Biogenic sources contribute to cloud condensation nuclei (CCN) in the clean marine atmosphere, but few measurements exist to constrain climate model simulations of their importance. The chemical composition of individual atmospheric aerosol particles showed two types of sulfate-containing particles in clean marine air masses in addition to mass-based Estimated Salt particles. Both types of sulfate particles lack combustion tracers and correlate, for some conditions, to atmospheric or seawater dimethyl sulfide (DMS) concentrations, which means their source was largely biogenic. The first type is identified as New Sulfate because their large sulfate mass fraction (63% sulfate) and association with entrainment conditions means they could have formed by nucleation in the free troposphere. The second type is Added Sulfate particles (38% sulfate), because they are preexisting particles onto which additional sulfate condensed. New Sulfate particles accounted for 31% (7 cm−3) and 33% (36 cm−3) CCN at 0.1% supersaturation in late-autumn and late-spring, respectively, whereas sea spray provided 55% (13 cm−3) in late-autumn but only 4% (4 cm−3) in late-spring. Our results show a clear seasonal difference in the marine CCN budget, which illustrates how important phytoplankton-produced DMS emissions are for CCN in the North Atlantic.
Abstract. Marine biogenic particle contributions to atmospheric aerosol concentrations are not well understood though they are important for determining cloud optical and cloud-nucleating properties. Here we examine the relationship between marine aerosol measurements (with satellites and model fields of ocean biology) and meteorological variables during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). NAAMES consisted of four field campaigns between November 2015 and April 2018 that aligned with the four major phases of the annual phytoplankton bloom cycle. The FLEXible PARTicle (FLEXPART) Lagrangian particle dispersion model is used to spatiotemporally connect these variables to ship-based aerosol and dimethyl sulfide (DMS) observations. We find that correlations between some aerosol measurements with satellite-measured and modeled variables increase with increasing trajectory length, indicating that biological and meteorological processes over the air mass history are influential for measured particle properties and that using only spatially coincident data would miss correlative connections that are lagged in time. In particular, the marine non-refractory organic aerosol mass correlates with modeled marine net primary production when weighted by 5 d air mass trajectory residence time (r=0.62). This result indicates that non-refractory organic aerosol mass is influenced by biogenic volatile organic compound (VOC) emissions that are typically produced through bacterial degradation of dissolved organic matter, zooplankton grazing on marine phytoplankton, and as a by-product of photosynthesis by phytoplankton stocks during advection into the region. This is further supported by the correlation of non-refractory organic mass with 2 d residence-time-weighted chlorophyll a (r=0.39), a proxy for phytoplankton abundance, and 5 d residence-time-weighted downward shortwave forcing (r=0.58), a requirement for photosynthesis. In contrast, DMS (formed through biological processes in the seawater) and primary marine aerosol (PMA) concentrations showed better correlations with explanatory biological and meteorological variables weighted with shorter air mass residence times, which reflects their localized origin as primary emissions. Aerosol submicron number and mass negatively correlate with sea surface wind speed. The negative correlation is attributed to enhanced PMA concentrations under higher wind speed conditions. We hypothesized that the elevated total particle surface area associated with high PMA concentrations leads to enhanced rates of condensation of VOC oxidation products onto PMA. Given the high deposition velocity of PMA relative to submicron aerosol, PMA can limit the accumulation of secondary aerosol mass. This study provides observational evidence for connections between marine aerosols and underlying ocean biology through complex secondary formation processes, emphasizing the need to consider air mass history in future analyses.
Abstract. Deposition to the sea surface is a major atmospheric loss pathway for many important trace gases, such as sulfur dioxide (SO2). The air–sea transfer of SO2 is controlled entirely on the atmospheric side of the air–sea interface due to high effective solubility and other physical–chemical properties. There have been few direct field measurements of such fluxes due to the challenges associated with making fast-response measurements of highly soluble trace gases at very low ambient levels. In this study, we report direct eddy covariance air–sea flux measurements of SO2, sensible heat, water vapor, and momentum. The measurements were made over shallow coastal waters from the Scripps Pier, La Jolla, CA, using negative ion chemical ionization mass spectrometry as the SO2 sensor. The observed transfer velocities for SO2, sensible heat, water vapor, and momentum and their wind speed dependences indicate that SO2 fluxes can be reliably measured using this approach. As expected, the transfer velocities for SO2, sensible heat, and water vapor are lower than that for momentum, demonstrating the contribution of molecular diffusion to the overall air-side resistance to gas transfer. Furthermore, transfer velocities of SO2 were lower than those of sensible heat and water vapor when observed simultaneously. This result is attributed to diffusive resistance in the interfacial layer of the air–sea interface.
This work presents an overview of a unique set of surface ocean dimethylsulfide (DMS) measurements from four shipboard field campaigns conducted during the North Atlantic Aerosol and Marine Ecosystem Study (NAAMES) project. Variations in surface seawater DMS are discussed in relation to biological and physical observations. Results are considered at a range of timescales (seasons to days) and spatial scales (regional to sub-mesoscale). Elevated DMS concentrations are generally associated with greater biological productivity, although chlorophyll a (Chl) only explains a small fraction of the DMS variability (15%). Physical factors that determine the location of oceanic temperature fronts and depth of vertical mixing have an important influence on seawater DMS concentrations during all seasons. The interplay of biomass and physics influences DMS concentrations at regional/seasonal scales and at smaller spatial and shorter temporal scales. Seawater DMS measurements are compared with the global seawater DMS climatology and predictions made using a recently published algorithm and by a neural network model. The climatology is successful at capturing the seasonal progression in average seawater DMS, but does not reproduce the shorter spatial/temporal scale variability. The input terms common to the algorithm and neural network approaches are biological (Chl) and physical (mixed layer depth, photosynthetically active radiation, seawater temperature). Both models predict the seasonal North Atlantic average seawater DMS trends better than the climatology. However, DMS concentrations tend to be under-predicted and the episodic occurrence of higher DMS concentrations is poorly predicted. The choice of climatological seawater DMS product makes a substantial impact on the estimated DMS flux into the North Atlantic atmosphere. These results suggest that additional input terms are needed to improve the predictive capability of current state-of-the-art approaches to estimating seawater DMS.
<p>Surface ocean dimethylsulfide (DMS) was measured during four shipboard field campaigns conducted during the North Atlantic Aerosol and Marine Ecosystem Study (NAAMES). &#160;Variations in surface seawater DMS are discussed in relation to biological and physical observations. The interplay of biomass and physics influences DMS concentrations at regional/seasonal scales and at smaller spatial and shorter temporal scales. Observations are compared with the best-available climatological predictions of seawater DMS, including output from an empirical algorithm and a neural network model. The input terms common to the algorithm and neural network approaches are biological (chlorophyll) and physical (mixed layer depth, photosynthetically active radiation, seawater temperature). DMS concentrations tend to be under-predicted and the episodic occurrence of higher DMS concentrations is poorly predicted. The choice of climatological seawater DMS product makes a substantial impact on the estimated DMS flux into the North Atlantic atmosphere. These results suggest that additional input terms are needed to improve the predictive capability of current state-of-the-art approaches to estimating seawater DMS.</p>
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