Extreme air pollution from residential solid fuel burning


Atmospheric aerosol particles (also known as particulate matter) are central to the cause of the two greatest threats to human security: air pollution (~5 million premature deaths per year) and climate change (~0.5 million per year). Addressing these threats requires an understanding of particulate matter sources responsible for both extreme air pollution immediately affecting human health and less extreme levels affecting climate over longer timescales. Here, extraordinary levels of air pollution, with submicrometre aerosol (PM1) mass concentration surpassing 300 µg m−3, were observed in a moderately sized European city and are attributed to emissions from residential solid fuel—specifically peat and wood, often promoted as ‘slow-renewable’, ‘low-carbon’ or ‘carbon-neutral’ biomass. Using sophisticated fingerprinting techniques, we find that consumption of peat and wood in up to 12% and 1% of households, respectively, contributed up to 70% of PM1. The results from this approach can better inform emissions reduction policies and help to ensure the most appropriate air pollution sources are targeted. Given the far greater abundance of solid fuels and concomitant emissions required to match the calorific benefit of liquid fuels, even modest increases in the consumption of ‘green’-marketed solid fuels will disproportionally increase the frequency of extreme pollution events.

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Fig. 1: Chemical composition of PM1 during two extreme pollution events.
Fig. 2: The contribution of organic factors, including oil, peat, coal, wood and OOA, to the total OA mass.


  1. 1.

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

    CAS  Article  Google Scholar 

  2. 2.

    Pope, C. A. III & Dockery, D. W. Health effects of fine particulate air pollution: lines that connect. J. Air Waste Manag. Assoc. 56, 709–742 (2006).

    CAS  Article  Google Scholar 

  3. 3.

    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).

    CAS  Article  Google Scholar 

  4. 4.

    WHO Air Quality Guidelines: Global Update 2005 (World Health Organization, 2006).

  5. 5.

    Harrison, R. M. & Yin, J. Particulate matter in the atmosphere: Which particle properties are important for its effects on health? Sci. Total Environ. 249, 85–101 (2000).

    CAS  Article  Google Scholar 

  6. 6.

    Hao, J., Wang, L., Shen, M., Li, L. & Hu, J. Air quality impacts of power plant emissions in Beijing. Environ. Pollut. 147, 401–408 (2007).

    CAS  Article  Google Scholar 

  7. 7.

    Zhou, Y. et al. The impact of transportation control measures on emission reductions during the 2008 Olympic Games in Beijing, China. Atmos. Environ. 44, 285–293 (2010).

    CAS  Article  Google Scholar 

  8. 8.

    Minguillón, M. C. et al. Effect of ceramic industrial particulate emission control on key components of ambient PM10. J. Environ. Manage. 90, 2558–2567 (2009).

    Article  CAS  Google Scholar 

  9. 9.

    Carvalho, V. S. B. et al. Air quality status and trends over the Metropolitan Area of São Paulo, Brazil as a result of emission control policies. Environ. Sci. Policy 47, 68–79 (2015).

    CAS  Article  Google Scholar 

  10. 10.

    Johnson, T. V. Diesel emission control in review. SAE Int. J. Fuels Lubr. 1, 68–81 (2009).

    CAS  Article  Google Scholar 

  11. 11.

    Mohr, M., Forss, A.-M. & Lehmann, U. Particle emissions from diesel passenger cars equipped with a particle trap in comparison to other technologies. Environ. Sci. Technol. 40, 2375–2383 (2006).

    CAS  Article  Google Scholar 

  12. 12.

    DeWitt, H. L. et al. Near-highway aerosol and gas-phase measurements in a high-diesel environment. Atmos. Chem. Phys. 15, 4373–4387 (2015).

    CAS  Article  Google Scholar 

  13. 13.

    Decarlo, P. F. et al. Investigation of the sources and processing of organic aerosol over the Central Mexican Plateau from aircraft measurements during MILAGRO. Atmos. Chem. Phys. 10, 5257–5280 (2010).

    CAS  Article  Google Scholar 

  14. 14.

    Mohr, C. et al. Identification and quantification of organic aerosol from cooking and other sources in Barcelona using aerosol mass spectrometer data. Atmos. Chem. Phys. 12, 1649–1665 (2012).

    CAS  Article  Google Scholar 

  15. 15.

    Liu, J. et al. Air pollutant emissions from Chinese households: a major and underappreciated ambient pollution source. Proc. Natl Acad. Sci. USA 113, 7756–7761 (2016).

    CAS  Article  Google Scholar 

  16. 16.

    Lu, Z., Zhang, Q. & Streets, D. G. Sulfur dioxide and primary carbonaceous aerosol emissions in China and India, 1996–2010. Atmos. Chem. Phys. 11, 9839–9864 (2011).

    CAS  Article  Google Scholar 

  17. 17.

    Smith, K. R. et al. Millions dead: how do we know and what does it mean? Methods used in the comparative risk assessment of household air pollution. Annu. Rev. Public Health 35, 185–206 (2014).

    Article  Google Scholar 

  18. 18.

    Crippa, M. et al. Wintertime aerosol chemical composition and source apportionment of the organic fraction in the metropolitan area of Paris. Atmos. Chem. Phys. 13, 961–981 (2013).

    Article  CAS  Google Scholar 

  19. 19.

    Allan, J. D. et al. Contributions from transport, solid fuel burning and cooking to primary organic aerosols in two UK cities. Atmos. Chem. Phys. 10, 647–668 (2010).

    CAS  Article  Google Scholar 

  20. 20.

    Xu, L. et al. Wintertime aerosol chemical composition, volatility, and spatial variability in the greater London area. Atmos. Chem. Phys. 16, 1139–1160 (2016).

    CAS  Article  Google Scholar 

  21. 21.

    Young, D. E. et al. Investigating a two-component model of solid fuel organic aerosol in London: processes, PM1 contributions, and seasonality. Atmos. Chem. Phys. 15, 2429–2443 (2015).

    CAS  Article  Google Scholar 

  22. 22.

    Young, D. E. et al. Investigating the annual behaviour of submicron secondary inorganic and organic aerosols in London. Atmos. Chem. Phys. 15, 6351–6366 (2015).

    CAS  Article  Google Scholar 

  23. 23.

    Solomon, P. A. et al. U.S. national PM2.5 chemical speciation monitoring networks-CSN and IMPROVE: description of networks. J. Air Waste Manag. Assoc. 64, 1410–1438 (2014).

    CAS  Article  Google Scholar 

  24. 24.

    Grigas, T. et al. Sophisticated clean air strategies required to mitigate against particulate organic pollution. Sci. Rep. 7, 44737 (2017).

    CAS  Article  Google Scholar 

  25. 25.

    Ng, N. L. et al. An aerosol chemical speciation monitor (ACSM) for routine monitoring of the composition and mass concentrations of ambient aerosol. Aerosol Sci. Technol. 45, 780–794 (2011).

    CAS  Article  Google Scholar 

  26. 26.

    Drinovec, L. et al. The “dual-spot” aethalometer: an improved measurement of aerosol black carbon with real-time loading compensation. Atmos. Meas. Tech. 8, 1965–1979 (2015).

    CAS  Article  Google Scholar 

  27. 27.

    Paatero, P. The multilinear engine-a table-driven, least squares program for solving multilinear problems, including the n-way parallel factor analysis model. J. Comput. Graph. Stat. 8, 854–888 (1999).

    Google Scholar 

  28. 28.

    Paatero, P. Least squares formulation of robust non-negative factor analysis. Chemom. Intell. Lab. Syst. 37, 23–35 (1997).

    CAS  Article  Google Scholar 

  29. 29.

    Canonaco, F., Crippa, M., Slowik, J. G., Baltensperger, U. & Prévôt, A. S. H. SoFi, an IGOR-based interface for the efficient use of the generalized multilinear engine (ME-2) for the source apportionment: ME-2 application to aerosol mass spectrometer data. Atmos. Meas. Tech. 6, 3649–3661 (2013).

    Article  Google Scholar 

  30. 30.

    Lanz, V. A. et al. Source attribution of submicron organic aerosols during wintertime inversions by advanced factor analysis of aerosol mass spectra. Environ. Sci. Tech. 42, 214–220 (2008).

    CAS  Article  Google Scholar 

  31. 31.

    Lin, C. et al. Characterization of primary organic aerosol from domestic wood, peat, and coal burning in Ireland. Environ. Sci. Tech. 51, 10624–10632 (2017).

    CAS  Article  Google Scholar 

  32. 32.

    Sandradewi, J. et al. Using aerosol light absorption measurements for the quantitative determination of wood burning and traffic emission contributions to particulate matter. Environ. Sci. Tech. 42, 3316–3323 (2008).

    CAS  Article  Google Scholar 

  33. 33.

    2011 Population Census Data (Central Statistics Office, accessed on 1 June 2017); https://www.cso.ie

  34. 34.

    2010 Population Census Data (National Bureau of Statistics of China; accessed on 1 May 2018); http://www.stats.gov.cn/english/Statisticaldata/CensusData/

  35. 35.

    Ramanathan, V., & Carmichael, G. Global and regional climate changes due to black carbon. Nat. Geosci. 1, 221–227 (2008).

    CAS  Article  Google Scholar 

  36. 36.

    Bond, T. C. & Bergstrom, R. W. Light absorption by carbonaceous particles: an investigative review. Aerosol Sci. Technol. 40, 27–67 (2006).

    CAS  Article  Google Scholar 

  37. 37.

    Haslett, S. L. et al. Highly controlled, reproducible measurements of aerosol emissions from combustion of a common African biofuel source. Atmos. Chem. Phys. 18, 385–403 (2018).

    CAS  Article  Google Scholar 

  38. 38.

    Ng, N. L. et al. Real-time methods for estimating organic component mass concentrations from aerosol mass spectrometer data. Environ. Sci. Tech. 45, 910–916 (2011).

    CAS  Article  Google Scholar 

  39. 39.

    Alfarra, M. R. et al. Identification of the mass spectral signature of organic aerosols from wood burning emissions. Environ. Sci. Tech. 41, 5770–5777 (2007).

    CAS  Article  Google Scholar 

  40. 40.

    Ryer, T. A., & Langer, A. W. Thickness change involved in the peat-to-coal transformation for a bituminous coal of Cretaceous age in central Utah. J. Sediment. Res. 50, 987–992 (1980).

    Google Scholar 

  41. 41.

    Ng, N. L. et al. Organic aerosol components observed in Northern Hemispheric datasets from aerosol mass spectrometry. Atmos. Chem. Phys. 10, 4625–4641 (2010).

    CAS  Article  Google Scholar 

  42. 42.

    Jimenez, J. L. et al. Evolution of organic aerosols in the atmosphere. Science 326, 1525–1529 (2009).

    CAS  Article  Google Scholar 

  43. 43.

    Tiitta, P. et al. Transformation of logwood combustion emissions in a smog chamber: formation of secondary organic aerosol and changes in the primary organic aerosol upon daytime and nighttime aging. Atmos. Chem. Phys. 16, 13251–13269 (2016).

    CAS  Article  Google Scholar 

  44. 44.

    Favez, O. et al. Inter-comparison of source apportionment models for the estimation of wood burning aerosols during wintertime in an Alpine city (Grenoble, France). Atmos. Chem. Phys. 10, 5295–5314 (2010).

    CAS  Article  Google Scholar 

  45. 45.

    Crilley, L. R. et al. Sources and contributions of wood smoke during winter in London: assessing local and regional influences. Atmos. Chem. Phys. 15, 3149–3171 (2015).

    CAS  Article  Google Scholar 

  46. 46.

    Mohr, C. et al. Contribution of nitrated phenols to wood burning brown carbon light absorption in Detling, United Kingdom during winter time. Environ. Sci. Technol. 47, 6316–6324 (2013).

    CAS  Article  Google Scholar 

  47. 47.

    Zotter, P. et al. Evaluation of the absorption Ångström exponents for traffic and wood burning in the aethalometer-based source apportionment using radiocarbon measurements of ambient aerosol. Atmos. Chem. Phys. 17, 4229–4249 (2017).

    CAS  Article  Google Scholar 

  48. 48.

    Clancy, L., Goodman, P., Sinclair, H. & Dockery, D. W. Effect of air-pollution control on death rates in Dublin, Ireland: an intervention study. Lancet 360, 1210–1214 (2002).

    Article  Google Scholar 

  49. 49.

    Goodman, P. G., Rich, D. Q., Zeka, A., Clancy, L. & Dockery, D. W. Effect of air pollution controls on black smoke and sulfur dioxide concentrations across Ireland. J. Air Waste Manag. Assoc. 59, 207–213 (2009).

    CAS  Article  Google Scholar 

  50. 50.

    Directive 2009/28/EC of the European Parliament and of the Council of 23 April 2009 (European Union, 2009); https://eur-lex.europa.eu/eli/dir/2009/28/oj

  51. 51.

    Driving Europe’s transition to a low-carbon economy. European Commission (20 July 2016).

  52. 52.

    Global Wood Pellet Industry and Trade Study 2017 (International Energy Agency Bioenergy, accessed on 1 June 2017).

  53. 53.

    Biomass for Electricity and Heating (European Parliament, 2015).

  54. 54.

    Global Energy Data (International Energy Agency, accessed on 1 June 2017); http://www.iea.org

  55. 55.

    Martucci, G., Milroy, C. & O’Dowd, C. D. Detection of cloud-base height using Jenoptik CHM15K and Vaisala CL31 ceilometers. J. Atmos. Ocean. Tech. 27, 305–318 (2010).

    Article  Google Scholar 

  56. 56.

    Allan, J. D. et al. A generalised method for the extraction of chemically resolved mass spectra from Aerodyne aerosol mass spectrometer data. J. Aerosol Sci. 35, 909–922 (2004).

    CAS  Article  Google Scholar 

  57. 57.

    Ulbrich, I. M., Canagaratna, M. R., Zhang, Q., Worsnop, D. R. & Jimenez, J. L. Interpretation of organic components from positive matrix factorization of aerosol mass spectrometric data. Atmos. Chem. Phys. 9, 2891–2918 (2009).

    CAS  Article  Google Scholar 

  58. 58.

    Garg, S. et al. Limitation of the use of the absorption Angstrom exponent for source apportionment of equivalent black carbon: a case study from the North West Indo-Gangetic Plain. Environ. Sci. Tech. 50, 814–824 (2016).

    CAS  Article  Google Scholar 

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This work was funded by the Irish Environmental Protection Agency (AEROSOURCE, 529 2016-CCRP-MS-31; SAPPHIRE, 2013-EH-MS-15), Science Foundation Ireland (MaREI award 14-SP-2740), the European Commission, the National Natural Science Foundation of China 530 (NSFC) under grant no. 91644219, China Scholarship Council (CSC, no. 201506310020) 531 and the Irish Research Council (GOIPG/2015/3051). We also acknowledge Met Éireann for ceilometer and meteorological data.

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J.O., D.C., M.R., M.C.F., J.W., R.-J.H. and C.O’D. conceived and designed the experiments; C.L., J.O., D.C. and P.B. performed the experiments; C.L., R.-J.H., J.O., P.B., J.P. and C.O’D. analysed the data; C.L. and C.O’D. wrote the paper with input from all co-authors.

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Correspondence to Ru-Jin Huang or Colin O’Dowd.

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Supplementary Figures 1-9, Supplementary Tables 1-5, Supplementary Methods 1-2, Supplementary References 1-7

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Lin, C., Huang, R., Ceburnis, D. et al. Extreme air pollution from residential solid fuel burning. Nat Sustain 1, 512–517 (2018). https://doi.org/10.1038/s41893-018-0125-x

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