Sand as a relevant fraction in geochemical studies in intertidal environments

Soil and sediment samples from several intertidal environment exposed to different types of contamination were studied to investigate the importance of grain size in relation to the capacity of the substrates to retain trace metals. The unfractionated samples (referred to as bulk samples) were separated into the following grain/size fractions: fine–coarse sand (2?0.100 mm), very fine sand (0.100?0.050 mm), silt (0.050?0.002 mm), and clay (0.002 mm). The sample into its fractions was carried out was in a glove box under high-purity N₂ atmosphere in order to minimize any alterations to the samples. The bulk samples were characterized in terms of physicochemical properties such as pH, redox potential, and grain size. The total organic carbon (TOC), total sulfur (S), iron (Fe) pyrite, Fe, and manganese (Mn), and trace metals lead (Pb), mercury (Hg), chromium (Cr), and nickel (Ni) were analyzed in the bulk samples and in each fraction. The sand fractions were also examined by scanning electron microscopy (SEM). Comparisons of the above parameters were made between fractions and between each fraction and the corresponding bulk sample. The fine–coarse sand fraction contained high levels of the primary elements of the geochemical processes that occur in marine sedimentary environments such as TOC, total Fe, Mn, and S. The net concentrations of these four elements were higher in the fine-coarse sand fraction than in the very fine sand fraction and were similar to the net concentrations in the silt and clay fractions. Detailed SEM analysis of the sand coarse fraction revealed the presence of Fe and aluminum oxyhydroxide coatings in the oxic layers, whereas the framboidal pyrites and coatings observed in the anoxic layers were Fe sulfides. The presence of the various coatings explains why the trace metal concentrations in the sand fine–coarse fraction were similar to those in the clay fraction and higher than those in the very fine sand fraction. The present results highlight the importance of the sand fraction, which is generally disregarded in geochemical and environmental studies of sedimentary layers.     

Arsenic and other trace elements in two catfish species from Paranaguá Estuarine Complex, Paraná, Brazil

Concentrations of arsenic and four additional trace elements (Cu, Cr, Ni, and Zn) were determined by inductively coupled plasma–optical emission spectrometry in the muscular tissue of the yellow catfish (Cathorops spixii) and the urutu catfish (Genidens genidens) from Paranaguá Estuarine Complex, Brazil (PEC). The PEC can be characterized by an environment of high ecological and economic importance in which preserved areas of rainforest and mangroves coexist with urban activities as ports and industries. The average concentrations (in milligram per kilogram dry weight) of elements in the muscle tissue of C. spixii are as follows: Zn (31), As (17), Cu (1.17), Cr (0.62), and Ni (0.28). Similar concentrations could be found in G. genidens with exception of As: Zn (36), As (4.78), Cu (1.14), Cr (0.51), and Ni (0.14). Fish from the geographic northern rural region (Guaraqueçaba–Benito) display higher As concentrations in the muscle tissues than fish found in the south-western (urban) part of the PEC. An international comparison of muscle tissue concentrations of trace elements in fish was made. Except for Ni in C. spixii, a tendency of decrease in element concentration with increasing size (age) of the fish could be observed. According to the National Health Surveillance Agency of Brazil, levels of Cr and As exceeded the permissible limits for seafood. An estimation of the provisional tolerable weekly intake of As was calculated with 109 % for C. spixii and with 29 % for G. genidens.     

Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

Energy Security: A Robust Optimization Approach to Design a Robust European Energy Supply via TIAM-WORLD

Energy supply routes to a given region are subject to random events, resulting in partial or total closure of a route (corridor). For instance, a pipeline may be subject to technical problems that reduce its capacity. Or, oil supply by tanker may be reduced for political reasons or because of equipment mishaps at the point of origin or again, by a conscious decision by the supplier in order to obtain economic benefits. The purpose of this article is to formulate a simplified version of the above issue that mainly addresses long-term uncertainties. The formulation is done via a version of the TIAM-WORLD Integrated Model, modified to implement the approach of robust optimization. In our case, the approach can be interpreted as a revival of chance-constrained programming under the name of distributionally robust, or ambiguous, chance-constrained programming. We apply the approach to improve the security of supply to the European Energy system. The resulting formulation provides several interesting features regarding the security of EU energy supply and has also the advantage to be numerically tractable.     

Changes in the sorption and rate of 17β-estradiol biodegradation by dissolved organic matter collected from different water sources

The potential biodegradation and subsequent transformation of 17β-estradiol (E2) to estrone (E1) were examined in the presence of various dissolved organic matter (DOM) isolated from effluent, river and lake waters. In addition, estrogenicity was estimated in association with the removal of E2 via its sorption onto DOM and biodegradation. The more biodegradable lake-derived DOM promoted more extensive transformation of E2 into E1 than the effluent organic matter through a biodegradation process. Overall, under all conditions, biodegradation dominated the removal of E2 in water. The increased dissolved organic carbon (DOC) concentrations in river and lake-derived DOM (e.g. 6.5 mg C L(-1)) reduced the removal of E2 by decreasing its biodegradation due to the moderate sorption of E2 onto DOM. The effluent organic matter showed greater removal of E2 via biodegradation, as well as significantly high sorption. This was associated with a large amount of hydrophobic fulvic acid (FA)- and humic acid (HA)-like organic components, as shown by the small increase in the specific UV absorbance at 254 nm (SUVA(254)). An increase in the DOC concentration reduced the removal of E2, resulting in high estrogenicity. The present study suggests that both organic composition and DOC concentration influenced the removal of E2 and, therefore, should be fully considered when assessing estrogenicity and its impacts on the aquatic environment.     

Selecting Variables for Habitat Suitability of <Emphasis Type="Italic">Asellus</Emphasis> (Crustacea,Isopoda) by Applying Input Variable Contribution Methods to Artificial Neural Network Models

This study aimed to compare different methods to analyse the contribution of individual river characteristics to predict the abundance of Asellus (Crustacea, Isopoda). Six methods which provide the relative contribution and/or the contribution profile of the input variables of artificial neural network models were therefore compared: (1) the ‘partial derivatives’ method; (2) the ‘weights’ method; (3) the ‘perturb’ method; (4) the ‘profile’ method; (5) the ‘classical stepwise’ method; (6) the ‘improved stepwise’ method. Consequently, the key variables which affect the habitat preferences of Asellus could be identified. To evaluate the performance of the artificial neural network model, the model predictions were compared with the results of a multiple linear regression analysis. The dataset consisted of 179 samples, collected over a 3-year period in the Zwalm catchment in Flanders, Belgium. Twenty-four environmental variables as well as the log-transformed abundance of Asellus were used in this study. The different contribution methods seemed to give similar results concerning the order of importance of the input variables. Nevertheless, their diverse computation led to differences in sensitivity and stability of the methods and the derived outcomes on the habitat preferences. From an ecological point of view, the environmental variables describing the stream type (width, depth, stream order and distance to mouth) were the most significant variables for Asellus in the Zwalm catchment during the period 2000–2002 for all applied methods. Indirectly, one can conclude that the water quality is not the limiting factor for the survival of Asellus in the Zwalm catchment.     

Trace element concentrations in surface estuarine and marine sediments along the Mississippi Gulf Coast following Hurricane Katrina

Hurricanes are relatively frequent ecological disturbances that may cause potentially long-term impacts to the coastal environment. Hurricane Katrina hit the Mississippi Gulf Coast in August 2005, and caused a storm surge with the potential to change the trace element content of coastal surface sediments. In this study, surface estuarine and marine sediments were collected monthly following the storm from ten sites along the Mississippi Gulf Coast (Mobile Bay, Grand Bay Bayous Heron and Cumbest, Pascagoula, Ocean Springs, Biloxi Gulf, Back Biloxi Bay, Gulfport Gulf, Gulfport Courthouse Rd, and Gulfport Marina). Concentrations of V, Cr, Mn, Fe, Co, Ni, Zn, As, Cd, and Pb were measured by inductively coupled plasma–mass spectrometry to evaluate their temporal and spatial variations in the year following Hurricane Katrina. Sediments were characterized by pH, particle size distribution and total carbon and nitrogen content. Trace element contents of the sediments were determined in both <2 mm and <63 μm grain size fractions. Results revealed no significant temporal and spatial variability in trace element concentrations, in either size fraction. Potential ecological risk of the sediments was assessed by using NOAA SQuiRTs’ guideline values; most concentrations remained below probable adverse effects guidelines to marine organisms suggesting that trace elements redistributed by Hurricane Katrina would not cause an adverse impact on resident organisms. Instead, the concentrations of trace elements were site-dependent, with specific contaminants relating to the use of the area prior to Hurricane Katrina.