Neighborhood Scale Research Articles

Characteristics and prediction of traffic-related PMs and CO2 at the urban neighborhood scale

Accurate portrayal of the spatial-temporal distribution of traffic-related pollutants at the neighborhood scale contributes to refined management for the urban air environment. This study conducted mobile monitoring of traffic-related particulate matters (TRPMs, including PM10, PM2.5, and BC) and CO2 on urban roads in a neighborhood-scale area of Xi'an. Random forest land-use regression (RF-LUR) models for TRPMs and CO2 were developed to quantify the contributions of relevant influencing factors. Finally, the accuracy of the LUR and RF-LUR prediction models was evaluated and compared. The results showed that the pollutants in the neighborhood-scale regions had significant spatial-temporal heterogeneity. The concentrations of TRPMs and CO2 were significantly higher in the morning peak than in the evening peak. BC and CO2 hotspots mostly appeared on arterial roads, while PM10 and PM2.5 exhibited considerably greater spatial variability and more widely dispersed hotspots. The prediction models demonstrated that the RF-LUR model outperforms the LUR model in all evaluation indicators. Specifically, the RF-LUR model displays a higher degree of explanatory power, as evidenced by R2 values of 0.784, 0.871, 0.533, and 0.551 for PM10, PM2.5, BC, and CO2, respectively. Further analysis of the contributions of various factors showed that the concentrations of PM10 and PM2.5, which reflect the background concentrations, were the main influencing factors, with explanatory powers of 57.72% and 78.27%, respectively. Additionally, meteorological factors explained TRPMs and CO2 to a greater extent than did different land use types. Our results showed that RF-LUR can be effectively applied to the prediction of neighborhood scale traffic pollutants.

Functional diversity and spatial association analyses at different spatial scales reveal no changes in community assembly processes along an aridity gradient in the Atacama Desert

The structuring of plant assemblages along environmental gradients is typically explained by shifts from competition (limiting similarity) to environmental filtering as the environment becomes more stressful. However, facilitation, weaker-competitor exclusion, environmental heterogeneity, and the colonization-competition tradeoff can also structure plant assemblages along gradients. These assembly processes act on different plant traits and organs, and their prevalence varies with respect to the spatial scale. Using patterns of functional diversity, coupled with patterns of species association at two spatial scales, here we discern the assembly processes that structure shrub communities in four localities along an aridity gradient of the Atacama Desert. At each site, we calculated functional dispersion indexes for above- and below-ground traits, and patterns of species association at a patch and neighborhood scale. Our results revealed that at the patch scale in intermediate levels of aridity, the dominant assembly process was within-site environmental heterogeneity. At the neighborhood scale, communities are assembled mainly through random processes. Nonetheless, in some communities, the dominant assembly process was competition via limiting similarity or exclusion of the weaker competitor, and these did not change along the gradient. Together, these results reveal that environmental heterogeneity and competition are the main drivers of plant community assembly in a hyper-arid environment.

A global-scale review of smart city practice and research focusing on residential neighbourhoods

Smart cities have emerged as a pivotal aspect of urban planning and policy, leveraging technology and data analytics to enhance sustainability and citizens' quality of life. Nonetheless, the focus on residential neighbourhoods, integral components of cities, has been notably lacking in the sphere of smart city planning and policy. This paper endeavours to assess the evolution of smart cities in relation to neighbourhoods, elucidating dimensions and sectors while concentrating on comprehending project applications and their outcomes. This study employs a systematic literature review to ascertain the role of neighbourhoods within smart cities. Using content analysis, this methodology facilitates the accumulation of insights into smart city research and practice at the neighbourhood level. The paper empirically addresses these findings, identifying dimensions and pertinent sectors concerning residential neighbourhoods.Furthermore, it delves into projects and applications, elaborating on their implementation across diverse sectors. The analysis discerns gaps in technology-driven development planning for varying neighbourhood types within smart cities. Introducing technology-driven advancements into existing urban settings presents substantial challenges, particularly for developing nations, primarily due to limitations and constraints imposed by their current built environments. The study further underscores the perils tied to implementing city-level policies at the neighbourhood scale, prompting a query about their inclusivity. The findings imply the imperative of integrating physical planning and technology-driven solutions within smart city development, with a keen focus on neighbourhoods' social and physical characteristics. This approach becomes particularly significant when considering the inherent risks and constraints that accompany technology-based urban enhancements in the context of neighbourhoods.

Associations of built environment characteristic using NEWS questionnaires with major cardiovascular diseases and all-cause mortality

Abstract Background The WHO of 2016 reports that cardiovascular diseases (CVDs) represent the leading cause of death in most countries and China has one of the highest prevalence of CVDs[1-2]. In order to reduce the burden of CVD risk factors, environmental interventions have become increasingly recognized as necessary approaches to health promotion and diseases prevention[3]. Pervious evidence mainly from the western countries, examined the effects of built environment on health (i.e. physical activity, mental health, self-reported health scale and CVD risk factors) , while the potential impact on CVDs has not been fully explored[4]. Thus, the aim of this study is to evaluate the longitudinal relationships between perceived built environment attributes using neighborhood environment walkability scale (NEWS) questionnaire and the CVDs in Chinese adults, to explore the different between urban and rural areas, and to provide a logical foundation for both research and policy making. Methods PURE-China is a prospective cohort study, recruiting participants aged 35–70 years from 115 urban and rural communities in 12 provinces of China between 2005 and 2009[5]. Baseline including NEWS information was collected using standardized questionnaires. Participants without any NEWS data and with baseline CVDs were excluded. The primary outcome is the composite of major CVD events and all-cause mortality. The main exposure variables including land use mix-diversity, land use-access, streets connectivity, infrastructure for walking and cycling, aesthetics, safety from traffic, safety from crime, and community satisfaction. Cox frailty model with random intercepts to account for cluster were used to assess the association between total built environment score/ subscales score and the time to occurrence of events. Based and fully-adjusted model were estimated and presented as HR and 95%CI. Interactions and stratified subgroup analysis were also tested. Results A total of 32,534 PURE participants were included with averaged 51 years old and 59.9% females. During a median follow-up period of 11.7 years (IQR 9.4 – 12.2), we documented 3298 (10.2%) new CVD events and 1639 (5.1%) all cause deaths. Table 1 summarizes based models and adjusted models results. For composite outcomes, higher level of land use access (HR, 1.06; 95%CI, 1.01-1.11), aesthetics (HR, 1.07; 95%CI, 1.02-1.12), safety from crime (HR, 1.06; 95%CI, 1.01-1.10), community satisfaction (HR, 1.04; 95%CI, 1.00-1.09), combined BE metrics (HR, 1.05; 95%CI, 1.01-1.10) were associated with a lower risk of composite outcome in adjusted model. For major CVD events more statistically significant differences were observed. Conclusions and Relevance High level of specific BE characteristics were associated with lower risk of all-cause mortality and CVD in China. Our findings may guide policy makers on how to implement BE measures to easing the burden of CVDs and premature deaths.Table 1

Analyzing the scale dependent effect of urban building morphology on land surface temperature using random forest algorithm

With continuous urban densification, revealing impacts of urban structures on thermal environment is necessary for climate adaptive design. In this study, random forest and partial difference plots were employed to depict the relative importance and interdependent effects of complex building morphology to land surface temperature (LST) variability. The six spatial factors of building density (BD), mean building height (MBH), building height difference (BHD), floor area ratio (FAR), building volume density (BVD) and mean compactness factor (MCF) were calculated at grids of 90, 300, 600 and 900 m. The results showed that BD, MCF and MBH exerted stable and significant impacts on LST with the highest prediction accuracy at 600 m neighborhood scale, and FAR and BVD were the least correlated to LST changes. Meanwhile, the influencing factors presented different correlation patterns with LST. Among them, the increase of BD had a positive linear effect on LST. MCF and MBH were nonlinearly correlated with the LST variation, and their threshold values of cooling effect were also identified. In addition to controlling BD, it also suggested that comprehensively arranging more small-volume buildings as well as increasing building height to enlarge shadow coverage were more conducive to ground heat mitigation.

Solar neighborhoods: the impact of urban layout on a large-scale solar strategies application

The article addresses the challenges of evaluating energy performance in different neighborhood settings under various energy efficiency measures and proposes a methodology for selecting appropriate solar strategies on a neighborhood scale. The study selects five representative neighborhoods from various climatic zones with different building and street layouts. The proposed methodology involves a systematic three-step multi-domain workflow for implementing energy efficiency measures and solar strategies in the existing neighborhoods. The first step involves typical energy performance simulation, the second step involves energy simulation using high performance building envelope, and the third step involves the addition of solar strategies in combination with retrofitting materials to achieve net-zero status. The results of the study show that modifying the building envelope leads to a significant reduction in energy consumption, with up to 60% reduction observed. The study also finds that the optimal mix of solar strategies depends strongly on the type of neighborhood, its street layouts, and the type of buildings. The article highlights the importance of considering these factors when implementing solar strategies on a neighborhood scale to achieve energy efficiency and net-zero status. It provides urban planners with a systematic decision-making approach to evaluate and optimize neighborhoods to achieve net-zero energy status.

Optihood – a multi-objective analysis and optimization framework for building energy systems at neighborhood scale

Strategic planning of future energy systems in a district is essential to fully exploit the benefits from sector coupling. In particular, new solutions may arise when a group of buildings is considered rather than individual buildings. Therefore, in order to identify optimal production and storage technologies within a district, new tools are needed. In this paper we present the open-source software framework optihood, which allows for multi-objective optimization and analysis of energy systems for neighborhoods. The tool assists researchers and, in a future stage, energy planners in the design of energy systems as well as in optimizing their operation strategy. After introducing the tool, its applicability is demonstrated with a case study, wherein we investigated the supply of a small neighborhood of four residential buildings with space heat, domestic hot water and electricity demands. The optimizer was allowed to consider heat pumps (geothermal/air-source), PV, batteries and hot water storage tanks as available technologies. We show comparisons between optimal solutions in terms of total annualized cost for the buildings considered (a) together as a group and (b) individually.

Smart meter-based archetypes for socioeconomically sensitive urban building energy modeling

Urban building energy modeling (UBEM) and its associated tools have proliferated in recent years, leading to various model development, simulation, calibration approaches, and use cases. UBEM is becoming a valid policy support tool to guide planning and intervention efforts at the neighborhood and city scale. However, current UBEM workflows focus primarily on the physical properties of buildings and geospatial geometry data without consideration for socioeconomic factors or demographic characteristics of the modeled/studied areas. This limitation impedes UBEM's effectiveness as a policy support tool. This paper presents a novel method – using a combination of supervised and unsupervised learning techniques on smart meter and census data – to develop hourly usage schedules for different socioeconomic personas. The schedules can be used to refine building archetypes for UBEMs. The method is piloted in two cities with similar building stocks but different socioeconomic compositions. It was found that socioeconomic indicators are important in classifying building archetypes. Considering these indicators changes the predicted city-wide energy use for residential buildings by up to 10%. The method presented is scalable and applicable to cities and municipalities worldwide (large or small) and elucidates the importance of accounting for demographic and socioeconomic indicators to reflect lived realities accurately.

Economic and environmental benefits of decentralized multi-energy systems for energy communities

In the context of growing interest in decentralised multi energy systems, this work aims at quantifying the benefit of optimized energy concepts for energy communities at the neighbourhood scale compared to individually optimized solution. To tackle this question a multi-objective optimization framework was developed and applied to a case study of 6 buildings consisting of 85% of residential dwellings and 15% to retail shop and food stores. Grouped buildings have decreased costs and greenhouse gases emissions (GHGE) respectively by 18% and 12% in the cost optimum compared to individual buildings. In the environmental optimum, costs have decreased by 11%, while GHGE remains in the same range. This decrease is at both optimum driven by electricity prices favourable to large consumers since exchanges on the electrical microgrid for this neighbourhood is very small. Optimal decrease of GHGE is obtained with greater use of HPs and smaller natural gas consumption. This work illustrates the interest of multi-objective approaches to identify optimal energy solutions for groups of buildings.

Syn(En)ergies in neighbourhood regeneration. Al Safarat experimental laboratory in transition

Integrating the energy issue in the regeneration of neighbourhoods influences the entire metabolism of the urban settlement. It opens up a reflection, within the disciplines of the project, on approaches, methods, and tools to make the energy transition operational in space. The complexity of the energy transition requires a holistic, multidisciplinary and integrated approach to design, capable of addressing energy transition processes at the neighbourhood scale. By adopting a method that interprets the landscape as a complex techno-natural infrastructure, the Al Safarat neighbourhood in Riyadh will be considered a possible experimental laboratory for the energy transition of the districts of the Gulf cities.

MEASURING AIR QUALITY IMPACTS OF GREEN AREAS AND ECOSYSTEM SERVICES (ESS) USING WEB-BASED I-TREE CANOPY TOOL: A CASE STUDY IN ISTANBUL

In this study, it was aimed to evaluate the regulating ecosystem services for improving the air quality provided in the Kuzguncuk Neighborhood, which is located within the borders of Üsküdar district of Istanbul province. In this context, 5500 random points were identified within the boundaries of the research area by using the i-Tree canopy tool, which is a web-based tool. The land cover represented by each point is grouped into five classes: i) Tree/Shrub (tree and tall shrub vegetations), ii) Grass/herbaceous (areas covered with herbaceous vegetation, iii) Soil/Bare Ground (soil surface with little or no vegetation), iv) Impervious Surfaces (building, structures, asphalt, impervious roads, etc.) and v) Water (areas with streams or stagnant water). According to these classifications, the annual amount of carbon sequestered by the tree-shrub canopy in the Kuzguncuk neighborhood, the amount of CO₂, the amount of carbon they stored over their lifetimes, the amount of CO₂, and their economic contribution have been calculated. Additionally, the amount of significant air pollutants removed by this canopy, such as carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2), and particulate matter PM2.5 and PM10, and the economic benefits of removing these pollutants have been determined. The results showed that trees sequestered 855.93 tons of CO2 annually and stored 21,495.71 tons of CO2 in the neighborhood, 46.05% of which is covered with canopy. However, it was calculated that 69.94 kg of CO, 381.39 kg of NO2, 3,798.45 kg of O3, 240.34 kg of SO2, 184.57 kg of PM2.5 and 1,272.34 kg of PM10 particulate matter were removed from the atmosphere in a year by the vegetation cover. It has been calculated that the economic contribution provided by this removal is $ 2,251 per year. This study reveals the ecological and economic importance of green spaces for ecosystem services studies in urban areas by considering a neighborhood scale in determining the ecosystem services provided by the canopy cover. It is thought that the numerical values obtained in this sample region will contribute to urban planning strategies in terms of green infrastructures for future studies.

The Michigan–Ontario Ozone Source Experiment (MOOSE): An Overview

The Michigan–Ontario Ozone Source Experiment (MOOSE) is an international air quality field study that took place at the US–Canada Border region in the ozone seasons of 2021 and 2022. MOOSE addressed binational air quality issues stemming from lake breeze phenomena and transboundary transport, as well as local emissions in southeast Michigan and southern Ontario. State-of-the-art scientific techniques applied during MOOSE included the use of multiple advanced mobile laboratories equipped with real-time instrumentation; high-resolution meteorological and air quality models at regional, urban, and neighborhood scales; daily real-time meteorological and air quality forecasts; ground-based and airborne remote sensing; instrumented Unmanned Aerial Vehicles (UAVs); isotopic measurements of reactive nitrogen species; chemical fingerprinting; and fine-scale inverse modeling of emission sources. Major results include characterization of southeast Michigan as VOC-limited for local ozone formation; discovery of significant and unaccounted formaldehyde emissions from industrial sources; quantification of methane emissions from landfills and leaking natural gas pipelines; evaluation of solvent emission impacts on local and regional ozone; characterization of the sources of reactive nitrogen and PM2.5; and improvements to modeling practices for meteorological, receptor, and chemical transport models.

Modelling Four Neighbourhood-Scale Urban Forest Scenarios for 2050: Vancouver, Canada

Abstract Background Urban forests are increasingly recognized as important tools in climate change mitigation and adaptation, prompting many cities to set tree canopy cover targets. However, current gaps in knowledge include understanding relationships and the feasibility of maximizing benefits between urban greening and other climate actions, such as densification. This study offers a data-driven and manageable framework for assessing current and anticipated future urban forestry conditions using spatial tree and built-form models. Methods We spatially modelled 4 planting scenarios for increasing tree canopy cover by 2050 in a densifying neighbourhood in Vancouver, Canada, with low (< 10%) existing tree canopy. Results Based on mortality assumptions, we aged out and replaced 1,853 to 2,445 trees since 2020. We added 6,079 to 11,726 trees across the 4 scenarios (10,228 to 15,823 total), increasing canopy cover from 7% in 2020 to a maximum of 16% by 2050. Despite rigorous tree planting, we were unable to achieve a 30% canopy cover target at neighbourhood scale. Tree replacement due to mortality was a major contributor to decreased canopy cover and volume in future scenarios. The 31% to 34% reduction in future canopy cover due to the replacement of aged-out trees was driven by changes on private parcels. Conclusion Our systematic framework for generating and spatially modelling trees in a simulated future neighbourhood provides an opportunity for iteratively assessing multiple potential tree planting configurations. Future work for this project includes investigating social-ecological, outdoor shading, and building energy implications of various modelled urban forest strategies.

Site selection modeling of hybrid renewable energy facilities using suitability index in spatial planning

The research focuses on how hybrid renewable energy facilities can be addressed within the spatial planning system by adopting an approach that minimizes the problems related to the sustainability of energy. The study aims to develop a spatial model based on parameters for the site selection processes of hybrid renewable energy facilities relying on wind, solar, and biomass energy sources within the spatial planning system in Turkey. The integration of fuzzy logic approach and Geographic Information Systems (GIS) tools has been proposed to establish a spatially applicable methodological framework. The methodology focuses on the neighborhood scale in terms of planning level and covers the Karatay district, where the hybrid renewable energy potential is high. The research findings indicate that the GAMMA operator used in the methodology provides the most optimal areas with a value of γ = 0.90 and generates site selections for hybrid renewable energy facilities based on the source with the highest suitability index in single-source utilization. Additionally, the operator determines the best alternative in terms of resources in different hybrid scenarios. In this context conducted in Karatay district, it was found that the highest suitability index in terms of hybrid applications is associated with biomass-solar energy combinations.

Influences of occupant preferences for living environments on household energy consumption: A case study of Indonesia

Generally, economic factors, demographic factors and home appliances are several known factors that directly influence the level of household energy consumption (HEC). But still, individual differences often remain among the households. This study aims to explore indirect factors affecting HEC in Indonesia, focusing especially on occupant preferences for their living environments. A nationwide online survey (n = 1629) was conducted between July and August 2021 to depict the preferences using the Evaluation Grid Method (EGM) at various scales, including behavioral, interior, building and neighborhood scales. A new EGM approach incorporating text mining methods was developed and demonstrated, which was able to draw the comprehensive overviews of the complex relationships between occupant psychology and the surrounding environment. In the survey, 400 respondents were randomly chosen for each of the four scales and 29 respondents participated in the following online interviews for all scales. The results of EGM were analyzed among different levels of HEC to find the specific psychological factors affecting their HEC levels. The extracted major Original Evaluation Items (OEIs) include “healthy lifestyle” in behavior (10.0 %), “wide place” in interior (3.6 %), “comfortable building” in building (6.4 %) and “cool air” in neighborhood (5.3 %), respectively. The axis of sociability-introvert was found to be a key factor affecting their HEC. Other key factors include the design preferences and leisure preferences. As such, the results revealed several differences in preferences and sense of values among respondents with various levels of HEC. These findings would help find a way to balance between economic growth and energy-saving objectives in the fast-developing countries such as Indonesia.

In light of transit: Documenting the scales of urban change along the LRT line in Hamilton, Ontario

AbstractLarge‐scale transit projects, such as light rail, are transformational for cities due to their ability to attract investment, curb sprawl, and intensify urban areas. In part because of enhancements to the public realm and improved connectivity, areas along new transit lines witness significant growth and investment, making them less affordable for residents already there. However, very little research has examined experiences of transit‐induced gentrification, particularly at the early stages of a new transit project. The purpose of this article is to document these experiences from the perspective of those living along the planned LRT corridor in Hamilton, Ontario. Importantly, our research was conducted before construction started. Through in‐depth interviews with residents living within 800 m of the planned LRT route, we found disparate experiences of change and ongoing housing affordability concerns on an individual, neighbourhood, and city scale. Many Hamilton residents express a need for more community engagement and transparency in the decision‐making process. We detail these experiences and offer policy recommendations to inhibit further housing insecurity and displacement in light of the LRT development.

Urban classification of the built-up and seasonal variations in vegetation: A framework integrating multisource datasets

The growing emphasis on integrating natural elements into urban environments to counteract adverse impacts has increased research into the role of vegetation within cities. Nonetheless, the inclusion of vegetation in urban classifications remains limited due to the associated challenges, such as time and cost constraints related to its measurement. This study introduces a classification framework that integrates spatio-temporal vegetation characteristics and built-up density variables at the neighbourhood scale using open-access datasets and remote sensing for data retrieval. Through a combination of statistical and spatial autocorrelation analyses and the application of two distinct classification methods to the 15 assessed variables, we identified four primary urban clusters. These clusters are further refined considering vegetation categories, which encompass general vegetation cover, vegetation cover levels, and vegetation cover changes tracked across two different seasons, corresponding to winter and summer. This comprehensive classification not only characterizes the built-up elements but also elucidates the distribution of vegetation showing the nuances in vegetation within similar urban clusters. The resulting classifications aim to bridge the existing gap in urban studies by incorporating the spatio-temporal scale and cover changes of vegetation. This framework serves as a precedent for creating context-specific classifications, which can be subsequently used for conducting further assessments on various urban issues. The outcomes of this study offer an overview of a study area, encompassing urban density and seasonal variations in vegetation. This information facilitates the identification of specific areas where additional attention may be warranted, particularly concerning the provision of ecosystem services and the development of strategies to enhance urban microclimates and thermal comfort, among other aspects.

Identifying spatial heterogeneity of COVID-19 transmission clusters and their built-environment features at the neighbourhood scale

The identification of high-risk areas for infectious disease transmission and its built-environment features are crucial for targeted surveillance and early prevention efforts. While previous research has explored the association between infectious disease incidence and urban built environment, the investigation of spatial heterogeneity of built-environment features in high-risk areas has been insufficient. This paper aims to address this gap by analysing the spatial heterogeneity of COVID-19 clusters in Shanghai at the neighbourhood scale and examining associated built-environment features. Using a spatiotemporal clustering algorithm, the study analysed 1395 reported cases in Shanghai from March 6 to March 17, 2022. Both global Poisson regression (GPR) and geographically weighted Poisson regression (GWPR) models were applied to examine the association between built-environment variables and the size of COVID-19 clusters. Our findings suggest that larger COVID-19 clusters emerging in the suburbs compared with the downtown and multiple built-environment features are significantly associated with this pattern. Specifically, neighbourhoods with a higher proportion of commercial, public service and industrial land, higher centrality of metro stations, and proximity to hospitals are positively associated with larger COVID-19 clusters, while neighbourhoods with higher land use mix and green/open spaces density are associated with smaller COVID-19 clusters. Moreover, we identified that metro stations with high centrality present the highest risk in the downtown, while commercial and public service places exhibit the highest risk in the suburbs. By highlighting the overlooked spatial heterogeneity of built-environment features for high-risk areas, this study aims to provide valuable guidance for public health departments in implementing place-based interventions to effectively prevent the spread of potential epidemics.

Sociodemographic analysis of unbraced unbolted cripple wall retrofits in the City of Los Angeles

Disparities in seismic risk mitigation programs can lead to uneven impacts during an earthquake and an increased burden on socially vulnerable and underserved communities. This article examines the extent to which the distribution of cripple wall retrofits in residential buildings (primarily one- and two-family units) located within the City of Los Angeles (LA), varies based on the sociodemographics of the affected populations. Utilizing multiple data sources including the LA Department of Building and Safety (LADBS) and LA Open Data Portal (LAOPD), a combination of spatial and statistical approaches are implemented at the regional, neighborhood, and census-tract scales. At each scale, the number of retrofitted buildings normalized by the total number of pre-1980 one- and two-family residential buildings (or retrofit rate) is the primary dependent variable. The effect of the Earthquake Brace and Bolt (EBB) program on the disparities in the retrofit rate distribution is also assessed. Despite having relatively older one- and two-family residential buildings, those neighborhoods with the highest representation of Black and Hispanic households are generally associated with lower retrofit rates. We also found that the neighborhoods with the lowest median income have retrofit rates that are less than the average for the entire City of LA. The rate among Black, Hispanic, and low-income households was found to increase significantly after the EBB program was instituted in 2013, suggesting that the initiative may have served as a mechanism to reduce the demographic and economic disparities in the cripple wall retrofits. However, to date, the average retrofit rate in the ten neighborhoods with the highest representation of Hispanic households is roughly one-third that of the rest of LA City.

Consumption and production of edible insects in an urban circularity context: Opinions and intentions of urban residents

The success of emerging urban agriculture initiatives is partly determined by the acceptance and active involvement of residents. Edible insects can contribute to urban agriculture and to the transition to a circular economy by converting organic side flows into high-value biomass. This explorative online survey (N = 750) assessed the opinions and intentions of residents of Amsterdam city, the Netherlands (18–75 years old) about consumption and production of edible insects for food on household, neighborhood (i.e., centralized facilities for neighbored households), and industrial scales utilizing various side flows. Of the proposed scenarios, industrial insect production was perceived as more attractive (24.9 % of all respondents), than neighborhood (16.3 %) and household (6.7 %) production. Respondents indicated a higher preference for drivers (environmental, economic, expert support, and safety) related to purchasing industrially produced insects (median-5 of 7-point scale) than to participating in neighborhood or household production. Accordingly, most barriers were associated with household production (e.g., inconvenience, economic reasons, lack of knowledge and available information, median-5-6) rather than neighborhood (safety concerns, median-5) and industrial (no defined barriers, median 4) production. Nature (vegetal, animal, or mixed) and source of insect feed were considered important to the respondents, and >80 % of the respondents prefer feed mentioning on the labels of insect-containing food products. The findings suggest that urban initiatives on insect production should consider the current state of acceptance of this idea and the willingness to participate in it, as well as ensure its simplicity, safety, and low monetary cost. Relevant information and expert support should be made available to residents. Moreover, as edible insects are still a novel food concept in Amsterdam, further introduction of insects into the diet might make all proposed scenarios more attractive and meaningful for residents, contributing to the development of circular urban ecosystems in the future.