Biomass burning is a major global source of atmospheric ammonia (NH3), significantly influencing air quality, aerosol formation, and nitrogen cycling. Nitrogen isotope composition (delta 15N) of NH3 has been proposed as a powerful tool for source apportionment, yet values for several emission sources remain poorly constrained. This study presents the first field-based delta 15N of total reduced inorganic nitrogen (NH x = NH3 + pNH4) measurements from fresh and aged biomass-burning plumes, collected during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign in the western United States during summer 2019. The NH x concentrations were strongly correlated with carbon monoxide (CO) and fine particulate matter (PM2.5), reflecting elevated emissions during smoldering conditions. The delta 15N(NH x ) ranged from -9.1 parts per thousand to 2.1 parts per thousand (x +/- sigma: -3.3 +/- 2.9 parts per thousand; n = 16). Using a Keeling plot approach, we derived a representative biomass-burning delta 15N(NH3) value of -4.7 +/- 1.3 parts per thousand, that integrates measurements across the sampled biomass burning events, while also accounting for background NH x influences. This field-based isotopic signature is clearly distinct from agricultural and vehicular sources and substantially lower than the +12 parts per thousand value commonly assumed for biomass burning in delta 15N-based source apportionment studies. Overall, this work improves our ability to track NH3 emissions using novel isotopic constraints. Field-based nitrogen isotope measurements of ammonia emissions from biomass burning reveal distinct isotopic signatures, enabling improved source apportionment and nitrogen cycling insights.

Biomass burning (BB) is a primary source of atmospheric chemistry reactants, aerosols, and greenhouse gases. Smoke plumes have air quality impacts local to the fire itself and regionally via long distance transport. Open burning of agriculture fields in Southeast Asia leads to frequent seasonal occurrences of regional BB-induced smoke haze and long-range transport of BB particles via the northeast monsoon. The Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) campaign visited several areas including the Philippines, South Korea, Thailand, and Taiwan during a time of agricultural burning. This campaign consisted of airborne measurements on the NASA DC-8 aircraft aimed to validate observations from South Korea's Geostationary Environment Monitoring Spectrometer (GEMS) and to address local air quality challenges. We developed a method that used a combination of BB markers to identify ASIA-AQ DC-8 data influenced by BB and flag them for further analysis. Specifically, we used rolling slope enhancement ratios of CO/CO2 and CH4/CO along with mixing ratios of CH3CN, HCN, and CO, and particle scattering coefficient measurements. The flag was triggered when a combination of these variables exceeded a flight specific threshold. We found varying levels of BB-influence in the areas studied, with data flagged for BB being < 1 % for the Philippines and Korea, and < 2 % for Taiwan, but 19 % for Thailand. Our method for flagging ASIA-AQ BB-affected data can be used to focus additional analyses of the ASIA-AQ campaign such as pairing with back trajectories, satellite hotspot products, and microphysical aerosol characteristics.

The NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) experiment was a multi-agency, inter-disciplinary research effort to: (a) obtain detailed measurements of trace gas and aerosol emissions from wildfires and prescribed fires using aircraft, satellites and ground-based instruments, (b) make extensive suborbital remote sensing measurements of fire dynamics, (c) assess local, regional, and global modeling of fires, and (d) strengthen connections to observables on the ground such as fuels and fuel consumption and satellite products such as burned area and fire radiative power. From Boise, ID western wildfires were studied with the NASA DC-8 and two NOAA Twin Otter aircraft. The high-altitude NASA ER-2 was deployed from Palmdale, CA to observe some of these fires in conjunction with satellite overpasses and the other aircraft. Further research was conducted on three mobile laboratories and ground sites, and 17 different modeling forecast and analyses products for fire, fuels and air quality and climate implications. From Salina, KS the DC-8 investigated 87 smaller fires in the Southeast with remote and in-situ data collection. Sampling by all platforms was designed to measure emissions of trace gases and aerosols with multiple transects to capture the chemical transformation of these emissions and perform remote sensing observations of fire and smoke plumes under day and night conditions. The emissions were linked to fuels consumed and fire radiative power using orbital and suborbital remote sensing observations collected during overflights of the fires and smoke plumes and ground sampling of fuels. Plain Language Summary The NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) experiment was aimed at understanding how fuel and fire conditions at the point of emission influence the chemistry of smoke, what conditions and processes control the rise of smoke plumes, what happens to smoke as it is distributed in the atmosphere, and how chemical transformation of smoke impacts air quality, weather, and climate downwind. Lessons learned from FIREX-AQ will also be used to assess and improve the effectiveness of satellites for estimating the emissions from wildfires and prescribed burns and to reduce uncertainties associated with modeling and forecasting of smoke. Here we present an overview of the FIREX-AQ effort, its motivation and design, with detailed descriptions of the measurements and analyses carried out, their connections to FIREX-AQ science goals, and the early findings of this exceptionally broad effort to understand fire and its many impacts on the atmosphere.

. High levels of fine particulate matter (PM 2.5 ) pollution in East Asia often exceed local air quality

Coastal areas are some of the most densely populated and economically important regions in the world. As such, protecting the health of the human population and ecosystems at the coastal interface and understanding the impacts of environmental stressors such as air pollutants provides wide-ranging benefits. Air quality (AQ) processes within coastal regions have been studied using ground and space-based platforms, with intensive field campaigns focused on addressing key science questions that are typically partitioned into either direct atmospheric effects (e.g., anthropogenic emissions creating air pollution) or indirect processes and feedback loops (e.g., terrestrial/marine biogenic processes modifying atmospheric properties). The atmospheric planetary boundary layer (PBL) and its depth (or height) connect land, air, and the water surface via many pathways, especially with transport and exchange processes tied to the complexities of the coastal interface. We still cannot accurately characterize-through field, aircraft, or space-based observations-the spatial and temporal PBL variability and processes within the PBL that couple together coastal dynamics and air quality. Several upcoming geostationary and polar-orbiting satellite missions are likely to make significant progress in characterizing these air/land/water interactions over the next decade. Here, we present a framework of the current understanding of the PBL's role in coastal regions, primarily regarding air quality and atmospheric deposition, to motivate future concerted efforts from ground- and space-based platforms to achieve a holistic understanding of the coastal interface.

The NASA North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) ship and aircraft field campaign deployed to the western subarctic Atlantic between the years 2015 and 2018. One of the primary goals of NAAMES is to improve the understanding of aerosol–cloud interaction (ACI) over the Atlantic Ocean under different seasonal regimes. ACIs currently represent the largest source of uncertainty in global climate models. During three NAAMES field campaigns (NAAMES-1 in November 2015, NAAMES-2 in May 2016, and NAAMES-3 in September 2017), multiple 10 h science flights were conducted using the NASA C-130 aircraft to measure marine boundary layer aerosol and cloud properties. The standard flight pattern includes vertical spirals where the C-130 transitioned from high altitude to low altitude (and vice versa), collecting in situ measurements of aerosols, trace gases, clouds, and meteorological parameters as a function of altitude. We examine the data collected from 37 spirals during the three NAAMES field campaigns, and we present a comprehensive characterization of the vertical profiles of aerosol properties under different synoptic conditions and aerosol regimes. The vertical distribution of submicron aerosol particles exhibited strong seasonal variation, as well as elevated intra-seasonal variability depending on emission sources and aerosol processes in the atmospheric column. Pristine marine conditions and new particle formation were prevalent in the wintertime (NAAMES-1) due to low biogenic emissions from the surface ocean and reduced continental influence. Higher concentrations of submicron aerosol particles were observed in the spring (NAAMES-2) due to strong phytoplankton activity and the arrival of long-range-transported continental plumes in the free troposphere with subsequent entrainment into the marine boundary layer. Biomass burning from boreal wildfires was the main source of aerosol particles in the region during the late summer (NAAMES-3) in both the marine boundary layer and free troposphere.

In-situ marine cloud droplet number concentrations (CDNCs), cloud condensation nuclei (CCN), and CCN proxies, based on particle sizes and optical properties, are accumulated from seven field campaigns: ACTIVATE; NAAMES; CAMP2EX; ORACLES; SOCRATES; MARCUS; and CAPRICORN2. Each campaign involves aircraft measurements, ship-based measurements, or both. Measurements collected over the North and Central Atlantic, Indo-Pacific, and Southern Oceans, represent a range of clean to polluted conditions in various climate regimes. With the extensive range of environmental conditions sampled, this data collection is ideal for testing satellite remote detection methods of CDNC and CCN in marine environments. Remote measurement methods are vital to expanding the available data in these difficult-to-reach regions of the Earth and improving our understanding of aerosol-cloud interactions. The data collection includes particle composition and continental tracers to identify potential contributing CCN sources. Several of these campaigns include High Spectral Resolution Lidar (HSRL) and polarimetric imaging measurements and retrievals that will be the basis for the next generation of space-based remote sensors and, thus, can be utilized as satellite surrogates.

Abstract. High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. In the surface level, the model underestimates campaign average sulfate aerosol by −64 % but overestimates nitrate aerosol by 36 %. The largest underestimate in sulfate occurs during the pollution event in conditions of high relative humidity, where models typically struggle to generate the high concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100 % against aircraft observations. We hypothesize that this is due to a missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66 % to 54 %. Locally-produced sulfate increased from 1 % to 46 % of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements.

. High levels of fine particulate matter (PM 2.5 ) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme 30 pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM 2.5 . Atmospheric models often have difficulty simulating PM 2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM 2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. In the surface level, the model underestimates campaign average sulfate aerosol 35 by -64% but overestimates nitrate aerosol by 36%. The largest underestimate in sulfate occurs during the pollution event in conditions of high relative humidity, where models typically struggle to generate the high concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100% against aircraft observations. We hypothesize that this is due to a missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH 3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO 2 hydrolysis in 45 the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N 2 O 5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, 50 mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM 2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO 2 is added to the model which previously only considered aqueous production of sulfate from SO 2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO 2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM 2.5 . During the haze pollution event, the inclusion of heterogeneous aerosol uptake of the emissions inventory for key emitted species in the nested East Asia domain for May 2016. Model dry deposition for gas-phase species is based on the resistance-in-series scheme from Wesely (1989) as implemented by Wang et al. (1998), where species deposition is limited by aerodynamic resistance, quasi-laminar layer resistance, and canopy or surface resistance. Species with low surface resistance, such as HNO 3 , are limited in their deposition velocity by aerodynamic resistance only. Aerosol deposition is from Zhang et al. (2001). The original model wet deposition scheme is described by Liu et al. (2001) for water-soluble aerosols and Amos et al. (2012) for gases. Wet deposition includes scavenging from moist convective updrafts and rainout and washout from precipitation. We include the revised wet deposition scheme of Luo et al. (2019) that uses an empirical washout rate for nitric acid two orders of magnitude higher than the previous value and replaces the standard constant value for in-cloud condensation water content with the value calculated by the meteorological fields (GEOS-FP). GEOS-Chem uses a non-local boundary layer mixing scheme (Holtslag and Boville, 1993; Lin and McElroy, 2010) where mixing is calculated explicitly from meteorological variables provided by GEOS-FP (i.e. 160 sensible and latent heat flux, temperature, friction velocity). The mixing height is restricted from dropping below a minimum mechanical mixing depth, defined as a function of local friction velocity (Lin and McElroy, 2010). (SALA) (SALC) (Alexander and in four size the first bin and 38% of the second bin are included in PM 2.5 . The recommended definition of dry PM 2.5 is given by Eq 1.

Brown carbon (BrC) in aerosol particles and cloud droplets can contribute to climate warming by absorbing solar radiation in the visible region of the solar spectrum. Large uncertainties remain in our parameterization of this warming, in part due to a lack of knowledge about atmospheric lifetimes for the chromophores (the light absorbing structures in BrC molecules). An important removal pathway includes chemical transformations that fragment the chromophore, thus removing its ability to absorb visible light. However, the photochemical loss rates measured in the laboratory do not generally match what is observed in ambient measurements. There are also different amounts of photo-resistant BrC, which is a fraction of the mixture that does not rapidly bleach. An important BrC source in the atmosphere is biomass burning and the overall photochemical decay rates for these emissions are important to quantify to improve our parameterizations of their radiative effects. Here we show results for laboratory studies of FIREX filter samples probing the role of water vapor in photolysis of aerosol particles irradiated on a filter. Kinetic analysis of photo-bleaching in aqueous solutions demonstrates that an intermediate photolysis rate should be included to improve predictions for BrC lifetimes in the atmosphere.

Atmospheric marine particle concentrations impact cloud properties, which strongly impact the amount of solar radiation reflected back into space or absorbed by the ocean surface. While satellites can provide a snapshot of current conditions at the overpass time, models are necessary to simulate temporal variations in both particle and cloud properties. However, poor model accuracy limits the reliability with which these tools can be used to predict future climate. Here, we leverage the comprehensive ocean ecosystem and atmospheric aerosol–cloud dataset obtained during the third deployment of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES3). Airborne and ship-based measurements were collected in and around a cold-air outbreak during a 3 d (where d stands for day) intensive operations period from 17–19 September 2017. Cold-air outbreaks are of keen interest for model validation because they are challenging to accurately simulate, which is due, in part, to the numerous feedbacks and sub-grid-scale processes that influence aerosol and cloud evolution. The NAAMES observations are particularly valuable because the flight plans were tailored to lie along Lagrangian trajectories, making it possible to spatiotemporally connect upwind and downwind measurements with the state-of-the-art FLEXible PARTicle (FLEXPART) Lagrangian particle dispersion model and then calculate a rate of change in particle properties. Initial aerosol conditions spanning an east–west, closed-cell-to-clear-air transition region of the cold-air outbreak indicate similar particle concentrations and properties. However, despite the similarities in the aerosol fields, the cloud properties downwind of each region evolved quite differently. One trajectory carried particles through a cold-air outbreak, resulting in a decrease in accumulation mode particle concentration (−42 %) and cloud droplet concentrations, while the other remained outside of the cold-air outbreak and experienced an increase in accumulation mode particle concentrations (+62 %). The variable meteorological conditions between these two adjacent trajectories result from differences in the local sea surface temperature in the Labrador Current and surrounding waters, altering the stability of the marine atmospheric boundary layer. Further comparisons of historical satellite observations indicate that the observed pattern occurs annually in the region, making it an ideal location for future airborne Lagrangian studies tracking the evolution of aerosols and clouds over time under cold-air outbreak conditions.

This study reports measurements of size-resolved aerosol composition at a site in Incheon along with other aerosol characteristics for contrast between Incheon (coastal) and Seoul (inland), South Korea, during a transboundary pollution event during the early part of an intensive sampling period between 4 and 11 March 2019. Anthropogenic emissions were dominant in the boundary layer over the study region between 4 and 6 March, with much smaller contributions from dust, smoke, and sea salt. The meteorology of this period (shallow boundary layer, enhanced humidity, and low temperature) promoted local heterogeneous formation of secondary inorganic and organic species, including high nitrate (NO3-) relative to sulfate (SO42-). Seoul exhibited higher PM2.5 levels than Incheon, likely due to local emissions. The following findings point to secondary aerosol formation and growth sensitivity to water vapor during this pollution event: (i) significant concentrations of individual inorganic and organic acids in the supermicrometer range relative to their full size range (∼40 %) at higher humidity; (ii) high correlation (r=0.95) between oxalate and SO42-, a marker of secondary aqueous production of oxalate; (iii) increased sulfur and nitrogen oxidation ratios as a function of humidity; and (iv) matching composition apportionment (for soluble ions) between the PM1 and PM2.5−1 size fractions. The last finding confirms that PM1 aerosol composition measurements fully capture PM2.5 composition apportionment (for soluble ions) during haze events and may therefore be reliably applied in modeling studies of such events over the full PM2.5 size range. However, the differences evident in the periods following the haze event imply that under other atmospheric conditions PM1 composition measurements will not fully reflect the apportionment of PM2.5 aerosols. The study period was marked by relatively low temperatures that made NO3- the most abundant species detected, pointing to the sensitivity of PM2.5 levels and composition as a function of season during such transboundary events. For instance, other such events in previous studies exhibited more comparable levels between SO42- and NO3- coincident with higher temperatures than the current study. This dataset can contribute to future evaluation of model PM2.5 composition to better support regulatory efforts to control PM2.5 precursors.

Abstract. Cloud droplet composition is a key observable quantity that can aid understanding of how aerosols and clouds interact. As part of the Clouds, Aerosols and Monsoon Processes – Philippines Experiment (CAMP2Ex), three case studies were analyzed involving collocated airborne sampling of relevant clear and cloudy airmasses associated with maritime warm convection. Two of the cases represented a polluted marine background, with signatures of transported East Asian regional pollution, aged over water for several days, while the third case comprised a major smoke transport event from Kalimantan fires. Sea salt was a dominant component of cloud droplet composition, in spite of fine particulate enhancement from regional anthropogenic sources. Furthermore, the proportion of sea salt was enhanced relative to sulfate in rainwater and may indicate both a propensity for sea salt to aid warm rain production and an increased collection efficiency of large sea salt particles by rain in subsaturated environments. Amongst cases, as precipitation became more significant, so too did the variability in the sea salt to (non-sea salt) sulfate ratio. Across cases, nitrate and ammonium were fractionally greater in cloud water than fine-mode aerosol particles; however, a strong co-variability in cloud water nitrate and sea salt was suggestive of prior uptake of nitrate on large salt particles. A mass-based closure analysis of non-sea salt sulfate compared the cloud water air-equivalent mass concentration to the concentration of aerosol particles serving as cloud condensation nuclei for droplet activation. While sulfate found in cloud was generally constrained by the sub-cloud aerosol concentration, there was significant intra-cloud variability that was attributed to entrainment – causing evaporation of sulfate containing droplets – and losses due to precipitation. In addition, precipitation tended to promote mesoscale variability in the sub-cloud aerosol through a combination of removal, convective downdrafts, and through dynamically-driven convergence. Physical mechanisms exerted such strong control over the cloud water compositional budget that it was not possible to isolate any signature of chemical production/loss using in-cloud observations. The cloud-free environment surrounding the non-precipitating, smoke case indicated sulfate enhancement compared to convective mixing quantified by a stable gas tracer; however, this was not observed in the cloud water (either through use of ratios or the mass closure) perhaps implying that the warm convective cloud time scale was too short for chemical production to be a leading-order budgetary term. Closure of other species was truncated by incomplete characterization of coarse aerosol (e.g., it was found that only 10-50% of sea salt mass found in cloud was captured during clear air sampling) and unmeasured gas phase abundances affecting closure of semi-volatile aerosol species (e.g., ammonium, nitrate and organic aerosols) and soluble volatile organic compound contributions to total organic carbon in cloud water.

Cloud droplet chemical composition is a key observable property that can aid understanding of how aerosols and clouds interact. As part of the Clouds, Aerosols and Monsoon Processes – Philippines Experiment (CAMP2Ex), three case studies were analyzed involving collocated airborne sampling of relevant clear and cloudy air masses associated with maritime warm convection. Two of the cases represented a polluted marine background, with signatures of transported East Asian regional pollution, aged over water for several days, while the third case comprised a major smoke transport event from Kalimantan fires. Sea salt was a dominant component of cloud droplet composition, in spite of fine particulate enhancement from regional anthropogenic sources. Furthermore, the proportion of sea salt was enhanced relative to sulfate in rainwater and may indicate both a propensity for sea salt to aid warm rain production and an increased collection efficiency of large sea salt particles by rain in subsaturated environments. Amongst cases, as precipitation became more significant, so too did the variability in the sea salt to (non-sea salt) sulfate ratio. Across cases, nitrate and ammonium were fractionally greater in cloud water than fine-mode aerosol particles; however, a strong covariability in cloud water nitrate and sea salt was suggestive of prior uptake of nitrate on large salt particles. A mass-based closure analysis of non-sea salt sulfate compared the cloud water air-equivalent mass concentration to the concentration of aerosol particles serving as cloud condensation nuclei for droplet activation. While sulfate found in cloud was generally constrained by the sub-cloud aerosol concentration, there was significant intra-cloud variability that was attributed to entrainment – causing evaporation of sulfate-containing droplets – and losses due to precipitation. In addition, precipitation tended to promote mesoscale variability in the sub-cloud aerosol through a combination of removal, convective downdrafts, and dynamically driven convergence. Physical mechanisms exerted such strong control over the cloud water compositional budget that it was not possible to isolate any signature of chemical production/loss using in-cloud observations. The cloud-free environment surrounding the non-precipitating smoke case indicated sulfate enhancement compared to convective mixing quantified by a stable gas tracer; however, this was not observed in the cloud water (either through use of ratios or the mass closure), perhaps implying that the warm convective cloud timescale was too short for chemical production to be a leading-order budgetary term and because precursors had already been predominantly exhausted. Closure of other species was truncated by incomplete characterization of coarse aerosol (e.g., it was found that only 10 %–50 % of sea salt mass found in cloud was captured during clear-air sampling) and unmeasured gas-phase abundances affecting closure of semi-volatile aerosol species (e.g., ammonium, nitrate and organic) and soluble volatile organic compound contributions to total organic carbon in cloud water.

Ångström exponents (α) allow reconstruction of aerosol optical spectra over a broad range of wavelengths from measurements at two or more wavelengths. Hyperspectral measurements of atmospheric aerosols provide opportunities to probe measured spectra for information inaccessible from only a few wavelengths. Four sets of hyperspectral in situ aerosol optical coefficients (aerosol‐phase total extinction, σext, and absorption, σabs; liquid‐phase soluble absorption from methanol, σMeOH‐abs, and water, σDI‐abs, extracts) were measured from biomass burning aerosols (BBAs). Hyperspectral single scattering albedo (ω), calculated from σext and σabs, provide spectral resolution over a wide spectral range rare for this optical parameter. Observed spectral shifts between σabs and σMeOH‐abs/σDI‐abs argue in favor of measuring σabs rather than reconstructing it from liquid extracts. Logarithmically transformed spectra exhibited curvature better fit by second‐order polynomials than linear α. Mapping second order fit coefficients (a1, a2) revealed samples from a given fire tended to cluster together, that is, aerosol spectra from a given fire were similar to each other and somewhat distinct from others. Separation in (a1, a2) space for spectra with the same α suggest additional information in second‐order parameterization absent from the linear fit. Spectral features found in the fit residuals indicate more information in the measured spectra than captured by the fits. Above‐detection σMeOH‐abs at 0.7 μm suggests assuming all absorption at long visible wavelengths is BC to partition absorption between BC and brown carbon (BrC) overestimates BC and underestimates BrC across the spectral range. Hyperspectral measurements may eventually discriminate BBA among fires in different ecosystems under variable conditions.

Abstract. Atmospheric marine particle concentrations impact cloud properties, which strongly impact the amount of solar radiation reflected back into space or absorbed by the ocean surface. While satellites can provide a snapshot of current conditions at the overpass time, models are necessary to simulate temporal variations in both particle and cloud properties. However, poor model accuracy limits the reliability with which these tools can be used to predict future climate. Here, we leverage the comprehensive ocean ecosystem and atmospheric aerosol-cloud data set obtained during the third deployment of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES3). Airborne and ship-based measurements were collected in and around a cold-air outbreak during a three-day intensive operations period from September 17–19, 2017. Cold-air outbreaks are of keen interest for model validation because they are challenging to accurately simulate, which is due, in part, to the numerous feedbacks and sub-grid scale processes that influence aerosol and cloud evolution. The NAAMES observations are particularly valuable because the flight plans were tailored to lie along Lagrangian trajectories, making it possible to spatiotemporally connect upwind and downwind measurements with the state-of-the-art FLEXible PARTicle (FLEXPART) Lagrangian particle dispersion model and then calculate a rate of change in particle properties. Initial aerosol conditions spanning an east-west, closed-cell cloudy to clear air transition region of the cold-air outbreak indicate similar particle concentrations and properties. However, despite the similarities in the aerosol fields, the cloud properties downwind of each region evolved quite differently. One trajectory carried particles through a cold-air outbreak, resulting in a decrease in accumulation mode particle concentration (−42 %) and cloud droplet concentrations, while the other remained outside of the cold-air outbreak and experienced an increase in accumulation mode particle concentrations (+62 %). The variable meteorological conditions between these two adjacent trajectories result from differences in the local sea surface temperature altering stability of the marine atmospheric boundary layer because of the location of the Labrador Current. Further comparisons of historical satellite observations indicate that the observed pattern occurs annually in the region, making it an ideal location for future airborne Lagrangian studies tracking the evolution of aerosols and clouds over time under cold air outbreak conditions.

This two-part study explores hyperspectral (300–700 nm) aerosol optical measurements obtained from in situ sampling methods employed during the May–June 2016 Korea–United States Ocean Color (KORUS-OC) cruise conducted in concert with the broader air quality campaign (KORUS-AQ). Part 1 focused on the hyperspectral measurement of extinction coefficients (σext) using the recently developed in situ Spectral Aerosol Extinction (SpEx) instrument and showed that second-order polynomials provided a better fit to the measured spectra than power law fits. Two dimensional mapping of the second-order polynomial coefficients (a1, a2) was used to explore the information content of the spectra. Part 2 expands on that work by applying a similar analytical approach to filter-based measurements of aerosol hyperspectral total absorption (σabs) and soluble absorption from filters extracted with either deionized water (σDI-abs) or methanol (σMeOH-abs). As was found for σext, second-order polynomials provided a better fit to all three absorption spectra sets. Averaging the measured σext from Part 1 over the filter sampling intervals in this work, hyperspectral single-scattering albedo (ω) was calculated. Water-soluble aerosol composition from the DI extracts was used to examine relationships with the various measured optical properties. In particular, both σDI-abs(365 nm) and σMeOH-abs(365 nm) were found to be best correlated with oxalate (C2O42-), but elevated soluble absorption was found from two chemically and optically distinct populations of aerosols. The more photochemically aged aerosols of those two groups exhibited partial spectra (i.e., the longer wavelengths of the spectral range were below detection) while the less-aged aerosol of the other group exhibited complete spectra across the wavelength range. The chromophores of these groups may have derived from different sources and/or atmospheric processes, such that photochemical age may have been only one factor contributing to the differences in the observed spectra. The differences in the spectral properties of these groups was evident in (a1, a2) maps. The results of the two-dimensional mapping shown in Parts 1 and 2 suggest that this spectral characterization may offer new methods to relate in situ aerosol optical properties to their chemical and microphysical characteristics. However, a key finding of this work is that mathematical functions (whether power laws or second-order polynomials) extrapolated from a few wavelengths or a subrange of wavelengths fail to reproduce the measured spectra over the full 300–700 nm wavelength range. Further, the σabs and ω spectra exhibited distinctive spectral features across the UV and visible wavelength range that simple functions and extrapolations cannot reproduce. These results show that in situ hyperspectral measurements provide valuable new data that can be probed for additional information relating in situ aerosol optical properties to the underlying physicochemical properties of ambient aerosols. It is anticipated that future studies examining in situ aerosol hyperspectral properties will not only improve our ability to use optical data to characterize aerosol physicochemical properties, but that such in situ tools will be needed to validate hyperspectral remote sensors planned for space-based observing platforms.

In situ observations of spectrally resolved aerosol extinction coefficients (300–700 nm at ∼ 0.8 nm resolution) from the May–June 2016 Korea–United States Ocean Color (KORUS-OC) oceanographic field campaign are reported. Measurements were made with the custom-built Spectral Aerosol Extinction (SpEx) instrument that previously has been characterized only using laboratory-generated aerosols of known size and composition. Here, the performance of SpEx under realistic operating conditions in the field was assessed by comparison to extinction coefficients derived from commercial instruments that measured scattering and filter-based absorption coefficients at three discrete visible wavelengths. Good agreement was found between these two sets of extinction coefficients with slopes near unity for all three wavelengths within the SpEx measurement error (± 5 Mm−1). The meteorological conditions encountered during the cruise fostered diverse ambient aerosol populations with varying sizes and composition at concentrations spanning 2 orders of magnitude. The sampling inlet had a 50 % size cut of 1.3 µm diameter particles such that the in situ aerosol sampling suite deployed aboard ship measured fine-mode aerosols only. The extensive hyperspectral extinction data set acquired revealed that nearly all measured spectra exhibited curvature in logarithmic space, such that Ångström exponent (α) power law fits could lead to large errors compared to measured values. This problem was particularly acute for α values calculated over only visible wavelengths and then extrapolated to the UV, highlighting the need for measurements in this wavelength range. Second-order polynomial fits to the logarithmically transformed data provided a much better fit to the measured spectra than the linear fits of power laws. Building on previous studies that used total column aerosol optical depth observations to examine the information content of spectral curvature, the relationship between α and the second-order polynomial fit coefficients (a1 and a2) was found to depend on the wavelength range of the spectral measurement such that any given α maps into a line in (a1, a2) coefficient space with a slope of −2LN(λch), where λch is defined as the single wavelength that characterizes the wavelength range of the measured spectrum (i.e., the “characteristic wavelength”). Since the curvature coefficient values depend on λch, it must be taken into account when comparing values from spectra obtained from measurement techniques with different λch. Previously published work has shown that different bimodal size distributions of aerosols can exhibit the same α yet have differing spectral curvature with different (a1, a2). This implies that (a1, a2) contain more information about size distributions than α alone. Aerosol size distributions were not measured during KORUS-OC, and the data reported here were limited to the fine fraction, but the (a1, a2) maps obtained from the SpEx data set are consistent with the expectation that (a1, a2) may contain more information than α – a result that will be explored further with future SpEx and size distribution data sets.