Steven J. Dutton

The temporal lag structure of short-term associations of fine particulate matter chemical constituents and cardiovascular and respiratory hospitalizations.

Background: In air pollution time-series studies, the temporal pattern of the association of fine particulate matter (PM2.5; particulate matter ≤ 2.5 µm in aerodynamic diameter) and health end points has been observed to vary by disease category. The lag pattern of PM2.5 chemical constituents has not been well investigated, largely because daily data have not been available. Objectives: We explored the lag structure for hospital admissions using daily PM2.5 chemical constituent data for 5 years in the Denver Aerosol Sources and Health (DASH) study. Methods: We measured PM2.5 constituents, including elemental carbon, organic carbon, sulfate, and nitrate, at a central residential site from 2003 through 2007 and linked these daily pollution data to daily hospital admission counts in the five-county Denver metropolitan area. Total hospital admissions and subcategories of respiratory and cardiovascular admissions were examined. We assessed the lag structure of relative risks (RRs) of hospital admissions for PM2.5 and four constituents on the same day and from 1 to 14 previous days from a constrained distributed lag model; we adjusted for temperature, humidity, longer-term temporal trends, and day of week using a generalized additive model. Results: RRs were generally larger at shorter lags for total cardiovascular admissions but at longer lags for total respiratory admissions. The delayed lag pattern was particularly prominent for asthma. Elemental and organic carbon generally showed more immediate patterns, whereas sulfate and nitrate showed delayed patterns. Conclusion: In general, PM2.5 chemical constituents were found to have more immediate estimated effects on cardiovascular diseases and more delayed estimated effects on respiratory diseases, depending somewhat on the constituent.

Estimating effects of ambient PM2.5 exposure on health using PM2.5 component measurements and regression calibration

Most air pollution and health studies conducted in recent years have examined how a health outcome is related to pollution concentrations from a fixed outdoor monitor. The pollutant effect estimate in the health model used indicates how ambient pollution concentrations are associated with the health outcome, but not how actual exposure to ambient pollution is related to health. In this article, we propose a method of estimating personal exposures to ambient PM2.5 (particulate matter less than 2.5 μm in diameter) using sulfate, a component of PM2.5 that is derived primarily from ambient sources. We demonstrate how to use regression calibration in conjunction with these derived values to estimate the effects of personal ambient PM2.5 exposure on a continuous health outcome, forced expiratory volume in 1 s (FEV1), using repeated measures data. Through simulation, we show that a confidence interval (CI) for the calibrated estimator based on large sample theory methods has an appropriate coverage rate. In an application using data from our health study involving children with moderate to severe asthma, we found that a 10 μg/m3 increase in PM2.5 was associated with a 2.2% decrease in FEV1 at a 1-day lag of the pollutant (95% CI: 0.0–4.3% decrease). Regressing FEV1 directly on ambient PM2.5 concentrations from a fixed monitor yielded a much weaker estimate of 1.0% (95% CI: 0.0–2.0% decrease). Relatively small amounts of personal monitor data were needed to calibrate the estimate based on fixed outdoor concentrations.

Positive Matrix Factorization of PM2.5: Comparison and Implications of Using Different Speciation Data Sets

To evaluate the utility and consistency of different speciation data sets in source apportionment of PM(2.5), positive matrix factorization (PMF) coupled with a bootstrap technique for uncertainty assessment was applied to four different 1-year data sets composed of bulk species, bulk species and water-soluble elements (WSE), bulk species and organic molecular markers (OMM), and all species. The five factors resolved by using only the bulk species best reproduced the observed concentrations of PM(2.5) components. Combining WSE with bulk species as PMF inputs also produced five factors. Three of them were linked to soil, road dust, and processed dust, and together contributed 26.0% of reconstructed PM(2.5) mass. A 7-factor PMF solution was identified using speciated OMM and bulk species. The EC/sterane and summertime/selective aliphatic factors had the highest contributions to EC (39.0%) and OC (53.8%), respectively. The nine factors resolved by including all species as input data are consistent with those from the previous two solutions (WSE and bulk species, OMM and bulk species) in both factor profiles and contributions (r = 0.88-1.00). The comparisons across different solutions indicate that the selection of input data set may depend on the PM components or sources of interest for specific source-oriented health study.

Shear attenuation and dispersion in MgO

Abstract An understanding of anelastic effects on seismic wave propagation is crucial for developing accurate seismic models of the mantle. The lower mantle is thought to contain a significant volume fraction, approximately 20%, of magnesiowustite, (Mg,Fe)O, in addition to the dominant silicate perovskite. Weaker magnesiowustite may dominate the rheological response of the lower mantle. It may also account for the shear attenuation observed in the lower mantle. We have measured the complex torsional modulus of a single crystal of the magnesiowustite end member periclase, MgO, at small strains, seismic frequencies, and high temperature. The attenuation is approximately 0.030 ( Q approximately 33) at 0.003 Hz and 1500 K with a dislocation density of approximately 5 × 109 m−2. The corresponding dispersion reduces the shear velocity of MgO at 0.001 Hz and 1500 K by approximately 4% relative to ultrasonic values. To the extent that magnesiowustite behaves similarly to MgO, it appears to be a good candidate to account for a major portion of lower-mantle attenuation.

Indoor Pollutant Levels from the Use of Unvented Natural Gas Fireplaces in Boulder, Colorado

ABSTRACT High CO and NO2 concentrations have been documented in homes with unvented combustion appliances, such as natural gas fireplaces. In addition, polycyclic aromatic hydrocarbons (PAH) are emitted from incomplete natural gas combustion. The acute health risks of CO and NO2 exposure have been well established for the general population and for certain high-risk groups, including infants, the elderly, and people with heart disease or asthma. Health effects from PAH exposure are less well known, but may include increased risk of cancer. We monitored CO emissions during the operation of unvented natural gas fireplaces in two residences in Boulder, CO, at various times between 1997 and 2000. During 1999, we expanded our tests to include measurements of NO2 and PAH. Results show significant pollutant accumulation indoors when the fireplaces were used for extended periods of time. In one case, CO concentrations greater than 100 ppm accumulated in under 2 hr of operation; a person at rest exposed for 10 hr to this environment would get a mild case of CO poisoning with an estimated 10% carboxyhemoglobin level. Appreciable NO2 concentrations were also detected, with a 4-hr time average reaching 0.36 ppm. Similar time-average total PAH concentrations reached 35 ng/m3. The results of this study provide preliminary insights to potential indoor air quality problems in homes operating unvented natural gas fireplaces in Boulder.

Regional variations in particulate matter composition and the ability of monitoring data to represent population exposures.

Epidemiologic studies have demonstrated that relative risks for mortality associated with ambient particulate matter (PM) concentrations vary with location in the U.S. with larger associations in both magnitude and strength observed in the East compared to the West. Two factors potentially contributing to the regional heterogeneity in PM-mortality associations observed are regional variations in PM composition and the ability of a single PM concentration estimate to represent the community-average exposure for an entire study area, which may lead to regional differences in exposure error. Variations in PM composition and the proportion of the population living in proximity to ambient monitors, an indicator of potential exposure error, are examined for the 20 most populated and 10 mid-size study areas included in the National Morbidity, Mortality and Air Pollution Study (NMMAPS). Clear differences in PM and in the proportion of the population living in proximity to ambient monitors are found for some of these cities. Differences in these exposure parameters may be interpreted more reasonably in terms of north-south differences compared to east-west differences, and may need to be considered when conducting future epidemiologic studies that aim to examine the factors that influence the regional variability in PM-mortality associations.

The sensitivity of health effect estimates from time-series studies to fine particulate matter component sampling schedule

The US Environmental Protection Agency air pollution monitoring data have been a valuable resource commonly used for investigating the associations between short-term exposures to PM2.5 chemical components and human health. However, the temporally sparse sampling on every third or sixth day may affect health effect estimation. We examined the impact of non-daily monitoring data on health effect estimates using daily data from the Denver Aerosol Sources and Health (DASH) study. Daily concentrations of four PM2.5 chemical components (elemental and organic carbon, sulfate, and nitrate) and hospital admission counts from 2003 through 2007 were used. Three every-third-day time series were created from the daily DASH monitoring data, imitating the US Speciation Trend Network (STN) monitoring schedule. A fourth, partly irregular, every-third-day time series was created by matching existing sampling days at a nearby STN monitor. Relative risks (RRs) of hospital admissions for PM2.5 components at lags 0–3 were estimated for each data set, adjusting for temperature, relative humidity, longer term temporal trends, and day of week using generalized additive models, and compared across different sampling schedules. The estimated RRs varied somewhat between the non-daily and daily sampling schedules and between the four non-daily schedules, and in some instances could lead to different conclusions. It was not evident which features of the data or analysis were responsible for the variation in effect estimates, although seeing similar variability in resampled data sets with relaxation of the every–third-day constraint suggests that limited power may have had a role. The use of non-daily monitoring data can influence interpretation of estimated effects of PM2.5 components on hospital admissions in time-series studies.

Framework for assessing causality of air pollution-related health effects for reviews of the National Ambient Air Quality Standards

ABSTRACT To inform regulatory decisions on the risk due to exposure to ambient air pollution, consistent and transparent communication of the scientific evidence is essential. The United States Environmental Protection Agency (U.S. EPA) develops the Integrated Science Assessment (ISA), which contains evaluations of the policy‐relevant science on the effects of criteria air pollutants and conveys critical science judgments to inform decisions on the National Ambient Air Quality Standards. This article discusses the approach and causal framework used in the ISAs to evaluate and integrate various lines of scientific evidence and draw conclusions about the causal nature of air pollution‐induced health effects. The framework has been applied to diverse pollutants and cancer and noncancer effects. To demonstrate its flexibility, we provide examples of causality judgments on relationships between health effects and pollutant exposures, drawing from recent ISAs for ozone, lead, carbon monoxide, and oxides of nitrogen. U.S. EPAs causal framework has increased transparency by establishing a structured process for evaluating and integrating various lines of evidence and uniform approach for determining causality. The framework brings consistency and specificity to the conclusions in the ISA, and the flexibility of the framework makes it relevant for evaluations of evidence across media and health effects. HIGHLIGHTSSystematic approach for drawing causal conclusions on effects of air pollutants.Provides consistency, clarity, transparency, and flexibility.Informs decisions on U.S. air quality standards.Examples from recent assessments provided.

A systematic review of cardiovascular emergency department visits, hospital admissions and mortality associated with ambient black carbon

BACKGROUND Black carbon (BC) is a ubiquitous component of particulate matter (PM) emitted from combustion-related sources and is associated with a number of health outcomes. OBJECTIVES We conducted a systematic review to evaluate the potential for cardiovascular morbidity and mortality following exposure to ambient BC, or the related component elemental carbon (EC), in the context of what is already known about the associations between exposure to fine particulate matter (PM2.5) and cardiovascular health outcomes. DATA SOURCES We conducted a stepwise systematic literature search of the PubMed database and employed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for reporting our results. STUDY ELIGIBILITY CRITERIA Studies meeting inclusion criteria (i.e., include a quantitative measurement of BC or EC used to characterize exposure and an effect estimate of the association of the exposure metric with ED visits, hospital admissions, or mortality due to cardiovascular disease) were evaluated for risk of bias in study design and results. STUDY APPRAISAL AND SYNTHESIS METHODS Risk of bias evaluations assess some aspects of internal validity of study findings based on study design, conduct, and reporting and identify potential issues related to confounding or other biases. RESULTS The results of our systematic review demonstrate similar results for BC or EC and PM2.5; that is, a generally modest, positive association of each pollutant measurement with cardiovascular emergency department visits, hospital admissions, and mortality. There is no clear evidence that health risks are greater for either BC or EC when compared to one another, or when either is compared to PM2.5. LIMITATIONS We were unable to adequately evaluate the role of copollutant confounding or differential spatial heterogeneity for BC or EC compared to PM2.5. CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS Overall, the evidence at present indicates that BC or EC is consistently associated with cardiovascular morbidity and mortality but is not sufficient to conclude that BC or EC is independently associated with these effects rather than being an indicator for PM2.5 mass. SYSTEMATIC REVIEW REGISTRATION NUMBER Not available.