Metabolic Scaling Analysis of Building Energy Efficiency: A Case Study of Massachusetts Institute of Technology
Name
HSU-minahsu-MEng-CEE-2025-thesis.pdf
Description
Thesis PDF
Size
3.49 MB
Format
Adobe PDF
Checksum (MD5)
050c8f3db4cc62dacaea72c5634c22f4
Author(s)
Hsu, Yu-Hsuan
Advisor(s)
Saavedra, Serguei
Date Issued
May 2025
Publisher
Massachusetts Institute of Technology
Abstract
The building sector plays a critical role in global energy consumption and carbon emissions, accounting for 21% of global GHG emissions (12 GtCO₂-eq) and 31% of global final energy demand (128.8 EJ) in 2019 (Cabeza et al. 2022). This reality underscores the urgent need to enhance energy efficiency within the sector. This research applies ecological metabolic scaling principles to building energy analysis, utilizing the Massachusetts Institute of Technology (MIT) campus as a case study. Analogous to biological systems, where an animal’s metabolic rate scales to 3/4 power of its mass, our findings indicate that larger buildings, similar to larger organisms, are inherently more energy efficient.
Furthermore, an analysis of overall energy consumption at MIT from 2009 to 2020 reveals a steady decline, though not proportionally, as the scaling exponent fluctuated with a decreasing trend (<3/4), indicating improved efficiency in larger buildings. However, the COVID-19 pandemic in 2020 acted as a major shock, disrupting this trend. This disruption was likely driven by operational and behavioral changes, including reduced occupancy, increased remote work, and adjustments to ventilation and heating systems to ensure health and safety. These shifts highlighted the system’s tendency to return to the baseline scaling exponent of 3/4, demonstrating regression to the mean and ultimately pushing efficiency back to its prior baseline level of 25%.
Additionally, the study includes case analyses of specific buildings on the MIT campus to provide deeper insight into comparative energy performance. While several guidelines for energy systems have been proposed, certain limitations remain. Future research should focus on expanding the dataset to help validate the applicability of these findings to other contexts while also accounting for variations in building types. Ultimately, this study aims to facilitate the development of more effective policies and innovations in building energy management.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
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