Estimating and classifying urban carbon budget based on land use intensity with regulatory strategies developing

This study develops an integrated framework to evaluate urban carbon emissions based on land-use intensity. Using Taipei City as a case study, the research employs a 100 × 100 meter high-resolution grid to quantify operational carbon, embodied carbon, and carbon sequestration. Key spatial indicators including Floor Area Ratio (FAR), Building Coverage Ratio (BCR), and Green Coverage Ratio (GCR) are analyzed through regression to identify their influence on carbon emissions. Results indicate that FAR is the most influential variable, enabling the construction of simplified linear and polynomial models for emission estimation. The study further applies a group mean method and quantile binning to classify carbon intensity into 10 levels, which are aggregated into 5 urban land-use intensity types. Scenario simulations show that enhancing green coverage and installing rooftop photovoltaics could reduce approximately 50,000 and 1.5 million tCO₂e annually, respectively. The proposed methodology provides a scalable and operable urban carbon governance model, offering a scientific basis for implementing carbon-based development intensity control and emission quota allocation in future urban planning.