Study on the Changes and Influencing Factors of Industrial Carbon Emission in Beijing-Tianjin-Hebei Region

Though the development of China’s civil aviation and the improvement of control ability have strengthened the safety operation and support ability effectively, the airlines are under the pressure of operation costs due to the increase of aircraft fuel price. With the development of optimization controlling methods in flight management systems, it becomes increasingly challenging to cut down flight fuel consumption by control the flight status of the aircraft. Therefore, the airlines both at home and abroad mainly rely on the accurate estimation of aircraft fuel to reduce fuel consumption, and further reduce its carbon emission. The airlines have to take various potential factors into consideration and load more fuel to cope with possible negative situation during the flight. Therefore, the fuel for emergency use is called PBCF (Performance-Based Contingency Fuel). The existing PBCF forecasting method used by China Airlines is not accurate, which fails to take into account various influencing factors. This paper aims to find a method that could predict PBCF more accurately than the existing methods for China Airlines.This paper takes China Eastern Airlines as an example. The experimental data of flight fuel of China Eastern Airlines Co, Ltd. were collected to find out the relevant parameters affecting the fuel consumption, which is followed by the establishment of the LSTM neural network through the parameters and collected data. Finally, through the established neural network model, the PBCF addition required by the airline with different influencing factors is output. It can be seen from the results that the all the four models are available for the accurate prediction of fuel consumption. The amount of data of A319 is much larger than that of A320 and A330, which leads to higher accuracy of the model trained by A319. The study contributes to the calculation methods in the fuel-saving project, and helps the practitioners to learn about a particular fuel calculation method. The study brought insights for practitioners to achieve the goal of low carbon emission and further contributed to their progress towards circular economy.

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Difference in the drivers of industrial carbon emission costs determines the diverse policies in middle-income regions: A case of northwestern China

Renewable and Sustainable Energy Reviews ◽

10.1016/j.rser.2021.111942 ◽

2022 ◽

Vol 155 ◽

pp. 111942

Author(s):

Yi Yang ◽

Zhuqing Yuan ◽

Shengnan Yang

Keyword(s):

Carbon Emission ◽

Northwestern China ◽

Middle Income ◽

Industrial Carbon

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Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015

Energies ◽

10.3390/en12163081 ◽

2019 ◽

Vol 12 (16) ◽

pp. 3081 ◽

Cited By ~ 5

Author(s):

Zeng ◽

Lu ◽

Liu ◽

Zhou ◽

Hu

Keyword(s):

Influencing Factors ◽

Regional Differences ◽

Carbon Emission ◽

Industrial Structure ◽

Tobit Model ◽

Policy Implications ◽

Dea Model ◽

Emission Efficiency ◽

Unit Root Testing ◽

Technology Level

With the challenge to reach targets of carbon emission reduction at the regional level, it is necessary to analyze the regional differences and influencing factors on China’s carbon emission efficiency. Based on statistics from 2005 to 2015, carbon emission efficiency and the differences in 30 provinces of China were rated by the Modified Undesirable Epsilon-based measure (EBM) Data Envelopment Analysis (DEA) Model. Additionally, we further analyzed the influencing factors of carbon emission efficiency’s differences in the Tobit model. We found that the overall carbon emission efficiency was relatively low in China. The level of carbon emission efficiency is the highest in the East region, followed by the Central and West regions. As for the influencing factors, industrial structure, external development, and science and technology level had a significant positive relationship with carbon emission efficiency, whereas government intervention and energy intensity demonstrated a negative correlation with carbon emission efficiency. The contributions of this paper include two aspects. First, we used the Modified Undesirable EBM DEA Model, which is more accurate than traditional methods. Secondly, based on the data’s unit root testing and cointegration, the paper verified the influencing factors of carbon emission efficiency by the Tobit model, which avoids the spurious regression. Based on the results, we also provide several policy implications for policymakers to improve carbon emission efficiency in different regions.

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Characteristics and influencing factors of carbon emission from typical community household consumption: a case of Beijing

Acta Ecologica Sinica ◽

10.5846/stxb201904150750 ◽

2019 ◽

Vol 39 (21) ◽

Author(s):

王悦 WANG Yue ◽

李锋 LI Feng ◽

陈新闯 CHEN Xinchuang ◽

胡印红 HU Yinhong ◽

胡盼盼 HU Panpan ◽

...

Keyword(s):

Influencing Factors ◽

Carbon Emission ◽

Household Consumption

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