Analysis and Prediction of the Influencing Factors of China’s Secondary Industry Carbon Emission under the New Normal

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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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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Carbon Dioxide Emissions from Energy Consumption and Projections in Shaanxi Province

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.522-524.176 ◽

2014 ◽

Vol 522-524 ◽

pp. 176-180

Author(s):

Jian Xu ◽

Wei Zhang ◽

Jin Suo Zhang

Keyword(s):

Economic Growth ◽

Energy Consumption ◽

Carbon Dioxide Emissions ◽

Carbon Emission ◽

Carbon Oxide ◽

Industry Structure ◽

Shaanxi Province ◽

Energy Structure ◽

Calculation Methodology ◽

Secondary Industry

Using the calculation methodology based on energy consumption, the amount of carbon emissions due to energy consumption in Shaanxi province were calculated from 2000 to 2010. The decreasing trends in carbon emission were analyzed in terms of energy structure, economic growth and industry structure. The increasing of carbon oxide emission of energy consumption of Shaanxi province was mainly drove by economic increasing. The carbon emission of the Secondary industry is the biggest one in energy consumption which is 60% in the gross carbon emission, then, the Tertiary industry is 20% of the gross carbon emission.

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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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A study on the spatial and temporal evolution of urban shrinkage and its influencing factors from a multidimensional perspective: A case study of resource-based cities in China

PLoS ONE ◽

10.1371/journal.pone.0258524 ◽

2021 ◽

Vol 16 (10) ◽

pp. e0258524

Author(s):

Ruili Wang ◽

Chengxin Wang ◽

Shuai Zhang ◽

Xiaoming Ding

Keyword(s):

Influencing Factors ◽

Entropy Method ◽

Evaluation Index System ◽

Three Dimensions ◽

Shrinking Cities ◽

Industry Output ◽

Evolution Characteristics ◽

Secondary Industry ◽

The Impact

With social and economic environment changes occurring in the world and deepening of the urbanization process, China’s urban development exhibits a new phenomenon of growth and shrinkage fluctuations. The resource-based city shrinkage phenomenon is particularly prominent. Research on the commonalities and patterns of similar groups should be enhanced. We constructed an urban shrinkage evaluation index system from the three dimensions of population, economy and space. Accordingly, we explored the spatiotemporal evolution characteristics of 175 resource-based cities in China from a multidimensional perspective with the entropy method, shrinkage model and transfer matrix method. The results indicated that most resource-based cities in China occurred in the non-shrinking state, but their development speed gradually decreased or even presented stagflation. The shrinkage measure-related results in the different dimensions revealed that the number of shrinking cities is increasing. The population, economic and comprehensive shrinkage levels were mainly slight and remained stable. The number of cities experiencing moderate and severe shrinkage was relatively small and mostly encompassed short-term shrinkage. Spatial shrinkage demonstrated a clear administrative hierarchy difference. Moreover, the spatial distribution range of shrinking cities in each dimension expanded and exhibited obviously similar characteristics, i.e., shrinking cities were relatively concentrated in Northeast China, while they were more scattered in other regions. Furthermore, the geodetector technique was applied to reveal the influencing factors of resource-based city growth and shrinkage. Based on the results, the change in the secondary industry output value share at the start of the study was the primary factor. The impact of each employment structure indicator from 2014 to 2018 was particularly significant. Comprehensive exploration of the shrinkage characteristics of this particular group of cities and their development behavior from a multidimensional perspective can provide an important reference for the transformation and high-quality development of resource-based cities.

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Effects of straw’s comprehensive utilization-technology on agricultural carbon emission in Jiangsu Province

E3S Web of Conferences ◽

10.1051/e3sconf/202126701014 ◽

2021 ◽

Vol 267 ◽

pp. 01014

Author(s):

Xue Qin ◽

Jun Yan ◽

G.Y. Zhu

Keyword(s):

Influencing Factors ◽

Carbon Emissions ◽

Emission Reduction ◽

Carbon Emission ◽

Explanatory Variable ◽

Inhibitory Effect ◽

Jiangsu Province ◽

Stirpat Model ◽

Comprehensive Utilization ◽

The Core

Straw resources are abundant in Jiangsu province, the utilization and burning of straw is an important problem in agriculture carbon emission reduction. In order to analyze the effect of straw’s comprehensive utilization technology on agricultural carbon emission, the STIRPAT model is introduced, which takes straw utilization technology as the core explanatory variable while other influencing factors as control variables, and the ridge regression is adopted to conduct an empirical analysis on the influencing factors of agricultural carbon emission in Jiangsu province from 2008 to 2018. The results demonstrate that for every 1% increasing of straw’s comprehensive utilization technology, agriculture carbon emission will be reduced by 0.17%; the labor force is the biggest driver of agriculture carbon emissions; agriculture economic development, energy consumption takes a certain inhibitory effect on agriculture carbon emissions, but not very great.

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