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[Display omitted] • Bibliometric analysis of patents and papers about technologies of pyrolysis. • Comparing fluidized bed pyrolysis, hot balls pyrolysis, microwave pyrolysis, plasma pyrolysis and laser pyrolysis. • Evaluating publication trend, innovation index and performances, i.e. heating rate and reaction temperature. • Evolution of pyrolysis depends by the reduction of the heating zone from macro to micro level. • Laser pyrolysis resulted the most promising technology. This paper analyses over 89,000 documents between scientific journals and international patents in order to identify main technologies for material pyrolysis (i.e. fluidized bed, hot balls, microwave, plasma, and laser), compare them in terms of technical performances and discover future trends. The predictive model for future trends is based on the evolutionary model of the TRIZ theory, with particular attention to the evolutionary law, "from macro to micro", which explains how technical systems evolve towards increasingly smaller, controlled, and resource-efficient interactions. In our case, we applied the focus to the interface between the heat source and the pyrolyzed raw material. The proposed evolutionary model showed a substantial alignment with chronological trends, and the model was consistent with both patent trends and those of the scientific literature. To make the analysis quantitatively more robust, a comparison of the different technologies has also been introduced in terms of percentage distribution and the number of patents/papers referring to the different classes of heating rates and reaction temperatures and types of flash/fast/intermediate/slow reaction. Finally, a quantitative metric based on the innovation index has been adopted, to take into account the number of citations normalized on the years of publication. The main outputs of this study identified that radiations-based pyrolysis, involving microscopic interaction, seem more interesting in term of technical performances (i.e. heating rate and reaction temperature), although their technological growth has yet to occur, unlike fluidized bed and hot balls, which typically work at a macroscopic level and seem to have already reached maturity. According to a bibliometric index, laser corpus resulted three time more innovative then fluidized bed reactors papers, especially for heating rates and reactions temperature. [ABSTRACT FROM AUTHOR]

In modern times, any disturbances caused by natural or artificial factors to technological systems must be identified and eliminated promptly. Space weather has been acknowledged for more than ten years as a key cause of breakdowns in numerous ground- and space-based technology systems that are essential to human life. Thus, this article about research interest trends related to space weather events (SWEs), from all around the world was analyzed through bibliometric analysis using Scopus publications from 1994 until 2022. Initially, 2779 journal articles on SWE were collected over the course of 28 years, but only 1713 were retained when review articles were omitted. The study also presents the trends of co-authorships in correspondence to countries/academic institutions and co-occurrences of author keywords. Since 2005, the number of publications regarding SWE has steadily increased, resulting in a substantial library of publications until 2022. The three top-ranked nations that produced the most papers with the highest levels of international collaboration and networking are the United States, the United Kingdom, and China. [ABSTRACT FROM AUTHOR]

• Co-occurrence network analysis of driving distraction literature in terms of time, country, publication, author and keywords. • Deep learning algorithm recognition model based on video surveillance data source has become the mainstream hotspot distraction recognition method. • Among the driving distraction detection methods based on video images, the accuracy of CNN is higher than that of random forest, but the real-time performance of random forest is better than that of CNN. • Based on ECG and GER to detect driving distraction, there is contact with the driver, the accuracy is high, but the real-time performance is poor. • Driving volatility can be used as a measure of driving distraction, and it is of great significance to study driving distraction. Introduction: The existing selection of driving distraction recognition methods is based on a specific research perspective and does not provide comprehensive information on the entire field of view. Method: We conducted a systematic review of previous studies, aiming to come up with appropriate research methods to identify the driver's distraction state. First, this article selects four sets of search keywords related to driving distraction discrimination from five databases (Web of Science, ScienceDirect, Springer Link, IEEE, and TRID) and identifies 1,620 peer-reviewed documents from 2000 to 2020; these 1,620 documents underwent bibliographic analysis and co-occurrence network analysis. The co-occurrence coupling relationship is analyzed from the aspects of time, country, publication, author and keywords. Second, 37 papers published were screened, and the driving distraction recognition methods proposed by these 37 papers were summarized and analyzed. Results: The results show that this field has been prevalent since 2013; countries such as the United States, Britain, Germany, Australia, China, and Canada are in the forefront of research in this field, and the cooperation between related countries is relatively close. The cooperation between authors is characterized by aggregation, and the mobile phone as the main keyword is almost connected to other keyword nodes; the recognition model of deep learning algorithm based on video surveillance data sources has become the mainstream hot spot distraction recognition method. The recognition model of machine learning algorithm based on vehicle dynamics data, driver physiology, and eye movement data sources has specific advantages and disadvantages. Practical Applications: The results can help people to understand the current situation of driving distraction comprehensively and systematically, provide better theoretical support for researchers to choose the subsequent driving distraction recognition model, and provide research direction for driving distraction recognition in the future. [ABSTRACT FROM AUTHOR]

Mindful consumption (MC) has ancient roots, but the scholarship has recently received industry and academic attention. This research examines MC through a hybrid systematic review, including a bibliometric analysis of 41 years with 368 papers from 196 journals and a TCCM analysis to add further depth. Results indicate that the field is still evolving and has been approached by multiple disciplines and methodologies. Further, bibliographic coupling analysis presents six emerging themes in MC research, such as MC conceptualization, responsible consumption, and responsible practices by firms. Finally, the paper proposes future avenues for research for the resultant clusters. [ABSTRACT FROM AUTHOR]

Natural capital accounting plays a pivotal role in the sustainable management and conservation of natural resources. This paper aims to contribute to this field by conducting a bibliometric review of 1409 articles and employing explainable artificial intelligence modeling (XAI) to identify and predict the factors that influence the impact of natural capital accounting (NCA) research, especially in terms of citations to this research. The findings revealed that the Journal of Cleaner Production is the leading publication in this field, with the highest h-index of 37. The XAI found that age of publication and number of references significantly impacted the likelihood of a paper receiving many citations. This study offers an innovative and practical framework for forecasting citation counts and provides effective strategies for authors and editors to enhance the citation impact of their work. [ABSTRACT FROM AUTHOR]

• Study analyzes 1374 papers on sensitivity analysis in Scopus. • RStudio, CiteSpace, and VOSviewer are used. • China has most articles published; India leads in international cooperation. • Top three cited journals: J. Clean. Prod., Expert Syst. Appl., and Comput. Ind. Eng. • Most cited authors are Pamučar D, Kahraman C, and Zavadskas EK. In the present era, the implementation of scientifically grounded Multi-Criteria Decision Making (MCDM) has emerged as a pivotal solution to diverse decision-making challenges across various domains. Although a substantial body of exploratory, conceptual, and experimental studies exists, only 9.457% studies have incorporated sensitivity analyses to assess the robustness of MCDM methods. An exhaustive scientific exploration of sensitivity analysis within the scope of MCDM is thus lacking. This research aims to address this gap through Bibliometric Analysis while examining 1374 articles published between January 2000 and March 2023 from the Scopus database. Using RStudio (Biblioshiny), CiteSpace, and VOSviewer software, the study constructs a visual representation of the most prolific countries, institutions, and authors. Impressively, China takes the lead in article publications, while India excels in international collaboration. "An extended TODIM multi-criteria group decision-making method for green supplier selection in an interval type-2 fuzzy environment," featured in the Journal of Environmental Management, emerges as the most cited paper with a total citation of 455. The study also identifies the top three most cited journals, namely "Journal of Cleaner Production," "Expert Systems With Applications," and "Computers and Industrial Engineering." "North China Electric Power University" is the leading institute with the highest research outputs. "Pamučar D" is the most cited author, with 2594 citations and 39 articles, followed by "Kahraman C" and "Zavadskas EK. This study sheds light on trends in scientific developments and collaborations, providing a model for the application of sensitivity analysis in MCDM research and highlighting global trends. An understanding of the current state of sensitivity analysis research can assist researchers working in the entire domain of MCDM. Additionally, the visualization provides prescriptive data for future work and applications related to sensitivity analysis. [ABSTRACT FROM AUTHOR]

In recent years increasing attention has been paid to theory building and empirical research that explore the links between the business model and open innovation (BM&OI). Nevertheless, studies presenting the results of bibliometric analyses merging these two terms are still scarce. Therefore, the main aim of this paper was to present the results of a comprehensive bibliometric analysis focused on the determination and mapping of the evolving cognitive and social structures in the BM&OI literature to set proposals for directions of future research. Our research was based on the dataset obtained from the Scopus database and made use of the Biblioshiny and the VOSviewer software. Descriptive and network analyses were conducted to demonstrate an overview of the scientific field under consideration. We identified the leading authors, sources, countries and institutions in the BM&OI literature. The most influential publications on the BM&OI and the most cited references by documents covering the BM&OI research were indicated. Based on the thematic evolution and thematic maps, the evolving structures of key sub-fields of the BM&OI research were determined and discussed. Moreover, the major clusters and the specificity of scientific collaboration in the analyzed research domain were identified and described. Our intention was to demonstrate to both scholars and practitioners the wide-ranging landscape of multifaceted research on the BM&OI. [ABSTRACT FROM AUTHOR]

Risk management in construction projects requires effective construction supply chain risk management (CSCRM). To gain insights into CSCRM research, this paper conducts a systematic literature review and bibliometric analysis covering the period from 1999 to 2023. The findings of this comprehensive analysis shed light on various aspects, including risk management phases, classification of micro or macrolevel risks, traditional approaches, and the emergence of artificial intelligence (AI) applications. Through an extensive database search, relevant articles on CSCRM were identified for analysis. The review reveals that while traditional techniques such as surveys, case studies, and statistical tools remain prominent, there is an increasing adoption of AI methods. Initially focused on risk identification, assessment, and analysis; the CSCRM phases have expanded over time to include risk allocation, prioritization, and recovery. Analysis of publication trends shows a rise in the use of AI techniques since 2016 alongside persistent utilization of traditional approaches. Moreover, influential authors, journals, and collaborative networks are highlighted to provide valuable insights into the field's development. Overall visualization contributes to advancing both research and practice in CSCRM by presenting a holistic overview of theories, methods, and emerging technologies within the field along with critical risk management approaches and publication trends. [Display omitted] • Systematic analysis of CSCRM research from 1999 to 2023. • Insights on risk management phases and risk classifications. • Traditional vs. AI approaches in CSCRM. • Identification of influential authors, journals, and networks. • Evolving trends: Increased AI adoption in CSCRM research. [ABSTRACT FROM AUTHOR]

Bioelectrochemical systems have emerged as efficient and sustainable wastewater treatments. Constructed wetland microbial fuel cell has gained considerable attention for electrogenic bacteria-driven wastewater treatment and electricity generation. Electrogenic bacteria play a pivotal role in constructed wetland microbial fuel cell by converting organic waste into electrons, thereby providing a critical biocatalyst for wastewater treatment and electricity generation. However, understanding their regulation, enrichment, and interactions remains lacking. This paper presents a comprehensive and systematic review of current research advancements in electroactive bacteria, offering valuable insights for further investigation. Through a bibliometric analysis and systematic review, this article presents a study on the factors influencing the role of electroactive bacteria and provides a comprehensive overview of the system removal performance. Finally, suggestions and future research directions for constructed wetland microbial fuel cell are presented. [Display omitted] • Bibliometric analysis identified key factors and trends in CW-MFC system. • The structure and operational parameters influencing EAB are studied. • EAB is vital in the removal of traditional and emerging pollutants in CW-MFC. • Research of interactions among EAB, electrodes, and pollutant removal is required. [ABSTRACT FROM AUTHOR]

[Display omitted] • Scientometric analysis of MPs in soil ecosystems was performed. • A total of 2210 articles on MPs from 2012 to 2022 were analyzed. • Knowledge bases, trends, and hotspots in MP research were identified. • China was the top country in terms of publications and funding. • The migration of MPs from terrestrial to aquatic systems should be considered in the future. Soil microplastic (MP) pollution is a growing global environmental issue leading to a series of ecosystem problems and functional losses. However, understanding the advances and trends in soil MP pollution research proved to be difficult based on individual studies. Herein, CiteSpace visualization analysis software was used to sort the literature obtained on soil MP research from the Web of Science (WoS) TM core collection database, and bibliometric analysis of publication volume, country/region, keywords and other information was conducted. Results showed that soil microplastics (MP) research had much lower publication volume than hydrological system MP research, and was still in its developing stage. However, the number of research hotspots in soil MP research increased continuously since 2018. Countries such as China, the United States, the Netherlands and Australia have published more papers in this field than other countries, and collaboration among research institutions is strong. The source, pollution status, analysis methods and toxic effects of MPs in soils are current research hotspots. In the future, the focus of MP research in terrestrial ecosystems should shift from ecotoxicology to the impact of MPs on ecosystems and earth system feedback. The bibliometric analysis results of this study can serve as a reference for in-depth studies of the pollution status of MPs in soils. For MP soil pollution research, cross-background, cross-institution, cross-country cooperation and cross-disciplinary roles should be encouraged to accelerate the growth and diversification of the field. [ABSTRACT FROM AUTHOR]

Heavy metals pollution in soils is an urgent environmental issue worldwide. Phytoremediation is a green and eco-friendly way of remediating heavy metals. However, a systematic overview of this field is limited, and little is known about future development trends. Therefore, we used CiteSpace software to conduct bibliometric and visual analyses of published literature in the field of phytoremediation of heavy metals in soils from the Web of Science core collection and identified research hotspots and development trends in this field. Researchers are paying increased attention to phytoremediation of heavy metals in soils, especially environmental researchers. A total of 121 countries or regions, 3790 institutions, 4091 funded organisations and 15,482 authors have participated in research in this area. China, India, and Pakistan are the largest contributors. There has been extensive cooperation between countries, institutions, and authors worldwide, but there is a lack of cooperation among top authors. 'Calcareous soil', 'Co-contaminated soil' and 'Metal availability' are the most intensively investigated topics. 'EDTA', 'Plant growth-promoting Rhizobacteria', 'Photosynthesis', 'Biochar' and 'Phytoextraction' are research hotspots in this field. In addition, more and more researchers are beginning to pay attention to research on co-contaminated soil, metal availability, chelating agents, and microbial-assisted phytoremediation. In summary, bibliometric, and visual analyses in the field of phytoremediation of heavy metals in soils identifies probable directions for future research and provides a resource through which to better understand this rapidly advancing subject. [Display omitted] • Research progress on the phytoremediation of heavy metal in soils was reviewed. • This article explores the countries, institutions and authors that play a leading role. • This article explores the main research hotspots in this field. • This paper explores the opportunities and challenges for this research. • The results provide a valuable reference for follow-up research. [ABSTRACT FROM AUTHOR]

The number of scientific publications studying open innovation (OI) and tourism has increased since the first concept appeared. Nevertheless, there is still a gap regarding the science mapping and performance analysis of these two concepts. Although there are studies that focus on open innovation and tourism, few are studying the relationship between themes. We aimed to address this gap by reviewing the literature and searching the Scopus database using R. Bibliometrix. We identified 45 published articles between 2010 and 2022, covering 23 sources and 130 authors. The results indicate a strong collaboration network among authors. Open Innovation, Tourism, and Sustainability are the trend topics, as well as the three main keywords. The emerging topics are "open innovation in tourism", "service innovation" and "overtourism". Keywords, trend topics, and emerging topics can be valuable guides for researchers and help them decide which path to take in their studies in this field. This paper is a starting point for carrying out further research that relates OI to other areas of tourism, such as smart tourism or smart tourism destinations, which are highlighted in some of the most recent articles that were under this study. [ABSTRACT FROM AUTHOR]

Society has become increasingly socially and environmentally conscious owing to global environmental challenges, and COVID-19 has become an eye-opener. Although people have started developing a significant understanding of sustainable consumption, much work remains to be done in this field. Our study recapitulates the research that has been published in the area of sustainable marketing and sustainable consumer behavior over the last three decades. We conducted a hybrid literature review using bibliometric analysis combined with TCM (Theory-Context-Methodology) framework-based approach on a total of 1998 relevant papers published from 1991 to 2021. Our findings validate that the literature in this field has been on the rise, particularly since 2016. The subject area with the highest number of publications was Business & Economics (803). The USA is the major contributor, with (444) publications, followed by England (219) and China (416). The study also classifies the status of the extant literature, notable research gaps, and future research directions following a theoretical framework, empirical methods, and contextual phenomena. The study provides valuable insights into filling the "green attitude-behavior gap". Given the growing tendency among consumers to go sustainable, this study offers practitioners a new perspective on the much-needed changes in the marketing strategy of companies selling sustainable products. Given the growing importance of people and companies being more environmentally and socially responsible, our study will help pave the way towards this much-desired goal. [ABSTRACT FROM AUTHOR]

In the present situation, renewable energy has become a vital source to mitigate energy crises and environmental threats. In order to ensure that women's contributions, knowledge and opinions represent a significant portion of the expanding energy sector, it is crucial to approach the development of renewable energy from a gender perspective. Bibliometric analysis was performed to identify prior research on two primary terms, "Gender" and "Renewable Energy", from 1995 to 2022. Identifying the most influential countries, authors, publications, journals, and co-occurrence of keywords helps to understand the evaluation and trends of the research through network visualisations by bibliometric approach. This paper presents a comprehensive bibliometric review of the influence of gender on renewable energy. The result of this paper gives details picture of the gender impact on renewable energy during the period from 1995 to 2022. The paper centred on bibliometric and cluster analysis based on the two most important databases, Web of Science and Scopus. The study involved utilising various bibliometric tools, including R Studio, VOSviewer, and Biblioshiny. The study revealed an increase in publications and citations during the third period since 2017, after the United Nations set the target of the Sustainable Development Goal. Most influential countries and productive authors belong to China, the United States of America, and the United Kingdom. Energy Research and Social Science are predominated in publications on the research topic. In addition, the co-occurrence of keywords found major keywords related to this topic, such as renewable energy, gender, women, knowledge, sustainability, climate change and sustainable development. Finally, the study observed a huge research gap because developing nations are more affected by the lack of gender-influencing policies on the growth of renewable energy. Thus, the study provides a comprehensive overview of research in this field that can help researchers and stakeholders identify potential ways for future research in gender considerations on renewable energy access by formulating effective policies to change society and reach the Sustainable Development Goals. • Gender has become a focal point of interest within the renewable energy sector. • Using network visualisation, bibliometric analysis examines research trends by keyword occurrence and country collaborations. • Publication, citation, journal, and authorship contribution trends are to be analysed. • The research growth across different periods was discussed for potential future studies. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) technologies are increasingly applied to traffic flow prediction (TFP) to enhance prediction accuracy. This study utilizes bibliometric methods and network analysis measures to gain insights into the research status, development process, opportunities, and challenges of AI-based TFP research based on the literature data retrieved from the Web of Science core collection. The study first conducts basic statistical analysis of all papers. Subsequently, cooperation network analysis is conducted to identify the most productive countries/territories, institutions, and authors, the cooperative relationships, and the formed research communities. Co-citation network analysis is then employed to identify publications that have made outstanding contributions to the AI-based TFP field. Finally, the main path analysis of the paper citation network is used to analyze the knowledge diffusion process, while the keyword co-occurrence analysis is conducted to reveal the evolution characteristics of the research topics. Based on the bibliometric analysis results, we gain insights into the opportunities and challenges in this field from the perspectives of data, models, and applications, and provide pertinent suggestions for future research. Overall, this study can assist researchers in capturing the state-of-the-art and research directions in AI-based TFP. [ABSTRACT FROM AUTHOR]

Sustainability leadership (SL) is a complex and relevant phenomenon that can contribute to several types of organisations during the process of becoming more sustainability-oriented. Over the past few years, a considerable number of publications have increased the level of knowledge in this field; however, on the other hand, it also has generated more complexity, literature dispersity and lack of complete understanding of the possible research avenues on SL. This paper aims to address this by complementing and building on previous qualitative and quantitative studies of SL by unveiling and exploring the landscape of the research field. This study differs from prior research in three main ways: (1) explores how the term SL evolved from the leadership theory, (2) explores the research streams that scholars have been conducting in the field by adopting a robust search string revised by specialists and considering a wide range of terms related to formal and informal leadership, as well as sustainability-related terms and (3) understands how the several leadership theories and styles are connected to sustainable development (SD) and corporate social responsibility (CSR). After applying the inclusion and exclusion criteria, a total of 1,813 well-cited papers published in top journals that directly tackle sustainability leadership were selected. This sample was then used for the bibliometric assessment based on the co-occurrence of terms technique. The results indicate the existence of four main clusters and twelve subclusters, which can be considered research strands. In addition, this study also explores how the selected studies build on several leadership theories in order to understand how leadership aspects can contribute to SD and CSR adoption. [ABSTRACT FROM AUTHOR]

The path to implementing successful, productive, and sustainable off-site 3D concrete printing building systems is unclear. To provide clarity, this paper aims to determine targeted actions for stakeholders in the construction industry. A systematic literature review and a bibliometric analysis are conducted to identify driver-barriers of Off-site Construction (OSC) and 3D Concrete Printing (3DCP). Thirty-four stakeholder-linked targeted actions are determined and divided into industry, organisational, project, and system levels. The findings indicate the success of off-site 3DCP building systems is not exclusively dependent on the system performance and a variety of actions are required from multiple stakeholders. This paper provides a theoretical foundation for practical actions and further research to implement off-site 3DCP building systems in local construction industries. • Drivers and barriers are identified with a systematic literature review on off-site construction and 3D concrete printing. • A bibliometric analysis using VOSviewer software is performed. • Stakeholders in off-site 3DCP are identified. • Stakeholder-linked targeted actions which aim to enable the development of off-site 3DCP building systems are derived [ABSTRACT FROM AUTHOR]

A scientometric approach is utilized to investigate the dynamic maps of relationships among researchers, institutes, and countries in the field of Artificial Intelligence for Fluid-flow and Heat-transfer (AIFH). The Web of Science database was searched for related publications during the last 40 years (1982 and 2022). A total of 6151 articles were discovered, which were analyzed in detail. Using a bibliometric analysis, the most relevant and most cited sources of publications were identified. The most active researchers, institutions, and countries leading AIFH were reported. Then, the worldwide dynamic collaboration maps and coupling maps of relationships were reported. The Islamic Azad University (1893 T.C.), the Chinese Academy of Sciences (1374 T.C.), and Beihang University (1266 T.C.) were the most influential institutes in AIFH. The most influential countries were China, the USA, and Iran. The dynamic map of collaborations shows a good worldwide collaboration distribution. The USA and China established the most connection with the rest of the world. ANNs are the most studied topic (19.5% of publications), followed by Machine Learning (17.9%) and Neural Networks (15.4%). Support Vector Machines lag behind at 1.4%. ANNs boast the highest total citations (17,064) and H-index (63). Most ANIF papers were published by Medical Physics (119 T.P.). Half of the articles in AIFH were published by five journals of Medical Physics, Neurocomputing, International Journal of Heat and Mass Transfer, International Journal of Radiation Oncology Biology Physics, and IEEE Access. The International Journal of Heat and Mass Transfer received the most citations in AIFH. [ABSTRACT FROM AUTHOR]

This research aims to evaluate the scientific production on public relations addressing Latin America through a quantitative content and bibliometric analysis of articles and special issues published between 1980 and 2020, written in the official languages of the region: Spanish and Portuguese. The results of 123 articles confirm a substantial increase of studies since 2011, and some limitations of scientific dissemination. Although almost half of the authors were based in Brazil (40%), 17 base countries were counted. This work complements the latest studies on the object of study in English (Thelen, 2021) and provides the scientific community with recognition and access to native production. • A set of 123 native language articles where analised on public relations addressing Latin America. • There is a significant increase in the number of studies from 2016 onwards (29%). • Brazil accumulated the largest number of papers in the period (n = 49). • It was found that the impact in native languages (4.2) was lower than in English (43.2). [ABSTRACT FROM AUTHOR]

Due to the massive use of antibiotics, antibiotics resistance genes (ARGs) are widely present in organic solid wastes (OSWs) such as livestock manure and sludge. As a common recycling technology, composting is often used to eliminate ARGs from OSWs. However, there is no bibliometric perspective on the fate of ARGs during OSWs composting to reveal the current state and future directions in this field. In this study, CiteSpace and VOSviewer were applied to count the available data from 2000 to 2021 in Web of Science to review the development and characteristics of relevant research. The results showed that the number of relevant papers and citations has increased consistently, with institutions and authors from China being the main contributors. The research belongs to the multidisciplinary with a focus on the environmental sciences ecology, and the results were mainly published in Bioresource Technology. Moreover, crucial literatures were screened to explore the framework within which the subject was constructed. Based on keyword analysis, the bacterial community was highlighted, and the research hotspots were revealed on the occurrence, affect factors including physicochemical properties, microbial community, MGEs, antibiotic, and heavy metal, and reduction strategies including exogenous additive, microbial inoculant, and improved process, as well as the spread of ARGs in soil. This study provides the first review and summary of the hotspots, current challenges, and future directions of the fate of ARGs during OSWs composting based on bibliometric analysis, which could provide significant insights for effective control of the spread of ARGs from OSWs. • First bibliometric analysis of the fate of ARGs during composting. • Relevant research burst in recent years, with China being the main contributor. • Bacterial community is the keywords most closely related to ARGs in composts. • Review the hotspots of research on the fate of ARGs during composting. • Propose the current challenges and future directions in the field. [ABSTRACT FROM AUTHOR]

The management of uncertainty in decision-making problems remains a very challenging and timely research issue despite many proposals. An interesting topic in this area in recent years has been Granular Computing. In this paper, we present a coherent framework for various models of information granules, using hierarchies of information for dealing with knowledge acquired and processed at different levels of abstraction. Granular Computing, a paradigm for handling higher types of uncertainty in decision analysis, is considered a new conceptual and algorithmic asset of decision-making studies and, in particular, data-driven decision-making. Most relevant studies have focused on categories of information granules, namely intervals, fuzzy sets, rough sets, and shadowed sets. To better understand this promising area, this study provides a comprehensive overview of Granular Computing for decision-making through literature analysis, enhancing a variety of extensions, applications, and challenges. • We propose a comprehensive review for granular computing in decision making. • We provide a bibliometric review for granular computing in decision making. • We review main applications in granular computing in decision making. • We provide some future directions for granular computing in decision making. [ABSTRACT FROM AUTHOR]

• Ventilation rate and arrangement are crucial to prevent airborne disease in healthcare facilities. • Local ventilation is practical for supply fresh air and diluting contaminants in high-risk areas. • Microplastics emerged as potential virus carriers in indoor environments, warrant further investigations. The prevalence and transmission of airborne infections pose significant challenges to public health, leading to consequential negative impacts. Ventilation strategies are crucial in mitigating airborne infections in healthcare settings, preventing the spread of infectious diseases, thus protecting patients and healthcare workers. While individual studies have explored various aspects of ventilation in healthcare settings, a synthesized overview of the current state of knowledge is lacking. Therefore, this study attempts to bridge the gap by conducting a review and bibliometric analysis based on 198 papers published within the recent decades (1993–2022). The findings will provide a holistic understanding on the innovative interventions and identify areas for future research, thereby contributing to the development of effective guidelines for controlling airborne infections. The co-authorship analysis revealed that China emerged as the main contributor in the current research field due to the keen interest of researchers and the substantial financial support provided by funding agencies. The keyword co-occurrence analysis identified three primary research hotspots within the field, (i) the optimized ventilation strategies for combating airborne infection, (ii) the transition towards the application of computational fluid dynamics (CFD) in analyzing airflow patterns, and, (iii) the characteristics of airborne particles and their impact on infection transmission. The present review highlights the significance of local ventilation as an additional measure to the main ventilation system for enhanced dilution of contaminants in high-risk areas. The transition towards dynamic airflow analysis considered human movement's effect, allowing for more precise assessments and tailored ventilation strategies optimization. The review also underscores the emerging concern of microplastic as an indoor contaminant with potential implications as a virus carrier, emphasizing further research on its behavior and impact on airborne infection transmission. [ABSTRACT FROM AUTHOR]

With the advancement of Industry 4.0 and the development of science and technology, industries have seen the advantages of digital twin (DT) implementations and concepts. Although the construction industry is still in the early stage of DT development and implementation, it is urgent for the industry to have a DT agenda. This paper identifies 1158 related bibliographic records from the Web of Science and 745 records from the Derwent Patent Database and quantitatively analyzed them to describe patterns of publications. Two knowledge mapping tools were selected to visualize and analyze the literature in the relevant scientific domain. Then, we integrated clustering, knowledge mapping, and network analysis methods to show the current foci and future directions of DT-MT derived from the data of time distribution, journal areas, and subject distribution. The results indicate that DT is a cross-disciplinary information technology with great development potential, and its development in the construction industry is scattered with the leading advancement in the manufacturing of construction materials and components. The derived knowledge map shows three stages of construction DT, including (1) data collection and creation of DT framework and database; (2) implementation of planning and design modules in detail and control of construction sites; and (3) carrying out asset management and fault prediction in the operation and maintenance phase of projects. The novelty of this paper is the specific analysis of DT in the construction industry. This study adds value to the architecture, engineering, and construction industries by shedding light on the focus of DT practical applications and the formation of a development path of construction DT. • This paper seeks to improve the understanding of Digital Twins in the construction industry. • Helps relevant industries to develop a well-structured development path. • Smart engineering, manufacturing, and construction affect industrial performance and the quality of construction projects. • Integration of clustering, knowledge mapping, and network analysis methods to identify the current foci and future directions. • Prediction of the technology influences and its clean production to enhance domain-general strategy knowledge. [ABSTRACT FROM AUTHOR]

The spiraling growth of the world's population and unregulated urbanization have resulted in many environmental problems, including poor quality of air, which is associated with a wide range of health issues. Machine learning approaches have been extensively employed to predict air quality, attracting the attention of the scientific community worldwide. Bibliometric studies provide a useful means by which to visualize and analyze published works, helping researchers to make novel scientific contributions by filling existing knowledge gaps in the research. To acquire an in-depth understanding of the topic, this paper presents a bibliometric analysis of all published articles on the use of machine learning networks to predict air quality found in the Web of Science (WoS) search engine from 1992 to 2021. S-curve analysis and social network analysis were used to identify the temporal distribution of articles, productivity by countries/continents, research institutions, and scientific metrics of journal productivity. This study indicated that maximum expansion of the literature witnessed during 2017–2021 (second phase) which represents an expansion or growth stage of machine learning and air quality prediction research. The number of published works increased significantly with 1432 articles accounting for 68.51% of all publications. As a result of the increased interest in machine learning-based prediction tools, the number of articles grew 2.17-fold compared to the 1992–2016 (first phase). In terms of international collaboration impact, Italy emerged as the most successful country (43.44), followed by Greece (31.22) and Spain (23.29). Author keywords analysis was employed to explore and evaluate the emerging research trends on the subject of air quality using machine learning models. Keywords that appear most frequently in this study are 'air pollution', 'air quality', 'machine learning', and 'forecasting'. Citation burst analysis, research productivity analysis, highly influential and highly cited works were also employed to examine various research themes and questions. In this study we also discussed how conventional methods were transformed into machine learning approaches. It is expected that this paper will provide technical guidelines, research priorities, and future opportunities for the precise prediction of air quality and emergency management of air pollution globally. • Interest in air quality prediction through machine learning model is expanding. • China and US were found productive countries in terms of countries collaboration. • Big data, Internet of Things, and Smart city are emerging topic for future research. • Significant difference between citations, funded and non-funded research. • Ensemble modeling is popular in air quality prediction research. [ABSTRACT FROM AUTHOR]

Constructing an eco-civilization is crucial in achieving green, low-carbon development, and thus bridging the gap between theory and practice is imperative to better promote urban ecological transformation. At present, there are inconsistencies and imbalances between theoretical research and practical efforts to achieve an eco-civilization. This paper uses bibliometric analysis and Latent Dirichlet Allocation to analyze China's progress towards an eco-civilization at the theoretical and practical levels. The 'theory' is analyzed using 632 articles, while the 'practice' is analyzed using 100 eco-civilization pilot zone reports. The two are compared, with results showing: from 2015 onwards, the theory is moving in an interdisciplinary direction, with seven themes focusing on macro topics. eco-civilization construction projects have multiple overlapping themes, and the growing connection between energy consumption, economic growth and environmental impacts driven by significant projects is the key to improving the level of regional ecological development. the theory and practice are similar in that both are concerned with environmental protection, ecological education, and ecotourism. However, eco-civilization construction projects lack forward-looking and dynamic development tracking of low-carbon research. the paper proposes that dynamic evaluation and project tracking methods should be applied to monitor critical indicators to achieve a solid link between the theory and practice during eco-construction projects. This paper also proposes academia should do more research on townships and other micro level phenomena to promote climate change and energy revolution in the construction of a Chinese eco-civilization. • Analysis of the similarities and differences between theoretical research and practical measures of eco-civilization. • Academic research focuses on sustainability, while practical activities lack attention to climate change. • Optimizing the energy-economy-environment integration project is the key to improving China's ecology. • Environmental protection, eco-civilization education, and eco-tourism are common concerns in the theory and practice. • Suggestions include focusing on crucial indicators and micro-level activities. [ABSTRACT FROM AUTHOR]

The spiraling growth of the world's population and unregulated urbanization have resulted in many environmental problems, including poor quality of air, which is associated with a wide range of health issues. Machine learning approaches have been extensively employed to predict air quality, attracting the attention of the scientific community worldwide. Bibliometric studies provide a useful means by which to visualize and analyze published works, helping researchers to make novel scientific contributions by filling existing knowledge gaps in the research. To acquire an in-depth understanding of the topic, this paper presents a bibliometric analysis of all published articles on the use of machine learning networks to predict air quality found in the Web of Science (WoS) search engine from 1992 to 2021. S-curve analysis and social network analysis were used to identify the temporal distribution of articles, productivity by countries/continents, research institutions, and scientific metrics of journal productivity. This study indicated that maximum expansion of the literature witnessed during 2017–2021 (second phase) which represents an expansion or growth stage of machine learning and air quality prediction research. The number of published works increased significantly with 1432 articles accounting for 68.51% of all publications. As a result of the increased interest in machine learning-based prediction tools, the number of articles grew 2.17-fold compared to the 1992–2016 (first phase). In terms of international collaboration impact, Italy emerged as the most successful country (43.44), followed by Greece (31.22) and Spain (23.29). Author keywords analysis was employed to explore and evaluate the emerging research trends on the subject of air quality using machine learning models. Keywords that appear most frequently in this study are 'air pollution', 'air quality', 'machine learning', and 'forecasting'. Citation burst analysis, research productivity analysis, highly influential and highly cited works were also employed to examine various research themes and questions. In this study we also discussed how conventional methods were transformed into machine learning approaches. It is expected that this paper will provide technical guidelines, research priorities, and future opportunities for the precise prediction of air quality and emergency management of air pollution globally. • Interest in air quality prediction through machine learning model is expanding. • China and US were found productive countries in terms of countries collaboration. • Big data, Internet of Things, and Smart city are emerging topic for future research. • Significant difference between citations, funded and non-funded research. • Ensemble modeling is popular in air quality prediction research. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is a chronic multifactorial disorder of autoimmune etiology with a complex pathophysiological mechanism that is not yet fully elucidated. RA pharmacotherapy includes active molecules of chemical or biological nature that offer symptomatic relief and a slowing of progression, but still in a context of incurability. Therefore, the development of continuous research and multidisciplinary collaboration is essential. Although the management of RA is a topic of significant scientific relevance, existing bibliometric analyses are insufficient to assess this vast field. Consequently, the present study examines numerous manuscripts indexed in the Web of Science database using the VOSviewer software to provide through statistical interpretation of the data a comprehensive description of RA pharmacotherapy in terms of scientific impact, current state of research, number and frequency of citations, most prolific journals, authors, and countries, along with their relationships and other useful data for the literature search/publication process. Furthermore, the use of bubble maps of term occurrence has applicability in identifying current research trends in the field of RA pharmacotherapy as well as their evolution over the years. The leader in this field in terms of published papers is the United States, and the most prolific journal is Annals of the rheumatic diseases. The global management of RA, which is characterized by extensiveness and depth due to many variables, suggests the need for a conceptual framework based on pharmacotherapy coupled with comprehensive bibliometric studies, and the results may be useful for researchers in setting specific objectives that contribute to improving RA outcomes. [Display omitted] • Rheumatoid arthritis (RA) pharmacotherapy includes active molecules that offer symptomatic relief and slowing of progression. • This research examines 44832 manuscripts indexed in the Web of Science database using the VOSviewer software. • It provides through statistical interpretation of the data the description of RA pharmacotherapy scientific impact. • Bubble maps of term occurrence identify current research trends and evolution of RA pharmacotherapy. • The leader in publishing papers is the US, and the most prolific journal is Annals of the rheumatic diseases. [ABSTRACT FROM AUTHOR]

[Display omitted] • Bibliometric analysis on cool pavement technologies to mitigate urban heat islands. • Number of articles published per year, productive journal, institute, countries and authors were studied. • The study of cool pavement technologies has increased significantly in the last decade. • Research trends on cool pavements were analysed through science mapping, and thematic evolution. • Topical trends of cool pavement technologies were discussed. In the last few decades, researchers have sought ways to counterbalance the effect of the urban heat island (UHI) phenomenon of increased urban temperatures resulting from human activities and the surrounding structures. A significant portion of any urban area is made up of paved surfaces, which greatly contributes to the UHI effect. The concept of utilising cool pavement technologies (where 'pavement' refers to all paved surfaces) has gained popularity lately. These technologies tend to involve releasing less sensible heat and lowering pavement surface temperatures, which may result in substantial changes to the heating in areas with high urban temperatures. However, no quantitative study of the pertinent numerical features of the research and the development of cool pavement technology research has been published. This paper presents a science mapping and bibliometric analysis of cool pavement technology research represented by 342 selected publications in the Scopus database, a widely recognised scientific database. This analysis revealed that the production of documents related to cool pavements has increased exponentially since 1993, reaching a peak of 44 articles in 2022. China had the most publications, followed by the USA. An analysis of topical trends showed that most research on cool pavement technology has focused on increasing the solar reflectance of the pavement surface—the subject of 159 of the total of 342 documents. Surprisingly, the total number of studies on evaporative pavements was only about one-third of the number (53) conducted on reflective pavements. In addition to research on reflective and evaporative pavements, significant efforts have been undertaken in the past few years to identify techniques to help lower paved surface temperatures to mitigate the UHI effect. This indicates that this research area is still evolving and far from fully mature. [ABSTRACT FROM AUTHOR]

Researchers have aimed to find sustainable solutions for future mobility because of climate and energy demand issues, making the shift toward sustainable-powered traction essential. However, high costs and the need for partnerships between public and private entities affect hydrogen mobility in its early-stage development. This study examines 233 papers from the Scopus database to shed light on a systematic road to this theme's main features and recurrent issues by adopting bibliometric and coding analyses. The main results show an expansion of publications from 1999 to 2022, which is related to the increased publications and scientific productivity of researchers on this topic and factors such as energy crises and restrictive oil price policies. Furthermore, the expansion of interest is also due to multiple initiatives by supranational entities. The study uncovers the most relevant journals, authors, countries of collaboration, and co-occurrences of keywords. Using a topic dendrogram, we discovered four search clusters: (1) hydrogen for sustainable development, (2) hydrogen as an alternative fuel for mobility: challenges, (3) hydrogen and policy implications, and (4) hydrogen and mobility reshaped. Based on the knowledge gained, our study confirms the challenges of hydrogen mobility and the difficulties associated with higher costs, mainly in sectors where the energy used for transformation is derived from sources other than renewable ones. Further implications show that an alternative to traditional engines requires substantial investment from public and private companies and proper business models. We provide a scientific roadmap of the most relevant issues for managers and policymakers to extend the use of hydrogen in the transportation sector. [ABSTRACT FROM AUTHOR]

Oil wax deposition and precipitation are becoming a major problem during oil production, transportation, and refining. Deposition mitigation by chemical additives, like polymer and surfactants, are commonly used in the oil industry. Because there is no clarity in wax inhibition mechanisms of the additive with crude type and conditions, chemical wax inhibitors are still used in a trial-and-error manner in the oil fields, which is an expensive and inefficient methodology. Understanding the wax inhibition mechanism is important for the design of new inhibitors. This review aims to give an overview of the understanding and development of nanoparticle technology, surfactants, polymer, and their combination in the inhibition of wax deposition. The review looks into lab and pilot plant experiments reported in the recent literature, with more focus on the fundamentals of nanohybridization approaches in wax deposition control, testing methodologies (i.e., thermal, rheological, and morphological analysis), inhibition performance assessment, and mechanisms. The review begins with an overview of bibliometric analysis to shed light on the emerging areas in that field and also explore and analyze the large volumes of scientific data reported from 2000 to 2022 in this field. The performance parameters used for assessing the wax inhibitors in the laboratory are also summarized and addressed. Finally, the challenges and future remarks of the reported chemical inhibitors are reported in this paper. This review provides insights into the integration of nanomaterials into the existing technologies to overcome the existing challenges. [Display omitted] • A comprehensive review focusing on petroleum wax deposit inhibition stratigies. • Methods and technological advancements in wax inhibition and additive design largely impact performance. • Combination of nanoparticle technology and conventional additives "nanohybridization" could improve inhibition performance. • Physical aspects of reported wax inhibitors are discussed. • The performance indicators, advantages, and disadvantages of reported methods are discussed. [ABSTRACT FROM AUTHOR]

Blockchain has attracted great attention in the architecture, engineering, construction, and operation (AECO) industry. To capture its research trends, this study conducted a comprehensive review of blockchain development in the industry using a mixed approach of bibliometrics and content analyses. Ninety-four papers were filtered from the Scopus and Web of Science databases for this review. Bibliometric analysis revealed annual publication trends, journal distributions, country distributions, high-yielding authors, author cooperation networks, and keyword co-occurrence networks, whereas content analysis identified five key topics of contract management, supply chain management, information management, stakeholder management, and the integration of blockchain with other technologies. Research gaps and future research directions are articulated and explained within the research framework. This paper contributes to the body of knowledge by synthesizing the current state and development areas of blockchain research, which would promote the strategic adoption and use of blockchain to a greater extent in the AECO industry. [Display omitted] • Blockchain has many new applications that can improve and transform the AECO industry. • Bibliometrics and content analyses were adopted to review and analyze the blockchain development. • The research themes and future research directions are articulated in a research framework. • It contributes to the continued development and strategic adoption of blockchain in the industry. [ABSTRACT FROM AUTHOR]

[Display omitted] • Landscape of blue carbon research from the perspective of bibliometrics. • Blue carbon ecosystem was the main research area, but macroalgae deserve attention. • Artificial intervention and methods are potential hotspots in the future research. • Statistics, co-occurrence analysis and thematic evolution are main used methods. Blue carbon sequestration is a nature-based solution to environmental problems caused by climate change and has a significant positive impact on the planet and human well-being. This paper bibliometrically and systematically analyzed 2,613 studies found in the Web of Science Core Collection (WoSCC) from 2003 to 2021 to explore the hotspots and trends of blue carbon research using the Bibliometrix package in R studio and VOSviewer software. The results based on network co-occurrence analysis indicated that mangroves, seagrasses, and salt marshes were the major blue carbon ecosystems (BCEs), and mangrove carbon sinks were the most popular central research area. Furthermore, phytoplankton and microalgae have essential roles in the marine carbon cycle and bioenergy utilization, as revealed by the high proportion of published literature, while the carbon transport mechanisms of seagrass and macroalgae was understudied. Thematic evolution analysis revealed that remote sensing was the most commonly used technology as an emerging research field for ecological monitoring and ecological investigation in blue carbon research in recent years. In addition, increasing carbon sinks by artificial approaches, fishery carbon sinks, and carbon sequestration by macroalgae have been potential hotspots for blue carbon research development. The findings from this study shed light on the trends of blue carbon in the past eighteen years, current research points in the field, and areas that need more research investment going forward. [ABSTRACT FROM AUTHOR]

In order to facilitate data analysis techniques for solving construction management (CM) problems, especially in a collaborative manner, it is essential to define the data schemas of various construction information as the common variables. However, one of the critical barriers is that there is no standard set of variables addressed for collaborative research and practice. Therefore, defining standard variable terms is essential to share, utilize, and analyze construction data systematically and efficiently. In this context, the purpose of this paper is to propose a structured set of standard CM variable terms to enable the global collective analyses of CM data, not only for human managers but also for automated machine inferences. To address this issue, firstly, bibliographic data was extracted from Scopus, focusing on CM research, and the VOSviewer was used to analyze the bibliographic information. Proposed standard variable terms were then organized into a hierarchical structure with two levels, including eight variables in the first level and fifty-seven variables in the second level. Additionally, examples of utilizing standard variable terms were presented to the traditional analytical techniques, ontology, and artificial intelligence (AI) techniques to illustrate the viability of the proposed variable terms in CM. The proposed standard variable terms can be used as the basis for further detailed taxonomy toward collective advanced analytics implementation in CM. This approach will significantly enhance automated knowledge sharing between different applications and machines, resulting in global collective intelligence among unspecified CM professionals. • Standard variable terminologies in CM were proposed. • A hypothesis for first-level variables was established and validated. • Standard variables were defined through keywords found from bibliographic data. • A comprehensive concept for collective data exchange was presented. [ABSTRACT FROM AUTHOR]

[Display omitted] • Visualization and quantitative analysis of the global ecological carbon sinks and sources. • Enhance the prediction of carbon sequestration dynamics under climate change. • Climate change potentially affecting the carbon-climate feedback. • Research content is becoming clearer and more systematic. • Keyword clustering the classification of the research into six relatively independent subtopics. Climate change is extensively affecting the global ecosystem, especially the ecosystem carbon sequestration and sequestration potential, which are issues of global concern. The proposed concept of "carbon neutrality" in 2020 has brought ecological carbon sequestration to the forefront. Therefore, the research on climate change and ecosystem carbon sequestration need to be systematically reviewed, summarized, and examined. Based on the Web of Science database, this paper analyzed 4005 articles (1992–2022 year) after rigorous screening via a bibliometrics analysis and then presented the research trends and future research focus of ecological carbon sequestration. The following conclusions are drawn: (1) the research over the last 30 years has steadily improved, and the annual number of publications has increased in a cubic polynomial fashion (R 2 = 0.9937), with 87.57 % of the total publications appearing after 2009. Global Change Biology and Science of the Total Environment are the most influential journals in the field; (2) participation in such research is becoming increasingly common with expanding research areas covering Eurasia, America, Oceania, and Africa. The United States and China are the most productive and influential countries; (3) the diversity of this research is increasing, and the research content is becoming more explicit and systematic. Most research focuses on climate change, carbon sequestration, management, land-use changes, and nitrogen and soil organic carbon; (4) although traditional ecological evaluation techniques were essential early on, remote sensing and modeling have become the primary methods for assessment; (5) keyword clustering allows the classification of the research into six relatively independent subtopics: climate change and terrestrial ecosystems, sequestration and organic-carbon, ecosystem services, nitrogen and carbon cycling, biomass and forest, and blue carbon, which provides a reference for further research on ecological carbon sequestration and carbon neutrality. [ABSTRACT FROM AUTHOR]

This paper reviews the state-of-the-art smart building research by a bibliometric analysis, a content analysis, and a qualitative review. The bibliometric analysis of 364 academic papers shows that smart building is a burgeoning, interdisciplinary field with a relatively high international collaboration level. Keyword's clustering identified two major themes: (1) IoT, WSN, and cloud computing for automation control and (2) the balance between energy efficiency and human comfort based on continuous monitoring and machine learning. The content analysis statistically detected a transition from the cyber-physical system (CPS) to the human-cyber-physical system (HCPS) in smart building research. We therefore proposed an HCPS framework with three dimensions—cyber-physical scale, human needs, and human roles—to summarize current research and discover potential gaps. Under this framework, five HCPS future research directions for occupants-centered smart buildings were proposed: adaptive building envelope, integrated building management system, enhanced building energy management, adaptive thermal comfort, and microgrid adoption. [Display omitted] • Conducted a bibliometric analysis of smart building research. • A statistical content analysis of 364 papers shows a transition from CPS to HCPS. • Proposed an HCPS framework to brainstorm potential research focus. • Proposed five HCPS future research directions for smart buildings. [ABSTRACT FROM AUTHOR]

Previous researchers have broadly studied plastic pollution in the water ecosystem worldwide, but the research topics development and performance trends in this study area are still insufficient and unclear. A bibliometric analysis was conducted to explore research trends regarding plastic pollution in the water ecosystem. Data of publications output was identified based on the Web of Science (WoS) database's research articles from 2000 to 2020. This study used VOSviewer to analyse collaboration networks among authors, countries, institutions, and co-occurrence analysis of keywords in three defined periods. A total of 2182 papers in plastic pollution in water ecosystem research were identified. The USA has been in a top position in plastic pollution in water ecosystem research moving from 2 output publications in 2000 to 68 output publications in 2020. Centre National De La Recherche Scientifique (CNRS) was ranked first in terms of the total publication output (105 publications, 4.81%). Most previous studies in Phase I (2000–2006) and Phase II (2007–2013) emphasise plastic pollution studies in marine environments compared to freshwater ecosystem-focused research. However, in Phase III (2014–2020), researchers more focused on plastic pollution in freshwater ecosystems such as rivers, lakes, estuary and inland water. The valuable results obtained from this study can help scholars better understand the research development trends and research hotspots in the field of plastic pollution in the water ecosystem and provide direction for future research. [Display omitted] • A bibliometric review of plastic pollution in water ecosystems was conducted. • A total of 2182 papers in plastic pollution research were identified. • Bibliometric and network analyses are used to corroborate the review results. • In Phase III, scholars more focus on plastic pollution in freshwater ecosystems. [ABSTRACT FROM AUTHOR]

The popularity of remanufacturing among the research community resulted in an increase in the number of academic publications in recent years. Quite a number of literature reviews related to reverse logistics, core acquisition management, Design for Remanufacturing (DfRem), production planning, analytical models in remanufacturing were published in various journals. The management of remanufactured products is quite complex due to specific operations like core acquisition, reverse logistics, disassembly, cleaning, repairing and reassembly. This often makes determining the price of remanufactured product a difficult task. Moreover, pricing of remanufactured products acts as a control mechanism to maintain the demand for both new and remanufactured products. A significant number of academic publications have been published regarding pricing and competition decision in remanufacturing. This paper aims to study with a focus on pricing related decisions in remanufacturing through bibliometric analysis that can provide insights into the latest research trends in this area by analysing the most significant and cited papers, authors collaboration network, keywords, countries, and institutions. In this paper, a thorough review and bibliometric analysis are conducted over 336 articles from 2000 until May 2020. The systematic mapping and analysis help to identify developing research areas, key research topics, publication evolution over time, collaboration patterns among authors, countries, the co-occurrence of authors keywords, and future research directions. From the content analysis, we have identified five pricing models such as pricing of remanufactured products under competition, impact of the product lifecycle on remanufacturing pricing, pricing related to product design in remanufacturing, pricing models under an uncertain environment, and optimal pricing under customer willingness-to-pay. We have also identified the decision variables, assumptions, and research objective(s) for each model. The findings of this research provide a direction for a further study in this domain, such as how pricing of a remanufactured products can be done in oligopolistic competition, how an effective product design strategy determines the price of remanufactured product, how the government regulatory policies influence the profitability in remanufacturing, or what is the effect of carbon cap and trade mechanism on the price of remanufactured products. [ABSTRACT FROM AUTHOR]

• Systematic literature review based on 136 papers on artificial intelligence applications in supply chain. • The distribution of the different AI techniques used across the SCOR areas is presented. • A classification of the research articles is proposed based on four critical structural dimensions. • Future research perspectives and areas needing further investigations are suggested. Today's supply chains are very different from those of just a few years ago, and they continue to evolve within an extremely competitive economy. Dynamic supply chain processes require a technology that can cope with their increasing complexity. In recent years, several functional supply chain applications based on artificial intelligence (AI) have emerged, yet very few studies have addressed the applications of AI in supply chain processes. Machine learning, natural language processing, and robotics are all potential enablers of supply chain transformation. Aware of the potential advantages of AI implementation in supply chains and of the paucity of work done regarding it, we explore what researchers have done so far with respect to AI and what needs further exploration. We reviewed 136 research papers published between 1996 and 2020 from the Scopus database and provided a classification of the research material according to four critical structural dimensions (level of analytics, AI algorithms or techniques, sector or industry of application, and supply chain processes). This study is the first attempt to study the AI applications in SC from a process perspective and provides a decisional framework for adequate use of AI techniques in the different SC processes. [ABSTRACT FROM AUTHOR]

The impact of micro- and nanoplastics (M/NPs) on terrestrial ecosystems has been a hot topic in recent years since the soil has been recognized as an important sink for M/NPs. In the current study, a CiteSpace-based scientometric analysis of 506 papers was performed to show the intellectual background, research performance, and state of art knowledge structure of M/NPs in the terrestrial environment over the past six years (2016 - January 2022). The most prolific publications, journals, authors, and countries involved in the flourishment of this field were identified. Additionally, visualization methods were employed to determine the highly productive keywords, hotspots, and research frontiers in the field of M/NPs in terrestrial environments. Furthermore, cluster analysis was performed to provide an accurate summary of this field by exploring the sub-domains of this field. China has proven to be the most prominent country among others in terms of publications and funding. This study can help researchers identify new research fronts and distinguish the most critical sub-domains of M/NPs in the terrestrial environment research. [Display omitted] • Scientometric analysis of micro- and nanoplastic in terrestrial ecosystem was done. • Sub-domains of this field were extracted through knowledge structuring. • Publications in this field increased by 8533.3% in 2021 relative to 2016. • China was the most prominent country in terms of publication and funding. • Studies about the trophic transfer of M/NPs should be considered in future. [ABSTRACT FROM AUTHOR]

Recent global commitments towards net-zero 2050 have resulted in an increased interest within a number of industries. The built environment has been identified as a major culprit contributing to the ongoing complex problem of carbon emissions. In an attempt to reveal the efforts, put into alleviating this challenge, this paper aims to provide a comprehensive, quantitative analysis of the literature on net-zero (energy and GHG emissions) in the built environment over the last two decades. In this study, well-established bibliometric and scientometric techniques are deployed to map the scientific domains by developing and analysing the resulting co-citation and keyword co-occurrence network developed from the bibliometric data from 1934 peer-reviewed articles retrieved from the SCOPUS database. The most significant contributions in net-zero research have originated primarily from UK, USA, and China. The results of the network analysis identified seven foundational themes of research - greenhouse gas emission, deep decarbonisation, earth material, residential building, high-rise building, displacement, ventilation, and walling element. The burst analysis revealed how a number of emerging digital technologies in the sector present opportunities to optimise future developments towards the attainment of a net-zero emission-built environment. To address the complexity associated with emissions caused by the built environment, the findings suggest that there is a need to expand the current LCA assessments to a broader, industry-wide scale, beyond the predominant 'single building case study' as the unit of reference. Moreover, the national net-zero pathway studies should aim to extend beyond the operational emission scenarios, and into assessing the impacts on materials and embedded emissions, which has grown exponentially. [ABSTRACT FROM AUTHOR]

In recent years, emerging contaminants have been found in the wastewater, surface water, and even drinking water, which should be treated to ensure the safety of our living environment. In this study, we provide a comprehensive summary of wastewater treatment and emerging contaminants research from 1998 to 2021 by using the bibliometric analysis. This study is conducted based on the Web of Science Core Collection Database. The bibliometix R-package, VOSviewer and CiteSpace software are used for bibliometric analysis and science mapping. A dataset of 10, 605 publications has been retrieved. The analysis results show that China has produced the most publications. China and the United States have the closest cooperation. Analysis of the most cited papers reveals that the purification or removal techniques such as ozonation or membrane filtration can effectively remove pharmaceutical compounds from the water environment. We also found that the efficient detection of emerging contaminants and the optimization of removal methods are current challenges. Finally, future research directions are discussed. Co-occurrence network of keywords. [Display omitted] • 10,605 publications of wastewater treatment and emerging contaminants were analyzed. • China and the United States have the closest cooperation. • China, United States, and Spain have the most documents. • The publication published by Heberer (2002) receives the most citations. • Removal is a popular keyword in this research. [ABSTRACT FROM AUTHOR]

Networks of coauthorship for scientific publication well represent the collaboration dynamics among members of a scientific community. Here, we employed a coauthor network analysis to identify research communities and their evolutionary patterns as the first attempt to characterize the dynamics of collaboration in environmental engineering. Using bibliometric data from 2007 to 2018 in environmental engineering, 20 research communities were identified and two major drivers of scientific collaboration were revealed: research interest and country of one's affiliation. We developed a novel methodology that enables tracking cluster's evolutionary patterns. This methodology allowed systematic stereotyping of each cluster as "mature" or "emerging". The two stereotypes did not show a significant difference in the annual growth rate of the volume of publications, implying that comparable attention has been paid to advancing the knowledge of formerly-established subjects and exploring innovative subjects of environmental engineering. • A total of 68,881 environmental engineering papers published 2007–2018 were collected to construct the coauthor network. • Twenty clusters identified from the coauthor network represent research communities in environmental engineering developed from spontaneous coauthoring. • Major drivers of scientific collaboration in environmental engineering were research interest and country of author's affiliation. • Novel methodology developed herein categorized evolutionary behaviors of research communities into "mature" or "emerging". [ABSTRACT FROM AUTHOR]

Phosphogypsum is a by-product of the phosphate fertilizer industry. It is generally treated by stacking, which not only causes environmental pollution, but also wastes resources. Therefore, the harmless, comprehensive, and high-value utilization of phosphogypsum has attracted more and more scholars around the world. From the perspective of bibliometrics, this paper systematically and comprehensively describes the research progress, trends and hot spots of phosphogypsum resource utilization. This article is based on a scientific network database, and a total of 1067 articles from 1985 to 2020 were collected. Then, use VOSViewer software to perform co-occurrence, co-citation analysis and cluster analysis. The visual analysis results demonstrate that the research on the resource utilization of phosphogypsum shows the characteristics of rapid growth. The active countries are mainly China, Brazil, Spain and the United States. Four of the top 10 active organizations are from China. It systematically expounds the changes in research hotspots in this field at different stages and possible future research hotspots. Including the gradual attention to the preparation of phosphogypsum building materials, phosphogypsum adsorption materials, and radioactive elements in phosphogypsum; the extraction of rare earth elements from phosphogypsum; the use of phosphogypsum to prepare fertilizer or soil improvement. Research shows that phosphogypsum can be reasonably designed, transformed, and used in different fields.However, the radioactivity contained in phosphogypsum should be paid attention to because it has an impact on humans and the environment. We believe that this research provides a comprehensive and systematic overview for future research on phosphogypsum resource utilization. • For the first time, the current research status of phosphogypsum is proposed by bibliometrics. • The extraction of building materials and rare earth elements reflects current research hotspots. • The environment and material application of phosphogypsum are discussed in detail. • Prospects and challenges in the field of comprehensive utilization of phosphogypsum are proposed. [ABSTRACT FROM AUTHOR]

• A bibliometric analysis on machine learning research in all engineering fields. • VOSviewer is employed to this study based on retrieved 3057 articles. • Research distributions of this topic are identified. • A detailed discussion on the knowledge bases, research hotspots and frontiers. In this work, we conducted a visualized bibliometric analysis to map the research trends of machine learning in engineering (MLE) based on articles indexed in the Web of Science Core Collection published between 2000 and 2019. The research distributions, knowledge bases, research hotspots, and research frontiers for MLE studies are revealed by using VOSviewer software and visualization technology. The growth of the literature related to MLE averaged 24.3% in the past two decades. A total of 3057 peer-reviewed papers from 96 countries published in 1299 different journals were identified. The USA was the most productive country, with 23.73% of the overall articles and 32.25% of the overall citations. The most active research organization was MIT, with 41 publications and 1079 citations, and the Journal of Machine Learning Research had the largest number of citations in the field of MLE. In particular, our findings indicate that the research issues of "random forests", "support vector machine", "extreme learning machine", "deep learning", "statistical learning theory", and "Python machine learning" formed the knowledge bases of MLE from 2000 to 2019, while the research hotspots focused on applications of machine learning benchmark algorithms. Burst detection analysis results showed that more burst keywords emerged and had a higher frequency of change after 2010. This study provides an insight view of the overall research trends of MLE and may help researchers better understand this research field and predict its dynamic directions. [ABSTRACT FROM AUTHOR]

Circular Economy (CE) and nexus thinking are increasingly considered as promising solutions for resource sustainability. While CE aims to design out waste through reducing, reusing, recycling and recovery of materials, the Nexus approach is interested to minimise waste and inefficiencies by focusing on the interlinkages between resources. Both concepts have been evolving separately with limited academic work to analyse their relationship. The aim of this systematic review, based on academic publications from 2004 to 2020, is to scrutinise the relationship between the circular economy and the nexus approach by adopting a mixed methods research design including bibliometric analysis and thematic synthesis. Our quantitative bibliometric analysis shows that, out of 7956 circular economy and 5795 nexus papers, academic documents explicitly mentioning both concepts account for less than 1% of each literature. Nonetheless, there is considerable overlap in most frequent words (50%–71%) as well as the most relevant sources (54%–56%) between both literatures. A detailed qualitative analysis of the documents relevant to both concepts also supports the existence of a close relationship between the two. From these analyses, we develop a new integrative conceptualization of the relationship between circular economy and the nexus approach. We conclude that there is good evidence for a three-tiered hierarchical relationship: 'intersection', 'interrelation' and 'interdependence', which we discuss in detail. Finally, emphasising the importance of an integrated approach, we propose a novel conceptual framework which combines circular economy and nexus approaches, which helps to operationalise nexus thinking on the one hand, and to converge the circular economy towards environmental sustainability on the other hand. As such, the framework addresses two known challenges of the concepts. However, whilst our integrated framework contributes to the conceptual development of both circular economy and the nexus approach, further research is required to highlight and facilitate their interrelation and interdependence in practice. [ABSTRACT FROM AUTHOR]