Urban areas with parks tend to have the best outdoor thermal comfort in regions with high urban heat island effects during summer. This study analyzed the synergistic cooling effects of 94 urban parks and the adjacent built-up areas in six districts of Xi’an City using four cooling indicators: park cooling intensity (PCI), park cooling area (PCA), park cooling effect (PCE), and park cooling gradient (PCG). The results showed that 84 out of 94 parks exhibited significant cooling effects, with an average PCI of 1.98 °C, PCA of 51.7 ha, PCE of 6.6, and PCG of 8.2 °C/km. Correlation analyses indicated that the intrinsic park attributes, external buffer zone building height, and building density were the main factors affecting the cooling effect. The park landscape configuration, building height, and density significantly influenced the PCI and PCG, while the park shape and size were crucial for the PCA (positive) and PCE (negative). The optimal park areas for improving the thermal environment were identified as 26 ha (cooling area focus, building density <13%) and 15 ha (cooling intensity focus, building height 32%). This study provides theoretical guidance for planning urban parks and the surrounding areas based on cooling effects, offering insights for future climate resilience planning.

Urban parks are vital for mitigating high urban temperatures, yet optimizing their design for maximum cooling benefits remains a challenge. This study investigates the cooling mechanisms of 65 parks in Tianjin, assessing their characteristics and spatial equity regarding cooling capacity. Results show that 63 parks significantly lower temperatures, with an average Park Cooling Area (PCA) of 45.0 hectares, Park Cooling Efficiency (PCE) of 8.09, Park Cooling Gradient (PCG) of 16.4 °C/km, and Park Cooling Intensity (PCI) of 2.64 °C. Key factors influencing cooling effectiveness include park albedo and nearby water bodies, with optimal albedo values between 3 and 3.6, and water bodies of at least 2.5 hectares enhancing efficiency. Notably, only 38.9% of residents can easily access park cooling services. While neighborhood parks in dense urban areas provide high economic benefits, they serve fewer residents; comprehensive parks cover more people but are less accessible. This study offers new insights into the cooling effects of coastal urban parks, aiding planners in addressing marginalized residents’ needs and enhancing urban resilience amid climate change.

Intensive urban development has resulted in the degradation of the urban thermal environment in most regions. There is a growing consensus on the need to enhance urban thermal comfort through well-designed forms, especially in open spaces like urban canyons. To address this, our study focuses on Xi’an’s commercial pedestrian streets, employing K-means clustering analysis to create 32 representative models based on actual scenes, capturing their textural characteristics. Simultaneously, 11 geometric indicators (2D/3D) were chosen to quantify the canyon’s geometric form. We assessed the spatial and temporal distribution differences in the thermal environment across these models using Envi-met simulation. Finally, Spearman correlation analysis was employed to examine the correlation and significance of the two sets of indicators, culminating in formulating an ideal model. The findings reveal that (1) wind conditions are predominantly influenced by the canyon’s geometric form, followed by solar radiation and temperature, with the lowest relative humidity change amplitude among the assessed thermal parameters. (2) Among the 11 geometric form indicators, 3D indicators correlate more significantly with thermal environment parameters than 2D indicators. Specifically, street orientation significantly impacts the thermal environment, Build-To-Line Rat holds greater significance than interface density, and both building shape coefficient and block surface ratio are significantly correlated with air temperature and wind speed, with a weaker correlation to solar radiation. (3) In the Xi’an region, courtyards oriented north-south demonstrate a more favorable trend in the thermal environment.

Urban green spaces (UGS) play a critical role in mitigating the urban heat island (UHI) effect and addressing climate change challenges through their cooling effects. Expanding green space and optimizing its layout are key strategies in urban planning. However, with limited land resources, maximizing cooling efficiency becomes crucial. While previous studies have yet to reach a consensus on the optimal UGS size threshold for achieving maximum cooling efficiency, this study employs high-resolution remote sensing imagery to extract 25,594 UGS patches in Xi’an and explores the scale dependency of UGS cooling effects. Results show that 54.20% of the patches exhibit a “cooling island effect”, reducing surface temperatures by 0.10 ± 0.13 °C to 1.66 ± 1.15 °C. A nonlinear relationship was observed between cooling intensity and UGS size, influenced by vegetation coverage and edge complexity. Further analysis reveals that medium-sized UGS have the highest cooling efficiency. These UGS were categorized into five functional zones to explore the dominant factors affecting cooling efficiency in each zone, and corresponding strategies for improvement were proposed. These findings provide insights into optimizing UGS layout and refining the cooling efficiency thresholds.

Intensive urban development has resulted in the degradation of the urban thermal environment. There is a growing consensus on the need to enhance urban thermal comfort through well-designed forms, especially in open spaces like urban canyons. To address this, our study focuses on Xi'an's commercial pedestrian streets, employing K-means clustering analysis to create 32 representative models based on actual scenes, capturing their textural characteristics. Simultaneously, 11 geometric indicators (2D/3D) were chosen to quantify the canyon's geometric form. We assessed the spatial and temporal distribution differences in the thermal environment across these models using Envi-met simulation. Finally, Spearman correlation analysis was employed to examine the correlation and significance of the two sets of indicators, culminating in formulating an ideal model. The findings reveal that (1) wind conditions are predominantly influenced by the canyon's geometric form, followed by solar radiation and temperature, with the lowest relative humidity change amplitude among the assessed thermal parameters. (2) Among the 11 geometric form indicators, 3D indicators correlate more significantly with thermal environment parameters than 2D indicators. Specifically, SO significantly impacts the thermal environment, P holds greater significance than De, and both BSC and BSR are significantly correlated with air temperature and wind speed, with a weaker correlation to solar radiation. (3) In the Xi'an region, courtyards oriented north-south demonstrate a more favorable trend in the thermal environment.