A site selection model to identify optimal locations for microalgae biofuel production facilities in sicily (Italy)

The lack of sustainability and negative environmental impacts of using fossil fuel resources for energy production and their consequent increase in prices during last decades have led to an increasing interest in the development of renewable biofuels. Among possible biomass fuel sources, microalgae represent one of the most promising solutions. The present work is based on the implementation of a model that facilitates identification of optimal geographic locations for large-scale open ponds for microalgae cultivation for biofuels production. The combination of a biomass production model with specific site location parameters such as irradiance, geographical constraints, land use, topography, temperatures and CO2 for biofuels plants were identified in Sicily (Italy). A simulation of CO2 saved by using the theoretical biofuel produced in place of traditional fuel was implemented. Results indicate that the territory of Sicily offers a good prospective for these technologies and the results identify ideal locations for locating biomass fuel production facilities. Moreover, the research provides a robust method that can be tailored to the specific requirements and data availability of other territories. © Research India Publications

Performance and economic assessment of a grid-connected photovoltaic power plant with a storage system. A comparison between the north and the south of Italy

Grid-connected low voltage photovoltaic power plants cover most of the power capacity installed in Italy. They offer an important contribution to the power demand of the utilities connected but, due to the nature of the solar resource, the night-time consumption can be satisfied only withdrawing the energy by the national grid, at the price of the energy distributor. Thanks to the improvement of storage technologies, the installation of a system of battery looks like a promising solution by giving the possibility to increase auto-consumption dramatically. In this paper, a model-based approach to analyze and discuss the performance and the economic feasibility of grid-connected domestic photovoltaic power plants with a storage system is presented. Using as input to the model the historical series (2008-2017) of the main ambient variables, the proposed model, based on Stochastic Hybrid Fault Tree Automaton, allowed us to simulate and compare two alternative technical solutions characterized by different environmental conditions, in the north and in the south of Italy. The performances of these systems were compared and an economic analysis, addressing the convenience of the storage systems was carried out, considering the characteristic useful-life time, 20 years, of a photovoltaic power plant. To this end the Net Present Value and the payback time were evaluated, considering the main characteristics of the Italian market scenario

PM10 Dispersion Modeling by Means of CFD 3D and Eulerian–Lagrangian Models: Analysis and Comparison with Experiments☆

Abstract This research deals with the analysis of the dispersion of PM10 by using fluid-dynamic simulation framework. Firstly, an experimental campaign was made in a wind tunnel. A cylindrical emitter of PM10 was characterized in terms of PM10 mass flow rate and outlet velocity. It was positioned in the wind tunnel chamber where several sensors were also placed downwind. The use of different sensor configurations allowed the evaluation of the PM10 concentrations in several locations. The experimental campaign was reproduced in ANSYS-Fluent, by recreating in Design-Model, a 3D geometries of the test case. Different calculation grids were tested in order to find the proper balance between computing time and accuracy. The CFD 3D model was based on the Eulerian approach for the continuous phase and Lagrangian approach for the dispersion phase setting the DPM for the evaluation and dispersion of particulate matters. The turbulence was solved by using a k-ɛ RANS approach and a quite advanced unsteady DES model. Several simulations were carried out by varying the flow inlet velocities in configurations with and without obstacles. The results obtained from the post-processing phase were then compared with the experimental campaign. With obstacles a PM concentration increment is observed at all imposed air velocity because of recirculation phenomena generated around the obstacles

Experimental Analysis of a Plume Dispersion Around Obstacles

Abstract Nowadays, transport and deposition of aerosol particles (PM 2.5 , PM 10 , TSP) caused by industrial plants, environmental applications and transports, are of great concern to public health. Despite the establishment by the European Union of emission standards (European directive 2008/50/CE e.g) to control the limits of particulates in the air, the emissions by industrial plants are still not accurately monitored. In particular, the interaction between plume dispersion and obstacles, such as buildings, is not currently well studied. A lot of theoretical researches were carried out in this field with a lack of experimental data comparison. This paper focuses on a laboratory work made to better explain the interaction of a continuous plume released from a point source and various obstacles. First of all a vertical pipe was reproduced, a continuous aerosol emitter was characterized in terms of a specified and controlled mass flow and the ratio between smoke emission and the total suspended particulates thanks to use of the certified gravimetric calculation of PM 10 . The experimental campaigns were conducted by means of a wind tunnel all the data collected were validated. The characterization of plume was made by the use of several sensors and calculation of velocity in several points of the field. Moreover, the plume dispersion was studied also by using digital image analysis. It was then investigated downwind the influence of obstacles of various shapes and distances from source in terms of aerosol concentration in several points

Antecedentes Relacionales de la Innovación en las Empresas Familiares: El Complejo Papel del Compromiso de los Empleados No Familiares

A better understanding of the relational antecedents of innovation in family firms is central to explaining their long-term success and survival. Our study proposes an original model that shows that the internal social capital of non-family members does not always foster innovation directly as existing theory suggests, but through their organizational commitment. These results differ across the different dimensions of organizational commitment. Therefore, our study challenges existing thinking on commitment studies by offering theoretical grounding and empirical evidence that neglected dimensions of commitment have a crucial intermediate role in the relationship between internal social capital and innovation in family firms.Una mejor comprensión de los antecedentes relacionales de la innovación en las empresas familiares es fundamental para explicar su éxito y supervivencia a largo plazo. Nuestro estudio propone un modelo original que muestra que el capital social interno de los no familiares no siempre fomenta la innovación directamente, como sugiere la teoría exis-tente, sino a través de su compromiso organizacional. Estos resultados difieren en las diversas dimensiones del compromiso organizacional. Por lo tanto, nuestro estudio desafía el pensa-miento existente sobre los estudios de compromiso al ofrecer una base teórica y evidencia empírica de que las dimensiones desatendidas del compromiso tienen un papel intermedio crucial en la relación entre el capital social interno y la innovación en las empresas familiares

Theoretical and Experimental Study of Gaussian Plume Model in Small Scale System

Abstract Atmospheric dispersion pollution modelling is of great and actual concern in the scientific international community. Many dispersion models have been developed and used to estimate the downwind ambient concentration of air pollutants from sources such as industrial plants, vehicular traffic or accidental chemical release. Among them, Gaussian model is perhaps the most commonly used model type. It is often used to predict the dispersion of air pollution plumes originated from ground-level or elevated sources. In this research an experimental campaign was carried out in the wind tunnel of the Industrial Engineering Department of University of Catania. It was tested an emission plume of particulate matters and the concentrations of PM 10 were evaluated in several points downwind beyond the emitter. Both the wind velocity and PM 10 mass flow were varied in order to test the differences in terms of PM10 concentrations in the sampling points. A Gaussian plume mathematical model was developed according the boundaries conditions of the experimental campaign. The results of the model were compared with experimental ones in order to identify the limits and the advantages of this model in such a small scale system

Coronary Microvascular Dysfunction Induced by Primary Hyperparathyroidism is Restored After Parathyroidectomy

Background— Symptomatic primary hyperparathyroidism (PHPT) is associated with increased cardiovascular mortality. However, data on the association between asymptomatic PHPT and cardiovascular risk are lacking. We assessed coronary flow reserve (CFR) as a marker of coronary microvascular function in asymptomatic PHPT of recent onset. Methods and Results— We studied 100 PHPT patients (80 women; age, 58±12 years) without cardiovascular disease and 50 control subjects matched for age and sex. CFR in the left anterior descending coronary artery was detected by transthoracic Doppler echocardiography, at rest, and during adenosine infusion. CFR was the ratio of hyperemic to resting diastolic flow velocity. CFR was lower in PHPT patients than in control subjects (3.0±0.8 versus 3.8±0.7; P <0.0001) and was abnormal (≤2.5) in 27 patients (27%) compared with control subjects (4%; P =0.0008). CFR was inversely related to parathyroid hormone (PTH) levels ( r =−0.3, P <0.004). In patients with CFR ≤2.5, PTH was higher (26.4 pmol/L [quartiles 1 and 3, 16 and 37 pmol/L] versus 18 [13–25] pmol/L; P <0.007), whereas calcium levels were similar (2.9±0.1 versus 2.8±0.3 mmol/L; P =0.2). In multivariable linear regression analysis, PTH, age, and heart rate were the only factors associated with CFR ( P =0.04, P =0.01, and P =0.006, respectively). In multiple logistic regression analysis, only PTH increased the probability of CFR ≤2.5 ( P =0.03). In all PHPT patients with CFR ≤2.5, parathyroidectomy normalized CFR (3.3±0.7 versus 2.1±0.5; P <0.0001). Conclusions— PHPT patients have coronary microvascular dysfunction that is completely restored after parathyroidectomy. PTH independently correlates with the coronary microvascular impairment, suggesting a crucial role of the hormone in explaining the increased cardiovascular risk in PHPT

Genetic Architecture of Aluminum Tolerance in Rice (Oryza sativa) Determined through Genome-Wide Association Analysis and QTL Mapping

Aluminum (Al) toxicity is a primary limitation to crop productivity on acid soils, and rice has been demonstrated to be significantly more Al tolerant than other cereal crops. However, the mechanisms of rice Al tolerance are largely unknown, and no genes underlying natural variation have been reported. We screened 383 diverse rice accessions, conducted a genome-wide association (GWA) study, and conducted QTL mapping in two bi-parental populations using three estimates of Al tolerance based on root growth. Subpopulation structure explained 57% of the phenotypic variation, and the mean Al tolerance in Japonica was twice that of Indica. Forty-eight regions associated with Al tolerance were identified by GWA analysis, most of which were subpopulation-specific. Four of these regions co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified QTLs. Three regions corresponding to induced Al-sensitive rice mutants (ART1, STAR2, Nrat1) were identified through bi-parental QTL mapping or GWA to be involved in natural variation for Al tolerance. Haplotype analysis around the Nrat1 gene identified susceptible and tolerant haplotypes explaining 40% of the Al tolerance variation within the aus subpopulation, and sequence analysis of Nrat1 identified a trio of non-synonymous mutations predictive of Al sensitivity in our diversity panel. GWA analysis discovered more phenotype–genotype associations and provided higher resolution, but QTL mapping identified critical rare and/or subpopulation-specific alleles not detected by GWA analysis. Mapping using Indica/Japonica populations identified QTLs associated with transgressive variation where alleles from a susceptible aus or indica parent enhanced Al tolerance in a tolerant Japonica background. This work supports the hypothesis that selectively introgressing alleles across subpopulations is an efficient approach for trait enhancement in plant breeding programs and demonstrates the fundamental importance of subpopulation in interpreting and manipulating the genetics of complex traits in rice

Genome-wide association mapping identifies a new arsenate reductase enzyme critical for limiting arsenic accumulation in plants

Inorganic arsenic is a carcinogen, and its ingestion through foods such as rice presents a significant risk to human health. Plants chemically reduce arsenate to arsenite. Using genome-wide association (GWA) mapping of loci controlling natural variation in arsenic accumulation in Arabidopsis thaliana allowed us to identify the arsenate reductase required for this reduction, which we named High Arsenic Content 1 (HAC1). Complementation verified the identity of HAC1, and expression in Escherichia coli lacking a functional arsenate reductase confirmed the arsenate reductase activity of HAC1. The HAC1 protein accumulates in the epidermis, the outer cell layer of the root, and also in the pericycle cells surrounding the central vascular tissue. Plants lacking HAC1 lose their ability to efflux arsenite from roots, leading to both increased transport of arsenic into the central vascular tissue and on into the shoot. HAC1 therefore functions to reduce arsenate to arsenite in the outer cell layer of the root, facilitating efflux of arsenic as arsenite back into the soil to limit both its accumulation in the root and transport to the shoot. Arsenate reduction by HAC1 in the pericycle may play a role in limiting arsenic loading into the xylem. Loss of HAC1-encoded arsenic reduction leads to a significant increase in arsenic accumulation in shoots, causing an increased sensitivity to arsenate toxicity. We also confirmed the previous observation that the ACR2 arsenate reductase in A. thaliana plays no detectable role in arsenic metabolism. Furthermore, ACR2 does not interact epistatically with HAC1, since arsenic metabolism in the acr2 hac1 double mutant is disrupted in an identical manner to that described for the hac1 single mutant. Our identification of HAC1 and its associated natural variation provides an important new resource for the development of low arsenic-containing food such as rice