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Unlabelled: The Maryland State Highway Administration (SHA) monitoring program monitored the impact of vehicular emissions on the concentrations of the fine particles smaller than 2.5 microns (PM2.5). PM2.5 concentrations were monitored in close proximity to a highway in order to determine whether traffic conditions on the roadway impact concentrations at this location. The monitoring program attempted to connect monitored concentrations with the roadway traffic exhaust or with the other sources of PM2.5. PM2.5 concentrations were collected near the Capital Beltway (I-495/I-95) in Largo, Maryland. The monitoring program was launched on May 13, 2009 and continued through the end of 2012. Two co-located monitors, one for continuous PM2.5 measurements and the other for speciation measurements, were used in this program. Meteorological and traffic information was also continuously collected at or near the monitoring site. Additionally, data from the two other monitoring locations, one at the Howard University-Beltsville, MD and one at McMillan Reservoir, DC, was used for comparison with the data collected at the SHA monitoring location. The samples collected by the speciation monitor were analyzed at the RTI and DRI Laboratories to determine the composition and the sources of the collected PM2.5 samples. Based on the apportionment analysis, the contribution of roadway sources is about 12 to 17 percent of PM2.5 at the near-road site., Implications: PM2.5 monitoring at 150 m (approximately 500 feet) from a major highway in Maryland near Washington, DC, demonstrated that roadway traffic contributes to the total PM2.5 concentration near the roadway, but the contribution at such distance is small, in the order of 12-17% of the total.

The US. EnvironmentalProtection Agency (EPA) initiated the national PM2.5 Chemical Speciation Monitoring Network (CSN) in 2000 to support evaluation of long-term trends and to better quantify the impact of sources on particulate matter (PM) concentrations in the size range below 2.5 μm aerodynamic diameter (PM2.5; fine particles). The network peaked at more than 260 sites in 2005. In response to the 1999 Regional Haze Rule and the need to better understand the regional transport of PM, EPA also augmented the long-existing Interagency Monitoring of Protected Visual Environments (IMPROVE) visibility monitoring network in 2000, adding nearly 100 additional IMPROVE sites in rural Class 1 Areas across the country. Both networks measure the major chemical components of PM2.5 using historically accepted filter-based methods. Components measured by both networks include major anions, carbonaceous material, and a series of trace elements. CSN also measures ammonium and other cations directly, whereas IMPROVE estimates ammonium assuming complete neutralization of the measured sulfate and nitrate. IMPROVE also measures chloride and nitrite. In general, the field and laboratory approaches used in the two networks are similar; however, there are numerous, often subtle differences in sampling and chemical analysis methods, shipping, and quality control practices. These could potentially affect merging the two data sets when used to understand better the impact of sources on PM concentrations and the regional nature and long-range transport of PM2zs. This paper describes, for the first time in the peer-reviewed literature, these networks as they have existed since 2000, outlines differences infield and laboratory approaches, provides a summary of the analytical parameters that address data uncertainty, and summarizes major network changes since the inception of CSN. Implications: Two long-term chemical speciation particle monitoring networks have operated simultaneously in the United States since 2001, when the EPA began regular operations of its PM2.5 Chemical Speciation Monitoring Network (IMPROVE began in 1988). These networks use similar field sampling and analytical methods, but there are numerous, often subtle differences in equipment and methodologies that can affect the results. This paper describes these networks since 20000 (inception of CSN) and their differences, and summarizes the analytical parameters that address data uncertainty, providing researches and policymakers with background information they may need (e.g., for 2018 PM2.5 designation and State Implementation Plan process; McCarthy, 2013) to assess results from each network and decide how these data sets can be mutually employed for enhanced analyses. Changes in CSN and IMPROVE that have occurred over the years also are described.

Animal feeding operations (AFOs) produce particulate matter (PM) and gaseous pollutants. Investigation of the chemical composition of PM2.5 inside and in the local vicinity of AFOs can help to understand the impact of the AFO emissions on ambient secondary PM formation. This study was conducted on a commercial egg production farm in North Carolina. Samples of PM2.5 were collected from five stations, with one located in an egg production house and the otherfour located in the vicinity ofthe farm alongfour wind directions. The major ions of NH4+, Na+, K+, SO4(2-), Cl-, and NO3- were analyzed using ion chromatography (IC). In the house, the mostly abundant ions were SO4(2-), Cl-, and K+. At ambient stations, SO4(2-), and NH4+ were the two most abundant ions. In the house, NH4+, SO4(2-), and NO3- accounted for only 10% of the PM2.5 mass; at ambient locations, NH4+, SO4(2-), and NO3- accounted for 36-41% of the PM2.5 mass. In the house, NH4+ had small seasonal variations indicating that gas- phase NH3. was not the only major force driving its gas-particle partitioning. At the ambient stations, NH4+ had the highest concentrations in summer In the house, K+, Na+, and Cl- were highly correlated with each other In ambient locations, SO4(2-) and NH4+ had a strong correlation, whereas in the house, SO4(2-) and NH4+ had a very weak correlation. Ambient temperature and solar radiation were positively correlated with NH4+ and SO4(2-). This study suggests that secondary PM formation inside the animal house was not an important source of PM2.5. In the vicinity, NH3 emissions had greater impact on PM2.5 formation.

Ammonia (NH3) is an important base gas and can react with acidic species to form atmospheric aerosols. Due to the rapid growth of poultry and swine production in the North Carolina Coastal Plain, atmospheric NH3 concentrations across the region have subsequently increased. Ammonia concentrations and inorganic particulate matter (PM) at four ambient stations in the vicinity of an egg production facility were measured for 1 year using PM2.5 speciation samplers with honeycomb denuders and ion chromatography (IC). Meanwhile, concentrations of NH3 and inorganic PM in one of the egg production houses were also simultaneously measured using a gas analyzer for NH3 and the filter pack plus IC method for inorganic PM. An equilibrium model-ISORROPIA II was applied to predict the behavior of inorganic aerosols in response to precursor gas concentrations and environmental parameters. Average ambient NH3 concentrations varied from 10.0 to 27.0 μg/m(3), and they were negatively correlated with the distances from the ambient location to the nearest egg production house exhausts. Ambient NH3 concentrations were higher in warm seasons than in cold seasons. Measured NH3 concentrations agreed well with ISORROPIA II model predictions at all sampling stations. For the ambient stations, there was a good agreement in particle phase NH4 (+) between the model simulation and observations. For the in-house station, the model simulation was applied to correct the overestimation of particle phase NH4 (+) due to gas phase NH3 breaking through the denuders. Changes in SO4 (2-), NO3 (-), and Cl(-) yield proportional changes in inorganic PM mass. Due to the abundance of NH3 gas in the vicinity area of the monitored farm, changes in NH3 concentrations had a small effect on inorganic PM mass. Aerosol equilibrium modeling may be used to assess the influence of precursor gas concentrations on inorganic PM formation when the measurements for some species are unavailable.

The U.S. Environmental Protection Agency (EPA)'s PM2.5 Chemical Speciation Network (CSN) and the Interagency Monitoring of Protected Visual Environments (IMPROVE) network use X-ray fluorescence (XRF) analysis to quantify trace elements in samples of fine particles less than 2.5 microns in aerodynamic diameter (PM2.5). Methods for calculating uncertainty values for XRF results vary considerably among laboratories and instrument makes and models. To support certain types of modeling and data analysis, uncertainty estimates are required that are consistent within and between monitoring programs, and that are independent of the laboratories that performed the analyses and the analytical instrumentation used. The goal of this work was to develop a consensus model for uncertainties associated with XRF analysis of PM2.5 filter samples. The following important components of uncertainty are included in the model described herein: variability in peak area, calibration, field sampling, and attenuation of X-ray intensity for light elements. This paper includes a detailed analysis of how attenuation uncertainties for light elements are derived. For the remaining uncertainty components included in the model, an approach and recommendations are presented to ensure that laboratories performing this type of analysis can use similar equations and parameterizations. By applying this uniform approach, it is illustrated how the uncertainties reported by the CSN and IMPROVE network laboratories can be brought into very good agreement. The proposed method is best applied at the time of data generation, but retrospective estimation of uncertainties in existing data-sets is also possible. This paper serves to document the equations used for calculating the uncertainties in speciated PM2.5 data currently being posted on EPA's Air Quality System database for the PM2.5 CSN program.

The purpose of the Enhanced Particulate Matter Surveillance Program was to provide scientifically founded information on the chemical and physical properties of dust collected over a period of approximately 1 year in Djibouti, Afghanistan (Bagram, Khowst), Qatar, United Arab Emirates, Iraq (Balad, Baghdad, Tallil, Tikrit, Taji, Al Asad), and Kuwait (northern, central, coastal, and southern regions). Three collocated low-volume particulate samplers, one each for the total suspended particulate matter, < 10 micro m in aerodynamic diameter (PM(10)) particulate matter, and < 2.5 micro m in aerodynamic diameter (PM(2.5)) particulate matter, were deployed at each of the 15 sites, operating on a '1 in 6' day sampling schedule. Trace-element analysis was performed to measure levels of potentially harmful metals, while major-element and ion-chemistry analyses provided an estimate of mineral components. Scanning electron microscopy with energy dispersive spectroscopy was used to analyze the chemical composition of small individual particles. Secondary electron images provided information on particle size and shape. This study shows the three main air pollutant types to be geological dust, smoke from burn pits, and heavy metal condensates (possibly from metals smelting and battery manufacturing facilities). Non-dust storm events resulted in elevated trace metal concentrations in Baghdad, Balad, and Taji in Iraq. Scanning-electron-microscopy secondary electron images of individual particles revealed no evidence of freshly fractured quartz grains. In all instances, quartz grains had rounded edges and mineral grains were generally coated by clay minerals and iron oxides.

The purpose of the Enhanced Particulate Matter Surveillance Program was to provide scientifically founded information on the chemical and physical properties of dust collected during a period of approximately 1 year in Djibouti, Afghanistan (Bagram, Khowst), Qatar, United Arab Emirates, Iraq (Balad, Baghdad, Tallil, Tikrit, Taji, Al Asad), and Kuwait (northern, central, coastal, and southern regions). To fully understand mineral dusts, their chemical and physical properties, as well as mineralogical inter-relationships, were accurately established. In addition to the ambient samples, bulk soil samples were collected at each of the 15 sites. In each case, approximately 1 kg of soil from the top 10 mm at a previously undisturbed area near the aerosol sampling site was collected. The samples were air-dried and sample splits taken for soil analysis. Further sample splits were sieved to separate the < 38 micro m particle fractions for mineralogical analysis. Examples of major-element and trace-element chemistry, mineralogy, and other physical properties of the 15 grab samples are presented. The purpose of the trace-element analysis was to measure levels of potentially harmful metals while the major-element and ion-chemistry analyses provided an estimate of mineral components. X-ray diffractometry provided a measure of the mineral content of the dust. Scanning electron microscopy with energy dispersive spectroscopy was used to analyze chemical composition of small individual particles. From similarities in the chemistry and mineralogy of re-suspended and ambient sample sets, it is evident that portions of the ambient dust are from local soils.

The Positive Matrix Factorization (PMF) receptor model version 1.1 was used with data from the fine particulate matter (PM2.5) Chemical Speciation Trends Network (STN) to estimate source contributions to ambient PM2.5 in a highly industrialized urban setting in the southeastern United States. Model results consistently resolved 10 factors that are interpreted as two secondary, five industrial, one motor vehicle, one road dust, and one biomass burning sources. The STN dataset is generally not corrected for field blank levels, which are significant in the case of organic carbon (OC). Estimation of primary OC using the elemental carbon (EC) tracer method applied on a seasonal basis significantly improved the model's performance. Uniform increase of input data uncertainty and exclusion of a few outlier samples (associated with high potassium) further improved the model results. However, it was found that most PMF factors did not cleanly represent single source types and instead are "contaminated" by other sources, a situation that might be improved by controlling rotational ambiguity within the model. Secondary particulate matter formed by atmospheric processes, such as sulfate and secondary OC, contribute the majority of ambient PM2.5 and exhibit strong seasonality (37 +/- 10% winter vs. 55 +/- 16% summer average). Motor vehicle emissions constitute the biggest primary PM2.5 mass contribution with almost 25 +/- 2% long-term average and winter maximum of 29 +/- 11%. PM2.5 contributions from the five identified industrial sources vary little with season and average 14 +/- 1.3%. In summary, this study demonstrates the utility of the EC tracer method to effectively blank-correct the OC concentrations in the STN dataset. In addition, examination of the effect of input uncertainty estimates on model results indicates that the estimated uncertainties currently being provided with the STN data may be somewhat lower than the levels needed for optimum modeling results.

NIST standard reference material SRM 2783 was employed to validate a high temperature, high pressure, two-stage microwave assisted acid digestion procedure using HNO3, HF and H3BO3 developed for the analysis of trace elements (including rare earths) in atmospheric fine particulate matter (PM2.5) prior to inductively coupled plasma mass spectrometry (ICP-MS). This method quantitatively solubilized Na, Mg, Al, K, Ti, V, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Rb, Sb, Cd, Cs, Ba, Pb, Th, U and several rare earth elements (REEs) (La, Ce, Pr, Nd, Gd, Dy, Er, Sm and Eu) from SRM 1648 and SRM 2783. A small amount of HF in the first stage was required to dissolve silicates necessitating the corresponding addition of H3BO3 in second stage to dissolve fluoride precipitates of Mg, La, Ce and Th. The optimized microwave dissolution-ICP-MS method detected Na, Mg, Al, K, Ti, V, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Rb, Sr, Cd, Mo, Sb, Cs, Ba, La, Ce, Pr, Nd, Sm, Gd, Pb, Th and U at trace to ultra-trace levels in ambient airborne fine particles from three sites in North Carolina. La to light lanthanide signature ratios suggested that soil and motor vehicles are the dominant REE sources in SRM 2783 and PM2.5 samples collected during this study.

The objectives of this paper are to contrast the relative variability of replicate laboratory measurements of selected chemical components of fine particulate matter (PM) with total variability from collocated measurements and to compare the magnitudes of the uncertainties determined from collocated sampler data with those currently being provided to U.S. Environmental Protection Agency (EPA)'s Air Quality System (AQS) database by RTI International (RTI). Pointwise uncertainty values are needed for modeling and data analysis and should include all the random errors affecting each data point. Total uncertainty can be decomposed into two primary components: analytical measurement uncertainty and sampling uncertainty. Analytical measurement uncertainties are relatively easy to calculate from routine quality control (QC) data. Sampling uncertainties, on the other hand, are comparatively difficult to measure. In this paper, the authors describe data from collocated samplers to provide a snapshot of whole-system uncertainty for several important chemical species. The components of uncertainty were evaluated for key species from each of the analytical methods employed by the PM2.5 Speciation Trends Network (STN) program: gravimetry, ion chromatography (IC), X-ray fluorescence (XRF), and thermal-optical analysis for organic carbon and elemental carbon. The results show that the laboratory measurement uncertainties are typically very small compared with uncertainties calculated from the differences between samples collected from collocated samplers. These differences are attributable to the "field" components uncertainty, which may include contamination and/or losses during shipping, handling, and sampling, as well as other distortions of the concentration level due to flow and sample volume variations. Uncertainties calculated from the collocation results were found to be generally similar to the uncertainties currently being loaded into EPA's AQS system, with some exceptions described below.

The use of prescribed fire is expected to increase in an effort to reduce the risk of catastrophic fire, particularly at urban/forest interfaces. Fire is a well-known source of particulate matter (PM) with particle sizes < or =2.5 microm (PM2.5), small diameter PM known to affect climate, visibility, and human health. In this work, PM2.5 was collected during seven first-entry burns (flaming and smoldering stages) and one maintenance burn of the Coconino National Forest. Samples were analyzed for organic and elemental carbon, cations (sodium, potassium [K+], and ammonium [NH4+]), anions (nitrate [NO3-] and sulfate), and 48 elements (with atomic weights between sodium and lead). The PM2.5 contained high organic carbon levels (typically >90% by mass), commonly observed ions (K+, NH4+, and NO3-) and elements (K+, chlorine, sulfur, and silicon), as well as titanium and chromium. Flaming produced higher K+ and NH4+ levels than smoldering, and the elemental signature was more complex (20 versus 7 elements). Average organic carbon x 1.4 mass fractions (+/-standard deviation) were lower during flaming (92+/-14%) than during smoldering (124+/-24%). The maintenance (grassland) burn produced lower particle concentrations, lower NH4+ and NO3- levels, and higher K and chlorine levels than did the first-entry fires.

A portable Fourier transform infrared gas analyzer with a photoacoustic detector performed reliably during pollution prevention research at two industrial facilities. It exhibited good agreement (within approximately 6%) with other analytical instruments (dispersive infrared and flame ionization) when analyte concentrations were high and relatively steady. It did not show good agreement when analyte concentrations were low (approximately 10 parts per million [ppm]) or were varying rapidly (less than 1.5 min). The precision for total acetates measurements was estimated to be approximately 40 ppm for measurements in the 0- to 700-ppm region. The precision for styrene measurements was estimated to be approximately 10 ppm for measurements in the 0- to 90-ppm region.

A portable Fourier transform infrared gas analyzer with a photoacoustic detector performed reliably during pollution prevention research at two industrial facilities. It exhibited good agreement (within approximately 6%) with other analytical instruments (dispersive infrared and flame ionization) when analyte concentrations were high and relatively steady. It did not show good agreement when analyte concentrations were low (approximately 10 parts per million [ppm]) or were varying rapidly (less than 1.5 min). The precision for total acetates measurements was estimated to be approximately 40 ppm for measurements in the 0- to 700-ppm region. The precision for styrene measurements was estimated to be approximately 10 ppm for measurements in the 0- to 90-ppm region.

Consumer products are potentially significant sources of volatile organic compounds (VOCs), which are precursors to the formation of ozone in photochemical smog. To address the problem of ozone formation in ambient air, the U.S. Environmental Protection Agency (EPA) has been involved in the development of test methods for measuring the VOC content of consumer products. This paper describes results of an interlaboratory study to estimate the repeatability (precision of analyses performed by a single laboratory) and reproducibility (precision of analyses performed by different laboratories) of the consumer products' VOC measurement method based on EPA Method 24 (for VOCs in surface coatings). The mean method repeatability was 2.7 wt% VOC, and the mean method reproducibility was 4.8 wt% VOC. Method repeatability ranged from 0.2 to 4.4 wt% VOC, and reproducibility ranged from 0.6 to 11.9 weight percent VOC. The precision of the VOC method for consumer products is similar to the precision of EPA Method 24 for surface coatings.

A test method based upon the adsorption of chloroform onto charcoal was evaluated for the collection and analysis of chloroform emissions from stationary sources. In this method, a source gas sample is pulled through adsorption tubes containing activated charcoal (to adsorb the chloroform), and chloroform is extracted from the charcoal with a hexane/methanol mixture. The extract is analyzed by gas chromatography with an electron capture detector. Procedures in Environmental Protection Agency (EPA) Method 301 were utilized to test the suitability of the method under field conditions at two sampling sites (paper mills). EPA Method 301 requires that four separate trains ("quad train") operate simultaneously in each run. During each run, two of the four sampling trains were spiked with a known amount of gaseous chloroform. The quad train sampling was performed six or more times. In the first field test, the stack emissions of chloroform were approximately 300 ppm, the mean spike recovery was 82%, the precision of the method for unspiked samples was within 5%, and the sampling bias was -43 ppm. Modifications were made to the sampling method and the spike gas introduction system. The revised method was then tested at a second field site which had chloroform emissions of approximately 220 ppm. The mean spike recovery improved to 95%, the unspiked sample precision was within 5%, and the sampling bias improved to -8.5 ppm.

Title III of the 1990 Clean Air Act Amendments designated methanol as a pollutant to be regulated. The U.S. Environmental Protection Agency (EPA), through a contract with Research Triangle Institute, has developed a method for measuring methanol emissions from stationary sources. The methanol sampling train (MST) consists of a glass-lined heated probe, two condensate knockout traps, and three sorbent cartridges packed with Anasorb 747. Samples are desorbed with a 1:1 mixture of carbon disulfide (CS2) and N,N-dimethylformamide (DMF). Condensate water and CS2/ DMF samples are analyzed by gas chromatography with flame ionization detection. The MST has a practical quantitation limit of approximately 3 ppm for a 20-L sample. Samples were shown to be stable for at least two weeks after collection. Field tests of the MST and the National Council of the Paper Industry for Air and Stream Improvement (NCASI) methanol sampling method were conducted at two pulp and paper mills. Sampling and analysis procedures followed EPA Method 301 requirements. The sampling location for the first field test was the inlet vent to a softwood bleach plant scrubber, where the methanol concentration was approximately 30 ppm. The mean recovery of spike was 108.3% for the MST method and 81.6% for the NCASI method. Although neither method showed significant bias at the 95% confidence level, the between-methods bias was significantly different. A second field test was conducted at a vent from a black liquor oxidation tank where the methanol concentration was approximately 350 ppm. Mean spike recoveries were 96.6 and 94.2% for the MST and NCASI methods, respectively. The biases of the two methods and the between-methods bias were not significantly different for the second field test.

A quality assurance program was developed for two grantee laboratories studying the herbicides atrazine and linuron in Chesapeake Bay water. Proposed methodologies were evaluated by performance and system audits. The objectives of the quality assurance program and the results of the audit program are discussed.

Regulation to control air emissions of toxic organic compounds require the collection and analysis of effluent gas from low level sources such as hazardous waste incinerators. The standard SW-846 Method specifies the use of Tenax and Tenax/charcoal adsorbent traps for collection of volatile organics from incinerators. This study evaluates passivated stainless steel canisters as an alternative to adsorbent traps to eliminate some of the problems associated with adsorbent sampling. Initially the stability of 18 nonpolar, volatile organic compounds was determined in Summa-treated stainless steel canisters with greater than 100 ppmv HCl and saturated with water vapor. All 18 components were stable for a two-week period; however, an interference caused a 10-fold increase in the FID response of trichloroethylene, toluene, and chlorobenzene. No interference of the ECD response was found for any of the 11 compounds detected with the ECD including trichloroethylene. A pilot scale incinerator was sampled using canisters, and the destruction efficiency of 1,1,1-trichloroethane was determined at a concentration of less than 0.5 ppbv while determining 1,1-dichloroethylene, the major product of incomplete combustion, at a concentration of 8000 ppbv from the same sample.