Search Results (633)

: Unitised integration is a management model used to address the fragmentation of multiple management entities in complex environments. Small- and medium-sized enterprise (SME) safety alliances play an important role in centralised management and cost reduction in the safety management of SMEs, which are large in number, widely distributed, and small in volume. On the basis of the investigation and analysis of the current situation of SMEs’ own safety management and external supervision, as well as the market situation of safety service institutions, this paper explores the fragmentation problem of SMEs’ safety management. An idealised framework for the unitised integration of safety management in SMEs is proposed theoretically, and the model is tested and its limitations are discussed through a field investigation of the operational mechanism and problems of the SME Safety Alliance in Pukou District, Nanjing City, China, taking the SME safety alliance as a case study, with a view to proposing policy recommendations for the optimisation and promotion of the model. The unitised integration of safety management can help promote the adaptation of safety service supply and demand, thereby reducing the cost of safety management for SMEs, promoting the effective implementation of the main responsibility for safety, alleviating the pressure of production safety supervision, and ultimately promoting the further improvement of safety supervision and management systems for SMEs. Full article

Exploring the characteristics of changes in cropland function trade-off and the influencing factors in highly urbanized areas can promote the synergistic development of urbanization and fine cropland management. Taking the Yangtze River Delta region as the study area, this paper developed a cropland function evaluation system from the production–ecology–living perspective, identified the spatial and temporal changes in cropland function trade-offs through Wavelet analysis and Root mean square error, and explored the driving factors of the trade-offs by using GeoDetector. The results indicated the following: (1) The cropland function in the Yangtze River Delta region has undergone a transition from a single production function to a composite function integrating ecology and life in conjunction with urbanization. The trade-offs between cropland functions are weakened, and the rate of decline from 2010 to 2023 is significantly higher than that from 2000 to 2010, and the characterization of cropland in different types of cities is revealed. (2) The turning points of cropland function trade-off changes in cities of different scales diverge, with the inflection points of small and medium-sized cities and large cities shrinking toward the center (decreasing from 42–48 km to 30–36 km), and metropolises showing an obvious trend of outward expansion (expanding from 42 km to 60 km). (3) The influence of natural and socioeconomic factors on cropland function trade-off intensity generally increases over time, with socioeconomic factors increasingly becoming significant drivers of the trade-off intensities. It is recommended that the study area focus on developing cropland characterization in different types of cities in the future, and continue to improve the degree of sharing the integration of profits from cropland functions, so as to promote optimal development. Full article

Disruptive events and the rapid evolution of urban energy systems highlight the need for robust methods to reconstruct critical infrastructure networks. Comprehensive, up-to-date power grid representations are essential for both researchers developing methods for analysing and optimising power systems and first responders requiring approximate data for urgent decisions. However, traditional grid reconstruction approaches often rely on incomplete data, expert knowledge, or closed datasets, limiting their utility during emergencies. This study proposes a novel automated method for reconstructing medium-voltage (MV) power grids. The novelty of the proposed method lies in combining OpenStreetMap energy and land-use data in a unified and automated framework, thereby reducing the need for expert input. The proposed method employs a systematic aggregation of data, an estimation of energy demand, and the application of algorithmic techniques to generate synthetic MV grid models that functionally represent real networks, capturing key topological features. The resulting outputs include visual representations to support decision-makers in simulating "what-if” scenarios and ensuring rapid operational awareness. In a step toward eliminating reliance on proprietary data, our approach broadens access to critical infrastructure insights across diverse urban contexts, contributing to critical infrastructure resilience and potentially supporting both energy system research and crisis management. A case study demonstrates that a medium-sized city’s MV grid can be reconstructed in minutes without expert knowledge or geographically constrained datasets, underscoring the method’s deployment potential and practical value for emergency scenarios. Full article

Background: Although screening for early signs of autism spectrum disorder (ASD) using the Modified Checklist for Autism in Toddlers (M-CHAT) has been recommended by the Brazilian Ministry of Health since 2014, the feasibility of this intervention and its effects in primary care have not been sufficiently investigated. Objectives: (1) to verify the feasibility of implementing the M-CHAT in the Brazilian Unified Health System, through routine childcare vaccination; (2) to evaluate the level of knowledge and practices of nursing professionals in Brazilian primary health care in relation to ASD to check the expertise to apply M-CHAT to verify early signs of this condition; (3) to verify, after implementation, the frequency of children with possible early signs of ASD using the M-CHAT. Methods: This is an observational, cross-sectional study conducted in a medium-sized city in southeastern Brazil. A total of 97 nursing professionals from 21 health facilities participated. The professionals answered a questionnaire on knowledge and practices regarding ASD, attended training on early signs of ASD and for the use of M-CHAT. Finally, they administered the M-CHAT to 267 parents of children aged 16 to 57 months in primary care settings. Results: Insufficient knowledge of ASD was identified among the nursing professionals evaluated. Approximately 80% agreed that the training was satisfactory, and 88% agreed that they felt competent to use the M-CHAT; 74% agreed with the benefits of using the M-CHAT to detect early signs of ASD in public health settings. However, 91% of the professionals reported that incorporating the M-CHAT into the day care routine overloaded their work, and less than 50% agreed that the instrument should continue to be used in the day care routine. Sixty-seven (25.09%) children screened positive for possible early signs of ASD by M-CHAT. Conclusions: The insufficient level of knowledge on ASD found among nursing professionals suggests gaps in Brazilian academic and professional training in this area. Although most participants recognized the importance of early detection of signs of ASD in primary care settings, the implementation of the M-CHAT in the routine primary care settings was not well accepted for most participants due to work overload, which indicates the need for public health policies to offer working conditions that minimize the overload of professionals, maintaining early screening interventions for ASD in Brazilian primary care institutions. Full article

This study investigated the relationship between surface meteorological variables and the levels of surface air pollutants (O₃, PM₁₀, and PM_2.5) in scenarios of simulated temperature increases in Rio Grande, a medium-sized Brazilian city with strong industrial influence. This study utilized five years of daily meteorological data (from 1 January 2019 to 31 December 2023) to model atmospheric conditions and two years of daily air pollutant data (from 21 December 2021 to 20 December 2023) to simulate how pollutant levels would respond to annual temperature increases of 1 °C and 2 °C, employing a Support Vector Machine, a supervised machine learning algorithm. Predictive models were developed for both annual averages and seasonal variations. The predictive analysis results indicated that, when considering annual averages, pollutant concentrations showed a decreasing trend as temperatures increased. This same pattern was observed in seasonal scenarios, except during summer, when O₃ levels increased with the simulated temperature rise. The greatest seasonal reduction in O₃ occurred in winter (decreasing by 10.33% and 12.32% under 1 °C and 2 °C warming scenarios, respectively), while for PM₁₀ and PM_2.5, the most significant reductions were observed in spring. The lack of a correlation between temperature and pollutant levels, along with their relationship with other meteorological variables, explains the observed pattern in Rio Grande. This research provides important contributions to the understanding of the interactions between climate change, air pollution, and meteorological factors in similar contexts. Full article

In the context of global climate change, carbon emission trading (CET) has become a critical tool for driving urban green economic transformation. Since 2011, China has launched CET pilot programs, supporting the achievement of the “dual carbon” goals. Studying the relationship between CET and urban green economic efficiency is essential for advancing urban green economic transitions. However, the existing research is limited by its single-perspective approach, insufficient exploration of mechanisms, and weak heterogeneity analysis, which restricts a comprehensivethe comprehensiveness of our understanding of policy effects. To address these gaps, this study is the first to integrate macro-regional data with micro-enterprise behavior, evaluating the impact of CET on urban green economic efficiency from a dual macro–micro perspective, thereby filling the research void in macro–micro data integration. At the macro level, this study employs panel data from 281 Chinese cities spanning 2007 to 2020, using fixed-effects and difference-in-differences (DID) models to assess the impact of CET on urban green economic efficiency. At the micro level, a game-theoretic pricing decision model is constructed to reveal behavioral differences among enterprises in complete and incomplete information markets and their indirect effects on green economic efficiency. The findings indicate that CET significantly enhances urban green economic efficiency, with technological innovation, green finance, and industrial structural upgrading serving as mediating mechanisms. Heterogeneity analysis shows that the effects are more pronounced in eastern, non-resource-based, small-to-medium-sized, and non-old industrial cities. The game-theoretic model further demonstrates that enterprises in complete information markets more effectively indirectly enhance green economic efficiency through CET mechanisms. By combining macro and micro perspectives, this study provides a new theoretical framework and practical insights for understanding the policy effects of CET. However, limitations such as data confined to Chinese pilots and model simplifications remain. Future research should expand data dimensions, allowing researchers to more comprehensively evaluate policy outcomes. Full article

This study examines urban structure typologies for small- to medium-sized cities in South Korea facing population decline, with a focus on urban compactness as a sustainable strategy. Population reduction and aging trends have become prominent issues in South Korea, especially impacting smaller cities, where decreased population density affects urban service functionality and infrastructure maintenance. This research applies and adapts Japan’s urban structure evaluation framework, specifically designed for the Japanese compact city model, to analyze the spatial conditions of 15 small- and medium-sized cities in Gyeongsangbuk-do province, South Korea. Using various indicators such as population density, accessibility to daily services, public transport, and local economic activity, this study conducts a typological classification based on principal component analysis and clustering methods. The findings suggest distinct urban structure patterns within these cities, offering strategic insights for urban policy aimed at enhancing urban compactness and sustainability. The implications highlight the need for tailored policies that address the spatial reorganization of services and infrastructure to maintain urban viability amidst demographic shifts. Full article

Exploring the urban spatial pattern and expansion characteristics of African countries under shared socioeconomic pathways (SSPs) is crucial to optimizing urban development in Africa and ensuring ecological sustainability. We use land and socioeconomic panel data and the least squares dummy variable regression method to predict the urban land increment in African countries from 2030 to 2060, we use the FLUS model to simulate the urban spatial layout in 2060, and we analyze from the perspective of the relationship between population density and urban expansion. The results show that the urban space of African countries will show a significant expansion trend from 2020 to 2060, with stronger growth under the SSP1 and SSP5 scenarios and relatively weaker growth under the SSP3 scenario; the urban land expansion patterns of different countries under different SSP scenarios are significantly different, and countries with rapid urbanization and economic growth are mostly urban patch agglomeration and extended expansion, while urban patches are relatively evenly distributed; a large number of cities in Africa show specific expansion patterns, with large cities mostly showing loose expansion and small- and medium-sized cities mostly showing compact expansion; and cities in different regions such as North Africa and sub-Saharan Africa have their own expansion characteristics in terms of population density and urban form. Our research provides important data support and inspiration for promoting the rational development of African cities and enhancing regional ecological resilience. Full article

Assessing water demand is essential for urban planning, aligning with socio-economic and climatic needs. The territorial water footprint identifies water requirements across sectors and detects sources of consumption. This aids in mitigating impacts and evaluating alternative water sources like reclaimed water. In Gavà, water impacts were assessed for residential, commercial, municipal, tourism, industrial, agricultural, and livestock sectors. The total water footprint is 6,458,118 m³, comprising 3,293,589 m³ from blue water, 2,250,849 m³ from green water, and 913,680 m³ from grey water. Agriculture (54.2%), residential (30.9%), and industrial activities (5.8%) are the main water footprint contributors. A key methodological advancement of this study is the refinement of grey water footprint calculations for livestock facilities within the RWF framework, allowing for a more precise assessment of their environmental impact. Integrating geographic information systems with land use mapping helps localize impacts, detect hotspots, and identify infrastructure improvement opportunities. Full article

Urban greenspaces, such as parks and other public vegetated spaces, provide respite from the built environment for residents and visitors. Lesser-known urban greenspaces are community-managed open spaces (CMOSs), such as play lots, community gardens, and memorial gardens. This study investigated the effect of the distance to and size of parks and CMOSs on residential house prices in Baltimore, MD, in 2016–2017 using a hedonic price model. This is the first study of an urban city comparing parks and CMOSs. The study included 21,116 houses sold and revealed that park proximate price premiums ranged from 7.73% to 11.01% for distances of up to a 1/2 mile, and the CMOS proximate price premiums were 8.69% and 8.96% for distances of up to 1/8 and 1/4 miles, respectively. Moreover, both parks and CMOSs revealed a buyer preference of a 1/8 to 1/2 mile distance from these urban greenspaces. Small- to medium-sized parks, less than 9.65 acres, increased house prices by approximately 2.36%, and small CMOSs, less than 0.24 acres, increased house prices by 5.93%. These results confirm that parks and CMOSs provide economic benefits in addition to their social, health, and well-being benefits and suggest that CMOSs are a viable economic development strategy for communities. Full article

In the Beijing–Tianjin–Hebei urban agglomeration—one of China’s three largest city clusters, the GDP reached CNY 950 billion with a population of approximately 110 million in 2021. While megacity expansion has slowed, rapid growth in small and medium-sized cities is expected to increase their vulnerability to urban heat island (UHI) effects. This necessitates urgent, size-differentiated studies of the UHI to inform sustainable urban planning. This study examines the Beijing–Tianjin–Hebei urban agglomeration using Landsat 8 data to explore the UHI between different-sized cities and analyze the driving mechanisms of UHI intensity attributed to urban buildings. The results indicate the following: (1) Beijing displays the smallest temperature change (1.39 °C) and lower heating effect intensity (484.44 km² °C) compared to Shijiazhuang (919.11 km² °C); (2) a logarithmic relationship (R² = 0.4261) exists between the building volume and heating effect intensity, and the specificity of megacities significantly influences the regional analysis results of the heat island effect; and (3) the total energy consumption power of the heating effect in 10 cities within the Beijing–Tianjin–Hebei region is 326.23 × 10¹² KJ/h, which is equivalent to 11.14 × 10⁹ kg/h of standard coal. Full article

The primary aim of this study was to evaluate the spatial and temporal variation in human exposure to electromagnetic fields across different frequency bands within an urban area identified as the commercial zone of a medium-sized city. Central to this investigation was the use of an exposimeter, strategically positioned on the back of the operator and secured to the hip area via a belt, to ensure comprehensive and accurate field measurements. An initial analysis was conducted to determine the shielding coefficients of the human body, allowing for precise corrections of the electric field values used in the spatial assessment. To map power density across the study area for each frequency, kriging interpolation was applied. Furthermore, temporal variations in exposure levels were analyzed at three distinct times of day—morning business hours, afternoon business hours, and non-business hours—using robust statistical methods. The study’s innovative approach lies in the integration of GIS technology to uncover and visualize temporal patterns in exposure, particularly during periods of higher pedestrian density. This integration facilitated both the detection of temporal variations and the spatial representation of these changes, enabling rapid identification and assessment of exposure hotspots. Full article

This is the first study to analyze the coverage and profile of establishments registered on a meal delivery application (MDA) in small and medium-sized cities in Brazil. The app serves 497 municipalities across 22 states, offering 28,325 establishments. App coverage was measured as the ratio of cities served to the total small and medium-sized cities in each Brazilian region. The establishments were categorized using keyword analysis into six groups: International Cuisine, Snacks, Bakery Products, Complete Meals and Side Dishes, Sweets, Ice Creams and Desserts, and Healthy Options. Greater app coverage was observed in the South (13.68%) and Southeast (13.63%) regions. In contrast, lower coverage was noted in the North (2.46%) and Northeast (2.30%) regions. The keyword category ‘Snacks’ was the most used across all Brazilian regions, while ‘Healthy Options’ was the least utilized. Positive correlations were identified between the number of establishments on the app and the Municipal Human Development Index (r = 0.30; p < 0.001), demographic density (r = 0.23; p < 0.001), and urban population (r = 0.55; p < 0.001). The use of keyword categories varied across municipalities based on their demographic and socioeconomic characteristics. Our findings reveal significant asymmetries in app coverage and the types of registered establishments, which may further exacerbate inequalities in food access. Full article

Improving road safety is a major challenge for urban administrations due to the high frequency of accidents and their associated social costs. This study presents a methodology that combines historical accident data analysis with a proactive risk assessment approach to enhance decision-making in road safety planning. Using the International Road Assessment Programme (iRAP) and Geographic Information Systems (GIS), the proposed framework identifies high-risk locations and estimates the benefits of planned safety interventions. A key innovation of this methodology is the integration of cost–benefit analysis to prioritize interventions, ensuring optimal resource allocation. The approach was tested in a medium-sized Italian city where it helped identify critical areas and assess the potential impact of various safety measures, such as intersection redesign and traffic-calming strategies. The results demonstrated a significant potential to reduce accidents and associated social costs, offering a scalable model for urban road safety planning. By integrating data-driven insights with proactive evaluation, this methodology supports urban administrations in implementing effective, targeted interventions that contribute to Vision Zero goals. Full article

In many countries located in Central–Eastern Europe, there is a need for heating in the autumn and winter seasons. In Poland, this has been met over the years, mainly through the development of centralized heating systems. The heat sources in such systems are based on fossil fuels like coal or gas. New regulations and climate concerns are forcing a transformation of existing systems towards green energy. The research presents two scenarios of such a change. The first focuses on maintaining centralized heat sources but increases the share of renewables in the heat supply. This can be realized by weather-independent, high-power sources such as biomass boilers and/or high-temperature heat pumps (HP) such as sewage heat pumps or ground source HP. The second scenario changes the location of the heat sources to more dispersed locations so that the unit power can be lower. In this case, renewable heat sources can be used at favorable locations in the system. Among the sources included in this scenario are solar panels, photovoltaic panels, micro wind turbines, and ground source heat pumps with local heat storage. These are characterized by low energy density. Their dispersion in the urban space can contribute to the desired energy generation, which would be impossible to achieve in the centralized scenario. Furthermore, the transmission losses are lower in this case, so lower heating medium temperatures are required. The existing district heating network can be used as a buffer or heat storage, contributing to stable system operation. The article presents a comparative analysis of these solutions. Full article