An integrated simulation-optimization coupling approach for supporting pesticide pollution control

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Today, more than 1.2 billion pounds of pesticides are used annually in North America by a variety of industries (e.g., agri-food industry, forestry, and lawn/landscaping industry), with up to 98% of the pesticide residues entering and contaminating the environment. Recently, the growing concerns on pesticide pollution have demanded more in-depth and comprehensive modeling and experimental studies for effectively supporting best management practice and sound pollution control. This proposed research attempts to meet such a demand. The major objective is to develop an integrated simulation-optimization coupling approach for supporting pesticide pollution control, which entails tasks of pollution simulation, practice optimization, decision making under uncertainty, and experimental analysis. The developed methodologies and associated technologies will be examined through multi-scale lab and field experiments in Newfoundland. The proposed research will comprehensively take into account a number of uncertain economic and environmental concerns arising in pesticide pollution control, and will be directly useful for both generating more cost-effective alternatives and improving control decision robustness. This search will help governments to improve their effectiveness and capabilities in controlling the challenging pesticide pollution problems in Canada; it will also benefit industries by providing them with efficient and cost-saving methods for the design and planning of their pesticide management and pollution control practices. In addition, undergraduate and graduate students will be involved throughout the research program and provide their input in a multidisciplinary research setting. The trained graduates will fill a pressing need for environmental and management professionals in industrial, consulting, governmental, and academic sectors, and contribute to Canadian competitiveness and advancement.