Key drivers of the rebound trend of China's CO2emissions

被引:10
作者
Zhang, Yaxin [1 ]
Zheng, Xinzhu [2 ]
Cai, Wenjia [3 ,4 ]
Liu, Yuan [5 ]
Luo, Huilin [1 ]
Guo, Kaidi [1 ]
Bu, Chujie [1 ]
Li, Jin [1 ]
Wang, Can [1 ,4 ]
机构
[1] Tsinghua Univ, State Key Joint Lab Environm Simulat & Pollut Con, Sch Environm, Beijing 100084, Peoples R China
[2] China Univ Petr, Sch Econ & Management, Beijing 102249, Peoples R China
[3] Tsinghua Univ, Dept Earth Syst Sci, Beijing 100084, Peoples R China
[4] Tsinghua Rio Tinto Joint Res Ctr Resources Energy, Beijing 100084, Peoples R China
[5] Hitotsubashi Univ, Sch Econ, Tokyo 1868601, Japan
基金
中国国家自然科学基金;
关键词
CO(2)emission; rebound; SDA; infrastructure investment; economic transformation; INDUSTRIAL-STRUCTURE; TECHNICAL PROGRESS; ECONOMIC-GROWTH; CO2; EMISSIONS; ENERGY; INFRASTRUCTURE; INVESTMENT; INTENSITY; DECLINE;
D O I
10.1088/1748-9326/aba1bf
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
China's CO(2)emissions declined by 5.1% in 2013-2016 as China steps into a new period of development, in which the economy shifts from the previous high-speed growth driven by input and investment to a medium-speed growth driven by innovation and consumption. However, the decline did not continue; the national CO(2)emissions rebounded since 2016, with the drivers of the rebound unclear. Here, we apply the input-output structure decomposition analysis to decompose emissions in 2002-2017 to reveal driving factors of the emission rebound trend. Results show that the input-output structure among sectors (partially reflecting production structure) and the demand pattern have contributed to emission reduction as China entering 'the new normal' pattern of development. However, the two factors reversed and therefore induced emissions, contributing to 5.2% and 0.1% of the increase in emissions since 2015. Such obvious contribution reversal can be explained as a new round of infrastructure stimulated substantial energy consumption and the electricity demand was mainly supported by coal-fired power (59.0%). Besides, the emission reduction effect of the energy mix has shrunk from -11.8% in 2012-2015 to -6.9% in 2015-2017, closely related to the slowing growth of renewable energy and the slight recovery of coal consumption. The findings can reasonably infer novel insights into curbing the potential reversal of China's emission trend and aligning China's CO(2)emission trend with the goal of achieving peak emissions before 2030.
引用
收藏
页数:10
相关论文
共 45 条
[1]  
[Anonymous], 1999, Handbook of Input-Output Table Compilation and Analysis
[2]  
[Anonymous], 2018, GLOB INFR HUB
[3]   Nonlinear Effect of Public Infrastructure on Energy Intensity in China: A Panel Smooth Transition Regression Approach [J].
Bi, Chao ;
Jia, Minna ;
Zeng, Jingjing .
SUSTAINABILITY, 2019, 11 (03)
[4]   Industrial structure, technical progress and carbon intensity in China's provinces [J].
Cheng, Zhonghua ;
Li, Lianshui ;
Liu, Jun .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2018, 81 :2935-2946
[5]  
Crippa M, 2019, 29849 EUR EN
[6]   China's non-fossil fuel CO2 emissions from industrial processes [J].
Cui, Duo ;
Deng, Zhu ;
Liu, Zhu .
APPLIED ENERGY, 2019, 254
[7]   Leveraging Green Communications for Carbon Emission Reductions: Techniques, Testbeds, and Emerging Carbon Footprint Standards [J].
Despins, Charles ;
Labeau, Fabrice ;
Tho Le Ngoc ;
Labelle, Richard ;
Cheriet, Mohamed ;
Thibeault, Claude ;
Gagnon, Francois ;
Leon-Garcia, Alberto ;
Cherkaoui, Omar ;
St Arnaud, Bill ;
McNeill, Jacques ;
Lemieux, Yves ;
Lemay, Mathieu .
IEEE COMMUNICATIONS MAGAZINE, 2011, 49 (08) :101-109
[8]  
Dietzenbacher E., 1998, ECON SYST RES, V10, P307, DOI [10.1080/09535319800000023, DOI 10.1080/09535319800000023]
[9]   Sustainable transportation based on electric vehicle concepts: a brief overview [J].
Eberle, Ulrich ;
von Helmolt, Rittmar .
ENERGY & ENVIRONMENTAL SCIENCE, 2010, 3 (06) :689-699
[10]   Novel home energy management system using wireless communication technologies for carbon emission reduction within a smart grid [J].
Elkhorchani, Habib ;
Grayaa, Khaled .
JOURNAL OF CLEANER PRODUCTION, 2016, 135 :950-962