Multi‐Scenario Carbon Peak Prediction for Aviation Logistics Based on an Extended <scp>STIRPAT</scp> Model: Empirical Analysis From Guangxi, China

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🔬研究者:The integrated LMDI-STIRPAT-scenario methodology provides a replicable framework for regional carbon peak studies in transport sectors.

🏢実務担当者:Regional aviation authorities and logistics firms can use the quantified reduction potentials (e.g., 1% energy intensity cut = 70.8 kt CO2) to prioritize efficiency investments.

🏛政策担当者:The finding that a rapid reduction strategy can shift peaking from 2041 to 2035 with 25.6% lower peak supports ambitious NDC updates and sectoral roadmaps.

ABSTRACT The aviation logistics industry is a significant contributor to global carbon emissions. Guangxi, a critical logistics corridor between China and ASEAN, faces severe challenges to regional carbon reduction targets due to the rapid development of its aviation sector. Existing research lacks systematic carbon emission predictions and multi‐scenario comparative analyses for such specific regions. This study integrates the Logarithmic Mean Divisia Index (LMDI) decomposition method, an extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, and scenario analysis to uncover the historical driving mechanisms of carbon emissions in Guangxi's aviation logistics industry and to forecast its peaking prospects and emission reduction potential under different development pathways until 2045. The findings reveal that: (1) historical growth was primarily driven by per capita GDP and population scale, while the industrial scale effect showed a significant inhibitory role; (2) elasticity analysis indicates that population scale, industrial scale, urbanization rate and transportation intensity are highly sensitive factors, whereas energy intensity is the only key technical variable with a significantly negative impact; (3) multi‐scenario simulations predict that emissions will peak around 2041 under the baseline pathway, but implementing a rapid carbon reduction strategy centred on enhancing energy efficiency could achieve peaking around 2035, reducing the peak by approximately 25.6%; (4) assessment of reduction potential further quantifies the outcomes of different choices, showing that a 1% reduction in energy intensity can mitigate about 70.8 thousand tons of Carbon Dioxide (CO 2 ), and shifting from a high‐development to a rapid carbon reduction pathway could cumulatively avoid about 3.7574 million tons of carbon emissions by 2045. This study confirms that for gateway hubs like Guangxi, a green growth pathway that utilizes technological innovation to absorb growth pressures is superior to mere economic contraction or disorderly expansion, providing a quantitative decision‐making basis for the low‐carbon transition of regional aviation industries.

• openalex https://doi.org/10.1002/gdj3.70089first seen 2026-07-29 05:21:02