Sustainability has become a focus area for practitioners and scholars due to the growing socio-economic issues. The sustainability of airport operations is being raised in various international platforms. This paper aims to identify the dimensions of sustainability and evaluate sustainable practices in airports of selected ASEAN countries. The various dimensions associated with the environmental aspect are energy management, emissions management, water and effluents management, solid waste management. It was understood that noise management, employee development, and community investment belong to the social dimension. Similarly, the factors such as economic contribution, passenger experience, airport safety, and security are inclined to economic dimensions of sustainability. It was found that environmentally sustainable practices have greater importance than social and economic initiatives in the airport context which provide quantifiable benefits for airports in the long term. Airport operators in South East Asia strived to mitigate carbon emissions, reduce waste and effluents, enhance the economic contribution, satisfy passengers, and meet employee needs. Compared to the total economic and social benefits obtained from these airports, the negative impacts of airport operation (such as noise emission from aircraft) are minimal but significant. The most common sustainable initiatives in airports, such as employee development, energy management, and passenger safety, supported sustainable development goals (SDG) 8, SDG 9, and SDG 11. A weak connection is observed between SDG 14 & SDG 15 and the airport's sustainable practices. The new technological innovations are concentrated in busy and profitable airports. A slow trend towards the adoption of new technologies for sustainable practices is observed in airports. The paper concludes that major airport operators in South-East Asia have effectively responded to the growing sustainability challenges in aviation markets. The sustainable dimensions and practices discussed will be valuable resource for airports striving to achieve sustainability goals.
In the realm of internal combustion engines, there is a growing utilization of alternative renewable fuels as substitutes for traditional diesel and gasoline. This surge in demand is driven by the imperative to diminish fuel consumption and adhere to stringent regulations concerning engine emissions. Sole reliance on experimental analysis is inadequate to effectively address combustion, performance, and emission issues in engines. Consequently, the integration of engine modelling, grounded in machine learning methodologies and statistical data through the response surface method (RSM), has become increasingly significant for enhanced analytical outcomes. This study aims to explore the contemporary applications of RSM in assessing the feasibility of a wide range of renewable alternative fuels for internal combustion engines. Initially, the study outlines the fundamental principles and procedural steps of RSM, offering readers an introduction to this multifaceted statistical technique. Subsequently, the study delves into a comprehensive examination of the recent applications of alternative renewable fuels, focusing on their impact on combustion, performance, and emissions in the domain of internal combustion engines. Furthermore, the study sheds light on the advantages and limitations of employing RSM, and discusses the potential of combining RSM with other modelling techniques to optimise results. The overarching objective is to provide a thorough insight into the role and efficacy of RSM in the evaluation of renewable alternative fuels, thereby contributing to the ongoing discourse in the field of internal combustion engines.