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The European Aerosol Research Lidar Network (EARLINET), part of the Aerosols, Clouds and Trace gases Research Infrastructure (ACTRIS), organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. Besides the standard operational processing of the lidar data in EARLINET, for seven EARLINET sites having collocated sun-photometric observations in the Aerosol Robotic Network (AERONET), a network exercise was held in order to derive profiles of the concentration and effective column size distributions of the aerosols in the atmosphere, by applying the GRASP/GARRLiC (from Generalized Aerosol Retrieval from Radiometer and Lidar Combined data – GARRLiC – part of the Generalized Retrieval of Atmosphere and Surface Properties – GRASP) inversion algorithm. The objective of this network exercise was to explore the possibility of identifying the anthropogenic component and of monitoring its spatial and temporal characteristics in the COVID-19 lockdown and relaxation period. While the number of cases is far from being statistically significant so as to provide a conclusive description of the atmospheric aerosols over Europe during this period, this network exercise was fundamental to deriving a common methodology for applying GRASP/GARRLiC to a network of instruments with different characteristics. The limits of the approach are discussed, in particular the missing information close to the ground in the lidar measurements due to the instrument geometry and the sensitivity of the GRASP/GARRLiC retrieval to the settings used, especially for cases with low aerosol optical depth (AOD) like the ones we show here. We found that this sensitivity is well-characterized in the GRASP/GARRLiC products, since it is included in their retrieval uncertainties. [ABSTRACT FROM AUTHOR]

The methodology of analysing the biomass burning events recorded in the database of the European Aerosol Research Lidar Network in the framework of the Aerosol, Clouds and Trace Gases Research Infrastructure is presented. The period of 2008–2017 was chosen to analyse all of the events stored in the database under the Forest Fire category for a total of 14 stations available. The data provided ranged from complete datasets (particle backscatter, extinction and linear depolarization ratio profiles) to single profiles (particle backscatter coefficient profile). Smoke layers geometry was evaluated and the mean optical properties within each layer were computed. The back-trajectory technique was used to double-check the source of all pollution layers. The biomass burning layers were identified by taking into account the presence of the fires along the back trajectory. The biomass burning events are analysed by the means of the intensive parameters. The analysis was structured in three directions: (I) common biomass burning source (fire) recorded by at least two stations, (II) long-range transport from North America, and (III) analysis over four geographical regions (south-eastern Europe, north-eastern Europe, central Europe, and south-western Europe). Based on back-trajectory calculations and fire locations, the lidar measurements can be labelled either as measurements of a "single fire" or "mixed fires" (case I), measurements of North American fires, or measurements of mixed North American and local fires (case II). The histogram of the fire locations reveals the smoke sources for each region. For each region, statistics on intensive parameters are performed. The source origin of the intensive parameters is categorized based on the continental origin of the air mass (European, African, Asian, North American, or a combination of them). The methodology presented here is meant to provide a perspective to explore a large number of lidar data and deliver novel approaches to analyse the intensive parameters based on the assigned biomass burning sources. A thorough consideration of all potential fire sources reveals that most of the time the lidar measurements characterize the smoke from a mixture of fires. A comprehensive discussion of all the results (based on the intensive parameters and the source locations) will be given in a companion paper submitted to the ACP EARLINET special issue. [ABSTRACT FROM AUTHOR]