Recent studies have associated short-term exposure to respirable particulate matter (PM10) exposure with peak flow decrements, increased symptoms of respiratory irritation, increased use of asthma medications, and increased hospitalization for asthma. Increased mortality from chronic respiratory disease has also been reported. To help confirm whether PM10 exposure is a risk factor for the exacerbation of asthma, we compiled daily records of asthma emergency room visits from eight hospitals in the Seattle area. In Poisson regressions controlling for weather, season, time trends, age, hospital, and day of the week, the daily counts of emergency room visits for persons under age 65 were significantly associated with PM10 exposure on the previous day. The mean of the previous 4 days' PM10 was a better predictor (p < 0.005). The relative risk for a 30 micrograms/m3 increase in PM10 was 1.12 (95% confidence interval 1.20 to 1.04). Daily PM10 concentrations never exceeded 70% of the current ambient air quality standards during the period. The consistency of investigations of the health effects of PM10 suggest that increased attention should be given to the control of particulate matter air pollution.

Snow samples obtained at 36 sites in Alaska, Canada, Greenland, Russia, and the Arctic Ocean in early 2007 were analyzed for light-absorbing aerosol concentration together with a suite of associated chemical species. The light absorption data, interpreted as black carbon concentrations, and other chemical data were input into the EPA PMF 1.1 receptor model to explore the sources for black carbon in the snow. The analysis found four factors or sources: two distinct biomass burning sources, a pollution source, and a marine source. The first three of these were responsible for essentially all of the black carbon, with the two biomass sources (encompassing both open and closed combustion) together accounting for >90% of the black carbon.

The contribution of outdoor particulate matter (PM) to residential indoor concentrations is currently not well understood. Most importantly, separating indoor PM into indoor- and outdoor-generated components will greatly enhance our knowledge of the outdoor contribution to total indoor and personal PM exposures. This paper examines continuous light scattering data at 44 residences in Seattle, WA. A newly adapted recursive model was used to model outdoor-originated PM entering indoor environments. After censoring the indoor time-series to remove the influence of indoor sources, nonlinear regression was used to estimate particle penetration (P, 0.94 +/- 0.10), air exchange rate (a, 0.54 +/- 0.60 h(-1)), particle decay rate (k, 0.20 +/- 0.16 h(-1)), and particle infiltration (F(inf), 0.65 +/- 0.21) for each of the 44 residences. All of these parameters showed seasonal differences. The F(inf) estimates agree well with those estimated from the sulfur-tracer method (R2 = 0.78). The F(inf) estimates also showed robust and expected behavior when compared against known influencing factors. Among our study residences, outdoor-generated particles accounted for an average of 79 +/- 17% of the indoor PM concentration, with a range of 40-100% at individual residences. Although estimates of P, a, and k were dependent on the modeling technique and constraints, we showed that a recursive mass balance model combined with our censoring algorithms can be used to attribute indoor PM into its outdoor and indoor components and to estimate an average P, a, k, and F(inf), for each residence.

We measured fractional exhaled nitric oxide (FENO), spirometry, blood pressure, oxygen saturation of the blood (SaO2), and pulse rate in 16 older subjects with asthma or chronic obstructive pulmonary disease (COPD) in Seattle, Washington. Data were collected daily for 12 days. We simultaneously collected PM10 and PM2.5 (particulate matter ≤10 μm or ≤2.5 μm, respectively) filter samples at a central outdoor site, as well as outside and inside the subjects’ homes. Personal PM10 filter samples were also collected. All filters were analyzed for mass and light absorbance. We analyzed within-subject associations between health outcomes and air pollution metrics using a linear mixed-effects model with random intercept, controlling for age, ambient relative humidity, and ambient temperature. For the 7 subjects with asthma, a 10 μg/m3 increase in 24-hr average outdoor PM10 and PM2.5 was associated with a 5.9 [95% confidence interval (CI), 2.9–8.9] and 4.2 ppb (95% CI, 1.3–7.1) increase in FENO, respectively. A 1 μg/m3 increase in outdoor, indoor, and personal black carbon (BC) was associated with increases in FENO of 2.3 ppb (95% CI, 1.1–3.6), 4.0 ppb (95% CI, 2.0–5.9), and 1.2 ppb (95% CI, 0.2–2.2), respectively. No significant association was found between PM or BC measures and changes in spirometry, blood pressure, pulse rate, or SaO2 in these subjects. Results from this study indicate that FENO may be a more sensitive marker of PM exposure than traditional health outcomes and that particle-associated BC is useful for examining associations between primary combustion constituents of PM and health outcomes.

[1] Particles generated by combustion of fossil fuels contribute to climate forcing by absorbing and scattering visible light. Residential combustion takes place in homes for heating or cooking purposes and is thought to contribute a large fraction of the global burden of anthropogenic primary particles. We present optical properties and size distributions of particulate matter emitted from three types of coal burned in residential combustors: bituminous coal, hard coal briquettes, and lignite. Emissions from these coals differ significantly and can be partially explained by differences in coal composition. For bituminous coal, particulate matter emission factors are somewhat greater than those used in current emission inventories. We observe particles for which the light absorption is weak and has a strong spectral dependence. For hard coal briquettes and lignite, emitted light absorption is low, and based on our measurements, current inventories of lightabsorbing aerosols significantly overestimate the contribution from these sources. Hard coal briquettes produce very few particles in the optically active size range. For all coals tested the size distributions required to represent the average of the emitted particles are broader than atmospheric size distributions, with geometric standard deviations between 2.2 and 3.0.

Summary Background Long-term exposure to fine particulate matter less than 2·5 μm in diameter (PM2·5) and traffic-related air pollutant concentrations are associated with cardiovascular risk. The disease process underlying these associations remains uncertain. We aim to assess association between long-term exposure to ambient air pollution and progression of coronary artery calcium and common carotid artery intima-media thickness. Methods In this prospective 10-year cohort study, we repeatedly measured coronary artery calcium by CT in 6795 participants aged 45–84 years enrolled in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) in six metropolitan areas in the USA. Repeated scans were done for nearly all participants between 2002 and 2005, for a subset of participants between 2005 and 2007, and for half of all participants between 2010 and 2012. Common carotid artery intima-media thickness was measured by ultrasound in all participants at baseline and in 2010–12 for 3459 participants. Residence-specific spatio-temporal pollution concentration models, incorporating community-specific measurements, agency monitoring data, and geographical predictors, estimated concentrations of PM2·5 and nitrogen oxides (NOX) between 1999 and 2012. The primary aim was to examine the association between both progression of coronary artery calcium and mean carotid artery intima-media thickness and long-term exposure to ambient air pollutant concentrations (PM2·5, NOX, and black carbon) between examinations and within the six metropolitan areas, adjusting for baseline age, sex, ethnicity, socioeconomic characteristics, cardiovascular risk factors, site, and CT scanner technology. Findings In this population, coronary calcium increased on average by 24 Agatston units per year (SD 58), and intima-media thickness by 12 μm per year (10), before adjusting for risk factors or air pollutant exposures. Participant-specific pollutant concentrations averaged over the years 2000–10 ranged from 9·2–22·6 μg PM2·5/m3 and 7·2–139·2 parts per billion (ppb) NOX. For each 5 μg PM2·5/m3 increase, coronary calcium progressed by 4·1 Agatston units per year (95% CI 1·4–6·8) and for each 40 ppb NOX coronary calcium progressed by 4·8 Agatston units per year (0·9–8·7). Pollutant exposures were not associated with intima-media thickness change. The estimate for the effect of a 5 μg/m3 higher long-term exposure to PM2·5 in intima-media thickness was −0·9 μm per year (95% CI −3·0 to 1·3). For 40 ppb higher NOX, the estimate was 0·2 μm per year (−1·9 to 2·4). Interpretation Increased concentrations of PM2·5 and traffc-related air pollution within metropolitan areas, in ranges commonly encountered worldwide, are associated with progression in coronary calcification, consistent with acceleration of atherosclerosis. This study supports the case for global efforts of pollution reduction in prevention of cardiovascular diseases. Funding US Environmental Protection Agency and US National Institutes of Health.

Many cohort studies in environmental epidemiology require accurate modeling and prediction of fine scale spatial variation in ambient air quality across the U.S. This modeling requires the use of small spatial scale geographic or “land use” regression covariates and some degree of spatial smoothing. Furthermore, the details of the prediction of air quality by land use regression and the spatial variation in ambient air quality not explained by this regression should be allowed to vary across the continent due to the large scale heterogeneity in topography, climate, and sources of air pollution. This paper introduces a regionalized national universal kriging model for annual average fine particulate matter (PM2.5) monitoring data across the U.S. To take full advantage of an extensive database of land use covariates we chose to use the method of Partial Least Squares, rather than variable selection, for the regression component of the model (the “universal” in “universal kriging”) with regression coefficients and residual variogram models allowed to vary across three regions defined as West Coast, Mountain West, and East. We demonstrate a very high level of cross-validated accuracy of prediction with an overall R2 of 0.88 and well-calibrated predictive intervals. In accord with the spatially varying characteristics of PM2.5 on a national scale and differing kriging smoothness parameters, the accuracy of the prediction varies by region with predictive intervals being notably wider in the West Coast and Mountain West in contrast to the East.

Most particulate matter (PM) health effects studies use outdoor (ambient) PM as a surrogate for personal exposure. However, people spend most of their time indoors exposed to a combination of indoor-generated particles and ambient particles that have infiltrated. Thus, it is important to investigate the differential health effects of indoor- and ambient-generated particles. We combined our recently adapted recursive model and a predictive model for estimating infiltration efficiency to separate personal exposure (E) to PM2.5 (PM with aerodynamic diameter ≤2.5 μm) into its indoor-generated (Eig) and ambient-generated (Eag) components for 19 children with asthma. We then compared Eig and Eag to changes in exhaled nitric oxide (eNO), a marker of airway inflammation. Based on the recursive model with a sample size of eight children, Eag was marginally associated with increases in eNO [5.6 ppb per 10-μg/m3 increase in PM2.5; 95% confidence interval (CI), −0.6 to 11.9; p = 0.08]. Eig was not associated with eNO (−0.19 ppb change per 10μg/m3). Our predictive model allowed us to estimate Eag and Eig for all 19 children. For those combined estimates, only Eag was significantly associated with an increase in eNO (Eag: 5.0 ppb per 10-μg/m3 increase in PM2.5; 95% CI, 0.3 to 9.7; p = 0.04; Eig: 3.3 ppb per 10-μg/m3 increase in PM2.5; 95% CI, −1.1 to 7.7; p = 0.15). Effects were seen only in children who were not using corticosteroid therapy. We conclude that the ambient-generated component of PM2.5 exposure is consistently associated with increases in eNO and the indoor-generated component is less strongly associated with eNO.