The spatial characteristics of embodied carbon emission flow in Chinese provinces: a network-based perspective

A comprehensive study on carbon emissions flows and key drivers within China's domestic and global value chains

Numerous studies have examined the transfer of carbon emissions in China's trade. However, few papers have established a link between China's domestic value chains (DVCs) and the global value chains (GVCs) to comprehensively trace the flows of carbon emissions within a unified framework. To address this research gap, our paper aims to connect China's DVCs with the GVCs and map the carbon emissions flows of China's eight regions in both domestic and international trade. Using structural decomposition analysis (SDA), it studies the driving factors behind change in carbon emissions transfer (CET). Our findings are as follows: Firstly, in 2018, the total carbon emissions transfer of China's eight regions amounted to 5122.0mt, a significant increase of 31.1 % compared to 2012. Notably, the carbon emissions transfer through intermediate product trade is more than four times that of the final product trade. Secondly, significant variations exist in the sources and destinations under different trade patterns, which have been largely overlooked in the existing literature. Over 70.0 % of carbon emissions resulting from final product trade are directed towards regions outside of Chinese mainland, while approximately two-thirds of carbon emissions resulting from intermediate product trade are allocated to Chinese mainland's internal regions. Thirdly, the reduction of carbon emissions transfer increment is primarily driven by the carbon intensity, while the indirect demand scale effect of Chinese mainland's internal regions emerges as the most significant driving factor, playing a substantial role in the increase of carbon emissions transfer. Additionally, the unreasonable input-output structure between regions within Chinese mainland has contributed to the rise in carbon emissions transfer. The research findings offer valuable insights and policy recommendations for the formulation of regional carbon reduction policies in China.

Spatial and socioeconomic characteristics of CO2 emissions and sequestration in Indonesian cities

In dealing with the impacts of climate change, mitigation efforts play a crucial role. As one of the G20 countries on the list of the top 5 biggest contributors to emissions, Indonesia must play an active role. With all their characteristics and as one of the most significant contributors to global emissions, cities are fully responsible as a core area for climate mitigation. By analyzing the spatial and socioeconomic characteristics within the city scope, this study examines 32 representative cities and municipalities in Indonesia to understand the condition of carbon emissions and sequestration. Emissions and sequestration in selected cities in Indonesia show varying statuses; most cities have higher emission levels than sequestration, but some cities do the opposite. In addition, emissions and sequestration are also influenced by many complex and interrelated factors, including spatial (distribution, intensity, LULC, geographical conditions, total area), social (total population, urbanization rate, employment rate), economic (GDP/GRDP), and technological (industry structure and energy sector). As an archipelagic country, the uniqueness of cities in Indonesia, primarily located in coastal and waterfront areas, also influences the emission intensity, which tends to be lower in these areas on a micro basis. Cities classified as economically developed contribute more emissions at the national level. Therefore, a characteristic-based classification of the selected cities can encourage policy implications according to the characteristics of each city. These cities can learn from each other, especially from cities with high sequestration rates, to develop in a sustainable way while supporting national mitigation targets.

Analysis of spatial correlation networks of carbon emissions in emerging economies

Studies have shown that energy consumption from economic development leads to an increase in carbon emissions. Emerging economies, as important sources of carbon emissions with high growth potential, play a crucial role in global decarbonisation efforts. However, the spatial pattern and evolution trend of carbon emissions in emerging economies have not been studied in depth. Therefore, this paper uses the improved gravitational model and carbon emission data from 2000 to 2018 to construct a spatial correlation network of carbon emissions in 30 emerging economies around the world, aiming to reveal the spatial characteristics and influencing factors of carbon emissions at the national level. The results show that the spatial network structure of carbon emissions in emerging economies is closely linked, forming a "big network" of interconnection. Amongst them, Argentina, Brazil, Russia, Estonia, etc. are at the centre of the network and play a leading role. Geographical distance, economic development level, population density, and scientific and technological level have a significant impact on the formation of spatial correlation between carbon emissions. Further use of GeoDetector shows that the explanatory power of two-factor interaction on centrality is greater than that of a single factor, indicating that a single economic development cannot well enhance the influence of countries in the carbon emission network, and needs to be combined with factors such as industrial structure and scientific and technological level. These results are helpful to understand the correlation between carbon emissions between countries from the perspective of the whole and part and provide a reference for optimizing the carbon emission network structure in the future.

Research on Carbon Emission Efficiency Space Relations and Network Structure of the Yellow River Basin City Cluster

The Yellow River Basin serves as China's primary ecological barrier and economic belt. The achievement of the Yellow River Basin's "double carbon" objective is crucial to China's green and low-carbon development. This study examines the spatial link and network structure of city cluster carbon emission efficiency in the Yellow River Basin, as well as the complexity of the network structure. It focuses not only on the density and centrality of the carbon emission efficiency network from the standpoint of city clusters, but also on the excellent cities and concentration of the city cluster 's internal carbon emission efficiency network. The results show that: (1) The carbon emission efficiency of the Yellow River Basin has been dramatically improved, and the gap between city clusters is narrowing. However, gradient differentiation characteristics between city clusters show the Matthew effect. (2) The distribution of carbon emission efficiency in the Yellow River Basin is unbalanced, roughly showing a decreasing trend from east to west. Lower-level efficiency cities have played a significant role in the evolution of carbon emissions efficiency space. (3) The strength of the carbon emission efficiency network structure in the Yellow River Basin gradually transitions from weakly correlated dominant to weakly and averagely correlated dominant. Among them, the Shandong Peninsula city cluster has the most significant number of connected nodes in the carbon emission efficiency network. In contrast, the emission efficiency network density of the seven city clusters shows different changing trends. Finally, this study suggests recommendations to improve carbon emission efficiency by adopting differentiated governance measures from the perspective of local adaptation and using positive spatial spillover effects.