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Quantitative analysis of the interactions between nanomaterials and environmental contamINANts, such as pesticides, in natural water systems and food residuals is crucial for the application of nanomaterials-based tools for the detection of the presence of toxic substances, monitoring pollution levels and environmental remediation. Previously, the Biological Surface Adsorption Index (BSAI) has demonstrated promising capabilities of interaction characterization and prediction based on experimental data from small organic molecules. In this article, the first attempt of the application of such quantitative measures toward environmental endpoints by analyzing the interactions of a selected group of nanomaterials with a variety of pesticides was made. Statistical modeling was conducted on the experimental obtained adsorption data based on polynomial BSAI models, as well as models with the incorporation of artificial neural network methodologies. Finally, clustering analyzes were performed for the categorization of nanomaterials based on surface physicochemical properties using both polynomial indices and physical adsorption modeling parameters. These quantitative computational approaches support the application of BSAI modeling in the area of environmental contamINANt detection and remediation. [ABSTRACT FROM PUBLISHER]

An integrated system based on a heterogeneous catalytic wet hydrogen peroxide oxidation (CWHPO) and subsequent rotating biological contactors (RBCs) has been modeled for the treatment of agrochemical wastewater. One dimensional pseudo-homogeneous model was proposed for the CWHPO step. The reaction rate for TOC removal (k 1 ) was 0.087 1/min. In the case of the RBCs, two different approaches were considered: the pseudo-homogeneous model was based on Kornegy and Clark equations and it is restricted to only one substrate limitation, TOC, for the microbial growth. The microbial growth was modeled by a Monod type equation. The uptake rate and saturation coefficient values were P = 0.94 g/dm 2 d and Ks = 0.53 g/dm 3 . The integrated non-pseudo-homogeneous model considers a two-phase bioreactor in which all the biochemical processes occur in the solid biofilm phase. In this model, processes such as biofilm growth and diffusion of nutrients into biofilm were taken into account. The microbial growth was modeled using a double Monod equation with substrate limitation by TOC and total nitrogen (TN). Both approaches were able to describe the CWHPO-RBCs performance at different operating conditions with an estimated growth rate (μ MAX ) of 3.62 1/d. The calculated TOC removal was in good agreement with the experimental results. The two-phase model was also able to predict the TN removal of the system. The modeling of the coupling CWHPO/RBCs process could be a useful guide in order to achieve a cost-effective process leading to optimum C/N composition of the treated effluent and resulting in better overall removal efficiency. [ABSTRACT FROM AUTHOR]

Enormous amounts of pesticides are manufactured and used worldwide, some of which reach soils and aquatic systems. Glyphosate is a non-selective herbicide that is effective against all types of weeds and has been used for many years. It can therefore be found as a contaminant in water, and procedures are required for its removal. This work investigates the use of biopolymeric membranes prepared with chitosan (CS), alginate (AG), and a chitosan/alginate combination (CS/AG) for the adsorption of glyphosate present in water samples. The adsorption of glyphosate by the different membranes was investigated using the pseudo-first order and pseudo-second order kinetic models, as well as the Langmuir and Freundlich isotherm models. The membranes were characterized regarding membrane solubility, swelling, mechanical, chemical and morphological properties. The results of kinetics experiments showed that adsorption equilibrium was reached within 4 h and that the CS membrane presented the best adsorption (10.88 mg of glyphosate/g of membrane), followed by the CS/AG bilayer (8.70 mg of glyphosate/g of membrane). The AG membrane did not show any adsorption capacity for this herbicide. The pseudo-second order model provided good fits to the glyphosate adsorption data on CS and CS/AG membranes, with high correlation coefficient values. Glyphosate adsorption by the membranes could be fitted by the Freundlich isotherm model. There was a high affinity between glyphosate and the CS membrane and moderate affinity in the case of the CS/AG membrane. Physico-chemical characterization of the membranes showed low values of solubility in water, indicating that the membranes are stable and not soluble in water. The SEM and AFM analysis showed evidence of the presence of glyphosate on CS membranes and on chitosan face on CS/AG membranes. The results showed that the glyphosate herbicide can be adsorbed by chitosan membranes and the proposed membrane-based methodology was successfully used to treat a water sample contaminated with glyphosate. Biopolymer membranes therefore potentially offer a versatile method to eliminate agricultural chemicals from water supplies. [ABSTRACT FROM AUTHOR]

The molecular imprinting technique is a highly predeterminative recognition technology. Molecularly imprinted polymers (MIPs) can be applied to the cleanup and preconcentration of analytes as the selective adsorbent of solid-phase extraction (SPE). In recent years, a new type of SPE has formed, molecularly imprinted polymer solid-phase extraction (MISPE), and has been widely applied to the extraction of agrochemicals. In this review, the mechanism of the molecular imprinting technique and the methodology of MIP preparations are explained. The extraction modes of MISPE, including offline and online, are discussed, and the applications of MISPE in the analysis of agrochemicals such as herbicides, fungicides and insecticides are summarized. It is concluded that MISPE is a powerful tool to selectively isolate agrochemicals from real samples with higher extraction and cleanup efficiency than commercial SPE and that it has great potential for broad applications. [ABSTRACT FROM AUTHOR]

The pH dependency of soluble phosphate in soil was measured for six agricultural soils over a pH range of 3-10. A mechanistic model, the LCD (ligand charge distribution) model, was used to simulate this change, which considers phosphate adsorption to metal (hydr)oxides in soils under the influence of natural organic matter (NOM) and polyvalent cations (Ca2+, Al3+, and Fe3+). For all soils except one, the description in the normal pH range 5-8 is good. For some soils at more extreme pH values (for low P-loading soils at low pH and for high P-loading soils at high pH), the model over predicts soluble P. The calculation shows that adsorption is the major mechanism controlling phosphate solubility in soils, except at high pH in high P-loading soils where precipitation of calcium phosphate may take place. NOM and polyvalent cations have a very strong effect on the concentration level of P. The pattern of pH dependency of soluble P in soils differs greatly from the pH effects on phosphate adsorption to synthetic metal (hydr)oxides in a monocomponent system. According to the LCD model, the pH dependency in soil is mainly caused by the synergistic effects of Ca2+ adsorption to oxides. Adsorption of Al3+ to NOM adsorbed plays an important role only at a pH < 4.5. Presence of NOM coating strongly competes with phosphate for the adsorption and is an important factor to consider in modeling phosphate adsorption in natural samples. [ABSTRACT FROM AUTHOR]

This paper analyses flow and transport of pesticides from the unsaturated zone to groundwater so as to predict concentration of those contaminants in the Fucino Plain’s groundwater, by site investigations and numerical simulations. Pesticides were detected in surface water (peaks of 13 μg L−1) and groundwater (peaks of 0.37 μg L−1). Modelling tools made it possible to identify that pattern of precipitation, organic matter content, and root thickness are the key factors involved in vertical seepage of pesticides. Numerical simulations indicated that a significant fraction of contaminants is leached from the most surficial soil layers through runoff, while only a secondary fraction is mobilised towards groundwater. Likelihood of contaminating deep groundwater is fairly low, whereas surface waters show higher susceptibility. Results of the proposed conceptual hydrogeological model show that pesticides are more likely to be entrained by mixing of stream water with shallow groundwater in periods of high water exploitation from shallow wells. [ABSTRACT FROM AUTHOR]

Simazine is a s-triazine herbicide that has been applied worldwide for agriculture. This herbicide is the second most commonly detected pesticide in surface and groundwater in the United States, Europe and Australia. In this study, simazine adsorption behaviour was studied in two agricultural soils of the Aconcagua valley, central Chile. The two studied soils were soil A (loam, 8.5% organic matter content) and soil B (clay-loam, 3.5% organic matter content). Three times higher simazine adsorption capacity was observed in soil A (68.03mgkg−1) compared to soil B (22.03mgkg−1). The simazine adsorption distribution coefficients (K d) were 9.32Lkg−1 for soil A and 7.74Lkg−1 for soil B. The simazine adsorption enthalpy in soil A was −21.0kJmol−1 while in soil B the adsorption enthalpy value was −11.5kJmol−1. These results indicate that simazine adsorption process in these soils is exothermic, governing H bonds the adsorption process of simazine in both the loam and clay-loam soils. These results and the potentiometric profiles of both soils, suggest that simazine adsorption in soil A is mainly governed by simazine–organic matter interactions and in soil B by simazine–clay interactions. The understanding of simazine sorption–desorption processes is essential to determine the pesticide fate and availability in soil for pest control, biodegradation, runoff and leaching. [Copyright &y& Elsevier]

This study was conducted to examine adsorption of pesticides bifenthrin, carbosulfan, λ-cyhalothrin, cypermethrin, endosulfan, parathion methyl, monocrotophos and 4-nitrophenol by sandy clay loam (S.C.L) and sandy loam (S.L) soils (with varying organic content). There was no significant difference between the observed soil water partitioning coefficient values (Kd) derived from linear and nonlinear Freundlich isotherms. Adsorption of pesticides on S.C.L soils was higher than those on S.L soils. Kd values showed significant correlations (r2 = 0.8 - 0.99 and 0.65 - 0.97) with soil organic carbon content (OC) and weak correlations (r2 = 0.2 - 0.29 and 0.1 - 0.18) with clay contents of S.C.L and S.L soil at p ≤ 0.05, respectively for all pesticides (except monocrotophos). Observed Koc values (soil-water partitioning constants based on the organic C fraction of the soil) were in accordance with the literature values of Wauchope and Tomlin with a maximum deviation of less than 0.5 log units. Ten Quantitative Property-Property Relationships (QPPR) among water solubility, n-octanol water coefficient (Kow) and Koc were proposed for studied pesticides except monocrotophos. The models were considered acceptable when predicted-observed difference for log Kow and log Koc were ≤ 0.3 and ≤ 0.5 log units, respectively, during the validation procedure. This work indicates that the log Koc derived from the log Kow, from some of existing relationships, may be a fair predictor where observed values (i.e., Kd and Koc) are not available. Furthermore, predicted leaching potential by groundwater ubiquity scores (GUS) equation was solved by using observed Koc values and literature reported half lives of pesticides. GUS ranked the mobility of nonvolatile compounds i.e., bifenthrin, λ-cyhalothrin, cypermethrin and endosulfan extremely low; methyl parathion very low; 4-nitrophenol low; carbofuran and monocrotophos very high in S.C.L and S.L soils, respectively. Results discussed in this paper provide background to prioritize pesticides or chemical groups that should be evaluated under field conditions with regard to their leaching potential to groundwater in arid climates. [ABSTRACT FROM AUTHOR]

Se presenta un estudio de un mecanismo de solubilización de iones metálicos en plantas tratadas con metales pesados. Se utiliza una mezcla de oligogalacturónidos (Pectimorf) y semillas de tomate de la variedad Amalia. Las semillas recibieron diversos tratamientos con Pectimorf y luego fueron tratadas con una solución nutritiva con exceso de iones Cu2+. Los resultados indican el efecto en la longitud de las raices de las plantas.