Challenge For Cities Research Articles

Modeling the impact of urban land cover features and changes on the land surface temperature (LST): The case of Jordan

Higher land surface temperature (LST) in cities than their surrounding areas presents a major sustainability challenge for cities. Decision-makers and planners use the LST measurements to monitor the urban environment to reduce the urban climate’s main challenges. Therefore, there is an urgent need to examine the impacts of urban features and changes on the LST. This study focused on the relationship between LST and urban land changes and the impact of these changes on LST during different periods. Although a set of studies explored the relationship between landscape features and urban LST, several aspects still need further discussion. Here, the study aims to explore the influence of landscape features and land cover patterns on land surface temperature LST in two cities (Amman and Zarqa) in Jordan, and identify which of these features (vegetation cover, built-up and population density) has the most effective and influence on LST values. Therefore, this paper is the first study about land surface temperature LST and its relations with these aspects in Jordan. This study used a mixed method approach using quantitative method (GIS) and qualitative method (comparative case studies). This study revealed that the most important features affecting the LST values were: (1) Population density; (2) Built-up; and (3) Vegetation, and in descending order from the strongest to the least effective. It is also concluded that in the city in which the population density is high, the effect of built-up areas on the values of LST is as high as possible and positive more than the cities with medium and low population density. As for the city in which the population density is medium to low, the effect of vegetation cover on the values of LST is greater, and this can be more positive than in cities with a high population density. Therefore, the study contributes to improving the planners' and policymakers’ suitable future decisions for making sustainable cities.

An Auction Pricing Model for Energy Trading in Electric Vehicle Networks

In recent years, the interest in electric vehicles (EVs) in the research community has been growing, particularly in the context of decarbonization. Additionally, there is a growing increase in their number, leading to massive energy demand on the charging stations (CSs). Energy trading management for CSs puts great pressure on the power grid and is a stimulating challenge in smart cities. In this paper, we propose an innovative market formulation in which autonomous vehicles and smart charging and discharging stations are motivated to cooperate dynamically with changing roles. In order to mathematically formulate the energy trading market, we adopt a double auction strategy that is repeated in steps. In this strategy, EVs and CSs participate by buying and selling energy. The investigated problem has high complexity, and thus, multi-objective optimization is employed so as to encapsulate the opposing objectives that the EVs and CSs have. Multi-objective optimization leads to a fairer and more efficient market operation. The performance of the presented approach is investigated through analytical and experimental results. More specifically, the proposed algorithm achieves up to 52.5% reduction in energy consumption. The performance evaluation proves that the suggested strategy offers both fairness and significant energy benefits, encouraging both electric vehicles and charging stations to take part in a double auction energy trading system.

Exploring the potential impact of smart urban technologies on urban sustainability using structural topic modelling: Evidence from Belgium

This study explores the potential impact of smart urban technologies used in smart city projects on three dimensions of urban sustainability (economic, environmental and social). Although the literature notes that smart urban technologies and their capabilities are potential saviours when it comes to urban and sustainability challenges in cities, there is a lack of studies exploring the impact of smart urban technologies on urban sustainability. Thus, we address this literature gap by conducting structural topic modelling on smart city projects retrieved from the Smart Territory call for projects. In these projects, city managers' report extensively on how smart urban technologies can support urban sustainability. Our results show nine groups of smart urban technologies that will support at least two urban sustainability dimensions. Smart mobility systems can support all three dimensions of urban sustainability. Technology benefits will be realised by smart urban technology capabilities and through the involvement of the city's community in the use of technology.

6G Connected Vehicle Framework to Support Intelligent Road Maintenance Using Deep Learning Data Fusion

The growth of IoT, edge and mobile Artificial Intelligence (AI) is supporting urban authorities exploit the wealth of information collected by Connected and Autonomous Vehicles (CAV), to drive the development of transformative intelligent transport applications for addressing smart city challenges. A critical challenge is timely and efficient road infrastructure maintenance. This paper proposes an intelligent hierarchical framework for road infrastructure maintenance that exploits the latest developments in 6G communication technologies, deep learning techniques, and mobile edge AI training approaches. The proposed framework abides with the stringent requirements of training efficient machine learning applications for CAV, and is able to exploit the vast numbers of CAVs forecasted to be present on future road networks. At the core of our framework is a novel Convolution Neural Networks (CNN) model which fuses imagery and sensory data to perform pothole detection. Experiments show the proposed model can achieve state of the art performance in comparison to existing approaches while being simple, cost-effective and computationally efficient to deploy. The proposed system can form part of a federated learning framework for facilitating large scale real-time road surface condition monitoring and support adaptive resource allocation for road infrastructure maintenance.

Characterization, quantification and management of municipal solid waste in Shivamogga city, Karnataka, India

Planning and implementing an integrated, effective solid waste management system is one of the biggest challenges in large cities. In this study, all the wards under the Shivamogga City Corporation (SCC) were surveyed to collect data on the number of households, commercial establishments and bulk waste generators to determine the average waste generation rate in each ward. To determine the total waste generation in the city, average quantity of waste generated by each generator was multiplied with the estimated number of waste generators. To find the average household waste generation, waste sampled from 400 households and 100 commercial establishments was recorded. A waste characterisation study was also conducted over a period of 3 days at the transfer station. GIS techniques were used to prepare the various maps to understand the population growth, road network, ward boundaries etc. The study showed that the total quantity of waste generated in the Shivamogga city can be estimated as 210 tons per day (TPD), including 34 TPD of silt waste from drainage. Through the sampling studies conducted on field, it has been estimated that households and commercial establishments are the major waste generators in the city, with households generate about 55% of waste generated in the city and commercial establishments generate about 11% of the waste adding up to 66% of the total waste generated. This paper also provides recommendations on building adaptable solutions for the existing problems in Shivamogga.

Impact of Sustainability Transition in Moroccan Cities Identity: The Case of Benguerir

Whether internationally or in Morocco, the construction industry is one of the world's most energy-consuming industries. Nationally, this sector is estimated to account for 33% of total energy consumption. In addition, the construction industry is one of the highest producers of GHG emissions. For these reasons, Morocco has taken steps to reduce the sector's impact on the economy and the environment. That's why the green sustainable cities trend has started in the last decade. Globalization trends and efforts to keep the concept of sustainability alive in a concrete city have brought along many conflicting choices. Moroccan cities are known for their strong identities due to the long process of shaping these cities throughout history. But new sustainability trends seem to introduce new colors that can strip them of their identity. This article is a research paper for the arid climate city of Benguerir, located in the South, one of the green cities of Morocco. Green represents a challenging context for implementing sustainability. This study reveals the different parameters of sustainability in cities, how important urban identity is, and how it can be perceived and discusses the transition and identity changes of cities. The case study exemplifies the Moroccan context, the reason behind the need for Moroccan green cities, the efforts of the government, and the problems green Moroccan cities may face when trying to preserve their identity. Benguerir is an example that has achieved various sustainability parameters and represents the policies of Moroccan green cities. The city can also represent upcoming challenges for cities in a similar context.

Urban livestock rearing and the paradox of sustainable cities and urban governance in West Africa: Empirical evidence from Wa, Ghana

Although inner-city livestock rearing provides households with food security and cash income opportunities, urban farmers and planners face challenges balancing urban livestock rearing with sustainable cities’ ideals. Literature on the interface of inner-city rearing, sustainable cities and urban governance dilemma is limited in African cities. Using the city of Wa in Ghana as a case, this study seeks to understand cattle-rearing practices, driving forces, the public health risk and governance challenges in African cities. The study employed a questionnaire to elicit data from 96 cattle keepers, while interviews were conducted with neighborhood residents and city authorities. Descriptive statistics and binary logistic regression were used to analyze the quantitative data, and thematic analysis employed to analyze the qualitative data. The study found that cattle keepers are spread across the inner-city and keep indigenous, exotic, and crossbreeds. Open grazing and stall feeding were adopted in the wet and dry seasons, respectively. The animals are kept in makeshift structures and open kraals. The holders earn substantial income, making demand for cattle the main determinant of farmers' decision to rear. Although the cattle pose a health risk and cause inconvenience to residents, political interferences and logistical constraints limit local authority's efforts to govern rearing in the inner-city. Based on the challenges and the benefits, city authorities might be faced with trying to strike a balance with sustainable cities' agenda. Therefore, actions towards harmony between livestock rearing, environmental sustainability and human safety are imperative for effective urban governance.

Housing refugees from Ukraine: preliminary insights and learnings from the local response in five European cities

ABSTRACT The Russian war of aggression against Ukraine caused an escape of >7 million people to other European countries. In this extreme context, the accommodation of refugees has been an urgent need and an unexpected challenge for the host cities and societies. This short paper discusses insights and learnings on housing and accommodation of Ukraine war refugees at the local scale. It summarises challenges within the general management of (housing) integration, discusses related learnings from the hitherto coping mechanisms and sheds light on policy implications for the future by embedding the migration challenge of Ukrainian refugees into a wider context.

Pathways toward PM2.5 air quality attainment and its CO2 mitigation co-benefits in China's northern cities by 2030

Rapid economic development and urbanization have left millions of people in urban areas vulnerable to the adverse effects of air pollution. Reducing serious PM2.5 pollution remains a major policy challenge for Chinese cities, such as the “2 + 26” Cities in the most polluted region of China, despite adopting various air pollution-control measures since 2017. In this study, we use a Greenhouse Gas and Air Pollution Interactions and Synergies model for the “2 + 26” Cities to explore feasible pathways for achieving the PM2.5 air quality annual standard (35 μg/m3) until 2030 by developing four future scenarios based on a 2017 emission inventory. The results show that by continuing the control policies from before 2020, including the Air Pollution Prevention and Control Action Plan from 2013 and the Three-Year Action Plan for Wining the Blue Sky Defense Battle from 2018, and implementing the policies likely to be proposed after 2020, the “2 + 26” Cities will not succeed in achieving the standard by 2030; furthermore, the amount of the population living below 35 μg/m3 will not exceed 12%. Nevertheless, by combining the best available technologies, the regional average PM2.5 concentration in the “2 + 26” Cities is 34 μg/m3 by 2030, attaining the target; moreover, more than half of the population will experience air quality that conforms to the standard. Under this scenario, emissions of primary PM2.5, SO2, NOx, NH3 and NMVOCs are estimated to decrease by 75%, 69%, 76%, 32% and 52%, respectively, in 2017–2030. The emission reductions under alternative scenarios vary widely across cities, indicating the need for differentiated control strategies among cities. Considering the predominant contributions to emissions and the lack of effective control measures, fuel conversion, off-road, agricultural and solvent use sectors should be paid more attention to enable further emission reductions in future. In addition, CO2 emission reduction co-benefits of implemented clean air action measures have been identified; however, the negative reduction effects of these measures should be given more attention (e.g., increased carbon emissions in the power sector from electrification of end-users).

Neutrosophic Framework for Assessment Challenges in Smart Sustainable Cities based on IoT to Better Manage Energy Resources and Decrease the Urban Environment's Ecological Impact

Sustainable smart cities based on the Internet of Things (IoT) technology provide promising prospects for improving quality of life. However, in order to facilitate the widespread implementation of IoT-based smart city solutions, there is a need to concern about data privacy and security, standardization, interoperability, scalability, and sustainability. Reducing the environmental effect of urban activities, optimizing the management of energy resources, and designing novel services and solutions for inhabitants are all examples of how the smart city concept is inextricably linked to sustainability. There is a need to assess challenges in smart sustainable cities based on IoT. This paper is intended to introduce a new neutrosophic framework for assessment challenges in smart, sustainable cities based on IoT for better-managing energy resources and decreasing the urban environment's ecological impact. The proposed framework used nine criteria and five alternatives. Also, the proposed framework applied the neutrosophic Weighted Product Method (WPM) to compute the weights of criteria and rank challenges. Moreover, the proposed framework integrated the single-valued neutrosophic set to deal with uncertain data. The results indicated that the proposed framework can handle uncertain data and give more effective results in assessing challenges in smart, sustainable cities based on IoT to better manage energy resources and decrease the urban environment's ecological impact.

Dissecting ecosystem services distribution and inequality of typical cities in China

Conserving and restoring ecosystem services in urban areas is an efficient measure to deal with increasing ecological challenges for cities while enhancing urban ecological resilience. However, rising inequalities threaten to improve critical environmental justice, public health and urban ecological resilience. This study proposed a non-monetary framework for accounting for urban ecosystem services and explored the inequality of ecosystem services using the Gini coefficient. Further, a regression-based decomposition method was used to identify primary socioeconomic factors that contributed to inequality. The results showed that the total ecosystem service in the urban areas presented a trend of first growing rapidly and then fluctuating steadily from 6.78 × 1022 sej in 1985 to 1.14 × 1023 sej in 2020 the percentage of existing services in the total ecosystem services was over 50%. The Gini coefficient of 1985 was more extensive than that of other years, which is 0.461. The runoff regulation service and the temperature mitigation service were the primary contributors for the inequality. Meanwhile, such income per capita, nonfarm rate and industrial production provided over 70% contribution rate to the inequality. This study assessed the inequality of urban ecosystem services and analyzed the driving factors, emphasizing the importance of reducing inequality, and providing a specific reference basis and theoretical support for decision-makers in urban planning and development strategies.

Preferensi Masyarakat Terhadap Penggunaan Telemedicine Sebagai Pendukung Sarana Kesehatan pada Masa Pandemi Covid-19 di DKI Jakarta

The Covid-19 pandemic has become a great challenge for cities around the world, one of which is DKI Jakarta, to adapt to the impact it has. One of the biggest impacts of the pandemic is health services that become vulnerable to experiencing over capacity during the pandemic. This condition gave rise to a new phenomenon, namely the use of telemedicine as a form of community adaptation to overcome the problem of limited access to health services when a wave of COVID-19 cases occurred. As a form of public service, it is important to know the preferences of the community as users of telemedicine, so that later the benefits obtained from telemedicine can be maximized. The results of this study indicate that people's preferences for the use of telemedicine are very diverse, which people give a positive response to the use of telemedicine as a form of health service, as proved by the number of people who will continue to use it in the future. The community also uses telemedicine as a solution to the problems of conventional health services, such as the high cost of services and the service process which is considered to be complicated and take a long time. However, the use of telemedicine is still facing obstacles, one of which is the quality of the application which is considered to be still not good. The use of telemedicine can be a solution to the problems of conventional health services, because telemedicine cannot remove the existing health care system, but is complementary.

Introduction to the Special Issue: Planning for Climate Transformations

Growing climate impacts and ambitious calls to decarbonize society pose unprecedented challenges for cities and their built environments, political economic systems, and governance institutions. This special issue invites planning scholars to consider how planning research can inform transformative climate initiatives and how planning itself needs to transform to better support climate transformation. In this introduction, we review definitions of transformation, introduce each of the six articles and their approaches to transformation, and explore cross-cutting tensions among them. We conclude with our reflections for future research that would help planning prepare for and contribute to climate transformations.

Water challenges of Dire Dawa city of Ethiopia: An assessment of urban growth and groundwater supply

Urbanization in Ethiopia is increasing rapidly, leading to environmental changes and necessitating improved urban infrastructure. Dire Dawa, the second most populous city in Ethiopia, has a high rate of urban growth. This study focuses on three main areas: remote sensing analysis of urban growth, urban water supply and water distribution system, and groundwater resources management. Land use and land cover (LULC) analysis over four different time periods showed significant and rapid expansion of the city. The current and future water demand and supply analysis found that the water supply is three times less than the water demand, indicating that existing water sources are not adequate for the future expansion of the city. Moreover, the hydraulic performance of the existing distribution system as analyzed by WaterGems software found that pressure at 22.41% of nodes and velocities at 29.83% of pipes are sufficient to provide water for the study area. Finally, the study investigated the discharge and water level and water quality of each borehole in Dire Dawa City. Overall, this study showed that high urbanization rate together with the population growth has put pressure on the existing water supply source and existing water distribution system calling for feasible water management strategy for the city.

An assessment of Africa’s second-hand clothing value chain: a systematic review and research opportunities

A rapid change in fast fashion has significantly accelerated the expansion of the volume of discarded clothing across the globe. Africa is the world’s largest destination for second-hand clothes (SHC, sometimes known as ‘Mitumba’). However, fewer studies have been conducted on Africa’s SHC, making it challenging to evaluate the impact of the market and its value chain. This study examines the economic contribution and assessment of the SHC value chain and the resulting environmental challenges, identifies the trends of scholarly discourse on the topic in Africa, examines their methodologies and develops future research opportunities. The study shows that the SHC trade is an essential supply chain connecting developed and developing countries and a valuable clothing consumption alternative for people experiencing economic decline, poverty and low purchasing power. SHC is crucial in delivering fashion products to customers in underdeveloped African countries. It also creates job opportunities for hundreds of thousands of people in the trade, distribution, repairs, laundry services and upcycling. Results further show that Africans are being enriched with new skills and knowledge of the SHC trade, which is expected to help grow and promote small- to medium-sized enterprises. However, poorly made Mitumba become unmarketable, creating environmental challenges in cities across the continent. The study found fewer empirical studies, due largely to limited data on Africa’s SHC trade. This calls for more empirical studies to scale the SHC trade in the region, expand the boundaries of entrepreneurial opportunities for Africa to interact with the global market, and alleviate the widespread problem of extreme poverty while also addressing the environmental challenges posed by SHC.

Hardware-Efficient Scheme for Trailer Robot Parking by Truck Robot in an Indoor Environment with Rendezvous.

Autonomous grounded vehicle-based social assistance/service robot parking in an indoor environment is an exciting challenge in urban cities. There are few efficient methods for parking multi-robot/agent teams in an unknown indoor environment. The primary objective of autonomous multi-robot/agent teams is to establish synchronization between them and to stay in behavioral control when static and when in motion. In this regard, the proposed hardware-efficient algorithm addresses the parking of a trailer (follower) robot in indoor environments by a truck (leader) robot with a rendezvous approach. In the process of parking, initial rendezvous behavioral control between the truck and trailer robots is established. Next, the parking space in the environment is estimated by the truck robot, and the trailer robot parks under the supervision of the truck robot. The proposed behavioral control mechanisms were executed between heterogenous-type computational-based robots. Optimized sensors were used for traversing and the execution of the parking methods. The truck robot leads, and the trailer robot mimics the actions in the execution of path planning and parking. The truck robot was integrated with FPGA (Xilinx Zynq XC7Z020-CLG484-1), and the trailer was integrated with Arduino UNO computing devices; this heterogenous modeling is adequate in the execution of trailer parking by a truck. The hardware schemes were developed using Verilog HDL for the FPGA (truck)-based robot and Python for the Arduino (trailer)-based robot.

Evaluating Social Equity of Transit Accessibility: A Case of Salt Lake County, U.S.

Addressing social equity in public transportation remains a key challenge for many cities and planning organizations. In this study, we examined social equity dimensions of accessibility to light rail transit (LRT) stations in Salt Lake County, U.S., by employing two novel methods. First, we used the two-step floating catchment area (2SFCA) method to examine the interactions between the demand and supply of the public transit service. Second, we developed geospatial models to account for spatial bias in transit equity analysis. Results showed little evidence of inequitable access to LRT stations in Salt Lake County. The accessibility to LRT stations appeared to be generally higher in the downtown and transit catchment areas with a higher concentration of low-income and ethnic minority populations. Furthermore, we found statistically significant associations between higher transit accessibility and households which are not homeowners, and/or do not own a private motor vehicle. Our findings suggest that transit investments in Salt Lake County could leverage substantial transportation accessibility opportunities to achieve an equitable and sustainable future.

Impact of extreme wildfires from the Brazilian Forests and sugarcane burning on the air quality of the biggest megacity on South America

Recently, extreme wildfires have damaged important ecosystems worldwide and have affected urban areas miles away due to long-range transport of smoke plumes. We performed a comprehensive analysis to clarify how smoke plumes from Pantanal and Amazon forests wildfires and sugarcane harvest burning also from interior of the state of São Paulo (ISSP) were transported and injected into the atmosphere of the Metropolitan Area of São Paulo (MASP), where they worsened air quality and increased greenhouse gas (GHG) levels. To classify event days, multiple biomass burning fingerprints as carbon isotopes, Lidar ratio and specific compounds ratios were combined with back trajectories modeling. During smoke plume event days in the MASP fine particulate matter concentrations exceeded the WHO standard (>25 μg m−3), at 99 % of the air quality monitoring stations, and peak CO2 excess were 100 % to 1178 % higher than non-event days. We demonstrated how external pollution events such as wildfires pose an additional challenge for cities, regarding public health threats associated to air quality, and reinforces the importance of GHG monitoring networks to track local and remote GHG emissions and sources in urban areas.

Analyzing the Challenges for Future Smart and Sustainable Cities

The fast growth of the urban population increases the demand for energy, water, and transportation, amongst other needs. This study explores the current state and future scenarios of Smart Cities and the environmental, economic, and social challenges that must be overcome. We used the Rapid Review method to understand the challenges of implementing Smart Cities in different urban contexts and the potential impact of research on Smart City planning in future Smart Cities. The study offers insights into the potential for Smart City growth while identifying obstacles that must be addressed to ensure sustainability. Results serve as a foundation for planning and decision-making, highlighting aspects such as the adoption of alternative energies, reduction in car use, preservation of ecosystems, waste reduction, citizen participation, infrastructure, and citizen data privacy, among others. These aspects are essential to overcome obstacles and promoting Smart Cities’ development.

Identification of Critical Road Links Based on Static and Dynamic Features Fusion

Traffic congestion is a significant challenge in modern cities, leading to economic losses, environmental pollution, and inconvenience for the public. Identifying critical road links in a city can assist urban traffic management in developing effective management strategies, preserving the efficiency of critical road links, and ensuring the smooth operation of urban transportation systems. However, the existing road link importance evaluation metrics mostly rely on complex network metrics and traffic metrics, which may lead to biased results. In this paper, we propose a critical road link identification framework based on the fusion of dynamic and static features. First, we propose a directed dual topological traffic network model that considers the subjectivity of road links, traffic circulation characteristics, and time-varying characteristics, which addresses the limitations of existing traffic network topology construction. Subsequently, we employ a novel graph representation learning network to learn the road link node low-dimensional embeddings. Finally, we utilize clustering algorithms to cluster each road link node and evaluate critical road links using the average importance evaluation indicator of different categories. The results of comparison experiments using real-world data demonstrate the clear superiority and effectiveness of our proposed method. Specifically, our method is able to achieve a reduction in traffic network efficiency of 70–75% when less than 25% of the road links are removed. In contrast, the other baseline methods only achieve a reduction of 50–70% when removing the same proportion of road links. These findings highlight the significant advantages of our approach in identifying the critical links.