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.

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.

Greenhouse gas emissions are primary drivers of climate change, and the intensification of extreme heat and urban heat island effects poses serious threats to urban ecosystems, public health, and energy consumption. This study systematically evaluated the carbon reduction potential of 369 urban parks in Jinan during extreme heat events using land surface temperature (LST) retrieval, combined with CatBoost + SHAP machine learning methods. Results indicate that the LST in Jinan ranged from 1.77 °C to 59.44 °C, and 278 parks exhibited significant cooling effects, collectively saving 2943 tons of CO₂ per day—offsetting 11.28% of the city’s fossil fuel emissions. Small parks, such as community parks, demonstrated higher carbon-saving efficiency (CSE), while large ecological parks showed greater carbon-saving intensity (CSI). CSE was strongly correlated with vegetation coverage and surrounding population density, with efficiency increasing when the vegetation index was within 0.3–0.7 and population density ranged 0–5000 or 15,000–22,500 people. CSI was influenced by evapotranspiration and park geometric form, increasing significantly when the park area exceeded 250 hectares or evapotranspiration ranged 2.5–6.0. However, elevation and albedo negatively impacted both metrics, with the lowest CSI observed when elevation exceeded 150 m or albedo surpassed 18%.

Urban form plays a crucial role in regulating urban thermal environments and air pollution patterns. However, the indirect mechanisms through which urban form influences PM2.5 concentrations via land surface temperature (LST) remain poorly understood. This study investigates these pathways by analyzing representative two- and three-dimensional urban form indices (UFIs) in the central urban area of Taiyuan, China. Multiple log-linear regression and mediation analysis were applied to evaluate the combined effects of urban form on LST and PM2.5. The results indicate that UFIs significantly influence both LST and PM2.5. The frontal area index (FAI) and sky view factor (SVF) emerged as key variables, with LST playing a significant mediating role. The indirect pathways affecting PM2.5 via LST, along with the direct LST-PM2.5 correlation, exhibit pronounced seasonal differences in direction and intensity. Moreover, different urban functional zones exhibit heterogeneous responses to the same form indices, highlighting the spatial variability of these linkages. These findings underscore the importance of incorporating seasonal and spatial differences into urban design. Accordingly, this study proposes targeted urban form optimization strategies to improve air quality and thermal comfort, offering theoretical insights and practical guidance for sustainable urban planning.