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- Creators: Phelan, Patrick
- Member of: ASU Electronic Theses and Dissertations
- Resource Type: Text
Description
Understanding and predicting climate changes at the urban scale have been an important yet challenging problem in environmental engineering. The lack of reliable long-term observations at the urban scale makes it difficult to even assess past climate changes. Numerical modeling plays an important role in filling the gap of observation and predicting future changes. Numerical studies on the climatic effect of desert urbanization have focused on basic meteorological fields such as temperature and wind. For desert cities, urban expansion can lead to substantial changes in the local production of wind-blown dust, which have implications for air quality and public health. This study expands the existing framework of numerical simulation for desert urbanization to include the computation of dust generation related to urban land-use changes. This is accomplished by connecting a suite of numerical models, including a meso-scale meteorological model, a land-surface model, an urban canopy model, and a turbulence model, to produce the key parameters that control the surface fluxes of wind-blown dust. Those models generate the near-surface turbulence intensity, soil moisture, and land-surface properties, which are used to determine the dust fluxes from a set of laboratory-based empirical formulas. This framework is applied to a series of simulations for the desert city of Erbil across a period of rapid urbanization. The changes in surface dust fluxes associated with urbanization are quantified. An analysis of the model output further reveals the dependence of surface dust fluxes on local meteorological conditions. Future applications of the models to environmental prediction are discussed.
ContributorsTahir, Sherzad Tahseen (Author) / Huang, Huei-Ping (Thesis advisor) / Phelan, Patrick (Committee member) / Herrmann, Marcus (Committee member) / Chen, Kangping (Committee member) / Clarke, Amanda (Committee member) / Arizona State University (Publisher)
Created2019
Description
Many expect renewable energy technologies to play a leading role in a sustainable energy supply system and to aid the shift away from an over-reliance on traditional hydrocarbon resources in the next few decades. This dissertation develops environmental, policy and social models to help understand various aspects of photovoltaic (PV) technologies. The first part of this dissertation advances the life cycle assessment (LCA) of PV systems by expanding the boundary of included processes using hybrid LCA and accounting for the technology-driven dynamics of environmental impacts. Hybrid LCA extends the traditional method combining bottom-up process-sum and top-down economic input-output (EIO) approaches. The embodied energy and carbon of multi-crystalline silicon photovoltaic systems are assessed using hybrid LCA. From 2001 to 2010, the embodied energy and carbon fell substantially, indicating that technological progress is realizing reductions in environmental impacts in addition to lower module price. A variety of policies support renewable energy adoption, and it is critical to make them function cooperatively. To reveal the interrelationships among these policies, the second part of this dissertation proposes three tiers of policy architecture. This study develops a model to determine the specific subsidies required to support a Renewable Portfolio Standard (RPS) goal. The financial requirements are calculated (in two scenarios) and compared with predictable funds from public sources. A main result is that the expected investments to achieve the RPS goal far exceed the economic allocation for subsidy of distributed PV. Even with subsidies there are often challenges with social acceptance. The third part of this dissertation originally develops a fuzzy logic inference model to relate consumers' attitudes about the technology such as perceived cost, maintenance, and environmental concern to their adoption intention. Fuzzy logic inference model is a type of soft computing models. It has the advantage of dealing with imprecise and insufficient information and mimicking reasoning processes of human brains. This model is implemented in a case study of residential PV adoption using data through a survey of homeowners in Arizona. The output of this model is the purchasing probability of PV.
ContributorsZhai, Pei (Author) / Williams, Eric D. (Thesis advisor) / Allenby, Braden (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2010
Description
The applications utilizing nanoparticles have grown in both industrial and academic areas because of the very large surface area to volume ratios of these particles. One of the best ways to process and control these nanoparticles is fluidization. In this work, a new microjet and vibration assisted (MVA) fluidized bed system was developed in order to fluidize nanoparticles. The system was tested and the parameters optimized using two commercially available TiO2 nanoparticles: P25 and P90. The fluidization quality was assessed by determining the non-dimensional bed height as well as the non-dimensional pressure drop. The non-dimensional bed height for the nanosized TiO2 in the MVA system optimized at about 5 and 7 for P25 and P90 TiO2, respectively, at a resonance frequency of 50 Hz. The non-dimensional pressure drop was also determined and showed that the MVA system exhibited a lower minimum fluidization velocity for both of the TiO2 types as compared to fluidization that employed only vibration assistance. Additional experiments were performed with the MVA to characterize the synergistic effects of vibrational intensity and gas velocity on the TiO2 P25 and P90 fluidized bed heights. Mathematical relationships were developed to correlate vibrational intensity, gas velocity, and fluidized bed height in the MVA. The non-dimensional bed height in the MVA system is comparable to previously published P25 TiO2 fluidization work that employed an alcohol in order to minimize the electrostatic attractions within the bed. However, the MVA system achieved similar results without the addition of a chemical, thereby expanding the potential chemical reaction engineering and environmental remediation opportunities for fluidized nanoparticle systems.
In order to aid future scaling up of the MVA process, the agglomerate size distribution in the MVA system was predicted by utilizing a force balance model coupled with a two-fluid model (TFM) simulation. The particle agglomerate size that was predicted using the computer simulation was validated with experimental data and found to be in good agreement.
Lastly, in order to demonstrate the utility of the MVA system in an air revitalization application, the capture of CO2 was examined. CO2 breakthrough time and adsorption capacities were tested in the MVA system and compared to a vibrating fluidized bed (VFB) system. Experimental results showed that the improved fluidity in the MVA system enhanced CO2 adsorption capacity.
In order to aid future scaling up of the MVA process, the agglomerate size distribution in the MVA system was predicted by utilizing a force balance model coupled with a two-fluid model (TFM) simulation. The particle agglomerate size that was predicted using the computer simulation was validated with experimental data and found to be in good agreement.
Lastly, in order to demonstrate the utility of the MVA system in an air revitalization application, the capture of CO2 was examined. CO2 breakthrough time and adsorption capacities were tested in the MVA system and compared to a vibrating fluidized bed (VFB) system. Experimental results showed that the improved fluidity in the MVA system enhanced CO2 adsorption capacity.
ContributorsAn, Keju (Author) / Andino, Jean (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Adrian, Ronald (Committee member) / Emady, Heather (Committee member) / Kasbaoui, Mohamed (Committee member) / Arizona State University (Publisher)
Created2019