Articles | Volume 18, issue 24
https://doi.org/10.5194/amt-18-7735-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-7735-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Particulate matter concentrations derived from airborne high spectral resolution lidar measurements using machine learning regression
Richard Ferrare
CORRESPONDING AUTHOR
NASA Langley Research Center, Hampton, VA, United States
Johnathan Hair
NASA Langley Research Center, Hampton, VA, United States
Taylor Shingler
NASA Langley Research Center, Hampton, VA, United States
Chris Hostetler
NASA Langley Research Center, Hampton, VA, United States
Amin Nehrir
NASA Langley Research Center, Hampton, VA, United States
Marta Fenn
Psionic, LLC, Hampton, VA, United States
Amy Jo Scarino
Psionic, LLC, Hampton, VA, United States
Sharon Burton
NASA Langley Research Center, Hampton, VA, United States
Marian Clayton
Psionic, LLC, Hampton, VA, United States
James Collins
Psionic, LLC, Hampton, VA, United States
Laura Judd
NASA Langley Research Center, Hampton, VA, United States
James Crawford
NASA Langley Research Center, Hampton, VA, United States
Katherine Travis
NASA Langley Research Center, Hampton, VA, United States
Travis Toth
NASA Langley Research Center, Hampton, VA, United States
Pablo Saide
Department of Atmospheric and Oceanic Sciences, University of California–Los Angeles, Los Angeles, California, United States
Institute of the Environment and Sustainability, University of California–Los Angeles, Los Angeles, California, United States
Jose Luis Jimenez
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
Department of Chemistry, University of Colorado Boulder, Boulder, CO, United States
Pedro Campuzano-Jost
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
Department of Chemistry, University of Colorado Boulder, Boulder, CO, United States
Guy Symonds
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
Department of Chemistry, University of Colorado Boulder, Boulder, CO, United States
Richard Moore
NASA Langley Research Center, Hampton, VA, United States
Luke Ziemba
NASA Langley Research Center, Hampton, VA, United States
Michael Shook
NASA Langley Research Center, Hampton, VA, United States
Glenn Diskin
NASA Langley Research Center, Hampton, VA, United States
Joshua P. DiGangi
NASA Langley Research Center, Hampton, VA, United States
Ryan Bennett
Bay Area Environmental Research Institute, Newport News, Virginia, United States
Chia-Hsiang Ho
Ministry of Environment, ROC (Taiwan), Taipei City, Taiwan
Lim-Seok Chang
Air Quality Research Division, National Institute of Environmental Research, Incheon, Republic of Korea
Adisak Aiampisanuvong
Air and Noise Quality Management Division, Environment Department, Bangkok Metropolitan Administration, Bangkok, Thailand
Ittipol Pawarmart
Pollution Control Department, Bangkok, Thailand
Data sets
STAQS JSC GV High Spectral Resolution Lidar-2 Data NASA/LARC/SD/ASDC https://doi.org/10.5067/ASDC/SUBORBITAL/STAQS/DATA001/GV/AircraftRemoteSensing/HSRL2_1
ASIA-AQ LaRC G-III High Spectral Resolution Lidar-2 Data NASA/LARC/SD/ASDC https://doi.org/10.5067/ASDC/SUBORBITAL/ASIA-AQ/DATA001/G3/AircraftRemoteSensing/HSRL2_1
ASIA-AQ Analysis Data NASA/LARC/SD/ASDC https://doi.org/10.5067/SUBORBITAL/ASIA-AQ/DATA001/DC8/Analysis_1
Short summary
We present a new method to retrieve atmospheric particulate matter concentrations using only airborne High Spectral Resolution Lidar measurements in machine learning algorithms. Retrieved concentrations agree well with surface measurements. These concentrations and our estimates of the particle mass extinction efficiency are also consistent with those retrieved from airborne in situ measurements. This methodology can also be applied to the Atmosphere Lidar on the EarthCARE satellite.
We present a new method to retrieve atmospheric particulate matter concentrations using only...