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RECORD NUMBER: 12 OF 14

OLS Field Name OLS Field Data
Main Title Subjective-Probability-Based Scenarios for Uncertain Input Parameters: Stratospheric Ozone Depletion.
Author Hammitt., J. K. ;
CORP Author RAND Corp., Santa Monica, CA.;National Aeronautics and Space Administration, Washington, DC.
Publisher Apr 90
Year Published 1990
Report Number N-3140-EPA/JMO/RC;
Stock Number N90-28157/7
Additional Subjects Computerized simulation ; Environment pollution ; Ozone depletion ; Probability density functions ; Stratosphere ; Atmospheric composition ; Monte carlo method ; Quantiles ;
Holdings
Library Call Number Additional Info Location Last
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Status
NTIS  N90-28157/7 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 03/04/1991
Collation 14p
Abstract Risk analysis often depends on complex, computer-based models to describe links between policies (e.g., required emission-control equipment) and consequences (e.g., probabilities of adverse health effects). Appropriate specification of many model aspects is uncertain, including details of the model structure; transport, reaction-rate, and other parameters; and application-specific inputs such as pollutant-release rates. Because these uncertainties preclude calculation of the precise consequences of a policy, it is important to characterize the plausible range of effects. In principle, a probability distribution function for the effects can be constructed using Monte Carlo analysis, but the combinatorics of multiple uncertainties and the often high cost of model runs quickly exhaust available resources. A method to choose sets of input conditions (scenarios) that efficiently represent knowledge about the joint probability distribution of inputs is presented and applied. A simple score function approximately relating inputs to a policy-relevant output, in this case, globally averaged stratospheric ozone depletion, is developed. The probability density function for the score-function value is analytically derived from a subjective joint probability density for the inputs. Scenarios are defined by selected quantiles of the score function. Using this method, scenarios can be systematically selected in terms of the approximate probability distribution function for the output of concern, and probability intervals for the joint effect of the inputs can be readily constructed.
Supplementary Notes Repr. From Risk Analysis, V. 10, No. 1, p 93-102.
Category Codes 68A; 55E
NTIS Prices PC A03/MF A01
Document Type NT
Cataloging Source NTIS/MT
Control Number 034829437
Origin NTIS
Type CAT