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Sector aggregation effect on embodied carbon emission based on city-centric global multi-region input-output (CCG-MRIO) model

Duo Xu, Gengyuan Liu, Fanxin Meng, Ningyu Yan, Hui Li, Feni Agostinho, Cecilia MVB Almeida and Biagio F Giannetti

Ecological Modelling, 2023, vol. 484, issue C

Abstract: Sector aggregation under the input-output framework may lead to deviation in results and the lack of detailed sectoral information, which hinder the targeted implementation of accurate sectoral adjustment policies. This paper explores the effects of sector aggregation on the embodied carbon emission of the residential consumptions of Beijing and Shanghai based on the city-centric global multi-region input-output (CCG-MRIO) model. Integrating with structural path analysis and structural decomposition analysis, the impacts of sector aggregation on the identifying of critical emission transmission paths and driving forces are also revealed. Three sector aggregation datasets are discussed to track the sector aggregation effect in 2012 and 2017. The findings show that the carbon emission results at 8 sector level better align with the results at the 22 sector level than those at 32 sector level. Moreover, sector aggregation will lead to the absence of some critical carbon transmission paths, some factor contributions on carbon emission also changed their directions at different sector levels. On the basis of clarifying the sector aggregation effect on embodied carbon emission, the research results provide a reference for similar studies to select the appropriate level of sector aggregation, to realize the goal of simplifying the calculation or gaining more detailed sectoral emission information.

Keywords: City-centric global multi-region input-output model; Sector aggregation effect; Embodied carbon emission; Structural decomposition analysis; Structural path analysis (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:484:y:2023:i:c:s030438002300217x

DOI: 10.1016/j.ecolmodel.2023.110487

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