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Environmental Sensitivity WG: Exploring Rural Environments Post-Emergency

The Environmental Sensitivity Working Group aims to examine environmental sensitivity in rural and semi-natural settings post-emergency incidents. This involves defining sensitivity factors, creating scenarios, and conducting modeling exercises. The group's tasks include literature reviews, compiling sensitivity factors, and connecting them to various environments. Key activities include scenario development, endpoint determination, modeling, and countermeasure exploration. The WG collaborates with various countries, such as Canada, Norway, France, and others. Potential models like RODOS-FDMT, ASTRAL-FRA, and ECOSYS are considered for different environments.

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Environmental Sensitivity WG: Exploring Rural Environments Post-Emergency

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  1. Environmental sensitivity EMRAS II kickoff meeting WG leader: Bliss Tracy, Canada WG moderator: John Brittain, Norway

  2. Participating Countries • Canada • Norway • France • Belgium • Finland • Germany • Austria • Others to be contacted

  3. Environmental sensitivity WG Objective: Explore the concept of environmental sensitivity in rural and semi-natural environments in the framework of assessments after an emergency situation Main tasks: • Formulate the concept of environmental sensitivity • Compile a list of sensitivity factors • Design scenarios • Carry out modelling exercises

  4. The concept of environmental sensitivity Literature review Draft concept document • IUR research: GER • VAMP: NOR • Canadian documents: CAN • Other • Radioecological sensitivity (journals): All • FASSET: GER • SENSIB: FRA • PRIME: FRA,... • STRATEGY / Handbook for food production systems: BEL, NOR

  5. List of sensitivity factors • Literature review • TRS 364 ...: NOR • Published data: CAN, GER, NOR, all • Group factors and link them to different environments • Agricultural: FRA, BEL (?) • Semi-natural • Arctic, alpine: NOR, CAN, FIN

  6. Exercises • Scenarios • End-points • Models • Countermeasures

  7. Scenarios • Artificial scenario • PWR, typical scenario • Generate ground deposition data • Input from the Urban WG? • Variations with season, etc, for same deposition pattern • Chernobyl • Measured ground deposition data

  8. End-points of model calculations and countries generating scenarios • Alpine (AUT, GER ?) • Milk • Arctic (NOR, FIN ?) • Mushrooms • Fish • Reindeer • Agricultural (FRA, NOR ?, CAN ?) • Plant products • Animal products • Temperate forest (FIN ?) • Mushrooms • Berries

  9. Potential models • Agricultural: RODOS-FDMT or SCK model, ASTRAL-FRA; STRATEGY-NOR, CHERPAC-CAN • Alpine: ECOSYS or RODOS-FDMT - GER, STRATEGY-NOR, Austrian model (?) • Arctic: FIN (?), CAN, STRATEGY-NOR, MOIRA-NOR (and/or ITA, SWE); FRA-EdF?

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