Human Exposure to Sulfates from Coal-Fired Power Plants

Abstract

Increased interest in the health effects of ambient par–ticulate mass (PM) has focused attention on the evaluation of existing mass measurement methodologies and the definition of PM in ambient air. The Rupprecht and Patashnick Tapered Element Oscillating MicroBalance (TEOM^®) method for PM is compared with time–integrated gravimetric (manual) PM methods in large urban areas during different seasons. Comparisons are conducted for both PM₁₀ and PM_2.5 concentrations.

In urban areas, a substantial fraction of ambient PM can be semi–volatile material. A larger fraction of this component of PM₁₀ may be lost from the TEOM–heated filter than the Federal Reference Method (FRM). The observed relationship between TEOM and FRM methods varied widely among sites and seasons. In East Coast urban areas during the summer, the methods were highly correlated with good agreement. In the winter, correlation was somewhat lower, with TEOM PM concentrations generally lower than the FRM. Rubidoux, CA, and two Mexican sites (Tlalnepantla and Merced) had the highest levels of PM₁₀ and the largest difference between TEOM and manual methods.

PM_2.5 data from collocation of 24–hour manual samples with the TEOM are also presented. As most of the semi–volatile PM is in the fine fraction, differences between these methods are larger for PM_2.5 than for PM₁₀.     

Improving the correlations of ambient tapered element oscillating microbalance PM2.5 data and SHARP 5030 Federal Equivalent Method in Ontario: A multiple linear regression analysis

Tapered element oscillating microbalances equipped with sample equilibration system (TEOM-SES) used by the province of Ontario for the ambient monitoring of PM_2.5 (particulate matter with an aerodynamic diameter ≤2.5 µm) in its air quality index (AQI) network were collocated with the Synchronized Hybrid Ambient Real-time Particulate monitor (SHARP 5030) at two monitoring sites for a period spanning approximately 2 years to determine the similarities and differences between the measurement outputs of both instrumental systems. Due mainly to mass loss observed with the TEOM-SES in cooler months, the province has recently switched its PM_2.5 instrumentation at all stations in its monitoring network from the TEOM-SES to the SHARP 5030, which has the U.S. Environmental Protection Agency (EPA) Federal Equivalent Method (FEM) Class III designation. Thus, it has become imperative to develop corrections for historical and future TEOM measurements for the purpose of making them more agreeable to the new FEM method. This work details the authors’ multiple linear regression analyses (MLRAs) of particulate matter data from both instrumental monitors, with the inclusion of operational parameters of physicochemical relevance for both cases of transformations of historical TEOM and TEOM measurements to be made in the future. For historical TEOM data, it was observed that the transformations only benefited winter and fall months. Furthermore, comparisons of the transformed historical TEOM data with PM_2.5 concentrations determined from the Federal Reference Method (FRM) sampler at seven locations within the province showed marked improvements over the observed TEOM-FRM comparisons.

Implications:This work provides a path to correcting the historically observed underreporting of particulate mass in winter and fall in Ontario by making the TEOM-based continuous data resemble the new FEM outputs (in this case, more SHARP-like). It is possible that the transformation of mainly winter TEOM data as detailed in this work may potentially lead to revisions in historical annual composite mean PM_2.5 concentrations and total annual number of days PM_2.5 exceeded the Canada-wide Standard (CWS) metric across the province.     

Long-Term Field Characterization of Tapered Element Oscillating Microbalance and Modified Tapered Element Oscillating Microbalance Samplers in Urban and Rural New York State Locations

Abstract

Long-term field comparisons of continuous and integrated filter measurements of mass concentrations of par-ticulate matter (PM) with an aerodynamic diameter less than or equal to 2.5 μm (PM_2.5) were performed at rural and urban sites in New York State. Two versions of the continuous tapered element oscillating microbalance (TEOM) mass monitor are deployed at each site, in addition to Federal Reference Method filter samplers. Data are grouped into monthly averages to retain and demonstrate seasonal differences. Strong seasonal dependence is observed—the TEOM monitors with the heated sensors are biased systematically low with respect to the Federal Reference Method measurements during the cold season. For the rural site, the average bias for the sample equilibration system (SES)-equipped and standard TEOM monitors is 14 and 24%, respectively. At this location, the TEOM monitor measurements were biased low for all 34 months. For the urban site, the average bias for the SES and standard TEOM monitors is 8 and 18%, respectively. At this location, the TEOM monitor measurements are as likely to be biased high as low during the warm-season months. The hour averaged data from the two versions of the TEOM monitor are also compared, and also indicate that the SES-equipped version of the TEOM monitor captures 7-11% more PM_2.5 mass at these locations.     

A Simple Methodology for the Determination of Back Trajectories

Abstract

This study comprehensively characterizes hourly fine particulate matter (PM_2.5) concentrations measured via a tapered element oscillating microbalance (TEOM), β-gauge, and nephelometer from four different monitoring sites in U.S. Environment Protection Agency (EPA) Region 5 (in U.S. states Illinois, Michigan, and Wisconsin) and compares them to the Federal Reference Method (FRM). Hourly characterization uses time series and autocorrelation. Hourly data are compared with FRM by averaging across 24-hr sampling periods and modeling against respective daily FRM concentrations. Modeling uses traditional two-variable linear least-squares regression as well as innovative nonlinear regression involving additional meteorological variables such as temperature and humidity. The TEOM shows a relationship with season and temperature, linear correlation as low as 0.7924 and nonlinear model correlation as high as 0.9370 when modeled with temperature. The β-gauge shows no relationship with season or meteorological variables. It exhibits a linear correlation as low as 0.8505 with the FRM and a nonlinear model correlation as high as 0.9339 when modeled with humidity. The nephelometer shows no relationship with season or temperature but a strong relationship with humidity is observed. A linear correlation as low as 0.3050 and a nonlinear model correlation as high as 0.9508 is observed when modeled with humidity. Nonlinear models have higher correlation than linear models applied to the same dataset. This correlation difference is not always substantial, which may introduce a tradeoff between simplicity of model and degree of statistical association. This project shows that continuous monitor technology produces valid PM_2.5 characterization, with at least partial accounting for variations in concentration from gravimetric reference monitors once appropriate nonlinear adjustments are applied. Although only one regression technically meets new EPA National Ambient Air Quality Standards (NAAQS) Federal Equivalent Method (FEM) correlation coefficient criteria, several others are extremely close, showing optimistic potential for use of this nonlinear adjustment model in garnering EPA NAAQS FEM approval for continuous PM_2.5 sampling methods.     

Air Quality Measurements from the Fresno Supersite

ABSTRACT

The Fresno Supersite intends to 1) evaluate non-routine monitoring methods, establishing their comparability with existing methods and their applicability to air quality planning, exposure assessment, and health effects studies; 2) provide a better understanding of aerosol characteristics, behavior, and sources to assist regulatory agencies in developing standards and strategies that protect public health; and 3) support studies that evaluate relationships between aerosol properties, co-factors, and observed health end-points. Supersite observables include in-situ, continuous, short-duration measurements of 1) PM_2.5, PM₁₀, and coarse (PM₁₀ minus PM_2.5) mass; 2) PM_2.5 SO₄ ^-2, NO₃ ^-, carbon, light absorption, and light extinction; 3) numbers of particles in discrete size bins ranging from 0.01 to ~10μm; 4) criteria pollutant gases (O₃, CO, NO_x); 5) reactive gases (NO₂, NO_y, HNO₃, peroxyacetyl nitrate [PAN], NH₃); and 6) single particle characterization by time-of-flight mass spectrometry. Field sampling and laboratory analysis are applied for gaseous and particulate organic compounds (light hydrocarbons, heavy hydrocarbons, carbonyls, polycyclic aromatic hydrocarbons [PAH], and other semi-volatiles), and PM_2.5 mass, elements, ions, and carbon. Observables common to other Supersites are 1) daily PM_2.5 24-hr average mass with Federal Reference Method (FRM) samplers; 2) continuous hourly and 5-min average PM_2.5 and PM₁₀ mass with beta attenuation monitors (BAM) and tapered element oscillating microbalances (TEOM); 3) PM_2.5 chemical specia-tion with a U.S. Environmental Protection Agency (EPA) speciation monitor and protocol; 4) coarse particle mass by dichotomous sampler and difference between PM₁₀ and PM_2.5 BAM and TEOM measurements; 5) coarse particle chemical composition; and 6) high sensitivity and time resolution scalar and vector wind speed, wind direction, temperature, relative humidity, barometric pressure, and solar radiation. The Fresno Supersite is coordinated with health and toxicological studies that will use these data in establishing relationships with asthma, other respiratory disease, and cardiovascular changes in human and animal subjects.     

Effects of Equilibration Temperature on PM10 Concentrations from the TEOM Method in the Lower Fraser Valley

ABSTRACT

This study investigated the effect of equilibration temperature on PM₁₀ concentrations from the tapered element oscillating microbalance (TEOM) method by operating collocated TEOM monitors at different equilibration temperatures in an airshed (the Lower Fraser Valley, British Columbia). This airshed contained an abundance of par-ticulate semivolatile material (PSVM). For the period when three collocated TEOM monitors were operated, the PM₁₀ from the monitor at an equilibration temperature of 30 ° C was 2.5 μ g/m³ (22%) and 1.7 (17%) μ g/m³ higher, on average, than the PM₁₀ from monitors at 50 and 40 ° C, respectively, and the differences were proportional to the ambient PM₁₀ loading. Greater volatilization of PSVM in the TEOM monitors at higher equilibration temperatures may have been a cause of the differences.     

Development of a Sample Equilibration System for the TEOM Continuous PM Monitor

ABSTRACT

In recent years, scientific discussion has included the influence of thermodynamic conditions (e.g., temperature, relative humidity, and filter face velocity) on PM retention efficiency of filter-based samplers and monitors. Method-associated thermodynamic conditions can, in some instances, dramatically influence the presence of particle-bound water and other light-molecular-weight chemical components such as particulate nitrates and certain organic compounds. The measurement of fine particle mass presents a new challenge for all PM measurement methods, since a relatively greater fraction of the mass is semi-volatile.

The tapered element oscillating microbalance (TEOM) continuous PM monitor is a U.S. Environmental Protection Agency (EPA) PM₁₀ equivalent method (EQPM-1090-079). Several hundred of these monitors are deployed throughout the United States. The TEOM monitor has the unique characteristic of providing direct PM mass measurement without the calibration uncertainty inherent in mass surrogate methods. In addition, it provides high-precision, near-real-time continuous data automatically. Much attention has been given to semi-volatile species retention of the TEOM method.

While using this monitor, it is desirable to maintain as low an operating temperature as practical and to remove unwanted particle-bound water. A new sample equilibration system (SES) has been developed to allow conditioning of the PM sample stream to a lower humidity and temperature level. The SES incorporates a special low-particle-loss Nafion dryer. This paper discusses the configuration and theory of the SES. Performance results include high time-resolved PM_2.5 data comparison between a 30 °C sample stream TEOM monitor with SES and a standard 50 °C TEOM monitor. In addition, 24-hr integrated data are compared with data collected using an EPA PM_2.5 Federal Reference Method (FRM)-type sampler. The SES is a significant development because it can be applied easily to existing TEOM monitors.     

Errors in coarse particulate matter mass concentrations and spatiotemporal characteristics when using subtraction estimation methods

In studies of coarse particulate matter (PM_10-2.5), mass concentrations are often estimated through the subtraction of PM_2.5 from collocated PM₁₀ tapered element oscillating microbalance (TEOM) measurements. Though all field instruments have yet to be updated, the Filter Dynamic Measurement System (FDMS) was introduced to account for the loss of semivolatile material from heated TEOM filters. To assess errors in PM_10-2.5 estimation when using the possible combinations of PM₁₀ and PM_2.5 TEOM units with and without FDMS, data from three monitoring sites of the Colorado Coarse Rural–Urban Sources and Health (CCRUSH) study were used to simulate four possible subtraction methods for estimating PM_10-2.5 mass concentrations. Assuming all mass is accounted for using collocated TEOMs with FDMS, the three other subtraction methods were assessed for biases in absolute mass concentration, temporal variability, spatial correlation, and homogeneity. Results show collocated units without FDMS closely estimate actual PM_10-2.5 mass and spatial characteristics due to the very low semivolatile PM_10-2.5 concentrations in Colorado. Estimation using either a PM_2.5 or PM₁₀ monitor without FDMS introduced absolute biases of 2.4 µg/m³ (25%) to –2.3 µg/m³ (–24%), respectively. Such errors are directly related to the unmeasured semivolatile mass and alter measures of spatiotemporal variability and homogeneity, all of which have implications for the regulatory and epidemiology communities concerned about PM_10-2.5. Two monitoring sites operated by the state of Colorado were considered for inclusion in the CCRUSH acute health effects study, but concentrations were biased due to sampling with an FDMS-equipped PM_2.5 TEOM and PM₁₀ TEOM not corrected for semivolatile mass loss. A regression-based model was developed for removing the error in these measurements by estimating the semivolatile concentration of PM_2.5 from total PM_2.5 concentrations. By estimating nonvolatile PM_2.5 concentrations from this relationship, PM_10-2.5 was calculated as the difference between nonvolatile PM₁₀ and PM_2.5 concentrations.

Implications: Errors in the estimation of PM_10-2.5 concentrations using subtraction methods were shown to be related to the unmeasured semivolatile mass when using certain combinations of TEOM instruments. For the northeastern Colorado region, the absolute bias associated with this error significantly affects mean and 95th percentile values, which would affect assessment of compliance if PM_10-2.5 is regulated in the future. Estimating PM_10-2.5 mass concentrations using nonvolatile mass concentrations from collocated PM₁₀ and PM_2.5 TEOM monitors closely estimates the total PM_10-2.5 mass concentrations. A corrective model that removes the described error was developed and applied to data from two sites in Denver.

Supplemental Materials: Supplemental materials are available for this paper. Go to the publisher's online edition of the Journal of the Air & Waste Management Association.     

Characterization and contribution to PM2.5 of semi-volatile aerosols in Paris (France)

Collocated PM_2.5 measurements using a conventional R&P TEOM (model 1400a) and a TEOM-FDMS were performed at a Paris urban background site during winter/summer field experiments. Results showed that conventional TEOM underestimates PM_2.5 mass concentrations by about 50% in winter and 35% in summer. They also confirmed that this negative sampling artifact, due to the volatilization of semi-volatile material (SVM) inside the instrument, cannot be accurately accommodated by a single correction factor because of SVM routine fluctuations. A basic filter-based investigation of the SVM chemical composition also indicated that SVM, measured by the TEOM–FDMS, is mainly formed by ammonium nitrate in winter while significant contributions of semi-volatile organic matter were observed in summer. The latter species was found to possibly account for more than 50% of secondary organic aerosol formed during summer afternoons. These findings call for more investigation of the SVM chemical composition, particularly during the summer season, in Paris and in Europe.     

Evaluation and comparison of continuous fine particulate matter monitors for measurement of ambient aerosols

To provide a scientific basis for the selection and use of continuous monitors for exposure and/or health effects studies, and for compliance and episode measurements at strategic locations in the State of New Jersey, we evaluated the performance of seven continuous fine particulate matter (PM2.5) monitors in the present study. Gravimetric samplers, as reference methods, were collocated with realtime instruments in both laboratory and field tests. The results of intercomparison of real-time monitors showed that the two nephelometers used in this study correlated extremely well (r2 approximately 0.97), and two tapered element oscillating monitors (TEOM 1400 and TEOM filter dynamics measurement system [FDMS]) correlated well (r2 > 0.85), whereas two beta gauges displayed a weaker correlation (r2 < 0.6). During a summertime controlled (laboratory) evaluation, the measurements made with the gravimetric method correlated well with the 24-hr integrated measurements made with the real-time monitors. The SidePak nephelometer overestimated the particle concentration by a factor of approximately 3.4 compared with the gravimetric method. During a summertime field evaluation, the TEOM FDMS monitor reported approximately 30% higher mass concentration than the Federal Reference Method (FRM); and the difference could be explained by the loss of semi-volatile materials from the FRM sampler. Results also demonstrated that 24-hr average PM2.5 mass concentrations measured by beta gauges and TEOM (50 degrees C) in winter correlated well with the integrated gravimetric method. Seasonal differences were observed in the performance of the TEOM (50 degrees C) monitor in measuring the particle mass attributed to the higher semi-volatile material loss in the winter weather. In applying the realtime particulate matter monitoring data into Air Quality Index (AQI) reporting, the Conroy method and the 8-hr end-hour average method were both found to be suitable.     

Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial,California, USA

The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM_2.5 and PM₁₀ (particulate matter with aerodynamic diameters <2.5 and <10 μm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R² for converted hourly averaged Dylos mass measurements versus a PM_2.5 BAM was 0.79 and that versus a PM₁₀ BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM_2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R² = 0.35–0.81).

Implications: The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on susceptible populations, assist in the identification of air pollution hotspots, and increase community awareness of air pollution.     

Field performance of dichotomous sequential PM air samplers

For over one year, the Environmental Protection Commission of Hillsborough County (EPCHC) in Tampa, Florida, operated two dichotomous sequential particulate matter air samplers collocated with a manual Federal Reference Method (FRM) air sampler at a waterfront site on Tampa Bay. The FRM was alternately configured as a PM_2.5, then as a PM₁₀ sampler. For the dichotomous sampler measurements, daily 24-h integrated PM_2.5 and PM_10–2.5 ambient air samples were collected at a total flow rate of 16.7 l min⁻¹. A virtual impactor split the air into flow rates of 1.67 and 15.0 l min⁻¹ onto PM_10–2.5 and PM_2.5 47-mm diameter PTFE^® filters, respectively. Between the two dichotomous air samplers, the average concentration, relative bias and relative precision were 13.3 μg m⁻³, 0.02% and 5.2% for PM_2.5 concentrations (n=282), and 12.3 μg m⁻³, 3.9% and 7.7% for PM_10–2.5 concentrations (n=282). FRM measurements were alternate day 24-h integrated PM_2.5 or PM₁₀ ambient air samples collected onto 47-mm diameter PTFE^® filters at a flow rate of 16.7 l min⁻¹. Between a dichotomous and a PM_2.5 FRM air sampler, the average concentration, relative bias and relative precision were 12.4 μg m⁻³, −5.6% and 8.2% (n=43); and between a dichotomous and a PM₁₀ FRM air sampler, the average concentration, relative bias and relative precision were 25.7 μg m⁻³, −4.0% and 5.8% (n=102). The PM_2.5 concentration measurement standard errors were 0.95, 0.79 and 1.02 μg m⁻³; for PM₁₀ the standard errors were 1.06, 1.59, and 1.70 μg m⁻³ for two dichotomous and one FRM samplers, respectively, which indicate the dichotomous samplers have superior technical merit. These results reveal the potential for the dichotomous sequential air sampler to replace the combination of the PM_2.5 and PM₁₀ FRM air samplers, offering the capability of making simultaneous, self-consistent determinations of these particulate matter fractions in a routine ambient monitoring mode.     

Observations and Interpretations from the Canadian Fine Particle Monitoring Program

ABSTRACT

Canadian particle monitoring programs examining PM10, PM2.5, and particle composition have been in operation for over 10 years. Until recently, the measurements were manual/filter-based with 24-hr sample collection varying in frequency from daily to every sixth day, using GrasebyAnderson dichotomous samplers. In the past few years, these monitoring activities have been expanded to include hourly measurements using tapered element oscillating microbalances (TEOMs). This continuous monitoring program started operation focusing on PM_10, but now emphasizes PM_2.5 through the addition of more TEOMs and switching of the inlets of some of the existing units. The data from all of these measurement activities show that there are broad geographical differences and also local- to regional-scale spatial differences in mass and composition of PM2.5. Due to variations in sources, significantly different PM2.5 concentrations are not uncommon within the same city. Comparison of nearby urban and rural sites indicates that 30 and 40% of the PM_2.5 is from local urban sources in Montreal and Toronto, respectively. Hourly PM_2.5 measurements in Toronto suggest that vehicular emissions are an important contributor to urban PM_2.5. There has been a decreasing trend in urban PM_2.5, with annual average concentrations between the 1987–1990 and 1993–1995 periods decreasing by 11 to 39%, depending upon the site. The largest declines were in Montreal and Halifax, and the smallest decline was in Toronto. Comparison of 24-hr TEOM and manual dichotomous sampler PM_2.5 measurements from a site in Toronto indicates that the TEOM results in lower concentrations. The magnitude of this difference is relatively small in the warmer months, averaging about 12%. During the colder months the difference averages about 23%, but can be as large as 50%.     

Adjusting tapered element oscillating microbalance data for comparison with Federal Reference Method PM2.5 measurements in region 5

Continuous monitoring of particulate matter (PM) with a diameter less than 2.5 microm (PM2.5) is quickly gaining acceptance as an alternative means of measuring fine PM in the United States. For this project, data were taken from all monitoring sites within Region 5 that used the tapered element oscillating microbalance (TEOM) for PM2.5 and had a collocated Federal Reference Method (FRM) monitor. Scatter plots of TEOM versus FRM show that for a significant fraction of the observations, an independent factor causes the TEOM to underestimate the FRM value. This underestimation appears to increase as temperature decreases. For this analysis, a linear relationship was fit to the TEOM versus FRM data, allowing a break or knot in the relationship, modeled as a change of slope, at a site-specific temperature. To test whether the models are adequate for adjusting future measurements, models were also developed using the first year of data only, and the remaining observations were used to test the durability of the relationships. For all but one monitor in Minnesota, the models developed for each site had consistently high R2s, were predictive of future measurements, and could be used to derive "FRM-like" results from the TEOM measurements. The temperature knots fitted by the model for individual sites ranged from 12.9 to 20.6 degrees C. Data from all six sites in the state of Michigan were also combined to determine if a single model could be developed for the entire state. While the single model for the state of Michigan worked reasonably well, some of the predicted concentrations at individual sites were systematically underestimating the observed concentrations on more polluted days. The same conclusion was drawn for a Region 5-wide model. This approach was also found to work very well for six individual TEOM monitors in New York State.     

The Aerosol Research and Inhalation Epidemiology Study (ARIES): PM25 Mass and Aerosol Component Concentrations and Sampler Intercomparisons

ABSTRACT

The Aerosol Research and Inhalation Epidemiology Study (ARIES) was designed to provide high-quality measurements of PM₂₅, its components, and co-varying pollutants for an air pollution epidemiology study in Atlanta, GA.

Air pollution epidemiology studies have typically relied on available data on particle mass often collected using filter-based methods. Filter-based PM_2.5 sampling is susceptible to both positive and negative errors in the measurement of aerosol mass and particle-phase component concentrations in the undisturbed atmosphere. These biases are introduced by collection of gas-phase aerosol components on the filter media or by volatilization of particle phase components from collected particles. As part of the ARIES, we collected daily 24-hr PM_2.5 mass and speciation samples and continuous PM_2.5 data at a mixed residential-light industrial site in Atlanta. These data facilitate analysis of the effects of a wide variety of factors on sampler performance. We assess the relative importance of PM_2.5 components and consider associations and potential mechanistic linkages of PM_2.5 mass concentrations with several PM_2.5 components.

For the 12 months of validated data collected to date (August 1, 1998-July 31, 1999), the monthly average Federal Reference Method (FRM) PM_{2 5} mass always exceeded the proposed annual average standard (12-month average = 20.3 ± 9.5 ug/m³). The particulate SO₄ ^2- fraction (as (NH₄)₂SO₄) was largest in the summer and exceeded 50% of the FRM mass. The contribution of (NH₄)₂SO₄ to FRM PM_2.5 mass dropped to less than 30% in winter. Particu-late NO₃ ^- collected on a denuded nylon filter averaged 1.1 ± 0.9 ug/m³. Particle-phase organic compounds (as organic carbon × 1.4) measured on a denuded quartz filter sampler averaged 6.4 ± 3.1 ug/m³ (32% of FRM PM_{2 5} mass) with less seasonal variability than SO₄ ^2-.     

Particulate Matter in California: Part 1—Intercomparison of Several PM2.5, PM10–2.5, and PM10 Monitoring Networks

Abstract

It will be many years before the recently deployed network of fine particulate matter with an aerodynamic diameter less than 2.5 [H9262]m (PM_2.5) Federal Reference Method (FRM) samplers produces information on nonattainment areas, trends, and source impacts. However, data on PM_2.5 and its major constituents have been routinely collected in California for the past 20 years. The California Air Resources Board operated as many as 20 dichotomous (dichot) samplers for PM_2.5 and coarse PM (PM_10–2.5). The California Acid Deposition Monitoring Program (CADMP) collected 12-h-average PM_2.5 and PM₁₀ from 1988 to 1995 at ten urban and rural sites and 24-h-average PM_2.5 at five urban sites since 1995. Beginning in 1994, the Children’s Health Study collected 2-week averages of PM_2.5 in 12 communities in southern California using the Two-Week Sampler (TWS). Comparisons of collocated samples establish relationships between the dichot, CADMP, and TWS samplers and the 82-site network of PM_2.5 FRM samplers deployed since 1999 in California. PM mass data from the different monitoring programs have modest to high correlation to FRM mass data, fairly small systematic biases and negative proportional biases ranging from 7 to 22%. If the biases are taken into account, all of the programs should be considered comparable with the FRM program. Thus, historical data can be used to develop long-term PM trends in California.     

Comparison between a personal PM10 sampling head and the tapered element oscillating microbalance (TEOM) system

A new personal PM₁₀ sampling head has been developed by the Institute of Occupational Medicine (IOM), Edinburgh. The purpose of this study was to compare its performance in the field with the accepted fixed-location PM₁₀ sampler, the tapered element oscillating microbalance (TEOM). The comparisons were carried out on three separate occasions during 1997 at each of two city centre locations in the UK. On each occasion two personal IOM PM₁₀ sampling heads were located adjacent to a TEOM monitor and four successive sets of 24-h filter samples were collected. The data was compared with 24-h average TEOM concentrations, calculated as the arithmetic mean of the recorded hourly averages. There was a statistically significant linear relationship between the two types of monitor, although the concentrations from the IOM PM₁₀ samplers were consistently higher than the TEOM data. It is therefore possible to use the regression equations presented in this paper to correct ambient PM₁₀ concentrations measured by either method to equivalent values. Further research is needed to properly understand the reason for the difference between the TEOM and filter samplers.     

Estimation of Ambient PM2.5 Concentrations in Maryland and Verification by Measured Values

Abstract

In 1997, Maryland had no available ambient Federal Reference Method data on particulate matter less than 2.5 μm in aerodynamic diameter (PM_2.5), but did have annual ambient data for PM smaller than 10 μm (PM₁₀) at 24 sites. The PM₁₀ data were analyzed in conjunction with local annual and seasonal zip-code-level emission inventories and with speciated PM_2.5 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 PM_2.5 concentrations at the 24 PM₁₀ monitor sites operating from 1992 to 1996. All seasonal high concentrations were estimated to be below the 24-hr PM_2.5 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 PM_2.5 NAAQS of 15 ug/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 PM_2.5 monitor network was installed. The estimates were adequate for describing the chemical composition of the PM_2.5, forecasting compliance status with the 24-hr and annual standards, and determining the spatial variations in PM_2.5 across central Maryland.     

Development and validation of the volatile correction model for PM10 – An empirical method for adjusting TEOM measurements for their loss of volatile particulate matter

EU Directives stipulate that PM₁₀ should be measured using the gravimetric reference method as laid out in EN12341 [CEN, 1998. Air Quality – Determination of the PM₁₀ Fraction of Suspended Particulate Matter – Reference Method and Field Test Procedure to Demonstrate Reference Equivalence of Measurement Methods. European Committee for Standardisation], or an equivalent method as demonstrated using EC guidance [EC, 2005. Demonstration of Equivalence of Ambient Air Monitoring Methods. European Commission Working Group on Guidance for the Demonstration of Equivalence]. There is however a conflict between the requirement to measure PM₁₀ using the gravimetric reference method and the need for rapid public reporting, and many member states, including the UK, rely on non-gravimetric techniques to measure PM₁₀. In the UK the majority of PM₁₀ measurements are made using the Tapered Element Oscillating Microbalance (TEOM), which does not meet the equivalence criteria [Harrison, D., 2006. UK Equivalence Programme for Monitoring of Particulate Matter. Defra, London]. The implied need to upgrade or replace TEOMs with an equivalent automated measurement technique has significant cost implications. The model described in this paper was based on analysis of daily mean measurements of PM₁₀ by the Filter Dynamics Measurement System (FDMS) and the TEOM at UK sites. It uses the FDMS measurement of the volatile component of PM₁₀ (referred to here as FDMS purge) to correct for differences in the sensitivity to volatile PM₁₀ between the TEOM and the EU gravimetric reference method. The model equation for the correction of TEOM PM₁₀ measurements is: TEOM_VCM = TEOM ? 1.87 FDMS purge due to the regional homogeneity of volatile PM, the FDMS purge concentration may be measured at a site distant to the TEOM, allowing the possibility of using a single FDMS instrument to correct PM₁₀ measurements made by several TEOMs in a defined geographical area. The model was assessed against the criteria for the EC Working Group's Guidance for the Demonstration of Equivalence of Ambient Air Monitoring Methods [EC, 2005. Demonstration of Equivalence of Ambient Air Monitoring Methods. European Commission Working Group on Guidance for the Demonstration of Equivalence]. The model satisfies the equivalence criteria using remote FDMS purge measurements for distances up to 200 km (in 22 out of 23 data sets). These data provide strong evidence that the model is a viable tool for correcting measurements from TEOM instruments on the national and local government networks.     

Using Continuous PM2.5 Monitoring Data to Report an Air Quality Index

Abstract

As stated in 40 CFR 58, Appendix G (2000), statistical linear regression models can be applied to relate PM_2.5 continuous monitoring (CM) measurements with federal reference method (FRM) measurements, collocated or otherwise, for the purpose of reporting the air quality index (AQI). The CM measurements can then be transformed via the model to remove any bias relative to FRM measurements. The resulting FRM-like modeled measurements may be used to provide more timely reporting of a metropolitan statistical area’s (MSA’s) AQI.¹ Of considerable importance is the quality of the model used to relate the CM and FRM measurements. The use of a poor model could result in misleading AQI reporting in the form of incorrectly claiming either good or bad air quality.

This paper describes a measure of adequacy for deciding whether a statistical linear regression model that relates FRM and continuous PM_2.5 measurements is sufficient for use in AQI reporting. The approach is the U.S. Environmental Protection Agency’s (EPA’s) data quality objectives (DQO) process, a seven-step strategic planning approach to determine the most appropriate data type, quality, quantity, and synthesis for a given activity.² The chosen measure of model adequacy is r², the square of the correlation coefficient between FRM measurements and their modeled counterparts. The paper concludes by developing regression models that meet this desired level of adequacy for the MSAs of Greensboro/Winston-Salem/High Point, NC; and Davenport/Moline/Rock Island, IA/IL. In both cases, a log transformation of the data appeared most appropriate. For the data from the Greens-boro/Winston-Salem/High Point MSA, a simple linear regression model of the FRM and CM measurements had an r² of 0.96, based on 227 paired observations. For the data from the Davenport/Moline/Rock Island MSA, due to seasonal differences between CM and FRM measurements, the simple linear regression model had to be expanded to include a temperature dependency, resulting in an r² of 0.86, based on 214 paired observations.