Graduation Semester and Year
2012
Language
English
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Civil Engineering
Department
Civil Engineering
First Advisor
Melanie L Sattler
Abstract
The increasing production of municipal solid waste is a direct consequence of the continuous growth of the world's population and economy. This fact makes protecting the environment against contamination by different kinds of waste a challenging job for engineers and decision makers. Conventional landfilling practices have sometimes failed to protect fresh water resources against leachate contamination as well as the atmosphere against greenhouse gases such as carbon dioxide and methane. Many developed countries have already taken serious steps toward moving to properly engineered, environmental friendly landfills.Landfill leachate contains organic and inorganic pollutants that have been extensively studied in the last four decades. Biochemical oxygen demand (BOD) and chemical oxygen demand (COD) are the most widely used indicators of leachate organic pollution. These two parameters are monitored regularly during the process of leachate treatment. They can also be used to recognize the solid waste stabilization stage in landfills. Understanding the behavior of BOD and COD throughout the life of a landfill via mathematical models would help in predicting the future extent of leachate organic pollution and, hence, the most efficient way of operating the leachate treatment facility. The main objective of this study was to develop two mathematical relationships for calculating the first-order reaction rate constants (k values) for leachate BOD and COD in terms of rainfall rate, temperature and waste composition.Twenty-seven lab-scale anaerobic reactor landfills were designed and operated under three temperatures (70, 85, and 100 °F) and three rainfall rates (2, 6, and 12 mm/day). The reactors were filled with various proportions of five waste components: food, paper, yard, textile, and inert inorganics. The range of temperatures and rainfall rates were chosen to include average rates for most locations worldwide, with the exception of deserts. Leachate was collected from these reactors and analyzed for BOD and COD content on a biweekly basis. The two models were developed using multiple linear regression analysis.The peak BOD concentrations in all the reactors ranged between 856 and 46,134 mg/L and peak COD concentrations were between 2,458 and 64,032 mg/L. Leachate from the 85 ℉ reactors showed higher BOD and COD content than other reactors with the same waste composition but different temperatures. The 2-mm/day reactors showed longer time (180-200 days) in reaching minimum or stable BOD and COD concentrations and BOD:COD ratio than all other reactors. Low moisture content in those reactors led to slow waste stabilization rates. Food waste reactors produced the highest BOD (46,134 mg/L) and COD (64,032 mg/L) leachate and textile waste produced the lowest (BODmax=8,960 mg/L and CODmax= 16,054 mg/L). The two models developed in this study show that increasing rainfall rate and temperature leads to higher BOD and COD content in leachate, which translates into faster waste decomposition. The kCOD model suggests that only paper and textile are the types of refuse that contribute to shaping leachate's COD concentration profile. Paper, yard, and food waste components were found to be significant in the kBOD model. The TP interaction term in both models suggests that paper waste decomposes faster at higher temperatures. In future work, the two models will be validated using field data.
Disciplines
Civil and Environmental Engineering | Civil Engineering | Engineering
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Altouqi, Said, "Modeling Leachate BOD And COD Using Lab-scale Reactor Landfills And Multiple Linear Regression Analysis" (2012). Civil Engineering Dissertations. 223.
https://mavmatrix.uta.edu/civilengineering_dissertations/223
Comments
Degree granted by The University of Texas at Arlington