Search

The replacement of the Desert Research Institute (DRI) model 2001 with model 2015 thermal/optical analyzers (TOAs) results in continuity of the long-term organic carbon (OC) and elemental carbon (EC) database, and it adds optical information with no additional carbon analysis effort. The value of multiwavelength light attenuation is that light absorption due to black carbon (BC) can be separated from that of brown carbon (BrC), with subsequent attribution to known sources such as biomass burning and secondary organic aerosols. There is evidence of filter loading effects for the 25% of all samples with the highest EC concentrations based on the ratio of light attenuation to EC. Loading corrections similar to those used for the seven-wavelength aethalometer need to be investigated. On average, nonurban Interagency Monitoring of PROtected Visual Environments (IMPROVE) samples show higher BrC fractions of short-wavelength absorption than urban Chemical Speciation Network (CSN) samples, owing to greater influence from biomass burning and aged aerosols, as well as to higher primary BC contributions from engine exhaust at urban sites. Sequential samples taken during an Everglades National Park wildfire demonstrate the evolution from flaming to smoldering combustion, with the BrC fraction increasing as smoldering begins to dominate the fire event., Implications: The inclusion of seven wavelengths in thermal/optical carbon analysis of speciated PM 2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm) samples allows contributions from biomass burning and secondary organic aerosols to be estimated. This separation is useful for evaluating control strategy effectiveness, identifying exceptional events, and determining natural visibility conditions.

A thermal/optical carbon analyzer (TOA), normally used for quantification of organic carbon (OC) and elemental carbon (EC) in PM 2.5 (fine particulate matter) speciation networks, was adapted to direct thermally evolved gases to an electron impact quadrupole mass spectrometer (QMS), creating a TOA-QMS. This approach produces spectra similar to those obtained by the Aerodyne aerosol mass spectrometer (AMS), but the ratios of the mass to charge (m/z) signals differ and must be remeasured using laboratory-generated standards. Linear relationships are found between TOA-QMS signals and ammonium (NH 4 + ), nitrate (NO 3 - ), and sulfate (SO 4 2- ) standards. For ambient samples, however, positive deviations are found for SO 4 2- , compensated by negative deviations for NO 3 - , at higher concentrations. This indicates the utility of mixed-compound standards for calibration or separate calibration curves for low and high ion concentrations. The sum of the QMS signals across all m/z after removal of the NH 4 + , NO 3 - , and SO 4 2- signals was highly correlated with the carbon content of oxalic acid (C₂H₂O₄) standards. For ambient samples, the OC derived from the TOA-QMS method was the same as the OC derived from the standard IMPROVE_A TOA method. This method has the potential to reduce complexity and costs for speciation networks, especially for highly polluted urban areas such as those in Asia and Africa., Implications: Ammonium, nitrate, and sulfate can be quantified by the same thermal evolution analysis applied to organic and elemental carbon. This holds the potential to replace multiple parallel filter samples and separate laboratory analyses with a single filter and a single analysis to account for a large portion of the PM 2.5 mass concentration.

It is axiomatic that good measurements are integral to good public policy for environmental protection. The generalized term for "measurements" includes sampling and quantitation, data integrity, documentation, network design, sponsorship, operations, archiving, and accessing for applications. Each of these components has evolved and advanced over the last 200 years as knowledge of atmospheric chemistry and physics has matured. Air quality was first detected by what people could see and smell in contaminated air. Gaseous pollutants were found to react with certain materials or chemicals, changing the color of dissolved reagents such that their light absorption at selected wavelengths could be related to both the pollutant chemistry and its concentration. Airborne particles have challenged the development of a variety of sensory devices and laboratory assays for characterization of their enormous range of physical and chemical properties. Advanced electronics made possible the sampling, concentration, and detection of gases and particles, both in situ and in laboratory analysis of collected samples. Accurate and precise measurements by these methods have made possible advanced air quality management practices that led to decreasing concentrations over time. New technologies are leading to smaller and cheaper measurement systems that can further expand and enhance current air pollution monitoring networks., Implications: Ambient air quality measurement systems have a large influence on air quality management by determining compliance, tracking trends, elucidating pollutant transport and transformation, and relating concentrations to adverse effects. These systems consist of more than just instrumentation, and involve extensive support efforts for siting, maintenance, calibration, auditing, data validation, data management and access, and data interpretation. These requirements have largely been attained for criteria pollutants regulated by National Ambient Air Quality Standards, but they are rarely attained for nonroutine measurements and research studies.

Unlabelled: Collocated comparisons for three PM(2.5) monitors were conducted from June 2011 to May 2013 at an air monitoring station in the residential area of Fort McMurray, Alberta, Canada, a city located in the Athabasca Oil Sands Region. Extremely cold winters (down to approximately -40°C) coupled with low PM(2.5) concentrations present a challenge for continuous measurements. Both the tapered element oscillating microbalance (TEOM), operated at 40°C (i.e., TEOM(40)), and Synchronized Hybrid Ambient Real-time Particulate (SHARP, a Federal Equivalent Method [FEM]), were compared with a Partisol PM(2.5) U.S. Federal Reference Method (FRM) sampler. While hourly TEOM(40) PM(2.5) were consistently ~20-50% lower than that of SHARP, no statistically significant differences were found between the 24-hr averages for FRM and SHARP. Orthogonal regression (OR) equations derived from FRM and TEOM(40) were used to adjust the TEOM(40) (i.e., TEOM(adj)) and improve its agreement with FRM, particularly for the cold season. The 12-year-long hourly TEOM(adj) measurements from 1999 to 2011 based on the OR equations between SHARP and TEOM(40) were derived from the 2-year (2011-2013) collocated measurements. The trend analysis combining both TEOM(adj) and SHARP measurements showed a statistically significant decrease in PM(2.5) concentrations with a seasonal slope of -0.15 μg m(-3) yr(-1) from 1999 to 2014., Implications: Consistency in PM(2.5) measurements are needed for trend analysis. Collocated comparison among the three PM(2.5) monitors demonstrated the difference between FRM and TEOM, as well as between SHARP and TEOM. The orthogonal regressions equations can be applied to correct historical TEOM data to examine long-term trends within the network.

Unlabelled: Geological samples were collected from 27 representative locations in the Athabasca Oil Sands Region (AOSR) in Alberta, Canada. These samples were resuspended onto filter substrates for PM2.5 and PM10 size fractions. Samples were analyzed for 229 chemical species, consisting of elements, ions, carbon, and organic compounds. These chemical species are normalized to gravimetric mass to derive individual source profiles. Individual profiles were grouped into six categories typical of those used in emission inventories: paved road dust, unpaved road dust close to and distant from oil sand operations, overburden soil, tailings sands, and forest soils. Consistent with their geological origin, the major components are minerals, organic and elemental carbon, and ions. The sum of five major elements (i.e., Al, Si, K, Ca, and Fe) and their oxidized forms account for 25-40% and 45-82% of particulate matter (PM) mass, respectively. Si is the most abundant element, averaging 17-18% in the Facility (oil sand operations) and 23-27% in the Forest profiles. Organic carbon is the second most abundant species, averaging 9-11% in the Facility and 5-6% in the Forest profiles. Elemental carbon abundance is 2-3 times higher in Facility than Forest profiles. Sulfate abundance is ~7 times higher in the Facility than in the Forest profiles. The ratios of cation/anion and base cation (sum of Na+, Mg2+, K+, and Ca2+)/nitrogen- and sulfur-containing ions (sum of NH4+, NO2-, NO3-, and SO4(2-)) exceed unity, indicating that the soils are basic. Lead (Pb) isotope ratios of facility soils are similar to the AOSR stack and diesel emissions, while those of forest soils have much lower 206Pb/207Pb and 208Pb/207Pb ratios. High-molecular-weight n-alkanes (C25-C40), hopanes, and steranes are more than an order of magnitude more abundant in Facility than Forest profiles. These differences may be useful for separating anthropogenic from natural sources of fugitive dust at receptors., Implications: Several organic compounds typical of combustion emissions and bitumen are enriched relative to forest soils for fugitive dust sources near oil sands operations, consistent with deposition uptake by biomonitors. AOSR dust samples are alkaline, not acidic, indicating that potential acid deposition is neutralized. Chemical abundances are highly variable within emission inventory categories, implying that more specific subcategories can be defined for inventory speciation.

Unlabelled: Positive matrix factorization (PMF) and effective variance (EV) solutions to the chemical mass balance (CMB) were applied to PM(2.5) (particulate matter with an aerodynamic diameter <2.5 μm) mass and chemically speciated measurements for samples taken from 2008 to 2010 at the Atlanta, Georgia, and Birmingham, Alabama, sites. Commonly measured PM(2.5) mass, elemental, ionic, and thermal carbon fraction concentrations were supplemented with detailed nonpolar organic speciation by thermal desorption-gas chromatography/mass spectrometry (TD-GC/MS). Source contribution estimates were calculated for motor vehicle exhaust, biomass burning, cooking, coal-fired power plants, road dust, vegetative detritus, and secondary sulfates and nitrates for Atlanta. Similar sources were found for Birmingham, with the addition of an industrial source and the separation of biomass burning into open burning and residential wood combustion. EV-CMB results based on conventional species were qualitatively similar to those estimated by PMF-CMB. Secondary ammonium sulfate was the largest contributor, accounting for 27-38% of PM(2.5), followed by biomass burning (21-24%) and motor vehicle exhaust (9-24%) at both sites, with 4-6% of PM(2.5) attributed to coal-fired power plants by EV-CMB. Including organic compounds in the EV-CMB reduced the motor vehicle exhaust and biomass burning contributions at both sites, with a 13-23% deficit for PM(2.5) mass. The PMF-CMB solution showed mixing of sources within the derived factors, both with and without the addition of speciated organics, as is often the case with complex source mixtures such as those at these urban-scale sites. The nonpolar TD-GC/MS compounds can be obtained from existing filter samples and are a useful complement to the elements, ions, and carbon fractions. However, they should be supplemented with other methods, such as TD-GC/MS on derivitized samples, to obtain a wider range of polar compounds such as sterols, sugars, and organic acids. The PMF and EV solutions to the CMB equations are complementary to, rather than replacements for, each other, as comparisons of their results reveal uncertainties that are not otherwise evident., Implications: Organic markers can be measured on currently acquired PM(2.5) filter samples by thermal methods. These markers can complement element, ion, and carbon fraction measurements from long-term speciation networks. Applying the positive matrix factorization and effective variance solutions for the chemical mass balance equations provides useful information on the accuracy of the source contribution estimates. Nonpolar compounds need to be complemented with polar compounds to better apportion cooking and secondary organic aerosol contributors.

PM2.5 (particulate matter with an aerodynamic diameter <2.5 microm) samples (n = 58) collected every sixth day in Xi'an, China, from 5 July 2008 to 27 June 2009 are analyzed for levoglucosan (1,6-anhydro-beta-D-glucopyranose) to evaluate the impacts of biomass combustion on ambient concentrations. Twenty-four-hour levoglucosan concentrations displayed clear summer minima and winter maxima that ranged from 46 to 1889 ng m(-3), with an average of 428 +/- 399 ng m(-3). Besides agricultural burning, biomass/biofuel combustion for household heating with straws and branches appears to be of regional importance during the heating season in northwestern China. Good correlations (0.70 < R < 0.91) were found between levoglucosan relative to water- soluble K+, Cl-, organic carbon (OC), elemental carbon (EC), and glyoxal. The highest levoglucosan/OC ratio of2.3% wasfound in winter, followed by autumn (1.5%). Biomass burning contributed to 5.1-43.8% of OC (with an average of 17.6 +/- 8.4%).

The 2012 Critical Review Discussion complements Wilson, (2012), provides pointers to more detailed treatments of different topics and adds additional dimensions to the area of "energy". These include broader aspects of technologies driven by fuel resources and environmental issues, the concept of energy technology innovation, evolution in transportation resources, and complexities of energy policies addressing carbon taxes or carbon trading. National and global energy data bases are identified and evaluated and conversion factors are given to allow their comparability.

Unlabelled: PM2.5 in 14 of China's large cities achieves high concentrations in both winter and summer with averages > 100 microg m(-3) being common occurrences. A grand average of 15 microg m(-3) was found for all cities, with a minimum of 27 microg m(-3) measured at Qingdao during summer and a maximum of 356 microg m(-3) at Xi 'an during winter. Both primary and secondary PM2.5 are important contributors at all of the cities and during both winter and summer. While ammonium sulfate is a large contributor during both seasons, ammonium nitrate contributions are much larger during winter. Lead levels are still high in several cities, reaching an average of 1.68 microg m(-3) in Xi 'an. High correlations of lead with arsenic and sulfate concentrations indicate that much of it derives from coal combustion, rather than leaded fuels, which were phased out by calendar year 2000. Although limited fugitive dust markers were available, scaling of iron by its ratios in source profiles shows -20% of PM2.5 deriving from fugitive dust in most of the cities. Multipollutant control strategies will be needed that address incomplete combustion of coal and biomass, engine exhaust, and fugitive dust, as well as sulfur dioxide, oxides of nitrogen, and ammonia gaseous precursors for ammonium sulfate and ammonium nitrate., Implications: PM2.5 mass and chemical composition show large contributions from carbon, sulfate, nitrate, ammonium, and fugitive dust during winter and summer and across fourteen large cities. Multipollutant control strategies will be needed that address both primary PM2.5 emissions and gaseous precursors to attain China's recently adopted PM2.5 national air quality standards.

Chemical mass balance (CMB) and trajectory receptor models were applied to speciated particulate matter with aerodynamic diameter < or =2.5 microm (PM2.5) measurements from Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network across the state of Minnesota as part of the Minnesota PM2.5 Source Apportionment Study (MPSAS). CMB equations were solved by the Unmix, positive matrix factorization (PMF), and effective variance (EV) methods, giving collective source contribution and uncertainty estimates. Geological source profiles developed from local dust materials were either incorporated into the EV-CMB model or used to verify factors derived from Unmix and PMF. Common sources include soil dust, calcium (Ca)-rich dust, diesel and gasoline vehicle exhausts, biomass burning, secondary sulfate, and secondary nitrate. Secondary sulfate and nitrate aerosols dominate PM2.5 mass (50-69%). Mobile sources outweigh area sources at urban sites, and vice versa at rural sites due to traffic emissions. Gasoline and diesel contributions can be separated using data from the STN, despite significant uncertainties. Major differences between MPSAS and earlier studies on similar environments appear to be the type and magnitude of stationary sources, but these sources are generally minor (<7%) in this and other studies. Ensemble back-trajectory analysis shows that the lower Midwestern states are the predominant source region for secondary ammoniated sulfate in Minnesota. It also suggests substantial contributions of biomass burning and soil dust from out-of-state on occasions, although a quantitative separation of local and regional contributions was not achieved in the current study. Supplemental materials are available for this article. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for a summary of input data, Unmix and PMF factor profiles, and additional maps.

Day- and nighttime total suspended particulate matter was collected inside and outside Emperor Qin's Terra-Cotta Museum in winter and summer 2008. The purpose was to characterize the winter and summer differences of indoor airborne particles in two display halls with different architectural and ventilation conditions, namely the Exhibition Hall and Pit No. 1. The morphology and elemental composition of two season samples were investigated using scanning electron microscopy and energy dispersive X-ray spectrometry. It is found that the particle size, particle mass concentration, and particle type were associated with the visitor numbers in the Exhibition Hall and with the natural ventilation in Pit No. 1 in both winter and summer. Evident winter and summer changes in the composition and physicochemical properties of the indoor suspended particulate matters were related to the source emission and the meteorological conditions. Particle mass concentrations in both halls were higher in winter than in summer. In winter, the size of the most abundant particles at the three sites were all between 0.5 and 1.0 microm, whereas in summer the peaks were all located at less than 0.5 microm. The fraction of sulfur-containing particles was 2-7 times higher in winter than in summer. In addition to the potential soiling hazard, the formation and deposition of sulfur-containing particles in winter may lead to the chemical and physical weathering of the surfaces of the terra-cotta statues.

The main objective of this study was to investigate the capabilities of the receptor-oriented inverse mode Lagrangian Stochastic Particle Dispersion Model (LSPDM) with the 12-km resolution Mesoscale Model 5 (MM5) wind field input for the assessment of source identification from seven regions impacting two receptors located in the eastern United States. The LSPDM analysis was compared with a standard version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) single-particle backward-trajectory analysis using inputs from MM5 and the Eta Data Assimilation System (EDAS) with horizontal grid resolutions of 12 and 80 km, respectively. The analysis included four 7-day summertime events in 2002; residence times in the modeling domain were computed from the inverse LSPDM runs and HYPSLIT-simulated backward trajectories started from receptor-source heights of 100, 500, 1000, 1500, and 3000 m. Statistics were derived using normalized values of LSPDM- and HYSPLIT-predicted residence times versus Community Multiscale Air Quality model-predicted sulfate concentrations used as baseline information. From 40 cases considered, the LSPDM identified first- and second-ranked emission region influences in 37 cases, whereas HYSPLIT-MM5 (HYSPLIT-EDAS) identified the sources in 21 (16) cases. The LSPDM produced a higher overall correlation coefficient (0.89) compared with HYSPLIT (0.55-0.62). The improvement of using the LSPDM is also seen in the overall normalized root mean square error values of 0.17 for LSPDM compared with 0.30-0.32 for HYSPLIT. The HYSPLIT backward trajectories generally tend to underestimate near-receptor sources because of a lack of stochastic dispersion of the backward trajectories and to overestimate distant sources because of a lack of treatment of dispersion. Additionally, the HYSPLIT backward trajectories showed a lack of consistency in the results obtained from different single vertical levels for starting the backward trajectories. To alleviate problems due to selection of a backward-trajectory starting level within a large complex set of 3-dimensional winds, turbulence, and dispersion, results were averaged from all heights, which yielded uniform improvement against all individual cases.

The Chinese Loess Plateau (CLP) receives and potentially contributes to Asian dust storms that affect particulate matter (PM) concentrations, visibility, and climate. Loess on the CLP has experienced little weathering effect and is regarded as an ideal record to represent geochemical characteristics of Asian paleo dust. Samples were taken from 2-, 9-, and 15-m depths (representing deposition periods from approximately 12,000 to approximately 200,000 yr ago) in the Xi Feng loess profile on the CLP. The samples were resuspended and then sampled through total suspended particulates (TSP), PM10, PM2.5, and PM1 (PM with aerodynamic diameters < approximately 30, 10, 2.5, and 1 microm, respectively) inlets onto filters for mass, elemental, ionic, and carbon analyses using a Desert Research Institute resuspension chamber. The elements Si, Ca, Al, Fe, K, Mg, water-soluble Ca (Ca2+), organic carbon, and carbonate carbon are the major constituents (> 1%) in loess among the four PM fractions (i.e., TSP, PM10, PM2.5, and PM1). Much of Ca is water soluble and corresponds with measures of carbonate, indicating that most of the calcium is in the form of calcium carbonate rather than other calcium minerals. Most of the K is insoluble, indicating that loess can be separated from biomass burning contributions when K+ is measured. The loess has elemental abundances similar to those of the upper continental crust (UCC) for Mg, Fe, Ti, Mn, V, Cr, and Ni, but substantially different ratios for other elements such as Ca, Co, Cu, As, and Pb. These suggest that the use of UCC as a reference to represent pure or paleo Asian dust needs to be further evaluated. The aerosol samples from the source regions have similar ratios to loess for crustal elements, but substantially different ratios for species from anthropogenic sources (e.g., K, P, V, Cr, Cu, Zn, Ni, and Pb), indicating that the aerosol samples from the geological-source-dominated environment are not a "pure" soil product as compared with loess.

Light attenuation (b(att)) measured from filter light transmission is compared with elemental carbon (EC) measurements for more than 180,000 collocated PM2.5 (particulate matter [PM] < or = 2.5 microm in aerodynamic diameter) and PM10 (PM < or = 10 microm in aerodynamic diameter) samples from nearly 200 U.S. locations during the past 2 decades. Although there are theoretical reasons for expecting highly variable relationships between b(att) and EC (such as the effects of "brown carbon" and iron oxides in PM2.5), reasonable correlations are found. These correlations are not a strong function of season or location (e.g., rural vs. urban). Median EC concentrations can be predicted from filter transmittance measurements to within +/- 15-30%. Although EC predicted from b(att) shows larger uncertainties (30-60%), especially at concentrations less than 0.3 microg/m3, the consistent mass absorption efficiency (sigm(att)) derived from the regression analysis demonstrates the feasibility of using b(att) as a surrogate for EC. This study demonstrates that a constant factor of 0.1 g/m2 (equivalent to the 10 m2/g sigma(att) used in the Interagency Monitoring of Protected Visual Environments chemical extinction formula) can be used to estimate EC concentrations from b(att) through a Teflon-membrane filter sample. Greater accuracy is achieved with site-specific sigma(att) derived from a period with collocated EC measurements.

Particulate black or elemental carbon (EC) (black carbon [BC]) and organic carbon (OC) affect climate, visibility, and human health. Several "top-down" and "bottom-up" global emission inventories for these components have compiled country-wide emission factors, source profiles, and activity levels that do not necessarily reflect local conditions. Recent estimates of global BC and OC emissions range from 8 to 24 and 33 to 62 Tg (1012 g) per year, respectively. U.S. BC emissions account for 5.6% of the global total emissions. Uncertainties in global BC emission estimates are a factor of 2 or more. The U.S. National Emissions Inventory is well documented, but its major source categories are not easily related to EC- and OC-emitting source subcategories. California's bottom-up emission inventory is easily accessible at many levels of detail and provides an example of how sources can be regrouped for speciated emission rates. PM2.5 (particulate matter with aerodynamic diameters < 2.5 microm) emissions from these categories are associated with EC and OC source profiles to generate California's speciated emissions. A BC inventory for California of 38,731 t/yr was comparable to the 33,281 t/yr estimated from a bottom-up global BC inventory. However, further examination showed substantial differences among subcategories, with the global inventory BC from fossil fuel combustion at two-thirds that from the California inventory and the remainder attributed to biomass burning. Major discrepancies were found for directly emitted OC, with the global inventory estimating more than twice that of the California inventory. Most of the discrepancy was due to differences in open biomass burning (wildfires and agricultural waste) for which carbon emissions are highly variable. BC and OC emissions are sensitive to the availability and variability of existing source profiles, and profiles more specific to fuels and operating conditions are needed to increase emission accuracy.

The ability of receptor models to estimate regional contributions to fine particulate matter (PM 2.5 ) was assessed with synthetic, speciated datasets at Brigantine National Wildlife Refuge (BRIG) in New Jersey and Great Smoky Mountains National Park (GRSM) in Tennessee. Synthetic PM 2.5 chemical concentrations were generated for the summer of 2002 using the Community Multiscale Air Quality (CMAQ) model and chemically speciated PM 2.5 source profiles from the U.S. Environmental Protection Agency (EPA)'s SPECIATE and Desert Research Institute's source profile databases. CMAQ estimated the "true" contributions of seven regions in the eastern United States to chemical species concentrations and individual source contributions to primary PM 2.5 at both sites. A seven-factor solution by the positive matrix factorization (PMF) receptor model explained approximately 99% of the variability in the data at both sites. At BRIG, PMF captured the first four major contributing sources (including a secondary sul-fate factor), although diesel and gasoline vehicle contributions were not separated. However, at GRSM, the resolved factors did not correspond well to major PM 2.5 sources. There were no correlations between PMF factors and regional contributions to sulfate at either site. Unmix produced five- and seven-factor solutions, including a secondary sulfate factor, at both sites. Some PMF factors were combined or missing in the Unmix factors. The trajectory mass balance regression (TMBR) model apportioned sulfate concentrations to the seven source regions using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) trajectories based on Meteorological Model Version 5 (MM5) and Eta Data Simulation System (EDAS) meteorological input. The largest estimated sulfate contributions at both sites were from the local regions; this agreed qualitatively with the true regional apportionments. Estimated regional contributions depended on the starting elevation of the trajectories and on the meteorological input data.

To elucidate the relationship between factors resolved by the positive matrix factorization (PMF) receptor model and actual emission sources and to refine the PMF modeling strategy, speciated PM2.5 (particulate matter with aerodynamic diameter < 2.5 microm) data generated from a state-of-the-art chemical transport model for two rural sites in the eastern United States are subjected to PMF analysis. In addition to chi2 and R2 used to infer the quality of fitting, the interpretability of PMF factors with respect to known primary and secondary sources is evaluated using a root mean square difference analysis. For the most part, factors are found to represent imperfect combinations of sources, and the optimal number of factors should be just adequate to explain the input data (e.g., R2 > 0.95). Retaining more factors in the model does not help resolve minor sources, unless temporal resolution of the data is increased, thus allowing more information to be used by the model. If guided with a priori knowledge of source markers and/or special events, rotation of factors leads to more interpretable PMF factors. The choice of uncertainty weighting coefficients greatly influences the PMF modeling results, but it cannot usually be determined for simulated or real-world data. A simple test is recommended to check whether the weighting coefficients are suitable. However, uncertainties in the data divert PMF solutions even when the optimal weighting coefficients and number of factors are in place.

To elucidate the relationship between factors resolved by the positive matrix factorization (PMF) receptor model and actual emission sources and to refine the PMF modeling strategy, speciated PM 2.5 (particulate matter with aerodynamic diameter <2.5 μm) data generated from a state-of-the-art chemical transport model for two rural sites in the eastern United States are subjected to PMF analysis. In addition to χ- 2 and R 2 used to infer the quality of fitting, the interpretability of PMF factors with respect to known primary and secondary sources is evaluated using a root mean square difference analysis. For the most part, factors are found to represent imperfect combinations of sources, and the optimal number of factors should be just adequate to explain the input data (e.g., R 2 > 0.95). Retaining more factors in the model does not help resolve minor sources, unless temporal resolution of the data is increased, thus allowing more information to be used by the model. If guided with a priori knowledge of source markers and/or special events, rotation of factors leads to more interpretable PMF factors. The choice of uncertainty weighting coefficients greatly influences the PMF modeling results, but it cannot usually be determined for simulated or real-world data. A simple test is recommended to check whether the weighting coefficients are suitable. However, uncertainties in the data divert PMF solutions even when the optimal weighting coefficients and number of factors are in place.

The In-Plume Emission Test Stand (IPETS) characterizes gaseous and particulate matter (PM) emissions from combustion sources in real time. Carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), and other gases are quantified with a closed-path Fourier transform infrared spectrometer (FTIR). Particle concentrations, chemical composition, and other particle properties are characterized with an electrical low-pressure impactor (ELPI), a light-scattering particle detector, an optical particle counter, and filter samples amenable to different laboratory analysis. IPETS measurements of fuel-based emission factors for a diesel generator are compared with those from a Mobile Emissions Laboratory (MEL). IPETS emission factors ranged from 0.3 to 11.8, 0.2 to 3.7, and 22.2 to 32.8 g/kg fuel for CO, NO2, and NO, respectively. IPETS PM emission factors ranged from 0.4 to 1.4, 0.3 to 1.8, 0.3 to 2.2, and 1 to 3.4 g/kg fuel for filter, photoacoustic, nephelometer, and impactor measurements, respectively. Observed linear regression statistics for IPETS versus MEL concentrations were as follows: CO slope = 1.1, r2 = 0.99; NO slope = 1.1, r2 = 0.92; and NO2 slope = 0.8, r2 = 0.96. IPETS versus MEL PM regression statistics were: filter slope = 1.3, r2 = 0.80; ELPI slope = 1.7, r2 = 0.87; light-scattering slope = 2.7, r2 = 0.92; and photoacoustic slope = 2.1, r2 = 0.91. Lower temperatures in the dilution air (approximately 25 degrees C for IPETS vs. approximately 50 degrees C for MEL) may result in greater condensation of semi-volatile compounds on existing particles, thereby explaining the 30% difference for filters. The other PM measurement devices are highly correlated with the filter, but their factory-default PM calibration factors do not represent the size and optical properties of diesel exhaust. They must be normalized to a simultaneous filter measurement.

Source apportionment analyses were carried out by means of receptor modeling techniques to determine the contribution of major fine particulate matter (PM2.5) sources found at six sites in Mexico City. Thirty-six source profiles were determined within Mexico City to establish the fingerprints of particulate matter sources. Additionally, the profiles under the same source category were averaged using cluster analysis and the fingerprints of 10 sources were included. Before application of the chemical mass balance (CMB), several tests were carried out to determine the best combination of source profiles and species used for the fitting. CMB results showed significant spatial variations in source contributions among the six sites that are influenced by local soil types and land use. On average, 24-hr PM2.5 concentrations were dominated by mobile source emissions (45%), followed by secondary inorganic aerosols (16%) and geological material (17%). Industrial emissions representing oil combustion and incineration contributed less than 5%, and their contribution was higher at the industrial areas of Tlalnepantla (11%) and Xalostoc (8%). Other sources such as cooking, biomass burning, and oil fuel combustion were identified at lower levels. A second receptor model (principal component analysis, [PCA]) was subsequently applied to three of the monitoring sites for comparison purposes. Although differences were obtained between source contributions, results evidence the advantages of the combined use of different receptor modeling techniques for source apportionment, given the complementary nature of their results. Further research is needed in this direction to reach a better agreement between the estimated source contributions to the particulate matter mass.

Although emissions of air pollutants from some military tactical equipment are not subject to the emissions standards, local communities near military bases must conform to the National Ambient Air Quality Standards. Military diesel generators are widely used in training. A portable in-plume system was used to measure fuel-based emission factors (EFs) for particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), and hydrocarbons (HCs) for 30-, 60-, and 100-kW generators at five load levels and for cold starts. It was found that EFs depend on multiple parameters including engine size, engine load, unit age, and total running hours. The average CO EF of generators tested was 5% lower, and the average NOx EF was 63% lower than AP-42 estimates; average PM EF was 80% less than the AP-42 estimates. A 2002 model-year 60-kW engine produced 25% less PM than a 1995 engine of the same family with similar running hours. CO EFs decrease with increasing engine load, NOx EFs increase up to mid-loads and decrease slightly at high loads, PM EFs increase with loads for 30- and 60-kW engines. CO and PM have higher EFs and NOx has a lower EF during cold starts than during hot-stabilized operation. PM chemical source profiles were also examined.

The Critical Review of Hoff and Christopher, along with the discussants, provides an important perspective on the interface between satellite measurement science and air quality observations. A top-down picture of the usefulness of satellite observations in terms of air quality regulatory and technical support requirements can be summarized. The air quality requirements are (1) determination of compliance with the ambient air quality standards, (2) inference of human and ecosystem exposure, (3) identification of intra- and intercontinental events relevant to EE, (4) establishment of trends in ambient concentrations relevant to accountability, (5) regulatory and forecast model applications, and (6) extension of fundamental knowledge relevant to air quality. Each of these topics is important to air quality management, and each has detailed technical issues associated with spatial and temporal resolution, accuracy, and precision, etc. In any case, one can summarize the broad capabilities of measurement systems to address these requirements as listed in Table 1. From this rather superficial summary table, investigators should be encouraged to forward increased interaction between the various measurement communities and to facilitate the utility of a comprehensive portfolio of measurements and adjunct analyses for improved air quality applications. The Critical Review has done much to educate air quality scientists on the possibilities for using satellite remote sensing for various purposes. However, space scientists also need a better education on air quality science. Recently published reviews on PM air quality measurements are available that complement the Hoff-Christopher paper on this topic. The need for greater collaboration of air quality and space scientists is evident in an article published in the July issue of the journal. Al-Hamdan et al. provide an interesting and useful analysis of relationships between surface air quality and space-based satellite AOD to estimate human exposure. They obtain mostly urban PM data from EPA's Air Quality System (AQS), but they neglect the potentially more useful PM2.5 and chemical speciation data from the nonurban Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Southeastern Aerosol Research and Characterization (SEARCH) networks. They correlate PM2.5 mass with optical depth, although visibility assessments show that light extinction is better represented by a weighted sum of PM2.5 sulfate, nitrate, organic carbon, elemental carbon, and soil dust. Their comparison of hourly measurements with filter measurements does not specify the source of the hourly values as TEOM or BAM. Spatial outliers for ground-level measurements are removed to improve the correlation of PM2.5 with AOD, although these "outliers" are probably real values that relate to human exposure or a nearby source effect. The point here is not to overly criticize a good publication that will be highly cited. The intent is to demonstrate the value of air quality and space scientists working together more closely on this topic. This is something the review authors alluded to in their review, but if, as they concluded, the "promised land" has not been reached, then perhaps it is an appropriate time for the atmospheric community to ask, "Can near-term satellite observations play a role in characterizing broad-based (outdoor) exposure to pollutants and consequently influence public health improvement?" and, if so, then, "What comprehensive, integrated system is needed if satellite observations are to be used together with ground-based observations and modeling to continue improving air quality management options?"

Volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) adsorb to quartz fiber filters during fine and coarse particulate matter (PM2.5 and PM10, respectively) sampling for thermal/optical carbon analysis that measures organic carbon (OC) and elemental carbon (EC). Particulate SVOCs can evaporate after collection, with a small portion adsorbed within the filter. Adsorbed organic gases are measured as particulate OC, so passive field blanks, backup filters, prefilter organic denuders, and regression methods have been applied to compensate for positive OC artifacts in several long-term chemical speciation networks. Average backup filter OC levels from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network were approximately 19% higher than field blank values. This difference is within the standard deviation of the average and likely results from low SVOC concentrations in the rural to remote environments of most IMPROVE sites. Backup filters from an urban (Fort Meade, MD) site showed twice the OC levels of field blanks. Sectioning backup filters from top to bottom showed nonuniform OC densities within the filter, contrary to the assumption that VOCs and SVOCs on a backup filter equal those on the front filter. This nonuniformity may be partially explained by evaporation and readsorption of vapors in different parts of the front and backup quartz fiber filter owing to temperature, relative humidity, and ambient concentration changes throughout a 24-hr sample duration. OC-PM2.5 regression analysis and organic denuder approaches demonstrate negative sampling artifact from both Teflon membrane and quartz fiber filters.

A study using two stack-sampling methodologies for collecting particulate matter (PM) emissions was conducted using a hot filter followed by a cold impinger sampling train and a dilution sampler. Samples were collected from ferrous iron metal casting processes that included pouring molten iron into a sand mold containing an organic binder, metal cooling, removal of the sand from the cooled casting (shakeout), and postshakeout cooling. The shakeout process contributed more to PM emissions than the metal pouring and cooling processes. Particulate matter less than 2.5 microm in aerodynamic diameter (PM2.5) mass emissions for the entire casting cycle ranged from 3.4 to 4.7 lb/t of metal for the hot filter/impinger method and from 0.8 to 1.8 lb/t of metal for the dilution method. Most of the difference was due to PM captured by the impingers, much of which was probably dissolved gases rather than condensable vapors. Of the PM fraction captured by the impingers, 96-98% was organic in nature. The impinger PM fraction contributed 32-38% to the total suspended particle mass and caused a factor of 2-4 positive bias for PM2.5 emissions. For the pouring and cooling processes only, the factor increased to over seven times.

Receptor models are used to identify and quantify source contributions to particulate matter and volatile organic compounds based on measurements of many chemical components at receptor sites. These components are selected based on their consistent appearance in some source types and their absence in others. UNMIX, positive matrix factorization (PMF), and effective variance are different solutions to the chemical mass balance (CMB) receptor model equations and are implemented on available software. In their more general form, the CMB equations allow spatial, temporal, transport, and particle size profiles to be combined with chemical source profiles for improved source resolution. Although UNMIX and PMF do not use source profiles explicitly as input data, they still require measured profiles to justify their derived source factors. The U.S. Supersites Program provided advanced datasets to apply these CMB solutions in different urban areas. Still lacking are better characterization of source emissions, new methods to estimate profile changes between source and receptor, and systematic sensitivity tests of deviations from receptor model assumptions.

Recent improvements in integrated and continuous PM2.5 mass and chemical measurements from the Supersite program and related studies in the past decade are summarized. Analytical capabilities of the measurement methods, including accuracy, precision, interferences, minimum detectable levels, comparability, and data completeness are documented. Upstream denuders followed by filter packs in integrated samplers allow an estimation of sampling artifacts. Efforts are needed to: (1) address positive and negative artifacts for organic carbon (OC), and (2) develop carbon standards to better separate organic versus elemental carbon (EC) under different temperature settings and analysis atmospheres. Advances in thermal desorption followed by gas chromatography/ mass spectrometry (GC/MS) provide organic speciation of approximately 130 nonpolar compounds (e.g., n-alkanes, alkenes, hopanes, steranes, and polycyclic aromatic hydrocarbons [PAHs]) using small portions of filters from existing integrated samples. Speciation of water-soluble OC (WSOC) using ion chromatography (IC)-based instruments can replace labor-intensive solvent extraction for many compounds used as source markers. Thermal gas-based continuous nitrate and sulfate measurements underestimate filter ions by 10-50% and require calibration against on-site filter-based measurements. IC-based instruments provide multiple ions and report comparable (+/-10%) results to filter-based measurements. Maintaining a greater than 80% data capture rate in continuous instruments is labor intensive and requires experienced operators. Several instruments quantify black carbon (BC) by optical or photoacoustic methods, or EC by thermal methods. A few instruments provide real-time OC, EC, and organic speciation. BC and EC concentrations from continuous instruments are highly correlated but the concentrations differ by a factor of two or more. Site- and season-specific mass absorption efficiencies are needed to convert light absorption to BC. Particle mass spectrometers, although semiquantitative, provide much information on particle size and composition related to formation, growth, and characteristics over short averaging times. Efforts are made to quantify mass by collocating with other particle sizing instruments. Common parameters should be identified and consistent approaches are needed to establish comparability among measurements.

Thermally derived carbon fractions including organic carbon (OC) and elemental carbon (EC) have been reported for the U.S. Interagency Monitoring of PROtected Visual Environments (IMPROVE) network since 1987 and have been found useful in source apportionment studies and to evaluate quartz-fiber filter adsorption of organic vapors. The IMPROVE&#95;A temperature protocol defines temperature plateaus for thermally derived carbon fractions of 140 degrees C for OC1, 280 degrees C for OC2, 480 degrees C for OC3, and 580 degrees C for OC4 in a helium (He) carrier gas and 580 degrees C for EC1, 740 degrees C for EC2, and 840 degrees C for EC3 in a 98% He/2% oxygen (O2) carrier gas. These temperatures differ from those used previously because new hardware used for the IMPROVE thermal/optical reflectance (IMPROVE&#95;TOR) protocol better represents the sample temperature than did the old hardware. A newly developed temperature calibration method demonstrates that these temperatures better represent sample temperatures in the older units used to quantify IMPROVE carbon fractions from 1987 through 2004. Only the thermal fractions are affected by changes in temperature. The OC and EC by TOR are insensitive to the change in temperature protocol, and therefore the long-term consistency of the IMPROVE database is conserved. A method to detect small quantities of O2 in the pure He carrier gas shows that O2 levels above 100 ppmv also affect the comparability of thermal carbon fractions but have little effect on the IMPROVE&#95;TOR split between OC and EC.

This paper presents the design and performance of a compact dilution sampler (CDS) for characterizing fine particle emissions from stationary sources. The sampler is described, along with the methodology adopted for its use. Dilution sampling has a number of advantages, including source emissions that are measured under conditions simulating stack gas entry and mixing in the ambient atmosphere. This is particularly important for characterizing the semivolatile species in effluents as a part of particulate emissions. The CDS characteristics and performance are given, along with sampling methodology. The CDS was compared with a reference dilution sampler. The results indicate that the two designs are comparable for tests on gas-fired units and a diesel electrical generator. The performance data indicate that lower detection limits can be achieved relative to current regulatory methods for particulate emissions. Test data for the fine particulate matter (PM2.5) emissions are provided for comparison with U.S. Environment Protection Agency (EPA) Conditional Test Method 040 for filterable particulate matter (FPM) and the EPA Method 202 for condensable particulate matter. This comparison showed important differences between methods, depending on whether a comparison is done between in situ FPM determinations or the sum of such values with condensable PM from liquid filled impingers chilled in an ice bath. These differences are interpretable in the light of semivolatile material present in the stack effluent and, in some cases, differences in detection and quantification limits. Determination of emissions from combustors using liquid fuels can be readily achieved using 1-hr sampling with the CDS. Emissions from gasfired combustors are very low, requiring careful attention to sample volumes. Sampling volumes corresponding with 6-hr operation were used for the combined mass and broad chemical speciation. Particular attention to dilution sampler operation with clean dilution air also is essential for gas-fired sources.

With the recent focus on fine particle matter (PM2.5), new, self-consistent data are needed to characterize emissions from combustion sources. Such data are necessary for health assessment and air quality modeling. To address this need, emissions data for gas-fired combustors are presented here, using dilution sampling as the reference. The dilution method allows for collection of emitted particles under conditions simulating cooling and dilution during entry from the stack into the air. The sampling and analysis of the collected particles in the presence of precursor gases, SO2 nitrogen oxide, volatile organic compound, and NH3 is discussed; the results include data from eight gas fired units, including a dual-fuel institutional boiler and a diesel engine powered electricity generator. These data are compared with results in the literature for heavy-duty diesel vehicles and stationary sources using coal or wood as fuels. The results show that the gas-fired combustors have very low PM2.5 mass emission rates in the range of approximately 10(-4) lb/million Btu (MMBTU) compared with the diesel backup generator with particle filter, with approximately 5 x 10(-3) lb/MMBTU. Even higher mass emission rates are found in coal-fired systems, with rates of approximately 0.07 lb/MMBTU for a bag-filter-controlled pilot unit burning eastern bituminous coal. The characterization of PM2.5 chemical composition from the gas-fired units indicates that much of the measured primary particle mass in PM2.5 samples is organic or elemental carbon and, to a much less extent, sulfate. Metal emissions are quite low compared with the diesel engines and the coal- or wood-fueled combustors. The metals found in the gas-fired combustor particles are low in concentration, similar in concentration to ambient particles. The interpretation of the particulate carbon emissions is complicated by the fact that an approximately equal amount of particulate carbon (mainly organic carbon) is found on the particle collector and a backup filter. It is likely that measurement artifacts, mostly adsorption of volatile organic compounds on quartz filters, are positively biasing "true" particulate carbon emission results.

This study tested the feasibility of using pyrolysis (Py)-gas chromatography (GC)/mass spectrometry (MS) to obtain organic chemical species data suitable for source apportionment modeling of soil-derived coarse particulate matter (PM10) dust on ambient filters. A laboratory resuspension apparatus was used with known soils to generate simulated receptor filter samples loaded with approximately 0.4 mg of PM10 dust, which is within the range of mass loading on ambient filters. Py-GC/MS at 740 degrees C generated five times more resolvable compounds than were obtained with thermal desorption GC/MS at 315 degrees C. The identified compounds were consistent with literature from Py experiments using larger samples of bulk soils. A subset of 91 organic species out of the 178 identified Py products was used as input to CMB8 software in a demonstration of source apportionment using laboratory-generated mixtures simulating ambient filter samples. The 178 quantified organic species obtained by Py of soil samples is an improvement compared with the 38 organic species obtained by thermal desorption of soils and the four functionally defined organic fractions reported by thermal/ optical reflectance. Significant differences in the concentration of specific species were seen between samples from different sites, both geographically distant and close, using analysis of variance and cluster analysis. This feasibility study showed that Py-GC/MS can generate useful source profile data for receptor modeling and justifies continued method development.

Results from six continuous and semicontinuous black carbon (BC) and elemental carbon (EC) measurement methods are compared for ambient samples collected from December 2003 through November 2004 at the Fresno Supersite in California. Instruments included a multi-angle absorption photometer (MAAP; lambda = 670 nm); a dual-wavelength (lambda = 370 and 880 nm) aethalometer; seven-color (lambda = 370, 470, 520, 590, 660, 880, and 950 nm) aethalometers; the Sunset Laboratory carbon aerosol analysis field instrument; a photoacoustic light absorption analyzer (lambda = 1047 nm); and the R&P 5400 ambient carbon particulate monitor. All of these acquired BC or EC measurements over periods of 1 min to 1 hr. Twenty-four-hour integrated filter samples were also acquired and analyzed by the Interagency Monitoring of Protected Visual Environments (IMPROVE) thermal/optical reflectance carbon analysis protocol. Site-specific mass absorption efficiencies estimated by comparing light absorption with IMPROVE EC concentrations were 5.5 m2/g for the MAAP, 10 m2/g for the aethalometer at a wavelength of 880 nm, and 2.3 m2/g for the photoacoustic analyzer; these differed from the default efficiencies of 6.5, 16.6, and 5 m2/g, respectively. Scaling absorption by inverse wavelength did not provide equivalent light absorption coefficients among the instruments for the Fresno aerosol measurements. Ratios of light absorption at 370 nm to those at 880 nm from the aethalometer were nearly twice as high in winter as in summer. This is consistent with wintertime contributions from vehicle exhaust and from residential wood combustion, which is believed to absorb more shorter-wavelength light. To reconcile BC and EC measurements obtained by different methods, a better understanding is needed of the wavelength dependence of light-absorption and mass-absorption efficiencies and how they vary with different aerosol composition.

Particle light scattering (Bsp) from nephelometers and fine particulate matter (PM2.5) mass determined by filter samplers are compared for summer and winter at 35 locations in and around California's San Joaquin Valley from December 2, 1999 to February 3, 2001. The relationship is described using particle mass scattering efficiency (sigmasp) derived from linear regression of Bsp on PM2.5 that can be applied to estimated PM2.5 from nephelometer data within the 24-hr filter sampling periods and between the every-6th-day sampling frequency. An average of sigmaSp = 4.9 m2/g was found for all of the sites and seasons; however, sigmasp averaged by site type and season provided better PM2.5 estimates. On average, the sigmasp was lower in summer than winter, consistent with lower relative humidities, lower fractions of hygroscopic ammonium nitrate, and higher contributions from fugitive dust. Winter average sigmasp were similar at non-source-dominated sites, ranging from 4.8 m2/g to 5.9 m2/g. The sigmasp was 2.3 m2/g at the roadside, 3.7 m2/g at a dairy farm, and 4.1 m2/g in the Kern County oilfields. Comparison of Bsp from nephelometers with and without a PM2.5 inlet at the Fresno Supersite showed that coarse particles contributed minor amounts to light scattering. This was confirmed by poorer correlations between Bsp and coarse particulate matter measured during a fall sampling period.

Continuous measurements of particle size distributions of 3-407 nm were collected from August 2002 to July 2004 at the Fresno Supersite to understand their number concentrations, size distributions, and formation processes. Measurements for fine particulate matter (PM2.5) mass, sulfate (SO4(2-)), nitrate (NO3-), black carbon (BC), particle-bound polycyclic aromatic hydrocarbons (PAHs), nitrogen oxides (NOx), carbon monoxide (CO), ozone (O3), and meteorological data (wind speed, wind direction, temperature [T], relative humidity [RH], and solar radiation) were used to determine the causes of nanoparticle (3-10 nm) and ultrafine (10-100 nm) particle events. These events were found to be divided into four types: (1) 3- to 10-nm morning nucleation; (2) 10- to 30-nm morning traffic; (3) 10- to 30-nm afternoon photochemical; and (4) 50- to 84-nm evening home heating, including residential wood combustion. Intense examples of the first type (>10(4) number [#]/cm3) were observed on 29 days, nearly always during the summer. The second type of event was observed on more than 73 days and occurred throughout the year. The third type was observed on 36 days, from spring through summer. The fourth type was found on 109 days, all of them during the winter. Although sulfur dioxide (SO2) emissions in Central California are low, the small residual amounts in gasoline and diesel fuel are apparently sufficient to initiate nucleation events. These were measured in the morning, soon after the shallow surface inversion coupled with layers aloft where nucleation probably was initiated. PM2.5 concentrations were poorly correlated with nanoparticle number.

Evaporative loss of particulate matter (with aerodynamic diameter < 2.5 microm, [PM2.5]) ammonium nitrate from quartz-fiber filters during aerosol sampling was evaluated from December 3, 1999, through February 3, 2001, at two urban (Fresno and Bakersfield) and three nonurban (Bethel Island, Sierra Nevada Foothills, and Angiola) sites in central California. Compared with total particulate nitrate, evaporative nitrate losses ranged from < 10% during cold months to > 80% during warm months. In agreement with theory, evaporative loss from quartz-fiber filters in nitric acid denuded samplers is controlled by the ambient nitric acid-to-particulate nitrate ratio, which is determined mainly by ambient temperature. Accurate estimation of nitrate volatilization requires a detailed thermodynamic model and comprehensive chemical measurements. For the 14-month average of PM2.5 acquired on Teflon-membrane filters, measured PM2.5 mass was 8-16% lower than actual PM2.5 mass owing to nitrate volatilization. For 24-hr samples, measured PM2.5 was as much as 32-44% lower than actual PM2.5 at three California Central Valley locations.

The results of a 12-month study of more than 100 solvent extractable organic compounds (SEOC) in particulate matter (PM) less than or equal to 2.5 microm (PM2.5) collected at three air monitoring stations located at roadside, urban, and rural sites in Hong Kong are reported. The total yield of SEOC that accounts for approximately 8-18% of organic carbon (OC) determined by a thermal optical transmittance method was 125-2060 ng/m3, which included 14.6-128 ng/m3 resolved aliphatic hydrocarbons, 39.4-1380 ng/m3 unresolved complex mixtures, 0.6-17.2 ng/m3 polycyclic aromatic hydrocarbons, 41.6-520 ng/m3 fatty acids, and < 0.1-12.1 ng/m3 alkanols. Distinct seasonal variations (summer/winter differences) were observed with higher concentrations of the total and each class of SEOC in the winter and lower concentrations in the summer. Spatial variations are also obvious, with the roadside samples having the highest concentrations of SEOC and the rural samples having the lowest concentrations in all seasons. Characteristic ratios of petroleum hydrocarbons, such as carbon preference index, unresolved to resolved components, and carbon number with maximum concentration, suggest that PM2.5 carbon in Hong Kong originates from both biogenic and anthropogenic sources. The proportion of SEOC in PM2.5 from anthropogenic sources is estimated.