329 Aerosol Classification with the 532- and 1047-nm Lidar Depolarization Ratio

Monday, 13 January 2020
Hall B (Boston Convention and Exhibition Center)
Yunhui Zheng, Hexagon U.S. Federal, Lanham, MD

Aerosols play an important role in the global climate, air pollution, and aviation transportation. In recent years, aerosol LiDAR has been routinely used to remotely monitor aerosol concentration and air pollution (Welton, 2001). A small class of LiDAR instruments are designed to measure the depolarization ratio for aerosol classification. Aerosol’s depolarization value varies with their particle size and sphericity, and are captured differently depending on the designated wavelength of the instrument.Mini Micro Pulse Lidar (MiniMPL) available from Hexagon Corporation is a single wavelength (532nm) aerosol LiDAR instrument capable of measuring aerosol vertically up to 15km. With the addition of a mounted scanner, the instrument can capture a 360-degree horizontal scan typically up to 6km. With single wavelength, however, there are still ambiguities in aerosol classification. For example, since the depolarization of ice cloud, dust and volcanic ash are all in the range of 0.2-0.4. They are not distinguishable from each other based on 532nm depolarization only. The MiniMPL has recently added a single wavelength LiDAR at 1047nm. The instruments maintain their integrity as separate, independent units, but when collocated, data captured at 532nm and 1047nm can be synchronized either electronically or digitally through post-processing, and the instruments serve as a dual-wavelength LiDAR. By capturing two wavelengths of the same dataset, a more detailed view of the atmosphere emerges, and typing ambiguities that are sometimes present with single wavelength LiDAR can be eliminated. Using both instruments with different wavelength, a yearlong campaign is underway to develop a particle typing database with the dual-wavelength depolarization measurements. The goal is to classify ice/dust/ash and various kinds of pollution such as smoke/haze/emission. Some example data will show the dual-wavelength particle classification advantage over a single wavelength. Data synergy with other information such as color ratio will also be presented.
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