Speaker
Description
As global climate change accelerates, cities worldwide are increasingly affected by wet-heat stress (WHS), driven by the combined effects of Urban Heat Islands (UHI) and Urban Moisture Islands (UMI). Human perception of the thermal environment depends on both temperature and humidity. While UHI has been extensively studied, research on UMI remains limited, and few studies have integrated both phenomena into a unified analysis. Given that urban built environments (UBE) are key factors influencing these effects, understanding how different built environment characteristics contribute to WHS is crucial for developing effective urban planning strategies. This study fills the research gap by introducing a novel joint analysis framework that simultaneously assesses UHI and UMI dynamics in Chinese urban agglomerations. It also examines the combined effects of three key built environment dimensions—physical morphology, natural characteristics, and development indicators—on these phenomena.
The objective of this study is to quantify the spatial distribution of UHI and UMI across 1,635 urban agglomerations in China during the summer months of 2020 (June, July, and August). Utilizing high-resolution satellite data and an advanced machine learning approach integrating the LightGBM model with the SHAP algorithm, we assess the contributions of UBE to WHS. All associated models achieved R-squared values greater than 0.9, indicating robust representations of the contributions and marginal effects of different UBE dimensions on urban WHS. Through this approach, we gain novel insights into the complex interplay between UHI, UMI, and urban environmental factors.
The results reveal that approximately 28.9% of urban areas experience concurrent UHI and UMI stress, with these effects being more pronounced in warm climatic zones and in cities categorized as Super Cities (populations over 5 million). This study identifies five major insights into the UBE’s role in WHS: (1) Urban greening alleviates WHS, particularly in larger cities, effectively lowering UHI without substantially raising UMI. This finding addresses concerns from previous studies that vegetation may increase air humidity through evapotranspiration, potentially exacerbating WHS and offsetting cooling benefits. (2) Both high building density (BD) and impervious surface ratios (IR) concurrently intensify UHI and UMI, indicating that controlling their upper thresholds is crucial for mitigating combined WHS. (3) Once building height (BH) exceeds 10–12 meters, improved urban ventilation reduces both UHI and UMI, with this effect growing stronger in larger cities. (4) High albedo surfaces, such as glass curtain walls, exacerbate WHS by reflecting and concentrating solar radiation in localized areas, particularly in large cities. (5) Urban development indicators, including Night-Time Lights and Population Density, significantly increase UHI while inhibiting UMI, with this impact intensifying as city size grows.
The study’s findings offer actionable recommendations for urban planning, emphasizing the promotion of urban greening, particularly in larger cities, through innovative measures like rooftop and vertical greening to effectively utilize limited urban space and increase green coverage. It advocates for optimizing building morphology by regulating BD and IR and adjusting BH to enhance urban ventilation, thereby alleviating both UHI and UMI. Additionally, managing surface albedo through the selection of appropriate materials can mitigate WHS. Moreover, rapid urban development should strategically balance high economic growth with sustainable planning practices, maintaining economic vitality while mitigating UHI and UMI.
In conclusion, this study underscores the importance of addressing both UHI and UMI comprehensively in sustainable city design. It calls for a shift in urban planning that not only targets heat mitigation but also accounts for moisture dynamics, offering a holistic approach to enhancing urban resilience against climate change. The proposed framework serves as a robust tool for policymakers to make informed decisions aimed at reducing the impacts of WHS.
References
Zhang, K., Cao, C., Chu, H., Zhao, L., Zhao, J., & Lee, X. (2023). Increased heat risk in wet climate induced by urban humid heat. Nature, 617(7962), 738-742. https://doi.org/10.1038/s41586-023-05911-1
Zhang, Z., Wang, Y., Zhang, G. J., Xing, C., Xia, W., & Yang, M. (2024). Light rain exacerbates extreme humid heat. Nature Communications, 15(1), 7326. https://doi.org/10.1038/s41467-024-51778-9
Venter, Z. S., Chakraborty, T., & Lee, X. Crowdsourced air temperatures contrast satellite measures of the urban heat island and its mechanisms. Science Advances, 7(22), eabb9569. https://doi.org/10.1126/sciadv.abb9569
Shi, Y., & Zhang, Y. (2022). Urban morphological indicators of urban heat and moisture islands under various sky conditions in a humid subtropical region. Building and Environment, 214, 108906. https://doi.org/https://doi.org/10.1016/j.buildenv.2022.108906
Ming, Y., Liu, Y., Gu, J., Wang, J., & Liu, X. (2023). Nonlinear effects of urban and industrial forms on surface urban heat island: Evidence from 162 Chinese prefecture-level cities. Sustainable Cities and Society, 89, 104350. https://doi.org/https://doi.org/10.1016/j.scs.2022.104350
| Keywords | Wet-heat stress; Urban climate islands; Urban built environment; Ensemble learning |
|---|---|
| Best Congress Paper Award | Yes |
