Zhen Qu

Assessing the relative impacts of satellite ozone and its precursor observations to improve global tropospheric ozone analysis using multiple chemical reanalysis systems

ATMOSPHERIC CHEMISTRY AND PHYSICS, 25(4), 2243–2268.

High-resolution US methane emissions inferred from an inversion of 2019 TROPOMI satellite data: contributions from individual states, urban areas, and landfills

ATMOSPHERIC CHEMISTRY AND PHYSICS, 24(8), 5069–5091.

Inverse modeling of 2010-2022 satellite observations shows that inundation of the wet tropics drove the 2020-2022 methane surge

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 121(40).

Particulate matter from wildfire smoke in northern Colorado appears to be associated with conjunctivitis in dogs

JAVMA-JOURNAL OF THE AMERICAN VETERINARY MEDICAL ASSOCIATION, 262, S40–S46.

East Asian methane emissions inferred from high-resolution inversions of GOSAT and TROPOMI observations: a comparative and evaluative analysis

ATMOSPHERIC CHEMISTRY AND PHYSICS, 23(14), 8039–8057.

Observation-derived 2010-2019 trends in methane emissions and intensities from US oil and fields tied to metrics

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 120(17).

Attribution of the 2020 surge in atmospheric methane by inverse analysis of GOSAT observations

Environmental Research Letters, 17(9), 094003.

Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations

Geoscientific Model Development, 15(14), 5787–5805.

Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations

Atmospheric Chemistry and Physics, 22(16), 10809–10826.

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 CH<sub>4</sub> ObsPack) and satellite (GOSAT) atmospheric observations

Atmospheric Chemistry and Physics, 22(1), 395–418.

Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane

Atmospheric Chemistry and Physics, 22(14), 9617–9646.

Satellite quantification of oil and natural gas methane emissions in the US and Canada including contributions from individual basins

Atmospheric Chemistry and Physics, 22(17), 11203–11215.

Secondary PM2.5 decreases significantly less than NO2 emission reductions during COVID lockdown in Germany

Atmospheric Chemistry and Physics, 22(11), 7105–7129.

Sector‐Based Top‐Down Estimates of NOx, SO2, and CO Emissions in East Asia

Geophysical Research Letters, 49(2).

The 2019 methane budget and uncertainties at 1° resolution and each country through Bayesian integration Of GOSAT total column methane data and a priori inventory estimates

Atmospheric Chemistry and Physics, 22(10), 6811–6841.

Updated Global Fuel Exploitation Inventory (GFEI) for methane emissions from the oil, gas, and coal sectors: evaluation with inversions of atmospheric methane observations

Atmospheric Chemistry and Physics, 22(5), 3235–3249.

A Bayesian framework for deriving sector-based methane emissions from top-down fluxes

Communications Earth &Amp; Environment, 2(1).

Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments

Atmospheric Chemistry and Physics, 21(18), 14159–14175.

Impacts of sectoral, regional, species, and day-specific emissions on air pollution and public health in Washington, DC

Elementa: Science of the Anthropocene, 9(1).

Impacts of the COVID-19 economic slowdown on ozone pollution in the U.S.

Atmospheric Environment, 264, 118713.

Transboundary transport of ozone pollution to a US border region: A case study of Yuma

Environmental Pollution, 273, 116421.

Tropospheric NO2 and O3 Response to COVID‐19 Lockdown Restrictions at the National and Urban Scales in Germany

Journal of Geophysical Research: Atmospheres, 126(19).

US COVID‐19 Shutdown Demonstrates Importance of Background NO2 in Inferring NOx Emissions From Satellite NO2 Observations

Geophysical Research Letters, 48(10).

Unravelling a large methane emission discrepancy in Mexico using satellite observations

Remote Sensing of Environment, 260, 112461.

Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations

Zhang, Y., Jacob, D. J., Lu, X., Maasakkers, J., Scarpelli, T. R., Sheng, J., … Boesch, H. (2020, September 25). (Vol. 9). Vol. 9.

Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) observations

Lu, X., Jacob, D. J., Zhang, Y., Maasakkers, J., Sulprizio, M. P., Shen, L., … Ma, S. (2020, September 17). (Vol. 9). Vol. 9.

Impacts of global NOx inversions on NO2 and ozone simulations

Atmospheric Chemistry and Physics, 20(21), 13109–13130.

Intercomparison of Magnitudes and Trends in Anthropogenic Surface Emissions From Bottom‐Up Inventories, Top‐Down Estimates, and Emission Scenarios

Earth's Future, 8(8).

Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data – Part 1: Formulation and sensitivity analysis

Atmospheric Chemistry and Physics, 20(11), 6631–6650.

Hybrid Mass Balance/4D‐Var Joint Inversion of NOx and SO2 Emissions in East Asia

Journal of Geophysical Research: Atmospheres, 124(14), 8203–8224.

SO2 Emission Estimates Using OMI SO2 Retrievals for 2005–2017

Journal of Geophysical Research: Atmospheres, 124(14), 8336–8359.

Unexpected slowdown of US pollutant emission reduction in the past decade

Proceedings of the National Academy of Sciences, 115(20), 5099–5104.

Monthly top‐down NOx emissions for China (2005–2012): A hybrid inversion method and trend analysis

Journal of Geophysical Research: Atmospheres, 122(8), 4600–4625.

A new approach for monthly updates of anthropogenic sulfur dioxide emissions from space: Application to China and implications for air quality forecasts

Geophysical Research Letters, 43(18), 9931–9938.