{"title":"Infrastructure and the cognitive ecosystem: an irrevocable transformation","authors":"M. Chester, B. Allenby","doi":"10.1088/2634-4505/aced1f","DOIUrl":"https://doi.org/10.1088/2634-4505/aced1f","url":null,"abstract":"Disruption of legacy infrastructure systems by novel digital and connected technologies represents not simply the rise of cyberphysical systems as hybrid physical and digital assets but, ultimately, the integration of legacy systems into a new cognitive ecosystem. This cognitive ecosystem, an ecology of massive data flows, artificial intelligence, institutional and intellectual structures, and connected technologies, is poised to alter how humans and artificial intelligence understand and control our world. Infrastructure managers need to be ready for this paradigm shift, recognizing their systems are increasingly being absorbed into an emerging suite of data, analytical tools, and decisionmaking technologies that will fundamentally restructure how legacy systems behave and are controlled, how decisions are made, and most importantly how workers interact with the systems. Infrastructure managers must restructure their organizations and engage in cross-organizational sensemaking if they are to be capable of navigating the complexity of the cognitive ecosystem. The cognitive ecosystem is fundamentally poised to change what infrastructures are, necessitating the need for managers to take a close look at the functions and actions of their own systems. The continuing evolution of the Anthropocene and the cognitive ecosystem has profound implications for infrastructure education. A sustained commitment to change is necessary that restructures and reorients infrastructure organizations within the cognitive ecosystem, where knowledge is generated, and control of services is wielded by myriad stakeholders.","PeriodicalId":309041,"journal":{"name":"Environmental Research: Infrastructure and Sustainability","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124767245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Understanding resource consumption and sustainability in the built environment","authors":"A. Stillwell, A. Cominola, C. Beal","doi":"10.1088/2634-4505/ace738","DOIUrl":"https://doi.org/10.1088/2634-4505/ace738","url":null,"abstract":"The built environment and the communities that contribute to its infrastructure, services, and systems are important aspects of human life. As urbanization increases, time spent indoors also increases, with urban residents spending most of their time indoors. This indoor lifestyle concentrates the effects of water, energy, and food consumption in the built environment, with local, regional, and global implications for interconnected resources and their supply chains. As such, resource consumption in the built environment has sustainability implications, especially with increasing populations and living standards. This focus issue, ‘Resource Consumption and Sustainability in the Built Environment’, examines infrastructure and sustainability from many perspectives. The articles investigate water, energy, and/or food consumption across various scales, ranging from a single household to nationwide supply chains to global climate models. Each paper in this issue considers essential elements of context, since water, energy, and food have local and global sustainability considerations, along with multi-sector dependencies within urban metabolism. Digital technologies, data, and modeling approaches are opening new opportunities for better monitoring and understanding of the built environment. In an uncertain future, understanding resource consumption in the built environment and its implications for the environment and society is a critical aspect of overall human health and well-being. In-depth knowledge of the dynamics shaping the built environment is paramount to supporting adaptive infrastructure planning and management, including supply and demand interventions to help cities and communities become climate neutral while increasing equity in access and affordability of resources and services.","PeriodicalId":309041,"journal":{"name":"Environmental Research: Infrastructure and Sustainability","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115326580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Complexity of increasing knowledge flows: the 2022 Southwest Airlines Scheduling Crisis","authors":"Alysha M. Helmrich, M. Chester, Megan S. Ryerson","doi":"10.1088/2634-4505/ace5ce","DOIUrl":"https://doi.org/10.1088/2634-4505/ace5ce","url":null,"abstract":"The 2022 Southwest Airlines Scheduling Crisis, resulting in approximately 15 000 flight cancellations, demonstrates the challenges of structuring infrastructure systems and their knowledge-making processes for increasingly disruptive conditions. While the point-to-point configuration was the focus of immediate assessments of the failure, it became rapidly evident that the crew-assignment software was unable to operate effectively due to the scale of disruption. The airline failed to recognize environmental shifts associated with internal and external complexity, leaving operations vulnerable to a known potential risk: computer and telecommunications failures due to an extreme weather event resulting in knowledge systems failures. The cascading failures of the crisis emphasize the necessity to invest in adaptive capacity prior to catastrophic events and provide a lesson to other infrastructure managers pursuing resilience in the face of increasingly uncertain environments.","PeriodicalId":309041,"journal":{"name":"Environmental Research: Infrastructure and Sustainability","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115180688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Equity of bike infrastructure access in the United States: a risky commute for socially vulnerable populations","authors":"Alireza Ermagun, Jacquelyn Erinne, Sanju Maharjan","doi":"10.1088/2634-4505/ace5cf","DOIUrl":"https://doi.org/10.1088/2634-4505/ace5cf","url":null,"abstract":"This study examines the bike access risk gap (BARG) for commuting in the 50 most populated metropolitan areas in the United States and equips bike advocates with the knowledge and tools necessary to identify the priority areas that need bike infrastructure improvements and the well-connected low-stress bike infrastructure. The analysis (i) examines the average BARGs of metropolitan areas for twelve travel time thresholds, (ii) considers the temporal and spatial disparities of slightly and extremely risky bike infrastructure, and (iii) reveals the disproportionate exposure of socially vulnerable populations to extremely risky bike infrastructure for a journey to work. The results indicate that (i) few metropolitan areas are associated with slightly risky bike infrastructure, (ii) the exposure to extremely risky bike infrastructure becomes more likely as commute travel time increases, and (iii) African Americans, Hispanics, low-income, and carless households are disproportionally exposed to extremely risky bike infrastructure and yet are the least prioritized in urban planning and bike infrastructure investments. The findings offer insights for identifying areas in which constructing low-stress bike infrastructure on or near high-stress bike infrastructure narrows the BARG.","PeriodicalId":309041,"journal":{"name":"Environmental Research: Infrastructure and Sustainability","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131343775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Estimating the electric vehicle charging demand of multi-unit dwelling residents in the United States","authors":"Xiaobin Cheng, Eleftheria Kontou","doi":"10.1088/2634-4505/acde06","DOIUrl":"https://doi.org/10.1088/2634-4505/acde06","url":null,"abstract":"Early battery electric vehicle (EV) adopters can access home chargers for reliable charging. As the EV market grows, residents of multi-unit dwellings (MUDs) may face barriers in owning EVs and charging them without garage or parking availability. To investigate the mechanisms that can bridge existing disparities in home charging and station deployment, we characterized the travel behavior of MUD residents and estimated their EV residential charging demand. This study classifies the travel patterns of MUD residents by fusing trip diary data from the National Household Travel Survey and housing features from the American Housing Survey. A hierarchical agglomerative clustering method was used to cluster apartment complex residents’ travel profiles, considering attributes such as dwell time, daily vehicle miles traveled (VMT), income, and their residences’ US census division. We propose a charging decision model to determine the charging station placement demand in MUDs and the charging energy volume expected to be consumed, assuming that MUD drivers universally operate EVs in urban communities. Numerical experiments were conducted to gain insight into the charging demand of MUD residents in the US. We found that charging availability is indispensable for households that set out to meet 80% state of charge by the end of the day. When maintaining a 20% comfortable state of charge the entire day, the higher the VMT are, the greater the share of charging demand and the greater the energy use in MUD chargers. The upper-income group requires a greater share of MUD charging and greater daily kWh charged because of more VMT.","PeriodicalId":309041,"journal":{"name":"Environmental Research: Infrastructure and Sustainability","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116936396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The inequitable distribution of power interruptions during the 2021 Texas winter storm Uri","authors":"Zeal Shah, J. Carvallo, F. Hsu, Jay Taneja","doi":"10.1088/2634-4505/acd4e7","DOIUrl":"https://doi.org/10.1088/2634-4505/acd4e7","url":null,"abstract":"Climate change induced extreme weather events will increase in intensity and frequency, leading to longer and widespread electricity outages. As an example, Winter Storm Uri in Texas left over 4.5 million customers without power between 14 and 18 February 2021. The social justice consequences of these events remain an outstanding question, as outage data are, typically, only available at the county level, obscuring detailed experiences. We produce a first-of-its-kind unique spatially resolved dataset of interruptions using satellite data on nighttime lights to track blackouts at the census block group (CBG) level. Correlating this dataset with demographic data reveals that minority CBGs were 1.5–3 times more likely to suffer from interruptions compared to predominantly white CBGs, whereas income status was positively correlated with the likelihood of interruption. The presence of critical facilities—including police and fire stations, hospitals, and water treatment facilities—in a CBG reduced the chances of interruptions by around 16% , a small difference that does not otherwise explain the disparity among communities. We suggest explanations, test a subset of them, and propose further work needed to explain what drives these disparities.","PeriodicalId":309041,"journal":{"name":"Environmental Research: Infrastructure and Sustainability","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127217052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cesario Tavares, K. Skillen, Xijun Shi, Z. Grasley
{"title":"Multi-criteria comparison tools to evaluate cost- and eco-efficiency of ultra-high-performance concrete","authors":"Cesario Tavares, K. Skillen, Xijun Shi, Z. Grasley","doi":"10.1088/2634-4505/acd475","DOIUrl":"https://doi.org/10.1088/2634-4505/acd475","url":null,"abstract":"This work was motivated by the increasing need for proper metrics and tools to demonstrate the effect of mechanical performance, as a function of concrete mix composition, in dictating the dimensions of structural elements and associated costs and embodied carbon dioxide (CO2) emissions. Mixture compositions associated with different concrete technologies were compared using multi-criteria comparison indices derived using structural design considerations and calculated using information on compressive strength, volumetric embodied CO2 and unit costs. In addition, predicted compressive strengths obtained with machine learning (ML) models are used to calculate these indices for a domain of mix proportions associated with ultra-high-performance concrete materials to generate multi-objective density diagrams (MODDs). The makeup of this tool facilitates the evaluation of rather complicated trends associated with mix proportions and multi-objective outcomes, allowing ML-based tools to be of easy interpretation by industry personnel with no expertise in artificial intelligence. MODDs could be used as aids in the decision-making process during mix design stages and serve as proof of mixture optimization that could be introduced in environmental product declarations. Results show that, in contrast to conventional wisdom, high-binder content and ultra-high strength concrete technologies are not necessarily detrimental to cost and/or eco efficiencies. For the applications evaluated herein, optimum solutions were mostly obtained with these types of concrete, suggesting that industry trends toward requiring minimization of embodied carbon footprint on a per volume of concrete basis are misguided and should not be used as a standalone metric to minimize the total carbon footprint of concrete structures.","PeriodicalId":309041,"journal":{"name":"Environmental Research: Infrastructure and Sustainability","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130157957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Public and private transportation in Chinese cities: impacts of population size, city wealth, urban typology, the built environment, and fuel price","authors":"Xiangwen Fu, D. Mauzerall, A. Ramaswami","doi":"10.1088/2634-4505/acd419","DOIUrl":"https://doi.org/10.1088/2634-4505/acd419","url":null,"abstract":"The development of urban transportation is affected by city population size, wealth, urban typology, the built environment, and fuel price, and has significant implications for urban sustainability. We analyze data of 297 Chinese cities between 2017 and 2019 using both simple regressions to examine the relationships between metrics of public and private transportation and city size, and multiple regressions to examine the impacts of the above urban factors on public transit use and private vehicle number. Both public transit use and private vehicle number scale super-linearly with population and sub-linearly with gross regional product. We find that the impacts of population size, city wealth, the built environment, and fuel price on transportation vary across city groups (industrial, mixed-economy, and commercial cities). We find that the relationships between urban transportation metrics and their factors extracted from intra-city variations over time are different from those derived from pooling data of multiple cities over time, indicating the importance of choosing appropriate analyses to inform local policymaking. A key finding is that to reduce private vehicle ownership, enhancing land use diversity, increasing rail transit, and expanding taxi fleets are more effective than increasing density in already dense Chinese cities. Our findings improve understanding of the drivers of public and private transportation in urban China which are needed to promote sustainable growth of Chinese cities.","PeriodicalId":309041,"journal":{"name":"Environmental Research: Infrastructure and Sustainability","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130754512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kelsey Biscocho, Mohammad Rezqalla, Aaron Farha, Alexandru Boanta, Rebecca E. Ciez
{"title":"Development of a high-resolution top-down model to estimate actual household-level heat pump electricity consumption","authors":"Kelsey Biscocho, Mohammad Rezqalla, Aaron Farha, Alexandru Boanta, Rebecca E. Ciez","doi":"10.1088/2634-4505/acd1ab","DOIUrl":"https://doi.org/10.1088/2634-4505/acd1ab","url":null,"abstract":"Heat pumps can play an important part in decarbonizing the residential sector due to their use of electricity instead of fossil fuels, and their high efficiency, which often exceeds 100%. However, heat pump performance and energy savings vary with climate and individual household energy usage. Recent studies have used geospatial models to estimate potential heat pump energy consumption across the United States. Yet most studies use generic and oversimplified heat pump models. We contribute to this field with a geospatial model based on manufacturer data and measured test data for 16 different R410A, high efficiency, variable speed compressor heat pumps. Using linear regression, we estimate a market average of COP with respect to ambient temperature. From this, we can identify the variation in efficiency with temperature across this technology class. We also use linear regression to estimate demand for heating and cooling as a function of ambient temperature and household characteristics. We compare the performance of both the predicted energy demand and heat pump efficiency against measured data from a heat pump-equipped house in West Lafayette, Indiana, and find that the model predicts daily heat pump electricity consumption with 27.8% relative error, comparable to other building simulation models. By incorporating high-resolution geospatial data inputs, such top-down models can still maintain a large scope across technologies and diverse climates while increasing spatial and temporal resolution.","PeriodicalId":309041,"journal":{"name":"Environmental Research: Infrastructure and Sustainability","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115475540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Koks, J. Rozenberg, Mersedeh Tariverdi, Ben Dickens, C. Fox, Kees C. H. van Ginkel, S. Hallegatte
{"title":"A global assessment of national road network vulnerability","authors":"E. Koks, J. Rozenberg, Mersedeh Tariverdi, Ben Dickens, C. Fox, Kees C. H. van Ginkel, S. Hallegatte","doi":"10.1088/2634-4505/acd1aa","DOIUrl":"https://doi.org/10.1088/2634-4505/acd1aa","url":null,"abstract":"Every country relies on a well-functioning road system. However, we do not have a clear understanding yet of the vulnerability of each of these road networks to different forms of disruption. In this study, we aim to better understand how road networks are affected by different disruptive events, to identify hotspots of road network vulnerabilities, and to better target where and what type of future investments can be made to develop more resilient networks. To do so, we developed a fully open-source modelling framework to expose over 200 country road systems across the world to random, local, and targeted disruption schemes. For each country, we assessed the impact of such disruptions on intra-country travel activities and regional accessibility. The results highlight the vulnerability of road systems in mountainous and small-island countries owing to the limited availability of alternative routes. Additionally, we find that, on average, low-income countries experience a collapse of road-system services with much fewer disruptions, relative to high-income countries, due to the lack of redundancy in their systems. While the value of goods and services disrupted may be higher in wealthier countries, the results highlight that from an equity perspective, transport infrastructure investments are more desired in low-income country networks.","PeriodicalId":309041,"journal":{"name":"Environmental Research: Infrastructure and Sustainability","volume":"136 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128744516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}