Environmental pollution has been one of the most challenging problems in modern society and more and more health issues are now linked to environmental pollution and especially, air pollution. Certain sensitive group like patients with asthma are highly influenced by the environmental air quality and knowledge of the daily air pollution exposure is of great importance for the management and prevention of asthma attack. Hence small form factor, real time, accurate, sensitive and easy to use portable devices for environmental monitoring are of great value.

Three novel image-based methods for quantitative real time environmental monitoring were introduced and the sensing principle, sensor performances were evaluated through simulation and field tests. The first sensing principle uses surface plasmon resonance (SPR) image and home-made molecular sieve (MS) column to realize real time chemical separation and detection. SPR is sensitive and non-specific, which makes it a desirable optical method for sensitive biological and chemical sensing, the miniaturized MS column provides small area footprint and makes it possible for SPR to record images of the whole column area. The innovative and system level integration approach provide a new way for simultaneous chemical separation and detection. The second sensor uses scattered laser light, Complementary metal-oxide-semiconductor (CMOS) imager and image processing to realize real-time particulate matter (PM) sensing. Complex but low latency algorithm was developed to obtain real time information for PM including PM number, size and size distribution. The third sensor uses gradient based colorimetric sensor, absorbance light signal and image processing to realize real-time Ozone sensing and achieved high sensitivity and substantially longer lifetime compared to conventional colorimetric sensors. The platform provides potential for multi-analyte integration and large-scale consumer use as wearable device.

The three projects provide novel, state-of-the-art and sensitive solutions for environmental and personal exposure monitoring. Moreover, the sensing platforms also provide tools for clinicians and epidemiologists to conduct large scale clinical studies on the adverse health effects of pollutants on various kinds of diseases.

Capnography is the monitoring of concentrations of carbon dioxide in exhaled breath. It allows reliable insight into patients' metabolism, ventilation, and blood circulation. Capnography has become an integral part of anesthesiology monitoring in operating rooms. However, its used is limited in other contexts due to deeply engrained protocols, size of capnographs, and the complexity of its interpretation. Intensive care units and in-home use could greatly benefit by a widespread usage of capnographs. Measuring methods include infrared spectroscopy, mass spectroscopy, and chemical colorimetric analysis. Infrared technology is currently the most widely used and cost-effective method for measuring carbon dioxide. However, this device can be bulky and costly. A novel portable breath CO2 analyzer was developed for this purpose. The analyzer features an accurate colorimetric CO2 sensor that can analyze ETCO2 in real time. Many advancements have been in made in the sensor fabrication process. Nevertheless, research on optimal packaging conditions and accelerated aging times have been limited. In this experiment, carbon dioxide sensors were packaged at four different environmental conditions to test their long-term stability. This was done to determine if these conditions had an effect on sensor degradation. In the second part of the experiment, a separate batch of sensors was placed inside an oven at 48 oC to investigate the effect of stabilization temperature dependence and accelerated aging. In conclusion, the data obtained from the sensors packaged at different conditions could not be concluded to be statistically different. Sensors packaged at ambient conditions had the highest average value at 0.45030 V and the ones at controlled 33% humidity had the lowest at 0.39348 V. The sensors packaged at 8.25% CO2 had the smallest variance in their voltage measurements. From these data, it can be concluded that environmental testing conditions had the greatest effect on the measured signal. The oven experiment showed that sensors rapidly stabilize at high temperature and these stay constant after reaching this stabilization. For future work, the signal difference at different environmental conditions should be done. Control of environmental conditions can be achieved by building a glove box to control temperature and humidity.

Background:
Ketogenic diets are high fat and low carbohydrate or very low carbohydrate diets, which render high production of ketones upon consumption known as nutritional ketosis (NK). Ketosis is also produced during fasting periods, which is known as fasting ketosis (FK). Recently, the combinations of NK and FK, as well as NK alone, have been used as resources for weight loss management and treatment of epilepsy.

Methods:
A crossover study design was applied to 11 healthy individuals, who maintained moderately sedentary lifestyle, and consumed three types of diet randomly assigned over a three-week period. All participants completed the diets in a randomized and counterbalanced fashion. Each weekly diet protocol included three phases: Phase 1 - A mixed diet with ratio of fat: (carbohydrate + protein) by mass of 0.18 or the equivalence of 29% energy from fat from Day 1 to Day 5. Phase 2- A mixed or a high-fat diet with ratio of fat: (carbohydrate + protein) by mass of approximately 0.18, 1.63, or 3.80 on Day 6 or the equivalence of 29%, 79%, or 90% energy from fat, respectively. Phase 3 - A fasting diet with no calorie intake on Day 7. Caloric intake from diets on Day 1 to Day 6 was equal to each individual’s energy expenditure. On Day 7, ketone buildup from FK was measured.

Results:
A statistically significant effect of Phase 2 (Day 6) diet was found on FK of Day 7, as indicated by repeated analysis of variance (ANOVA), F(2,20) = 6.73, p < 0.0058. Using a Fisher LDS pair-wise comparison, higher significant levels of acetone buildup were found for diets with 79% fat content and 90% fat content vs. 29% fat content (with p = 0.00159**, and 0.04435**, respectively), with no significant difference between diets with 79% fat content and 90% fat content. In addition, independent of the diet, a significantly higher ketone buildup capability of subjects with higher resting energy expenditure (R[superscript 2] = 0.92), and lower body mass index (R[superscript 2] = 0.71) was observed during FK.

Biosensors aiming at detection of target analytes, such as proteins, microbes, virus, and toxins, are widely needed for various applications including detection of chemical and biological warfare (CBW) agents, biomedicine, environmental monitoring, and drug screening. Surface Plasmon Resonance (SPR), as a surface-sensitive analytical tool, can very sensitively respond to minute changes of refractive index occurring adjacent to a metal film, offering detection limits up to a few ppt (pg/mL). Through SPR, the process of protein adsorption may be monitored in real-time, and transduced into an SPR angle shift. This unique technique bypasses the time-consuming, labor-intensive labeling processes, such as radioisotope and fluorescence labeling. More importantly, the method avoids the modification of the biomarker’s characteristics and behaviors by labeling that often occurs in traditional biosensors. While many transducers, including SPR, offer high sensitivity, selectivity is determined by the bio-receptors. In traditional biosensors, the selectivity is provided by bio-receptors possessing highly specific binding affinity to capture target analytes, yet their use in biosensors are often limited by their relatively-weak binding affinity with analyte, non-specific adsorption, need for optimization conditions, low reproducibility, and difficulties integrating onto the surface of transducers. In order to circumvent the use of bio-receptors, the competitive adsorption of proteins, termed the Vroman effect, is utilized in this work. The Vroman effect was first reported by Vroman and Adams in 1969. The competitive adsorption targeted here occurs among different proteins competing to adsorb to a surface, when more than one type of protein is present. When lower-affinity proteins are adsorbed on the surface first, they can be displaced by higher-affinity proteins arriving at the surface at a later point in time. Moreover, only low-affinity proteins can be displaced by high-affinity proteins, typically possessing higher molecular weight, yet the reverse sequence does not occur. The SPR biosensor based on competitive adsorption is successfully demonstrated to detect fibrinogen and thyroglobulin (Tg) in undiluted human serum and copper ions in drinking water through the denatured albumin.

Monitoring of air pollutants is critical for many applications and studies. In

order to access air pollutants with high spatial and temporal resolutions, it is

necessary to develop an affordable, small size and weight, low power, high

sensitivity and selectivity, and wireless enable device that can provide real time

monitoring of air pollutants. Three different kind of such devices are presented, they

are targeting environmental pollutants such as volatile organic components (VOCs),

nitrogen dioxide (NO2) and ozone. These devices employ innovative detection

methods, such as quartz crystal tuning fork coated with molecularly imprinted

polymer and chemical reaction induced color change colorimetric sensing. These

portable devices are validated using the gold standards in the laboratory, and their

functionality and capability are proved during the field tests, make them great tools

for various air quality monitoring applications.

The accurate and fast determination of carbon dioxide (CO2) levels is critical for many health and environmental applications. For example, the analysis of CO2 levels in exhaled breath allows for the evaluation of systemic metabolism, perfusion, and ventilation, and provides the doctors and patients with a non-invasive and simple method to predict the presence and severity of asthma, and Chronic Obstructive Pulmonary Disease (COPD). Similarly, the monitoring of CO2 levels in the atmosphere allows for assessment of indoor air quality (IAQ) as the indoor CO2 levels have been proved to be associated with increased prevalence of certain mucous membrane and respiratory sick building syndrome (SBS) symptoms. A pocket-sized CO2 analyzer has been developed for real-time analysis of breath CO2 and environmental CO2. This CO2 analyzer is designed to comprise two key components including a fluidic system for efficient gas sample delivery and a colorimetric detection unit integrated into the fluidic system. The CO2 levels in the gas samples are determined by a disposable colorimetric sensor chip. The sensor chip is a novel composite based sensor that has been optimized to provide fast and reversible response to CO2 over a wide concentration range, covering the needs of both environmental and health applications. The sensor is immune to the presence of various interfering gases in ambient or expired air. The performance of the sensor in real-time breath-by-breath analysis has also been validated by a commercial CO2 detector. Furthermore, a 3D model was created to simulate fluid dynamics of breath and chemical reactions for CO2 assessment to achieve overall understanding of the breath CO2 detection process and further optimization of the device.

An imaging measurement technique is developed using surface plasmon resonance. Plasmonic-based electrochemical current imaging (P-ECi) method has been developed to image the local electrochemical current optically, it allows us to measure the current density quickly and non-invasively [1, 2]. In this thesis, we solve the problems when we extand the P-ECi technique to the field of thin film system. The P-ECi signal in thin film structure was found to be directly proportional to the electrochemical current. The upper-limit of thin film thickness to use the proportional relationship between P-ECi signal and EC current was discussed by experiment and simulation. Furthermore, a new algorithm which can calculate the current density from P-ECi signal without any thickness limitation is developed and tested. Besides, surface plasmon resonance is useful phenomenon which can be used to detect the changes in the refractive index near the gold sensing surface. With the assistance of pH indicator, by applied EC potential on the gold film as the working electrode, the detection of H2 evolution reaction can be enhanced. This measurement technique is useful in analyzing local EC information and H2 evolution. References [1] S. Wang, et al., "Electrochemical Surface Plasmon Resonance: Basic Formalism and Experimental Validation," Analytical Chemistry, vol. 82, pp. 935-941, 2010/02/01 2010. [2] X. Shan, et al., "Imaging Local Electrochemical Current via Surface Plasmon Resonance," Science, vol. 327, pp. 1363-1366, March 12, 2010 2010.

This work demonstrates the integration of a wearable particulate detector and a wireless chemical sensor into a single portable system. The detection philosophy of the chemical sensor is based on highly selective and sensitive microfabricated quartz tuning fork arrays and the particle detector detects the particulate level in real-time using a nephelometric (light scattering) approach. The device integration is realized by carefully evaluating the needs of flow rate, power and data collection. Validation test has been carried out in both laboratory and in field trials such as parking structures and highway exits with high and low traffic emissions. The integrated single portable detection system is capable of reducing the burden for a child to carry multiple devices, simplifying the task of researchers to synchronize and analyze data from different sensors, and minimizing the overall weight, size, and cost of the sensor. It also has a cell phone for data analysis, storage, and transmission as a user-friendly interface. As the chemical and particulate levels present important exposure risks that are of high interests to epidemiologists, the integrated device will provide an easier, wearable and cost effective way to monitor it.

Windows based mobile application for m-health and environmental monitoring sensor devices were developed and tested. With the number of smartphone users exponentially increasing, the applications developed for m-health and environmental monitoring devices are easy to reach the general public, if the applications are simple, user-friendly and personalized. The sensing device uses Bluetooth to communicate with the smartphone, providing mobility to the user. Since the device is small and hand-held, the user can put his smartphone in his pocket, connected to the device in his hand and can move anywhere with it. The data processing performed in the applications is verified against standard off the shelf software, the results of the tests are discussed in this document. The user-interface is very simple and doesn't require many inputs from the user other than during the initial setting when they have to enter their personal information for the records. The m-health application can be used by doctors as well as by patients. The response of the application is very quick and hence the patients need not wait for a long time to see the results. The environmental monitoring device has a real-time plot displayed on the screen of the smartphone showing concentrations of total volatile organic compounds and airborne particle count in the environment at the location of the device. The programming was done with Microsoft Visual Studio and was written on VB.NET platform. On the applications, the smartphone receives data as raw binary bytes from the device via Bluetooth and this data is processed to obtain the final result. The final result is the concentration of Nitric Oxide in ppb in the Asthma Analyzer device. In the environmental monitoring device, the final result is the concentration of total Volatile Organic Compounds and the count of airborne Particles.