Theses and Dissertations from UMD

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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM

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    QUANTIFYING THE EMISSIONS OF CARBON DIOXIDE (CO2), CARBON MONOXIDE (CO), AND NITROGEN OXIDES (NOx) FROM HUMAN ACTIVITIES: TOP-DOWN AND BOTTOM-UP APPROACHES
    (2021) Ahn, Doyeon; Salawitch, Ross J.; Dickerson, Russell R.; Chemistry; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This dissertation encompasses three projects that quantify the emissions of greenhouse gases and air pollutants from human activities. In the first project, we use the aircraft-based mass balance (MB) approach to quantify the emission of CO2 from the Baltimore, MD-Washington, D.C. (Balt-Wash) area during winter 2015. Based on analysis of aircraft observations using the MB-based top-down approach, we estimate the emission of 1.9 ± 0.3 million metric tons (MtC) of CO2 due to the combustion of fossil fuels (FFCO2) from the Balt-Wash region February 2015. Our value is 14% lower than the 2.2 ± 0.3 MtC mean estimate of FFCO2 from four bottom-up inventories often used to drive climate policy. In the second project, we investigate the declines in the emissions of CO2 and CO from the Balt-Wash area during the COVID-19 pandemic. We estimate using the MB approach applied to aircraft data that the emission of CO2 and CO declined by 29–32% and by 27–37%, respectively, from February 2020 (prior to COVID-19 lockdowns) to April – May 2020 (in the midst of COVID-19 pandemic). We show that for February 2020, two bottom-up emission inventories (EDGARv50 and the state of Maryland inventory) underestimate CO2 emissions by 13–18%, whereas two bottom-up inventories (EDGARv50 and NEI2017) overestimate the emission of CO by 54–66%. We show that the major contributor to the overestimation of the emission of CO in the bottom-up inventory is due to the mobile (i.e., cars and trucks) sector. The third project examines the emissions of CO2 and NOx from the U.S. power sector. We quantify reductions in the emissions due to the following two factors: the direct impact of COVID-19; changes in the fuel-mix profile during 2015-2020 (i.e., switching from coal to natural gas). For the contiguous U.S., we estimate the impact of COVID-19 in April 2020 to be the decline of 18±4% on the emission of CO2 and 22± 5% on the emission of NOx. For the same month, we estimate the impact of the fuel-mix transition to be declines of 26% on the emission of CO2 and 42% on the emission of NOx.
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    Assimilation of trace gas retrievals with the Local Ensemble Transform Kalman Filter
    (2009) Kuhl, David Derieg; Kalnay, Eugenia; Szunyogh, Istvan; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Over the 50 year history of Numerical Weather Prediction (NWP), the focus has been on the modeling and prediction of meteorological parameters such as surface pressure, temperature, wind, and precipitation. However, due to concerns over pollution and to recent advancements in satellite technologies, an increasing number of NWP systems have been upgraded to include capabilities to analyze and predict the concentration of trace gases. This dissertation explores some of the specific issues that have to be addressed for an efficient modeling of the concentration of the trace gases. These issues include modeling the effects of convective mixing on the concentration of the trace gases and the multivariate assimilation of space-based observations of the concentration of the trace gases. In this dissertation, we assimilate observations of the concentration of trace gases with an implementation of the Local Ensemble Transform Kalman Filter (LETKF) data assimilation system on the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) NWP model. We use a modified version of the NCEP GFS model that was operational in 2004 at resolution T62/L28. We modify the model by adding parameterization for the process of convective mixing of the trace gases. We consider two specific trace gases: ozone (O3) and carbon monoxide (CO). We incorporate these gases into the model by using 3-dimensional time-dependent O3 and CO production-loss values from the Real-time Air Quality Modeling System (RAQMS) global chemical model. The O3 observations we assimilate are from the Solar Backscatter UltraViolet generation 2 (SBUV/2) satellite instrument (version 8) flown on the NOAA 16 and 17 satellites. The CO observations we assimilate are from the Measurements Of Pollution In The Troposphere (MOPITT) instrument (version 3) flown on the NASA TERRA satellite. We also develop a new observation operator for the assimilation of retrievals with the LETKF. We carry out numerical experiment for the period between 000UTC 1 July 2004 to 000UTC 15 August in the summer of 2004. The analysis and forecast impact of the assimilation of trace gas observations on the meteorological fields is assessed by comparing the analyses and forecasts to the high resolution operational NCEP GFS analyses and to radiosonde observations. The analysis and forecast impact on the trace gas fields is assessed by comparing the analyzed and predicted fields to observations collected during the Intercontinental Chemical Transport Experiment (INTEX-A) field mission. The INTEX-A field mission was conducted to characterize composition of pollution over North America, thus providing us with ozonesonde and aircraft based verification data. We find that adding the process of convective mixing to the parameterization package of the model and the assimilation of observations of the trace gases improves the analysis and forecast of the concentration of the trace gases. In particular, our system is more accurate in quantifying the concentration of O3 in the troposphere than the original NCEP GFS. Also, our system is competitive with the state-of-the-art RAQMS atmospheric chemical model in analyzing the concentration of O3 and CO throughout the full atmospheric model column. The assimilation of O3 and CO observations has a mixed impact on the analysis and forecast of the meteorological fields. We find that most of the negative impact on the meteorological fields can be eliminated, without much reduction to the positive impact on the trace gas fields, by inflating the prescribed variance of the trace gas observations. The appendices of this dissertation reproduces two papers on related research. The first paper covers the northward front movement and rising surface temperatures in the great planes. The second paper covers the assessment of predictability with a Local Ensemble Kalman Filter.