Retrieval method of aerosol extinction coefficient profile based on backscattering, side-scattering and Raman-scattering lidar

Shan, Huihui; Zhang, Hui; Liu, Junjian; Wang, Shenhao; Ma, Xiaojun; Zhou, Pucheng; Yao, Ling; Xie, Chenbo; Wang, Yingjian

doi:10.1016/j.optcom.2017.11.015

Cited by 9 publications

(3 citation statements)

References 8 publications

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“…In general, LIDAR systems are used to obtain both optical and microphysical parameters, which may be considered a two-step inversion process. In the first step, the measured backscattered power is used to estimate the optical parameters [16][17][18][19][20][21][22]. These parameters are then used in the second inversion to obtain the microphysical parameters, such as number size distribution, refractive index, etc.…”

Section: Introductionmentioning

confidence: 99%

Profiling of Aerosols and Clouds over High Altitude Urban Atmosphere in Eastern Himalaya: A Ground-Based Observation Using Raman LIDAR

et al. 2023

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Profiles of aerosols and cloud layers have been investigated over a high-altitude urban atmosphere in the eastern Himalayas in India, for the first time, using a Raman LIDAR. The study was conducted post-monsoon season over Darjeeling (latitude 27°01′ N longitude 88°36′ E, 2200 masl), a tourist destination in north-eastern India. In addition to the aerosols and cloud characterization and atmospheric boundary layer detection, the profile of the water vapor mixing ratio has also been analyzed. Effects of atmospheric dynamics have been studied using the vertical profiles of the normalized standard deviation of RCS along with the water vapor mixing ratio. The aerosol optical characteristics below and above the Atmospheric Boundary Layer (ABL) region were studied separately, along with the interrelation of their optical and microphysical properties with synoptic meteorological parameters. The backscatter coefficient and the extinction coefficient were found in the range from 7.15×10−10 m−1 sr−1 to 3.01×10−5 m−1 sr−1 and from 1.02×10−5 m−1 to 2.28×10−3 m−1, respectively. The LIDAR ratio varies between 3.9 to 78.39 sr over all altitudes. The variation of the linear depolarization ratio from 0.19 to 0.32 indicates the dominance, of non-spherical particles. The periodicity observed in different parameters may be indicative of atmospheric wave phenomena. Cloud parameters, such as scattering coefficients, top and bottom height, and optical depth for different cloud phases, have been evaluated. A co-located Micro Rain Radar has been used with LIDAR for cloud life cycle study.

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Section: Introductionmentioning

confidence: 99%

Profiling of Aerosols and Clouds over High Altitude Urban Atmosphere in Eastern Himalaya: A Ground-Based Observation Using Raman LIDAR

et al. 2023

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“…However, due to a monostatic receiving field and "geometric overlap factor (GOF)", the hundreds of meters of blind zone and the transition zone in traditional Mie-lidars [14][15][16][17][18][19][20] always lead to a difficulty in probing aerosols, especially in the lower troposphere [21][22][23]. A few groups have developed side-scattering imaging technologies [24][25][26][27] or multi-field-of-view (mFOV) techniques [28,29] to overcome such difficulties. However, the former methods are limited as the detection range ignores important information from the distant atmosphere, and the latter methods are laboratory instruments that are difficult to move.…”

Section: Introductionmentioning

confidence: 99%

The Determination of Aerosol Distribution by a No-Blind-Zone Scanning Lidar

Wang

Liu

et al. 2020

Remote Sensing

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A homemade portable no-blind zone laser detection and ranging (lidar) system was designed to map the three-dimensional (3D) distribution of aerosols based on a dual-field-of-view (FOV) receiver system. This innovative lidar prototype has a space resolution of 7.5 m and a time resolution of 30 s. A blind zone of zero meters, and a transition zone of approximately 60 m were realized with careful optical alignments, and were rather meaningful to the lower atmosphere observation. With a scanning platform, the lidar system was used to locate the industrial pollution sources at ground level. The primary parameters of the transmitter, receivers, and detectors are described in this paper. Acquiring a whole return signal of this lidar system represents the key step to the retrieval of aerosol distribution with applying a linear joining method to the two FOV signals. The vertical profiles of aerosols were retrieved by the traditional Fernald method and verified by real-time observations. To effectively and reliably retrieve the horizontal distributions of aerosols, a composition of the Fernald method and the slope method were applied. In this way, a priori assumptions of even atmospheric conditions and the already-known reference point in the lidar equation were avoided. No-blind-zone vertical in-situ observation of aerosol illustrated a detailed evolution from almost 0 m to higher altitudes. No-blind-zone detection provided tiny structures of pollution distribution in lower atmosphere, which is closely related to human health. Horizontal field scanning experiments were also conducted in the Shandong Province. The results showed a high accuracy of aerosol mass movement by this lidar system. An effective quantitative way to locate pollution sources distribution was paved with the portable lidar system after validation by the mass concentration of suspended particulate matter from a ground air quality station.

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“…However, the suction-type arrangement is still not suitable for long-term operation in the commercial catering industry [10][11][12]. Some researchers have developed a laserbased side-scattering device [13] for measuring the PM concentration in the atmosphere, and the continuous day and night monitoring of aerosols near the ground has been achieved [14][15][16]. This is generally realized by calibrating the correspondence relationship between the scattered light energy flux and the PM concentration, which is usually measured at the same time by another standard method.…”

Section: Introductionmentioning

confidence: 99%

A side-scattering imaging method for the in-line monitoring of particulate matter emissions from cooking fumes

Zhou¹,

Mei²,

Qin³

et al. 2020

Meas. Sci. Technol.

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To monitor the concentration of particulate matter (PM) from cooking fumes, an in-line measurement method was proposed based on the Lorenz–Mie scattering theory, and a measurement system was developed based on the side-scattering imaging technique with a laser beam for illumination. Polystyrene particles in water suspensions with a known particle size and concentration were utilized for validation. The experimentally obtained gray level of the image of the particle cloud along the laser beam agrees well with that predicted by theoretical model in the same configuration. The artificial fish swarm algorithm was adopted for inversion, and the results of particle size measurements show a standard deviation lower than 5% of the mean measured value at concentrations of 0.5–50 mg · m−3. Using the retrieved particle size distribution, the PM concentrations can be measured with the calculated scattering coefficient k 2 and the measurement system dependent coefficients I 0 k 1. The calibration experiments with polystyrene particle suspensions show a very good linear relationship of the image gray value on the particle concentration. This method makes it possible to monitor the PM concentrations using a non-contact and non-suction approach.

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Retrieval method of aerosol extinction coefficient profile based on backscattering, side-scattering and Raman-scattering lidar

Cited by 9 publications

References 8 publications

Profiling of Aerosols and Clouds over High Altitude Urban Atmosphere in Eastern Himalaya: A Ground-Based Observation Using Raman LIDAR

Profiling of Aerosols and Clouds over High Altitude Urban Atmosphere in Eastern Himalaya: A Ground-Based Observation Using Raman LIDAR

The Determination of Aerosol Distribution by a No-Blind-Zone Scanning Lidar

A side-scattering imaging method for the in-line monitoring of particulate matter emissions from cooking fumes

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