0000000000017307
AUTHOR
V. Piazza
Analytic solutions of the diffusion-deposition equation for fluids heavir than atmospheric air
A steady-state bi-dimensional turbulent diffusion equation was studied to find the concentration distribution of a pollutant near the ground. We have considered the air pollutant emitted from an elevated point source in the lower atmosphere in adiabatic conditions. The wind velocity and diffusion coefficient are given by power laws. We have found analytical solutions using or the Lie Group Analysis or the Method of Separation of Variables. The classical diffusion equation has been modified introducing the falling term with non-zero deposition velocity. Analytical solutions are essential to test numerical models for the great difficulty in validating with experiments.
Hourly Forecasting of SO2 Pollutant Concentration Using an Elman Neural Network
In this paper the first results produced by an Elman neural network for hourly SO2 ground concentration forecasting are presented. Time series has been recorded between 1998 and 2001 and are referred to a monitoring station of SO2 in the industrial site of Priolo, Syracuse, Italy. Data has been kindly provided by CIPA (Consorzio Industriale per la Protezione dell'Ambiente, Siracusa, Italia). Time series parameters are the horizontal and vertical wind velocity, the wind direction, the stability classes of Thomas, the base level of the layer of the atmospheric stability, the gradient of the potential temperature and the difference of the potential temperature of reference.
Three Hours Ahead Prevision of SO2 Pollutant Concentration Using an Elman Neural based Forecaster
Abstract Indoor air quality near the industrial site is tightly joined to pollutant concentration level, since outdoor pollution heavily influences air quality and, consequently, inhabitants health. A pollution management system is essential for health protection. Automatic air quality management systems have became an important research issue with strong implications for inhabitants’ health. In this paper an automatic forecaster based on neural networks for SO 2 concentration prevision is proposed. The analyzed area covers different small towns near the industrial site of Priolo, in the south of the world. Among these towns, Melilli was the first town in Italy that was evacuated for high l…
Emergency hernia repair in the elderly: multivariate analysis of morbidity and mortality from an Italian registry
Abstract Purpose The incidence of inguinal hernia is higher in elderly because of aging-related diseases like prostatism, bronchitis, collagen laxity. A conservative management is common in elderly to reduce surgery-related risks, however watchful waiting can expose to obstruction and strangulation. The aim of the present study was to assess the impact of emergency surgery in a large series of elderly with complicated groin hernia and to identify the independent risk factors for postoperative morbidity and mortality. The predictive performance of prognostic risk scores has been also assessed. Methods This is a prospective observational study carried out between January 2017 and June 2018 in…
Frailty and emergency surgery in the elderly: protocol of a prospective, multicenter study in Italy for evaluating perioperative outcome (The FRAILESEL Study)
Improvements in living conditions and progress in medical management have resulted in better quality of life and longer life expectancy. Therefore, the number of older people undergoing surgery is increasing. Frailty is often described as a syndrome in aged patients where there is augmented vulnerability due to progressive loss of functional reserves. Studies suggest that frailty predisposes elderly to worsening outcome after surgery. Since emergency surgery is associated with higher mortality rates, it is paramount to have an accurate stratification of surgical risk in such patients. The aim of our study is to characterize the clinicopathological findings, management, and short-term outcom…
Estimation of biogas produced by the landfill of Palermo, applying a Gaussian model
Abstract In this work, a procedure is suggested to assess the rate of biogas emitted by the Bellolampo landfill (Palermo, Italy), starting from the data acquired by two of the stations for monitoring meteorological parameters and polluting gases. The data used refer to the period November 2005–July 2006. The methane concentration, measured in the CEP suburb of Palermo, has been analysed together with the meteorological data collected by the station situated inside the landfill area. In the present study, the methane has been chosen as a tracer of the atmospheric pollutants produced by the dump. The data used for assessing the biogas emission refer to night time periods characterized by weak…
First outbreak of Pepper vein yellows virus infecting sweet pepper in Italy
Sweet pepper (Capsicum annum) is an economically important crop worldwide, including Sicily where about 4,000 hectares are grown each year. In October 2015, severe symptoms not previously reported by growers in the horticultural area of the province of Trapani (Sicily, Italy) were observed on sweet pepper plants in eight different greenhouses. Symptoms included upward leaf curling, internodal shortening and interveinal yellowing. Symptoms were more evident in the upper part of the plants. These symptoms were reminiscent of those caused by poleroviruses. In the greenhouse, symptoms were evident in about 35% of the plants. Three samples per greenhouse (24 in total) were collected for analysis.
Two-days ahead prediction of daily maximum concentrations of SO2, O3, PM10, NO2, CO in the urban area of Palermo, Italy
Abstract Artificial neural networks are functional alternative techniques in modelling the intricate vehicular exhaust emission dispersion phenomenon. Pollutant predictions are notoriously complex when using either deterministic or stochastic models, which explains why this model was developed using a neural network. Neural networks have the ability to learn about non-linear relationships between the used variables. In this paper a recurrent neural network (Elman model) based forecaster for the prediction of daily maximum concentrations of SO2, O3, PM10, NO2, CO in the city of Palermo is proposed. The effectiveness of the presented forecaster was tested using a time series recorded between …