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.     

Excitation–emission matrices applied to the study of urban effluent discharges in the Chubut River (Patagonia, Argentina)

Natural and contaminated waters of the final reaches of the Chubut River (Patagonia, Argentina) were studied to obtain information about river organic matter and effects of domestic and industrial discharges (fishery effluents and sewages). Fluorescence Excitation–Emission Matrices (EEMs) were obtained from samples only filtered (0.45 μm) and diluted, if necessary, to avoid the inner filter effect. In addition, physicochemical parameters were measured to know the quality of the water and the effluents. Results show that EEMs allow a rapid and simple control of the effluents from fisheries and domestic sewage in Chubut River estuary, necessary to take management decisions.     

Ecosystem Viable Yields

The World Summit on Sustainable Development (Johannesburg, 2002) encouraged the application of the ecosystem approach by 2010. However, at the same summit, the signatory States undertook to restore and exploit their stocks at maximum sustainable yield (MSY), a concept and practice without ecosystemic dimension, since MSY is computed species by species, on the basis of a monospecific model. Acknowledging this gap, we propose a definition of “ecosystem viable yields” (EVY) as yields compatible (a) with biological safety levels (over which biomasses can be maintained for all times) and (b) with an ecosystem dynamics. The difference from MSY is that this notion is not based on equilibrium but on viability theory, which offers advantages for robustness. For a generic class of multispecies models with harvesting, we provide explicit expressions for the EVY. We apply our approach to the anchovy–hake couple in the Peruvian upwelling ecosystem.     

Evaluation of concentration efficiency of the Pseudomonas aeruginosa phage PP7 in various water matrixes by different methods

Enteric viruses monitoring in surface waters requires the concentration of viruses before detection assays. The aim of this study was to evaluate different methods in terms of recovery efficiencies of bacteriophage PP7 of Pseudomonas aeruginosa, measured by real-time PCR, using it as a viral control process in water analysis. Different nucleic acid extraction methods (silica–guanidinium thiocyanate, a commercial kit (Qiagen Viral RNA Kit) and phenol–chloroform with alcohol precipitation) exhibited very low recovery efficiencies (0.08–4.18 %), being the most efficient the commercial kit used for subsequent experiments. To evaluate the efficiency of three concentration methods, PBS (as model for clean water) and water samples from rivers were seeded to reach high (HC, 10⁶ pfu ml^?1) and low concentrations (LC, 10⁴ pfu ml^?1) of PP7. Tangential ultrafiltration proved to be more efficient (50.36?±?12.91, 17.21?±?9.22 and 12.58?±?2.35 % for HC in PBS and two river samples, respectively) than adsorption–elution with negatively charged membranes (1.00?±?1.34, 2.79?±?2.62 and 0.05?±?0.08 % for HC in PBS and two river samples, respectively) and polyethylene glycol precipitation (15.95?±?7.43, 4.01?±?1.12 and 3.91?±?0.54 %, for HC in PBS and two river samples, respectively), being 3.2–50.4 times more efficient than the others for PBS and 2.7–252 times for river samples. Efficiencies also depended on the initial virus concentration and aqueous matrixes composition. In consequence, the incorporation of an internal standard like PP7 along the process is useful as a control of the water concentration procedure, the nucleic acid extraction, the presence of inhibitors and the variability of the recovery among replicas, and for the calculation of the sample limit of detection. Thus, the use of a process control, as presented here, is crucial for the accurate quantification of viral contamination.     

Fast simultaneous determination of traces of Cu(II) and Co(II) in soils and sediments with the luminol/perborate chemiluminescent system

A flow injection analysis method based on ion chromatography and luminol chemiluminescence detection was used for the simultaneous determination of copper (II) and cobalt (II) trace levels in soils and sediments following microwave-assisted acid digestion. Detection was based on chemiluminescence (CL) of the luminol–perborate system in an alkaline medium, which is catalyzed by both transition metals. The concentration and pH of the eluent (oxalic acid) was found to affect CL intensities and retention times, both of which were inversely proportional to the oxalic acid concentration. The calibration curves for both metal ions were linear and allowed a limit of detection of 0.003 μg l^?1 for cobalt (II) and 0.014 μg l^?1 for cooper (II) to be calculated. The proposed method was successfully used to determine both metal ions in certified reference materials of stream and river sediments and soil samples. Based on the results, the determination is free of interferences from the usual concomitant ions.     

The spatial statistics formalism applied to mapping electromagnetic radiation in urban areas

Determining the electromagnetic radiation levels in urban areas is a complicated task. Various approaches have been taken, including numerical simulations using different models of propagation, sampling campaigns to measure field values with which to validate theoretical models, and the formalism of spatial statistics. In the work, we present here that this latter technique was used to construct maps of electric field and its associated uncertainty from experimental data. For this purpose, a field meter and a broadband probe sensitive in the 100-kHz–3-GHz frequency range were used to take 1,020 measurements around buildings and along the perimeter of the area. The distance between sampling points was 5 m. The results were stored in a geographic information system to facilitate data handling and analysis, in particular, the application of the formalism of spatial statistical to the analysis of the distribution of the field levels over the study area. The spatial structure was analyzed using the variographic technique, with the field levels at non-sampled points being interpolated by kriging. The results indicated that, in the urban area analyzed in the present work, the linear density of sampling points could be reduced to a distance which coincides with the length of the blocks of buildings without the statistical parameters varying significantly and with the field level maps being reproduced qualitatively and quantitatively.     

Water quality index for agricultural systems in Northwest Uruguay

Agricultural systems have experienced rapid expansion and intensification in the last several decades. In Uruguay, since the beginning of 2000, the most common cropping systems have included soybeans. Currently, this crop is expanding towards lowlands traditionally occupied by rice in rotation with pastures. However, the environmental effects of agricultural intensification and diversification are not well known. Thus, some indices have been proposed to quantify the changes in agricultural production systems and assess water quality. The main goal of this study was to develop a water quality index (WQI) to assess the impacts of the diversification of rice production systems in northwest Uruguay. The study was carried out in an agricultural basin where other summer crops have been incorporated in the rice-pasture sequence. Agriculture intensification and crop diversification indices were calculated using information provided by farmers. Water samples were collected downstream of the production area before crop sowing and after crop harvest (2008–2009 to 2010–2011 and 2016–2017 to 2017–2018). Biochemical oxygen demand, nitrates, total phosphorus, fecal coliforms, and total suspended solids were the variables that mainly explained the effects of the agricultural activities on water quality. The proposed water quality index included these unweighted variables, which allowed for the pre-sowing and post-harvest to be differentiated, as well as the degree of diversification. Therefore, the proposed WQI constitutes a tool that can be used to evaluate the water quality in an agricultural basin. Likewise, it can be used to select agricultural sequences that generate the least possible impacts on the associated water resources.     

An integrated approach for assessing the migration behavior of chlorpyrifos and carbaryl in the unsaturated soil zone

Chlorpyrifos (O, O-diethyl O-3,5,6-trichloropyridin-2-yl phosphorothioate) and carbaryl (1-naphthyl methylcarbamate) are often applied concurrently as insecticides in food production. The aim of this study was to research their migration behavior in a real environment. We researched the leaching of both pesticides by setting up field lysimeters on a farm with the typical soil used in fruit production today. In order to analyze the variables involved in this process, we performed complementary adsorption studies, we performed complementary adsorption studies using batches and undisturbed soil laboratory columns for both compounds. The results for pesticide transport through the lysimeters showed that less than 1% of chlorpyrifos was recovered in the leachates, while almost 17% was recovered for carbaryl. Having completed the experiment in undisturbed laboratory columns, soil analysis showed that chlorpyrifos mainly remained in the first 5 cm, while carbaryl moved down to the lower sections. These results can be explained in view of the sorption coefficient values (K_D) obtained in horizons A and B for chlorpyrifos (393 and 184 L kg^?1) and carbaryl (3.1 and 4.2 L kg^?1), respectively. By integrating the results obtained in the different approaches, we were able to characterize the percolation modes of these pesticides in the soil matrix, thus contributing to the sustainable use of resources.     

Honeybees (<Emphasis Type="Italic">Apis mellifera</Emphasis>) as a biological barrier for contamination of honey by environmental toxic metals

The aim of the study was to investigate the transfer of toxic metals from honeybee workers (Apis mellifera L.) to bee honey in relation to the ecological state of the environment. The materials of the study consisted of samples of honeybee bodies and varietal honeys taken from the same apiary located in three areas: R1—urbanized (16), R2—ecologically clean (16) and R3—industrialized (15) of south-eastern Poland. The contents of 14 elements in all tested samples, including toxic metals (Cd, Pb, Hg, Al, Ni, Tl) as well as bioelements (K, Mg, Ca, Mn, Fe, Zn, Cu, Se), were analysed by the ICP-OES method with prior microwave mineralization. The concentrations of the majority of the studied elements, excluding aluminum and lead, were significantly higher in bee bodies than in honey samples (P?<?0.05). The pollution of bee bodies by toxic metals was dependent on the environmental cleanliness, and the most pollution was observed in the industrialized area. The bee body was the most effective barrier for Cd and Tl transfer to the honey, while the level of Ni was similar in both tested materials. The Al concentration was significantly higher in honey than bee bodies (14.81?±?24.69 and 6.51?±?5.83 mg kg^?1, respectively), which suggests the possibility of secondary contamination of honey. The greatest sensitivity to heavy metal pollution was observed in honeydew honey compared to nectar honeys (P?<?0.05). It was proved for the first time that bees work as biofilters for toxic metals and prevent honey contamination.     

Air Quality Modeling Using the PSO-SVM-Based Approach,MLP Neural Network,and M5 Model Tree in the Metropolitan Area of Oviedo (Northern Spain)

The main aim of this study was to construct several regression models of air quality using techniques based on the statistical learning, in the metropolitan area of Oviedo, in northern Spain. In this research, a hybrid particle swarm optimization-based evolutionary support vector regression is implemented to predict the air quality from the experimental dataset (specifically, nitrogen oxides, carbon monoxide, sulfur dioxide, ozone, and dust) collected from 2013 to 2015 in the metropolitan area of Oviedo. Furthermore, a multilayer perceptron network (MLP) and the M5 model tree were also fitted to the experimental dataset for comparison purposes. Finally, the predicted results show that the hybrid proposed model is more robust than the MLP and M5 model tree prediction methods in terms of statistical estimators and testing performances.