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Review

Evaluating the Transition Towards Post-Carbon Cities: A Literature Review

Interuniversity Department of Regional and Urban Studies and Planning, Politecnico di Torino, 10125 Turin, Italy
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Author to whom correspondence should be addressed.
Sustainability 2021, 13(2), 567; https://0-doi-org.brum.beds.ac.uk/10.3390/su13020567
Submission received: 13 December 2020 / Revised: 31 December 2020 / Accepted: 1 January 2021 / Published: 8 January 2021

Abstract

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To achieve the new European targets concerning CO2 emission reduction, the concept of a post-carbon city has been promoted, which is focused on low-energy and low-emission buildings provided with intelligent heating and cooling systems, electric and hybrid cars, and better public transport. This paradigm entails the inclusion of aspects not strictly related to energy exploitation but referring to environmental, social, and economic domains, such as improvement in local energy security, people’s opinion on different energy solutions, economic co-benefits for private users, environmental externalities, and so on. In this domain, it is of particular importance to provide the decision makers with evaluation tools able to consider the complexity of the impacts, thus leading to the choice of the most sustainable solutions. The paper aims to investigate the scientific literature in the context of evaluation frameworks for supporting decision problems related to the energy transition. The review is carried out through the scientific database SCOPUS. The analysis allows for systematizing the contributions according to the main families of evaluation methodologies, discussing to what extent they can be useful in real-world applications. The paper also proposes emerging trends and innovative research lines in the domain of energy planning and urban management. While the energy transition is an important trend, the analysis showed that few studies were conducted on the evaluation of projects, plans, and policies that aim to reach post-carbon targets. The scales of application refer mainly to global or national levels, while few studies have been developed at the district level. Life cycle thinking techniques, such as life cycle assessment and cost-benefit analysis, were widely used in this research field.

1. Introduction

The new paradigm of the post-carbon city is becoming increasingly developed [1]. This new concept of urban space has led to a significant reconsideration of the fossil fuel-dependent city system, which aims at defining a new model of the sustainable city [2]. The European Commission defines a post-carbon city as a city characterized by a low-carbon system, where buildings are characterized by reduced energy consumption and limited production of climate-altering emissions, thanks to intelligent heating and cooling systems. Equally, the transport sector is influenced by this new concept through the use of electric and hybrid cars and a sustainable public transport system that makes cities less polluted. Taking into account all these challenges, the European Commission released a “Roadmap for moving to a competitive low-carbon economy in 2050”, in which the way to achieve a low-carbon future is described [3]. The biggest challenges are the refurbishment of existing buildings because, in Europe, new buildings only comprise 1% of the total amount of building stocks and the expansion of new measures and interventions at the district and municipal level. Furthermore, since the percentage of the global population living in the urban context will increase, reaching the percentage of 70% of people living in cities by 2050, the urban level will become fundamental to develop new sustainable models. In this perspective, all sectors can contribute to reducing emissions, and every possible action must be made from every side. The focus on the energy transition of cities was also underlined by the United Nations in the definition of the 17 Sustainable Development Goals (SDGs) within the 2030 Agenda [4]. Sustainable development to tackle climate change and build peaceful societies by the year 2030 is strongly reiterated by the SDG 11. In particular, the goal is to make cities and human settlements inclusive, safe, and durably built from a sustainable perspective. The main challenge is to keep urban centers as workplaces capable of producing income without damaging the environment and the territory and preserving natural resources by 2030. Energy is the central element of SDG 7, which aims to ensure access to affordable, reliable, sustainable, and modern energy systems for all. SDGs 7 and 11 recognize the close link between cities and the energy sector, with the sole objective of guaranteeing human well-being by reducing energy poverty and preserving the environment by reducing the effects of climate change. Moreover, the goal of climate neutrality was evoked in December 2019 by the European Commission, which placed the environment at the center of its political action and launched the European Green Deal, which aims to base Europe on a green economy that can achieve carbon neutrality by 2050 [5]. The Green New Deal has assumed a leading role, especially during 2020 in the European panorama, passing from a strategy for growth to a strategy for relaunching the economy in the post-COVID-19 period [6].
With innovative and sustainable city models, new parameters come into play, intending to identify the best design profile to respond to new energy, environmental, and market policies. In this sense, evaluation tools able to support Decision Makers (DMs) and stakeholders in decision processes in the domain of the transformation of buildings/cities/regions are needed. A wide variety of tools for organizing and processing energy problems are available. The main evaluation methods could be clustered in three families; economic methods, multi-criteria approaches, and environmental evaluation techniques. Among the monetary methods, the most common standardized approaches used in the domain of energy decision-making problems are life thinking techniques, such as life cycle cost (LCC) [7] and cost-benefit analysis (CBA) [8]. In 2010, the Energy Performance of Buildings Directives recast (EBPD, 2010/31/EU) introduced the cost-optimal approach, which is determined by considering the overall costs related to the useful life of a building, such as investment costs for energy efficiency, costs of maintenance, operation, and replacement, and any disposal costs [9]. Over the past decade, multi-criteria decision analysis (MCDA) techniques have been widely used in this field [10]. These evaluation tools can support the decision problem in different ways and considering different evaluation principles. Unlike CBA, MCDA is inclined to involve decision-makers to capture a wide range of perspectives and verify the power of stakeholders’ consent. Hybrid models that combine manual-based CBA with MCDA methods in the field of the district sustainability sector are being developed so that tangible and intangible criteria can be included in the assessment [11,12,13]. Moreover, several certification protocols based on qualitative assessment have been developed to assess the sustainability of buildings and neighborhoods, up to urban plans. These assessment tools define a project’s performance score, analyzing all stages of the life cycle, from raw material purchase to demolition, and including the full range of economic, environmental, and social impacts [14,15,16]. The most widely used and recognized international certification schemes are the “Building Research Establishment Environmental Assessment Method” (BREEAM) [17], the “Leadership in Energy and Environmental Design” (LEED) [18], the “Green Star” in Australia [19], “Comprehensive Assessment System for Building Environmental Efficiency” (CASBEE) in Japan [20], and the “Green Mark” in Singapore [21].
In the context of the energy transition, review articles are limited. Most of the articles in the literature present in the most well-known and reliable bibliometric databases connect the concept of the energy transition to specific cases. Often, the energy transition is linked to the concept of landscape transformation, land consumption, the use of renewable energy sources, and what benefits they bring but also what conflicts they have with the Sustainable Development Goals [22,23,24,25,26]. Papers have also been written about specific methods that can be used to examine the energy transition, such as system dynamics [27]. Other papers argue the issue from a regulatory point of view and how states can overcome the barriers that block a post-carbon vision and the reasons why it is necessary to do so [28,29]. Horschig and Thrän [30] examined several modeling approaches applicable to renewable energy policy planning and evaluation. However, the review is focused on quantitative and qualitative approaches, such as input/output modeling [31], computable general equilibrium modeling [32], system dynamics modeling [33], agent-based modeling [34], theory-based evaluation [35], multiple decision aiding analysis [36], and hybrid approaches. The authors do not take into consideration the monetary approaches that constitute the main tools required by national or international energy directives such as discounted cash flow (DCF), cost-benefit analysis (CBA) [8], and life cycle cost (LCC) [37].
The proposed paper, on the other hand, aims to have a broader view of the concept of energy transition and post-carbon vision. It proposes an innovative literature review that provides a systematic assessment of the energy transition, aiming to demonstrate the importance that the different evaluation methods acquire within the theme and the various fields of application that these methods are involved in. In addition, this review aims to highlight how different evaluation approaches can help to take into consideration the benefits and advantages for the development of society and future generations in a sustainable way [38,39].
This research aims to get a clear point of view on the issue of the energy transition, that is, the shift from the use of non-renewable energy sources to renewable sources. This change of direction is the basis for the formation of sustainable economies that are attentive to the use of renewable energy and sustainable development [40]. The study focuses, in particular, on the geographical areas that have shown a particular interest in this issue, but also the sector in which the topic is inserted, such as buildings, urban infrastructure, or, more generally, that of cities. The research also focuses on analyzing the role of different evaluation methods and approaches to support this goal. To achieve the purpose of the research, the literature analysis was carried out using the SCOPUS database. The paper is structured as follows: after the Introduction, a section dedicated to research methodology describes the method used to conduct the analysis of the literature and the different steps of the investigation. Next, the results section highlights the outcomes of the different steps taken during the analysis. Finally, in the Conclusions, the paper seeks to explain the overall view of the topic covered and the most interesting results present in the literature, but also the key points for future perspectives of the research.

2. Research Methodology

As previously mentioned, the purpose of this paper is to develop a bibliography analysis of literature regarding the context of energy transition and post-carbon vision, focusing in particular on decision-making processes and the role of evaluation tools. The aim is to highlight the more recent trends and key topics relevant to this issue, and obtain a current view of decision tools for supporting a sustainable economy and development. This overview can be useful as a guide for future research activities and for proving the central role that evaluation methods can play in this field of interest. The literature’s bibliography analysis was conducted using the SCOPUS database, one of the most well-known and reliable online bibliography collection platforms. The analysis and all the data collected for the drafting of this paper are part of the period from May 2020 to October 2020. A multi-step approach was used in this research. Figure 1 shows the framework of the literature review performed in this research. The first step was selecting the keywords to use in the SCOPUS search. Specifically, given the large number of documents on the energy topic on SCOPUS, the analysis was conducted on three different and increasingly specific levels, adding keywords to the basic ones chosen to refine the research carried out. For the first phase of the search, the most general one, it was decided to use the following keywords: (“evaluation” OR “valuation” OR “assessment”) AND (“energy transition” OR “post-carbon”). A total of 14,443 documents were found with an “all fields” search, while 699 documents were found by limiting the search to title, abstract, and keywords. The second phase of the research aimed at limiting the analysis to the territorial scale to which the documents found refer, and subsequently to the sector. For this purpose, specific keywords were added that focus on the scale of the application. The keywords used are the following:
  • ((“evaluation” OR “valuation” OR “assessment”) AND (“energy transition” OR “post-carbon”) AND (“global”)) = 139 Documents;
  • ((“evaluation” OR “valuation” OR “assessment”) AND (“energy transition” OR “post-carbon”) AND (“national”)) = 91 Documents;
  • ((“evaluation” OR “valuation” OR “assessment”) AND (“energy transition” OR “post-carbon”) AND (“regional”)) = 63 Documents;
  • ((“evaluation” OR “valuation” OR “assessment”) AND (“energy transition” OR “post-carbon”) AND (“urban”)) = 63 Documents;
  • ((“evaluation” OR “valuation” OR “assessment”) AND (“energy transition” OR “post-carbon”) AND (“district”)) = 23 Documents.
Next, the analysis was narrowed based on the sector they refer to. Specifically, it was chosen to include the building sector, infrastructure sector, and, more generally, the city. The keywords used are the following:
  • ((“evaluation” OR “valuation” OR “assessment”) AND (“energy transition” OR “post-carbon”))) AND (“building”) = 86 Documents;
  • ((“evaluation” OR “valuation” OR “assessment”) AND (“energy transition” OR “post-carbon”))) AND (“infrastructure”) = 52 Documents;
  • ((“evaluation” OR “valuation” OR “assessment”) AND (“energy transition” OR “post-carbon”) AND (“city” OR “cities”)) = 56 Documents.
For both searches in this second phase, the analysis was carried out considering only the results by title, abstract, and keywords. In the third phase of the analysis—the most interesting for the research—other keywords were added with the precise purpose of focusing on evaluation methods and approaches to identify, thanks to the analysis of the literature, what are the trends and use of these methods in the topic of energy. The new keywords used were partly suggested by SCOPUS as search filters, while others were manually entered into the database. The words that appeared as suggestions in the filters are the following:
“Life Cycle Assessment (LCA)” (28 document results); “Cost-Benefit Analysis” (22 document results); “Sensitivity Analysis” (16 document results); “Environmental Impact Assessment” (14 document results); “Monte Carlo Methods” (13 document results).
While the manually added words that reference evaluation methods are as follows:
“Discounted Cash Flow” OR “DCF” (0 results); “Life Cycle Cost” OR “LCC” (4 document results); “Multicriteria” OR “MCDA” OR “MCA” OR “Multi-criteria” OR “Multiple Criteria Decision Analysis” (13 Document Results); “Neural network” (2 document results); “Regression Analysis” OR “Parametric Model” (3 document results); “Preference evaluation” OR “econometrics” (5 document results); “Geographical Information System” OR “GIS” (12 document results); “Quantitative Analysis” (15 document results).
Those keywords were added to the string of keywords used in the first analysis phase. In the next paragraphs, these three phases will be named, respectively, Group A, Group B, and Group C. For each group, different analyses were conducted, which are titled historical production analysis, country productivity analysis, and subject area analysis. The first type of analysis (historical production) allows the comprehension of the productivity of the literature relating to these themes in the time frame indexed in SCOPUS. In this way, it is possible to understand the overall trend of the selected sample. The second analysis (country productivity) shows how many documents published by the different countries were produced in the period indexed in SCOPUS, according to the authors’ affiliation city. The third analysis (subject area) provides an overview of the sectors dealing with the issue of the energy transition and post-carbon issue. In addition, a cross-sectional comparison of the selected keywords for each group was provided to understand the relevance of specific words, approaches, and methods in this field. In particular, this comparison can support the identification of the gaps in literature production and of the most consolidated fields of research.

3. Results and Discussion

3.1. Group A: Analysis about Search Fields

The first analysis conducted on the topic of energy and post-carbon transition shows a large number of documents; 14,443 considering all with an “all fields” search, and 699 by limiting the search to title, abstract, and keywords. Historical production started in 1957, but only in the 1980s is the number of indexed documents over 10 per year. The intensive production of literature about the energy transition and post-carbon issue began after the 2000s. From 2000 to 2020, the number of documents is 14,138, equal to 97% of the entire literature production. In particular, in the last 10 years, the number documents published is 13,359, which is 92% of the total. The second analysis, which focused on the research on title, abstract, and keywords (TITLE-ABS-KEY), shows similar results to the historical production. Additionally, in this case, the first document indexed in SCOPUS dates back to 1957, but only in 2005 is there a slight increase in production. From 2010 to 2020, the literature production increases significantly, with a total of 650 documents, equal to 93% of the entire production. Figure 2 reports the historical production of the literature for the research in “all fields” and limited to title, abstract, and keywords.
The examination of the subject areas performed by SCOPUS is reported in Figure 3 and Figure 4, and shows how many sectors deal with the topic of energy transition and post-carbon, including from energy to engineering, and from chemistry to mathematics, for a total of 27 subjects. Figure 3 shows the analysis of the 14,443 documents found on SCOPUS, and the main subjects involved in this topic are energy, environmental science, social science, and engineering. These four subjects alone account for 63% of the entire literature production.
In the same way, Figure 4 shows the analysis of sectors that have included this topic, taking into consideration only the 699 documents found by limiting to title, abstract, and keywords. In this case, energy, environmental science, and engineering represent the subjects with the largest number of documents. Social science is only equal to 9.4% of the total.
Comparing the weights of the two keywords energy transition and post-carbon, which are the keystones of this literature review, it can be seen that of the 699 documents found in SCOPUS, only 24 documents are related to the post-carbon keyword. Figure 5, Figure 6, Figure 7 and Figure 8 show the results of the analysis of the comparison between the energy transition and post-carbon keywords. The largest proportion of documents related to energy transition was written in 2020 (172 documents). For the energy transition keyword, the production of literature has increased significantly in the last four years (Figure 5). While the contributions that use the post-carbon keyword record a constant trend, the production starts in 2005 to present, with a narrow difference throughout these fifteen years (Figure 6). Most of the documents with the energy transition keyword were involved in the fields of energy, environmental science, and engineering (Figure 7). The sector that used the post-carbon keyword the most is environmental science (Figure 8).

3.2. Group B: Energy Transition and Post-Carbon View at Territorial Scale and in Sector of Application

The second phase of analysis focused on the territorial scale in which the documents are inserted. The searches were conducted by limiting the research to title, abstract, and keywords. In particular, five searches were performed, each one using a specific keyword that identifies a particular scale. The keywords used are the following: global, national, regional, urban, district. The results show that the global keyword has the largest number of documents (139 documents). Twenty-three documents are related to the district keyword which addresses the issue on a smaller and less used territorial scale. The historical production for the national keyword has been extensive since the 1970s. For the district keyword, instead, the first documents date back to 2015, with a slight increase in recent years. In each case, about 90% of documents relating to the different scales were written after 2015. Figure 9 reports the historical trends of literature for the different territorial analyses considered in this study.
Finally, as regards country productivity analysis, it is clear that the most of the documents were written in Germany. However, some slight differences can be observed between different countries. For example, with regard to the global territorial scale, the main producing countries are Germany and the United States, with 35 and 21 documents, respectively. On the national territorial scale, the UK is more productive than the United States. It is interesting to note that Italy is, together with Switzerland, the country with the highest production of documents linked to the urban territorial scale. At the same time, Italy and Germany are the countries with the greatest interest in writing documents about the district scale in the field of the energy transition and post-carbon issue. Figure 10 shows the number of publications produced by each country. Those with a lower incidence due to few publications are considered as “Others”.
As mentioned above, most of the documents that include the district keyword were written in Germany, Italy, and Spain since 2015. The main subjects of those 23 documents are energy, environmental science, and engineering. Furthermore, taking into consideration the analysis of documents for affiliations carried out by SCOPUS, the results conclude that the Politecnico di Torino is the institution with the highest number of affiliations, followed by the Technical University of Munich [41]. Figure 11 shows the result of the analysis on authors’ affiliations performed by SCOPUS.
The second search conducted in Group B narrows the analysis of the first group of documents found (699) based on the sector to which they refer. Specifically, three searches were carried out: one for the building sector, one for the infrastructure sector, and the last one, more generally, for the city environment. The results show that 86 documents deal with the building sector, 56 documents with city/cities, and 52 with the infrastructure sector.

3.3. Group C: Evaluation Approach and New Trends in Energy Transition and Post-Carbon View

The purpose of the third analysis—the most interesting for this literature review—is to focus on evaluation approaches, operational research, and new trends emerging about this topic. The search starts from the primary analysis (Group A). New keywords were introduced each time in each search, and in some cases derived from filter keywords suggested by SCOPUS in the primary search. Interestingly, words like life cycle assessment (LCA) and cost-benefit analysis (CBA) are among the first keywords suggested by SCOPUS. Other keywords are defined according to the authors’ disciplinary field, to verify the possible gaps present in the literature production and highlight the importance of the specific approach and evaluation methods in the field of energy and post-carbon transition.
The results show different situations, as can be seen in Figure 12 and Table A1 in Appendix A. Discount cash flow (DCF) is absent in the literature production on this topic. On the contrary, LCA is the most used approach for the energy transition and post-carbon issue (28 documents). Another relevant result is given by the adoption of CBA (21 documents). Sensitivity analysis, environmental impact assessment, Monte Carlo methods, MCDA, GIS, and quantitative analysis have approximately the same number of documents, with more than 13 documents each. A greater number of documents with LCA and CBA could be explained by the relation that these methods have with the themes of the energy transition, what benefits come from the use of renewable sources, and the possibility to monitor and reuse each thing done with this type of energy approach [42,43,44,45,46,47,48,49,50]. Furthermore, LCA and CBA are manual-based analyses mostly used in practice to validate the economic feasibility of a large-scale project [8,51]. The absence of documents related to DCF can be partially explained by its use as an ex-ante approach to calculate the feasibility of new constructions or interventions, and is therefore more connected with the economic area.
Generally, the historical production in the context of evaluation approaches and methods to support the issue of energy transition and post-carbon target starts around 2005. In the last three years, the intensive production of documents begins, as it is possible to see in Figure 13. Most methods and approaches were involved in the energy sector only in recent years, but there are some exceptions. GIS and neural networks are the first two methods to appear in the articles between 2005 and 2006. However, these evaluation methods reappeared in the searches only in 2014, slightly increasing their presence in documents. Anyway, the increase in these evaluation methods within the documents only in recent years is caused by the modernity of the theme of the energy transition, but also because the evaluation methods are recent and not yet consolidated. As might be expected, the results of the subject area analysis show an important production in the fields of energy, environmental science, and engineering in general for all evaluation approaches considered, as can be seen in Figure 14. It is interesting to notice that GIS and environmental impact assessment have the largest number of documents associated with social science, with seven and six documents, respectively.

4. Conclusions and Future Implications

The present paper allowed us to understand the recent trends and the main issues related to the theme of energy transition and post-carbon targets. The energy transition and post-carbon view are currently the main trends because they are closely linked to the concept of sustainable development and the life cycle of products. This relationship is also reflected in the recent number of documents adopting LCA and CBA approaches. The application of these two techniques by the academic literature in the energy sector is due to the fact that they represent the tools recognized at the European level in terms of project evaluation for all member states, regulated by standards capable of guaranteeing absolute transparency in the selection of projects to be carried out. In these documents, the topics range from the chemical to the food industry, and from the use of non-renewable resources to new renewable energy models, evaluating the realization costs and benefits brought about by some changes in the production methods.
Another aspect that emerges from this review is the growing interest in the field of energy transition and the natural environment to be preserved, with particular attention paid to the benefits and advantages for the development of society and future generations. These aspects are in fact in line with the aims suggested by the Sustainable Development Goals defined by the United Nations. In this context, life cycle analyses let to consider all the positive and negative impacts generated by a project, allowing us to obtain an overview of the performances and calculate the net benefit for society, and guarantee the achievement of economic and environmental sustainability goals.
It is clear that the interest in this topic involves all the world and will have positive repercussions on the environment on a planetary scale. From the territorial-scale analysis, the interest of different countries to study the impact of energy transition in a global vision is highlighted. The number of documents related to a global scale is greater with respect to the other territorial scales taken into consideration. Nevertheless, the interest in the district scale is deepened in different countries. The idea to operate on a small scale could probably guarantee the application of the post-carbon vision. Creating and making small areas of cities self-sufficient from an energy point of view, with a proactive character regarding the principles of eco-sustainability, are certainly easier. This is the beginning of a necessary change, which allows us to preserve natural resources and ensure a better quality of life for future generations.
It was interesting to discover that Italy, among the various European countries, is more interested in working and developing research on an urban and district scale, studying realistic solutions for cities and promoting their development with the purpose of guaranteeing the best quality of life. As previously mentioned, the Politecnico di Torino is the university with the majority of published documents and a high interest in developing studies in this field.
This preliminary search on SCOPUS has highlighted in recent years an increase in documents on this sector. Particularly interesting was the comparison between historical and country production and the subject areas, as well as the evaluation approaches and methods, to guide and understand the development of new trends in the research and which topics could be explored in the future.
The research provides a comprehensive view of the state of the art, which is useful for guiding future research and demonstrating the role of some evaluation approaches and methods in this field. At the same time, the research certainly shows some limitations. First of all, the analysis was conducted using a single database, even though SCOPUS is one of the most recognized and reliable bibliometric databases. Secondly, the search was implemented in a general way, because there is no in-depth analysis on individual documents, and the search, specifically, in the second and third stages, is limited to title, abstract, and keywords. Thirdly, the analyzed topic is very recent and there are not many applications of the evaluation methods in this area, so there are few documents to conduct an exhaustive analysis. Future investigations could consider the possibility of analyzing the individual documents in a more advanced way, to better understand the role and potentials of the single approach and methods applied in the view of energy changes. Since COP21, with the adoption of the Paris Agreement on Climate, and the new objectives set by the United Nations Economic Commission for Europe (UNECE), an increasing number of cities have committed themselves to concretely combat climate change and to pursue the common goal of carbon neutrality. The C40 cities established that the neutral city must also take into consideration the urban sectors relevant to green spaces, waste, and water, and not only energy, mobility, and buildings, with the general objective of promoting sustainable development and ensuring green growth. In this comprehensive perspective, every single part of the city becomes a potential field of the experiment for new zero-carbon technologies. This vision involves a certain complexity in the definition of decisions. Multi-step evaluation procedures that investigate the economic, environmental, and social performance of city transition operations are necessary to define the milestones for actions in priority areas and create an organizational framework. Furthermore, hybrid models that facilitate dialogue between the different stakeholders involved can help define a decision-making process that is inclusive from a social point of view and sustainable from an economic and environmental point of view. In the future, it will be interesting to understand how the academic sector, researchers and scholars respond to the new rules that will emerge from these new models of sustainable cities and support public and private DMs.

Author Contributions

Conceptualization, M.B., F.D., and V.M.; methodology, M.B., F.D., and V.M.; investigation M.B., F.D., and V.M.; data curation, M.B., F.D., and V.M.; writing—original draft preparation, M.B., F.D., and V.M.; visualization, M.B., F.D., and V.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. Summary collection of studies by type of evaluation applied (Group C).
Table A1. Summary collection of studies by type of evaluation applied (Group C).
AuthorsYearsSource TitleEvaluation MethodObjective and Application Context
Barnes et al. [52]2005The Urban Household Energy Transition: Social and Environmental Impacts in the Developing WorldGeographical Information SystemAnalysis of the use of renewable energy and impacts on society
Shterenlikht and Howard [53]2006Fatigue and Fracture of Engineering Materials and StructuresNeural NetworkEvaluation of the ductile to brittle transition behavior of ferritic steels.
Duke et al. [54]2010Frontiers of Chemical Engineering in ChinaPreference Evaluation OR EconometricsEvaluation of the post-combustion sector and its involvement in energy production
Guasco et al. [55]2011Journal of Physical Chemistry AMonte Carlo MethodsStudy of the origin of anharmonic effects through Monte Carlo analysis
Arthur et al. [56]2012Energy EconomicsPreference Evaluation OR EconometricsCalculation of the elasticity of domestic energy demand at price and income in Mozambique
Heun and de Wit [57]2012Energy PolicyRegression Analysis OR Parametric ModelAnalysis of the rise in the price of oil in relation to the energy transition
Schaede et al. [58]2013Design and AssessmentLife Cycle Assessment, Life Cycle CostEvaluation and design of electric energy storage
Eising et al. [59]2014Applied EnergyGeographical Information SystemAnalysis of transport and supply chain integration
Evanno and Weinberger [60]2014Techniques-Sciences-MethodesEnvironmental Impact AssessmentAnalysis of specific feedback processes related to the biogas of accidents
King [61]2014EnergyLife Cycle AssessmentComparison between the energy performance of systems in the energy transition
Nordman [62]2014Renewable EnergyLife Cycle CostAnalysis of wind farms to power tea factories in Kenya
Zimmermann et al. [63]2014Metallurgical Research and TechnologyLife Cycle AssessmentImportance of electric vehicles in the energy transition
Bachmann [64]2015Environmental Science and TechnologyCost–Benefit AnalysisStrengths and disadvantages of an approach to the environmental economy
Wesseh et al. [65]2015Journal of Cleaner ProductionCost–Benefit AnalysisBenefit analysis for renewable energy research and development programs in Liberia
Zimmermann et al. [66]2015Integrated Environmental Assessment and ManagementLife Cycle AssessmentStudy on the importance of electric vehicles for the energy transition
Calvert [67]2016Progress in Human GeographyGeographical Information SystemAnalysis of geographical contributions, study of energy and energy futures.
Cucchiella et al. [41]2016Energy Conversion and ManagementCost–Benefit Analysis, Sensitivity AnalisisEvaluation of small-scale photovoltaic systems and results
Herbert et al. [68]2016Sustainable Production and ConsumptionLife Cycle AssessmentA proposal for types of greenhouse gas emissions
Lizana et al. [69]2016Energy and BuildingsMultiple Criteria Decision AnalysisEconomic, environmental, and social assessment for a residential energy retrofit
Sager-Klauß [70]2016A+BE Architecture and the Built EnvironmentGeographical Information SystemSupport for sustainable energy transition planning in small and medium-sized communities
Sgouridis et al. [71]2016Renewable and Sustainable Energy ReviewsCost–Benefit AnalysisAnalysis of renewable energy costs in the United Arab Emirates
Carlier and Chardonnet [72]2017Environnement, Risques et SanteEnvironmental Impact AssessmentSearch for the path with the lowest environmental and health impact for the reconstruction of an power line
Kaltenegger et al. [73]2017Energy PolicyCost–Benefit AnalysisInput–output and trend-based energy cost study in Germany and EU
Ketzer et al. [74]2017Biomass and BioenergyGeographical Information SystemAssessment of the sustainable potential of pasture biomass for energy supply
Kraan et al. [75]2017Advances in Intelligent Systems and ComputingCost–Benefit AnalysisModels and studies for adaptation to climate change
Li and Trutnevyte [76]2017Applied EnergyQuantitative Analysis, Monte Carlo MethodsAnalysis to reduce UK greenhouse gas emissions by 2050
Loßner et al. [77]2017Energy EconomicsCost–Benefit AnalysisSimulation of alternative scenarios on renewable energy
Muratori et al. [78]2017Renewable and Sustainable Energy ReviewsCost–Benefit Analysis, Sensitivity AnalysisAssessment of the increase in the cost of building large energy plants in the US
Rakotoson and Praene [79]2017Journal of Cleaner ProductionLife Cycle AssessmentAssessment of the environmental impacts of energy production in the French overseas territories
Scipioni et al. [80]2017Hydrogen Economy: Supply Chain, Life Cycle Analysis and Energy Transition for SustainabilityMultiple Criteria Decision AnalysisAnalysis of the difficulties for a sustainable hydrogen economy
Serp et al. [81]2017EnergiesLife Cycle AssessmentEvaluation of nuclear energy recycling
Wan Ahmad et al. [82]2017Journal of Cleaner ProductionMultiple Criteria Decision AnalysisQuantitative assessment of the forces necessary for the sustainable management of the supply chain
Wang et al. [83]2017Energy ProcediaLife Cycle Cost, Multiple Criteria Decision AnalysisResilience analysis for energy systems
Danielson et al. [84]2018Lecture Notes in Business Information ProcessingMultiple Criteria Decision AnalysisMulti-policy analysis of sustainable choices in Jordan
Deakin and Reid [85]2018Journal of Cleaner ProductionCost–Benefit AnalysisSmart city analytics and behavior tips
Desthieux et al. [86]2018Frontiers in Built EnvironmentGeographical Information SystemPresentation of a methodology for assessing solar radiation and energy production on building roofs and vertical facades in the city center
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Tarighaleslami et al. [43]2020Journal of Cleaner ProductionMonte Carlo Methods, Life Cycle AssessmentAssessment for a cheese production plant
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Wang et al. [153]2020EnergyCost–Benefit Analysis, Environmental Impact AssessmentCost–benefit analysis on different domestic energy use options
Wei et al. [154]2020China Economic ReviewPreference Evaluation OR Econometrics, Quantitative AnalysisPresentation of energy demand progress in China
Wen et al. [155]2020International Journal of Electrical Power and Energy SystemsQuantitative AnalysisQuantitative analysis of the energy transition in China and future hypothetical scenarios
Wiehe et al. [156]2020International Journal of Energy ResearchGeographical Information SystemPresentation of a geospatial model that calculates the potential of renewable energies and their influence on society
Yan et al. [157]2020IEEE Sensors JournalNeural NetworkProposal for an ultrasonic method for the inspection of gas pipelines

References

  1. Becchio, C.; Becchio, C.; Delmastro, C.; Fabi, V.; Lombardi, P. The role of nearly-zero energy buildings in the transition towards Post-Carbon Cities. Sustain. Cities Soc. 2016, 27, 324–337. [Google Scholar] [CrossRef]
  2. Bottero, M.; Caprioli, C.; Cotella, G.; Santangelo, M. Sustainable Cities: A Reflection on Potentialities and Limits based on Existing Eco-Districts in Europe. Sustainability 2019, 11, 5794. [Google Scholar] [CrossRef] [Green Version]
  3. European Commission. A Roadmap for Moving to a Competitive Low Carbon Economy in 2050; European Commission: Brussels, Belgium, 2011. [Google Scholar]
  4. United Nations Department of Economic and Social Affairs. The Sustainable Development Goals Report 2016; United Nations Department of Economic and Social Affairs: New York, NY, USA, 2016. [Google Scholar]
  5. European Commission. The European Green Deal; European Commission: Brussels, Belgium, 2019. [Google Scholar]
  6. Napoli, G.; Barbaro, S.; Giuffrida, S.; Trovato, M.R. The European Green Deal: New Challenges for the Economic Feasibility of Energy Retrofit at District Scale. In New Metropolitan Perspectives; Bevilacqua, C., Calabrò, F., Della Spina, L., Eds.; Springer: Cham, Switzerland, 2021; pp. 1248–1258. [Google Scholar]
  7. International Organization for Standardization. Building and Constructed Assets-Service Life Planning-Part 8: Reference Service Life and Service Life Estimation; ISO 15686-8:2008; International Organization for Standardization: Geneva, Switzerland, 2008. [Google Scholar]
  8. European Commission. Guide to Cost-Benefit Analysis of Investment Projects: Economic Appraisal Tool for Cohesion Policy 2014–2020; European Commission: Brussels, Belgium, 2014. [Google Scholar]
  9. European Commission. Directive 2010/31/UE, Energy Performance of Building Directive Recast (EPBD Recast); European Commission: Brussels, Belgium, 2010. [Google Scholar]
  10. Strantzali, E.; Aravossis, K. Decision making in renewable energy investments: A review. Renew. Sustain. Energy Rev. 2016, 55, 885–898. [Google Scholar] [CrossRef]
  11. Becchio, C.; Bottero, M.; Corgnati, S.; Dell’Anna, F.; Pederiva, G.; Vergerio, G. Proposal for an Integrated Approach to Support Urban Sustainability: The COSIMA Method Applied to Eco-Districts. In Smart and Sustainable Planning for Cities and Regions; Bisello, A., Vettorato, D., Ludlow, D., Baranzelli, C., Eds.; Springer: Cham, Switzerland, 2021; in press. [Google Scholar]
  12. Prestwood, E.; Longhurst, J.; Townsend, I.; Haines, T.; Tsiarapa, E. Facilitating stakeholder dialogues on a carbon neutral city: We need to talk about carbon (and air quality). Air Pollut. XXVI 2018, 501–510. [Google Scholar] [CrossRef] [Green Version]
  13. Laine, J.; Heinonen, J.; Junnila, S. Pathways to Carbon-Neutral Cities Prior to a National Policy. Sustainability 2020, 12, 2445. [Google Scholar] [CrossRef] [Green Version]
  14. Awadh, O. Sustainability and green building rating systems: LEED, BREEAM, GSAS and Estidama critical analysis. J. Build. Eng. 2017, 11, 25–29. [Google Scholar] [CrossRef]
  15. Kaur, H.; Garg, P. Urban sustainability assessment tools: A review. J. Clean. Prod. 2019, 210, 146–158. [Google Scholar] [CrossRef]
  16. Dell’Anna, F.; Bottero, M. Green premium in buildings: Evidence from the real estate market of Singapore. J. Clean. Prod. 2021, 286, 125327. [Google Scholar] [CrossRef]
  17. BRE Global. GreenBook Live: Certified BREEAM Assessments; BRE Global: Hertfordshire, UK, 2015. [Google Scholar]
  18. USGBC U.S. Green Building Council–Green Building Rating System; USGBC U.S.: Washington, DC, USA, 2011. [Google Scholar]
  19. Green Building Council of Australia. Green Star Communities. Guide for Local Governemnt; Green Building Council of Australia: Sydney, Australia, 2012. [Google Scholar]
  20. Japan Sustainable Building Consortium. Comprehensive Assessment System for Built Environment Efficiency (CASBEE); Japan Sustainable Building Consortium: Tokyo, Japan, 2010. [Google Scholar]
  21. BCA. Green Mark Buildings Directory; BCA: Singapore, Singapore, 2005. [Google Scholar]
  22. Yiran, G.A.B.; Ablo, A.D.; Asem, F.E. Urbanisation and domestic energy trends: Analysis of household energy consumption patterns in relation to land-use change in peri-urban Accra, Ghana. Land Use Policy 2020, 99, 105047. [Google Scholar] [CrossRef]
  23. Oudes, D.; Stremke, S. Climate adaptation, urban regeneration and brownfield reclamation: A literature review on landscape quality in large-scale transformation projects. Landsc. Res. 2020, 45, 905–919. [Google Scholar] [CrossRef] [Green Version]
  24. Brunet, C.; Savadogo, O.; Baptiste, P.; Bouchard, M.A.; Rakotoary, J.C.; Ravoninjatovo, A.; Cholez, C.; Gendron, C.; Merveille, N. Impacts Generated by a Large-Scale Solar Photovoltaic Power Plant Can Lead to Conflicts between Sustainable Development Goals: A Review of Key Lessons Learned in Madagascar. Sustainability 2020, 12, 7471. [Google Scholar] [CrossRef]
  25. Raoux, A.; Dambacher, J.M.; Pezy, J.-P.; Mazé, C.; Dauvin, J.-C.; Niquil, N. Assessing cumulative socio-ecological impacts of offshore wind farm development in the Bay of Seine (English Channel). Mar. Policy 2018, 89, 11–20. [Google Scholar] [CrossRef]
  26. Vakulchuk, R.; Overland, I.; Scholten, D. Renewable energy and geopolitics: A review. Renew. Sustain. Energy Rev. 2020, 122, 109547. [Google Scholar] [CrossRef]
  27. Selvakkumaran, S.; Ahlgren, E.O. Review of the use of system dynamics (SD) in scrutinizing local energy transitions. J. Environ. Manag. 2020, 272, 111053. [Google Scholar] [CrossRef] [PubMed]
  28. Gährs, S.; Knoefel, J. Stakeholder demands and regulatory framework for community energy storage with a focus on Germany. Energy Policy 2020, 144, 111678. [Google Scholar] [CrossRef]
  29. Biresselioglu, M.E.; Demir, M.H.; Demirbag-Kaplan, M.; Solak, B. Individuals, collectives, and energy transition: Analysing the motivators and barriers of European decarbonisation. Energy Res. Soc. Sci. 2020, 66, 101493. [Google Scholar] [CrossRef]
  30. Horschig, T.; Thrän, D. Are decisions well supported for the energy transition? A review on modeling approaches for renewable energy policy evaluation. Energy, Sustain. Soc. 2017, 7, 5. [Google Scholar] [CrossRef] [Green Version]
  31. Leontief, W. Input-Output Economics; Oxford University Press: Oxford, UK, 1986; ISBN 0195035275. [Google Scholar]
  32. Burfisher, M.E. Introduction to Computable General Equilibrium Models; Cambridge University Press: Cambridge, UK, 2011; ISBN 9780511975004. [Google Scholar]
  33. Datola, G.; Bottero, M.; De Angelis, E. How Urban Resilience Can Change Cities: A System Dynamics Model Approach. In Lecture Notes in Computer Science; Springer: New York, NY, USA, 2019; pp. 108–122. [Google Scholar] [CrossRef]
  34. Caprioli, C.; Bottero, M.; De Angelis, E. Supporting Policy Design for the Diffusion of Cleaner Technologies: A Spatial Empirical Agent-Based Model. ISPRS Int. J. Geo-Inf. 2020, 9, 581. [Google Scholar] [CrossRef]
  35. Rossi, P.; Lipsey, M.; Freeman, H. Evaluation: A Systematic Approach, 7th ed.; SAGE Publications: Thousand Oaks, CA, USA, 2004. [Google Scholar]
  36. D’Alpaos, C.; Bragolusi, P. Multicriteria prioritization of policy instruments in buildings energy retrofit. Valori Valutazioni 2018, 21, 15–25. [Google Scholar]
  37. International Organization for Standardization. ISO 15686:2008—Buildings and Constructed Assets—Service-Life Planning—Part 5: Life Cycle Costing. ISO/TC 59/CS 14; International Organization for Standardization: Geneva, Switzerland, 2008. [Google Scholar]
  38. Vellini, M.; Bellocchi, S.; Gambini, M.; Manno, M.; Stilo, T. Impact and costs of proposed scenarios for power sector decarbonization: An Italian case study. J. Clean. Prod. 2020, 123667. [Google Scholar] [CrossRef]
  39. Ameur, A.; Berrada, A.; Loudiyi, K.; Aggour, M. Forecast modeling and performance assessment of solar PV systems. J. Clean. Prod. 2020, 267, 122167. [Google Scholar] [CrossRef]
  40. Dell’Anna, F. Green jobs and energy efficiency as strategies for economic growth and the reduction of environmental impacts. Energy Policy 2020, 112031. [Google Scholar] [CrossRef]
  41. Cucchiella, F.; D’Adamo, I.; Gastaldi, M. A profitability assessment of small-scale photovoltaic systems in an electricity market without subsidies. Energy Convers. Manag. 2016, 129, 62–74. [Google Scholar] [CrossRef]
  42. Ghannadzadeh, A.; Tarighaleslami, A.H. Environmental life cycle assessment of glycerine production: Energy transition from natural gas to biomass. Sustain. Energy Technol. Assess. 2020, 42, 100775. [Google Scholar] [CrossRef]
  43. Tarighaleslami, A.H.; Ghannadzadeh, A.; Atkins, M.J.; Walmsley, M.R. Environmental life cycle assessment for a cheese production plant towards sustainable energy transition: Natural gas to biomass vs. natural gas to geothermal. J. Clean. Prod. 2020, 275, 122999. [Google Scholar] [CrossRef]
  44. Banacloche, S.; Herrera, I.; Lechón, Y. Towards energy transition in Tunisia: Sustainability assessment of a hybrid concentrated solar power and biomass plant. Sci. Total. Environ. 2020, 744, 140729. [Google Scholar] [CrossRef] [PubMed]
  45. Jiang, L.; Xue, B.; Ma, Z.; Yu, L.; Huang, B.; Chen, X. A life-cycle based co-benefits analysis of biomass pellet production in China. Renew. Energy 2020, 154, 445–452. [Google Scholar] [CrossRef]
  46. Cox, B.; Bauer, C.; Beltran, A.M.; Van Vuuren, D.P.; Mutel, C.L. Life cycle environmental and cost comparison of current and future passenger cars under different energy scenarios. Appl. Energy 2020, 269, 115021. [Google Scholar] [CrossRef]
  47. Ghannadzadeh, A. Exergy-aided environmental sustainability assessment of an ethylene dichloride–vinyl chloride production process. Chem. Eng. Res. Des. 2018, 130, 109–128. [Google Scholar] [CrossRef]
  48. Ghannadzadeh, A. Assessment of power generation from natural gas and biomass to enhance environmental sustainability of a polyol ether production process for rigid foam polyurethane synthesis. Renew. Energy 2018, 115, 846–858. [Google Scholar] [CrossRef]
  49. Harajli, H.; Kabakian, V.; El-Baba, J.; Diab, A.; Nassab, C. Commercial-scale hybrid solar photovoltaic–diesel systems in select Arab countries with weak grids: An integrated appraisal. Energy Policy 2020, 137, 111190. [Google Scholar] [CrossRef]
  50. Bottero, M.; D’Alpaos, C.; Dell’Anna, F. Boosting Investments in Buildings Energy Retrofit: The Role of Incentives. In New Metropolitan Perspectives; Bevilacqua, C., Calabro, F., Della Spina, L., Eds.; Springer: Cham, Switzerland, 2019; pp. 593–600. ISBN 9783319921013. [Google Scholar]
  51. Becchio, C.; Bertoncini, M.; Boggio, A.; Bottero, M.; Corgnati, S.P.; Dell’Anna, F. The Impact of Users’ Lifestyle in Zero-Energy and Emission Buildings: An Application of Cost-Benefit Analysis. In New Metropolitan Perspectives; Calabrò, F., Della Spina, L., Bevilacqua, C., Eds.; Springer: Cham, Switzerland, 2019; pp. 123–131. [Google Scholar]
  52. Barnes, D.F.; Krutilla, K.; Hyde, W.F. The Urban Household Energy Transition: Social and Environmental Impacts in the Developing World; Routledge: Abingdon, UK, 2005; ISBN 9781936331000. [Google Scholar]
  53. Shterenlikht, A.; Howard, I.C. The CAFE model of fracture—Application to a TMCR steel. Fatigue Fract. Eng. Mater. Struct. 2006, 29, 770–787. [Google Scholar] [CrossRef]
  54. Duke, M.; Ladewig, B.P.; Smart, S.; Rudolph, V.; Da Costa, J.C.D.; Da Costa, J.C.D. Assessment of postcombustion carbon capture technologies for power generation. Front. Chem. Eng. China 2009, 4, 184–195. [Google Scholar] [CrossRef]
  55. Guasco, T.L.; Johnson, M.A.; McCoy, A.B. Unraveling Anharmonic Effects in the Vibrational Predissociation Spectra of H5O2+and Its Deuterated Analogues. J. Phys. Chem. A 2011, 115, 5847–5858. [Google Scholar] [CrossRef] [PubMed]
  56. Arthur, M.D.F.S.; Bond, C.A.; Willson, B. Estimation of elasticities for domestic energy demand in Mozambique. Energy Econ. 2012, 34, 398–409. [Google Scholar] [CrossRef]
  57. Heun, M.K.; De Wit, M. Energy return on (energy) invested (EROI), oil prices, and energy transitions. Energy Policy 2012, 40, 147–158. [Google Scholar] [CrossRef]
  58. Schaede, H.; Von Ahsen, A.; Rinderknecht, S.; Schiereck, D. Electric energy storages–A method for specification, design and assessment. Int. J. Agil. Syst. Manag. 2013, 6, 142. [Google Scholar] [CrossRef]
  59. Eising, J.W.; Van Onna, T.; Alkemade, F. Towards smart grids: Identifying the risks that arise from the integration of energy and transport supply chains. Appl. Energy 2014, 123, 448–455. [Google Scholar] [CrossRef] [Green Version]
  60. Evanno, S.; Weinberger, B. Procédés de méthanisation et gestion des risques industriels. Tech. Sci. Méthodes 2014, 62–73. [Google Scholar] [CrossRef]
  61. King, C.W. Matrix method for comparing system and individual energy return ratios when considering an energy transition. Energy 2014, 72, 254–265. [Google Scholar] [CrossRef]
  62. Nordman, E.E. Energy transitions in Kenya’s tea sector: A wind energy assessment. Renew. Energy 2014, 68, 505–514. [Google Scholar] [CrossRef] [Green Version]
  63. Zimmermann, B.M.; Dura, H.; Weil, M. Towards time-resolved LCA of electric vehicles in Germany. Met. Res. Technol. 2014, 111, 169–178. [Google Scholar] [CrossRef]
  64. Bachmann, T.M. Assessing Air Pollutant-Induced, Health-Related External Costs in the Context of Nonmarginal System Changes: A Review. Environ. Sci. Technol. 2015, 49, 9503–9517. [Google Scholar] [CrossRef] [PubMed]
  65. Wesseh, P.K.; Lin, B. Renewable energy technologies as beacon of cleaner production: A real options valuation analysis for Liberia. J. Clean. Prod. 2015, 90, 300–310. [Google Scholar] [CrossRef]
  66. Zimmermann, B.M.; Dura, H.; Baumann, M.; Weil, M. Prospective time-resolved LCA of fully electric supercap vehicles in Germany. Integr. Environ. Assess. Manag. 2015, 11, 425–434. [Google Scholar] [CrossRef]
  67. Calvert, K. From ‘energy geography’ to ‘energy geographies’. Prog. Hum. Geogr. 2015, 40, 105–125. [Google Scholar] [CrossRef]
  68. Herbert, A.-S.; Azzaro-Pantel, C.; Le Boulch, D. A typology for world electricity mix: Application for inventories in Consequential LCA (CLCA). Sustain. Prod. Consum. 2016, 8, 93–107. [Google Scholar] [CrossRef] [Green Version]
  69. Lizana, J.; Barrios-Padura, Ÿ.; Molina-Huelva, M.; Friedrich, D.; Barrios-Padura, Á. Multi-criteria assessment for the effective decision management in residential energy retrofitting. Energy Build. 2016, 129, 284–307. [Google Scholar] [CrossRef]
  70. Sager-Klauß, C.V. Energetic Communities: Planning Support for Sustainable Energy Transition in Small- and Medium-Sized Communities; TU Delft: Delft, The Netherlands, 2016; Volume 5, ISBN 9789461866363. [Google Scholar]
  71. Sgouridis, S.; Abdullah, A.; Griffiths, S.; Saygin, D.; Wagner, N.; Gielen, D.; Reinisch, H.; McQueen, D. RE-mapping the UAE’s energy transition: An economy-wide assessment of renewable energy options and their policy implications. Renew. Sustain. Energy Rev. 2016, 55, 1166–1180. [Google Scholar] [CrossRef]
  72. Carlier, J.-L.; Chardonnet, C. A high voltage power line: The route with the least environmental and health impact. Public consultation on the plan to rebuild the 400 kV power line between Lille and Arras | Tracé de moindre impact environnemental et sanitaire pour une ligne électrique. Environ. Risques Sante 2017, 16, 292–300. [Google Scholar] [CrossRef]
  73. Kaltenegger, O.; Baikowski, M.; Lingens, J.; Löschel, A. Energy costs in Germany and Europe: An assessment based on a (total real unit) energy cost accounting framework. Energy Policy 2017, 104, 419–430. [Google Scholar] [CrossRef] [Green Version]
  74. Ketzer, D.; Rösch, C.; Haase, M. Assessment of sustainable Grassland biomass potentials for energy supply in Northwest Europe. Biomass-Bioenergy 2017, 100, 39–51. [Google Scholar] [CrossRef]
  75. Kraan, O.; Kramer, G.J.; Van Der Lei, T.; Huppes, G. Modelling the Energy Transition: Towards an Application of Agent Based Modelling to Integrated Assessment Modelling. Adv. Intell. Syst. Comput. 2017, 528, 207–216. [Google Scholar]
  76. Li, F.G.; Trutnevyte, E. Investment appraisal of cost-optimal and near-optimal pathways for the UK electricity sector transition to 2050. Appl. Energy 2017, 189, 89–109. [Google Scholar] [CrossRef] [Green Version]
  77. Loßner, M.; Böttger, D.; Bruckner, T. Economic assessment of virtual power plants in the German energy market—A scenario-based and model-supported analysis. Energy Econ. 2017, 62, 125–138. [Google Scholar] [CrossRef]
  78. Muratori, M.; Ledna, C.; McJeon, H.; Kyle, P.; Patel, P.; Kim, S.H.; Wise, M.; Kheshgi, H.S.; Clarke, L.E.; Edmonds, J. Cost of power or power of cost: A U.S. modeling perspective. Renew. Sustain. Energy Rev. 2017, 77, 861–874. [Google Scholar] [CrossRef]
  79. Rakotoson, V.; Praene, J.P. A life cycle assessment approach to the electricity generation of French overseas territories. J. Clean. Prod. 2017, 168, 755–763. [Google Scholar] [CrossRef] [Green Version]
  80. Scipioni, A.; Manzardo, A.; Ren, R. Hydrogen Economy: Supply Chain, Life Cycle Analysis and Energy Transition for Sustainability; Academic Press: Cambridge, MA, USA, 2017; ISBN 9780128111338. [Google Scholar]
  81. Serp, J.; Poinssot, C.; Bourg, S. Assessment of the Anticipated Environmental Footprint of Future Nuclear Energy Systems. Evidence of the Beneficial Effect of Extensive Recycling. Energies 2017, 10, 1445. [Google Scholar] [CrossRef] [Green Version]
  82. Wan Ahmad, W.N.K.; Rezaei, J.; Sadaghiani, S.; Tavasszy, L.A. Evaluation of the external forces affecting the sustainability of oil and gas supply chain using Best Worst Method. J. Clean. Prod. 2017, 153, 242–252. [Google Scholar] [CrossRef]
  83. Wang, J.; Sun, T.; Deng, S.; Li, K.; Zhao, J.; Gao, L.; Wang, Y. A resilience analysis on energy system: A preliminary case study for solar-assisted CCS. Energy Procedia 2017, 142, 3220–3225. [Google Scholar] [CrossRef]
  84. Danielson, M.; Ekenberg, L.; Komendantova, N. A Multi-Stakeholder Approach to Energy Transition Policy Formation in Jordan; Springer: Cham, Switzerland, 2018; Volume 315, ISBN 9783319928739. [Google Scholar]
  85. Deakin, M.; Reid, A. Smart cities: Under-gridding the sustainability of city-districts as energy efficient-low carbon zones. J. Clean. Prod. 2018, 173, 39–48. [Google Scholar] [CrossRef]
  86. Desthieux, G.; Carneiro, C.; Camponovo, R.; Ineichen, P.; Morello, E.; Boulmier, A.; Abdennadher, N.; Dervey, S.; Ellert, C. Solar Energy Potential Assessment on Rooftops and Facades in Large Built Environments Based on LiDAR Data, Image Processing, and Cloud Computing. Methodological Background, Application, and Validation in Geneva (Solar Cadaster). Front. Built Environ. 2018, 4. [Google Scholar] [CrossRef]
  87. Huang, J.; Xue, Y.; Jiang, C.; Xue, F.; Qian, F. Carbon Market Risk Analysis and Control Part Ⅰ Framework Design. Dianli Xitong Zidonghua/Automation. Electr. Power Syst. 2018, 42, 11–18. [Google Scholar] [CrossRef]
  88. Li, F.G.; Pye, S. Uncertainty, politics, and technology: Expert perceptions on energy transitions in the United Kingdom. Energy Res. Soc. Sci. 2018, 37, 122–132. [Google Scholar] [CrossRef] [Green Version]
  89. Prol, J.L.; Steininger, K.W. The social profitability of photovoltaics in Germany. Prog. Photovolt. Res. Appl. 2018, 26, 631–641. [Google Scholar] [CrossRef]
  90. Maennel, A.; Kim, H.-G. Comparison of Greenhouse Gas Reduction Potential through Renewable Energy Transition in South Korea and Germany. Energies 2018, 11, 206. [Google Scholar] [CrossRef] [Green Version]
  91. Meschede, H.; Child, M.; Breyer, C. Assessment of sustainable energy system configuration for a small Canary island in 2030. Energy Convers. Manag. 2018, 165, 363–372. [Google Scholar] [CrossRef]
  92. Meylan, G.; Haupt, M.; Duygan, M.; Hellweg, S.; Stauffacher, M. Linking energy scenarios and waste storylines for prospective environmental assessment of waste management systems. Waste Manag. 2018, 81, 11–21. [Google Scholar] [CrossRef]
  93. Mullally, G.; Dunphy, N.; O’Connor, P. Participative environmental policy integration in the Irish energy sector. Environ. Sci. Policy 2018, 83, 71–78. [Google Scholar] [CrossRef]
  94. Shmelev, S.E.; Shmeleva, I.A. Global urban sustainability assessment: A multidimensional approach. Sustain. Dev. 2018, 26, 904–920. [Google Scholar] [CrossRef]
  95. Skoczkowski, T.; Bielecki, S.; Węglarz, A.; Włodarczak, M.; Gutowski, P. Impact assessment of climate policy on Poland’s power sector. Mitig. Adapt. Strat. Glob. Chang. 2018, 23, 1303–1349. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  96. Moghadam, S.T.; Toniolo, J.; Mutani, G.; Lombardi, P. A GIS-statistical approach for assessing built environment energy use at urban scale. Sustain. Cities Soc. 2018, 37, 70–84. [Google Scholar] [CrossRef]
  97. Tronchin, L.; Manfren, M.; James, P.A. Linking design and operation performance analysis through model calibration: Parametric assessment on a Passive House building. Energy 2018, 165, 26–40. [Google Scholar] [CrossRef] [Green Version]
  98. Walker, S.; Labeodan, T.; Boxem, G.; Maassen, W.; Zeiler, W. An assessment methodology of sustainable energy transition scenarios for realizing energy neutral neighborhoods. Appl. Energy 2018, 228, 2346–2360. [Google Scholar] [CrossRef]
  99. Wen, Y.; Cai, B.; Xue, Y.; Wang, S.; Chen, Z.; Zhu, J.; Jiang, D.; Yue, Z. Assessment of Power System Low-carbon Transition Pathways Based on China’s Energy Revolution Strategy. Energy Procedia 2018, 152, 1039–1044. [Google Scholar] [CrossRef]
  100. Zaman, R.; Brudermann, T.; Kumar, S.; Islam, N. A multi-criteria analysis of coal-based power generation in Bangladesh. Energy Policy 2018, 116, 182–192. [Google Scholar] [CrossRef]
  101. Zeyringer, M.; Fais, B.; Keppo, I.; Price, J. The potential of marine energy technologies in the UK–Evaluation from a systems perspective. Renew. Energy 2018, 115, 1281–1293. [Google Scholar] [CrossRef]
  102. Zimmermann, M.; Pye, S. Inequality in energy and climate policies: Assessing distributional impact consideration in UK policy appraisal. Energy Policy 2018, 123, 594–601. [Google Scholar] [CrossRef]
  103. Bódis, K.; Kougias, I.; Jäger-Waldau, A.; Taylor, N.; Szabó, S. A high-resolution geospatial assessment of the rooftop solar photovoltaic potential in the European Union. Renew. Sustain. Energy Rev. 2019, 114, 114. [Google Scholar] [CrossRef]
  104. Böing, F.; Regett, A. Hourly CO2 Emission Factors and Marginal Costs of Energy Carriers in Future Multi-Energy Systems. Energies 2019, 12, 2260. [Google Scholar] [CrossRef] [Green Version]
  105. Burnley, S.J. A life cycle assessment of energy from waste and recycling in a post-carbon future. Detritus 2018, 5, 150–162. [Google Scholar] [CrossRef]
  106. Camargo, L.R.; Wuth, J.; Biberacher, M.; Dorner, W. A spatially explicit assessment of middle and low voltage grid requirements in Bavaria until 2050. GeoScape 2019, 13, 88–97. [Google Scholar] [CrossRef] [Green Version]
  107. Cavalcanti, E.J.; Carvalho, M.; Azevedo, J.L.B. Exergoenvironmental results of a eucalyptus biomass-fired power plant. Energy 2019, 189, 116188. [Google Scholar] [CrossRef]
  108. Coroiu, M. Energy efficiency holistic approach for new energy business model towards 2030. In Proceedings of the 2019 8th International Conference on Modern Power Systems (MPS), Cluj Napoca, Romania, 21–23 May 2019; pp. 1–8. [Google Scholar]
  109. Correa-Florez, C.; Michiorri, A.; Kariniotakis, G. Comparative Analysis of Adjustable Robust Optimization Alternatives for the Participation of Aggregated Residential Prosumers in Electricity Markets. Energies 2019, 12, 1019. [Google Scholar] [CrossRef] [Green Version]
  110. Costantini, V.; Crespi, F.; Paglialunga, E. Capital–energy substitutability in manufacturing sectors: Methodological and policy implications. Eurasian Bus. Rev. 2018, 9, 157–182. [Google Scholar] [CrossRef]
  111. Drouilles, J.; Aguacil, S.; Hoxha, E.; Jusselme, T.; Lufkin, S.; Rey, E. Environmental impact assessment of Swiss residential archetypes: A comparison of construction and mobility scenarios. Energy Effic. 2019, 12, 1661–1689. [Google Scholar] [CrossRef]
  112. Ghannadzadeh, A.; Meymivand, A. Environmental sustainability assessment of an ethylene oxide production process through Cumulative Exergy Demand and ReCiPe. Clean Technol. Environ. Policy 2019, 21, 1765–1777. [Google Scholar] [CrossRef]
  113. Ghannadzadeh, A.; Tarighaleslami, A.H. Exergetic environmental sustainability assessment supported by Monte Carlo simulations: A case study of a chlorine production process. Environ. Prog. Sustain. Energy 2019, 38. [Google Scholar] [CrossRef]
  114. Jenniches, S.; Worrell, E. Regional economic and environmental impacts of renewable energy developments: Solar PV in the Aachen Region. Energy Sustain. Dev. 2019, 48, 11–24. [Google Scholar] [CrossRef]
  115. Jin, Y.; Behrens, P.; Tukker, A.; Scherer, L. Water use of electricity technologies: A global meta-analysis. Renew. Sustain. Energy Rev. 2019, 115, 109391. [Google Scholar] [CrossRef]
  116. Leporini, M.; Marchetti, B.; Corvaro, F.; Polonara, F. Reconversion of offshore oil and gas platforms into renewable energy sites production: Assessment of different scenarios. Renew. Energy 2019, 135, 1121–1132. [Google Scholar] [CrossRef]
  117. Marcucci, A.; Panos, E.; Kypreos, S.; Fragkos, P. Probabilistic assessment of realizing the 1.5 °C climate target. Appl. Energy 2019, 239, 239–251. [Google Scholar] [CrossRef]
  118. Markov, K.K.; Rajaković, N. Multi-energy microgrids with ecotourism purposes: The impact of the power market and the connection line. Energy Convers. Manag. 2019, 196, 1105–1112. [Google Scholar] [CrossRef]
  119. Mohajeri, N.; Perera, A.; Coccolo, S.; Mosca, L.; Le Guen, M.; Scartezzini, J.-L. Integrating urban form and distributed energy systems: Assessment of sustainable development scenarios for a Swiss village to 2050. Renew. Energy 2019, 143, 810–826. [Google Scholar] [CrossRef]
  120. Nitsch, F.; Turkovska, O.; Schmidt, J. Observation-based estimates of land availability for wind power: A case study for Czechia. Energy, Sustain. Soc. 2019, 9, 1–13. [Google Scholar] [CrossRef] [Green Version]
  121. Pedinotti-Castelle, M.; Astudillo, M.F.; Pineau, P.-O.; Amor, B. Is the environmental opportunity of retrofitting the residential sector worth the life cycle cost? A consequential assessment of a typical house in Quebec. Renew. Sustain. Energy Rev. 2019, 101, 428–439. [Google Scholar] [CrossRef]
  122. Selvakkumaran, S.; Ahlgren, E.O. Determining the factors of household energy transitions: A multi-domain study. Technol. Soc. 2019, 57, 54–75. [Google Scholar] [CrossRef]
  123. Stremke, S.; Schöbel, S. Research through design for energy transition: Two case studies in Germany and The Netherlands. Smart Sustain. Built Environ. 2019, 8, 16–33. [Google Scholar] [CrossRef] [Green Version]
  124. Thonemann, N.; Maga, D. Life Cycle Assessment of German Energy Scenarios; Springer: Cham, Switzerland, 2018; pp. 165–175. [Google Scholar]
  125. Watari, T.; McLellan, B.C.; Giurco, D.; Dominish, E.; Yamasue, E.; Nansai, K. Total material requirement for the global energy transition to 2050: A focus on transport and electricity. Resour. Conserv. Recycl. 2019, 148, 91–103. [Google Scholar] [CrossRef]
  126. Yang, D.; Huang, J.; Hu, X.; Guo, H.; Xie, D. Breakdown of energy transfer gap laws revealed by full-dimensional quantum scattering between HF molecules. Nat. Commun. 2019, 10, 1–6. [Google Scholar] [CrossRef] [Green Version]
  127. Yang, X.; Cai, B.; Xue, Y.; Zhang, J.; Zhao, Y.; Hu, R. Quantitative Assessment of Clean Transition of GenCo Considering Other Participants’ Generation Investment. Energy Procedia 2019, 156, 23–27. [Google Scholar] [CrossRef]
  128. Yu, H.-H.; Chang, K.-H.; Hsu, H.-W.; Cuckler, R. A Monte Carlo simulation-based decision support system for reliability analysis of Taiwan’s power system: Framework and empirical study. Energy 2019, 178, 252–262. [Google Scholar] [CrossRef]
  129. Albers, A.; Collet, P.; Benoist, A.; Hélias, A. Back to the future: Dynamic full carbon accounting applied to prospective bioenergy scenarios. Int. J. Life Cycle Assess. 2019, 25, 1242–1258. [Google Scholar] [CrossRef]
  130. Albers, A.; Avadí, A.; Benoist, A.; Collet, P.; Hélias, A. Modelling dynamic soil organic carbon flows of annual and perennial energy crops to inform energy-transport policy scenarios in France. Sci. Total. Environ. 2020, 718, 135278. [Google Scholar] [CrossRef]
  131. Atkins, E. Contesting the ‘greening’ of hydropower in the Brazilian Amazon. Polit. Geogr. 2020, 80, 102179. [Google Scholar] [CrossRef]
  132. Braunholtz-Speight, T.; Sharmina, M.; Manderson, E.; McLachlan, C.; Hannon, M.; Hardy, J.; Mander, S. Business models and financial characteristics of community energy in the UK. Nat. Energy 2020, 5, 169–177. [Google Scholar] [CrossRef]
  133. Dean, M.; Blackford, J.; Connelly, D.; Hines, R. Insights and guidance for offshore CO2 storage monitoring based on the QICS, ETI MMV, and STEMM-CCS projects. Int. J. Greenh. Gas Control. 2020, 100, 103120. [Google Scholar] [CrossRef]
  134. Höfer, T.; Madlener, R. A participatory stakeholder process for evaluating sustainable energy transition scenarios. Energy Policy 2020, 139, 111277. [Google Scholar] [CrossRef] [Green Version]
  135. Hu, C.; Huang, J.; Xue, Y.; Li, T.; Song, X.; Lai, Y. Monetary Value Evaluation for Carbon Emission Reduction Benefit of Energy Transition. Dianli Xitong Zidonghua/Autom. Electr. Power Syst. 2020, 44, 29–34. [Google Scholar] [CrossRef]
  136. Kim, P.; Kim, J.; Yim, M.-S. How deliberation changes public opinions on nuclear energy: South Korea’s deliberation on closing nuclear reactors. Appl. Energy 2020, 270, 115094. [Google Scholar] [CrossRef]
  137. Kokkinos, K.; Karayannis, V.; Moustakas, K. Circular bio-economy via energy transition supported by Fuzzy Cognitive Map modeling towards sustainable low-carbon environment. Sci. Total. Environ. 2020, 721, 137754. [Google Scholar] [CrossRef] [PubMed]
  138. Middelhauve, L.; Santeccia, A.; Girardin, L.; Margni, M.; Maréchal, F. Key performance indicators for decision making in building energy systems. In Proceedings of the ECOS 2020–Proceedings of the 33rd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, Osaka, Japan, 29 June–3 July 2020; pp. 401–412. [Google Scholar]
  139. Miranda, M.M.; Raymond, J.; Dezayes, C. Uncertainty and Risk Evaluation of Deep Geothermal Energy Source for Heat Production and Electricity Generation in Remote Northern Regions. Energies 2020, 13, 4221. [Google Scholar] [CrossRef]
  140. Muñoz, I.; Hernandez, P.; Pérez-Iribarren, E.; Pedrero, J.; Arrizabalaga, E.; Hermoso, N. Methodology for integrated modelling and impact assessment of city energy system scenarios. Energy Strat. Rev. 2020, 32, 100553. [Google Scholar] [CrossRef]
  141. Nechifor, V.; Calzadilla, A.; Bleischwitz, R.; Winning, M.; Tian, X.; Usubiaga, A. Steel in a circular economy: Global implications of a green shift in China. World Dev. 2020, 127, 104775. [Google Scholar] [CrossRef]
  142. Paltsev, S. Projecting Energy and Climate for the 21st Century. Econ. Energy Environ. Policy 2020, 9, 43–62. [Google Scholar] [CrossRef]
  143. Partidário, P.; Aguiar, R.; Martins, P.; Rangel, C.M.; Cabrita, I. The hydrogen roadmap in the Portuguese energy system–Developing the P2G case. Int. J. Hydrog. Energy 2019, 45, 25646–25657. [Google Scholar] [CrossRef] [Green Version]
  144. Patouillard, L.; Lorne, D.; Collet, P.; Bulle, C.; Margni, M. Prioritizing regionalization to enhance interpretation in consequential life cycle assessment: Application to alternative transportation scenarios using partial equilibrium economic modeling. Int. J. Life Cycle Assess. 2020, 25, 2325–2341. [Google Scholar] [CrossRef]
  145. Raugei, M.; Peluso, A.; Leccisi, E.; Fthenakis, V.M. Life-Cycle Carbon Emissions and Energy Return on Investment for 80% Domestic Renewable Electricity with Battery Storage in California (U.S.A.). Energies 2020, 13, 3934. [Google Scholar] [CrossRef]
  146. Rohe, S. The regional facet of a global innovation system: Exploring the spatiality of resource formation in the value chain for onshore wind energy. Environ. Innov. Soc. Transitions 2020, 36, 331–344. [Google Scholar] [CrossRef]
  147. Sareen, S.; Grandin, J. European green capitals: Branding, spatial dislocation or catalysts for change? Geogr. Ann. Ser. B Hum. Geogr. 2019, 102, 101–117. [Google Scholar] [CrossRef]
  148. Saretta, E.; Caputo, P.; Frontini, F. An integrated 3D GIS-based method for estimating the urban potential of BIPV retrofit of façades. Sustain. Cities Soc. 2020, 62, 102410. [Google Scholar] [CrossRef]
  149. Seck, G.S.; Hache, E.; Bonnet, C.; Simoën, M.; Carcanague, S. Copper at the crossroads: Assessment of the interactions between low-carbon energy transition and supply limitations. Resour. Conserv. Recycl. 2020, 163, 105072. [Google Scholar] [CrossRef] [PubMed]
  150. Sharma, T.; Gallachóir, B.Ó.; Rogan, F. A new hybrid approach for evaluating technology risks and opportunities in the energy transition in Ireland. Environ. Innov. Soc. Transit. 2020, 35, 429–444. [Google Scholar] [CrossRef]
  151. Shaw-Williams, D.; Susilawati, C. A techno-economic evaluation of Virtual Net Metering for the Australian community housing sector. Appl. Energy 2020, 261, 114271. [Google Scholar] [CrossRef]
  152. Taherahmadi, J.; Noorollahi, Y.; Panahi, M. Toward comprehensive zero energy building definitions: A literature review and recommendations. Int. J. Sustain. Energy 2020, 1–29. [Google Scholar] [CrossRef]
  153. Wang, Q.; Lin, J.; Zhou, K.; Fan, J.; Kwan, M.-P. Does urbanization lead to less residential energy consumption? A comparative study of 136 countries. Energy 2020, 202, 117765. [Google Scholar] [CrossRef]
  154. Wei, C.; Löschel, A.; Managi, S. Recent advances in energy demand research in China. China Econ. Rev. 2020, 63, 101517. [Google Scholar] [CrossRef]
  155. Wen, Y.; Cai, B.; Yang, X.; Xue, Y. Quantitative analysis of China’s Low-Carbon energy transition. Int. J. Electr. Power Energy Syst. 2020, 119, 105854. [Google Scholar] [CrossRef]
  156. Wiehe, J.; Thiele, J.; Walter, A.; Hashemifarzad, A.; Hingst, J.Z.; Von Haaren, C. Nothing to regret: Reconciling renewable energies with human wellbeing and nature in the German Energy Transition. Int. J. Energy Res. 2021, 45, 745–758. [Google Scholar] [CrossRef]
  157. Yan, Y.; Liu, D.; Gao, B.; Tian, G.; Cai, Z.C. A Deep Learning-Based Ultrasonic Pattern Recognition Method for Inspecting Girth Weld Cracking of Gas Pipeline. IEEE Sensors J. 2020, 20, 7997–8006. [Google Scholar] [CrossRef]
Figure 1. Literature review framework.
Figure 1. Literature review framework.
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Figure 2. Historical production for “all fields” research and limited to title, abstract, and keywords.
Figure 2. Historical production for “all fields” research and limited to title, abstract, and keywords.
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Figure 3. Subject area analysis for all fields of research.
Figure 3. Subject area analysis for all fields of research.
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Figure 4. Subject area analysis limited to title, abstract, and keywords.
Figure 4. Subject area analysis limited to title, abstract, and keywords.
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Figure 5. Historical production of literature using “energy transition” keyword in research, limited to title, abstract, and keywords.
Figure 5. Historical production of literature using “energy transition” keyword in research, limited to title, abstract, and keywords.
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Figure 6. Historical production of literature using “post-carbon” keyword in research, limited to title, abstract, and keywords.
Figure 6. Historical production of literature using “post-carbon” keyword in research, limited to title, abstract, and keywords.
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Figure 7. Subject area analysis for articles that used “energy transition” as a keyword.
Figure 7. Subject area analysis for articles that used “energy transition” as a keyword.
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Figure 8. Subject area analysis for articles which used “post-carbon” as a keyword.
Figure 8. Subject area analysis for articles which used “post-carbon” as a keyword.
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Figure 9. Historical production in different territorial scales.
Figure 9. Historical production in different territorial scales.
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Figure 10. Number of publications per country.
Figure 10. Number of publications per country.
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Figure 11. Number of documents by affiliations performed by SCOPUS.
Figure 11. Number of documents by affiliations performed by SCOPUS.
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Figure 12. Number of documents in relation to evaluation approaches and methods.
Figure 12. Number of documents in relation to evaluation approaches and methods.
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Figure 13. Historical production of literature per evaluation approach and method considered.
Figure 13. Historical production of literature per evaluation approach and method considered.
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Figure 14. Subject areas per evaluation approach.
Figure 14. Subject areas per evaluation approach.
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Bottero, M.; Dell’Anna, F.; Morgese, V. Evaluating the Transition Towards Post-Carbon Cities: A Literature Review. Sustainability 2021, 13, 567. https://0-doi-org.brum.beds.ac.uk/10.3390/su13020567

AMA Style

Bottero M, Dell’Anna F, Morgese V. Evaluating the Transition Towards Post-Carbon Cities: A Literature Review. Sustainability. 2021; 13(2):567. https://0-doi-org.brum.beds.ac.uk/10.3390/su13020567

Chicago/Turabian Style

Bottero, Marta, Federico Dell’Anna, and Vito Morgese. 2021. "Evaluating the Transition Towards Post-Carbon Cities: A Literature Review" Sustainability 13, no. 2: 567. https://0-doi-org.brum.beds.ac.uk/10.3390/su13020567

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