Contaminant transport through agroecosystems: assessing relative importance of environmental, physiological, and management factors
Agroecosystems can become contaminated by atmospherically released radionuclides. The subsequent concentrations of radionuclides in foods are dependent on numerous environmental, physiological, and management factors. We compared four approaches for estimating the relative importance of several of t...
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Published in | Ecological applications Vol. 2; no. 3; p. 285 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
01.08.1992
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Subjects | |
Online Access | Get more information |
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Summary: | Agroecosystems can become contaminated by atmospherically released radionuclides. The subsequent concentrations of radionuclides in foods are dependent on numerous environmental, physiological, and management factors. We compared four approaches for estimating the relative importance of several of these factors in determining concentrations of
I and
Cs in milk. A series of sensitivity analyses with Monte Carlo and full-factorial sampling designs was conducted on the PATHWAY model, which simulates radionuclide transport through an agroecosystem. Sensitivity of time-integrated concentrations in milk was estimated as a function of the time of year that fallout was deposited and as a function of time following a spring deposition. The dominant parameters affecting time-integrated concentrations of
I in milk were the initial fraction of radionuclides deposited on vegetation, timing and amount of pasture consumption, and the production rate of milk. For time-integrated concentrations of the longer-lived
Cs in milk, resuspension was a dominant parameter and pasture use was less important. The sampling designs were compared by ranking the parameters to which the model output is sensitive. The three sampling designs based on parameter variances produced sets of ranks that were similar to each other but differed from the ranking produced by the sampling design based on parameter magnitude. The results indicate which data are most crucial for real-time calculations following an accident and how subsequent dose from ingestion can be most effectively reduced, provide insight into model behavior, and help prioritize future research. This paper demonstrates the importance of variance-based sensitivity analysis. |
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Bibliography: | 9308803 T01 Q03 |
ISSN: | 1051-0761 1939-5582 |
DOI: | 10.2307/1941862 |