7 resultados para methodologies for greenhouse gases emissions inventory and CO2 capture and storage
em DRUM (Digital Repository at the University of Maryland)
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
Tropospheric ozone (O3) adversely affects human health, reduces crop yields, and contributes to climate forcing. To limit these effects, the processes controlling O3 abundance as well as that of its precursor molecules must be fully characterized. Here, I examine three facets of O3 production, both in heavily polluted and remote environments. First, using in situ observations from the DISCOVER-AQ field campaign in the Baltimore/Washington region, I evaluate the emissions of the O3 precursors CO and NOx (NOx = NO + NO2) in the National Emissions Inventory (NEI). I find that CO/NOx emissions ratios derived from observations are 21% higher than those predicted by the NEI. Comparisons to output from the CMAQ model suggest that CO in the NEI is accurate within 15 ± 11%, while NOx emissions are overestimated by 51-70%, likely due to errors in mobile sources. These results imply that ambient ozone concentrations will respond more efficiently to NOx controls than current models suggest. I then investigate the source of high O3 and low H2O structures in the Tropical Western Pacific (TWP). A combination of in situ observations, satellite data, and models show that the high O3 results from photochemical production in biomass burning plumes from fires in tropical Southeast Asia and Central Africa; the low relative humidity results from large-scale descent in the tropics. Because these structures have frequently been attributed to mid-latitude pollution, biomass burning in the tropics likely contributes more to the radiative forcing of climate than previously believed. Finally, I evaluate the processes controlling formaldehyde (HCHO) in the TWP. Convective transport of near surface HCHO leads to a 33% increase in upper tropospheric HCHO mixing ratios; convection also likely increases upper tropospheric CH3OOH to ~230 pptv, enough to maintain background HCHO at ~75 pptv. The long-range transport of polluted air, with NO four times the convectively controlled background, intensifies the conversion of HO2 to OH, increasing OH by a factor of 1.4. Comparisons between the global chemistry model CAM-Chem and observations show that consistent underestimates of HCHO by CAM-Chem throughout the troposphere result from underestimates in both NO and acetaldehyde.
Resumo:
Terrestrial and oceanic biomass carbon sinks help reduce anthropogenic CO2 emissions and mitigate the long-term effect of increasing atmospheric CO2. Woody plants have large carbon pools because of their long residence time, however N availability can negatively impact tree responses to elevated CO2. Seasonal cycling of internal N in trees is a component that contributes to fitness especially in N limited environments. It involves resorption from senescing leaves of deciduous trees and storage as vegetative storage proteins (VSP) in perennial organs. Populus is a model organism for tree biology that efficiently recycles N. Bark storage proteins (BSP) are the most abundant VSP that serves as seasonal N reserves. Here I show how poplar growth is influenced by N availability and how growth is influenced by shoot competition for stored N reserves. I also provide data that indicates that auxin mediates BSP catabolism during renewed shoot growth. Understanding the components of N accumulation, remobilization and utilization can provide insights leading to increasing N use efficiency (NUE) of perennial plants.
Resumo:
This dissertation studies technological change in the context of energy and environmental economics. Technology plays a key role in reducing greenhouse gas emissions from the transportation sector. Chapter 1 estimates a structural model of the car industry that allows for endogenous product characteristics to investigate how gasoline taxes, R&D subsidies and competition affect fuel efficiency and vehicle prices in the medium-run, both through car-makers' decisions to adopt technologies and through their investments in knowledge capital. I use technology adoption and automotive patents data for 1986-2006 to estimate this model. I show that 92% of fuel efficiency improvements between 1986 and 2006 were driven by technology adoption, while the role of knowledge capital is largely to reduce the marginal production costs of fuel-efficient cars. A counterfactual predicts that an additional $1/gallon gasoline tax in 2006 would have increased the technology adoption rate, and raised average fuel efficiency by 0.47 miles/gallon, twice the annual fuel efficiency improvement in 2003-2006. An R&D subsidy that would reduce the marginal cost of knowledge capital by 25% in 2006 would have raised investment in knowledge capital. This subsidy would have raised fuel efficiency only by 0.06 miles/gallon in 2006, but would have increased variable profits by $2.3 billion over all firms that year. Passenger vehicle fuel economy standards in the United States will require substantial improvements in new vehicle fuel economy over the next decade. Economic theory suggests that vehicle manufacturers adopt greater fuel-saving technologies for vehicles with larger market size. Chapter 2 documents a strong connection between market size, measured by sales, and technology adoption. Using variation consumer demographics and purchasing pattern to account for the endogeneity of market size, we find that a 10 percent increase in market size raises vehicle fuel efficiency by 0.3 percent, as compared to a mean improvement of 1.4 percent per year over 1997-2013. Historically, fuel price and demographic-driven market size changes have had large effects on technology adoption. Furthermore, fuel taxes would induce firms to adopt fuel-saving technologies on their most efficient cars, thereby polarizing the fuel efficiency distribution of the new vehicle fleet.
Resumo:
As the semiconductor industry struggles to maintain its momentum down the path following the Moore's Law, three dimensional integrated circuit (3D IC) technology has emerged as a promising solution to achieve higher integration density, better performance, and lower power consumption. However, despite its significant improvement in electrical performance, 3D IC presents several serious physical design challenges. In this dissertation, we investigate physical design methodologies for 3D ICs with primary focus on two areas: low power 3D clock tree design, and reliability degradation modeling and management. Clock trees are essential parts for digital system which dissipate a large amount of power due to high capacitive loads. The majority of existing 3D clock tree designs focus on minimizing the total wire length, which produces sub-optimal results for power optimization. In this dissertation, we formulate a 3D clock tree design flow which directly optimizes for clock power. Besides, we also investigate the design methodology for clock gating a 3D clock tree, which uses shutdown gates to selectively turn off unnecessary clock activities. Different from the common assumption in 2D ICs that shutdown gates are cheap thus can be applied at every clock node, shutdown gates in 3D ICs introduce additional control TSVs, which compete with clock TSVs for placement resources. We explore the design methodologies to produce the optimal allocation and placement for clock and control TSVs so that the clock power is minimized. We show that the proposed synthesis flow saves significant clock power while accounting for available TSV placement area. Vertical integration also brings new reliability challenges including TSV's electromigration (EM) and several other reliability loss mechanisms caused by TSV-induced stress. These reliability loss models involve complex inter-dependencies between electrical and thermal conditions, which have not been investigated in the past. In this dissertation we set up an electrical/thermal/reliability co-simulation framework to capture the transient of reliability loss in 3D ICs. We further derive and validate an analytical reliability objective function that can be integrated into the 3D placement design flow. The reliability aware placement scheme enables co-design and co-optimization of both the electrical and reliability property, thus improves both the circuit's performance and its lifetime. Our electrical/reliability co-design scheme avoids unnecessary design cycles or application of ad-hoc fixes that lead to sub-optimal performance. Vertical integration also enables stacking DRAM on top of CPU, providing high bandwidth and short latency. However, non-uniform voltage fluctuation and local thermal hotspot in CPU layers are coupled into DRAM layers, causing a non-uniform bit-cell leakage (thereby bit flip) distribution. We propose a performance-power-resilience simulation framework to capture DRAM soft error in 3D multi-core CPU systems. In addition, a dynamic resilience management (DRM) scheme is investigated, which adaptively tunes CPU's operating points to adjust DRAM's voltage noise and thermal condition during runtime. The DRM uses dynamic frequency scaling to achieve a resilience borrow-in strategy, which effectively enhances DRAM's resilience without sacrificing performance. The proposed physical design methodologies should act as important building blocks for 3D ICs and push 3D ICs toward mainstream acceptance in the near future.