Articles | Volume 21, issue 20
https://doi.org/10.5194/acp-21-15447-2021
© Author(s) 2021. 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-21-15447-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Oct 2021
Research article |
| 15 Oct 2021
| 15 Oct 2021
OMI-observed HCHO in Shanghai, China, during 2010–2019 and ozone sensitivity inferred by an improved HCHO ∕ NO2 ratio
Danran Li
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China
Shanshan Wang
CORRESPONDING AUTHOR
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China
Institute of Eco-Chongming (IEC), No. 20 Cuiniao Road, Shanghai 202162, China
Ruibin Xue
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China
Sanbao Zhang
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China
Zhibin Sun
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China
Bin Zhou
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China
Institute of Eco-Chongming (IEC), No. 20 Cuiniao Road, Shanghai 202162, China
Institute of Atmospheric Sciences, Fudan University, Shanghai, 200438, China
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37 citations as recorded by crossref.
- Assessing the Significance of Regional Transport in Ozone Pollution through Machine Learning: A Case Study of Hainan Island J. Liu et al. 10.1021/acsestair.4c00297
- Multiple evaluations of atmospheric behavior between Criegee intermediates and HCHO: Gas-phase and air-water interface reaction T. Zhang et al. 10.1016/j.jes.2022.06.004
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- Research on ozone formation sensitivity based on observational methods: Development history, methodology, and application and prospects in China W. Chu et al. 10.1016/j.jes.2023.02.052
- HCHO and NO2 profile characteristics under different synoptic patterns in Shanghai, China Y. Shi et al. 10.1016/j.jes.2025.01.028
- Disentangling the effects of meteorology and emissions from anthropogenic and biogenic sources on the increased surface ozone in Eastern China M. Shao et al. 10.1016/j.atmosres.2024.107699
- Revealing the drivers of surface ozone pollution by explainable machine learning and satellite observations in Hangzhou Bay, China T. Yao et al. 10.1016/j.jclepro.2024.140938
- Drivers of divergent trends in tropospheric ozone hotspots in Spain, 2008–2019 J. Massagué et al. 10.1007/s11869-023-01468-0
- Evolution of global O3-NOx-VOCs sensitivity before and after the COVID-19 from the ratio of formaldehyde to NO2 from satellite observations D. Wang et al. 10.1016/j.jes.2024.07.029
- What caused ozone pollution during the 2022 Shanghai lockdown? Insights from ground and satellite observations Y. Tan & T. Wang 10.5194/acp-22-14455-2022
- Characterization, source apportionment, and risk assessment of ambient volatile organic compounds in urban and background regions of Hainan Island, China W. Xu et al. 10.1016/j.atmosenv.2023.120167
- Ozone Pollution of Megacity Shanghai during City-Wide Lockdown Assessed Using TROPOMI Observations of NO2 and HCHO R. Xue et al. 10.3390/rs14246344
- Constructing the 3D Spatial Distribution of the HCHO/NO2 Ratio via Satellite Observation and Machine Learning Model Z. Jiang et al. 10.1021/acs.est.4c12362
- The role of NOx in Co-occurrence of O3 and PM2.5 pollution driven by wintertime east Asian monsoon in Hainan J. Zhan et al. 10.1016/j.jenvman.2023.118645
- Changing ozone sensitivity in Fujian Province, China, during 2012–2021: Importance of controlling VOC emissions N. Chen et al. 10.1016/j.envpol.2024.124757
- Meteorological mechanisms of regional PM2.5 and O3 transport in the North China Plain driven by the East Asian monsoon S. Liu et al. 10.1016/j.apr.2022.101638
- Variations, sources, and effects on ozone formation of VOCs during ozone episodes in 13 cities in China D. Shan et al. 10.3389/fenvs.2022.1084592
- Research on the diurnal variation characteristics of ozone formation sensitivity and the impact of ozone pollution control measures in “2 + 26” cities of Henan Province in summer M. Wang et al. 10.1016/j.scitotenv.2023.164121
- Deeper NOx emission reductions toward better air quality in the Yangtze River Delta: Numerical evidences from NOx and VOCs emissions control measures C. Liu et al. 10.1016/j.atmosres.2025.108103
- Source and variability of formaldehyde in the Fenwei Plain: An integrated multi-source satellite and emission inventory study L. Li et al. 10.1016/j.jes.2024.02.030
- Spatio-temporal analysis of formaldehyde and its association with atmospheric and environmental variables over the Southeast Asian region using satellite data S. Dhankar & B. Pani 10.1007/s10661-025-13617-2
- Impact Assessment of COVID‐19 Lockdown on Vertical Distributions of NO2 and HCHO From MAX‐DOAS Observations and Machine Learning Models S. Zhang et al. 10.1029/2021JD036377
- Machine Learning to Characterize Biogenic Isoprene Emissions and Atmospheric Formaldehyde with Their Environmental Drivers in the Marine Boundary Layer T. Wang et al. 10.3390/atmos15060679
- Remote Sensing Measurements at a Rural Site in China: Implications for Satellite NO2 and HCHO Measurement Uncertainty and Emissions From Fires K. Chong et al. 10.1029/2023JD039310
- The Ozone Concentration and Changes in the Sensitivity of Its Formation in Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from a Carbon Neutral Perspective H. Jianghong et al. 10.5814/j.issn.1674-764x.2024.01.018
- Diagnosing ozone–NOx–VOC–aerosol sensitivity and uncovering causes of urban–nonurban discrepancies in Shandong, China, using transformer-based estimations C. Tao et al. 10.5194/acp-24-4177-2024
- Assessment of Formaldehyde’s Impact on Indoor Environments and Human Health via the Integration of Satellite Tropospheric Total Columns and Outdoor Ground Sensors E. Barrese et al. 10.3390/su16229669
- Long-term variation of O3 in the Yangtze River Delta and its influencing factors from a regional perspective Q. Bao et al. 10.1016/j.uclim.2025.102353
- Air Quality Index (AQI) Did Not Improve during the COVID-19 Lockdown in Shanghai, China, in 2022, Based on Ground and TROPOMI Observations Q. Ma et al. 10.3390/rs15051295
- Research on regional ozone prevention and control strategies in eastern China based on pollutant transport network and FNR H. Qi et al. 10.1016/j.scitotenv.2024.170486
- Why did ozone concentrations remain high during Shanghai's static management? A statistical and radical-chemistry perspective J. Zhu et al. 10.5194/acp-24-8383-2024
- Achievements and challenges in improving air quality in China: Analysis of the long-term trends from 2014 to 2022 H. Zheng et al. 10.1016/j.envint.2023.108361
- Investigating Changes in Ozone Formation Chemistry during Summertime Pollution Events over the Northeastern United States M. Tao et al. 10.1021/acs.est.2c02972
- Long-term changes of surface ozone and ozone sensitivity over the North China Plain based on 2015–2021 satellite retrievals C. Zhu et al. 10.1007/s11869-024-01598-z
- Diagnosing ozone–NOx–VOC sensitivity and revealing causes of ozone increases in China based on 2013–2021 satellite retrievals J. Ren et al. 10.5194/acp-22-15035-2022
- Ambient Formaldehyde over the United States from Ground-Based (AQS) and Satellite (OMI) Observations P. Wang et al. 10.3390/rs14092191
- Multi-scale correlation reveals the evolution of socio-natural contributions to tropospheric HCHO over China from 2005 to 2022 H. Xia et al. 10.1016/j.scitotenv.2024.176197
Latest update: 22 Apr 2025
Short summary
Satellite-observed HCHO / NO2 ratios are usually used to infer the O3 formation sensitivity regime. However, it only provides the one ratio around overpass time per day. In order to better characterize the O3 formation during the daytime, we proposed to introduce the surface-observed hourly O3 concentration increment and HCHO / NO2 to correct the satellited-observed HCHO / NO2. Moreover, the temporal and spatial variations of HCHO VCDs and the influencing factors in Shanghai were investigated.
Satellite-observed HCHO / NO2 ratios are usually used to infer the O3 formation sensitivity...
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