Perspective on China?s commitment to carbon neutrality under the innovation-energy-emissions nexus

被引:19
作者
Ahmed, Khalid [1 ,2 ]
机构
[1] Xi An Jiao Tong Univ, Sch Publ Policy, Adm SPPA, Xianning West Rd, Xian 710049, Shaanxi, Peoples R China
[2] Australian Natl Univ, Crawford Sch Publ Policy, 132 Lennox Crossing, Canberra, ACT 2600, Australia
关键词
Green innovation; CO; 2; emissions; Renewables; GDP; EKC; RENEWABLE ENERGY; SUSTAINABLE DEVELOPMENT; TECHNOLOGICAL-INNOVATION; ECONOMIC-GROWTH; CO2; EMISSIONS; ENVIRONMENTAL SUSTAINABILITY; POLICY; CONSUMPTION; INDICATORS; MANAGEMENT;
D O I
10.1016/j.jclepro.2023.136202
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The changing landscape in global geopolitics of energy security coupled with post-COVID slow economic re-covery has raised concerns about China's carbon neutrality commitment. This study seeks to answer the role of China's green innovation, renewables, non-renewables, and GDP for CO2 emissions using the novel Quantile Auto-regressive Distributed Lag (QARDL) model over an extended period from 1990 to 2020. The results conclude that green innovation can reduce CO2 emissions by up to three times with a 1:3 ratio while renewable energy sources are able to cut CO2 emissions with a modest rate of return at a 1:0.8 ratio. Similarly, with a 1:3.5 ratio, fossil fuels which still account for more than 83% of total energy consumption are highly emission -intensive. GDP spurs CO2 emissions but at a decreasing rate. In addition, the results also conclude the valida-tion of the EKC hypothesis, meaning that GDP has the potential to offset environmental degradation in both short-and long-run paths. In the current situation, the renewable energy sector is environmentally inefficient and needs policy reforms. Considering the current economic slowdown and potential future challenges to energy security, the country needs to take stringent policy measures to fulfill its existing commitments in self-interest.
引用
收藏
页数:9
相关论文
共 77 条
[1]   Impact of knowledge management practices on green innovation and corporate sustainable development: A structural analysis [J].
Abbas, Jawad ;
Sagsan, Mustafa .
JOURNAL OF CLEANER PRODUCTION, 2019, 229 :611-620
[2]   CO2 behavior amidst the COVID-19 pandemic in the United Kingdom: The role of renewable and non-renewable energy development [J].
Adebayo, Tomiwa Sunday ;
AbdulKareem, Hauwah K. K. ;
Bilal ;
Kirikkaleli, Dervis ;
Shah, Muhammad Ibrahim ;
Abbas, Shujaat .
RENEWABLE ENERGY, 2022, 189 :492-501
[3]   The potency of eco-innovation, natural resource and financial development on ecological footprint: a quantile-ARDL-based evidence from China [J].
Afshan, Sahar ;
Yaqoob, Tanzeela .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (33) :50675-50685
[4]   What new technology means for the energy demand in China? A sustainable development perspective [J].
Ahmed, Khalid ;
Ozturk, Ilhan .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2018, 25 (29) :29766-29771
[5]   Predictive analysis of CO2emissions and the role of environmental technology, energy use and economic output: evidence from emerging economies [J].
Ahmed, Sidrah ;
Ahmed, Khalid ;
Ismail, Muhammad .
AIR QUALITY ATMOSPHERE AND HEALTH, 2020, 13 (09) :1035-1044
[6]   Cleaner Production initiatives and challenges for a sustainable world: an introduction to this special volume [J].
Almeida, C. M. V. B. ;
Bonilla, S. H. ;
Giannetti, B. F. ;
Huisingh, D. .
JOURNAL OF CLEANER PRODUCTION, 2013, 47 :1-10
[7]  
[Anonymous], WORLD DEV IND
[8]   The asymmetric effect of public private partnership investment on transport CO2 emission in China: Evidence from quantile ARDL approach [J].
Anwar, Ahsan ;
Sharif, Arshian ;
Fatima, Saba ;
Ahmad, Paiman ;
Sinha, Avik ;
Khan, Syed Abdul Rehman ;
Jermsittiparsert, Kittisak .
JOURNAL OF CLEANER PRODUCTION, 2021, 288
[9]   Energy supply, its demand and security issues for developed and emerging economies [J].
Asif, M. ;
Muneer, T. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2007, 11 (07) :1388-1413
[10]   Quantile forecasting and data-driven inventory management under nonstationary demand [J].
Cao, Ying ;
Shen, Zuo-Jun Max .
OPERATIONS RESEARCH LETTERS, 2019, 47 (06) :465-472