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A Comparative Review of Polymer, Bacterial-based, and Alkali-Activated (also Geopolymer) Binders: Production, Mechanical, Durability, and Environmental impacts (life cycle assessment (LCA))

Nodehi, M., Aguayo, F., Madey, N., & Zhou, L. (2024). A Comparative Review of Polymer, Bacterial-based, and Alkali-Activated (also Geopolymer) Binders: Production, Mechanical, Durability, and Environmental impacts (life cycle assessment (LCA)). Construction & Building Materials, 422. https://doi.org/10.1016/j.conbuildmat.2024.135816
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Abstract

This review paper presents a comparative evaluation of polymer, bacterial-based, alkali-activated, and geopolymer binders in regard to their production methods, mechanical properties, their environmental/life cycle assessment (LCA), and durability when exposed to deteriorating cycles (such as sulfates, acids, and high temperatures). The significance of this study is to compare the results of over 400 journal papers, which present an in-depth analysis of fresh and hardened state properties of various binders that are advocated in the literature. Historically, Portland cement is generally considered a binder that plays a major role in any cementitious composites because of its high availability, and relatively inexpensive cost. Despite its significant benefits, it is known that the manufacturing process of Portland cement is energy and carbon intensive, and the resulted material often has shortcomings when exposed to deteriorating causes such as sulfates, acids, and high temperatures. However, recent movement toward net-zero as well as ultra-high-performance practices has increased the need for a more sustainable and durable binding system. Based on the result of this paper, each binder presents specific advantages when compared to Portland cement for specific applications that can be a better choice for their ultra-high capabilities and ecological properties. This includes the significantly better performance of alkali-activated binders (specifically geopolymers), under high temperatures, or very rapid strength gain of polymer (e.g., epoxy, polyester, and vinyl ester) binders, making them great alternatives to Portland cement, for rapid repair and rehabilitation purposes. Similarly, bacterial concrete also have certain capabilities such as long term durability and the potential for a continued self-repair or self-healing. In terms of environmental impacts, however, polymer binders are heavily depedant on their source of energy (e.g., petroleum vs. bio-based resins) while alkali-activated concretes and geopolymers have activators' large contributions to overall LCA impact categories. For bacterial binders, the used urea and nutrition can play a key role in their LCA results. Finally, based on the highlighted capabilities of each binder, recommendations on performance-based or hybrid design methods and specifications for an optimized system are also provided. Novel areas in polymer, bacterial-based, alkali-activated, and geopolymer binders are also included.

Keywords

Binding agents; Polymer concreteBacterial (or bio) concrete; Alkali-activated materials and geopolymer; Mechanical and durability properties

Identifying recurrent and persistent landslides using satellite imagery and deep learning: A 30-year analysis of the Himalaya

Tzu-Hsin Karen Chen, Mark E. Kincey, Nick J. Rosser, Karen C. Seto, Identifying recurrent and persistent landslides using satellite imagery and deep learning: A 30-year analysis of the Himalaya, Science of The Total Environment, Volume 922, 2024, 171161, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2024.171161.

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Abstract

This paper presents a remote sensing-based method to efficiently generate multi-temporal landslide inventories and identify recurrent and persistent landslides. We used free data from Landsat, nighttime lights, digital elevation models, and a convolutional neural network model to develop the first multi-decadal inventory of landslides across the Himalaya, spanning from 1992 to 2021. The model successfully delineated >265,000 landslides, accurately identifying 83 % of manually mapped landslide areas and 94 % of reported landslide events in the region. Surprisingly, only 14 % of landslide areas each year were first occurrences, 55–83 % of landslide areas were persistent and 3–24 % had reactivated. On average, a landslide-affected pixel persisted for 4.7 years before recovery, a duration shorter than findings from small-scale studies following a major earthquake event. Among the recovered areas, 50 % of them experienced recurrent landslides after an average of five years. In fact, 22 % of landslide areas in the Himalaya experienced at least three episodes of landslides within 30 years. Disparities in landslide persistence across the Himalaya were pronounced, with an average recovery time of 6 years for Western India and Nepal, compared to 3 years for Bhutan and Eastern India. Slope and elevation emerged as significant controls of persistent and recurrent landslides. Road construction, afforestation policies, and seismic and monsoon activities were related to changes in landslide patterns in the Himalaya.

Keywords

Landslide inventory; Landslide evolution; Vegetation recovery; Multi-temporalSpatiotemporal analysis; Machine learning

Automating building environmental assessment: A systematic review and future research directions

T.A.D.K. Jayasanka, Amos Darko, D.J. Edwards, Albert P.C. Chan, Farzad Jalaei, Automating building environmental assessment: A systematic review and future research directions, Environmental Impact Assessment Review, Volume 106, 2024, 107465, ISSN 0195-9255, https://doi.org/10.1016/j.eiar.2024.107465.

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Abstract

Building environmental assessment (BEA) is critical to improving sustainability. However, the BEA process is inefficient, costly, and often inaccurate. Because automation has the potential to enhance the efficiency and accuracy of the BEA process, studies have focused on automating BEA (ABEA). Updated until now, a comprehensive analysis of prevailing literature on ABEA remains absent. This study conducts the first comprehensive systematic analysis appraising the state-of-the-art of research on ABEA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guided to systematically analyse 91 relevant studies. Results uncover that only 29.7% of BEA systems worldwide have automated their processes, with the US LEED residing at the vanguard of automation efforts. The New Buildings scheme was mostly focused on, while largely ignoring other schemes, e.g., Existing Buildings. Five key digital approaches to ABEA were revealed, namely building information modelling (BIM) and plug-in software, BIM-ontology, data mining and machine learning, cloud-BIM, and digital twin-based approaches. Based on identified gaps, future research directions are proposed, specifically: using data mining and machine learning models for ABEA; development of a holistic cloud-based approach for real-time BEA; and digital twin for dynamic BEA. This study generates a deeper understanding of ABEA and its theoretical implications, such as major constructs and emerging perspectives, constitute a basis for holistic, and innovation in, BEA.

Unraveling energy justice in NYC urban buildings through social media sentiment analysis and transformer deep learning

Ashayeri, M., & Abbasabadi, N. (2024). Unraveling energy justice in NYC urban buildings through social media sentiment analysis and transformer deep learning. Energy and Buildings, 306, 113914-. https://doi.org/10.1016/j.enbuild.2024.113914
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Abstract

This study explores the intricate relationship between human sentiment on social media data, herein tweet posts on X platform, urban building characteristics, and the socio-spatial dynamics of New York City (NYC) boroughs. Leveraging Natural Language Processing (NLP) techniques, particularly sentiment analysis, augmented by the capabilities of transformer deep learning models, RoBERTa, the study places particular emphasis on the term ‘Stay-at-Home’ to encapsulate the pronounced shift in building occupancy during the pandemic's inaugural year. This focus intertwines with pivotal terms like ‘Energy Bill’ and ‘HVAC’, shedding light on their interconnected implications. The sentiment analysis leverages data from New York City's PLUTO and the Department of Energy's LEAD databases to emotional disparities connected to urban building characteristics as well as demographic and socioeconomic factors. This analytical approach unravels prevailing public emotions and extends the discussion to include energy justice concerns, viewing them through the lens of the city's built infrastructure. The research uncovers profound disparities in the built environment and the allocation of resources in NYC, highlighting the critical need to embrace a spatial justice framework for a sustainable future. This research can aid designers, planners, and policymakers in their efforts to promote equitable and inclusive urban development.

Legacies of redlining lead to unequal cooling effects of urban tree canopy

Jung, M. C., Yost, M. G., Dannenberg, A. L., Dyson, K., & Alberti, M. (2024). Legacies of redlining lead to unequal cooling effects of urban tree canopy. Landscape and Urban Planning, 246. https://doi.org/10.1016/j.landurbplan.2024.105028
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Abstract

Redlining—a racially discriminatory policy of systematic disinvestment established by the Home Owners’ Loan Corporation (HOLC) in the 1930s and continued until the late 1960s—still influences the contemporary landscape of cities in the US. While the heterogeneous distribution of land surface temperature and tree canopy cover between neighborhoods with different HOLC grades have been recently examined, the development of long-term and city-specific heat management strategies is still limited. Here, we explored the effect of redlining in Portland, Oregon, and Philadelphia, Pennsylvania, to assess its contemporary impact on climate equity. We performed a change analysis of land surface temperature and tree canopy area over the past and introduced mixed-effects models to test the intra- and inter-city differences in canopy cooling effects between the different HOLC grades. We found that (1) persistent temporal patterns of lower land surface temperatures and larger tree canopy areas are observed in higher HOLC grades, (2) greater green equity was achieved through contrasting temporal changes in tree canopy areas across HOLC grades in Portland and Philadelphia, and (3) opposite patterns exist between these cities, with stronger canopy cooling effects in neighborhoods with a Low HOLC grade in Portland and those with a High HOLC grade in Philadelphia. Differences in tree canopy change between the two cities over the past decade highlight potential influences of city-specific tree planting practices. Local planners should back tree planting initiatives to equitably mitigate urban heat exposure, considering historical redlining contexts and contemporary landscape features.

Keywords

Redlining; HOLC grade; Tree canopy; Land surface temperature; Tree equity

An Ontological Analysis for Comparison of the Concepts of Sustainable Building and Intelligent Building

Borhani, A., Borhani, A., Dossick, C. S., & Jupp, J. (2024). An Ontological Analysis for Comparison of the Concepts of Sustainable Building and Intelligent Building. Journal of Construction Engineering and Management, 150(4). https://doi.org/10.1061/JCEMD4.COENG-13711

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Abstract

The concept of intelligent building is emerging in the contemporary built environment. Intelligent buildings aim to leverage digital technologies and information throughout the building’s life cycle (design, construction, and operation phases) to improve the building’s performance and value. In recent years, academic scholars and industry practitioners have made efforts to articulate the intelligent building concept and identify its components. However, there is still no commonly accepted definition for the term intelligent (or smart) building. Furthermore, the term is used interchangeably with similar terms such as sustainable building and high-performance building. The primary gaps in research are the lack of a holistic and clearly defined list of intelligent building components. This gap limits building stakeholders’ abilities to decide which technologies to implement in their buildings, prove its capabilities and advantages, and improve its performance. In response to the identified gaps, this research conceptualizes intelligent building in comparison with the concept of sustainable building. We identified the key components that each concept entails and conducted a comparative analysis of the identified components. The findings of this research include a categorization of intelligent building’s definitions which helps to conceptualize intelligent building and distinguish it from other similar concepts. In addition, the research team used the developed ontologies for intelligent and sustainable buildings to provide a fundamental overview of the structure of building evaluation systems and their different approaches for determining evaluation criteria. Overall, this study contributes to the body of knowledge by identifying and classifying components of intelligent buildings, which is a prerequisite for intelligent buildings’ evaluation. It also makes a distinction between the concepts of intelligent building and sustainable building in order to determine their context and applications.

 

Incentive-based coordination for scheduled delivery in prefab construction

Kim, Y.-W., & Rhee, B.-D. (2024). Incentive-based coordination for scheduled delivery in prefab construction. Construction Management and Economics, 1–16. https://doi.org/10.1080/01446193.2024.2305763.

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Abstract

An increasing number of projects are adopting prefabrication to economize on time, labor, and materials in fixed-position layout operations, such as construction, ship building, and aircraft manufacturing. In such contexts, independent contractor and fabricator make interdependent decisions, which calls for prudent supply chain management because performance relies on coordination between their decisions. Many studies have developed integrated systems and propose various algorithms for scheduling efficiency and reliability. Nevertheless, they pay scant attention to conflicting interests amongst independent partners, which may result in subpar performance not only for the supplier but for the contractor as well. Coordination of conflicting interests has been extensively studied in economics and supply chain management; yet, those studies focus on order-quantity decisions under demand uncertainty for profit maximization, while managers in fixed-position operations are more concerned about delivery decisions under scheduling uncertainty for cost minimization. We consider the case of construction and explore a contractual scheme that aligns the agents' decisions for coordination in a construction supply chain. Specifically, we propose a supplier rebate for coordination: the supplier grants a rebate if the contractor accepts the shipment in accordance with the delivery schedule that the contractor initially chose. We show that the optimal rebate fully coordinates the supply chain to minimize the joint supply chain costs. Thus, both the contractor and supplier benefit from the coordination by negotiating a mutually acceptable way to allocate the savings in joint costs between them. We further show that the rebate motivates the contractor to enhance its work scheduling.

Keywords

Construction supply chain; coordination; delivery schedule reliability; prefabrication; rebate for scheduled delivery

Suitability of the height above nearest drainage (HAND) model for flood inundation mapping in data-scarce regions: a comparative analysis with hydrodynamic models

Thalakkottukara, N. T., Thomas, J., Watkins, M. K., Holland, B. C., Oommen, T., & Grover, H. (2024). Suitability of the height above nearest drainage (HAND) model for flood inundation mapping in data-scarce regions: a comparative analysis with hydrodynamic models. Earth Science Informatics. https://doi.org/10.1007/s12145-023-01218-x.

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Abstract

Unprecedented floods from extreme rainfall events worldwide emphasize the need for flood inundation mapping for floodplain management and risk reduction. Access to flood inundation maps and risk evaluation tools remains challenging in most parts of the world, particularly in rural regions, leading to decreased flood resilience. The use of hydraulic and hydrodynamic models in rural areas has been hindered by excessive data and computational requirements. In this study, we mapped the flood inundation in Huron Creek watershed, Michigan, USA for an extreme rainfall event (1000-year return period) that occurred in 2018 (Father's Day Flood) using the Height Above Nearest Drainage (HAND) model and a synthetic rating curve developed from LIDAR DEM. We compared the flood inundation extent and depth modeled by the HAND with flood inundation characteristics predicted by two hydrodynamic models, viz., HEC-RAS 2D and SMS-SRH 2D. The flood discharge of the event was simulated using the HEC-HMS hydrologic model. Results suggest that, in different channel segments, the HAND model produces different degrees of concurrence in both flood inundation extent and depth when compared to the hydrodynamic models. The differences in flood inundation characteristics produced by the HAND model are primarily due to the uncertainties associated with optimal parameter estimation of the synthetic rating curve. Analyzing the differences between the HAND and hydrodynamic models also highlights the significance of terrain characteristics in model predictions. Based on the comparable predictive capability of the HAND model to map flood inundation areas during extreme rainfall events, we demonstrate the suitability of the HAND-based approach for mitigating flood risk in data-scarce, rural regions.

Keywords

Flood inundation mapping; Father's Day Flood; Data-scarce regions; HAND; HEC-RAS 2D; SMS-SRH 2D

Association between property investments and crime on commercial and residential streets: Implications for maximizing public safety benefits

Walter, R. J., Acolin, A., & Tillyer, M. S. (2024). Association between property investments and crime on commercial and residential streets: Implications for maximizing public safety benefits. SSM – Population Health, 25, 101537–101537. https://doi.org/10.1016/j.ssmph.2023.101537.

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Abstract

Physical property investments enhance public safety in communities while alleviating the need for criminal justice system responses. Policy makers and local government officials must allocate scare resources for community and economic development activities. Understanding where physical property investments have the greatest crime reducing benefits can inform decision making to maximize economic, safety, and health outcomes. This study uses Spatial Durbin models with street segment and census tract by year fixed effects to examine the impact of physical property investments on changes in property and violent crime over an 11-year period (2008-2018) in six large U.S. cities. The units of analysis are commercial and residential street segments. Street segments are classified into low, medium, and high crime terciles defined by initial crime levels (2008-2010). Difference of coefficients tests identify significant differences in building permit effects across crime terciles. The findings reveal there is a significant negative relationship between physical property investments and changes in property and violent crime on commercial and residential street segments in all cities. Investments have the greatest public safety benefit where initial crime levels are the highest. The decrease in violent crime is larger on commercial street segments, while the decrease in property crime is larger on residential street segments. Targeting the highest crime street segments (i.e., 90th percentile) for property improvements will maximize public safety benefits.

Keywords

Violent and property crime; Public safety; Physical property investments