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Achieving China's energy and climate policy targets in 2030 under multiple uncertainties

Duan, Hongbo, Mo, Jianlei, Fan, Ying and Wang, Shouyang (2018) Achieving China's energy and climate policy targets in 2030 under multiple uncertainties. Energy Economics, 70. pp. 45-60. ISSN 0140-9883

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Identification Number: 10.1016/j.eneco.2017.12.022

Abstract

The stringency of China's energy and climate targets in 2030 and the policy needed to realize these targets are full of controversy, mainly as a result of multiple future uncertainties. This study has developed a stochastic energy-economy-environment integrated model, to assess China's energy and climate targets in 2030, with a particular focus on the carbon intensity reduction, carbon emission peaking, and non-fossil energy development. The probabilities of realizing the targets are obtained, and the nexus among different targets is explored. It's argued that carbon emission management and policy-making should be implemented from the perspective of risk management, and policy makers can take corresponding policy measures based on the degree of confidence required under multiple future uncertainties. It is found that the probabilities of realizing carbon emission-peaking target and non-fossil energy target are low, with the business-as-usual efforts, and additional policies may still be needed. More specific, carbon pricing plays a major role in curbing and peaking carbon emissions, while the policy mix of carbon pricing and non-fossil energy subsidies can peak the carbon emission with relatively low cost compared to the single carbon pricing policy. It is also found that the carbon intensity reduction target is most likely to be attained, followed by the carbon-peaking target, and then the non-fossil energy target, given the same policy efforts. This indicates that, China may not deliberately increase carbon emissions rapidly over the next decade to make the carbon emission peak as high as possible; otherwise, it may be difficult to achieve the non-fossil energy target.

Item Type: Article
Official URL: https://www.sciencedirect.com/science/journal/0140...
Additional Information: © 2017 Elsevier
Divisions: Grantham Research Institute
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
G Geography. Anthropology. Recreation > GF Human ecology. Anthropogeography
H Social Sciences > HC Economic History and Conditions
JEL classification: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods and Programming > C63 - Computational Techniques
O - Economic Development, Technological Change, and Growth > O1 - Economic Development > O13 - Agriculture; Natural Resources; Energy; Environment; Other Primary Products
O - Economic Development, Technological Change, and Growth > O3 - Technological Change; Research and Development > O33 - Technological Change: Choices and Consequences; Diffusion Processes
O - Economic Development, Technological Change, and Growth > O4 - Economic Growth and Aggregate Productivity > O41 - One, Two, and Multisector Growth Models
Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics > Q4 - Energy > Q43 - Energy and the Macroeconomy
Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics > Q5 - Environmental Economics > Q54 - Climate; Natural Disasters
Date Deposited: 18 Jan 2018 11:24
Last Modified: 19 Mar 2024 19:39
Projects: 71774153, 71503242, 71403263, 71690245, 201604910047
Funders: National Natural Science Foundation of China, China Scholarship Council
URI: http://eprints.lse.ac.uk/id/eprint/86481

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