Ship-source greenhouse gas (GHG) emissions could increase by up to 250% from 2012 levels by 2050 owing to increasing global freight volumes. Binding international legal agreements to regulate GHGs, however, are lacking as technical solutions remain expensive and crucial industrial support is absent. In 2003, IMO adopted Resolution A.963 (23) to regulate shipping CO2 emissions via technical, operational, and market-based routes. However, progress has been slow and uncertain; there is no concrete emission reduction target or definitive action plan. Yet, a full-fledged roadmap may not even emerge until 2023. In this policy analysis, we revisit the progress of technical, operational, and market-based routes and the associated controversies. We argue that 1) a performance-based index, though good-intentioned, has loopholes affecting meaningful CO2 emission reductions driven by technical advancements; 2) using slow steaming to cut energy consumption stands out among operational solutions thanks to its immediate and obvious results, but with the already slow speed in practice, this single source has limited emission reduction potential; 3) without a technology-savvy shipping industry, a market-based approach is essentially needed to address the environmental impact. To give shipping a 50:50 chance for contributing fairly and proportionately to keep global warming below 2°C, deep emission reductions should occur soon.
The aim of this research/project is to investigate and analyze the opportunities and challenges of implementing AI technologies in general and in the transport and logistics sectors. Also, the potential impacts of AI at sectoral, regional, and societal scales that can be identified and chan- neled, in the field of transport and logistics sectors, are investigated. Special attention will be given to the importance and significance of AI adoption in the development of sustainable transport and logistics activities using intelligent and autonomous transport and cleaner transport modalities. The emphasis here is therefore on the pursuit of ‘zero emissions’ in transport and logistics at the urban/city and regional levels.Another goal of this study is to examine a new path for follow-up research topics related to the economic and societal impacts of AI technology and the adoption of AI systems at organizational and sectoral levels.This report is based on an exploratory/descriptive analysis and focuses mainly on the examination of existing literature and (empirical) scientific research publica- tions, previous and ongoing AI initiatives and projects (use cases), policy documents, etc., especially in the fields of transport and logistics in the Netherlands. It presents and discusses many aspects of existing challenges and opportunities that face organizations, activities, and individuals when adopting AI technology and systems.
