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Amplified positive effects on air quality, health, and renewable energy under China’s carbon neutral target

Nature Geoscience volume 17, pages 411–418 (2024)Cite this article

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Abstract

China pledged to achieve carbon neutrality by 2060 to combat global climate change, yet the resulting multi-aspect domestic impacts are not fully analysed due to an incomplete understanding of the underlying anthropogenic–natural interactions. Building an integrated cross-disciplinary modelling framework that can capture the feedbacks of changing aerosols on meteorology, here we highlight the amplified air quality, human health and renewable energy self-reinforcing synergies of China’s carbon neutral target in comparison to the baseline in 2015 and 2060. We find that owing to emissions reduction and more favourable meteorological conditions caused by less aerosol, achieving China’s carbon neutrality target in 2060 reduces national population-weighted PM2.5 concentrations and associated premature deaths by ~39 μg m−3 and 1.13 (95% confidence interval: 0.97–1.29) million while boosting provincial solar (wind) power performance by up to ~10% (~6%) with mostly decreased resource variability in comparison to the 2060 baseline. Enhanced renewable performance along with low-carbon energy transition may provide additional opportunities to address the remaining air pollution and associated human health damages upon achieving carbon neutrality. Our results highlight that global developing and polluting countries’ pledge for carbon neutrality can produce important positive feedbacks between aerosols mitigation, air quality improvement and enhanced renewable energy, which can be amplified via weakened aerosol–meteorology interactions and better atmospheric dispersion.

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Fig. 1: Aerosol distribution and its radiative effects on solar radiation, wind speed and air quality changes in 2015.
Fig. 2: Air quality and human health co-benefits under China’s carbon neutral target.
Fig. 3: Renewable energy-related meteorology and performance changes under China’s carbon neutral target.
Fig. 4: Multi-aspect synergies and self-reinforcing renewables under China’s quest for carbon neutrality.
Fig. 5: Conceptual model of multi-aspect synergies and renewable self-reinforcing effects.

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Data availability

Meteorology data for 2015 are obtained from the 1-hour ERA5 climate reanalysis dataset (https://cds.climate.copernicus.eu/#!/search?text=ERA5&type=dataset)53; natural and anthropogenic fire emissions are from the Fire INventory from NCAR (FINN; https://www2.acom.ucar.edu/modeling/finn-fire-inventory-ncar)54; anthropogenic emissions are from the DPEC emissions inventory v1.1 (http://meicmodel.org.cn/?page_id=1918&lang=en)55; 2060 meteorological data are available via figshare at https://doi.org/10.6084/m9.figshare.16802326 (ref. 56). Source codes of the WRF-Chem model utilized in this study are available at https://github.com/wrf-model/WRF/releases/tag/V3.6.1. All source data generated or analysed during this study are included in this published paper (and its Supplementary Information) and are available at https://doi.org/10.6084/m9.figshare.25302031 (ref. 57).

Code availability

The Python and R scripts for processing and plotting results in this study are available at https://doi.org/10.6084/m9.figshare.25302031 (ref. 57).

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Acknowledgements

The work was financially supported by the National Natural Science Foundation of China grant number 42325506 to X. Huang, grant number 42277482 to Y.Q. and Fundamental Research Funds for the Central Universities (14380198) to A.D. M.Z. acknowledges support from the Princeton School of Public and International Affairs and its Center for Policy Research on Energy and the Environment. C.Z. acknowledges National Key R&D Program of China (grant number 2023YFF0613900). X. He acknowledges the Top-Notch Young Talents Program of China.

Author information

Author notes

  1. These authors contributed equally: Yue Qin, Mi Zhou.

Authors and Affiliations

  1. College of Environmental Sciences and Engineering, Peking University, Beijing, China

    Yue Qin, Liangdian Huang, Weiyi Gu, Licheng Wang, Qi Chen & Tong Zhu

  2. Institute of Carbon Neutrality, Peking University, Beijing, China

    Yue Qin, Liangdian Huang, Chuan Zhang, Weiyi Gu, Licheng Wang & Qi Chen

  3. Princeton School of Public and International Affairs, Princeton University, Princeton, NJ, USA

    Mi Zhou

  4. School of Atmospheric Sciences, Nanjing University, Nanjing, China

    Yueting Hao, Xin Huang, Derong Zhou & Aijun Ding

  5. Department of Earth System Science, Tsinghua University, Beijing, China

    Dan Tong

  6. Institute of Energy, Peking University, Beijing, China

    Chuan Zhang

  7. Department of Earth System Science, University of California, Irvine, CA, USA

    Jing Cheng

  8. The Administrative Center for China’s Agenda 21, Beijing, China

    Xiaojia He

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Contributions

Y.Q. and X. Huang designed this study. X. Huang, M.Z., Y.Q., Y.H., D.T., L.H., C.Z., J.C., W.G., L.W., X. He, D.Z. and Q.C. led the model simulations and analysed the data. Y.Q., X. Huang, M.Z., A.D. and T.Z. wrote the paper with input from all co-authors.

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Correspondence to Yue Qin or Xin Huang.

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Nature Geoscience thanks Jinyue Yan 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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Extended data

Extended Data Fig. 1 Provincial PM2.5 surface concentration changes due to aerosols’ radiative effects across mainland China in 2015.

(a, b) Area-weighted (A-W) and (c, d) population-weighted (P-W) PM2.5 surface concentration changes in (a, c) absolute and (b, d) percentage changes across mainland China due to aerosols’ radiation interactions (ARI) in 2015. Base map data are from the Resource and Environment Science and Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (https://doi.org/10.12078/2023010103, 2023)1.

Extended Data Fig. 2 Provincial solar radiation and wind speed changes due to aerosols’ radiative effects across mainland China in 2015.

(a, b) Solar radiation and (c, d) wind speed changes in (a, c) absolute and (b, d) percentage changes across mainland China. Base map data are from the Resource and Environment Science and Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (https://doi.org/10.12078/2023010103, 2023)1.

Extended Data Fig. 3 2060 Provincial PM2.5 surface concentrations in mainland China.

Area-weighted (A-W) and population-weighted (P-W) PM2.5 surface concentration in (a-d) 2060 Baseline scenario and (e-h) 2060 Carbon neutral scenario, with (ARIon) and without (ARIoff) considering aerosols’ radiation interactions respectively. Base map data are from the Resource and Environment Science and Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (https://doi.org/10.12078/2023010103, 2023)1.

Extended Data Fig. 4 2060 Provincial PM2.5 associated premature deaths in mainland China.

PM2.5 associated premature deaths in (a,b) 2060 Baseline scenario, (c,d) 2060 Carbon neutral scenario with (ARI_on) and without (ARI_off) considering aerosols’ radiation interactions respectively. Base map data are from the Resource and Environment Science and Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (https://doi.org/10.12078/2023010103, 2023)1.

Extended Data Table. 1 Scenarios design and description
Full size table

Supplementary information

Supplementary Information

Supplementary Notes, Figs. 1–15 and Tables 1–7.

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Qin, Y., Zhou, M., Hao, Y. et al. Amplified positive effects on air quality, health, and renewable energy under China’s carbon neutral target. Nat. Geosci. 17, 411–418 (2024). https://doi.org/10.1038/s41561-024-01425-1

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