CO2 emissions in Beijing: Sectoral linkages and demand drivers

Hua Liao*, Célio Andrade, Julio Lumbreras, Jing Tian

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    40 Citations (Scopus)

    Abstract

    Cities contribute to most of the CO2 emissions. And the economic system at city level is much complex due to various linkaged sectors. This paper aims to analyze the economy-wide contribution of sectors and households to CO2 emissions in Beijing (China) by utilizing a semi-closed input-output model integrated with a modified hypothetical extraction method. Results show that, compared with 2005, in 2012 (1) interprovincial export caused the largest amount of CO2 emissions [135.5 Mt] with the main contributions arising from manufacturing (42.1 Mt); transportation, storage, and post (TSP in short, 29.1 Mt); and households (23.6 Mt); (2) across the intermediate input-output system, real estate activities accounted for the largest amount of embodied CO2 intensity (0.07 kg per yuan) and more sectors outsourced CO2; (3) tracing the integrated sector network, CO2 linkages pointed to manufacturing and TSP dominating the internal linkages, manufacturing prominent in mixed linkages, secondary industry leading the net forward linkages, and tertiary industry dominant in terms of net backward linkages, helping control CO2 according to its origin; (4) CO2 emissions induced by household strikingly affected total CO2 emissions in Beijing, mainly coming from income-oriented affects, with a large rural-urban disparity and a similar sectoral distribution pattern. Finally, we propose suggestions on carbon reduction in terms of technological interlinkages, final demand and household participation.

    Original languageEnglish
    Pages (from-to)395-407
    Number of pages13
    JournalJournal of Cleaner Production
    Volume166
    DOIs
    Publication statusPublished - 10 Nov 2017

    Keywords

    • Beijing
    • CO emissions
    • City
    • Modified hypothetical extraction method
    • Semi-closed input-output model

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