Emmanuel Arthur

Direct and Indirect Short-term Effects of Biochar on Physical Characteristics of an Arable Sandy Loam

Abstract Biochar addition to agricultural soil is reported in several studies to reduce climate gas emissions, boost carbon storage, and improve soil fertility and crop productivity. These effects may be partly related to soil physical changes resulting from biochar amendment, but knowledge of how biochar application mechanistically affects soil physical characteristics is limited. This study investigated the effect of biochar application on soil structural and functional properties, including specific surface area, water retention, and gas transport parameters. Intact soil cores were taken from a field experiment on an arable sandy loam that included four reference plots without biochar and four plots with 20 tons ha−1 biochar incorporated into the upper 20 cm 7 months before sampling. Water retention was measured at matric potentials ranging from wet (pF 1.0) to extremely dry conditions (pF ∼6.8), whereas gas transport parameters (air permeability, ka, and gas diffusivity, Dp/Do, where Dp is the gas diffusion coefficient in soil and Do is the gas diffusion coefficient in free air) were measured between pF 2.0 and 3.0. Water retention under dry conditions and measured specific surface area were not significantly greater in the biochar-amended soil than the reference soil probably because of the relatively low biochar application rate. Yet, the biochar-amended soil showed a significant decrease in soil bulk density and an accompanying increase in total porosity. Water retention and air-filled porosity (&egr;) were both markedly greater in the biochar-amended soil than in the reference soil between pF 1.0 and 3.0. Soil macroporosity (equivalent to >0.1 mm pore diameter) and the ratio of macroporosity to total porosity were also significantly greater in the biochar-amended soil. As a result, the level of the pore organization (PO, ka/&egr;) was greater in the biochar-amended soil. Across the tested matric potentials, biochar amendment caused average increases of 28 to 34% in &egr;, 53 to 161% in Dp/Do, and 69 to 223% in ka, with the most significant increases occurring around natural field capacity (pF 2.0). Overall, the results suggest that biochar application even at a relatively low rate can alter soil functional characteristics, especially under normal field moisture conditions.

Effects of Past Copper Contamination and Soil Structure on Copper Leaching from Soil

Copper contamination affects biological, chemical, and physical soil properties and associated ecological functions. Changes in soil pore organization as a result of Cu contamination can dramatically affect flow and contaminant transport in polluted soils. This study assessed the influence of soil structure on the movement of water and Cu in a long-term polluted soil. Undisturbed soil cores collected along a Cu gradient (from about 20 to about 3800 mg Cu kg soil) were scanned using X-ray computed tomography (CT). Leaching experiments were performed to analyze tracer transport, colloid leaching, and dissolved organic carbon (DOC) and Cu losses. The 5% arrival time () and apparent dispersivity (λ) for tracer breakthrough were calculated by fitting the experimental data to a nonparametric, double-lognormal probability density function. Soil bulk density, which did not follow the Cu gradient, was the main driver of preferential flow, while macroporosity determined by X-ray CT (for pores >180 μm) proved the best predictor of solute transport. Higher preferential flow due to the presence of well-aligned pores and small cracks controlled water movement in compacted soil. Transport of Cu was rapid during the first flush (≈1 pore volume) in association with the movement of colloid particles, followed by slower transport in association with the movement of DOC in the soil solution. The relative amount of Cu released was strongly correlated with macroporosity as determined by X-ray CT, indicating the promising potential of this visualization technique for predicting contaminant transport through soil.

Compost Amendment to Sandy Soil Affects Soil Properties and Greenhouse Tomato Productivity

Sandy soils, with low productivity, could be improved by compost application to sustain crop production. This study aimed to examine the effect of three compost types (vegetable, fruit and yard waste compost, garden waste compost, and spent mushroom compost) on basic properties of a loamy sand and greenhouse tomato productivity. Disturbed and intact soil samples were taken from a decade-long compost field experiment on loamy sand with three compost types at application rate of 30 m3 ha−1 yr−1 (7.5 ton ha−1 yr−1). The soils were characterized for chemical and physical properties. Tomato was planted in a greenhouse using soil samples from the field and vegetative and yield parameters (plant height, stem diameter, leaf number, and fruit yield), water productivity, and harvest index were evaluated. All compost types significantly increased soil total carbon, total nitrogen, pH, electrical conductivity and significantly decreased bulk density, with no effect on plant available water compared to the control. Fresh and dry fruit weights were significantly increased after compost addition. Plant height, leaf number, stem diameter, and total biomass did not significantly improve after compost addition. Spent mushroom compost had greater effect in improving tomato productivity. A decade-long application of composts on loamy sand improved basic chemical and physical properties which were reflected in increased fruit yield in tomato. Since no negative effect of compost was observed, we suggest that sandy soils may serve as a safe end use option for these composts and potentially support crop growth.

Pore Structure Characteristics after 2 Years of Biochar Application to a Sandy Loam Field

Abstract Soil pore structure comprises the size and shape of soil pores and has a major impact on water retention and gas movement. The porous nature of biochar suggests that its application to soil can potentially alter soil pore structure characteristics, and the purpose of this study was to evaluate the effects of birch wood biochar (20, 40, and 100 Mg ha−1) applied to a sandy loam on soil total porosity and pore structure indices. Bulk and intact soil samples were collected for physicochemical analyses and water retention and gas diffusivity measurements between pF 1.0 and pF 3.0. Biochar application reduced bulk density and increased total porosity especially for soil with 100 Mg ha−1 biochar (16% and 14% reduction in bulk density and total porosity, respectively). Biochar application of more than 20 Mg ha−1 enhanced water retention, and the trend increased with increasing biochar application rate, where the maximum increment was 12% at 100 Mg ha−1 biochar treatment. A pore size distribution index, B, derived from water retention, indicated a wider soil pore size distribution in biochar-amended soil than in the reference soil, especially for the 100–Mg ha−1 application. At given matric potentials, biochar increased soil air-filled porosity by up to 25%. However, there was no difference in gas diffusivities between biochar-amended soil and the reference soil. At pF 3.0, the soil pore system became more tortuous after biochar application, with a trend that pore tortuosity increased with increasing biochar rate. Overall, addition of a wood-based biochar to a sandy loam soil resulted in a soil structure with broader pore size distribution and higher tortuosity of the interaggregate pore network. Similar studies with other types of biochars and soils are recommended toward better understanding of biochar effects on soil functions and services.

Assessing Soil Water Repellency of a Sandy Field with Visible near Infrared Spectroscopy

Soil water repellency (WR) is a widespread phenomenon caused by aggregated organic matter (OM) and layers of hydrophobic organic substances coating the surface of soil particles. These substances have a very low surface free energy, reducing a soils water attraction. There is focus on WR due to its effects on germination, root growth, liquid–vapour dynamics, surface erosion and leaching of chemicals through fingered flow paths. However, common techniques for measuring WR are time-consuming and expensive. Meanwhile, it is well established that visible near infrared (vis-NIR) spectroscopy is a reliable method for determining soil OM. Potentially it could therefore provide fast measurements of WR through autocorrelation with OM. The aim of this study was to test the feasibility of vis-NIR spectroscopy for estimating the WR of soils with a small gradient in soil organic carbon (SOC) and texture, and to evaluate the effect of soil pretreatment on the predictive ability of WR models. A total of 87 soil samples from an agricultural coarse sandy field in Denmark were analysed for SOC, particle size fractions, water content and WR. Soil samples were scanned with a vis-NIR sensor (350–2500 nm) after air- and oven-drying at 60°C and 105°C. WR, expressed as liquid surface tension (mN m−1), was determined using the molarity of ethanol droplet test. Partial least squares regression models of SOC, texture and water content showed no predictive ability (r2 values between 0.10 and 0.51). However, successful models (r2 = 0.85) were generated for WR. The majority of bands important in the vis-NIR region of WR models were related to different components of OM indicating that, across the investigated field, WR was related to specific hydrophobic components of soil OM rather than to the total amount of carbon. A lower prediction error of the WR model for soils dried at 105°C (1.93 mN m−1) than at 60°C (2.52 mN m−1) can be explained by a lower range of WR values for the soils dried at 105°C. Moreover, a higher temperature reduced the number of absorption bands related to OM, indicating a degradation of hydrocarbon groups and a more hydrophobic character of the soil.

Clay-to-Carbon Ratio Controls the Effect of Herbicide Application on Soil Bacterial Richness and Diversity in a Loamy Field

Soil texture and soil organic carbon (OC) influence the bacterial microenvironment and also control herbicide sorption. A field-scale exploratory study was conducted to investigate the potential interaction between soil texture parameters, herbicides, and soil bacterial richness and diversity. Glyphosate and bentazon were used to evaluate the herbicidal effect on bacterial community under different conditions created by clay and OC gradients in a loamy field. Metabarcoding by high-throughput sequencing of bacterial rDNA was used to estimate bacterial richness and diversity using OTUs, abundance-based coverage (ACE), Shannon diversity index, and phylogenetic diversity. In general, bacterial richness and diversity increased after bentazon application and decreased after glyphosate application. There was no significant effect for field locations with Dexter n (the ratio between clay and OC) values below 4.04 (the median of the values in the field study). The correlation coefficient (r) between bacterial richness and clay decreased after bentazon application, but increased after glyphosate application. Correlations between Dexter n and bacterial indices followed the same pattern, decreasing after bentazon application and increasing after glyphosate application. This indicated that the specific chemical nature of individual herbicides affected bacterial communities. This study reinforced the importance of including soil physical and chemical characteristics to explain the influence of pesticides on the variation in soil bacterial communities in agroecosystems.

Prediction of the soil water retention curve for structured soil from saturation to oven-dryness

The soil water retention curve (SWRC) is the most fundamental soil hydraulic function required for modelling soil–plant–atmospheric water flow and transport processes. The SWRC is intimately linked to the distribution of the size of pores, the composition of the solid phase and the soil specific surface area. Detailed measurement of the SWRC is impractical in many cases because of the excessively long equilibration times inherent to most standard methods, especially for fine textured soil. Consequently, it is more efficient to predict the SWRC based on easy-to-measure basic soil properties. In this research we evaluated a new two-stage approach developed recently to predict the SWRC based on measurements for disturbed repacked soil samples. Our study involved undisturbed structured soil and took into account the effects of bulk density, organic matter content and particle-size distribution. Independently measured SWRCs for 171 undisturbed soil samples with organic matter contents that ranged from 3 to 14% were used for model validation. The results indicate that consideration of the silt and organic matter fractions, in addition to the clay fraction, improved predictions for the dry-end SWRC. The dry-end results revealed that the smallest matric potential at hypothetical ‘zero-water-content’ varies between −45 000 and −125 000 m (pF 6.65–7.1) even for soils with similar clay mineralogy. The sensitivity analysis of the two-stage approach indicated that predicted SWRC results are more sensitive to bulk density than to organic matter content or soil texture. For the soils studied, the two-stage approach showed reasonable agreement with measured data, with a root mean square error of 0.04 cm3 cm−3 for the matric potential range from pF 1 to pF 6.6. Highlights Is a new approach to modelling the soil water retention (SWR) curve applicable to structured soil? The model accurately predicts the full SWR curve with an RMSE of 0.04 cm3 cm−3. Prediction accuracy of the wet part of the SWR curve was sensitive to variation in bulk density. The pF at zero water content, which affects the prediction of dry SWR, ranged from 6.65 to 7.10.

Rapid estimation of cation exchange capacity from soil water content

Summary Estimates of cation exchange capacity (CEC) for soil or earth materials are vital for several applications in agriculture and geotechnical engineering. The time-consuming and laborious nature of standard methods of CEC determination prompted the development of regression-based techniques and more sophisticated methodologies, such as artificial neural networks (ANNs), to estimate CEC from other soil properties (e.g. clay, organic matter and pH). The present study proposes regression relations for estimating CEC from soil water content at different relative humidity (RH) values that range from 10 to 90% and considering sorption hysteresis. For model development, water adsorption and desorption isotherms were measured for 203 soil samples from different parts of the world with a vapour sorption analyser within an RH range from 3 to 93%. Regression models were developed for both adsorption and desorption for nine RH values (10, 20, 30, 40, 50, 60, 70, 80 and 90%). For 35 independent soil samples, the models predicted CEC accurately (root mean squared error (RMSE): adsorption = 2.47 (0.04) cmol(+) kg−1; desorption = 2.52 (0.09) cmol(+) kg−1) with no clear effect of RH value or sorption direction on the accuracy of prediction. The new models were superior to three models from the literature based on clay, organic matter and pH; the smallest RMSE from these models was 4.13 cmol(+) kg−1 for the same 35 soil samples. Furthermore, the water sorption-based models performed better than literature models based on data mining tools (ANNs, support vector machines) and visible near infrared spectroscopy when standardized RMSE values were compared. Thus, a simple measure of soil water content at a known RH can serve as an accurate substitute for measuring soil CEC. Highlights A simple method to estimate cation exchange capacity (CEC) accurately is needed. Regression models for estimating CEC from soil water contents were developed and tested. Models predicted CEC accurately with no effect of relative humidity or sorption direction. Proposed models performed better than existing models based on the validation dataset.

Manure distribution as a predictor of N2O emissions from soil

Predicting nitrous oxide (N2O) emissions from manure-amended soil remains a challenge. One reason may be that spatial heterogeneity in distribution of manure is not accounted for in models of N2O emission, but experimental results suggest that both manure and soil properties affect the distribution of manure constituents after field application in a systematic way. Key to predicting the fate of labile carbon (C) and nitrogen (N) in manure is to acknowledge that the liquid phase, and a corresponding fraction of labile C and N, is partly absorbed by the bulk soil in response to the water potential gradient, and partly retained by particulate manure organic matter. Therefore, boundary conditions for subsequent transformations of C and N may be better described as two separate compartments. In this study, N2O emissions were determined in a 42-day experiment that included two soils (7.5% and 17% clay) adjusted to three soil water potentials (–3, –5 and –10 kPa) and amended with surface-applied pig slurry, cattle slurry, digestate or water only, in total 24 treatments. Net emissions of N2O corresponded to between 0.18% and 0.64% of manure N. Experimental results were analysed with a conceptual model of short-term N2O emissions from manure-amended soil, which estimates redistribution of manure constituents and predicts emissions from three sources, i.e. nitrification in bulk soil, and nitrification and denitrification in manure hotspots. Adopting a recent modification, oxygen availability in manure hotspots was related to relative soil gas diffusivity. Model efficiencies were 42% and 12% for the two soil types when using parameters determined by multiple regression of experimental results. With the process-based model Manure-DNDC as reference, the importance of accounting for distribution of manure water and labile C and N is discussed.

Simple predictive models for saturated hydraulic conductivity of technosands.

Abstract Accurate estimation of saturated hydraulic conductivity (Ks) of technosands (gravel-free, coarse sands with negligible organic matter content) is important for irrigation and drainage management of athletic fields and golf courses. In this study, we developed two simple models for predicting Ks of technosands based on either (i) the classic Kozeny-Carman (K-C) model modified by considering the content of finer particles (fines) less than 200 &mgr;m to estimate an immobile water fraction or (ii) the Revil-Cathles (R-C) model modified by using the characteristic particle diameter from the Rosin-Rammler particle size distribution (PSD) function. The Ks and PSD data of 14 golf course sands from literature as well as newly measured data for a size fraction of Lunar Regolith Simulant, packed at three different dry bulk densities, were used for model evaluation. The pore network tortuosity-connectivity parameter (m) obtained for pure coarse sand after fitting to measured Ks data was 1.68 for both models and in good agreement with m values obtained from recent solute and gas diffusion studies. Both the modified K-C and R-C models are easy to use and require limited parameter input, and both models gave comparable accuracy as more complex Ks models. The models are therefore recommended for preliminary assessment and design of technosand layers, for example, with regard to selecting sand PSD for optimal hydrological performance at athletic fields or golf courses.