Multi-Source Emission Determination Using an Inverse-Dispersion Technique |
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| Authors: | Thomas K Flesch Lowry A Harper Raymond L Desjardins Zhiling Gao Brian P Crenna |
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| Institution: | (1) Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, Canada;(2) Department of Poultry Science, University of Georgia, Athens, GA, USA;(3) Agriculture and Agri-Food Canada, 960 Carling Ave., Ottawa, Canada;(4) College of Resources and Environmental Science, Agricultural University of Hebei, Baoding, China |
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| Abstract: | Inverse-dispersion calculations can be used to infer atmospheric emission rates through a combination of downwind gas concentrations
and dispersion model predictions. With multiple concentration sensors downwind of a compound source (whose component positions
are known) it is possible to calculate the component emissions. With this in mind, a field experiment was conducted to examine
the feasibility of such multi-source inferences, using four synthetic area sources and eight concentration sensors arranged
in different configurations. Multi-source problems tend to be mathematically ill-conditioned, as expressed by the condition
number κ. In our most successful configuration (average κ = 4.2) the total emissions from all sources were deduced to within 10% on average, while component emissions were deduced
to within 50%. In our least successful configuration (average κ = 91) the total emissions were calculated to within only 50%, and component calculations were highly inaccurate. Our study
indicates that the most accurate multi-source inferences will occur if each sensor is influenced by only a single source.
A “progressive” layout is the next best: one sensor is positioned to “see” only one source, the next sensor is placed to see
the first source and another, a third sensor is placed to see the previous two plus a third, and so on. When it is not possible
to isolate any sources κ is large and the accuracy of a multi-source inference is doubtful. |
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| Keywords: | Condition number Dispersion modelling Emission rates Inverse dispersion Open path laser |
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