Oil Refineries Emissions: Source and Impact: A Study using AERMOD
The main objectives of this paper are to measure
pollutants concentrations in the oil refinery area in Kuwait over three
periods during one year, obtain recent emission inventory for the
three refineries of Kuwait, use AERMOD and the emission inventory
to predict pollutants concentrations and distribution, compare model
predictions against measured data, and perform numerical
experiments to determine conditions at which emission rates and the
resulting pollutant dispersion is below maximum allowable limits.
[1] R. S. Ettouney, J. G. Zaki, M. A. El-Rifai, and H. M. Ettouney, "An
assessment of the air pollution data from two monitoring stations in
Kuwait," Toxicological & Environmental Chemistry., vol. 92, Aug.
2010, pp. 655-668.
[2] R. S. Ettouney, S. Abdul-wahab, and A. S. Elkilani, "Emissions
inventory, iscst, and neural network: modeling of air pollution in
Kuwait," International Journal of Environmental Studies., vol. 66, Aug.
2009, pp. 181-194.
[3] S. M. Al-Alawi, S. A. Abdul-Wahab, C. S. Bakheit, "Combining
principal component regression and artificial neural networks for more
accurate predictions of ground-level ozone," Environmental Modeling &
Software., vol. 23, Aug. 2008, pp. 396-403.
[4] J. Gilham, et al., "On the applicability of xps for quantitative total
organic and elemental carbon analysis of airborne particulate matter,"
Atmospheric Environment., vol. 42, Aug. 2008, pp. 3888-3891.
[5] A. Monteiro, et al, "Air Quality Assessment for Portugal," Science of the
Total Environment., vol. 373, Aug. 2006, pp. 22-31.
[6] C. A. Borrego, and C.A. Brebbia, Air Pollution XV. Belmont,
WITPRESS, UK, 2007, pp. 15-113.
[1] R. S. Ettouney, J. G. Zaki, M. A. El-Rifai, and H. M. Ettouney, "An
assessment of the air pollution data from two monitoring stations in
Kuwait," Toxicological & Environmental Chemistry., vol. 92, Aug.
2010, pp. 655-668.
[2] R. S. Ettouney, S. Abdul-wahab, and A. S. Elkilani, "Emissions
inventory, iscst, and neural network: modeling of air pollution in
Kuwait," International Journal of Environmental Studies., vol. 66, Aug.
2009, pp. 181-194.
[3] S. M. Al-Alawi, S. A. Abdul-Wahab, C. S. Bakheit, "Combining
principal component regression and artificial neural networks for more
accurate predictions of ground-level ozone," Environmental Modeling &
Software., vol. 23, Aug. 2008, pp. 396-403.
[4] J. Gilham, et al., "On the applicability of xps for quantitative total
organic and elemental carbon analysis of airborne particulate matter,"
Atmospheric Environment., vol. 42, Aug. 2008, pp. 3888-3891.
[5] A. Monteiro, et al, "Air Quality Assessment for Portugal," Science of the
Total Environment., vol. 373, Aug. 2006, pp. 22-31.
[6] C. A. Borrego, and C.A. Brebbia, Air Pollution XV. Belmont,
WITPRESS, UK, 2007, pp. 15-113.
@article{"International Journal of Chemical, Materials and Biomolecular Sciences:63100", author = "Amir. AL-Haddad and Hisham. Ettouney and Samiya. Saqer", title = "Oil Refineries Emissions: Source and Impact: A Study using AERMOD", abstract = "The main objectives of this paper are to measure
pollutants concentrations in the oil refinery area in Kuwait over three
periods during one year, obtain recent emission inventory for the
three refineries of Kuwait, use AERMOD and the emission inventory
to predict pollutants concentrations and distribution, compare model
predictions against measured data, and perform numerical
experiments to determine conditions at which emission rates and the
resulting pollutant dispersion is below maximum allowable limits.", keywords = "Emissions, ISCST3 model, Modeling, Pollutants,
Refinery", volume = "6", number = "2", pages = "174-5", }