4.7 Article

Model-based assessment of the pattern differences and the equity of national carbon emissions in China during 2000-2010

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 103, Issue -, Pages 696-704

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2014.08.066

Keywords

Carbon emissions; The differences of spatial pattern; 3E model; Remote sensing survey; Carbon sink

Funding

  1. Key Research Program of the Chinese Academy of Sciences [KZZD-EW-14]
  2. National Natural Science Foundation of China [41171334]
  3. Talent Fund of Yantai Institute of Coastal Zone Research, Ecological Innovation & Breeding Project [Y254021031, Y355031061]
  4. USDA NIFA Project [2010-34263-21075]

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Land cover information of China was extracted using the supervised classification of remote sensing data and the carbon sink and carbon emissions of each province were calculated by combining the statistical data with the method of the Intergovernmental Panel on Climate Change (IPCC) 2006 listing. With the newly built 3E model, the three indexes of ESI (ecological support index), EDI (equitable distribution index) and EEI (economic efficiency index) were calculated and their spatial pattern characteristics and regional differences over time were analyzed. The research results indicated that as the forest coverage rate increased, the carbon sink of the ecosystem in China also increased. ESI in the central and western China was tending to decrease, while ESI in the eastern coast was growing. Although the EEI gap between eastern China and western China was large, their EDI value gap was becoming shrinking as the economic growth shifted towards the central China and western China. The 3E values which were calculated with the consideration of ecology, equity and efficiency for China's carbon emissions indicated that the carbon emissions in half provinces of China were in good conditions, with benign ecosystem circulation, fairness and high economic efficiency in the recent 11 years. These results could act as references for China's low carbon economic development and also could provide guidance for the spatial pattern planning of China's carbon emissions. (C) 2014 Elsevier Ltd. All rights reserved.

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