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Year: 2024

Urban landscape affects scaling of transportation carbon emissions across geographic scales

Jung, M. C., Wang, T., Kang, M., Dyson, K., Dawwas, E. B., & Alberti, M. (2024). Urban landscape affects scaling of transportation carbon emissions across geographic scales. Sustainable Cities and Society, 113, 105656-. https://doi.org/10.1016/j.scs.2024.105656

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Abstract

Understanding the carbon dynamics of the transportation sector is necessary to mitigate global climate change. While urban scaling laws have been used to understand the impact of urban population size on carbon efficiency, the instability of these scaling relationships raises additional questions. Here, we examined the scaling of on-road transportation carbon emissions across 378 US metropolitan statistical areas (MSAs) using diverse urban landscape patterns and spatial units, from the MSA level down to 1 km grid cells. Beginning with a baseline scaling model that uses only population size, we expanded the model to include landscape metrics at each spatial scale based on correlation results. We found that: (1) urban landscape characteristics provide insights into carbon mechanisms not fully captured by population size alone, (2) the impact of population size on on-road carbon emissions transitions from linear to sub-linear scaling relationships as the geographic scale of analysis decreases, and (3) clustered urban developments can form carbon-efficient landscapes, while fragmented urban areas tend to be carbon-inefficient. Based on empirical evidence, this research advocates for hierarchical spatial planning and supports the implementation of policy measures aligned with smart growth principles to mitigate carbon pollution.

Let’s Be Clear-Health Impact Assessments or Assessing Health Impacts?

Kim, J., Dannenberg, A., Haigh, F., & Harris-Roxas, B. (2024). Let’s Be Clear—Health Impact Assessments or Assessing Health Impacts? Public Health Reviews, 45, 1607722-. https://doi.org/10.3389/phrs.2024.1607722

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Abstract

The article discusses the distinction between studies that assess health impacts and those that are specifically associated with health impact assessments (HIAs). It highlights the misuse of the term HIA in scholarly literature, where studies that evaluate health impacts are often labeled as HIAs. The authors emphasize that HIAs are intended to support decision-making and provide recommendations, rather than simply describing or evaluating health impacts. They suggest the need for better documentation of HIA recommendations and their impacts, as well as the development of reporting guidelines for academic HIA literature.

Keywords

decision making; health impact assessment; health risk assessment; policy recommendations; stakeholder engagement

Evaluating carbonation resistance and microstructural behaviors of calcium sulfoaluminate cement concrete incorporating fly ash and limestone powder

Mohammed, T., Torres, A., Aguayo, F., & Okechi, I. K. (2024). Evaluating carbonation resistance and microstructural behaviors of calcium sulfoaluminate cement concrete incorporating fly ash and limestone powder. Construction & Building Materials, 442, 137551-. https://doi.org/10.1016/j.conbuildmat.2024.137551

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Abstract

This study investigates the effects of accelerated carbonation on calcium sulfoaluminate (CSA) cement concrete, focusing on mixtures enhanced with 20 % fly ash (FA), 20 % remediated fly ash (RF), 15 % limestone powder (LP), and a combination of 20 % FA with 15 % LP (35 %). The study further evaluates the mechanical properties including compressive strength, splitting tensile strength, elastic modulus, along with drying shrinkage and bulk resistivity. To delve into the microstructural characteristics of moist curing versus carbonation exposure on the CSA cement system, X-ray diffraction (XRD) and thermogravimetric analysis (TGA) were employed, particularly analyzing phase assemblage changes. The results show that the addition of FA reduced the carbonation depth in concrete mixtures over time (105 days). However, LP and the combination of FA and LP presented mixed effects. The microstructural analysis highlighted ettringite as the predominant phase in samples moist cured for 3 days. In contrast, carbonation-cured samples were characterized by different calcium carbonate (CaCO3) polymorphs alongside aluminum hydroxide (Al(OH)3) and residual ye'elimite, with the formation of low-pH carbonic acid facilitating the conversion of ettringite into CaCO3. This study highlights the impact of different SCMs on the durability and microstructural characteristics of CSA cement concrete, underscoring the interplay between curing methods, effects of SCM, and carbonation processes.

Keywords

Calcium sulfoaluminate cement (CSA); Carbonation; Limestone powder; Fly Ash; Microstructural analysis

Applications of blockchain for construction project procurement

Kim, M., & Kim, Y.-W. (2024). Applications of blockchain for construction project procurement. Automation in Construction, 165, 105550-. https://doi.org/10.1016/j.autcon.2024.105550

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Abstract

Blockchain technology has shown potential in enhancing project performance by instilling trust in data sharing among stakeholders, thereby encouraging the stakeholders to ensure a strategic acquisition and resource management through procurement activities. However, despite the recent research efforts on blockchain in the construction sector, there is a lack of knowledge of the status quo in that barely any research investigated the synergy of blockchain and procurement by recognizing the inextricable linkage between procurement management and project delivery system. This paper conducts a systematic review of 54 articles to assess blockchain's potential in addressing issues inherent in the current organizational structures and collaborative efforts. Findings offer profound insight into the current landscape of procurement-specific blockchain research, highlighting areas needing attention. This paper identified opportunities in construction procurement by investigating the extent to which the technology is integrated into the current project management context emphasizing integration and collaboration.

Keywords

Blockchain; Procurement; Construction industry; Procurement process; Project delivery system; Literature review

“All roads lead to Rome?” Performance evaluation across different types of community land trusts based on a large-scale survey

Wang, R., & Spicer, J. (2024). “All roads lead to Rome?” Performance evaluation across different types of community land trusts based on a large-scale survey. Journal of Urban Affairs, 1–22. https://doi.org/10.1080/07352166.2024.2371400

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Abstract

Community land trusts (CLTs) seek to keep homes and other urban spaces permanently affordable and community controlled. As their number across the United States has increased, different iterations of the CLT model seem to have proliferated in practice, stoking scholarly debate as to their varying outcomes and benefits. There has, however, been little attempt to empirically measure the relationship between this institutional diversity and outcomes. Applying institutional theory to a national CLT dataset, we identify five main organizational sub-types of CLT: traditional CLTs, start-up CLTs, government-housed CLTs, nonprofits with a CLT/shared equity (SE) program, and adapted CLTs. Statistical tests confirm a high degree of similarity in operational scope, organizational capacity, and performance outcomes across the most prominent sub-types. The limited statistical differences which can be identified are consistent with known CLT and urban institutional development processes. Further studies might seek to determine how consequential such limited differences may be.

Keywords

Community land trust; permanently affordable housing; historical institutionalism; community control; shared equity housing

Pacific Coast Architecture Database (PCAD)

PCAD archives a range of information on the buildings and architects of California, Oregon and Washington. Also included are professionals in other fields who have made an impact on the built environment, such as landscape architects, interior designers, engineers, urban planners, developers, and building contractors. Building records are tied to those of their creators (when known) and include historical and geographical information and images. Bibliographical information, such as magazine and book citations and web sites, has also been linked for creators and their partnerships and structures.

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Measures, benefits, and challenges to retrofitting existing buildings to net zero carbon: A comprehensive review

Weerasinghe, L. N. K., Darko, A., Chan, A. P. C., Blay, K. B., & Edwards, D. J. (2024). Measures, benefits, and challenges to retrofitting existing buildings to net zero carbon: A comprehensive review. Journal of Building Engineering, 94, 109998-. https://doi.org/10.1016/j.jobe.2024.109998

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Abstract

Net zero carbon (NZC) retrofitting of existing buildings contributes to improving occupants' well-being, addressing carbon footprint directly and is key to solving the global climate crisis. However, a fragmented NZC retrofit knowledge base exists and this challenges the ability to effectively implement NZC practices. This study, therefore, integratively and comprehensively reviews existing literature on NZC retrofitting of existing buildings and identifies research gaps to provide future research directions. Bibliometric analysis was conducted using 1544 relevant articles identified from Scopus. Moreover, based on 125 carefully selected articles, a further qualitative analysis was also conducted. Results indicated a gradual increase in interest in NZC retrofitting research since 2007. Emergent findings reveal that the UK, Italy, US, China and Spain are the top five countries in this research field and that in NZC retrofitting, energy is mostly prioritised. Key research themes include NZC retrofitting benefits, challenges and measures. Based on identified knowledge gaps, future research directions are proposed to include: (1) analysis of NZC retrofitting measures based on building types and climate conditions; (2) integration of NZC retrofitting measures; (3) effects of occupants' health, well-being and satisfaction on retrofitting; (4) integration of modern technology; (5) quantitative study on benefits; and (6) dealing with objections to NZC retrofitting. Emergent findings generate an in-depth understanding of the NZC retrofitting field and provide a useful milestone reference for future NZC retrofitting practice and improvement in the industry.

Acoustic design evaluation in educational buildings using artificial intelligence

Tabatabaei Manesh, M., Nikkhah Dehnavi, A., Tahsildoost, M., & Alambeigi, P. (2024). Acoustic design evaluation in educational buildings using artificial intelligence. Building and Environment, 261, 111695-. https://doi.org/10.1016/j.buildenv.2024.111695

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Abstract

Speech intelligibility is a critical aspect of building science, particularly in educational buildings where poor sound quality may have a detrimental impact on students' learning and teachers’ health. However, considering the numerous building regulations proposing varying definitions and ranges of acoustic comfort, calculating the necessary acoustic indicators can be challenging for designers. Speech intelligibility is a crucial component of indoor acoustics and acoustic comfort and can be calculated using formulas, simulation software, and data-based web tools. While formulas are fast, they lack details; acoustic simulation software is highly accurate but time-consuming and expensive. Data-based web tools, including machine learning algorithms, offer both speed and accuracy and are widely accessible. In this study, we present a system utilizing machine learning techniques to predict acoustic indicators, numeric and heatmap, in an educational building. The Pachyderm plugin in the Grasshopper was utilized to conduct extensive simulations in a single educational space, focusing on acoustic indicators in six different frequencies and general modes. Using Catboost and the pix2pix algorithm, the prediction models provide numerical and image indices on the developed dataset. Also, SHAP values were employed to interpret the Catboost model, analyzing the significance of each feature. The results showed remarkable accuracy, (i.e., between 89 % and 99 %) in the numerical portion, and PSNR index ranging from 0.817 to 0.970, and an SSIM index ranging from 15.56 to 31.57 in the image section. By utilizing data-driven methods, the system provides an efficient and accurate approach to calculating acoustic indicators, helping to ensure optimal acoustic environment in educational buildings.

Keywords

Building acoustics; Catboost; Pix2pix; Educational building; Speech intelligibility

Online toolkits for collaborative and inclusive global research in urban evolutionary ecology

Savage, A. M., Willmott, M. J., Moreno‐García, P., Jagiello, Z., Li, D., Malesis, A., Miles, L. S., Román‐Palacios, C., Salazar‐Valenzuela, D., Verrelli, B. C., Winchell, K. M., Alberti, M., Bonilla‐Bedoya, S., Carlen, E., Falvey, C., Johnson, L., Martin, E., Kuzyo, H., Marzluff, J., … Gotanda, K. M. (2024). Online toolkits for collaborative and inclusive global research in urban evolutionary ecology. Ecology and Evolution, 14(6), e11633-n/a. https://doi.org/10.1002/ece3.11633

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Abstract

Urban evolutionary ecology is inherently interdisciplinary. Moreover, it is a field with global significance. However, bringing researchers and resources together across fields and countries is challenging. Therefore, an online collaborative research hub, where common methods and best practices are shared among scientists from diverse geographic, ethnic, and career backgrounds would make research focused on urban evolutionary ecology more inclusive. Here, we describe a freely available online research hub for toolkits that facilitate global research in urban evolutionary ecology. We provide rationales and descriptions of toolkits for: (1) decolonizing urban evolutionary ecology; (2) identifying and fostering international collaborative partnerships; (3) common methods and freely-available datasets for trait mapping across cities; (4) common methods and freely-available datasets for cross-city evolutionary ecology experiments; and (5) best practices and freely available resources for public outreach and communication of research findings in urban evolutionary ecology. We outline how the toolkits can be accessed, archived, and modified over time in order to sustain long-term global research that will advance our understanding of urban evolutionary ecology.

From Tweets to Energy Trends (TwEn): An exploratory framework for machine learning-based forecasting of urban-scale energy behavior leveraging social media data

Abbasabadi, N., & Ashayeri, M. (2024). From Tweets to Energy Trends (TwEn): An exploratory framework for machine learning-based forecasting of urban-scale energy behavior leveraging social media data. Energy and Buildings, 317, 114440-. https://doi.org/10.1016/j.enbuild.2024.114440

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Abstract

TwEn framework links tweet frequency with urban energy use patterns. AI models forecast energy from social media data sourced from X. Framework predicts NYC electricity use with high accuracy. Tweet frequency’s seasonal stability enhances energy research. Real-time social data can aid sustainable urban energy policy. Understanding energy behavior is crucial in addressing climate change, yet the accuracy of energy predictions is often limited by reliance on oversimplified occupancy data. This study develops an exploratory framework, from Tweets to Energy Trends (TwEn), leveraging machine learning and geo-tagged social media data to investigate the social dynamics of urban energy behavior. TwEn explores the relationship between social media interactions, specifically the frequency of tweets using data from the X Platform, and energy use patterns on an hourly basis. Employing various machine learning models, including artificial neural networks (ANN), decision tree (DTREE), random forest (RDF), and gradient boosting machine (GBM), the study evaluates their efficiency in both static and time-series forecasting of energy use trends and investigates the capability of social media data in predicting urban energy patterns. In addition, the study carries out a series of sensitivity analyses to provide an examination of the data and models. Furthermore, comprehensive data acquisition methods are developed and implemented. Tested on New York City using actual hourly electricity consumption data, the framework demonstrates significant predictive power of tweet frequency on urban electricity use. The framework also exhibits significant seasonality in X data, identifying patterns and trends that can inform time series urban building energy models (UBEM). The results offer new insights into the determinants of urban energy behavior and provide crucial perspectives for augmenting UBEMs, ensuring they are closely aligned with the complex social dynamics of contemporary urban environments. By integrating both digital and physical data, this study sheds light on urban energy behavior, supporting the formulation of effective and sustainable energy policies for urban futures.

Keywords

Occupancy; Social Media; Time Series Forecast; Urban Building Energy Modeling (UBEM); Urban Energy Behavior