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Redesigning the FDMT Food Chain Transfer Model: Now Probabilistically Enabled and Fully Flexible

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Abstract

In Europe, the two main nuclear accident response decision support systems in use are ARGOS and JRODOS, both of which make use of the FDMT (Food Chain and Dose Module for Terrestrial pathways) model to simulate the transfer of radioactivity along terrestrial food chains and to predict radionuclide activity concentrations in human foodstuffs. FDMT was originally developed in the early 1990s for Southern German agricultural conditions. Its application to other geographical settings has raised concerns regarding its fitness for purpose. Furthermore, the FDMT model in its original format lacks transparency, flexibility, and the possibility to be run probabilistically. In order to improve FDMT’s fitness for purpose and overcome its main shortcomings, it has been implemented in a new modelling platform which incorporates powerful numerical solvers and renders uncertainty and sensitivity analysis possible. The modelling structure of FDMT has been re-configured, and a library configuration has been introduced which offers flexibility in working such that model components can be tested, modified, or replaced easily. The new FDMT allows for the consideration of case/region-specific issues and to make predictions which are of more relevance and of better use with regard to decision making and management of risk. Furthermore, the default databases of FDMT have been updated and wherever possible PDFs have been assigned. In this paper, the transition of FDMT from an old to a new modelling structure is presented along with a demonstration of developments achieved.

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Notes

  1. The choice of iteration numbers is somewhat arbitrary, the number of iterations for sensitivity analysis selected as being a factor of 10 higher than probabilistic runs. The common factor in both cases was that enough iterations were selected to ensure that the statistical information being generated could be deemed reliable.

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Acknowledgements

The authors would like to thank Cath Barnett (UK CEH) for collating the revised parameter values we have used. The work described in this paper was conducted within the CONFIDENCE project which was part of the CONCERT project.

Funding

The CONCERT project received funding from the Euratom Research and Training programme (2014–2018) under grant agreement no. 662287. The work of Ali Hosseini, Deborah Oughton, and Justin Brown was (partly) supported by the Research Council of Norway through its Centre’s of Excellence funding scheme, project number 223268/F50.

Author information

Authors and Affiliations

  1. DSA – Norwegian Radiation and Nuclear Safety Authority, Osteras, Norway

    A. Hosseini & J. E. Brown

  2. Facilia Networking, Hökens gata 9, Stockholm, 11646, Sweden

    R. Avila

  3. UKCEH – UK Centre for Ecology & Hydrology, Lancaster, UK

    N. A. Beresford

  4. NMBU/CERAD - Norwegian University of Life Sciences, Centre for Environmental Radioactivity, As, Norway

    D. Oughton

Authors
  1. A. Hosseini
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  2. J. E. Brown
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  3. R. Avila
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  4. N. A. Beresford
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  5. D. Oughton
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Contributions

AH coordinated the activities in the study and is the main author of the work. AH collated parameter datasets and conducted simulations using the newly developed software. RA was responsible for the development and implementation of the software/programme code used in the study. NB was coordinator of the project under which this work was performed (i.e. CONFIDENCE work-package Leader) and was instrumental in directing this work. NB was a co-author and involved in drafting of the manuscript and collated parameter datasets. JB is a co-supervisor of AH’s PhD and as such was involved in the planning and direction of the study. He was heavily involved in assisting to draft and structure the manuscript, collated parameter datasets, and conducted simulations using the newly developed software. DO is the main supervisor of AH’s PhD and as such was involved in the planning and direction of the study. DO was involved in prior-to-submission review of the manuscript.

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Correspondence to A. Hosseini.

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Appendix

Appendix

Soil to plant transfer factors (TF, unitless) for caesium, strontium, and iodine (new values from IAEA [29])

Element

Plant

New default (old default)

Distribution*

Mean

STD

Cs

Beet_leaves

5.6E − 3 (3.0E − 2)

1.1E − 2

1.9E − 2

Leafy_vegetables

6.0E − 3 (2.0E − 2)

1.7E − 2

2.1E − 2

Maize

1.8E − 2 (2.0E − 2)

3.0E − 2

2.8E − 2

Beet

6.7E − 3 (1.0E − 2)

1.2E − 2

1.8E − 2

Corncobs

6.3E − 3 (1.0E − 2)

1.1E − 2

1.1E − 2

Fruit

8.7E − 4 (2.0E − 2)

2.3E − 3

3.3E − 3

Oats

2.5E − 2 (2.0E − 2)

6.6E − 2

1.3E − 1

Potatoes

1.2E − 2 (1.0E − 2)

2.1E − 2

2.5E − 2

Rye

2.5E − 2 (2.0E − 2)

6.6E − 2

1.3E − 1

Spring_barley

2.5E − 2 (2.0E −  − 2)

6.6E − 2

1.3E − 1

Spring_wheat

2.6E − 2 (2.0E − 2)

6.7E − 2

1.3E − 1

Winter_barley

2.5E − 2 (2.0E − 2)

6.6E − 2

1.3E − 1

Winter_wheat

2.6E − 2 (2.0E − 2)

6.7E − 2

1.3E − 1

Berries

1.5E − 3 (2.0E − 2)

2.9E − 3

3.3E − 3

Fruit_vegetables

1.1E − 3 (1.0E − 2)

3.5E − 3

7.5E − 3

Root_vegetables

6.7E − 3 (1.0E − 2)

1.2E − 2

1.8E − 2

Grass (Intensive)

5.5E − 2 (5.0E − 2)

1.2E − 1

1.8E − 1

Grass (Extensive)

1.7E − 1 (1.0E0)

2.4E − 2

2.6E − 2

Sr

Beet_leaves

1.2E − 1 (8.0E − 1)

2.4E − 1

2.2E − 1

Leafy_vegetables

7.6E − 2 (4.0E − 1)

1.9E − 1

1.8E − 1

Maize

1.8E − 1 (3.0E − 1)

2.5E − 1

1.9E − 1

Beet

1.2E − 1 (4.0E − 1)

2.4E − 1

2.2E − 1

Corn_cobs

6.1E − 2 (2.0E − 1)

1.1E − 1

1.2E − 2

Fruit

2.6E − 3 (1.0E − 1)

3.8E − 3

2.9E − 3

Oats

9.6E − 2 (2.0E − 1)

1.6E − 1

1.7E − 1

Potatoes

3.4E − 2 (5.0E − 2)

5.0E − 2

4.6E − 2

Rye

9.6E − 2 (2.0E − 1)

1.6E − 1

1.7E − 1

Spring_barley

9.6E − 2 (2.0E − 1)

1.6E − 1

1.7E − 1

Spring_wheat

9.7E − 2 (2.0E − 1)

1.6E − 1

1.7E − 1

Winter_barley

9.6E −  − 2 (2.0E − 1)

1.6E − 1

1.7E − 1

Winter_wheat

9.7E − 2 (2.0E − 1)

1.6E − 1

1.7E − 1

Berries

3.3E − 2 (1.0E − 1)

5.5E − 2

6.9E − 2

Fruit_vegetables

1.8E − 2 (2.0E − 1)

4.9E − 2

9.0E − 2

Root_vegetables

1.2E − 1 (3.0E − 1)

2.4E − 1

2.2E − 1

Grass (Intensive)

2.9E − 1 (5.0E − 1)

3.74E − 1

2.6E − 1

Grass (Extensive)

2.9E − 1 (1.0E0)

3.74E − 1

2.6E − 1

I

Beet_leaves

1.2E − 3 (1.0E − 1)

2.1E − 3

1.9E − 3

Leafy_vegetables

6.5E − 4 (1.0E − 1)

1.6E − 3

2.9E − 3

Maize

1.3E − 2 (1.0E − 1)

2.8E − 2**

4.5E − 2**

Beet

1.2E − 3 (1.0E − 1)

2.1E − 3

19E − 3

Corn_cobs

1.2E − 4 (1.0E − 1)

2.7E − 4

5.3E − 4

Fruit

9.5E − 4 (1.0E − 1)

1.8E − 3

1.8E − 3

Oats

5.5E − 4 (1.0E − 1)

1.3E − 4

2.4E − 3

Potatoes

2.1E − 2 (1.0E − 1)***

  

Rye

5.5E − 4 (1.0E − 1)

1.2E − 4

2.4E − 3

Spring_barley

5.5E − 4 (1.0E − 1)

1.2E − 4

2.4E − 3

Spring_wheat

5.5E − 4 (1.0E − 1)

1.2E − 4

2.5E − 3

Winter_barley

5.5E − 4 (1.0E − 1)

1.2E − 4

2.4E − 3

Winter_wheat

5.5E − 4 (1.0E − 1)

1.2E − 4

2.5E − 3

Berries

1.5E − 2 (1.0E − 1)***

  

Fruit_vegetables

5.0E − 3 (1.0E − 1)***

  

Root_vegetables

1.2E − 3 (1.0E − 1)

2.1E − 3

1.9E − 3

Grass (Intensive)

8.1E − 4 (1.0E − 1)

9.9E − 2

3.1E − 2

Grass (Extensive)

8.1E − 4 (1.0E − 1)

9.9E − 2

3.1E − 2

  1. *Untruncated lognormal distribution; **for cereal stem and shoots; ***No distribution, based on one value

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Hosseini, A., Brown, J.E., Avila, R. et al. Redesigning the FDMT Food Chain Transfer Model: Now Probabilistically Enabled and Fully Flexible. Environ Model Assess 27, 311–326 (2022). https://doi.org/10.1007/s10666-021-09794-2

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  • DOI: https://doi.org/10.1007/s10666-021-09794-2

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