Carbon emission performance evaluation and allocation in Chinese cities

被引:98
作者
Zhou, Zhongbao [1 ]
Liu, Cenjie [1 ]
Zeng, Ximei [1 ]
Jiang, Yong [1 ]
Liu, Wenbin [1 ,2 ]
机构
[1] Hunan Univ, Sch Business Adm, Changsha 410082, Hunan, Peoples R China
[2] Univ Kent, Kent Business Sch, Canterbury CT2 7PE, Kent, England
基金
中国国家自然科学基金;
关键词
Data envelopment analysis; Total-factor CO2 emission performance; CO2 emission allocation; Multiple abatement factors; Urban environment; NONPARAMETRIC PRODUCTION ANALYSIS; FUEL POWER-PLANTS; CO2; EMISSIONS; ENVIRONMENTAL EFFICIENCY; UNDESIRABLE OUTPUTS; DIOXIDE EMISSIONS; REGIONAL ALLOCATION; PRODUCTIVITY GROWTH; WEAK DISPOSABILITY; INITIAL ALLOCATION;
D O I
10.1016/j.jclepro.2017.10.208
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper presents a DEA approach with multiple abatement factors to evaluate CO2 emission performance and allocate CO2 emission quotas in Chinese cities. We first consider the difference of marginal abatement costs among cities, and construct the non-radial directional distance function with multiple abatement factors. The total-factor CO2 emission performance index and its dynamic change index are then proposed to measure CO2 emission performance. Considering equity and efficiency, we develop a composite index by the hybrid method to allocate emissions quota, which considers CO2 emissions as well as CO2 emission performance. Then we conduct an empirical study using inputs and outputs dataset of 71 Chinese cities in 2005-2012. Chinese cities have poor energy efficiency and still have high CO2 emissions. The eastern region outperforms the central region and the western region performs worst, whereas the dynamic CO2 emission performance of the central region has the largest increase. The change of CO2 emission performance is driven mainly by technological advances. As for the CO2 emission allocation, the composite index method encourages cities to reduce emissions and enhance emission performance through carbon trading market. It also motivates cities with high historical emissions to reduce their emissions by improving technology when they have poor CO2 emission performance. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1254 / 1272
页数:19
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