A Thesis submitted to The University of Arizona College of Medicine - Phoenix in partial fulfillment of the requirements for the Degree of Doctor of Medicine. / The rate of technology expansion is rapidly covering even the most remote parts of the globe and in the lowest resource settings. With globalization however, low and middle income areas are facing emerging health issues such as injuries and chronic medical conditions. With these illnesses, there are inevitable demands on emergency services. It has been thought that technology be utilized to augment emergency medical care in such settings where formal Emergency Medical Services. To aggregate and analyze the existing literature on the topic a systematic literature review was conducted. This study analyzed the existing literature on prehospital emergency care in settings in which no formal EMS services were utilized. Four databases were searched with inclusion and exclusion criteria, yielding 1782 results. The initial screening excluded all but 21 articles. Of the 21 articles in full review, 15 were included in the final review. Studies included in the final review were grouped into those reporting outcomes from five categories: Feasibility, Quality of Care, Response Time, Patient Outcomes, and Cost Effectiveness. Only one study was identified to be of high quality. There was a lack of studies with adequate statistical analysis to conduct statistical aggregation. Most studies however reported prehospital telemedicine in settings without EMS to be feasible, provide quality care, are be cost effective. However, the lack of statistical analysis makes it difficult to make conclusions. Also, several studies did show response time of a trained basic life support volunteer to be faster than EMS in many of the settings. But no positive health outcomes were observed in patients treated with projects utilizing technology in the prehospital setting. The prehospital emergency medicine setting is a young field of study that may have significant hurdles in application. The studies conducted have shown promise in the use of technology in prehospital settings without formal EMS services, but are not robust enough to make strong conclusions or recommendations that could be put into practice. Thus, more robust, statistically oriented research is imperative in the field so that we can fully explore the potential of technology in the prehospital setting, especially in low resource and rural settings without formal EMS services. With more robust studies, we can hope to integrate new technologies into practice and better serve the populations without adequate EMS coverage to provide more timely emergency care.

Anthropogenic emissions into the troposphere can impact air quality, leading to poorer health outcomes in the affected areas. Volatile organic compounds (VOCs) are a group of chemical compounds, including some which are toxic, that are precursors in the formation of ground-level ozone and secondary organic aerosols. VOCs have a variety of sources, and the distribution of atmospheric VOCs differs significantly over time and space. Historically, the large number of chemical species present at low concentrations (parts-per-trillion to parts-per-billion by volume) have made VOCs difficult to measure in ambient air. However, with improvements in analytical instrumentation, these measurements are becoming more common place. Direct mass spectrometry (MS), such as membrane introduction mass spectrometry (MIMS) and proton-transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) facilitate real-time, continuous measurements of VOCs in air, with full scan mass spectral data capturing changes in chemical composition with high temporal resolution. Operated on-road, mobilized direct MS has been used for quantitative mapping of VOCs at the neighborhood scale, but identifying VOC sources based on the observed mixture of molecules in the full scan MS dataset has yet to be explored. This dissertation describes the use of chemometric techniques to interrogate full scan MS data, and the progression from discriminating VOC samples of known chemical composition based on full scan MIMS data through to the apportionment of VOC sources measured continuously with a PTR-ToF-MS system operating in a moving vehicle. Lab‐constructed VOC samples of known chemical composition and concentration demonstrated the use of principal component analysis (PCA) to discriminate, and k-nearest neighbours to classify, samples based on normalized full scan MIMS data. Furthermore, multivariate curve resolution-alternating least squares (MCR-ALS) was used to resolve mixtures into molecular component contributions. PCA was also used to discriminate ‘real-world’ VOC mixtures (e.g., woodsmoke VOCs, headspace above aqueous hydrocarbon samples) of unknown chemical composition measured by MIMS. Using vehicle mounted MIMS and PTR-ToF-MS systems, full scan MS data of ambient atmospheric VOCs were collected and PCA was applied to the normalized full scan MS data. A supervised analysis performed PCA on samples collected near known VOC sources, while an unsupervised analysis using PCA followed by cluster analysis was used to identify groups in a continuous, time series PTR-ToF-MS dataset measured between Nanaimo and Crofton, British Columbia (BC). In both the supervised and unsupervised analysis, samples impacted by emissions from different sources (e.g., internal combustion engines, sawmills, composting facilities, pulp mills) were discriminated. With PCA, samples were discriminated based on differences in the observed full scan MS data, however real-world samples are often impacted by multiple VOC sources. MCR-weighted ALS (MCR-WALS) was applied to the continuous, time series PTR-ToF-MS data from three field campaigns on Vancouver Island, BC for source apportionment. Variable selection based on signal-to-noise ratios was used to reduce the mass list while retaining the observed m/z that capture changes in the mixture of VOCs measured, improving model results, and reducing computation time. Both point (e.g., anthropogenic hydrocarbon emissions, pulp mill emissions) and diffuse (e.g., VOCs from forest fire smoke) VOC sources were identified in the data, and were apportioned to determine their contributions to the measured samples. The data analyzed captured fine scale changes in the ambient VOCs present in the air, and geospatial maps of each individual source, and of the source apportionment were used to visualize the distribution of VOC sources across the sampling area. This work represents the first use of MCR-WALS to identify and apportion ambient VOC sources based on continuous PTR-ToF-MS data measured from a moving vehicle. The methods described can be applied to larger scale field campaigns for the source apportionment of VOCs across multiple days to capture diurnal and seasonal variations. Identifying spatial and temporal trends in the sources of VOCs at the regional scale can help to identify pollution ‘hot spots’ and inform evidence-based public policy for improving air quality. / Graduate / 2022-08-17