Urban agglomerations, as hubs of population, economic activity, and energy consumption, significantly contribute to greenhouse gas emissions. The interconnected infrastructure, energy networks, and shared economic systems of these regions create complex emission dynamics that cannot be effectively managed through isolated city-level strategies. However, these regions also present unique opportunities for innovation, policy implementation, and resource optimization, making them crucial focal points in efforts to reduce carbon emissions. This study examines China’s three major urban agglomerations: the Yangtze River Delta, the Pearl River Delta, and the Beijing–Tianjin–Hebei region. Utilizing data from 2005 to 2020 and a comprehensive evaluation model (BCPCAM), the research offers more profound insights into the socio-economic factors and collaborative mechanisms influencing emission trends, facilitating the development of targeted strategies for sustainable development and carbon neutrality. The findings indicate that (1) economic development and carbon control can progress synergistically to some extent, as economically advanced cities like Beijing and Shanghai have achieved their carbon peaks earlier; (2) natural resource endowment significantly affects urban carbon emissions, with resource-rich cities such as Tangshan and Handan, where fossil fuels dominate the energy mix, facing considerable challenges in reducing emissions; and (3) notable differences exist in the growth patterns of carbon emissions between urban and rural buildings, underscoring the need for tailored carbon reduction policies.

High-density cities face increasing pressure to curb the rapid growth of building-sector carbon emissions, yet the specific impacts of China’s dual-control policy—regulating both total emissions and emission intensity—remain insufficiently understood. To address this gap, this study aims to quantify how dual-control constraints shape urban building-emission trajectories by developing a dynamic scenario model that integrates both operational and embodied emissions while accounting for technological progress, energy-structure adjustments, and socioeconomic change. The model is applied to Guangzhou, a representative high-density metropolis in China’s low-carbon transition. Three policy scenarios are evaluated: a baseline pathway reflecting existing trends, an energy-conservation pathway emphasizing efficiency improvements, and a deep-decarbonization pathway that combines enhanced efficiency with accelerated clean-energy adoption. The results show that rising residential energy demand is the primary driver of emission growth, whereas technological advancement provides the strongest mitigation potential. Under the energy-conservation scenario, emissions are projected to peak around 2029, consistent with China’s national carbon-peaking target for 2030. Overall, the findings offer clear empirical evidence and actionable policy insights for accelerating urban decarbonization in high-density contexts under dual-control constraints.