006). In summary, only a few studies have provided informa￾tion concerning both inorganic and organic aerosol chemi￾cal composition which can be directly used by cloud mod￾els. These papers provide a comprehensive description of the chemical composition of different aerosol types as a function of size (Chan et al., 1999; Zappoli et al., 1999; Pakkanen et al., 2001; Putaud et al., 2000; Temesi et al., 2001; Maria et al., 2003; Sellegri et al., 2003; Cabada et al., 2004; Chio et al., 2004; Sardar et al., 2005). Atmos. Chem. Phys., 6, 2593–2649, 2006 www.atmos-chem-phys.net/6/2593/2006/