Atmospheric aerosols play a crucial role in the Earth's system, but their role is not completely understood, partly because of the large variability in their properties resulting from a large number of possible aerosol sources. Recently developed lidar-based techniques were able to retrieve the height distributions of optical and microphysical properties of fine-mode and coarse-mode particles, providing the types of the aerosols. One such technique is based on artificial neural networks (ANNs). In this article, a Neural Network Aerosol Typing Algorithm Based on Lidar Data (NATALI) was developed to estimate the most probable aerosol type from a set of multispectral lidar data. The algorithm was adjusted to run on the EARLINET 3β + 2α( + 1δ) profiles. The NATALI algorithm is based on the ability of specialized ANNs to resolve the overlapping values of the intensive optical parameters, calculated for each identified layer in the multiwavelength Raman lidar profiles. The ANNs were trained using synthetic data, for which a new aerosol model was developed. Two parallel typing schemes were implemented in order to accommodate data sets containing (or not) the measured linear particle depolarization ratios (LPDRs): (a) identification of 14 aerosol mixtures (high-resolution typing) if the LPDR is available in the input data files, and (b) identification of five predominant aerosol types (low-resolution typing) if the LPDR is not provided. For each scheme, three ANNs were run simultaneously, and a voting procedure selects the most probable aerosol type. The whole algorithm has been integrated into a Python application. The limitation of NATALI is that the results are strongly dependent on the input data, and thus the outputs should be understood accordingly. Additional applications of NATALI are feasible, e.g. testing the quality of the optical data and identifying incorrect calibration or insufficient cloud screening. Blind tests on EARLINET data samples showed the capability of NATALI to retrieve the aerosol type from a large variety of data, with different levels of quality and physical content.

This study analyzed the variability of equivalent black carbon (eBC) mass concentrations and their sources in urban Europe to provide insights into the use of eBC as an advanced air quality (AQ) parameter for AQ standards. This study compiled eBC mass concentration datasets covering the period between 2006 and 2022 from 50 measurement stations, including 23 urban background (UB), 18 traffic (TR), 7 suburban (SUB), and 2 regional background (RB) sites. The results highlighted the need for the harmonization of eBC measurements to allow for direct comparisons between eBC mass concentrations measured across urban Europe. The eBC mass concentrations exhibited a decreasing trend as follows: TR > UB > SUB > RB. Furthermore, a clear decreasing trend in eBC concentrations was observed in the UB sites moving from Southern to Northern Europe. The eBC mass concentrations exhibited significant spatiotemporal heterogeneity, including marked differences in eBC mass concentration and variable contributions of pollution sources to bulk eBC between different cities. Seasonal patterns in eBC concentrations were also evident, with higher winter concentrations observed in a large proportion of cities, especially at UB and SUB sites. The contribution of eBC from fossil fuel combustion, mostly traffic (eBC_T) was higher than that of residential and commercial sources (eBC_RC) in all European sites studied. Nevertheless, eBC_RC still had a substantial contribution to total eBC mass concentrations at a majority of the sites. eBC trend analysis revealed decreasing trends for eBC_T over the last decade, while eBC_RC remained relatively constant or even increased slightly in some cities.

This paper focuses on optical and microphysical properties of long‐range transported biomass burning (BB) aerosols and their variation with atmospheric evolution (ageing), as observed by a multiwavelength Raman lidar, part of EARLINET (European Aerosol LIdar NETwork). Chemical analysis of the atmospheric aerosol was done using a colocated aerosol mass spectrometer (AMS). One relevant optical parameter for the ageing process is the Ångström exponent. In our study, we find that it decreases from 2 for fresh to 1.4–0.5 for aged smoke particles. The ratio of lidar (extinction‐to‐backscatter) ratios (LR₅₃₂/LR₃₅₅) changes rapidly from values 1 for aged particles. The imaginary part of the refractive index is the most sensitive microphysical parameter. It decreases sharply from 0.05 to less than 0.01 for fresh and aged smoke particles, respectively. Single‐scattering albedo (SSA) varies from 0.74 to 0.98 depending on aerosol age and source. The AMS was used to measure the marker ions of wood‐burning particles during 2 days of measurements when the meteorological conditions favored the downward mixing of aerosols from lofted layers. Particle size distribution and particle effective radius from both AMS and lidar are similar, i.e., particle effective radii were approximately 0.27 µm for fresh BB aerosol particles. Microphysical aerosol properties from inversion of the lidar data agree with similar studies carried out in different regions on the globe. Our study shows that the Ångström exponent LR₅₃₂/LR₃₅₅ and the imaginary part of the refractive index can be used to clearly distinguish between fresh and aged smoke particles.

This work describes results obtained from the 2016 Aerosol Chemical Speciation Monitor (ACSM) intercomparison exercise performed at the Aerosol Chemical Monitor Calibration Center (ACMCC, France). Fifteen quadrupole ACSMs (Q_ACSM) from the European Research Infrastructure for the observation of Aerosols, Clouds and Trace gases (ACTRIS) network were calibrated using a new procedure that acquires calibration data under the same operating conditions as those used during sampling and hence gets information representative of instrument performance. The new calibration procedure notably resulted in a decrease in the spread of the measured sulfate mass concentrations, improving the reproducibility of inorganic species measurements between ACSMs as well as the consistency with co-located independent instruments. Tested calibration procedures also allowed for the investigation of artifacts in individual instruments, such as the overestimation of m/z 44 from organic aerosol. This effect was quantified by the m/z (mass-to-charge) 44 to nitrate ratio measured during ammonium nitrate calibrations, with values ranging from 0.03 to 0.26, showing that it can be significant for some instruments. The fragmentation table correction previously proposed to account for this artifact was applied to the measurements acquired during this study. For some instruments (those with high artifacts), this fragmentation table adjustment led to an “overcorrection” of the f44 (m/z 44/Org) signal. This correction based on measurements made with pure NH₄NO₃, assumes that the magnitude of the artifact is independent of chemical composition. Using data acquired at different NH₄NO₃ mixing ratios (from solutions of NH₄NO₃ and (NH₄)₂SO₄) we observe that the magnitude of the artifact varies as a function of composition. Here we applied an updated correction, dependent on the ambient NO₃ mass fraction, which resulted in an improved agreement in organic signal among instruments. This work illustrates the benefits of integrating new calibration procedures and artifact corrections, but also highlights the benefits of these intercomparison exercises to continue to improve our knowledge of how these instruments operate, and assist us in interpreting atmospheric chemistry.

Multi-wavelength depolarization Raman lidar measurements from Magurele, Romania are used in this study along with simulated mass-extinction efficiencies to calculate the mass concentration profiles of different atmospheric components, due to their different depolarization contribution to the 532 nm backscatter coefficient. Linear particle depolarization ratio (δ^part) was computed using the relative amplification factor and the system-dependent molecular depolarization. The low depolarizing component was considered as urban/smoke, with a mean δ^part of 3%, while for the high depolarizing component (mineral dust) a mean δ^part of 35% was assumed. For this study 11 months of lidar measurements were analysed. Two study cases are presented in details: one for a typical Saharan dust aerosol intrusion, 10 June 2012 and one for 12 July 2012 when a lofted layer consisting of biomass burning smoke extended from 3 to 4.5 km height. Optical Properties of Aerosols and Clouds software package (OPAC) classification and conversion factors were used to calculate mass concentrations. We found that calibrated depolarization measurements are critical in distinguishing between smoke-reach aerosol during the winter and dust-reach aerosol during the summer, as well as between elevated aerosol layers having different origins. Good agreement was found between lidar retrievals and DREAM- Dust REgional Atmospheric Model forecasts in cases of Saharan dust. Our method was also compared against LIRIC (The Lidar/Radiometer Inversion Code) and very small differences were observed.

The bioclimatology of thermal stress over Europe between 1979 and 2019 was analysed using the Universal Thermal Climate Index (UTCI) derived from ERA5‐HEAT reanalysis. The bioclimatology of different European regions was assessed using Köppen–Geiger climate classification. The annual number of hours with heat stress (UTCI > 32°C) increased significantly during the study period for all the analysed Köppen–Geiger climate subclasses, showing also a clear increase towards southern Europe. The highest percentage of hours (20% of all hours) with cold stress (UTCI < −13°C) occur over northern Europe. A significant increasing trend (>0.05 hr·year⁻¹) in the number of hours with heat stress was observed for 23 out of 32 analysed European cities representative for the Köppen–Geiger climate subclasses. For these cities not only the number of hours with heat stress has increased but also the heat stress is more persistent, while the number of cases and the persistence of the periods with cold stress have decreased over the last four decades. The UTCI values showed a statistically significant increase between 0.6 and 3.2°C for all the analysed cities over the study period reflecting the rising of global mean temperatures.