Long-range-transported Canadian smoke layers in the stratosphere over northern France were detected by three lidar systems in August 2017. The peaked optical depth of the stratospheric smoke layer exceeds 0.20 at 532 nm, which is comparable with the simultaneous tropospheric aerosol optical depth. The measurements of satellite sensors revealed that the observed stratospheric smoke plumes were transported from Canadian wildfires after being lofted by strong pyro-cumulonimbus. Case studies at two observation sites, Lille (lat 50.612, long 3.142, 60 m a.s.l.) and Palaiseau (lat 48.712, long 2.215, 156 m a.s.l.), are presented in detail. Smoke particle depolarization ratios are measured at three wavelengths: over 0.20 at 355 nm, 0.18–0.19 at 532 nm, and 0.04–0.05 at 1064 nm. The high depolarization ratios and their spectral dependence are possibly caused by the irregular-shaped aged smoke particles and/or the mixing with dust particles. Similar results are found by several European lidar stations and an explanation that can fully resolve this question has not yet been found. Aerosol inversion based on lidar 2α+3β data derived a smoke effective radius of about 0.33 µm for both cases. The retrieved single-scattering albedo is in the range of 0.8 to 0.9, indicating that the smoke plumes are absorbing. The absorption can cause perturbations to the temperature vertical profile, as observed by ground-based radiosonde, and it is also related to the ascent of the smoke plumes when exposed in sunlight. A direct radiative forcing (DRF) calculation is performed using the obtained optical and microphysical properties. The calculation revealed that the smoke plumes in the stratosphere can significantly reduce the radiation arriving at the surface, and the heating rate of the plumes is about 3.5 K day⁻¹. The study provides a valuable characterization for aged smoke in the stratosphere, but efforts are still needed in reducing and quantifying the errors in the retrieved microphysical properties as well as radiative forcing estimates.

This article presents a study of long-range transported biomass burning aerosols (BBA) originated from the North American wildfires in September 2020. The BBA plumes presented in this study were in the troposphere and underwent 1–2 weeks of aging before arriving at the lidar station ATOLL (ATmospheric Observatory of LiLle) in northern France. A novel lidar-derived dataset, $\mathrm{2}\mathit{\alpha }+\mathrm{3}\mathit{\beta }+\mathrm{3}\mathit{\delta }+\mathit{\varphi }$ (α: extinction coefficient; β: backscatter coefficient; δ: particle linear depolarization ratio, i.e., PLDR; ϕ: fluorescence capacity), is provided for the characterization of BBA. The fluorescence capacity is an intensive aerosol parameter describing the ability of aerosols in producing fluorescence when exposed to UV excitation. In our BBA observations, obvious variations in aerosol intensive parameters, reflecting the variability of BBA properties, were detected. The PLDRs varied from less than 0.03 at all wavelengths to 0.15–0.22 and 0.12–0.16, respectively, at 355 and 532 nm. The extinction related Angström exponent was within the range of −0.3 to 1.0 and the fluorescence capacity was 1.0 × 10⁻⁴–4.0 × 10⁻⁴. Lidar ratio as low as 24 ± 4 sr (50 ± 8 sr) was observed in the BBA plumes at 355 (532) nm on 17–18 September, which was lower than most previously observed aged BBAs. These variations are likely correlated with the combustion process, the lifting of BBA plumes and the conditions (temperature, humidities, etc.) in the aging process. In addition, our results indicate BBA could act as ice nucleating particles in tropospheric conditions. The lidar fluorescence channel proves to be an important added value in aerosol characterization and aerosol–cloud interactions studies, due to its high sensitivity. With the increase in wildfire occurrence and intensity, BBAs become a more and more important atmospheric component. In this context, we show the potential of our novel lidar-derived dataset for aged BBA particles' characterization and for the understanding of their role in cloud processes.

The paper presents an approach to revealing the variability in aerosol type, at high spatiotemporal resolution, by combining fluorescence and Mie–Raman lidar observations. The multiwavelength Mie–Raman lidar system in operation at the ATOLL (ATmospheric Observation at liLLe) platform, Laboratoire d'Optique Atmosphérique, University of Lille, has included, since 2019, a wideband fluorescence channel allowing the derivation of the fluorescence backscattering coefficient β_F. The fluorescence capacity G_F, which is the ratio of β_F to the aerosol backscattering coefficient, is an intensive particle property, strongly changing with aerosol type, thus providing a relevant basis for aerosol classification. In this first stage of research, only two intensive properties are used for classification, namely the particle depolarization ratio at 532 nm, δ₅₃₂, and the fluorescence capacity, G_F. These properties are considered because they can be derived at high spatiotemporal resolution and are quite specific to each aerosol type. In particular, in this study, we use a δ₅₃₂–G_F diagram to identify smoke, dust, pollen, and urban aerosol particles. We applied our new classification approach to lidar data obtained during the 2020–2021 period, which includes strong smoke, dust, and pollen episodes. The particle classification was performed with a height resolution of about 60 m and temporal resolution better than 8 min.

A remote sensing method, based on fluorescence lidar measurements, that allows us to detect and to quantify the smoke content in the upper troposphere and lower stratosphere (UTLS) is presented. The unique point of this approach is that smoke and cirrus properties are observed in the same air volume simultaneously. In this article, we provide results of fluorescence and multiwavelength Mie–Raman lidar measurements performed at ATOLL (ATmospheric Observation at liLLe) observatory from Laboratoire d'Optique Atmosphérique, University of Lille, during strong smoke episodes in the summer and autumn seasons of 2020. The aerosol fluorescence was induced by 355 nm laser radiation, and the fluorescence backscattering was measured in a single spectral channel, centered at 466 nm and having 44 nm width. To estimate smoke particle properties, such as number, surface area and volume concentration, the conversion factors, which link the fluorescence backscattering and the smoke microphysical properties, are derived from the synergy of multiwavelength Mie–Raman and fluorescence lidar observations. Based on two case studies, we demonstrate that the fluorescence lidar technique provides the possibility to estimate the smoke surface area concentration within freshly formed cirrus layers. This value was used in the smoke ice nucleating particle (INP) parameterization scheme to predict ice crystal number concentrations in cirrus generation cells.

Lidar plays an essential role in monitoring the vertical variation of atmospheric aerosols. However, due to the limited information that lidar measurements provide, ill-posedness still remains a big challenge in quantitative lidar remote sensing. In this study, we describe the Basic algOrithm for REtrieval of Aerosol with Lidar (BOREAL), which is based on maximum likelihood estimation (MLE), and retrieve aerosol microphysical properties from extinction and backscattering measurements of multi-wavelength Mie–Raman lidar systems. The algorithm utilizes different types of a priori constraints to better constrain the solution space and suppress the influence of the ill-posedness. Sensitivity test demonstrates that BOREAL could retrieve particle volume size distribution (VSD), total volume concentration (V_t), effective radius (R_eff), and complex refractive index (CRI = n − ik) of simulated aerosol models with satisfying accuracy. The application of the algorithm to real aerosol events measured by LIlle Lidar AtmosphereS (LILAS) shows it is able to realize fast and reliable retrievals of different aerosol scenarios (dust, aged-transported smoke, and urban aerosols) with almost uniform and simple pre-settings. Furthermore, the algorithmic principle allows BOREAL to incorporate measurements with different and non-linearly related errors to the retrieved parameters, which makes it a flexible and generalized algorithm for lidar retrieval.

The fluorescence lidar at the Prokhorov General Physics Institute (Moscow) was utilized to study smoke transported over the Atlantic during the wildfire season from May to September 2023. The lidar system, which is based on a tripled Nd : YAG laser, performs fluorescence measurements across five spectral intervals centered at wavelengths of 438, 472, 513, 560 and 614 nm. This configuration enables the assessment of the spectral dependence of fluorescence backscattering over a broad range of altitudes, from the planetary boundary layer (PBL) to the middle and upper troposphere (MUT). The fluorescence capacity of smoke, defined as the ratio of fluorescence backscattering to aerosol backscattering at the laser wavelength, exhibits significant variation in the MUT, with changes of up to a factor of 3. This variation is likely indicative of differences in the relative concentration of organic compounds within the smoke. Analysis of more than 40 smoke episodes has enabled an evaluation of the height dependence of smoke fluorescence properties. Observations reveal that the fluorescence capacity generally increases with altitude, suggesting a higher concentration of organic compounds in the MUT compared to the lower troposphere. Additionally, the measurements consistently show differences in the fluorescence spectra of smoke and urban aerosol. Urban aerosol fluorescence tends to decrease gradually with wavelength, whereas the peak of smoke fluorescence is observed in the 513 and 560 nm channels. This spectral distinction provides an effective means of separating smoke from urban aerosol. The technique was applied the analysis of events where smoke from the upper troposphere descended into the PBL, demonstrating its utility in distinguishing between these aerosol types.