Articles | Volume 22, issue 18
https://doi.org/10.5194/acp-22-12629-2022
© Author(s) 2022. 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-22-12629-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Seasonal modeling analysis of nitrate formation pathways in Yangtze River Delta region, China
Jinjin Sun
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Key Laboratory of Meteorological Disaster, Ministry of Education,
Joint International Research Laboratory of Climate and Environment Change,
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China
Meteorological Administration, Nanjing University of Information Science and
Technology, Nanjing 210044, China
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Xiaodong Xie
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Wenxing Fu
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Yang Qin
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Key Laboratory of Meteorological Disaster, Ministry of Education,
Joint International Research Laboratory of Climate and Environment Change,
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China
Meteorological Administration, Nanjing University of Information Science and
Technology, Nanjing 210044, China
Li Sheng
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Lin Li
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Jingyi Li
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Ishaq Dimeji Sulaymon
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Lei Jiang
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Lin Huang
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Xingna Yu
Key Laboratory of Meteorological Disaster, Ministry of Education,
Joint International Research Laboratory of Climate and Environment Change,
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China
Meteorological Administration, Nanjing University of Information Science and
Technology, Nanjing 210044, China
Jianlin Hu
CORRESPONDING AUTHOR
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, Nanjing University of Information
Science & Technology, Nanjing 210044, China
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Latest update: 29 Nov 2025
Short summary
NO3- has become the dominant and the least reduced chemical component of fine particulate matter in China. NO3- formation is mostly in the NH3-rich regime in the Yangtze River Delta (YRD). OH + NO2 contributes 60 %–83 % of the TNO3 production rates, and the N2O5 heterogeneous pathway contributes 10 %–36 %. The N2O5 heterogeneous pathway becomes more important in cold seasons. Local emissions and regional transportation contribute 50 %–62 % and 38 %–50 % to YRD NO3- concentrations, respectively.
NO3- has become the dominant and the least reduced chemical component of fine particulate matter...
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