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A source apportionment scheme based on gas and aerosol phase reactive tracers has been implemented in the chemical-transport model FARM, to efficiently estimate contributions of different sources to ambient concentrations. The on-line scheme deals with all the main processes that the chemical species undergo in the model, to enhance consistency with the calculation of bulk concentrations. The fate of precursors through gas-phase chemical reactions is followed by an efficient solver that determines their incremental reactivity, while the contributions to the secondary particulate species from their gaseous precursors is determined by assuming the thermodynamic equilibrium between the two phases. The paper details the new employed methodologies and illustrates the application of the apportionment scheme (based on 6 source sectors) to PM10 and O3, simulated on three domains of different dimensions in Italy, all sharing the same horizontal resolution and a common region (Lombardy). Spatial patterns of results show, on average, a relevant contribution of heating on PM10 concentration in January, with local hotspots dominated by road traffic. Contributions appear consistent in the three simulated domains, apart from the boundary conditions, influenced by the dimension of the domain. Hourly series of contributions to O3 concentrations in July at three selected sites show the dominance of boundary conditions, underlining the large scale of O3 formation. Finally, for PM10 components, the resulting sectorial contributions are compared with the impacts computed via the brute force method, showing that results are similar for elemental carbon and sulfate, while they are different for nitrate and ammonium, due to a different allocation of contributions and impacts between the methods. Each approach responds in principle to a different purpose, and their combined use provides possibly a wide set of information useful for addressing the different air quality management needs. [ABSTRACT FROM AUTHOR]

The indoor climate of non-climatized churches is usually subject to cyclical fluctuations of temperature and relative humidity induced by external climate conditions which might be dampened by the high thermal capacity of their envelope. However, several phenomena affect their indoor climate (e.g., internal gains due to people and artificial lighting, air infiltration, etc.), which lead to environmental variations that might jeopardize the artworks contained within. In particular, one of the most influential parameters that may affect non-climatized churches is the massive and intermittent presence of people who constantly visit their spaces. In such regard, long-term monitoring allows the collection of environmental data with different building operation conditions and visitor fluxes. This paper analyses the indoor climate of the Milan Cathedral (Duomo di Milano) in Italy for three continuous years (including the lockdown period that occurred in 2020 caused by the COVID-19 pandemic), with a focus on visitors' effects on the indoor environment and the conservation of the main artworks contained within. The results of the analysis have shown that spaces with huge volume are most influenced by the opening of the doors rather than the hygrothermal contribution of the intermittent presence of massive crowds. Moreover, the absence of visitors for a prolonged period correlates with an improvement in the indoor conservation conditions for artworks, especially those made of hygroscopic materials, due to the reduction in short, rapid climate fluctuations. [ABSTRACT FROM AUTHOR]

The green transformation of the built environment is aimed at improving sustainability and can be supported by digitalization, which has become a significant tool to support the supply, integration, and management of information throughout the construction life cycle. In addition, climate change highly affects human comfort in the built environment and different strategies should be evaluated for adapting cities. This paper developed a digital workflow by integrating existing tools (i.e., Grasshopper, Ladybug, Honeybee, and Dragonfly) to evaluate how different green infrastructure strategies affected the thermal comfort by reducing the UTCI. The workflow was applied to a typical historical urban context (Catania, South of Italy), consisting of a square surrounded by three-floor buildings. Three basic scenarios were created that depended on the pavement material used in the built environment: a black stone pavement (reference material from Mount Etna), a permeable pavement, and grass. These three scenarios were combined with different green infrastructure strategies: tree pattern on the square, green walls and green roofs on the surrounding buildings, and the integrations of all these above-mentioned strategies. The results demonstrated that the integration of different green strategies (a grass square instead of pavement, with trees, and green walls and green roofs) increased the thermal comfort by reducing the UTCI by more than 8 °C compared to the existing urban context (black stone pavement and building envelope). However, this temperature reduction was highly affected by the location of the human body into the urban context and by the evaporation rates from vegetation. The workflow developed will be useful for designers to evaluate the effectiveness of different green strategies during the early-design stage in mitigating and adapting cities to climate change. [ABSTRACT FROM AUTHOR]

The interest in radiation protection in industrial sectors involving Naturally Occurring Radioactive Materials (NORM) is increasingly growing. This is due also to the recent implementation of the European Council Directive 59/2013/Euratom which in Italy and in the other European Union Member States extends the field of application to industrial sectors never involved before. This paper reports main results of a research project on radiation protection in industries involving NORM carried out in Italy aimed to provide useful tools for stakeholders to comply new legal obligations. The project activities were mainly focused on different aspects relevant to the NORM involving industries, accounting for the positive list reported in the Italian law. Firstly, the inventory of the industries currently operating in Italy in order to identify the industrial sectors with an important radiological impact on population and workers was updated. Based on this information, a general methodology was elaborated taking into account a graded approach. The first phase consists in the identification and characterization of the most critical exposure scenarios and of the radiological content of NORMs involved in the different phases of the industrial processes. In the second phase calculation methods were developed for dose estimation for workers and members of public. These tools require the use of existing and well tested calculation codes, and the development of a dedicated user-friendly software. [ABSTRACT FROM AUTHOR]

This paper aims to present simple regressive equations to estimate the parameters of the three-parameter depth–duration–frequency (DDF) curve (3p-DDF), which accurately expresses, for a preassigned return period, the relationship between the rainfall depth and the rainfall duration over large duration ranges, from below 1 h (i.e., tens of minutes) to above 1 h (up to 24 h). These equations are developed to relate their parameters to those of the two-parameter DDF curve (2p-DDF), which can be estimated more easily being based on more readily available data related to rainfall durations above 1 h. In the applications, the regressive equations are first calibrated using recent pluviographic data in northern Italy, Germany, and Sweden. Two validation steps are then carried out to test the equations in terms of estimated rainfall depths using the same data as those used in the calibration step and data of stations from other geographic areas, i.e., Sicily in southern Italy, and from the past century, respectively. The results obtained prove this methodology capable of providing reliable estimation of short-duration rainfalls with various return periods in the absence of measurements with fine temporal resolution. [ABSTRACT FROM AUTHOR]

Climate change has a strong impact on inland water bodies such as lakes. This means that the increase in lake temperature recorded in recent decades-in Europe as well-can change the evaporation regime of the lakes. This, together with the variation of the water cycle, in particular precipitation, implies that the water mass balance of lakes may vary due to climate change. Water mass balance modeling is therefore of paramount importance to monitor lakes in the context of global warming. Although many studies have focused on such a modeling, there is no shared approach that can be used for any lake across the globe, irrespective of the size. This becomes even more problematic for shallow and small lakes, for which few studies exist. For this reason, in this paper the use of reanalysis data, in particular ERA5-Land provided by the European Centre for Medium-Range Weather Forecasts (ECMWF), is proposed for the mass balance modeling. In fact, ERA5-Land has a global coverage and it is the only data source comprising a specific model for lakes, the Fresh-water Lake model (FLake). The chosen case study is the Trasimeno lake, a small and shallow lake located in Central Italy. The use of the reanalysis was preceded by data validation by considering both ground-based and satellite observations. The results show that there is a good agreement between the observed monthly variation of the lake level, Δ H , and the corresponding values of the water storage, δ , computed by means of the ERA5-Land data (Pearson coefficient larger than 70%). Discrepancies between observations and the ERA5-Land data happen in periods characterized in Europe by an extreme climate anomaly. This promising result encourages the use of ERA5-Land for other lakes. [ABSTRACT FROM AUTHOR]

Particular Matter (PM) data are the most used for the assessment of air quality, but it is also useful to monitor VOC and CO. The health impact of PM increases with decreasing aerodynamic dimensions, therefore most of the monitoring is aimed at PM10 (fraction of PM with aerodynamic dimensions smaller than 10 µm) and PM2.5 (fraction with aerodynamic dimensions lower than 2.5 µm). Generally, anthropogenic emissions contribute mainly to PM2.5 levels, whereas natural sources can largely affect PM10 concentrations. PM2.5/PM10 ratio can be used as a proxy of the origin (anthropogenic vs natural) of the PM, providing a useful indication about the main sources of PM that characterizes a specific geographical or urban setting. This paper presents the results of the analysis of continuous measurements of PM10 and PM2.5 concentrations at eight stations of the regional air quality monitoring network in Abruzzo (Central Italy), in the period 2017–2018. The application of models based on machine learning technique shows that PM2.5/PM10 ratio can be used to classify PM emissions and to know the nature of the emission source (natural and anthropogenic), under determinate conditions, and properly taking into account the meteorological parameters. [ABSTRACT FROM AUTHOR]

Humans are mostly exposed to ionizing radiation through radon and its decay products. The results of indoor radon measurements in 39 kindergartens and primary schools in the Campania region of southern Italy are presented in this paper. The survey was carried out with CR-39 solid-state nuclear track detectors (SSNTDs). Radon concentrations were measured and ranged from 11 to 1416 Bq/m3, with a geometric mean of 77 Bq/m3 and a geometric standard deviation of 2. The findings revealed that 70% of the measures were below the WHO recommended level of 100 Bq/m3 and that 97 percent of the measurements were below the 300 Bq/m3 level set by Italian law. [ABSTRACT FROM AUTHOR]

Odor pollution is nowadays recognized as a serious environmental concern. Italy still lacks a national regulation about odors, but several regions issued specific guidelines and regulations regarding odor emissions management, which combine olfactometric measurements with dispersion modeling for assessing odor impacts and verifying compliance with acceptability criteria. However, in cases of variable or diffuse sources, this approach is sometimes hardly applicable, because odor emission rates can hardly be estimated. In such cases, electronic noses, or more generally, Instrumental Odor Monitoring Systems (IOMS), represent a suitable solution for direct odor measurement. Accordingly, IOMS are explicitly mentioned in the most recent regional regulations as advanced tools for odor impact assessment. In Italy, data from instrumental odor monitoring have started to have regulatory value; thus the need arises to have specific quality programs to ensure and verify the reliability of IOMS outcomes. This paper describes the monitoring by a commercial electronic nose (EOS507F) of odors from an area dedicated to tire storage, a diffuse source with variable emissions over time, for which dispersion modeling is not applicable. The paper proposes also a protocol for IOMS performance testing in the field, to provide experimental data to support technical groups working on standardization both on the national and European level. [ABSTRACT FROM AUTHOR]

Evaluation of effects of climate change on climate variable extremes is a key topic in civil and structural engineering, strongly affecting adaptation strategy for resilience. Appropriate procedures to assess the evolution over time of climatic actions are needed to deal with the inherent uncertainty of climate projections, also in view of providing more sound and robust predictions at the local scale. In this paper, an ad hoc weather generator is presented that is able to provide a quantification of climate model inherent uncertainties. Similar to other weather generators, the proposed algorithm allows the virtualization of the climatic data projection process, overcoming the usual limitations due to the restricted number of available climate model runs, requiring huge computational time. However, differently from other weather generation procedures, this new tool directly samples from the output of Regional Climate Models (RCMs), avoiding the introduction of additional hypotheses about the stochastic properties of the distributions of climate variables. Analyzing the ensemble of so-generated series, future changes of climatic actions can be assessed, and the associated uncertainties duly estimated, as a function of considered greenhouse gases emission scenarios. The efficiency of the proposed weather generator is discussed evaluating performance metrics and referring to a relevant case study: the evaluation of extremes of minimum and maximum temperature, precipitation, and ground snow load in a central Eastern region of Italy, which is part of the Mediterranean climatic zone. Starting from the model ensemble of six RCMs, factors of change uncertainty maps for the investigated region are derived concerning extreme daily temperatures, daily precipitation, and ground snow loads, underlying the potentialities of the proposed approach. [ABSTRACT FROM AUTHOR]

Heavy and localized summer events are very hard to predict and, at the same time, potentially dangerous for people and properties. This paper focuses on an event occurred on 15 July 2020 in Palermo, the largest city of Sicily, causing about 120 mm of rainfall in 3 h. The aim is to investigate the event predictability and a potential way to improve the precipitation forecast. To reach this aim, lightning (LDA) and radar reflectivity data assimilation (RDA) was applied. LDA was able to trigger deep convection over Palermo, with high precision, whereas the RDA had a key role in the prediction of the amount of rainfall. The simultaneous assimilation of both data sources gave the best results. An alert for a moderate–intense forecast could have been issued one hour and a half before the storm developed over the city, even if predicting only half of the total rainfall. A satisfactory prediction of the amount of rainfall could have been issued at 14:30 UTC, when precipitation was already affecting the city. Although the study is centered on a single event, it highlights the need for rapidly updated forecast cycles with data assimilation at the local scale, for a better prediction of similar events. [ABSTRACT FROM AUTHOR]

In this paper we analyse temporal variations of the phase of a very low frequency (VLF) signal, used for the lower ionosphere monitoring, in periods around four earthquakes (EQs) with magnitude greater than 4. We provide two analyses in time and frequency domains. First, we analyse time evolution of the phase noise. And second, we examine variations of the frequency spectrum using Fast Fourier Transform (FFT) in order to detect hydrodynamic wave excitations and attenuations. This study follows a previous investigation which indicated the noise amplitude reduction, and excitations and attenuations of the hydrodynamic waves less than one hour before the considered EQ events as a new potential ionospheric precursors of earthquakes. We analyse the phase of the ICV VLF transmitter signal emitted in Italy recorded in Serbia in time periods around four earthquakes occurred on 3, 4 and 9 November 2010 which are the most intensive earthquakes analysed in the previous study. The obtained results indicate very similar changes in the noise of phase and amplitude, and show an agreement in recorded acoustic wave excitations. However, properties in the obtained wave attenuation characteristics are different for these two signal parameters. [ABSTRACT FROM AUTHOR]

This work presents the on-line coupled meteorology–chemistry transport model BOLCHEM, based on the hydrostatic meteorological BOLAM model, the gas chemistry module SAPRC90, and the aerosol dynamic module AERO3. It includes parameterizations to describe natural source emissions, dry and wet removal processes, as well as the transport and dispersion of air pollutants. The equations for different processes are solved on the same grid during the same integration step, by means of a time-split scheme. This paper describes the model and its performance at horizontal resolution of 0.2 ∘ × 0.2 ∘ over Europe and 0.1 ∘ × 0.1 ∘ in a nested configuration over Italy, for one year run (December 2009–November 2010). The model has been evaluated against the AIRBASE data of the European Environmental Agency. The basic statistics for higher resolution simulations of O3, NO2 and particulate matter concentrations (PM 2.5 and PM10) have been compared with those from Copernicus Atmosphere Monitoring Service (CAMS) ensemble median. In summer, for O3 we found a correlation coefficient R of 0.72 and mean bias of 2.15 over European domain and a correlation coefficient R of 0.67 and mean bias of 2.36 over Italian domain. PM10 and PM 2.5 are better reproduced in the winter, the latter with a correlation coefficient R of 0.66 and the mean bias MB of 0.35 over Italian domain. [ABSTRACT FROM AUTHOR]

Urban air contains benzene and polycyclic aromatic hydrocarbons (PAHs) which have carcinogenic properties. The objective of this paper is to study the correlation of exposure biomarkers with biomarkers of nucleic acid oxidation also considering smoking. In 322 subjects, seven urinary dose biomarkers were analyzed for benzene, pyrene, nitropyrene, benzo[a]pyrene, and naphthalene exposure, and four effect biomarkers for nucleic acid and protein oxidative stress. Chemometrics was applied in order to investigate the existence of a synergistic effect for the exposure to the mixture and the contribution of active smoking. There is a significant difference between nicotine, benzene and PAH exposure biomarker concentrations of smokers and non-smokers, but the difference is not statistically significant for oxidative stress biomarkers. The PAH biomarkers are those which best correlate with all the oxidative stress biomarkers. Results suggest that 8-Oxo-7,8-dihydroguanine and protein nitro-oxidation 3-nitrotyrosine are the most sensitive biomarkers for the exposure to the urban pollutant mixtures and that a synergic effect of the mixtures exists. All the oxidative stress biomarkers studied drive the increase in the oxidative stress biomarkers in the subjects having higher exposures. Chemometrics proved to be a powerful method for the interpretation of human biomonitoring data. [ABSTRACT FROM AUTHOR]

This paper is devoted to the assessment of urban greening effects on two important ecosystem services, i.e., air quality and CO2 storage, including the corresponding economic impacts in a real urban area, i.e., a district located in the Mediterranean city of Lecce (southern Italy). Two tools were employed, i-Tree Canopy and the computational fluid dynamics (CFD) microclimate model ENVI-met. i-Tree Canopy allowed fully determining the land-cover percentage on the basis of different ground cover classes and obtaining an estimate of annual values of CO2 storage, air pollutant removal, and economic benefits in the presence of urban greening. The estimate in i-Tree Canopy considered only the amount of greening; therefore, air pollutant removal estimates were only potential. As the vegetation was located in street canyons, its interaction with local meteorology and urban geometry strictly affected the dispersion of nitrogen oxides (NOx) (taken here as an example) as obtained from ENVI-met simulations. In ENVI-met, both deposition/absorption and aerodynamic effects were considered, and local increases in concentration were found in the district. The analysis of results obtained from different tools (one complex (CFD model) and the other simple (i-Tree model)) showed the error associated with the simple model in the computation of impacts if the interaction among the vegetation characteristics, the meteorological conditions, and the urban geometry was neglected; however, it also uncovers a novel approach for comprehensively characterizing a given area in terms of its vegetation cover, CO2 storage, and economic benefits, as well as local effects on air quality. This study is set in a broader context aimed at assessing the air quality in urban canopies of Mediterranean areas characterized by the presence of narrow street canyons where pollutants can accumulate due to ineffective air exchange with the above atmosphere. [ABSTRACT FROM AUTHOR]

Italy is characterized by a very variable configuration in terms of altitude, proximity to the sea, latitude and the presence of industrial plants. This paper summarizes the chemical characterization of PM10 obtained from 38 sampling campaigns carried out in 16 sites in Italy during the years 2008–2018. Chemical determinations include all macro-components (six macro-elements, eight ions, elemental carbon and organic carbon). The sum of the individual components agrees well with the PM10 mass. The chemical composition of the atmospheric aerosol clearly reflects the variety in the Italian territory and the pronounced seasonal variations in the meteoclimatic conditions that characterize the country. Macro-sources reconstruction allowed us to identify and evaluate the strength of the main PM10 sources in different areas. On 10 sampling sites, the soluble and insoluble fractions of 23 minor and trace elements were also determined. Principal Component Analysis was applied to these data to highlight the relationship between the elemental composition of PM10 and the characteristics of the sampling sites. [ABSTRACT FROM AUTHOR]

In this paper, an operational forecasting and daily assessment system of air quality is presented. This new system is thought of as a Copernicus-CAMS downstream national service, able to develop and implement a service for air quality forecasting and monitoring in the Italian domain, running every day on the National territory. The system is being developed on behalf of a cooperation between Agenzia Spaziale Italiana (ASI) and Sistema Nazionale Protezione Ambiente (SNPA). SNPA is the network between Istituto Superiore per la Protezione e Ricerca Ambientale (ISPRA) and the Regional Environmental Agencies (ARPAs). The objective of the cooperation is to provide full operation service in terms of continuity, sustainability, and availability of the air quality forecast and evaluation services at the national level. The system forecasts and analyzes air quality throughout Italy, with a focus on Italian regions, for the principal pollutants: Particulate matter with diameter smaller than 10 μm (PM10), ozone (O3), and nitrogen dioxide (NO2). It includes a Chemical Transport Model (CTM) nested with the Copernicus Atmosphere Monitoring Service (CAMS) global model and data from the air quality monitoring stations in Italy. The system, under public control and based on open software, is now under testing. To date, it is able to deliver free open data, which is available to environmental agencies and citizens. The data are delivered both as maps and graphs, and as numerical data, useful for providing boundary conditions to local–high resolution-air quality models or for developing customized services. In this work, a downscaling application to a regional nested domain highlights how the new air quality forecasting system gains better results than the Copernicus-CAMS system. [ABSTRACT FROM AUTHOR]

In the context of the architectures for health, it is an utmost priority to operate a regular and continuous updating of quality, efficacy, and efficiency's processes. In fact, health promotion and prevention take place through a proper management and design of healing spaces, in particular with regard to the most sensitive users. In recent decades, there has been increasing attention to indoor air quality in healthcare facilities. Nowadays, this issue must involve the implementation of a series of appropriate interventions, with a global approach of prevention and reduction of risk factors on users' health, which allows, in addition to a correct management of hospital settings, the realization of concrete actions. To date, in Italy, despite the indoor air being taken in consideration in numerous activities and studies aimed at understanding both building hygiene and environmental aspects, the greatest difficulty is strongly related to the absence of an integrated national policy. The scope of the paper is to underline the relevance of indoor air quality in hospital settings, highlighting the need of procedures, protocols, and tools for strengthening and improving interventions for health prevention, protection, and promotion of users. [ABSTRACT FROM AUTHOR]

This work is an overview of the oxidative potential (OP) values up to date measured in Italy, with the aim to provide a picture of the spatial and seasonal variability of OP in the various geographical areas across Italy. The summarized works used the common acellular assays-based dithiothreitol (OPDTT), ascorbic acid (OPAA), glutathione (OPGSH), and 2′,7′-dichlorodfluorescein (OPDCFH) assays. The paper describes the association of OP responses with PM chemical composition, the sensitivity of various acellular OP assays to PM components and emission sources, and PM size distribution of the measured OP values. Our synthesis indicates that crustal and transition metals (e.g., Fe, Ni, Cu, Cr, Mn, Zn, and V), secondary ions and carbonaceous components (elemental carbon, EC, organic carbon, OC and water soluble carbon, WSOC) show significant correlations with OP across different urban and rural areas and size ranges. These chemical species are mainly associated with various PM sources, including residual/fuel oil combustion, traffic emissions, and secondary organic aerosol formation. Although the OP assays are sensitive to the same redox-active species, they differ in the association with PM chemical components. The DDT assay is mainly sensitive to the organic compounds that are mostly accumulated in the fine PM fraction, i.e., tracers of burning sources, and redox active organics associated with other markers of photochemical aging. In contrast, OPAA and OPGSH were mostly responsive to metals, mainly those related to non-exhaust traffic emissions (Cu, Zn, Cr, Fe, Ni, Mn, Sn, Cd, Pb), that are mainly accumulated in the coarse PM. Among the investigated sites, our synthesis shows larger OP values in Trentino region and the Po Valley, that may be explained by the high density of anthropogenic sources, and the orographic and meteorological characteristics, that favor the pollutants accumulation and aerosol photo-oxidative aging. [ABSTRACT FROM AUTHOR]

Due to some harmful effects on humans and the environment, particulate matter (PM) has recently become among the most studied atmospheric pollutants. Given the growing sensitivity to the problem and, since production and accumulation phenomena involving both primary and secondary P M 10 fractions are complex and non-linear, environmental authorities need tools to assess their plans designed to improve the air quality as requested from environmental laws. Multi-criteria decision analysis (MCDA) can be applied to support decision makers, by processing quantitative opinions provided by pools of experts, especially when different views on social aspects should be considered. The results obtained through this approach, however, can be highly dependent on the subjectivity of experts. To partially overcome these challenges, this paper suggests a two-step methodology in which an MCDA is fed with the solution of a multi-objective analysis (MOA). The methodology has been applied to a test case in northern Italy and the results show that this approach is a viable solution for the inclusion of subjective criteria in decision making, while reducing the impact of uncertain expert opinions for data that can be computed through the MOA. [ABSTRACT FROM AUTHOR]