Emissions inventory, ISCST, and neural network modelling of air pollution in Kuwait

This paper focuses on modelling of emission inventory, pollutant dispersion by the industrial source complex short term model (ISCST), and neural network analysis of air pollution in Kuwait. A novel neural network-based scheme is suggested and applied to site-specific short- and medium-term forecast...

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Bibliographic Details
Published in:International journal of environmental studies 2009-04, Vol.66 (2), p.193-206
Main Authors: Ettouney, Reem S., Abdul-Wahab, Sabah, Elkilani, Amal S.
Format: Article
Language:English
Subjects:
Air pollution
Emission inventory
ISCST and neural network modelling
Monitoring
Seasonal and temporal variations
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Summary:This paper focuses on modelling of emission inventory, pollutant dispersion by the industrial source complex short term model (ISCST), and neural network analysis of air pollution in Kuwait. A novel neural network-based scheme is suggested and applied to site-specific short- and medium-term forecasting of ozone concentrations. Two feed forward artificial neural networks (ANN) are used to improve the performance of time series predictions. Results show that this forecasting technique represents a significant improvement over the conventional ANN approach.
ISSN:0020-7233
1029-0400
DOI:10.1080/00207230902859929