As(V)-reduction to As(III) by arsenic-resistant Bacillus spp. bacterial strains isolated from low-contaminated sediments of the Oliveri-Tindari Lagoon,Italy

Five arsenic-resistant bacterial strains designated MT1, MT2, MT3, V1 and V2 were isolated from sediments of the Oliveri-Tindari Lagoon (Italy), which comprises six small lakes whose sediments contain low arsenic concentrations. Phylogenetic analysis of the 16S rRNA gene sequences assigned them to the genus Bacillus. Bacillus sp. strain MT3 showed higher tolerance to As(III) and As(V), as indicated by minimum inhibitory concentrations of 14 and 135 mmol^?1, respectively. Bacillus sp. strain V1 showed growth inhibition at 14 mmol^?1 in the presence of As(III) and at 68 mmol^?1 in the presence of As(V), whereas the arsenic resistance of Bacillus sp. strain MT1 was 10 and 27 mmol^?1 for As(III) and As(V), respectively. The strains Bacillus spp. MT2 and V2 showed low levels of As(III) and As(V) resistance, as it was unable to grow at concentrations>7 and 14 mmol^?1, respectively. The isolated arsenic-resistant Bacillus spp. strains were able to reduce As(V) to As(III), especially Bacillus spp. strain MT3. This study suggests that the isolated bacterial strains play a role in the arsenic biogeochemical cycle of arsenic-poor sediments in the Oliveri-Tindari Lagoon.     

Capacitated location of collection sites in an urban waste management system

Urban waste management is becoming an increasingly complex task, absorbing a huge amount of resources, and having a major environmental impact. The design of a waste management system consists in various activities, and one of these is related to the location of waste collection sites. In this paper, we propose an integer programming model that helps decision makers in choosing the sites where to locate the unsorted waste collection bins in a residential town, as well as the capacities of the bins to be located at each collection site. This model helps in assessing tactical decisions through constraints that force each collection area to be capacitated enough to fit the expected waste to be directed to that area, while taking into account Quality of Service constraints from the citizens' point of view. Moreover, we propose an effective constructive heuristic approach whose aim is to provide a good solution quality in an extremely reduced computational time. Computational results on data related to the city of Nardò, in the south of Italy, show that both exact and heuristic approaches provide consistently better solutions than that currently implemented, resulting in a lower number of activated collection sites, and a lower number of bins to be used.     

Design-based estimation in environmental surveys with positional errors

The recent increased availability of information about the micro-geographic positions of population units in environmental surveys has led to important developments in spatial sampling methodologies and, as a result, has improved the estimation accuracy. In real data, however, information about the location of units is often affected by inaccuracy about their exact spatial positions, and these non-sampling errors can affect the estimation procedure. This paper aims to investigate the effects of positional errors on total estimation through a Monte-Carlo simulation study based on real populations of trees. Starting from perfect positioning, we examine two typical types of coarsening that frequently impact two different species of trees. The simulation results show that the exploitation of spatial information to estimate population totals continues to be relevant in the context of environmental surveys, even in the presence of inaccuracies.     

Multitechnique diagnostic analysis and 3D surveying prior to the restoration of St. Michael defeating Evil painting by Mattia Preti

Environmental Science and Pollution Research - In this study, a multimethodological analysis involving optical and physical/chemical diagnostic techniques and 3D photogrammetric survey was...     

Vitality of viruses,including SARS-CoV-2, in airborne particulate matter: the “micellar model” hypothesis

Environmental Science and Pollution Research -