4.7 Article

What is the probability of achieving the carbon dioxide emission targets of the Paris Agreement? Evidence from the top ten emitters

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 622, 期 -, 页码 1294-1303

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.scitotenv.2017.12.093

关键词

CO2 emission; Climate change; Paris Agreement; Energy consumption; Renewable energy

资金

  1. National Natural Science Foundation of China [71273277, 41371530]
  2. National Social Science Foundation of China [13ZD159, 13ZD045, 17BGL014]

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This study predicts the probabilities of achieving the carbon dioxide (CO2) emission targets set by the Paris Agreement and the Intended Nationally Determined Contribution (INDC) of the top ten CO2 emitters (TTCE). The TTCE are China, USA, India, Russia, Japan, Germany, South Korea, Iran, Saudi Arabia and Indonesia based on their emission trends over 1991-2015 period. The methods of trend extrapolation and back propagation (BP) neural networks are used in this paper to overcome the weakness of multiple linear regression (MLR) and the assumptions of the environmental Kuznets curve (EKC). The results show that the model performs well and has high predictive accuracy. The volume of the CO2 emissions by the TTCE in 2030 is predicted to increase by 26.5-36.5%, compared with 2005. According to different trends of economic growth, energy consumption, and changes in share of renewable energy, the results show that China, India and Russia will achieve their INDC targets in some scenarios, whereas there will be a shortfall in achieving targets by USA, Japan, Germany, and South Korea. In particular, the carbon reduction situations of Saudi Arabia, Iran and Indonesia are quite severe. Moreover, the results show that there is no common trend that can be used as a suitable benchmark for every country for the implementation of carbon reductions targets of the Paris Agreement and their INDC goals. Finally, there are signs of improvement of the equality of carbon emissions based on the analysis of the Gini coefficient. (C) 2017 Elsevier B.V. All rights reserved.

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