Carbon footprint (CF) research has attained tremendous popularity for improving the climate environment purposes. In particular, current energy use has been identified as the main cause of climate change. CF plays an irreplaceable role in managing energy use, reducing gas emissions, and improving climate change. The objective of this study was to review studies that have developed CF and to perform a bibliometric analysis using two key terms: “climate change” and “energy use”. From bibliometric analysis using CiteSpace and VOSviewer, it was possible to establish a knowledge map of cooperative network structure and research evolution. We are aiming to reveal the main logical chain of CF research leading to climate change, to make up for the lack of current literature, and provide research inspiration for researchers. The research findings mainly focus on four aspects. First, the relevant research began in 2008 and is in a state of continuous rise. Second, due to the law of research development and the prominence of practical problems, related research has experienced a stage from conceptual methods to specific problems. Third, China and the USA assume an important role in which international cooperation is the overall trend. Fourth, related research can be divided into CF algorithm research, ecological environment management research, and specific cross-industry fields. In addition, possible opportunities for change in related research are explored. It is also suggested that the integration of CF with other footprints, when energy use and environmental change are fully considered, may become an important future research trend by providing a more comprehensive environmental impact.
This study analyzes the driving factors behind regional income inequality to provide an important reference for China and other developing countries and to support the formulation of more effective regional development policies. The study used data from 625 county-level administrative units in China in 2017 and conducted a total factor analysis of China's regional income based on 10 economic dimensions using spatially explicit regression methods. The results show that commerce, population footprint, industrialization, and investment are the main factors that affected a Chinese region’s income, but different factors have different degrees of influence in different regions. The impact of economic institutions (developing an institutionally diverse market economy) on income cannot be ignored. Based on our findings, China should give local governments more autonomy, so they can formulate strategies that account for local constraints and opportunities, thereby increasing their chances of decreasing regional income inequality.
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