Regional differences and driving factors analysis of carbon emission intensity from transport sector in China

Liu, Jiaguo; Li, Sujuan; Ji, Qiang

doi:10.1016/j.energy.2021.120178

Cited by 170 publications

(73 citation statements)

References 48 publications

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“…(1) Total carbon emissions. This paper draws on the ideas of Liu et al ( 2021 ); the material balance algorithm is adopted to calculate the total carbon emissions according to formula ( 7 ): …”

Section: Model Construction and Variable Selectionmentioning

confidence: 99%

“…(2) The carbon emission intensity. The intensity of carbon dioxide emissions is the amount of CO 2 emissions per unit of GDP, and the calculation formula is total carbon dioxide emissions/GDP (Liu et al 2021 ).…”

Section: Model Construction and Variable Selectionmentioning

confidence: 99%

“…Knapp and Mookerjee (1996) believe that population is the reason for the growth of global CO 2 emissions. As the number of permanent residents reflects the actual population of the region, we follow the method of Liu et al (2021); the population is measured by the total resident population.…”

Section: Variable Selectionmentioning

confidence: 99%

See 2 more Smart Citations

Energy structure, digital economy, and carbon emissions: evidence from China

Yang

Ran

et al. 2021

Environ Sci Pollut Res

409

128

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As a new production factor, digitalization plays a vital role in society, economy, and the environment. Based on the expanded STIRPAT model, this paper empirically tests the impact of energy structure and digital economy on carbon emissions by panel data from 2011 to 2017 in 30 provinces of China. The results show that the energy structure mainly based on coal has a significant driving effect on carbon emissions. Compared with non-resource-based provinces, the increase of energy structure dominated by coal has a greater effect on carbon emission in resource-based provinces. It is worth noting that this kind of influence has a greater impact on the central region of China, followed by the western region and the eastern region. Besides, the digital economy has a significant moderating effect. With the development of digital economy, the impact of coal-based energy structure on carbon emissions is gradually decreasing. This effect is more significant in non-resource-based provinces and eastern China, but not significant in resource-based cities and central and western China.

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Section: Model Construction and Variable Selectionmentioning

confidence: 99%

Section: Model Construction and Variable Selectionmentioning

confidence: 99%

See 1 more Smart Citation

Energy structure, digital economy, and carbon emissions: evidence from China

Yang

Ran

et al. 2021

Environ Sci Pollut Res

409

128

View full text Add to dashboard Cite

show abstract

“…However, relatively speaking, the intensity of carbon emissions caused by energy is more representative and has been widely studied by scholars (Pan et al, 2019;Liu et al, 2021a). However, research on carbon emission intensity and ICT-related research is relatively rare, and we can only find some relevant evidence in some research on the industrial framework or emerging technology industry.…”

Section: Carbon Emission Intensities and Ict Sectorsmentioning

confidence: 99%

Assessing Embodied Carbon Emission and Its Intensities in the ICT Industry: The Global Case

2021

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With the intensification of globalization, the information and communication technologies (ICT) sector, as one of the emerging industrial sectors, has played an important role in reducing carbon emissions in regional trade and improving the energy efficiency of traded products. This article uses a multi-regional input-output (MRIO) model to explore the flow of embodied carbon emissions and embodied carbon emission intensities in the ICT sector triggered by trade in 15 major economies around the world from 2000 to 2014. The article further discusses the emission-reduction strategies of each ICT sector. The results show that: (1) The overall embodied carbon emissions of ICT have demonstrated a significant downward trend, but the proportion of embodied carbon emissions caused by trade is increasing; (2) The embodied carbon emissions in the ICT sector of most developed countries in 2014 are significantly lower than in 2000, but in developing countries such as China and India they show an upward trend during this period; (3) The ICT sector’s export embodied carbon emission intensity in Indonesia is much higher than that of other countries, and the embodied carbon emissions of ICT exported by Mexico have increased significantly; (4) The manufacture of computer, electronic and optical products (S1) is the main contributor to the ICT sector’s embodied carbon emissions, while import embodied carbon emission intensities among publishing activities (S2) are increasing significantly in most countries. The conclusion of this paper has important implications for how to reduce ICT’s embodied carbon emissions of major countries.

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“…A hybrid decomposition analysis framework is proposed by Xu et al [28] to analyze the growth sources of EU in the passenger transport sector, which concludes that transport service increase and transport structure shift are the main reasons for the increase in EU, while energy efficiency improvement is a major cause to counteract the increase. Employing the extended STIRPAT (stochastic impacts by regression on population, affluence, and technology) and GTWR (geographically and temporally weighted regression) model, Liu et al [29] investigate the influence of driving factors on the carbon emission intensity of China's transportation sector.…”

Section: Introductionmentioning

confidence: 99%

Embodied Energy Use in China’s Transportation Sector: A Multi-Regional Input–Output Analysis

Fang

et al. 2021

IJERPH

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Energy transition in the transport sector (TS) is important for the goals of achieving carbon peak by 2030 and carbon neutrality by 2060 in China. A number of scholars have conducted studies to identify the potential energy savings of the TS and to improve its energy efficiency. Most of them concentrate on the direct energy use (EU). The indirect EU along the supply chain of the TS is often neglected. In this paper, the direct and indirect energy use, i.e., the embodied EU, of China’s TS is measured by applying a multi-regional input–output (MRIO) model, where they are investigated from both the provincial and sectoral perspectives. Results show that intermediate use is the major driving force for the TS’s embodied EU in China. From the sectoral level, supply from sectors such as petroleum refining and coking and demand from the service sector are the main reasons of the TS’s embodied EU. From the provincial perspective, the TS’s embodied EU is driven by low transportation technologies in most provinces located in central and western China. By contrast, abundant economic and social activities are the primary reason for the TS’s embodied EU in most provinces in eastern China. In the terms of interprovincial transfer, the energy embodied in the TS flows from resource-intensive provinces located in central and western China to resource-deficient provinces in eastern China. In addition, a close geographical connection exists in the transfer. Finally, several strategies from the sectoral and provincial levels are provided for policymakers.

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Regional differences and driving factors analysis of carbon emission intensity from transport sector in China

Cited by 170 publications

References 48 publications

Energy structure, digital economy, and carbon emissions: evidence from China

Energy structure, digital economy, and carbon emissions: evidence from China

Assessing Embodied Carbon Emission and Its Intensities in the ICT Industry: The Global Case

Embodied Energy Use in China’s Transportation Sector: A Multi-Regional Input–Output Analysis

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