Articles | Volume 23, issue 1
https://doi.org/10.5194/acp-23-551-2023
© Author(s) 2023. 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-23-551-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantifying daily NOx and CO2 emissions from Wuhan using satellite observations from TROPOMI and OCO-2
Environmental Science Group, Wageningen University, Wageningen, the
Netherlands
Key Laboratory of Radiometric Calibration and Validation for
Environmental Satellites, Innovation Center for Fengyun Meteorological Satellite (FYSIC), National Satellite Meteorological Center, China Meteorology Administration, Beijing, 100081, China
K. Folkert Boersma
CORRESPONDING AUTHOR
Environmental Science Group, Wageningen University, Wageningen, the
Netherlands
Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of environment, Tsinghua University, Beijing, 100084, China
Henk Eskes
Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
Cuihong Chen
Satellite Application Center for Ecology and Environment, Ministry of Ecology and Environment of the People's Republic of China, Beijing, 100094, China
Haotian Zheng
State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of environment, Tsinghua University, Beijing, 100084, China
Xingying Zhang
Key Laboratory of Radiometric Calibration and Validation for
Environmental Satellites, Innovation Center for Fengyun Meteorological Satellite (FYSIC), National Satellite Meteorological Center, China Meteorology Administration, Beijing, 100081, China
now at: the Department of Science & Technology and Climate Change, China Meteorology Administration, Beijing, 10081, China
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Cited
17 citations as recorded by crossref.
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- Temporal Variability of Tropospheric NO2 over Cities in the United States, Western Europe and China from 2005 to 2022 Q. Zhang 10.1007/s11769-024-1454-5
- Estimating global 0.1° scale gridded anthropogenic CO2 emissions using TROPOMI NO2 and a data-driven method Y. Zhang et al. 10.1016/j.scitotenv.2024.175177
- Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: A case study of Matimba/Medupi power stations in South Africa J. Hakkarainen et al. 10.1016/j.apr.2024.102171
- Toward monitoring daily anthropogenic CO2 emissions with air pollution sensors from space H. Li & B. Zheng 10.1016/j.oneear.2024.08.019
- Satellite reveals a steep decline in China’s CO 2 emissions in early 2022 H. Li et al. 10.1126/sciadv.adg7429
- Evaluating NOx stack plume emissions using a high-resolution atmospheric chemistry model and satellite-derived NO2 columns M. Krol et al. 10.5194/acp-24-8243-2024
- Anthropogenic NO x emissions of China, the U.S. and Europe from 2019 to 2022 inferred from TROPOMI observations Y. Mao et al. 10.1088/1748-9326/ad3cf9
- Quantification of CO2 Emissions from Three Power Plants in China Using OCO-3 Satellite Measurements Y. Yang et al. 10.1007/s00376-024-3293-9
- Monitoring fossil fuel CO2 emissions from co-emitted NO2 observed from space: progress, challenges, and future perspectives H. Li et al. 10.1007/s11783-025-1922-x
- Unveiling Air Pollution in Crimean Mountain Rivers: Analysis of Sentinel-5 Satellite Images Using Google Earth Engine (GEE) V. Tabunschik et al. 10.3390/rs15133364
- The impact of COVID-19 lockdowns on urban photochemistry as inferred from TROPOMI S. Lama et al. 10.1016/j.atmosenv.2023.120042
- CO2 and CO temporal variability over Mexico City from ground-based total column and surface measurements N. Taquet et al. 10.5194/acp-24-11823-2024
- Retrieval anthropogenic CO2 emissions from OCO-2 and comparison with gridded emission inventories C. Jin et al. 10.1016/j.jclepro.2024.141418
- A simplified non-linear chemistry transport model for analyzing NO2 column observations: STILT–NOx D. Wu et al. 10.5194/gmd-16-6161-2023
- TROPOMI NO2 Shows a Fast Recovery of China’s Economy in the First Quarter of 2023 H. Li & B. Zheng 10.1021/acs.estlett.3c00386
- Estimating anthropogenic CO2 emissions from China's Yangtze River Delta using OCO-2 observations and WRF-Chem simulations M. Sheng et al. 10.1016/j.rse.2024.114515
17 citations as recorded by crossref.
- Nitrogen oxides emissions from selected cities in North America, Europe, and East Asia observed by the TROPOspheric Monitoring Instrument (TROPOMI) before and after the COVID-19 pandemic C. Lonsdale & K. Sun 10.5194/acp-23-8727-2023
- Temporal Variability of Tropospheric NO2 over Cities in the United States, Western Europe and China from 2005 to 2022 Q. Zhang 10.1007/s11769-024-1454-5
- Estimating global 0.1° scale gridded anthropogenic CO2 emissions using TROPOMI NO2 and a data-driven method Y. Zhang et al. 10.1016/j.scitotenv.2024.175177
- Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: A case study of Matimba/Medupi power stations in South Africa J. Hakkarainen et al. 10.1016/j.apr.2024.102171
- Toward monitoring daily anthropogenic CO2 emissions with air pollution sensors from space H. Li & B. Zheng 10.1016/j.oneear.2024.08.019
- Satellite reveals a steep decline in China’s CO 2 emissions in early 2022 H. Li et al. 10.1126/sciadv.adg7429
- Evaluating NOx stack plume emissions using a high-resolution atmospheric chemistry model and satellite-derived NO2 columns M. Krol et al. 10.5194/acp-24-8243-2024
- Anthropogenic NO x emissions of China, the U.S. and Europe from 2019 to 2022 inferred from TROPOMI observations Y. Mao et al. 10.1088/1748-9326/ad3cf9
- Quantification of CO2 Emissions from Three Power Plants in China Using OCO-3 Satellite Measurements Y. Yang et al. 10.1007/s00376-024-3293-9
- Monitoring fossil fuel CO2 emissions from co-emitted NO2 observed from space: progress, challenges, and future perspectives H. Li et al. 10.1007/s11783-025-1922-x
- Unveiling Air Pollution in Crimean Mountain Rivers: Analysis of Sentinel-5 Satellite Images Using Google Earth Engine (GEE) V. Tabunschik et al. 10.3390/rs15133364
- The impact of COVID-19 lockdowns on urban photochemistry as inferred from TROPOMI S. Lama et al. 10.1016/j.atmosenv.2023.120042
- CO2 and CO temporal variability over Mexico City from ground-based total column and surface measurements N. Taquet et al. 10.5194/acp-24-11823-2024
- Retrieval anthropogenic CO2 emissions from OCO-2 and comparison with gridded emission inventories C. Jin et al. 10.1016/j.jclepro.2024.141418
- A simplified non-linear chemistry transport model for analyzing NO2 column observations: STILT–NOx D. Wu et al. 10.5194/gmd-16-6161-2023
- TROPOMI NO2 Shows a Fast Recovery of China’s Economy in the First Quarter of 2023 H. Li & B. Zheng 10.1021/acs.estlett.3c00386
- Estimating anthropogenic CO2 emissions from China's Yangtze River Delta using OCO-2 observations and WRF-Chem simulations M. Sheng et al. 10.1016/j.rse.2024.114515
Latest update: 08 Dec 2024
Short summary
We developed an improved superposition column model and used the latest released (v2.3.1) TROPOMI satellite NO2 observations to estimate daily city-scale NOx and CO2 emissions. The results are verified against bottom-up emissions and OCO-2 XCO2 observations. We obtained the day-to-day variation of city NOx and CO2 emissions, allowing policymakers to gain real-time information on spatial–temporal emission patterns and the effectiveness of carbon and nitrogen regulation in urban environments.
We developed an improved superposition column model and used the latest released (v2.3.1)...
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