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Impact assessment of crude oil mix, electricity generation mix, and vehicle technology on road freight emission reduction in China

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Abstract

To achieve net zero emissions, the global transportation sector needs to reduce emissions by 90% from 2020 to 2050, and road freight has a significant potential to reduce emissions. In this context, emission reduction paths should be explored for road freight over the fuel life cycle. Based on panel data from 2015 to 2020 in China, China’s version of the GREET model was established to evaluate the impact of crude oil mix, electricity mix, and vehicle technology on China’s reduction in road freight emissions. The results show that the import share of China’s crude oil has increased from 2015 to 2020, resulting in an increase in the greenhouse gas (GHG) emission intensity of ICETs in the well-to-tank (WTT) stage by 7.3% in 2020 compared with 2015. Second, the share of China’s coal-fired electricity in the electricity mix decreased from 2015 to 2020, reducing the GHG emission intensity of battery electric trucks (BETs), by approximately 6.5% in 2020 compared to 2015. Third, different vehicle classes and types of BETs and fuel cell electric trucks (FCETs) have different emission reduction effects, and their potentials for energy-saving and emission reduction at various stages of the fuel life cycle are different. In addition, in a comparative study of vehicle technology, the results show that (1) for medium-duty trucks (MDTs) and heavy-duty trucks (HDTs), FCETs have lower GHG emission intensity than BETs, and replacing diesel-ICETs can significantly reduce GHG emissions from road freight; (2) for light-duty trucks (LDTs), BETs and FCETs have the highest GHG emission reduction potential; thus, improving technologies such as electricity generation, hydrogen fuel production, hydrogen fuel storage, and transportation will help to improve the emission reduction capabilities of BETs and FCETs. Therefore, policymakers should develop emission standards for road freight based on vehicle class, type, and technology.

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Data availability

Data will be made available upon request.

Abbreviations

BET:

Battery electric truck

EC:

Energy consumption

FCEV:

Fuel cell electric vehicle

GREET:

Greenhouse gases, regulated emissions, and energy use in transportation

GWP:

Global warming potential

ICET:

Internal combustion engine truck

IEA:

International Energy Agency

LCA:

Life cycle assessment

MDT:

Medium-duty truck

WTT:

Well-to-tank

BEV:

Battery electric vehicle

FCET:

Fuel cell electric truck

GHG:

Greenhouse gas

GVWR:

Gross vehicle weight rating

HDT:

Heavy-duty truck

ICEV:

Internal combustion engine vehicle

IPCC:

Intergovernmental Panel on Climate Change

LDT:

Light-duty truck

TTW:

Tank-to-wheel

WTW:

Well-to-wheel

References

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Funding

The research was supported by the Education Department of Shaanxi Province of China (No. 19JK0789) and the Nanjing University of Information Science & Technology of China (No. 2020r038).

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Authors and Affiliations

Authors

Contributions

Zhijuan Jiang: literature search and data analysis, conceptualization, investigation, methodology, software; visualization; writing—original draft, reviewing, and editing. Rui Yan: literature search and data analysis, writing—reviewing and editing. Zaiwu Gong: investigation, writing—reviewing and editing. Gaofeng Guan: investigation, writing—reviewing and editing.

Corresponding author

Correspondence to Zhijuan Jiang.

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Competing interests

The authors declare no competing interests.

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Responsible Editor: Philippe Garrigues

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Appendix

Appendix

Table

Table 5 Crude oil quality by region and shipping distance to Dalian Port, China

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Table

Table 6 Energy consumption (MJ/MJ), energy efficiency, and GHG emissions (g CO2 eq/MJ) of electric energy in the WTT stage under the electricity mix scenario of China from 2015 to 2020

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Table

Table 7 Energy consumption (MJ/MJ), energy efficiency, and GHG emissions (g CO2 eq /MJ) of diesel fuel in the WTT stage under the crude oil scenario of China from 2015 to 2020

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Table

Table 8 Energy consumption (MJ/MJ), energy efficiency, and GHG emissions (g CO2 eq/MJ) of hydrogen fuels in the WTT stage in 2020

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Table

Table 9 Energy consumption (MJ/tonne∙km) of various trucks during the WTW stage

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Table

Table 10 GHG emissions (g CO2 eq/tonne∙km) of various trucks during the WTW stage

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Jiang, Z., Yan, R., Gong, Z. et al. Impact assessment of crude oil mix, electricity generation mix, and vehicle technology on road freight emission reduction in China. Environ Sci Pollut Res 30, 27763–27781 (2023). https://doi.org/10.1007/s11356-022-24150-x

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  • DOI: https://doi.org/10.1007/s11356-022-24150-x

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