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Activity Number: 71
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistics and the Environment
Abstract #319151
Title: Bayesian Modeling of Days in Risk Due to Concentration of PM10 in Kuwait
Author(s): Fahimah Alawadhi*
Companies: Kuwait University
Keywords: Air-pollution ; Prediction ; Bayesian technique ; MCMC ; particulate matters
Abstract:

Along with economic development in modern world, the air pollution has already been a problem to human being and the ecological system for a long time. One of the most common pollutants that affect the inhabitants of some cities is Particulate matters (PM10). Particulate matters consist of very small liquid and solid particles floating in the air. These particulates are of greatest concern to public health in Kuwait because these are small enough to be inhaled into the deepest parts of the lung. These particles are less than 10 microns in diameter (about 1/7 of the thickness of a human hair). When PM10 remains above a certain threshold for a given period of time, individuals exposed to the pollutant may experience serious health problems. Therefore, modeling and predicting the exceeding of the threshold limit are very important issues. In this research aims to analyze the hazardous situations due to PM10 for 2010 in Kuwait and forecast new ones, in a context of reliability checking before it occurs.


Authors who are presenting talks have a * after their name.

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