2019 Archives - Page 3 of 7

Spatial Relationships between Urban Structures and Air Pollution in Korea

Jung, Meen Chel; Park, Jaewoo; Kim, Sunghwan. (2019). Spatial Relationships between Urban Structures and Air Pollution in Korea. Sustainability, 11(2).

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Abstract

Urban structures facilitate human activities and interactions but are also a main source of air pollutants; hence, investigating the relationship between urban structures and air pollution is crucial. The lack of an acceptable general model poses significant challenges to investigations on the underlying mechanisms, and this gap fuels our motivation to analyze the relationships between urban structures and the emissions of four air pollutants, including nitrogen oxides, sulfur oxides, and two types of particulate matter, in Korea. We first conduct exploratory data analysis to detect the global and local spatial dependencies of air pollutants and apply Bayesian spatial regression models to examine the spatial relationship between each air pollutant and urban structure covariates. In particular, we use population, commercial area, industrial area, park area, road length, total land surface, and gross regional domestic product per person as spatial covariates of interest. Except for park area and road length, most covariates have significant positive relationships with air pollutants ranging from 0 to 1, which indicates that urbanization does not result in a one-to-one negative influence on air pollution. Findings suggest that the government should consider the degree of urban structures and air pollutants by region to achieve sustainable development.

Keywords

Land-use Regression; Particulate Matter Concentrations; Nitrogen-dioxide; Temporal Variations; Smart City; Quality; Health; Pm10; Fine; Pollutants; Urban Structure; Air Pollution; Moran's I; Bayesian Spatial Model; Motivation; Population; Urbanization; Nitrogen Oxides; Urban Structures; Emissions; Regression Analysis; Regression Models; Sulfur; Spatial Dependencies; Environmental Impact; Outdoor Air Quality; Metropolitan Areas; Economic Growth; Photochemicals; Industrial Areas; Urban Areas; Industrial Plant Emissions; Particulate Emissions; Particulate Matter; Data Analysis; Bayesian Analysis; Sustainable Development; Sulfur Oxides; Regions; Mathematical Models; Cities; China

Section 8 Vouchers and Rent Limits: Do Small Area Fair Market Rent Limits Increase Access to Opportunity Neighborhoods? An Early Evaluation

Reina, Vincent; Acolin, Arthur; Bostic, Raphael W. (2019). Section 8 Vouchers and Rent Limits: Do Small Area Fair Market Rent Limits Increase Access to Opportunity Neighborhoods? An Early Evaluation. Housing Policy Debate, 29(1), 44 – 61.

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Abstract

One critique of the U.S. Department of Housing and Urban Development (HUD)'s Housing Choice Voucher program is that its maximum rent limit is set at the metropolitan level, making more expensive neighborhoods effectively off limits to households who receive rental assistance. As a result, the design of the program limits a voucher household's access to opportunity neighborhood. In response, HUD created the Small Area Fair Market Rent (SAFMR) demonstration program, which calculates the maximum voucher rent at the zip code level so that HUD's rent limits more closely align with local neighborhood rents. In theory, this program should improve a voucher household's choice set and location outcomes. Looking at changes in the location of beneficiaries in the six sites that participated in the SAFMR demonstration program, we find a significant amount of regional variation in the results. Specifically, introduction of the SAFMR rent calculations results in voucher households living in higher opportunity neighborhoods in Dallas, Texas, in lower opportunity neighborhoods in Chattanooga, Tennessee, and mixed effects in other areas. These mixed results highlight some of the potential incremental benefits of the program and reinforce the importance of viewing this policy over a longer period of time, and in the context of other constraints voucher households face in accessing neighborhood opportunity.

Keywords

Choice; Mobility; Families; Live; Section 8; Low-income Housing; Subsidized Housing; Vouchers; Neighborhood; Access; Markets; Mathematical Analysis; Federal Agencies; Urban Development; Housing; Households; Neighborhoods; Rents; Limitations; Beneficiaries; Housing Subsidies; United States--us; Dallas Texas; Chattanooga Tennessee

Cluster-based LSTM Network for Short-term Passenger Flow Forecasting in Urban Rail Transit

Zhang, Jinlei; Chen, Feng; Shen, Qing. (2019). Cluster-based LSTM Network for Short-term Passenger Flow Forecasting in Urban Rail Transit. Ieee Access, 7, 147653 – 147671.

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Abstract

Short-term passenger flow forecasting is an essential component for the operation of urban rail transit (URT). Therefore, it is necessary to obtain a higher prediction precision with the development of URT. As artificial intelligence becomes increasingly prevalent, many prediction methods including the long short-term memory network (LSTM) in the deep learning field have been applied in road transportation systems, which can give critical insights for URT. First, we propose a novel two-step K-Means clustering model to capture not only the passenger flow variation trends but also the ridership volume characteristics. Then, a predictability assessment model is developed to recommend a reasonable time granularity interval to aggregate passenger flows. Based on the clustering results and the recommended time granularity interval, the LSTM model, which is called CB-LSTM model, is proposed to conduct short-term passenger flow forecasting. Results show that the prediction based on subway station clusters can not only avoid the complication of developing numerous models for each of the hundreds of stations, but also improve the prediction performance, which make it possible to predict short-term passenger flow on a network scale using limited dataset. The results provide critical insights for subway operators and transportation policymakers.

Keywords

Traffic Flow; Neural-network; Prediction; Ridership; Models; Volume; Lstm; Short-term Passenger Flow Forecasting; Urban Rail Transit; K-means Clustering; Deep Learning

Identifying High-risk Built Environments for Severe Bicycling Injuries

Chen, Peng; Shen, Qing. (2019). Identifying High-risk Built Environments for Severe Bicycling Injuries. Journal of Safety Research, 68, 1 – 7.

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Abstract

Introduction: This study is aimed at filling part of the knowledge gap on bicycling safety in the built environment by addressing two questions. First, are built environment features and bicyclist injury severity correlated; and if so, what built environment factors most significantly relate to severe bicyclist injuries? Second, are the identified associations varied substantially among cities with different levels of bicycling and different built environments? Methods: The generalized ordered logit model is employed to examine the relationship between built environment features and bicyclist injury severity. Results: Bicyclist injury severity is coded into four types, including no injury (NI), possible injury (PI), evident injury (El), and severe injury and fatality (SIF). The findings include: (a) higher percentages of residential land and green space, and office or mixed use land are correlated with lower probabilities of El and SIF; (b) land use mixture is negatively correlated with El and SIF; (c) steep slopes are positively associated with bicyclist injury severity; (d) in areas with more transit routes, bicyclist injury is less likely to be severe; (e) a higher speed limit is more likely to correlate with SIF; and (f) wearing a helmet is negatively associated with SIF, but positively related to PI and El. Practical applications: To improve bicycle safety, urban planners and policymakers should encourage mixed land use, promote dense street networks, place new bike lanes in residential neighborhoods and green spaces, and office districts, while avoiding steep slopes. To promote bicycling, a process of evaluating the risk of bicyclists involving severe injuries in the local environment should be implemented before encouraging bicycle activities. (C) 2018 National Safety Council and Elsevier Ltd. All rights reserved.

Keywords

Motor Vehicle; Land-use; Crashes; Severities; Facilities; Frameworks; Frequency; Cyclists; Bike; Bicyclist Injury Severity; Built Environments; Generalized Ordered Logit Model; Us Cities; Bicycles; Urban Environments; Injuries; Neighborhoods; Land Use; Urban Areas; Paths; Protective Equipment; Bicycling; Fatalities; Correlation; Residential Areas; Traffic Accidents & Safety; Safety; Logit Models; Ecological Risk Assessment; Slopes; Health Risks; Urban Transportation; Studies; Environments

Intersections and Non-Intersections: A Protocol for Identifying Pedestrian Crash Risk Locations in GIS

Kang, Mingyu; Moudon, Anne Vernez; Kim, Haena; Boyle, Linda Ng. (2019). Intersections and Non-Intersections: A Protocol for Identifying Pedestrian Crash Risk Locations in GIS. International Journal Of Environmental Research And Public Health, 16(19).

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Abstract

Intersection and non-intersection locations are commonly used as spatial units of analysis for modeling pedestrian crashes. While both location types have been previously studied, comparing results is difficult given the different data and methods used to identify crash-risk locations. In this study, a systematic and replicable protocol was developed in GIS (Geographic Information System) to create a consistent spatial unit of analysis for use in pedestrian crash modelling. Four publicly accessible datasets were used to identify unique intersection and non-intersection locations: Roadway intersection points, roadway lanes, legal speed limits, and pedestrian crash records. Two algorithms were developed and tested using five search radii (ranging from 20 to 100 m) to assess the protocol reliability. The algorithms, which were designed to identify crash-risk locations at intersection and non-intersection areas detected 87.2% of the pedestrian crash locations (r: 20 m). Agreement rates between algorithm results and the crash data were 94.1% for intersection and 98.0% for non-intersection locations, respectively. The buffer size of 20 m generally showed the highest performance in the analyses. The present protocol offered an efficient and reliable method to create spatial analysis units for pedestrian crash modeling. It provided researchers a cost-effective method to identify unique intersection and non-intersection locations. Additional search radii should be tested in future studies to refine the capture of crash-risk locations.

Keywords

Traffic Crash; Walking; Collisions; Accidents; Models; Pedestrian Safety; Spatial Autocorrelation; Algorithm

A Roadmap for Urban Evolutionary Ecology

Rivkin, L. Ruth; Santangelo, James S.; Alberti, Marina; Aronson, Myla F. J.; De Keyzer, Charlotte W.; Diamond, Sarah E.; Fortin, Marie-josee; Frazee, Lauren J.; Gorton, Amanda J.; Hendry, Andrew P.; Liu, Yang; Losos, Jonathan B.; Macivor, J. Scott; Martin, Ryan A.; Mcdonnell, Mark J.; Miles, Lindsay S.; Munshi-south, Jason; Ness, Robert W.; Newman, Amy E. M.; Stothart, Mason R.; Theodorou, Panagiotis; Thompson, Ken A.; Verrelli, Brian C.; Whitehead, Andrew; Winchell, Kristin M.; Johnson, Marc T. J. (2019). A Roadmap for Urban Evolutionary Ecology. Evolutionary Applications, 12(3), 384 – 398.

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Abstract

Urban ecosystems are rapidly expanding throughout the world, but how urban growth affects the evolutionary ecology of species living in urban areas remains largely unknown. Urban ecology has advanced our understanding of how the development of cities and towns change environmental conditions and alter ecological processes and patterns. However, despite decades of research in urban ecology, the extent to which urbanization influences evolutionary and eco-evolutionary change has received little attention. The nascent field of urban evolutionary ecology seeks to understand how urbanization affects the evolution of populations, and how those evolutionary changes in turn influence the ecological dynamics of populations, communities, and ecosystems. Following a brief history of this emerging field, this Perspective article provides a research agenda and roadmap for future research aimed at advancing our understanding of the interplay between ecology and evolution of urban-dwelling organisms. We identify six key questions that, if addressed, would significantly increase our understanding of how urbanization influences evolutionary processes. These questions consider how urbanization affects nonadaptive evolution, natural selection, and convergent evolution, in addition to the role of urban environmental heterogeneity on species evolution, and the roles of phenotypic plasticity versus adaptation on species' abundance in cities. Our final question examines the impact of urbanization on evolutionary diversification. For each of these six questions, we suggest avenues for future research that will help advance the field of urban evolutionary ecology. Lastly, we highlight the importance of integrating urban evolutionary ecology into urban planning, conservation practice, pest management, and public engagement.

Keywords

Urban Ecology (biology); Climate Change; Urban Growth; Species Diversity; Urbanization; Citizen Science; Community Engagement; Eco-evolutionary Feedback; Gene Flow; Landscape Genetics; Urban Evolution; Urban Socioecology; Mouse Peromyscus-leucopus; Rapid Evolution; Population Genomics; Selection; Habitat; Differentiation; Framework; Environments; Biodiversity; Eco-evolutionary Feedback

The Effect of Market Conditions on the Housing Outcomes of Subsidized Households: The Case of the US Voucher Programme

Colburn, Gregg. (2019). The Effect of Market Conditions on the Housing Outcomes of Subsidized Households: The Case of the US Voucher Programme. Housing Studies, 34(9), 1465 – 1484.

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Abstract

Since being created in the 1970s, housing vouchers have become the primary mode of federal housing support for low-income households in the US. The voucher programme was designed to provide recipients with the mobility needed to secure higher quality housing in neighbourhoods of their choice. Decades of analysis suggest that the programme has failed to produce the favourable outcomes envisioned by policymakers. To add to our understanding of the outcomes of this important federal programme, this paper seeks to underscore the importance of context-dependent policy analysis. In particular, this study analyses the impact of housing market conditions on the outcomes achieved by voucher recipients. Using neighbourhood and housing outcome data from the American Housing Survey, and median rent and rental market vacancy data, this paper demonstrates the important role that market conditions play in programme outcomes. The results from this study suggest that voucher recipients are successful at improving housing unit quality outcomes regardless of market conditions, but the ability to move to a better neighbourhood is a function of vacancy rates.

Keywords

Housing Subsidies; Housing Vouchers; Housing Market; Poor Communities; Neighborhoods; Housing; Housing Choice Voucher; Market; Neighbourhood; Section 8; Vacancy; Voucher; Residential-mobility Decisions; Choice Vouchers; Neighborhood; Income; Live; Families; Place; Home; Markets; Economic Conditions; Policy Analysis; Households; Impact Analysis; Policy Making; Low Income Groups; Vouchers; Mobility; Vacancies; Conditions; United States--us

Identification and Reduction of Synchronous Replacements in Life-Cycle Cost Analysis of Equipment

Kim, Jonghyeob; Han, Sangwon; Hyun, Chang-taek. (2019). Identification and Reduction of Synchronous Replacements in Life-Cycle Cost Analysis of Equipment. Journal Of Management In Engineering, 35(1).

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Abstract

Life-cycle cost analysis (LCCA) is a methodology used to calculate the total cost of a project from initial planning to final disposal. In conventional approaches, LCCA assumes that regular and preventive maintenance will be performed according to each replacement cycle for individual components, and replacement for each component is considered independently. However, because the components of equipment used in buildings are installed systemically, replacements of major components may cause unexpected replacements of dependent minor components. Therefore, it is necessary to identify additional replacements based on the associations among these related replacement components to achieve a more reliable LCCA. In response, this study proposes an LCCA model that comprehensively considers the relationships among the maintenance components. The development of the model involves identifying relationships among components using social network analysis (SNA), arranging individual replacement timings of the components that reflect these relationships, and analyzing the life-cycle cost (LCC) based on the arranged timing. To validate the model, its applicability and effectiveness was illustrated and tested using 19 components of a rainwater reuse system. This study makes a theoretical contribution to the body of knowledge by suggesting concepts of synchronous relationships and replacements based on SNA. In addition, the use of the model proposed in this study enables practitioners to analyze LCCs that reflect synchronous replacements, which allows more reasonable decision-making considering hidden costs in conventional LCC. (C) 2018 American Society of Civil Engineers.

Keywords

Decision Making; Life Cycle Costing; Preventive Maintenance; Synchronous Replacements; Life-cycle Cost Analysis; Lcca Model; Maintenance Components; Social Network Analysis; Painted Surfaces; Decision-making; Prediction; Model; Risk; Maintenance; Replacement; Synchronous Replacement; Synchronous Relationship; Life-cycle Cost Analysis (lcca); Social Network Analysis (sna)

A Taxonomy for Whole Building Life Cycle Assessment (WBLCA)

Rodriguez, Barbara X.; Simonen, Kathrina; Huang, Monica; De Wolf, Catherine. (2019). A Taxonomy for Whole Building Life Cycle Assessment (WBLCA). Smart And Sustainable Built Environment, 8(3), 190 – 205.

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Abstract

Purpose The purpose of this paper is to present an analysis of common parameters in existing tools that provide guidance to carry out Whole Building Life Cycle Assessment (WBLCA) and proposes a new taxonomy, a catalogue of parameters, for the definition of the goal and scope (G&S) in WBLCA. Design/methodology/approach A content analysis approach is used to identify, code and analyze parameters in existing WBLCA tools. Finally, a catalogue of parameters is organized into a new taxonomy. Findings In total, 650 distinct parameter names related to the definition of G&S from 16 WBLCAs tools available in North America, Europe and Australia are identified. Building on the analysis of existing taxonomies, a new taxonomy of 54 parameters is proposed in order to describe the G&S of WBLCA. Research limitations/implications The analysis of parameters in WBLCA tools does not include Green Building Rating Systems and is only limited to tools available in English. Practical implications This research is crucial in life cycle assessment (LCA) method harmonization and to serve as a stepping stone to the identification and categorization of parameters that could contribute to WBLCA comparison necessary to meet current global carbon goals. Social implications The proposed taxonomy enables architecture, engineering and construction practitioners to contribute to current WBLCA practice. Originality/value A study of common parameters in existing tools contributes to identifying the type of data that is required to describe buildings and contribute to build a standardized framework for LCA reporting, which would facilitate consistency across future studies and can serve as a checklist for practitioners when conducting the G&S stage of WBLCA.

Keywords

Content Analysis; Taxonomy; Lca; Lca Tools; Tools For Practitioners; Whole Building Life Cycle Assessment

Between Fixities and Flows: Navigating Place Attachments in an Increasingly Mobile World

Di Masso, Andres; Williams, Daniel R.; Raymond, Christopher M.; Buchecker, Matthias; Degenhardt, Barbara; Devine-Wright, Patrick; Hertzog, Alice; Lewicka, Maria; Manzo, Lynne; Shahrad, Azadeh; Stedman, Richard; Verbrugge, Laura; von Wirth, Timo. (2019). Between Fixities and Flows: Navigating Place Attachments in an Increasingly Mobile World. Journal Of Environmental Psychology, 61, 125 – 133.

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Abstract

This paper develops a theoretical argument for how place attachments are forged and become dynamically linked to increasingly common mobility practices. First, we argue that mobilities, rather than negating the importance of place, shift our understanding of place and the habitual ways we relate to and bond with places as distinct from a conception of place attachment premised on fixity and stability. Second, we document how the body of research on place attachment has both reinforced and contested 'sedentaristic' assumptions criticized within the so-called 'mobilities turn' in the social sciences. Third, we present a conceptual framework, built around different modes of interrelation between fixity and flow, as a way to re-theorize, link and balance the various studies of place attachment that have grappled with mobility. Finally, we sketch out the main research implications of this framework for advancing our understanding of place attachment in a mobile world.

Keywords

Sense; Identity; Dimensions; Mobilities; Home; Cosmopolitan; Environment; Migration; Community; Benefits; Flow; Fixity; Place Attachment; Human Settlements; Psychology; Social Environment