Apportionment of Ambient Primary and Secondary PM2.5 During a 2001 Summer Intensive Study at the NETL Pittsburgh Site Using PMF2 and EPA UNMIX

Apportionment of primary and secondary pollutants during a July 2001 intensive study at the National Energy Technology Laboratory is reported. PM_2.5 was apportioned into primary and secondary contributions using PMF2, and results were compared with apportionment based on UNMIX 2.3. Input to PMF2 included PM_2.5 mass data from four per 24 hour PC-BOSS filters and TEOM, NO_x, NO₂, O₃, non-volatile, semi-volatile, and volatile organic material, elemental carbon, sulfate, and PIXE determined trace metals. Nine factors were identified in the PMF analysis. Six factors were associated with primary particles from crustal, mobile (gasoline and diesel), and three local sources high in trace metals. Three factors were associated with secondary sources. Two were associated with local emissions dominated by organic material, one was dominated by transported ammonium sulfate. UNMIX was able to identify the two major mobile sources, major local secondary source and transported secondary source. The three major sources of PM_2.5 were identified as secondary transported material (dominated by ammonium sulfate) from west and southwest (46%), secondary material formed during mid-day photochemical processes (21%), and primary emissions from diesel (10%) and gasoline (8%) mobile sources. The other five sources accounted for the remaining 15% of the PM_2.5. These findings are consistent with the majority of secondary ammonium sulfate in the Pittsburgh area resulting from distant transport, and so decoupled from local activity involving organic pollutants in the metropolitan area. In contrast, the major local secondary sources were dominated by organic material.     

Chemical Characteristics of Fine Particles (PM1) from Xi'an,China

Daily mass concentrations of water-soluble inorganic (WS-i) ions, organic carbon (OC), and elemental carbon (EC) were determined for fine particulate matter (PM₁, particles < 1.0 μm in diameter) collected at Xi'an, China. The annual mean PM₁ mass concentration was 127.3 ± 62.1 μg m^–3: WS-i ions accounted for ～38% of the PM₁ mass; carbonaceous aerosol was ～30%; and an unidentified fraction, probably mostly mineral dust, was ～32%. WS-i ions and carbonaceous aerosol were the dominant species in winter and autumn, whereas the unidentified fraction had stronger influences in spring and summer. Ion balance calculations indicate that PM₁ was more acidic than PM_2.5 from the same site. PM₁ mass, sulfate and nitrate concentrations followed the order winter > spring > autumn > summer, but OC and EC levels were higher in autumn than spring. Annual mean OC and EC concentrations were 21.0 ± 12.0 μg m^?3 and 5.1 ± 2.7 μg m^–3 with high OC/EC ratios, presumably reflecting emissions from coal combustion and biomass burning. Secondary organic carbon, estimated from the minimum OC/EC ratios, comprised 28.9% of the OC. Positive matrix factorization (PMF) analysis indicates that secondary aerosol and combustion emissions were the major sources for PM₁.     

Application of PSCF and CPF to PMF-Modeled Sources of PM2.5 in Pittsburgh

Ambient PM _2.5 composition data in Pittsburgh, PA have been used with Positive Matrix Factorization (PMF) to determine the major sources of PM _2.5 sampled. This paper describes the use of the potential source contribution function (PSCF) with the PMF-modeled source contributions to locate the sources in a grid of 0.1° × 0.1° cells. The domain extends from the Pittsburgh Supersite at 40.44°N, 79.94°W over the range 35°–50° north latitude and 75°–90° west longitude. Six-hour back trajectories have been obtained from HYSPLIT four times each day for the 13 months of the study for use with PSCF. Using the results, higher probability locations are compared with known locations of specific source types, based on information from the EPA Toxic Release Inventory (TRI) and the EPA AIRS Database. PSCF results for several sources are compared to the conditional probability function (CPF) analysis, which uses 15-minute wind direction data to determine the most probable direction of a source. Using PSCF and CPF together aids in interpretation of potential source regions. The selenium and sulfate factor source locations are regional, while the lead, cadmium, and specialty steel factor source locations are local. The gallium-rich and Fe, Mn, and Zn factor source locations are potentially both local and regional. The nitrate, vehicle emissions and road dust, wood combustion, vegetative detritus and cooking, and crustal material factor CPF and PSCF results were inconclusive as sources of these factors exist in all directions from the site and therefore one would not expect a clear probability field in any one direction.     

Source Investigation for Ambient PM 2.5 in Indianapolis,IN

The objectives of this study were to identify the sources of the PM _2.5 in Indianapolis, Indiana and estimate their contributions to the total PM _2.5 mass concentrations by analyzing the data from the samples collected at the EPA Speciation Trends Networks (STN) site in Indianapolis, Indiana. Both positive matrix factorization (PMF2) and an expanded factor analysis model were applied. The two methods obtained essentially identical source profiles and contributions, so the results of the simpler method, PMF, are described in the formal text of this paper in detail while the corresponding results provided by the expanded factor analysis model are presented in the supplemental material for this paper. The seven resolved sources are secondary sulfate (40.2%), secondary nitrate (21.9%), gasoline emission (16.6%), diesel emission (7.9%), airborne soil (5.3%), Fe-related industries (4.4%), and Cu-related industries (2.5%). The comparison between two models suggests that PMF coupled with subsequent data analysis methods (such as CPF, PSCF, seasonal variation analysis, and weekday/weekend variation analysis) yields the results that are comparable to those of the expanded factor analysis. The results suggest that such studies of STN data can be used to assist in the development of State Implementation Plans (SIPs) for PM _2.5 .     

Source Apportionment of One-Hour Semi-Continuous Data Using Positive Matrix Factorization with Total Mass (Nonvolatile plus Semi-Volatile) Measured by the R&P FDMS Monitor

Positive matrix factorization (PMF) was used to elucidate sources of fine particulate material (PM _2.5 ) for a study conducted during July 2003 in Rubidoux, CA. One-h averaged semi-continuous measurements were made with a suite of instruments to provide PM _2.5 mass and chemical composition data. Total PM _2.5 mass concentrations (nonvolatile plus semi-volatile) were measured with a R&P filter dynamic measurement system (FDMS) and a conventional TEOM monitor was used to measure nonvolatile mass concentrations. Semi-volatile material (SVM) was calculated as the FDMS minus the TEOM determined PM _2.5 mass. PM _2.5 chemical species monitors included a R&P 5400 carbon monitor, an Anderson Aethalometer and a R&P 8400N nitrate monitor. Gas phase data including CO, NO ₂ , NO _x , and O ₃ were also collected during the sampling period. Two distinct PMF analysis were performed. In analysis 1, the TEOM was excluded from the analysis and in analysis 2, the SVM was excluded from the analysis. PMF2 was able to identify six factors from the data set and factors corresponding to both primary and secondary sources were identified. Factors were attributed to being primarily from automobile, diesel emissions, secondary nitrate formation, a secondary photochemical associated source, organic emissions and primary emissions. Good agreement was observed between the PMF predicted mass and the FDMS measured mass for both analyses.     

Atmospheric aerosols over two sites in a southeastern region of Texas

Speciated samples of PM_2.5 were collected at the Bayland Park and Orange sites in Southeastern Texas by US EPA (Environmental Protection Agency) from July 2003 to August 2005. A total of 256 samples for the Bayland Park site and 293 samples for the Orange site with 52 species were measured; however, 22 species were excluded because of too many below‐detection‐limit data. Among the 22 species excluded, 19 species are common to both sites. The two data sets were analyzed by positive matrix factorization (PMF) to infer the sources of PM observed at the two sites. The analysis identified ten common source‐related factors: sulphate‐rich secondary aerosol I, sulphate‐rich secondary aerosol II, cement/carbon‐rich, wood smoke, motor vehicle/road dust, nitrate‐rich secondary aerosol, metal processing, soil, sea salt, and chloride‐depleted marine aerosol. sulphate and nitrate mainly exist as ammonium salts. The two sulphate‐rich secondary aerosols account for about 59% and 54% of the PM_2.5 mass concentration at the two sites, respectively. The factor containing highest concentrations of Cl and Na was attributed to sea salt due to the proximity of the monitoring sites to the Gulf of Mexico. The chloride‐depleted marine aerosol was related to the sea salt aerosol but was identified separately due to the chlorine replacement reactions. Basically, the factor of sulphate, nitrate, and soil at the two sites showed similar chemical composition profiles and seasonal variation that reflect the regional characteristics of these sources. The regional factors showed predominantly low frequency variations, however, the area‐related and local factors showed both high and low frequency variations. Motor vehicle/road dust, sea salt, and chloride‐depleted marine aerosol were likely to be area‐related factors. Cement/carbon‐rich, wood smoke, and metal processing factor were likely to be the local sources.     

Characteristics of PM2.5 Episodes Revealed by Semi-Continuous Measurements at the Baltimore Supersite at Ponca St

Highly time-resolved measurements of PM_2.5, its major constituents, particle size distributions (9 nm to 20 μ m), CO, NO/NO₂, and O₃, and meteorological parameters were made from February through November 2002, at the Baltimore Supersite at Ponca St. using commercial and prototype semi-continuous instruments. The average PM_2.5 mass concentration during the study period was 16.9 μ g/m³ and a total of 29 PM_2.5 pollution episodes, each in which 24-h averaged PM_2.5 mass concentrations exceeded 30.0 μ g/m³ for one or more days, were observed. Herein, 6 of the worst episodes are discussed. During these events, PM_2.5 excursions were often largely due to elevations in the concentration of one or two of the major species. In addition, numerous short-term excursions were observed and were generally attributable to local sources. Those in OC, EC, nitrate, CO, and NO_x levels were often observed in the morning traffic hours, particularly before breakdown of nocturnal inversions. Moreover, fresh accumulation aerosols from local stationary combustion sources were observed on several occasions, as evidenced by elevations in elemental markers when winds were aligned with sources resulting in PM_2.5 increments of ～ 17 μ g/m³. Overall, the results described herein show that concentrations of PM_2.5 and its major constituents vary enormously on time scales ranging from < 1 hr to several days, thus imposing a more highly complex pattern of pollutant exposure than can be captured by 24-hr integrated methods, alone. The data suggest that control of a limited number of local sources might achieve compliance with daily and annual PM_2.5 standards.     

PM1.0 and PM2.5 Characteristics in the Roadside Environment of Hong Kong

Daily mass concentrations of PM _1.0 (particles less than 1.0 μm in diameter), PM _2.5 (particles less than 2.5 μm in diameter), organic carbon (OC), and elemental carbon (EC) were measured from January through May 2004 at a heavily trafficked sampling site in Hong Kong (PU). The average concentrations for PM _1.0 and PM _2.5 were 35.9 ± 12.4 μ g cm ^{? 3} and 52.3 ± 18.3 μ g cm ^{? 3} . Carbonaceous aerosols were the dominant species in fine particles, accounting for ～ 45.7% of PM _1.0 and ～ 44.4% of PM _2.5 . During the study period, seven fine-particle episodes occurred, due to the influence of long-range transport of air masses from mainland China. PM _1.0 and PM _2.5 responded in similar ways; i.e., with elevated mass and OC concentrations in those episode days. During the sampling period, PM _1.0 OC and EC generally behaved similarly to the carbonaceous aerosols in PM _2.5 , regardless of seasonal variations and influence by regional pollutions. The low and relatively constant OC/EC ratios in PM _1.0 and PM _2.5 indicated that vehicular emissions were major sources of carbonaceous aerosols. PM _1.0 and PM _2.5 had the same dominant sources of vehicular emissions in winter, while in spring PM _2.5 was more influenced by PM _{1 ? 2.5} (particles 1–2.5 μ m in diameter) that did not form from vehicle exhausts. Therefore, PM _1.0 was a better indicator for vehicular emissions at the Roadside Station.     

Comparison of particle emissions from an engine operating on biodiesel and petroleum diesel

Biodiesel is an alternative fuel with growing usage in the transportation sector. To compare biodiesel and petroleum diesel effects on particle emissions, engine dynamometer tests were performed on a Euro II engine with three test fuels: petroleum diesel (D), biodiesel made from soy bean oil (BS) and biodiesel made from waste cooking oil (BW). PM_2.5 samples were collected on Teflon and quartz filters with a Model 130 High-Flow Impactor (MSP Corp). Organic (OC) and elemental (EC) carbon fractions of PM_2.5 were quantified by a thermal-optical reflectance analysis method and particle size distributions were measured with an electrical low pressure impactor (ELPI). In addition, the gaseous pollutants were measured by an AMA4000 (AVL Corp). The biodiesels were found to produce 19-37% less and 23-133% more PM_2.5 compared to the petroleum diesel at higher and lower engine loads respectively. On the basis of the carbon analysis results, the biodiesel application increased the PM_2.5 OC emissions by 12-190% and decreased the PM_2.5 EC emissions by 53-80%, depending on the fuel and engine operation parameters. Therefore OC/EC was increased by three to eight times with biodiesel application. The geometrical mean diameter of particles from biodiesels and petroleum diesel had consistent trends with load and speed transition. In all the conditions, there is a shift of the particles towards smaller geometric mean diameter for the biodiesel made from waste oil.     

Chemical Mass Closure and Chemical Characteristics of Ambient Ultrafine Particles and other PM Fractions

Ambient ultrafine particles (UPs or PM _0.1 ), PM _2.5 and PM ₁₀ were investigated at the roadside of Syuefu road in Hsinchu city and in the Syueshan highway tunnel in Taipei, Taiwan. A SMPS (TSI Model 3936), three Dichotomous samplers (Andersen Model SA-241), and three MOUDIs (MSP Model 110) were collocated to determine the PM number and mass concentrations simultaneously. The filter samples were further analyzed for organic carbon (OC), element carbon (EC), water-soluble ions, and trace elements. The OC artifact was studied and quantified using the quartz behind quartz (QBQ) method for all PM fractions. Taking into account the OC artifact, chemical mass closure (ratio of the reconstructed chemical mass to the gravimetrical mass) of PM _0.1 , PM _2.5 , and PM ₁₀ was then calculated and found to be good. The chemical analysis results of UPs at both sites showed that UPs in the present tunnel was mostly contributed from the vehicle emissions while UPs at the roadside was mainly influenced by urban sources.     

Using Statistical Regressions to Identify Factors Influencing PM2.5 Concentrations: The Pittsburgh Supersite as a Case Study

Using data from the Pittsburgh Air Quality Study, we find that temperature, relative humidity, their squared terms, and their interactions explain much of the variation in airborne concentrations of PM _2.5 in the city. Factors that do not appreciably influence the concentrations over a full year include wind direction, inverse mixing height, UV radiation, SO ₂ , O ₃ , and season of the year. Comparison with similar studies of PM _2.5 in other cities suggests that the relative importance of different factors can vary greatly. Temperature and relative humidity are important factors in both Pittsburgh and New York City, and synoptic scale meteorology influencing these two sites can explain much of the pattern in PM _2.5 concentrations which peak in the summer. However, PM _2.5 levels in other cities have different seasonal patterns and are affected by a number of other factors, and thus the results presented here cannot be generalized to other locations without additional study.     

Development and Laboratory Performance Evaluation of a Personal Multipollutant Sampler for Simultaneous Measurements of Particulate and Gaseous Pollutants

A personal multipollutant sampler has been developed. This sampler can be used for measuring exposures to particulate matter and criteria gases. The system uses asingle personalsampling pump that operates at a flow rate of 5.2 l/min. The basic unit consists of two impaction-based samplers for PM_2.5 and PM₁₀ attached to a single elutriator. Two mini PM_2.5 samplers are also attached to the elutriator for organic carbon (OC), elemental carbon (EC), sulfate, and nitrate measurements. For the collection of nitrate and sulfate, the minisampler includes a miniaturized honeycomb glass denuder that is placed upstream of the filter to remove nitric acid and sulfur dioxide and to minimize artifacts. Two passive samplers can also be attached to the elutriator for measurements of gaseous copollutants such as O₃, SO₂, and NO₂. The performance of the multipollutant sampler was examined through a series of laboratory chamber tests. The results showed a good agreement between the multipollutant sampler and the reference methods. The overall sampler performance demonstrates its suitability for personal exposure assessment studies.     

An Intercomparison of Measurement Methods for Carbonaceous Aerosol in the Ambient Air in New York City

Measurement methods for fine carbonaceous aerosol were compared under field sampling conditions in Flushing, New York during the period of January and early February 2004. In-situ 5- to 60-minute average PM _2.5 organic carbon (OC), elemental carbon (EC), and black carbon (BC) concentrations were obtained by the following methods: Sunset Laboratory field OC/EC analyzer, Rupprecht and Patashnick (R&P) series 5400 ambient carbon particulate monitor, Aerodyne aerosol mass spectrometer (AMS) for total organic matter (OM), and a two-wavelength AE-20 Aethalometer. Twenty-four hour averaged PM _2.5 filter measurements for OC and EC were also made with a Speciation Trends Network (STN) sampler. The diurnal variations in OC/EC/BC concentrations peaked during the morning and afternoon rush hours indicating the dominant influence of vehicle emissions. BC/EC slopes are found to range between 0.86 and 1.23 with reasonably high correlations (r > 0.75). Low mixing heights and absence of significant transported carbonaceous aerosol are indicated by the measurements. Strong correlations are observed between BC and thermal EC as measured by the Sunset instrument and between Sunset BC and Aethalometer BC. Reasonable correlations are observed among collocated OC/EC measurements by the various instruments.     

Effects of Dilution Sampling on Fine Particle Emissions from Pulverized Coal Combustion

A dilution sampler was used to examine the effects of dilution ratio and residence time on fine-particle emissions from a pilot-scale pulverized coal combustor. Measurements include the particle size distribution from 0.003 to 2.5 μm, PM_2.5 mass, and PM_2.5 composition (OC/EC, major ions, and elemental). Heated filter samples were also collected simultaneously at stack temperatures in order to compare the dilution sampler measurements with standard stack sampling methodologies. Measurements were made both before and after the bag house, the particle control device used on the coal combustor, and while firing three different coal types and one coal–biomass blend. The PM_2.5 mass emission rates measured using the dilution sampler agreed to within experimental uncertainty with those measured with the hot-filter sampler. Relative to the heated filter sample, dilution did increase the PM_2.5 mass fraction of selenium for all fuels tested, as well as ammonium and sulfate for selected fuels. However, the additional particulate mass created by gas-to-particle conversion of these species is within the uncertainty of the gravimetric analysis used to determine the overall mass emission rate. The enrichment of PM_2.5 selenium caused by dilution did not vary with dilution ratio and residence time. The enrichment of PM_2.5 sulfate and ammonium varied with fuel composition and dilution ratio but not residence time. For example, ammonium was only enriched in diluted acidic aerosol samples. A comparison of the PM_2.5 emission profiles for each of the fuels tested underscores how differences in PM_2.5 composition are related to the fuel ash composition. When sampling after the bag house, the particle size distribution and total particle number emission rate did not depend on residence time and dilution ratio because of the much lower particle number concentrations in diluted sample and the absence of nucleation. These results provide new insight into the effects of dilution sampling on measurements of fine particle emissions, providing important data for the ongoing effort of the EPA and ASTM to define a standardized dilution sampling methodology for characterizing emissions from stationary combustion sources.     

Tailpipe emission characteristics of PM2.5 from selected on-road China III and China IV diesel vehicles

Eighteen China III and IV diesel vehicles, including light-duty diesel trucks (LDDTs), medium-duty diesel trucks (MDDTs), heavy-duty diesel trucks (HDDTs) and buses, were tested with real-world measurements using a portable emission measurement system (PEMS). The emission factors (EFs), chemical components and surface morphology of emitted particles from these vehicles were characterized. Measured features included organic carbon (OC), elemental carbon (EC), water soluble ions (WSIs) and trace elements of PM_2.5. The modelling system MOtor Vehicle Emission Simulator (MOVES) was also employed to estimate the PM_2.5 EFs from these vehicles. Carbonaceous content made up 35.8–110.8% of PM_2.5, the largest contribution of all the determined chemical components; WSIs and elements accounted for less than 10%. The average PM_2.5 EFs of MDDTs and HDDTs were 0.389 g·km^?1 and 0.115 g·km^?1, respectively, approximately one order of magnitude higher than that of LDDTs. The PM_2.5 EFs of China III buses were much lower than those of China III MDDTs and HDDTs, indicating that the inspection maintenance program (I/M) system was carried out effectively on public diesel vehicles. Moreover, the chemical composition of 9.2–56.2% of the PM_2.5 mass emitted from China IV diesel trucks could not be identified in the present study. It was possible this unidentified mass was particle bound water, but this hypothesis should be confirmed with further measurements. The SEM images of PM_2.5 samples presented a loose floc structure. In addition, the trends of variation of estimated PM_2.5 EFs derived from the MOVES simulation were essentially consistent with those of tested values.

Copyright © 2018 American Association for Aerosol Research     

Reconstructing Primary and Secondary Components of PM2.5 Composition for an Urban Atmosphere

Total 360 samples (of 8 h each) of PM_2.5 were collected from six sampling sites for summer and winter seasons in Kanpur city, India. The collected PM_2.5 mass was subjected to chemical speciation for: (1) ionic species (NH⁺ ₄, SO^2– ₄, NO^– ₃, and Cl^–), (2) carbon contents (EC and OC), and (3) elemental contents (Ca, Mg, Na, K, Al, Si, Fe, Ti, Mn, V, Cr, Ni, Zn, Cd, Pb, Cu, As, and Se). Primary and secondary components of PM_2.5 were assessed from speciation results. The influence of marine source to PM_2.5 was negligible, whereas the contribution of crustal dust was significant (10% in summer and 7% in winter). A mass reconstruction approach for PM_2.5 could distinctly establish primary and secondary components of measured PM_2.5 as: (1) Primary component (27% in summer and 24% in winter): crustal, elemental carbon, and organic mass, (2) Secondary component (45% in summer and 50% in winter): inorganic and organic mass, and (3) others: unidentified mass (27% in summer and 26% in winter). The secondary inorganic component was about 34% in summer (NH⁺ ₄: 9%; SO^2– ₄: 16%; NO^– ₃: 9%) and 32% in winter (NH⁺ ₄: 8%; SO²⁺ ₄: 13%; NO^– ₃: 11%). The secondary organic component was 12% in summer and 18% in winter. In conclusion, secondary aerosol formation (inorganic and organic) accounted for significant mass of PM _2.5 (about 50%) and any particulate control strategy should also include control of primary precursor gases.     

Evaluation of portable dilution system for aerosol measurement from stationary and mobile combustion sources

This study presents the emission factor of PM_2.5, elemental carbon (EC), organic carbon (OC), and water-soluble ions for biomass-fired-induced downdraft gasifier and light duty diesel vehicle (LDDV). A portable dilution system (PDS) developed for on-field measurement of aerosol and their precursors from combustion sources were used for quenching of aerosol at near-atmospheric condition before collection on filters. PDS consists of a heated duct and particle sampling probe, dilution tunnel, zero air assembly, and a power supply unit. PDS was evaluated under controlled conditions in laboratory for gasifier cookstove and LDDV over wide range of dilution ratios to understand the effect of dilution on mixing, particle formation, and loss. The invariability in CO₂, recorded along the length and at radial distances of cross-section of dilution tunnel, confirmed the rapid and homogenous mixing inside the dilution tunnel. The particle loss and nucleation inside the dilution tunnel accounted for 6–20% at different dilution ratios (30:1–90:1). PM_2.5 emission factors for wood combustion in gasifier cookstove showed mild decrease (13%) with increasing dilution ratio from 75:1 to 108:1. However, a considerable decrease of 37% (221–139 mg km^?1) was observed for LDDV with increase in dilution ratio from 39:1 to 144:1. Similar decrease in particulate organic carbon emission rates were observed indicating scarcity of sorptive organics, and insufficient residence time for condensation limited the particle formation from vapor phase organic compounds at high dilution ratios.

© 2016 American Association for Aerosol Research     

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

The chemical composition of PM_2.5 was investigated at four sites (Rubidoux, CA, Phoenix, AZ, Philadelphia, PA, and Research Triangle Park, NC) in January and February of 1999. Three samplers were used to determine both the overall mass and the chemical composition of the aerosol. Teflon filters were weighed for total mass. Ions were analyzed using ion chromatography. Elements were determined using X-ray fluorescence. Organic and elemental carbon were measured using a thermo-optical method. At all of the sites, reconstructed mass was observed to be greater than or equal to the measured mass. Good ionic balance was found for ammonium, nitrate, and sulfate at each of the sites. Overall, the chemical composition of the aerosol for each site was in good agreement with the expected composition based upon previous studies, with the exception of relatively high nitrate contribution to the total mass at Philadelphia. Good agreement was found between the predicted amount of sulfate by XRF analysis of sulfur and the sulfate measured by ion chromatography. As expected, sulfate was a more important contributor to the total mass at the East Coast sites. Nitrate contributed more to the total mass at the West Coast sites and was an important factor in the highest observed mass concentration at Rubidoux. Teflon filters appear to lose nitrate to a greater extent than heat-treated quartz fiber filters. Organic carbon was also found to be the largest part of the aerosol mass on minimum days for all sites and a significant portion of the mass on other days with 25-50% of the total mass at all of the sites. At three of the sites, organic carbon (OC) collected on denuded filters was less than that found on nondenuded samples, indicating an absorptive artifact on the quartz fiber filters. It was also found that the crustal component to PM_2.5 was highest at Phoenix. PM_2.5 was also found to contribute significantly to the PM₁₀ particle mass at all the sites.     

Characterization of Fine Particulate Emissions from Casting Processes

Fine particle (PM_2.5) emission rates and compositions from gray iron metal casting foundry were characterized for No-Bake molds poured at the Research Foundry located at Technikon, LLC (McClellan, CA). For each mold, PM_2.5 was collected for chemical analysis, and particle size distributions were measured by an Electrical Low Pressure Impactor (ELPI) to understand PM emissions during different part of the casting process. Molds prepared with phenolic urethane binders were poured with Class 30 gray cast iron at 1,427–1,480°C. PM_2.5 was collected from the pouring, cooling, and shakeout processes for each mold. Most of the PM_2.5 mass emitted from these processes was composed of carbonaceous compounds, including 37–67% organic carbon (OC) and 17–30% elemental carbon (EC). Oxides of aluminum (Al), silicon (Si), calcium (Ca), and iron (Fe) constituted 8–20% of PM_2.5 mass, and trace elements (e.g., K, Ti, Mn, Cu, Zn, and Pb) contributed 3–6%. Chemical abundances in PM were different between pouring and shakeout for each discrete mold. PM_2.5 mass emissions from pouring were 15–25% of the total from each discrete mold. Ultrafine particles (< 0.1 μm) contributed less than 1% of PM_2.5 mass, but nearly all of the particle numbers. Different mechanisms for pouring and shakeout result in variations in chemical abundances and particle size distributions. The highest PM_2.5 mass and number concentrations were observed when shakeout started. PM_2.5 size distributions in mass concentration during shakeout contained particles in the tail of coarse particles (1.6–2.5 μm) and a vapor condensation mode (0.65–1.6 μm). Flame conditions, vaporization, thermal decomposition of organic materials, and the variability of mold breakup during shakeout affect PM emission rates. A detailed chemical speciation for size-segregated PM samples at different process points needs to be conducted at full-scale foundries to obtain emission factors and source profiles applicable to emission inventories, source receptor modeling, and implementation of emission standards.     

Twenty Four-Hour PC-BOSS Air-Monitoring Results from the NETL Fine-Particulate Sampling Site in Pittsburgh,Pennsylvania: An Annual Perspective

The concentration and composition of PM _2.5 from May to September of 2000 and monthly trends in ambient fine-particulate material concentrations from October 1999 through December 2000 at the National Energy Technology Laboratory's airmonitoring site in Pittsburgh are reported. Twenty four-hour integrated samples were collected using the Particle Concentrator-Brigham Young University Organic Sampling System (PC-BOSS), a multichannel integrated diffusion denuder sampler designed for routine determination of the chemical composition of ambient particulate matter. The fine-particulate pollutants determined were sulfate estimated as ammonium sulfate, nonvolatile organic material, semivolatile organic material lost from particles during sampling, elemental carbon, nitrate estimated as ammonium nitrate, including ammonium nitrate lost from particles during sampling and elemental content determined by PIXE (for a limited number of samples). Episodes with elevated sulfate and organic material (both semivolatile and nonvolatile) concentrations were seen throughout this period. For the purpose of this discussion, an episode was defined as all times when 3 h average TEOM monitor PM _2.5 concentrations exceeded 30 μg/m³. The use of estimated back-trajectories indicated that during the periods for which these elevated concentrations were observed, pollutants were transported predominantly from the Southwest from the Ohio River Valley to the sampling site. For days when fine particulate episodes occurred, back-trajectory computations were derived for time intervals for which PM _2.5 TEOM concentrations exceeded 30 μg/m³. However, for nonepisode days, back trajectories were computed over a 24 h period. Average PC-BOSS–constructed PM _2.5 concentration (including semivolatile components lost from particles during sampling) for the period from October 1999 through December 2000 was 19 μg/m ³ , excluding crustal material concentration.