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.
Research article
| 
28 Sep 2022
Research article |
| 28 Sep 2022
| 28 Sep 2022
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
Viewed
Total article views: 2,257 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 28 Jun 2022)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,678 | 540 | 39 | 2,257 | 179 | 20 | 47 |
- HTML: 1,678
- PDF: 540
- XML: 39
- Total: 2,257
- Supplement: 179
- BibTeX: 20
- EndNote: 47
Total article views: 1,554 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 28 Sep 2022)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,191 | 345 | 18 | 1,554 | 106 | 17 | 37 |
- HTML: 1,191
- PDF: 345
- XML: 18
- Total: 1,554
- Supplement: 106
- BibTeX: 17
- EndNote: 37
Total article views: 703 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 28 Jun 2022)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 487 | 195 | 21 | 703 | 73 | 3 | 10 |
- HTML: 487
- PDF: 195
- XML: 21
- Total: 703
- Supplement: 73
- BibTeX: 3
- EndNote: 10
Viewed (geographical distribution)
Total article views: 2,257 (including HTML, PDF, and XML)
Thereof 2,454 with geography defined
and -197 with unknown origin.
Total article views: 1,554 (including HTML, PDF, and XML)
Thereof 1,725 with geography defined
and -171 with unknown origin.
Total article views: 703 (including HTML, PDF, and XML)
Thereof 729 with geography defined
and -26 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
10 citations as recorded by crossref.
- Dominant physical and chemical processes impacting nitrate in Shandong of the North China Plain during winter haze events J. Yang et al. 10.1016/j.scitotenv.2023.169065
- Quantifying Contributions of Factors and Their Interactions to Aerosol Acidity with a Multiple-Linear-Regression-Based Framework: A Case Study in the Pearl River Delta, China H. Ling et al. 10.3390/atmos15020172
- Modeling PM2.5 During Severe Atmospheric Pollution Episode in Lagos, Nigeria: Spatiotemporal Variations, Source Apportionment, and Meteorological Influences I. Sulaymon et al. 10.1029/2022JD038360
- Examining the implications of photochemical indicators for O3–NOx–VOC sensitivity and control strategies: a case study in the Yangtze River Delta (YRD), China X. Li et al. 10.5194/acp-22-14799-2022
- WITHDRAWN: Insights into the source contributions to the elevated fine particulate matter in Nigeria using a source-oriented chemical transport model I. Sulaymon et al. 10.1016/j.chemosphere.2024.141548
- Trends of source apportioned PM2.5 in Tianjin over 2013–2019: Impacts of Clean Air Actions Q. Dai et al. 10.1016/j.envpol.2023.121344
- Evolution of atmospheric age of particles and its implications for the formation of a severe haze event in eastern China X. Xie et al. 10.5194/acp-23-10563-2023
- Light absorption enhancement of black carbon and its impact factors during winter in a megacity of the Sichuan Basin, China Y. Lan et al. 10.1016/j.scitotenv.2024.170374
- Using the COVID-19 lockdown to identify atmospheric processes and meteorology influences on regional PM2.5 pollution episodes in the Beijing-Tianjin-Hebei, China I. Sulaymon et al. 10.1016/j.atmosres.2023.106940
- Diagnosing the Sensitivity of Particulate Nitrate to Precursor Emissions Using Satellite Observations of Ammonia and Nitrogen Dioxide R. Dang et al. 10.1029/2023GL105761
10 citations as recorded by crossref.
- Dominant physical and chemical processes impacting nitrate in Shandong of the North China Plain during winter haze events J. Yang et al. 10.1016/j.scitotenv.2023.169065
- Quantifying Contributions of Factors and Their Interactions to Aerosol Acidity with a Multiple-Linear-Regression-Based Framework: A Case Study in the Pearl River Delta, China H. Ling et al. 10.3390/atmos15020172
- Modeling PM2.5 During Severe Atmospheric Pollution Episode in Lagos, Nigeria: Spatiotemporal Variations, Source Apportionment, and Meteorological Influences I. Sulaymon et al. 10.1029/2022JD038360
- Examining the implications of photochemical indicators for O3–NOx–VOC sensitivity and control strategies: a case study in the Yangtze River Delta (YRD), China X. Li et al. 10.5194/acp-22-14799-2022
- WITHDRAWN: Insights into the source contributions to the elevated fine particulate matter in Nigeria using a source-oriented chemical transport model I. Sulaymon et al. 10.1016/j.chemosphere.2024.141548
- Trends of source apportioned PM2.5 in Tianjin over 2013–2019: Impacts of Clean Air Actions Q. Dai et al. 10.1016/j.envpol.2023.121344
- Evolution of atmospheric age of particles and its implications for the formation of a severe haze event in eastern China X. Xie et al. 10.5194/acp-23-10563-2023
- Light absorption enhancement of black carbon and its impact factors during winter in a megacity of the Sichuan Basin, China Y. Lan et al. 10.1016/j.scitotenv.2024.170374
- Using the COVID-19 lockdown to identify atmospheric processes and meteorology influences on regional PM2.5 pollution episodes in the Beijing-Tianjin-Hebei, China I. Sulaymon et al. 10.1016/j.atmosres.2023.106940
- Diagnosing the Sensitivity of Particulate Nitrate to Precursor Emissions Using Satellite Observations of Ammonia and Nitrogen Dioxide R. Dang et al. 10.1029/2023GL105761
Latest update: 23 Apr 2024
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...
Altmetrics
Final-revised paper
Preprint