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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 (WRF-LES) 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.
The atmospheric concentration of methane (CH4) - the most significant non-CO2 anthropogenic long-lived greenhouse gas - stabilized between 1999 and 2006 and then began to rise again. Explanations for this behavior differ but studies agree that more measurements and better modeling are needed to reliably explain the model-data discrepancies and predict future change. This dissertation focuses on measurements of CH4 and inverse modeling of atmospheric CH4 fluxes using field measurements at a variety of spatial scales.
First concise textbook on Large-Eddy Simulation, a very important method in scientific computing and engineering From the foreword to the third edition written by Charles Meneveau: "... this meticulously assembled and significantly enlarged description of the many aspects of LES will be a most welcome addition to the bookshelves of scientists and engineers in fluid mechanics, LES practitioners, and students of turbulence in general."
First concise textbook on Large-Eddy Simulation, a very important method in scientific computing and engineering From the foreword to the third edition written by Charles Meneveau: "... this meticulously assembled and significantly enlarged description of the many aspects of LES will be a most welcome addition to the bookshelves of scientists and engineers in fluid mechanics, LES practitioners, and students of turbulence in general."
Understanding, quantifying, and tracking atmospheric methane and emissions is essential for addressing concerns and informing decisions that affect the climate, economy, and human health and safety. Atmospheric methane is a potent greenhouse gas (GHG) that contributes to global warming. While carbon dioxide is by far the dominant cause of the rise in global average temperatures, methane also plays a significant role because it absorbs more energy per unit mass than carbon dioxide does, giving it a disproportionately large effect on global radiative forcing. In addition to contributing to climate change, methane also affects human health as a precursor to ozone pollution in the lower atmosphere. Improving Characterization of Anthropogenic Methane Emissions in the United States summarizes the current state of understanding of methane emissions sources and the measurement approaches and evaluates opportunities for methodological and inventory development improvements. This report will inform future research agendas of various U.S. agencies, including NOAA, the EPA, the DOE, NASA, the U.S. Department of Agriculture (USDA), and the National Science Foundation (NSF).
Emissions reduction legislation relies upon 'bottom-up' accounting of industrial and biogenic greenhouse-gas (GHG) emissions at their sources. Yet, even for relatively well constrained industrial GHGs, global emissions based on 'top-down' methods that use atmospheric measurements often agree poorly with the reported bottom-up emissions. For emissions reduction legislation to be effective, it is essential that these discrepancies be resolved. Because emissions are regulated nationally or regionally, not globally, top-down estimates must also be determined at these scales. High-frequency atmospheric GHG measurements at well-chosen station locations record 'pollution events' above the background values that result from regional emissions. By combining such measurements with inverse methods and atmospheric transport and chemistry models, it is possible to map and quantify regional emissions. Even with the sparse current network of measurement stations and current inverse-modelling techniques, it is possible to rival the accuracies of regional 'bottom-up' emission estimates for some GHGs. But meeting the verification goals of emissions reduction legislation will require major increases in the density and types of atmospheric observations, as well as expanded inverse-modelling capabilities. The cost of this effort would be minor when compared with current investments in carbon-equivalent trading, and would reduce the volatility of that market and increase investment in emissions reduction.
Originally published in 1993, this book was the first to offer a comprehensive review of large eddy simulations (LES) - the history, state of the art, and promising directions for research. Among topics covered are fundamentals of LES; LES of incompressible, compressible, and reacting flows; LES of atmospheric, oceanic, and environmental flows; and LES and massivelt parallel computing. The book grew out of an international workshop that, for the first time, brought together leading researchers in engineering and geophysics to discuss developments and applications of LES models in their respective fields. It will be of value to anyone with an interest in turbulence modelling.