Analysis on the influencing factors of carbon emission in China's logistics industry based on LMDI method

Quan, Chunguang; Cheng, Xingwang; Yu, Shuxia; Ye, Xin

doi:10.1016/j.scitotenv.2020.138473

Cited by 208 publications

(73 citation statements)

References 18 publications

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“… Wang and Jiang (2020) selected BRICS countries as object to investigate the impact of labor and investment on carbon emission by combining LMDI and C-D function. Besides, a lot of scholars put an eye on industrial carbon emission decomposition analysis, from manufacture ( Chontanawat et al, 2020 ), power sector ( Liao et al, 2019 ; Xie et al, 2019 ), agriculture ( Wen et al, 2019 ), logistics sector ( Quan et al, 2020 ), residential building sector ( Liang et al, 2019 ), transport sector ( Kim, 2019 ) and so on.…”

Section: Literature Reviewmentioning

confidence: 99%

Preventing carbon emission retaliatory rebound post-COVID-19 requires expanding free trade and improving energy efficiency

Wang

2020

Science of The Total Environment

121

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Existing studies have shown that the COVID-19 pandemic caused a sharp drop in carbon emissions in 2020. A recent example of the impact of sudden extreme events on carbon emissions occurred in the 2008 global financial crisis, in which carbon emissions droped in 2009, but jumped in 2010. This study is aimed to discuss how to prevent the retaliatory growth of carbon emissions post COVID-19 through learning the lessons from analysis of short-term and long-term drivers of carbon emissions. This study explored the short-term (annual) effects (population scale. affluence level, carbon intensity, energy intensity) of changes in carbon emissions by decomposing carbon emissions in the world, different income groups and selected countries before and after the 2008 financial crisis using LMDI technique. In addition, this study explored the long-term effects (energy consumption per capita, energy structure, energy intensity, foreign direct investment, and trade openness) of changes in carbon emissions by decomposing carbon emission in the world and different income groups from 1990 to 2014 using VAR technique. The decomposition results of short-term drivers of carbon emission uncovered that the deterioration in energy efficiency (increase in energy intensity) was the main reason for the retaliatory rebound in carbon emissions post-2008 financial crisis, especially in high-income countries. The decomposition results of long-term drivers of carbon emission uncovered that trade openness contributed to reduce carbon emission in the world and the incomes groups in the long term, although trade openness led to increase in carbon emission in developing countries in the short term. To prevent retaliatory rebound of carbon emissions, what we should learn two lessons from the decomposition of carbon emission: improving energy efficiency, and expanding trade openness. Unfortunately, energy efficiency has been neglected in the economic recovery plans to respond to COVID-19 of various countries, especially developed countries, and worse, trade protectionism is on the rise, especially in developed countries. Therefore, we are pessimistic about preventing a retaliatory rebound in carbon emissions post-COVID-19 for now.

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Section: Literature Reviewmentioning

confidence: 99%

Preventing carbon emission retaliatory rebound post-COVID-19 requires expanding free trade and improving energy efficiency

Wang

2020

Science of The Total Environment

121

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“…The existing research found that the capital stocks and energy consumption in the logistics industry are the main sources of carbon emissions, which increase the CO 2 emissions [ 4 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ]. The factors that reduce the CO 2 emissions are adjustments to the energy structure and reductions of the carbon emissions intensity [ 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ]. Additionally, the logistics industry is characterized by regional synergy and differentiation, therefore it is necessary to utilize local area advantages and optimize the layout of the logistics industry.…”

Section: Resultsmentioning

confidence: 99%

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

Jiang

Zhu

et al. 2020

IJERPH

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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.

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“…The main reason is that the economic effect has a large positive contribution. Therefore, future emission reduction measured in the XPCC could be implemented through the following two methods: one method is to reduce economic effect promotion, and emission reduction may be rationally planned through reducing the energy demand in economic production (Quan et al, 2020); the second approach is to increase the inhibitory effect of the energy structure, strengthen the construction of key energy-saving projects, and vigorously develop the circular economy and environmental protection industries, while much room remains for green economic development.…”

Section: Discussionmentioning

confidence: 99%

Carbon Emissions in the Xinjiang Production and Construction Corps and Driving Factors

et al. 2021

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Xinjiang production and Construction Corps (XPCC) is an important provincial administration in China and vigorously promotes the construction of industrialization. However, there has been little research on its emissions. This study first established the 1998-2018 XPCC subsectoral carbon emission inventory based on the Intergovernmental Panel on Climate Change (IPCC) carbon emission inventory method and adopted the logarithmic mean Divisia indexmethod (LMDI) model to analyze the driving factors. The results revealed that from 1998 to 2018, the total carbon emissions in the XPCC increased from 6.11 Mt CO2 in 1998 to 115.71 Mt CO2 in 2018. For the energy structure, raw coal, coke and industrial processes were the main contributors to carbon emissions. For industrial structure, the main emission sectors were the production and supply of electric power, steam and hot water, petroleum processing and coking, raw chemical materials and chemical products, and smelting and pressing of nonferrous metals. In addition, the economic effect was the leading factor promoting the growth of the corps carbon emissions, followed by technical and population effects. The energy structure effect was the only factor yielding a low emission reduction degree. This research provides policy recommendations for the XPCC to formulate effective carbon emission reduction measures, which is conducive to the construction of a low-carbon society. Moreover, it is of guiding significance for the development of carbon emission reduction actions for the enterprises under the corps and provides a reference value for other provincial regions.

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Analysis on the influencing factors of carbon emission in China's logistics industry based on LMDI method

Cited by 208 publications

References 18 publications

Preventing carbon emission retaliatory rebound post-COVID-19 requires expanding free trade and improving energy efficiency

Preventing carbon emission retaliatory rebound post-COVID-19 requires expanding free trade and improving energy efficiency

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

Carbon Emissions in the Xinjiang Production and Construction Corps and Driving Factors

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