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The Aerosol, Clouds and Trace Gases Research Infrastructure ACTRIS is currently being developed with support from more than 20 countries and more than 100 research-performing organizations in Europe. The pan-European distributed research infrastructure shall provide data and services related to short-lived atmospheric constituents to facilitate high-quality Earth system research in the long term (over at least 20 years). While some of the activities are already in place, ACTRIS functionality will be further ramped up until full operation in 2025. The observation of aerosol, clouds and reactive trace gases with in-situ and remote-sensing techniques in ACTRIS is supported by six Topical Centres, which are responsible for common standards and quality assurance. Free and open virtual access to ACTRIS data is provided by the Data Centre. International users will also have physical access to ACTRIS observatories, atmospheric simulation chambers and mobile platforms as well as remote or physical access to calibration services, digital services and training. Access provision is organized through a single-entry point by the Head Office. In this contribution, the general principles and structure of ACTRIS are introduced, and the observational component related to aerosol remote sensing, which builds on the heritage of the European Aerosol Research Lidar Network (EARLINET) and the European part of the Aerosol Robotic Network (AERONET-Europe), is explained in more detail.

The biomass burning events are analyzed using the EARLINET-ACTRIS atmospheric profiling of aerosols using lidars. The period of 2008-2017 was chosen to analyze all the events assigned in the EARLINET database under Forest Fire category. A number of fourteen stations were considered. The data provided, ranged from complete data sets (backscatter, extinction and particle linear depolarization ratio) to single profiles (backscatter coefficient). A thorough quality control was performed. Smoke layers geometry was evaluated and the mean properties within each layer were computed. The Hysplit backward-trajectory technique and the FIRMS fire database were used to double check the source of each layer. Discussions were made under the following scenarios: fire events seen by two stations, long range transport from North America, and geographical clusters.

The paper presents the preliminary results of the lidar&radiometer measurement campaign (LRMC-2017), estimation of statistical relations between aerosol mode concentrations retrieved from CALIOP and ground-based lidar stations and case study of fire smoke events in the Eurasian regions using combined ground-based and space lidar and radiometer observations.

Total ozone and other trace gases are measured and reported regularly due to the increased interest started with the ozone hole discovery but the new satellites dedicated to worldwide observations of these species need both short-and long-term well calibrated ground based observation for validation procedures. The ESA/NASA Pandora network established a sophisticated, automatic calibration procedure that utilizes a variety of narrow-line and broadband emission lamps with temperature control for their UV-Vis-NIR spectroradiometers. In this study, we describe additional calibration efforts for ozone retrievals. In this paper we explore the local aerosol field influence on the retrieval of the ozone spectra from PANDORA 2S measurements using collocated lidar and sunphotometer measurements and proposed a methodology to be implemented in the calibration procedure of the instruments.

This study documents a complex fire event that occurred on October 2016, in Middle East belligerent area. Two fire outbreaks were detected by different spacecraft monitoring instruments on board of TERRA, CALIPSO and AURA Earth Observation missions. Link with local weather conditions was examined using ERA Interim Reanalysis and CAMS datasets. The detection of the event by multiple sensors enabled a detailed characterization of fires and the comparison with different observational data.

The present study is focused on microphysics analysis of different cloud types observed by a multi-wavelength Raman lidar. Particle’s content from a wide variety of cloud types, produced in various atmospheric environments, were investigated using data provided by lidar and validated using ECMWF’s ERA Interim reanalysis. The results emphasized the capability of lidar instruments to detect multiple cloud layers, and to discriminate between ice particles and water droplets found within the studied clouds.

Aerosol typing is essential for understanding the impact of the different aerosol sources on climate, weather system and air quality. An aerosol classification method for EARLINET (European Aerosol Research Lidar Network) measurements is introduced which makes use the Mahalanobis distance classifier. The performance of the automatic classification is tested against manually classified EARLINET data. Results of the application of the method to an extensive aerosol dataset will be presented.

A Python code was developed to automatically retrieve the aerosol type (and its predominant component in the mixture) from EARLINET’s 3 backscatter and 2 extinction data. The typing relies on Artificial Neural Networks which are trained to identify the most probable aerosol type from a set of mean-layer intensive optical parameters. This paper presents the use and limitations of the code with respect to the quality of the inputed lidar profiles, as well as with the assumptions made in the aerosol model.

The Cloud-Aerosol Transport System (CATS) onboard the International Space Station (ISS), is a lidar system providing vertically resolved aerosol and cloud profiles since February 2015. In this study, the CATS aerosol product is validated against the aerosol profiles provided by the European Aerosol Research Lidar Network (EARLINET). This validation activity is based on collocated CATS-EARLINET measurements and the comparison of the particle backscatter coefficient at 1064nm.

This paper presents an algorithm for aerosol typing from multiwavelength lidar data, based on Artificial Neural Networks. The aerosol model used to simulate optical properties for the training of the network is described. The algorithm is tested on real observations from ESA-CALIPSO database.

This paper presents the newly established Lidar Calibration Centre, a distributed infrastructure in Europe, whose goal is to offer services for complete characterization and calibration of lidars and ceilometers. Mobile reference lidars, laboratories for testing and characterization of optics and electronics, facilities for inspection and debugging of instruments, as well as for training in good practices are open to users from the scientific community, operational services and private sector. The Lidar Calibration Centre offers support for trans-national access through the EC HORIZON2020 project ACTRIS-2.

In this work we propose a two-step advancement of the Mie spherical-particle model accounting for particle non-sphericity. First, a naturally two-dimensional (2D) generalized model (GM) is made, which further triggers analogous 2D re-definitions of microphysical parameters. We consider a spheroidal-particle approach where the size distribution is additionally dependent on aspect ratio. Second, we incorporate the notion of a sphere-spheroid particle mixture (PM) weighted by a non-sphericity percentage. The efficiency of these two models is investigated running synthetic data retrievals with two different regularization methods to account for the inherent instability of the inversion procedure. Our preliminary studies show that a retrieval with the PM model improves the fitting errors and the microphysical parameter retrieval and it has at least the same efficiency as the GM. While the general trend of the initial size distributions is captured in our numerical experiments, the reconstructions are subject to artifacts. Finally, our approach is applied to a measurement case yielding acceptable results.

One hundred years after the discovery of cosmic rays, the study of charged ultra-high energy cosmic rays remains a vital activity in fundamental physics. While primary cosmic rays could not be measured directly until it was possible to get the detectors high in the atmosphere using balloons or spacecraft, nowadays very energetic cosmic rays are detected indirectly by ground-based experiments measuring their Extensive Air Showers (EAS) induced Cherenkov and fluorescent light, or radio waves. Moreover, all cosmic ray measurements (performed either from space or ground) rely on accurate understandings of atmospheric phenomena. The concept of the COSAT project is the inter-link between Astroparticle Physics, Remote Sensing and Atmospheric Environment, willing to investigate the energetic cosmic rays physical processes using the atmosphere as a detector in order to identify potential scientific niches in the field of space sciences. A short introduction on the current status and perspectives of the national partnership COSAT project will be given.

Biomass burning episodes measured at 14 stations of the European Aerosol Research Lidar Network (EARLINET) over 20082017 were analysed using the methodology described in "Biomass burning events measured by lidars in EARLINET -- Part 1: Data analysis methodology" (Adam et al., 2020, this issue). The smoke layers were identified in lidar optical properties profiles. A number of 795 layers for which we measured at least one intensive parameter was analysed. These layers were geographically distributed as follows: 399 layers observed in South-East Europe, 119 layers observed in South-West Europe, 243 layers observed in North-East Europe, and 34 layers observed in Central Europe. The mean layer intensive parameters are discussed following two research directions: (I) the long-range transport of smoke particles from North America, and (II) the smoke properties (fresh versus aged), separating the smoke events into four continental source regions (European, North American, African, Asian or a mixture of two), based on back trajectory analysis. The smoke detected in Central Europe (Cabauw, Leipzig, and Hohenpeißenberg) was mostly transported from North America (87% of fires). In North-East Europe (Belsk, Minsk, Warsaw) smoke advected mostly from Eastern Europe (Ukraine and Russia), but there was a significant contribution (31%) from North America. In South-West Europe (Barcelona, Evora, Granada) smoke originated mainly from the Iberian Peninsula and North Africa (while 9% were originating in North America). In the South-East Europe (Athens, Bucharest, Potenza, Sofia, Thessaloniki) the origin of the smoke was mostly local (only 3% represented North America smoke). The following features, correlated with the increased smoke travel time (corresponding to aging) were found: the colour ratio of the lidar ratio (i.e., the ratio of the lidar ratio at 532 nm to the lidar ratio at 355 nm) and the colour ratio of the backscatter Ängström exponent (i.e., the ratio of the backscatter-related Angstrom exponent for the pair 532 nm -- 1064 nm to the one for the pair 355 nm -- 532 nm) increase, while the extinction Ängström exponent and the colour ratio of the particle depolarization ratio (i.e., the ratio of the particle linear depolarization ratio at 532 nm to the particle depolarization ratio at 355 nm) decrease. The smoke originating from all continental regions can be characterized on average as aged smoke, with a very few exceptions. In general, the long range transported smoke shows higher lidar ratio and lower depolarization ratio compared to the local smoke. [ABSTRACT FROM AUTHOR]

Black carbon aerosols are the second largest contributor to global warming while also being linked to respiratory and cardiovascular disease. These particles are generally found in smoke plumes originating from biomass burning and fossil fuel combustion. They are also heavily concentrated in smoke plumes originating from oil fires exhibiting the largest ratio of black carbon to organic carbon. In this study, we identified and analyzed oil smoke plumes derived from 30 major industrial events within a 12-year timeframe. To our knowledge, this is the first study of its kind that utilized a synergetic approach based on satellite remote sensing techniques. One objective of this study is to highlight the importance of satellite remote sensing techniques in identifying these types of events. As opposed to ground stations, satellite data offers access to remote areas all over the globe which would otherwise be very difficult to reach. Satellite data offers access to these events which, as seen in this study, are mainly located in war prone or hazardous areas. This study focuses on the use of MODIS (Moderate Resolution Imaging Spectroradiometer) and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) products regarding these types of aerosol while also highlighting their intrinsic limitations. By using data from both MODIS instruments onboard Terra and Aqua satellites we addressed the temporal evolution of the smoke plume while assessing Lidar specific properties and plume elevation using CALIPSO data. We present several aerosol properties in the form of plume specific averaged values. The MODIS ocean algorithms were successful in retrieving aerosol properties which, on average, ranged from -0.06 to 0.16 for plume specific AOD, - 0.18 to 1.25 for Ångström exponent and 0.29 to 1.73 μm for the effective radius. CALIPSO measurements showed values of plume AOD ranging from 0 to 0.14 (532 nm) and 0 to 0.13 (1064 nm) except for one event where AOD values showed 1.52 (532 nm) and 1.42 (1064 nm). AE values ranged from 0.11 to 0.33 which were in agreeance with MODIS values. A large discrepancy can be found in one event where CALIPSO measured AOD values 5 times higher than MODIS. This event also produced the largest lidar ratio at 109 sr (532 nm) and 86 (1064 nm). Other lidar ratio values ranged from 37 to 55 sr however these unconstrained solutions were obtained for the entire layer of which the plumes were a part of and thus did not reflect specific plume conditions. Particulate backscatter values ranged from 0.002 to 0.0017km-1 sr-1 while extinction coefficient values ranged from 0.10 to 1.65 km-1. On average backscatter and extinction coefficient values were 2 to 9 times higher than local background values. Particulate depolarization ratios ranged from 0.11 to 0.15 in 4 out of 6 cases while the remaining two ranged from 0.27 to 0.32 where dust was highly dominant. The values represented in this study are in good agreement with similar studies that used ground based and flight measurements. We believe that MODIS values are a conservative estimation of plume AOD since MODIS algorithms rely on general aerosol models and various atmospheric conditions within the look-up tables which do not reflect the highly absorbing nature of these smoke plumes. CALIPSO measurements are heavily dependent on lidar ratios which are not directly measured if plumes within the planetary boundary layer. We also believe that AOD values based on CALIPSO measurements are conservative in nature since heavy absorbing smoke would yield larger lidar ratios and AOD values. Based on this study we conclude that the MODIS land algorithms are not yet suited for retrieving aerosol properties for these types of smoke plumes due to the strong absorbing properties of these aerosols. We believe that these types of studies are a strong indicator for the need of improved aerosol models and retrieval algorithms. [ABSTRACT FROM AUTHOR]