scholarly journals Use of BP Neural Networks to Determine China’s Regional CO2 Emission Quota

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yawei Qi ◽  
Wenxiang Peng ◽  
Ran Yan ◽  
Guangping Rao

China declared a long-term commitment at the United Nations General Assembly (UNGA) in 2020 to reduce CO2 emissions. This announcement has been described by Reuters as “the most important climate change commitment in years.” The allocation of China’s provincial CO2 emission quotas (hereafter referred to as quotas) is crucial for building a unified national carbon market, which is an important policy tool necessary to achieve carbon emissions reduction. In the present research, we used historical quota data of China’s carbon emission trading policy pilot areas from 2014 to 2017 to identify alternative features of corporate CO2 emissions and build a backpropagation neural network model (BP) to train the benchmark model. Later, we used the model to calculate the quotas for other regions, provided they implement the carbon emission trading policy. Finally, we added up the quotas to obtain the total national quota. Additionally, considering the perspective of carbon emission terminal, a new characteristic system of quota allocation was proposed in order to retrain BP including the following three aspects: enterprise production, household consumption, and regional environment. The results of the benchmark model and the new models were compared. This feature system not only builds a reasonable quota-related indicator framework but also perfectly matches China’s existing “bottom-up” total control quota approach. Compared with the previous literature, the present report proposes a quota allocation feature system closer to China’s policy and trains BP to obtain reasonable feature weights. The model is very important for the establishment of a unified national carbon emission trading market and the determination of regional quotas in China.

2021 ◽  
Vol 13 (10) ◽  
pp. 5664
Author(s):  
Qiong Wu ◽  
Kanittha Tambunlertchai ◽  
Pongsa Pornchaiwiseskul

As China has an important role in global climate change, the Chinese government has set goals to improve its environmental efficiency and performance and launched carbon emission trading pilot markets in 2013, aiming to reduce CO2 emissions. Based on panel data of 30 provinces from 2005 to 2017, this paper uses the difference-in-difference method to study the impact of China’s carbon emission trading pilot markets on carbon emissions and regional green development. The paper also explores possible influencing channels. The main conclusions are as follows: (1) China’s carbon emission trading policy has promoted a reduction in CO2 emissions and carbon emission intensity and has increased green development in the pilot areas. (2) The main path for China’s carbon emission trading policy to achieve carbon emission reduction and regional green development is to promote technology adoption. (3) China’s carbon emission trading policy achieves green development through synergistic SO2 emission reduction. The pilot carbon markets have reduced both the amount of SO2 emissions and SO2 emission intensity.


Author(s):  
Qiong Wu ◽  
Kanittha Tambunlertchai ◽  
Pongsa Pornchaiwiseskul

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


2021 ◽  
Vol 9 ◽  
Author(s):  
Lei Chen ◽  
Yining Liu ◽  
Yue Gao ◽  
Jingjing Wang

Improving carbon emission efficiency is an important means to achieve pollution reduction and sustainable economic development. Rather than focusing on the implementation of market-incentive environmental policies in developed countries, we study the effect of the implementation of market-incentive environmental policies on the efficiency of carbon emissions in developing countries, which is generally ignored by frontiers researches. Based on panel data of 282 cities at prefecture-level and above in China from 2007 to 2017, we first adopt the non-radial distance function (NDDF) and global DEA model to measure the carbon emission efficiency of China’s cities. Then we take the Chinese carbon emission trading pilot as a quasi-natural experiment and explore the impact of carbon emission trading policy on carbon emission efficiency based on DID method. And the mechanisms are analyzed through the mediation effect model. It is found that the carbon emission rights trading policy can significantly improve the carbon emission efficiency of the pilot cities, and it mainly plays a role through three channels: technological progress effect, green innovation effect and energy consumption structure optimization effect. The heterogeneity test results show that for resource-based cities and cities with a higher degree of marketization, the carbon emission trading policy has a more obvious effect on improving carbon emission efficiency.


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