Estimating K(oc) for persistent organic pollutants: limitations of correlations with K(ow)

Influence of edaphic conditions and persistent organic pollutants on earthworms in an infiltration basin

In recent decades, stormwater management has developed to allow stormwater to infiltrate directly into the soils instead of being collected and routed to sewer systems. However, during infiltration, stormwater creates a sediment deposit at the soil surface as the result of high loads of suspended particles (including pollutants), leading to the settlement of sedimentary layers prone to colonization by plants and earthworms. This study aims to investigate the earthworm communities of a peculiar infiltration basin and investigate the influence of edaphic conditions (water content, organic matter content, pH, height of sediment) and of persistent organic pollutants (POPs: PCBs, PCDDs and PCDFs) on these earthworms. Attention was paid to their age (juveniles or adults) and their functional group (epigeic, endogeic, anecic). We found that the earthworm abundance was mostly driven by edaphic conditions, with only a slight impact of POPs, with a significant negative impact of PCBDLno for juveniles and endogeic, and PCDDs for epigeic. On the contrary, the height of the sediment and the water content are beneficial for their presence and reproduction. Furthermore, POPs contents are also linked to physicochemical parameters of the sediment. Bioaccumulation was clearly revealed in the studied site but does not differ between juveniles and adults, except for PCDDs. Conversely, BAF values seemed to vary between functional groups, except for PCBDL non-ortho. It strongly varies with the family types (PCBs versus PCCD/Fs) and between congeners within the same family, with specific strong bioaccumulation for a few congeners.

Quantification of the sorption of organic pollutants to minerals via an improved mathematical model accounting for associations between minerals and soil organic matter

The retention of organic pollutant (OP) in soils is commonly attributed to interactions with soil organic matter (SOM), perhaps overlooking substantial involvement of soil minerals. In this study, 36 soil samples with far-ranging ratios of clay to organic carbon were used to examine contribution of minerals on soil sorption of pentachlorophenol (PCP) and phenanthrene (PHE). Sorption isotherms (n = 216) were fit individually using three typical sorption models, with the most fitted K_d values screened out for quantification of the net mineral contribution to total sorption via development of mathematical model accounting for associations between minerals and SOM. Two mineral-relevant parameters [adsorption distribution coefficient (K_min) and mineral contribution index (MCI)] were simultaneously defined. Previously reported soil sorption data of PCP, PHE and butachlor (13, 12 and 46, respectively) were also extracted and included to improve the credibility of mathematic model. The average MCI values were calculated as 0.421, 0.405 and 0.512 in PCP, PHE and butachlor treated soils, respectively, very close to or even over than the minerals dominant critical value (0.5). This suggested the significant, or even predominant, contribution of minerals - as compared to SOM. Significant dependence of MCI with four conventional parameters of soil property further offered the possibility to roughly evaluate mineral contributions based on estimated threshold values of soil property parameters (especially TOC). This study provides an accessible approach for predicting the contribution of minerals in soil OP retention, especially highlighting their predominant roles vs. SOM in regulating OP removal in most of subsurface soil or contaminated brownfields where organic carbon content of soil was very low, that was not like what previously believed.

Pesticide regulations for agriculture: Chemically flawed regulatory practice

Two categories of pesticide soil models now exist. Government regulatory agencies use pesticide fate and transport hydrology models, including versions of PRZM.gw. They have good descriptions of pesticide transport by water flow. Their descriptions of chemical mechanisms are unrealistic, having been postulated using the universally accepted but incorrect pesticide soil science. The objective of this work is to report experimental tests of a pesticide soil model in use by regulatory agencies and to suggest possible improvements. Tests with experimentally based data explain why PRZM.gw predictions can be wrong by orders of magnitude. Predictive spreadsheet models are the other category. They are experimentally based, with chemical stoichiometry applied to integral kinetic rate laws for sorption, desorption, intra-particle diffusion, and chemical reactions. They do not account for pesticide transport through soils. Each category of models therefore lacks what the other could provide. They need to be either harmonized or replaced. Some preliminary tests indicate that an experimental mismatch between the categories of models will have to be resolved. Reports of pesticides in the environment and the medical problems that overlap geographically indicate that government regulatory practice needs to account for chemical kinetics and mechanisms. Questions about possible cause and effect links could then be investigated.

Estimating baseline toxicity of PAHs from marine chronically polluted sediments and bioaccumulation in target organs of fish hypothetically exposed to them: a new tool in risk assessment

In soils and sediments contaminated by Hydrophobic Organic Compounds (HOCs), the total concentrations are less indicative of potential exposure and distribution than the associated freely dissolved concentrations (Cfree) or chemical activity. Therefore, these two parameters are increasingly used to assess sediment contamination with regard to their (1) partitioning into the water column, (2) bioaccumulation and (3) baseline toxic potential. In this work, sediments from a chronically polluted coastal area, with similar total PAH concentrations, were studied using PDMS coated glass jars (obtaining Cfree(SW) and chemical activity) to predict baseline toxicity and potential bioaccumulation from these sediments. The results indicate that, on the one hand, the chemical activity of the sediments differed by up to one order of magnitude and was below the level at which lethal baseline toxicity is expected, but is still a cause for concern due to the presence of other pollutants and different mechanisms of action. On the other hand, the combination of Cfree measurements and Biota to Sediment Accumulation Factors (BSAFs) allowed concentrations in different target organs of benthic flatfish, hypothetically exposed to these chronically polluted sediments, to be estimated. This new approach allows us to predict the concentration in biological tissues under the study of Cfree(SW) in sediments, as a useful tool in risk assessment.

Efficiency of wipe sampling on hard surfaces for pesticides and PCB residues in dust

Pesticides and polychlorinated biphenyls (PCBs) are commonly found in house dust and have been described as a valuable matrix to assess indoor pesticide and PCB contamination. The aim of this study was to assess the efficiency and precision of cellulose wipe for collecting 48 pesticides, eight PCBs, and one synergist at environmental concentrations. First, the efficiency and repeatability of wipe collection were determined for pesticide and PCB residues that were directly spiked onto three types of household floors (tile, laminate, and hardwood). Second, synthetic dust was used to assess the capacity of the wipe to collect dust. Third, we assessed the efficiency and repeatability of wipe collection of pesticides and PCB residues that was spiked onto synthetic dust and then applied to tile. In the first experiment, the overall collection efficiency was highest on tile (38%) and laminate (40%) compared to hardwood (34%), p<0.001. The second experiment confirmed that cellulose wipes can efficiently collect dust (82% collection efficiency). The third experiment showed that the overall collection efficiency was higher in the presence of dust (72% vs. 38% without dust, p<0.001). Furthermore, the mean repeatability also improved when compounds were spiked onto dust (<30% for the majority of compounds). To our knowledge, this is the first study to assess the efficiency of wipes as a sampling method using a large number of compounds at environmental concentrations and synthetic dust. Cellulose wipes appear to be efficient to sample the pesticides and PCBs that adsorb onto dust on smooth and hard surfaces.

In silico model for predicting soil organic carbon normalized sorption coefficient (K(OC)) of organic chemicals

As a kind of in silico method, the methodology of quantitative structure-activity relationship (QSAR) has been shown to be an efficient way to predict soil organic carbon normalized sorption coefficients (KOC) values. In the present study, a total of 824 logKOC values were used to develop and validate a QSAR model for predicting KOC values. The model statistics parameters, adjusted determination coefficient (R(2)adj) of 0.854, the root mean square error (RMSE) of 0.472, the leave-one-out cross-validation squared correlation coefficient (Q(2)LOO) of 0.850, the external validation coefficient Q(2)ext of 0.761 and the RMSEext of 0.558 were obtained, which indicate satisfactory goodness of fit, robustness and predictive ability. The squared Moriguchi octanol-water partition coefficient (MLOGP2) explained 66.5% of the logKOC variance. The applicability domain of the current model has been extended to emerging pollutants like polybrominated diphenyl ethers, perfluorochemicals and heterocyclic toxins. The developed model can be used to predict the compounds with various functional groups including C=C, -C≡C-, -OH, -O-, -CHO, C=O, -C=O(O), -COOH, -C6H5, -NO2, -NH2, -NH-, N-, -N-N-, -NH-C(O)-NH-, -O-C(O)-NH2, -C(O)-NH2, -X(F, Cl, Br, I), -S-, -SH, -S(O)2-, -OS(O)2-, -NH-S(O)2-, (SR)2PH(OR)2 and Si.

Experimental device for dioxin vapour generation: a steady and adjustable source of gaseous 2,3-DCDD

PCDD/Fs are Persistent Organic Pollutants (POPs), generated by incomplete combustion of carbonaceous and chlorinated compounds. Because of their toxicity, they have to be monitored at emission, from stationary sources like waste incinerator. In the framework of the development of an on-line analyser, the laboratory prototype requires a gaseous dioxin source. We detail the principles of a dynamic generator based on the sublimation of solid sample and on the diffusion method. Such a device has to supply a polluted flow at steady and adjustable concentration of dioxin. The dioxin generation rate is determined by the weight loss of the solid sample. It is constant during time for temperatures ranging between 75 and 100°C and for generation flow rates greater than or equal to 50 mL min(-1). Variation of generation rate with temperature is predictable. With the increasing of temperature, emitted concentration increases while the increase of the inlet pressure decreases the concentration. Helium carrier gas leads to a higher generation rate than with N2 in agreement with mass and molecular volume ratio. Thus, the outlet concentration and flow rate can be settled independently in the range of 3-100 ppm and 50-200 mL min(-1).

The effect of different log P algorithms on the modeling of the soil sorption coefficient of nonionic pesticides

Collecting data on the effects of pesticides on the environment is a slow and costly process. Therefore, significant efforts have been focused on the development of models that predict physical, chemical or biological properties of environmental interest. The soil sorption coefficient normalized to the organic carbon content (Koc) is a key parameter that is used in environmental risk assessments. Thus, several log Koc prediction models that use the hydrophobic parameter log P as a descriptor have been reported in the literature. Often, algorithms are used to calculate the value of log P due to the lack of experimental values for this property. Despite the availability of various algorithms, previous studies fail to describe the procedure used to select the appropriate algorithm. In this study, models that correlate log Koc with log P were developed for a heterogeneous group of nonionic pesticides using different freeware algorithms. The statistical qualities and predictive power of all of the models were evaluated. Thus, this study was conducted to assess the effect of the log P algorithm choice on log Koc modeling. The results clearly demonstrate that the lack of a selection criterion may result in inappropriate prediction models. Seven algorithms were tested, of which only two (ALOGPS and KOWWIN) produced good results. A sensible choice may result in simple models with statistical qualities and predictive power values that are comparable to those of more complex models. Therefore, the selection of the appropriate log P algorithm for modeling log Koc cannot be arbitrary but must be based on the chemical structure of compounds and the characteristics of the available algorithms.

Soil-water interfacial adsorption of phenanthrene along a Chinese climatic gradient of soils with and without the addition of black carbon

Sorption isotherms for a hydrophobic solute probe, phenanthrene, were determined in 16 Chinese soils. They were sampled along a climatic gradient, and amended, or not, with charcoal (0.2%, 0.5%, and 1%), a form of black carbon (BC). Within the concentration range of added phenanthrene (0.2-0.8 mg l(-1)), most of the adsorption isotherms of the unamended soils were non-linear. Both the Freundlich equation and the Dual Reactive Domain Model (DRDM) model closely fitted the data, indicating that phenanthrene sorption in these soils was site-specific and demonstrated capacity-limited adsorption in a condensed organic domain. Correlations between the Freundlich model capacity factor (K(F)) and soil physico-chemical properties showed that the total soil organic C (TOC) concentrations, cation exchange capacities and silt had a cumulative effect on phenanthrene sorption, indicating that organic and inorganic components interacted in this process. The soils studied also indicated that humic acid carbon (HAC) concentration may be a further relevant factor that should be considered. The soils covered a wide range of physical and chemical properties, in particular organic C and the organic carbon-normalized distribution coefficients (K(OC)) demonstrated a large range of variation. Therefore, K(OC) values may be poor predictive parameters for phenanthrene sorption by soils. Addition of BC not only enhanced the sorption of phenanthrene but also altered the sorptive characteristics of the soils studied.

Levels and distribution of dissolved hydrophobic organic contaminants in the Morava river in Zlín district, Czech Republic as derived from their accumulation in silicone rubber passive samplers

Dissolved waterborne polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) were assessed over a period of one year at five sampling sites in a model industrial region in the Czech Republic using silicone rubber passive samplers. The spatial variability of POPs in the studied region in water was small and diffusive pollution sources predominate. Concentrations of the most volatile PAHs decreased with increasing water temperature in the whole region, which reflects the seasonality in atmospheric deposition. The dissolved concentrations of more hydrophobic PAHs, PCBs and OCPs in and downstream the industrial zone are related to desorption from suspended particles. Upstream the industrial area, a positive correlation of dissolved and particle-bound contamination was observed only for DDT metabolites and hexachlorobenzene. Calculated fugacities in water and bottom sediment indicated a fair degree of equilibrium between these compartments for OCPs and PCBs, whereas sediment represented a potential source of PAHs.

Linear and non-linear relationships between soil sorption and hydrophobicity: model, validation and influencing factors

The hydrophobic parameter represented by the octanol/water partition coefficient (logP) is commonly used to predict the soil sorption coefficient (K(oc)). However, a simple non-linear relationship between logK(oc) and logP has not been reported in the literature. In the present paper, soil sorption data for 701 compounds was investigated. The results show that logK(oc) is linearly related to logP for compounds with logP in the range of 0.5-7.5 and non-linearly related to logP for the compounds in a wide range of logP. A non-linear model has been developed between logK(oc) and logP for a wide range of compounds in the training set. This model was validated in terms of average error (AE), average absolute error (AAE) and root-mean squared error (RMSE) by using an external test set with 107 compounds. Nearly the same predictive capacity was observed in comparison with existing models. However, this non-linear model is simple, and uses only one parameter. The best model developed in this paper is a non-linear model with six correction factors for six specific classes of compounds. This model can well predict logK(oc) for 701 diverse compounds with AAE = 0.37. The reasons for systemic deviations in these groups may be attributed to the difference of sorption mechanism for hydrophilic/polar compounds, low solubility for highly hydrophobic compounds, hydrolysis of esters in solution, volatilization for volatile compounds and highly experimental errors for compounds with extremely high or low sorption coefficients.

Linear and non-linear relationships between soil sorption and hydrophobicity

The relationship between log K (oc) and log P was examined by use of a large dataset. For most of the hydrophobic compounds (e.g. 0.5 < log P < 7.5), the organic carbon content plays a dominant role in soil sorption and the sorption coefficient is linearly related to the octanol/water partition coefficient. For hydrophilic compounds (e.g. log P < 0.5), hydrophobic sorption becomes less significant. The hydrophilic contribution to sorption is equal to, or higher than, the hydrophobic contribution to sorption, resulting in the observed K (oc) values being higher than those predicted from their log P values. For highly hydrophobic compounds (e.g. log P > 7.5), log K (oc) decreases with increasing hydrophobicity because of a lack of chemical availability due to low solubility. A linear solvation energy relationship shows that the sorption potential increases with increasing molecular size by increasing the dispersion interactions between the chemical and soil organic phase. The sorption potential decreases with increase in the basicity of hydrophobic compounds by increasing the H-bonding of chemicals with water. Principal component analysis shows that the octanol/water system is the closest system, but not an ideal surrogate, to describe the soil sorption for hydrophobic compounds as compared with other solvent/water partition systems.

Human and environmental biomonitoring of polychlorinated biphenyls and hexachlorobenzene in Saxony, Germany based on the German Environmental Specimen Bank

The objective of the present study was to investigate the principle relationships between concentrations in human and environmental matrices of polychlorinated biphenyls (PCBs) and hexachlorobenzene (HCB) in short distance comparable areas within Saxony, Germany by employing the data of the German Environmental Specimen Banking (ESB). Examples supporting this idea were presented by selecting data on blood plasma collected from students in University of Halle and pine shoots, egg matter of city pigeons, earthworm, and roe deer liver. Similar pattern for PCB 138 and PCB 180 was found for the human plasma and pine shoots samples during investigated years and the human data followed the corresponding environmental levels with some delay of approximately two years. However, PCB 153 that was the prevailing congener did not manifest this relationship. In addition, the correlation of the ratios of concentrations (human/environmental concentration) to some physicochemical constants such as molecular weight (MW), octanol-water partition coefficient (logK(ow)), Henry's law constant (K(H)), and sorption partition coefficient (logK(oc)) of HCB, PCB 138, PCB 153, and PCB 180 were studied. The resulted negative slopes with all constants in case of blood plasma/city pigeons egg matter pairs suggested that the accumulation of lipophilic compounds is more pronounced in pigeon eggs than in human blood.

Occurrence of priority hazardous PAHs in water, suspended particulate matter, sediment and common eels (Anguilla anguilla) in the urban stretch of the River Tiber (Italy)

This study investigated the occurrence of polycyclic aromatic hydrocarbons (PAHs) in water, suspended particulate matter (SPM), bed sediment and common eels (Anguilla anguilla) in the urban stretch of the River Tiber (Italy). The selected PAHs, fluoranthene, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo(a)pyrene, benzo(g,h,i)perylene, indeno(1,2,3-cd)pyrene, belong to the EC priority list of dangerous substances. SPM was found to be the most polluted compartment, with values ranging from 1663.1 to 15472.9 ngg(-1) (Σ(6)PAHs), followed by sediment samples, from 157.8 to 271.6 ngg(-1) and by aqueous samples, from 23.9 to 72.0 ngL(-1). The distribution coefficient (K(d)) showed a good correlation with particle organic carbon (OC) content, while K(oc) values experimentally measured for sediment/SPM deviated from those predicted by K(ow), implying that for very hydrophobic compounds, K(ow) alone may not be an appropriate descriptor of all the thermodynamic forces involved in their sorption to aquatic particles. Some selected PAH ratios indicated that PAHs in the River Tiber come mainly from pyrolitic sources and vehicular traffic. Concentrations of individual PAHs in muscles of common eels varied from 0.8 to 7.0 ngg(-1) wet wt. and the calculated toxicity equivalent concentration (TEQ, 1.8 ngg(-1) wet wt.) of total PAHs fell below the recommended screening value (SV) in US EPA guidelines, suggesting no concern for human consumption.

Seasonal PCB bioaccumulation in an arctic marine ecosystem: a model analysis incorporating lipid dynamics, food-web productivity and migration

Primary production and species' lipid contents in Arctic ecosystems are notoriously seasonal. Additionally, seasonal migration patterns of fish may alter prey availability and thus diet. Taking the southern Barents Sea as a study region and PCBs as model contaminants, we examined to what extent each of these factors cause bioaccumulation in fish to change throughout the year. Data on physiology and standing stocks of multiple trophic levels were used to estimated season-specific carbon budgets and by inference also corresponding values for food ingestion and production of cod, capelin, and herring. When combining these values with Arctic lipid dynamics for bioaccumulation model parameter setting, we predicted bioaccumulation factors (BAFs) that were in good agreement with BAFs for cod and capelin observed between 1998 and 2008. BAFs in all fish were 10 times lower in summer than in spring and fall/winter and were mainly driven by lipid dynamics. Trophic magnification factors (TMFs: increase in BAF per unit increase in trophic level as derived from our carbon budgets) were highest for PCB 153 during spring (2.3-2.4) and lowest for PCB 52 in summer and fall/winter (1.5-1.6) and were driven by seasonal shifts in trophic level and lipid dynamics.

Statistical external validation and consensus modeling: a QSPR case study for Koc prediction

The soil sorption partition coefficient (log K(oc)) of a heterogeneous set of 643 organic non-ionic compounds, with a range of more than 6 log units, is predicted by a statistically validated QSAR modeling approach. The applied multiple linear regression (ordinary least squares, OLS) is based on a variety of theoretical molecular descriptors selected by the genetic algorithms-variable subset selection (GA-VSS) procedure. The models were validated for predictivity by different internal and external validation approaches. For external validation we applied self organizing maps (SOM) to split the original data set: the best four-dimensional model, developed on a reduced training set of 93 chemicals, has a predictivity of 78% when applied on 550 validation chemicals (prediction set). The selected molecular descriptors, which could be interpreted through their mechanistic meaning, were compared with the more common physico-chemical descriptors log K(ow) and log S(w). The chemical applicability domain of each model was verified by the leverage approach in order to propose only reliable data. The best predicted data were obtained by consensus modeling from 10 different models in the genetic algorithm model population.

Uncertainty associated to the analysis of organochlorine pesticides in water by solid-phase microextraction/gas chromatography–electron capture detection—Evaluation using two different approaches

As the performances of analytical instrumentation are being gradually enhanced, the limits of detection become increasingly lower, allowing more environmental contaminants to be determined in different matrices. Problems emerge when dealing with data from different origins, once the uncertainty of the results is difficult to be compared, especially if its calculation procedure is rather different, as very often happens. Samples of two organochlorine pesticides of somewhat opposite characteristics (lindane and heptachlor, classified as persistent organic pollutants--POPs) were analyzed in aqueous media using headspace solid-phase microextraction (SPME) prior to gas chromatography-electron capture detection (GC-ECD) and this methodology was in-house validated. Detection limits of 0.097 and 0.050 microg l(-1), average intermediate precision of 11.6% and 27.5%, and average recovery of 95.6% and 103.0%, for lindane and heptachlor, respectively, were found. In the absence of available interlaboratory studies to assess the reliability of the results, the expanded uncertainty was calculated following two different approaches (bottom-up/Eurachem and modified top-down) and the results were compared. Globally it was clearly shown that, for both pesticides, the lower the concentration range, the higher the uncertainty associated to the results. Expanded uncertainties estimated by bottom-up/Eurachem approach varied from 51% to 14% for a lindane concentration range of 0.1-1 microg l(-1), and from 48% to 24% for a heptachlor range of 0.1-2 microg l(-1). Modified top-down approach pointed to 44% (lindane and heptachlor) in the same ranges, meaning that a uniform procedure for uncertainty estimation should be adopted.

QSPR study on soil sorption coefficient for persistent organic pollutants

Quantitative structure-property relationship (QSPR) models of soil sorption coefficients for 32 persistent organic pollutants were constructed using our recently introduced Lu index and novel distance-based atom-type DAI topological indices. Using multiple linear regression technique, a 6-variable model was obtained with the correlation coefficient of estimations (R) being 0.95, and the standard error of estimations (s) being 0.23, and the correlation coefficient (R(cv)) and the standard error (s(cv)) in the leave-4-out cross-validation procedure are 0.90 and 0.31, respectively. The results in this study indicate that soil sorption coefficients of POPs are dominated by molecular size while some DAI indices have smaller influence.

QSPR Treatment of the Soil Sorption Coefficients of Organic Pollutants

In this study, general and class-specific QSPR models for soil sorption, logK(OC), of 344 organic pollutants (0 < logK(OC) < 4.94) were developed using a large variety of theoretical molecular descriptors based only on molecular structure. Two general models were obtained. The first model was derived for a structurally representative set of 68 chemicals (R2=0.76, s=0.44), whereas the second involved a total of 344 compounds (R2=0.76, s=0.41). The first was validated using the data for the remaining 276 pollutants (R2=0.70, s=0.45). An additional validation of both models was performed using an independent set of 48 pollutants. Both models predict the logK(OC) at the level of experimental precision, while the theoretical molecular descriptors appearing in the QSPR models give further insight into the mechanisms of soil sorption. The analysis of the distribution of the residuals of the logK(OC) values calculated by both general models indicated the need and possible advantages of modeling soil sorption for smaller data sets related to individual classes of chemicals. Accordingly, QSPR models were also developed for 14 chemical classes. The descriptors appearing in these models were discussed as related to the possible interaction mechanisms in soil sorption.

Particle-water partitioning of PCBs in the photic zone: a 25-month study in the open Baltic Sea

From previous laboratory and field studies, it remains unclear whether partitioning of hydrophobic organic contaminants (HOCs) to phytoplankton from water is kinetically limited or may be treated as an equilibrium process. Here, we report on the partitioning of polychlorinated biphenyls (PCBs) to particulate organic carbon (POC), dominated by planktonic primary production, in the open Baltic Sea during a 25-month period. The organic carbon-normalized partition coefficient (Koc) was corrected for temperature, salinity, and sorption to filter-passing organic carbon. At all 21 sampling occasions, the log Koc-log Kow regression was significantly linear, despite a large variation in biogeochemical parameters such as POC concentration and composition, primary production, and phytoplankton species composition. These data strongly suggest that partitioning of PCBs to POC in temperate surface waters is equilibrated and therefore not kinetically limited by factors such as rapid phytoplankton growth rate or large cell size. The partitioning of PCBs to the POC was described throughout seasonal cycles by log Koc = 0.88 +/- 0.07 log Kow + 0.90 +/- 0.47 (95% confidence interval). The slope of the log Koc-log Kow regression for the single sampling occasions varied between 0.56 and 1.25, and there was a seasonal variation in the POC sorbent quality (e.g., log Koc for PCB 28 varied between 5.5 and 6.9; median 5.9). These variations reflect the variability in structural composition of the POC pool in such pelagic waters. Being able to predict particle-water partitioning of HOCs significantly reduces the required complexity of both food web uptake models and predictions of POC-mediated export of HOCs to the deep ocean.

Fuzzy QSARs for predicting logKoc of persistent organic pollutants

Fuzzy regression methodology has been employed in this study to develop a relationship for logKoc for persistent organic pollutants (POPs) using other property and molecular descriptors. Fuzzy regression is distinct from statistical regression and is used to characterize the imprecision arising from limited data and/or incomplete model descriptions. The study is based on the premise that statistically based QSARs do not fully account for all the sorbate-sorbent interactions pertinent to the partitioning of POPs and as such these relationships have inherent fuzziness associated with them. A comparison between the statistical and fuzzy logKow-logKoc relationship indicated that the fuzzy regression model enveloped all scatter in the data and provided a tighter fit around the mid-point values (least-square estimates). In addition, fuzzy regression was also employed to characterize imprecision associated with a three parameter QSAR that employs molecular connectivity indicies. A comparison between fuzzy and statistical regression analysis indicated that the fuzziness in this model was primarily associated with characterization of local (atomic) scale interactions while statistical randomness manifested at both local and global (molecular) scales. Experimental and estimation artifacts appear to have a higher impact on statistical regression than fuzzy regression. However, the superiority of the fuzzy regression seems to diminish with increasing correlation between the inputs and the output variable.

Prediction of Soil Sorption Coefficient of a Diverse Set of Organic Chemicals From Molecular Structure

A correlation study based on simple structural descriptors for predicting the soil sorption coefficient, log K(oc), of a diverse set of 568 organic compounds is presented. Using a training set of 403 compounds, in which the log K(oc) values were in the range 0-6.5, multiple linear regression (MLR) was utilized to build the models. The models were validated using a test set of 165 chemicals not included in the training set. The statistics for a linear regression model with calculated aqueous solubility, log S, were r(2) = 0.80 and s = 0.51 in the training set, and r(2) = 0.76 and s = 0.61 in the test set. The model parameters used allow rapid and accurate calculation of log K(oc) values for a diverse set of organic chemicals, and propose the importance of molecular solubility, lipophilicity, size, flexibility, and ionization for a chemicals' sorption to organic soil material.

General and class specific models for prediction of soil sorption using various physicochemical descriptors

Diverse chemical descriptors were explored for use in QSAR models aimed to screen the soil sorption potential of organic compounds. The descriptors included logP, HyperChem QSARProperties descriptors, a combination of connectivity indices, geometrical, and quantum chemical measures, and two sets from the DRAGON and CODESSA program packages, respectively. Generally, the univariate logP models were capable of capturing most of the variation and give an indication of the sorption potential. The multivariate models required refined variable selection procedures but were shown to include crucial descriptors for modeling compound classes with specific chemical characteristics.

Soil ecotoxicity of polycyclic aromatic hydrocarbons in relation to soil sorption, lipophilicity, and water solubility

A data set was generated aiming to predict the toxicity of PAHs to soil organisms. Toxicity data include the effects of 16 PAHs on the survival and reproduction of the soil-dwelling springtail Folsomia fimetaria. The results show that only PAHs with reported log Kow values < or = 5.2 (i.e., naphthalene, acenaphthene, acenaphthylene, anthracene, phenanthrene, fluorene, pyrene, and fluoranthene) significantly affected the survival or reproduction of the test organisms. Threshold values for the toxicity of the individual PAHs could be expressed as pore-water concentrations by the use of reported organic carbon-normalized soil-pore-water partitioning coefficients (Koc values). For the PAHs with a log Kow < or = 5.2, toxicity significantly increased with increasing lipophilicity of the substances (r2 = 0.67; p = 0.012; n = 8), suggesting a narcotic mode of toxic action for most substances. However, the position of anthracene in the regression plot indicated a more specific mode of toxic action than narcosis, and removing this data point yielded the following regression equation: log EC10 (micromol/L) = -0.97 log Kow + 4.0 (r2 = 0.80; p = 0.006; n = 7). Using this quantitative structure-activity relationship (QSAR) to calculate threshold values for the toxicity of the remaining nontoxic substances (benz[a]anthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoranthene, dibenz[a,h]anthracene, benzo[a]pyrene, perylene, and indeno[1,2,3-cd]pyrene), the absence of toxicity could, in most cases, be explained by a limited water solubility, indicating that these substances do act by narcosis as the mode of toxic action and that their toxicity is governed by concentrations in the pore-water. The results provide important input to future model predictions of the ecological risk posed by PAH contaminated sites.

Solubility predictions for crystalline nonelectrolyte solutes dissolved in organic solvents based upon the Abraham general solvation model

The Abraham general solvation model is used to predict the saturation solubility of crystalline nonelectrolyte solutes in organic solvents. The derived equations take the form of log (CS/CW) = c + rR2 + sπ2H + aΣα2H + bΣβ2H + vVx and log (CS/CG) = c + rR2 + sπ2H + aΣα2H + bΣβ2H + l log L(16) where CS and CW refer to the solute solubility in the organic solvent and water, respectively, CG is a gas-phase concentration, R2 is the solute's excess molar refraction, Vx is McGowan volume of the solute, Σα2H and Σβ2H are measures of the solute's hydrogen-bond acidity and hydrogen-bond basicity, π2H denotes the solute's dipolarity and (or) polarizability descriptor, and log L(16) is the solute's gas-phase dimensionless Ostwald partition coefficient into hexadecane at 298 K. The remaining symbols in the above expressions are known equation coefficients, which have been determined previously for a large number of gas–solvent and water–solvent systems. Computations show that the Abraham general solvation model predicts the observed solubility behavior of anthracene, phenanthrene, and hexachlorobenzene to within an average absolute deviation of about ±35%.Key words: solubility predictions, organic solvents, nonelectrolyte solutes, partition coefficients.

Reliable QSAR for estimating Koc for persistent organic pollutants: correlation with molecular connectivity indices

Several recent studies have shown that n-octanol/water partition coefficients may not be a good predictor for estimating soil sorption coefficients of persistent organic pollutants (POPs), defined here as chemicals with log Kow greater than 5. Thus, an alternative QSAR model was developed that seems to provide reliable estimates for the soil sorption coefficients of persistent organic pollutants. This model is based on a set of calculated molecular connectivity indices and evaluated soil sorption data for 18 POPs. The chemical's size and shape, quantified by 1chi, 3chiC and 4chiC(v) indices, have a dominant effect on the soil sorption process of POPs. The developed QSAR model was rationalized in terms of potential hydrophobic interactions between persistent organic pollutants and soil organic matrix. Its high predictive power has been verified by an extensive internal and external validation procedure.