This study evaluates the effectiveness of occupant-centric control for enhancing carbon performance during building operation, extending beyond the conventional objective of maintaining thermal comfort. An occupant-centric control framework is proposed that integrates real-time metabolic rate (MET) and clothing insulation (CLO) into the HVAC control system through a feedback-based decision-making loop. The methodology follows a three-stage evaluation process: building energy simulations examining 110 combinations of MET (0.7–1.7 met) and CLO (0.1–1.0 clo); controlled test-bed experiments with eight participants across nine MET–CLO conditions; and an eight-day living lab validation with 11 occupants. All stages were evaluated against a conventional temperature-based control baseline, and carbon emissions were quantified from simulated and measured heating and cooling energy consumption using source-specific emission factors. Results show that dynamic occupant variables significantly influence system-level carbon emissions, with MET exerting a greater impact than CLO under heating conditions. In the living lab, the proposed framework reduced carbon emissions by approximately 63% on average relative to conventional control, while maintaining target comfort levels, and emission patterns observed in simulations were consistently reproduced in field experiments. These findings indicate that occupant-related variables function as critical control inputs shaping operational carbon performance, underscoring the potential of occupant-centric control as a scalable strategy for low-carbon building operation.
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Choi et al. (2026) studied this question.
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