Assessing the efficiency of urban blue-green space in carbon-saving: Take a high-density urban area in a cold region as an example

Abstract

Urban blue-green space responds to climate change by providing relatively cooler surrounding environments to indirectly reduce residents' energy consumption and directly adsorb CO2 from the air. However, the carbon-saving potential of urban blue-green space at the urban scale needs to be addressed in the literature. In this study, an improved ideal quantitative model of carbon-saving is constructed from the user's perspective, considering the cooling effects of urban blue-green space and integrating surface temperature, building information, and urban public space layout. A high-density urban area in a northern cold region of China (Tianjin center urban area) is taken as an example to estimate the annual carbon-saving by performing Landsat surface temperature inversions with the delineation of the effective cooling area, as well as regression analyses based on four seasons of data. The results show that the annual carbon-saving in 2021 is about 78 tonneC/km2, equivalent to 2.21 times the carbon sequestration of the same region. Compared with the edge of the center urban area, the urban blue-green space in the center has a carbon-saving with a 1.4 times higher fluctuation value and a cumulative annual difference of about 394 tonneC/km2. Large blue-green patches in the cold region, while capable of conserving more carbon in spring, summer, and fall, become carbon-source in winter due to increased heating energy consumption and reduced willingness of residents to adopt zero-carbon transportation. The indicators that have the most significant impact on the carbon-saving of urban blue-green space are the cooling area and the background surface temperature. The urban blue-green space coverage and the percentage of impervious surfaces, such as buildings and open spaces, will indirectly impact carbon-saving by affecting the cooling area. The above finding recognizes the carbon-saving potential of urban blue-green space in cold regions. It provides a feasible estimation scheme for comparing the carbon-saving capacity in different seasons.