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Control of toxicity of fine particulate matter emissions in China

Nature volume 643, pages 404–411 (2025)Cite this article

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Abstract

Fine particulate matter (particulate matter with a diameter of 2.5 μm or less; PM2.5) causes millions of premature deaths globally1, but not all particles are equally harmful2,3,4. Current air-pollution control strategies, prioritizing PM2.5 mass reduction, have provided considerable health benefits but further refinements based on differences in the toxicity of various emission sources may provide greater benefits5,6,7. Here we integrated field measurements with air-quality modelling to assess the unequal toxicities of PM2.5 from various anthropogenic sources. Our findings revealed that the toxicity per unit of PM2.5 mass differed substantially between major sources, differing by up to two orders of magnitude. PM2.5 from solid fuel combustion in residential stoves had the highest toxicity, followed by those from the metallurgy industry, brake wear, diesel vehicles, petrol vehicles, the cement industry and power plants. We further analysed the source contributions of toxicity-adjusted PM2.5 emissions and population exposures in China. From 2005 to 2021, both the PM2.5 mass and relative-potency-adjusted emissions substantially decreased. Although industrial sources contributed 57.5% to the reduction in PM2.5 mass emissions, the reduction in relative potency-adjusted emissions was driven by residential combustion (approximately 80%). Clean-air policies should consider the differing toxicities of PM2.5 when formulating source-specific emission control regulations. This study proposes a cellular toxicity-based framework for PM2.5 reduction that could address the specific health risks in diverse regions, but further epidemiological studies will be required to confirm their relevance to human health outcomes and their application to public policy.

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Fig. 1: Relative toxic potencies of source-specific PM2.5.
Fig. 2: Sectoral contributions to the changes in RPAE and PM2.5 emissions in China during the period 2005–2021.
Fig. 3: Spatial distribution of RPAE and relative potency of PM2.5 emissions in China in 2021.
Fig. 4: Geographical disparities in PM2.5 exposure and associated toxicity in China in 2021.

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Data availability

The results of the cellular tests of source-specific PM2.5 samples are presented in the paper and/or the Supplementary Information. The mass fractions and relative contributions to oxidative stress toxicity of individual PAHs and metals are given in the Supplementary Data. The ABaCAS emissions inventory is available online at Figshare (https://doi.org/10.6084/m9.figshare.21777005.v1)62. The base map (approval no. GS(2019)1822) of Figs. 3 and 4 and Extended Data Figs. 5, 7–9 is sourced from the Standard Map Service System hosted by the Ministry of Natural Resources of China (http://bzdt.ch.mnr.gov.cn/index.html). The map is used unmodified and complies with public map regulations. Source data are provided with this paper.

Code availability

The open-source numerical models WRF (v.3.9.1, https://www.mmm.ucar.edu/models/wrf) and CMAQ (v.5.3.3, https://github.com/USEPA/CMAQ) were used for the modelling. The model codes used in this work as well as sample datasets used to test the codes are available at Figshare (https://figshare.com/s/c60433809e435a82e333)63.

References

  1. Brauer, M. et al. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 403, 2162–2203 (2024).

    Article  Google Scholar 

  2. Bell, M. L. Assessment of the Health Impacts of Particulate Matter Characteristics. Research Report 161 (Health Effects Institute, 2012).

  3. Lippmann, M., Chen, L.-C., Gordon, T., Ito, K. & Thurston, G. D. National Particle Component Toxicity (NPACT) Initiative: Integrated Epidemiologic and Toxicologic Studies of the Health Effects of Particulate Matter Components. Research Report 177 (Health Effects Institute, 2013).

  4. Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D. & Pozzer, A. The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature 525, 367–371 (2015).

    Article  ADS  CAS  PubMed  Google Scholar 

  5. Li, X. D., Jin, L. & Kan, H. D. Air pollution: a global problem needs local fixes. Nature 570, 437–439 (2019).

    Article  ADS  CAS  PubMed  Google Scholar 

  6. Zhao, B., Wang, S. & Hao, J. Challenges and perspectives of air pollution control in China. Front. Environ. Sci. Eng. 18, 68 (2024).

    Article  Google Scholar 

  7. Weichenthal, S. et al. Epidemiological studies likely need to consider PM2.5 composition even if total outdoor PM2.5 mass concentration is the exposure of interest. Environ. Epidemiol. 8, e317 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Berna, F. et al. Microstratigraphic evidence of in situ fire in the Acheulean strata of Wonderwerk Cave, Northern Cape province, South Africa. Proc. Natl Acad. Sci. USA 109, E1215–E1220 (2012).

    Article  PubMed Central  Google Scholar 

  9. Davis, D. A look back at the London smog of 1952 and the half century since. Environ. Health Perspect. 110, A734–A735 (2002).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Huang, R. J. et al. High secondary aerosol contribution to particulate pollution during haze events in China. Nature 514, 218–222 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  11. Calvert, J. G. Hydrocarbon involvement in photochemical smog formation in Los Angeles atmosphere. Environ. Sci. Technol. 10, 256–262 (1976).

    Article  ADS  CAS  PubMed  Google Scholar 

  12. Pope, C. A. III et al. Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. JAMA 287, 1132–1141 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Dockery, D. W. et al. An association between air pollution and mortality in six U.S. cities. N. Engl. J. Med. 329, 1753–1759 (1993).

    Article  CAS  PubMed  Google Scholar 

  14. Schwartz, J. Air pollution and daily mortality: a review and meta analysis. Environ. Res. 64, 36–52 (1994).

    Article  CAS  PubMed  Google Scholar 

  15. Samet, J. M. The clean air act and health—a clearer view from 2011. N. Engl. J. Med. 365, 198–201 (2011).

    Article  CAS  PubMed  Google Scholar 

  16. Ding, D., Xing, J., Wang, S., Liu, K. & Hao, J. Estimated contributions of emissions controls, meteorological factors, population growth, and changes in baseline mortality to reductions in ambient PM2.5 and PM2.5-related mortality in China, 2013–2017. Environ. Health Perspect. 127, 067009 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Thurston, G. D. et al. Ischemic heart disease mortality and long-term exposure to source-related components of U.S. fine particle air pollution. Environ. Health Perspect. 124, 785–794 (2016).

    Article  CAS  PubMed  Google Scholar 

  18. Weichenthal, S. et al. Association of sulfur, transition metals, and the oxidative potential of outdoor PM2.5 with acute cardiovascular events: a case-crossover study of Canadian adults. Environ. Health Perspect. 129, 107005 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Pye, H. O. T., Ward-Caviness, C. K., Murphy, B. N., Appel, K. W. & Seltzer, K. M. Secondary organic aerosol association with cardiorespiratory disease mortality in the United States. Nat. Commun. 12, 7215 (2021).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  20. Lippmann, M. Toxicological and epidemiological studies of cardiovascular effects of ambient air fine particulate matter (PM2.5) and its chemical components: coherence and public health implications. Crit. Rev. Toxicol. 44, 299–347 (2014).

    Article  CAS  PubMed  Google Scholar 

  21. Jin, L. et al. Contributions of city-specific fine particulate matter (PM2.5) to differential in vitro oxidative stress and toxicity implications between Beijing and Guangzhou of China. Environ. Sci. Technol. 53, 2881–2891 (2019).

    Article  ADS  CAS  PubMed  Google Scholar 

  22. Wu, D. et al. Toxic potency-adjusted control of air pollution for solid fuel combustion. Nat. Energy 7, 194–202 (2022).

    Article  ADS  CAS  Google Scholar 

  23. Luo, X.-S. et al. Source differences in the components and cytotoxicity of PM2.5 from automobile exhaust, coal combustion, and biomass burning contributing to urban aerosol toxicity. Atmos. Chem. Phys. 24, 1345–1360 (2024).

    Article  ADS  CAS  Google Scholar 

  24. Kelly, F. J. & Fussell, J. C. Size, source and chemical composition as determinants of toxicity attributable to ambient particulate matter. Atmos. Environ. 60, 504–526 (2012).

    Article  ADS  CAS  Google Scholar 

  25. Shiraiwa, M., Selzle, K. & Pöschl, U. Hazardous components and health effects of atmospheric aerosol particles: reactive oxygen species, soot, polycyclic aromatic compounds and allergenic proteins. Free Radic. Res. 46, 927–939 (2012).

    Article  CAS  PubMed  Google Scholar 

  26. Kazemiparkouhi, F. et al. The impact of long-term PM2.5 constituents and their sources on specific causes of death in a US Medicare cohort. Environ. Int. 159, 106988 (2022).

    Article  CAS  PubMed  Google Scholar 

  27. Hopke, P. K. et al. Changes in the hospitalization and ED visit rates for respiratory diseases associated with source-specific PM2.5 in New York State from 2005 to 2016. Environ. Res. 181, 108912 (2020).

    Article  CAS  PubMed  Google Scholar 

  28. Pond, Z. A. et al. Cardiopulmonary mortality and fine particulate air pollution by species and source in a national U.S. cohort. Environ. Sci. Technol. 56, 7214–7223 (2022).

    Article  ADS  CAS  PubMed  Google Scholar 

  29. Integrated Science Assessment (ISA) for Particulate Matter (Final Report, Dec 2019) (US Environmental Protection Agency, 2019).

  30. 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  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  31. GBD MAPS Working Group. Burden of Disease Attributable to Coal-Burning and Other Air Pollution Sources in China. Special Report 20 (Health Effects Institute, 2016).

  32. McDuffie, E. E. et al. Source sector and fuel contributions to ambient PM2.5 and attributable mortality across multiple spatial scales. Nat. Commun. 12, 3594 (2021).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  33. Zheng, H. et al. Transition in source contributions of PM2.5 exposure and associated premature mortality in China during 2005–2015. Environ. Int. 132, 105111 (2019).

    Article  CAS  PubMed  Google Scholar 

  34. Zheng, H. et al. Unpacking the factors contributing to changes in PM2.5-associated mortality in China from 2013 to 2019. Environ. Int. 184, 108470 (2024).

    Article  CAS  PubMed  Google Scholar 

  35. Kelly, F. J. & Fussell, J. C. Toxicity of airborne particles—established evidence, knowledge gaps and emerging areas of importance. Phil. Trans. R. Soc. A 378, 20190322 (2020).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  36. Jiang, X. A conversation on air pollution in China. Nat. Geosci. 16, 939–940 (2023).

    Article  ADS  CAS  Google Scholar 

  37. Weichenthal, S., Lavigne, E., Evans, G., Pollitt, K. & Burnett, R. T. Ambient PM2.5 and risk of emergency room visits for myocardial infarction: impact of regional PM2.5 oxidative potential: a case-crossover study. Environ. Health 15, 46 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Bates, J. T. et al. Review of acellular assays of ambient particulate matter oxidative potential: methods and relationships with composition, sources, and health effects. Environ. Sci. Technol. 53, 4003–4019 (2019).

    Article  ADS  CAS  PubMed  Google Scholar 

  39. Backhaus, T. & Faust, M. Predictive environmental risk assessment of chemical mixtures: a conceptual framework. Environ. Sci. Technol. 46, 2564–2573 (2012).

    Article  ADS  CAS  PubMed  Google Scholar 

  40. Shen, G. et al. Emissions of PAHs from indoor crop residue burning in a typical rural stove: emission factors, size distributions, and gas−particle partitioning. Environ. Sci. Technol. 45, 1206–1212 (2011).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  41. Wu, D. et al. More than concentration reduction: contributions of oxidation technologies to alleviating aerosol toxicity from diesel engines. Environ. Sci. Technol. Lett. 9, 280–285 (2022).

    Article  CAS  Google Scholar 

  42. Chen, R. et al. Fine particulate air pollution and daily mortality. A nationwide analysis in 272 Chinese cities. Am J Respir Crit Care Med 196, 73–81 (2017).

    Article  CAS  PubMed  Google Scholar 

  43. Jiang, Y. et al. Extreme emission reduction requirements for China to achieve world health organization global air quality guidelines. Environ. Sci. Technol. 57, 4424–4433 (2023).

    Article  CAS  PubMed  Google Scholar 

  44. Zhao, B. et al. Change in household fuels dominates the decrease in PM2.5 exposure and premature mortality in China in 2005–2015. Proc. Natl Acad. Sci. USA 115, 12401 (2018).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  45. Ma, T. et al. Costs and health benefits of the rural energy transition to carbon neutrality in China. Nat. Commun. 14, 6101 (2023).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  46. Xing, J. et al. The quest for improved air quality may push China to continue its CO2 reduction beyond the Paris Commitment. Proc. Natl Acad. Sci. USA 117, 29535–29542 (2020).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  47. Sovacool, B. K. et al. Sustainable minerals and metals for a low-carbon future. Science 367, 30–33 (2020).

    Article  ADS  CAS  PubMed  Google Scholar 

  48. Fussell, J. C. et al. A review of road traffic-derived non-exhaust particles: emissions, physicochemical characteristics, health risks, and mitigation measures. Environ. Sci. Technol. 56, 6813–6835 (2022).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  49. Sato, T. et al. Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche. Nature 459, 262–265 (2009).

    Article  ADS  CAS  PubMed  Google Scholar 

  50. Liu, Y. et al. Unequal health risks of integrated volatile organic compounds emitted from various anthropogenic sources. J. Geophys. Res. Atmos. 128, e2023JD038594 (2023).

    Article  ADS  CAS  Google Scholar 

  51. Wu, D. et al. Achieving health-oriented air pollution control requires integrating unequal toxicities of industrial particles. Nat. Commun. 14, 6491 (2023).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  52. Ding, X. et al. Direct observation of sulfate explosive growth in wet plumes emitted from typical coal-fired stationary sources. Geophys. Res. Lett. 48, e2020GL092071 (2021).

    Article  ADS  Google Scholar 

  53. Ding, X. et al. Unexpectedly increased particle emissions from the steel industry determined by wet/semidry/dry flue gas desulfurization technologies. Environ. Sci. Technol. 53, 10361–10370 (2019).

    Article  ADS  CAS  PubMed  Google Scholar 

  54. Wu, D. et al. Primary particulate matter emitted from heavy fuel and diesel oil combustion in a typical container ship: characteristics and toxicity. Environ. Sci. Technol. 52, 12943–12951 (2018).

    Article  ADS  CAS  PubMed  Google Scholar 

  55. Wu, D. et al. Commodity plastic burning as a source of inhaled toxic aerosols. J. Hazard. Mater. 416, 125820 (2021).

    Article  CAS  PubMed  Google Scholar 

  56. Wu, D., Zhang, F., Lou, W., Li, D. & Chen, J. Chemical characterization and toxicity assessment of fine particulate matters emitted from the combustion of petrol and diesel fuels. Sci. Total Environ. 605–606, 172–179 (2017).

    Article  ADS  PubMed  Google Scholar 

  57. Li, S. et al. Emission trends of air pollutants and CO2 in China from 2005 to 2021. Earth Syst. Sci. Data 15, 2279–2294 (2023).

    Article  ADS  Google Scholar 

  58. Zheng, H. et al. Development of a unit-based industrial emission inventory in the Beijing–Tianjin–Hebei region and resulting improvement in air quality modeling. Atmos. Chem. Phys. 19, 3447–3462 (2019).

    Article  ADS  CAS  Google Scholar 

  59. Wu, Q. et al. Facility-level emissions and synergistic control of energy-related air pollutants and carbon dioxide in China. Environ. Sci. Technol. 57, 4504–4512 (2023).

    Article  CAS  PubMed  Google Scholar 

  60. Zheng, H. et al. Sources of organic aerosol in China from 2005 to 2019: a modeling analysis. Environ. Sci. Technol. 57, 5957–5966 (2023).

    Article  ADS  CAS  PubMed  Google Scholar 

  61. Fu, Z. et al. Emissions of multiple metals from vehicular brake linings wear in China, 1980–2020. Sci. Total Environ. 889, 164380 (2023).

    Article  CAS  PubMed  Google Scholar 

  62. Li, S. et al. Emission trends of air pollutants and CO2 in China from 2005 to 2021. Figshare https://doi.org/10.6084/m9.figshare.21777005.v1 (2022).

  63. Codes and data for manuscript ‘Control of PM2.5 Toxicity Emissions in China’. Figshare https://figshare.com/s/c60433809e435a82e333 (2024).

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (grant no. 22188102 to S. Wang, grant nos. U22A20405 and T2122006 to Q. Li, and grant no. 22406026 to D.W.), the National Key Research and Development Program (grant no. 2022YFC3702905 to S. Wang and grant no. 2022YFC3700501 to Q. Li), the New Cornerstone Science Foundation through the XPLORER PRIZE (to S. Wang), the Research Grants Council of Hong Kong (grant no. T24-508/22-N to X.D.L. and L.N.J., and grant nos. 25210420, 15213922 and C2002-22Y to L.N.J.), and the ‘GeoX’ Interdisciplinary Project of Frontiers Science Center for Critical Earth Material Cycling, Nanjing University (grant no. 20250210 to H.Z.). We thank A. Cheng, Y. Tan, L. Wang and T. Liu for supporting the collection of field samples and Y. Wu, S. Zhang and Z. Fu for contributing to the emissions inventory. A.J.C. is a consulting principal scientist at the Health Effects Institute. The views expressed here are those of the authors and do not necessarily reflect the views of the Health Effects Institute, or its sponsors.

Author information

Author notes

  1. Haotian Zheng

    Present address: Nanjing-Helsinki Institute in Atmospheric and Earth System Sciences, Nanjing University, Nanjing, China

  2. These authors contributed equally: Haotian Zheng, Di Wu

Authors and Affiliations

  1. State Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing, China

    Haotian Zheng, Shuxiao Wang, Bin Zhao, Shengyue Li, Yisheng Sun, Zhaoxin Dong, Qingru Wu, Jingkun Jiang, Kebin He & Jiming Hao

  2. Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China

    Haotian Zheng, Xiangdong Li & Ling N. Jin

  3. Department of Environmental Science and Engineering, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Fudan University, Shanghai, China

    Di Wu, Xiu Chen, Yuzhe Liu, Jianmin Chen & Qing Li

  4. Key Laboratory of Sources and Control of Air Pollution Complex, Ministry of Ecology and Environment, Beijing, China

    Shuxiao Wang, Bin Zhao, Shengyue Li, Yisheng Sun, Zhaoxin Dong, Qingru Wu, Jingkun Jiang, Kebin He & Jiming Hao

  5. Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China

    Ling N. Jin

  6. State Key Laboratory of Regional Environment and Sustainability, School of Environment, Beijing Normal University, Beijing, China

    Hezhong Tian

  7. State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China

    Qian Liu

  8. School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China

    Haidong Kan

  9. State Key Laboratory of Regional Environment and Sustainability, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China

    Hong He

  10. Key Laboratory of Photochemistry, Institute of Chemistry, Chinese Academy of Sciences, Beijing, China

    Chuncheng Chen & Jincai Zhao

  11. Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Canada

    Scott Weichenthal

  12. Vanke School of Public Health, Tsinghua University, Beijing, China

    John S. Ji

  13. Health Effects Institute, Boston, MA, USA

    Aaron J. Cohen

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Contributions

S. Wang and Q. Li conceived and designed the experiments. D.W., Q. Li, X.C. and Y.L. performed the experiments. H.Z. and D.W. analysed the data and prepared the graphs. X.D.L., L.N.J., B.Z., S.L., Y.S., Z.D., Q.W., J.C., H.T., Q. Liu, J.J., H.K., K.H., H.H., C.C., J.Z., S. Weichenthal, J.S.J., A.J.C. and J.H. contributed materials and analysis tools. H.Z. and D.W. wrote the manuscript, and all of the authors helped to revise the manuscript.

Corresponding authors

Correspondence to Shuxiao Wang or Qing Li.

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Extended data figures and tables

Extended Data Fig. 1 Chemical drivers of PM2.5 toxicity.

The mass fractions of key toxic components in PM2.5 emissions from residential combustion (fuel types: coal and biomass), power generation (fuel types: coal, biomass, and waste), transportation (including on-road gasoline/diesel vehicles, inland waterways, and non-exhaust emissions), and industrial sections (including iron and steel, non-ferrous metallurgy, cement, industry boilers, coking, and glass production): a, 16 US EPA priority PAHs; b, 10 selected toxic metals. The data are plotted as box-and-whiskers (the line in the box is the median, the solid squares are the mean values, the edges of the boxes are the quartile ranges (25th and 75th percentiles), and the lengths of the whiskers are within 1.5 times the interquartile range). PM2.5 from residential solid fuel combustion is rich in PAHs, while industrial emissions are rich in toxic metals. Data represent 16 PAHs (n = 268) and toxic metals (n = 275) per unit mass of PM2.5 samples. Results are derived from three independent experiments, each comprising a minimum of three technical replicates.

Extended Data Fig. 2 Industrial PM2.5 emissions and RPAE in China during 2005–2021.

a, PM2.5 emissions. b, RPAEOS. c, RPAECT. The gray and black curves denote the RPOS and RPCT of the PM2.5 emissions from industrial sources (right y-axis).

Extended Data Fig. 3 Transportation PM2.5 emissions and RPAE in China during 2005–2021.

a, PM2.5 emissions. b, RPAEOS. c, RPAECT. The gray and black curves denote the RPOS and RPCT of the PM2.5 emissions from transportation sources (right y-axis).

Extended Data Fig. 4 Source-resolved contributions to PM2.5 emissions and RPAE in China during 2005–2021.

a, PM2.5 mass. b, RPAEOS. c, RPAECT. The data in parentheses are the range (minimum to maximum) of percentage contributions among provinces. Residential combustion sources dominated the reductions in RPAE while industrial sources dominated the reductions in PM2.5 mass.

Extended Data Fig. 5 Spatial distribution of PM2.5 emissions, RPAE, and RP of PM2.5 emissions in China in 2021.

a, PM2.5 emissions (resolution: 9 km × 9 km). b, RPAECT. c, RPCT of PM2.5. The bold boundaries denote the Beijing-Tianjin-Hebei (BTH) region, Yangtze River Delta (YRD), Pearl River Delta (PRD), and Northwestern China (Northwest). The base map is from the Standard Map Service System hosted by the Ministry of Natural Resources of China.

Extended Data Fig. 6 Joint probability density distributions of PM2.5 emission intensity (t/km²) versus associated relative potencies.

a, RPOS. b, RPCT. For each region, 2,000 data points were sampled from grid cells, and the joint probability densities were estimated using Seaborn’s kdeplot function in Python. The contours represent the iso-proportion levels of the data density, with the lowest level threshold set at 0.33 to highlight primary density hotspots.

Extended Data Fig. 7 Spatial distribution of the RPAE and RP of PM2.5 emissions in the Beijing-Tianjin-Hebei (BTH) region in China in 2021.

a, RPAEOS (resolution: 9 km × 9 km). b, RPOS. c, RPAECT. d, RPCT. The base map is from the Standard Map Service System hosted by the Ministry of Natural Resources of China.

Extended Data Fig. 8 Multiscale exposure-toxicity relationship for PM2.5 exposure in China in 2021.

a-c, Grid-level distributions of the PM2.5 exposure, RPOS, and RPCT of exposure. d-f, Province-level spatial distributions of the PM2.5 exposure, RPOS, and RPCT of exposure. g-h, Province-level spatial distribution of RPOS- and RPCT-adjusted exposure. The base map is from the Standard Map Service System hosted by the Ministry of Natural Resources of China.

Extended Data Fig. 9 Provincial source apportionment of PM2.5 exposure (outer ring) and RPOS- (middle ring) and RPCT-adjusted exposure (inner ring) in China in 2021.

The top three sources per category are colored distinctly, while the remaining contributors are combined as “Others” in gray. The base map is from the Standard Map Service System hosted by the Ministry of Natural Resources of China.

Supplementary information

Supplementary Information (download PDF )

Supplementary Notes 1–5 and additional references, Figs. 1–12 and Tables 1–5.

Supplementary Data (download XLSX )

The mass fractions and relative contributions to oxidative stress toxicity of individual PAHs and metals.

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Zheng, H., Wu, D., Wang, S. et al. Control of toxicity of fine particulate matter emissions in China. Nature 643, 404–411 (2025). https://doi.org/10.1038/s41586-025-09158-w

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