On the Importance of Nanoparticle Necks and Carbon Impurities for Charge Trapping in TiO2

Particle attachment and neck formation inside TiO2 nanoparticle networks determine materials performance in sensing, photo-electrochemistry, and catalysis. Nanoparticle necks can feature point defects with potential impact on the separation and recombination of photogenerated charges. Here, we investigated with electron paramagnetic resonance a point defect that traps electrons and predominantly forms in aggregated TiO2 nanoparticle systems. The associated paramagnetic center resonates in the g factor range between g = 2.0018 and 2.0028. Structure characterization and electron paramagnetic resonance data suggest that during materials processing, the paramagnetic electron center accumulates in the region of nanoparticle necks, where O2 adsorption and condensation can occur at cryogenic temperatures. Complementary density functional theory calculations reveal that residual carbon atoms, which potentially originate from synthesis, can substitute oxygen ions in the anionic sublattice, where they trap one or two electrons that mainly localize at the carbon. Their emergence upon particle neck formation is explained by the synthesis- and/or processing-induced particle attachment and aggregation facilitating carbon atom incorporation into the lattice. This study represents a substantial advance in linking dopants, point defects, and their spectroscopic fingerprints to microstructural features of oxide nanomaterials

On the Importance of Nanoparticle Necks and Carbon Impurities for Charge Trapping in TiO2

Particle attachment and neck formation inside TiO 2 nanoparticle networks determine materials performance in sensing, photo-electrochemistry, and catalysis. Nanoparticle necks can feature point defects with potential impact on the separation and recombination of photogenerated charges. Here, we investigated with electron paramagnetic resonance a point defect that traps electrons and predominantly forms in aggregated TiO 2 nanoparticle systems. The associated paramagnetic center resonates in the g factor range between g = 2.0018 and 2.0028. Structure characterization and electron paramagnetic resonance data suggest that during materials processing, the paramagnetic electron center accumulates in the region of nanoparticle necks, where O 2 adsorption and condensation can occur at cryogenic temperatures. Complementary density functional theory calculations reveal that residual carbon atoms, which potentially originate from synthesis, can substitute oxygen ions in the anionic sublattice, where they trap one or two electrons that mainly localize at the carbon. Their emergence upon particle neck formation is explained by the synthesis- and/or processing-induced particle attachment and aggregation facilitating carbon atom incorporation into the lattice. This study represents a substantial advance in linking dopants, point defects, and their spectroscopic fingerprints to microstructural features of oxide nanomaterials

A carrying capacity framework for soil phosphorus and hydrological sensitivity from farm to catchment scales

Publication history: Accepted - 30 May 2019; Published online - 4 June 2019.Agricultural fieldswith above optimumsoil phosphorus (P) are considered to pose risks to water quality and especially when those areas are coincident with hydrologically sensitive areas (HSAs) that focus surface runoff pathways. This is a challenge tomanage in areas of agricultural intensity in surfacewater dominated catchments where water quality targets have to be met. In this study, a soil P survey of 13 sub-catchments and 7693 fields was undertaken in a 220 km2 catchment. HSAs were also determined as the top 25th percentile risk froma runoff routingmodel that used a LiDAR digital elevation model and soil hydraulic conductivity properties. Distributions of these spatial data were compared with river soluble reactive phosphorus (SRP) concentration measured fortnightly over one year. The results showed that 41% of fields exceeded the agronomic optimumfor soil P across the sub-catchments.When compared with the available water quality data, the results indicated that the high soil P carrying capacity area of the sub-catchmentswas 15%. Combining high soil P and HSA, the carrying capacity area of the sub-catchmentswas 1.5%. The opportunities to redistribute these riskswere analysed on fields with below optimum soil P and where HSA risk was also minimal. These ranged from 0.4% to 13.8% of sub-catchment areas and this limited potential, unlikely to fully reduce the P pressure to over-supplied fields, would need to be considered alongside addressing this over-supply and also with targeted HSA interception measures.This work was undertaken as a component of the “EU EAA Soil Sampling and Analysis Scheme”, funded by the Department of Agriculture, Environment and Rural Affairs (DAERA), Northern Ireland, under the European Union Exceptional Adjustment Aid Scheme.We thank catchment farmers for land access and participation. We acknowledge the contributions of AFBI scientific staffwhowere instrumental in the planning, acquisition and processing of data, Colleen Ward (AFBI Project Manager) and Peter Scott (DAERA lead). Finally we thank both anonymous reviewers for insightful comments and suggestions on the manuscript

Dwarf alleles differentially affect barley root traits influencing nitrogen acquisition under low nutrient supply

Sustainable food production depends critically on the development of crop genotypes that exhibit high yield under reduced nutrient inputs. Rooting traits have been widely advocated as being able to influence optimal plant performance, while breeding-based improvements in yield of spring barley suggest that this species is a good model crop. To date, however, molecular genetics knowledge has not delivered realistic plant ideotypes, while agronomic trials have been unable to identify superior traits. This study explores an intermediate experimental system in which root traits and their effect on plant performance can be quantified. As a test case, four modern semi-dwarf barley varieties, which possess either the ari-e.GP or the sdw1 dwarf allele, were compared with the long-stemmed old variety Kenia under two levels of nutrient supply. The two semi-dwarf types differed from Kenia, exhibiting smaller stem mass and total plant nitrogen (N), and improved partitioning of mass and N to grain. Amongst the semi-dwarfs, the two ari-e.GP genotypes performed better than the two sdw1 genotypes under standard and reduced nutrient supply, particularly in root mass, root investment efficiency, N acquisition, and remobilization of N and mass to grain. However, lack of between-genotype variation in yield and N use efficiency indicated limited potential for exploiting genetic variation in existing varieties to improve barley performance under reduced nutrient inputs. Experimental approaches to test the expression of desirable root and shoot traits are scrutinized, and the potential evaluated for developing a spring barley ideotype for low nutrient conditions

Melting and differentiation of early-formed asteroids: The perspective from high precision oxygen isotope studies

A number of distinct methodologies are available for determining the oxygen isotope composition of minerals and rocks, these include laser-assisted fluorination, secondary ion mass spectrometry (SIMS)and UV laser ablation. In this review we focus on laser-assisted fluorination, which currently achieves the highest levels of precision available for oxygen isotope analysis. In particular, we examine how results using this method have furthered our understanding of early-formed differentiated meteorites. Due to its rapid reaction times and low blank levels, laser-assisted fluorination has now largely superseded the conventional externally-heated Ni “bomb” technique for bulk analysis. Unlike UV laser ablation and SIMS analysis, laser-assisted fluorination is not capable of focused spot analysis. While laser fluorination is now a mature technology, further analytical improvements are possible via refinements to the construction of sample chambers, clean-up lines and the use of ultra-high resolution mass spectrometers. High-precision oxygen isotope analysis has proved to be a particularly powerful technique for investigating the formation and evolution of early-formed differentiated asteroids and has provided unique insights into the interrelationships between various groups of achondrites. A clear example of this is seenin samples that lie close to the terrestrial fractionation line (TFL). Based on the data from conventional oxygen isotope analysis, it was suggested that the main-group pallasites, the howardite eucrite diogenite suite (HEDs) and mesosiderites could all be derived from a single common parent body. However,high precision analysis demonstrates that main-group pallasites have a Δ17O composition that is fully resolvable from that of the HEDs and mesosiderites, indicating the involvement of at least two parent bodies. The range of Δ17O values exhibited by an achondrite group provides a useful means of assessing the extent to which their parent body underwent melting and isotopic homogenization. Oxygen isotope analysis can also highlight relationships between ungrouped achondrites and the more well-populated groups. A clear example of this is the proposed link between the evolved GRA 06128/9 meteorites and the brachinites. The evidence from oxygen isotopes, in conjunction with that from other techniques, indicates that we have samples from approximately 110 asteroidal parent bodies (∼60 irons, ∼35 achondrites and stony-iron, and ∼15 chondrites) in our global meteorite collection. However, compared to the likely size of the original protoplanetary asteroid population, this is an extremely low value. In addition, almost all of the differentiated samples (achondrites, stony-iron and irons) are derived from parent bodies that were highly disrupted early in their evolution. High-precision oxygen isotope analysis of achondrites provides some important insights into the origin of mass-independent variation in the early Solar System. In particular, the evidence from various primitive achondrite groups indicates that both the slope 1 (Y&R) and CCAM lines are of primordial significance. Δ17O differences between water ice and silicate-rich solids were probably the initial source of the slope 1 anomaly. These phases most likely acquired their isotopic composition as a result of UV photo-dissociation of CO that took place either in the early solar nebula or precursor giant molecular cloud. Such small-scale isotopic heterogeneities were propagated into larger-sized bodies, such as asteroids and planets, as a result of early Solar System processes, including dehydration, aqueous alteration,melting and collisional interactions

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Predicting the future of forests in the Mediterranean under climate change, with niche- and process-based models: CO2 matters!

Assessing the potential future of current forest stands is a key to design conservation strategies and understanding potential future impacts to ecosystem service supplies. This is particularly true in the Mediterranean basin, where important future climatic changes are expected. Here, we assess and compare two commonly used modeling approaches (niche- and process-based models) to project the future of current stands of three forest species with contrasting distributions, using regionalized climate for continental Spain. Results highlight variability in model ability to estimate current distributions, and the inherent large uncertainty involved in making projections into the future. CO2 fertilization through projected increased atmospheric CO2 concentrations is shown to increase forest productivity in the mechanistic process-based model (despite increased drought stress) by up to three times that of the non-CO2 fertilization scenario by the period 2050-2080, which is in stark contrast to projections of reduced habitat suitability from the niche-based models by the same period. This highlights the importance of introducing aspects of plant biogeochemistry into current niche-based models for a realistic projection of future species distributions. We conclude that the future of current Mediterranean forest stands is highly uncertain and suggest that a new synergy between niche- and process-based models is urgently needed in order to improve our predictive ability

Seasonal changes in plankton respiration and bacterial metabolism in a temperate shelf sea

The seasonal variability of plankton metabolism indicates how much carbon is cycling within a system, as well as its capacity to store carbon or export organic matter and CO2 to the deep ocean. Seasonal variability between November 2014, April 2015 and July 2015 in plankton respiration and bacterial (Bacteria+Archaea) metabolism is reported for the upper and bottom mixing layers at two stations in the Celtic Sea, UK. Upper mixing layer (UML, >75 m in November, 41 - 70 m in April and ~50 m in July) depth-integrated plankton metabolism showed strong seasonal changes with a maximum in April for plankton respiration (1.2- to 2-fold greater compared to November and July, respectively) and in July for bacterial production (2-fold greater compared to November and April). However UML depth-integrated bacterial respiration was similar in November and April and 2-fold lower in July. The greater variability in bacterial production compared to bacterial respiration drove seasonal changes in bacterial growth efficiencies, which had maximum values of 89 % in July and minimum values of 5 % in November. Rates of respiration and gross primary production (14C-PP) also showed different seasonal patterns, resulting in seasonal changes in 14C-PP:CRO2 ratios. In April, the system was net autotrophic (14C-PP:CRO2 > 1), with a surplus of organic matter available for higher trophic levels and export, while in July balanced metabolism occurred (14C-PP:CRO2 = 1) due to an increase in plankton respiration and a decrease in gross primary production. Comparison of the UML and bottom mixing layer indicated that plankton respiration and bacterial production were higher (between 4 and 8-fold and 4 and 7-fold, respectively) in the UML than below. However, the rates of bacterial respiration were not statistically different (p > 0.05) between the two mixing layers in any of the three sampled seasons. These results highlight that, contrary to previous data from shelf seas, the production of CO2 by the plankton community in the UML, which is then available to degas to the atmosphere, is greater than the respiratory production of dissolved inorganic carbon in deeper waters, which may contribute to offshore export

Variation in the angiosperm ionome

The ionome is defined as the elemental composition of a subcellular structure, cell, tissue, organ or organism. The subset of the ionome comprising mineral nutrients is termed the functional ionome. A ‘standard functional ionome’ of leaves of an ‘average’ angiosperm, defined as the nutrient composition of leaves when growth is not limited by mineral nutrients, is presented and can be used to compare the effects of environment and genetics on plant nutrition. The leaf ionome of a plant is influenced by interactions between its environment and genetics. Examples of the effects of the environment on the leaf ionome are presented and the consequences of nutrient deficiencies on the leaf ionome are described. The physiological reasons for (1) allometric relationships between leaf nitrogen and phosphorus concentrations and (2) linear relationships between leaf calcium and magnesium concentrations are explained. It is noted that strong phylogenetic effects on the mineral composition of leaves of angiosperm species are observed even when sampled from diverse environments. The evolutionary origins of traits including (1) the small calcium concentrations of Poales leaves, (2) the large magnesium concentrations of Caryophyllales leaves, and (3) the large sulfur concentrations of Brassicales leaves are traced using phylogenetic relationships among angiosperm orders, families and genera. The rare evolution of hyperaccumulation of toxic elements in leaves of angiosperms is also described. Consequences of variation in the leaf ionome for ecology, mineral cycling in the environment, strategies for phytoremediation of contaminated land, sustainable agriculture, and the nutrition of livestock and humans are discussed

Making the most of what we have: Application of extrapolation approaches in radioecological wildlife transfer models

© 2015 The Authors. We will never have data to populate all of the potential radioecological modelling parameters required for wildlife assessments. Therefore, we need robust extrapolation approaches which allow us to make best use of our available knowledge. This paper reviews and, in some cases, develops, tests and validates some of the suggested extrapolation approaches.The concentration ratio (CRproduct-diet or CRwo-diet) is shown to be a generic (trans-species) parameter which should enable the more abundant data for farm animals to be applied to wild species.An allometric model for predicting the biological half-life of radionuclides in vertebrates is further tested and generally shown to perform acceptably. However, to fully exploit allometry we need to understand why some elements do not scale to expected values.For aquatic ecosystems, the relationship between log10(a) (a parameter from the allometric relationship for the organism-water concentration ratio) and log(Kd) presents a potential opportunity to estimate concentration ratios using Kd values.An alternative approach to the CRwo-media model proposed for estimating the transfer of radionuclides to freshwater fish is used to satisfactorily predict activity concentrations in fish of different species from three lakes. We recommend that this approach (REML modelling) be further investigated and developed for other radionuclides and across a wider range of organisms and ecosystems.Ecological stoichiometry shows potential as an extrapolation method in radioecology, either from one element to another or from one species to another.Although some of the approaches considered require further development and testing, we demonstrate the potential to significantly improve predictions of radionuclide transfer to wildlife by making better use of available data