Bioaccumulation depuration kinetics and effects of benzo(a)anthracene on Mytilus galloprovincialis

Polycyclic aromatic hydrocarbons (PAHs) are important environmental pollutants due to their persistence and bioaccumulation potential both in organisms and in sediments. In this study, bioaccumulation and depuration experiments were performed employing local Mediterranean mussel species, Mytilus galloprovincialis, with two biomarkers: filtration rate and lysosomal stability (neutral red retention) assay. Benzo(a)anthracene (BaA) was chosen as the model PAH compound due to its common presence in several matrices in the marine environment. Bioconcentration Factors (BCFs) for the mussels exposed to different BaA concentrations were calculated from both kinetic rate constants and from the experimental data and found between 27-3184 and 16-2745, respectively. Experimental QSAR values were found comparable to the previous QSAR models created for BaA. The effect of BaA exposure on the mussels showed a more clear dose-response relationship according to the results of lysosomal stability compared to the filtration rate.     

Distribution and source apportionments of polychlorinated biphenyls (PCBs) in mariculture sediments from the Pearl River Delta, South China

Surface and core sediments collected from six mariculture farms in the Pearl River Delta (PRD) were analyzed to evaluate contamination levels of polychlorinated biphenyls (PCBs). The ∑PCBs (37 congeners) concentrations ranged from 5.10 to 11.0 ng g(-1) (mean 7.96 ng g(-1)) in surface and 3.19 to 22.1 ng g(-1) (mean 7.75 ng g(-1)) in core sediments, respectively. The concentrations were significantly higher than that measured in the sediments of their corresponding reference sites, whereby the average enrichment percentages were 62.0% and 42.7% in surface and core sediments, respectively. Significant correlations (R2=0.77, p<0.05) of PCB homologue group proportions between fish feeds and surface mariculture sediments suggested that fish feed input was probably the main source for the enrichment of PCBs. Due to the fact that PCBs could be transferred along food chains, PCB contamination in fish feeds and mariculture sediments should not be overlooked.     

Rapid earthquake loss assessment after damaging earthquakes

This article summarizes the work done over the last decades regarding the development of new approaches and setting up of new applications for earthquake rapid response systems that function to estimate earthquake losses in quasi-real time after an earthquake. After a critical discussion of relevant earthquake loss estimation methodologies, the essential features and characteristics of the available loss estimation software are summarized. Currently operating near-real-time loss estimation tools can be classified under two main categories depending on the size of area they cover: global and local systems. For the global or regional near-real-time loss estimation systems: GDACS, WAPMERR, PAGER, and NERIES-ELER methodologies are presented together with their loss estimations for the 2009 Abruzzo (L’Aquila) earthquake in Italy. Examples are provided for the local rapid earthquake loss estimation systems, including the Taiwan Earthquake Rapid Reporting System, Real-time Earthquake Assessment Disaster System in Yokohama, Real Time Earthquake Disaster Mitigation System of the Tokyo Gas Co., and Istanbul Earthquake Rapid Response System.     

Sectional forces for seismic design of R/C frames by linear time history analysis and application to 3D single-story buildings

The aim of the present paper is to present a rational procedure for the appropriate selection of the sectional forces needed for the calculation of the longitudinal reinforcement to R/C elements within the context of linear time history analysis. The proposed procedure is based on the maximum normal stresses, which occurs in each relevant cross section, and takes into consideration the critical angle of the seismic excitation, i.e., the angle that yields the maximum value of each response quantity of interest. Moreover, in an attempt to realistically interpret pertinent code provisions, three other code compatible methods of selecting the cross sectional forces are presented and compared to the here proposed method. For this purpose, three single-story buildings subjected to 47 bi-directional strong earthquake ground motions are analyzed. For each ground motion, the longitudinal reinforcement at all critical cross sections is calculated using the above four methods. Furthermore, the necessary reinforcement due to 3 and 7 representative earthquake records, required by the seismic code provisions, is determined. Comparison of results clearly shows that methods compatible with current seismic code provisions can significantly underestimate the necessary reinforcement with regards to the proposed method.     

Preliminary Interlaboratory Trial for ISO/DIS 12010: Determination of Short Chain Polychlorinated Alkanes (SCCP) in Water

A first preliminary interlaboratory trial was planned to prepare ISO/DIS 12010: Water quality – determination of short chain polychlorinated alkanes (SCCP) in water – method using GC/MS and electron capture negative ionisation (ECNI). The task was to determine the sum of short chain polychlorinated n‐alkanes with carbon chain lengths of C₁₀–C₁₃ and a chlorine content between 49 and 67% in water by GC‐ECNI‐MS and quantification by multiple linear regression described in ISO/DIS 12010 as the compulsory method. Distributed samples were obtained from a real water extract spiked with a target concentration of 0.4 µg/mL sum of SCCP, i.e. the environmental quality target level according to the Water Framework Directive. The interlaboratory trial included the calibration, a column chromatographic clean up, a concentration step and an integration of chromatographic unresolved humps as well as the quantification with multiple linear regression. Reproducibility standard deviations between 21.5 and 22.9% were achieved by 17 participating laboratories from four countries. The method outlined no significant difference of the results between the standard solution and a real water matrix extract. On the basis of this succeeded preliminary interlaboratory trial the final interlaboratory trial for validation of ISO 12010 was prepared in autumn 2010.     

Prominence Characteristics in 16th Activity Cycle

Digitization of the daily prominence sketches based on data from the global observational network of visual solar spectroscopes was performed for 1922–1934. More than 55000 prominences were distinguished. The results of analysis of distributions by area, height, and prominence location are presented. In addition, the prominence characteristics were compared to those obtained from more recent observations at the Kislovodsk Mountain Astronomical Station of Pulkovo Observatory. The distributions of prominence areas and heights are close to lognormal. The maximal height distribution corresponds to ~25–40 arcsecs. A second maximum also exists for prominence heights of ~70–90 arcsecs.     

Use of artificial neural networks for classification of noisy seismic signals

Automatic identification of noisy seismic events is still a problem. The process involves the analysis of complex relationships between data from different sources. Moreover, there are disturbing factors such as poor signal-to-noise ratio, the presence of accidental bursts of man-made noise, and changes in the amplitude and phase of the waves as they travel through the medium. The amount of observed data increases rapidly, so it is imperative to develop suitable and effective methods for processing and analyzing the influx of big data. Artificial neural networks (ANNs) show promise as a disruptive technology that will accelerate and improve analysis of seismic signals. ANNs are easy to apply, and the results often outperform alternative methods. This paper gives an overview of the highs and lows of neural networks, discusses the possibility of routine processing of seismic signals using ANNs, and presents examples of some interesting applications. It is hoped that researchers who read the article will actively use this technique, because ANNs could become more robust and flexible for solving complex problems that currently cannot be solved by the standard approach.     

A computationally efficient method for uncertainty analysis of SWAT model simulations

The physically based distributed hydrological models are ideal for hydrological simulations; however most of such models do not use the basic equations pertaining to mass, energy and momentum conservation, to represent the physics of the process. This is plausibly due to the lack of complete understanding of the hydrological process. The soil and water assessment tool (SWAT) is one such widely accepted semi-distributed, conceptual hydrological model used for water resources planning. However, the over-parameterization, difficulty in its calibration process and the uncertainty associated with predictions make its applications skeptical. This study considers assessing the predictive uncertainty associated with distributed hydrological models. The existing methods for uncertainty estimation demand high computational time and therefore make them challenging to apply on complex hydrological models. The proposed approach employs the concepts of generalized likelihood uncertainty estimation (GLUE) in an iterative procedure by starting with an assumed prior probability distribution of parameters, and by using mutual information (MI) index for sampling the behavioral parameter set. The distributions are conditioned on the observed information through successive cycles of simulations. During each cycle of simulation, MI is used in conjunction with Markov Chain Monte Carlo procedure to sample the parameter sets so as to increase the number of behavioral sets, which in turn helps reduce the number of cycles/simulations for the analysis. The method is demonstrated through a case study of SWAT model in Illinois River basin in the USA. A comparison of the proposed method with GLUE indicates that the computational requirement of uncertainty analysis is considerably reduced in the proposed approach. It is also noted that the model prediction band, derived using the proposed method, is more effective compared to that derived using the other methods considered in this study.