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Article

Synergistic Mechanism of Spatiotemporal Dynamics in Urban Thermal Environments and Air Pollutants in China

1
State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
2
School of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, China
3
Faculty of Science, University of Copenhagen, 1350 Copenhagen, Denmark
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(23), 3810; https://doi.org/10.3390/rs17233810
Submission received: 10 October 2025 / Revised: 12 November 2025 / Accepted: 22 November 2025 / Published: 24 November 2025
(This article belongs to the Section Environmental Remote Sensing)

Abstract

Rapid urbanization in China has exacerbated the dual challenges of urban heat islands (UHIs) and air pollution, threatening urban sustainability. We conducted a national-scale analysis of the spatiotemporal dynamics and synergy between the surface UHI intensity, distinguished as daytime (DUHI) and nighttime (NUHI), and major air pollutants (PM2.5, PM10, NO2) in 370 Chinese cities (2000–2019). Using multi-source remote sensing, ground-based monitoring, and urban data, we applied coupling coordination and correlation analyses to quantify these interactions. Key findings reveal distinct patterns: (1) The annual mean land surface temperature (LST) rose, with the nighttime LST (NLST) increasing faster than the daytime LST (DLST). Conversely, the UHI intensity showed an overall decline, with the DUHI decreasing more than the NUHI. (2) Air pollutants displayed strong seasonality; while PM10 concentrations decreased slightly over the long term, NO2 levels rose significantly. (3) Monthly, pollutants correlated negatively with LST (R2 > 0.92 for PM2.5), suppressing the DUHI but intensifying the NUHI. Long-term, the correlation trend revealed a strengthening synergy, particularly between particulate matter and NUHI (trend R2 = 0.50). (4) Spatially, over 90% of cities exhibited high UHI–particle coordination. Key associated factors include anthropogenic activities, urban morphology, and natural mitigation factors. We conclude that disrupting the heat–pollution synergy requires integrated strategies, namely reducing emissions at the source, optimizing the urban form, and enhancing ecological regulation. This is essential for advancing low-carbon, climate-resilient urban development.
Keywords: urban heat island (UHI); air pollution; spatiotemporal coupling; driving mechanisms; coupling coordination degree; remote sensing urban heat island (UHI); air pollution; spatiotemporal coupling; driving mechanisms; coupling coordination degree; remote sensing

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MDPI and ACS Style

Liu, S.; Zhang, J.; Chen, W.; Ding, S.; Wang, L. Synergistic Mechanism of Spatiotemporal Dynamics in Urban Thermal Environments and Air Pollutants in China. Remote Sens. 2025, 17, 3810. https://doi.org/10.3390/rs17233810

AMA Style

Liu S, Zhang J, Chen W, Ding S, Wang L. Synergistic Mechanism of Spatiotemporal Dynamics in Urban Thermal Environments and Air Pollutants in China. Remote Sensing. 2025; 17(23):3810. https://doi.org/10.3390/rs17233810

Chicago/Turabian Style

Liu, Shidong, Jie Zhang, Wei Chen, Shengping Ding, and Li Wang. 2025. "Synergistic Mechanism of Spatiotemporal Dynamics in Urban Thermal Environments and Air Pollutants in China" Remote Sensing 17, no. 23: 3810. https://doi.org/10.3390/rs17233810

APA Style

Liu, S., Zhang, J., Chen, W., Ding, S., & Wang, L. (2025). Synergistic Mechanism of Spatiotemporal Dynamics in Urban Thermal Environments and Air Pollutants in China. Remote Sensing, 17(23), 3810. https://doi.org/10.3390/rs17233810

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