Federal Reference Method Samplers Research Articles

Particulate matter annual emission factors for dairy facilities and cattle feedlots of Texas, USA

The direct emission of inhalable particulate matters (PM2.5 and PM10) from agricultural sources imposes major concern to human health. It is imperative to keep regular update of the pollutant emissions to scrutinize the sources and take necessary preventive measures. Two representative animal feeding operations, one dairy and one feedlot of Texas were selected during the year 2021 for summer and winter sampling using programmable Federal Reference Method (FRM) samplers and Texas A&M University (TAMU) designed samplers. Additionally, for quick and simple emission concentration determination, handheld particle counters were utilized parallel to the FRM and TAMU designed samplers. The air quality index showed that the PM2.5 pollutant fell into ‘Moderate’ category for about 20.93% times and 13.89% times in the dairy and the feedlot respectively. The maximum mean of daily PM10 concentration observed in the Feedlot during the summer was 1676.3 μg/m3 which can be aggravating. The correlation developed using the emission data from the FRM and handheld samplers demonstrated linear relationship and 0.66 of goodness of fit. During the summer, maximum mean PM2.5 emission factors (EF) of 0.84 kg 1000 hd−1 d−1 and 8.09 kg 1000 hd−1 d−1 were determined for the dairy and for the feedlot respectively. However, the winter and the summer PM10 EF for the dairy did not differ significantly (P > 0.05). Although there has not been enough record of PM2.5 annual EF, the current study PM10 annual EF was benchmarked with some of the previously published EFs. This investigation on the air pollutant EFs from the animal feeding operations can greatly benefit in preventing the pollution and updating the most recent EFs. However, continuous monitoring and further research are suggested to improve data quality and develop strategic management practices.

Particulate Matter Emission Factors for Dairy Facilities and Cattle Feedlots during Summertime in Texas.

Particulate matter (PM) emissions from dairies and feedlot sources require regular emission factor update. Likewise, development of simple measurement technique to accurately measure pollution concentration is warranted to limit the impact of air pollution and take necessary actions. During June of 2020, a dairy facility from central Texas and a feedlot from the Texas Panhandle region, titled as Dairy B and Feedlot C, respectively, were chosen for measurement of PM emissions in the state of Texas to represent dairy facilities and cattle feedlots PM emission rates. Four stations, each assigned with an EPA-approved Federal Reference Method (FRM) sampler, Texas A&M University (TAMU) designed sampler and handheld non-FRM AEROCET (MET One Instruments) sampler for collocation, were selected within each sampling locations. Drones were also utilized mounted with a handheld AEROCET sampler for simultaneously sampling at a certain height. PM2.5 emissions of Dairy B were all below 24-h PM2.5 standard of 35 μg m-3 as specified by National Ambient Air Quality Standards (NAAQS) even at the 98th percentile. The PM ratio between regulated PM10 to PM2.5 was determined to make an estimate of relative percentage of coarser particles to fine particles in both feedlot and the dairy representative animal facilities. The maximum mean emission factor determined using AERMOD for PM2.5 and PM10 was found to be 0.53 and 7.09 kg 1000-hd-1 d-1, respectively, for the dairy facility while 8.93 and 33.42 kg 1000-hd-1 d-1, respectively, for the feedlot. A conversion factor and correlation matrix were developed in this study to relate non-FRM sampler data from the handheld AERCET samplers with FRM samplers. Cheaper handheld samplers (AEROCETs) may play a potential role in quick and relatively instant measurement of PM emissions to initiate necessary preventive actions to control PM emission from dairy facility and feedlot sources.

On the concentration differences between PM2.5 FEM monitors and FRM samplers

BAM-1020 and TEOM-FDMS have undergone rigorous testing and analysis protocols to become the Federal Equivalent Method (FEM) monitors and serve as reliable near real-time monitors for compliance with the National Ambient Air Quality Standards and references for low-cost PM2.5 sensor calibration. However, differences between the FEM and FRM (Federal Reference Method) data still exist, which cause inconsistency in PM2.5 measurements. This study carried out the field tests across five geographically diverse stations in different seasons in Taiwan with 265 daily samples collected by the collocated BAM-1020 and TEOM-FDMS and the FRM sampler and found that the biases between the FEM and FRM values increased with the decreasing PM2.5 concentrations and varied with ambient conditions. The measurement uncertainties exist in the BAM-1020 were mainly due to the aerosol water content, while the TEOM-FDMS always over-measured PM2.5 compared to the FRM sampler since it corrects for the evaporation loss of semi-volatile particle materials. To reduce the biases between the FEM monitors and FRM samplers, empirical equations based on PM2.5 concentrations (μg m−3), temperature (oC), and relative humidity (%) were derived to convert the FEM data to the FRM data. After correction, the mean normalized biases were decreased from +1.67 ± 12.43% to +0.63 ± 8.75% for the BAM-1020 and from +13.86 ± 14.50% to −0.85 ± 9.0% for the TEOM-FDMS. Also, the same empirical equation was used to convert the FRM PM2.5 values to the “true” or “actual” PM2.5 values represented by the TEOM-FDMS with the bias reduced from −10.76 ± 11.42% to +1.33 ± 8.44% after conversion.

Multi-Year Continuous PM2.5 Measurements with the Federal Equivalent Method SHARP 5030 and Comparisons to Filter-Based and TEOM Measurements in Ontario, Canada

Continuous monitoring of fine particulate matter (PM2.5) is important to provide near-real-time air quality information for public health protection, especially when ambient levels are elevated. The Tapered Element Oscillating Microbalance (TEOM), operated at 30 °C with a sample equilibration system (SES), was used to measure PM2.5 hourly concentrations from 2002 to 2012 in Ontario, Canada. In January 2013, the Federal Equivalent Method (FEM) Synchronized Hybrid Ambient Real-time Particulate (SHARP) model 5030 monitors replaced the TEOM devices at all monitoring stations across the province to improve measurements in cold months. Continuous PM2.5 measurements from 2013 to 2016 showed good reliability of the SHARP 5030 with an average 98% valid hourly data reported to the public. Collocated measurements indicated that 24 h averages of the SHARP 5030 were comparable to those by the filter-based integrated samplers including the Federal Reference Method (FRM), and the FEM dichotomous (Dichot) and Speciation samplers. The slope and intercept of the linear regression between the SHARP 5030 and the FRM results generally met the acceptance limits for PM2.5 Class III FEM designation, and the ratio of FEM/FRM was 1.0 or 1.1. Twenty-four-hour averages of the SHARP 5030 also correlated well with the collocated 24 h Dichot and Speciation results. The difference percentages between SHARP 5030 and 24 h integrated results were found to be larger at low rather than at high PM2.5 levels, but not dependent on seasons. Absolute differences ranged from 0 to 16 µg/m3 and root mean square differences ranged from 2.0 to 2.3 µg/m3 when the SHARP 5030 was compared with the FRM, Dichot, and Speciation samplers. A simplified approach was further developed to correct historical TEOM data for cold months to continue long-term trend analyses based on collocated measurements at eight stations where PM2.5 emission sources varied.

Performance of Passive Samplers Analyzed by Computer-Controlled Scanning Electron Microscopy to Measure PM10-2.5.

We report on the precision and accuracy of measuring PM10-2.5 and its components with particles collected by passive aerosol samplers and analyzed by computer-controlled scanning electron microscopy with energy dispersive X-ray spectroscopy. Passive samplers were deployed for week-long intervals in triplicate and colocated with a federal reference method sampler at three sites and for 5 weeks in summer 2009 and 5 weeks in winter 2010 in Cleveland, OH. The limit of detection of the passive method for PM10-2.5 determined from blank analysis was 2.8 μg m(-3). Overall precision expressed as root-mean-square coefficient of variation (CVRMS) improved with increasing concentrations (37% for all samples, n = 30; 19% for PM10-2.5 > 10 μg m(-3), n = 9; and 10% for PM10-2.5 > 15 μg m(-3), n = 4). The linear regression of PM10-2.5 measured passively on that measured with the reference sampler exhibited an intercept not statistically different than zero (p = 0.46) and a slope not statistically different from unity (p = 0.92). Triplicates with high CVs (CV > 40%, n = 5) were attributed to low particle counts (and mass concentrations), spurious counts attributed to salt particles, and Al-rich particles. This work provides important quantitative observations that can help guide future development and use of passive samplers for measuring atmospheric particulate matter.

Calibration of PM2.5 mass concentrations used in the Pittsburgh Aerosol Research and Inhalation Epidemiology Study

Fifteen different types of PM2.5 mass concentration samplers were used by seven different monitoring networks at 47 locations in the Pittsburgh, Pennsylvania, region from 1999 to 2008. The samplers included Federal Reference Method (FRM) samplers, speciation samplers, tapered element oscillating microbalance (TEOM) samplers, and others. The different measurement principles used in these designs tended to lead to systematic differences (biases) when measuring the same quantity, and to differences in the typical size of random errors (imprecision) introduced by each type of sampler. Bias can take different forms either as a constant bias or as a non-constant (scale) bias, which depends on the size of the quantity being measured. The objective of the work presented here was to simultaneously calibrate the measurements made by these different samplers to remove relative biases (both constant and non-constant) so that all of the available PM2.5 data could be used interchangeably to develop exposure estimates for a retrospective epidemiology study. In order to accomplish this, we used linked temperature-stratified structural equation models, nonlinear regression models, and nonlinear mixed effects models. Applying these methods we constructed a comprehensive measurement error model that included both systematic error and random error components, and derived calibration equations that can be applied to place all of the PM2.5 mass concentration measurements on the same scale. The FRM sampler was used as the reference scale although the parameter estimates are invariant to this choice. Results showed that: (1) 50 °C TEOM samplers tended to show a large downward bias relative to the FRM sampler at low temperatures, and the magnitude of this bias decreased according to a nonlinear (sigmoidal) pattern with increasing temperature, (2) speciation samplers and other integrated samplers generally showed smaller biases relative to the FRM sampler that were not temperature-dependent, and (3) FRM samplers tended to be more precise than non-FRM samplers. These results are consistent with our previous work focusing on just a single monitoring site. Results are also presented here for several types of samplers that were not part of our previous study, including 30 °C TEOM, FDMS TEOM, and beta attenuation monitors.

Using structural equation modeling to construct calibration equations relating PM2.5 mass concentration samplers to the federal reference method sampler

The objective of this study was to remove systematic bias among fine particulate matter (PM2.5) mass concentration measurements made by different types of samplers used in the Pittsburgh Aerosol Research and Inhalation Epidemiology Study (PARIES). PARIES is a retrospective epidemiology study that aims to provide a comprehensive analysis of the associations between air quality and human health effects in the Pittsburgh, Pennsylvania, region from 1999 to 2008. Calibration was needed in order to minimize the amount of systematic error in PM2.5 exposure estimation as a result of including data from 97 different PM2.5 samplers at 47 monitoring sites. Ordinary regression often has been used for calibrating air quality measurements from pairs of measurement devices; however, this is only appropriate when one of the two devices (the “independent” variable) is free from random error, which is rarely the case. A group of methods known as “errors-in-variables” (e.g., Deming regression, reduced major axis regression) has been developed to handle calibration between two devices when both are subject to random error, but these methods require information on the relative sizes of the random errors for each device, which typically cannot be obtained from the observed data. When data from more than two devices (or repeats of the same device) are available, the additional information is not used to inform the calibration. A more general approach that often has been overlooked is the use of a measurement error structural equation model (SEM) that allows the simultaneous comparison of three or more devices (or repeats). The theoretical underpinnings of all of these approaches to calibration are described, and the pros and cons of each are discussed. In particular, it is shown that both ordinary regression (when used for calibration) and Deming regression are particular examples of SEMs but with substantial deficiencies. To illustrate the use of SEMs, the 7865 daily average PM2.5 mass concentration measurements made by seven collocated samplers at an urban monitoring site in Pittsburgh, Pennsylvania, were used. These samplers, which included three federal reference method (FRM) samplers, three speciation samplers, and a tapered element oscillating microbalance (TEOM), operated at various times during the 10-year PARIES study period. Because TEOM measurements are known to depend on temperature, the constructed SEM provided calibration equations relating the TEOM to the FRM and speciation samplers as a function of ambient temperature. It was shown that TEOM imprecision and TEOM bias (relative to the FRM) both decreased as temperature increased. It also was shown that the temperature dependency for bias was non-linear and followed a sigmoidal (logistic) pattern. The speciation samplers exhibited only small bias relative to the FRM samplers, although the FRM samplers were shown to be substantially more precise than both the TEOM and the speciation samplers. Comparison of the SEM results to pairwise simple linear regression results showed that the regression results can differ substantially from the correctly-derived calibration equations, especially if the less-precise device is used as the independent variable in the regression.

Large Particle Penetration During PM10Sampling

The objective of the present study was to characterize the performance of a federal reference method (FRM) PM10 size-selective inlet using analysis methods designed to minimize uncertainty in measured sampling efficiencies for large particles such as those most often emitted from agricultural operations. The performance of an FRM PM10 inlet was characterized in a wind tunnel at a wind speed of 8 km/h. Data were also collected for 20 and 25 μm particles at wind speeds of 2 and 24 km/h. Results of the present sampler evaluation compared well with those of previous studies for a similar inlet near the cutpoint, and the sampler passed the criteria required for certification as a FRM sampler when tested at 8 km/h. Sampling effectiveness values for particles with nominal diameters of 20 and 25 μm exceeded 3% for 8 and 24 km/h wind speeds in the present study and were statistically higher than both the “ideal” PM10 sampler (as defined in 40 CFR 53) and the ISO (1995) standard definition of thoracic particles (p < 0.05) for 25 μm particles leading to the potential for significant sampling bias relative to the “ideal” PM10 sampler when measuring large aerosols.Copyright 2014 American Association for Aerosol Research

Particulate Matter Sample Deposit Geometry and Effective Filter Face Velocities

Aerosol filter face velocities can be underestimated when the sample deposit area does not cover the entire face of the filter. In many aerosol samplers, Teflon filters are backed with a metal support screen. In these samplers, air flows through the filter only in the small area upstream of each hole in the screen, resulting in a sample deposit that is an array of tiny dots that mimics the array of holes. Thus, the filter deposit area is smaller than the total filter area and the effective face velocity is greater than that calculated from the sample deposit envelope. The Inter-agency Monitoring of Protected Visual Environments (IMPROVE) network has used filter holders with two different screen hole arrays. The U.S. Environmental Protection Agency’s Chemical Speciation Network (CSN) and the Federal Reference Method samplers also use a metal support screen, but with much smaller screen holes than IMPROVE. These networks also use larger filters and lower flow rates than those used in IMPROVE. Filter face velocities for all of these networks that are calculated using the actual deposit array area range from 1.6 to 3.5 times larger than those calculated incorrectly using the entire sample deposit envelope.

Design and evaluation of an inlet conditioner to dry particles for real-time particle sizers

Real-time particle sizers provide rapid information about atmospheric particles, particularly peak exposures, which may be important in the development of adverse health outcomes. However, these instruments are subject to erroneous readings in high-humidity environments when compared with measurements from filter-based, federal reference method (FRM) samplers. Laboratory tests were conducted to evaluate the ability of three inlet conditioners to dry aerosol prior to entering a real-time particle sizer for measuring coarse aerosols (Model 3321 Aerodynamic Particle Sizer, APS) under simulated highly humid conditions. Two 30 day field studies in Birmingham, AL, USA were conducted to compare the response of two APSs operated with and without an inlet conditioner to that measured with FRM samplers. In field studies, the correlation of PM(10-2.5) derived from the APS and that measured with the FRM was substantially stronger with an inlet conditioner applied (r2 ranged from 0.91 to 0.99) than with no conditioner (r2 = 0.61). Laboratory experiments confirmed the ability of the heater and desiccant conditioner to remove particle-borne moisture. In field tests, water was found associated with particles across the sizing range of the APS (0.5 microm to 20 microm) when relative humidity was high in Birmingham. Certain types of inlet conditioners may substantially improve the correlation between particulate mass concentration derived from real-time particle sizers and filter-based samplers in humid conditions.

Estimating FRM PM10 Sampler Performance Characteristics Using Particle Size Analysis and Collocated TSP and PM10 Samplers: Cotton Gins

In the U.S., regional air quality compliance with national ambient air quality standards (NAAQS) for particulate matter (PM) is based on concentration measurements taken by federal reference method (FRM) samplers. The EPA specifies the performance criteria for the FRM samplers. These criteria for the FRM PM10 samplers are defined as a cutpoint and slope of 10 ±0.5 µm and 1.5 ±0.1, respectively. It is commonly assumed that the performance characteristics of the FRM PM10 sampler do not vary and are independent of the PM characteristics. Several sources have observed errors in the concentrations measured by the FRM PM10 samplers and have suggested that shifts in the sampler performance characteristics may lead to the observed concentration measurement errors. Limited work has been conducted on quantifying the shift in the performance characteristics of the FRM PM10 sampler operating under field conditions. Recent work at a south Texas cotton gin showed that true PM10 concentrations were 55% of the concentrations measured by the FRM PM10 sampler. If the FRM PM10 sampler were operating within the performance criteria range specified by the EPA, then the true concentrations would be within approximately 12% of the concentrations measured by the FRM PM10 sampler. The focus of this work was to quantify the shifts in the cutpoint and slope of the penetration curve of the FRM PM10 sampler. Results show that the cutpoint and slope of the FRM PM10 sampler shifted substantially and ranged from 13.8 to 34.5 µm and from 1.7 to 5.6, respectively, when exposed to large PM as is characteristic of agricultural sources. These shifts in the cutpoint and slope of the FRM PM10 sampler resulted in overestimation of true PM10 concentrations by 145% to 287%.

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 real-time 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 ∼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 gravi-metric 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 °C) in winter correlated well with the integrated gravi-metric method. Seasonal differences were observed in the performance of the TEOM (50 °C) monitor in measuring the particle mass attributed to the higher semi-volatile material loss in the winter weather. In applying the real-time 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.

Passive Sampler for PM10–2.5 Aerosol

This study investigates the use of a small passive sampler for aerosol particles to determine particulate matter (PM)10–2.5 concentrations in outdoor air. The passive sampler collects particles by gravity, diffusion, and convective diffusion onto a glass coverslip that is then examined with an optical microscope; digital images are processed with free software and the resultant PM10–2.5 concentrations determined. Both the samplers and the analyses are relatively inexpensive. Passive samplers were collocated with Federal Reference Method (FRM) samplers in Chapel Hill, NC; Phoenix, AZ; and Birmingham, AL; for periods from 5 to 15 days. Particles consisted primarily of inorganic dusts at some sites and a mix of industrial and inorganic materials at other sites. Measured concentrations ranged from <10 µg/m3 to ∼40 µg/m3. Overall, PM10–2.5 concentrations measured with the passive samplers were within ∼1 standard deviation of concentrations measured with the FRM samplers. Concentrations determined with passive samplers depend on assumptions about particle density and shape factors and may also depend somewhat on local wind speed and turbulence; accurate values for these parameters may not be known. The degree of agreement between passive and FRM concentrations measured here suggests that passive measurements may not be overly dependent on accurate knowledge of these parameters.

The Measurement of Fine Particulate Semivolatile Material in

Ammonium nitrate and semivolatile organic material (SVOM) are significant components of fine particles in urban atmospheres. These components, however, are not properly determined with methods such as the fine particulate matter (PM2.5) Federal Reference Method (FRM) or other single filter samplers because of significant losses of semivolatile material (SVM) from particles collected on the filter during sampling. The R&P tapered element oscillating microbalance (TEOM) monitor also does not measure SVM, because this method heats the sample to remove particle bound water, which also results in evaporation of SVM. Recent advances in monitoring techniques have resulted in samplers for both integrated and continuous measurement of total PM2.5, including the particle concentrator Brigham Young University organic sampling system (PC-BOSS), the real time total ambient mass sampler (RAMS), and the R&P filter dynamics measurement system (FDMS) TEOM monitor. Results obtained using these samplers have been compared with those obtained with either a PM2.5 FRM sampler or a TEOM monitor in studies conducted during the past five years. These studies have shown the following: (1) the PC-BOSS, RAMS, and FDMS TEOM are all comparable. Each instrument measures both the nonvolatile material and the SVM. (2) The SVM is not retained on the heated filter of a regular TEOM monitor and is not measured by this sampling technique. (3) Much of the SVM is also lost during sampling from single filter samplers such as the PM2.5 FRM sampler. (4) The amount of SVM lost from single filter samplers can vary from less than one-third of that lost from heated TEOM filters during cold winter conditions to essentially all during warm summer conditions. (5) SVOM can only be reliably collected using an appropriate denuder sampler. (6) A PM2.5 speciation sampler can be easily modified to a denuder sampler with filters that can be analyzed for semivolatile organic carbon (OC), nonvolatile OC, and elemental carbon using existing OC/elemental carbon analytical techniques. The research upon which these statements are based for various urban studies are summarized in this paper.

Performance evaluation of continuous [formula omitted] mass concentration monitors

PM 2.5 mass concentrations were measured on a short time interval basis using the continuous ambient mass monitor (CAMM) and real-time ambient mass sampler (RAMS) along with a differential tapered element oscillating microbalance (TEOM) in Rubidoux CA, and intercomparisons were made among these samplers to evaluate their measurement performance of PM 2.5 mass. Nephelometers were used as an additional sampler to assist in the between-sampler comparisons. Based on the correlation with particulate nitrate concentrations and particulate mass, the differential TEOM showed better measurement of semivolatile species in PM 2.5 than either the CAMM or the RAMS. The RAMS typically measured more mass than the CAMM. The results suggest that the differential TEOM was better reflecting the PM 2.5 mass concentrations, with less impact from the loss of semivolatile components. Particulate ammonium nitrate losses estimated from the paired Harvard-EPA annular denuder system and a commercial federal reference method (FRM) sampler were equivalent to the PM 2.5 mass difference between the paired differential TEOM and FRM samplers. It suggests that volatilization of semivolatile ammonium nitrate was substantial at Rubidoux, and thus, the differential TEOM performed better in measurement of the actual PM 2.5 mass concentrations, including semivolatile and non-volatile PM, with less loss of semivolatile materials from the filter.

The Ddevelopment and Designation Testing of a New USEPA-Approved Fine Particle Inlet: A Study of the USEPA Designation Process

This article discusses the practical challenge of meeting USEPA requirements for equivalency between novel particulate matter monitoring instruments and the USEPA WINS PM2.5 Impactor (i.e., the Federal Reference Method sampler for fine particulate matter). A project was undertaken to develop a new PM2.5 instrument in which the WINS impactor was substituted by a cyclone, to give superior performance over long sampling periods under heavy loading. Empirical cyclone models were used to develop a new generation of very sharp cut cyclones (VSCC), together with a particular VSCC specimen suited to PM2.5 sampling at 16.67 l min−1. In laboratory tests, this VSCC demonstrated a precise 2.5 μm D50 cutpoint and sharpness as good as the WINS. A formal application was then undertaken to achieve USEPA Class II Equivalency designation. The process included aerosol laboratory loading trials, with results showing no change in cutpoint after up to 90 days between cleaning cycles. Field trials to compare the VSCC to the WIN...

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

It will be many years before the recently deployed network of fine particulate matter with an aerodynamic diameter less than 2.5 [H9262]m (PM2.5) Federal Reference Method (FRM) samplers produces information on nonattainment areas, trends, and source impacts. However, data on PM2.5 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 PM2.5 and coarse PM (PM10–2.5). The California Acid Deposition Monitoring Program (CADMP) collected 12-h-average PM2.5 and PM10 from 1988 to 1995 at ten urban and rural sites and 24-h-average PM2.5 at five urban sites since 1995. Beginning in 1994, the Children’s Health Study collected 2-week averages of PM2.5 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 PM2.5 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 and evaluation of in situ and filter carbon measurements at the Fresno Supersite

The Fresno Supersite in Fresno, California, USA, acquires in situ 5‐ to 60‐min average PM2.5 organic carbon (OC), elemental carbon (EC), and total carbon (TC) measurements by the following methods: (1) thermal evolution carbon analyzer for organic, elemental, and total carbon; (2) single‐wavelength and seven‐color aethalometer for black carbon (BC); and (3) photoionization for particle‐bound polycyclic aromatic hydrocarbons. Twenty‐four‐hour average PM2.5 filter‐based measurements include (1) nondenuded quartz filters with no backup filter in a PM2.5 Federal Reference Method (FRM) sampler; (2) quartz filters behind an organic carbon denuder with a quartz backup filter in a Reference Ambient Aerosol Sampler (RAAS); (3) nondenuded quartz filters with backup filter in a RAAS; and (4) nondenuded quartz filters with no backup filter in a sequential filter sampler. Filter samples are analyzed after sampling by the Interagency Monitoring of Protected Visual Environments (IMPROVE) thermal/optical reflectance carbon analysis protocol. Collocated measurements are examined for year 2000. Measurement equivalence is found for PM2.5 mass, light transmission, and TC between the FRM and RAAS speciation samplers. The average ratios of front filter carbon between the denuded and nondenuded channels in the RAAS sampler are 0.83 ± 0.19 for TC, 0.81 ± 0.20 for OC, and 1.01 ± 0.33 for EC. The average differences for TC and OC are low (1.2 to 1.4 μg m‐3) and are comparable to the measurement uncertainties. Continuous thermal evolution carbon measurements are not comparable to filter measurements. Aethalometer BC and filter EC are highly correlated, but filter EC is consistently 20–25% higher than continuous aethalometer BC. Pairwise comparisons show filter EC measurements acquired in this study are predictable from aethalometer BC measurements.

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 PM 10 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 PM 10 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 PM 10 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 PM 10 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 PM 10 FRM air samplers, offering the capability of making simultaneous, self-consistent determinations of these particulate matter fractions in a routine ambient monitoring mode.

PM 2.5 Semivolatile Organic Material at Riverside, California: Implications for the PM 2.5 Federal Reference Method Sampler

Particulate semivolatile organic compounds can be lost from particles on a filter during sample collection and storage, resulting in a artifact. Gas-phase organic compounds can adsorb on a quartz filter to cause a artifact. A sampler (Particle Concentrator-Brigham Young University Organic Sampling System: PC-BOSS) has been developed that uses a cyclone and virtual impactor (particle concentrator) inlet to provide a concentrated stream of 0.1-2.5 w m particles. The concentrator is followed by a BOSS diffusion denuder to remove interfering gas-phase compounds and filter packs to collect particles, including any semivolatile species lost from the particles during sampling. The sampler can be used for the determination of both fine particulate nitrate and semivolatile organic material without significant positive or negative sampling artifacts. The sampler has been evaluated at Riverside, CA. The collection efficiency of the particle concentrator was stable, being 65% - 2% and 61% - 1% f...