Using Field Studies and Mathematical Modelling to Better Understand and Predict Pesticide Vapour Drift
|dc.contributor.advisor||Hageman, Kimberly J|
|dc.contributor.advisor||Hewitt, Andrew J|
|dc.contributor.author||Geoghegan, Trudyanne Sophia|
|dc.identifier.citation||Geoghegan, T. S. (2014). Using Field Studies and Mathematical Modelling to Better Understand and Predict Pesticide Vapour Drift (Thesis, Doctor of Philosophy). University of Otago. Retrieved from http://hdl.handle.net/10523/4742||en|
|dc.description.abstract||Pesticide vapour drift is increasingly being recognised as an environmental and human health issue. Vapour drift occurs when pesticides volatilise from soil or plant surfaces, onto which they were sprayed, and are transported off-site by the wind. This work uses experimental and modelling approaches to better understand pesticide volatilisation and vapour drift, and to determine the subsequent risk that volatilised pesticides pose to foraging honeybees in downwind non-target fields. Vapour drift is often measured with high-volume air samplers (HVS), but these are expensive to purchase and require network electricity, which can limit the number that are used in a study and the locations where they can be sited. This work tested a new type of wind-driven passive sampler, the flow-through sampler (FTS), in a near-field vapour drift study with short sampling periods to determine if FTS could be used as alternative to HVS. FTS and HVS were used to measure pyrimethanil (a fungicide) in the air in a vineyard for 48 hours after spraying. Pyrimethanil was detected with both types of sampler, therefore the FTS was considered suitable for use in vapour drift studies. The concentrations of pyrimethanil measured were between 0.35 µg m-3 and 2.38 µg m-3, which is well below the occupational exposure limit for this pesticide (5.3 mg m-3). The FTS required low density polyurethane foam (PUF) sampling media which was not available from scientific suppliers. The PUF used in this study contained a black dye that was co-extracted with the pesticides when standard solvent extraction methods were used, and which severely inhibited the detection of the pesticides with gas-chromatography mass-selective detection (GC-MS). To resolve this problem, a new analytical method was developed that coupled pressurised liquid extraction (PLE) with solid phase microextraction (SPME) to selectively extract pyrimethanil from the FTS-PUF and analyse it using GC-MS. Pyrimethanil was extracted from FTS-PUF using PLE, the extract volume was reduced to 400 µl and added to 10 000 µl of distilled water before being extracted with a 50/30-µm divinylbenzene/carboxen/polydimethylsiloxane SPME fibre at 60±1 °C for 60 minutes. The full extraction method gave 80% recovery of pyrimethanil from FTS-PUF and a method detection limit of 27 pg m-3. Modelling pesticide emissions to air is important for understanding pesticide vapour drift and its potential effects on non-target environments. Several environmental fate models have been developed for pesticides but few use plant or species-specific descriptors to describe volatilisation from crops. As a chemical’s environmental fate is a function of its physical-chemical properties and the nature of the environmental media in which it resides, both factors should be considered when estimating pesticide volatilisation. A new planted-field pesticide volatilisation model was developed, based on mass-balance equations and Fick’s Law of diffusion. The model uses several parameters to describe the size and shape of the plants in the field, and the plant-air partition coefficient to describe pesticide-plant surface interactions, thus allowing the model to accommodate variation in the species and growth stage of the plants. The model was used to investigate the difference in volatilisation between a planted- and a bare-field, and the effect of plant growth stage and species on the volatilisation by calculating the cumulative percent volatilisation in 24 hours (CPV24h) of 224 pesticides, of which 53% are currently registered for use in New Zealand. The analysis suggested that no rule of thumb should be applied to whether pesticides volatilise more from planted- or bare-fields. It also showed that CPV24h varied with the growth stage of the plants, and for most pesticides the highest CPV24h occurred with young plants and the least with mature plants, although hydrophilic pesticides showed the opposite trend. Lastly, estimates of interspecies showed that it was proportional to the octanol-air partition coefficient (Koctanol-air) of the pesticide and was most important for pesticides with a log Koctanol-air between 7.5 and 11 (at 25°C). It is important to put measured and modelled values into context because large amounts of pesticide vapour drift will not necessarily result in an adverse environmental effect. Risk assessment methods were therefore used to determine if volatilised pesticides could have an effect on foraging honeybees in downwind areas. The pesticide volatilisation model was extended to calculate the concentration of pesticides in the air and plants at different distances downwind of a sprayed field. These values were then used to calculate acute (24-hour) honeybee exposure via the oral, contact and respiratory exposure routes. A new approach was proposed for estimating respiratory exposure for honeybees. Oral exposure was the most important exposure route for most pesticides but respiratory exposure was important for pesticides that do not sorb well to plants from the air. Risk quotients were calculated for 224 pesticides and eight sets of environmental conditions. Risk varied with the distance from the sprayed field, temperature, wind speed and the presence of vegetation between the sprayed and non-target fields; however, the effect of vegetation was minor for the spatial scale used. These analyses showed that in some cases volatilised pesticides could affect foraging honeybees in non-target areas downwind of a sprayed field, and therefore vapour drift is an important exposure mechanism which should be considered as part of future risk assessments for bees.|
|dc.publisher||University of Otago|
|dc.rights||All items in OUR Archive are provided for private study and research purposes and are protected by copyright with all rights reserved unless otherwise indicated.|
|dc.subject||Pesticide Vapour Drift|
|dc.subject||cummulative percent volatilisation|
|dc.title||Using Field Studies and Mathematical Modelling to Better Understand and Predict Pesticide Vapour Drift|
|thesis.degree.name||Doctor of Philosophy|
|thesis.degree.grantor||University of Otago|
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