Publication Date:
2017-11-17
Description:
Mobile laboratory measurements provide information on the distribution of CH4 emissions from point sources such as oil and gas wells, but uncertainties are poorly constrained or justified. Sources of uncertainty and bias in ground-based Gaussian derived emissions estimates from a mobile platform were analyzed in a combined field and modeling study. In a field campaign where 1009 natural gas sites in Pennsylvania were sampled, a hierarchical measurement strategy was implemented with increasing complexity. Of these sites, ~ 93 % were sampled with an average of 2 transects (standard sampling), ~ 5 % were sampled with an average of 10 transects (replicate sampling) and ~ 2 % were sampled with an average of 20 transects while simultaneously deploying a tower to measure high-frequency meteorological data (intensive sampling). Five of the intensive sampling sites were modeled using large eddy simulation (LES) to reproduce CH4 concentrations in a turbulent environment. The LES output and derived emission estimates were used to compare with the results of a standard Gaussian approach. The LES and Gaussian derived emission rates agreed within a factor of 2, in most cases with average differences of 25 %. A controlled release was also used to investigate sources of bias in either technique. The Gaussian agreed with the release rate more closely than the LES underlying the importance of inputs as sources of uncertainty for the LES. The LES was also used as a virtual experiment to investigate optimum number of repeat transects and spacing needed to produce representative statistics. Approximately 10 repeat transects spaced at least 1 min apart are required to produce statistics similar to the observed variability over the entire LES simulation period of 30 min. In addition, other sources of uncertainty including source location, wind speed and stability were analyzed. In total, atmospheric variability, observed by repeat measurements at individual sites under relatively constant conditions, was found to be the most significant contributor to total uncertainty. Accurate measurements of this condition provide a reasonable estimate of the lower bound for emission uncertainty. It is recommended that future mobile monitoring schemes quantify this metric under representative conditions to accurately estimate emission uncertainty.
Electronic ISSN:
1680-7375
Topics:
Geosciences
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