Emission reduction policy: A regional economic analysis for China

Chen, Anping; Groenewold, Nicolaas

doi:10.1016/j.econmod.2015.08.001

Cited by 23 publications

(3 citation statements)

References 46 publications

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“…However, our findings are different from some of the other research. Some existing studies on carbon reduction are interested in environment curve tests, policy tools [58,59], stochastic frontier models, and LMDI-PDA decomposition methods [60,61], and they involve comparisons among some provinces in China, metropolitan areas, and economic belts [62,63]. Hu et al [64], by sampling panel data from the Chinese provinces along the Yangtze River Economic Belt during 1998-2018, investigated carbon emissions from railway, highway, airline, and water transportation, and showed that the emissions were higher in eastern and western China than in central China.…”

Section: Discussionmentioning

confidence: 99%

Improving Transportation Technologies for Carbon Reduction in the Chinese Provinces along the Silk Road

Zhang

Sakata

Long³

2022

Energies

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As an economic corridor, the Silk Road Economic Belt (SREB) connects the East to Western nations, where carbon emissions are gradually becoming severe. This study aims to provide solutions for dealing with carbon emissions from the transportation of the SREB in the Chinese range. By employing the Malmquist index method of data envelopment analysis (DEA), this study develops models to test the different carbon-reduction performances (CRP) of transportation in the Chinese provinces along the SREB. This study shows that carbon-reduction performance has improved since 2013 because of the improvements in transportation technology. Technical efficiency, including scale efficiency and pure technological efficiency, may improve carbon reduction, while the lagged technological progress restricts the CRP. It is further suggested that the provincial CRPs are different. The southwest provinces have the best decarbonization performance, followed by the northwest, while the northeast provinces, including Inner Mongolia, underperform compared to the others. Therefore, the government should release some technology-orientated policies as soon as possible to facilitate the improvements in technical efficiency and progress in transportation vehicles and infrastructures in order to consequently reduce carbon emissions.

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Section: Discussionmentioning

confidence: 99%

Improving Transportation Technologies for Carbon Reduction in the Chinese Provinces along the Silk Road

Zhang

Sakata

Long³

2022

Energies

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“…At present, China is under tremendous pressure because of its industrial effects in the context of the global climate crisis (Chen and Groenewold, 2015). Owing to the increasing awareness of climate change, the labeling scheme will drive enterprises to take action on product design and innovation to provide environmentally friendly products for consumers and thus gradually transform into green businesses (Dangelico and Pontrandolfo, 2010;Cohen and Vandenbergh, 2012;Zhao et al, 2012a).…”

Section: Policy Variable Category Diagram Functionmentioning

confidence: 99%

For the sustainable performance of the carbon reduction labeling policies under an evolutionary game simulation

Zhao

Zhou

Han

et al. 2016

Technological Forecasting and Social Change

141

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“…The most direct impact of this continuous increase in household consumption in China is to increase energy consumption and CO 2 emissions by the industrial production sector 2,3 . Since the reform and opening‐up implementation in 1978, China's CO 2 emissions had maintained a growth rate of about 5.8% per year 4 . In 2008, China surpassed the United States as the world's largest energy consumer and the largest CO 2 emitter 5–7 .…”

Section: Introductionmentioning

confidence: 99%

Exploring the characteristics and drivers of indirect energy consumption of urban and rural households from a sectoral perspective

Xi-yu

et al. 2020

Greenhouse Gases

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China is actively taking measures to guide the household energy-saving consumption pattern because the total household indirect energy consumption and CO 2 emissions have rapidly multiplied from 2002 to 2017 with an annual growth rate of 5.95%, and 5.56%, respectively. This paper calculates indirect energy consumption and CO 2 emissions by four energy sources (raw coal, crude oil, natural gas, and electricity), analyzes the energy structure, and conducts a structural decomposition analysis in urban and rural areas in China from 2002 to 2017. The results reveal that the indirect energy consumption and CO 2 emissions of urban households was 3.84 and 3.80 times, respectively, that of rural households in 2017 with most contributions from the 'Agriculture, Forestry, Animal Husbandry, and Fishery', 'Foods and Tobacco', and 'OTHERS' sectors. The energy consumption structure has changed. The percentage of coal consumption falls from 66.87% to 57.62%. Electricity consumption, ranked second, increased substantially from 10.77% to 22.90%. The key sectors of the energy mix have been found to help energy conservation. The high indirect energy consumption sectors with higher indirect energy intensity are the key sectors, especially the 'Processing of Petroleum, Coking and Processing of Nuclear Fuel' and 'Production and Supply of Electric Power and Heat Power'. The consumption structure effect is more obvious in urban areas than in rural areas. In the process of urbanization, its effect has little impact on urban indirect energy consumption. It implies that the focus is on optimizing consumption structure rather than reducing consumption scale.

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Emission reduction policy: A regional economic analysis for China

Cited by 23 publications

References 46 publications

Improving Transportation Technologies for Carbon Reduction in the Chinese Provinces along the Silk Road

Improving Transportation Technologies for Carbon Reduction in the Chinese Provinces along the Silk Road

For the sustainable performance of the carbon reduction labeling policies under an evolutionary game simulation

Exploring the characteristics and drivers of indirect energy consumption of urban and rural households from a sectoral perspective

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