Thesis (MTech (Environmental Management))--Cape Peninsula University of Technology, 2015. / The integrity of natural air has been compromised due to the deposition of chemical, biological and particulate substances from natural and anthropogenic sources. Adverse health consequences arising from the exposure of plants, animals and human to elevated atmospheric concentrations have been reported severally. The ambient baseline levels of many air contaminants in urban and industrial layouts of many Africa cities, especially Zimbabwe have not been fully characterized. Information on levels of these contaminants and their real time variability is therefore scarce and scanty. In this study, the ambient air concentration levels of selected gaseous pollutants in the vicinity of a fertilizer production facility in Zimbabwe were investigated. Nine sampling stations were systematically and randomly identified for the measurement of selected air pollutants (SO2, NO2, and NH3) the fertilizer production factory to capture air quality data on all wind directions. The electrochemical Drager Sensors which rely on electrochemical measuring transducer for measuring concentration of gases under atmospheric conditions was used for the measurement of NH3, SO2, and NO2. The ambient air monitored was allowed to diffuse through a membrane into the sensor liquid electrolytes, containing a sensing electrode, a counter electrode, a reference electrode, and an electronic potentiostat-circuit which ensures constant electrical voltage between the sensing electrode and the reference electrode. The flow of electrons, generated by the reaction is proportional to the concentration of the measured gas. The observed concentrations of NH3, SO2, and NO2 measured within and around the study site were very variable. Levels of NH3 ranged between 0.36 - 7.36 ppm; corresponding values for SO2 and NO2 were 0.02 - 84.61 ppm and 0.61 - 34.78 ppm respectively. These concentrations were significantly higher (p < 0.05) than measured (NH3; 0.01 - 0.05 ppm: SO2; 0.03 - 0.18 ppm: NO2; 0.17 - 1.30 ppm) at the control sampling station about 5 km from the industry. Isokinetic and dissipation of the measured gases, governed by the processes of molecular diffusion and convection, confirmed a common pattern of distance dissipation. Thus, the cloud concentrations of NH3, SO2, and NO2 within the facility were higher than observed distances away from the fertilizer factory. / Zimbabwe Presidential Scholarship

This thesis has investigated the cascade impactor with its fractionating particulate capabilities for monitoring respirable particulate matter. Additionally, the cascade impactor was compared with the high volume sampler, the present acceptable method of measuring total suspended particulates.This two-year study analyzed the quarterly and annual geometric means, geometric standard deviations and mass median diameters of the cascade impactor concentrations. Correlation coefficients between the cascade impactor and high volume sampler were analyzed to reveal the relationship between the two sampling methods.Ball State UniversityMuncie, IN 47306

Beginning in March 1999 at Georgia Institute of Technology, the ASACA (Assessment of Spatial Aerosol Composition in Atlanta) program has provided PM₂. ₅ concentration and speciation using particle concentration monitoring in and around metropolitan Atlanta. Since 1999, three of the ASACA sites have collected PM₂. ₅ in an urban setting: Fort McPherson (FT, SW), South Dekalb (SD, SE), and Tucker (TU, NE). In January 2007, TU was retired and Fire Station 8 (FS8, NE) was employed as the new urban site. Starting in 2002, PM₂. ₅ concentrations have also been characterized at a rural site, Fort Yargo (YG). Water-soluble ionic species and carbonaceous species concentrations are collected daily on filters using a three-channel particulate composition monitor (PCM). From 1999 to 2008, average PM₂. ₅ concentrations range from 12.9 µg/m3 at YG to 15.4 µg/m3 at TU. Sulfate and organic matter are the main components of Atlanta PM, contributing around 26% and 31% respectively to PM mass. Overall ASACA data quality increased from around 5 in 1999 to a value of 9 in 2005. Seasonal PM data quality appears to be significantly affected by volatility of secondary aerosol species during warm months because ionic data quality regularly decreases in the summer. PM is more sensitive to total sulfate concentration than nitrate and ammonia year-round.

Both long-term and short-term exposure to fine particulate matter (PM2.5) has been shown to increase the rate of respiratory and cardiovascular illness, premature death, and hospital admissions from respiratory causes. It is important to understand what contributes to ambient PM2.5 level to establish effective regulation, and air quality model can provide guidance based on the best scientific understanding available. However, PM2.5 simulations in air quality models have often found performance less than desirable, particularly for organic carbon levels. Here, some of major shortcomings of current air quality model will be addressed and improved by using CMAQ, receptor models, and regression analysis. Detailed source apportionment of PM2.5 performed using the CMAQ-tracer method suggests that wood combustion and mobile sources are the largest sources of PM2.5, followed by meat cooking and industrial processes. Biases in emission estimates are investigated using tracer species, such as organic molecular markers and trace metals that are used in receptor models. Comparison of simulated and observed tracer species shows some consistent discrepancies, which enables us to quantify biases in emissions and improve CMAQ simulations. Secondary organic aerosol (SOA) is another topic that is investigated. CMAQ studies on organic aerosol usually underestimate organic carbon with larger than a 50% bias. Formation of aged aerosol from multigenerational semi-volatile organic carbon is added to CMAQ, significantly improving performance of organic aerosol simulations.

published_or_final_version / abstract / toc / Mechanical Engineering / Master / Master of Philosophy

published_or_final_version / Chemistry / Master / Master of Philosophy

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D.Phil. (Geography) / The Infrared Atmospheric Sounding Interferometer (lASI), operational in polar-orbit since 2006 on the European MetOp-A satellite, is the most advanced of its kind in space. It has been designed to provide soundings of the troposphere and lower stratosphere at nadir in a spectral interval of 0.25 em" across the range 645-2 760 em". Fine spectral sampling such as this is imperative in the sounding of trace gases. Since its launch, the routine retrievals of greenhouse, species from IASI measurements have made a valuable contribution to atmospheric chemistry studies at a global scale. The main contribution of this thesis is the development of a new trace gas retrieval scheme for IASI measurements. The goal was to improve on the global operational scheme in terms of the algorithm complexity, speed of calculation and spatial resolution achieved in the final solution. This schemedirectly retrieves column integrated trace gas densities at single field-of-view (FOV) from IASI measurements within a 10% accuracy limit. The scheme is built on the Bayesian framework of probability and based on the assumption that the inversion of total column values, as apposed to gas profiles, is a near-linear problem. Performance of the retrieval scheme is demonstrated on simulated noisy measurements for carbon monoxide (CO). Being a linear solution, the scheme is'highly dependent on the accuracy of the a priori. A statistical estimate of the a priori was computed using a principal component regression analysis with 50 eigenvectors. The corresponding root-mean-square (RMS) error of the a priori was calculated to be 9.3%. In general terms, the physical retrieval improved on the a priori, and sensitivity studies were performed to demonstrate the accuracy and stability of the retrieval scheme under a numberof perturbations. A full system characterization and error analysis is additionally preformed to elicidate the nature of this complex problem. The hyperspectral IASI measurements introduce a significant correlation error in the retrieval. The Absorption Line Cluster (ALC) channel selection method was developed in this thesis, to address the correlation error explicitly. When a first neighbour correlation factor of 0.71 is assumed in the measurement error covariance for the clusters of ALC channels, then most of the correlation error is removed in the retrieval. In conclusion, the total column trace gas retrieval scheme developed here is fast, simple, intuitive, transparent and robust. These characteristics together make it highly suitable for implementation in an operational environment intended for air quality monitoring on a regional scale.