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Wavelength-specific urban nighttime light modulates expressed sentiment across China

Nature Cities (2026)Cite this article

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Abstract

As cities brighten under rapidly expanding lighting infrastructure, residents face increasing sentimental risks at night. Although artificial light at night is linked to mental health risks, its wavelength-specific effects remain poorly understood. Here we integrate the satellite observations of artificial light at night and sentiment analysis of geotagged social media posts to quantify wavelength-specific associations between urban light exposure and expressed sentiment across China. We find that exposure to blue light (424–526 nm) increases negative sentiment by 15.9%, whereas moderate green light (506–612 nm) enhances positive sentiment by 5.0%. Spatial mapping further reveals pronounced disparities both within and between cities, with elevated sentiment risk concentrated in commercial areas and eastern cities of China. In particular, optimizing correlated color temperature reduces sentiment risk by 89.7% compared with intensity reduction alone. These findings provide evidence-based guidance for urban lighting design to promote public mental wellbeing through spectral optimization, not just brightness control.

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Fig. 1: Individual outdoor ALAN exposure and sentiment measurement.
Fig. 2: Effects of ALAN exposure on sentiment.
Fig. 3: Heterogenous effects of outdoor ALAN exposure on sentiment.
Fig. 4: Geographical distribution of sentiment risks associated with ALAN exposure.
Fig. 5: Sentiment risk mitigation under different lighting optimization scenarios.

Data availability

All the data used in this study are publicly available. The SDGSAT-1 datasets are available at https://www.sdgsat.ac.cn/. Geotagged social media data used in this study were obtained from Weibo and can be accessed at https://weibo.com/. The ERA5-Land reanalysis dataset is available at https://developers.google.com/earth-engine/datasets/catalog/. The China High Air Pollutants dataset can be found at https://doi.org/10.5281/zenodo.3539349 (ref. 51). The Global Urban Boundary dataset can be found at https://data-starcloud.pcl.ac.cn/zh. WorldPop population data are available at https://www.worldpop.org/.

Code availability

The code used to generate the results of this study is available at https://doi.org/10.5281/zenodo.17777725 (ref. 52).

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Acknowledgements

Q.W. is supported by the National Natural Science Foundation of China (Major Program number 42192580). Z.C. is supported by the National Natural Science Foundation of China (grant number 41901414). J.W. is supported by the National Natural Science Foundation of China (grant number 42222110). We acknowledge the International Research Center of Big Data for Sustainable Development Goals (CBAS) for providing the SDGSAT-1 data.

Author information

Author notes

  1. These authors contributed equally: Chaoqun Zhang, Mei Meng.

Authors and Affiliations

  1. Faculty of Geographical Science, Beijing Normal University, Beijing, China

    Chaoqun Zhang, Ziyue Chen, Weihua Dong, Jianqiang Hu, Yuheng Fu, Jing Yang & Qiao Wang

  2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

    Mei Meng, Jianghao Wang & Kaixin Zhu

  3. NTU Psychology, School of Social Science, Nottingham Trent University, Nottingham, UK

    Wenchong Du

  4. College of Land Science and Technology, China Agricultural University, Beijing, China

    Bingbo Gao

  5. Division of Public Policy, The Hong Kong University of Science and Technology, Hong Kong, China

    Fangxin Yi

  6. School of Geography and Ocean Science, Nanjing University, Nanjing, China

    Manchun Li

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Contributions

C.Z., M.M., Z.C. and J.W. conceived and designed the research. C.Z., M.M., J.H., K.Z., J.Y., F.Y. and Y.F. performed the data analysis. C.Z., M.M., W. Du, J.W. and Z.C. wrote the manuscript. W. Dong, M.L., B.G. and Q.W. contributed ideas to the data analysis, interpretation of results or manuscript revisions.

Corresponding authors

Correspondence to Ziyue Chen or Jianghao Wang.

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Nature Cities thanks Weitong Chen, Fengchao Liang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Zhang, C., Meng, M., Chen, Z. et al. Wavelength-specific urban nighttime light modulates expressed sentiment across China. Nat Cities (2026). https://doi.org/10.1038/s44284-025-00384-x

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