Publications

2026

• Fan, K., A. Bloom, and Z. Qu, Machine Learning Predictions of PM2.5 and Their Applications to Exposure and Health Assessment in the CONUS, GeoHealth., in press.

• Qu, Z., An activity-based inversion framework for estimating sectoral anthropogenic CO2 emissions using multi-pollutant satellite observations, Geophys. Res. Lett., 53, e2026GL122365, 2026.

• Bloom, A., Z. Qu, and Vatsavai, R. R., A Two-Stream CNN Framework for Spatiotemporally Resolved NO2 Estimates Using TEMPO and Sentinel-2 Satellite Data, Computational Science – ICCS 2026, 16784, 404–411, 2026.

• Worden, J., S. Pandey, H. Nesser, K. Bowman, C. Harkins, C. Lyu, J. D. Maasakkers, D. Gordon, D. Jacob, L. Estrada, D. J. Varon, J. D. East, L. Schmeisser, and Z. Qu, Top-down benchmark of U.S. methane inventories reveals regional discrepancies in activity-based estimates, Atmos. Chem. Phys., 26, 8855–8873, 2026.

• Kumm, J. and Z. Qu, Constraining NOx emissions with satellite NO2 data to improve modeling of 2023 wildfire air quality, Atmos. Environ., 375, 121985, 2026.

• Jones, D. B. A., Prates, L., Z. Qu, W. Y. Y. Cheng, K. Miyazaki, A. Inness, R. Kumar, X. Tang, H. Worden, G. Koren, and V. Huijnen, Assessment of regional and interannual variations in tropospheric ozone in chemical reanalyses, Atmos. Chem. Phys., 26, 6655-6682, 2026.

2025

• Wang, H., K. Miyazaki, H. Sun, Z. Qu, X. Liu, A. Inness, M. Schultz, S. Schroder, M. Serre, and J. J. West, Intercomparison of global ground-level ozone datasets for health relevant metrics, Atmos. Chem. Phys., 25, 15969-15990, 2025.

• Sekiya R., E. Emili, K. Miyazaki, A. Inness, Z. Qu, R. B. Pierce, D. Jones, H. Worden, W. Y. Y. Cheng, V. Huijnen, and G. Koren, Assessing the relative impacts of satellite ozone and its precursor observations on improving global tropospheric ozone analysis using multiple chemical reanalysis systems, Atmos. Chem. Phys., 25, 2243–2268, 2025.

• Penn E., D. J. Jacob, Z. Chen, J. D. East, M. P. Sulprizio, L. Bruhwiler, J. D. Maasakkers, H. Nesser, Z. Qu, Y. Zhang, and J. Worden, What can we learn about tropospheric OH from satellite observations of methane?, Atmos. Chem. Phys., 25, 2947–2965, 2025.

2024

• Qu Z., D. J. Jacob, A. Bloom, J. Worden, R. J. Parker, and H. Boesch, Inverse modeling of satellite observations shows that the wet tropics drive the 2010-2022 methane increase, Proc. Natl. Acad. Sci., 121 (40), e2402730121, 2024.

• Shindell D., P. Sadavarte, I. Aben, T. Bredariol, G. Dreyfus, L. Höglund-Isaksson, B. Poulter, M. Saunois, G. A. Schmidt, S. Szopa, K. Rentz, L. Parsons, Z. Qu, G. Faluvegi, and J. D. Maasakkers, The methane imperative, Front. Sci., 2, 1349770, 2024.

• Jones K.E.V., Z. Qu, K. R. Love, J. B. Daniels, M. R. Lappin, M. Henriksen, Particulate matter (PM2.5) from wildfire smoke in northern Colorado appears to be associated with conjunctivitis in dogs, J. Am. Vet. Med. Assoc., 2024.

• Nesser H., D. J. Jacob, J. D. Maasakkers, A. Lorente, Z. Chen, X. Lu, L. Shen, Z. Qu, M. P. Sulprizio, M. Winter, S. Ma, A. A. Bloom, J. R. Worden, R. N. Stavins, and C. A. Randles, High-resolution U.S. methane emissions inferred from an inversion of 2019 TROPOMI satellite data: contributions from individual states, urban areas, and landfills, Atmos. Chem. Phys., 24, 5069–5091, 2024.

• Mao Y.-H., Y. Shang, H. Liao, H. Cao, Z. Qu, D. K. Henze, Sensitivities of ozone to its precursors during heavy ozone pollution events in the Yangtze River Delta using the adjoint method, Sci. Total Environ., 925,171585, 2024.

2023

• Worden J. R., S. Pandey, Y. Zhang, D. Cusworth, Z. Qu, A. A. Bloom, S. Ma, J. D. Maasakkers, B. Byrne, R. Duren, D. Crisp, D. Gordon, and D. J. Jacob, Verifying methane inventories and trends with atmospheric methane data, AGU Adv., e2023AV000871, 2023 .

• Chen Z., D. J. Jacob, R. Gautam, M. Omara, R. N. Stavins, R. C. Stowe, H. Nesser, M. P. Sulprizio, A. Lorente, D. J. Varon, X. Lu, L. Shen, Z. Qu, D. C. Pendergrass, and S. Hancock, 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., 23, 5945–5967, 2023.

• Varon D. J., D. J. Jacob, B. Hmiel, R. Gautam, D. Lyon, M. Omara, M. Sulprizio, L. Shen, D. Pendergrass, H. Nesser, Z. Qu, Z. R. Barkley, N. L. Miles, S. J. Richardson, K. J. Davis, S. Pandey, X. Lu, A. Lorente, J. D. Maasakkers, and I. Aben, Continuous weekly monitoring of methane emissions from the Permian Basin by inversion of TROPOMI satellite observations, Atmos. Chem. Phys., 23, 7503–7520, 2023.

• Liang R., Y. Zhang, J. Liu, W. Chen, P. Zhang, C. Chen, H. Mao, G. Shen, Z. Qu, Z. Chen, M. Zhou, P. Wang, R. J. Parker, H. Boesch, A. Lorente, J. D. Maasakkers, and I. Aben, East Asian methane emissions inferred from high-resolution inversions of GOSAT and TROPOMI observations: a comparative and evaluative analysis, Atmos. Chem. Phys., 23, 8039-8057, 2023.

• Lu X., D. J. Jacob, Y. Zhang, L. Shen, M. P. Sulprizio, J. D. Maasakkers, D. J. Varon, Z. Qu, Z. Chen, B. Hmiel, R. J. Parker, H. Boesch, H. Wang, C. He, and S. Fan, Observation-derived 2010-2019 trends in methane emissions and intensities from US oil and gas fields tied to activity metrics, Proc. Natl. Acad. Sci., 120(17), e2217900120, doi:10.1073/pnas.2217900120, 2023.

2022

• 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, Environ. Res. Lett., 17, 094003, doi:10.1088/1748-9326/ac8754, 2022.

• Chen, Z., D. J. Jacob, H. Nesser, M. Sulprizio, A. Lorente, D. Varon, X. Lu, L. Shen, Z. 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.

• 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, Z. 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.

• 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, Z. 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.

• Varon D. J., D. J. Jacob, M. Sulprizio, L. A. Estrada, W. B. Downs, L. Shen, S. E. Hancock, H. Nesser, Z. 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.

• Balamurugan V., J. Chen, Z. Qu, X. Bi, and F. N. Keutsch, Secondary PM_2.5 decreases significantly less than NO₂ emission reductions during COVID lockdown in Germany, Atmos. Chem. Phys., 22, 7105-7129, doi:10.5194/acp-22-7105-2022, 2022.

• Worden J. R., D. H. Cusworth, Z. 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.

• Scarpelli, T. R., D. J. Jacob, S. Grossman, X. Lu, Z. 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-22-3235-2022, 2022.

• Qu, Z., D. K. Henze, H. Worden, Z. Jiang, B. Gaubert, N. Theys, and W. Wang, Sector-based top-down estimates of NO_x, SO₂, and CO emissions in East Asia, Geophys. Res. Lett., 49, e2021GL096009, doi: 10.1029/2021GL096009, 2022.

• Lu, X., D. J. Jacob, H. Wang, J. D. Maasakkers, Y. Zhang, T. R. Scarpelli, L. Shen, Z. 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.

2021

• Nawaz, M. O., D. K. Henze, S. Anenberg, D. Goldberg, D. Jo, B. Nault, J. Jimenez, H. Cao, C. Harkins, and Z. Qu, Impacts of sectoral, regional, species and day-specific emissions on air pollution and public health in Washington DC, Elementa, 9, 1, doi: 10.1525/elementa.2021.00043, 2021.

• 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, Atmos. Chem. Phys., 21, 14159-14175, doi:10.5194/acp-21-14159-2021, 2021.

• Cusworth, D. H., A. A. Bloom, S. Ma, C. E. Miller, K. Bowman, Y. Yin, J. D. Maasakkers, Y. Zhang, T. R. Scarpelli, Z. 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.

• Balamurugan V., J. Chen, Z. Qu, X. Bi, J. Gensheimer, A. Shekhar, S. Bhattacharjee, and F. N. Keutsch, Tropospheric NO₂ and O₃ response to COVID-19 lockdown restrictions at the national and urban scales in Germany, 126, e2021JD035440, J. Geophys. Res. – Atmos., doi:10.1029/2021JD035440, 2021.

• Campbell, P. C., D. Tong, Y. Tang, B. Baker, P. Lee, R. Saylor, A. Stein, S. Ma, L. Lamsal, and Z. Qu, Impacts of the COVID-19 economic slowdown on ozone pollution in the U.S., Atmos. Environ., 264, 118713, doi:10.1016/j.atmosenv.2021.118713, 2021.

• Qu, Z., D. J. Jacob, R. F. Silvern, V. Shah, P. C. Campbell, L. C. Valin, L. T. Murray, US COVID-19 shutdown shows the importance of background NO₂ in inferring nitrogen oxide (NO_x) emissions from satellite NO₂ observations, Geophys. Res. Lett., doi:10.1029/2021GL092783, 2021.

• Shen, L., D. Zavala-Araiza, R. Gautam, M. Omara, T. Scarpelli, J. Sheng, M. P. Sulprizio, J. Zhuang, Y. Zhang, Z. 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:10.1016/j.rse.2021.112461, 2021.

• Zhang, Y., D. J. Jacob, X. Lu, J. D. Maasakkers, T. R. Scarpelli, J. Sheng, L. Shen, Z. 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.

• Lu, X., D. J. Jacob, Y. Zhang, J. D. Maasakkers, M. P. Suprizio, L. Shen, Z. 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.

• Qu, Z., D. Wu, D. K. Henze, Y. Li, M. Sonenberg, and F. Mao, Transboundary transport of ozone pollution to a US border region: a case study of Yuma, Environ. Pollut., 273, 116421, doi:10.1016/j.envpol.2020.116421, 2021.

2020

• Qu, Z., D. K. Henze, O. R. Cooper, and J. L. Neu, Impacts of global NO_x inversion on NO₂ and ozone simulations, Atmos. Chem. Phys., 20, 13109-13130, doi:10.5194/acp-20-13109-2020, 2020.

• Elguindi, N., C. Granier, T. Stavrakou, S. Darras, M. Bauwens, H. Cao, C. Chen, H.A.C. Denier van der Gon, O. Dubovik, T. M. Fu, D. K. Henze, Z. Jiang, S. Keita, J. J. P. Kuenen, J. Kurokawa, C. Liousse, K. Miyazaki, J. F. Muller, Z. Qu, F. Solmon, and B. Zheng, Intercomparison of magnitudes and trends in anthropogenic surface emissions from bottom-up inventories, top-down estimates, and emission scenarios, Earths Future, doi:10.1029/2020EF001520, 2020.

• Wang, Y., J. Wang, X. Xu, D. K. Henze, Z. Qu, and K. Yang, Inverse modeling of SO₂ and NO_x emissions over China using multi-sensor satellite data – Part 1: Formulation and sensitivity analysis, Atmos. Chem. Phys., doi:10.5194/acp-20 6631-2020, 2020.

2019 and earlier

• Qu, Z., D. K. Henze, C. Li, N. Theys, Y. Wang, J. Wang, W. Wang, J. Han, C. Shim, R. R. Dickerson, and X. Ren, SO₂ emission estimates using OMI SO₂ retrievals for 2005-2017, J. Geophys. Res. – Atmos., 124, 8336–8359, doi:10.1029/2019JD030243, 2019.

• Qu, Z., D. K. Henze, N. Theys, J. Wang, and W. Wang, Hybrid mass balance / 4D-Var joint inversion of NO_x and SO₂ emissions in East Asia, J. Geophys. Res. – Atmos., 124, 8203–8224, doi: 10.1029/2018JD030240, 2019.

• Jiang, Z., B. C. McDonald, H. Worden, J. R. Worden, K. Miyazaki, Z. Qu, D. K. Henze, D. B. A. Jones, A. F. Arellano, E. V. Fischer, L. Zhu, and F. K. Boersma, Unexpected slowdown of US pollutant emission reduction in the past decade, Proc. Natl. Acad. Sci., 115(20), 5099-5104, doi:10.1073/pnas.1801191115, 2018.

• Qu, Z., D. K. Henze, S. L. Capps, Y. Wang, X. Xu, J. Wang, and M. Keller, Monthly top-down NO_x emissions for China (2005-2012): A hybrid inversion method and trend analysis, J. Geophys. Res. – Atmos., 122, 4600–4625, doi:10.1002/2016JD025852, 2017.

• Wang, Y., J. Wang, X. Xu, D. K. Henze, Y. Wang, and Z. Qu, A new approach for monthly updates of anthropogenic sulfur dioxide emissions from space: Application to China and implications for air quality forecasts, Geophys. Res. Lett., 43, 9931-9938 doi:10.1002/2016GL070204, 2016.