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Slow and long-term variations of sea surface temperature anomalies have been interpreted as a red-noise response of the ocean surface mixed layer to fast and random atmospheric perturbations. How fast the atmospheric noise is damped depends on the mixed layer depth. In this work we apply this theory to determine the relevant spatial and temporal scales of surface layer thermal inertia in lakes. We fit a first order auto-regressive model to the satellite-derived Lake Surface Water Temperature (LSWT) anomalies in Lake Garda, Italy. The fit provides a time scale, from which we determine the mixed layer depth. The obtained result shows a clear spatial pattern resembling the morphological features of the lake, with larger values (7.18± 0.3 m) in the deeper northwestern basin, and smaller values (3.18 ± 0.24 m) in the southern shallower basin. Such variations are confirmed by in-situ measurements in three monitoring points in the lake and connect to the first Empirical Orthogonal Function of satellite-derived LSWT and chlorophyll-a concentration. Evidence from our case study open a new perspective for interpreting lake-atmosphere interactions and confirm that remotely sensed variables, typically associated with properties of the surface layers, also carry information on the relevant spatial and temporal scales of mixed-layer processes. [ABSTRACT FROM AUTHOR]

This article analyses the winter warm spells (WWS) that occurred in central Mediterranean over the period 1993–2022, examining the daily maximum temperatures collected at eight airport sites located in the Italian Peninsula, belonging to different climate zones. According to the definition proposed in 1999 by the Expert Team on Climate Change Detection and Indices (ETCCDI), a WWS is a sequence of at least six consecutive days when daily maximum air temperature exceeds the calendar day 90th percentile centred on a 5‐day window for a base period. WWS occurring over the entire Italian territory or only over northern/central/southern Italy have been identified and related to the peculiar synoptic conditions. It was found that December is the month most prone to WWS and, on average, WWS last 9.4 days in northern Italy, 6.6 days in central Italy, and 8.5 days in southern Italy. Over the period under investigation, the Italian Peninsula experienced only one common event characterized by persistent high‐pressure systems associated with air subsidence over western Mediterranean and, therefore, with exceptional warming. Finally, it has been proven that the definition of WWS proposed by ETCCDI allows to capture synoptic scale events but, in orographically complex areas such as Italy, underestimates moderate spells, which generally might have a duration of at least 3 days. Consequently, it is important to consider the possibility of reducing the period length threshold used for the detection of WWS when orographically heterogeneous regions are studied. [ABSTRACT FROM AUTHOR]

It is commonly recognized that the observed increase in global mean annual air temperature is strongly related to the increase in global carbon dioxide concentration C, and that both these variables are related to global development. It remains, however, unclear the degree to which local mean annual urban air temperature T is affected by local variables such as annual precipitation depth P and urban area extent A. This study assumes that A is a proxy of local development and C is a proxy of global development and investigates the commingled effects of A, P, and C on T by using long-term annual data observed over the years 1881–2019 from the Modena Observatory in Italy. Linear relationships between T, C and A are found to be spurious since all these series have a monotonic increasing trend with time. Parametric analytic models like logistic functions are found to lack flexibility. Smoothing splines can only give insights into the strength of the relationships but not on their shape defining the functional relationship between variables. Advanced nonlinear models like generalized additive models, instead, are found to combine flexibility in a parametric form, and appear therefore to be suitable models for explaining the complex relationships between A, P, and C on T. The different models are evaluated using traditional goodness of fit statistics like R2, AIC, BIC, and a new index of relation IR which is introduced to jointly evaluate the goodness-of-fit of relationships between variables that may either be dependent or independent. [ABSTRACT FROM AUTHOR]

The research presented in this paper aims at providing a statistical model that is capable of estimating soil water content based on weather data. The model was tested using a long-time series of field experimental data from continuous monitoring at a test site in Oltrepò Pavese (northern Italy). An innovative statistical function was developed in order to predict the evolution of soil–water content from precipitation and air temperature. The data were analysed in a framework of robust statistics by using a combination of robust parametric and non-parametric models. Specifically, a statistical model, which includes the typical seasonal trend of field data, has been set up. The proposed model showed that relevant features present in the field of experimental data can be obtained and correctly described for predictive purposes. [ABSTRACT FROM AUTHOR]

Analyses of climate change, due to its impact not only on the weather and the environment but also on human health and life, are one of the most important study activities made in recent years. There is relatively high confidence that glacial melt and heavy rainfall events will continue to increase. These climate-related events carry a microseismic signature that can guide monitoring activities. In the last decade, there have been growing applications of long-term continuous ambient seismic noise systems to monitor landslides and potentially unstable rock sites. This work reports some of the activities made during a project performed under the Department of Excellence on Climate Change (2018–2022), funded by the Italian Ministry for University and Research (MUR), in order to improve environmental seismic analyses. The selected test site is the Bossea Cave (NW Italy), where two seismic stations were installed. The goals were to use these stations to understand and study climate change events above the Bossea Cave, analyzing the data from a geophysical and geomatics point of view. Starting with UAV flights and photogrammetric processing to obtain a 3D model of the cave, both ambient seismic noise and microseismicity analyses highlighted an important effect of air temperature and precipitation on the seismic response of the monitored rock mass overlying the Bossea Cave. In particular, a clear effect on the ambient seismic noise spectral content and the peak frequency of the microseismic events driven by temperature and precipitation was found during the warmer monitoring months, with almost zero delays in the seismic response. This is a preliminary but important study, even if longer monitoring data and thermal modeling efforts are needed to fully understand this seasonal variation. [ABSTRACT FROM AUTHOR]

This work aims to assess the impacts of climate change on photovoltaic (PV) electricity in two Italian cities, with different latitudes and Köppen–Geiger climate classifications. This was undertaken using the recent EURO-CORDEX set of high-resolution climate projections and PV power generation models, implemented on TRNSYS software. Data for two variables (surface air temperature and solar radiation) were analysed over a long period from 1971 to 2100. For future periods, two of the Representative Concentration Pathway scenarios (RCP4.5 and RCP8.5) used in the Intergovernmental Panel on Climate Change Fifth Assessment Report were considered. In both RCP scenarios and both locations, it is estimated that the yearly PV energy produced in the future period will not undergo significant variations on average given that the rate of decrease is foreseen almost constant; instead, a slight reduction in the PV energy was detected in the past period. It can be concluded that the PV market in Italy will grow in the next years considering that the reduction in the foreseen PV purchase costs will be also supported by the slight positive effect of climate change on PV manufacturability. [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]

• An association between environmental stressors and venous thromboembolism is not firmly established. • We analyzed hospital discharge data for the entire Italy during 2006–2015. • An adverse effect of low temperatures in winter/autumn on pulmonary embolism was found. • There was also a negative impact of high temperatures in summer on pulmonary embolism. • No short-term effect of air pollution on these outcomes was observed. Previous studies reported a link between short-term exposure to environmental stressors (air pollution and air temperature) and atherothrombotic cardiovascular diseases. However, only few of them reported consistent associations with venous thromboembolism (VTE). Our aim was to estimate the association between daily air temperature and particulate matter (PM) air pollution with hospital admissions for pulmonary embolism (PE) and venous thrombosis (VT) at national level in Italy. We collected daily hospital PE and VT admissions from the Italian Ministry of Health during 2006–2015 in all the 8,084 municipalities of Italy, and we merged them with air temperature and daily PM10 concentrations estimated by satellite-based spatiotemporal models. First, we applied multivariate Poisson regression models at province level. Then, we obtained national overall effects by random-effects meta-analysis. This analysis was conducted on 219,952 PE and 275,506 VT hospitalizations. Meta-analytical results showed weak associations between the two exposures and the study outcomes in the full year analysis. During autumn and winter, PE hospital admissions increased by 1.07% (95% confidence intervals [CI]: 0.21%; 1.92%) and 0.96% (95% CI: 0.07%; 1.83%) respectively, per 1 °C decrement of air temperature in the previous 10 days (lag 0–10). In summer we observed adverse effects at high temperatures, with a 1% (95% CI: 0.10%; 1.91%) increasing risk per 1 °C increment. We found no association between VT and cold temperatures. Results show a significant effect of air temperature on PE hospitalizations in the cold seasons and summer. No effect of particulate matter was detected. [ABSTRACT FROM AUTHOR]

The continuous increase of atmospheric CO2 content mainly due to anthropogenic CO2 emissions is causing a rise in temperature on earth, altering the hydrological and meteorological processes and affecting crop physiology. Evapotranspiration is an important component of the hydrological cycle. Thus, understanding the change in evapotranspiration due to global warming is essential for better water resources planning and management and agricultural production. In this study, the effect of climate change with a focus on the combined effect of temperature and elevated CO2 concentrations on reference evapotranspiration (ETo) was evaluated using the Penman–Monteith equation. A EURO-CORDEX regional climate model (RCM) ensemble was used to estimate ETo in five locations in the Emilia-Romagna region (Northern Italy) during the period 2021–2050. Then, its projected changes in response to different CO2 concentrations (i.e., 372 ppm and 550 ppm) under two Representative Concentration Pathways (RCP) scenarios (i.e., RCP4.5 and RCP8.5) were analyzed. Simulation results with both scenarios, without increasing CO2 levels (372 ppm), showed that the annual and summertime ETo for all locations increased by an average of 4 to 5.4% with regard to the reference period 1981–2005, for an increase of air temperature by 1 to 1.5 °C. When the effect of elevated CO2 levels (550 ppm) was also considered in combination with projected changes in temperature, changes in both annual and summer ETo demand for all locations varied from − 1.1 to 2.2% during the 2021–2050 period with regard to the reference period 1981–2005. This shows that higher CO2 levels moderated the increase in ETo that accompanies an increase in air temperature. [ABSTRACT FROM AUTHOR]

With the purpose of revising World Meteorological Organization's Commission for Instruments and Methods of Observation (WMO/CIMO) Guide #8 on weather stations siting, an experiment to evaluate metrologically the maximum influence of a paved road on 2‐m air temperature measurements ("road siting effect") has been designed, installed and run in Italy. It consists of a 100‐m long array of seven measurement stations, at increasing distances from a local road, equipped with shielded Pt100 thermometers and ancillary sensors. Data coming from 1 year of observations have been analysed for daily climatological metrics, finding that the road mostly effects minimum temperatures, with average values of ~0.30 ± 0.18 °C at a distance of 1 m; then, in order to quantify the instrumental effect on the measurement, data were filtered by applying a generalized additive model, selecting only times when the effect is more intense (during nights, in presence of low winds coming from the road), and the road siting effect has been calculated by modelling the maximum temperature differences by using extreme values analysis. The 1‐year return value on 10‐min measurements is 1.22 ± 0.30 °C at 1 m from the road, with a gradual decline (~0.1 °C·m−1), while an extrapolation to 100‐year return level gives a value of 1.71 ± 0.79 °C with a decline rate of about 0.17 °C·m−1. This is a first step towards a redefinition of the weather station classification scheme of WMO/CIMO Guide #8, together with building and tree effects experiments which have been run in parallel with the road siting experiment here presented and which will be presented elsewhere. [ABSTRACT FROM AUTHOR]

Accelerating the decarbonisation of the built environment necessitates increasing electrification of end-uses, which in turn poses the issue of rethinking the role of energy efficiency in conjunction with flexibility in grid interaction. This requires a better understanding of the electricity load profiles at hourly or sub-hourly intervals using techniques that are simple, reliable, and interpretable. To this extent, this study proposes a reformulation of the Time Of Week and Temperature modelling approach. This approach is able to separate the energy consumption dependence on building operational characteristics (Time Of Week) and on weather (outdoor air temperature), through a highly automated modelling workflow, necessitating minimal effort for model tuning. These features, along with its intrinsic interpretability due to its formulation using multivariate regression and the availability of open-source software, makes it an ideal starting point for applied research. The case study selected for the research is a fully electrified public building in Southern Italy. The building has been monitored for 5 years, before, during and after the COVID-19 lockdown. The novel model formulation is calibrated using hourly interval data with a Coefficient of Variation of Root Mean Square Error in the range of 20.0–28.5% throughout the various monitoring periods. The counterfactual analysis of electricity consumption indicates a 10.7–26.7% decrease in electricity consumption due to operational adjustments following COVID-19 lockdown, highlighting the impact of behavioural change. Finally, the possibility of additional workflow automation and enhanced interpretability is discussed. • Fully electrified building monitored for 5 years, before, during and after COVID-19 lockdown. • Novel Time Of Week and Temperature algorithm formulation for electric load profiles modelling. • Models calibrated with Coefficient of Variation of Root Mean Square Error in the range 20.0–28.5%. • Counterfactual analysis shows a reduction of electricity consumption in the range 10.7–26.7%. • Further modelling workflow automation possible while enhancing interpretability. [ABSTRACT FROM AUTHOR]

Alpine glaciers are shrinking at a relentless pace, as an effect of global warming. The impact of these changes in the European Alps is relevant, given the importance of this territory from both ecological and economic viewpoints. While the ubiquitous reduction of glaciers' mass through the Alps has been reported in several studies, its effect on streamflow is less studied. In the present work, we analyzed the long streamflow time series, available since 1976, of the Careser Stream, a headwater stream emerging from the Careser Glacier, in northeastern Italy. A large amount of missing data characterizes the streamflow time series, which we filled with a high level of confidence by using a Feed Forward Deep Neural Network algorithm. We explored the influence of climatic drivers on streamflow at monthly and annual time scales. Our analysis highlighted significant changes in the timing of streamflow due to the combined effect of early snow melting and a progressive reduction of the glacier's area. The hydrological regime changed significantly with glacier water contributing to streamflow proportionally less after a tipping point identified in 1996. Projections performed by using eight bias-corrected climate models of the EURO-CORDEX collections confirmed this tendency with the complete transition of the catchment from the glacial to the nival regime by 2045 at the latest. The Deep Neural Network algorithm was very effective in filling the missing streamflow data and this offers an encouraging premise for applications in other glaciers of the Alps suffering from the same transformation. [Display omitted] • Comprehensive analysis of the long-term hydrological behavior of an Alpine glacier. • Rising air temperature alters streamflow dynamics of the Careser Glacier. • Glacier shrinkage offsets the effect of climate change on streamflow. • Climate change scenarios project the glacier to vanish by 2045 at the latest. • Feed Forward Deep Neural Network model provides an accurate streamflow reconstruction. [ABSTRACT FROM AUTHOR]

The purpose of this work was to establish the desorption isotherms and thermodynamic characteristics of grapes cv. Italia. These characteristics are important tools in food science, particularly due to their contribution to the prevision of quality, constancy, and durability of agri-food commodities. Desorption isotherms were determined by the static gravimetric method. All the curves revealed type II behavior, according to Brunauer's classification. The desorption isotherms fitted by eight equations showed that Adam and Shove and also the GAB models gave the best fit to the experimental results. But the GAB model was recommended for the prediction of the desorption isotherms of Italia grapes owing to its physical explanation of the sorption process compared to the Adam and Shove model which was purely empirical. The moisture isotherms were exothermic, enthalpy driven, and spontaneous. The enthalpy–entropy compensation existed with an isokinetic temperature of 390 K. [ABSTRACT FROM AUTHOR]

The aim of this study is to evaluate human thermal comfort in different green area settings in the city of Florence by using the Universal Thermal Climate Index (UTCI). Field measurements of air temperature, solar radiation, relative humidity, wind speed and black globe thermometer were collected during hot summer days in various parts of Cascine Park, the biggest urban park in Florence (Italy). UTCI was evaluated over different surfaces (asphalt, gravel and grass) completely exposed to the sun or shaded by a large lime tree (Tilia × europaea). The results showed strong differences in UTCI values depending on the exposure to tree shade, while no significant difference was found among ground-cover materials when all surfaces were equally exposed to solar radiation. Future studies are needed to investigate the microclimatic effects of different tree species on UTCI. [ABSTRACT FROM AUTHOR]

Daphnia are key organisms in pelagic food webs, acting as a food resource for fish and predatory zooplankton and regulating phytoplankton through grazing. Its population dynamic follows regular seasonal patterns, with spring peaks followed by summer population declines (midsummer declines, MSDs). Midsummer declines show high inter‐annual variation, which has been attributed to different causes. However, the mechanisms controlling the MSD remain poorly understood, especially in deep stratified lakes.We tried to disentangle the factors causing Daphnia MSDs in Lake Lugano and Lake Iseo (in Switzerland and Italy), two deep peri‐alpine lakes with similar trophic status and vertical mixing dynamics, characterised by phosphorus accumulation in the hypolimnion and variable mixing during late‐winter turnovers.Specifically, we assessed the effects of three different hypothetical pathways according to which: (1) winter air temperature controls MSDs by influencing mixing depth during turnovers and epilimnetic phosphorus replenishment; (2) vernal air temperature influences MSD by accelerating the timing of spring population peak; and (3) summer temperature influences MSDs by increasing fish predation. We assessed the relative strength of these pathways using structural equation modelling on long‐term datasets for the two lakes (29 years for Lake Lugano and 19 years for Lake Iseo).Between the hypothesised pathways, the one driven by winter air temperature (through P replenishment) influenced Daphnia abundance in spring in both lakes, but the effects propagated to summer Daphnia abundance only in Lake Lugano. Additionally, summer Daphnia abundance was influenced by the summer air temperature through a positive (although weak) effect. By comparison, vernal air temperature had no detectable effects on summer Daphnia abundance.The results revealed marked differences between the meromictic study lakes and the shallow hypertrophic water bodies that were the focus of previous research on Daphnia MSD, and also between the two study lakes. The influence of epilimnetic P replenishment on the summer Daphnia abundance in Lake Lugano, which was recovering from past eutrophication, may have reflected the greater susceptibility of deep, stratified lakes to P depletion after spring compared to shallow hypertrophic lakes or reservoirs. This effect might not have been detected in Lake Iseo because P was more consistently depleted during the study period (i.e. variance in the predictor was too low to detect an effect).This study highlighted the complexity of the effects of climate variability on Daphnia MSD in deep lakes, showing that the responses can differ even between two neighbouring lakes with similar vertical mixing dynamics and trophic status. At the same time, the results suggest that future increases in winter air temperature, caused by global warming, may cause critically low densities of Daphnia during spring and summer and compromise the ability of zooplankton to control phytoplankton biomass. [ABSTRACT FROM AUTHOR]

Soil moisture plays a key role in land-atmosphere interaction systems. Although it can be estimated through in situ measurements, satellite remote sensing, and hydrological modelling, using indicators to index soil moisture conditions is another useful way. In this study, one of these indicators, the antecedent precipitation index (API), is explored. Modifications were proposed to the conventional version of API by introducing two parameters to make it more in line with the physical process. First, the recession coefficient is allowed to vary with the change of air temperature, which could take into account the variation of the evapotranspiration process. Second, the API value is restricted by the maximum value of API, accounting for the maximum water holding capacity of the soil. The modified API was then calibrated and validated by comparing with the in situ measured soil moisture. The better correlation between these two datasets demonstrates that the modified API could better indicate soil moisture conditions, compared with the conventional API. The capability of the modified API to index soil moisture conditions was further explored by applying it to landslide predictions in the Emilia-Romagna region, northern Italy. Here, the recent 3-day rainfall vs the antecedent soil wetness thresholds (RS thresholds) were constructed, in which the soil wetness is indexed by the modified API. The validation of RS thresholds was carried out with the use of the contingency matrix and receiver operating characteristic (ROC) curves. By comparing the prediction performance between RS thresholds and rainfall thresholds, it is found that RS threshold could provide better prediction capabilities in terms of higher hit rate and lower false alarm rate. The positive results indicate that the modified API could provide superior performance of indexing soil moisture conditions, demonstrating the effectiveness of the proposed modifications. [ABSTRACT FROM AUTHOR]

Enhanced temperature-index distributed models for snowpack simulation, incorporating air temperature and a term for clear sky potential solar radiation, are increasingly used to simulate the spatial variability of the snow water equivalent. This paper presents a new snowpack model (termed TOPMELT) which integrates an enhanced temperature-index model into the ICHYMOD semi-distributed basin-scale hydrological model by exploiting a statistical representation of the distribution of clear sky potential solar radiation. This is obtained by discretizing the full spatial distribution of clear sky potential solar radiation into a number of radiation classes. The computation required to generate a spatially distributed water equivalent reduces to a single calculation for each radiation class. This turns into a potentially significant advantage when parameter sensitivity and uncertainty estimation procedures are carried out. The radiation index may be also averaged in time over given time periods. Thus, the model resembles a classical temperature-index model when only one radiation class for each elevation band and a temporal aggregation of 1 year is used, whereas it approximates a fully distributed model by increasing the number of the radiation classes and decreasing the temporal aggregation. TOPMELT is integrated within the semi-distributed ICHYMOD model and is applied at an hourly time step over the Aurino Basin (also known as the Ahr River) at San Giorgio (San Giorgio Aurino), a 614 km 2 catchment in the Upper Adige River basin (eastern Alps, Italy) to examine the sensitivity of the snowpack and runoff model results to the spatial and temporal aggregation of the radiation fluxes. It is shown that the spatial simulation of the snow water equivalent is strongly affected by the aggregation scales. However, limited degradation of the snow simulations is achieved when using 10 radiation classes and 4 weeks as spatial and temporal aggregation scales respectively. Results highlight that the effects of space–time aggregation of the solar radiation patterns on the runoff response are scale dependent. They are minimal at the scale of the whole Aurino Basin, while considerable impact is seen at a basin scale of 5 km 2. [ABSTRACT FROM AUTHOR]

Mobile monitoring can offer data of high spatial resolution within various urban contexts. Yet, devising efficient monitoring protocols for mobile campaigns is still a challenge. Relevant studies typically follow protocols based on the accumulated knowledge of authors and not standardized protocols. Thus the results may be prone to biases. Here, we present a transect monitoring methodology focused on urban areas' thermal environment and air quality. The methodology follows a specific protocol for choosing the monitoring days and evaluating post-process corrections of the retrieved data and is applied within a city in central Italy at a seasonal scale with respect to the Sky View Factor. The presented method is simple, yet comprehensive and can be easily applied to almost any city and urban context. Results showed significant variations of the parameters measured, i.e. air temperature, humidity, short-wave radiation, wind speed, CO 2 and PM10. For example, differences of air temperature within the same city may be up to 5.1 °C in autumn and differences of short-wave radiation may be up to 501 W/m 2 in spring. The results of this study enhance the understanding of how to efficiently assess the quality of urban environments. As such, they could serve as a catalyst for developing mobile monitoring protocols, with the goal of enhancing the evaluation of urban environmental quality. • A simple yet comprehensive mobile monitoring technique for almost any city is presented. • A protocol for post-processing the data is evaluated. • An evaluation of the thermal environment and air quality of a historical city in Italy is presented. • The evaluation of the variables is performed with respect to seasonality and urban geometry. • A reverse thermal stress is found within the suburbs as compared to the city-center. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study was to evaluate the relationship between high air temperatures and occupational injuries (OIs) occurred during the summer seasons 2000-2013 in agricultural workers from the Autonomous Province of Trento (APT), North-Eastern Italy.Material and Methods: Data about OIs for the APT from 2000 to 2013 occurring during the warm season (N = 7325) was provided by the National Institute of Insurance for Occupational Illness and Injury. Daily average and daily maximum temperatures values for the specific geographical site of events were retrieved. Daily temperatures were then assessed in 3 time lags: for the day of the event (lag 0), and for the previous 24 h (lag 1) and 48 h (lag 2). Daily temperatures were then categorized in 3 exposure groups (< 75th, 75-95th and > 95th percentiles). The risk of OIs was assessed as odds ratio (OR) calculated through a Poisson regression model controlled for age, sex, ethnicity and time period, and assuming OI rates for days on which temperature was comprised in < 75th percentile exposure groups as the referent ones.Results: Estimated incidence of OIs during the study period was 3.4±2.3 events/day. The peak of work-related accidents occurred on days characterized by severe thermal conditions, and in particular during heat waves (incidence rate ratio = 1.09, 95% confidence interval (CI): 1.02-1.17, p = 0.0165). Days having temperatures higher than 95th percentile, assessed as daily average, both on current days (OR = 1.119, 95% CI: 1.008-1.242) and in lag 1 (OR = 1.125, 95% CI: 1.013-1.249), as well as daily maximum temperatures, were at the highest risk of work-related injuries (OR = 1.144, 95% CI: 1.029-1.272).Conclusions: In conclusion, presented findings recommend policymakers to develop appropriate warning/alert systems for agricultural workers regarding high environmental temperatures. Int J Occup Med Environ Health 2018;31(3):317-331. [ABSTRACT FROM AUTHOR]

ABSTRACT: This study provides an assessment of recent changes in near‐surface air temperature over the central Adriatic region of Italy, focusing on extreme events at annual and seasonal scales. It investigates trends in selected indices calculated from quality controlled and homogenized daily temperature data recorded from 1980 to 2012 at 34 meteorological stations distributed over the territory. The results reveal overall warming tendencies, particularly pronounced in spring and summer, with significant increases in the duration of warm spells (WSDI) and in the frequency of warm days (TX90p) and warm nights (TN90p), summer days (SU) and tropical nights (TR). Moreover, cold‐related extremes (cold spell duration (CSDI), cool days (TX10p) and cool nights (TN10p), frost days (FD) and icing days (ID)) show significant reductions, although of lower magnitudes, thus confirming the recent warming over the study domain. Prevalent increasing tendencies are also observed for absolute extreme temperature indices (highest and lowest daily values of maximum and minimum temperatures), but with more mixed and less uniform spatial patterns. Finally, the influence of large‐scale circulation modes on temperature extremes is examined. The results highlight the presence of significant correlations between most of the selected extreme temperature indices and the East‐Atlantic pattern, in particular for the warm season. [ABSTRACT FROM AUTHOR]

ABSTRACT: During the last few decades, weather circulation type classifications (CTCs) have been widely used to gain insight into processes at the synoptic scale, but also for studying the relationship between atmospheric circulation and surface climate variability. This study aims to evaluate the best performing CTCs based on COST733 software for the stratification of daily ground‐level precipitation and surface air temperature across Italy by means of four statistical metrics. Six classification methods belonging to the four COST733 groups (threshold‐based, PCA‐based, leader algorithms and optimization algorithms) were investigated on 32 and 26 data time series derived from Italian weather stations for daily mean temperature and daily mean precipitation, respectively. CTCs were computed using gridded mean sea level pressure and geopotential height at 500 hPa derived from the NCEP Reanalysis 2 dataset between 1979 and 2015 and tested on three different numbers of classes (8/9, 11/12 and 18 circulation types). Evaluation metrics showed an evident seasonal variability and high‐spatial heterogeneity reflecting the geographical complexity of the Italian territory. The study points out that the best classification, both for temperature and precipitation, is strongly dependent on the classification variable (mean sea level pressure and geopotential height at 500 hPa) showing relevant differences between surface temperature and precipitation. A low number of circulation types (8/9) resulted as the most appropriate grouping for the Italian domain and the Principal Component Transversal and Simulated Annealing were the best performing classification procedures for ground‐level precipitation and temperature stratification, respectively. [ABSTRACT FROM AUTHOR]

Climate change has become an important issue for scientific community, for its numerous impacts, especially on agriculture and environment. To shed light on this phenomenon, long data-sets of meteorological data as well as temperature and rainfall extreme events are needed, since they are important climate variability indicators. In a small semi-agricultural catchment of the Italian Apennines, drained by the Centonara Stream, weather data have been monitored for 30 years (1986-2015). Here, their trend was identified with Mann-Kendall test, and the temperature and precipitation extremes were characterized by means of specific indices. Data were analyzed at event, daily, seasonal, and annual bases. In addition, to understand implications of rainfall patterns on catchment hydrological response, a total of 388 rainfall-streamflow events (recorded during 1994-2009) were analyzed. Results showed a significant increase of temperature (minimum (Tn), mean (Tm), and maximum (Tx)), both at annual and seasonal base, except for Winter, with an annual mean increase of 0.08, 0.09, and 0.13 °C year for Tn, Tm, and Tx, respectively. Annual rainfall data showed a positive trend for the number of wet days, but not in the quantity. In Winter, the rainfall amount and the number of wet days increased. The annual number of rainfall extreme events ( P > 20.2 mm and D > 18.3 h) significantly increased, especially in spring and autumn. The rainfall-streamflow relationship suggested that the flow response of the Centonara Stream depends mainly on the rainfall amount. So, since the number of extreme events ( P > 20.2 mm) is increasing in spring and autumn, an increase of events with high streamflow in these seasons may occur. [ABSTRACT FROM AUTHOR]

ABSTRACT The analyses of temperature extremes can be very useful because they are highly representative of the climatic tendency of an area. In this study, 19 temperature series registered in southern Italy have been analysed for detecting trends through the Mann-Kendall non-parametric test. The tendencies have been detected since 1951 for the maximum and minimum monthly temperatures and for several indices of daily extremes. As a result, the minimum and maximum monthly temperatures mainly denote a positive trend for spring and summer months and a marked negative one in September. Moreover, the trend analysis on the extreme temperature indices shows opposite behaviours: a clear positive tendency in the frequency and intensity of the highest values and some negative trends for the lowest ones. [ABSTRACT FROM AUTHOR]

With the aim of evaluating the influence of glacial meltwater signature on tree-ring stable isotopes, we analysed δ18 O and δ13 C in the tree rings of Larix decidua Mill. specimens growing in the area of an ice-contact lake ( Lago Verde, at Miage Glacier, European Alps). Additionally, we analysed δ18 O in the glacial meltwater of the lake and of the glacier stream and compared it with the δ18 O of precipitation predicted by a spatial model. We found that tree-ring cellulose of trees fed by glacial meltwaters ( LVW site) is significantly more depleted in δ18 O than at a control site LVM (−0.91‰) fed only by precipitation, thus reflecting the measured higher depletion of glacial meltwaters with respect to local precipitation. δ13 C values did not show significant differences in mean values between the two sites but an anomalous correlation with summer temperature was found at the LVW site, probably due to the different responses of trees stomatal conductance. Over the 30-year period of analysis, four years at LVW (1992, 1995, 2003 and 2009) were markedly depleted in δ18 O. These years are those when the highest summer temperatures were recorded in the area (the ones during which glacier ablation usually increases and more depleted meltwaters fill the lake), with the exception of 1995 during which high water levels occurred following the year with the second highest summer temperature (1994). Overall, our analysis demonstrates that tree-ring δ18 O, driven by the glacial meltwater signature in the lake, can be used for detecting past major glacier runoff events. The proposed approach could also be used for quantifying past glacier runoff and for defining past distribution areas of glacial meltwaters in glacier forefields, thus contributing to past environmental reconstructions and to hazard assessment. [ABSTRACT FROM AUTHOR]

Abstract: The response of both microbial activities and prokaryotic abundances to environmental variability was studied in a transitional Mediterranean system (Oliveri–Tindari, Italy) during two yearly surveys (1997–'98 and 2005–'06). The total enzymatic (leucine aminopeptidase, β-glucosidase, alkaline phosphatase) and respiratory activity rates as well as of the abundances of total prokaryotes, culturable heterotrophic bacteria, faecal coliforms and enterococci were measured in surface waters of four brackish ponds, together with temperature, salinity, dissolved oxygen, pH, inorganic nutrients, chlorophyll-a and particulate organic carbon and particulate nitrogen determinations. The seasonal and interannual patterns of microbial parameters were investigated in relation to environmental variations. Both the microbial activities and the abundances of culturable heterotrophic bacteria, faecal coliforms and enterococci varied significantly among the ponds, reflecting their haline and trophic variability. Significant seasonal and interannual variations were found in the patterns of microbial activity, but not in total prokaryotic abundance, in response to temperature, dissolved oxygen and trophic changes. Microbial parameters showed a different response to environmental variability in the two examined periods: during 1997–'98, increases in the microbial activity rates and culturable bacterial counts were positively related with the trophic changes, while during 2005–'06 the patterns of leucine aminopeptidase, alkaline phosphatase and respiratory activities and of total prokaryotic and culturable bacteria abundances were uncoupled with those of temperature, salinity, dissolved oxygen, particulate organic carbon and chlorophyll-a. Changes in the relative importance of environmental and trophic variables between the two considered periods explain this discrepancy. [Copyright &y& Elsevier]

This work presents a functional clustering procedure applied to meteorological time series. Our proposal combines time series interpolation with smoothing penalized B-spline and the partitioning around medoids clustering algorithm. Our final goal is to obtain homogeneous climate zones of Italy. We compare this approach to standard methods based on a combination of principal component analysis and Cluster Analysis (CA) and we discuss it in relation to other functional clustering approaches based on Fourier analysis and CA. We show that a functional approach is simpler than the standard methods from a methodological and interpretability point of view. Indeed, it becomes natural to find a clear connection between mathematical results and physical variability mechanisms. We discuss how the choice of the basis expansion (splines, Fourier) affects the analysis and propose some comments on their use. The basis for classification is formed by monthly values of temperature and precipitation recorded during the period 1971-2000 over 95 and 94 Italian monitoring stations, respectively. An assessment based on climatic patterns is presented to prove the consistency of the clustering and a comparison of results obtained with different methods is used to judge the functional data approach. [ABSTRACT FROM AUTHOR]

A statistical calibration scheme is applied to multi-model global seasonal ensemble reforecasts in order to predict the interannual variability of summer averaged surface maximum temperature over Italy. In some cases, this technique is shown to be able to improve the skill scores of the seasonal predictions during the last 35 years, with respect to the direct model output (DMO), using seasonal predictions initialised 1 month before the beginning of the season. It is shown that the presence of some skill in the DMO multi-model predictions is mostly due to the correct prediction of the observed secular trends in maximum temperature, and, partly, to the correct prediction of outliers, in particular, of the summer of 2003. At the same time, while the removal of trends produces a small reduction of skill in both the raw and calibrated predictions, the removal of outliers improves the performance of the calibration scheme. Once all trends and outliers are removed, the DMO predictions have no skill, while the calibrated predictions still present a detectable skill. The improvement introduced by the calibration are shown to be statistically significant by applying resampling techniques. It is shown that the reason of this partial success is linked to the fact that although the models present several shortcomings, some models can capture the existence of a weak large-scale signal, possibly linked with the presence of a summer teleconnection between the equatorial Pacific and Europe, with a spatial pattern substantially different from that associated with the temperature secular trend. The teleconnection is associated with a modulation of the quasi-stationary barotropic eddies in the Northern Hemisphere extra-tropics. [ABSTRACT FROM AUTHOR]

This study evaluates the accuracy of daily reference evapotranspiration (ET o), computed according to the FAO Penman-Monteith equation by using a set of input weather variables obtained by blending ERA5-Land (ERA5L) reanalysis data with surface incoming solar radiation (R s) provided by the instruments on board the Meteosat geostationary satellites, operationally delivered by the Satellite Applications Facility on Climate Monitoring (CM-SAF). Performance assessment was carried out in Sicily (southern Italy) by using data from 38 automatic ground weather stations (AWSs) for years 2003–2020. ERA5L and CM-SAF data were first downscaled and bias-corrected with a calibration dataset; ERA5L air temperature data were also downscaled by lapse-rate correction. ET o estimates obtained with the blended ERA5L and CM-SAF validation dataset (ERA5L+CM-SAF) were compared with two other ET o estimates respectively obtained by using ERA5L and interpolated ground weather data (IGD). Performance indicators of the IGD dataset were evaluated by recursively applying universal kriging or ordinary kriging to the observed weather data, according to a cross-validation procedure. R s provided by CM-SAF outperformed R s obtained by ground interpolation, thus confirming the convenience of using bias-corrected CM-SAF data even when ground observations are available in the study area. ET o estimates with ERA5L+CM-SAF showed a normalized RMSE of 12%, outperforming ERA5L ET o estimates while performing comparably to ET o estimates obtained with the IGD dataset. The results suggested that the proposed blended dataset is a good proxy for interpolated ground weather observations in the assessment of ET o at regional scale when weather measurements cannot be easily gathered or in data-sparse regions. • Shortwave radiation by CM-SAF outperforms ERA5-Land shortwave radiation. • ET o is estimated by blending CM-SAF satellite-based radiation and ERA5-Land data. • ET o computed by the blended dataset is as accurate as ET o by interpolated ground data. • Blended datasets are good proxy for interpolated observations in data-sparse regions. • Shortwave radiation by CM-SAF outperforms spatially interpolated pyranometer data. [ABSTRACT FROM AUTHOR]

• Geochemical study on the fluids discharged in the Cotronei-Caccuri area. • Three different approaches to water geothermometry were adopted. • Geothermal conceptual model was reconstructed. • Implications for: seismo-geochemical studies and exploitation of geothermal resources. Geochemical, geological, and hydrological data suggest, for the Cotronei-Caccuri thermal area (Northern Calabria – Southern Italy), the presence of a deep primary geothermal aquifer hosted in the crystalline basement (at Ponte Coniglio) and two secondary aquifers (at Bruciarello and Repole) developed in the Miocene sedimentary succession. Despite the spatial proximity of the three thermal sites, the waters have different compositions: Na(Ca)-Cl for Ponte Coniglio-Cotronei, Na(Ca)-Cl(SO 4) for Bruciarello and Na-SO 4 (Cl) for Repole. The composition of the Cotronei-Ponte Coniglio end-member was reconstructed based on conservative constituents and resulted in a Cl concentration of about 1700 mg kg−1. The thermal waters of Bruciarello and Repole are derived from this primary fluid. Geothermometric calculations support a possible dilution affecting the waters studied to different degrees. For the pure (undiluted) thermal end-member, hosted in the primary granitic aquifer, comparable temperature estimations are provided by cationic geothermometers (67 ± 4 °C) and geothermometric simulations (65 ± 4 °C). However, Bruciarello and Repole waters are in equilibrium with anhydrite and fluorite at a temperature (68.5 ± 4 °C) very similar to that obtained for the granitic aquifer suggesting slight cooling during the travel from the primary granitic aquifer and fast equilibration with anhydrite and fluorite favoured by the rapid dissolution kinetics of these solid phases. From the isotopic point of view, the secondary aquifers have δ34S S(6+) values (+23.01‰ and +22.77‰ ± 0.23‰) comparable with those of the Messinian gypsum (average of +21.8‰). The thermal waters of Cotronei, on the other hand, show enriched δ34S S(6+) values (+38.60‰ ± 0.78‰) due to bacterial reduction of sulfate probably also derived from by Messinian evaporates. Furthermore, the δ18O and δ2H values indicate a meteoric origin for all three thermal sites with an average infiltration altitude of about 1650 – 1850 m asl, which agree with the Sila plateau elevations. Based on the results obtained in this work, assuming a geothermal gradient of about 33 °C/km, a temperature of the deep thermal reservoir of about 65 °C and an average predicted atmospheric temperature of 6 °C in the recharge area (Sila plateau), it follows that the meteoric waters descend to depths of ∼1800 m, where the thermal aquifer of interest is presumably located. This depth is consistent with the location of the primary geothermal reservoir within the crystalline basement. The reconstruction of this conceptual model has been made possible thanks to adopting a "local" approach integrating previously existing and new geological, hydrogeological, and geochemical data. Furthermore, this study has allowed us to identify the presence of an important regional geothermal aquifer hosted in the crystalline basement that, in addition to the carbonate and Upper Triassic evaporite reservoirs (well characterized in previous works), make the Calabria region of high geothermal interest. [ABSTRACT FROM AUTHOR]

Abstract: Climate changes has become one of the most analysed subjects from researchers community, mainly because of the numerous extreme events that hit the globe. To have a better view of climate changes and trends, long observations time series are needed. During last decade a lot of Italian time series, concerning several surface meteorological variables, have been analysed and published. No one of them includes one of the longest record in Italy, the time series of the Geophysical Observatory of the University of Modena and Reggio Emilia. Measurements, collected since early 19th century, always in the same position, except for some months during the second world war, embrace daily temperature, precipitation amount, relative humidity, pressure, cloudiness and other variables. In this work we concentrated on the analysis of yearly and seasonal trends and climate extremes of temperature, both minimum and maximum, and precipitation time series, for the periods 1861–2010 and 1831–2010 respectively, in which continuous measurements are available. In general, our results confirm quite well those reported by IPCC and in many other studies over Mediterranean area. In particular, we found that minimum temperature has a non significant positive trend of +0.1°C per decade considering all the period, the value increases to 0.9°C per decade for 1981–2010. For maximum temperature we observed a non significant +0.1°C trend for all the period, while +0.8°C for the last thirty years. On the other hand precipitation is decreasing, -6.3mm per decade, considering all the analysed period, while the last thirty years are characterised by a great increment of 74.8mm per decade. For both variables several climate indices have been analysed and they confirm what has been found for minimum and maximum temperatures and precipitation. In particular, during last 30years frost days and ice days are decreasing, whereas summer days are increasing. During the last 30-year tropical nights and warm spell duration indices are characterised by a particular strong increment, if compared to the ones of the entire period. Finally, a cursory comparison between winter precipitation and NAO index was done, showing a high anti-correlation, especially since the second half of 20th century. [Copyright &y& Elsevier]

Abstract: National Forest Inventories (NFIs) provide quantitative information on forest area, volume, growing stock and composition at national level but in most cases these data cannot be directly linked with geographical or climatic data sources, such as temperature and precipitation. Assuming that NFIs represent the most useful source of data to evaluate area, volume, age class distribution and composition of forests, the objective of this work was to combine these data with the geo-referenced data provided by CORINE (Coordination of Information on the Environment) and with other data on local climatic conditions. This is a necessary prerequisite for a long-term project aimed at the application of a full carbon accounting approach at European level. The approach was applied to the Italian NFI, assumed as a representative example at European level. Maps of temperature and precipitation classes were projected over a CORINE map and over the Italian administrative units defined at Nuts 2 level. The resulting combinations of precipitation and mean temperature values were used to define 24 climatic land units (CLUs). The results were validated against data provided by 111 weather stations in 3 different administrative regions. The proportion of NFI forest area associated with each CLU at regional level, divided into broadleaved, coniferous and mixed forests, was estimated on the basis of CORINE data. Because this approach maintained all the information reported by NFI linking them to climatic data, both the final forest area and the distribution of forest types at national level were also maintained, avoiding any inconsistency with data directly provided by CORINE. This also ensured full consistency with the forest threshold parameters applied at national level and with the application of these data to international reporting documents (i.e. the UNFCCC report on LULUCF). The approach can easily be applied to every other European country, linking data reported by NFI with other land use geo-referenced data and with climatic data. In the meantime, maintaining the supra-national classification system proposed by CORINE, the results could be more consistently compared across national borders. [Copyright &y& Elsevier]

Abstract: The present study aimed to investigate the possible role played by environmental temperature in modulating circadian preference, collecting data in Italy and India. We chose these countries because of extremely different mean maximum temperatures. The reduced version of the Morningness–Eveningness Questionnaire (MEQr) was administered to 1462 young adults (479 males and 983 females; 952 Italians and 510 Indians), ranging in age between 18 and 28years. Considering morningness–eveningness preference as a continuum, in the whole sample females gained higher MEQr scores than males, indicating a preference towards morningness. Indians reported significantly higher MEQr scores than Italians. Moreover Italian females showed significantly higher MEQr scores than Italian males, while this difference was not observed between Indian females and males. These results have been confirmed also when chronotypes as categories were considered. On the whole our results highlight a significantly different distribution of circadian preference in the two countries, with higher prevalence of morningness in India and eveningness in Italy. The present findings are discussed in relation to the higher environmental temperatures in India in comparison to Italy. [Copyright &y& Elsevier]

Abstract: The longest series of instrumental observations have a number of problems in the early period. This paper is focused on the recovery of early indoor and outdoor observations in Padua and their transformation in terms of a modern series. The Padua series was started by Giovanni Poleni with outdoor observations in 1716–1718, but soon, the readings passed indoors (1725–1764) to join the directives of the Royal Society, London. The indoor readings were recovered within the EU project IMPROVE, but it was necessary to transform indoor observations into outdoor ones, and this was possible thanks to the presence of simultaneous indoor and outdoor observations by Morgagni in Padua and Beccari in Bologna. These parallel series were also useful to fill a short gap. Another problem was to reconstruct the calibration of the Amontons thermometer, which changed when Poleni moved to a new house. Also the problem of the use of variable and/or different sampling times was solved making reference to the trend of the daily cycles in the different seasons and under diverse weather conditions. The data analysis has shown a trend that appears similar to the well-known results (IPCC 2007) for the last 160yr but a less marked recent warming for winter and autumn. The 18th century was characterized by cold winters (culminated 1709 and 1740) and springs, and warm summers and autumns. A well-marked Bruckner cycle (35.8yr), continually repeated and attenuated, is visible for the period 1716–1930. The wide time scale and the repetition of warmer and colder periods over two-thirds of the series noted in Padua and other Mediterranean stations may induce us to suppose that such cycles could continue in the future, at least on the local scale. [Copyright &y& Elsevier]

A few concurrent and/or counteracting factors (increase of average air temperature, rainfall shortage, drought, CO2 enrichment, ozone, nitrogen fertilization, sulphate deposition) drive today the soil-tree-atmosphere relationships in the Mediterranean area. Radial stem growth measured within the ICPForests level II Italian network provides a sensitive response to these occurrences. Climate fluctuations and repeated anomalous seasons or extreme events are the major evidences of the change in progress. The 2003 heat wave is the main event occurred in this decade over large part of Europe. In Italy, it provoked a marked water deficit coupled to high air temperature, which resulted in a heavy water stress. The growth performance in different forest types was analyzed in this paper: growth rate in 2000-2004, compared with 1997- 1999, showed reductions up to 50% on half of the plots examined. Most of them were: (i) in northern-central Italy within the southern continental border of the climatic deviation; (ii) at low elevation, which is more sensitive to high air temperature and drought; (iii) made up of deciduous broadleaved forests (beech and oaks), i.e., species showing growth effects also in the following year. Over the time-window 2005-2009, a significant growth decrease was vice-versa detected within the coniferous spruce forests located at medium- high elevation in the Alps. Repeated seasonal deviations in temperature and rainfall were recorded in the Alps in 2005-2009. Climate effects at local scale were examined in a site where two oak species with a different auto-ecology (sessile oak and Turkey oak) grow together. The on-going change produced heavy mortality and reduced the growth of the more demanding and less drought-tolerant sessile oak; in a few years Turkey oak became prevailing in the stand composition and structure. [ABSTRACT FROM AUTHOR]

Abstract: Viscosities of shoshonitic and latitic melts, relevant to the Campi Flegrei caldera magmas, have been experimentally determined at atmospheric pressure and 0.5GPa, temperatures between 840K and 1870K, and H2O contents from 0.02 to 3.30wt.%. The concentric cylinder technique was employed at atmospheric pressure to determine viscosity of nominally anhydrous melts in the viscosity range of 101.5 −103 Pas. The micropenetration technique was used to determine the viscosity of hydrous and anhydrous melts at atmospheric pressure in the high viscosity range (1010 Pas). Falling sphere experiments were performed at 0.5GPa in the low viscosity range (from 100.35 to 102.79 Pas) in order to obtain viscosity data of anhydrous and hydrous melts. The combination of data obtained from the three different techniques adopted permits a general description of viscosity as a function of temperature and water content using the following modified VFT equation: where η is the viscosity in Pa·s, T the temperature in K, w the H2O content in wt.%, and a, b, c, d, e, and g are the VFT parameters. This model reproduces the experimental data (95 measurements) with a 1σ standard deviation of 0.19 and 0.22 log units for shoshonite and latite, respectively. The proposed model has been applied also to a more evolved composition (trachyte) from the same area in order to create a general model applicable to the whole compositional range of Campi Flegrei products. Moreover, speed data have been used to constrain the ascent velocity of latitic, shoshonitic, and trachytic melts within dikes. Using petrological data and volcanological information (geometrical parameters of the eruptive fissure and depth of magma storage), we estimate a time scale for the ascent of melt from 9km to 4km depth (where deep and shallow reservoirs, respectively, are located) in the order of few minutes. Such a rapid ascent should be taken into account for the hazard assessment in the Campi Flegrei area. [Copyright &y& Elsevier]

Plant traits of Malcolmia littorea growing at the Botanic Garden of Rome and transplanted from the wild population developing along the Latium coast (Italy) were analyzed. The highest photosynthetic rates [ P, 22.5 ± 0.5 μmol(CO) m s], associated to the highest chlorophyll content (Chl, 60 ± 5 SPAD units), and respiration rates [ R, 11.1 ± 0.2 μmol(CO) m s] were reached in spring, when mean air temperature ( T) was in the range 17°C to 23°C. P, Chl, and R decreased by 86, 38, and 59% in summer when mean maximum air temperature ( T) was 30.3 ± 2.6°C. Leaf water potential decreased by 34% in summer compared to the spring value, and it was associated to a relative water content (RWC) of 74 ± 4%, and to a water-use efficiency (WUE) of 2.15 ± 0.81 μmol(CO) mmol(HO). Moreover, also low air temperatures determined a significant P and R decreases (by 52 and 40% compared to the maximum, respectively). Responsiveness of gross photosynthetic rate ( P) to R was higher than that to P as underlined by the slope of the regression line between the two variables. The results underlined a low tolerance to both high- and low air temperatures of M. littorea. The selected key traits ( R, WUE, Chl) by the discriminant analysis might be used to monitor the M. littorea wild population in the long time. The ex situ cultivated plants could be propagated and used to increase the individuals number of the wild population. [ABSTRACT FROM AUTHOR]

The article presents a research study that deals with the accuracy of the surface high-resolution temperature forecast for the Calabria region, Italy. Researchers have exerted their efforts in quantifying the forecast errors that have been gathered through cumulative statistical method. They used Optimal Interpolation's gridded analysis to determine the region's maximum and minimum temperature.

The article presents a study which evaluates the climatic change projections of Italy based on the CMIP3 and PRUDENCE datasets. It mentions that the study focuses on precipitation, changes in the season-average quantities, and air temperature. It states that the climatic change signal in Italy changes seasonally wherein maximum warming and decreased precipitation were noticed during summer. Results of the study shows that the dataset models used separates multi-decadal variability.

Abstract: Adsorption equilibria of water and ethanol vapors on a zeolitized tuff from Campania (Southern Italy), containing both phillipsite and chabazite, were studied. The adsorption isotherms of both compounds on a tuff sample with a grain size ranging from 120 to 60mesh and having a total zeolite content of 40% were determined at temperatures of 20, 40, 60 and 80°C and furthermore the same isotherms were determined at T =20°C and T =80°C on two other samples of the same tuff, having zeolite contents of 18% and 68% and grain size distributions in the ranges >120mesh and 60×35mesh, respectively. The experimental results were satisfactorily interpreted in terms of the pore filling Dubinin–Astakhov model. The model used allowed to estimate the micropore volume of the three grain size fractions considered (ranging from 36 to 121ml/kg) and the characteristic energy of adsorbate–tuff interaction (about −20kJ/mol for water and about −25kJ/mol for ethanol). Furthermore, the binary (water–ethanol) adsorption isotherms were predicted. The overall results indicated that a strong correlation between zeolitic content of the tuff and adsorption capacity exists and that the selected tuff is very selective towards water, with a molar separation factor in the order of 6–7 if the azeotropic mixture is considered. [Copyright &y& Elsevier]

Abstract: Several types of DNA damage, including DNA breaks and DNA base oxidation, display a seasonal trend. In the present work, a sample of 79 healthy subjects living in the city of Florence, Italy, was used to analyse this effect. Three possible causative agents were taken into consideration: solar radiation, air temperature and air ozone level. DNA damage was measured in isolated human lymphocytes at different times during the year and the observed damage was correlated with the levels of these three agents in the days preceding blood sampling. Three time windows were chosen: 3, 7 and 30 days before blood sampling. DNA strand breaks and the oxidized purinic bases cleaved by the formamidopyrimidine glycosylase (FPG sites) were measured by means of the comet assay. The results of multivariate regression analysis showed a positive correlation between lymphocyte DNA damage and air temperature, and a less strong correlation with global solar radiation and air ozone levels. [Copyright &y& Elsevier]

Discusses the history of the origin of the study of meteorology in Padova, Italy. Connection of Padova series of meteorological observations to the major developments of this science in Italy and the international context; Cultural background that favored the development of meteorology; Plurisecular time series of meteorological observations taken in Padova since 1725; Meteorological factors that are considered in the study including air temperature.

Discusses the data homogenization of the Milan series of meteorological observations based on objective information extracted from station history and on some statistical estimates. Events that could cause inhomogeneities in the temperature series; Causes of the inhomogeneities in the pressure series; Tests used to check possible errors in temperature and pressure series; Result of the application of a step-by-step procedure to homogenize the data.

Focuses on the history of Milan's daily temperature and pressure series. Reconstruction of daily temperature and pressure series for Milan; Recovery and study of information that can be used to evaluate the quality and homogeneity of the data; Homogenization of data on the basis of this information and by comparison with other series; Role of the development of a national meteorological network on Milan series.

The use of a model based on Langmuir's isotherm to evaluate the metal associated with separate geochemical phases of a sediment is proposed and its validity tested with sediments of certified composition. The model takes into account a standard procedure for a certified reference material (CRM601), which defines, experimentally, a set of sequential extractions that divide the sediment into four operational fractions. The derived equations allow the treatment of data from sediment of Flumendosa Lake, Italy, and certified material CRM601 and also allow the computation of corrected concentrations, i.e., the metal affinities for each fraction. Experimental values for Ni show its low sensitivity and an equal distribution among different phases, which suggests a similar adsorption mechanism in all cases. In the case of Cd, the corrected concentration in the Fe/Mn oxide phase is nine times higher than for the residual fraction. For sediment of the Bèsos River, Spain, results show the percentage distribution of Ni over different fractions. Affinity values for Ni on a Flumendosa Lake sediment have also been calculated. The present model is simple to apply and shows satisfactory agreement with experimental data. [ABSTRACT FROM AUTHOR]

The European Bee-eater (Merops apiaster), usually breeding in lower, warm latitudes up to July isotherm of 21°C (Cramp, 1985), has recently begun his expansion in northern Italy. Gregarious throughout the year, the European Bee-eater is a summer visitor in Europe. In 2017 a new breeding colony of four-five breeding pairs, has been found out in mountain habitat facing the plain at 1,250 meters a.s.l. in Italian western Alps, showing his expansion not only in northern latitudes but even in altitudinal environment. [ABSTRACT FROM AUTHOR]

• OVF summer performance was monitored in a full-scale demonstrator in Torino – Italy. • All the analysed façade configurations were compared with an unventilated reference façade. • The influence of façade height, external colour and grill-openings was analysed. • It was found that OVF guarantees higher performance in temperate-subtropical climate. In the last few years opaque ventilated façades (OVFs) have reached an increasing diffusion in the Mediterranean area for their capability of reducing the heat flux across the building envelope in summer conditions as well as preventing the condensation and infiltration risk in the winter period providing wind and rain protection, thus increasing the durability of the façade. Moreover, the possibility to host different cladding allows architects to explore a wide range of façade combinations. In the framework of a regional funded project, an extensive in-field experimental campaign was carried out in the summer period on different full-scale OVF configurations, with the aim of assessing the thermal performance of a newly developed OVF based on hollow clay claddings technology. A sensitivity analysis was thus performed, in order to evaluate, on the one hand, the effect on the performance of the main façade features, e.g. ventilation channel height, solar absorption coefficient and ventilation grills openings ratio, and on the other hand, the influence of the outdoor boundary conditions, e.g. solar radiation and external air temperature. The experimental results highlight that the façade configuration and the design features significantly affect the capability of OVFs on minimising the solar heat loads across the wall (between ~30% and ~70%) if compared to an unventilated façade (representing the reference configuration). These results allow providing general guidelines for an optimised OVF design. Moreover, the assessment of the effect of the outdoor boundary conditions allowed to identify the conditions in which the façade shows the higher exploitation of natural ventilation. [ABSTRACT FROM AUTHOR]

Mercury (Hg) is a global pollutant, being highly persistent in the atmosphere, in particular gaseous elemental mercury (GEM), which can easily be emitted and then transported over long distances. In the Gulf of Trieste (northern Adriatic Sea, Italy), contamination by Hg is well characterised but little is known regarding the concentrations, sources and fate of GEM in the atmosphere. In this work, discrete measurements of GEM were recorded from several sites at different times of the year. The database is consistent with temporal night-day variations monitored using a continuous real-time device. The meteorological conditions were collected as ancillary parameters. GEM levels varied from

Water use efficiency in agriculture can be improved by implementing advisory systems that support on-farm irrigation scheduling, with reliable forecasts of the actual crop water requirements, where crop evapotranspiration (ETc) is the main component. The development of such advisory systems is highly dependent upon the availability of timely updated crop canopy parameters and weather forecasts several days in advance, at low operational costs. This study presents a methodology for forecasting ETc, based on crop parameters retrieved from multispectral images, data from ground weather sensors, and air temperature forecasts. Crop multispectral images are freely provided by recent satellite missions, with high spatial and temporal resolutions. Meteorological services broadcast air temperature forecasts with lead times of several days, at no subscription costs, and with high accuracy. The performance of the proposed methodology was applied at 18 sites of the Campania region in Italy, by exploiting the data of intensive field campaigns in the years 2014–2015. ETc measurements were forecast with a median bias of 0.2 mm, and a median root mean square error (RMSE) of 0.75 mm at the first day of forecast. At the 5th day of accumulated forecast, the median bias and RMSE become 1 mm and 2.75 mm, respectively. The forecast performances were proved to be as accurate and as precise as those provided with a complete set of forecasted weather variables. [ABSTRACT FROM AUTHOR]

Intense convective storms usually produce large rainfall volumes in short time periods, increasing the risk of floods and causing damages to population, buildings, and infrastructures. In this paper, we propose a framework to couple visual and statistical analyses of convective thunderstorms at the basin scale, considering both the spatial and temporal dimensions of the process. The dataset analyzed in this paper contains intense convective events that occurred in seven years (2012–2018) in the Seveso-Olona-Lambro basin (North of Italy). The data has been acquired by MeteoSwiss using the Thunderstorm Radar Tracking (TRT) algorithm. The results show that the most favorable conditions for the formation of convective events occur in the early afternoon and during summertime, confirming the key role of the temperature in atmospheric convection. The orography emerged as a driver for convection, which takes place more frequently in mountain areas. The storm paths analysis shows that the predominant direction is from South-West to North-East. Considering storm duration, long-lasting events reach higher values of radar reflectivity and cover more extended areas than short-lasting ones. The results obtained can be exploited for many practical applications including nowcasting, alert systems, and sensors deployment. [ABSTRACT FROM AUTHOR]

Despite the relevance for occupational safety policies, the health effects of temperature on occupational injuries have been scarcely investigated. A nationwide epidemiological study was carried out to estimate the risk of injuries for workers exposed to extreme temperature and identify economic sectors and jobs most at risk. The daily time series of work-related injuries in the industrial and services sector from the Italian national workers' compensation authority (INAIL) were collected for each of the 8090 Italian municipalities in the period 2006–2010. Daily air temperatures with a 1 × 1 km resolution derived from satellite land surface temperature data using mixed regression models were included. Distributed lag non-linear models (DLNM) were used to estimate the association between daily mean air temperature and injuries at municipal level. A meta-analysis was then carried out to retrieve national estimates. The relative risk (RR) and attributable cases of work-related injuries for an increase in mean temperature above the 75th percentile (heat) and for a decrease below the 25th percentile (cold) were estimated. Effect modification by gender, age, firm size, economic sector and job type were also assessed. The study considered 2,277,432 occupational injuries occurred in Italy in the period 2006–2010. There were significant effects for both heat and cold temperatures. The overall relative risks (RR) of occupational injury for heat and cold were 1.17 (95% CI: 1.14–1.21) and 1.23 (95% CI: 1.17–1.30), respectively. The number of occupational injuries attributable to temperatures above and below the thresholds was estimated to be 5211 per year. A higher risk of injury on hot days was found among males and young (age 15–34) workers occupied in small-medium size firms, while the opposite was observed on cold days. Construction workers showed the highest risk of injuries on hot days while fishing, transport, electricity, gas and water distribution workers did it on cold days. Prevention of the occupational exposure to extreme temperatures is a concern for occupational health and safety policies, and will become a critical issue in future years considering climate change. Epidemiological studies may help identify vulnerable jobs, activities and workers in order to define prevention plans and training to reduce occupational exposure to extreme temperature and the risk of work-related injuries. • Health effects of extreme temperatures on occupational injuries have been scarcely investigated; • We found a significant effect of extreme temperature exposure on occupational injuries risk in Italy; • The identified pattern of susceptible workers could help regulators and governments for developing prevention measures; • Climate change scenarios suggest considering the prevention of extreme temperature occupational exposure as a priority. [ABSTRACT FROM AUTHOR]