Fine-grained urban carbon stock management and decision-making for land-use regulation require adequate, effective and theoretically supported methods. Based on multi-temporal, high-resolution land cover data, temporal structural differences in the carbon stocks of different functional zones were revealed by calculating and analyzing the carbon storage at multiple times. Carbon storage changes and the key transition pathways affecting it were then analyzed using the Patch-generating Land-Use Simulation (PLUS) model. GeoDetector was employed to analyze the explanatory power of different factors affecting the carbon storage changes, and the corresponding driver was ranked. By incorporating the ranked drivers into scenario parameter settings to construct closed-loop consistency validation indicators, a reasonable and practical assessment was conducted. The results showed that total carbon stock in Shenyang City decreased from 92.47 × 10 6 t (corresponding to 13.61 MgC·rm⁻ 2 ) in 2000 to 86.18 × 10 6 t (13.08 MgC·rm⁻ 2 ) in 2015. The area of high-carbon zones (˃5 MgC·ha⁻ 1 ) accounted for 914.5 km 2 , or 3.35% of the urban area. Land use (especially crop and forest) and the interaction between population density and land use had the greatest influence on the spatial differences in carbon storage. Under the ecological protection scenario, the total carbon stock increased to 87.62 × 10 6 t (a relative increase of + 1.67% relative to the business-as-usual scenario). The difference in total emissions relative to the Emission Database for Global Atmospheric Research (EDGAR) dataset was less than 5%. The minimum difference between driver identification results and scenario response rankings was zero, demonstrating closed-loop consistency. This study presents a theoretically supported and effective technical framework for predicting urban carbon stock evolution and conducting spatial optimization management.
Qiao et al. (Sat,) studied this question.