About the possibility of sorption concentration of heavy metals using magnetite

This paper addresses the possibility of using magnetite nanoparticles for sorption concentration of heavy metals ions in the analysis of their trace amounts. On the example of copper, lead and nickel ions, optimum conditions for concentrating have been determined, pH, temperature and contact time effect on the adsorption process have been studied in the static mode, and magnetite sorption capacity has been calculated on the basis of experimental data

The influence of ash tree sawdust acid treatment on the removal of crude oil from water surfaces

Agricultural and timber industry wastes may constitute a significant source of promising oil sorption materials. In this study the potential application of Fráxinus excélsior ash tree sawdust as sorption material for crude oil removal was investigated. The effect of acid treatment on physicochemical and sorption properties of sawdust was studied in a batch system. Oil sorption capacity and water uptake of sorption materials in static system were evaluated. For the determination of raw and treated samples structure and surface changes X-ray diffraction analysis, atomic force microscopy, FTIR spectroscopy and contact angle evaluation were used. The highest oil sorption capacity was shown by 3% HNO3 treated sawdust, 43.2% and 37.4% increase of oil sorption capacity for Devonian oil and Carbon oil, respectively, was observed in comparison with untreated sawdust. The exhibited reduction of modified sawdust water uptake indicated the increase of sorbent material hydrophobicity that was confirmed by the results of contact angle determination. Based on atomic force microscopy results, the surface roughness of treated sawdust was shown to be enhanced that could be a primary factor affecting on oil sorption capacity improvement. Thus, acid treated ash tree sawdust was shown to have improved oil sorption and physicochemical characteristics for crude oil removal

Results of AAS measurements of atmospheric trace metals deposition in snow cover in lower kama urban agglomeration

The study of pollutant level of snow cover of the explored territory required establishment of more than 80 sample plots within the territory of several hundreds square kilometers including industrial area of Naberezhnye Chelny (steam power plants, JSC KAMAZ plants, etc.), which are exposed to intense human impact of the area of agroindustrial complex of the Tukai district, the part of "Lower Kama" national park area, and the territory of the city of Naberezhnye Chelny as well. Within the framework of the study snow sampling was carried out within these sample plots, its main features and contaminators' weight content were defined. Moreover, the results of long-term observations over snow cover state of the territory of the Naberezhnye Chelny (Lower Kama) urban agglomeration that allow - taking into account synoptic conditions by the end of cold period - forecasting the beginning of intense snow melting and planning snow-measuring measures and sampling correspondingly. To assess impact on environment, accumulated with snow and soil cover of pollutants, their inflow per unit area and per explored territory was estimated. Obtained results allowed to asses the snow cover contamination level by several complex indicators. The snow cover contamination level based on this data should be recognized as quite considerable: median value of contamination total index Kp5 is 15,1 that allow us to relate this territory to heavily polluted. Whereby partial coefficients of contamination with cooper and zinc, and manganese iron and nickel to a somewhat less degree, make a major contribution to this index

Sorption concentration of arsenic ions by magnetite

© The author(s). This paper is focused on the possibility of using magnetite powders obtained by chemical and plasma-chemical method for sorption concentration of arsenic ions. Processes of arsenic concentration by two-site sorption in magnetite-water system have been studied, and the optimal conditions for concentration have been defined. In static mode, effects of pH, temperature and contact time on the adsorption process have been studied. As a result, a method for pre-sorption concentration has been proposed, allowing reducing the lower limit of the atomic absorption determination of arsenic content

Reverse engineering model structures for soil and ecosystem respiration: the potential of gene expression programming

Accurate model representation of land-atmosphere carbon fluxes is essential for climate projections. However, the exact responses of carbon cycle processes to climatic drivers often remain uncertain. Presently, knowledge derived from experiments, complemented with a steadily evolving body of mechanistic theory provides the main basis for developing such models. The strongly increasing availability of measurements may facilitate new ways of identifying suitable model structures using machine learning. Here, we explore the potential of gene expression programming (GEP) to derive relevant model formulations based solely on the signals present in data by automatically applying various mathematical transformations to potential predictors and repeatedly evolving the resulting model structures. In contrast to most other machine learning regression techniques, the GEP approach generates "readable" models that allow for prediction and possibly for interpretation. Our study is based on two cases: artificially generated data and real observations. Simulations based on artificial data show that GEP is successful in identifying prescribed functions with the prediction capacity of the models comparable to four state-of-the-art machine learning methods (Random Forests, Support Vector Machines, Artificial Neural Networks, and Kernel Ridge Regressions). Based on real observations we explore the responses of the different components of terrestrial respiration at an oak forest in south-east England. We find that the GEP retrieved models are often better in prediction than some established respiration models. Based on their structures, we find previously unconsidered exponential dependencies of respiration on seasonal ecosystem carbon assimilation and water dynamics. We noticed that the GEP models are only partly portable across respiration components; the identification of a "general" terrestrial respiration model possibly prevented by equifinality issues. Overall, GEP is a promising tool for uncovering new model structures for terrestrial ecology in the data rich era, complementing more traditional modelling approaches

Pd Nanoparticles and Thin Films for Room Temperature Hydrogen Sensor

We report the application of palladium nanoparticles and thin films for hydrogen sensor. Electrochemically grown palladium particles with spherical shapes deposited on Si substrate and sputter deposited Pd thin films were used to detect hydrogen at room temperature. Grain size dependence of H2sensing behavior has been discussed for both types of Pd films. The electrochemically grown Pd nanoparticles were observed to show better hydrogen sensing response than the sputtered palladium thin films. The demonstration of size dependent room temperature H2sensing paves the ways to fabricate the room temperature metallic and metal–metal oxide semiconductor sensor by tuning the size of metal catalyst in mixed systems. H2sensing by the Pd nanostructures is attributed to the chemical and electronic sensitization mechanisms

Seasonal Spatial Segregation in Blue Sharks (Prionace glauca) by Sex and Size Class in the Northeast Pacific Ocean

Aim: Animal tracking can provide unique insights into the ecology and conservation of marine species, such as the partitioning of habitat, including differences between life history stages or sexes, and can inform fisheries stock assessments, bycatch reduction and spatial management such as dynamic management. Location: Northeast Pacific Ocean. Methods: We used satellite tracking data from 47 blue sharks (Prionace glauca) from the Northeast Pacific to determine movements and home range along the west coast of North America, and sex–size class (immature females, mature males) specific habitat preferences using boosted regression trees. Using a suite of static and dynamic environmental variables, we determined distribution and habitat preferences across summer and fall for each sex–size class. Results: We found that there was spatial segregation between sex–size classes particularly in the summer months with immature females found largely north of 33°N, and males south of 35°N. In fall, females travelled south, resulting in an overlap in distributions south of 37°N. Sea surface temperature (SST), latitude and longitude were top predictors. However, immature females and adult males demonstrated unique habitat preferences including SST, with immature females preferring cooler temperatures (SST \u3c 15°C) than adult males in summer, and a broader band of SST than adult males in fall. All models performed well, explaining 50%–67% of deviance, and 23%–41% of deviance when predictions were cross‐validated. Main conclusions: We provide first insights into coastal movements and habitat preferences of blue sharks in the Northeast Pacific. We found that immature females undergo a seasonal southward migration in this more coastal habitat, similar to patterns observed in the North Atlantic. We also found some overlap between adult males and immature females in fall months, suggesting the importance of more coastal habitat in managing this species, particularly in determining population structure for blue shark stock assessments, and reducing blue shark bycatch