Ph.D. / South Africa is the highest produce-producing and therefore the highest pesticide consumer on the African continent. Although greatly beneficial to the industry, indiscriminate and over usage of these agrochemicals pose a risk to the aquatic ecosystems through non-point source pollution. Data on these risks are limited in the developing countries such as Africa since limited environmental monitoring of pesticides is undertaken. This is due to technical, logistical and economical constraints in determining the links between exposure and effect on non-target organisms. Methods that are able to screen for and monitor pesticides that could pose a risk according to site-specific scenarios are therefore necessary. Economical and easy-to-use predictive models incorporated into Preliminary Risk Assessments (PRA’s) are useful in this regard and have been developed and applied globally to assist in estimating the probability of risks of pesticides associated with aquatic ecosystems. Currently no such risk assessment model is applied in South Africa for this purpose. The main aim of the present study was to present and assess the suitability of selected PRA models as preliminary screening tools for estimating potential pesticide exposure and associated effects within aquatic ecosystems. To achieve this, the primary objectives were to apply and validate these models for assessing predicted risks and to relate these to actual ecological hazards by monitoring the exposure and effects of selected pesticides that were identified as potentially posing a risk. It was hypothesised that the data determined by these models would elucidate the association between potential risks of pesticides and actual environmental impacts and could therefore be applied and validated for South African conditions. A framework was thus developed using multidisciplinary approaches to predict the risks of agricultural pesticides to non-target aquatic organisms and to validate these risks in an area known to have a high pesticide usage, namely the Crocodile (west) Marico catchment. This area is representative of a typical farming community in the subtropical central area of South Africa. It is a catchment area that exhibits high urban and agricultural usage, which has compromised the overall ecological integrity of the aquatic systems. The focus of the study was on the Crocodile (west) and Magalies Rivers and the associated irrigation canal network systems. The present study was based on integrating multidisciplinary techniques following the implementation of a tiered approach for assessing the ecological risks of selected pesticides known to be used within the Crocodile (west) Marico catchment. Tier 1 starts with the PRA assuming a relatively worst-case scenario by identifying pesticides most commonly used (through surveys) and estimating exposures posing a potential risk to the aquatic environment using the PRIMET (Pesticide Risks In the tropics to Man, Environment and Trade) model. The second tier can establish a more realistic characterisation of risk for the pesticide application scenarios of interest by using models such as PERPEST (Predicting the Ecological Risks of PESTicides), PEARL (Pesticide Emission Assessment of Regional and Local Scales), TOXSWA (TOXic substances in Surface Waters), or SSDs (Species Sensitivity Distributions). Higher tiers then include comparing the results from the PRA model predictions to the actual hazards of pesticides and can determine if these risk models are valid under South Africa conditions. This can be achieved using a combination of laboratory- and field-based monitoring assessments in the form of a triad approach (using chemical, toxicological and ecological assessments) to construct several lines-of-evidence (LoEs). The risk assessment process ends with a summary and integration of the data based on the multiple LoEs gathered during monitoring using a weight-of-evidence (WoE) approach.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uj/uj:8882 |
| Date | 31 July 2012 |
| Source Sets | South African National ETD Portal |
| Detected Language | English |
| Type | Thesis |
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