Carbon-Emission Assessment of Regional Electric Vehicles From the Full Life Cycle Perspective

doi:10.12204/j.issn.1000-7229.2023.06.004

Abstract

Abstract:

“Carbon peaking” and “carbon neutrality” are important strategic decisions implemented by countries, and the development of electric vehicles is one measure of achieving low carbon emissions. This study proposes a regional-level method for assessing carbon emissions of electric vehicles from a full lifecycle perspective. This method addresses the one-sidedness and inaccuracies present in existing carbon emission assessments for electric vehicles. To evaluate the carbon emissions of electric vehicles throughout their life cycle, an evaluation index and a quantitative model, beginning from the material and fuel cycles, were constructed. Subsequently, a three-stage data envelopment analysis was employed to analyze the carbon emissions and obtain the carbon emission assessment results of all regional electric vehicles. The method was further applied at the provincial level using actual vehicle and development data from each province to evaluate the carbon emissions of electric vehicles in various provinces of China. The simulation results indicated significant differences in the carbon emission efficiency of provincial electric vehicles in China and demonstrated that the proposed evaluation method can eliminate random factor disturbances and comprehensively evaluate the carbon emissions of regional electric vehicles.

Key words: electric vehicles, carbon emission assessment, full life cycle, data envelopment analysis

CLC Number:

TM73

WANG Jiacheng, LIU Xiaofeng, MEI Wenqing, JI Zhenya, LIU Guobao. Carbon-Emission Assessment of Regional Electric Vehicles From the Full Life Cycle Perspective[J]. ELECTRIC POWER CONSTRUCTION, 2023, 44(6): 33-40.

Figures/Tables 11

Fig.1 Carbon emission assessment framework of electric vehicles from the perspective of full life cycle

Table 1 Parameters of carbon emission DEA of electric vehicles

Table 2 Descriptive statistical results of data

Fig.2 Mean values of carbon emission assessment parameters in each year

Table 3 Results of SFA regression analysis

Fig.3 Scatter plot of Sev in each province from 2016 to 2020

Table 4 Sev results before and after adjustment

Fig.4 Comparison of carbon emission assessment before and after adjustment

Table 5 Comparison of electric vehicle carbon emission assessment before and after adjustment in 2018

Fig.5 Carbon emissions per unit and income per capita

Table 6 Comparison of unit carbon emission and carbon emission performance of electric vehicles in 2020

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