Size-Resolved Surface-Active Substances of Atmospheric Aerosol

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Environmental Processes

Size-resolved surface active substances of atmospheric aerosol: reconsideration of the impact on cloud droplet formation Ana Krofli#, Sanja Frka, Martin Simmel, Heike Wex, and Irena Grgi# Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b02381 • Publication Date (Web): 26 Jul 2018 Downloaded from http://pubs.acs.org on July 26, 2018

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Environmental Science & Technology

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Size-resolved surface active substances of atmospheric aerosol: reconsideration of the

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impact on cloud droplet formation

3 Ana Kroflič†┴║, Sanja Frka†‡║*, Martin Simmel§, Heike Wex± and Irena Grgić†

4 5 †

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Department of Analytical Chemistry, National Institute of Chemistry, Ljubljana, 1000,

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Slovenia; ┴

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Atmospheric Chemistry, Leibniz Institute for Tropospheric Research, Leipzig, 04318,

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Germany; ‡

Division for Marine and Environmental Research, Ruđer Bošković Institute, Zagreb, 10000,

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Croatia; §

Modelling of Atmospheric Processes, Leibniz Institute for Tropospheric Research, Leipzig,

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04318, Germany; ±

Experimental Aerosol and Cloud Microphysics, Leibniz Institute for Tropospheric Research,

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Leipzig, 04318, Germany

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║

Co-first authors contributed equally to this work

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*Corresponding author

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Tel: +385 1 4561 185

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Fax: +385 1 4680 242

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Email address: [email protected]

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Abstract

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Our current understanding of the importance of surface active substances (SAS) on

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atmospheric aerosol cloud-forming efficiency is limited, as explicit data on the content of

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size-resolved ambient aerosol SAS, which are responsible for lowering the surface tension (σ)

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of activating droplets, are not available. We report on the first data comprising seasonal

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variability of size-segregated SAS concentrations in ambient aerosol particulate matter (PM).

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To assess the impact of SAS distribution within PM on cloud droplet activation and growth, a

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concept of surfactant activity was adopted and a parametrization developed, i.e. surfactant

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activity factor (SAF) was defined, which allowed translation of experimental data for use in

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cloud parcel modeling. Results show that SAS-induced σ depression during cloud activation

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may affect droplet number (Nd) as much as a two-fold increase in particle number, whereas by

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considering also the size distribution of particulate SAS, Nd may increase for another 10%.

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This study underscores the importance of size-resolved SAS perspective on cloud activation,

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as data typically obtained from aqueous extracts of PM2.5 and PM10 may result in misleading

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conclusions about droplet growth due to large mass fractions of supermicron particles with

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SAS deficit and little or no influence on CCN and Nd.

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Introduction

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One of the major uncertainties in the current understanding of the Earth’s climate is the effect

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that aerosol particles have on cloud formation processes and the resulting impact on the

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radiative balance.1,2 The ability of an aerosol particle to act as a cloud condensation nucleus

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(CCN) and to become a cloud droplet (i.e., its cloud-forming efficiency) is described by the

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Köhler theory.3 The theory accounts for a competition between the Kelvin term, which

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considers also the surface tension of particulate aqueous phase (σ), and the Raoult term,

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which links the surrounding water vapor pressure to the solute content. The interplay between 2 ACS Paragon Plus Environment

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both effects results in a size- and composition-dependent growth of hydrated particles/droplets

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in humid air and only a fraction of hygroscopic particles competing for the available water

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vapor in the surrounding can grow beyond their critical sizes for spontaneous growth at a

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given supersaturation. As larger particles nucleate easier than small ones, the effect of

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chemical composition on the cloud-forming efficiency is most significant in the submicron

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size-range particles. Coupling with inorganic components,4–6 both model and natural organic

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surface active substances (SAS) or surfactants have been shown to lower σ of atmospheric

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cloud, rain, and fog waters and aqueous extracts of atmospheric aerosol from various

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sources.7–13 By influencing the Kelvin effect, σ depression caused by SAS could promote

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cloud droplet formation and importantly affect cloud properties such as albedo.14 On the other

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hand, it is believed that displacement of SAS from the droplet bulk to the particle/droplet

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surface simultaneously attributes to a change in the Raoult term (opposing effect as from the

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σ depression) which also has to be accounted for.15,16 In a recent publication, however, a

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closure between chemical composition, growth factor measurements and CCN activity could

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not be achieved under particular conditions which was explained by a lack in accounting for

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the σ reduction of aerosol aqueous phase.17 Although diverse modeling efforts have been

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made to assess the influence of the observed σ depression on cloud droplet nucleation and

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growth, the magnitude and even the sign of the cumulative effect of SAS on cloud droplet

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number (Nd) are still subjects of controversy.16,18–23 The direct experimental evidence for σ

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depression in microscopic droplets remains elusive. Nozière et al. (2014) examined the

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dynamic development of surface tension in droplets containing SAS, and demonstrated that

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the effect of SAS on σ of growing droplets cannot be directly measured due to limitations of

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state-of-the-art instrumentation for studying cloud droplet formation which is unable to detect

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kinetically governed σ effects of aerosol SAS on CCN activity.24 By applying an alternative

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approach, Ruehl et al. (2016) measured the size of haze droplets up to the point of cloud 3 ACS Paragon Plus Environment


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droplet activation and beyond, for particles containing SAS.25 The observed droplet sizes at

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activation being larger than expected by the Köhler theory are explained by organics

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accumulated on the surface of haze droplets, forming a compressed film which reduces σ and

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allows for larger droplets to form prior to their activation. Gérard et al. (2016) further

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measured σ of isolated SAS from atmospheric aerosol samples at a range of dilutions,

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discussing that atmospheric haze droplets prior to activation still have the σ clearly lower than

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that of pure water.26 Nevertheless, a widely used parameterization in atmospheric models

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known as the κ-Köhler theory27 describing CCN activation ignores the influence of SAS by

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assuming that the σ of growing droplets is that of pure water, such that the experimentally

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derived hygroscopicity parameter κ correctly describes particle activation when used together

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with this assumption. Therefore, a more rigorous exploration of the content of ambient SAS

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and the conditions under which they exert an effect on droplet activation are urgently needed

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to elucidate their true impact on cloud-formation processes and global indirect aerosol

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forcing. Here, the particular examination of SAS distribution in particles of submicron size

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ranges, considered as critical for CCN activation, is explicitly addressed,17,26 because SAS

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might occur enriched at these sizes, compared to the bulk samples.

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Until now no explicit data on the size-resolved SAS in ambient particulate matter (PM) have

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been published. Former efforts were limited to measuring SAS in various bulk aerosol water

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extracts,28–36 including those that applied pre-concentrating solid-phase extraction (SPE)

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protocols26,37,38 used at the same time for the isolation and concentration of aerosol HUmic-

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LIke Substances (HULIS)e.g.,13. This is mainly due to the sensitivity limitations of classical

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methods used for low-level SAS quantification in atmospheric samples. Notwithstanding, the

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herein applied electrochemical method (phase sensitive alternating current (ac) voltammetry;

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out of phase mode) has been proven to be sensitive and directly applicable for the qualitative

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and quantitative characterization of SAS in various natural aqueous systems,e.g.,39–42 including 4 ACS Paragon Plus Environment

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bulk precipitation43,44 and aqueous aerosol extracts,34 serving as a platform for low-level SAS

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determination in aqueous extracts of size-segregated aerosols.

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We report the first data on size-segregated SAS concentrations in ambient aerosol particles

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with aerodynamic diameters between 0.04 and 15.6 µm, divided into nine size bins. For cloud

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modeling purposes, novel parametrization was developed which allowed us to account for σ

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effects on droplet formation in a size-resolved manner. For this purpose, size-resolved

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surfactant activity factors (SAF) were derived from the electrochemically determined size-

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segregated SAS, which were originally considered dissolved within the adsorbed water layer

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on the surface of the corresponding size-segregated particle population (i.e., within the water

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shell of hydrated particles/droplets in the particular size bin). SAS distribution within PM was

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obtained by combining size-resolved SAF with the measured PM mass size distribution. Size-

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segregated proxy data for σ were estimated according to Gérard et al.,26 the only report on the

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σ curves for the natural SAS of ambient PM2.5 samples. Finally, a cloud parcel model was

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applied to inspect size-resolved σ effects of ambient SAS on the kinetics of droplet growth

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and activation.

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EXPERIMENTAL SECTION

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Aerosol sampling

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Seasonal size-segregated and PM10 aerosol samples were collected in parallel at an urban

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background site of Ljubljana, Slovenia (approx. 279,000 inhabitants, 298 m a.s.l.). Size-

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segregated aerosols were collected on pre-baked aluminum foils (500 °C for 24 h) with a 10-

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stage low-pressure Berner cascade impactor (HAUKE, LPI 25/0,015/2) operated at ambient

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temperature at a flow rate of 25.8 L min−1. 2–3 consecutive 48–72 h samples were combined

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into each investigated sample set to ensure at least 90 µg of PM deposit for each size fraction 5 ACS Paragon Plus Environment


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as described elsewhere.45 In addition to ensure the sufficient amount of material for chemical

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analyses, stages 1 and 2 of each sample set were processed together (called stage 2a herein).

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In total, we examined four impactor sample sets (one for each season: winter (14/02–

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20/02/2015), spring (15/05–25/05/2015), summer (10/08–21/08/2015) and autumn (05/11–

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11/11/2015), each comprising nine size-segregated stages, representing the average of 6 to 12

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days. In parallel, PM10 samples were collected onto prebaked glass fiber filters (0.47 mm;

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Whatman) for 24 h at 2.3 m3 h−1 using a Leckel sampler. In each season (winter 02/2015;

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spring 05/2015; summer 08/2015; autumn 11/2015), 6 daily PM10 samples were processed

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together. The collected samples and the foil/filter blanks (no air drawn through the

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impactor/sampler) were stored at −18 °C until analysis.

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PM size distribution

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The impactor comprises 10 stages of nominal aerosol size ranges expressed in aerodynamic

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equivalent diameter, d; however, as already explained, stages 1 and 2 were combined (stage

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2a: 0.038–0.104 µm; stage 3: 0.104–0.16 µm, stage 4: 0.16–0.305 µm, stage 5: 0.305–0.56

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µm, stage 6: 0.56–1.01 µm, stage 7: 1.01–2.1 µm, stage 8: 2.1–3.99 µm; stage 9: 3.99–8.06

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µm, stage 10: 8.06–15.6 µm). Aerosol mass of each stage of size-segregated aerosol was

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determined by weighing the sample before and after the sampling; prior to weighing, all

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samples were conditioned for at least 24 h at a relative humidity of 50±5% and a temperature

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of 20±1 °C. For numerical modeling purposes (see below), discrete size-bin PM mass

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distributions (Figure 1a) were inverted to continuous size distributions and the model was

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initialized with the continuous PM size distributions of the respective seasons shown in

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Figure 1b. For details about the applied numerical treatment see Supporting Information (SI),

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Appendix 1.

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Aerosol pretreatment

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SAS of size-segregated aerosol and PM10 samples were concentrated by adopting a standard

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solid phase extraction (SPE) protocol for the isolation of aerosol HULIS.26,46,47 Aqueous PM

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extracts were first obtained by extraction of joined samples in 15–24 mL of high purity

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reagent Milli-Q water (Millipore, Bedford, MA, USA) for 24 h at 4 ºC, followed by filtration

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through a 0.22 µm pore size filter (Supelco, USA). Aqueous extracts were further treated

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according to the SPE procedure steps on C18 columns (SEP-PAK VAC, 3 mL, 500 mg,

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Waters; see SI, Appendix 3) to obtain MeOH isolates. Aqueous aerosol extracts and HULIS

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extracts (obtained after evaporation of MeOH extracts to dryness and redissolution in Milli-Q

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water) were further analyzed for their water-soluble organic carbon (WSOC and HULIS-C,

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respectively) and SAS content. Blank filters were also subjected to the same processing steps

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to ensure appropriate extraction procedure and control the purity of final extracts.

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SAS extraction efficiency. SAS extraction yield was determined as a ratio between SAS

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concentrations (in equiv. of model surfactant T-X-100) in aerosol aqueous extracts after and

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before the C18 SPE procedure. The applied procedure enabled high SAS yields (nearly

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100%), indicating their complete isolation from the aerosol water-soluble organic matter (SI,

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Appendix 3).

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Water-soluble organic carbon analysis

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WSOC and HULIS-C were analyzed by sensitive Combustion TOC Analyzer (Teledyne,

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Apollo 9000 HS) with a non-dispersive infrared gas detector (NDIR). In order to eliminate the

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inorganic carbonates, each sample was acidified with 2 M HCl to pH 2–3 before analysis.

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WSOC or HULIS-C of each sample was calculated as an average of three to five replicate

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measurements.



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SAS analysis

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Electrochemical measurements. The phase sensitive ac voltammetry was applied for SAS

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analysis, being already used as a successful tool for the determination of SAS in a plethora of

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environmental aquatic samples.39 Measurements (out-of-phase mode, frequency 77 Hz, and

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amplitude 10 mV) were performed with µAutolab-type II (Eco Chemie B. V., The

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Netherlands), GPES 4.6 software (Eco Chemie B. V., The Netherlands). A standard

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polarographic Metrohm cell of 50 cm3 with a three-electrode system was used: working

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electrode – hanging mercury drop electrode (HMDE; Metrohm, Switzerland; A = 0.01245

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cm2), reference electrode – Ag/AgCl/3 mol L−1 KCl, auxiliary electrode – platinum coil.

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Before each measurement, previously purified (450 °C for 5 h; charcoal organic residue

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removal) saturated NaCl (Kemika, Croatia) solution was added to the sample to adjust the

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electrolyte concentration to 0.55 mol L−1. In brief, because of their amphiphilic nature, SAS

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have the capability of spontaneous adsorption at different phase boundaries. Due to the

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hydrophobic character of the mercury electrode, its interface with aqueous electrolyte solution

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serves as a good model for the study of SAS.48 SAS adsorption at the surface of the mercury

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electrode changes its double layer capacitance, which is directly proportional to the measured

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capacity current (IC) at the applied potential. At the optimal potential for the adsorption of

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amphiphilic SAS (-0.6 V versus Ag/AgCl), IC decrease (compared to the capacity current of

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the supporting electrolyte alone (IC0)) is linearly dependent on the adsorbate concentration in

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aqueous solution, allowing for the precise quantification of low SAS concentrations.

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Method sensitivity. Interfacial tensiometers and drop shape analyzers are commonly in use for

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measurements of σ decrease due to the presence of SAS in aqueous solutions. However, due

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to the insufficient sensitivity, their usefulness for the investigation of ambient PM samples

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with low-level SAS is limited.e.g.,9,12,13 Taking tetraoctylphenolethoxylate (T-X-100) as typical

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model SAS, we compared sensitivities of ac voltammetry and tensiometry obtained with a 8 ACS Paragon Plus Environment

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digital tensiometer (Kruss, K10T, GmbH, Hamburg). Ac voltammetry is shown to be two

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orders of magnitude more sensitive than the conventional tensiometry (Figure S1b, for details

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refer to SI, Appendix 2).

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Calibration. Many scientists strive for the quantification of ambient aerosol surfactants,

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although without knowing their chemical nature or strength (i.e., how surface active they

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are).49 Traditional model surfactants are often used as surrogate substances for these versatile

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species;8,50,51 however, particular model surfactants have already been shown to fail to

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reproduce the overall surface-active properties of aerosol water-soluble fraction.e.g.,52 Some

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authors have already reported on the potential of more realistic representation of aerosol SAS

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deduced from real atmospheric samples.13,53 As we show that aerosol SAS fraction is

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completely isolated within the HULIS material with joint water soluble and hydrophobic

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properties, HULIS concentration can be regarded as a rough upper-limit estimate of aerosol

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SAS. Thus, instead of using model surfactants as commonly applied today, calibration with

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HULIS material isolated from the ambient PM10 samples collected in parallel to Berner

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impactor samples was performed for accurate quantification of SAS in size-segregated

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aerosols (details within SI, Appendices 3 and 4). Calibration plots ∆IC vs. concentration of

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HULIS-C were constructed and are shown in Figure S2. Limits of SAS detection and

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quantification are 0.1 and 0.16 mgC L−1 (equiv. of HULIS-C), respectively. Relative standard

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deviation obtained from three to five repetitive analyses of the same solution containing 1

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mgC L−1 is less than 5%.

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Numerical modeling

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The spectral microphysics model SPECS describes standard Köhler theory-based aerosol

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particle growth as well as droplet nucleation and growth with respect to water content using a

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2-dimensional grid.54 Thus, both, water and particulate mass were divided into discrete bins



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(360 for particulate mass with mass doubling every 8 bins, 264 for water mass with mass

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doubling every 4 bins). Dry aerosol was assumed to be an internal mixture where 50% of the

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particulate mass consisted of ammonium sulfate and 50% were insoluble substances, the latter

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not contributing to the Raoult term at all. The number of moles of solute was kept constant

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during the modeling. Surface tension (σ) was iteratively calculated for every time step from

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the respective dry PM size distribution and the condensed water load (giving us time- and

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size-resolved PM/water concentrations, c, see details below). Note that SAS bulk-surface

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partitioning was not accounted for, which could lead to an overestimation of the effect of σ on

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the modeled droplet growth.15,16 Nevertheless, the main focus of this work is to demonstrate

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the influence of size-resolved SAS on droplet growth, as compared to assuming a size

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independent σ. We do not want to elaborate on the absolute effect of σ, as that is still

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controversial. Recent literature has reported contradictory results, ranging from a possibly

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large effect of σ on atmospheric CCN concentrations (increase by a factor of 10)17 to cases for

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which a range of results, including a negligible impact on CCN activation55, has been

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reported.

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The model was initialized with the continuous dry PM size distributions of the respective

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seasons shown in Figure 1b. For the modeling purposes, d was converted into geometric

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diameters, geo, via the formula: geo = water/AP with particle density AP = 1.5 g cm3

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and water density water = 1.0 g cm3. Total aerosol number concentrations were 3.9×109,

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5.4×109, 1.4×1010 and 1.5×1010 m-3 for spring, summer, autumn and winter, respectively.

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Initially, equilibrium was assumed at a relative humidity (RH) of 99%, together with

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accounting for a possible σ reduction due to the presence of SAS in the distinct aerosol size

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fractions. The air parcel was lifted to a height of 250 m, starting at the 99% RH level, with a

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constant updraft velocity of 0.5 m s−1 as a standard case. The only microphysical process

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considered was water vapor condensation, i.e. droplet nucleation and further droplet growth 10 ACS Paragon Plus Environment

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by condensation. For the latter, a water accommodation coefficient of 0.5 was taken. The

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growth calculation was interactively coupled to the vapor phase, meaning that e.g.,

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supersaturation was explicitly calculated at each time step. Again, we stress that at each time

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step, σ was also calculated from the condensed water load (see size-dependent σ evolution

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during the modeling in SI, Appendix 11, Figure S11). Due to the 2D model configuration, the

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underlying dry aerosol particle distribution remained perfectly conserved throughout the

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model run while the spectrum referring to water mass evolved.

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As the determination of the influence of SAS on the σ of aerosol water layer is beyond the

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scope of this study, experimentally-obtained σ (mN m−1) dependence on PM/water

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concentration (c in µg µL−1 aqueous solution) was taken from Gerard et al.26 and a model

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function was fitted to the data (details in SI, Appendix 5, Eq. S2) to obtain the equation used

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in the aerosol model (Case 1):

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=

.

.

+ 36.638

(1)

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Note, cumulative SAS within PM2.5 was considered in the cited work; therefore, as we wanted

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to also explicitly account for SAS distribution within PM, further data treatment was needed.

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To account for a particular case of size-resolved SAS described below (Case 2), adapted PM

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size distributions with considering experimentally-derived surfactant activity factors (SAF)

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were initialized as well (Figure 1d; obtained according to SI Eq. S3, see Appendix 6) and used

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only for the modeling of σ in Case 2, i.e. for the calculation of c (the modeled PM size

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distribution remained unchanged).

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SAF$ =

%&%' %&% ().* +,' +, ().*

(2)

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where SASi and PMi are the experimentally determined SAS and PM concentrations of the

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corresponding size bin i, respectively. Namely, SAF is a weight that corrects σ dependence on

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c derived from Gerard et al.26 for the size-segregated SAS aspect brought-up in this work, 11 ACS Paragon Plus Environment


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describing the enrichment of SAS in the particular size bin: SAF values >1 represent the

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fractions enriched with SAS, while values 1 at stages 3 and 4 for all seasons (Figure

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1c), which resulted in more droplets formed in the case of SEG-SAS in comparison to EVEN-

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SAS (except in winter). With this we show that averaged SAS data over a broader PM size

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range (PM2.5 or PM10) are not necessarily representative for the cut-off size range and can

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result in misleading conclusions about the droplet growth. As an extreme case, consideration

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of the water-soluble size-segregated SAS distribution expressed on the surface area of particle

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population (FILM-SAS case; details in SI, Appendix 7) resulted in a relatively low Nd

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compared to EVEN-SAS and SEG-SAS (SI, Figure S6). Furthermore, a SAS-induced σ

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decrease during droplet growth affected Nd about as much or even more than the factor-of-two

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increase in CCN in WAT-2 (Figure 3a). Nenes et al.61 found numerous conditions where the

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effect of chemical composition on Nd was comparable to the effect of the CCN number. Under

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marine conditions, the influence of σ accounted for up to 50% of the Twomey effect, whereas

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under urban conditions it exceeded it. Moreover, for urban aerosols, inclusion of the σ effect

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exerted by water-soluble organic compounds may increase the CCN number concentration up

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to 110% relative to the case in which only the inorganic aerosol composition is considered.60

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Atmospheric relevance

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To date, the influence of SAS on cloud formation has mainly been exploratory and partially

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speculative, as explicit data on the abundance and size distribution of aerosol SAS,

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responsible for lowering σ of activating droplets, have been unknown. Electrochemical

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determination of low concentrations of SAS, together with the developed parametrization

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enabled us to model droplet activation and growth with considering the size-resolved σ effects

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on cloud formation. According to our results, SAS-induced σ depression during 18 ACS Paragon Plus Environment

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CCN activation (Case 1, without considering the influence of SAS partitioning between the

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droplet surface and the bulk which likely overestimates the σ effect) may influence Nd to a

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similar extent or even more than increasing particle number by a factor of two. The

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investigated water-soluble SAS unlikely exert the observed surface-film effect on droplet

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activation, as there is not enough SAS for lowering the σ of submicron particles substantially

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(SI, Appendix 11). It should rather be volatile organic compounds62 or organics adsorbed at

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the droplet surface from the gas phase,63 as proposed recently. Based on considering also the

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size distribution of particulate SAS, we showed that Nd may increase for another 10% (up to

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12% if moderate σ depression is considered), already when compared with a non-size

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resolved treatment of SAS. This effect is especially pronounced in spring and summer, when

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smaller particles (d ~ 100−250 nm) are enriched with SAS. The demonstrated influence of

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size-segregated SAS on cloud formation is comparable to a 26% increase in apparent particle

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hygroscopicity due to acetaldehyde adsorption to the aerosol-gas interface and the resulting σ

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reduction.62 Although the observed 10% droplet number increase is not likely to result in

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significant changes with respect to cloud lifetime and precipitation formation in urban

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regions, there could be a special situation where such CCN number increase triggers the

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precipitation. As the latter is most likely to happen under much cleaner than tested conditions

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with low CCN numbers (where SAS effect on droplet number is expected to be larger),

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studies should be repeated on aerosol samples from pristine environments (remote, maritime,

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polar etc.). We believe that the abovementioned increase in Nd due to size-resolved SAS most

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importantly influences the optical properties of clouds, which could have an indirect impact

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on the climate forcing. If globally relevant, 10% increase in Nd changes the cloud albedo for

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up to ~1%, corresponding to a radiative forcing in the order of −1 Wm−2.14,50 To better assess

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the magnitude of the size-resolved SAS effect on cloud droplet formation, further large-scale



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field studies and climate predictions using the same approach are needed, especially in areas

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that are critical for the climate response, such as oceanic regions.

443 444

Acknowledgments

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We thank the Faculty of Chemistry and Chemical Technology University of Ljubljana,

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Slovenia (UL FCCT) for the permission to install the Berner impactor in the area of the

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faculty. The authors acknowledge Dr. Bojan Šarac from UL FCCT for the access to the

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tensiometer and Dr. Janja Turšič from the Environment Agency of the Republic of Slovenia,

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Ljubljana for providing PM10 samples and performing WSOC analyses. We gratefully

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acknowledge Dr. Hartmut Herrmann from TROPOS for enabling this international

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collaboration and Dr. Frank Stratmann also from TROPOS for a fruitful discussion. The

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authors acknowledge the financial support from European Union Seventh Framework

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Programme (FP7 2007-2013) Marie Curie FP7-PEOPLE-2011-COFUND (GA no291823)

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through NEWFELPRO project (Contract no. 47) and the Slovenian Research Agency

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(research core funding No. P1-0034).

456 457

Supporting Information

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Detailed procedures of data manipulation: continuous PM and SAS distributions, sensitivity

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of electrochemical determination of SAS, SAS isolation and extraction efficiency,

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quantification of SAS, surface tension dependence on PM concentration, different

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representations of SAS within aqueous aerosols, updraft velocity and lower-limit surface

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tension impacts, drop number and cut-off diameter; surface tension evolution during droplet

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nucleation; 1 Table, 11 Figures.

464 465

References


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(1)

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Aerosol size

Page 29 Environmental of 29 Science & Technology

ACS Paragon Plus Environment Surfactant activity factor = Surfactant enrichment

Size-Resolved Surface-Active Substances of Atmospheric Aerosol

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