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Estimating methane gas generation from Devil's swamp landfill using greenhouse gas emission models

Posted on:2014-12-07Degree:M.EngType:Thesis
University:Southern University and Agricultural and Mechanical CollegeCandidate:Adeyemi, Ayodeji ThompsonFull Text:PDF
GTID:2451390008453712Subject:Engineering
Abstract/Summary:
Greenhouse gas (GHG) has been a key issue in the study, design, and management of landfills. Landfill gas (LFG) is considered either as a significant source of renewable energy (if extracted and processed accordingly) or significant source of pollution and risk (if not mitigated or processed). A municipal solid waste (MSW) landfill emits a significant amount of methane, a potent GHG. Thus, quantification and mitigation of GHG emissions is an important area of study in engineering and other sciences related to landfill technology and management.;The present study will focus on estimating methane generation from Devils swamp landfill (DSLF), a closed landfill in Baton Rouge, LA. The landfill operated for 53 years (1940-1993) and contains both industrial and municipal waste products. Since the Clean Air Act of 1963, landfills are now classified as New Source Performance Standard (NSPS) waste (i.e., waste that will decompose to generate LFG). Currently, the DSLF is being used as source of renewable energy through the "Waste to Energy" program. For this study, to estimate the methane potential in the DSLF, it is important to determine the characteristics and classification of the landfill's wastes. The study uses and compares different GHG modeling tools—LandGEM, a multiphase model, and a simple first-order model—to estimate methane gas emission and compare results with the actual emissions from the DSLF.;The sensitivity of the methane generation rate was analyzed by the methane generation models to assess the effects of variables such as initial conditions, specific growth rate, and reaction rate constants. The study concludes that methane (L0) and initial organic concentration in waste (k) are the most important parameters when estimating methane generation using the models.
Keywords/Search Tags:Methane, Landfill, Gas, Generation, GHG, Waste, DSLF
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