Large-eddy simulation, atmospheric measurement and inverse modeling of greenhouse gas emissions at local spatial scales.

摘要

Anthropogenic greenhouse gas (GHG) emissions enhance the atmospheric greenhouse effect, tend to increase the average global temperature, and contribute to global climate change. Those consequences motivate the establishment of regulatory frameworks to control and reduce GHG emissions. The credibility of emissions regulations depends on reliable, independent methods for long-term monitoring, verification and accounting of the actual emissions of market participants. Therefore the objectives of the present study are: (1) to evaluate the performance of state of the art trace gas dispersion models for the atmospheric boundary layer; (2) to develop novel measurement and modeling techniques for quantifying GHG emissions from spatially distributed sources using a top-down approach. Top-down methods combine atmospheric measurements of GHG concentration with meteorological data, and inverse transport models to quantify emissions sources.;The ability of Weather Research and Forecasting, large-eddy simulation (WRFLES) to model passive scalar dispersion from continuous sources in the atmospheric boundary layer was investigated. WRF-LES profiles of mean and fluctuating concentration in the daytime convective boundary layer were similar to data from laboratory experiments and other LES models. Poor turbulence resolution near the surface in neutral boundary layer simulations caused under prediction of mean dispersion in the crosswind direction, and over prediction of concentration variance in the surface layer. WRF-LES simulations also showed that the concentration intermittency factor is a promising metric for detecting source location using atmospheric measurements.;A source determination model was developed to predict the location and strength of continuous, surface level, trace gas sources using concentration and turbulence measurements at two locations. The need for measurements at only two locations is advantageous for GHG monitoring applications where large sensor arrays are unfeasible due to high equipment costs and practical constraints on sensor placement. Atmospheric measurements of turbulence and methane concentration made during an outdoor, controlled release experiment were used to demonstrate the feasibility of the source determination model. The model predicted trace gas flux with less than 50% uncertainty, and provided an upper bound for fluxes from localized sources. The model can be used for detection and continuous, long-term monitoring of fugitive GHG emissions.