Raman Lidar System Research Articles

Powerful Raman Lidar systems for atmospheric analysis and high-energy physics experiments

In this paper the author presents modern commercial Raman Lidar systems which can be applied to high-energy physics experiments. Raymetrics is a world-leader in laser remote (lidar) sensing applications. Products series include lidar systems for various applications like atmospheric analysis, meteorology, and recently more operational applications including volcanic ash detection systems, visual rangers for application to airports etc.

Design of Laser Based Monitoring Systems for Compliance Management of Odorous and Hazardous Air Pollutants in Selected Chemical Industrial Estates at Hyderabad, India

Abstract. Industrialization can no longer sustain without internalization of the concerns of the receiving environment and land-use. Increased awareness and public pressure, coupled with regulatory instruments and bodies exert constant pressure on industries to control their emissions to a level acceptable to the receiving environment. However, when a group of industries come-up together as an industrial estate, the cumulative impacts of all the industries together often challenges the expected/desired quality of receiving environment, requiring stringent pollution control and monitoring measures. Laser remote sensing techniques provide powerful tools for environmental monitoring. These methods provide range resolved measurements of concentrations of various gaseous pollutants and suspended particulate matter (SPM) not only in the path of the beam but over the entire area. A three dimensional mapping of the pollutants and their dispersal can be estimated using the laser remote sensing methods on a continuous basis. Laser Radar (Lidar) systems are the measurements technology used in the laser remote sensing methods. Differential absorption lidar (DIAL) and Raman Lidar technologies have proved to be very useful for remote sensing of air pollutants. DIAL and Raman lidar systems can be applied for range resolved measurements of molecules like SO2, NO2, O3 Hg, CO, C2H4, H2O, CH4, hydrocarbons etc. in real time on a continuous basis. This paper describes the design details of the DAIL and Raman lidar techniques for measurement of various hazardous air pollutants which are being released into the atmosphere by the chemical industries operating in the Bachupally industrial Estate area at Hyderabad, India. The relative merits of the two techniques have been studied and the minimum concentration of pollutants that can be measured using these systems are presented. A dispersion model of the air pollutants in the selected chemical industrial estates at Hyderabad has been developed.

Gluing for Raman lidar systems using the lamp mapping technique.

In the context of combined analog and photon counting (PC) data acquisition in a Lidar system, glue coefficients are defined as constants used for converting an analog signal into a virtual PC signal. The coefficients are typically calculated using Lidar profile data taken under clear, nighttime conditions since, in the presence of clouds or high solar background, it is difficult to obtain accurate glue coefficients from Lidar backscattered data. Here we introduce a new method in which we use the lamp mapping technique (LMT) to determine glue coefficients in a manner that does not require atmospheric profiles to be acquired and permits accurate glue coefficients to be calculated when adequate Lidar profile data are not available. The LMT involves scanning a halogen lamp over the aperture of a Lidar receiver telescope such that the optical efficiency of the entire detection system is characterized. The studies shown here involve two Raman lidar systems; the first from Howard University and the second from NASA/Goddard Space Flight Center. The glue coefficients determined using the LMT and the Lidar backscattered method agreed within 1.2% for the water vapor channel and within 2.5% for the nitrogen channel for both Lidar systems. We believe this to be the first instance of the use of laboratory techniques for determining the glue coefficients for Lidar data analysis.

Retrieval of the single scattering albedo of Asian dust mixed with pollutants using lidar observations

The vertical distribution of single scattering albedos (SSAs) of Asian dust mixed with pollutants was derived using the multi-wavelength Raman lidar observation system at Gwangju (35.10°N, 126.53°E). Vertical profiles of both backscatter and extinction coefficients for dust and non-dust aerosols were extracted from a mixed Asian dust plume using the depolarization ratio from lidar observations. Vertical profiles of backscatter and extinction coefficients of non-dust particles were input into an inversion algorithm to retrieve the SSAs of non-dust aerosols. Atmospheric aerosol layers at different heights had different light-absorbing characteristics. The SSAs of non-dust particles at each height varied with aerosol type, which was either urban/industrial pollutants from China transported over long distances at high altitude, or regional/local pollutants from the Korean peninsula. Taking advantage of independent profiles of SSAs of non-dust particles, vertical profiles of SSAs of Asian dust mixed with pollutants were estimated for the first time, with a new approach suggested in this study using an empirical determination of the SSA of pure dust. The SSAs of the Asian dust-pollutants mixture within the planetary boundary layer (PBL) were in the range 0.88–0.91, while the values above the PBL were in the range 0.76–0.87, with a very low mean value of 0.76±0.05. The total mixed dust plume SSAs in each aerosol layer were integrated over height for comparison with results from the Aerosol Robotics Network (AERONET) measurements. Values of SSA retrieved from lidar observations of 0.92±0.01 were in good agreement with the results from AERONET measurements.

Compact airborne Raman lidar for profiling aerosol, water vapor and clouds.

A compact airborne Raman lidar system, which can perform water vapor and aerosol measurements both during nighttime and daytime is described. The system design, setup and the data processing methods are described in the paper. The Raman lidar was tested on University of Wyoming King Air research aircraft (UWKA) during the Wyoming King Air PBL Exploratory Experiment (KAPEE) in 2010. An observation showing clouds, aerosols and a dry line is presented to illustrate the lidar detection capabilities. Comparisons of the water vapor and aerosol measurements using the Raman lidar and other in situ airborne instruments show good agreement.

Aircraft Evaluation of Ground-Based Raman Lidar Water Vapor Turbulence Profiles in Convective Mixed Layers

AbstractHigh temporal and vertical resolution water vapor measurements by Raman and differential absorption lidar systems have been used to characterize the turbulent fluctuations in the water vapor mixing ratio field in convective mixed layers. Since daytime Raman lidar measurements are inherently noisy (due to solar background and weak signal strengths), the analysis approach needs to quantify and remove the contribution of the instrument noise in order to derive the desired atmospheric water vapor mixing ratio variance and skewness profiles. This is done using the approach outlined by Lenschow et al.; however, an intercomparison with in situ observations was not performed.Water vapor measurements were made by a diode laser hygrometer flown on a Twin Otter aircraft during the Routine Atmospheric Radiation Measurement (ARM) Program Aerial Facility Clouds with Low Optical Water Depths Optical Radiative Observations (RACORO) field campaign over the ARM Southern Great Plains (SGP) site in 2009. Two days with Twin Otter flights were identified where the convective mixed layer was quasi stationary, and hence the 10-s, 75-m data from the SGP Raman lidar could be analyzed to provide profiles of water vapor mixing ratio variance and skewness. Airborne water vapor observations measured during level flight legs were compared to the Raman lidar data, demonstrating good agreement in both variance and skewness. The results also illustrate the challenges of comparing a point sensor making measurements over time to a moving platform making similar measurements horizontally.

Ice thickness measurements by Raman scattering.

A compact Raman LIDAR system with a spectrograph was used for express ice thickness measurements. The difference between the Raman spectra of ice and liquid water is employed to locate the ice-water interface while elastic scattering was used for air--ice surface detection. This approach yields an error of only 2 mm for an 80 mm thick ice sample, indicating that it is a promising express noncontact thickness measurements technique in field experiments.

Analysis of cirrus cloud spectral signatures in the far infrared

This paper analyses high spectral resolution downwelling radiance measurements in the far infrared in the presence of cirrus clouds taken by the REFIR-PAD interferometer, deployed at 3500m above the sea level at the Testa Grigia station (Italy), during the Earth COoling by WAter vapouR emission (ECOWAR) campaign. Atmospheric state and cloud geometry are characterised by the co-located millimeter-wave spectrometer GBMS and by radiosonde profile data, an interferometer (I-BEST) and a Raman lidar system deployed at a nearby location (Cervinia). Cloud optical depth and effective diameter are retrieved from REFIR-PAD data using a limited number of channels in the 820–960cm−1 interval. The retrieved cloud parameters are the input data for simulations covering the 250–1100cm−1 band in order to test our ability to reproduce the REFIR-PAD spectra in the presence of ice clouds. Inverse and forward simulations are based on the same radiative transfer code. A priori information concerning cloud ice vertical distribution is used to better constrain the simulation scheme and an analysis of the degree of approximation of the phase function within the radiative transfer codes is performed to define the accuracy of computations. Simulation-data residuals over the REFIR-PAD spectral interval show an excellent agreement in the window region, but values are larger than total measurement uncertainties in the far infrared. Possible causes are investigated. It is shown that the uncertainties related to the water vapour and temperature profiles are of the same order as the sensitivity to the a priori assumption on particle habits for an up-looking configuration. In case of a down-looking configuration, errors due to possible incorrect description of the water vapour profile would be drastically reduced.

Characterization of the planetary boundary layer height and structure by Raman lidar: comparison of different approaches

Abstract. The planetary boundary layer (PBL) includes the portion of the atmosphere which is directly influenced by the presence of the earth's surface. Aerosol particles trapped within the PBL can be used as tracers to study the boundary-layer vertical structure and time variability. As a result of this, elastic backscatter signals collected by lidar systems can be used to determine the height and the internal structure of the PBL. The present analysis considers three different methods to estimate the PBL height. The first method is based on the determination of the first-order derivative of the logarithm of the range-corrected elastic lidar signals. Estimates of the PBL height for specific case studies obtained through this approach are compared with simultaneous estimates from the potential temperature profiles measured by radiosondes launched simultaneously to lidar operation. Additional estimates of the boundary layer height are based on the determination of the first-order derivative of the range-corrected rotational Raman lidar signals. This latter approach results to be successfully applicable also in the afternoon–evening decaying phase of the PBL, when the effectiveness of the approach based on the elastic lidar signals may be compromised or altered by the presence of the residual layer. Results from these different approaches are compared and discussed in the paper, with a specific focus on selected case studies collected by the University of Basilicata Raman lidar system BASIL during the Convective and Orographically-induced Precipitation Study (COPS).

Data Assimilation of Water Vapor for a Numerical Weather Prediction Model Using the Raman Lidar System

Data Assimilation of Water Vapor for a Numerical Weather Prediction Model Using the Raman Lidar System

Effects of systematic and random errors on the retrieval of particle microphysical properties from multiwavelength lidar measurements using inversion with regularization

Abstract. 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.

Water vapour mixing ratio profiles over Hornsund, Arctic. Intercomparison of lidar and AIRS results

Since October 2009, a ground-based Raman lidar system has been deployed to perform a regular, night-time, vertical sounding of a water vapour content in the lower and middle troposphere above Polish Polar Station at Hornsund (77.00°N, 15.55°E, 10 m a.s.l.) in the Arctic. The water vapour mixing ratio profiles were obtained for the atmosphere up to 6 km altitude, based on analysis of inelastic Raman backscattering signals from nitrogen molecules (at 387 nm) and water vapour particles (at 407 nm), calibrated with the data from a local Vaisala’s automatic meteorological station. The results obtained for winter seasons in the years 2009–2012 are in a good general agreement with the results obtained from the atmospheric infrared sounder (AIRS) on the Aqua satellite.

Simultaneous PMC and PMSE observations with a ground-based lidar and SuperDARN HF radar at Syowa Station, Antarctica

Abstract. A Rayleigh–Raman lidar system was installed in January 2011 at Syowa Station, Antarctica (69.0° S, 39.6° E). Polar mesospheric clouds (PMCs) were detected by lidar at around 22:30 UTC (LT −3 h) on 4 February 2011, which was the first day of observation. This was the first detection of PMCs over Syowa Station by lidar. On the same day, a Super Dual Auroral Radar Network (SuperDARN) HF radar with oblique-incidence beams detected polar mesospheric summer echoes (PMSE) between 21:30 and 23:00 UTC. This event is regarded as the last PMC activity around Syowa Station during the austral summer season (2010–2011), since no other PMC signals were detected by lidar in February 2011. This is consistent with results of PMC and mesopause temperature observations by satellite-born instruments of AIM (Aeronomy of Ice in the Mesosphere)/CIPS (Cloud Imaging and Particle Size) and AURA/MLS (Microwave Limb Sounder) and horizontal wind measurements taken by a separate MF radar. Doppler velocity of PMSE observed by the HF radar showed motion toward Syowa Station (westward). This westward motion is consistent with the wind velocities obtained by the MF radar. However, the PMSE region showed horizontal motion from a north-to-south direction during the PMC event. This event indicates that the apparent horizontal motion of the PMSE region can deviate from neutral wind directions and observed Doppler velocities.

다파장 라만 라이다 시스템을 이용한 고도별 황사의 단산란 알베도 산출

본 연구에서는 다파장 라만 라이다 시스템을 이용하여 대기 중의 비구형 순수 황사입자와 구형 오염 입자가 혼합된 황사 입자의 단산란 알베도를 산출할 수 있는 방법론을 제시하고, 실제 대기 관측 사례 분석 자료로부터 정확도를 검증하고자 하였다. 편광소멸도는 황사와 비황사와의 혼합정도에 반비례함을 응용하여 편광소멸도 값으로부터 황사비를 산출하고 이를 이용하여 황사와 비황사로 황사층을 구분하였다. 산출된 비황사의 두 파장(355, 532 nm)의 소산계수와 세 파장(355, 532, 1064 nm)의 후방산란계수를 이용하여 역행렬 분석을 수행하여 비황사의 고도별 단산란알베도를 도출하였다. 황사와 비황사의 가중치를 소산계수값으로부터 산출하고 각 가중치를 황사와 비황사에 적용하여 황사 층 전체의 고도별 단산란알베도를 산출하였다. 단, 황사의 단산란알베도는 순수황사로 가정하여 발원지에서 측정된 순수황사가 나타내는 0.96의 값을 적용하였다. 본 연구로부터 개발된 분석방법은 기존의 원격탐사 기술의 한계점을 극복하여 황사의 이동시 타 오염입자와의 혼합에 따른 광학적 특성의 변화에 대한 정밀한 자료를 제공할 수 있을 것으로 기대된다. A new approach to retrieve the single-scattering albedo (SSA) of Asian dust plume, mixed with pollution particles, using multi-wavelength Raman lidar system was suggested in this study. Asian dust plume was separated as dust and non-dust particle (i.e. spherical particle) by the particle depolarization ratio at 532 nm. The vertical profiles of optical properties (the particle extinction coefficient at 355 and 532 nm and backscatter coefficient at 355, 532 and 1064 nm) for non-dust particle were used as input parameter for the inversion algorithm. The inversion algorithm provides the vertical distribution of microphysical properties of non-dust particle only so that the estimation of the SSA for the Asian dust in mixing state was suggested in this study. In order to estimate the SSA for the mixed Asian dust, we combined the SSA of non-dust particles retrieved by the inversion algorithms with assumed the SSA of 0.96 at 532 nm for dust. The retrieved SSA of Asian dust plume by lidar data was compared with the Aerosol Robotics Network (AERONET) retrieved values and showed good agreement.

Experimental estimation of Raman lidar sensitivity in the middle UV

The experimental results of remote detection of vapors of some atmospheric chemical compounds using a Raman lidar system with a narrow-line excimer KrF laser and a multichannel spectral analyzer, based on a diffraction spectrograph and an intensified CCD camera, are presented. The system sensitivity is estimated for a sounding range of 6–10 m. Using additional means for suppressing the intense Raman bands of N2 and O2 molecules, a detection threshold of 1 ppm is reached. Base rovibrational Raman bands of oxygen and nitrogen and their first overtones are observed during experiments on noise level estimation and Raman spectra recording in the atmosphere. The absence of overlapping of fluorescence and Raman signals is confirmed experimentally.

Four-dimensional distribution of the 2010 Eyjafjallajökull volcanic cloud over Europe observed by EARLINET

Abstract. The eruption of the Icelandic volcano Eyjafjallajökull in April–May 2010 represents a "natural experiment" to study the impact of volcanic emissions on a continental scale. For the first time, quantitative data about the presence, altitude, and layering of the volcanic cloud, in conjunction with optical information, are available for most parts of Europe derived from the observations by the European Aerosol Research Lidar NETwork (EARLINET). Based on multi-wavelength Raman lidar systems, EARLINET is the only instrument worldwide that is able to provide dense time series of high-quality optical data to be used for aerosol typing and for the retrieval of particle microphysical properties as a function of altitude. In this work we show the four-dimensional (4-D) distribution of the Eyjafjallajökull volcanic cloud in the troposphere over Europe as observed by EARLINET during the entire volcanic event (15 April–26 May 2010). All optical properties directly measured (backscatter, extinction, and particle linear depolarization ratio) are stored in the EARLINET database available at http://www.earlinet.org. A specific relational database providing the volcanic mask over Europe, realized ad hoc for this specific event, has been developed and is available on request at http://www.earlinet.org. During the first days after the eruption, volcanic particles were detected over Central Europe within a wide range of altitudes, from the upper troposphere down to the local planetary boundary layer (PBL). After 19 April 2010, volcanic particles were detected over southern and south-eastern Europe. During the first half of May (5–15 May), material emitted by the Eyjafjallajökull volcano was detected over Spain and Portugal and then over the Mediterranean and the Balkans. The last observations of the event were recorded until 25 May in Central Europe and in the Eastern Mediterranean area. The 4-D distribution of volcanic aerosol layering and optical properties on European scale reported here provides an unprecedented data set for evaluating satellite data and aerosol dispersion models for this kind of volcanic events.

Implementation of High Dynamic Raman Lidar System for 3D Map of Particulate Optical Properties and Their Time Evolution

Fast scanning lidar system can provide aerosol volume distribution and time evolution in atmosphere. Usually fast scanning lidar has a relative simple configuration. Multiwavelength depolarization and Raman measurements gave us more information about the particulate shape, type and dimension. The most Raman lidars use high power laser source in order to get enough Raman scattering signal. One of a challenge for Raman lidar system is to have enough dynamic range to satisfy the measurements both for pure molecule Rayleigh scattering and high dene aerosol, such as dust storm, volcano emitted aerosol and high polluted urban aerosol. The estimation of microphysical properties requires independent measurements of both backscatter and extinction coefficient at several wavelengths (multiwavelength Raman lidar). Additional information can be retrieved from simultaneous measurements of the depolarization signal and water vapor mixing ratio, since those measurements are particularly useful to correlate aerosol optical properties with their shape and hygroscopicity. A multi-wavelength depolarization and Raman lidar system has been designed to perform volume scanning of the atmosphere and to retrieve high quality 3D map of particulate optical properties and their time evolution. This system is equipped with a doubled and tripled Nd:YAG diode-pumped laser that is specifically designed for this device, with a repetition rate of 1KHz and average optical power of 0.6W at 355nm, 1.5W at 532nm and 1W at 1064nm. The relative high repetition rate laser source can increase the detectable signal dynamic range. The receiving system is based on a 25cm modified Cassegrain telescope. The spectral selection of the backscatter elastic and Raman signals is made through a system of dichroic beam splitters and narrow band (0.5 nm) interferential filters. Fast single photon counting photomultipliers are used to collect the selected radiation. Each detected signal is acquired by multichannel scalers with a raw spatial resolution varying from 30cm to 30m. Moreover, polarization purity of laser line allows to perform polarization measurements at both 355 and 532nm. This device is installed in the Beijing city area, which is strongly affected from anthropogenic pollution and sand dust from Gobi desert.

Design and analysis of new spectroscopic system of Raman lidar for detection of atmospheric water vapor

A new ultraviolet Raman lidar system is proposed and developed for detecting atmospheric water vapor and aerosol study. The combination of dichroic mirrors and narrow-band interference filters is used as high-performance spectroscopic system to obtain the fine-separation and high-efficiency extraction of Mie-Rayleigh scattering signals, the vibrational Raman scattering signal of H2O and N2. By the American standard model and a set of atmospheric scattering signal model, the signal-to-noise ratio (SNR) and the water vapor measurement error are simulated and analyzed. The preliminary experiments are carried out at nighttime in Xi'an area for detecting the atmospheric water vapor and aerosols. Taking a set of the atmospheric returned signals measured under cloudy weather for example, the profiles of atmospheric backscatter ratio and water vapor mixing ratio are retrieved, and the SNR profiles of the three channels are discussed and verify that this configuration can achieve a high rejection rate (10-7) to Mie-Rayleigh scattering. The theoretical and experimental results show that water vapor detection error of less than 15% can be obtained under a backscatter ratio of 17, which demonstrates the feasibility of the system for the atmospheric aerosol and water vapor measurements.

Correction technique for Raman water vapor lidar signal-dependent bias and suitability for water vapor trend monitoring in the upper troposphere

Abstract. The MOHAVE-2009 campaign brought together diverse instrumentation for measuring atmospheric water vapor. We report on the participation of the ALVICE (Atmospheric Laboratory for Validation, Interagency Collaboration and Education) mobile laboratory in the MOHAVE-2009 campaign. In appendices we also report on the performance of the corrected Vaisala RS92 radiosonde measurements during the campaign, on a new radiosonde based calibration algorithm that reduces the influence of atmospheric variability on the derived calibration constant, and on other results of the ALVICE deployment. The MOHAVE-2009 campaign permitted the Raman lidar systems participating to discover and address measurement biases in the upper troposphere and lower stratosphere. The ALVICE lidar system was found to possess a wet bias which was attributed to fluorescence of insect material that was deposited on the telescope early in the mission. Other sources of wet biases are discussed and data from other Raman lidar systems are investigated, revealing that wet biases in upper tropospheric (UT) and lower stratospheric (LS) water vapor measurements appear to be quite common in Raman lidar systems. Lower stratospheric climatology of water vapor is investigated both as a means to check for the existence of these wet biases in Raman lidar data and as a source of correction for the bias. A correction technique is derived and applied to the ALVICE lidar water vapor profiles. Good agreement is found between corrected ALVICE lidar measurments and those of RS92, frost point hygrometer and total column water. The correction is offered as a general method to both quality control Raman water vapor lidar data and to correct those data that have signal-dependent bias. The influence of the correction is shown to be small at regions in the upper troposphere where recent work indicates detection of trends in atmospheric water vapor may be most robust. The correction shown here holds promise for permitting useful upper tropospheric water vapor profiles to be consistently measured by Raman lidar within NDACC (Network for the Detection of Atmospheric Composition Change) and elsewhere, despite the prevalence of instrumental and atmospheric effects that can contaminate the very low signal to noise measurements in the UT.

Analysis of lidar depolarization calibration procedure and application to the atmospheric aerosol characterization

A Raman lidar system is used to monitor the aerosol depolarization features of the urban atmosphere at the Andalusian Centre for Environmental Research (CEAMA), in Granada, southeastern Spain. The lidar system was upgraded in 2010 to enable the application of the ±45° calibration method, which does not require any external optical device. We analyse the method and classify the atmospheric aerosol following the criteria based on depolarization. Backscatter coefficient, backscatter-related Angström exponent (å β), volume linear depolarization ratio (δv), and particle linear depolarization ratio (δp) profiles are studied in Saharan dust and biomass burning smoke events during the summer of 2010. The strength of these events was visualized in the aerosol optical depth (AOD) series obtained by Sun and star photometers operated at CEAMA. During the analysed events, the AOD at 440 nm ranged between 0.2 and 0.3, although the Angström exponent (å AOD) retrieved by the Sun photometer was considerably lower during the Saharan dust event (å AOD = 0.4 ± 0.1) than during the biomass burning event (å AOD = 1.4 ± 0.1). Regarding å β profiles, å β values were similar along the vertical profiles and comparable to å AOD values for each event. In contrast, the particle linear depolarization ratio (δp) at 532 nm showed an opposite behaviour to å β, changing along the vertical profiles. In fact, the aerosol layers located in the free troposphere showed mean values of δp of 0.13 ± 0.08 and 0.03 ± 0.01 in the Saharan dust and biomass burning events, respectively. These results show that the use of depolarization techniques enables an accurate aerosol typing and the understanding of the layer's composition in the atmosphere.