Carbon tax, emission trading, or the mixed policy: which is the most effective strategy for climate change mitigation in China?

Wei Li () and Zhijie Jia
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Wei Li: North China Electric Power University

Mitigation and Adaptation Strategies for Global Change, 2017, vol. 22, issue 6, No 7, 973-992

Abstract: Abstract China, as the world’s largest emitter, intends to achieve the peaking of carbon dioxide (CO2) emissions around 2030 and to make best efforts to peak early to mitigate global change. Under this strategy, a dynamic, recursive computable general equilibrium (CGE) model is used to analyze the economy, energy, and environment impact of CO2 emission reduction policy based on 17 scenarios in China: carbon tax, emission trading scheme (ETS), and the mixed policy in different price level, in order to find out which kind of emission reduction strategy is more feasible. The results show that CO2 emission in 2030 will be reduced with the implementation of tax, ETS and mixed policy, by 10–13 %, 12–14 %, and 18–28 %, respectively. From 2016 to 2030, China can reduce 18,338–24,156 Mt CO2 through the implementation of mixed policy. Furthermore, relative to single policy, mixed policy has stronger effects on primary energy consumption cut, by 738–1124 Mtoe or 18–28 %, which will make CO2 emissions reach a peak before 2030 and the peak emission is not greater than 12 billion tons which is in line with the reduction demand in China. Thus, the mixed policy is the most effective strategy so that mixed policy is recommended to parties included in Annex I in United Nations Framework Convention on Climate Change Kyoto Protocol and other countries with large potential of emission reduction, while ETS is suggested to countries with low carbon emissions per capita which can balance economic development and CO2 mitigation.

Keywords: Carbon tax; Climate change; Computable general equilibrium (CGE) model; Emission trading scheme (ETS); Energy consumption; Mitigation strategy; Mixed policy (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (32)

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DOI: 10.1007/s11027-016-9710-3

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