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The industrial revolution brought environmental degradation to light. Concrete and plastic degrade the ecosystem and cause unsustainable development. Academic and industrial sectors are interested in lowering carbon emissions associated with concrete. Meanwhile, global sand scarcity worries environmentalists. To reach sustainable development goals, cement and fine aggregate must be substituted with other abundant waste/natural materials. This study aimed to develop a green concrete by utilizing plastic waste and creating modelling tool for predicting the mechanical properties of plastic concrete. Different composition of silica fume and superplasticizers substituted fine aggregate and cement in both irradiated (treated) and regular (untreated) plastic concrete. Compressive strength (fc’) and split tensile strength (fst) of the resulting concrete were studied. Moreover, from literature data, 320 data points each for fc' and fst were used to train gene expression programming (GEP) models. Models’ accuracy was evaluated employing various statistical measures. Regular plastic waste concrete has demonstrated a lower fc’ and exhibited anomalous behavior for fst. While irradiated plastic waste concrete has demonstrated improved mechanical characteristics, comparatively. Correlation coefficients using GEP models for fc’ and fst were found to be 0.92 and 0.88, respectively. Furthermore, sensitivity analysis revealed that plastic was the most significant in the GEP model’s development. K fold validation was employed to prevent over-fitting of the models. GEP provides an empirical expression for each outcome to predict future database features. This research improves green concrete's long-term sustainability by reducing carbon emissions and alleviating fine aggregate scarcity.

Accurate and reliable wave forecasting is crucial for optimizing the performance of various marine operations, such as offshore energy production, shipping, and fishing. Meanwhile, predicting wave height and wave energy is crucial for achieving sustainability as a renewable energy source, as it enables the harnessing of the power of wave energy efficiently based on the water-energy nexus. Advanced wave forecasting models, such as machine learning models and the semi-analytical approach, have been developed to provide more accurate predictions of ocean waves. In this study, the Sverdrup Munk Bretschneider (SMB) semi-analytical approach, Emotional Artificial Neural Network (EANN) approach, and Wavelet Artificial Neural Network (WANN) approach will be used to estimate ocean wave parameters in the Gulf of Mexico and Aleutian Basin. The accuracy and reliability of these approaches will be evaluated, and the spatial and temporal variability of the wave field will be investigated. The available wave characteristics are used to generate hourly, 12-hourly, and daily datasets. The WANN and SMB model shows good performance in the daily prediction of the significant wave height in both case studies. In the SMB model, specifically on a daily time scale, the Nash–Sutcliffe Efficiency (NSE) and the peak deviation coefficient (DCpeak) were determined to be 0.62 and 0.54 for the Aleutian buoy and 0.64 and 0.55 for the Gulf of Mexico buoy, respectively, for significant wave height. In the context of the WANN model and in the testing phase at the daily time scale, the NSE and DCpeak indices exhibit values of 0.85 and 0.61 for the Aleutian buoy and 0.72 and 0.61 for the Gulf of Mexico buoy, respectively, while the EANN model is a strong tool in hourly wave height prediction (Aleutian buoy (NSEEANN = 0.60 and DCpeakEANN = 0.88), Gulf of Mexico buoy (NSEEANN = 0.80 and DCpeakEANN = 0.82)). In addition, the findings pertaining to the energy spectrum density demonstrate that the EANN model exhibits superior performance in comparison to the WANN and SMB models, particularly with regard to accurately estimating the peak of the spectrum (Aleutian buoy (DCpeakEANN= 0.41), Gulf of Mexico buoy (DCpeakEANN = 0.59)).

Many practical issues arise when dealing with solid waste management, and there are also environmental effects to be considered. Selecting landfill sites requires extra care with respect to many factors such as the environment, health hazards for people, and the cost of transportation. Furthermore, cities have their own rules, methods, and practices for managing and selecting the best locations for collecting solid waste. In this research, multi-criteria decision analysis (MCDA) was presented and used to evaluate the appropriateness of and suggest the best locations for landfill sites in Najran, KSA. Some remote sensing data and the ArcGIS software were used to prepare nine thematic layers, including drainage density, groundwater depth, land use, soil type, road network, surface elevation, surface slope, distance from residential areas, and distance from protected areas. To evaluate the layer weightings, a questionnaire with pairwise comparisons was distributed among experts and analyzed using the analytical hierarchy process (AHP) and fuzzy set technique. The one-factor-at-a-time (OFAT) sensitivity test was conducted to test the sensitivity of the evaluated weightings. A landfill suitability index (LSI) map was created using raster calculator tools and divided into five classes: limited suitability (LSI value 1.39–2.49), least suitable (2.50–3.03), relatively suitable (3.04–3.48), suitable (3.49–3.91), and most suitable (3.92–4.66). According to the statistical analysis, 18.0% and 18.2% of the total area were within the most suitable and suitable landfill regions, while 21.2%, 14.9%, and 9.5% accounted for relatively suitable, least suitable, and limited suitability areas, respectively. The employed technique and its findings can provide an appropriate guideline to assist the municipality of Najran city, regional planners, and decision-makers in selecting an optimal landfill site in the future. This study also presented some recommendations to enhance the suitability map of landfill sites in Najran city.

The city of Jeddah experienced a severe flood in 2020, resulting in loss of life and damage to property. In such scenarios, a flood forecasting model can play a crucial role in predicting flood events and minimizing their impact on communities. The proposed study aims to evaluate the performance of machine learning algorithms in predicting floods and non-flood regions, including Gradient Boosting, Extreme Gradient Boosting, AdaBoosting Gradient, Random Forest, and the Light Gradient Boosting Machine, using the dataset from Jeddah City, Saudi Arabia. This study identified fourteen continuous parameters and various classification variables to assess the correlation between these variables and flooding incidents in the analyzed region. The performance of the proposed algorithms was measured using classification matrices and regression matrices. The highest accuracy (86%) was achieved by the Random Forest classifier, and the lowest error rate (0.06) was found with the Gradient Boosting regressor machine. The performance of other algorithms was also exceptional compared to existing literature. The results of the study suggest that the application of these machine learning algorithms can significantly enhance flood prediction accuracy, enabling various industries and sectors to make more informed decisions.

This study aims to review the off-plan sales program to identify the financial and marketing challenges being faced by such programs in Saudi Arabia and formulate consensus-based measures to overcome these challenges. The study implies an analytical descriptive method to achieve its objectives, based on the opinion of experts involved in the off-plan sales program and analyzing the data using the Delphi technique. Various statistical parameters were calculated to validate the obtained results. The study found several challenges being faced by off-plan sales programs, including financing challenges such as mortgaging on the land deed, as well as marketing challenges, including low turnout of the buyers due to the long duration of project implementation. The study concludes with several suggested measures, the most important of which is to find an alternative to the condition of mortgaging the land deed, such as putting insurance on the project or providing a financial bank guarantee. The study contributes to the improvement of the real estate sector of Saudi Arabia and would benefit the construction and development sectors as well.

Energy consumption in the building sector accounts for a large percentage of global energy consumption. For this reason, it is essential to take action to minimize this destructive consumption and promote energy conservation practices within the building sector. A Zero Energy Building (ZEB) concept has been proven as a viable technique for improving energy efficiency in various climatic conditions. This concept can minimize the environmental impact of buildings and helping to advance sustainable development in the construction industry. Worldwide, the ZEB is of the utmost importance to meet sustainability development goals in the built environment. The building sector in the Kingdom of Saudi Arabia (KSA) consumes about 75% of total electrical energy. KSA has experienced an unprecedented energy consumption in the last decade. This is due to the country’s rapid population growth and urbanization, which in turn put more pressures on the kingdom’s natural resources. However, KSA is committed to promote energy efficiency and renewable energy technologies to achieve the goals of sustainability development, as part of its Vision 2030. This paper therefore explores various green building solutions, especially in hot-arid regions, with the aim of reaching ZEB, and at the same time minimizing potential adverse environmental impacts. In order to verify proposed solutions, energy simulation software (Integrated Environmental Solution-IES) is used, along with reviews of related work. The major finding of this paper reveals that several green building concepts are crucial to the design and operation of a building in hot dry region, including thermal mass; daylight; natural ventilation; cavity wall; double-glazing and solar panels (PV). Bear in mind that the operation of a building has to be powered by a Building Management System (BMS). This paper also proposes an auxiliary holistic framework that explains how green practices such as Zero Energy Buildings (ZEBs) can be achievable in Saudi Arabia with no harm to its local environment.

Cities around the world increasingly recognize the need to build on their resilience to deal with converging forces such as disasters, environmental degradation, urban sprawl, and climate change. Given the significance of critical infrastructure networks (CINs) for maintaining the quality of life in buildings and communities, improving their resilience is of high importance to governors, planners, and policymakers. Therefore, this study is proposed to spatially analyze the resilience of CINs in Saudi Arabia and to develop a holistic resilience framework for buildings and communities. The research method of this study involves a case study of Najran, including a collection of CIN data, history of natural disasters, and future potential hazards. The data were compiled to list the basic parameters required for the development of resilience criteria. Overall results show that CINs in the city of Najran were performing below average compared with the measurement criteria. The study highlights the need to make improvements in terms of the robustness, redundancy, and flexibility of the CINs in the city. Moreover, this paper proposes a holistic framework of key aspects of resilient criteria that need to be taken into account by the city governor, policymakers, and developer bodies for better management of available infrastructure and its development in future years.

The current coronavirus COVID-19 pandemic is impacting countries across the world, resulting in governments undertaking a number of precautionary measures for their populations. This raises the issue of the effectiveness of urban design of dwellings to assist with these measures. This study therefore determines the current readiness of local neighborhoods and housing in Saudi Arabia to face epidemics. The study employs an analysis of a public survey achieving a comprehensive (n = 413) across the country to identify: (a) the current situation of local neighborhood and services, including density and the ability to fulfil human needs during periods of quarantine; (b) the ability of housing design to assist with social distancing: (c) appropriate housing design to fulfil social needs; and (d) the design of housing to accommodate the ability for infected household members to self-isolate. The findings identify that neighborhoods in Saudi Arabia meet current social requirements and can assist in avoiding gatherings. In addition, it illustrates the advantages and disadvantages of housing design, revealing that villas tend to be low density, and so facilitate social distancing, but neighborhoods with a high number of residential units face considerable challenges, due to the high density of population, particularly in areas lacking planning.

In hot and humid climates, a significant part of the energy is used to cool the building. There are several ways to reduce this air conditioning load, but one standout is through the selection and design of the right building envelope and its components. The thermal characteristics of the building envelope, in particular the thermal resistance of the insulation used, have an impact on the thermal and energy performance of building structures. Thermal conductivity, which indicates the ability of heat to move through a material given a temperature difference, is the primary factor affecting the performance of a thermal insulation material. Both temperature and humidity changes can affect a material’s thermal conductivity value, which can then change. In fact, due to the fluctuating ambient air temperature and solar radiation, thermal insulation in buildings is susceptible to significant and continuous temperature variations. Thermal insulation used in building walls and roofs helps to reduce the energy demand of the building. It improves thermal comfort and, if used correctly, reduces the operational cost of the building. The present study has focused on the effects of location and insulation material on the energy performance of a residential building by considering five climatic locations in the Kingdom of Saudi Arabia (KSA). Five commonly used insulation materials with different thermal characteristics, namely polyurethane board (PU), expanded polystyrene (EPS), glass wool (GW), urea-formaldehyde foam (UFF), and expanded perlite (EP), were analyzed under various climatic zones as per the Saudi Building Code 601/602. The selected cities were categorized based on cooling degree days (CDD) and outdoor dry bulb temperature (DBT) as hot, very hot, and extremely hot climatic zones. Insulation improves thermal comfort and, if used correctly, reduces running costs. Experiments were conducted to determine the thermal conductivity, and the energy simulation was performed by employing IES-VE software for various insulation options. The findings indicate that the location has a significant impact on the energy performance of the insulating materials. The energy saving potential of polyurethane board (PU) insulation is more attractive in cities with higher DBTs and CDDs than in cities with lower DBTs and CDDs. The benefit of installing insulation ranged from a 2 to 14% decrease in energy demand for the climate zones studied. The sensitivity analysis showed that the energy saving potential of the insulation materials is sensitive to the set-point temperature (ST) band.

This study focuses on highlighting the major effects on the agricultural activities caused by the reduction in water resources in Najran, Saudi Arabia. Since the last decade, there has been a sharp decrease in the availability of water in the area as reported by many researchers due to urban sprawl, excessive groundwater extraction causing a decrease in land fertility, and destruction of soil structure. The water resources of the area and the agricultural heritage is endangered, and also the environmental, economic, and social impact of these actions can be severe if such activities continue in the future. The purpose of the study is to obtain detailed information regarding the major causes of water depletion in the Najran Valley as per the opinion of the residents. A survey questionnaire was designed with a high level of flexibility, covering the key issues including causes of groundwater depletion, factors that affected agricultural activities and irrigation practices and the environmental impact of the Najran Dam, and the risks of floods related to it. An overwhelming response was received from the people of the area. Significant results were obtained from the analysis, and the major effects and causes were highlighted as conclusions. The study shall help the city planners and policymakers in identifying the major causes of water depletion and the actual needs of the residents in order to manage the water resources of the area efficiently. Understanding the public opinion on the issues discussed in this study shall provide a base to develop management options for water resources problems suited to local contexts that fits the need of the community.

Despite recent innovations in soil improvement techniques, it remains difficult for project managers to select the most appropriate technique for soil improvement projects due to the lack of a reliable and systemic framework that may support the decision-making process. Therefore, the aim of this paper is to introduce a new systematic assessment framework that establishes reliable criteria for the selection of dynamic compaction (DC) technology, evaluates its effectiveness using Cone Penetration Test (CPT) data, and predicts the expected improvement in soil bearing capacity (Qc). The proposed framework uses zone-based soil categorization in conjunction with soil behavior type index (Ic) and CPT data to predict the expected improvement in soil bearing capacity after the implementation of the DC technique. In addition, a case study is used to highlight the applicability and the effectiveness of the proposed framework in evaluating the suitability of the DC technique and in predicting the expected improvement in the bearing capacity of soil. The results show that the DC technique is appropriate when the soil has a behavior type index of Ic ≤ 1.31, 1.31 < Ic ≤ 2.05, 2.05 < Ic ≤ 2.6, 2.6 < Ic ≤ 2.95 and Ic > 2.95, and the expected improvement in soil bearing-capacity (Qc) is within the range of [+20, +∞], [15–20], [5–15], [1–5] and [0–1] MPa, respectively.

In the modern era, population and economic growth have accelerated urban sprawl in Saudi Arabia. This has placed tremendous pressure on the country’s natural resources, including water, energy, and raw materials. Hence, the conventional means of expanding the built environment is no longer appropriate, as it has been found to be one of major causes of climate change and global warming. In the early 1970s, the principles of sustainable development emerged in developed countries, in order to remedy this global issue. During this period, Saudi Arabia experienced dramatic development in all of its industries, but the principles of sustainable development were, to a large degree, overlooked. However, there is now an ambitious Vision 2030 for Saudi Arabia, one of the purposes of which is to promote greater sustainability in the country. This study seeks to assist decision makers to identify the challenges and opportunities of the current Saudi practices of city design, and their related operational aspects, and to enable the adoption of effective measures for implementing sustainable development principles. Employing an ethnographic research methodology, the fieldwork concerned includes a public perception survey, followed by a site inspection, in order to develop an insider’s view of the current level of sustainable practice in the city of Najran. A public survey is distributed to well-informed citizens, with the goal of obtaining their insights, and to assess their willingness to embrace green city practices. This is followed by a site inspection visit that seeks to obtain in-depth information regarding site design and operational practices. A checklist of sustainable criteria is adapted from well-known systems. The major outcomes of the study reveal that many challenges are encountered the application of green city principles. The paper offers effective approaches and strategic actions for overcoming these challenges.

Polyaniline (PANI), which is a member of the family of electrically conducting polymers, has been widely discussed as a potential membrane for wastewater treatment. Although a steady growth in PANI literature was observed, analyzing PANI literature quantitatively is still a novelty. The main aim of this study is to unearth the current research status, global trends, and evolution of PANI membranes literature and their use in water treatment applications over time. For this purpose, a scientometric study was performed consisting of bibliometric and bibliographic analysis. A total of 613 entities were extracted from Web of Science published during the last 50 years and were analyzed to map trends based on leading peer-reviewed journals, publication records, leading research disciplines, countries, and organizations. The study shows that the number of annual publications increased exponentially from 2005 to 2020 and is expected to keep increasing in the current decade. The Journal of Membrane Science published the highest number of articles and was identified as the most-cited journal in the field. China, India, and the USA were observed as the top three research hubs. The top-ranked authors in the field were Wang, Jixiao, and Wang, Zhi. To find research trends, four different clusters of keywords were generated and analyzed. The top five most frequent keywords turn out to be polyaniline, water, performance, membranes, and nanoparticles. The analysis suggests that the application of nanotechnology for modifying PANI membranes (using nanoparticles, nanotubes, and graphene specifically) is the future of this field. This study elucidates the research streamline of the field that may serve as a quick reference for early career researchers and industries exploring this field.

Deterioration of asphalt pavements due to massive load of vehicles and climatic variation has demanded the use of pavements construction material with an excellent resilience characteristic, resistance to permanent deformation, and most importantly, a much longer service lifespan. The main structural distresses in pavement construction are permanent deformation at high temperatures and fatigue cracking under repetitive traffic loadings. To comprehensively investigate the performance of bitumen penetration grade (PG) 70 against rutting, fatigue, and high temperature cracking in hot mix asphalt (HMA) pavements, polycarbonate (PC) and polytetrafluoroethylene (PTFE) were used. The investigation of the internal structure, rheological, and physical properties of base and modified bitumen (MB) mixes with different percentages of modifiers (0%, 2.5%, and 5%) by weight were performed via scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FTIR) analysis, X-ray diffraction (XRD) pattern analysis, rolling thin-film oven test (RTFOT), pressurized aging vessel (PAV), dynamic shear rheometer (DSR), rotational viscosity (RV), and bending beam rheometer (BBR). The results of the RV test indicate that modification of neat bitumen with polycarbonate and polytetrafluoroethylene increased the viscosity for polycarbonate-modified bitumen (PCMB), polytetrafluoroethylene-modified bitumen (PTFEMB), and for a blend of PCMB-PTFEMB by 44%, 50%, and 55.75% at 135 °C and 111.10%, 127.80%, and 138.88% at 165 °C, accordingly. BBR test results revealed that modifiers increased the rigidity of neat bitumen by 74.8%, 75.8%, and 74.5% at −16 °C, −22 °C, and −28 °C, respectively.

The scientometric analysis is statistical scrutiny of books, papers, and other publications to assess the “output” of individuals/research teams, organizations, and nations, to identify national and worldwide networks, and to map the creation of new (multi-disciplinary) scientific and technological fields that would be beneficial for the new researchers in the particular field. A scientometric review of 3D printing concrete is carried out in this study to explore the different literature aspects. There are limitations in conventional and typical review studies regarding the capacity of such studies to link various elements of the literature accurately and comprehensively. Some major problematic phases in advanced level research are: co-occurrence, science mapping, and co-citation. The sources with maximum articles, the highly creative researchers/authors known for citations and publications, keywords co-occurrences, and actively involved domains in 3D printing concrete research are explored during the analysis. VOS viewer application analyses bibliometric datasets with 953 research publications were extracted from the Scopus database. The current study would benefit academics for joint venture development and sharing new strategies and ideas due to the graphical and statistical depiction of contributing regions/countries and researchers.

Due to their simple synthesis method and excellent properties, such as superior adsorption and regeneration capabilities, with a large surface area and tunable pores, metal-organic frameworks (MOFs) have emerged as a suitable option for wastewater treatment. Although an exponential growth in MOF literature has been observed in recent years, conducting a quantitative literature analysis of MOF application in wastewater treatment is a novelty. To fill this gap, a total of 1187 relevant publications were extracted from the Web of Science, published during the last 50 years, and analyzed using bibliometric and content analysis techniques. A bibliometric analysis was conducted to reveal growing publication trends, leading journals, prolific countries, and organizations; whereas, a content analysis was used to highlight key research themes and hot topics in this field. The analyses revealed that there is a strong international collaboration among authors, countries, and organizations. Chemical Engineering Journal, Journal of Hazardous Materials, and Journal of Environmental Chemical Engineering are the most prolific journals in this field. Furthermore, the use of MOFs for removing antibiotics from wastewater was identified as a recent hot topic. In addition, performance enhancements of MOFs, in terms of a higher adsorption capacity and water stability, were identified as topics of great interest. To cater to these issues, the application of graphene, graphene oxides, nanoparticles, and quantum dots was also observed in the research fronts in this field.

It has been claimed that the adoption of a smart and sustainable city concept is one of the most effective ways to eliminate the risk of unsustainable living. Since the sixties, the Kingdom of Saudi Arabia was transformed from a country of traditional settlements to a modern urban setting. However, this development has been based on conventional methods of city construction and building practices. Therefore, the main aim of this primary research is to establish the fundamental aspects of developing a sustainable and smart city framework that can be applied to most Saudi Arabian cities and societies. A qualitative research methodology is adopted to determine end-user requirements, with more than 500 well-informed participants from 17 different cities. Subsequently, the main contributions here can be summaries as follows: (a) evaluating public willingness regarding smart sustainable city movements, (b) establishing requirements for a sustainable and smart city framework based on end-user perspectives, (c) providing a decision makers with a robust generic framework of sustainable development across Saudi Arabian cites, and (d) an Internet of Thing (IoT) architecture for SSC Adoption and implementation along with an integrated socio-organizational, financial, and technical generic framework for smart sustainable city adoption in the Saudi Arabian context.