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Article

Spread Is Better: Suitability for Climate Neutrality of Italian Urban Systems

EPiC Earth and Polis Research Centre, Università Iuav di Venezia, 30123 Venice, Italy
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(18), 13710; https://doi.org/10.3390/su151813710
Submission received: 3 August 2023 / Revised: 4 September 2023 / Accepted: 6 September 2023 / Published: 14 September 2023

Abstract

:
In light of the challenges required by the European Green Deal policies concerning the achievement of climate neutrality by 2050, this paper analyses the suitability of different Italian urban systems for energy consumption and CO2 emission reduction. In anthropised territories, there are strong relationships between energy consumption, climate-changing emissions and settlement patterns. Lands considered low could increase their rating because they have far greater environmental, energy and land resources than more pivotal ones. After an Italian-scale overview of the ecosystem capacities, this paper develops a detailed study of three exemplary areas: the northeast, the northwest, and the central-west coast. The analysis uses Burkhard’s matrix for ecosystem values and the energy consumption 2021 report of the National Energy Authority. The first finding is that the northeast region, characterised by spread and rarefied urbanisation, has a peculiar suitability for climate neutrality. In the results, spread territories perform much better than centralised ones. The coexistence of little urban cores, space for vegetation and a widespread water network promotes synergies for enhancing an ecosystem approach to land design.

1. Introduction

This paper aims to define the suitability of Italian territorial settlement models based on the challenges required by the European Green Deal to achieve climate neutrality by 2050. The research has three motivations. The first is to recognise which territorial settlements are best suited to achieve climate neutrality. The second is to identify whether there is a need to convert spread cities towards more centrality. The third is to provide a framework for differentiating tailor-made local actions for neutrality.
The European Green Deal is a programme developed by the European Commission to fight climate change, bringing Europe to climate neutrality. The main goals of this programme are to have no more greenhouse gas emissions generated by 2050, economic growth dissociated from resource use and no person and place neglected [1,2,3].
Addressing the problem of the suitability of the Italian territorial settlement models means, first and foremost, understanding how to recognise the level of preparedness of the Italian system, which is quite complex with highly dissimilar settlement, economic and service models. This system is characterised by a mix of more peripheral areas, often in the medium or high mountains, and more central and strategic zones, mainly located on the coast or in the open plain. In recent decades, a growth in economic and demographic flows from the peripheries of this territory towards its centres is evident.
The tendency is to represent the aggregation compactly as more sustainable and functional in mitigating climate change. This article questions this assumption. A careful analysis of the territorial settlement could testify to a relevant capacity in the neutrality of areas with medium polarisation and high sprawl, considered unattractive. Large centres depend entirely on energy, food, water and risk in less densely urbanised areas, and analysis of the adequacy for neutrality cannot consider these aspects. The spread areas testify to the great proximity of ecosystem services to the inhabited areas and the significant redundancy in infrastructure and manufacturing locations. The spread urban system composed of medium-sized cities and axial ramifications between them is strategic on a European scale and widely described in the literature [4]. Although growth in economic and demographic flows from the peripheries of peripheric territory towards its centres is evident, a careful analysis of the state and sustainability prospects of the settlements will help in recognising a fundamental character that is often underestimated in the development of a project for sustainability [5]: the relevance of the dependence in terms of energy, food, water and risk of the centres in the less urbanised areas, much less polarised in the spread territories [6].
The construction market cycle we are currently experiencing is the first in which transforming the built environment is the most relevant way to develop new urban areas. Urban development is one of the major causes of the production of fossil emissions in Europe and among the hardest to abate. Urban development will have to wisely select which types of settlement schemes to favour because the preferred scheme will significantly affect the future capacity for neutrality. Transforming the settlement scheme to achieve neutrality will cause significant fossil emissions. Therefore, it is essential to choose the paths to neutrality correctly.
Questioning the preferred development model for European objectives and abandoning the narrative of the inevitable failure of the land of sprawl and extensive consumption [7,8,9] means understanding this dependency link and fostering a shift from a polyperiphery geography to a nonhierarchical, networked one [10]. The analysis outcomes can provide critical reflections on spatial and urban development perspectives at the European level, suggesting a change in mindset for all design and planning processes of the significant spatial transformations underway for climate change adaptation and mitigation [11,12]. To date, real estate and census values predominantly drive spatial developments, concentrating transformations towards the centres with the highest financial availability and the soils where the value is highest. The indicators of consumption and climate-changing emissions illustrated in the following lines prompt reflection on the potential value chains that median territories have [13,14] when observing the environmental challenges of the near future [15,16,17,18].
The application context of this research is Italian territory. Deepening the state condition and the process profile necessary for neutrality in Italy is particularly relevant to the Euro-Mediterranean system. Italy has different urbanisation conditions: spread, as in the northeast; polycentric networked, as in Emilia-Romagna and on the Adriatic coast; and monocentric, as in the northwest and the centre-south. These conditions correspond to different settlement schemes and economic and service management patterns. Understanding which ones are most efficient in terms of achieving the neutrality objectives proposed by the European Green Deal is particularly significant because it will not only help the development of sustainability in Italy but also allow the entire Euro-Mediterranean region to orient its urban development.
Italy not only presents several scenarios to analyse in a homogeneous environment, reducing the complexity of comparison, but also has a deep tradition of research and projects in sustainability and neutrality. Applied research and projects vary in many fields, from transport networks to energy networks, disaster risk to adaptation of built systems and circular economy to waste management.
For an in-depth look at the general Italian situation in terms of sustainability issues, the most known references are the works of Musco [19,20,21], De Gregorio [22] and Lanzani [23,24,25]; however, the literature in this field is vast [26,27,28,29,30,31]. Aside from the general studies, some research presents a systematic review of the regeneration of minor fabric in Italy, which is fundamental to the research described here [29,32,33].
There are several studies on the relationship between the territorial context, the infrastructural capacity of public mobility, the availability and safety of soft mobility infrastructures and the impacts of private motorised transport [34,35].
There are many works [36,37,38,39,40] on the topics of risk and adaptation due to the high risk of Italian territories concerning climate (landslides, floods, avalanches, drought, heat, intense precipitation, combined climate-geological risks, sea storms, erosion).
Several valuable experiments have been carried out in the last decade in Italy on the topics of circular economy and waste management concerning domestic waste, industrial waste, integration between agro-food production and waste disposal and the conversion of waste into energy [41,42,43,44,45,46].

2. Materials and Methods

This research selected three areas capable of portraying the main recognisable models to investigate the condition of the Italian territorial fabric regarding neutrality. The areas have homogeneous characteristics regarding the number of inhabitants and strategic and economic value on an Italian and European scale. These areas are the northeast (understood as the Veneto Region, Friuli-Venezia Giulia Region, Province of Trento, Province of Bolzano), the Region of Lombardy and the Region of Lazio. The Region of Lombardy is representative of the northwest area. The Region of Lazio is representative of the central area. While the northeast has several residents and an economic system that necessitated consideration of the entire area, the other two regions represent a large part of the residents and economy of the reference areas. Considering the whole northwestern and central areas would be misleading for the metrics mixing urban and nonurban areas’ average energy consumption and emission values.
The three areas have very different settlement patterns, economic models, extensions and densities. The northeast is predominantly a spread territory, with small centres and great sprawl, the economy being predominantly manufacturing-industrial, organised into hundreds of small centres. Lombardy has a monocentric structure with a production-industrial economy intensely concentrated around the Milan-Bergamo metropolitan system [47]. Lazio has a monocentric system with a predominantly service-based economy, with more than 75 per cent of the regional GDP of tertiary origin strongly centralised in Rome. Table 1 shows the data comparing the territorial systems considered.
This research exclusively uses certificated open data released by regional and state administrative bodies and official bodies for environmental protection and research (ISPRA, ARPAV, ARPA FVG, APPA, DPC, TERNA) as described in the final note. This study also used statistical data certified by ISTAT and risk data produced internationally by EU-ESPON and IPCC [49,50,51,52,53,54,55,56,57,58,59]. The data processing, developed in a GIS environment, amalgamated the data while paying attention to the scale of the reference data to avoid statistical simplifications or unsound projections.
The survey selected four key indicators to conduct the analysis: average energy consumption (A); exergy capture (I2); global climate regulation (I3); and energy-biomass (I4). All energy and environmental values were calculated based on the land use of the northeast as expressed by Corine Land Cover 2018 (CLC).
(A) The first environmental indicator is derived from Terna’s energy consumption inventory and describes for each CLC item the average value per hectare of the two anthropogenic impacts.
The subsequent indicators are derived from Burkhard’s matrix [50,51,52,53]. The matrix provides a qualitative picture of the ecosystem services in the territory concerned. The indicators describe these services in terms of extension. Extents per region (S) are expressed as a percentage of land. Burkhard’s matrix is a tool for assessing ecosystem services first defined by Benjamin Burkhard in 2009 and applied in many studies from different fields. The matrix, refined in subsequent publications, determines the levels of ecosystem services of each land cover type (based on Corine Land Cover legend) on qualitative scales for 30 different services organised into 3 categories: regulating services, provisioning services and cultural services.
(I2) Exergy capture measures the fraction of energy that can be transformed into mechanical work. In ecosystems, captured exergy is used to build biomass (e.g., through primary production) and structures. Its representation is a picture of the extent to which ecosystems cannot transform the energy received into usable energy; by extension, it is also a measure of a specific ecosystem’s metabolic cost and efficiency. Exergy is conserved in reversible processes and diminished in irreversible processes; it is used in thermo-economics to assess the economic value of an energy flow.
(I3) The Global Climate Regulation is an integrated indicator that measures potential sinks or sources of CO2, methane and water vapour in 5 classes. Ecosystems play an essential role in climate, both in the absorption and emission of greenhouse gases. The Global Climate Regulation indicator in this research has a structure of three classes: the territories that can capture more CO2 than they emit and have indices between +1 and +5; the second shows the territories that are sources of climate-altering gases, which emit more CO2 than they can absorb, with indices between −1 and −5; the third shows the neutral territories, whose balance between potentially produced and absorbed climate-altering substances is zero and which have a slight surplus and deficit, with indices between −1 and +1.
(I4) Energy-biomass measures, on the one hand, are a function of the presence of trees or plants that can potentially be used as an energy source and, on the other hand, of the potential demand for energy concerning the activities of a given land use. This energy indicator is structured into 5 value classes from the measurement of woody or plant biomass/ha, kJ/ha or energy demand. The biomass energy indicator has a structure of three classes: the first aggregates energy-credit territories, i.e., territories that produce more energy than they consume and have indices between +1 and +5; the second aggregates debit territories, which consume more than they can produce, with indices between −1 and −5; the third aggregates neutral territories, whose balance between potentially produced and consumed energy is zero and which have a slight surplus and deficit, with indices between −1 and +1.
Energy consumption indicators (I1) are expressed in GwH. The average energy consumption value (A) of each region is expressed in GwH/Km2. Exergy capture indicators (I2), global climate regulation (I3), and energy-biomass (I4) are expressed in the value of ecosystem service per percentage of regional territory with that specific land use according to Formula (1)
In = Bn × S
Bn represents the value attributed by the Buckhard matrix to a given land use for an ecosystem service n (exergy capture; global climate regulation; energy-biomass).
The overall ecosystem value of the area is a weighted sum of the In values for each of the three indicators considered. According to the procedure Burkhard [50,51,52] indicated and repeatedly applied in the literature in the territorial evaluation of ecosystem services, the overall ecosystem value will allow a comparison between the ecosystem capacity of the three regions.
From the comparison of these four indicators will emerge an assessment of the current state of sustainability, expressed by current energy consumption, and of potential sustainability concerning the settlement pattern present in the different territories. Once this research established these relationships, the article proceeds by cartographically comparing the distribution of ecosystem services, mapping the distribution of the most suitable tissues to achieve climate neutrality according to the indications of the European Green Deal. The research concludes by comparing the findings of the geo-statistical survey and the cartographic survey.

3. Results

From the application of the method described, we recognise a significant contradiction between the current state of energy consumption, often understood as a significant indicator of a territory’s capacity for sustainability even in the future, and the territorial ecosystem capacity in the application of the Burkhard matrix.
In Table 2, we report the energy consumption of the northeast and, for comparison, of Lombardy and Lazio. Although the areas differ in extension, the indicators are expressed by the percentage of soil type and energy consumed and, therefore, are comparable. We report only the most significant entries by topic and for the territories considered.
The table shows a sizeable average energy consumption (A) in the northeast and a relatively low consumption in Lazio, with an intermediate value for Lombardy. The compact city proves to be advantageous to date because it contains logistical spoils. Thus, in a scenario of energy production from imported fossil fuels, it consumes less. The limited energy consumption is generally considered indicative of greater sustainability, but is this true? Energy consumption does not provide information about the mitigation capacity of emissions.
Table 3 shows the values for the three indicators for the northeast and, for comparison, for Lombardy and Lazio. The table shows the most significant items by topic and the territories considered. The value of sea and ocean is considered on an equal minimum territorial component for all sea-facing territories to avoid it weighing too heavily on the total, distorting the overall result.
Observe the difference in values between the three territories, especially for the total values of I2, I3 and I4. The territory with the best performance is the northeast, especially regarding Global Climate Regulation and energy-biomass values. The graph below in Figure 1 compares the four general indicators. The values have been normalised on a 0–1 scale to be comparable. The value of average energy consumption is shown here in the form of 1-A (A’) to be more comparable at a glance.
The values depicted show a potential radical reversal of the sustainability rating of settlement models when considered in terms of the ability to produce biomass energy autonomously on site, containing fuel transport, and the ability to eliminate climate-altering gases (I3) directly.
Next, the research produces a cartographic comparison between Northeast, Northwest and Central Italy. Below are the three figures representing the spatial distribution of the Buckhard matrix results for the I3 indicator. The decision to publish the maps related to this indicator has two reasons. Firstly, there is a significant similarity between these maps and the energy-biomass maps, and thus, through these maps, we also offer pretty approximate information on the geographical distribution of local energy production capacity. Secondly, the climate-changing gas abatement was more valuable between these two indicators because it is the first operational factor towards climate neutrality among ecosystem services. The maps represent the territories most capable of climate neutrality in black. Figure 2 shows the map of the northeast territories. As described above, the northeast has the settlement structure of a spreading city, densifying into a few main centres of not considerable size and ramifying along axes, continuously interspersing vegetation and water systems. Neutrality-functional ecosystem services are close to neighbourhood-scale settlements. This continuity offers a basis for designing the territory of neutrality without radical upheavals in urban forms. Mobility systems and infrastructures must become a capillary network in the diffuse grid, but a significant relocation of settlements is unnecessary.
The map geographically corroborates the capabilities that emerged in the statistical survey and reaffirms the potential relevance of this territory. From what emerged in the geo-statistical and geographical investigation, we can state that the northeast territories have, at the same time, relevant energy consumption but equally significant capacities in fixing climate-altering gases and opportunities for energy production from renewables. Therefore, this is a vast territory in-between, which, if correctly oriented, presents an outstanding possibility to achieve the climate neutrality expected from European policies. In the following Figure 3, we will see the potential neutrality in the northwest.
In the northwest, the territories of energy and climate neutrality are limited. They are located just to the south of the extensive metropolitan system. Investments in greening in Milan have been significant in recent years and have brought results. However, looking at this map, we can see how these investments are severely limited in their systemic effectiveness and how the present settlement patterns contain the prospect of radical transformation towards neutrality. The Lombardy metropolis has a density and compactness that does not allow for the penetration of ecosystem services in abundance. In the following Figure 4, we see the potential neutrality in the centre.
For the centre, too, we can see a considerable white centralisation, corresponding to the inhabited city, surrounded by an intense and extensive black area. The city of anthropic services and the city of ecosystem services are separated, requiring significant logistical investments for the exchange between the two, especially for food and electricity production and the abatement of climate-changing gases. Again, the settlement patterns do not make a profound transformation to acephalous grid-to-grid models easy.
The territories of climate neutrality are much more identifiable in the northeast, as emerged in the statistical survey. Therefore, the spread cities and medium-sized centres have characteristics favourable for climate neutrality. Summarising what has emerged from the geo-statistical and geographical survey, we can state that the territories of the northeast have great energy consumption concerning their extension but equally significant capacities for fixing climate-altering gases and opportunities for energy production from renewables. We are, therefore, faced with a vast territory in between, which, if correctly oriented, presents excellent resilience and is naturally ready for the neutrality expected from European policies. The situation is different in the northwest and Lazio, where the climate neutrality territories are strongly polarised, exogenous and located south of the extensive metropolitan system described above.

4. Discussion

The research was limited in terms of territorial extent and the indicators included to avoid contaminating the results with too much complexity. The assumption underlying the research was radical. Denying a direct connection between the compact city and sustainability merits cautious evaluation. The application of the research method led to three primary outcomes. In the future, it will be possible to repeat the investigation on a larger scale and with more complexity to investigate the most effective ways to achieve climate neutrality.
1. The general indicators of ecosystem services per region depicted in Figure 1 are very different, suggesting a correlation between settlement schemes and the availability of services, primarily in the abatement of climate-altering gases and biomass production. Furthermore, the maps (Figure 2, Figure 3 and Figure 4) show the different distribution of ecosystem services in the different regions, describing different degrees of availability of ecosystem services according to settlement patterns. The first result of the research is the confirmation of a significant dependency between settlement patterns and the ability to achieve climate neutrality.
2. The regions with a strong polarisation between the centre and peripheries are usually considered more efficient in sustainability. Nevertheless, ecological performance is weak in Lombardy and Lazio, independent of economic and social aspects. On the contrary, the northeast’s spread structure shows higher performance in indicators. Therefore, spread structures may exert less effort to achieve neutrality for spread settlement patterns than a pattern with relevant separation between inhabited and ecological zones.
3. The territory of neutrality in the spread settlement schemes is not distributed outside the urbanised areas. It represents a background and support for land development. First, it is an ecological support: it is a generator for the production of biomass, a system for the absorption of climate-altering gases, and an infrastructure for the mitigation of hydraulic and heat risks. It is also social support because many practices related to leisure time and slow mobility of the diffused city occur. Finally, it is geographical support because the grain and density of its partitions of ditches, hedges and unpaved roads define the palimpsest that ground the landscapes characterising their regions [34,35,36,37]. It, therefore, seems helpful to encourage more proximity between inhabited areas and ecosystem services.
The research findings state that the northeast has a vast territory quite effortlessly ready for improving the climate neutrality expected in the Green Deal agenda [1,2]. The neutral territory of the northeast crosses small and medium-sized cities and diffuses urbanisation systems [9,49]. It is a cultivated and weakly urbanised space that forms the backdrop to the scaffold of infrastructures, diffuses urbanisation and small towns that describe the entire Veneto-Friuli metropolitan system, extending around half of the Po Valley megalopolis [50]. It is a territory contained between the significant biomass reserves of the Alps and the Apennines, crossed by that dense network of rivers, ditches and canals, wetlands and marshes, which, over time, man’s work has made habitable [51]. It is a potential reserve of food and energy, suspended between scarcity and excess of water, which climate change has made increasingly fragile [52,53,54].
Northeastern Italy is on the edge of a transition of its settlement scheme based on a nonecosystemic and spatialised reading of energy consumption and climate-changing gas emission data. What has emerged here, however, suggests a decidedly reverse process, i.e., a transition of an ad hoc territorial project, which must not be distorted in its distribution and in which the territory of climate neutrality may play a decisive role.
What emerges from the research allows for further reflection on proximity. Very often, the assessment of the risk status of territory for climate [60,61,62,63,64] disregards the conditions of resource availability [65]. The maps produced by ESPON [7,66] represent the metropolitan areas of London, Paris and Berlin as being at shallow risk. ESPON map derives its considerations in the correspondence from the location of the expected extreme events [67]. However, the cascading effects of the event, such as the interruption of the production of energy, food, timber or other natural goods, are not considered. These metropolises, which correspond on a larger scale to the centre of Lombardy, have no such production. How safe are they, therefore, in light of what emerges from identifying ecosystem services? New research can question the effective resilience of large metropolitan systems testified by ESPON to assess whether the spatial design horizons are predefined to date, i.e., concentration.
Given that climate neutrality is a long-term goal, the research results could take unexpected directions at present for potential shifts in energy technologies, socioeconomic trends or climate impacts. The suitability of the identified territorial models could become obsolete if the directions hypothesised at present are not confirmed. For example, a large availability of house-by-house energy production could reduce the need for biomass and proximity to water or wind sources, favouring centralised urban systems. On the other hand, a significant economic collapse or difficult access to food distribution might reinforce the need for sprawl. Unexpected climate impacts, connected, for example, to the global average temperature exceeding 4 degrees, could lead to the total nonhabitability of settlement schemes considered to date. However, these scenarios are currently not included in the accepted models or are very remote and will have to be considered in subsequent confirmatory studies to verify the suitability of the development models undertakens.
In conclusion, the spread settlement model, which is a territory that merges countryside and city in a third type of articulation, has a relevant strategic potential if duly infrastructured for sustainable mobility and grid-to-grid energy production. This observation must become a planning horizon for rethinking land value determinations and reorienting development plans.

Author Contributions

The research was directed, conceptualised and developed by L.F., M.B. and L.F. worked together to detail the methodology and develop the calculation. The cartographic surveys were carried out by L.F. The writing of the paper is divided as follows: L.F. can be attributed paragraphs 2, 3, 4; M.B. produced paragraph 1. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by PNRR-Piano Nazionale di Ripresa e Resilienza, Missione 4 “istruzione e Ricerca”, Componente 2 Investimento 1.5, Ecosistema INEST-Interconnected Nord-Est Innovation, Spoke 4. The research coordinator for Spoke 4 is Prof. Lorenzo Fabian.

Data Availability Statement

The research considers only certificated open data released by regional and state administrative bodies and official bodies for environmental protection and research: ISPRA-isprambiente.gov.it/it, ARPAV-arpa. Veneto.it, ARPA FVG-arpa.fvg.it, APPA-appa.provincia.tn.it, DPC-protezionecivile.gov.it/it/, TERNA-terna.it/it.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. European Commission. Comunicazione Della Commissione al Parlamento Europeo, al Consiglio, al Comitato Economico e Sociale Europeo e al Comitato Delle Regioni Il Green Deal Europeo. 2019. Available online: https://eur-lex.europa.eu/legal-content/IT/TXT/?uri=COM%3A2019%3A640%3AFIN (accessed on 15 July 2023).
  2. European Commission. A European Green Deal. Available online: https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/european-green-deal_en (accessed on 15 July 2023).
  3. D’Adamo, I.; Gastaldi, M.; Imbriani, C.; Morone, P. Assessing Regional Performance for the Sustainable Development Goals in Italy. Sci. Rep. 2021, 11, 24117. [Google Scholar] [CrossRef]
  4. Meng, X.; Jiang, Z.; Wang, X.; Long, Y. Shrinking Cities on the Globe: Evidence from LandScan 2000–2019. Environ. Plan. Econ. Space 2021, 53, 1244–1248. [Google Scholar] [CrossRef]
  5. Camagni, R.; Borri, D.; Ferlaino, F. Per un Concetto di Capitale Territoriale, in BORRI D., FERLAINO F. Crescita e Sviluppo Regionale: Strumenti Sistemi e Azioni; Franco Angeli: Milano, Italy, 2009; pp. 66–90. [Google Scholar]
  6. Bezner Kerr, R.; Hasegawa, T.; Lasco, R.; Bhatt, I.; Deryng, D.; Farrell, A.; Gurney-Smith, H.; Ju, H.; Lluch-Cota, S.; Meza, F.; et al. Food, Fibre, and Other Ecosystem Products. In Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; Pörtner, H.-O., Roberts, D.C., Tignor, M.M.B., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., et al., Eds.; Cambridge University Press: Cambridge, UK, 2022. [Google Scholar]
  7. ESPON. ESPON Climate—Climate Change and Territorial Effects on Regions and Local Economies in Europe. 2022. Available online: https://www.espon.eu/climate (accessed on 15 July 2023).
  8. Peduzzi, P.; Dao, H.; Herold, C.; Mouton, F. Assessing Global Exposure and Vulnerability towards Natural Hazards: The Disaster Risk Index. Nat. Hazards Earth Syst. Sci. 2009, 9, 1149–1159. [Google Scholar] [CrossRef]
  9. Richard Eiser, J.; Bostrom, A.; Burton, I.; Johnston, D.M.; McClure, J.; Paton, D.; van der Pligt, J.; White, M.P. Risk Interpretation and Action: A Conceptual Framework for Responses to Natural Hazards. Int. J. Disaster Risk Reduct. 2012, 1, 5–16. [Google Scholar] [CrossRef]
  10. Secchi, B. Shifting Models. In Water and Asphalt: The Project of Isotropy; Viganò, P., Fabian, L., Secchi, B., Eds.; UFO: Amsterdam, The Netherlands; Park Books: Zürich, Switzerland, 2016; pp. 202–209. ISBN 978-3-906027-71-5. [Google Scholar]
  11. Sturiale, L.; Scuderi, A.; Timpanaro, G. Citizens’ Perception of the Role of Urban Nature-Based Solutions and Green Infrastructures towards Climate Change in Italy. Front. Environ. Sci. 2023, 11, 1105446. [Google Scholar] [CrossRef]
  12. Bassolino, E.; D’Ambrosio, V.; Sgobbo, A. Data Exchange Processes for the Definition of Climate-Proof Design Strategies for the Adaptation to Heatwaves in the Urban Open Spaces of Dense Italian Cities. Sustainability 2021, 13, 5694. [Google Scholar] [CrossRef]
  13. Coppola, A.; Lanzani, A.S.; Zanfi, F.; Del Fabbro, M.; Pessina, G. Ricomporre i Divari. Politiche e Progetti Territoriali Contro Le Disuguaglianze e per La Transizione Ecologica; Il Mulino: Bologna, Italy, 2021. [Google Scholar]
  14. Kercuku, A.; Curci, F.; Lanzani, A.; Zanfi, F. Italia Di Mezzo: The Emerging Marginality of Intermediate Territories between Metropolises and Inner Areas. Region 2023, 10, 89–112. [Google Scholar] [CrossRef]
  15. Schipper, E.L.F.; Revi, A.; Preston, B.L.; Carr, E.R.; Eriksen, S.H.; Fernández-Carril, L.R.; Glavovic, B.; Hilmi, N.J.M.; Ley, D.; Mukerji, R.; et al. Climate Resilient Development Pathways. In Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; Pörtner, H.-O., Roberts, D.C., Tignor, M.M.B., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., et al., Eds.; Cambridge University Press: Cambridge, UK, 2022. [Google Scholar]
  16. Caretta, M.A.; Mukherji, A.; Arfanuzzaman, M.; Betts, R.A.; Gelfan, A.; Hirabayashi, Y.; Lissner, T.K.; Lopez Gunn, E.; Liu, J.; Morgan, R.; et al. Water. In Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; Pörtner, H.-O., Roberts, D.C., Tignor, M.M.B., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., et al., Eds.; Cambridge University Press: Cambridge, UK, 2022. [Google Scholar]
  17. Dodman, D.; Hayward, B.; Pelling, M.; Broto, V.C.; Chow, W.; Chu, E.; Dawson, R.; Khirfan, L.; McPhearson, T.; Prakash, A.; et al. Cities, Settlements and Key Infrastructure. In Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; Pörtner, H.-O., Roberts, D.C., Tignor, M.M.B., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., et al., Eds.; Cambridge University Press: Cambridge, UK, 2022. [Google Scholar]
  18. Davoudi, S. Climate Change, Securitisation of Nature, and Resilient Urbanism. Environ. Plan. C Gov. Policy 2014, 32, 360–375. [Google Scholar] [CrossRef]
  19. Pietrapertosa, F.; Salvia, M.; Hurtado, S.D.G.; d’Alonzo, V.; Church, J.M.; Geneletti, D.; Musco, F.; Reckien, D. Urban Climate Change Mitigation and Adaptation Planning: Are Italian Cities Ready? Cities 2019, 91, 93–105. [Google Scholar]
  20. Russo, M.; Fabian, L.; Morello, E.; Musco, F. La Resilienza al Cambiamento Climatico Come Paradigma Dell’Agenda Urbana; FrancoAngeli: Milano, Italy, 2017. [Google Scholar]
  21. Litt, G.; Ferraioli, E.; Magni, F.; Lucertini, G.; Musco, F. Inter-Municipal Methodology for Climate Transition Strategies: The First Case in Italy. Sustainability 2022, 14, 2529. [Google Scholar] [CrossRef]
  22. Hurtado, S.D.G.; Olazabal, M.; Salvia, M.; Pietrapertosa, F.; Olazabal, E.; Geneletti, D.; D’Alonzo, V.; Feliú, E.; Di Leo, S.; Reckien, D. Implications of Governance Structures on Urban Climate Action: Evidence from Italy and Spain; BC3 Working Paper Series; Basque Centre for Climate Change (BC3): Bilbao, Spain, 2014. [Google Scholar]
  23. Lanzani, A.S.; Zanfi, F. Un Territorio Ibrido e Complesso, a Un Bivio Evolutivo. In Quando l’autostrada non Basta. Infrastrutture, Paesaggio e Urbanistica nel Territorio Pedemontano Lombardo; Lanzani, A.S., Ed.; Quodlibet: Macerata, MC, Italy, 2013. [Google Scholar]
  24. Carrosio, G.; De Renzi, A. Nelle Aree Interne: Una Corretta Gestione e Valorizzazione Del Capitale Naturale. In Ricomporre i Divari. Politiche e Progetti Territoriali Contro le Disuguaglianze e per la Transizione Ecologica; Coppola, A., Lanzani, A.S., Zanfi, F., Pessina, G., Eds.; Il Mulino: Bologna, Italy, 2021. [Google Scholar]
  25. Lanzani, A.; Curci, F. Le Italie in Contrazione, Tra Crisi e Opportunità. In Riabitare l’Italia. Le Aree Interne tra Abbandoni e Riconquiste; Donzelli: Roma, Italy, 2018; pp. 79–107. ISBN 88-6843-849-6. Available online: https://re.public.polimi.it/handle/11311/1071032 (accessed on 15 July 2023).
  26. Akadiri, S.S.; Alkawfi, M.M.; Uğural, S.; Akadiri, A.C. Towards Achieving Environmental Sustainability Target in Italy. The Role of Energy, Real Income and Globalization. Sci. Total Environ. 2019, 671, 1293–1301. [Google Scholar] [CrossRef]
  27. Battisti, L.; Aimar, F.; Giacco, G.; Devecchi, M. Urban Green Development and Resilient Cities: A First Insight into Urban Forest Planning in Italy. Sustainability 2023, 15, 12085. [Google Scholar] [CrossRef]
  28. Bresciani, S.; Rizzo, F.; Deserti, A. Toward a Comprehensive Framework of Social Innovation for Climate Neutrality: A Systematic Literature Review from Business/Production, Public Policy, Environmental Sciences, Energy, Sustainability and Related Fields. Sustainability 2022, 14, 13793. [Google Scholar] [CrossRef]
  29. D’Onofrio, R.; Camaioni, C.; Mugnoz, S. Local Climate Adaptation and Governance: The Utility of Joint SECAP Plans for Networks of Small–Medium Italian Municipalities. Sustainability 2023, 15, 8738. [Google Scholar] [CrossRef]
  30. Rivas, S.; Urraca, R.; Bertoldi, P. Covenant of Mayors 2020 Achievements: A Two-Speed Climate Action Process. Sustainability 2022, 14, 15081. [Google Scholar] [CrossRef]
  31. Scandurra, G.; Thomas, A. The SDGs and Non-Financial Disclosures of Energy Companies: The Italian Experience. Sustainability 2023, 15, 12882. [Google Scholar] [CrossRef]
  32. Amini Toosi, H.; Lavagna, M.; Leonforte, F.; Del Pero, C.; Aste, N. Towards Sustainability Assessment of the Built Environment: A Classification of the Existing Challenges. Sustainability 2023, 15, 12055. [Google Scholar] [CrossRef]
  33. Carra, M.; Caselli, B.; Rossetti, S.; Zazzi, M. Widespread Urban Regeneration of Existing Residential Areas in European Medium-Sized Cities—A Framework to Locate Redevelopment Interventions. Sustainability 2023, 15, 13162. [Google Scholar] [CrossRef]
  34. Rocco, G.; Pipino, C.; Pagano, C. An Overview of Urban Mobility: Revolutionising with Innovative Smart Parking Systems. Sustainability 2023, 15, 13174. [Google Scholar] [CrossRef]
  35. Sakib, N.; Appiotti, F.; Magni, F.; Maragno, D.; Innocenti, A.; Gissi, E.; Musco, F. Addressing the Passenger Transport and Accessibility Enablers for Sustainable Development. Sustainability 2018, 10, 903. [Google Scholar] [CrossRef]
  36. Baker, I.; Peterson, A.; Brown, G.; McAlpine, C. Local Government Response to the Impacts of Climate Change: An Evaluation of Local Climate Adaptation Plans. Landsc. Urban Plan. 2012, 107, 127–136. [Google Scholar] [CrossRef]
  37. Magni, F. Climate Proof Planning: L’adattamento in Italia tra Sperimentazioni e Innovazioni; FrancoAngeli: Milano, Italy, 2019. [Google Scholar]
  38. Maragno, D.; Dalla Fontana, M.; Musco, F. Mapping Heat Stress Vulnerability and Risk Assessment at the Neighborhood Scale to Drive Urban Adaptation Planning. Sustainability 2020, 12, 1056. [Google Scholar] [CrossRef]
  39. Gregorio Hurtado, S.D.; Ruiz Sánchez, J.; Berraondo Amezketa, M.; Astorga Fernández, Ó.I.; Celleri Yanzahuano, R.A.; Coronel Muñoz, M.P.; Martínez Nuñez, C.; Moya Camba, M.V.; Yépez González, A.; Abad Alva, A.A. Plan Director de Adaptación General Del Distrito de Carabanchel-Madrid; Instituto Juan de Herrera: Madrid, Spain, 2021. [Google Scholar]
  40. Tocchi, G.; Ottonelli, D.; Rebora, N.; Polese, M. Multi-Risk Assessment in the Veneto Region: An Approach to Rank Seismic and Flood Risk. Sustainability 2023, 15, 12458. [Google Scholar] [CrossRef]
  41. Ugliotti, F.M.; Osello, A.; Daud, M.; Yilmaz, O.O. Enhancing Risk Analysis toward a Landscape Digital Twin Framework: A Multi-Hazard Approach in the Context of a Socioeconomic Perspective. Sustainability 2023, 15, 12429. [Google Scholar] [CrossRef]
  42. Castiblanco Jimenez, I.A.; Mauro, S.; Napoli, D.; Marcolin, F.; Vezzetti, E.; Rojas Torres, M.C.; Specchia, S.; Moos, S. Design Thinking as a Framework for the Design of a Sustainable Waste Sterilization System: The Case of Piedmont Region, Italy. Electronics 2021, 10, 2665. [Google Scholar] [CrossRef]
  43. Longato, D.; Lucertini, G.; Dalla Fontana, M.; Musco, F. Including Urban Metabolism Principles in Decision-Making: A Methodology for Planning Waste and Resource Management. Sustainability 2019, 11, 2101. [Google Scholar] [CrossRef]
  44. Zardo, L.; Granceri Bradaschia, M.; Musco, F.; Maragno, D. Promoting an integrated planning for a sustainable upscale of renewable energy. A regional GIS-based comparison between ecosystem services tradeoff and policy constraints. Renew. Energy 2023, 217, 119131. [Google Scholar] [CrossRef]
  45. Russo, M. Circular Economies and Regenerative for the City: Ecology, Resilience and Metabolism of the Urban Waste Areas. Abitare la Terra. 2017, pp. 102–105. Available online: https://www.torrossa.com/en/resources/an/4571088 (accessed on 15 July 2023).
  46. Lucertini, G.; Di Giustino, G.; dall’Omo, C.F.; Musco, F. An Innovative Climate Adaptation Planning Process: IDEAL Project. J. Environ. Manag. 2022, 317, 115408. [Google Scholar] [CrossRef]
  47. Fabian, L.; Centis, L. The Lake of Venice: A Scenario for Venice and Its Lagoon; Anteferma: Conegliano, Italy, 2022; ISBN 9791259530226. [Google Scholar]
  48. Istat—Istituto Nazionale di Statistica. Rapporto Annuale 2023; Annual Report; Italian National Statistical Institute: 2023. Available online: https://www.istat.it/it/archivio/285017 (accessed on 15 July 2023).
  49. IPCC. Global Warming of 1.5 °C: IPCC Special Report on Impacts of Global Warming of 1.5 °C above Pre-Industrial Levels in Context of Strengthening Response to Climate Change, Sustainable Development, and Efforts to Eradicate Poverty; Cambridge University Press: Cambridge, UK, 2018. [Google Scholar]
  50. Burkhard, B.; Kroll, F.; Nedkov, S.; Müller, F. Mapping Ecosystem Service Supply, Demand and Budgets. Ecol. Indic. 2012, 21, 17–29. [Google Scholar] [CrossRef]
  51. Burkhard, B.; Kandziora, M.; Hou, Y.; Müller, F. Ecosystem Service Potentials, Flows and Demands-Concepts for Spatial Localisation, Indication and Quantification. Landsc. Online 2014, 34, 1–32. [Google Scholar] [CrossRef]
  52. Burkhard, B.; Maes, J. (Eds.) Mapping Ecosystem Services; Pensoft Publishers: Sofia, Bulgaria, 2017; ISBN 978-954-642-830-1. [Google Scholar]
  53. Burkhard, B.; Maes, J. An Operational Framework for Integrated Mapping and Assessment of Ecosystems and Their Services (MAES); Burkhard, B., Santos-Martin, F., Nedkov, Eds.; Gottfried Wilhelm Leibniz Universität Hannover Technische Informationsbibliothek (TIB): Hannover, Germany, 2018; p. e22831. [Google Scholar] [CrossRef]
  54. ISPRA Inventario Nazionale—EMISSIONI. Available online: http://emissioni.sina.isprambiente.it/inventario-nazionale/ (accessed on 5 June 2023).
  55. AA.VV. Statistiche regionali di consumo energetico 2021. TERNA SISTAN Lav. Inser. Nel Programma Stat. Naz. 2020-2022 Delibera CIPE Gazzetta Uff. Ser. Gen N202 24082021 TER-00001 E TER-00007. 2022. Available online: https://download.terna.it/terna/Terna_Annuario_Statistico_2021_8dafd2a9a68989c.pdf (accessed on 15 July 2023).
  56. Fabian, L.; Bertin, M. Italy Is Fragile: Soil Consumption and Climate Change Combined Effects on Territorial Heritage Maintenance. Sustainability 2021, 13, 6389. [Google Scholar] [CrossRef]
  57. Turri, E. La Megalopoli Padana; Biblioteca/Marsilio; Marsilio: Venezia, Italy, 2004; ISBN 978-88-317-7556-4. [Google Scholar]
  58. Cattaneo, C. Saggi di Economia Rurale; Giulio Einaudi Editore: Torino, Italy, 1975. [Google Scholar]
  59. Brunetti, M.; Maugeri, M.; Nanni, T. Changes in Total Precipitation, Rainy Days and Extreme Events in Northeastern Italy. Int. J. Climatol. 2001, 21, 861–871. [Google Scholar] [CrossRef]
  60. Brunetti, M.; Colacino, M.; Maugeri, M.; Nanni, T. Trends in Daily Intensity of Precipitation in Italy from 1951 to 1996. Int. J. Climatol. 2001, 21, 299–316. [Google Scholar] [CrossRef]
  61. ISPRA. Annuario Dei Dati Ambientali—Edizione 2019; 2020; ISBN 978-88-448-0975-1. Available online: https://www.isprambiente.gov.it/it/pubblicazioni/stato-dellambiente/annuario-dei-dati-ambientali-edizione-2019 (accessed on 15 July 2023).
  62. Highfield, W.E.; Peacock, W.G.; Van Zandt, S. Mitigation Planning: Why Hazard Exposure, Structural Vulnerability, and Social Vulnerability Matter. J. Plan. Educ. Res. 2014, 34, 287–300. [Google Scholar] [CrossRef]
  63. Rufat, S.; Tate, E.; Burton, C.G.; Maroof, A.S. Social Vulnerability to Floods: Review of Case Studies and Implications for Measurement. Int. J. Disaster Risk Reduct. 2015, 14, 470–486. [Google Scholar] [CrossRef]
  64. Russo, M.; Attademo, A. Il Metabolismo Del Rischio. In Geografie del Rischio. Nuovi paradigmi per il governo del territorio; Galderisi, A., Di Venosa, M., Fera, G., Menoni, S., Eds.; Donzelli: Roma, Italy, 2020. [Google Scholar]
  65. Amenta, L.; Attademo, A.; Remøy, H.; Berruti, G.; Cerreta, M.; Formato, E.; Palestino, M.F.; Russo, M. Managing the Transition towards Circular Metabolism: Living Labs as a Co-Creation Approach. Urban Plan. 2019, 4, 5–18. [Google Scholar] [CrossRef]
  66. Coronato, M. Capitalisation and Dissemination of ESPON Concepts–ESPON CaDEC. The Italian Experience. In ESPON Italian Evidence in Changing Europe; STF, 2014; pp. 139–142. ISBN 88-909765-2-7. Available online: https://www.espon.eu/programme/projects/espon-2013/transnational-networking-activities/cadec-capitalisation-and (accessed on 15 July 2023).
  67. Reckien, D.; Flacke, J.; Olazabal, M.; Heidrich, O. The Influence of Drivers and Barriers on Urban Adaptation and Mitigation Plans—An Empirical Analysis of European Cities. PLoS ONE 2015, 10, e0135597. [Google Scholar] [CrossRef]
Figure 1. Confrontation of ecological performances of the territorial settlement model for the three cases considered.
Figure 1. Confrontation of ecological performances of the territorial settlement model for the three cases considered.
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Figure 2. A geographical analysis of the neutrality in climate change mitigation in the northeast region. Black represents the areas that are already neutral, and white represents the areas that are far from neutral. There is no strong separation between the two categories. Most anthropised land is in direct contact with areas capable of sound neutrality.
Figure 2. A geographical analysis of the neutrality in climate change mitigation in the northeast region. Black represents the areas that are already neutral, and white represents the areas that are far from neutral. There is no strong separation between the two categories. Most anthropised land is in direct contact with areas capable of sound neutrality.
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Figure 3. A geographical analysis of the neutrality in climate change mitigation in northwest region. The white and black areas are dense and exclusive patterns without significant overlapping.
Figure 3. A geographical analysis of the neutrality in climate change mitigation in northwest region. The white and black areas are dense and exclusive patterns without significant overlapping.
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Figure 4. Geographical analysis of the neutrality in climate change mitigation in central region. The white and black areas are dense and exclusive patterns without significant overlapping.
Figure 4. Geographical analysis of the neutrality in climate change mitigation in central region. The white and black areas are dense and exclusive patterns without significant overlapping.
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Table 1. Comparison between the Italian territorial systems considered for this research 1.
Table 1. Comparison between the Italian territorial systems considered for this research 1.
TerritoryExtensionInhabitantsGDPDensity
Northeast39,865 Km27,193,000USD 219,210 mil180
Lombardy23,864 Km210,060,000USD 333,475 mil422
Lazio17,242 Km25,879,000USD 169,349 mil341
Italy302,073 Km258,815,463USD 2,090,448 mil195
1 Data from Istat 2023 [48].
Table 2. Percentage of energy consumption by land use type (clc-2018) in the northeast, Lombardy and Lazio areas [54]. Energy consumption data from Terna 2021 [56].
Table 2. Percentage of energy consumption by land use type (clc-2018) in the northeast, Lombardy and Lazio areas [54]. Energy consumption data from Terna 2021 [56].
Land UseS N-E
(%Km2)
I1 N-E
(GwH)
S Lo
(%Km2)
I1 Lo
(GwH)
S La
(%Km2)
I1 La
(GwH)
Continuous urban fabric0.064343.91.275790.30.443300.7
Discontinuous urban fabric4.7417,380.36.5323,148.12.7113,204.9
Industrial or commercial units1.2616,066.14.2023,492.60.692255.8
Road and rail networks0.062295.20.893358.90.05321.3
Port areas0.082295.20.013358.90.02321.3
Airports0.062295.20.113358.90.11321.3
Mineral extraction sites0.1258.00.2299.40.1346.8
Dump sites0.0058.00.0299.40.0246.8
Construction sites0.03647.50.11397.50.02238.3
Green urban areas0.03806.90.981033.50.06442.6
Sport and leisure facilities0.12806.90.601033.50.13442.6
Agriculture38.191261.141.471079.942.17336.2
Totals39,865 Km248,31965,183 Km266,251.125,268 Km221,281
Average consumption GwH/Km2Northeast1.21Lombardy1.02Lazio0.84
Table 3. Value of ecosystem services in the three study areas.
Table 3. Value of ecosystem services in the three study areas.
Land UseNortheastLombardyLazio
I2I3I4I2I3I4I2I3I4
Continuous urban fabric0.00−0.18−0.240.00−3.81−5.080.00−1.32−1.76
Discontinuous urban fabric4.74−14.22−14.226.53−19.59−19.592.71−8.12−8.12
Industrial or commercial units0.00−6.30−5.040.00−21.00−16.800.00−3.43−2.74
Road and rail networks0.00−0.24−0.240.00−3.56−3.560.00−0.18−0.18
Nonirrigated arable land106.10−21.220.00−29.780.00106.1089.480.00−22.37
Principally occupied by agriculture11.130.000.0019.8515.883.9720.550.000.00
Mixed forest40.4032.328.0819.8515.883.971.901.520.38
Water bodies2.720.680.0010.682.670.003.710.930.00
Coastal lagoons7.650.001.530.000.000.000.000.000.00
Sea and ocean0.090.150.090.000.000.000.090.150.09
Totals3.921.020.103.870.15−0.261.18−0.10−0.35
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Bertin, M.; Fabian, L. Spread Is Better: Suitability for Climate Neutrality of Italian Urban Systems. Sustainability 2023, 15, 13710. https://doi.org/10.3390/su151813710

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Bertin M, Fabian L. Spread Is Better: Suitability for Climate Neutrality of Italian Urban Systems. Sustainability. 2023; 15(18):13710. https://doi.org/10.3390/su151813710

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Bertin, Mattia, and Lorenzo Fabian. 2023. "Spread Is Better: Suitability for Climate Neutrality of Italian Urban Systems" Sustainability 15, no. 18: 13710. https://doi.org/10.3390/su151813710

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