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Microplastics in the environment are a subject of intense research as they pose a potential threat to marine organisms. Plastic fibers from textiles have been indicated as a major source of this type of contaminant, entering the oceans via wastewater and diverse non-point sources. Their presence is also documented in terrestrial samples. In this study, the amount of microfibers shedding from synthetic textiles was measured for three materials (acrylic, nylon, polyester), knit using different gauges and techniques. All textiles were found to shed, but polyester fleece fabrics shed the greatest amounts, averaging 7360 fibers/m−2/L−1 in one wash, compared with polyester fabrics which shed 87 fibers/m−2/L−1. We found that loose textile constructions shed more, as did worn fabrics, and high twist yarns are to be preferred for shed reduction. Since fiber from clothing is a potentially important source of microplastics, we suggest that smarter textile construction, prewashing and vacuum exhaustion at production sites, and use of more efficient filters in household washing machines could help mitigate this problem.

With the global outbreak of coronavirus disease (COVID-19) all over the world, artificial intelligence (AI) technology is widely used in COVID-19 and has become a hot topic. In recent 2 years, the application of AI technology in COVID-19 has developed rapidly, and more than 100 relevant papers are published every month. In this paper, we combined with the bibliometric and visual knowledge map analysis, used the WOS database as the sample data source, and applied VOSviewer and CiteSpace analysis tools to carry out multi-dimensional statistical analysis and visual analysis about 1903 pieces of literature of recent 2 years (by the end of July this year). The data is analyzed by several terms with the main annual article and citation count, major publication sources, institutions and countries, their contribution and collaboration, etc. Since last year, the research on the COVID-19 has sharply increased; especially the corresponding research fields combined with the AI technology are expanding, such as medicine, management, economics, and informatics. The China and USA are the most prolific countries in AI applied in COVID-19, which have made a significant contribution to AI applied in COVID-19, as the high-level international collaboration of countries and institutions is increasing and more impactful. Moreover, we widely studied the issues: detection, surveillance, risk prediction, therapeutic research, virus modeling, and analysis of COVID-19. Finally, we put forward perspective challenges and limits to the application of AI in the COVID-19 for researchers and practitioners to facilitate future research on AI applied in COVID-19.

Graphical abstract A massive increase in the use and production of masks worldwide has been seen in the current COVID-19 pandemic, which has contributed to reducing the transmission of the virus globally. This paper aims to evaluate the life cycle environmental impacts of disposable medical masks to identify the life cycle stages that cause the highest impact on the environment. A further goal is to estimate the total environmental impacts at the global level in 2020. The inventory data was constructed directly from the industry. The system boundary of the study is from cradle to grave comprising raw material extraction and processing, production, packaging, distribution, use, and disposal as well as transport and waste management along the supply chain. Eleven environmental impacts have been estimated. The results suggest that the global warming potential of a disposable medical mask is 0.02 g CO2-eq. for which the main contributor is the raw material supply (40.5%) followed by the packaging (30.0%) and production (15.5%). Sensitivity analysis was carried out to test the environmental impacts. In total, 52 billion disposable medical masks used worldwide consumes 22 TJ of energy in 2020. The global warming potential of disposable medical masks supplied in a year of the COVID-19 pandemic is 1.1 Mt CO2 eq. This paper assessed the hotspots in the medical mask. The findings of this study will be of interest to policymakers, global mask manufacturers, and users, allowing them to make more informed decisions about the medical mask industry.

Renewable energy plays a significant role in achieving energy savings and emission reduction. As a sustainable and environmental friendly renewable energy power technology, concentrated solar power (CSP) integrates power generation and energy storage to ensure the smooth operation of the power system. However, the cost of CSP is an obstacle hampering the commercialization of this emerging industry, so the paper studies the technical characteristics, economic analysis, and policy implications of CSP. This paper sorts out the relevant policies of CSP and uses the levelized cost of electricity (LCOE) model by considering financial parameters, investment parameters, operation and maintenance parameters, tax parameters, capacity parameters, etc., to analyze the economics of CSP. The model parameters are set by the actual situation of CSP projects. The economic evaluation of different technology types of parabolic trough (PT), solar tower (ST), secondary reflection ST, and linear Fresnel reflector (LFR) is carried out. The LCOE of PT project is 1.11 RMB/kWh (0.17 US$/kWh), the ST project is 0.93 RMB/kWh (0.14 US$/kWh), the secondary reflection ST project is 0.97 RMB/kWh (0.15 US$/kWh), and the LFR project is 0.92 RMB/kWh (0.14 US$/kWh). The results show that the grid parity era of CSP in China is within reach, and ST is the most potential technology type. Based on the results of economic analysis and the problems faced by CSP in China, this paper puts forward policy implications by preferential loans, tax incentives, and R&D fund support to promote the development of CSP.

Biopolymer-based flocculants have become a potential substitute for inorganic coagulants and synthetic organic flocculants due to their wide natural reserves, environmental friendliness, easy natural degradation, and high material safety. In recent years, with more and more attention to clean technologies, a lot of researches on the modification and application of biopolymer-based flocculants have been carried out. The present paper reviews the latest important information about the base materials of biopolymer-based flocculants, including chitosan, starch, cellulose, and lignin etc. This review also highlights the various modification methods of these base materials according to reaction types in detail. Via the recent researches, the flocculation mechanisms of biopolymer-based flocculants, such as adsorption, bridging, charge neutralization, net trapping, and sweeping, as well as, some other special mechanisms are comprehensively summarized. This paper also focuses on the water treatment conditions, the removal efficiency, and advantages of biopolymer-based flocculants in applications. Further, this review sheds light on the future perspectives of biopolymer-based flocculants, which may make progress in the sources of base materials, modification processes, multi-function, and deepening application researches. We believe that this review can guide the further researches and developments of biopolymer-based flocculants in the future, to develop them with a higher efficiency, a lower cost, more safety, and multi-function for more diversified applications. Graphical abstract.

Even though higher education R&D expenditures (HEEXP) are important determinants of economic growth that facilitate science, technology, new ideas, and innovation, yet its effect on environmental sustainability remains unexplored. This paper examines the nexus between HEEXP and carbon dioxide emissions (CO2e), followed by control variables such as electricity consumption (EC), foreign direct investment (FDI), gross domestic product (GDP), and total population (TP) for the period 2000Q1–2019Q4. Data were evaluated using different tests, e.g., the cross-sectional dependence test, cross-sectionally augmented Dickey-Fuller unit root test, Westerlund error-correction–based panel cointegration test, mean group, augmented mean group, common correlated effects mean group, and Dumitrescu-Hurlin panel causality test. First, the results validated the cointegration association among HEEXP, EC, FDI, GDP, TP, and CO2e. Second, the finding showed significant long-term negative nexus between HEEXP and CO2e. Third, the findings indicated that electricity consumption, foreign direct investment, gross domestic product, and total population are the important factors that intensify the overall situation of CO2e. Fourth, the results indicated that there exists bidirectional causality between EC and CO2e; FDI and CO2e; GDP and CO2e; POP and CO2e; and HEEXP and CO2e. This paper’s findings call for devising policies and strengthening financial support to induce higher education for developing green patents.

The facilities that energy delivers to social life and economic activities render it indispensable. Hence, it is equally critical that the energy cycle must have a sustainable structure. Therefore, it is an indisputable fact that developing and performing correct and consistent energy policies is vitally necessary. Energy consumption planning includes a continuous process to reassess existing and potential alternative energy approaches and strategies. The public and private decision-makers in charge of planning and managing energy consumption policies must adapt their strategies to novel and superior alternative resources according to sustainability and efficiency criteria. In this paper, the fuzzy EDAS method is used to address the best renewable energy consumption by taking political, economic, social, technological, legal, and environmental (PESTLE) dimensions into account. The analysis of the paper indicates the most efficient renewable energy consumption is sourced by geothermal, solar, wind, hydroelectricity, and biomass, respectively. By further investigation, it is concluded that the most optimum renewable energy consumption alternatives based on PESTLE dimensions are geothermal and solar energies.

Environment protection and food safety are two critical issues in the world. In this review, a novel approach which integrates statistical study and subjective discussion was adopted to review recent advances on environment and food safety. Firstly, a scientometric-based statistical study was conducted based on 4904 publications collected from the Web of Science Core Collection database. It was found that the research on environment and food safety was growing steadily from 2001 to 2020. Interestingly, the statistical analysis of most-cited papers, titles, abstracts, keywords, and research areas revealed that the research on environment and food safety was diverse and multidisciplinary. In addition to the scientometric study, strategies to protect environment and ensure food safety were critically discussed, followed by a discussion on the emerging research topics, including emerging contaminates (e.g., microplastics), rapid detection of contaminants (e.g., biosensors), and environment friendly food packaging materials (e.g., biodegradable polymers). Finally, current challenges and future research directions were proposed. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-021-16069-6.

This paper assesses the convergence of the EU-28 countries toward their common goal of 20% in the renewable energy share indicator by year 2020. The potential presence of clubs of convergence toward different steady-state equilibria is also analyzed from both the standpoints of global convergence to the 20% goal and specific convergence to the various targets assigned to Member States. Two clubs of convergence are detected in the former case, each corresponding to different renewable energy source targets. A probit model is also fitted with the aim of better understanding the determinants of club membership, which seemingly include real GDP per capita, expenditure on environmental protection, energy dependence, and nuclear capacity, with all of them having statistically significant effects. Finally, convergence is also analyzed separately for the transport, heating and cooling, and electricity sectors.

In recent times, the issue of plastic recycling has become one of the leading issues of environmental protection and waste management. Polymer materials have been found an application in many areas of daily life and industry. Along with their extended use, the problem of plastic wastes appeared because, after withdrawal from use, they became persistent and noxious wastes. The possibility of reusing polymeric materials gives a possibility of valorization—a second life—and enables effective waste utilization to obtain consumable products. The 3D printing market is a well-growing sector. Printable filaments can be made from a variety of thermoplastic materials, including those from recycling. This paper focuses on a review of the available literature on the production of filaments for 3D printers from recycled polymers as the alternative to present approach of central selective collection of plastics. The possibility of recycling of basic thermoplastic materials and the impact of processing on their physicochemical and mechanical properties were verified (Lanzotti et al. 2019). In addition, commercially available filaments produced from recycled materials and devices which allow self-production of filaments to 3D printing from plastic waste were reviewed.

As the whole world is witnessing what novel coronavirus (COVID-19) can do to the mankind, it presents several unique features also. In the absence of specific vaccine for COVID-19, it is essential to detect the disease at an early stage and isolate an infected patient. Till today there is a global shortage of testing labs and testing kits for COVID-19. This paper discusses about the role of machine learning techniques for getting important insights like whether lung computed tomography (CT) scan should be the first screening/alternative test for real-time reverse transcriptase-polymerase chain reaction (RT-PCR), is COVID-19 pneumonia different from other viral pneumonia and if yes how to distinguish it using lung CT scan images from the carefully selected data of lung CT scan COVID-19-infected patients from the hospitals of Italy, China, Moscow and India? For training and testing the proposed system, custom vision software of Microsoft azure based on machine learning techniques is used. An overall accuracy of almost 91% is achieved for COVID-19 classification using the proposed methodology.

Wind energy is seen as an important energy to sustainably meet the energy needs of Ghana. However, the industry in Ghana is yet to take off due to policy uncertainty and regulatory costs. The paper analyzed the key determinants and how they interact to impact the scaling up of wind energy in Ghana, using time series data, the vector auto regression (VAR) model from 2013 to 2019.There were four endogenous variables, grouped under policy, population growth, wind capacity, and electrification rate. The findings revealed the dynamic behavior of the variables from the VAR to a strongly significant positive correlation to deploying wind energy in Ghana. The impulse response functions (IRFs) equally exhibited a positive impact long-run trajectory growth of the variables after a shock to the system. The response of the first lags had differences of log policy and that of the log of GDP produced a curious result from the shock by taking a steady positive growth path in the short run and nosedived to a negative pathway in the long run. On the other hand, the interaction of the first differences of the lags of log wind capacity and log policy is quite instructive, as the headwind produced a negative relationship in the short run and to a positive growth path in the long run. This was anticipated, as the wind capacity installation of Ghana is expected to increase in the long run, when pipeline projects materialize.

Sustainable development has by now become an element deeply integrated in the everyday design. It has many shades and may be found under many names. We speak about resiliency in design and procurement of passive, ecologic, plus energy, or nZEB buildings. Nevertheless, if we look closely, we may distinguish certain characteristic ideas. First, sustainable development of societies and urbanization processes should be consistent on a deeper level than presently, and be included within design processes, organization, and planning, as well as modernization and redevelopment procedures of existing urban tissue. Secondly, urbanization should be perceived holistically, as an interaction and harmonious development of both natural and manmade environments, with solutions based on the best technical and technological standards available. Lastly, described ideas are achievable only, if we include continuous cooperation between urban planners, architects, specialist consultants, as well as energy-efficient interdisciplinary solutions to achieve high standard energy measures. One of the thresholds is economic feasibility; the other is health and well-being of the users which should always be discussed as a priority. This paper—outside a brief theoretical approach to initial procedures in design management—will dwell on transformation and modernization of an existing building belonging to the Warsaw University of Technology, one of the oldest universities in Poland, its founding dating back to the beginning of the twentieth century. In 2015, a Nordic Finance Mechanism grant dedicated to the nZEB technology transfer from Norway to Poland was awarded to a group of researchers from Warsaw University of Technology and NTNU Trondheim. The main aim of the project is implementation of nZEB knowledge in Poland, as well as preparation of two integrated concept designs for public (University) buildings as exemplary case studies which could act as the benchmarks for other public buildings.

Food industry is one of the most important and fastest growing sectors of economy in Poland. This sector is also characterized by high demand for the resources, particularly for water. Polish food industrial plants consumed 793 hm3 of water in 2014. Dairy branch had a combined 35% share of the above consumption. As shown by the data obtained from the Polish Central Statistical Office, the majority of dairy plants use its own source of water, so this branch is also important water producer in Poland. Water used for dairy industry should meet the requirements of at least drinking water quality, so the factories need to treat the water. This paper analyses the correlations between selected technical process, equipment profiles and water quality, and consumption in two types of dairy factories (DF). The first one DF-1 processes approx. 50,000 L of milk, and the second, DF-2 processes approx. 330,000 L of milk per day. The water taken from the wells needs to be pre-treated because of iron and manganese concentration and due to specific requirements in various industrial processes. As a result of this work, we have managed to propose technological solutions in the context of water consumption rationalization. The proposed solutions aim at improving water and wastewater management by reducing the amount of consumed water by industry.