A universal deep learning-based framework towards fully ab initio simulation of atmospheric aerosol nucleation

Atmospheric aerosol nucleation contributes to around half of cloud condensation nuclei globally. Despite the importance for climate, detailed nucleation mechanisms are still poorly understood. Understanding aerosol nucleation dynamics is hindered by non-reactivity of force fields and high computational costs due to rare event nature of aerosol nucleation. Developing reactive force fields for nucleation systems are even more challenging than covalently bonded materials because of wide size range and high dimensional characteristics of non-covalent hydrogen bonding bridging clusters. Here we proposes a system transferable framework to train an accurate reactive force field (FF) based on deep neural network (DNN) and further bridges the DNN-FF based molecular dynamics (MD) with cluster kinetics model based on Poisson distributions of reactive events to overcome high computational costs from direct MD. We found that previously reported acid-base formation rates tend to be underestimated several times, emphasizing acid-base nucleation observed in multiple environments should be revisited.

A Cross-laboratory Comparison Study of Titan Haze Analogs: Surface Energy

In Titan’s nitrogen-methane atmosphere, photochemistry leads to the production of complex organic particles, forming Titan’s thick haze layers. Laboratory-produced aerosol analogs, or “tholins,” are produced in a number of laboratories; however, most previous studies have investigated analogs produced by only one laboratory rather than a systematic, comparative analysis. In this study, we performed a comparative study of an important material property, the surface energy, of seven tholin samples produced in three independent laboratories under a broad range of experimental conditions, and we explored their commonalities and differences. All seven tholin samples are found to have high surface energies and are therefore highly cohesive. Thus, if the surface sediments on Titan are similar to tholins, future missions such as Dragonfly will likely encounter sticky sediments. We also identified a commonality between all the tholin samples: a high dispersive (nonpolar) surface energy component of at least 30 mJ m−2. This common property could be shared by the actual haze particles on Titan as well. Given that the most abundant species interacting with the haze on Titan (methane, ethane, and nitrogen) are nonpolar in nature, the dispersive surface energy component of the haze particles could be a determinant factor in condensate−haze and haze−lake liquid interactions on Titan. With this common trait of tholin samples, we confirmed the findings of a previous study by Yu et al. that haze particles are likely good cloud condensation nuclei for methane and ethane clouds and would likely be completely wetted by the hydrocarbon lakes on Titan.

The Effect of Using a New Parameterization of Nucleation in the WRF-Chem Model on New Particle Formation in a Passive Volcanic Plume

We investigated the role of the passive volcanic plume of Mount Etna (Italy) in the formation of new particles in the size range of 2.5–10 nm through the gas-to-particle nucleation of sulfuric acid (H2SO4) precursors, formed from the oxidation of SO2, and their evolution to particles with diameters larger than 100 nm. Two simulations were performed using the Weather Research and Forecasting Model coupled with chemistry (WRF-Chem) under the same configuration, except for the nucleation parameterization implemented in the model: the activation nucleation parameterization (JS1 = 2.0 × 10−6 × (H2SO4)) in the first simulation (S1) and a new parameterization for nucleation (NPN) (JS2 = 1.844 × 10−8 × (H2SO4)1.12) in the second simulation (S2). The comparison of the numerical results with the observations shows that, on average, NPN improves the performance of the model in the prediction of the H2SO4 concentrations, newly-formed particles (~2.5–10 nm), and their growth into larger particles (10–100 nm) by decreasing the rates of H2SO4 consumption and nucleation relative to S1. In addition, particles formed in the plume do not grow into cloud condensation nuclei (CCN) sizes (100–215 nm) within a few hours of the vent (tens of km). However, tracking the size evolution of simulated particles along the passive plume indicates the downwind formation of particles larger than 100 nm more than 100 km far from the vent with relatively high concentrations relative to the background (more than 1500 cm−3) in S2. These particles, originating in the volcanic source, could affect the chemical and microphysical properties of clouds and exert regional climatic effects over time.

Aviation impact on the cirrus ice crystal number using satellite observation

<p align="justify">Aviation outflow is the only anthropogenic source of pollution that is directly emitted into the upper troposphere. This emission has the potential to modify the cloudiness directly by forming linear contrails and indirectly by injecting aerosols, which can act as cloud condensation nuclei (CCN) and ice nucleating particles (INP). Contrail cirrus can persist either in cloud-free supersaturated air, increasing high-cloud cover or inside natural cirrus cloud, and therefore modifying the microphysical properties of already existing cirrus clouds. Even though the situation that an aircraft flies through a natural cirrus is one of the highly probable situations in the upper troposphere, its subsequent impact is unclear with the present state of knowledge. Quantifying such impact is necessary if we are to properly account for the influence of aviation on climate. One main limitation preventing us to better identify these impacts is the lack of height resolved measurements inside the cirrus clouds.</p> <p align="justify">In this study, we used new retrievals from combined satellite cloud radar and lidar (Cloud- Sat/CALIPSO; DARDAR-Nice algorithm), which provide height resolved information of ice crystal number concentration, at intercepts between the CALIPSO ground track and the position of civil aircraft operating between the west coast of the continental United States (Seattle, San Francisco and Los Angeles) and Hawaii during 2010 and 2011 from an earlier study.</p> <p align="justify">Comparing cloudy air behind the aircraft inside the flight track to the adjacent regions and to ahead of the aircraft revealed a notable difference in ice number concentration at 300 m to 540 m beneath the flight height. These differences are derived from the reduction of ice number concentrations as we proceed toward the cloud base in regions unaffected by aviation and the increase of ice crystals as we distance a few hundreds of meters beneath the flight level in the regions affected by aviation.</p>

Arctic fog chemistry induces the unexpected growth of Aitken mode particles to CCN-active particles

<p>New particle formation (NPF) and early growth are efficient processes producing high concentrations of cloud condensation nuclei (CCNs) precursors in the Arctic marine boundary layer (AMBL). However, due to short lifetime and lack of condensable vapors, newly formed particles do often not grow beyond 50 nm and cause low CCN particle concentrations in the AMBL. Thus, even the smallest amount of Aitken mode particle growth is capable to significantly increase the CCN budget. However, the growth mechanism of Aitken-mode particles from NPF into CCN range in the Arctic is still rather unclear and was therefore investigated during the cruise campaign PASCAL in 2017.</p> <p>During PASCAL, aerosol particles measurements were performed and an unexpected rapid growth of Aitken mode particles was observed right after fog episodes. Combined field data analyses and detailed multiphase chemistry box model simulations with the CAPRAM mechanism were performed to study the underlying processes. Resulting, a new mechanism is proposed explaining how particles with d < 50 nm are able to grow into CCN size range in the Arctic without requiring high water vapor supersaturation (SS). The investigations demonstrated that the rapid post-fog particle growth of Aitken mode is related to chemical processes within the Arctic fog. The redistribution of semi-volatile acidic (e.g., methanesulfonic acid) and basic (e.g., ammonia) compounds from processed CCN-active particles to smaller CCN-inactive particles can cause a rapid particle growth of Aitken mode particles after fog evaporation enabling them to grow towards CCN size. Comparisons of the model results with Berner impactor measurements supports the proposed growth mechanism.</p> <p>Overall, this study provided new insights on how the increasing frequency of NPF and fog-related particle processing can increase in the number of CCNs and cloud droplets leading to an increased albedo of Arctic clouds and thus affect the radiative balance in the Arctic. Since fogs will occur more frequently in the Arctic as a result of climate change, this growth mechanism and a deeper knowledge on its feedbacks can be essential to understand Arctic warming.</p>

A closer look at the invisible: Unprecedented levels of ultrafine particles and the hydrological cycle

<p>Continental as well as maritime ultrafine particles as cloud condensation nuclei (CCN) are likely initially produced by gas to particle conversion starting with nucleation mode aerosol and slowly (within several hours)  growing into CCN sizes. Although these birth and growing processes were well investigated since about 50 years, the source locations, where the anthropogenic fraction of these particles are preferably formed still remain uncertain as well as the strength of individual natural or anthropogenic sources.</p> <p>We present an analysis based on two decades of airborne studies of number and size distribution measurements across Europe, Australia, Mexico and China on nucleation and Aitken mode particles serving as CCN or their precursors. Selected flight patterns allow source apportionment for typical major sources and even a quantitative estimate of their emission rates. </p> <p>Contrary to current global climate model RCP assumptions with decreasing aerosol from 2005 towards the end of the century trends of ultrafine particles and CCN are no longer correlated to sulphur emissions within the last two decades. Nowadays nitrogen and ammonia chemistry is becoming increasingly important for global anthropogenic nanoparticle particle formation and number concentrations. Due to their impact on the hydrological cycle, changes like a slowdown of raindrop production, an increased latent heat flux into the lower free troposphere, an invigoration of torrential rains and a larger water vapour column density might be the consequences. Such recently observed weather patterns are well in agreement with current observations of regional UFP/CCN concentrations and their timely evolution.</p>

Impact of dry intrusion events on the composition and mixing state of particles during the winter Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA)

Long-range transport of continental emissions has a far-reaching influence over remote regions, resulting in substantial change in the size, morphology, and composition of the local aerosol population and cloud condensation nuclei (CCN) budget. Here, we investigate the physicochemical properties of atmospheric particles collected on board a research aircraft flown over the Azores during the winter 2018 Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA) campaign. Particles were collected within the marine boundary layer (MBL) and free troposphere (FT) after long-range atmospheric transport episodes facilitated by dry intrusion (DI) events. Chemical and physical properties of individual particles were investigated using complementary capabilities of computer-controlled scanning electron microscopy and X-ray spectromicroscopy to probe particle external and internal mixing state characteristics. Furthermore, real-time measurements of aerosol size distribution, cloud condensation nuclei (CCN) concentration, and back-trajectory calculations were utilized to help bring into context the findings from offline spectromicroscopy analysis. While carbonaceous particles were found to be the dominant particle type in the region, changes in the percent contribution of organics across the particle population (i.e., external mixing) shifted from 68 % to 43 % in the MBL and from 92 % to 46 % in FT samples during DI events. This change in carbonaceous contribution is counterbalanced by the increase in inorganics from 32 % to 57 % in the MBL and 8 % to 55 % in FT. The quantification of the organic volume fraction (OVF) of individual particles derived from X-ray spectromicroscopy, which relates to the multi-component internal composition of individual particles, showed a factor of 2.06 ± 0.16 and 1.11 ± 0.04 increase in the MBL and FT, respectively, among DI samples. We show that supplying particle OVF into the κ-Köhler equation can be used as a good approximation of field-measured in situ CCN concentrations. We also report changes in the κ values in the MBL from κMBL, non-DI=0.48 to κMBL, DI=0.41, while changes in the FT result in κFT, non-DI=0.36 to κFT, DI=0.33, which is consistent with enhancements in OVF followed by the DI episodes. Our observations suggest that entrainment of particles from long-range continental sources alters the mixing state population and CCN properties of aerosol in the region. The work presented here provides field observation data that can inform atmospheric models that simulate sources and particle composition in the eastern North Atlantic.

Long- and Short-Term Temporal Variability in Cloud Condensation Nuclei Spectra in the Southern Great Plains

When aerosol particles seed formation of liquid water droplets in the atmosphere, they are called cloud condensation nuclei (CCN). Different aerosols will act as CCN under different degrees of water supersaturation (relative humidity above 100 %) depending on their size and composition. In this work we build and analyze a best-estimate CCN spectrum product, tabulated at ~45 min resolution, generated using high quality data from eight independent instruments at the US Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The data product spans a large supersaturation range, from 0.0001 to ~30 %, and time period, 5 years from 2009–2013 and is available on the ARM data archive. We leverage this added statistical power to examine relationships that are unclear in smaller datasets. Probability distributions of many aerosol and CCN metrics are found to exhibit skewed log-normal distribution shapes. Clustering analyses of CCN spectra reveal that the primary drivers of CCN differences are aerosol number size distributions, rather than hygroscopicity or composition, especially at supersaturations above 0.2 %, while also allowing for simplified understanding of seasonal and diurnal variations in CCN behaviour. The predictive ability of using limited hygroscopicity data with accurate number size distributions to estimate CCN spectra is investigated and uncertainties of this approach are estimated. Finally, the dynamics of CCN spectral clusters and concentrations are examined with cross-correlation and autocorrelation analyses, which assist in determining the time scales of changing CCN concentrations at different supersaturations and are important for cloud modelling studies.