Gary A. Norris

Effects of ambient air pollution on nonelderly asthma hospital admissions in Seattle, Washington, 1987-1994.

As part of the Clean Air Act, Congress has directed EPA to set air quality standards to protect sensitive population groups from air pollutants in the ambient environment. People with asthma represent one such group. We undertook a study of the relation between measured ambient air pollutants in Seattle and nonelderly hospital admissions with a principal diagnosis of asthma. We regressed daily hospital admissions to local hospitals for area residents from 1987 through 1994 on particulate matter less than 10 and 2.5 microm in aerodynamic diameter (PM10 and PM2.5, respectively); coarse particulate mass; sulfur dioxide (SO2); ozone (O3); and carbon monoxide (CO) in a Poisson regression model with control for time trends, seasonal variations, and temperature-related weather effects. With the exception of seasonally monitored O3, we supplemented incomplete pollutant measures in a multiple imputation model to create a complete time series of exposure measures. We found an estimated 4-5% increase in the rate of asthma hospital admissions associated with an interquartile range change in PM (19 microg/m3 PM(10),11.8 microg/m3 PM2.5, and 9.3 microg/m3 coarse particulate mass) lagged 1 day; relative rates were as follows: for PM10, 1.05 [95% confidence interval (CI) = 1.02-1.08]; for PM2.5, 1.04 (95% CI = 1.02-1.07); and for coarse particulate mass, 1.04 (95% CI = 1.01-1.07). In single-pollutant models we also found that a 6% increase in the rate of admission was associated with an interquartile range change in CO (interquartile range, 924 parts per billion; 95% CI = 1.03-1.09) at a lag of 3 days and an interquartile range change in O3 (interquartile range, 20 parts per billion; 95% CI = 1.02-1.11) at a lag of 2 days. We did not observe an association for SO2. We found PM and CO to be jointly associated with asthma admissions. We estimated the highest increase in risk in the spring and fall seasons.

Source Apportionment of Phoenix PM2.5 Aerosol with the Unmix Receptor Model

Abstract The multivariate receptor model Unmix has been used to analyze a 3-yr PM2.5 ambient aerosol data set collected in Phoenix, AZ, beginning in 1995. The analysis generated source profiles and overall average percentage source contribution estimates (SCEs) for five source categories: gasoline engines (33 ± 4%), diesel engines (16 ± 2%), secondary SO4 2− (19 ± 2%), crustal/soil (22 ± 2%), and vegetative burning (10 ± 2%). The Unmix analysis was supplemented with scanning electron microscopy (SEM) of a limited number of filter samples for information on possible additional low-strength sources. Except for the diesel engine source category, the Unmix SCEs were generally consistent with an earlier multivariate receptor analysis of essentially the same data using the Positive Matrix Factorization (PMF) model. This article provides the first demonstration for an urban area of the capability of the Unmix receptor model.

Methods for estimating uncertainty in PMF solutions: Examples with ambient air and water quality data and guidance on reporting PMF results

The new version of EPAs positive matrix factorization (EPA PMF) software, 5.0, includes three error estimation (EE) methods for analyzing factor analytic solutions: classical bootstrap (BS), displacement of factor elements (DISP), and bootstrap enhanced by displacement (BS-DISP). These methods capture the uncertainty of PMF analyses due to random errors and rotational ambiguity. To demonstrate the utility of the EE methods, results are presented for three data sets: (1) speciated PM2.5 data from a chemical speciation network (CSN) site in Sacramento, California (2003-2009); (2) trace metal, ammonia, and other species in water quality samples taken at an inline storage system (ISS) in Milwaukee, Wisconsin (2006); and (3) an organic aerosol data set from high-resolution aerosol mass spectrometer (HR-AMS) measurements in Las Vegas, Nevada (January 2008). We present an interpretation of EE diagnostics for these data sets, results from sensitivity tests of EE diagnostics using additional and fewer factors, and recommendations for reporting PMF results. BS-DISP and BS are found useful in understanding the uncertainty of factor profiles; they also suggest if the data are over-fitted by specifying too many factors. DISP diagnostics were consistently robust, indicating its use for understanding rotational uncertainty and as a first step in assessing a solutions viability. The uncertainty of each factors identifying species is shown to be a useful gauge for evaluating multiple solutions, e.g., with a different number of factors.

East versus West in the US: Chemical Characteristics of PM2.5 during the Winter of 1999

The chemical composition of PM2.5 was investigated at four sites (Rubidoux, CA, Phoenix, AZ, Philadelphia, PA, and Research Triangle Park, NC) in January and February of 1999. Three samplers were used to determine both the overall mass and the chemical composition of the aerosol. Teflon filters were weighed for total mass. Ions were analyzed using ion chromatography. Elements were determined using X-ray fluorescence. Organic and elemental carbon were measured using a thermo-optical method. At all of the sites, reconstructed mass was observed to be greater than or equal to the measured mass. Good ionic balance was found for ammonium, nitrate, and sulfate at each of the sites. Overall, the chemical composition of the aerosol for each site was in good agreement with the expected composition based upon previous studies, with the exception of relatively high nitrate contribution to the total mass at Philadelphia. Good agreement was found between the predicted amount of sulfate by XRF analysis of sulfur and the sulfate measured by ion chromatography. As expected, sulfate was a more important contributor to the total mass at the East Coast sites. Nitrate contributed more to the total mass at the West Coast sites and was an important factor in the highest observed mass concentration at Rubidoux. Teflon filters appear to lose nitrate to a greater extent than heat-treated quartz fiber filters. Organic carbon was also found to be the largest part of the aerosol mass on minimum days for all sites and a significant portion of the mass on other days with 25-50% of the total mass at all of the sites. At three of the sites, organic carbon (OC) collected on denuded filters was less than that found on nondenuded samples, indicating an absorptive artifact on the quartz fiber filters. It was also found that the crustal component to PM2.5 was highest at Phoenix. PM2.5 was also found to contribute significantly to the PM10 particle mass at all the sites.

Personal exposures to PM2.5 mass and trace elements in Baltimore, MD, USA

In a recent study, EPA found a significant relationship between PM2.5 mass measurements at a community site and personal exposure samples in a Towson, MD retirement facility. This manuscript builds upon the mass concentration results by evaluating the exposure relationships with the elemental composition of the PM2.5 mass. Daily community, outdoor, and indoor PM2.5 were measured with a URG Versatile Air Pollutant Sampler (VAPS). Daily personal and apartment PM2.5 samples were collected with a Marple Personal Exposure Monitor (PEM). Only subjects with the most complete data records (n=10) were used in this analysis. Significant differences were found between the VAPS and PEM samplers for PM2.5 elemental composition, so all subsequent analyses were conducted independently for each of the data sets. Both the VAPS and PEM samples were analyzed with energy dispersive X-ray fluorescence (XRF). In addition, the VAPS samples were analyzed for pH, major ions, and elemental/organic carbon. The spatial correlation coefficients between the community and outdoor monitor, and the indoor infiltration rates were calculated for several PM2.5 constituents calculated from the VAPS samples including sulfate, nitrate, trace element oxides, soil, and NaCl. The spatial correlations for most PM2.5 constituents were good (e.g. sulfate (r2=0.99)), with the exception of soil (r2=0.40). Infiltration rates of the PM2.5 constituents were determined by linear regression analysis and varied according to particle size. Infiltration rates ranged from 0.41 (r2=0.98) for sulfate to 0.09 (r2=0.83) for nitrate. Outdoor, central indoor, apartment, and personal exposures PEM samples were also evaluated using a linear mixed effects model and median Pearson correlation coefficients. The modeling results indicate that personal exposures to PM2.5 and sulfate were strongly associated with outdoor concentrations. Conversely, personal exposures to soil and trace element oxides were not significantly correlated to outdoor concentrations.

Individual Particle Analysis of Indoor, Outdoor and Community Samples from the 1998 Baltimore Particulate Matter Study

Abstract The United States Environmental Protection Agency (US EPA) recently conducted the 1998 Baltimore Particulate Matter (PM) Epidemiology-Exposure Study of the Elderly. The primary goal of that study was to establish the relationship between outdoor PM concentrations and actual human PM exposures within a susceptible (elderly) sub-population. Personal, indoor, and outdoor sampling of particulate matter was conducted at a retirement center in the Towson area of northern Baltimore County. Concurrent sampling was conducted at a central community site. The main objective of this work was to use computer-controlled scanning electron microscopy (CCSEM) with individual-particle X-ray analysis to measure the chemical and physical characteristics of geological and trace element particles collected at the various sampling locations in and around the retirement facility. The CCSEM results show that the relative abundances of some geological and trace element particle classes identified at the outdoor and community locations differ from each other and from the indoor location. Particle images acquired during the computer-controlled analyses played a key role in the identification of certain particle types. Review of these images was particularly useful in distinguishing spherical particles (usually indicative of combustion) from non-spherical particles of similar chemical composition. Pollens and spores were also identified through a manual review of the particle images.

Field Method Comparison between Passive Air Samplers and Continuous Monitors for VOCs and NO2 in El Paso, Texas

Abstract This study evaluates the performance of Model 3300 Ogawa Passive Nitrogen Dioxide (NO2) Samplers and 3M 3520 Organic Vapor Monitors (OVMs) by comparing integrated passive sampling concentrations to averaged hourly NO2 and volatile organic compound (VOC) measurements at two sites in El Paso, TX. Sampling periods were three time intervals (3-day weekend, 4-day weekday, and 7-day weekly) for three consecutive weeks. OVM concentrations were corrected for ambient pressure to account for higher elevation. Precise results (<5% relative standard deviation, RSD) were found for NO2 measurements from collocated Ogawa samplers. Reproducibility was lower from duplicate OVMs for BTEX (benzene, toluene, ethylbenzene, and xylene isomers) VOCs (≥7% RSD for 2-day samples) with better precision for longer sampling periods. Comparison of Ogawa NO2 samplers with chemiluminescence measurements averaged over the same time period suggested potential calibration problems with the chemiluminescence analyzer. For BTEX species, generally good agreement was obtained between OVMs and automated-gas chromatograph (auto-GC) measurements. The OVMs successfully tracked increasing levels of VOCs recorded by the auto-GCs.

Receptor modeling of ambient and personal exposure samples: 1998 Baltimore Particulate Matter Epidemiology-Exposure Study

Sources of particulate matter exposure for an elderly population in a city north of Baltimore, MD were evaluated using advanced factor analysis models. Data collected with versatile air pollutant samplers positioned at a community site, outside and inside of an elderly residential facility were analyzed with a three-way analysis to identify the source(s) that contributed to all sample types. These sources were secondary sulfate, secondary nitrate, motor vehicles, and a organic carbon (OC). The OC source contained 96% OC and most likely represents positive volatile organic carbon artifact and other unidentified sources. No soil source was found that contributed significantly to these samples. A second set of data was collected with personal samplers (PEM) from 10 elderly subjects, their apartments, a central indoor location, and outdoors. The PEM data were analyzed using a complex model with a target for soil that included factors that are common to all of the types of samples (external factors) and factors that only apply to the data from the individual and apartment samples (internal factors). From these results, the impact of outdoor sources and indoor sources on indoor concentrations were assessed. The identified external factors were sulfate, soil, and an unknown factor. Internal factors were identified as gypsum or wall board, personal care products, and a factor representing variability not explained by the other indoor sources. The latter factor had a composition similar to outdoor particulate matter and explained 36% of the personal exposure. External factors contributed 63% to personal exposure with the largest contribution from sulfate (48%).

Quantifying the Impact of Residential Heating on the Urban Air Quality in a Typical European Coal Combustion Region

The present investigation, carried out as a case study in a typical major city situated in a European coal combustion region (Krakow, Poland), aims at quantifying the impact on the urban air quality of residential heating by coal combustion in comparison with other potential pollution sources such as power plants, industry, and traffic. Emissions were measured for 20 major sources, including small stoves and boilers, and the particulate matter (PM) was analyzed for 52 individual compounds together with outdoor and indoor PM10 collected during typical winter pollution episodes. The data were analyzed using chemical mass balance modeling (CMB) and constrained positive matrix factorization (CMF) yielding source apportionments for PM10, B(a)P, and other regulated air pollutants namely Cd, Ni, As, and Pb. The results are potentially very useful for planning abatement strategies in all areas of the world, where coal combustion in small appliances is significant. During the studied pollution episodes in Krakow, European air quality limits were exceeded with up to a factor 8 for PM10 and up to a factor 200 for B(a)P. The levels of these air pollutants were accompanied by high concentrations of azaarenes, known markers for inefficient coal combustion. The major culprit for the extreme pollution levels was demonstrated to be residential heating by coal combustion in small stoves and boilers (>50% for PM10 and >90% B(a)P), whereas road transport (<10% for PM10 and <3% for B(a)P), and industry (4-15% for PM10 and <6% for B(a)P) played a lesser role. The indoor PM10 and B(a)P concentrations were at high levels similar to those of outdoor concentrations and were found to have the same sources as outdoors. The inorganic secondary aerosol component of PM10 amounted to around 30%, which for a large part may be attributed to the industrial emission of the precursors SO2 and NOx.

Source apportionment of particulate matter in the U.S. and associations with lung inflammatory markers.

Size-fractionated particulate matter (PM) samples were collected from six U.S. cities and chemically analyzed as part of the Multiple Air Pollutant Study. Particles were administered to cultured lung cells and the production of three different proinflammatory markers was measured to explore the association between the health effect markers and PM. Ultrafine, fine, and coarse PM samples were collected between December 2003 and May 2004 over a 4-wk period in each city. Filters were pooled for each city and the PM samples were extracted then analyzed for trace metals, ions, and elemental carbon. Particle extracts were applied to cultured human primary airway epithelial cells, and the secreted levels of interleukin-8 (IL-8), heme oxygenase-1, and cyclooxygenase-2 were measured 1 and 24 h following exposure. Fine PM sources were quantified by the chemical mass balance (CMB) model. The relationship between toxicological measures, PM sources, and individual species were evaluated using linear regression. Ultrafine and fine PM mass were associated with increases in IL-8 (r2 = .80 for ultrafine and r2 = .52 for fine). Sources of fine PM and their relative contributions varied across the sampling sites and a strong linear association was observed between IL-8 and secondary sulfate from coal combustion (r2 = .79). Ultrafine vanadium, lead, copper, and sulfate were also associated with increases in IL-8. Increases in inflammatory markers were not observed for coarse PM mass and source markers. These findings suggest that certain PM size fractions and sources are associated with markers of lung injury or inflammation.