Speciation Samplers Research Articles

P54.05 The Heterogeneity of Air Pollution Particulate Matters and the Potential Tumorigenecity in Lung Progenitor Cells

Clean air is a vital factor for human and all living organisms in the ecosystem. However, air pollutants have been produced, accumulated and further amplified, impacting global health and leading to several severe diseases, including lung cancer. The most well-known air pollutant as the reference of the air quality is the particulate matter (PM), especially, the particle size smaller than 2.5 μm (PM2.5). However, PM2.5 represents a complex mixture of carcinogens, the feature of dynamic heterogeneity and the composition of second metabolites remain unclear. Most importantly, the additive and synergistic effects of these fine/ultrafine particles with different carcinogens (e.g., PAHs, nitro-PAHs, heavy metals) on cell transformation, DNA damage, and carcinogenesis stand urgently to be investigated. PM samples (size: 1∼10 μm) were collected from Shalu (N=6) and Fengyuan (N=6) districts in Taichung city by Super SASS speciation sampler and detected by scanning electron microscope (FEI Nova 200 NanoSEM). The time of flight secondary ion mass spectrometry (TOF-SIMS)(PHI TRIFT V nanoToF) was applied to clarify the heterogenic components of the PM2.5. Furthermore, the synergistic mutagenicity and carcinogenicity of PM2.5-absorbed carcinogens (TCDD, nitro-PAHs, nitrosamines, and heavy metals) were analyzed in OCT4+/CAR+ murine lung progenitor cells (mPSCsCAR+), human bronchial epithelial cells (BEAS2B) and lung adenocarcinoma cells (HOP62) using genome-wide transcriptomic analysis and protein-protein-interaction (PPI)/pathway enrichment. Q-PCR and Western blotting were used for validation. The SIMS data showed that the toxic metal ions (Cr, As, Pb, Ni, Mo, Cu, Co, Fe) were mostly identified on the surface of PMs collected from the location nearby the thermal power plants. The tandem mass imaging analysis of the single PM particle indicated the heterogeneity of its components. Noticeably, we observed carcinogens, including 2,3,7,8-tetrachlorodibenzo-P-dioxin (TCDD), benzo[a]pyrene (B[a]P), nitro-PAHs, nitrosamines, 3-chloro-4-(dichloromethyl)-5-hydroxy-2(5H)-furanone) in different PMs varies as well as metal signals, giving the various particle sizes and different collected locations. In addition, we found that the exposure of B[a]P, TCDD, nitro-PAHs and nitrosamines induced γH2AX in mPSCsCAR+, BEAS2B and HOP62 cells. The phase-I carcinogen metabolism gene expression, cyp1a1, and cyp1b1, and the apolipoprotein B mRNA editing complex 3 family (APOBEC3) were up-regulated. Furthermore, transcriptomics with pathway enrichment analysis showed that TCDD could drive the TNF, MAPK, TLF3, and PI3K-AKT signaling (P<0.01); whereas, nitro-PAHs correlated significantly with RHO GTPase signaling, chemokines, and immune modulation-related signaling; and nitrosamines could stimulate IGFBPs and several oncogenic signaling. Combination exposure of TCDD with nitrosamine significantly up-regulated the signaling by receptor tyrosine kinases, chemical carcinogenesis signaling and metabolism pathway. We found that the toxic heavy metals and environmental carcinogens (nitro-PAHs and nitrosamines) display heterogeneous in the air pollution particles. The identified carcinogens showed significant tumorigenic potential through inducing DNA damage, regulating cell cycle progression, and promoting oncogenic signaling independently and synergistically in lung progenitor cells. This mechanism could be the cause of lung adenocarcinoma for never smokers.

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.

Aerosols Characterization during the Holi festival in Dehradun: Foothills of the Himalayas, India

In this study, Partisol 2300 speciation sampler and ICP-OES were used for determining the mass and elemental composition of fine particulate matter (PM2.5) during Holi festival week 13th March 2014 to 20th March 2014 at Dehradun, India. Chemical analysis for 15 elements (Fe, Ni, Cr, Mn, Cu, Zn, Cd, As, Pb, Na, K, Al, Mg, Sb and Ca) were carried out with the collected samples (n=8). The order of concentration of chemical species during holi festival days were K&gt;Fe&gt;Na&gt;Mn&gt;Mg&gt;Cr&gt; Zn&gt;Ca&gt;Al&gt;Cu&gt;As&gt;Pb&gt;Ni&gt;Sb&gt;Cd. Aethalometer was used for determining the Black Carbon (BC) concentration and percentage of black carbon contributed by the biomass burning (BB). The average mass concentration of PM2.5 and BC during holi festival week (pre-Holi (3 days), holi(holi festival days) (2 days) and post-holi (3 days)) period was found to be 41.58, 68.61, 42.96 µg/m3 and 4.97 ± 1.89, 7.61 ± 2.37, 3.20 ± 2.46 µg/m3 respectively. The percentage of BC contributed by BB during pre-Holi, Holi and post-Holi period was 15.05 %, 18.20 % and 17.24 %. On analyzing the concentration of PM2.5, BC, surface ozone (O3), oxides of nitrogen (NOx) during the sampling period, substantial increase in concentration was observed during Holi from pre-Holi period.

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.

Spatial and seasonal variations of atmospheric particulate carbon fractions and identification of secondary sources at urban sites in North India.

An intensive measurement campaign was undertaken to characterize eight fractions of organic carbon (OC) and elemental carbon (EC) in particulate matter (PM) at four urban sites with different pollution characteristics during summer, post-monsoon, and winter at Kanpur, India. Speciation samplers were used to collect particulate samples on quartz filters followed by analysis of OC and EC using Interagency Monitoring of Protected Visual Environments (IMPROVE)-based thermal/optical reflectance (TOR) method. Based on 24-h average results at each site, the highest levels of OC and EC were observed during winter as 96.7 ± 26.9 and 31.8 ± 9.8μg/m(3) at residential site and traffic site, respectively. The levels of OC at residential sites during winter appeared to be more than twice of that during summer. The site close to the road traffic had the least value of OC/EC, as 1.77 ± 0.28 during post-monsoon, and the site influenced by emissions of domestic cooking and heating had the highest value of OC/EC, as 4.05 ± 0.79 during winter. The average abundances of OC1, OC2, OC3, OC4, OP, EC1, EC2, and EC3 in total carbon (TC) at all sites for three seasons were 10.03, 19.04, 20.03, 12.32, 10.53, 33.39, 3.21, and 1.99%, respectively. A sharp increase in levels of OC1 and EC1-OP during winter at two residential sites revealed that biomass burning could be a significant contributor to carbonaceous aerosols. From the application of EC-tracer method, it was observed that contribution of secondary organic carbon (SOC) to PM mass increased from 5% during post-monsoon to 16% during winter at residential sites and from 2% during post-monsoon to 7% during winter at traffic sites. Therefore, it could be inferred that increase in primary emissions coupled with unfavorable meteorological conditions could cause particle agglomeration and hygroscopic growth, leading to unpleasant pollution episode during winter.

Gas-to-particle conversion of atmospheric ammonia and sampling artifacts of ammonium in spring of Beijing

PM2.5 and gaseous pollutants (SO2, HNO2, HNO3, HCl, and NH3) were simultaneously collected by Partisol® Model 2300 Sequential Speciation Sampler with denuder-filter pack system in the spring of 2013 in Beijing. Water-soluble inorganic ions and gaseous pollutants were measured by Ion Chromatography. Results showed that the concentrations of NH3, NH4 + and PM2.5 had similar diurnal variation trends and their concentrations were higher at night than in daytime. The results of gas-to-particle conversion revealed that [NH3]:[NH4 +] ratio was usually higher than 1; however, it was less than 1 and the concentration of NH4 + increased significantly during the haze episode, indicating that NH3 played an important role in the formation of fine particle. Research on the sampling artifacts suggested that the volatilization loss of NH4 + was prevalent in the traditional single filter-based sampling. The excess loss of HNO3 and HCl resulted from ammonium-poor aerosols and semivolatile inorganic species had severe losses in the clean day, whereas the mass of NH4 + was usually overestimated during the single filter-based sampling due to the positive artifacts. Correlation analysis was used to evaluate the influence of meteorological conditions on the volatilization loss of NH4 +. It was found that the average relative humidity and temperature had great effects on the loss of NH4 +. The loss of NH4 + was significantly under high temperature and low humidity, and tended to increase with the increasing of absorption of gaseous pollutants by denuder. The total mass of volatile loss of NH4 +, NO3 − and Cl− could not be ignored and its maximum value was 12.17 μg m−3. Therefore it is important to compensate sampling artifacts for semivolatile inorganic species.

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.

Ammonia concentrations and modeling of inorganic particulate matter in the vicinity of an egg production facility in Southeastern USA

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

Field comparison of cyclonic separator and mass inertial impactor for PM10 monitoring

Monitoring of ambient PM10 concentrations was carried out using two co-located samplers at 10 different locations over the three seasons (summer, winter and post-monsoon) in Delhi, India. The samplers used for the study were the high volume sampler fitted with a cyclone (commonly known in India as respirable particulate matter sampler or RPM sampler), and a 4-channel speciation sampler (4-SS). The RPM sampler separates the PM10 fraction using centrifugal inertia while the 4-SS separates them using the principle of mass inertial impaction. Comparison of the measured data are made using different graphical techniques and statistical analysis, comprising classical two tailed paired t-test and the criteria recommended by the European Commission working group on particulate matter. The PM10 data monitored by both the samplers showed good overall correlations for the entire data set, with a regression co-efficient value of 0.61. Results indicated that inertial impaction based 4-SS consistently measures higher PM10 concentration compared with the cyclone fitted RPM sampler. Such results were valid for 81% of the total data set and this difference in measured concentrations was ∼66% in the regulatory limit value ranges. Both the samplers have their merits and limitations and hence a conscious choice and appropriate data correction is needed when deploying them for scientific and regulatory monitoring purposes.

Field evaluation of particulate matter measurements using tapered element oscillating microbalance in a layer house

The tapered element oscillating microbalance (TEOM) is one type of continuous ambient particulate matter (PM) monitor. Adsorption and desorption of moisture and semivolatile species may cause positive or negative artifacts in TEOM PM mass measurement. The objective of this field study was to investigate possible uncertainties associated with TEOM measurements in the poultry operation environment. For comparisons of TEOM with filter-based gravimetric method, four instruments (TEOM-PM10, low-volume PM10 sampler, TEOM-PM2.5, and PM2.5 speciation sampler) were collocated and tested inside a poultry house for PM2.5 and PM10 (PM with aerodynamic equivalent diameter ≤2.5 and ≤10 μm, respectively) measurements. Fifteen sets of 24-hr PM10 concentrations and 13 sets of 24-hr PM2.5 measurements were obtained. Results indicate that compared with filter-based gravimetric method, TEOM gave significantly lower values of both PM10 and PM2.5 mass concentrations. For PM10, the average ratio of TEOM to the gravimetric method was 0.936. For PM2.5, the average ratio of TEOM to the gravimetric method was 0.738. Particulate matter in the poultry houses possibly contains semivolatile compounds and moisture due to high levels of relative humidity (RH) and gas pollutants. The internal heating mechanism of the TEOM may cause losses in mass through volatilization. To investigate the effects of TEOM settings on concentration measurements, the heaters of two identical TEOMs were set at 50 °C, 30 °C, or no heating at all. They were collocated and tested for total suspended particle (TSP), PM10, and PM2.5 measurements in layer house for 6 weeks. For all TSP, PM10, and PM2.5 measurements, the internal TEOM temperature setting had a significant effect (P < 0.05). Significantly higher PM mass concentrations were measured at lower temperature settings. The effects of environmental (i.e., temperature, RH, NH3 and CO2 concentrations) and instrumental (i.e., filter loading and noise) parameters on PM measurements were also assessed using regression analysis. Implications Because of its potential health and environmental effects, particulate matter (PM) emissions from animal feeding operations (AFOs) have been a great concern to the public and to the regulatory agencies. The tapered element oscillating microbalance (TEOM) PM monitor has been was adapted for continuous PM measurements in some AFO air quality studies. This study investigated possible uncertainties associated with TEOM measurements in an egg production environment. It was discovered that there was a significant bias in TEOM measurements of PM10 as compared with federal reference method. Internal temperature settings of a TEOM have significant impact on its PM measurement.

Evaluation of ambient SO2 measurement methods at roadside sites

Abstract Accurate measurements of SO2 at low ambient concentrations are needed in order to investigate the role of SO2 in particle nucleation events and the long-term impact of reductions in sulfur emissions in recent decades. In this study, artifacts in SO2 concentration measurements were investigated using two identical ion chromatography-based instruments (the Gas Particle Ion Chromatograph, GP-IC, Dionex Corporation) and two identical UV fluorescence-based SO2 analyzers (the TECO 43CTL, an industry standard). The SO2 concentration values measured with the GP-IC at roadside sites were compared with simultaneous side-by-side measurements made with the fluorescence analyzers. The SO2 concentration measured with the GP-IC had an ∼30% negative calibration artifact. When the GP-ICs were calibrated using an improved procedure developed in the course of this study, only a ±5% difference from the TECO analyzers remained, except under high NO concentration conditions. The fluorescence analyzers exhibited a positive artifact under elevated NO concentration conditions. Sulfur oxidation ratios were calculated based on the GP-IC-measured SO2 and SO42- concentrations and used to help identify potential emission sources. The SO2 concentrations measured with the GP-IC were also compared to data obtained from a National Air Pollution Surveillance (NAPS) speciation sampler equipped with a Na2CO3-coated denuder. Good correlation between SO2 data from the two methods was seen during five months of measurement, but the GP-IC SO2 data were ∼30% lower than the NAPS data. Deposition of SO2 within an urban street canyon is discussed as a possible explanation for this difference.

Fine Particulate Matter in a High-Rise Layer House and Its Vicinity

Fine particulate matter (PM2.5) is one of many air pollutants emitted from animal feeding operations (AFOs). Knowledge about PM2.5 in AFO production facilities and their vicinity is important for studies of its impact on health, animal welfare, and the environment. However, very little information is available about PM2.5 concentrations and emissions, and their spatial and temporal variations, associated with egg production facilities. In this study, Partisol 2300 PM2.5 speciation samplers were used to take daily PM2.5 samples in a high-rise layer house and at four ambient stations. The sampling period covered four seasons, with a total of 300 samples. The results showed that none of the ambient PM2.5 concentrations exceeded the 35 µg m-1 (24 h) and 15 µg m-1 (annual) PM2.5 National Ambient Air Quality Standards (NAAQS). The ambient stations and the in-house station showed strong seasonal variations; the ambient stations had the highest PM2.5 concentrations in summer, and the in-house station had the highest concentration in winter. Based on the gamma distribution, 95% confidence intervals of PM2.5 emissions (mg PM2.5 d-1 hen-1) were [7.86, 11.4]. The downtime PM2.5 concentration mean was one-tenth that of the occupied house. PM2.5 concentrations were negatively correlated with ambient RH, egg production, and ventilation rate. Statistical tests did not show a strong correlation between ambient PM2.5 concentrations and emissions from the layer house. This study adds to a growing body of research assessing the environmental impact, air quality, emissions of AFOs and the relationship between PM2.5 and the environmental and farm management inventory information.

Comparison of Speciation Sampler and PC-BOSS Fine Particulate Matter Organic Material Results Obtained in Lindon, Utah, during Winter 2001–2002

The Particle Concentrator-Brigham Young University Organic Sampling System (PC-BOSS) has been previously verified as being capable of measuring total fine particulate matter (PM2.5), including semi-volatile species. The present study was conducted to determine if the simple modification of a commercial speciation sampler with a charcoal denuder followed by a filter pack containing a quartz filter and a charcoal-impregnated glass (CIG) fiber filter would allow for the measurement of total PM2.5, including semi-volatile organic material. Data were collected using an R&P (Rupprecht and Pastasnik Co., Inc.) Partisol Model 2300 speciation sampler; an R&P Partisol speciation sampler modified with a BOSS denuder, followed by a filter pack with a quartz and a CIG filter; a Met One spiral aerosol speciation sampler (SASS); and the PC-BOSS from November 2001 to March 2002 at a U.S. Environmental Protection Agency (EPA) Science to Achieve Results (STAR) sampling site in Lindon, UT. Total PM2.5 mass, ammonium nitrate (both nonvolatile and semi-volatile), ammonium sulfate, organic carbon (both non-volatile and semi-volatile), and elemental carbon were determined on a 24-hr basis. Results obtained with the individual samplers were compared to determine the capability of the modified R&P speciation sampler for measuring total PM2.5, including semi-volatile components. Data obtained with the modified speciation sampler agreed with the PC-BOSS results. Data obtained with the two unmodified speciation samplers were low by an average of 26% because of the loss of semi-volatile organic material from the quartz filter during sample collection.

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.

Measurement of total PM2.5mass (nonvolatile plus semivolatile) with the Filter Dynamic Measurement System tapered element oscillating microbalance monitor

Field studies have been performed in Lindon, Utah (February 2003) and Rubidoux, California (July 2003) to determine if the Rupprecht and Patashnick (R&amp;P) Filter Dynamic Measurement System (FDMS) determines total fine particulate mass, including the semivolatile ammonium nitrate and organic material. Collocated measurements were made with the FDMS, a conventional tapered element oscillating microbalance (TEOM) monitor with a heated filter, an R&amp;P differential TEOM monitor, the Brigham Young University (BYU) Real‐Time Total Ambient Mass Sampler (RAMS), the BYU particle concentrator‐organic sampling system (PC‐BOSS), a PM2.5Federal Reference Method (FRM), a PM2.5speciation sampler, an R&amp;P continuous nitrate monitor, and two Sunset continuous carbon monitors (one to measure quartz filter‐retained particulate carbon and one to measure particulate semivolatile carbonaceous material lost from the particles on a filter during sampling). The RAMS and PC‐BOSS samplers have been shown to determine fine particulate material, including both the semivolatile and the nonvolatile components. Linear regression analysis at the Lindon site between the FDMS (X) and the PC‐BOSS (Y), and the FDMS (X) and the RAMS (Y), resulted in zero‐intercept slopes of 1.01 ± 0.06 (r2= 0.63) and 1.00 ± 0.01 (r2= 0.69), respectively. At the Rubidoux sampling site, linear regression analysis between the PC‐BOSS (X) and the FDMS (Y) gave a zero‐intercept slope of 0.96 ± 0.02 (r2= 0.90). Linear regression analysis between the FDMS (X) and the RAMS (Y) resulted in a zero‐intercept slope of 0.99 ± 0.01 (r2= 0.80). Measurements made at the two sites indicate that the FDMS and the R&amp;P differential TEOM monitors do measure total fine particulate mass, including the semivolatile ammonium nitrate and organic material. Both the heated TEOM monitor and PM2.5FRM did not measure the semivolatile material. The difference between the FDMS and a heated TEOM monitor was explained by the semivolatile ammonium nitrate and organic material measured by the various chemical composition monitors.

Development of an Air Quality Learning and Demonstration Center at the Arboretum at Penn State

An Air Quality Learning and Demonstration Center has been developed within the Arboretum at Penn State Univ.. The Center provides opportunities where students (of all ages) and teachers (grade-school through to classes within the Univ.) can learn about air quality as one of our most important natural resources. A seasonally interactive display of air quality monitoring instrumentation, self guided walkways through gardens of air pollution sensitive plant species, innovative techniques for demonstrating the effects of air pollutants on plants, displays of recent research findings, industry supported displays of pollution abatement technologies, and a teaching pavilion are within the Center. A Pennsylvania Dept. of Environmental Protection air quality monitoring station with ozone, sulfur dioxide, nitrogen oxides, carbon dioxide, PM &lt; 2.5 u mass and speciation samplers, and a complete meteorological station provide data on the immediate environmental parameters. These data are relayed to an LCD crystal display board that has been mounted on the outside of the monitoring building; visitors are able to see the various measures of the air quality on a real time basis. Pannier type fiberglass display panels provide understandings of the various facets of air pollution formation and transport phenomena, air quality monitoring methods, the functions of open-top chambers, foliar symptoms expressed by pollution sensitive plants within the bioindicator gardens, and the impacts of pollution on agricultural and forested ecosystems. Handicapped accessible walkways lead visitors throughout the Center to the Teaching Pavilion that easily accommodates 80 persons. The pavilion is equipped with drop down curtains, electric power, and internet connections.

Measurement of fine particulate matter using electron microscopy techniques

Ambient fine particulate matter, defined as material with an aerodynamic diameter less than or equal to 2.5 μm (PM 2.5), comprises a broad range of primary and secondary particles that are dispersed through the atmosphere from a variety of sources. Attention has recently shifted to investigating ambient PM 2.5 because fine particles are thought to have a greater influence on health effects. Of particular interest are sources of fossil fuel combustion because they have been hypothesized as potentially contributing to the observed link between atmospheric particulate matter and health effects. Current studies are focused on the use of multiple analytical techniques to assist in the characterization of particulate matter to gain a better understanding of the relationship between anthropogenic emission sources and ambient PM 2.5. Electron microscopy techniques are being employed to provide information on the size, morphology, and elemental composition of individual particles. Individual particle data offers the potential to more specifically identify and quantify sources of particulate matter contributing to ambient air quality. However, electron microscopy has not been widely utilized in air quality studies because of the difficulties associated with collecting a sample that is well suited for individual particle analysis. Recent improvements in sampling technology, specifically the speciation sampler, permit collection of samples that are more amenable for electron microscopy analysis. This paper discusses the application of electron microscopy in environmental studies for individual particle analysis using scanning electron microscopy (SEM), computer-controlled scanning electron microscopy (CCSEM), and transmission electron microscopy (TEM) techniques. The paper also addresses managing the difficulties associated with the characterization of fine particulate matter using electron microscopy due to substrate interference and describes the benefits of sample collection with speciation samplers.

Development and Evaluation of a High Loading PM2.5Speciation Sampler

A high loading sampler for the chemical characterization of fine particles (PM 2.5 ) was developed and validated through laboratory and field experiments. This speciation sampler consists of two identical serially connected impaction stages to remove particles larger than 2.5 μm, following by a chamber to allow use of one or two all-glass honeycomb diffusion denuders, and a holder for a 47 mm filter. Two configurations of the sampler allow sampling at flows of 10 lpm and 16.7 lpm. System performance was evaluated in laboratory experiments using artificially generated polydisperse aerosols. This novel sampler provides a much larger mass loading capacity than previous impactors that use flat, rigid substrate surfaces. The polyurethane foam (PUF) substrate maintains adequate performance characteristics (retention of size cut-off, sharpness of cut-off curve, and minimal particle bounce and re-entrainments) at loadings of at least 35 mg. This is equivalent to 728 μg/m3 for a 48 h sampling period (or 500 h of s...

Comparison of Integrated Filter and Automated Carbon Aerosol Measurements at Research Triangle Park, North Carolina

Carbon aerosol measurements from the Rupprecht & Patashnick Series 5400 carbon analyzer, the Magee Scientific AE-21 Aethalometer and a filter-based Andersen RAAS2.5-410 Chemical Speciation sampler with quartz filters analyzed by Thermal Optical Transmittance (TOT) were compared. The Series 5400 total carbon (TC) and organic carbon (OC) were moderately correlated (r = 0.64 and 0.67) with the RAAS TOT method and the elemental carbon (EC) was poorly correlated (r = 0.37). The 5400 underestimated the RAAS TC and OC by 64% and 78%, respectively. The underestimate is attributed in part to the positive OC artifact of the filter-based sampling method. Another difference between the 5400 measurements and the RAAS TOT is a correction for char. The lack of correction for any char that occurs in the 5400 could cause and underestimate of OC and an overestimate of EC. The 5400 overestimated RAAS EC by 89%. The Aethalometer black carbon (BC) was compared to the 5400 EC and the RAAS TOT EC measured. The Aethalometer BC correlated well (r = 0.86) with the RAAS EC, but the Aethalometer overestimated the RAAS EC by 30%. The 5400 EC was compared to Aethalometer BC both with and without a PM2.5 size selective inlet. The correlations were 0.92 (inlet) and 0.55 (no inlet). The 5400 overestimated the mean Aethalometer BC by 17% with the inlet and 39% without. The improvement in results may not be due to the addition of the PM2.5 inlet, but instead may be due to a difference in the amount of char formed by the 5400. Factors contributing to the differences in these results are discussed.

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.