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The main aim of this study was to define a procedure useful to evaluate the potential environmental, social and economic benefits contained in paper and cardboard (or other recyclables), which are wasted in the unsorted fraction of municipal solid waste (MSW). To give a practical example, the procedure was applied to the 550 municipalities of the Campania region, in Southern Italy, but the developed procedure is applicable in any context in an 'urban mining' perspective. The procedure consists of five phases and uses two methodologies: one for the estimation of the composition analysis of the unsorted residual waste and another for the calculation of sustainability indicators able to measure the benefits wasted in the unsorted residual MSW. Six indicators were defined: two for the environment (carbon footprint and ecological footprint), two for the society (health footprint and occupational benefits) and two for the economy (economic profit and economic saving). The first methodology was developed by the regional environmental protection agency to update the MSW regional management plan. The second methodology is based on the use of the Life Cycle Assessment (LCA) through which it was possible to calculate the reference parameters useful for the calculation of the impacts (i.e., loss of benefits) for recycling, mechanical and biological treatment (MBT), incineration and landfilling of paper and cardboard contained in the unsorted residual waste. The obtained results confirmed the presence of such an enormous deposit of recyclable materials contained in the unsorted residual waste, which is a potential source, but not exploited, of environmental, social and economic benefits. For instance, the paper and cardboard 'urban mine' of Naples was greater than 16 million of euro (economic profit + economic saving), with a potential saving of around 11.4 million of kgCO 2 eq. (carbon footprint), 207 million of m2 (ecological footprint), 44 Disability Adjusted Life Years (health footprint), with a creation of 30 job positions in the waste management sector (occupational benefits). [Display omitted] • A procedure consisting of five phases was developed using two methodologies. • One methodology estimates the composition analysis of the unsorted residual waste. • Another methodology used a Life Cycle Assessment (LCA) approach. • Two indicators for the environment, two for the society and two for the economy. • The paper and cardboard 'urban mine' of Naples was greater than 16 million of euro. [ABSTRACT FROM AUTHOR]

• There are few examples of field survey data being utilized to test the effectiveness of UN SDG indicator 15.3.1. • The annual mean of NDVI shows some weakness in detecting land productivity dynamics. • Remote sensing coupled with a cloud-based computing platform may improve knowledge of the land productivity index. • The trend of maximum NDVI values appears more suitable for the assessing of land degradation processes. • Analysis of finer resolution satellite datasets is the best solution for regional/local contexts. Land degradation is a critical issue at a global level and its progressive increasing greatly reduces soil ecosystem services. In this context, the 2030 Agenda for Sustainable Development, adopted by all United Nations Member States in 2015, defined the Sustainable Development Goals (SDGs) and indicated some targets of particular interest for a territory to be integrated into short- and medium-term national programs. Target 15.3, which aims to end desertification and restore degraded lands, is currently monitored by indicator 15.3.1, measured as the combination of three sub-indicators (trends in land cover change, land productivity and carbon stocks) as suggested by the United Nations Convention to Combat Desertification (UNCCD), the custodian agency for the SDG indicator. In our opinion, this assessment shows some weakness that are generally caused by a lack of information from direct field observations. The greatest limitation regards land productivity dynamics linked to the NDVI trajectory adopted by the UNCCD methodological approach. For this reason, the paper proposes an alternative approach that consists of using annual maximum NDVI value assessments instead of annual mean values for trajectory calculation. To come to these conclusions, the study addresses a reliability assessment by using remote sensing techniques via the Google Earth Engine (GEE) and analysing the NDVI evolution over time at 450 locations spread around the Campania region (southern Italy). To this end, a customised Graphical User Interface (GUI) was built on the GEE platform and a Google Earth time slider tool was applied to visualize land cover changes which occurred at each location over a period of 18 years (2001–2018). The survey was carried out on MODIS and Landsat 7 collections and showed that the new approach had a better performance than the UNCCD approach (90 % vs 62 % of successful reliability tests, up to 96 % considering results from Landsat images). The application of maximum NDVI values to assess productivity dynamics spatially shows, with regard to UNCCD data, more than double the percentages of degraded and stable lands and a drastic reduction in improved areas within the Campania region. Overall, this innovative approach appears to agree more closely with ground truth and the use of finer resolution data is more suitable for investigating land degradation processes within a regional context. [ABSTRACT FROM AUTHOR]

Nowadays, Artificial intelligence (AI), combined with the digitalization of healthcare, can lead to substantial improvements in Patient Care, Disease Management, Hospital Administration, and supply chain effectiveness. Among predictive analytics tools, time series forecasting represents a central task to support healthcare management in terms of bookings and medical services predictions. In this context, the development of flexible frameworks to provide robust and reliable predictions became a central point in this healthcare innovation process. This paper presents and discusses a multi-source time series fusion and forecasting framework relying on Deep Learning. By combining weather, air-quality and medical bookings time series through a feature compression stage which preserves temporal patterns, the prediction is provided through a flexible ensemble technique based on machine learning models and a hybrid neural network. The proposed system is able to predict the number of bookings related to a specific medical examination for a 7-days horizon period. To assess the proposed approach's effectiveness, we rely on time series extracted from a real dataset of administrative e-health records provided by the Campania Region health department, in Italy. • We propose a multi-source time-series fusion methodology relying on Deep Learning. • We design a robust framework for daily 7-days-horizon predictions. • We assess the proposed approach on a real medical bookings dataset. [ABSTRACT FROM AUTHOR]

The paper focuses on the seismic response of earth dams close to active faults. The engineering implications of such an issue may be crucial since many existing dams, which have been in operation for several years, are located nearby or even on seismogenic faults. Owing to their size, large earth dams could dramatically be compromised by near-source ground motion. The spatial variability of the incoming seismic wave could promote differential settlements in the dam body and consequently fractures in the watertightness elements with an overall decrease of dam safety. The paper refers to the iconic case of Conza Dam in Italy. During its construction, it was seriously damaged by the catastrophic 1980 Irpinia earthquake (M = 6.9), whose epicenter was very close to the dam site. To model the seismic wave propagation from the causative fault to the dam site, a physics-based approach has been adopted by implementing the domain reduction method to simulate the whole boundary value problem. Two models were hence considered: a regional model, containing the source and the propagation medium of the Campania region basin, and a site model containing the upper foundation soils and the dam body. The paper compares the different response of the dam in the hypothesis of contemplating or disregarding near-source effects. Finally, the dam performance to seismic scenarios resembling the source mechanism of the 1980 Irpinia earthquake was analysed to ascertain the resilience of the dam to future earthquake scenarios having source characteristics similar to those of the 1980 event. [ABSTRACT FROM AUTHOR]

Abstract: The waste crisis in Campania has inspired a vast amount of studies. Nevertheless, very little research has been done to explain the figures of waste generation and disposal in the region. The analyses carried out so far according to the indicators used by official statistics – i.e. Waste Generated, Waste Generated per capita and Separate Collection – fail to represent this hot spot case. This paper attempts to bridge this gap. Adopting the rationale of a new accounting system, the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM), two waste indicators are proposed to complement the conventional ones: the Metabolic Rate of Waste and the Density of Waste. Then a multi-scale analysis of the Density of Waste Disposed (DWD) tests its suitability to characterise Campania’s waste patterns. The data cover the period from 1999 to 2007. The results show that the DWD complements available indicators and further helps to explain the biophysical pressure and ecological unsustainability of the waste management in the region. The multi-scale analysis shows that regional data hide a relevant territorial diversity, emergent in the provincial analysis and even more so in the municipal one. These results have implications for governance and for the debate about mono-scale versus multi-scale solutions to waste management problems. Finally, the analysis allows some analytical generalisations on the suitability of the DWD to detect situations of potential waste crisis in other study-contexts. [Copyright &y& Elsevier]

Abstract: The present work is focused on investigating the potential role of capillary barriers on the stability of layered soil deposits laying upon high permeability steep slopes. In presence of capillary barrier effects, often possible on a soil stratigraphy characterized by contrasting hydraulic properties (pyroclastics deposit over pumices, silt upon fractured bedrock, silt over sand) failure might originate in less permeable layers, where unsaturated conditions might provide a crucial contribution to stability. Basic ideas and considerations have been drawn from a peculiar case study, the catastrophic landslide occurred in Campania, Southern Italy, on May 1998, which is discussed in this paper from a different perspective. The areal extent of failures’ distribution, their dense concentration at the steeper and higher slopes, the extremely high number of initial failures occurred within a relatively short time span suggest that the intimate cause of the event is related at some extent to the soil state characteristic parameters rather than positive pore pressure pulses from water circulation in coarser layers or groundwater level rising from bedrock and springs. A widespread loss of soil strength related to saturation can contribute to explain such phenomena. Capillary barrier effects favor accumulation and lateral distribution of percolating rainfall and possibly divert flowlines downslope, thus leading to localized increases in water content and loss of strength. Diversion of percolating waters facilitates lateral redistribution of soil moisture along the slope with possible further localized saturation, because more permeable layers may act temporarily as barriers and not as drains, as one could expect. Numerical 2-D infiltration models with parameters calibrated versus laboratory data show a relevant influence of capillary barrier effects on infiltration in layered slopes with vertically stratified variations of hydraulic properties and point out significant localized moisture accumulation with possible consequences on slope stability. Landslide initiation phenomena in layered covers might thus be conditioned by the increase in saturation within the least permeable soil layers due to capillary barrier phenomena. [Copyright &y& Elsevier]

Abstract: A complexity indicator based on the diversity of energy and resource uses by a system is proposed in this paper. The indicator is an emergy-based index of complexity derived from a modified Shannon information formula that provides a quantitative assessment of the diversity of sources. The emergy approach assigns to each driving input a weight that derives from the environmental work performed by nature in order to generate such resource. This quality assessment goes far beyond the simple accounting of mass and energy of input flows, but takes into proper account their interlinkage with the biosphere dynamics. The rationale of the proposed indicator is that complexity cannot be assessed by simply counting individuals, species and processes, but requires that focus is placed on several aspects of resource flows, namely their amount, frequency, and quality. Different mixes of emergy input flows originate different levels of growth and complexity. Systems that only rely on a small set of sources out of the large number potentially available possess a built-in fragility, that may determine their collapse in times of shrinking or changing resource basis. For validation purpose, the proposed indicator was applied to the performance of selected national economies (Nicaragua, Latvia, Denmark and Italy) in selected years and of the urban system of Roma (Italy) over a forty-year (1962–2002) historical series. Results point out an increasing complexity of the urban system of Rome over time, while a lower complexity was calculated for the investigated national systems as a whole (likely effect of nationwide averaging), with Italy ranking highest and Latvia lowest. The same assessment performed for the Italian agricultural system over a twenty-year time series (1985–2006) shows a decline of the emergy-adjusted Shannon indicator from about 75% down to 62%, while the decline was from 73% to 63% for the agriculture of Campania region (southern Italy). [Copyright &y& Elsevier]

Abstract: Campania Region (Italy), one of the most densely populated areas in Europe, is probably the one with the highest risk of landslide. A large part of the region is covered by unsaturated cohesionless pyroclastic deposits subjected to rainfall-induced landslides. According to experience, these can display different features and magnitude. The most catastrophic landslides are liquefied debris flows which periodically occur on steep slopes, causing death and destruction in areas located downslope. Therefore, zoning of those areas which can be the source of liquefied debris flow is necessary. The paper reports some useful elements for zoning based on infinite slope analysis, accounting for the results of recent research on the mechanics of rainfall-induced landslides in pyroclastic soils. [Copyright &y& Elsevier]

Abstract: In the Northern Campanian coastal zone, over 150 km long, three geomorphic units are recognised: (1) sandy beaches that are well developed in the northern area, where a prominent river mouth (Volturno River) is also present; (2) steep and rocky shores, often with gravelly beaches or debris cones at their base, are mainly diffuse in the southern area (Sorrentine Peninsula); and, lastly, (3) “techno coast”, shorelines stabilized with revetments and seawalls as well as former natural environments no longer clearly operational because of urbanization, as is visible in Naples and in the Vesuvian coast. Six primary hazards are considered in this investigation: shoreline erosion, riverine flooding, storms, landslides, seismicity and volcanism, and man-made structures. These hazards do not have a uniform distribution along this coast in terms of their frequency and intensity; moreover both their interaction and the intensive action of humans, often uncontrolled, makes it difficult to assess the overall coastal hazard. In this paper a semi-quantitative method with which to quantify, rank and map the distribution of hazard is applied along this particular stretch of coast. In such a stretch, previously characterized in terms of types and processes and compartmentalized into geomorphic units, the effect of individual hazards, based on their magnitude and recurrence, is evaluated. Dominant and subordinate hazards for each geomorphic unit are identified, assigning a rank that is also a weighting. Comparison of each weighting through an interaction matrix permits the calculation of a resultant, which is the overall hazard assessment and which can be expressed cartographically. The results obtained for a coastal zone with one of the highest pressures from urbanization in the world, help us to recognise that this approach could become a useful tool to aid decision-making regarding coastal land-use and planning. [Copyright &y& Elsevier]

According to the Italian national Energy strategy elaborated in 2017, the biomass sector has one of the most important strategic roles in energy renewables policy. Thus, estimating the potential of this resource is crucial for its energy valorization. Therefore, in this paper, a method to assess the energy potential from residual biomass is presented. The availability of residual biomass and its energy potential are estimated by using statistical and literature data. To account for the variability of the factors taken into account a comprehensive literature review is carried out focusing on the case studies related to Mediterranean areas. Based on the collected data, uncertainty analysis and sensitivity analysis are performed to provide reliable results. As a case study, the energy potential of residual biomass from agro-industry in the Campania region (southern Italy) is considered. The proposed method allows estimating a total of about 14.5 PJ per year of recoverable primary energy potential in the Campania region, which may cover around 14% of its thermal demand. The analysis carried out is intended to be a useful tool for policymakers of Mediterranean regions, to integrate energy recovery from agro-industrial biomass in the regulatory and investment strategies of the energy sector. • A model to estimate energy potential of residual biomasses typical of Mediterranean climate conditions is presented. • As a case study, a southern Italy region is taken into account. • The recoverable bio-energy potential may cover around 16% of the regional thermal demand. • The analysis may be a useful tool for policymakers of Mediterranean regions. [ABSTRACT FROM AUTHOR]

Shallow flowslides, debris flows and debris avalanches are rainfall-induced landslides consisting in the shear failure of few metres of soils (or in some cases even less than a metre), which greatly increase downslope in volume and flow velocity. The southern Italian region of Campania has been historically affected by such events involving pyroclastic soils mainly resting on steep carbonate slopes. This paper deals with the analysis of factors influencing the occurrence of flow-like landslides, adopting the Lattari Mts. in Campania as a case study. The results of two investigation campaigns carried out in the area allowed effective large-scale geological and geotechnical characterization to be set up. Stratigraphic profiles, mean physical properties and typical friction angles at the critical state for each soil layer were investigated. The effect of suction on peak and critical shear strength, whose drop is responsible for soil failure, was analysed. Using detailed information on both the stratigraphic and geotechnical features of the soils involved in past flow-like landslides, typical triggering models were selected, representing locally recurrent geomorphologic conditions at the basin scale. The identified models were adopted for slope stability analyses carried out on four cross-sections of flowslides occurring prior to the event, to back-analyse the triggering conditions. From the evidence on the triggering mechanisms and the results of analyses, the infinite slope approach is not always suitable to model slope stability conditions properly, because the onset of landslides is also affected by local topographic and stratigraphic factors. • Flow-like landslides can be triggered due to local features. • Local topographic irregularities can be represented by roads, tracks, scarps and terraces. • Infinite slope model can be suitable to model only slopes characterized by angles higher than 39–40°. • Local natural and anthropic factors can affect the results of slope stability analysis. • The triggered landslides occurred when the 3-months precedent rainfall exceeded the 40 years average value. [ABSTRACT FROM AUTHOR]