Optimizing synthesis conditions of nanoscale zero-valent iron (nZVI) through aqueous reactivity assessment

Nanoscale iron particles (nZVI) is one of the most important engineered nanomaterials applied to environmental pollution control and abatement. Although a multitude of synthesis approaches have been proposed, a facile method to screen the reactivity of candidate nZVI materials produced using different methods or under varying synthesis conditions has yet been established. In this study, four reaction parameters were adjusted in the preparation of borohydride-reduced nZVI. The reductive properties of the resultant nanoparticles were assayed independently using two model aqueous contaminants, Cu(II) and nitrate. The results confirm that the reductive reactivity of nZVI is most sensitive to the initial concentration of iron precursor, borohydride feed rate, and the loading ratio of borohydride to ferric ion during particle synthesis. Solution mixing speed, in contrast, carries a relative small weight on the reactivity of nZVI. The two probing reactions (i.e., Cu(II) and nitrate reduction) are able to generate consistent and quantitative inference about the mass-normalized surface activity of nZVI. However, the nitrate assay is valid in dilute aqueous solutions only (50 mg·L⁻¹ or lower) due to accelerated deactivation of iron surface at elevated nitrate concentrations. Additional insights including the structural and chemical makeup of nZVI can be garnered from Cu(II) reduction assessments. The reactivity assays investigated in this study can facilitate screening of candidate materials or optimization of nZVI production parameters, which complement some of the more sophisticated but less chemically specific material characterization methods used in the nZVI research.     

Nexus between polymer support and metal oxide nanoparticles in hybrid nanosorbent materials (HNMs) for sorption/desorption of target ligands

Metal oxide nanoparticles like hydrated ferric oxide (HFO) or hydrated zirconium oxide (HZrO) are excellent sorbents for environmentally significant ligands like phosphate, arsenic, or fluoride, present at trace concentrations. Since the sorption capacity is surface dependent for HFO and HZrO, nanoscale sizes offer significant enhancement in performance. However, due to their miniscule sizes, low attrition resistance, and poor durability they are unable to be used in typical plug-flow column setups. Meanwhile ion exchange resins, which have no specific affinity toward anionic ligands, are durable and chemically stable. By impregnating metal oxide nanoparticles inside a polymer support, with or without functional groups, a hybrid nanosorbent material (HNM) can be prepared. A HNM is durable, mechanically strong, and chemically stable. The functional groups of the polymeric support will affect the overall removal efficiency of the ligands exerted by the Donnan Membrane Effect. For example, the removal of arsenic by HFO or the removal of fluoride by HZrO is enhanced by using anion exchange resins. The HNM can be precisely tuned to remove one type of contaminant over another type. Also, the physical morphology of the support material, spherical bead versus ion exchange fiber, has a significant effect on kinetics of sorption and desorption. HNMs also possess dual sorption sites and are capable of removing multiple contaminants, namely, arsenate and perchlorate, concurrently.     

Evaluation of a fast response pressure solver for flow around an isolated cube

This work describes and evaluates a pressure solver that has been incorporated into a fast response three-dimensional building-resolving diagnostic wind modeling system. The solver computes the three-dimensional pressure field around buildings and on exterior walls in terms of a coefficient of pressure by solving a simplified pressure Poisson equation (that neglects turbulence stresses in the Navier-Stokes) for incompressible flow. The input to the solver is the three-dimensional mean wind field obtained from a fast response empirical-diagnostic urban wind model. The present study is an evaluation of the pressure solver using wind-tunnel data for flow normal to and at a 45° angle to an isolated cubical building. Results for the normal incident wind angle case indicate that the model satisfactorily reproduces the general spatial patterns and the magnitude of the pressure difference around much of the cube. Details of the flow field that are not satisfactorily predicted include the spatial distribution of pressure on the roof and the lower half of the front side of the building and the magnitude along the sidewalls where pressures are over predicted. The results for the 45° case show reasonable agreement between the model and experiments on the front and the back walls, but over predict pressures on the leading edge of the rooftop. Regions with poor pressure predictions appear to be a result of unsatisfactory mean wind modeling.     

Spatial extremes of wildfire sizes: Bayesian hierarchical models for extremes

In Portugal, due to the combination of climatological and ecological factors, large wildfires are a constant threat and due to their economic impact, a big policy issue. In order to organize efficient fire fighting capacity and resource management, correct quantification of the risk of large wildfires are needed. In this paper, we quantify the regional risk of large wildfire sizes, by fitting a Generalized Pareto distribution to excesses over a suitably chosen high threshold. Spatio-temporal variations are introduced into the model through model parameters with suitably chosen link functions. The inference on these models are carried using Bayesian Hierarchical Models and Markov chain Monte Carlo methods.     

Post-larval development of two intertidal barnacles at elevated CO2 and temperature

Ocean acidification and global warming are occurring concomitantly, yet few studies have investigated how organisms will respond to increases in both temperature and CO₂. Intertidal microcosms were used to examine growth, shell mineralogy and survival of two intertidal barnacle post-larvae, Semibalanus balanoides and Elminius modestus, at two temperatures (14 and 19°C) and two CO₂ concentrations (380 and 1,000 ppm), fed with a mixed diatom-flagellate diet at 15,000 cells ml⁻¹ with flow rate of 10 ml⁻¹ min⁻¹. Control growth rates, using operculum diameter, were 14 ± 8 μm day⁻¹ and 6 ± 2 μm day⁻¹ for S. balanoides and E. modestus, respectively. Subtle, but significant decreases in E. modestus growth rate were observed in high CO₂ but there were no impacts on shell calcium content and survival by either elevated temperature or CO₂. S. balanoides exhibited no clear alterations in growth rate but did show a large reduction in shell calcium content and survival under elevated temperature and CO₂. These results suggest that a decrease by 0.4 pH_(NBS) units alone would not be sufficient to directly impact the survival of barnacles during the first month post-settlement. However, in conjunction with a 4–5°C increase in temperature, it appears that significant changes to the biology of these organisms will ensue.     

Seasonal contrasts in abundance and reproductive parameters of Penilia avirostris (Cladocera, Ctenopoda) in a coastal subtropical area

We studied the population dynamics and the reproductive biology of Penilia avirostris during three consecutive years on the inner shelf off Ubatuba, Brazil. Penilia avirostris individuals and its eggs and embryos were counted, measured, and classified into stages. The species occurred throughout the studied period, in a wide temperature range (14.8–28.2°C). Cladoceran densities were usually higher (>2,000 ind m⁻³) in warm seasons, when the water column was stratified as a consequence of bottom intrusions of the cold- and nutrient-rich South Atlantic Central Water. Juveniles, non-reproducing females, and parthenogenic females were the dominant developmental stages. Males and gamogenic females were rare and only occurred when females reached peak abundances. This suggests that in tropical and subtropical coastal seas gamogenesis in P. avirostris is not as common as in temperate seas, but may play a significant role in the density-dependent control of the population preceding unfavourable periods.     

Short- and long-term consequences of prenatal testosterone for immune function: an experimental study in the zebra finch

Hormone-mediated maternal effects play an important role in the formation of a differentiated phenotype. They have been shown to influence a wide array of offspring traits, both early in life and in adulthood. One important offspring trait that is under the influence of maternal androgens is the immune system. In birds, a growing number of studies show that yolk androgens modulate immune function during the chick stage. However, there is a lack of knowledge regarding long-term effects of prenatal androgens on offspring immunity. In this study, we therefore investigated the influence of prenatal testosterone (T) on several measures of immunity in fledgling and adult zebra finches (Taeniopygia guttata). Cell-mediated immune response (towards phytohaemagglutinin, PHA) of fledglings hatching from control eggs was negatively related to brood size, whereas there was no such association for fledglings hatching from eggs with experimentally elevated T levels (T fledglings). Male control fledglings showed reduced mass gain compared to female control fledglings within 24 h after the PHA injection. This pattern was reversed in T fledglings. Total antibody levels in fledglings were not affected by egg treatment. Neither cell-mediated immunity nor total antibody levels in sexually mature zebra finches were influenced by egg treatment. However, there was an immuno-enhancing effect of elevated egg T on both primary and secondary humoral immune responses toward diphtheria and tetanus antigens in ca 5 and 7 month old zebra finches. In addition, the covariation between different immune components differed between T and control offspring, suggesting that egg treatment may have altered the potential trade-offs between different parts of the immune system. Our results suggest that prenatal androgens could be an important factor contributing to individual variation in immune function even in adulthood.     

Sensitivity analysis of the two dimensional application of the Generic Ecological Model (GEM) to algal bloom prediction in the North Sea

Harmful algae can cause damage to co-existing organisms, tourism and farmers. Accurate predictions of algal future composition and abundance as well as when and where algal blooms may occur could help early warning and mitigating. The Generic Ecological Model is an instrument that can be applied to any water system (fresh, transitional or coastal) to calculate the primary production, chlorophyll-a concentration and phytoplankton species composition. It consists of physical, chemical and ecological model components which are coupled together to build one generic and flexible modelling tool. In this paper the model has been analyzed to assess sensitivity of the simulated chlorophyll-a concentration to a subset of ecologically significant input factors. Only a small number of approaches could be considered as suitable for several reasons including the model complexity, engagement of numerous interacting parameters and relatively long time of a single simulation. Thus, sensitivity analysis has been carried out with the use of the Morris method and later enriched by the computation of the correlation ratios of the selected parameters on the model response at more than a few locations in the modelled area. The obtained results are in agreement with expert knowledge of the ecological processes in the North Sea and correspond well with local characteristics.     

Impact of the quality of climate models for modelling species occurrences in countries with poor climatic documentation: a case study from Bolivia

The quality of climate models has largely been overlooked as a possible source of uncertainty that may affect the outcomes of species distribution models, especially in the tropics, where comparatively few climatic stations are available. We compared the geographical discrepancies and potential conservation implications of using two different climate models (Saga and Worldclim) in combination with the species modelling approach Maxent in Bolivia. We estimated ranges of selected bird and fern species biogeographically restricted to either humid montane forest of the northern Bolivian Andes or seasonal dry tropical forests (in the Andes and southern lowlands). Saga and Worldclim predicted roughly similar climate patterns of temperature that were significantly correlated. Precipitation layers of both climate models were also roughly similar, but showed important differences. Species ranges estimated with Worldclim and Saga likewise produced different results. Ranges of species endemic to humid montane forests estimated with Saga had higher AUC (Area under the curve) values than those estimated with Worldclim, which for example predicted the occurrence of humid montane forest bird species near Lake Titicaca, an area that is clearly unsuitable for these species. Likewise, Worldclim overpredicted the occurrence of fern and bird species in the lowlands of the Chapare region and well south of the Andean Elbow, where more seasonal biomes occur. By contrast, Saga predictions were coherent with the known distribution of humid montane forests in the northern Bolivian Andes. Estimated ranges of species endemic to seasonal dry tropical forests predicted with Saga and Worldclim were not statistically different in most cases. However, detailed comparisons revealed that Saga was able to distinguish fragments of seasonal dry tropical forests in rain-shadow valleys of the northern Bolivian Andes, whereas Worldclim was not. These differences highlight the neglected influence of climate layers on modelling results and the importance of using the most accurate climate data available when modelling species distributions.     

Development of a hydrothermal time seed germination model which uses the Weibull distribution to describe base water potential

Seed germination has been modelled extensively using hydrothermal time (HTT) models, that predict time to germination as a function of the extent to which seedbed temperature, T, and water potential, Ψ, exceed the base temperature, T_b, and base water potential, Ψ_b, of each seed percentile, g. Within a seed population the variation in time to germination arises from variation in Ψ_b(g) modelled by a normal distribution. We tested the assumption of normality in the distribution of Ψ_b(g) by germinating seed of two unrelated species with non-dormant seed (Buddleja davidii (Franch.) and Pinus radiata D. Don) across a range of constant Ψ at sub-optimal T. When incorporated into a HTT model the Weibull distribution more accurately described both the right skewed distribution of Ψ_b(g) and germination time course over sub-optimal T than the HTT based on the normal distribution, for both species. Given the flexibility of the Weibull distribution this model not only provides a useful method for predicting germination but also a means of determining the distribution of Ψ_b(g).