Soil Sorption Coefficients Research Articles

Leaching of picloram, atrazine and simazine through two New Zealand soils

Picloram, atrazine, simazine, and bromide were applied to two sites, a Te Awa silt loam and a Twyford fine sandy loam, located in Hawkes Bay, New Zealand, in November 1993. Soil water concentrations were monitored at approximately monthly intervals using suction cup lysimeters over the following 640 days. Leaching of all chemicals below 1.1 m was observed at the Te Awa site but only bromide and picloram had reached 1.3 m depth at the Twyford site after 400 and 600 days, respectively. Atrazine and simazine were observed at 0.4 m depth but not at 0.8 or 1.3 m depth at the Twyford site. Soil half lives and soil sorption coefficients ( K oc) for each pesticide were estimated by comparing the observed results with simulations using the GLEAMS model. Picloram was less mobile but more persistent than available values quoted by Wauchope et al. [Wauchope, R.D., Buttler, T.M., Hornsby, A.G., Augustijn-Beckers, P.W.M., Burt, J.P., 1992. The SCS/ARS/CES Pesticide Database for Environmental Decision Making. Reviews of Environmental Contamination and Toxicology, Vol. 123, Springer-Verlag, 164 pp.] while atrazine and simazine were more mobile and had about the same persistence as these values. The pesticides were more mobile (smaller K oc) at the Te Awa site than at the Twyford site, possibly because of preferential flow at the Te Awa (silt loam) site.

Comparison of analytical procedures for determination of soil sorption coefficients of some triazine herbicides

The sorption behavior of three triazine herbicides: atrazine, metribuzin, and terbutryn was studied in two different soils. Three experimental procedures to determine the Kf values were assayed: the conventional batch equilibration method in which the sorbed concentration is calculated by difference from the change in solution concentration; an alternative mass balance equilibrium batch technique in which the solution and the sorbed phase concentration are measured directly; and the flow equilibration method in which a solution of known concentration was passed through a column of soil until the effluent reached the same concentration as the input solution. Four concentrations of each herbicide were selected and results were fitted to the linearized form of the Freundlich isotherm. Recovery of the herbicides was studied in soil and water samples using the same four concentrations employed in the sorption assays. Average recoveries ranged from 86 to 104% with standard deviations lower than 10%. The Koc (mg1–1/n kg‐1 Ll/n) values obtained ranged from 43 to 87 for atrazine, 27 to 114 for metribuzin, and 355 to 505 for terbutryn. The exponents 1/n of the Freundlich adsorption isotherms were lower than unity, with only one exception, and varied from 0.72 to 0.86 for atrazine, 0.73 to 1.12 for metribuzin, and 0.76 to 0.99 for terbutryn. The solution method gave values of Koc that were 1.25, 1.55, and 2.65 (average of both soils) times those of the mass balance method for terbutryn, atrazine and metribuzin, respectively. When adsorption was low, the mass balance calculation method is recommended if the batch equilibration method is used, since the solution method can produce a considerable overestimation of adsorption. The flow equilibration method produced similar values of adsorption than the mass balance batch equilibration method and it made the experimental procedure easier since pesticide solution concentration need not to be measured once the equilibration time has been determined to ensure that the equilibrium was reached.

Quantum chemical modelling of soil sorption coefficients: Multiple linear regression models

Soil sorption coefficients for nonpolar compounds easily can be modelled with log P OW or with connectivity indices. This is not the case for polar compounds: for polar substances either compound class dependent models or models using correction factors based on substructures are described in the literature. In the present study a systematic search on multiple linear regression models using log P OW and several quantum chemical descriptors was performed to model the log K OC for a set of 66 substances from different compound classes (pesticides and other nonpolar and polar chemicals. It is shown that the soil sorption coefficient K OC can be modelled with one equation for the whole data set.

Cluster‐based Design in Environmental QSAR

AbstractIn QSAR analysis in environmental sciences adverse effects of chemicals released to the environment are modelled and predicted as a function of the chemical properties of the pollutants. Usually, the set of compounds under study contains several classes of substances, i.e., a more or less strongly clustered set. It is then needed to ensure that the selected training set comprises compounds representing all those chemical classes. Multivariate design in the principal properties of the compound classes is usually appropriate for selecting a meaningful training set. However, with clustered data, often seen in environmental chemistry and toxicology, a single multivariate design may be suboptimal. This because of the risk of ignoring small classes with few members and only selecting training set compounds from the largest classes. In this paper, a procedure for training set selection recognizing clustering is proposed. Here, when non‐selective biological or environmental responses are modelled, local multivariate designs are constructed within each cluster (class). The chosen compounds arising from the local designs are finally united in the overall training set, which thus will contain members from all clusters. Our illustration deals with a set of 66 compounds, categorized into five classes, for which the soil sorption coefficient is available. The training set selection is discussed, followed by multivariate QSAR modelling, model validation and interpretation, and predictions for the test set.

Predicting soil sorption coefficients of organic chemicals using a neural network model

AbstractThe soil/sediment adsorption partition coefficient normalized to organic carbon (Koc) is extensively used to assess the fate of organic chemicals in hazardous waste sites. Several attempts have been made to estimate the value of Koc from chemical structure or its parameters. The primary purpose of this study was to develop a nonlinear model for estimating Koc applicable to polar and nonpolar organics based on artificial neural networks using the octanol/water partition coefficient (Kow) and water solubility (S). An analytic equation was obtained by starting with a neural network, converging the bias and weight values using the available data on water solubility, octanol/water partition coefficient, and the normalized soil/sediment adsorption partition coefficient, and then combining the equations for each node in the final neural network. For the 119 chemicals in the training set, estimates using the neural network equation lie outside the 2σ region (the standard deviation for the training set, σ = 0.52) for only five chemicals, while all the chemicals in the test set lie within the 2σ region. It was concluded that the neural network equation outperforms the linear models in fitting the Koc values for the training set and predicting them for the test set.

Comparison of screening methods for the estimation of adsorption coefficients on soil

The HPLC screening method for estimating soil sorption coefficients was compared to other QSAR approaches based on log P ow, connectivity indices, molar refraction and molecular fragment approaches. For the data set under consideration (66 compounds from different chemical classes) only the HPLC screening method and, to a lesser extend, the log P ow method proved to be suitable for predicting soil sorption coefficients with acceptable accuracy. The HPLC method and the regression with log P ow were then cross-validated.

Prediction of the soil sorption coefficient of organic pollutants by the characteristic root index model

Quantitative Structure-Property Relationship (QSPR) technique was used to develop a simple predictive model for the soil sorption coefficient (K oc) of Polychlorinated Biphenyls (PCBs), chlorinated phenols (CPs) and chlorinated benzenes (CBs). Tests performed on 36 such compounds clearly demonstrate that this simple model accurately predicts the soil sorption coefficients of these chemicals. The correlation equation was then used to predict the unknown soil sorption data of chlorinated biphenyls, phenols and benzenes. The result of these tests also demonstrates that the CRI can be an alternative and a very accurate predictive tool for the soil sorption coefficients of structurally similar compounds.

The Prediction of Soil Sorption Coefficients of Heterocyclic Nitrogen Compounds by Octanol/Water Partition Coefficient, Water Solubility, and by Molecular Connectivity Indices

The Prediction of Soil Sorption Coefficients of Heterocyclic Nitrogen Compounds by Octanol/Water Partition Coefficient, Water Solubility, and by Molecular Connectivity Indices

Mobility of 2,2’,5,5’-Tetrachlorobiphenyl in Model Systems Containing Bottom Sediments and Water from the Lower Fox River, Wisconsin

Sediment-water partitioning and diffusive transport of 2,2’,5,5’-tetrachlorobiphenyl, PCB congener IUPAC #52 (TCB52) were examined in laboratory experiments with sediments from two sites in the lower Fox River, Wisconsin. Native water was pumped at controlled flow rates through cells containing sediments amended with a known activity of carbon-14-labeled TCB52. Concentrations of TCB52 in water and sediments were determined by liquid scintillation measurements of carbon-14 activity. Sediment-water partitioning was independent of flow rate for rates up to 8 m/d. Distribution coefficients (K d) and soil-sorption coefficients (K oc) were found to be at maximum levels 5–10 cm below the surface, despite an absence of significant variation in the fraction of organic carbon (f oc) through the same profile. Other factors, such as the effects of colloids and microbial activity in the sediments, are likely to be important in controlling the PCB distribution. Log K d and log K oc ranges were 4.1–4.9 and 5.3–6.1, respectively, and calculated effective diffusivities at the sediment-water interface ranged from 3 to 8 × 10 −10 cm 2/s. Gradual increases with time in TCB52 concentrations in the water phase, possibly due to effects of microbial activity, were observed. Diffusion experiments and models showed that the TCB52 migration rate within the sediment column is 8-9 mm/yr.

QSAR modelling of soil sorption. Improvements and systematics of log K OC vs. log K OW correlations

A systematic study was performed to evaluate the quality and reliability of the quantitative relationships between the soil sorption coefficients and the n-octanol/water partition coefficients (log K OC vs. log K OW). A system of QSAR models has been derived which is based on a reliable set of experimental log K OW data (LOGPSTAR data) or reliable estimates calculated with the latest version of the ClogP algorithm. Particular emphasis has been made to clearly define the boundaries for application of developed models as well as the quality of estimates. Thus, for each developed model the application domain is clearly defined through the chemical (structural) domain, substituents domain, and X-variable domain. Finally, the QSAR model with the first-order molecular connectivity indices has been incorporated in the derived system of QSAR models since the soil sorption estimates of the predominantly hydrophobic chemicals based on the log K OW data have large uncertainties, particularly in the log K OW data range from 4 to 7.5.

Implication of spatial variability of organic carbon on predicting pesticide mobility in soil

In this study, the depth distribution of organic carbon (OC) content in a sandy soil was characterized for a small agricultural plot (1.5 ha). The means and the distributions for measured OC were used as sorption-related parameters in a solute transport model to predict the movement of the herbicide atrazine in the unsaturated zone. Simulations were performed in order to assess the impact of OC variability in the evaluation of the herbicide concentration reaching the water table. The frequency distributions for soil OC at various depth intervals followed typical normal laws. The value for the coefficient of variation was lower at the first depth interval than at deeper soil intervals, possibly as a result of soil tillage practices. In predicting pesticide transport, the deterministic approach was shown to be sensitive to the variability of the soil sorption coefficient controlled by OC content. However a stochastic approach showed that in actual field situations, the in situ variability of soil parameters that control the soil-water flow could have a greater influence than the sorption-related parameter such as OC content. In this case, the field characterization of the horizontal distribution of OC may not improve the representativeness of the simulation results.

Modelling the fate of organic chemicals in the soil plant environment: Model study of root uptake of pesticides

The fate of organic chemicals in the soil-plant-atmosphere environment and the governing processes were studied with a coupled dynamic soil transport and plant compartment model. Scenarios with applications of pesticides on sand and loam soils with chemical uptake in barley and wheat were used in the model calculations. Root uptake and concentrations in the plant compartments stem, leave and fruit were calculated for the pesticides terbuthylazine, isoproturon and carbofuran. The effectivity of uptake from soils with different soil sorption coefficients had been shown for sand and loam soils. The processes degradation in plant and volatilization from leaves to atmosphere are especially effective for carbofuran and terbuthylazine. Although the concentrations in corn at harvest are lower than the maximum allowed concentrations, the peak concentrations in the course of the vegetation period are significantly higher (factor ≤ 200).

Environmental fate of chlorpyrifos.

Chlorpyrifos is an organophosphorus compound that displays broad-spectrum insecticidal activity against a number of important arthropod pests. As a result, it is employed in a wide variety of agricultural and specialty pest control scenarios. Various formulations of chlorpyrifos have been developed to maximize stability and contact with pests and minimize human exposure. From corn agriculture in the United States to termite control in Japan to cotton agriculture in Egypt to citrus horticulture in Spain, chloropyrifos has been successfully employed to combat insect and other arthropod pests threatening the production of food and fiber and maintenance of human health. Due to the nonpolar nature of the chlorpyrifos molecule, it possesses a low water solubility (< 2 ppm) and great tendency to partition from aqueous into organic phases in the environment (log P of 4.7-5.3). It is characterized by an average soil and sediment sorption coefficient (Koc) of 8498 and aquatic bioconcentration factor of 100-5100 in fish. As a result of its high propensity for sorption, its movement through and over the soil profile is limited. It has been found to be relatively immobile vertically in soil and has not proved to be a groundwater contaminant. Surface runoff and erosion mobility are also low, and, in general, less than 0.3% of soil surface application has been observed to move even under the heaviest simulated precipitation conditions. Chlorpyrifos has an intermediate vapor pressure (2 x 10(-5) mm Hg, 25 degrees C), and under some conditions volatility is a significant mechanism of dissipation. This is especially true for plant foliage, from which it is the major means of loss, to some extent from water surfaces, and to a lesser degree from moist soil surfaces. Chlorpyrifos is a degradable compound, and both abiotic and biotic transformation processes effect its degradation within environmental compartments (Fig. 1). In all cases, the major pathway of transformation involves cleavage of the phosphate ester bond to form 3,5,6-trichloro-2-pyridinol (TCP). Hydrolytic transformation, although relatively slow in pure water under ideal conditions (half-lives of 29-74 d at pH 7, 25 degrees C), may be catalyzed under certain environmental conditions. These include alkaline conditions in water (pH > or = 8) and alkaline (pH > or = 7.5) and air-dry conditions in soil, and in some soils hydrolysis may be the major means of dissipation (Fig. 2).(ABSTRACT TRUNCATED AT 400 WORDS)

Soil sorption and chemical topology

This study was undertaken to test the ability of the molecular connectivity model to predict the soil sorption coefficients of polar organic compounds. Quantitative models, based on the first- and second-order molecular connectivity indices, were developed for estimating soil sorption coefficients of 65 polar compounds arranged into four classes by their functional groups: acetanilides, amides, dinitroanilines, and triazoles.

Organic matter fractions controlling the sorption of atrazine in sandy soils

The soil-water distribution (K d) of atrazine has been studied in 24 soil profiles, comprising 109 soil horizons derived from granodioritic materials; K d ranged from 0.01 L/kg to 64 L/kg with a mean value of (2.4 ± 7.3) L/kg. The concentrations of organic carbon, cation exchange capacity, clay, and oxides of iron, aluminum, and manganese were determined. In a multiple linear regression analysis K d was strongly correlated with the organic carbon content (f oc) and weakly correlated with aluminum oxides. No other soil components were correlated with K d. The organic carbon soil sorption coefficient (K oc) was estimated to be 216 ± 9 L/kg (95% confidence limits) from a linear plot of K d versus the f oc. In a logarithmic correlation between K d and f oc the non-linearity constant proved statistically significant from unity: logK d=(1.81 ± 0.20) + (0.75 ± 0.07) x logf oc which indicates that not only the concentration, but also the composition of the organic matter play important roles in soil sorption of atrazine. In 48 of the 109 soil horizons which contained more than 0.1% of organic carbon, the organic matter was fractionated into humic acids, fulvic acids, humin and free organic matter. A multiple linear regression analysis between K d and the various organic matter fractions revealed that humic acid (Ha) explained 71% of the variance compared to 26% for humin plus free organic matter (Hum + Fom). In addition, 3% of the variance was explained by manganese oxide: K d= (167± 11) x Ha-(0.74 ± 0.09) x (Hum + Fom) + (21± 16) x MnO- (1.6± 1.0) Previously published equations for predictions of K oc of a compound from its water solubility and its octanol-water partition coefficient (K ow) were evaluated. K ow proved to be the best predictor for atrazine.

Molecular topology/fragment contribution method for predicting soil sorption coefficients

The first-order molecular connectivity index ( 1 χ) has been successfully used to predict soil sorption coefficients (K oc ) for nonpolar organics, but extension of the model to polar compounds has been problematic. To address this, we developed a new estimation method based on 1 χ and a series of statistically derived fragment contribution factors for polar compounds. After developing an extensive database of measured K oc values, we divided the dataset into a training set of 189 chemicals and an independent validation set of 205 chemical.

Quantitative modeling of environmental fate and impact of commercial chemicals

AbstractPresent laws in many countries require that all commercial chemicals be assessed for their environmental behavior and hazards. Because there are a large number of chemicals currently in common use (approximately 100,000) and new chemicals are being registered at a very high rate (1,000 per year), it is obvious that our human and material resources are insufficient to obtain experimentally even basic information about environmental fate and effects for all these chemicals. Thus, it is necessary to develop quantitative models that will accurately and rapidly predict environmental behavior for large sets of chemicals. During the last decade, a considerable effort has been made to develop methods that use molecular characteristics to describe environmental behavior of organic pollutants. Thus far, molecular connectivity indexes have been shown to be the most successful structural property for describing and predicting soil sorption coefficients, association coefficients with dissolved humic substances, Henry's law constants, bioconcentration factors in aquatic organisms and vegetation, biodegradation rates, and fish acute toxicity. The general quantitative model, based on the first‐order molecular connectivity index (MCI), has been developed for the accurate estimation of soil sorption coefficients for predominantly hydrophobic chemicals: polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), halogenated hydrocarbons, and phenols. It is possible to extend this model for many classes of agricultural chemicals. A similar model, based on the second‐order valence MCI, has been developed for fish bioconcentration factors of PCBs, chlorinated diphenyl oxides, halogenated hydrocarbons, PAHs, and phenols, plus substituted benzenes. Furthermore, a prototype expert system has been developed for classifying untested chemicals as readily or not readily biodegradable, based on their chemical structures. Finally, using a standardized data base for fish acute toxicity, we have obtained a simple linear correlation between the valence zero‐order MCI and the 96‐h LC50 data for a large group of 150 structurally diverse commercial chemicals.

Chemical topology and ecotoxicology

The experimental determination of environmental parameters (e.g. soil sorption, bioconcentration, biodegradation and biotransformation, toxic effects, etc.) of commercial chemicals is a costly and time-consuming process. Since there is a large number of chemicals currently in common use (approximately 100 000) and new chemicals are registered at a very high rate (1000/year) it is obvious that our human and material resources are insufficient to obtain experimentally even basic information on environmental fate and effects for all those chemicals. Thus, it is necessary to develop quantitative models that will accurately and rapidly predict environmental behaviour for large sets of chemicals. Thus far, molecular connectivity indices have been shown to be the most successful structural property for describing and predicting soil sorption coefficients, association with dissolved humic substances, Henry's law constants, bioconcentration factors in aquatic organisms and vegetation, biodegradation, and acute toxicity. We describe and discuss the most recent results on modelling environmental fate of organic pollutants by the application of molecular connectivity indices. Two sections describe the usefulness of environmental QSAR models based on n-octanol/ water coefficients and the systematics and possible physical interpretation of molecular connectivity indices. Some practical and theoretical weaknesses and pitfalls are discussed concerning the use of n-octanol/water partition coefficients in environmental QSAR research.

Predictive QSPR models for estimating soil sorption coefficients: potential and limitations based on dominating processes

The sorption coefficients of 50 organic chemicals and pesticides of defined chemical classes (carboxylic acids, esters, amines and amides — polar and nonpolar) were determined with three different sorbents according to OECD Guideline 106. For various xenobiotics the potential of predicting K oc from molecular descriptors, e.g. electronic, geometric (calculated by quantum mechanical methods) and topological parameters, was analysed in order to determine the scope and limitations of respective quantum structure-property relationships. Several regression equations were derived for nonpolar compounds, e.g. esters. As for the more polar compounds the variation in K oc values is up to two orders of magnitude, and only poor correlations were obtained for most of the descriptors analysed.

Fate of diethylene glycol dinitrate in surface waters

The environmental fate of diethylene glycol dinitrate (DEGDN) in surface waters is dominated by photolysis with surface half-lives ranging from 15 days in summer to 59 days in winter at 40°N. The environmental quantum yield is 0.18. Photolysis of DEGDN initially forms nitrate ion and 2-hydroxyethyl nitratoacetate; the latter photolyzes further to 1- and 2-carbon acids and additional nitrate. DEGDN biotransforms with a second-order rate constant of 3.9 × 10 −11 mL cell −1 h −1, corresponding to a half-life of about 2 years in a typical surface water. Intermediate biotransformation products were observed but were further transformed and did not accumulate. DEGDN is expected to move readily through soils because it had low soil sorption coefficients K p of 2 and 0.8 g mL −1 on EPA-5 and EPA-18 sediments, respectively. Abiotic reduction occurred rapidly in lake and river sediments but the importance of this process for overall fate is difficult to quantitate. Other fate parameters measured at 25°C were a water solubility of 3900 mg L −1, octanol/water partition coefficient of 9.6 (dimensionless), Henry's constant of < 10 −6 (dimensionless), base-catalyzed hydrolysis constant of 7 × 10 −7 M −1 s −1, neutral hydrolysis constant ≤ 2 × 10 −8 s −1, and biouptake constants of < 10 g dry cells/g water for Anabena flos-aquae and Selenastrum capricornutum.