First Author Publications:
- Qu, Z., et al. (2022), Sector-based top-down estimates of NOx, SO2, and CO emissions in East Asia, Geophys. Res. Lett., 49, e2021GL096009, doi:10.1029/2021GL096009.
- Qu, Z., et al. (2022), Attribution of the 2020 surge in atmospheric methane by inverse analysis of GOSAT observations, Environ. Res. Lett., 17, 094003, doi:10.1088/1748-9326/ac8754.
- Qu, Z., et al. (2021), Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments, Atmos. Chem. Phys., 21, 14159-14175, doi:10.5194/acp-21-14159-2021.
Co-Authored Publications:
- Chen, Z., et al. (2023), Satellite quantification of methane emissions and oil–gas methane intensities from individual countries in the Middle East and North Africa: implications for climate action, Atmos. Chem. Phys., doi:10.5194/acp-23-5945-2023.
- Chen, Z., et al. (2023), Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations, Atmos. Chem. Phys., doi:10.5194/acp-22-10809-2022.
- Jacob, D. J., et al. (2023), Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane, Atmos. Chem. Phys., doi:10.5194/acp-22-9617-2022.
- Shen, L., et al. (2023), Satellite quantification of oil and natural gas methane emissions in the US and Canada including contributions from individual basins, Atmos. Chem. Phys., doi:10.5194/acp-22-11203-2022.
- Varon, D. J., et al. (2023), Continuous weekly monitoring of methane emissions from the Permian Basin by inversion of TROPOMI satellite observations, Atmos. Chem. Phys., doi:10.5194/acp-23-7503-2023.
- Varon, D. J., et al. (2023), 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., doi:10.5194/gmd-15-5787-2022.
- Worden, J., et al. (2023), California Institute of Technology and The Authors. Government sponsorship acknowledged. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided t, AGU Advances, 1, 16.
- Lu, X., et al. (2022), Methane emissions in the United States, Canada, and Mexico: evaluation of national methane emission inventories and 2010-2017 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.
- Scarpelli, T. R., et al. (2022), 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-22-3235-2022.
- Satellite, N. O., et al. (2021), US COVID-19 Shutdown Demonstrates Importance of Background NO2 in Inferring NOx Emissions From, Geophys. Res. Lett..
- Shen, L., et al. (2021), Unravelling a large methane emission discrepancy in Mexico using satellite observations, Remote Sensing of Environment, 260, 112461, doi:10.1016/j.rse.2021.112461.
- Zhang, Y., et al. (2021), 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-21-3643-2021.
- Wang, Y., et al. (2020), Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data - Part 1: Formulation and sensitivity analysis, Atmos. Chem. Phys., 20, 6631-6650, doi:10.5194/acp-20-6631-2020.
- Wang, Y., et al. (2020), Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data – Part 1: Formulation and sensitivity analysis, Atmos. Chem. Phys., 20, 6631-6650, doi:10.5194/acp-20-6631-2020.
- Jiang, Z., et al. (2018), Unexpected slowdown of US pollutant emission reduction in the past decade, Proc. Natl. Acad. Sci., 201801191, doi:10.1073/pnas.1801191115.
- Jiang, Z., et al. (2018), Unexpected slowdown of US pollutant emission reduction in the past decade, Proc. Natl. Acad. Sci., 115, 5099-5104, doi:10.1073/pnas.1801191115.
- Davis, A. B., et al. (2013), 3D radiative transfer effects in multi-angle/multispectral radio-polarimetric signals from a mixture of clouds and aerosols viewed by a non-imaging sensor, SPIE Proceedings, 8873, 887309, doi:10.1117/12.2023733.
Note: Only publications that have been uploaded to the
ESD Publications database are listed here.