In Duić et al. [7], a RenewIslands method was put forth to transform island energy systems that are dependent on fossil fuels from the mainland into 100% renewable energy systems. The method involves the integration of resource flows according to the needs and resources of islands through integration between systems, including storage in the form of desalinated water when necessary. In this pioneering study, the RenewIslands method across resources, commodities, and technologies was initially applied to the islands of Porto Santo, Corvo, and Mljet. In addition, Krajačić et al. [8] analysed the production and storage of hydrogen (H₂) for energy supply structures with 100% renewable energy in islands, including Malta. Other studies based on the RenewIslands method include Pfeifer et al. [9], in which interconnected energy systems for multiple Croatian islands were simulated. In addition, Mimica and Krajačić [10] sought to automatise the approach for smart islands and tested it with the islands of Krk and Vis. Dorotić et al. [11] optimised island energy systems assuming 100% variable renewable energy and electric transport with smart charging. With a focus on Singapore, Dominković and Krajačić [12] determined the optimal share of district cooling to reduce socio-economic costs. Moreover, water desalination, demand side management, and energy efficiency measures were considered to lower carbon dioxide (CO₂) emissions, primary energy supply, and particulate matter [13].

Among other studies, Groppi et al. [14] analysed the long-term energy transition of Favignana island in Italy, which was modelled based on a new version of H2RES. From another perspective, sector coupling options were analysed with multi-objective optimisation [15] for the same island. As another Italian island, EnergyPLAN was used for Sardinia, which was considered a smart energy system with high shares of renewable energy [16]. In the context of satisfying cooling loads, flexibility provision was found to provide additional revenue when analysed for the coastal city of Rijeka in Croatia [17]. In addition, Meschede [18] proposed increasing the utilization of solar and wind resources on the island of La Gomera in Spain based on demand response in the water supply and distribution system. Salamanca et al. [19] investigated an osmosis power plant that utilises the salinity gradient between a river and the Caribbean Sea.

Other studies that are triggered by integrated approaches include Liu et al. [20], in which the need to reduce the import of energy and water to the islands of Maldives was targeted based on solar, wind, and biomass energy resources towards a zero-input island system. Selosse et al. [21] investigated scenarios for the island of Réunion, including a 100% renewable energy power sector by the year 2030 based on biomass, hydropower, solar, wave and wind energy, ocean thermal energy conversion, and geothermal energy. In other renewable energy-oriented studies, Selvaggi et al. [22] considered the diffusion of biogas plants with flexibility of power, heat, and biomethane production in the Sicilian context based on residual biomass from agricultural by-products, ground-cover crops, and municipal organic waste. Montorsi et al. [23] simulated a waste-to-energy plant considering fluctuations in the amount of wastewater generation due to tourism cycles in a town in Sicily. Ocon and Bertheau [24] considered transitioning the energy system of the Philippine archipelago from diesel power plants to hybrid systems with solar photovoltaic (PV) and battery energy storage. Battery and thermal energy storage options are deemed essential across a range of studies, including those to provide benefits for the power, heating, and transport sectors in the island of Samsø in Denmark as well as the Orkney Islands in Scotland [25]. Related studies further provide insight into the energy transition, particularly the municipal planning process leading to the fossil fuel-free island of Samsø that involved a synthesis of energy and socio-technical priorities [26].

Through these and other advances for islands, the first cluster in the scientific landscape of Appendix 1 with the main node of sustainable development represents studies that are directed to aspects of development with environmental protection and the conservation of natural resources. A key subset of studies emphasises the need for an integrated approach to realise sustainable development with linkages to multiple other clusters, predominately renewable energy. Studies seek to address the problematic use of fossil fuels on islands, especially when compared to the opportunities to utilise renewable energy, including solar, wind, bioenergy, geothermal energy, wave, and/or tidal energy.

Water management, water supply, water quality, agriculture, and recycling are other aspects of the scientific literature. Such studies include a focus on water desalination utilising renewable energy with an integrated, systemic approach. Advances in renewable energy technologies with local case studies that relate to coastal or coastal island cities include a polygeneration system with geothermal and solar energy that meets the energy and water demands of 800 buildings on Pantelleria Island [27]. Calise et al. [28] put forth a polygeneration system based on solar and biomass to produce electricity, heating, and cooling, as well as desalinated water. In Beccali et al. [29], a renewable energy retrofit of a hotel building in Lampedusa Island was evaluated based on solar thermal collectors, PV with and without electrical energy storage, and retrofits for building automation. The interaction of climate change and coastal settlements can also be observed in studies that relate to the urban heat island effect, energy utilisation, and urban planning.

Other studies have focused on reducing the environmental impacts of waste management systems. Empirical data from the municipal waste management system of Palermo indicated that the current collection, transport, and disposal of waste have an ecological footprint of 6331 ha. In contrast, increasing the recycling rate from only 7% up to 37%, as well as composting and landfill methane recovery as included in an integrated waste management plan, was found to produce a net saving of 36,336 ha [30]. Siracusa and La Rosa [31] evaluated the benefit-cost ratio of using wetlands for wastewater treatment in a small town in Sicily from an emergy perspective. The treated water was proposed to be reused for agricultural irrigation where risks of desertification are prevalent. Ruiz-Orejón et al. [32] evaluated the accumulating amount of floating plastic debris in the coastal waters surrounding the Balearic Islands. The highest concentrations were found on the surface of coastal waters that did not correspond to more highly populated areas, which suggested impacts from hydrodynamic conditions.

Multi-sectoral approaches that improve livelihoods and the sustainable use of resources are essential for coastal communities [33]. Among the limited number of studies with the keyword of benchmarking, however, none of the studies focused on benchmarking multiple dimensions of sustainable development. Ioannidis et al. [34] compared the energy and emissions intensity as well as the diversity of energy sources in 44 different islands. Islands with opposite performances were given, including Trinidad and Tobago, which have high energy and emissions intensity and zero diversity, in contrast to Iceland, which has near-zero energy and emissions intensity and high diversity. The results suggested the need to shift to renewable energy solutions, while the benchmarking process did not consider co-benefits, such as air quality or other dimensions. Schipper et al. [35] developed an approach to compare the performance and long-term plans of 10 ports, including a Sustainable Integrated Condition Index, to compare policy measures to address the social, environmental, and economic aspects of sustainability. The measures were scored according to evidence-based knowledge that was obtained from available sources, while the need for a standard in key performance indicators was underlined.

In other studies, a zero energy concept based on solar, wind, and wave energy for a small island of Hong Kong that otherwise relies on fossil fuels and nuclear energy was analysed [36]. Co-located wind and wave energy was another solution that was analysed to achieve the goal of an energy-sufficient island in Spain [37]. Experimental sea energy technologies, including osmotic energy, were included in the portfolio of renewable energy options in analyses for Réunion Island [38]. In Mendoza-Vizcaino et al. [39], the possibility of solar and wind energy for an island in Mexico was found to reduce the price of grid electricity by 35%. This possibility was compared to various renewable energy developments in 77 other islands from 45 countries. For comparative purposes, the study did not benchmark islands based on current or future performances.

A direct focus on the aim of benchmarking cities in coastal and/or island contexts towards sustainable development based on a composite indicator is, therefore, limited. In contrast, the literature review emphasises the suitability of islands in acting as pilot sites for demonstrating the integration of multiple systems towards complete decarbonisation, which merits benchmarking studies that are dedicated to islands as well as coastal settlements from a multi-dimensional perspective. This study addresses this gap in the scientific literature by pursuing the application of the Sustainable Development of Energy, Water and Environment Systems (SDEWES) Index [40]–[46] to coastal and coastal island cities. This multi-dimensional index provides a benchmarking framework that can be used to support renewable energy penetration, the integration of urban and energy planning, and a decoupling of emissions from greater well-being. Existing benchmarking studies with the SDEWES Index focused on 22 port cities in the Mediterranean Sea Basin [41]. Other island cities in and outside of the Mediterranean Sea Basin that take place among the largest islands in Europe were also benchmarked.^† Overall, benchmarking studies with the SDEWES Index involve 120 cities across the world [45], and the data inputs are openly accessible [46]. As the 121^st city, the index was also applied to Çankaya municipality in Ankara, Türkiye [47]. Recently, cities that have been benchmarked with the SDEWES Index and analysed based on urban emissions scenarios in a green-growth mitigation context were compared for 8 urban areas [48] and 15 Mission Cities in Europe [49].

The present study contributes to increasing an understanding of the relative sustainability of newly benchmarked port cities and coastal settlements on islands in the Mediterranean Sea Basin area. The uniqueness of the SDEWES Index for benchmarking the selected coastal and coastal island cities arises from the multi-dimensional nature of this index in aspects of energy, water and environment systems. Moreover, the index is suitable for evaluating opportunities for decoupling energy usage from emissions through renewable energy utilisation, which is undertaken in this research work through a scenario application that extends beyond benchmarking present levels of performance. Such a future-oriented scenario for 100% renewable energy is further analysed based on its possible impact on the ranking results and co-benefits for local employment opportunities. These aspects provide an original research endeavour in the scope of benchmarking studies involving the SDEWES Index. The results are further discussed in the context of recent island initiatives at the European and international levels. Opportunities for co-learning among coastal cities on different continents are exemplified, including a particular focus on Viña del Mar in Chile.

Table 1 provides the data compilation for the first dimension of the SDEWES Index, namely, “Energy Usage and Climate” (D₁). The values of the benchmarked cities indicate an average energy usage of 1,400,805 MWh in buildings and 1,458,327 MWh in transport, with an average energy usage of 11.27 MWh per capita. The lowest and highest values of energy usage per capita occur in Siracusa and Cagliari, respectively. Aspects of climate indicate total degree days of 1,080 when weighted with an average seasonal coefficient of performance.

Based on other aspects of the data compilation in D₁, local energy generation in the 11 benchmarked cities is still limited, with reliance on energy generation from outside the vicinity and on the mainland. The island cities are interconnected to the mainland power grid that allows for the usage of the primary energy factor for electricity generation at the national level [75] along with primary energy factors for solid, liquid, and gas fossil fuels as well as waste within the energy resource flow of the cities. Among the region of the cities, Andalucía reports both final energy usage and primary energy spending [53]. In the case of Italy, the primary energy factor for electricity generation varies from about 2.0 in the winter months to about 1.85 in May and June for an annual average of about 1.95 [75]. Considering the broader energy system in which the coastal and coastal island settlements are located, including the power mix and the transformation facilities, the average final to primary energy intensity ratio is about 73%.

Table 2 provides the data inputs to the main indicators of the second dimension, namely “Penetration of Energy and CO₂ Saving Measures” (D₂), while Tables A1−A3 provide the evaluations for the sub-indicators. Among the cities, the use of high-exergy resources, particularly natural gas, remains to be prevalent. Electricity supplies 82% of the building energy needs in Cartagena. Combined heat and power systems are still emerging (Table A1), including plans to integrate micro-CHP in hotel buildings in Alicante [78] and measures to increase micro-production plants undertaken in Cagliari. Renewable energy-based district energy networks are being considered in Trieste. Another approach for piloting a transition in the urban energy system is based on a 33 kW_e dish Stirling concentrated solar power unit in Palermo.

In the aspect of net-zero energy buildings (Table A2), Palermo has retrofits of school buildings based on the nZEB target. Similarly, the CERtuS project in Messina has targets for near-net-zero buildings. However, net-zero energy buildings constitute less than 0.002% of the building stock in Sicily, the island of Sardinia, and the Campania, as well as the Friuli-Venezia Giulia regions in Italy. For the density of public transport (Table A3), Alicante has about 0.41 km/km² of urban light rail based on a tram network. In contrast, multiple cities have municipal bicycle-sharing programs as alternatives to the use of private vehicles.

Best practices in public lighting are based on the relative penetration of LED lighting in a zero-energy neighbourhood in Palermo and the LED replacement of 1,530 lighting points in Siracusa. In contrast, LED lighting is not used in Palma de Mallorca for 10,000 lighting points, which indicates additional room for improvement in this city.

Table 3 provides the data compilation for the third dimension, which focuses on “Renewable Energy Potential and Utilization” (D₃). As coastal or coastal island cities in the Mediterranean Sea Basin, the benchmarked cities have favourable solar energy potential at an annual average of 5,563 Wh/(m²day), wind energy potential at an average of 4.78 m/s at a height of 50 m and geothermal energy potential of 61 mW/m². Among the benchmark cities, Catania has the highest installation of solar PV panels at 50,834 kW, followed by Palermo at 14,074 kW [79]. Cagliari utilises the local wind energy potential with an installed capacity of 46,321 kW [58]. Overall, however, the share of renewable energy is still below 40% in the energy mix of the electricity sector. Considering the inclusion of the transport and thermal energy sectors, the share of renewable energy is even less, which necessitates greater shares of renewable energy across all sectors. In the transport sector, the share of green energy in transport is less than 8%, based on data from Spain and Italy.

In Table 4, data inputs into the fourth dimension of “Water Usage and Environmental Quality” (D₄) are provided. The average of the benchmarked cities represents domestic water consumption per capita at 13.09 m³. The average water quality level is 90.65 out of a perfect score of 100 for dissolved oxygen, pH, conductivity, nitrogen, and phosphorus. For Sicily, the water demand has been met based on desalination plants through the use of multi-stage flash and reverse osmosis at Gela as well as thermal vapour compression based multiple effect distillation at Trapani and mechanical vapour compression in Porto Empedocle [85]. Among these options, mechanical vapour compression is the most energy intense, with energy usage up to 12 kWh/m³, while the multi-stage flash and thermal vapour compression based on multiple effect distillation plants require at most 1 and 2 kWh/m³, respectively. Water treatment from reservoirs is planned to better manage water shortages.

In aspects of air quality, the average value of the annual mean particulate matter concentration of PM₁₀ at a value of 22.54 µg/m³ is above the guidelines of the World Health Organisation. Alicante receives the cleanest annual mean PM₁₀ concentration at a value of 16.00 µg/m^3, while Palermo currently has the highest annual mean PM₁₀ concentration at about 31.70 µg/m³. An existing transport issue with extended traffic in the city centre is one of the reasons for the continued deterioration in air quality. Palermo has an average congestion level of 43%, with above 60% congestion in the morning and evening peak hours. As the impact of the benchmarked cities in and outside of the urban area and vicinity, the average ecological footprint per capita is 3.92 gha. In comparison, the average biocapacity is 1.08 gha per capita, which indicates an average ecological deficit of about 2.84 gha per capita as the accumulating impacts on the global environment.

The data inputs of the benchmarked cities for the fifth dimension of “CO₂ Emissions and Industrial Profile” (D₅) are provided in Table 5. Since any of these cities are not yet neutral on CO₂ emissions, the average amount of CO₂ emissions is 551,163 tonnes of CO₂ emissions from the building sector and 395,783 tonnes of CO₂ emissions from the transport sector at the urban level. On average, the CO₂ intensity of the energy mix is 0.32 tonnes of CO₂ per MWh. Based on measures for energy planning, a 585 MW coal and gas-fired power plant on the island of Mallorca is already targeted to be phased out based on the energy transition plan for the Balearic Islands [93]. Prior to a phase-out, the island had the highest CO₂ intensity at 0.45 tonnes of CO₂ per MWh.

The island of Sardinia, on which Cagliari is located, as well as the island of Sicily, also established energy plans [94], [95]. In addition, Palermo has a plan for smart buildings and smart mobility, including measures for renewable energy and energy sharing [96]. The scheme of energy sharing is targeted to extend to the utilisation of residual energy from the industry. Currently, the island of Sicily has sources of waste heat or residual energy based on facilities for non-metallic minerals, fuel supply, and refineries, as well as the chemical and petrochemical sectors [97]. In addition to the benchmarked cities in Sicily, others based on Cartagena, Alicante, Salerno, and Trieste also have similar sources of residual energy from industry (Table A4). In the aspect of airports that serve the cities, four airports reached the mapping or reduction levels of the Airport Carbon Accreditation scheme, including Cagliari Airport.

Table 6 provides the data inputs into the main indicators in the sixth dimension, namely “Urban Planning and Social Welfare” (D₆). Among the benchmarked cities, Alicante has the lowest waste generation per capita at 431 kg per capita, which is also close to the overall sample average of 433 kg per capita [46]. Three cities have shares of waste reuse, recycling, or composting at about 30% or higher (Table A5).

In the aspect of municipal wastewater treatment, all cities have 0% discharge of wastewater without treatment, with the exception of Catania (Table A6). Compliance with wastewater treatment criteria is upheld in all benchmarked cities, with the exception of Cagliari and Trieste, to various extents (Table A6). In the context of urban form, no cities among benchmarked cities have polycentricity, while relatively high shares of the population live in the urban core (Table A7). In contrast, land use and land use changes are documented based on Copernicus satellite images, including an exceptionally high sprawl index of 15.2% in Catania, which indicates that the built land area is growing much faster than the growth in population.

The presence of urban green areas as a provider of protection against climate change impacts, as well as better air quality, is currently best maintained in Cartagena at 86.61% (Table A7). In about 100 km of the city, three cities have protected sites that are larger than 1000 km², namely Marbella, Palermo, and Salerno. In aspects of social welfare, the benchmarked cities have an average of 28,826 PPP USD of gross domestic product (GDP) per capita at the regional level when adjusted using purchasing power parity (PPP) rates. Inequality-adjusted well-being is surveyed to be 7.1 out of 10, and the tertiary education rate is 26.1% for the population of 30−35 years of age, based on the relevant statistics.

Table 7 provides data inputs for the indicators in the cross-cutting seventh dimension of “Research, Development (R&D), Innovation and Sustainability Policy” (D₇). Aspects of R&D and innovation policy orientation are higher for Italian cities than Spanish cities, with similar performances in national patents in clean technologies (Tables A8−A9). The project of Palma de Mallorca (OPTi) is one of the projects in the Smart Cities Information System, while Palermo takes place in the Roadmaps for Energy project [96]. Alicante has the most universities and institutes in the local ecosystem based on two universities that are ranked in the Scimago top 1000 institutional rankings (Table A10).

Based on the strength of scientific knowledge production as represented within the h-index, the average value for the benchmarked cities is 797. These knowledge assets can provide an advantage for a city to reach CO₂ mitigation targets if well-aligned with related efforts and innovation activities. Among the benchmarked cities, Palma de Mallorca declared a CO₂ neutrality target for 2050, while Siracusa had a CO₂ reduction target of 39% by the year 2020. Subsequently, Siracusa is one of the municipalities that adopted a Climate Energy Declaration based on the scientific findings and the necessity for limiting global warming to 1.5 °C [112], [113].

The data inputs in the compilation process are searched for outliers. Winsorisation is not necessary since the data inputs in each of the 35 main indicators contributed to values of skewness less than 2.0 and kurtosis less than 3.5. The data inputs are, therefore, directly normalised according to the min-max method with minimum and maximum values that are harmonised with those of other cities in the benchmarking studies of the SDEWES Index. Table 8 summarises the average value of the cities that are benchmarked with the SDEWES Index prior to and after the inclusion of the newly benchmarked 11 coastal or coastal island cities. From Table 8, the average values increase by at most 1.918% in dimensions D₁, D₃, and D_5, while the average values decrease in dimensions D₂, D₄, D₆, and D₇ by at most −1.721%. These same dimensions represent the areas of relative strengths and weaknesses in the cities that are benchmarked in the present study. Overall, the new average values for a total of 132 cities are represented by the grey dashed lines in Figures 4−10.

In the context of D₁, Figure 4 provides the normalised values for the 11 newly benchmarked cities. Siracusa receives the highest sum of normalised values at a value of 40.413 out of a perfect score of 50.000. Advantages in multiple indicators, including energy usage per capita, appear to be influential in allowing Siracusa to obtain such a performance based on the results in Figure 4. The normalised values for the indicator on the total degree days have relatively less variance across the urban areas in Figure 4, given that all of the newly benchmarked cities belong to the common Mediterranean climate zone. Only two cities remain below the average value in D₁, namely Palma de Mallorca and Cagliari.

Figure 4.

Sum of normalised values for the indicators in D₁

Figure 5 provides the normalised values of the data inputs into D₂, indicating that the cities of Palermo, Cagliari, and Trieste are the top three cities in this dimension. The plans of these cities to initiate district heating and/or cooling networks or micro-CHP, as well as projects for net-zero energy school buildings, are influential in differentiating the approach of these cities over others. In some cities, the use of natural gas boilers remains prevalent without plans for significant change (Tables A1 and A2). None of the cities receive the maximum dimension value of 50.000 in D_2, and 9 cities remain below the average value across the 132 cities. Despite transport-related shortcomings, Palermo and Palma de Mallorca receive relatively higher normalised values for the density of public transport than other cities in Figure 5 based on light rail options, which would have some favourable impacts on performance if this had not been the case. As 7 cities have inefficient public lighting infrastructure, normalised values in this indicator disfavour these cities.

Figure 5.

Sum of normalised values for the indicators in D₂

The results in Figure 6 indicate that significant progress remains to be captured for the coastal or coastal island cities to utilise their favourable renewable energy potential. The island city of Reykjavík, benchmarked in reference [46], had 100% renewable energy in the electricity mix. In contrast, the urban settlements in the present study have limited local energy generation and rely on interconnections to the national electricity grid with up to 36.61% of renewable energy.

Figure 6.

Sum of normalised values for the indicators in D₃

In other cities, shares of green energy in transport reach above 12.04% in Stockholm and higher in the Brazilian cities of Rio de Janeiro and São Paulo, which are winsorised as outliers [46]. In comparison, those in the newly benchmarked urban areas remain less than 8.00%, which is further reflected in the normalised values in Figure 6. Despite these shortcomings in D₃, Cagliari, Marbella, and Siracusa are able to obtain the highest dimension values among the cities in the present study in aspects of renewable energy potential and utilisation with a top value of 30.921 out of a possible 50.000.

The normalised values in Figure 7 indicate that all of the 11 coastal or coastal island cities perform close to the average value of the 132 cities. Among the newly benchmarked cities, Messina, Alicante, and Trieste receive about a 1.015 above-average ratio that is marked as the ratio of the values of C_j over C_AV in Figure 7. This performance may be explained based on relatively lower domestic water consumption per capita in Messina and Trieste, lower annual mean PM₁₀ concentration in Alicante, and other aspects. The relatively high annual mean concentration of PM₁₀ in Palermo, including impacts due to traffic congestion, affects reducing the performance of this city in this dimension. In contrast, ecological footprint per capita is the second lowest in Palermo and other Sicilian cities, so a higher normalised value is received under this indicator. The cities of Cagliari, Salerno, and Trieste have a higher ecological footprint per capita and, thus, lower normalised values for this indicator. The normalised value of biocapacity per capita is not favourable considering the values of the other benchmarked cities.

Figure 7.

Sum of normalised values for the indicators in D₄

Figure 8 provides the normalised values of the indicators in D₅, where some of the cities, including Marbella, Alicante, and Messina, have favourable performances in this dimension with above-average performances. While the average value for D₅ across the 132 cities is 29.591, Marbella receives a sum of 36.320, which is a ratio of 1.227 with this average value. The average CO₂ intensity of the energy mix is among the indicators that support a relatively better position of Marbella in this dimension. In addition, Marbella, Alicante, and Messina are among the cities that have relatively low or absent energy-intensive industries in the urban vicinity. In Palma de Mallorca, however, the relatively high average CO₂ intensity has given this city the lowest normalised value for this indicator among the 11 cities in Figure 8. At the same time, the city plans to phase out the coal-based power plant by 2025 [119] in the next years, and the airport of Palma de Mallorca is accredited for reducing CO₂ emissions.

Figure 8.

Sum of normalised values for the indicators in D₅

Figure 9 presents the results of the normalised values for the indicators in D₆. Accordingly, the cities of Alicante, Salerno, and Palma de Mallorca are able to obtain the highest positions in this dimension. In contrast, the lowest sum of the normalised values for D₆ is obtained by Catania, which includes the impact from the 9% share of urban wastewater that is discharged without being treated. The relatively lower tertiary education rates in the Sicilian cities of Messina, Palermo, Siracusa, and Catania, when compared to a best practice value as high as 62.4% in Incheon [46], have affected limiting the performance of these cities in D₆. Overall, 6 of the newly benchmarked cities are able to surpass the 132-cities average value that remains at 25.414 for D₆ based on a comparison of the average values (see Table 8). Of the newly benchmarked cities, 5 cities receive below average performances by a ratio as low as 0.823.

Figure 9.

Sum of normalised values for the indicators in D₆

The sum of the normalised values for dimension D₇ is put forth within the scope of Figure 10, in which the cities of Siracusa, Cagliari, and Messina are able to obtain higher values. In the case of Siracusa, the more ambitious CO₂ mitigation target that the Climate Emergency Declaration follows enables the city to obtain a higher performance than the next best-performing city, namely Cagliari. In contrast, this city has other advantages when compared to Siracusa, which is based on universities in the local ecosystem and is surpassed only by Alicante among the newly benchmarked cities. The last 4 cities have below-average performances in D₇, namely Palma de Mallorca, Alicante, Cartagena, and Marbella, with a ratio as low as 0.822 with the average value.

Figure 10.

Sum of normalised values for the indicators in D₇

Table 9 summarises the aggregated sum of dimension values according to the formulation of the SDEWES Index [40]–[46] for the coastal and coastal island cities. These urban areas are ordered according to their aggregated index values in descending order that corresponds to rank positions from the top to the lowest rank among the 11 newly benchmarked cities. The marks (↑) or (↓) signify dimensions in which the cities receive above or below-average performances. According to Table 9, the top 3 cities among the newly benchmarked cities are Messina (SDEWES = 30.385), Siracusa (SDEWES = 30.232), and Palermo (SDEWES = 30.019). These cities, located on the island of Sicily, are differentiated based on energy and water usage, air quality, and CO₂ emissions, among multiple other aspects.

In contrast, the city of Catania, also located in Sicily, is ranked 5^th (SDEWES = 29.524), with one of the shortcomings being in D₆ based on urban water management. The rank 4 is taken by Alicante (SDEWES = 29.704), in which 5 dimensions have above-average performances. The lowest rank among the newly benchmarked coastal and coastal island cities is observed for Cartagena (SDEWES = 27.720), in which the city has 4 dimensions that are below the average dimension values when compared to the average of all cities.

In Table 9, the last two columns represent the index values for the benchmarked performances and the comparison of these values for the newly analysed 11 cities with the median index value for all 132 cities. The top index value of SDEWES = 30.385 for Messina, for example, is the summation of the dimension values D₁ – D₇ in Table 9 with default weights prior to the scenario application in eq. (1). This benchmarked index value is 4.083% above the median index value for all other cities. These percentage values that are marked as ΔM_j are further elaborated in Figure 11 in which the vertical axis of index rank is plotted against the percentage differences with the median value as ΔM_j. Based on Figure 11, none of the newly benchmarked cities are positioned in the top 25% of the benchmarked cities that contain the pioneering cities. However, the index values of 8 of the cities in Table 9 enable them to take place in the next quartile, which contains cities with index performances in the upper 25% to 50% of cities, as marked with the red circular markings. The remaining 3 cities in Table 9 have a relative positioning in the quartile immediately after the median value as marked with the green triangular markings. According to the performance definitions [45], these quartiles represent the transitioning and solution-seeking cities, respectively, as further grouped in Figure 11. The values of ΔM_j range between 4.083% for Messina and −5.046% for Cartagena.

Figure 11.

Analysis of the benchmarking results according to index performance

The relative positioning of the newly benchmarked cities is further compared in the context of uncertainty analyses. The ordering of cities, as provided in Table 9, remains stable based on the mean values of 10,000 Monte Carlo simulations, with the exception of the exchange in rank between the two adjacent cities of Trieste (original rank 6) and Marbella (original rank 7). Cagliari has the highest standard error of the mean, with a standard deviation of 2.482 for the rank positions in the 10,000 Monte Carlo simulations. Cartagena has the lowest standard error of the mean, considering a standard deviation of 0.870 for the rank positions in the Monte Carlo simulations. Overall, the rank positions of the cities based on the SDEWES Index, as given in Table 9, are within the upper and lower bounds of the rank positions with confidence intervals at a confidence level of 95% with a level of significance (α) equal to 0.05. This situation provides complete coverage of the highest and lowest ranks. Figure 12 provides the ranking of the 11 newly benchmarked cities according to the mean values of 10,000 Monte Carlo simulations and corresponding confidence intervals at a confidence level of 95%.

Figure 12.

Ranking results of the Monte Carlo simulations and confidence intervals

One of the most persistent shortcomings of the newly benchmarked cities is the reliance on fossil fuels despite the presence of favourable renewable energy resources. Figure 13 provides exemplary Sankey diagrams for the present energy and CO₂ emission flows in the three coastal cities of Messina, Trieste, and Cartagena. These diagrams clearly put forth the existing situation in which there is no indication of any decoupling between energy usage and CO₂ emissions due to the reliance on fossil fuels in the energy mix, including transport. Such a problematic issue on the supply side is further exacerbated with the use of natural gas, which is a high-quality, high-exergy resource for low-exergy demands in residential buildings. In fact, the natural gas network that was introduced on the island of Sicily [60] remains one of the infrastructural barriers to the greater penetration of renewable energy on the island. From another perspective, the persistent problems that are common to the benchmarked cities are representative of the significant opportunities to realise progress toward sustainable energy systems based on a transition to renewable energy resources. Solutions that enable higher shares of renewable energy across various sectors of the energy system also provide the opportunity to decouple energy usage from CO₂ emissions with additional possibilities to obtain multiple co-benefits, including those for environmental quality, lower demands on limited water resources, and human well-being.

Currently, options for a renewable energy transition include concepts for a net-zero energy island in Sicily based on the utilization of solar, wind, and geothermal energy [120], water desalination based on wave energy [121], and offshore renewable energy platforms that produce hydrogen to be used in public transport [122]. The energy roadmap for Palermo under the Roadmap4Energy project [96] also puts forth strategic objectives for energy sharing and the utilisation of waste heat. Already, the Pan-European Thermal Atlas of Heat Roadmap Europe [97] indicates a theoretically available sum of 1.33 PJ of waste heat in the urban vicinity about 12 km from Palermo. Moreover, the coastal and coastal island cities have ample opportunities to displace the use of fossil fuels based on multiple uses of land and offshore sources of renewable energy. In this context, four main strategies can be identified to accelerate progress towards reaching net-zero emissions: (1) increasing the share of electricity in transport, (2) increasing the share of renewables in the energy mix, (3) reducing energy demand and increasing demand flexibility, including in the water sector, and (4) eliminating the use of natural gas for low exergy demands as important steps towards decarbonisation.

Figure 13.

Sankey diagrams for energy (left, MWh) and CO₂ emissions (right, tonnes) for Messina (a), Trieste (b), and Cartagena (c); based on data in [63], [66] and [55]

Figure 14.

Depiction of the upward shift in performance with a renewable energy scenario

Figure 14 provides a view of the changes in the SDEWES Index when the results for the newly benchmarked cities are re-calculated, considering that these same cities will be frontrunners in transitioning to renewable energy to reach net-zero emissions. For example, in 2022, the islands of Sicily and Sardinia received 208 MW and 137 MW of new solar photovoltaic installations, respectively [123]. There were also 113 MW of new wind energy installations in Sicily, while significantly less in Sardinia. In addition, 42 municipalities in Italy reached 100% renewable energy municipalities, including the power sector [123]. The potential impact of a pathway that allows the 11 benchmarked cities to reach renewable energy systems and net-zero CO₂ emissions is represented in the SDEWES Index by allowing these cities to receive the best possible normalised value of 10.000 in indicators on CO₂ emissions under D₅. Since the aim of the scenario is to represent a decoupling between energy usage and CO₂ emissions, all else is taken equally. In reality, there will be multiple co-benefits for other indicators within the scope of the SDEWES Index that are not further quantified in this scenario despite their importance. Even in this base situation, the attainment of the best possible values in indicators on CO₂ emissions enables 6 of the newly benchmarked cities to take place among the top 25% of cities among the pioneering cities (the blue diamond markings that take place within the blue ellipse area). Such an upward shift in index performance with corresponding improvements in rankings is also valid for the remaining newly benchmarked cities, as observed in Figure 14, including Cartagena.

Figure 15 further quantifies the improvements in the ranking results based on the considered scenario where lower rank values signify a higher performance. Among the cities that have achieved the most progress in index performance and ranking based on the 100% renewable energy scenario with net-zero emissions is Palma de Mallorca, which has a rank of 32 among all 132 cities. Such an improvement allows this city to jump exactly two quartiles from the lower 50%−25% quartile to the upper 25% among the pioneering cities. The first three cities also contained an exchange of rank, with Palermo, originally ranked third, now being able to receive the top rank among the newly benchmarked cities. Prior to the 100% renewable energy scenario for net-zero emissions, Messina held the top rank, which is second rank based on Figure 15. In the overall ranking of the 132 cities, Palermo and Messina receive ranks of 14 and 17, respectively.

Figure 15.

Improvements in rank based on the net-zero emissions scenario (dimensionless)

The co-benefits of the scenario for local job opportunities in each city are calculated based on eq. (2) and eq. (3) in the method of the research work. In the context of considering that all else is equal for the scenario, the values of E_I per city C_j are based on the data compilations for the energy indicators under D₁ in Table 1. Opportunities for increasing energy savings can enable conditions that are closer to this simplification despite population growth in cities. Statistics on local job opportunities per GWh in each category of renewable energy technologies are based on the values in Table 10.

The year of the statistics for the number of jobs by renewable energy technology [68] considers the time lag in the most recent statistics for renewable energy production in GWh from [69] for consistency when obtaining variable β*. The values of two other coefficients in eq. (2) are based on the results of a 100% renewable energy scenario for Europe [70] within a global modelling study across the energy, transport, and desalination sectors [71]. In Europe, the share of electricity in the overall renewable energy mix is modelled to be 66% with a complete electrification of the transport sector. Such a finding is taken as the value of γ for the electrification ratio in eq. (2). Within this share, the amount of electricity generation for the energy, transport, and desalination sectors is driven mainly by contribution from solar energy that is followed by wind energy and about a 5.5% contribution from hydropower, bioenergy, geothermal, and marine energy. The last column of Table 10 provides the specific percentages that are also used as the coefficient δ in eq. (2).

The summation of the product of the relevant values for each category of renewable energy technology per benchmarked city C_j under the scenario is provided in Figure 16. These results underline the significant employment opportunities that can be captured with a transition to renewable energy technologies. Given the assumptions of the scenario, Palma de Mallorca and Palermo are estimated to obtain the highest employment benefits with 4,945 and 2,866 jobs, respectively. The amount of renewable energy that is involved in the scenario values in these two cities is about 1.1 times higher in Palermo, while β^* ratios are different. Palma de Mallorca benefits from about 1.35 jobs per GWh, and Palermo benefits from about 0.60 jobs per GWh in the context of Spain and Italy, respectively, based on Table 10. Such values that are based on recent statistics are higher than in previous years considering progress [68]. Comparatively, the values are within the range of local employment in other studies [124] with potential ahead. Across the 11 different coastal and coastal island settlements, there is potential for generating an estimated 18,062 jobs in the renewable energy sector based on the scenario of this study.

Figure 16.

Estimated co-benefits for local job opportunities under the scenario

The results of this research work are aligned with the action points in the Smart Islands Declaration and the aim of decarbonising over 1000 European islands by 2030. Table 11 provides a comparison of the 10 action points that are declared within the Smart Islands Initiative [73] and the dimensions of the SDEWES Index. As an original composite indicator to benchmark cities, characteristics that may be even more specific to the socio-economic and geographical context of coastal or coastal island cities are not targeted directly. Even so, there are certain correspondences between the action points of the Smart Islands Declaration and the dimensions of the SDEWES Index. Such correspondence is strengthened based on a focus on sustainable development and an integrated approach across energy, water and environment systems. In addition, the action point that is related to the need to provide “new and innovative jobs locally” [73] is addressed with a focus on the job opportunities that are possible through a renewable energy transition, as emphasised in the scenario-related analyses of this research work. Other synergistic options based on circular economy, eco-tourism, cultural tourism, and local R&D and innovation are also possible. Collective financing schemes, as emphasised in the Declaration, can be used to support progress for decarbonisation alongside a quadruple helix R&D and innovation model [125].

Strategies across the energy, transport, waste, and water sectors are gaining speed, particularly in islands [4], and related progress will improve the values of multiple indicators across the dimensions of the SDEWES Index. In comparison to the Greening the Islands Observatory [72] of the Greening the Islands Initiative [126], most of the available good practices continue to target sectors, as summarised in Table 12. At the same time, implementations that directly represent cross-sectoral perspectives are emerging, including water desalination with solar energy. In accordance with the aims of the initiative, there is room for improvement also in enabling islands to become living laboratories for more integrated approaches, including the circular economy.

Currently, the good practices in Table 12 involve solar, wind, wave, and bioenergy, energy storage, desalination technologies, water conservation, and electromobility. The importance of eliminating the brine discharges of desalination plants and protecting marine water resources is further represented among the implementations. In the context of the present study, the newly benchmarked coastal and coastal island cities provide additional good practices, including net-zero energy buildings and building integrated PV installations in cultural buildings in Palermo, including an initial flexible array of 20 kW_e solar PV panels on the roof of the Teatro Crystal. In aspects of regulatory tools and governance, the target of reaching decarbonization with renewable energy in the Balearic Islands (the location of Palma de Mallorca) is supported by the Law on Climate Change and Energy Transition [127]. The Law stipulates that emissions are to be reduced by 90% by the year 2050 based on 100% renewable energy and increases in energy efficiency with binding targets at the local level. In addition to measures for the power sector, new diesel and all new fossil fuel vehicles will be banned from the years 2025 and 2035 onward, respectively. Some public concerns about the issue of waste being imported for waste-to-energy may be addressed with accelerated solar and wind investments.

In addition to the Balearic Islands, the islands of Samsø in Denmark, Graciosa in Portugal, Gotland in Sweden, and Wight in the United Kingdom, as well as coastal cities on other islands, including Copenhagen and Edinburgh, have adopted targets for climate neutrality with 100% renewable energy [128]. In the race against time to limit global warming to as close as possible to an average increase in mean surface temperature of 1.5 °C above pre-industrial levels, coastal and coastal island cities have responsibilities not only to mitigate CO₂ emissions for the sake of the global climate similar to all cities but also to protect themselves against additional climate impacts. The striking differences between the impacts of 1.5 °C and 2.0 °C of global warming on sustainable development include an additional 10 million people who will be directly exposed to flooding in coastal cities due to sea level rise and extreme weather events for a total of up to 79 million people [129]. Moreover, up to 360 million more people will be exposed to lower crop yields, and an extra 2.2 billion people will be exposed to heat waves around the world, which will cause 8% more water stress [129]. Impacts on ecosystems are extremely severe, with 99% of coral reefs at risk of being bleached [33] and a conservative estimate of 1 million animal and plant species being threatened with extinction [130]. Already, multiple tipping points in the global climate are on the verge of irreversible change [131]. In short, the climate crisis represents an existential threat to civilization with irreversible damage on ecological balances. All means are necessary to provide additional impetus to implementing effective solutions, including in coastal and coastal island cities.

Similar comparisons can provide related perspectives for coastal settlements in Latin America, including Viña del Mar, which was the venue of the 4^th Latin American Conference on SDEWES [132]. At the national level, the government recognises the importance of renewable energy, which is estimated to have a total potential of more than 1800 GW, with about 1180 GW coming from solar PV [133]. This value is about 70 times the recently installed capacity. Based on the National Green Hydrogen Strategy of Chile [133], there is an ambition to produce green hydrogen in at least two hydrogen valleys with a production capacity of about 200 kilotons per year by 2025. In addition, there is a target to produce the cheapest green hydrogen on the planet with a cost of less than 1.5 USD per kg of green hydrogen by 2030 [133]. Based on the examples of the 11 coastal and coastal island settlements in this study, there are plenty of reasons why coastal settlements in Chile, such as Viña del Mar, can also pursue renewable energy scenarios. With proper energy planning [134], the region can eventually support the green hydrogen strategy of the country, advance in making progress towards climate neutrality in Chile [135], and demonstrate promising opportunities for accelerating the energy transition in Latin America. Other promising pathways in Latin America include limitations on fossil-fuel-based electricity generation in Mexico as mandated by a national energy bill [136]. In addition, a transition strategy indicates ways to attain a 75% share of renewable electricity generation towards a defossilised, renewable energy system, including optimal capacity combinations of bioenergy, wind, and solar PV capacities [136]. Globally, jobs in the renewable energy sector have reached 13.7 million in 2022 [137] and progress to triple renewable energy by 2030 will increase co-benefits for people and the planet.

In an outlook towards future possibilities for benchmarking, one of the limitations of the present research work is that the data inputs into the SDEWES Index are based on published sources of data within an extensive compilation process due to the distributed but harmonised data sources. Across the dimensions, the data sources also include those from geographic information systems and even remote sensing. Digitalisation trends and new initiatives can be used to benefit the multi-parameter data compilation processes, especially when data inputs into the SDEWES Index are linked to integrated platforms. For example, a Digital Earth Viewer aims to represent multiple heterogeneous data sources, including both mixed observational and simulation data [138]. The flagship European initiative of Destination Earth also seeks to develop an accurate digital model to monitor, simulate, and predict aspects related to environmental data, climate change data, data for renewable energy and energy efficiency, and other domains [139]. These advances provide opportunities to support the applications of the SDEWES Index.