Document Type

Article

Publication Date

3-13-2025

Department

Department of Civil, Environmental, and Geospatial Engineering

Abstract

Achieving Leadership in Energy and Environmental Design (LEED) certification is a key objective for sustainable building projects, yet targeting LEED credit attainment remains a challenge influenced by multiple factors. This study applies machine learning (ML) models to analyze the relationship between project attributes, climate conditions, and LEED certification outcomes. A structured framework was implemented, beginning with data collection from the USGBC (LEED-certified projects) and US NCEI (climate data), followed by preprocessing steps. Three ML models—Decision Tree (DT), Support Vector Regression (SVR), and XGBoost—were evaluated, with XGBoost emerging as the most effective due to its ability to handle large datasets, manage missing values, and provide interpretable feature importance scores. The results highlight the strong influence of the LEED version and project type, demonstrating how certification criteria and project-specific characteristics shape sustainability outcomes. Additionally, climate factors, particularly cooling degree days (CDD) and precipitation (PRCP), play a crucial role in determining LEED credit attainment, underscoring the importance of regional environmental conditions. By leveraging ML techniques, this research offers a data-driven approach to optimizing sustainability strategies and enhancing the LEED certification process. These insights pave the way for more informed decision-making in green building design and policy, with future opportunities to refine predictive models for even greater accuracy and impact.

Publisher's Statement

Publisher's record: https://doi.org/10.3390/su17062521

© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Supporting Data

Data for this study were collected from publicly available data sources. The LEED project directory, provided by the U.S. Green Building Council (USGBC), includes information on LEED-certified projects worldwide and was accessed from their official website. Climate data were obtained from the National Centers for Environmental Information (NCEI), which provides U.S. Climate Normal based on a uniform 30-year period from approximately 15,000 U.S. weather stations.

Publication Title

Sustainability (Switzerland)

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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