Combining the principles of systemicity, cyclicity, and diversity in agroecosystem theory, we constructed an analytical framework for the ecological co-culture model (rice-fish + livestock + fruit mix), and attempted to reveal its synergistic mechanism and evolutionary pathway in low-carbon agriculture by bibliometric methods. The COVID-19 pandemic, which emerged in 2019, has significantly impacted agricultural production and food security, emphasizing the urgent need for high-quality, sustainable agricultural development. Although agriculture is not the largest contributor to energy use or carbon emissions, its sustainable development can reduce global energy dependency, accelerate the energy transition, and contribute to achieving carbon neutrality. Moreover, a green, low-carbon energy structure is crucial for supporting sustainable agricultural practices. This study systematically reviews current research on ecological co-culture models in low-carbon agriculture in China, offering theoretical foundations for future research and strategic insights for promoting sustainable agricultural development. Using the China National Knowledge Infrastructure (CNKI) and Web of Science (WOS) Core Collection for data retrieval and employing CiteSpace software for bibliometric analysis, the study reveals the following key findings: (1) Research is highly concentrated, with approximately 52% of studies focused on the “rice-fish symbiosis” model, while research on the “fruit trees + poultry ecological co-culture” model remains relatively sparse. Although approximately one-third of the literature addresses “low-carbon agriculture,” only 2% of the articles explore the relationship between “ecological co-culture” and “low-carbon agriculture,” with approximately 8% covering “vertical cultivation.” (2) Both domestic and international publications primarily focus on ecology, life sciences, agriculture, and aquaculture, with minimal representation in geographical journals. (3) The CiteSpace analysis of research publications between 2008 and 2023 found that China Agricultural University and the Institute of Geographic Sciences and Natural Resources Research of the Chinese Academy of Sciences were in a leading position in the field of agriculture and life sciences. (4) There are 255 principal authors with 319 cooperative connections, indicating that there are extensive collaboration networks among scholars and significant potential for advancing research on low-carbon agriculture and ecological co-culture models in China. (5) The most prominent keywords from 2014 to 2023 include “rice,” “rice-fish symbiosis,” and “ecological symbiosis.” Additional keywords such as “rural revitalization” and “low-carbon agricultural technology” have attracted considerable attention, with a peak intensity value of 4.8. These results reflect the evolving focus of research on low-carbon agriculture in the post-pandemic era. Over time, research priorities have shifted from vertical farming and paddy-field fish farming to food security under peak carbon and green finance, while international studies have increasingly emphasized on genetic diversity. Through a quantitative review of domestic and international literature, this paper addresses a critical gap in the study of low-carbon ecological co-culture. In conclusion, our findings underscore that research on ecological co-culture models within low-carbon agriculture remains a critical area of focus both domestically and internationally. Continued exploration in this field will not only improve sustainable agriculture but also provide valuable insights for future research directions.

The rapid development of the global transportation industry has led to increased carbon dioxide emissions, intensifying the pressure to reduce these emissions. On the basis of constructing a global carbon emission analysis framework for the transportation industry, this study used panel data on carbon emissions from the transportation industry in 140 countries or regions for a long-term time series from 1971 to 2018. The standard deviation ellipse, Gini coefficient, and Moran’s I index were used to characterize the spatial patterns of carbon emissions in the global transportation industry. The factors influencing carbon emissions from the global transportation industry were analyzed using quantile regression. The main findings are as follows: (1) From the distribution pattern, the total carbon emissions from the global transportation industry showed a significant upward trend, and the spatial polarization characteristics were particularly significant. (2) The Gini coefficient of global carbon emissions from the transportation industry showed a significant downward trend, characterizing a more balanced spatial distribution. (3) From the perspective of correlation patterns, the spatial distribution of carbon emissions from the global transportation industry was positively correlated. (4) Regarding influencing factors, population size had a significant role in promoting carbon emissions from the transportation industry, and the difference was not apparent. The influence of affluence on carbon emissions was basically in line with the characteristics of the Kuznets curve, technological advances had a significant negative influence on carbon emissions, and participation in the global value chain had a significant influence on carbon emissions from countries or regions with high carbon emissions. In conclusion, it is necessary to enhance international cooperation on carbon emission management in the global transportation industry and adopt differentiated policy measures. For instance, we should accelerate the construction of a multimodal transport system, increase the promotion and support for new energy heavy-duty trucks, implement policies such as priority road rights for new energy heavy-duty trucks and reduce tolls on expressways, and deepen the integration of transportation and energy.