Continually using fossil fuels as the main source for producing electricity is one of the main factors causing global warming. Through the past years, several efforts have been made, looking for sustainable, environmentally friendly, and clean energy alternatives. Harvesting geothermal energy from roadway pavement is one of the alternatives that have been developed and investigated recently. Herein, a systematic review and bibliometric analysis were conducted to provide a comprehensive overview of the potentials of harvesting thermal energy from asphalt pavement and to assess the level of achievement being attained towards developed technologies. A total of 713 articles were initially collected, considering the period between 2006 and 2021; later, a series of filtration processes were performed to reach 47 publications. The thermal energy harvesting technologies were categorized into three main sectors, at which their basics and principles were discussed. In addition, a detailed description of the systems’ configurations, materials, and efficiency was presented and described. Finally, gaps and future directions were summarized at the end of this paper. The fundamental knowledge introduced herein can inspire researchers to detect research gaps and serve as a wake-up call to motivate them to explore the high potentials of utilizing pavements as a clean and sustainable energy source.
Natural hazard threats have grown as a result of climate change, fast demographic development, and major urbanization. Devastating floods have occurred in several areas of the world recently, including the Kingdom of Saudi Arabia, which is located in a region with a dry environment. In arid or semi-arid regions, rapidly forming flash floods associated with debris flowing down over dry water courses leading to a potential threat to both lives and property. Being located at the coastal plain of western Saudi Arabia, Jeddah City has witnessed an unexpected amount of rainfall events in recent years. Such extreme rainfall events, integrated with other factors, namely topography, land use, surface runoff, etc., have led to flood generation, which is alarming indeed. Herein, this paper addresses the varying climatic classifications of the Kingdom, its risk and vulnerability, followed by reasoning about the impact of flash flood events and the associated casualties and property losses. Further, it reports about the existing strategies of the government and proposes a systematic way forward on how to alleviate such events in future. Thus, risk variables have been discovered and integrated in the context of climate change and rising anthropogenic strain on coastal communities to give planners and decision makers tools to assure effective and appropriate flood risk management.
Global climate change has increased severe torrential hazards, particularly debris flows in mountainous regions. After floods and earthquakes, debris flows are the most devastating natural hazard in the world. The effects of debris flow on human life and built environments necessitate reconsidering current infrastructure planning, engineering, and risk management practices. Hence, the vulnerability of elements at risk is critical for effective risk reduction systems. Therefore, this article reviews the existing physical vulnerability approach of infrastructure, particularly building toward debris flow hazards in the last 20 years. Furthermore, uncertainties associated with the vulnerability assessment and their quantification techniques have also been discussed in detail. It was found that matrices, curves, and indicators have been extensively used for vulnerability assessment approaches in the last two decades. However, if aleatory and epistemic uncertainties are not quantified or conserved in the vulnerability assessment process, it makes the system inefficient and unreliable. Moreover, data requirements, strengths, and weaknesses of approaches presented herein are highlighted with case studies. Finally, a thorough discussion on future needs in the field of risk assessment methodologies is highlighted by considering uncertainties into account.