Updating sea spray aerosol emissions in the Community Multiscale Air Quality ( CMAQ ) model version 5 . 0 . 2

Introduction Conclusions References Tables Figures

munity Multiscale Air Quality (CMAQ) model was updated to enhance fine mode SSA emissions, include sea surface temperature (SST) dependency, and reduce coastallyenhanced emissions. Predictions from the updated CMAQ model and those of the previous release version, CMAQv5.0.2, were evaluated using several regional and national observational datasets in the continental US. The updated emissions generally 10 reduced model underestimates of sodium, chloride, and nitrate surface concentrations for an inland site of the Bay Regional Atmospheric Chemistry Experiment (BRACE) near Tampa, Florida. Including SST-dependency to the SSA emission parameterization led to increased sodium concentrations in the southeast US and decreased concentrations along parts of the Pacific coast and northeastern US. The influence of sodium 15 on the gas-particle partitioning of nitrate resulted in higher nitrate particle concentrations in many coastal urban areas due to increased condensation of nitric acid in the updated simulations, potentially affecting the predicted nitrogen deposition in sensitive ecosystems. Application of the updated SSA emissions to the California Research at the Nexus of Air Quality and Climate Change (CalNex) study period resulted in mod-

Introduction
Sea spray aerosols (SSA) contribute significantly to the global aerosol burden, both in terms of mass (Lewis and Schwartz, 2004) and cloud condensation nuclei concentration (Pierce and Adams, 2006). The chemical composition of SSA (e.g., major ions: Na + , Mg 2+ , Ca 2+ , K + , Cl − , SO 2− 4 ; Tang et al., 1997) is affected by atmospheric pro-5 cessing, with the uptake of nitric acid (Gard et al., 1998, and references therein), sulfuric acid (McInnes et al., 1994), dicarboxylic acids (Sullivan and Prather, 2007), and methylsulfonic acid (Hopkins et al., 2008) shown to be important processes. Sea spray aerosols also influence gas-phase atmospheric chemistry via displacement of chlorine and bromine from the particle phase and subsequent impacts on ozone formation and Introduction  (2011) shows a broad range (0.05-0.1 µm in dry diameter) of particle sizes having the maximum number production flux. Recent SSA production parameterizations (see Grythe et al., 2014) reflect these measurements, with most having a production rate maximum at aerosol sizes lower than the lower cutoff (0.07 µm dry diameter) of Gong (2003). Due to the lack of detailed submicron measurements at the time, the Gong where dF dr is the SSA number flux with units of m −2 s −1 µm −1 , r is the particle radius in µm at 80 % relative humidity, U 10 is the 10 m wind speed in m s −1 , and Θ is an adjustable shape parameter that controlled the submicron size distribution. Gong (2003) tested Θ 10 values between 15 and 40, suggesting (with limited observational evidence) a Θ value of 30. Seawater temperature can increase or decrease SSA number emissions by up to ∼ 100 % due to the temperature dependency of surface tension, density, viscosity, and air entrainment (Mårtensson et al., 2003;Sellegri et al., 2006;Zábori et al., 2012a;15 Ovadnevaite et al., 2014;Callaghan et al., 2014). Mårtensson et al. (2003), Sellegri et al. (2006), and Zábori et al. (2012a) all observe a negative temperature dependence for the production flux of SSA < 70 nm diameter in synthetic seawater laboratory experiments. Similar negative temperature dependencies are measured in SSA generated from Arctic Ocean seawater (Zábori et al., 2012b). Mårtensson et al. (2003) 20 and Sellegri et al. (2006) also reported positive temperature dependencies for the SSA production flux for particles larger than 70 nm in diameter. This difference in the temperature-dependence of small and large SSA emissions is likely due to their bubble size-dependence and impact of SST on small and large bubbles (Sellegri et al., 2006). Sofiev et al. (2011) Jaeglé et al. (2011) leads to the development of a third order polynomial function for the SST dependence of the Gong et al. (2003) SSA emission parameterization. Grythe et al. (2014) compares the Jaeglé et al. (2011) andSofiev et al. (2011) temperature dependencies, finding that the Jaeglé et al. (2011) function gives the best model improvement to the observed temperature dependence.  ing studies implementing the Jaeglé et al. (2011) temperature-dependent SSA emissions have shown improved prediction of surface sea-salt mass concentration (Spada et al., 2013;Grythe et al., 2014) relative to temperature-indepenent emissions. Using a process-based approach incorporating seawater viscosity and wave state, Ovadnevaite et al. (2014) finds a positive temperature dependence of SSA emissions sim-10 ilar to Jaeglé et al. (2011) but resembling a linear (rather than third order polynomial) relationship.
In addition to bubble bursting in the open ocean, SSA can be emitted via wave breaking in the surf zone covering an area roughly 20 to 100 m from the coastline (Petelski and Chomka, 1996;Lewis and Schwartz, 2004). Surf zone SSA emissions have been shown to be enhanced relative to the open ocean, resulting in higher sea-salt concentrations near the coast (de Leeuw et al., 2000). Vignati et al. (2001) concludes that surf zone SSA emissions provide additional surface for heterogeneous reactions and impact the atmospheric chemistry of coastal areas. There are limited observations and large uncertainties in the surf zone SSA emissions related to the zone width and in diameter (PM 10 ) by up to 20 % in the Eastern Mediterranean (Im, 2013).
The current SSA treatment in the Community Multiscale Air Quality (CMAQ) model version 5.0.2 is described by Kelly et al. (2010) and includes the open ocean emissions of Gong (2003), coastally-enhanced emissions similar to de Leeuw et al. (2000) 3909 in which a fixed whitecap coverage of 100 % is applied to the Gong (2003) parameterization for a 50 m-wide surf zone, and dynamic transfer of HNO 3 , H 2 SO 4 , HCl, and NH 3 between coarse mode particles and the gas phase. Based on comparison with observations from three Tampa, Florida sites at different distances from the coastline, Kelly et al. (2010) finds that enhancing sea spray emissions in coastal grid cells according 5 to a 50 m wide surf zone with a 100 % whitecap coverage improved CMAQ model underprediction of sodium, chloride, and nitrate concentrations (particularly at the coastal site) relative to a simulation with only the Gong (2003) open ocean emissions. The dynamic transfer of HNO 3 , H 2 SO 4 , HCl, and NH 3 between coarse particles and the gas phase as implemented by Kelly et al. (2010) further improves predicted concentrations 10 of semi-volatile species like chloride and nitrate. Despite these improvements, persistent underpredictions of sodium, chloride, and nitrate concentrations at the inland site remain unresolved. In this work, we expand upon the Kelly et al. (2010) CMAQ SSA emission treatment by updating the fine mode size distribution, SST dependence, and coastally-enhanced emissions to reflect recent SSA research. Due to the advanced 15 treatment of SSA chemistry in CMAQ, their emissions can be evaluated using concentrations of the directly-emitted sea-salt components such as sodium and species such as nitrate that react with sea-salt components in the atmosphere. Specifically, we hypothesize that the improved prediction of sodium will correspond to improvements in the gas-particle partitioning of nitrate aerosol as suggested by Kelly et al. (2014).

20
The goal of this work is to improve the size distribution, magnitude, and spatiotemporal variability of CMAQ-predicted SSA emissions and the resulting impacts on atmospheric chemistry in coastal and inland areas.

Observational datasets
Two field campaigns with different meteorology, atmospheric chemistry, and SSA sources from oceans having distinct surface temperatures and bathymetry were used to evaluate the updated emissions. The Bay Regional Atmospheric Chemistry Exper-5 iment (BRACE) (Atkeson et al., 2007;Nolte et al., 2008)  (≤ 15 min) using a soluble particle collector employing ion chromatography (Dasgupta et al., 2007) and denuder difference (Arnold et al., 2007). The California Research at the Nexus of Air Quality and Climate Change (CalNex) 2010 field project was conducted from May to July 2010 throughout California. The goal of the study was to simultaneously measure variables affected by emissions, 20 atmospheric transport and dispersion, atmospheric chemical processing, and cloudaerosol interactions and aerosol radiative effects (Ryerson et al., 2013). The South Coast portion of the CalNex campaign included continuous ground-based measurements of PM < 2.5 µm in diameter (PM 2.5 ) composition using particle-into-liquid sampling and ion chromotography (Weber et al., 2001)  ical Speciation Network (CSN) within the South Coast, San Francisco Bay, and San Diego air basins. Hereafter, these CSN sites and the Pasadena site will collectively be referred to as the coastal CalNex sites. In addition to local field campaigns, we evaluated SSA emissions in CMAQ against surface PM 2.5 concentrations of sodium and nitrate measured throughout the continental US (CONUS) as part of the Interagency Monitoring of Protected Visual Environments (IMPROVE) for remote/rural locations and CSN for urban locations during the May 2002 BRACE time period. Daily-average sodium mass concentrations in the IM-PROVE and CSN networks were measured once every three days via tube-generated X-ray fluorescence (XRF) (White, 2008). Nitrate concentrations for both the IMPROVE 10 and CSN networks are determined by ion chromatography. During the May 2002 period, the IMPROVE network consisted of ∼ 160 sites while the CSN network consisted of ∼ 230 sites.

Model configuration
In this work, we used the CMAQ model v5.0.2 to simulate the impact of updated sea 15 spray aerosol emissions on surface aerosol concentrations/size distribution and gasparticle partitioning. CMAQ represents the aerosol size distribution using three modes (Aitken, accumulation, and coarse) and simulates inorganic aerosol thermodynamics using ISORROPIA II (Binkowski and Roselle, 2003;Fountoukis and Nenes, 2007). Kelly et al. (2010) further enhanced the SSA chemical treatment in CMAQ by allowing 20 dynamic transfer of HNO 3 , H 2 SO 4 , HCl, and NH 3 between coarse particles and the gas phase. For comparison with the CONUS observational datasets such as IMPROVE and CSN, we used a model domain covering the continental US at 12 km×12 km horizontal resolution and 41 vertical layers with a surface layer up to 20 m a.g.l. The simulation time period (1 May to 3 June 2002 with an 11 day spin-up) was made to coincide with 25 the BRACE campaign to enable additional evaluation of the coastal-to-inland changes in the aerosol composition/size distribution and gas-particle partitioning. Meteorological parameters were generated by the Weather Research Forecasting et al., 2008), with initial and boundary conditions generated from a previous CMAQ simulation and a GEOS-Chem global model simulation, respectively. Detailed meteorological and emission inputs can be found in Bash et al. (2013). For the CalNex comparison, we used a model domain covering nearly all of California and Nevada as well as parts of the Pacific Ocean, Mexico, and Arizona with 4 km horizontal resolution and 34 vertical layers. Chemical boundary conditions were derived from a GEOS-Chem simulation (Henderson et al., 2014), and prognostic meteorological fields used to drive CMAQ were generated with WRF version 3.4. Detailed description of the meteorological and emission inputs can be found in Baker et al. (2013) and Kelly et al. (2014). SST was taken from the Moderate Resolution Imaging Spectroradiometer 10 (MODIS) composite for all simulations.
As the Θ value primarily affects the fine mode size distribution of the Gong (2003) SSA production parameterization, adjusting Θ allows the user to change the (1) number flux without affecting the mass flux and (2) peak aerosol size emitted (see Fig. S1 in the Supplement). These two changes can result in higher downwind concentrations of 15 sea-salt components due to the reduced dry deposition velocities of fine mode aerosols relative to the coarse mode and resulting increase in atmospheric lifetime. The higher downwind concentration of sodium aerosol can increase the concentration of nitrate aerosol by affecting the gas-particle partitioning of total inorganic nitrate (NO − 3 +HNO 3 ). This increase, in turn, can increase the nitrate lifetime as fine mode NO − 3 has a longer 20 atmospheric lifetime than gaseous HNO 3 . Both the sea-salt and nitrate aerosol concentrations at the Sydney inland site were found to be underpredicted in CMAQ (Kelly et al., 2010). For this study, we used Θ values of 30 (consistent with the current CMAQ representation, given as CMAQv5.0.2a), 20 (CMAQv5.0.2b), 10 (CMAQv5.0.2c), and 8 (CMAQv5.0.2d), which were expected to result in increasingly large fine mode SSA 25 emissions (see Fig. S1). For the simulations using Θ values ≤ 20, the lower limit of the SSA dry diameter is decreased to 10 nm to better reflect changes in the size distribution (see Fig. S1). This decrease was consistent with measurements of Aitken mode SSA (Clarke et al., 2006) (Grythe et al., 2014). The radius of peak emissions at 80 % relative humidity (RH) from the Gong (2003) parameterization with a Θ value of 8 was ∼ 60 nm; this value was similar to the radius of maximum production flux from several parameterizations reviewed in de Leeuw et al. (2011). Including the positive temperature dependence for SSA emissions in CMAQ was ex- where SST has units of • C. The updated SSA emission parameterization given in Eq.
(2) was mapped to the CMAQ aerosol modes as a function of relative humidity following Zhang et al. (2005Zhang et al. ( , 2006. A summary of the different CMAQ model simulations in which SSA emissions were changed is given in

BRACE
The total particulate (PM tot ) nitrate, chloride, and sodium concentrations observed at the three sites during the BRACE campaign and corresponding CMAQ predicted concentrations for the "Baseline" (v.5.0.2a) and sensitivity simulations (v5.0.2b-h) are sum-5 marized in Table 2. Generally, the Baseline simulation underpredicted the nitrate concentrations for all sites with a normalized mean bias (NMB) of −46.4 %. The Baseline simulation predicted the magnitude of chloride and sodium at the coastal site (Azalea Park) relatively well. However, it increasingly underpredicted chloride and sodium as the distance from the shore increased. The Baseline simulation overestimated by ap-10 proximately a factor of 2 the observed decrease in PM tot chloride and sodium between the coastal Azalea Park and inland Sydney sites. The average fine mode sodium concentration (given as PM 1.8 for the measurements and the sum of the Aitken and accumulation modes for the model predictions) were consistently underpredicted by the Baseline simulation for the BRACE sites with an NMB of −21.6 %. As the Θ value 15 was changed from 30 to 20 (v5.0.2b), the predicted PM tot chloride and sodium (and nitrate via secondary processes) decreased slightly despite an increase in fine mode sodium concentrations. This surprising result was due to slight differences in the fitting of coarse mode SSA emissions to CMAQ's aerosol modes. The transition of Θ values from 20 to 10 to 8 led to small (< 10 %) increases in the nitrate, chloride, and sodium 20 concentrations relative to the Baseline simulation for all sites. Although it slightly overestimated chloride and sodium at the coastal Azalea Park site, the v5.0.2d simulation with a Θ value of 8 had the best prediction (both in terms of magnitude and correlation) of concentrations at the Gandy Bridge and Sydney sites. The modeled chloride and sodium aerosol concentrations were much more sensi-  Fig. S2), concentrations of nitrate, chloride, and sodium were predicted to be higher (> 20 %) in the v5.0.2e simulation than the Baseline for all sites. The reduction in coastally-enhanced emissions in the v5.0.2f simulation had a more site-specific impact on surface concentrations, with the coastal Azalea Park site hav-5 ing a 30 % decrease in predicted chloride and sodium concentrations and the bayside (Gandy Bridge) and inland (Sydney) sites having only a 10-15 % decrease relative to the Baseline simulation. Figure S3 shows the model grid cells in the vicinity of Tampa Bay (including the Gandy Bridge site) have a representation of the open ocean fraction but not the surf zone fraction used for enhancement of coastal SSA emissions. 10 The predicted 50 % decrease in the chloride and sodium surface concentrations from Azalea Park to Sydney in the v5.0.2f simulation was more similar to the observed 30 % decrease than the 60 % decrease predicted by the Baseline simulation. The best model performance at the BRACE sites occurred with SSA emissions having a Θ value of 8, SST-dependence, and a reduced coastal enhancement as implemented in the v5.0.2g and v5.0.2h simulations. While both the v5.0.2g and v5.0.2h simulations underpredicted nitrate concentrations at all sites, the chloride and sodium concentrations were consistently improved both in magnitude and correlation compared to the Baseline simulation. The largest improvement occurred at the inland Sydney site, where substantial underpredictions of chloride and sodium in the Baseline simulation 20 were largely eliminated. Comparison of the simulations with the third order polynomial (v5.0.2g) and linear (v5.0.2h) SST dependence of SSA emissions revealed that the linear dependence led to improved prediction of chloride and sodium at the Azalea Park and Sydney sites and similar performance at the Gandy Bridge site. Improved prediction of chloride and sodium concentrations at these sites was not surprising as veloped for GEOS-Chem in Jaeglé et al. (2011). Therefore, the v5.0.2h simulation is referred hereafter as the "Revised" simulation. The statistical improvement in the Revised simulation relative to the Baseline (v5.0.2a) simulation is reflected in the time series of sodium concentrations at the three sites (Fig. 2). Besides showing the generally higher PM tot sodium concentrations at the 5 bayside and inland sites and higher PM 1.8 sodium concentrations at all sites, Fig. 2 also shows that the Revised simulation diverges most from v5.0.2a during periods of high SSA concentration episodes (15, 22 May 2002). This suggests that the Revised simulation better replicated the sea spray aerosol emissions during periods with strong onshore flow compared to the Baseline simulation. The range of PM 1.8 sodium concentrations predicted by the Revised simulation was more consistent with observations than the Baseline simulation, especially at the Sydney site which has observed con- decreases were limited spatially, as adjacent cells just offshore had large increases in sodium concentration. Like the fine mode changes, the largest total sodium concentration increases occurred offshore while more modest increases were predicted for inland locations. The coastal-inland concentration gradients were stronger for the total concentration changes due to the faster deposition velocity of coarse mode aerosols 5 (relative to the fine mode) which comprise most of the total mass. The hourly time series of observed and predicted nitrate gas/particle partitioning from the Sydney site for May 2002 (Fig. 4) shows that the Revised simulation pushes the partitioning towards the particle phase (relative to the Baseline simulation) and closer to observations. The average observed fraction of nitrate in the particle phase 10 was 0.51 while the predicted fractions from the Baseline and Revised simulations were 0.36 and 0.42, respectively. Figure 4 indicates that the largest difference in the nitrate partitioning between the Baseline and Revised simulations occurred during the daytime, when higher concentrations of inorganic ions like sodium prevented some of the nitric acid evaporation from the particle phase during the hot afternoon period. Despite 15 improvement in the daytime partitioning, the Revised simulation continued to overpredict the nighttime nitrate fraction and daytime nitric acid fraction. This impact on partitioning is consistent with Kelly et al. (2014), which suggested that improving CMAQ prediction of sodium concentration and relative humidity would improve gas-particle partitioning of nitrate in the CalNex model domain.

CalNex
Similar to results for the BRACE sites, the predicted PM 2.5 sodium surface concentrations were improved in the Revised simulation relative to the Baseline for sites examined during the CalNex simulation period (see Fig. 5). Surface sodium concentrations were underpredicted by both the Baseline and Revised simulations for all the coastal 25 CalNex sites, especially in the 11-16 June time period when high sodium concentrations at several of the sites were not well captured by either the Revised or Baseline simulation. It is worth noting that a sensitivity test in which the coastally-enhanced 3918 Introduction

Tables Figures
Back Close

Full Screen / Esc
Printer-friendly Version

Interactive Discussion
Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | emissions were increased (using a surf zone width of 100 m rather than 25 m as in the Revised simulation) did not substantially improve the sodium underpredictions at the coastal CalNex sites. Monthly-average (June 2010) sodium concentrations predicted in the Revised simulation increased by up to ∼ 0.25 µg m −3 off the California coast relative to the Baseline simulation, with increases between 0.05 and 0.1 µg m −3 widespread in 5 the San Francisco, Los Angeles, and San Diego air basins (Fig. 5). Hourly-or dailyaverage increases between the Revised and Baseline simulations were even higher in these urban areas, with the time series plots in Fig. 5 showing increases up to 0.2 µg m −3 . The spatial patterns of impacts on sodium in the Central Valley and South Coast air basin matched those of tracers released from San Francisco and LAX airport 10 that are drawn inland on the sea breeze (Baker et al., 2013). Improving the sodium underprediction at the coastal CalNex sites in the Revised simulation had the effect of improving the frequent nitrate aerosol underprediction at the same sites (see Fig. 6). Unlike the sodium concentration changes, the largest (0.5 µg m −3 ) increases in monthly-average nitrate aerosol concentration occurred over 15 the Los Angeles air basin well inland from the coast. The increase of nitrate largely occurred in inland areas where nitric acid was produced downwind of urban centers with large NO x emissions. For conditions unfavorable for ammonium nitrate formation (e.g., high temperature, low RH, low NH 3 ), nitrate may still form in sea spray particles through replacement reactions (e.g., NaCl(p) + HNO 3 (g) → NaNO 3 (p) + HCl(g)). Since 20 such pathways involve pollution derived from urban emissions (HNO 3 ) in addition to sea salt (NaCl), the highest nitrate increases occurred inland despite the relatively small increases in sodium compared to the Baseline simulation in these areas. Similarly, polluted sites such as Pasadena and Riverside had larger increases in nitrate concentrations than cleaner sites in the San Francisco air basin despite having simi-25 lar sodium concentration changes. This behavior suggested that these SSA emission updates had the largest air quality impact in coastal urban areas with mixtures of marine and polluted air masses. Note that the nitrate-to-sodium ratio of molar masses is about 2.7, and so a 1 : 1 increase in the moles of sodium and nitrate according to NaNO 3 stoichiometry would lead to a greater increase of nitrate than sodium mass. The nitrate underpredictions in Fig. 6 were not resolved entirely by improved sodium predictions. In Riverside, for example, nitrate underpredictions in the Revised simulation were likely due in part to underestimates of ammonia emissions from upwind dairy facilities (Nowak et al., 2012;Kelly et al., 2014).

Continental US
Unlike the PM 1.8 or PM 2.5 sodium concentrations evaluated using the BRACE and Cal-Nex observations, the total sodium surface concentration changes shown in Fig. 1b both increased and decreased in the CONUS domain due to the variability in coastal and oceanic SST. The distribution of fine (Aitken + accumulation) mode concentration changes (Fig. 1a) had some similar features to the total concentration changes (Fig. 1b), with the largest increases occurring over areas with high (>∼ 20 • C) SSTs.
Differences between the fine mode and total concentration changes were most notable for regions with low (<∼ 10 • C) SSTs (Pacific and northeast US coasts) and for inland regions. Because fine mode particles have a low dry deposition velocity, offshore in- 15 creases in the fine mode sodium concentrations were able to extend inland and lead to increased deposition (see Fig. S4a). The flat topography and large offshore concentration increases in the southeast US resulted in concentration increases of up to 0.25 µg m −3 hundreds of kilometers from the coast. While reductions in fine mode SSA emissions due to low SSTs were balanced by increased emissions from chang-20 ing Θ, cold seawater temperatures off the Pacific coast and northeast US led to large decreases in total sodium concentration of up to −0.5 µg m −3 . As in the BRACE domain, the decrease in coastally-enhanced emissions led to localized decreases in PM tot sodium concentration for grid cells immediately adjacent to the coastline throughout the CONUS domain. Regions with rugged coastlines and barrier islands experienced the 25 largest concentration decreases because of the large surf zone area. Model comparison of PM 2.5 sodium concentrations from the IMPROVE and CSN networks revealed improvement from the Baseline to Revised simulation (see Fig. 7 both the IMPROVE and CSN networks, far fewer sites had an increased error (Fig. 7a) in the Revised simulation relative to the Baseline than had reductions in the model error (Fig. 7b). Sites where the model error increased in the Revised simulation were widely scattered across the CONUS domain and typically overpredicted concentrations. The sites where model error was reduced in the Revised simulation were in the 5 Southeast and mid-Atlantic US and typically underestimated concentrations. Sodium concentrations at numerous sites were underpredicted by > 0.1 µg m −3 in the Revised simulation, suggesting that the SSA emission changes were insufficient to bring the model into agreement with most observations. Despite cold waters off the Pacific coast leading to lower emissions (relative to the warmer Gulf of Mexico) in the Revised simulation, there were more sites in California that had an error reduction in the predicted concentrations than had increased model error. Cold waters in the Gulf of Maine and the associated lower emissions/concentrations in the Revised simulation had the effect of reducing the overprediction of sodium at several sites in coastal New England. where changes in sodium concentrations were more likely to have an impact on the partitioning of HNO 3 , HCl, and NH 3 between gas and particle phases leading to increases in nitrate aerosol concentrations (see Fig. 6 for an example). The enhanced partitioning of nitrate to the particle phase in the Revised simulation also led to de- creased deposition of total nitrate inland because of the lower dry deposition velocity of nitrate aerosol relative to nitric acid (see Fig. S4b).

Conclusions
In this study, the size distribution, temperature dependence, and coastal enhancement of sea spray aerosol (SSA) emissions were updated in the Community Multiscale Air 5 Quality (CMAQ) model version 5.0.2. Increasing fine mode emissions, including temperature dependence, and reducing the coastally-enhanced emissions from the "Baseline" to the "Revised" simulation collectively improved the summertime surface concentration predictions for sodium, chloride, and nitrate at three Bay Regional Atmospheric Chemistry Experiment (BRACE) sites near Tampa, Florida. Surface concentrations at the inland site near Tampa were particularly affected by these emission changes, as low dry deposition velocities for the fine mode aerosols increased the atmospheric lifetime and inland concentrations. The coastal-inland concentration gradient was also affected by the updated emissions, as the reduction in surf zone width used to enhance coastal emissions brought the Revised simulation in closer agreement with observa- 15 tions. These SSA emission updates led to increases in the fine mode sodium surface concentrations throughout coastal areas of the continental US, with the largest increases occurring near the Southeast US coast where sea surface temperatures (SST) were high. Decreases in the total sodium concentration were predicted for oceanic regions with low SST such as the Pacific and northern Atlantic coasts. Comparison of 20 the Baseline and Revised simulation with sodium observations from the IMPROVE and CSN networks showed that the updated emissions reduced the widespread underprediction of concentrations, especially in the Southeast and mid-Atlantic US. Non-linear responses between changes in total and sea-salt PM 2.5 concentrations indicated that the impacts of these emissions changes on aerosol chemistry were enhanced in pol-

Tables Figures
Back Close

Full Screen / Esc
Printer-friendly Version

Interactive Discussion
Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | aerosol concentrations at most CalNex sites, slightly reducing the underprediction from the Baseline simulation. Potential future work includes treating the organic fraction of SSA (Gantt et al., 2010), implementing the Group for High Resolution Sea Surface Temperature (GHRSST) dataset (Donlon et al., 2007), and linking the SSA emissions to marine boundary layer 5 halogen chemistry via debromination (Yang et al., 2005). Episodic high SSA concentrations are not well captured at any of the coastal CalNex sites in the Revised simulation, suggesting that other factors not accounted for in our updated SSA emission parameterization such as wind history, wave state, ocean biology, solar radiation, whitecap timescales, or the limited ocean surface area in the modeing domian (Callaghan et al., 10 2008(Callaghan et al., 10 , 2014Ovadnevaite et al., 2014;Long et al., 2014) may play an important role. Additional model developments focused on the South Coast region of California are warranted considering the impact on nitrate discussed above as well as the impact that reactive chlorine atoms derived from sea spray particles can have on ozone in this region (Simon et al., 2009;Sarwar et al., 2012;Riedel et al., 2014). As the fine mode size 15 distribution has a far greater impact on the number concentration than the mass concentration, the changes described in this study likely impact other model parameters such as aerosol radiative feedbacks which are included in the coupled WRF-CMAQ modeling system (Gan et al., 2014).