論文

2017年9月

Developing a city-centric global multiregional input-output model (CCG-MRIO) to evaluate urban carbon footprints

ENERGY POLICY
  • Jianyi Lin
  • ,
  • Yuanchao Hu
  • ,
  • Xiaofeng Zhao
  • ,
  • Longyu Shi
  • ,
  • Jiefeng Kang

108
開始ページ
460
終了ページ
466
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1016/j.enpol.2017.06.008
出版者・発行元
ELSEVIER SCI LTD

The consumption-based carbon footprint (CBF) can facilitate the implementation of broader mitigation policies that concern final consumption. Here, a city-centric global multiregional input-output model (CCG-MRIO) was developed to assess the carbon footprints of urban consumption in the global supply chain. Beijing was selected as the studied case, and results were as follow. In 2010, Beijing's CBF was 338.26 Mt CO(2)e, which was 1.90 times amount of its purely geographic accounting (PGA). Manufacturing, services, and construction were the top three consumers, while Mainland China and other developing regions were the main net importing areas, and utilities, manufacturing, and agriculture were the top net importing sectors. These findings indicated that Beijing imports large amounts of energy, water, and raw materials to support its consumption, while it mainly exports services and industrial products. The study fills the gap of data and methods for urban CBF compiling and can replicate to other cities with an input-output table. The CBF can promote sustainable local consumption behaviors, local production efficiencies improvement, and cooperation with importing regions. However, the model uncertainties increase in coordinating sectors, estimating trade relationship, and ignoring traffic differences; and the availability of municipal input-output table and energy data hinder its application.

リンク情報
DOI
https://doi.org/10.1016/j.enpol.2017.06.008
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000406725800043&DestApp=WOS_CPL
ID情報
  • DOI : 10.1016/j.enpol.2017.06.008
  • ISSN : 0301-4215
  • eISSN : 1873-6777
  • Web of Science ID : WOS:000406725800043

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