US presidential approval of Federal Emergency Management Agency (FEMA) funding has been the subject of much research that largely has been inconclusive or contradictor as it relates to whether funds may have been distributed in a biased way through the use of presidential discretionary power. The purpose of this study was to explore if or to what degree US presidents acted in a potentially biased manner with the approval of FEMA approvals during election years in election battleground states. This study was an exploration of whether there was presidential political favoritism in approving FEMA funding from 1996-2012. The theoretical constructs for this study were group justification bias and social identity theory. Study data were obtained through freedom of information requests from FEMA for access to every gubernatorial request for FEMA aid from 1995-2012 resulting in 1137 records. Data were analyzed using chi-square as tests of association. By measuring the presidential discretionary choice of approvals or turndowns with other variables highlighted what, if any, associations existed. This enables a reasonable person to form their own perception on whether bias was present, or not, based on the results. A key finding illuminated an association between presidential party affiliation and public assistance (p = .005), 1 type of FEMA aid. The study did not, however, indicate any statistical association between the award of FEMA hazard mitigation funding and presidential bias. The positive social change implication stemming from this study includes information to policy makers regarding how FEMA aid is granted, which could assist in an evaluation of the FEMA aid process and approval in the future.

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A novel technique for measuring gas temperature and spectral particle emissivity in high-temperature gas-particle streams is presented. The main application of this optical sensor is to improve the process control of batch unit operations, such as steelmaking furnaces. The spectral emission profile of CO and CO2 and the continuous particle emission in the 3.5 to 5 μm wavelength region was recorded and analyzed in real time with a low-resolution passive sensor. The sensor consisted of light collecting optics, a dispersion element (grating spectrometer) and a 64-pixel pyroelectric array. Wavelength and radiance calibrations were performed. The temperature of the gas-particle medium (Tg+p) followed from the least-squares minimization of the difference between the measured radiance in the 4.56-4.7 μm region –which saturates due to the large CO2 concentrations and path lengths in industrial furnaces– and the corresponding blackbody radiance. Particle emissivity (εp) was calculated at 3.95 μm from an asymptotic approximation of the Radiative Transfer Equation that yields the emerging radiance from a semi-infinite particle cloud. The major source of error in the magnitude of Tg+p and εp could come from particle scattering. Through the method of embedded invariance an expression was developed to estimate the lowering effect of particle size and volume fraction on the saturation of the 4.56-4.7 μm CO2 emission region. An iterative procedure for correcting the values of the gas-particle temperature and particle emissivity was applied to the datasets from the two industrial tests. Results from the measurement campaigns with the infrared sensor prototype at two full-scale furnaces are presented. A proof-of-concept test at a coal-fired boiler for electricity production was followed by more extensive measurements at a Basic Oxygen Furnace (BOF) for steelmaking. The second test provided temperature and particle emissivity profiles for eight heats, which highlighted the simplicity of the technique in obtaining in-situ measurements for modeling studies. Through the analysis of the particle emissivity profile in the BOF and the definition of a new variable –the minimum carbon time– a novel end-point strategy to stop the injection of high-purity oxygen during low-carbon heats in BOF converters was proposed.

A novel technique for measuring gas temperature and spectral particle emissivity in high-temperature gas-particle streams is presented. The main application of this optical sensor is to improve the process control of batch unit operations, such as steelmaking furnaces. The spectral emission profile of CO and CO2 and the continuous particle emission in the 3.5 to 5 μm wavelength region was recorded and analyzed in real time with a low-resolution passive sensor. The sensor consisted of light collecting optics, a dispersion element (grating spectrometer) and a 64-pixel pyroelectric array. Wavelength and radiance calibrations were performed. The temperature of the gas-particle medium (Tg+p) followed from the least-squares minimization of the difference between the measured radiance in the 4.56-4.7 μm region –which saturates due to the large CO2 concentrations and path lengths in industrial furnaces– and the corresponding blackbody radiance. Particle emissivity (εp) was calculated at 3.95 μm from an asymptotic approximation of the Radiative Transfer Equation that yields the emerging radiance from a semi-infinite particle cloud. The major source of error in the magnitude of Tg+p and εp could come from particle scattering. Through the method of embedded invariance an expression was developed to estimate the lowering effect of particle size and volume fraction on the saturation of the 4.56-4.7 μm CO2 emission region. An iterative procedure for correcting the values of the gas-particle temperature and particle emissivity was applied to the datasets from the two industrial tests. Results from the measurement campaigns with the infrared sensor prototype at two full-scale furnaces are presented. A proof-of-concept test at a coal-fired boiler for electricity production was followed by more extensive measurements at a Basic Oxygen Furnace (BOF) for steelmaking. The second test provided temperature and particle emissivity profiles for eight heats, which highlighted the simplicity of the technique in obtaining in-situ measurements for modeling studies. Through the analysis of the particle emissivity profile in the BOF and the definition of a new variable –the minimum carbon time– a novel end-point strategy to stop the injection of high-purity oxygen during low-carbon heats in BOF converters was proposed.