Aerosol Backscatter Coefficient Research Articles

Innovative aerosol hygroscopic growth study from Mie–Raman–fluorescence lidar and microwave radiometer synergy

Abstract. This study focuses on the characterization of aerosol hygroscopicity using remote sensing techniques. We employ a Mie–Raman–fluorescence lidar (Lille Lidar for Atmospheric Study, LILAS), developed at the ATOLL platform, Laboratoire d'Optique Atmosphérique, Lille, France, in combination with the RPG-HATPRO-G5 microwave radiometer to enable continuous aerosol and water vapor monitoring. We identify hygroscopic growth cases when an aerosol layer exhibits an increase in both aerosol backscattering coefficient and relative humidity. By examining the fluorescence backscattering coefficient, which remains unaffected by the presence of water vapor, the potential temperature, and the absolute humidity, we verify the homogeneity of the aerosol layer. Consequently, the change in the backscattering coefficient is solely attributed to water uptake. The Hänel theory is employed to describe the evolution of the backscattering coefficient with relative humidity and introduces a hygroscopic coefficient, γ, which depends on the aerosol type. The particularity of this method revolves around the use of the fluorescence which is employed to take into account and correct the aerosol concentration variations in the layer. Case studies conducted on 29 July and 9 March 2021 examine, respectively, an urban and a smoke aerosol layer. For the urban case, γ is estimated as 0.47 ± 0.03 at 532 nm; as for the smoke case, the estimation of γ is 0.5 ± 0.3. These values align with those reported in the literature for urban and smoke particles. Our findings highlight the efficiency of the Mie–Raman–fluorescence lidar and microwave radiometer synergy in characterizing aerosol hygroscopicity. The results contribute to advance our understanding of atmospheric processes, aerosol–cloud interactions, and climate modeling.

Quality assessment of aerosol lidars at 1064 nm in the framework of the MEMO campaign

Abstract. Aerosol lidar networks can play an important role in revealing structural characteristics of the atmospheric boundary layer, the urban heat island effect, and the spatial distribution of aerosols, especially in relation to the monitoring of atmospheric pollution in megacities. To fulfill the need of the monitoring and numerical forecasting of atmospheric pollution, an aerosol lidar network is proposed by the China Meteorological Administration which serves as an important part of the “MegaCity Experiment on Integrated Meteorological Observation in China” (MEMO). To ensure a high standard of data quality and traceability of measurement error, an inter-comparison campaign, dedicated to the quality assessment of lidar systems from different institutes and manufacturers, was designed and performed at Beijing Southern Suburb Observatory in September 2021. Six Mie–Rayleigh lidar systems at 1064 nm were involved in this campaign. The strategies for lidar self-evaluations and inter-comparisons were predefined. A lidar system at 1064 nm, which was developed by the Atmospheric Remote Sensing group at Wuhan University, was selected as the reference lidar system after passing all strict self-evaluation quality checks. The reference lidar system serves as the cornerstone for evaluating the performance of other lidar systems. After using the Rayleigh fit and signal-to-noise evaluation self-tests for each individual lidar system as a fast check of the data quality, the range-corrected signal and backscatter coefficient obtained from all the lidar systems were inter-compared with a reference lidar system. In the end, the lidar systems passed the quality control/assurance, ensuring that the standard deviation of range-corrected signal could be controlled within 5 % at 500–2000 m and 10 % at 2000–5000 m. For the derived aerosol backscatter coefficients, standard deviations can be controlled within 10 % at 500–2000 and 2000–5000 m. The quality assurance strategy lays down a solid basis for atmospheric lidar at near-infrared wavelengths and will be applied in Chinese lidar network development.

An explicit formulation for the retrieval of the overlap function in an elastic and Raman aerosol lidar

Abstract. We derive an explicit (i.e., non-iterative) formula for the retrieval of the overlap function in an aerosol lidar with both elastic and Raman N2 and/or O2 channels used for independent measurements of aerosol backscatter and extinction coefficients. The formula requires only the measured, range-corrected elastic and the corresponding Raman signals, plus an assumed lidar ratio. We assess the influence of the lidar ratio error in the overlap function retrieval and present retrieval examples.

Saharan Dust Loads over Sofia, Bulgaria: Lidar Observations on Winter and Spring Dust Events

Aerosols have significant impacts on the climate, ecosystems, and human health. Sahara Desert is the largest source of natural mineral aerosols (dust) on Earth. Enormous amounts of Saharan particulate matter are frequently transported to Europe through advection of warm air masses, being typical for spring and summer. Over the last years, winter Saharan dust load events have also been reported for various locations over Europe, including Sofia. In this work, we give a description of lidar observations of atmospheric aerosols present above Sofia, Bulgaria, during episodes of Saharan dust intrusions in periods of minimum (in winter) and maximum (in spring) activity of dust transport to the region. Measurements were conducted in February and April 2021, with the two aerosol channels (at 532 nm and 1064 nm) of the Nd:YAG-laser based lidar. Aerosol/dust layering and optical and microphysical properties are characterized. Colourmaps of the vertical aerosol distribution and its temporal dynamics were presented. Time-averaged vertical profiles of the aerosol backscatter coefficients and corresponding backscatter-related Ångström exponents were retrieved and analyzed. The Saharan origin of the aerosols detected was identified using online available air/dust tracking and mapping web resources. Results obtained show that the considered here dust load events have affected significantly both the structure and aerosol composition of the local troposphere.

Use of lidar aerosol extinction and backscatter coefficients to estimate cloud condensation nuclei (CCN) concentrations in the southeast Atlantic

Abstract. Accurately capturing cloud condensation nuclei (CCN) concentrations is key to understanding the aerosol–cloud interactions that continue to feature the highest uncertainty amongst numerous climate forcings. In situ CCN observations are sparse, and most non-polarimetric passive remote sensing techniques are limited to providing column-effective CCN proxies such as total aerosol optical depth (AOD). Lidar measurements, on the other hand, resolve profiles of aerosol extinction and/or backscatter coefficients that are better suited for constraining vertically resolved aerosol optical and microphysical properties. Here we present relationships between aerosol backscatter and extinction coefficients measured by the airborne High Spectral Resolution Lidar 2 (HSRL-2) and in situ measurements of CCN concentrations. The data were obtained during three deployments in the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) project, which took place over the southeast Atlantic (SEA) during September 2016, August 2017, and September–October 2018. Our analysis of spatiotemporally collocated in situ CCN concentrations and HSRL-2 measurements indicates strong linear relationships between both data sets. The correlation is strongest for supersaturations (S) greater than 0.25 % and dry ambient conditions above the stratocumulus deck, where relative humidity (RH) is less than 50 %. We find CCN–HSRL-2 Pearson correlation coefficients between 0.95–0.97 for different parts of the seasonal burning cycle that suggest fundamental similarities in biomass burning aerosol (BBA) microphysical properties. We find that ORACLES campaign-average values of in situ CCN and in situ extinction coefficients are qualitatively similar to those from other regions and aerosol types, demonstrating overall representativeness of our data set. We compute CCN–backscatter and CCN–extinction regressions that can be used to resolve vertical CCN concentrations across entire above-cloud lidar curtains. These lidar-derived CCN concentrations can be used to evaluate model performance, which we illustrate using an example CCN concentration curtain from the Weather Research and Forecasting Model coupled with physics packages from the Community Atmosphere Model version 5 (WRF-CAM5). These results demonstrate the utility of deriving vertically resolved CCN concentrations from lidar observations to expand the spatiotemporal coverage of limited or unavailable in situ observations.

First assessment of Aeolus Standard Correct Algorithm particle backscatter coefficient retrievals in the eastern Mediterranean

Abstract. Since 2018, the Aeolus satellite of the European Space Agency (ESA) has acquired wind HLOS (horizontal line-of-sight) profiles throughout the troposphere and up to the lower stratosphere, filling a critical gap in the Global Observing System (GOS). Aeolus, carrying ALADIN (Atmospheric LAser Doppler INstrument), the first UV HSRL (High Spectral Resolution Lidar) Doppler lidar ever placed in space, provides also vertically resolved optical properties of particulates (aerosols and clouds). The present study focuses on the assessment of Aeolus L2A particulate backscatter coefficient (baseline 2A11), retrieved by the Standard Correct Algorithm (SCA), in the eastern Mediterranean, a region hosting a variety of aerosol species. Ground-based retrievals acquired by lidar instruments operating in Athens (central Greece), Thessaloniki (northern Greece) and Antikythera (southwestern Greece) serve as reference. All lidar stations provide routine measurements to the PANACEA (PANhellenic infrastructure for Atmospheric Composition and climatE chAnge) network. A set of ancillary data, including sun-photometric observations (AERONET), reanalysis products (CAMS and MERRA-2), satellite observations (MSG-SEVIRI and MODIS Aqua) and backward-trajectories modelling (FLEXPART), is utilized towards an optimum characterization of the probed atmospheric conditions under the absence of a classification scheme in Aeolus SCA profiles. First, emphasis is given on the assessment of Aeolus SCA backscatter coefficient under specific aerosol scenarios over Antikythera island. Due to the misdetection of the cross-polar component of the backscattered lidar signal, Aeolus underestimates the aerosol backscatter coefficient by up to 33 % when non-spherical mineral particles are recorded (10 July 2019). A good performance is revealed on 3 July 2019, when horizontally homogeneous loads of fine spherical particles are confined below 4 km. For other two cases (8 July 2020 and 5 August 2020), due to noise issues, the SCA performance degrades in terms of depicting the stratification of aerosol layers composed of particles of different origin. According to the statistical assessment analysis of 43 identified cases, a poor-to-moderate performance is revealed for the unfiltered (aerosols plus clouds) SCA profiles, which improves substantially when cloud-contaminated profiles are excluded from the collocated sample. This improvement is evident at both Aeolus vertical scales (regular scales have 24 bins and mid-bin scales have 23 bins), and it is justified by the drastic reduction in the bias (from 0.45 to 0.27 Mm−1 sr−1 for SCA and from 0.69 to 0.37 Mm−1 sr−1 for SCA mid-bin) and root mean square error (from 2.00 to 1.65 Mm−1 sr−1 for SCA and from 1.88 to 1.00 Mm−1 sr−1 for SCA mid-bin) scores. In the vertical, the SCA performance degrades at the lowermost bins due to either the contamination from surface signals or the increased noise levels for the aerosol retrievals. Among the three PANACEA stations, the best agreement is found at the remote site of Antikythera with respect to the urban sites of Athens and Thessaloniki. Finally, all key Cal/Val (calibration and validation) aspects necessary for future relevant studies, the recommendations for a possible Aeolus follow-on mission and an overview of the ongoing related activities are thoroughly discussed.

Analysis of the air quality in upper atmospheric boundary layer in a high-density city in Asia using 3-year vertical profiles measured by the 3-Dimensional Real-Time Atmospheric Monitoring System (3DREAMS).

Past studies focused on ground-level air quality, whereas air quality in upper atmospheric boundary layer (ABL) remains unclear due to lack of long-term and high time-resolution profile data. This study utilized the 3-Dimensional Real-Time Atmospheric Monitoring System (3DREAMS) to provide vertical profiles of aerosol backscatter coefficients and wind for three years (2019-2021), along with DustTrak to describe and analyze the characteristics of aerosols in the upper ABL in a high-density city in Asia (Hong Kong, China). It is the first study to assess the long-term record and spatial variations of upper-level aerosol in a high-density city using a LiDAR network. Results show an opposite diurnal profile of aerosol comparing between ground-level and upper ABL, which is different with the diurnal pattern observed in ground measurements (higher air pollutant concentration level in daytime and lower in nighttime). The co-location vertical wind measurements provided the explanation of the opposite diurnal patterns. The 3-year vertical profiles also show the significant spatial variation of vertical distribution of aerosol at different locations, whereas the temporal variations can be affected by various factors such as emissions and transboundary air pollution. Our episode analysis clearly demonstrated the capability of 3DREAMS to monitor transboundary air pollution with detailed information of horizontal transport and vertical convection. 3DREAMS is therefore proved as a suitable system for transboundary air pollution monitoring. Our findings provide a critical reference for atmospheric scientists and decisionmakers to understand transboundary air pollution.

Research on Lidar Network Observation of Aerosol and Pollution in Beijing 2022 Winter Olympics

During the Beijing Winter Olympics, three sets of aerosol lidar in different regions were used to conduct continuous observations to study the optical properties and vertical distribution characteristics of atmospheric aerosol. Based on the lidar data and sun photometer data, the accurate lidar ratio was determined to improve the inversion accuracy of the aerosol backscattering coefficient. The influence of meteorological conditions such as temperature, relative humidity, wind speed, and wind direction on the optical properties of aerosol were analyzed, and the type of aerosol was classified by the depolarization ratio of aerosol particles and CALIPSO data. Furthermore, the backward trajectory analysis, potential source contribution function (PSCF), and concentration weighted trajectories (CWT) were employed to explore the sources and transport mechanisms of pollutants. The analysis found that the extinction coefficient under the atmospheric boundary layer during the Winter Olympics had a spatial distribution pattern of high value in the southeast and low value in the northwest. The occurrence of aerosol pollution events is not only caused by local emissions, but is also related to regional transmission.

Seasonal Variation of Dust Aerosol Vertical Distribution in Arctic Based on Polarized Micropulse Lidar Measurement

This study investigates the seasonal variation of dust aerosol vertical distribution using polarized Micropulse lidar (MPL) measurements at the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) observatory from January 2013 to September 2017. For the first time, multi-year aerosol backscatter coefficients are retrieved at the ARM NSA site from MPL measurements and are consistent with co-located high spectral resolution lidar (HSRL) measurements. The high-quality aerosol backscatter coefficient retrievals are used to derive the particle depolarization ratio (PDR) at the wavelength of 532 nm, which is used to identify the presence of dust aerosols. The annual cycles of the vertical distributions of dust backscatter coefficient and PDR and dust aerosol optical depth (DAOD) show that aerosol loading has a maximum in late winter and early spring but a minimum in late summer and early autumn. Vertically, dust aerosol occurs in the entire troposphere in spring and winter and in the low and middle troposphere in summer and autumn. Because dust aerosols are effective ice nuclei, the seasonality of dust aerosol vertical distribution has important implications for the Arctic climate through aerosol–cloud–radiation interactions, primarily through impacting mixed-phase cloud processes.

Calibration method of Fernald inversion for aerosol backscattering coefficient profiles via multi-wavelength Raman–Mie lidar

Mie scattering lidar is widely used in the detection of atmospheric aerosol optical properties, however, the inversion algorithm is lack of accuracy, which is mainly caused by the inaccurate calibration of reference condition in Fernald inversion. Here, we propose a multi-wavelength aerosol backscattering ratio parameterized-calibration method (MABP-CM) based on parameterized equations for reference condition calibration of Fernald inversion. The aerosol backscatter ratios at 355 nm, 532 nm, and 1064 nm wavelengths are respectively calculated from the aerosol size distribution of aerial survey data. We find that there is a positive correlation between the backscatter ratios at different wavelengths, and the parameterized equations are established. The parameterized equations can be used as conversion factors of aerosol backscatter ratio at different wavelengths, which is beneficial to improving the calibration accuracy of multi-wavelength backscatter ratios at reference height in Fernald inversion. The Raman inversion is used to retrieve the 355 nm aerosol backscattering coefficient and aerosol backscatter ratio. Then, combined with MABP-CM, the 532 nm and 1064 nm aerosol backscatter ratios at reference height are respectively derived, to obtain the backscattering coefficients with Fernald backward integration equation. With the improved method, the reference height is allowed not to be at clear atmosphere, and the reference condition can still be accurately calibrated. Simulation verification of multi-wavelength backscattering coefficients is carried out with aerial survey data. Our simulation suggests that MABP-CM can reduce the error of 532 nm backscattering coefficient to ±20%, and reduce the error of 1064 nm backscattering coefficient to ±40%. Multi-wavelength aerosol backscattering coefficients can be simultaneously retrieved with high accuracy on cloudy and heavily haze days with MABP-CM. Finally, the multi-wavelength Raman–Mie lidar is used to observe the short-term and long-term changes of aerosol backscattering coefficient on clear and cloudy days.

Coherent high-spectral-resolution lidar for the measurement of the atmospheric Mie-Rayleigh-Brillouin backscatter spectrum.

In this study, a 1550 nm coherent high-spectral-resolution lidar (CHSRL) is developed to measure the optical properties of aerosols and atmospheric wind profiles in the atmospheric boundary layer. To determine the optical properties, a coherent frequency discriminator based on the fast Fourier transform is designed in the CHSRL to separate the Mie and the Rayleigh-Brillouin backscatter spectra to fulfill the needs of high-spectral measurements. The atmospheric wind velocity is retrieved using the simultaneously measured Doppler shift. This non-optical frequency discriminator is a feasible and low-cost solution compared to a narrow-bandwidth optical filter, such as a Fabry-Perot interferometer or an atomic filter. However, shot, amplifier spontaneous emission, and detector noise interfere with the Rayleigh-Brillouin spectrum. Therefore, a spectrum correction algorithm is proposed to recover the interfered Rayleigh-Brillouin spectrum, and the measurement results of the spectral line agree well with those modeled with Tenti S6 at different central frequencies. Finally, field observations for comparison are conducted with the co-located CHSRL, Raman lidar, and coherent Doppler wind lidar. The comparison results indicate that the correlation coefficient of the aerosol backscatter coefficient is 0.84. The correlation coefficient and standard deviation of wind velocity are 0.98 and 0.13 m · s-1, respectively.

Investigation of the effective transmittance of Mach-Zehnder interferometer in the multi-longitudinal-mode high-spectral-resolution lidar

Effective transmittance is an important parameter of Mach-Zehnder interferometer in the retrieval of aerosol optical properties using the multi-longitudinal-mode high-spectral-resolution lidar, which is a function of the complex degree of coherence. In this paper, we retrieve the parameter of the complex degree of coherence for the multi-longitudinal-mode laser from the theoretical analysis, optical simulation and experimental measurements, which are 0.726, 0.678 and 0.453 using the Mach-Zehnder interferometer with the optimal optical path difference of two times of laser optical cavity length (∼1000 mm) and under the light illumination of the high power Nd:YAG laser with the mode number of 101 and mode interval of 300 MHz under the condition of laser linewidth of 1 cm−1 (30 GHz). The preliminary measurement results of aerosol optical properties using the constructing multi-longitudinal-mode high-spectral-resolution lidar show that the difference of the complex degree of coherence retrieved from the presented methods results in the relative error of 40% in the aerosol backscattering coefficient with thin cloud layer and 90% with the presence of dense aerosol layer.

Combining Mie–Raman and fluorescence observations: a step forward in aerosol classification with lidar technology

Abstract. 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 βF. The fluorescence capacity GF, which is the ratio of βF 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, GF. 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–GF 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.

Simulating wildfire emissions and plume rise using geostationary satellite fire radiative power measurements: a case study of the 2019 Williams Flats fire

Abstract. We use the Weather Research and Forecasting with Chemistry (WRF-Chem) model with new implementations of GOES-16 wildfire emissions and plume rise based on fire radiative power (FRP) to interpret aerosol observations during the 2019 NASA-NOAA FIREX-AQ field campaign and perform model evaluations. We compare simulated aerosol concentrations and optical properties against observations of black carbon aerosol from the NOAA Single Particle Soot Photometer (NOAA-SP2), organic aerosol from the CU High-Resolution Aerosol Mass Spectrometer (HR-AMS), and aerosol backscatter coefficients from the high-spectral-resolution lidar (HSRL) system. This study focuses on the Williams Flats fire in Washington, which was repeatedly sampled during four science flights by the NASA DC-8 (3–8 August 2019). The emissions and plume-rise methodologies are implemented following NOAA's operational High-Resolution Rapid Refresh coupled with Smoke (HRRR-Smoke) forecasting model. In addition, new GOES-16 FRP-based diurnal cycle functions are developed and incorporated into WRF-Chem. The FIREX-AQ observations represented a diverse set of sampled environments ranging from fresh/aged smoke from the Williams Flats fire to remnants of plumes transported over long distances. The Williams Flats fire resulted in significant aerosol enhancements during 3–8 August 2019, which were substantially underestimated by the standard version of WRF-Chem. The simulated black carbon (BC) and organic carbon (OC) concentrations increased between a factor of 92–125 (BC) and a factor of 28–78 (OC) with the new implementation compared to the standard WRF-Chem version. These increases resulted in better agreement with the FIREX-AQ airborne observations for BC and OC concentrations (particularly for fresh smoke sampling phases) and aerosol backscatter coefficients. The model still showed a low bias in simulating the aerosol loadings observed in aged plumes from Williams Flats. WRF-Chem with the FRP-based plume rise simulated similar plume heights to the standard plume-rise model in WRF-Chem. The simulated plume heights (for both versions) compared well with estimated plume heights using the HSRL measurements. Therefore, the better agreement with observations was mainly driven by the higher emissions in the FRP-based version. The model evaluations also highlighted the importance of accurately accounting for the wildfire diurnal cycle and including adequate representation of the underlying chemical mechanisms, both of which could significantly impact model forecasting performance.

Detecting aerosol backscattering coefficient across the whole troposphere by the sidescattering lidar system with three CCD cameras.

Due to geometric overlap factor, the backscattering lidar is not suitable to detect atmospheric characteristics near the ground. A new sidescattering lidar system consisting of three CCD cameras and one CW laser is developed for the first time to measure the profiles of the backscattering coefficient of atmospheric aerosols across the whole troposphere, which has no detection blind zone near the ground. The aerosol relative phase function was detected by its horizontal CCD channel. The vertical distribution of aerosol backscattering coefficient across the whole troposphere was observed by the other two CCD cameras of vertical channel. The reasons for choosing three CCD cameras and their respective functions are analyzed in detail. Comparative experiments and continuous observations indicate that the new sidescattering lidar system including three CCD cameras is simple in structure and reliable in performance with low cost as well.

Retrieval of Aged Biomass-Burning Aerosol Properties by Using GRASP Code in Synergy with Polarized Micro-Pulse Lidar and Sun/Sky Photometer

The aim of this study was to analyze the potential of the GRASP code to retrieve optical and microphysical properties vertically-resolved using a synergy of polarized Micro-Pulse Lidar and Sun/sky photometer observations. The focus was on the long-range transport of Canadian aged-smoke plumes observed at El Arenosillo/Huelva (Spain) from 7 to 8 September 2017. Both the columnar and height-resolved microphysical and optical properties were assessed in comparison with AERONET data and vertical lidar-retrieved profiles, respectively. In particular, the vertical properties were also derived using the POLIPHON approach, which serves as a comparison for GRASP retrievals. The retrieved columnar aerosol microphysical properties (volume concentration and effective radius) showed an excellent agreement, with negligible differences, and were within the uncertainties. Nevertheless, for the retrieved columnar optical properties, we could only perform an individual comparison, due to the strong AERONET limitations, and although the agreements were generally good, no conclusions were obtained, due to differences in the real refractive index and due to the large uncertainties obtained in the retrievals. For the vertical profiles, however, we present a large advance that permits obtaining aerosol backscatter and extinction coefficients, plus volume concentrations, without the need for internal assumptions (extinction-to-backscatter ratios and depolarization measurements), due to the very good agreement observed between GRASP and the lidar-derived methodologies. However, the separation of the properties into their fine and coarse modes was not feasible using the one-wavelength elastic lidar measurements with the GRASP retrieval configuration used in this work. Therefore, current studies are being addressed to assessing the introduction of lidar depolarization in the GRASP code as an encouraged added-value, for the improvement of the retrieval of vertical aerosol properties.

Two Practical Methods to Retrieve Aerosol Optical Properties from Coherent Doppler Lidar

Complexly distributed aerosol particles have significant impacts on climate and environmental changes. As one of the vital atmospheric power sources, the wind field deeply affects the distribution and transport of aerosol particles. For a more comprehensive investigation of the aerosols flux and transport mechanism, two retrieval methods of aerosol optical properties (backscatter coefficient and extinction coefficient at 1550 nm) from coherent Doppler lidar (CDL) observation are proposed in this paper. The first method utilizes the calculated aerosol backscatter coefficient (532 nm) from Mie-scattering lidar datasets and the iterative Fernald method to retrieve aerosol optical property profiles during joint measurements with CDL and Mie-scattering lidar. After verifying the correctness of the first method compared with AERONET datasets, we proposed the second retrieval method. Using the forward integral Fernald method with near-ground reference aerosol extinction coefficient calculated by atmospheric visibility, aerosol optical properties at 1550 nm could be obtained. Thirty-six-day joint measurements with two lidars were specially designed and conducted to verify the correctness of these retrieval methods. The validation results of these two methods indicate great performances, where the mean relative errors are 0.0272 and 0.1656, and the correlation coefficients are 0.9306 and 0.9197, respectively. In conclusion, the feasibility of these two retrieval methods extends the capability of CDL to detect aerosol optical properties and also provides a possibility to observe the aerosol distribution and transport process comprehensively, which is a great promotion of aerosol transport studies development.

Numerical Weather Predictions and Re-Analysis as Input for Lidar Inversions: Assessment of the Impact on Optical Products

The atmospheric molecular number density can be obtained from atmospheric temperature and pressure profiles and is a significant input parameter for the inversion of lidar measurements. When measurements of vertical profiles of temperature and pressure are not available, atmospheric models are typically considered a valid alternative option. This paper investigates the influence of different atmospheric models (forecast and reanalysis) on the retrieval of aerosol optical properties (extinction and backscatter coefficients) by applying Raman and elastic-only methods to lidar measurements, to assess their use in lidar data processing. In general, reanalyzes are more accurate than forecasts, but, typically, they are not delivered in time for allowing near-real-time lidar data analysis. However, near-real-time observation is crucial for real-time monitoring of the environment and meteorological studies. The forecast models used in the paper are provided by the Integrated Forecasting System operated by the European Centre for Medium-Range Weather Forecasts (IFS_ECMWF) and the Global Data Assimilation System (GDAS), whereas the reanalysis model is obtained from the fifth-generation European Centre for Medium-Range Weather Forecasts ReAnalysis v5 (ERA5). The lidar dataset consists of measurements collected from four European Aerosol Research Lidar Network (EARLINET) stations during two intensive measurement campaigns and includes more than 200 cases at wavelengths of 355 nm, 532 nm, and 1064 nm. We present and discuss the results and influence of the forecast and reanalysis models in terms of deviations of the derived aerosol optical properties. The results show that the mean relative deviation in molecular number density is always below ±3%, while larger deviations are shown in the derived aerosol optical properties, and the size of the deviation depends on the retrieval method together with the different wavelengths. In general, the aerosol extinction coefficient retrieval is more dependent on the model used than the aerosol backscatter retrievals are. The larger influence on the extinction retrieval is mainly related to the deviation in the gradient of the temperature profile provided by forecast and reanalysis models rather than the absolute deviation of the molecular number density. We found that deviations in extinction were within ±5%, with a probability of 83% at 355 nm and 60% at 532 nm. Moreover, for aerosol backscatter coefficient retrievals, different models can have a larger impact when the backscatter coefficient is retrieved with the elastic method than when the backscatter coefficient is calculated using the Raman method at both 355 nm and 532 nm. In addition, the atmospheric aerosol load can also influence the deviations in the aerosol extinction and backscatter coefficients, showing a larger impact under low aerosol loading scenarios.

Impact of Vertical Profiles of Aerosols on the Photolysis Rates in the Lower Troposphere from the Synergy of Photometer and Ceilometer Measurements in Raciborz, Poland, for the Period 2015–2020

The effect of the aerosol vertical distribution on photolysis frequencies of O3 and NO2 is studied. Aerosol measurements in Raciborz (50.08° N, 18.19° E), Poland, made using the CIMEL Sun photometer and collocated CHM-15k “Nimbus” ceilometer are analyzed for the period 2015–2020. Vertical profiles of the aerosol extinction are derived from the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm combining the ceilometer measurements of the aerosol backscattering coefficient with the collocated CIMEL measurements of the columnar characteristics of aerosols. The photolysis frequencies are calculated at the three levels in the lower troposphere (the surface and 0.5 and 2 km above the surface) using a radiative transfer model, Tropospheric Ultraviolet and Visible (TUV), for various settings of aerosol optical properties in the model input. The importance of the aerosol vertical distribution on photolysis frequencies is inferred by analyzing statistics of the differences between the output of the model, including the extinction profile from the GRASP algorithm, and the default TUV model (based on columnar aerosol characteristics by the CIMEL Sun photometer and Elterman’s extinction profile). For model levels above the surface, standard deviation, 2.5th percentile, 97.5th percentile, and the extremes, calculated from relative differences between these input settings, are comparable with the pertaining statistical values for the input pair providing changes of photolysis frequencies only due to the variability of the columnar aerosol characteristics. This indicates that the vertical properties of aerosols affect the distribution of the photolysis frequencies in the lower troposphere on a similar scale to that due to variations in columnar aerosol characteristics.

Vertical Profiling of Fresh Biomass Burning Aerosol Optical Properties over the Greek Urban City of Ioannina, during the PANACEA Winter Campaign

Vertical profiling of aerosol particles was performed during the PANhellenic infrastructure for Atmospheric Composition and climatE chAnge (PANACEA) winter campaign (10 January 2020–7 February 2020) over the city of Ioannina, Greece (39.65° N, 20.85° E, 500 m a.s.l.). The middle-sized city of Ioannina suffers from wintertime air pollution episodes due to biomass burning (BB) domestic heating activities. The lidar technique was applied during the PANACEA winter campaign on Ioannina city, to fill the gap of knowledge of the spatio-temporal evolution of the vertical mixing of the particles occurring during these winter-time air pollution episodes. During this campaign the mobile single-wavelength (532 nm) depolarization Aerosol lIdAr System (AIAS) was used to measure the spatio-temporal evolution of the aerosols’ vertical profiles within the Planetary Boundary Layer (PBL) and the lower free troposphere (LFT; up to 4 km height a.s.l.). AIAS performed almost continuous lidar measurements from morning to late evening hours (typically from 07:00 to 19:00 UTC), under cloud-free conditions, to provide the vertical profiles of the aerosol backscatter coefficient (baer) and the particle linear depolarization ratio (PLDR), both at 532 nm. In this study we emphasized on the vertical profiling of very fresh (~hours) biomass burning (BB) particles originating from local domestic heating activities in the area. In total, 33 out of 34 aerosol layers in the lower free troposphere were characterized as fresh biomass burning ones of local origin, showing a mean particle linear depolarization value of 0.04 ± 0.02 with a range of 0.01 to 0.09 (532 nm) in a height region 1.21–2.23 km a.s.l. To corroborate our findings, we used in situ data, particulate matter (PM) concentrations (PM2.5) from a particulate sensor located close to our station, and the total black carbon (BC) concentrations along with the respective contribution of the fossil fuel (BCff) and biomass/wood burning (BCwb) from the Aethalometer. The PM2.5 mass concentrations ranged from 5.6 to 175.7 μg/m3, while the wood burning emissions from residential heating were increasing during the evening hours, with decreasing temperatures. The BCwb concentrations ranged from 0.5 to 17.5 μg/m3, with an extremely high mean contribution of BCwb equal to 85.4%, which in some cases during night-time reached up to 100% during the studied period.