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Air pollution reduction and climate co-benefits in China’s industries

Nature Sustainability volume 4, pages 417–425 (2021)Cite this article

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An Author Correction to this article was published on 15 January 2021

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Abstract

Air pollution reduction policies can simultaneously mitigate CO2 emissions in the industrial sector, but the extent of these co-benefits is understudied. We analyse the potential co-benefits for SO2, NOx, particulate matter (PM) and CO2 emission reduction in major industrial sectors in China. We construct and analyse a firm-level database covering nearly 80,000 observations and use scenario simulations to estimate the co-benefits. The findings show that substantial co-benefits could be achieved with three specific interventions. Energy intensity improvement can reduce SO2, NOx, PM and CO2 emissions for non-power sectors by 26–44%, 19–44%, 25–46% and 18–50%, respectively. Reductions from scale structure adjustment such as phasing out small firms and developing large ones can amount to 1–8%, 1–6%, 2–20% and 0.2–3%. Electrification can reduce emissions by 19–25%, 4–28%, 20–29% and 11–12% if the share of electricity generated from non-fossil fuel sources is 70%. Since firm heterogeneity is essential to realize the co-benefits and directly determines the magnitudes of these benefits, stricter and sensible environmental policies targeting industrial firms can accelerate China’s sustainable transformation.

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Fig. 1: Drivers of SO2 reduction in the main industrial sectors.
Fig. 2: Direct co-benefits through energy intensity adjustment.
Fig. 3: Indirect co-benefits through scale structure adjustment.
Fig. 4: Indirect co-benefits of electrification.

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Data availability

The firm-level emission database that supports the findings of this study is available from H.Q.’s GitHub repository (https://github.com/qianhaoqi/NS-co-benefit). Source data are provided with this paper.

Code availability

The code that supports the findings of this study is available from H.Q.’s GitHub repository (https://github.com/qianhaoqi/NS-co-benefit).

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (grant nos 71925010, 71703027, 71904125, 72088101 and 71690244), the National Key R&D Program of China (grant nos 2018YFC1509007 and 2016YFA0602604) and the Shanghai Sailing Program (grant no. 18YF1417500).

Author information

Author notes

  1. These authors contributed equally: Haoqi Qian, Shaodan Xu.

Authors and Affiliations

  1. Institute for Global Public Policy, Fudan University, Shanghai, China

    Haoqi Qian

  2. LSE-Fudan Research Centre for Global Public Policy, Fudan University, Shanghai, China

    Haoqi Qian

  3. School of Economics, Fudan University, Shanghai, China

    Shaodan Xu, Feizhou Ren & Libo Wu

  4. Center for Energy Economics and Strategy Studies, Fudan University, Shanghai, China

    Shaodan Xu, Feizhou Ren & Libo Wu

  5. School of Economics and Management, Tsinghua University, Beijing, China

    Jing Cao

  6. School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, China

    Wendong Wei

  7. SJTU-UNIDO Joint Institute of Inclusive and Sustainable Industrial Development, Shanghai Jiao Tong University, Shanghai, China

    Wendong Wei

  8. Bartlett School of Construction and Project Management, University College London, London, UK

    Jing Meng

  9. Institute for Big Data, Fudan University, Shanghai, China

    Libo Wu

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Contributions

H.Q., W.W., J.M. and L.W. conceived the study. J.C. and F.R. provided the energy and emission data. H.Q. and S.X. performed the analysis. All authors (H.Q., S.X., J.C., F.R., W.W., J.M. and L.W.) interpreted the data. H.Q. and S.X. prepared the manuscript. W.W., J.M. and L.W. revised the manuscript.

Corresponding authors

Correspondence to Wendong Wei, Jing Meng or Libo Wu.

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The authors declare no competing interests.

Additional information

Peer review information Nature Sustainability thanks Hidemichi Fujii and Shaohui Zhang for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Each factor’s contribution to pollutant emission for each industrial sector based on LMDI decompositions (between 2011 and 2014).

A red block indicates the emission increase caused by each factor; a blue block shows the emission decrease caused by each factor. a, Drivers for SO2 emission reduction. b, Drivers for NOx emission reduction. c, Drivers for PM emission reduction.

Source data

Extended Data Fig. 2 Comparison of the estimated direct co-benefits by using different benchmarks.

a, SO2 emissions reduction. b, NOx emissions reduction. c, PM emissions reduction. d, CO2 emissions reduction. Different markers stand for different setting up for benchmarks.

Source data

Extended Data Fig. 3 Indirect co-benefits through electrification (setting the ratio of non-fossil fuel generation as 0.3).

a, SO2 emissions reduction. b, NOx emissions reduction. c, PM emissions reduction. d, CO2 emissions reduction. The horizontal axes are percentages of the fossil fuels that are assumed to be replaced by electricity. Percentages are from 5 to 30, with an interval of 5. This figure provides co-benefits estimations for the assumption that ratio of non-fossil fuel in electricity generation structure is 30%.

Source data

Extended Data Fig. 4 Indirect co-benefits through electrification (setting the ratio of non-fossil fuel generation as 0.5).

a, SO2 emissions reduction. b, NOx emissions reduction. c, PM emissions reduction. d, CO2 emissions reduction. The horizontal axes are percentages of the fossil fuels that are assumed to be replaced by electricity. Percentages are from 5 to 30, with an interval of 5. This figure provides co-benefits estimations for the assumption that ratio of non-fossil fuel in electricity generation structure is 50%.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–25, Tables 1–6 and Notes 1–4.

Reporting Summary

Supplementary Data 1

The firm-level emission database that supports the findings of this study. This database is also available from H.Q.’s GitHub repository (https://github.com/qianhaoqi/NS-co-benefit).

Source data

Source Data Fig. 1

Data for the plots in Fig. 1.

Source Data Fig. 2

Data for the plots in Fig. 2.

Source Data Fig. 3

Data for the plots in Fig. 3.

Source Data Fig. 4

Data for the plots in Fig. 4.

Source Data Extended Data Fig. 1

Data for the plots in Extended Data Fig. 1.

Source Data Extended Data Fig. 2

Data for the plots in Extended Data Fig. 2.

Source Data Extended Data Fig. 3

Data for the plots in Extended Data Fig. 3.

Source Data Extended Data Fig. 4

Data for the plots in Extended Data Fig. 4.

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Qian, H., Xu, S., Cao, J. et al. Air pollution reduction and climate co-benefits in China’s industries. Nat Sustain 4, 417–425 (2021). https://doi.org/10.1038/s41893-020-00669-0

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