Several epidemiological studies have revealed an association between particulate matter (PM) pollution and various health effects. Importantly, there is evidence to suggest that individuals with pre-existing respiratory disease, such as asthma, are more sensitive to elevated ground levels of particulate matter as compared to healthy subjects. Among the various sources of PM pollution, diesel powered vehicles have been identified as important contributors. The aim of this thesis was to investigate the airway effects of experimental chamber exposure to diesel exhaust (DE) in healthy and asthmatic subjects, focusing on airway responsiveness, airway inflammation and lung function. To achieve a comprehensive picture of the airway responses to DE, a number of different methods were used, including lung function measurements, methacholine inhalation tests, induced sputum and bronchoscopy. Each subject acted as his/her own control by being exposed both to filtered air and DE in a crossover design. Short term exposure to DE, at a particle concentration (PMi0) of 300 ug/m3, was associated with a clinically significant increase in bronchial hyperresponsiveness in asthmatic subjects. In accordance with the epidemiological data suggesting a 1-4 day lag effect for most health outcomes to PM pollution, the increase was detected one day after DE exposure, indicating a long lasting response to DE in asthmatic airways. Diesel exhaust induced a range of airway inflammatory changes as reflected in induced sputum, bronchoalveolar lavage and bronchial mucosal biopsies. In healthy subjects, DE exposure was associated with an increase in neutrophils and IL-6 in sputum, elevated levels of IL-8 and IL-6 in bronchial wash (BW), enhanced expression of IL-8 and GRO-a in the bronchial epithelium and with increases in P-selectin and VCAM-1 in the airway mucosa. In contrast, asthmatics responded with an increase in IL-6 in sputum and an enhanced expression of IL-10 in the bronchial epithelium following exposure DE. Thus, clear differences were identified between healthy and asthmatic subjects in the inflammatory response to DE. Airway epithelial cells constitute the first line of cellular defence towards inhaled air pollutants and increasing evidence suggests that these cells contribute markedly to the initiation of airway inflammatory responses. The bronchial epithelium was identified to have an important regulatory role in response to diesel exhaust, including the capacity to produce chemoattractant and immunoregulatory proteins associated with development of airway inflammation and bronchial hyperresponsiveness. Lung function measurements revealed that short-term exposure to DE induces an immediate bronchoconstrictive response in both healthy and asthmatic individuals, with significant increases in airway resistance (Raw) following DE exposure. This thesis also investigated the effects of a lower concentration of DE (PMio 100 ug/m3) than previously studied. It was shown that exposure to DE at a concentration corresponding to a PM level that may be encountered in busy traffic situations, was still associated with potentially adverse airway responses in healthy and asthmatic subjects. In summary, the results presented here indicate that short term exposure to diesel exhaust, at high ambient concentrations, has the potential to induce a range of biological events in the airways of healthy and asthmatic subjects. / <p>Diss. (sammanfattning) Umeå : Umeå universitet, 2002, härtill 4 uppsatser.</p> / digitalisering@umu

The aim of this study is to quantify the social cost of air pollution in Bophelong Township. Bophelong is a dominantly Black low-income settlement located on the South-western part of the Emfuleni Local Municipality in the Vaal Triangle. In 2006 the Vaal Triangle was the first region in the country to be declared an Airshed Priority Area in terms of the National Environmental Management Act (39/2004). Economic literature reveals that there is a strong positive correlation between poverty and pollution. It is on this basis that the study provides a theoretical background to poverty and pollution. The study makes use of a Contingent valuation method to elicit respondents‘ maximum willingness to pay for the reduction of air-pollution in the area. The survey questionnaire covers three broad socio-economic categories namely, the demographic profile, labour force profile and the residents‘ attitudes towards environmental issues. The valuation part of the questionnaire makes use of an open-ended questionnaire to elicit the respondents‘ maximum willingness to pay for the reduction of air pollution in Bophelong. The mean willingness to pay for the reduction of air-pollution in Bophelong is estimated at R132 per annum. The annual social cost of air-pollution in Bophelong is calculated by multiplying the mean willingness to pay with the estimated total population. Bophelong‘s total population was estimated at 49 408. The annual social cost of pollution is thus estimated at R6 521 856. The regression analysis shows that several factors positively influence respondents‘ willingness to pay. The analysis shows that education, employment and level of income are positively correlated with the respondents‘ willingness to pay. This study indicates that there is a positive correlation between poverty and pollution. Most of the air pollution that affects the population of Bophelong is generated from domestic sources such as the burning of coal and biomass fuels for VALUING THE SOCIAL COST OF AIR-POLLUTION IN BOPHELONG TOWNSHIP heating and cooking purposes. In order to eliminate the negative impacts of air pollution on the residents of Bophelong the study recommends that authorities must begin by ameliorating the poverty situation in the area. On the main authorities must introduce measures that target domestic sources of pollution. Some of the measures that could be undertaken to reduce the impact of pollution could include: (a) encouraging residents to adopt the more cleaner top-down coal ignition method known as Basa-njengo-Magogo, (b) providing free basic electricity to poor households in the area and (c) ensuring that houses are constructed with thermal comfort in mind, as this will minimise the need for space heating particularly during winter months. / PhD (Economics), North-West University, Vaal Triangle Campus, 2013

Within the context of global climate change and soaring energy prices, people are searching for inexpensive and renewable sources of energy; therefore, burning wood for home heating is increasing. Woodsmoke contains substances known to harm human health and is a major contributor to air pollution in many parts of the world; yet there is limited research into the health effects of woodsmoke and existing research suffers from methodological constraints. As a result, there is interest in producing robust woodsmoke exposure estimates for health research and air quality management purposes. Studying health and the environment is inherently spatial; however, research related to air pollution and health tends to be aspatial. As investigators begin to understand the influence of spatial processes on research findings, the importance of adopting a spatial approach to modelling exposure and health risk is becoming apparent. This thesis describes a spatially explicit model for predicting fine particulate matter (PM2.5) attributable to woodsmoke from residential heating in Victoria, British Columbia, Canada. Spatially resolved measurements of PM2.5 were collected for 32 evenings during the winter heating seasons of 2004/05, 2005/06, 2006/07 using a nephelometer installed in a passenger vehicle. Positional data were collected concurrently using a Global Positioning System (GPS). Levoglucosan, a chemical unique to woodsmoke, was measured to confirm the presence of woodsmoke in the measured PM2.5. The spatial scale for the analysis of woodsmoke data was determined using semivariograms to identify the maximum distance of spatial dependence in the data which typically occurred near 2700m. Different spatial approaches for modelling woodsmoke concentrations were evaluated both qualitatively in terms of transferability, meeting statistical assumptions, and potential for exposure misclassification; and quantitatively to assess the association between the model’s predicted PM2.5 concentrations and observed PM2.5. The baseline model characterized exposure based on the PM2.5 value from the closest fixed monitor (R=0.51, α=0.05). The Krigged model produced a seasonal average surface based on nephelometer measurements and showed the weakest performance (R=0.25, α=0.05). The regression models predicted concentrations of woodsmoke based on predictor variables available from census data, typically used in health research, and spatial property assessment data (SPAD), an underused data source at a finer spatial resolution. Different approaches to regression modelling were investigated. A regression model already developed for Victoria performed the best quantitatively (R=0.84, α=0.05); however, qualitative considerations precluded it from being selected as an appropriate model. A quantitatively (R=0.62, α=0.05) and qualitatively robust regression model was developed using SPAD (M6). SPAD improved the spatial resolution and model performance over census data. Removing spatial and temporal autocorrelation in the data prior to modelling produced the most robust model as opposed to modelling spatial effects post regression. A Bayesian approach to M6 was applied; however, model performance remained unchanged (R=0.62, α=0.05). The spatial distribution of susceptibility to health problems associated with woodsmoke was derived from census data relating to population, age and income. Intersecting the exposure model with population susceptibility in a Geographic Information System (GIS) identified areas at high risk for health effects attributable to woodsmoke.

Background Anthropogenic air pollution is a global health problem estimated to contribute to millions of premature deaths. Exposure to biomass smoke is common due to varying sources, such as wildfires, indoor cooking over open fires, and residential heating from wood stoves. In urban environments transportation and industry rely heavily on the combustion of fossil fuels yet environmental policies increasingly support a shift to renewable fuels such as biodiesel. It has not been investigated how either wood smoke or biodiesel exhaust affect human health in general or the cardiovascular system in particular. We hypothesized that wood smoke exposure would induce acute cardiovascular impairment via similar underlying mechanisms as have been established for petrodiesel exhaust exposure. We also hypothesized that replacing petrodiesel with biodiesel, as a blend or pure biodiesel, would generate an exhaust profile with a less harmful effect on the cardiovascular system than petrodiesel exhaust. Methods In four separate studies healthy non-smoking subjects were exposed to different air pollutants in controlled exposure chambers followed by clinical investigations of the cardiovascular system. All studies were performed as randomized controlled trials in a crossover fashion with each individual acting as her own control. In study I healthy volunteers were exposed to wood smoke at a target concentration of particulate matter (PM) 300 µg/m3 for three hours followed by measures of blood pressure, heart rate variability and central arterial stiffness. In study II subjects were exposed to wood smoke at a target concentration of PM 1000 µg/m3 for one hour followed by measures of thrombus formation using the Badimon technique and vasomotor function using forearm venous occlusion plethysmography. In study III subjects were exposed to petrodiesel exhaust and a 30% rapeseed methyl ester (RME30) biodiesel blend for one hour at a target concentration of PM 300 µg/m3. Following exposure, thrombus formation and vasomotor function were assessed as in study II. In study IV subjects were exposed to petrodiesel exhaust at a target concentration of PM 300 μg/m3for one hour and pure rapeseed methyl ester (RME100) exhaust generated at identical running conditions of the engine. Following exposure, thrombus formation and vasomotor function were assessed as in study II and III. Results In study I fourteen subjects (8 males) were exposed to wood smoke at P M 294±36 μg/m3. Compared to filtered air exposure, measures of central arterial stiffness were increased and heart rate variability was decreased following wood smoke exposure. No effect was seen on blood pressure. In study II sixteen males were exposed to wood smoke at PM 899±100 μg/m3. We found no evidence of increased thrombus formation or impaired vasomotor function following wood smoke exposure. In study III sixteen subjects (14 males) were exposed to petrodiesel exhaust (PM 314±27 µg/m3) and RME30 exhaust (PM 309±30 µg/m3). Thrombus formation and vasomotor function were equal following either exposure. In study IV nineteen males were exposed to petrodiesel exhaust (PM 310±34 µg/m3, 1.7±0.3 x105 particles/cm3) and RME100 exhaust (PM 165±16 µg/m3, 2.2±0.1 x105 particles/cm3). As in study III, thrombus formation and vasomotor function were identical following both exposures. Conclusions We have for the first time demonstrated that wood smoke exposure can increase central arterial stiffness and decrease heart rate variability in healthy subjects. We did not, however find evidence of increased thrombus formation and impaired vasomotor function following wood smoke exposure at a higher concentration for a shorter time period. We have, for the first time, demonstrated that exhaust from RME biodiesel induced acute adverse cardiovascular effects of increased thrombus formation and impaired vasomotor function in man. These effects are on par with those seen following exposure to petrodiesel exhaust, despite marked physicochemical differences of the exhaust characteristics.

A large number of studies have shown that both temperature and air pollution (eg, particulate matter and ozone) are associated with health outcomes. So far, it has received limited attention whether air pollution and temperature interact to affect health outcomes. A few studies have examined interactive effects between temperature and air pollution, but produced conflicting results. This thesis aimed to examine whether air pollution (including ozone and particulate matter) and temperature interacted to affect health outcomes in Brisbane, Australia and 95 large US communities. In order to examine the consistency across different cities and different countries, we used two datasets to examine interactive effects of temperature and air pollution. One dataset was collected in Brisbane City, Australia, during 1996-2000. The dataset included air pollution (PM10, ozone and nitrogen dioxide), weather conditions (minimum temperature, maximum temperature, relative humidity and rainfall) and different health outcomes. Another dataset was collected from the 95 large US communities, which included air pollution (ozone was used in the thesis), weather conditions (maximum temperature and dew point temperature) and mortality (all non-external cause mortality and cardiorespiratory mortality). Firstly, we used three parallel time-series models to examine whether maximum temperature modified PM10 effects on cardiovascular hospital admissions (CHA), respiratory hospital admissions (RHA), cardiovascular emergency visits (CEV), respiratory emergency visits (REV), cardiovascular mortality (CM) and non-external cause mortality (NECM), at lags of 0-2 days in Brisbane. We used a Poisson generalized additive model (GAM) to fit a bivariate model to explore joint response surfaces of both maximum temperature and particulate matter less than 10 μm in diameter (PM10) on individual health outcomes at each lag. Results show that temperature and PM10 interacted to affect different health outcomes at various lags. Then, we separately fitted non-stratification and stratification GAM models to quantify the interactive effects. In the non-stratification model, we examined the interactive effects by including a pointwise product for both temperature and the pollutant. In the stratification model, we categorized temperature into two levels using different cut-offs and then included an interactive term for both pollutant and temperature. Results show that maximum temperature significantly and positively modified the associations of PM10 with RHA, CEV, REV, CM and NECM at various lags, but not for CHA. Then, we used the above Poisson regression models to examine whether PM10 modified the associations of minimum temperature with CHA, RHA, CEV, REV, CM and NECM at lags of 0-2 days. In this part, we categorized PM10 into two levels using the mean as cut-off to fit the stratification model. The results show that PM10 significantly modified the effects of temperature on CHA, RHA, CM and NECM at various lags. The enhanced adverse temperature effects were found at higher levels of PM10, but there was no clear evidence for synergistic effects on CEV and REV at various lags. Three parallel models produced similar results, which strengthened the validity of these findings. Thirdly, we examined whether there were the interactive effects between maximum temperature and ozone on NECM in individual communities between April and October, 1987-2000, using the data of 60 eastern US communities from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS). We divided these communities into two regions (northeast and southeast) according to the NMMAPS study. We first used the bivariate model to examine the joint effects between temperature and ozone on NECM in each community, and then fit a stratification model in each community by categorizing temperature into three levels. After that, we used Bayesian meta-analysis to estimate overall effects across regions and temperature levels from the stratification model. The bivariate model shows that temperature obviously modified ozone effects in most of the northeast communities, but the trend was not obviously in the southeast region. Bayesian meta-analysis shows that in the northeast region, a 10-ppb increment in ozone was associated with 2.2% (95% posterior interval [PI]: 1.2%, 3.1 %), 3.1% (95% PI: 2.2%, 3.8 %) and 6.2 % (95% PI: 4.8%, 7.6 %) increase in mortality for low, moderate and high temperature levels, respectively, while in the southeast region, a 10-ppb increment in ozone was associated with 1.1% (95% PI: -1.1%, 3.2 %), 1.5% (95% PI: 0.2%, 2.8%) and 1.3% (95% PI: -0.3%, 3.0 %) increase in mortality. In addition, we examined whether temperature modified ozone effects on cardiovascular mortality in 95 large US communities between May and October, 1987-2000 using the same models as the above. We divided the communities into 7 regions according to the NMMAPS study (Northeast, Industrial Midwest, Upper Midwest, Northwest, Southeast, Southwest and Southern California). The bivariate model shows that temperature modified ozone effects in most of the communities in the northern regions (Northeast, Industrial Midwest, Upper Midwest, Northwest), but such modification was not obvious in the southern regions (Southeast, Southwest and Southern California). Bayesian meta-analysis shows that temperature significantly modified ozone effects in the Northeast, Industrial Midwest and Northwest regions, but not significant in Upper Midwest, Southeast, Southwest and Southern California. Nationally, temperature marginally positively modified ozone effects on cardiovascular mortality. A 10-ppb increment in ozone was associated with 0.4% (95% posterior interval [PI]: -0.2, 0.9 %), 0.3% (95% PI: -0.3%, 1.0%) and 1.6% (95% PI: 4.8%, 7.6%) increase in mortality for low, moderate and high temperature levels, respectively. The difference of overall effects between high and low temperature levels was 1.3% (95% PI: - 0.4%, 2.9%) in the 95 communities. Finally, we examined whether ozone modified the association between maximum temperature and cardiovascular mortality in 60 large eastern US communities during the warmer days, 1987-2000. The communities were divided into the northeast and southeast regions. We restricted the analyses to the warmer days when temperature was equal to or higher than the median in each community throughout the study period. We fitted a bivariate model to explore the joint effects between temperature and ozone on cardiovascular mortality in individual communities and results show that in general, ozone positively modified the association between temperature and mortality in the northeast region, but such modification was not obvious in the southeast region. Because temperature effects on mortality might partly intermediate by ozone, we divided the dataset into four equal subsets using quartiles as cut-offs. Then, we fitted a parametric model to examine the associations between temperature and mortality across different levels of ozone using the subsets. Results show that the higher the ozone concentrations, the stronger the temperature-mortality associations in the northeast region. However, such a trend was not obvious in the southeast region. Overall, this study found strong evidence that temperature and air pollution interacted to affect health outcomes. PM10 and temperature interacted to affect different health outcomes at various lags in Brisbane, Australia. Temperature and ozone also interacted to affect NECM and CM in US communities and such modification varied considerably across different regions. The symmetric modification between temperature and air pollution was observed in the study. This implies that it is considerably important to evaluate the interactive effect while estimating temperature or air pollution effects and further investigate reasons behind the regional variability.

Exposure to air contaminants is significantly associated with both short-term and long-term health effects. However, the precise mechanisms that derive such effects are not always understood. While an extensive background database from in vivo toxicological studies have been developed, most toxicity data is from oral and dermal chemical exposures rather than inhalation exposure. There is a need to explore new alternative approaches to provide toxicity information particularly on this technically demanding area. This research explores the potential of in vitro methods for toxicity assessment of workplace air contaminants. A tiered approach for in vitro toxicity testing of workplace contaminants was designed in which appropriate air sampling and exposure techniques were developed. A diversified battery of in vitro assays including the MTS (tetrazolium salt, Promega), NRU (neutral red uptake, Sigma) and ATP (adenosine triphosphate, Promega) and a multiple human cell system including: A549- lung derived cells; HepG2-liver derived cells, and skin fibroblasts were used. Primarily the application and merits of in vitro methods for prediction of toxicity of selected workplace contaminants including Ammonium hydroxide, Cadmium chloride, Cobalt chloride, Formaldehyde, Glutaraldehyde, Manganese chloride, Mercuric chloride, Sodium dichromate, Sulphureous acid and Zinc chloride was confirmed. To study the toxicity of airborne contaminants an indirect exposure method was established using air sampling techniques followed by static and dynamic direct exposure methods by culturing cells on porous membranes to reveal representative data relating to human airborne exposures. The static method enabled the measurement of an airborne IC50 (50% inhibitory concentration) value for selected volatile organic compounds (VOCs) including: Xylene (IC50 = 5,350-8,200 ppm) and Toluene (IC50 = 10,500- 16,600 ppm) after 1 hr exposure. By implementing the dynamic method, airborne IC50 values were calculated for gaseous contaminants including: NO2 (IC50 = 11 ?? 3.54 ppm; NRU), SO2 (IC50 = 48 ?? 2.83 ppm; ATP) and NH3 (IC50 = 199 ?? 1.41 ppm; MTS). A higher sensitivity of in vitro methods was observed compared to in vivo published data. A range of in vitro bioassays in conjunction with exposure techniques developed in this thesis may provide an advanced technology for a comprehensive risk assessment of workplace air contaminants.

The presence of complex mixtures of compounds in ambient air, many of which are either unknown or uncharacterised makes an assessment of risk associated with these exposures problematic. Bioanalytical methods can provide an integrative assessment of complex mixture potency for specific mechanisms of toxicity within these contexts. The aim of this study was to evaluate the suitability of monitoring ambient air exposures as sampled by (polyurethane foam) PUF passive air samplers (PAS) using effect based techniques (bioanalytical methods). Passive samplers have the advantage of offering a low-tech inexpensive monitoring strategy which can thereby increase sampling capacity across a broader range of scenarios simultaneously. One challenge posed by the application of passive samplers in particular for these assessments has been the expression of potency estimates in relatively non-comparable terms specific to a given dose of the sampler or for a specific deployment period. The project was therefore designed in order to address these aims and previously identified challenges by investigating the applicability of these techniques for: monitoring in both indoor and outdoor air, the determination of seasonal exposure gradients; the determination of exposure gradients in different locations (urban capitals, regional centres, background); and the application of in-situ calibration to provide comparable effect measurements in terms of equivalent reference compound air concentrations. Air sampled using PUF PAS was monitored for its capacity to induce biological responses which are mechanistically relevant to critical health endpoints in these scenarios. The mechanisms assessed included genotoxicity (DNA damage – umuC assay), Aryl hydrocarbon receptor (AhR) activity (CAFLUX assay), and estrogenicity (ESCREEN assay). The findings from this effect based monitoring revealed that the level of biological response measured changes with the exposure scenario (indoor vs. outdoor; summer vs. winter; urban capital cities vs. background locations). Estrogenicity for example assessed as estradiol equivalent air concentrations (E Eq BIO) averaged 54 pg.m-3 (1.5 - 185 pg.m-3) in indoor air, while samples from ambient air were found to be not estrogenic. Total aryl hydrocarbon receptor (AhR) activity assessed as 2,3,7,8-tetrachlorodibenzo-p-dioxin equivalent air concentrations (TCDD Eq BIO) averaged 4.1 pg.m-3 (1.3 – 7.2 pg.m-3) in indoor air while samples from ambient air averaged 15 pg.m-3 (1.5 – 46 pg.m-3)in summer and 53 pg.m-3 (2.2 – 251 pg.m-3) in winter. The relationship for both direct (-S9) and indirect (+S9) acting genotoxicity and AhR activity were found to be relatively consistent with respect to both season (elevated in winter) and location (elevated in urban capital cities). Overall suitable techniques were developed for combining passive sampling with multiple end-point toxicity testing and it was demonstrated that these techniques may be applied across different exposure scenarios. During the course of this method development and interpretation process a range of limitations were identified relating to: the use and application of effect based techniques to monitor environmental samples; the use of passive samplers within this context specifically; and also with the application of in-situ calibration techniques to passive samplers to improve the comparability of these assessments.

Diss. (sammanfattning) Linköping : Univ., 2004. / Härtill 6 uppsatser.

Diss. (sammanfattning) Stockholm : Karol. inst., 2004. / Härtill 5 uppsatser.

Diss. (sammanfattning) Uppsala : Sveriges lantbruksuniversitet, 2004. / Härtill 6 uppsatser.