Chemical Mass Balance Source Apportionment Research Articles

Wintertime Air Quality across the Kathmandu Valley, Nepal: Concentration, Composition, and Sources of Fine and Coarse Particulate Matter.

The Kathmandu Valley in Nepal experiences poor air quality, especially in the dry winter season. In this study, we investigated the concentration, chemical composition, and sources of fine and coarse particulate matter (PM2.5, PM10, and PM10-2.5) at three sites within or near the Kathmandu Valley during the winter of 2018 as part of the second Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE 2). Daily PM2.5 concentrations were very high throughout the study period, ranging 72-149 μg m-3 at the urban Ratnapark site in Kathmandu, 88-161 μg m-3 at the suburban Lalitpur site, and 40-74 μg m-3 at rural Dhulikhel on the eastern rim of the Kathmandu Valley. Meanwhile, PM10 ranged 194-309, 174-377, and 64-131 μg m-3, respectively. At the Ratnapark site, crustal materials from resuspended soil contributed an average of 11% of PM2.5 and 34% of PM10. PM2.5 was largely comprised of organic carbon (OC, 28-30% by mass) and elemental carbon (EC, 10-14% by mass). As determined by chemical mass balance source apportionment modeling, major PM2.5 OC sources were garbage burning (15-21%), biomass burning (10-17%), and fossil fuel (14-26%). Secondary organic aerosol (SOA) contributions from aromatic volatile organic compounds (13-23% OC) were larger than those from isoprene (0.3-0.5%), monoterpenes (0.9-1.4%), and sesquiterpenes (3.6-4.4%). Nitro-monoaromatic compounds-of interest due to their light-absorbing properties and toxicity-indicate the presence of biomass burning-derived SOA. Knowledge of primary and secondary PM sources can facilitate air quality management in this region.

Application of an improved gas-constrained source apportionment method using data fused fields: A case study in North Carolina, USA

A number of studies have found differing associations of disease outcomes with PM2.5 components (or species) and sources (e.g., biomass burning, diesel vehicles and gasoline vehicles). Here, a unique method of fusing daily chemical transport model (Community Multiscale Air Quality Modeling) results with observations has been utilized to generate spatiotemporal fields of the concentrations of major gaseous pollutants (CO, NO2, NOx, O3, and SO2), total PM2.5 mass, and speciated PM2.5 (including crustal elements) over North Carolina for 2002–2010. The fused results are then used in chemical mass balance source apportionment model, CMBGC-Iteration, which uses both gas constraint and particulate matter concentrations to quantify source impacts. The method, as applied to North Carolina, quantifies the impacts of ten source categories and provides estimates of source contributions to PM2.5 concentrations. The ten source categories include both primary sources (diesel vehicles, gasoline vehicles, dust, biomass burning, coal-fired power plants and sea salt) and secondary components (ammonium sulfate, ammonium bisulfate, ammonium nitrate and secondary organic carbon). The results show a steady decrease in anthropogenic source impacts, especially from diesel vehicles and coal-fired power plants. Secondary pollutant components accounted for approximately 70% of PM2.5 mass. This study demonstrates an ability to provide spatiotemporal fields of both PM components and source impacts using a chemical transport model fused with observation data, linked to a receptor-based source apportionment method, to develop spatiotemporal fields of multiple pollutants.

Ambient air quality in the Kathmandu Valley, Nepal, during the pre-monsoon: concentrations and sources of particulate matter and trace gases

Abstract. The Kathmandu Valley in Nepal is a bowl-shaped urban basin that experiences severe air pollution that poses health risks to its 3.5 million inhabitants. As part of the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE), ambient air quality in the Kathmandu Valley was investigated from 11 to 24 April 2015, during the pre-monsoon season. Ambient concentrations of fine and coarse particulate matter (PM2.5 and PM10, respectively), online PM1, inorganic trace gases (NH3, HNO3, SO2, and HCl), and carbon-containing gases (CO2, CO, CH4, and 93 non-methane volatile organic compounds; NMVOCs) were quantified at a semi-urban location near the center of the valley. Concentrations and ratios of NMVOC indicated origins primarily from poorly maintained vehicle emissions, biomass burning, and solvent/gasoline evaporation. During those 2 weeks, daily average PM2.5 concentrations ranged from 30 to 207 µg m−3, which exceeded the World Health Organization 24 h guideline by factors of 1.2 to 8.3. On average, the non-water mass of PM2.5 was composed of organic matter (48 %), elemental carbon (13 %), sulfate (16 %), nitrate (4 %), ammonium (9 %), chloride (2 %), calcium (1 %), magnesium (0.05 %), and potassium (1 %). Large diurnal variability in temperature and relative humidity drove corresponding variability in aerosol liquid water content, the gas–aerosol phase partitioning of NH3, HNO3, and HCl, and aerosol solution pH. The observed levels of gas-phase halogens suggest that multiphase halogen-radical chemistry involving both Cl and Br impacted regional air quality. To gain insight into the origins of organic carbon (OC), molecular markers for primary and secondary sources were quantified. Levoglucosan (averaging 1230±1154 ng m−3), 1,3,5-triphenylbenzene (0.8±0.6 ng m−3), cholesterol (2.9±6.6 ng m−3), stigmastanol (1.0 ±0.8 ng m−3), and cis-pinonic acid (4.5±1.9 ng m−3) indicate contributions from biomass burning, garbage burning, food cooking, cow dung burning, and monoterpene secondary organic aerosol, respectively. Drawing on source profiles developed in NAMaSTE, chemical mass balance (CMB) source apportionment modeling was used to estimate contributions to OC from major primary sources including garbage burning (18±5 %), biomass burning (17±10 %) inclusive of open burning and biomass-fueled cooking stoves, and internal-combustion (gasoline and diesel) engines (18±9 %). Model sensitivity tests with newly developed source profiles indicated contributions from biomass burning within a factor of 2 of previous estimates but greater contributions from garbage burning (up to three times), indicating large potential impacts of garbage burning on regional air quality and the need for further evaluation of this source. Contributions of secondary organic carbon (SOC) to PM2.5 OC included those originating from anthropogenic precursors such as naphthalene (10±4 %) and methylnaphthalene (0.3±0.1 %) and biogenic precursors for monoterpenes (0.13±0.07 %) and sesquiterpenes (5±2 %). An average of 25 % of the PM2.5 OC was unapportioned, indicating the presence of additional sources (e.g., evaporative and/or industrial emissions such as brick kilns, food cooking, and other types of SOC) and/or underestimation of the contributions from the identified source types. The source apportionment results indicate that anthropogenic combustion sources (including biomass burning, garbage burning, and fossil fuel combustion) were the greatest contributors to PM2.5 and, as such, should be considered primary targets for controlling ambient PM pollution.

Source-specific Fine Particulate Using Spatiotemporal Concentration Fields Developed using Chemical Transport Modelling and Data Assimilation

OPS 47: Increasing spatiotemporal resolution in assessment of exposure to outdoor air pollutants, Room 412, Floor 4, August 27, 2019, 4:30 PM - 5:30 PM A number of studies have found differing associations of disease outcomes with PM2.5 components (or species), and sources (e.g., biomass burning, diesel vehicle and gasoline vehicle). Here, a unique data fusion method has been utilized to generate spatiotemporal fields of major gaseous pollutants and PM2.5 components (e.g., ozone, NO2, SO2, total PM2.5 mass and speciated PM2.5 including crustal metals) over North Carolina for 2002-2010. In a prior study, the PM2.5 total mass field was used as part of the CATHGEN study of associations between PM2.5 and disease associated with cardiac heart disease patients. Here, we extend the exposure method for further health analyses. The method fuses daily CMAQ model observations with observations to develop accurate spatiotemporal maps of pollutant concentrations. Those results are then used in an advanced chemical mass balance source apportionment model, CMBGC-Iteration that uses both gas and particulate matter concentrations to quantify source impacts. The method, as applied to North Carolina, quantifies the impacts of nine source categories and estimate source contributions of total PM2.5 mass. The nine source categories include sources of both primary (diesel vehicle, gasoline vehicle, suspended dust, biomass burning, and coal combustion sources) and secondary components (ammonium sulfate, ammonium bisulfate, ammonium nitrate and secondary organic carbon). The results show the dramatic decrease in source impacts, e.g., sulfate, primarily from coal-burning, and from mobile sources. Secondary organic aerosol, e.g., from biogenic emissions, is becoming more dominant over the state. This study highlights an advantage of using a chemical transport model to develop spatiotemporal fields of pollutants, i.e., the ability to assess PM components and their sources.

Source apportionment of PM2.5 organic carbon in the San Joaquin Valley using monthly and daily observations and meteorological clustering

Two hundred sixty-three fine particulate matter (PM2.5) samples collected on 3-day intervals over a 14-month period at two sites in the San Joaquin Valley (SJV) were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC), and organic molecular markers. A unique source profile library was applied to a chemical mass balance (CMB) source apportionment model to develop monthly and seasonally averaged source apportionment results. Five major OC sources were identified: mobile sources, biomass burning, meat smoke, vegetative detritus, and secondary organic carbon (SOC), as inferred from OC not apportioned by CMB. The SOC factor was the largest source contributor at Fresno and Bakersfield, contributing 44% and 51% of PM mass, respectively. Biomass burning was the only source with a statistically different average mass contribution (95% CI) between the two sites. Wintertime peaks of biomass burning, meat smoke, and total OC were observed at both sites, with SOC peaking during the summer months. Exceptionally strong seasonal variation in apportioned meat smoke mass could potentially be explained by oxidation of cholesterol between source and receptor and trends in wind transport outlined in a Residence Time Analysis (RTA). Fast moving nighttime winds prevalent during warmer months caused local emissions to be replaced by air mass transported from the San Francisco Bay Area, consisting of mostly diluted, oxidized concentrations of molecular markers. Good agreement was observed between SOC derived from the CMB model and from non-biomass burning WSOC mass, suggesting the CMB model is sufficiently accurate to assist in policy development. In general, uncertainty in monthly mass values derived from daily CMB apportionments were lower than that of CMB results produced with monthly marker composites, further validating daily sampling methodologies.Strong seasonal trends were observed for biomass and meat smoke OC apportionment, and monthly mass averages had lowest uncertainty when derived from daily CMB apportionments.

Influence of rain on the abundance of bioaerosols in fine and coarse particles

Abstract. Assessing the environmental, health, and climate impacts of bioaerosols requires knowledge of their size and abundance. These two properties were assessed through daily measurements of chemical tracers for pollens (sucrose, fructose, and glucose), fungal spores (mannitol and glucans), and Gram-negative bacterial endotoxins in two particulate matter (PM) size modes: fine particles (< 2.5 µm) and coarse particles (2.5–10 µm) as determined by their aerodynamic diameter. Measurements were made during the spring tree pollen season (mid-April to early May) and late summer ragweed season (late August to early September) in the Midwestern US in 2013. Under dry conditions, pollen, and fungal spore tracers were primarily in coarse PM (> 75 %), as expected for particles greater than 2.5 µm. Rainfall on 2 May corresponded to maximum atmospheric pollen tracer levels and a redistribution of pollen tracers to the fine PM fraction (> 80 %). Both changes were attributed to the osmotic rupture of pollen grains that led to the suspension of fine-sized pollen fragments. Fungal spore tracers peaked in concentration following spring rain events and decreased in particle size, but to a lesser extent than pollens. A short, heavy thunderstorm in late summer corresponded to an increase in endotoxin and glucose levels, with a simultaneous shift to smaller particle sizes. Simultaneous increase in bioaerosol levels and decrease in their size have significant implications for population exposures to bioaerosols, particularly during rain events. Chemical mass balance (CMB) source apportionment modeling and regionally specific pollen profiles were used to apportion PM mass to pollens and fungal spores. Springtime pollen contributions to the mass of particles < 10 µm (PM10) ranged from 0.04 to 0.8 µg m−3 (0.2–38 %, averaging 4 %), with maxima occurring on rainy days. Fungal spore contributions to PM10 mass ranged from 0.1 to 1.5 µg m−3 (0.8–17 %, averaging 5 %), with maxima occurring after rain. Overall, this study defines changes to the fine- and coarse-mode distribution of PM, pollens, fungal spores, and endotoxins in response to rain in the Midwestern United States and advances the ability to apportion PM mass to pollens.

Chemical mass balance source apportionment of fine and PM<sub>10</sub> in the Desert Southwest, USA

The Desert Southwest Coarse Particulate Matter Study was undertaken in Pinal County, Arizona, to better understand the origin and impact of sources of fine and coarse particulate matter (PM) in rural, arid regions of the U.S. southwestern desert. The desert southwest experiences some of the highest PM10 mass concentrations in the country. To augment previously reported results, 6-week aggregated organic speciation data that included ambient concentrations of n-alkanes, polycyclic aromatic hydrocarbons, organic acids, and saccharides were used in chemical mass balance modeling (CMB). A set of re-suspended soil samples were analyzed for specific marker species to provide locally-appropriate source profiles for the CMB analysis. These profiles, as well as previously collected plant and fungal spore profiles from the region, were combined with published source profiles for other relevant sources and used in the CMB analysis. The six new region-specific source profiles included both organic and inorganic species for four crustal material sources, one plant detritus source, and one fungal spore source. Results indicate that up to half of the ambient PM2.5 was apportioned to motor vehicles with the highest regional contribution observed in the small urban center of Casa Grande. Daily levels of apportioned crustal material accounted for up to 50% of PM2.5 mass with the highest contributions observed at the sites closest to active agricultural areas. Apportioned secondary PM, biomass burning, and road dust typically contributed less than 35% as a group to the apportioned PM2.5 mass. Crustal material was the primary source apportioned to PM10 and accounted for between 50–90% of the apportioned mass. Of the other sources apportioned to PM10, motor vehicles and road dust were the largest contributors at the urban and one of the rural sites, whereas road dust and meat cooking operations were the largest contributors at the other rural site.

Source Contributions to Wintertime Elemental and Organic Carbon in the Western Arctic Based on Radiocarbon and Tracer Apportionment.

To quantify the contributions of fossil and biomass sources to the wintertime Arctic aerosol burden source apportionment is reported for elemental (EC) and organic carbon (OC) fractions of six PM10 samples collected during a wintertime (2012-2013) campaign in Barrow, AK. Radiocarbon apportionment of EC indicates that fossil sources contribute an average of 68 ± 9% (0.01-0.07 μg m(-3)) in midwinter decreasing to 49 ± 6% (0.02 μg m(-3)) in late winter. The mean contribution of fossil sources to OC for the campaign was stable at 38 ± 8% (0.04-0.32 μg m(-3)). Samples were also analyzed for organic tracers, including levoglucosan, for use in a chemical mass balance (CMB) source apportionment model. The CMB model was able to apportion 24-53% and 99% of the OC and EC burdens, respectively, during the campaign, with fossil OC contributions ranging from 25 to 74% (0.02-0.09 μg m(-3)) and fossil EC contributions ranging from 73 to 94% (0.03-0.07 μg m(-3)). Back trajectories identified two major wintertime source regions to Barrow: the Russian and North American Arctic. Atmospheric lifetimes of levoglucosan, ranging from 50 to 320 h, revealed variability in wintertime atmospheric processing of this biomass burning tracer. This study allows for unambiguous apportionment of EC to fossil fuel and biomass combustion sources and intercomparison with CMB modeling.

Chemical Mass Balance Source Apportionment of Size-Fractionated Particulate Matter in Nanjing, China

In recent years, atmospheric particulate matter has become the primary air pollutant in Nanjing, China. In order to support a scientific basis for particles reduction, it is of great importance to investigate the contribution of different sources to particulate matter. In this paper, the characteristics of chemical composition of observational data for size-fractionated particulate matter at Gulou site and Pukou site in Nanjing from May 2010 to April 2011 were analyzed. Emission samples of particulate matter were collected and size-fractionated particulate chemical compositions were analyzed to obtain the source profiles. A chemical mass balance (CMB) model was applied to apportion the contribution rate of different sources. Investigations show that the annual average concentrations of PM10 (particles with an aerodynamic diameter of 10 µm or less) at Gulou and Pukou are 135.8 ± 66.4 μg m–3 and 132.2 ± 73.0 μg m–3, respectively. For PM2.1, the concentrations are 55.1 ± 36.3 μg m–3 and 64.8 ± 40.2 μg m–3, respectively. The dominant chemical constituents are SO42–, NO3–, Ca, NH4+, Cl–, Fe, Al, and K, accounting for 93.02% and 91.56% of all of the measured compositions in PM10 at Gulou and Pukou. These components account for 95.23% and 93.48% of PM2.1 at Gulou and Pukou. Seven types of sources, including coal combustion dust, construction dust, smelting dust, soil dust, vehicle exhaust, secondary aerosols and sea salt, are considered. The results of source apportionment show that in coarse particles, construction dust contributes a maximum of 58.9% at Gulou and 47.3% at Pukou. Smelting dust, as the second most important source, contributes 14.1% and 19.7% at these two sites. For fine particulate matter, secondary inorganic aerosols and coal dust contribution are the two largest sources accounting for 58.8% and 15.9% at Gulou and 44.2% and 39.5% at Pukou. The findings will be useful for the local government to create efficient control strategies to reduce the emission of construction dust and to pay great attention to the prevention of secondary aerosols and coal combustion dust.

Source apportionment of atmospheric particulate carbon in Las Vegas, Nevada, USA

A study was conducted to quantify wintertime contributions of source types to carbonaceous PM2.5 at four urban sites in the Las Vegas Valley, one of the most rapidly growing urban areas in the southwestern United States. Twenty-four hour average ambient samples were collected for mass, ions, elements, organic carbon (OC), elemental carbon (EC), and trace organic markers analysis. Additional measurements were made to determine diurnal patterns in light-absorbing black carbon (BC) as a marker for combustion sources. Carbonaceous PM sources of on-road gasoline vehicles, on-road diesel vehicles, and off-road diesel engines were characterized with their chemical profiles, as well as fuel-based emission factors, using an In-Plume Sampling System. The Effective Variance Chemical Mass Balance (EV-CMB) source apportionment model was applied to the ambient samples collected, using source profiles developed in this study as well as profiles from other relevant studies. Four main sources contributed to PM2.5 carbon within the Las Vegas Valley: (1) paved road dust, (2) on-road gasoline vehicles, (3) residential wood combustion, and (4) on-road diesel vehicles. CMB estimated that on-road mixed fleet gasoline vehicles are the largest source for OC and EC at all the sites. The contribution of paved road dust to both OC and EC was 5–10% at the four sites. On-road diesel vehicles contribute 22% of the OC and 34% of the EC at a site near the city center, which is located immediately downwind of a major freeway. Residential wood combustion is a more important source than on-road diesel vehicles for two residential neighborhood sites. These results are consistent with our conceptual model, and the research methodology may be applied to studying other urban areas.

Bayesian Chemical Mass Balance Method for Surface Water Contaminant Source Apportionment

AbstractA Bayesian chemical mass balance (CMB) source apportionment method is developed using the Markov Chain Monte Carlo (MCMC) approach. Compared with deterministic approaches, the Bayesian method is capable of accounting for the measurement errors and the impact of variability of the source elemental compositions resulting from the heterogeneities and estimate the uncertainties associated with the estimated source contributions. The method estimates the joint probability densities and consequently, the credible intervals and correlation matrices of source contributions of various sources into a receiving water using observed elemental profiles of samples from both potential sources and the receiving surface waters. The model is applied to samples collected from possible sources and runoff and stream flow from two stream crossing sites along Highway 89 in the Lake Tahoe Basin. The contributing sources of total dissolved nitrogen, total dissolved phosphorus concentrations, and microparticles (<20 μm) f...

Corrigendum to “Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks” [Atmos. Environ. 44 (2010) 4908–4918

A mislabeling of sampling sites was discovered after final proofing of the paper. GRRI data were labeled as BLMO and BLMO data were labeled as GRRI in Table 2e3, Figs. 2 and 3, and supplemental Table S1 and S4. Texts that explain the tables and figures also need to be corrected. Since the two sites were discussed as a group for the most part, the mislabeling does not change the conclusions of the paper except for Section 5.2: Inter-network differences. In Section 5.2, GRRI source apportionment results were compared with those from ROC (see the 5th and 6th paragraphs). It was concluded that ROC and GRRI (really BLMO) showed similar contributions from regional sources secondary sulfate (including coal-fired utility), secondary nitrate, and soil dust. When ROC is compared with the actual GRRI, secondary sulfate contributions are similar (2.67 versus 2.72 mgm 3), but ROC shows higher secondary nitrate, secondary organic carbon, soil dust, Ca-rich dust, engine exhaust, and road salt contributions than GRRI. Biomass burning contributions are 36e39% lower at ROC. These differences may be explained by local activities around ROC (e.g., traffic, construction, and de-icing) and GRRI (e.g., campfires). The reconstructed PM2.5 concentrations were 102% and 99% of measured PM2.5 mass at ROC and GRRI, respectively. Other changes include:

Chemical Mass Balance Source Apportionment of Ambient Total Suspended Particulate Matters Near Jhuoshuei River in Central Taiwan

Based on an investigation of ambient total suspended particulate (TSP) matter concentrations, this study not only evaluates how the TSP levels deteriorate the air quality near Jhuoshuei River in central Taiwan, but also demonstrates that the monsoon season profoundly influences ambient TSP concentrations. Samples of ambient TSP obtained from representative areas in target areas during monsoon and other seasons in 2005–2006 were collected for use in receptor modeling. A chemical mass balance model version 8 (CMB8) developed by the United States Environmental Protection Agency, was implemented based on TSP emission information from version 5.1 of the Taiwan Emission Data System (TEDS5.1) and a source profile from SPECIATE3.2. CMB8 model estimates indicated that windblown soil coming from the Jhuoshuei riverbed largely contributed to the receptor site during the monsoon season. Statistical analysis revealed that metal species appearing during the monsoon season have a higher correlation with each other than during other seasons. The well-known fact that these elements are emitted from soil suggests that the soil source significantly contributes to TSP concentration at downwind sampling sites during the monsoon season. Moreover, the concentration of TSPs at downwind sites is significantly higher than that at upwind site during monsoons, posing a potential risk to human health in the downwind residential communities.

Chemical mass balance source apportionment for combined PM 2.5 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.

Fine Particulate Matter Source Apportionment Following a Large Woodstove Changeout Program in Libby, Montana

Before a community-wide woodstove changeout program, a chemical mass balance (CMB) source apportionment study was conducted in Libby, MT, during the winter of 2003–2004 to identify the sources of fine particulate matter (PM2.5) within the valley. Results from this study showed that residential woodstoves were the major source, contributing approximately 80% of the ambient PM2.5 throughout the winter months. In an effort to lower the ambient PM2.5, a large woodstove changeout program was conducted in Libby from 2005 to 2007 in which nearly 1200 old woodstoves were changed out with cleaner burning models. During the winter of 2007–2008, a follow-up CMB source apportionment study was conducted to evaluate the effectiveness of the changeout. Results from this study showed that average winter PM2.5 mass was reduced by 20%, and woodsmoke-related PM2.5 (as identified by the CMB model) was reduced by 28% when compared with the pre-changeout winter of 2003– 2004. These results suggest that a woodstove changeout can be an effective tool in reducing ambient levels of PM2.5 in woodstove-impacted communities.

Insights into the Origin of Water Soluble Organic Carbon in Atmospheric Fine Particulate Matter

Concentrations of fine carbonaceous aerosols (PM 2.5 ), including elemental carbon (EC), organic carbon (OC), and water-soluble organic carbon (WSOC) were measured from filters collected every 6th day for one year at three urban/industrial sites in the Midwestern United States: Cincinnati, Cleveland, and Mingo Junction, Ohio. The water-soluble fraction of fine particulate OC varied considerably from site to site and monthly averages were between 39–85% at Cincinnati, 35–68% at Cleveland, and 32–65% at Mingo Junction. Average monthly concentrations of WSOC were compared with measurements of organic source tracers, including levoglucosan, to better understand the spatial and temporal distribution and sources of WSOC. Two methods of predicting the non-biomass burning portion of WSOC (WSOC NB ) were compared including estimation of secondary organic carbon (SOC) by the EC-tracer Method and comparison of the unapportioned OC from a chemical mass balance (CMB) source apportionment analysis. Poor correlations be...

Assessment of diesel particulate matter exposure in the workplace: freight terminals

A large study has been undertaken to assess the exposure to diesel exhaust within diesel trucking terminals. A critical component of this assessment is an analysis of the variation in carbonaceous particulate matter (PM) across trucking terminal locations; consistency in the primary sources can be effectively tracked by analyzing trends in elemental carbon (EC) and organic molecular marker concentrations. Ambient samples were collected at yard, dock and repair shop work stations in 7 terminals in the USA and 1 in Mexico. Concentrations of EC ranged from 0.2 to 12 microg m(-3) among the terminals, which corresponds to the range seen in the concentration of summed hopanes (0.5 to 20.5 ng m(-3)). However, when chemical mass balance (CMB) source apportionment results were presented as percent contribution to organic carbon (OC) concentrations, the contribution of mobile sources to OC are similar among the terminals in different cities. The average mobile source percent contribution to OC was 75.3 +/- 17.1% for truck repair shops, 65.4 +/- 20.4% for the docks and 38.4 +/- 9.5% for the terminal yard samples. A relatively consistent mobile source impact was present at all the terminals only when considering percentage of total OC concentrations, not in terms of absolute concentrations.

Ft. McHenry tunnel study: Source profiles and mercury emissions from diesel and gasoline powered vehicles

During the fall of 1998, the US Environmental Protection Agency and the Florida Department of Environmental Protection sponsored a 7-day study at the Ft. McHenry tunnel in Baltimore, MD with the objective of obtaining PM 2.5 vehicle source profiles for use in atmospheric mercury source apportionment studies. PM 2.5 emission profiles from gasoline and diesel powered vehicles were developed from analysis of trace elements, polycyclic aromatic hydrocarbons (PAH), and condensed aliphatic hydrocarbons. PM 2.5 samples were collected using commercially available sampling systems and were extracted and analyzed using conventional well-established methods. Both inorganic and organic profiles were sufficiently unique to mathematically discriminate the contributions from each source type using a chemical mass balance source apportionment approach. However, only the organic source profiles provided unique PAH tracers (e.g., fluoranthene, pyrene, and chrysene) for diesel combustion that could be used to identify source contributions generated using multivariate statistical receptor modeling approaches. In addition, the study found significant emission of gaseous elemental mercury (Hg 0), divalent reactive gaseous mercury (RGM), and particulate mercury (Hg(p)) from gasoline but not from diesel powered motor vehicles. Fuel analysis supported the tunnel measurement results showing that total mercury content in all grades of gasoline (284±108 ng L −1) was substantially higher than total mercury content in diesel fuel (62±37 ng L −1) collected contemporaneously at local Baltimore retailers.

Positive Matrix Factorization (PMF) Analysis of Molecular Marker Measurements to Quantify the Sources of Organic Aerosols

One hundred and twenty five particulate matter samples that were collected over a 2 year period at the St. Louis Midwest Supersite were analyzed for 24 hour average organic carbon (OC), elemental carbon (EC), and particle-phase organic compound (molecular markers) concentrations. Over 100 organic compounds along with measurements of silicon and aluminum were analyzed using a factor analysis based source apportionment model, positive matrix factorization (PMF), which has been widely used in the past with elemental data but not organic molecular markers. Four different solutions (7, 8, 9, and 10 factor solutions) to the PMF model were explored to consider the stability of the source apportionment results, which were found to be reasonably stable. The eight-factor solution was further explored and compared to a parallel chemical mass balance (CMB) source apportionment modeling result that used a subset of the PMF data. A base case eight-factor PMF solution resolved two point source factors, two winter combustion factors, a biomass-burning factor, a mobile source factor, a secondary organic aerosol factor, and a resuspended soil factor. An optimized eight-factor case was also examined, which was formulated by removing three extreme point source impacts observed in the base case, to better understand the nonpoint sources. In the optimized case, the daily OC explained by the biomass burning shows good agreement with the corresponding CMB source, with a slope of 0.93 +/- 0.03. Likewise, the average OC explained by the optimized PMF resuspended soil factor showed good correlation with the CMB road dust apportionment, but there was a significant bias between the two results. The optimized PMF OC from one of the winter combustion factors showed good correlation with the CMB natural gas combustion apportionment but also has a significant bias. In both cases, PMF analysis factored one mobile source controlled by hopanes and streranes, which did not correlate well with any of the three CMB mobile sources. Although the most of the molecular markers were clustered with the PMF model in a manner consistent with prior knowledge of these organic compounds, one significant deviation was observed. Cholesterol, used in the past as a tracer for meat smoke, was found to largely associate with road dust, which raises questions on the suitability of cholesterol as a tracer for meat smoke in the midwestern U.S.

Evaluation of organic markers for chemical mass balance source apportionment at the Fresno Supersite

Abstract. Sources of PM2.5 at the Fresno Supersite during high PM2.5 episodes occurring from 15 December 2000–3 February 2001 were estimated with the Chemical Mass Balance (CMB) receptor model. The ability of source profiles with organic markers to distinguish motor vehicle, residential wood combustion (RWC), and cooking emissions was evaluated with simulated data. Organics improved the distinction between gasoline and diesel vehicle emissions and allowed a more precise estimate of the cooking source contribution. Sensitivity tests using average ambient concentrations showed that the gasoline vehicle contribution was not resolved without organics. Organics were not required to estimate hardwood contributions. The most important RWC marker was the water-soluble potassium ion. The estimated cooking contribution did not depend on cholesterol because its concentrations were below the detection limit in most samples. Winter time source contributions were estimated by applying the CMB model to individual and average sample concentrations. RWC was the largest source, contributing 29–31% of measured PM2.5. Hardwood and softwood combustion accounted for 16–17% and 12–15%, respectively. Secondary ammonium nitrate and motor vehicle emissions accounted for 31–33% and 9–15%, respectively. The gasoline vehicle contribution (3–10%) was comparable to the diesel vehicle contribution (5–6%). The cooking contribution was 5–19% of PM2.5. Fresno source apportionment results were consistent with those estimated in previous studies.