Mitigation of ozone damage to the world’s land ecosystems by source sector


Surface ozone damages photosynthesis and reduces the ability of land ecosystems to assimilate carbon from the atmosphere thereby further increasing global warming1,2. Ozone is not emitted directly but formed in the atmosphere during complex chemical reactions of precursors, carbon monoxide, methane, non-methane volatile organic compounds and nitrogen oxides, in sunlight. These ozone precursors are emitted from a wide range of anthropogenic activities. Reductions in ozone precursor emissions are needed to mitigate ozone vegetation damage but it is unclear which are the most effective source sectors to target. Here, we apply a global Earth system model to compare the benefits to gross primary productivity of stringent 50% emission reductions in the seven largest anthropogenic ozone source sectors. Deep cuts in air pollutant emissions from road transportation and the energy sector are the most effective mitigation measures for ozone-induced gross primary productivity losses in Eastern China, Eastern United States, Europe and globally. Our results suggest that mitigation of ozone vegetation damage is a unique opportunity to contribute to negative carbon emissions, offering a natural climate solution that links fossil fuel emission abatement, air quality and climate. However, achieving these benefits requires ambitious mitigation pathways that tackle multiple source sectors.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Annual average GPP losses due to O3 damage.
Fig. 2: Annual average surface O3 concentration decreases in ppbv due to 50% source sector emission reduction relative to CTRL.
Fig. 3: Annual average GPP increases due to 50% source sector emission reduction relative to CTRL.

Data availability

Model output data relating to this study not presented in the manuscript are available from the corresponding author on request.

Code availability

The YIBs model was developed by X.Y. and N.U. and is available at The source code for the frozen CMIP5/AR5 version of the GISS ModelE2 can be obtained from NASA GISS (


  1. 1.

    Sitch, S., Cox, P. M., Collins, W. J. & Huntingford, C. Indirect radiative forcing of climate change through ozone effects on the land-carbon sink. Nature 448, 791–794 (2007).

    CAS  Article  Google Scholar 

  2. 2.

    Ainsworth, E. A., Yendrek, C. R., Sitch, S., Collins, W. J. & Emberson, L. D. The effects of tropospheric ozone on net primary productivity and implications for climate change. Annu. Rev. Plant Biol. 63, 637–661 (2012).

    CAS  Article  Google Scholar 

  3. 3.

    Oliver, R. J. et al. Large but decreasing effect of ozone on the European carbon sink. Biogeosciences 15, 4245–4269 (2018).

    CAS  Article  Google Scholar 

  4. 4.

    Le Quéré, C. et al. Global carbon budget 2018. Earth Syst. Sci. Data 10, 2141–2194 (2018).

    Article  Google Scholar 

  5. 5.

    Lombardozzi, D., Levis, S., Bonan, G., Hess, P. G. & Sparks, J. P. The influence of chronic ozone exposure on global carbon and water cycles. J. Clim. 28, 292–305 (2015).

    Article  Google Scholar 

  6. 6.

    Yue, X. & Unger, N. Ozone vegetation damage effects on gross primary productivity in the United States. Atmos. Chem. Phys. 14, 9137–9153 (2014).

    Article  Google Scholar 

  7. 7.

    Yue, X. et al. Ozone and haze pollution weakens net primary productivity in China. Atmos. Chem. Phys. 17, 6073–6089 (2017).

  8. 8.

    Chang, K.-L., Petropavlovskikh, I., Copper, O. R., Schultz, M. G. & Wang, T. Regional trend analysis of surface ozone observations from monitoring networks in eastern North America, Europe and East Asia. Elem. Sci. Anth. 5, 50 (2017).

    Article  Google Scholar 

  9. 9.

    Lu, X. et al. Severe surface ozone pollution in China: a global perspective. Environ. Sci. Technol. Lett. 5, 487–494 (2018).

    CAS  Article  Google Scholar 

  10. 10.

    Jiang, F. et al. A comprehensive estimate of recent carbon sinks in China using both top-down and bottom-up approaches. Sci. Rep. 6, 22130 (2016).

    CAS  Article  Google Scholar 

  11. 11.

    King, A. W. et al. North America’s net terrestrial CO2 exchange with the atmosphere 1990–2009. Biogeosciences 12, 399–414 (2015).

    CAS  Article  Google Scholar 

  12. 12.

    Yue, X. & Unger, N. Fire air pollution reduces global terrestrial productivity. Nat. Commun. 9, 5413 (2018).

    CAS  Article  Google Scholar 

  13. 13.

    Rogelj, J. et al. in Special Report on Global Warming of 1.5°C (eds Masson-Delmotte, V. et al.) Ch. 2 (IPCC, WMO, 2018).

  14. 14.

    Rao, S. et al. Future air pollution in the Shared Socio-economic Pathways. Glob. Environ. Change 42, 346–358 (2017).

    Article  Google Scholar 

  15. 15.

    Simon, H., Reff, A., Wells, B., Xing, J. & Frank, N. Ozone trends across the United States over a period of decreasing NOx and VOC emissions. Environ. Sci. Technol. 49, 186–195 (2015).

    CAS  Article  Google Scholar 

  16. 16.

    Yue, X. & Unger, N. The Yale Interactive terrestrial Biosphere model version 1.0: description, evaluation and implementation into NASA GISS ModelE2. Geosci. Model Dev. 8, 2399–2417 (2015).

    CAS  Article  Google Scholar 

  17. 17.

    Rogelj, J. et al. Scenarios towards limiting global mean temperature increase below 1.5 °C. Nat. Clim. Change 8, 325–332 (2018).

    CAS  Article  Google Scholar 

  18. 18.

    Turnock, S. T., Wild, O., Sellar, A. & O’Connor, F. M. 300 years of tropospheric ozone changes using CMIP6 scenarios with a parameterised approach. Atmos. Environ. 213, 686–698 (2019).

    CAS  Article  Google Scholar 

  19. 19.

    Fiore, A. M. et al. Global air quality and climate. Chem. Soc. Rev. 41, 6663–6683 (2012).

  20. 20.

    Fiore, A. M., West, J. J., Horowitz, L. W., Naik, V. & Schwarzkopf, M. D. Characterizing the tropospheric ozone response to methane emission controls and the benefits to climate and air quality. J. Geophys. Res. 113, D08307 (2008).

    Article  Google Scholar 

  21. 21.

    Felzer, B. S., Cronin, T., Reilly, J. M., Melillo, J. M. & Wang, X. Impacts of ozone on trees and crops. Comptes Rendus Geosci. 339, 784–798 (2007).

    CAS  Article  Google Scholar 

  22. 22.

    Mills, G. et al. Ozone impacts on vegetation in a nitrogen enriched and changing climate. Environ. Pollut. 208, 898–908 (2016).

    CAS  Article  Google Scholar 

  23. 23.

    Sitch, S. et al. Recent trends and drivers of regional sources and sinks of carbon dioxide. Biogeosciences 12, 653–679 (2015).

    CAS  Article  Google Scholar 

  24. 24.

    Dinerstein, E. et al. A global deal for nature: guiding principles, milestones, and targets. Sci. Adv. 5, eaaw2869 (2019).

  25. 25.

    Griscom, B. W. et al. Natural climate solutions. Proc. Natl Acad. Sci. USA 114, 11645–11650 (2017).

    CAS  Article  Google Scholar 

  26. 26.

    Schmidt, G. A. et al. Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive. J. Adv. Model. Earth Syst. 6, 141–184 (2014).

    Article  Google Scholar 

  27. 27.

    Unger, N., Yue, X. & Harper, K. L. Aerosol climate change effects on land ecosystem services. Faraday Discuss. 200, 121–142 (2017).

    CAS  Article  Google Scholar 

  28. 28.

    Harper, K. L., Zheng, Y. & Unger, N. Advances in representing interactive methane in ModelE2-YIBs (version 1.1). Geosci. Model Dev. 11, 4417–4434 (2018).

    CAS  Article  Google Scholar 

  29. 29.

    Stohl, A. et al. Evaluating the climate and air quality impacts of short-lived pollutants. Atmos. Chem. Phys. 15, 10529–10566 (2015).

    CAS  Article  Google Scholar 

  30. 30.

    Klimont, Z. et al. Global anthropogenic emissions of particulate matter including black carbon. Atmos. Chem. Phys. 17, 8681–8723 (2017).

    CAS  Article  Google Scholar 

  31. 31.

    Yue, X. & Unger, N. Aerosol optical depth thresholds as a tool to assess diffuse radiation fertilization of the land carbon uptake in China. Atmos. Chem. Phys. 17, 1329–1342 (2017).

  32. 32.

    Mercado, L. M. et al. Impact of changes in diffuse radiation on the global land carbon sink. Nature 458, 1014–1017 (2009).

    CAS  Article  Google Scholar 

  33. 33.

    Saari, R. K., Mei, Y., Monier, E. & Garcia-Menendez, F. Effect of health-related uncertainty and natural variability on health impacts and cobenefits of climate policy. Environ. Sci. Technol. 53, 1098–1108 (2019).

    CAS  Article  Google Scholar 

  34. 34.

    Anav, A. et al. Spatiotemporal patterns of terrestrial gross primary production: a review. Rev. Geophys. 53, 785–818 (2015).

    Article  Google Scholar 

  35. 35.

    Jung, M. et al. Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations. J. Geophys. Res. 116, G00J07 (2011).

    Article  Google Scholar 

  36. 36.

    Yue, X., Unger, N. & Zheng, Y. Distinguishing the drivers of trends in land carbon fluxes and plant volatile emissions over the past 3 decades. Atmos. Chem. Phys. 15, 11931–11948 (2015).

    CAS  Article  Google Scholar 

  37. 37.

    Shindell, D. T. et al. Interactive ozone and methane chemistry in GISS-E2 historical and future climate simulations. Atmos. Chem. Phys. 13, 2653–2689 (2013).

    Article  Google Scholar 

  38. 38.

    Stevenson, D. S. et al. Tropospheric ozone changes, radiative forcing and attribution to emissions in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Atmos. Chem. Phys. 13, 3063–3085 (2013).

    Article  Google Scholar 

  39. 39.

    Bowman, K. W. et al. Evaluation of ACCMIP outgoing longwave radiation from tropospheric ozone using TES satellite observations. Atmos. Chem. Phys. 13, 4057–4072 (2013).

    CAS  Article  Google Scholar 

  40. 40.

    Sofen, E. D. et al. Gridded global surface ozone metrics for atmospheric chemistry model evaluation. Earth Syst. Sci. Data 8, 41–59 (2016).

    Article  Google Scholar 

Download references


N.U. acknowledges funding support from the University of Exeter. X.Y. acknowledges funding support from the National Natural Science Foundation of China (grant no. 41975155) and the National Key Research and Development Program of China (grant no. SQ2019YFA060013). This project was supported by the ISCA High Performance Computing facility at the University of Exeter. The authors thank K.J. van Groenigen and S. Sitch for helpful discussions.

Author information




N.U. conceived the project. N.U. and Y.Z. designed the research. Y.Z. performed the simulations. X.Y. calibrated, validated and evaluated the land carbon fluxes and O3 vegetation damage in YIBs. K.L.H. developed and evaluated the dynamic CH4 simulation. N.U. and Y.Z. analysed model output. N.U. wrote the paper with all authors providing input.

Corresponding author

Correspondence to Nadine Unger.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Ben Felzer, Jin Han Park and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended Data

Extended Data Fig. 1 Annual average surface O3 concentration in ppbv in the CTRL simulation.

Results shown are the decadal average for model run years 15–24. The 3 key regions are marked with black boxes: Eastern US, Europe and Eastern China.

Extended Data Fig. 2 Comparison of June-July-August (JJA) average modelled and observed surface O3 in ppbv.

Observed surface O3 is from a global gridded dataset compiled by Sofen et al40. The monitoring networks are predominantly in the US and Europe. Observations are climatological averages 2001–2010. The modelled values are from the CTRL simulation. The correlation coefficient (R) and normalized mean bias (NMB) are shown in the figure panel where N=130 is the number of grid cells used for the comparison statistics.

Supplementary information

Supplementary Information

Supplementary Tables 1–6.

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Unger, N., Zheng, Y., Yue, X. et al. Mitigation of ozone damage to the world’s land ecosystems by source sector. Nat. Clim. Chang. 10, 134–137 (2020).

Download citation

Further reading


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing