Exposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures. We assessed error magnitude by estimating calibration coefficients as the association between personal PM2.5 exposures from validation studies and typically available surrogate exposures.

Background: Exposure to fine particulate matter air pollutants (PM_2.5) affects heart rate variability parameters, and levels of serum proteins associated with inflammation, hemostasis and thrombosis. This study investigated sources potentially responsible for cardiovascular and hematological effects in highway patrol troopers. Results: Nine healthy young non-smoking male troopers working from 3 PM to midnight were studied on four consecutive days during their shift and the following night. Sources of in-vehicle PM_2.5 were identified with variance-maximizing rotational principal factor analysis of PM_2.5-components and associated pollutants. Two source models were calculated. Sources of in-vehicle PM_2.5 identified were 1) crustal material, 2) wear of steel automotive components, 3) gasoline combustion, 4) speed-changing traffic with engine emissions and brake wear. In one model, sources 1 and 2 collapsed to a single source. Source factors scores were compared to cardiac and blood parameters measured ten and fifteen hours, respectively, after each shift. The "speed-change" factor was significantly associated with mean heart cycle length (MCL, +7% per standard deviation increase in the factor score), heart rate variability (+16%), supraventricular ectopic beats (+39%), % neutrophils (+7%), % lymphocytes (-10%), red blood cell volume MCV (+1%), von Willebrand Factor (+9%), blood urea nitrogen (+7%), and protein C (-11%). The "crustal" factor (but not the "collapsed" source) was associated with MCL (+3%) and serum uric acid concentrations (+5%). Controlling for potential confounders had little influence on the effect estimates. Conclusion: PM_2.5 originating from speed-changing traffic modulates the autonomic control of the heart rhythm, increases the frequency of premature supraventricular beats and elicits pro-inflammatory and pro-thrombotic responses in healthy young men.

A combined epidemiological–exposure panel study was conducted during the summer of 1998 in Baltimore, Maryland. The objectives of the exposure analysis component of the 28-day study were to investigate the statistical relationships between particulate matter (PM) and related co-pollutants from numerous spatial boundaries associated with an elderly population, provide daily mass concentrations needed for the epidemiological assessment, and perform an extensive personal exposure assessment. Repeated 24-h integrated PM_2.5 (n=394) and PM₁₀ (n=170) data collections corresponding to stationary residential central indoor, individual apartment, residential outdoor and ambient monitoring were obtained using the same sampling methodology. An additional 325 PM_2.5 personal air samples were collected from a pool of 21 elderly (65+ years of age) subjects. These subjects were residents of the 18-story retirement facility where residential monitoring was conducted. Mean daily central indoor and residential apartment concentrations were approximately 10 µg/m³. Outdoor and ambient PM_2.5 concentrations averaged 22 µg/m³ with a daily range of 6.7–59.3 µg/m³. The slope of the central indoor/outdoor PM_2.5 mass relationship was 0.38. The average daily ratio of PM_2.5/PM₁₀ mass co ncentrations across the measurement sites ranged from 0.73 to 0.92. Both the central indoor and mean apartment PM_2.5 mass concentrations were highly correlated with the outdoor variables (r>0.94). The lack of traditionally recognized indoor sources of PM present within the facility might have accounted for the high degree of correlation observed between the variables. Results associated with the personal monitoring effort are discussed in depth in Part 2 of this article.

The US Environmental Protection Agency (EPA) and other federal agencies face a number of challenges in interpreting and reconciling short-duration (seconds to minutes) readings from mobile and handheld air sensors with the longer duration averages (hours to days) associated with the National Ambient Air Quality Standards (NAAQS) for the criteria pollutants-particulate matter (PM), ozone, carbon monoxide, lead, nitrogen oxides, and sulfur oxides. Similar issues are equally relevant to the hazardous air pollutants (HAPs) where chemical-specific health effect reference values are the best indicators of exposure limits; values which are often based on a lifetime of continuous exposure. A multi-agency, staff-level Air Sensors Health Group (ASHG) was convened in 2013. ASHG represents a multi-institutional collaboration of Federal agencies devoted to discovery and discussion of sensor technologies, interpretation of sensor data, defining the state of sensor-related science across each institution, and provides consultation on how sensors might effectively be used to meet a wide range of research and decision support needs. ASHG focuses on several fronts: improving the understanding of what hand-held sensor technologies may be able to deliver; communicating what hand-held sensor readings can provide to a number of audiences; the challenges of how to integrate data generated by multiple entities using new and unproven technologies; and defining best practices in communicating health-related messages to various audiences. This review summarizes the challenges, successes, and promising tools of those initial ASHG efforts and Federal agency progress on crafting similar products for use with other NAAQS pollutants and the HAPs. NOTE: The opinions expressed are those of the authors and do not necessary represent the opinions of their Federal Agencies or the US Government. Mention of product names does not constitute endorsement.