Articles | Volume 26, issue 11
https://doi.org/10.5194/acp-26-8021-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-8021-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
NOx emissions constraints from GEMS NO2 retrievals: inversion methodology and air quality model evaluation in Bangkok using ASIA-AQ multi-platform observations
Julianna A. Christopoulos
CORRESPONDING AUTHOR
Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, USA
Pablo E. Saide
Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, USA
Institute of the Environment and Sustainability, University of California, Los Angeles, CA, USA
Manas R. Mohanty
Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, USA
Nattamon Maneenoi
Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, USA
Jhoon Kim
Department of Atmospheric Sciences, Yonsei University, Seoul, South Korea
Laura Judd
NASA Langley Research Center, Hampton, VA, USA
Katherine R. Travis
NASA Langley Research Center, Hampton, VA, USA
Savitri Garivait
The Joint Graduate School of Energy and Environment, King Mongkut's University of Technology, Thonburi, Thailand
Center of Excellence on Energy Technology and Environment, PERDO, Ministry of Higher Education, Science, Research and Innovation, Bangkok, Thailand
Agapol Junpen
The Joint Graduate School of Energy and Environment, King Mongkut's University of Technology, Thonburi, Thailand
Center of Excellence on Energy Technology and Environment, PERDO, Ministry of Higher Education, Science, Research and Innovation, Bangkok, Thailand
Kazuyuki Miyazaki
Jet Propulsion Laboratory (JPL), California Institute of Technology, Pasadena, 91109 CA, USA
Joint Institute for Regional System Science and Engineering (JIFRESSE), University of California, Los Angeles, CA, USA
Jinkyul Choi
Jet Propulsion Laboratory (JPL), California Institute of Technology, Pasadena, 91109 CA, USA
Joint Institute for Regional System Science and Engineering (JIFRESSE), University of California, Los Angeles, CA, USA
Takashi Sekiya
Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
David Peterson
US Naval Research Laboratory, Monterey, CA, USA
Theodore M. McHardy
US Naval Research Laboratory, Monterey, CA, USA
Nicholas Gapp
Science Applications International Corporation, Monterey, CA, USA
Jason M. St. Clair
Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, USA
GESTAR II, University of Maryland, Baltimore Country, Baltimore, USA
Erin Delaria
ESSIC, University of Maryland, College Park, MD, USA
Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, USA
Glenn M. Wolfe
Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, USA
Abby Sebol
Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, USA
Alessandro Franchin
Atmospheric Chemistry Observations and Modeling Laboratory, NSF National Center for Atmospheric Research, Boulder, CO, USA
Changmin Cho
Atmospheric Chemistry Observations and Modeling Laboratory, NSF National Center for Atmospheric Research, Boulder, CO, USA
Morgan L. Silverman
NASA Langley Research Center, Hampton, VA, USA
Science Systems and Applications, Inc., Hampton, VA, USA
James H. Crawford
NASA Langley Research Center, Hampton, VA, USA
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Short summary
Air quality in rapidly growing cities is difficult to model because emissions vary during the day and are often poorly constrained. We demonstrate a methodology for constraining urban emissions using hourly satellite observations combined with high-resolution air quality modeling in Bangkok. We find that emissions inventories likely overestimate nitrogen dioxide emissions, and that updated emissions improve agreement between the model and independent aircraft and ground-based observations.
Air quality in rapidly growing cities is difficult to model because emissions vary during the...
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