Scaling of the morphology of African cities.

A large proportion of Africa's infrastructure is yet to be built. Where and how these new buildings are constructed matters since today's decisions will last for decades. The resulting morphology of cities has lasting implications for a city's energy needs. Estimating and projecting these needs has always been challenging in Africa due to the lack of data. Yet, given the sweeping urbanization expected in Africa over the next three decades, this obstacle must be overcome to guide cities toward a trajectory of sustainability and resilience. Based on the location and surface of nearly 200 million buildings on the continent, we estimate the interbuilding distance of almost six thousand cities. Buildings' footprint data enable the construction of urban form indicators to compare African cities' elongation, sprawl, and emptiness. We establish the BASE model, where the mean distance between buildings is a functional relation to the number of Buildings and their average Area, as well as the Sprawl and the Elongation of its spatial arrangement. The mean distance between structures in cities-our proxy for its energy demands related to mobility-grows faster than the square root of its population, resulting from the combined impact of a sublinear growth in the number of buildings and a sublinear increase in building size and sprawl. We estimate that when a city doubles its population, it triples its energy demand from transport.

Satellite mapping of urban built-up heights reveals extreme infrastructure gaps and inequalities in the Global South.

Information on urban built-up infrastructure is essential to understand the role of cities in shaping environmental, economic, and social outcomes. The lack of data on built-up heights over large areas has limited our ability to characterize urban infrastructure and its spatial variations across the world. Here, we developed a global atlas of urban built-up heights circa 2015 at 500-m resolution from the Sentinel-1 Ground Range Detected satellite data. Results show extreme gaps in per capita urban built-up infrastructure in the Global South compared with the global average, and even larger gaps compared with the average levels in the Global North. Per capita urban built-up infrastructures in some countries in the Global North are more than 30 times higher than those in the Global South. The results also show that the built-up infrastructure in 45 countries in the Global North combined, with ∼16% of the global population, is roughly equivalent to that of 114 countries in the Global South, with ∼74% of the global population. The inequality in urban built-up infrastructure, as measured by an inequality index, is large in most countries, but the largest in the Global South compared with the Global North. Our analysis reveals the scale of infrastructure demand in the Global South that is required in order to meet sustainable development goals.

Urban design and cardio-metabolic risk factors.

Accumulating evidence suggests that the built environment may be associated with cardiovascular disease via its influence on health behaviours. The aim of this study was to estimate the associations between traditional and novel neighbourhood built environment metrics and clinically assessed cardio-metabolic risk factors among a sample of adults in Canada. A total of 7171 participants from Albertas Tomorrow Project living in Alberta, Canada, were included. Cardio-metabolic risk factors were clinically measured. Two composite built environment metrics of traditional walkability and space syntax walkability were calculated. Among men, space syntax walkability was negatively associated with systolic and diastolic blood pressure (b = -0.87, 95% CI -1.43, -0.31 and b = -0.45, 95% CI -0.86, -0.04, respectively). Space syntax walkability was also associated with lower odds of overweight/obese among women and men (OR = 0.93, 95% CI 0.87, 0.99 and OR = 0.88, 95% CI 0.79, 0.97, respectively). No significant associations were observed between traditional walkability and cardio-metabolic outcomes. This study showed that the novel built environment metric based on the space syntax theory was associated with some cardio-metabolic risk factors.

Urban Form Metrics for Promoting Walking: Street Layouts and Destinations.

There is evidence that higher street connectivity and availability of destinations can support walking behavior. However, the availability of data and comparability between previous studies remain a challenge. Based on a large Canadian adult sample, this study examined the associations between street layout and walking behaviors and explored whether objectively measured destinations may mediate these relationships. This study used data from 12,378 adults from Alberta's Tomorrow Project (ATP), a prospective cohort study conducted in Alberta, Canada. Walking behaviors were obtained by questionnaires. Street layout and destination measures were calculated objectively. Covariate-adjusted multivariate linear models estimated the associations between the space syntax street integration and duration of transport and leisure walking. The mediation effects of the availability of destinations in these associations were tested by the structural equation modelling. Street integration was significantly positively associated with transportation walking (b=0.01, 95% CI 0.00, 0.01, p = 0.01) (indirect effect). The availability of destinations partially mediated this association. Using the natural movement theory in space syntax, our study provides insights into using street layouts as a primary measure to (re)design the built environment to support walking.

Effect of urban form on PM2.5 concentrations in urban agglomerations of China: Insights from different urbanization levels and seasons.

Planned urban form has become an important strategy to improve air quality in urban agglomerations (UAs), especially pollution due to PM2.5, but the influencing mechanisms are not yet clear. This study explores the relationship between four metrics of urban form (size, fragmentation, shape, and dispersion) as determined by analysis of remotely sensed images at 30-m resolution and PM2.5 concentrations in 19 Chinese UAs. The influence of level of urban development and season is examined. Five control variables, including population density, temperature, precipitation, wind speed, and the normalized difference vegetation index (NDVI) are selected for use in multiple linear regression models. Size, fragmentation, and shape of urban form, but not dispersion, were found to have significant effects on PM2.5 concentrations of different urbanization-level UAs. Urban size and fragmentation have stronger impacts on PM2.5 concentrations in UAs with lower urbanization levels while urban shape has a greater impact in higher-level UAs. In terms of seasonal variation in all UAs, urban form is more pronouncedly associated with PM2.5 concentrations during spring and autumn than summer and winter. Urban size and fragmentation are positively associated with PM2.5 concentrations whereas urban shape and dispersion are on the contrary. The relationships between urban form and PM2.5 uncovered here underscore the importance of urban planning as a tool to minimize PM2.5 pollution. Specifically, local government should encourage polycentric urban form with lower fragmentation in urban agglomerations. UAs with lower urbanization levels should control the disordered expansion of construction land and higher-level UAs should promote the mix of green land and construction land. Moreover, measures to control air pollution from anthropogenic activities in spring, autumn and winter are likely to be more effective in decreasing PM2.5 concentrations in UAs.

Categorizing relative water use perception bias using household surveys and monthly water bills.

We introduce the concept of relative water use perception bias to highlight the role of human relationships, social cues, and the built environment in household water consumption. Although previous studies have explored actual water use, it is also important to understand how people perceive their relative behaviors because humans are social animals and act in relation to each other. We combine household survey responses and water utility bills in a large sample of households to quantify the degree of over- and under-estimation bias in perceived relative household water use. We then use multi-level nested regression models to investigate four categories of potential influence: sociodemographic characteristics, perceived social norms, neighborhood characteristics, and water bill information. Results show that most households tended to view themselves as 'better than average' water users when they actually used more water compared to neighbors. Respondents in high-income households and those who are more concerned about water shortages were more likely to underestimate their relative water use (using comparatively more than they thought). However, in more suburbanized neighborhood environments, households were more likely to overestimate their relative water use (using comparatively less than they thought). We call the inaccuracy in assessing water usage compared to their neighbors' relative water use perception bias. We propose that a better understanding of this bias can aid the design of policy initiatives like neighborhood planning, better water bill design, targeted messaging, and social signaling. By bringing a relational lens to bear on water conservation studies, understanding relative water use perception bias sheds new light on the complex drivers of household water consumption.

Assessing outdoor air quality vertically in an urban street canyon and its response to microclimatic factors.

The vertical distribution of air pollutants in urban street canyons is closely related to residents' health. However, the vertical air quality in urban street canyons has rarely been assessed using field observations obtained throughout the year. Therefore, this study investigated the seasonal and annual concentrations of particulate matter (PM2.5 and PM10), CO, NO2, SO2, O3, air quality index, and their responses to microclimatic factors at three height levels (1.5, 27, and 69 m above street level) in an urban street canyon. The PM concentration was higher at 27 m than at 1.5 m in winter, whereas the situation was reversed in other seasons. It was found that photochemical pollutants such as NO2 and O3 were the primary pollutants in the urban street canyon. The days on which O3 was the primary pollutant at the height of 1.5 m accounted for 81.07% of the entire year. The days on which NO2 was the primary pollutant at the height of 27 and 69 m accounted for 82.49% and 72.33% of the entire year, respectively. Substantially higher concentrations of NO2 and O3 were found at the height of 27 m than at 69 m. In-canyon concentrations of NO2 and O3 were strongly correlated with air temperature, wind speed, and wind direction, which played important roles in photochemical reactions and pollutant dispersion.

Evaluating the Meteorological Effects on the Urban Form-Air Quality Relationship Using Mobile Monitoring.

Predictive models based on mobile measurements have been increasingly used to understand the spatiotemporal variations of intraurban air quality. However, the effects of meteorological factors, which significantly affect the dispersion of air pollution, on the urban-form-air-quality relationship have not been understood on a granular level. We attempt to fill this gap by developing predictive models of particulate matter (PM) in the Bronx (New York City) using meteorological and urban form parameters. The granular PM data was collected by mobile low-cost sensors as the ground truth. To evaluate the effects of meteorological factors, we compared the performance of models using the urban form within fixed and wind-sensitive buffers, respectively. We find better predictive power in the wind-sensitive group (R = 0.85) for NC10 (number concentration for particles with diameters of 1 µm-10 µm) than the control group (R = 0.01), and modest improvements for PM2.5 (R = 0.84 for the wind sensitive group, R = 0.77 for the control group), indicating that incorporating meteorological factors improved the predictive power of our models. We also found that urban form factors account for 62.95% of feature importance for NC10 and 14.90% for PM2.5 (9.99% and 4.91% for 3-D and 2-D urban form factors, respectively) in our Random Forest models. It suggests the importance of incorporating urban form factors, especially for the uncommonly used 3-D characteristics, in estimating intraurban PM. Our method can be applied in other cities to better capture the influence of urban context on PM levels.

The Associations Between Urban Form and Major Non-communicable Diseases: a Systematic Review.

In the current century, non-communicable diseases (NCDs), particularly cardiovascular diseases, diabetes, cancer, and chronic respiratory diseases, are the most important cause of mortality all over the world. Given the effect of the built environment on people's health, the present study seeks to conduct a systematic review in order to investigate the relationship between urban form and these four major NCDs as well as their main risk factors. Two independent reviewers in November 2020 after an extensive search through PubMed and Scopus identified 77 studies. Studies published in English were included if they addressed one or more attributes of urban form in relation to any major NCDs and their main risk factors. Publication date, country, geographical scale, study design, methods of built environment measurement, and findings of the relationships among variables were extracted from eligible studies. The findings suggest that the elements of urban form (density, transportation and accessibility, characteristics of building and streetscape, land use, spatial layouts and configuration) could increase or inhibit these diseases through their effect on physical activity, diet, air pollution, blood pressure, and obesity. However, there are study shortages, contradictions, and ambiguities in these relationships which are mainly due to methodological and conceptual challenges. As a result, more in-depth research is needed to achieve solid and consistent results that could be made into clear guidelines for planning and designing healthier cities.

Public transit cuts during COVID-19 compound social vulnerability in 22 US cities.

The COVID-19 pandemic has severely impacted public transit services through plummeting ridership during the lockdown and subsequent budget cuts. This study investigates the equity impacts of reductions in accessibility due to transit service cuts during COVID-19 and their association with urban sprawl. We evaluated transit access to food and health care services across 22 US cities in three phases during 2020. We found stark socio-spatial disparities in access to basic services and employment in food and health care. Transit service cuts worsened accessibility for communities with multiple social vulnerabilities, such as neighborhoods with high rates of poverty, low-income workers, and zero-vehicle households, as well as poor neighborhoods with high concentrations of black residents. Moreover, sprawled cities experienced greater access loss during COVID-19 than compact cities. Our results point to policies and interventions to maintain social equity and sustainable urban development while benefiting diverse social groups during disruptions.

The influence of urban form compactness on CO2 emissions and its threshold effect: Evidence from cities in China.

Although compact urban form plays an important role in constraining emissions of carbon dioxide (CO2), the boundary for the impact of compact urban form on these emissions has nevertheless received little attention. We consequently applied the entropy weight method and several key landscape metrics to a dataset from 295 cities in China to quantify urban form compactness (UFC) between 2000 and 2015. The STIRPAT model then was employed to estimate the impact of UFC on CO2 emissions, and a panel threshold regression model was used to estimate threshold effects capable of limiting the impact of compact urban form on emissions. Although CO2 emissions increased sharply over the 15-year study period, a significant negative relationship between UFC and CO2 emissions was detected. Two thresholds of UFC were detected, and this allowed three categories to be differentiated: before the first threshold, between the two thresholds, and after the second threshold. These categories were respectively associated with no impact, strong impact, and weak impact of UFC on reduction of carbon emissions in the 295 cities. Carbon emissions reduction consequently becomes effective when the UFC exceeds the first threshold and effectiveness persists but at a reduced level when the UFC exceeds the second threshold. Further temporal analysis confirmed that an increasing number of mostly small- and medium-sized cities could constrain their future carbon emissions by adopting a compact urban form. Thus, government policies should emphasize UFC as a strategy to reduce CO2 emissions. Moreover, by defining the range of compact urban form that has the greatest impact on CO2 emissions, our study deepens the overall understanding of the influence of UFC on carbon emission reductions, so as to make contributions to the design of low-carbon cities.

Exploring the impact of urban form on urban land use efficiency under low-carbon emission constraints: A case study in China's Yellow River Basin.

In the Urban Anthropocene, how to meet the demands of growing urban populations on limited urban land is a key global challenge. Unreasonable urban planning and land use has brought about undesirable consequences including huge carbon emissions. However, research on the spatial impact of urban form on urban land use efficiency (ULUE) under low-carbon emission constraints is limited. This study analyzes 91 cities located in China's Yellow River Basin (YRB). First, we define a new comprehensive indicator system to measure ULUE under low-carbon constraints using the SBM-UN model. We then select nine landscape indicators to quantify the sprawl, complexity, and aggregation of urban form. Finally, we use Spatial Durbin Model to reveal the relationship between urban form and ULUE. We find that carbon emissions in the YRB increased steadily during the study period. The average value of ULUE increased from 0.469 in 1994 to 0.772 in 2018. Efficiency improved most in the provinces of Shaanxi, Henan, Ningxia, and Shandong, with growth rates of 234.15%, 102.40%, 93.09%, and 66.24%, respectively. Positive global Moran's I indices suggest that the spatial distribution of ULUE is positively correlated at basin level. Moreover, urban form metrics in the YRB demonstrated significant regional differences from 1994 to 2018. The regression results showed irregular urban form can negatively impact ULUE while compact and aggregated urban forms can improve ULUE under low carbon constrains. In addition, there are both positive and negative correlations between urban sprawl and ULUE in different regions. Today's choices on urban form can restrict the development pattern of cities and lock in pathways of carbon emissions in the future. Based on the findings in this study, the government should pursue optimal city sizes, avoid scattered patterns and aim for compact urban form.

How do single-family homeowners value residential and commercial density? It depends.

This paper develops estimates of the relationship between local density and single-family home values across five U.S. metropolitan areas using 2017 transactions in Chicago, Los Angeles, Minneapolis, Philadelphia, Seattle. Proposals to build new commercial and residential development projects that would increase local density commonly face opposition from local homeowners. Academic literature links the response from homeowners to concerns that higher density is associated with lower property values but there is limited empirical evidence establishing this relationship at the local level. We find a positive and significant relationship between density and house value in the core area of the five metropolitan regions we analyze. For outlying areas, the estimates are smaller and even negative in several cases. We instrument density based on topographic and soil characteristics and find similar results. These findings point to the need for a more nuanced discussion of the relationship between local density and housing values.

Relationships between urban form and air quality: A reconsideration based on evidence from China's five urban agglomerations during the COVID-19 pandemic.

The outbreak of Coronavirus disease 2019 (COVID-19) led to the widespread stagnation of urban activities, resulting in a significant reduction in industrial pollution and traffic pollution. This affected how urban form influences air quality. This study reconsiders the influence of urban form on air quality in five urban agglomerations in China during the pandemic period. The random forest algorithm was used to quantitate the urban form-air quality relationship. The urban form was described by urban size, shape, fragmentation, compactness, and sprawl. Air quality was evaluated by the Air Quality Index (AQI) and the concentration of six pollutants (CO, O3, NO2, PM2.5, PM10, SO2). The results showed that urban fragmentation is the most important factor affecting air quality and the concentration of the six pollutants. Additionally, the relationship between urban form and air quality varies in different urban agglomerations. By analyzing the extremely important indicators affecting air pollution, the urban form-air quality relationship in Beijing-Tianjin-Hebei is rather complex. In the Chengdu-Chongqing and the Pearl River Delta, urban sprawl and urban compactness are extremely important indicators for some air pollutants, respectively. Furthermore, urban shape ranks first for some air pollutants both in the Triangle of Central China and the Yangtze River Delta. Based on the robustness test, the performance of the random forest model is better than that of the multiple linear regression (MLR) model and the extreme gradient boosting (XGBoost) model.

COVID-19 impact on teleactivities: Role of built environment and implications for mobility.

This paper presents new evidence on changes in a broad range of teleactivities due to the Coronavirus disease (COVID-19) pandemic and investigates how the built environment relates to these changes. The paper relies on survey and geospatial data from Oslo and its surrounding Viken region in Norway. Findings suggest that most teleactivities increased due to COVID-19. Telework, teleconferencing, online learning, telehealth, and virtual meetings with friends and family all increased during COVID-19 compared to the pre-COVID-19 period. The next step in the analysis examined relationships between built environment characteristics and teleactivities before and during COVID-19. Telework and virtual meetings increased to a greater extent in denser neighborhoods than in lower-density neighborhoods. A larger increase in online learning was associated with lower neighborhood density, lower accessibility to public transport, and more local facilities. Numerous local facilities were associated with more frequent telework and virtual meetings both before and during COVID-19. The substantial COVID-19-induced increase in teleactivities found in the study highlights the potential of information and communications technology (ICT) for replacing travel for various activities.

Effects of urban form on air quality: A case study from China comparing years with normal and reduced human activity due to the COVID-19 pandemic.

This study explored the dynamic and complex relationships between air quality and urban form when considering reduced human activities. Applying the random forest method to data from 62 prefecture-level cities in China, urban form-air quality relationships were compared between 2015 (a normal year) and 2020 (which had significantly reduced air pollution due to COVID-19 lockdowns). Significant differences were found between these two years; urban compactness, shape, and size were of prime importance to air quality in 2020, while fragmentation was the most critical factor in improving air quality in 2015. An important influence of traffic mode was also found when controlling air pollution. In general, in the pursuit of reducing air pollution across society, the best urban forms are continuous and compact with reasonable building layouts, population, and road densities, and high forest area ratios. A polycentric urban form that alleviates the negative impacts of traffic pollution is preferable. Urban development should aim to reduce air pollution, and optimizing the effects of urban form on air quality is a cost-effective way to create better living environments. This study provides a reference for decision-makers evaluating the effects of urban form on air pollution emission, dispersion, and concentration in the post-pandemic era.

National Empirical Models of Air Pollution Using Microscale Measures of the Urban Environment.

National-scale empirical models of air pollution (e.g., Land Use Regression) rely on predictor variables (e.g., population density, land cover) at different geographic scales. These models typically lack microscale variables (e.g., street level), which may improve prediction with fine-spatial gradients. We developed microscale variables of the urban environment including Point of Interest (POI) data, Google Street View (GSV) imagery, and satellite-based measures of urban form. We developed United States national models for six criteria pollutants (NO2, PM2.5, O3, CO, PM10, SO2) using various modeling approaches: Stepwise Regression + kriging (SW-K), Partial Least Squares + kriging (PLS-K), and Machine Learning + kriging (ML-K). We compared predictor variables (e.g., traditional vs microscale) and emerging modeling approaches (ML-K) to well-established approaches (i.e., traditional variables in a PLS-K or SW-K framework). We found that combined predictor variables (traditional + microscale) in the ML-K models outperformed the well-established approaches (10-fold spatial cross-validation (CV) R2 increased 0.02-0.42 [average: 0.19] among six criteria pollutants). Comparing all model types using microscale variables to models with traditional variables, the performance is similar (average difference of 10-fold spatial CV R2 = 0.05) suggesting microscale variables are a suitable substitute for traditional variables. ML-K and microscale variables show promise for improving national empirical models.

Road Traffic and Urban Form Factors Correlated with the Incidence of Lung Cancer in High-density Areas: An Ecological Study in Downtown Shanghai, China.

The incidence of lung cancer is affected by air pollution, especially in high-density urban areas with heavy road traffic and dense urban form. Several studies have examined the direct relationship between lung cancer incidence and road traffic as well as urban form. However, the results are still inconsistent for high-density urban areas. This study focused on urban form and road traffic, aiming at revealing their relationship with lung cancer incidence in high-density urban areas at the neighborhood level. For this, an ecological study was conducted in downtown Shanghai to identify important indicators and explore quantitative associations. Negative binomial regression was fitted with lung cancer incidence as the dependent variable. The independent variables included indicators for road traffic and urban form, greenness, demographic, and socio-economic factors. The results showed that building coverage, averaged block perimeter area ratio, density of metro station without the glass barrier system, and the percentage of low-quality residential land were positively correlated with lung cancer incidence in the neighborhood, while population density was negatively correlated with lung cancer incidence. This study found a strong self-selection effect of socio-economic factors in the relationship between lung cancer incidence and greenness. These results may be useful for conducting health impact assessments and developing spatial planning interventions for respiratory health in high-density urban areas.

Impacts of urban form and urban heat island on the outdoor thermal comfort: a pilot study on Mashhad.

There is an increasing demand for cooling cities because of its importance on human health and the quality of life in outdoor urban spaces. However, the development of methods in improving outdoor thermal comfort and zoning cities based on outdoor thermal comfort is still challenging. In this work, we propose a new approach to cities zoning from the lens of outdoor thermal comfort in the arid climate of the city of Mashhad, Iran, and investigate the impacts of urban form characteristics on pedestrian thermal comfort. The effects of complex urban form parameters including height to width (H/W) ratio, canyon orientation, tree canopy cover, and building surface materials on the thermal comfort of pedestrians were studied in the arid climate of Mashhad. Microclimate simulation and analysis is conducted in ENVI-met software, and ArcMap is used to calculate Mashhad urban heat islands. Path analysis in SPSS presents an urban form formulation, which predicts approximate outdoor thermal comfort condition in current and future urban context of Mashhad and other cities with the same climate. We finally demonstrate the use of our research method as an alternative method for all cities: urban heat island (UHI) zoning can be used as a substitute for urban form zonings based on outdoor thermal comfort, especially in large cities where data collection on urban form can be difficult due to limited time and resources.

Influence of urban morphological parameters on the distribution and diffusion of air pollutants: A case study in China.

Air pollution has a serious fallout on human health, and the influences of the different urban morphological characteristics on air pollutants cannot be ignored. In this study, the relationship between urban morphology and air quality (wind speed, CO, and PM2.5) in residential neighborhoods at the meso-microscale was investigated. The changes in the microclimate and pollutant diffusion distribution in the neighborhood under diverse weather conditions were simulated by Computational Fluid Dynamics (CFD). This study identified five key urban morphological parameters (Building Density, Average Building Height, Standard Deviation of Building Height, Mean Building Volume, and Degree of Enclosure) which significantly impacted the diffusion and distribution of pollutants in the neighborhood. The findings of this study suggested that three specific strategies (e.g. volume of a single building should be reduced, DE should be increased) and one comprehensive strategy (the width and height of the single building should be reduced while the number of single buildings should be increased) could be illustrated as an optimized approach of urban planning to relief the air pollution. The result of the combined effects could provide a reference for mitigating air pollution in sustainable urban environments.