Carbon Emission Factor Decomposition Model and Empirical Research of Inner Mongolia Based on LMDI

2013 ◽  
Vol 291-294 ◽  
pp. 1375-1379 ◽  
Author(s):  
Zhi Yuan Gao ◽  
Tian Tian Li ◽  
Xi Wang ◽  
Ji Chao Peng
Keyword(s):  
Carbon Emissions ◽  
Inner Mongolia ◽  
Carbon Emission ◽  
Scientific Development ◽  
Energy Structure ◽  
Low Carbon ◽  
Close Relationship ◽  
Great Leap Forward ◽  
Factor Decomposition ◽  
Growing Economy

Inner Mongolia has rich energy resources, and how to realize low carbon scientific development is a very important issue for the autonomous region to realize great-leap-forward development. This article analyzed the factors which have been influencing the Inner Mongolia’s carbon emission from 2001 to 2010 by using the LMDI model, revealed the coal-dominated energy structure and the fast-growing economy are the main reasons that influence Inner Mongolia carbon emissions. The research results show that economic growth and carbon emissions have a close relationship, and the author gives some policy suggestions depend on the results.

scholarly journals Benchmarking Analysis of Carbon Emission in China and Foreign Countries from the Perspective of Urbanization

2021 ◽  
Vol 241 ◽  
pp. 02003
Author(s):  
Jun Wang ◽  
Hua Zhao
Keyword(s):  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Carbon Emission ◽  
National Level ◽  
Energy Structure ◽  
Low Carbon ◽  
The Sustainable Development ◽  
Per Capita ◽  
City Construction ◽  
Low Carbon City

With the further aggravation of global warming and the increasingly serious problems of ecological environment, the construction of low-carbon cities has become an inevitable choice for the global response to climate change and the sustainable development of economy and society. In order to understand the basic situation of China’s low-carbon cities more specifically, this paper selects countries with different urbanization rates to carry out benchmarking analysis with China, hoping to draw on the experience of other countries from the national level through multi-dimensional comparison, and guide the direction of China’s future urban development. Firstly, this paper selects the basic indicators such as the total amount of carbon dioxide emissions, per capita carbon emissions and carbon emissions per unit GDP of each country; Secondly, it compares the proportion of coal in energy and other indicators, and analyzes the energy structure of each country in depth; Thirdly, it compares the trend of carbon emissions in each country among 1990-2017. Finally, in order to reflect the carbon emission in the development of urbanization, this paper uses the “urbanization carbon emission index”, which is the ratio of per capita carbon emission and urbanization rate, to show the relationship between the degree of urbanization and carbon emission. Through benchmarking analysis, we can more clearly understand the overall trend of low-carbon city construction in different countries, recognize the gap between China and other countries, and better guide the development of low-carbon cities in China in the future.

scholarly journals Carbon Emission Estimation of Assembled Composite Concrete Beams during Construction

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1810
Author(s):  
Kaitong Xu ◽  
Haibo Kang ◽  
Wei Wang ◽  
Ping Jiang ◽  
Na Li
Keyword(s):  
Life Cycle ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Composite Beams ◽  
Total Carbon ◽  
Construction Process ◽  
Low Carbon ◽  
Carbon Emission Reduction ◽  
The Government

At present, the issue of carbon emissions from buildings has become a hot topic, and carbon emission reduction is also becoming a political and economic contest for countries. As a result, the government and researchers have gradually begun to attach great importance to the industrialization of low-carbon and energy-saving buildings. The rise of prefabricated buildings has promoted a major transformation of the construction methods in the construction industry, which is conducive to reducing the consumption of resources and energy, and of great significance in promoting the low-carbon emission reduction of industrial buildings. This article mainly studies the calculation model for carbon emissions of the three-stage life cycle of component production, logistics transportation, and on-site installation in the whole construction process of composite beams for prefabricated buildings. The construction of CG-2 composite beams in Fujian province, China, was taken as the example. Based on the life cycle assessment method, carbon emissions from the actual construction process of composite beams were evaluated, and that generated by the composite beam components during the transportation stage by using diesel, gasoline, and electric energy consumption methods were compared in detail. The results show that (1) the carbon emissions generated by composite beams during the production stage were relatively high, accounting for 80.8% of the total carbon emissions, while during the transport stage and installation stage, they only accounted for 7.6% and 11.6%, respectively; and (2) during the transportation stage with three different energy-consuming trucks, the carbon emissions from diesel fuel trucks were higher, reaching 186.05 kg, followed by gasoline trucks, which generated about 115.68 kg; electric trucks produced the lowest, only 12.24 kg.

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.

scholarly journals Low-carbon development via greening global value chains: a case study of Belarus

2020 ◽  
Vol 476 (2239) ◽  
pp. 20200024
Author(s):  
Huiqing Wang ◽  
Yixin Hu ◽  
Heran Zheng ◽  
Yuli Shan ◽  
Song Qing ◽  
...  
Keyword(s):  
International Trade ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Clean Energy ◽  
Global Value Chains ◽  
Value Chains ◽  
Energy Structure ◽  
Low Carbon ◽  
Low Carbon Development ◽  
Plastic Products

The rise of global value chains (GCVs) has seen the transfer of carbon emissions embodied in every step of international trade. Building a coordinated, inclusive and green GCV can be an effective and efficient way to achieve carbon emissions mitigation targets for countries that participate highly in GCVs. In this paper, we first describe the energy consumption as well as the territorial and consumption-based carbon emissions of Belarus and its regions from 2010 to 2017. The results show that Belarus has a relatively clean energy structure with 75% of Belarus' energy consumption coming from imported natural gas. The ‘chemical, rubber and plastic products' sector has expanded significantly over the past few years; its territorial-based emissions increased 10-fold from 2011 to 2014, with the ‘food processing' sector displaying the largest increase in consumption-based emissions. An analysis of regional emissions accounts shows that there is significant regional heterogeneity in Belarus with Mogilev, Gomel and Vitebsk having more energy-intensive manufacturing industries. We then analysed the changes in Belarus' international trade as well as its emission impacts. The results show that Belarus has changed from a net carbon exporter in 2011 to a net carbon importer in 2014. Countries along the Belt and Road Initiative, such as Russia, China, Ukraine, Poland and Kazakhstan, are the main trading partners and carbon emission importers/exporters for Belarus. ‘Construction’ and ‘chemical, rubber and plastic products' are two major emission-importing sectors in Belarus, while ‘electricity' and ‘ferrous metals' are the primary emission-exporting sectors. Possible low-carbon development pathways are discussed for Belarus through the perspectives of global supply and the value chain.

scholarly journals Does Emission Trading Improve Carbon Emission Efficiency of China’s Iron and Steel Industry? An Exploration Using a DEA-SBM and Difference-In-Differences Approach

2021 ◽  
Author(s):  
Xiping Wang ◽  
Sujing Wang
Keyword(s):  
Steel Industry ◽  
Carbon Emission ◽  
Emission Trading ◽  
Energy Structure ◽  
Iron And Steel Industry ◽  
Low Carbon ◽  
Difference In Differences ◽  
Iron And Steel ◽  
Emission Efficiency ◽  
The Impact

Abstract As an effective tool of carbon emission reduction, emission trading has been widely used in many countries. Since 2013, China implemented carbon emission trading in seven provinces and cities, with iron and steel industry included in the first batch of pilot industries. This study attempts to explore the policy effect of emission trading on iron and steel industry in order to provide data and theoretical support for the low-carbon development of iron and steel industry as well as the optimization of carbon market. With panel data of China’s 29 provinces from 2006 to 2017, this study adopted a DEA-SBM model to measure carbon emission efficiency of China’s iron and steel industry (CEI) and a difference-in-differences (DID) method to explore the impact of emission trading on CEI. Moreover, regional heterogeneity and influencing mechanisms were further investigated, respectively. The results indicate that: (1) China's emission trading has a significant and sustained effect on carbon abatement of iron and steel industry, increasing the annual average CEI by 12.6% in pilot provinces. (2) The policy effects are heterogeneous across diverse regions. Higher impacts are found in the western and eastern regions, whereas the central region is not significant. (3) Emission trading improves CEI by stimulating technology innovation, reducing energy intensity, and adjusting energy structure. (4) Economic level and industrial structure are negatively related to CEI, while environmental governance and openness degree have no obvious impacts. Finally, according to the results and conclusions, some specific suggestions are proposed.

scholarly journals Constructing an Environmental Friendly Low-Carbon-Emission Intelligent Transportation System Based on Big Data and Machine Learning Methods

2020 ◽  
Vol 12 (19) ◽  
pp. 8118
Author(s):  
Tu Peng ◽  
Xu Yang ◽  
Zi Xu ◽  
Yu Liang
Keyword(s):  
Sustainable Development ◽  
Environmental Pollution ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Intelligent Transportation ◽  
Exhaust Emissions ◽  
Low Carbon ◽  
Vehicle Exhaust ◽  
The Sustainable Development ◽  
Low Carbon Emission

The sustainable development of mankind is a matter of concern to the whole world. Environmental pollution and haze diffusion have greatly affected the sustainable development of mankind. According to previous research, vehicle exhaust emissions are an important source of environmental pollution and haze diffusion. The sharp increase in the number of cars has also made the supply of energy increasingly tight. In this paper, we have explored the use of intelligent navigation technology based on data analysis to reduce the overall carbon emissions of vehicles on road networks. We have implemented a traffic flow prediction method using a genetic algorithm and particle-swarm-optimization-enhanced support vector regression, constructed a model for predicting vehicle exhaust emissions based on predicted road conditions and vehicle fuel consumption, and built our low-carbon-emission-oriented navigation algorithm based on a spatially optimized dynamic path planning algorithm. The results show that our method could help to significantly reduce the overall carbon emissions of vehicles on the road network, which means that our method could contribute to the construction of low-carbon-emission intelligent transportation systems and smart cities.

scholarly journals The Determinants of Carbon Emissions in the Chinese Construction Industry: A Spatial Analysis

2020 ◽  
Vol 12 (4) ◽  
pp. 1428 ◽  
Author(s):  
Na Lu ◽  
Shuyi Feng ◽  
Ziming Liu ◽  
Weidong Wang ◽  
Hualiang Lu ◽  
...  
Keyword(s):  
Construction Industry ◽  
Carbon Emissions ◽  
Industrial Structure ◽  
Spillover Effects ◽  
Energy Structure ◽  
Chinese Government ◽  
Low Carbon ◽  
Industry Agglomeration ◽  
Technology Innovations ◽  
Growth Energy

As the largest carbon emitter in the world, China is confronted with great challenges of mitigating carbon emissions, especially from its construction industry. Yet, the understanding of carbon emissions in the construction industry remains limited. As one of the first few attempts, this paper contributes to the literature by identifying the determinants of carbon emissions in the Chinese construction industry from the perspective of spatial spillover effects. A panel dataset of 30 provinces or municipalities from 2005 to 2015 was used for the analysis. We found that there is a significant and positive spatial autocorrelation of carbon emissions. The local Moran’s I showed local agglomeration characteristics of H-H (high-high) and L-L (low-low). The indicators of population density, economic growth, energy structure, and industrial structure had either direct or indirect effects on carbon emissions. In particular, we found that low-carbon technology innovation significantly reduces carbon emissions, both in local and neighboring regions. We also found that the industry agglomeration significantly increases carbon emissions in the local regions. Our results imply that the Chinese government can reduce carbon emissions by encouraging low-carbon technology innovations. Meanwhile, our results also highlight the negative environmental impacts of the current policies to promote industry agglomeration.

scholarly journals Low-Carbon Impact of Urban Rail Transit Based on Passenger Demand Forecast in Baoji

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 782
Author(s):  
Na Zhang ◽  
Zijia Wang ◽  
Feng Chen ◽  
Jingni Song ◽  
Jianpo Wang ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Quantitative Research ◽  
Carbon Emission ◽  
Urban Traffic ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Low Carbon ◽  
Demand Forecast ◽  
Passenger Demand ◽  
Urban Rail

There are increasing traffic pollution issues in the process of urbanization in many countries; urban rail transit is low-carbon and widely regarded as an effective way to solve such problems. The passenger flow proportion of different transportation types is changing along with the adjustment of the urban traffic structure and a growing demand from passengers. The reduction of carbon emissions brought about by rail transit lacks specific quantitative research. Based on a travel survey of urban residents, this paper constructed a method of estimating carbon emissions from two different scenarios where rail transit is and is not available. This study uses the traditional four-stage model to forecast passenger volume demand at the city level and then obtains the basic target parameters for constructing the carbon emission reduction model, including the trip origin-destination (OD), mode, and corresponding distance range of different modes on the urban road network. This model was applied to Baoji, China, where urban rail transit will be available from 2023. It calculates the changes in carbon emission that rail transit can bring about and its impact on carbon emission reductions in Baoji in 2023.

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