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European directives on sustainable finance identify binding guidelines in investment planning for the decarbonization of the real estate sector. The Sustainable Finance Disclosure Regulation regularizes the methods of economic evaluation of projects by identifying the pillars Environmental (E), Social (S) and Governance (G) as thematic reference stylistic features. The ESG triptych constitutes inspiration in the scientific literature in the field for the proposal and testing of valuation algorithms aimed at the optimal structuring of investment portfolios. The paper proposes an ESG-based economic-financial analysis model for energy retrofit programs referring to the existing real estate sector. The model assumes the configuration of a multi-objective system built by borrowing algebraic formalisms of Operations Research, especially those of optimization algorithms. These algorithms make it possible to construct logical-functional relationships such as to represent the anatomy of the proposed evaluation model in terms of objective function and constraints, for example on the European decarbonization pathway target, or even on the available budget. The implementation of the proposed model, applied to a case study, returns a time priority list of assets to be energy efficient, balancing for each the investment costs, payback period and post-retrofit CO2 production.

Urban development is increasingly scrutinized for its sustainability from an economic, social, and environmental viewpoint. This study emphasizes how important indicators are in capturing the complexity of urban settings when assessing urban landscapes and making sure that comprehensive development plans incorporate all these aspects. The work aim is to forward the investigation of the ontology of indicators related to urban sustainability, specifically, a framework for spatial and temporal analysis and an attempt to align terminology with the sustainability indicators of the ISO spectrum. The methodology encompasses three main phases: a systematic review of sustainability indicators from the scientific literature across various territorial scales; the mapping of individual indicators to their appropriate spatial–temporal measurement ranges; and the alignment of these spatially and temporally specific indicators with ISO standards. Focusing on the Italian context, this study establishes an ontological spatial–temporal framework. It analyzes ISO indicators that can be managed in Italian spatial settings. The main objective of this part of the research is to select through a critical analysis the most frequent indicators in order to be able to make an alignment and define those that aim more at the goals of the 2030 Agenda on sustainability. This innovative approach enhances urban issue awareness and supports informed decision-making by demonstrating how sustainability indicators can be effectively utilized in downscaling strategies to create a policy for the practical use of indicators.

Europe faces a situation where housing represents the main savings for most of the population, while the majority of homeowners are seniors aged over 65. The desire to supplement pensions has led to a growing interest in generating income from these savings, with bare ownership emerging as a notable option. This solution makes it possible to transfer the ownership of the home while maintaining usufruct rights for the duration of the owner’s lifetime. This paper examines the status of bare ownership in the city of Rome by web scraping the house offers published on web portals and segmenting those offered as bare ownership. Machine learning analysis based on neural networks and binary logit regression allows for the observation of the particular behavior of the housing supply in bare ownership; it shows the different intrinsic and extrinsic characteristics that determine this Real Estate segment. The findings highlight the development of a growing market strongly influenced by the location of assets. These findings provide valuable insights for both investors and urban planners regarding changes in urban dynamics processes.

The dynamics underpinning the urban landscape change are primarily driven by social, economic, and environmental issues. Owing to the population’s fluctuating needs, a new and dual perspective of urban space emerges. The Artificial Intelligence (AI) of a territory, or the system of technical diligence associated with the anthropocentric world, makes sense in the context of this temporal mismatch between territorial processes and utilitarian apparatus. This creates cerebral connections between several concurrent decision-making systems, leading to numerous perspectives of the same urban environment, often filtered by the people whose interests direct the information flow till the transformability. In contrast to the conventional methodologies of decision analysis, which are employed to facilitate convenient judgments between alternative options, innovative Artificial Intelligence tools are gaining traction as a means of more effectively evaluating and selecting fast-track solutions. The study’s goal is to investigate the cross-functional relationships between Artificial Intelligence (AI) and current decision-making support systems, which are increasingly being used to interpret urban growth and development from a multi-dimensional perspective, such as a multi-criteria one. Individuals in charge of administering and governing a territory will gain from artificial intelligence techniques because they will be able to test resilience and responsibility in decision-making circumstances while also responding fast and spontaneously to community requirements. The study evaluates current grading techniques and recommends areas for future upgrades via the lens of the potentials afforded by AI technology to the establishment of digitization pathways for technological advancements in the urban valuation.

In a global context, the identification of frameworks and assessment tools for achieving sustainable development requires the study of urban sustainability at different scales. While sustainability can be quantified more precisely on a larger scale, it is challenging to adapt these accounting techniques to smaller sites. Measuring becomes more challenging when researching urban sustainability from several viewpoints, especially when constructing an acceptable set of measurements while taking into account the several issues of the unique decision-making apparatus from theoretical and geographical perspectives. Which sorts of indicators should be prioritized above others? How many indicators should be used? Which criteria should be employed to choose the best indicators for the location of interest? This study addresses the aforementioned research problems by proposing a systematic, multidirectional approach to defining an adequate collection of indicators for sustainability accounting in urban situations. A top-down strategy, which provides a literature study to identify regularly used indicators in essential sustainability categories, is joined by a bottom-up approach, which creates indicators based on real-world circumstances. The combination of these two methodologies seeks to produce a set of relevant sustainability measurements. A neighborhood rehabilitation project for public housing in Le Lignon (Switzerland) serves as a pilot case for calibrating the proposed multidirectional technique. The final findings can support the public and private parties involved in sustainable urban planning procedures in assessing urban projects based on location-specific features.

IntroductionThe industrial activity constitutes one of the most driving sectors of a nation, as it is often considered at the center of public debate as the fulcrum of development policies. However, considering the climate impacts generated, many industries have necessarily changed, relocated, and/or interrupted their production. Due to the connection of industrial sites with the socio-economic, environmental, and health systems of cities, the real estate market dynamics can be differently affected by the presence of polluting industrial sites. With reference to the Italian context, the goal of the research is to, firstly, verify whether there is a functional relationship between the presence of polluting industrial sites and the residential real estate market dynamics, for then determining its type and the extent of purchase price affection.MethodThe proposed logical-evaluative model is based on the application of an econometric technique for investigating the significance of the industrial sites on the residential real estate dynamics through a set of technological, locational, and health variables.ResultsThe obtained results show that the total surface area of the polluting sites, the activity level and the industrial plant opening date are among the most relevant variables, instead the accessibility to the industrial site does not influence the real estate market dynamics.Discussion and practical implicationsThe main practical implication of the present research consists of the possibility to provide a support for the activation of strategies aimed at adopting sustainable development models in the industrial sector.

Green areas in urban agglomerations are strategic resource for the sustainable city development. The implementation of Urban Forestry Projects (UFP) allows on the one hand to raise the environmental quality level, improving the microclimate and preserving biodiversity, on the other hand to promote urban regeneration and promote socio-economic development by creating eco-systemic s er vices for the population. The result is a more rational land use and an increase in real estate values. Although the EU Directives show the need to promote the sustainable territory growth through the recover y and redevelopment of the built environment, the implementation of investments based on eco-system logic is rarely counted as a priority action for the city, often preferring a different allocation of available resources. The present work aims first to define an indicators set useful to express the value components – financial, social, cultural and ecological- environmental – for the UFP. These indicator s are the reference terms for the characterization of an innovative protocol of multicriteria analysis for the public operator who wants to establish the optimal distribution of funds between UFP units in limited areas of the urban fabric. The protocol uses the algorithms of mathematical programming and is tested on a case study about urban areas to be redeveloped.

The issue of sustainability is central to development strategies. Although this alignment is acknowledged and shared world-wide, territorial development in a sustainable light must also take the ongoing COVID-19 pandemic into consideration, specifically by evaluating the effects of COVID-19 on the global health, social order, and economic-environmental system. The research suggests a sensitivity index to gauge the degree of territorial sustainability taking the COVID-19 pandemic’s impacts into account. A study set of countries, as identified by the Organization for Economic Co-operation and Development (OECD), is used to test the developed index. The index evaluates a country’s performance in terms of economic, social, and environmental sustainability while also considering the relative risk of COVID-19. The proposed index measures territorial sustainability from a variety of angles by enabling comparisons between the circumstances before and after current shocks in the socioeconomic and environmental performance frames by pandemic emergency. The index was created using an integrated assessment method that was based on the Choquet Integral (CI) mathematical framework and Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA). The study establishes a unique and up-scaling methodology for constructing the sensitivity index, significantly advancing the suggestions for sustainable accounting under uncertain circumstances at the territorial scale. Adopting indices that quantify territorial sustainability under uncertainty may help guide policy decisions from an investment programming viewpoint, particularly when it comes to allocating financial resources to the economic sectors most impacted by shock events such as the COVID-19 pandemic.

Abstract Fingolimod is the first orally administered drug approved for the treatment of relapsing–remitting multiple sclerosis (MS). This drug, modulating sphingosine receptors, regulates the trafficking of lymphocytes between primary and secondary lymphoid organs, trapping naïve T cells and central memory T cells in secondary lymphoid organs, without affecting effector memory T cells and therefore without compromising immunosurveillance. Additionally, fingolimod inhibits expression of Th1 and Th17 cytokines and enhances regulatory T-cell differentiation. It also acts on the B arm of immunity through an increased ratio of naïve to memory B cells, higher percentage of plasma cells, and highly increased proportion of transitional B cells as well as additional regulatory subsets. Fingolimod treatment enhances the capacity of regulatory B cells to transmigrate across brain endothelial cells. In fact, patients treated with fingolimod have increased regulatory B-cell frequency in the cerebrospinal fluid. These findings suggest a novel role for fingolimod in MS, by both direct effects and indirect partitioning effects on lymphocytes.

Background and Aims: Interferon beta (IFNb) is a safe first-line drug commonly used for relapsing-remitting (RR)-MS. Nevertheless, a considerable proportion of patients do not respond to IFNb treatment. Therefore, until now, a number of studies have investigated various markers that could predict the patients who would respond to IFNb therapy. The objective of this study was to identify reliable biomarkers to predict the efficacy of IFNb treatment in MS. Methods: In a group of 116 patients with clinically isolated syndrome (CIS) and RR-MS, we explored the association between CSF detectability of a large set of proinflammatory and anti-inflammatory molecules at the time of diagnosis and response to IFNb after the first year of treatment. The absence of clinical relapses, radiological activity and disability progression (NEDA-3) was assessed at the end of 1-year follow up. The results were compared with those obtained in additional groups of CIS and RR-MS patients treated with other first-line drugs (dimethyl fumarate and glatiramer acetate). Results: CSF undetectability of macrophage inflammatory protein (MIP)-1α was the main predictor of reaching NEDA-3 status after 1 year of IFNb treatment. Moreover, detectable platelet-derived growth factor (PDGF) was associated with higher probability of reaching NEDA-3. Conversely, no associations with the CSF molecules were found in the two other groups of patients treated either with dimethyl fumarate or with glatiramer acetate. Conclusion: MIP-1α and PDGF could potentially represent suitable CSF biomarkers able to predict response to IFNb in MS.

Specific proinflammatory and anti-inflammatory molecules could represent useful cerebrospinal fluid (CSF) biomarkers to predict the clinical course of multiple sclerosis (MS). The proinflammatory molecule interleukin (IL)-6 has been investigated in the pathophysiology of MS and has been associated in previous smaller studies to increased disability and disease activity. Here, we wanted to further address IL-6 as a possible CSF biomarker of MS by investigating its detectability in a large cohort of 534 MS patients and in 103 individuals with other non-inflammatory neurological diseases. In these newly diagnosed patients, we also explored correlations between IL-6 detectability, MS phenotypes, and disease characteristics. We found that IL-6 was more frequently detectable in the CSF of MS patients compared with their control counterparts as significant differences emerged between patients with Clinically isolated syndrome (CIS), Relapsing–remitting (RR), and secondary progressive and primary progressive MS compared to non-inflammatory controls. IL-6 was equally present in the CSF of all MS phenotypes. In RR MS patients, IL-6 detectability was found to signal clinically and/or radiologically defined disease activity, among all other clinical characteristics. Our results add further evidence that CSF proinflammatory cytokines could be useful for the identification of those MS patients who are prone to increased disease activity. In particular, IL-6 could represent an interesting prognostic biomarker of MS, as also demonstrated in other diseases where CSF IL-6 was found to identify patients with worse disease severity.

Obtaining accurate tree cover maps within cities is a first step toward managing for equitable access to their ecosystem services. For example, by removing air pollutants trees contribute to fewer health impacts, and tree cover expansion could extend these benefits by targeting the most polluted areas and vulnerable populations. To support strategic tree expansion, this research created urban tree cover maps using the 2017 NASA MOD44B satellite 250 m pixel product for 35 megacities, areas with large levels of pollution and vulnerable populations. Estimates of tree cover from photo-interpretation (PI) were used to characterize map error, city-wide, and from low to high tree cover, using 21 bins from 0 to 100% tree cover. Map accuracy was highest when MOD44B percent tree cover was combined with its tree cover standard deviation product, with average difference of 1.8% compared with PI estimates of 19.9% city-wide tree cover. MOD44B estimates of tree cover spatial patterns had strong explanatory value. The maps explained the PI estimates of low to high tree cover at 5% tree cover intervals with an R2 = 0.97. The Getis Ord Gi* statistic determined a non-random spatial distribution of tree cover within the megacities, with significant clustering into hot spots of relatively high tree cover and cold spots of relatively low tree cover. Tree cover hot spots were most often furthest from downtown, at the rural-urban interface or within higher elevation terrain. Tree cover cold spots were most often in areas of concentrated development and along traffic corridors known for high levels of particulate matter and other air pollutants that could be reduced by trees. Given small increases in exposure to particulate matter are associated with significant increases in death rates from viruses, and that climate change and associated heat waves are forecast to exacerbate health risks to air pollution, we need to improve global urban tree cover. These map products can be used to expand tree cover that strategically contributes to pollutant abatement, human well-being, and sustainable cities.

The International Energy Agency (2019) states 40% of CO2 emissions in cities are linked to the buildings stock, in particular to heating and cooling systems, material types and users’ performance. According to Green New Deal, the energy transition of buildings is becoming a priority. This is via investments with low environmental impacts through renewable energy sources. The paper describes an integrated economic-energy-environmental framework (IE3F), i.e., an economic evaluation protocol for new constructions and/or existing renewal projects aimed at supporting the choice phase between alternative technological solutions based on biocompatible materials. The IE3F borrows the logical-operative flow of the life cycle assessment multi-criteria approach. The value aspects translated into monetary terms that characterize the project life cycle are taken into account. The protocol was tested on an emergency project in Italy, namely in Messina City. The results obtained provide evidence of the versatile use of IE3F and its practical utility to guide economic convenience judgements on building investments and choice problems between alternatives in sustainable perspective. The research deepening will be about keeping track of multiple performance levels of the construction, not only the energy performance, and attempting to estimate the corresponding economic value in terms of increase/decrease of construction cost value.

The technological components regarding building cladding are designed for ensuring thermo-hygrometric comfort conditions within habitable spaces and realising smart buildings. Often the solutions adopted are identified referring only to the characteristics of mechanical and energy materials without considering the ecological−environmental properties in an urban context. Thus, it is appropriate to choose technological components not only according to material type, but also ecological aspects pursued through presence and/or structured integration of natural elements. The technical-design forms based on “building−nature” integration allows, on one hand, the sustainable soil use with multiple benefits (ecosystem services) that natural systems produce, on the other hand, the identification of technological solutions sized referring environmental quality levels achieved through appropriate natural species use. In this way, it can be obtained lower buildings investment and maintenance costs, and greater energetic−environmental benefits. So, it is proposed an evaluation protocol for settlement transformation interventions structured considering environmental effects obtained with Nature-Based Solutions (NBSs) into the project. According to ecological−environmental quality level achieved with NBSs, the technological component is sized according to preliminary design parameters (noise reduction and solar irradiation degree) obtained through NBSs. The total performance level of technological solutions is expressed using Economic−Environmental Indicators. The protocol is tested on social housing case in Anagnina district of Rome (Italy).