• Energy Research

Water management strategies in the Ile River basin (Republic of Kazakhstan) have traditionally relied on historical data without fully considering the potential impacts of climate change. This gap can lead to underestimating the changes in temperature, precipitation patterns, and runoff, hindering effective water resource management. This study aimed to analyze how a changing climate is affecting the Ile River basin’s water regime. Specifically, it investigated trends in temperature, precipitation, and runoff within the basin, emphasizing the importance of incorporating these intra-annual variations when planning water management strategies and hydraulic structures. A detailed analysis of the long-term data was conducted, focusing on changes in meteorological indicators. This included average air temperatures and annual precipitation for elevations above and below 1500 m during cold and warm periods. The analysis aimed to identify and quantify trends of increase or decrease. Meteorological stations were strategically chosen to represent both arid and humid areas within the basin, accounting for the region’s significant altitude variations. The investigation revealed several key findings. Rising average annual air temperatures are leading to a larger area experiencing snowmelt and a longer warm period within the runoff formation zone. This directly impacts the water balance of the basin. Additionally, an increase in total annual precipitation, particularly during the cold season within the runoff formation zone, suggests a potential for future water resource growth, assuming that these trends persist. This study highlights the importance of considering intra-annual variations in water regimes when developing water management strategies. The observed changes in temperature and precipitation patterns within the Ile River basin necessitate adjustments to existing plans to ensure sustainable water resource management in a changing climate.

Several factors over the years have contributed to stigma in public transport. Many studies have highlighted the need to make the transport system more equitable both from economic and gender perspectives. This study attempts to demonstrate how the perceptions of public transport users and non-users are stigmatized from social and cultural standpoints. Thus, it identifies the social and cultural stigma-induced barriers embedded with the use and people’s general perception about the public bus service, taking SAPTCO (Saudi Public Transport Company) as a case study. The study results suggest that privacy concern is the primary cause of stigma. Most of the users are unwilling to ride with their families as SAPTCO does not account for gender needs (e.g., privacy, travel convenience, safety, comfort, etc.). Moreover, people from the high-income classes are more stigmatized against this ridership. A fuzzy inference system (FIS) model is used to analyze the survey questionnaire responses and understand what stigma means for the public bus service. Expert opinions are employed to generate “if–then” rules of the FIS models. Sensitivity of the defined fuzzy model is conducted to different aspects of the ridership. The study results further suggest that “inconvenience” poses the highest impact while “feeling safe”, “privacy”, “fare”, “timing”, and “comfort” are found to be the medium impact-making variables for stigma. The stigma-defining variables would be critical for the public bus service to improve its service quality and help (re-)design the policies that would attract a high amount of ridership. Some solutions are suggested in the end that would complement, strengthen, and promote the current SAPTCO service. The demonstrated methodology of this study would be relevant and adaptive to any relevant context to improve public transportation service and pertaining policies.

All countries have suffered from the COVID-19 crisis; the pandemic has adversely impacted all sectors. In this study, we examine the transport sector with a specific focus on the problem of commuting mode choice and propose a new decision-making approach for the alternative modes after synthesizing expert opinions. As a methodology, a customized model of the recently developed best–worst method (BWM) is used to evaluate mobility choice alternatives. The survey reflects citizens’ opinions toward mobility choices in two Italian cities, Palermo and Catania, before and during the pandemic. BWM is a useful tool for examining mobility choice in big cities. The adopted model is easy to apply and capable of providing effective solutions for sustainable mode choice. The urban context is analyzed considering the importance of transport choices, evaluating the variation of resilience to the changing opinions of users.

Smart, green, and resilient city paradigms have been mainly promoted through top-down and technocratic approaches. However, based on the notion to return to “the right to the city”, emerging community-driven initiatives are providing self-managed infrastructures contributing to urban sustainability transitions. This paper explores the relevance of the behavioral aspects of people-centered approaches in dealing with two different facets of urban metabolism: physical infrastructure (involvement with the management of decentralized infrastructures) and consumption patterns (involvement in proactive reduction of resources used). In the first case we assessed community perceptions about the roles, benefits, and willingness to proactively engage in the management of decentralized green infrastructures in Bogotá City, Colombia. For the second facet, we measured the effectiveness of change agents in re-shaping energy consumption decisions within urban social networks in South Africa and Saudi Arabia. This paper’s results show that pre-determined and standardized strategies do not guarantee positive, nor homogeneous, results in terms of meeting sustainability targets, or promoting community involvement. Hence, a better integration of people-centered and top-down approaches is needed through context-dependent policies, for enhancing both users’ appreciation of and commitment to urban metabolism participative management.

As many studies have already shown, the COVID-19 pandemic has had a great impact on the daily routines of people all over the world. University students form one of the most affected groups of people, since they have had to interrupt many of the activities that they usually perform, and have also had to get used to a new way of learning (e-learning). An important question that now arises is whether the changes that were identified within the pandemic period are to be maintained when the risk of being infected is eliminated. To this end, 537 university students of the Kore University of Enna, Italy, were surveyed. Their responses are analyzed descriptively, and an ordinal regression model is being developed to shed more light on the likelihood of retaining changes related with to transport mode choice. The results show that the likelihood of retaining all the changes when commuting and during daily activities is very high, demonstrating such willingness from the participants. Moreover, it has been shown that public transport has increased the probability of people being negatively affected by the pandemic in the long-term, and opportunities appear for increasing the modal share of active modes.

Many techniques including logistic regression and artificial intelligence have been employed to explain school-goers mode choice behavior. This paper aims to compare the effectiveness, robustness, and convergence of three different machine learning tools (MLT), namely the extreme learning machine (ELM), support vector machine (SVM), and multi-layer perceptron neural network (MLP-NN) to predict school-goers mode choice behavior in Al-Khobar and Dhahran cities of the Kingdom of Saudi Arabia (KSA). It uses the students’ information, including the school grade, the distance between home and school, travel time, family income and size, number of students in the family and education level of parents as input variables to the MLT. However, their outputs were binary, that is, either to choose the passenger car or walking to the school. The study examined a promising performance of the ELM and MLP-NN suggesting their significance as alternatives for school-goers mode choice modeling. The performances of the SVM was satisfactory but not to the same level of significance in comparison with the other two. Moreover, the SVM technique is computationally more expensive over the ELM and MLP-NN. Further, this research develops a majority voting ensemble method based on the outputs of the employed MLT to enhance the overall prediction performance. The presented results confirm the efficacy and superiority of the ensemble method over the others. The study results are likely to guide the transport engineers, planners, and decision-makers by providing them with a reliable way to model and predict the traffic demand for transport infrastructures on the basis of the prevailing mode choice behavior.

The limited availability of public transportation in Saudi Arabia leads to an increased demand for private vehicles. An increase in using private cars does not meet the global sustainability goals, e.g., reducing energy consumption and improving the air quality. Road users should be encouraged to use sustainable mobility modes, particularly public transportation, equally accessible to both men and women However, women’s mobility has been somewhat limited and challenged in spatio-temporal terms, and partly due to socio-cultural barriers. This study attempts to understand the gender experience of a sample of public transport users and consider their aspirations and needs into daily mobility. A survey campaign (structured interviews and online questionnaires) was launched in the Dammam Metropolitan Region (DMR), taking four different types of respondents into account. The results suggest a predominant preference for taxis for shopping and leisure activities due to a poor public transport service, pivotally characterized by limited operational routes, hours, and infrastructure. This study ponders upon the adequacy of the supporting infrastructures and interior design of the public buses to women’s needs and compare them with global best practices. The results suggest that, due to the absence of a gender-responsive design and infrastructure, women are forced to use taxis, although privacy and a sense of insecurity often become concerns when traveling alone or with children. The study results allow future research to be expanded, considering women’s mobility patterns, needs, and embedded barriers by comparing the results with current transport policies, plans, and practices.