Articles | Volume 25, issue 22
https://doi.org/10.5194/acp-25-16797-2025
© Author(s) 2025. 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-25-16797-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
HONO formation mechanisms and impacts on ambient oxidants in coastal regions of Fujian, China
Haoran Zhang
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing, 210023, China
Chengchun Shi
Fujian Academy of Environmental Sciences, Fuzhou, 350013, China
Fujian Key Laboratory of Environmental Engineering, Fuzhou, 350013, China
Chuanyou Ying
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing, 210023, China
Fuzhou Research Academy of Environmental Sciences, Fuzhou, 350013, China
Shengheng Weng
Fujian Institute of Meteorological Sciences, China Meteorological Administration, Fuzhou, 350001, China
Erling Ni
Fujian Academy of Environmental Sciences, Fuzhou, 350013, China
Fujian Key Laboratory of Environmental Engineering, Fuzhou, 350013, China
Lanbu Zhao
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing, 210023, China
Peiheng Yang
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing, 210023, China
Keqin Tang
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China
Xueyu Zhou
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing, 210023, China
Chuanhua Ren
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing, 210023, China
Xuguang Chi
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing, 210023, China
Derong Zhou
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Mengmeng Li
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing, 210023, China
Nan Li
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China
Tengyu Liu
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing, 210023, China
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing, 210023, China
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Guangdong Niu, Ximeng Qi, Liangduo Chen, Lian Xue, Shiyi Lai, Xin Huang, Jiaping Wang, Xuguang Chi, Wei Nie, Veli-Matti Kerminen, Tuukka Petäjä, Markku Kulmala, and Aijun Ding
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Haoran Zhang, Nan Li, Keqin Tang, Hong Liao, Chong Shi, Cheng Huang, Hongli Wang, Song Guo, Min Hu, Xinlei Ge, Mindong Chen, Zhenxin Liu, Huan Yu, and Jianlin Hu
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Qi En Zhong, Chunlei Cheng, Zaihua Wang, Lei Li, Mei Li, Dafeng Ge, Lei Wang, Yuanyuan Li, Wei Nie, Xuguang Chi, Aijun Ding, Suxia Yang, Duohong Chen, and Zhen Zhou
Atmos. Chem. Phys., 21, 17953–17967, https://doi.org/10.5194/acp-21-17953-2021, https://doi.org/10.5194/acp-21-17953-2021, 2021
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Mengmeng Li, Zihan Zhang, Quan Yao, Tijian Wang, Min Xie, Shu Li, Bingliang Zhuang, and Yong Han
Atmos. Chem. Phys., 21, 15135–15152, https://doi.org/10.5194/acp-21-15135-2021, https://doi.org/10.5194/acp-21-15135-2021, 2021
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Yuliang Liu, Wei Nie, Yuanyuan Li, Dafeng Ge, Chong Liu, Zhengning Xu, Liangduo Chen, Tianyi Wang, Lei Wang, Peng Sun, Ximeng Qi, Jiaping Wang, Zheng Xu, Jian Yuan, Chao Yan, Yanjun Zhang, Dandan Huang, Zhe Wang, Neil M. Donahue, Douglas Worsnop, Xuguang Chi, Mikael Ehn, and Aijun Ding
Atmos. Chem. Phys., 21, 14789–14814, https://doi.org/10.5194/acp-21-14789-2021, https://doi.org/10.5194/acp-21-14789-2021, 2021
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Oxygenated organic molecules (OOMs) are crucial intermediates linking volatile organic compounds to secondary organic aerosols. Using nitrate time-of-flight chemical ionization mass spectrometry in eastern China, we performed positive matrix factorization (PMF) on binned OOM mass spectra. We reconstructed over 1000 molecules from 14 derived PMF factors and identified about 72 % of the observed OOMs as organic nitrates, highlighting the decisive role of NOx in OOM formation in populated areas.
Shibao Wang, Yun Ma, Zhongrui Wang, Lei Wang, Xuguang Chi, Aijun Ding, Mingzhi Yao, Yunpeng Li, Qilin Li, Mengxian Wu, Ling Zhang, Yongle Xiao, and Yanxu Zhang
Atmos. Chem. Phys., 21, 7199–7215, https://doi.org/10.5194/acp-21-7199-2021, https://doi.org/10.5194/acp-21-7199-2021, 2021
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Da Gao, Min Xie, Jane Liu, Tijian Wang, Chaoqun Ma, Haokun Bai, Xing Chen, Mengmeng Li, Bingliang Zhuang, and Shu Li
Atmos. Chem. Phys., 21, 5847–5864, https://doi.org/10.5194/acp-21-5847-2021, https://doi.org/10.5194/acp-21-5847-2021, 2021
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O3 has been increasing in recent years over the Yangtze River Delta region of China and is closely associated with dominant weather systems. Still, the study on the impact of changes in synoptic weather patterns (SWPs) on O3 variation is quite limited. This work aims to reveal the unique features of changes in each SWP under O3 variation and quantifies the effects of meteorological conditions on O3 variation. Our findings could be helpful in strategy planning for O3 pollution control.
Yanxu Zhang, Xingpei Ye, Shibao Wang, Xiaojing He, Lingyao Dong, Ning Zhang, Haikun Wang, Zhongrui Wang, Yun Ma, Lei Wang, Xuguang Chi, Aijun Ding, Mingzhi Yao, Yunpeng Li, Qilin Li, Ling Zhang, and Yongle Xiao
Atmos. Chem. Phys., 21, 2917–2929, https://doi.org/10.5194/acp-21-2917-2021, https://doi.org/10.5194/acp-21-2917-2021, 2021
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Urban air quality varies drastically at street scale, but traditional methods are too coarse to resolve it. We develop a 10 m resolution air quality model and apply it for traffic-related carbon monoxide air quality in Nanjing megacity. The model reveals a detailed geographical dispersion pattern of air pollution in and out of the road network and agrees well with a validation dataset. The model can be a vigorous part of the smart city system and inform urban planning and air quality management.
Yang Yang, Yu Zhao, Lei Zhang, Jie Zhang, Xin Huang, Xuefen Zhao, Yan Zhang, Mengxiao Xi, and Yi Lu
Atmos. Chem. Phys., 21, 1191–1209, https://doi.org/10.5194/acp-21-1191-2021, https://doi.org/10.5194/acp-21-1191-2021, 2021
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We conducted new NOx emission estimation based on the satellite-derived NO2 column constraint and found reduced emissions compared to previous estimates for a developed region in east China. The subsequent improvement in air quality modeling was demonstrated based on available ground observations. With multiple emission reduction cases for various pollutants, we explored the effective control approaches for ozone and inorganic aerosol pollution.
Cited articles
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Short summary
This study reports a unique diurnal pattern of nitrous acid (HONO), featuring higher concentrations around noon, based on one-month measurements in coastal Fujian, southeast China. Using an improved chemical transport model, we successfully reproduced the observed HONO levels and temporal variations. Further process analyses and sensitivity experiments quantified the formation mechanisms of HONO in coastal areas and shed light on its impact on the formation of OH radicals and ozone.
This study reports a unique diurnal pattern of nitrous acid (HONO), featuring higher...
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