A novel framework of the Natural–Anthropogenic Carbon Estimation Scheme (NACES) for China's megacities

High-resolution simulation of urban carbon emissions is critical for achieving national carbon-peaking and carbon-neutrality targets. Previous studies that rely on sectoral fossil-fuel emission inventories often fail to capture the spatial heterogeneity and dynamic evolution of CO 2 fluxes within cities. In this study, we develop the Natural–Anthropogenic Carbon Estimation Scheme (NACES) by fusing multi-source data, and map urban CO 2 fluxes to 100 m grid cells to perform hourly CO 2 flux simulations for four megacities: Beijing, Shanghai, Guangzhou, and Shenzhen. NACES reproduces the temporal variability and absolute magnitudes of CO 2 fluxes well at eight eddy-covariance (EC) sites, with R 2 reaching 0.81 at the Beijing Shuangqing station. While exhibiting broadly consistent large-scale trends with ODIAC (Open-source Data Inventory for Anthropogenic CO 2 ) and EDGAR (Emissions Database for Global Atmospheric Research) inventory products, NACES can effectively capture 74.66%–82.93% of diurnal carbon-flux variability in megacities and distinctly uncover critical emission hotspots that conventional kilometer-scale inventories have masked. All four cities display pronounced diurnal variability in carbon fluxes, yet differ markedly in peak fluxes and spatial heterogeneity: Beijing's high fluxes are concentrated in the urban core and along major traffic arteries; Shanghai's largest emission zones are centered on the central business district and large thermal power plants; Guangzhou shows a multi-centric pattern; and Shenzhen exhibits a relatively even spatial distribution. Time-series analysis from 2019 to 2023 indicates that Shanghai was most affected by COVID-19 mobility restrictions and lockdowns, with mean annual CO 2 flux declining by 12.70%; Beijing, Guangzhou, and Shenzhen experienced declines of 7.54%, 3.44%, and 3.50%, respectively. NACES effectively reconstructs the locations, magnitudes, and temporal dynamics of high-flux corridors and point sources, enabling a refined depiction of the coupled natural–anthropogenic carbon cycle and addressing limitations of existing inventories in characterizing intra-urban variability.