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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]

The population of the Venafro Valley (Southern Italy) faces various type of air pollution problems (industrial facilities, traffic, and biomass combustion). To estimate exposure to various pollution sources, a multi-stage random forest model was used, integrating particulate matter (PM) data with satellite observations, land-use patterns, and meteorological information generating maps of PM2.5 concentration. Four distinct PM2.5 exposure categories were established using the quartile method. To assess the association between PM2.5 and cause-specific mortality and morbidity, a time-dependent and sex-specific Cox multiple regression analysis was conducted, adjusting for age classes. In addition, the hazard ratios were accompanied by a probability measure of the strength of the evidence toward a hypothesis of health risk associated with the exposure under study (1−p value). The whole cohort was exposed to PM2.5 annual levels exceeding the 5 µg/m3 limit recommended by the World Health Organization. Mortality excesses were observed in class 3 for both sexes for cardiac heart diseases. Excesses of cardiovascular diseases were observed for both sexes in class 3 and 4. The study highlights significant signals warranting mitigation actions, which regional authorities are currently considering. [ABSTRACT FROM AUTHOR]

Due to its high short-term global warming potential (GWP) compared to carbon dioxide, methane (CH4) is a considerable agent of climate change. This research is aimed at analyzing data on methane gathered at the GAW (Global Atmosphere Watch) station of Lamezia Terme (Calabria, Southern Italy) spanning seven years of continuous measurements (2016–2022) and integrating the results with key meteorological data. Compared to previous studies on detected methane mole fractions at the same station, daily-to-yearly patterns have become more prominent thanks to the analysis of a much larger dataset. Overall, the yearly increase of methane at the Lamezia Terme station is in general agreement with global measurements by NOAA, though local peaks are present, and an increase linked to COVID-19 is identified. Seasonal changes and trends have proved to be fully cyclic, with the daily cycles being largely driven by local wind circulation patterns and synoptic features. Outbreak events have been statistically evaluated depending on their weekday of occurrence to test possible correlations with anthropogenic activities. A cross analysis between methane peaks and specific wind directions has also proved that local sources may be deemed responsible for the highest mole fractions. [ABSTRACT FROM AUTHOR]

Indoor radon surveying and remediation were implemented in a single-family home affected by high levels of indoor radon in the Celleno municipality (central Italy) with the aim of identifying the contribution of radon sources, evaluating the factors affecting radon entry into the building, and reducing radon risk. Average radon levels were relatively low at the ground floor (286 ± 202 Bq m−3) and first floor (167 ± 84 Bq m−3) in autumn when the temperature was still warm and the windows were open, but increased up to 2776 ± 1768 Bq m−3 and 970 ± 202 Bq m−3 in the first half of December, when the heating system was on and the windows were closed. The inner walls of the pilot room at the ground floor, semi buried on one side, were then treated with a waterproof product (a silane terminated polymer) and the average radon was halved (1475 ± 1092 Bq m−3) in the following month, which was still characterised by winter conditions. Radon entry in the room was identified and sealed with the same product, and a radon accumulation space behind a NE-SW oriented wall was naturally ventilated, reducing radon below the reference level in April with northerly winds conditions. [ABSTRACT FROM AUTHOR]

Air pollution poses a significant threat to human health and ecosystems. Forecasting the concentration of key pollutants like particulate matter can help support air quality planning and prevention measures. Deep learning methods are becoming increasingly popular for predicting air pollution and particulate matter concentration. Architectures like Convolutional Neural Networks can effectively account for the geographical features of the study domain. This work tests a Feed-Forward, a Long Short-Term Memory (LSTM), and a Convolutional Neural Network (CNN) on a polluted geographical domain in northern Italy. The best convolutional architecture was then implemented in two other quite different regions. The results show that the same CNN architecture provides remarkably accurate forecasts in all applications and that a network trained on PM10 data can accurately forecast PM2.5 concentrations up to 10 days ahead. These results suggest that the proposed CNN has high generalization capabilities and can thus be reliably used as a forecasting model for different areas. [ABSTRACT FROM AUTHOR]

The Campus of the Sapienza University of Rome, frequented daily by several thousands of students and workers, collects allergenic airborne pollen from many sources. Here, we report the results of detailed pollen monitoring of 49 pollen types within the University Campus, allowing us to trace the main local and regional sources of airborne pollen throughout the year. The amount of allergenic pollen has been calculated for each daily record to evaluate the risk of exposure for students and workers on Campus in relation to academic activities and to suggest possible mitigation measures. Our results show that the maximum pollen concentrations are recorded from March to May, and the highest floristic richness occurs in April–June. We distinguish massive local pollen producers from pollen of regional origin and local ornamental and invasive taxa. Pollen with extreme allergenicity is dominant from mid-January to mid-March and in May with Cupressaceae/Taxaceae, Corylus and Olea; high allergenicity from late March to late April with Platanus, Ostrya, Ginkgo and Moraceae; and medium allergenicity from late April to the beginning of May with Quercus and Pinus. In August–December, pollen concentration is relatively low. Diversified mitigation actions are suggested in relation to the provenance, allergenicity and emission period of pollen. [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]

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]

The objective of this study is to investigate the impact of the COVID-19 pandemic on the carbon footprint (CF) of two research projects. These projects were initiated prior to the onset of the pandemic and subsequently concluded afterward, serving as the Base Case (BC) for analysis. Furthermore, the study seeks to explore the potential applicability of measures implemented during the period of lockdown for future mitigation of CF. The applied methodology, which adheres to the guidelines provided by the GHG Protocol and the Department for Environment Food & Rural Affairs (DEFRA) emission factors, is utilized to examine the CF of the projects under two different scenarios. The first scenario assumes that the projects were implemented without the pandemic, while the second scenario considers that the projects were conducted entirely during the pandemic. Among the two projects under review, one emphasizes innovation and entails a collaboration between academia and business. This project is supported by a limited number of employees, exclusively from domestic partners. The other project is more oriented toward policy-making and involves a larger group of partners from Greece and Italy. Its main priority is dissemination. Carbon dioxide (CO2) emissions associated with project activities mainly stem from electricity use, material consumption, project-hosted events, project participation in events, employees commuting, and equipment. Results show that in the first scenario, the projects exhibit a more than 40% increase in CO2 emissions compared to the BC, while in the second scenario, the implementation of measures such as teleworking, virtual participation in events, and digitization of bureaucratic processes lead to a reduction in emissions by at least 20%. The study suggests that adopting such measures after the COVID-19 pandemic could significantly decrease greenhouse gas emissions. [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]

A destructive V-shaped thunderstorm occurred over the Marche Region, in Central Italy, on 15 September 2022. Twelve people died during the event, and damage to properties was extensive because the small Misa River flooded the area. The synoptic-scale conditions that caused this disastrous event are analysed and go back to the presence of tropical cyclone Danielle in the eastern Atlantic. The performance of the weather research and forecasting (WRF) model using lightning data assimilation (LDA) is studied in this case by comparing the forecast with the control forecast without lightning data assimilation. The forecast performance is evaluated for precipitation and lightning. The case was characterised by four intense 3-h (3 h) periods. The forecasts of these four 3-h phases are analysed in a very short-term forecast (VSF) approach, in which a 3 h data assimilation phase is followed by a 3 h forecast. A homemade 3D-Var is used for lightning data assimilation with two different configurations: ANL, in which the lightning is assimilated until the start of the forecasting period, and ANL-1H, which assimilates lightning until 1 h before the 3 h forecasting period. A sensitivity test for the number of analyses used is also discussed. Results show that LDA has a significant and positive impact on the precipitation and lightning forecast for this case. [ABSTRACT FROM AUTHOR]

The atmosphere is an important pathway for microplastic (MP) transport; however, observations are limited, as traditional sampling methods are generally labor-intensive. Biological monitors (biomonitors) have been widely used as a simple alternative to determine the abundance or presence of anthropogenic pollutants. Here, we compared the effectiveness of co-located lichen and moss species as biomonitors of the atmospheric deposition of microplastics. Samples of the epiphytic lichen Evernia prunastri and the epigeic moss Pseudoscleropodium purum were collected from five remote areas of central Italy. A total of 154 MPs were found across all samples, 93.5% of which were fibers and 6.5% were fragments. The accumulation of MPs for lichens (range of 8–12 MP/g) was significantly lower than for mosses (12–17 MP/g), which might be related to their structural characteristics or habitat positions (epiphytic versus epigeic). Nonetheless, higher accumulation facilitates analytical determination and provides greater separation from the limit of detection, suggesting that mosses are preferred over lichens for studying the deposition of airborne MPs. This study further suggests that biomonitoring may be an effective tool to assess the spatial distribution of atmospheric microplastics, which is a key requirement for the development of waste mitigation policies. [ABSTRACT FROM AUTHOR]

This work represents a first step in the definition of a framework aimed at finding, by means of efficient global optimization based on metamodels, an optimal configuration of physical parameters for the ICON (ICOsahedral Nonhydrostatic) Limited Area Mode at high resolution (about 1.1 km) over Southern Italy, to be used for operational runs. The objective of the optimization is to reduce the distance between observed meteorological variables and modeled data. This distance is measured by an opportunely designed objective function. This work represents a preparatory step, since the input parameters considered are only a reduced number with respect to the huge amount of parameters potentially involved. First, domain size sensitivity was performed to choose the optimal domain. Then, the optimization was conducted by means of an Efficient Global Optimization algorithm relying on a Gaussian-based metamodel. The four parameters considered control the heat transfer in the turbulent layer, the laminar resistance and the snow vertical velocity. They were optimized over a week in November 2018, a period characterized by extreme events in the region considered. The results demonstrated the effectiveness of the proposed approach, reducing the distance from observed data, and the method can be considered promising from the perspective taking into account a larger set of physical parameters, and validation over a wider time-window. [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]

The concentrations of trace elements in atmospheric bulk depositions (wet plus dry) were investigated from two highly industrialised areas of Sicily (southern Italy) from June 2018 to July 2019, in order to recognise the main natural and anthropogenic sources. A side objective of this study was to improve the common sampling procedures and analytical methods used for monitoring trace elements in atmospheric deposition. The trace element VWM (Volume-Weighted Mean) concentrations ranged from less than 0.01 μg L−1 for trace elements such as Cs, Tl, and U, up to 24 μg L−1 for minor elements (Al, Zn, Sr), in the filtered aliquot, while they reached concentrations up to 144 μg L−1 for the same elements, in the unfiltered aliquot. Therefore, significant differences in concentrations between these two aliquots were found, particularly for Al, Fe, Ti, Zn, Cr, Pb, Se, Cs, and U. This implies that filtering operations may produce a consistent underestimation of concentrations of certain 'constituents' of the atmospheric deposition. Natural (marine spray, local and regional geogenic input, volcanic emanations) and anthropogenic sources (industrial emissions, auto vehicular traffic, and diffuse background pollution) which influence rainwater chemistry were identified. Enrichment factors (EFs), with respect to the upper crust composition, provided clear evidence of the different sources above mentioned: Ti, Fe, Al, Cs, Cr, Rb, and Co have low EFs (<1), and are referable to the (local and/or regional) geogenic input, while Se, Sb, Zn, B, Cd, Cu, Mo, Sr, As, with high EFs (>10), highlight the influence of marine and/or industrial sources. The study produced a novel dataset on the atmospheric deposition rate of several trace elements, which had never been studied in the investigated areas. Finally, a comparison of trace element deposition rates in the studied areas with the atmospheric deposition reported for 53 different sites, belonging to 20 different European nations, was made. The comparison showed that some elements, such as Al, V, Zn, and Mo had higher median deposition fluxes in the Sicilian sites than in European monitoring sites. [ABSTRACT FROM AUTHOR]

We apply extreme value theory (EVT) to study the daily precipitation and temperature extremes in the Calabria region (southern Italy) mainly considering a long-term observational dataset (1990–2020) and also investigating the possible use of the ERA5 (ECMWF Reanalysis v5) fields. The efficiency of the EVT applied on the available observational dataset is first assessed—both through a punctual statistical analysis and return-level maps. Two different EVT methods are adopted, namely the peak-over-threshold (POT) approach for the precipitation and the block-maxima (BM) approach for the temperature. The proposed methodologies appear to be suitable for describing daily extremes both in quantitative terms, considering the punctual analysis in specific points, and in terms of the most affected areas by extreme values, considering the return-level maps. Conversely, the analysis conducted using the reanalysis fields for the same time period highlights the limitations of using these fields for a correct quantitative reconstruction of the extremes while showing a certain consistency regarding the areas most affected by extreme events. By applying the methodology on the observed dataset but focusing on return periods of 50 and 100 years, an increasing trend of daily extreme rainfall and temperature over the whole region emerges, with specific areas more affected by these events; in particular, rainfall values up to 500 mm/day are predicted in the southeastern part of Calabria for the 50-year-return period, and maximum daily temperatures up to 40 °C are expected in the next 100 years, mainly in the western and southern parts of the region. These results offer a useful perspective for evaluating the exacerbation of future extreme weather events possibly linked to climate change effects. [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 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]

An updated climatology of EF1+ (Enhanced Fujita category 1 or stronger) tornadoes in Italy (445 events in the period of 1990–2021) confirms that the central Tyrrhenian (CT) and the southeastern (SE) regions of the Italian peninsula represent two of the areas most affected by tornadoes in the Mediterranean. We performed a comparative analysis between these two hotspots, examining the large-scale atmospheric features associated to the tornado occurrences, throughout the analysis of radiosounding observations and reanalysis (ERA5) fields. The conditions in which the tornadoes develop are investigated using metrics regarding atmospheric instability and/or horizontal/vertical wind shear. Common synoptic characteristics are found for both regions, i.e., a prevalent occurrence of tornadoes on the eastern flank of approaching troughs, with moderate shear/CAPE mean values. A large number of events develop in a high-shear/low-CAPE (HSLC) environment, in the presence of positive sea surface and 850 hPa temperature anomalies. Conversely, the upper-level winds suggest different characteristics of the tornado-spawning cells in the two areas, i.e., multi-cells/linear systems for CT and isolated supercells for SE. The maximum values for some typical atmospheric fields/instability parameters in the areas around the tornado hotspots permit the obtention of thresholds that identify the most favorable environments for tornado formation in these Italian areas. [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]

Air pollution is one of the most important environmental problems for rural, urban and industrial areas. This study assesses the concentrations, the possible interaction with the vegetation conditions and the sources of trace elements in atmospheric aerosol particles. To this aim, a novel holistic approach integrating biomonitoring techniques, satellite observations and multivariate statistical analysis was carried out in a semi-rural area before an on-shore reservoir (crude oil and gas) and an oil/gas pre-treatment plant identified as "Tempa Rossa" (High Sauro Valley—Southern Italy) were fully operative. The atmospheric trace element concentrations (i.e., Al, Ca, Cd, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, P, Pb, S, Ti and Zn) were assessed by "lichen-bag" monitoring. Satellite-derived normalized difference vegetation index (NDVI') estimates were used to support the identification of environmental imbalances affecting vegetation conditions and linked to possible anthropogenic drivers. Principal component analysis (PCA) allowed identifying both natural and anthropogenic trace element sources, such as crustal resuspension, soil and road dust, traffic, biomass burning and agriculture practices. Empirical evidence highlighted an interaction between NDVI' and S, Ni, Pb and Zn. The health risk impact of atmospheric trace elements on the exposed population, both adults and children, considering inhalation, ingestion and the dermal contact pathway, highlighted a possible non-carcinogenic risk concerning Ni and a not-negligible carcinogenic risk related to Cr(VI) for the adult population in the study area. [ABSTRACT FROM AUTHOR]

On 10 July 2019, a giant hail-bearing supercell hit the Adriatic coast of central Italy. Hailstones with a maximum diameter of 14 cm were reported in the city of Pescara between 10:00 and 11:00 UTC. In this work, the main synoptic and mesoscale features, responsible for the triggering and the development of the supercell, are analyzed using the WRF model. The intrusion of Bora wind over the northern and central Adriatic was relevant for two reasons: on the one side, the arrival of low-level cold air produced an uplift of the pre-existing warm air and favored the triggering of convection; on the other side, the strong vertical wind shear, also due to the presence of intense upper-level southwesterlies, created conditions favorable to the formation of the supercell. The predictability of the event is also discussed, comparing simulations starting at different initial times and forced with GFS and IFS forecasts. The model results show that the runs initialized at earlier times reproduced more accurately the track and the time evolution of the supercell. The HAILCAST module of WRF was also used to simulate hailstorm characteristics, such as the average hailstone diameter. WRF-HAILCAST simulations proved to be in fair agreement with the radar reflectivity retrievals and with local reports. [ABSTRACT FROM AUTHOR]

The adversities of climate change represent a serious risk factor on both food production, rural territories and landscapes. In light of these irreversible trends, the process of adaptation of the rural territory is a necessary step, in order to increase its climate resilience. In this study, the vulnerability assessment was the tool used to evaluate the specific phenomenon of "flooding and backwatering" in the case study of Emilia Romagna region (Italy). The approach was based on the IPCC's risk analysis methodology, populated by different layers regarding specifical proxies related to the adaptive capacity and the sensitivity of the territory to water stagnation, then we assessed with the normalization process of the different information levels. The aim of the research consisted in the realization of a regional map of the vulnerability to floods and backwaters, in order to rank the territory to this specific phenomenon. The final result could be useful both for the relationship with planning choices and for local-based actions in agricultural policies that in Italy are taken at regional level. [ABSTRACT FROM AUTHOR]

Citizen science has shown great potential for bringing large groups of people closer to science, thanks in part to cooperation with universities and research centers. In this context, amateur weather networks played a major role in the last few decades thanks to a constant growth in technology. An example is given by the Meteonetwork association, born in 2002, and mainly composed by atmospheric science enthusiasts, who built up in time a huge weather station network in Italy. In recent years, they have enlarged their horizons over Europe, displaying real time observations and daily maps coming from both personal weather stations and official networks. This study described how Meteonetwork has set up an open crowdsourced weather data system, how data are validated, and which products are generated and freely accessible for scientists and stakeholders for their own purposes. Two concrete use cases were described as examples: the Weatherness Project, which selects a subnet of Meteonetwork data for biometeorological and health purposes and the data assimilation process implemented to improve the initial conditions into the WRF meteorological model for daily weather forecasts. [ABSTRACT FROM AUTHOR]

The honeybee (Apis mellifera L.) has been used in several studies for monitoring the environmental health status in terms of pollution, due to its wide-ranging foraging flights. Based on this consideration, this study aimed to analyze heavy metal pollution in Molise Region (Italy), by investigating five sites characterized by different levels of contamination. Furthermore, the authors carried out a sampling activity for a long period, in order to obtain a complete dataset. In this way, detailed information about the status of the environments was able to be obtained. The main purpose of this work was to assess the health status of Molise Region and to confirm the suitability of honeybees as environmental bioindicators of heavy metal pollution, by analyzing their variability over time and space. Furthermore, the study compared the health status associated with contamination in terms of heavy metals with that in two different areas of Italy, using hierarchical cluster analysis and principal component analysis, to evaluate the correlation existing among the three different areas of Italy. Following the findings, the authors suggest the use of honeybees as a bioindicator for heavy metal pollution in air quality studies. [ABSTRACT FROM AUTHOR]

In this work, the results of a sensitivity study based on ICON-LAM simulations at 2.5 km of spatial resolution over the Italian area, driven by ECMWF IFS global data, are presented. The main aim is to provide a contribution to the selection of suitable parameterization schemes that result in more effective for a proper representation of the Italian climate features. Model evaluation was conducted in terms of the air temperature and precipitation for three subregions, comparing a set of 13 simulations against SCIA and E-OBS standard datasets. In addition, evaluation was also conducted against selected data stations scattered over the Italian area. We found that the ICON-LAM model was able to provide a good representation of the temperature over Italy, whereas non-negligible biases were observed for precipitation in certain regions. The model proved to be sensitive to changes in physical parameterization schemes. In particular, we found that the explicit treatment of deep convection and the "clouds as in turbulence" scheme for cloud cover allowed for a better representation of precipitation in the summer over the Alpine region. The single moment scheme is currently the best option for cloud microphysics. [ABSTRACT FROM AUTHOR]

The aim of this study was to characterise the contamination in settled dust in French classrooms and to provide an overview of the influencing factors of dust contamination. Cat, dog and dust mite allergens and metals were measured in 51 classrooms at 17 schools. The concentrations of pet allergens in settled dust were generally low (mean value of 0.1 μg.g-1), with carpeted and rug-covered floors presenting higher dust and cat allergen concentrations. The highest metal loadings in dust were observed for manganese (Mn) and copper (Cu), while the lead (Pb) loadings were lower (16 ± 19 μg.m-2) and fell below the French guideline. Higher metal leachability was found for cadmium (Cd), Cu, Pb and strontium (Sr) at values of approximately 80%, which suggest that, in cases of dust ingestion by children, a large proportion should be assimilated through the gastro-intestinal tract. The intra-classroom and intra-school variabilities of the metal concentrations in settled dust were lower than the variability between schools. Classrooms with tiled floors had higher Pb loadings than classrooms with wood or vinyl floors. In addition, wet cleaning less than once a week resulted in greater loadings of Cu and Pb in the settled dust. Lastly, enrichment factors showed that metals in settled dust of classrooms were not only from the contribution of the natural background concentrations in soils. [ABSTRACT FROM AUTHOR]

The combined use of Lecce-University AERONET-photometer measurements and PM2.5, PM10, NO2, CO, and SO2 concentrations from different sites of Apulia-Region Air-Quality Agency represents the peculiarity of this study, which evaluates the impact of COVID-19 lockdown (LD) measures on aerosol and gaseous pollutants. Monthly-averaged columnar and surface parameters of the 2020-year were compared with corresponding monthly parameters of the ref-year obtained by averaging 2017, 2018, and 2019 measurements in order to evaluate LD measure impacts by Average Percent Departure (APD%). Photometer measurements showed that LD measures were likely responsible for the decrease in Aerosol Optical Depth (AOD). The APD% estimated between the 2020- and ref-year AOD (at 440 nm) was characterized by negative values from June to August, reaching the smallest mean value (−46%) in June. Moreover, the columnar aerosol load appeared less affected by continental urban/industrial particles than previous years in the summer of 2020. The PM-concentration-APD% calculated at ten sites was characterized by monthly trends similar to those of AOD-APD%. PM-APD% values varied from site to site and smaller values (up to −57% in June) were on average detected at urban/suburban sites than at background sites (up to −37%). The impact of LD measures on gaseous pollutants was observed from the onset of LD. [ABSTRACT FROM AUTHOR]

Minimetrò (MM) is a ropeway public mobility system that has been in operation in the city of Perugia for about ten years to integrate with urban mobility and lighten vehicular traffic in the historic city center. The purpose of this work was to evaluate the impact of MM as a source of pollutants in the urban context, and the exposure of people in the cabins and the platforms along the MM line. These topics have been investigated by means of intensive measurement and sampling campaigns performed in February and June 2015 on three specific sites of the MM line representative of different sources and levels of urban pollution. Stationary and dynamic measurements of particle size distribution, nanoparticle and black carbon aerosol number and mass concentrations measurements were performed by means of different bench and portable instruments. Aerosol sampling was carried out using low volume and high-volume aerosol samplers, and the samples nalysed by off-line methods. Results show that MM is a considerable source of atmospheric particulate matter having characteristics very similar to those of the common urban road dust in Perugia. In the lack of clear indications on road dust effect, the contribution of MM to the aerosol in Perugia cannot be neglected. [ABSTRACT FROM AUTHOR]

Indoor built environments' design and management require a holistic approach inspired by ergonomic principles and sustainability criteria. This is especially in case of renovation of existing buildings where any kind of intervention requires the direct feedback of occupants. This work deals with two aspects of these issues, often studied separately: the quality of interior spaces, in terms of Indoor Environmental Quality (IEQ), and the quality of the architecture in terms of orientation and wayfinding. A methodology focused on the subjective evaluation of the IEQ giving relevance to users and their fruition needs is also proposed. Main findings from a specific subjective investigation carried out at the Fisciano Campus of the University of Salerno (Italy) demonstrate that the subjective approach is a valuable tool to make more sustainable intervention strategies. In this way, all multidisciplinary skills can be synergically involved in improving the livability of a complex reality as University Campuses are. [ABSTRACT FROM AUTHOR]

Populated coastal areas are exposed to emissions from harbour-related activities (ship traffic, loading/unloading, and internal vehicular traffic), posing public health issues and environmental pressures on climate. Due to the strategic geographical position of Italy and the high number of ports along coastlines, an increasing concern about maritime emissions from Italian harbours has been made explicit in the EU and IMO (International Maritime Organization, London, UK) agenda, also supporting the inclusion in a potential Mediterranean emission control area (MedECA). This work reviews the main available outcomes concerning shipping (and harbours') contributions to local air quality, particularly in terms of concentration of particulate matter (PM) and gaseous pollutants (mainly nitrogen and sulphur oxides), in the main Italian hubs. Maritime emissions from literature and disaggregated emission inventories are discussed. Furthermore, estimated impacts to air quality, obtained with dispersion and receptor modeling approaches, which are the most commonly applied methodologies, are discussed. Results show a certain variability that suggests the necessity of harmonization among methods and input data in order to compare results. The analysis gives a picture of the effects of this pollution source, which could be useful for implementing effective mitigation strategies at a national level. [ABSTRACT FROM AUTHOR]

We analyse the earthquakes catalogues for Italy, South California, and Greece across the COVID-19 lockdown period for each country. The results for Italy and Greece show that, even if the reduction of the signal to noise ratio has improved the earthquake detection capability, the completeness magnitude remains substantially unchanged, making the improved detection capability ineffective from the statistical point of view. A slight reduction (0.2) of the completeness magnitude is observed for South California, likely related to the relatively higher number of seismic stations located close to urban areas. Our findings suggest that—given the present configuration of the seismic network considered here—only an important decrease in the station spacing can produce a significant decrease of the completeness magnitude. [ABSTRACT FROM AUTHOR]

Long and short-term exposure to atmospheric particulate matter (PM) has detrimental effects on human health. The effective mechanisms leading to PM toxicity are still not fully understood, even if it is known that physical-chemical properties, strongly influenced by sources and atmospheric processes, are known to play an important role. In this work, PM10 samples were collected, at an urban background site in southern Italy, to determine cytotoxicity (using MTT test on A549 cells), genotoxicity (using the comet assay), and intracellular oxidative stress on A549 cells exposed for 24 h to aqueous extracts of PM10 samples. Organic carbon (OC) and elemental carbon (EC) content of PM10 and acellular determination of oxidative potential with DTT assay were performed to compare results of acellular and cellular biological assays. Cellular (OSGCV and MTTV) and acellular (OPDTTV) outcomes, normalized in volume, are well correlated (statistically significant results) with carbon content suggesting that combustion sources play an important role in determining cellular oxidative stress and cytotoxicity of PM10. Even if the number of data is limited, genotoxicity results are well correlated (Pearson r > 0.95) with OSGCV and MTTV, and a weaker, but statistically significant correlation was observed with OPDTTV. OSGCV is well correlated with the cell mortality observed with the MTTV test and a lower, but still statistically significant correlation is observed between MTTV and OPDDTV. A statistically significant correlation was found between OPDTTV and OSGCV results. When the outcomes of the cellular and acellular assay are compared normalized in mass (i.e., intrinsic values), the correlations become significantly weaker suggesting that the different sources acting on the site produces particulate matter with different toxicological potential influencing differently the biological tests studied. [ABSTRACT FROM AUTHOR]

In order to slow the spread of SARS-CoV-2, governments have implemented several restrictive measures (lockdown, stay-in-place, and quarantine policies). These provisions have drastically changed the routines of residents, altering environmental conditions in the affected areas. In this context, our work analyzes the effects of the reduced emissions during the COVID-19 period on the ultrafine particles number concentration and their turbulent fluxes in a suburban area. COVID-19 restrictions did not significantly reduce anthropogenic related PM10 and PM2.5 levels, with an equal decrement of about 14%. The ultrafine particle number concentration during the lockdown period decreased by 64% in our measurement area, essentially due to the lower traffic activity. The effect of the restriction measures and the reduction of vehicles traffic was predominant in reducing concentration rather than meteorological forcing. During the lockdown in 2020, a decrease of 61% in ultrafine particle positive fluxes can be observed. At the same time, negative fluxes decreased by 59% and our observation site behaved, essentially, as a sink of ultrafine particles. Due to this behavior, we can conclude that the principal particle sources during the lockdown were far away from the measurement site. [ABSTRACT FROM AUTHOR]

Characteristics of extratropical cyclones that cause tornadoes in Italy are investigated. Tornadoes between 2007 and 2016 are analyzed, and statistical analysis of the associated cyclone structures and environments is performed using the JRA-55 reanalysis. Tornadoes are distributed sporadically around the cyclone location within a window of 10° × 10°. The difference in the cyclone tracks partially explains the seasonal variability in the distribution of tornadoes. The highest number of tornadoes occur south of the cyclone centers, mainly in the warm sector, while a few are observed along the cold front. Composite mesoscale parameters are examined to identify the environmental conditions associated with tornadoes in different seasons. Potential instability is favorable to tornado development in autumn. The highest convective available potential energy (CAPE) in this season is associated with relatively high-temperature and humidity at low-levels, mainly due to the strong evaporation over the warm Mediterranean Sea. Upper-level potential vorticity (PV) anomalies and the associated cold air reduce the static stability above the cyclone center, mainly in spring and winter. On average, the values of CAPE are lower than for US tornadoes and comparable with those occurring in Japan, while storm relative helicity (SREH) is comparable with US tornadoes and higher than Japanese tornadoes, indicating that the environmental conditions for Italian tornadoes have peculiar characteristics. Overall, the conditions emerging in this study are close to the high-shear, low-CAPE environments typical of cool-season tornadoes in the Southeastern US. [ABSTRACT FROM AUTHOR]

Wildfire occurrence and severity in the Mediterranean region during the summer season is increasing, being favoured by climate change-induced conditions (i.e., drought, heatwaves). Moreover, additional natural sources frequently impact this region, particularly Saharan dust intrusions. This study focuses on the combined effect of wildfires and Saharan dust on the air quality of the central Mediterranean Basin (CMB) during 2017, an exceptional year for forested burned areas in southern Italy. The annual behaviors of PM2.5, PM10, CO, benzene, and benzo(a)pirene measurements that were recorded at a rural regional-background station located in southern Italy, highlighted a concentration increase during summer. Both Saharan dust and wildfire events were identified while using Navy Aerosol Analysis and Prediction System (NAAPS) model maps, together with high-resolution Weather Research and Forecast—Hybrid Single-Particle Lagrangian Integrated Trajectory (WRF-HYSPLIT) back-trajectories. Additionally, Visible Infrared Imaging Radiometer Suite (VIIRS) satellite detections were considered to establish the enrichment of air masses by wildfire emissions. Finally, the occurrence of these natural sources, and their influence on particulate matter, were examined. In this case study, both PM2.5 and PM10 exceedances occurred predominantly in conjunction with wildfire events, while Saharan dust events mainly increased PM10 concentration when overlapping with wildfire effects. [ABSTRACT FROM AUTHOR]

This study aims to assess the capabilities of a weather forecasting system based on simulations performed with the COSMO (COnsortium for Small-scale Modeling) model over a domain located in southern Italy, employing a spatial resolution of about 1 km, driven by ECMWF-IFS global data. The model is run daily at the Italian Aerospace Research Center (CIRA), and the evaluation was performed from January to May 2018 using a combination of observational data, specifically data provided by the CIRA meteorological station, wind profiler and ceilometer. Moreover, data provided by radio sounding located at Pratica di Mare and ground stations at two other locations were also used. A model configuration optimized through a tuning procedure over the domain considered was employed, while the evaluation was performed by comparing daily values of several variables and using standard monitoring indices. The results highlight that the model has good capability in reproducing daily values of temperature, while precipitation intensity is generally underestimated, even if rain patterns are well captured (alternating rainy and dry days). Good agreement is also reported for wind speed, especially at 100 and 500 m altitude. Regarding radio sounding data, the COSMO model configuration selected can reproduce the vertical profile of temperature and dew point, with the exception of inversion points. Evaluation against ceilometer data is achieved in terms of cloud height and planetary boundary layer height. [ABSTRACT FROM AUTHOR]

The complex interaction between the Urban Heat Island (UHI), local circulation, and air quality requires new methods of analysis. To this end, this study investigates the multiple scale nature of the UHI and its relationship with flow and pollutant dispersion in urban street canyons with and without the presence of vegetation. Two field experimental campaigns, one in summer and one in winter, were carefully designed in two parallel urban street canyons in the city of Bologna (44°29′ N, 11°20′ E; Italy) characterized by a similar orientation with respect to the impinging background flow but with a different aspect ratio and a different presence of vegetation. In addition to standard meteorological variables, the dataset collected included high-resolution flow data at three levels and concentration data of several pollutants. The UHI has been evaluated by combining surface temperature of building facades and ground surfaces acquired during two intensive thermographic campaigns with air temperature from several stations in order to verify the presence of intra-city neighborhood scale UHIs additional to the more classical urban–rural temperature differences. The presence of trees together with the different morphologies was shown to mitigate the UHI intensity of around 40% by comparing its value in the center of the city free of vegetation and the residential area. To capture the multiple-scale nature of UHI development, a simple relationship for the UHI convergence velocity, used as a surrogate for UHI strength, is proposed and used to establish the relationship with pollutant concentrations. The reliability of the proposed relationship has been verified using a Computational Fluid Dynamics (CFD) approach. The existence of a robust relationship between UHI strength and pollutant concentration may indicate that the positive effect of mitigation solutions in improving urban thermal comfort likely will also positively impact on air pollution. These results may be useful for a quick assessment of the pollutant accumulation potential in urban street canyons. [ABSTRACT FROM AUTHOR]