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• W2954086192 abstract "To identify the interaction pattern features and driving forces of intersectoral CO2 emissions, this paper studies the interaction pattern types, interaction linkage strengths and key interaction patterns of 28-sector CO2 emissions flow networks in China from 1997 to 2015 via network motif analysis. Network motif analysis is a useful tool for measuring interactions between agents and their function in networks. This paper extends network motif analysis by investigating the weighted edges of motifs to observe the function of motifs. The results show that in 1997–2002 and 2008–2015, the strongest carbon intensity sectors, including electricity production, metal smelting and gas production, were the greatest contributors to the increase in intersectoral CO2 emissions. From 2003 to 2007, the strongest energy intensity sectors, including electricity production and fuel processing, were the greatest contributors. In contrast, the strongest export intensity sectors, including other electronic equipment, leather manufacturing, instrumentation, and textile, were the largest contributors to the decrease in intersectoral CO2 emissions. Second, the strongest interaction linkages were between construction and nonmetallic products and metal smelting, machinery and construction and metal smelting, construction and nonmetallic products, construction and metal smelting. Third, the key interaction patterns for the increase in intersectoral CO2 emissions were patterns such as infrastructure-export, manufacturing intensive, energy consumption, and energy tracing, while the export-intensive pattern and high export pattern were the key interaction patterns for the decrease in intersectoral CO2 emissions. This paper is beneficial to the establishment of a coordinated emissions reduction mechanism across sectors." @default.
• W2954086192 created "2019-07-12" @default.
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• W2954086192 date "2019-10-01" @default.
• W2954086192 modified "2023-10-14" @default.
• W2954086192 title "Interaction pattern features and driving forces of intersectoral CO2 emissions in China: A network motif analysis" @default.
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• W2954086192 doi "https://doi.org/10.1016/j.resconrec.2019.03.006" @default.
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