Phillips, C. P., Bourassa, S. C., & Virant, M. A. (2024). The State of the State’s Housing 2024: Supply and Affordability in Washington State. Washington Center for Real Estate Research. College of Built Environments, University of Washington.
Year: 2024
Machine Learning in Urban Building Energy Modeling
Abbasabadi, N., & Ashayeri, M. (2024). Machine Learning in Urban Building Energy Modeling. In Abbasabadi, N., & Ashayeri, M. (Eds.), Artificial Intelligence in Performance-Driven Design : Theories, Methods, and Tools: Theories, Methods, and Tools. Wiley-Blackwell.
Abstract
Urban building energy modeling (UBEM) plays a pivotal role in effective urban energy management and the holistic understanding of citywide energy performance. This book chapter delves into the integration of machine learning (ML) in UBEM, covering applications such as predictive energy consumption modeling and optimization, and providing insights into how ML techniques enhance modeling accuracy and efficiency. It explores current UBEM methods, highlighting their strengths and limitations, and discusses the opportunities presented by ML for advancing UBEM approaches. The chapter also introduces a hybrid UBEM approach that combines data-driven and physics-based simulations to enhance modeling accuracy and reduce uncertainties in capturing urban energy use. This fusion of ML and UBEM offers promising prospects for improving urban energy management practices.
Understanding Social Dynamics in Urban Building and Transportation Energy Behavior
Abbasabadi, N., & Ashayeri, M. (2024). Understanding Social Dynamics in Urban Building and Transportation Energy Behavior. In Abbasabadi, N., & Ashayeri, M. (Eds.), Artificial Intelligence in Performance-Driven Design : Theories, Methods, and Tools: Theories, Methods, and Tools. Wiley-Blackwell.
Abstract
This chapter explores the impact of human dynamics, social determinants of public health ( SDPH ), mobility, and occupancy on urban energy use behavior, a topic previously overlooked due to individual buildings or transportation models. A novel, data-driven urban energy model is developed using Artificial Neural Networks ( ANN ), augmented by Garson, Lek's profile and Partial dependence Plot ( PDP ) methods, to holistically evaluate urban energy behavior across Chicago communities, integrating both building and transportation energy use. Utilizing diverse public datasets from the city of Chicago, and validated through cross-validation, the model assesses human dynamics in development of an integrated urban energy modeling. The findings reveal a significant association between SDPH status, mobility, occupancy, and urban energy behavior with household income being a major contributor post accounting for urban spatial patterns and building physical attributes. The study suggests that meeting decarbonization targets in cities requires a broader evaluation encompassing various urban energy determinants. It advocates for emerging technologies and detailed analytical scrutiny, urging researchers and policymakers towards a comprehensive understanding of urban energy use behaviors.
A Hybrid Physics-Based Machine Learning Approach for Integrated Energy and Exposure Modeling
Abbasabadi, N., & Ashayeri, M. (2024). A Hybrid Physics-Based Machine Learning Approach for Integrated Energy and Exposure Modeling. In Abbasabadi, N., & Ashayeri, M. (Eds.), Artificial Intelligence in Performance-Driven Design : Theories, Methods, and Tools: Theories, Methods, and Tools. Wiley-Blackwell.
Abstract
This chapter introduces a hybrid framework that brings machine learning (ML) and urban big data analytics into integrated modeling of indoor air quality, building operational energy, and ambient airflow dynamics. This holistic approach allows for more effective and accurate simulation results for the design of built environments that prioritize both climate and health considerations. To validate this framework, we undertook a pilot study on a naturally ventilated, large-size office building prototype, as provided by the U.S. Department of Energy. This prototype was hypothetically placed in a densely populated area of Downtown Chicago, IL. For our computations, we employed tools, including EnergyPlus, CONTAM, CFD0, and artificial neural networks (ANNs). The findings highlighted the proposed framework's robust ability to evaluate the effects of building energy efficiency strategies, such as natural ventilation. Additionally, it took into account the indoor concentration of outdoor pollution resulting from the implementation of such strategies. Employing the hybrid approach, we achieved an accuracy characterized by an R -squared value of up to 0.96, facilitated by ANNs. Compared to conventional physics-based simulation methods, the hybrid approach further accelerated the simulation process by up to 200 times. This novel framework offers valuable insights to architects and engineers during early-stage design decisions, enabling them to harmonize occupant health considerations with energy conservation objectives, thereby placing health and well-being at the forefront of decarbonization goals.
Exploring U.S. Occupant Perception Toward Indoor Air Quality Via Social Media and NLP Analysis
Ashayeri, M., Piri, S., & Abbasabadi, N. (2024). Exploring U.S. Occupant Perception Toward Indoor Air Quality Via Social Media and NLP Analysis. Journal of Environmental Science and Public Health, 8(2). https://doi.org/10.26502/jesph.96120205.
Abstract
The global implementation of stay-at-home mandates altered people's activities within the built environment, prompting a slowdown in the spread of covid viruses. Nevertheless, this period shed light on previously unforeseen challenges in achieving "better" indoor air quality (IAQ) within buildings, necessitating a focus on building health resilience for future scenarios. This study aims to evaluate occupants' feedback on the impact of stay-at-home measures on IAQ perception in buildings across the U.S. during the first year of the pandemic (2020) and compare it with the baseline from the previous year (2019) nationwide to assess the changes and identify potential areas for IAQ management strategies. Geo-tagged textual data from X (formerly known as Twitter) platform were collected and analyzed using Natural Language Processing (NLP) based on time series sentiment analysis techniques to compute the feedback. Findings indicate that occupants’ negative feedback on IAQ increased during 2020 compared to the baseline. It was also found that public perception of IAQ in 2020 was notably less favorable, potentially due to deteriorating conditions inside homes as people spent more time indoors. The study underscores the potential of NLP in capturing occupant perception, contributing to data-driven studies that can inform design, engineering, and policy-making for sustainable future.
Keywords
Indoor Air Quality; Occupant Perception; COVID Stay-athome; Natural Language Processing (NLP); Time Series Sentiment Analysis
Integrating climate change into state hazard mitigation plans: A five-year follow-up survey of state hazard mitigation officers
Mix, E. C., Hamele, M., Dannenberg, A. L., Freitag, R., & Errett, N. A. (2024). Integrating climate change into state hazard mitigation plans: A five-year follow-up survey of state hazard mitigation officers. PLOS Climate, 3(10), e0000385-. https://doi.org/10.1371/journal.pclm.0000385.
Abstract
Climate change is making disaster events more frequent and intense, increasing the risk to economic security, ecosystem health, and human health and well-being. Hazard mitigation planning, overseen in the United States by the Federal Emergency Management Agency (FEMA), aims to reduce disaster risk by identifying hazards and taking action to reduce their impact. While FEMA policy requires states and territories to consider the risks of climate change in their plans, guidance remains broad. As a result, jurisdictions have taken different approaches to integrating climate change into their hazard mitigation plans (HMPs). Thirty of 56 U.S. State and Territorial Hazard Mitigation Officers (SHMOs) responded to a survey concerning climate planning, building on a similar survey conducted in 2018. A majority of respondents recognized that their jurisdictions are vulnerable to climate change and agreed that climate change is a threat to their jurisdictions both now and in the future. Respondents were motivated to integrate climate change into their HMPs by factors including increased evidence for climate change projections and disaster events in either their jurisdictions or neighboring ones. Among the most frequently reported barriers was reliance on historical patterns of hazard exposure. Most respondents had incorporated at least one climate change adaptation strategy into their HMPs but reported having insufficient resources to plan for and implement climate-related hazard mitigation activities. Findings suggest that state and territorial hazard mitigation planning programs are taking more steps to integrate climate change into their plans and that SHMOs are more aware of the risks that climate change poses than in 2018. Further research is needed to explore how best to support state-level hazard mitigation program response to climate change.
Equity issues associated with the widespread implementation of autonomous vehicles
Fatima, S., Hsiu Lee, C., & Dannenberg, A. L. (2024). Equity issues associated with the widespread implementation of autonomous vehicles. Oxford Open Infrastructure and Health, 2. https://doi.org/10.1093/ooih/ouae002.
Abstract
Autonomous vehicles (AVs), either shared or privately owned, are predicted to become a common transport mode used by the general population in coming decades. Policies governing the use of AVs may increase or decrease social inequities. This review synthesizes existing literature and provides policy recommendations to enhance equity as the use of AVs becomes more widespread. We identified nine areas in which AVs could impact equity: (i) assessment of community mobility needs and priorities, (ii) education and outreach, (iii) disparities in infrastructure quality, (iv) equitable distribution of customer services, (v) access to AVs by persons with low incomes, (vi) shared infrastructure services, (vii) barriers to shared AV use, (viii) access to AVs by persons with disabilities and (ix) disruption of existing transportation jobs. Recommendations for promoting equitable use of AVs include (i) policies governing how jurisdictions oversee AV implementation and (ii) policies addressing how jurisdictions issue permits to AV service providers. Oversight policies include ensuring input from disadvantaged communities, providing subsidies for low-income users, establishing ride-sharing rules to protect vulnerable populations, reviewing the equity implications of proposed AV infrastructure improvements, providing retraining opportunities for those who may lose jobs due to AV implementation and monitoring the impact of AV policies implemented. Permitting processes include ensuring equitable access to AVs for low-income, minority, and older users and persons with disabilities, ensuring equitable distribution of AV service areas and verifying that data from all communities are incorporated into the artificial intelligence algorithms used to guide AVs.
Municipal Sidewalk Inventories: A Tool to Support Compliance with the Americans with Disabilities Act
Cahen, A., Dannenberg, A. L., & Kraft, M. K. (2024). Municipal Sidewalk Inventories: A Tool to Support Compliance with the Americans with Disabilities Act. Transportation Research Record. https://doi.org/10.1177/03611981241281738.
Abstract
Sidewalks are a critical but underresourced part of our transportation system. Despite their importance in promoting equity, health, and safety, sidewalk networks are often underfunded and municipalities may have little information about their condition. We conducted a document review, informant interviews, and a descriptive study of 21 selected U.S. cities to compare practices for conducting sidewalk inventories and their use for improving municipal sidewalk networks. Although diverse in geography, population size, density, and median household income, the selected cities represent a sample of convenience and not a random sample of U.S. cities. The results suggested that compliance with the Americans with Disabilities Act is a primary motivator for conducting sidewalk inventories and the cost of conducting an inventory is not prohibitive. Inventory methods included walking each sidewalk segment using handheld devices, LIDAR mounted on wheeled vehicles, and aerial photography, with data uploaded to geographic information system databases. Sidewalk inventories can be used to promote equity by increasing the percentage of city streets that have sidewalks. Areas for future study include developing better cost estimates for each type of sidewalk inventory method, examining the legal implications of sidewalk inventories, and estimating the incremental health benefits obtained for each additional investment in sidewalk construction and repair.
Economic impact on local businesses of road safety improvements in Seattle: implications for Vision Zero projects
Osterhage, D. R., Acolin, J., Fishman, P. A., & Dannenberg, A. L. (2024). Economic impact on local businesses of road safety improvements in Seattle: implications for Vision Zero projects. Injury Prevention, 30(6), 468–473. https://doi.org/10.1136/ip-2023-044934.
Abstract
Background Local transportation agencies implementing Vision Zero road safety improvement projects often face opposition from business owners concerned about the potential negative impact on their sales. Few studies have documented the economic impact of these projects.
Methods We examined baseline and up to 3 years of postimprovement taxable sales data for retail, food and service-based businesses adjacent to seven road safety projects begun between 2006 and 2014 in Seattle. We used hierarchical linear models to test whether the change in annual taxable sales differed between the 7 intervention sites and 18 nearby matched comparison sites that had no road safety improvements within the study time frame.
Results Average annual taxable sales at baseline were comparable at the 7 intervention sites (US$44.7 million) and the 18 comparison sites (US$56.8 million). Regression analysis suggests that each additional year following baseline was associated with US$1.20 million more in taxable sales among intervention sites and US$1.14 million more among comparison sites. This difference is not statistically significant (p=0.64). Sensitivity analyses including a random slope, using a generalised linear model and an analysis of variance did not change conclusions.
Discussion Results suggest that road safety improvement projects such as those in Vision Zero plans are not associated with adverse economic impacts on adjacent businesses. The absence of negative economic impacts associated with pedestrian and bicycle road safety projects should reassure local business owners and may encourage them to work with transportation agencies to implement Vision Zero road safety projects designed to eliminate traffic-related injuries.
Evaluating the Impact of CO2 on Calcium SulphoAluminate (CSA) Concrete
Akerele, D. D., & Aguayo, F. (2024). Evaluating the Impact of CO2 on Calcium SulphoAluminate (CSA) Concrete. Buildings, 14(8), 2462. https://doi.org/10.3390/buildings14082462
Abstract
The construction industry is a significant contributor to global CO2 emissions, primarily due to the extensive use of ordinary portland cement (OPC). In response to the urgent need for sustainable construction materials, calcium sulphoaluminate (CSA) cement has emerged as a promising alternative. CSA cement is renowned for its low carbon footprint, high early-age strength, and superior durability, making it an attractive option for reducing the environmental impact of construction activities. While CSA cement offers benefits in carbon emissions reduction, its susceptibility to carbonation presents challenges. Although the body of literature on CSA cement is rapidly expanding, its adoption rate remains low. This disparity may be attributed to several factors including the level of scientific contribution in terms of research focus and lack of comprehensive standards for various applications. As a result, the present study sets out to track the research trajectory within the CSA cement research landscape through a systematic literature review. The study employed the Prefer Reporting Item for Systematic Review and Meta-Analysis (PRISMA) framework to conduct a literature search on three prominent databases, and a thematic analysis was conducted to identify the knowledge gap for future exploration. The study revealed that while CSA concrete demonstrates superior early-age strength and environmental resistance, its susceptibility to carbonation can compromise structural integrity over time. Key mitigation strategies identified include the incorporation of supplementary cementitious materials (SCMs), use of corrosion inhibitors, and optimization of mix designs. The review also highlights the global distribution of research, with notable contributions from the USA, China, and Europe, emphasizing the collaborative effort in advancing CSA concrete technology. The findings are crucial for enhancing sustainability and durability in the construction sector and advancing CSA binders as a sustainable alternative to traditional cement.
Keywords
concrete; calcium sulphoaluminate cement (CSA); mechanical properties; carbonation (CO2); durability; sustainability