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Urban artificial surfaces and structures induce modifications in land–atmosphere interactions, affecting the exchange of energy, momentum, and substances. These modifications stimulate urban climate formation by altering the values and dynamics of atmospheric parameters, including cloud-related features. This study evaluates the presence and quantifies the extent of such changes over Sofia, Bulgaria. The findings reveal that estimations of low-level cloud base height (CBH) derived from lifting condensation level (LCL) calculations may produce unexpected outcomes due to microclimate influence. Ceilometer data indicate that the CBH of low-level clouds over urban areas exceeds that of surrounding regions by approximately 200 m during warm months and afternoon hours. Moreover, urban clouds exhibit reduced persistence relative to rural counterparts, particularly pronounced in May, June, and July afternoons. Reanalysis-derived low-level cloud cover (LCC) shows no significant disparities between urban and rural areas, although increased LCC is observed above the western and northern city boundaries. Satellite-derived cloud products reveal that the optically thinnest low-level clouds over urban areas exhibit slightly higher cloud tops, but the optically thickest clouds are more prevalent during warm months. These findings suggest an influence of urbanization on cloudiness, albeit nuanced and potentially influenced by the city size and surrounding physical and geographical features.

Abstract This study aims at assessing the impact of compost application on the physical (porosity, volumetric-moisture and bulk density) and the chemical traits of soil (pH, organic carbon, electrical conductivity, cation exchange capacity and soil nutrients) on the leaf nutrient concentration and growth (height, diameter, new leaf-structures and chlorophyll content) of five native species used in urban forestry. Using a two-way factorial design, we evaluated three substrates: i) Soil (ii) Soil-compost mixture SC-12.5 (12.5 % compost (v/v)) (iii) Soil-compost mixture SC-25 (25 % compost (v/v)) and five species: Retrophyllum rospigliosii, Inga edulis, Citharexylum montanum, Caesalpinia spinosa, and Citharexylum sulcatum. We found that SC-25 and SC-12.5 increased the electric conductivity, cation exchange capacity, organic carbon, and soil base saturation. Moreover, compost addition increased the growth of the five native species evaluated. Such results suggest that compost-application is a viable option to improve soil fertility and promote the growth of native trees.

The article is a review of the part of the research conducted in the framework of the grant of the Russian Foundation for Basic Research “Urban well-being of people with disabilities”. The immediate subject of the article is professional self-realization as a factor of urban well-being of a person with a disability. Well-being is understood as a subjectively constructed phenomenon, that is, through the prism of people with disabilities’ own perceptions of the sufficiency of conditions created in the urban environment for their professional self-realization and, as a consequence, for well-being in general. Professional self-realization has become one of the six factor groups that directly or indirectly influence the urban well-being of citizens with disabilities. Along with professional self-realization, the factors of urban well-being in the framework of the study were: trust in the government and involvement in management processes; the level of implementation of basic values; psychological comfort; accessibility of the spatial environment; and finally, the quality of social services. The five factor groups listed above are not discussed in the article, but the reader should have an idea of the context in which professional self-realization is studied. The study included two sub-samples, reflecting the specifics of a megalopolis (Moscow) and a regional center (Saratov).

This paper examines how visual narratives of Egypt’s class politics over the past decade have problematized contemporary urban configurations and socio-spatial ordering. Following the 2011 political rupture, multiple class imaginaries have emerged, intricately linked to the country’s newly reconfigured political economy. Recent state policies have systematically marginalized the middle classes by tightening political control and exacerbating economic pressures, thereby foreclosing avenues for civic agency. Conversely, affluent groups have consolidated their presence in urban politics, shaping emergent spatial dynamics, while underclasses have sustained resilience through localized knowledge networks and grassroots resources. Within this contested landscape, the paper explores creative dissent schemes as sites where class interplay and state–citizen relations are visually negotiated. In these schemes, the city appears devoid of its middle classes, represented instead as a polarized environment housing only the wealthy and the destitute. This phenomenon is conceptualized as the agency of the invisible middle classes. Drawing on in-depth interviews and visual ethnographic methods, the paper seeks to reintegrate questions of class, representation, and agency into broader debates on urban politics. Preliminary conclusions are drawn toward mapping the middle class(es) in post-revolutionary Egypt, highlighting how their visual erasure both reflects and reinforces broader structures of exclusion and dissent.

Širitev Evropske unije pomeni pomembno spremembo dosedanjega funkcionalnega teritorialne zgradbe Evrope. Globalne politične posledice so pretežno znane, težave, ki so hkrati priložnosti regionalnega in lokalnega razvoja, pa dobivajo stvarne razsežnosti. Predmet prispevka je podeželsko območje severovzhodne Avstrije, na katero vplivajo funkcijsko-gravitacijski suburbanizacijski učinki glavnega mesta sosednje države, kjer nastaja rastoča bratislavska aglomeracija.

As smart city development deepens, its impact on the urban-rural income gap has become a key concern for both the government and society. This article uses panel data from Chinese prefecture-level cities between 2010 and 2022, treating the pilot smart city policy as a quasi-natural experiment, and applying a multi-period difference-in-differences (DID) method to empirically examine how smart city construction affects the urban-rural income gap. It also analyzes the role of economic agglomeration in this process. The research indicates that smart city development has significantly increased the incomes of urban and rural residents and has positively contributed to sharing development benefits between these areas. Mechanism analysis shows that economic agglomeration plays an important mediating and threshold role—smart cities indirectly influence the urban-rural income distribution by fostering economic agglomeration, with this effect showing nonlinear characteristics at different levels of agglomeration. Based on these findings, the article proposes policy recommendations aimed at optimizing economic agglomeration models and advancing urban-rural integrated development, offering theoretical insights and practical strategies for narrowing the income gap and promoting common prosperity.

Teaching civil engineers of the future the planning, design and construction of sustainable urban infrastructure systems is a multifaceted challenge. This paper presents case studies from two universities in the United Kingdom that design and deliver teaching modules in sustainable construction. The case studies presented here are integral to the curriculum design and delivery of a module entitled ‘Sustainable Construction’ offered to the first year undergraduate students registered at Teesside University and another, multidisciplinary design module called ‘Design of Sustainable Engineering Systems2 (DSES2)’ offered to the second year civil engineering students at Newcastle University. The academic institutions and the engineering professions as a whole have sincere intentions of imparting intellectual and technical capabilities consistent with Sustainable Design (SD) and so they must invest in the creation of learning environments that are appropriate for Sustainable Design education. The universities owning the modules presented in this paper have recognized the challenges associated with the delivery of SD skills among their students. This appreciation of the difficulties led them to innovate and as a result they were able to introduce novel changes to the curriculum delivery of civil engineering programmes. The authors for this paper have been using a range of different pedagogic strategies including problem-based, design-based and self-directed learning methods in their efforts to deliver SD concepts in urban environments. Particular attention is paid to the epistemic methods that are transferable in nature and can be implemented by other academic institutions delivering Sustainable Design education to their students from science and engineering degree programmes.

This research was focused on the 'receiver' end of the supply chain that has, in recent years, emerged as a novel area of investigation by European urban freight researchers. The paper explores the importance of procurement policy and mechanisms in a higher education establishment in order to drive a sustainable approach to inbound logistics. There is little known of the purchasing behaviour at individual level within such organisations. A localised city logistics Delivery Service Plan, within a 'coherent campus strategy' for an academic campus was established at Newcastle University, located at the centre of a medium size British city. Purchasing data and interviews with the purchasing manager demonstrated the current state of purchasing practice at the University, relative to the benchmarks established in the literature. In order to better understand the relationships between delivery services, the urban environment, and staff attitudes, a questionnaire was conducted with Newcastle University staff, addressing the purchasing of all goods to be delivered to the workplace. Multivariate analysis of cross-sectional data, as well as qualitative analysis, shows that variable frequency in demand can be explained by: job type; the different ways to raise a purchase order (PO); type of goods purchased; expected delivery times; and from where the PO originates. The findings suggest that training within specific staff roles would benefit the University's urban freight coordination and management. We can also see that a very small core of people raise most of the orders and that, through them, it should be possible to influence the majority of orders. Lastly, demonstrating to the University's Executive that employee views on private purchasing directly influence the practice, has convinced the board that changing purchasing behaviour towards freight efficiency is a feasible option for a sustainable institutional organisation.

Delineating urban functional use plays a key role in understanding urban dynamics, evaluating planning strategies and supporting policymaking. In recent years, Points of Interest (POI) data, with precise geolocation and detailed attributes, have become the primary data source for exploring urban functional use from a bottom-up perspective, using local, highly disaggregated, big datasets. Previous studies using POI data have given insufficient consideration to the relationship among POI classes in the spatial context, and have failed to provide a straightforward means by which to classify urban functional areas. This study proposes an approach for delineating urban functional use at the scale of the Lower Layer Super Output Area (LSOA) in Greater London by integrating the Doc2Vec model, a neural network embedding method commonly used in natural language processing for vectoring words and documents from their context. In this study, the neural network vectorises both POI classes (‘Word’) and urban areas (‘Document’) based on their functional context by learning features from the spatial distribution of POIs in the city. Specifically, we first construct POI sequences based on the distribution of POI classes, and add their LSOA IDs as ‘document’ tags. By utilising these constructed POI–LSOA sequences, the Doc2Vec model trains the vectors of 574 POI classes (word vectors) and 4836 LSOAs (document vectors). The vectors of POI classes are then used in calculating the functional similarity scores based on their cosine distance, with the vectors of LSOAs grouped into clusters (i.e., functional areas) via the k-means clustering algorithm. We also identify latent functions in each cluster of LSOAs by performing topic modelling and enrichment factor. Compared with TF–IDF, LDA and Word2Vec models, the Doc2Vec model obtains the highest accuracy when classifying functional areas. This study proposes a straightforward approach in which the model directly trains vectors for urban areas, subsequently using them to classify urban functional areas. By employing the enhanced neural network model with low-cost and ubiquitous POI datasets, this study provides a potential tool with which to monitor urban dynamics in a timely and adaptive manner, thereby providing enhanced, data-driven support to urban planning, development and management.