A dual-core system dynamics approach for carbon emission spillover effects analysis and cross-regional policy simulation

Social network analysis of regional transport carbon emissions in China: Based on motif analysis and exponential random graph model

Given the significant impact of transportation-related carbon emissions on air quality and climate change, understanding the regional dynamics of these emissions is crucial. Despite numerous studies on carbon emissions, there is a lack of comprehensive analysis of China's interprovincial transport carbon emission correlation network. Based on China's provincial data from 2007 to 2021, we analyzed the network's basic structural characteristics and categorized it into four significant plates to investigate their interactions. Subsequently, motif analysis is employed to examine the micro-correlation patterns within the network, and the Exponential random graph model (ERGM) is utilized to analyze the network's formation mechanism. Findings reveal that: (1) Provinces with high correlation intensity are predominantly concentrated in the eastern region, such as Shanghai and Beijing. Additionally, provinces in the eastern region assume a central role in the transport carbon emission correlation network, mainly receiving carbon emissions from other provinces. In contrast, the western region primarily emits carbon emissions to other provinces, continuously converging towards the center. (2) The network is segmented into net beneficiary plate, net overflow plate, bidirectional spillover plate, and broker plate, with distinct roles and influences across different years. (3) Bidirectional correlation motif structures emerge as primary influencers within the network, although specific structures impede interregional communication and collaborative emission reduction. (4) Internal network's structural variables, such as mutuality, cyclic triple, and geometrically weighted edgewise shared partner, along with influencing factors including government intervention, urbanization rate, openness, fiscal expenditure on transport, and province adjacency significantly impact the formation of the transport carbon emission correlation network. The above transportation network research provides a theoretical basis for the country to promote low-carbon transportation and improve air quality, and also has important guiding significance for the cross-regional collaborative emission reduction work of provinces.

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.