Research Terms
Civil Engineering Environmental Engineering Hazardous Wastes Solid Waste Landfills
Keywords
Famu-Fsu College Of Engineering
Abichou, T., Barlaz, M., Green, R., & Hater, G. (2013). Liquid balance monitoring inside conventional, retrofit, and bio-reactor landfill cells. Waste Mangement, 3, 9.http://dx.doi.org/10.1016/j.wasman.2013.05.023.
Abichou, T., Barlaz, M., Green, R., & Hater, G. (2013). The Outer Loop Bioreactor: A Case Study of Settlement Monitoring and Solids Decomposition. Waste Management, 20. Retrieved from http://dx.doi.org/10.1016/j.wasman.2013.02.005
Abichou, T., Clark, J., & Chaton, J. (2012). A new approach to characterize emission contributions from area sources during optical remote sensing technique testing. Journal of the Air & Waste Management Association, 1403-1410. Retrieved from http://www.tandfonline.com/doi/abs/10.1080/10962247.2012.716384 doi:DOI: 10.1080/10962247.2012.716384
Abichou, T., Musagasa, J., Yuan, L., Chanton, J., Tawfiq, K., & Rockwood, R. (2012). Field Performance of Alternative Landfill Covers Vegetated with Cottonwood and Eucalyptus Trees. International Journal of Phytoremediation, 47-60. doi:10.1080/15226514.2011.607869
Goldsmith, C., Chanton, J., Abichou, T., Swan, N., Green, R., & Hater, G. (2012). Methane emissions from 20 landfills across the United States using vertical radial plume mapping. Journal of the Air & Waste Management Association, 183-197. doi:10.1080/10473289.2011.639480
Abichou, T., Clark, J., & Chanton, J. (2011). Reporting central tendencies of chamber measured surface emission and oxidation. Waste Management, 31(5), 1002-1008. Retrieved from http://dx.doi.org/10.1016/j.wasman.2010.09.014
Abichou, T., Mahieu, K., Chanton, J., Romdhane, M., & Mansouri, I. (2011). Scaling methane oxidation: From laboratory incubation experiments to landfill cover field conditions. Waste Management, 31(5), 978-986. Retrieved from http://dx.doi.org/10.1016/j.wasman.2010.12.002
Abichou, T., Mahieu, K., Yuan, L., Chanton, J., & Hater, G. (2009). Effects of compost biocovers on gas flow and methane oxidation in a landfill cover. Waste Management, 29(5), 1595-1601. Retrieved from http://dx.doi.org/10.1016/j.wasman.2008.11.007
The algorithm identifies positions of leakage sources and to quantify the gas emission rate from the surface of a landfill. An optimization-based approach using Genetic Algorithms (GA) is employed to solve the inverse problem that consists of identifying source data (locations of hot-spots and corresponding emission rates) having only receptor location and surface measurements as input data. Single and multi-objective optimization schemes through GAs are used with surface methane concentration data along with wind speed and wind direction during the monitoring campaign. This is the measurement data. The optimization methodology uses atmospheric dispersion calculations to predict major methane emissions sources in a landfill. The total emissions of the landfill are then estimated by summing all of the methane sources predicted by the algorithm.
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