Study on Low-Carbon Environment Optimization Model for Dynamic Evaluation of Building Life Cycle Consultation

In order to respond to the demand of global climate strategy for intelligent environmental information system, this paper constructs a dynamic decision support system for carbon management in the whole life cycle of built environment, which integrates dynamic LCA, BIM, time-sharing power grid emission factors, and IoT data to form a unified environmental information architecture. Real-time feedback of design iteration and carbon performance is realized through the “double-loop and three-level” mechanism, and multi-objective genetic algorithm is used to optimize implied carbon, operating carbon, cost, and construction period. The case shows that the carbon emission in the whole life cycle is reduced by 28% on average, the decision-making period is shortened by 22%, and the carbon recovery period is advanced to the seventh year. The system has strong robustness, good interoperability, and popularization potential. This study provides a new paradigm of adaptive environmental information system for complex infrastructure, which can be extended to urban green infrastructure management.