Response

ABSTRACT

The Las Vegas Valley PM₁₀ Study was conducted during 1995 to determine the contributions to PM₁₀ aerosol from fugitive dust, motor vehicle exhaust, residential wood combustion, and secondary aerosol sources. Twenty-four-hr PM₁₀ samples were collected at two neighborhood-scale sites every sixth day for 13 months. Five week-long intensive studies were conducted over a middle-scale sub-region at 29 locations that contained many construction projects emitting fugitive dust. The study found that the zone of influence around individual emitters was less than 1 km. Most of the sampling sites in residential and commercial areas yielded equivalent PM₁₀ concentrations in the neighborhood region, even though they were more distant from each other than they were from the nearby construction sources. Based on chemical mass balance (CMB) receptor modeling, fugitive dust accounted for 80–90% of the PM₁₀, and motor vehicle exhaust accounted for 3–9% of the PM₁₀ in the Las Vegas Valley.     

Chemical characteristics and source apportionment of PM<Subscript>2.5</Subscript> using PCA/APCS,UNMIX, and PMF at an urban site of Delhi,India

The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM_2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM_2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM_2.5 was recorded as 121.9 ± 93.2 μg m^?3 (range 25.1–429.8 μg m^?3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ～17% of PM_2.5. Strong seasonal variation was observed in PM_2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM_2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM_2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM_2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM_2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM_2.5 from the north-west India and Pakistan were mostly pertinent.     

A Comparison of Filter Types in the Collection and Gravimetric Determination of Airborne Particulate Matter Less than 2.5 Microns (PM25)

ABSTRACT

Five identical, collocated, low-volume samplers were operated to collect airborne particulate matter less than 2.5 microns (PM₂₅). Five commercially available filter types were installed in the samplers to compare the gravimetric determination of PM_2.5 concentrations in the atmosphere. The filters were rotated through the five samplers for two study periods—one in summer and one in winter. The study was performed in Sheridan, WY, in close proximity to a gravimetric laboratory to minimize the introduction of errors associated with sample handling. Rigorous quality assurance procedures were employed throughout the study.Four of the five filter types provided comparable gravimetric determinations of airborne PM_2.5.     

Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks

The Minnesota Particulate Matter 2.5 (PM_2.5) Source Apportionment Study was undertaken to explore the utility of PM_2.5 mass, element, ion, and carbon measurements from long-term speciation networks for pollution source attribution. Ambient monitoring data at eight sites across the state were retrieved from the archives of the Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and analyzed by an Effective Variance – Chemical Mass Balance (EV-CMB) receptor model with region-specific geological source profiles developed in this study. PM_2.5 was apportioned into contributions of fugitive soil dust, calcium-rich dust, taconite (low grade iron ore) dust, road salt, motor vehicle exhaust, biomass burning, coal-fired utility, and secondary aerosol. Secondary sulfate and nitrate contributed strongly (49–71% of PM_2.5) across all sites and was dominant (≥60%) at IMPROVE sites. Vehicle exhausts accounted for 20–70% of the primary PM_2.5 contribution, largely exceeding the proportion in the primary PM_2.5 emission inventory. The diesel exhaust contribution was separable from the gasoline engine exhaust contribution at the STN sites. Higher detection limits for several marker elements in the STN resulted in non-detectable coal-fired boiler contributions which were detected in the IMPROVE data. Despite the different measured variables, analytical methods, and detection limits, EV-CMB results from a nearby IMPROVE-STN non-urban/urban sites showed similar contributions from regional sources – including fugitive dust and secondary aerosol. Seasonal variations of source contributions were examined and extreme PM_2.5 episodes were explained by both local and regional pollution events.     

Characterization of the Fugitive Particulate Emissions from Construction Mud/Dirt Carryout

Abstract

Although the fugitive dust associated with construction mud/dirt carryout can represent a substantial portion of the particulate matter (PM) emissions inventory in non-attainment areas, it has not been well characterized by direct sampling methods. In this paper, a research program is described that directly determined both PM₁₀ and PM_2.5 (particles ≤10 and 2.5 μm in classical aerodynamic diameter, respectively) emission factors for mud/dirt carryout from a major construction project located in metropolitan Kansas City, MO. The program also assessed the contribution of automotive emissions to the total PM_2.5 burden and determined the baseline emissions from the test road. As part of the study, both time-integrated and continuous exposure-profiling methods were used to assess the PM emissions, including particle size and elemental composition. This research resulted in overall PM₁₀ and PM_2.5 emission factors of 6 and 0.2 g/vehicle, respectively. Although PM₁₀ is within the range of prior U.S. Environmental Protection Agency (EPA) guidance, the PM_2.5 emission factor is far lower than previous estimates published by EPA. In addition, based on both the particle size and chemical data obtained in the study, a major portion of the PM_2.5 emissions appears to be attributable to automotive exhaust from light-duty, gasoline-powered vehicles and not to the fugitive dust associated with re-entrained mud/dirt carryout.     

Loss of Particle Nitrate from Teflon Sampling Filters: Effects on Measured Gravimetric Mass in California and in the IMPROVE Network

Abstract

The extent of mass loss on Teflon filters caused by ammonium nitrate volatilization can be a substantial fraction of the measured particulate matter with an aerodynamic diameter less than 2.5 μm (PM_2.5)or 10 μm (PM₁₀) mass and depends on where and when it was collected. There is no straightforward method to correct for the mass loss using routine monitoring data. In southern California during the California Acid Deposition Monitoring Program, 30-40% of the gravimetric PM_2.5 mass was lost during summer daytime. Lower mass losses occurred at more remote locations. The estimated potential mass loss in the Interagency Monitoring of Protected Visual Environments network was consistent with the measured loss observed in California. The biased mass measurement implies that use of Federal Reference Method data for fine particles may lead to control strategies that are biased toward sources of fugitive dust, other primary particle emission sources, and stable secondary particles (e.g., sulfates). This analysis clearly supports the need for speciated analysis of samples collected in a manner that preserves volatile species. Finally, although there is loss of volatile nitrate (NO₃ ^?) from Teflon filters during sampling, the NO₃ ^? remaining after collection is quite stable. We found little loss of NO₃ ^? from Teflon filters after 2 hr under vacuum and 1 min of heating by a cyclotron proton beam.     

Wintertime PM2.5 and PM10 Source Apportionment at Sacramento,California

ABSTRACT

The chemical mass balance (CMB) model was applied to winter (November through January) 1991–1996 PM2.5 and PM10 data from the Sacramento 13th and T Streets site in order to identify the contributions from major source categories to peak 24-hr ambient PM_2.5 and PM₁₀ levels. The average monthly PM₁₀ monitoring data for the nine-year period in Sacramento County indicate that elevated concentrations are typical in the winter months. Concentrations on days of highest PM₁₀ are dominated by the PM2.5 fraction. One factor contributing to increased PM_2.5 concentrations in the winter is meteorology (cool temperatures, low wind speeds, low inversion layers, and more humid conditions) that favors the formation of secondary nitrate and sulfate aerosols. Residential wood burning also elevates fine particulate concentrations in the Sacramento area.

The results of the CMB analysis highlight three key points. First, the source apportionment results indicate that primary motor vehicle exhaust and wood smoke are significant sources of both PM_2.5 and PM₁₀ in winter. Second, nitrates, secondarily formed as a result of motor-vehicle and other sources of nitrogen oxide (NO_x), are another principal cause of the high PM_2.5 and PM₁₀ levels during the winter months. Third, fugitive dust, whether it is resuspended soil and dust or agricultural tillage, is not the major contributor to peak winter PM_2.5 and PM10 levels in the Sacramento area.     

Loss of PM2.5 Nitrate from Filter Samples in Central California

Abstract

Evaporative loss of particulate matter (with aerodynamic diameter <2.5 μm, [PM_2.5]) 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 PM_2.5 acquired on Teflon-membrane filters, measured PM_2.5 mass was 8–16% lower than actual PM_2.5 mass owing to nitrate volatilization. For 24-hr samples, measured PM_2.5 was as much as 32–44% lower than actual PM_2.5 at three California Central Valley locations.     

Spatial differences in ambient coarse and fine particles in the Monterrey metropolitan area,Mexico: Implications for source contribution

The ambient air of the Monterrey Metropolitan Area (MMA) in Mexico frequently exhibits high levels of PM₁₀ and PM_2.5. However, no information exists on the chemical composition of coarse particles (PM_c = PM₁₀ – PM_2.5). A monitoring campaign was conducted during the summer of 2015, during which 24-hr average PM₁₀ and PM_2.5 samples were collected using high-volume filter-based instruments to chemically characterize the fine and coarse fractions of the PM. The collected samples were analyzed for anions (Cl^–, NO₃^–, SO₄^2–), cations (Na⁺, NH₄⁺, K⁺), organic carbon (OC), elemental carbon (EC), and 35 trace elements (Al to Pb). During the campaign, the average PM_2.5 concentrations did not showed significance differences among sampling sites, whereas the average PM_c concentrations did. In addition, the PM_c accounted for 75% to 90% of the PM₁₀ across the MMA. The average contribution of the main chemical species to the total mass indicated that geological material including Ca, Fe, Si, and Al (45%) and sulfates (11%) were the principal components of PM_c, whereas sulfates (54%) and organic matter (30%) were the principal components of PM_2.5. The OC-to-EC ratio for PM_c ranged from 4.4 to 13, whereas that for PM_2.5 ranged from 3.97 to 6.08. The estimated contribution of Secondary Organic Aerosol (SOA) to the total mass of organic aerosol in PM_2.5 was estimated to be around 70–80%; for PM_c, the contribution was lower (20–50%). The enrichment factors (EF) for most of the trace elements exhibited high values for PM_2.5 (EF: 10–1000) and low values for PM_c (EF: 1–10). Given the high contribution of crustal elements and the high values of EFs, PM_c is heavily influenced by soil resuspension and PM_2.5 by anthropogenic sources. Finally, the airborne particles found in the eastern region of the MMA were chemically distinguishable from those in its western region.

Implications: Concentration and chemical composition patterns of fine and coarse particles can vary significantly across the MMA. Public policy solutions have to be built based on these observations. There is clear evidence that the spatial variations in the MMA’s coarse fractions are influenced by clearly recognizable primary emission sources, while fine particles exhibit a homogeneous concentration field and a clear spatial pattern of increasing secondary contributions. Important reductions in the coarse fraction can come from primary particles’ emission controls; for fine particles, control of gaseous precursors—particularly sulfur-containing species and organic compounds—should be considered.     

Temporal and spatial variation of the chemical composition of PM10 at urban and rural sites in the Basel area,Switzerland

Particulate matter measurements of different size fractions (PM₄, PM₁₀, TSP) were performed in the Basel area (Switzerland) at seven urban sites throughout 1997 and at two urban and two rural sites during the following year (April 1998–May 1999). Based on a sample of filters which was chemically analyzed, we investigated the chemical composition of PM₁₀ both within the city of Basel and among urban and rural sites. The temporal and spatial variability of the chemical composition of PM₁₀ was evaluated taking into account additional data from meteorology and further air pollutants. The chemical analyses of PM₁₀ showed that carbonaceous substances (elemental carbon, organic matter) and inorganic substances of secondary origin such as sulfate, nitrate and ammonium were the most abundant component of PM₁₀ in the Basel area (approximately 60–70%). Difference in the PM₁₀ concentration between urban and rural sites was larger during the cold season than during the warm season. This was mainly due to the presence of an inversion layer between the city and the more elevated rural sites resulting in higher concentrations of nitrate, ammonium and organic matter in the city during the cold season. The higher PM₁₀ concentration on workdays compared to weekends was mostly a result of the temporal variation of the concentration of Ca, elemental carbon, Ti, Mn, and Fe, indicating that these compounds are for the most part caused by regional human activities. Although total PM₁₀ mass concentration was found to be in general uniformly distributed within the city of Basel, the chemical composition was more variable due to specific sources like road traffic and other anthropogenic emissions.     

An evaluation of mass absorption cross-section for optical carbon analysis on Teflon filter media

Black carbon (BC) or elemental carbon (EC) is a by-product of incomplete fuel combustion, and contributes adversely to human health, visibility, and climate impacts. Previous studies have examined nondestructive techniques for particle light attenuation measurements on Teflon® filters to estimate BC. The incorporation of an inline Magee Scientific OT21 transmissometer into the MTL AH-225 robotic weighing system provides the opportunity to perform optical transmission measurements on Teflon filters at the same time as the gravimetric mass measurement. In this study, we characterize the performance of the inline OT21, and apply it to determine the mass absorption cross-section (MAC) of PM_2.5 BC across the United States. We analyzed 5393 archived Teflon® filters from the Chemical Speciation Network (CSN) collected during 2010–2011 and determined MAC by comparing light attenuation on Teflon® filters to corresponding thermal EC on quartz-fiber filters. Results demonstrated the importance of the initial transmission (I₀) value used in light attenuation calculations. While light transmission varied greatly within filter lots, the average I₀ of filter blanks during the sampling period provided an estimate for archived filters. For newly collected samples, it is recommended that filter-specific I₀ measurements be made (i.e., same filter before sample collection). The estimated MAC ranged from 6.9 to 9.4 m²/g and varied by region and season across the United States, indicating that using a default value may lead to under- or overestimated BC concentrations. An analysis of the chemical composition of these samples indicated good correlation with EC for samples with higher EC content as a fraction of total PM_2.5 mass, while the presence of light-scattering species such as crustal elements impacted the correlation affecting the MAC estimate. Overall, the method is demonstrated to be a quick, cost-effective approach to estimate BC from archived and newly sampled Teflon® filters by combining both gravimetric and BC measurements.

Implications: Robotic optical analysis is a valid, cost-effective means to obtain a vast amount of BC data from archived and current routine filters. A tailored mass absorption cross-section by region and season is necessary for a more representative estimate of BC. Initial light transmission measurements play an important role due to the variability in blank filter transmission. Combining gravimetric mass and BC analysis on a single Teflon® filter reduces costs for monitoring agencies and maximizes data collection.     

Development of a PM2 5 Emissions Inventory for the South Coast Air Basin

ABSTRACT

With the promulgation of a national PM_2.5 ambient air quality standard, it is important that PM_2.5 emissions inventories be developed as a tool for understanding the magnitude of potential PM2.5 violations. Current PM₁₀ inventories include only emissions of primary particulate matter (1 ^ï PM), whereas, based on ambient measurements, both PM₁₀ and PM2.5 emissions inventories will need to include sources of both 1^ï PM and secondary particulate matter (2^ï PM). Furthermore, the U. S. Environmental Protection Agency’s (EPA) current edition of AP-42 includes size distribution data for 1o PM that overestimate the PM_2.5 fraction of fugitive dust sources by at least a factor of 2 based on recent studies.

This paper presents a PM_2.5 emissions inventory developed for the South Coast Air Basin (SCAB) that for the first time includes both 1^ï PM and 2^ï PM. The former is calculated by multiplying PM₁₀ emissions estimates by the PM_2.5/PM₁₀ ratios for different sources. The latter is calculated from estimated emission rates of gas-phase aerosol precursor and gas to aerosol conversion rates consistent with the measured chemical composition of ambient PM_2.5 concentrations observed in the SCAB. The major finding of this PM_2.5 emissions inventory is that the ^2ï aerosol component is more than twice the ^1ï aerosol component, which may result in widely different control strategies being required for fine PM and coarse PM.     

The characteristics of PM2.5 in Beijing,China

Weekly PM_2.5 samples were simultaneously collected at a residential (Tsinghua University) and a downtown (Chegongzhuang) site in Beijing from July 1999 through September 2000. The ambient mass concentration and chemical composition of the PM_2.5 were determined. Analyses included elemental composition, water-soluble ions, and organic and elemental carbon. Weekly PM_2.5 mass concentrations ranged from 37 to 357 μg/m³, with little difference found between the two sites. Seasonal variation of PM_2.5 concentrations was significant, with the highest concentration in the winter and the lowest in the summer. Spring dust storms had a strong impact on the PM_2.5. Overall, organic carbon was the most abundant species, constituting no less than 30% of the total PM_2.5 mass at both sites. Concentrations of organic and elemental carbon were 35% and 16% higher at Tsinghua University than at Chegongzhuang. Ammonium, nitrate and sulfate were comparable at the sites, accounting for 25–30% of the PM_2.5 mass.     

Analysis of PM2.5and PM10 in the Atmosphere of Mexico City during 2000-2002

Abstract

During the last 10 years, high atmospheric concentrations of airborne particles recorded in the Mexico City metropolitan area have caused concern because of their potential harmful effects on human health. Four monitoring campaigns have been carried out in the Mexico City metropolitan area during 2000-2002 at three sites: (1) Xalos-toc, located in an industrial region; (2) La Merced, located in a commercial area; and (3) Pedregal, located in a residential area. Results of gravimetric and chemical analyses of 330 samples of particulate matter (PM) with an aerodynamic diameter less than 2.5 μm (PM_2.5) and PM with an aerodynamic diameter less than 10 μm (PM₁₀) indicate that (1) PM_2.5/PM₁₀ average ratios were 0.42, 0.46, and 0.52 for Xalostoc, La Merced, and Pedregal, respectively; (2) the highest PM_2.5 and PM₁₀ concentrations were found at the industrial site; (3) PM_2.5 and PM₁₀ concentrations were lower at nighttime; (4) PM_2.5 and PM₁₀ spatial averages concentrations were 35 and 76 μg/m³, respectively; and (5) when the PM_2.5 standard was exceeded, nitrate, sulfate, ammonium, organic carbon, and elemental carbon concentrations were high. Twenty-four hour averaged PM_2.5 concentrations in Mexico City and Sao Paulo were similar to those recorded in the 1980s in Los Angeles. PM₁₀ concentrations were comparable in Sao Paulo and Mexico City but 3-fold lower than those found in Santiago.     

The Southeastern Aerosol Research and Characterization Study: Part II. Filter-Based Measurements of Fine and Coarse Particulate Matter Mass and Composition

Abstract

The Southeastern Aerosol Research and Characterization Study (SEARCH) was implemented in 1998–1999 to provide data and analyses for the investigation of the sources, chemical speciation, and long-term trends of fine particulate matter (PM_2.5) and coarse particulate matter (PM_10–2.5) in the Southeastern United States. This work is an initial analysis of 5 years (1999–2003) of filter-based PM_2.5 and PM_10–2.5 data from SEARCH. We find that annual PM_2.5 design values were consistently above the National Ambient Air Quality Standards (NAAQS) 15 µg/m³ annual standard only at monitoring sites in the two largest urban areas (Atlanta, GA, and North Birmingham, AL). Other sites in the network had annual design values below the standard, and no site had daily design values above the NAAQS 65 µg/m³ daily standard. Using a particle composition monitor designed specifically for SEARCH, we found that volatilization losses of nitrate, ammonium, and organic carbon must be accounted for to accurately characterize atmospheric particulate matter. In particular, the federal reference method for PM_2.5 underestimates mass by 3–7% as a result of these volatilization losses. Organic matter (OM) and sulfate account for ≥60% of PM_2.5 mass at SEARCH sites, whereas major metal oxides (MMO) and unidentified components (“other”) account for ≥80% of PM_10–2.5 mass. Limited data suggest that much of the unidentified mass in PM_10–2.5 may be OM. For paired comparisons of urban-rural sites, differences in PM_2.5 mass are explained, in large part, by higher OM and black carbon at the urban site. For PM₁₀, higher urban concentrations are explained by higher MMO and “other.” Annual means for PM_2.5 and PM_10–2.5 mass and major components demonstrate substantial declines at all of the SEARCH sites over the 1999–2003 period (10–20% in the case of PM_2.5, dominated by 14–20% declines in sulfate and 11–26% declines in OM, and 14–25% in the case of PM_10–2.5, dominated by 17–30% declines in MMO and 14–31% declines in “ other”). Although declining national emissions of sulfur dioxide and anthropogenic carbon may account for a portion of the observed declines, additional investigation will be necessary to establish a quantitative assessment, especially regarding trends in local and regional emissions, primary carbon emissions, and meteorology.     

The Relationship between Cross-Sectional and Time Series Studies

Abstract

There is a dearth of information on dust emissions from sources that are unique to the U.S. Department of Defense testing and training activities. However, accurate emissions factors are needed for these sources so that military installations can prepare accurate particulate matter (PM) emission inventories. One such source, coarse and fine PM (PM₁₀ and PM_2.5) emissions from artillery backblast testing on improved gun positions, was characterized at the Yuma Proving Ground near Yuma, AZ, in October 2005. Fugitive emissions are created by the shockwave from artillery pieces, which ejects dust from the surface on which the artillery is resting. Other contributions of PM can be attributed to the combustion of the propellants. For a 155–mm howitzer firing a range of propellant charges or zones, amounts of emitted PM₁₀ ranged from ～19 g of PM₁₀ per firing event for a zone 1 charge to 92 g of PM₁₀ per firing event for a zone 5. The corresponding rates for PM_2.5 were ～9 g of PM_2.5 and 49 g of PM_2.5 per firing. The average measured emission rates for PM₁₀ and PM_2.5 appear to scale with the zone charge value. The measurements show that the estimated annual contributions of PM₁₀ (52.2 t) and PM_2.5 (28.5 t) from artillery backblast are insignificant in the context of the 2002 U.S. Environment Protection Agency (EPA) PM emission inventory. Using national–level activity data for artillery fire, the most conservative estimate is that backblast would contribute the equivalent of 5 x 10^–4% and 1.6 x 10^–3% of the annual total PM₁₀ and PM_2.5 fugitive dust contributions, respectively, based on 2002 EPA inventory data.     

The impact of wood smoke on ambient PM2.5 in northern Rocky Mountain valley communities

During the winters of 2006/2007 and 2007/2008, PM_2.5 source apportionment programs were carried out within five western Montana valley communities. Filter samples were analyzed for mass and chemical composition. Information was utilized in a Chemical Mass Balance (CMB) computer model to apportion the sources of PM_2.5. Results showed that wood smoke (likely residential woodstoves) was the major source of PM_2.5 in each of the communities, contributing from 56% to 77% of the measured wintertime PM_2.5. Results of ¹⁴C analyses showed that between 44% and 76% of the measured PM_2.5 came from a new carbon (wood smoke) source, confirming the results of the CMB modeling. In summary, the CMB model results, coupled with the ¹⁴C results, support that wood smoke is the major contributor to the overall PM_2.5 mass in these rural, northern Rocky Mountain airsheds throughout the winter months.     

Characterisation and source apportionment of fine particulate sources at Hanoi from 2001 to 2008

PM_2.5 particulate matter has been collected on Teflon filters every Sunday and Wednesday at Hanoi, Vietnam for nearly eight years from April 2001 to December 2008. These filters have been analysed for over 21 different chemical species from hydrogen to lead by ion beam analysis techniques. This is the first long term PM_2.5 dataset for this region. The average PM_2.5 mass for the study period was (54 ± 33) μg m^?3, well above the current US EPA health goal of 15 μg m^?3. The average PM_2.5 composition was found to be (29 ± 8)% ammonium sulfate, (8.9 ± 3.3)% soil, (28 ± 11)% organic matter, (0.6 ± 1.4)% salt and (9.2 ± 2.8)% black carbon. The remaining missing mass (25%) was mainly nitrates and absorbed water. Positive matrix factorisation techniques identified the major source contributions to the fine mass as automobiles and transport (40 ± 10)%, windblown soil (3.4 ± 2)%, secondary sulfates (7.8 ± 10)%, smoke from biomass burning (13 ± 6)%, ferrous and cement industries (19 ± 8)%, and coal combustion (17 ± 7)% during the 8 year study period.     

Investigation and modeling of the residential infiltration of fine particulate matter in Beijing,China

The objective of this study was to estimate the residential infiltration factor (Finf) of fine particulate matter (PM_2.5) and to develop models to predict PM_2.5 Finf in Beijing. Eighty-eight paired indoor–outdoor PM_2.5 samples were collected by Teflon filters for seven consecutive days during both non-heating and heating seasons (from a total of 55 families between August, 2013 and February, 2014). The mass concentrations of PM_2.5 were measured by gravimetric method, and elemental concentrations of sulfur in filter deposits were determined by energy-dispersive x-ray fluorescence (ED-XRF) spectrometry. PM_2.5 Finf was estimated as the indoor/outdoor sulfur ratio. Multiple linear regression was used to construct Finf predicting models. The residential PM_2.5 Finf in non-heating season (0.70 ± 0.21, median = 0.78, n = 43) was significantly greater than in heating season (0.54 ± 0.18, median = 0.52, n = 45, p < 0.001). Outdoor temperature, window width, frequency of window opening, and air conditioner use were the most important predictors during non-heating season, which could explain 57% variations across residences, while the outdoor temperature was the only predictor identified in heating season, which could explain 18% variations across residences. The substantial variations of PM_2.5 Finf between seasons and among residences found in this study highlight the importance of incorporating Finf into exposure assessment in epidemiological studies of air pollution and human health in Beijing. The Finf predicting models developed in this study hold promise for incorporating PM_2.5 Finf into large epidemiology studies, thereby reducing exposure misclassification.

Implications: Failure to consider the differences between indoor and outdoor PM_2.5 may contribute to exposure misclassification in epidemiological studies estimating exposure from a central site measurement. This study was conducted in Beijing to investigate residential PM_2.5 infiltration factor and to develop a localized predictive model in both nonheating and heating seasons. High variations of PM_2.5 infiltration factor between the two seasons and across homes within each season were found, highlighting the importance of including infiltration factor in the assessment of exposure to PM_2.5 of outdoor origin in epidemiological studies. Localized predictive models for PM_2.5 infiltration factor were also developed.