Poo, CP (2020) Climate change adaptation for seaports and airports. Doctoral thesis, Liverpool John Moores University.

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Abstract

Seaports and airport systems, being crucial nodes in international supply chains with high similar operational functions, are highly vulnerable to the risks that climate change poses to their infrastructure and operations. Transportation systems’ inability to adapt to climate change risk would result in a severe blow to economic prosperity and human welfare. It is now too late to avoid all harmful effects posed by climate change, not least due to the uncertainties on how they should be addressed. Policymakers and stakeholders must thoroughly understand potential climate change risks on seaports and airports, and undertake appropriate adaptation planning and strategies to tackle them. However, until now, there are inadequate works on reducing the uncertainties of decision-making when dealing with climate change and its impacts on human welfare. With the occurrence of increasingly frequent and severe climate-related events, adapting to the impacts posed by climate change has been a pivotal research topic influencing transport operation, infrastructure, planning and policymaking in recent decades. As most studies on climate change still focus on its short-term impacts, there is insufficient research on how to systematically adapt to the effects of climate change on transportation, in particular in the critical nodes of transport system, e.g., seaports and airports. Hence, it urgently requires illustrating the status quo regarding long-term risks posed by climate change on seaports and airports, including detailed analyses of the current measures and dilemmas in handling the issues of climate change and adaptation of planning to provide competent advice with seaport and airport stakeholders. Over the past few years, the focus on climate change study has switched from just mitigation to both mitigation and adaptation. As global warming is still unstoppable, and it brings more extreme weather, accidents and failures become more frequent. Moreover, losses and fatalities are more severe. In the past two decades, several weather-related severe events have caused significant economic loss. In 2005, Hurricane Katrina in the United States was one of the deadliest hurricanes (CNN, 2017b). In 2011, Tohoku, Japan, a Tsunami destroyed several provinces (CNN, 2017a). It brought more than 15,000 deaths, and about 230,000 people lost their homes. In 2011, Missouri experienced the deadliest U.S. tornadoes, which killed 161 people (Wheatley, 2013). In 2012, Louisiana, Mississippi, Alabama and Arkansas faced an intense and rainy Hurricane Issac which cost $2.0 billion regarding insured loss and left more than 644,000 people without power (Castellano et al., 2012). In 2013, a two mile-tornado near Oklahoma City caused more than 50 deaths and destroyed many homes (Howell et al., 2013). During the 2017 Atlantic hurricane season, more than nine hurricanes threatened North America and Caribbean areas. Until October, storms, including the most potent Maria, brought more than 200 billion dollars in losses and 103 death toll in the U.S. (Vo and Castro, 2018). For instance, in 2018, Typhoon Mangkhut crashed into Asian countries by bringing high winds and storm surges to the coastal cities. Transportation is profoundly affected by extreme weather (Wallemacq et al., 2018). Seaports are the critical nodes of international supply chains and thus stand on the edge of social and economic disasters. Besides storms and flooding, the heatwave also presents a severe climate issue. In 2003, the heatwave in Central Europe caused the death toll of more than 70,000 (Bouchama, 2004). On the other hand, extreme and continuous heat can also damage road surfaces and distort rail lines (Sieber, 2013), and it affects the land transport connectivity of seaports. Apart from the heatwave, fog disrupts transportation services across the United Kingdoms (UK) (World Market Intelligence News, 2015). Therefore, climate change adaptation planning for seaports and airports is critical to visualise the climate risks of passengers and goods from different extreme weather events (EWEs). As the seaports and airports are hubs in the global network, climate impacts can be assessed locally and internationally. So, this thesis presents five main working packages for evaluating the climate impact with different perspectives. The Intergovernmental Panel on Climate Change (IPCC) is an international body for assessing the science related to climate change. Climate change adaptation is one of the critical studies by the IPCC working group II in the fifth Assessment Report (IPCC, 2014a). IPCC has undertaken thorough reviews on transport infrastructures and stated that transportation systems would face enormous challenges by the environment in the near future (2030-2040) and the long future (2080-2100), especially in developed cities. They have also indicated climate-related drivers of impacts for coastal zone systems and transportation systems. Coastal cities with extensive port facilities and large-scale industries are vulnerable to increased flood exposure. High-growth cities located in low-lying coastal areas are also at higher risk. There is a possibility of a nonlinear increase in coastal vulnerability over the next two decades. Especially in developed country cities, climate change also leads to potentially significant secondary economic impacts with regional and possibly global consequences for trade and business. Emergency response requires well-functioning transport infrastructure. Furthermore, IPCC finds that a changing climate leads to changes in EWEs in different sectors, including frequency, intensity, spatial extent, duration, and timing. It can result in unprecedented extreme weather and climate events (IPCC, 2012). Starting with an extensive literature review, this thesis proposes the five main research themes regarding academic journals on seaport and airport adaptation to climate change, addresses on climate change from international organisations, climate change adaptation reports in the United Kingdom, centrality assessment in maritime transportation, port disruption due to climate extremes, multiple-objective decision support for environmental sustainability in maritime industry, and Artificial Bee Colony (ABC) algorithm for vehicle routing problem and supply chain management. Literature shows that existing research on climate change is relatively scattered, lacking in leading journals, researchers and theories. Especially, climate adaptation planning is still at an embryonic stage that even transport planners who have taken countermeasures to minimise the impacts of climate change confront a few dilemmas remaining. Also, climate vulnerability assessments are still at a national and regional level, and the climate change impact on the global shipping network (GSN) has not been assessed yet. Based on the review, there are two focuses for the upcoming parts of the thesis, regional study and international study. The first part of the regional study is to explore a standardised conceptual framework for developing a Climate change risk indicator (CCRI) framework for climate adaptation of transportation critical infrastructures, including seaports and airports. The assessments by implying the CCRI framework enables research-informed policymaking on such a demanding and multi-discipline topic. Many climate assessments have been done for measuring climate vulnerabilities, and various climate adaptation measures have been proposed for reducing climate risks. However, few of them used quantitative approaches for climate risk evaluations in seaports and airports, and fewer on the provisions of CCRIs for comparing climate risks of different locations. Furthermore, climate change is a dynamic issue, requiring big objective data to support the analysis (e.g. monthly climate data on CCRIs) of climate threats and vulnerabilities. In this part, Fuzzy Evidence Reasoning (FER) is employed to evaluate the climate risks in seaports and airports because incomplete forecasting data are in place. The findings reveal that climate change risks are varied in different locations and different months. Nevertheless, the risk levels of seaports and airports in the future are assessed for observing the changes and informing policymaking. By integrating the CCRI framework with an expert-supported seaport vulnerability indicator framework in the North East United States, a Climate resilience indicator (CRI) framework is designed to access the climate resilience level by assessing the indicators on exposure, sensitivity, and adaptive capacity. The conceptual framework is then constructed by a nationwide survey among the seaport and airport stakeholders in the UK. It also illustrates an overall picture of current climate adaptation issues in both the seaport and airport domains by weighting the indicators in the framework. Then, the further comparative analysis takes place by comparing the results of both seaports and airports by the CCRI and CRI frameworks. Also, climate change adaptation reports of seaports and airports of the UK and peer-reviewed works of literature related to climate change adaptation are collected and summarised to present the differences between seaports and airports on climate adaptation issues. On the international side, the climate vulnerability of the whole shipping network is assessed by combining two assessments, centrality assessment and ship routing assessments. First, a centrality assessment of port cities by a novel multi-centrality-based indicator is implemented. Afterwards, the centrality assessment result has been used to analyse global climate vulnerabilities by a set of climate vulnerability and adaptation indices. These reveal that climate vulnerabilities are needed to be tackled within a “node” (seaport) and in the whole seaport network. Then, a shipping network model has been designed to find the optimum shipping route between ports, and changes in route selections based upon more port disruption days caused by extreme weather. The Artificial bee colony (ABC) algorithm, an optimisation algorithm based on the intelligent foraging behaviour of a bee swarm, is imparted in the model. The central ports, known as hubs, are found in the centrality assessment, are exclusively tested on changes to look at the sensitivity on shipping networks between continents. The routing problem is somewhat simpler for airports than seaports as the short-haul is under three hours, the medium-haul is three to six hours, long haul is six to twelve hours, and ultra-long-haul is over twelve hours. Comparing ultra-long-haul with more than 30 days for seaports, it is not necessary to implement the airline data to the routing model as the decision of flying is relatively binary. Therefore, airport network is dropped for network assessment. This research re-emphasises the importance of raising the awareness of the community’s consideration of the risks of climate change on seaports and airports and strives for useful risk analysis and adaptation planning to cope with them. Findings from this thesis show that the newly developed climate adaptation framework, together with the FER model and empirical case studies, has provided a pioneer trail in systematically evaluating climate risks in the whole British transport system. This work has great potential to be tailored for broader applications, offering useful recommendations and global references for climate adaptation in other regions. On the other hand, the international shipping network is assessed by a vessel routing model, together with centrality assessment and climate vulnerability index. This work has great potential to be tailored for more comprehensive assessments, offering global references for climate adaptation in other transportation systems, especially airports.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	Transportation; Climate change adaptation
Subjects:	T Technology > TC Hydraulic engineering. Ocean engineering T Technology > TD Environmental technology. Sanitary engineering
Divisions:	Maritime & Mechanical Engineering (merged with Engineering 10 Aug 20)
Date Deposited:	31 Jul 2020 14:33
Last Modified:	07 Sep 2022 15:54
DOI or ID number:	10.24377/LJMU.t.00013421
Supervisors:	Yang, Z, Delia, D and Qu, Z
URI:	https://researchonline.ljmu.ac.uk/id/eprint/13421

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