Abstract

Rapid industrialization and urbanization in developing countries has led to an increase in air pollution, along a similar trajectory to that previously experienced by the developed nations1. In China, particulate pollution is a serious environmental problem that is influencing air quality, regional and global climates, and human health2,3. In response to the extremely severe and persistent haze pollution experienced by about 800 million people during the first quarter of 2013 (refs 4, 5), the Chinese State Council announced its aim to reduce concentrations of PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 micrometres) by up to 25 per cent relative to 2012 levels by 2017 (ref. 6). Such efforts however require elucidation of the factors governing the abundance and composition of PM2.5, which remain poorly constrained in China3,7,8. Here we combine a comprehensive set of novel and state-of-the-art offline analytical approaches and statistical techniques to investigate the chemical nature and sources of particulate matter at urban locations in Beijing, Shanghai, Guangzhou and Xi’an during January 2013. We find that the severe haze pollution event was driven to a large extent by secondary aerosol formation, which contributed 30–77 per cent and 44–71 per cent (average for all four cities) of PM2.5 and of organic aerosol, respectively. On average, the contribution of secondary organic aerosol (SOA) and secondary inorganic aerosol (SIA) are found to be of similar importance (SOA/SIA ratios range from 0.6 to 1.4). Our results suggest that, in addition to mitigating primary particulate emissions, reducing the emissions of secondary aerosol precursors from, for example, fossil fuel combustion and biomass burning is likely to be important for controlling China’s PM2.5 levels and for reducing the environmental, economic and health impacts resulting from particulate pollution.

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Acknowledgements

The research leading to these results received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 290605, the Swiss National Science Foundation (SAPMAV, no.200021_13016, WOOSHI, no. 200021L_140590, and Ambizione, PZ00P2_131673), the Swiss Competence Centers Environment and Sustainability as well as Energy and Mobility under project OPTIWARES, the National Science Foundation of China (no. 40925009), the “Strategic Priority Research Program” of the Chinese Academy of Sciences (XDA05100402), and the Helmholtz Virtual Institute of Complex Molecular Systems in Environmental Health – Aerosol and Health (HICE). The help of G. Salazar (University of Bern) during 14C analysis is acknowledged.

Author information

Author notes

    • Ru-Jin Huang
    •  & Imad El Haddad

    These authors contributed equally to this work.

    • Monica Crippa

    Present address: European Commission, Joint Research Centre, Institute for Environment and Sustainability, Air and Climate Unit, Via Fermi, 2749, 21027 Ispra, Italy.

Affiliations

  1. Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), 5232 Villigen, Switzerland

    • Ru-Jin Huang
    • , Carlo Bozzetti
    • , Kaspar R. Daellenbach
    • , Jay G. Slowik
    • , Stephen M. Platt
    • , Francesco Canonaco
    • , Peter Zotter
    • , Robert Wolf
    • , Simone M. Pieber
    • , Emily A. Bruns
    • , Monica Crippa
    • , Giancarlo Ciarelli
    • , Urs Baltensperger
    • , Imad El Haddad
    •  & André S. H. Prévôt
  2. State Key Laboratory of Loess and Quaternary Geology (SKLLQG), and Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710075, China

    • Ru-Jin Huang
    • , Jun-Ji Cao
    • , Yongming Han
    •  & Zhisheng An
  3. Department of Chemistry and Biochemistry, and Oeschger Centre for Climate Change Research, University of Bern, 3012 Bern, Switzerland

    • Yanlin Zhang
    • , Margit Schwikowski
    •  & Sönke Szidat
  4. Laboratory of Radiochemistry and Environmental Chemistry, Paul Scherrer Institute (PSI), 5232 Villigen, Switzerland

    • Yanlin Zhang
    •  & Margit Schwikowski
  5. The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China

    • Kin-Fai Ho
  6. Department of Earth and Environmental Sciences, University of Milano Bicocca, Piazza della Scienza 1, Milan 20126, Italy

    • Andrea Piazzalunga
  7. Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Joint Mass Spectrometry Centre, Cooperation Group Comprehensive Molecular Analytics and Helmholtz Virtual Institute of Complex Molecular Systems in Environmental Health — Aerosol and Health (HICE), 85764 Neuherberg, Germany

    • Gülcin Abbaszade
    • , Jürgen Schnelle-Kreis
    •  & Ralf Zimmermann
  8. University of Rostock, Joint Mass Spectrometry Centre, Institute of Chemistry, Analytical Chemistry, 18015 Rostock, Germany

    • Ralf Zimmermann

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Contributions

R.-J.H., I.E.H. and C.B. wrote the paper. R.-J.H., J.-J.C. and A.S.H.P. designed the study. R.-J.H., I.E.H., C.B. and K.R.D. performed the offline AMS analysis. Y.Z., P.Z. and S. S. performed the 14C analysis. M.S. performed the IC analysis. G.A. and J.S.-K. performed the TD-GC-MS analysis. R.-J.H., I.E.H., C.B. and A.S.H.P. analysed the data. All authors reviewed and commented on the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Jun-Ji Cao or André S. H. Prévôt.

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains additional information on the sample collection and sampling sites (Section 1); details of the chemical analysis (Section 2); extensive evaluation of a set of environmentally optimal solutions for source apportionment of PM2.5 and OC using the CMB and ME-2 models (Section 3); evaluation of model uncertainty and the sensitivity of the results to model inputs as well as the estimate of the contribution of fossil and non-fossil sources to secondary organic aerosol (Section 4); examination of potentially unidentified sources (Section 5); representativeness of the measurement sites (Section 6) and relevance of SOA formation (Section 7). The Supplementary Information also includes Supplementary Figures S1-S30, Supplementary Tables S1-S3 and additional references.

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