We study retrieval methods in regard to their potential to accurately retrieve particle microphysical parameters (PMP) from 3β + 2α HSRL/Raman lidar measurements. PMPs estimated with these methods are number, surface-area and volume concentrations, the effective radius, and complex refractive index of the investigated particle size distribution (PSD). The 3β + 2α optical data are particle backscatter coefficients at 355, 532 and 1064 nm and extinction coefficients at 355 and 532 nm. We present results that are fundamental for our understanding of how uncertainties of the optical data convert into uncertainties of PMPs. PMPs can only be retrieved with preset accuracy if the input optical data are accurate to at least eight significant digits, i.e., 10⁻⁶%. Such measurement accuracy cannot be achieved by currently existing lidar measurement techniques and the fact that atmospheric conditions are not static during lidar observations. Our analysis of the results derived with the novel approach shows that (a) the uncertainty of the retrieved surface-area concentration increases proportionally to the measurement uncertainty of the extinction coefficient at 355 nm, (b) the uncertainty of the effective radius is inversely proportional to the measurement uncertainty of the extinction-related Ångström exponent, (c) the uncertainty of volume concentration is close to the one of the effective radius, and (d) the uncertainty of number concentration is proportional to the inverse of the square value of the uncertainty of the effective radius. The complex refractive index (CRI) cannot be estimated without introducing extra constraints, even if measurement uncertainties of the optical data are as low as 1−3%. We tested constraints and their impact on the solution space, and in how far these constraints could allow us to restrict the retrieval uncertainties. For example, we used information about relative humidity that can be measured with Raman lidar. Relative humidity is an important piece of information that allows for more accurate aerosol typing and thus plays a vital role in any kind of aerosol characterization. The measurement example we used in this study shows that such a constraint can reduce the retrieval uncertainty of single scattering albedo (SSA) to as low as ±0.01–±0.025 (at 532 nm), on the condition that the uncertainty of the input optical data stays below 15%. The results will be used for uncertainty analysis of data products provided by future versions of the Tikhonov Advanced Regularization Algorithm (TiARA). This algorithm has evolved into a standard tool for the derivation of microphysical particle properties from multiwavelength High-Spectral-Resolution Lidar (HSRL)/Raman lidar operated in Europe, East Asia, and the US. Full article

Atmospheric aerosols have important impacts on global radiative forcing, air pollution, and human health. This study investigated the optical and physical properties of aerosol layers over Australia from 2007 to 2019 using the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Level 2 aerosol products. Australia was divided into three sub-regions (western highlands, central plains, and eastern ranges). Interannual and seasonal optical property variations in aerosol layers in the three sub-regions were analyzed and compared. Results showed that annual mean values of AOD_L (lowest aerosol layer AOD) and AOD_T (total AOD of all aerosol layers) were always higher in the eastern ranges region than the other two regions from 2007 to 2019. The reason could be that Australian population was predominantly located in the eastern ranges region, where more human activities could bring significant aerosol loadings. B_L (base height of the lowest aerosol layer), H_L (top height of the lowest aerosol layer), and H_H (top height of the highest aerosol layer) all showed trends of “western highlands > eastern mountains > central plains”, indicating that the higher the elevation, the higher the B_L, H_L, and H_H. T_L (thickness of the lowest aerosol layer) was higher during the day than at night, which might account for increased diurnal atmospheric convection and nocturnal aerosol deposition. DR_L (depolarization ratio of the lowest aerosol layer) was higher in the western highlands and central plains than the eastern mountains, probably because these two regions have large deserts with more irregularly shaped dust aerosols. CR_L (color ratio of the lowest aerosol layer) had slightly higher values in the eastern ranges than the other two regions, probably due to the wet climate of the eastern ranges, where aerosols were more hygroscopic and had larger particle sizes. This study can provide technical support for the control and management of regional air pollutants. Full article

To investigate the vertical distribution of aerosol optical characteristics in Nanyang City, a ground-based dual-wavelength (532 nm and 355 nm) lidar system was developed for aerosol observation at the Nanyang Normal University Station (NYNU) from November 2021 to December 2022. Spatio-temporal dynamics information on vertical distributions of aerosol optical properties during polluted and non-polluted days was obtained. Aerosols were characterized by low altitudes (up to 2 km), thinner layers, and high-altitude (up to 4 km) thick layers during non-polluted and polluted days, with extinction coefficient values of ~0.03 km⁻¹ and ~0.2 km⁻¹, respectively. The mean values of the extinction coefficient at different altitudes (0~5 km) were all about ten-times higher on polluted days (0.04~0.19 km⁻¹) than on non-polluted days (0.004~0.02 km⁻¹). These results indicate that aerosol loadings and variations at different altitudes (0~5 km) were much higher and more prominent on polluted days than non-polluted days. The results show ten-times larger aerosol optical depth (AOD) values (0.4~0.6) on polluted days than on non-polluted days (0.05~0.08). At the same time, AOD values on both polluted and non-polluted days slightly decreased from 19:00 to 05:00, possibly due to dry depositions at nighttime. For the first time, this study established a ground-based lidar remote sensing system to investigate the vertical distribution of atmospheric aerosol optical characteristics in Henan Province. The experimental results can provide scientific dataset support for the local government to prevent and control air pollution. Full article

The atmospheric boundary layer provides useful information about the accumulation and diffusion of pollutants. As a fast method, remote sensing techniques are used to retrieve the atmospheric boundary layer height (ABLH). Atmospheric detection lidar has been widely applied for retrieving the ABLH by providing information on the vertical distribution of aerosols. However, these previous algorithms that rely on gradient change are susceptible to residual layers. Contrary to the use of gradient change to retrieve ABLH, in this paper, we propose using a cluster analysis approach through multifunction lidar remote sensing techniques due to its increasing availability. The clustering algorithm for multi-wavelength lidar data can be divided into two parts: characteristic signal selection and selection of the classifier. First, since the separability of each type of signal is different, careful selection of the input characteristic signal is important. We propose using Fourier transform for all the observed signals; the most suitable characteristic signal can be determined based on the dispersion degree of the signal in the frequency domain. Then, the performances of four common classifiers (K-means method, Gaussian mixture model, hierarchical cluster method (HCM), and density-based spatial clustering of applications with noise) are evaluated by comparing with the radiosonde measurements from June 2015 to June 2016. The results show that the performance of the HCM classifier is the best under all states (R² = 0.84 and RMSE = 0.18 km). The findings obtained here offer insight into ABLH remote sensing technology. Full article

This paper presents the Backscattering Lidar Signal Simulator (BLISS), an end-to-end lidar simulator developed by the Centre National d’Etudes Spatiales (CNES). We computed the constant multiple-scattering (MS) coefficient of BLISS with a Monte Carlo (MC) code in the framework of CALIOP/CALIPSO observations for different homogeneous and plane-parallel stratocumulus and cirrus cloud geophysical scenes. The MS coefficient varies from 0.46 to 0.63. Then we evaluated the Level 1 products of BLISS. Above and in-cloud relative difference between the attenuated backscattering coefficient vertical profile simulated by BLISS and by the MC code is smaller than 0.5% under single-scattering regime and smaller than 10% (30% if optical depth of cirrus is large) under multiple-scattering regime, thus confirming the robustness of BLISS. Full article

In the quantification model of emission intensity of emission sources, the estimation of the background concentration of greenhouse gases near an emission source is an important problem. The traditional method of estimating the background concentration of greenhouse gases through statistical information often results in a certain deviation. In order to solve this problem, we propose an adaptive estimation method of CO₂ background concentrations near emission sources in this work, which takes full advantage of robust local regression and a Gaussian mixture model to achieve accurate estimations of greenhouse gas background concentrations. It is proved by experiments that when the measurement error is 0.2 ppm, the background concentration estimation error is only 0.08 mg/m³, and even when the measurement error is 1.2 ppm, the background concentration estimation error is less than 0.4 mg/m³. The CO₂ concentration measurement data all show a good background concentration assessment effect, and the accuracy of top-down carbon emission quantification based on actual measurements should be effectively improved in the future. Full article

Marine aerosol is one of the most important natural aerosols. It has a significant impact on marine climate change, biochemical cycling and marine ecosystems. Previous studies on marine aerosols, especially in the South China Sea, were carried out by satellite and shipborne measurements. The above methods have drawbacks, such as low temporal–spatial resolution and signal interference. However, lidar has high accuracy and high temporal–spatial resolution, so it is suitable for high-precision long-term observations. In this work, we obtain marine aerosol data using Mie Lidar in Sansha, an island in the South Chain Sea. Firstly, by comparing boundary layer height (BLH) between Sansha and Hefei, we found that Sansha’s boundary layer height has significant differences with that of inland China. Secondly, we compare the aerosol extinction coefficients and their variation with height in Sansha and Hefei. Finally, we obtain hourly averaged aerosol optical depth at Sansha and explore its relation with weather. To analyze the AOD–weather relation, we select three meteorological factors (sea surface temperature, mean sea level pressure and 10 m u-component of wind) based on their feature importance, which is determined by random forest regression. We also analyze the relationship between AOD and the above meteorological factors in each season separately. The results show that there is a strong relation between the meteorological factors and AOD in spring and summer, while there is no clear correlation in fall and winter. These analyses can provide valid data for future researches on marine aerosols in the South China Sea. Full article

The carbon dioxide (CO₂) differential absorption lidar echo signal is susceptible to noise and must satisfy the high demand for signal-retrieval precision. Thus, a proper de-noising method should be selected to improve the inversion result. In this paper, we simultaneously decompose three signal pairs into different intrinsic mode functions (IMFs) using the method of ensemble empirical mode decomposition (EEMD). Further, the correlation coefficients of the IMFs with the same temporal scale are regarded as the criterion to determine the components that need removal. This method not only retains the useful information effectively but also removes the noise component. A significant improvement in the R² of the differential absorption optical depth (DAOD) of the de-noised signals is obtained. The results of the simulated and observed analysis signal demonstrated improvement both in the SNR and in the retrieval precision. Full article