Abstract:Coal-to-methanol remains the dominant industrial pathway for methanol production; however, its significant carbon emissions pose major challenges to the chemical industry′s transition toward green and low-carbon development. As global methanol demand continues to grow, addressing the environmental burden of coal-based production has become increasingly critical. Carbon capture, utilization, and storage (CCUS) is widely recognized as a promising solution for large-scale emission reduction. However, its high energy consumption, process complexity, and potential leakage risks can offset some of the net climate benefits. Therefore, a comprehensive and scientifically robust carbon emission accounting framework is essential for accurately evaluating the mitigation potential of CCUS across the entire coal-to-methanol value chain. Integrating CCUS into coal-to-methanol systems introduces a range of challenges due to complex inter-unit interactions and the nonlinear behavior of material and energy flows. Existing carbon accounting standards are often difficult to apply directly, as they fail to capture internal carbon transfers among subsystems and overlook feedback mechanisms induced by CCUS. To address these limitations, this study develops a full-process carbon emission accounting framework tailored for coal-to-methanol systems with integrated CCUS. The framework aims to fill current methodological gaps, enhance transparency and comparability of emission data, and support scientific evaluation of emission reduction performance at both process and system levels. The framework defines system boundaries encompassing raw material input, syngas generation, methanol synthesis, purification, CCUS operation, and product delivery. Layered and categorized accounting methods are applied to systematically trace carbon sources, flows, and sinks throughout each stage. To improve accuracy and represent process dynamics, the framework is coupled with Aspen Plus process simulations, allowing real-time tracking of carbon flows under various operational scenarios. This coupling overcomes limitations of static accounting approaches and enables quantitative assessment of the impact of process integration on carbon balance. Sensitivity analysis is conducted to evaluate the influence of uncertain parameters on accounting results, thereby assessing the robustness of the proposed method. A case study of an industrial-scale coal-to-methanol plant with an annual capacity of 1.2 million tons validates the framework. Results indicate that the baseline carbon emission intensity of the conventional process is 3.00 tons of CO2 per ton of methanol, which decreases to 1.88 tons after CCUS integration. Despite an 83.1% CO2 capture rate, the net emission reduction rate is only 37.8% due to emissions from CCUS operations. Further analysis reveals that maximizing mitigation potential requires coordinated optimization of both the gasification and acid gas removal units. Overall, the proposed framework provides a rigorous and generalizable approach for carbon emission assessment in coal-to-methanol and other carbon-intensive industries. Close-