Health impacts from pesticide use are of continuous concern. Hence, health impacts need to be characterized accounting for specific crops contributing differently to overall human exposure as well as accounting for individual substances showing distinct environmental behaviour and toxicity. We will work with a dynamic plant uptake model (dynamiCROP) to characterize potential health impacts of pesticides applied to six different food crops, based on a flexible set of interconnected compartments. In an exercise, we will demonstrate how to analyse the dynamics of residues by applying mathematical decomposition techniques. Finally, we investigate how toxicity potentials can be reduced by defining adequate pesticide substitution scenarios.
A participant who follows this course will be able to:
explain the principles and processes involved in the distribution of pesticides applied to different food crops,
quantify potential health impacts from pesticide intake via food crop consumption,
discuss different potentials for pesticide substitution.
This course is designed for:
new and experienced researchers in the field of environmental chemistry and engineering,
practitioners in life cycle impact assessment and risk assessment
For this course a basic knowledge in environmental chemistry is required as well as reading the background materials. Insight into multimedia modeling, matrix algebra, life cycle impact assessment (and/or risk assessment) is useful.
Course duration: 120 min (presentations and exercises)
1. Introduction into pesticide residues in food crops and assessment model design
2. Characterizing pesticides impacts and comparison across pesticides and food crops (30 min)
3. Insight into potentials for pesticide substitution (30 min)
4. Quantification and analysis of residues, health impacts and substitution potentials (15 min)
5. Exercises – (45 min)
Follow the course now via YouTube:
Background reading material:
All material will be made freely accessible to all course participants.
(1) Fantke et al., 2011: Environ Sci Technol 45, 8842-8849.
(2) Fantke et al., 2011: Chemosphere 85, 1639-1647.
(3) Juraske et al., 2012: Chemosphere 89, 850-855.
(4) Fantke et al., 2013: Environ Modell Softw 40, 316-324.
(5) Fantke et al., 2012: Environ Int 49, 9-17.