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Page 12 of 18 Tong et al. Carbon Footprints 2025;4:2 https://dx.doi.org/10.20517/cf.2024.44

focus on transforming the upstream material industry through a systematic transition toward a circular
economy, driven by downstream eco-design for low-carbon development.

Scenario comparison of different circular economy strategies
Figure 2 presents an illustration of the shifts in GHG emissions within China’s automobile manufacturing
sector across various scenarios. A notable challenge emerges in the form of the relentlessly expanding final
demand, posing a substantial barrier to the reduction of GHG emissions generated by this industry. When
juxtaposed with the baseline scenario in 2018, where emissions stood at 434.76 million tons, it becomes
evident that a lack of a more progressive low-carbon transition or the development of a circular economy
could lead to a dramatic escalation in overall emissions. Specifically, under a scenario that merely accounts
for a low-carbon energy transition without addressing the underlying demand growth, emissions are
projected to soar to 734.56 million tons. This finding resonates with prior research that examined the
[59]
rebound effects of new energy vehicle development from a macroeconomic perspective. The research
underscores that, even as the adoption of new energy vehicles increases, the overall lifecycle energy
consumption may shift upstream within the supply chain. Consequently, merely transitioning to cleaner
energy sources within the automotive sector is not sufficient to mitigate emissions comprehensively. It
necessitates a holistic approach that encompasses the entire production chain, including upstream
processes, to effectively curb the rise in GHG emissions.

Secondly, in contrast to the baseline scenario, a progressive low-carbon energy transition stands out as the
most impactful measure in reducing GHG emissions from China’s automobile manufacturing sector, with
the potential to contribute to approximately 60% of the total emission reduction. Assuming the same level of
automobile production output in 2030, this transition could lead to a substantial decrease in total GHG
emissions, slashing them by around one-third compared to 2018 levels. The significance of a low-carbon
energy transition extends beyond the manufacturing phase; it also plays a pivotal role in reducing emissions
during the use stage of automobiles, particularly for electric vehicles. Consequently, our study reinforces the
current strategic direction of the automobile industry and national policies that prioritize low-carbon
[18]
energy transitions . This alignment underscores the critical importance of adopting comprehensive and
forward-thinking approaches to mitigate the environmental impact of the automobile sector. In essence, a
robust commitment to low-carbon energy transitions is not just a desirable goal for one sector, but a
necessity for achieving significant GHG emission reductions through systemic transformation toward low-
carbon energy infrastructure.

Thirdly, our research results show significant potential in the circular economy to further reduce GHG
emissions induced by automobile manufacturing. In the scenario of closed-loop material recycling, with
only improving the recycling rate of steel and plastics, the total emission can be reduced up to about 10%
compared to the baseline scenario. The input-output table we used was made in 2018 when the market
share of electric vehicles was still very low in China. Therefore, the data do not illustrate the non-ferrous
metal used in battery production. However, according to the LCA of electric vehicles, battery production
accounts for a significant portion of emissions, in which non-ferrous metals play a critical role in the supply
[16]
chain . The potential of closed-loop material recycling in the context of electrification of automobiles will
be even higher than our estimation.

Finally, the potential contribution of shared mobility to GHG emission reductions could range from 4% to
18%, contingent upon the extent to which it reduces vehicle demand. This estimation has considerable
uncertainty, primarily because the shifts in mobility patterns driven by autonomous driving technology are
currently difficult to predict with precision. Mainstream research suggests that shared mobility will lead to a