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Relocate 10 billion livestock to reduce harmful nitrogen pollution exposure for 90% of China’s population

Nature Food volume 3, pages 152–160 (2022)Cite this article

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Abstract

Livestock production in China is increasingly located near urban areas, exposing human populations to nitrogen pollution via air and water. Here we analyse livestock and human population data across 2,300 Chinese counties to project the impact of alternative livestock distributions on nitrogen emissions. In 2012 almost half of China’s livestock production occurred in peri-urban regions, exposing 60% of the Chinese population to ammonia emissions exceeding UN guidelines. Relocating 5 billion animals by 2050 according to crop–livestock integration criteria could reduce nitrogen emissions by two-thirds and halve the number of people exposed to high ammonia emissions. Relocating 10 billion animals away from southern and eastern China could reduce ammonia exposure for 90% of China’s population. Spatial planning can therefore serve as a powerful policy instrument to tackle nitrogen pollution and exposure of humans to ammonia.

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Fig. 1: Geographic distribution of livestock production.
Fig. 2: Relationships between livestock density, NH3 emissions and nitrogen losses in 1990 and 2012.
Fig. 3: Nitrogen use, surplus and loss, and NH3 emissions for various scenarios.
Fig. 4: Livestock density, NH3 emission intensity and nitrogen losses to watercourses in 2050 for five scenarios.
Fig. 5: Suggested scheme for selecting criteria, setting priorities and optimizing the spatial planning of livestock production in cities and counties in China.

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All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.

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Acknowledgements

This work was supported by the Nature Science Foundation of China (31872403, 32002138, 71961137011, 31801941, 31972517); the Youth Innovation Promotion Association, Chinese Academy of Sciences (2019101); the National Social Science Fund of China (20BZZ040); Key Laboratory of Agricultural Water Resources-CAS (ZD201802); the Outstanding Young Scientists Project of Natural Science Foundation of Hebei (C2019503054); Key R&D Program of Hebei (21327507D); Hebei Dairy Cattle Innovation Team of Modern Agro-industry Technology Research System HBCT2018120206. Z.B. thanks the FABLE Consortium, Food and Land Use (FOLU) Coalition and the Norwegian Climate and Forest Initiative (NICFI). This publication contributes to UNCNET, a project funded under the JPI Urban Europe/China collaboration (870234, FFG, Austria).

Author information

Author notes

  1. These authors contributed equally: Zhaohai Bai, Xiangwen Fan, Xinpeng Jin.

Authors and Affiliations

  1. Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Soil Ecology, Center for Agricultural Resources Research, Institute of Genetic and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China

    Zhaohai Bai, Xiangwen Fan, Xinpeng Jin, Chunsheng Hu & Lin Ma

  2. Wageningen University, Soil Quality Group, Wageningen, Netherlands

    Zhaohai Bai & Oene Oenema

  3. Xiongan Institute of Innovation, Chinese Academy of Sciences, Beijing, China

    Zhaohai Bai

  4. School of Land Science and Space Planning, Hebei GEO University, Shijiazhuang, China

    Zhanqing Zhao

  5. Zhejiang University City College, Hangzhou, China

    Yan Wu

  6. Wageningen Environmental Research, Wageningen, Netherlands

    Gerard Velthof

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All authors contributed equally to the design, implementation, and analysis of this study.

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Extended data

Extended Data Fig. 1 Contribution of each counties group to total livestock population (a), manure nitrogen (N) excretions, synthetic fertilizer N application (c) and N surplus of cropland (d) according to their livestock density in 1990, 2012 and different scenarios in 2050. Level represents the livestock density, in LU ha-1.

Note: BAU is business as usual scenario which follows the SSP2 storyline; SNT, is south to north transfer of pig production scenario; ITI is the integrated technology improvement scenario; SP-NH3 is livestock spatial planning with NH3 criteria scenario; and SP-CLI is livestock spatial planning with crop–livestock integration criteria.

Extended Data Fig. 2

Ratio of livestock manure N excretions and crop N uptake at county level in 1992 (a) and 2012 (b), and ratio of synthetic fertilizer N input and crop N uptake at county level in 1992 (c) and 2012 (d).

Extended Data Fig. 3

Mapping the manure N and crop N ratio in United States in 1992 (a) and 2012 (b), and synthetic fertilizer use in 1992 (c) and 2012 (d).

Extended Data Fig. 4

Spatial distributions of the correlation coefficients of the annual mean PM2.5 concentration in the air and total synthetic fertilizer N use per county level (a), of the PM2.5 concentration with total livestock N excretion (b), with annual mean NOX concentration in air (c), with annual mean SO2 concentration in air (d), with annual mean air temperature (e) and with annual mean wind speed (f) to in China in 2012. Note: value indicates the slope of simulated correlations (regression coefficients), while the significance was represents by color.

Extended Data Fig. 5 Ammonia emissions from the food system (a), and manure N surplus due to uneven distribution of crop–livestock production when considering the bioavailability of manure N as criterion for estimating the N surplus in 1990, 2012 and for different scenarios in 2050.

Note: Definition of scenarios see Extended Data Fig. 1. The bioavailability of different organic resources under improved management see Jin et al., 2020.

Extended Data Fig. 6 Illustration of the relocation of livestock following the optimization of livestock spatial planning scenarios – SP-NH3 in 2050.

Arrows indicate the likely movement of animals from southeast to west and northwest, mainly via shutdown farms in the move out regions and build new farms in the move in regions.

Extended Data Fig. 7 Illustration of the relocation of livestock following within or outside of the provincial border under the livestock spatial planning scenarios – SP-NH3 (a) and SP-CLI (b) in 2050.

Note: Definition of scenarios see Extended Data Fig. 1.

Extended Data Fig. 8 Illustration of the relocation of livestock following the optimization of livestock spatial planning scenarios – SP-CLI in 2050.

Note: Arrows indicate the likely movement of animals from southeast to west and northwest, mainly via shutdown farms in the move out regions and build new farms in the move in regions.

Extended Data Fig. 9 County level information about total livestock unit in the business as usual (BAU) scenario (a), south-north transfer of pig production (SNT) scenario (b) and spatial planning under the NH3 emission criteria (SP-NH3) scenario (c), and spatial planning under the crop–livestock integration scenario (SP-CLI) in 2050.

Note: Definition of scenarios see Extended Data Fig. 1.

Extended Data Fig. 10

Short-term changes of livestock production distribution between 2012 and 2017, and expansion plan of top pig production companies in 2020.

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Supplementary methods and discussion, Figures 1–10 and Tables 1 and 2.

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Bai, Z., Fan, X., Jin, X. et al. Relocate 10 billion livestock to reduce harmful nitrogen pollution exposure for 90% of China’s population. Nat Food 3, 152–160 (2022). https://doi.org/10.1038/s43016-021-00453-z

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