Sustainable Urban Environment Research Articles

Urban Environments, Health, and Environmental Sustainability: Findings From the SALURBAL Study

Abstract Despite the relevance of cities and city policies for health, there has been limited examination of large numbers of cities aimed at characterizing urban health determinants and identifying effective policies. The relatively few comparative studies that exist include few cities in lower and middle income countries. The Salud Urbana en America Latina study (SALURBAL) was launched in 2017 to address this gap. The study has four aims: (1) to investigate social and physical environment factors associated with health differences across and within cities; (2) to document the health impact of urban policies and interventions; (3) to use systems approaches to better understand dynamics and identify opportunities for intervention and (4) to create a new dialogue about the drivers of health in cities and their policy implications and support action. Beyond these aims SALURBAL, has an overarching goal of supporting collaborative policy relevant research and capacity -building that engages individuals and institutions from across Latin America. In this review we provide an update on the SALURBAL data resource and collaborative approach and summarize key findings from the first aim of the study. We also describe key elements of our approach, challenges we have faced and how we have overcome them, and identify key opportunities to support policy relevant evidence generation in urban health for the future.

Advancing Sustainability in Urban Planning by Measuring and Matching the Supply and Demand of Urban Green Space Ecosystem Services

As global cities rapidly develop, the realization of sustainable urban development has become a pressing global concern. As a critical component of the urban built environment, urban green spaces are essential for maintaining the sustainability of urban ecosystems by offering a variety of ecological benefits. However, there are some problems in the design and construction of urban green framework, which often disregard the real needs of residents and hinder the sustainable development of urban areas. Therefore, urban planning that takes into account the supply and demand relationship of urban green space is considered to be a key technology that should help to improve residents’ happiness and promote urban sustainable development. This paper takes Zunyi City as an example; selects six indicators; combines UAV images, population, economic, and environmental data to evaluate ecosystem services valuation existing green space in the city; and analyzes its social and ecological needs. Affected by land utilization and development density, the supply value showed low spatial density characteristics in the central urban area and high spatial distribution characteristics in the surrounding urban area. The correlation between demand value and population density is the largest, and the distribution pattern is similar to that of population density. The supply-demand ratio in the study area is −0.54, indicating a severe imbalance between supply and demand. The correlation analysis between the comprehensive supply and demand ratio and each influencing factor shows that the correlation with population density is the largest. The combination of supply and demand maps addresses a major problem in planning, namely, ensuring that communities have priority in providing urban green space based on society’s need for ecosystem services. In addition, these maps will help develop the best green space planting plans to meet the specific needs of different communities. Taken together, the findings can help city planners and decision makers improve the layout of urban green areas, increase ecosystem service potential, and improve urban environmental quality and sustainability.

Free Trade and Haze Control: The Impact of Pilot Free Trade Zone Policy on Haze Pollution

As a new window for opening up in the new era, whether the China Free Trade Pilot Zones (PFTZs) can effectively balance urban economic development and environmental sustainability remains a topic that warrants further exploration. This study employs the PFTZ policy as a quasi-natural experiment and constructs a difference-in-differences model to empirically investigate the impact and mechanism of the PFTZ policy on haze pollution using city-level data from 2005 to 2020 in China. The study finds that: (1) the PFTZ policy significantly reduces haze pollution, and the results remain robust using the historical opening of treaty ports as an instrumental variable; (2) the PFTZ policy reduces haze pollution through the learning effect, demonstration effect, and agglomeration effect; and (3) the haze reduction effect of PFTZs is particularly pronounced inland and in areas with high public environmental awareness. The results directly address the key question of whether the PFTZ policy can foster sustainable economic development. It provides empirical evidence on how the PFTZ policy balances environmental sustainability and economic growth and draws policy recommendations for formulating more sustainable development strategies.

An Assessment of Land Use and Land Cover Changes on Urban Flooding: A Case Study in Sri Jayewardenepura Kotte

This study investigates the relationship between Land Use and Land Cover (LULC) changes and urban flooding in the Sri Jayewardenepura Kotte Divisional Secretariat Division (DSD). The research objectives include analysing flooding patterns, mapping LULC changes, and assessing the correlation between these changes and flooding occurrences. Additionally, a temporal rainfall variation analysis was conducted to provide further context. The study employed Geographic Information System (GIS) technology, specifically utilising ArcGIS for LULC classification and Inverse Distance Weighting (IDW) interpolation technique for rainfall data. The analysis reveals a clear association between heightened precipitation and major flood events. In 2010, the flood inundation area was 5.762 km² during the major flood in May, despite a monthly rainfall of over 650mm. However, in 2016, with over 700 mm of rainfall in May, the flood-inundated area was reduced to 4.046 km², highlighting the role of other factors such as wetland recovery. Moreover, it identifies significant LULC changes, emphasising rapid urbanisation and wetland decline. From 2009 to 2018, built-up areas increased from 11.49 km² to 14.18 km², while wetlands decreased from 2.29 km² in 2009 to 1.19 km² in 2015, before recovering slightly to 1.58 km² by 2018. The expansion of built-up areas is found to slightly increase flood risks, while wetland recovery acts as a natural flood buffer. This research underscores the importance of targeted interventions for urban flood resilience, such as flood-resistant infrastructure and wetland management. The findings provide critical insights for evidence-based urban planning and flood management strategies, aiming to create more resilient and sustainable urban environments.

INTELIGÊNCIA ARTIFICIAL NO TRÂNSITO

This study examines the role of Artificial Intelligence (AI) in urban traffic management, considering the growing challenges arising from the increase in the vehicle fleet and rapid urbanization. These factors contribute to frequent traffic congestion, increased pollutant emissions and a higher accident rate, which generates an urgent need for innovative solutions that promote safer, more efficient and sustainable traffic. The main objective is to evaluate how AI can be used to optimize urban mobility, reduce the frequency of accidents and minimize traffic-related pollution, in addition to identifying the main challenges and opportunities in the implementation of such technologies in modern urban contexts. The research was carried out through a literature review, analyzing scientific articles, publications and specialized documents. This survey sought to synthesize the existing knowledge on advances in intelligent transportation systems (ITS) and explore the practices and technologies that interconnect data and communication applied to traffic. The sources consulted included databases such as Google Scholar and recognized publications in the area, with a focus on developing countries, where the adoption of AI in urban mobility is still incipient. The use of AI-powered ITS can not only improve traffic flow and reduce congestion, but also contribute to a more sustainable urban environment. The research suggests that investment in infrastructure and capacity building will be crucial to the successful implementation of AI in traffic systems, especially in developing countries.

Adapting Cities for Older Adults Through Universal Design.

In the coming decades, population ageing will shape our cities and communities. In Finland, and in the other Nordic countries, the cohort of population 75 years old and older is increasing fastest in the urban areas. This demographic development will have impact on design of urban environment and housing, as well as on local services and transport. The WHO has recognized this challenge and launched the global network of Age Friendly Cities and Communities. The WHO proposes eight factors supporting older population that are interlinked. This paper focus on the three of the eight factors of age-friendliness directly related to the built environment: housing, access to outdoor environments and transport. The objective is to assess through case studies how has the Age-friendly cities framework promoted inclusive design of the cities. The research question is: How have the qualitative factors for age-friendliness been implemented in the urban environment? and How does the Age-friendly Cities framework shape the urban environment in the case study cities? The project uses qualitative case study methods involving users. The assessment of the quality of the environment is carried out with mixed methods: through city age-friendly policies, observations on site, and user participation. The analyses are based on Universal Design principals and the WHO framework. The objective is to provide further information on the practical measures to enhance age-friendliness through urban design and universally designed living environments. The overall aim is to promote sustainable and age-friendly urban environments through user knowledge and best practice examples.

Understanding of the predictability and uncertainty in population distributions empowered by visual analytics

Understanding the intricacies of fine-grained population distribution, including both predictability and uncertainty, is crucial for urban planning, social equity, and environmental sustainability. The spatial processes associated with the distribution of populations are complex, and enhancing their predictability involves revealing nonlinear interactions among various explanatory variables. Additionally, population distribution is influenced by various factors that are often challenging to quantify, thereby introducing uncertainty into predictive models. Although the development of explainable artificial intelligence (XAI) helps identify underlying factors, the complex geographical processes and the special nature of spatial data present challenges for purely statistical-based explanation methods, leading to incomplete or incorrect explanations. To address these challenges, we introduce GeoVisX, a geospatial visual analytics framework integrated with XAI. GeoVisX integrates XAI with visual analytics to dissect the spatial processes. Through a case study of Munich, GeoVisX demonstrates its utility in analyzing spatial distribution and identifying key factors impacting population distribution at the 100 m grid level. Our findings highlight the GeoVisX’s capability to enhance understanding of geographical phenomena, contributing to more informed urban policy and planning strategies. This study not only validates the effectiveness of GeoVisX but also emphasizes the importance of incorporating visual analytics and explainable methodologies for addressing complex geographical issues.

Transforming Insights Into Action: The Influence Of Business Analytics On Corporate Strategy Development

The escalating urbanization and industrial activities in cities have significantly impacted air quality, posing health risks and environmental challenges that demand innovative solutions. This review systematically explores the integration of artificial intelligence (AI) and Internet of Things (IoT) sensors within smart cities, focusing on their role in real-time air quality monitoring and dynamic response mechanisms. By adhering to PRISMA guidelines, we analyze recent advancements in AI-driven automated control systems, which utilize IoT sensors to continuously monitor pollutants, including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and particulate matter (PM). The data gathered by these sensors feed into AI algorithms that facilitate immediate, adaptive responses, such as modifying traffic light sequences to alleviate congestion and notifying nearby facilities to adjust emissions during high pollution periods. This review synthesizes findings on the effectiveness, limitations, and scalability of these systems, highlighting key challenges like sensor data accuracy, privacy considerations, and the infrastructure required for city-wide deployment. The paper concludes by emphasizing the transformative potential of AI and IoT in fostering sustainable urban environments and presents recommendations for future research and policy improvements to optimize smart city air quality management.

AI-Driven Adaptive Ventilation Systems For Real-Time Pollution Control In Industrial And Urban Settings: A Systematic Review

The escalating urbanization and industrial activities in cities have significantly impacted air quality, posing health risks and environmental challenges that demand innovative solutions. This review systematically explores the integration of artificial intelligence (AI) and Internet of Things (IoT) sensors within smart cities, focusing on their role in real-time air quality monitoring and dynamic response mechanisms. By adhering to PRISMA guidelines, we analyze recent advancements in AI-driven automated control systems, which utilize IoT sensors to continuously monitor pollutants, including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and particulate matter (PM). The data gathered by these sensors feed into AI algorithms that facilitate immediate, adaptive responses, such as modifying traffic light sequences to alleviate congestion and notifying nearby facilities to adjust emissions during high pollution periods. This review synthesizes findings on the effectiveness, limitations, and scalability of these systems, highlighting key challenges like sensor data accuracy, privacy considerations, and the infrastructure required for city-wide deployment. The paper concludes by emphasizing the transformative potential of AI and IoT in fostering sustainable urban environments and presents recommendations for future research and policy improvements to optimize smart city air quality management.

Impact of Urban Surfaces on Microclimatic Conditions and Thermal Comfort in Burdur, Türkiye

Rapid urbanization worldwide offers numerous benefits but also introduces challenges, particularly concerning urban climate comfort, which affects the physical and social well-being in cities. This study examined the microclimatic characteristics of the Burç neighborhood in the historical core of Burdur city, using ENVI-Met models with temperature, relative humidity, wind and PET data collected over a 33,665 m2 area at 06:00, 09:00, 12:00, 15:00, 18:00 and 21:00 on 15 August 2023. The analysis revealed that thermal comfort decreases significantly from 09:00 onwards, especially on hard surfaces like asphalt, concrete and parquet, which lack vegetation and intensify heat retention. By contrast, green areas were found to enhance bioclimatic comfort by reducing perceived temperatures by up to 20% in shaded and vegetated zones. Based on these findings, it is recommended that urban areas reduce heat-absorbing materials, such as asphalt and concrete and prioritize green spaces in landscape planning to improve thermal comfort and create more sustainable urban environments.

Re-wilding the Night: Understanding How Darkness Is Valued Through the Nighttime Light Ecology of Bonn Botanical Gardens

Rewilding the Night is an interdisciplinary research project that aims to reimagine the urban night by capturing and communicating the qualities and rhythms of both artificial and natural light at night. Through a collaborative and experimental approach, the project seeks to make the urban night legible by employing sensor technologies and data visualization techniques, thus fostering a deeper engagement with and appreciation for urban darkness. The project has three aims—first, to capture and analyse environmental light data in Bonn Botanical Gardens, Germany to create an accessible understanding of the variations in natural and artificial nighttime light. Second, to use this groundwork to inform subsequent workshops to capture public perceptions and values regarding darkness; and third, to develop lighting prototypes that respond to light data and the insights gained through the workshops. Central to the project is the re-evaluation of urban darkness by questioning and expanding the normative frameworks surrounding urban lighting. The project underscores the importance of interdisciplinary research and design in addressing complex urban challenges, offering a model for future research aimed at creating more livable, sustainable, and inclusive urban night environments for both humans and non-humans.

Integrated Framework for Enhancing Liveability and Ecological Sustainability in UAE Communities

Urban growth is vast in the United Arab Emirates (UAE) due to economic development, and there is a need to consider liveability and sustainable ecosystems for future urban expansion. Promising strategies for sustainability focus on minimizing a building’s effects on the environment and improving residents’ quality of life, which is important in the desert and when confronting the issues of water and climate change. Sustainable practices that impact the livelihood of people in the UAE include factors such as walkable areas, open space, policing, healthcare, education, housing, and ensuring friendly transport that enhance the overall quality of life of residents in the region. Recognizing and appreciating the UAE’s cultural values is crucial when incorporating these aspects, allowing references to the nation’s character when creating communal areas. The primary research included quantitative surveys of three identified communities, composed of fifty participants each, where the findings indicate partial to full compliance, with 85.7% of the liveability indices being about public transport and green space. Through this analysis, liveability and sustainability principles need to be trialed and incorporated into future urban development to embrace the ecology as well as the inhabitants. To realize these targets, the proposed study adopted a four-part approach. Initially, an analysis of related studies concerning the UAE or the Gulf area was carried out to obtain important liveability and quality-of-life factors. A total of 6 dimensions and 51 indicators were extracted from the literature to inform the next stage. Subsequently, the authors identified and evaluated the design of three chosen communities in various cities in the UAE concerning liveability and sustainability indices. Consequently, a conceptual redesign of a typical community was made, illustrating the improved quality of life and sustainability. Lastly, a survey with respective facets from an urban planning architect and environmental scientist cum environmental economist was conducted to evaluate the practicality of the proposed design. This research gives a comprehensive picture of how liveability and sustainable ecosystem concepts need to be implemented in the UAE urban context and offers a direction to develop lively, context-specific, culturally attached, and sustainable urban environments for the present day and for the future.

Modeling and Optimization of NO2 Stations in the Smart City of Barcelona

The growing problem of nitrogen dioxide (NO2) pollution in urban environments is driving cities to adopt smart and sustainable approaches to address this challenge. To quantify and compare the effect of environmental policies, cities must be able to make informed decisions with real-time data that reflect the actual situation. Therefore, the objective of this work is threefold: The first is to study the behavior of the key performance indicator (KPI) of NO2 concentrations per station in Barcelona through exploratory analysis and clustering. The second is to predict NO2 concentration behavior, considering meteorological data. Lastly, a new distribution of current and new stations will be proposed using an optimization algorithm that maximizes the distance between them and covers the largest area of the city. As a result of this study, the importance of the location of measurement points and the need for better distribution in the city are highlighted. These new spatial distributions predict an 8% increase in NO2 concentrations. In conclusion, this study is a comprehensive tool for obtaining an accurate representation of NO2 concentrations in the city, contributing to informed decision-making, helping to improve air quality, and promoting a more sustainable urban environment.

Leveraging Spatial Analysis Techniques for Developing a Climate Resilient and Localized Urban Greening Plan for Pasig City

Abstract. A recent study has been conducted to evaluate the current state of green spaces in Pasig City, Philippines, and to propose a Climate Resilient and Localized Urban Greening Plan (CRLUGP) to address urban greening that is essential for creating sustainable cities, especially in the face of climate change and urban population growth. The study utilized Geographic Information Systems (GIS), Remote Sensing (RS), and Machine Learning (ML) to map green spaces, analyze climate risks, and identify necessary corrective measures. The findings revealed that Pasig City currently only has 70.18 hectares of green space, which is significantly below the World Health Organization's recommended minimum of nine (9) square meters of green space per capita. Projections indicate that by 2032, the city will need 925.72 hectares of green space to meet the needs of its growing population. Additionally, the study identified a connection between low canopy cover and increased urban heat island effects, with the top 10 barangays showing a canopy cover of only 27.64%, well below the recommended 40%. Moreover, areas with limited green spaces were found to be at a higher risk of flooding, highlighting the importance of more vegetation for managing stormwater and mitigating climate-related risks. The study recommends a strategic approach to urban greening, leveraging spatial analysis for continuous monitoring and evaluation. By integrating spatial technologies and data-driven decision-making, Pasig City aims to establish a more sustainable and resilient urban environment for its residents.

Innovative Applications of Parametric Design and Digital Tools in Architecture: Exploring the Integration of Generative Design and BIM Technology

Abstract. Through parametric design and generative design, as well as the broader Building Information Modeling (BIM) approach, there is now a whole body of new tools being used by architects to are opening up new ways of designing buildings in innovative, efficient and sustainably responsible ways. This paper presents the emergence of parametric design and its evolution from simple structural optimisations to complex fulling the design of complete buildings and entire urban areas. The paper discusses the integration of both parametric design and generative design with Building Information Modelling (BIM). This technology pairing enables architects to research and test hundreds of design alternatives and optimise for particular variables, such as structural integrity, material efficiency and energy use. This paper showcases a number of case studies of how these technologies are applied to develop innovative and sustainable urban environments (eg, Sidewalk Toronto) and discusses the challenges associated with adopting these technologies, such as computational requirements and a lack of digital interoperability between these technologies. The paper concludes by identifying the innovation opportunities for sustainable development and the future of architectural practice that these technologies are offering.

Assessing Buffer Gradient Synergies: Comparing Objective and Subjective Evaluations of Urban Park Ecosystem Services in Century Park, Shanghai

Urban parks provide essential ecosystem services (ESs) that enhance human wellbeing. However, discrepancies often arise between objective assessments of these services and stakeholders’ subjective perceptions. This study addresses a research gap concerning the synergies and tradeoffs between objective evaluations and subjective perceptions of key ecosystem services across various spatial scales. We investigated six key ecosystem services in Century Park, Shanghai, across seven buffer radii (8–100 m). Objective data were obtained from park view images (PVIs) and spatial analysis, while subjective perceptions were gathered through a scoring survey of 33 stakeholders. The key finding is that a buffer radius of 35 m offers optimal synergy between objective and subjective assessments for most ESs, particularly in pollution mediation, temperature regulation, and cultural services. Professionals showed stronger alignment in regulatory services like pollution mediation and temperature regulation, while residents exhibited higher synergy in net primary production (NPP) beyond a 75 m radius. Notably, cultural services displayed nuanced differences, with professionals preferring simpler landscapes and residents demonstrating varied aesthetic preferences. These findings emphasize the importance of integrating objective data and human perceptions in urban green space planning and governance. By incorporating diverse stakeholders and identifying optimal buffer zones, planners and designers can effectively balance ESs with human experiences. This approach ultimately fosters more sustainable and wellbeing-centered urban environments.

Boundary Layer Modelling of Flow Acceleration and Energy Transfer Effects in Smart Pavement Design

The integration of remote technology into the construction industry has advanced the emergence of smart, self-learning infrastructure across all levels of land transportation design and development. However, energy harvesting capabilities for smart road ventilation purposes have not yet been fully researched as the world gravitates towards energy sustainability. This study thus presents a mathematical investigation of the self-draining design potentials of road pavements, leveraging on energy absorption and conversion to accelerate conductive and convective ventilation of these pavements during wet conditions, as a means of ensuring the skid resistance and safety of such pavements are not compromised. Applying numerical methods with the aid of commercial software code MATLAB®, the classical physics of fluid-surface interaction was used to model accelerated drainage of microflood off paved surfaces through methodical modification of the thickness of the boundary layer associated with the flow regime over the flat road surface. Results indicate significant influences of energy exchange, thermal, and viscous diffusivity on flow acceleration. Alterations in parameters such as the slip factor, thermally induced Brownian motion or phoretic characteristics of the fluid particles at the boundary induce accelerated flow at the surface of the pavement. The findings contribute to the advancement of smart infrastructure by offering practical insights into the potential benefits of integrating energy-harvesting technologies into road pavement systems. By optimizing flow acceleration mechanisms, smart pavements can play a crucial role in improving road safety and sustainability in urban environments.

INFORMATION SYSTEM OF STREET LIGHTING CONTROL IN A SMART CITY

Context. In the context of the rapid development of technologies and the implementation of the concept of smart cities, smart lighting becomes a key element of a sustainable and efficient urban environment. The research covers the analysis of aspects of the use of sensors, intelligent lighting control systems with the help of modern information technologies, in particular such as the Internet of Things. The use of such technologies makes it possible to automate the regulation of lighting intensity depending on external conditions, the movement of people or the time of a day. This contributes to the efficient use of electricity and the reduction of emissions into the atmosphere. Objective. The purpose of the paper is to analyze the procedures for creating an information system as a tool for monitoring and evaluating the level of illumination in a smart city with the aim of improving energy efficiency, safety, comfort and effective lighting management. The implementation of a smart lighting system for Lviv will help improve energy efficiency and community safety. Method. A content analysis of scientific publications was carried out, in which the results of research on the creation of street lighting monitoring systems in real urban environments were presented. The collection and analysis of data on street lighting in the city, such as energy consumption, illumination level, lamp operation schedules, and others, was carried out. Machine learning methods were used to analyze data and predict lighting needs. Using the UML methodology, the conceptual model of the street lighting monitoring information system was developed based on the identified needs and requirements. Results. The role of data processing technologies in creating effective lighting management strategies for optimal use of resources and meeting the needs of citizens is highlighted. The study draws attention to the challenges and opportunities of implementing smart lighting in cities, maximizing the positive impact of smart lighting on modern urban environments. The peculiarities of the development and use of an information system for controlling street lighting in a smart city are analyzed. The potential advantages and limitations of using the developed system are determined. Conclusions. The project on the creation of an information system designed to provide an energy-efficient lighting system in a smart city will contribute to increasing security, particularly, ensuring the safety of the community through integration with security systems, reducing energy consumption, through minimizing the electricity usage in periods when the need for lighting is not necessary. It has been determined that to implement an information system for remote monitoring and lighting control in a smart city, it is advisable to consider the possibility of using a complex lighting control system. Calculations were made on the example of Lviv for the city’s lighting needs. The use of motion sensors to determine the need to turn on lighting was analyzed. A conceptual model of the information system was developed using the object-oriented methodology of the UML notation. The main functionality of the information system is defined.

The Role of the Internet of Things in Enhancing Sustainable Urban Energy Systems: A Review of Lessons Learned from the COVID-19 Pandemic

ABSTRACT The Internet of Things (IoT) has emerged as an indispensable technology enabling the efficient management of energy consumption and deployment of renewable energy solutions within urban energy systems. While urban energy systems can be made sustainable in both smart cities (SC) and traditional cities, the former provide a more advantageous environment for achieving sustainability thanks to advanced technology integration, data-driven decision-making, integration of renewable energy, as well as policy and infrastructure support. Across the globe, cities are evolving into SCs through the implementation of sustainable urban energy systems and adaptation to the latest IoT technologies. For them, advanced cutting-edge technologies such as digital twins, artificial intelligence (AI), Big Data, and IoT are all positioned to underpin the civic platform for new forms of a city that is simultaneously sustainable and prosperous. The COVID-19 pandemic brought about significant challenges, emphasizing the need for resilient and sustainable urban environments and demonstrating that IoT became a must for the modern cities in energy generation, transmission, and the efficient use of energy sources by cities. This bibliometric review focuses on the new role of IoT in the development of post-COVID sustainable urban energy systems. It demonstrates how IoT can help to efficiently manage energy consumption and to deploy novel renewable energy solutions in the cities using the experience from the two years of the COVID-19 pandemic. The article explores the role of IoT in the post-COVID urban energy development highlighting how the technology can contribute to sustainable urbanization. It employs the extended literature review including both 151 publications retrieved from the Web of Science (WoS) database selected based on the relevant keywords and the analytical tools based on Google Trends as well as the enhanced network dynamics VOSviewer v.1.6.15 software (the latter being frequently used for identifying the dominant trends in intersectoral bibliometric research). The findings stemming from this research can contribute to the clustering of the discussion of the strategies required for boosting SCs’ development and growth. Therefore, the results and outcomes can provide many useful insights for academics and stakeholders alike on the role of the IoT in the development of sustainable urban energy in post-pandemic cities.

Data augmented planning: A data-driven approach to measuring-understanding-optimizing green justice across 263 Chinese cities

Urban Green Spaces (UGS) are pivotal in fostering sustainable urban environments, with disparities in access to UGS raising concerns about 'green justice'. Existing research often focuses on the socioeconomic influences on green justice, overlooking the role of urban green planning and design. To address this, we evaluated green justice levels across 263 Chinese cities using extensive geospatial data and explainable machine learning techniques. Our findings highlight a significant relationship between the planar configuration of UGS and green justice. Notably, these associations are non-linear, showing threshold effects where certain UGS characteristics beyond specific values can adversely affect green justice. The study also identifies interaction effects among these spatial characteristics. Our results offer practical guidelines for urban planning to enhance green justice, especially in China's large cities. Recommendations include optimizing green space morphology and proximity, and reconfiguring the layout of various green spaces. This research provides valuable insights and strategies for promoting green justice, particularly in densely populated cities in developing nations like China.