Petros Koutrakis

Characterization of indoor particle sources using continuous mass and size monitors

ABSTRACT A comprehensive indoor particle characterization study was conducted in nine Boston-area homes in 1998 in order to characterize sources of PM in indoor environments. State-of-the-art sampling methodologies were used to obtain continuous PM2.5 concentration and size distribution particulate data for both indoor and outdoor air. Study homes, five of which were sampled during two seasons, were monitored over week-long periods. Among other data collected during the extensive monitoring efforts were 24hr elemental/organic carbon (EC/OC) particulate data as well as semi-continuous air exchange rates and time-activity information. This rich data set shows that indoor particle events tend to be brief, intermittent, and highly variable, thus requiring the use of continuous instrumentation for their characterization. In addition to dramatically increasing indoor PM25 concentrations, these data demonstrate that indoor particle events can significantly alter the size distribution and composition of indoor particles. Source event data demonstrate that the impacts of indoor activities are especially pronounced in the ultrafine (da < 0.1 um) and coarse (2.5 < da < 10 |um) modes. Among the sources of ultrafine particles characterized in this study are indoor ozone/terpene reactions. Furthermore, EC/OC data suggest that organic carbon is a major constituent of particles emitted during indoor source events. Whether exposures to indoor-generated particles, particularly from large short-term peak events, may be associated with adverse health effects will become clearer when biological mechanisms are better known.

Fine particulate air pollution and its components in association with cause-specific emergency admissions

BackgroundAlthough the association between exposure to particulate matter and health is well established, there remains uncertainty as to whether certain chemical components are more harmful than others. We explored whether the association between cause-specific hospital admissions and PM2.5 was modified by PM2.5 chemical composition.MethodsWe estimated the association between daily PM2.5 and emergency hospital admissions for cardiac causes (CVD), myocardial infarction (MI), congestive heart failure (CHF), respiratory disease, and diabetes in 26 US communities, for the years 2000-2003. Using meta-regression, we examined how this association was modified by season- and community-specific PM2.5 composition, controlling for seasonal temperature as a surrogate for ventilation.ResultsFor a 10 μg/m3 increase in 2-day averaged PM2.5 concentration we found an increase of 1.89% (95% CI: 1.34- 2.45) in CVD, 2.25% (95% CI: 1.10- 3.42) in MI, 1.85% (95% CI: 1.19- 2.51) in CHF, 2.74% (95% CI: 1.30- 4.2) in diabetes, and 2.07% (95% CI: 1.20- 2.95) in respiratory admissions. The association between PM2.5 and CVD admissions was significantly modified when the mass was high in Br, Cr, Ni, and Na+, while mass high in As, Cr, Mn, OC, Ni, and Na+ modified MI, and mass high in As, OC, and SO42- modified diabetes admissions. For these species, an interquartile range increase in their relative proportion was associated with a 1-2% additional increase in daily admissions per 10 μg/m3 increase in mass.ConclusionsWe found that PM2.5 mass higher in Ni, As, and Cr, as well as Br and OC significantly increased its effect on hospital admissions. This result suggests that particles from industrial combustion sources and traffic may, on average, have greater toxicity.

The role of particle composition on the association between PM2.5 and mortality.

Background: Although the association between exposure to particulate matter (PM) mass and mortality is well established, there remains uncertainty about which chemical components of PM are most harmful to human health. Methods: A hierarchical approach was used to determine how the association between daily PM2.5 mass and mortality was modified by PM2.5 composition in 25 US communities. First, the association between daily PM2.5 and mortality was determined for each community and season using Poisson regression. Second, we used meta-regression to examine how the pooled association was modified by community and season-specific particle composition. Results: There was a 0.74% (95% confidence interval = 0.41%–1.07%) increase in nonaccidental deaths associated with a 10 &mgr;g/m3 increase in 2-day averaged PM2.5 mass concentration. This association was smaller in the west (0.51% [0.10%–0.92%]) than in the east (0.92% [0.23%–1.36%]), and was highest in spring (1.88% [0.23%–1.36%]). It was increased when PM2.5 mass contained a higher proportion of aluminum (interquartile range = 0.58%), arsenic (0.55%), sulfate (0.51%), silicon (0.41%), and nickel (0.37%). The combination of aluminum, sulfate, and nickel also modified the effect. These species proportions explained residual variability between the community-specific PM2.5 mass effect estimates. Conclusions: This study shows that certain chemical species modify the association between PM2.5 and mortality and illustrates that mass alone is not a sufficient metric when evaluating health effects of PM exposure.

Association of Air Pollution with Increased Incidence of Ventricular Tachyarrhythmias Recorded by Implanted Cardioverter Defibrillators

Epidemiologic studies have demonstrated a consistent link between sudden cardiac deaths and particulate air pollution. We used implanted cardioverter defibrillator (ICD) records of ventricular tachyarrhythmias to assess the role of air pollution as a trigger of these potentially life-threatening events. The study cohort consisted of 203 cardiac patients with ICD devices in the Boston metropolitan area who were followed for an average of 3.1 years between 1995 and 2002. Fine particle mass and gaseous air pollution plus temperature and relative humidity were measured on almost all days, and black carbon, sulfate, and particle number on a subset of days. Date, time, and intracardiac electrograms of ICD-detected arrhythmias were downloaded at the patients’ regular follow-up visits (about every 3 months). Ventricular tachyarrhythmias were identified by electrophysiologist review. Risk of ventricular arrhythmias associated with air pollution was estimated with logistic regression, adjusting for season, temperature, relative humidity, day of the week, patient, and a recent prior arrhythmia. We found increased risks of ventricular arrhythmias associated with 2-day mean exposure for all air pollutants considered, although these associations were not statistically significant. We found statistically significant associations between air pollution and ventricular arrhythmias for episodes within 3 days of a previous arrhythmia. The associations of ventricular tachyarrhythmias with fine particle mass, carbon monoxide, nitrogen dioxide, and black carbon suggest a link with motor vehicle pollutants. The associations with sulfate suggest a link with stationary fossil fuel combustion sources.

Evaluation of the TEOM® Method for Measurement of Ambient Particulate Mass in Urban Areas

Increased interest in the health effects of ambient particulate mass (PM) has focused attention on the evaluation of existing mass measurement methodologies and the definition of PM in ambient air. The Rupprecht and Patashnick Tapered Element Oscillating MicroBalance (TEOM) method for PM is compared with time-integrated gravimetric (manual) PM methods in large urban areas during different seasons. Comparisons are conducted for both PM10 and PM2.5 concentrations. In urban areas, a substantial fraction of ambient PM can be semi-volatile material. A larger fraction of this component of PM10 may be lost from the TEOM-heated filter than the Federal Reference Method (FRM). The observed relationship between TEOM and FRM methods varied widely among sites and seasons. In East Coast urban areas during the summer, the methods were highly correlated with good agreement. In the winter, correlation was somewhat lower, with TEOM PM concentrations generally lower than the FRM. Rubidoux, CA, and two Mexican sites (Tlalnepantla and Merced) had the highest levels of PM10 and the largest difference between TEOM and manual methods. PM2.5 data from collocation of 24-hour manual samples with the TEOM are also presented. As most of the semi-volatile PM is in the fine fraction, differences between these methods are larger for PM2.5 than for PM10.

Estimating Regional Spatial and Temporal Variability of PM2.5 Concentrations Using Satellite Data, Meteorology, and Land Use Information

Background Studies of chronic health effects due to exposures to particulate matter with aerodynamic diameters ≤ 2.5 μm (PM2.5) are often limited by sparse measurements. Satellite aerosol remote sensing data may be used to extend PM2.5 ground networks to cover a much larger area. Objectives In this study we examined the benefits of using aerosol optical depth (AOD) retrieved by the Geostationary Operational Environmental Satellite (GOES) in conjunction with land use and meteorologic information to estimate ground-level PM2.5 concentrations. Methods We developed a two-stage generalized additive model (GAM) for U.S. Environmental Protection Agency PM2.5 concentrations in a domain centered in Massachusetts. The AOD model represents conditions when AOD retrieval is successful; the non-AOD model represents conditions when AOD is missing in the domain. Results The AOD model has a higher predicting power judged by adjusted R2 (0.79) than does the non-AOD model (0.48). The predicted PM2.5 concentrations by the AOD model are, on average, 0.8–0.9 μg/m3 higher than the non-AOD model predictions, with a more smooth spatial distribution, higher concentrations in rural areas, and the highest concentrations in areas other than major urban centers. Although AOD is a highly significant predictor of PM2.5, meteorologic parameters are major contributors to the better performance of the AOD model. Conclusions GOES aerosol/smoke product (GASP) AOD is able to summarize a set of weather and land use conditions that stratify PM2.5 concentrations into two different spatial patterns. Even if land use regression models do not include AOD as a predictor variable, two separate models should be fitted to account for different PM2.5 spatial patterns related to AOD availability.

Measurement of particulate aliphatic and polynuclear aromatic hydrocarbons in Santiago de Chile : source reconciliation and evaluation of sampling artifacts

Abstract Using a novel sampler, particulate organic compounds were collected in Santiago de Chile from June 9 to August 10, 1997. This sampler consists of a diffusion denuder to remove gas-phase organics prior to particle collection, a Teflon filter, and a PUF cartridge downstream of the filter. PAHs and n -alkanes were measured using gas chromatography/mass spectrometry analysis. Volatilization of particles collected on the Teflon filter varied from 15 to 85% for both n -alkanes and PAHs, with strong dependence on molecular weight. The relative distribution of n -alkanes and the values of molecular diagnostic ratios, such as Carbon preference index, indicated a mixed origin with strong anthropogenic input. Indeed, CPI values ranged from 0.66 to 1.96 (for the whole range of n -alkanes). The percent contribution of leaf “wax” n -alkanes (4.55–20.83%) indicated the low contribution of biogenic sources. In addition, the distribution pattern of PAHs was characteristic of anthropogenic emissions. The dominant contribution of combustion-related PAHs (CPAHs), 74–84%, indicated that vehicular emissions was the major source of PAHs.

Assessing the relationship between personal particulate and gaseous exposures of senior citizens living in Baltimore, MD

ABSTRACT We conducted a multi-pollutant exposure study in Baltimore, MD, in which 15 non-smoking older adult subjects (>64 years old) wore a multi-pollutant sampler for 12 days during the summer of 1998 and the winter of 1999. The sampler measured simultaneous 24-hr integrated personal exposures to PM25, PM10, SO4 2-, O3, NO2, SO2, and exhaust-related VOCs. Results of this study showed that longitudinal associations between ambient PM2.5 concentrations and corresponding personal exposures tended to be high in the summer (median Spearmans r = 0.74) and low in the winter (median Spearmans r = 0.25). Indoor ventilation was an important determinant of personal PM2.5 exposures and resulting personal-ambient associations. Associations between personal PM25 exposures and corresponding ambient concentrations were strongest for well-ventilated indoor environments and decreased with ventilation. This decrease was attributed to the increasing influence of indoor PM2 5 sources. Evidence for this was provided by SO4 2-measurements, which can be thought of as a tracer for ambient PM25. For SO4 2-, personal-ambient associations were strong even in poorly ventilated indoor environments, suggesting that personal exposures to PM2.5 of ambient origin are strongly associated with corresponding ambient concentrations. The results also indicated that the contribution of indoor PM2.5 sources to personal PM2.5 exposures was lowest when individuals spent the majority of their time in well-ventilated indoor environments. Results also indicate that the potential for confounding by PM2.5 co-pollutants is limited, despite significant correlations among ambient pollutant concentrations. In contrast to ambient concentrations, PM2.5 exposures were not significantly correlated with personal exposures to PM2.5-10, PM2.5 of non-ambient origin, O3, NO2, and SO2. Since a confounder must be associated with the exposure of interest, these results provide evidence that the effects observed in the PM2.5 epidemiologic studies are unlikely to be due to confounding by the PM2.5 co-pollutants measured in this study.

Ambient gas concentrations and personal particulate matter exposures: implications for studying the health effects of particles.

Background: Data from a previous study conducted in Baltimore, MD, showed that ambient fine particulate matter less than 2.5 &mgr;m in diameter (PM2.5) concentrations were strongly correlated with corresponding personal PM2.5 exposures, whereas ambient O3, NO2, and SO2 concentrations were weakly correlated with their personal exposures to these gases. In contrast, many of the ambient gas concentrations were reasonable surrogates of personal PM2.5 exposures. Methods: Personal multipollutant exposures and corresponding ambient air pollution concentrations were measured for 43 subjects living in Boston, MA. The cohort consisted of 20 healthy senior citizens and 23 schoolchildren. Simultaneous 24-hour integrated PM2.5, O3, NO2, and SO2 personal exposures and ambient concentrations were measured. All PM2.5 samples were also analyzed for SO42− (sulfate). We analyzed personal exposure and ambient concentration data using correlation and mixed model regression analyses to examine relationships among (1) ambient PM2.5 concentrations and corresponding ambient gas concentrations; (2) ambient PM2.5 and gas concentrations and their respective personal exposures; (3) ambient gas concentrations and corresponding personal PM2.5 exposures; and (4) personal PM2.5 exposures and corresponding personal gas exposures. Results: We found substantial correlations between ambient PM2.5 concentrations and corresponding personal exposures over the course of time. Additionally, our results support the earlier finding that summertime gaseous pollutant concentrations may be better surrogates of personal PM2.5 exposures (especially personal exposures to PM2.5 of ambient origin) than they are surrogates of personal exposures to the gases themselves. Conclusions: Particle health effects studies that include both ambient PM2.5 and gaseous concentrations as independent variables must be analyzed carefully and interpreted cautiously, since both parameters may be serving as surrogates for PM2.5 exposures.

Field validation of a semi-continuous method for aerosol black carbon (aethalometer) and temporal patterns of summertime hourly black carbon measurements in southwestern PA

Two methods for measuring aerosol elemental carbon (EC) are compared. Three-hour integrated carbon samples were collected on quartz filters during the summer of 1990 in Uniontown, PA, primarily during episodes of elevated particulate pollution levels. These samples were analyzed for EC and organic carbon (OC) using a thermo/optical reflectance (TOR) method. Aerosol black carbon (BC) was measured using an Aethalometer, a semi-continuous optical absorption method. The optical attenuation factor for ambient BC was supplied by the instrument manufacturer. Three-hour average concentrations were calculated from the semi-continuous BC measurements to temporally match the EC/OC integrated quartz filter samples. BC and EC concentrations are highly correlated over the study period (R2=0.925). The regression equation is BC (μg m-3)=0.95 (±0.04) EC−0.2 (±0.4). The means of 3 h average measurements for EC and BC are 2.3 and 2.0 μg m-3, respectively, average concentrations of EC and BC ranged from 0.6 to 9.4 and 0.5 to 9.0 μg m-3 respectively. TOR OC and EC concentrations were not highly correlated (R2=0.22). The mean OC/EC ratio was 1.85. The 10-week Aethalometer hourly dataset was analyzed for daily and weekly temporal patterns. A strong diurnal BC pattern was observed, with peaks occurring between 7 a.m. and 9 a.m. local time. This is consistent with the increase in emissions from ground level combustion sources in the morning, coupled with poor dispersion before daytime vertical mixing is established. There was also some indication of a day-of-week effect on BC concentrations, attributed to activity of local ground level anthropogenic sources. Comparison of BC concentrations with co-located measurements of coefficient of haze in a separate field study in Philadelphia, PA, during the summer of 1992 showed good correlation between the two measurements (R2=0.82).