Articles | Volume 26, issue 19
https://doi.org/10.5194/acp-26-14015-2026
© 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-26-14015-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Oct 2026
Research article |
| 06 Oct 2026
| 06 Oct 2026
Cross-phase partitioning of sulfur-nitrogen ratios and aerosol mixing-state evolution based on single-particle observations
Yuan Dai
Jiangsu Key Laboratory of Intelligent Atmospheric Environment Monitoring and Carbon-Pollution Co-Control (IAEMCPC), Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CIC-AEET), School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yangzhou Environmental Monitoring Center, Yangzhou 225009, China
Jiangsu Key Laboratory of Intelligent Atmospheric Environment Monitoring and Carbon-Pollution Co-Control (IAEMCPC), Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CIC-AEET), School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Mindong Chen
Jiangsu Key Laboratory of Intelligent Atmospheric Environment Monitoring and Carbon-Pollution Co-Control (IAEMCPC), Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CIC-AEET), School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Su Zhang
Yangzhou Environmental Monitoring Center, Yangzhou 225009, China
Haiwei Li
Jiangsu Key Laboratory of Intelligent Atmospheric Environment Monitoring and Carbon-Pollution Co-Control (IAEMCPC), Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CIC-AEET), School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yunjiang Zhang
Jiangsu Key Laboratory of Intelligent Atmospheric Environment Monitoring and Carbon-Pollution Co-Control (IAEMCPC), Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CIC-AEET), School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yun Wu
Jiangsu Key Laboratory of Intelligent Atmospheric Environment Monitoring and Carbon-Pollution Co-Control (IAEMCPC), Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CIC-AEET), School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Ming Wang
Jiangsu Key Laboratory of Intelligent Atmospheric Environment Monitoring and Carbon-Pollution Co-Control (IAEMCPC), Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CIC-AEET), School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Xinlei Ge
CORRESPONDING AUTHOR
School of Energy and Environment, Southeast University, Nanjing 211189, China
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Short summary
Air pollution involves complex interactions between airborne particles and gases, but these links are not fully understood. We analyzed individual particles and gases across different emission levels. We found that relative sulfur and nitrogen levels influence how gases interact with particles and alter their properties. These processes vary by particle type and humidity, helping explain how pollution forms and evolves. Our findings provide new evidence for particle-gas interactions.
Air pollution involves complex interactions between airborne particles and gases, but these...
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