Abstract
The use of pesticides in the agricultural sector, alongside other technological advances, caused dramatic increases in crop yield but also accompanying increases in environmental concerns. Pesticide volatilisation and subsequent vapour drift is a special concern because many pesticides can travel long distances from the application site and may cause adverse environmental impact, human health effects and also ineffective pest control. With pesticide use perpetually linked to negative environmental and human health issues, it is essential that efforts are made to understand the processes and properties controlling their distribution so that more accurate predictions of their fate and behaviour can be made in the future.
Pesticide fate and transport can be experimentally determined or predicted using a modelling approach. However, a combination approach of experimentally determined volatilisation rates under specified conditions to compare with model predictions can help to understand volatilisation and transport of pesticides better. This thesis work aimed to use experimental and modelling approaches to better understand pesticide volatilisation, vapour drift, and near-field transport of semi-volatile commercial pesticide formulations.
Vapour drift occurs when pesticides volatilise from sprayed fields and are blown off-site by wind, potentially affecting non-target ecosystems. Organophosphate insecticides can travel many kilometres through the atmosphere and due to their toxic and moderately persistent nature, damage may occur away from the application site. The objective of this work was to better predict the fate and transport of an organophosphate insecticide, chlorpyrifos. Chlorpyrifos was sprayed on a field of Purple Tansey (Phacelia tanacetifolia) at a farm near Ida Valley, Central Otago, New Zealand in January 2017. Leaves and soil samples were collected from the sprayed field for 21 days. Seven medium-volume and one high-volume active air samplers were deployed 30 meters to 500 meters away from the sprayed field to collect airborne chlorpyrifos and chlorpyrifos oxon for 21 days after spraying. Chlorpyrifos and its oxon were quantified in the leaves, soil and air and used modelling tool to understand the concentration trends with time and space.
The pesticide Loss via Volatilisation (PLoVo) model predicts the cumulative volatilisation losses of pesticides from agricultural fields, based on environmentally relevant partition coefficients and the mass-balance distribution of pesticides between soil, air, and water compartments. Originally, soil-air partition coefficient (Ksoil-air) values for pure active ingredients were used in the PLoVo model as input parameters. To better understand and predict pesticide volatilisation, how partition coefficients are affected by the adjuvants (e.g. solvents, wetting agents, dyes) found in real commercial pesticide formulations is necessary to know. In this project, a modified version of a fugacity meter was used to measure Ksoil-air values of three semi-volatile pesticides (trifluralin, chlorpyrifos & pyrimethanil) as (a) pure active ingredients, (b) active ingredients in commercial formulations, and (c) active ingredients in the commercial formulation with additional adjuvant. Experiments were conducted at several environmentally relevant temperatures (10-30 °C). I have found that the Ksoil-air values for active ingredients present in commercial formulations (Ksoil-air, formulation) were at least an order magnitude lower than those for pure active ingredients. When Ksoil-air, formulation values were used as input values in the PLoVo model, the cumulative percentage volatilisation for 24 hours increased by four to thirteen times compared to when using Ksoil-air values for the active ingredients. This suggests that a better qualitative understanding of how adjuvants affect pesticide-soil interaction is needed.
Dicamba (3, 6-dichloro-2-methoxybenzoic acid), a synthetic systemic herbicide, can drift away to non-target fields and cause injury to nearby sensitive plants. While only a handful field studies were conducted to chemically measure dicamba volatility, no quantitative prediction is available in the form of modelling to identify the factors that trigger the volatilisation of dicamba. To better understand the dicamba volatilisation and vapour drift potential in field conditions, I have used a visual screening tool, named ‘Pesticide Loss via Volatilisation (PLoVo)’ to predict the volatilisation and vapour drift potential of dicamba herbicide from an agricultural field. Different environmentally relevant conditions were analysed to identify under which the greatest dicamba volatilisation possibilities occurs. I have found that vapour drift potential increased with increasing temperature and wind speed. The current version of the PLoVo model does not take account of the pH effect; therefore, I have improved the model by including pH in it. Measured losses of dicamba in the field conditions were also compared with the modelled predictions. Deviation in model predictions from reported measured volatilisation losses was observed and showed limitations of current volatilisation models, such as pesticide formulation effects were not considered in this screening model.