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Positive matrix factorization of PM2.5 - eliminating the effects of gas/particle partitioning of semivolatile organic compounds.

ABSTRACT: Gas-phase concentrations of semi-volatile organic compounds (SVOCs) were calculated from gas/particle (G/P) partitioning theory using their measured particle-phase concentrations. The particle-phase data were obtained from an existing filter measurement campaign (27 January 2003-2 October 2005) as a part of the Denver Aerosol Sources and Health (DASH) study, including 970 observations of 71 SVOCs (Xie et al., 2013). In each compound class of SVOCs, the lighter species (e.g. docosane in n alkanes, fluoranthene in PAHs) had higher total concentrations (gas + particle phase) and lower particle-phase fractions. The total SVOC concentrations were analyzed using positive matrix factorization (PMF). Then the results were compared with source apportionment results where only particle-phase SVOC concentrations were used (particle only-based study; Xie et al., 2013). For the particle only-based PMF analysis, the factors primarily associated with primary or secondary sources (n alkane, EC/sterane and inorganic ion factors) exhibit similar contribution time series (r = 0.92-0.98) with their corresponding factors (n alkane, sterane and nitrate+sulfate factors) in the current work. Three other factors (light n alkane/PAH, PAH and summer/odd n alkane factors) are linked with pollution sources influenced by atmospheric processes (e.g. G/P partitioning, photochemical reaction), and were less correlated (r = 0.69-0.84) with their corresponding factors (light SVOC, PAH and bulk carbon factors) in the current work, suggesting that the source apportionment results derived from particle-only SVOC data could be affected by atmospheric processes. PMF analysis was also performed on three temperature-stratified subsets of the total SVOC data, representing ambient sampling during cold (daily average temperature < 10 °C), warm (? 10 °C and ? 20 °C) and hot (> 20 °C) periods. Unlike the particle only-based study, in this work the factor characterized by the low molecular weight (MW) compounds (light SVOC factor) exhibited strong correlations (r = 0.82-0.98) between the full data set and each sub-data set solution, indicating that the impacts of G/P partitioning on receptor-based source apportionment could be eliminated by using total SVOC concentrations.

SUBMITTER: Xie M

PROVIDER: S-EPMC4268888 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Positive matrix factorization of PM<sub>2.5</sub> - eliminating the effects of gas/particle partitioning of semivolatile organic compounds.

Xie M M Barsanti K C KC Hannigan M P MP Dutton S J SJ Vedal S S

Atmospheric chemistry and physics 20130101

Gas-phase concentrations of semi-volatile organic compounds (SVOCs) were calculated from gas/particle (G/P) partitioning theory using their measured particle-phase concentrations. The particle-phase data were obtained from an existing filter measurement campaign (27 January 2003-2 October 2005) as a part of the Denver Aerosol Sources and Health (DASH) study, including 970 observations of 71 SVOCs (Xie et al., 2013). In each compound class of SVOCs, the lighter species (e.g. docosane in <i>n</i> ...[more]

PMID: 25530748

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Project description:BackgroundThe metabolomic signatures of short- and long-term exposure to PM2.5 have been reported and linked to inflammation and oxidative stress. However, little is known about the relative contribution of the specific PM2.5 species (hence sources) that drive these metabolomic signatures.ObjectivesWe aimed to determine the relative contribution of the different species of PM2.5 exposure to the perturbed metabolic pathways related to changes in the plasma metabolome.MethodsWe performed mass-spectrometry based metabolomic profiling of plasma samples among men from the Normative Aging Study to identify metabolic pathways associated with PM2.5 species. The exposure windows included short-term (one, seven-, and thirty-day moving average) and long-term (one year moving average). We used linear mixed-effect regression with subject-specific intercepts while simultaneously adjusting for PM2.5, NO2, O3, temperature, relative humidity, and covariates and correcting for multiple testing. We also used independent component analysis (ICA) to examine the relative contribution of patterns of PM2.5 species.ResultsBetween 2000 and 2016, 456 men provided 648 blood samples, in which 1158 metabolites were quantified. We chose 305 metabolites for the short-term and 288 metabolites for the long-term exposure in this analysis that were significantly associated (p-value < 0.01) with PM2.5 to include in our PM2.5 species analysis. On average, men were 75.0 years old and their body mass index was 27.7 kg/m2. Only 3% were current smokers. In the adjusted models, ultrafine particles (UFPs) were the most significant species of short-term PM2.5 exposure followed by nickel, vanadium, potassium, silicon, and aluminum. Black carbon, vanadium, zinc, nickel, iron, copper, and selenium were the significant species of long-term PM2.5 exposure. We identified several metabolic pathways perturbed with PM2.5 species including glycerophospholipid, sphingolipid, and glutathione. These pathways are involved in inflammation, oxidative stress, immunity, and nucleic acid damage and repair. Results were overlapped with the ICA.ConclusionsWe identified several significant perturbed plasma metabolites and metabolic pathways associated with exposure to PM2.5 species. These species are associated with traffic, fuel oil, and wood smoke. This is the largest study to report a metabolomic signature of PM2.5 species' exposure and the first to use ICA.

Project description:Volatile and semivolatile organic compounds in ambient air and occupational settings are of great concern due to their associated adverse human health and environmental impacts. Novel graphene wool samplers have been developed and tested to overcome limitations of commercially available sorbents that can only be used once and typically require solvent extraction. Graphene wool (GW) was synthesized by non-catalytic chemical vapor deposition with optimized conditions, resulting in a novel fibrous graphene wool that is very easy to manage and less rigid than other forms of graphene, lending itself to a wide range of potential applications. Here, the air pollutant sampling capabilities of the GW were of interest. The optimal packing weight of GW inside a glass tube (length 178 mm, i.d. 4 mm, o.d. 6 mm) was investigated by the adsorption of vaporized alkane standards on the GW, using a condensation aerosol generator in a temperature-controlled chamber and subsequent detection using a flame ionization detector. The optimized GW packing density was found to be 0.19 mg mm-3 at a flow rate of 500 mL min-1, which provided a gas collection efficiency of >90% for octane, decane, and hexadecane. The humidity uptake of the sampler is less than 1% (m/m) for ambient humidities <70%. Breakthrough studies showed the favorable adsorption of polar molecules, which is attributed to the defective nature of the graphene and the inhomogeneous coating of the graphene layers on the quartz wool, suggesting that the polar versus non-polar uptake potential of the GW can be tuned by varying the graphene layering on the quartz wool substrate during synthesis. Oxidized domains at the irregular edges of the graphene layers, due to a broken, non-pristine sp2 carbon network, allow for adsorption of polar molecules. The GW was applied and used in a combustion sampling campaign where the samplers proved to be comparable to frequently used polydimethylsiloxane sorbents in terms of sampling and thermal desorption of non-polar semivolatile organic compounds. The total alkane concentrations detected after thermal desorption of GW and PDMS samplers were found to be 17.96 ± 13.27 and 18.30 ± 16.42 μg m-3, respectively; thus, the difference in the alkane sampling concentration between the two sorbent systems was negligible. GW provides a new, exciting possibility for the monitoring of organic air pollutants with numerous advantages, including high sampling efficiencies, simple and cost-effective synthesis of the thermally stable GW, solvent-free and environmentally friendly analysis, and, importantly, the reusability of samplers.

Project description:IntroductionDespite the London Underground (LU) handling on average 2.8 million passenger journeys per day, the characteristics and potential health effects of the elevated concentrations of metal-rich PM2.5 found in this subway system are not well understood.MethodsSpatial monitoring campaigns were carried out to characterise the health-relevant chemical and physical properties of PM2.5 across the LU network, including diurnal and day-to-day variability and spatial distribution (above ground, depth below ground and subway line). Population-weighted station PM2.5 rankings were produced to understand the relative importance of concentrations at different stations and on different lines.ResultsThe PM2.5 mass in the LU (mean 88 μg m-3, median 28 μg m-3) was greater than at ambient background locations (mean 19 μg m-3, median 14 μg m-3) and roadside environments in central London (mean 22 μg m-3, median 14 μg m-3). Concentrations varied between lines and locations, with the deepest and shallowest submerged lines being the District (median 4 μg m-3) and Victoria (median 361 μg m-3 but up to 885 μg m-3). Broadly in agreement with other subway systems around the world, sampled LU PM2.5 comprised 47% iron oxide, 7% elemental carbon, 11% organic carbon, and 14% metallic and mineral oxides. Although a relationship between line depth and air quality inside the tube trains was evident, there were clear influences relating to the distance from cleaner outside air and the exchange with cabin air when the doors open. The passenger population-weighted exposure analysis demonstrated a method to identify stations that should be prioritised for remediation to improve air quality.ConclusionPM2.5 concentrations in the LU are many times higher than in other London transport Environments. Failure to include this environment in epidemiological studies of the relationship between PM2.5 and health in London is therefore likely to lead to a large exposure misclassification error. Given the significant contribution of underground PM2.5 to daily exposure, and the differences in composition compared to urban PM2.5, there is a clear need for well-designed studies to better understand the health effects of underground exposure.

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Positive matrix factorization of PM2.5 - eliminating the effects of gas/particle partitioning of semivolatile organic compounds.

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Positive matrix factorization of PM<sub>2.5</sub> - eliminating the effects of gas/particle partitioning of semivolatile organic compounds.

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