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1. The spatial and social correlates of neighborhood morphology: Evidence from building footprints in five U.S. metropolitan areas

   https://doi.org/10.1371/journal.pone.0299713  

   Durst, Noah J; Sullivan, Esther; Jochem, Warren C (April 2024, PLOS ONE)

   Xu, Gang (Ed.)

   Recent advances in quantitative tools for examining urban morphology enable the development of morphometrics that can characterize the size, shape, and placement of buildings; the relationships between them; and their association with broader patterns of development. Although these methods have the potential to provide substantial insight into the ways in which neighborhood morphology shapes the socioeconomic and demographic characteristics of neighborhoods and communities, this question is largely unexplored. Using building footprints in five of the ten largest U.S. metropolitan areas (Atlanta, Boston, Chicago, Houston, and Los Angeles) and the open-source R package,foot, we examine how neighborhood morphology differs across U.S. metropolitan areas and across the urban-exurban landscape. Principal components analysis, unsupervised classification (K-means), and Ordinary Least Squares regression analysis are used to develop a morphological typology of neighborhoods and to examine its association with the spatial, socioeconomic, and demographic characteristics of census tracts. Our findings illustrate substantial variation in the morphology of neighborhoods, both across the five metropolitan areas as well as between central cities, suburbs, and the urban fringe within each metropolitan area. We identify five different types of neighborhoods indicative of different stages of development and distributed unevenly across the urban landscape: these include low-density neighborhoods on the urban fringe; mixed use and high-density residential areas in central cities; and uniform residential neighborhoods in suburban cities. Results from regression analysis illustrate that the prevalence of each of these forms is closely associated with variation in socioeconomic and demographic characteristics such as population density, the prevalence of multifamily housing, and income, race/ethnicity, homeownership, and commuting by car. We conclude by discussing the implications of our findings and suggesting avenues for future research on neighborhood morphology, including ways that it might provide insight into issues such as zoning and land use, housing policy, and residential segregation. 

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2. Lifetime energy performance of residential buildings: A sensitivity analysis of energy modeling parameters

   Malekpour Koupaei, D. Geraudin (October 2020, Proceedings of the symposium on Simulation for Architecture and Urban Design)

   Chronis, A. (Ed.)

   Traditional building energy simulation tools often assess performance as a function of the unique climate, physical characteristics, and operational parameters that define specific buildings and communities, planned or existing. This paper presents the results of a sensitivity analysis on the input parameters(relating to both the building and climate) that affect the annual energy consumption loads of an existing residential neighborhood in the U.S. Midwest over the anticipated service life of its buildings using the Urban Modeling Interface (umi). Accordingly, first, the effect of multiple building construction characteristic packages and inclusion of outdoor vegetation, are investigated under typical meteorological climate conditions. Afterwards, since typical climate conditions may not adequately describe the potential extreme conditions that will be encountered over the entire service life of these buildings, alternative weather datasets were also utilized in the sensitivity analysis. The study’s findings suggest that cooling loads are expected to increase dramatically over the next five decades, both due to changes in the climate and the more wide-spread use of air-conditioning units. Since the results showed that trees can effectively reduce cooling loads by up to 7%, it is recommended that urban vegetation should be considered as an effective adaptation measure for facing the growing cooling demands. 

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3. Enhancing Urban Thermal Environment and Energy Sustainability With Temperature‐Adaptive Radiative Roofs

   https://doi.org/10.1029/2024EF005246  

   Zhang, Keer; Zhao, Lei; Oleson, Keith; Li, Xinchang “Cathy”; Lee, Xuhui (January 2025, Earth's Future)

   Abstract Urban overheating presents significant challenges to public health and energy sustainability. Conventional radiative cooling strategies, such as cool roofs with high albedo, lead to undesired winter cooling and increased space heating demand for cities with cold winters, a phenomenon known as heating energy penalty. A novel roof coating with high albedo and temperature‐adaptive emissivity (TAE)—low emissivity during cold conditions and high emissivity during hot conditions—has the potential to mitigate winter heating energy penalty. In this study, we implement this roof coating in a global climate model to evaluate its impact on air temperature and building energy demand for space heating and cooling in global cities. Adopting roofs with TAE increases global urban air temperature by up to +0.54°C in the winter (99th percentile; mean change +0.16°C) but has negligible effects on summer urban air temperature (mean change +0.05°C). Combining TAE with high albedo effectively provides summer cooling and does not increase building energy demand in the winter, particularly for mid‐latitude cities. Sensitivities of air temperature to changes in emissivity and albedo are associated with local “apparent” net longwave radiation and incoming solar radiation, respectively. We propose a simple parameterization of air temperature responses to emissivity and albedo to facilitate the development of city‐specific radiative mitigation strategies. This study emphasizes the necessity of developing mitigation approaches specific to local cloudiness. 

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4. Mapping pedestrian network level outdoor heat hazard distributions in Philadelphia

   https://doi.org/10.1177/23998083241274391  

   Li, Xiaojiang (May 2025, Environment and Planning B: Urban Analytics and City Science)

   With the rise of global temperature, many cities are suffering from more and more frequent extreme heat in hot summers. Quantitative information on the spatial distributions of urban heat has become more and more important for extreme heat mitigation and adaptation in cities. This study first investigated the fine-level heat hazard distributions at the sidewalk and building block level from the pedestrian perspective in Philadelphia, Pennsylvania. The urban microclimate modeling based on a high-resolution urban geometrical model was used to generate the 1m resolution outdoor heat hazard map in the study area. The sidewalk map was overlaid on the generated high-resolution heat hazard map to estimate the sidewalk level heat hazard. Based on the sidewalk level heat hazard map, this study further calculated the heat hazard level in the 400m walkshed along sidewalks for each building block. The building level hazard data were then aggregated at the census tract level to compare with the socioeconomic and racial/ethnic variables. The result shows that neighborhoods with higher proportion of African Americans have a higher heat hazard level in Philadelphia. This study would provide new insights for developing more thermally comfortable and pedestrian-friendly neighborhoods in the context of climate change. 

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5. Utilizing smart-meter data to project impacts of urban warming on residential electricity use for vulnerable populations in Southern California

   https://doi.org/10.1088/1748-9326/ab6fbe  

   Chen, Mo; Ban-Weiss, George A.; Sanders, Kelly T. (May 2020, Environmental Research Letters)

   Abstract Extreme heat events are increasing in frequency and intensity, challenging electricity infrastructure due to growing cooling demand and posing public health risks to urbanites. In order to minimize risks from increasing extreme heat, it is critical to (a) project increases in electricity use with urban warming, and (b) identify neighborhoods that are most vulnerable due in part to a lack of air conditioning (AC) and inability to afford increased energy. Here, we utilize smart meter data from 180 476 households in Southern California to quantify increases in residential electricity use per degree warming for each census tract. We also compute AC penetration rates, finding that air conditioners are less prevalent in poorer census tracts. Utilizing climate change projections for end of century, we show that 55% and 30% of the census tracts identified as most vulnerable are expected to experience more than 16 and 32 extreme heat days per year, respectively. 

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