Abstract
Fossil fuel combustion and industrial process would lead to substantial carbon emissions. Carbon emission metabolism is essential for alleviating climate changes globally. Here, a dynamic input-output model is developed for analyzing carbon emission metabolism and ecological hierarchy. Both direct and indirect carbon emissions are evaluated, and mutual relationships between various sectors are explored. Novelties of this research are summarized as follows: firstly, for negative ecological elements, e.g., carbon emissions, production activities between sectors with competition relationship should be encouraged since its positive effects in emission mitigation. On the contrary, interferring production activities between sectors with mutualism relationships would help to carbon abatement. More-over, analysis of indirect carbon emissions could identify the embodied sectors with large emissions, and these sectors should adjust their production structures and upgrade the cleaner production technology. In addition, ecological hierarchy analysis would help to identify key sectors lacking driving or pulling force during study period. It provides a new insight into formulating or maintaining a healthy ecological system. Results show that carbon emissions mainly concentrated in electricity-generation, manufacturing, and transportation sec-tors. For the Province of Guangdong, electricity-generation and mining sectors should upgrade the cleaner production technologies. Sub-stitution for renewable energy would accelerate the green transition within power system. For construction sector with large indirect carbon emissions, adjusting the consumption structure would contribute to achiving the emission mitigation goal. Tertiary industry is not sufficiently promoting Guangdong’s economic development, and therefore plays a restrictive role in the current economy. These would support the formation of emission abatement policies.
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Li, J. Z., & Li, S. C. (2021). Dynamic Input Output Analysis: Carbon, Water and Ecological Hierarchy. Journal of Environmental Informatics Letters, 6(1), 45–54. https://doi.org/10.3808/jeil.202100065
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