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Activity Number:
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244
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Type:
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Invited
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Date/Time:
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Tuesday, August 5, 2008 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #300154 |
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Title:
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Estimating a Pollutant's Policy-Related Background Level with Deterministic and Statistical Models
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Author(s):
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James V. Zidek*+ and Zhong Liu and Nhu Le
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Companies:
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The University of British Columbia and The University of British Columbia and BC Cancer Research Center
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Address:
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Department of Statistics, Vancouver, BC, V6T 1Z2, Canada
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Keywords:
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air pollution ; deterministic models ; ozone ; environmetrics ; MAQSIP ; policy related background
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Abstract:
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A PRB (Policy Related Background) level of a criterion pollutant such as ozone addressed in US regularity policy, is its (hypothetical) level if there were no anthropogenic sources in North America. It is a foundation above which to set regulatory standards but it cannot be measured directly so is inferred by deterministic CTMs (chemical transport models). The Bayesian melding approach of Fuentes and Raftery offers an approach for comparing CTM outputs with measurements to check accuracy. This paper describes the result of using that method along with aspects of the MCMC involved in this very parameter high dimensional parameter problem. Finally, some simpler alternative approaches to recalibrating the CTM outputs will be described.
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