Particulate matter (PM) air pollution is considered a top-10 contributor to (and the leading environmental risk factor for) the global burden of disease. To date, evidence on PM health effects has been gathered primarily from medium-to-large scale epidemiology studies, which have traditionally relied upon relatively crude measures of human exposure (i.e., fixed site sampling for PM mass with little to no PM composition analyses). As a result, these studies tend to emphasize the effects of PM on more sedentary populations (such as the elderly) and/or that live close to air monitoring sites. The field now recognizes that air pollution exposure is highly heterogeneous and that exposure measurement error substantially limits the linkage of exposures to specific pathologies. Recently, epidemiologic interest in mobile populations (e.g., school-aged children or working adults) has increased and the exposure assessment field has shifted towards measures and models of personal exposure to specific PM chemical constituents (and PM properties) suspected to drive human morbidity and mortality. Unfortunately existing technologies for both sampling and analysis are limited by cost, and usability. Thus, a need exists for personal PM sensors that are inexpensive, wearable (with low-burden), yet still highly sensitive and capable of measuring specific PM properties. Our team has developed technology that meets these needs: a small, portable, inexpensive micro environmental sampler and a low cost sensing chemistry that can quantify PM chemical composition both quickly and cost-effectively. During this project, we propose to 1) Evaluate and validate the sampling and analysis methods using laboratory, field, and limited personal exposure studies (R21 phase) and 2) Demonstrate performance and added scientific value through application in the Children's Health and Air Pollution in the San Joaquin Valley (CHAPS-SJV) study (R33 phase). In the first phase, we will demonstrate the usability of our technology by engaging multiple test populations (college students, 9-11 year olds in Fort Collins, CO and high school students in Fresno, CA). In the second phase, we will use the system to provide first of its kinds information on micro environmental exposures and PM composition as it relates to inflammation biomarkers for acute exposures. The resulting data will be used to improve models of air pollution exposure for children in the San Joaquin Valley with the long-term goal of improving the health of these children.
Particulate matter (PM) air pollution is a major contributor to the global burden of disease but our understanding of the sources, chemistries, and mechanisms of PM-induced disease is still limited. Our team has developed a small, wearable sampler for assessing PM exposure as a function of microenvironment, along with ultra-low-cost chemical analysis methods for metals, black carbon, and reactive oxygen species. The sensor technology developed here will empower epidemiologists to conduct personal exposure measurements that are affordable, sensitive, and specific to various etiologic agents of interest. Long term, this technology possesses the versatility to be adapted to additional agents and chemical compounds of interest while being unobtrusive enough to expand the power and precision of epidemiology to a broader set of at-risk populations: children, pregnant women, and mobile adults.
| Quinn, Casey; Miller-Lionberg, Daniel D; Klunder, Kevin J et al. (2018) Personal Exposure to PM2.5 Black Carbon and Aerosol Oxidative Potential using an Automated Microenvironmental Aerosol Sampler (AMAS). Environ Sci Technol 52:11267-11275 |
| Mettakoonpitak, Jaruwan; Miller-Lionberg, Dan; Reilly, Thomas et al. (2017) Low-Cost Reusable Sensor for Cobalt and Nickel Detection in Aerosols Using Adsorptive Cathodic Square-Wave Stripping Voltammetry. J Electroanal Chem (Lausanne) 805:75-82 |
