Eco-Cement with Low Carbon Dioxide Emission and Less Operation Energy

2017 ◽  
Author(s):  
Adel Abd Elrazek
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emission ◽  
Low Carbon

Research of Graphic User Interface of Carbon Dioxide Emission Evaluation Model in Construction Life Cycle Based on Matlab

2013 ◽  
Vol 689 ◽  
pp. 546-550
Author(s):  
Xue Hong Gan ◽  
Wei Wang ◽  
Shi Mei Liu
Keyword(s):  
Carbon Dioxide ◽  
Life Cycle ◽  
Evaluation Model ◽  
Carbon Dioxide Emission ◽  
Graphic User Interface ◽  
Property Management ◽  
Low Carbon ◽  
Management Responsibility ◽  
Residential Quarter ◽  
First Time

To build carbon dioxide emission evaluation model in construction life cycle is the key link to make low-carbon research of theoretical studies head towards practical application. For the first time, residential quarter is selected as the object in the study, carbon dioxide emission management responsibility of owner and property being considered and carbon dioxide emission evaluation model in construction life cycle based on matlab as well as database of carbon dioxide factor being built initially. Net carbon dioxide emission information will be shown timely, then carbon dioxide emission and absorption can be adjusted by property management accordingly.

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.

Measures to Reduce Carbon Dioxide Emission of China Cement Industry

2011 ◽  
Vol 233-235 ◽  
pp. 412-415 ◽  
Author(s):  
Li Xia Hao ◽  
Feng Qing Zhao ◽  
Peng Xiang Zhao
Keyword(s):  
Carbon Dioxide ◽  
Raw Materials ◽  
Carbon Dioxide Emission ◽  
Cement Industry ◽  
Oxide Content ◽  
Low Carbon ◽  
Dry Process ◽  
Implementation Approach ◽  
Concentration Degree ◽  
Reduce Carbon Dioxide

Cement industry bear the brunt in the tide of resisting global warming because of large carbon dioxide emission. Five low-carbon measures and implementation approach to Chinese cement industry was put forward: Increasing industrial concentration degree and developing new dry process cement; Processing waste in cement kilns and reducing the use of raw materials and fuels; Increasing the amount of admixture in cement; Producing cement from calcium oxide content solid waste; Taking energy-saving measures such as cogeneration and grinding technology.

Calculation of Carbon Dioxide Emission in Nanjing City and its Influencing Factors

2014 ◽  
Vol 665 ◽  
pp. 517-520
Author(s):  
Qiang Zhao ◽  
Xiu Mei Li ◽  
Xiang Yu Cui
Keyword(s):  
Carbon Dioxide ◽  
Energy Consumption ◽  
Influencing Factors ◽  
Carbon Dioxide Emissions ◽  
Carbon Dioxide Emission ◽  
Clean Energy ◽  
Energy Structure ◽  
Low Carbon ◽  
Index Decomposition ◽  
Laspeyres Index

The research estimates the carbon dioxide emissions of energy consumption from 2003 to 2011 using the method in IPCC national greenhouse gases listing guidance, by adopting the method of Kaya identities and Laspeyres index decomposition technique to analyze the influencing factors and the influencing degree. The result shows that the main factors influencing carbon dioxide emissions are energy structure and per capita GDP, and to develop clean energy, to improve energy structure are important choice to reduce the carbon dioxide emissions of energy consumption, realize low carbon in the future. This research provides an important reference to protect the environment and to promote the sustainable development of economy.

scholarly journals Innovation of Talent Training Mode for Undergraduates Majored in Energy Under the “Carbon Neutralization” Target

2021 ◽  
Author(s):  
Yining Wang ◽  
Wei Rong
Keyword(s):  
Carbon Dioxide ◽  
Technological Innovation ◽  
Carbon Dioxide Emissions ◽  
Carbon Dioxide Emission ◽  
Low Carbon ◽  
Training Mode ◽  
Un General Assembly ◽  
Low Carbon Development ◽  
Emission Growth ◽  
Carbon Peak

In September 22, 2020, Xi Jinping said at the seventy-fifth general debate of the UN General Assembly that China will enhance the national independent contribution, and strive to achieve the peak of carbon dioxide emissions by 2030, and strive to achieve carbon neutralization by 2060. Under the goal of carbon peak and carbon neutralization, the implementation of carbon emission reduction is an important strategy for China to achieve green and low-carbon development, but also faces major challenges “The Fourteenth Five Year Plan” Period is an important window period for scientific and technological innovation to realize the transformation of carbon dioxide emission growth rate. Only with the support of scientific and technological innovation can China be expected to achieve the goal of carbon peak and carbon neutralization on schedule. This paper attempts to study how to innovate the energy undergraduate talent training mode under the goal of “carbon neutral” from the aspects of the current situation of talent training, the analysis of talent training objectives, and the path analysis of talent training mode innovation.

scholarly journals Energy conversion path and optimization model in COVID-19 under low carbon constraints based on statistical learning theory

2020 ◽  
Vol 39 (6) ◽  
pp. 9053-9061
Author(s):  
Wensheng Wang ◽  
Han Yu ◽  
Qing Gao ◽  
Muhan Hu
Keyword(s):  
Carbon Dioxide ◽  
Big Data ◽  
Energy Consumption ◽  
Objective Function ◽  
Statistical Learning ◽  
Learning Theory ◽  
Optimization Model ◽  
Carbon Dioxide Emission ◽  
Low Carbon ◽  
Consumption Structure

This paper uses statistical learning theory and big data analysis to study the energy consumption structure of China from qualitative and quantitative aspects during COVID-19. According to the domestic and foreign scholars’ research on the optimization of energy consumption structure, the carbon emission factor is considered in the optimization of energy consumption structure. Taking the minimum energy consumption cost and carbon dioxide emission as the objective function, the carbon dioxide emission is taken as the objective function, and the total energy consumption and various energy consumption proportions as the constraint conditions, the multi-objective planning method is used to evaluate the energy consumption structure of China. The optimization model of source consumption structure is analyzed, and the medium and long-term energy transformation path and optimization model under low-carbon constraints are studied. Combined with the experimental algorithms related to big data, it is concluded that China’s economic development mainly depends on a large amount of energy consumption during the COVID-19 period. On this basis, some suggestions are put forward to realize the sustainable development of China’s economy and energy.

scholarly journals Coupled Climate–Economy–Biosphere (CoCEB) model – Part 2: Deforestation control and investment in carbon capture and storage technologies

2015 ◽  
Vol 6 (1) ◽  
pp. 865-906
Author(s):  
K. B. Z. Ogutu ◽  
F. D'Andrea ◽  
M. Ghil ◽  
C. Nyandwi ◽  
M. M. Manene ◽  
...  
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Carbon Capture ◽  
Carbon Dioxide Emission ◽  
Carbon Capture And Storage ◽  
Carbon Dioxide Concentration ◽  
Gdp Growth ◽  
Low Carbon ◽  
Ccs Technologies ◽  
And Storage

Abstract. This study uses the global climate–economy–biosphere (CoCEB) model developed in Part 1 to investigate economic aspects of deforestation control and carbon sequestration in forests, as well as the efficiency of carbon capture and storage (CCS) technologies as policy measures for climate change mitigation. We assume – as in Part 1 – that replacement of one technology with another occurs in terms of a logistic law, so that the same law also governs the dynamics of reduction in carbon dioxide emission using CCS technologies. In order to take into account the effect of deforestation control, a slightly more complex description of the carbon cycle than in Part 1 is needed. Consequently, we add a biomass equation into the CoCEB model and analyze the ensuing feedbacks and their effects on per capita gross domestic product (GDP) growth. Integrating biomass into the CoCEB and applying deforestation control as well as CCS technologies has the following results: (i) low investment in CCS contributes to reducing industrial carbon emissions and to increasing GDP, but further investment leads to a smaller reduction in emissions, as well as in the incremental GDP growth; and (ii) enhanced deforestation control contributes to a reduction in both deforestation emissions and in atmospheric carbon dioxide concentration, thus reducing the impacts of climate change and contributing to a slight appreciation of GDP growth. This effect is however very small compared to that of low-carbon technologies or CCS. We also find that the result in (i) is very sensitive to the formulation of CCS costs, while to the contrary, the results for deforestation control are less sensitive.

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