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Health co-benefits of climate change mitigation depend on strategic power plant retirements and pollution controls


Reducing CO2 emissions from fossil fuel- and biomass-fired power plants often also reduces air pollution, benefitting both climate and public health. Here, we examine the relationship of climate and health benefits by modelling individual electricity-generating units worldwide across a range of climate–energy policy scenarios. We estimate that ~92% of deaths related to power plant emissions during 2010–2018 occurred in low-income or emerging economies such as China, India and countries in Southeast Asia, and show that such deaths are quite sensitive to future climate–energy trajectories. Yet, minimizing future deaths will also require strategic retirements of super-polluting power plants and deployment of pollution control technologies. These findings underscore the importance of considering public health in designing and implementing climate–energy policies: improved air quality and avoided air pollution deaths are not an automatic and fixed co-benefit of climate mitigation.

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Fig. 1: Shares of PM2.5-related deaths from global power plants as of 2010.
Fig. 2: Mean annual change in CO2 emissions and PM2.5-related deaths.
Fig. 3: PM2.5 exposures and PM2.5-related deaths that are linked to emissions from global power plants.
Fig. 4: Cumulative avoided PM2.5-related deaths and CO2 emissions 2010–2050.

Data availability

The database GPED that supports the base-year findings of this study is available at The base mortality incidences data during 2010–2018 are available at The future base mortality incidences database is available at The future demographic structure database is available at Emission data for other sectors are available at Emissions data of the power plants in scenarios produced that support the findings of this study are available at (ref. 74).

Code availability

The code of the GEOS-Chem model to simulate the global PM2.5 concentrations is available at


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This work was supported by the National Natural Science Foundation of China (grant nos. 41921005 and 41625020) and the Energy Foundation (G-2009-32416). D.T. was supported by a gift to Carnegie Institution for Science from Gates Ventures LLC. C.H. and S.J.D. were supported by the US National Science Foundation (Innovations at the Nexus of Food, Energy and Water Systems grant no. EAR 1639318).

Author information




Q.Z., D.T. and S.J.D. designed the study. D.T. performed the emission and health analyses with support from J.C., X.Q. and C.H. on analytical approaches. G.G. conducted GEOS-Chem simulations. D.T., S.J.D. and Q.Z. interpreted the data. D.T., S.J.D., G.G. and Q.Z. wrote the paper with input from all co-authors.

Corresponding authors

Correspondence to Qiang Zhang or Steven J. Davis.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Jan Steckel 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 The framework of unit-level power emission projection model.

The figure shows the framework of unit-level power emission projection model developed for this study.

Extended Data Fig. 2 Regional average lifetimes for each retirement strategy.

The figure shows the regional average lifetimes of power plants for each retirement strategy.

Source data

Extended Data Fig. 3 Identified capacity and death contributions of 2010-coal super-polluting units.

The figure shows capacity and death contributions of 2010-coal super-polluting units in 2010 and 2018 across nine regions.

Source data

Extended Data Fig. 4 Mean annual change in CO2 emissions and PM2.5-related years of life lost.

The figure shows the relationship between annual average CO2 reduction rate and PM2.5-related years of life lost under the scenario assemble in (a) 2030 and (b) 2050, spanning four levels of climate ambition (RCP6.0, RCP4.5, RCP2.6, and RCP1.9) and three different retirement strategies (historical, performance-based, and early retirement) and two stringencies of pollution controls (that is strong and weak). The black circles show the mean annual change in CO2 emissions during 2010–2015 (and 2010-level PM2.5-related years of life lost), and 2010–2018 (and 2018-level PM2.5-related years of life lost), respectively.

Source data

Extended Data Fig. 5 Future emission reductions during 2010–2050 under various combined mitigation options.

The period during 2010–2018 show the real emission differences, equalling 0. The RCP6.0 with performance-based retirement and weak pollution control scenario was set as the base scenario for comparison, Figs. a1-a4 show the emission reductions among different ambitious climate–energy scenarios (that is RCP4.5, RCP2.6, and RCP1.9); Figs. b1-b4 show the emission changes among different retirement strategies (that is historical and early retirements) covering RCP6.0 and RCP1.9; Figs. c1-c4 show the emission reductions from weak to strong pollution controls covering RCP6.0 and RCP1.9.

Source data

Supplementary information

Supplementary Information

Supplementary Notes 1–7 and Figs. 1–9.

Supplementary Tables

Supplementary Tables 1–18.

Source data

Source Data Fig. 1

Source Data for Fig. 1.

Source Data Fig. 2

Source Data for Fig. 2.

Source Data Fig. 3

Source Data for Fig. 3.

Source Data Fig. 4

Source Data for Fig. 4.

Source Data Extended Data Fig. 2

Source Data for Extended Data Fig. 2.

Source Data Extended Data Fig. 3

Source Data for Extended Data Fig. 3.

Source Data Extended Data Fig. 4

Source Data for Extended Data Fig. 4.

Source Data Extended Data Fig. 5

Source Data for Extended Data Fig. 5.

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Tong, D., Geng, G., Zhang, Q. et al. Health co-benefits of climate change mitigation depend on strategic power plant retirements and pollution controls. Nat. Clim. Chang. 11, 1077–1083 (2021).

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