Mid-sized City Research Articles

The Narrative Identity of European Cities in Contemporary Literature

This volume aimed to highlight narrative identities of European cities or city neighbourhoods that have been overlooked, such as mid-sized cities. These cities are neither small towns nor metropolises, cities that are now unveiling their appeal or specificity. The present special issue thus covers a range of representations of cities. The articles investigate more systematically how different texts deal with various cities from different experiential and fictional perspectives. The issue covers the geographical scope across Europe, from east to west or vice versa, as well as a range of different works of national literature(s), but with a clear emphasis on mid-sized European cities that have until now been deemed as lesser-known, secondary, peripheral, ‘other’ cities that are in the focus of the research of the COST project Writing Urban Places. New Narratives of the European City, within which this journal issue is being published.

The legitimacy of sub-municipal councils in small and mid-sized cities under post-socialist conditions

Sub-municipal spatial community-based bodies, represented in the form of councils, have important roles in urban governance in many countries. This paper attempts to contribute to a better understanding of the legitimacy of sub-municipal councils (SMCs) in the specific conditions of small and mid-sized cities, within the context of democratising post-socialist society and decentralising government. Using the questionnaire and additional local resources, we discuss a selected set of relevant components of the legitimacy of SMCs, such as the traditions of their existence, legal and democratic grounds, autonomy, personal qualities, expertise, procedural issues, results and stability. We document these issues pertaining to the case of SMCs in small and medium-sized cities in Slovakia, emphasising the need for more components of legitimacy for their stable existence, with the strong impact of local traditions, legal framework development and incorporation into local representative democracy bodies.

Preface: The Narrative Identity of European Cities in Contemporary Literature

Preface: The Narrative Identity of European Cities in Contemporary Literature

Estimating Travel Demand with a Multimodal Transport Model Including E-Scooters in Iași, Romania

Cities, even medium-sized and small ones, have become overwhelmed by traffic and congestion. Innovative solutions are required and recent studies have focused on sustainable approaches. This study aims to develop a multimodal transport model consisting of an urban public transportation (UPT) service combined with an e-scooter sharing service. The main purpose of the model is a comparison between two travel alternatives (car and UPT + e-scooter), calculating their associated levels of utility. The methodology is based on a multinomial logit model, implemented in Matlab software, using results from an online mobility survey (socio-economic characteristics of potential users of e-scooters). The additional aim is related to the assessment of the inhabitants’ availability to shift from car to multimodal service or to simple e-scooter service. The developed micromodel was applied in Iași, a mid-sized city located in the northeast of Romania. Several price strategies were analysed in order to find their influence on users’ mobility behaviour. It turned out that the price for the shared e-scooter is too high at this moment to be used for daily travel. Without a price decrease and public authorities’ involvement in facilitating the multimodality, the e-scooter remains only an entertainment activity.

How daily activities and built environment affect health? A latent segmentation-based random parameter logit modeling approach

Transport studies have recently started focusing on the link between activity participation and general health. This study explores the relationship between general health and travel activities, physical activity, and built environment attributes. Individuals’ self-rated health is considered a general health indicator. Using data from the Impacts of Bicycle Infrastructure in Mid-sized Cities (IBIMS) survey of Kelowna, British Columbia, Canada, this study develops a latent segmentation-based random parameter logit (LSRPL) model. The motivation for adopting the LSRPL model is to capture multi-dimensional heterogeneity by allocating individuals into discrete latent segments (inter-segment heterogeneity) and then allowing a continuous distribution of the parameters within the segments (intra-segment heterogeneity). The model is estimated for two segments where segment one includes younger suburban dwellers; segment two includes older urban dwellers. The model results confirm the effect of travel, physical activity, and built environment on general health revealing multi-dimensional heterogeneity. In the case of inter-segment heterogeneity, results confirm that a higher share of travel duration using a car reduces the likelihood of excellent health in segment one. In contrast, a positive relationship is found in segment two. Whereas, for intra-segment heterogeneity results reveal that, a higher commute duration is found to be negatively associated with good health in segment two. However, this variable shows higher heterogeneity in mean for land use mix index, which indicates that urban areas coupled with higher land use mix increase the propensity towards good health. These findings will assist in developing transportation policies and investment decisions to build healthier cities.

Perspectives on food safety across traditional market supply chains in Nigeria

Food supply chains play a key role in ensuring food safety, as actions anywhere along the chain can impact the safety of food when it arrives at markets and in homes. However, pre-retail food supply chains are often understudied and receive limited policy attention; most work on food safety focuses on the retail or consumer level. This study helps fill these gaps by examining perceptions and actions related to food safety among the supply-chain actors who provide food to traditional markets in Birnin Kebbi, a mid-sized secondary city in northern Nigeria. Data were collected through extended in-depth interviews with producers, processors, transporters, storage providers, and wholesalers of six food commodities (including legumes, grains, vegetables, and animal-source foods). With some diversity depending on the commodity, the study found supply chain actors share similar motivations and challenges. All supply chains were dominated by men, and children were found to play a non-negligible role in supporting supply chain activities (e.g., loading vehicles). Interviewees generally had a limited conception of food safety hazards and little worry about the food they sold/handled being unsafe and were confident that they could detect food safety/quality issues through simple (mostly visual) signs. Interviewees generally reported that their clients had little concern about food safety or interest in discussing it. Worries related to price fluctuations and limited perception of their responsibility emerged as barriers to supply chain actors’ adopting food safety practices. These barriers seemed highest for transport providers, who stood out as being less well organized into associations; less vested in and knowledgeable about particular commodities; and feeling particularly little responsibility for food quality/safety. The importance of repeat relationships of trust to maintain their livelihoods, strong social norms, and rapid uptake of an emerging safe-storage technology were all identified as factors potentially facilitating improved food safety. The results are discussed in the context of the literature to consider potential approaches and inroads for improving food safety along the supply chain in Nigeria, with potential lessons for LMICs more broadly.

Culturally Responsive Practices or Assimilation? Views and Practices on Linguistic Diversity of Community College Instructors Working with Multilingual Learners

Despite the recent growth of multilingual learners in community colleges, research is still scarce on how instructors perceive and interact with students institutionally classified as English as a second language (ESL). In this paper, I use racialization of language and culturally relevant pedagogy to explain how 6 instructors from first-year freshmen in a community college, serving a high percentage of immigrant multilingual learners, view, understand and operationalize culturally and linguistically responsive practices in their classrooms. I use a qualitative critical approach to analyze data from interviews, fieldnotes, and observations from a year-long study in a community college in a mid-sized city in the South of the United States. I show evidence of instructors’ views of students regarding their cultural, linguistic, educational, and class backgrounds. Findings suggest that even when instructors celebrate differences in the classroom and are aware of the cultural differences, their opinions, and academic expectations were sometimes focused on students’ lack of confidence to advocate for themselves and their failure to assimilate into the mainstream culture. Despite the best intentions, these expectations still enclosed assimilationist views of language and personhood that require students to communicate in ways that often resemble the American traditional monolingual college student. The study of language from a racial perspective can promote powerful ways to understand how institutions structure and operationalize services to multilingual learners; conscious changes in services may result in more equitable practices for these students.

Happiness, life satisfaction, and the greenness of urban surroundings

Cities’ environmental factors are pivotal for the quality of life of the population, and green space is increasingly recognized as a significant environmental factor in this regard. In this analysis, we study the contribution of green space to happiness in a mid-sized city in the Global South. We use a population survey and open satellite imagery to assess the relationship between self-reported happiness and the surrounding greenness of the respondent's place of residence while controlling for age, gender, and socioeconomic status. We measure surrounding greenness using the average NDVI value within different distances from the home address, calculated with open satellite imagery. The results show that age and surrounding greenness are significantly correlated with happiness, while the relationships with gender and socioeconomic status appear to be not significant. Our results indicate that increases of 10% in surrounding greenness at different distances from 100 up to 500 m increase the likelihood of self-reported happiness between 13% and 18%. When quality aspects of green areas are considered, they are also significantly correlated with happiness. This paper contributes to the knowledge of surrounding greenness and subjective well-being in one of the most urbanized regions in the world and promotes the discussion of well-being policies in urban planning. The results indicate that increasing surrounding greenness and its quality in dense urban environments could help to improve the quality of life and well-being of the urban populations in Global South cities like Cali.

Mental Health and Health-Related Quality of Life After Firearm Injury: A Preliminary Descriptive Study.

Mental Health and Health-Related Quality of Life After Firearm Injury: A Preliminary Descriptive Study.

A mission perspective on emissions reduction at the city level: the case of Glasgow, Scotland

ABSTRACT City leaders around the world are setting ambitious targets for emissions reductions. Yet the pathway to achieving this remains largely unspecified. Starting with this objective, the paper explores the merits of deploying a mission-oriented framework within the context of a ‘wicked problem’ by looking at a mid-sized city, Glasgow, which has a target for net zero by 2030. Focusing on themes drawn from one high-emitting sector – transport – the paper points to the real-world policy implications that stem from such a mission-oriented approach to suggest aspects of the approach that may be usefully developed further. The latter hinges on a-priori considerations given to: agency, boundaries and inter-temporality, leading to questions about the nature and scope of wickedness and argues that core issues of wickedness – uncertainty, contestation and complexity – can be amplified in local and multi-layered policy making contexts.

Sentinel satellite data monitoring of air pollutants with interpolation methods in Guayaquil, Ecuador

In Ecuador, there is a limitation on air quality monitoring due to the cost of monitoring networks. Although air quality monitoring stations are instruments for air measurement, they do not cover an entire city due to their scope. Satellite remote sensing is now an effective tool to study atmospheric pollutants and has been applied to continuously assess a region and overcome the limitations of fixed stations. Despite the application of satellite data for air quality monitoring, there are some limitations, such as measurement frequency, cloud cover and wide spatial resolution, which do not allow the assessment of air pollution in cities. Therefore, downscaling, applying interpolation methods, is essential for continuous air quality monitoring at smaller scales. For this research, Nitrogen Dioxide (NO2) data from the Sentinel-5 satellite percussor was used in the city of Guayaquil for January–December 2020, which is considered before, during and after the COVID-19 quarantine. This mid-size port city does not have a permanent monitoring network, which prevents us from knowing the air quality. Due to the limitation of pixel size, this study used satellite data to apply interpolation techniques and reduce pixels to assess air quality. Two categories of interpolation were selected: deterministic and stochastic. The empirical Bayesian kriging (EBK) interpolation obtained a R2 of 0.9546, which was superior to the other methods applied. Therefore, the EBK method had the best accuracy for tropospheric NO2 concentration. Finally, the method used in this research can help monitor air quality in cities lacking continuous monitoring networks, as the reduction of the pixel size gives us a better pattern of pollutants.

Towards an automated image-based estimation of building age as input for Building Energy Modeling (BEM)

Today's methods for data acquisition usually involve a considerable amount of manual work and, depending on the level of detail, must find a compromise between accuracy and workload. As a result, various typologies of building stocks have been developed. These typologies provide engineers and architects with rough descriptions for classifying buildings into certain periods and construction types. However, real-world applications lack objective decision-making, as these classifications are usually conducted by manual investigations of buildings. To overcome this subjective approach and to ensure the reproducibility of data acquisition, this paper proposes an image-based classification using Deep Learning (DL) methods. We present the acquisition of ground truth and describe the training and testing routines on a dataset of 5,307 images obtained in the city of Weimar (located in the Free State of Thuringia, Germany), a mid-sized city representative of eastern Germany. All building images are linked to an existing building typology, allowing a classification of buildings in ten predefined and acknowledged periods. These periods are ranging from pre-1859 to post-2002. As a benchmark, an expert human baseline is acquired, showing a lower prediction accuracy than the results obtained by DL methods. Our results highlight the potential for automation in image analysis and beneficial impacts for Building Energy Modeling (BEM) on urban scale. Thus, a trustworthy data acquisition regarding the building age holds benefits for various stakeholders in BEM (engineers, architects, policymakers as well as customers).

City-scale model for COVID-19 epidemiology with mobility and social activities represented by a set of hidden Markov models

Background and objectiveSARS-CoV-2 emerged by the end of 2019 and became a global pandemic due to its rapid spread. Various outbreaks of the disease in different parts of the world have been studied, and epidemiological analyses of these outbreaks have been useful for developing models with the aim of tracking and predicting the spread of epidemics. In this paper, an agent-based model that predicts the local daily evolution of the number of people hospitalized in intensive care due to COVID-19 is presented. MethodsAn agent-based model has been developed, taking into consideration the most relevant characteristics of the geography and climate of a mid-size city, its population and pathology statistics, and its social customs and mobility, including the state of public transportation. In addition to these inputs, the different phases of isolation and social distancing are also taken into account. By means of a set of hidden Markov models, the system captures and reproduces virus transmission associated with the stochastic nature of people's mobility and activities in the city. The spread of the virus in the host is also simulated by following the stages of the disease and by considering the existence of comorbidities and the proportion of asymptomatic carriers. ResultsAs a case study, the model was applied to Paraná city (Entre Ríos, Argentina) in the second half of 2020. The model adequately predicts the daily evolution of people hospitalized in intensive care due to COVID-19. This adequacy is reflected by the fact that the prediction of the model (including its dispersion), as with the data reported in the field, never exceeded 90% of the capacity of beds installed in the city. In addition, other epidemiological variables of interest, with discrimination by age range, were also adequately reproduced, such as the number of deaths, reported cases, and asymptomatic individuals. ConclusionsThe model can be used to predict the most likely evolution of the number of cases and hospital bed occupancy in the short term. By adjusting the model to match the data on hospitalizations in intensive care units and deaths due to COVID-19, it is possible to analyze the impact of isolation and social distancing measures on the disease spread dynamics. In addition, it allows for simulating combinations of characteristics that would lead to a potential collapse in the health system due to lack of infrastructure as well as predicting the impact of social events or increases in people's mobility.

Access to Care and Therapy for Kawasaki Disease in the Arab Countries: A Kawasaki Disease Arab Initiative (Kawarabi) Multicenter Survey.

Kawasaki Disease (KD) is still the most common acquired heart disease in children below the age of five years; it has been well described in the developed world; however, data from the Arab world are limited to case reports or single-center case series. In an effort of optimizing KD research in the Arab world, a group of physicians and researchers established the KD Arab Initiative (Kawarabi) in 2021, and published the first survey, which showed disparities in the availability of intravenous immunoglobulin (IVIG); this had prompted Kawarabi to assess the access to care and therapy of KD patients in Arab countries. A 32 structured questions survey was conducted in thirteen Arab countries and addressed KD patients' access to healthcare in urban and rural settings. The survey results showed that access to care was uniform across large, mid-size cities and rural areas in 7/13 (54%) countries, while in 6/13 (46%) countries, it was in favor of large and mid-size cities over rural areas. The quality of medical services received by children with KD in large cities was rated as excellent in 6/13 or good in 7/13 countries compared to fair in 4/13 or poor in 4/13 countries in rural areas. Availability of IVIG was limited (23%) in mid-size cities and almost impossible (23%) in rural areas. The KD patients in mid-size cities and rural areas have limited access to standard healthcare in the Arab world. This survey laid the foundation for future Kawarabi endeavors to improve the care of children with KD.

Assessing the leapfrogging potential to water sensitive: the Dutch case of Zwolle

Abstract Urban floods can cause significant damage and are expected to become more common due to climate change. Previous research has identified that climate change adaptation in cities requires the development of blue-green infrastructure (BGI), and it is expected that cities can leapfrog to a water-sensitive state by implementing BGI. However, leapfrogging is context-dependent, and little is known about how governance factors affect leapfrogging, particularly in midsize cities. This paper addresses this knowledge gap, providing empirical insights into leapfrogging by assessing the governance factors that support or restrict BGI implementation in Zwolle (The Netherlands) towards reaching a water-sensitive state. For the analysis, we employ a governance assessment tool and three catalytic factors that promote leapfrogging. The results show that the governance context supports leapfrogging at a moderate to high level. This means that while the governmental levels and stakeholder networks collaborate to support climate change adaptation of the city, new legislation on BGI and citizens’ involvement in climate change adaptation projects could increase the leapfrog possibilities for Zwolle in achieving its goal of becoming climate-proof by 2050.

Modelling climate analogue regions for a central European city

In this study, we describe a methodology to derive climate analogue cities for spatially highly resolved future climate scenarios. For the computation, a reduced and in hindsight bias-adjusted EURO-CORDEX EUR-11 dataset is used based on two climate scenarios (RCP4.5 and RCP8.5). A total of 389 European cities are processed by the algorithm, which uses five statistical climate variables (2-m air temperature average and amplitude, precipitation sum and amplitude, correlation between 2-m air temperature average and precipitation sum). Additionally, extreme weather events (hot days, summer days, tropical nights, extreme precipitation events) are calculated for further comparison and validation. Finding an appropriate analogue permits a more accurate derivation and depiction of necessary climate adaptation efforts and therefore assist decision-making in city planning. As an example of our method, we searched for plausible climate twins for the mid-sized city of Aachen (Germany) at the end of the twenty-first century. Our results show that the French city of Dijon is highly likely to become Aachen’s climate twin by the end of the century for RCP4.5. As for the scenario RCP8.5, no clear European analogue city could be determined, indicating that the city might enter a novel climate. The nearest match suggests the cities of Florence and Prato in Tuscany. However, considering climate indices, the encompassing region of the French–Spanish city triangle Bordeaux–Toulouse–Bilbao is a better fit. The developed algorithm can be applied to any of the cities included in the dataset.

Applying a Critical Policy Lens to Contracting in Indigenous Mental Health: An Ethnographic Study with Urban Indigenous Providers

This article reports on the findings of a larger study that explored urban Indigenous providers’ experiences with contracting in mental health and addictions care. The study was undertaken with seven Indigenous and one non-Indigenous non-profit organizations based in diverse large and mid-size cities (off reserve) in British Columbia, Canada. Indigenous and critical theoretical perspectives provided the lens for this ethnographic inquiry. In-depth interviews were the primary data source. Participants’ narratives provide an account of the ideological embeddedness of contracting and how a New Public Management operates to perpetuate colonial power imbalances and structural barriers to culturally safe and equity-oriented care within urban Indigenous communities. Policy and practice implications for government funders are discussed.

“Not as Bad as the ‘90s”? Firearm Violence in Small, Mid-Size, and Large US Cities, 2015–2021

I examine firearm homicide and injury data from more cities ( N = 1,328) during a longer timespan (2015–2021) than previous research on firearm violence encapsulating the Covid-19 pandemic. I contextualize the historic 2020 spike in gun violence within a broader trend of worsening gun violence impacting hundreds of US cities since 2015. More cities (364) are surpassing adverse homicide rate benchmarks observed during the 1980s–1990s, and US states situated in all regions contain numerous peak gun violence cities. Examining gun violence trends outside of the largest US cities is imperative, since 42% of all firearm homicides occur in places with populations <250,000, and over two-thirds of peak violence cities (243) have fewer than 100,000 residents. A shared sense of the scope and severity of the problem of gun violence is also urgently needed. For too many American communities, it’s not as bad as the 1990s, it’s worse.

MONITORING THE ENVIRONMENT IN SMART CITIES: THE IMPORTANCE OF GEOSPATIAL LOCATION REFERENCING

Abstract. The Smart City concept is taking momentum recently as big metropolises as well as mid-size cities are intensifying their efforts to improve the life of people living in dense urban environment. Local governments are eager to have up-to-date information of every aspect of city life, including environmental data, such as air and water quality parameters; mobility data, such as traffic flow, including vehicles, transit passengers; crowd control, such as public events, mobility in hospitals; life quality data, such as social status, education level, health records; etc. Monitoring all these very different data streams in space and time is a formidable challenge. While on the data acquisition side, tremendous progress has been achieved, as sensors have been deployed in increasingly large numbers on both mobile and static platforms, there is a lack of creating accurate geotags, as the quality of georeferencing varies over a large scale. It is important to note that the data acquisition is becoming largely customer-based, as smart devices are efficient sensor systems and with advancing communication technologies, crowdsourcing is quickly becoming the dominant data source on mobile platforms. In this paper, we investigate the potential to exploit the ranging capabilities of imaging and communication sensors and use the strength of the spatial network formed by the sensors to improve the georeferencing of a group of platforms operating in a close environment, such as UAS swarm or a platoon of autonomous vehicles. Transportation in cities and in general mobility are of great interest to Smart Cities, they represent one of the most significant components of the activities, so having an optimized transportation system is essential to reduce carbon footprint, decrease commute time, and just improve the quality of life. To assess the performance of collaborative navigation based accurate georeferencing, data was acquired at a simulated intersection area at The Ohio State University, where multiple vehicles, pedestrians and cyclists were moving around. In addition, drones were flying above the area. Here we report about our initial results.

Environmental and economic outlook of construction and demolition waste management practices in a mid-sized city

Environmental and economic outlook of construction and demolition waste management practices in a mid-sized city