A protocol to select high quality datasets of ecotoxicity values for pesticides

The key to any QSAR model is the underlying dataset. In order to construct a reliable dataset to develop a QSAR model for pesticide toxicity, we have derived a protocol to critically evaluate the quality of the underlying data. In developing an appropriate protocol that would enable data to be selected in constructing a QSAR, we concentrated on one toxicity end point, the 96 h LC50 from the acute rainbow trout study. This end point is key in pesticide regulation carried out under 91/414/EEC. The dataset used for this exercise was from the US EPA-OPP database.     

The role of toxicology in the evaluation of new agrochemicals

Abstract

The use of agrochemicals like crop protecting agents, veterinary disinfectants, and wood preservatives may result in (un)intentional exposure of the environment, animals and man. This paper deals with current testing strategies to assess the potential health risks for humans exposed to these chemicals during production or application or via consumption of foods containing pesticide residues.

Principles and procedures for safety assessment of pesticide residues in food as developed by WHO/FAO are described. Different types of toxicity studies in mammalian test animal species are discussed and a strategy is outlined in order to characterize the toxicity profile of a compound and the relationship between applied doses and adverse effects. Safety testing of agrochemicals should be carried out in relation to its intended use, and in particular attention will be paid to toxicity testing of residues of pesticides in food. Extrapolation of results from animal studies to humans and the use of safety factors is discussed.

Besides the use of animal protocol studies for safety testing of agrochemicals, the potential use of in‐vitro models derived from organs and tissues of animals is discussed. Data on the in‐vitro metabolism of thiabendazole, aldicarb and alachlor are discussed in order to demonstrate that such data may complement or partly substitute whole animal experimentation.

Principles and procedures for safety testing of residues of agrochemicals in food as applied during the last three decades, constitute a ‘safety‐first’ approach, providing sufficient safety margins for the consumer of foods which may contain low levels of residues of agrochemicals.     

Quantitative structure-activity relationship (QSAR) models for polycyclic aromatic hydrocarbons (PAHs) dissipation in rhizosphere based on molecular structure and effect size

Rhizoremediation is a significant form of bioremediation for polycyclic aromatic hydrocarbons (PAHs). This study examined the role of molecular structure in determining the rhizosphere effect on PAHs dissipation. Effect size in meta-analysis was employed as activity dataset for building quantitative structure-activity relationship (QSAR) models and accumulative effect sizes of 16 PAHs were used for validation of these models. Based on the genetic algorithm combined with partial least square regression, models for comprehensive dataset, Poaceae dataset, and Fabaceae dataset were built. The results showed that information indices, calculated as information content of molecules based on the calculation of equivalence classes from the molecular graph, were the most important molecular structural indices for QSAR models of rhizosphere effect on PAHs dissipation. The QSAR model, based on the molecular structure indices and effect size, has potential to be used in studying and predicting the rhizosphere effect of PAHs dissipation.     

QSAR trout toxicity models on aromatic pesticides

The pesticides originally designed to kill target organisms are dangerous for many other wild species. Since they are applied directly to the environment, they can easily reach the water basins and the topsoil. A dataset of 125 aromatic pesticides with well-expressed aquatic toxicity towards trout was subjected to quantitative structure activity relationships (QSAR) analysis aimed to establish the relationship between their molecular structure and biological activity. A literature data for LC₅₀ concentration killing 50% of fish was used. In addition to the standard 2D-QSAR analysis, a comparative molecular field analysis (CoMFA) analysis considering the electrostatic and steric properties of the molecules was also performed. The CoMFA analysis helped the recognition of the steric interactions as playing an important role for aquatic toxicity. In addition, the transport properties and the stability of the compounds studied were also identified as important for their biological activity.     

Removal of pesticides from rinsate by adsorption using agricultural residuals as medium

Abstract

The feasibility of using agricultural residual with highly organic matter content ‐ spent mushroom compost (SMC) as adsorption medium for removal of pesticides including carbaryl, carbofuran, and aldicarb with a concentration range of 0–30 mg/L from rinsate was investigated. Bottle‐point method was used to determine adsorption isotherms for single‐pesticide and multi‐pesticides. It was found that SMC might potentially be used for on‐farm treatment of pesticide rinsate. The adsorption capacity of SMC was increased compared to most soils, possibly related to the increased organic matter content. The rapid equilibrium of pesticide solution and SMC was consistent with a physical type of adsorption mechanism. The adsorption of carbamate pesticides on SMC was found to exhibit nonlinear “favorable”; adsorption behavior that could be characterized well by the Freundlich isotherm model. In addition, the multi‐pesticide adsorption tests displayed the characteristics of competitive behavior. The competitive ability of these three pesticides in multi‐components adsorption was in the order carbaryl > carbofuran > aldicarb, which was consistent with the adsorbability of pesticides.     

Pesticide concentration variations correlated with well bore volume removal in shallow coastal plain ground water

Abstract

The effects of well bore volume removal (V_n) on the concentration of alachlor [2‐chloro‐N‐(2,6‐diethylphenyl)‐N‐(methoxy methyl) acetamide] and prometon (6‐methoxy‐N,N'‐bis(1‐methylethyl)‐1,3,5‐triazine‐2,4‐diamine] in ground water obtained from three monitoring wells installed in the Coastal Plain region of North Carolina was investigated. Seasonal effects were also investigated by conducting the exercise in February and May. In the majority of cases, the lowest pesticide concentrations occurred in the initial well bore volume (V₁ = stagnant water). Removal of additional well bore volumes (V₂ to V₁₀) from two of the wells resulted in pesticide concentrations that did not vary substantially. This indicates that a representative aquifer sample was obtainable, in most cases from these wells, after removal of the initial well bore volume. In contrast, a third well required the purging of two well bore volumes before a stable alachlor concentration was achieved. Seasonal effects of bore volume removal vs. pesticide concentrations for the three wells were not significant (P > 0.05). It was concluded that a protocol for improved accuracy in pesticide analyses of ground water can be obtained by establishing a pesticide concentration‐purging (well bore volume) relationship for each well.     

Forecasting Air Pollution Potential: A Synoptic Climatological Approach

ABSTRACT

This paper describes the development and application of an air pollution potential (APP) forecast model based on a synoptic climatological approach in a heavily industrialized area in Durban, South Africa. The aim of the forecasting procedure, based on a system of orange, red, and all-clear alerts, was to give industry advance warning of periods of poor atmospheric dispersion so that it could take action to reduce emissions. The key meteorological parameter in accurately identifying the commencement of an APP episode was found to be negative surface pressure tendency. Wind direction was the most useful parameter in estimating the end point of an APP episode. The model was very successful in identifying periods of elevated SO₂, but there is a need for further refinement in forecasting the end point of an episode.     

Estimating pesticide runoff in small streams

Surface runoff is one of the most important pathways for pesticides to enter surface waters. Mathematical models are employed to characterize its spatio-temporal variability within landscapes, but they must be simple owing to the limited availability and low resolution of data at this scale. This study aimed to validate a simplified spatially-explicit model that is developed for the regional scale to calculate the runoff potential (RP). The RP is a generic indicator of the magnitude of pesticide inputs into streams via runoff. The underlying runoff model considers key environmental factors affecting runoff (precipitation, topography, land use, and soil characteristics), but predicts losses of a generic substance instead of any one pesticide. We predicted and evaluated RP for 20 small streams. RP input data were extracted from governmental databases. Pesticide measurements from a triennial study were used for validation. Measured pesticide concentrations were standardized by the applied mass per catchment and the water solubility of the relevant compounds. The maximum standardized concentration per site and year (runoff loss, R_Loss) provided a generalized measure of observed pesticide inputs into the streams. Average RP explained 75% (p < 0.001) of the variance in R_Loss. Our results imply that the generic indicator can give an adequate estimate of runoff inputs into small streams, wherever data of similar resolution are available. Therefore, we suggest RP for a first quick and cost-effective location of potential runoff hot spots at the landscape level.     

Mixture Toxicity of the Antifouling Compound Irgarol to the Marine Phytoplankton Species Dunaliella tertiolecta

This study examined the toxicity of irgarol, individually and in binary mixtures with three other pesticides (the fungicide chlorothalonil, and the herbicides atrazine and 2,4-D), to the marine phytoplankton species Dunaliella tertiolecta. Standard 96-h static algal bioassays were used to determine pesticide effects on population growth rate. Irgarol significantly inhibited D. tertiolecta growth rate at concentrations ≥ 0.27 μ g/L. Irgarol was significantly more toxic to D. tertiolecta than the other pesticides tested (irgarol 96 h EC₅₀ = 0.7 μ g/L; chlorothalonil 96 h EC₅₀ = 64 μ g/L; atrazine 96 h EC₅₀ = 69 μ g/L; 2,4-D 96 h EC₅₀ = 45,000 μ g/L). Irgarol in mixture with chlorothalonil exhibited synergistic toxicity to D. tertiolecta, with the mixture being approximately 1.5 times more toxic than the individual compounds. Irgarol and atrazine, both triazine herbicides, were additive in mixture. The toxicity threshold of 2,4-D was much greater than typical environmental levels and would not be expected to influence irgarol toxicity. Based on these interactions, overlap of certain pesticide applications in the coastal zone may increase the toxicological risk to resident phytoplankton populations.     

A novel approach to predict aquatic toxicity from molecular structure

The main aim of the study was to develop quantitative structure-activity relationship (QSAR) models for the prediction of aquatic toxicity using atom-based non-stochastic and stochastic linear indices. The used dataset consist of 392 benzene derivatives, separated into training and test sets, for which toxicity data to the ciliate Tetrahymena pyriformis were available. Using multiple linear regression, two statistically significant QSAR models were obtained with non-stochastic (R2=0.791 and s=0.344) and stochastic (R2=0.799 and s=0.343) linear indices. A leave-one-out (LOO) cross-validation procedure was carried out achieving values of q2=0.781 (scv=0.348) and q2=0.786 (scv=0.350), respectively. In addition, a validation through an external test set was performed, which yields significant values of Rpred2 of 0.762 and 0.797. A brief study of the influence of the statistical outliers in QSAR's model development was also carried out. Finally, our method was compared with other approaches implemented in the Dragon software achieving better results. The non-stochastic and stochastic linear indices appear to provide an interesting alternative to costly and time-consuming experiments for determining toxicity.     

Residues of endosulfan in cotton growing area of Vehari,Pakistan: an assessment of knowledge and awareness of pesticide use and health risks

This study is based on self-reported information collected from selected farmers of Vehari District, Punjab, Pakistan, to determine their technical knowledge and awareness about pesticide use and associated environmental and health risks. Moreover, soil contamination by routinely used persistent organochlorine pesticide, endosulfan, was also evaluated. Survey data revealed very low literacy rate (on an average 9th grade education) and technical knowledge (almost missing) of the farmers in Vehari District. The farmers are unable to fully read and understand the instructions about the use of pesticide marked on the containers. They are not fully aware of pesticide persistence and toxicity (73%), unable to identify cotton pests and diseases (86%), and do not know which crop to grow in cotton adjacent fields (100%). Data also revealed that the farmers (100%) do not follow safety measure during pesticide application and are unaware of pesticide toxicity symptoms in human as well as the basic first-aid practices (89%).

Poor literacy rate and lack of technical knowledge of farmers in Vehari regarding pesticide use and handling are posing serious environmental and health risks among the local inhabitants, particularly among farmers. Soil analysis results showed that concentration of α- and β-endosulfan ranged from 0–14 to 0–14.64 μg/mg, respectively. Principal component analysis showed that soil organic matter is the key soil parameter controlling the occurrence and fate of endosulfan under sandy loam soil conditions of Vehari District. There is a serious need of improving technical and environmental knowledge of farmer about pesticide risks on human health in the studied area, in particular, and the entire country in general. Findings are of great use for policymaking in Pakistan to minimize pesticide risks in Pakistan.

     

Combined toxic impacts of thiamethoxam and four pesticides on the rare minnow (Gobiocypris rarus)

To examine pesticide mixture toxicity to aqueous organisms, we assessed the single and combined toxicities of thiamethoxam and other four pesticides (chlorpyrifos, beta-cypermethrin, tetraconazole, and azoxystrobin) to the rare minnow (Gobiocypris rarus). Data from 96-h semi-static toxicity assays of various developmental phases (embryonic, larval, juvenile, and adult phases) showed that beta-cypermethrin, chlorpyrifos, and azoxystrobin had the highest toxicities to G. rarus, and their LC₅₀ values ranged from 0.0031 to 0.86 mg a.i. L^?1, from 0.016 to 6.38 mg a.i. L^?1, and from 0.39 to 1.08 mg a.i. L^?1, respectively. Tetraconazole displayed a comparatively high toxicity, and its LC₅₀ values ranged from 3.48 to 16.73 mg a.i. L^?1. By contrast, thiamethoxam exhibited the lowest toxic effect with LC₅₀ values ranging from 37.85 to 351.9 mg a.i. L^?1. Rare minnow larvae were more sensitive than embryos to all the pesticides tested. Our data showed that a pesticide mixture of thiamethoxam–tetraconazole elicited synergetic toxicity to G. rarus. Moreover, pesticide mixtures containing beta-cypermethrin in combination with chlorpyrifos or tetraconazole also had synergetic toxicities to fish. The majority of pesticides are presumed to have additive toxicity, while our data emphasized that the concurrent existence of some chemicals in the aqueous circumstance could cause synergetic toxic effect, leading to severe loss to the aqueous environments in comparison with their single toxicities. Thence, the synergetic impacts of chemical mixtures should be considered when assessing the ecological risk of chemicals.

     

PeLM: Modeling of Pesticide-Losses Through Runoff and Sediment Transport

Abstract

A GIS-aided pesticide loss model (PeLM) was developed to simulate pesticide losses through surface runoff and sediment transport in watershed systems. The PeLM could tackle the movement of eroded soil along with surface runoff as well as the pesticide losses in adsorbed and dissolved phases. The contributions of different soil types in the sediment were also examined. The model was applied to the Kintore Creek Watershed of southern Ontario, Canada. The simulation results were verified through observed data, indicating a correlation level of 0.89–0.98. The results also showed that clay particles usually held the largest share of contributions to pesticide losses through soil erosion. This study is significant in the efforts for modeling nonpoint source pollution in watershed systems. It provides useful information and support for the related decisions of watershed management.     

Safety testing of pesticides and methods of evaluating human exposure in the field

Abstract

The importance of field surveys to provide data on acute pesticide hazards is discussed. The types of questions which small field surveys of pesticide exposure should answer are presented. In addition to protective clothing, the value of distance, time, and personal hygiene in reducing exposure are considered. Finally, the importance of an adequate data base for the development of protocols and guidelines for public protection is discussed.     

Pesticide transport via sub-surface drains in Europe

Transport of pesticides from point of application via sub-surface drains can contribute significantly to contamination of surface waters. Results of 23 field drainage experiments undertaken at sites across Europe were collated and analysed by residual maximum likelihood. Both maximum concentration of pesticide in drainflow (n = 167) and seasonal loss of pesticide to drains (n = 97) were significantly related to strength of pesticide sorption to soil, half-life of the pesticide in soil, the interval between application and first drainflow and the clay content of the soil. The statistical models accounted for 71% of the variability in both maximum concentration and seasonal load. Next, the dataset was used to evaluate the current methodology for assessment of aquatic exposure used in pesticide registration in Europe. Simulations for seven compounds with contrasting properties showed a good correspondence with field measurements. Finally, the review examines management approaches to reduce pesticide transport via sub-surface drains. Despite a large amount of work in this area, there are few dependable mitigation options other than to change application rate or timing or to restrict use of a compound in the most vulnerable situations.     

Inhibitory Effects on Esterase Enzymes Buche and Ache in Rainbow Trout (Oncorhyncus mykiss) Produced by the Slow Release Insecticide Chitosan Diethyl Phosphate

The study on the toxicity of chitosan diethyl phosphate (ChDP), a controlled release insecticide, on the activities of butyrylcholinesterase (BuChE) and acetylcholinesterase (AChE) in rainbow trout exposed to this pesticide was carried out. It was found that ChDP reduced BuChE activity in O. mykiss by a factor of eight at 6 days, with high fluctuation to the end of the exposition time at 12 days. The in vitro analysis of brain AChE treated with ChDP and Phenamiphos showed that it was competitively inhibited by both organophosphates. The values obtained for K_m and V_max for the AChE-ChDP (K_m: 21.23 μ M; V_max: 43.10 μ mol/min/g) and AChE-Phenamiphos (K_m: 38.62 μ M; V_max: 38.91 μ mol/min/g) systems were relatively low compared to values of the AChE (control) system (K_m: 62.99 μ M; V_max: 63.29 μ mol/min/g). Results reported in this study confirmed that chitosan diethyl phosphate performs similarly to organophosphate pesticides, producing inhibition in cholinesterases in rainbow trout.     

Prediction of mixture toxicity with its total hydrophobicity

Based on the C18 Empore disk/water partition coefficient of a mixture, quantitative structure-activity relationships (QSARs) are presented, which are used to predict the toxicity of mixed halogenated benzenes to P. phosphoreum. The predicted toxicity of 10 other related mixtures based on the QSAR model, agree well with the observed data with r2 = 0.973, SE = 0.113 and F = 287.785 at a level of significance P < 0.0001. The joint effect of these chemicals is simple similar action and the toxicity of the mixtures can be predicted from total hydrophobicity and is independent of hydrophobicity of the components or the ratio of the individual chemicals.