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Dietary shifts can reduce premature deaths related to particulate matter pollution in China

Nature Food volume 2, pages 997–1004 (2021)Cite this article

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A Publisher Correction to this article was published on 07 January 2022

This article has been updated

Abstract

Shifting towards more meat-intensive diets may have indirect health consequences through environmental degradation. Here we examine how trends in dietary patterns in China over 1980–2010 have worsened fine particulate matter (PM2.5) pollution, thereby inducing indirect health impacts. We show that changes in dietary composition alone, mainly by driving the rising demands for meat and animal feed, have enhanced ammonia (NH3) emissions from Chinese agriculture by 63% and increased annual PM2.5 by up to ~10 µg m–3 (~20% of total PM2.5 increase) over the period. Such effects are more than double that driven by increased food production solely due to population growth. Shifting the current diet towards a less meat-intensive recommended diet can decrease NH3 emission by ~17% and PM2.5 by 2–6 µg m–3, and avoid ~75,000 Chinese annual premature deaths related to PM2.5.

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Fig. 1: Trends in daily per capita food consumption.
Fig. 2: Trends in national food production and utilization.
Fig. 3: Worsening of PM2.5 air quality due to dietary changes.
Fig. 4: Indirect health cost of dietary changes related to PM2.5 pollution.
Fig. 5: Environmental and indirect health benefits of less meat-intensive diets.

Data availability

The datasets generated during this study are available on the Zenodo repository (https://doi.org/10.5281/zenodo.5643549). Source data are provided with this paper.

Code availability

Programming language R version 4.1.0 (ref. 57) was used for analysis and visualization in this study. A publicly released map of China was obtained from the National Geomatics Center of China (http://www.ngcc.cn/ngcc/html/1/391/392/16114.html), and all map-related operations were performed using programming language R version 4.1.0 (ref. 57). The R code is available on the Zenodo repository (https://doi.org/10.5281/zenodo.5643549). The code for the GEOS-Chem chemical transport model is available on the GitHub repository (https://github.com/geoschem/geos-chem).

Change history

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Acknowledgements

This work was supported by funding (MD18518) from the CUHK–Exeter Joint Centre for Environmental Sustainability and Resilience (ENSURE) awarded to the whole team, Research Grants Council (RGC) General Research Fund (14323116) awarded to A.P.K.T., and RGC Area of Excellence Scheme (AoE/M-403/16) awarded to H.-M.L.

Author information

Author notes

  1. Xueying Liu

    Present address: Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, USA

Authors and Affiliations

  1. Earth System Science Programme and Graduate Division of Earth and Atmospheric Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong SAR, China

    Xueying Liu & Amos P. K. Tai

  2. Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong SAR, China

    Amos P. K. Tai & Hon-Ming Lam

  3. Centre for Soybean Research, State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong SAR, China

    Amos P. K. Tai & Hon-Ming Lam

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

    Youfan Chen & Lin Zhang

  5. Department of Mathematics, University of Exeter, Exeter, UK

    Gavin Shaddick

  6. Joint Centre for Excellence in Environmental Intelligence, Met Office, University of Exeter, Exeter, UK

    Gavin Shaddick

  7. Environment and Sustainability Institute, University of Exeter, Penryn, UK

    Xiaoyu Yan

  8. School of Life Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong SAR, China

    Hon-Ming Lam

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Contributions

A.P.K.T. and H.-M.L. conceived the concepts and strategies. A.P.K.T. devised the overall methodology and supervised the writing of the manuscript. X.L. processed and analysed food and agricultural data, conducted GEOS-Chem simulations, analysed results and drafted the manuscript. Y.C. and L.Z. provided the NH3 emission model and scenarios. G.S. provided PM2.5 for 2010 at 0.1° × 0.1° spatial resolution, and participated in the writing of the manuscript. X.Y. and H.-M.L. participated in the discussion and writing of the manuscript.

Corresponding author

Correspondence to Amos P. K. Tai.

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Nature Food thanks Eri Saikawa, Matthew Hayek and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Information

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Liu, X., Tai, A.P.K., Chen, Y. et al. Dietary shifts can reduce premature deaths related to particulate matter pollution in China. Nat Food 2, 997–1004 (2021). https://doi.org/10.1038/s43016-021-00430-6

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