Wastewater effluents, groundwater, surface water, sediments, soils and air particulate matter are often contaminated by a multitude of chemicals. Since often no a priori knowledge of relevant toxicants exists, chemical analysis alone is not an appropriate tool for hazard assessment. Instead, a linkage of effect data and hazardous compounds is required. For that purpose, effect-directed analysis (EDA) was developed, which is based on a combination of biotesting, fractionation procedures and chemical analytical methods. Since a controversial discussion about the prospects of success in relation to the expense exists, the current methodological state of EDA for organic toxicants in complex mixtures and important results are reviewed in this paper with the aim of establishing criteria for the successful use of this promising tool. While EDA is a powerful tool to identify specifically acting individual toxicants close to the source of emission, it is inappropriate for screening purposes and often may fail in remote areas where the concentrations of specific toxicants are too low relative to the nonspecific toxicity of the whole mixture of natural and anthropogenic compounds. The biological tools have to be carefully selected with respect to their ability to detect specific effects and their significance in hazard assessment. Sophisticated chemical tools are required to identify individual toxicants in mixtures of thousands of compounds, which are typical for contaminated environments.

Effect-directed analysis: a promising tool for the identification of organic toxicants in complex mixtures?

Results of published pesticide mixture toxicity experiments conducted with aquatic organisms were compiled and evaluated to assess the accuracy of predictive mixture models. Three types of models were evaluated: Concentration addition (CA), independent action (IA), and simple interaction (SI). The CA model was the most often tested (207 experiments), followed by SI (59) and IA (37). The reviewed experiments are listed in the Supplemental material to provide a resource for future investigators. The predictive accuracy of each model was quantified for each experiment by the model deviation ratio (MDR), which was calculated by dividing the predicted toxicity by the observed toxicity. Eighty-eight percent of all experiments that evaluated the CA model had observed effective concentrations within a factor of 2 of predicted values (MDR values from 0.5–2.0). The median MDR was 1, about 5% of MDRs were less than 0.5, and about 5% were greater than 2, indicating unbiased estimates overall. The predictive accuracy of CA and IA models was influenced, however, by the different modes of action (MOA) of the pesticides. For experiments with pesticides with the same MOA, CA more accurately predicted effective concentrations for more experiments compared to IA, which tended to underpredict toxicity. The IA model was somewhat more accurate than the CA model for most mixtures with different MOAs, but in most cases there were relatively small differences between the models. Additionally, 80% of SI experiments had an MDR value below 2.0 despite a bias towards experiments that are likely to have an interaction. Thus, results indicate that the CA model may be used as a slightly conservative, but broadly applicable model with a relatively small likelihood of underestimating effects due to interactions.

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How Well Can We Predict the Toxicity of Pesticide Mixtures to Aquatic Life

An overview of Toxicity Identification and Evaluation (TIE) procedures, used for the effect-based analysis of endocrine disrupting compounds (EDCs) in environmental samples, is presented. Future trends in advanced chemical analysis of EDCs and some emerging contaminants are outlined. The review also gives an overview of concentration levels found in environmental samples and discusses the correlation of calculated estrogenicity (based on chemical analysis of target EDCs) with that measured by various bioassays.

Endocrine disrupting compounds and other emerging contaminants in the environment: a survey on new monitoring strategies and occurrence data.

Groundwater contamination potential from stormwater infiltration practices

The paper assesses the usefulness of the concept of ‘concentration addition’ (CA) for describing the joint effect of pesticides on aquatic organisms, based on literature data from 1972 to 1998. For more than 90% of 202 mixtures in 26 studies, CA was found to predict effect concentrations correctly within a factor of two. Although from a theoretical point of view the assumption of CA may be invalid when dealing with mixtures of compounds with dissimilar modes of action, the experimental results have usually been indistinguishable from that predicted by CA. Deviations from CA did occur, but were mostly limited in extent. Upward and downward deviations from CA were of comparable magnitude and frequency, and tended to cancel each other out. The combinations identified as most frequently leading to deviations from CA were those of an organophosphorus ester or a carbamate with either another organophosphorus ester or a synthetic pyrethroid.

© 2000 Society of Chemical Industry

Toxicity of mixtures of pesticides in aquatic systems

Pesticides are applied to the rice fields in the Sacramento Valley to prevent the growth of plants, algae and insects that reduce rice yields. Following the pesticide application, field water is released into agricultural drains that in turn discharge into the Sacramento River and delta. Rice irrigation is the largest single use of irrigation water in the Sacramento Valley, and because the irrigation water (or rice return) flows are the primary source of drain effluent during the spring and summer (up to 33% of the total flow), these discharges can significantly affect drain water quality and resident aquatic organisms. Acute and chronic toxicity to freshwater organisms (Ceriodaphnia dubia) was observed in the drain water during the period that coincides with the initial draining of the fields in 1986, 1987 and 1988. In 1988, a toxicity identification evaluation (TIE) was conducted using Ceriodaphnia dubia in an effort to identify the cause of toxicity. Both methyl parathion and carbofuran were identified as possible toxicants. Mixture tests and chronic toxicity tests indicated that the concentrations of methyl parathion and carbofuran in the water sample account for the toxicity observed in Ceriodaphnia dubia.

Application of toxicity identification evaluation procedures to the ambient waters of the colusa basin drain, California

A toxicity identification evaluation (TIE) conducted on a municipal wastewater discharge from the southeast United States was part of a research project aimed at developing U.S. Environmental Protection Agency (EPA) TIE methods for acutely toxic effluents. The effluent consistently exhibited acute toxicity to Ceriodaphnia dubia but not to fathead minnows (Pimephales promelas). Toxicity characterization procedures revealed that the primary toxicant was a nonpolar organic. Toxicity was recovered through C18 solid-phase extraction and concentration steps. Gas chromatography–mass spectroscopy of these concentrates revealed the presence of diazinon (O, O-diethyl O-[6-methyl-2-(1-methylethyl)-4-pyrimidinyl] phosphorothioate). Diazinon concentrations in whole effluent, determined by GC analyses, correlated well with the toxicity measurements of each sample. Relative species sensitivity also implicated diazinon as the primary toxicant. This study illustrates the successful application of EPA TIE methodologies for identifying a nonpolar organic toxicant in a complex effluent. The significance of detecting diazinon at acutely toxic concentrations in municipal wastewater may indicate a more widespread problem in this region of the United States. This toxicity problem may be attributed to the chemical characteristics of diazinon and its applications.

An example of the identification of diazinon as a primary toxicant in an effluent

The Fourier transform infrared (FTIR) spectra combined with one-dimensional convolutional neural network (1DCNN) based on multi-level feature fusion, that is, MLF-1DCNN, were used to determine the concentration of imidacloprid in water. The FTIR spectra of imidacloprid water solutions with different concentrations (0–0.41 g/L) in 700–4,000 cm –1 were measured and the corresponding dataset was constructed, and the concentrations were predicted by the MLF-1DCNN. The effect of the spectral data preprocessing by multivariate scattering correction (MSC) and standard normal variate (SNV) transformation on improving the concentration prediction accuracy was studied. The result shows that the SNV preprocessing has the better prediction effect. The comparison of our model with partial least squares (PLS), support vector regression (SVR) and multiple linear regression (MLR) shows that our model can effectively predict the imidacloprid concentrations with a higher prediction accuracy than the other comparative models. The results obtained in this study demonstrate the analytical potential of applying this method to rapidly predict imidacloprid concentration in water.

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Concentration prediction of imidacloprid in water through the combination of Fourier transform infrared spectral data and 1DCNN with multilevel feature fusion

This paper mainly experimentally studies the imidacloprid degradation in an atmospheric dielectric barrier discharge (DBD) plasma. The effects of DBD discharge parameters, temperature and initial concentration on the degradation ratio were investigated with the help of high-performance liquid chromatography (HPLC). The analyses of HPLC-MS (mass spectrometry) and the comparison with database proved that after plasma treatment four new degradation products were generated. It shows that plasma treatment can effectively degrade imidacloprid and the degradation effect depends on the initial concentration of imidacloprid as well as discharge voltage and treatment time. Under the proper plasma parameters, the degradation ratio can be up to 98%. The increase in temperature caused by plasma discharge only affected the degradation ratio by a few percent, which is negligible compared to that by plasma itself. These results show that low temperature plasma has the potential to be an effective imidacloprid degradation method.

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Eric D. Robert

Papers

Application of toxicity identification evaluation procedures to the ambient waters of the colusa basin drain, California

An example of the identification of diazinon as a primary toxicant in an effluent

Concentration prediction of imidacloprid in water through the combination of Fourier transform infrared spectral data and 1DCNN with multilevel feature fusion

Degradation of Imidacloprid in Water by a DBD Plasma