Biomedical subjects

Philip K Hopke

Publications and source records attributed to Philip K Hopke.

At least 19 recordsLinked to original sources

PubMed2006

Seasonal variation of 2-methyltetrols in ambient air samples.

PM2.5 samples were collected from June to December 2005 in Potsdam, New York and analyzed for polar organic compounds by GC/MS. The major compounds that were identified in the samples included 2-methyltetrols (2-methylthreitol and 2-methylerythritol), levoglucosan, cispinonic acid, and mannitol. 2-Methyltetrols were quantified during the analysis. A seasonal variation for these two diastereoisomers was observed, with the highest concentrations occurring during the summer and the lowest concentrations occurring during the winter. OC/EC analyses of these samples were also performed. The variation of the carbon contribution of 2-methyltetrols to OC was found to follow the same pattern as the concentration variation of 2-methyltetrols. During summer, the period of high photochemical activity, the maximum carbon contribution of 2-methyltetrols to OC was 2.8%. The observation of high 2-methyltetrol concentrations during the summer indicates isoprene is a significant summertime source of secondary organic aerosol in this rural area in the northeastern United States.

Air Pollutants↗

PubMed2006

Characterization of fine particle sources in the Great Smoky Mountains area.

A source apportionment study to characterize sources of fine particles in the Great Smoky Mountains area was conducted analyzing ambient PM(2.5) (particulate matter< or =2.5 microm in aerodynamic diameter) speciation data collected at a Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring site. A total of 1442 samples collected between March 1988 and December 2003 analyzed for 30 elemental species were analyzed with the application of the positive matrix factorization (PMF). Eight major sources were extracted: summer-high secondary sulfate (55%), carbon-rich secondary sulfate (16%), summer-low secondary sulfate (2%), gasoline vehicle emissions (13%), diesel emissions (1%), airborne soil (6%), industry (5%), and secondary nitrate (2%). The contributions from the carbon-rich secondary sulfate particles are likely a combination of local and regional influences of the biogenic as well as anthropogenic secondary particles. The compositional profiles for gasoline vehicle and diesel emissions are similar to those identified in other US areas. Backward trajectories indicate that the high impacts of airborne soil were likely caused by Asian and Saharan dust storms. This study would assist in the implementation plan development for attaining the air quality standards for PM(2.5), regional haze rule planning, and source-specific community epidemiology.

Air Pollutants↗

PubMed2006

Exposure to airborne particulate matter in the ambient, indoor, and occupational environments.

Exposure to airborne particulate matter results in various adverse health effects. Unlike other pollutants, such as ozone, sulfur dioxide, carbon monoxide, and oxides of nitrogen, for which there is significant exposure, particulate matter exposure is much more complex because it is not a single chemical species or even a limited number of chemical species. Particulate matter includes various chemical species in particles having a wide range of diameters and shapes that have widely varying toxicities. People are exposed to particles in the ambient environment, in indoor spaces, and in the occupational environment. This article reviews the information available on the concentrations of particulate matter and its composition in these general environmental categories.

Air Pollutants↗

PubMed2006

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

During the past three decades, receptor models have been used to identify and apportion ambient concentrations to sources. A number of groups are employing these methods to provide input into air quality management planning. A workshop has explored the use of resolved source contributions in health effects models. Multiple groups have analyzed particulate composition data sets from Washington, DC and Phoenix, AZ. Similar source profiles were extracted from these data sets by the investigators using different factor analysis methods. There was good agreement among the major resolved source types. Crustal (soil), sulfate, oil, and salt were the sources that were most unambiguously identified (generally highest correlation across the sites). Traffic and vegetative burning showed considerable variability among the results with variability in the ability of the methods to partition the motor vehicle contributions between gasoline and diesel vehicles. However, if the total motor vehicle contributions are estimated, good correspondence was obtained among the results. The source impacts were especially similar across various analyses for the larger mass contributors (e.g., in Washington, secondary sulfate SE=7% and 11% for traffic; in Phoenix, secondary sulfate SE=17% and 7% for traffic). Especially important for time-series health effects assessment, the source-specific impacts were found to be highly correlated across analysis methods/researchers for the major components (e.g., mean analysis to analysis correlation, r>0.9 for traffic and secondary sulfates in Phoenix and for traffic and secondary nitrates in Washington. The sulfate mean r value is >0.75 in Washington.). Overall, although these intercomparisons suggest areas where further research is needed (e.g., better division of traffic emissions between diesel and gasoline vehicles), they provide support the contention that PM(2.5) mass source apportionment results are consistent across users and methods, and that today's source apportionment methods are robust enough for application to PM(2.5) health effects assessments.

Air Pollutants↗

PubMed2006

Impact of banning of two-stroke engines on airborne particulate matter concentrations in Dhaka, Bangladesh.

Vehicular air pollution is common in growing metropolitan areas throughout the world. Vehicular emissions of fine particles are particularly harmful because they occur near ground level, close to where people live and work. Two-stroke engines represented an important contribution to the motor vehicle emissions where they constitute approximately half of the total vehicle fleet in Dhaka city. Two-stroke engines have lower fuel efficiency than four-stroke engines, and they emit as much of an order of magnitude and more particulate matter (PM) than four-stroke engines of similar size. To eliminate their impact on air quality, the government of Bangladesh promulgated an order banning all two-stroke engines from the roads in Dhaka starting on December 31, 2002. The effect of the banning of two-stroke engines on airborne PM was studied at the Farm Gate air quality-monitoring station in Dhaka (capital of Bangladesh), a hot spot with very high-pollutant concentrations because of its proximity to major roadways. The samples were collected using a "Gent" stacked filter unit in two fractions of 0-2.2 microm and 2.2-10 microm sizes. Samples of fine and coarse fractions of airborne PM collected from 2000 to 2004 were studied. It has been found that the fine PM and black carbon concentrations decreased from the previous years because of the banning of two-stroke engine baby taxies.

Air Pollutants↗

PubMed2006

Influence of atmospheric dispersion and new particle formation events on ambient particle number concentration in Rochester, United States, and Toronto, Canada.

Continuous measurements of particle number concentrations were performed in Rochester, NY, and Toronto, Ontario, Canada during the 2003 calendar year. Strong seasonal dependency in particle number concentration was observed at two sites. The average number concentration of ambient particles was 9670 +/- 6960 cm(-3) in Rochester, whereas in Toronto the average number of particles was 28,010 +/- 13,350 cm(-3). The particle number concentrations were higher in winter months than in summer months by a factor of 1.5 in Rochester and 1.6 in Toronto. In general, there were also distinct diurnal variations of aerosol number concentration. The highest weekdays/weekends ratio of number concentration was typically observed during the rush-hour period in winter months with a ratio of 2.1 in Rochester and 2.0 in Toronto. The correlation in the total particle number concentrations between the two urban sites was stronger in winter because of the common urban traffic patterns, but weaker in summer because of local sulfur dioxide (SO2)-related particle formation events in Rochester in the summer. Strong morning particle formation events were frequently observed during colder winter months. Good correlations between particle number and carbon monoxide (CO) as well as temperature suggested that motorvehicle emissions lead to the formation of new particles as the exhaust mixes with the cold air. Regional nucleation and growth events frequently occurred in April. Local SO2-related particle formation events most frequently occurred in August. SO2 and UV-B were highly correlated with particle concentration, suggesting a high association of photochemical processes with these local events. A high directionality in a northerly direction was observed for particle number and SO2, indicating the influence of point sources located north of Rochester.

Air Pollutants↗

PubMed2006

Sources of fine particulate species in ambient air over lake Champlain Basin, VT.

This study is a part of an ongoing investigation of the types and locations of emission sources that contribute fine particulate air contaminants to Underhill, VT. The air quality monitoring data used for this study are from the Interagency Monitoring of Protected Visual Environments network for the period of 2001-2003 for the Underhill site. The main source-receptor modeling techniques used are the positive matrix factorization (PMF) and potential source contribution function (PSCF). This new study is intended as a comparison to a previous study of the 1988-1995 Underhill data that successfully revealed a total of 11 types of emission sources with significant contributions to this rural site. This new study has identified a total of nine sources: nitrate-rich secondary aerosol, wood smoke, East Coast oil combustion, automobile emission, metal working, soil/dust, sulfur-rich aerosol type I, sulfur-rich aerosol type II, and sea salt/road salt. Furthermore, the mass contributions from the PMF identified sources that correspond with sampling days with either good or poor visibility were analyzed to seek possible correlations. It has been shown that sulfur-rich aerosol type I, nitrate aerosol, and automobile emission are the most important contributors to visibility degradation. Soil/dust and sea salt/road salt also have an added effect.

Aerosols↗

PubMed2006

Comparison of source apportionments of fine particulate matter at two San Jose speciation trends network sites.

In this study, the chemical composition of fine particulate matter samples collected at U.S. Environmental Protection Agency Speciation Trends Network sites in San Jose, CA, from February 2000 to February 2005 were analyzed. A San Jose site was initially established at 4th Street and then subsequently moved to Jackson Street in mid-2002. These sites are approximately 1 km apart. There were no known major changes in the nature of the sources in the area over this period. The study used positive matrix factorization model to extract the source profiles and their mass contributions and to compare the results for the congruence of the source apportionments between these two nearby sites. In the case of the 4th Street site, the average mass was apportioned to wood combustion (32.1 +/- 2.5%), secondary nitrate (22.3 +/- 2%), secondary sulfate (10.7 +/- 0.6%), fresh sea salt (7.7 +/- 0.9%), gasoline vehicles (7.3 +/- 0.5%), aged sea salt (6.8 +/- 0.4%), road dust (6.7 +/- 0.7%), diesel emissions (3.9 +/- 0.3%), and a Ni-related industrial source (2.5 +/- 0.4%). At the Jackson Street site, the average mass was apportioned to wood combustion (33.6 +/- 2.6%), secondary nitrate (20.3 +/- 1.9%), secondary sulfate (13.9 +/- 0.9%), aged sea salt (12.4 +/- 0.7%), gasoline vehicle (8.3 +/- 0.6%), fresh sea salt (5.3 +/- 0.5%), diesel emission (3.2 +/- 0.3%), road dust (1.9 +/- 0.1%), and Ni-related industrial source (1.3 +/- 0.1%). Conditional probability function analysis was used to help identify local sources. These results suggested that moving the sampling site a short distance had little effect on the nature of the resolved source types although some differences in their quantitative impacts were obtained in the positive matrix factorization analyses.

Air Pollutants↗

PubMed2005

PM source apportionment and health effects: 2. An investigation of intermethod variability in associations between source-apportioned fine particle mass and daily mortality in Washington, DC.

Source apportionment may be useful in epidemiological investigation of PM health effects, but variations and options in these methods leave uncertainties. An EPA-sponsored workshop investigated source apportionment and health effects analyses by examining the associations between daily mortality and the investigators' estimated source-apportioned PM(2.5) for Washington, DC for 1988-1997. A Poisson Generalized Linear Model (GLM) was used to estimate source-specific relative risks at lags 0-4 days for total non-accidental, cardiovascular, and cardiorespiratory mortality adjusting for weather, seasonal/temporal trends, and day-of-week. Source-related effect estimates and their lagged association patterns were similar across investigators/methods. The varying lag structure of associations across source types, combined with the Wednesday/Saturday sampling frequency made it difficult to compare the source-specific effect sizes in a simple manner. The largest (and most significant) percent excess deaths per 5-95(th) percentile increment of apportioned PM(2.5) for total mortality was for secondary sulfate (variance-weighted mean percent excess mortality=6.7% (95% CI: 1.7, 11.7)), but with a peculiar lag structure (lag 3 day). Primary coal-related PM(2.5) (only three teams) was similarly significantly associated with total mortality with the same 3-day lag as sulfate. Risk estimates for traffic-related PM(2.5), while significant in some cases, were more variable. Soil-related PM showed smaller effect size estimates, but they were more consistently positive at multiple lags. The cardiovascular and cardiorespiratory mortality associations were generally similar to those for total mortality. Alternative weather models generally gave similar patterns, but sometimes affected the lag structure (e.g., for sulfate). Overall, the variations in relative risks across investigators/methods were found to be much smaller than those across estimated source types or across lag days for these data. This consistency suggests the robustness of the source apportionment in health effects analyses, but remaining issues, including accuracy of source apportionment and source-specific sensitivity to weather models, need to be investigated.

Air Pollutants↗

PubMed2005

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

As part of an EPA-sponsored workshop to investigate the use of source apportionment in health effects analyses, the associations between the participant's estimated source contributions of PM(2.5) for Phoenix, AZ for the period from 1995-1997 and cardiovascular and total nonaccidental mortality were analyzed using Poisson generalized linear models (GLM). The base model controlled for extreme temperatures, relative humidity, day of week, and time trends using natural spline smoothers. The same mortality model was applied to all of the apportionment results to provide a consistent comparison across source components and investigators/methods. Of the apportioned anthropogenic PM(2.5) source categories, secondary sulfate, traffic, and copper smelter-derived particles were most consistently associated with cardiovascular mortality. The sources with the largest cardiovascular mortality effect size were secondary sulfate (median estimate=16.0% per 5th-to-95th percentile increment at lag 0 day among eight investigators/methods) and traffic (median estimate=13.2% per 5th-to-95th percentile increment at lag 1 day among nine investigators/methods). For total mortality, the associations were weaker. Sea salt was also found to be associated with both total and cardiovascular mortality, but at 5 days lag. Fine particle soil and biomass burning factors were not associated with increased risks. Variations in the maximum effect lag varied by source category suggesting that past analyses considering only single lags of PM(2.5) may have underestimated health impact contributions at different lags. Further research is needed on the possibility that different PM(2.5) source components may have different effect lag structure. There was considerable consistency in the health effects results across source apportionments in their effect estimates and their lag structures. Variations in results across investigators/methods were small compared to the variations across source categories. These results indicate reproducibility of source apportionment results across investigative groups and support applicability of these methods to effects studies. However, future research will also need to investigate a number of other important issues including accuracy of results.

Air Pollutants↗

PubMed2005

Reconciling trajectory ensemble receptor model results with emissions.

Several approaches have been developed that use ensembles of air parcel back trajectories to identify likely source regions for contaminants observed at a downwind receptor site. Although the results of these models have appeared to provide results that agree with known sources, there have not been efforts to make direct comparisons between the results of such analyses with emissions inventories. In this paper, the results of residence time analysis (RTA) of data from Underhill, VT and from Brigantine, NJ are compared to the average estimated emissions of coal- and oil-fired power plants. Excellent correspondence was found between the areas of highest probability identified in the trajectory ensemble analyses and the averaged emission intensities.

Air Movements↗

PubMed2005

An algorithm for semi-empirical design of nucleation rate surface.

During the last half of century, Classical Nucleation Theory (CNT) has been developed and there have been advances in the molecular theory of nucleation. Most of these efforts have been directed towards small molecule system modeling using intermolecular potentials. Summarizing the nucleation theory, it can be concluded that the current theory is far from complete. Agreement is generally not obtained between experimental and theoretical results. In practical applications, parametric theories can be used for the systems of interest. However, experimental measurements are still the best source of information on nucleation. Experiments are labor intensive and costly, and thus, it is useful to extend the value of limited experimental measurements to a broader range of nucleation conditions. The available nucleation parameters represent only small regions of possible nucleation conditions over the range from the critical temperature to absolute zero. Thus, it is useful to develop better tools to use the data to estimate semi-empirical nucleation rate surfaces. Following our published approach, the nucleation rate surface for any system can be constructed over its phase diagram. This concept involves using the phase equilibrium diagram to establish lines of zero nucleation rates. Nucleation rate surfaces arise from equilibrium lines and their extensions that are representing unstable equilibria. Only limited experimental data is available for use in normalizing the slopes of the linearized nucleation rate surfaces. The nucleation rate surface is described in terms of steady-state nucleation rates. To design the surfaces of nucleation rates, several assumptions are presented. In the present study, an algorithm for the semi-empirical design of nucleation rate surfaces is introduced. The topology of the nucleation rate surface for a unary system using the example of water vapor nucleation is created semi-empirically. The nucleation of two concurrent (stable and unstable) phase states of critical embryos is considered in the context of multi-surface nucleation rates. Only one phase transition (melting) in the condensed state of water is considered for simplicity. The nucleation rate surface is constructed numerically using the available experimental results for vapor nucleation and phase diagram for water. The nucleation rate for water vapor is developed for the full temperature interval, i.e. from critical point to absolute zero. The results help to suggest a new direction for experimental nucleation research.

Journal Article↗

PubMed2005

Temporal variations and spatial distribution of ambient PM2.2 and PM10 concentrations in Dhaka, Bangladesh.

Concentrations and characteristics of airborne particulate matter (PM(10), PM(2.2) and BC) on air quality have been studied at two air quality-monitoring stations in Dhaka, the capital of Bangladesh. One site is at the Farm Gate area, a hot spot with very high pollutant concentrations because of its proximity to major roadways. The other site is at a semi-residential area located at the Atomic Energy Centre, Dhaka Campus, (AECD) with relatively less traffic. The samples were collected using a 'Gent' stacked filter unit in two fractions of 0-2.2 mum and 2.2-10 mum sizes. Samples of fine (PM(2.2)) and coarse (PM(2.2-10)) airborne particulate matter fractions collected from 2000 to 2003 were studied. It has been observed that fine particulate matter has a decreasing trend, from prior year measurements, because of Government policy interventions like phase-wise plans to take two-stroke three-wheelers off the roads in Dhaka and finally banned from January 1, 2003. Other policy interventions were banning of old buses and trucks to ply on Dhaka city promotion of the using compressed natural gas (CNG), introducing air pollution control devices in vehicles, etc. It was found that both local (mostly from vehicular emissions) and possibly some regional emission sources are responsible for high PM(2.2) and BC concentrations in Dhaka. PM(2.2), PM(2.2-10) and black carbon concentration levels depend on the season, wind direction and wind speed. Transport related emissions are the major source of BC and long-range transportation from fossil fuel related sources and biomass burning could be another substantial source of BC.

Air Pollutants↗

PubMed2005

Sources of fine particles in a rural midwestern U.S. area.

Ambient PM2.5 (particulate matter < or = 2.5 microm in aerodynamic diameter) samples collected at a rural monitoring site in Bondville, IL on every third day using Interagency Monitoring of Protected Visual Environments (IMPROVE) sampler were analyzed through the application of the positive matrix factorization (PMF). The particulate carbon fractions were obtained from the thermal optical reflectance method that divides particulate carbon into four organic carbon, pyrolyzed organic carbon (OP), and three elemental carbon fractions. A total of 257 samples collected between March 2001 and May 2003 analyzed for 35 species were used and eight sources were identified: summer-high secondary sulfate aerosol (40%), secondary nitrate aerosol (32%), gasoline vehicle (9%), OP-high secondary sulfate aerosol (7%), selenium-high secondary sulfate aerosol (4%), airborne soil (4%), aged sea salt (2%), and diesel emissions (2%). The compositional profiles for gasoline vehicle and diesel emissions are similar to those estimated in other U.S. areas. Backward trajectories indicate that the highly elevated airborne soil impacts were likely caused by Asian and Saharan dust storms. Potential source contribution function analyses show the potential source areas and pathways of secondary sulfate aerosols, especially the regional influences of the biogenic as well as anthropogenic secondary aerosol.

Air Pollutants↗

PubMed2005

Spatial variability of fine particle mass, components, and source contributions during the regional air pollution study in St. Louis.

Community time-series epidemiology typically uses either 24-hour integrated particulate matter (PM) concentrations averaged across several monitors in a city or data obtained at a central monitoring site to relate PM concentrations to human health effects. If the day-to-day variations in 24-hour integrated concentrations differ substantially across an urban area (i.e., daily measurements at monitors at different locations are not highly correlated), then there is a significant potential for exposure misclassification in community time-series epidemiology. If the annual average concentration differs across an urban area, then there is a potential for exposure misclassification in epidemiologic studies that use annual averages (or multi-year averages) as an index of exposure across different cities. The spatial variability in PM2.5 (particulate matter < or = 2.5 microm in aerodynamic diameter), its elemental components, and the contributions from each source category at 10 monitoring sites in St. Louis, Missouri were characterized using the ambient PM2.5 compositional data set of the Regional Air Pollution Study (RAPS) based on the Regional Air Monitoring System (RAMS) conducted between 1975 and 1977. Positive matrix factorization (PMF) was applied to each ambient PM2.5 compositional data set to estimate the contributions from the source categories. The spatial distributions of components and source contributions to PM2.5 at the 10 sites were characterized using Pearson correlation coefficients and coefficients of divergence. Sulfur and PM2.5 are highly correlated elements between all of the site pairs Although the secondary sulfate is the most highly correlated and shows the smallest spatial variability, there is a factor of 1.7 difference in secondary sulfate contributions between the highest and lowest site on average. Motor vehicles represent the next most highly correlated source component. However, there is a factor of 3.6 difference in motor vehicle contributions between the highest and lowest sites. The contributions from point source categories are much more variable. For example, the contributions from incinerators show a difference of a factor of 12.5 between the sites with the lowest and highest contributions. This study demonstrates that the spatial distributions of elemental components of PM2.5 and contributions from source categories can be highly heterogeneous within a given airshed and thus, there is the potential for exposure misclassification when a limited number of ambient PM monitors are used to represent population-average ambient exposures.

Air Pollutants↗

PubMed2005

Comparison between back-trajectory based modeling and Lagrangian backward dispersion modeling for locating sources of reactive gaseous mercury.

Reactive gaseous mercury (RGM) was measured using an annular denuder coated with potassium chloride at three rural sites (Potsdam, Stockton, and Sterling) in New York State from April 2002 to April 2003. Concentrations of RGM ranged from 0.1 to 84.6 pg m(-3) with large spatial and temporal variation. Potential source contribution function (PSCF), a common receptor modeling tool, was used with these measurements, and source-receptor relationships were calculated using back-dispersion and deposition as well as back-trajectories. Modeling results were compared with the RGM emissions inventory, and Spearman rank-order correlation coefficients were calculated. PSCF results incorporating backward dispersion and deposition were better correlated with the emissions inventory than PSCF based on back-trajectories alone. This difference was determined to be mainly due to the inclusion of dispersion rather than deposition. The main sources of RGM were suggested to be coal-fired power plants in New York and Pennsylvania, the large copper smelter in Quebec, and the taconite mining areas around the Great Lakes.

Air Movements↗

PubMed2005

Source identification of fine particles in Washington, DC, by expanded factor analysis modeling.

An expanded factor analysis model (ME-2) that is capable of taking into account the influence of independent variables such as wind speed, wind direction, time of year and other variables of the measured fine particle matter (PM2.5) concentration data was utilized for identifying sources of airborne pollutants and providing quantitative estimations of the contribution of each source. The chemical composition data used in this study were obtained from PM2.5 samples collected using the Interagency Monitoring of Protected Visual Environments samplers from August 1999 to December 2001 at an urban monitoring site in Washington, DC. The expanded model has been applied to two different data sets based on the particulate carbon variables. Such an approach had been successfully applied previously and provided improved source resolution in simulated and ambient concentration data. Initially, total OC and EC were used in the expanded model and were compared to the results using conventional positive matrix factorization that had been done previously using the individual carbon fractions data. In the other expanded model analysis, the eight carbon fractions were used during the modeling in order to ascertain if additional source information could be extracted from the data. In both cases, it was possible to separate diesel from spark-ignition vehicles. The use of the individual carbon fractions in the model provides information on what appears to be secondary organic aerosol formation.

Air Pollutants↗

PubMed2005

Investigation of sources of atmospheric aerosol at a hot spot area in Dhaka, Bangladesh.

Samples of fine and coarse fractions of airborne particulate matter were collected at the Farm Gate area in Dhaka from July 2001 to March 2002. Dhaka is a hot spot area with very high pollutant concentrations because of the proximity of major roadways. The samples were collected using a "Gent" stacked filter unit in two fractions of 0- to 2.2-microm and 2.2- to 10-microm sizes. The samples were analyzed for elemental concentrations by particle-induced X-ray excitation (PIXE) and for black carbon by reflectivity methods, respectively. The data were analyzed by positive matrix factorization (PMF) to identify the possible sources of atmospheric aerosols in this area. Six sources were found for both the coarse and fine PM fractions. The data sets were also analyzed by an expanded model to explore additional sources. Seven and six factors were obtained for coarse and fine PM fractions, respectively, in these analyses. The identified sources are motor vehicle, soil dust, emissions from construction activities, sea salt, biomass burning/brick kiln, resuspended/fugitive Pb, and two-stroke engines. From the expanded modeling, approximately 50% of the total PM2.2 mass can be attributed to motor vehicles, including two-stroke engine vehicle in this hot spot in Dhaka, whereas the PMF modeling indicates that 45% of the total PM2.2 mass is from motor vehicles. The PMF2 and expanded models could resolve approximately 4% and 3% of the total PM2.2 mass as resuspended/fugitive Pb, respectively. Although, Pb has been eliminated from gasoline in Bangladesh since July 1999, there still may be substantial amounts of accumulated lead in the dust near roadways as well as fugitive Pb emissions from battery reclaimation and other industries. Soil dust is the largest component of the coarse particle fraction (PM2.2-10) accounting for approximately 71% of the total PM2.2-10 mass in the expanded model, whereas from the PMF modeling, the dust (undifferentiated) contribution is approximately 49%.

Aerosols↗