Aerosol Classification Based on Airborne High Spectral Resolution Lidar

Na Yao; Miaomiao Zhang; Lingbing Bu; Haiyang Gao; Qin Wang

doi:10.3788/AOS230519

Acta Optica Sinica, Volume. 43, Issue 24, 2428005(2023)

Aerosol Classification Based on Airborne High Spectral Resolution Lidar

Na Yao¹, Miaomiao Zhang², Lingbing Bu^1、*, Haiyang Gao¹, and Qin Wang¹

¹School of Atmospheric Physics, Nanjing University of Information Science & Technology, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing 210044, Jiangsu , China

²Shanghai Institute of Satellite Engineering, Shanghai 201109, China

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Figures & Tables(13)

Fig. 1. Composition of aerosol channel receiver system in HSRL system

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Fig. 2. Correlation analysis of AODs of HSRL, CE318, and spaceborne detector. (a) AOD correlation between HSRL and CE318; (b) AOD correlation between HSRL and spaceborne detector

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Fig. 3. Changes of PM2.5 and PM10 at four sites. (a) PM2.5; (b) PM10

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Fig. 4. Profiles of aerosol optical parameters on three underlying surfaces. (a) Lidar ratio profile; (b) depolarization profile; (c) color ratio profile

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Fig. 5. Aerosol classification results on March 11, 2019

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Fig. 6. Aerosol classification results of CALIPSO

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Fig. 7. Aerosol classification results on March 14, 2019

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Fig. 8. Changes of PM2.5 and PM10 at four sites. (a) PM2.5; (b) PM10

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Fig. 9. Humidity map of Shanhaiguan on March 14, 2019

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Fig. 10. Aerosol classification results on March 19, 2019

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Fig. 11. Changes of PM2.5 and PM10 at four sites. (a) PM2.5; (b) PM10

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Table 1. Airborne HSRL system flight test process

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Table 1. Airborne HSRL system flight test process

Serial number	Time	Place	Event
1	March 4，2019	Shanhaiguan，Qinhuangdao，Hebei Province	Flight 1：4 km highly airspace-adapted flight
2	March 9，2019		Flight 2：3 km altitude flight test
3	March 11，2019		Flight 3：5 km altitude flight test
4	March 14，2019		Flight 4：7 km altitude flight test
5	March 16，2019		Flight 5：8 km altitude flight test
6	March 18，2019		Flight 6：4 km altitude flight test
7	March 19，2019		Flight 7：5 km altitude flight test

Table 2. Measurement range of aerosol strength parameters for categorical measurements

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Table 2. Measurement range of aerosol strength parameters for categorical measurements

Aerosol type	Aerosol depolarization /%	Lidar ratio /sr	Backscatter color ratio	Measuring equipment or method information	Source
	30-45			Polarization diversity lidar	Sassen and Hsueh（1998，cirrus clouds）^［41］
	60-70			Polarization diversity lidar	Sassen and Hsueh（1998，contails）^［41］
	30-70			Polarization lidar/T~matrix computations	Mischenko and Sassen（1998）^［42］
Ice		<30		Raman lidar and polarization lidar	Sakai et al.（2003）^［43］
	50-60	~20	0.7-2.9	Airborne HSRL/Haar wavelet et al.	Burton et al.（2012）^［10］
	18-33	23-32	0.7-1.1	Airborne HSRL	Burton et al.（2013）^［44］
	18-70	20-32	0.7-2.9		Summary
		42-55		HSRL et/T~matrix calculation	Liu et al.（2002）^［5］
	~30	45-63		Mie backscatter lidar and C~130 aircraft	Murayama et al.（2003）^［45］

	~35	50		Mie scattering lidar with polarization channels/Two~component model for aerosol	Sugimoto and Lee（2006）^［6］
Pure dust	30-32	44-64		SAMUM~2a and SAMUM~2b et al.	Tesche et al.（2011）^［46］
	30-35	~59		Depolarization lidar	Wiegner et al.（2011）^［47］
	30-32	57-67		Three wavelengths with three lidar systems	Groβ et al.（2011）^［9］
	~33	40-58	1.0-1.7	Aerborne HSRL	Burton et al.（2012）^［10］
	29-33	43-53		CPC，DMA，HSRL	Groβ et al.（2013）^［11］
	31-33	45-51	1.4-1.6	Airborne HSRL	Burton et al.（2013）^［44］
	29-35	40-67	1.0-1.7		Summary
	8-20			Raman，depolarization lidar	Chen et al.（2007）^［48］
	17-23	28-48		Raman lidar	Xie et al.（2008）^［7］
	19-28				Groβ et al.（2011）^［9］
Dusty mix	24-32	46-60		CIMEL sun photometer，multiwavelength Raman lidar et al.	Preiβler et al.（2011）^［49］
	20-35	30-50	1.0-2.2		Burton et al.（2012）^［10］
	25-29	46-54			Groβ et al.（2013）^［11］
	13-20	29-49	1.3-1.8		Burton et al.（2013）^［44］
	8-35	28-60	1.0-2.2		Summary
	~8				Sakai et al.（2010）^［50］
	1-3	16-20			Groβ et al.（2011）^［9］
Marine	<10	15-25	1.2-1.8		Burton et al.（2012）^［10］
	2-4	13-23			Groβ et al.（2013）^［11］
	4-9	17-27	1.3-1.6		Burton et al.（2013）^［44］
	1-10	13-27	1.2-1.8		Summary
Polluted	3-5	36-45	1.5-1.7		Burton et al.（2013）^［44］
marine	3-5	36-45	1.5-1.7		Summary
	5-9	47-75			Xie et al.（2008，moderate pollution）^［7］
Urban	5-9	36-52			Xie et al.（2008，heavy pollution）^［7］
	<10	50-70	1.4-2.4		Burton et al.（2012）^［10］
	5-7	50-62			Groβ et al.（2013）^［11］
	3-7	53-70	1.7-2.1		Burton et al.（2013）^［44］
	3-10	36-75	1.4-2.4		Summary
	2-5	30-60	1.4-3.0		Burton et al.（2012）^［10］
Smoke	5-9	52-86			Groβ et al.（2013）^［11］
	4-9	55-73	1.9-2.5		Burton et al.（2013）^［44］
	2-9	30-86	1.4-3.0		Summary
Fresh	3-6	33-46	2.1-2.5		Burton et al.（2013）^［44］
smoke	3-6	33-46	2.1-2.5		Summary

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Na Yao, Miaomiao Zhang, Lingbing Bu, Haiyang Gao, Qin Wang. Aerosol Classification Based on Airborne High Spectral Resolution Lidar[J]. Acta Optica Sinica, 2023, 43(24): 2428005

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Paper Information

Category: Remote Sensing and Sensors

Received: Feb. 6, 2023

Accepted: Apr. 3, 2023

Published Online: Dec. 12, 2023

The Author Email: Bu Lingbing (lingbingbu@nuist.edu.cn)

DOI:10.3788/AOS230519

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology