Monitoring and Source Apportionment of Particulate Matter near a Large Phosphorus Production Facility

ABSTRACT

A source apportionment study was conducted to identify sources within a large elemental phosphorus plant that contribute to exceedances of the National Ambient Air Quality Standards (NAAQS) for 24-hr PM₁₀. Ambient data were collected at three monitoring sites from October 1996 through July 1999, and included the following: 24-hr PM₁₀ mass, 24-hr PM_2.5 and PM_10–2.5 mass and chemistry, continuous PM₁₀and PM_2.5 mass, continuous meteorological data, and wind-direction-resolved PM_2.5 and PM₁₀ mass and chemistry. Ambient-based receptor modeling and wind-directional analysis were employed to help identify major sources or source locations and source contributions. Fine-fraction phosphate was the dominant species observed during PM₁₀ exceedances, though in general, re-suspended coarse dusts from raw and processed materials at the plant were also needed to create an exceedance. Major sources that were identified included the calciners, the CO flares, process-related dust, and electric-arc furnace operations.     

PM10 dispersion modeling for Treasure Valley, Idaho

The recorded exceedances of the 24-hr PM10 National Ambient Air Quality Standard (NAAQS) in Treasure Valley, Idaho, have been associated with prolonged stagnation periods during the winter. A comprehensive modeling study of PM10 impact in Treasure Valley was performed to support the State Implementation Plan (SIP). The study included base-year and short-term episodic conditions. The ISCST3 (Industrial Source Complex Short Term 3) model, using the base-year meteorology and gridded emissions of mobile sources, point sources, and wood burning as input, generally agreed well with measurements in both temporal patterns and annual averages. The WYNDvalley model was evaluated using monitoring data and was used to simulate the PM10 impact for episodic exceedances during stagnant winter conditions. An emission inventory was prepared for a base year (1995) and then extrapolated to the years 2000, 2005, 2010, and 2015 in order to determine air quality planning requirements. According to the simulations using base-year emissions and meteorology, exceedances are not expected. However, exceedances at some stations could be expected using projected emissions and episodic meteorology. Results from emission control strategies we developed indicate that mobile-source emissions have the most significant impact; reduction of 25% would be needed to eliminate the simulated exceedances in all projected years.     

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.     

Estimation of ambient PM2.5 concentrations in Maryland and verification by measured values

In 1997, Maryland had no available ambient Federal Reference Method data on particulate matter less than 2.5 microm in aerodynamic diameter (PM23), but did have annual ambient data for PM smaller than 10 microm (PM10) at 24 sites. The PM10 data were analyzed in conjunction with local annual and seasonal zip-code-level emission inventories and with speciated PM2.5 data from four nearby monitors in the IMPROVE network (located in the national parks, wildlife refuges, and wilderness areas) in an effort to estimate annual average and seasonal high PM2.5 concentrations at the 24 PM10 monitor sites operating from 1992 to 1996. All seasonal high concentrations were estimated to be below the 24-hr PM2.5 National Ambient Air Quality Standards (NAAQS) at the sites operating in Maryland between 1992 and 1996. The estimates also indicated that 12 monitor sites might exceed the 3-year annual average PM2.5 NAAQS of 15 microg/m3, but Maryland's air quality shows signs that it has been improving since 1992. The estimates also were compared with actual measurements after the PM2.5 monitor network was installed. The estimates were adequate for describing the chemical composition of the PM2.5, forecasting compliance status with the 24-hr and annual standards, and determining the spatial variations in PM2.5 across central Maryland.     

Apportionment of ambient primary and secondary fine particulate matter at the Pittsburgh National Energy Laboratory particulate matter characterization site using positive matrix factorization and a potential source contributions function analysis

Fine particulate matter (PM2.5) concentrations associated with 202 24-hr samples collected at the National Energy Technology Laboratory (NETL) particulate matter (PM) characterization site in south Pittsburgh from October 1999 through September 2001 were used to apportion PM2.5 into primary and secondary contributions using Positive Matrix Factorization (PMF2). Input included the concentrations of PM2.5 mass determined with a Federal Reference Method (FRM) sampler, semi-volatile PM2.5 organic material, elemental carbon (EC), and trace element components of PM2.5. A total of 11 factors were identified. The results of potential source contributions function (PSCF) analysis using PMF2 factors and HYSPLIT-calculated back-trajectories were used to identify those factors associated with specific meteorological transport conditions. The 11 factors were identified as being associated with emissions from various specific regions and facilities including crustal material, gasoline combustion, diesel combustion, and three nearby sources high in trace metals. Three sources associated with transport from coal-fired power plants to the southeast, a combination of point sources to the northwest, and a steel mill and associated sources to the west were identified. In addition, two secondary-material-dominated sources were identified, one was associated with secondary products of local emissions and one was dominated by secondary ammonium sulfate transported to the NETL site from the west and southwest. Of these 11 factors, the four largest contributors to PM2.5 were the secondary transported material (dominated by ammonium sulfate) (47%), local secondary material (19%), diesel combustion emissions (10%), and gasoline combustion emissions (8%). The other seven factors accounted for the remaining 16% of the PM2.5 mass. The findings are consistent with the major source of PM2.5 in the Pittsburgh area being dominated by ammonium sulfate from distant transport and so decoupled from local activity emitting organic pollutants in the metropolitan area. In contrast, the major local secondary sources are dominated by organic material.     

Characterization of summertime coarse particulate matter in the Desert Southwest—Arizona,USA

A year-long study was conducted in Pinal County, AZ, to characterize coarse (2.5 – 10 μm aerodynamic diameter, AD) and fine (< 2.5 μm AD) particulate matter (PMc and PMf, respectively) to further understand spatial and temporal variations in ambient PM concentrations and composition in rural, arid environments. Measurements of PMc and PMf mass, ions, elements, and carbon concentrations at one-in-six day resolution were obtained at three sites within the region. Results from the summer of 2009 and specifically the local monsoon period are presented.

The summer monsoon season (July – September) and associated rain and/or high wind events, has historically had the largest number of PM₁₀ NAAQS exceedances within a year. Rain events served to clean the atmosphere, decreasing PMc concentrations resulting in a more uniform spatial gradient among the sites. The monsoon period also is characterized by high wind events, increasing PMc mass concentrations, possibly due to increased local wind-driven soil erosion or transport. Two PM₁₀ NAAQS exceedances at the urban monitoring site were explained by high wind events and can likely be excluded from PM₁₀ compliance calculations as exceptional events. At the more rural Cowtown site, PM₁₀ NAAQS exceedances were more frequent, likely due to the impact from local dust sources.

PM mass concentrations at the Cowtown site were typically higher than at the Pinal County Housing and Casa Grande sites. Crustal material was equal to 52-63% of the PMc mass concentration on average. High concentrations of phosphate and organic carbon found at the rural Cowtown were associated with local cattle feeding operations. A relatively high correlation between PMc and PMf (R²?=?0.63) indicated that the lower tail of the coarse particle fraction often impacts the fine particle fraction, increasing the PMf concentrations. Therefore, reductions in PMc sources will likely also reduce PMf concentrations, which also are near the value of the 24-hr PM_2.5 NAAQS.

Implications: In the desert southwest, summer monsoons are often associated with above average PM₁₀ (<10 μm AD) mass concentrations. Competing influences of monsoon rain and wind events showed that rain suppresses ambient concentrations while high wind increase them. In this region, the PMc fraction dominates PM₁₀ and crustal sources contribute 52-63% to local PMc mass concentrations on average. Cattle feedlot emissions are also an important source and a unique chemical signature was identified for this source. Observations suggest monsoon wind events alone cannot explain PM₁₀ NAAQS exceedances, thus requiring these values to remain in compliance calculations rather than being removed as exceptional wind events.     

Use of a continuous nephelometer to measure personal exposure to particles during the U.S. Environmental Protection Agency Baltimore and Fresno Panel studies

In population exposure studies, personal exposure to PM is typically measured as a 12- to 24-hr integrated mass concentration. To better understand short-term variation in personal PM exposure, continuous (1-min averaging time) nephelometers were worn by 15 participants as part of two U.S. Environmental Protection Agency (EPA) longitudinal PM exposure studies conducted in Baltimore County, MD, and Fresno, CA. Participants also wore inertial impactor samplers (24-hr integrated filter samples) and recorded their daily activities in 15-min intervals. In Baltimore, the nephelometers correlated well (R2 = 0.66) with the PM2.5 impactors. Time-series plots of personal nephelometer data showed each participant's PM exposure to consist of a series of peaks of relatively short duration. Activities corresponding to a significant instrument response included cooking, outdoor activities, transportation, laundry, cleaning, shopping, gardening, moving between microenvironments, and removing/putting on the instrument. On average, 63-66% of the daily PM exposure occurred indoors at home (about 2/3 of which occurred during waking hours), primarily due to the large amount of time spent in that location (an average of 72-77%). Although not a reference method for measuring mass concentration, the nephelometer did help identify PM sources and the relative contribution of those sources to an individual's personal exposure.     

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.     

The Steubenville Comprehensive Air Monitoring Program (SCAMP): concentrations and solubilities of PM(2.5) trace elements and their implications for source apportionment and health research

The elemental compositions of the water-soluble and acid-digestible fractions of 24-hr integrated fine particulate matter (PM(2.5)) samples collected in Steubenville, OH, from 2000 to 2002 were determined using dynamic reaction cell inductively coupled plasma-mass spectrometry. The water-soluble elemental compositions of PM(2.5) samples collected at four satellite monitoring sites in the surrounding region were also determined. Fe was the most abundant but least water soluble of the elements determined at the Steubenville site, having a mean ambient concentration of 272 ng/m3 and a median fractional solubility of 6%. Fe solubility and its correlations with SO4(2-) and temperature varied significantly by season, consistent with the hypothesis that secondary sulfates may help to mobilize soluble Fe under suitable summertime photochemical conditions. Significantly higher ambient concentrations were observed at Steubenville than at each of the four satellite sites for 10 of the 18 elements (Al, As, Ca, Cd, Fe, Mg, Mn, Na, Pb, and Zn) determined in the water-soluble PM(2.5) fraction. Concentrations of Fe, Mn, and Zn at Steubenville were substantially higher than concentrations reported recently for larger U.S. cities. Receptor modeling identified seven sources affecting the Steubenville site. An (NH4)2SO4-dominated source, likely representing secondary PM(2.5) from coal-fired plants to the west and southwest of Steubenville, accounted for 42% of the PM(2.5) mass, and two sources likely dominated by emissions from motor vehicles and from iron and steel facilities in the immediate Steubenville vicinity accounted for 20% and 10%, respectively. Other sources included an NH4NO3 source (15%), a crustal source (6%), a mixed nonferrous metals and industrial source (3%), and a primary coal combustion source (3%). Results suggest the importance of very different regional and local source mechanisms in contributing to PM(2.5) mass at Steubenville and reinforce the need for further research to elucidate whether metals such as Fe, Mn, and Zn play a role in the PM(2.5) health effects observed previously there.     

Particle size distributions and elemental composition of atmospheric particulate matter in southern Italy

Three 2-wk seasonal field campaigns were performed in 2003 and 2004 at a sampling site on the southern Tyrrhenian coast of Italy with the aim to investigate the dynamics and characteristics of particle-bound pollutants in the Mediterranean area. Fine (PM(2.5)) and coarse particulate matter (PM(10-2.5)) size fractions were collected by a manual dichotomous sampler on 37-mm Teflon filters over a 24-hr sampling period. On average, 70% of the total PM(10) (PM(2.5) + PM(10-2.5)) mass was associated with the coarse fraction and 30% with the fine fraction during the three campaigns. The ambient concentrations of Pb, Ni, Cr, Zn, Mn, V, Cd, Fe, Cu, Ca, and Mg associated with both size fractions were determined by atomic absorption spectrometry. Ambient concentrations showed differences in their absolute value, ranging from few ng x m(-3) to microg x m(-3), as well as in their variability within the PM(2.5) and PM(10-2.5) size fractions. PM(10) levels were well below the European Union (EU) limit value during the study period with the exception of three events during the first campaign (fall) and five events during the third campaign (spring). Two main sources were identified as the major contributors including mineral dust, transported from North Africa, and sea spray from the Tyrrhenian Sea. Comparing the results with backward trajectories, calculated using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) and Total Ozone Mapping Spectrometer-National Aeronautics and Space Administration (TOMS-NASA) maps, it was observed that in central and eastern Europe, the Tyrrhenian Sea and North Africa were the major emission source regions that affected the temporal variations and daily averages of PM(2.5) and PM(10-2.5) concentrations.     

The influence of human activity patterns on personal PM exposure: a comparative analysis of filter-based and continuous particle measurements

Particulate matter (PM) exposure data from the U.S. Environmental Protection Agency (EPA)-sponsored 1998 Baltimore and 1999 Fresno PM exposure studies were analyzed to identify important microenvironments and activities that may lead to increased particle exposure for select elderly (>65 years old) subjects. Integrated 24-hr filter-based PM2.5 or PM10 mass measurements [using Personal Environmental Monitors (PEMs)] included personal measurements, indoor and outdoor residential measurements, and measurements at a central indoor site and a community monitoring site. A subset of the participants in each study wore passive nephelometers that continuously measured (1-min averaging time) particles ranging in size from 0.1 to approximately 10 microm. Significant activities and locations were identified by a statistical mixed model (p < 0.01) for each study population based on the measured PM2.5 or PM10 mass and time activity data. Elevated PM concentrations were associated with traveling (car or bus), commercial locations (store, office, mall, etc.), restaurants, and working. The modeled results were compared to continuous PM concentrations determined by the nephelometers while participants were in these locations. Overall, the nephelometer data agreed within 6% of the modeled PM2.5 results for the Baltimore participants and within approximately 20% for the Fresno participants (variability was due to zero drift associated with the nephelometer). The nephelometer did not agree as well with the PM10 mass measurements, most likely because the nephelometer optimally responds to fine particles (0.3-2 microm). Approximately one-half (54 +/- 31%; mean +/- standard deviation from both studies) of the average daily PM2.5 exposure occurred inside residences, where the participants spent an average of 83 +/- 10% of their time. These data also showed that a significant portion of PM2.5 exposure occurred in locations where participants spent only 4-13% of their time.     

Particulate matter in California: part 2--Spatial, temporal, and compositional patterns of PM2.5, PM10-2.5, and PM10

Geographic and temporal variations in the concentration and composition of particulate matter (PM) provide important insights into particle sources, atmospheric processes that influence particle formation, and PM management strategies. In the nonurban areas of California, annual-average PM2.5 and PM10 concentrations range from 3 to 10 microg/m3 and from 5 to 18 microg/m3, respectively. In the urban areas of California, annual-averages for PM2.5 range from 7 to 30 microg/m3, with observed 24-hr peaks reaching levels as high as 160 microg/m3. Within each air basin, exceedances are a mixture of isolated events as well as periods of elevated PM2.5 concentrations that are more prolonged and regional in nature. PM2.5 concentrations are generally highest during the winter months. The exception is the South Coast Air Basin, where fairly high values occur throughout the year. Annual-average PM2.5 mass, as well as the concentrations of major components, declined from 1988 to 2000. The declines are especially pronounced for the sulfate (SO4(2-)) and nitrate (NO3-) components of PM2.5 and PM10) and correlate with reductions in ambient levels of oxides of sulfur (SOx) and oxides of nitrogen (NOx). Annual averages for PM10-2.5 and PM10 exhibited similar downwind trends from 1994 to 1999, with a slightly less pronounced decrease in the coarse fraction.     

PM10 Dispersion Modeling for Treasure Valley,Idaho

ABSTRACT

The recorded exceedances of the 24-hr PM₁₀ National Ambient Air Quality Standard (NAAQS) in Treasure Valley, Idaho, have been associated with prolonged stagnation periods during the winter. A comprehensive modeling study of PM₁₀ impact in Treasure Valley was performed to support the State Implementation Plan (SIP). The study included base-year and short-term episodic conditions. The ISCST3 (Industrial Source Complex Short Term 3) model, using the base-year meteorology and gridded emissions of mobile sources, point sources, and wood burning as input, generally agreed well with measurements in both temporal patterns and annual averages. The WYNDvalley model was evaluated using monitoring data and was used to simulate the PM₁₀ impact for episodic exceedances during stagnant winter conditions. An emission inventory was prepared for a base year (1995) and then extrapolated to the years 2000, 2005, 2010, and 2015 in order to determine air quality planning requirements. According to the simulations using base-year emissions and meteorology, exceedances are not expected. However, exceedances at some stations could be expected using projected emissions and episodic meteorology. Results from emission control strategies we developed indicate that mobile-source emissions have the most significant impact; reduction of 25% would be needed to eliminate the simulated exceedances in all projected years.     

Roadside particulate air pollution in Bangkok

Airborne fine particles of PM(2.5-10) and PM2.5 in Bangkok, Nonthaburi, and Ayutthaya were measured from December 22, 1998, to March 26, 1999, and from November 30, 1999, to December 2, 1999. Almost all the PM10 values in the high-polluted (H) area exceeded the Thailand National Ambient Air Quality Standards (NAAQS) of 120 microg/m3. The low-polluted (L) area showed low PM10 (34-74 microg/m3 in the daytime and 54-89 microg/m3 at night). PM2.5 in the H area varied between 82 and 143 microg/m3 in the daytime and between 45 and 146 microg/m3 at night. In the L area, PM2.5 was quite low both day and night and varied between 24 and 54 microg/m3, lower than the U.S. Environmental Protection Agency (EPA) standard (65 microg/m3). The personal exposure results showed a significantly higher proportion of PM2.5 to PM10 in the H area than in the L area (H = 0.80 +/- 0.08 and L = 0.65 +/- 0.04). Roadside PM10 was measured simultaneously with the Thailand Pollution Control Department (PCD) monitoring station at the same site and at the intersections where police work. The result from dual simultaneous measurements of PM10 showed a good correlation (correlation coefficient: r = 0.93); however, PM levels near the roadside at the intersections were higher than the concentrations at the monitoring station. The relationship between ambient PM level and actual personal exposures was examined. Correlation coefficients between the general ambient outdoors and personal exposure levels were 0.92 for both PM2.5 and PM10. Bangkok air quality data for 1997-2000, including 24-hr average PM10, NO2, SO2, and O3 from eight PCD monitoring stations, were analyzed and validated. The annual arithmetic mean PM10 of the PCD data at the roadside monitoring stations for the last 3 years decreased from 130 to 73 microg/m3, whereas the corresponding levels at the general monitoring stations decreased from 90 to 49 microg/m3. The proportion of days when the level of the 24-hr average PM10 exceeded the NAAQS was between 13 and 26% at roadside stations. PCD data showed PM10 was well correlated with NO2 but not with SO2, suggesting that automobile exhaust is the main source of the particulate air pollution. The results obtained from the simultaneous measurement of PM2.5 and PM10 indicate the potential environmental health hazard of fine particles. In conclusion, Bangkok traffic police were exposed to high levels of automobile-derived particulate air pollution.     

PM source identification at Sunland Park, New Mexico, using a simple heuristic meteorological and chemical analysis

The causes for evening low-wind PM10 and PM2.5 peaks at Sunland Park, NM, were investigated by using wind sector analysis and by assessing relationships between PM loadings and meteorological parameters through canonical ordination analysis. Both PM10 and PM2.5 concentrations during the evening hours accounted for approximately 50% of their respective 24-hr averages, and the PM10 was mainly composed of coarse material (PM10-2.5 amounted to 77% of PM10). A wind sector analysis based on data from three surface meteorological monitoring stations in the region narrowed the potential source region for PM10 and PM2.5 to an area within a few kilometers south of Sunland Park. Canonical ordination analysis confirmed that the peak frequently occurred under stable conditions with weak southerly winds. Chemical analyses of PM showed that elemental and organic carbon (EC and OC, respectively) dominate PM2.5 and inorganic elements dominate PM10-2.5. The combined data for EC/OC, geologic elements, and various trace elements indicate that under low wind and stable conditions, traffic-related PM emissions (motor vehicle exhausts and re-suspended road dust) from the south of the site are the most likely sources for the evening PM10 and PM2.5 peaks.     

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).     

Assessing source characteristics of PM2.5 in the eastern United States using positive matrix factorization

Fine aerosol (PM2.5) measurements obtained from the first year of operation of the nationwide network of PM2.5 monitors were studied with the factor analysis technique of positive matrix factorization (PMF). PM2.5 mass concentration data were extracted from the Atmospheric Information Retrieval System (AIRS) database of the U.S. Environmental Protection Agency (EPA). PMF was applied to measurements at more than 350 monitoring locations in the eastern half of the United States. Data consisted of PM2.5 24-hr averaged concentrations measured every third day from April through December 1999. The PMF model suggested six factors representing source influences to the PM2.5 mass concentrations at measurement sites. Factor 5, covering much of the Appalachian states, exhibited significant seasonal behavior.     

Field evaluation of particulate matter measurements using tapered element oscillating microbalance in a layer house

The tapered element oscillating microbalance (TEOM) is one type of continuous ambient particulate matter (PM) monitor. Adsorption and desorption of moisture and semivolatile species may cause positive or negative artifacts in TEOM PM mass measurement. The objective of this field study was to investigate possible uncertainties associated with TEOM measurements in the poultry operation environment. For comparisons of TEOM with filter-based gravimetric method, four instruments (TEOM-PM10, low-volume PM10 sampler TEOM-PM2.5, and PM2.5 speciation sampler) were collocated and tested inside a poultry house for PM2.5 and PM10 (PM with aerodynamic equivalent diameter < or =2.5 and < or =10 microm, respectively) measurements. Fifteen sets of 24-hr PM10 concentrations and 13 sets of 24-hr PM2.5 measurements were obtained. Results indicate that compared with filter-based gravimetric method, TEOM gave significantly lower values of both PM10 and PM2.5 mass concentrations. For PM10, the average ratio of TEOM to the gravimetric method was 0.936. For PM2.5, the average ratio of TEOM to the gravimetric method was 0.738. Particulate matter in the poultry houses possibly contains semivolatile compounds and moisture due to high levels of relative humidity (RH) and gas pollutants. The internal heating mechanism of the TEOM may cause losses in mass through volatilization. To investigate the effects of TEOM settings on concentration measurements, the heaters of two identical TEOMs were set at 50 degrees C, 30 degrees C, or no heating at all. They were collocated and tested for total suspended particle (TSP), PM10, and PM25 measurements in layer house for 6 weeks. For all TSR PM10, and PM2.5 measurements, the internal TEOM temperature setting had a significant effect (P < 0.05). Significantly higher PM mass concentrations were measured at lower temperature settings. The effects of environmental (i.e., temperature, RH, NH3 and CO2 concentrations) and instrumental (i.e., filter loading and noise) parameters on PM measurements were also assessed using regression analysis.     

宁波市大气可吸入颗粒物PM1o和PM2.5的源解析研究

在宁波市布设4个代表性点位,于2010年春季、夏季和冬季进行大气PM10和PM2.s的采样,同时采集了多种颗粒物源样品,建立了PM10、PM2.5和源样品的化学成分谱.采用化学质量平衡模型(CMB)对宁波市PM10、PM2.5进行源解析.结果表明,城市扬尘、煤烟尘、机动车尾气尘是宁波市PM10、PM2.5的3大污染源,...     

Spatial characteristics of fine particulate matter: identifying representative monitoring locations in Seattle, Washington

This study investigates how PM2.5 varies spatially and how these spatial characteristics can be used to identify potential monitoring sites that are most representative of the overall ambient exposures to PM2.5 among susceptible populations in the Seattle, WA, area. Data collected at outdoor sites at the homes of participants of a large exposure assessment study were used in this study. Harvard impactors (HIs) were used at 40 outdoor sites throughout the Seattle metropolitan area. Up to six sites at a time were monitored for 10 consecutive 24-hr average periods. A fixed-effect analysis of variance (ANOVA) model that included date and location effects was used to analyze the spatial variability of outdoor PM2.5 concentrations. Both date and location effects were shown to be highly significant, explaining 92% of the variability in outdoor PM2.5 measurements. The day-to-day variability was 10 times higher than the spatial variability between sites. The site mean square was more than twice the error mean square, showing that differences between sites, while modest, are potentially an important contribution to measurement error. Variances of the model residuals and site effects were examined against spatial characteristics of the monitoring sites. The spatial characteristics included elevation, distance from arterials, and distance from major PM2.5 point sources. Results showed that the most representative PM2.5 sites were located at elevations of 80-120 m above sea level, and at distances of 100-300 m from the nearest arterial road. Location relative to industrial PM2.5 sources is not a significant predictor of residential outdoor PM2.5 measurements. Additionally, for sites to be representative of the average population exposures to PM2.5 among those highly susceptible to the health effects of PM2.5, areas of high elderly population density were considered. These representative spatial characteristics were used as multiple, overlapping criteria in a Geographic Information System (GIS) analysis to determine where the most representative sites are located.