Four researchers associated with the University of Washington have been included in Research.com’s 2026 Best Rising Stars of Science rankings, highlighting scientific contributions across energy storage, atmospheric science, sustainable construction and artificial intelligence. Assistant Professor Amos Darko, Construction Management, is ranked #69 nationally for Best Rising Stars of Science 2026 Ranking. Assistant Professor Darko’s work was recognized for its impact on sustainable construction, green buildings, and the use of artificial intelligence in building design and performance. Additional information about the institution’s…
Research Theme: Data Science & Spatial Analysis
Data-driven methodologies like GIS and remote sensing, as well as “big data”, artificial intelligence, and other methods of scholarship rooted in analyzing large datasets
Material use and embodied carbon from new construction buildings in North America: Analysis and projection to 2050
Ashtiani, M., Benke, B., Shen, Y., Jungclaus, M., Lewis, M., Rempher, A., Esau, R., & Simonen, K. (2026). Material use and embodied carbon from new construction buildings in North America: Analysis and projection to 2050. Journal of Building Engineering, 130, Article 116959. https://doi.org/10.1016/j.jobe.2026.116959
Abstract
Buildings are a major consumer of raw materials and emitter of greenhouse gases (GHGs), yet data on their resource use and embodied environmental impacts remain limited. This study investigates the material use intensity (MUI) and embodied carbon intensity (ECI) of new construction commercial and multifamily residential buildings in North America using data from 239 building life cycle assessment (LCA) models. This study develops a benchmark data analysis framework to provide MUI and ECI values, defined in units of mass and embodied carbon per building floor area, across different building typologies, structural systems, and material categorizations. Results show a wide variability in building-level MUI (269-2860 kg/m2) and ECI (115-1030 kgCO2e/m2) within A1-A3 LCA modules. The study also establishes material-level MUIs and ECIs, highlighting that concrete, steel, gypsum, masonry, and wood and composites account for more than 96% of the mean MUI, while concrete, steel, insulation, aluminum, and applied fireproofing account for more than 80% of the mean ECI across all buildings. Using a bottom-up approach, future material consumption and embodied carbon emissions for new construction buildings in the US from 2020 to 2050 were projected to establish a business-as-usual (status quo) baseline under constant-intensity assumptions. Concrete and steel remain the largest contributors to embodied carbon of buildings in 2050, accounting for 38% and 24% of total emissions, respectively. Findings indicate that effective building decarbonization requires concurrent accounting of material use and embodied carbon at both building and material levels. The study calls for standardized material-level analysis methods to improve comparability across studies and support data-driven decarbonization policies and practices. Methods and results are shared as open-access code and an interactive visualization dashboard to support reuse and transparency.
Keywords
Embodied carbon; Material use; Life cycle assessment; Building; Projection; Benchmark
A review of building-scale LCA tools: recent trends, gaps and future directions
Torabi, M., Huang, M., Evins, R., & Simonen, K. (2026). A review of building-scale LCA tools: recent trends, gaps and future directions. Journal of Building Performance Simulation, 1–28. https://doi.org/10.1080/19401493.2026.2663472
Abstract
This study reviews active building-scale LCA tools in North America to evaluate how effectively they support the transition toward net-zero and carbon-negative design. A structured Characterization Framework was developed through a targeted literature review and stakeholder input to identify key features that enable low-carbon building design. Thirteen continuously updated and widely used tools were analyzed to assess trends, gaps, and opportunities. The results reveal positive developments such as greater self-sufficiency through embedded defaults, expanded life-cycle scope, and enhanced user control. However, significant gaps persist, including limited treatment of carbon sequestration, dynamic climate modeling, and novel material integration, as well as inconsistent data, simplistic scenarios modeling and limited functionality for early-stage design. Overall, while building LCA tools are becoming more transparent and flexible, advancing time-sensitive impact modeling, carbon sequestration accounting, and interoperability with design workflows will be essential to achieve more accurate, consistent, and forward-looking assessment that enable carbon-positive building practices.
Keywords
Building LCA tool; Carbon sequestration; Carbon reduction; Life cycle assessment; Tool review
Tool Requirements for Life Cycle Assessment in the Innovation of Novel Carbon-Storing Construction Materials
Huang, M., Ellingboe, E., Lin, M.-Y., Echenagucia, T. M., & Simonen, K. (2026). Tool Requirements for Life Cycle Assessment in the Innovation of Novel Carbon-Storing Construction Materials. Applied Sciences, 16(8), 4040. https://doi.org/10.3390/app16084040
Abstract
Novel carbon-storing construction materials have the potential to reduce greenhouse gas emissions by removing carbon dioxide from the atmosphere and storing it in long-lived building products. In order to understand the full benefits and shortcomings of carbon-storing materials, life cycle assessments (LCAs) must be performed. However, material innovators who are looking to perform LCAs of their products during early-stage research and development (R&D) face many challenges. While these challenges have been reported in the literature, this information has been fragmented and required a more comprehensive investigation. We explored these LCA challenges by holding an in-person workshop with sixteen R&D teams who were developing carbon-storing materials and building designs. From the data collected in this workshop, we found that the R&D teams struggled with data availability, biogenic carbon, and uncertainty, which confirmed our findings from the literature. They also struggled with various other LCA topics. Since current LCA tools lack functions that would be useful for this user group, we also proposed a list of tool ideas that could address their LCA needs, which can inform future LCA tool development.
Keywords
LCA; sustainability; early-stage; low-carbon; R&D; workshop
A Proxy Method to Bridge LCA Data Gaps Using Automated Material Classification and Probabilistic Under-Specification
Ellingboe, E., Huang, M., Sultana Priyota, A., & Simonen, K. (2026). A Proxy Method to Bridge LCA Data Gaps Using Automated Material Classification and Probabilistic Under-Specification. Environmental Science & Technology, 60(16), 12268–12279. https://doi.org/10.1021/acs.est.5c12282
Abstract
Life cycle assessments (LCAs) are essential for understanding the environmental impacts of material production. However, gaps in life cycle inventory (LCI) data for material and chemical inputs present a key challenge for LCA practitioners, especially in the early design stages. Strategies for filling in these gaps require additional time and expertise, which can hinder the LCA’s completion. This study combined automatic material classification and probabilistic under-specification to create a time-efficient method to fill material LCI data gaps. To illustrate the proposed method, proxy environmental impact distributions were generated using publicly available material LCI data classified into the ChemOnt chemical taxonomy using the open-source chemical classification software ClassyFire. Input materials with data gaps were then classified into the same taxonomy, where proxy environmental impact values could be selected from the available distributions to quickly fill in any data gaps. Although these methods were applied to classify material production processes available in the Federal LCA Commons and Ecoinvent databases, they can be applied to any LCA database. This study shows that classifying materials by their chemical structure produces taxonomies with increased granularity relative to industrial classification, improving the ability of under-specified proxy data to be used for differentiating the environmental impacts of competing designs.
Keywords
Life Cycle Assessment; Data Gap; Proxy Data; Chemical Classification; Novel Materials; Probabilistic Under-Specification
Exploratory Data Analysis of a North American Whole Building Life Cycle Assessment datasets
Shen, Y., Benke, B., Ashtiani, M., Huang, M., & Simonen, K. (2025). Exploratory Data Analysis of a North American Whole Building Life Cycle Assessment datasets. Building and Environment, 286, Article 113655. https://doi.org/10.1016/j.buildenv.2025.113655
Abstract
The building construction sector is a major contributor to global greenhouse gas emissions, with embodied carbon—the emissions from material production, use, and disposal—forming a significant portion. While whole building life cycle assessment (WBLCA) quantifies such impacts, detailed statistical analysis for interpretation of WBLCA data remains underutilized. This study addresses the gap by introducing a systematic exploratory data analysis (EDA) framework applied to a harmonized and high-resolution dataset of 244 real-world North American buildings. The core steps in the EDA framework include distinguishing attributes, univariate analysis, bivariate analysis, and feature engineering. These steps address the different data challenges, such as high dimensionality, mixed attribute types, missing values, outliers, and multivariate relationships through the evaluation of robust selections of statistical methods in EDA. Bivariate analysis (e.g., mutual information, one-way ANOVA, post-hoc analysis, and two-way ANOVA) and feature engineering methods quantified the correlation and differences in pairwise and global relationships. Embodied carbon intensity weakly correlated with most meta-features, while materials and building use emerged as the most influential factors. Given that the dataset is uniquely comprehensive and disaggregated, a more nuanced and detailed understanding of environmental impact patterns and relationships is possible. This research demonstrates that following the systematic EDA framework provides a well-defined process to address the database challenges. Its integration into WBLCA dataset evaluation enhances interpretation and supports informed decision-making for low-carbon building design and decarbonization strategies that a conventional simplified analysis would miss. Moreover, it helps to build the insights necessary for advanced analysis and predictive modeling.
Keywords
Life cycle assessment; Whole building life cycle assessment; Embodied carbon; Data analysis; Exploratory data analysis; Statistical analysis; Building decarbonization
Developing digital twins for bridge infrastructure: Roadmap and challenges from a proof-of-concept R&D study
Borjigin, O., Sturts Dossick, C., Treece, B., Thonstad, T., Bernard, T., & Motley, M. (2026). Developing digital twins for bridge infrastructure: Roadmap and challenges from a proof-of-concept R&D study. Journal of Information Technology in Construction (ITcon), 31, 917-938. https://doi.org/10.36680/j.itcon.2026.039.
Abstract
The exploration of Digital Twins (DT) technology in the Architecture, Engineering, Construction, and Operation (AECO) industry has gained momentum in recent years, with numerous studies proposing frameworks for its development. However, few real-world infrastructure applications have been systematically documented to guide future practitioners and researchers. This study addresses this gap by providing an empirical example of DT design and development through a proof-of-concept research and development (R&D) project. The I-90 Homer M. Hadley Bridge (I-90 Bridge) DT project, led by the University of Washington (UW) DT research team, was selected as a case study to demonstrate the application of DT technology for bridge health monitoring. Using a vignette-style narrative approach, the study integrates data from semi-structured interviews with project team members and project documentation generated during the project to illustrate how the system was conceptualized, developed, and delivered. The findings reveal that interoperability emerged as a consistent theme throughout the project, including technical challenges (legacy systems, proprietary programming, lack of standardization) and organizational challenges (multi-stakeholder engagement, organizational silos). Recognizing these challenges can help practitioners and researchers better identify key problems to address, thereby supporting a successful adoption of DT technologies.
Keywords
Digital Twins; Bridge Infrastructure; Organizational Interoperability; Technical Interoperability; Research & Development; Case Study
I-90 Bridge Digital Twin Project feature
Professor Carrie Sturts Dossick (Construction Management) is on the project team that has created a digital twin model of the I-90 bridge in Seattle. Monitoring this bridge, which now includes the world’s first light rail crossing on a floating bridge, is an innovative and collaborative project evolving in real-time. Read the full feature story on the Civil & Environmental Engineering website here.
2025 Innovation in the Construction Industry
Prof. Dossick’s CM515 Spring 2025 Class. Eds. Dossick, Carrie. & Ray, Lauren. (2025). 2025 Innovation in the Construction Industry. University of Washington. Pressbooks. Seattle, WA. https://uw.pressbooks.pub/2025innovationcm/
Abstract
A collection of case studies about adopting new technologies and changing practices in design, construction, and operations of the built environment.
Keywords
Technology; Engineering; Agriculture; Industrial Processes
Partial Least Squares Structural Equation Modeling of Challenges to Existing Residential Building Net Zero Carbon Retrofitting
Abstract
Residential buildings play a significant role in global energy usage and carbon emissions. In Hong Kong, they contribute to 27% of energy usage and associated carbon emissions. Retrofitting residential buildings to net zero carbon (NZC) is an efficient way to lower carbon emissions and prevent climate change. However, the widespread adoption of NZC retrofitting in the industry has been limited by several challenges, which have rarely been addressed in research. This study intended to evaluate the linkages among various challenges while assessing their impacts on NZC retrofitting of existing residential buildings. Data were collected through a questionnaire survey with 123 residential building occupants in Hong Kong, whose perspectives are largely ignored in existing building retrofit research. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the data. Outcomes indicated that technical and social challenges have a considerable negative effect on residential building NZC retrofitting. In addition, this study highlights the connections between challenge categories and presents a predictive model illustrating the relationships between challenges and residential building NZC retrofitting. Theoretically, the outcomes of this study provide new insights into the relationships between residential building NZC retrofitting challenges and their interactive effects, revealing that the challenges influence one another and do not exist in isolation. Practically, the findings could be useful to policymakers and practitioners seeking to promote NZC retrofitting by enabling the development of effective policies and strategies to mitigate the identified challenges.