Inversion algorithm of black carbon mixing state based on machine learning

The radiative properties of black carbon (BC) are significantly influenced by its mixing state. The single-particle soot photometer (SP2) is a widely recognized instrument for quantifying BC mixing state. However, the derivation of BC mixing state from SP2 is quite challenging. Since the SP2 records...

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Bibliographic Details
Published in:	Atmospheric measurement techniques Vol. 18; no. 5; pp. 1149 - 1162
Main Authors:	Tian, Zeyuan, Wang, Jiandong, Wang, Jiaping, Liu, Chao, Xing, Jia, Wang, Jinbo, Zhang, Zhouyang, Jin, Yuzhi, Shen, Sunan, Wang, Bin, Nie, Wei, Huang, Xin, Ding, Aijun
Format:	Journal Article
Language:	English
Published:	Katlenburg-Lindau Copernicus GmbH 06.03.2025 Copernicus Publications
Subjects:	Aerosols Algorithms Analysis Black carbon Carbon Data analysis Data mining Data processing Decision making Ensemble learning Lasers Leading edges Learning algorithms Light Machine learning Optical properties Particle size Photometers Physical properties Protective coatings Radiation Real time Sensors Signal to noise ratio
ISSN:	1867-8548, 1867-1381, 1867-8548
Online Access:	Get full text
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