Biomedical subjects

Colin D Brown

Publications and source records attributed to Colin D Brown.

16 recordsLinked to original sources

PubMed2006

Pesticide sorption and desorption by lignin described by an intraparticle diffusion model.

Lignin was used as a model compound for soil organic matter to gain insight into the mechanisms that control the kinetics of pesticide sorption and desorption. Hydrolytic lignin was immobilized in a matrix of alginate gel, and sorption-desorption experiments were undertaken with isoproturon. Sorption increased with time and was close to equilibrium after 14 days. Desorption was measured after sorption for different time intervals and for a number of successive desorption steps of different lengths. The results showed strong differences between the sorption and desorption isotherms. The ratio of sorbed to dissolved pesticide approached and even exceeded the equilibrium ratio, depending on the number of desorption steps and the length of each equilibration period. A numerical diffusion model was developed to describe radial diffusion into the lignin particles in combination with Freundlich sorption inside the particles. Key model parameters were adjusted to fit the sorption data, and the same parameters were then used to predict stepwise desorption. Desorption was well described by the model, which suggests that sorption and desorption were driven by the same mechanism and occurred at the same rate. The observed difference between the sorption and desorption isotherms could be fully explained by the nonattainment of equilibrium due to slow diffusion into and out of the lignin particles.

Adsorption↗

PubMed2006

Impact of correlation between pesticide parameters on estimates of environmental exposure.

Monte Carlo techniques are increasingly used in pesticide exposure modelling to evaluate the uncertainty in predictions arising from uncertainty in input parameters and to estimate the confidence that should be assigned to modelling results. The approach typically involves running a deterministic model repeatedly for a large number of input values sampled from statistical distributions. A key decision in setting up a probabilistic analysis is whether there is correlation between any of the inputs to the analysis. Pesticide properties are often the most sensitive in exposure assessment. Analysis of the literature demonstrated that there are examples of both positive and negative correlation between the sorption and degradation behaviour of a pesticide, but that general trends are not apparent at present. The inclusion of even weak correlation between sorption and degradation was found to greatly influence a probabilistic analysis of leaching through soil. Correlation will reduce the predicted extent of leaching for pesticides, and it is recommended to set the correlation to zero unless the experimental data support an alternative assumption (i.e. where the correlation is statistically significant (P <or= 0.05) and experimental artefacts can be excluded).

Environmental Exposure↗

PubMed2006

User subjectivity in Monte Carlo modeling of pesticide exposure.

Monte Carlo techniques are increasingly used in pesticide exposure modeling to evaluate the uncertainty in predictions arising from uncertainty in input parameters and to estimate the confidence that should be assigned to the modeling results. The approach typically involves running a deterministic model repeatedly for a large number of input values sampled from statistical distributions. In the present study, six modelers made choices regarding the type and parameterization of distributions assigned to degradation and sorption data for an example pesticide, the correlation between the parameters, the tool and method used for sampling, and the number of samples generated. A leaching assessment was carried out using a single model and scenario and all data for sorption and degradation generated by the six modelers. The distributions of sampled parameters differed between the modelers, and the agreement with the measured data was variable. Large differences were found between the upper percentiles of simulated concentrations in leachate. The probability of exceeding 0.1 microg/L ranged from 0 to 35.7%. The present study demonstrated that subjective choices made in Monte Carlo modeling introduce variability into probabilistic modeling and that the results need to be interpreted with care.

Monte Carlo Method↗

PubMed2005

Pesticide sorption and diffusion in natural clay loam aggregates.

Pesticide sorption in soils is controlled by time-dependent processes such as diffusion into soil aggregates and microscopic sorbent particles. This study examines the rate-controlling step for time-dependent sorption in clay loam aggregates. Aggregates (5 mm) were stabilized with alginate, and adsorption of azoxystrobin, chlorotoluron, and cyanazine was measured in batch systems equilibrated for periods between 1 h and 7 days. Stepwise desorption was measured at 1- or 3-day intervals following 1 or 7 days of adsorption. Time-dependent adsorption was also measured on dispersed soil. Results were interpreted using process-based modeling. Adsorption on dispersed soil was described by intraparticle sorption and diffusion. Adsorption in the aggregates was much less than in suspension, suggesting that part of the sorption capacity of the dispersed soil was not available within the aggregates (approximately 50%). Adsorption and desorption were reversible and could be described by pore diffusion into the aggregate with effective diffusion coefficients between 0.5 x 10(-10) and 1 x 10(-10) m2 s(-1), a factor 3-6 slower than estimated theoretically. Intraparticle diffusion did not seem to contribute to sorption in the aggregates at this time scale. Apparent hysteresis was explained by nonattainment of equilibrium during the adsorption and desorption steps.

Adsorption↗

PubMed2005

Evaluation of simplifying assumptions on pesticide degradation in soil.

There is evidence that degradation of pesticides in simple laboratory systems may differ from that in the field, but it is not clear which of the simplifications inherent in laboratory studies present serious shortcomings. Laboratory experiments evaluated several simplifying assumptions for a clay loam soil and contrasting pesticides. Degradation of cyanazine [2-(4-chloro-6-ethylamino-1,3,5-triazin-2-ylamino)-2-methylpropiononitrile] and bentazone [3-isopropyl-1H-2,1,3-benzothiadiazin-4(3H)-one 2,2-dioxide] at fluctuating temperature and moisture was predicted reasonably well based on parameters derived from degradation under constant conditions. There was a tendency for slower degradation of cyanazine and bentazone in soil aggregates of 3 to 5 mm in diameter (DT50 at 15 degrees C and 40% maximum water holding capacity of 25.1 and 58.2 d, where DT50 is the time for 50% decline of the initial pesticide concentration) than in soil sieved to <3 mm (DT50 of 19.1 and 37.6 d), but the differences were not significant for most datasets. Degradation of cyanazine, isoproturon [3-(4-isopropylphenyl)-1,1-dimethylurea], and chlorotoluron [3-(3-chloro-p-tolyl)-1,1-dimethylurea] was measured in soil amended with different amounts of lignin. The effect of lignin on degradation was small despite considerable differences in sorption. The DT50 values of cyanazine, isoproturon, and chlorotoluron were 16.2, 18.6, and 33.0 d, respectively, in soil without lignin and 19.0, 23.4, and 34.6 d, respectively, in soil amended with 2% lignin. Degradation of bentazone and cyanazine in repacked soil columns was similar under static and flow conditions with 50.1 and 47.2% of applied bentazone and 74.7 and 73.6% of applied cyanazine, respectively, degraded within 20 d of application. Thus, the assumptions underpinning laboratory to field extrapolation tested here were considered to hold for our experimental system. Additional work is required before general conclusions can be drawn.

Aluminum Silicates↗

PubMed2004

Exposure to sulfosulfuron in agricultural drainage ditches: field monitoring and scenario-based modelling.

Field monitoring and scenario-based modelling were used to assess exposure of small ditches in the UK to the herbicide sulfosulfuron following transport via field drains. A site in central England on a high pH, clay soil was treated with sulfosulfuron, and concentrations were monitored in the single drain outfall and in the receiving ditch 1 km downstream. Drainflow in the nine months following application totalled 283 mm. Pesticide lost in the first 12.5 mm of flow was 99% of the total loading to drains (0.5% of applied). Significant dilution was observed in the receiving ditch and quantifiable residues were only detected in one sample (0.06 microg litre(-1)). The MACRO model was evaluated against the field data with minimal calibration. The parameterisation over-estimated the importance of macropore flow at the site. As a consequence, the maximum concentration in drainflow (2.3 microg litre(-1)) and the total loading to drains (0.76 g) were over-estimated by factors of 2.4 and 5, respectively. MACRO was then used to simulate long-term fate of the herbicide for each of 20 environmental scenarios. Resulting estimates for concentrations of sulfosulfuron in a receiving ditch were weighted according to the prevalence of each scenario to produce a probability distribution of daily exposure.

Agriculture↗

PubMed2004

Inverse modelling for estimating sorption and degradation parameters for pesticides.

The leaching model PESTRAS was used to estimate sorption and degradation values for bentazone from three lysimeter datasets using the inverse modelling package PEST. Investigations were undertaken to assess the influence on calibration results of (1) values attributed to uncertain parameters not included in the calibration, and (2) starting values supplied to the inverse modelling package. Automatic calibrations with different realistic values for the Freundlich exponent n(f) yielded different combinations of K(om) and DT50. Similarly, the supply of different starting values for K(om) and DT50 revealed that different combinations of these two parameters equally calibrated PESTRAS for two of the three lysimeters. Examination of the error surface, ie the forward running of the model for different combinations of K(om) and DT50 values, and the calculation of the goodness-of-fit to the experimental data, was found useful for identifying those instances where non-uniqueness in the calibration is likely to occur. Although the derivation of sorption and degradation values through inverse modelling is expected to offer significant benefits over laboratory determinations, care should be exercised when examining values derived through this approach. Research is needed to identify data requirements for robust estimation of sorption and degradation parameters through calibration of pesticide fate models against leaching data.

Adsorption↗

PubMed2004

Influence of kinetic sorption and diffusion on pesticide movement through aggregated soils.

Laboratory studies were carried out to investigate solute leaching at different times from application in relation to temperature and initial soil moisture. Aggregates of a heavy clay soil were treated with a non-interactive solute (bromide) and the herbicides chlorotoluron, isoproturon and triasulfuron. The soil was incubated at 90% field capacity and either 5 or 15 degrees C. The influence of application to initially dry and initially wet aggregates on the behaviour of isoproturon was also investigated. At intervals, samples were either leached in small columns, centrifuged to characterise the fraction of chemical available in pore water under natural moisture conditions or extracted with organic solvents to assess total residues in soil. Bromide concentrations in leachate and in pore water extracted by centrifugation were constant with time. In contrast, availability for leaching and concentration in pore water of the herbicides decreased with increasing time from application in soil incubated at 15 degrees C. The effect of residence time was much smaller at 5 than at 15 degrees C. At the higher temperature, pesticide concentrations in leachate and pore water declined faster than would be expected from degradation alone, probably due to slow diffusion of the pesticides into soil aggregates where they are less available for leaching and/or slow sorption-desorption. The faster decline in availability for leaching at 15 than at 5 degrees C was attributed to faster degradation of the readily available fraction. There was no significant influence of initial soil moisture on either the leaching behaviour of isoproturon or its availability in soil water.

Adsorption↗

PubMed2004

Determination of time-dependent partition coefficients for several pesticides using diffusion theory.

Diffusion-retarded partitioning of pesticides with aggregated soils results in a time-dependent partition coefficient (Kd') which is different at equilibrium from the partition coefficient derived from conventional 24-h batch studies (Kd) measured on dispersed soil. An experiment was undertaken to determine the importance of Kd' for the prediction of pesticide concentrations in solutions bathing artificial soil aggregates and to determine whether diffusion theory could accurately predict the concentrations. Two clay soils were mixed with polyacrylamide to create artificial aggregates of 0.8, 1.4 and 1.7 cm diameter when dry. After saturation, the aggregates were immersed in solutions containing isoproturon or a mixture of isoproturon, chlorotoluron and triasulfuron. The decline with time of the pesticide concentrations in the bathing solution was monitored and the results were compared with predictions from a diffusion-based model. The effective diffusion coefficients of the compounds were obtained by either fitting the non-linear diffusion model to the data (D(ef)) or by independent calculations based on the properties of the compounds and of the aggregates (D(ec)). The diffusion model was able to predict the temporal variation in pesticide concentrations in the bathing solution reasonably well whether D(ef) or D(ec) values were used. However, equilibrium concentrations in solution were sometimes overestimated due to increased sorption with time at the particle scale. Overall, the ratio between D(ef) and D(ec) ranged from 0.23 to 0.95 which was a reasonable variation when compared to the range of aggregate sizes used in the experiments and of the Kd values of the compounds.

Acrylic Resins↗

PubMed2003

Sources of uncertainty in pesticide fate modelling.

There is worldwide interest in the application of probabilistic approaches to pesticide fate models to account for uncertainty in exposure assessments. The first steps in conducting a probabilistic analysis of any system are: (i) to identify where the uncertainties come from; and (ii) to pinpoint those uncertainties that are likely to affect most of the predictions made. This article aims at addressing those two points within the context of exposure assessment for pesticides through a review of the different sources of uncertainty in pesticide fate modelling. The extensive listing of sources of uncertainty clearly demonstrates that pesticide fate modelling is laced with uncertainty. More importantly, the review suggests that the probabilistic approaches, which are typically being deployed to account for uncertainty in the pesticide fate modelling, such as Monte Carlo modelling, ignore a number of key sources of uncertainty, which are likely to have a significant effect on the prediction of environmental concentrations for pesticides (e.g. model error, modeller subjectivity). Future research should concentrate on quantifying the impact these uncertainties have on exposure assessments and on developing procedures that enable their integration within probabilistic assessments.

Animals↗

PubMed2003

Sensitivity analyses for four pesticide leaching models.

Sensitivity analyses using a one-at-a-time approach were carried out for leaching models which have been widely used for pesticide registration in Europe (PELMO, PRZM, PESTLA and MACRO). Four scenarios were considered for simulation of the leaching of two theoretical pesticides in a sandy loam and a clay loam soil, each with a broad distribution across Europe. Input parameters were varied within bounds reflecting their uncertainty and the influence of these variations on model predictions was investigated for accumulated percolation at 1-m depth and pesticide loading in leachate. Predictions for the base-case scenarios differed between chromatographic models and the preferential flow model MACRO for which large but transient pesticide losses were predicted in the clay loam. Volumes of percolated water predicted by the four models were affected by a small number of input parameters and to a small extent only, suggesting that meteorological variables will be the main drivers of water balance predictions. In contrast to percolation, predictions for pesticide loss were found to be sensitive to a large number of input parameters and to a much greater extent. Parameters which had the largest influence on the prediction of pesticide loss were generally those related to chemical sorption (Freundlich exponent nf and distribution coefficient Kf) and degradation (either degradation rates or DT50, QTEN value). Nevertheless, a significant influence of soil properties (field capacity, bulk density or parameters defining the boundary between flow domains in MACRO) was also noted in at least one scenario for all models. Large sensitivities were reported for all models, especially PELMO and PRZM, and sensitivity was greater where only limited leaching was simulated. Uncertainty should be addressed in risk assessment procedures for crop-protection products.

Algorithms↗

PubMed2002

Lysimeter study to investigate the effect of rainfall patterns on leaching of isoproturon.

The influence of five rainfall treatments on water and solute leaching through two contrasting soil types was investigated. Undisturbed lysimeters (diameter 0.25 m, length 0.5 m) from a sandy loam (Wick series) and a moderately structured clay loam (Hodnet series) received autumn applications of the radio-labelled pesticide isoproturon and bromide tracer. Target rainfall plus irrigation from the end of November 1997 to May 1998 ranged from drier to wetter than average (235 to 414 mm); monthly rainfall was varied according to a pre-selected pattern or kept constant (triplicate lysimeters per regime). Leachate was collected at intervals and concentrations of the solutes were determined. Total flow (0.27-0.94 pore volumes) and losses of bromide (3-80% of applied) increased with increasing inputs of water and were larger from the Wick sandy loam than from the Hodnet clay loam soil. Matrix flow appeared to be the main mechanism for transport of isoproturon through the Wick soil whereas there was a greater influence of preferential flow for the Hodnet lysimeters. The total leached load of isoproturon from the Wick lysimeters was 0.02-0.26% of that applied. There was no clear variation in transport processes between the rainfall treatments investigated for this soil and there was an approximately linear relationship (r2 = 0.81) between leached load and total flow. Losses of isoproturon from the Hodnet soil were 0.03-0.39% of applied and there was evidence of enhanced preferential flow in the driest and wettest treatments. Leaching of isoproturon was best described by an exponential relationship between load and total flow (r2 = 0.62). A 45% increase in flow between the two wettest treatments gave a 100% increase in leaching of isoproturon from the Wick soil. For the Hodnet lysimeters, a 35% increase in flow between the same treatments increased herbicide loss by 325%.

Aluminum Silicates↗

PubMed2002

Prediction of pesticide concentrations found in rivers in the UK.

SWATCATCH is a distributed model combined with databases within a GIS as the POPPIE system to predict pesticide concentrations in rivers at the catchment outlet. The model was evaluated against a dataset of pesticide concentrations in rivers of England and Wales. More than 2000 individual analyses in each of the years 1995 and 1997 covered approximately 150 catchment-pesticide combinations drawn from 29 catchments and 16 pesticides, themselves selected to represent a range of characteristics and properties. SWATCATCH was better able to simulate maximum pesticide concentrations at any time during the year than the proportion of samples containing residues of a particular pesticide above the limit of quantification. The model simulated maximum pesticide concentrations in surface waters which were within a factor of 10 of those observed for 66-74% of catchment-pesticide-year combinations. Simulated and observed frequency of detection could not be differentiated using a Chi 2 test for 54-67% of simulations. Time series analysis for seven of the 29 catchment-pesticide combinations indicated that measured and detected series of concentrations generally followed similar patterns. The evaluation supports the intended use of the model in assisting the construction of pesticide monitoring programmes.

Adsorption↗

PubMed2002

Higher-tier laboratory methods for assessing the aquatic toxicity of pesticides.

Registration schemes for plant-protection products require applicants to assess the potential ecological risk of their products using a tiered approach. Standard aquatic ecotoxicity tests are used at lower tiers and clearly defined methodologies are available for assessing the potential environmental risks. Safety factors are incorporated into the assessment process to account for the uncertainties associated with the use of lower-tier single-species ecotoxicity studies. If lower-tier assessments indicate that a substance may pose a risk to the environment, impacts can be assessed using more environmentally realistic conditions through the use of either pond mesocosms, artificial streams or field monitoring studies. Whilst these approaches provide more realistic assessments, the results are difficult to interpret and extrapolation to other systems is problematic. Recently it has been recognised that laboratory approaches that are intermediate between standard aquatic toxicity tests and field/mesocosm studies may provide useful data and help reduce the uncertainties associated with standard single-species tests. However, limited guidance is available on what tests are available and how they can be incorporated into the risk-assessment process. This paper reviews a number of these higher-tier laboratory techniques, including modified exposure studies, species sensitivity studies, population studies and tests with sensitive life stages. Recommendations are provided on how the approaches can be incorporated into the risk-assessment process.

Animals↗

PubMed2002

Calibration of pesticide leaching models: critical review and guidance for reporting.

Calibration of pesticide leaching models may be undertaken to evaluate the ability of models to simulate experimental data, to assist in their parameterisation where values for input parameters are difficult to determine experimentally, to determine values for specific model inputs (e.g. sorption and degradation parameters) and to allow extrapolations to be carried out. Although calibration of leaching models is a critical phase in the assessment of pesticide exposure, lack of guidance means that calibration procedures default to the modeller. This may result in different calibration and extrapolation results for different individuals depending on the procedures used, and thus may influence decisions regarding the placement of crop-protection products on the market. A number of issues are discussed in this paper including data requirements and assessment of data quality, the selection of a model and parameters for performing calibration, the use of automated calibration techniques as opposed to more traditional trial-and-error approaches, difficulties in the comparison of simulated and measured data, differences in calibration procedures, and the assessment of parameter values derived by calibration. Guidelines for the reporting of calibration activities within the scope of pesticide registration are proposed.

Calibration↗

PubMedDate not supplied

Sensitivity and first-step uncertainty analyses for the preferential flow model MACRO.

Sensitivity analyses for the preferential flow model MACRO were carried out using one-at-a-time and Monte Carlo sampling approaches. Four different scenarios were generated by simulating leaching to depth of two hypothetical pesticides in a sandy loam and a more structured clay loam soil. Sensitivity of the model was assessed using the predictions for accumulated water percolated at a 1-m depth and accumulated pesticide losses in percolation. Results for simulated percolation were similar for the two soils. Predictions of water volumes percolated were found to be only marginally affected by changes in input parameters and the most influential parameter was the water content defining the boundary between micropores and macropores in this dual-porosity model. In contrast, predictions of pesticide losses were found to be dependent on the scenarios considered and to be significantly affected by variations in input parameters. In most scenarios, predictions for pesticide losses by MACRO were most influenced by parameters related to sorption and degradation. Under specific circumstances, pesticide losses can be largely affected by changes in hydrological properties of the soil. Since parameters were varied within ranges that approximated their uncertainty, a first-step assessment of uncertainty for the predictions of pesticide losses was possible. Large uncertainties in the predictions were reported, although these are likely to have been overestimated by considering a large number of input parameters in the exercise. It appears desirable that a probabilistic framework accounting for uncertainty is integrated into the estimation of pesticide exposure for regulatory purposes.

Adsorption↗