Research of Equipment Sustainable Development Based on Resource Constraint

2011 ◽  
Vol 347-353 ◽  
pp. 2843-2848
Author(s):  
Ming Fang Ni ◽  
Yang Zhuo Wei ◽  
Lu Xi Kang ◽  
Zhong Fan
Keyword(s):  
Sustainable Development ◽  
Energy Consumption ◽  
Resource Constraint ◽  
Utilization Efficiency ◽  
Military Equipment ◽  
Equipment Construction ◽  
Foreign Countries ◽  
High Efficient ◽  
Equipment Development ◽  
Whole Life Cycle

Under the background of fact that the shortage situation of present global being severer and severer day by day, the army equipment development faces enormous challenge. How to walk out a low-input, high-efficient road of equipment construction seems particularly important, which has been a great strategic task of the modernization of military equipment. Based on the resource constraint, this article aims at the resource "bottlenecks" such as the unreasonable structure of energy consumption, high dependence of traditional fossil energy, large resource dependent degree on foreign countries, low resource utilization efficiency, serious environmental pollution, starts from every stage of the whole life cycle of equipment, regards idea of sustainable development as guidelines, proposes strategic actions including strengthening the resource design, adjusting the energy consumption structure, strengthening resources substitute, improving the recycling system and so on, in order to break through resource constraint and realize the strategic measures of equipment sustainable development, in the hope of having some realistic significance in equipment construction and development under the new situation.

scholarly journals Machine Learning Approach to Quantity Management for Long-Term Sustainable Development of Dockless Public Bike: Case of Shenzhen in China

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Qingfeng Zhou ◽  
Chun Janice Wong ◽  
Xian Su
Keyword(s):  
Machine Learning ◽  
Sustainable Development ◽  
Clustering Algorithms ◽  
Utilization Efficiency ◽  
Impact Factors ◽  
Classification Algorithms ◽  
Learning Approach ◽  
High Efficient ◽  
Machine Learning Approach

Since the number of bicycles is critical to the sustainable development of dockless PBS, this research practiced the introduction of a machine learning approach to quantity management using OFO bike operation data in Shenzhen. First, two clustering algorithms were used to identify the bicycle gathering area, and the available bike number and coefficient of available bike number variation were analyzed in each bicycle gathering area’s type. Second, five classification algorithms were compared in the accuracy of distinguishing the type of bicycle gathering areas using 25 impact factors. Finally, the application of the knowledge gained from the existing dockless bicycle operation data to guide the number planning and management of public bicycles was explored. We found the following. (1) There were 492 OFO bicycle gathering areas that can be divided into four types: high inefficient, normal inefficient, high efficient, and normal efficient. The high inefficient and normal inefficient areas gathered about 110,000 bicycles with low usage. (2) More types of bicycle gathering area will affect the accuracy of the classification algorithm. The random forest classification had the best performance in identifying bicycle gathering area types in five classification algorithms with an accuracy of more than 75%. (3) There were obvious differences in the characteristics of 25 impact factors in four types of bicycle gathering areas. It is feasible to use these factors to predict area type to optimize the number of available bicycles, reduce operating costs, and improve utilization efficiency. This work helps operators and government understand the characteristics of dockless PBS and contributes to promoting long-term sustainable development of the system through a machine learning approach.

scholarly journals An Improved Forecasting Method and Application of China’s Energy Consumption under the Carbon Peak Target

2021 ◽  
Vol 13 (15) ◽  
pp. 8670
Author(s):  
Xiwen Cui ◽  
Shaojun E ◽  
Dongxiao Niu ◽  
Dongyu Wang ◽  
Mingyu Li
Keyword(s):  
Sustainable Development ◽  
Energy Consumption ◽  
Environmental Pollution ◽  
Optimization Methods ◽  
Support Vector ◽  
The Sustainable Development ◽  
Consumption Data ◽  
Forecasting Method ◽  
Forecasting Performance ◽  
Carbon Peak

In the process of economic development, the consumption of energy leads to environmental pollution. Environmental pollution affects the sustainable development of the world, and therefore energy consumption needs to be controlled. To help China formulate sustainable development policies, this paper proposes an energy consumption forecasting model based on an improved whale algorithm optimizing a linear support vector regression machine. The model combines multiple optimization methods to overcome the shortcomings of traditional models. This effectively improves the forecasting performance. The results of the projection of China’s future energy consumption data show that current policies are unable to achieve the carbon peak target. This result requires China to develop relevant policies, especially measures related to energy consumption factors, as soon as possible to ensure that China can achieve its peak carbon targets.

scholarly journals Mechanisms of Environmental Regulation’s Impact on Green Technological Progress—Evidence from China’s Manufacturing Sector

2021 ◽  
Vol 13 (4) ◽  
pp. 1600
Author(s):  
Weijiang Liu ◽  
Mingze Du ◽  
Yuxin Bai
Keyword(s):  
Sustainable Development ◽  
Energy Consumption ◽  
Technological Change ◽  
Environmental Protection ◽  
Technological Progress ◽  
Manufacturing Industry ◽  
Manufacturing Sector ◽  
The Sustainable Development ◽  
Biased Technological Change ◽  
Chinese Manufacturing Industry

As the world’s largest developing country, and as the home to many of the world’s factories, China plays a crucial role in the sustainable development of the world economy regarding environmental protection, energy conservation, and emission reduction issues. Based on the data from 2003–2015, this paper examined the green total factor productivity and the technological progress in the Chinese manufacturing industry. A slack-based measure (SBM) Malmquist productivity index was used to measure the bias of technological change (BTC), input-biased technological change (IBTC), and output-biased technological change (OBTC) by decomposing the technological progress. It also investigated the mechanism of environmental regulation, property right structure, enterprise-scale, energy consumption structure, and other factors on China’s technological progress bias. The empirical results showed the following: (1) there was a bias of technological progress in the Chinese manufacturing industry during the research period; (2) although China’s manufacturing industry’s output tended to become greener, it was still characterized by a preference for overall CO2 output; and (3) the impact of environmental regulations on the Chinese manufacturing industry’s technological progress had a significant threshold effect. The flexible control of environmental regulatory strength will benefit the Chinese manufacturing industry’s technological development. (4) R&D investment, export delivery value, and structure of energy consumption significantly contributed to promoting technological progress. This study provides further insight into the sustainable development of China’s manufacturing sector to promote green-biased technological progress and to achieve the dual goal of environmental protection and healthy economic growth.

scholarly journals Evaluation of CO2 emissions and energy use with different container terminal layouts

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Muhammad Arif Budiyanto ◽  
Muhammad Hanzalah Huzaifi ◽  
Simon Juanda Sirait ◽  
Putu Hangga Nan Prayoga
Keyword(s):  
Energy Efficiency ◽  
Sustainable Development ◽  
Energy Consumption ◽  
Statistical Analysis ◽  
Energy Use ◽  
Container Terminal ◽  
Container Terminals ◽  
Future Planning ◽  
Container Handling

AbstractSustainable development of container terminals is based on energy efficiency and reduction in CO2 emissions. This study estimated the energy consumption and CO2 emissions in container terminals according to their layouts. Energy consumption was calculated based on utility data as well as fuel and electricity consumptions for each container-handling equipment in the container terminal. CO2 emissions were estimated using movement modality based on the number of movements of and distance travelled by each container-handling equipment. A case study involving two types of container terminal layouts i.e. parallel and perpendicular layouts, was conducted. The contributions of each container-handling equipment to the energy consumption and CO2 emissions were estimated and evaluated using statistical analysis. The results of the case study indicated that on the CO2 emissions in parallel and perpendicular layouts were relatively similar (within the range of 16–19 kg/TEUs). These results indicate that both parallel and perpendicular layouts are suitable for future ports based on sustainable development. The results can also be used for future planning of operating patterns and layout selection in container terminals.

scholarly journals Technowomen: Women’s Autonomy and Its Impact on Environmental Quality

2021 ◽  
Vol 13 (4) ◽  
pp. 1611
Author(s):  
Saima Mujeed ◽  
Shuangyan Li ◽  
Musarrat Jabeen ◽  
Abdelmohsen A. Nassani ◽  
Sameh E. Askar ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Environmental Quality ◽  
Ghg Emissions ◽  
Renewable Energy Consumption ◽  
Women’S Autonomy ◽  
Women's Autonomy ◽  
Role Of Women

The role of women in economic development and the global environment is vital for progressing them towards the United Nations sustainable development goal (SDG-5) that emphasized the need to empower women in every walk of life. The study examines women’s autonomy in the sustainable development agenda under China’s open innovation system from 1975 to 2019. The study employed an autoregressive distributed lag (ARDL) model, vector autoregressive (VAR) Granger causality, and innovation accounting matrix to estimate parameters. The existing data are summarized and collated in the context of China to explain as a correlational study. The results show that women’s autonomy moderated with technology spills over to decrease greenhouse gas (GHG) emissions and substantiate the hump-shaped relationship between them. The increased spending on research and development (R&D) activities, patent publications, and renewable energy consumption empowers women to be equipped with the latest sustainable technologies to improve environmental quality. The pollution haven hypothesis verifies a given country, where trade liberalization policies tend to increase polluting industries to set up their plants that engaged in dirty production that exacerbate GHG emissions. The causality estimates confirmed that technological innovations and renewable energy consumption leads to women’s autonomy. In contrast, females’ share in the labor force participation rate leads to an increase in renewable energy consumption. Thus, it is evident that there is a positive role of women in the country’s sustainable development.

scholarly journals The Impact of Energy Consumption on the Three Pillars of Sustainable Development

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1372
Author(s):  
Silviu Nate ◽  
Yuriy Bilan ◽  
Danylo Cherevatskyi ◽  
Ganna Kharlamova ◽  
Oleksandr Lyakh ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Energy Consumption ◽  
Energy Density ◽  
Ecological Footprint ◽  
Policy Design ◽  
Disability Adjusted Life ◽  
The Social ◽  
Low Efficiency ◽  
Disability Adjusted Life Year ◽  
The Impact

The paper analyzes the impact of energy consumption on the three pillars of sustainable development in 74 countries. The main methodological challenge in this research is the choice of a single integral indicator for assessing the social component of sustainable development. Disability-adjusted life year (DALY), ecological footprint, and GDP (Gross domestic product) are used to characterize the social, ecological, and economical pillars. The concept of physics, namely the concept of density (specific gravity), is used. It characterizes the ratio of the mass of a substance to its volume, i.e., reflects the saturation of a certain volume with this substance. Thus, to assess the relationship between energy consumption and the three foundations of sustainable development, it is proposed to determine the energy density of the indicators DALY, the ecological footprint, and GDP. The reaction to changes in energy consumption is described by the elasticity of energy density functions, calculated for each of the abovementioned indicators. The state of the social pillar is mostly dependent on energy consumption. As for the changes in the ecological pillar, a 1% reduction in energy consumption per capita gives only a 0.6% ecological footprint reduction, which indicates a low efficiency of reducing energy consumption policy and its danger for the social pillar. The innovative aspect of the research is to apply a cross-disciplinary approach and a calculative technique to identify the impact that each of the pillars of sustainable development imposes on energy policy design. The policy of renewable energy expansion is preferable for all sustainable development pillars.

scholarly journals TOPOI RESOURCES: Quantification and Assessment of Global Warming Potential and Land-Uptake of Residential Buildings in Settlement Types along the Urban–Rural Gradient—Opportunities for Sustainable Development

2021 ◽  
Vol 13 (8) ◽  
pp. 4099
Author(s):  
Ann-Kristin Mühlbach ◽  
Olaf Mumm ◽  
Ryan Zeringue ◽  
Oskars Redbergs ◽  
Elisabeth Endres ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Global Warming ◽  
Energy Consumption ◽  
Global Warming Potential ◽  
Residential Buildings ◽  
Residential Building ◽  
Negative Effects ◽  
Building Stock ◽  
Residential Building Stock ◽  
Urban Rural

The METAPOLIS as the polycentric network of urban–rural settlement is undergoing constant transformation and urbanization processes. In particular, the associated imbalance of the shrinkage and growth of different settlement types in relative geographical proximity causes negative effects, such as urban sprawl and the divergence of urban–rural lifestyles with their related resource, land and energy consumption. Implicitly related to these developments, national and global sustainable development goals for the building sector lead to the question of how a region can be assessed without detailed research and surveys to identify critical areas with high potential for sustainable development. In this study, the TOPOI method is used. It classifies settlement units and their interconnections along the urban–rural gradient, in order to quantify and assess the land-uptake and global warming potential driven by residential developments. Applying standard planning parameters in combination with key data from a comprehensive life cycle assessment of the residential building stock, a detailed understanding of different settlement types and their associated resource and energy consumption is achieved.

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.

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