Data Insights From Over 500 Building Projects for Low-Carbon Structures

By Jonathan Broyles, Mel Chafart, Martín Torres, Demi Fang

In 2022, building operations and material production were responsible for 37% of global anthropogenic greenhouse gas emissions. Of these emissions, about three-quarters were from the direct and indirect emissions from energy use in buildings (i.e., operational carbon), and a quarter was from building materials and construction (i.e., embodied carbon). Efforts to reduce embodied carbon in both research and practice have lagged behind efforts for reducing operational emissions. As such, there is an urgent and critical need to understand and reduce embodied carbon in the built environment to mitigate impacts of the climate crisis.

To help address this issue, the Structural Engineers (SE) 2050 Commitment Program, supported by the Structural Engineering Institute (SEI) of the American Society of Civil Engineers (ASCE) was formed to catalyze the building design industry’s alignment with the SE 2050 Challenge, in which firms pledge to “understand, reduce, and ultimately eliminate embodied carbon emissions in structural systems by 2050.” Signatory firms, the structural engineering firms who have committed to the pledge, are required to submit project data to an anonymized database hosted by the SE 2050 Committee. While individual signatory firms might be limited to collecting data on their own projects, the SE 2050 Database (currently in beta version) allows simple and secure collection of many relevant project characteristics for hundreds of diverse projects across different firms, locations, and building types.

The SE 2050 Database contains a diverse set of project data with a range of building characteristics, structural engineering design features, and structural system embodied carbon emissions, measured as Global Warming Potential (GWP) (kilogram of carbon dioxide equivalent, kg CO2e). As of November 1, 2023, the SE 2050 Database had 522 project submissions. The SE 2050 Data Science Team (DST) was formed as an internal working group within the SE 2050 Committee to perform a preliminary analysis of the data. As more data is collected, the collection and analysis will be refined to continue to inform the SE 2050 Commitment Program. This analysis identifies relationships between the embodied carbon of structural systems and building characteristics. These insights are meant to inform structural engineers, building practitioners, and policymakers to facilitate widespread embodied carbon reduction in the structural systems of buildings.

A brief overview of the methodology for data filtering and analysis is summarized here. For more details, the reader is referred to the SE 2050 Commitment Program 2023 Data Analysis and Findings Report.

Before analyzing the data, the SE 2050 Database was processed to filter out project entries deemed out-of-scope. The filtered project data was categorized into two datasets according to the life-cycle stages reported: stage A with 241 entries; and stages A to C with 100 data entries, referred to as Upfront Carbon and A to C, respectively. After reviewing the filtered data, the Upfront Carbon subset was chosen as the primary dataset to be analyzed because it contained the largest number of projects and represented the life cycle stages where structural engineers have the largest influence on structural embodied carbon emissions.

GWP Intensity Excluding Biogenic Carbon was selected as the performance objective (i.e., the primary metric studied), herein referred to as GWP Intensity. An exploratory data analysis was first conducted on the Upfront Carbon dataset, which involved creating a series of plots that demonstrate the relationships (or lack thereof) between GWP Intensity and project features. This included building and structural features such as gross floor area, stories above grade, typical floor live load, and primary horizontal gravity system (refer to the full report for the full list of building and structural features). The exploratory data analysis was followed by more detailed statistical analyses to clarify the importance of relationships in the data. These analyses included linear regressions and machine learning regressions with feature importance to confirm the trends between GWP Intensity and salient building features identified in the exploratory data analysis.

The analysis of the Upfront Carbon dataset revealed a broad distribution of GWP Intensities, indicative of the spread of building projects and building characteristics. Figure 1 shows the box-and-whisker plot overlaid with a strip plot showing all design data points in the Upfront Carbon dataset. The median GWP Intensity (gray number) is 234 kg CO2e/m2 and the mean (dark blue number marked with an X) GWP Intensity is 270 kg CO2e/m2.

The data exhibits a wide spread of GWP Intensities. The 80th percentile value from this Upfront Carbon dataset is proposed as a recommended limit for upfront (A1-A5) structural embodied carbon: 350 kgCO2e/m2. A GWP Intensity (excluding biogenic carbon) larger than this proposed threshold might warrant further design intervention to reduce its high embodied carbon.

Although not all plots from the analysis are shown in this article, the strongest relationship identified is shown in Figure 2, between Total GWP and gross floor area. The linear regression demonstrated an R2 value of 0.84 (R2=1 indicates a perfect linear relationship; R is the Pearson correlation coefficient, which is a measure of the strength and direction of the linear relationship between two variables.) This result indicates that the size of building projects is a critical design consideration when aiming to reduce embodied carbon emissions.

Another important result from the data analysis is the importance of system selection (including the structural material of the system) on embodied carbon emissions of structures in buildings. As seen in Figure 3, concrete and steel systems tend to have higher GWP intensities, which are seen across all three structural system features (i.e., primary horizontal gravity system, primary vertical gravity system, and primary lateral system).

Lastly, machine learning regression models were trained on different subsets of the Upfront Carbon dataset to distill potentially multivariate relationships into a hierarchy of building features with the largest influence on structural embodied carbon. For more details on these findings, the reader is referred to the full report. In short, the linear regressions and feature importance from the machine learning models showed the following design features to have relatively stronger correlations with GWP Intensity when compared to other design features:

The strongest correlation was found between Total GWP and gross floor area. The machine learning feature importance found gross floor area, typical floor live load, and mean roof height to be the strongest predictors of GWP Intensity. Additional influential features identified with this analysis include the building use type, primary horizontal gravity system, and primary vertical gravity system. These key findings suggest that structural engineers and building designers should consider these building features to more effectively reduce structural embodied carbon emissions.

The wide distribution of GWP Intensity in the current database can be explained by a variety of factors and therefore should not be used to establish benchmarks. With a higher quantity, quality, and granularity of data, a clearer understanding of building projects can emerge to establish meaningful benchmarks. While more data is needed to confidently establish program- or system-specific benchmarks, a recommended threshold for upfront carbon is proposed. Using the 80th percentile GWP Intensity limit for Upfront Carbon (A1-A5) dataset, the recommended threshold for structural embodied carbon emissions is 350 kgCO2e/m2. Structural engineers and building designers should use this value to determine if the structural design would have poor embodied carbon performance.

As the SE 2050 Database grows, these results will be regularly updated to ensure that the industry is supplied with the most up-to-date, science-based recommendations to support embodied carbon emission reduction. Furthermore, future iterations of the analysis may be able to make more definitive conclusions, including program- and system-specific benchmarks.

The data analysis revealed limitations and opportunities to improve the SE 2050 Database. The underlying LCA tools to obtain embodied carbon performances for design projects have different embodied carbon coefficients and assumptions, inhibiting comparability. Furthermore, due to the database’s anonymity, the SE 2050 team is unable to clarify unusual or unexpected data entries with the signatory firms, so potentially incorrect data are left uncorrected. Thus, the Sustainability Committee under the Structural Engineering Institute has written a pre-standard document to help signatory firms correctly calculate and report the embodied carbon emissions of structural systems. Despite these limitations, this analysis and corresponding results reveal useful trends to inform better project data collection and produce more robust embodied carbon benchmarks.

More high-quality project data entries can improve the findings of this inaugural analysis. Practicing structural engineers are strongly encouraged to submit their project information to the SE 2050 Database to contribute to this effort to illuminate features important to structural embodied carbon. Furthermore, recommendations from this analysis related to improving data collection will be included in future updates to the SE 2050 Database, such as requiring the submission of structural material quantities with each project, requiring embodied carbon emissions to be separated by LCA stages, and providing further guidance on biogenic carbon emissions reporting.

This first analysis of the SE 2050 Database identifies important design considerations for structural engineers to better reduce embodied carbon emissions in buildings. First, designers should consider how much floor area is needed for a project, as gross floor area was found to have the highest correlation to GWP. Structural engineers should pay special attention to the type of structural system selected, as concrete and steel systems trended with higher embodied carbon emissions. These findings may already be intuitive for those designing with embodied carbon in mind but are now quantitatively validated with empirical data from the industry. The quality of such insights will only be improved with future improvements in the database. Importantly, this report highlights that there are different pathways and design choices that can reduce carbon emissions; therefore, it would be beneficial for all building stakeholders to collaborate early and throughout the building design process.

The analyses used in this study can be improved upon with more complete and verifiable data to better understand which building characteristics, and combination of building characteristics, are most important to consider for embodied carbon emission reduction. Future iterations of this study can inform data-driven policy and guidelines through feature-importance hierarchies and feature-specific embodied carbon benchmarking. ■

Embodied Carbon: The carbon emissions associated with the production life-cycle of building materials, including material extraction, transportation, production, manufacturing, use, maintenance, replacement, and end-of-life.
Global Warming Potential (GWP, in kg CO2e): A measure of how much energy the emissions of 1 kg of a greenhouse gas will absorb over a given period of time, relative to the emissions of 1 kg of carbon dioxide (CO2). This metric enables a common unit of measure of the global warming impacts of different greenhouse gasses. The larger the GWP, the more that a given gas warms the earth compared to CO2 over a time period (typically 100 years).
Global Warming Potential Intensity (GWP Intensity, in kg CO2e/meter2): A measure of GWP normalized by the Gross Floor Area of a building. Note that biogenic carbon is excluded in this metric due to data limitations.
Gross Floor Area: A measure of the total horizontal area, measured in plan, taken to the outer edge of the exterior envelope. The gross floor area is consistent with the architectural information of the building project.
Life Cycle Assessment (LCA): A method of environmental accounting in accordance with International Organization for Standardization (ISO) 14040 and ISO 14044 that tracks the inputs from nature (e.g., materials and resources) and outputs to nature (e.g., waste, carbon dioxide, and methane) considering all of the processes that take place during the manufacture, use, and disposal of a product or system. An LCA can assess several outputs, referred to as mid-point indicators, including GWP.
Life Cycle Stage: A temporal subdivision of a product or system’s life cycle. In the context of a building product, these modules are the Product stage (modules A1-A3), Construction stage (modules A4-A5), Use stage (modules B1-B7), and End-of-life stage (modules C1 to C4). This article focuses on the GWP results in the Product and Construction (modules A1-A5) life cycle stages.

About the Authors

Jonathan Broyles, Ph.D, is a Postdoctoral Research Associate and Lecturer at the University of Colorado Boulder, where he researches at the intersection of structural engineering, sustainability, computational design, and acoustics.

Manuel Chafart, PE, is a Research Engineer at the Life Cycle Lab at the University of Washington and a Research Affiliate at the Carbon Leadership Forum. His work focuses on providing more access to data on low carbon design of buildings in North America.

Martín Torres, PE, is a Ph.D student at the University of Colorado Boulder, where he is researching novel methods of uncertainty modeling for whole-building life cycle assessment.
Demi Fang, Ph.D, is incoming Assistant Professor at Northeastern University School of Architecture, with an affiliate appointment in Civil and Environmental Engineering. Her research includes data-driven approaches to mitigating the environmental impacts of structural systems in design.