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Title: DEDUCING GROUND-AIR EMISSIONS FROM OBSERVED TRACE GAS CONCENTRATIONS: A FIELD TRIAL WITH WIND DISTURBANCE

Author
item FLESCH, T - UNIVERSITY OF ALBERTA
item WILSON, J - UNIVERSITY OF ALBERTA
item Harper, Lowry

Submitted to: Journal of Applied Meteorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/10/2004
Publication Date: 4/1/2005
Citation: Flesch, T.K., Wilson, J.D., Harper, L.A. 2005. Deducing ground-air emissions from observed trace gas concentrations: A field trial with wind disturbance. Journal of Applied Meteorology. 44:475-484.

Interpretive Summary: Ammonia is an air-quality gas emitted from animal waste-products. In the atmosphere, ammonia is combined with compounds from fossil fuel combustion (cars and electricity production) and produces particulates which are part of atmospheric haze and smog. Due to ammonia chemical and physical properties, its emissions are very expensive and time-consuming to measure accurately. Farm managers and regulatory agencies (state and federal) need a relatively inexpensive and easy technology to determine emission rates. The purpose of this report by scientists at the J.P. Campbell, Sr. Natural Resource Conservation Center, USDA-ARS, at Watkinsville, GA, and University of Alberta, Edmonton, is to discuss a new technology called the backward Lagrangian stochastic (bLS) method for evaluating trace-gases. Known concentrations of gases were released from a 6X6 square meter source. Concentrations were measured at the source and as much as 100 meters downwind. Gas emissions were calculated using the new bLS method and compared with known release rates. Over a six-day period, there was only a 2% difference between calculated and known emission rates. This new technology will provide an easier, less-expensive method for determining ammonia emissions and it is comparable in accuracy to other methods currently being used.

Technical Abstract: Inverse-dispersion techniques allow inference of a gas emission rate from a measured concentration. In ideal surface-layer situations, where the Monin-Obukhov similarity theory (MOST) describes the winds transporting the gas, application of the technique can be straight forward. The purpose of this research is to determine if a MOST-based dispersion model may be used to infer emissions in non-ideal settings. We apply an inverse-dispersion technique to estimate short-term (15 min) emission rates from a 6 m x 6 m area source surrounded by a windbreak fence (20 m x 20 m, 1.25 m tall) that perturbed the ambient winds. Open-path lasers gave line-average concentration downwind of the source, and a backward Lagrangian stochastic (bLS) dispersion model was used to infer emissions. Despite the disturbance of the mean wind and turbulence caused by the fence, the emissions estimates were quite accurate (within 2%) provided ambient winds (measured upwind of the plot) were used in the bLS model. In the worst cases, with the line-average concentration measured near the plot fence and within the disturbed flows, the bLS emissions overestimated the release emissions by an average of 50%. Our results indicate that if the bLS technique is applied to estimate emissions sources with disturbed wind-flows, if judgement is applied in the placement of the concentration detector and windspeed measuring equipment, the determinations may be of acceptable accuracy.