Urban carbon emissions significantly contribute to climate change, exacerbating environmental issues such as global warming. Understanding carbon metabolism is vital for identifying key emission sources and implementing targeted mitigation strategies. This study presents an innovative carbon metabolism analysis framework that integrates an ecological network analysis (ENA) with land use dynamics, enriching the theoretical system and providing policy recommendations for sustainable urban development. We investigated carbon metabolism in the Beijing–Tianjin–Hebei Urban Agglomeration (BTHUA) from 2000 to 2020 using land use and statistical data. The ENA method quantified the ecological relationships between land use compartments. Our findings revealed that industrial and transportation land exhibited the highest carbon emission density, while forest land demonstrated the highest carbon sequestration density. Notably, the negative net horizontal carbon flow indicated that land use changes exacerbated the disorder of carbon metabolism. The increasing mutualism index suggested a reduction in the negative impacts of land use changes on carbon metabolism. This study highlights the importance of spatial planning in transforming ecological relationships and provides a comprehensive understanding of carbon metabolism dynamics influenced by land use changes. The insights gained can inform effective mitigation strategies in the BTHUA and similar urban agglomerations, ultimately contributing to sustainable urban development.