This research highlights that street layouts, including the vegetation ratio, street orientation, and aspect ratio, are key in diminishing urban heat islands (UHIs), building energy use, and carbon emissions. The optimal street layout for minimal building energy consumption, carbon emissions, and maximal outdoor thermal comfort in Tianjin was established via field measurements, ENVI-met 5.6.1, Energy Plus simulations, and correlation analysis. The findings indicate the following: (1) The carbon emissions of winter residential heating energy consumption are 2.9–3.2 times higher than those for summer cooling. Urban design should thus prioritize winter energy efficiency and summer thermal comfort outdoors. (2) The summer street PET (physiological equivalent temperature) inversely correlates with the vegetation ratio and aspect ratio. Winter heating energy use inversely correlates with the street orientation and directly correlates with the aspect ratio. Adequate vegetation and proper orientation can decrease energy and carbon output while enhancing summer outdoor comfort. (3) Streets with an NW–SE orientation, H/W = 0.9, and 50% trees in summer yield the best thermal comfort, while those with an NE–SW orientation, H/W = 0.3, and 50% vegetative trees in winter produce the lowest carbon emissions. These insights are instrumental in refining urban streets and building designs in cold zones.

Efficiently harnessing the urban cool island effect associated with large urban aquatic bodies holds significant importance in mitigating the urban heat island (UHI) effect and enhancing the quality of residential living. This study focuses on Tianjin’s Meijiang Lake and its surrounding 47 residential areas, combining Landsat 8 remote sensing satellite data with geographic information system (GIS) buffer analyses and multiple linear regression analyses to reveal the summer thermal characteristics of residential waterfront areas with diverse spatial layouts. The results indicate that: (1) Meijiang Lake’s effective cooling radius extends up to 130 m from the water’s edge, achieving a maximum temperature reduction of 14.44%. Beyond 810 m, the cooling effect diminishes significantly. (2) Waterfront distance (WD), building density (BD), building width (L) and normalized difference vegetation index (NDVI) emerge as the primary factors influencing changes in average land surface temperature (ΔLST) in residential areas. The degrees of influence are ordered as follows: BD > WD > NDVI > L. “Dispersed” pattern residential areas exhibit the most favorable thermal environments, which are primarily influenced by WD, while “parallel” pattern residential areas demonstrate the least favorable conditions, primarily due to WD and NDVI. (3) The direct adjacency of residential areas to large-scale aquatic bodies proves to be the most effective approach for temperature reduction, resulting in a 5.03% lower average temperature compared to non-adjacent areas. Consequently, this study derives strategies for improving the thermal environment via the regulation of spatial planning elements in residential areas, including waterfront patterns, vegetation coverage, WD, and BD.