Estimating fine particulate matter component concentrations and size distributions using satellite-retrieved fractional aerosol optical depth: part 2--a case study

We use the fractional aerosol optical depth (AOD) values derived from Multiangle Imaging Spectroradiometer (MISR) aerosol component measurements, along with aerosol transport model constraints, to estimate ground-level concentrations of fine particulate matter (PM2.5) mass and its major constituents in the continental United States. Regression models using fractional AODs predict PM2.5 mass and sulfate (SO4) concentrations in both the eastern and western United States, and nitrate (NO3) concentrations in the western United States reasonably well, compared with the available ground-level U.S. Environment Protection Agency (EPA) measurements. These models show substantially improved predictive power when compared with similar models using total-column AOD as a single predictor, especially in the western United States. The relative contributions of the MISR aerosol components in these regression models are used to estimate size distributions of EPA PM2.5 species. This method captures the overall shapes of the size distributions of PM2.5 mass and SO4 particles in the east and west, and NO3 particles in the west. However, the estimated PM2.5 and SO4 mode diameters are smaller than those previously reported by monitoring studies conducted at ground level. This is likely due to the satellite sampling bias caused by the inability to retrieve aerosols through cloud cover, and the impact of particle hygroscopicity on measured particle size distributions at ground level.     

Size and composition distributions of particulate matter emissions: part 1--light-duty gasoline vehicles

Size-resolved particulate matter (PM) emitted from light-duty gasoline vehicles (LDGVs) was characterized using filter-based samplers, cascade impactors, and scanning mobility particle size measurements in the summer 2002. Thirty LDGVs, with different engine and emissions control technologies (model years 1965-2003; odometer readings 1264-207,104 mi), were tested on a chassis dynamometer using the federal test procedure (FTP), the unified cycle (UC), and the correction cycle (CC). LDGV PM emissions were strongly correlated with vehicle age and emissions control technology. The oldest models had average ultrafine PM0.1 (0.056- to 0.1-microm aerodynamic diameter) and fine PM1.8 (< or =1.8-microm aerodynamic diameter) emission rates of 9.6 mg/km and 213 mg/km, respectively. The newest vehicles had PM0.1 and PM1.8 emissions of 51 microg/km and 371 microg/km, respectively. Light duty trucks and sport utility vehicles had PM0.1 and PM1.8 emissions nearly double the corresponding emission rates from passenger cars. Higher PM emissions were associated with cold starts and hard accelerations. The FTP driving cycle produced the lowest emissions, followed by the UC and the CC. PM mass distributions peaked between 0.1- and 0.18-microm particle diameter for all vehicles except those emitting visible smoke, which peaked between 0.18 and 0.32 microm. The majority of the PM was composed of carbonaceous material, with only trace amounts of water-soluble ions. Elemental carbon (EC) and organic matter (OM) had similar size distributions, but the EC/OM ratio in LDGV exhaust particles was a strong function of the adopted emissions control technology and of vehicle maintenance. Exhaust from LDGV classes with lower PM emissions generally had higher EC/OM ratios. LDGVs adopting newer technologies were characterized by the highest EC/OM ratios, whereas OM dominated PM emissions from older vehicles. Driving cycles with cold starts and hard accelerations produced higher EC/OM ratios in ultrafine particles.     

Identification of haze-creating sources from fine particulate matter in Dhaka aerosol using carbon fractions

Fine particulate matter (PM_2.5) samples were simultaneously collected on Teflon and quartz filters between February 2010 and February 2011 at an urban monitoring site (CAMS2) in Dhaka, Bangladesh. The samples were collected using AirMetrics MiniVol samplers. The samples on Teflon filters were analyzed for their elemental composition by PIXE and PESA. Particulate carbon on quartz filters was analyzed using the IMPROVE thermal optical reflectance (TOR) method that divides carbon into four organic carbons (OC), pyrolized organic carbon (OP), and three elemental carbon (EC) fractions. The data were analyzed by positive matrix factorization using the PMF2 program. Initially, only total OC and total EC were included in the analysis and five sources, including road dust, sea salt and Zn, soil dust, motor vehicles, and brick kilns, were obtained. In the second analysis, the eight carbon fractions (OC1, OC2, OC3, OC4, OP, EC1, EC2, EC3) were included in order to ascertain whether additional source information could be extracted from the data. In this case, it is possible to identify more sources than with only total OC and EC. The motor vehicle source was separated into gasoline and diesel emissions and a fugitive Pb source was identified. Brick kilns contribute 7.9 μg/m³ and 6.0 μg/m³ of OC and EC, respectively, to the fine particulate matter based on the two results. From the estimated mass extinction coefficients and the apportioned source contributions, soil dust, brick kiln, diesel, gasoline, and the Pb sources were found to contribute most strongly to visibility degradation, particularly in the winter.

Implications: Fine particle concentrations in Dhaka, Bangladesh, are very high and cause significant degradation of urban visibility. This work shows that using carbon fraction data from the IMPROVE OC/EC protocol provides improved source apportionment. Soil dust, brick kiln, diesel, gasoline, and the Pb sources contribute strongly to haze, particularly in the winter.     

Spatial and temporal variability in urban fine particulate matter concentrations

Identification of hot spots for urban fine particulate matter (PM(2.5)) concentrations is complicated by the significant contributions from regional atmospheric transport and the dependence of spatial and temporal variability on averaging time. We focus on PM(2.5) patterns in New York City, which includes significant local sources, street canyons, and upwind contributions to concentrations. A literature synthesis demonstrates that long-term (e.g., one-year) average PM(2.5) concentrations at a small number of widely-distributed monitoring sites would not show substantial variability, whereas short-term (e.g., 1-h) average measurements with high spatial density would show significant variability. Statistical analyses of ambient monitoring data as a function of wind speed and direction reinforce the significance of regional transport but show evidence of local contributions. We conclude that current monitor siting may not adequately capture PM(2.5) variability in an urban area, especially in a mega-city, reinforcing the necessity of dispersion modeling and methods for analyzing high-resolution monitoring observations.     

Transport of atmospheric fine particulate matter: part 2--findings from recent field programs on the intraurban variability in fine particulate matter

Air quality field data, collected as part of the fine particulate matter Supersites Program and other field measurements programs, have been used to assess the degree of intraurban variability for various physical and chemical properties of ambient fine particulate matter. Spatial patterns vary from nearly homogeneous to quite heterogeneous, depending on the city, parameter of interest, and the approach or method used to define spatial variability. Secondary formation, which is often regional in nature, drives fine particulate matter mass and the relevant chemical components toward high intraurban spatial homogeneity. Those particulate matter components that are dominated by primary emissions within the urban area, such as black carbon and several trace elements, tend to exhibit greater spatial heterogeneity. A variety of study designs and data analysis approaches have been used to characterize intraurban variability. High temporal correlation does not imply spatial homogeneity. For example, there can be high temporal correlation but with spatial heterogeneity manifested as smooth spatial gradients, often emanating from areas of high emissions such as the urban core or industrial zones.     

Size and composition distributions of particulate matter emissions: part 2--heavy-duty diesel vehicles

Particulate matter (PM) emissions from heavy-duty diesel vehicles (HDDVs) were collected using a chassis dynamometer/dilution sampling system that employed filter-based samplers, cascade impactors, and scanning mobility particle size (SMPS) measurements. Four diesel vehicles with different engine and emission control technologies were tested using the California Air Resources Board Heavy Heavy-Duty Diesel Truck (HHDDT) 5 mode driving cycle. Vehicles were tested using a simulated inertial weight of either 56,000 or 66,000 lb. Exhaust particles were then analyzed for total carbon, elemental carbon (EC), organic matter (OM), and water-soluble ions. HDDV fine (< or =1.8 microm aerodynamic diameter; PM1.8) and ultrafine (0.056-0.1 microm aerodynamic diameter; PM0.1) PM emission rates ranged from 181-581 mg/km and 25-72 mg/km, respectively, with the highest emission rates in both size fractions associated with the oldest vehicle tested. Older diesel vehicles produced fine and ultrafine exhaust particles with higher EC/OM ratios than newer vehicles. Transient modes produced very high EC/OM ratios whereas idle and creep modes produced very low EC/OM ratios. Calcium was the most abundant water-soluble ion with smaller amounts of magnesium, sodium, ammonium ion, and sulfate also detected. Particle mass distributions emitted during the full 5-mode HDDV tests peaked between 100-180 nm and their shapes were not a function of vehicle age. In contrast, particle mass distributions emitted during the idle and creep driving modes from the newest diesel vehicle had a peak diameter of approximately 70 nm, whereas mass distributions emitted from older vehicles had a peak diameter larger than 100 nm for both the idle and creep modes. Increasing inertial loads reduced the OM emissions, causing the residual EC emissions to shift to smaller sizes. The same HDDV tested at 56,000 and 66,000 lb had higher PM0.1 EC emissions (+22%) and lower PM0.1 OM emissions (-38%) at the higher load condition.     

Evaluating inter-continental transport of fine aerosols: (1) Methodology,global aerosol distribution and optical depth

Our objectives are to evaluate inter-continental source-receptor relationships for fine aerosols and to identify the regions whose emissions have dominant influence on receptor continents. We simulate sulfate, black carbon (BC), organic carbon (OC), and mineral dust aerosols using a global coupled chemistry-aerosol model (MOZART-2) driven with NCEP/NCAR reanalysis meteorology for 1997–2003 and emissions approximately representing year 2000. The concentrations of simulated aerosol species in general agree within a factor of 2 with observations, except that the model tends to overestimate sulfate over Europe in summer, underestimate BC and OC over the western and southeastern (SE) U.S. and Europe, and underestimate dust over the SE U.S. By tagging emissions from ten continental regions, we quantify the contribution of each region's emissions on surface aerosol concentrations (relevant for air quality) and aerosol optical depth (AOD, relevant for visibility and climate) globally. We find that domestic emissions contribute substantially to surface aerosol concentrations (57–95%) over all regions, but are responsible for a smaller fraction of AOD (26–76%). We define “background” aerosols as those aerosols over a region that result from inter-continental transport, DMS oxidation, and emissions from ships or volcanoes. Transport from other continental source regions accounts for a substantial portion of background aerosol concentrations: 36–97% for surface concentrations and 38–89% for AOD. We identify the Region of Primary Influence (RPI) as the source region with the largest contribution to the receptor's background aerosol concentrations (or AOD). We find that for dust Africa is the RPI for both aerosol concentrations and AOD over all other receptor regions. For non-dust aerosols (particularly for sulfate and BC), the RPIs for aerosol concentrations and AOD are identical for most receptor regions. These findings indicate that the reduction of the emission of non-dust aerosols and their precursors from an RPI will simultaneously improve both air quality and visibility over a receptor region.     

Simulating the fine and coarse inorganic particulate matter concentrations in a polluted megacity

A three dimensional chemical transport model (PMCAMx) is applied to the Mexico City Metropolitan Area (MCMA) in order to simulate the chemical composition and mass of the major PM₁ (fine) and PM_1–10 (coarse) inorganic components and determine the effect of mineral dust on their formation. The aerosol thermodynamic model ISORROPIA-II is used to explicitly simulate the effect of Ca, Mg, and K from dust on semi-volatile partitioning and water uptake. The hybrid approach is applied to simulate the inorganic components, assuming that the smallest particles are in thermodynamic equilibrium, while describing the mass transfer to and from the larger ones. The official MCMA 2004 emissions inventory with improved dust and NaCl emissions is used. The comparison between the model predictions and measurements during a week of April of 2003 at Centro Nacional de Investigacion y Capacitacion Ambiental (CENICA) “Supersite” shows that the model reproduces reasonably well the fine mode composition and its diurnal variation. Sulfate predicted levels are relatively uniform in the area (approximately 3 μg m^?3), while ammonium nitrate peaks in Mexico City (approximately 7 μg m^?3) and its concentration rapidly decreases due to dilution and evaporation away from the urban area. In areas of high dust concentrations, the associated alkalinity is predicted to increase the concentration of nitrate, chloride and ammonium in the coarse mode by up to 2 μg m^?3 (a factor of 10), 0.4 μg m^?3, and 0.6 μg m^?3 (75%), respectively. The predicted ammonium nitrate levels inside Mexico City for this period are sensitive to the physical state (solid versus liquid) of the particles during periods with RH less than 50%.     

Particle size distributions and elemental composition of atmospheric particulate matter in southern Italy

Three 2-wk seasonal field campaigns were performed in 2003 and 2004 at a sampling site on the southern Tyrrhenian coast of Italy with the aim to investigate the dynamics and characteristics of particle-bound pollutants in the Mediterranean area. Fine (PM(2.5)) and coarse particulate matter (PM(10-2.5)) size fractions were collected by a manual dichotomous sampler on 37-mm Teflon filters over a 24-hr sampling period. On average, 70% of the total PM(10) (PM(2.5) + PM(10-2.5)) mass was associated with the coarse fraction and 30% with the fine fraction during the three campaigns. The ambient concentrations of Pb, Ni, Cr, Zn, Mn, V, Cd, Fe, Cu, Ca, and Mg associated with both size fractions were determined by atomic absorption spectrometry. Ambient concentrations showed differences in their absolute value, ranging from few ng x m(-3) to microg x m(-3), as well as in their variability within the PM(2.5) and PM(10-2.5) size fractions. PM(10) levels were well below the European Union (EU) limit value during the study period with the exception of three events during the first campaign (fall) and five events during the third campaign (spring). Two main sources were identified as the major contributors including mineral dust, transported from North Africa, and sea spray from the Tyrrhenian Sea. Comparing the results with backward trajectories, calculated using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) and Total Ozone Mapping Spectrometer-National Aeronautics and Space Administration (TOMS-NASA) maps, it was observed that in central and eastern Europe, the Tyrrhenian Sea and North Africa were the major emission source regions that affected the temporal variations and daily averages of PM(2.5) and PM(10-2.5) concentrations.     

Estimating trace gas and aerosol emissions over South America: Relationship between fire radiative energy released and aerosol optical depth observations

Contemporary human activities such as tropical deforestation, land clearing for agriculture, pest control and grassland management lead to biomass burning, which in turn leads to land-cover changes. However, biomass burning emissions are not correctly measured and the methods to assess these emissions form a part of current research area. The traditional methods for estimating aerosols and trace gases released into the atmosphere generally use emission factors associated with fuel loading and moisture characteristics and other parameters that are hard to estimate in near real-time applications. In this paper, fire radiative power (FRP) products were extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) and from the Geostationary Operational Environmental Satellites (GOES) fire products and new South America generic biomes FRE-based smoke aerosol emission coefficients were derived and applied in 2002 South America fire season. The inventory estimated by MODIS and GOES FRP measurements were included in Coupled Aerosol-Tracer Transport model coupled to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) and evaluated with ground truth collected in Large Scale Biosphere–Atmosphere Smoke, Aerosols, Clouds, rainfall, and Climate (SMOCC) and Radiation, Cloud, and Climate Interactions (RaCCI). Although the linear regression showed that GOES FRP overestimates MODIS FRP observations, the use of a common external parameter such as MODIS aerosol optical depth product could minimize the difference between sensors. The relationship between the PM_2.5μm (Particulate Matter with diameter less than 2.5 μm) and CO (Carbon Monoxide) model shows a good agreement with SMOCC/RaCCI data in the general pattern of temporal evolution. The results showed high correlations, with values between 0.80 and 0.95 (significant at 0.5 level by student t test), for the CATT-BRAMS simulations with PM_2.5μm and CO.     

Estimating distributions of long-term particulate matter and manganese exposures for residents of Toronto,Canada

Methylcyclopentadienyl manganese tricarbonyl (MMT), a manganese-based gasoline additive, has been used in Canadian gasoline for about 20 yr. Because MMT potentially increases manganese levels in particulate matter resulting from automotive exhausts, a population-based study conducted in Toronto, Canada assessed the levels of personal manganese exposures. Integrated 3-day particulate matter (PM_2.5) exposure measurements, obtained for 922 participant periods over the course of a year (September 1995–August 1996), were analyzed for several constituent elements, including Mn. The 922 measurements included 542 participants who provided a single 3-day observation plus 190 participants who provided two observations (in two different months). In addition to characterizing the distributions of 3-day average exposures, which can be estimated directly from the data, including the second observation for some participants enabled us to use a model-based approach to estimate the long-term (i.e. annual) exposure distributions for PM_2.5 mass and Mn. The model assumes that individuals’ 3-day average exposure measurements within a given month are lognormally distributed and that the correlation between 3-day log-scale measurements k months apart (after seasonal adjustment) depends only on the lag time, k, and not on the time of year. The approach produces a set of simulated annual exposures from which an annual distribution can be inferred using estimated correlations and monthly means and variances (log scale) as model inputs. The model appeared to perform reasonably well for the overall population distribution of PM_2.5 exposures (mean=28 μg m^-3). For example, the model predicted the 95th percentile of the annual distribution to be 62.9 μg m^-3 while the corresponding percentile estimated for the 3-day data was 86.6 μg m^-3. The assumptions of the model did not appear to hold for the overall population of Mn exposures (mean=13.1 ng m^-3). Since the population included persons who were potentially occupationally exposed to Mn (in non-vehicle-related jobs), we used responses to questionnaire items to form a subgroup consisting of non-occupationally exposed participants (671 participant periods), for which the model assumptions did appear to hold. For that subpopulation (mean=9.2 ng m^-3), the model-predicted 95th percentile of the annual Mn distribution was 16.3-ng m^-3, compared with 21.1 ng m^-3 estimated for the 3-day data.     

An overview of the gulf coast aerosol research and characterization study: the Houston fine particulate matter supersite

The Gulf Coast Aerosol Research and Characterization Study ([GC-ARCH], also known as the Houston Fine Particulate Matter [PM] Supersite) examined the spatial and temporal variability in fine PM source contributions and composition and the physical and chemical processes that govern PM formation and transformation in southeastern Texas. This was accomplished through the analysis of data collected in a 16-month field sampling program (August 2000 through November 2001). Three core sites and approximately 15 peripheral sites, jointly operated by the study team and the Texas Commission on Environmental Quality (TCEQ), were used. Key scientific findings related to spatial and temporal variability in fine PM concentrations, sizes and composition of the fine PM, the strength of primary emission sources and causes of secondary fine PM formation are reported.     

The Southeastern Aerosol Research and Characterization Study, part 3: continuous measurements of fine particulate matter mass and composition

Deployment of continuous analyzers in the Southeastern Aerosol Research and Characterization Study (SEARCH) network began in 1998 and continues today as new technologies are developed. Measurement of fine particulate matter (PM2.5) mass is performed using a dried, 30 degrees C tapered element oscillating microbalance (TEOM). TEOM measurements are complemented by observations of light scattering by nephelometry. Measurements of major constituents include: (1) SO4(2-) via reduction to SO2; (2) NH4+ and NO3- via respective catalytic oxidation and reduction to NO, (3) black carbon (BC) by optical absorption, (4) total carbon by combustion to CO2, and (5) organic carbon by difference between the latter two measurements. Several illustrative examples of continuous data from the SEARCH network are presented. A distinctive composite annual average diurnal pattern is observed for PM2.5 mass, nitrate, and BC, likely indicating the influence of traffic-related emissions, growth, and break up of the boundary layer and formation of ammonium nitrate. Examination of PM2.5 components indicates the need to better understand the continuous composition of the unmeasured "other" category, because it contributes a significant fraction to total mass during periods of high PM2.5 loading. Selected episodes are presented to illustrate applications of SEARCH data. An SO2 conversion rate of 0.2%/hr is derived from an observation of a plume from a coal-fired power plant during early spring, and the importance of local, rural sources of NH3 to the formation of ammonium nitrate in particulate matter (PM) is demonstrated.     

Effects of sulfur dioxide and oxides of nitrogen emission reductions on fine particulate matter mass concentrations: regional comparisons

Two thermodynamic equilibrium models were applied to estimate changes in mean airborne fine particle (PM2.5) mass concentrations that could result from changes in ambient concentrations of sulfate, nitric acid, or ammonia in the southeastern United States, the midwestern United States, and central California. Pronounced regional differences were found. Southeastern sites exhibited the lowest current mean concentrations of nitrate, and the smallest predicted responses of PM2.5 nitrate and mass concentrations to reductions of nitric acid, which is the principal reaction product of the oxidation of nitrogen dioxide (NO2) and the primary gas-phase precursor of fine particulate nitrate. Weak responses of PM2.5 nitrate and mass concentrations to changes in nitric acid levels occurred even if sulfate concentrations were half of current levels. The midwestern sites showed higher levels of fine particulate nitrate, characterized by cold-season maxima, and were projected to show decreases in overall PM levels following decreases of either sulfate or nitric acid. For some midwestern sites, predicted PM2.5 nitrate concentrations increased as modeled sulfate levels declined, but sulfate reductions always reduced the predicted fine PM mass concentrations; PM2.5 nitrate concentrations became more sensitive to reductions of nitric acid as modeled sulfate concentrations were decreased. The California sites currently have the highest mean concentrations of fine PM nitrate and the lowest mean concentrations of fine PM sulfate. Both the estimated PM2.5 nitrate and fine mass concentrations decreased in response to modeled reductions of nitric acid at all California sites. The results indicate important regional differences in expected PM2.5 mass concentration responses to changes in sulfate and nitrate precursors. Analyses of ambient data, such as described here, can be a key part of weight of evidence (WOE) demonstrations for PM2.5 attainment plans. Acquisition of the data may require special sampling efforts, especially for PM2.5 precursor concentration data.     

Personal exposure to fine particulate matter in elderly subjects: relation between personal, indoor, and outdoor concentrations

The time-series correlation between ambient levels, indoor levels, and personal exposure to PM2.5 was assessed in panels of elderly subjects with cardiovascular disease in Amsterdam, the Netherlands, and Helsinki, Finland. Subjects were followed for 6 months with biweekly clinical visits. Each subject's indoor and personal exposure to PM2.5 was measured biweekly, during the 24-hr period preceding the clinical visits. Outdoor PM2.5 concentrations were measured at fixed sites. The absorption coefficients of all PM2.5 filters were measured as a marker for elemental carbon (EC). Regression analyses were conducted for each subject separately, and the distribution of the individual regression and correlation coefficients was investigated. Personal, indoor, and ambient concentrations were highly correlated within subjects over time. Median Pearson's R between personal and outdoor PM2.5 was 0.79 in Amsterdam and 0.76 in Helsinki. For absorption, these values were 0.93 and 0.81 for Amsterdam and Helsinki, respectively. The findings of this study provide further support for using fixed-site measurements as a measure of exposure to PM2.5 in epidemiological time-series studies.     

Proinflammatory effect of fine and ultrafine particulate matter using size-resolved urban aerosols from Paris

Epidemiological and experimental studies have underlined that exposure to particulate matter (PM) leads mainly to airway inflammation, but the roles of particle size and chemical composition associated to such adverse health outcomes need to be better investigated. This study was performed to validate novel strategies of particle sampling, recovery and cell exposure in order to evaluate the pro-inflammatory potential of fine and ultrafine particles from a fractionated aerosol. Samplings of Paris background aerosols using 13-stage low pressure impactors (0.03-10 microm) gave bimodal mass distributions with an accumulation mode centered on a median diameter of 0.42 microm and a coarse one on 3.25 microm. PM 1 accounted for 70% and PM 0.1 for 12% of PM 10. The latter mainly comprised carbon-chained aggregates. The development of an efficient and reproducible method to recover fine (PM 1-0.1) and ultrafine (PM 0.1-0.03) particulate matter has permitted experimental comparison of the impact of such particles on human bronchial epithelial cells (HBECs). In this study we have compared the relative effects of fine and ultrafine particles at non-cytotoxic concentrations over 24h on the production of the pro-inflammatory cytokine GM-CSF by HBECs. Combining two cell exposure strategies to the size-fraction particles according to either their proportion (isovolume exposure) or their quantity in the aerosol (isomass exposure), we showed that both ultrafine and fine particles induced a concentration-dependent GM-CSF release by HBECs which is significant from 1 microg cm(-2). In conclusion, short duration samplings using 13-stage impactors enable to obtain size-resolved PM in sufficient quantities to carry out toxicological investigations. These findings are promising in view to conduct a more intensive study joining chemical and toxicological assays.     

Transport of atmospheric fine particulate matter: part 1--findings from recent field programs on the extent of regional transport within North America

Air quality field data, collected as part of the fine particulate matter Supersites program and other field measurements programs, have been used to assess the role of aerosol transport, over length scales of approximately 100-1000 km, on fine particulate matter concentrations. Assessment of data from New York, NY; Baltimore, MD; Pittsburgh, PA; Atlanta, GA; Houston, TX; St. Louis, MO; and Fresno, CA, indicates that in virtually all of the regions, transport of aerosol over distances of 100-1000 km has a significant impact on urban particulate matter concentrations and a dominant role in determining rural particulate matter concentrations, though the nature of the regional contributions differs from region to region. This assessment is generally consistent with previous conceptual models of fine particulate matter formation and accumulation in these regions. The nature of the transported aerosol is largely sulfate in Eastern and Midwestern cities and nitrate in the Central Valley of California. In addition to physical transport of aerosol over distances of 100-1000 km, regional transport of aerosol precursors may lead to conditions conducive to large-scale nucleation events. Regional nucleation events have been reported in the East, Midwest, and in California. The events occurred in the morning soon after surface layers coupled with layers aloft, and the events generate ultrafine particles. In some cases, these nucleation events have been correlated with availability of sulfur dioxide and, therefore, may be sulfate formation events.     

Predicting residential indoor concentrations of nitrogen dioxide,fine particulate matter,and elemental carbon using questionnaire and geographic information system based data

Previous studies have identified associations between traffic-related air pollution and adverse health effects. Most have used measurements from a few central ambient monitors and/or some measure of traffic as indicators of exposure, disregarding spatial variability and factors influencing personal exposure-ambient concentration relationships. This study seeks to utilize publicly available data (i.e., central site monitors, geographic information system, and property assessment data) and questionnaire responses to predict residential indoor concentrations of traffic-related air pollutants for lower socioeconomic status (SES) urban households.As part of a prospective birth cohort study in urban Boston, we collected indoor and outdoor 3–4 day samples of nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5) in 43 low SES residences across multiple seasons from 2003 to 2005. Elemental carbon (EC) concentrations were determined via reflectance analysis. Multiple traffic indicators were derived using Massachusetts Highway Department data and traffic counts collected outside sampling homes. Home characteristics and occupant behaviors were collected via a standardized questionnaire. Additional housing information was collected through property tax records, and ambient concentrations were collected from a centrally located ambient monitor.The contributions of ambient concentrations, local traffic and indoor sources to indoor concentrations were quantified with regression analyses. PM_2.5 was influenced less by local traffic but had significant indoor sources, while EC was associated with traffic and NO₂ with both traffic and indoor sources. Comparing models based on covariate selection using p-values or a Bayesian approach yielded similar results, with traffic density within a 50 m buffer of a home and distance from a truck route as important contributors to indoor levels of NO₂ and EC, respectively. The Bayesian approach also highlighted the uncertanity in the models. We conclude that by utilizing public databases and focused questionnaire data we can identify important predictors of indoor concentrations for multiple air pollutants in a high-risk population.     

Assessment of heterogeneity of metal composition of fine particulate matter collected from eight U.S. counties using principal component analysis

The main objectives of this study are to (1) characterize chemical constituents of particulate matter (PM) and (2) compare overall differences in PM collected from eight US. counties. This project was undertaken as a part of a larger research program conducted by the Johns Hopkins Particulate Matter Research Center (JHPMRC). The goal of the JHPMRC is to explore the relationship between health effects and exposure to ambient PM of differing composition. The JHPMRC collected weekly filter-based ambient fine particle samples from eight US. counties between January 2008 and January 2010. Each sampling effort consisted of a 5-6-week sampling period. Filters were analyzed for 25 metals using inductively coupled plasma mass spectrometry (ICP-MS). Overall compositional differences were ranked by principal component analysis (PCA). The results showed that weekly concentrations of each element varied 3-40 times between the eight counties. PCA showed that the first five principal components explained 85% of the total variance. The authors found significant overall compositional differences in PM as the average of standardized principal component scores differed between the counties. These findings demonstrate PCA is a useful tool to identify the differences in PM compositional mixtures by county. These differences will be helpful for epidemiological and toxicological studies to help explain why health risks associated with PM exposure are different in locations with similar mass concentrations of PM.     

Detection of Asian dust aerosols using meteorological satellite data and suspended particulate matter concentrations

The advection and dispersion of Asian dust events from China to the Pacific Ocean around Japan during 2000–2002 were investigated using the meteorological satellite data of NOAA/AVHRR and GMS-5/VISSR. Aerosol vapour index images, taking the brightness temperature difference between 11 and 12 μm, are very effective for monitoring the Asian dust phenomenon in the East Asia region, with their capacity for detection during the day or night. We discuss the dust events, focusing on the advection patterns shown in satellite images, which are classified into three types as ‘dry slot’, ‘high-pressure wedge’ and ‘travelling high’, based on synoptic patterns. The results are compared with suspended particulate matter concentrations measured at Japanese surface stations and with ground-based observations of Sakurajima volcano by a web camera system at Kagoshima in Kyushu, Japan. We found that the passage of cold fronts caused a rapid increase of suspended particulate matter (SPM) concentrations, which exceeded 100 μg m⁻³, and that deep low-pressure complexes strengthened the dust phenomenon. The ‘high-pressure wedge’ type is seen much more clearly in satellite images than the ‘travelling high’ type, but SPM concentrations and visibility were similar in both owing to the differences in the vertical distribution of the dust and in viewing conditions.