How will the emissions trading scheme save cost for achieving China’s 2020 carbon intensity reduction target?

Industrial sectors account for around 70% of the total energy-related CO 2 emissions in China. It is of great importance to measure the potential for CO 2 emissions reduction and calculate the carbon price in industrial sectors covered in the Emissions Trading Scheme and carbon tax. This paper employs the directional distance function to calculate the marginal abatement costs of CO 2 emissions during 2005-2011 and makes a comparative analysis between our study and the relevant literature. Our empirical results show that the marginal abatement costs vary greatly from industry to industry: high marginal abatement costs occur in industries with low carbon intensity, and vice versa. In the application of the marginal abatement cost, the abatement distribution scheme with minimum cost is established under different abatement targets. The conclusions of abatement distribution scheme indicate that those heavy industries with low MACs and high carbon intensity should take more responsibility for emissions reduction and vice versa. Finally, the policy implications for marginal abatement cost are provided.

Section: Introductionmentioning

confidence: 99%

Marginal Abatement Cost of CO2 in China Based on Directional Distance Function: An Industry Perspective

Xiao

Niu

et al. 2017

“…Therefore, the larger R i is, the smaller k i will be. Thus, we use a natural logarithm form to describe this relationship, which is used in some studies [2,49,50].…”

Section: Inter-industrial Allocation Of China's 2020 Intensity Reductmentioning

confidence: 99%

The Allocation of Carbon Intensity Reduction Target by 2020 among Industrial Sectors in China

Yang

Liu

et al. 2017

Abstract:In order to realize the national carbon intensity reduction target, China has decided to establish a unified national carbon emissions trading market in 2017. At the initial stage, eight industrial sectors will be covered in the carbon market and the other industrial sectors will be included gradually. The aim of this paper is to study the issue of how to allocate the carbon emissions quotas among different industrial sectors fairly and effectively. We try to provide theoretical support for how to determine the coverage scope and access order of the carbon market. In this paper, we construct a comprehensive reduction index based on indicators of equity and efficiency principle. We adopt entropy method to get the objective weights of the three indicators. Then, an allocation model is developed to determine each sector's reduction target for the year of 2020. The result shows that our allocation scheme based on entropy method is more reasonable, and our allocation method will promote the equity of carbon quotas allocation and the efficiency of carbon emissions. With consideration of China's current economic situation and industrial background, we discuss some policy implications regarding the construction of carbon market.

“…During the past few years, some scholars have developed related research on the realization of the carbon intensity target from different angles using various methods [2][3][4][5][6][7][8][9][10][11][12][13][14][15]. These studies show that industry structure adjustment is one of the effective measures for decreasing carbon intensity, which can provide some important references for making out energy conservation and emission reduction policies.…”

Section: Introductionmentioning

confidence: 99%

Estimating the Contribution of Industry Structure Adjustment to the Carbon Intensity Target: A Case of Guangdong

Wang

Zhu

2016

Industry structure adjustment is an effective measure to achieve the carbon intensity target of Guangdong Province. Accurately evaluating the contribution of industry structure adjustment to the carbon intensity target is helpful for the government to implement more flexible and effective policies and measures for CO 2 emissions reduction. In this paper, we attempt to evaluate the contribution of industry structure adjustment to the carbon intensity target. Firstly, we predict the gross domestic product (GDP) with scenario forecasting, industry structure with the Markov chain model, CO 2 emissions with a novel correlation mode based on least squares support vector machine, and then we assess the contribution of industry structure adjustment to the carbon intensity target of Guangdong during the period of 2011-2015 under nine scenarios. The obtained results show, in the ideal scenario, that the economy will grow at a high speed and the industry structure will be significantly adjusted, and thus the carbon intensity in 2015 will decrease by 25.53% compared to that in 2010, which will make a 130.94% contribution to the carbon intensity target. Meanwhile, in the conservative scenario, the economy will grow at a low speed and the industry structure will be slightly adjusted, and thus the carbon intensity in 2015 will decrease by 23.89% compared to that in 2010, which will make a 122.50% contribution to the carbon intensity target.