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Journal article

AERMOD as a Gaussian dispersion model for planning tracer gas dispersion tests for landfill methane emission quantification

In Waste Management 2019, Volume 87, pp. 924-936
From

University College Dublin1

Polytechnic University of Turin2

University of Southampton3

Department of Environmental Engineering, Technical University of Denmark4

Air, Land & Water Resources, Department of Environmental Engineering, Technical University of Denmark5

The measurement of methane emissions from landfills is important to the understanding of landfills' contribution to greenhouse gas emissions. The Tracer Dispersion Method (TDM) is becoming widely accepted as a technique, which allows landfill emissions to be quantified accurately provided that measurements are taken where the plumes of a released tracer-gas and landfill-gas are well-mixed.

However, the distance at which full mixing of the gases occurs is generally unknown prior to any experimental campaign. To overcome this problem the present paper demonstrates that, for any specific TDM application, a simple Gaussian dispersion model (AERMOD) can be run beforehand to help determine the distance from the source at which full mixing conditions occur, and the likely associated measurement errors.

An AERMOD model was created to simulate a series of TDM trials carried out at a UK landfill, and was benchmarked against the experimental data obtained. The model was used to investigate the impact of different factors (e.g. tracer cylinder placements, wind directions, atmospheric stability parameters) on TDM results to identify appropriate experimental set ups for different conditions.

The contribution of incomplete vertical mixing of tracer and landfill gas on TDM measurement error was explored using the model. It was observed that full mixing conditions at ground level do not imply full mixing over the entire plume height. However, when full mixing conditions were satisfied at ground level, then the error introduced by variations in mixing higher up were always less than 10%.

Language: English
Year: 2019
Pages: 924-936
ISSN: 18792456 and 0956053x
Types: Journal article
DOI: 10.1016/j.wasman.2018.02.007
ORCIDs: Mønster, Jacob and Scheutz, Charlotte

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