Issue |
E3S Web Conf.
Volume 118, 2019
2019 4th International Conference on Advances in Energy and Environment Research (ICAEER 2019)
|
|
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Article Number | 04014 | |
Number of page(s) | 7 | |
Section | Environmental Protection, Pollution and Treatment | |
DOI | https://doi.org/10.1051/e3sconf/201911804014 | |
Published online | 04 October 2019 |
Multi-Perspective Influence Mechanism Analysis and Multi-Scenario Prediction of Carbon Emissions——A Case of the Yangtze River Delta, China
1
School of Economics and Management, North China Electric Power University, No.2, Beinong Rd., Huilongguan Town, Changping District, Beijing 102206, China
2
State Grid Corporation of China, State Grid Handan Electric Power Supply Company, No.48, North China Street, Congtai District, Handan City, HeBei Province 056035, China
3
State Grid Corporation of China, State Grid Shanghai Municipal Electric Power Supply Company, No.1122, Yuanshen Rd., Pudong New Area, Shanghai 200120, China
* Corresponding author: Mohan Qiu 15356794885@163.com
Under the mandatory push of meeting carbon emission reduction commitments proposed in the Paris Agreement, the analysis on the peaking time of China’s carbon emissions deserves enough attention. This paper focuses on the peaking times of total carbon emissions (TCE) and carbon emission intensity (CEI) in the Yangtze River Delta (YRD). According to the development of carbon emissions in YRD and related targets in the 13th Five-Year Plan, the peaking times of TCE and CEI in different scenarios are predicted based on the influence mechanism analysis of carbon emissions in YRD from the perspective of energy, economy and society. Considering the development characteristics of China at this stage, this paper introduces several new indicators such as full-time equivalent of research and development (R&D) personnel and investment in environmental pollution control. Based on the study results, several policy recommendations are put forward to fulfil China’s carbon emission reduction commitments.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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