Resumen
The concept of green and low-carbon development is integrated into territorial spatial planning and district control research. It is one of the systematic policy tools for emission reduction and carbon sequestration, greatly contributing to achieving the double carbon goal. This paper presents a method for measuring the carbon emissions of urban territorial spaces using multisource big data, aiming to identify the spatial patterns and levels of carbon emissions at microspatial scales. The spatial patterns of carbon emissions were used to construct a carbon balance zoning method to evaluate the regional differences in the spatial distribution of carbon emissions, taking Suzhou as an example to achieve carbon balance zoning at the micro scale of the city. Based on our research, the following was determined: (1) Suzhou?s total carbon emissions in 2020 was approximately 240.3 million tons, with the industrial sector accounting for 81.32% of these emissions. The total carbon sink was about 0.025 million tons. (2) In Suzhou City, the high-value plots of carbon emissions are mainly located in industrial agglomeration areas. By contrast, low-value plots are primarily located in suburban areas and various carbon sink functional areas, exhibiting a scattered distribution. (3) The territorial space unit was divided into four functional areas of carbon balance, with 36 low-carbon economic zone units accounting for 37.11%, 29 carbon-source control zone units accounting for 29.90%, 14 carbon-sink functional zone units accounting for 14.43%, and 18 high-carbon optimization zone units accounting for 18.56%. As a result of this study, carbon balance zoning was achieved at the grassroots space level, which will assist the city in low-carbon and refined urban governance. Some ideas and references are also provided to formulate policies for low-carbon development at the micro scale of a city.