Chemistry & Biochemistry
Permanent URI for this communityhttp://hdl.handle.net/1903/11812
Browse
3 results
Search Results
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 Simulation and Projection of Global Temperature Change and Recovery of Extra-polar Ozone using Multiple Linear Regression Models(2022) McBride, Laura Anne; Salawitch, Ross J.; Chemistry; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Climate change and the depletion of the ozone layer are two important global environmental problems caused by the release of gases into the atmosphere. This dissertation uses multiple linear regression to quantify the natural and human components that affect Earth’s global mean surface temperature (GMST) and the thickness of the ozone layer. To analyze changes in Earth’s climate, the Empirical Model of Global Climate (EM-GC) is used to simulate and project variations in GMST. Numerous scenarios of greenhouse gas and aerosol emissions are considered to analyze the probability of achieving the 1.5 and 2.0°C warming goals set by the Paris Agreement. There is a 53% likelihood of the rise in GMST staying below 1.5°C if the world follows the greenhouse gas and aerosol emissions in SSP1-2.6, and a 64% probability of staying below 2.0°C if the world follows SSP4-3.4. The amount of warming attributed to humans from 1975 to 2014 based on the EM-GC is 0.157°C decade−1 (range of 0.120 to 0.195°C decade−1). Multi-model output from the Coupled Model Intercomparison Project Phase 6 (CMIP6) indicates humans contributed 0.221°C decade−1 (0.151 to 0.299°C decade−1) of warming from 1975 to 2014, which is notably faster warming than inferred from the historical climate record. The rise in GMST at 2×preindustrial concentrations of carbon dioxide is also examined. The effects of increasing methane emissions are discussed, as well as the timeline for emitting the remainder of the world’s carbon budget. Humans can emit another 150 ± 79 Gt C after 2019 to have a 66% likelihood of limiting warming to 1.5°C and another 400 ± 104 Gt C to have the same probability of limiting warming to 2.0°C. Given the estimated emission of 11.7 Gt C per year for 2019 due to human activities, carbon and methane emissions must be severely curtailed in the next 10 years to achieve the 1.5°C goal of the Paris Agreement. The results from the EM-GC are compared to other reduced complexity climate models (RCMs) as part of an international collaboration, as well as multi-model output from CMIP6. All RCMs, including the EM-GC, show that the CMIP6 global climate models warm too quickly. To analyze changes in the ozone layer due to human activities, a multiple linear regression model is used that includes equivalent effective stratospheric chlorine (EESC) as a measure of the human effect on ozone. Results using the updated EESC calculation indicate anthropogenic, very short-lived chlorine (VSL Cl) species not regulated by the Montreal Protocol have already caused a seven-year delay in the recovery of the ozone layer. Future simulations indicate that if human emissions of VSL Cl species continue to rise, the recovery of the ozone layer could be delayed up to 25 years.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.