Air pollution is one of the major environmental issues. It can cause adverse health effects such as cancer, cardiovascular diseases and high mortality rates. High population density is a huge contributory factor of air pollution in cities and urbanized areas. The third biggest city of the Czech Republic, Ostrava the subject of this thesis, is one of the most densely polluted areas of the country. The main air pollutants of concern are suspended particles and poly aromatic hydrocarbons. Ostrava's high proportion of heavy industry is a major source of air pollution compared to the rest of the Czech Republic. Other sources of air pollution are transport, local heating and possibly a pollution transfer from a neighboring industrial region in Poland. This thesis deals mainly with long term time series, including air pollutants (PM10, SO2, NOx), and meteorological variables. Information about the opening and closing of industrial plants can be considered as an added value to this work. The purpose of this data thesis is to compare the concentration levels before and after the closing or opening of particular industrial plants in the city of Ostrava during the last 35 years. So far no one has utilized these data sets for comprehensive analyses. Key words: Urban area, Emission, PM10, SO2, Industry

Identification of airborne pollutant sources and estimation of source contributions to air quality ‘hot spots’ are very important in ambient air quality management. Social, economical, political and legal constraints on air quality management demand a convenient and accurate method for attributing air pollution sources to the ‘hot spots’. In this PhD research degree project, an automatic air pollution monitoring station was set up on the library roof at the University of Abertay Dundee to monitor urban background air quality in Dundee. Concentrations of the particulate with aerodynamic diameter less than 10 pm (PMio), the total suspended particulate (TSP), nitric oxide (NO), nitrogen dioxide (NO2) and nitrogen oxides (NOx) as well as wind speed, wind direction, ambient temperature and total rainfall were measured continuously for one year. The chemical components of PM10 and TSP, calcium (Ca2+), magnesium (Mg2+), copper (Cu), lead (Pb), nickel (Ni), zinc (Zn), sulphate (SO42'), nitrate (NO3'), chloride (C1‘), ammonium (NH/), sodium (Na+) and potassium (K+) were analysed in the laboratory. Additionally, the inventories of atmospheric emission sources in Dundee were investigated in detail in order to satisfy the needs of air dispersion model. A new software package for the atmospheric dispersion models was also developed by the author using Microsoft Visual C++. In contrast to other available software packages, this package offers a choice of different atmospheric models. The user may select a model according to the situation prevailing and the available parameters. The package for the atmospheric dispersion models was used to simulate transport of airborne pollutants in Dundee. Performance of the models was evaluated using the data gathered at the monitoring station and atmospheric emission inventories. The contributions of various air pollution sources of NOx and PM10 measured at the station were estimated. The receptor model was used to discriminate airborne pollutant emission sources and quantitatively apportion PM10 measured at the station to these sources. The results from the atmospheric dispersion model and the receptor model were compared and used in a complementary manner. A new methodology that combines the features of the receptor oriented and source oriented models, and supplements and corrects the two modelling approaches has been developed. The applicability of the methodology has been tested against the gathered air quality and source emission data in Dundee. The following outputs from the research work are completely novel: • A comprehensive database that consists of concentrations of gaseous pollutants and particulates, chemical compositions of particulates, weather conditions and atmospheric emission inventories. • A new software package for modelling atmospheric dispersion. This was programmed using Microsoft Visual C++. In contrast to other available commercial packages, the models embedded in the package include a modified hybrid plume dispersion model and a ground level release dispersion model that incorporate recent advances in the understanding of planetary boundary layer and atmospheric dispersion. They also include the conventional Gaussian plume dispersion model that is still generally used. The user may select different models according to the prevailing situation and the available parameters when applying the package. • The use of error estimate in ‘weighting’ the data of element matrix and complementary use of subjective information in receptor model trials. • A new methodology that complements atmospheric dispersion and receptor models to attribute sources of airborne pollutants to their receptors.

7 Abstract Air pollution has a great impact on human health, with acute consequences possibly resulting even in death. It is therefore important to inform the public about up-to-date air quality and its impact on health in a simple and easily undestandable way. Air quality indices seems to be ideal for this purpouse, but there is large variety of them. In this master thesis, the air quality index most suitable for the capital city of Prague has been searched for. A comparison of the following indices has been carried out based on available data: of following indicies based on avaible data (concentration of O3, PM10, NO2, SO2 a CO): Air Quality Index, Aggregate Air Quality Index, Revised Air Quality Index, Common Air Quality Index a Pollution Index and their modifications according to european standards. As a criterion of aptness of a particular index, a degree of correlation between the index itself and corresponding health problems (daily count of deaths, daily count of deaths caused by diseases of the respiratory system, daily count of deaths caused by diseases of circulatory system, daily count of hospitalization caused by diseases of the respiratory system, daily count of hospitalization caused by diseases of circulatory system) of the local population has been chosen. This relationship was verified...

Ambient air pollution, including airborne particulate matter (PM) derived from combustion of fossil fuels (FF) or biomass (BM), has detrimental inflammatory effects on human health. Myeloid antigen presenting cells, including dendritic cells (DCs) regulate immune responses in the airway and sample inhaled PM. This study tests the hypothesis that PM interacts with multiple environmental sensing pathways in DCs with outcomes that depend on particle size and composition as determined by combustion source. The effects of different sized PM (< 10μm, PM10; < 2.5μm, PM2.5), derived from the combustion of FF or BM, on human monocyte-derived or ex vivo sputum DCs, were examined. DC activation status, cytokine production and aryl hydrocarbon receptor (AhR) signalling were assessed by flow-cytometry, multiplex ELISA and qRT-PCR, following exposure to PM. Pathway-specific antagonists were used to explore underlying mechanisms. Particle size and combustion source influenced the effects of PM on DCs. Irrespective of combustion source, PM10 but not PM2.5, induced MoDC maturation and stimulated production of inflammatory cytokines, including IL-1β and IL-18, indicative of inflammasome activation. These responses were dependent, at least in part, on TLR4 as was the induction of IDO by PM10. AhR signalling was induced by PM in both MoDC and ex vivo sputum DC. It was stimulated by both PM10 and PM2.5 and was induced more strongly by BM-derived PM. AhR activation was independent of DC maturation and TLR4 signalling. Additionally, BM- but not FF-derived PM increased NADH levels in DC suggestive of altered metabolism. Thus, PM induces a complex programme of DC activation, influenced by size and combustion source, which includes classical maturation, inflammasome dependent cytokine release and AhR signalling as well as potential metabolic changes. In the airway, exposure to different PM and the changes in DCs induced by them may lead to altered responses to inhaled antigen.

Hazardous air pollutants (HAP’s) are assumed to act without threshold meaning any level of exposure can theoretically initiate the carcinogenic process. With approximately 57,000 new cancer diagnoses and 25,900 deaths predicted in Ontario in 2006, the implications of lifetime low dose cumulative exposure to HAP’s in the etiology of cancer is unknown, yet may be significant. As such, this burden of disease (BoD) model was designed to provide a comprehensive assessment of the current and future BoD attributable to long term cumulative exposure to six carcinogenic HAP’s in two highly exposed regions of Ontario, using a summary measure of population health, disability-adjusted life years (DALY’s). Results indicated a total of 32,074 DALY’s were lost in Toronto and Southwestern Ontario (SWO) from six cancer sites in 2001, with the largest burden from cancers of the lung, followed by lymphomas, then leukemia. Approximately 0.58% of the burden (187 DALY’s) was attributable to current HAP exposures, with the largest health impacts associated with exposure to nickel refinery dusts in SWO (8.91 DALY’s) and benzene in Toronto (46.30 DALY’s). The model predicted 0.3% of the exposure attributable BoD (96 DALY’s) could be avoided in the future if ambient exposures were reduced to a feasible distribution. If ambient exposures were further reduced to levels expected if there were no anthropogenic releases, the model predicts 147 DALY’s could be avoided, such that only 0.12% of the total BoD would be attributable to natural sources of HAP’s. Results of the sensitivity analysis support the notion of the DALY as a robust measure to estimate exposure attributable health impacts, as the incorporation of alternative value choices had negligible impact on the relative importance of cancer sites, or exposures to the total BoD. Results of the model can be used by decision makers to inform public health policy regarding abatement priorities of HAP’s in Ontario, on the basis associated health impacts.

Hazardous air pollutants (HAP’s) are assumed to act without threshold meaning any level of exposure can theoretically initiate the carcinogenic process. With approximately 57,000 new cancer diagnoses and 25,900 deaths predicted in Ontario in 2006, the implications of lifetime low dose cumulative exposure to HAP’s in the etiology of cancer is unknown, yet may be significant. As such, this burden of disease (BoD) model was designed to provide a comprehensive assessment of the current and future BoD attributable to long term cumulative exposure to six carcinogenic HAP’s in two highly exposed regions of Ontario, using a summary measure of population health, disability-adjusted life years (DALY’s). Results indicated a total of 32,074 DALY’s were lost in Toronto and Southwestern Ontario (SWO) from six cancer sites in 2001, with the largest burden from cancers of the lung, followed by lymphomas, then leukemia. Approximately 0.58% of the burden (187 DALY’s) was attributable to current HAP exposures, with the largest health impacts associated with exposure to nickel refinery dusts in SWO (8.91 DALY’s) and benzene in Toronto (46.30 DALY’s). The model predicted 0.3% of the exposure attributable BoD (96 DALY’s) could be avoided in the future if ambient exposures were reduced to a feasible distribution. If ambient exposures were further reduced to levels expected if there were no anthropogenic releases, the model predicts 147 DALY’s could be avoided, such that only 0.12% of the total BoD would be attributable to natural sources of HAP’s. Results of the sensitivity analysis support the notion of the DALY as a robust measure to estimate exposure attributable health impacts, as the incorporation of alternative value choices had negligible impact on the relative importance of cancer sites, or exposures to the total BoD. Results of the model can be used by decision makers to inform public health policy regarding abatement priorities of HAP’s in Ontario, on the basis associated health impacts.

The use of near ambient air drying for the preservation of wheat stored in granaries is common in Western Canada. Guidelines have been developed to assist farmers in selecting appropriate drying methods. During this process the top layer of wheat can remain at moisture contents (m.c.) greater than the safe storage limit, 14.5% wet bulb (wb), for up to 12 weeks. This study tested the effects of this drying procedure on the development of ochratoxin A (OTA) using 1 m3 bulks of durum wheat at 18% m.c. (wb) contained within steel bins inside a Weather Simulation Lab. In a second study using 20 L volumes of wheat at a m.c. of 20% (wb) within an environmental growth chamber potential development of OTA was also evaluated. The wheat was exposed to two treatments, airflow and no airflow, for a period of 12 weeks under conditions of high relative humidity (greater than 80%) and typical Manitoba fall temperatures. The storage quality parameters of germination, fat acidity value, and presence of OTA were measured weekly. It was found that high moisture wheat stored under all treatment conditions showed a rapid decrease in germination and increase in fat acidity value over time, with no significant difference between the treatments. Under the tested conditions the development of ochratoxin A was not detected in significant quantities in the 1 m3 bulks of grain but was detected in the smaller 20 L bulks.

No description available.

No description available.

Agricultural operations across the United States are encountering difficulties complying with current air pollution regulations for particulate matter (PM). PM is currently regulated in terms of particle diameters less than or equal to a nominal 10 μm (PM10); however, current legislation is underway to regulate PM with diameters less than or equal to a nominal 2.5 μm (PM2.5). The goals of this research were to determine the biases and uncertainties associated with current PM10 and PM2.5 sampling methods and to determine the extent to which these errors may impact the determination of cotton gin emission factors. Ideally, PM samplers would produce an accurate measure of the pollutant indicator; for instance, a PM10 sampler would produce an accurate measure of PM less than or equal to 10 μm. However, samplers are not perfect and errors are introduced because of the established tolerances associated with sampler performance characteristics and the interaction of particle size and sampler performance characteristics. Results of this research indicated that a source emitting PM characterized by a mass median diameter (MMD) of 20 μm and a geometric standard deviation (GSD) of 1.5 could be forced to comply with a 3.2 and 14 times more stringent regulation of PM10 and PM2.5, respectively, than a source emitting PM characterized by a MMD of 10 μm and a GSD of 1.5. These estimates are based on both sources emitting the same concentrations of true PM or concentrations corresponding to the particle diameters less than the size of interest. Various methods were used to estimate the true PM10 and PM2.5 emission factors associated with cotton gin exhausts and the extent to which the sampler errors impacted the PM regulation. Results from this research indicated that current cotton gin emission factors could be over-estimated by about 40%. This over-estimation is a consequence of the relatively large PM associated with cotton gin exhausts. These PM sampling errors are contributing to the misappropriation of source emissions in State Implementation Plans, essentially forcing Air Pollution Regulatory Agencies to require additional controls on sources that may be incorrectly classified has high emitters.