Atmospheric Methane

We use statistical methods and satellite observations to analyze the factors driving recent trends of atmospheric methane concentrations. This method has been applied to analyze the regional methane emissions (e.g., North America, Mexico, China) and emissions from the oil and gas production regions. This approach significantly improves the accuracy of methane emission inventory and can further attribute methane sources from different activities and sectors. We also compared the atmospheric methane observations from different satellites to evaluate the robustness of using these observations in estimating emissions. These results provide important support for the Global Stocktake in support of the Paris Agreement by the United Nations Framework Convention on Climate Change.

Related Publications

 

  • Qu, Z., D. J. Jacob, Y. Zhang, L. Shen, D. J. Varon, X. Lu, T. Scarpelli, A. Bloom, J. Worden, and R. J. Parker, Attribution of the 2020 surge in atmospheric methane by inverse analysis of GOSAT observations, Res. Lett., 17, 094003, doi:10.1088/1748-9326/ac8754, 2022.

 

  • Qu, Z., D. J. Jacob, L. Shen, X. Lu, Y. Zhang, T. R. Scarpelli, H. O. Nesser, M. P. Sulprizio, J. D. Maasakers, A. A. Bloom, J. R. Worden, R. J. Parker and A. L. Delgado, Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments, Chem. Phys., 21, 14159-14175, doi:10.5194/acp-21-14159-2021, 2021. (21)

 

  • Chen, Z., D. J. Jacob, H. Nesser, M. Sulprizio, A. Lorente, D. Varon, X. Lu, L. Shen, Qu, E. Penn, and X. Yu, Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations, Atmos. Chem. Phys., 22, 10809-10826, doi:10.5194/acp-22-10809-2022, 2022. (2)

 

  • Shen, L., R. Gautam, M. Omara, D. Zavala-Araiza, J. D. Maasakkers, T. R. Scarpelli, A. L. Delgado, D. Lyon, J. Sheng, D. Varon, H. Nesser, Qu, X. Lu, M. P. Sulprizio, S. Hamburg, and D. J. Jacob, Satellite-based quantification of methane emissions from the oil and natural gas sector in the United States and Canada, doi:10.5194/acp-22-11203-2022, 2022. (3)

 

  • Varon D. J., D. J. Jacob, M. Sulprizio, L. A. Estrada, W. B. Downs, L. Shen, S. E. Hancock, H. Nesser, Qu, E. Penn, Z. Chen, X. Lu, A. Lorente, A. Tewari, and C. A. Randles, Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations, Geosci. Model. Dev., 15, 5787-5805, doi:10.5194/gmd-15-5787-2022, 2022. (2)

 

  • Jacob, D. J., D. J. Varon, D. H. Cusworth, P. E. Dennison, C. Frankenberg, R. Gautam, L. Guanter, J. Kelley, J. McKeever, L. E. Ott, B. Poulter, Qu, A. K. Thorpe, J. R. Worden, and R. M. Duren, Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane, Atmos. Chem. Phys., 22, 9617-9646, doi:10.5194/acp-22-9617-2022, 2022. (6)

 

  • Worden J. R., D. H. Cusworth, Qu, Y. Yin, Y. Zhang, A. A. Bloom, S. Ma, B. Byrne, T. Scarpelli, J. D. Maasakkers, D. Crisp, R. Duren, and D. J. Jacob, The 2019 methane budget and uncertainties at 1 degree resolution and each country through Bayesian integration of GOSAT total column methane data and a priori inventory estimates, Atmos. Chem. Phys., 22, 6811-6841, doi:10.5194/acp-22-6811-2022, 2022. (2)

 

  • Scarpelli, T. R., D. J. Jacob, S. Grossman, X. Lu, Qu, M. P. Sulprizio, Y. Zhang, F. Reuland, and D. Gordon, Updated Global Fuel Exploitation Inventory (GFEI) for methane emissions from the oil, gas, and coal sectors: evaluation with inversions of atmospheric methane observations, Atmos. Chem. Phys., 22, 3235-3249, doi:10.5194/acp-22-3235-3249, 2022. (5)

 

  • Lu, X., D. J. Jacob, H. Wang, J. D. Maasakkers, Y. Zhang, T. R. Scarpelli, L. Shen, Qu, M. P. Suprizio, H. Nesser, A. A. Bloom, S. Ma, J. R. Worden, S. Fan, R. J. Parker, H. Boesch, R. Gautam, D. Gordon, M. D. Moran, F. Reuland, and C. A. O. Villasana, Methane emissions in the United States, Canada, and Mexico: Evaluation of national methane emission inventories and sectoral trends by inverse analysis of in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) atmospheric observations, Atmos. Chem. Phys., 22, 395-418, doi:10.5194/acp-22-395-2022, 2022. (6)

 

  • Cusworth, D. H., A. A. Bloom, S. Ma, C. E. Miller, K. Bowman, Y. Yin, J. D. Maasakkers, Y. Zhang, T. R. Scarpelli, Qu, D. J. Jacob, and J. R. Worden, A Bayesian framework for deriving sector-based methane emissions from top-down fluxes, Commun. Earth Environ., 2, 242, doi: 10.1038/s43247-021-00312-6, 2021. (4)

 

  • Shen, L., D. Zavala-Araiza, R. Gautam, M. Omara, T. Scarpelli, J. Sheng, M. P. Sulprizio, J. Zhuang, Y. Zhang, Qu, X. Lu, S. Hamburg, and D. J. Jacob, Unravelling a large methane emission discrepancy in Mexico using satellite observations, Remote Sens. Environ., 260, 112461, doi:10.1061/j.rse.2021.112461, 2021. (23)

 

  • Zhang, Y., D. J. Jacob, X. Lu, J. D. Maasakkers, T. R. Scarpelli, J. Sheng, L. Shen, Qu, M. P. Sulprizio, J. Chang, A. A. Bloom, S. Ma, J. Worden, R. J. Parker, and H. Boesch, Attribution of the accelerating increase in atmospheric methane during 2010-2018 by inverse analysis of GOSAT observations, Atmos. Chem. Phys., 21, 3643-3666, doi:10.5194/acp-2020-964, 2021. (45)

 

  • Lu, X., D. J. Jacob, Y. Zhang, J. D. Maasakkers, M. P. Suprizio, L. Shen, Qu, T. R. Scarpelli, H. Nesser, R. M. Yantosca, J. Sheng, A. Andres, R. J. Parker, H. Boech, A. A. Bloom, and S. Ma, Global methane budget and trend, 2010-2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) observations, Atmos. Chem. Phys., 21, 4637-4657, doi:10.5194/acp-2020-775, 2021. (32)