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A large but transient carbon sink from urbanization and rural depopulation in China

Nature Sustainability volume 5, pages 321–328 (2022)Cite this article

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Abstract

China has experienced unprecedented urbanization and associated rural depopulation during recent decades alongside a massive increase in the total population. By using satellite and demographical datasets, we here test the hypothesis that urbanization and carbon neutrality are not mutually exclusive and that sustainably managed urbanization may even be an integral part of the pathway to reduce atmospheric CO2. We show that, although urban expansion caused an initial aboveground carbon loss of −0.02 PgC during 2002–2010, urban greening compensates these original losses with an overall balance of +0.03 PgC in urban areas during 2002–2019. We further show that a maximum increase in aboveground carbon stocks was observed at intermediate distances to rural settlements (2–4 km), reflecting the decreased pressure on natural resources. Consequently, rural areas experiencing depopulation (−14 million people yr−1) coincided with an extensive aboveground carbon sink of 0.28 ± 0.05 PgC yr−1 during 2002–2019, while at the same time only a slight decline in cropland areas (4%) was observed. However, tree cover growth saturation limits the carbon removal capacity of forests and only a decrease in CO2 emissions from fossil fuel burning will make the aim of carbon neutrality achievable.

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Fig. 1: Population change and urbanization in China.
Fig. 2: Land use/cover systems and MODIS carbon density change in China.
Fig. 3: Population migration and aboveground carbon density change in relation to distance to settlements.
Fig. 4: Comparison of tree cover, carbon density and NTL for grouped changes of population density in China for different periods.
Fig. 5: Land cover transitions and fossil carbon emissions in China.

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Data availability

Population density data from WorldPop (2000–2020) can be obtained at https://www.worldpop.org. Demographical data are accessible from the National Bureau of Statistics of the People’s Republic of China. Tree cover from AVHRR (VCF5KYR) can be downloaded from https://search.earthdata.nasa.gov. Tree cover from MODIS (MOD44B) is available from Google Earth Engine. DMSP/OLS Nighttime Lights Time Series Version 4 can be download from https://ngdc.noaa.gov/eog/dmsp/downloadV4composites.html. GlobaLand30 land cover dataset is available at http://www.globallandcover.com/home_en.html. ESA-CCI land cover dataset is available at http://maps.elie.ucl.ac.be/CCI/viewer/. The MODIS carbon density map and mobile phone location-based dataset are available on request.

Code availability

No custom codes were used. The codes used to analyse the data and create the plot are available on request.

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Acknowledgements

X.Z. is funded by the National Natural Science Foundation of China (41930652) and China Scholarship Council (CSC, grant no. 201904910835). M.B. received funding from the DFF Sapere Aude (9064-00049B) and the European Research Council under the European Union’s Horizon 2020 Research and Innovation Programme (TOFDRY, grant agreement no. 947757). X.T. is funded by a Marie Curie fellowship (795970). Y.Y. is funded by the National Natural Science Foundation of China (41930652, U20A2048). X.X. is supported by the US National Science Foundation (1911955). R.F. is supported by the Villum Foundation through the project ‘Deep Learning and Remote Sensing for Unlocking Global Ecosystem Resource Dynamics’ (DeReEco) (project no. 34306).

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Authors and Affiliations

  1. Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark

    Xiaoxin Zhang, Martin Brandt, Xiaowei Tong, Wenmin Zhang & Rasmus Fensholt

  2. Laboratoire des Sciences du Climat et de l’Environnement, CEA-CNRS-UVSQ, CE Orme des Merisiers, Gif sur Yvette, France

    Philippe Ciais

  3. Key Laboratory for Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China

    Yuemin Yue & Kelin Wang

  4. Huanjiang Observation and Research Station for Karst Ecosystem, Chinese Academy of Sciences, Huanjiang, China

    Yuemin Yue & Kelin Wang

  5. Department of Microbiology and Plant Biology, Center for Earth Observation and Modeling, University of Oklahoma, Norman, OK, USA

    Xiangming Xiao

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Contributions

X.Z., M.B. and Y.Y. designed the research. X.Z. conducted experiments and analysis. MODIS C density was prepared by M.B. and X.T. Mobile phone location dataset was prepared and provided by Y.Y. and K.W. The paper was drafted by X.Z., M.B., P.C., X.T. and R.F. All co-authors discussed the results and contributed to the interpretation and revision of the final manuscript.

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Correspondence to Xiaowei Tong or Yuemin Yue.

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Nature Sustainability thanks Richard Houghton, Zhu Liu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Dynamic of tree cover in China.

Dynamic of tree cover in China. a, AVHRR VCF5KYR tree cover for 20011; b, trends of AVHRR VCF5KYR tree cover before 20001; c, trends of AVHRR VCF5KYR tree cover after 20011; d, Trends of MOD44B tree cover after 2001.

Extended Data Fig. 2 Land cover transition in China from GlobeLand30 during 2000–2020.

Land cover transition in China from GlobeLand30 during 2000–2020.

Extended Data Fig. 3 Topography and vegetation trends.

Topography and vegetation trends. a, Topography; b, significant change (P < 0.05) in tree cover, trends of short vegetation from AVHRR VCF5KYR1, and elevation for 1990-2016.

Extended Data Fig. 4 Trends and temporal profiles separated in groups of population density change for 2000–2020.

Trends and temporal profiles separated in groups of population density change for 2000–2020. a, Spatial distribution of each group of population density change based on WorldPop population density (2000,2020); b, MODIS-based aboveground carbon density; c, MOD44B tree cover; d, AVHRR VCF5KYR tree cover; e, calibrated nighttime light from DMSP/OLS; f, yearly mean Standardized Precipitation-Evapotranspiration Index (SPEI).

Extended Data Fig. 5 Boxplots showing changes in carbon density in relation to distance to settlements in agricultural areas over China (× mean value, - median value).

Boxplots showing changes in carbon density in relation to distance to settlements in agricultural areas over China (× mean value, - median value). a, MODIS-Based aboveground carbon density change for different distance to settlement; b, relative aboveground carbon density change (carbon density change / carbon density in 2002) in relation to distance to settlements.

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Zhang, X., Brandt, M., Tong, X. et al. A large but transient carbon sink from urbanization and rural depopulation in China. Nat Sustain 5, 321–328 (2022). https://doi.org/10.1038/s41893-021-00843-y

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