Mao, DingXu, SaiWang, JayShen, LinhuaHe, Wei2026-01-072026-01-072026-01-05Sustainable Cities and Society, ISSN: 2210-6707 (Print), Elsevier BV, 107118-107118. doi: 10.1016/j.scs.2026.1071182210-6707http://hdl.handle.net/10292/20449Urban district heating systems are vital infrastructures of sustainable cities, providing efficient and centralized thermal energy to residential and industrial users. However, these systems consist of numerous interdependent components that are prone to faults, which can disrupt heat supply and compromise service reliability. Identifying critical components to maintain system stability is crucial for enhancing the resilience and sustainability of urban energy infrastructure. Critical components are generally determined by evaluating the consequences of failures, which involves simulating all possible fault scenarios, a process that is computationally expensive and time-consuming. To address this challenge, we propose a comprehensive component importance identification framework. This framework incorporates two methods: the Importance Calculation Method (ICM), which operates under normal system conditions, and the Failure-Simulation-Based Method (FSM), which simulates failure consequences. These methods evaluate component criticality under both independent and cascading failure scenarios, incorporating topological and functional perspectives. To validate the proposed framework, gridded heating system models of varying scales, comprising 4-, 9-, 16-, and 25-node configurations, were developed. Applying the framework to these models revealed a strong correlation between ICM and FSM results: the topological importance index in ICM showed a high correlation with FSM’s functional consequence indices (ρ > 0.75), while the functional importance indices achieved even higher correlations (ρ = 0.94–0.97). Finally, the framework was applied to a real-world district heating system in China, where it successfully identified critical pipes and demonstrated the effectiveness and practical value of the proposed ICM through comparison with traditional fault-simulation-based methods.This is the Author's Accepted Manuscript of an article published in Sustainable Cities and Society. The Version of Record is available at DOI: 10.1016/j.scs.2026.1071180502 Environmental Science and Management1205 Urban and Regional Planning3302 Building3304 Urban and regional planning4406 Human geographyJournal ArticleOpenAccess10.1016/j.scs.2026.107118