scholarly journals Carbon emission factor decomposition and carbon peak prediction based on multi-objective decision and information fusion processing

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Chunxue Shi ◽  
Xiwen Feng
Keyword(s):  
Carbon Dioxide ◽  
Decision Making ◽  
Information Fusion ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Emission Factor ◽  
Carbon Emission ◽  
Multi Objective ◽  
Factor Decomposition ◽  
Carbon Peak

AbstractGlobal warming caused by excessive carbon dioxide emissions has seriously threatened the sustainable development of human society. How to reduce carbon dioxide emissions has become a common problem faced by the international community. This article aims to study the decomposition of carbon emission factors and the prediction of carbon peaks from the perspective of multi-objective decision-making and information fusion processing. The sample collection method and statistical analysis method are used to collect samples and simplify the algorithm. A collection experiment of carbon emission factors based on the industry of City A is designed. The experimental data collection takes into account the conversion of coal and oil products into standard coal and carbon dioxide the resulting emissions impact. The experimental results in this paper show that the simulated and real values of my country’s petroleum carbon emissions have both increased from 2000 to 2015, and the decline will be controlled in 2017. Both the simulated value and the real value of my country's coal carbon emissions have been on the rise from 2000 to 2015, and the decline will be controlled in 2017. The carbon emissions of coal are far greater than those of petroleum. The research on carbon emission factor decomposition and carbon peak prediction based on multi-objective decision-making and information fusion processing has been completed well. The research results can be used for industrial carbon emission factor decomposition and carbon peak prediction in other cities across the country.

Research on the Methods of Reducing Carbon Emissions in Airspace Optimization

2013 ◽  
Vol 718-720 ◽  
pp. 858-862
Author(s):  
Dai Wu Zhu ◽  
Zhi Heng Liu ◽  
Shu Yang ◽  
Jian Guo Xu
Keyword(s):  
Carbon Dioxide ◽  
Regression Analysis ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Carbon Emission ◽  
International Community ◽  
Saving Energy ◽  
Function Model ◽  
Specific Data

The international community is increasingly concerned about saving energy and less carbon dioxide emissions. But with growing air passenger and cargo traffic, the airspace tension highlights would inevitably lead to the increase in carbon emissions. However, there is little research on the methods of reducing carbon emission in airspace optimization. So this paper does some research in this field. Firstly this paper provides and exemplifies the method for decreasing the carbon emissions in airspace optimization. Secondly it puts forward the BPR function model to estimating the amount of carbon emissions of the method of increasing the number of air routes and uses the Regression analysis to confirm the parameters αβ. At last utilizing the specific data testifies the huge contribution of reducing the amount of carbon emissions from airspace optimization.

Discussion about Calculation Principle of Carbon Emission in Low-Carbon Architectures

2011 ◽  
Vol 213 ◽  
pp. 302-305
Author(s):  
Xiao Fei Zhu ◽  
Da Wei Lv
Keyword(s):  
Carbon Dioxide ◽  
Energy Efficiency ◽  
Life Cycle ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Carbon Emission ◽  
Building Materials ◽  
Low Carbon ◽  
Equipment Manufacturing ◽  
Reduce Carbon Dioxide

There are more and more low-carbon architectures around us gradually. Low-carbon architectures is to decrease the use of renewable energy, improving energy efficiency, reduce carbon dioxide emissions during materials and equipment manufacturing, construction and the whole life of building use. According to calculating carbon emissions of the building materials in production, construction, using and removal, and the process of calculation, the total sum of carbon emissions in the life cycle was calculated.

scholarly journals Dynamic relationship between urban carbon dioxide emissions and economic growth

2020 ◽  
Keyword(s):  
Economic Growth ◽  
Carbon Dioxide ◽  
Energy Consumption ◽  
Granger Causality ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Carbon Dioxide Emission ◽  
Dynamic Relationship

<p>Urban economic development cannot be separated from energy consumption, and energy consumption directly leads to a large number of carbon emissions. It is of great significance to study the relationship between carbon dioxide emissions and economic growth for the implementation of energy conservation, emission reduction and the development of low-carbon economy in cities. A new method of dynamic relationship between urban carbon dioxide emission and economic growth is put forward. The carbon dioxide emission data in cities are calculated by using urban carbon dioxide emission measurement method. The data of economic attributes are obtained by using classification algorithm under uncertain data flow environment. Based on this data, a decoupling model of carbon emission and economic growth is constructed to measure economic growth elasticity of urban carbon emissions; Granger causality test model is established to analyze the Granger causality between urban carbon dioxide emissions and economic growth. The experimental results show that the growth rate of urban economy is obviously faster than that of carbon emissions. Economic growth is the Granger causality of carbon dioxide emissions. On the contrary, the implementation of carbon emission reduction measures will not hinder economic growth.</p>

scholarly journals A critical review on the environmental impact of manufacturing: a holistic perspective

2021 ◽  
Author(s):  
Vasiliki Christina Panagiotopoulou ◽  
Panagiotis Stavropoulos ◽  
George Chryssolouris
Keyword(s):  
Carbon Dioxide ◽  
Sensitivity Analysis ◽  
Carbon Footprint ◽  
Carbon Emissions ◽  
Emission Factor ◽  
Carbon Emission ◽  
Electrical Energy ◽  
Emission Factors ◽  
System Level ◽  
Greenhouse Gases Emissions

AbstractManufacturing sector is considered to be the second highest contributor in greenhouse gases emissions in EU, secondary to energy sector. The environmental impact of products, processes, and infrastructures of manufacturing is defined as the mass equivalent of carbon dioxide emissions, also known as carbon footprint, because carbon dioxide accounts for the largest portion of greenhouse gases emissions. The aim of this review is to show the impact of manufacturing on carbon emissions and to investigate the importance of carbon emission factors on the carbon footprint of manufacturing. This was performed via (1) mapping and categorizing the sources of carbon emission at process, machine, and system level; (2) identifying the weight factor of carbon emissions factors via sensitivity analysis; and (3) determining which carbon emission factor has the heaviest contribution in carbon footprint calculation. In all examples of the sensitivity analysis, it was shown that carbon emission factor for electrical energy was the only contributing factor at process level while being the strongest at machine level. At system level, the strongest contributor was the carbon emission factor for material production. To reduce the carbon emissions, one must identify the tuneable parameters at process, machine, and system level, from material, machine tool, and energy point of view. However, the highest reduction in carbon footprint can be achieved by reducing the carbon emission factors of electrical energy using renewable power sources such as solar or wind and by reducing the carbon emission factors for material production using recycling materials as “raw” material.

scholarly journals Decomposition Analysis in Electricity Sector Output from Carbon Emissions in China

2018 ◽  
Vol 10 (9) ◽  
pp. 3251 ◽  
Author(s):  
Xue-Ting Jiang ◽  
Min Su ◽  
Rongrong Li
Keyword(s):  
Carbon Dioxide ◽  
Co2 Emissions ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Carbon Emission ◽  
Decomposition Analysis ◽  
Mitigation Strategies ◽  
Electricity Sector ◽  
Emission Mitigation ◽  
Electric Sector

Carbon emissions from China’s electricity sector account for about one-seventh of the global carbon dioxide emissions, or half of China’s carbon dioxide emissions. A better understanding of the relationship between CO2 emissions and electric output would help develop and adjust carbon emission mitigation strategies for China’s electricity sector. Thus, we applied the electricity elasticity of carbon emissions to a decoupling index that we combined with advanced multilevel Logarithmic Mean Divisia Index tools in order to test the carbon emission response to the electric output and the main drivers. Then, we proposed a comparative decoupling stability analysis method. The results show that the electric output effect played the most significant role in increasing CO2 emissions from China’s electric sector. Also, “relative decoupling” was the main state during the study period (1991–2012). Moreover, the electricity elasticity of CO2 emissions had a better performance regarding stability in the analysis of China’s electricity output.

A Study on the Carbon Emissions Calculation Model of Iron and Steel Products Based on EIO-LCA

2015 ◽  
Vol 713-715 ◽  
pp. 2970-2974 ◽  
Author(s):  
Xing Ling Luo ◽  
An Quan Zou ◽  
Chun Guang Quan
Keyword(s):  
Carbon Dioxide ◽  
Life Cycle ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Carbon Emission ◽  
Large Scale ◽  
Ferrous Metal ◽  
Steel Production ◽  
Calculation Model ◽  
Iron And Steel

Carbon emission has become a global focus. The construction of carbon emissions calculation model is helpful for its control. Currently, there is still no uniform method about accounting on the carbon emissions of steel products. The common calculation models are not totally suitable for China. To make up for the shortcomings of them, this paper defines the life cycle system of the iron and steel products based on EIO-LCA, measures the quantity of the direct, indirect carbon emissions and carbon emission deduction in various stages of this life cycle, identifies the hotspot and department which contributes most in carbon emission, and takes Hunan Valin Xiangtan Iron and Steel Co., Ltd (abbreviated Xiang Gang) as an example to validate it. It shows that 2103.87kg of carbon in total would be emitted when one tonne of steel is produced by Xiang Gang. Among the total, the quantity of direct, indirect and deductible carbon emission are 2033.5kg, 216.75kg and 146.38kg respectively, namely carbon emissions of producing per ton of steel is 2.1 tons. Direct carbon emissions from all stages of the life cycle of steel products mainly exist in the stage of steel production and transportation. And ferrous metal smelting and rolling processing industry are the largest emissions industries of the total indirect emissions. Converting by-product gas, heat, and pressure into electrical energy use can reduce carbon dioxide emissions by 146kg, which is the equivalent of reducing carbon dioxide emissions per ton of steel 0.15 tons. Therefore, in order to make the carbon dioxide emissions reach the advanced domestic level of 1.7 tons per ton steel, the iron and steel enterprises can meet emissions reduction targets by strengthening control of carbon emission and improving the efficiency of the utilization of secondary energy from small and large scale.

scholarly journals An Examination of Green Credit Promoting Carbon Dioxide Emissions Reduction: A Provincial Panel Analysis of China

2021 ◽  
Vol 13 (13) ◽  
pp. 7148
Author(s):  
Wenjie Zhang ◽  
Mingyong Hong ◽  
Juan Li ◽  
Fuhong Li
Keyword(s):  
Carbon Dioxide ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Industrial Structure ◽  
Emissions Reduction ◽  
Green Finance ◽  
Carbon Emissions Reduction ◽  
Negative Effect ◽  
Emissions Intensity ◽  
The Impact

The implementation of green finance is a powerful measure to promote global carbon emissions reduction that has been highly valued by academic circles in recent years. However, the role of green credit in carbon emissions reduction in China is still lacking testing. Using a set of panel data including 30 provinces and cities, this study focused on the impact of green credit on carbon dioxide emissions in China from 2006 to 2016. The empirical results indicated that green credit has a significantly negative effect on carbon dioxide emissions intensity. Furthermore, after the mechanism examination, we found that the promotion impacts of green credit on industrial structure upgrading and technological innovation are two effective channels to help reduce carbon dioxide emissions. Heterogeneity analysis found that there are regional differences in the effect of green credit. In the western and northeastern regions, the effect of green credit is invalid. Quantile regression results implied that the greater the carbon emissions intensity, the better the effect of green credit. Finally, a further discussion revealed there exists a nonlinear correlation between green credit and carbon dioxide emissions intensity. These findings suggest that the core measures to promote carbon emission reduction in China are to continue to expand the scale of green credit, increase the technology R&D investment of enterprises, and to vigorously develop the tertiary industry.

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