Sustainable Shift: Analyzing Drivers for Low-Carbon Transportation Adoption in California's Heavy-Duty and Off-Road Sectors

被引:3
|
作者
Chowdhury, Vuban [1 ]
Tuli, Farzana Mehzabin [1 ]
Mitra, Suman Kumar [1 ]
机构
[1] Univ Arkansas, Dept Civil Engn, Fayetteville, AR 72701 USA
关键词
low-carbon transportation; generative AI; California; heavy-duty vehicles; off-road equipment; sustainable transportation; VEHICLES; BEHAVIOR;
D O I
10.3390/su16051722
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The transportation sector stands out as a major challenge for California's transition to a more sustainable transportation system, as it accounts for most of the greenhouse gas emissions. This underscores the urgency for government agencies to take decisive action in promoting the adoption of low-carbon transportation (LCT) within the heavy-duty vehicle (HDV) and off-road equipment (ORE) sectors. This study employs content analysis to investigate the impact of behavioral factors, specifically awareness and impression, on LCT adoption within these sectors. The analysis results are refined using a generative artificial intelligence (AI) tool. The results indicate that awareness about LCT, in conjunction with factors such as government incentives and environmental considerations, positively influences the likelihood of adopting LCT. Moreover, the findings highlight the significant impact of financial barriers on small-fleet organizations, reflecting the inherent challenges these entities may encounter in adapting to significant changes. Conversely, technical barriers are particularly notable for adopters and larger organizations. These insights provide valuable guidance for government agencies to develop targeted strategies, including mandates and incentives, tailored to the specific needs of organizations within the HDV and ORE sectors. By addressing these barriers and fostering a supportive environment for sustainable practices, policymakers can accelerate California's transition toward a greener transportation landscape.
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页数:19
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