scholarly journals Analysis of Influencing Factors of Carbon Emissions in China’s Logistics Industry: A GDIM-Based Indicator Decomposition

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5742
Author(s):  
Changyou Zhang ◽  
Wenyu Zhang ◽  
Weina Luo ◽  
Xue Gao ◽  
Bingchen Zhang
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Added Value ◽  
Total Carbon ◽  
Carbon Intensity ◽  
Contribution Ratio ◽  
Logistics Industry ◽  
Per Capita ◽  
First Time

Due to increased global carbon dioxide emissions, the greenhouse effect is being aggravated, which has attracted wide attention. China is committed to promoting the low-carbon development of all industries. This paper analyzed the influencing factors of carbon emissions in the Chinese logistics industry, so as to identify the key factors that influence carbon emissions. Based on the carbon emission data of China’s logistics industry in 2000–2019, this paper applied the carbon emission coefficients issued by the Intergovernmental Panel on Climate Change. For the first time, the Generalized Divisia Index Method was used to analyze the degree of influence of the factors on carbon emissions. This method considered more variables and their relationships. The results showed that (1) the carbon emissions of the logistics industry were increased by 3.22 times from 2000 to 2018, and showed negative growth for the first time in 2019; (2) the added value of the logistics industry is the most important factor in increasing carbon emissions (with a contribution ratio of 65.45%), energy consumption and practical population size are the main factors in carbon emissions. The promotion of this industry is subjected to decreased per capita carbon emissions, which have a large impact on total carbon emissions; (3) the intensity of carbon output is the most important factor in the reduction of carbon emissions (with a contribution ratio of −29.1%), where the energy carbon intensity and per capita added value are the main influencing factors with regard to the reduction of carbon emissions, while energy intensity has a negative inhibitory effect on carbon emissions, and (4) the influencing factors have negative effects on the cumulative inhibition of carbon emissions in the logistics industry, to an extent that is far less than the integral promotion of carbon emissions. Finally, according to the research conclusions of this paper, it is feasible to make recommendations for the carbon reduction of the logistics industry.

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 Temporal Evolution and Influencing Factors of Energy Consumption and Related Carbon Emissions from the Perspective of Industrialization and Urbanization in Shanghai, China

2018 ◽  
Vol 10 (9) ◽  
pp. 3054 ◽  
Author(s):  
Pingxing Li ◽  
Wei Sun
Keyword(s):  
Energy Consumption ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Temporal Evolution ◽  
Added Value ◽  
Living Standard ◽  
Total Energy Consumption ◽  
Consumption Level ◽  
Economic Output ◽  
Per Capita

Improvements of manufacturability and living standard driven by industrialization and urbanization typically cause a spike in total energy consumption (TEC) and related carbon emissions (TCEM). However, there have been few comparative studies to include industrial and residential energy consumption (IEC and REC, respectively) and related carbon emissions (ICEM and RCEM, respectively). Since China is a major emerging industrial country wherein urbanization is still ongoing, the present study was conducted in an attempt to analyze the temporal evolution of China’s continued energy consumption and related carbon emissions regarding both industrialization and urbanization. The influencing factors of TCEM, RCEM and ICEM are determined via the log-mean divisia index (LMDI) model. The results showed that both TEC and TCEM gradually increased (apart from a slight decrease in 2014); REC and RCEM increased steadily with no sharp peak; while IEC and ICEM declined sharply. TCEM was positively affected by economic output, consumption level, and population size; the influence of consumption level became more and more significant. Per capita GDP and per capita expenditure were the most significant driving factors for RCEM, while industrial added value (IAV) was the main driving factor for ICEM. The temporal evolution and influencing factors of energy consumption and carbon emissions had stage-related characteristics in accordance with Shanghai’s three stages of development. The Shanghai case study provided a comprehensive understanding of energy consumption and related carbon emissions from the dual perspective of industrialization and urbanization.

scholarly journals Spatial-Temporal Characteristics of the Driving Factors of Agricultural Carbon Emissions: Empirical Evidence from Fujian, China

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3102 ◽  
Author(s):  
Yihui Chen ◽  
Minjie Li ◽  
Kai Su ◽  
Xiaoyong Li
Keyword(s):  
Carbon Emissions ◽  
Carbon Emission ◽  
Agricultural Development ◽  
Agricultural Sector ◽  
Industrial Structure ◽  
Arable Land ◽  
Added Value ◽  
Agricultural Labor ◽  
Intergovernmental Panel ◽  
Per Capita

With the development of agricultural modernization, the carbon emissions caused by the agricultural sector have attracted academic and practitioners’ circles’ attention. This research selected the typical agricultural development province in China, Fujian, as the research object. Based on the carbon emission sources of five main aspects in agricultural production, this paper applied the latest carbon emission coefficients released by Intergovernmental Panel on Climate Change of the UN (IPCC) and World Resources Institute (WRI), then used the ordered weighted aggregation (OWA) operator to remeasure agricultural carbon emissions in Fujian from 2008–2017. The results showed that the amount of agricultural carbon emissions in Fujian was 5541.95 × 103 tonnes by 2017, which means the average amount of agricultural carbon emissions in 2017 was 615.78 × 103 tonnes, with a decrease of 13.13% compared with that in 2008. In terms of spatial distribution, agricultural carbon emissions in the eastern coastal areas were less than those in the inland regions. Among them, the highest agricultural carbon emissions were in Zhangzhou, Nanping, and Sanming, while the lowest were in Xiamen, Putian, and Ningde. In addition, this paper selected six influencing variables, the research and development intensity, the proportion of agricultural labor force, the added value of agriculture, the agricultural industrial structure, the per capita disposable income of rural residents, and per capita arable land area, to clarify further the impacts on agricultural carbon emissions. Finally, geographically- and temporally-weighted regression (GTWR) was used to measure the direction and degree of the influences of factors on agricultural carbon emission. The conclusion showed that the regression coefficients of each selected factor in cities were positive or negative, which indicated that the impacts on agricultural carbon emission had the characteristics of geospatial nonstationarity.

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.

scholarly journals Evaluating the Carbon Emissions Efficiency of the Logistics Industry Based on a Super-SBM Model and the Malmquist Index from a Strong Transportation Strategy Perspective in China

2020 ◽  
Vol 17 (22) ◽  
pp. 8459
Author(s):  
Xiaohong Jiang ◽  
Jianxiao Ma ◽  
Huizhe Zhu ◽  
Xiucheng Guo ◽  
Zhaoguo Huang
Keyword(s):  
Carbon Emissions ◽  
Growth Rates ◽  
Carbon Emission ◽  
High Efficiency ◽  
Malmquist Index ◽  
Logistics Industry ◽  
Sbm Model ◽  
Low Efficiency ◽  
Emission Growth ◽  
Second Category

Carbon emissions from the logistics industry have been rising year after year. Correct handling of the relationship between economic development and environmental protection is of great significance to the implementation of green logistics, which is an important component of China’s strategy for strong transportation. This paper focuses on the evaluation of the carbon emissions efficiency of logistics industry from a new strong transportation strategy perspective. A super-efficiency slack-based measurement (Super-SBM) model and Malmquist index are combined to evaluate the static and dynamic carbon emissions efficiency of the logistics industry. The results indicate that compared with the SBM model, the Super-SBM model can more effectively measure the carbon emissions efficiency of the logistics industry. Pilot regions for the strong transportation strategy were divided into two categories, namely regions with slow carbon emission growth rates but high efficiency, and regions with high carbon emission growth rates but low efficiency. Some policy recommendations from the strong transportation strategy perspective were proposed to improve the carbon emissions efficiency of the logistics industry, especially for the second category of pilot regions. This study is expected to provide a basis for decision-making for efficient emissions reduction measures and policies, and to encourage the pilot regions to take the lead in achieving the goal of China’s strategy for transportation.

scholarly journals Spatial cluster and Heterogeneity Research on Energy-Related Carbon Emissions in Districts and Counties of Guangdong Province

2019 ◽  
Vol 79 ◽  
pp. 03019
Author(s):  
Wenxiu Wang ◽  
Shangjun Ke ◽  
Daiqing Zhao ◽  
Guotian Cai
Keyword(s):  
Spatial Autocorrelation ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Guangdong Province ◽  
Total Carbon ◽  
Low Carbon ◽  
Cluster Area ◽  
Reduce Emissions ◽  
Global Spatial Autocorrelation ◽  
High Cluster

Energy-related carbon emissions in districts and counties of Guangdong province from 2005 to 2016 are researched based on spatial econometrics method in this article, and significance cluster area and heterogeneity area are precise pinpointed. Conclusions are as follows: (1) total carbon emissions and per capita carbon emissions exist significance global spatial autocorrelation in the year 2005-2016, and formed significance high-high cluster area in districts and counties of Guangzhou city, Shenzhen city and Dongguan city. It also formed three significance low-low cluster areas in districts and counties of eastern, western and northern of Guangdong province. Low-high heterogeneity area and high -low heterogeneity area often appears in the scope of high-high cluster area and low-low cluster area. (2)Carbon emission intensity not exist significance global spatial autocorrelation, but exist significance cluster area and heterogeneity area in the ecological development areas of eastern, western and northern of Guangdong province. In the end, the paper puts forward the regional and detailed policy recommendations for efficient carbon emission reduction for each cluster type region: carbon high-high cluster areas are priority reduce emissions area, heighten energy saving technology and optimize industrial structure are two grippers to reduce emissions. Low - low carbon emissions concentrated area in western of Guangdong should primarily develop high and new technology industry. Low low carbon emissions concentrated areas and high - high carbon emissions intensity concentrated area for eastern and northern of Guangdong province should try hard to wins ecological compensation at the same time focus on developing ecological tourism.

scholarly journals How to Allocate Carbon Emission Permits Among China’s Industrial Sectors Under the Constraint of Carbon Intensity?

2019 ◽  
Vol 11 (3) ◽  
pp. 914 ◽  
Author(s):  
Jianguo Zhou ◽  
Yushuo Li ◽  
Xuejing Huo ◽  
Xiaolei Xu
Keyword(s):  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Abatement Cost ◽  
Carbon Intensity ◽  
Carbon Trading ◽  
Emission Permits ◽  
Carbon Abatement ◽  
Industrial Sectors ◽  
Ferrous Metals

With the official launch of China’s national unified carbon trading system (ETS) in 2017, it has played an increasingly important role in controlling the growth of carbon dioxide emissions. One of the core issues in carbon trading is the allocation of initial carbon emissions permits. Since the industry emits the largest amount of carbon dioxide in China, a study on the allocation of carbon emission permits among China’s industrial sectors is necessary to promote industry carbon abatement efficiency. In this study, industrial carbon emissions permits are allocated to 37 sub-sectors of China to reach the emission reduction target of 2030 considering the carbon marginal abatement cost, carbon abatement responsibility, carbon abatement potential, and carbon abatement capacity. A hybrid approach that integrates data envelop analysis (DEA), the analytic hierarchy process (AHP), and principal component analysis (PCA) is proposed to allocate carbon emission permits. The results of this study are as follows: First, under the constraint of carbon intensity, the carbon emission permits of the total industry in 2030 will be 8792 Mt with an average growth rate of 3.27%, which is 1.57 times higher than that in 2016. Second, the results of the carbon marginal abatement costs show that light industrial sectors and high-tech industrial sectors have a higher abatement cost, while energy-intensive heavy chemical industries have a lower abatement cost. Third, based on the allocation results, there are six industrial sub-sectors that have obtained major carbon emission permits, including the smelting and pressing of ferrous metals (S24), manufacturing of raw chemical materials and chemical products (S18), manufacturing of non-metallic mineral products (S23), smelting and pressing of non-ferrous metals (S25), production and supply of electric power and heat power (S35), and the processing of petroleum, coking, and processing of nuclear fuel (S19), accounting for 69.23% of the total carbon emissions permits. Furthermore, the study also classifies 37 industrial sectors to explore the emission reduction paths, and proposes corresponding policy recommendations for different categories.

scholarly journals Temporal-Spatial Differentiation and Optimization Analysis of Cultivated Land Green Utilization Efficiency in China

Land ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 158 ◽  
Author(s):  
Qianru Chen ◽  
Hualin Xie
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Spatial Differentiation ◽  
Utilization Efficiency ◽  
Added Value ◽  
Scale Model ◽  
Eastern Region ◽  
Cultivated Land ◽  
Land Utilization ◽  
Extension System

Cultivated land is closely related to national food security, rural economic development and social stability. The cultivated land pollution and carbon emissions caused by chemical fertilizers, pesticides, film residues, etc., in the process of cultivated land utilization pose a serious threat to the cultivated land ecosystem in China. The comprehensive analysis on the cultivated land green utilization efficiency (GUECL), its influencing factors, and optimization direction provides a valuable basis for the green utilization of cultivated land. Based on a panel data of 30 provinces (cities or districts) in China from 2001 to 2016, the GUECL in China under the constraints of pollution and carbon emissions was measured by using a super-efficient SBM-VRS (slack based model-variable return to scale) model. The influencing factors and optimization directions of the GUECL were analyzed through the Tobit model and slack values, respectively. The results show that the GUECL in China rose with fluctuations from 2001 to 2016. Since 2014, the eastern region has surpassed the western region and has become the region with the highest mean GUECL value. The room for resource conservation and pollution reduction varies in different regions of China. Farmers’ dependence on cultivated land and agricultural added value are positively related to the GUECL in China. Farmers’ occupational differentiation, agricultural machinery density, and agricultural disaster rate have had negative effects on the GUECL in China. The loss of the GUECL in China is mainly due to the redundancies of land input, pollution emission, and mechanical input. By analyzing these influencing factors and optimization directions, it is concluded that improving rural land transfer market and agricultural infrastructure construction, establishing a new agricultural technology extension system, and vigorously cultivating new professional farmers are the targeted measures to improve the GUECL.

Research on the Relationship between Economic Growth, Environmental Governance Investment and Carbon Emission--Based on the Time Series Data from 2000 to 2019

2020 ◽  
pp. 713-727
Author(s):  
Xiaohui Wang, Xin Zhang
Keyword(s):  
Economic Growth ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Carbon Emission ◽  
Environmental Governance ◽  
Time Series Data ◽  
Series Data ◽  
Per Capita ◽  
The Relationship

The study on the relationship between investment in environmental governance, carbon emission and economic growth is helpful for the relevant government departments to coordinate the influence among them when formulating the policies of reducing emission and conserving energy, so as to take the comparative advantages of various factors and promote the benign interaction between economic development and environmental governance. In this paper, the data of Per capita GDP, per capita investment in environmental governance and per capita CARBON dioxide emissions in China from 2000 to 2019 are selected as the research basis, and variables are studied by means of Granger causality and impulse response function. As shown in the results, there is a single Granger relationship between investment in environmental governance and carbon emissions, that is, the increase of investment in environmental governance leads to the reduction of carbon emissions. The influence of economic growth on environmental governance investment is small, but in the long term, it can restrain the growth of carbon emissions. Investment in environmental governance can promote economic growth and stimulate a reduction in the emissions in the short term; Economic growth was hindered by the emissions in the long term and fail to stimulate increased investment in environmental governance. Based on these findings, this paper proposes policy Suggestions for optimizing the structure of environmental governance investment, improving the carbon emission monitoring and response mechanism, and strengthening the technological level of energy conservation and emission reduction.

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