Search Results (249)

One of the fundamental goals of contemporary mobility is to optimize transport processes in urban areas. The solution in this area seems to be the implementation of the idea of sustainable transport systems based on the Smart City concept. The article presents a case study—an assessment of the possibilities of changing mobility habits based on the idea of sustainable urban transport, taking into account the criterion of energy consumption of individual means of transport. The analyses are based on a comparison of selected means of transport occurring in the urban environment according to several key parameters for the optimization and efficiency of transport processes, i.e., cost, time, travel comfort, and impact on the natural environment, while simultaneously linking them to the criterion of energy consumption of individual means of transport. The analyzed parameters currently constitute the most important group of challenges in the area of shaping and planning optimal and sustainable urban transport. The presented research was used to indicate the connections between various areas of optimization of the transport process and the energy efficiency of individual modes of transport. Analyses have shown that the least time-consuming process of urban mobility is associated with the highest level of CO₂ emissions and, at the same time, the highest level of energy efficiency. However, combining public transport with other means of transport can meet most of the transport expectations of city residents, also in terms of energy optimization. The research results presented in the article can contribute to the creation of a strategy for the development of the transport network based on the postulates of increasing the optimization and efficiency of individual means of transport in urban areas. At the same time, recognizing the criterion of energy intensity of means of transport as leading in the development of sustainable urban mobility. Thus, confirming the important role of existing transport systems in the process of shaping and planning sustainable urban mobility in accordance with the idea of Smart City. Full article

Drinking Water Safety Plans (DWSP) in buildings serve to identify health hazards associated with the drinking water system. Sanitation Safety Plans (SSP) fulfill the same purpose for the sewage system. Water Safety Plans (WSP) include DWSPs, SSPs, and water systems like gray water and firefighting water. WSPs are based on a high-quality description of the water systems. This paper presents a new methodology for describing water systems. In contrast to previous approaches, the system description begins at the point where the water is consumed. These points of use are described using ecomaps, which are then supplemented with information about the pipe network. This approach makes it possible to fulfill four relevant premises: (1) the system description includes all essential parts of the drinking water installation, (2) the system description is possible with usual equipment, (3) the system description can be carried out with the least possible additional personnel costs, and (4) the system description is controllable, versionable, changeable, and forgery-proof. The ecomaps created in this way are suitable for the next step within the WSP framework, namely hazard and risk assessment. In addition, the ecomaps can be integrated into a quality, occupational safety, or environmental management system. Aspects of water security can be added to enable the ecomaps to be used as the basis for a total integrated water management system. Full article

Urban ventilation corridors play a critical role in improving wind environments, mitigating the urban heat island (UHI) effect, and enhancing urban climate resilience. Traditional Computational Fluid Dynamics (CFD) methods offer high accuracy in simulating wind fields but are computationally intensive and inefficient for large-scale, multi-scenario urban planning tasks. To address this limitation, this study proposes a morphology-driven, machine learning-based framework for ventilation corridor identification. The method integrates Lattice Boltzmann Method (LBM) simulations, neighborhood-based feature normalization, and a random forest regression model to establish a predictive relationship between morphological indices and wind speed distributions under prevailing wind conditions. Input features include raw and log-transformed LBM values, neighborhood-normalized indicators within multiple radii (100–2000 m), and porosity statistics. The model is trained and validated using CFD-simulated wind speeds, with the dataset randomly divided into training (80%), validation (10%), and testing (10%) subsets. The results show that the proposed method can accurately predict spatial wind speed patterns and identify both primary and secondary ventilation corridors. Primary corridors are closely aligned with large rivers and lakes, while secondary corridors are shaped by arterial roads and localized open spaces. Compared with conventional approaches such as FAI classification, Least Cost Path (LCP), and circuit theory models, the proposed framework offers higher spatial resolution and better alignment with the CFD results while significantly reducing computational cost. This study demonstrates the feasibility of using morphological and data-driven approaches to support efficient and scalable urban ventilation analysis, providing valuable guidance for climate-responsive urban design. Full article

Unplanned dilution is a critical challenge in underground mining, directly affecting operating costs, resource recovery, stope stability and operational safety. This study presents an empirical–statistical framework that integrates the Mathews–Potvin stability graph, the Equivalent Linear Overbreak/Slough (ELOS) metric, and a site-specific linear calibration to improve dilution prediction in sublevel stoping operations. A database of more than 65 stopes from a Brazilian underground zinc mine was analyzed and classified as cable-bolted, non-cable-bolted, or self-supported. Planned dilution derived from the Potvin graph was compared with actual ELOS measured by cavity-monitoring surveys. Results show a strong correlation between cable-bolted/supported stopes (r = 0.918), whereas non-cabled/unsupported and self-supported stopes display lower correlations (r = 0.755 and 0.767). Applying a site-specific linear calibration lowered the mean absolute dilution error from 0.126 m to 0.101 m (≈20%), with the largest improvement (≈29%) occurring in self-supported stopes where the unadjusted graph is least reliable. Because the equation can be embedded in routine stability calculations, mines can obtain more realistic forecasts without abandoning established empirical workflows. Beyond geotechnical accuracy, the calibrated forecasts improve grade-control decisions, reduce unnecessary waste haulage, and extend resource life—thereby enhancing both the efficiency and the accessibility of mineral resources. This research delivers the first Brazilian case study that couples Potvin analysis with ELOS back-analysis to generate an operational calibration tool, offering a practical pathway for other sites to refine dilution estimates while retaining the simplicity of empirical design. Full article

Continuous use of agricultural chemicals and fertilizers, sporadic sewer overflow events, and an increase in urbanization have led to significant nutrient/pollutant loadings into the semi-arid Arroyo Colorado River basin, which is located in South Texas, U.S. Priority nutrients that require reduction include phosphorus and nitrogen and to mitigate issues of low dissolved oxygen, in some of its river segments. Consequently, the river’s potential to support aquatic life has been significantly reduced, thus highlighting the need for restoration. To achieve this restoration, a watershed protection plan was developed, comprising several preventive mitigation measures, including installing green infrastructure (GI) practices. However, for effective reduction of excessive nutrient loadings, there is a need to study the effects of different combinations of GI practices under current and future land use scenarios to guide decisions in implementing the cost-effective infrastructure while considering factors such as the existing drainage system, topography, land use, and streamflow. Therefore, this study coupled the Soil and Water Assessment Tool (SWAT) model with the System for Urban Stormwater Treatment and Analysis Integration (SUSTAIN) model to determine the effects of different combinations of GI practices on the reduction of nitrogen and phosphorus under changing land use conditions in three selected Arroyo Colorado subwatersheds. Two land use maps from the U.S. Geological Survey (USGS) Forecasting Scenarios of land use (FORE-SCE) model for 2050, namely, A1B and B1, were implemented in the coupled SWAT-SUSTAIN model in this study, where the urban area is projected to increase by 6% and 4%, respectively, with respect to the 2018 land use scenario. As expected, runoff, phosphorus, and nitrogen slightly increased with imperviousness. The modeling results showed that implementing either vegetated swales or wet ponds reduces flow and nutrients to meet the Total Maximum Daily Loads (TMDLs) targets, which cost about USD 1.5 million under current land use (2018). Under the 2050 future projected land use changes (A1B scenario), the cost-effective GI practice was implemented in vegetated swales at USD 1.5 million. In contrast, bioretention cells occupied the least land area to achieve the TMDL targets at USD 2 million. Under the B1 scenario of 2050 projected land use, porous pavements were most cost effective at USD 1.5 million to meet the TMDL requirements. This research emphasizes the need for collaboration between stakeholders at the watershed and farm levels to achieve TMDL targets. This study informs decision-makers, city planners, watershed managers, and other stakeholders involved in restoration efforts in the Arroyo Colorado basin. Full article

Soil spectroscopy offers a rapid, cost-effective alternative to traditional soil analyses for characterization and classification. Previous studies have mainly focused on predicting soil categories using single sensors, particularly visible–near-infrared (vis–NIR) or mid-infrared (MIR) spectroscopy. In this study, we evaluated the performance of vis–NIR, MIR, and their combined spectra for soil classification by partial least-squares discriminant analysis (PLSDA) and random forest (RF). Utilizing 60 typical soil profiles’ data of four soil classes from the global soil spectral library (GSSL), our results demonstrated that in PLSDA models, direct combination (optimal overall accuracy: 70.6%, kappa coefficient: 0.60) and outer product analysis (OPA) fused spectra (optimal overall accuracy: 68.1%, kappa coefficient: 0.57) outperformed vis–NIR (optimal overall accuracy: 62.2%, kappa coefficient: 0.49) but underperformed compared to MIR (optimal overall accuracy: 71.4%, kappa coefficient: 0.62). In RF models, classification accuracy using fused spectra was inferior to single spectral ranges, with MIR achieving the highest classification accuracy (optimal overall accuracy: 89.1%, kappa coefficient: 0.85). Therefore, MIR alone remains the most effective spectral range for accurate soil class discrimination. Our findings highlight the potential of MIR spectroscopy for enhancing global soil classification accuracy and efficiency, with important implications for soil resource management and agricultural planning across diverse environments. Full article

The number of individuals with disabilities around the world and in Poland is constantly increasing. Social inclusion, anti-discrimination, and social integration are among the Sustainable Development Goals, which include inclusive tourism. Fostering inclusion in the tourism industry contributes to improving quality of life in marginalised communities, community involvement in tourism development planning, and ethical activities related to the production and consumption of tourism services. Making attractions accessible to people with disabilities also contributes to enriching the tourist offerings of a region. The aim of this study is to assess the accessibility of tourist attractions in the Świętokrzyskie region, located in central Poland. The natural, cultural, and historical attractions there create potential for the development of various forms of tourism. The accessibility of 20 major tourist attractions for people with mobility, sight, and hearing impairments was examined. The results indicate a varying level of adaptation of facilities to the needs of the surveyed groups. Recreation and entertainment facilities are the best adapted, while sacred and historical facilities are the least adjusted. The majority of adaptations were directed towards individuals with mobility impairments, with blind and partially sighted people as well as deaf and partially hearing people often being overlooked. The identified barriers to adaptation included the excessive cost of adaptation and the limitations of the historic nature of the building. The inadequate preparation of attraction staff to support disabled individuals was also highlighted, as well as the importance of modern technology in creating accessibility and the need to promote inclusion among attraction managers and in regional policy. The article also includes an analysis of the local government’s measures aimed at social inclusion. Full article

With the frequent occurrence of extreme weather events worldwide, the compound frequency of drought and flood events has significantly increased, imposing multidimensional pressures on agricultural water resource management. Agricultural water consumption accounts for approximately 70%, with severe waste, as a large amount of water is lost during transmission and distribution. Faced with increasingly severe and frequent extreme weather, traditional drainage systems may become unsustainable. Identifying the factors influencing drainage time is crucial for efficient drainage. The MIKE URBAN model has significant potential in farmland waterlogging simulation and drainage network optimization. This study validated the model’s accuracy based on infiltration well overflow capacity experiments, with Average Relative Error (ARE) values of 2.29%, 6.52%, 4.41%, 3.17%, 4.37%, and 5.69%, demonstrating good simulation accuracy. The MIKE URBAN model was used to simulate drainage networks, explore factors affecting drainage time, establish an annual cost system for the drainage network, and optimize the network using a genetic algorithm with the objective of minimizing annual costs. Research findings: There is a clear negative correlation between the maximum inflow of infiltration wells and drainage time. As inflow increases, drainage becomes faster, but beyond 0.0075 m³/s (27 m³/h), the efficiency gains level off. This indicates that selecting infiltration wells with at least a 20% opening ratio is essential. Similarly, increasing the collector’s diameter enhances drainage efficiency significantly, though the effect follows a diminishing return pattern. While smaller lateral spacing improves local water collection, it may lead to flow congestion if the collector is undersized; conversely, larger spacing increases drainage paths and delays, even if the collector is large. An optimal spacing range of 100–150 m is suggested alongside the collector diameter. Lateral diameter also affects performance: increasing it reduces drainage time, but the benefit plateaus around 200 mm, making further enlargement cost-ineffective. The genetic algorithm helped to optimize the drainage network design. Utilizing the genetic algorithm, the drainage network was optimized in just 15 iterations. The fitness function value rapidly decreased from 351,000 CNY to 55,000 CNY and then stabilized, reducing the annual cost from 59,640.67 CNY to 45,337.86 CNY—a 24% savings—highlighting the approach’s effectiveness in designing efficient and economical farmland drainage systems. This study has shown that the simulation-based optimization of drainage networks provides a more rational and cost-effective approach to planning drainage infrastructure. Full article

Aim: This study aimed to evaluate the knowledge and attitudes of family physicians and family health personnel who are responsible for childhood vaccination services in primary care regarding meningococcal, rotavirus, and human papillomavirus vaccines. Methods: This cross-sectional study was conducted between October 2021 and January 2022. A total of 700 healthcare professionals from all geographical regions in Turkey were included in the study. The participants filled out an online questionnaire consisting of 39 questions created with Google Forms. Results: Of the participants, 340 (48.6%) are family physicians, and 360 (51.4%) are family health personnel. Most participants are from the Marmara region, Turkey’s most densely populated region. The most recommended vaccine among the participants was rotavirus (84.3%), while the least recommended vaccine was human papilloma virus (47.6%). The number of family physicians recommending meningococcal and human papilloma virus vaccines was significantly higher than that of family health personnel (p < 0.001). Furthermore, there was a statistically significant correlation between seeing a patient with these viruses in one’s professional life or considering the severity of these three diseases to be severe and recommending these vaccines (p < 0.001 for both). However, lack of knowledge about vaccines and doses, the high cost of vaccines, and concerns about side effects were among the reasons for not recommending vaccines. Conclusions: Healthcare professionals involved in childhood immunization should be trained to increase their knowledge and awareness on this issue. The training plan and curriculum should take into account the issues raised in our research, such as age, occupation, region of residence, and professional experience. In general, knowledge about the efficacy and safety of vaccines will help healthcare professionals develop their confidence in vaccines and willingness to recommend childhood vaccines to others. Full article

This paper presents two innovative procedures developed for rural electrification planning. To address the challenges of processing vast geospatial data, handling complex and computationally intensive network design, and making detailed yet accessible economic assessments, this work introduces a Buffering plugin for community identification and a Grid Routing and Cost Allocation plugin for network design and economic assessment, both integrated into the open-source QGIS platform. The first enables the identification of potential electrification zones through dual methodologies, while the second introduces three key processes: hierarchical clustering, a modified minimum spanning tree, and a novel cost allocation methodology that provides village-specific LCOE calculations. Testing in Zambia has proven that this approach is not only effective but also—compared to existing tools—offers significant advantages in terms of computational efficiency and accessibility, while providing practical solutions to large-scale challenges. This synergistic approach enables planners to move from granular geospatial data to actionable electrification decisions through a streamlined process. The analysis covered over 3 million buildings, grouped into 162,142 settlement clusters, and subsequently determined optimal electrification strategies for 3025 villages—40.4% connected to grid extensions and 59.6% to mini-grids—serving a total population of 18 million people. Full article

Recognizing the factors that influence business formation in developing contexts is critical for promoting economic growth. This study examines the drivers of entrepreneurship among university alumni in Ecuador, addressing gaps in the literature regarding the roles of individual, organizational, and institutional factors in business creation. Drawing on established theories such as the Theory of Planned Behavior and Resource-Based Theory, a multilevel causal model was developed and tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). Data were collected from 550 alumni through a structured questionnaire, complemented by semi-structured interviews. The model integrates micro-level (entrepreneurial attitudes and funding experience), meso-level (entrepreneurial knowledge acquired from working experience), and macro-level determinants (opportunity cost). Results indicate that while individual traits play a role, organizational knowledge and institutional context have more pronounced impacts on entrepreneurial actions. In particular, opportunity costs have a negative impact on the business formation process, reflecting the challenges of entrepreneurship in unfavorable environments. The findings highlight the importance of fostering entrepreneurial ecosystems within universities, emphasizing education and support mechanisms tailored to overcoming institutional barriers. This study contributes to the understanding of entrepreneurship in Latin America, offering insights for policymakers and academic institutions aiming to enhance entrepreneurial activity and economic development. Full article

The adoption of electric motorcycles is critical for reducing transportation-related greenhouse gas emissions in Indonesia, which reached 674.54 million t of CO₂ in 2023. This study integrates the Theory of Planned Behavior with situational, contextual, and demographic factors to explore the determinants of electric motorcycle adoption intentions and actual usage. Data were collected from 1602 respondents across ten provinces with the highest motorcycle sales using purposive sampling and analyzed through Partial Least Squares—Structural Equation Modeling. Findings reveal that psychological factors—attitude, subjective norms, and perceived behavioral control—significantly influence purchase intentions, while personal moral norms do not. Situational factors such as technology and cost indirectly affect adoption intentions through attitude and perceived behavioral control. Contextual factors show mixed results; government policies effectively shape attitudes and perceived behavioral control, but infrastructure remains inadequate to influence attitudes directly. Demographic analysis highlights gender as a moderating factor, with men showing higher moral-driven adoption intentions. These results imply that the government and manufacturers need to develop the appropriate strategy to foster public interest in adopting electric motorcycles to increase the adoption rate of pro-environmental vehicles. Government policies such as purchase price subsidies, tax reductions, and charging rate discounts can motivate the intention to adopt electric motorcycles. In addition, manufacturers could improve technical performance and reduce the total cost of ownership, such as the purchase price and battery replacement costs. Full article

The grand challenge of sustainable development, increased demands for resilient critical infrastructure systems, and cost efficiency calls for thinking and acting “out of the box”. We must strive to search for, identify, and utilize new and emerging technologies and new combinations of existing technologies that have the potential to improve present best practices. In integrity management of, e.g., bridge, offshore, and marine structures, relatively new technologies have shown substantial potentials for improvements that not least concern structural health monitoring (SHM), digital twin (DT)-based structural and mechanical modeling, and risk-based inspection (RBI) and maintenance planning (RBI). The motivation for the present paper is to investigate and document to what extent such technologies in isolation or jointly might have the potential to improve best practices for integrity management of offshore wind turbine structures. In this pursuit, the present paper conducts a comprehensive bibliometric analysis to explore the current landscape of advanced technologies within the offshore wind turbine industry suitable for integrity management. It examines the integration of these technologies into future best practices, taking into account normative factors like risk, resilience, and sustainability. Through this analysis, the study sheds light on current research trends and the degree to which normative considerations influence the application of RBI, SHM, and DT, either individually or in combination. This paper outlines the methodology used in the bibliometric study, including database selection and search term criteria. The results are presented through graphical representations and summarized key findings, offering valuable insights to inform and enhance industry practices. These key findings are condensed into a road map for future research and development, aimed at improving current best practices by defining a series of projects to be undertaken. Full article

The Philippines aspires for a clean energy future but has become increasingly reliant on imported fossil fuels due to rising energy demands. Despite renewable energy targets and a coal moratorium, emissions reductions have yet to materialize. This study evaluates the potential of offshore wind (floating and fixed), floating solar PV, in-stream tidal, and nuclear power to contribute to a Net-Zero energy plan for the Philippines, utilizing the Open-Source Energy Modelling System (OSeMOSYS). Seven scenarios were analyzed, including least-cost, renewable energy targets; Net-Zero emissions; and variations in offshore wind growth and nuclear power integration. Floating solar PV and offshore wind emerged as key decarbonization technologies, with uptake in all scenarios. Achieving Net-Zero CO₂ emissions by 2050 proved technically feasible but requires substantial capital, particularly after 2037. Current renewable energy targets are inadequate to induce emissions reductions; and a higher target of ~42% by 2035 was found to be more cost-effective. The addition of nuclear power showed limited cost and emissions benefits. Emissions reductions were projected to mainly occur after 2038, highlighting the need for more immediate policy action. Recommendations include setting a higher renewables target, offshore wind capacity goals, a roadmap for floating solar PV, and better incentives for private investment in renewables and electric transport. Full article

Riverside cities are vulnerable to pluvial flooding due to multiple factors, such as landscape fragmentation caused by land-use changes, which weakens the ecosystem service of pluvial flood mitigation. This ecosystem service is essential because it reduces the impact of this climatic event through water infiltration into the soil. The metropolitan area of Arequipa, Peru, a riverside city, is currently fragmented by accelerated population growth, which has filled the river buffer zones and agricultural areas with concrete, resulting in a fragile flood control ecosystem service. This research assesses the pluvial flood mitigation ecosystem service in the metropolitan area of Arequipa using the InVEST software 3.12.1 to map an ecological corridor. The results show low runoff control in urban environments but significant retention in agricultural and non-agricultural vegetation areas. Zero-runoff patches were identified as ecological sources, and a resistance surface map and least-cost path model were created, yielding a 57 km ecological corridor connecting 18 ecological sources across 12 of Arequipa’s 19 metropolitan districts. This study highlights the importance of integrating ecosystem services into urban planning to support green infrastructure initiatives, which contribute to sustainable and resilient cities by mitigating fragmentation and enhancing natural flood defenses. Full article