The mitigation of the urban heat island effect is increasingly imperative in light of climate change. Blue–green space, integrating water bodies and green spaces, has been demonstrated to be an effective strategy for reducing the urban heat island effect and enhancing the urban environment. However, there is a lack of coupled analysis on the cooling island effect of blue–green space at the meso-micro scale, with previous studies predominantly focusing on the heat island effect. This study coupled the single urban canopy model (UCM) with the mesoscale Weather Research and Forecasting (WRF) numerical model to simulate the cooling island effect of blue–green space in the Eastern Sea-River-Stream-Lake Linkage Zone (ESLZ) within the northern subtropical zone. In particular, we comparatively investigated the cooling island effect of micro-scale blue–green space via three mitigation strategies of increasing vegetation, water bodies, and coupling blue–green space, using the temperature data at the block scale within 100 m square of the urban center on the hottest day in summer. Results showed that the longitudinally distributed lakes and rivers in the city had a significant cooling effect on the ambient air temperature (Ta) at the mesoscale, with the largest cooling range occurring during the daytime and ranging from 1.01 to 2.15 °C. In contrast, a 5~20% increase in vegetation coverage or 5~15% increase in water coverage at the micro-scale was observed to reduce day and night Ta by 0.71 °C. Additionally, the most significant decrease in physiologically equivalent temperature (PET) was found in the mid-rise building environment, with a reduction of 2.65–3.26 °C between 11:00 and 13:00 h, and an average decrease of 1.25°C during the day. This study aims to guide the optimization of blue–green space planning at the meso-micro scale for the fast-development and expansion of new urban agglomerations.

Rapid urbanization has led to a significant expansion of urban space, causing ecological problems such as fragmentation, declining landscape connectivity, and decreasing biodiversity. There is an urgent need to mitigate the conflict between urban expansion and ecological environmental protection by constructing ecological networks to help promote sustainable regional development. This study selected the Funiu Mountain area as the study area. Morphological spatial pattern analysis, the minimal cumulative resistance model, and network index evaluation were used to construct an ecological network in the study area and conduct a comparative analysis with local nature reserves. The results showed: (1) nine ecological source sites were identified, concentrated in the central and northern regions, which had a high spatial overlap with local nature reserves; (2) 34 ecological corridors were extracted, which could effectively connect all ecological source sites as well as most nature reserves; (3) 32 ecological nodes were identified, of which 20 strategic points were scattered along ecological corridors, and 12 artificial environment points were scattered in low-lying areas around nature reserves; (4) the ecological network showed a structure of central concentration and peripheral dispersion. The structural evaluation of the network indicated that it had strong integrity.

Blue–green space refers to blue space (rivers and lakes) and green space (lawns and trees), which have the cooling island effect and are increasingly acknowledged as a potential and effective way to help alleviate the urban heat island effect. Scientific and flexible blue–green space planning is required, especially for medium- and large-scale urban agglomerations in the face of climate change. However, the temporal evolution and spatial patterns of the cooling island effect in the blue–green space under different future scenarios of climate change have not been fully investigated. This would impede long-term urban strategies for climate change adaptation and resilience. Here we studied the relationship between future climate change and blue–green spatial layout with Weather Research and Forecasting (WRF), based on the numerical simulation data of 15 global climate models under different extreme Shared Socioeconomic Pathway (SSP) scenarios. As a result, future changes in urban cooling island (UCI) magnitudes were estimated between historical (2015–2020) and future timelines: 2030s (2021–2040), 2050s (2041–2060), 2070s (2061–2080), and 2090s (2081–2100). Our results showed different land use types in blue and green space across the study area were predicted to present various changes in the next 80 years, with forest, grassland, and arable land experiencing the most significant land use transfer. The future UCI intensity of cities under SPP5-8.5 (12) was found to be lower than that under SPP2-4.5 (15), indicating that cities may be expected to experience decreases in UCI magnitudes in the future under SSP5-8.5. When there is no expansion of urban development land, we found that the conversion of different land use types into blue and green space leads to little change in future UCI intensity. While the area growth of forests and water bodies is proportional to the increase in UCI, the increase of farmland was observed to have the most significant impact on reducing the amplitude of urban UCI. Given that Huai’an City, Yancheng City, and Yangzhou City have abundant blue–green space, the urban cooling island effect was projected to be more significant than that of other cities in the study area under different SSP scenarios. The simulation results of the WRF model indicate that optimizing the layout of urban blue–green space plays an important role in modulating the urban thermal environment.