A study of polycyclic aromatic hydrocarbons concentrations and source identifications by methods of diagnostic ratio and principal component analysis at Taichung chemical Harbor near Taiwan Strait

Fine (PM(2.5)) and Coarse (PM(2.5-10)) particulates concentrations of ambient air particle-bound polycyclic aromatic hydrocarbons (PAHs) were measured simultaneously from February 2004 to January 2005 at the Taichung Harbor (TH) sampling site near Taiwan of central Taiwan. Particle-bound polycyclic aromatic hydrocarbons (PAHs) were collected on quartz filters, the collected sample used soxhlet analytical method extracted with a dichloromethane (DCM)/n-hexane mixture (50/50, v/v) for 24h, and then the extracts were subjected to gas chromatography-mass spectrometric (GC-MS) analysis. The results indicated that vehicle emissions, coal combustion, incomplete combustion and pyrolysis of fuel and oil burning were the main source of PAHs near Taiwan Strait of central Taiwan. Diagnostic ratio and principal component analysis (PCA) were also used to characterize and identify PAHs emission source in this study.     

Source contributions to fine particulate matter in an urban atmosphere

This paper proposes a practical method for estimating source attribution by using a three-step methodology. The main objective of this study is to explore the use of the three-step methodology for quantifying the source impacts of 24-h PM2.5 particles at an urban site in Seoul, Korea. 12-h PM2.5 samples were collected and analyzed for their elemental composition by ICP-AES/ICP-MS/AAS to generate the source composition profiles. In order to assess the daily average PM2.5 source impacts, 24-h PM2.5 and polycyclic aromatic hydrocarbons (PAH) ambient samples were simultaneously collected at the same site. The PM2.5 particle samples were then analyzed for trace elements. Ionic and carbonaceous species concentrations were measured by ICP-AES/ICP-MS/AAS, IC, and a selective thermal MnO2 oxidation method. The 12-h PM2.5 chemical data was used to estimate possible source signatures using the principal component analysis (PCA) and the absolute principal component scores method followed by the multiple linear regression analysis. The 24-h PM2.5 source categories were extracted with a combination of PM2.5 and some PAH chemical data using the PCA, and their quantitative source contributions were estimated by chemical mass balance (CMB) receptor model using the estimated source profiles and those in the literature. The results of PM2.5 source apportionment using the 12-h derived source composition profiles show that the CMB performance indices; chi2, R2, and percent of mass accounted for are 2.3%, 0.97%, and 100.7%, which are within the target range specified. According to the average PM2.5 source contribution estimate results, motor vehicle exhaust was the major contributor at the sampling site, contributing 26% on average of measured PM2.5 mass (41.8 microg m-3), followed by secondary sulfate (23%) and nitrate (16%), refuse incineration (15%), soil dust (13%), field burning (4%), oil combustion (2.7%), and marine aerosol (1.3%). It can be concluded that quantitative source attribution to PM2.5 in an urban area where source profiles have not been developed can be estimated using the proposed three-step methodology approach.     

Source identification of personal exposure to fine particulate matter using organic tracers

Personal exposure to fine particulate matter (PM2.5) is due to both indoor and outdoor sources. Contributions of sources to personal exposure can be quite different from those observed at ambient sampling locations. The primary goal of this study was to investigate the effectiveness of using trace organic speciation data to help identify sources influencing PM2.5 exposure concentrations. Sixty-four 24-h PM2.5 samples were obtained on seven different subjects in and around Boulder, CO. The exposure samples were analyzed for PM2.5 mass, elemental and organic carbon, organic tracer compounds, water-soluble metals, ammonia, and nitrate. This study is the first to measure a broad distribution of organic tracer compounds in PM2.5 personal samples. PM2.5 mass exposure concentrations averaged 8.4 μg m^?3. Organic carbon was the dominant constituent of the PM2.5 mass. Forty-four organic species and 19 water-soluble metals were quantifiable in more than half of the samples. Fifty-four organic species and 16 water-soluble metals had measurement signal-to-noise ratios larger than two after blank subtraction.The dataset was analyzed by Principal Component Analysis (PCA) to determine the factors that account for the greatest variance. Eight significant factors were identified; each factor was matched to its likely source based primarily on the marker species that loaded the factor. The results were consistent with the expectation that multiple marker species for the same source loaded the same factor. Meat cooking was an important source of variability. The factor that represents meat cooking was highly correlated with organic carbon concentrations (r = 0.84). The correlation between ambient PM2.5 and PM2.5 exposure was relatively weak (r = 0.15). Time participants spent performing various activities was generally not well correlated with PCA factor scores, likely because activity duration does not measure emissions intensity. The PCA results demonstrate that organic tracers can aid in identifying factors that influence personal exposures to PM2.5.     

Improving source apportionment of fine particles in the eastern United States utilizing temperature-resolved carbon fractions

The objectives of this study were to examine the use of carbon fractions to identify particulate matter (PM) sources, especially traffic-related carbonaceous particle sources, and to estimate their contributions to the particle mass concentrations. In recent studies, positive matrix factorization (PMF) was applied to ambient fine PM (PM2.5) compositional data sets of 24-hr integrated samples including eight individual carbon fractions collected at three monitoring sites in the eastern United States: Atlanta, GA, Washington, DC, and Brigantine, NJ. Particulate carbon was analyzed using the Interagency Monitoring of Protected Visual Environments/Thermal Optical Reflectance method that divides carbon into four organic carbons (OC): pyrolized OC and three elemental carbon (EC) fractions. In contrast to earlier PMF studies that included only the total OC and EC concentrations, gasoline emissions could be distinguished from diesel emissions based on the differences in the abundances of the carbon fractions between the two sources. The compositional profiles for these two major source types show similarities among the three sites. Temperature-resolved carbon fractions also enhanced separations of carbon-rich secondary sulfate aerosols. Potential source contribution function analyses show the potential source areas and pathways of sulfate-rich secondary aerosols, especially the regional influences of the biogenic, as well as anthropogenic secondary aerosol. This study indicates that temperature-resolved carbon fractions can be used to enhance the source apportionment of ambient PM2.5.     

Primary and secondary carbonaceous species in PM2.5 samples in Milan (Italy)

Seasonal elemental carbon (EC) and organic carbon (OC) concentration levels in PM2.5 samples collected in Milan (Italy) are presented and discussed, enriching the world-wide database of carbonaceous species in fine particulate matter (PM). High-volume PM2.5 sampling campaigns were performed from August 2002 through December 2003 in downtown Milan at an urban background site. Compared to worldwide average concentrations, in Milan warm-season OC and both warm- and cold-season EC are relatively low; conversely, cold-season OC concentrations are rather high. Consequently, high values for the OC/EC ratio are observed, especially in the winter period. The relation between OC/EC ratio values and wind direction is investigated, pointing out that the highest ratios are associated to winds blowing from those nearby areas where wood consumption for domestic heating is larger. Information on the OC partitioning between its primary and secondary fraction are derived by means of the EC-tracer method and principal component analysis. In the warm-season, OC is mainly of secondary origin, secondary organic aerosol (SOA) accounting for about 84% of the particulate organic matter and 25–28% of the PM2.5 mass. For the cold season the full application of the EC-tracer method was not possible and the primary organic aerosol deriving from traffic could only be estimated. However, principal component analysis (PCA) suggest a prevailing primary origin for OC, thus raising the attention on space heating emissions, and on wood combustion in particular, for air quality control. The role of traffic emissions on PM2.5 concentration levels, as a primary source, are also assessed: EC and primary organic matter from traffic account for a warm-season 30% and a cold-season 7% of the total carbon in PM2.5, that is for about 10% and 6% of PM2.5 mass, respectively. This latter small primary contribution estimated for the cold-season points out that stationary sources, which were not thought to play a significant role on PM concentration levels, may conversely be as much responsible for ambient particulate pollution.     

Effects of sulfur dioxide and oxides of nitrogen emission reductions on fine particulate matter mass concentrations: regional comparisons

Two thermodynamic equilibrium models were applied to estimate changes in mean airborne fine particle (PM2.5) mass concentrations that could result from changes in ambient concentrations of sulfate, nitric acid, or ammonia in the southeastern United States, the midwestern United States, and central California. Pronounced regional differences were found. Southeastern sites exhibited the lowest current mean concentrations of nitrate, and the smallest predicted responses of PM2.5 nitrate and mass concentrations to reductions of nitric acid, which is the principal reaction product of the oxidation of nitrogen dioxide (NO2) and the primary gas-phase precursor of fine particulate nitrate. Weak responses of PM2.5 nitrate and mass concentrations to changes in nitric acid levels occurred even if sulfate concentrations were half of current levels. The midwestern sites showed higher levels of fine particulate nitrate, characterized by cold-season maxima, and were projected to show decreases in overall PM levels following decreases of either sulfate or nitric acid. For some midwestern sites, predicted PM2.5 nitrate concentrations increased as modeled sulfate levels declined, but sulfate reductions always reduced the predicted fine PM mass concentrations; PM2.5 nitrate concentrations became more sensitive to reductions of nitric acid as modeled sulfate concentrations were decreased. The California sites currently have the highest mean concentrations of fine PM nitrate and the lowest mean concentrations of fine PM sulfate. Both the estimated PM2.5 nitrate and fine mass concentrations decreased in response to modeled reductions of nitric acid at all California sites. The results indicate important regional differences in expected PM2.5 mass concentration responses to changes in sulfate and nitrate precursors. Analyses of ambient data, such as described here, can be a key part of weight of evidence (WOE) demonstrations for PM2.5 attainment plans. Acquisition of the data may require special sampling efforts, especially for PM2.5 precursor concentration data.     

Improving Source Apportionment of Fine Particles in the Eastern United States Utilizing Temperature-Resolved Carbon Fractions

Abstract

The objectives of this study were to examine the use of carbon fractions to identify particulate matter (PM) sources, especially traffic‐related carbonaceous particle sources, and to estimate their contributions to the particle mass concentrations. In recent studies, positive matrix factorization (PMF) was applied to ambient fine PM (PM_2.5) compositional data sets of 24‐hr integrated samples including eight individual carbon fractions collected at three monitoring sites in the eastern United States: Atlanta, GA, Washington, DC, and Brigantine, NJ. Particulate carbon was analyzed using the Interagency Monitoring of Protected Visual Environments/Thermal Optical Reflectance method that divides carbon into four organic carbons (OC): pyrolized OC and three elemental carbon (EC) fractions. In contrast to earlier PMF studies that included only the total OC and EC concentrations, gasoline emissions could be distinguished from diesel emissions based on the differences in the abundances of the carbon fractions between the two sources. The compositional profiles for these two major source types show similarities among the three sites. Temperature‐resolved carbon fractions also enhanced separations of carbon‐rich secondary sulfate aerosols. Potential source contribution function analyses show the potential source areas and pathways of sulfate‐rich secondary aerosols, especially the regional influences of the biogenic, as well as anthropogenic secondary aerosol. This study indicates that temperature‐resolved carbon fractions can be used to enhance the source apportionment of ambient PM_2.5.     

Main particulate matter components in Saxony (Germany)

Aerosol filter samples have been collected nearby the industrialised basin of Leipzig in Saxony (Germany) at the research station Melpitz of the Institut für Troposphärenforschung e.V. (IfT). Time series (1992–1998) and a three year comparison (1995–1997) of two different aerosol filter sampling systems, the Sierra-Andersen-PM 10 high volume sampler (daily sample, PM 10 inlet) and the Rupprecht and Patashnik Co. Inc. Model Partisol 2000 (weekly sample, PM 10 and PM 2.5 inlet) are presented and discussed. The comparison of the different sampling systems and strategies yields small differences between the daily and weekly samples for mass and different ions, which may be influenced by sampling duration and flow rates. A general trend of change in aerosol composition was observed: Soot and Sulphate concentrations decreased whereas Nitrate and Ammonium concentrations increased. During summers the mass of coarse particles is higher than in other seasons. One reason could be found in the occurence of longer periods of dry ground surfaces enabling reemission of crustal and biological material. The time series have been integrated in a longer historical aerosol mass trend for Saxony and do show a good agreement. Since 1990 a significant downward trend in gravimetric mass concentration was found.     

Profile analysis of ambient and source emitted particle-bound polycyclic aromatic hydrocarbons from three sites in northern Greece

Polycyclic aromatic hydrocarbons (PAHs) adsorbed to ambient PM(10) were determined at three sites in Thessaloniki, northern Greece, during the period June 1997-July 1998. Ambient PAH profiles exhibited significant seasonal and spatial variations. Source PAH profiles were obtained for a number of urban, industrial and geological sources including cement, fertilizer and asphalt production, quarry operations, metal electroplating, metal welding and tempering, steel manufacture, lead and bronze smelters, metal scrap incineration, oil burning, non-catalyst equipped passenger cars, diesel fueled taxies and buses, paved road dust and soil dust. Principal component analysis (PCA) and diagnostic ratios were employed to compare ambient and source PAH profiles in an attempt to recognize compositional patterns. Similarities between the ambient PAH profiles and the profiles of certain sources, such as vehicular emissions, oil burning and metal industries, were identified.     

Exposure of chronic obstructive pulmonary disease patients to particulate matter: relationships between personal and ambient air concentrations

Mot time-series studies of particulate air pollution and acute health outcomes assess exposure of the study population using fixed-site outdoor measurements. To address the issue of exposure misclassification, we evaluate the relationship between ambient particle concentrations and personal exposures of a population expected to be at risk of particle health effects. Sampling was conducted within the Vancouver metropolitan area during April-September 1998. Sixteen subjects (non-smoking, ages 54-86) with physician-diagnosed chronic obstructive pulmonary disease (COPD) wore personal PM2.5 monitors for seven 24-hr periods, randomly spaced approximately 1.5 weeks apart. Time-activity logs and dwelling characteristics data were also obtained for each subject. Daily 24-hr ambient PM10 and PM2.5 concentrations were measured at five fixed sites spaced throughout the study region. SO4(2-), which is found almost exclusively in the fine particle fraction and which does not have major indoor sources, was measured in all PM2.5 samples as an indicator of accumulation mode particulate matter of ambient origin. The mean personal and ambient PM2.5 concentrations were 18 micrograms/m3 and 11 micrograms/m3, respectively. In analyses relating personal and ambient measurements, ambient concentrations were expressed either as an average of the values obtained from five ambient monitoring sites for each day of personal sampling, or as the concentration obtained at the ambient site closest to each subject's home. The mean personal to ambient concentration ratio of all samples was 1.75 (range = 0.24 to 10.60) for PM2.5, and 0.75 (range = 0.09 to 1.42) for SO4(2-). Regression analyses were conducted for each subject separately and on pooled data. The median correlation (Pearson's r) between personal and average ambient PM2.5 concentrations was 0.48 (range = -0.68 to 0.83). Using SO4(2-) as the exposure metric, the median r between personal and average ambient concentrations was 0.96 (range = 0.66 to 1.0). Use of the closest ambient site did not improve the median correlation of the group for either PM2.5 or SO4(2-). All pooled analyses resulted in lower correlation coefficients than the median correlation coefficient of individual regressions. Personal SO4(2-) was more highly correlated with all ambient measures than PM2.5. Inclusion of time-activity and dwelling characteristics data did not result in a useful predictive regression model for PM2.5 personal exposure, but improved the model fit from simply regressing against ambient concentration (R2 = 0.27). The model for SO4(2-) was predictive (R2 = 0.82), as personal exposures were largely explained by ambient levels. These results indicate a relatively low correlation between personal exposure and ambient PM2.5 that is not improved by assigning exposure to the closest ambient monitor. The correlation between personal exposure and ambient concentration is high, however, when using SO4(2-), an indicator of accumulation mode particulate matter of ambient origin.     

Estimated hourly personal exposures to ambient and nonambient particulate matter among sensitive populations in Seattle, Washington

Epidemiological studies of particulate matter (PM) routinely use concentrations measured with stationary outdoor monitors as surrogates for personal exposure. Despite the frequently reported poor correlations between ambient concentrations and total personal exposure, the epidemiologic associations between ambient concentrations and health effects depend on the correlation between ambient concentrations and personal exposure to ambient-generated PM. This paper separates personal PM exposure into ambient and nonambient components and estimates the outdoor contribution to personal PM exposures with continuous light scattering data collected from 38 subjects in Seattle, WA. Across all subjects, the average exposure encountered indoors at home was lower than in all other microenvironments. Cooking and being at school were associated with elevated levels of exposure. Previously published estimates of particle infiltration (Finf) were combined with time-location data to estimate an ambient contribution fraction (alpha, mean = 0.66+/-0.21) for each subject. The mean alpha was significantly lower for subjects monitored during the heating season (0.55+/-0.16) than for those monitored during the nonheating season (0.80+/-0.17). Our modeled alpha estimates agreed well with those estimated with the sulfur-tracer method (slope = 1.08; R2 = 0.67). We modeled exposure to ambient and nonambient PM with both continuous light scattering and 24-hr gravimetric data and found good agreement between the two methods. On average, ambient particles accounted for 48% of total personal exposure (range = 21-80%). The personal activity exposure was highly influenced by time spent away from monitored microenvironments. The median hourly longitudinal correlation between central site concentrations and personal exposures was 0.30. Although both alpha and the nonambient sources influence the personal-central relationship, the latter seems to dominate. Thus, total personal exposure may be poorly predicted by stationary outdoor monitors, particularly among persons whose PM exposure is dominated by nonambient exposures, for example, those living in tightly sealed homes, those who cook, and children.     

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.     

Source identifications of airborne fine particles using positive matrix factorization and U.S. Environmental Protection Agency positive matrix factorization

The widely used source apportionment model, positive matrix factorization (PMF2), has been applied to various air pollution data. Recently, U.S. Environmental Protection Agency (EPA) developed EPA positive matrix factorization (PMF), a version of PMF that will be freely distributed by EPA. The objectives of this study were to conduct source apportionment studies for particulate matter less than 2.5 microm in aerodynamic diameter (PM(2.5)) speciation data using PMF2 and EPA PMF (version 1.1) and to compare identified sources between the two models. In the present study, ambient PM(2.5) compositional datasets of 24-hr integrated samples collected at EPA Speciation Trends Network monitoring sites in Chicago, IL, and Portland, OR, were analyzed. Both PMF2 and EPA PMF extracted eight sources for the Chicago data and 10 sources for the Portland data. The model-resolved source profiles were similar between two models for both datasets. However, in several sources, the average contributions did not agree well and the time series contributions were not highly correlated. The differences between PMF2 and EPA PMF solutions were caused by the different least-square algorithm and the different nonnegativity constraints. Most of the average source contributions resolved by both models were within 5-95% uncertainty provided by EPA PMF, indicating that the sources resolved by both models were reproducible.     

Designing Optimal Strategies to Attain the New U.S. Particulate Matter Standards: Some Initial Concepts

ABSTRACT

This paper proposes that a fundamental principle for designing optimal strategies to attain new U.S. particulate matter (PM) standards be minimization of community and susceptible group exposure to, and inhaled dosage of, ambient PM. Properly done, such minimization maximizes human health risk reduction. To illustrate implementation of such a principle, an initial prototype model, PM Exposure (PMEX), is described that calculates PM exposure and inhaled dosage as figures-of-merit for control strategy optimization. The model accounts for age-occupation and susceptible group activity patterns, indoor-outdoor concentration differences, and geographical location. Modeling results are presented for a hypothetical example, apportioning inhaled dosage among different classes of sources, under alternative assumptions about the relative potency of different PM species categories. The results, while preliminary, demonstrate that conclusions about source class contribution based on inhaled dosage can be appreciably different than those based on ambient air measurements or emission inventories.     

The chemical composition of tropospheric aerosols and their contributing sources to a continental background site in northern Zimbabwe from 1994 to 2000

Atmospheric aerosols were collected in separate coarse (2–10 μm diameter) and fine (diameter less than 2 μm) size fractions at Rukomechi Research Station (16.1°S, 29.4°E), Zimbabwe, in the central part of southern Africa, from September 1994 to January 2000. The samples were analysed for the particulate mass (PM), black carbon, and 47 elements. The overall data set and the separate wet and dry season data sets were examined with absolute principal component analysis (APCA). Natural and anthropogenic aerosol sources were identified in both seasons, but the sources and their contributions to the total PM were found to vary between seasons and between size fractions. Crustal matter, sea salt (SS), a mixed biogenic (BIO) emission/biomass burning (BB) component, and a copper component were identified for the coarse aerosols during the wet season. APCA attributed 29% of the total wet season coarse PM to the mixed BIO/BB component, and 32% to SS. The copper component is likely due to the copper smelters in the Zambian Copperbelt. The dry season coarse PM originated from crustal matter, BB, BIO, and SS sources, with the major contribution (32%) coming from BB. Four components (crustal matter, BB, non-ferrous smelters, and SS) were identified for the fine particles for both the wet and dry seasons. The BB component provided the major contribution to the total fine PM, accounting for 44% and 79% in the wet and dry seasons, respectively. The relative contributions to the total PM (both fine and coarse) for all sources were greater in the dry season than the wet season, except for SS.     

First assessment of the PM<Subscript>10</Subscript> and PM<Subscript>2.5</Subscript> particulate level in the ambient air of belgrade city

INTENTION, GOAL, SCOPE, BACKGROUND: As the strong negative health effect of exposure to the inhalable particulate matter PM10 in the urban environment has been confirmed, the study of the mass concentrations, physico-chemical characteristics, sources, as well as spatial and temporal variation of atmospheric aerosol particles becomes very important. OBJECTIVE: This work is a pilot study to assess the concentration level of ambient suspended particulate matter, with an aerodynamic diameter of less than 10 microm, in the Belgrade central urban area. Average daily concentrations of PM10 and PM2.5 have been measured at three representative points in the city between June 2002 and December 2002. The influence of meteorological parameters on PM10 and PM2.5 concentrations was analyzed, and possible pollution sources were identified. METHODS: Suspended particles were collected on Pure Teflon filters by using a Mini-Vol low-volume air sampler (Airmetrics Co., Inc.; 5 l min(-1) flow rate). Particle mass was determined gravimetrically after 48 h of conditioning in a desiccator, in a Class 100 clean room at the temperature T = 20 degrees C and at about 50% constant relative humidity (RH). RESULTS AND DISCUSSION: Analysis of the PM10 data indicated a marked difference between season without heating--(summer; mean value 56 microg m(-3)) and heating season--(winter; mean value 96 microg m3); 62% of samples exceeded the level of 50 microg m(-3). The impact of meteorological factors on PM concentrations was not immediately apparent, but there was a significant negative correlation with the wind speed. CONCLUSIONS: The PM10 and PM2.5 mass concentrations in the Belgrade urban area had high average values (77 microg m(-3) and 61 microg m(-3)) in comparison with other European cities. The main sources of particulate matter were traffic emission, road dust resuspension, and individual heating emissions. When the air masses are coming from the SW direction, the contribution from the Obrenovac power plants is evident. During days of exceptionally severe pollution, in both summer and winter periods, high production of secondary aerosols occurred, as can be seen from an increase in PM2.5 in respect to PM10 mass concentration. RECOMMENDATION AND OUTLOOK: The results obtained gave us the first impression of the concentration level of particulate matter, with an aerodynamic diameter of less than 10 microm, in the Belgrade ambient air. Due to measured high PM mass concentrations, it is obvious that it would be very difficult to meet the EU standards (EEC 1999) by 2010. It is necessary to continue with PM10 and PM2.5 sampling; and after comprehensive analysis which includes the results of chemical and physical characterization of particles, we will be able to recommend effective control measures in order to improve air quality in Belgrade.     

The 1999 Fresno particulate matter exposure studies: comparison of community, outdoor, and residential PM mass measurements

Two collaborative studies have been conducted by the U.S. Environmental Protection Agency (EPA) National Exposure Research Laboratory (NERL) and National Health and Environmental Effects Research Laboratory to determine personal exposures and physiological responses to particulate matter (PM) of elderly persons living in a retirement facility in Fresno, CA. Measurements of PM and other criteria air pollutants were made inside selected individual residences within the retirement facility and at a central outdoor site on the premises. In addition, personal PM exposure monitoring was conducted for a subset of the participants, and ambient PM monitoring data were available for comparison from the NERL PM research monitoring platform in central Fresno. Both a winter (February 1-28, 1999) and a spring (April 19-May 16, 1999) study were completed so that seasonal effects could be evaluated. During the spring study, a more robust personal exposure component was added, as well as a more detailed evaluation of physical factors, such as air-exchange rate, that are known to influence the penetration of particles into the indoor environment. In this paper, comparisons are made among measured personal PM exposures and PM mass concentrations measured at the NERL Fresno Platform site, outside on the premises of the retirement facility, and inside selected residential apartments at the facility during the two 28-day study periods. The arithmetic daily mean personal PM2.5 exposure during the winter study period was 13.3 micrograms/m3, compared with 9.7, 20.5, and 21.7 micrograms/m3 for daily mean overall apartment, outdoor, and ambient (i.e., platform) concentrations, respectively. The daily mean personal PM2.5 exposure during the spring study period was 11.1 micrograms/m3, compared with 8.0, 10.1, and 8.6 micrograms/m3 for the daily mean apartment, outdoor, and ambient concentrations, respectively.     

Analysis of trace elements and ions in ambient fine particulate matter at three elementary schools in Ohio

The results from a chemical characterization study of fine particulate matter (PM2.5) measured at three elementary schools in Central and Southeast Ohio is presented here. PM2.5 aerosol samples were collected from outdoor monitors and indoor samplers at each monitoring location during the period of February 1, 1999, through August 31, 2000. The locations included a rural elementary school in Athens, OH, and two urban schools within Columbus, OH. The trace metal and ionic concentrations in the collected samples were analyzed using an X-ray fluorescence spectrophotometer and ion chromatography unit, respectively. Sulfate ion was found to be the largest component present in the samples at all three of the sites. Other abundant components included nitrate, chloride, ammonium, and sodium ions, as well as calcium, silicon, and iron. The average PM2.5 concentrations showed similar temporal variations among the three sites within the study region. PM2.5 and its major component, sulfate ion, showed strong seasonal variations with maximum concentrations observed during the summer at all three of the sites. The indoor environment was found to be more contaminated during the spring months (March through May) at New Albany (a suburb of Columbus, OH) and East Athens (rural Ohio area). Potential source contribution function analysis showed that particulate matter levels at the monitoring sites were affected by transport from adjoining urban areas and industrial complexes located along the Ohio River Valley. A preliminary outdoor source apportionment using the principal component analysis (PCA) technique was performed. The results from the PCA suggest that the study region was primarily impacted by industrial, fossil fuel combustion, and geological sources. The 2002 emissions inventory data for PM2.5 compiled by Ohio Environmental Protection Agency also showed impacts of similar source types, and this was used to validate the PCA analysis.     

A procedure for use in estimating human exposure to particulate matter of ambient origin

Modern epidemiology has shown that fluctuations of mortality data are statistically significantly correlated with fluctuations of ambient particulate matter (PM) concentration data. This relation cannot be confounded by exposure to PM of indoor origin because the concentrations of ambient PM are not correlated with concentrations of PM of indoor origin. It has been suggested, given the above understanding, that modern PM exposure measurements and analysis should create separate estimates of exposure to all PM of ambient origin and exposure to all PM of nonambient origin (primarily of indoor origin), and not exposure to total PM. This paper reviews the developments of the form of the general microenvironmental mass balance equation that can be utilized for estimating human exposure to PM of ambient origin and for estimating the portion of total PM exposure that is attributable to nonambient origin PM. The equation is perfectly general and can be applied to conditions of time-varying factors that influence exposure, such as rapidly changing air-exchange rates in a home as doors and windows are opened and closed, and turning on and off air cleaners in a home. It is suggested that this procedure be applied in exposure assessment studies and validated using independent techniques of estimating exposure to PM of ambient origin available in the literature.