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Increased terrestrial ecosystem carbon storage associated with global utility-scale photovoltaic installation

Nature Geoscience volume 18, pages 607–614 (2025)Cite this article

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Abstract

Utility-scale photovoltaic (USPV) stands out as one of the foremost renewable energy technologies crucial for achieving global climate targets, owing to its low carbon footprint. While individual case studies exist, a comprehensive global analysis of the impacts of USPV deployment on land-cover changes and subsequent carbon pool dynamics across diverse ecosystems remains lacking. Here we show that worldwide deployment of USPV plants between 2000 and 2018 would increase the carbon pool of the hosting ecosystem by a total of 2.1 TgC over their lifespans, as revealed by the ensemble mean of multiple datasets. Although the carbon pool changes associated with global USPV deployment currently contribute approximately \({15.9}_{-5.8}^{+1.0}\%\) (\({{{\mathrm{ensemble}}\; {\mathrm{mean}}}}_{-{{\mathrm{difference}}\; {\mathrm{to}}\; {\mathrm{percentile}}}\,25}^{+{{\mathrm{difference}}\; {\mathrm{to}}\; {\mathrm{percentile}}}\,75}\)) (or an average absolute carbon footprint of approximately \({10.5}_{-3.8}^{+0.5}\,{\mathrm{g}}\) CO2-equivalent per kilowatt-hour) of the carbon footprint of USPV plants, this share is projected to increase by around 7-fold by 2050, driven primarily by decreasing photovoltaic manufacturing emissions. Notably, optimizing land management strategies can potentially enhance carbon density in the hosting ecosystem of existing USPV plants by approximately \({3.0}_{-0.4}^{+3.7}\,{\mathrm{kgC}}\,{\mathrm{m}}^{-2}\), thereby facilitating an average reduction of \({4.3}_{-0.2}^{+9.3}\%\) in the carbon footprint of these USPV plants.

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Fig. 1: Land-cover patterns before and after USPV deployment.
Fig. 2: C pool changes induced by USPV deployment.
Fig. 3: Effect of C pool changes on C footprint of USPV plants.
Fig. 4: C pool and C footprint changes under different land management scenarios.

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Data availability

The global inventory of solar PV energy generating units utilized as basic data in this study is available via Zenodo at https://doi.org/10.5281/ZENODO.5005868 (ref. 77). The Landsat 5 and Landsat 8 atmospherically corrected surface reflectance data are available at https://www.usgs.gov/landsat-missions or in the Google Earth Engine (GEE) repository. The 300-m-resolution land-cover data are available at http://maps.elie.ucl.ac.be/CCI/viewer/download.php. The 10-m-resolution land-cover data are available at https://esa-worldcover.org/en or in the GEE repository. The observation-based C density data of soil are available via Zenodo at https://doi.org/10.5281/ZENODO.2536040 (ref. 78). The observation-based C density data of vegetation are available at https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1763 (ref. 79). The C density data derived from models included in the Trendy dataset are available at https://mdosullivan.github.io/GCB. The ERA5-Land hourly reanalysis data are available at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land?tab=overview (ref. 80) or in the GEE repository. The time series dataset developed in this study and the relevant data are available via Figshare at https://doi.org/10.6084/m9.figshare.28328765 (ref. 81). Source data are provided with this paper.

Code availability

The source code used in this study is available via Figshare at https://doi.org/10.6084/m9.figshare.28328810 (ref. 82).

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Acknowledgements

We thank N. Carvalhais, P. McGuire, X. Yue, S. Falk and Q. Sun for their assistance. This work was financially supported by the National Natural Science Foundation of China (grant nos. 72293601 (Q.Y.) and 72242104 (Q.W.)), the Joint Research Fund in Smart Grid under cooperative agreement between the National Natural Science Foundation of China and State Grid Corporation of China (grant no. U1966601) (W.W.), and the Postdoctoral Innovation Talents Support Program of China (grant no. BX20240019) (K.W.). We also thank the members of the Harvard-China Project on Energy, Economy and Environment for their valuable comments and suggestions. We are grateful to the Harvard Global Institute for providing funding support to the Harvard-China Project on Energy, Economy and Environment. The computation is completed in the HPC Platform of Huazhong University of Science and Technology.

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  1. These authors contributed equally: Qingrui Wang, Kai Wang, Lintao Shao.

Authors and Affiliations

  1. State Key Laboratory of Coal Combustion, Huazhong University of Science and Technology, Wuhan, China

    Qingrui Wang, Lintao Shao, Xinyi Tang & Qing Yang

  2. Department of New Energy Science and Engineering, School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan, China

    Qingrui Wang, Lintao Shao, Xinyi Tang & Qing Yang

  3. Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China

    Kai Wang & Shuchang Tang

  4. UK Biochar Research Centre, School of GeoSciences, University of Edinburgh, Edinburgh, UK

    Ondřej Mašek

  5. Climate Research Division, Environment and Climate Change Canada, Victoria, British Columbia, Canada

    Gesa Meyer

  6. Department of Mechanical and Aerospace Engineering and Center for Energy Research, University of California, San Diego, CA, USA

    Jan Kleissl

  7. State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, China

    Liwei Zhang

  8. Research Institute for Eco-civilization, Chinese Academy of Social Sciences, Beijing, China

    Mudan Wang

  9. State Key Laboratory of the Operation and Control of Renewable Energy and Storage Systems, China Electric Power Research Institute, Beijing, China

    Weisheng Wang

  10. China-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan, China

    Qing Yang

  11. John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA

    Qing Yang

  12. Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK

    Stephen Sitch

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Contributions

Q.Y. and Q.W. designed the study. Q.W., K.W., L.S. and G.M. collected the data. M.W. contributed to economic analysis. X.T. performed accuracy validation of the datasets. S.S. and S.T. contributed to microclimate analysis. Q.W., K.W., L.S., S.S., J.K., O.M., L.Z. and W.W. performed data analysis and wrote the manuscript with substantial contributions from all co-authors.

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Correspondence to Qing Yang.

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Nature Geoscience thanks Zhengyao Lu and Dirk-Jan van de Ven and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Xujia Jiang, in collaboration with the Nature Geoscience team.

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Wang, Q., Wang, K., Shao, L. et al. Increased terrestrial ecosystem carbon storage associated with global utility-scale photovoltaic installation. Nat. Geosci. 18, 607–614 (2025). https://doi.org/10.1038/s41561-025-01715-2

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