High-density Cities Research Articles

Comprehensive walkability assessment of urban pedestrian environments using big data and deep learning techniques.

Assessing street walkability is a critical agenda in urban planning and multidisciplinary research, as it facilitates public health, community cohesion, and urban sustainability. Existing evaluation systems primarily focus on objective measurements, often neglecting subjective assessments and the diverse walking needs influenced by different urban spatial elements. This study addresses these gaps by constructing a comprehensive evaluation framework that integrates both subjective and objective dimensions, combining three neighbourhood indicators: Macro-Scale Index, Micro-Scale Index, and Street Walking Preferences Index. A normalization weighting method synthesizes these indicators into a comprehensive index. We applied this framework to assess the street environment within Beijing's Fifth Ring Road. The empirical results demonstrate that: (1) The framework reliably reflects the distribution of walkability. (2) The three indicators show both similarities and differences, underscoring the need to consider the distinct roles of community and street-level elements and the interaction between subjective and objective dimensions. (3) In high-density cities with ring-road development patterns, the Macro-Scale Index closely aligns with the Comprehensive Index, demonstrating its accuracy in reflecting walkability. The proposed framework and findings offer new insights for street walkability research and theoretical support for developing more inclusive, sustainable and walkable cities.

Challenges and Potentials: Environmental Assessment of Particulate Matter in Spaces Under Highway Viaducts

Under-viaduct space (UVS) is becoming an important solution to urban mobility problems, and the construction and use of high-density city center highways and elevated bridges are increasing, which has a negative impact on the UVS. Air pollution is a problem in these spaces, but research on air pollution in UVSs is lacking. To further study air pollution in UVS, this study selected a case area of a UVS in central Shanghai and investigated the spatiotemporal distribution patterns of air pollution and the influencing factors. We found that air pollution in the UVS is significantly higher than the background levels, and the higher the background levels, the greater the difference between the pollution of the UVS and the background. In terms of the impact factor, air pollution is highly correlated with the built environment and traffic flow. The research provides evidence of the exposure to air pollution in under viaducts spaces in the microenvironment.

Rethinking residential building design in high-density cities for enhancing pandemic resilience: Balancing importance and practicality

The relationship between the built environment and epidemic transmission is particularly pronounced within the context of lockdown policies and high-density urban areas. Non-pharmaceutical interventions have become increasingly important during and after the COVID-19 pandemic. This study proposes an evaluation index system for pandemic-resilient residential building designs in high-density cities, covering the entire design process including site planning, architecture design, building equipment and management. The system includes 64 design strategies, categorized into 15 sub-categories and 4 categories. Then, we evaluate the preference of each strategy by synthesizing the dimensions of importance and implementation difficulty. A questionnaire survey was conducted among experts who have experience with pandemic-resilient designs in high-density cities. Fuzzy synthetic evaluation analysis was implemented along with the “preference index” concept to identify the most important and practical interventions during the pandemic outbreak. The results indicate that “service and management” is the category that requires priority, followed by “property management,” “common areas” and “building morphology” in sub-categories. Among the design strategies, “waste receptacle,” “publicity and education,” “floor drain and water seal” and “environmental cleaning and disinfection” are the top four recommended strategies. This study provides policymakers and practitioners with effective and easily implementable prevention measures during an outbreak of respiratory tract infections. It also offers specific policy recommendations and application suggestions for new and existing buildings, contributing to creating a safer and healthier living environment

Sustainability Performance Differences of Industrial Heritage Regeneration Implementation Modes

In high-density cities around the world, the contradiction of sustaining development and limited resources has become more evident. Transforming historic industrial buildings, through both functional and spatial adjustments, has emerged as a key strategy to manage these challenges effectively. There is a significant demand for the quick regeneration of industrial heritage districts, resulting in the emergence of various implementation modes (IMs). While the Sustainable Development Goals (SDGs) have gained widespread acceptance, the integration of sustainability principles into urban regeneration practices has strengthened globally. However, in many regions, approaches to achieving sustainable regeneration are still unclear, with a lack of evaluation and adjustment of sustainability performance (SP). This paper combines qualitative analysis and a quantitative assessment of indicators to compare three representative case studies with different IMs. It explores whether there is a connection between the chosen IM and SP, examines the mechanisms of impact, and discusses how to select the most suitable IM for industrial heritage regeneration. The study confirms the practicality of an SP evaluation system and identifies key factors within IMs that affect SP. Future research is expected to produce tools that support the promotion of sustainability in industrial heritage regeneration efforts.

Is LCZ Enough? Physical Properties, Thermal Environments and Cooling Effects of Green Roofs in High-Density Urban Industrial Blocks

With rapid worldwide urbanization, the urban heat island (UHI) effect is becoming more and more serious. The UHI effect is more intense in industrial areas. Green roofs are an effective way to mitigate UHIs in high-density cities, which calls for thorough examination. This study explored the associations between the block characteristics and block thermal environment in high-density industrial areas based on the widely accepted Local Climate Zone (LCZ) scheme. The pedestrian air temperature comparisons before and after virtual green roof installations presented the cooling effects of green roofs. Thirty-six typical industrial blocks were involved in the study and the simulations were conducted utilizing ENVI-met. The results showed that (1) the air temperature in LCZ4 is significantly lower than those in LCZ2 and LCZ6, but no significant differences were identified between other pairs of LCZ types; (2) the cooling effect of green roofs significantly differs among LCZs, and is associated with sky view factor (SVF), average building area (ABA) and average building shape index (ABSI); (3) in high-density urban areas, additional functional parameters and building-volume indices should be included to better address the physical characteristics, thermal environment, and green roof cooling effect of industrial blocks. This study could improve the validity of LCZ classification for high-density industrial blocks and may provide direct implications for green roof planning.

The Building Decarbonization in High-Density Cities: Challenges and Solutions

Abstract Decarbonization of buildings is an imperative and challenging task. Beyond the common challenges associated with building decarbonization, those in high-density urban areas also face technical challenges due to geographical conditions and resource endowments. As decarbonization practices deepen, it has been found that reliance on conventional methods is fraught with difficulties, primarily due to the high proportion of incremental costs involved. This review study explores methods not widely incorporated into existing building energy efficiency standards but which hold the potential for aiding decarbonization. It advocates for a synergistic strategy involving surrounding infrastructure such as power and other building energy systems, innovative low-carbon building materials, and greenery to facilitate this transition.

Health effects of greenspace morphology: Large, irregular-shaped, well-connected, and close-clustered greenspaces may reduce mortality risks, especially for neighborhoods with higher aging levels

The healthcare burden has intensified with urbanization and aging populations in many global cities. While the health effects of urban greenspaces have been well documented, little is known about the associations between greenspace morphological features and health, especially in a high-density city with significant aging populations. Drawing on land use data with 10-m resolution, we assessed seven greenspace morphological metrics in terms of size (the percentage of greenspace, the largest pixel index, the average greenspace area), fragmentation (the patch density), shape (the average weighted shape index), connectedness (the cohesion index), and proximity (the aggregation index). We further conducted an ecological study to examine their associations with all-cause and three cause-specific (cardiovascular disease, respiratory disease, and cancer) mortality. Results from the negative binomial regression models revealed protective effects of five greenspace morphology metrics, including the percentage of greenspace, the largest pixel index, the average weighted shape index, the cohesion index, and the aggregation index, on mortality. The shape index showed the greatest effects, with every 1 Standard Deviation (SD) increase in the shape index linked to a reduction of 22.1% (95% CI: 22.0%–31.0%) in all-cause mortality, 22.1% (12.2%–30.8%) in mortality from cardiovascular diseases, 25.0% (14.0%–34.6%) in mortality from respiratory diseases, and 22.0% (12.3%–30.6%) in mortality from cancers. Moreover, stratified analyses revealed that the health effects of the cohesion index and the aggregation index were significantly more pronounced in neighborhoods with higher aging levels. Our findings highlight the significance of greenspace morphology features, beyond greenspace quantity, in improving residents’ health, particularly for societies with high aging populations.

Designing breezeways to enhance wind environments in high-density cities: A comprehensive analysis of ten morphological parameters

To advance urban breezeway designs, this paper presents a pioneering and comprehensive study of breezeway morphological parameters. Ten parameters, selected through extensive literature review, include coverage ratio, porosity, line density, sinuosity, rotation angle, width, length, average height, height variation, and aspect ratio. Regression analysis, utilizing over 200 data points collected from wind tunnel experiments in Hong Kong, established correlations between these parameters and pedestrian-level wind velocity ratio (VRpoint). Results reveal that among the 2D parameters, width, length, line density, and coverage ratio exhibit the strongest correlations with VRpoint, while aspect ratio and porosity emerge as significant factors among the 3D parameters. Notably, simple 2D parameters, coverage ratio and width, effectively substitute for their 3D counterparts, porosity and aspect ratio, in high-density urban areas. Furthermore, the results highlight the parameters’ relative contributions to urban ventilation. From a street-level perspective, VRpoint is primarily influenced by configurations of street segments (width, 80%) and street intersections (rotation angle, 20%). From a neighborhood-level perspective, permeability (coverage ratio, 35%), fragmentation (line density, 30%), and roughness (average height, 35%) are critical factors. Illustrative examples are provided to facilitate the translation of findings into spatial analysis tools and design guidelines to assist planners and decision-makers in sustainable developments.

Supporting Aging-in-Place: Drivers and Desired Outcomes of a Healing Environment for Older Adults in Block Spaces of High-Density Cities.

Aim: The objective of this study was to develop a comprehensive multidimensional framework by identifying the key drivers and components associated with the health of older people in healing environments, and to apply this framework in high-density city block spaces, creating opportunities for aging in place. Background: Effective theoretical and practical research frameworks are necessary to determine how to best support older adults in high-density city areas as they face aging-related challenges. Methods: The methodological approach involved bibliometric analysis (SciMAT) and systematic literature review of approximately 4446 articles related to rehabilitation settings and older adults. The review focused on literature that developed concepts and research frameworks and provided an empirical foundation. Results: The review identified four types of drivers for a healing environment for older individuals in high-density city blocks (HEOI-HCBs): self-environment, interpersonal, physical, and informational environments. These drivers were linked to eight desirable outcomes: initiative acquisition, shared vision, trust, empathy, integrity, systematicity, networking, and perceived usefulness. Conclusion: The drivers and outcomes formed the HEOI-HCBs framework, each representing a distinct dimension of the HEOI-HCBs concept. This study and the resulting framework facilitate the application and understanding of healing environments.

Associations between neighborhood compactness, perceived accessibility to urban amenities, and mental distress of older adults in a high-density city

Neighborhood compactness has been identified as a sustainable approach for fostering social relationships. However, existing studies have not clearly demonstrated whether neighborhood compactness in high-density cities directly influences the mental distress of community-dwelling older adults, or whether it indirectly influences mental distress through perceived accessibility to urban amenities (PA). Using a composite score of three dimensions (depressive symptoms, loneliness, and social isolation) to measure mental distress, and applying a mediation model within a cross-sectional design involving 947 older adults (aged ≥ 60) with at least mild symptoms in Hong Kong, our findings suggest an indirect pathway between neighborhood compactness, PA, and mental distress. Neighborhood compactness was positively associated with PA (B = 7.791, p < 0.001), and PA was negatively associated with mental distress (B = −0.12, p = 0.017). However, no direct impact of neighborhood compactness on mental distress was found. Moderated mediation analysis further indicated that neighborhood compactness and PA supported older females but not males. These results align with our hypothesis that (1) neighborhood compactness may not always be beneficial for older adults with mental distress in high-density cities unless compactness itself enhances PA and facility usage to support community-dwelling individuals, and (2) gender differences may result in varying interactions and perceptions of urban amenities and the built environment. To support the concept of “aging in place” in the future, urban plans aimed at enhancing neighborhood compactness and its social impacts should focus on addressing social inequality, including strategies to improve urban design, social participation, and gender-specific protocols, so that older adults can achieve better community awareness, environmental satisfaction, and facility usage, ultimately reducing mental distress.

Effects of building configuration and upstream buildings on pedestrian risk around ideal buildings in a floodwater–wind joint environment

Urban building affects both floodwater inundation and air flow in high-density cities, influencing the pedestrian risk within urban blocks. Previous studies have identified physical characteristics of buildings as important factors influencing either floodwater spread or the wind environment. However, the correlation between the building configuration and pedestrian risk under the combined effect of floodwater and wind is not yet fully understood. This study estimates the integrated effects of building configuration and an upstream building on the pedestrian risk around ideal buildings in a joint floodwater–wind environment. Computational fluid dynamics (CFD) simulations are performed to model the inundation depth, floodwater velocity, and wind speed at pedestrian level for single- and double-building models. The pedestrian risk in terms of the toppling instability is evaluated, and a series of laboratory flume experiments on the stability/instability of a dummy representing pedestrians in a quasi-natural state are conducted to validate the CFD simulation results. The findings show that the building configuration affects the pedestrian risk to some degree; however, the building height yields a minor effect and converging and diverging flows lead to different pedestrian risk distributions within the area of interest. Floodwater always plays a dominant role over wind in triggering pedestrian toppling, and pedestrian evacuation speeds vary depending on the circumstances. When an upstream building is added, its distance from the target building, length, and the reduced ratio relative to the reference case, as well as the interspace between its segments, influence the pedestrian risk; however, the height of the upstream building has the smallest effect on the pedestrian risk response. The study outcome can provide insights for administrators and stakeholders when implementing tailored measures against direct impacts of surging floodwater and strong wind in the context of resilient city management.

Sensitivity of Local Climate Zones and Urban Functional Zones to Multi-Scenario Surface Urban Heat Islands

Local climate zones (LCZs) and urban functional zones (UFZs) can intricately depict the multidimensional spatial elements of cities, offering a comprehensive perspective for understanding the surface urban heat island (SUHI) effect. In this study, we retrieved two types of land surface temperature (LST) data and constructed 12 SUHI scenarios over the Guangdong–Hong Kong–Macao Greater Bay Area Central region using six SUHI identification methods. It compared the SUHI sensitivity differences among different types of LCZ and UFZ to analyze the global and local sensitivity differences of influencing factors in the 12 SUHI scenarios by utilizing the spatial gradient boosting trees, geographically weighted regression, and the coefficient of variation model. Results showed the following: (1) The sensitivity of different LCZ and UFZ types to multi-scenario SUHI was significantly affected by differences in SUHI identification methods and non-urban references. (2) In the morning, the shading effect of building clusters reduced the surface urban heat island intensity (SUHII) of some built environment types (such as LCZ 1 (compact high-rise zone) to LCZ 5 (open midrise zone)). The SUHIIs of LCZ E (bare rock or paved zone) and LCZ 10 (industry zone) were 4.22 °C and 3.87 °C, respectively, and both are classified as highly sensitive to SUHI. (3) The sensitivity of SUHI influencing factors exhibited regional variability, with importance differences in the sensitivity of importance for factors such as the impervious surface ratio, elevation, average building height, vegetation coverage, and average building volume between LCZs and UFZs. Amongst the 12 SUHI scenarios, an average of 87.43% and 89.97% of areas in LCZs and UFZs, respectively, were found to have low spatial sensitivity types. Overall, this study helps urban planners and managers gain a more comprehensive understanding of the complexity of the SUHI effect in high-density cities, providing a scientific basis for future urban climate adaptability planning.

Evolvement of Spatio-Temporal Pattern and Driving Forces Analysis of Ancient Trees Based on the Geographically Weighted Regression Model in Guangzhou and Foshan, China

Ancient trees play an important ecosystem service role in high-density cities, revealing the zonal distribution characteristics of vegetation under climate influence. The ancient trees in Guangzhou and Foshan in 2018 and 2023 were taken as study objects to explore the evolution of their spatio-temporal patterns and to analyze the spatial differentiation characteristics of their driving factors using the geographical weighted regression (GWR) model. The results showed the following: (1) The ancient trees in Guangzhou and Foshan were composed of typical subtropical evergreen broad-leaved forest communities, mainly represented by broad-leaved species of evergreen dicotyledonous plants. The dominant species mainly included Litchi chinensis, Ficus microcarpa, Canarium pimela, Ficus virens, and Dimocarpus longan. However, there was a significant difference between Guangzhou and Foshan. (2) The number of ancient trees in Guangzhou showed negative growth, while Foshan saw a significant increase. However, species diversity in both areas increased, with the highest diversity in the northeast, higher diversity in the south-central part, and lower diversity in the western and northwestern parts. (3) The maximum kernel density of ancient trees in Guangzhou and Foshan differed 22-fold, indicating a spatial distribution pattern of multiple clusters. (4) The GWR model effectively explained the driving factors of the heterogeneity of the spatial distribution of ancient trees. The results showed that artificial disturbance was the most important factor affecting the spatial distribution of ancient trees in high-density urban agglomerations in the same vegetation zone. The study clarified the characteristics of the spatial distribution and species diversity of ancient trees in the region, revealed the driving factors for the evolution of the spatial pattern of ancient trees in highly urbanized areas, and provided guidelines for policies and measures for enhancing biodiversity and conserving germplasm resources in the region.

The impact of urban configuration types on urban heat islands, air pollution, CO2 emissions, and mortality in Europe: a data science approach

The world is becoming increasingly urbanised. As cities around the world continue to grow, it is important for urban planners and policy makers to understand how different urban configuration patterns affect the environment and human health. However, previous studies have provided mixed findings. We aimed to identify European urban configuration types, on the basis of the local climate zones categories and street design variables from Open Street Map, and evaluate their association with motorised traffic flows, surface urban heat island (SUHI) intensities, tropospheric NO2, CO2 per person emissions, and age-standardised mortality. We considered 946 European cities from 31 countries for the analysis defined in the 2018 Urban Audit database, of which 919 European cities were analysed. Data were collected at a 250 m × 250 m grid cell resolution. We divided all cities into five concentric rings based on the Burgess concentric urban planning model and calculated the mean values of all variables for each ring. First, to identify distinct urban configuration types, we applied the Uniform Manifold Approximation and Projection for Dimension Reduction method, followed by the k-means clustering algorithm. Next, statistical differences in exposures (including SUHI) and mortality between the resulting urban configuration types were evaluated using a Kruskal-Wallis test followed by a post-hoc Dunn's test. We identified four distinct urban configuration types characterising European cities: compact high density (n=246), open low-rise medium density (n=245), open low-rise low density (n=261), and green low density (n=167). Compact high density cities were a small size, had high population densities, and a low availability of natural areas. In contrast, green low density cities were a large size, had low population densities, and a high availability of natural areas and cycleways. The open low-rise medium and low density cities were a small to medium size with medium to low population densities and low to moderate availability of green areas. Motorised traffic flows and NO2 exposure were significantly higher in compact high density and open low-rise medium density cities when compared with green low density and open low-rise low density cities. Additionally, green low density cities had a significantly lower SUHI effect compared with all other urban configuration types. Per person CO2 emissions were significantly lower in compact high density cities compared with green low density cities. Lastly, green low density cities had significantly lower mortality rates when compared with all other urban configuration types. Our findings indicate that, although the compact city model is more sustainable, European compact cities still face challenges related to poor environmental quality and health. Our results have notable implications for urban and transport planning policies in Europe and contribute to the ongoing discussion on which city models can bring the greatest benefits for the environment, climate, and health. Spanish Ministry of Science and Innovation, State Research Agency, Generalitat de Catalunya, Centro de Investigación Biomédica en red Epidemiología y Salud Pública, and Urban Burden of Disease Estimation for Policy Making as a Horizon Europe project.

Subsidizing residents or companies? An equilibrium-based analysis of subsidy strategies for EV charging facilities

This study examines the charging location choice behavior of residents in relation to employer-provided charging facilities and investigates the impact of different government subsidy strategies for charging facility construction on urban spatial structure and traffic-related air pollution. Using a monocentric two-zone city model, we analyze the residential distribution and travel mode choice of urban residents under various subsidy strategies from the perspective of social planners. The government can optimize urban resource allocation through transport infrastructure investments and implementation of emission taxes to maximize the so-called residents’ utility. We observe that despite the distorting effect of employer-provided charging facilities on travel mode choice, residents still experience an enhanced utility due to the positive environmental impact resulting from reduced pollution levels associated with electric vehicles (EVs) compared to gasoline vehicles (GVs). We provide numerical evidence to show that government subsidies, whether directed towards companies or residents, can effectively enhance the adoption of EVs and improve utility. In low-density cities, it is advisable for the government to encourage and subsidize residents in building charging facilities. Conversely, in high-density cities, prioritizing subsidies for companies would be more beneficial in improving utility and expanding the coverage of charging facilities. Furthermore, in cities where resident environmental awareness is relatively low, it is recommended that the government increase subsidies to promote EV adoption.

Assessing the walkability of high-density neighborhoods: Development and reliability of the high-density environment assessment tool (HEAT)

BackgroundWalking is a widespread and multifaceted activity among residents in high-density cities, making assessing the neighborhood walking environments important. Existing tools for assessing walkability in high-density cities primarily focus on the immediate environment of sidewalks. However, an individual's walking behavior is influenced by environmental characteristics across multiple dimensions and scales. Consequently, based on a systematic analysis of the features of high-density cities, this study proposes the High-density Environment Assessment Tool (HEAT). This hybrid approach comprehensively assesses walkability in high-density cities by incorporating variables of neighborhood, segment (sidewalk), and crossing. MethodsThe HEAT consisted of three sections with 108 items. To validate the reliability and applicability, field tests were conducted in two 15-min walkable neighborhoods with different built environment contexts in Chongqing City, China. The neighborhood section was objectively assessed using ArcGIS Software. The segment section and crossing section were audited through systematic on-site observation. Four pairs of trained raters assessed all of the segments (n = 139) and crossings (n = 123) within the two neighborhoods. The inter-rater reliability of the repeated audit data was evaluated by Kappa/Weighted Kappa or Percentage Agreement values. A web-based application was used for data collection and input. ResultsFor the neighborhood section, 21 assessment items were included. For the segment and crossing sections, 87 assessment items were included for the reliability test, and 84 (96.6%) of the items indicated satisfying inter-rater reliability (with Kappa/Weighted Kappa value ≥ 0.4 or high Percentage Agreement). In addition, the audit of each segment and crossing sample was completed in an average of 7.9 and 1.8 min, respectively. ConclusionsThe results indicated that the HEAT was reliable and efficient. The HEAT provided an effective tool for assessing the walkability of the neighborhood built environment in high-density cities, thereby facilitating environmental interventions aimed at promoting walking activities.

Optimizing community green roof spaces in high-density cities: a K-modes clustering algorithm based analysis of resident preferences and spatial configuration

ABSTRACT Green roofs are an important part of the ecological system in high-density cities and a crucial component of community public green spaces. Analyzing preferences of residents during spatial planning can help improve their satisfaction and efficiency in using community rooftop spaces. This study uses K-modes algorithm to perform cluster analysis on questionnaires from 699 residents, and summarizes user profiles with significant characteristics by combing the comprehensive ratings of residents regarding different roof space functions. The study shows that differences in preferences among people are not only related to demographic characteristics but also to their interests and environmental perceptions. For example, low-to-middle-income groups, being price-sensitive, tend to reduce energy consumption expenditure. The highly educated population, driven by social needs, shows a clear preference for activity spaces and sports facilities. The elderly population, emphasizing healthy eating and rural memories, gives higher ratings to agricultural spaces. Finally, this study explores the correlation between certain resident characteristics and their preferences for green roof space functions, and proposes a “1+X” spatial configuration strategy dominated by Landscape Leisure Space, with Ecological Low-carbon Space, Agricultural Production Space, and Activity Gathering Space as options, in order to optimize community green roof spaces guided by resident needs.

How urban spatial characteristics impact surface urban heat island in subtropical high-density cities based on LCZs: A case study of Macau

Although numerous studies have explored the influence of urban spatial characteristics (USC) on surface urban heat island intensity (SUHII) from the perspective of local climate zone (LCZ), the spatio-temporal heterogeneity within and between LCZs has not been demonstrated. In this study, a total of 1540 grid units in Macau across 7 years were screened as the research samples. USC, SUHII and LCZ were calculated and derived from multi-source data. GWR and GTWR models were applied to detect the spatio-temporal non-stationarity between USC and SUHII, and Geodetector was used for ranking the interpretation strength of driving factors in each LCZ class. Results show that SUHII in LCZ 7 and LCZ 8 is the highest. Besides, the GWR model had the best fitting degree in accounting for thermal variations due to urban form changes, and the regression performance was generally different among LCZ classes, especially between the compact-types and the open-types. Furthermore, strategies related to urban form optimization were finally proposed in each LCZ class based on the contribution of driving factors. This study sheds new light on the spatio-temporal variations of “USC-SUHII-LCZ” linkage and provides specific planning recommendations for thermal environment improvement, especially in subtropical highdensity cities.

Flavored Tobacco Sales Restrictions and Youth E-cigarette Behavior: Impact by Tobacco Retailer Density in Diverse Communities in California.

Factors that impact flavored tobacco sales restriction (flavor restrictions) effectiveness on youth e-cigarette behavior are unclear. Tobacco retailer density (retailer density) is a health equity issue with greater retailer density in high-minority, low-income areas. We examined the association between flavor restrictions and youth e-cigarette behavior by retailer density across diverse communities in the California Bay Area. We analyzed data from the California Healthy Kids Survey using a difference-in-differences (DID) strategy. We compared pre- and post-policy changes in e-cigarette access and use one-year post-implementation among high school students in the Bay Area with a flavor restriction (n = 20 832) versus without (n = 66 126). Separate analyses were conducted for students in cities with low and high retailer density, with a median cutoff of 3.3 tobacco retailers/square mile. Students with high retailer density were more likely to identify as a minority and have parents with lower education. Among students with low retailer density, flavor restrictions were associated with 24% lower odds in the pre- to post-policy increase in ease of access relative to unexposed students (DID = 0.76, 95% CI: 0.58, 0.99). Among students with high retailer density, flavor restrictions were associated with 26% higher odds in ease of access (DID: 1.26, 95% CI: 1.02, 1.56) and 57% higher odds of current use (DID = 1.57, 95% CI: 1.31, 1.87). Flavor restrictions had positive impacts on youth e-cigarette access in low, but not high retailer density cities. From a health equity perspective, our results underscore how flavor restrictions may have uneven effects among vulnerable groups. In diverse communities in the California Bay Area, our results suggest a protective association between flavored tobacco sales restrictions and youth access to e-cigarettes in low, but not high tobacco retailer density cities one-year post-implementation. These results underscore how flavor restrictions may have uneven effects, and when implemented in high retailer density areas, may disproportionately place already vulnerable groups at heightened exposure to e-cigarette use and access. In high retailer density areas, additional tobacco control efforts may need to be included with flavor restriction implementation, such as increased education, youth prevention and cessation programs, policies to reduce tobacco retailer density, or stronger tobacco retailer enforcement or compliance monitoring.

Robust digital-twin airspace discretization and trajectory optimization for autonomous unmanned aerial vehicles

The infiltration of heterogenous fleets of autonomous Unmanned Aerial Vehicles (UAVs) in smart cities is leading to the consumerization of city air space which includes infrastructure creation of roads, traffic design, capacity estimation, and trajectory optimization. This study proposes a novel autonomous Advanced Aerial Mobility (AAM) logistical system for high density city centers. First, we propose a real-time 3D geospatial mining framework for LiDAR data to create a dynamically updated digital twin model. This enables the identification of viable airspace volumes in densely populated 3D environments based on the airspace policy/regulations. Second, we propose a robust city airspace dynamic 4D discretization method (Skyroutes) for autonomous UAVs to incorporate the underlying real-time constraints coupled with externalities, legal, and optimal UAV operation based on kinematics. An hourly trip generation model was applied to create 1138 trips in two scenarios comparing the cartesian discretization to our proposed algorithm. The results show that the AAM enables a precise airspace capacity/cost estimation, due to its detailed 3D generation capabilities. The AAM increased the airspace capacity by up to 10%, the generated UAV trajectories are 50% more energy efficient, and significantly safer.