The present project aims to provide a contribution to the characterization of the dust component from Iceland capable of being transported over great distances towards Svalbard. A sampling campaign of sediments, resuspended dust and aerosols was carried out in Icelandic dust hot spots. The sediment samples underwent resuspension tests in a dust resuspension/sampling chamber designed for the purpose. All the samples were analysed by ICP-MS and SEM-EDS methods in order to compare soil, dust and aerosol samples, and finally compared with aerosol samples from Ny-Ålesund and Hornsund Arctic stations. The results of the geochemical investigation are reported and discussed.

The metal-bearing airborne particles pose obvious risks to human health.This study aimed to characterize and identify the sources of atmospheric dust collected around an open pit mine and hydrometallurgical plant on the Congolese Copperbelt. PM was collected using a Dekati 3-stage cascade impactor at eight sampling points around the mining site. Results indicated that PM2.5 concentrations ranged from 146 to 380 μg m-3. Silicon and related detrital elements: Al, K, etc. were abundant in all size fractions and showed a decreasing trend with PM size. Dust from dry mine dumps, rock blasting, and terrigenous sources were the main sources identified.

Stubble burning (SB) in North-Western India significantly impacts air quality, particularly post-monsoon. To study fresh SB aerosols, we conducted the STUB-BURN campaign at a rural site in Punjab using CARLab, a mobile research platform with real-time PM₂.₅ and gas analyzers. Sampling period was from Oct 27–Nov 18, 2023 and we identified ten plume events based on CO and BB% enhancements. Emission factors (EFs) were estimated for key species. These first-of-their-kind regional EFs will aid emission inventory refinement and chemical transport modeling, providing crucial insights into agricultural residue burning emissions and aerosol evolution in N-W India.

Radiative properties and cloud condensation from wildfire aerosols depend on organic coatings and on the distribution of optically and nucleation-active substances across the particle ensemble. We show the distribution of hydrophilic molecules and hydrophobic polyaromatic hydrocarbons in a boreal forest smoke experiment. For the water-soluble phase, glyoxal and methylglyoxal are emitted directly from the combustion and oxalate is rapidly formed upon ageing. The co-existence of hydropobic, optical absorbing PAHs and hydrophilic oxalate on the same particles indicates that the resulting lensing and droplet activation are highly prevalent in wildfire smoke and need to be considered in models.

This study investigates Polycyclic Aromatic Compounds (PACs) in Heraklion, Greece, through a three-year monitoring campaign (2022–2024). Seasonal variations reveal significantly higher PAC concentrations in winter, driven by residential biomass burning, while summer levels are influenced by traffic and shipping. Benzo[a]Pyrene (B[a]P) and oxygenated PAHs (OPAHs) exhibit concentrations up to 18 times higher in winter. Carcinogenic risk assessment (BaPeq) indicates a 16-fold increase in winter. These findings provide critical insights into PAC sources and exposure, emphasizing the need for targeted air quality management strategies in urban Mediterranean environments.

Black Carbon (BC) particles contribute to air pollution and climate change. Its health impacts extend beyond respiratory diseases. Studying BC translocation into human tissues explores the mechanisms of adverse outcomes. The placenta provides tissue for understanding BC impacts on this organ and embryo/fetus, and for developing prevention strategies. Thus, measured tissue dose metrics provide an epidemiological tool to related exposures to a variety of health outcomes in the woman, fetus, and resulting child. A microscopic methodology for quantifying BC particles in human placental histology slides free of artifacts was developed in which the transplacental movement of BC particles were determined

The transportation sector emits ultrafine particles (UFPs), impacting air quality and health. A co-culture model of bronchial, macrophage, and endothelial cells was exposed to emissions from six transportation sources, including road, marine, and aviation. Fresh and aged emissions were tested using the oxidation flow reactor PEAR. Cytotoxicity, barrier integrity, and inflammation were assessed via LDH, TEER, and IL8. A hazard ranking using weighted Power Weakness Ratio (wPWR) for multi-criterion decision making identified fresh CNG and diesel as most hazardous. Ageing generally reduced toxicity, especially for diesel, while marine fuels showed minimal change.

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous organic compounds from human activities like industrial processes and vehicle emissions. Recent studies are focusing on PAH derivatives (nitro-PAHs and oxy-PAHs) produced from incomplete combustion and photochemical reactions in atmosphere known for their high toxicity and limited emission sources knowledge. This work deals with the determination of PAH, Nitro- and Oxy-PAH concentrations in two sites located in Sacco River Valley (IT) and on the investigation of possible relationship between local emission source and PHAs and their derivates concentration. In addition, correlation with oxidative potential were evaluated and risk assessment analysis was performed.

The WellHome study focused on indoor air quality inside and outside over 100 homes in London to identify dominant air pollution exposures across the indoor:outdoor continuum. Air quality measurements were sampled in three rooms in each house during two 4-week campaigns using 60 small sensors. To ensure comparability between homes a robust quality assurance calibration program was designed to account for source specificity for home activities. Our findings demonstrate significant drift in pollutant responses for the sensors and by challenging the sensors with different PM_2.5 sources we showed that the PM_2.5 sensors had a lower sensivitivity to some indoor sources.

In low-income countries, resource shortages limit student training and research opportunities. At Arba Minch University, Ethiopia, low-cost sensor (LCS) development and research with students (student science) addressed this challenge for air quality research. A locally developed PM_2.5 sensor system was validated at ambient and indoor locations, showing strong intra-correlation (r≥0.97) and accuracy versus gravimetric methods (r≥0.95). More than 50,000 hours of data across 16 locations were collected, 7,048 of which by undergraduate students. LCS development and student science provided local training and reliable data at costs under €1,500, making air quality research more accessible to Ethiopian universities.

With the decrease of electronic component prices, powerful yet low-cost optical particle counters (OPCs) gain in popularity. Sensor performance and long-term accuracy must be evaluated in order to maintain data quality. During a measurement campaign focusing on Arctic dust emission (HiLDA), we deployed seven measurement stations, equiped with four Alphasense OPC-N3 low-cost OPCs. In this work, we present a correction scheme for cross-dependencies of the measured data and different aging effects.

Low-cost sensors (LCS) can complement the current air pollution measuring network by increasing the density of the measurements collected. This additional data can be used to provide crucial information, which can be used to improve the air quality for everyone. With data collected using LCS and novel methodologies we managed to generate information which expand our understanding of air pollution, the sources driving it and their range of effect in a spatial resolution that was not possible before. Furthermore, by testing different ML methodologies we managed to fill spatial and temporal air quality data gaps and predict their future trends.

Aerosol remote sensing relies on retrieving key properties such as size distribution or single scattering albedo from measurements of the aerosol light scattering phase function (angular distribution), thereby relying on sophisticated retrieval algorithms such as GRASP. We present in situ measurements of such phase function data during using a novel Inverse Multi-Angular Polarimeters with Polarization. Measurements were taken in Granada, Spain, and a nearby mountain site in the Sierra Nevada. This provides detailed characterization of aerosol optical properties, in addition to extensive testing of GRASP retrieval results against parallel independent aerosol property measurements and remote sensing data.

The 9-wavelength Aethalometer AE36s (Aerosol Magee Scientific) was used to characterise aerosol type based on the absorption Ångström exponent in the long and short wavelenth range (2D AAE) across multiple European sites. Results from the 2D AAE approach revealed clear separation of different aerosol types (e.g. traffic-related BC, biomass burning, Saharan dust). This method enhances souce apportionment in urban environments, improves pollution source identification, and enables better detection of special events like Saharan dust intrusions.

This study evaluates the Aethalometer approach for equivalent black carbon (eBC) source apportionment across 16 European sites using site-specific Absorption Ångström Exponents (AAE_LF and AAE_SF, 470–950 nm). By harmonizing eBC mass concentrations and absorption coefficients in historical and near real-time AE33 datasets, the study emphasizes the necessity of site-specific calibration over fixed AAE values. A percentile-based method effectively refines source apportionment, using summer-derived AAE_LF (1st percentile) to minimize brown carbon (BrC) influence and winter-derived AAE_SF (99th percentile) to enhance BrC detection. Despite the strong correlation with m/z 60 tracer (R² = 0.78), methodological limitations persist in high-traffic and BrC-influenced sites.

In this study we present the results from a laboratory campaign that took place in summer 2024 at the Northern Forestry Center in Edmonton, Canada, where we performed biomass burning experiments to analyze their coathing thickness and mass absorption cross-section properties. To this end, we performed over 40 controlled burns over fuel types characteristic of Canadian wildfires and domestic heating were burned, including, grass, ponderosa pine, peat, mulch and mixtures mulch with peat. To measure their coating thickness we used a CPMA-SP2 tandem configuration, and for measuring the aerosol particles absorption we used a PTTAM-2λ.

Warming in the Arctic can be exacerbated by light absorbing particles, i.e. black and brown carbon (BC and BrC) originating from near-Arctic biomass burning sources.The projected rise in boreal fires driven by climate change will likely enhance the deposition of light absorbing particles onto the Arctic. Aerosol emission characteristics from Eurasian boreal fires present important gaps in knowledge, and the atmospheric transformations of those particles may induce changes in the radiative properties that are not fully constrained. In this work, the effects of combustion conditions and atmospheric aging on the light absorbing particles from boreal forest surface fires were studied.

Particulate matter from wood combustion has a significant impact on climate and human health. Black carbon and freshly emitted brown carbon are strong light absorbers. During aging, the particles become less absorbing, or some originally colorless particles become light-absorbing. The secondary formed particles also modify the optical properties of the original emission.

Aerosol sample from wood combustion was measured with the new Aethalometer (AE36s), which has spectral resolution of nine wavelengths. The measurements were performed in the simulation chamber of the CEAM-EUPHORE research center in Valencia, Spain. Flaming and smoldering burning conditions were separately investigated and compared to diesel emission.

Romania's Bucharest faces air pollution issues. RADO-Bucharest, a three-component ACTRIS national facility, provides the opportunity to assess the levels and properties of contaminants within a region using high-time resolution data. The 10-year analysis of carbonaceous aerosols mass concentration daily variability at site points to biomass burning as a source of increased concentrations during the cold season. Mobile monitoring campaigns were performed during the warm and cold periods to capture air pollution variability in Bucharest. The retrieved air pollution maps show the contribution of diverse areas to air pollution, gradients in particle concentrations between areas, and individual exposure along roads.

African nations have part of the economy informal with street dealers selling goods while being exposed to pollution from vehicles. A survey was conducted to assess their level of awareness and exposure to particulate matter in the city of Thiès, Senegal. A Particle Plus 8301-AQM2 Series measured particles concentrations. More than 40% of participants declared to be often affected by cough, headaches, cold and sore throat. Measured PM_2.5 and PM₁₀ concentrations were in the range of 25-75 and, 250-700 µg/m³, respectively. Therefore, it is recommended that measures being taken to inform and help street dealers monitor their health and safety.

In this paper, the use of the model organism D. melanogaster is proposed to study PM-induced adverse effects. Individuals of D. melanogaster were exposed under laboratory conditions to increasing concnetrations of brake dust and in situ in an art ceramic factory at 4 selected sites each representative of a different work process. For both exposures analyses included element bioaccumulation, antioxidant enzymes, NMR metabolomics, and oxidative stress were performed. Results showed metabolic alterations and oxidative stress, varying by exposure. D. melanogaster bioaccumulation correlated with PM₁₀ composition. This highlights D. melanogaster's potential as a PM toxicity assessment tool.

A case study in Mordelles (France) examined the relationship between airborne pesticides and agricultural activities using a monitoring station. Data on pesticides use came from a national sales database, while farming practices were gathered from a local survey and meteorological data from official records. Herbicides, especially prosulfocarb and pendimethalin, showed seasonal peaks, linking application periods to air concentrations. The detection of banned lindane highlights its persistence. Triallate, though not sold or applied locally, was also present, demonstrating pesticide mobility. Additionally, the survey identified 54 unmonitored substances, revealing the need for adaptations in national surveillance lists to better reflect regional practices.

Recent advances in sensing technologies and community engagement have resulted in mobile air quality monitoring tools, enabling data collection at unprecedented scales. This study presents outcomes from mobile monitoring campaigns with citizens carrying portable instrumentation for black carbon (BC), ultrafine particles (UFP) and particulate matter (PM) in Rotterdam (NL), Barcelona (ES) and Warsaw (PL). Results show spatiotemporal and seasonal variability of the pollutants and allowed identification of specific cold- and hotspot locations. A data processing workflow for mobile air quality measurements is proposed including (i) instrument validation, (ii) spatial aggregation and (iii) temporal correction to obtain representative air quality maps.

This study compares the performance of machine learning and land use regression models to estimate the concentration of Black Carbon (BC), Ultrafine Particle Number Concentration (PNC), PM_¹⁰, and PM_2.5 in Zurich City, Switzerland. High spatial resolution (50 m x 50 m grid) models were succesfully developed and externally validated. Among four algorithms (LM-LUR, GAM, RF, XGBoost), RF stands out as the most optimum with fair R² range of 0.74 - 0.87 for four pollutants. All models were derived from small-scale monitoring campaign utilizing low-cost sensors. This approach could be implemented in country/ city with lack of large scale monitoring network.

Children are particularly vulnerable to indoor air pollution and school environments significantly contribute to their overall exposure. This study, part of the InChildHealth project, examined PAH and BC levels in schools and homes in Barcelona, located in different areas. Results showed higher concentrations in urban intensive-traffic sites in colder months and rural areas that were affected by wood combustion. Poor ventilation and indoor activities like smoking also contributed to PAH accumulation. Moreover, a strong correlation between BC and high-molecular PAHs (R²=0.74) suggests common sources. These findings highlight the need for better air quality policies to effectively safeguard children’s health.

The Berlin-Brandenburg Air Study (BEAR) is the first study in Germany to comprehensively assess short- and long-term AV-UFP exposures and their potential health effects. The study specifically examines pulmonary, cardiovascular, and cognitive health outcomes in primary school children. As part of BEAR, extensive particle number concentration (PNC) measurements were conducted at multiple schools in Berlin and Brandenburg from 2020 to 2024, providing an opportunity to analyse UFP exposure near two international airports. The exposure assessment results will play an important role in forthcoming epidemiological investigations, offering a holistic understanding of airports’ impact on health implications.

The study investigates New Particle Formation (NPF) at the high-altitude Izaña Atmospheric Observatory (2367 m a.s.l.) in Tenerife, Spain, through a three-month campaign (March–June 2022). Results indicate that particle concentrations are influenced by the upward transport of ~20 nm particles from the boundary layer (BL) and local clustering of sub-3 nm particles, which is enhanced by this transport. Sulfuric acid and highly oxygenated organic molecules contribute to NPF and originate from the BL, highlighting its critical role. Additionally, the study analyzes growth and formation rates of sub-3 nm particles, volatile organic compounds, and SO₂ to identify chemical pathways of NPF.

Mineral dust particles have been found to promote clustering and subsequent new particle formation (NPF) in the atmosphere.

Here we investigate the chemical composition and volatility of NPF precursors contributing to the mineral dust-influenced clustering events at a pristine high-altitude location, Canary Islands.

Lower concentrations of NPF precursors were observed for dust-influenced clustering events than clear clustering events. They were most likely to be biogenic origin.

We will compare the chemical composition and volatility of NPF precursors, as well as their potential formation pathways and discuss the resulting effects on particle formation and growth in the presence of dust.

This study explores two decades of ultrafine particle observations at Monte Cimone (2165 m a.s.l.), a key site for monitoring atmospheric processes in the Mediterranean. We analyze particle size distributions and new particle formation (NPF) events, revealing interannual, seasonal, and diurnal trends. Additionally, we examine how meteorological conditions, chemical precursors like sulfur dioxide, and proxies such as VOCs and BC for different emission sources influence particle dynamics and NPF. To assess the role of transport, we integrate FLEXPART backward simulations to trace air mass origins (marine/continental/regional) and evaluate the impact of long-range transport on aerosol properties at CMN.

New Particle Formation (NPF) is a major source of Arctic ultrafine particles (UFP), yet its vertical distribution and drivers remain unclear. This study presents balloon-borne observations of UFP during the 2024 melting season at Ny-Ålesund, Svalbard. Using condensation particle counters and a mobility particle sizer, 45 measurement flights revealed altitude-dependent UFP variability, influenced by temperature, radiation, and wind. Case studies highlight diurnal variations and elevated concentrations between clouds, suggesting in situ NPF. These findings enhance understanding of Arctic aerosol dynamics, improving atmospheric models and climate predictions.

The Environmentally Coupled, Lidar-Integrated Pollution Prognostics System (ECLIPPS), which couples in situ and lidar measurements with global forecasts and regional transport models, has been developed to aid air quality forecasting. ECLIPPS extracts the Integral Length Scale from measurements with the Mini Micro Pulse LiDAR (MiniMPL,), converts backscatter to fine particle concentrations (PM2.5), accesses meteorological data and inputs all these parameters into a transport model to provide air quality forecasts. The ECLIPPS has been used to evaluate aerosol vertical profiles in Mexico City during a period of extremely high PM2.5 due to regional transport of wildfire emissions

The Multi-Angle Imager for Aerosols (MAIA) mission, part of NASA’s Earth Venture Instrument program, investigates the health impacts of exposure to ambient particulate matter (PM). MAIA focuses on 12 Primary Target Areas (PTAs) worldwide, integrating satellite observations with ground-based PM measurements to map PM2.5, PM10, and chemically speciated PM2.5 at 1-km resolution. NASA and the Italian Space Agency (ASI) jointly implement MAIA, with satellite launch planned for 2026. This presentation provides a status update on MAIA’s ground-based monitoring network and preliminary findings, highlighting PM variability across PTAs.

Accurate aerosol quantification is vital for climate modeling, air quality assessment, and aviation safety. This study investigates the volume-to-extinction ratio (ζ) for mineral dust using a unique combination of UAV-mounted optical particle counters, ground-based lidar, and sun photometers. Data from the 2021 Cyprus Fall and 2022 ASKOS campaigns capture diverse dust events from the Middle East and Sahara. Results highlight discrepancies in size distribution retrievals, impacting ζ estimates. Comparisons with MOPSMAP and WRF-Chem-GOCART reveal model limitations. This synergistic approach, combining airborne in-situ observations with remote sensing, provides valuable insights into this important ratio, essential for remote sensing and atmospheric modeling.

Mineral dust chemical and mineralogical composition are key parameters for modeling its earth system impacts. Here, we link the chemical characteristics (full mass closure) of over 25 long-range transported Saharan dust plumes observed at the Jungfraujoch (JFJ) high-altitude research station in Switzerland (3580 m a.s.l.) to their source regions and transport trajectories. Systematic analysis of different satellite-based remote sensing products stands in the centre of identifying these relationships. Clear geographical as well as transport time related trends are observed for different chemical parameters, highlighting the need for differentiation related to source regions and transport when estimating dust earth system impacts.

This study evaluates vertical aerosol profiles (backscatter βₐₑᵣ and extinction αₐₑᵣ coefficients) using ceilometer, GRASP_pac (ceilometer-sun photometer synergy), and COBALD balloon soundings across three European stations (2019 - 2020). Analyzing 4,530 profiles and 35 COBALD soundings. Forward inversion with ceilomneters exhibited the lowest deviations and variability compared with backward. This study underscores the enhanced performance of ceilometer retrievals utilizing the forward inversion in comparison to GRASP_pac. Furthemore, the findings validate the reliability of GRASP_pac for aerosol profiling emphasizing the advantages of synergistic retrieval approaches.

This paper presents a new technique for estimating the dry deposition of aerosols based on the synergy between observational data from ground-based remote sensing and in situ instruments (operated at the RADO-Bucharest ACTRIS station), Copernicus Atmosphere Monitoring Service (CAMS) products and atmospheric models. To estimate the dry deposition, black carbon was used as a proxy for aerosols. The result shown that the modeling of aerosol deposition requires also precise vertical aerosol profiles at the in situ station; the effect of medium- and long-range transport of aerosol can not be neglected when investigating the air quality using in situ measurements.

In this work, we propose a formulation for two-way coupled large eddy simulations of particle laden dilute flows, with the aim of simulating volcanic aerosol plumes.The method comprises a stochastic Lagrangian approach coupled with the equilibrium model for low-inertia particles (Stokes number less than 1). This allows for capturing events in regions where the applicability of the equilibrium model is ambiguous and retain the benefits of using a Eulerian approach, which include facilitating the modelling of microphysical kinetic processes of aerosol interaction such as aggregation, while keeping the computational cost and memory requirements low.

Chemical ionization mass spectrometry (CIMS) is essential in atmospheric chemistry research but faces challenges in compound identification due to complex reagent ion-target compound interactions. Quantum chemical calculations can model these interactions, yet the vast configuration space and high costs hinder database creation, preventing a definitive compound identification workflow. This project explores a machine learning (ML) cost-efficient approach for CIMS compound identification. As a first step, the ML workflow developed can predict the detection and signal intensity of known compounds, and map the functional groups likely interacting with the reagent ion.

Severe PM pollution episodes frequently impact the Seoul Metropolitan Area, with nitrate playing a dominant role. Nitrate formation occurs through complex atmospheric pathways, including gas-phase oxidation, heterogeneous uptake, and aqueous-phase processes. This study employs explainable machine learning to analyze drivers of nitrate formation in Seoul, using high-resolution aerosol mass spectrometry data. Results reveal that nitrate formation sharply increases at RH >65%, persisting even as RH declines, suggesting prolonged aqueous-phase processing. Additionally, temperature exhibits a strong nonlinear effect, with nitrate formation suppressed below freezing due to phase-state constraints. These findings highlight the role of hygroscopic properties in nitrate-driven haze.

In this work, we present the most complete database of transported metals, along with a machine learning model designed to predict dust concentrations over Europe. The model is validated thoroughly with a combination of long measurement timeseries and ice core records. We find that dust concentrations increased over the period of 2012-2021, driven by more severe episodes, as a consequence of further desertification, which has significant implications both for regulatory purposes but also for public health.

An Ecodesign compliant stove was use to investigate the mechanisms of PM formation, using a variety of both softwood and hardwoods with 3 fuel moisture levels- dry (10%), seasoned (15%-20%) and wet (>25%). Additionally, the impacts of user behaviour such as overloading or underloading the stove was assessed. Finally, the effect of flue draft was investigated, simulating impacts of changing atmospheric conditions. The results are discussed in terms of relationship between fuels and operation, and the formation mechanisms of PM in relation to the combustion chemistry and the Global Warming Potential (GWP) the of soot particles.

Chemical nucleation of carbonaceous nanoparticles is explored by reactive Molecular Dynamics. The critical nucleus size is determined by free formation energy calculations and a nucleation rate is proposed, for the first time to the best of our knowledge, without a priori assumptions of the chemical reaction network and associated rate constants, or of the nucleation mechanism.

Hetero-aggregates are composites of different particles, often formed by mixing aerosol streams. Simulating their formation is complex due to factors like volume, fractal structure, and composition, making traditional sectional models computationally expensive. This study presents a new, efficient population balance equation (PBE) model based on the monodisperse framework by Jeong and Choi (2003), integrated with computational fluid dynamics (CFD) using the Eulerian-Lagrangian decomposition (ELD) method. Validated against a sectional model developed by Shigeta and Watanabe (2003, 2004), it maintains accuracy while being over 2500 times faster. This efficiency makes it ideal for CFD applications, including the PsiPhi in-house CFD code.

We will presnet a laboratory study of contrail potential formation from hydrogen combustion, In this study, water, air, oil vapors and nitrogen oxides are injected into a system to simulate the potential emissions generated by a hydrogen engine. Different NOx concentrations have been studied, combined or not with lubrication oil vapors and background aerosol.

Delhi is one of the most polluted cities globally, experiencing some of the world's highest urban particulate matter concentrations. However, these studies are performed for a short period with limited temporal variation information. Here, we performed the complete long-term characterization of the ambient fine particulate matter (PM_2.5) compositions. We performed analysis on different seasons (winter, spring, summer, and post monsoon) of the years on high time-resolved PM_2.5 data, including non-refractory PM_2.5 (NR- PM_2.5), elements, and black carbon (BC), to develop a variation of the composition-based estimate PM2.5 and its sources ("C-PM_2.5" = NR-PM_2.5 + elements + BC) concentrations.

We present online aerosol chemical and elemental compositions measured at an air quality research supersite located at an urbanised arid region in the city of Doha in Qatar. Utilizing an Aerodyne Time-of-Flight Aerosol Chemical Speciation Monitor (ToF-ACSM) and Xact multi-metal analyzer, we also monitor criteria pollutants, meteorological parameters, and PMx fractions. This study represents the first continuous online aerosol chemical and elemental composition measurements in the Middle East and provides insightes in the contriubiton of natual and anthropogenic sources to PM10 and PM2.5 in different seasons.

High-mountain regions serve as valuable observatories to study atmospheric composition and dynamics, and the Italian Alpine region is of particular interest due to its sensitive environment and its proximity to the Po Valley, a major pollution hotspot in Europe. This study examined chemical composition, size distribution and optical properties of aerosols collected at three study sites located at different altitudes in the Western Italian Alps, applying a multi-proxy approach to assess sources and transport processes. Results highlighted both diurnal mesoscale circulation patterns between the Po Valley and Alpine valleys and long-range transport events, revealing different aerosol types and sources.

Since 2013, the chemical characterization on PM10 and PM2.5 samples from Milano-Pascal (UB site) are available: PAHs, elements, OC and EC, soluble inorganic salts and sugars. The chemical speciation data were also processed through the application of the PMF algorithm, statistical methods, de-seasonalization techniques, and a rolling approach over the time to evaluate long-term trends and detect potential changes in source contributions over time. High-resolution PM component analyses and size distribution measurements (SMPS) have been introduced to complement the existing long-term dataset, and to evaluate the characteristics of aerosols at different size ranges.

This study examines size-resolved particulate matter at two Moroccan sites: the rural Atlas Mohammed V observatory and urban Fez. Research conducted in September-October 2019 revealed significant urban-rural disparities. PM10 concentrations in Fez were nearly triple those at the rural site, with ultrafine particles comprising 30% of urban PM10 versus only 12% at the rural location.

Chemical analysis showed much higher carbon concentrations in urban areas. PMF identified distinct source profiles: rural areas were dominated by mineral dust and aged sea salt, while urban areas showed significant traffic emissions, biomass burning, and road dust. Secondary aerosols contributed significantly at both sites.

Aerosol chemical speciation monitors (ACSM) provide valuable data for identifying aerosol sources using techniques like positive matrix factorization (PMF). However, PMF is time-consuming, prompting the exploration of faster, machine learning-based solutions. This study investigates the use of supervised regression models trained on data from multiple European sites for aerosol source identification. Results show moderate prediction accuracy for hydrocarbon-like OA (HOA) and biomass burning OA (BBOA), with higher error rates for less-oxidized (LO-OOA) and more-oxidized (MO-OOA) oxygenated OA.

Aerosol absorption and scattering coefficients were measured continuously in Milan for 1-year. Scattering data are the first ones obtained in Milan (Italy) and are still scarce in urban environments. From the Absorption and Scattering Angstrom Exponents provided information on the fossil fuel vs. wood burning presence as well as on particle-size dependence, respectively. An optical source apportionment was performed through the revised MWAA Model combined with the Aethalometer Model. In addition, absorption and scattering measurements were combined to retrieve aerosol typing (e.g. Saharan dust, local soil dust resuspension, wood burning, fossil fuel emissions).

The abstract reports experimental measurements of atrmospheric heating rate induced by light absorbing aerosol. These measurements were collected in the Po Valley at a urban (Milano) and rural site (Schivenoglia) during 2023. Measurements were collected at 1 min time resulution in any sky condition. Source and species apportionment of light absorbing aerosol allowed to determine the contribution of fossil fuel, biomass burning, black carbon and brown carbon on the heating rate. Moreover, brown carbon was apportioned between primary and secondary origin highlighting the climatic effect of both contribution in the atmosphere.

This study uses BLAnCA, an innovative, high-resolution laboratory instrument, to measure spectral absorption across the UV-NIR range of mineral dust samples from several arid areas around the world. The measurements reveal distinct optical properties tied to mineral composition.

This study was conducted at three distinct locations in Spain, representing different atmospheric environments: an urban site in Barcelona (77 m a.s.l.), a regional background site in Montseny (720 m a.s.l.), and a continental site in Montsec (1600 m a.s.l.). The primary objective of this research is to characterize the absorption properties and heating rates of black carbon (BC) and mineral dust (MD), with respect to their size distribution.

We present a roadmap for providing standardised BC measurements, which follows a top-down approach, beginning with SI-traceable measurements of the aerosol absorption coefficient (babs) using in-situ reference methods with a target measurement uncertainty of ≤ 10 % (coverage factor k=2). Two measurement workshops have been successfully conducted, providing essential data to achieve the research goals: 1) two primary reference methods for aerosol light absorption have been tested and validated; these include photo-thermal interferometry and extinction-minus-scattering for at least two different wavelengths. 2) MACBC has been determined for different aerosol mixtures including bare BC, coated BC and externally mixed BC.

This study presents the first experimental analysis of the thermal response time (𝜏) of single aerosol particles using multi-frequency photothermal interferometry (nω-PTI). Optically trapped tetraethylene glycol droplets were excited by a modulated infrared laser, and their frequency-dependent photothermal response was analyzed. A theoretical model was developed to separate the frequency-dependent particle temperature from the effects due to thermal wave propagation and the interferometric detection. Results showed good agreement with simulations for particles between 2 and 5 µm. The study highlights nω-PTI as a promising method to retrieve optical and thermophysical properties and analyze heat transport in the Knudsen transition regime.

Fine particulate matter (PM) poses significant health risks, necessitating accurate monitoring. Low-cost sensors (LCS) are increasingly used for PM measurement in citizen science and pollution mapping, but their reliability is affected by environmental factors and particle properties. Traditional calibration methods often fail to address non-linearities, prompting the use of Machine Learning (ML) for in-situ calibration. This study leverages the SensEURcity dataset from Antwerp, comparing ML models like linear regression, random forests, and Long Short-Term Memory (LSTM) networks. LSTM outperformed others models, achieving the lowest RMSE (8.79 µg/m³) . Model transferability revealed improved data reliability for deployed sensors across urban areas.

Measuring large aerosol particles in a wide size range is challenging due to sampling inefficiencies above 20 µm. The SwisensPoleno Jupiter addresses this with a three-stage virtual impactor, enabling efficient sampling and single-particle characterization using light scattering, holography, fluorescence, and polarization. A combined sizing approach integrates light scattering (0.5–15 µm) and holography (>10 µm) based on confidence metrics. Validation with PSL beads (0.6–100 µm) shows <6% error for 2–20 µm but larger deviations at detection limits.

Multiangle Implementation of Atmospheric Correction (MAIAC) AOD from both the MODIS TERRA and AQUA satellites was investigated focussing over Rome (Italy) urban area and its surroundings over the 21-years period (2001–2022). The satellite AOD was firstly validated exploiting long-term dataset of the AERONET Rome-Tor Vergata station. Interesting results were obtained concerning the influence of geometrical configuration of the satellite acquisition and the aerosol predominant mode (fine and coarse) on the accuracy of the MAIAC AOD product. Finally, the investigation on the study area confirms the general decrease of AOD over Rome over the two decades.

The Planetary Boundary Layer (PBL) is the lowest part of the atmosphere, directly interacting with the Earth's surface. Its height (PBLH) is crucial for studying pollution and meteorology but is often difficult to measure. This research utilizes aerosol and Doppler wind lidar data to analyze PBLH evolution across South Italian ACTRIS stations. Various gradient-based and wavelet transform algorithms are applied to lidar data, revealing consistent trends with some deviations during transition periods. Additionally, wind speed and turbulence analyses using Doppler lidar enhance PBLH retrieval accuracy. The study provides valuable insights into PBLH variability across different seasons and atmospheric conditions.

Atmospheric aerosol scattering and absorption wavelength tendencies of AERONET level 2.0, version 3 data (cloud-screened, quality-assured, and AOD at 440 nm > 0.4 a.u.) of 10 long-term stations across Italy have been evaluated (Holben et al, 1998, Dubovik et al, 2002). By using an optical typing approach, the means of Scattering Angstrom Exponent (SAE) versus Absorption Angstrom Exponent (AAE) between 440 - 675 nm of all stations have been categorized in the following aerosol dominant types: dust, dust/OC mixture, dust/EC mixture, coated particles, mixture, OC, EC, and OC/EC mixture (Cazorla et al, 2013).

In this work, aerosol attenuation coefficients from Aethalometers (AE33, AE36S) and aerosol light absorption coefficient measured off-line by polar photometry at five wavelengths (using PP_UNIMI, University of Milan) were compared at different wavelengths. The samples refer to two Arctic cruises carried out in summer 2024 on different research vessels (Oceania - IOPAN and Polarstern - AWI).

This allowed to determine experimentally multiple-scattering enhancement parameters for the Aethalomethers, evidencing instrument- and wavelength- dependence.

Finally, a comparison with the results obtained at high temporal resolution using the approach described in Ferrero et al. (Sci. Total Environ., 917, 170221) was carried out.

We propose the use of tunable-laser PTI (TL-PTI) as a self-calibrating reference technique for quantifying β_abn. In TL-PTI, a wavelength-tunable laser is used to quantify the narrow absorption lines of a gas via direct absorption spectroscopy, providing a reference β_abn,ref in units of Mm^-1. The A-band absorption lines of ambient oxygen at about 760 nm provide a convenient reference. The PTI signal is then calibrated to this β_abn,ref. This gas-PTI signal can then be “switched off” by tuning the laser wavelength away from the absorption lines, so that only particulate PTI signals remain in the background-subtracted signal.

A novel aerosol collection method using suspended liquid films and electrostatic precipitation has been developed to enhance airborne particle detection, including pathogens. The technique employs strong electrostatic fields to capture particles into a liquid film, increasing particle concentration and reducing system losses. An optimised liquid formulation was tested in a chamber with aerosolised microspheres, showing enhanced collection performance with increasing electrostatic field strength. Results suggest that dielectrophoretic forces primarily drive the improvement, with potential applications for sampling low concentrations and recovering viable bioaerosols. The technique shows promise for advancing aerosol sampling methods in various fields.

Illicit substances pose a significant threat to EU public health and security. Conventional surface sampling methods have limitations, prompting a new approach: collecting airborne fractions using an aerosol device. Integrating this with a novel detection device enables analysis via spectroscopy and mass spectrometry, providing a complete characterization. This innovative method enhances detection of illicit substances, streamlines border security processes, and reduces risks associated with handling hazardous materials. It offers a more effective and efficient solution for pre-screening at critical checkpoints, such as customs, airports, and postal services, improving overall security and public safety.

Nanoparticles exhibit complex shapes, influencing properties like bioavailability, toxicity, and reaction kinetics, necessitating detailed size and shape characterization. Conventional methods measure equivalent sizes (e.g., aerodynamic or mobility equivalent diameters) using devices like DMA or APS. Comprehensive analysis requires multidimensional distributions of particle properties. The Centrifugal Differential Mobility Analyzer (CDMA) addresses this by simultaneously classifying particles based on electric and centrifugal fields. It enables two-dimensional property distribution measurements of aerodynamic and mobility equivalent diameters. Results show robust measurements of silver aerosols, highlighting shape factors and multidimensional particle characterization.

The Aerosol InfraRed Monitor (AIRMon) is a novel instrument for near real-time chemical characterization of particulate matter using IR spectroscopy. The AIRMon integrates patented aerosol collection with automated IR measurements, providing quantitative data on organic functional groups and inorganic components. It utilizes an IR-transparent substrate to overcome previous limitations, granting access to previously unavailable spectral regions. This contribution presents detailed calibration analyses and compares AIRMon measurements with other established techniques. Field data from two ACTRIS sites and laboratory measurements of biomass burning emissions are discussed, demonstrating the AIRMon potential for improved air quality monitoring in real-world settings.

Atmospheric trace gases exhibit diverse chemical properties that challenge comprehensive analysis. We introduce Multi-Pressure Chemical Ionization Mass Spectrometry (MPCIMS), integrating high‐ and low‐pressure ionization in a single instrument to quantify volatile precursors and their oxidation products from one gas stream. By incorporating uronium as a reagent, MPCIMS achieves ultra‐sensitive, humidity‐resilient ionization—making uronium a promising positive mode CIMS reagent of choice. Demonstrated in laboratory experiments with a‑pinene, our approach captures the full spectrum from volatile precursors to highly functionalized products, offering comprehensive sensitivity and simplified operation for gas phase measurements to study secondary organic aerosol formation.

Oxidative potential was measured with chemical composition in mulitiple cities in western and Eastern Europe, China, and India. The main drivers of oxidative potential in the different regions and seasons will be discussed taking into account measurements of DTT and ascorbic acid in conjuncition with organic aerosol characterization, elemental composition anaylysis and source apportionment.

The oxidative potential of PM [capacity of PM to oxidize the lungs] is attracting growing interest in research into PM health impacts. OP appears to be a relevant indicator, as it allows to provide information about the intrinsic reactivity of particles and their possible risk for health. In this work, a large database of homogeneous OP measurements throughout Europe has been used to assess its spatial variability and to distinguish several types of environments according to their oxidative burden. These observations then fuel the discussion on the integration of OP into European regulations, using various OP exposure scenarios.

In this work, mineral dust was aerosolized into an atmospheric simulation chamber and oxidized with HONO, SO₂ and O₃, then the OP of mineral dust was estimated with different assays (DTT, AA and H₂O_2eq) for the total and soluble fraction. Experiments were also run for bulk samples for controlled pH changed.

We used quasi-Poisson regression models to estimate the effects of PM2.5 and PM10 oxidative potential (OP) exposure on mortality from four European cities: Barcelona, Grenoble, Paris, and Zurich. The associations obtained were combined using random effect meta-analysis. Two OP assays were evaluated, ascorbic acid (AA) and dithiothreitol (DTT), and the results were normalized by mass and volume.

OP was associated with both increased and decreased mortality risks, depending on assay type, PM fraction, and normalization unit. More epidemiological studies are needed to elucidate the effects of OP exposure on health.

This work investigates spatial and seasonal variabilities of PM_2.5 and PM₁₀ concentrations, composition, and oxidative potential (OP^DTT_V, obtained with DTT-assay), simultaneously at 22 sites in a central Mediterranean area in south Italy. Source apportionment using PMF5 allowed to evaluate the contributions of eight sources: traffic, biomass burning (BB), nitrate, sulphate-rich, marine, crustal, carbonates/construction, and industrial (only for PM_2.5). OP^DTT_V had relevant spatial variability only during the cold season. The use of soluble and insoluble fractions of OC and Ca in PMF5 allowed a better separation between traffic and BB sources and allowed to determined the role of local construction works.

Measuring the oxidative potential (OP) of atmospheric particles is used to assess their toxicity. We present a chemical kinetics model of aerosol oxidative potential to quantify the effects of particles on the production of reactive oxygen species and the depletion of ascorbic acid and dithiothreitol. An inverse modelling framework was applied to laboratory OP data. We extrapolate the findings from the laboratory experiments to field data, and find good agreement between the model and data across three sites. We further extend the to a multiphase kinetic model of the respiratory tract to translate assay-based OP into biomarkers of oxidative stress.

Poor indoor air quality can have a significant impact on occupants’ health and well-being. Despite this evidence, there are still major gaps in our understanding of the most important harmful pollutant components and their mechanisms of toxicity. This project aimed to investigate the mechanisms by which two dominant indoor air pollution sources (cooking and cleaning activities) can cause pulmonary adverse effects. A combination online of air-liquid interface lung epithelial cell exposure and accellular oxidative potential were used to link the chemical composition of the aerosol with adverse acellular and cellular toxicity measurements.

This study tackles key challenges in using oxidative potential (OP) to estimate health effects induced by various particulate matter (PM) sources. We employed OP^DTT, OP^AA, and OP^DCFH on more than one thousand fully chemically characterized PM samples collected in three urban/industrial areas of Italy. Samples were collected in each area using multi-stage impactors, conventional one-site daily samplings, and innovative spatially-resolved, long-term samplings. Source apportionment of PM₁₀ and its OP was performed using PMF, principal component analysis (PCA), and focused PCA. Size distribution analyses and spatially-resolved data significantly enhanced OP source apportionment, allowing for a more thorough investigation of its complexity.

This study examines the oxidative potential (OP) of airborne particulate matter (PM) and settled dust from homes in Slovenia, Sweden, and the UK, as part of the INQUIRE project. Using simulated lung fluid and LC-MS, antioxidant depletion rates (ascorbic acid, glutathione, cysteine) and glutathione disulfide accumulation were measured. Preliminary results show a strong correlation between PM mass and the initial depletion rate of ascorbic acid, and the later depletion phase of glutathione. These patterns suggest distinct oxidative mechanisms involving organics and soluble metals. These findings emphasize the potential health risks of indoor PM, particularly through oxidative stress in respiratory pathways.

In the present work, for first time an electrochemical sensor was developed for monitoring oxidative potential with high sensitivity and easy operation using portable devices. The proposed approach is based on ascorbic acid assay where, after being oxidized by particulate matter, the remaining ascorbic acid is analyzed directly by flow injection analysis with chronoamperometric detection using a screen-printed carbon electrode modified with azure-A polymer and platinum nanoparticles.