Delbert J. Eatough

PM source apportionment and health effects: 1. Intercomparison of source apportionment results

During the past three decades, receptor models have been used to identify and apportion ambient concentrations to sources. A number of groups are employing these methods to provide input into air quality management planning. A workshop has explored the use of resolved source contributions in health effects models. Multiple groups have analyzed particulate composition data sets from Washington, DC and Phoenix, AZ. Similar source profiles were extracted from these data sets by the investigators using different factor analysis methods. There was good agreement among the major resolved source types. Crustal (soil), sulfate, oil, and salt were the sources that were most unambiguously identified (generally highest correlation across the sites). Traffic and vegetative burning showed considerable variability among the results with variability in the ability of the methods to partition the motor vehicle contributions between gasoline and diesel vehicles. However, if the total motor vehicle contributions are estimated, good correspondence was obtained among the results. The source impacts were especially similar across various analyses for the larger mass contributors (e.g., in Washington, secondary sulfate SE=7% and 11% for traffic; in Phoenix, secondary sulfate SE=17% and 7% for traffic). Especially important for time-series health effects assessment, the source-specific impacts were found to be highly correlated across analysis methods/researchers for the major components (e.g., mean analysis to analysis correlation, r>0.9 for traffic and secondary sulfates in Phoenix and for traffic and secondary nitrates in Washington. The sulfate mean r value is >0.75 in Washington.). Overall, although these intercomparisons suggest areas where further research is needed (e.g., better division of traffic emissions between diesel and gasoline vehicles), they provide support the contention that PM2.5 mass source apportionment results are consistent across users and methods, and that todays source apportionment methods are robust enough for application to PM2.5 health effects assessments.

A multiple-system, multi-channel diffusion denuder sampler for the determination of fine-particulate organic material in the atmosphere

Abstract Measurement of the loss of semi-volatile organic compounds from particles collected with a filter is carried out by comparing the amounts collected by comparable filter pack and diffusion denuder samplers. The sorbents used to collect organic compounds in the denuder and sorbent filters must have the same efficiency for collection of all gas-phase organic compounds present. Interpretation of the data requires that the efficiency of collection of gas-phase compounds by the denuder be known. In theory this can be accomplished by determination of the deposition pattern of all organic compounds collected in the denuder, but in practice this is very difficult if the organic material consists of a wide variety of compounds. An alternative approach is to determine the breakthrough of organic compounds in a sampler with a particle-collection filter preceding the denuder and sorbent filter. In such a sampler only gas-phase organic material enters the denuder. We have developed both a multi-channel parallel plate diffusion denuder sampler and a comparable sampler in which the denuder is preceded by a filter. Samples can be collected with the multisystem sampler at a flow rate of 35 sLpm. The denuder surfaces and the sorbent filters are made from sheets of an activated charcoal-impregnated filter paper. Collection of semi-volatile compounds by the samplers has been characterized and the systems have been field tested. The samplers are now being used for the routine collection and determination of semi-volatile organic compounds in particles at Canyonlands National Park in southeastern Utah. Available data from this field program show significant losses of particulate organic compounds on a quartz filter due to volatilization during sampling.

Determination of equilibrium constants by titration calorimetry: Part II. Data reduction and calculation techniques

Abstract Techniques of data reduction and methods of calculation have been given for the determination of equilibrium constants by titration calorimetry. It has been shown how, starting with typical titration calorimetry data, the apparent heat liberated in the reaction vessel can be calculated, corrected for extraneous heat effects, and used to solve for the equilibrium constant and enthalpy change value(s) for the reaction(s) under investigation. Equations are given for calculating the energy contributed to the overall heat effects measured in the reaction vessel by processes other than chemical reactions such as heat of stirring, heat losses, heat of dilution, etc., and by chemical reactions other than the one(s) for which equilibrium constant(s) are sought. Mathematical techniques and equations are presented for calculating equilibrium constants and enthalpy change values from titration data by least squares analysis.

Determination of equilibrium constants by titration calorimetry: Part I. Introduction to titration calorimetry☆

Abstract Techniques for determining thermodynamic equilibrium constants by titration calorimetry have been developed for a wide spectrum of reactions. The method is still relatively new and improvements and extensions are foreseeable. Chief among the advantages of the method is its university. It can be used in any solvent to determine equilibrium constants for proton ionization and metal ion—ligand interactions over a large pH range for simple and complex equilibria. It yields a good overall picture of the stoichiometry of the reaction(s) taking place and the experimentation and data analysis can be done rapidly. The chief drawback of the method has been the initial expense of the calorimeter and the unavailability of commercial calorimeters. However, this is partially offset by the fact that commercial calorimeters are now available from LKB Instruments (Rockville, Maryland) and Tronac (Orem, Utah). Computer programs have been worked out for most types of reactions and are available in Fortran IV computer language (see Part II and III, pp. 219Δ-246). Simple and inexpensive apparatus can be built for demonstration and laboratory classwork in which the equilibrium constants for simple interactions can be obtained by the solution of simultaneous equations.

Workgroup Report: Workshop on Source Apportionment of Particulate Matter Health Effects—Intercomparison of Results and Implications

Although the association between exposure to ambient fine particulate matter with aerodynamic diameter < 2.5 μm (PM2.5) and human mortality is well established, the most responsible particle types/sources are not yet certain. In May 2003, the U.S. Environmental Protection Agency’s Particulate Matter Centers Program sponsored the Workshop on the Source Apportionment of PM Health Effects. The goal was to evaluate the consistency of the various source apportionment methods in assessing source contributions to daily PM2.5 mass–mortality associations. Seven research institutions, using varying methods, participated in the estimation of source apportionments of PM2.5 mass samples collected in Washington, DC, and Phoenix, Arizona, USA. Apportionments were evaluated for their respective associations with mortality using Poisson regressions, allowing a comparative assessment of the extent to which variations in the apportionments contributed to variability in the source-specific mortality results. The various research groups generally identified the same major source types, each with similar elemental makeups. Intergroup correlation analyses indicated that soil-, sulfate-, residual oil-, and salt-associated mass were most unambiguously identified by various methods, whereas vegetative burning and traffic were less consistent. Aggregate source-specific mortality relative risk (RR) estimate confidence intervals overlapped each other, but the sulfate-related PM2.5 component was most consistently significant across analyses in these cities. Analyses indicated that source types were a significant predictor of RR, whereas apportionment group differences were not. Variations in the source apportionments added only some 15% to the mortality regression uncertainties. These results provide supportive evidence that existing PM2.5 source apportionment methods can be used to derive reliable insights into the source components that contribute to PM2.5 health effects.

The nitric acid shootout: field comparison of measurement methods

Eighteen instruments for measuring atmospheric concentrations of nitric acid were compared in an eight day field study at Pomona College, situated in the eastern portion of the Los Angeles Basin, in September 1985. The study design included collocated and separated duplicate samplers, and the analysis by each laboratory of a set of quality assurance filters, so that the experimental variability could be distinguished from differences due to measurement methods. For all sampling periods, the values for nitric acid concentrations reported by the different instruments vary by as much as a factor of four. The differences among measurement techniques increase with nitric acid loading, corresponding to a coefficient of variation of 40%. In contrast, samplers of the same design operated by the same group show variability of 11–27 %. Overall, the highest reported concentrations are observed with the filter packs and lower concentrations are observed by the annular denuders and tunable diode laser absorption spectrometers. When the nitric acid concentrations are high enough to be detected by the FTIR, the FTIR values are close to those obtained by the denuder difference method and to the mean value from the other sampler groups. In the absence of a reference standard for the entire study, measurement methods are compared to the average of four denuder difference method samplers (DDM). Filter pack samplers are higher than the DDM for both daytime and night-time sampling. Two different filter packs using Teflon® prefilters are higher than the DDM by factors of 1.25 and 1.4. The results from the three annular denuders do not agree; the ratios of means to the DDM value are 1.0,0.8 and 0.6. For the transition flow reactor method and for two dichotomous samplers operated as denuder difference samplers, the ratio of means to the DDM are 1.09 and 0.93, respectively. The tunable diode laser absorption spectrometers gave lower daytime and higher night-time readings compared to the DDM, especially during the last three days of the study. Averaged over the entire measurement period, the daytime ratio of TDLAS to DDM is 0.8 and the night-time ratio is 1.7.

PM source apportionment and health effects. 3. Investigation of inter-method variations in associations between estimated source contributions of PM2.5 and daily mortality in Phoenix, AZ

As part of an EPA-sponsored workshop to investigate the use of source apportionment in health effects analyses, the associations between the participants estimated source contributions of PM2.5 for Phoenix, AZ for the period from 1995–1997 and cardiovascular and total nonaccidental mortality were analyzed using Poisson generalized linear models (GLM). The base model controlled for extreme temperatures, relative humidity, day of week, and time trends using natural spline smoothers. The same mortality model was applied to all of the apportionment results to provide a consistent comparison across source components and investigators/methods. Of the apportioned anthropogenic PM2.5 source categories, secondary sulfate, traffic, and copper smelter-derived particles were most consistently associated with cardiovascular mortality. The sources with the largest cardiovascular mortality effect size were secondary sulfate (median estimate=16.0% per 5th-to-95th percentile increment at lag 0 day among eight investigators/methods) and traffic (median estimate=13.2% per 5th-to-95th percentile increment at lag 1 day among nine investigators/methods). For total mortality, the associations were weaker. Sea salt was also found to be associated with both total and cardiovascular mortality, but at 5 days lag. Fine particle soil and biomass burning factors were not associated with increased risks. Variations in the maximum effect lag varied by source category suggesting that past analyses considering only single lags of PM2.5 may have underestimated health impact contributions at different lags. Further research is needed on the possibility that different PM2.5 source components may have different effect lag structure. There was considerable consistency in the health effects results across source apportionments in their effect estimates and their lag structures. Variations in results across investigators/methods were small compared to the variations across source categories. These results indicate reproducibility of source apportionment results across investigative groups and support applicability of these methods to effects studies. However, future research will also need to investigate a number of other important issues including accuracy of results.

Semi-volatile secondary organic aerosol in urban atmospheres: meeting a measurement challenge

Ammonium nitrate and semi-volatile organic compounds are significant components of fine particles in urban atmospheres. These components, however, are not properly determined with current US EPA accepted methods such as the PM2.5 FRM or other single filter samplers due to significant losses of semi-volatile material (SVM) from particles collected on the filter during sampling. Continuous PM2.5 mass measurements are attempted using methods such as the R&P TEOM monitor. This method, however, heats the sample to remove particle-bound water which also results in evaporation of SVM. Research at Brigham Young University has resulted in samplers for both the integrated and continuous measurement of total PM2.5, including the SVM. The PC-BOSS is a charcoal diffusion denuder based sampler for the determination of fine particulate chemical composition including the semi-volatile organic material. The RAMS is a modified TEOM monitor which includes diffusion denuders and Nafion dryers to remove gas phase material which can be absorbed by a charcoal sorbent filter. The RAMS then uses a “sandwich filter” consisting of a conventional particle collecting Teflon coated TX40 filter, followed by an activated charcoal sorbent filter which retains any semi-volatile ammonium nitrate or organic material lost from the particles collected on the TEOM monitor Teflon coated filter, thus allowing for determination of total PM2.5 mass including the SVM. Recent research conducted by Brigham Young University using these two samplers has indicated the following about semi-volatile organic aerosol: • The majority of semi-volatile fine particulate organic material is secondary organic aerosol. • This semi-volatile organic aerosol is not retained on the heated filter of a regular TEOM monitor and hence is not measured by this sampling technique. In addition, secondary ammonium nitrate is also lost. • Much of the semi-volatile organic aerosol is also lost during sampling from single filter samplers such as the PM2.5 FRM sampler. • The amount of semi-volatile organic aerosol lost from single filter samplers can vary from less than 13 that lost from heated TEOM filters during cold winter conditions to essentially all during warm summer conditions. • Semi-volatile organic aerosol can only be reliably collected using an appropriate denuder sampler. • Either a PM2.5 FRM sampler or the IMPROVE sampler can be easily modified to a denuder sampler with filters which can be analyzed for semi-volatile OC, nonvolatile OC and EC using existing OC/EC analytical techniques. The research upon which these statements are based is summarized in this document.

Determination of equilibrium constants by titration calorimetry: Part III. Application of method to several chemical systems☆

The determination of equilibrium constants and enthalpy change values from titration calorimetry data has been demonstrated for three chemical systems. It has been known how, starting with the calorimetric data, the computational methods outlined in the previous papers of this series can be used to calculate the heat, Qc, produced, due to the reaction(s) of interest and from these Qc values the K and ΔDH values can be calculated for the interactions occuring in the calorimeter. Source of computer programs used in the calculations have been given.

Aerosol Measurement: The Use of Optical Light Scattering for the Determination of Particulate Size Distribution, and Particulate Mass, Including the Semi-Volatile Fraction

Abstract The GRIMM model 1.107 monitor is designed to measure particle size distribution and particulate mass based on a light scattering measurement of individual particles in the sampled air. The design and operation of the instrument are described. Protocols used to convert the measured size number distribution to a mass concentration consistent with U.S. Environmental Protection Agency protocols for measuring particulate matter (PM) less than 10 μm (PM10) and less than 2.5 μm (PM2.5) in aerodynamic diameter are described. The performance of the resulting continuous monitor has been evaluated by comparing GRIMM monitor PM2.5 measurements with results obtained by the Rupprecht and Patashnick Co. (R&P) filter dynamic measurement system (FDMS). Data were obtained during month-long studies in Rubidoux, CA, in July 2003 and in Fresno, CA, in December 2003. The results indicate that the GRIMM monitor does respond to total PM2.5 mass, including the semi-volatile components, giving results comparable to the FDMS. The data also indicate that the monitor can be used to estimate water content of the fine particles. However, if the inlet to the monitor is heated, then the instrument measures only the nonvolatile material, more comparable to results obtained with a conventional heated filter tapered element oscillating microbalance (TEOM) monitor. A recent modification of the model 180, with a Nafion dryer at the inlet, measures total PM2.5 including the nonvolatile and semi-volatile components, but excluding fine particulate water. Model 180 was in agreement with FDMS data obtained in Lindon, UT, during January through February 2007