Technical note: Interpretation of field observations of point-source methane plume using observation-driven large-eddy simulations

ATMOSPHERIC CHEMISTRY AND PHYSICS(2022)

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摘要
This study demonstrates the ability of large-eddy simulation (LES) forced by a large-scale model to reproduce plume dispersion in an actual field campaign. Our aim is to bring together field observations taken under non-ideal conditions and LES to show that this combination can help to derive point-source strengths from sparse observations. We analyze results from a single-day case study based on data collected near an oil well during the ROMEO campaign (ROmanian Methane Emissions from Oil and gas) that took place in October 2019. We set up our LES using boundary conditions derived from the meteorological reanalysis ERA5 and released a point source in line with the configuration in the field. The weather conditions produced by the LES show close agreement with field observations, although the observed wind field showed complex features due to the absence of synoptic forcing. In order to align the plume direction with field observations, we created a second simulation experiment with manipulated wind fields that better resemble the observations. Using these LESs, the estimated source strengths agree well with the emitted artificial tracer gas plume, indicating the suitability of LES to infer source strengths from observations under complex conditions. To further harvest the added value of LES, higher-order statistical moments of the simulated plume were analyzed. Here, we found good agreement with plumes from previous LES and laboratory experiments in channel flows. We derived a length scale of plume mixing from the boundary layer height, the mean wind speed and convective velocity scale. It was demonstrated that this length scale represents the distance from the source at which the predominant plume behavior transfers from meandering dispersion to relative dispersion.
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关键词
methane,field observations,point-source,observation-driven,large-eddy
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