3 resultados para GREENHOUSE GASES

em DRUM (Digital Repository at the University of Maryland)


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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.

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Carbon and nitrogen loading to streams and rivers contributes to eutrophication as well as greenhouse gas (GHG) production in streams, rivers and estuaries. My dissertation consists of three research chapters, which examine interactions and potential trade-offs between water quality and greenhouse gas production in urban streams of the Chesapeake Bay watershed. My first research project focused on drivers of carbon export and quality in an urbanized river. I found that watershed carbon sources (soils and leaves) contributed more than in-stream production to overall carbon export, but that periods of high in-stream productivity were important over seasonal and daily timescales. My second research chapter examined the influence of urban storm-water and sanitary infrastructure on dissolved and gaseous carbon and nitrogen concentrations in headwater streams. Gases (CO2, CH4, and N2O) were consistently super-saturated throughout the course of a year. N2O concentrations in streams draining septic systems were within the high range of previously published values. Total dissolved nitrogen concentration was positively correlated with CO2 and N2O and negatively correlated with CH4. My third research chapter examined a long-term (15-year) record of GHG emissions from soils in rural forests, urban forest, and urban lawns in Baltimore, MD. CO2, CH4, and N2O emissions showed positive correlations with temperature at each site. Lawns were a net source of CH4 + N2O, whereas forests were net sinks. Gross CO2 fluxes were also highest in lawns, in part due to elevated growing-season temperatures. While land cover influences GHG emissions from soils, the overall role of land cover on this flux is very small (< 0.5%) compared with gases released from anthropogenic sources, according to a recent GHG budget of the Baltimore metropolitan area, where this study took place.

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This dissertation analyzes how individuals respond to the introduction of taxation aimed to reduce vehicle pollution, greenhouse gases and traffic. The first chapter analyzes a vehicle registration tax based on emissions of carbon dioxide (CO2), a major greenhouse gas, adopted in the UK in 2001 and subject to major changes in the following years. I identify the impact of the policy on new vehicle registrations and carbon emissions, compared to alternative measures. Results show that consumers respond to the tax by purchasing cleaner cars, but a carbon tax generating the same revenue would further reduce carbon emissions. The second chapter looks at a pollution charge (polluting vehicles pay to enter the city) and a congestion charge (all vehicles pay) adopted in 2008 and 2011 in Milan, Italy, and how they affected the concentration of nitrogen dioxides (NOx). I use data from pollution monitoring stations to measure the change between areas adopting the tax and other areas. Results show that in the first quarter of their introduction, both policies decreased NOx concentration in a range of -8% and -5%, but the effect declines over time, especially in the case of the pollution charge. The third chapter examines a trial conducted in 2005 in the Seattle, WA, area, in which vehicle trips by 276 volunteer households were recorded with a GPS device installed in their vehicles. Households received a monetary endowment which they used to pay a toll for each mile traveled: the toll varied with the time of the day, the day of the week and the type of road used. Using information on driving behavior, I show that in the first week a $0.10 toll per mile reduces the number of miles driven by around 7%, but the effect lasts only few weeks at most. The effect is mainly driven by a reduction in highway miles during trips from work to home, and it is strongly influenced by past driving behavior, income, the size of the initial endowment and the number of children in the household.