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.

Systematic measurements of dust concentration profiles at a continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable data set and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAMABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. The observations, which include coincident multi-wavelength lidar and sun photometer measurements, were processed with the Lidar-Radiometer Inversion Code (LIRIC) to retrieve aerosol concentration profiles. The methodology proposed here shows advantages when compared to traditional evaluation techniques that utilize separately the available measurements such as separating the contribution of dust from other aerosol types on the lidar profiles and avoiding model assumptions related to the conversion of concentration fields to aerosol extinction values. When compared to LIRIC retrievals, the simulated dust vertical structures were found to be in good agreement for all models with correlation values between 0.5 and 0.7 in the 1–6 km range, where most dust is typically observed. The absolute dust concentration was typically underestimated with mean bias values of -40 to -20 μg m⁻³ at 2 km, the altitude of maximum mean concentration. The reported differences among the models found in this comparison indicate the benefit of the systematic use of the proposed approach in future dust model evaluation studies.

One year of ground-based night-time Raman lidar observations has been analysed under the Optimization of Aerosol Seeding In rain enhancement Strategies (OASIS) project, in order to characterize the aerosol particle properties over a rural site in the United Arab Emirates. In total, 1130 aerosol particle layers were detected during the 1-year measurement campaign which took place between March 2018 and February 2019. Several subsequent aerosol layers could be observed simultaneously in the atmosphere up to 11 km. The observations indicate that the measurement site is a receptor of frequent dust events, but predominantly the dust is mixed with aerosols of anthropogenic and/or marine origin. The mean aerosol optical depth over the measurement site ranged at 0.37 ± 0.12 and 0.21 ± 0.11 for 355 and 532 nm, respectively. Moreover, mean lidar ratios of 43 ± 11 sr at a wavelength of 355 nm and 39 ± 10 sr at 532 nm were found. The average linear particle depolarization ratio measured over the course of the campaign was 15 ± 6 % and 19 ± 7 % at the 355 and 532 nm wavelengths, respectively. Since the region is both a source and a receptor of mineral dust, we have also explored the properties of Arabian mineral dust of the greater area of the United Arab of Emirates and the Arabian Peninsula. The observed Arabian dust particle properties were 45 ± 5 (42 ± 5) sr at 355 (532) nm for the lidar ratio, 25 ± 2 % (31 ± 2 %) for the linear particle depolarization ratio at 355 (532) nm, and 0.3 ± 0.2 (0.2 ± 0.2) for the extinction-related Ångström exponent (backscatter-related Ångström exponent) between 355 and 532 nm. This study is the first to report comprehensive optical properties of the Arabian dust particles based on 1-year long observations, using to their fullest the capabilities of a multi-wavelength Raman lidar instrument. The results suggest that the mineral dust properties over the Middle East and western Asia, including the observation site, are comparable to those of African mineral dust with regard to the particle depolarization ratios, but not for lidar ratios. The smaller lidar ratio values in this study compared to the reference studies are attributed to the difference in the geochemical characteristics of the soil originating in the study region compared to northern Africa.

We present the results of birch pollen characterization using lidar and in situ measurements based on a 11 d pollination period from 5 to 15 May 2016 at the European Aerosol Research Lidar Network (EARLINET) station in Vehmasmäki (Kuopio; 62^∘44^′ N, 27^∘33^′ E), Finland. The ground-based multiwavelength Raman polarization lidar Polly^XT performed continuous measurements at this rural forest site and has been combined with a Hirst-type volumetric air sampler, which measured the pollen type and concentration at roof level (4 m). The period was separated into two parts due to different atmospheric conditions and detected pollen types. During the first period, high concentrations of birch pollen were measured with a maximum 2 h average pollen concentration of 3700 grains m⁻³. Other pollen types represented less than 3 % of the total pollen count. In observed pollen layers, the mean particle depolarization ratio at 532 nm was 10±6 % during the intense birch pollination period. Mean lidar ratios were found to be 45±7 and 55±16 sr at 355 and 532 nm, respectively. During the second period, birch pollen was still dominant, but a significant contribution of spruce pollen was observed as well. Spruce pollen grains are highly nonspherical, leading to a larger mean depolarization ratio of 26±7 % for the birch–spruce pollen mixture. Furthermore, higher lidar ratios were observed during this period with mean values of 60±3 and 62±10 sr at 355 and 532 nm, respectively. The presented study shows the potential of the particle depolarization ratio to track pollen grains in the atmosphere.

We present a novel algorithm for characterizing the optical properties of pure pollen particles, based on the depolarization ratio values obtained in lidar measurements. The algorithm was first tested and validated through a simulator and then applied to the lidar observations during a 4-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. With a Burkard sampler, 20 types of pollen were observed and identified from concurrent measurements, with birch (Betula), pine (Pinus), spruce (Picea), and nettle (Urtica) pollen being the most abundant, contributing more than 90 % of the 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. An enhanced depolarization ratio was found when there were pollen grains in the atmosphere, and an even higher depolarization ratio (with mean values of 0.25 or 0.14) was observed with the presence of the more non-spherical spruce or pine pollen. Under the assumption that the backscatter-related Ångström exponent between 355 and 532 nm should be zero for pure pollen, the depolarization ratio of pure pollen particles at 532 nm was assessed, resulting in 0.24±0.01 and 0.36±0.01 for birch and pine pollen, respectively. Pollen optical properties at 1064 and 355 nm were also estimated. The backscatter-related Ångström exponent between 532 and 1064 nm was assessed to be ∼0.8 (∼0.5) for pure birch (pine) pollen; thus the longer wavelength would be a better choice to trace pollen in the air. Pollen depolarization ratios of 0.17 and 0.30 at 355 nm 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.

In this study we investigate the climatological behavior of the aerosol optical properties over Thessaloniki during the years 2003–2017. For this purpose, measurements of two independent instruments, a lidar and a sunphotometer, were used. These two instruments represent two individual networks, the European Lidar Aerosol Network (EARLINET) and the Aerosol Robotic Network (AERONET). They include different measurement schedules. Fourteen years of lidar and sunphotometer measurements were analyzed, independently of each other, in order to obtain the annual cycles and trends of various optical and geometrical aerosol properties in the boundary layer, in the free troposphere, and for the whole atmospheric column. The analysis resulted in consistent statistically significant and decreasing trends of aerosol optical depth (AOD) at 355 nm of −23.2 and −22.3 % per decade in the study period over Thessaloniki for the EARLINET and the AERONET datasets, respectively. Therefore, the analysis indicates that the EARLINET sampling schedule can be quite effective in producing data that can be applied to long-term climatological studies. It is also shown that the observed decreasing trend is mainly attributed to changes in the aerosol load inside the boundary layer. Seasonal profiles of the most dominant aerosol mixture types observed over Thessaloniki have been generated from the lidar data. The higher values of the vertically resolved extinction coefficient at 355 nm appear in summer, while the lower ones appear in winter. The dust component is more dominant in the free troposphere than in the boundary layer during summer. The biomass burning layers tend to arrive in the free troposphere during spring and summer. This kind of information can be quite useful for applications that require a priori aerosol profiles. For instance, they can be utilized in models that require aerosol climatological data as input, in the development of algorithms for satellite products, and also in passive remote-sensing techniques that require knowledge of the aerosol vertical distribution.