Use of pesticide ranking indices in the modelling of environmental impacts from pesticide use: a case study of the European apple industry

Abstract

Agricultural pollution from pesticides is an example of technological externality. In the presence of externalities decision making will probably never be optimal as externalities typically exist outside the decision making process. One of the main problems of incorporating externalities into the decision making process has been a lack of environmental impact data.

This thesis examines one methodological approach for identifying the environmental impacts associated with pesticide pollution: pesticide ranking indices. It will discuss the general rationale for the use of pesticide ranking indices, discuss the strengths and weaknesses of the various approaches, and recommend the adoption of one particular model for assessing the impacts associated with pesticide use at the farm and regional level. The model was tested against pesticide use data collected from European apple growing regions to ascertain whether results could be obtained that would be useable and understandable to decision makers at all levels.

Accepting that each methodology for identifying the impacts associated with pesticide use has both strengths and weaknesses, improvements in both model structure and data presentation are proposed that render the inclusion of environmental impact information in the decision making process more useable at the farm level. Thus, a modified model is presented that, it is argued, can adequately describe some of the external effects associated with pesticide use. This methodology can then be used by regulators wishing to minimise environmental pollution from agriculture and forestry, by identifying an appropriate threshold of acceptable, or unacceptable, environmental impact.