A general equilibrium analysis on the impacts of regional and sectoral emission allowance allocation at carbon trading market

It is critical to adapt to climate change and reduce the overall carbon emissions. China announced its Nationally Determined Contributions (NDC) at the Paris climate conference in 2015. The carbon cap-and-trade scheme, which plays a key role in carbon emissions abatement, is an effective policy for...

Full description

Bibliographic Details
Main Authors: Bleischwitz, R. (Author), Dai, H. (Author), Geng, Y. (Author), Liu, Z. (Author), Tian, X. (Author), Wu, R. (Author), Yu, Z. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2018
Subjects:
Online Access:View Fulltext in Publisher
Description
Summary:It is critical to adapt to climate change and reduce the overall carbon emissions. China announced its Nationally Determined Contributions (NDC) at the Paris climate conference in 2015. The carbon cap-and-trade scheme, which plays a key role in carbon emissions abatement, is an effective policy for China to achieve its NDC. This study focuses on the allocation of regional and sectoral initial carbon emission allowances in Shanghai. An impact evaluation on the macro-economy, carbon trading markets and participating sectors for the year 2030 was conducted by applying a computable general equilibrium (CGE) model. The results show that the carbon cap-and-trade scheme would cause a 3.4% GDP loss and an 8.9% welfare loss in 2030. The carbon price would be 161.2 USD/t and 147.2 USD/t under the two representative scenarios. The allocation of initial allowances would have a significant impact on both carbon market scale and sectoral trading behaviors. The power generation sector and the petrol oil sector would undertake the greatest output loss, while the metal smelting sector would become the main seller. Furthermore, the initial allowances allocation under a certain abatement target would hardly affect sectoral production but remarkably affect trade behaviors at the carbon trading markets. © 2018 Elsevier Ltd
ISBN:09596526 (ISSN)
DOI:10.1016/j.jclepro.2018.05.006