Fine Particles and Oxidant Pollution: Developing an Agenda for Cooperative Research

ABSTRACT

This paper describes a background for the North American Research Strategy for Tropospheric Ozone (NARSTO) cooperative program integrating studies of O₃ and PM_{2 5}. It discusses several important aspects for rationalizing NARSTO's trinational investigative approach, including (1) an outlook on the state of knowledge about fine particles in the troposphere and their origins in Canada, Mexico, and the United States; (2) the need for enhancement and strengthening of key field measurements in relation to tropospheric chemistry and a health effects component; and (3) the use of a central theme for advancing air quality modeling using evolving techniques to integrate and guide key process-oriented field campaigns. The importance of organizing a scientific program to acquire “policy-relevant” information is stressed, noting cooperative research directions that address combined PM_2.5 and O₃ issues, illustrated through exploration of hypothetical pathways of PM_2.5 response to choices of O₃ and PM precursor emission reductions. The information needed for PM_2.5 research is noted to intersect in many cases with those of O₃, but diverge in other cases. Accounting for these distinctions is important for developing NARSTO's strategy over the next decade.     

Laboratory and field evaluation of measurement methods for one-hour exposures to O3, PM2.5, and CO.

While researchers have linked acute (less than 12-hr) ambient O3, PM2.5, and CO concentrations to a variety of adverse health effects, few studies have characterized short-term exposures to these air pollutants, in part due to the lack of sensitive, accurate, and precise sampling technologies. In this paper, we present results from the laboratory and field evaluation of several new (or modified) samplers used in the "roll-around" system (RAS), which was developed to measure 1-hr O3, PM2.5, and CO exposures simultaneously. All the field evaluation data were collected during two sampling seasons: the summer of 1998 and the winter of 1999. To measure 1-hr O3 exposures, a new active O3 sampler was developed that uses two nitrite-coated filters to measure O3 concentrations. Laboratory chamber tests found that the active O3 sampler performed extremely well, with a collection efficiency of 0.96 that did not vary with temperature or relative humidity (RH). In field collocation comparisons with a reference UV photometric monitor, the active O3 sampler had an effective collection efficiency ranging between 0.92 and 0.96 and a precision for 1-hr measurements ranging between 4 and 6 parts per billion (ppb). The limits of detection (LOD) of this method were 9 ppb-hr for the chamber tests and approximtely 16 ppb-hr for the field comparison tests. PM2.5 and CO concentrations were measured using modified continuous monitors--the DustTrak and the Langan, respectively. A size-selective inlet and a Nafion dryer were placed upstream of the DustTrak inlet to remove particles with aerodynamic diameters greater than 2.5 microm and to dry particles prior to the measurements, respectively. During the field validation tests, the DustTrak consistently reported higher PM2.5 concentrations than those obtained by the collocated 12-hr PM2.5 PEM samples, by approximately a factor of 2. After the DustTrak response was corrected (correction factor of 2.07 in the summer and 2.02 in the winter), measurements obtained using these methods agreed well with R2 values of 0.87 in the summer and 0.81 in the winter. The results showed that the DustTrak can be used along with integrated measurements to measure the temporal and spatial variation in PM2.5 exposures. Finally, during the field validation tests, CO concentrations measured using the Langan were strongly correlated with those obtained using the reference method when the CO levels were above the LOD of the instrument [approximately 1 part per million (ppm)].     

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

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 PM2.5, 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 Spearman's r = 0.74) and low in the winter (median Spearman's r = 0.25). Indoor ventilation was an important determinant of personal PM2.5 exposures and resulting personal-ambient associations. Associations between personal PM2.5 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 PM2.5. 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.     

Characterization of PM2.5 and PM10 in the South Coast Air Basin of southern California: Part 1--Spatial variations

In December 1994, the South Coast Air Quality Management District (SCAQMD) initiated a comprehensive program, the PM10 Technical Enhancement Program (PTEP), to characterize fine PM in the South Coast Air Basin (SCAB). A 1-year special particulate monitoring project was conducted from January 1995 to February 1996 as part of the PTEP. Under this enhanced monitoring, HNO3, NH3, and speciated PM10 and PM2.5 concentrations were measured at five stations (Anaheim, downtown Los Angeles, Diamond Bar, Fontana, and Rubidoux) in the SCAB and at one background station at San Nicolas Island. PM2.5 and PM10 mass and 43 individual species were analyzed for a full chemical speciation of the particle data. The PTEP data indicate that the most abundant chemical components of PM10 and PM2.5 in the SCAB are NH4+ (8-9% of PM10 and 14-17% of PM2.5), NO3- (23-26% of PM10 and 28-41% of PM2.5), SO4- (6-11% of PM10 and 9-18% of PM2.5), organic carbon (OC) (15-19% of PM10 and 18-26% of PM2.5), and elemental carbon (EC) (5-8% of PM10 and 8-13% of PM2.5). On an annual average basis, PM2.5 comprises 52-59% of the SCAB PM10. Annual average PM10 and PM2.5 concentrations showed strong spatial variations, low at coastal sites and high at inland sites. Annual average PM10 concentrations varied from 40.8 micrograms/m3 at Anaheim to 76.8 micrograms/m3 at Rubidoux, while annual average PM2.5 concentrations varied from 21.7 micrograms/m3 at Anaheim to 39.8 micrograms/m3 at Rubidoux. The chemical characterizations of the PM2.5 and PM10 concentrations, as well as their spatial variations, were examined; the important findings are summarized in this paper, and the temporal variations are discussed in the companion paper.     

Objectives and Design of Central California's 1995 Integrated Monitoring Study of the California Regional PM10/PM2.5 Air Quality Study

ABSTRACT

The 1995 Integrated Monitoring Study (IMS95) is part of the Phase 1 planning efforts for the California Regional PM_10/PM_2.5 Air Quality Study. Thus, the overall objectives of IMS95 are to (1) fill information gaps needed for planning an effective field program later this decade; (2) develop an improved conceptual model for pollution buildup (PM10, PM2.5, and aerosol precursors) in the San Joaquin Valley; (3) develop a uniform air quality, meteorological, and emissions database that can be used to perform initial evaluations of aerosol and fog air quality models; and (4) provide early products that can be used to help with the development of State Implementation Plans for PM_10. Consideration of the new particulate matter standards were also included in the planning and design of IMS95, although they were proposed standards when IMS95 was in the planning process.     

The Steubenville comprehensive air monitoring program (SCAMP): overview and statistical considerations

Average concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 microm (PM2.5) in Steubenville, OH, have decreased by more than 10 microg/m3 since the landmark Harvard Six Cities Study associated the city's elevated PM2.5 concentrations with adverse health effects in the 1980s. Given the promulgation of a new National Ambient Air Quality Standard (NAAQS) for PM2.5 in 1997, a current assessment of PM2.5 in the Steubenville region is warranted. The Steubenville Comprehensive Air Monitoring Program (SCAMP) was conducted from 2000 through 2002 to provide such an assessment. The program included both an outdoor ambient air monitoring component and an indoor and personal air sampling component. This paper, which is the first in a series of four that will present results from the outdoor portion of SCAMP, provides an overview of the outdoor ambient air monitoring program and addresses statistical issues, most notably autocorrelation, that have been overlooked by many PM2.5 data analyses. The average PM2.5 concentration measured in Steubenville during SCAMP (18.4 microg/m3) was 3.4 microg/m3 above the annual PM2.5 NAAQS. On average, sulfate and organic material accounted for approximately 31% and 25%, respectively, of the total PM2.5 mass. Local sources contributed an estimated 4.6 microg/m3 to Steubenville's mean PM2.5 concentration. PM2.5 and each of its major ionic components were significantly correlated in space across all pairs of monitoring sites in the region, suggesting the influence of meteorology and long-range transport on regional PM2.5 concentrations. Statistically significant autocorrelation was observed among time series of PM2.5 and component data collected at daily and 1-in-4-day frequencies during SCAMP. Results of spatial analyses that accounted for autocorrelation were generally consistent with findings from previous studies that did not consider autocorrelation; however, these analyses also indicated that failure to account for autocorrelation can lead to incorrect conclusions about statistical significance.     

Monitoring study of the near-road PM2.5 concentrations in Maryland

The Maryland State Highway Administration (SHA) monitoring program monitored the impact of vehicular emissions on the concentrations of the fine particles smaller than 2.5 microns (PM2.5). PM2.5 concentrations were monitored in close proximity to a highway in order to determine whether traffic conditions on the roadway impact concentrations at this location. The monitoring program attempted to connect monitored concentrations with the roadway traffic exhaust or with the other sources of PM2.5. PM2.5 concentrations were collected near the Capital Beltway (I-495/I-95) in Largo, Maryland. The monitoring program was launched on May 13, 2009 and continued through the end of 2012. Two co-located monitors, one for continuous PM2.5 measurements and the other for speciation measurements, were used in this program. Meteorological and traffic information was also continuously collected at or near the monitoring site. Additionally, data from the two other monitoring locations, one at the Howard University-Beltsville, MD and one at McMillan Reservoir, DC, was used for comparison with the data collected at the SHA monitoring location. The samples collected by the speciation monitor were analyzed at the RTI and DRI Laboratories to determine the composition and the sources of the collected PM2.5 samples. Based on the apportionment analysis, the contribution of roadway sources is about 12 to 17 percent of PM2.5 at the near-road site.

Implications: PM_2.5 monitoring at 150 m (approximately 500 feet) from a major highway in Maryland near Washington, DC, demonstrated that roadway traffic contributes to the total PM_2.5 concentration near the roadway, but the contribution at such distance is small, in the order of 12–17% of the total.     

Feasibility of using low-cost portable particle monitors for measurement of fine and coarse particulate matter in urban ambient air

Exposure to ambient particulate matter (PM) is known as a significant risk factor for mortality and morbidity due to cardiorespiratory causes. Owing to increased interest in assessing personal and community exposures to PM, we evaluated the feasibility of employing a low-cost portable direct-reading instrument for measurement of ambient air PM exposure. A Dylos DC 1700 PM sensor was collocated with a Grimm 11-R in an urban residential area of Houston Texas. The 1-min averages of particle number concentrations for sizes between 0.5 and 2.5 µm (small size) and sizes larger than 2.5 µm (large size) from a DC 1700 were compared with the 1-min averages of PM_2.5 (aerodynamic size less than 2.5 µm) and coarse PM (aerodynamic size between 2.5 and 10 µm) concentrations from a Grimm 11-R. We used a linear regression equation to convert DC 1700 number concentrations to mass concentrations, utilizing measurements from the Grimm 11-R. The estimated average DC 1700 PM_2.5 concentration (13.2 ± 13.7 µg/m³) was similar to the average measured Grimm 11-R PM_2.5 concentration (11.3 ± 15.1 µg/m³). The overall correlation (r²) for PM_2.5 between the DC 1700 and Grimm 11-R was 0.778. The estimated average coarse PM concentration from the DC 1700 (5.6 ± 12.1 µg/m³) was also similar to that measured with the Grimm 11-R (4.8 ± 16.5 µg/m³) with an r² of 0.481. The effects of relative humidity and particle size on the association between the DC 1700 and the Grimm 11-R results were also examined. The calculated PM mass concentrations from the DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM_2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM_2.5.

Implications: The performance of a low-cost particulate matter (PM) sensor was evaluated in an urban residential area. Both PM_2.5 and coarse PM (PM_10-2.5) mass concentrations were estimated using a DC1700 PM sensor. The calculated PM mass concentrations from the number concentrations of DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM_2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM_2.5.     

Evaluation of time-resolved PM2.5 data in urban/suburban areas of New Jersey

Time-resolved data is needed for public notification of unhealthful air quality and to develop an understanding of atmospheric chemistry, including insights important to control strategies. In this research, continuous fine particulate matter (PM2.5) mass concentrations were measured with tapered element oscillating microbalances (TEOMs) across New Jersey from July 1997 to June 1998. Data features indicating the influence of local sources and long-distance transport are examined, as well as differences between 1-hr maxima and 24-hr average concentrations that might be relevant to acute health effects. Continuous mass concentrations were not significantly different from filter-collected gravimetric mass concentrations with 95% confidence intervals during any season. Annual mean PM2.5 concentrations from July 1997 to June 1998 were 17.3, 16.4, 14.1, and 15.3 micrograms/m3 at Newark, Elizabeth, New Brunswick, and Camden, NJ, respectively. Monthly averaged 24- and 1-hr daily maximum PM2.5 concentrations suggest the existence of a high PM2.5 (May-October) and a low PM2.5 (November-April) season. PM2.5 magnitudes and temporal trends were very similar across the state during high PM2.5 events. In fact, the between-site coefficients of determination (R2) for daily PM2.5 measurements were 84-98% for June and July. Additionally, during the most pronounced PM2.5 episode, PM2.5 concentrations closely tracked the daily maximum 1-hr O3 concentrations. These observations suggest the importance of transport and atmospheric chemistry (i.e., secondary formation) to PM2.5 episodes in New Jersey. The influence of local sources was observed in diurnal concentration profiles and annual average between-site differences. Urban wintertime data illustrate that high 1-hr maximum PM2.5 concentrations can occur on low 24-hr PM2.5 days.     

Estimating national-scale ground-level PM25 concentration in China using geographically weighted regression based on MODIS and MISR AOD

Taking advantage of the continuous spatial coverage, satellite-derived aerosol optical depth (AOD) products have been widely used to assess the spatial and temporal characteristics of fine particulate matter (PM2.5) on the ground and their effects on human health. However, the national-scale ground-level PM2.5 estimation is still very limited because the lack of ground PM2.5 measurements to calibrate the model in China. In this study, a national-scale geographically weighted regression (GWR) model was developed to estimate ground-level PM2.5 concentration based on satellite AODs, newly released national-wide hourly PM2.5 concentrations, and meteorological parameters. The results showed good agreements between satellite-retrieved and ground-observed PM2.5 concentration at 943 stations in China. The overall cross-validation (CV) R ² is 0.76 and root mean squared prediction error (RMSE) is 22.26 μg/m³ for MODIS-derived AOD. The MISR-derived AOD also exhibits comparable performance with a CV R ² and RMSE are 0.81 and 27.46 μg/m³, respectively. Annual PM2.5 concentrations retrieved either by MODIS or MISR AOD indicated that most of the residential community areas exceeded the new annual Chinese PM2.5 National Standard level 2. These results suggest that this approach is useful for estimating large-scale ground-level PM2.5 distributions especially for the regions without PMs monitoring sites.     

Comparison of short-term variations (15-minute averages) in outdoor and indoor PM2.5 concentrations

Measurements of 15-min average PM2.5 concentrations were made with a real-time light-scattering instrument at both outdoor (central monitoring sites in three communities) and indoor (residential) locations over two seasons in the Minneapolis-St. Paul metropolitan area. These data are used to examine within-day variability of PM2.5 concentrations indoors and outdoors, as well as matched indoor-to-outdoor (I/O) ratios. Concurrent gravimetric measurements of 24-hr average PM2.5 concentrations were also obtained as a way to compare real-time measures with this more traditional metric. Results indicate that (1) within-day variability for both indoor and outdoor 15-min average PM2.5 concentrations was substantial and comparable in magnitude to day-to-day variability for 24-hr average concentrations; (2) some residences exhibited substantial variability in indoor aerosol characteristics from one day to the next; (3) peak values for indoor short-term (15-min) average PM2.5 concentrations routinely exceeded 24-hr average outdoor values by factors of 3-4; and (4) relatively strong correlations existed between indoor and outdoor PM2.5 concentrations for both 24-hr and 15-min averages.     

Particulate matter modeling in the Los Angeles basin using SAQM-AERO

The SARMAP air quality model, enhanced with aerosol modeling capability, and its associated components were developed to understand causes of ozone (O3) and particulate matter exceedances in the San Joaquin Valley of California. In order for this modeling system to gain increasing acceptance and use in guiding air quality management, it is important to assess how transportable this modeling system is across geographic domains. We describe the first application of the modeling system outside the "home" domain for which it was developed and evaluated. We have chosen the August 27-28, 1987, intensive monitoring period of the Southern California Air Quality Study to evaluate the performance of the modeling system and to assess its sensitivity to emission control options. The predicted surface concentrations of O3 and other gas-phase species were spatially and temporally correlated with measured data. The fractional normalized absolute error was 0.32 to 0.36 for O3, and somewhat larger for other species. The fractional normalized bias for O3 on August 27 and 28, 1987, was 0.02 to 0.04. The simulated PM2.5 mass and constituent species concentrations reproduced the magnitude and variability of the observed daytime concentrations at most locations; however, nighttime PM2.5 concentrations were overpredicted by the model. The model's response to emission control options was consistent with other models of the same genre.     

Identification and chemical characterization of industrial particulate matter sources in southwest Spain

A detailed physical and chemical characterization of coarse particulate matter (PM10) and fine particulate matter (PM2.5) in the city of Huelva (in Southwestern Spain) was carried out during 2001 and 2002. To identify the major emission sources with a significant influence on PM10 and PM2.5, a methodology was developed based on the combination of: (1) real-time measurements of levels of PM10, PM2.5, and very fine particulate matter (PM1); (2) chemical characterization and source apportionment analysis of PM10 and PM2.5; and (3) intensive measurements in field campaigns to characterize the emission plumes of several point sources. Annual means of 37, 19, and 16 microg/m3 were obtained for the study period for PM10, PM2.5, and PM1, respectively. High PM episodes, characterized by a very fine grain size distribution, are frequently detected in Huelva mainly in the winter as the result of the impact of the industrial emission plumes on the city. Chemical analysis showed that PM at Huelva is characterized by high PO4(3-) and As levels, as expected from the industrial activities. Source apportionment analyses identified a crustal source (36% of PM10 and 31% of PM2.5); a traffic-related source (33% of PM10 and 29% of PM2.5), and a marine aerosol contribution (only in PM10, 4%). In addition, two industrial emission sources were identified in PM10 and PM2.5: (1) a petrochemical source, 13% in PM10 and 8% in PM2.5; and (2) a mixed metallurgical-phosphate source, which accounts for 11-12% of PM10 and PM2.5. In PM2.5 a secondary source has been also identified, which contributed to 17% of the mass. A complete characterization of industrial emission plumes during their impact on the ground allowed for the identification of tracer species for specific point sources, such as petrochemical, metallurgic, and fertilizer and phosphate production industries.     

Air pollution and hospital admissions for diseases of the circulatory system in three U.S. metropolitan areas

Generalized additive models were used to analyze the time series of daily hospital admissions for cardiovascular and cerebrovascular diseases over the period of 1987-1995 in three major metropolitan areas--Cook County, IL; Los Angeles County, CA; and Maricopa County, AZ--in the United States. In Cook and Maricopa Counties, admissions information was only available for the elderly (ages 65 and over), while in Los Angeles County, admissions information was available for all ages. In Cook County, daily monitoring information was available on PM10, CO, SO2, NO2, and O3. In Los Angeles and Maricopa Counties, monitoring information was available daily on the gases, and information on PM10 was available every sixth day. In Los Angeles County, information on PM2.5 was also available every sixth day. In Cook and Los Angeles Counties, associations were found between each pollutant, with the exception of O3, and admissions for cardiovascular disease, with the gases showing the strongest associations. In two-pollutant models with PM and one of the gases, the effect of the gases remained stable, while the effect of PM became unstable and insignificant. In Maricopa County, the gases, with the exception of O3, were weakly associated with hospital admissions for cardiovascular disease, while PM was not. In two-pollutant models with two of CO, SO2, and NO2, the pattern of results is heterogeneous in the three counties. In all three counties, only weak evidence of any association between air pollution and cerebrovascular admissions was found.     

Source apportionment of PM10 and PM2.5 in five Chilean cities using factor analysis

Chile is a fast-growing country with important industrial activities near urban areas. In this study, the mass and elemental concentrations of PM10 and PM2.5 were measured in five major Chilean urban areas. Samples of particles with diameter less than 10 microm (PM10) and 2.5 microm (PM2.5) were collected in 1998 in Iquique (northern Chile), Valparaiso, Vi?a del Mar, Rancagua (central Chile), and Temuco (southern Chile). Both PM10 and PM2.5 annual mean concentrations (PM10: 56.9-77.6 microg/m3; PM2.5: 22.4-42.6 microg/m3) were significantly higher than the corresponding European Union (EU) and U.S. Environmental Protection Agency (EPA) air quality standards. Moreover, the 24-hr PM10 and PM2.5 U.S. standards were exceeded infrequently for some of the cities (Rancagua and Valparaiso). Elements ranging from Mg to Pb were detected in the aerosol samples using X-ray fluorescence (XRF). For each of the five cities, factor analysis (FA) was applied to identify and quantify the sources of PM10 and PM2.5. The agreement between calculated and measured mass and elemental concentrations was excellent in most of the cities. Both natural and anthropogenic sources were resolved for all five cities. Soil and sea were the most important contributors to coarse particles (PM10-PM2.5), whereas their contributions to PM2.5 were negligible. Emissions from Cu smelters and oil refineries (and/or diesel combustion) were identified as important sources of PM2.5, particularly in the industrial cities of Rancagua, Valparaiso, and Vi?a del Mar. Finally, motor vehicles and wood burning were significant sources of both PM2.5 and PM10 in most of the cities (wood burning was not identified in Iquique).     

The Steubenville Comprehensive Air Monitoring Program (SCAMP): analysis of short-term and episodic variations in PM2.5 concentrations using hourly air monitoring data

One-hour average ambient concentrations of particulate matter (PM) with an aerodynamic diameter < 2.5 microm (PM2.5) were determined in Steubenville, OH, between June 2000 and May 2002 with a tapered element oscillating microbalance (TEOM). Hourly average gaseous copollutant [carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxide (NOx), and ozone (O3)] concentrations and meteorological conditions also were measured. Although 75% of the 14,682 hourly PM2.5 concentrations measured during this period were < or = 17 microg/m3, concentrations > 65 microg/m3 were observed 76 times. On average, PM2.5 concentrations at Steubenville exhibited a diurnal pattern of higher early morning concentrations and lower afternoon concentrations, similar to the diurnal profiles of CO and NO(x). This pattern was highly variable; however, PM2.5 concentrations > 65 microg/m3 were never observed during the mid-afternoon between 1:00 p.m. and 5:00 p.m. EST. Twenty-two episodes centered on one or more of these elevated concentrations were identified. Five episodes occurred during the months June through August; the maximum PM2.5 concentration during these episodes was 76.6 microg/m3. Episodes occurring during climatologically cooler months often featured higher peak concentrations (five had maximum concentrations between 95.0 and 139.6 microg/m3), and many exhibited strong covariation between PM2.5 and CO, NO(x), or SO2. Case studies suggested that nocturnal surface-based temperature inversions were influential in driving high nighttime concentrations of these species during several cool season episodes, which typically had dramatically lower afternoon concentrations. These findings provide insights that may be useful in the development of PM2.5 reduction strategies for Steubenville, and suggest that studies assessing possible health effects of PM2.5 should carefully consider exposure issues related to the intraday timing of PM2.5 episodes, as well as the potential for toxicological interactions among PM2.5, and primary gaseous pollutants.     

Particulate matter in California: part 1--Intercomparison of several PM2.5, PM10-2.5, and PM10 monitoring networks

It will be many years before the recently deployed network of fine particulate matter with an aerodynamic diameter less than 2.5 microm (PM2.5) Federal Reference Method (FRM) samplers produces information on nonattainment areas, trends, and source impacts. However, data on PM2.5 and its major constituents have been routinely collected in California for the past 20 years. The California Air Resources Board operated as many as 20 dichotomous (dichot) samplers for PM2.5 and coarse PM (PM10-2.5). The California Acid Deposition Monitoring Program (CADMP) collected 12-h-average PM2.5 and PM10 from 1988 to 1995 at ten urban and rural sites and 24-h-average PM2.5 at five urban sites since 1995. Beginning in 1994, the Children's Health Study collected 2-week averages of PM2.5 in 12 communities in southern California using the Two-Week Sampler (TWS). Comparisons of collocated samples establish relationships between the dichot, CADMP, and TWS samplers and the 82-site network of PM2.5 FRM samplers deployed since 1999 in California. PM mass data from the different monitoring programs have modest to high correlation to FRM mass data, fairly small systematic biases and negative proportional biases ranging from 7 to 22%. If the biases are taken into account, all of the programs should be considered comparable with the FRM program. Thus, historical data can be used to develop long-term PM trends in California.     

Characterization and identification of trends in average ambient ozone and fine particulate matter levels through trajectory cluster analysis in eastern Canada

In many locations in Eastern Canada, ambient levels of fine particulate matter (PM,25) and surface ozone (O3) depend on airflow direction and synoptic scale meteorological conditions. In this study, a cluster analysis was performed on 10 yr (1994-2003) of back-trajectory data for 11 locations in Eastern Canada, resulting in the identification of 10 unique back-trajectory clusters (or airflows) for each location. The airflows were then used to characterize and identify spatial and temporal trends in the daily maximum 8-hr average O3 (dmax 8-hr O3) and the daily average PM2.5 levels. Results showed that airflows from the southwest passing over Michigan and Southern Ontario were associated, on average, with the highest O3 levels at most locations in Eastern Canada. For PM2.5, the highest levels occurred with airflows from the Eastern Ohio River Valley. At major urban locations in Ontario and Quebec, the warm season mean (May to September) dmax 8-hr O3 and the annual mean PM2.5 were, on average, 12 parts per billion and 7.6 microg/m3 higher, respectively, than airflows from the north. Elevated levels of O3 and PM2.5 also occurred under light airflows, and, on average, the levels under light airflows were higher than their nonlight counterparts. At several locations in Canada, including Toronto, Montreal, Quebec City, and Kejimkujik, the annual warm season mean dmax 8-hr O3 experienced a statistically significant (95% confidence) increasing trend over the 10-yr period. When airflow direction was considered, a number of locations experienced statistically significant upward trends in O3 for airflow from the north and northwest. Several locations also showed significant upward trends associated with airflow from the southwest passing over Michigan and Southwestern Ontario. Although there are no statistically significant downward trends, airflows from the southwest have shown a reduction in O3 levels in Southwestern Ontario in more recent years.     

Application and evaluation of two air quality models for particulate matter for a southeastern U.S. episode

The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29-July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O3), particulate matter with an aerodynamic diameter less than or equal to 2.5 microm (PM2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 microm (PM10) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O3 and PM than CMAQ. Both models tend to predict O3 values that are higher than those observed. For observed O3 values above 60 ppb, O3 performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O3 values above 40 ppb. Both models predict similar amounts of sulfate (SO4(2-)) and organic matter, and both predict SO4(2-) to be the largest contributor to PM2.5. PMCAMx generally predicts higher amounts of ammonium (NH4+), nitrate (NO3-), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO3-, NH4+, and BC than observed, which degrades its performance. For PM10 and PM2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37-43% and -33-4% for CMAQ and 50-59% and 7-30% for PMCAMx. Both models predict the largest MNGEs for NO3- (98-104% for CMAQ 138-338% for PMCAMx). The inaccurate NO3- predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.