Abstract. Contrails or condensation trails are a major contributor to aviation-induced cloudiness, which represents a significant, yet highly uncertain, component of aviation's environmental impact. The reliable detection and characterization of contrails has become increasingly important for quantifying their radiative forcing and developing mitigation strategies. However, contrail detection and prediction remains challenging due to their variable optical properties, lack of accuracy in humidity, temperature and pressure sensor measurements, as well as in weather prediction. This paper investigates the use of machine vision on board aircraft to inform contrail formation and classification in real time. The focus of this work is the comparison of two major airborne measurement campaigns conducted by NASA, industry, and international partners: the 2018 NASA – DLR ECLIF II/ND-MAX and the 2023 NASA – Boeing ecoDemonstrator flight tests. The atmospheric data from the campaigns are used with the Schmidt-Appleman criterion to identify periods of contrail formation. For the ND-MAX dataset classification accuracies of 94.0 %, 87.1 %, and 81.5 % were obtained for contrail absence, short-lived and persistent categories, respectively. For the ecoDemonstrator dataset the corresponding accuracies were 90.4 %, 89.5 %, and 93.3 %. Comparison between the two campaigns reveals that camera placement affects the classification performance; longer visible contrail segments improve detection for the absence and short-lived categories while reduced airframe intrusion in the camera's field of view improves persistent contrail classification. Based on these findings, some recommendations for camera placement on flights are provided. The approach requires only an onboard camera as additional instrumentation, making it a cost-effective and scalable tool that may complement existing contrail monitoring and mitigation strategies.

Abstract. The NASA airborne Arctic Radiation-Cloud-aerosol-Surface-Interaction Experiment (ARCSIX) collected a unique data set providing a near-simultaneous characterization of radiative fluxes, surface, cloud, and aerosol particle properties to address science questions on the surface radiation budget, the processes governing the cloud lifecycle, atmospheric composition, and the interactions between the surface and atmosphere. The overarching goal of ARCSIX was to quantify the contributions of surface, clouds, aerosol particles, and precipitation to summer sea ice melt. ARCSIX consisted of two deployments in 2024 (Spring: 2024-05-28 through 2024-06-13 and Summer: 2024-07-25 through 2024-08-15) to capture pre- and post-melt conditions. ARCSIX provided coordinated remote sensing and in situ sampling using three aircraft in a high-flyer/low-flyer configuration. The NASA G-III served as the high-flying remote sensing platform with two lower flying in situ and near-target remote sensor observing platforms, NASA P-3B and SPEC Inc. Learjet. ARCSIX data are well-suited to improve satellite remote sensing capabilities in the Arctic. ARCSIX included an array of sea ice mass balance buoys deployed in the Lincoln Sea that were regularly overflown during the campaign. ARCSIX research flights spanned the Baffin Bay, Lincoln Sea, west and north of the Canadian Archipelago, and the Greenland north and northeast coasts. During the spring deployment, 19 research flights took place covering 114 flight hours: 10 flights and 68 hours by the P-3B and nine flights and 46 hours by the G-III. During summer, 24 research flights covered 136 flight hours: nine flights and 75 hours by the P-3B, five flights and 26 hours by the G-III, and 10 flights and 35 hours by the Learjet. A total of 13 coordinated flights with 2+ aircraft were carried out. This paper describes the ARCSIX flight strategy, instrumentation, and data set access, and usage details. ARCSIX data are publicly available at https://doi.org/10.5067/SUBORBITAL/ARCSIX/DATA001.

Separating contributions of the fine and coarse modes is important for characterizing aerosols and assessing their impacts. This work develops retrievals of fine mode fraction (FMF) from lidar observables for the marine boundary layer (MBL) using data collected during the ACTIVATE field campaign. First, we calculate multiwavelength backscatter and extinction and derived metrics for spherical particles derived from measured size distributions (combining in situ aerosol and cloud probes) and hygroscopicity estimates. The calculations show reasonable skill when compared to airborne High Spectral Resolution Lidar-generation 2 (HSRL-2) retrievals, displaying low biases and explaining up to 87% of the variability in backscattering. While slopes are generally close to 1:1 for lidar ratios and Angstrom exponents (AEs), the variability within HSRL-2 data is only well captured for lidar ratios (50%-67%). Having established that the calculated optical properties are representative of remotely sensed ones in the marine environment, they are used together with in situ aircraft particle size data to train multilinear regression models to estimate FMF proxies (extinction FMF, PM1/PM10 and PM2.5/PM10 ratios). When tested with HSRL-2 observations as inputs, these models can represent up to 67%-78% of the variability of the observed FMF proxies with biases at high FMFs that depend on the accuracy of the coarse mode aerosol size measurements. The regression retrievals are tested for lidar transects and show expected gradients due to continental influence on the MBL and differential hygroscopicity of fine versus coarse mode aerosol with height. These results are encouraging for their application for various lidar systems.

Understanding the vertical distribution of cloud condensation nuclei (CCN) concentrations is crucial for reducing uncertainty associated with aerosol–cloud interactions (ACIs) and their effective radiative forcing. Many studies take advantage of widely available remote sensing observations to develop proxies, parameterizations, and relationships between CCN concentration and aerosol optical properties (AOPs). Such methods generally provide a good constraint for CCN concentration, but many uncertainties and limitations exist, generally related to high relative humidity (RH), environments with internal or external mixtures of several different aerosol types, and differences in parts of the aerosol size distribution relevant to both CCN and AOPs. In this study, we use in situ observations of the aerosol size distribution and chemical composition in a recent airborne field campaign to inform theoretical calculations of CCN concentration (CCNtheory) and aerosol backscatter at 532 nm (BSCtheory) with the purpose of understanding the dominant governing factors of the CCNtheory–BSCtheory relationship. Estimates from random forest models indicate that, for smoke, marine, and urban aerosols, the aerosol size distribution, as parameterized by the effective radius (Reff), is the most important predictor of the CCNtheory–BSCtheory relationship. We further investigate how Reff impacts CCNtheory : BSCtheory and find an exponential relationship between the parameters. We find that modeling CCNtheory : BSCtheory using this exponential Reff relationship can explain about 68 %–79 % of the variance in the CCNtheory–BSCtheory relationship. These findings suggest that including information about aerosol size is critical for future studies in constraining CCN concentration from AOPs.

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.

We present direct measurements of the asymmetry parameter ( g ) from biomass burning aerosol at two wavelengths using the Laser Imaging Nephelometer. We compare the measurements with Mie theory calculations based on optically measured size distributions and with g values derived from hemispheric backscatter ( b ) measurements using both an integrating and an imaging nephelometer. During the FIREX‐AQ field mission, we measured the optical and microphysical properties of smoke plumes that had been emitted between 0.5 and 8.5 hr earlier. We find that the measured g can only be reproduced from particle size distribution measurements using a higher refractive index than is typically retrieved from remote measurements and assumed in some models. Retrievals performed using the GRASP algorithm suggest the refractive index is wavelength‐dependent with n = 1.55 ± 0.03 at λ = 660 nm and (1.63 ± 0.04) at λ = 405 nm. Using a simple radiative transfer equation, we show that the instantaneous aerosol cooling of the planet by fresh smoke is increased by 20% when evaluated using the measured g values instead of assuming n = 1.52. Besides improving model representations of radiative cooling by fresh smoke, using a more accurate aerosol optical model can improve retrievals of aerosol microphysical properties from remote sensing techniques. Better retrievals will provide a more accurate constraint on the emissions inventories used in global and regional models. This will ultimately reduce the uncertainty in radiative forcing associated with the increasing frequency and magnitude of wildfires.

Biomass burning (BB) affects air quality and climate by releasing large quantities of gaseous and particulate pollutants into the atmosphere. Photochemical processing during daylight transforms these emissions, influencing their overall environmental impact. Accurately quantifying the photochemical drivers, namely actinic flux and photolysis frequencies, is crucial to constraining this chemistry. However, the complex radiative transfer within BB plumes presents a significant challenge for both direct observations and numerical models. This study introduces an expanded version of the 1D VLIDORT-QS radiative transfer (RT) model, named VLIDORT for photochemistry (VPC). VPC is designed for photochemical and remote sensing applications, particularly in BB plumes and other complex scenarios. To validate VPC and investigate photochemical conditions within BB plumes, the model was used to simulate spatial distributions of actinic fluxes and photolysis frequencies for the Shady wildfire (Idaho, US, 2019) based on plume composition data from the NOAA/NASA FIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality) campaign. Comparison between modeling results and observations by the CAFS (charged-coupled device actinic flux spectroradiometer) yields a modeling accuracy of 10 %–20 %. Systematic biases between the model and observations are within 2 %, indicating that the uncertainties are most likely due to variability in the input data caused by the inhomogeneity of the plume as well as 3D RT effects not captured in the model. Random uncertainties are largest in the ultraviolet (UV) spectral range, where they are dominated by uncertainties in the plume particle size distribution and brown carbon (BrC) absorptive properties. The modeled actinic fluxes show a decrease from the plume top to the bottom of the plume with a strong spectral dependence caused by BrC absorption, which darkens the plume towards shorter wavelengths. In the visible (Vis) spectral range, actinic fluxes above the plume are enhanced by up to 60 %. In contrast, in the UV, actinic fluxes above the plume are not affected or even reduced by up to 10 %. Strong reductions exceeding an order of magnitude in and below the plume occur for both spectral ranges but are more pronounced in the UV.

Advancing knowledge of cloud condensation nuclei (CCN) characteristics has important consequences for weather and climate, making field observations vital. This work characterizes CCN using airborne data from the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) spanning areas from the U.S. East Coast to Bermuda between November 2020 through June 2022. CCN concentrations at the most commonly sampled supersaturation (SS; 0.37-0.43%) ranged from medians of 652 cm-3 in summer to 460 cm-3 in winter, dropping to 310 cm-3 near Bermuda in June. The median observed hygroscopicity parameter (kappa) varied from 0.19-0.21 across winter, spring, and summer and increased to 0.97 near Bermuda. Using speciated composition and number size distribution measurements, we predict CCN concentrations with those measured at SS ranging from 0.16-0.72%, revealing that the cumulative median predicted-to-observed CCN ratio was 1.08, with the best agreement in spring (1.10) and the largest discrepancies near Bermuda (0.89). CCN overpredictions were associated with biomass burning events in summer, while CCN were largely underestimated near Bermuda due to higher observed kappa than assumed for inorganics. This study provides key insights into CCN activity over the northwest Atlantic, capturing the transition from polluted to remote oceanic environments. Advancing knowledge of cloud condensation nuclei (CCN) characteristics has important consequences for weather and climate, making field observations vital.

The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) is a NASA mission to characterize aerosol–cloud interactions over the western North Atlantic Ocean (WNAO). Such characterization requires understanding of life cycle, composition, transport pathways, and distribution of aerosols over the WNAO. This study uses the GEOS-Chem model to simulate aerosol distributions and properties that are evaluated against aircraft, ground-based, and satellite observations during the winter and summer field deployments in 2020 of ACTIVATE. Transport in the boundary layer (BL) behind cold fronts was a major mechanism for the North American continental outflow of pollution to the WNAO in winter. Turbulent mixing was the main driver for the upward transport of sea salt within and ventilation out of BL in winter. The BL aerosol composition was dominated by sea salt, which increased in the summer, followed by organics and sulfate. Aircraft in situ aerosol measurements provided useful constraints on wet scavenging in GEOS-Chem. The model generally captured observed features such as continental outflow, land–ocean gradient, and mixing of anthropogenic aerosols with sea salt. Model sensitivity experiments with elevated smoke injection heights to the mid-troposphere (versus within BL) better reproduced observations of smoke aerosols from the western US wildfires over the WNAO in the summer. Model analysis suggests strong hygroscopic growth of sea salt particles and their seeding of marine BL clouds over the WNAO (< 35° N). Future modeling efforts should focus on improving parameterizations for aerosol wet scavenging, implementing realistic smoke injection heights, and applying high-resolution models that better resolve vertical transport.

There is a need to quickly convert aerosol microphysical properties into optical properties for global modeling, data assimilation, and remote sensing applications. This is generally accomplished through look-up tables (LUTs) of aerosol mass extinction coefficients (MEC), mass absorption coefficients (MAC), asymmetry parameters, normalized phase functions, etc. Unfortunately, many scientists are using outdated LUTs that are based upon measurements and computational techniques first published by Shettle and Fenn (1979) and later updated by Hess et al. (1998). Thus, the computations in common use are still largely based upon Mie theory and in situ information that has not been updated during this century.The Table of Aerosol Optics (TAO) is an open relational database (under construction) that expands upon existing LUTs by including recent measurements and new computational techniques for non-spherical particles (https://science.larc.nasa.gov/mira-wg/topics/tao/). The ‘open’ aspect of TAO is important, since the measurements and techniques of today will undoubtedly yield to different values in the future. This open architecture allows specialists to add new tables and gain exposure for their work and benefits modelers and remote sensing scientists by giving them easy access to computations that utilize the latest techniques. Quality is controlled by requiring methods to be peer-reviewed in the scientific literature.Thus far, we have computed mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at 73 wavelengths ranging from 0.25-40 µm for black carbon (BC), brown carbon (BrC), non-absorbing organic carbon, and mineral dust. For mineral dust, we use hexahedra shapes and mineral mixtures of montmorillonite, illite, hematite, and goethite. The illite volume fraction varies from 0 to 59% to capture the range of real refractive indices found in AERONET climatologies; the sum of the hematite and goethite mass fractions are ~2%. Additional mixtures will be added as appropriate.We have also computed optical properties for 22 size distributions of bare aggregated BC using the Multi-Sphere T-Matrix (MSTM) code (https://github.com/dmckwski/MSTM) at several remote sensing wavelengths. Our MSTM computations use aggregates of 20-nm spherules with particle-cluster growth. We obtained mass absorption coefficients (MACs) of 7.2-7.5 m2/g at a mid-visible wavelength (532 nm) when the BC fractal dimension was fixed at Df = 1.8 (i.e., fresh BC), consistent with values commonly recommended in literature reviews.We will present the TAO vision and example results for several aerosol types. TAO is part of the Models, In situ, and Remote sensing of Aerosols (MIRA) working group. MIRA seeks to build collaboration, consistency, and openness amongst the aerosol disciplines. We seek community feedback from aerosol scientists regarding the construction and content of TAO, especially in this early phase. Check out the MIRA webpage at https://science.larc.nasa.gov/mira-wg/ and subscribe to our mailing list at https://espo.nasa.gov/lists/listinfo/mira.Hess et al. (1998): Optical properties of aerosols and clouds: The software package OPAC, BAMS, 79, 831–844.Shettle and Fenn (1979): Tech. Rep. AFGL-TR-790214, Air Force Geophysics Laboratory, 1979.

The evolution of organic aerosol (OA) composition and aerosol size distributions within smoke plumes are uncertain due to variability in the rates of OA evaporation/condensation and coagulation within a plume. It remains unclear how the evolution varies across different parts of individual plumes. We use a large eddy simulation model coupled with aerosol‐microphysics and radiation models to simulate the Williams Flats fire sampled during the Fire Influence on Regional to Global Environments and Air Quality field campaign. At aircraft altitude, the model captures observed aerosol changes through 4 hr of aging. The model evolution of primary OA (POA), oxidized POA (OPOA), and secondary OA (SOA) shows that >90% of the SOA formation occurs before the first transect (∼40 min of aging). Lidar observations and the model show a significant amount of smoke in the planetary boundary layer (PBL) and free troposphere (FT) with the model having equal amounts of smoke in the PBL and FT. Due to faster initial dilution, PBL concentrations are more than a factor of two lower than the FT concentrations, resulting in slower coagulational growth in the PBL. A 20 K temperature decrease with height in the PBL influences faster POA evaporation near the surface, while net OA evaporation in the FT is driven by continued dilution after the first aircraft transect. Net OA condensation in the PBL after the first transect is the result of areas with higher OH concentration leading to OPOA formation. Our results motivate the need for systematic observations of the vertical gradients of aerosol size and composition within smoke plumes.

Varying anthropogenic emissions during a typical week can lead to shifts in aerosol properties, yet such signals are rarely examined in marine outflow regions. Since aerosol data from the IMPROVE network along the U.S. East Coast show weekday peaks in anthropogenically influenced aerosol species, this study leverages airborne measurements from NASA's ACTIVATE campaign (2020-2022) to investigate weekly cycles of aerosol properties over the Northwest Atlantic Ocean. Analysis focuses on winter and summer flights that sampled continental outflow along repeated transects between NASA Langley Research Center (LaRC) and two aviation waypoints (ZIBUT and OXANA). Aerosol number concentration (N) between 0.1 and 1 mu m (N 0.1-1 mu m), N CCN at 0.37-0.43% supersaturation, and aerosol surface area concentration (SA0.003-1 mu m) show midweek peaks for LaRC-OXANA and LaRC-ZIBUT, with minima on Sunday/Monday. However, the most pronounced weekly cycle for both corridors was for variables relevant to new particle formation (NPF: N 3 nm, N 3 nm-N 10 nm, N 0.01-0.1 mu m, N 3:N 10, where N 3:N 10 is the ratio of particles greater than 3 nm to those greater than 10 nm), which peak earlier in the week (Sunday/Monday) and decrease into the work week. While IMPROVE data show a weekly cycle for many variables along the coast (PMcoarse, PM2.5, fine soil, sulfate, and nitrate), airborne data show that organics exhibit consistent peaks on Thursday and minima on Sunday for both corridors. The weekly cycles are generally robust (especially NPF-related variables) when isolating wintertime data and when dividing LaRC-OXANA and LaRC-ZIBUT corridors in half. The results provide evidence for a weekly cycle for some aerosol characteristics offshore of a major continent with implications for cloud microphysics, remote sensing, and downwind air quality. Aerosols offshore the eastern U.S. appear to follow a weekly cycle coinciding with anthropogenic emission patterns. Differences in aerosol properties affect clouds, air quality, and satellite data interpretation.

Analyzing the formation of contrails on emissions from the most recent generation of aircraft engines is key to understand the climate impact from aviation. As for conventional Rich-Quench-Lean engines contrail ice crystals mainly form on a high number of emitted soot particles, the question arises which and how many particles are activated during the contrail formation process if soot emissions are strongly reduced through the Lean Combustion technology. The ecoDemonstrator experiment is a collaboration between Boeing, GE, NASA, DLR and other international partners and took place in October 2023. For the first time, we present in-flight measurements of contrail ice crystals in the exhaust of the ultra-low soot emitting CFM International LEAP-1B engine. This experiment combines the lean-burning engine technology with the use of Sustainable Aviation Fuels (SAF) and ultra-low sulfur kerosene (LS-Jet-A) in newly manufactured engines to achieve close to soot-free emissions. During the experiment, we performed measurements on board the NASA DC-8 research aircraft, sampling emissions behind a Boeing 737 MAX 10 aircraft. In addition to gas and particle emissions, we also measured the number concentrations of ice crystals that formed behind the 737 MAX 10 at a distance between 3 and 8 kilometers with two Cloud and Aerosol Spectrometers (CAS) that were positioned on the upper and lower fuselage of the DC-8. We show a first analysis of the contrail ice data for selected flights and present apparent ice emission indices (AEI) in relation to ambient conditions.

Aerosol-cloud interactions contribute significant uncertainty to modern climate model predictions. Analysis of complex observed aerosol-cloud parameter relationships is a crucial piece of reducing this uncertainty. Here, we apply two machine learning methods to explore variability in in-situ observations from the NASA ACTIVATE mission. These observations consist of flights over the Western North Atlantic Ocean, providing a large repository of data including aerosol, meteorological, and microphysical conditions in and out of clouds. We investigate this dataset using principal component analysis (PCA), a linear dimensionality reduction technique, and an autoencoder, a deep learning non-linear dimensionality reduction technique. We find that we can reduce the dimensionality of the parameter space by more than a factor of 2 and verify that the deep learning method outperforms a PCA baseline by two orders of magnitude. Analysis in the low dimensional space of both these techniques reveals two consistent physically interpretable regimes—a low pollution regime and an in-cloud regime. Through this work, we show that unsupervised machine learning techniques can learn useful information from in-situ atmospheric observations and provide interpretable results of low-dimensional variability.

Abstract. The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) is a six-year (2019–2024) NASA Earth-Venture Suborbital-3 (EVS-3) mission to robustly characterize aerosol-cloud-meteorology interactions over the western North Atlantic Ocean (WNAO) during winter and summer seasons, with a focus on marine boundary layer clouds. This characterization requires understanding the aerosol life cycle (sources and sinks), composition, transport pathways, and distribution in the WNAO region. We use the GEOS-Chem chemical transport model driven by the MERRA-2 reanalysis to simulate tropospheric aerosols that are evaluated against in situ and remote sensing measurements from Falcon and King Air aircraft, respectively, as well as ground-based and satellite observations over the WNAO during the winter (Feb. 14 – Mar. 12) and summer (Aug. 13 – Sep. 30) field deployments of ACTIVATE 2020. Transport of pollution in the boundary layer behind cold fronts is a major mechanism for the North American continental outflow to the WNAO during Feb.–Mar. 2020. While large-scale frontal lifting is a dominant mechanism in winter, convective lifting significantly increases the vertical extent of major continental outflow aerosols in summer. Turbulent mixing is found to be the dominant process responsible for the vertical transport of sea salt within and ventilation out of the boundary layer in winter. The simulated boundary layer aerosol composition and optical depth (AOD) in the ACTIVATE flight domain are dominated by sea salt, followed by organic aerosol and sulfate. Compared to winter, boundary layer sea salt concentrations increased in summer over the WNAO, especially from the ACTIVATE flight areas to Bermuda, because of enhanced surface winds and emissions. Dust concentrations also significantly increased in summer because of long-range transport from North Africa. Comparisons of model and aircraft submicron non-refractory aerosol species (measured by an HR-ToF-AMS) vertical profiles show that intensive measurements of sulfate, nitrate, ammonium, and organic aerosols in the lower troposphere over the WNAO in winter provide useful constraints on model aerosol wet removal by precipitation scavenging. Comparisons of model aerosol extinction (at 550 nm) with the King Air High Spectral Resolution Lidar-2 (HSRL-2) measurements (at 532 nm) and CALIOP/CALIPSO satellite retrievals (at 532 nm) indicate that the model generally captures the continental outflow of aerosols, the land-ocean aerosol extinction gradient, and the mixing of anthropogenic aerosols with sea salt. Large enhancements of aerosol extinction at ~1.5–6.0 km altitudes from long-range transport of the western U.S. fire smoke were observed by HSRL-2 and CALIOP during Aug.–Sep. 2020. Model simulations with biomass burning (BB) emissions injected up to the mid-troposphere (vs. within the BL) better reproduce these remote-sensing observations, Falcon aircraft organic aerosol vertical profiles, as well as AERONET AOD measurements over eastern U.S. coast and Tudor Hill, Bermuda. High aerosol (mostly coarse-mode sea salt) extinction near the top (~1.5–2.0 km) of the marine BL along with high relative humidity and cloud extinction were typically seen over the WNAO (< 35° N) in the CALIOP aerosol extinction profiles and GEOS-Chem simulations, suggesting strong hygroscopic growth of sea salt particles and sea salt seeding of marine boundary layer clouds. Contributions of different emission types (anthropogenic, BB, biogenic, marine, and dust) to the total AOD over the WNAO in the model are also quantified. Future modeling efforts should focus on improving parameterizations for aerosol wet scavenging and sea salt emissions, implementing realistic BB emission injection height, and applying high-resolution models that better resolve vertical transport.

New particle formation in the free troposphere is a major source of cloud condensation nuclei globally. The prevailing view is that in the free troposphere, new particles are formed predominantly in convective cloud outflows. We present another mechanism using global observations. We find that during stratospheric air intrusion events, the mixing of descending ozone-rich stratospheric air with more moist free tropospheric background results in elevated hydroxyl radical (OH) concentrations. Such mixing is most prevalent near the tropopause where the sulfur dioxide (SO 2 ) mixing ratios are high. The combination of elevated SO 2 and OH levels leads to enhanced sulfuric acid concentrations, promoting particle formation. Such new particle formation occurs frequently and over large geographic regions, representing an important particle source in the midlatitude free troposphere.

Table S1: Two-mode, lognormal model results for aerosol number concentration (N) for different bins of distance relative to LaRC.N1 represents the mode corresponding to the smaller Dp,g while N2 corresponds to the larger Dp,g.The bolded values represent the measurements made within the smoke layer, which correspond to the FT measurements made on 22 March 2022 in the 550 -800 km range.Blank cells indicate unavailable data or when the data can be better represented by a single mode.

Remote marine regions comprise a high fraction of Earth's surface, but in situ vertically resolved measurements over these locations remain scarce. Here we use airborne data during 15 vertical spiral soundings (0.15–8.5 km) over Bermuda during the NASA Aerosol Cloud meTeorology Interactions over the western ATlantic Experiment (ACTIVATE) to investigate the impact of different source regions on the vertical structure of trace gases, aerosol particles, and meteorological variables over 1000 km offshore of the US East Coast. Results reveal significant differences in vertical profiles of variables between three different air mass source categories (North America, Ocean, Caribbean/North Africa) identified using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model: (i) the strongest pollution signature is from air masses from the North America category, while the weakest one is from the Ocean category; (ii) North America air has the highest levels of CO, CH4, submicron particle number concentration, aerosol mass spectrometer (AMS) mass, and organic mass fraction along with smoke layers in the free troposphere (FT); (iii) Ocean air has the highest relative amount of nitrate, non-sea-salt sulfate, and oxalate, which are key acidic species participating in chloride depletion; (iv) air masses from the Caribbean/North Africa showed a pronounced coarse aerosol signature in the FT and reduced aerosol hygroscopicity, which is associated with dust transport; and (v) there is considerable vertical heterogeneity for almost all variables examined, including higher O3 and submicron particle concentrations with altitude, suggesting that the FT is a potential contributor of both constituents in the marine boundary layer. This study highlights the importance of considering air mass source origin and vertical resolution to capture aerosol and trace gas properties over remote marine areas.