Dr. Jasper Verschuur

Infrastructure systems are particularly vulnerable to climate hazards, such as flooding, wildfires, cyclones and temperature fluctuations. Responding to these threats in a proportionate and targeted way requires quantitative analysis of climate risks, which underpins infrastructure resilience and adaptation strategies. The aim of this paper is to review the recent developments in quantitative climate risk analysis for key infrastructure sectors, including water and wastewater, telecommunications, health and education, transport (seaports, airports, road, rail and inland waterways), and energy (generation, transmission and distribution). We identify several overarching research gaps, which include the (i) limited consideration of multi-hazard and multi-infrastructure interactions within a single modelling framework, (ii) scarcity of studies focusing on certain combinations of climate hazards and infrastructure types, (iii) difficulties in scaling-up climate risk analysis across geographies, (iv) increasing challenge of validating models, (v) untapped potential of further knowledge spillovers across sectors, (vi) need to embed equity considerations into modelling frameworks, and (vii) quantifying a wider set of impact metrics. We argue that a cross-sectoral systems approach enables knowledge sharing and a better integration of infrastructure interdependencies between multiple sectors.

Disruptions to ports from climate extremes can have systemic impacts on global shipping, trade and supply chains. By combining estimated climatic-related port downtime at 1,320 ports with a global model of transport flows, we pinpoint systemic risks to global maritime transport, trade and supply-chain networks. We estimate a total of US81 billion of global trade and at least US122 billion of economic activity being at-risk on average annually.

Despite their economic importance, the risk that ports face from multiple natural hazards has not yet been monetised on a global scale. Here, we perform an asset-level risk analysis of global port infrastructure from multiple hazards, quantifying the risk to physical asset damages and logistics services (i.e. port-specific risk) and maritime trade flows at-risk (i.e. trade risk). We find that 86% majority of ports are exposed to more than three hazards. Globally, port-specific risk totals 7.5 USD bn per year, with 32% of the risk attributed to tropical cyclone impacts. In addition, 63.1 USD bn of trade is at-risk every year, with trade risk as a fraction of total trade being particularly high in Small Island Developing States. Our result underline that port resilience is determined by various critical factors, such as engineering standards, operational thresholds, recovery duration, that vary widely across ports, requiring tailored solutions to improve port resilience.

Ports are embedded in different networks, including the local critical infrastructure network, the regional hinterland transport network and the global maritime transport network. These networks are exposed to a variety of natural hazards, which cause disruptions that can propagate to other network components, resulting in wider supply chain losses. However, the risks of such indirect network disruptions, or systemic risks, are often not considered in risk analyses of ports. We propose a systemic risk framework for different networks interconnected through ports, and describe the state-of-the-art risk modelling approaches to quantify systemic risks. In addition, we present a port risk layering framework that can help identify how resilience against systemic risks can be improved. As climate change will likely increase the occurrence of natural hazards to ports and transport networks, efforts to enhance system-wide resilience should be considered, alongside port adaptation, to prevent exacerbation of supply chain losses in the future.

We quantify the criticality of the world’s 1300 most important ports for global supply chains by predicting the allocation of trade flows on the global maritime transport network, which we link to a global supply-chain database to evaluate the importance of ports for the economy. We find that 50% of global trade in value terms is maritime, with low-income countries and small islands being 1.5 and 2.0 times more reliant on their ports compared to the global average. The five largest ports globally handle goods that embody >1.4% of global output, while 40 ports add >10% of domestic output of the economies they serve, predominantly small islands. We identify critical cross-border infrastructure dependencies for some landlocked and island countries that rely on specific ports outside their jurisdiction. Our results pave the way for developing new strategies to enhance the resilience and sustainability of port infrastructure and maritime trade.

The implementation of large-scale containment measures by governments to contain the spread of the COVID-19 virus has resulted in large impacts to the global economy. Here, we derive a new high-frequency indicator of economic activity using empirical vessel tracking data, and use it to estimate the global maritime trade losses during the first eight months of the pandemic. We go on to use this high-frequency dataset to infer the effect of individual non-pharmaceutical interventions on maritime exports, which we use as a proxy of economic activity. Our results show widespread port-level trade losses, with the largest absolute losses found for ports in China, the Middle-East and Western Europe, associated with the collapse of specific supply-chains (e.g. oil, vehicle manufacturing). In total, we estimate that global maritime trade reduced by -7.0% to -9.6% during the first eight months of 2020, which is equal to around 206–286 million tonnes in volume losses and up to 225–412 billion USD in value losses. We find large sectoral and geographical disparities in impacts. Manufacturing sectors are hit hardest, with losses up to 11.8%, whilst some small islands developing states and low-income economies suffered the largest relative trade losses. Moreover, we find a clear negative impact of COVID-19 related school and public transport closures on country-wide exports. Overall, we show how real-time indicators of economic activity can inform policy-makers about the impacts of individual policies on the economy, and can support economic recovery efforts by allocating funds to the hardest hit economies and sectors.

Guan and colleagues used a model of the global economy to quantify the impacts of the coronavirus disease 2019 (COVID-19) pandemic under different scenarios of pandemic spreading and lockdown stringencies. Using real-time ship tracking data from before and during the pandemic, we show how the onset of disruption to trade was slower than modelled by Guan et al. Whereas supply chains to some countries with strong trading links to China (for example, Australia and Malaysia) have been affected in ways that resemble the results of their model (although to a lower extent than predicted), others with equally strong links (for example, Vietnam) have managed to increase their trade, contrary to the model’s predictions. Understanding the propagation of the economic shock from COVID-19, which can be informed by real-time observations as well as model predictions, will help to better allocate international aid and economic stimuli.

Ports are located in low-lying coastal and riverine areas making them prone to the physical impacts of natural disasters. The consequential disruptions can potentially propagate through supply chains, resulting in widespread economic losses. Previous studies to quantify the risks of port disruptions have adopted various modelling assumptions about the resilience of individual ports and marine network logistics. However, limited empirical evidence is available to validate these modelling assumptions or to provide deeper understanding of the ways in which operations are adapted during and after disruptions. Here, we use vessel tracking data to analyse past port disruptions due to natural disasters, evaluating 141 incidences of disruptions across 74 ports and 27 disasters. Results show a median disruption duration of six days with a 95th percentile of 22.2 days. All analysed events show multiple ports being affected simultaneously, challenging some of the studies that only focus on single port disruptions. Moreover, we find that the duration of the disruption scales with the severity of the event, with an increment of 1.0 m storm surge or 10 m/s wind speed associated with a two day increase in disruption duration. In contrast to commonplace assumptions in model studies, substitution between ports is rarely observed during short-term disruptions. On the other hand, production recapture happens in practice in many cases of port disruptions. In short, empirical vessel tracking data provides valuable insights for future modelling studies in order to better approximate the extent of the disruption and the potential resilience of the port and maritime network.

Quantified flood risk assessments focus on asset losses, neglecting longer-term impacts to household welfare via income and consumption losses. The extent of welfare losses depends upon resilience – the ability to anticipate, resist, cope, recover and learn from a shock. Here, we use a novel welfare loss modelling framework and perform a high-resolution spatial analysis in coastal Bangladesh to quantify welfare losses from a tropical cyclone under present and future climatic and socio-economic conditions. We further test various adaptation options that are intended to enhance resilience. Results show that poor households experience, on average, 7% of the asset losses, but 42% of the welfare losses. Combining dike heightening, post-disaster support and stronger housing can reduce welfare losses by up to 70%, and foster sustainable development by benefitting the poor, increasing resilience and demonstrating robustness under socio-economic and climatic uncertainties. Thus, a welfare-orientated perspective helps to identify adaptation options that enhance resilience and leave no-one behind.