Szopa, S. et al. in Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change Ch. 6 (eds Masson-Delmotte, V. et al.) 817–922 (Cambridge Univ. Press, 2023).
Saunois, M. et al. The global methane budget 2000–2017. Earth Syst. Sci. Data 12, 1561–1623 (2020).
Rigby, M. et al. Renewed growth of atmospheric methane. Geophys. Res. Lett. 35, L22805 (2008).
Zhang, Z. et al. Anthropogenic emission is the main contributor to the rise of atmospheric methane during 1993–2017. Natl Sci. Rev. 9, nwab200 (2021).
Qu, Z. et al. Inverse modeling of 2010–2022 satellite observations shows that inundation of the wet tropics drove the 2020–2022 methane surge. Proc. Natl Acad. Sci. 121, e2402730121 (2024).
Turner, A. J., Frankenberg, C. & Kort, E. A. Interpreting contemporary trends in atmospheric methane. Proc. Natl Acad. Sci. 116, 2805–2813 (2019).
Lelieveld, J., Gromov, S., Pozzer, A. & Taraborrelli, D. Global tropospheric hydroxyl distribution, budget and reactivity. Atmos. Chem. Phys. 16, 12477–12493 (2016).
Kuklinska, K., Wolska, L. & Namiesnik, J. Air quality policy in the U.S. and the EU – a review. Atmos. Pollut. Res. 6, 129–137 (2015).
Zhao, Y. et al. On the role of trend and variability in the hydroxyl radical (OH) in the global methane budget. Atmos. Chem. Phys. 20, 13011–13022 (2020).
Naik, V. et al. Preindustrial to present-day changes in tropospheric hydroxyl radical and methane lifetime from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Atmos. Chem. Phys. 13, 5277–5298 (2013).
Voulgarakis, A. et al. Analysis of present day and future OH and methane lifetime in the ACCMIP simulations. Atmos. Chem. Phys. 13, 2563–2587 (2013).
Turner, A. J., Fung, I., Naik, V., Horowitz, L. W. & Cohen, R. C. Modulation of hydroxyl variability by ENSO in the absence of external forcing. Proc. Natl Acad. Sci. 115, 8931–8936 (2018).
He, J., Naik, V. & Horowitz, L. W. Hydroxyl radical (OH) response to meteorological forcing and implication for the methane budget. Geophys. Res. Lett. 48, e2021GL094140 (2021).
Stevenson, D. S. et al. Trends in global tropospheric hydroxyl radical and methane lifetime since 1850 from AerChemMIP. Atmos. Chem. Phys. 20, 12905–12920 (2020).
Nicely, J. M. et al. A machine learning examination of hydroxyl radical differences among model simulations for CCMI-1. Atmos. Chem. Phys. 20, 1341–1361 (2020).
Duncan, B. N. et al. Opinion: Beyond global means – novel space-based approaches to indirectly constrain the concentrations of and trends and variations in the tropospheric hydroxyl radical (OH). Atmos. Chem. Phys. 24, 13001–13023 (2024).
Baublitz, C. B. et al. An observation-based, reduced-form model for oxidation in the remote marine troposphere. Proc. Natl Acad. Sci 120, e2209735120 (2023).
Shutter, J. D. et al. Interannual changes in atmospheric oxidation over forests determined from space. Sci. Adv. 10, eadn1115 (2024).
Zhu, Q., Fiore, A. M., Correa, G., Lamarque, J.-F. & Worden, H. The impact of internal climate variability on OH trends between 2005 and 2014. Environ. Res. Lett. 19, 064032 (2024).
Wolfe, G. M. et al. Mapping hydroxyl variability throughout the global remote troposphere via synthesis of airborne and satellite formaldehyde observations. Proc. Natl Acad. Sci. 116, 11171–11180 (2019).
Anderson, D. C. et al. Technical note: Constraining the hydroxyl (OH) radical in the tropics with satellite observations of its drivers – first steps toward assessing the feasibility of a global observation strategy. Atmos. Chem. Phys. 23, 6319–6338 (2023).
Anderson, D. C. et al. Trends and interannual variability of the hydroxyl radical in the remote tropics during boreal autumn inferred from satellite proxy data. Geophys. Res. Lett. 51, e2024GL108531 (2024).
Souri, A. H. et al. Enhancing long-term trend simulation of the global tropospheric hydroxyl (TOH) and its drivers from 2005 to 2019: a synergistic integration of model simulations and satellite observations. Atmos. Chem. Phys. 24, 8677–8701 (2024).
Pimlott, M. A. et al. Investigating the global OH radical distribution using steady-state approximations and satellite data. Atmos. Chem. Phys. 22, 10467–10488 (2022).
Nicely, J. M. et al. Changes in global tropospheric OH expected as a result of climate change over the last several decades. J. Geophys. Res. Atmos. 123, 10,774–710,795 (2018).
Rowlinson, M. J. et al. Impact of El Niño–Southern Oscillation on the interannual variability of methane and tropospheric ozone. Atmos. Chem. Phys. 19, 8669–8686 (2019).
Peng, S. et al. Wetland emission and atmospheric sink changes explain methane growth in 2020. Nature 612, 477–482 (2022).
Naus, S. et al. Constraints and biases in a tropospheric two-box model of OH. Atmos. Chem. Phys. 19, 407–424 (2019).
Patra, P. K. et al. Methyl chloroform continues to constrain the hydroxyl (OH) variability in the troposphere. J. Geophys. Res. Atmos. 126, e2020JD033862 (2021).
Thompson, R. L. et al. Estimation of the atmospheric hydroxyl radical oxidative capacity using multiple hydrofluorocarbons (HFCs). Atmos. Chem. Phys. 24, 1415–1427 (2024).
Zheng, B. et al. Rapid decline in carbon monoxide emissions and export from East Asia between years 2005 and 2016. Environ. Res. Lett. 13, 044007 (2018).
Zheng, B. et al. Global atmospheric carbon monoxide budget 2000–2017 inferred from multi-species atmospheric inversions. Earth Syst. Sci. Data 11, 1411–1436 (2019).
Wang, H. et al. Global tropospheric ozone trends, attributions, and radiative impacts in 1995–2017: an integrated analysis using aircraft (IAGOS) observations, ozonesonde, and multi-decadal chemical model simulations. Atmos. Chem. Phys. 22, 13753–13782 (2022).
Held, I. M. & Soden, B. J. Water vapor feedback and global warming. Annu. Rev. Energy Environ. 25, 441–475 (2000).
Crippa, M. et al. GHG emissions of all world countries. Publications Office of the European Union https://doi.org/10.2760/953322 (2023).
Hoesly, R. M. et al. Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS). Geosci. Model Dev. 11, 369–408 (2018).
Miyazaki, K. et al. Global tropospheric ozone responses to reduced NOx emissions linked to the COVID-19 worldwide lockdowns. Sci. Adv. 7, eabf7460 (2021).
Lan, X., Thoning, K. W. & Dlugokencky, E. J. Trends in globally-averaged CH4, N2O, and SF6 determined from NOAA Global Monitoring Laboratory measurements. Global Monitoring Laboratory https://doi.org/10.15138/P8XG-AA10 (2022).
Feng, L., Palmer, P. I., Parker, R. J., Lunt, M. F. & Bösch, H. Methane emissions are predominantly responsible for record-breaking atmospheric methane growth rates in 2020 and 2021. Atmos. Chem. Phys. 23, 4863–4880 (2023).
Qu, Z. et al. Attribution of the 2020 surge in atmospheric methane by inverse analysis of GOSAT observations. Environ. Res. Lett. 17, 094003 (2022).
Ziemke, J. R. et al. NASA satellite measurements show global-scale reductions in free tropospheric ozone in 2020 and again in 2021 during COVID-19. Geophys. Res. Lett. 49, e2022GL098712 (2022).
Zheng, B. et al. Record-high CO2 emissions from boreal fires in 2021. Science 379, 912–917 (2023).
Fischer, E. V. et al. Atmospheric peroxyacetyl nitrate (PAN): a global budget and source attribution. Atmos. Chem. Phys. 14, 2679–2698 (2014).
Knoblauch, C., Beer, C., Liebner, S., Grigoriev, M. N. & Pfeiffer, E.-M. Methane production as key to the greenhouse gas budget of thawing permafrost. Nat. Clim. Change 8, 309–312 (2018).
Unger, N., Zheng, Y., Yue, X. & Harper, K. L. Mitigation of ozone damage to the world’s land ecosystems by source sector. Nat. Clim. Change 10, 134–137 (2020).
Fleming, Z. et al. Tropospheric Ozone Assessment Report: present-day ozone distribution and trends relevant to human health. Elementa 6, 12 (2018).
Hou, X., Wild, O., Zhu, B. & Lee, J. Future tropospheric ozone budget and distribution over east Asia under a net-zero scenario. Atmos. Chem. Phys. 23, 15395–15411 (2023).
Zheng, B. et al. Increasing forest fire emissions despite the decline in global burned area. Sci. Adv. 7, eabh2646 (2021).
Hegglin, M. I. & Shepherd, T. G. Large climate-induced changes in ultraviolet index and stratosphere-to-troposphere ozone flux. Nat. Geosci. 2, 687–691 (2009).
Zhao, Y. et al. Reconciling the bottom-up and top-down estimates of the methane chemical sink using multiple observations. Atmos. Chem. Phys. 23, 789–807 (2023).
Frith, S. M. et al. Recent changes in total column ozone based on the SBUV Version 8.6 Merged Ozone Data Set. J. Geophys. Res. Atmos. 119, 9735–9751 (2014).
Ziemke, J. R. et al. Tropospheric ozone determined from Aura OMI and MLS: evaluation of measurements and comparison with the Global Modeling Initiative’s Chemical Transport Model. J. Geophys. Res. 111, D19303 (2006).
Boersma, K. F. et al. Improving algorithms and uncertainty estimates for satellite NO2 retrievals: results from the quality assurance for the essential climate variables (QA4ECV) project. Atmos. Meas. Tech. 11, 6651–6678 (2018).
Krotkov, N. A. et al. OMI/Aura NO2 Cloud-Screened Total and Tropospheric Column L3 Global Gridded 0.25 degree x 0.25 degree V3. NASA Goddard Space Flight Center, Goddard Earth Sciences Data and Information Services Center (GES DISC) https://doi.org/10.5067/Aura/OMI/DATA3007 (2019).
Inness, A. et al. The CAMS reanalysis of atmospheric composition. Atmos. Chem. Phys. 19, 3515–3556 (2019).
Agustí-Panareda, A. et al. Technical note: The CAMS greenhouse gas reanalysis from 2003 to 2020. Atmos. Chem. Phys. 23, 3829–3859 (2023).
Miyazaki, K. et al. Updated tropospheric chemistry reanalysis and emission estimates, TCR-2, for 2005–2018. Earth Syst. Sci. Data 12, 2223–2259 (2020).
Zhao, Y. et al. Influences of hydroxyl radicals (OH) on top-down estimates of the global and regional methane budgets. Atmos. Chem. Phys. 20, 9525–9546 (2020).
Gelaro, R. et al. The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). J. Clim. 30, 5419–5454 (2017).
Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).
Geddes, J. A., Martin, R. V., Boys, B. L. & Donkelaar, A. V. Long-term trends worldwide in ambient NO2 concentrations inferred from satellite observations. Environ. Health Perspect. 124, 281–289 (2016).
Anderson, D. C. et al. Spatial and temporal variability in the hydroxyl (OH) radical: understanding the role of large-scale climate features and their influence on OH through its dynamical and photochemical drivers. Atmos. Chem. Phys. 21, 6481–6508 (2021).
Shah, V. et al. Nitrogen oxides in the free troposphere: implications for tropospheric oxidants and the interpretation of satellite NO2 measurements. Atmos. Chem. Phys. 23, 1227–1257 (2023).
Morgenstern, O. et al. Review of the global models used within phase 1 of the Chemistry–Climate Model Initiative (CCMI). Geosci. Model Dev. 10, 639–671 (2017).
Tilmes, S. et al. Representation of the Community Earth System Model (CESM1) CAM4-chem within the Chemistry-Climate Model Initiative (CCMI). Geosci. Model Dev. 9, 1853–1890 (2016).
Molod, A., Takacs, L., Suarez, M. & Bacmeister, J. Development of the GEOS-5 atmospheric general circulation model: evolution from MERRA to MERRA2. Geosci. Model Dev. 8, 1339–1356 (2015).
Oman, L. D. et al. The ozone response to ENSO in Aura satellite measurements and a chemistry-climate simulation. J. Geophys. Res. Atmos. 118, 965–976 (2013).
Nielsen, J. E. et al. Chemical mechanisms and their applications in the Goddard Earth Observing System (GEOS) earth system model. J. Adv. Model. Earth Syst. 9, 3019–3044 (2017).
Granier, C. et al. Evolution of anthropogenic and biomass burning emissions of air pollutants at global and regional scales during the 1980–2010 period. Clim. Change 109, 163 (2011).
Duncan, B. N., Strahan, S. E., Yoshida, Y., Steenrod, S. D. & Livesey, N. Model study of the cross-tropopause transport of biomass burning pollution. Atmos. Chem. Phys. 7, 3713–3736 (2007).
Horowitz, L. W., Liang, J., Gardner, G. M. & Jacob, D. J. Export of reactive nitrogen from North America during summertime: sensitivity to hydrocarbon chemistry. J. Geophys. Res. Atmos. 103, 13451–13476 (1998).
Zhao, Y. et al. Inter-model comparison of global hydroxyl radical (OH) distributions and their impact on atmospheric methane over the 2000–2016 period. Atmos. Chem. Phys. 19, 13701–13723 (2019).
Emmerson, K. M. & Evans, M. J. Comparison of tropospheric gas-phase chemistry schemes for use within global models. Atmos. Chem. Phys. 9, 1831–1845 (2009).
Sander, S. P. et al. Chemical kinetics and photochemical data for use in atmospheric studies, evaluation number 17. JPL publication (NASA, 2011).
Zhang, Z. et al. Enhanced response of global wetland methane emissions to the 2015–2016 El Niño-Southern Oscillation event. Environ. Res. Lett. 13, 074009 (2018).
Wells, K. C. et al. Satellite isoprene retrievals constrain emissions and atmospheric oxidation. Nature 585, 225–233 (2020).
Wells, K. C. et al. Next-generation isoprene measurements from space: detecting daily variability at high resolution. J. Geophys. Res. Atmos. 127, e2021JD036181 (2022).
