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Fossil fuel CO₂ emissions over metropolitan areas from space: A multi-model analysis of OCO-2 data over Lahore, Pakistan

Lei, Ruixue and Feng, Sha and Danjou, Alexandre and Broquet, Grégoire and Wu, Dien and Lin, John C. and O'Dell, Christopher W. and Lauvaux, Thomas (2021) Fossil fuel CO₂ emissions over metropolitan areas from space: A multi-model analysis of OCO-2 data over Lahore, Pakistan. Remote Sensing of Environment, 264 . Art. No. 112625. ISSN 0034-4257. doi:10.1016/j.rse.2021.112625.

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Urban areas, where more than 55% of the global population gathers, contribute more than 70% of anthropogenic fossil fuel carbon dioxide (CO_(2ff)) emissions. Accurate quantification of CO_(2ff) emissions from urban areas is of great importance for formulating global warming mitigation policies to achieve carbon neutrality by 2050. Satellite-based inversion techniques are unique among “top-down” approaches, potentially allowing us to track CO_(2ff) emission changes over cities globally. However, their accuracy is still limited by incomplete background information, cloud blockages, aerosol contamination, and uncertainties in models and priori emission inventories. To evaluate the current potential of space-based quantification techniques, we present the first attempt to monitor long-term changes in CO_(2ff) emissions based on the OCO-2 satellite measurements of column-averaged dry-air mole fractions of CO₂ (X_(CO₂)) over a fast-growing Asian metropolitan area: Lahore, Pakistan. We first examined the OCO-2 data availability at global scale. About 17% of OCO-2 soundings over the global 70 most populated cities from 2014 to 2019 are marked as high-quality. Cloud blockage and aerosol contamination are the two main causes of data loss. As an attempt to recover additional soundings, we evaluated the effectiveness of OCO-2 quality flags at the city level by comparing three flux quantification methods (WRF-Chem, X-STILT, and the flux cross-sectional integration method). The satellite/bottom-up emissions (OCO-2/ODIAC) ratios of the high-quality tracks with reduced uncertainties in emissions are better agreed across the three methods compared to the all-data tracks. This demonstrates that OCO-2 quality flags are useful filters of low-quality OCO-2 retrievals at local scales. All three methods consistently suggested that the ratio medians are greater than 1, implying that the ODIAC slightly underestimated CO_(2ff) emissions over Lahore. Additionally, our estimation of the a posteriori CO2ff emission trend was about 734 kt C/year (i.e., an annual 6.7% increase). 10,000 Monte Carlo simulations of the Mann-Kendall upward trend test showed that less than 10% prior uncertainty for 8 tracks (or less than 20% prior uncertainty for 25 tracks) is required to achieve a greater-than-50% trend significant possibility at a 95% confidence level. It implies that the trend is driven by the prior and not due to the assimilation of OCO-2 retrievals. The key to improving the role of satellite data in CO₂ emission trend detection lies in collecting more frequent high-quality tracks near metropolitan areas to achieve significant constraints from X_(CO₂) retrievals.

Item Type:Article
Related URLs:
URLURL TypeDescription ItemNCAR Upper Air Database ItemNCEP ADP Global Surface Observational Weather Data ItemCO2ff emission from ODIAC ItemTIMES temporal scaling factors ItemMsTMIP Biogenic CO2 Fluxes ItemOCO2_L2_Lite_FP ItemERA5 climate reanalysis ItemGDAS0p5
Lei, Ruixue0000-0001-6226-7075
Feng, Sha0000-0002-2376-0868
Wu, Dien0000-0002-2915-5335
Lin, John C.0000-0003-2794-184X
O'Dell, Christopher W.0000-0002-0271-8433
Lauvaux, Thomas0000-0002-7697-742X
Alternate Title:Fossil fuel CO2 emissions over metropolitan areas from space: A multi-model analysis of OCO-2 data over Lahore, Pakistan
Additional Information:© 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license ( Received 29 January 2021, Revised 25 June 2021, Accepted 26 July 2021, Available online 10 August 2021. R. Lei and S. Feng have been funded jointly by the NASA grants #80NSSC18K1313 (subcontracted from the Universities Space Research Association #05783-01 to Penn State) and #80NSSC19k0093. S. Feng is also supported by NASA grant #80HQTR21T0070 at Pacific Northwest National Laboratory (PNNL). PNNL is operated for DOE by Battelle Memorial Institute under contract DE-AC06-76RLO 1830. T. Lauvaux has been supported by the French research program Make Our Planet Great Again (project CIUDAD). A. Danjou has been supported by the PhD fellowship program of Commissariat à l'Energie Atomique et aux Energies Alternatives. G. Broquet has been supported by the French National Space Agency (CNES) as part of the TOSCA program (OCO-3 City project). D. Wu and J. Lin have been funded by the NASA grants #80NSSC19K0196. C. O'Dell was funded by a subcontract with the NASA Jet Propulsion Laboratory. Computing resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center. We thank Albert Y. Chang at the California Institute of Technology for explaining the quality flags in OCO-2 L2Sel files. We also thank Annmarie Eldering and Robert Nelson at NASA Jet Propulsion Laboratory (JPL) for their assistance in explaining the quality flags in OCO-2 L2 v9r lite files. The authors acknowledge the support of Beth Mundy (PNNL) in editing this manuscript. Data availability. The following data in this study is available from public sources: NCAR Upper Air Database: NCEP ADP Global Surface Observational Weather Data: CO2ff emission from ODIAC: TIMES temporal scaling factors: MsTMIP Biogenic CO2 Fluxes: OCO2_L2_Lite_FP: ERA5 climate reanalysis: GDAS0p5: All analysis code will be made available on request. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Funding AgencyGrant Number
Universities Space Research Association05783-01
Department of Energy (DOE)DE-AC06-76RLO 1830
Commissariat a l'Energie Atomique (CEA)UNSPECIFIED
Centre National d'Études Spatiales (CNES)UNSPECIFIED
Subject Keywords:GHGs; Quality flags; WRF-Chem; X-STILT; Flux cross-sectional integration; Bayesian inversion; ODIAC
Record Number:CaltechAUTHORS:20210908-225042542
Persistent URL:
Official Citation:Ruixue Lei, Sha Feng, Alexandre Danjou, Grégoire Broquet, Dien Wu, John C. Lin, Christopher W. O'Dell, Thomas Lauvaux, Fossil fuel CO2 emissions over metropolitan areas from space: A multi-model analysis of OCO-2 data over Lahore, Pakistan, Remote Sensing of Environment, Volume 264, 2021, 112625, ISSN 0034-4257,
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:110788
Deposited By: George Porter
Deposited On:09 Sep 2021 17:48
Last Modified:09 Sep 2021 17:48

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