Date of Award

January 2023

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Energy Engineering

First Advisor

Michael Mann

Abstract

The population of the planet surpassed the 8-billion-person mark in 2022, and the increase in population has brought about an increase in waste, both household and commercial. The municipal solid waste that is created is primarily stored in landfills, particularly in the United States. These landfills release methane and carbon dioxide into the atmosphere, creating what is known as anthropogenic emissions, due to their being caused by man-made issues. These two primary gases, along with others, make up greenhouse gases, and their reduction is key to potentially reducing or even reversing the greenhouse effect. Total municipal solid waste generation in the United States reached 292.4 million tons in 2018, which was an increase from the 268.7 million tons in 2017. Of the 292.4 million tons in 2018, over 146 million tons were sent to landfills, over 69 million tons were recycled, and 34 million tons were combusted for energy. The large amount of waste sent to landfills creates a significant opportunity to avoid emissions, increase energy savings, produce energy through renewable energy, and create wage impacts, or employment, by way of recycling. The opportunity to study the avoidance of emissions, energy savings, and wage or employment impact, comes from a life-cycle analysis of the municipal solid waste. The studying of potential energy production will come from the emissions generated by the landfill over its lifespan. This dissertation will address both life-cycle analysis and landfill gas generation in the form of modeling. The life-cycle analysis will utilize an EPA model called the Waste Reduction Model (WARM), which takes a cradle-to-grave approach and analyzes alternatives to the current waste management methodology. The Landfill Gas Emissions Model (LandGEM) provides an estimation of the gases from the municipal solid waste landfill, which will then be utilized to provide an energy potential estimate. The dissertation will evaluate the models with the primary goal of producing a practical option or strategy to simulate the largest quantity of emissions avoided, the largest possible energy savings, and greatest renewable energy potential.

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