Digitized by Kansas Correctional Industries

Digitized by Kansas Correctional Industries

In February 1994, EPA proposed to "refine" its carbon monoxide (CO) hot spot model, CAL3QHC, to increase its accuracy and reliability. Currently, this proposal includes using hourly meteorological data recorded at airports near the modeling sites instead of the worst case conditions now recommended as a modeling default. The analysis in this study has shown that airport data should be used only on a situational basis as discrepancies exist between airports and local intersections. It is unclear if the added meteorological data will improve CAL3QHC's performance. This study also compares actual CO concentrations and their corresponding meteorology with the worst case modeling defaults. The highest CO levels are occurring at calms (wind speed less than one meter per second) which are not able to be modeled with the current Gaussian dispersion equation in CAL3QHC. Given the findings of this analysis and the lack of other scientific evidence supporting the proposed refinements, recommendations for developing an alternative model improvement plan are outlined. / Graduation date: 1995

No description available.

A photoacoustic spectrometer was developed and built for measuring absorption of light by collected particles. Major advantages of the photoacoustic method are that it measures absorption directly, it is insensitive to scattered light, and it is readily used at different wavelengths. To evaluate the performance of the spectrometer, comparisons were made between photoacoustic absorption spectra and spectra calculated with Mie thoery. Pure powders with varied optical properties were used in the comparison, including carbon, hematite, and others. Results were reasonable in both absolute magnitude and spectral shape. Aerosol particles were collected in different environments in southern Arizona under background conditions in the mid-troposphere, and in a moderately polluted city. Results for the two locations, and two size ranges, are compared and contrasted in this thesis. Absolute magnitudes of absorption coefficients, measured at green wavelengths, are used to summarize many important results. Absorption by fine urban aerosol was 6 ± 4 x 10⁻⁷ m⁻¹, and four times larger than absorption by coarse urban aerosol. Normalized photoacoustic absorption spectra for urban aerosol are uniform with wavelength; background aerosol spectra have a relative increase in absorption at near UV wavelengths compared to near IR wavelengths. Urban aerosol absorption can be attributed to carbon particles larger than approximately 0.1 micron. Absorption by hematite (alpha iron oxide) particles in more strongly wavelength dependent than absorption by carbon particles, of the same size. This wavelength dependence is still not great enough to be attributed to hematite alone--although submicron hematite particles may be the dominant absorber in coarse background aerosol. (Abstract shortened with permission of author.)

The potential of a condensate method for sampling atmospheric trace gases is investigated. A theoretical approach to the collection of condensate by a cooled surface is presented, followed by an experimental procedure and verification of the method. Heat and mass transfer problems are solved to give distributions of temperature, velocity and mass concentration. From these distributions, collection rates for water vapor, trace gases, and particulates are derived. It is shown that the collection of particulates is negligible in most cases when compared to the collection of gases in the condensate; highly soluble gases are sampled with the greatest efficiency. Experimentally, a plate, cooled to below the ambient dew point temperature, collected condensate which was subsequently analyzed for various components. Atmospheric concentrations were determined from the corresponding species in the condensate. Several trace gases have been detected by the condensate method. Concentrations of two of these, ammonia and nitric acid, are compared with filter methods, with reasonably good agreement. Comparison is also made with concentrations of ammonia, formaldehyde, nitric acid and nitrous acid found by others under similar conditions. Typical daily variations of trace components in more remote areas surrounding Tucson, Arizona, are presented in an attempt to estimate background Southwest U.S.A. levels; these are as follows: 1.0 ppb for ammonia, 0.5 ppb for formaldehyde, 0.1 ppb for nitrous acid, 0.4 ppb for nitric acid, 1.1 ppb for formic acid, 0.9 ppb for acetic acid, 0.3 ppb for sulfur dioxide, 0.3 ppb for hydrochloric acid and 1 ppb for hydrogen peroxide. The diurnal variation of these gases and relationship between them is discussed. Possible sources of error in the condensate method of sampling are considered. The collection rate of water vapor is measured and compared to that theoretically predicted; explanations are presented for the discrepancy between the two. The sensitivity to errors in the measurement of the collection temperature and dew point temperature is determined.

Four receptor models and a chemical transport model were used to quantify the sources of PM2.5 impacting the St. Louis Supersite (STL-SS) between June 2001 and May 2003. The receptor models utilized two independent datasets, one that included ions and trace elements and a second that incorporated 1-in-6 day organic molecular marker data. Since each source apportionment (SA) technique has its own limitations, this work compared the results of five different SA approaches to better understand the biases and limitations of each. The source impacts predicted by these five models were then integrated into an ensemble-trained SA methodology. The ensemble method offered several improvements over the five individual SA techniques. Primarily, the ensemble method calculated source impacts on days when individual models either did not converge to a solution or did not have adequate input data to develop source impact estimates. Additionally, the ensemble method resulted in fewer days on which major emissions sources (e.g., secondary organic carbon and diesel vehicles) were estimated to have either a zero or negative impact on PM2.5 concentrations at the STL-SS. When compared with a traditional chemical mass balance (CMB) approach using measurement-based source profiles (MBSPs), the ensemble method was associated with better fit statistics, including reduced chi-squared values and improved PM2.5 mass reconstruction. A comparison of the different modeling techniques also revealed some of the subjectivities associated with applying specific SA models to the STL-SS dataset. For instance, positive matrix factorization (PMF) results were very sensitive to both the fitting species and number of factors selected for the analysis, whereas source impacts predicted in CMB were sensitive to the selection of source profiles to represent local metals processing emissions. Additionally, the different SA approaches predicted different impacts for the same source on a given day, with correlation coefficients ranging from 0.03 to 0.66 for gasoline vehicle, -0.51 to 0.85 for diesel vehicles, -0.29 to 0.86 for dust, -0.34 to 0.76 for biomass burning, 0.22 to 0.72 for metals processing, and -0.70 to 0.68 for secondary organic carbon. These issues emphasized the value of using several different SA techniques at a given receptor site, either by comparing source impacts predicted by different models or by utilizing an ensemble-trained SA technique.

Submitted in partial fulfilment of the requirements for the Degree of Master of Technology: Chemical Engineering, Durban Institute of Technology, 2003. / Motor vehicles are considered a major source of air pollution in urban environments. Nitrogen dioxide (N02) and nitric oxide (NO) which are collectively referred to as oxides of nitrogen (NOx) are formed at high temperatures during combustion processes in the engines of motor vehicles and are emitted via the exhaust into the atmosphere. Nitrogen dioxide is regarded as an irritant of the respiratory system. / M

Fine particulate matter (PM2.5) is the leading public health risk factor of global disease burden, which has caused 4.2 million deaths in 2015. This thesis aims to improve the scientific understanding on the sources and health impacts of PM2.5 in Hong Kong. Various chemical and biological analytical techniques were applied to characterize the chemical and toxicological properties of PM2.5 samples collected in Hong Kong during 2011-2012. Positive matrix factorization (PMF), together with the quantified chemical markers and water-soluble PM2.5-induced reactive oxygen species (ROS) activity as the input matrix, was performed to apportion the source-specific contributions to ambient organic carbon (OC) and the oxidative potential of water-soluble PM2.5. Zebrafish was applied as in-vivo model to evaluate the PM2.5-induced differential expression genes (DEGs). An L2-normaliztion integrated PMF was developed and applied to quantitatively assess the ability of PM2.5 to induced DEGs in relation to various sources and chemical compositions of PM2.5. The main findings are summarized below: (1) Thirty nine primary organic aerosol (POA) and secondary organic aerosol (SOA) markers of various anthropogenic (i.e. biomass burning (BB)) and biogenic sources (i.e. isoprene, monoterpenes and β-caryophyllene) were identified and quantified. High levels of OC and SOA markers were observed on regional pollution days than long regional transport (LRT) pollution and local emissions days. A kinetic model (Kintecus) was applied to explore the major formation channels of isoprene SOA, and it was found that isoprene SOA was mainly formed through the ring-opening reaction of isoprene epoxydiols (IEPOX) in Hong Kong. (2) PMF analysis, together with the chemical markers measured in Chapter 1 &2, was performed to evaluate the sources of OA in Hong Kong. Sea salt, marine vessels, vehicle emissions, BB/SOA, SOA, and secondary sulfate (SS) were apportioned as the major sources of ambient OC in Hong Kong. Secondary formation, including SOA, BB aging and SS sources, was found to be the major contributor to OC (~51%) throughout the whole year. BB was the major anthropogenic contributor to OC on regional days (28.8%); while marine vessel was the dominated primary source of OC on local days (33.2%). SOC concentrations were estimated using a tracer-based method (SOCTBM) and PMF (SOCPMF). Both SOCTBM and SOCPMF showed highest concentrations on regional days (SOCTBM: 0.74 µg m-3; SOCPMF: 3.27 µg m-3). Among all SOA precursors, monoterpenes had the most abundant contribution (40.9%) to SOCTMB during the whole year. Moreover, sulfate has significant impacts on SS-related SOC and SOA from monoterpenes and naphthalene. Particle acidity (HP+) showed correlation with SOC from BB aging. These results provide us a quantitative understanding on the SOA origins in the region, which lays a foundation for the source apportionment of PM2.5-induced toxicity in the following chapters. (3)Cell-free dithiothreitol (DTT) and ·OH generation assays were applied to measure the ROS activity induced by water-soluble PM2.5 collected in Hong Kong during 2011-2012. Different levels of ROS activity were observed for different chemical fractions of PM2.5 and PM2.5 from various sources. Six factors, i.e. SS, BB, SOA, vehicle emissions, marine vessels and metal factors were apportioned by PMF as the major sources of water-soluble PM2.5 induced ROS potential. Metal factors was found to be the major contributor to both DTT activity (39.1%) and ·OH generation ability (84.5%) throughout the year, especially on LRT (DTT: 54.8%; ·OH generation: 91.1%) and regional days (DTT: 53.9%; ·OH generation: 87.7%). On local days, contribution of marine vessels to DTT oxidation become more significant (48.7%), however its contribution to ·OH generation is negligible. Metal factors is by far the most significant contributor to ·OH generation, even on local days (73.1%). It is interesting to note that all six PMF-resolved sources are associated with DTT oxidation, however only three sources (i.e. metal factor, vehicle emissions and SOA) showed contributions to ·OH generation. Moreover, among these six sources, marine vessels exhibited the highest intrinsic DTT ability; while metal factor was the most effective source in ·OH generation. (4) Zebrafish embryo (AB strain) was applied as the in-vivo model to assess PM2.5 toxicity in Hong Kong through genome-wide gene transcriptional analysis. The results showed that embryonic exposure to PM2.5 could induce remarkable changes in gene expression patterns in zebrafish. DEGs between PM2.5 extract treated and untreated zebrafish embryo samples were identified, and they were found mainly associated with responses to xenobiotic stimulus, and muscle and heart development and functions. The correlation analysis between co-expressed gene modules and chemical species of PM2.5 implied the different chemical compositions and sources of PM2.5 have significant influences on the PM2.5-induced biological responses. (5) An L2-normalizaiton integrated PMF was developed to analyze the high throughput biological and chemical data simultaneously, which quantitatively evaluated the ability of PM2.5 to induce DEGs in relation to sources and compositions. In this chapter, nine sources associated with PM2.5-induced DEGs were well apportioned, i.e. fresh sea salt, aged sea salt, SS, SOA, BB, coal combustion, vehicle emissions, marine vessels and metal factors. Among these sources, metal factors (annual mean: 26.5%, range: 17.6-39.3%) and vehicle emissions (annual mean: 16.3%, range: 0.0-25.3%) are the two leading contributors to PM2.5-induced DEGs levels. PM2.5 from combustion related sources (e.g. vehicle emissions, metal factors, BB) and sea salt exhibited stronger ability to induce DEGs than those from secondary sources. Although secondary formation (including SOA and SS) has a significant contribution to ambient PM2.5 (12 μg m-3, 40%), its capacity of DEGs induction is quite low. Moreover, several biological functions and pathways influenced by PM2.5 from various sources have also been well evaluated. In this study, large scales of biological and chemical data were analyzed for the first time by a L2-normalizaiton integrated PMF to apportion the PM2.5-induced DEGs, and this thesis work firstly reported the major sources of water-soluble PM2.5-induced ROS in Hong Kong. Results from this study provide a scientific basis for the prediction of PM2.5-associated adverse health outcomes and can help the policy makers to formulate cost-effective and targeted PM2.5 mitigation strategies to protect public health.;Fine particulate matter (PM2.5) is the leading public health risk factor of global disease burden, which has caused 4.2 million deaths in 2015. This thesis aims to improve the scientific understanding on the sources and health impacts of PM2.5 in Hong Kong. Various chemical and biological analytical techniques were applied to characterize the chemical and toxicological properties of PM2.5 samples collected in Hong Kong during 2011-2012. Positive matrix factorization (PMF), together with the quantified chemical markers and water-soluble PM2.5-induced reactive oxygen species (ROS) activity as the input matrix, was performed to apportion the source-specific contributions to ambient organic carbon (OC) and the oxidative potential of water-soluble PM2.5. Zebrafish was applied as in-vivo model to evaluate the PM2.5-induced differential expression genes (DEGs). An L2-normaliztion integrated PMF was developed and applied to quantitatively assess the ability of PM2.5 to induced DEGs in relation to various sources and chemical compositions of PM2.5. The main findings are summarized below: (1) Thirty nine primary organic aerosol (POA) and secondary organic aerosol (SOA) markers of various anthropogenic (i.e. biomass burning (BB)) and biogenic sources (i.e. isoprene, monoterpenes and β-caryophyllene) were identified and quantified. High levels of OC and SOA markers were observed on regional pollution days than long regional transport (LRT) pollution and local emissions days. A kinetic model (Kintecus) was applied to explore the major formation channels of isoprene SOA, and it was found that isoprene SOA was mainly formed through the ring-opening reaction of isoprene epoxydiols (IEPOX) in Hong Kong.

No description available.