Nonlinear regression adjustments of multiple continuous monitoring methods produce effective characterization of short-term fine particulate matter

This study comprehensively characterizes hourly fine particulate matter (PM(2.5)) concentrations measured via a tapered element oscillating microbalance (TEOM), beta-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 beta-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.     

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.     

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.     

Collocated comparisons of continuous and filter-based PM2.5 measurements at Fort McMurray,Alberta, Canada

Collocated comparisons for three PM_2.5 monitors were conducted from June 2011 to May 2013 at an air monitoring station in the residential area of Fort McMurray, Alberta, Canada, a city located in the Athabasca Oil Sands Region. Extremely cold winters (down to approximately ?40°C) coupled with low PM_2.5 concentrations present a challenge for continuous measurements. Both the tapered element oscillating microbalance (TEOM), operated at 40°C (i.e., TEOM₄₀), and Synchronized Hybrid Ambient Real-time Particulate (SHARP, a Federal Equivalent Method [FEM]), were compared with a Partisol PM_2.5 U.S. Federal Reference Method (FRM) sampler. While hourly TEOM₄₀ PM_2.5 were consistently ~20–50% lower than that of SHARP, no statistically significant differences were found between the 24-hr averages for FRM and SHARP. Orthogonal regression (OR) equations derived from FRM and TEOM₄₀ were used to adjust the TEOM₄₀ (i.e., TEOM_adj) and improve its agreement with FRM, particularly for the cold season. The 12-year-long hourly TEOM_adj measurements from 1999 to 2011 based on the OR equations between SHARP and TEOM₄₀ were derived from the 2-year (2011–2013) collocated measurements. The trend analysis combining both TEOM_adj and SHARP measurements showed a statistically significant decrease in PM_2.5 concentrations with a seasonal slope of ?0.15 μg m^?3 yr^?1 from 1999 to 2014.Implications: Consistency in PM_2.5 measurements are needed for trend analysis. Collocated comparison among the three PM_2.5 monitors demonstrated the difference between FRM and TEOM, as well as between SHARP and TEOM. The orthogonal regressions equations can be applied to correct historical TEOM data to examine long-term trends within the network.     

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.     

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.     

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.     

Comparison of Real-Time Instruments Used To Monitor Airborne Particulate Matter

ABSTRACT

Measurements collected using five real-time continuous airborne particle monitors were compared to measurements made using reference filter-based samplers at Bakers-field, CA, between December 2, 1998, and January 31, 1999. The purpose of this analysis was to evaluate the suitability of each instrument for use in a real-time continuous monitoring network designed to measure the mass of airborne particles with an aerodynamic diam less than 2.5 μm (PM_2.5) under wintertime conditions in the southern San Joaquin Valley. Measurements of airborne particulate mass made with a beta attenuation monitor (BAM), an integrating nephelometer, and a continuous aerosol mass monitor (CAMM) were found to correlate well with reference measurements made with a filter-based sampler. A Dusttrak aerosol sampler overestimated airborne particle concentrations by a factor of ~3 throughout the study. Measurements of airborne particulate matter made with a tapered element oscillating microbalance (TEOM) were found to be lower than the reference filter-based measurements by an amount approximately equal to the concentration of NH₄NO₃ observed to be present in the airborne particles. The performance of the Dusttrak sampler and the integrating nephelometer was affected by the size distribution of airborne particulate matter. The performance of the BAM, the integrating nephelometer, the CAMM, the Dusttrak sampler, and the TEOM was not strongly affected by temperature, relative humidity, wind speed, or wind direction within the range of conditions encountered in the current study. Based on instrument performance, the BAM, the integrating nephelometer, and the CAMM appear to be suitable candidates for deployment in a real-time continuous PM_2.5 monitoring network in central California for the range of winter conditions and aerosol composition encountered during the study.     

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.     

The Influence of Human Activity Patterns on Personal PM Exposure: A Comparative Analysis of Filter-Based and Continuous Particle Measurements

ABSTRACT

Particulate matter (PM) exposure data from the U.S. Environmental Protection Agency (EPA)-sponsored 1998 Baltimore and 1999 Fresno PM exposure studies were analyzed to identify important microenvironments and activities that may lead to increased particle exposure for select elderly (>65 years old) subjects. Integrated 24-hr filter-based PM_2.5 or PM₁₀ mass measurements [using Personal Environmental Monitors(PEMs)] included personal measurements, indoor and outdoor residential measurements, and measurements at a central indoor site and a community monitoring site. A subset of the participants in each study wore passive nephelometers that continuously measured (1-min averaging time) particles ranging in size from 0.1 to ~10 um. Significant activities and locations were identified by a statistical mixed model (p < 0.01) for each study population based on the measured PM_2.5 or PM₁₀ mass and time activity data. Elevated PM concentrations were associated with traveling (car or bus), commercial locations (store, office, mall, etc.), restaurants, and working.

The modeled results were compared to continuous PM concentrations determined by the nephelometers while participants were in these locations. Overall, the nephelometer data agreed within 6% of the modeled PM_2.5 results for the Baltimore participants and within ~20% for the Fresno participants (variability was due to zero drift associated with the nephelometer). The nephelom-eter did not agree as well with the PM₁₀ mass measurements, most likely because the nephelometer optimally responds to fine particles (0.3–2 um). Approximately one-half (54 ± 31%; mean ± standard deviation from both studies) of the average daily PM_2.5 exposure occurred inside residences, where the participants spent an average of 83 ± 10% of their time. These data also showed that a significant portion of PM_2.5 exposure occurred in locations where participants spent only 4–13% of their time.     

APCA Financial Statements for FY 1979-80

The U.S. Environmental Protection Agency (EPA) has proposed a new secondary standard based on visibility in urban areas. The proposed standard will be based on light extinction, calculated from 24-hr averaged measurements. It would be desirable to base the standard on a shorter averaging time to better represent human perception of visibility. This could be accomplished by either an estimation of extinction from semicontinuous particulate matter (PM) data or direct measurement of scattering and absorption. To this end we have compared 1-hr measurements of fine plus coarse particulate scattering using a nephelometer, along with an estimate of absorption from aethalometer measurements. The study took place in Lindon, UT, during February and March 2012. The nephelometer measurements were corrected for coarse particle scattering and compared to the Filter Dynamic Measurement System (FDMS) tapered element oscillating microbalance monitor (TEOM) PM_2.5 measurements. The two measurements agreed with a mass scattering coefficient of 3.3 ± 0.3 m²/g at relative humidity below 80%. However, at higher humidity, the nephelometer gave higher scattering results due to water absorbed by ammonium nitrate and ammonium sulfate in the particles. This particle-associated water is not measured by the FDMS TEOM. The FDMS TEOM data could be corrected for this difference using appropriate IMPROVE protocols if the particle composition is known. However, a better approach may be to use a particle measurement system that allows for semicontinuous measurements but also measures particle bound water. Data are presented from a 2003 study in Rubidoux, CA, showing how this could be accomplished using a Grimm model 1100 aerosol spectrometer or comparable instrument.

Implications: Visibility is currently based on 24-hr averaged PM mass and composition. A metric that captures diurnal changes would better represent human perception. Furthermore, if the PM measurement included aerosol bound water, this would negate the need to know particulate composition and relative humidity (RH), which is currently used to estimate visibility. Methods are outlined that could accomplish both of these objectives based on use of a PM monitor that includes aerosol-bound water. It is recommended that these techniques, coupled with appropriate measurements of light scattering and absorption by aerosols, be evaluated for potential use in the visibility based secondary standard.     

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.     

A two-step approach for relating tapered element oscillating microbalance and dichotomous air sampler PM2.5 measurements

A method for transforming continuous monitoring (CM) fine particulate matter (aerodynamic diameter <2.5 μm; PM_2.5) data (i.e., by tapered element oscillating microbalance [TEOM]) obtained from the Canadian National Air Pollution Surveillance (NAPS) program to meet the data quality objective (DQO) of R² > 0.8 against the co-located federal reference method (i.e., dichotomous air sampler) is described. By using a two-step linear regression to account for the effect of the ambient temperature, 16 out of the 23 examined sites met the common model adequacy threshold of R² > 0.8. After the transformation, 20 out of the 23 examined sites met the DQO of R² > 0.7, as recommended by the U.S. Environmental Protection Agency (EPA). A combined two-step statistical approach was also examined and revealed similar results. The methods described herein show that the CM data can be successfully transformed to meet DQOs for representative sites across Canada using year-round (both summer and winter) data.

Implications:This study provides a transformation approach to correct ambient TEOM data against the federal reference method without dividing the ambient data according to warm and cold seasons. This transformation approach will significantly improve the correlation coefficient between TEOM and dichotomous air sampler data. It is possible that TEOM data at many Canadian locations can be transformed to meet the EPA data quality objective, thus making this transformation approach useful for comparisons of ambient PM data across jurisdictions.     

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.     

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.     

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%.     

Design of a Cost-Effective Weighing Facility for PM2.5 Quality Assurance

Abstract

The U.S. Environmental Protection Agency (EPA) Quality Assurance (QA) Guidance Document 2.12: Monitoring PM_2.5 in Ambient Air Using Designated Reference or Class I Equivalent Methods¹ (Document 2.12) requires conditioning of PM_2.5 filters at 20-23 °C and 30-40% relative humidity (RH) for 24 hr prior to gravimetric analysis. Variability of temperature and humidity may not exceed ±2 °C and ±5% RH during the conditioning period. The quality assurance team at EPA Region 2’s regional laboratory designed a PM_2.5 weighing facility that operates well within these strict performance requirements.

The traditional approach to meeting the performance requirements of Document 2.12 for PM_2.5 filter analysis is to build a walk-in room, with costs typically exceeding $100,000. The initial one-time capital cost for the laboratory at EPA’s Edison, NJ, facility was approximately $24,000. Annual costs [e.g., National Institute of Standards and Technology (NIST) recertifications and nitrogen replacement cylinders used for humidity control] are approximately $500. The average 24-hr variabilities in temperature and RH in the Region 2 weighing chamber are small, ±0.2 °C and ±0.8% RH, respectively. The mass detection limit for the PM_2.5 weighing system of 47-mm stretched Teflon (lab blank) filters is 6.3 μg. This facility demonstrates an effective and economical example for states and other organizations planning PM_2.5 weighing facilities.     

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.     

Impact of smoking on in-vehicle fine particle exposure during driving

Indoor smoking ban in public places can reduce secondhand smoke (SHS) exposure. However, smoking in cars and homes has continued. The purpose of this study was to assess particulate matter less than 2.5 μm (PM_2.5) concentration in moving cars with different window opening conditions. The PM_2.5 level was measured by an aerosol spectrometer inside and outside moving cars simultaneously, along with ultrafine particle (UFP) number concentration, speed, temperature and humidity inside cars. Two sport utility vehicles were used. Three different ventilation conditions were evaluated by up to 20 repeated experiments. In the pre-smoking phase, average in-vehicle PM_2.5 concentrations were 16–17 μg m^?3. Regardless of different window opening conditions, the PM_2.5 levels promptly increased when smoking occurred and decreased after cigarette was extinguished. Although only a single cigarette was smoked, the average PM_2.5 levels were 506–1307 μg m^?3 with different window opening conditions. When smoking was ceased, the average PM_2.5 levels for 15 min were several times higher than the US National Ambient Air Quality Standard of 35 μg m^?3. It took longer than 10 min to reach the level of the pre-smoking phase. Although UFP levels had a similar temporal profile of PM_2.5, the increased levels during the smoking phase were relatively small. This study demonstrated that the SHS exposure in cars with just a single cigarette being smoked could exceed the US EPA NAAQS under realistic window opening conditions. Therefore, the findings support the need for public education against smoking in cars and advocacy for a smoke-free car policy.     

The Steubenville Comprehensive Air Monitoring Program (SCAMP): Analysis of Short-Term and Episodic Variations in PM2.5 Concentrations Using Hourly Air Monitoring Data

Abstract

One-hour average ambient concentrations of particulate matter (PM) with an aerodynamic diameter <2.5 μm (PM_2.5) were determined in Steubenville, OH, between June 2000 and May 2002 with a tapered element oscillating microbalance (TEOM). Hourly average gaseous copollutant [carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen oxide (NO_x), and ozone (O₃)] concentrations and meteorological conditions also were measured. Although 75% of the 14,682 hourly PM_2.5 concentrations measured during this period were ≤17 μg/m³, concentrations >65 μg/m³ were observed 76 times. On average, PM_2.5 concentrations at Steubenville exhibited a diurnal pattern of higher early morning concentrations and lower afternoon concentrations, similar to the diurnal profiles of CO and NO_x. This pattern was highly variable; however, PM_2.5 concentrations >65 μg/m³ were never observed during the mid-afternoon between 1:00 p.m. and 5:00 p.m. EST. Twenty-two episodes centered on one or more of these elevated concentrations were identified. Five episodes occurred during the months June through August; the maximum PM_2.5 concentration during these episodes was 76.6 μg/m³. Episodes occurring during climatologically cooler months often featured higher peak concentrations (five had maximum concentrations between 95.0 and 139.6 μg/m³), and many exhibited strong covariation between PM_2.5 and CO, NO_x, or SO₂. Case studies suggested that nocturnal surface-based temperature inversions were influential in driving high nighttime concentrations of these species during several cool season episodes, which typically had dramatically lower afternoon concentrations. These findings provide insights that may be useful in the development of PM_2.5 reduction strategies for Steubenville, and suggest that studies assessing possible health effects of PM_2.5 should carefully consider exposure issues related to the intraday timing of PM_2.5 episodes, as well as the potential for toxicological interactions among PM_2.5 and primary gaseous pollutants.