scholarly journals Intelligent Measurement and Monitoring of Carbon Emissions for 5G Shared Smart Logistics

2022 ◽  
Vol 2022 ◽  
pp. 1-13
Author(s):  
Ailing Zhang ◽  
Sha Li ◽  
Lin Tan ◽  
Yingchao Sun ◽  
Fuxiao Yao
Keyword(s):  
Supply Chain ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Emission Factor ◽  
Carbon Emission ◽  
Storage Technology ◽  
Factor Method ◽  
Smart Logistics ◽  
Intelligent Measurement ◽  
Logistics Process

With the upgrading of logistics demand and the innovation of modern information technology, the smart logistics platform integrates advanced concepts, technologies, and management methods, maximizes the integration of logistics resources and circulation channels, and effectively improves the efficiency of logistics transactions, but its energy consumption problem is particularly prominent. The study of intelligent measurement and monitoring of carbon emissions in smart logistics is of great value to reduce energy consumption, reduce carbon emissions in buildings, and improve the environment. In this paper, by comparing and analyzing the accounting standards of carbon emissions and their calculation methods, the carbon emission factor method is selected as the method to study the carbon emissions of the smart logistics process in this paper. The working principle of each key storage technology in the smart logistics process is analyzed to find out the equipment factors affecting the carbon emission of each storage technology in the smart logistics process, and the carbon emission calculation model of each key storage technology is established separately by using the carbon emission factor method. Meanwhile, according to the development history of energy consumption assessment, the assessment process of different stages from logistics storage energy consumption assessment to smart logistics energy consumption assessment is analyzed, and based on this, a carbon emission energy consumption assessment framework based on 5G shared smart logistics is constructed. This paper applies the supply chain idea to define the smart logistics supply chain, constructs a conceptual model of the smart logistics supply chain considering carbon emissions, and at the same time combines the characteristics of the smart logistics supply chain to analyze the correlation between the carbon emissions of the smart logistics supply chain and the related social, environmental, and economic systems.

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 Mitigating the Energy Consumption and the Carbon Emission in the Building Structures by Optimization of the Construction Processes

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3287
Author(s):  
Alireza Tabrizikahou ◽  
Piotr Nowotarski
Keyword(s):  
Life Cycle ◽  
Energy Consumption ◽  
Structural Optimization ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Construction Materials ◽  
High Energy ◽  
Building Structures ◽  
Life Cycle Stages ◽  
Reduction Of Energy Consumption

For decades, among other industries, the construction sector has accounted for high energy consumption and emissions. As the energy crisis and climate change have become a growing concern, mitigating energy usage is a significant issue. The operational and end of life phases are all included in the building life cycle stages. Although the operation stage accounts for more energy consumption with higher carbon emissions, the embodied stage occurs in a time-intensive manner. In this paper, an attempt has been made to review the existing methods, aiming to lower the consumption of energy and carbon emission in the construction buildings through optimizing the construction processes, especially with the lean construction approach. First, the energy consumption and emissions for primary construction materials and processes are introduced. It is followed by a review of the structural optimization and lean techniques that seek to improve the construction processes. Then, the influence of these methods on the reduction of energy consumption is discussed. Based on these methods, a general algorithm is proposed with the purpose of improving the construction processes’ performance. It includes structural optimization and lean and life cycle assessments, which are expected to influence the possible reduction of energy consumption and carbon emissions during the execution of construction works.

Carbon Emission of Mining Industry’s Energy Consumption in Heilongjiang Province

2015 ◽  
Vol 1092-1093 ◽  
pp. 1597-1600
Author(s):  
Zhong Hua Wang ◽  
Xin Ye Chen
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Mining Industry ◽  
Calculation Model ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Heilongjiang Province ◽  
Low Carbon

The need to reduce carbon emission in Heilongjiang Province of China is urgent challenge facing sustainable development. This paper aims to make explicit the problem-solving of carbon emission to find low carbon emission ways. According to domestic and foreign literatures on estimating and calculating carbon emissions and by integrating calculation methods of carbon emissions, it was not possible to consider all of the many contributions to carbon emissions. Calculation model of carbon emissions suitable to this paper is selected. The carbon emissions of energy consumption in mining industry are estimated and calculated from 2005 to 2012, and the characteristics of carbon emission are analyzed at the provincial level. It makes the point that carbon emissions of energy consumption in mining industry can be reduced when we attempt to alter energy consumption structure, adjust industrial structure and improve energy utilization efficiency.

Study on the Relationship between Energy Consumption, Carbon Emission and Economic Growth in China

2013 ◽  
Vol 869-870 ◽  
pp. 746-749
Author(s):  
Tian Tian Jin ◽  
Jin Suo Zhang
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Energy Structure ◽  
Ardl Model ◽  
Relationship Of ◽  
The Relationship ◽  
Reducing Energy

Abstract. Based on ARDL model, this paper discussed the relationship of energy consumption, carbon emission and economic growth.The results indicated that the key to reduce carbon emissions lies in reducing energy consumption, optimizing energy structure.

scholarly journals Analysis of total carbon emission of the logistics industry in Guangdong and solutions to emission reduction

2021 ◽  
Vol 245 ◽  
pp. 01020
Author(s):  
Aixia Xu ◽  
Xiaoyong Yang
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Energy Utilization ◽  
Total Carbon ◽  
Utilization Rate ◽  
Low Carbon ◽  
Logistics Industry ◽  
Direct Energy ◽  
Reduce Emissions

The input-output method is employed in this study to measure the total carbon emission of the logistics industry in Guangdong. The findings revealed that the carbon emission of direct energy consumption of the logistics industry in Guangdong is far above the actual carbon emissions, the second and third industries play a significant role in carbon emission of indirect energy consumption in the logistics industry in Guangdong. To reduce energy consumption and carbon emissions in Guangdong, it is not only important to control the carbon emissions in the logistics industry, but strengthen carbon emission detection in relevant industries, improve the energy utilization rate and reduce emissions in other industries, and move towards low-carbon sustainable development.

Research of Calculating Corrugated Board Carbon Footprint Based on Energy Conservation

2012 ◽  
Vol 200 ◽  
pp. 524-527
Author(s):  
He Nian ◽  
Xiao Min Wang ◽  
Xiao Juan Shi
Keyword(s):  
Energy Conservation ◽  
Carbon Footprint ◽  
Carbon Emissions ◽  
Heat Balance ◽  
Production Line ◽  
Emission Factor ◽  
Carbon Emission ◽  
Corrugated Board ◽  
Indirect Emission ◽  
The Heat Balance

Based on the energy conservation, calculate the carbon footprint of single wall corrugated boards. By calculating the heat balance of each unit in the corrugated board production line, the steam quantity of each unit was calculated and translated into direct carbon emissions; indirect carbon emission was calculated by the electric carbon emission factor. Evaluates to: producing quantitative 140/110/170(g/m2) single wall board for 100m2, the direct and indirect emission of CO2 is 25.4kg and 9.4kg.

Energy Consumption and Structural Reformation in Chinese Northeast Old Industrial Base

2013 ◽  
Vol 448-453 ◽  
pp. 4281-4284 ◽  
Author(s):  
Shao Bo Liu
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Energy Utilization ◽  
Energy Structure ◽  
Energy Technology ◽  
Industrial Base ◽  
Old Industrial Base ◽  
Emissions Intensity

Using IPCC methodology, the carbon emissions of Chinese Northeast Old Industrial Base is calculated, and the energy's synthesized impact on carbon emissions intensity is presented. The resulting shows that the carbon emissions in the three northeast provinces decreased 52.87% from 2000 to 2010, of which, Liaoning, Jilin and Heilongjiang are individually 60.09%, 45.47% and 54.14% lower. The implications are that the energy structure is one of the main factors in carbon emission in the Old Industrial Base of Northeast China, and its industrial structure is changing greatly due to energy consumption carbon emission. To adjust optimally the energy and industrial structure, and to develop the energy technology to promote energy utilization are recommended.

scholarly journals The carbon emissions of Chinese cities

2012 ◽  
Vol 12 (14) ◽  
pp. 6197-6206 ◽  
Author(s):  
H. Wang ◽  
R. Zhang ◽  
M. Liu ◽  
J. Bi
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
National Policy ◽  
Emission Inventories ◽  
Chinese Cities ◽  
Industrial Energy ◽  
Per Capita ◽  
Policy Priority

Abstract. As increasing urbanization has become a national policy priority for economic growth in China, cities have become important players in efforts to reduce carbon emissions. However, their efforts have been hampered by the lack of specific and comparable carbon emission inventories. Comprehensive carbon emission inventories for twelve Chinese cities, which present both a relatively current snapshot and also show how emissions have changed over the past several years, were developed using a bottom-up approach. Carbon emissions in most Chinese cities rose along with economic growth from 2004 to 2008. Yet per capita carbon emissions varied between the highest and lowest emitting cities by a factor of nearly 7. Average contributions of sectors to per capita emissions for all Chinese cities were 65.1% for industrial energy consumption, 10.1% for industrial processes, 10.4% for transportation, 7.7% for household energy consumption, 4.2% for commercial energy consumption and 2.5% for waste processing. However, these shares are characterized by considerable variability due to city-specific factors. The levels of per capita carbon emissions in China's cities were higher than we anticipated before comparing them with the average of ten cities in other parts of the world. This is mainly due to the major contribution of the industry sector in Chinese cities.

scholarly journals Energy Demand and Carbon Emission Peak Forecasting of Beijing Based on Leap Energy Simulation Method

2020 ◽  
Keyword(s):  
Sustainable Development ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Energy Demand ◽  
Carbon Emission ◽  
Simulation Method ◽  
Negative Influence ◽  
Low Carbon ◽  
Peak Value

<p>The long-term forecasting of the energy demand is an important issue of an area’s sustainable development, especially for mega cities such as Beijing. Beijing is changing its energy supply strategy to depend on energy imports from other provinces due to the city’s long-term low carbon sustainable development plan. Beijing has promised that it will reach the peak value of energy consumption by 2050 and the peak value of the carbon emissions by 2030. To understand whether this can be achieved, this study built an energy demand simulation model using the LEAP with different development scenarios. The results show that, the peak value of Beijing’s energy demand is between 108.25 and 131.74 Mtce during the period of 2044 to 2048, while the peak value of carbon emissions is between 134 and 139.38 million tons in 2025. We also find that adjusting the industry structure and improving the tertiary industry’s energy usage efficiency can be efficient ways to reduce energy consumption. These approaches not only reduce the negative influence of the economic development, but also achieve the energy saving and carbon emission reducing requirements. This study provides an interpretation of the implications for the future energy and climate policies of Beijing.</p>

scholarly journals Decision Optimization of Low-Carbon Dual-Channel Supply Chain of Auto Parts Based on Smart City Architecture

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Zheng Liu ◽  
Bin Hu ◽  
Bangtong Huang ◽  
Lingling Lang ◽  
Hangxin Guo ◽  
...  
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Carbon Emissions ◽  
Smart City ◽  
Carbon Emission ◽  
Low Carbon ◽  
Supply Chain System ◽  
Chain System ◽  
Carbon Supply ◽  
Auto Parts

Affected by the Internet, computer, information technology, etc., building a smart city has become a key task of socialist construction work. The smart city has always regarded green and low-carbon development as one of the goals, and the carbon emissions of the auto parts industry cannot be ignored, so we should carry out energy conservation and emission reduction. With the rapid development of the domestic auto parts industry, the number of car ownership has increased dramatically, producing more and more CO2 and waste. Facing the pressure of resources, energy, and environment, the effective and circular operation of the auto parts supply chain under the low-carbon transformation is not only a great challenge, but also a development opportunity. Under the background of carbon emission, this paper establishes a decision-making optimization model of the low-carbon supply chain of auto parts based on carbon emission responsibility sharing and resource sharing. This paper analyzes the optimal decision-making behavior and interaction of suppliers, producers, physical retailers, online retailers, demand markets, and recyclers in the auto parts industry, constructs the economic and environmental objective functions of low-carbon supply chain management, applies variational inequality to analyze the optimal conditions of the whole low-carbon supply chain system, and finally carries out simulation calculation. The research shows that the upstream and downstream auto parts enterprises based on low-carbon competition and cooperation can effectively manage the carbon footprint of the whole supply chain through the sharing of responsibilities and resources among enterprises, so as to reduce the overall carbon emissions of the supply chain system.

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