Global climate forcing of aerosols embodied in international trade

Journal name:
Nature Geoscience
Volume:
9,
Pages:
790–794
Year published:
DOI:
doi:10.1038/ngeo2798
Received
Accepted
Published online

Abstract

International trade separates regions consuming goods and services from regions where goods and related aerosol pollution are produced. Yet the role of trade in aerosol climate forcing attributed to different regions has never been quantified. Here, we contrast the direct radiative forcing of aerosols related to regions’ consumption of goods and services against the forcing due to emissions produced in each region. Aerosols assessed include black carbon, primary organic aerosol, and secondary inorganic aerosols, including sulfate, nitrate and ammonium. We find that global aerosol radiative forcing due to emissions produced in East Asia is much stronger than the forcing related to goods and services ultimately consumed in that region because of its large net export of emissions-intensive goods. The opposite is true for net importers such as Western Europe and North America: global radiative forcing related to consumption is much greater than the forcing due to emissions produced in these regions. Overall, trade is associated with a shift of radiative forcing from net importing to net exporting regions. Compared to greenhouse gases such as carbon dioxide, the short atmospheric lifetimes of aerosols cause large localized differences between consumption- and production-related radiative forcing. International efforts to reduce emissions in the exporting countries will help alleviate trade-related climate and health impacts of aerosols while lowering global emissions.

At a glance

Figures

  1. Net aerosol emissions embodied in trade.
    Figure 1: Net aerosol emissions embodied in trade.

    EcEp for ten regions and six aerosol-related species; the values for Rest of the World (including Greenland and the Antarctic) are negligible and omitted here. For a given region, the percentage value indicates the relative change from Ep to Ec, and the value in the parenthesis is the associated error (2σ).

  2. Global differences between consumption- and production-based radiative forcing (RFc - RFp).
    Figure 2: Global differences between consumption- and production-based radiative forcing (RFc − RFp).

    The three columns refer to RF contributed by East Asia, North America and Western Europe, respectively.

  3. Global production- and consumption-based radiative forcing of SIOA + POA and BC for all regions except Rest of the World.
    Figure 3: Global production- and consumption-based radiative forcing of SIOA + POA and BC for all regions except Rest of the World.

    a,b, RFp (upper bar) and RFc (lower bar) contributed by individual regions, summed from the RF imposed above (grey) and outside (blue in a and red in b) their territories. For a given region, the percentage value indicates the relative change from RFp to RFc, and the value in the parenthesis is the associated error (2σ). c,d, Similar to a,b, but highlighting the percentages of RF imposed above (grey) and outside (blue in c and red in d) the territory of a given region.

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Author information

  1. These authors contributed equally to this work.

    • Jintai Lin &
    • Dan Tong

Affiliations

  1. Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China

    • Jintai Lin,
    • Ruijing Ni,
    • Xiaoxiao Tan,
    • Yingying Yan,
    • Yongyun Hu &
    • Jing Li
  2. Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China

    • Dan Tong,
    • Hongyan Zhao,
    • Tong Feng,
    • Qiang Zhang,
    • Xujia Jiang &
    • Guannan Geng
  3. Department of Earth System Science, University of California, Irvine, California 92697, USA

    • Steven Davis
  4. Department of Atmospheric & Oceanic Sciences, McGill University, Montreal, Quebec H3A 0B9, Canada

    • Xiaoxiao Tan &
    • Yi Huang
  5. Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey 08544, USA

    • Da Pan
  6. Energy Systems Division, Argonne National Laboratory, Argonne, Illinois 60439, USA

    • Zifeng Lu &
    • David Streets
  7. Resnick Sustainability Institute, California Institute of Technology, Pasadena, California 91125, USA

    • Zhu Liu
  8. State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China

    • Kebin He
  9. Collaborative Innovation Center for Regional Environmental Quality, Beijing 100084, China

    • Kebin He
  10. School of International Development, University of East Anglia, Norwich NR4 7TJ, UK

    • Dabo Guan

Contributions

J.L., Q.Z. and Y.Huang conceived the research. D.T., D.P., H.Z., T.F., Z.L., D.S. and Q.Z. calculated the emissions. R.N., Y.Y. and J.L. conducted chemical transport model simulations. X.T., R.N., Y.Huang and J.L. conducted radiative transfer model simulations. J.L., S.D., Y.Huang and R.N. led the analysis and writing. All authors contributed to the writing.

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The authors declare no competing financial interests.

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