scholarly journals Forecasting CO2 Emissions Using a Novel Conformable Fractional Order Discrete Grey Model

2021 ◽  
Author(s):  
Peng Zhu ◽  
Wanli Xie ◽  
Yunshen Shi ◽  
Mingyong Pang ◽  
Yuhui Shi
Keyword(s):  
Carbon Dioxide ◽  
Fractional Order ◽  
Carbon Dioxide Emissions ◽  
Industrial Development ◽  
Grey Model ◽  
Optimal Order ◽  
Low Carbon ◽  
Grey System ◽  
Industrial Carbon ◽  
Proposed Model

Abstract Accurate and scientific forecasting of carbon dioxide emissions will help make better industrial carbon emission planning so as to promote low-carbon industrial development and achieve sustainable economic growth. For depressing the disturbance of various elements, grey system-based models play an important role in forecasting science. In this paper, we extend the cumulative order from integer order to fractional order based on the discrete gray model, which we call CFDGM (1,1). After introducing the free quantity of the model order, the accuracy of the prevenient grey-based models can be further enhanced. We selected the data for carbon dioxide production by Germany, Japan, and Thailand for modeling. To obtain the optimal order of our grey model, we selected four optimizers to search for the order. The results show that although the search history of the four types of optimizers is different, the search results are the same, which proves that the four types of optimizers are stable and reliable, and the order for which we searched is reliable. By substituting the optimal order into CFDGM (1,1), we obtained the fitting and prediction error of the proposed model. The final results show that a satisfactory fitting effect and forecasting effect is obtained by our proposed model.

scholarly journals Application of a New Information Priority Accumulated Grey Model with Simpson to Forecast Carbon Dioxide Emission

2020 ◽  
pp. 70-83 ◽  
Author(s):  
Xiwang Xiang ◽  
Yubin Cai ◽  
Shuchuan Xie
Keyword(s):  
Carbon Dioxide ◽  
Climate Warming ◽  
Carbon Dioxide Emissions ◽  
Human Life ◽  
Carbon Dioxide Emission ◽  
Grey Model ◽  
New Information ◽  
Proposed Model ◽  
Accurate Forecast ◽  
Work First

Climate warming is a hot topic of common concern all over the world and it has had a significant impact on climate, oceans and human life. The increase in the concentration of carbon dioxide in the atmosphere has become a significant factor in climate warming. In recent years, the concentration of carbon dioxide in the atmosphere has been mostly anthropogenic emissions. Accurate forecasting of carbon dioxide emissions will effectively propose solutions to the problem of global warming and then improve the environment in which we live. In our work, first of all, we use the new information priority accumulation method to optimize the weight of the new information in the prediction. Then we use the numerical integration method to optimize the background value of the grey model to achieve more accurate forecast. Application case results show that our proposed model is superior to other grey models in predicting carbon dioxide emission in India and Bangladesh.

China City Industrial Structure Planning and Industry Trends of Low Carbon Economy

2012 ◽  
Vol 573-574 ◽  
pp. 977-983
Author(s):  
Yu Xing Chen ◽  
Hui Luo
Keyword(s):  
Carbon Dioxide ◽  
Energy Consumption ◽  
Carbon Dioxide Emissions ◽  
Energy Intensity ◽  
Productivity Index ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Industrial Carbon ◽  
Industrial Energy ◽  
Carbon Economy

The article in had the selection based on industrial energy consumption, industrial energy intensity, industrial carbon dioxide emissions, industrial carbon dioxide Emissions intensity and industrial carbon productivity index analysis such as China's industrial economic development three stages of evolution characteristics of low carbon, and according to the 1985 ~ 2007 China work Industry economic data through the regression analysis forecast industry a low carbon economy future development tendency. The analysis results show that, from 1985 to 2007 years although energy consumption Quantity and industrial carbon emissions overall a growing trend, but the industrial strength of energy consumption declined, industrial carbon production ability enhancement, industrial energy intensity reducing to reduce co2 emissions larger contribution, based on this proposed to promote the development of China's industrial low carbon specific Suggestions.

scholarly journals Forecasting China’s per Capita Living Energy Consumption by Employing a Novel DGM (1, 1, tα) Model with Fractional Order Accumulation

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yumu Lu ◽  
Chong Liu ◽  
Haodan Pang ◽  
Ting Feng ◽  
Zijie Dong
Keyword(s):  
Energy Consumption ◽  
Fractional Order ◽  
Prediction Models ◽  
Grey Model ◽  
Grey Prediction ◽  
Grey System ◽  
Annual Increment ◽  
Model Based ◽  
Proposed Model ◽  
Per Capita

The living energy consumption of residents has become an important technical index to promote the economic and social development strategy. The country’s medium- and short-term living energy consumption is featured with both a certainty of annual increment and an uncertainty of random variation. Thus, it can be seen as a typical grey system and shall be suitable for the grey prediction model. In order to explore the future development trend of China’s per capita living energy consumption, this paper establishes a novel grey model based on the discrete grey model with time power term and the fractional accumulation (FDGM (1, 1, tα) for short) for forecasting China’s per capita living energy consumption, which makes the existing model to adapt to different time series by adjusting fractional order accumulation parameter and power term. In order to verify the feasibility and effectiveness of the novel model, the proposed and eight other existing grey prediction models are applied to the case of China’s per capita living energy consumption. The results show that the proposed model is more suitable for predicting China’s per capita energy consumption than the other eight grey prediction models. Finally, the proposed model based on metabolism mechanism is used to predict China’s per capita living energy consumption from 2018 to 2029, which can provide a reference for energy companies or government decision makers.

The Scenario Analysis of Carbon Emissions Based on Improved IPAT Model in China

2012 ◽  
Vol 616-618 ◽  
pp. 1484-1489 ◽  
Author(s):  
Xu Shan ◽  
Hua Wang Shao
Keyword(s):  
Carbon Dioxide ◽  
Economic Development ◽  
Carbon Dioxide Emissions ◽  
Industrial Structure ◽  
Energy Structure ◽  
Low Carbon ◽  
Policy Scenario ◽  
Social And Economic Development ◽  
Energy Environment ◽  
Development Goals

The coordination development of economy-energy-environment was discussed with traditional environmental loads model, combined with "decoupling" theory. Considering the possibilities of social and economic development, this paper set out three scenarios, and analyzed quantitatively the indexes, which affected carbon dioxide emissions, including population, per capita GDP, industrial structure and energy structure. Based on this, it forecasted carbon dioxide emissions in China in future. By comparing the prediction results, it held that policy scenario was the more realistic scenario, what’s more it can achieve emission reduction targets with the premise of meeting the social and economic development goals. At last, it put forward suggestions to implement successfully policy scenario, from energy structure, industrial structure, low-carbon technology and so on.

scholarly journals Life Cycle Energy Consumption and Carbon Dioxide Emissions of Agricultural Residue Feedstock for Bioenergy

2021 ◽  
Vol 11 (5) ◽  
pp. 2009
Author(s):  
Valerii Havrysh ◽  
Antonina Kalinichenko ◽  
Anna Brzozowska ◽  
Jan Stebila
Keyword(s):  
Carbon Dioxide ◽  
Power Generation ◽  
Life Cycle ◽  
Carbon Dioxide Emissions ◽  
Crop Production ◽  
Agricultural Residues ◽  
Environmental Indicators ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Energy Inputs

The depletion of fossil fuels and climate change concerns are drivers for the development and expansion of bioenergy. Promoting biomass is vital to move civilization toward a low-carbon economy. To meet European Union targets, it is required to increase the use of agricultural residues (including straw) for power generation. Using agricultural residues without accounting for their energy consumed and carbon dioxide emissions distorts the energy and environmental balance, and their analysis is the purpose of this study. In this paper, a life cycle analysis method is applied. The allocation of carbon dioxide emissions and energy inputs in the crop production by allocating between a product (grain) and a byproduct (straw) is modeled. Selected crop yield and the residue-to-crop ratio impact on the above indicators are investigated. We reveal that straw formation can consume between 30% and 70% of the total energy inputs and, therefore, emits relative carbon dioxide emissions. For cereal crops, this energy can be up to 40% of the lower heating value of straw. Energy and environmental indicators of a straw return-to-field technology and straw power generation systems are examined.

scholarly journals DEPENDENCE OF THE COST OF ELECTRICITY ON THE VOLUME OF GREENHOUSE GAS EMISSIONS

2022 ◽  
Vol 1 (15) ◽  
pp. 71-75
Author(s):  
Dmitriy Kononov
Keyword(s):  
Carbon Dioxide ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Energy Security ◽  
Carbon Dioxide Emissions ◽  
Power Plants ◽  
Low Carbon ◽  
Electricity Prices ◽  
Low Carbon Development ◽  
The Cost

The strategy of low-carbon development of the economy and energy of Russia provides for the introduction of a fee (tax) for carbon dioxide emissions by power plants. This will seriously affect their prospective structure and lead to an increase in electricity prices. The expected neg-ative consequences for national and energy security are great. But serious and multilateral research is needed to properly assess these strategic threats

scholarly journals Modeling the Multicommodity Multimodal Routing Problem with Schedule-Based Services and Carbon Dioxide Emission Costs

2015 ◽  
Vol 2015 ◽  
pp. 1-21 ◽  
Author(s):  
Yan Sun ◽  
Maoxiang Lang
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Transportation Network ◽  
Linearization Method ◽  
Mixed Integer ◽  
Multicommodity Flow ◽  
Routing Problem ◽  
Multimodal Transportation ◽  
Proposed Model ◽  
Freight Routing

We explore a freight routing problem wherein the aim is to assign optimal routes to move commodities through a multimodal transportation network. This problem belongs to the operational level of service network planning. The following formulation characteristics will be comprehensively considered: (1) multicommodity flow routing; (2) a capacitated multimodal transportation network with schedule-based rail services and time-flexible road services; (3) carbon dioxide emissions consideration; and (4) a generalized costs optimum oriented to customer demands. The specific planning of freight routing is thus defined as a capacitated time-sensitive multicommodity multimodal generalized shortest path problem. To solve this problem systematically, we first establish a node-arc-based mixed integer nonlinear programming model that combines the above formulation characteristics in a comprehensive manner. Then, we develop a linearization method to transform the proposed model into a linear one. Finally, a computational experiment from the Chinese inland container export business is presented to demonstrate the feasibility of the model and linearization method. The computational results indicate that implementing the proposed model and linearization method in the mathematical programming software Lingo can effectively solve the large-scale practical multicommodity multimodal transportation routing problem.

scholarly journals Location Optimization of Multidistribution Centers Based on Low-Carbon Constraints

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Peixin Zhao ◽  
Bo Liu ◽  
Lulu Xu ◽  
Di Wan
Keyword(s):  
Carbon Dioxide ◽  
Carbon Footprint ◽  
Carbon Dioxide Emission ◽  
Decision Makers ◽  
Low Carbon ◽  
Distribution Centers ◽  
Numerical Examples ◽  
Industrial Carbon ◽  
Location Optimization ◽  
Decision Making Factors

Location optimization of distribution centers is a systematic and important task in logistics operations. Recently, reducing carbon footprint is becoming one of the decision-making factors in selecting the locations for distribution centers. This paper analyzes the necessity of industrial carbon dioxide emission cost internalization in four aspects and builds a model for multidistribution centers location in effort of reducing carbon footprint that can provide optimized strategy support for decision makers and logistic operators. Numerical examples are presented to illustrate the feasibility and effectiveness of the models.

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