The purpose of this research study is to reveal the current status of and the willingness to adopt renewable energy technologies in the western region of Saudi Arabia. The main contribution of this work is the revealed levels of background knowledge presented on six types of renewable technologies, as well as five willingness perspectives on adoption by different sociodemographics. This was achieved following a quantitative research study to randomly collect cross-sectional data from 416 participants using a carefully designed questionnaire survey. Descriptive and inferential statistics were used to analyze the collected data. Results of the study provided and ranked the background knowledge of participants’ viewpoints on six renewable energy sources. It was revealed that education is paramount in increasing the level of awareness of renewable energy technologies. The results also ranked the five willingness perspectives to adopting renewable energy technologies. It was revealed that the economic factor is the main factor influencing the willingness to adoption. The analysis also showed that age was an important factor influencing the adoption of these technologies. This research study acts as a guide assisting energy policy-makers, government agencies, and investors in designing better-targeted public awareness and marketing campaigns on renewable energy technologies. This is in turn will assist in achieving the energy efficiency and production targets of Vision 2030 in Saudi Arabia.

In the present study, nanocellulose was extracted from palm leaves to synthesize nanocellulose/chitosan nanocomposites for the removal of dyes from textile industrial wastewater. Nanocellulose is of interest in water purification technologies because of its high surface area and versatile surface chemistry. Following bleach, alkali, and acid treatments on palm leaves, nanocellulose is obtained as a white powder. The produced nanocellulose was investigated. The adsorption capacity of chitosan, nanocellulose, and novel synthetic nanocellulose/chitosan microbeads (CCMB) for direct blue 78 dye (DB78) removal was studied. A series of batch experiments were conducted in terms of adsorbent concentration, mixing time, pH, dye initial concentration, and nanocellulose concentration in synthetic microbeads. The CCMB was characterized by using physicochemical analysis, namely Brunauer–Emmett–Teller (BET), scanning electron microscope (SEM), zeta potential analysis, and Fourier-transform infrared spectroscopy (FTIR). It was found that the surface area of synthetic CCMB is 10.4 m²/g, with a positive net surface charge. The adsorption tests showed that the dye removal efficiency increases with an increasing adsorbent concentration. The maximum removal efficiencies were 91.5% and 88.4%, using 14 and 9 g/L of CCMB-0.25:1. The initial dye concentrations were 50 and 100 mg/L under acidic conditions (pH = 3.5) and an optimal mixing time of 120 min. The equilibrium studies for CCMB-0.25:1 showed that the equilibrium data were best fitted to Langmuir isothermal model with R² = 0.99. These results revealed that nanocellulose/chitosan microbeads are an effective eco-adsorbent for the removal of direct blue 78 dye and provide a new platform for dye removal.

Renewable energy has become an important element of today’s modern technology targeting high-efficiency energy production. As part of its 2030 Vision, Saudi Arabia is aiming to increase its energy production through renewable sources. The purpose of this research study is to explore the factors affecting public willingness to adopt renewable energy technologies in the western region of Saudi Arabia. This was achieved through an extensive literature review of previous studies conducted worldwide and resulted in the extraction of 19 factors that affect public willingness to adopt renewable energy technologies. Following a quantitative research design, random cross-sectional data of 416 participants using the extracted factors were collected via an online questionnaire survey. Following a dimension reduction statistical approach, key components were extracted with exploratory factor analysis using principal component analysis. Five main components clustering the 19 extracted factors were revealed: cost and government regulations and policies, public awareness and local market, environment and public infrastructure, residential building, and renewable energy technology systems. The implications of this research study assist in guiding governments, regulations and policy makers, marketing agencies, and investors to better understand the concerns and enablers of renewable energy technologies adoption from the public perspective.

Workers’ wellbeing and safety is important in the construction industry due to the high risk of accidents. Safety climate development is a positive initial step toward raising the safety levels of construction practitioners. This study aims at revealing the factors influencing safety climate perceptions in the construction industry of Saudi Arabia. A set of extracted factors from the literature was validated and used to design a comprehensive questionnaire survey. Data was collected from 401 personnel working on 3 large construction project sites in Saudi Arabia. Descriptive statistics and the crosstabulation algorithm, Kendall’s tau-b correlation test, were used to analyze the data. The study revealed a set of 13 factors influencing safety climate perceptions, which are: Supervision, guidance and inspection, appraisal of risks and hazards, social security and health insurance, workmate influences, management safety justice, management commitment to safety, education and training, communication, workers’ safety commitment, workers’ attitude toward health and safety, workers’ involvement, supportive environment, and competence. The results also indicate the significant and anticipated role of top management in safety climate at sites. Implications of this study include assisting construction industry stakeholders to better understand and enhance safety climate, which in turn will lead to improved safety behavior, culture, motivation, and performance.

Many countries around the globe have recently pursued sustainability. The public and governments are demanding sustainability due to worldwide environmental disasters caused by pollution and man-made activities that impact the ecological system. Green buildings represent a significant component of sustainability, as their construction is intended to reduce natural resources consumption through energy and water conservation. Saudi Arabia is one of the world’s richest countries, but its number of certified green buildings is notably low. In addition, all of these buildings are certified by the US Green Building Council LEED rating system and not by a national organization. It seems that numerous barriers exist, slowing the development and diffusion of green buildings in Saudi Arabia. Through a systematic qualitative research approach, this research aims to explore barriers to the diffusion and adoption of green buildings in Saudi Arabia, which will facilitate the development of green buildings in Saudi Arabia. This research concludes the identification of 14 green building barriers, with lack of skilled personal and unsupportive government policies and regulations being the most significant barriers.

This study explores the opportunities and challenges of integrating artificial intelligence (AI) into engineering education. Through a review of the literature and a qualitative focus group study, an assessment was made for the role of AI in personalizing learning, enhancing simulation engagement, providing real-time feedback, and preparing students for AI-integrated workplaces. The study emphasizes how AI may significantly improve educational experiences by making them more dynamic, interactive, and successful. It also draws attention to important issues, such as moral questions, algorithmic biases in AI, infrastructure constraints, the need for AI literacy training for educators, and a range of student perspectives on AI engineering education. The results support a systematic approach to AI integration, highlighting the necessity of cooperative efforts by educators, legislators, curriculum designers, and technologists in order to overcome these obstacles. The study makes the case that AI can transform engineering education by negotiating these challenges and providing students with the information and skills needed for the digital future, all the while assuring fair and moral access to technology-enhanced learning.