Chemical speciation of arsenic in different marine organisms: Importance in monitoring studies

Arsenic is a widely distributed element in the marine environment. Inorganic and organic compounds have extremely different toxicological effects, and their characterization is thus of great utility when monitoring and assessing the impact of arsenic pollution. In this study both the levels of total arsenic and its chemical speciation were analyzed in several marine organisms collected from Cienfuegos Bay (Cuba) following an episode of acute As-contamination. Fish from the more impacted site were characterized by elevated concentrations of arsenic (up to 500 microg/g d.w.) and inorganic species represented the predominant forms in muscle tissues of these organisms.     

A rapid approach to estimate the rockfall energies and distances at the base of rock cliffs

This paper presents a new methodology for estimating the expected energies and first impact distances at the base of a rock cliff, subject to the geometry and properties of the cliff and the representative block being known. The method is based on a sensitivity analysis, conducted by means of kinematic simulations and carried out for a large range of input parameters and their combinations, taking into account the uncertainty associated with their estimate. The proposed approach is validated by comparing predictions to experimental data and shows great potential for a quick qualitative hazard assessment.     

The genetic structure of the exotic ascidian Styela plicata (Tunicata) from Italian ports,with a re‐appraisal of its worldwide genetic pattern

The pleated ascidian Styela plicata (Lesueur, 1823) is a solitary species commonly found in ports and marinas around the world. It has been recorded in the Mediterranean region since the mid‐19th century. In the present work, the species’ genetic diversity was analysed, employing a 613‐bp portion of the mitochondrial cytochrome c oxidase subunit I (COI) gene from 149 individuals collected in 14 ports along Italian coasts at spatial scales ranging from 1 to approximately 2200 km. Haplotype and nucleotide diversity values were h = 0–0.933 (total h = 0.789) and π = 0–0.145 (total π = 0.0094), respectively. A general southward trend of increasing within‐population genetic diversity was observed. Analysis of molecular variance revealed significant genetic structuring but no significant differences were detected among basins, and no isolation by distance was found. Our data were integrated with the COI sequences available from previous studies and re‐analysed in order to investigate the possible routes of introduction of this ascidian into the Mediterranean Sea. The presence of the two COI haplogroups detected in previous molecular investigations on S. plicata at intercontinental spatial scale was confirmed in the Mediterranean Sea. The results revealed multiple introductions of S. plicata, although some locations appear to have experienced rapid expansion from few founding individuals with reduced genetic diversity. However, continuous introductions would confound the pattern deriving from single founder events and make it difficult to estimate the time needed for gene diffusion into established populations. This mixing of effects creates difficulties in understanding the past and current dynamics of this introduction, and managing this alien invasive ascidian whose genetic structure is continuously shuffled by vessel‐mediated transport.     

Predicting Nocturnal Wind and Temperature Profiles Based on External Forcing Parameters

We introduce a simple, physically consistent method to predict nocturnal wind and temperature profiles from external forcing parameters such as the geostrophic wind. As an indicator of the radiative ??forcing?? the net longwave radiative cooling is used as a proxy. Surface fluxes are expressed in terms of these parameters by coupling an Ekman model to a rudimentary surface energy balance. Additionally the model assumes validity of Monin-Obukhov similarity in order to predict near-surface wind and temperature profiles up to a height equal to the Obukhov length. The predictions are validated against an independent dataset that covers 11-years of observations at Cabauw, The Netherlands. It is shown that the characteristic profiles in response to external forcings are well-captured by the conceptual model. For this period the observational climatology is in close agreement with ECMWF re-analysis data. As such, the conceptual model provides an alternative tool to giving a first-order estimate of the nocturnal wind and temperature profile near the surface in cases when advanced numerical or observational infrastructure is not available.     

Detrending time series for astronomical variability surveys

We present a detrending algorithm for the removal of trends in time series. Trends in time series could be caused by various systematic and random noise sources such as cloud passages, changes of airmass, telescope vibration, CCD noise or defects of photometry. Those trends undermine the intrinsic signals of stars and should be removed. We determine the trends from subsets of stars that are highly correlated among themselves. These subsets are selected based on a hierarchical tree clustering algorithm. A bottom-up merging algorithm based on the departure from normal distribution in the correlation is developed to identify subsets, which we call clusters. After identification of clusters, we determine a trend per cluster by weighted sum of normalized light curves. We then use quadratic programming to detrend all individual light curves based on these determined trends. Experimental results with synthetic light curves containing artificial trends and events are presented. Results from other detrending methods are also compared. The developed algorithm can be applied to time series for trend removal in both narrow and wide field astronomy.     

The contribution of satellite SAR-derived displacement measurements in landslide risk management practices

Natural Hazards - Landslides are common phenomena that occur worldwide and are a main cause of loss of life and damage to property. The hazards associated with landslides are a challenging concern...     

Impact of event landslides on road networks: a statistical analysis of two Italian case studies

Despite abundant information on landslides, and on landslide hazard and risk, in Italy, little is known on the direct impact of event landslides on road networks and on the related economic costs. We investigated the physical and economic damage caused by two rainfall-induced landslide events in Central and Southern Italy, to obtain road restoration cost statistics. Using a GIS-based method, we exploited road maps and landslide event inventory maps to compute different metrics that quantify the impact of the landslide events on the natural landscape and on the road networks, by road type. The maps were used with cost data obtained from multiple sources, including local authorities, and specific legislation, to evaluate statistically the unit cost per metre of damaged road and the unit cost per square metre of damaging landslide, separately for main and secondary roads. The obtained unit costs showed large variations which we attribute to the different road types in the two study areas and to the different abundance of landslides. Our work confirms the long-standing conundrum of obtaining accurate landslide damage data and outlines the need for reliable, standardized methods to evaluate landslide damage and associated restoration costs that regional and local administrations can use rapidly in the aftermath of a landslide event. We conclude recommending that common standardized procedures to collect landslide cost data following each landslide event are established, in Italy and elsewhere. This will allow for more accurate and reliable evaluations of the economic costs of landslide events.     

Thermo-hydro-mechanical response of a large piled raft equipped with energy piles: a parametric study

This paper presents the results of a parametric study in which a series of fully coupled, 3-dimensional thermo-hydro-mechanical Finite Element (FE) analyses has been conducted to investigate the effects of the thermal changes imposed by the regular performance of a GSHP system driven by energy piles on a very large piled raft. The FE simulation program has been focused mainly on the evaluation of the following crucial aspects of the energy system design: the assessment of the soil–pile–raft interaction effects during thermal loading conditions; the quantification of the influence of the thermal properties of the soil and of the geometrical layout of the energy piles on the soil–foundation system response, and the evaluation of the influence of the active pile spacing on the thermal performance of the GSHP–energy pile system. The results of the numerical simulations show that the soil–pile–raft interaction effects can be very important. In particular, the presence of a relatively rigid raft in direct contact with the soil is responsible for axial load variations in inactive piles of the same order of those experienced by the thermo-active piles, even when the latter are relatively far and temperature changes in inactive piles are small. As far as the effect of pile spacing is concerned, the numerical simulations show that placing a high number of energy piles in a large piled raft with relatively small pile spacings can lead to a significant reduction of the overall heat exchange from the piles to the soil, thus reducing the thermal efficiency of the system.     

Hazard and population vulnerability analysis: a step towards landslide risk assessment

In this paper, an attempt to analyse landslide hazard and vulnerability in the municipality of Pahuatlán, Puebla, Mexico, is presented. In order to estimate landslide hazard, the susceptibility,magnitude(area-velocity ratio) and landslide frequency of the area of interest were produced based on information derived from a geomorphological landslide inventory; the latter was generated by using very high resolution satellite stereo pairs along with information derived from other sources(Google Earth,aerial photographs and historical information).Estimations of landslide susceptibility were determined by combining four statistical techniques:(i) logistic regression,(ii) quadratic discriminant analysis,(iii) linear discriminant analysis, and(iv)neuronal networks. A Digital Elevation Model(DEM)of 10 m spatial resolution was used to extract the slope angle, aspect, curvature, elevation and relief.These factors, in addition to land cover, lithology anddistance to faults, were used as explanatory variables for the susceptibility models. Additionally, a Poisson model was used to estimate landslide temporal frequency, at the same time as landslide magnitude was obtained by using the relationship between landslide area and the velocity of movements. Then,due to the complexity of evaluating it, vulnerability of population was analysed by applying the Spatial Approach to Vulnerability Assessment(SAVE) model which considered levels of exposure, sensitivity and lack of resilience. Results were expressed on maps on which different spatial patterns of levels of landslide hazard and vulnerability were found for the inhabited areas. It is noteworthy that the lack of optimal methodologies to estimate and quantify vulnerability is more notorious than that of hazard assessments.Consequently, levels of uncertainty linked to landslide risk assessment remain a challenge to be addressed.