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Modelling PM2.5 reduction scenarios for future cardiopulmonary disease reduction

Nature Sustainability volume 9, pages 77–85 (2026)Cite this article

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Abstract

Long-term PM2.5 exposure is a risk factor for cardiovascular and respiratory mortality. Here a global health impact assessment was conducted utilizing seven future scenarios evaluating strategies to reduce PM2.5 exposure. Strategies included reducing fossil fuel use, air pollution control, adopting cleaner cooking methods and combinations thereof. Under current trends, air quality is projected to improve by 2050; nevertheless, the absolute attributable burden of ischaemic heart disease, stroke and chronic obstructive pulmonary disease remains high in many regions. Cleaner cooking fuel use is effective in the short term (by 2030) in South and Central America, Asia, and Africa for reducing PM2.5-related deaths. In the long term (by 2050) for most regions, only strategies that simultaneously target ambient and cooking-related PM2.5 resulted in sustained improvements that expand beyond current trends for reducing disease burden across these three health outcomes. In the Asian region, for example, under current trends, the population-attributable fraction decreases from 35% in 2015 to 18% in 2050. In the scenario combining universal clean cooking and climate policy, it drops further to 15%, and when all strategies are combined, it reaches as low as 11% by 2050. With all strategies combined, the average global population-weighted PM2.5 exposure from both ambient and cooking sources is reduced by nearly two-thirds (66 µg m−3 compared with 26 µg m−3). For North Africa and the Middle East region, the population-attributable fraction remains high across all scenarios. Additional strategies beyond those mentioned here are required to further improve air quality. It is recommended to pursue climate mitigation alongside universal access to cleaner household fuels to maximize cardiopulmonary health benefits.

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Fig. 1: Population-weighted annual average ambient and cooking concentration of PM2.5 concentrations (µg m−3) for baseline year 2015 and selected 2050 scenarios.
Fig. 2: Estimated PAF of three cardiopulmonary diseases due to total PM2.5 air pollution from both ambient and household cooking by scenario.

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Data availability

Most data relevant to the results are provided in Supplementary Information and are available via Zenodo at https://doi.org/10.5281/zenodo.17206910 (ref. 51). If additional data are needed, they are available upon request from the corresponding author.

Code availability

Code and PM2.5 data used for the models introduced here are available via Zenodo at https://doi.org/10.5281/zenodo.17206910 (ref. 51).

References

  1. Murray, C. J. L. et al. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 396, 1223–1249 (2020).

    Article  Google Scholar 

  2. Krittanawong, C. et al. PM2.5 and cardiovascular diseases: state-of-the-art review. Int. J. Cardiol. Cardiovasc. Risk Prev. 19, 200217 (2023).

    Google Scholar 

  3. Alexeeff, S. E., Liao, N. S., Liu, X., Van Den Eeden, S. K. & Sidney, S. Long-term PM2.5 exposure and risks of ischemic heart disease and stroke events: review and meta-analysis. J. Am. Heart Assoc. 10, e016890 (2021).

    Article  Google Scholar 

  4. van Ruijven, B. J., De Cian, E. & Sue Wing, I. Amplification of future energy demand growth due to climate change. Nat. Commun. 10, 2762 (2019).

    Article  Google Scholar 

  5. Share of rural vs. urban population with electricity access. Our World in Data https://ourworldindata.org/grapher/share-of-rural-population-with-electricity-access-vs-share-of-total-population-with-electricity-access (2025).

  6. Power outages in firms in a typical month. Our World in Data https://ourworldindata.org/grapher/power-outages-in-firms-per-month (2023).

  7. Tisserant, A. et al. Solid waste and the circular economy: a global analysis of waste treatment and waste footprints. J. Ind. Ecol. 21, 628–640 (2017).

    Article  Google Scholar 

  8. Ramadan, B. S. et al. A comprehensive review of domestic-open waste burning: recent trends, methodology comparison, and factors assessment. J. Mater. Cycles Waste Manag. 24, 1633–1647 (2022).

    Article  Google Scholar 

  9. Uzoigwe, J. C., Prum, T., Bresnahan, E. & Garelnabi, M. The emerging role of outdoor and indoor air pollution in cardiovascular disease. North Am. J. Med. Sci. 5, 445–453 (2013).

    Article  Google Scholar 

  10. Rajagopalan, S. & Brook, R. D. The indoor–outdoor air-pollution continuum and the burden of cardiovascular disease: an opportunity for improving global health. Glob. Heart 7, 207–213 (2012).

    Article  Google Scholar 

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

    Article  Google Scholar 

  12. Riahi, K. et al. The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: an overview. Glob. Environ. Change 42, 153–168 (2017).

    Article  Google Scholar 

  13. Weber, E., Downward, G. S., Ebi, K. L., Lucas, P. L. & van Vuuren, D. The use of environmental scenarios to project future health effects: a scoping review. Lancet Planet. Health 7, e611–e621 (2023).

    Article  Google Scholar 

  14. Harmsen, M. J. H. M. et al. Co-benefits of black carbon mitigation for climate and air quality. Clim. Change 163, 1519–1538 (2020).

    Article  CAS  Google Scholar 

  15. Vandyck, T. et al. Air quality co-benefits for human health and agriculture counterbalance costs to meet Paris Agreement pledges. Nat. Commun. 9, 4939 (2018).

    Article  Google Scholar 

  16. West, J. J. et al. Co-benefits of mitigating global greenhouse gas emissions for future air quality and human health. Nat. Clim. Change 3, 885–889 (2013).

    Article  CAS  Google Scholar 

  17. Yang, H., Huang, X., Westervelt, D. M., Horowitz, L. & Peng, W. Socio-demographic factors shaping the future global health burden from air pollution. Nat. Sustain. 6, 58–68 (2023).

    Article  Google Scholar 

  18. Burnett, R. et al. Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter. Proc. Natl Acad. Sci. USA 115, 9592–9597 (2018).

    Article  CAS  Google Scholar 

  19. Krewski, D. et al. Extended follow-up and spatial analysis of the American Cancer Society study linking particulate air pollution and mortality. Res. Rep. Health Eff. Inst. 140, 5–114 discussion 115–136 (2009).

  20. Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019). Particulate matter risk curves. Institute for Health Metrics and Evaluation https://doi.org/10.6069/KHWH-2703 (2021).

  21. Bennitt, F. B. et al. Global, regional, and national burden of household air pollution, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 405, 1167–1181 (2025).

    Article  Google Scholar 

  22. Kim, S. E. et al. Air quality co-benefits from climate mitigation for human health in South Korea. Environ. Int. 136, 105507 (2020).

    Article  Google Scholar 

  23. Johnson, M., Lam, N., Brant, S., Gray, C. & Pennise, D. Modeling indoor air pollution from cookstove emissions in developing countries using a Monte Carlo single-box model. Atmos. Environ. 45, 3237–3243 (2011).

    Article  CAS  Google Scholar 

  24. Van Dingenen, R. et al. TM5-FASST: a global atmospheric source-receptor model for rapid impact analysis of emission changes on air quality and short-lived climate pollutants. Atmos. Chem. Phys. 18, 16173–16211 (2018).

    Article  Google Scholar 

  25. van Ruijven, B., de Vries, B., van Vuuren, D. P. & van der Sluijs, J. P. A global model for residential energy use: Uncertainty in calibration to regional data. Energy 35, 269–282 (2010).

    Article  Google Scholar 

  26. Database of input variables for the WHO Household Multiple Emission Sources (HOMES) and performance targets (PT) models. World Health Organization https://worldhealthorg.shinyapps.io/HAPmodelinputdata/ (2025).

  27. World Heart Report 2024 (World Heart Federation, 2024); https://world-heart-federation.org/report2024/

  28. Tang, Z., Ku, P.-W., Xia, Y., Chen, L.-J. & Zhang, Y. Preexisting multimorbidity predicts greater mortality risks related to long-term PM2.5 exposure. Environ. Pollut. 368, 125762 (2025).

    Article  CAS  Google Scholar 

  29. Burke, M. et al. The contribution of wildfire to PM2.5 trends in the USA. Nature 622, 761–766 (2023).

    Article  CAS  Google Scholar 

  30. Zhong, Q., Shen, G., Wang, B., Ma, J. & Tao, S. Climate-driven escalation of global PM2.5 health burden from wildland fires. Environ. Sci. Technol. 59, 3131–3142 (2025).

    Article  CAS  Google Scholar 

  31. Dagnachew, A. G., Hof, A. F., Roelfsema, M. R. & van Vuuren, D. P. Actors and governance in the transition toward universal electricity access in Sub-Saharan Africa. Energy Policy 143, 111572 (2020).

    Article  Google Scholar 

  32. Rigorous Verification of Results:Value for Money or Waste of Time? (EnDev., 2021); https://endev.info/rigorous-verification-of-results-value-for-money-or-waste-of-time/

  33. Carley, S. & Konisky, D. M. The justice and equity implications of the clean energy transition. Nat. Energy 5, 569–577 (2020).

    Article  CAS  Google Scholar 

  34. Zapata, V., Dagnachew, A., Edelenbosch, O. Y. & Vuuren, D. van. High-resolution global pathways to achieve 100% electricity access in 2030. Preprint at Research Square https://doi.org/10.21203/rs.3.rs-3388210/v1 (2023).

  35. Mansournia, M. A. & Altman, D. G. Population attributable fraction. BMJ 360, k757 (2018).

    Article  Google Scholar 

  36. Region classification map – IMAGE. PBL https://models.pbl.nl/image/index.php/Region_classification_map (2018).

  37. EDGAR – The Emissions Database for Global Atmospheric Research. European Commission https://edgar.jrc.ec.europa.eu/ (2018).

  38. Welcome to IMAGE 3.3 Documentation – IMAGE. Netherlands Environmental Assessment Agency (PBL) https://models.pbl.nl/image/Welcome_to_IMAGE_3.3_Documentation

  39. de Vries, B. et al. Greenhouse gas emissions in an equity-, environment- and service-oriented world: an IMAGE-based scenario for the 21st century. Technol. Forecast. Soc. Change 63, 137–174 (2000).

    Article  Google Scholar 

  40. Daioglou, V., van Ruijven, B. J. & van Vuuren, D. P. Model projections for household energy use in developing countries. Energy 37, 601–615 (2012).

    Article  Google Scholar 

  41. Dagnachew, A. G., Hof, A. F., Lucas, P. L. & van Vuuren, D. P. Scenario analysis for promoting clean cooking in Sub-Saharan Africa: costs and benefits. Energy 192, 116641 (2020).

    Article  Google Scholar 

  42. Household Multiple Emission Source (HOMES) model. WHO https://www.who.int/tools/household-multiple-emission-source-homes-model (2020).

  43. IPUMS MTUS: Select Time Use Variable Template. University of Minnesota https://www.mtusdata.org/mtus-action/time_use_variables/select_template

  44. Shupler, M. et al. Global household air pollution database: kitchen concentrations and personal exposures of particulate matter and carbon monoxide. Data Brief. 21, 1292–1295 (2018).

    Article  Google Scholar 

  45. Pandey, A. et al. Health and economic impact of air pollution in the states of India: the Global Burden of Disease Study 2019. Lancet Planet. Health 5, e25–e38 (2021).

    Article  Google Scholar 

  46. Ghosh, R. et al. Ambient and household PM2.5 pollution and adverse perinatal outcomes: A meta-regression and analysis of attributable global burden for 204 countries and territories. PLoS Med. 18, e1003718 (2021).

    Article  CAS  Google Scholar 

  47. Fricko, O. et al. The marker quantification of the Shared Socioeconomic Pathway 2: a middle-of-the-road scenario for the 21st century. Glob. Environ. Change 42, 251–267 (2017).

    Article  Google Scholar 

  48. R Core Team R: A Language and Environment for Statistical Computing (R Core Team, 2021).

  49. Becker, A. R., Wilks, R. A,. Brownrigg, R., Minka, P. T. & Deckmyn, A. R package for geographical maps. GitHub https://github.com/adeckmyn/maps (2025).

  50. Gómez-Sanabria, A., Kiesewetter, G., Klimont, Z., Schoepp, W. & Haberl, H. Potential for future reductions of global GHG and air pollutants from circular waste management systems. Nat. Commun. 13, 106 (2022).

    Article  Google Scholar 

  51. Weber, E. Code for modelling PM2.5 reduction scenarios for future cardiopulmonary disease reduction. Zenodo https://doi.org/10.5281/zenodo.17206910 (2025).

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Acknowledgements

We acknowledge funding from the European Research Council (ERC) under the Horizon Europe programme (PICASSO project; grant agreement ID 819566). The funder had no role in the study design, data collection, data analysis, writing of the report or data interpretation. D.v.V. and V.D. received funding from the European Union’s Horizon Europe programme under grant agreement no. 101081604. We acknowledge the following contributions: M. Harmsen provided insight into precursor emissions. M. van der Marel helped with the HOMES model code validation. M. Van Den Berg created IMAGE’s version of the TM5-FAAST submodel. We thank R. Ghosh for advising E.W. on early stages of the work about MR-BRT curves.

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Author notes

  1. These authors contributed equally: George Downward, Maria Gabriela Matias de Pinho, Detlef van Vuuren.

Authors and Affiliations

  1. Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands

    Eartha Weber, Vassilis Daioglou, Maria Gabriela Matias de Pinho & Detlef van Vuuren

  2. PBL Netherlands Environmental Assessment Agency, The Hague, The Netherlands

    Vassilis Daioglou, Laszlo Vreedenburgh, Jonathan Doelman & Detlef van Vuuren

  3. Department Population Health Sciences, Julius Center for Health Sciences and Primary Care, Utrecht, The Netherlands

    George Downward

  4. Institute for Risk Assessment Sciences, Division of Environmental Epidemiology University Medical Center, Utrecht, The Netherlands

    George Downward

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Contributions

E.W. conducted the health impact analyses, made all figures, conceptualized the use of HOME’s model in this type of analysis and wrote the first draft. V.D. ran the energy modules of the IMAGE model for all scenarios and provided proportions of fuel usage for the SSP2 Baseline scenario. L.V. ran the TM5-FAAST analyses. J.D. ran the land model and provided results for the waste burning scenario. D.v.V. conceptualized the scenarios, provided supervision and leadership, and secured the funding for the study. G.D. and M.G.M.d.P. jointly supervised this work. All listed co-authors edited and revised the final drafts.

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Correspondence to Eartha Weber.

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Nature Sustainability thanks Lutz Sager and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Appendices A–F. Tables with all 26 region results, including uncertainty intervals for 7 different scenarios and 3 different health outcomes. Sensitivity analysis of the above with longer distribution of cooking times. Input data for Fig. 2 and functions explained.

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Weber, E., Daioglou, V., Vreedenburgh, L. et al. Modelling PM2.5 reduction scenarios for future cardiopulmonary disease reduction. Nat Sustain 9, 77–85 (2026). https://doi.org/10.1038/s41893-025-01676-9

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