Exploring Spatial Pattern Optimization Path of Urban Building Carbon Emission based on Low-Carbon Cities Analytical Framework: A Case Study of Xi'an, China

Reducing carbon dioxide emissions has become a prominent issue in city construction. Here, with the objective of spatial pattern optimization, we propose a comprehensive evaluation framework for low-carbon cities. To shed further light on the mechanism by which green finance facilitates the low-carbon transformation of the economy, we chose Xi'an as a study area, used the system dynamics model, simulated the relationship between different factors in the development of low-carbon cities, and provided guidance for spatial planning of low-carbon cities. Through systematic analysis of results, we found that with the progress of urbanization and the improvement of people's living standards, the carbon emissions from urban buildings in Xi'an will increase annually and reach 2.47 million tons by 2030. In scenario 1, the faster pace of urbanization raises carbon emissions from urban buildings by 3%, to 2.5543 million tons from the base. In contrast, in Scenario 2, the reduction in urbanization rate results in a decrease in urban building carbon emissions to 2.4243 million tons, a reduction of 2.26% compared to the baseline scenario. Thus it can be seen that diverse modifications of parameters exert distinct effects on the ultimate carbon emissions from urban buildings.