Articles | Volume 26, issue 16
https://doi.org/10.5194/acp-26-11967-2026
© 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-26-11967-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Improved representation of isoprene-derived secondary organic aerosol in CAM6-Chem reveals regional contrasts in its long-term changes over China
Wenxin Zhang
School of Atmospheric Science, Nanjing University, Nanjing, 210023, China
School of Atmospheric Science, Nanjing University, Nanjing, 210023, China
Zhejiang Institute of Meteorological Sciences, Hangzhou, 310008, China
Xinyue Shao
Jiangsu Meteorological Observatory, Jiangsu Meteorological Bureau, Nanjing, 210019, China
School of Atmospheric Science, Nanjing University, Nanjing, 210023, China
Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences & Institute for Climate and Global Change Research, Nanjing University, Nanjing, 210023, China
Minghuai Wang
School of Atmospheric Science, Nanjing University, Nanjing, 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences & Institute for Climate and Global Change Research, Nanjing University, Nanjing, 210023, China
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Short summary
Isoprene-derived secondary organic aerosol (ISOA) remains poorly represented in models, creating uncertainty in its changes and drivers. An improved model better matches observations and shows that low-NOx formation dominates. Overall ISOA changed little from 2000 to 2019 because opposite regional trends offset each other: increases in Southwest China were driven by stronger isoprene emissions, while decreases in Shaanxi–Gansu–Ningxia were driven by changes in anthropogenic emissions.
Isoprene-derived secondary organic aerosol (ISOA) remains poorly represented in models, creating...
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