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Profiting from the benefits of smart products connected through the Internet of Things (IoT) could disrupt business models and has the potential to foster a circular economy by embracing a performance economy. Extant literature has offered insights into circular strategies, smart products and product-service systems (PSS) in isolated ways or by considering partial overlaps, but lacks a holistic account of their interplay. By means of an integrated review, this paper synthesises literatures from various domains to describe interrelationships among these three concepts and propose a conceptual framework of smart-circular systems. This paper thereby advances research by providing a description of three binary interrelationships: smart circularity, smart PSS and circular PSS. Moreover, the review elaborates a new understanding of smart-circular (product-service) systems by articulating the base strategy smart use and extending the following circular strategies (or technical loops): maintenance, reuse, remanufacturing and recycling. Finally, the review outlines a critique of the state of the literature on this phenomenon and offers suggestions to guide future empirical and theoretical research in the domains of circular strategies, services and business models.

Currently, the “2019-CoV-2” has been raging across the world for months, causing massive death, huge panic, chaos, and immeasurable economic loss. Such emerging epidemic viruses come again and again over years, leading to similar destructive consequences. Air-borne transmission among humans is the main reason for the rapid spreading of the virus. Blocking the air-borne transmission should be a significant measure to suppress the spreading of the pandemic. Considering the hospital is the most “dangerous” place to occur massive cross-infection among patients as emerging virus usually comes in a disguised way, an air distribution optimization of a general three-bed hospital ward in China is carried out in this paper. Using the Eulerian-Lagrangian method, sneeze process from patients who are assumed to be the virus carrier, which is responsible for a common event to trigger cross-infection, is simulated. The trajectory of the released toxic particle and the probability of approaching others in the same ward are calculated. Two evaluation parameter, total maximum time (TMT) and overall particle concentration (OPC) to reflect the particle mobility and probability to cause cross-infection respectively, are developed to evaluate the proposed ten air distributions in this paper. A relatively optimized air distribution proposal with the lowest TMT and OPC is distinguished through a three-stage actively analysis. Results show that a bottom-in and top-out air distribution proposal is recommended to minimize the cross-infection., Highlights • A ward-based sneeze process from a patient with epidemic disease is modeled. • Air distribution (AD) affects the flow pattern of the sneeze-induced virus particles. • Ten AD proposals are developed to evaluate the their probability of cross-infection. • Two parameters are proposed to judge which proposals is better quantitatively. • The direct probability of cross-infection can be decreased by 95% via optimization.

Recent decades have witnessed considerable research advances on the relationship between sustainable product attributes and consumer decision-making. However, despite the substantial body of research, findings remain fragmented and sometimes even contradictory. This study provides a state-of-the-art overview of extant research, uncovers knowledge gaps and develops recommendations for future research. Specifically, it presents a systematic review of research into relationships between sustainable product attributes and consumer decision-making over the past decade (2008–2018). In general, this review finds that most papers assume linear and rational consumer decision-making process, focus on environmental sustainability, and mostly examine food products; social sustainability is comparatively neglected, as is work that addresses cultural contexts, particularly differences between emerging and developed countries.

Electric vehicle (EV) owners enjoy many positive aspects when driving their cars, including low running costs and zero tailpipe gas emissions, which makes EVs a clean technology provided that they are sourced through renewable sources, e.g., biomass, solar power, or wind energy. However, their driving behaviour is often negatively affected by the so-called range anxiety phenomenon, i.e., a concern that an EV might not have enough driving range to reach the desired destination due to its limited battery size. The perception of range anxiety may also affect potential buyers in their decisions on whether to purchase an internal combustion engine vehicle as opposed to an EV. This paper investigates some factors that influence range anxiety through a comparative analysis of two target groups: (i) existing EV owners, and (ii) non-EV owners (i.e., potential EV owners). The specially crafted survey was used to collect range anxiety data from more than 200 participants. In particular, participants provided their perceptions on (i) the potential relationship between existing gas station infrastructure and the desired EV charging station infrastructure, and (ii) the potential relationship between range anxiety and two influencing variables, namely the current state of charge and remaining range. Concerning the existing gas station infrastructure, evidence suggests that both target groups think that the distances between gas stations could be increased. Moreover, our analysis shows that the desired distances between charging stations correspond to the distances between the existing gas stations, which indicates that both EV owners and non-EV owners have a common view on the optimal gas station and charging station topology. Furthermore, we find that the type of settlement (urban vs rural) influences preferred distances, where both target groups living in cities desire shorter distances, and that non-EV owners, as opposed to EV owners, are more prone to be affected by the state of charge and remaining range. Quantitatively, we are able to define a measure for range anxiety, which is connected with the preferred distance between two neighbouring charging stations. Throughout our analyses, we find that the mean preferred distance between two neighbouring charging stations is 7 km, but this value significantly differs based on the settlement type of a (potential) EV owner.

Cities have been one of the most important areas of CO2 emissions. It is increasingly important to research the effect of urbanization on CO2 emissions, especially in large emerging and developing economies, due to the indispensable need for understanding the effect of urbanization on CO2 emissions, evaluating carbon reduction tasks and providing the scientific basis for low-carbon urbanization. Utilizing a balanced panel dataset in the Yangtze River Delta (YRD), China, during the period of 2000–2010, this paper employed data envelopment analysis (DEA) window analysis and a spatial lag panel Tobit model to investigate the effect of urbanization on CO2 emissions efficiency (the ratio of the target CO2 emissions to the actual CO2 emissions). The results show that the average CO2 emissions efficiency was 0.959 in 2010, and CO2 emissions efficiency ranged from 0.816 to 1 and exhibited spatial clustering in the region. The larger potential of CO2 emissions reduction appeared in Zhenjiang and Yangzhou, indicating that more CO2 emissions reduction tasks should be allocated to these two cities. Urbanization has negative effects on improving CO2 emissions efficiency, and there is a U-curve relation between CO2 emissions efficiency and urbanization, indicating that CO2 emissions efficiency decreases at the early stage of urbanization, then increases when urbanization reach a high level. There is spatial spillover effect among the prefecture-level cities, suggesting that different prefecture-level governments should coordinate with each other to improve CO2 emissions efficiency in the whole area. Gross domestic product (GDP) per capita also plays a markedly positive role in improving CO2 emissions efficiency. This research highlights the effect of urbanization on CO2 emissions efficiency and the importance of improving CO2 emissions efficiency in developing countries., Highlights • The effect of urbanization on CO2 emission efficiency in the YRD was investigated. • DEA window analysis and spatial lag panel Tobit model were utilized. • Urbanization, GDP and spatial effect have marked effects on CO2 emission efficiency.

Based on the newly adopted strategy “The European Green Deal”, by 2050, the European Union should become the first climate neutral region worldwide. This very ambitious goal will require many political, social and economic activities. Huge financial resources will also be needed to change the economy in order to reduce the emissions of harmful substances into the environment. The implementation of such an ambitious climate policy requires the development of a very reasonable economic plan, backed by many analyses, to ensure adequate financing of this idea. One of the basic objectives of such a plan should be to appropriately target aid funds to a group of countries with a similar structure of the emissions in question. The identification of the groups of similar countries in terms of the structure of harmful substance emissions requires the development of both appropriate methodology and applicable studies. Such methodology is presented in this paper, namely the Kohonen’s artificial neural network model. The main objective of the developed methodology was to divide the European Union countries into groups similar in terms of the emissions of selected gases and dusts into the atmosphere. In addition to the division of the European Union countries into similar groups by the total volume of the emissions of studied substances, completely new division criteria were introduced. It was assumed that in order for the results of this study to be practically used, it is necessary to broaden the scope of the analysis. Therefore, an additional division of the European Union countries was made in relation to the volume of the emissions per capita, the value of gross domestic product and the area of a given country. This new approach was intended to show the diversity of the European Union countries in economic, demographic and geographical terms. The grouping results should be regarded as additional information to be utilized when preparing specific action plans to improve the state of the environment. Definitely, these plans need to be dedicated both to the groups of countries and the entire sectors in these groups. This will enable the efficient use of financial resources and can be a huge impetus for the European Union economic development. It will also allow smaller and less prosperous countries to achieve their goals. Undoubtedly, the developed methodology and conducted research allowed the authors to solve a significant research problem, and the results can be successfully used in practice., Highlights • Greenhouse gas and air pollutant levels vary greatly amongst EU Member States. • Three greenhouse gases and six air pollutants are analyzed. • European Union countries were used as grouping objects using a SOM method. • The aim was to group the EU countries into homogeneous groups by the of gas and dust emissions to the atmosphere.

This paper performs an emergy analysis (EmA) to compare two real power plants include a conventional natural gas steam power plant (NGPP) with one that burns municipal solid waste (MSWPP). For this purpose, the EmA is used to investigate the sustainability, renewability, environmental impacts, and economic issues. The capacity of the NGPP and MSWPP are 247.5 and 3 MW, respectively. Results from this study show that the percent of renewability (PR) and emergy sustainability index (ESI) of the MSWPP are much more than those of the NGPP. The PR and ESI of the MSWPP are 46.81 and 1.65, while for the NGPP are 5.01 and 0.05, respectively. It is proved that the MSWPP is more efficient and has the better environmental impacts compared to the NGPP. Moreover, a hypothetical MSWPP with the same electricity output of the NGPP is studied using the EmA. A more efficient system with the higher PR and ESI is observed compared to the other case studies. Beside of these advantages, use of the MSW has other benefits such as reducing the greenhouse gases released in the atmosphere, saving fossil fuels, low land area required compared to the landfill, speed and ease of disposal, and production of clean and useful ash., Highlights • Emergy analysis is used to compare two kind of power plants. • The fuels of one of the power plants is natural gas and the other is MSW. • The emergy indices (EYR, ELR, and ESI) have been computed to compare them. • The best ESI is obtained by using the MSW as a fuel in power plants.