Chemistry & Biochemistry Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2752
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Item INVESTIGATION OF AMBIENT METHANE CONCENTRATION, SOURCES, AND TRENDS IN THE BALTIMORE-WASHINGTON REGION(2024) Sahu, Sayantan; Dickerson, Russell Professor; Chemistry; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Methane, an important and not yet fully understood greenhouse gas, has a global warming potential 25 times that of carbon dioxide over 100 years, although with an atmospheric lifetime much shorter than carbon dioxide. Controlling methane emissions is a useful way to avoid some of the adverse effects of climate change at least on short time scales. Natural sources include wetlands, ruminants, and wildfires, while anthropogenic sources include the production, transmission, distribution, and use of natural gas, livestock, and landfills. In the US, natural gas and petroleum systems, anthropogenic sources, are the second-largest source of methane emissions. Urban areas are a significant source of anthropogenic methane emissions, primarily fugitive emissions from natural gas distribution and usage.We studied methane observations from five towers in the Baltimore-Washington (BWR) region – two urban towers ARL (Arlington, VA), NEB (Northeast Baltimore, MD), and one rural tower, BUC (Bucktown, MD). Methane measurements from these three towers displayed distinct seasonal and diurnal cycles with maxima at night and in the early morning, which indicated significant local emissions. We concluded from our analysis that anthropogenic methane emissions dominate at the urban sites whereas wetland emissions dominate at the rural site. We compared observed enhancements (mole fractions above the 5th percentile) to simulated methane enhancements using the WRF-STILT model driven by two EDGAR inventories – EDGAR 4.2 and EDGAR 5.0. We did a similar comparison between model and observations with vertical gradients. We concluded that both versions of EDGAR underestimated the regional anthropogenic emissions of methane, but version 5.0 had a more accurate spatial representation. We ran the model with WETCHARTs to account for wetland emissions which significantly reduced the bias between model and observations especially in summer at the rural site. We investigated winter methane observations from three towers in the BWR including a ten-year record, 2013-2022, from BUC, located ~100 km southeast of these urban areas. We combined the observations with a HYSPLIT clustering analysis for all years to determine the major synoptic patterns influencing methane mixing ratios at BUC. For methane concentrations above global background, the cluster analysis revealed four characteristic pathways of transport into BUC – from the west (W), southwest (SW), northwest (NW), and east (E) and these showed significant differences in methane mixing ratios. We corroborated our conclusions from BUC using 2018-2022 data from towers in Stafford, Virginia (SFD), and Thurmont, Maryland (TMD); results confirmed the influence of synoptic pattern, typically associated with frontal passage, on methane. No significant temporal trend over the global background was detected overall or within any cluster. For BUC, low concentrations were observed for air off the North Atlantic Ocean (E cluster) and flowing rapidly behind cold fronts (NW cluster). High methane mixing ratios were observed, as expected, in the W cluster due to the proximity of the BWR and oil and gas operations in the Marcellus. Less expected were high mixing ratios for the SW cluster – we attribute these to agricultural sources in North Carolina. Swine production, ~500 km to the SW, impacts methane in eastern Maryland as much or more than local urban emissions plus oil and gas operations 100–300 km to the west; this supports the high end of emission estimates for animal husbandry and suggests strategies for future research and mitigation.Item 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.Item QUANTITATIVE ANALYSIS OF THE ATMOSPHERIC OXIDATION OF ISOPRENE USING MODELS AND MEASUREMENTS: IMPACTS ON SURFACE OZONE(2019) Marvin, Margaret Rosemary; Wolfe, Glenn; Salawitch, Ross; Chemistry; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The oxidation of isoprene – one of the most abundant volatile organic compounds (VOCs) in our atmosphere – significantly impacts the formation of surface ozone, which is detrimental to public health. Computer models simulate the complex relationships between ozone and VOCs like isoprene and are used to guide policy decisions directed at improving ozone. However, uncertainties in the emissions and chemistry of isoprene limit the accuracy of modeled ozone. This body of work comprises a quantitative analysis of atmospheric isoprene oxidation that strives to identify and improve such uncertainties through the combination of models with measurements. Measurements used in this work mainly comprise in situ observations from the Southeast Nexus (SENEX) aircraft campaign, which sampled atmospheric composition across the isoprene-rich summertime Southeast US. I have prepared two models – the Framework for 0-D Atmospheric Modeling (F0AM) and the Comprehensive Air Quality Model with Extensions (CAMx) – to drive simulations of atmospheric isoprene oxidation, which are evaluated against observations from SENEX. Using F0AM, a photochemical box model, I demonstrate that several commonly-used mechanisms significantly underestimate measured mixing ratios of formaldehyde, a high-yield product of isoprene oxidation, by 0.5–1 ppb across a wide range of NOx conditions. The consistent underestimation of formaldehyde suggests a deficit of VOC oxidation among all considered mechanisms. Although the cause for this deficit remains elusive, I provide recommendations for improving the simulated production of formaldehyde upon isoprene oxidation in the Carbon Bond version 6 revision 2 (CB6r2) mechanism, commonly used for air quality modeling. Using CAMx, a three-dimensional chemical transport model, I produce a standard air quality modeling scenario that simulates atmospheric composition across the continental US for the summer of 2013. Evaluation of this scenario reveals that the emissions of isoprene from the Biogenic Emissions Inventory System (BEIS) are underestimated in the Southeast US by at least 40%. Finally, implementation of improvements in the emissions and chemistry of isoprene within the CAMx modeling framework increases the net photochemical production of surface ozone by up to 0.5 ppb hr−1 and shifts surface ozone production regimes more NOx-limited, relative to the standard platform for regional air quality modeling.Item AN EXAMINATION OF HYDROXYL RADICAL: OUR CURRENT UNDERSTANDING OF THE OXIDATIVE CAPACITY OF THE TROPOSPHERE THROUGH EMPIRICAL, BOX, AND GLOBAL MODELING APPROACHES(2016) Nicely, Julie Megan; Salawitch, Ross J.; Chemistry; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Hydroxyl radical (OH) is the primary oxidant in the troposphere, initiating the removal of numerous atmospheric species including greenhouse gases, pollutants that are detrimental to human health, and ozone-depleting substances. Because of the complexity of OH chemistry, models vary widely in their OH chemistry schemes and resulting methane (CH4) lifetimes. The current state of knowledge concerning global OH abundances is often contradictory. This body of work encompasses three projects that investigate tropospheric OH from a modeling perspective, with the goal of improving the tropospheric community’s knowledge of the atmospheric lifetime of CH4. First, measurements taken during the airborne CONvective TRansport of Active Species in the Tropics (CONTRAST) field campaign are used to evaluate OH in global models. A box model constrained to measured variables is utilized to infer concentrations of OH along the flight track. Results are used to evaluate global model performance, suggest against the existence of a proposed “OH Hole” in the tropical Western Pacific, and investigate implications of high O3/low H2O filaments on chemical transport to the stratosphere. While methyl chloroform-based estimates of global mean OH suggest that models are overestimating OH, we report evidence that these models are actually underestimating OH in the tropical Western Pacific. The second project examines OH within global models to diagnose differences in CH4 lifetime. I developed an approach to quantify the roles of OH precursor field differences (O3, H2O, CO, NOx, etc.) using a neural network method. This technique enables us to approximate the change in CH4 lifetime resulting from variations in individual precursor fields. The dominant factors driving CH4 lifetime differences between models are O3, CO, and J(O3-O1D). My third project evaluates the effect of climate change on global fields of OH using an empirical model. Observations of H2O and O3 from satellite instruments are combined with a simulation of tropical expansion to derive changes in global mean OH over the past 25 years. We find that increasing H2O and increasing width of the tropics tend to increase global mean OH, countering the increasing CH4 sink and resulting in well-buffered global tropospheric OH concentrations.Item Development, enhancement, and evaluation of aircraft measurement techniques for criteria pollutants(2014) Brent, Lacey Cluff; Dickerson, Russell R; Chemistry; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The atmospheric contaminants most harmful to human health are designated Criteria Pollutants. To help Maryland attain the national ambient air quality standards (NAAQS) for Criteria Pollutants, and to improve our fundamental understanding of atmospheric chemistry, I conducted aircraft measurements in the Regional Atmospheric Measurement Modeling Prediction Program (RAMMPP). These data are used to evaluate model simulations and satellite observations. I developed techniques for improving airborne observation of two NAAQS pollutants, particulate matter (PM) and nitrogen dioxide (NO2). While structure and composition of organic aerosol are important for understanding PM formation, the molecular speciation of organic ambient aerosol remains largely unknown. The spatial distribution of reactive nitrogen is likewise poorly constrained. To examine water-soluble organic aerosol (WSOA) during an air pollution episode, I designed and implemented a shrouded aerosol inlet system to collect PM onto quartz fiber filters from a Cessna 402 research aircraft. Inlet evaluation conducted during a side-by-side flight with the NASA P3 demonstrated agreement to within 30%. An ion chromatographic mass spectrometric method developed using the NIST Standard Reference Material (SRM) 1649b Urban Dust, as a surrogate material resulted in acidic class separation and resolution of at least 34 organic acids; detection limits approach pg/g concentrations. Analysis of aircraft filter samples resulted in detection of 8 inorganic species and 16 organic acids of which 12 were quantified. Aged, re-circulated metropolitan air showed a greater number of dicarboxylic acids compared to air recently transported from the west. While the NAAQS for NO2 is rarely exceeded, it is a precursor molecule for ozone, America's most recalcitrant pollutant. Using cavity ringdown spectroscopy employing a light emitting diode (LED), I measured vertical profiles of NO¬2 (surface to 2.5 km) west (upwind) of the Baltimore/Washington, area in the morning, and east (downwind) in the afternoon. Column contents (altitude integrals of concentration) were remarkably similar (≈3x1015 molecules cm−2). These measurements indicate that NO2 is widely distributed over the eastern US and help quantify the regional nature of smog events and prove extensive interstate transport of pollutants. These results were used to help shape air pollution control policy based on solid science.Item Advanced Receptor Models for Exploiting Highly Time Resolved Data Acquired in the EPA Supersite Project(2012) Ke, Haohao; Ondov, John; Chemistry; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Receptor models have been widely used in air quality studies to identify pollution sources and estimate their contributions. A common problem for most current receptor models is insufficient consideration of realistic constraints such as can be obtained from emission inventories, chemical composition profiles of the sources, and the physics of plume dispersion. In addition, poor resolving of collinear sources was often found. With the high quality time-, composition-, and size-resolved measurements during the EPA Supersite project, efforts towards resolving nearby industrial sources were made by combinative use of Positive Matrix Factorization (PMF) and the Pseudo-Deterministic Receptor Model (PDRM). The PMF modeling of Baltimore data in September 2001 revealed coal-fired and oil-fired power plants (CFPP and OFPP, respectively) with significant cross contamination, as indicated by the high Se/Ni ratio in the OFPP profile. Nevertheless, the PMF results provided a good estimate of background and the PMF-constrained emission rates well seeded the trajectory-driven PDRM modeling. Using NOx as the tracer gas for χ/Q tuning, ultimately resolved emissions from individual stacks exhibited acceptable tracer ratios and the emission rates of metals generally agreed with the TRI estimates. This approach was later applied to two metal pollution episodes in St. Louis during in November 2001 and March 2002 and met a similar success. As NOx measurements were unavailable at those metal-production facilities, highly-specific tracer metals (i.e., Cd, Zn, and Cu) for the corresponding units were used to tune χ/Qs and their contributions were well resolved with the PMF-seeded PDRM. Opportunistically a PM2.5 excursion during a windless morning in November 2002 allowed the extraction of an in-situ profile of vehicular emissions in Baltimore. The profiles obtained by direct peak observation, windless model linear regression (WMA), PMF, and UNMIX were comparable and the WMA profile showed the best predictions for non-traffic tracers. Besides, an approach to evaluate vehicular emission factors was developed by receptor measurements under windless conditions. Using SVOC tracers, seasonal variations of traffic and other sources including coal burning, heating, biomass burning, and vegetation were investigated by PMF and in particular the November traffic profile was consistent with the WMA profile obtained earlier.