Vertical distribution of optical and microphysical properties of smog aerosols measured by multi-wavelength polarization lidar in Xi’an, China

Di, Huige; Hua, Hangbo; Cui, Yan; Hua, Dengxin; He, Tingyao; Wang, Yufeng; Qing, Yan

doi:10.1016/j.jqsrt.2016.05.027

Cited by 18 publications

(7 citation statements)

References 33 publications

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“…, 28. The values of K and b are chosen to achieve the minimization of the function in Equation (5). Then, the aerosol volume distribution can be obtained from Equation (2).…”

Section: Inversion Techniquementioning

confidence: 99%

“…Aerosols play an important role in the Earth's radiation budget [1][2][3][4]. The vertical distribution of aerosols is a critical issue in estimating aerosol radiative forcing and its associated climate impacts [5]. Furthermore, the spatial and temporal variabilities of aerosol size distributions are needed to better understand pollution processes [6].…”

Section: Introductionmentioning

confidence: 99%

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Aerosol Microphysical Particle Parameter Inversion and Error Analysis Based on Remote Sensing Data

Wang

Hua

et al. 2018

Remote Sensing

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The use of Raman and high-spectral lidars enables measurements of a stratospheric aerosol extinction profile independent of backscatter, and a multi-wavelength (MW) lidar can obtain additional information that can aid in retrieving the microphysical characteristics of the sampled aerosol. The inversion method for retrieving aerosol particle size distributions and microphysical particle parameters from MW lidar data was studied. An inversion algorithm for retrieving aerosol particle size distributions based on the regularization method was established. Based on the inversion of regularization, the inversion method was optimized by choosing the base function closest to the aerosol distribution. The logarithmic normal distribution function was selected over the triangle function as the base function for the inversion. The averaging procedure was carried out for three main types of aerosol. The 1% averaging result near the minimum of the discrepancy gave the best estimate of the particle parameters. The accuracy and stabilization of the optimized algorithm for microphysical parameters were tested by scores of aerosol size distributions. The systematic effects and random errors impacting the inversion were also considered, and the algorithm was tested by the data, showing 10% systematic error and 15% random error. At the same time, the reliability of the proposed algorithm was also verified by using the aerosol particle size distribution data of the aircraft. The inversion results showed that the algorithm was reliable in retrieving the aerosol particle size distributions at vertical heights using lidar data.In the last 20 years, research has been performed on solving the underlying inverse integral equation system for obtaining the microphysical parameters of aerosol particles from their optical properties. The regularization algorithm [6], the principal component analysis (PCA) technique [13], and the linear estimation algorithm [14] have been used for determining the aerosol bulk properties. The regularization algorithm is used most commonly for inverting multi-wavelength measurements [6], allowing the retrieval of particle size, concentration, and to some extent the main features of the particle size distribution.Using the regularized inversion algorithm, the particle size distribution and microphysical parameters of aerosols are obtained without assuming the initial complex refractive index and aerosol distribution. The inversion results are unstable, and there will be good results under certain spectral types; however, in some cases, the inversion error is very large. In Veselovskii's modified regularized inversion algorithm [15,16], the effective radius, number, surface area, and volume concentration for three distributions were retrieved with an average accuracy of 55%, 70%, 40%, and 50%, respectively. D. analyzed the effects of systematic and random errors on particle microphysical properties from multi-wavelength lidar measurements using an inversion with regularization. Three ASDs were used for this analys...

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“…, 28. The values of K and b are chosen to achieve the minimization of the function in Equation (5). Then, the aerosol volume distribution can be obtained from Equation (2).…”

Section: Inversion Techniquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Aerosol Microphysical Particle Parameter Inversion and Error Analysis Based on Remote Sensing Data

Wang

Hua

et al. 2018

Remote Sensing

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“…Four separate backscattering channels (vibrational nitrogen Raman signal at 386.7 nm, two Mie-Rayleigh signals at 355 nm with different polarization planes and Mie-Rayleigh signal at 1064 nm) were used in this study. A half-wave plate was installed in front of the polarization channels to calibrate the volume depolarization ratio (VDR) using the so called ±45 • method, and to correct the polarization plane offset [35]. Main components of the system are listed in Table 1.…”

Section: Lidar Systemmentioning

confidence: 99%

“…When available, backscatter coefficient profiles at 355 nm retrieved by Raman method were used in the subsequent atmospheric studies. While other methods to calculate the VDR exist [35], we selected the method used in [45] to be able to compare our results to previous measurements and to classify the aerosols we observed into established aerosol categories. The particle depolarization ratio (PDR) was separated from the VDR by evaluating the molecular backscatter coefficient using the properties of the standard atmosphere and radiosonde data [45].…”

Section: Data Processingmentioning

confidence: 99%

Investigation of Aerosol Properties and Structures in Two Representative Meteorological Situations over the Vipava Valley Using Polarization Raman LiDAR

et al. 2019

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Vipava valley in Slovenia is a representative hot-spot for complex mixtures of different aerosol types of both anthropogenic and natural origin. Aerosol loading distributions and optical properties were investigated using a two-wavelength polarization Raman LiDAR, which provided extinction coefficient, backscatter coefficient, depolarization ratio, backscatter Ångström exponent and LiDAR ratio profiles. Two different representative meteorological situations were investigated to explore the possibility of identifying aerosol types present in the valley. In the first case, we investigated the effect of strong downslope (Bora) wind on aerosol structures and characteristics. In addition to observing Kelvin–Helmholtz instability above the valley, at the height of the adjacent mountain ridge, we found new evidence for Bora-induced processes which inject soil dust aerosols into the free troposphere up to twice the height of the planetary boundary layer (PBL). In the second case, we investigated aerosol properties and distributions in stable weather conditions. From the observed stratified vertical aerosol structure and specific optical properties of different layers we identified predominant aerosol types in these layers.

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“…Furthermore, robotization of LiDAR devices is also very important to decrease data variability due to manual operation and thus increase their reliability in continuous long-term observations [18]. Our goal was to develop an automatic LiDAR system with high accuracy for long-term monitoring of atmospheric structures and a broad set of aerosol optical properties, such as aerosol backscatter coefficients [19,20,21], extinction coefficient [20,21], LiDAR ratio [21,22], and depolarization ratio [23,24]. It was deployed in the Vipava Valley, which is not covered by any of the existing ground-based LiDAR networks, indoors, to provide as large as possible a duty time and stable operation during adverse weather conditions, including strong winds.…”

Section: Introductionmentioning

confidence: 99%

Development of an Automatic Polarization Raman LiDAR for Aerosol Monitoring over Complex Terrain

Wang

Stanič

Eichinger

et al. 2019

Sensors

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High temporal and spatial resolution profiling of aerosol properties is required to study air pollution sources, aerosol transport, and features of atmospheric structures over complex terrain. A polarization Raman LiDAR with remote operation capability was developed for this purpose and deployed in the Vipava Valley, Slovenia, a location in the Alpine region where high concentrations of aerosols originating from a number of different local and remote sources were found. The system employs two high-power Nd:YAG pulsed lasers at 355 nm and 1064 nm as transmitters and provides the capability to extract the extinction coefficient, backscatter coefficients, depolarization ratio, Ångström exponent, and LiDAR ratio profiles. Automatized remote operation in an indoor environment provides a high duty cycle in all weather conditions. In addition to the detailed description of the device, an assessment of its potential and the retrieval uncertainties of the measured quantities is discussed. System optimization and performance studies include calibration of the depolarization ratio, merging of near-range (analog) and far-range (photon counting) data, determination of overlap functions, and validation of the retrieved observables with radiosonde data. Two cases for assessing LiDAR performance under specific weather conditions (during rain and in the presence of mineral dust) are also presented.

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Vertical distribution of optical and microphysical properties of smog aerosols measured by multi-wavelength polarization lidar in Xi’an, China

Cited by 18 publications

References 33 publications

Aerosol Microphysical Particle Parameter Inversion and Error Analysis Based on Remote Sensing Data

Aerosol Microphysical Particle Parameter Inversion and Error Analysis Based on Remote Sensing Data

Investigation of Aerosol Properties and Structures in Two Representative Meteorological Situations over the Vipava Valley Using Polarization Raman LiDAR

Development of an Automatic Polarization Raman LiDAR for Aerosol Monitoring over Complex Terrain

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