published_or_final_version / Architecture / Master / Master of Philosophy

No description available.

published_or_final_version / Chemistry / Doctoral / Doctor of Philosophy

Over the last several years studies have shown that the quality of indoor air may be worse than outdoor air. People spend as much as 90% of their time indoors, therefor, the associated health risk due to indoor air pollution may be greater than the risk due to outdoor air pollution. Building designs have altered dramatically over the last two decades resulted in "tighter" buildings that rely on sophisticated mechanical systems to provide for the quantity of air required throughout the building. These changes over the years could result in an increased number of complaints received regarding Sick Building Syndrome symptoms. The World Health Organization (WHO) estimates that up to 30% of office buildings world-wide may have significant problems regarding poor indoor air quality (IAQ). This study involves a literature study of the major indoor air pollutants regarding the source of the pollutant, the associated health effects, the measuring techniques available and the results of previous studies conducted on the specific pollutant. Measurements will be taken in two sealed buildings, one an old and the other a new building to identify the major pollutants. A questionnaire was compiled specifically for building occupants and completed by the occupants of both buildings. From the results obtained a step-by-step method for solving indoor air quality (IAQ) problems was proposed. The method was applied and evaluated in a case study of a problem building where indoor air quality related problems were experienced. The results of the study revealed that the major indoor air pollutants are present in old as well as new buildings. The study also revealed that some office workers might be more susceptible than others to the medical reactions cause to human beings by these pollutants. Some concentrations are higher in new buildings than in old buildings. The responses from the questionnaire was evaluated against the results obtained from the measurement study. The step-by-step method in the case study provided a more systematic approach at solving IAQ problems at buildings. Solving indoor air quality problems is a very practical issue and does not necessarily require an investment of expensive high technology equipment, but might merely require a practical approach. Environmental Health Officers can play a major role in providing expert advice when scrutinizing building plans. Environmental Health Officers should empower themselves with the knowledge to do inspections or investigations in office buildings by using the step-by-step method for investigating indoor air quality problems. By addressing indoor air quality problems in buildings, the workers in healthy buildings can increase their productivity with lasting effects on a company’s bottom line.

An automated tungstic acid technique (TAT) has been successfully used to measure gaseous HNO₃ in the presence of water vapor. The TAT is based on the diffusion of gaseous HNO₃ to the interior walls of a tube coated with tungsten VI oxide (WO₃), where it is selectively chemisorbed. The collected HNO₃ sample is thermally desorbed from the WO₃ surface, as NO, and measured by a chemiluminescent oxides of nitrogen analyzer. The integrated analyzer response is directly proportional to the nitric acid collected. Based on nitric acid hydration characteristics, a decrease in the diffusion coefficient and thus collection efficiency for denuder type measurement techniques may result with increased atmospheric water vapor (i.e., relative humidity). This study emphasizes the effect of water vapor (i.e., relative humidity) as a potential interferent for HNO₃ collection with the TAT system. The effect of water vapor (< 78% RH) on the collection efficiency for HNO₃ with the tungstic acid technique is negligible at 25°C, but is significant only at elevated sampling temperatures. This threshold effect is further substantiated and eliminated when a modified sampling collection system was designed with coolant capabilities. The new design has been tested to sub-part-per-billion (NO_x analyzer detection limit) levels with minimal loss of gaseous HNO₃ signal, thereby increasing sensitivity to atmospheric HNO₃ concentrations and maintaining the gas/aerosol sample integrity. / Ph. D.

Mobile source emissions are a major contributor to global and local air pollution. Governments and regulatory agencies have been increasing the stringency of regulations in the transportation sector for the last ten years to help curb transportation sector air pollution. The need for regulations has been emphasized by scientific research on the impacts from ambient pollution, especially research on the effect of particulate matter on human health. The particulate emissions from diesel vehicles, diesel particulate matter (DPM) is considered a known or probable carcinogen in various countries and increased exposure to DPM is linked to increased cardiovascular health problems in humans. The toxicity of vehicle emissions and diesel particulate emissions in particular, in conjunction with an increased awareness of potential petroleum fuel shortages, international conflict over petroleum fuel sources and climate change science, have all contributed to the increase of biodiesel use as an additive to or replacement for petroleum fuel. The goal of this research is to determine how this increased use of biodiesel in the particular emission testing setup impacts urban air quality. To determine if biodiesel use contributes to a health or climate benefit, both the size range and general composition were investigated using a comprehensive comparison of the particulate component of the emissions in real time. The emissions from various biodiesel and diesel mixtures from a common diesel passenger vehicle were measured with a cavity ring-down transmissometer (CRDT) coupled with a condensation particle counter, a SMPS, a nephelometer, NOx, CO, CO2, and O3 measurements. From these data, key emission factors for several biodiesel and diesel fuel mixtures were developed. This approach reduces sampling artifacts and allows for the determination of optical properties, particle number concentration, and size distributions, along with several important gas phase species' concentrations. Findings indicate that biodiesel additions to diesel fuel do not necessarily have an air quality benefit for particulate emissions in this emission testing scenario. The often cited linear decrease in particulate emissions with increasing biodiesel content was not observed. Mixtures with half diesel and half biodiesel tended to have the highest particulate emissions in all size ranges. Mixtures with more than 50% biodiesel had slightly lower calculated mass for light absorbing carbon, but this reduction in mass is most likely a result of a shift in the size of the emission particles to a smaller size range, not a reduction in the total number of particles. Evaluation of the extensive optical properties from this experimental set-up indicates that biodiesel additions to diesel fuel has an impact on emission particle extinction in both visible and near-IR wavelengths. The B99 mixture had the smallest emission factor for extinction at 532 nm and at 1064 nm. For the extinction at 532 nm, the trend was not linear and the emission factor peaked at the B50 mixture. Results from intensive properties indicate that emissions from B5 and B25 mixtures have Ångström exponents close to 1, typical for black carbon emissions. The mixtures with a larger fraction of biodiesel have Ångström exponent values closer to 2, indicating more absorbing organic matter and/or smaller particle size in the emissions. Additional experimental testing should be completed to determine the application of these results and emission factors to other diesel vehicles or types of diesel and biodiesel fuel mixtures.

Various epidemiological studies have linked exposure to Ultrafine Particles (UFP; diameter< 100 nm) to adverse health impacts. Roadway traffic is one of the major sources of UFPs and heavily influences UFP concentrations in the nearby vicinity of major roadways. Modeling efforts to predict UFPs have been limited due to the scarcity of reliable information on emissions, lack of monitoring data and limited understanding of complex processes affecting UFP concentrations near sources. In this study continuous measurement of ultrafine particle number concentrations (PNC) and mass concentrations of nitric oxide (NO), nitrogen dioxide (NO2) and PM2.5 was conducted near an arterial road and freeway at different seasons and meteorological conditions and integrated with traffic count data. PNC showed high correlation with NO (r=0.64 for arterial; 0.61 for freeway), NO2 (r=0.57 for arterial; 0.53 for freeway) and NOx (NOx=NO+NO2; r=0.63 for arterial; 0.59 for freeway) and moderate to low correlation with traffic volume (r=0.33 for arterial; 0.32 for freeway) and PM2.5 (r=0.28 for arterial; 0.23 for freeway); respectively; for both sites at 15 minute averages. The PNC-NOx relationship prevailed on a shorter term (15 min), hourly, and throughout the day basis. Both PNC and NOx showed comparatively higher correlation with traffic during the morning period but became lower during evening which can be attributed to the higher boundary layer and wind speeds. The variable meteorology in the evening affects both PNC and NOx concentrations in the same way and the correlation between NOx and PNC is maintained high both during morning (r=0.74 for arterial; 0.69 for freeway), and evening (r=0.62 for arterial; 0.59 for freeway) periods. Thus nitrogen oxides can be used as a proxy for traffic-related UFP number concentration reflecting the effect of both traffic intensity and meteorological dilution. The PNC-NOx relation was explored for various meteorological parameters i.e. wind speed and temperature. It is found that NOx emission is temperature independent and can be used to reflect the effect of traffic intensity and meteorological dilution. Once the effect of traffic intensity and dilution is removed, the effect of temperature on PNC-NOx ratio becomes important which can be attributed to the variation in PNC emission factors with temperature. The high morning PNC-NOx ratio found at the arterial road is a result of new particle formation due to lower temperature and low concentration of exhaust gases in the morning air favoring nucleation over condensation. This finding has important implication when calculating emission factors for UFP number concentrations. Thus it can be concluded that roadside concentration of ultrafine particles not only depends on traffic intensity but also on meteorological parameters affecting dilution or new particle formation. High concentrations of ultrafine particle number concentration close to a roadway is expected due to higher traffic intensity , as well as during low wind speed causing low dilution and low temperature conditions favoring new particle formation. Finally a simplified approach of calculating particle number emission factor was developed using existing and easily available emission inventory for traffic related tracer gases. Using NOx emission factors from MOVES emission model, the emission ratio of PNC to NOx was converted to develop particle number emission factors. NOx was selected as the traffic related tracer gas since the number concentration of particles is closely correlated to NOx, NOx and particles are diluted in the same way and NOx emission factors are available for a variety of traffic situations. To ensure contribution of fresh traffic exhaust, the average of the difference of pollutant concentrations at high traffic condition and background condition was used to calculate PNC-NOX ratio. Using nitrogen oxides to define background and high-traffic conditions and MOVES emission factor for NOX to convert corresponding PNC-NOX ratio, an average emission factor of (1.82 ± 0.17) E+ 14 particle/ vehicle-km was obtained, suitable for summertime. When compared to existing particle number emission factors derived from dynamometer tests, it was found that there exits reasonable agreement between the calculated real world particle number emission factors and emission factors from dynamometer tests. The calculated emission factor and R-Line dispersion model was tested in predicting near-road particle number concentrations. Although only 23% of the variability in PNC was explained by the dispersion model, 84.33% of the measurements fell within the factor of two envelope. This suggests that there is potential to effectively use these models and thus warrants more in-depth analysis. Finally, a simple map of PNC gradients from major roads of Portland was developed. The results of this study helped identify proxy-indicators to provide reference values for estimating UFP concentrations and emissions that can be used for simple evaluation of particle concentration near major roadways for environmental and urban planning purposes and to assess expected impact of UFP pollution on population living near roadways exposed to elevated concentrations.

Emissions inventories are an important tool, often built by governments, and used to manage emissions. To build an inventory of urban CO2 emissions and other fossil fuel combustion products in the urban atmosphere, an inventory of on-road traffic is required. In particular, a high resolution inventory is necessary to capture the local characteristics of transport emissions. These emissions vary widely due to the local nature of the fleet, fuel, and roads. Here we show a new model of ADT for the Portland, OR metropolitan region. The backbone is traffic counter recordings made by the Portland Bureau of Transportation at 7,767 sites over 21 years (1986-2006), augmented with PORTAL (The Portland Regional Transportation Archive Listing) freeway traffic count data. We constructed a regression model to fill in traffic network gaps using GIS data such as road class and population density. An EPA-supplied emissions factor was used to estimate transportation CO2 emissions, which is compared to several other estimates for the city's CO2 footprint.

Ph.D. (Geography) / The focus of Aeolian research has mainly been on wind-blown dust from desert and arid areas. Numerous dust emission schemes have been developed over the years aimed at accurately estimating dust emission rates from various soil types and land use surfaces. Limited research has been done on wind-blown dust from smaller area sources – such as mine tailings and ash storage facilities. Lately, the concern about the environmental and health impacts, caused by dust from mine tailings storage facilities and ash disposal sites, has become more prominent, calling for better methods in determining dust emissions and their related impacts. This thesis established a practical approach for wind-blown dust emissions estimation and dispersion modelling from mine waste and ash storage facilities for the purpose of legal compliance assessment. Extensive research on the physics of wind erosion has been done over the past decade, compelling the re-evaluation of previously applied techniques. The latest and most widely applied dust emission schemes are evaluated to determine, through systematic testing of parameterisation and validation, using empirical mine waste and coal ash data, a best-practice prescription for quantifying wind-blown dust emissions and determining effects on a local scale using commercially available dispersion models. The applicability of two dust-flux schemes, (one developed by Marticorena and Bergametti (1995) and the simplified Shao 2004 scheme, as reported in 2011) for the quantification of wind-blown dust emissions, were tested using site specific particle size distribution data, bulk density and moisture content from six gold- and one platinum- tailings storage facilities and from two ash storage facilities. The availability of the required input parameters and the uncertainty associated with these parameters, were tested. The dependency of the Shao et al. (2011) model on plastic pressure (P) and the coefficient cy, both of which are not easily determined, added to the uncertainty of the emission rates. In this study, P and cy were both interpolated using the range limits provided by Shao (2004) for natural soils. By calculating P, using the salt and calcium carbonate content, similar values were obtained. The minimally disturbed dust fraction, as required by the Shao et al. (2011) scheme were derived from particle size distribution analysis but found to be more representative of the fully disturbed particle size faction (𝜂fi) and therefore needed to be corrected to represent the minimally disturbed particle size faction (𝜂mi) through the application of a correction factor, CF𝜂mi. Specific attention was given to the quantification of the threshold friction velocity (u*t) and the threshold velocities (u*), and how these two parameters relate to each under variable wind speed and time durations. This was tested using sub-hourly averaged meteorological data, one set reflected 5-minute intervals and the other 10-minute intervals. Dependent on the frequency and strength of the sub-hourly wind gusts, the resulting dust-flux rates were found to vary significantly when based on hourly averaged wind data in comparison with 5- and 10-minute wind data. Dispersion models are useful tools in air quality management. Whereas ambient monitoring provides actual ambient concentrations for specific pollutants at set locations, atmospheric dispersion models can be used to simulate any number of pollutants and determine the impacts at any location within the modelling domain. These dust-flux schemes of Marticorena and Bergametti (1995) and Shao et al. (2011) have been coupled with the US EPA regulatory Gaussian plume AERMOD dispersion model for the simulation of ground level concentrations resulting from wind-blown dust from mine tailings facilities. For this study, two Case Studies were evaluated; one included two of the gold mine tailings and the second focused on the platinum tailings. Simulated ambient near surface concentrations were validated with ambient monitored data for the same period as used in the model. For the Marticorena and Bergametti (1995) dust-flux scheme, only z0 had to be adjusted to provide a good fit with measured data – whereas the Shao et al. (2011) scheme resulted in significantly higher concentrations, resulting in an over-prediction of the measured data. By applying the correction factor, CF𝜂mi, to the minimally disturbed dust fraction, the predicted concentrations improved considerably. The coupling of the dust-flux schemes with a regulatory Gaussian plume model provided simulated ground level PM10 concentrations in good agreement with measured data. The best correlation was found under conditions of high wind speeds when the prevailing wind was from the direction of the tailings storage facility. This thesis demonstrates that simulated impacts from complex source groups can be performed, within an acceptable range of certainty, using widely applied dust-flux schemes. These dust-flux schemes, developed primarily for large-scale desert and arid areas, have been demonstrated to be applicable also to small-scale sources, of the order of 1 km2, and can be coupled to regularly available dispersion models for impact evaluations of wind-blown dust. The value of this improved approach to the mining and mineral processing industries are substantial, allowing for more accurate health risks and adverse environmental assessments from wind-blown dust from large material storage piles, a source category that has hitherto been difficult to quantify.

Congested traffic corridors in dense urban areas are key contributors to the degradation of urban air quality. While waiting at bus stops, transit patrons may be exposed to greater amounts of vehicle-based pollution, including particulate matter, due to their proximity to the roadway. Current guidelines for the location and design of bus stops do not take into account air quality or exposure considerations. This thesis provides a unique contribution to roadside air quality studies and presents an innovative method for the consideration of bus shelter placement. Exposure to roadside pollutants is estimated for transit riders waiting at three-sided bus stop shelters that either: 1) face roadway traffic, or 2) face away from roadway traffic. Shelters were instrumented with particulate matter monitoring equipment, sonic anemometers for wind speed and direction, and vehicle counters capable of categorizing vehicles by length. Temperature and relative humidity were gathered from a nearby monitoring station. Data were collected for two different days at three shelters during both the morning and afternoon peak periods for a total of eleven data periods. Bus shelter orientation is found to significantly affect concentration of four sizes of particulate matter: ultrafine particles, PM1, PM2.5, and PM10. Shelters with an opening oriented towards the roadway were observed to have significantly higher concentrations inside the shelter than outside the shelter. In contrast, shelters oriented away from the roadway were observed to have significantly lower concentrations inside the shelter than outside the shelter. The differences in average particulate matter concentrations are statistically significant across all four sizes of particulate matter studied. Additional correlation and linear regression investigation reveals interactions between particulate concentrations and built environment characteristics, vehicle flow, and weather conditions. Temperature and relative humidity played a large role in the diurnal variation of average concentration levels. In all instances, particulate concentrations were greater during the morning period, often substantially so. Particulate concentrations are shown to vary based on both wind speed and direction. Vehicle flow is correlated with particulate levels, though significance is not consistent. Lagged vehicle flow is demonstrated to be more consistently significant. Regression analysis suggests weather factors such as wind, temperature, and relative humidity explain roughly 70% of particulate variation, while vehicle flow explains less than 6%.