Different Types Of Soil Research Articles

Granular Soils and Contaminant Modeling in Tailing Dams

The granular soils of tailings, encompassing clay, gravel, sand, and silt, play a pivotal role in the behavior and stability of tailings dams. Different types of granular soils significantly influence the tailings material’s strength, compressibility, and permeability. This study highlights the importance of understanding the relationship between soil types and contaminant properties when analyzing solute transport through numerical modeling. Consequently, various soil types were incorporated into the initial tailings dam model to simulate contaminant transport based on solute transport analysis. The findings underscored the essential role of granular soils in contaminant dispersion within tailings dams. Finer particles, such as clay and silt, demonstrated higher adsorption capacities, which slow contaminant movement. In contrast, coarser materials, like sand and gravel, enable faster transport, increasing the potential for rapid dispersion.

A mechanized assembly for erecting soil-cement barriers to protect agricultural lands from low-active waste during flood

The object of this study is the process of constructing a waterproof underground barrier from local soil using loess loam and medium-sized sand as an example. The values of waterproofing of soil cements on different types of soil and the norms of net labor consumption corresponding to them were obtained. The research solves the task of protecting agricultural lands in the areas of geological burials of low-level radioactive waste. Configuration of a mechanized drilling mixing assembly for installing a waterproof barrier in the field has been proposed. Waterproofness of soil cement on clay and sandy soils was determined experimentally. The corresponding norms of the net consumption of time for manufacturing the barrier in these soils have been determined. Units of the mechanized assembly are repairable, utilize widely available materials, parts, and mechanisms. As a result of studies on the labor intensity of the installation of soil cement, a net labor rate was established, which varies from 35 to 52 min/m3 depending on the type of soil. The corresponding values of waterproofness, which ranged from W6 to W14, were determined, which substantiates the possibility of effective functioning of soil-cement underground barriers. Options for the structural solution for impenetrable barriers have been offered. The values of the obtained net time rates are explained by the high degree of mechanization of the technological process and the use of local materials. A distinctive feature of the results is the emphasis on the data collection on the time consumption of machines and mechanisms, the characteristics of local soils under production conditions, and the use of local materials. The assembly implies using affordable and repairable units that can be serviced right in the field. Given this, the manufacturability of the proposed process was defined, confirmed by time-keeping studies. The realm of practical application of the reported results are sites within flat areas with sandy or loess bases. Barrier solutions are designed exclusively for geological waste storage facilities under the conditions of a high level of groundwater and the presence of a waterproof layer at the base

Numerical Modeling of Soil and Structure Behavior for Tunneling in Different Types of Soil

This note studies the correlation between surface and tunnel volume loss in various types of dry soil via finite element method. The effect of small strain stiffness, the buoyancy effect of soil, and tunnel overburden depth are considered in the 2D tunneling model. The results show that both surface volume loss ratio and settlement trough width parameter in the empirical solution can be expressed as a linear equation of tunnel volume loss ratio for 1D overburden shallow tunnels. Furthermore, the surface volume loss ratio can be presented as a non-linear polynomial equation of overburden depth and tunnel volume loss ratio in a 3D space, and this equation holds in different types of soil. The ranges of required fitting parameters and upper and lower bounding surfaces are suggested for various types of soil. Knowledge of this correlation between surface and tunnel volume loss is valuable, as it can be employed in practice for preliminary tunnel design in the absence of tunneling induced maximum ground settlement.

Agronomic potential of Hermetia illucens frass in the cultivation of ryegrass in distinct soils

Abstract Cropping systems are strongly dependent on mineral fertilisers, which are effective in achieving high crop productivities. However, these chemical inputs end up compromising soil quality in the long-term. Frass from black soldier fly (BSF) larvae is a novel organic fertiliser that is rich in organic matter and advocated as a material that can sustain crop productivity while increasing soil quality. This study aimed at evaluating distinct fertilisation regimes in the cultivation of ryegrass (Lolium multiflorum Lam. or annual ryegrass) in soils of different types (sandy, loamy and clay) and fertility levels. In a 7-month pot experiment conducted in a glass greenhouse, plants were cultivated with exclusive mineral (MT) or organic (OT) fertilisation, in addition to combinations between both (mineral and organic, MOTs) in different proportions (25:50; 50:50 and 75:25), considering a 140 kg per hectare N demand. Crop yield was favoured by the combination of organic and mineral fertilisers in all soils, which also had its fertility increased, especially regarding organic matter build-up and nutrient accumulation. In addition, the presence of frass in the sandy soil stimulated microbial activity, which was measured by the enzyme dehydrogenase. Frass derived from BSF larvae can be considered an adequate organic fertiliser in the cultivation of ryegrass in distinct soil types, when applied in partial (25% to 75%) replacement of mineral fertilisers, enabling high crop productivity and nutritional quality of the crop, while increasing soil fertility.

Application of different phosphatic fertilizers influences the different phosphorus fractions and morphophysiological traits of wheat in saline sodic soil

Nutrient constraints in salt-affected soils are one of the limiting factors for crop production. We investigated phosphorus (P) availability to wheat crop and its correlations with different fractions of P in salt-affected soils in response to various phosphatic fertilizer’s application. Three different types of soils having electrical conductivity of soil extract (ECe) < 4 dS m−1 and sodium adsorption ratio (SAR) < 13.2 (mmol L−1)1/2, ECe 8 dS m−1 SAR 20 (mmol L−1)1/2 and ECe 12 dS m−1 and SAR 30 (mmol L−1)1/2 were used for this experiment. Different P fertilizers viz. control, diammonium phosphate (DAP), single super phosphate (SSP) and nitrophos (NP) were applied on these soils. The doses of nitrogen, phosphorus and potassium were remained same for all the treatments. The P fractions, agronomic parameters and P-availability to plants were determined. Results indicated increase in shoot dry weight (61%) and photosynthetic rate (9%) in SSP treated soil at EC 8 dS m−1 and SAR 20 (mmol L)1/2. The total P (7.6%) in soil and respiration rate (1.9%) in plant was recorded maximum in DAP treated soil at EC 8 dS m−1 and SAR 20 (mmol L)1/2, and membrane stability index (44%) in plant shoot, extractable P (23%) in soil and P concentration (22%) in shoot were recorded maximum in SSP treated soil at EC 12 dS m−1 and SAR 30 (mmol L)1/2. It was concluded that SSP fertilizer perform better in salt-affected soil for growth and yield of wheat compared to other phosphatic fertilizers.

Prediction of thermal conductivity of frozen soils from basic soil properties using ensemble learning methods

Thermal conductivity is one of the important properties required for understanding the frozen soils behavior. There are several models available in the literature for the prediction of thermal conductivity of frozen soils based on the proportions of unfrozen water, ice, gas, and soil particles. In this study, two ensemble learning methods-based models; namely, the Random Forest (RF) model and the Least Squares Boosting (LSB) model, are extended to estimate the thermal conductivity of frozen soils. These models utilize basic soil properties as input parameters that include water content, dry density, temperature, and fractions of gravel, sand, silt, and clay, can be measured easily, or determined. Additionally, seven widely used thermal conductivity models, referred to as the traditional models for frozen soils, were evaluated. Both the RF and LSB models, as well as the traditional models, were assessed using data of 823 tests derived from 43 soils with different textures that were gathered from the literature. The results highlight that the traditional models have their strengths and limitations in terms of their use for different types of soils. In contrast, the proposed ensemble learning methods-based models provide higher prediction accuracy compared to the traditional models and can be applied to all soil types and temperature ranges. Furthermore, estimation from the ensemble learning methods-based models can be used to provide probability of multi-dimensional analysis of frozen soils.

Derivation of site-specific soil-water characteristic curve (SWCC) from extremely sparse experimental data by hierarchical Bayesian method with consideration of geotechnical sites similarity

Soil-water characteristic curves (SWCCs) play a crucial role in understanding soil behavior related to water movement and soil moisture effects, rendering them an essential tool in engineering geology and geotechnical engineering applications. Traditionally, SWCCs are determined through labor-intensive laboratory experiments involving varying levels of suction, a process that can take several months. Moreover, obtaining a high-quality SWCC from numerous measurements becomes particularly challenging when immediate site-specific data are required for design and analysis. This paper introduces a hierarchical Bayesian method for deriving site-specific SWCCs by integrating extremely sparse data (e.g., one or two measurements) for the site of interest with existing data from sites with similar geological and sedimentary characteristics. The SWCC parameters are estimated using a Bayesian framework and Markov chain Monte Carlo simulations. This approach not only enables the derivation of accurate SWCCs but also helps quantify the associated uncertainties. The effectiveness of the proposed method is demonstrated using both numerical and real-world data from different types of loess and unsaturated soils in the unsaturated soil database (UNSODA). The results show that site-specific SWCCs of unsaturated soils can be accurately estimated from sparse measurements by incorporating information from similar sites. This work offers an efficient and reasonably accurate approach for deriving SWCCs of unsaturated soils for geotechnical applications, especially when the number of site-specific SWCC measurement is extremely sparse and limited.

Exploring the sorption/desorption of nitenpyram in loess soils: implications for neonicotinoid fate and ecological risk assessment.

Neonicotinoids are widely used insecticides that accumulate in various environmental matrixes and potentially harm non-target organisms. However, the mechanism of sorption/desorption of neonicotinoids in different loess soils remains poorly understood. Therefore, this study investigated the sorption/desorption of nitenpyram (NIT), a commonly used neonicotinoid, in three different types of loess soils and examined factors influencing the adsorption process using batch experiments. The findings revealed that NIT reached adsorption equilibrium in 4h in all three loess soil samples. The R2 value (> 0.898) obtained from fitting the sorption/desorption kinetics indicated a good match with the pseudo-second-order model, suggesting the involvement of multiple mechanisms, including chemisorption. The linear and Freundlich models also adequately described the sorption of NIT in loess soils. Additionally, a clear hysteresis phenomenon was observed. The adsorption capacity of NIT is significantly related to the adsorption temperature, solution pH and ionic strength. Upon increasing the initial concentration, the equilibrium adsorption capacity of NIT for gray-cinnamon soil, sierozem, and cultivated loessial soil increased from 3.56, 2.51, and 2.64mg/kg to 8.49, 3.92, and 5.22mg/kg, respectively. FTIR spectral analysis revealed that the adsorption of NIT in loess soil was primarily governed by mixed mechanism. This study elucidates the behavior and fate of NIT in soil-water systems in the Northwest, while also establishing a foundation for assessing its ecological risks. The findings have significant practical implications for the future development of environmental management and pollution control strategies.

Fabrication of carboxymethyl tamarind kernel gum-based hydrogel and its applicability in different types of soils for agronomy

An avant-garde agricultural hydrogel - Carboxymethyl tamarind kernel gum-poly sodium acrylate-polyacrylamide hydrogel was designed by free-radical polymerization of biopolymer: carboxy-methyl tamarind kernel gum and monomers: sodium acrylate, acrylamide, using N,N′ methylene bisacrylamide as crosslinker and potassium persulphate as initiator, to explore its application as a soil conditioner. It was characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, and thermogravimetric techniques. Swelling was investigated at different pH and in saline solutions. The fabricated hydrogel absorbed 189 ml/g of distilled water. Minimal 0.1 % hydrogel-amended different soils unveiled an upswing in maximum water holding capacity: Sandy soil (43%), Clay soil (31 %), Silty soil (29 %) & Loamy soil (9 %).; decrease in porosity: Sandy (29 %) > Loamy (15.2 %) > Silty (6 %) > Clay (5.9 %), increase in available water content: Clay soil (17.52 %), Silty (13.45 %), Loamy soil (9.416 %), Sandy soil (10.375 %); increase in bulk density: Clay (1.7 %), Silty (5.3 %), Loamy (10 %) and Sandy (13%) as compared to control sample. These sequels were corroborated by water retention capacity in chickpea plants. The designed hydrogel, as a soil conditioner, was commendable in all types of soils but is worth applying in sandy and loamy soils. This hydrogel richly assists as a soil conditioner and boosts plant performance in a green eco-friendly way.

Micronutrient and heavy metal bioaccumulation in Bermuda grass (Cynodon dactylon L. Pers) grown in calcareous soil using stabilized and dried sewage sludge

This study examines the micronutrients and heavy metal bioaccumulation in Bermuda grass (Cynodon dactylon L. Pers), grown in two different types of calcareous soil (CS) with the application of stabilized and dried sewage sludge (SS). At the end of the growth period, the Fe, Zn, Mn and Cu (micronutrients) concentrations in the substrate have increased. Furthermore, it was determined that the total Fe, Zn, Mn and Cu concentrations were higher in CS1 compared to CS2. For the heavy metals the concentrations of Ni and Cr have increased, and the concentration of total Cd has slightly but significantly decreased. The total Pb concentration was below the detection limit (DL for Pb &lt;0.03 mg kg-1). It was determined that the total Ni, Cr and Cd concentrations were higher in CS1 than in CS2. In the aerial biomass of the Bermuda grass, the Fe and Zn concentrations have increased with increasing SS applications, whereas Mn concentrations have decreased. Ni, Cr, Cd and Pb concentrations were unaffected by SS applications for both types of CS. The bioconcentration factor (BCF) values for the shoot of the plant (BCFFe, BCFZn, BCFMn, BCFCu, BCFNi, BCFCr, BCFCd) were determined to be below the critical limit of 1. The application of sewage sludge has not resulted in bioaccumulation above critical limits in the shoot of the plant. However, considering Bermuda grass substrate, it can be suggested to add sewage sludge to the calcareous soil in amounts between 20–40 t ha-1, considering its long-term remanence.

Interaction of Te(IV) and Te(VI) with the soil matrix – Sorption and fractionation as a function of soil composition

Tellurium is a technology-critical element (TCE), with relatively limited data on its behavior in the environment, especially the pedosphere. As with other TCEs, its more widespread use, especially in new energy sources, might lead to Te spillage during production or in the eventual waste. Investigation of tellurium's interaction with soil is a necessary step in the research into the physiochemical transformation and determining the mobility of different tellurium species. To broaden the hitherto scarce knowledge of tellurium behavior in the soil environment, selected soluble tellurium compounds were introduced into different types of well-characterized soil (content of fertilizers, organic matrix, clay minerals, Mn, Fe, pH). The study of Te(IV) and Te(VI) sorption indicated that after 7 days the sorption is quantitative and close to 100%. Addition of Fe2O3 to a soil deficient in Mn and Fe increases its sorption potential by about 10 percentage points. Based on fractionation study (0.11 mol L−1 CH3COOH, 0.1 mol L−1 ascorbic acid in oxalate buffer (pH 3), 30% H2O2 at 85 °C followed by 0.5 mol L−1 CH3COONH4), it was shown that the presence of Mn/Fe (oxyhydr)oxides plays an essential role in the mobility of Te, especially Te(VI), regardless of the soil type. In the soil poor in reducible fraction and rich in organic matrix (peat), the organic fraction was responsible for the immobilization of Te, especially Te(IV). Extraction of the mobile fraction after incubation in the presence of DI water (Te extraction: 7–8%), oxalic acid (5–7%) or citric acid (6%) (mimicking rhizosphere activity) indicated that these did not play a significant role in Te retention. Nevertheless, soil modification with biocarbon limited the effect of citrates on Te mobilization. This knowledge is fundamental, i.e. in the context of soil remediation processes and counteracting the migration of Te in the environment from anthropogenic sources (e.g. solar farms).

Divergent responses of aggregate breakdown by slaking to nitrogen forms in solution for contrasting soil types

Aggregate stability strongly affects many soil processes and is critical to maintain sustainable agriculture. Aggregate breakdown is controlled by the interaction between soil intrinsic properties and solution characteristics. Nitrogen fertilization including different forms is well known to influence aggregate stability; however, relative to their long-term effects, there is little recognition on the rapid response of aggregate breakdown to nitrogen solutions. This study aimed to examine the effects of nitrogen form and concentration on aggregate stability for different types of soils. Aggregate breakdown against slaking of three soil types (Phaeozem, Luvisol, and Acrisol) and three horizons (organo-mineral (A), illuvium (B), and parent material horizons (C)) was determined subjected to nitrogen solutions of three forms (CO(NH2)2, NH4+, NO3–) and five concentrations (0.05 ∼ 1.0 mol/L). Among nitrogen forms, urea solution almost had non-significant effect irrespective of soil type and horizon (p > 0.05); for NH4+ and NO3– solutions, aggregate stability showed little variations (MWD of 0.19 ∼ 0.26 mm) with electrolyte concentration for Phaeozem in B and C horizons, overall increased for Luvisol and Phaeozem in A horizon, and decreased first and then reached a steady state for Acrisol. The effects of nitrogen forms on aggregate breakdown were dependent on soil aggregation status or cementing agents (mainly organic matter, clay mineralogy). Electrolyte nitrogen solutions (NH4+ and NO3–) inhibited aggregate breakdown mainly through reducing electrostatic repulsive forces for moderately developed soils rich in swelling clays, and promoted aggregate breakdown by both weakening particle cohesion and enhancing compression pressure of entrapped air for highly developed soils rich in non-swelling clays and Fe/Al oxides. These results facilitate an improvement of fertilizer management and irrigation to improve soil quality on different soil types.

Mathematical Modeling for Predicting Growth and Yield of Halophyte Hedysarum scoparium in Arid Regions under Variable Irrigation and Soil Amendment Conditions

Growing degree days (GDDs) and leaf area index (LAI) greatly influence the growth and yield of many crops grown in arid regions. Therefore, variation in LAI due to GDD can provide a theoretical basis for predicting crop growth, water consumption, plant development, and yield in arid agriculture via the development of mathematical growth models. This study described the relationship between plant biomass production and variation in LAI due to GDD in arid regions under different types of irrigation (fresh water and saline water) and soils amended with different substances (manure+sandy soil, compost+sandy soil, clay+sandy soil, and sandy soil). Mathematical models for LAI were established for GDDs. In addition, different water quality irrigation techniques were used as independent variables to calculate the LAI of halophytic plants (Hedysarum scoparium) in arid regions under different soil amendment treatments. Furthermore, mathematical models for plant biomass production were developed by using the LAI and GDDs. For this purpose, Logistic, Gaussian, modified Gaussian, and Cubic polynomial models were used. Modified Gaussian and Cubic polynomial models are the best among all developed models, but Cubic polynomial models are more suitable among all developed models because of their simple quadratic equations that can be solved by using the first derivative. It was observed that with increased salt concentration in the irrigation water, the growth of per plant production decreased. However, soil amendments like manure and compost enhance salt tolerance against salt stress and enable plants to sustain their growth. Furthermore, Hedysarum scoparium attains maximum LAI when its GDD is about 1117.5 °C under both irrigation regimes and in all soil amendment treatments. It was concluded that these predicted mathematical models can provide crucial insights for enhancing production in arid regions by using eco-friendly soil amendments to improve water use efficiency across diverse types of water irrigation.

Simultaneous determination of sixteen phthalic acid esters (PAEs) in soil and evaluation of matrix effect using a QuEChERS/GC/MS-internal standard method.

Phthalic acid esters (PAEs) are emerging pollutants that need to be analyzed precisely. Chromatography-based determination of PAE content in soils are frequently affected by matrix effect, which may limit the quantification of different kinds of PAEs from different types of soil. Here we optimized a QuEChERS protocol combined with gas chromatography-mass spectrometry (GC-MS) for simultaneous determination of 16 PAEs in different soils. PAEs in different type of soils (fluvo-aquic soil, red soil, and black soil) were extracted with acetonitrile followed by GC-MS detection based on quantitative ion internal standard method. All 16 PAEs showed excellent linear relationships with mass peak areas (R2 > 0.99). The limits of detection (LOD) and limits of quantitation (LOQ) of all the samples were in the range of 0.91-66.97µg/kg and 2.7-200.9µg/kg, respectively. The accurate test at 0.5, 0.1, and 1.0mg/kg spiking level recorded recovery rate between 80.11% and 100.99% with relative standard deviations (RSDs) ranging from 0.37 to 8.50% in tested matrices. No significant matrix effect was observed for most tested PAEs. This is a simple method with high sensitivity and strong stability, which is suitable and reproducible for quantifying large number of PAEs in different types of soil.

Ratio of physical model parameters can retrieve aggregate size from different types of soil in cultivated regions

Soil aggregate size, which is a proxy used to guide agricultural decisions and tillage management, can be estimated using optical remote sensing techniques. However, limited investigation has been conducted into the potential of using a physical model to retrieve soil aggregate size (< 2 mm) from different types of soil. This study is based on the multi-angular spectral measurements of seven soil samples from five soil types with 14 aggregate size fractions collected in Northeast China, three versions of the Hapke model were inverted using the Bayesian method. The findings confirmed that all three versions of the Hapke model can well characterize the angular reflection characteristics of all soil samples with different aggregate sizes. The inverted photometric parameters such as single scattering albedo ω, shape parameter b, and asymmetry parameter c were found to be sensitive to soil aggregate size, but the relationships rely on soil types because of the dependence of parameters related to soil composition. In order to obtain a general model that can be applied to different types of soil, the ratio of parameters (RoP) = (b + c)/ω, which is controlled by the external structure of soil aggregates, was proposed to retrieve the aggregate size from different soil types. Results show that the RoP can robustly capture the aggregate size of the soil with high accuracy and is insensitive to soil types. The combination of photometric parameters related to soil aggregate size provides a new method for retrieving the structural properties of the soil by eliminating interfering factors.

Numerical Simulation Study of Cavity Formation in Soil under Blast Load

The main applications of civil explosives in soils are soil compaction, mass excavation, and in situ pile creation. The suitability of explosives for each of these applications strongly depends upon the explosive properties and the soil properties. For those reasons, a reliable estimation or process simulation regarding cost efficiency and explosive work ability in the soil with known soil parameters is relevant. This paper presents a numerical simulation study of different types of soil (different amounts of gravel, sand, silt, and clay) under a blast load modeled using Ansys 2020 R1 Autodyn 2D hydrocode, with different types of explosives. The calculated results from the Ansys 2020 R1 Autodyn 2D and the experimental results obtained from the in situ cavity formation caused by blasting are presented. The Jones–Wilkins–Lee (JWL) equation of state parameters was calculated using EXPLO5 V7.01.01 supported by experimental data, while the soil and explosive properties were measured in laboratory and in situ.

Effect of Infilled Frames on Reduction Factor (R) for RC Irregular Structure

Investigating the modification factors as a critical seismic design tool, delineating the anticipated level of inelastic behavior within structural systems during seismic events. Both damping and ductility are included in this factor, particularly at movement nearing maximum capacity. Moreover, it offers valuable insights into buildings' response during earthquakes and the anticipated behavior of structures compliant with building codes during design earthquakes. Essentially, it mirrors the structure's capacity to dissipate energy via an inelastic mechanism. In this research, the infill (RC) structures with various structural irregularities were focused. The selected irregularities included dimension, elevation, and mass. Infill location, number of bays, and seismic zone were the expected R factors for RC frames. Non-linear static pushover analysis was adopted in numerical simulation. The available data gathered from the literature was used to validate the outcomes of the developed models. Additionally, the effects of different types of soil were taken into consideration, and the research results demonstrated that the value of the modification factor (R) for change in stiffness and mass of high-rise buildings for bare and infill (RC) structures is less compared to irregular (RC) structures. It was concluded that the same structure with different types of soil and different parameters has a great effect on the value of R for bare and infill regular and irregular (RC) structures. Furthermore, recommendations for accurate R estimation for RC structures were discussed. Doi: 10.28991/CEJ-2024-010-08-09 Full Text: PDF

Mercury Adsorption Test on Several Large Groups of Soils in West Sumbawa Regency, Indonesia

Mercury is one of the heavy metals that has the highest toxicity in the global environment. Mercury can cause environmental damage and if it enters the food chain it can have negative impacts on human health. In overcoming the problem of mercury entering the food chain, it is very important to study the mobility and distribution of mercury in the soil. The presence of mercury (Hg2+) in soil is largely controlled by adsorption reactions with certain specific adsorption patterns. Therefore, it is very important to study mercury adsorption on several different types of soil in order to get an idea of ​​how adsorption occurs in West Sumbawa Regency. The aim of this research is to determine the pattern and capacity of mercury adsorption on various large groups of soil in West Sumbawa Regency and the relationship between soil properties and mercury adsorption. The results of the research show that the adsorption isotherm pattern in the great soil groups Endoaquepts, Ustipsamments, and Udorthents more closely follows the Langmuir adsorption model, while the great soil groups Haplustepts, Hapludolls, Eutrudepts and Ustifluvents follow the Freundlich adsorption model. The major soil group that has the highest maximum mercury adsorption capacity in West Sumbawa Regency is Endoaquepts at 4,604 mg/g.

Exploring the sorption and degradation dynamics of validamycin-A in agricultural soils for environmental management.

Validamycin A (VA) is one of the antibiotics that have been utilized in agriculture in Asia; nevertheless, there haven't been many investigations on what happens to VA in soil. The rate at which pesticides are adsorbed into the soil must be determined, since their usage in agriculture is growing. In order to accomplish this, the current study investigated the sorption and degradation of VA in ten distinct soil samples via batch equilibrium studies while maintaining strict laboratory controls. In thermodynamic analysis with a C-type curve, the negative values of Gibbs free energy (ΔG) are thoroughly evaluated using both linear and Freundlich models. These values vary from - 16.8 to - 22.2kJ/mol. Impact of temperature (18, 23, and 30°C) and pH (5, 7, and 9) on the degradation of this antibiotic in soil was also scrutinized. Our findings demonstrated that, as a result of enhanced microbial activity at higher temperatures, VA deteriorated more quickly at 23°C and 30°C than at 18°C. In comparison to lower pH values, the VA removal efficiencies with sample-4 was significantly greater at pH 7.4 (92.9%) and pH 9 (97.4%). Moreover, first order reaction kinetics were followed in the degradation of VA. The results demonstrated that VA bound to the selected soils, resulting in medium to low persistence as demonstrated by degradation values. In summary, this study provides important information regarding the behavior and fate of VA in different types of soil, information that might be useful in developing workable management strategies and environmental risk assessments.

Artificial Neural Network-aided Mathematical Model for Predicting Soil Stress-strain Hysteresis Loop Evolution

This study presents a novel approach to forecasting the evolution of hysteresis stress-strain response of different types of soils under repeated loading-unloading cycles. The forecasting is made solely from the knowledge of soil properties and loading parameters. Our approach combines mathematical modeling, regression analysis, and Deep Neural Networks (DNNs) to overcome the limitations of traditional DNN training. As a novelty, we propose a hysteresis loop evolution equation and design a family of DNNs to determine the parameters of this equation. Knowing the nature of the phenomenon, we can impose certain solution types and narrow the range of values, enabling the use of a very simple and efficient DNN model. The experimental data used to develop and test the model was obtained through Torsional Shear (TS) tests on soil samples. The model demonstrated high accuracy, with an average R² value of 0.9788 for testing and 0.9944 for training.