Modelling the impact of liner shipping network perturbations on container cargo routing: Southeast Asia to Europe application

Understanding how container routing stands to be impacted by different scenarios of liner shipping network perturbations such as natural disasters or new major infrastructure developments is of key importance for decision-making in the liner shipping industry. The variety of actors and processes within modern supply chains and the complexity of their relationships have previously led to the development of simulation-based models, whose application has been largely compromised by their dependency on extensive and often confidential sets of data. This study proposes the application of optimisation techniques less dependent on complex data sets in order to develop a quantitative framework to assess the impacts of disruptive events on liner shipping networks. We provide a categorization of liner network perturbations, differentiating between systemic and external and formulate a container assignment model that minimises routing costs extending previous implementations to allow feasible solutions when routing capacity is reduced below transport demand. We develop a base case network for the Southeast Asia to Europe liner shipping trade and review of accidents related to port disruptions for two scenarios of seismic and political conflict hazards. Numerical results identify alternative routing paths and costs in the aftermath of port disruptions scenarios and suggest higher vulnerability of intra-regional connectivity

Review of Well-to-Wheel lifecycle emissions of liquefied natural gas heavy goods vehicles

It has been suggested that using liquefied natural gas as a fuel source for heavy goods vehicles could provide a reduction in greenhouse gas emissions. Various studies have investigated different aspects of the lifecycle emissions of natural gas heavy goods vehicles throughout the past decade, however, there has been little comparative analysis across these studies. This review provides a comprehensive examination of the well-to-wheel lifecycle emissions of liquefied natural gas for heavy goods vehicles in comparison to diesel, the current standard. A systematic selection criteria based on relevance to the defined well-to-wheel system boundary of liquefied natural gas as a fuel source for heavy goods vehicles, including greenhouse gas emissions, were augmented by the authors knowledge of the field. The various data are categorised by engine technology and model year (pre- and post-2015), average speed of the duty cycle, and then statistically analysed to identify clear trends and correlations in the emissions produced. The two primary factors affecting the well-to-wheel greenhouse gas emissions of natural gas heavy hoods vehicles are: (i) natural gas engine fuel efficiency relative to diesel, and (ii) methane leakage across the supply chain. Methane leakage rates are a significant uncertainty and range from 0.3 to 20 % of throughput. With long-term perspective of efficiency penalty (10 %) in natural gas engines, the well-to-wheel greenhouse gas emissions reduction of natural gas fuelled trucks against diesel is up to 10 %, which appears insufficient toward net zero emissions by 2050. The use of biomethane further reduces the greenhouse gas emissions by 34–66 % depending on the engine technology. Controlling fugitive methane emissions in the fuel production and supply chain remains critical

Natural gas fuel and greenhouse gas emissions in trucks and ships

Natural gas is a transport fuel which may help reduce greenhouse gas emissions in shipping and trucks. However, there is some disagreement regarding the potential for natural gas to provide significant improvements relative to current ships and trucks. In 2015, road freight represented ~7% of global energy related CO2 emissions, with international shipping representing ~2.6% of global emissions. These emissions are also expected to grow, with some estimates suggesting road freight emission growing by a third, and shipping emissions growing by between 50% and 250% from 2012 to 2050, making absolute emissions reductions challenging. In addition, reducing emissions in ships and trucks has proved technically difficult given the relatively long distances that ships and trucks travel. This paper documents a systematic review of literature detailing well-to-wheel/wake greenhouse gas emissions and economic costs in moving from diesel and heavy fuel oil to natural gas as a fuel for trucks and ships. The review found a number of important issues for greenhouse gas reduction. First, moderate greenhouse gas reductions of 10% were found when switching to natural gas from heavy fuel oil in shipping when comparing the lowest estimates. Comparing lowest well-to-wheel greenhouse gas emissions estimates for trucks, the benefit of switching to natural gas fuel is approximately a 16% reduction in greenhouse gas emissions. However, these emissions are highly variable, driven particularly by methane emissions in exhaust gas. Given this, in the worst cases natural gas ships and trucks emit more greenhouse gasses than the diesel trucks and heavy fuel oil ships that they would replace. It appears relatively cost effective to switch to natural gas as a transport fuel in ships and trucks. However, the limited emissions reduction potential raises questions for the ongoing role of natural gas to reduce greenhouse gas emissions in line with the challenging greenhouse gas reduction targets emerging in the transport sector

A quantitative framework for the assessment of transport vulnerability in container liner service networks

Access to the global container liner service network is vital to international trade. Disruptions to this network have major and immediate implications for consumers, industries, markets and national economies. The measurement and understanding of the existing liner service network performance susceptibility to disruptions (transport vulnerability) is therefore of critical importance to public and private stakeholders responsible for ensuring its operability and accessibility. Methodologies that assess transport vulnerability in liner service networks face two key modelling challenges: (i) A lack of historical disruption data on network components (such as ports, canals, and liner services) and (ii) the typical size of realistic liner service networks. The first challenge limits the implementation of methodologies that require prior knowledge of disruption probabilities to quantify the vulnerability of the network. The second challenge creates the need for models capable of capturing key industry practices such as transhipment, empty repositioning, and the ability of vessels to skip disrupted ports while still allowing implementations at realistic global scales. This study addresses the above-mentioned challenges by developing a quantitative framework capable of identifying critical components in large-scale networks with limited or unavailable historical disruption data. The proposed framework consists of a game-theoretic attacker-defender model (ADM) and a cost-based container assignment model (CBCAM) adapted for the analysis of networks under disruptions. The ADM consists of a two-player, zero-sum game between a malevolent agent (attacker) that seeks to maximise disruption costs and an ocean carrier (defender) that aims to minimise routing costs. The CBCAM is used to generate the payoff matrix of the game computing routing costs for the ocean carrier and disruption costs for the attacker on each of their available strategies. Linear program formulations of the joint AD-CBCAM allow for implementations on large-scale realistic liner service networks. This scalability is tested using CPLEX to solve network instances of up to 88 distinct liner services, 230 ports, and 2,648 OD pairs. Results allow establishing performance baselines and test the effectiveness of iterative interventions aimed at increasing the resilience of the system.Open Acces