36 research outputs found

    X-ray CT-derived soil characteristics explain varying air, water, and solute transport properties across a loamy field

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    The characterization of soil pore space geometry is important for explaining fluxes of air, water, and solutes through soil and understanding soil hydrogeochemical functions. X‐ray computed tomography (CT) can be applied for this characterization, and in this study CT‐derived parameters were used to explain water, air, and solute transport through soil. Forty‐five soil columns (20 by 20 cm) were collected from an agricultural field in Estrup, Denmark, and subsequently scanned using a medical CT scanner. Nonreactive tracer leaching experiments were performed in the laboratory along with measurements of air permeability (Ka) and saturated hydraulic conductivity (Ksat). The CT number of the matrix (CTmatrix), which represents the moist bulk density of the soil matrix, was obtained from the CT scans as the average CT number of the voxels in the grayscale image excluding macropores and stones. The CTmatrix showed the best relationships with the solute transport characteristics, especially the time by which 5% of the applied mass of tritium was leached, known as the 5% arrival time (t0.05). The CT‐derived macroporosity (pores >1.2 mm) was correlated with Ka and log10(Ksat). The correlation improved when the limiting macroporosity (the minimum macroporosity for every 0.6‐mm layer along the soil column) was used, suggesting that soil layers with the narrowest macropore section restricted the flow through the whole soil column. Water, air, and solute transport were related with the CT‐derived parameters by using a best subsets regression analysis. The regression coefficients improved using CTmatrix, limiting macroporosity, and genus density, while the best model for t0.05 used CTmatrix only. The scanning resolution and the time for soil structure development after mechanical activities could be factors that increased the uncertainty of the relationships. Nevertheless, the results confirmed the potential of X‐ray CT visualization techniques for estimating fluxes through soil at the field scale

    Hydroxyapatite-activated seaweed biochar for enhanced remediation of fluoride contaminated soil at various pH ranges

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    This research article was published by Elsevier, 2023This study investigated the defluoridation efficiency of hydroxyapatite-activated seaweed (Eucheuma Cottonii) biochar (HSB) at various soil pH ranges (3–11) while monitoring the impact of contact time (30 min - 2.5 h), adsorbent dosage (0.1–0.5 g) as well as the initial fluoride concentration and compare its performance to its respective seaweed biochar (SB). Activation of SB with the hydroxyapatite lead to a shift in its point-zero-charge (pHPZC) from 6 to 7.4 broadening its defluoridation pH range from a solitary 5 to amid 3 through 11. The fluoride adsorption mechanism was found to follow both Langmuir (R2 = 0.956) and Freundlich (R2 = 0.942) isotherm models with a maximum defluoridation capacity of 3.03 mg/g equivalent to the defluoridation efficiency of 79%. This is accounted to the existence of soil ions, SB active sites, and the attached hydroxyapatite, as fluoride adsorption sites each exhibiting a dissimilar fluoride removal mechanism. Therefore, the HSB could be a promising adsorbent for fluoride removal in the fluoride contaminated agricultural soils of inclusive pH ranges

    Prediction of the glyphosate sorption coefficient across two loamy agricultural fields

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    Sorption is considered one of the most important processes controlling pesticide mobility in agricultural soils. Accurate predictions of sorption coefficients are needed for reliable risk assessments of groundwater contamination from pesticides. In this work, we aim to estimate the glyphosate sorption coefficient, Kd, from easily measurable soil properties in two loamy, agricultural fields in Denmark: Estrup and Silstrup. Forty-five soil samples in Estrup and 65 in Silstrup were collected from the surface in a rectangular grid of 15 × 15-m from each field, and selected soil properties and glyphosate sorption coefficients were determined. Multiple linear regression (MLR) analyses were performed using nine geo-referenced soil properties as variables to identify the parameters related with glyphosate sorption. Scenarios considered in the analyses included: (i) each field separately, (ii) both fields together, and (iii) northern and southern sections of the field in Silstrup. Considering correlations with all possible sets of the same nine geo-referenced properties, a best-four set of parameters was identified for each model scenario. The best-four set for the field in Estrup included clay, oxalate-extractable Fe, Olsen P and pH, while the best-four set for Silstrup included clay, OC, Olsen P and EC. When the field in Silstrup was separated in a northern and southern section, the northern section included EC, and oxalate-extractable Fe, Al and P, whereas the southern part included pH, clay, OC and Olsen P. The best-four set for both fields together included clay, sand, pH and EC. Thus, the most common parameters repeated in the best-four sets included clay and pH as also reported previously in the literature, but in general, the composition of the best-four set differed for each scenario, suggesting that different properties control glyphosate sorption in different locations and at different scales of analysis. Better predictions were obtained for the best-four set for the field in Estrup (R2 = 0.87) and for both fields (R2 = 0.70), while the field in Silstrup showed a lower predictability (R2 = 0.36). Possibly, the low predictability for the field in Silstrup originated from opposing gradients in clay and oxalate-extractable Fe across the field. Also, whereas a lower clay content in Estrup may be the limiting variable for glyphosate sorption, the field in Silstrup has a higher clay content not limiting the sorption, but introducing more variability in Kd due to changes in other soil properties

    Predictivity Strength of the Spatial Variability of Phenanthrene Sorption Across Two Sandy Loam Fields

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    Sorption is commonly agreed to be the major process underlying the transport and fate of polycyclic aromatic hydrocarbons (PAHs) in soils. However, there is still a scarcity of studies focusing on spatial variability at the field scale in particular. In order to investigate the variation in the field of phenanthrene sorption, bulk topsoil samples were taken in a 15 × 15-m grid from the plough layer in two sandy loam fields with different texture and organic carbon (OC) contents (140 samples in total). Batch experiments were performed using the adsorption method. Values for the partition coefficient K d (L kg−1) and the organic carbon partition coefficient K OC (L kg−1) agreed with the most frequently used models for PAH partitioning, as OC revealed a higher affinity for sorption. More complex models using different OC compartments, such as non-complexed organic carbon (NCOC) and complexed organic carbon (COC) separately, performed better than single K OC models, particularly for a subset including samples with Dexter n < 10 and OC <0.04 kg kg−1. The selected threshold revealed that K OC-based models proved to be applicable for more organic fields, while two-component models proved to be more accurate for the prediction of K d and retardation factor (R) for less organic soils. Moreover, OC did not fully reflect the changes in phenanthrene retardation in the field with lower OC content (Faardrup). Bulk density and available water content influenced the phenanthrene transport mechanism phenomenon

    Linking pore network characteristics extracted from CT images to the transport of solute and colloid tracers in soils under different tillage managements

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    The understanding of relations between quantitative information of soil structure from X-ray computed tomography (CT) and soil functions is an important topic in agronomy and soil science. The influence of tillage on macroporosity (i.e., pores measured by CT >240â€ŻÎŒm in all directions) could be manifested in their effects on solute and colloid transport properties. Tillage will also have crucial importance on preferential flow; i.e., a direct flow through root and earthworm channels. Increasing knowledge of the relationships between soil tillage, structure, and transport contributes to a deeper insight into the key factors of soil management influencing productivity, environmental quality and crop health. The aim of this work is the identification of relationships between soil management of the pore network and the influence of the characteristics of the paths identified by CT on the transport of solute and colloidal tracers. In this work, we used CT to characterize the macropore network ( >0.24 mm) of sixteen columns (100 height × 84 diameter, mm) of adjacent plots under different soil management as follows: conventional management with shallow tillage after sowing (4 samples), conventional management with no tillage after sowing (4 samples), and organic vegetables (8 samples). The soil samples were installed in columns under a dripper, and the transport behavior was examined during breakthrough of Br− and 1-ÎŒm latex microspheres in samples near saturation. Transport of Br− and latex microspheres was modeled using a two-region physical non-equilibrium model (dual porosity). Preferential flow was higher under organic management, although the pore water velocities were, in general, lower. The preferential flow of Br− was correlated with the total volume of macropores extracted from each tomography, and the local increase in the Hounsfield value (i.e., CT matrix density, CTMatrix) surrounding the macropores. The denser lining, produced by the earthworms in the inner walls of the pores, was inversely correlated with the kinetic exchange coefficient between mobile and immobile zones of the dual-porosity model. The macropore roughness indicated by the CT-macropore surface area was correlated with the solute dispersion coefficient and with the solute travel time. Finally, we found that the overall CTMatrix density is inversely related to the preferential flow. The importance of this work lies in the improvement of the accuracy of predictions related to flow and transport through soils, especially those processes that include particles traveling through the soil

    Bypass and hyperbole in soil science:A perspective from the next generation of soil scientists

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    International audienceWe, the co‐authors of this letter, are an international group of soil scientists at early career stages, from PhD students to postdoctoral researchers, lecturers, and research fellows with permanent positions. Here, we present our collective musings on soil research challenges and opportunities and, in particular, the points raised by Philippe Baveye (Baveye, 2020a, 2020b) and Johan Bouma (Bouma, 2020) on bypass and hyperbole in soil science. Raising awareness about these issues is a first and necessary step. To this end, we would like to thank Philippe Baveye and Johan Bouma for initiating this debate.......
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