scholarly journals The Scale, Structure and Influencing Factors of Total Carbon Emissions from Households in 30 Provinces of China—Based on the Extended STIRPAT Model

Energies ◽  
2018 ◽  
Vol 11 (5) ◽  
pp. 1125 ◽  
Author(s):  
Yong Wang ◽  
Guangchun Yang ◽  
Ying Dong ◽  
Yu Cheng ◽  
Peipei Shang
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Scale Structure ◽  
Total Carbon ◽  
Stirpat Model

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

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.

scholarly journals Analysis of Influencing Factors of Carbon Emissions in China’s Logistics Industry: A GDIM-Based Indicator Decomposition

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5742
Author(s):  
Changyou Zhang ◽  
Wenyu Zhang ◽  
Weina Luo ◽  
Xue Gao ◽  
Bingchen Zhang
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Added Value ◽  
Total Carbon ◽  
Carbon Intensity ◽  
Contribution Ratio ◽  
Logistics Industry ◽  
Per Capita ◽  
First Time

Due to increased global carbon dioxide emissions, the greenhouse effect is being aggravated, which has attracted wide attention. China is committed to promoting the low-carbon development of all industries. This paper analyzed the influencing factors of carbon emissions in the Chinese logistics industry, so as to identify the key factors that influence carbon emissions. Based on the carbon emission data of China’s logistics industry in 2000–2019, this paper applied the carbon emission coefficients issued by the Intergovernmental Panel on Climate Change. For the first time, the Generalized Divisia Index Method was used to analyze the degree of influence of the factors on carbon emissions. This method considered more variables and their relationships. The results showed that (1) the carbon emissions of the logistics industry were increased by 3.22 times from 2000 to 2018, and showed negative growth for the first time in 2019; (2) the added value of the logistics industry is the most important factor in increasing carbon emissions (with a contribution ratio of 65.45%), energy consumption and practical population size are the main factors in carbon emissions. The promotion of this industry is subjected to decreased per capita carbon emissions, which have a large impact on total carbon emissions; (3) the intensity of carbon output is the most important factor in the reduction of carbon emissions (with a contribution ratio of −29.1%), where the energy carbon intensity and per capita added value are the main influencing factors with regard to the reduction of carbon emissions, while energy intensity has a negative inhibitory effect on carbon emissions, and (4) the influencing factors have negative effects on the cumulative inhibition of carbon emissions in the logistics industry, to an extent that is far less than the integral promotion of carbon emissions. Finally, according to the research conclusions of this paper, it is feasible to make recommendations for the carbon reduction of the logistics industry.

scholarly journals Carbon Emission Estimation of Assembled Composite Concrete Beams during Construction

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1810
Author(s):  
Kaitong Xu ◽  
Haibo Kang ◽  
Wei Wang ◽  
Ping Jiang ◽  
Na Li
Keyword(s):  
Life Cycle ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Composite Beams ◽  
Total Carbon ◽  
Construction Process ◽  
Low Carbon ◽  
Carbon Emission Reduction ◽  
The Government

At present, the issue of carbon emissions from buildings has become a hot topic, and carbon emission reduction is also becoming a political and economic contest for countries. As a result, the government and researchers have gradually begun to attach great importance to the industrialization of low-carbon and energy-saving buildings. The rise of prefabricated buildings has promoted a major transformation of the construction methods in the construction industry, which is conducive to reducing the consumption of resources and energy, and of great significance in promoting the low-carbon emission reduction of industrial buildings. This article mainly studies the calculation model for carbon emissions of the three-stage life cycle of component production, logistics transportation, and on-site installation in the whole construction process of composite beams for prefabricated buildings. The construction of CG-2 composite beams in Fujian province, China, was taken as the example. Based on the life cycle assessment method, carbon emissions from the actual construction process of composite beams were evaluated, and that generated by the composite beam components during the transportation stage by using diesel, gasoline, and electric energy consumption methods were compared in detail. The results show that (1) the carbon emissions generated by composite beams during the production stage were relatively high, accounting for 80.8% of the total carbon emissions, while during the transport stage and installation stage, they only accounted for 7.6% and 11.6%, respectively; and (2) during the transportation stage with three different energy-consuming trucks, the carbon emissions from diesel fuel trucks were higher, reaching 186.05 kg, followed by gasoline trucks, which generated about 115.68 kg; electric trucks produced the lowest, only 12.24 kg.

scholarly journals Examining the Driving Factors of the Direct Carbon Emissions of Households in the Ebinur Lake Basin Using the Extended STIRPAT Model

2021 ◽  
Vol 13 (3) ◽  
pp. 1339
Author(s):  
Ziyuan Chai ◽  
Zibibula Simayi ◽  
Zhihan Yang ◽  
Shengtian Yang
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Driving Factors ◽  
Series Data ◽  
Lake Basin ◽  
Stirpat Model ◽  
Consumption Structure ◽  
Ebinur Lake ◽  
Ebinur Lake Basin

In order to achieve the carbon emission reduction targets in Xinjiang, it has become a necessary condition to study the carbon emission of households in small and medium-sized cities in Xinjiang. This paper studies the direct carbon emissions of households (DCEH) in the Ebinur Lake Basin, and based on the extended STIRPAT model, using the 1987–2017 annual time series data of the Ebinur Lake Basin in Xinjiang to analyze the driving factors. The results indicate that DCEH in the Ebinur Lake Basin during the 31 years from 1987 to 2017 has generally increased and the energy structure of DCEH has undergone tremendous changes. The proportion of coal continues to decline, while the proportion of natural gas, gasoline and diesel is growing rapidly. The main positive driving factors affecting its carbon emissions are urbanization, vehicle ownership and GDP per capita, while the secondary driving factor is residents’ year-end savings. Population, carbon intensity and energy consumption structure have negative effects on carbon emissions, of which energy consumption structure is the main factor. In addition, there is an environmental Kuznets curve between DCEH and economic development, but it has not yet reached the inflection point.

scholarly journals Analysis of China’s Manufacturing Industry Carbon Lock-In and Its Influencing Factors

2020 ◽  
Vol 12 (4) ◽  
pp. 1502 ◽  
Author(s):  
Xia Wang ◽  
Lijun Zhang ◽  
Yaochen Qin ◽  
Jingfei Zhang
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Manufacturing Industry ◽  
Ferrous Metal ◽  
Bohai Bay ◽  
High Carbon ◽  
Intergovernmental Panel ◽  
Resource Endowment ◽  
Regional Factors ◽  
Lock In

There are industry lock-in and regional lock-in phenomena in China’s manufacturing industry carbon emissions. However, the existing researches often focus on global carbon emissions, which is not adverse to finding the main problems of manufacturing industry carbon emissions. The biggest contributions of this study are the identification of the industry lock-in and regional lock-in of China’s manufacturing industry and the finding of the regional factors that affect the carbon lock-in of the manufacturing industry, which points out the direction for the low-carbon transformation of the local manufacturing industry. This paper is based on the IPCC (Intergovernmental Panel on Climate Change) carbon emissions coefficient method and energy consumption data from 2000 to 2016 to count the manufacturing industry carbon emissions of 30 provinces in China (except Hong Kong, Macao, Taiwan and Tibet). On this basis, the paper uses a spatial–temporal geographical weighted regression (GTWR) model to analysis the regional influencing factors of the high-carbon manufacturing industry. Results demonstrate that China’s high-carbon manufacturing industry mainly concentrates on the ferrous metal processing industry, non-metallic mineral manufacturing industry and other sectors. In addition, the carbon emissions of high-carbon manufacturing industries are mainly concentrated in Bohai Bay and the North China Plain. The industrial structure and economic scale are the main reasons for the regional carbon lock-in of the high-carbon manufacturing industry, and the strength of the lock-in has continued to increase. Resource endowment is a stable factor of carbon lock-in in high-carbon regions. Technological progress helps to unlock carbon, while foreign direct investment results in the enhancement of carbon regional lock-in. This study focuses on the regional factors of carbon lock-in in the manufacturing industry, hoping to provide decision support for the green development of China’s manufacturing industry.

Multi-Objective Fleet Assignment Problem Based on Self-Adaptive Genetic Algorithm

2013 ◽  
Vol 694-697 ◽  
pp. 2895-2900 ◽  
Author(s):  
Xiao Yang ◽  
Bo Jiang
Keyword(s):  
Genetic Algorithm ◽  
Carbon Emissions ◽  
Assignment Problem ◽  
Network Capacity ◽  
Total Carbon ◽  
Adaptive Genetic Algorithm ◽  
Multi Objective ◽  
Route Network ◽  
Assignment Model ◽  
Key Factor

Since the beginning of the twenty-first century, energy conservation has become the theme of the development of the world. China government set the emissions-reduction targets in various industries on the 12th Five-Year Plan. And the airlines were committed to reduce their carbon emissions. From an operational perspective, the airline model assignment problem is a key factor of the total carbon emissions on the entire route network. But the traditional aircraft assignment models approach did not account for this purpose to reduce carbon emissions. By constructing the multi-objective optimization models consider carbon emissions assignment model using a genetic algorithm, numerical example shows that the model is able to meet all aspects demand which include meeting route network capacity demand, minimizing operating costs and reducing total aircraft fleet carbon emissions.

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