Articles | Volume 22, issue 22
https://doi.org/10.5194/acp-22-14547-2022
© 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-22-14547-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Nov 2022
Research article |
| 16 Nov 2022
| 16 Nov 2022
Towards sector-based attribution using intra-city variations in satellite-based emission ratios between CO2 and CO
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, USA
Junjie Liu
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, USA
Paul O. Wennberg
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, USA
Division of Engineering and Applied Science, California Institute of Technology, Pasadena, USA
Paul I. Palmer
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA
School of GeoSciences, University of Edinburgh, Edinburgh, UK
Robert R. Nelson
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA
Matthäus Kiel
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA
Annmarie Eldering
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA
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Cited
14 citations as recorded by crossref.
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- Seasonal and Diurnal Variations in XCO2 Characteristics in China as Observed by OCO‐2/3 Satellites: Effects of Land Cover and Local Meteorology H. Zhao et al. 10.1029/2023JD038841
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- A simplified non-linear chemistry transport model for analyzing NO2 column observations: STILT–NOx D. Wu et al. 10.5194/gmd-16-6161-2023
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- Towards a sector-specific CO∕CO2 emission ratio: satellite-based observations of CO release from steel production in Germany O. Schneising et al. 10.5194/acp-24-7609-2024
- Revealing the Covariation of Atmospheric O2 and Pollutants in an Industrial Metropolis by Explainable Machine Learning X. Liu et al. 10.1021/acs.estlett.3c00505
- Analysis of the carbon emission driving factors and prediction of a carbon peak scenario——A case study of Xi'an city Y. Zhang et al. 10.1016/j.heliyon.2022.e11753
- Theoretical assessment of the ability of the MicroCarb satellite city-scan observing mode to estimate urban CO2 emissions K. Wu et al. 10.5194/amt-16-581-2023
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- Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5) I. Super et al. 10.5194/gmd-17-7263-2024
- Role of space station instruments for improving tropical carbon flux estimates using atmospheric data P. Palmer et al. 10.1038/s41526-022-00231-6
13 citations as recorded by crossref.
- Observed decade-long improvement of combustion efficiency in the Yangtze River Delta region in China J. Zhao et al. 10.1088/1748-9326/ad521e
- Evaluating the consistency between OCO-2 and OCO-3 XCO2 estimates derived from the NASA ACOS version 10 retrieval algorithm T. Taylor et al. 10.5194/amt-16-3173-2023
- Seasonal and Diurnal Variations in XCO2 Characteristics in China as Observed by OCO‐2/3 Satellites: Effects of Land Cover and Local Meteorology H. Zhao et al. 10.1029/2023JD038841
- Dual-comb spectroscopy over a 100 km open-air path J. Han et al. 10.1038/s41566-024-01525-9
- A simplified non-linear chemistry transport model for analyzing NO2 column observations: STILT–NOx D. Wu et al. 10.5194/gmd-16-6161-2023
- Quantification of carbon monoxide emissions from African cities using TROPOMI G. Leguijt et al. 10.5194/acp-23-8899-2023
- Estimating enhancement ratios of nitrogen dioxide, carbon monoxide and carbon dioxide using satellite observations C. MacDonald et al. 10.5194/acp-23-3493-2023
- Towards a sector-specific CO∕CO2 emission ratio: satellite-based observations of CO release from steel production in Germany O. Schneising et al. 10.5194/acp-24-7609-2024
- Revealing the Covariation of Atmospheric O2 and Pollutants in an Industrial Metropolis by Explainable Machine Learning X. Liu et al. 10.1021/acs.estlett.3c00505
- Analysis of the carbon emission driving factors and prediction of a carbon peak scenario——A case study of Xi'an city Y. Zhang et al. 10.1016/j.heliyon.2022.e11753
- Theoretical assessment of the ability of the MicroCarb satellite city-scan observing mode to estimate urban CO2 emissions K. Wu et al. 10.5194/amt-16-581-2023
- “Urban Respiration” Revealed by Atmospheric O2 Measurements in an Industrial Metropolis X. Liu et al. 10.1021/acs.est.2c07583
- Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5) I. Super et al. 10.5194/gmd-17-7263-2024
1 citations as recorded by crossref.
Latest update: 23 Nov 2024
Short summary
Prior studies have derived the combustion efficiency for a region/city using observed CO2 and CO. We further zoomed into the urban domain and accounted for factors affecting the calculation of spatially resolved combustion efficiency from two satellites. The intra-city variability in combustion efficiency was linked to heavy industry within Shanghai and LA without relying on emission inventories. Such an approach can be applied when analyzing data from future geostationary satellites.
Prior studies have derived the combustion efficiency for a region/city using observed CO2 and...
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