# Contribution of sea spray to aerosol size distributions measured in a South African coastal zone

Faith February, Jacques Piazzola, Katye Altieri, Alexander M.J. van Eijk

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Faith February, Jacques Piazzola, Katye Altieri, Alexander M.J. van Eijk. Contribution of sea spray to aerosol size distributions measured in a South African coastal zone. Atmospheric Research, 2021, 262, pp.105790. 10.1016/j.atmosres.2021.105790. hal-03655243

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# Contribution of sea spray to aerosol size distributions measured in a South African coastal zone

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Faith J. February<sup>a,*</sup>, Jacques Piazzola<sup>b</sup>, Katye E. Altieri<sup>a</sup> and Alexander M. J. Van Eijk<sup>c, d, e</sup>

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Oceanography Department, University of Cape Town, South Africa; katye.altieri@uct.ac.za

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Mediterranean Institute of Oceanography, University of Toulon, France; piazzola@univ-tln.fr

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Netherlands Organization for Applied Scientific Research (TNO), The Hague, Netherlands;

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Fraunhofer Institute of Optronics, System Technologies, and Image Exploitation (IOSB),

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Ettlingen, Germany;

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LHEEA (UMR 6598), Ecole Centrale de Nantes, France;

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lex.vaneijk@tno.nl

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* Correspondence: fbrfai001@myuct.ac.za; University of Cape Town, Private Bag X3, Rondebosch, 7701, South Africa

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**Abstract:** The atmospheric aerosol has a large influence on global climate through its ability of scattering and absorbing electromagnetic radiation, which affect the Earth's radiative balance. Characteristics, such as size distribution, chemical composition and hygroscopic properties are important for improving global climate model projections of natural sea spray aerosols, which are numerically dominant in the global aerosol budget. Previous experimental studies in coastal locations revealed a complex mixing between natural and anthropogenic aerosols. This complexity makes it difficult to characterize the behavior of natural sea spray aerosols in a simplified form that is suitable for global models. The aim of the present paper is to characterize the size distributions of natural sea spray aerosols at a coastal site in False Bay, South Africa. The opening of False Bay towards the Southern Ocean with unlimited fetch from Antarctica provides a unique opportunity to measure and focus on pristine marine air masses solely. A large observational data set from the First European-South African Transmission Experiment (FESTER) was analyzed and two case studies are presented to illustrate the contribution of sea spray to aerosol size distributions under pure marine and mixed air mass conditions, respectively. A set of conditions for measuring pure marine aerosols in False Bay was established. The results of the relationship of aerosol concentrations with wind speed reveals the distinct behavior of natural sea spray aerosols and demonstrates the pure marine influence of the Southern Ocean in False Bay. Comparison of the aerosol size distributions to a coastal site in the Mediterranean Sea, attest to the contribution of sea spray to aerosol size distributions in False Bay.
32 **1. Introduction**

33 Although atmospheric aerosols are a large contributor to climate change, quantifying their
34 complex impact remains an important scientific challenge (Intergovernmental Panel on Climate
35 Change (IPCC), 2014). Atmospheric aerosols have a direct effect on the Earth's radiative balance
36 by scattering and absorbing electromagnetic radiation. Aerosols also have an indirect effect on
37 climate by acting as cloud condensation nuclei (Schmale et al., 2018; Sorooshian et al., 2013).
38 The multiple impacts of aerosols form a key component in models predicting climate change, but
39 the uncertainties surrounding aerosols (e.g., characteristics, size distributions, behavior with
40 changes in meteorological conditions) lead to low confidence levels of the climate prediction
41 models (IPCC, 2014). Despite numerous research studies at different locations (Van Eijk et al.,
42 2016), the understanding of aerosol properties is still insufficient to accurately predict future
43 climate (Alonso-Blanco et al., 2018). In order to improve climate models and predict the impact
44 of climate change more accurately, a better understanding and characterization of atmospheric
45 aerosols is needed. In particular, the lack of observational data of natural aerosols contributes to
46 uncertainties in understanding the climate system and its potential changes (IPCC, 2014).

47 The largest natural aerosol source globally is the ocean (Richter and Veron, 2016) and marine
48 aerosols are the most abundant natural aerosol species (Gaston et al., 2018). Marine aerosols
49 consist of primary sea spray (i.e., mixed sea salt and organics) as well as secondary aerosols
50 formed from oceanic emissions (e.g., dimethyl sulfide, volatile organic compounds, ammonia)
51 (O'Dowd et al., 1997). Several experimental studies have pointed to the presence of significant
52 concentrations of organic matter in marine aerosol, more particularly in the submicronic size
53 range (e.g., Kleefeld et al., 2002). For instance, O'Dowd et al. (2004) note that during bloom
54 periods, the organic fraction dominates and contributes 63% to the submicrometer aerosol mass
55 (about 45% is water-insoluble and about 18% water-soluble). In winter, when biological activity
56 is at its lowest, the organic fraction decreases to 15%.

57 The emission of primary sea spray aerosols results from the interaction between wind and
58 waves on the ocean surface. An increase in wind speed over the water leads to an increase in
59 the wave action and whitecap formation on the ocean surface (Andreas et al., 1995; Monahan et
60 al., 1983; Ross and Cardone, 1974). As the waves break, bubbles are entrained in the water and
61 move to the surface. When the bubbles burst, sea spray aerosols are released as film drops or
62 jet drops (Monahan et al., 1983), with a typical size range of 0.1 – 10 µm. At higher wind speeds
63 (~ > 11 m s⁻¹ (Andreas et al., 1995) the wind tears droplets directly off the wave crests producing
spume droplets (> 20 µm) (Andreas et al., 1995; Anguelova et al., 1999; Veron et al., 2012). Thus, sea spray production scales with wind speed, and to first order, an increase in wind speed results in an increased concentration of sea spray aerosols over a range of sizes.

In addition to wind speed, the fetch (the distance an air mass travels over water) also influences the sea spray aerosol production processes (Piazzola et al., 1998; Van Eijk and De Leeuw, 1992). The longer the fetch, the larger the production zone of sea spray aerosols, and hence an increase in concentration (Piazzola et al., 2003; Piazzola et al., 2010). Since submicron particles (< 1 µm) have longer residence times (Gong et al., 1997; Myhre et al., 2013), these can be transported with the longer fetch from remote marine regions (Krishna Moorthy et al., 1997) and further increase the atmospheric sea spray aerosol concentrations.

Coastal areas are ideal for time series observations of sea spray aerosols, however they can be challenging due to the mixing of emission types (e.g., dust, urban pollutants, and ocean emissions) (Paton-Walsh et al. 2018) and complex meteorology (e.g., land-sea breezes) (Freeman et al. 2017). Regional climate and air quality models struggle to simulate coastal areas in part due to the complexity of emissions and in part due to a lack of observational datasets (Seinfeld et al. 2016). In addition to sea spray aerosols, coastal areas are impacted by local cities, which are typically associated with high aerosol concentrations and poor air quality due to anthropogenic emissions of aerosols and their precursor gases. Furthermore, air masses may contain natural aerosols generated over land and advected to the coast, although these are typically lower in concentration than local anthropogenic aerosol sources (Rinaldi et al., 2009). For convenience, we will refer to aerosols generated on land (natural or anthropogenic) as continental aerosols, to underline that their production is on land and not over the sea. In offshore flow conditions, these continental aerosols are transported away from their production zones, dispersing more rapidly in high-wind conditions. Because of gravitational settling the ocean will then act as a sink (Van Eijk and De Leeuw, 1992). The concentration of continental aerosols thus decreases with wind speed when the air flows out over the sea, where no production of continental aerosols takes place.

Multiple studies have pointed out that fetch, aerosol size and wind speed scaling can serve as indicators for the possible presence of sea spray aerosol and a continental fraction in the atmospheric aerosol loading. These studies address a variety of sites in the Northern Hemisphere including Porquerolles (France) (Piazzola and Despiau, 1997), Vindeby (Denmark) (Vignati et al., 1999), South Uist (Outer Hebrides) (Smith et al., 1991), North Atlantic Ocean
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(Hoppel et al., 1990) and Oahu (Hawaii) (Reid et al., 2006), but the literature addressing the
Southern Hemisphere is relatively sparse.

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The present study addresses the lack of observational data in the Southern Hemisphere with
aerosol measurements acquired at the unique coastal location of Simon's Town in False Bay,
South Africa. During the First European-South African Transmission Experiment (FESTER) (Eisele
et al., 2016; Van Eijk et al., 2016), a series of aerosol size distribution measurements were
conducted from April 2015 to January 2016 in Simon's Town. This extensive data set is used to
determine the effect of wind speed and fetch on sea spray aerosol concentrations.

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The complex meteorology and complexity of emissions in coastal areas are addressed with the
unique orography and location of False Bay. False Bay has a horseshoe shape with the opening
towards the Southern Ocean and hence, an almost unlimited fetch to the Antarctic. This allows
for pristine marine air masses with no continental influence (natural or anthropogenic) to enter
the bay and reach Simon's Town. A Global Atmosphere Watch (GAW) station is located at the
entry of the Bay, at Cape Point, and measurements have shown that the air reaching the station
from Antarctica is among the cleanest on the planet (Brunke et al., 2004). These air masses
attract our interest for two reasons. First, the concentrations of natural sea salt aerosols are
thought to be more prominent in the Southern Ocean marine boundary layer than in other parts
of the world (Penner, 2019). Secondly, pure marine conditions may be a rare occurrence, even
in the Southern Hemisphere. According toBohlmann et al. (2018), in their voyage over the
Atlantic Ocean from the Northern to the Southern Hemisphere, pure marine conditions were
only observed near Cape Town, South Africa.

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In addition to the pure marine conditions, False Bay also experiences mixed air with the
influence of nearby land areas. In this paper, two case studies, representative for pure marine
and mixed air masses, will be discussed to highlight the specific characteristics of pure marine air
masses and to explore the differences between the different air masses. The results are also
compared to historic marine cases for sites in the Northern Hemisphere.

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## 2. Environmental data collection and data processing

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### 2.1. Field site

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False Bay is an almost enclosed bay at the southern tip of the African continent in South
Africa (Figure 1). On the left it is shielded by the mountainous Cape Peninsula, on the right,

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it is shielded by the south coast of South Africa, and to the north there is a sandy plane.

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False Bay has an opening of ~30 km to the South Atlantic Ocean, which allows oceanic air

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masses and wave fields to enter the bay. The region around False Bay is characterized by

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warm, dry south-easterly winds in summer and north-westerly winds in winter. As such,

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there is the potential for a variety of continental and marine aerosol types to be

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transported to the measuring site. A more descriptive and recent review of False Bay can be

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found in Pfaff et al. (2019).

<figure><img src="image_2.png" /><figcaption>**Figure 1.** Google images of False Bay, South Africa at the southern tip of the African continent. The inset shows the location of the aerosol sampler at 34°11′S, 18°26′E (X), the meteorological sampler at 34°11′S, 18°27.5′E (Y) and the 120° to 155° wind sector used to focus the data analysis on sea spray aerosols. (Figure to be printed in color.)</figcaption></figure>

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Figure 2 shows the vastness of False Bay with an extended production zone for sea spray

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aerosols. The aerosol measurement site was located in Simon's Town, directly at the water

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edge, at a height of approximately 3 m above the water (X in Figure 1 and red arrows in

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Figure 2). Possible local factors of kelp and rocks in front of the probes (Figure 2b) are

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mitigated by the vast extent of the water mass surrounding the measurement site as well as

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the high wind speeds during the analysis periods ensuring a lot of throughput from sea

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spray aerosols produced elsewhere.
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Meteorological data were acquired at the Roman Rock lighthouse (Y in Figure 1 and red arrows in Figure 2), a well exposed site in the Bay, about 2 km from the aerosol probes. Temperature, wind speed, wind direction, relative humidity and atmospheric pressure were measured using a Gill HS-90 Ultrasonic anemometer and a standard meteorological station. The bearing from Roman Rock to the edge of the Cape Peninsula is 155°, which differs slightly from the aerosol measurement site.

<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

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<caption>Figure 2. a) Photograph of False Bay taken from Old Signal School in Simon's Town with red circle indicating Roman Rock lighthouse, red arrow indicating location of aerosol probes and yellow arrow pointing towards the entrance of the bay. b) Close-up of aerosol measurement site, showing one optical counter while the other one was down for maintenance. Roman Rock lighthouse indicated by the red circle and the opening of False Bay in the direction of the yellow arrow. (Figure to be printed in color.)</caption>

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The bearing from the measurement site to the southern coast (Pringle Bay) is 120° and to the edge of the Cape Peninsula is 150° (www.igismap.com/map-tool/bearing-angle, accessed on 11 April 2019), providing a 30° view angle towards the ocean. Daily images were taken with an Arecon camera at 08h00, 12h00 and 16h00 from a position of ~ 14m
162 above the probes in an eastward direction towards the bay to give a visible account of the
163 weather and sea state.

164 In addition to the experimental observations, spatio-temporal fields of wind speed and
165 direction were generated from the numerical Weather Research and Forecast (WRF) model
166 (Skamarock - WRF (V3.9)). This is a mesoscale model with terrain following coordinates.

167 GFS analysis data from NOAA (https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/global-forcast-system-gfs, accessed 16 April 2019) in 0.5° horizontal resolution

168 were used as input data for the simulations. Nested runs were made to improve the
169 resolution. The model time step was 45 s and the output frequency was set to 1 hourly. A
170 simple 1D ocean mixed layer model obtained from the Advanced Research WRF User's
171 guide (http://www2.mmm.ucar.edu/wrf/users/docs/user_guide_V3/contents.html, accessed 16 April 2019) was used in the simulation. The domain was set to 3.3 km
172 resolution, the wind speed was taken at 10 m above ground level.

173 The domain was set to 3.3 km
174 resolution, the wind speed was taken at 10 m above ground level.

175 The raw aerosol data provided by the two optical probes were stored every second and
176 later resampled to create a single particle size distribution (PSD) averaged over 15 minutes.
177 The combined spectrum of the two probes spanned a particle diameter (D) range of 0.21 –
178 45 µm, distributed over 91 size bins. Aerosol concentrations were expressed as dN/dD in
179 units [µm⁻¹ cm⁻³]. These concentrations were normalized to 80% relative humidity by a
180 growth factor given by Equation 1 (Fitzgerald, 1975):

181 The combined spectrum of the two probes spanned a particle diameter (D) range of 0.21 –
182 45 µm, distributed over 91 size bins. Aerosol concentrations were expressed as dN/dD in
183 units [µm⁻¹ cm⁻³]. These concentrations were normalized to 80% relative humidity by a
184 growth factor given by Equation 1 (Fitzgerald, 1975):

185 The aerosol diameters were multiplied with the growth factors and polynomials of 1st
186 (Junge) and 5th order were fitted to the resulting size distribution. These polynomials
187 provide a better representation of the distribution by smoothing the noise of individual bin
188 counts. We will denote the 5th order polynomial fits by PSDᵢ, where the subscript
189 i identifies this PSD as a fit to a single, 15-minute long, data block of aerosol sampling
190 containing concentrations of 91 individual size bins.

191 The aerosol diameters were multiplied with the growth factors and polynomials of 1st
192 (Junge) and 5th order were fitted to the resulting size distribution. These polynomials
193 provide a better representation of the distribution by smoothing the noise of individual bin
194 counts. We will denote the 5th order polynomial fits by PSDᵢ, where the subscript
195 i identifies this PSD as a fit to a single, 15-minute long, data block of aerosol sampling
196 containing concentrations of 91 individual size bins.

## 2.2. Aerosol sampling and analytical procedures

176 Aerosol particle concentrations were measured continuously from April 2015 to January
177 2016 with two Classical Scattering Aerosol Spectrometer Probes (CSASP – 100-HV and
178 CSASP – 200; Particle Measuring Systems (PMS), Colorado, USA).

179 The raw aerosol data provided by the two optical probes were stored every second and
180 later resampled to create a single particle size distribution (PSD) averaged over 15 minutes.
181 The combined spectrum of the two probes spanned a particle diameter (D) range of 0.21 –
182 45 µm, distributed over 91 size bins. Aerosol concentrations were expressed as dN/dD in
183 units [µm⁻¹ cm⁻³]. These concentrations were normalized to 80% relative humidity by a
184 growth factor given by Equation 1 (Fitzgerald, 1975):

185 The aerosol diameters were multiplied with the growth factors and polynomials of 1st
186 (Junge) and 5th order were fitted to the resulting size distribution. These polynomials
187 provide a better representation of the distribution by smoothing the noise of individual bin
188 counts. We will denote the 5th order polynomial fits by PSDᵢ, where the subscript
189 i identifies this PSD as a fit to a single, 15-minute long, data block of aerosol sampling
190 containing concentrations of 91 individual size bins.

189 We will denote the 5th order polynomial fits by PSDᵢ, where the subscript
190 i identifies this PSD as a fit to a single, 15-minute long, data block of aerosol sampling
191 containing concentrations of 91 individual size bins.

191 The aerosol diameters were multiplied with the growth factors and polynomials of 1st
192 (Junge) and 5th order were fitted to the resulting size distribution. These polynomials
193 provide a better representation of the distribution by smoothing the noise of individual bin
194 counts. We will denote the 5th order polynomial fits by PSDᵢ, where the subscript
195 i identifies this PSD as a fit to a single, 15-minute long, data block of aerosol sampling
196 containing concentrations of 91 individual size bins.

$$G = 0.81 * e^{\left(\frac{0.066 * \frac{RH}{100}}{1.058 - \frac{RH}{100}}\right)} \quad (1)$$

186 The aerosol diameters were multiplied with the growth factors and polynomials of 1st
187 (Junge) and 5th order were fitted to the resulting size distribution. These polynomials
188 provide a better representation of the distribution by smoothing the noise of individual bin
189 counts. We will denote the 5th order polynomial fits by PSDᵢ, where the subscript
190 i identifies this PSD as a fit to a single, 15-minute long, data block of aerosol sampling
191 containing concentrations of 91 individual size bins.

188 The aerosol diameters were multiplied with the growth factors and polynomials of 1st
189 (Junge) and 5th order were fitted to the resulting size distribution. These polynomials
190 provide a better representation of the distribution by smoothing the noise of individual bin
191 counts. We will denote the 5th order polynomial fits by PSDᵢ, where the subscript
192 i identifies this PSD as a fit to a single, 15-minute long, data block of aerosol sampling
192 containing concentrations of 91 individual size bins.

192 We will denote the 5th order polynomial fits by PSDᵢ, where the subscript
193 i identifies this PSD as a fit to a single, 15-minute long, data block of aerosol sampling
194 containing concentrations of 91 individual size bins.

193 We will denote the 5th order polynomial fits by PSDᵢ, where the subscript
194 i identifies this PSD as a fit to a single, 15-minute long, data block of aerosol sampling
195 containing concentrations of 91 individual size bins.

195 We will denote the 5th order polynomial fits by PSDᵢ, where the subscript
196 i identifies this PSD as a fit to a single, 15-minute long, data block of aerosol sampling
196 containing concentrations of 91 individual size bins.

196 We will denote the 5th order polynomial fits by PSDᵢ, where the subscript
197 i identifies this PSD as a fit to a single, 15-minute long, data block of aerosol sampling
197 containing concentrations of 91 individual size bins.
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Each PSDᵢ was stored in a separate datafile, along with other relevant information such as date, time, and meteorological conditions. A total of 16 568 files were created for the full duration of the FESTER experiment, covering roughly 60% of the total experiment time. Gaps in the data acquisition were mainly due to equipment failure, electricity cut-offs, maintenance, data downloading and severe weather conditions.

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To obtain average aerosol properties over longer timeframes (e.g., hours to days), consecutive datafiles (PSDᵢ's) were averaged to evaluate numerical aerosol concentrations across the full size spectrum. The resulting averaged concentrations were again fitted to a 5th order polynomial to create a PSDᵣ, where the r signals that this particle size distribution is representative of a longer than 15-minute time period.

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## 3. Analysis

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### 3.1. Selection criteria for sea spray aerosols

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Since the main focus is on sea spray aerosols, conditions conducive to high concentrations of sea spray particles were selected a priori. These conditions correspond to a sustained flow (i.e., for more than 24 hours) with significant winds from a south-easterly (SE) direction, when oceanic air masses can enter False Bay (cf. Section 2.1). In order to also capture the dynamic behavior of sea spray, the selection was further narrowed to episodes that correspond to a substantial wind speed increase (preferably > 5 ms⁻¹) followed by a subsequent decrease over a sustained period of southeasterly flow. The wind speed interval was roughly 8 – 22 ms⁻¹.

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To determine the history of the air masses entering False Bay (i.e., the fetch), HYSPLIT (Draxler et al., 2017; Stein et al., 2015) was used to generate 72-hour air mass back trajectories. These trajectories represent the path an air mass has taken over the last 3 days before arriving at the ground level of the measurement site. Height values, extracted from the calculations of these trajectories, indicate whether the air mass was aloft or on the surface. A surface flow is likely to acquire sea spray aerosols when moving over the ocean.

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Applying the criteria described above, about 30 periods of sustained SE winds from the 120° – 155° sector were identified in the data set and 16 periods were analyzed. Two representative case studies will be presented to illustrate the effect on the aerosol size distributions. The first case study (20 – 23 July 2015) occurred towards the end of winter
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when there was a period (~3 days) of sustained SE winds. The air masses came directly from the deep south and remained over the sea before entering through the opening of FB to the measurement site. The second case study (28 – 30 November 2015) occurred in early summer when there was a period (~ 2 days) of high wind speeds with SE flow. The air masses in case study 2 skirted the continent before entering the bay. The length of the case studies corresponds to 216 data files for case study 1 and 102 data files for case study 2. These case studies are now analysed separately.

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## 3.2. Case study 1: 20 – 23 July 2015

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The timeframe for case study 1 was 20 – 23 July 2015 when there was sustained SE flow and high wind speeds (Figure 3). Prior to case study 1, on 18 – 19 July, there was a weak north-westerly flow. These conditions are consistent with a modest influx of continental aerosols (natural and anthropogenic) from the Cape Town area and limited air-sea interaction. Therefore, we assume that very little or no sea spray aerosols were present at the start of the case study.

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On 20 July 2015 the wind changed to the south-easterly direction and the wind speed increased abruptly to 12 ms⁻¹. On 21 July, it then blew for approximately 10 hours at an average speed of 14 ms⁻¹ (blue circle in Figure 3). In the afternoon, the wind speed steadily increased to above 20 ms⁻¹. The high wind speeds increased the wind-wave interaction, as evident in the daily images that show more whitecaps as the wind speed increases. At this time (red circle in Figure 3), the wind direction varied between 130° – 140°, i.e., air masses entered through the opening of False Bay (cf. Figure 1). On 22 July, the wind speed decreased steadily to 8 ms⁻¹, until a change in wind direction marked the end of case study 1. Within the timeframe of decreasing winds the speed averaged 14 ms⁻¹ for ~ 3 hours (green circle in Figure 3).
<figure><img src="image_5.png" /><figcaption>Figure 3. Wind speed (ms⁻¹, solid line left axis) and wind direction (degrees, dotted line right axis) for 18 - 24 July 2015. The blue circle indicates an average wind speed of 14 ms⁻¹, the red circle includes the peak of 21 ms⁻¹ and the green circle indicates the period of decrease in wind speed with an average of 14 ms⁻¹. The vertical black lines indicate the period of case study 1. (Figure to be printed in color.)</figcaption></figure>

The local observations were comparable to the mesoscale weather as simulated by the numerical WRF-model. In the simulation, on the evening of 19 July a southerly wind developed over the whole domain of several hundreds of kilometres. This southerly flow persisted for 3 consecutive days and the local wind speed reached its maximum (cf. Figure 3) on 22 July 22h00 (Figure 4). The boundary layer height over the bay was less than 500 m, suggesting limited vertical mixing and a surface wind that is favourable for sea spray production.

<figure><img src="image_6.png" /></figure>
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Figure 4. Wind field over False Bay for 22 July 2015. The arrows indicate the wind direction and the length of the arrow represent the wind speed. Atmospheric pressure in hPa is indicated by the colour scale. (Figure to be printed in color.)

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HYSPLIT back trajectories further confirm that the air masses were coming from the deep south (Figure 5). With Antarctica being ~4000 km from South Africa, an unlimited fetch was obtained during case study 1. Even when the air mass curved towards the east, it remained over the sea before it entered False Bay. The bottom panel of the images shows the height in meters and confirms that the trajectories remained close to the surface of the ocean.

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<figure><img src="image_7.png" /></figure>

Figure 5. The 72-hour HYSPLIT back trajectories for 21 July 2015 at 08h00, 22 July 2015 at 14h00 and 23 July 2015 at 02h00. The starting height was 100 m and the vertical motion method set to 0 for the calculations. The bottom of the figure indicates the height of the air masses above ground level.

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The local observations (Figure 3), the numerical mesoscale wind and pressure fields (Figure 4), and the HYSPLIT back trajectories (Figure 5) all confirm that Case study 1 represents a time when pure marine air masses were sampled at the study site.

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### 3.3. Case study 2: 28 – 30 November 2015

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Following the selection criteria of sustained strong winds from the south-easterly direction, the timeframe 28 – 30 November 2015 was identified as a second case study. In general, strong winds existed prior to the case study (Figure 6). The wind direction, which varied between 100° – 170°, indicates that the air mass reaching the measurement site likely crossed land to the east of False Bay, as well as the Cape Peninsula to the west (cf. Figure
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1). Consequently, the atmosphere of False Bay may have contained a mixed aerosol loading of continental and sea spray aerosols at the onset of the case study.

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Case study 2 started in the early morning of 28 November, after the wind had dropped to 9 ms⁻¹ for a few hours. The wind speed quickly reached ~ 12 ms⁻¹ and persisted for ~ 6 hours (blue circle in Figure 6). Then, the wind speed increased further to 16 – 18 ms⁻¹ and these conditions persisted (with a short exception) until late evening of the 29th. An average wind speed of 17 ms⁻¹ occurred over a 6-hour timeframe (Figure 6; red circle). On 30 November, the wind speed gradually decreased until reaching a minimum in the late afternoon, marking the arrival of a front and the end of case study 2. An average wind speed of 13 ms⁻¹ occurred over a 4-hour timeframe as the wind decreased (green circle in Figure 6).

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For the duration of case study 2, the wind direction was consistently between 140° and 155°, signalling that the air mass entered the Bay from the ocean. In combination with the high wind speed, conditions were thus favourable for wind-wave interaction and sea spray production. This was confirmed by the daily pictures, which showed an abundance of whitecaps in the bay.

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<figure><img src="image_8.png" /></figure>

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<caption>Figure 6. Wind speed (ms⁻¹, solid line left axis) and wind direction (degrees, dotted line right axis) for 26 - 1 December 2015. The blue circle indicates an average wind speed of 12 ms⁻¹, the red circle an average of 17 ms⁻¹ and the green circle an average of 13 ms⁻¹. The vertical black lines indicate the period of case study 2. (Figure to be printed in color.)</caption>

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The numerical mesoscale wind fields generated by WRF confirmed the south-easterly flow during case study 2 (Figure 7). In contrast to the purely marine air flow (case 1), the air mass
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travelled over the southern tip of the African continent. This was also observed with HYSPLIT back trajectories (Figure 8). During this time, continental aerosols may have been picked up by the air mass and it is thus likely that the air mass arriving at the measurement site contained a mixture of continental and marine aerosols.

<figure><img src="image_9.png" /><figcaption>Figure 7. Wind and pressure fields over False Bay for 29 November 2015 at 16h00. The arrows indicate the wind direction and the length of the arrow represent the wind speed. The pressure in hPa is indicated by the colour scale. (Figure to be printed in color.)</figcaption></figure>

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<figure><img src="image_10.png" /><figcaption>Figure 8. The 72-hour HYSPLIT back trajectories for 28 November 2015 at 08h00, 29 November 2015 at 10h00 and 30 November 2015 at 02h00. The starting height was 100 m and the vertical motion method set to 0 for the calculations. The bottom of the figure indicates the height of the air masses above ground level.</figcaption></figure>

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314 **4. Results and discussions**

315 **4.1. Wind speed dependence of aerosol concentrations**
The relationship between wind speed and aerosol concentration was investigated using regression analysis. It is well-recognized that the concentrations of aerosols in the marine atmosphere vary with wind speed. Monahan et al. (1983) determined a power law relation between wind speed and whitecap coverage, which was associated with sea spray concentrations. A linear function is obtained by applying a logarithmic function to the power law equation (Grythe, et al., 2014; Nilsson, et al., 2021; Wu, 1990):

$$ \text{Log } C = \alpha U + \beta \quad (2) $$

where C is the particle concentration, U is the wind speed, and α (slope) and β (intercept) are constants. Although the sea spray production mechanism is complicated, a logarithmic relation has been shown to be a good approximation for the wind-generated wave fields.

The instantaneous wind speed $U_i$ and aerosol number concentration $C(D)_i$ of individual data files were cross-correlated in linear-logarithmic space. The $C(D)_i$ were recalculated for two diameters, i.e., D=0.5 and D=5.0 µm. The latter diameter was chosen because sea spray reveals its presence as a hump in the number concentration used in the particle size distribution around 3 – 5 µm (Van Eijk and De Leeuw, 1992). This hump is indicative of the presence of sea spray because few other types of aerosols come in these sizes (with the notable exception of sand). Sea spray production is not limited to these size ranges, and large numbers of submicron sea spray particles are also being produced (Andreas et al., 1995). The submicron domain is also where many of the continental aerosols are found, and therefore we selected D=0.5 µm as our best chance of detecting these continental aerosols. It should be noted, however, that the total number concentration at D=0.5 µm can be a mixture of sea spray and continental particles. As our aerosol probes only register size, we cannot distinguish specific aerosol types.

The two sets of datapoints were subjected to a linear regression against wind speed. The slopes α (in Eq. 2) for both case studies are positive (Table 1), indicating an increase in aerosol concentration with an increase in wind speed. This is consistent with the fact that the aerosols sampled are probably sea spray aerosols issued from the wind-wave interaction processes. For the pure marine case, the slope values for both size fractions are higher than that of the mixed air case, which confirms the abundance of sea spray aerosols in the pure marine air mass. As evidenced by the standard deviations in Table 1, the slope of the 0.5 µm particles for the mixed air case is significantly lower than that of the 0.5 µm
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particles in the pure marine case, as well as the two slopes for the 5.0 µm particles. This lower slope is an indication that the sea spray production is not the dominant process. It might be that a counteracting effect of sea spray and continental particles is at play: on the one hand the production of sea spray tends towards a positive slope, and on the other hand the removal of continental particles due to dispersion and gravitational fall tends towards a negative slope. The net result of a relatively small positive slope suggests that the fraction of continental particles is higher in the mixed air case than in the pure marine case.

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Theoretically, the intercept $\beta$ (in Eq. 2) values give the concentration when the wind speed is zero (Piazzola and Kaloshin, 2005). Tentatively, we equate the intercept to a background concentration to which the wind speed effect is added. Within this assumption, we note that the background concentration for the 0.5 µm particles (representative of continental aerosols) in both cases are higher than that of the 5.0 µm particles (intercepts in table 1 are given as log-units). This agrees with the observation of a modest influx of continental aerosols prior to the pure marine case and the brief interaction of the air mass with the continent during the mixed case. The lower intercept values for the 5.0 µm particles are consistent with the initial conditions of both cases, where the pure marine case had little, or no sea spray aerosols and the mixed case had a mixture of sea spray aerosols and continental aerosols.

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<table><caption>Table 1. Slope and intercept values for the aerosol concentration and wind speed regression for the pure marine and mixed air mass cases in False Bay (this study), Porquerolles Island in the Mediterranean Sea and for Oahu in Hawaii. \#points indicates the number of 15-minute files included in the calculations of the regression values.</caption><thead><tr><th>Cases</th><th colspan="2">Pure marine air<br>(this study)</th><th colspan="2">Mixed air<br>(this study)</th><th colspan="2">Porquerolles<br>(Mediterranean)</th><th colspan="2">Oahu, Hawaii</th></tr><tr><th>Aerosol<br>Size</th><th>0.5µm</th><th>5µm</th><th>0.5µm</th><th>5µm</th><th>0.5µm</th><th>5µm</th><th>0.5µm</th><th>5µm</th></tr></thead><tbody><tr><th>Slope</th><td>0.056<br>±0.004</td><td>0.058<br>±0.004</td><td>0.019<br>±0.008</td><td>0.041<br>±0.006</td><td>0.039<br>±0.005</td><td>0.033<br>±0.005</td><td>0.062<br>±0.002</td><td>0.079<br>±0.002</td></tr><tr><th>Intercept</th><td>1.23<br>±0.06</td><td>-1.61<br>±0.06</td><td>1.64<br>±0.1</td><td>-1.40<br>±0.09</td><td>1.72<br>±0.07</td><td>-1.39<br>±0.07</td><td>1.27<br>±0.01</td><td>-1.33<br>±0.01</td></tr><tr><th>#points</th><td>216</td><td>216</td><td>102</td><td>102</td><td>108</td><td>108</td><td>5522</td><td>5522</td></tr></tbody></table>

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Furthermore, it should be noted that the intercept values for the mixed case for both size fractions are higher than that of the pure marine case. The higher intercept value for the 0.5 µm particles in the mixed air mass case confirms the larger contribution of continental
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(natural and/or anthropogenic) aerosols in this air mass. The higher value for the 5.0 µm particles is attributed to the possible build-up of sea spray aerosols during the strong SE-flow in the timeframe preceding the mixed air mass case (cf. Figure 6 in section 3.3). The lower intercept values for the pure marine case are confirmed by the observation in section 3.2 and Figure 3 that the pure marine case builds on a minimal background of predominantly continental aerosols.

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Table 1 also includes slope and intercept values for two other sites: a coastal site on the Island of Porquerolles in the Mediterranean Sea, France (Piazzola and Despiau, 1997) and a more remote and oceanic site at the eastern coast of Oahu, Hawaii (Reid et al., 2006). For the oceanic site of Oahu, the aerosol measurements were obtained during the Rough Evaporation Duct (RED) experiment (Anderson et al., 2004). The RED experiment was performed onboard the R/V Flip (Floating Instrument Platform), moored at 15 km East off the Northern tip of Oahu. Aerosol sampling was performed on a horizontal outrigger of the R/V Flip, at a height of 20 meters above the water, to ensure an unobstructed sampling of the air mass. The aerosol samplers were the same as used in False Bay, and data processing was identical to the procedure described in section 2.2, including normalization of the concentrations to a relative humidity of 80%. The RED experiment lasted for 20 days, with mostly unlimited fetch conditions. This implies that a very large number of aerosol size distributions were obtained in oceanic conditions, as shown in Table 1. The difference in observation height between Oahu and False Bay (20 versus 3 meters) was not corrected for. This does not impact on the slope of the wind speed versus concentration regression lines but has probably led to an underestimate of the intercept of the Oahu regression lines as compared to False Bay.

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The slope and intercept values for the submicron particles (0.5 µm) of the pure marine case in False Bay correspond well with that of Oahu. Oahu is considered as a pure marine data set and the good correspondence thereby confirms the oceanic influence from the deep south in the bay. For the 5 µm particles the production (slope) and background (intercept) values are lower in False Bay than that of Oahu (open ocean). The lower slope value might be due to some coastal influence in the bay and the lower intercept in False Bay is again due to the low sea spray background observed in Section 3.2. The higher values in Oahu are indicative of the dominance of the sea spray production in both size fractions as well as the purity and effectiveness of measuring the sea spray aerosols in the open ocean.

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The Mediterranean dataset used for the comparison in the present paper results from measurements of aerosol particle size distributions at the extreme west point of the island of Porquerolles, which is located on the French Riviera, between 6.15 and 6.25 degrees east longitude and at 43 degrees north latitude. The island of Porquerolles in the Mediterranean Sea is regarded as a coastal site with some continental influence. The same aerosol probes as used in False Bay were deployed at a height of 25 m above sea level and the data processing was the same as that for the False Bay data. Again, the difference in height (25 vs. 3 m) was not corrected for, but the data selection was for maritime conditions. Good correspondence was found for the slope and intercept values of the 5 µm aerosols for the mixed air mass conditions of False Bay compared to the Mediterranean site. This is likely due to the mixing of continental and marine aerosols that is characteristic of coastal sites. For the pure marine case of False Bay, the slope values of both representative sizes (0.5 and 5.0 µm) are higher than that for the Mediterranean, which confirms the dominance of the sea spray generation process in both size fractions during pure marine conditions. However, the pure marine case has lower intercept values than Porquerolles. This serves as evidence that the pure marine case has a lower background count of both continental and sea spray aerosols. The much higher background count (intercept value) of the 0.5 µm particles for Porquerolles is an indication of the strong presence of continental aerosols in the air mass.

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Table 1 shows that the 5 µm (representative of sea spray aerosols) slope values increase from Porquerolles to the False Bay cases and are the highest at the oceanic site of Oahu. The numerical values support our conclusions for False Bay, i.e., that a mixed marine / continental air mass was sampled during case 2 and an almost pure marine air mass was sampled during case 1.

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## 4.2. Aerosol size distributions

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To further characterize the behaviour of the aerosols in False Bay, the aerosol size distributions (calculated according to section 2.2) for the pure marine (case study 1) and mixed (case study 2) air mass conditions were analysed. The distributions of the two cases were then compared to each other as well as to that of a coastal site in the northern hemisphere.

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### 4.2.1. Pure marine distributions
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Figure 9 shows three representative size distributions (PSD<sub>r</sub>) for the pure marine air mass conditions, acquired during the blue, red and green circled timeframes in Figure 3. The blue PSD<sub>r</sub> (solid line) corresponds to the 10 hour timeframe with an average wind speed of 14 ms<sup>-1</sup> (blue circle in Figure 3) and the red PSD<sub>r</sub> (dashed line) to a 9 hour timeframe with an average wind speed of 18 ms<sup>-1</sup>. A clear increase in the aerosol concentration (typical standard deviation is ~0.5 log units) with an increase in the average wind speed to 18 ms<sup>-1</sup> is found for all aerosol sizes, consistent with sea spray production by wind-wave interaction.

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Previous studies (De Leeuw et al., 2011; Gantt et al., 2011; Piazzola et al., 2003; Van Eijk and De Leeuw, 1992) have also noted this increase in sea spray concentration, but primarily in the coarse size fraction (>1 um). It is generally accepted that at smaller sizes the increase is obscured by the presence of a significant fraction of non-sea-spray aerosols, which react differently to wind speed. Our observation of an increase in the concentration of submicron particles is therefore an indication of the purity of the marine air mass from the south. As submicron particles have residence times on the order of days (Gong et al., 1997), they could have been advected from the deep south and transported to the measurement site in False Bay.

<figure><img src="image_11.png" /><figcaption>Figure 9. Particle size distributions for average wind speeds of 14, 18 and 14 ms⁻¹ from circled areas in Figure 3 for Case study 1 (20 – 23 July 2015). Mean aerosol size distributions measured for an average</figcaption></figure>

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wind speed of 14 ms⁻¹ calculated over 10 hours in the beginning of case study (blue line), an average wind speed of 18 ms⁻¹ calculated over 9 hours (red dashed line) and an average decreasing wind speed of 14 ms⁻¹ (3 hours; green dotted line). (Figure to be printed in color.)

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Closer inspection of Figure 9 (ignoring the extremes of the size range at 0.21 and 45 µm due to instrumental effects at the endpoints (Garvey et al., 1983) shows a larger increase in aerosol concentration with wind speed for the 1 – 5 µm size range. This corresponds to the higher slope values in Table 1 for the 5 µm particles. The long (almost unlimited) fetch contributes to this larger increase which confirms the dominance of the sea spray generation process and the purity of the marine air mass reaching the measurement site.

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Figure 9 further shows the green $PSD_r$ (dotted line) for the decrease in wind speed to 14 ms⁻¹ corresponding to a 3-hour timeframe (green circle in Figure 3). The decrease in aerosol concentration with a decrease in wind speed is more pronounced for the smaller (< 3 µm) particles than for the larger particles (> 3 µm). This is contrary to Monahan's (1983) observation that the decrease in concentration of the larger particles is more pronounced due to gravitational settling after a period of high production.

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The concentration after the decrease in wind speed (green line Figure 9) is still higher than the concentration prior to the production period at the same average wind speed of 14 ms⁻¹ (blue line Figure 9). We therefore hypothesize that an accumulation process takes place in False Bay because the air mass cannot freely exit the Bay due to the Table Mountain complex. Furthermore, the production process remains active at 14 ms⁻¹ and sea spray aerosols are still injected into the air mass inside the Bay. The production and accumulation thus counterbalance the expected rapid fall-out of the aerosols that typically happens following a decrease in wind speed.

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The above reasoning does not explain the concentration decrease of the smaller (< 3 µm) particles (Figure 9). These particles are less affected by gravitational fall and their concentration could thus be enhanced by local production. However, WRF-simulations revealed that the marine boundary layer height increased during the decrease in wind speed, thereby facilitating the vertical dispersion of the aerosols and effectively diluting the aerosol at the surface (i.e., the measurement site). Since
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the smaller particles are more easily dispersed, this may have caused the
concentration decrease observed in Figure 9.

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In addition to the above-mentioned explanations, the wind-wave interaction may
continue after the wind itself has calmed down and still contribute to the sea spray
aerosol generation. Yang et al. (2019) noted that the aerosol flux is twice as high
during periods of decreasing wind speed than during periods of increasing wind
speed. This can have an influence on the measured atmospheric concentrations of
sea spray but has not been quantified in this study. Also, according to recent studies
(Feng et al., 2017 and Schiffer et al., 2018) surface ocean biology contributes
significantly to the submicron concentration during sea spray aerosol generation.
With the current analysis the precise effect of ocean biology with wind speed
increase and decrease could not be determined.

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To summarize, pure marine air mass conditions with an unlimited fetch from the
deep south existed for the period of 20 – 23 July 2015. The sustained SE wind
direction in the 120 – 155° wind sector limited continental influence. An increase in
wind speed led to an increase in aerosol concentration, which attests to the sea
spray generation process. Production was observed over the full size range of 0.2 –
42 µm of our probes, demonstrating that sea spray production also takes place at
submicron sizes. With the decrease in wind speed an accumulation effect of the sea
spray aerosols was observed.

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4.2.2. Mixed marine/continental distributions

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Figure 10 shows representative size distributions (PSD<sub>r</sub>) at the start of case study 2 (solid blue line, blue circle in Figure 6), at the wind speed maximum (dashed red line, red circle in Figure 6) and during the wind speed decrease (green dotted line, green circle in Figure 6). Again, a significant increase in aerosol concentration with an increase in wind speed was observed for the whole size range. This suggests that sea spray is the dominant aerosol in the air mass, for all sizes. The (small) fraction of (mostly submicron) continental aerosols that may have been picked up during the transit over the southern tip of the continent (Figure 8) does not manifest its presence by causing a negative correlation with wind speed (cf. section 4.1).
<figure><img src="image_12.png" /><figcaption>Figure 10. Particle size distributions for average wind speeds of 12, 17 and 13 ms⁻¹ from circled areas in Figure 6 for Case study 2 (28 – 30 November 2015). Mean aerosol size distributions measured for an average wind speed of 12 ms⁻¹ calculated over 6 hours in the beginning of case study (blue line), an average wind speed of 17 ms⁻¹ calculated over 7 hours (red dashed line) and an average decreasing wind speed of 13 ms⁻¹ (3 hours; green dotted line). (Figure to be printed in color.)</figcaption></figure>

For an increase in wind speed from 12 to 17 ms⁻¹, there is a greater increase in the aerosol concentration for the larger particles (>1 µm) than for the submicron aerosols (Figure 10). This corroborates the higher slope value observed for the 5 µm particles compared to that of the 0.5 µm particles (Table 1). The greater increase in supermicron aerosol concentrations can be due to the variability of the higher wind speeds, which have a more pronounced effect on larger particles (Veron et al., 2012). Variable high wind speeds lead to more wave breaking and tearing of the wave crests, which contributes to more jet and spume droplets being released and hence a larger increase in the bigger size fraction.

The submicron size range may consist of aged sea spray aerosols (sea spray that has been in the atmosphere for hours to days and has adjusted to the ambient humidity), continental aerosols, and fresh sea spray aerosols. With the air mass flowing over the 30 km stretch of water from entering False Bay to the measurement site, a fraction of continental and aged sea spray aerosols will be
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removed, and fresh sea spray aerosols will be added to the air mass. This latter
process will be important to the aerosol mixture reaching the measurement site
because the numerical mesoscale weather system (Figure 7) shows higher wind
speeds than over the open ocean due to an acceleration of the wind occurring in the
bay. In net, the local production at the high wind speed of 17 m.s⁻¹ appears to be
more effective than the removal processes, and thus, an increase in the submicron
aerosol concentrations is observed. However, it is not as large as that of the
supermicron particles. This is consistent with the low, but still positive slope value
for the 0.5 µm particles (Table 1). The presence of different particle sources,
characteristics of coastal zone, induces a lower slope of the wind speed-
concentrations regression due to a higher background. Above the oceans, the sea is
the only source of submicron aerosols and the atmospheric concentrations react
almost immediately to the production processes.

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Figure 10 further shows the green PSD<sub>r</sub> (dotted line) for the decrease in wind speed to 13 ms<sup>-1</sup> corresponding to a 4-hour timeframe (green circle in Figure 6). Here, the decrease in wind speed leads to a decrease in concentration over all the aerosol sizes, but the concentration of all the particles is higher than the concentration values at the beginning of the case study at 12 ms<sup>-1</sup>. This supports our hypothesis regarding the accumulation process in False Bay in that we do not observe a rapid gravitational fall-out of sea spray concentrations after high production.

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To summarize, for the mixed air mass conditions of case study 2 (28 – 30 November 2015), the particle size distributions show an increase in aerosol concentration with an increase in wind speed for the whole size range of 0.2 – 42 µm. This demonstrates that the fraction of locally produced sea spray aerosols is larger than the continental fraction, even for submicron particles. This is attributed to the relatively high wind speed in the bay and the observation that the air mass spent minimal time over the continent.

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4.2.3. Inter-comparison of False Bay and Mediterranean aerosol size distributions

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An inter-comparison of the two cases in False Bay was done to improve the
understanding of the changes in sea spray aerosol concentrations with wind speed.
Figure 11 depicts the particle size distribution (PSD<sub>r</sub>) graphs in False Bay for the pure
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marine (solid blue line) and mixed air masses (dashed red line) at the average wind speeds of 18 ms⁻¹ and 17 ms⁻¹, respectively. The same tendency as in Figure 11 was observed for the PSDᵣ's at the initial wind speeds of ~12 ms⁻¹ for the respective cases (data not shown).

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Figure 11 indicates that the pure marine air mass case has a higher concentration of aerosols in the 0.4 – 6 µm size range than the mixed air mass case. First, this can be attributed to the unlimited fetch during the pure marine case where the production zone of sea spray aerosols is increased compared to that of the mixed case. Furthermore, the residence times of submicron aerosols can be several days in the absence of precipitation (Gong et al., 1997), thus a fair amount of pure marine aerosols that were generated over the open ocean could still be transported with the air mass that travelled from the deep south to the measurement site without the possible contamination of continental aerosols as might have been the case with the mixed air mass conditions.

<figure><img src="image_13.png" /><figcaption>Figure 11. Comparison of aerosol size distributions in Simon's Town, False Bay for pure marine air masses (solid blue line), mixed air masses (dashed red line) and Porquerolles island in Mediterranean Sea (green dash-dotted line). (Figure to be printed in color.)</figcaption></figure>

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Below 0.4 µm, the concentrations of the two cases are quite similar. This is in contrast to the initial hypothesis of using the 0.5 µm particles as tracer for the
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continental contribution, where we expected a higher continental contribution in case 2 than case 1. Furthermore, with the expectation that ocean biology is more active in summer than in winter, the influence on the submicron concentration should be more pronounced in case 2 (summer) than in case 1 (winter). However, the submicron concentrations in Figure 11 show similar values for both cases at high wind speeds. It can thus be inferred that the ocean biology effect on the submicron size range is not pronounced. The similarity in concentrations for the submicron size range is attributed to the local sea spray aerosol production.

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Above 7 µm the aerosol concentration of the pure marine case is lower than that of the mixed air mass case. According to Table 1 in section 4.1 the background concentration for the pure marine case was much lower than that of the mixed case for the larger particles (represented by 5 µm). Hence, a lower concentration even after an increase in wind speed is still observed for the pure marine case. Furthermore, the interruption of the fetch during the mixed air mass case led to less developed wave fields at a shorter fetch, i.e. ~30 km from the entrance of the bay to the experimental station. According to Piazzola et al. (2009), less developed wave fields lead to steeper waves with an increase in breaking and hence more production of bigger (jet and spume) sea spray aerosols (Andreas et al., 1995; Anguelova et al., 1999). Also, the mixed case experienced high SE wind speeds prior to the start of the case study that could have led to a build-up of larger particles and resulted in the slightly higher concentrations observed for the larger particles.

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Figure 11 also shows a comparison between averaged aerosol size distributions measured in Simon's Town, False Bay and Porquerolles island in Mediterranean Sea. The Mediterranean $PSD_r$ is indicated by the green dash-dotted line at the average wind speed of 16 m.s⁻¹ (Figure 11). The island of Porquerolles is in close proximity to the mainland and represents a coastal site with mixed air conditions. For comparability with the False Bay study site, data was selected for conditions of marine origin (Piazzola et al., 2003) with large fetches (~100 km). Despite the restriction of the data selection, higher submicron aerosol concentration in the Mediterranean than for both cases in False Bay might be due to the stronger influence of the continental aerosols in Porquerolles. According to Table 1, the background (intercept) value was highest for the submicron (0.5 µm) size fraction of Porquerolles, which is consistent with the observed higher submicron aerosol concentration.
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Between the 1 and 10 µm size range the Mediterranean aerosol concentration corresponds well to the mixed air mass case of False Bay. Even though large fetch conditions were considered for Porquerolles, the island's close proximity (~5 km) from the mainland could still lead to the presence of continental aerosols. The mixture of sea spray and continental aerosols was confirmed with observations on board the R/V Atalante (Laussac et al., 2018) off the Mediterranean coast, and hence the good correspondence with the mixed air mass case of False Bay.

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The higher aerosol concentration for the pure marine air mass case in the 1 – 6 µm size range is still evident in the comparison with the Mediterranean PSD<sub>r</sub> (Figure 11).

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A higher slope value for the representative size of 5 µm was found for pure marine case in Table 1. This corresponds to higher production and hence the higher sea spray aerosol concentration observed in Figure 11.

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In summary, the inter-comparison between the two cases of False Bay and that of the Mediterranean show similar aerosol concentrations between the mixed air mass case and that of Porquerolles. This agrees with the mixture of continental and sea spray aerosols that are generally observed at coastal sites. The pure marine air mass case shows a higher increase in aerosol concentration with wind speed in the 1 – 6 µm size range than that of both the mixed air mass case and the Mediterranean.

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This higher aerosol concentration is attributed to the influence of the Southern Ocean with an unlimited fetch.

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## 5. Conclusion

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This paper presents a first survey of the aerosol size distributions measured in the extreme south of the African continent, at the coastal site of Simon's Town in False Bay. Aerosol concentrations were sampled in pure marine air masses coming from the Antarctic and mixed air masses, which also originated from Antarctica, but had partially travelled above continental areas. Our results confirm that long-range transport of aerosols from the open Southern Ocean influence the coastal atmosphere of southern Africa. The nature of the air masses transported from the south above the sea along thousands of kilometres induce a strong marine character in the sampled aerosols. We observe an increase in the aerosol concentrations with wind speed over all sizes for both the pure marine and the mixed air conditions. This shows that sea spray generation leads to aerosols across the measured size range (0.2 – to 42 µm).
The results of the wind speed and aerosol concentration relationship confirm the oceanic influence in False Bay with the good correspondence in regression values of the pure marine case to the open ocean site in Oahu (Hawaii). The slightly lower regression values for the pure marine case is attributed to False Bay not being completely exposed to the open ocean. Good correspondence was also found between the regression values of the mixed air mass case and that of the island of Porquerolles in the Mediterranean Sea. This attested to the mixture of sea spray and continental aerosols during the mixed air mass case which is typical of coastal sites.

Comparing the aerosol size distributions for the pure marine and mixed air mass cases of False Bay to that of the Mediterranean, a higher aerosol concentration in the 1 – 6 µm size range was observed for the pure marine case. The higher aerosol concentration is attributed to a stronger sea spray presence that was brought about by the pristine air mass from Antarctica with the unlimited fetch conditions. This might be an indication of the prominence of the sea spray aerosols in the Southern Ocean. To investigate this possibility, further comparisons to other sites around the globe are underway.

We also observed similar aerosol concentrations in the submicron sizes with an increase in wind speed for both the pure marine and the mixed air mass cases. This was attributed to the effect of the local sea spray aerosol production in the bay.

The unique sampling location in False Bay with the unlimited fetch conditions is unusual, and this coastal site experiences pristine open sea conditions. The pristine conditions were measured without using a ship or offshore measuring platform and thereby cutting cost immensely. A recommendation for future work would be to place aerosol probes at the Global Atmosphere Watch station at Cape Point, which is at the tip of the Peninsula in False Bay. This location may increase the possibility of consistently measuring the pristine marine conditions that are transported by the air masses from Antarctica.

## Author contributions:

Faith J. February: Conceptualization, Writing – Original draft preparation, Investigation, Formal analysis, Data curation. Jacques Piazzola: Supervision, Methodology, Writing – Reviewing and Editing. Katye E. Altieri: Supervision, Writing – Reviewing and Editing, Visualization, Funding acquisition. Alexander M.J. Van Eijk: Supervision, Methodology, Resources, Software, Writing – Reviewing and Editing, Validation
682 Funding sources:

683 This research was supported by the South African National Research Foundation through a South
684 African National Antarctic Programme Postgraduate Fellowship to F.J.F. and Grant to K.E.A.
685 (110732); University of Cape Town support to F.J.F. through the Advancing Womxn Ocean Womxn
686 Fellowship programme and to K.E.A. through a Vice Chancellor Future Leaders 2030 Grant.
687 Participation by the Institute for Maritime Technology (IMT) in FESTER was funded by the South
688 African Navy. The work of Fraunhofer-IOSB was supported and funded by the Bundeswehr Technical
689 Center for Weapons and Ammunition, WTD 91 in Meppen. Participation by TNO in FESTER was
690 funded by the Royal Netherlands Navy. The sponsors had no involvement in the study design; in the
691 collection, analysis, and interpretation of the data; in the writing of the report; and in the decision to
692 submit the article for publication.

693 Acknowledgements:

694 The authors acknowledge their colleagues of the FESTER experiment for the help in data acquisition
695 and maintenance. TNO in the Netherlands is the owner of the aerosol data and the authors are
696 thankful for the availability of the data. The authors wish to thank Carmen Ullwer from Fraunhofer -
697 IOSB, Germany, for providing the images of the WRF fields and Dennis Vister from the Institute for
698 Maritime Technology, South Africa for the photo of False Bay taken from the Old Signal School. The
699 authors gratefully acknowledge the NOAA (National Oceanic and Atmospheric Administration) Air
700 Resources Laboratory (ARL) for the provision of the HYSPLIT model from the READY website
701 (https://www ready.noaa.gov)
702 References:

703 Alonso-Blanco, E., Gómez-Moreno, F.J., Artíñano, B., Iglesias-Samitier, S., Juncal-Bello, V., Piñeiro-Iglesias, M., López-Mahía, P., Pérez, N., Brines, M., Alastuey, A., García, M.I., Rodríguez, S., Sorribas, M., Del Águila, A., Titos, G., Lyamani, H., Alados-Arboledas, L., 2018. Temporal and spatial variability of atmospheric particle number size distributions across Spain. Atmospheric Environment 190, 146-160, doi:10.1016/j.atmosenv.2018.06.046.

708 Anderson, K., Brooks, B., Caffrey, P., Clarke, A., Cohen, L., Crahan, K., Davidson, K., De Jong, A., De Leeuw, G., Dion, D., Doss-Hammel, S., Frederickson, P., Friehe, C., Hristov, T., Khelif, D., Moerman, M., Reid, J.S., Reising, S., Smith, M., Terrill, E., and Tsintikidis, D., 2004. The RED Experiment. AMERICAN METEOROLOGICAL SOCIETY 85, 1355-1365, doi:10.175/BAMS-85-9-1355.

713 Andreas, E. L., Edson, J.B., Monahan, E.C., Rouault, M.P., Smith, S.D., 1995. The spray contribution to net evaporation from the sea: A review of recent progress. Boundary Layer Meteorology 72, 3-52.

716 Anguelova, M., Barber Jr., R.P., and Wu, J., 1999. Spume Drops Produced by the Wind Tearing of Wave Crests. JOURNAL OF PHYSICAL OCEANOGRAPHY 29.

718 Bohlmann, S., Baars, H., Radenz, M., Engelmann, R., and Macke, A., 2018. Ship-borne aerosol profiling with lidar over the Atlantic Ocean: from pure marine conditions to complex dust-smoke mixtures. Atmospheric Chemistry and Physics 18, 9661-9679, doi:10.5194/acp-18-9661-2018.

722 Brunke, E. G., Labuschagne, C., Parker, B., Scheel, H.E., Whittlestone, S., 2004. Baseline air mass selection at Cape Point, South Africa: application of 222Rn and other filter criteria to CO2. Atmospheric Environment 38 5693-5702, doi:10.1016/j.atmosenv.2004.04.024.

725 De Leeuw, G., Andreas, E.L., Anguelova, M.D., Fairall, C.W., Lewis, E.R., O' Dowd, C., Schulz, M., and Schwartz, S.E., 2011. PRODUCTION FLUX OF SEA SPRAY AEROSOL. Reviews of Geophysics 49, 1-39, doi:10.1029/2010RG000349.

728 Draxler, R. R., and Rolph, G.D., 2017. HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory).

730 Eisele, C., Seiffer, D., Stein, K., Sucher, E., Gunter, W.H., February, F.J., Vrahimis, G., Wainman, C., Maritz, B., Koago, M.S., Van Eijk, A.M.J., Van Iersel, M., Cohen, L.H., Van Binsbergen, S.A., Heemskerk, H.J.M., Sternberg, A., Schulte, H., Van Rheenen, A.D., Brenthagen, E., Thomassen, J.B., and Griffith, D., 2016. FESTER: a propagation experiment, overview and first results. SPIE, Vol. 10002, Edinburgh.

735 Feng, L., Shen, H., Zhu, Y., Gao, H., and Yao, X., 2017. Insight into Generation and Evolution of Sea-Salt Aerosols from Field Measurements in Diversified Marine and Coastal Atmospheres. Scientific Reports, doi:10.1038/srep41260.

738 Fitzgerald, J. W., 1975. Approximation formulas for the equilibrium size of an aerosol particle as a function of its dry size and composition and the ambient relative humidity. Journal of Applied Meteorology 14, 1044-1049.

741 Freeman, B., Gharabaghi, B., Thé, J., Munshed, M., Faisal, S., Abdullah, M., and Al Aseed, A., 2017. Mapping air quality zones for coastal urban centers. Journal of the Air and Waste Management Association 67, 565-581, doi:10.1080/10962247.2016.1265025.

744 Gantt, B., Meskhidze, N., Facchini, M.C., Rinaldi, M., Ceburnis, D., and O'Dowd, C.D., 2011. Wind speed dependent size-resolved parameterization for the organic mass fraction of sea spray aerosol. Atmospheric Chemistry and Physics 11, 8777-8790.

747 Garvey, D. M., and Pinnick, R. G., 1983. Response Characteristics of the Particle Measuring Systems Active Scattering Aerosol Spectrometer Probe (ASASP-X). Aerosol Science and Technology 2, 477-488, doi:10.1080/02786828308958651.
750 Gaston, C. J., Cahill, J.F., Collins, D.B., Suski, K.J., Ge, J.Y., Barkley, A.E., and Prather, K.A., 2018. The
751 Cloud Nucleating Properties and Mixing State of Marine Aerosols Sampled along the
752 Southern California Coast. Atmosphere 9, 1-16.

753 Gong, S. L., Barrie, L.A., and Blanchet, J.-P., 1997. Modeling sea-salt aerosols in the atmosphere 1.
754 Model development. Geophysical Research 102, 3805-3818.

755 Grythe, H., Ström, J., Krejci, R., Quinn, P., and Stohl, A., 2014. A review of sea-spray aerosol source
756 functions using a large global set of sea salt aerosol concentration measurements.
757 Atmospheric Chemistry and Physics 14, 1277-1297.

758 Hoppel, W. A., Fitzgerald, J. W., Frick, G. M., Larson, R. E. and Mack, E. J., 1990. Aerosol Size
759 Distributions and Optical Properties Found in the Marine Boundary Layer Over the Atlantic
760 Ocean. JOURNAL OF GEOPHYSICAL RESEARCH 95, 3659-3686.

761 IPCC, 2014: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to
762 the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core
763 Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151 pp.

764 Kleefeld, S., Hoffer, A., Krivacsy, Z., and Jennings, S. G., 2002. Importance of organic and black carbon
765 in atmospheric aerosols at Mace Head, on the West Coast of Ireland. Atmos. Environ. 36,
766 4479-4490.

767 Krishna Moorthy, K., Satheesh, S.K., and Krishna Murthy, B.V., 1997. Investigations of marine
768 aerosols over the tropical Indian Ocean. JOURNAL OF GEOPHYSICAL RESEARCH 102, 18,827-
769 18,842.

770 Laussac, S., Piazzola, J., Tedeschi, G., Yohia, C., Canepa, E., Rizza, U., and Van Eijk, A.M.J., 2018.
771 Development of a fetch dependent sea-spray source function using aerosol concentration
772 measurements in the North-Western Mediterranean. Atmospheric Environment 193, 177-
773 189, doi:https://doi.org/10.1016/j.atmosenv.2018.09.009.

774 Monahan, E. C., Fairall, C.W., Davidson, K.L., and Jones Boyle, P., 1983. Observed inter-relations
775 between 10 m winds, ocean whitecaps and marine aerosols. Quart. J. R. Meteorological
776 Society 109, 379-392.

777 Myhre, G., Shindell, D., Bréon, F., Collins, W., Fuglestvedt, J., Huang, J., Koch, D., Lamarque, J., Lee,
778 D., Mendoza, B., Nakajima, T., Robock, A., Stephens, G., Takemura, T. and Zhang, H., 2013.
779 Anthropogenic and Natural Radiative Forcing. In: Daniel Jacob, A. R. R., Keith Shine, (Ed.),
780 Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the
781 Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge
782 University Press, Cambridge, United Kingdom and New York, NY, USA.

783 Nilsson, E. D., Hultin, K.A.H., Mårtensson, E.M., Markuszewski, P., Rosman, K., and Krejci, R., 2021.
784 Baltic Sea Spray Emissions: In Situ Eddy Covariance Fluxes vs. Simulated Tank Sea Spray.
785 Atmosphere 12, 1-33, doi:10.3390/atmos12020274.

786 O'Dowd, C. D., Smith, M.H., Consterdine, I.E., and Lowe, J.A., 1997. Marine aerosol, sea-salt, and the
787 marine sulphur cycle: A short review. Atmospheric Environment 31, 73-80.

788 O'Dowd, C. D., Facchini, M.C., Cavalli, F., Ceburnis, D., Mircea, M., Decesari, S., Fuzzi, S., Yoon, Y.J.,
789 and Putaud, J-P., 2004. Biogenically driven organic contribution to marine aerosol. Letters to
790 Nature 431, 676-680.

791 Paton-Walsh, C., Guérette, E-A., Kubistin, D., Humphries, R., Wilson, S., Buchholz, R., Jones, N.B.,
792 Griffith, D.W.T., Dominick, D., Galbally, I., Keywood, M., Lawson, S., Harnwell, J., Ward, J.,
793 Griffiths, A., and Chambers, S., 2018. Urban Air Quality in a Coastal City: Wollongong during
794 the MUMBA Campaign. Atmosphere 9, 1-22, doi:10.3390/atmos9120500.

795 Penner, J. E., 2019. Soot, sulphate, dust and the Climate - three ways through the fog. Nature 570,
796 158-159, doi:10.1038/d41586-019-01791-6.

797 Pfaff, M. C., Logston, R.C., Raemaekers, S.J.P.N., Hermes, J.C., Blamey, L.K., Cawthra, H.C.,
798 Colenbrander, D.R., Crawford, R.J.M., Day, E., Du Plessis, N., Elwen, S.H., Fawcett, S.E., Jury,
799 M.R., Karenyi, N., Kerwath, S.E., Kock, A.A., Krug, M., Lamberth, S.J., Omardien, A., Pitcher,
800 G.C., Rautenbach, C., Robinson, T.B., Rouault, M., Ryan, P.G., Shillington, F.A., Sowman, M.,
801

Sparks, C.C., Turpie, J.K., Van Niekerk, L., Waldron, H.N., Yeld, E.M., and Kirkman, S.P., 2019.

802

A synthesis of three decades of socio-ecological change in False Bay, South Africa: setting the scene for multidisciplinary research and management. Elementa Science of Anthropocene 7, 1-49, doi:https://doi.org/10.1525/elementa.367.

803

804

805

Piazzola, J., and Despiau, S., 1997. Contribution of marine aerosols in the particle size distributions observed in Mediterranean coastal zone. Atmospheric Environment 31, 2991-3009.

806

807

Piazzola, J., and Kaloshin, G., 2005. Performance evaluation of the coastal aerosol extinction code "MEDEX" with data from the Black Sea. Journal of Aerosol Science 36, 341-359.

808

809

Piazzola, J., Bouchara, F., De Leeuw, G., and Van Eijk, A.M.J., 2003. Development of the Mediterranean extinction code (MEDEX). Optical Engineering 42, 912-924

810

811

Piazzola, J., Demoisson, A., and Tedeschi, G., 2013. Transport of aerosols in the Mediterranean coastal zone. Air Pollution XXI 174, doi:10.2495/AIR130111.

812

813

Piazzola, J., Forget, P., Lafon, C., and Despiau, S., 2009. Spatial Variation of Sea-Spray Fluxes over a Mediterranean Coastal Zone Using a Sea-State Model. Boundary Layer Meteorology 132, 167-183.

814

815

816

Piazzola, J., Tedeschi, G., and Blot, R., 2010. Spatial variation of the aerosol concentration and deposition over the Mediterranean coastal zone. Atmospheric Research 97, 214-228, doi:10.1016/j.atmosres.2010.04.003.

817

818

819

Piazzola, J., Van Eijk, A.M.J., and De Leeuw, G., 1998. Aerosol concentration and fetch. SPIE Conference, Vol. 3433, San Diego, California.

820

821

Reid, J. S., Brooks, B., Crahan, K.K., Hegg, D.A., Eck, T.F., O'Neill, N., De Leeuw, G., Reid, E.A., and Anderson, K.D., 2006. Reconciliation of coarse mode sea-salt aerosol particle size measurements and parameterizations at a subtropical ocean receptor site. JOURNAL OF GEOPHYSICAL RESEARCH 111, 1-26, doi:10.1029/2005JD006200.

822

823

824

825

Richter, D. H., and Veron, F., 2016. Ocean spray: An outsized influence on weather and climate. Physics Today 69, 34-39, doi:10.1063/PT.3.3363.

826

827

Rinaldi, M., Facchini, M. C., Decesari, S., Carbone, C., Finessi, E., Mircea, M., Fuzzi, S., Ceburnis, D., Ehn, M., Kulmala, M., De Leeuw, G., and O'Dowd, C.D., 2009. On the representativeness of coastal aerosol studies to open ocean studies: Mace Head - a case study. Atmospheric Chemistry and Physics 9, 9635-9646, doi:9/9635/2009/.

828

829

830

831

Ross, D. B., and Cardone, V., 1974. Observations of Oceanic Whitecaps and Their Relation to Remote Measurements of Surface Wind Speed. JOURNAL OF GEOPHYSICAL RESEARCH 79, 444-452.

832

833

Schiffer, J. M., Mael, L.E., Prather, K.A., Amaro, R.E., and Grassian, V.H., 2018. Sea Spray Aerosol: Where Marine Biology Meets Atmospheric Chemistry. American Chemical Society Central Science 4, 1617-1623, doi:10.1021/acscentsci.8b00674.

834

835

836

Schmale, J., Henning, S., Decesari, S., Henzing, B., Keskinen, H., Sellegri, K., Ovadnevaite, J., Pöhlker, M.L., Brito, J., Bougiatioti, A., Kristensson, A., Kalivitis, N., Stavroulas, I., Carbone, S., Jefferson, A., Park, M., Schlag, P., Iwamoto, Y., Aalto, P., Äijälä, M., Bukowiecki, N., Ehn, M., Frank, G., Fröhlich, R., Frumau, A., Herrmann, E., Herrmann, H., Holzinger, R., Kos, G., Kulmala, M., Mihalopoulos, N., Nenes, A., O'Dowd, C., Petäjä, T., Picard, D., Pöhlker, C., Pöschl, U., Poulain, L., Prévôt, A.S.H., Swietlicki, E., Andreae, M.O., Artaxo, P., Wiedensohler, A., Ogren, J., Matsuki, A., Yum, S.S., Stratmann, F., Baltensperger, U., and Gysel, M., 2018. Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories. Atmospheric Chemistry and Physics 18, 2853-2881.

837

838

839

840

841

842

843

844

845

846

Seinfeld, J. H., Bretherton, C., Carslaw, K.S., Coe, H., DeMott, P.J., Dunlea, E.J., Feingold, G., Ghan, S., Guenther, A.B., Kahn, R., Kraucunas, I., Kreidenweis, S.M., Molina, M.J., Nenes, A., Penner, J.E., Prather, K.A., Ramanathan, V., Ramaswamy, V., Rasch, P.J., Ravishankara, A. R., Rosenfeldt, D., Stephens, G., and Wood, R., 2016. Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system. Proceedings of the National Academy of Sciences 113, 5781-5790, doi:10.1073/pnas.1514043113.

847

848

849

850

851
852

853

Smith, M. H., Park, P.M. and Consterdine, I.E., 1991. North Atlantic aerosol remote concentrations measured at a Hebridean coastal site. Atmospheric Environment 25A, 547-555.

854

855

856

Sorooshian, A., Shingler, T., Harpold, A., Feagles, C. W., Meixner, T., and Brooks, P. D., 2013. Aerosol and precipitation chemistry in the southwestern United States: spatiotemporal trends and interrelationships. Atmospheric Chemistry and Physics 13, 7361-7379.

857

858

859

Stein, A. F., Draxler, R.R., Rolph, G.D., Stunder, B.J.B., Cohen, M.D., and Ngan, F., 2015. NOAA's HYSPLIT atmospheric transport and dispersion modeling system. Bulletin of the American Meteorological Society 96, 2059-2077, doi:http://dx.doi.org/10.1175/BAMS-D-14-00110.1.

860

861

Van Eijk, A. M. J., and De Leeuw, G., 1992. Modeling Aerosol Particle Size Distributions over the North Sea. JOURNAL OF GEOPHYSICAL RESEARCH 97, 14,417-14,429.

862

863

864

865

Van Eijk, A. M. J., Gunter, W.H., February, F.J., Maritz, B., Vrahimis, G., Koago, M.S., Wainman, C., Eisele, C., Seiffer, D., Sucher, E., Stein, K., Van Iersel, M., Cohen, L.H., Van Binsbergen, S.A., Heemskerk, H.J.M., Sternberg, A., Schulte, H., Van Rheenen, A.D., Brenthagen, E., and Griffith, D., 2016. The FESTER field trial. SPIE, Vol. 9979, Edinburgh.

866

867

868

Van Eijk, A. M. J., Piazzola, J., Van Zuijlen, S., Cohen, L., Moerman, M., Missamou, T., Tedeschi, G., and Stein, K., 2016. A world-wide comparison of aerosol data. SPIE Conference, Vol. 10002, Edinburgh.

869

870

Vignati, E., De Leeuw, G., Schulz, M., and Plate, E., 1999. Characterization of aerosols at a coastal site near Vindeby (Denmark). JOURNAL OF GEOPHYSICAL RESEARCH 104, 3277-3287.

871

872

Wu, J., 1990. On Parameterization of Sea Spray. JOURNAL OF GEOPHYSICAL RESEARCH 95, 18,269-18,279.

873

874

875

Yang, M., Norris, S.J., T.G. Bell and I.M. Brooks (2019) Sea spray fluxes from the southwest coast of the United Kingdom - dependence on wind speed and wave height Atmos. Chem. Phys., 19, 15271-15284, 2019 https://doi.org/10.5194/acp-19-15271-2019.