A Stochastic Bilevel Decision-Making Model of Optimal Production Planning with Carbon Emission Trading

2014 ◽  
Author(s):  
Zhimiao Tao ◽  
Chunmei Chen ◽  
Haijun Xu
Keyword(s):  
Decision Making ◽  
Production Planning ◽  
Carbon Emission ◽  
Emission Trading ◽  
Optimal Production ◽  
Carbon Emission Trading ◽  
Decision Making Model

scholarly journals The Stimulation and Coordination Mechanisms of the Carbon Emission Trading Market of Public Buildings in China

2021 ◽  
Vol 9 ◽  
Author(s):  
Lingyan Li ◽  
Mimi Duan ◽  
Xiaotong Guo ◽  
Yao Wang
Keyword(s):  
Decision Making ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Emission Trading ◽  
Public Buildings ◽  
Public Building ◽  
Trading Mechanism ◽  
Carbon Emission Trading ◽  
Decision Making Behavior ◽  
The Impact

The most important issue related to the establishment of carbon emission trading in China is how to motivate the owners of public buildings to participate. However, Existing research few considered the characteristics of public building owners and the influence of various uncertain factors in carbon emission trading investments. To fill this gap, this study constructs a carbon emission trading investment decision model of public building owners to study the mechanism that encourages them to participate, incorporating these characteristics and uncertain factors. The findings are as follows. First, carbon price is important in adjusting the emission reductions of different owners to minimize the total social cost of emission-reduction measures. Second, the price of carbon-emission permits has a significant impact on the investment threshold and decision-making behavior of public building owners. Finally, reducing the cost of energy-conservation and emission-reduction technologies in public buildings and appropriately subsidizing owners for their emission-reduction investment were effective methods to motivate them to participate in carbon emission trading. The results were used to quantitatively analyze the impact of a carbon emission trading mechanism on the decision-making behavior of public building owners and to construct the carbon emission trading mechanism used in China’s public building industry.

Examining the Impact and Influencing Channels of Emission Trading Pilot Markets in China

2020 ◽  
Vol 11 (1) ◽  
pp. 136-136
Author(s):  
Qiong Wu ◽  
Kanittha Tambunlertchai ◽  
Pongsa Pornchaiwiseskul
Keyword(s):  
Total Factor Productivity ◽  
Co2 Emission ◽  
Carbon Emission ◽  
Emission Trading ◽  
Chinese Government ◽  
Synergy Effect ◽  
Factor Productivity ◽  
Plan Period ◽  
Carbon Emission Trading ◽  
The Impact

The global warming has become a serious issue in the world since the 1980s. The targets for the first commitment period of the Kyoto Protocol cover emissions of the six main greenhouse gasses (GHGs). China is the world's largest CO2 emitter and coal consumer and was responsible for 27.3 percent of the global total CO2 emission and 50.6 percent of the global total coal consumption in 2016 (BP, 2017). As China plays an important role in the global climate change, China has set goals to improve its environmental efficiency and performance. In 2011, the Chinese government for the first time announced an intent to establish carbon emission trading market in China. Eight regional emission trading schemes have been operating since 2013 (seven pilot markets during the 12th Five Year Plan period and one pilot market during the 13th Five Year Plan period) including provinces of Guangdong, Hubei, and Fujian, and cities of Beijing, Tianjin, Shanghai, Shenzhen, and Chongqing. The goal of these regional emission trading pilot markets is to help the government establish an efficient carbon emission trading scheme at national level. Some researchers have been focused on examining the impact of emission trading schemes in China using CGE model by constructing different scenarios and ex-ante analysis using data prior to emission trading pilot markets implementation. While this paper tries to conduct an ex-post analysis with data of 2005-2017 to evaluate the impact of emission trading pilot markets in China at provincial level using difference-in-difference (DID) model. By including both CO2 and SO2 as undesirable outputs to calculate Malmquist-Luenberger (ML) Index to measure green total factor productivity, this paper plans to evaluate the impact of carbon emission trading pilot markets in China via emission reduction, regional green development, synergy effect and influencing channels. This paper tries to answer the following research questions: (1) Do emission trading pilot markets reduce CO2 emission and increase regional green total factor productivity? (2) Is there any synergy effect from emission trading pilot markets? (3) What are the influencing channels of emission trading pilot markets? Keywords: Emission trading, CO2 emissions, Different-in-difference

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