You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Probability Modelling [and Discussion]
Dennis A. Laskowski, Patti M. Tillotson, Don D. Fontaine and Eric J. Martin
Philosophical Transactions: Biological Sciences
Vol. 329, No. 1255, Quantitative Theory is Soil Productivity and Environmental Pollution (Sep. 29, 1990), pp. 383-389
Published by: Royal Society
Stable URL: http://www.jstor.org/stable/76843
Page Count: 7
You can always find the topics here!Topics: Chemicals, Agricultural soils, Agrology, Soil biochemistry, Soil pollution, Soil water, Clay soils, Probabilities, Leaching, Soil properties
Were these topics helpful?See something inaccurate? Let us know!
Select the topics that are inaccurate.
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
This paper traces the development of modelling to assess the environmental fate of agricultural chemicals within DowElanco's Environmental Fate Group. Field monitoring of fate was the initial tool for assessment, but inefficiency of the process and poor data interpretability turned the group's attention to benchmarking. This, too, proved to be an inadequate and frustrating process as it evaluated fate only relative to other chemicals and did not allow in an absolute sense the assessment of risk of contamination away from treated locations. It also did not allow the evaluation of management programmes for minimization of environmental impact. Currently, probability modelling is being evaluated to assess the environmental fate of chemicals and the likelihood of attaining a given concentration at a specified site. It allows the handling of variability and provides estimates of likelihood for environmental events to take place in designated areas of the United States. Through the use of Fourier Amplitude Sensitivity Test and Monte Carlo sampling techniques, ranges of inputs are used to drive environmental models to provide frequency distribution data for output. The process appears useful for assessing environmental impact of chemicals because it allows whole range evaluation with data that are readily available, and provides information appropriate for best management practices.
Philosophical Transactions: Biological Sciences © 1990 Royal Society