Core Ideas
A new ImageJ plugin, TopCap, automatically captures soil surface complexity from CT images.
TopCap can quantify the immediate subsurface structure, highlighting soil crusting and sealing.
...Crust thickness varies under different soil textures following similar rainfall.
The surface of a material such as soil, as characterized by its topology and roughness, typically has a profound effect on its functional behavior. While nondestructive imaging techniques such as X‐ray computed tomography (CT) have been used extensively in recent years to characterize the internal architecture of soil, less attention has been paid to the morphology of the soil surface, possibly because other techniques such as scanning electron microscopy and atomic force microscopy are viewed as more appropriate. However, X‐ray CT exploration of the surface of a soil also permits analyses immediately below its surface and beyond into the sample, contingent on its thickness. This provides important information such as how a connected structure might permit solute infiltration or gaseous diffusion through the surface and beyond into the subsurface matrix. A previous limitation to this approach had been the inability to segment and quantify the actual three‐dimensional structural complexity at the surface, rather than a predefined geometrically simplistic volume immediately below it. To overcome this, we formulated TopCap, a novel algorithm that operates with ImageJ as a plugin and automatically captures the actual three‐dimensional surface morphology, segments the pore structure within the acquired volume, and provides a series of incisive morphological measurements of the associated porous architecture. TopCap provides rapid, automated analysis of the immediate surface of materials and beyond, and while developed in the context of soil, is applicable to any three‐dimensional image volume.
The Environment Agency has been using Gas Chromatography–Mass Spectrometry (GC–MS) and Accurate-mass Quadrupole Time-of-Flight (Q-TOF) / Liquid Chromatography-Mass Spectrometry (LC-MS) target screen ...analysis to semi-quantitatively measure organic substances in groundwater and surface water since 2009 for GC–MS and 2014 for LC-MS. Here we use this data to generate a worst-case “risk” ranking of the detected substances. Three sets of hazard values relating to effects on aquatic organisms, namely Water Framework Directive EQSs, NORMAN Network PNECs (hereafter NORMAN PNEC) and chronic Species Sensitivity Distribution (SSD) HC50s from Posthuma et al., (2019) were used for the assessment. These hazard values were compared to the highest measured concentration for each chemical to generate a worst-case hazard quotient (HQ). Calculated HQs for each metric were ranked, averaged and multiplied by rank for detection frequency to generate an overall ordering based on HQ and occurrence. This worst-case approach was then used to generate ranking lists for GC–MS and LC-MS detected substances in groundwater and surface water. Pesticides in the top 30 overall ranked list included more legacy pesticides in groundwater and more current use actives in surface water. Specific uses were linked to some high rankings (e.g. rotenone for invasive species control). A number of industrial and plastics associated chemicals were ranked highly in the groundwater dataset, while more personal care products and pharmaceuticals were highly ranked in surface waters. Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) compounds were commonly highly ranked in both environmental compartments. The approach confirmed high rankings for some substance (e.g. selected pesticides) from previous prioritization exercises, but also identified novel substance for consideration (e.g. some PFAS compounds and pharmaceuticals). Overall our approach provided a simple approach using readily accessible data to identify substances for further and more detailed assessment.
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•Hazard values and ground/surface water measures were obtained for 1144 chemicals.•Worst case ranking was conducted by HQ and detection frequency.•Multiple pesticides and PFAS were highly ranked in both environments.•More personal care products and pharmaceuticals were highly ranked in surface waters.•More industrial and plastics additive were highly ranked in groundwater.
•GC–MS and LC-MS were used to quantify organic chemical mixtures.•Chronic SSD HC50s were used as the hazard metric to predict mixture effect.•Increased hazard was found from the presence of a ...cocktail of substances.•The most toxic chemical contributed ≥ 20% of mixture effect in >99% of cases.•Mixture complexity was only weakly associated with increased mixture effect.
Semi-quantitative GC-MS and LC-MS measurements of organic chemicals in groundwater and surface waters were used to assess the overall magnitude and contribution of the most important substances to calculated mixture hazard. Here we use GC-MS and LC-MS measurements taken from two separate national monitoring programs for groundwater and surface water in England, in combination with chronic species sensitivity distribution (SSD) HC50 values published by Posthuma et al. (2019, Environ. Toxicol. Chem, 38, 905–917) to calculate individual substance hazard quotients and mixture effects using a concentration addition approach. The mixture analysis indicated that, as anticipated, there was an increased hazard from the presence of a cocktail of substances at sites compared to the hazard for any single chemical. The magnitude of the difference between the hazard attributed to the most important chemical and the overall mixture effect, however, was not large. Thus, the most toxic chemical contributed ≥ 20% of the calculated mixture effect in >99% of all measured groundwater and surface water samples. On the basis of this analysis, a 5 fold assessment factor placed on the risk identified for any single chemical would offer a high degree of in cases where implementation of a full mixture analysis was not possible. This finding is consistent with previous work that has assessed chemical mixture effects within field monitoring programs and as such provides essential underpinning for future policy and management decisions on how to effectively and proportionately manage mixture risks.
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•X-ray CT was effectively used to quantify soil seal/crust thickness.•Different micro-morphological zones within seal layers were revealed.•Rainfall had a strong and rapid impact on water transport ...and retention in soil.•The existence of a soil-dependent raindrop impact threshold was hypothesized.
This study delivers new insights into rainfall-induced seal formation through a novel approach in the use of X-ray Computed Tomography (CT). Up to now seal and crust thickness have been directly quantified mainly through visual examination of sealed/crusted surfaces, and there has been no quantitative method to estimate this important property. X-ray CT images were quantitatively analysed to derive formal measures of seal and crust thickness. A factorial experiment was established in the laboratory using open-topped microcosms packed with soil. The factors investigated were soil type (three soils: silty clay loam – ZCL, sandy silt loam – SZL, sandy loam – SL) and rainfall duration (2–14 min). Surface seal formation was induced by applying artificial rainfall events, characterised by variable duration, but constant kinetic energy, intensity, and raindrop size distribution. Soil porosities derived from CT scans were used to quantify the thickness of the rainfall-induced surface seals and reveal temporal seal micro-morphological variations with increasing rainfall duration. In addition, the water repellency and infiltration dynamics of the developing seals were investigated by measuring water drop penetration time (WDPT) and unsaturated hydraulic conductivity (Kun). The range of seal thicknesses detected varied from 0.6 to 5.4 mm. Soil textural characteristics and OM content played a central role in the development of rainfall-induced seals, with coarser soil particles and lower OM content resulting in thicker seals. Two different trends in soil porosity vs. depth were identified: i) for SL soil porosity was lowest at the immediate soil surface, it then increased constantly with depth till the median porosity of undisturbed soil was equalled; ii) for ZCL and SL the highest reduction in porosity, as compared to the median porosity of undisturbed soil, was observed in a well-defined zone of maximum porosity reduction c. 0.24–0.48 mm below the soil surface. This contrasting behaviour was related to different dynamics and processes of seal formation which depended on the soil properties. The impact of rainfall-induced surface sealing on the hydrological behaviour of soil (as represented by WDTP and Kun) was rapid and substantial: an average 60% reduction in Kun occurred for all soils between 2 and 9 min rainfall, and water repellent surfaces were identified for SZL and ZCL. This highlights that the condition of the immediate surface of agricultural soils involving rainfall-induced structural seals has a strong impact in the overall ability of soil to function as water reservoir.
The COVID-19 pandemic has put unprecedented pressure on public health resources around the world. From adversity, opportunities have arisen to measure the state and dynamics of human disease at a ...scale not seen before. In the United Kingdom, the evidence that wastewater could be used to monitor the SARS-CoV-2 virus prompted the development of National wastewater surveillance programmes. The scale and pace of this work has proven to be unique in monitoring of virus dynamics at a national level, demonstrating the importance of wastewater-based epidemiology (WBE) for public health protection. Beyond COVID-19, it can provide additional value for monitoring and informing on a range of biological and chemical markers of human health. A discussion of measurement uncertainty associated with surveillance of wastewater, focusing on lessons-learned from the UK programmes monitoring COVID-19 is presented, showing that sources of uncertainty impacting measurement quality and interpretation of data for public health decision-making, are varied and complex. While some factors remain poorly understood, we present approaches taken by the UK programmes to manage and mitigate the more tractable sources of uncertainty. This work provides a platform to integrate uncertainty management into WBE activities as part of global One Health initiatives beyond the pandemic.
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•Wastewater is a relatively unbiased medium transporting multiple markers of human health.•Biological- and chemical-based Wastewater-Based Epidemiology provides flexibility and resilience for public health security.•Measurements of target analytes in wastewater are subject to variability and uncertainty.•Identifying and mitigating uncertainty requires multi-disciplinary collaboration.•UK wastewater monitoring programmes have generated a substantial data resource to derive better understanding of uncertainty.
Hyperspectral (HS) data represents an extremely powerful means for rapidly detecting crop stress and then aiding in the rational management of natural resources in agriculture. However, large volume ...of data poses a challenge for data processing and extracting crucial information. Multivariate statistical techniques can play a key role in the analysis of HS data, as they may allow to both eliminate redundant information and identify synthetic indices which maximize differences among levels of stress. In this paper we propose an integrated approach, based on the combined use of Principal Component Analysis (PCA) and Canonical Discriminant Analysis (CDA), to investigate HS plant response and discriminate plant status. The approach was preliminary evaluated on a data set collected on durum wheat plants grown under different nitrogen (N) stress levels. Hyperspectral measurements were performed at anthesis through a high resolution field spectroradiometer, ASD FieldSpec HandHeld, covering the 325-1075 nm region. Reflectance data were first restricted to the interval 510-1000 nm and then divided into five bands of the electromagnetic spectrum green: 510-580 nm; yellow: 581-630 nm; red: 631-690 nm; red-edge: 705-770 nm; near-infrared (NIR): 771-1000 nm. PCA was applied to each spectral interval. CDA was performed on the extracted components to identify the factors maximizing the differences among plants fertilised with increasing N rates. Within the intervals of green, yellow and red only the first principal component (PC) had an eigenvalue greater than 1 and explained more than 95% of total variance; within the ranges of red-edge and NIR, the first two PCs had an eigenvalue higher than 1. Two canonical variables explained cumulatively more than 81% of total variance and the first was able to discriminate wheat plants differently fertilised, as confirmed also by the significant correlation with aboveground biomass and grain yield parameters. The combined approach proved to be effective, being able to synthesise the redundant radiometric information in a reduced number of indicators of plant nutritional status, which could be utilized to delineate homogeneous within-field areas to be submitted to site-specific fertilization.
The potential effect of climate change on the optimal allocation of irrigation water was investigated for a Southern Italy district. The study was carried out on 5 representative crops (grapevine, ...olive, sugar beet, processing tomato, asparagus), considering six simulated climate change conditions, corresponding to three 30-year periods (2011-2040; 2041-2070; 2071-2100) for two greenhouse gas emission schemes proposed by IPCC (A2 and B1), plus the current climatic condition. The framework adopted was based on: i) the modeling of crop yield response for increasing levels of water supply, under current and future climatic conditions, through a non-linear regression equation and ii) the definition of the best water allocation by means of a mathematical optimization model written in GAMS. Total irrigation water (TIW) volume was allowed to vary from a low total supply 10000 m3 to 7000000 m3, whilst a fixed surface, corresponding to that currently occupied in the studied district, was assigned to each crop. The economic return was studied in terms of Value of Production less the fixed and variable irrigation costs (VPlic). The TIW volume that maximized the VPlic of the whole district surface under the current climatic condition was 5697861 m3. The total volume was partitioned among the five crops as a function of the surface occupied: grapevine>olive>processing tomato>asparagus>sugar beet. Nevertheless, grapevine and olive received seasonal volumes corresponding only to 59 and 50% of total irrigation water requirements. On the contrary, processing tomato and asparagus received seasonal water volumes close to those fully satisfying irrigation water requirements (100% and 85% ETc). Future climatic conditions slightly differed from the current one for the expected optimal allocation. Under water shortage conditions (160000 m3) the whole irrigation water was allocated to the horticultural crops. Forecasted growing season features varied to a different extent in relation to crop and scenario considered with the more intense changes observed for A2 and olive.
Biodiesel Co-Product (BCP) is a complex organic material formed during the transesterification of lipids. We investigated the effect of BCP on the extracellular microbial matrix or ‘extracellular ...polymeric substance’ (EPS) in soil which is suspected to be a highly influential fraction of soil organic matter (SOM). It was hypothesised that more N would be transferred to EPS in soil given BCP compared to soil given glycerol. An arable soil was amended with BCP produced from either 1) waste vegetable oils or 2) pure oilseed rape oil, and compared with soil amended with 99% pure glycerol; all were provided with 15N labelled KNO3. We compared transfer of microbially assimilated 15N into the extracellular amino acid pool, and measured concomitant production of exopolysaccharide. Following incubation, the 15N enrichment of total hydrolysable amino acids (THAAs) indicated that intracellular anabolic products had incorporated the labelled N primarily as glutamine and glutamate. A greater proportion of the amino acids in EPS were found to contain 15N than those in the THAA pool, indicating that the increase in EPS was comprised of bioproducts synthesised de novo. Moreover, BCP had increased the EPS production efficiency of the soil microbial community (μg EPS per unit ATP) up to approximately double that of glycerol, and caused transfer of 21% more 15N from soil solution into EPS-amino acids. Given the suspected value of EPS in agricultural soils, the use of BCP to stimulate exudation is an interesting tool to consider in the theme of delivering sustainable intensification.
•BCP made from waste oils (BCPR) resulted in the highest EPS-production efficiencies.•BCPR resulted in the greatest 15N accumulation in extracellular bioproducts.•Glycerol resulted in the greatest 15N accumulation in intracellular bioproducts.•δ15N of extracellular amino acids shows that resin extracts EPS synthesised de novo.•Leucine in EPS was the most enriched soil amino acid measured (up to 29% 15N).
A complete vibrational state-specific kinetic scheme describing dissociating carbon dioxide mixtures is proposed. CO2 symmetric, bending and asymmetric vibrations and dissociation-recombination are ...strongly coupled through intermode vibrational energy transfers. Comparative study of state-resolved rate coefficients is carried out; the effect of different transitions may vary considerably with temperature. A nonequilibrium 1-D boundary layer flow typical to hypersonic planetary entry is studied in the state-to-state approach. To assess the sensitivity of fluid-dynamic variables and heat transfer to various vibrational transitions and chemical reactions, corresponding processes are successively included to the kinetic scheme. It is shown that vibrational–translational (VT) transitions in the symmetric and asymmetric modes do not alter the flow and can be neglected whereas the VT2 exchange in the bending mode is the main channel of vibrational relaxation. Intermode vibrational exchanges affect the flow implicitly, through energy redistribution enhancing VT relaxation; the dominating role belongs to near-resonant transitions between symmetric and bending modes as well as between CO molecules and CO2 asymmetric mode. Strong coupling between VT2 relaxation and chemical reactions is emphasized. While vibrational distributions and average vibrational energy show strong dependence on the kinetic scheme, the heat flux is more sensitive to chemical reactions.
Coupled state-to-state vibrational-chemical kinetics, gas dynamics, and heat transfer in the five-component mixture of dissociated CO2 are studied using the complete three-mode kinetic model and the ...reduced scheme involving mainly the vibrational states of the asymmetric mode. The emphasis is on the effect of asymmetric vibrations on the rate of dissociation, fluid dynamic variables, and heat flux. It is shown that intermode vibrational energy transitions between CO and CO2 asymmetric mode may considerably decrease the rate of dissociation; the presence of CO in the mixture quickly depletes high vibrational states and thus inhibits dissociation at low temperatures. The reduced model overpredicts populations of highly located states of the asymmetric mode, especially when intermode VV transitions are neglected; therefore, using the simplified model in flows with dominating dissociation may yield overestimated dissociation rate. In the hypersonic flow along the stagnation line, the influence of asymmetric vibrations on the fluid dynamics and heat transfer is weak; the main role belongs to chemical reactions and VT transitions in the bending mode. In this case, the computationally efficient simplified model can be used to predict macroscopic variables and heat flux without significant loss of accuracy.
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