Maritime Transport is a vital sector for global trade and the world economy. Particularly for islands, there is also an important social dimension introduced since island communities strongly rely on the sector for connection with the mainland and transportation of goods and passengers. Furthermore, islands are exceptionally vulnerable to climate change, as sea-level rise and extreme events are expected to induce severe impacts. Such hazards are anticipated to also affect the operations of the Maritime Transport sector, either in port infrastructures or ships en route. The present study is an effort to comprehend better and assess the future risk of Maritime Transport disruption in six European islands and archipelagos and aims at supporting regional to local policy and decision-making. We employ state-of-the-art regional climate datasets and the widely used Impact Chain approach to identify the different components that might drive such risks. Larger islands (e.g., Corsica, Cyprus, and Crete) are found to be more resilient to the impacts of climate change on maritime operations. Our findings also highlight the importance of adopting a low-emission pathway since this will keep the risk of Maritime Transport disruption similar to present levels, with an even slightly decreased risk for some islands because of enhanced adaptation capacity and advantageous demographic changes.
Research Article
Maritime transport disruption risk for EU islands under a changing climate
https://doi.org/10.21203/rs.3.rs-2346923/v1
This work is licensed under a CC BY 4.0 License
Journal Publication
published 26 May, 2023
Read the published version in Euro-Mediterranean Journal for Environmental Integration →
Version 1
posted
You are reading this latest preprint version
climate change
impacts
maritime transport
blue economy
Mediterranean
islands
Maritime Transport is defined as the carriage of goods and passengers by sea-going vessels on voyages undertaken wholly or partly at sea. It is often considered the backbone of the world economy, with 80% of the global trade volume passing through ports (Asariotis and Benamara, 2012). At the same time, the sector itself contributes to global warming through its carbon emissions which are found to be nearly 3% of the global CO2-equivalent emissions (IMO, 2015). Nevertheless, compared to land and air transport, it is by far the most economically and ecologically effective mean of distributing goods globally. A changing climate is therefore expected to challenge Maritime Transport to adapt to future risks and, at the same time, lower its emissions.
Maritime Transport is one of the key European Union’s (EU) Blue Economy sectors since Europe is amongst the leading maritime centers in the world, with more than 300 major seaports along its coastline and controlling around one-third of the world’s merchant fleet[1]. For EU countries, ports are vital gateways, linking European transport corridors to the rest of the world. As 75% of European external trade transits through EU ports, the shipping sector plays a major role in connecting the European market with its trade partners. For some Mediterranean countries, including Cyprus, Greece and Malta, there is a significant direct contribution (3-10%) of the Maritime Transport sector to the total Gross Value Added (GVA) (Eurostat 2020). Giannakis et al. (2019) also highlight the strong backward linkages of the water transport sector in the EU economy. For example, in 2015, for every 1 million Euro increase in the final demand for the products and services of the sector, the total output increased by 2 million Euros. However, for every 1 million Euro increase in the final demand for the products and services of the sector, 23.7 t of NOx, 8.5 t of SOx, 2 t of PM10 and 1.8 t of PM2.5 are emitted, while the sector already creates the largest direct and indirect emissions across the EU. According to Eurostat (2020), the sector employs nearly 250,000 persons (or 0.1% of the EU-27 workforce). About 20% of the total employment in the EU shipping industry is shore-based, while the remaining 80% is based at sea.
Besides the transport of goods within the EU territories and overseas, the Maritime Transport sector is also vital for transporting passengers (residents and visitors) and the connection between different countries or between remote islands and the mainland. Therefore, there is an important social dimension of maritime services. The islands under consideration in the present study currently report about 40 million passengers per year, including tourists and permanent residents (Eurostat, 2020). In addition, according to pre-COVID-19 estimations, the Mediterranean was among the world’s fastest-growing cruise markets, with an actual capacity increase of about 10.2% per year (Cruise Industry News Annual Report, 2018).
The broader Mediterranean region is a climate change hot spot that warms faster than the global rates (Cramer et al., 2018; Zittis et al., 2022). At the same time, a general decline in total precipitation is evident for most of the region (Cherif et al., 2020). Regional climate projections based on multi-model ensembles indicate further warming by 2100 (Zittis et al., 2019; Cherif et al., 2020). This will be within the range of 1 and 5 °C with respect to the end of the previous century and is expected to be strongest during summer. A general drying (between 10 and 40%) is also inferred for the Mediterranean, particularly under high-forcing scenarios. For the Canary Islands, warming and drying of similar magnitude are expected by the end of the century (Expósito et al., 2015; Carrillo et al., 2022). Despite the identification of the region as a prominent climate change hot spot, the whole range of potential impacts on ports and ships operations has not been extensively explored so far.
Various climate change stressors can affect both harbour infrastructure and ships en route. For example, ports are strongly impacted by rising sea levels, affecting port facilities and increasing the risk of flooding (e.g., Torres et al., 2021). Global mean sea-level rise has accelerated in the last century and will likely rise by 0.43 to 0.84 m until 2100, depending on the emission scenario (Pörtner et al., 2019). Due to ocean dynamics and the Earth’s gravity field, there will also be regional differences in sea-level rise in the order of 0.1 m (Asariotis and Benamara, 2012). Seaports generally are resilient to sea level rise plus storm surges under one meter and can operate without major interruptions by adopting soft adaptation strategies (Christodoulou and Demirel, 2017). Maritime Transport can also be affected by climate change through the increase in the intensity of extreme weather events, including tropical-like cyclones (Gaertner et al., 2007; Sánchez-Arcilla et al., 2016; González-Alemán et al., 2019; Hochman et al., 2021; Zittis et al., 2021a; Flaounas et al., 2022). According to climate projections, tropical cyclones are not expected to change significantly in frequency but in intensity due to rising sea-surface temperatures (Pörtner et al., 2019). For example, a doubling of Category 4 and 5 hurricanes in the Atlantic is expected by 2100 (Bender et al., 2010). The resulting extreme winds and waves can harm vessels but also cause damage and flooding of ports, especially in combination with sea-level rise (Hanson and Nicholls, 2012). For example, for the second half of the current century and under a business-as-usual pathway, such a combination is expected to cause an up to 66% increase in non-operability hours in northern Spain (Camus, 2019). The port processes affected by weather/climate hazards are dock flooding, basin agitation, port siltation, breakwater stability, overtopping and scouring (Sánchez-Arcilla et al. 2016).
In addition to the biophysical impacts related to weather and climate hazards, socio-economic impacts will likely be introduced (Léon et al., 2021). Such impacts can include an increase in users’ risk perception leading to lower rates of moorings and turnover, increased costs of maintenance in nautical installations and equipment, increased costs for new investment and insurance, carbon tax effects on fossil fuel prices, less turnover from Maritime Transport activities, and higher disruption costs. Most of these impacts and their economic value are still under investigation. Although some ports have already started to adapt to climate change (Becker et al., 2012; Ng et al., 2013, 2018), more investment from the public and private sectors is required (Monios and Wilmsmeier, 2020). This is particularly relevant for regional ports, such as those located on islands. Estimating the costs and effectiveness of adaptation measures depends on port location and is often difficult to assess. In most cases, the most effective adaptation measure would be to improve the flood resistance of transport infrastructure and increase the height of vulnerable ports (Yang et al. 2018).
Considering the importance of the sector and the lack of targeted impact studies in the broader Euro-Mediterranean region, our main objective is to provide a comprehensive framework to assess the risk of Maritime Transport disruption under present and future climate change conditions. The widely used Impact Chain approach is optimized and applied to six European islands or archipelagos that strongly rely on maritime means for transporting passengers and goods and are also common stops of leisure cruise ships. We also aim to decompose the different risk components and better understand the factors that drive future changes. Our framework is supported by state-of-the-art regional climate information and up-to-date socio-economic data. We focus primarily on large islands representative of the Mediterranean environment; nevertheless, European islands in the Atlantic Macaronesia are also considered (Figure 1). The list of case studies includes the Canary Islands, the Balearic Islands, Corsica, Malta (including Gozo and Comino), Crete, and Cyprus; however, our objective is to propose a framework that, with minor adjustments and availability of data, is transferable easily to other locations. The need for timely climate change mitigation efforts is investigated by comparing the results of a ‘business-as-usual’ scenario with a pathway closer to meeting the Paris Accord’s main targets (i.e., keeping global to less than 2 °C since the pre-industrial era). Finally, based on our results, we complement the discussion by proposing targeted adaptation measures for reducing the climate-driven risk of Maritime Transport disruption in the region of interest.
[1] https://ec.europa.eu/transport/modes/maritime/maritime-transport_en
2.1. Climate data
An important component of the present analysis is the climatic data used for the calculation of the hazard indicators. These include parameters such as sea-level rise, extreme winds and waves for historical and future climate projections. Near-surface wind data were obtained from a large ensemble of regional climate simulations performed under the Coordinated Regional Downscaling Experiment (CORDEX) (Giorgi and Gutowski, 2016). Information integrated for the European (EURO-CORDEX[2]) and the Middle East and North Africa (MENA-CORDEX[3]) domains of CORDEX was used for the Mediterranean and Atlantic regions, respectively, in a horizontal resolution of 0.11° (≈ 12 km) and 0.44° (≈ 50 km). More information on the simulations and domains’ extent can be found in Jacob et al. (2020), Obermann-Hellhund et al. (2018) and Zittis et al. (2021b). Extreme wave projections for the Mediterranean were available from the Med-CORDEX[4] initiative at a horizontal resolution of 0.11° (Ruti et al., 2016; Soto-Navarro et al., 2020). However, for the Canary Islands, located in the Atlantic Ocean, additional wave simulations were performed using the WaveWatchIII model (WW3DG, 2016), driven by meteorological input from the Hadley Centre Global Environmental Model (HadGEM). WaveWatchIII solves the random phase spectral action density balance equation for wavenumber-direction spectra. These simulations were performed at a horizontal resolution of 0.25°, covering a domain from 10 to 42°N and 70 to 5° W.
2.2. The Impact Chain Approach
Impact Chains (ICs) are an effective way to visually synthesize the complex relationships between Exposure (to mean climate conditions or hazards), Sensitivity (related to physical and socio-economic features), and Adaptive Capacity of a system under investigation. In more detail, an Impact Chain is an analytical tool that helps to better understand, systemize and prioritize the factors that drive vulnerability, and thus risk, in a system under review (GIZ 2017). This could be either a human or natural system. The concept of ICs was introduced by Schneiderbauer et al. (2013) and was refined by the German Cooperation for International Cooperation (GIZ) in their Vulnerability Sourcebook (Fritzsche et al., 2014). Impact Chains have since become more and more widely used as a climate risk assessment method at the regional-to-local level for research and decision-making support. Such successful examples include the assessment of climate change impacts in several socio-economic sectors, including agriculture, water and land resource management, tourism, as well as ecosystem-based adaptation (Hagenlocher et al., 2018; Arabadzhyan et al., 2020; Schneiderbauer et al., 2020; Léon et al., 2021; Zebisch et al., 2021).
The methodology can be used for both high-level identification of key risks as well as more in-depth analysis of specific risks and adaptation strategies. Some of the advantages of using this framework include its flexibility and simplicity in calculations, its applicability to different scales (from national to local), and the consideration of the entire planning cycle of the adaptation process (Zebisch et al., 2021). This can range from identifying the adaptation demand and selecting measures to monitor and evaluate the success of adaptation interventions in lowering vulnerability. Several variations of ICs have been proposed, however, in the present study, we apply the general framework presented in Zebisch et al. (2017) and Arabadzhyan et al. (2020), which makes the assessment approach with Impact Chains compatible with the concept of risk used in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC 2013). This conceptualization framework was adjusted for the risk of isolation due to Maritime Transport disruption (Figure 2) and was operationalized for the six EU islands and archipelagos under investigation (the Canary Islands, the Balearic Islands, Corsica, Malta, Crete, and Cyprus). The three main components drive risk are:
- Hazard, related to meteorological conditions, extreme weather, and changes in such physical phenomena due to global warming.
- Exposure, related to the presence of people, livelihoods, services, infrastructure, and economic, social or other assets.
- Vulnerability, related to the propensity or predisposition to be adversely affected. Vulnerability encompasses a variety of elements, including Sensitivity (i.e., susceptibility to harm) and Adaptive Capacity (i.e., lack of capacity to cope and adapt).
2.3 Description of indicators and scenarios
As depicted in Figure 2, several indicators have been identified for each component of risk. For climate change-driven hazards, we considered the regional mean sea-level rise (MSL), extreme waves (WaX98), and extreme wind (WiX98). The two extreme weather indicators (WaX98 and WiX98) were extracted from the 98th percentile of daily maximum values for each year. Exposure indicators include the number of passengers (NPax), islands’ total population (Npop), the value of transported goods expressed in total annual freight (VGTr), and the number of ports per island or archipelago (Npor). Indicators for sensitivity include the number of isolation days (NID) and the quality of port infrastructure (Nrni). Finally, for the component of adaptive capacity, the proposed indicators are the percentage of renewables contribution to energy production (PER), the existence and efficiency of early warning systems (EWS), and harbour alternatives such as airports (Napt). Since the risk is reduced when adaptive capacity is high, indicators of this component were treated inversely, for high values are assigned to low scores (i.e., contributing to risk). A more detailed description of indicators is presented in Appendix A.
Besides the historical reference period, we considered two 20-year future periods of analysis. One near the middle of the 21st century (2046-2065) and one covering the end of the 21st century (2081-2100). Therefore, for assessing future risk, we considered projections or estimations for the indicators when these were available. This was mainly the case for the components of hazard (mean sea level rise, extreme waves and wind), exposure (population, number of passengers, value of goods), and the contribution of renewables. Two Representative Concentration Pathways (RCPs) were considered for meteorological hazards (Meinshausen et al., 2011). One “high-emission” or “business-as-usual” pathway (RCP8.5) and a more optimistic one (RCP2.6) that is closer to the main targets of the Paris Accord to keep global warming to lower levels than 2 °C since pre-industrial times. Regarding future estimations of exposure indicators, we scaled the observed values according to the population projections (years 2050 and 2090). These projections were derived from the United Nations Department of Economic and Social Affairs (https://population.un.org/wpp/).
2.4. Normalization of indicators, Weighting and Risk Calculation
Prior to the calculation of risk, the indicators needed to be normalized to values between 0 and 1. For this, we have applied the minimum-maximum normalization method as it is described in OECD (2008) and GIZ (2017). The methodology is defined in the following formula:
where Xi represents the individual data point to be transformed, XMIN is the lowest value for that indicator, XMAX is the highest value for that indicator, and Xi,0 to 1 the new value you wish to be calculated (i.e. the normalized data point within the range of 0 to 1). For most of the exposure and vulnerability components, this normalization was applied across the different islands in order to facilitate an inter-island comparison and to prioritize the cases of higher risk. As an example, for the Npop indicator, XMIN is the value for the island with the lowest population (Corsica) and XMAX is the value for the archipelago with the highest population (Canary Islands). Therefore, we assigned a value of 0 for the former and a value of 1 for the latter, while the rest of the islands were assigned values in between. For the extreme hazard indicators, in order to provide normalized values that are meaningful in terms of physical impacts we have set the minimum/maximum values according to expert judgement. Critical thresholds of the Beaufort and Douglas scales (Owens, 1982) were used for extreme winds and waves respectively. Values before and after the normalization, as well as more information on the sources of each indicator are presented in Appendix A.
Regarding the weighting of the different risk components, several weights have been examined; however, based on expert judgement and discussion with stakeholders and specialists in the Maritime Transport sector, we have considered it more appropriate to conservatively assign equal weights to all main components of risk (i.e., 0.33 for Hazard, 0.33 for Exposure and 0.33 for Vulnerability). For the Exposure sub-components (see Figure 1), we have assigned a weight of 0.33 for the Nature of Exposure and a weight of 0.66 for the Level of Exposure since the latter is of greater importance. Similarly, for the Vulnerability sub-components, we have assigned a weight of 0.25 for the factors of Sensitivity and a weight of 0.75 for the factors of Adaptive Capacity. The selection of weights is a subjective decision, nevertheless, we consider our selection to be quite conservative, and therefore we believe that a slightly different choice would not significantly affect our calculations.
Finally, after the normalization of indicators and the application of weights for the different components, the relative risk for Maritime Transport disruption is calculated according to the following formula:
The derived relative risk values, calculated for each island and period of analysis, are eventually categorised into five classes for better visualisation and interpretation of results. Values between 0 and 0.2 indicate very low risk, values between 0.2 and 0.4 low risk, values between 0.4 and 0.6 medium risk, and values between 0.6 and 0.8 high risk, while greater values near indicate a very high risk for Maritime Transport disruption.
[2] https://www.euro-cordex.net/
[3] http://mena-cordex.cyi.ac.cy/
[4] https://www.medcordex.eu/
3.1. Overview for all islands
For the recent-past/present conditions, the operationalization of the Maritime Transport Impact Chain indicates low risk for all investigated islands (Table 1). In general, the Maritime Transport sector of the larger islands (e.g., Corsica, Cyprus, and Crete) is found to be more resilient to the impacts of climate change. Up to a point, this is related to a large number of harbour alternatives compared to smaller islands. Results for the future highlight the importance of adopting a low-emission pathway since this will keep the risk for Maritime Transport disruption similar to present conditions, while for some islands, the risk is expected to decline slightly.
Concerning changes in climate hazards, these are more important when it comes to the regional mean sea level rise. A visual summary of mean sea-level rise for all islands, different horizons and scenarios is presented in Figure 1. For RCP2.6, mean sea-level rise is not expected to exceed 27 cm, with respect to the historical reference. On the contrary, a business-as-usual pathway (RCP8.5) implies up to three times higher mean sea-level rise for both periods. Particularly at the end of the current century, mean sea level rise will likely reach 58 cm in all islands, while in the Canary Islands, this is projected to reach 74 cm, the greatest increase among all case studies. On the contrary, the projected changes are not expected to be significant for extreme wind and waves (Tables A2-A5).
In terms of inter-island comparison, Malta’s maritime sector is found to be the most vulnerable, nevertheless, future risk, even under the high-emission pathway (RCP8.5), is not expected to exceed medium risk values. Contrariwise, Corsica is the island least susceptible to climate change impacts. Detailed tables of the Impact Chain operationalization (including all components, islands and future scenarios) are presented in Tables B.1-B.5 of Appendix B. More detailed results for each investigated island are presented in the following sub-sections (3.2-3.7).
Table 1. Historical (1986-2005) and future risk of isolation due to Maritime Transport disruption for six European islands and archipelagos based on the Impact Chain approach (0=low risk, 1= high risk).
|
Historical Reference |
RCP2.6 (2046-2065) |
RCP2.6 (2081-2100) |
RCP8.5 (2046-2050) |
RCP8.5 (2081-2100) |
|
|
Cyprus |
0.24 |
0.21 |
0.22 |
0.26 |
0.29 |
|
Crete |
0.23 |
0.21 |
0.20 |
0.26 |
0.28 |
|
Malta |
0.38 |
0.35 |
0.34 |
0.39 |
0.41 |
|
Corsica |
0.22 |
0.19 |
0.19 |
0.24 |
0.27 |
|
Canary Isl. |
0.34 |
0.29 |
0.25 |
0.35 |
0.34 |
|
Balearic Isl. |
0.33 |
0.28 |
0.26 |
0.33 |
0.34 |
3.2. Cyprus
For the eastern Mediterranean island of Cyprus and the risk of isolation due to Maritime Transport disruption, our analysis indicated low-risk values (0.24) during the historical reference period (Table 1 and Figure 4). The greatest is the contribution that comes from the socioeconomic drivers of Adaptive Capacity and Nature of Exposure. On the contrary, the indicators related to meteorological hazards (sea level rise, extreme winds and waves) had a much smaller contribution. For the mid-century, the risk for transport disruption remains low for both RCP2.6 and RCP8.5 pathways (values of 0.21 and 0.26, respectively).
The contribution of Hazard indicators is expected to become more significant since the mean sea-level rise is increased compared to the default zero value of the historical reference period. Since the Exposure indicators have identical values for both pathways, the differences in the risk values are for this period mainly driven by the factors of Adaptive Capacity and primarily the contribution of renewables in the total energy production. This contribution is expected to be more critical in an RCP2.6 future. As a result, the risk values are somehow lower under this pathway. By the end of the 21st century, the risk values are not projected to change much for the optimistic RCP2.6. On the contrary, for RCP8.5, our analysis indicates a further increase in the risk value (0.29). Nevertheless, due to the lower contribution from the Exposure and Vulnerability components, the future risk for maritime transport disruption in Cyprus is still categorized in the low-risk class.
3.3. Crete
For the largest Greek island, during the historical reference period, the IC operationalization indicates similar conclusions as in the case of Cyprus (Table 1 and Figure 5). The risk value is characterized as low (0.23), with a more significant contribution arriving from the factors of Adaptive Capacity. This is due to the low contribution of renewables and the relatively low number of harbour alternatives (e.g., airports) on the particular island. For RCP2.6, the risk of transport disruption is projected to slightly decrease in the middle and remain stable for the end of the 21st century. This is mainly due to a higher contribution of renewable energy. This higher contribution makes the island less dependent on imported fossil fuel for energy production and therefore increases its capacity to adapt and be self-sustained. For the business-as-usual RCP8.5, our analysis indicates an increase for the end of the current century (risk value of 0.28). This increase can be attributed to the projected augmentation of meteorological hazards (mainly extreme winds and mean sea-level rise). The fact that Crete is one of the islands where the level of Exposure indicators (population, number of passengers and value of goods) is expected to decrease strongly, keeps the future risk for transport disruption at relatively low levels.
3.4. Malta
Compared to Cyprus and Crete, the IC operationalization for Malta (Figure 6) exhibits a higher present relative risk for isolation due to Maritime Transport disruption (risk value of 0.38). This is mostly related to the high values of Exposure indicators (nature and level of exposure). That is due to a combination of a small number of ports and the high value of goods, expressed as total freight. Two other contributors to the relatively higher risk value are related to increased vulnerability due to the small number of harbour alternatives (e.g., airports) and the small percentage of renewables in total energy production. For future pathway RCP2.6, the risk is expected to decrease slightly, mainly due to an anticipated increase in renewable energy contribution. Nevertheless, Malta will still be classified as a low-risk region. On the contrary, under the RCP8.5 pathway, the risk for transport disruption in the Maltese islands is projected to increase, marginally classified as low for the middle of the century (risk value of 0.39). Towards the end of the current century, the risk is projected to increase to medium values (0.41). This is due to the lower contribution of renewables in this high-emission scenario and the projected increase of the hazard indicators (mainly extreme winds and mean sea level rise). The mean sea level in the region, in particular, is expected to rise by 65 cm, thus posing an additional threat to harbour infrastructure.
3.5. Corsica
The Maritime Transport sector on the island of Corsica in France is found to be less susceptible to climate change as our Impact Chain operationalization indicates the lowest risk values among all investigated islands (risk value of 0.22 for present conditions). This is mostly related to the low contribution of the Exposure indicators (for example, number of passengers, value of transported goods, etc.). Under pathway RCP2.6, the relative risk value will likely slightly reduce because the adverse effect of increasing meteorological hazards is counterbalanced by an increase in the Adaptive Capacity component. This is mostly driven by the fact that the percentage of renewables is expected to increase in this low-emission pathway (Figure 7). Under scenario RCP8.5, and mainly due to increased contribution from future meteorological hazards, the risk is expected to slightly increase by the mid-21st century and reach a value of 0.27 by 2100.
3.6. Canary Islands
The Canary Islands is our only case-study archipelago outside the Mediterranean. For the historical reference period, our analysis determined a low-risk value of 0.34 (Figure 8). That is the second-largest risk value overall after Malta. This result is clearly due to the contribution of Exposure indicators. In particular, the total population, the number of passengers, and the value of goods are the highest among all investigated islands. Under an RCP2.6 sustainability pathway, the risk value is expected to decrease substantially (risk values of 0.25-0.29). This is mainly due to the combination of increased Adaptive Capacity and reduced contribution from Exposure indicators since the archipelago's population was assumed to be declining following the mainland Spain trends. Under pathway RCP8.5, this decrease in the exposure and adaptive capacity risk components is counterbalanced with a significantly increased contribution of meteorological hazards due to stronger climate change effects. As the Canaries are located in the Atlantic Ocean, the predicted mean sea-level rise (0.74 cm) is the highest among all investigated islands or archipelagos. As a result of this counterweight, the end-of-the-century risk value (0.34) will likely not exceed the low-level class.
3.7. Balearic Islands
The Balearic Islands in the western part of the Mediterranean is the last archipelago investigated for the impact of climate change in our assessment. For the historical reference period, the impact change operationalization resulted in a risk value of 0.33 (low risk), corresponding to the third-highest risk overall (Figure 9). The greatest contribution to the overall risk comes from the low Adaptive Capacity because of the small number of harbour alternatives and the low percentage of renewables for energy production on the island. Since the contribution of renewables is expected to increase under RCP2.6, whereas the contribution of Exposure and Hazard indicators will likely not significantly change in the coming decades the risk under this scenario is expected to decrease to a value of 0.28. By the end of the century, the risk of Maritime Transport disruption for the Balearic Islands is expected to further decrease (0.26). For the business-as-usual RCP8.5, the risk is anticipated to slightly increase (values of 0.33-0.34) as a result of the meteorological hazards (mainly extreme winds and mean sea-level rise) and a lower contribution of renewable energy production.
We conceived a comprehensive framework, defined and determined the relevant indicator values, and applied it for the assessment of the historical and future risk of Maritime Transport disruption in six European islands and archipelagos. Our results, based on state-of-art regional climate modeling data and local information on socio-economic drivers, highlight that for all investigated case studies, the future risk is not expected to exceed medium values. This conclusion is in agreement with previous studies (e.g., Izaguirre et al., 2020). The highest risk values are found for the islands with a limited number of harbour alternatives (as in the case of Malta) or high levels of exposure components (for instance, the Canary Islands). According to the updated regional projections used, climate change in the regions under investigation is mainly expected to exacerbate the future risk mainly through the increased mean sea levels, and to a lesser extent, from changes in wind and wave extremes. Nevertheless, for some islands, this increase in the particular hazard component is counteracted by a projected population (and thus in the number of passengers and value of goods) decrease, and, therefore, future risk values will likely remain at low-to-medium levels.
The present results can support policymakers and stakeholders in identifying and decomposing the major drivers of current and future risk for maritime transport disruption, as far as it concerns weather and climate hazards. For most islands under investigation, the current and near-term risk is mostly driven by the Vulnerability and Exposure components rather than the natural hazards per se. The latter are found to play a more important role towards the end of the current century. Our analysis also corroborates that adopting timely and aggressive mitigation measures through low greenhouse gas emission and concentration pathways (e.g., RCP2.6) will keep the risk for Maritime Transport disruption similar to present-day levels. For some islands, and in combination with demographic and socioeconomic data projections, the risk is even expected to decline. This decline ranges between 10 and 26%, with higher reductions for the Canary and the Balearic Islands and more evident benefits towards the end of the 21st century. On the contrary, a business-as-usual pathway (e.g., RCP8.5) leads to an increased risk for isolation due to Maritime Transport disruption. This is projected to be higher for all cases towards the end of the 21st century.
According to our findings, the severity of extreme winds and waves that could cause damage or disruptions to ships en route is not expected to alter significantly. Since, according to our findings, the most relevant future hazard for maritime transport disruption is mean sea level rise, adaptation strategies need to focus more on seaport infrastructure. Although some ports have already begun to adapt to climate change conditions, the development and implementation of additional adaptation strategies and measures are strongly recommended to secure the seamless operation of the Maritime Transport sector. Such measures can include (a) the increase of the number of port alternatives and establishment of backup routes during and after extreme weather events, (b) the enhancement of early warning systems, (c) the construction or expansion of coastal defences, (d) interventions to increase the height of critical infrastructure or (e) the reinforcement of inspection, repair and maintenance of port infrastructure and vessels (Becker et al. 2018; Léon et al. 2021). To achieve this, port capital-facilities planning should be expanded beyond the 5–10 year horizon, which is the current practice of most port operators (Becker et al., 2012; 2018). Moreover, the cost of such adaptation measures can exceed several million euros per year and strongly depends on the future emission pathways and associated hazards. For example, for the selected islands, the operational cost for increasing the height of critical port infrastructure can exceed 15 million Euros per year and is about three times higher for the business-as-usual pathway RCP8.5, compared to RCP2.6 (Léon et al. 2021). Port relocation could be an option only where higher inundation levels occur (e.g., exceeding three meters) and depending on the importance of the seaport, as this is a very costly solution (Christodoulou and Demirel 2017). According to our estimations, this is typically not a feasible option for the investigated islands.
Parts of the methodology and analysis were inevitably based on subjective decisions (e.g., the normalization of data and weighting of the risk components), however, we consider our choices conservative and therefore, we believe that slightly different values would not have affected the main conclusions drawn. With minor adjustments, and if reliable climate and socio-economic data are available, the proposed impact chain framework can be applied in other regions or sectors to support policy and decision making accordingly.
Acknowledgments. This work has received funding from the European Union’s H2020 Research and Innovation Programme under Grant Agreement No 776661 (SOCLIMPACT project). It was also supported by the EMME-CARE project that has received funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement No. 856612, as well as matching co-funding by the Government of the Republic of Cyprus.
Conflict of interest
The authors declare that they have no conflict of interest.
- Asariotis, R. and Benamara, H. (Eds.). (2012). Maritime transport and the climate change challenge. Routledge.
- Arabadzhyan, A. et al. (2020). Climate change, coastal tourism, and impact chains–a literature review. Curr. Issues Tour. 0, 1–36
- Becker, A., Inoue, S., Fischer, M., Schwegler, B. (2012). Climate change impacts on international seaports: Knowledge, perceptions, and planning efforts among port administrators. Clim. Change 110, 5–29. doi: https://doi.org/10.1007/s10584-011-0043-7
- Becker, A., Ng, A. K. Y., McEvoy, D., & Mullett, J. (2018). Implications of climate change for shipping: Ports and supply chains. Wiley Interdisciplinary Reviews: Climate Change, 9(2), e508. https://doi.org/10.1002/wcc.508
- Bender, M.A., Knutson, T.R., Tuleya, R.E., Sirutis, J.J., Vecchi, G.A., Garner, S.T., Held, I.M., 2010. Modeled impact of anthropogenic warming on the frequency of intense Atlantic hurricanes. Science (80-. ). 327, 454–458. doi: https://doi.org/10.1126/science.1180568
- Camus, P., Tomás, A., Díaz-Hernández, G., Rodríguez, B., Izaguirre, C., Losada, I.J. (2019). Probabilistic assessment of port operation downtimes under climate change. Coast. Eng. 147, 12–24.
- Carrillo, J., González, A., Pérez, J.C., Expósito, F.J., Díaz, J.P., 2022. Projected impacts of climate change on tourism in the Canary Islands. Reg. Environ. Chang. 22. https://doi.org/10.1007/s10113-022-01880-9
- Cherif, S., Doblas-Miranda, E., Lionello, P., Borrego, C., Giorgi, F., Iglesias, A., Jebari, S., Mahmoudi, E., Moriondo, M., Pringault, O., Rilov, G., Somot, S., Tsikliras, A., Vila, M., Zittis, G. (2020). Drivers of change. In: Climate and Environmental Change in the Mediterranean Basin – Current Situation and Risks for the Future. First Mediterranean Assessment Report [Cramer W, Guiot J, Marini K (eds.)] Union for the Mediterranean, Plan Bleu, UNEP/MAP, Marseille, France, pp. 59-180.
- Christodoulou, A., Demirel, H., (2017) Impacts of climate change on transport - A focus on airports, seaports and inland waterways. EUR 28896 EN, Publications Office of the European Union, Luxembourg, ISBN 978-92-79-76902-3, doi:10.2760/447178, JRC108865.
- Cramer, W., Guiot, J., Fader, M., Garrabou, J., Gattuso, J.P., Iglesias, A., et al. (2018). Climate change and interconnected risks to sustainable development in the Mediterranean. Nature Climate Change, 8(11), 972–980. doi: https://doi.org/10.1038/s41558-018-0299-2
- Cruise Industry News Annual Report (2018) https://www.cruiseindustrynews.com/store/product/annual-reports/2018-2019-annual-report/
- Eurostat (2020). Gross value added at basic prices by NUTS 3 regions. https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=nama_10r_3gva&lang=en
- Expósito, F.J., González, A., Pérez, J.C., Díaz, J.P., Taima, D. (2015). High-resolution future projections of temperature and precipitation in the Canary Islands. J. Clim. 28, 7846–7856. https://doi.org/10.1175/JCLI-D-15-0030.1
- Flaounas, E., Davolio, S., Raveh-Rubin, S., Pantillon, F., Miglietta, M.M., Gaertner, M.A., Hatzaki, M., Homar, V., Khodayar, S., Korres, G., Kotroni, V., Kushta, J., Reale, M., Ricard, D., 2022. Mediterranean cyclones: current knowledge and open questions on dynamics, prediction, climatology and impacts. Weather Clim. Dyn. 3, 173–208. https://doi.org/10.5194/wcd-3-173-2022
- Gaertner, M.A., Jacob D., Gil V., Dominguez M., Padorno E., Sánchez E., Castro M. (2007) Tropical cyclones over the Mediterranean Sea in climate change simulations. Geophys. Res. Lett. 34, L14711. doi:10.1029/2007GL029977
- Giorgi, F., Gutowski W.J. (2016). Coordinated Experiments for Projections of Regional Climate Change. Curr Clim Chang Reports 2:202–210. doi: 10.1007/s40641-016-0046-6
- Giannakis, E., Kushta, J., Giannadaki, D., Georgiou, G. K., Bruggeman, A., & Lelieveld, J. (2019). Exploring the economy-wide effects of agriculture on air quality and health: Evidence from Europe. Science of the Total Environment, 663, 889–900. https://doi.org/10.1016/j.scitotenv.2019.01.410
- GIZ (2017) The Vulnerability Sourcebook: Concept and guidelines for standardised vulnerability assessments. Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ)
- González-Alemán, J.J., Pascale, S., Gutierrez-Fernandez, J., Murakami, H., Gaertner, M. A., Vecchi, G. A. (2019). Potential Increase in Hazard from Mediterranean hurricane activity with global warming. Geophysical Research Letters, 46(3), 1754–1764. https://doi.org/10.1029/2018GL081253
- Hagenlocher, M., Schneiderbauer, S., Sebesvari, Z., Bertram, M., Renner, K., Renaud, F., Wiley, H., Zebisch, M., (2018). Climate risk assessment for ecosystem-based adaptation –a guidebook for planners andpractitioners. Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Bonn, Germany
- Hanson, S. and Nicholls, R. J. (2012). Extreme flood events and port cities through the twenty-first century. Maritime Transport and the Climate Change Challenge, 243.
- Hochman, A., Marra, F., Messori, G., Pinto, J., Raveh-Rubin, S., Yosef, Y., Zittis, G. (2021). ESD Reviews: Extreme Weather and Societal Impacts in the Eastern Mediterranean. Earth Syst. Dyn. Discuss. 2021, 1–53.
- International Maritime Organization – IMO (2015). Third IMO GHG Study 2014. Report, International Maritime Organization, London.
- IPCC (2013) Climate Change 2013: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker TF, Qin D, et al. (eds.)]. Cambridge University Press, Cambridge and New York.
- Izaguirre, C., Losada, I.J., Camus, P., Vigh, J.L., Stenek, V., 2020. Climate change risk to global port operations. Nat. Clim. Chang. https://doi.org/10.1038/s41558-020-00937-z
- Jacob, D., Teichmann, C., Sobolowski, S., et al. (2020). Regional climate downscaling over Europe: perspectives from the EURO-CORDEX community. Regional Environmental Change 20,51. doi: 10.1007/s10113-020-01606-9
- Léon C. et al (2021). Downscaling climate change impacts, socio-economic implications and alternative adaptation pathways for islands and outermost regions. McGrawHill, Madrid, https://doi.org/10.5281/zenodo.5141549
- Monios, J., Wilmsmeier, G. (2020). Deep adaptation to climate change in the Maritime Transport sector–a new paradigm for maritime economics? Maritime Policy & Management, 1-20. doi: 10.1080/03088839.2020.1752947
- Monioudi, I. Ν., Asariotis, R., Becker, A., Bhat, C., Dowding-Gooden, D., Esteban, M., et al. (2018). Climate change impacts on critical international transportation assets of Caribbean Small Island Developing States (SIDS): the case of Jamaica and Saint Lucia. Regional Environmental Change, 18, 2211–2225 doi: https://doi.org/10.1007/ s10113-018-1360-4
- Meinshausen, M. et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Clim. Change 109, 213–241 (2011).
- Ng, A. K. Y., Chen, S. L., Cahoon, S., Brooks, B. & Yang, Z. Climate change and the adaptation strategies of ports: The Australian experiences. Res. Transp. Bus. Manag. 8, 186–194 (2013). doi: https://doi.org/10.1016/j.rtbm.2013.05.005
- Ng, A.K.Y., Zhang, H., Afenyo, M., Becker, A., Cahoon, S., Chen, S. ling, Esteban, M., Ferrari, C., Lau, Y. yip, Lee, P.T.W., Monios, J., Tei, A., Yang, Z., Acciaro, M., 2018. Port Decision Maker Perceptions on the Effectiveness of Climate Adaptation Actions. Coast. Manag. 46, 148–175. https://doi.org/10.1080/08920753.2018.1451731
- Obermann-Hellhund A, Conte D, Somot S, et al (2018) Mistral and Tramontane wind systems in climate simulations from 1950 to 2100. Clim Dyn 50:693–703. doi: 10.1007/s00382-017-3635-8
- OECD (2008) Handbook on Constructing Composite Indicators: Methodology and User Guide. Organisation for Economic Co-operation and Development (OECD)
- Owens E.H. (1982) Sea conditions. In: Beaches and Coastal Geology. Encyclopedia of Earth Science. Springer, Boston, MA
- Pörtner, H. O., Roberts, D., Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., et al. (2019). IPCC Special Report on the Ocean and Cryosphere in a Changing Climate. IPCC Intergovernmental Panel on Climate Change: Geneva, Switzerland.
- Riahi K., van Vuuren D.P., Kriegler E., et al (2017) The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Glob Environ Chang 42:153–168. doi: 10.1016/j.gloenvcha.2016.05.009
- Ruti PM, Somot S, Giorgi F, et al (2016) Med-CORDEX initiative for Mediterranean climate studies. Bull Am Meteorol Soc 97:1187–1208. doi: 10.1175/BAMS-D-14-00176.1
- Schneiderbauer, S., M. Zebisch, S. Kass, L. Pedoth (2013). Assessment of vulnerability to natural hazards and climate change in mountain environments – examples from the Alps. In: J Birkmann (ed): Measuring Vulnerability, 2nd edition, ISBN-13: 978-81-7993-122-6, ISBN: 81-7993-122-6, United University Press, pp 349 – 380
- Sánchez-Arcilla, A., Sierra, J.P., Brown, S., Casas-Prat, M., Nicholls, R.J., Lionello, P., Conte, D. (2016). A review of potential physical impacts on harbours in the Mediterranean Sea under climate change. Reg. Environ. Chang. 16, 2471–2484. doi: https://doi.org/10.1007/s10113-016-0972-9
- Schneiderbauer, S., Baunach, D., Pedoth, L., Renner, K., Fritzsche, K., Bollin, C., et al. (2020). Spatial-explicit climate change vulnerability assessments based on impact chains. Findings from a case study in Burundi. Sustainability, 12(16). doi: https://doi.org/10.3390/SU12166354
- Soto-Navarro, J. et al. Evolution of Mediterranean Sea water properties under climate change scenarios in the Med-CORDEX ensemble. Climate Dynamics 54, (2020).
- Torres, C., Jordà, G., de Vílchez, P., Vaquer-Sunyer, R., Rita, J., Canals, V., Cladera, A., Escalona, J.M., Miranda, M.Á. (2021). Climate change and their impacts in the Balearic Islands: a guide for policy design in Mediterranean regions. Reg. Environ. Chang. 21. https://doi.org/10.1007/s10113-021-01810-1
- United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects: The 2019 Revision.
- WAVEWATCH IIIR Development Group (WW3DG) (2016). User manual and system documentation of WAVEWATCH IIIR© version 5.16. Tech. Note 329, NOAA/NWS/NCEP/MMAB, College Park, MD, USA, 326 pp.
- Yang, Z., Ng, A. K., Lee, P. T. W., Wang, T., Qu, Z., Rodrigues, V. S., ... & Lau, Y. Y. (2018). Risk and cost evaluation of port adaptation measures to climate change impacts. Transportation Research Part D: Transport and Environment, 61, 444-458.
- Zebisch, M., Schneiderbauer, S., Renner, K., Below, T., Brossmann, M., Ederer, W., Schwan, S. (2017). Risk supplement to the vulnerability sourcebook: Guidance on how to apply the vulnerability sourcebook’s approach with the new IPCC AR5 concept of climate risk. Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Bonn, Germany
- Zebisch, M., Schneiderbauer, S., Fritzsche, K., Bubeck, P., Kienberger, S., Kahlenborn, W., et al. (2021). The vulnerability sourcebook and climate impact chains – a standardised framework for a climate vulnerability and risk assessment. International Journal of Climate Change Strategies and Management, 13(1), 35–59. doi: https://doi.org/10.1108/IJCCSM-07-2019-0042
- Zittis G., Hadjinicolaou P., Klangidou M., et al. (2019). A multi-model, multi-scenario, and multi-domain analysis of regional climate projections for the Mediterranean. Regional Environmental Change 19:2621–2635. doi: 10.1007/s10113-019-01565-w
- Zittis G, Bruggeman A, Lelieveld, J. (2021a). Revisiting future extreme precipitation trends in the Mediterranean. Weather and Climate Extremes, 34:100380. doi: https://doi.org/10.1016/j.wace.2021.10038
- Zittis, G., Hadjinicolaou, P., Almazroui, M., Bucchignani, E., Driouech, F., El Rhaz, K., Kurnaz, L., Nikulin, G., Ntoumos, A., Ozturk, T., Proestos, Y., Stenchikov, G., Zaaboul, R., Lelieveld, J. (2021b) Business-as-usual will lead to super and ultra-extreme heatwaves in the Middle East and North Africa. npj Clim. Atmos. Sci. 4, 20. https://doi.org/10.1038/s41612-021-00178-7
- Zittis, G., Almazroui, M., Alpert, P., Ciais, P., Cramer, W., Dahdal, Y., Fnais, M., Francis, D., Hadjinicolaou, P., Howari, F., Jrrar, A., Kaskaoutis, D.G., Kulmala, M., Lazoglou, G., Mihalopoulos, N., Lin, X., Rudich, Y., Sciare, J., Stenchikov, G., Xoplaki, E., Lelieveld, J., 2022. Climate change and weather extremes in the Eastern Mediterranean and Middle East. Rev. Geophys., e2021RG000762. https://doi.org/https://doi.org/10.1029/2021RG000762