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Smoke Plume Trajectory From In Situ Burning of Crude Oil in Alaska: Field Experiments.


pdf icon Smoke Plume Trajectory From In Situ Burning of Crude Oil in Alaska: Field Experiments. (4870 K)
McGrattan, K. B.; Walton, W. D.; Putorti, A. D., Jr.; Twilley, W. H.; McElroy, J. A.; Evans, D. D.

NISTIR 5764; NIST SP 995; Volume 2; 40 p. November 1995.

Sponsor:

Alaska Department of Environmental Conservation, Juneau, AK

Available from:

National Technical Information Service
Order number: PB96-131560

Keywords:

crude oil; oil spills; in situ combustion; pool fires; smoke; fire plumes; smoke movement; in situ burning

Abstract:

As part of their effort to assess the impact of smoke plumes from in situ burning of crude oil on nearby populations, the Alaska Regional Response Team and the Alaska Department of Environmental Conservation established a Cooperative Research and Development Agreement with the National Institute of Standards and Technology (NIST) in 1993 with the intent of developing predictive methods to estimate the downwind concentration of particulate matter from a burning oil spill. The first phase of the study consisted of laboratory-scale burns of North Slope and Cook Inlet crude oils, the results of which were used to define the source terms for the LES (Large Eddy Simulation) plume trajectory model. A number of different fire sizes and weather conditions were considered with the aim of estimating the extent to which concentrations of smoke particulate matter would exceed ambient air quality standards. Recommendations were made in a previously published report. In the present report, experimental data collected at two sets of mesoscale burns are compared with the results of the LES model run using the recorded meteorological and physical conditions. The two experiments are the Newfoundland Offshore Burn Experiment (NOBE), August 1993, and the Alaska Clean Seas Burning of Emulsions, September 1994. Each series of burns was conducted under different conditions, and different data collection techniques were employed at each. The results show that the predictions of the LES model are in good agreement with the experimental measurements, given the uncertainty of the input parameters. This increases confidence in the accuracy of the predicted results reported in the original study, and it also provides guidance on how to assess the undertainty of model predictions. The original report was written without the benefit of field data to validate the physical assumptions of the model; thus it was suggested that a factor of safety of 2 be applied to a model prediction to account for both the uncertainties in the input parameters and the physical assumptions of the model. The results of the field experiments, however, suggest that the uncertainty of the model prediction is commensurate with the uncertainty of the input parameters. This is not to say that the model is perfect, but rather that the uncertainties due to the physical assumptions of the model are outweighted by the uncertainties due to the input parameters.