Duan et al. (2026) Land Surface Temperature Shows Negligible Difference Between Inside and Outside Photovoltaic Power Plants in China

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Journal of Geophysical Research Atmospheres
• Year: 2026
• Date: 2026-04-14
• Authors: Chunhui Duan, Cunbo Han, Wei Hu, Juan Liu, Yaoming Ma
• DOI: 10.1029/2026jd046444

Research Groups

Not explicitly mentioned in the abstract.

Short Summary

This study investigates the effects of ground-mounted photovoltaic (PV) power plants on land surface temperature (LST) across China, finding that PV plants generally induce daytime warming (0.10 °C) and nighttime cooling (−0.09 °C), with effects varying by vegetation type and season.

Objective

• To investigate in detail the effects of ground-mounted photovoltaic (PV) power plants on land surface temperature (LST) across China.

Study Configuration

• Spatial Scale: National scale, across China.
• Temporal Scale: Diurnal (daytime/nighttime) and seasonal (summer/winter) cycles.

Methodology and Data

• Models used: Random forest regression model, Shapley additive explanations (SHAP) method.
• Data sources: Thermal and Reanalysis Integrating Moderate-resolution Spatial-seamless (TRIMS) LST, land component of the fifth generation of European ReAnalysis (ERA5-Land).

Main Results

• PV power plants generally induce daytime warming (0.10 °C) and nighttime cooling (−0.09 °C) on LST relative to surrounding areas, resulting in a nearly negligible daily warming (0.01 °C).
• These effects are observed in vegetated areas (cropland, woodland, grassland), with the strongest effects found in woodlands.
• Daytime warming is strongest in summer (0.29 °C), while nighttime cooling is strongest in winter (−0.13 °C).
• The daily effect shows warming in summer (0.12 °C) but cooling in winter (−0.05 °C).
• Key factors influencing LST differences (ΔLST) between PV plants and surrounding areas include albedo, Normalized Difference Vegetation Index (NDVI), sensible heat flux, latent heat flux, wind speed, and downward shortwave radiation, with their contributions varying diurnally and seasonally.

Contributions

• Provides a detailed, national-scale investigation of the impacts of ground-mounted PV power plants on LST across China, addressing a gap in previous studies focused on individual plants or limited regions.
• Utilizes an integrated approach combining TRIMS LST and ERA5-Land data with advanced machine learning methods (random forest and SHAP) to analyze LST changes and their drivers.
• Elucidates the local-scale climate feedback mechanisms initiated by PV installations through land-atmosphere interactions, offering critical insights for the sustainable deployment of solar energy.

Funding

Not explicitly mentioned in the abstract.

Citation

@article{Duan2026Land,
  author = {Duan, Chunhui and Han, Cunbo and Hu, Wei and Liu, Juan and Ma, Yaoming},
  title = {Land Surface Temperature Shows Negligible Difference Between Inside and Outside Photovoltaic Power Plants in China},
  journal = {Journal of Geophysical Research Atmospheres},
  year = {2026},
  doi = {10.1029/2026jd046444},
  url = {https://doi.org/10.1029/2026jd046444}
}