Conceptualizing environmental effects of carsharing services: A system thinking approach

Waste management beyond the COVID-19 pandemic: Bibliometric and text mining analyses

The outbreak of the COVID-19 pandemic has significantly increased the demand for personal protective equipment, in particular face masks, thus leading to a huge amount of healthcare waste generated worldwide. Consequently, such an unprecedented amount of newly emerged waste has posed significant challenges to practitioners, policy-makers, and municipal authorities involved in waste management (WM) systems. This research aims at mapping the COVID-19-related scientific production to date in the field of WM. In this vein, the performance indicators of the target literature were analyzed and discussed through conducting a bibliometric analysis. The conceptual structure of COVID-19-related WM research, including seven main research themes, were uncovered and visualized through a text mining analysis as follows: (1) household and food waste, (2) personnel safety and training for waste handling, (3) sustainability and circular economy, (4) personal protective equipment and plastic waste, (5) healthcare waste management practices, (6) wastewater management, and (7) COVID-19 transmission through infectious waste. Finally, a research agenda for WM practices and activities in the post-COVID-19 era was proposed, focusing on the following three identified research gaps: (i) developing a systemic framework to properly manage the pandemic crisis implications for WM practices as a whole, following a systems thinking approach, (ii) building a circular economy model encompassing all activities from the design stage to the implementation stage, and (iii) proposing incentives to effectively involve informal sectors and local capacity in decentralizing municipal waste management, with a specific focus on developing and less-developed countries.

Development of a system model to predict flows and performance of regional waste management planning: A case study of England

Significant loss of valuable resources and increasing burdens on landfills are often associated with a lack of proper planning in waste management and resource recovery strategy. A sustainable waste management model is thus urgently needed to improve resource efficiency and divert more waste from landfills. This paper proposes a comprehensive system model using stock-and-flow diagram to examine the current waste management performance and project the future waste generation, treatment and disposal scenarios, using England as a case study. The model comprises three integrated modules to represent household waste generation and collection; waste treatment and disposal; and energy recovery. A detailed mass and energy balance has been established and waste management performance has been evaluated using six upstream and downstream indicators. The base case scenario that assumes constant waste composition shows that waste to landfills can be reduced to less than 10% of the total amount, by 2035. However, it entails greater diversion of waste to energy-from-waste facilities, which is not sustainable and would incur higher capital investment and gate fees. Alternative case scenarios that promote recycling instead of energy recovery result in lower capital investment and gate fees. Complete elimination of the food and organic fraction from the residual waste stream will help meet the 65% recycling target by 2035. In light of the need for achieving a more circular economy in England, enhancing material recovery through reuse and recycling, reducing reliance on energy-from-waste and deploying more advanced waste valorisation technologies should be considered in future policy and planning for waste management.

What Car for Car-Sharing? Conventional, Electric, Hybrid or Hydrogen Fleet? Analysis of the Vehicle Selection Criteria for Car-Sharing Systems

Short-term car rental services called “car-sharing” or “carsharing” are systems that in recent years have been an alternative form of transport by individual car in an increasing number of cities around the world. With the growing popularity of services, new decision-making problems have arisen among system operators. Among the challenges faced by operators, due to the constantly growing environmental requirements, is the fleet of vehicles for car-sharing systems-appropriate selection. Noticing this research gap, this article was dedicated to determining the criteria that are important when choosing a fleet of vehicles for car-sharing and to indicate the best suited to the needs of car-sharing vehicles. Own research was proposed, considering desk research, expert research and analyses using the multi-criteria decision support method (ELECTRE III). This research was carried out for the Polish market of car-sharing services. Studying the Polish market is appropriate due to the occurrence of significant difficulties with the fleet incorrectly adjusted to the needs of urban conditions. This study covers vehicles with conventional, electric, hybrid and hydrogen propulsion. The analyses allowed for the determination of the vehicles best suited to the needs of car-sharing. The results show the dominance of hydrogen-powered vehicles over conventional, hybrid and electric vehicles. What is more, it was determined that the most important criteria are the purchase price of the vehicle and energy/fuel consumption per 100 km. The obtained results are a guide to proceeding when making decisions regarding the implementation or modernization of the fleet in car-sharing systems. The results also support achieving more sustainable urban mobility in the zero-emission trend through hydrogen mobility.

Service Failure Risk Assessment and Service Improvement of Self-Service Electric Vehicle

Electric vehicle sharing is necessary for achieving carbon neutrality. The self-service electric vehicle mode offers unique advantages in terms of freedom of movement and privacy protection. Meanwhile, this mode requires a high-quality service guarantee because of the separation of management and use. The purpose of this study is to propose a framework for the risk control and service optimization of self-service electric vehicles, which includes service life cycle analysis, risk assessment by using a newly integrated fuzzy failure mode and effect analysis, and a consumer satisfaction survey based on the Kano model. Sixteen services were extracted through the service life cycle analysis and online review study, and their corresponding service failures were then ranked through risk assessment. The risk assessment showed that the reliability of vehicle-related services has the greatest impact on safety, followed by financial-related and driving-safety-related services. A Kano model-based survey showed that all kinds of service failures brought significant customer non-satisfaction, while different service improvements brought differentiated satisfaction. To deeply improve service satisfaction, a Risk-Satisfaction analysis was conducted, indicating that services with high risk and high satisfaction deserve further investment.

What Kind of Travellers Are Using Carsharing in Beijing? A Study Based on Selective Ensemble Learning

As a new urban travel mode, carsharing is significantly different from private cars, buses and other travel modes. Therefore, clarifying the typical characteristics of carsharing, such as individual users’ attributes, travel environment and travel behaviour, is conducive to accurately grasping the development of carsharing. In this study, a selective ensemble learning model is established to analyse typical travel characteristics of carsharing. Firstly, personal characteristics, environmental characteristics and behavioural characteristics were obtained through integrating order data, global positioning system data and station information. Then, based on a consolidated view of carsharing, different types of carsharing travel characteristics were distinguished using selective ensemble learning. Lastly, all kinds of carsharing travel are described in detail. It was identified through this research that carsharing travel can be divided into four kinds: long distance for leisure and entertainment, medium and short distances for business and commuting, a mixed category of medium and short distances for business and residence, and a mixed category of long distance for business and residence. This study can provide a theoretical reference and practical basis for precise planning and design and the scientific operation of carsharing.

Traffic-induced atmospheric pollution during the COVID-19 lockdown: Dispersion modeling based on traffic flow monitoring in Turin, Italy

The COVID-19 pandemic, as a worldwide threat to public health, has led many governments to impose mobility restrictions and adopt partial or full lockdown strategies in many regions to control the disease outbreak. Although these lockdowns are imposed to save public health by reducing the transmission of the virus, rather significant improvements of the air quality in this period have been reported in different areas, mainly as a result of the reduction in vehicular trips. In this research, the city of Turin in the northern part of Italy has been considered as the study area, because of its special meteorology and geographic location in one of the most polluted regions in Europe, and also its high density of vehicular emissions. A Lagrangian approach is applied to illustrate and analyze the effect of imposing full lockdown restrictions on the reduction of traffic-induced air pollution in the city. To do this, the real-time traffic flow during the lockdown period is recorded, and by utilizing CALPUFF version 7, the dispersion of PM_2.5, Total Suspended Particulate (TSP), Benzo(a)pyrene (BaP), NO_x, and Black Carbon (BC) emitted from all circulating vehicles during and before the lockdown period are compared. Results indicate that the concentration of pollutants generated by road traffic sources (including passenger cars, busses, heavy-duty vehicles, light-duty vehicles, mopeds, and motorcycles) reduced at least 70% (for PM_2.5) up to 88.1% (for BaP) during the studied period. Concentration maps show that the concentration reduction varied in different areas of the town, mainly due to the characteristics and strength of the emission sources and the geophysical features of the area.

Three pillars of sustainability in the wake of COVID-19: A systematic review and future research agenda for sustainable development

The COVID-19 pandemic has immensely impacted the economic, social, and environmental pillars of sustainability in human lives. Due to the scholars' increasing interest in responding to the urgent call for action against the pandemic, the literature of sustainability research considering COVID-19 consequences is very fragmented. Therefore, a comprehensive review of the COVID-19 implications for sustainability practices is still lacking. This research aims to analyze the effects of COVID-19 on the triple bottom line (TBL) of sustainability to support the future sustainable development agenda. To achieve that, the following research questions are addressed by conducting a systematic literature review: (i) what is the current status of research on the TBL of sustainability considering COVID-19 implications? (ii) how does COVID-19 affect the TBL of sustainability? and (iii) what are the potential research gaps and future research avenues for sustainable development post COVID-19? The results manifest the major implications of the COVID-19 outbreak for the triple sustainability pillars and the sustainable development agenda from the economic, social, and environmental points of view. The key findings provide inclusive insights for governments, authorities, practitioners, and policy-makers to alleviate the pandemic's negative impacts on sustainable development and to realize the sustainability transition opportunities post COVID-19. Finally, five research directions for sustainable development corresponding to the United Nations' sustainable development goals (SDGs) post COVID-19 are provided, as follows: (1) sustainability action plan considering COVID-19 implications: refining sustainability goals and targets and developing measurement framework; (2) making the most of sustainability transition opportunities in the wake of COVID-19: focus on SDG 12 and SDG 9; (3) innovative solutions for economic resilience towards sustainability post COVID-19: focus on SDG 1, SDG 8, and SDG 17; (4) in-depth analysis of the COVID-19 long-term effects on social sustainability: focus on SDG 4, SDG 5, and SDG 10; and (5) expanding quantitative research to harmonize the COVID-19-related sustainability research.