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Many chemicals off-gas or leech into indoor environments from sources such as consumer products, furnishings, and building materials. An understanding of the pathways from the sources to human exposure is vital in order to implement control strategies and lower exposure. Objects containing Brominated flame retardants (BFRs), one class of semivolatile organic compounds (SVOCs), burn more slowly during combustion. BFRs, especially polybrominated diphenyl ethers (PBDEs), are used in electronic devices including casings and circuit boards. Heat from internal circuitry increases the BFR vapor pressure and the partition coefficient, enhancing its transport out of the substrate and into the indoor environment. In this work, a computer tower in an office setting provides a case study to examine the emissions of, and exposure to, PBDEs. the case of a computer tower, the cooling fan increases the mass transfer coefficient, further increasing emissions. During computer use, the emission rate of PBDEs from the interior of the case is more than double the emission rate from the exterior of the case due to elevated internal temperatures and higher mass transfer due to the cooling fan. The concentration of PBDEs in the room air increases 40 - 80% for every 5°C increase inside the computer case, depending on the PBDE congener. Such enhanced emissions are a concern since recent studies have shown adverse health effects of PBDEs on human health. The major contributions of this work are: A model was developed that is useful for SVOC emissions for various heat and mass transfer situations, including diffusion through the slab and convective boundary conditions on each side of the slab, which may be simplified if the situation warrants; A systematic propagation of the uncertainties and variability of the model parameters was accomplished by using a Monte Carlo method for the input of the parameters into the model; A polydisperse indoor particle distribution was used as a sink, identifying the size-discretized particle phase PBDE concentration; An exposure assessment showed that the inhalation pathway for PBDEs in the gas and particulate phases is relevant and that the particulate phase exposure is dominant. / text

published_or_final_version / Architecture / Master / Master of Philosophy

Research was initiated to examine the feasibility of removing the majority of 4-PCH from the XSBR latex employed in carpet manufacturing. The reduction of 4-PCH from such latices would lend insight into the control of certain carpet related illnesses.

Problems associated with instruments used to measure low levels of NO₂ include non-specificity, low sensitivity, and an uncharacterized dependence on environmental conditions. MDA Scientific has recently introduced a continuous colorimetric tape technique (chemcassette) to monitor for pollutant gases. Advantages of this technology include ease of use, fast-response alarm capability, and adaptability to measure different pollutants. This research characterized and compared chemcassette performance for NO₂ with other low-level NO₂ monitoring technologies including the luminox LMA-3 monitor and the EPA reference CSI chemiluminescnt monitor. The test protocol was based on EPA procedures. The chemcassette was found to be sensitive to temperature and relative humidity effects. The chemiluminescent monitor had the best overall performance. The luminox monitor displayed temperature dependence. Variation in stability of the chemcassette optical system, tape paper uniformity, and possible interference from ozone were characterized. (Abstract shortened with permission of author.)

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Many applied statistical applications face the potential problem of model contamination and measurement error. The form and degree of contamination as well as the measurement error are usually unknown and sample-specific, which brings additional challenges for researchers. In this thesis, we have proposed several Bayesian inference models to address these issues, with the application to one type of special data for allergen concentration measurement, which is called serial dilution data and is self-calibrated. In our first chapter, we address the problem of model contamination by using a multilevel model to simultaneously flag problematic observations and estimate unknown concentrations in serial dilution data, a problem where the current approach can lead to noisy estimates and difficulty in estimating very low or high concentrations. In our second chapter, we propose the Bayesian joint contamination model for modeling multiple measurement units at the same time while adjusting for differences between experiments using the idea of global calibration, and it could account for uncertainty in both predictors and response variables in Bayesian regression. We are able to get efficacy gain by analyzing multiple experiments together while maintaining robustness with the use of hierarchical models. In our third chapter, we develop a Bayesian two-step inference model to account for measurement uncertainty propagation in regression analysis when the joint inference model is infeasible. We aim to increase model inference reliability while providing flexibility to users by not restricting the type of inference model used in the first step. For each of the proposed methods, We also demonstrate how to integrate multiple model building blocks through the idea of Bayesian workflow. In extensive simulation studies, we show that our proposed methods outperform other commonly used approaches. For the data applications, we apply the proposed new methods to the New York City Neighborhood Asthma and Allergy Study (NYC NAAS) data to estimate indoor allergen concentrations more accurately as well as reveal the underlying associations between dust mite allergen concentrations and the exhaled nitric oxide (NO) measurement for asthmatic children. The methods and tools developed here have a wide range of applications and can be used to improve lab analyses, which are crucial for quantifying exposures to assess disease risk and evaluating interventions.

The efficacy of indoor environment evaluation is, in part, a function of the reliability and validity of the different measures used. This thesis presents results of a study, conducted in a building without known problems, which compares the reliability and validity of sensory comfort components from three well-known survey questionnaires. A review of literature reveals that sensory comfort theory draws upon many disciplines including, hedonics, psychometrics, and olfaction theory. The fundamental domains thermal, air quality, lighting, and acoustics and their dimensions are identified. The conceptual model integrates these theories underlying human response to sensory comfort. The research questions involved in the selection of survey questionnaires are explored by examining sixteen indoor environment survey questionnaires. A meta-evaluation reveals that these questionnaires have three major functions, proactive, reactive, and re-evaluative studies. Finally, the methods used to analyze survey questionnaires for reliability and validity are examined. An analysis of variance shows that the order in which questions were presented did not affect responses. The reliability of the measures tested ranged from poor to good. Examination of content and face validity by expert and untrained judges demonstrates inconsistencies in common or accepted meanings of the measures considered in evaluating the indoor environment. Analysis of construct validity indicates that not all survey questionnaire variables were categorized under their expected dimensions. Contrary to advice found in the literature, this thesis suggests that the practice of combining items from different questionnaires is problematic. Finally, in buildings with known problems we can expect a relatively high degree of reliability and validity. However, the utility of such questionnaires in inventorying and assessing buildings without known problems will prove to be questionable. / Master of Urban and Regional Planning