Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/8632
Title: An inquiry into inter-provincial carbon emission difference in China: Aiming to differentiated KPIs for provincial low carbon development
Authors: Bai, Hongtao 
Qiao, Sheng 
Liu, Ting 
Dr. ZHANG Yingxuan, Cynthia 
Xu, He 
Issue Date: 2016
Source: Ecological Indicators, 2016, Vol. 60, pp. 754-765.
Journal: Ecological Indicators 
Abstract: Reasonable formulation of carbon emission reduction strategies at sub-national scale is an important technique to realize the national target. However, a set of binding unified key performance indicators (KPIs) is usually not conducive to equitable regional development. Our study employs a hybrid carbon emission estimation method and a multi-index joint representation approach to explore the inter-provincial energy-related carbon emission difference in the year of 2012 in China. Stepwise regression method and hierarchical clustering model were used to classify 30 provinces into economically developed low-carbon region, industrially optimized low-carbon region, resource-abundant high-carbon region, and economically developing high-carbon region. Different regions should take differentiated measures and KPIs related to the local government's efforts to promote low carbon roadmap according to local conditions: The lack of natural resource provides the impetus to improve energy structure in the economically developed low-carbon region. The industrially optimized low-carbon region should place great importance on economic growth and per capita GDP improvement. The low-carbon transformation strategy of the resource-abundant high-carbon regions should focus on carbon emission reduction performance and carbon intensity decline. For economically developing high-carbon regions, decision makers should conduct a sound SWOT analysis of regional low carbon development. © 2015 Elsevier Ltd. All rights reserved.
Type: Peer Reviewed Journal Article
URI: http://hdl.handle.net/20.500.11861/8632
ISSN: 1470160X
DOI: 10.1016/j.ecolind.2015.08.029
Appears in Collections:Business Administration - Publication

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