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Description of the simulated sensitivity experiments conducted in NorESM. The simulated climate was identical in all experiments.
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We have developed an inorganic sea spray source function that is based upon state-of-the-art measurements of sea spray aerosol production using a temperature-controlled plunging jet sea spray aerosol chamber. The size-resolved particle production was measured between 0.01 and 10 μm dry diameter. Particle production decreased non-linearly with incre...
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... simulations employ emissions of SO 2 , SO 4 , particulate organic matter, and black carbon from fossil-fuel and bio-fuel combustion and biomass burning, taken from the IPCC AR5 data sets as in Kirkevåg et al. (2013). The description of the runs and the sea spray parameterisation is presented in Table 3. The global sea spray aerosol mass emission predicted by the model using the sea spray source function pre- sented in this study is 1.84 ± 0.92 Pg yr −1 whilst the global sea spray aerosol number emission is (2.1 ± 1.1) × 10 5 particles m −2 s −1 based on the uncertainty in oceanic air entrainment presented by Long et al. (2011). ...
Citations
... Emission fluxes of bacteria and fPBAP (per m −2 s −1 ) were derived using two independent approaches: In the first approach, bacteria emission fluxes were derived by multiplying the EFs derived in this study with mass emissions estimates from existing 345 SSA parameterizations from Mårtensson et al. (2003), Salter et al. (2015) and Zinke et al. (2024c): ...
... The mass fluxes were integrated over a size range of 0.02 < D p < 2.8 µm, which corresponds to the range in which the Mårtensson et al. (2003) parameterization is valid. The parameterizations of Mårtensson et al. (2003) and Salter et al. (2015) were derived for salinities 33 and 35 g kg −1 , respectively. Since the current study was conducted under brackish conditions (S ∼ 6.7 g kg −1 ), a correction factor 6.7 (33 or 35) had to be applied for these two parameterizations. ...
... On the other hand, the parameterization by Zinke et al. (2024c) was derived for the exact conditions of the current study. While the parameterizations by Mårtensson et al. (2003) and Salter et al. (2015) are based on purely inorganic sea salt, the parameterization Zinke et al. (2024c) was derived for SSA containing organics. Unfortunately, the amount of organics in the SSA is unknown. ...
Primary biological aerosol particles (PBAP) can influence climate and affect human health. To investigate the aerosolization of PBAP with sea spray aerosol (SSA), we conducted ship-based campaigns in the central Baltic Sea near Östergarnsholm in May and August 2021. Using a plunging jet sea spray simulation chamber filled with local seawater, we performed controlled chamber experiments to collect filters and measure aerosols. We determined the abundance of bacteria in the chamber air and seawater by staining and fluorescence microscopy, normalizing these values to sodium concentration to calculate enrichment factors. Our results showed that bacteria were enriched in the aerosol by 13 to 488 times compared to the underlying seawater, with no significant enrichment observed in the sea surface microlayer. Bacterial abundances obtained through microscopy were compared with estimates of fluorescent PBAP (fPBAP) using a single-particle fluorescence spectrometer. We estimated bacterial emission fluxes using two independent approaches: (1) applying the enrichment factors derived from this study with mass flux estimates from previous SSA parameterizations, and (2) using a scaling approach from a companion study. Both methods produced bacterial emission flux estimates that were in good agreement and on the same order of magnitude as previous studies, while fPBAP emission flux estimates were significantly lower. Furthermore, 16S rRNA sequencing identified the diversity of bacteria enriched in the nascent SSA compared to the underlying seawater.
... Despite recognizing the significance of incorporating SSA into the aerosol budget of the marine boundary layer, the development of parameterizations for this aerosol source remains highly challenging and a wide array of parameterizations have been proposed, drawing from both laboratory studies (Monahan et al., 1982(Monahan et al., , 1994Mårtensson et al., 2003;Keene et al., 2007;Tyree et al., 2007;Long et al., 2011;Salter et al., 2015) and field studies Geever et al., 2005;Norris et al., 2008Norris et al., , 2012Yang et al., 2019;Nilsson et al., 2021;Zinke et al., 2024), here limiting the list only to such studies where 70 SSA emission fluxes where directly observed using the Eddy Covariance (EC) method. ...
... Mårtensson et al., 2003;Tyree et al., 2007;Fuentes 115 et al., 2010) or the decay time scale of white caps (Monahan et al. (1982;1986). A later approach is the scale the air entrainment in a laboratory tank to the air entrainment over the real ocean (Salter et al., 2015;Deike et al., 2022). Since direct measurements of sea spray fluxes using EC became available starting with , some laboratory based parameterisations have been constrained by in situ EC fluxes (e.g. ...
... It was extended to sub micrometric particles by Mårtensson et al., (2003). For sub micrometric particles, there is a near consensus with a decline in particle production with increasing temperature, especially below15˚C (Mårtensson et al., 2003;Hultin et al., 2011;Salter et al., 2014Salter et al., , 2015Zinke et al., 2022;Sellegri et al, 2023, both with artificial sea water and in situ with local sea water). Super micrometre SSA may have the opposite temperature trend (Bowyer et al., 1990;Jaeglé et al., 2011;Drod et al., 2018). ...
Ship-based measurements of sea spray aerosol (SSA) gradient fluxes in the size range 0.5–47 µm diameter were conducted between 2009–2017 in both the Baltic Sea and the North Atlantic Ocean. Measured total SSA fluxes varied between 8.9⸱103 ± 6.8⸱105 m-2 s-1 for the Baltic Sea, and 1.0⸱104 ± 105 m-2 s-1. for the Atlantic Ocean. The analysis uncovered a significant decrease (by a factor of 2.2 in wind speed range 10.5 m s-1–14.5 m s-1) in SSA fluxes with chlorophyll-a (Chl-a) concentration higher than 3.5 mg m-3 in the Baltic Sea area. We found statistically significant correlations for both regions of interest between SSA fluxes and various environmental factors including wind speed, wind acceleration, wave age, significant wave height, and wave Reynolds number. Using these factors, we developed separate parameterizations and compared them with previous studies. Additionally, in both measurement regions we observed weak correlations between SSA fluxes and air and water temperature, as well as atmospheric stability. Comparing the Baltic Sea and North Atlantic, we noted distinct emission behaviours, with higher emissions in the Baltic Sea at low wave age values compared to the Atlantic Ocean. This study represents the first comparative analysis of SSA flux measurements using the same methodology in these contrasting marine environments.
... Unfortunately, the aerosol fluxes reported in Nilsson et al. (2001) are not size-resolved and cannot be used as-is in atmospheric aerosol models. Therefore, we propose to parameterize sea spray emissions from leads by 95 applying a correction factor (R Nilsson ) to open ocean sea spray source functions, based on commonly used size-resolved sea spray source functions (here Gong (2003) and Salter et al. (2015)). R Nilsson is calculated as the ratio between aerosol fluxes from open ocean and leads derived from Nilsson et al. (2001), which depends on 10 m wind speed (Equation 1 and Figure 1a). ...
... (1) Gong (2003) together with Monahan et al. (1986), from which it is an adaptation, is the most commonly used open ocean sea 100 spray source function in global climate models, such as the ones involved in CMIP6 (Lapere et al., 2023). On the other hand, Salter et al. (2015) departs from the usual whitecap approach, and includes a dependency on SST, which can be an important factor for polar oceans and for leads. Furthermore, the Salter et al. (2015) source function has been tested and validated against measurements at high latitude stations. ...
... On the other hand, Salter et al. (2015) departs from the usual whitecap approach, and includes a dependency on SST, which can be an important factor for polar oceans and for leads. Furthermore, the Salter et al. (2015) source function has been tested and validated against measurements at high latitude stations. We choose aerosol diameters cutoff between 10 nm to 10 µm, typical of what most climate and atmospheric chemistry models use for the representation of sea salt aerosols. ...
Elongated open water areas in sea ice (leads) release sea spray particles to the atmosphere. However, there is limited knowledge on the amount, properties and drivers of sea spray emitted from leads, and no existing parameterization of this process is available for use in models. In this work, we use measurements of aerosol fluxes from Nilsson et al. (2001) to produce an estimate of the location, timing and amount of sea spray emissions from leads at the scale of the Arctic Ocean for one year. Lead fractions are derived using sea ice data sets from numerical models and satellite detection. The proposed parameterization estimates that leads account for 0.3 %–3 % of the annual sea salt aerosol number emissions in the high Arctic. Assuming similar size distribution as emissions from the open ocean, leads account for 30 %–85 % of mass emissions in sea ice regions. The total annual mass of sea salt emitted from leads, 0.1–1.9 Tg yr-1, is comparable to the mass of sea salt aerosol transported above sea ice from the open ocean, according to the MERRA-2 reanalysis. In addition to providing the first estimates of possible upper and lower bounds of sea spray emissions from leads, the conceptual model developed in this work is implemented and tested in the regional atmospheric chemistry model WRF-Chem. Given the estimates obtained in this work, the impact of sea spray from leads on Arctic clouds and radiative budget needs to be further explored.
... The empirical inorganic SSA source function used in NorESM2 was developed using the same sea spray simulation chamber as in the present study and consists of three log-normal modes: 0.095 μm, 0.6 μm, and 1.5 μm. (45). For each mode, the percentages of the mass in the eight size fractions were determined based on the area under the mass-size distribution curve of the estimated SSA emission flux ( fig. ...
Perfluoroalkyl acids (PFAAs) are highly persistent anthropogenic pollutants that have been detected in the global oceans. Our previous laboratory studies demonstrated that PFAAs in seawater are remobilized to the air in sea spray aerosols (SSAs). Here, we conducted field experiments along a north-south transect of the Atlantic Ocean to study the enrichment of PFAAs in SSA. We show that in some cases PFAAs were enriched >100,000 times in the SSA relative to seawater concentrations. On the basis of the results of the field experiments, we estimate that the secondary emission of certain PFAAs from the global oceans via SSA emission is comparable to or greater than estimates for the other known global sources of PFAAs to the atmosphere from manufacturing emissions and precursor degradation.
... To obtain an estimate of the size-resolved emission spectrum for particles with dry diameters between 0.015 and 10 µm, we combined the estimates of SSA particle production fluxes obtained using the EC measurements and the chamber measurements in three different ways: (1) using the traditional continuous whitecap method, (2) using air entrainment measurements, and (3) simply scaling the chamber data to the EC fluxes. In doing so, we observed that the magnitude of the EC-derived emission fluxes compared relatively well to the magnitude of the fluxes obtained using the chamber air entrainment method as well as the previous flux measurements of Nilsson et al. (2021) and the parameterizations of Mårtensson et al. (2003) and Salter et al. (2015). As a result of these measurements, we have derived a wind-speed-dependent and wave-state-dependent SSA parameterization for particles with dry diameters between 0.015 and 10 µm for low-salinity waters such as the Baltic Sea, thus providing a more accurate estimation of SSA production fluxes. ...
... Along with wind speed, sea state, seawater temperature, salinity, and the physicochemical and biological state of the ocean have been shown to influence the production of SSA (e.g. Woodcock, 1953;Monahan et al., 1983;Bowyer et al., 1990;Nilsson et al., 2001;Mårtensson et al., 2003;Sellegri et al., 2006;Russell and Singh, 2006;Tyree et al., 2007;Zábori et al., 2012;Modini et al., 2013;Park et al., 2014;Salter et al., 2014Salter et al., , 2015May et al., 2016;Schwier et al., 2017;Forestieri et al., 2018;Nielsen and Bilde, 2020). ...
... For instance, while SSA production has traditionally been parameterized as a function of wind speed, recent studies have attempted to include the impact of seawater temperature (e.g. Monahan et al., 1986;Gong, 2003;Mårtensson et al., 2003;Clarke et al., 2006;Long et al., 2011;Kirkevåg et al., 2013;Ceburnis et al., 2016;Salter et al., 2015). This is because wind-driven wave breaking alone is insufficient to explain the variability of SSA production estimates. ...
To compare in situ and laboratory estimates of sea spray aerosol (SSA) production fluxes, we conducted two research campaigns in the vicinity of an eddy covariance (EC) flux tower on the island of Östergarnsholm in the Baltic Sea during May and August 2021. To accomplish this, we performed EC flux measurements for particles with diameters between 0.25 and 2.5 µm simultaneously with laboratory measurements using a plunging jet sea spray simulation chamber containing local seawater sampled close to the footprint of the flux tower. We observed a log-linear relationship between wind speed and EC-derived SSA emission fluxes, a power-law relationship between significant wave height and EC-derived SSA emission fluxes, and a linear relationship between wave Reynolds number and EC-derived SSA emission fluxes, all of which are consistent with earlier studies. Although we observed a weak negative relationship between particle production in the sea spray simulation chamber and seawater chlorophyll-α concentration and a weak positive relationship with the concentration of fluorescent dissolved organic matter in seawater, we did not observe any significant impact of dissolved oxygen on particle production in the chamber. To obtain an estimate of the size-resolved emission spectrum for particles with dry diameters between 0.015 and 10 µm, we combined the estimates of SSA particle production fluxes obtained using the EC measurements and the chamber measurements in three different ways: (1) using the traditional continuous whitecap method, (2) using air entrainment measurements, and (3) simply scaling the chamber data to the EC fluxes. In doing so, we observed that the magnitude of the EC-derived emission fluxes compared relatively well to the magnitude of the fluxes obtained using the chamber air entrainment method as well as the previous flux measurements of Nilsson et al. (2021) and the parameterizations of Mårtensson et al. (2003) and Salter et al. (2015). As a result of these measurements, we have derived a wind-speed-dependent and wave-state-dependent SSA parameterization for particles with dry diameters between 0.015 and 10 µm for low-salinity waters such as the Baltic Sea, thus providing a more accurate estimation of SSA production fluxes.
... The flux of the number of sea-spray particles is expressed as a function of the particle radius at 80% humidity and the 10 m horizontal wind speed, assuming number median dry radius values of 0.09 and 0.794 μm for fine and coarse sea-spray particles, along with geometric standard deviations of 1.5 and 2.0, respectively . To further address the temperature 210 effects on the sea spray source fluxes, polynomial expressions derived based on laboratory (chamber) experiments (Salter et al., 2015) have been implemented. Note here that the emitted sea-spray particles are assumed to consist of pure sodium chloride (NaCl), although an explicit sea-salt composition is applied for thermodynamic calculations in the model (see Sect. 2.2.2). ...
Secondary inorganic aerosols (SIA) are major components of fine particulate matter (PM2.5), having substantial implications for climate and air quality in an urban environment. In this study, a state-of-the-art thermodynamic model has been coupled to the source dispersion and photochemistry city-scale chemistry transport model EPISODE-CityChem, able to simulate pollutants on a horizontal resolution of 100 x 100 m2, to determine the equilibrium between the inorganic gas and aerosol phases over the Greater Area of Athens, Greece, for the year 2019. In agreement with in-situ observations, sulfate (SO42-) is calculated to have the highest annual mean surface concentration (2.15 ± 0.88 μg m-3) among SIA in the model domain, followed by ammonium (NH4+; 0.58 ± 0.14 μg m-3) and fine nitrate (NO3-; 0.24 ± 0.22 μg m-3). Simulations denote that NO3- formation strongly depends on the local nitrogen oxide emissions, along with the ambient temperature, the relative humidity, and the photochemical activity. Additionally, we show that anthropogenic combustion sources may have an important impact on the NO3- formation in an urban area. During the cold period, the combined effect of decreased temperature in the presence of non-sea salt potassium favors the partitioning of HNO3 in the aerosol phase in the model, raising the NO3- formation in the area. Overall, this work highlights the significance of atmospheric composition and the local meteorological conditions for the equilibrium distribution of nitrogen-containing semivolatile compounds and the acidity of inorganic aerosols, especially in urban areas where atmospheric trace elements from natural and anthropogenic sources coexist.
... Instead, we assumed that the entire surface of the seawater was covered in bubbles, and used the total surface area of the seawater. 305 2.7.3 Derivation of SSA production fluxes from the chamber measurements using air entrainment Another method for obtaining estimates of the production flux of SSA particles from breaking waves and whitecaps using sea spray simulation chambers has been developed by Long et al. (2011) and Salter et al. (2015). These authors combined the number of particles produced per unit time in a logarithmic interval of D p with measurements of air entrainment/detrainment. ...
... Previous studies have observed an increase in particle 460 production at lower seawater temperatures (e.g. Woolf et al., 1987;Bowyer et al., 1990;Mårtensson et al., 2003;Sellegri et al., 2006;Zábori et al., 2012;Salter et al., 2014Salter et al., , 2015Nielsen and Bilde, 2020;Zinke et al., 2022). In contrast, other studies (e.g. ...
... while panel (b) shows estimated mass emission flux for particles with dry diameters 0.02 < Dp < 2.8 µm, which is the range in which the Mårtensson et al. (2003) parameterization is valid. Figure 7 shows that the wind speed-dependent parameterization derived in this study produces size-resolved number emis-585 sion fluxes and mass emission estimates that agree well with those obtained from the parameterizations by Mårtensson et al. (2003), Kirkevåg et al. (2013) and Salter et al. (2015). Although recent studies suggest that sea state is a better predictor of SSA emissions than wind speed alone (Norris et al., 2013;Ovadnevaite et al., 2014;Yang et al., 2019), our wave Reynolds number-dependent parameterization yields lower mass emission fluxes than the wind speed dependent parameterizations, particularly at wind speeds above 10 m s −1 . ...
To bridge the gap between in situ and laboratory estimates of sea spray aerosol (SSA) production fluxes, we conducted two research campaigns in the vicinity of an eddy covariance (EC) flux tower on the island of Östergarnsholm in the Baltic Sea during May and August 2021. To accomplish this, we performed EC flux measurements simultaneously with laboratory measurements using a plunging jet sea spray simulation chamber containing local seawater sampled close to the footprint of the flux tower. We observed a log-linear relationship between wind speed and EC-derived SSA emission fluxes, a power-law relationship between significant wave height and EC-derived SSA emission fluxes, and a linear relationship between wave Reynolds number and EC-derived SSA emission fluxes, all of which are consistent with earlier studies. Although we observed a weak negative relationship between particle production in the sea spray simulation chamber and seawater chlorophyll-α concentration and a weak positive relationship with the concentration of fluorescent dissolved organic matter in seawater, we did not observe any significant impact of dissolved oxygen on particle production in the chamber. To obtain an estimate of the size-resolved emission spectrum for particles with dry diameters between 0.015 and 10 μm, we combined the estimates of SSA particle production fluxes obtained using the EC measurements and the chamber measurements in three different ways: 1) using the traditional continuous whitecap method, 2) using air entrainment measurements, and 3) simply scaling the chamber data to the EC fluxes. In doing so, we observed that the magnitude of the EC-derived emission fluxes compared relatively well to the magnitude of the fluxes obtained using the chamber air entrainment method, as well as the previous flux measurements of Nilsson et al. (2021) and the parameterisations of Mårtensson et al. (2003) and Salter et al. (2015). As a result of these measurements, we have derived a wind speed-dependent and wave state-dependent SSA parameterization for particles with dry diameters between 0.015 and 10 μm for low-salinity waters such as the Baltic Sea, thus providing a more accurate estimation of SSA production fluxes.
... Sea spray emission over the open ocean is due to wind action that forms bursting bubbles at the sea surface, visible as white caps, which emit aerosols to the atmosphere (Monahan et al., 1986). The sea surface temperature (SST) can also modulate the size and number of aerosols emitted (Jaeglé et al., 2011;Liu et al., 2021;Mårtensson et al., 2003;Salter et al., 2015). Salinity affects the electrolytic properties of water, and as salinity increases, coalescence is inhibited and bubbles form in larger number and smaller radii, which then also affects the emission flux of SSaer (Zinke et al., 2022). ...
... The Note. MA06 is Mahowald et al. (2006), MO86 is Monahan et al. (1986), MA03 is Mårtensson et al. (2003), JA11 is Jaeglé et al. (2011), GR14 is Grythe et al. (2014), GO03 is Gong (2003), SA15 is Salter et al. (2015), and SM98 is M. H. Smith and Harrison (1998 , 2012). For regionally averaged numbers, a weighted mean is applied, with weights corresponding to the grid cell area. ...
... Although there is still debate on the exact role that SST plays in the sea spray emission process, including it generally improves the fit with observations as reviewed in Grythe et al. (2014). For example, the Jaeglé et al. (2011) parameterization decreases emissions at colder SST, whereas the Salter et al. (2015) source function does the opposite. For polar waters, for example, an increase in SST may decrease the number of sea spray aerosol produced, without significantly affecting the shape of the size distribution (Zábori et al., 2012). ...
Natural aerosols and their interactions with clouds remain an important uncertainty within climate models, especially at the poles. Here, we study the behavior of sea salt aerosols (SSaer) in the Arctic and Antarctic within 12 climate models from CMIP6. We investigate the driving factors that control SSaer abundances and show large differences based on the choice of the source function, and the representation of aerosol processes in the atmosphere. Close to the poles, the CMIP6 models do not match observed seasonal cycles of surface concentrations, likely due to the absence of wintertime SSaer sources such as blowing snow. Further away from the poles, simulated concentrations have the correct seasonality, but have a positive mean bias of up to one order of magnitude. SSaer optical depth is derived from the MODIS data and compared to modeled values, revealing good agreement, except for winter months. Better agreement for aerosol optical depth than surface concentration may indicate a need for improving the vertical distribution, the size distribution and/or hygroscopicity of modeled polar SSaer. Source functions used in CMIP6 emit very different numbers of small SSaer, potentially exacerbating cloud‐aerosol interaction uncertainties in these remote regions. For future climate scenarios SSP126 and SSP585, we show that SSaer concentrations increase at both poles at the end of the 21st century, with more than two times mid‐20th century values in the Arctic. The pre‐industrial climate CMIP6 experiments suggest there is a large uncertainty in the polar radiative budget due to SSaer.
... The prediction of smaller drops in colder water is in qualitative agreement with various field measurements (Saliba et al., 2019;Salter et al., 2015) and laboratory measurements (Mårtensson et al., 2003;Sellegri et al., 2006). The role of temperature on the total number of emitted sea spray aerosol is largely debated (Christiansen et al., 2019;Forestieri et al., 2018;Salter et al., 2014). ...
Bubbles bursting at the ocean surface are an important source of ocean‐spray aerosol, with implications on radiative and cloud processes. Yet, very large uncertainties exist on the role of key physical controlling parameters, including wind speed, sea state and water temperature. We propose a mechanistic sea spray generation function that is based on the physics of bubble bursting. The number and mean droplet radius of jet and film drops is described by scaling laws derived from individual bubble bursting laboratory and numerical experiments, as a function of the bubble radius and the water physico‐chemical properties (viscosity, density and surface tension, all functions of temperature), with drops radii at production from 0.1 to 500 µm. Next, we integrate over the bubble size distribution entrained by breaking waves. Finally, the sea spray generation function is obtained by considering the volume flux of entrained bubbles due to breaking waves in the field constrained by the third moment of the breaking distribution (akin to the whitecap coverage). This mechanistic approach naturally integrates the role of wind and waves via the breaking distribution and entrained air flux, and a sensitivity to temperature via individual bubble bursting mechanisms. The resulting sea spray generation function has not been tuned or adjusted to match any existing data sets, in terms of magnitude of sea salt emissions and recently observed temperature dependencies. The remarkable coherence between the model and observations of sea salt emissions therefore strongly supports the mechanistic approach and the resulting sea spray generation function.
... However, it has been found that SSSFs that rely solely on wind speed fail to predict measured SSA concentrations (Grythe et al., 2014;Jaeglé et al., 2011). Therefore, some SSSFs have been expanded to also include oceanic parameters such as sea surface temperature (SST) (Jaeglé et al., 2011;Mårtensson et al., 2003;Salter et al., 2015;Sofiev et al., 2011), water salinity (Sofiev et al., 2011), and wave state (Ovadnevaite et al., 2014), which led to better reproduction of observed SSA concentrations. ...
... The developed LSSF and SSSF are compared to a collection of common SSSFs from the literature in Fig. 4b. It is worth noting that some source functions shown in this figure are reported as a function of dry particle diameter (D dry ) (e.g., Clarke et al., 2006;Mårtensson et al., 2003;Salter et al., 2015), while others (e.g., Gong, 2003) are reported in terms of particle radius at RH = 80 % (r 80 ). For the sake of consistency, we converted the latter parameterizations (denoted by an asterisk in the legend) to a function of dry particle diameter D dry by assuming r dry = r 80 /2, a common rule of thumb (O'Dowd and de Leeuw, 2007;Veron, 2015). ...
... The Clarke et al. (2006) source function is developed based on ambient measurements of SSAs generated from the surf zone and hence might overestimate SSA emission from open-ocean breaking waves. Meanwhile, the Mårtensson et al. (2003), Salter et al. (2015), and present SSSFs are developed using measurements of laboratory-generated SSAs. However, the method in which SSAs were generated in each study is different, with the Mårtensson et al. (2003) study employ- ing a small chamber (2 L) with a glass frit, the Salter et al. (2015) study using a larger cylindrical tank (170 L) with a circular water jet, and the present study using the ∼ 300 L MART with a thin water sheet. ...
Lake spray aerosols (LSAs) are generated from freshwater breaking waves in a mechanism similar to their saltwater counterparts, sea spray aerosols (SSAs). Unlike the well-established research field pertaining to SSAs, studying LSAs is an emerging research topic due to their potential impacts on regional cloud processes and their association with the aerosolization of freshwater pathogens. A better understanding of these climatic and public health impacts requires the inclusion of LSA emission in atmospheric models, yet a major hurdle to this inclusion is the lack of a lake spray source function (LSSF), namely an LSA emission parameterization. Here, we develop an LSSF based on measurements of foam area and the corresponding LSA emission flux in a marine aerosol reference tank (MART). A sea spray source function (SSSF) is also developed for comparison. The developed LSSF and SSSF are then implemented in the Community Multiscale Air Quality (CMAQ) model to simulate particle emissions from the Great Lakes surface from 10 to 30 November 2016. Measurements in the MART revealed that the average SSA total number concentration was 8 times higher than that of LSA. Over the 0.01–10 µm aerosol diameter size range, the developed LSSF was around 1 order of magnitude lower than the SSSF and around 2 orders of magnitude lower for aerosols with diameters between 1 and 3 µm. Model results revealed that LSA emission flux from the Great Lakes surface can reach ∼105 m−2 s−1 during an episodic event of high wind speeds. These emissions only increased the average total aerosol number concentrations in the region by up to 1.65 %, yet their impact on coarse-mode aerosols was much more significant, with up to a 19-fold increase in some areas. The increase in aerosol loading was mostly near the source region, yet LSA particles were transported up to 1000 km inland. Above the lakes, LSA particles reached the cloud layer, where the total and coarse-mode particle concentrations increased by up to 3 % and 98 %, respectively. Overall, this study helps quantify LSA emission and its impact on regional aerosol loading and the cloud layer.
