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A long-lasting biomass burning event affected Europe from 27 August to 3 September 2018. The biomass burning aerosol layers were observed with ground- and space-based lidars in heights ranged between 2-7 km (a.s.l.). The mean backscatter coefficient for the ground-based stations ranged between 0.29 and 1.51 Mm-1sr-1, while the CALIPSO retrieved values ranged between 0.43 and 1.83 Mm-1sr-1. Moreover, the mean Ångström exponent (AEb) values, relevant to backscatter, ranged from 0.83 to 1.04 for the aforementioned lidar stations. At the same time, the mean AEb values obtained from CALIPSO ranged between 0.17 and 1.89. The mean particle depolarization ratio ranged between 0.037 and 0.080.

Three different aerosol classification methods have been used to characterize lidar observations: Mahalanobis distance automatic aerosol type classification, Neural Network Aerosol Typing Algorithm (NATALI) and Source and Analysis (SCAN) aerosol classification. The data selection has been made through the EARLINET database depending on the 3b+2a+1δ optical property availability. One hundred aerosol layers from four EARLINET stations (Bucharest, Kuopio, Leipzig and Potenza) have been classified. We present a typical case study of aerosol characterization observed by the MUSA system over Potenza on the 11th of April 2016 (20:30-21:30 UTC).

A cirrus cloud dataset from a groundbased lidar in a sub-arctic station is analyzed in terms of the particle depolarization ratio. The depolarization values -δ- showed a broad distribution, ranging between 0.25 and 0.7, with a mean value of 0.38 ± 0.07. This variability is examined in correlation with temperature dependencies and the cirrus optical depth. Depolarization values greater than 0.45 are observed from temperatures between -60oC and -40oC, where horizontally oriented planar ice crystals are to be expected. Two case studies are also, discussed and analyzed in terms of depolarization height dependence.

In order to document and study airborne pollen in the Mediterranean region, a pollen measurement campaign was performed during February-May 2018, at the Finokalia station in Crete. A ground-based multi-wavelength Raman polarization lidar PollyXT performed continuous measurements, together with a Hirst-type Burkard pollen sampler. The optical properties of pollen layers with presence of airborne pollen are retrieved and presented. Dust-free condition is applied for pollen study, using the dust models.

This paper presents a collection of lidar-derived aerosol intensive optical properties for several aerosol types, namely the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection, named DeLiAn, is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarization lidar measurements, conducted mainly with lidars that have been developed at the Leibniz Institute for Tropospheric Research. The intensive optical properties are presented at two wavelengths, 355 and 532 nm, for 13 aerosol categories. The categories cover the basic aerosol types (i.e., marine, pollution, continental European background, volcanic ash, smoke, mineral dust), as well as the most frequently observed mixtures they form. This extensive collection also incorporates more peculiar aerosol categories, including dried marine aerosol that, compared to marine aerosol, exhibits a significantly enhanced depolarization ratio (up to 15 %). Besides Saharan dust, additional mineral dust types related to their source region were identified due to their lower lidar ratios (Central Asian and Middle Eastern dust). In addition, extreme wildfire events (such as in north America and Australia) emitted smoke into the stratosphere showing significantly different optical properties, i.e., high depolarization values (up to 25 %), compared to tropospheric smoke. The data collection reflects and underlines the variety of aerosol mixtures in the atmosphere and can be used for the development of aerosol-typing schemes. The paper contains the most up-to-date and comprehensive overview of optical properties from aerosol lidar measurements and, therefore, provides a solid basis for future aerosol retrievals in the frame of both spaceborne and ground-based lidars. Furthermore, DeLiAn can assist the efforts for the harmonization of satellite records of aerosol properties performed at different wavelengths. [ABSTRACT FROM AUTHOR]

Geometrical and optical characteristics of cirrus clouds using Raman lidar PollyXT measurements at different locations are presented. The PollyXT has been participated in two long-term experimental campaigns, one close to New Delhi in India and one at Elandsfontein in South Africa, providing continuous measurements and covering a wide range of cloud types. First results of cirrus cloud properties at different latitudes, as well as their temporal distributions are presented in this study. An automatic cirrus clouds detection algorithm is applied based on the wavelet covariance transform. The measurements at New Delhi performed from March 2008 to February 2009, while at Elandsfontein measurements were performed from December 2009 to January 2011.

This paper presents a collection of lidar-derived aerosol intensive optical properties for several aerosol types, namely the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection, named DeLiAn, is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarisation lidar measurements, conducted mainly with lidars that have been developed at the Leibniz Institute for Tropospheric Research. The intensive optical properties are presented at two wavelengths, 355 and 532 nm, for 13 aerosol categories. The categories cover the basic aerosol types (i.e., marine, pollution, continental European background, volcanic ash, smoke, mineral dust) as well as the most frequently observed mixtures they form. This extensive collection also incorporates more peculiar aerosol categories, including dried marine aerosol that, compared to marine aerosol, exhibits a significantly enhanced depolarization ratio (up to 15 %). Besides Saharan dust, additional mineral dust types related to their source region were identified due to their lower lidar ratios (Central Asian and Middle Eastern dust). In addition, extreme wildfire events (such as in north America and Australia) emitted smoke into the stratosphere showing significant different optical properties, i.e., high depolarization values (up to 25 %), compared to tropospheric smoke. The data collection reflects and underlines the variety of aerosol mixtures in the atmosphere and can be used for the development of aerosol typing schemes. The paper contains the currently most comprehensive overview of optical properties from aerosol lidar measurements and, therefore, provides a solid basis for future aerosol retrievals in the frame of both spaceborne and ground-based lidars. Furthermore, DeLiAn can assist the efforts for harmonization of satellite records of aerosol properties performed at different wavelengths. [ABSTRACT FROM AUTHOR]

Layers of biomass burning aerosol particles were observed in the lower troposphere, at 2 to 5 km height on 4 to 6 June 2019, over Kuopio, Finland. These long-range-transported smoke particles originated from a Canadian wildfire event. The most pronounced smoke plume detected on 5 June was intensively investigated. Optical properties were retrieved from the multi-wavelength Raman polarization lidar PollyXT. Particle linear depolarization ratios of this plume were measured to be 0.08 ± 0.02 at 355 nm and 0.05 ± 0.01 at 532 nm which were slightly higher than the values given in the literature. Nonspherical shaped aged smoke particles and/or the mixing with a small amount of fine dust particles could cause the observed increase in the particle linear depolarization ratios. Lidar ratios were derived as 47 ± 5 sr at 355 nm and 71 ± 5 sr at 532 nm. A complete ceilometer data processing for a Vaisala CL51 is presented, including the water vapor correction for high latitude for the first time, from sensor provided attenuated backscatter coefficient to particle mass concentration. A combined lidar and sun-photometer approach (based on AERONET products) is applied for mass concentration estimations. Mass concentrations were estimated from both PollyXT and the ceilometer CL51 observations, which were of the order of ~ 30 µg m-3 in the morning and decreased to ~ 20 µg m-3 in the night. A difference of ~ 30 % was found between PollyXT and CL51 estimated mass concentrations. The mass retrievals were discussed and compared with the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) meteorological and aerosol reanalysis. The inclusion of dust in the retrieved mass concentration slightly improved the correspondence between the observations and the MERRA-2 simulations. [ABSTRACT FROM AUTHOR]

Lidar observations during the pollen season 2019 at the European Aerosol Research Lidar Network (EARLINET) station in Kuopio, Finland were analyzed in order to optically characterize atmospheric pollen. Previous studies showed the detectability of non-spherical pollen using depolarization ratio measurements. We present lidar depolarization ratio measurements at three wavelengths of atmospheric pollen in ambient conditions. In addition to the depolarization ratio detected with the multiwavelength Raman polarization lidar PollyXT at 355 and 532 nm, depolarization measurements of a co-located HALO Photonics Streamline Doppler lidar at 1565 nm were utilized. During a four days period of high birch (Betula) and spruce (Picea abies) pollen concentrations, unusually high depolarization ratios were observed within the boundary layer. Detected layers were investigated regarding the share of spruce pollen to the total pollen number concentration. Daily mean particle depolarization ratios of the pollen layers on the day with the highest spruce pollen share are 0.10 ± 0.02, 0.38 ± 0.23 and 0.29 ± 0.10 at 355, 532 and 1565 nm, respectively. Whereas on days with lower spruce pollen share, depolarization ratios are lower with less wavelength dependence. This spectral dependence of the depolarization ratios could be indicative of big, non-spherical spruce pollen. The depolarization ratio of pollen particles was investigated by applying a newly developed method and assuming a backscatter-related Ångström exponent of zero. Depolarization ratios of 0.44 and 0.16 at 532 and 355 nm for the birch and spruce pollen mixture were determined. [ABSTRACT FROM AUTHOR]

We introduce an automated aerosol type classification method, called Source Classification ANalysis (SCAN). SCAN is based on predefined and characterized aerosol source regions, the time that the air parcel spends above each geographical region and a number of additional criteria. The output of SCAN is compared with two independent aerosol classification methods, which use the intensive optical parameters from lidar data: (1) Mahalanobis distance automatic aerosol type classification (MD) and (2) Neural Network Aerosol Typing Algorithm (NATALI). In this paper, data from the European Aerosol Research Lidar Network (EARLINET) have been used. A total of 97 free tropospheric (FT) aerosol layers from 4 typical EARLINET stations (i.e., Bucharest, Kuopio, Leipzig and Potenza) in the period 2014-2018 were classified based on a 3β+2α+1δ lidar configuration. We found that SCAN, being an optical property independent method, is not affected by the overlapping optical values of different aerosol types. Furthermore, SCAN has no limitations concerning its ability to classify different aerosol mixtures. Additionally, it is a valuable tool to classify aerosol layers, based on even to single (elastic) lidar signals, in case of lidar stations which cannot provide a full data set (3β+2α+1δ) of aerosol optical properties, therefore it can work independently of the capabilities of a lidar system. Finally, our results show that NATALI has the lower percentage of unclassified layers (4 %), while MD has the percentage of unclassified layers (50 %) and the lower percentage of cases classified as aerosol mixtures (5 %). [ABSTRACT FROM AUTHOR]

We present a novel algorithm for characterizing the optical properties of pure pollen particles, based on the depolarization values obtained in lidar measurements. The algorithm was first tested and validated through a simulator, and then applied to the lidar observations during a four-month pollen campaign from May to August 2016 at the European Aerosol Research Lidar Network (EARLINET) station in Kuopio (62°44' N, 27°33' E), in Eastern Finland. Twenty types of pollen were observed and identified from concurrent measurements with Burkard sampler; Birch (Betula), pine (Pinus), spruce (Picea) and nettle (Urtica) pollen were most abundant, contributing more than 90% of total pollen load, regarding number concentrations. Mean values of lidar-derived optical properties in the pollen layer were retrieved for four intense pollination periods (IPPs). Lidar ratios at both 355 and 532 nm ranged from 55 to 70 sr for all pollen types, without significant wavelength-dependence. Enhanced depolarization ratio was found when there were pollen grains in the atmosphere, and even higher depolarization ratio (with mean values of 25% or 14%) was observed with presence of the more non-spherical spruce or pine pollen. The depolarization ratio at 532 nm of pure pollen particles was assessed, resulting to 24 ± 3% and 36 ± 5% for birch and pine pollen, respectively. Pollen optical properties at 1064 nm and 355 nm were also estimated. The backscatter-related Ångström exponent between 532 and 1064 nm was assessed as ~ 0.8 (~ 0.5) for pure birch (pine) pollen, thus the longer wavelength would be better choice to trace pollen in the air. The pollen depolarization ratio at 355 nm of 17% and 30% were found for birch and pine pollen, respectively. The depolarization values show a wavelength dependence for pollen. This can be the key parameter for pollen detection and characterization. [ABSTRACT FROM AUTHOR]

In this study we estimate the particle extinction profiles at Finokalia, Crete, using only the information provided by the elastic and polarization channels of a PollyXT lidar system. Most of the time Finokalia site is affected by only two aerosol types, i.e. marine and dust particles. These two aerosol types, having different optical properties, permit the separation of aerosol mixture. The proposed method uses the particle backscatter profiles at 532 nm and the vertically resolved particle linear depolarization ratio measurements at the same wavelength. The particle linear depolarization ratio and the lidar ratio values of pure aerosol types are taken from literature. The total extinction profile is then estimated and compared well with Raman retrievals. Any difference between the proposed methodology and Raman extinction profiles indicates that the non-dust component could be probably attributed to polluted marine or polluted continental aerosols. Comparison with sun-photometric aerosol optical depth observations is performed as well during daytime with reasonable differences between the two instruments. Differences in the total aerosol optical depth is attributed to the limited ability of the lidar to correctly represent the aerosol optical properties in the near range due to overlap problem. [ABSTRACT FROM AUTHOR]