ORCID

https://orcid.org/0000-0003-4369-7736

Date of Award

Fall 2025

Language

English

Embargo Period

9-30-2026

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Atmospheric and Environmental Sciences

Program

Atmospheric Science

First Advisor

James Schwab

Committee Members

Jie Zhang, Sara Lance, Lee Murray, Sarah Lu

Keywords

methane, landfill, emission rate, greenhouse gas, inventory

Subject Categories

Analysis | Atmospheric Sciences | Environmental Monitoring

Abstract

Greenhouse gas (GHG) emission increases are a consequence of global population rise and economic growth. It is well known that carbon dioxide is the dominant GHG by mass, but methane has received increasing attention recently due to its high warming potential and relatively short lifetime of about a decade. Methane has several different types of both natural and anthropogenic sources including wetlands, waste management, energy, agriculture and farming, and wildfires, which makes tracking and reducing methane emissions a complex problem. The emission rates of each of these sources are highly uncertain due to differing emission estimation methods, which can be divided into either bottom-up or top-down approaches. Bottom-up methods are process-based and use calculations and emission factors to extrapolate to larger scales while top-down methods use direct measurements and inverse modeling to estimate emissions of a facility or region and scale downward. While there is no clear answer to whether one is more accurate than the other given that both methods have their own uncertainties, past studies have shown that bottom-up methods (GHG inventories) have underestimated emissions across multiple sectors. This research focuses on comparing bottom-up and top-down methods across landfill and other source sector facilities in New York State (NYS), while also evaluating differences between the methods themselves. Specifically, several methods, including a Gaussian Plume Dispersion (GPD) method, mass balance approach using Gauss’s Theorem, and a ratio calculation, will be applied to mobile research laboratory (MRL) and aircraft measurements to estimate facility emission rates. These methods are evaluated relative to each other for efficacy and compared with the EPA’s self-reported GHG Emissions Inventory to assess inventory accuracy. While the aircraft mass balance estimate is generally considered reliable due to including most of the upper air measurements of the plume, there is still uncertainty due to the lack of measurements below the lowest flight level, which can leave out vital details on the plume concentration and wind flow. The observed aircraft methane emission rates at the sampled landfills ranged from 161–3440 kg h-1 and, on average, indicated an underreporting of the 2021 self-reported EPA Inventory by a factor of 2. The MRL methane emission estimates were calculated using the GPD method and mass balance approach with mixed results. The GPD estimates fared well compared to the aircraft estimates but were highly sensitive to sampling routes, distance, and stability class determination. The MRL mass balance estimates were calculated using two separate estimated plume heights with very different results, which highlights this method’s dependency on an accurate plume height estimation. The MRL emission rates were also mixed in how they compared with the self-reported EPA inventory. However, for two landfills, the observations were higher than the self-reported inventory using every method. Lastly, the ratio calculation method is beneficial for estimating the emission rate of a pollutant not included in the emissions inventory but is highly dependent on the reference pollutant. While this information is helpful and valuable, long-term measurements are necessary to achieve an emission rate representative of true conditions. The results from this study will help scientists, policymakers, and regulators in NYS and beyond with interpreting landfill measurement data, evaluating emission estimation methods and their applications, and assessing how well the inventory accounts for emissions.

License

This work is licensed under the University at Albany Standard Author Agreement.

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Available for download on Wednesday, September 30, 2026

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