The panel vector autoregression (PVAR) model preserves the advantages of the vector autoregression model while expanding its time series to the spatial direction, which can effectively solve the problem of individual heterogeneity using panel data. It is derived from econometrics but has been applied interdisciplinarily because of its advantages in metrology. Given its increasingly important role in econometrics and interdisciplinary applications, a systematic review based on the bibliometric tool was conducted by screening 292 articles related to PVAR from the Web of Science. First, a descriptive analysis of the related articles was conducted to identify the current research status of PVAR. It reveals that macroeconomic effects, economic growth and environmental protection, and model adaptation are the primary topics in PVAR-related research. Then, the study classifies PVAR models into three categories and summarizes the four estimation methods within the knowledge domain. Having clarity on the different categories and estimation methods enhances the practical utility of the PVAR model. Finally, to gain insight into the knowledge evolution of PVAR, this study discusses how research hotspots in the field have evolved over time. This analysis provides a historical perspective and allows researchers to anticipate future trends and emerging areas of interest within PVAR. Based on these findings, this study identifies three research opportunities that can guide future investigations in the field of PVAR. This study aims to foster extension applications of the model in econometric research and highlight its potential for interdisciplinary applications.

The Chinese government has attached great importance to environmental collaborative governance recently to cope with rising pollution problems. How to measure environmental collaborative governance degree is a key issue to evaluate the level and progress of the implementation of this great ambition. This paper designs an index system for measuring environmental collaborative governance degree, covering dimensions of government, corporation and the public. The entropy method is applied to measure the change of environmental governance capacity. The coupling coordination model is adapted to evaluate the environmental collaborative governance degree of government–corporation–public. Empirical analysis is conducted by using the panel data of 30 provinces of China for the years 2006–2015. The results are provided and discussed from various dimensions. Suggestions are put forward accordingly. This paper focuses on developing a method for measuring environmental collaborative governance degree and is meaningful for enlightening future research about the effect of collaboration on environmental governance.

The Coronavirus Disease 2019 (COVID-19) infectious pneumonia pandemic highlights the importance of emergency management of public health emergencies (EMPHE). This paper addresses the challenge of building a knowledge system for EMPHE research that may contribute to understand the spatial and temporal characteristics of knowledge distribution, research status, cutting-edge research and development trends, and helps to identify promising research topics and guide research and practice of EMPHE. Based on the Web of Science, this paper retrieves 1467 articles about EMPHE published from 2010 to date. Then, based on high-frequency keywords, we use CiteSpace to analyze their knowledge co-occurrence network, clustering network and knowledge evolution. Furthermore, we summarize the features and gaps in EMPHE research, providing references for future research directions. Based on the above analysis, this work constructs a knowledge system about EMPHE research, providing a comprehensive visual summary of the existing research in the field of EMPHE, with the aim to guide future research and practice.

The increasing occurrences of greenwashing pose great risks to environmental protection. The current studies mainly focused on corporate greenwashing, and few paid attention to the greenwashing of the local government (GLG), thus lacking methods to identify the risks of forming the GLG and finding practicable countermeasures. This paper tries to fill the research gap in the study of the GLG by analyzing human factors. Given that the GLG is in close relationship with environmental governance pressures related to environmental information disclosure (EID), this paper attempts to analyze the human-caused risks of forming the GLG in the process of EID. This work focused on the process analysis, examined the human causes that form the GLG in the stages of collecting, medium, and disseminating of environmental information (EI), and offered countermeasures embedded with resilience accordingly.

With the deepening of industrialization and urbanization in China, air pollution has become the most serious environmental issue due to huge energy consumption, which threatens the health of residents and the sustainable development of the country. Increasing attention has been paid to the efficiency evaluation of industrial system due to its fast development and severe air pollution emissions, but the efficiency evaluation on China’s industrial waste gas still has scope for improvement. This paper proposes a global non-radial Network Data Envelopment Analysis (NDEA) model from the perspective of pollution prevention (PP) and end-of-pipe treatment (ET), to explore the potential reduction of generation and emission of air pollutants in China’s industrial system. Given the differences of different air pollution treatment capacities, the ET stage is further subdivided into three parallel sub-stages, corresponding to SO₂, NO_X, and soot and dust (SD), respectively. Then, grey relation analysis (GRA) is adopted to figure out the key factor affecting the unified efficiency. The main findings are summarized as follows: firstly, the unified efficiency of China’s industrial waste gas underperformed nationwide, and most provinces had the potential to reduce the generation and emission of industrial waste gas. Secondly, the PP efficiency outperformed the ET efficiency in many provinces and the efficiency gap between two stages increasingly narrowed except in 2014. Thirdly, the unified efficiency in the eastern area performed well, while the area disparities increased significantly after 2012. Fourthly, significant differences were found in three ET efficiencies and the ET efficiency of NO_X was higher than that of SO₂ and SD in the sample period. Finally, the results of GRA indicated that different air pollutants had distinct influence on the improvement of the unified efficiency in three areas. To promote the unified efficiency of industrial waste gas, some pertinent policy suggestions are put forward from the perspectives of sub-stages, air pollutants and areas.