Beyond the general topics, we recognize the rapid development of digital technologies has begun to transform and even lead new directions in aerosol research. Cloud computing, digital twins, and artificial intelligence are providing unprecedented capabilities for this field. These approaches span multiple scales, from single particles to global systems, and from process-level understanding to impact attribution. This session will spotlight the growing role of digital technologies in aerosol chemistry and physics. We invite contributions that explore the application and highlight key discoveries enabled by digital technologies. At the same time, we also emphasize the importance of balancing innovation with rigor: conclusions and processes must be carefully validated, uncertainties explicitly assessed, and data-driven methods integrated with theory, process models, and experimental observations to ensure reliability and reproducibility. Through this lens, this session aims to discuss both the opportunities and responsibilities of integrating digital technologies into aerosol research.
We welcome submissions that fall under a broad range of atmospheric aerosol applications. This could include work on the role and impact of:
- Advance fundamental understanding of aerosol chemistry and physics
- Development of hybrid process-machine learning based aerosol models
- Increased resolution and/or computational efficiency of numerical methods
- Applications of AI-enabled (e.g., GenAI, foundation models) and new-generation tools in aerosol research
- AI-enabled interpretation/prediction of aerosol variability and consequences, from characterizing properties to forecasting extreme events and quantifying impacts
- Development of new physical and digital platforms/technologies for aerosol research
- Open science practices: benchmark datasets, reproducible workflows, model sharing, and evaluation standards
Orals: Tue, 5 May, 10:45–15:40 | Room F2
Oxygenated organic molecules (OOMs) form in the atmosphere by oxidation of volatile organic compounds from both natural and anthropogenic sources. Highly oxygenated organic molecules are likely to take part in new particle formation, but it is unclear to what extent they can form particles without the involvement of inorganic acids or ions, and whether they have a significant contribution to the initial formation of molecular clusters, or only to the growth of these clusters.
We have studied clusters of C10-C14 sized accretion products from isoprene and toluene oxidation, as well as clusters of C20 sized accretion products from ⍺-pinene oxidation. The studied OOMs were obtained using Gecko-AP, a RO2 + RO2 accretion product generator based on the Gecko-A software. The main bottleneck for modelling OOM cluster is the conformational sampling of their high-dimensional potential energy surfaces. Thus we we have update previous automated cluster conformational sampling protocols. Initial sampling of cluster configurations was done at semi-empirical level of theory. Minimum free energy configurations were found through successive rounds of filtering and re-optimization at higher DFT levels of theory. As we found that even an extensive sampling of cluster configuration space does not guarantee that the global minimum is found, we introduced constraints to initial sampling which force hydrogen bond formation between molecules. We also used metadynamics simulations to search for additional local minima. We are currently with neural network potentials which are likely to allow computationally even more effective configurational sampling.
The binding free energies of the OOM homodimers are almost uncorrelated with the saturation vapour pressures predicted by existing group-contribution approaches. Binding energy of heterodimers can, however, be estimated from homodimer binding energies with a spread of ±1-2 kcal/mol, indicating desired tranferability from unimolecular properties to clustering efficiecy. The predicted binding free energies are too high for substantial clustering to occur in typical lower-tropospheric conditions. For validation purposes we performed calculations on dimers of differently sized polyethylene glycol molecules (PEGs), for which the configurational sampling is relatively straightforward, and the saturation vapor pressures are available both from quantum chemistry (via COSMOTherm) and experimentally. Using the PEG molecules, we demonstrate that both the weak binding, and the lack of correlation between binding free energies and saturation vapour pressures, are likely caused by intramolecular hydrogen bonding. This self-bonding is dictated by the molecular flexibility, which is ultimately a unimolecular property, and potentially a cost-effectively descriptor for assessing the clustering ability of OOMs with machine learning based methods.
How to cite: Vehkamäki, H., Kähärä, J., Kurtén, T., Ingram, S., and Franzon, L.: Modelling clusters of complex organic molecules , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3019, https://doi.org/10.5194/egusphere-egu26-3019, 2026.
Black carbon (BC) is a global climate forcer due to its strong radiative absorption, which is highly sensitive to coating formation regulated by anthropogenic and biogenic emissions across regions. However, how cross-regional biogenic sources modulate BC coating formation and radiative effects, particularly in high anthropogenic emission environments, remains poorly understood. Here we show, using integrated observations and model simulations, that biogenic volatile organic compounds from vegetation-rich regions undergo atmospheric oxidation to produce oxygenated organic compounds, which are subsequently advected into downwind urban areas. These products enhance regional atmospheric oxidation capacity and supply additional precursors, thereby promoting secondary organic aerosol production. This biogenic-induced strengthening of regional photochemistry significantly drives the formation of highly oxidized secondary organic aerosol coatings on BC particles and increases its fraction within the total particle population. Consequently, BC absorption efficiency increases more steeply with the coating carbon oxidation state under biogenic-rich conditions, yielding an average ~20% enhancement in radiative absorption from the lensing effect relative to biogenic-poor periods. Our findings reveal that cross-regional biogenic-anthropogenic interactions enhance both the formation and particle population fraction of secondary organic aerosol coatings on urban BC, potentially further amplifying its radiative effects as biogenic emissions increase under future warming scenarios.
How to cite: Ge, X., Zhang, Y., Wang, J., and Li, H.: Urban black-carbon radiative heating intensified by biogenic-anthropogenic interactions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2770, https://doi.org/10.5194/egusphere-egu26-2770, 2026.
Atmospheric aerosols play a key role in Earth’s climate system, yet their vertical distribution, particularly in the free and upper troposphere, remains poorly constrained, strongly contributing to uncertainties in direct and indirect aerosol radiative forcing. We present an improved version of the EMAC (ECHAM5/MESSy for Atmospheric Chemistry) chemistry-climate model, evaluated against a comprehensive dataset from ground-based, remote-sensing, and aircraft observations, showing good agreement across the troposphere and lower stratosphere. Simulations reveal a global minimum in aerosol mass between 400 and 200 hPa, marking the transition from the free to the upper troposphere/lowermost stratosphere (UTLS), a region characterized by frequent new particle formation. Contrary to earlier model studies, boundary layer primary particles are rarely transported into the upper troposphere and stratosphere in our simulations, consistent with recent observational evidence. Finally, we outline specific aerosol process studies enabled by this improved model setup, in support of recent aircraft campaigns. The improved EMAC setup will provide the basis for detailed numerical studies of aerosol-(cloud-)radiation interactions across the lower and middle atmosphere.
How to cite: Kohl, M., Brühl, C., Tost, H., Xenofontos, C., Christoudias, T., Köllner, F., Joppe, P., Schneider, J., Lelieveld, J., and Pozzer, A.: Global aerosol distributions and composition from the Earth's surface to the stratosphere, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16817, https://doi.org/10.5194/egusphere-egu26-16817, 2026.
The local abundance of PM2.5 sulfate, an aerosol component with important health and environmental impacts, is often influenced by cross-regional transport. However, the associated dynamic and chemical processes governing PM2.5 sulfate transport under different synoptic conditions remain insufficiently understood. Improving this process-level understanding is essential for interpreting sulfate pollution in regions downwind of major emission sources. To this end, this study introduces a process-based framework to investigate how synoptic systems regulate PM2.5 sulfate transport.
Based on WRF/CMAQ simulations, we diagnosed the relative importance of horizontal transport and vertical exchange, as well as various in-plume sulfate production pathways, during two distinct PM2.5 sulfate pollution episodes in South China during autumn 2015. These episodes were linked to contrasting synoptic influences, namely the typhoon periphery and the subtropical high, and were characterized by strong and weak effects of cross-regional transport, respectively.
Our analyses show that vertical exchange across the boundary-layer top served as the major process of PM2.5 sulfate import in both episodes. Interestingly, pronounced vertical exchange occurred under both strong inflow and stagnant conditions, suggesting that they could independently intensify vertical PM2.5 sulfate exchange. Meanwhile, contrasting meteorological conditions and chemical environments in the two episodes resulted in different contributions of in-plume sulfate production pathways: gas-phase OH oxidation dominated within dry, cold and oxidant-rich plumes under typhoon periphery, whereas aqueous-phase H2O2 oxidation prevailed within wet and humid plumes under relatively stable conditions.
Overall, these results highlight the complex coupling between synoptic forcing, atmospheric dynamics and chemistry in cross-regional PM2.5 sulfate transport, providing new perspectives into sulfate pollution mechanisms and implications for future PM2.5 mitigation.
How to cite: Qu, K., Wang, X., Yan, Y., Jin, X., Cai, X., Shen, J., Xiao, T., Yin, M., Vrekoussis, M., Kanakidou, M., Brasseur, G., Zeng, L., and Zhang, Y.: Synoptic control on the dynamics and chemistry of regional PM2.5 sulfate transport in South China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5133, https://doi.org/10.5194/egusphere-egu26-5133, 2026.
Accurate determination of the aerosol mixing state is indispensable to assess aerosol direct and indirect effects. However, the characterization of the mixing state is often limited by the scarcity of direct, in situ measurements of chemical composition and single-particle morphology. Consequently, the aerosol community has largely relied on optical closure techniques to infer the aerosol mixing states from optical measurements, which were generally deemed only as probable mixing states. The heuristic nature of these techniques restricts the quantification of inherent uncertainties in the inferred mixing states. To address this gap, this study presents an analytical formulation of the optical inversion problem as a linear system using the Python aerosol optical model, AeroMix. This formulation explicitly characterizes the problem as both ill-posed and ill-conditioned, while offering a scalable, modular framework that remains agnostic to the specific forward model and measurement techniques. To mitigate mathematical instabilities, system dimensionality is reduced by eliminating physically infeasible core-shell components and grouping spectrally indistinguishable core-shell components. Establishing that a unique solution is mathematically impossible, the solution space is characterized as a high-dimensional convex polytope bounded by linear inequalities defined by the range of measured optical properties and physical component constraints. Finally, this study proposes retrieving physically meaningful, sparse solutions by using Markov Chain Monte Carlo (MCMC) techniques to sample the polytope boundaries lying on coordinate hyperplanes. This stochastic approach transforms optical inversion from a heuristic estimation into a probabilistic characterization of the valid solution space, enabling robust uncertainty quantification in the inferred aerosol mixing states.
How to cite: P Raj, S. and Sinha, P. R.: An analytical formulation of the optical inversion of aerosol mixing state and characterization of solution space , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3114, https://doi.org/10.5194/egusphere-egu26-3114, 2026.
Wildfires are both a consequence of and a contributor to extreme weather events. Their increasing frequency and intensity significantly impact the atmosphere by virtue of the aerosol particles and gases they release and the radiative forcing impact of those atmospheric injections. In-situ measurements of these aerosols are extremely limited. Here, we present results from an aircraft-based field campaign conducted in July 2025, in the vicinity of Red Lake, Ontario, Canada. Fires with both flaming combustion and lower radiative power following rainfall were sampled. The aerial platform was the National Research Council Canada’s Twin Otter aircraft. The Twin Otter aircraft is a specialized and customizable research platform equipped with a variety of scientific instruments and sensors.
Gaseous measurements including greenhouse gases carbon dioxide (CO2), methane (CH4) and water vapor (H2O) were taken. Auxiliary data included aircraft state (aircraft location, altitude, and orientation) and atmospheric state (temperature, pressure and dew point). Particulate measurements including particle size distributions (PSDs), concentrations, single scattering albedos (SSA) and refractory black carbon (rBC) concentrations are reported. In addition, the number of non-rBC particles observed after thermo-denuding – representing ash or char particles – was measured in a dedicated experiment.
During these dedicated flights, we sampled both aerosols and gases at varying distances from the source and from directly above the fire to several hundred kilometers downwind. Preliminary results will include the properties and characterization of wildfire aerosols and GHGs at different distances from the fire source.
How to cite: Ranjbar, K., O'Neill, N., Elsagan, N., Gomaa, I., and Corbin, J.: Airborne characterization of aerosol particles and gases emitted from the 2025 Canadian wildfires at Red Lake, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5897, https://doi.org/10.5194/egusphere-egu26-5897, 2026.
Aerosol particles influence climate both directly, by scattering and absorbing solar radiation, and indirectly, by acting as cloud condensation nuclei. However, the magnitude of these effects remains highly uncertain, largely due to limitations in how aerosol dynamics are represented in global climate models. Current models often rely on simplified process rate approximations and coarse aerosol dynamics, as more accurate simulations are computationally prohibitive.
To improve parameterizations in climate models, there is a need for robust methods to estimate aerosol process rates, such as condensation, formation, and deposition, from both chamber and atmospheric data. These rates are not well constrained, as the underlying physical mechanisms are not yet fully understood. Nevertheless, they are key drivers of aerosol size distribution evolution, which varies with atmospheric conditions.
Bayesian state-space methods offer a way to simultaneously estimate size distribution evolution and process rates from Mobility Particle Sizer Spectrometer (MPSS) data. In addition, Bayesian methods account measurement and process uncertainties directly into the estimation framework, enabling inherent uncertainty quantification.
In this study, we use the extended Kalman Filter (EKF) to estimate the state of the system, i.e., the expected values and credibility intervals of the size distribution and process rates. At each time step, the EKF predicts the next state based on a model of the system dynamics and updates this prediction with new measurements. In the evolution step, we use a finite element approximation of the General Dynamic Equation of Aerosols. We model the process rates as Markov processes. In this work, the measurements consist of time-series of counts given by the MPSS. The Fixed Interval Kalman Smoother (FIKS) back-iterates the EKF estimates refining them in the process by applying information about the future measurements. The inference of process rates using EKF and FIKS was tested both with synthetic and experimental data. The simulated MPSS data are generated by transforming a known aerosol distribution evolution to the output of the MPSS with a system matrix which maps size distributions to counts measured by a condensation particle counter. In the chamber measurement, 𝛼-pinene and ozone reacted chemically forming organic compounds, which caused ammonium sulfate particles to grow due to condensation. The data was measured with scanning mobility particle sizer (SMPS).
The EKF and FIKS captures the true process rates from the simulated data as the true value lies constantly inside the 95-% credibility interval of the estimated process rates. In the chamber measurements, the growth estimates obtained with the EKF and FIKS are close to the estimates obtained with the maximum concentration method. Notably, the EKF and FIKS give estimates for the each particle size at each time step which is not the case with the customary methods. Furthermore, a major strength of the proposed methods is that, in addition to estimates of the mean values, credibility intervals for the variables of interest are obtained simultaneously.
How to cite: Salminen, T., Ursin, A., Lehtinen, K., and Niskanen, M.: Simultaneous MPSS data inversion and aerosol process rate estimation with uncertainty quantification via Bayesian state-space methods, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13782, https://doi.org/10.5194/egusphere-egu26-13782, 2026.
The Schneefernerhaus observatory at Zugspitze, Germany is located at 2650 m a.s.l and provides the opportunity to monitor long-range transport of air pollutants in the free troposphere. In this study, we present aerosol observations performed from July to October 2025, with special focus on aerosol light absorption, i.e. brown and black carbon. Light-absorbing carbonaceous matter (LAC) is relevant to the climate due to its short atmospheric lifetime and the dynamic behaviour of its optical properties, which change upon aging. Black carbon is included as a metric to be measured in the recent modification of the European Air Quality Directive, underscoring the need for an SI-traceable calibration chain for black carbon. This need is particularly pressing for absorption photometers (e.g., aethalometers), which are widely deployed in air quality monitoring networks. A field calibration has proven challenging given that there is no standard reference material available and that primary measurement methods are not yet ready for straightforward field deployment.
In this study, we have used an Aethalometer AE36s (Aerosol d.o.o., Ljubljana, Slovenia) and a photo-acoustic extinctiometer (PAX, Droplet Measurement Technology, Longmont, USA) to monitor aerosol light absorption during a 10-week field campaign at Schneefernerhaus. Additionally, we have used particle number size distribution (PNSD), and multi-angle absorption photometer (MAAP) data to assess different aerosol physical properties. The primary objective was to use the PAX measurements as a transfer standard to calibrate AE36s measurements in the field. The calibration transfer has proven feasible for the IR wavelength of 880 nm, which is of special interest when the focus is to determine black carbon with the less interference from other LAC components.
Observations in August 2025 show clearly a spike of LAC concentration with different wavelength dependencies (see Fig. 1), indicating a highly variable contribution of brown carbon to the total aerosol mass. HYSPLIT back-trajectory analysis indicate that these aerosol episodes originated from Canadian wildfires, which were highly active during the measurement period.
Overall, the field calibration method using PAX as a transfer standard has proven to be reliable and plausible. However, the method is constrained by the sensitivity and limit of detection of the PAX and also require that the PAX itself is calibrated against a primary method, such as extinction-minus-scattering or photo-thermal interferometry. The development of a robust primary calibration strategy for photo-acoustic spectrometers would significantly improve the traceability chain and would minimize uncertainties for in-field calibration of absorption photometers.
Figure 1. Aerosol absorption coefficient measured by an Aethalometer AE36s at Schneefernerhaus Zugspitze, Germany in August 2025.
How to cite: Saturno, J., Couret, C., Elsasser, M., Hellack, B., and Nowak, A.: Long-range transport of wildfire emissions over Zugspitze, Germany: An opportunity to test the field calibration of black carbon absorption photometers, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7261, https://doi.org/10.5194/egusphere-egu26-7261, 2026.
The distribution and source of atmospheric particles significantly influence the atmospheric environment. This study examines changes in Particle Number Size Distribution (PNSD) and its relationship with Planetary Boundary Layer Height (PBLH), as well as nucleation trajectories during new particle formation (NPF) events in three major Chinese cities: Beijing (BJ), Guangzhou (GZ), and Shanghai (SH). The observation periods include July 2017 to October 2019 (408 effective observation days), November 2019 to March 2020 (127 effective observation days), and April to June 2020 (44 effective observation days) for BJ, GZ, and SH, respectively. The results show that BJ exhibits the highest Nucleation Mode Particle Number Concentration (PNC) at 2.05 × 10⁶ cm⁻³, while GZ records the highest NPF frequency at 25.98%. In contrast, SH has the lowest PNC at 6.27 × 10⁵ cm⁻³ and the lowest NPF frequency (18.87%). High background particle concentrations significantly impact NPF. The sources of PNSD at the three observation sites exhibit distinct trajectories on NPF days. The main source of pollutants in BJ is Mongolia, located to the northwest. In GZ, the contribution mainly comes from Jiangxi and Fujian provinces to the northeast, while in SH, the source lies to the northwest. NPF frequencies consistently exceed 25%, predominantly in the northern regions of each site, indicating higher NPF levels in the north compared to the south. Nucleation-mode particles at all sites originate from continental sources, rather than marine sources, during NPF events. This research provides valuable insights for developing strategies to manage the atmospheric environment.
How to cite: Hu, H., Wu, H., and Zhang, Y.: New insights into the boundary layer revolution impact on new particle formation characteristics in three megacities of China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4879, https://doi.org/10.5194/egusphere-egu26-4879, 2026.
The mixing of precursors significantly alters secondary organic aerosol (SOA) yield and composition. This study systematically investigates SOA formation from the photooxidation of two polycyclic aromatic hydrocarbons (naphthalene, 2-methylnaphthalene) and two terpenes (isoprene, alpha-pinene), representing anthropogenic and biogenic precursors, as well as their binary mixtures under both low and high NOx conditions in both smog chamber and flow tube reactor. SOA composition is analyzed using a Filter Inlet for Gases and Aerosols coupled to a high-resolution time-of-flight chemical ionization mass spectrometer (FIGAERO-CIMS). Results show that the SOA yield of naphthalene and 2-methylnaphthalene under high NOx is lower than under low NOx, consistent with previous studies. Suppression of SOA formation is observed in mixed precursor systems. This may result from differences in particle volatility between individual and mixed precursor systems, indicating distinct oxidation processes. Additionally, under NOx-free conditions, SOA yields from mixed precursors (e.g., isoprene/naphthalene and α-pinene/naphthalene) are not additive but exhibit a nonlinear dependence on the reactivity ratio—defined as the product of the OH rate constant and consumed concentration of each precursor. A synergistic enhancement of up to 60% is observed at optimal reactivity ratios. Molecular-level analysis reveals unique oxidation products in mixed systems, suggesting novel reaction pathways. The enhanced yield is attributed to an increased condensation sink and potential heterogeneous reactions. A parameterized formula linking yield to reactivity ratio is proposed, which could improve SOA model accuracy. These findings highlight the importance of precursor interactions, quantified via reactivity ratio, for accurately predicting aerosol loading, especially in clean atmospheres. This study provides new insights and a framework for understanding SOA formation from mixed anthropogenic and biogenic precursor systems.
How to cite: Guo, S., Yu, Y., Tan, R., Zhu, W., Lou, S., Zhao, Y., and Hu, M.: Non-additive Secondary Organic Aerosol Formation Yields from Mixed Biogenic and Anthropogenic Precursors, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3008, https://doi.org/10.5194/egusphere-egu26-3008, 2026.
The Indo-Gangetic Plain (IGP) experiences persistent and severe air pollution, with wintertime conditions particularly extreme. Cities across the IGP, including Delhi, consistently rank among the world’s most polluted. Fine particulate matter (PM2.5) dominates Delhi’s pollution burden, with sulfate contributing about 9-12% of non-refractory PM2.5. Yet atmospheric models consistently underestimate sulfate concentrations, both globally and over in India, largely because key physical and chemical processes governing sulfate formation under local conditions remain insufficiently represented. Moreover, India does not have publicly available emission inventory. As a result, most modelling studies rely on global inventories that do not fully capture region-specific emission characteristics or the impact of recent policy measures.
Sulfate primarily forms through gas-phase oxidation of SO2 by OH radicals and through aqueous-phase oxidation of S(IV) by O3, H2O2, NO2, and transition-metal-ion (TMI)-catalyzed reactions with O2. In extreme pollution episodes over Delhi during winter, suppressed sunlight limits OH production, weakening gas-phase oxidation. Furthermore, aqueous-phase pathways mainly occur in cloud water, whereas haze liquid water content is substantially lower, reducing their effectiveness. Conversely, the large aerosol surface area during haze episodes suggests an enhanced role for heterogeneous reactions.
To better represent regional emissions, we updated the global emissions inventory by integrating local policy interventions and revised regional energy-sector activity profiles. Numerical simulations using this modified inventory were evaluated using comprehensive winter observations at IIT Delhi. While the updated inventory substantially improves representation of total sulfur (NMB of 1.34%), the model continues to underestimate sulfate. After evaluating several recently proposed sulfate formation mechanisms for haze conditions (e.g., H2O2 and NO2 oxidation pathways), we find that metal-catalyzed heterogeneous oxidation of SO2 by O2 on aerosol surfaces is the dominant contributor, accounting for ~43% of the observed sulfate. Implementation of this mechanism significantly improves model agreement with observations. Lagrangian analysis indicates that this pathway is highly pH-dependent, with elevated sulfate production occurring at pH values between 4 and 5. Additionally, a substantial fraction of sulfate is formed during regional transport from nearby states power plants surrounding Delhi.
Our findings highlight that Delhi’s elevated sulfate concentrations are primarily driven by regional transport from nearby coal power plants and by metal-catalyzed heterogeneous oxidation on aerosol surfaces under severe winter haze conditions.
How to cite: Maity, R., Nandi, I., Kumar, A., Singh, V., Ganguly, D., and Kumar, M.: Heterogeneous chemistry and regional coal power emissions drive Delhi’s sulfate pollution, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-360, https://doi.org/10.5194/egusphere-egu26-360, 2026.
Ultrafine particles (UFPs, with diameters below 100 nm) pose greater health risks, as they can penetrate deep into the pulmonary alveoli and reach the bloodstream (Ohlwein et al., 2019). Understanding the sources of UFPs and their relative contributions to particle number concentration (PNC) through source apportionment is essential for developing effective emission regulation policies. This study aims to develop a newly implemented approach based on Non-Negative Matrix Factorization (NMF) receptor modeling to identify and quantify the sources of UFPs at the ATmospheric Observatory in LiLLe (ATOLL).
To ensure robust source resolution, three temporal scales approaches to source apportionment were applied in this study: (i) a focus analysis of summer months to resolve expected nucleation sources enhance by a strong photochemistry activity (ii) seasonal source apportionment over a full year to quantify intra-annual variability and (iii) a four year long term source apportionment to assess temporal trends of the sources.
The model was first applied to summer data (June – August) for all the year revealing a strong nucleation factor (~26% of PNC). This finding is consistent with previous observations of summer photochemical strong activities and New Particle Formation (NPF) events (Crumeyrolle et al., 2023). As expected, seasonal analysis then showed a lower nucleation contribution on winter (10.6% vs. 37% on summer). Together, these two approaches demonstrate the robustness of NMF to separate the sources of UFPs.
Long-term variations of sources were also investigated using a single source apportionment on a four-year dataset (2020–2024) , and a linear regression model was applied to the results to assess temporal trends. Traffic-related sources showed a decreasing trend with average annual reductions of -7.75 % (gasoline emissions) and -12.68 % (diesel emissions) likely following the impact of European Union regulation on PM (EC, 2023). In contrast, nucleation-related sources exhibit a significant increase of 9.28 % yr-1, consistent with recent observations of rising UFP PNC on ATOLL (Suchánková et al., 2025) but not with other studies on suburban sites (Garcia-Marlès et al., 2024). This observed increase in nucleation sources shows strong evidence on the growing role of secondary formation processes which might be enhance by the emission of gaseous precursors such as SO2 and environmental conditions.
Overall, traffic emissions remained the dominant contributor (~69.20 %) to total PNC with a contribution decreasing trend of -3 %yr-1, in contrast to nucleation contribution (~19.72 %) with an increasing trend of +12.48 %yr-1. These findings highlight the predominantly anthropogenic origin of UFPs on ATOLL and the rising importance of nucleation factor on PNC, emphasizing the need for specific emission policies targeting UFPs alongside existing PM2.5 regulations.
How to cite: Randrianomenjanahary, S., Crumeyrolle, S., Chen, H., and Riffault, V.: LONG TERM VARIATION IN ULTRAFINE PARTICLES (UFPs) SOURCES: RISING EVIDENCE FOR INCREASING NUCLEATION SOURCES CONTRIBUTION, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19173, https://doi.org/10.5194/egusphere-egu26-19173, 2026.
Hydroxyl radical (OH) is the major daytime oxidant, playing a key role in the atmospheric (photo)chemistry of numerous organics. More recently, there has been an increasing focus on multiphase reactions responsible for the formation and evolution of biogenic secondary organic aerosols (BSOAs). BSOAs are major components of fine particulate matter (PM), which strongly affects the climate and public health. The enhanced formation of SOAs in the aqueous phase (aqSOAs) may, at least in part, explain the discrepancies between observed and modeled budgets of organic aerosols.
Models are essential for understanding and predicting how emissions and chemical transformations shape the atmospheric chemistry. Despite the now well-documented influence of the multiphase reactions on the formation and evolution of BSOAs, modeling such processes remains challenging. This is, in part, because encompassing the OH-mediated transformation of biogenic, water-soluble organic compounds (WSOCs) into the atmospheric models requires advanced predictive tools.
To resolve the extreme molecular complexity of chemical reactions leading to BSOAs, automated generators were introduced. These systems can provide near-explicit reaction schemes, often necessary to represent chemical transformations of the numerous, atmospherically widespread organics. Reaction rate coefficients - (kOH M-1s-1) in case of OH-initiated oxidation in the aqueous phase, are a pivotal element of mechanism generators. However, kinetic databases exist for only a small subset of chemically diverse WSOCs present in the atmosphere. For this reason, generating (near)explicit mechanisms requires predicting the vast majority of rate coefficients. Hence, the reliability of these automated expert systems largely depends on kinetic models, primarily structure-activity relationships (SARs), which predict kOH for structurally diverse reactants.
SARs are regression models that use the measured properties of the (model) molecules to predict the properties (here kOH values) of a larger number of compounds, for which no experimental data exists. SARs are based on and evaluated against experimental data. At the same time, the kinetic data for many atmospherically widespread WSOCs remain limited.
In the work presented, the values of kOH for aliphatic alcohols, carbonyls, carboxylic acids, and esters were measured with the relative rate technique. Measurements were conducted in a custom-designed aqueous photoreactor, and the WSOCs under investigation were quantified using gas and liquid chromatography. With this approach, ≈ 30 kOH values can be measured in a single experiment, generating a significant amount of new data. To date, we have measured temperature-dependent values of kOH for more than 100 aliphatic WSOCs. The values of activation parameters obtained from these measurements provided new insights into the mechanisms of aqueous oxidation of WSOCs by the OH. Furthermore, this new kinetic dataset was combined with the existing data to improve and expand the applicability domain of kinetic SARs.
How to cite: Witkowski, B., Jain, P., Kim, M., Pawlak, K., and Gierczak, T.: Aqueous OH kinetics of aliphatic compounds in the context of formation and evolution of biogenic secondary organic aerosols, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18364, https://doi.org/10.5194/egusphere-egu26-18364, 2026.
The goal of the CAINA (Cloud-Aerosol Interactions in a Nitrogen-dominated Atmosphere) project is to investigate multiple aspects of aerosol-cloud interactions under high concentrations of reactive nitrogen. This chemical regime is starting to emerge in many regions following the strong reduction of SO2 emissions, but is already firmly established at our study location in the Netherlands. CAINA is a consortium project that aims to combine in-situ and remote sensing observations of aerosols and clouds with chamber experiments and high-resolution modelling to study the formation of CCN, cloud chemistry, and aerosol effects on clouds.
This talk will present first highlights of the CAINA project focussing on the cloud chamber experiments and the field campaign conducted in March/April 2025.
Extensive studies in the AIDA cloud chamber have shown that substantially more secondary organic aerosol is formed under high humidity (80-90%) than at dry conditions, when liquid seed particles are present. This is accompanied with distinct differences in the chemical composition of the formed SOA. We can show considerable formation of secondary organic aerosol in the aqueous phase and that the presence of ammonium nitrate in the particles causes the formation of organic nitrogen species and other higher-order reaction products.
First results from the field campaign at a coastal and a regional background site in the Netherlands highlight the high ammonium nitrate contributions to the aerosol mass concentration and especially high gas-phase NH3 concentrations (up to 50 mg m-3) during the field campaign, indicating a chemical regime dominated by reactive nitrogen and relatively high aerosol pH. Further highlights include strong new particle formation events, as well as distinct differences in particle chemical composition between the ground and at 250 m height, particularly when clouds were overhead. A potential effect of nitrogen pollution on cloud properties will be investigated, combining ground-based data, remote sensing by cloud profilers, and in-situ cloud measurements using the helicopter-borne cloud probe ACTOS.
This work is supported by the Dutch Science foundation NWO (grant # OCENW.XL21.XL21.112) and by the ATMO-ACCESS project (ATMO-TNA-3—0000000063).
CAINA: https://sites.google.com/view/cainaproject/
How to cite: Dusek, U., Fu, J., van de Born, M., Saathoff, H., Kroese, W., Holzinger, R., Fry, J., Wehner, B., Sinha, N., Russchenberg, H., Biskos, G., Jokinen, T., and Schneider, J. and the the CAINA team: Cloud-Aerosol Interactions under high reactive Nitrogen concentrations: First highlights from chamber and field experiments of the CAINA project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18552, https://doi.org/10.5194/egusphere-egu26-18552, 2026.
In the ongoing CAINA project (Cloud-Aerosol Interactions in a Nitrogen-dominated Atmosphere) we investigate multiple aspects of aerosol-cloud interactions under the high concentrations of reactive nitrogen present in the Netherlands. Here, we present results of year-long side-by-side deployment of two aerosol composition instruments with differing size cut inlets (PM2.5 and PM10), to investigate size-dependent composition, acidity, and nitrate speciation at the Cabauw tower, in the central Netherlands. Aerosol and gaseous composition were measured by two Monitors for AeRosols and Gasses in Ambient air (MARGA 2060IC), run at adjacent locations for over 1 year of measurements. We supplement and interpret these in-situ observations using thermodynamic equilibrium models such as ISORROPIA2 and interpret potential sources aided by back-trajectory modeling using HYSPLIT. We observe strong seasonal variations, with the highest monthly average gas-phase NH3 concentration of 15 μg m-3 observed in April 2025, accompanied by large NH4NO3 aerosol concentrations (as high as the wintertime maximum) and resulting in the highest pH period of ~ 5. We interpret this low aerosol acidity in terms of its impact on deposition pathways. Mineral dust contributions appear episodically in spring and winter, dominantly in the PM10 fraction, but they occasionally constitute the majority of aerosol mass (both PM10 and PM2.5) for up to a few days.
How to cite: Fry, J. L., Ooms, P., Voorneveld, M., in 't Veld, M., Rutlege-Jonker, S., Wichink Kruit, R., van Zanten, M., and Dusek, U.: Size-resolved aerosol chemical composition, acidity, and gas-aerosol partitioning of nitrate in the Netherlands, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14194, https://doi.org/10.5194/egusphere-egu26-14194, 2026.
Atmospheric aerosol acidity governs a wide range of chemical processes, yet current global climate and chemical transport models calculate aerosol and cloud pH assuming that organic aerosol (OA) components are electrically neutral. This omission persists despite observations showing that organics comprise ~40% of global aerosol mass and frequently include weakly and strongly acidic species. As a result, a major contributor to particle-phase hydrogen ion budgets is systematically neglected in models.
Here we address this gap by introducing organic aerosol acidity into a global aerosol–chemistry–climate model. We first implement an idealized representation of OA acidity based on intrinsic bulk-phase acid dissociation, treating organic species as weak acids that contribute dynamically to aerosol hydrogen ion concentrations. This bulk-acidity case serves as an upper-limit, chemically ideal reference. To account for non-ideal behaviour under atmospheric conditions, we then introduce suppressed organic acid dissociation, representing deviations arising from surface effects in small droplets, mixed-acid systems, and other environmental constraints.
In parallel, we identify a second chemical inconsistency in the model: the oxidation of SO₂ by H₂O₂ is treated using a pH-insensitive kinetic formulation. We replace this with a pH-dependent general-acid catalysis mechanism, allowing organic acids to act as proton donors in aqueous sulfate formation. These developments are implemented first in a box-model framework and subsequently translated to the fully coupled global climate model ECHAM–HAMMOZ.
Including organic aerosol acidity substantially increases aqueous sulfate production, leading to enhanced cloud droplet number concentrations across large regions. The resulting changes strengthen shortwave cloud radiative cooling, yielding an additional cloud radiative forcing of approximately -0.6 to -1.0 W m-2, depending on the degree of non-ideality assumed. This forcing is comparable to the current uncertainty range associated with aerosol–cloud interactions, demonstrating that organic aerosol acidity constitutes a previously missing and climatically significant chemical driver that should be represented in global models.
How to cite: Sengupta, G.: Why organic aerosol acidity matters: Bridging molecular acidity and global aerosol–cloud chemistry, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12555, https://doi.org/10.5194/egusphere-egu26-12555, 2026.
Atmospheric aerosols have a significant impact on cloud formation and life cycle. Aerosols enhance cloud formation and affect microphysical and radiative properties of clouds by acting as Cloud Condensation Nuclei (CCN). Aerosol-cloud interactions are very complex, and thus accurate global-scale simulations are challenging.
Aerosol-cloud interactions occur at a microscopic level, but cloud systems are often on a scale of tens or hundreds of kilometers. Accurate modeling of all aerosol-cloud processes at such a large scale is computationally demanding. Therefore, models simulating aerosols and their interactions with radiation and clouds, are usually greatly simplified, making them inaccurate. In this study, the accuracy of a simple aerosol model HAM-Lite will be enhanced with a machine-learning component, and the enhanced model will be coupled with a global kilometer-scale Numerical Weather Prediction (NWP) model OpenIFS.
OpenIFS is used for global climate simulations and weather forecasting. It is an easy-to-use version of Integrated Forecasting System (IFS) by the European Centre for Medium-Range Weather Forecasts (ECMWF). IFS models the atmosphere in EC-Earth 3 climate model and it is developed by the European Consortium of National Meteorological Services and Research Institutes. OpenIFS will be the main atmospheric model in the upcoming EC-Earth version 4.
HAM-Lite is a simplified version of a more complex aerosol model HAM-M7. While HAM-M7 includes seven log-normal aerosol modes and a total of twenty-five tracers, HAM-Lite describes only four tracers. HAM-M7 calculates microphysical processes, like nucleation, condensation and coagulation, as well as other processes like emissions and dry and wet deposition. HAM-Lite simplifies the processes by assuming constant hygroscopicity and very simplified calculations for extinction. These simplifications make the model computationally lighter.
Since aerosol hygroscopicity and extinction are highly simplified in HAM-Lite, we will incorporate machine learning methods to provide a more accurate representation, bringing its performance closer to that of HAM-M7. Training data for the machine learning component will be produced with HAM-M7 coupled with OpenIFS. The new enhanced HAM-Lite aerosol model will also be coupled with OpenIFS for improved global scale simulations.
By coupling the new enhanced aerosol model with the climate model, the aim is to make the system more accurate without significantly increasing the computational cost. Results from OpenIFS, with and without the enhanced aerosol model, will be compared to in situ measurements, satellite data, and simulations with other models. Expectation is that OpenIFS, coupled with the light aerosol module and machine learning methods, will achieve higher accuracy with reduced computational cost compared to OpenIFS coupled with HAM-M7.
This research is funded by the European Union's Horizon EU -project Digital Twin of Earth System for Cryosphere, Land Surface, and Related Interactions – TerraDT 101187992.
How to cite: Halonen, H., Holopainen, E., Bergman, T., Laakso, A., Mielonen, T., Vartiainen, A., and Kokkola, H.: Development and Evaluation of Climate Simulations Using Machine Learning Enhanced Aerosol Model in OpenIFS Atmospheric Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3123, https://doi.org/10.5194/egusphere-egu26-3123, 2026.
Brown carbon (BrC) is a significant component of absorbing aerosols, yet its wavelength-dependent complex refractive index (CRI) remains one of the least constrained parameters in aerosol optical modeling. This study aims to constrain the imaginary part of the BrC CRI using an observation-informed physical inversion framework. We utilized in-situ absorption measurements collected in Ansan, South Korea, representing seasonal variations in 2024, alongside aerosol mass concentrations simulated by the A Global/Regional Integrated Model System-Chemistry Climate Model (GRIMs-CCM) and Weather Research & Forecasting Model (WRF) coupled with GEOS-Chem chemistry (WRF-GC) models. Optical properties were computed using the Flexible Aerosol Optical Depth (FlexAOD) system based on Mie theory. In our framework, organic carbon was partitioned into water-soluble and water-insoluble components to account for hygroscopic and compositional differences. The imaginary refractive index was parameterized as a power-law function of wavelength. By iteratively adjusting the spectral exponent to minimize discrepancies between observed and simulated Absorption Ångström Exponent (AAE) values (365–500 nm), we derived optimized CRI values. The results show that the optimized imaginary refractive index decreases monotonically with increasing wavelength, with the strongest spectral gradient observed in winter, indicative of enhanced shortwave absorption by BrC. The retrieved values align with reported ranges for strongly absorbing BrC. This study presents a physically consistent framework for improving the representation of BrC optical properties in radiative forcing assessments.
Acknowledgment: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government (MSIT) (No. RS-2025-16070879).
How to cite: Cho, H., Kim, M. J., Yang, S. H., Choi, Y., Lee, M., and Lee, S.: Constraining the Imaginary Refractive Index of Brown Carbon via an Observation-Informed Inversion Framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6214, https://doi.org/10.5194/egusphere-egu26-6214, 2026.
Quantifying the light absorption of atmospheric aerosols remains one of the more critical challenges in climate science. Black carbon (BC) and mineral dust (MD) dominate aerosol light-absorption globally, yet their mass absorption cross-sections (MAC)—the fundamental measure linking particle mass to light absorption—vary by orders of magnitude across the literature. This inconsistency stems partly from measurement artefacts inherent to existing techniques. Filter-based methods suffer from systematic errors, photoacoustic approaches introduce thermal biases, and single-particle instruments like the SP2 (Single Particle Soot Photometer) require assumptions about particle morphology that may not hold in the real ambient environments.
This project proposes a hybrid strategy that integrates two complementary measurement platforms with machine learning to address these limitations. Photo-Thermal Aerosol Absorption Monitor (PTAAM) offers high sensitivity while remaining insensitive to scattering effects, whereas the SP2 provides detailed microphysical information about individual particles. The methodological novelty lies not merely in combining these tools, but in developing advanced algorithms—particularly graph neural networks (GNNs)—to extract physically meaningful patterns from their joint data streams.
The work encompasses three interconnected objectives: first, calibrating the SP2 for dust and iron oxide detection through rigorous laboratory work with size-selected aerosols; second, establishing size- and wavelength-resolved absorption spectra using a newly developed PTAAM system; third, constructing machine learning models that fuse these measurements to produce more reliable optical property estimates. Validation occurs through both controlled laboratory experiments and field campaigns in contrasting environments.
By reducing uncertainties in aerosol light-absorption measurements, this study promises to improve climate model predictions and remote sensing retrievals—bridging fundamental aerosol physics with practical applications in understanding aerosol-radiation interactions.
How to cite: Bhardwaj, A., Močnik, G., Yus-Díez, J., and Drinovec, L.: Machine Learning Integration of PTAAM and SP2 Measurements for Enhanced Aerosol Absorption Characterization, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10475, https://doi.org/10.5194/egusphere-egu26-10475, 2026.
Quantitative analysis of aerosol particle number size distributions (PNSDs) measured with a Differential Mobility Particle Sizer (DMPS), commonly relies on modal representations to describe dominant particle populations and their evolution. While lognormal models are widely used, they may inadequately represent skewed or heavy-tailed size spectra frequently observed in atmospheric measurements. However, observational PNSD data often exhibit strong skewness, multimodality, and occasional abnormal spikes arising from instrumental noise or transient sampling artefacts, which complicate conventional fitting approaches.
We present a robust, automated fixed-mode fitting framework for aerosol multi-mode inverse-gamma (AeroMiG) distributions to measured PNSDs across large datasets. The method represents each PNSD as a superposition of inverse-gamma modes, with parameters estimated via a differential evolution technique based on global optimization methods. Model parameters, including shape, scale, and amplitude of each inverse-gamma mode, are estimated by minimizing a robust objective function that combines reconstruction error (mean squared error) and goodness-of-fit measures (R-square). To evaluate fit quality and ensure consistency across time-resolved data, standard statistical metrics such as MSE, Akaike and Bayesian information criteria, and coefficients of determination are computed for each fitted spectrum.
The framework is designed for high-throughput applications to large datasets and supports parallel processing, enabling efficient analysis of long-term aerosol observations. Application to atmospheric PNSD measurements demonstrates that fixed mixtures of inverse-gamma modes effectively capture asymmetric and heavy-tailed distribution features, providing a flexible alternative to conventional lognormal parameterizations. This approach facilitates consistent intercomparison of modal parameters across time and supports improved interpretation of aerosol processes and source contributions.
How to cite: Rahman, A., Mikkonen, S., Kangasluoma, J., Hussein, T., Petäjä, T., Tarkoma, S., and Zaidan, M. A.: Fixed-Mode inverse-Gamma Fitting of Aerosol Particle Number Size Distributions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10426, https://doi.org/10.5194/egusphere-egu26-10426, 2026.
The CERN CLOUD experiment (Kirkby et al. 2011) investigates aerosol particle nucleation and growth under controlled atmospheric conditions. To extend its experimental capabilities, a new FLow TUbe System (FLOTUS) was recently developed as an external 60 litre flow tube directly coupled to the CLOUD chamber. FLOTUS consists of a quartz tube with conical entry and exit geometries for laminar-flow, following the approach of the Caltech Flow Tube Reactor (Huang et al. 2017). The 3 m long x 20 cm diameter quartz tube is mounted vertically to minimise convective turbulence. It is housed in a temperature-controlled enclosure with a gas system independent of the CLOUD chamber. Six separately-controlled ultraviolet lamps mounted inside the FLOTUS thermal housing enable in situ photochemical production of hydroxyl radicals (OH) from water vapour and O3 up to extremely high concentrations of up to 1010 cm-3.
The chemical composition and size distribution of particles generated in FLOTUS can be characterized either at a sampling point at the exit of FLOTUS or after transfer into the CLOUD chamber. We assessed the flow conditions inside the FLOTUS quartz tube and along the transfer line to the CLOUD chamber using computational fluid dynamics simulations with COMSOL, confirming laminar flow and well-defined transport of gases and particles in both the quartz chamber and the transfer line to CLOUD. We quantified OH production rates in FLOTUS using toluene attenuation experiments.
We have used FLOTUS to generate aerosol particles across a wide range of sizes between 10-150 nm and chemical compositions, which include sulfuric acid(–ammonia), highly oxygenated organic molecules (HOM, from α-pinene and isoprene), methanesulfonic acid, and other systems. We characterized the composition and size of particle populations produced in FLOTUS directly using aerosol mass spectrometry and mobility-based size distribution measurements, and after injection into CLOUD using a suite of state-of-the-art measurement instruments to determine particle size and chemical composition.
The controlled injection of freshly formed particles enables subsequent experiments in the CLOUD chamber under novel conditions, including studies of aerosol evaporation, cloud activation, aqueous-phase processing of aerosol, and surface chemistry, all under atmospheric conditions. FLOTUS represents an important technical advancement for the CLOUD experiment by decoupling particle formation from studies under different conditions in the CLOUD chamber, increasing the experimental flexibility and enabling systematic investigations of aerosol transport, fate, and cloud chemistry interactions.
Kirkby, Jasper, et al. "Role of sulphuric acid, ammonia and galactic cosmic rays in atmospheric aerosol nucleation." Nature 476.7361 (2011): 429-433.
Huang, Yuanlong, et al. "The Caltech Photooxidation Flow Tube reactor: design, fluid dynamics and characterization." Atmospheric Measurement Techniques 10.3 (2017): 839-867.
How to cite: Sommer, E., Bhattacharyya, N., Klebach, H., Almeida, J., Mentler, B., Busato, M., Huang, Y., Lombard, D., Onnela, A., Mathot, S., Weber, S., Flagan, R., and Kirkby, J.: FLOTUS: a new FLow TUbe System for the CERN CLOUD chamber, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18689, https://doi.org/10.5194/egusphere-egu26-18689, 2026.
Black carbon (BC) is an important climate forcing agent, yet its direct radiative forcing (DRF) remains highly uncertain at the global scale, largely due to simplified representations of particle morphology and chemical mixing state in numerical models. Despite advances in particle-scale studies, global assessments still commonly assume fully internal mixing. Here, we present an implementable modelling framework that characterises particle-scale chemical heterogeneity using the mixing state index (χ) and coating volume ratio (VR). Particle-resolved simulations are employed to quantify the effects of χ and VR on BC optical properties. Machine learning is then used to map this particle-scale information onto variables accessible in Earth system models, enabling the estimation of BC radiative forcing under more realistic mixing state conditions. This framework provides a practical pathway to improve global assessments of BC radiative effects.
How to cite: Jiang, F., Liu, D., Topping, D., Coe, H., and Zheng, Z.: Constraining the Global Direct Radiative Forcing of Black Carbon via the Chemical Aerosol Mixing State Index, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10146, https://doi.org/10.5194/egusphere-egu26-10146, 2026.
The scarcity of field observations of cloud condensation nuclei (CCN) limits effective constraints on aerosol–cloud interactions. While a small number of recent studies have explored machine learning approaches based on aerosol chemical and optical characteristics, even fewer have explicitly included particle number size distributions (PNSDs). Here, we developed an observation-driven model based on XGBoost to predict CCN number concentrations (NCCN) by incorporating PNSDs and auxiliary variables. The model exhibits robust performance on the test dataset at supersaturations (SS) of 0.2%, 0.4%, and 1.0% (R2 = 0.91–0.92; RMSE = 235–381 ppbv), demonstrating excellent capability in capturing the temporal variability of NCCN. PNSDs are identified as the most influential features for NCCN prediction using the SHapely Additive exPlanation (SHAP) approach, with the dominant size range shifting from 100–150 nm at SS ≤ 0.4% to 50–100 nm at 1.0% SS. The XGBoost model was further employed to reconstruct the long-term variations of NCCN in the upper boundary layer over North China during 2007–2025. Our results show that NCCN predominantly ranges from 866 to 2104 cm-3, with higher values in spring and winter but enhanced activation ratios in summer and autumn. Interannual variability beyond seasonal influences indicates that NCCN exhibits pronounced interannual fluctuations, largely driven by changes in highly oxidized particle sources. In contrast, overall aerosol hygroscopicity and activation ratio exhibit a gradual decline. The proposed XGBoost framework not only extends long-term NCCN records but also provides new mechanistic insights into CCN activation, thereby reducing uncertainties in the assessments of aerosol-cloud interactions.
How to cite: Cui, C., Zhu, Y., Mu, J., Zhang, Y., and Xue, L.: Machine Learning Prediction of Long-term Variations in Cloud Condensation Nuclei in the upper boundary layer of North China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9404, https://doi.org/10.5194/egusphere-egu26-9404, 2026.
Understanding the role organic aerosols (OA) play in air quality, climate, and human health requires detailed knowledge of their chemical composition. For example, the volatility of OA is further a crucial piece of information in the handling of secondary organic aerosols (SOA) in atmospheric models. Various experimental approaches to assess the composition of aerosol particles have been developed (FIGAERO, VIA, etc.), but they all struggle with limited sensitivity, particularly at small particle sizes.
Here, we demonstrate a novel online filter-based system, leveraging the Thermal Desorption Multi-scheme chemical IONization inlet coupled to an Orbitrap mass spectrometer (TD-MION-Orbitrap). This system enables semi-continuous online measurements of the physicochemical properties of aerosol particles. Aerosol particles are collected onto stainless steel mesh filters positioned inside the thermal desorber unit. By adjusting the collection time, sufficient particle accumulation for analysis is ensured. The sample is then thermally desorbed at temperatures exceeding 300°C. The MION-Orbitrap provides reagent- and polarity-switching chemical analysis of the evaporated molecules at high sensitivity and mass resolution.
We describe the operating principles of this system and present results from laboratory experiments where organic and inorganic aerosol particles are produced, collected, desorbed and analysed with two different chemical ionization schemes. The quantitative performance of the system is also explored, and initial data from a field campaign further demonstrate the capability of this novel analytical technique to advance the characterization of aerosol particles.
How to cite: Holm, S., Finkenzeller, H., Shcherbinin, A., Mikkilä, J., Rissanen, M., and Kangasluoma, J.: Assessing nano-particle composition using online filter-based TD-MION-Orbitrap, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20077, https://doi.org/10.5194/egusphere-egu26-20077, 2026.
Aerosols play a critical role in the Earth’s radiation budget by scattering and absorbing solar radiation; however, their classification remains a major source of uncertainty due to overlapping fine and coarse modes, complex mixing states, and strong spatio-temporal variability, particularly over mountainous terrain. This study presents a hybrid aerosol classification framework applied to long-term (2008–2025) sky–sun radiometer (SKYNET) observations from three high-altitude sites in the Ladakh region, together with global AERONET observations spanning 171 sites across six continents from 1993 to 2025. The algorithm is tested under both climatically sensitive high-altitude environments and diverse global conditions to evaluate its robustness and credibility. The approach integrates unsupervised spectral clustering with the statistical Mahalanobis distance (MD) metric to improve aerosol regime separation in high-dimensional feature space. The spectral clustering technique, an unsupervised data-driven approach, involves three main steps: constructing a similarity graph, projecting the data into a low-dimensional space, and forming clusters. Although spectral clustering partitions the entire dataset, real aerosol regimes typically exhibit a dense core of representative observations, with transitional or mixed cases occurring at the periphery. To reduce this overlap, the MD metric is introduced to retain only the core inliers. Internal validation of the algorithm is performed using the Silhouette coefficient, Calinski–Harabasz index, and Davies–Bouldin index. A traditional threshold-based classification method is employed for external validation of the proposed framework. Using the hybrid algorithm, aerosols are classified into four types: Dust, Mixed, Absorbing, and Non-absorbing. Among the 171 sites analysed, 83 sites are dominated by Absorbing aerosols, 19 by Dust, 1 by Mixed, and 68 by Non-absorbing aerosol types. Africa is primarily dominated by dust aerosols, accounting for 50% of the sites. Absorbing aerosols dominate in Asia (67.3%), Australia (55.6%), and South America (77.3%). In contrast, Europe and North America are largely characterised by Non-absorbing aerosol types, representing 75.8% and 73.5% of the sites, respectively. A strong and statistically significant positive correlation (Pearson’s r = 0.89, p = 0.0166) is observed between the continent-wise dominant aerosol fractions derived from the threshold-based and hybrid classification methods. Individual continental comparisons reveal small deviations for Africa, Europe, and North America (<3%), identical results for Australia, and comparatively larger differences for Asia (+8.4%) and South America (−9.1%), suggesting an enhanced sensitivity of the hybrid approach in regions characterised by complex aerosol regimes. At high-altitude sites, low aerosol concentrations make the development of robust aerosol classification schemes particularly challenging. Nevertheless, major aerosol types—such as absorbing, non-absorbing, and mixed aerosols—can be effectively distinguished using spectral clustering algorithms, thereby enhancing the effectiveness of the proposed hybrid method.
How to cite: Mukhopadhyay, S. and Ningombam, S. S.: Integrating the Mahalanobis Distance Metric with Spectral Clustering: A Hybrid Aerosol Classification Algorithm, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9815, https://doi.org/10.5194/egusphere-egu26-9815, 2026.
Fine particulate matter has declined across South Korea. Yet haze episodes remain frequent in the Seoul Metropolitan Area. Understanding these events requires a mechanistic analysis of nitrate formation, a major component of fine particulate matter.
Previous box model studies have not fully represented boundary layer evolution. They also have not captured the nighttime influence of residual layer entrainment and dilution. Even multi-layer box model frameworks often assume a fixed boundary layer height. Most related studies have focused on China. As a result, quantitative evidence for the role of boundary layer mixing in the Seoul Metropolitan Area is still limited.
Here we quantified how the residual layer affects nitrate production and loss over the Seoul Metropolitan Area using KAB (Korea Air Quality Observation-Based Box Model). KAB is an emissions- and observation-constrained box model derived from the 3D chemical transport model CMAQ. We extended the conventional single-layer configuration to a two-layer structure. We also diagnosed boundary layer and residual layer heights from ERA5 reanalysis to capture day–night differences. During daytime, we assumed a well-mixed layer. During nighttime, we prescribed distinct concentrations in the two layers to represent vertical gradients and multi-layer effects.
Our results show that residual layer development and boundary layer mixing exert substantial control on nitrate variability in the Seoul Metropolitan Area. Residual layer entrainment increases surface nitrate by transporting aerosol aloft down to the ground. It also enhances aerosol formation. This occurs when undiluted precursors are converted to particulate nitrate during subsequent mixing. These findings indicate that residual layer mixing is a key driver of high haze events in this region.
Acknowledgment: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. RS-2025-16070879).
How to cite: Kim, N.-H., Kim, M. J., Park, S. H., Heo, G.-Y., Park, J.-M., and Shin, H. J.: Influence of the nocturnal residual layer on nitrate formation in the Seoul Metropolitan Area using the Korea Air Quality Observation-Based Box Model (KAB), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6178, https://doi.org/10.5194/egusphere-egu26-6178, 2026.
Atmospheric new particle formation (NPF) has been recognized as a major contributor to aerosol and cloud condensation nuclei number concentrations, exerting substantial impacts on both air pollution and climate. However, NPF vertical distribution has been left largely uncharacterized because most, if not all, NPF observations were conducted on the ground surface, which may not be representative to the situation within the whole boundary layer. Here we conduct measurements on the vertical profiles of particle number size distribution and key precursors of NPF with a high payload tethered airship in Nanjing, China. We show that, while particle size distribution displays a homogeneous feature in a well-mixed boundary layer as expected, surprising particle nucleation is frequently seen at around 600 m altitude in early morning before the mixing layer is fully developed. The nucleation aloft is associated with sulfuric acid-rich plume, likely contributed by industrial emissions, yet its intensity is limited by low sulfuric acid clustering efficiency and low abundance of condensable organic vapors. Overall, our results reveal that industrial emission acts as an important source of urban sulfuric acid and nanoparticles, unrecognizable from ground-level measurement or in well-mixed atmosphere, and that the boundary layer dynamics has a profound influence on the vertical profiling of particle number size distribution.
How to cite: Wang, Z., Nie, W., Yan, C., Liu, Y., Liu, C., Zha, Q., Zhang, Y., Xu, T., Qi, X., Zhou, X., Ge, D., Zhou, C., Yin, J., Liu, H., Chen, L., Zhu, C., Chi, X., and Ding, A.: Study on the Influence of Sulfuric Acid Plumes in Urban Residual Layers on High-Altitude New Particle Formation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6963, https://doi.org/10.5194/egusphere-egu26-6963, 2026.
Being the most important alkaline gas in the atmosphere, ammonia (NH3) can react with acidic species to form ammonium salts, which have significant impacts on air quality and human health. Laboratory studies confirm that NH3 can heterogeneously react with carbonyl groups in secondary organic aerosol (SOA) to form nitrogen-containing organic compounds (NOCs), consuming gaseous ammonia and potentially influencing ammonia levels and aerosol composition. In order to study the possible impact of this reaction, we incorporated a first-order loss rate representing the NH3-SOA uptake reaction into the WRF-Chem air quality model and conducted simulations over the North China Plain (NCP) during November 2017. With an uptake coefficient γ of 10-5, the modeled average NOCs concentration was 1.60 μg m-3, closely matching the observed average of 1.52 μg m-3. However, given the presence of other significant sources contributing to NOCs, we consider γ = 10-5 to represent the upper limit for the uptake coefficient of this specific NH3–SOA reaction. Sensitivity tests indicate only minor changes in NH3 concentrations, with an average decrease of 0.69% (0.04 μg m⁻³). The average percentage changes for NO3-, NH4+, and SO42- were -0.08%, -0.06%, and -0.01%, respectively, while SOA and PM2.5 exhibited negligible variations of -0.03% and +0.03%. These results suggest that, although the NH3-SOA heterogeneous uptake can contribute to NOCs formation, its overall effect on atmospheric NH3 and particulate matter is limited, and it does not constitute a significant factor in regional air quality modeling in NCP.
How to cite: Lu, Y.: Modeling ammonia uptake by secondary organic aerosols in the North China Plain , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10819, https://doi.org/10.5194/egusphere-egu26-10819, 2026.
Secondary inorganic aerosols undergo a phase transition between solid and liquid states as a function of relative humidity. Different aerosol phases affect their size, altering their optical properties, radiative effects, and heterogeneous chemical reactions. Despite its importance, however, state-of-the-art chemical transport models have not explicitly simulated aerosol phases because of their complex hysteresis with respect to relative humidity history. We use aerosol phase-state observations from the ASIA-AQ campaign to evaluate ISORROPIA thermodynamic calculations with different hysteresis pathways constrained with observed meteorological conditions from the campaign. Although we found a marginal difference in total aerosol concentrations with the different hysteresis pathways, simulated AODs differ significantly, depending on aerosol phase, suggesting their significance for aerosol radiative forcing.
How to cite: Chung, Y., Park, R. J., Kim, H., Lee, M., and Song, M.: Observed vs. simulated aerosol phase state during the ASIA-AQ campaign: its implication for climate forcing , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16055, https://doi.org/10.5194/egusphere-egu26-16055, 2026.
Aerosols have a wide range of impacts on climate, clouds, ecosystems and public health. Much of the properties of aerosols that affect their impacts is related to their acidity levels. However, it remains understudied and only over the recent years ambient datasets become available to constrain it. One aspect that remains highly uncertain is the distribution of pH with height; given the large differences of semi-volatile concentration species affecting pH (like NH3) as well as changes in relative humidity (that affect water content) and temperature (that affect the thermodynamic constants) we expect large changes of aerosol pH with altitude and airmass type.
High-altitude stations provide a unique opportunity to study these variations owing to their ability to sample airmasses that originate from the boundary layer close to ground, and airmasses that are in the free troposphere containing aerosol and gas-phase precursors from long-range transport. In this work, we estimate the aerosol pH at a high-altitude monitoring station during the CHOPIN (CleanCloud Helmos OrograPhic sIte experimeNt campaign, http://go.epfl.ch/chopin-campaign) and CALISHTO field campaigns at Mount Helmos, Greece. Our goal is to identify pH variations when the station is located in the free troposphere compared to periods below the boundary layer and its variability over time-of-day and over time. Relative humidity, temperature, ammonia concentrations, and aerosol chemical composition observed were used to estimate aerosol pH using the ISORROPIA lite model.
We observed hourly pH variability at the site, with lower pH values between 7 am and 1 pm, before the boundary layer reached the site and after anthropogenic ammonia mixed into the atmosphere dispersed overnight. Higher pH values were observed in the afternoon when ammonia associated with anthropogenic emissions from nearby urban and agricultural activities reached the station. SHapley Additive exPlanations analysis (SHAP) was applied to identify the variables that contribute and influence the most to the observed pH, providing a more robust and reliable attribution than other models. It was found that during the free troposphere condition, SHAP values do not vary significantly with time; however, significant differences were observed when the station is below the boundary layer.
This work was supported by the CleanCloud project funded by the EC Horizon Europe Call “Improved knowledge in cloud-aerosol interaction” (HORIZON-CL5-2023-D1-01-04).
How to cite: Molina, C., Foskinis, R., Zhang, J., Zografou, O., Granakis, K., Gini, M. I., Fetfatzis, P., Eleftheriadis, K., and Nenes, A.: Boundary Layer Influence on Aerosol pH at a High-Altitude Monitoring Station During the Chopin Campaign, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18668, https://doi.org/10.5194/egusphere-egu26-18668, 2026.
Reactions occurring within organic aerosols are a crucial factor influencing both environmental systems and industrial processes. The composition of the atmosphere is heavily impacted by aerosol composition, which in turn is a critical factor in our ability to accurately predict global climate change. To calculate the aerosol budget, a deeper understanding of the reactions within aerosol particles and their influence on particle growth is essential. Specifically, the interactions between aerosols and climate parameters, such as cloud formation and radiation balance, are of paramount importance. Analysing these processes enhances our comprehension of aerosols' effects on climate, enabling more precise integration into climate models.
In industrial processes that rely on multiphase reactions with aerosol particles, reaction rates are theoretically dependent on particle size (Petters, 2022). This understanding is vital for optimizing processes in the chemical, pharmaceutical, and environmental engineering sectors, as it directly impacts the efficiency and safety of industrial applications. To simulate these reactions and measure product formation, we coupled the developed Chemical Ionization Orbitrap inlet (CI Orbitrap) by Riva et al. (2019) with an aerosol inlet consisting of a flow-through heating cartridge and a gas cooling unit. This setup enables the analysis of aerosol particles through thermal evaporation, combining the high mass resolving power of the Orbitrap (R ≥ 140,000 at m/z 200) with the selectivity and sensitivity to oxidized compounds of chemical ionization mass spectrometry (NO3-CIMS). An activated charcoal denuder removes the gas phase of the sample aerosol before thermal evaporation, preventing sampling artifacts and ensuring high time-resolved measurements (Riva, 2019).
We observed the size dependent reaction of citric acid with 99% 11B-boronic acid, resulting in a condensation product. The equilibrium reaction shows an exchange of boron isotopes, resulting in an increased 10B percentage in the product molecule.
This work is supported by the Deutsche Forschungsgemeinschaft (DFG) under project number 416710328.
- S. Petters (2022) Res. Lett 49.
- Riva, M. Ehn M., D. Li, S. Tomaz, F. Bourgain, S. Perrier, C. George. (2019) Ana. Chem. 91, 9419-9423.
How to cite: Blum, N., Douverne, M., and Hoffmann, T.: Online monitoring of the particle size-dependent reaction of citric acid with boronic acid in aerosols, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19264, https://doi.org/10.5194/egusphere-egu26-19264, 2026.
The pH of atmospheric aerosols plays a central role in multiphase chemistry, secondary aerosol formation, gas–particle partitioning, and aerosol toxicity among other processes. Despite its importance, ambient aerosol pH remains poorly constrained, as most estimates rely on indirect thermodynamic inferences from bulk aerosol composition, which induces uncertainties associated with equilibrium assumptions and measurement limitations. On the other hand, pH-responsive substrates can provide direct aerosol pH measurements, fast and reliably. Most of these materials are sensitive to protonation that can be quantified by spectroscopic techniques. In this work, ambient aerosol acidity during the CleanCloud PIANO field campaign in Summer 2025 to Spring 2026 was investigated by combining thermodynamic pH inference with direct spectroscopic measurements using pH-responsive sensors.
The field campaign commenced in summer 2025 and is ongoing, with completion expected in spring 2026, in Patras, Greece. Daily aerosol samples (PM2.5) were collected on quartz filters using a high-volume sampler. Two different pH-responsive substrates were mounted on top of each filter. The first, consisted of polymer-based sensors made from phase-inverted polybenzimidazole (PBI) membranes, whose protonation response was analyzed by Raman spectroscopy. The second substrate employed the low-molecular-weight imidazole probe 2-mercaptobenzimidazole (2-MBI), applied on the filters and analyzed using surface-enhanced Raman spectroscopy (SERS). In both cases, aerosol pH was quantified using laboratory-derived calibration curves, providing a daily pH over the sampling period. Additionally, the other half of the filter was used for offline chemical analysis.
Real time measurements were conducted using an aerosol mass spectrometer (AMS), an ammonia (NH₃) monitor, and a VOCUS chemical ionization time-of-flight mass spectrometer (VOCUS-CI-TOF) to characterize the gas and particle phases. Thermodynamic aerosol pH was inferred with ISORROPIA-lite using 30-min averaged AMS inorganic composition (SO₄²⁻, NO₃⁻, NH₄⁺, Cl⁻), relative humidity, and temperature. Calculations were performed in forward mode under the metastable aerosol assumption, and the resulting pH was aggregated to 24-h averages for comparison with the substrate-based spectroscopic measurements. The spectroscopic and thermodynamic pH estimates show consistent temporal behavior and comparable acidity levels.
This combined observational framework provides complementary and independent constraints on ambient aerosol acidity with diverse techniques. It also demonstrates the potential of Raman-based pH sensors deployed on common aerosol samplers to augment thermodynamic pH estimates in field studies.
This work was supported by the CleanCloud project funded by the EC Horizon Europe Call “Improved knowledge in cloud-aerosol interaction” (HORIZON-CL5-2023-D1-01-04).
How to cite: Theodoropoulos, G., Molina, C., Zhang, J., Mitsios, C., Kaitsa, I., Soto Beobide, A., Voyiatzis, G. A., and Nenes, A.: Ambient aerosol pH during the CleanCloud PIANO campaign inferred from thermodynamic analysis and spectroscopic pH sensors, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18381, https://doi.org/10.5194/egusphere-egu26-18381, 2026.
Nitrate is a major inorganic aerosol and a dominant component during air quality events in central Taiwan. This study analyzes a haze episode with record-high PM2.5 levels, peaking at 110 µg/m³ in central Taiwan’s urban areas (UAPRS) on 4–5 November 2021. During this event, PM2.5 at UAPRS averaged 29.0 µg/m³ in the daytime and 89.7 µg/m³ at night. Notably, nitrate rose sharply from 4.4 to 39.0 µg/m³, accounting for 43.5% of the nighttime PM2.5 increase in central Taiwan on the event day.
Simulation results indicated that the lee-side vortex, driven by the interaction between the ambient flow and the Central Mountain Range (CMR), facilitated the accumulation of pollutants, transporting them northward to the ocean and then returning as the ambient wind direction changed from easterly to southeasterly. Additionally, the swept-back plume in the afternoon, driven by the lee-side northwesterly flow and overlaid with urban pollution, was a key contributor to the first PM2.5 peak at 20:00-22:00 LST on November 4. The mechanisms study revealed that nitrate aerosol was dominant, with N₂O₅ hydrolysis playing a critical role in its formation in the nocturnal atmospheric chemistry. Furthermore, the convergence of the lee-side northwesterly flow with the mountain downslope wind at midnight, combined with the reduction in planetary boundary layer height, enhanced the second PM2.5 peak, which occurred between 02:00 and 03:00 LST on November 5. The findings of this study can be applied to other regions with similar complex topography, pollution environments, and comparable relief.
How to cite: Lin, C., Chen, W.-M., Sheng, Y.-F., Chen, W.-C., Cheung, H. C., and Chou, C. C. K.: Exploration of complex physical and chemical processes of a severe urban pollution episode over central Taiwan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6703, https://doi.org/10.5194/egusphere-egu26-6703, 2026.
To investigate the formation and dissipation mechanisms of severe winter haze in Changsha, this study presents a comprehensive analysis of a typical heavy haze episode from December 29 to 31, 2025, based on continuous ground-based multi-wavelength polarization lidar observations combined with near-surface PM2.5 and meteorological data.
Lidar profiling identified a stable pollution aerosol layer of 300-500 m, closely coupled with surface pollution. The episode evolved through four distinct stages. In the initial stage (daytime, 29th), a PM2.5 concentration of ~140 μg/m3, an extinction coefficient of ~1.8 km-1, and a depolarization ratio of 0.17 indicated the presence of mixed aerosols dominated by relatively dry fine particles. The explosive growth stage (17:00-19:00, 29th) was critical, where under stagnant conditions with rising relative humidity (~70%), PM2.5 surged from 134.6 to 244.2 μg/m3. The concurrent increase in the extinction coefficient to 2.3 km-1 and a slight decrease in the depolarization ratio to 0.15 confirmed rapid pollutant accumulation in a compressed boundary layer, with newly added particles being more hygroscopic and spherical. During the mature stable stage (evening 29th to morning 31st), pollution peaked and plateaued (PM2.5: 280-350 μg/m3). The high extinction coefficient (2.5-4.0 km-1) and a further reduced depolarization ratio (0.11) signified fully aged aerosols dominated by hygroscopic, spherical secondary inorganic particles. In the wet scavenging stage (after 12:00, 31st), driven by precipitation and wind, PM2.5 plummeted from 357.8 to 53.4 μg/m3 within 8 hours. Notably, the extinction coefficient temporarily peaked near 5 km-1, and the depolarization ratio increased to 0.2, clearly capturing the scavenging signal from non-spherical raindrops.
This study delineates the complete life cycle of "stagnant accumulation—explosive growth—sustained high pollution—removal by wind and precipitation". The core finding is that the co-evolution of lidar-derived extinction coefficients and depolarization ratios visually elucidates the microphysical processes governing pollution accumulation, aerosol aging, and wet removal. It confirms that polarization lidar is an indispensable tool for dynamically discriminating aerosol phases and quantifying pollution evolution, providing crucial scientific support for understanding haze formation.
How to cite: Lan, M., Zhou, L., Long, Q., Chen, J., Xu, J., Liu, L., Zhang, J., Zhou, H., and Huang, R.: Unraveling the Life Cycle of a Severe Winter Haze in Changsha with Polarization Lidar, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8034, https://doi.org/10.5194/egusphere-egu26-8034, 2026.
During the Saharan Dust Event (SDE) in February 2021, dust clouds were transported from the Moroccan-Algerian border to Central Europe. In Western Switzerland, large particles up to 300 µm in size falling to the ground were observed in situ. The large "particles" were multimineral spherical aggregates, termed iberulites (IF) after their first recording on the Iberian Peninsula (Díaz-Hernández et al., 2008). The cores contain coarser grains, lacking a visible cement matrix, and have a thin, dense surface layer of much smaller particles. The Particle Size Distribution (PSD) inside the iberulites is ±monomodal, with a maximum at 2.5 µm, i.e., much larger than the value, i.e., 0.2 µm, for Saharan dust sampled at the JungFrauJoch (JFJ) station in the main dust layer. The PSD of the particles inside the iberulites shows a minimum where the JFJ has a maximum, i.e., between 0.1 and 1.0 µm.
The atmospheric conditions during the IF were well documented (meteorological station in Payerne close to Frribourg!). In contrast to the previous IFs observed in the Iberian Peninsula, this IF occurred under lower-temperature conditions, e.g., near the freezing point in the cloud and at the surface. Two mechanisms have been envisaged for aggregating a large number of dust particles (Díaz-Hernández et al., 2008) 1. The coalescence of drops within a cloud increases the number of particles within a single growing drop (In-Cloud Scavenging, ICS), or 2. the particle concentration increases by collisions of drops with the latter below the cloud (Below-Cloud Scavenging, BCS). The BCS rate (= collection efficiency, CE) depends on particle size (Slinn, 1977).
Particles >1µm will be included by impaction, and CE is taken as 100%. However, for particles with radii between 0.3µm and 1µm, the CE is <<1. Particles with radii within the size span given above, despite being on collision trajectories, follow the flow lines and are sent around the latter, whereas very small particles (< 0.1µm) may be pushed by Brownian motion and deposited on the droplet's rear end (Brownian capture), and CE is also close to 1. For particles with radii between 0.3 and 1.0 µm, CE decreases by two orders of magnitude. This decrease in CE was first described by Greenfield(Greenfield, 1957) and is therefore referred to as Greenfield gap. The temperature at the upper boundary of the dust layer was below 0°C, and scavenging occurred by frozen hydrometeors, which are known to be better scavengers of aerosol particles than rain. The presence of a Greenfield gap in the iberulites collected in western Switzerland indicates that below-cloud scavenging is the probable formation mechanism
Díaz-Hernández, J. L. and Párraga, J., 2008., Geochimica et Cosmochimica Acta, 72, 3883–3906
Greenfield, S. M.,1957, Journal of Meteorology, 14, 115–125
How to cite: Grobety, B., Favreau, P., Rausch, J., Jaramillo, D., and Neururer, C.: Sahara dust event of 06.02.21 in Switzerland: Iberulite fall and formation mechanism, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10715, https://doi.org/10.5194/egusphere-egu26-10715, 2026.
As the largest tropical forest with approximately 4.7 million km2, the Amazon rainforest has a significant impact on regional and global climate. Atmospheric aerosols critically shape Earth’s climate by scattering and absorbing solar radiation and by influencing cloud formation and precipitation. Pristine regions such as the Amazon provide a glimpse of pre-industrial atmospheric conditions and are particularly important for assessing climate change. Previous studies have investigated aerosol concentrations, properties, and sources as a function of seasonality and diurnal variation [1–3]. However, the identity and interplay of natural aerosol sources, and their relevance to overall aerosol cycling, remain poorly understood.
In particular, the formation and growth of particles smaller than 100 nm is still uncertain. The very small masses of ultrafine particles present a major analytical challenge, resulting in an incomplete understanding of their origin and properties. Here, we propose two approaches that could provide new insights into the aforementioned questions. The first is size-resolved aerosol flux measurements to determine whether and when ultrafine particles are transported out of or into the canopy. The second is a chemical analysis of characteristic tracers in sub-100 nm aerosol samples.
Aerosol exchange between the forest and the atmosphere is driven by turbulence, influencing both deposition and emission of particles. To obtain turbulent fluctuations with high time resolution we applied the eddy covariance method (ECM) at 52 m on the 80 m walk-up tower at the Amazon Tall Tower Observatory (ATTO). Using 10 Hz eddy covariance measurements of 3D wind and size-resolved particle concentrations, we aim to quantify this exchange to improve our understanding of biosphere–atmosphere interactions. This approach yields a unique long-term dataset of size-resolved aerosol particle fluxes in the Amazon, enabling the investigation of biogenic aerosol exchange and the turbulent transport of nutrients. Preliminary analysis suggests pronounced diurnal cycles and seasonal variability in aerosol fluxes.
Additionally, we focus on the chemical characterization of sub-100 nm aerosol particles. Due to the major analytical challenges, we have applied a 'nanobulk' method combining spot sampler technology with scanning transmission X-ray microscopy and near-edge X-ray absorption fine structure (STXM-NEXAFS) spectroscopy. With this approach we collect and chemically characterize ultrafine particles under clean rainforest conditions. By sampling pristine background and new particle formation events, we aim to investigate potential differences in aerosol particle composition under varying atmospheric conditions.
The chemical characterization of ultrafine particles shows consistent spectroscopic signatures across all samples and deposition spots without major differences as a function of pollution and sub-100 nm events. Spectroscopic signatures suggest the predominance of secondary organic aerosols. Surprisingly, biogenic potassium salts could not be observed below 100 nm, yet they are very abundant at sizes larger than 100 nm.
[1] Artaxo et al., Tellus B: Chemical and Physical Meteorology, 74, 24–163, 2022
[2] Franco et al., ACP, 22, 3469-3492, 2022
[3] Valiati et al., ACP, 25, 14923-14944, 2025
How to cite: Englert, J., Tsokankunku, A., Quaresma Dias-Júnior, C., Held, A., Harder, H., Geis, D., Chilinski, M., Brill, S., Backes Meller, B., Pöschl, U., and Pöhlker, C.: Flux Measurements and Chemical Characterization of Ultrafine Aerosol Particles in the Amazon, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20135, https://doi.org/10.5194/egusphere-egu26-20135, 2026.
Biomass burning (BB) emissions have constituted an important source of ambient air pollution. Previous studies have focused on the impact of open BB (OBB) emissions on the regional air quality and climate, while it remains elusive about the effect of residential BB (RBB) emissions on the particulate matters (PM) pollution and regional climate. The WRF-Chem (Weather Research and Forecast model coupled with Chemistry) model has been used to evaluate the contribution of RBB emissions to the PM pollution in the Guanzhong Basin (GZB) during the persistent air pollution episode from December 14, 2020, to January 6, 2021 in this study. The RBB emission in the GZB is a significant source for primary aerosols under current conditions, with average contribution of 62.8%, 35.9%, and 33.4% for POA (primary organic aerosols), EC (element carbon), and primary PM2.5 (PM with aerodynamic diameter equal or less than 2.5 µm), respectively. The RBB emissions in the GZB also play an important role in the formation of SOA (secondary organic aerosols), with the average contribution of 52.6% to the SOA during the study period. Additionally, the RBB emissions in the GZB are also responsible for 4.6%, 9.4%, and 8.4% of the sulfate, nitrate, and ammonium, respectively. Therefore, the contribution of RBB emissions in the GZB to the near-surface PM2.5 mass concentrations during the simulation period is around 29.2% (18.4 μg m-3) averaged over the GZB. It is noted that the O3 concentration is slightly decreased by 1.6 μg m-3 (4.1%) averaged over the GZB with the exclusion of RBB emissions, which is might be resulted from the small decrease in NO2 concentration (5.9% or 2.0 μg m-3). Besides, the RBB emissions in the GZB contribute 16.4% (1.0 μg m-3) to the NH3 concentrations during the study period. Our results show that the RBB emissions should be considered in the air pollution control strategies for further alleviation of the wintertime PM pollution in the GZB under current conditions.
How to cite: Li, X.: Impact of residential biomass burning emissions on the wintertime particulate pollution in the Guanzhong Basin, China: a case study, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20457, https://doi.org/10.5194/egusphere-egu26-20457, 2026.
Winter smog episodes in Central European cities are associated with a significant increase in aerosol mass and optical effects. In this study, we have analyzed winter smog episode that occurred in January in Wrocław, using an integrated set of in situ measurements taken at an urban background location. Particle size distributions in the diameter range 10 - 800 nm were measured using a scanning mobility particle sizer (SMPS, TSI model 3938) and combined with total particle number concentrations obtained from a condensation particle counter (CPC, TSI model 3750). Aerosol optical properties were characterized using light scattering and backscattering coefficients measured at three wavelengths - 450, 525, and 635 nm with an Aurora 4000 nephelometer. Absorbing aerosol was quantified as equivalent black carbon (eBC) using a filter-based aethalometer (Magee AE43). The dataset was analyzed with different time resolutions to characterize changes before, during, and after the smog episode. During the episode, total particle concentrations and scattering coefficients increased significantly, while the relative contribution of ultrafine particles (<100 nm) decreased, indicating a shift towards larger particle sizes. This was accompanied by an increase in Ångström scattering exponents and an increase in the backscattering fraction, consistent with an increase in aerosol due to condensation and coagulation processes.
How to cite: Kopeć, W., Drzeniecka-Osiadacz, A., and Werner, M.: Multi-instrumental investigation of aerosol microphysical and optical evolution during a winter smog episode in Wrocław, Poland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20932, https://doi.org/10.5194/egusphere-egu26-20932, 2026.
Marine dimethyl sulfide (CH3SCH3, DMS) is a major source of natural gas-phase sulfur emissions. Moreover, DMS oxidation products such as methane sulfonic acid (CH3SO3H, MSA) and sulfuric acid (H2SO4) are known to influence the formation of cloud condensation nuclei (CCN). Recently, a stable intermediate formed from DMS oxidation, hydroperoxymethyl thioformate (HOOCH2SCHO, HPMTF), has been shown to sometime exceed mixing ratios of 100 ppt in the marine boundary layer. This product would thus be able to delay the formation of sulfate aerosols and could have a significant impact on cloud formation. In order to investigate these species, a cruise field campaign in the Atlantic Ocean was organized in 2025 to measure pristine marine air. However, we also sampled air masses coming from the Canadian wildfires that occurred early June 2025, which allowed for comparison between pristine marine air and biomass burning (BB) periods. Oxidation products were measured using a time-of-flight chemical ionization mass spectrometer (Vocus 2R-ToF-CIMS) coupled with a Filter Inlet for Gas and Aerosols (FIGAERO inlet), allowing measurements of both gas- and particle-phase chemical composition from one instrument. This FIGAERO CIMS alternated between iodide and bromide reagent ions. Based on the measurements with the iodide reagent ion, the relative distribution between DMS-derived sulfur containing species and oxygenated organic compounds (CHO) remained similar across the two periods, both for gas- and particle-phase. Indeed, the abundance of these species significantly increased by similar factors (2.5 and 2.2 times higher for sulfur containing species and organics, respectively) during the BB period for particle-phase compounds. Particle-phase MSA and H2SO4 were 2.7 and 1.5 times higher, respectively, during the BB period compared to the pristine marine environment. Similarly, many particle-phase CHO species were enhanced during the BB period. Such species include C6H10O5 (levoglucosan, 23 times higher), C4H4O6 (13 times higher), C6H8O6 (12 times higher), C3H4O5 (11 times higher) and C2H2O4 (3 times higher). Contrariwise, HPMTF, both in gas- and particle-phase, was more abundant during the pristine period compared to the BB period. As HPMTF is known to be removed by cloud uptake, this could indicate that biomass burning periods, loaded with sulfate aerosol, could result in higher cloud coverage, which would lead to higher HPMTF sink. Indeed, the irradiance measured from the ship was lower during the BB period compared to the usual pristine period irradiance. This could indicate that HPMTF was either less produced from marine DMS during this period due to lesser irradiance, or experienced higher sink due to enhanced cloud coverage, or both. This work shows that biomass burning can significantly change the abundance of DMS-derived compounds. As wildfires become more common due to global warming, it is important that these changes be considered for accurate modelling and predictions.
How to cite: Sari Doré, F., Wu, R., Matthews, E., Wu, C., Bannan, T., Coe, H., Archibald, A., and Hallquist, M.: Chemical composition differences in gas- and particle-phase organic and DMS-derived oxidation products between a pristine marine environment and a wildfire-influenced marine air mass, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21632, https://doi.org/10.5194/egusphere-egu26-21632, 2026.
Atmospheric aerosols represent one of the largest sources of uncertainty in estimates of future climate predictions. A key challenge arises from the large variety of aerosol types differing in physical properties, e.g. size and shape, and chemical composition as well as concentration. Coastal regions are particularly complex environments, where natural and anthropogenic aerosols co-exist, mix and interact, often fundamentally altering their original properties. At the same time, coastal areas are densely populated, hosting approximately 40 % of the global population. Consequently, improved knowledge of aerosol properties in coastal regions is essential not only for climate studies but also because of their relevance to human health.
The aerosols’ optical properties, defined by their interactions with sunlight through scattering and absorption, provide valuable insight into both their physical and chemical properties. The wavelength-dependent light scattering signal can be predominantly related to the particles size, while the wavelength-dependent absorption signal rather more reflects the aerosol particles’ chemical composition. By combining these types of information within a so-called Ångström matrix, the aerosol sources and types can be assessed.
In this work, aerosol optical properties were measured at three different coastal sites representing contrasting environments to identify dominant aerosol sources and types. Measurement campaigns were conducted in an urban environment at Aarhus Bay, Denmark, a rural environment at Askö, Sweden and a pristine Arctic environment at Villum Research Station, Northwest Greenland. Wavelength-dependent scattering coefficients were measured using a nephelometer (AURORA 3000, Ecotech) and wavelength-dependent absorption coefficients were obtained by an aethalometer (AE33 or AE36s, MAGEE). In addition, aerosol number size distributions were measured and air-mass back-trajectory analysis was performed. One intense measurement campaign of approximately five weeks was carried out at each site between spring 2023 and spring 2025. The resulting datasets were analysed regarding dominant aerosol sources, determining the importance of natural vs. anthropogenic emissions and locally emitted vs. long-range transported aerosols.
How to cite: Rosati, B., Skønager, J. T., Teng, Z., Salter, M., Foskinis, R., Evangeliou, N., Nenes, A., Skov, H., and Massling, A.: Source Attribution of High-Latitude Aerosols Based on Multi-Wavelength Optical Properties, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11907, https://doi.org/10.5194/egusphere-egu26-11907, 2026.
Wildfires are a significant source of atmospheric aerosols and can strongly affect regional air quality. In April 2023, a large wildfire occurred in Hongseong, western Korea. This study investigates the impact of the Hongseong wildfire on the chemical, physical, and optical properties of atmospheric aerosols observed at the Anmyeondo site. Quasi-real-time aerosol measurements were analyzed to examine variations in aerosol mass concentration, size-related characteristics, and optical parameters, as well as chemical composition, before, during, and after the wildfire event. Source apportionment analysis was applied to identify contributions from biomass burning relative to other emission sources. During the wildfire period, enhanced aerosol loading and biomass-burning-related components were observed, accompanied by changes in aerosol optical behavior. These results indicate that the Hongseong wildfire had a notable influence on aerosol properties at Anmyeondo, including both chemical composition and optical characteristics, despite the site being located downwind of the fire region. This study highlights the role of regional wildfire events in modifying aerosol physical and radiative properties at coastal background sites and emphasizes the importance of integrated observations for understanding wildfire impacts.
How to cite: Bu, J.-O., Ko, H.-J., Yoo, H.-J., Oh, S.-M., Kim, S.-M., and Kim, S.-B.: Influence of the 2023 Hongseong Wildfire on Atmospheric Aerosol Properties at Anmyeondo, Korea, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14913, https://doi.org/10.5194/egusphere-egu26-14913, 2026.
