Current methods for identifying links between an individual's exposure to toxic air pollutants and adverse health outcomes suffer shortcomings of limited temporal and spatial granularity in exposure monitoring and the lack of real-time analysis to establish a causal relationship between an individual's exposure profile and impact on health. The goals of this proposal are 1) to provide researchers with a new tool to better assess the impacts of pollutant exposure to respiratory and cardiovascular disease, and 2) to provide individuals with an inexpensive wearable device for real-time reporting of exposure data for personalized alerts and managed care services. In the long term, a significantly improved medical understanding of air toxics would allow more relevant regulation of toxic air pollutants and more effective personal prevention plans. To achieve these goals, we propose to explore several key technologies and approaches that will enable implementation of a novel wearable, autonomous, sensor array microsystem for acute multi-pollutant exposure assessment, with real-time monitoring of toxic gases and volatile organic compounds, initially targeting SO2, NOx, CO, ozone, formaldehyde, acetaldehyde, benzene, and o-nitrobenzene. The proposed exposure assessment microsystem will integrate into an inexpensive thumb-sized device with all of the sensing, signal conditioning and data analysis necessary to overcome the limitations of existing air pollution instruments. These groundbreaking capabilities will be accomplished through innovations including 1) systematic design across all layers of the sensor microsystem to uniquely achieve desired system attributes, 2) development of new, miniaturizable, ionic liquid electrochemical sensors, 3) incorporation of multi-mode electrochemical techniques to enhance analytical information content, enabling sensitivity improvement, automated drift calibration, and sensing of diverse pollutants with a small number of physical sensor elements, and 4) design of computationally efficient sensor array processing algorithms for real-time classification and quantification of target analytes. This project will pursue the following specifc aims:
Aim 1 : Develop and characterize a miniaturized electrochemical sensor array for detection and quantification of multiple air pollutants, Aim 2: Develop compact, energy efficient, instrumentation electronics and heterogeneous sensor array processing algorithms to enable an autonomous wearable microsystem, Aim 3: Integrate and characterize a model multi-pollutant electrochemical microsystem and benchmark its performance in the field against standard exposure assessment equipment. Through a combination of accuracy, reliability, small size, low power, real-time measurement, and autonomous operation, the proposed system will provide revolutionary capability to individual exposure monitoring and the study, treatment, and prevention of health impacts of acute exposure to air toxics. Our highly skilled, multidisciplinary team has expertise in electrochemical sensor interface design and characterization, integrated microarray and microelectronic instrumentation development, and exposure assessment and health effects of air pollutants.
To enable characterization and modeling of the adverse health impacts of airborne pollutants, we propose the development of a wearable sensor array microsystem for acute multi-pollutant exposure assessment, with real-time monitoring of toxic gases and volatile organic compounds, initially targeting SO2, NOx, CO, ozone, formaldehyde, acetaldehyde, benzene, and o-nitrobenzene. The system will achieve application-critical performance attributes (including rapid and reliable sensor response, long operational lifetime, and low cost, all within a miniaturized platform suitable for individuals to carry or wear) via systematic design across all layers of the system and innovations in 1) miniaturizable ionic liquid electrochemical sensors, 2) multi-mode (voltammetric and impedance) electrochemical techniques with enhanced analytical information content, enabling sensitivity improvement, automated drift calibration, and sensing of diverse pollutants with a small number of physical sensor elements, and 3) computationally efficient sensor array processing algorithms for real-time classification and quantification of target analytes. This project would provide medical researchers with a much needed and currently non-existent tool for personal exposure assessment, over fine time scales, adding revolutionary capability to the study and treatment of acute exposure to air toxics, and leading to more relevant air pollutant regulation, intervention for individuals most susceptible to the effects of exposure, and ultimately improvement of overall public health.
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