Search

Polarization properties of the fluorescence induced by polarized laser radiation are widely considered in laboratory studies. In lidar observations, however, only the total backscattered power of fluorescence is analyzed. In this paper we present results obtained with a modified Mie–Raman–fluorescence lidar operated at the ATOLL observatory, Laboratoire d'Optique Atmosphérique, University of Lille, France, allowing us to measure depolarization ratios of fluorescence at 466 nm (δF) and of water vapor Raman backscatter. Measurements were performed in May–June 2023 during the Alberta forest fires season when smoke plumes were almost continuously transported over the Atlantic Ocean towards Europe. During the same period, smoke plumes from the same sources were also detected and analyzed in Moscow, at the General Physics Institute (GPI), with a five-channel fluorescence lidar able to measure fluorescence backscattering at 438, 472, 513, 560 and 614 nm. Results demonstrate that, inside the planetary boundary layer (PBL), the urban aerosol fluorescence is maximal at 438 nm, and then it gradually decreases with the increase in wavelength. The smoke layers observed within 4–6 km height present a maximum fluorescence at 513 nm, while in the upper troposphere, fluorescence maximum shifts to 560 nm. Regarding the fluorescence depolarization ratio, for smoke its value typically varies within the 45 %–55 % range. The depolarization ratio of the water vapor Raman backscattering at 408 nm is shown to be quite low (2±0.5 %) in the absence of fluorescence because the narrowband interference filter (0.3 nm) in the water vapor channel selects only the strongest vibrational lines of the Raman spectrum. As a result, the depolarization ratio at the water vapor Raman channel is sensitive to the presence of strongly depolarized fluorescence backscattering and can be used for the evaluation of the aerosol fluorescence contribution to measured water vapor mixing ratio.

The multiwavelength Mie–Raman–fluorescence lidar of the University of Lille has the capability to measure three aerosol backscattering coefficients, two extinction coefficients and three linear depolarization ratios, together with fluorescence backscattering at 466 nm. It was used to characterize aerosols during the pollen season in the north of France for the period March–June 2020. The results of observations demonstrate that the presence of pollen grains in aerosol mixture leads to an increase in the depolarization ratio. Moreover, the depolarization ratio exhibits a strong spectral dependence increasing with wavelength, which is expected for the mixture containing fine background aerosols with low depolarization and strongly depolarizing pollen grains. A high depolarization ratio correlates with the enhancement of the fluorescence backscattering, corroborating the presence of pollen grains. Obtained results demonstrate that simultaneous measurements of particle depolarization and fluorescence allows for the separation of dust, smoke particles and aerosol mixtures containing the pollen grains.

To study the feasibility of a fluorescence lidar for aerosol characterization, the fluorescence channel is added to the LILAS multiwavelength Mie–Raman lidar of Lille University, France. A part of the fluorescence spectrum induced by 355 nm laser radiation is selected by the interference filter of 44 nm bandwidth centered at 466 nm. Such an approach has proved to have high sensitivity, allowing fluorescence signals from weak aerosol layers to be detected and the fluorescence backscattering coefficient from the ratio of fluorescence and nitrogen Raman backscatters to be calculated. Observations were performed during the November 2019–February 2020 period. The fluorescence capacity (ratio of fluorescence to elastic backscattering coefficients), measured under conditions of low relative humidity, varied in a wide range, being the highest for the smoke and the lowest for the dust particles. The results presented also demonstrate that the fluorescence measurements can be used for monitoring the aerosol inside the cloud layers.

We present the results of methane profiling in the lower troposphere using LILAS Raman lidar from the Lille University observatory platform (France). The lidar is based on a frequency-tripled Nd:YAG laser, and nighttime profiling up to 4000 with 100 m height resolution is possible for methane. Agreement between the measured photon-counting rate in the CH4 Raman channel in the free troposphere and numerical simulations for a typical CH4 background mixing ratio (2 ppm) confirms that CH4 Raman scattering is detected. The mixing ratio is calculated from the ratio of methane (395.7 nm) and nitrogen (386.7 nm) Raman backscatters, and within the planetary boundary layer, an increase of the CH4 mixing ratio, up to a factor of 2, is observed. Different possible interfering factors, such as leakage of the elastic signal and aerosol fluorescence, have been taken into consideration. Tests using backscattering from clouds confirmed that the filters in the Raman channel provide sufficient rejection of elastic scattering. The measured methane profiles do not correlate with aerosol backscattering, which corroborates the hypothesis that, in the planetary boundary layer, not aerosol fluorescence but CH4 is observed. However, the fluorescence contribution cannot be completely excluded and, for future measurements, we plan to install an additional control channel close to 393 nm, where no strong Raman lines exist and only fluorescence can be observed.

Observations of multiwavelength Mie–Raman lidar taken during the SHADOW field campaign are used to analyze a smoke–dust episode over West Africa on 24–27 December 2015. For the case considered, the dust layer extended from the ground up to approximately 2000 m while the elevated smoke layer occurred in the 2500–4000 m range. The profiles of lidar measured backscattering, extinction coefficients, and depolarization ratios are compared with the vertical distribution of aerosol parameters provided by the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The MERRA-2 model simulated the correct location of the near-surface dust and elevated smoke layers. The values of modeled and observed aerosol extinction coefficients at both 355 and 532 nm are also rather close. In particular, for the episode reported, the mean value of difference between the measured and modeled extinction coefficients at 355 nm is 0.01 km−1 with SD of 0.042 km−1. The model predicts significant concentration of dust particles inside the elevated smoke layer, which is supported by an increased depolarization ratio of 15 % observed in the center of this layer. The modeled at 355 nm the lidar ratio of 65 sr in the near-surface dust layer is close to the observed value (70 ± 10) sr. At 532 nm, however, the simulated lidar ratio (about 40 sr) is lower than measurements (55 ± 8 sr). The results presented demonstrate that the lidar and model data are complimentary and the synergy of observations and models is a key to improve the aerosols characterization.

Aerosol particles are important and highly variable components of the terrestrial atmosphere, and they affect both air quality and climate. In order to evaluate their multiple impacts, the most important requirement is to precisely measure their characteristics. Remote sensing technologies such as lidar (light detection and ranging) and sun/sky photometers are powerful tools for determining aerosol optical and microphysical properties. In our work, we applied several methods to joint or separate lidar and sun/sky-photometer data to retrieve aerosol properties. The Raman technique and inversion with regularization use only lidar data. The LIRIC (LIdar-Radiometer Inversion Code) and recently developed GARRLiC (Generalized Aerosol Retrieval from Radiometer and Lidar Combined data) inversion methods use joint lidar and sun/sky-photometer data. This paper presents a comparison and discussion of aerosol optical properties (extinction coefficient profiles and lidar ratios) and microphysical properties (volume concentrations, complex refractive index values, and effective radius values) retrieved using the aforementioned methods. The comparison showed inconsistencies in the retrieved lidar ratios. However, other aerosol properties were found to be generally in close agreement with the AERONET (AErosol RObotic NETwork) products. In future studies, more cases should be analysed in order to clearly define the peculiarities in our results.

Vibrational Raman scattering from nitrogen is commonly used in aerosol lidars for evaluation of particle backscattering (β) and extinction (α) coefficients. However, at mid-visible wavelengths, particularly in the daytime, previous measurements have possessed low signal-to-noise ratio. Also, vibrational scattering is characterized by a significant frequency shift of the Raman component, so for the calculation of α and β information about the extinction Ångström exponent is needed. Simulation results presented in this study demonstrate that ambiguity in the choice of Ångström exponent can be the a significant source of uncertainty in the calculation of backscattering coefficients when optically thick aerosol layers are considered. Both of these issues are addressed by the use of pure-rotational Raman (RR) scattering, which is characterized by a higher cross section compared to nitrogen vibrational scattering, and by a much smaller frequency shift, which essentially removes the sensitivity to changes in the Ångström exponent. We describe a practical implementation of rotational Raman measurements in an existing Mie–Raman lidar to obtain aerosol extinction and backscattering at 532 nm. A 2.3 nm width interference filter was used to select a spectral range characterized by low temperature sensitivity within the anti-Stokes branch of the RR spectrum. Simulations demonstrate that the temperature dependence of the scattering cross section does not exceed 1.5 % in the 230–300 K range, making correction for this dependence quite easy. With this upgrade, the NASA GSFC multiwavelength Raman lidar has demonstrated useful α532 measurements and was used for regular observations. Examples of lidar measurements and inversion of optical data to the particle microphysics are given.

This work deals with the applicability of the linear estimation technique (LE) to invert spectral measurements of aerosol optical depth (AOD) provided by AERONET CIMEL sun photometers. The inversion of particle properties using only direct-sun AODs allows the evaluation of parameters such as effective radius (reff) and columnar volume aerosol content (V) with significantly better temporal resolution than the operational AERONET algorithm which requires both direct sun and sky radiance measurements. Sensitivity studies performed demonstrate that the constraints on the range of the inversion are very important to minimize the uncertainties, and therefore estimates of reff can be obtained with uncertainties less than 30 % and of V with uncertainties below 40 %. The LE technique is applied to data acquired at five AERONET sites influenced by different aerosol types and the retrievals are compared with the results of the operational AERONET code. Good agreement between the two techniques is obtained when the fine mode predominates, while for coarse mode cases the LE results systematically underestimate both reff and V. The highest differences are found for cases where no mode predominates. To minimize these biases, correction functions are developed using the multi-year database of observations at selected sites, where the AERONET retrieval is used as the reference. The derived corrections are tested using data from 18 other AERONET stations offering a range of aerosol types. After correction, the LE retrievals provide better agreement with AERONET for all the sites considered. Finally, the LE approach developed here is applied to AERONET and star-photometry measurements in the city of Granada (Spain) to obtain day-to-night time evolution of columnar aerosol microphysical properties.

In this work we study the effects of systematic and random errors on the inversion of multiwavelength (MW) lidar data using the well-known regularization technique to obtain vertically resolved aerosol microphysical properties. The software implementation used here was developed at the Physics Instrumentation Center (PIC) in Troitsk (Russia) in conjunction with the NASA/Goddard Space Flight Center. Its applicability to Raman lidar systems based on backscattering measurements at three wavelengths (355, 532 and 1064 nm) and extinction measurements at two wavelengths (355 and 532 nm) has been demonstrated widely. The systematic error sensitivity is quantified by first determining the retrieved parameters for a given set of optical input data consistent with three different sets of aerosol physical parameters. Then each optical input is perturbed by varying amounts and the inversion is repeated. Using bimodal aerosol size distributions, we find a generally linear dependence of the retrieved errors in the microphysical properties on the induced systematic errors in the optical data. For the retrievals of effective radius, number/surface/volume concentrations and fine-mode radius and volume, we find that these results are not significantly affected by the range of the constraints used in inversions. But significant sensitivity was found to the allowed range of the imaginary part of the particle refractive index. Our results also indicate that there exists an additive property for the deviations induced by the biases present in the individual optical data. This property permits the results here to be used to predict deviations in retrieved parameters when multiple input optical data are biased simultaneously as well as to study the influence of random errors on the retrievals. The above results are applied to questions regarding lidar design, in particular for the spaceborne multiwavelength lidar under consideration for the upcoming ACE mission.

The results of the application of the linear estimation technique to multiwavelength Raman lidar measurements performed during the summer of 2011 in Greenbelt, MD, USA, are presented. We demonstrate that multiwavelength lidars are capable not only of providing vertical profiles of particle properties but also of revealing the spatio-temporal evolution of aerosol features. The nighttime 3β + 1α lidar measurements on 21 and 22 July were inverted to spatio-temporal distributions of particle microphysical parameters, such as volume, number density, effective radius and the complex refractive index. The particle volume and number density show strong variation during the night, while the effective radius remains approximately constant. The real part of the refractive index demonstrates a slight decreasing tendency in a region of enhanced extinction coefficient. The linear estimation retrievals are stable and provide time series of particle parameters as a function of height at 4 min resolution. AERONET observations are compared with multiwavelength lidar retrievals showing good agreement.

An algorithm for linear estimation of aerosol bulk properties such as particle volume, effective radius and complex refractive index from multiwavelength lidar measurements is presented. The approach uses the fact that the total aerosol concentration can well be approximated as a linear combination of aerosol characteristics measured by multi-wavelength lidar. Therefore, the aerosol concentration can be estimated from lidar measurements without the need to derive the size distribution, which entails more sophisticated procedures. The definition of the coefficients required for the linear estimates is based on an expansion of the particle size distribution in terms of the measurement kernels. Once the coefficients are established, the approach permits fast retrieval of aerosol bulk properties when compared with the full regularization technique. In addition, the straightforward estimation of bulk properties stabilizes the inversion making it more resistant to noise in the optical data. Numerical tests demonstrate that for data sets containing three aerosol backscattering and two extinction coefficients (so called 3β + 2α) the uncertainties in the retrieval of particle volume and surface area are below 45% when input data random uncertainties are below 20%. Moreover, using linear estimates allows reliable retrievals even when the number of input data is reduced. To evaluate the approach, the results obtained using this technique are compared with those based on the previously developed full inversion scheme that relies on the regularization procedure. Both techniques were applied to the data measured by multiwavelength lidar at NASA/GSFC. The results obtained with both methods using the same observations are in good agreement. At the same time, the high speed of the retrieval using linear estimates makes the method preferable for generating aerosol information from extended lidar observations. To demonstrate the efficiency of the method, an extended time series of observations acquired in Turkey in May 2010 was processed using the linear estimates technique permitting, for what we believe to be the first time, temporal-height distributions of particle parameters.