Particulate Matter Filter Samples Research Articles

Impact of anthropogenic and natural constituents on particulate matter in oasis cities on the southern margin of the Taklimakan Desert based on MERRA-2 and multi-site ground observation

Dust storms are associated with large amounts of particulate matter (PM) that can have adverse effects on health and the environment. The contribution of natural dust to atmospheric PM levels represents a scientific challenge, especially in areas with close proximity to dust sources. To improve our knowledge in this area, we collected 300 PM filter-samples across five oasis cities on the southern edge of the Taklimakan Desert in 2016, and applied the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) data to quantify the contribution of natural dust to PM on sand dust and non-sand dust days. Research has shown that the particle size distribution of mineral dust in Taklimakan dust aerosols was relatively uniform. On sand dust days, CaSO4 and Na2SO4 were directly emitted from the surface, leading to higher sulfate concentrations in PM. While the increase in the proportions of organic carbon - OC1 and OC2 was attributed to the mixed anthropogenic emissions. On non-sand dust days, SO42− concentration was significantly affected by emissions from anthropogenic sources. The automotive composite emissions and coal combustion were the main sources of elemental carbon - EC1. Based on the results of MERRA-2 reanalysis data, natural dust constituted 53 % and 70 % of the total PM2.5 and PM10, respectively. In this study, we have quantified the contribution of natural dust under different weather conditions and identifying potential sources of PM in oasis cities. This study provides support for the assessment of natural dust and PM prevention in oasis cities.

Mass spectrometry-based Aerosolomics: a new approach to resolve sources, composition, and partitioning of secondary organic aerosol

Abstract. Particulate matter (PM) largely consists of secondary organic aerosol (SOA) that is formed via oxidation of biogenic and anthropogenic volatile organic compounds (VOCs). Unambiguous identification of SOA molecules and their assignment to their precursor vapors are challenges that have so far only succeeded for a few SOA marker compounds, which are now well characterized and (partly) available as authentic standards. In this work, we resolve the complex composition of SOA by means of a top-down approach based on the newly created Aerosolomics database, which is fed by non-target analysis results of filter samples from oxidation flow reactor experiments. We investigated the oxidation products from the five biogenic VOCs α-pinene, β-pinene, limonene, 3-carene, and trans-caryophyllene and from the four anthropogenic VOCs toluene, o-xylene, 1,2,4-trimethylbenzene, and naphthalene. Using ultrahigh-performance liquid chromatography coupled to a high-resolution (Orbitrap) mass spectrometer, we determine the molecular formula of 596 chromatographically separated compounds based on exact mass and isotopic pattern. We utilize retention time and fragmentation mass spectra as a basis for unambiguous attribution of the oxidation products to their parent VOCs. Based on the molecular-resolved application of the database, we are able to assign roughly half of the total signal of oxygenated hydrocarbons in ambient suburban PM2.5 to one of the nine studied VOCs. The application of the database enabled us to interpret the appearance of diurnal compound clusters that are formed by different oxidation processes. Furthermore, by performing a hierarchical cluster analysis (HCA) on the same set of filter samples, we identified compound clusters that depend on sulfur dioxide mixing ratio and temperature. This study demonstrates how Aerosolomics tools (database and HCA) applied to PM filter samples can improve our understanding of SOA sources, their formation pathways, and temperature-driven partitioning of SOA compounds.

Particulate air pollution in the Copenhagen metro part 1: Mass concentrations and ventilation

The Copenhagen Metro comprises four lines, the M1, M2, M3 and M4, with 25 subterranean stations and an additional 14 stations above ground, serving ca. 80 million passengers annually. In this study we measure fine particulate matter (PM2.5) and carbon dioxide (CO2) concentrations in stations and in trains across the entire system. In partially underground lines, high PM2.5 concentrations with an average of 109 μg m−3 are found in below-ground stations. The observed correlation between PM2.5 concentration and distance between a station and a tunnel exit is attributed to ventilation via the piston effect. The piston effect via tunnel draught relief shafts was therefore found to be relatively limited. Filter samples of particulate matter are analysed using particle-induced X-ray emission and show an iron content of 88.6 % by mass which is quite different from above-ground particulate matter and consistent with particle production by train wheels, rails and brakes. The average concentration measured at the stations of a recently opened (2019) fully underground M3 closed loop line is 168 μg m−3, further demonstrating that while piston effect-driven ventilation is effective in close proximity to tunnel openings, it is relatively limited via tunnel draught relief shafts. Measurements onboard trains show even higher PM2.5 concentrations and the patterns in CO2 concentrations suggest carriage ventilation by tunnel air. Ventilation via doors during platform stops caused a drop in observed PM (and CO2) at stations, but the system is surprisingly polluted despite its recent construction. CO2 mixing ratios ranged from ambient to around 600 ppm. Measures should be taken to control PM levels using a combination of source control and increased clean air supply of the Copenhagen and other similar metro systems.

Collocated Measurements of Light‐Absorbing Organic Carbon in PM2.5: Observation Uncertainty and Organic Tracer‐Based Source Apportionment

AbstractIn this study, collocated filter samples of particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5) from northern Nanjing were extracted using water and methanol, followed by analysis of light absorption. A backup quartz filter was used to correct sampling artifacts caused by adsorption of gaseous organics. The collocated precision of light‐absorbing properties of water‐soluble organic carbon (WSOC) and methanol‐extractable organic carbon (MEOC) were parameterized using correlation coefficient (r), coefficient of divergence (COD), and average relative percent difference (ARPD, %). In general, the light absorption of WSOC and MEOC showed good agreement (r > 0.80, COD < 0.20) between collocated samples. Performing artifact correction is necessary and will increase the heterogeneity between collocated measurements. The duplicate‐derived ARPD values of MEOC absorption were more than 60% higher than those of WSOC absorption. Then, it would be inappropriate to assume a uniform uncertainty fraction (e.g., ∼10%) for WSOC and MEOC absorption in future studies on their climate effects and source apportionment. To apportion artifact‐corrected absorption of aerosol extracts to specific emission sources or formation pathways, positive matrix factorization was performed by using concentration data of selected bulk species and organic molecular markers. Among the nine identified factor/sources, the biomass burning factor had the highest average contributions to the absorption of both WSOC (31.6%) and MEOC (48.0%), followed by dust resuspension and coal combustion factors. Unlike combustion‐related primary emissions, the factors containing influences from atmospheric processing (e.g., secondary nitrate) contributed more fractions of WSOC absorption than MEOC absorption.

Quantifying organic matter and functional groups in particulate matter filter samples from the southeastern United States – Part 2: Spatiotemporal trends

Abstract. Organic species within atmospheric particles vary widely in molecular structure. The variety of molecules that comprise the aerosol make it rich in information about its sources and chemical life cycle but also make particulate organic matter (OM) difficult to characterize and quantify. In Part 1 of this pair of papers, we described a direct method for measuring the composition and concentrations of OM in aerosol samples that is compatible with routine monitoring of air quality. This method uses Fourier transform infrared (FT-IR) spectrometry of filter-based aerosol samples to quantify bonds, or functional groups, that represent the majority of organic composition. Summation of these functional groups gives OM. In this paper, functional group and OM concentrations are directly measured in 8 years of aerosol samples collected at two rural and two urban sites in the Southeastern Aerosol Research and Characterization (SEARCH) network. FT-IR spectrometry with a multivariate calibration is used to quantify the concentrations of aliphatic C−H (aCH), carboxylic acid (COOH), oxalate (oxOCO; representing carboxylates), non-acid and non-oxalate carbonyl (naCO), and alcohol O−H (aCOH) in approximately 3500 filter samples collected every third day from 2009 through 2016. In addition, measurements are made on samples from all days in 2016. To the best of our knowledge, this is the longest time period over which this type of analysis has been applied, and this work also demonstrates the application of a more chemically complete and less destructive method than in prior work using alternate techniques. A decline in the total OM is observed from 2011 to 2016 due to a decrease in the more oxygenated functional groups (carboxylic acid and oxalate) and is attributed to anthropogenic SO2 and/or volatile organic compound (VOC) emissions reductions. The trend in OM composition is consistent with those observed using more time- and labor-intensive analytical techniques. Concurrently, the fractional contributions of aCOH and naCO to OM increased, which might be linked to monoterpene-derived secondary OM, with plausible influences from decreasing NOx and/or increasing O3 concentrations. In addition, this work demonstrates that OM to organic carbon (OM/OC) ratios in the southeastern US (SE US) did not appreciably change over the study time period as a result of these competing functional group contributions to OM. Monthly observations support the sources suggested by these overall trends, including evidence of strong biogenic and photo-oxidation influences. Daily samples from 2016 further elucidate the consistent impact of meteorology and biomass burning events on shorter-term OM variability, including prescribed burning in the winter or spring and wildfires in the autumn, although these sources did not appear to be strong contributors to long-term OM or composition trends in the SE US. These shorter-term and spatial observations reinforce the results of the broader dataset and serve to evaluate the applicability of FT-IR spectrometry measurement to trends analysis on various timescales relevant to routine monitoring of aerosol composition.

Quantifying organic matter and functional groups in particulate matter filter samples from the southeastern United States – Part 1: Methods

Abstract. Comprehensive techniques to describe the organic composition of atmospheric aerosol are needed to elucidate pollution sources, gain insights into atmospheric chemistry, and evaluate changes in air quality. Fourier transform infrared absorption (FT-IR) spectrometry can be used to characterize atmospheric organic matter (OM) and its composition via functional groups of aerosol filter samples in air monitoring networks and research campaigns. We have built FT-IR spectrometry functional group calibration models that improve upon previous work, as demonstrated by the comparison of current model results with those of previous models and other OM analysis methods. Laboratory standards that simulated the breadth of the absorbing functional groups in atmospheric OM were made: particles of relevant chemicals were first generated, collected, and analyzed. Challenges of collecting atmospherically relevant particles and spectra were addressed by including interferences of particle water and other inorganic aerosol constituents and exploring the spectral effects of intermolecular interactions. Calibration models of functional groups were then constructed using partial least-squares (PLS) regression and the collected laboratory standard data. These models were used to quantify concentrations of five organic functional groups and OM in 8 years of ambient aerosol samples from the southeastern aerosol research and characterization (SEARCH) network. The results agreed with values estimated using other methods, including thermal optical reflectance (TOR) organic carbon (OC; R2=0.74) and OM calculated as a difference between total aerosol mass and inorganic species concentrations (R2=0.82). Comparisons with previous calibration models of the same type demonstrate that this new, more complete suite of chemicals has improved our ability to estimate oxygenated functional group and overall OM concentrations. Calculated characteristic and elemental ratios including OM∕OC, O∕C, and H∕C agree with those from previous work in the southeastern US, substantiating the aerosol composition described by FT-IR calibration. The median OM∕OC ratio over all sites and years was 2.1±0.2. Further results discussing temporal and spatial trends of functional group composition within the SEARCH network will be published in a forthcoming article.

Assessment on personal exposure to particulate compounds using an empirical exposure model in an elderly community in Tianjin, China

Using central site measurement data to predict personal exposure to particulate matter (PM) is challenging, because people spend most of their time indoors and ambient contribution to personal exposure is subject to infiltration conditions affected by many factors. Efforts in assessing and predicting exposure on the basis of associated indoor/outdoor and central site monitoring were limited in China. This study collected daily personal exposure, residential indoor/outdoor and community central site PM filter samples in an elderly community during the non-heating and heating periods in 2009 in Tianjin, China. Based on the chemical analysis results of particulate species, mass concentrations of the particulate compounds were estimated and used to reconstruct the PM mass for mass balance analysis. The infiltration factors (Finf) of particulate compounds were estimated using both robust regression and mixed effect regression methods, and further estimated the exposure factor (Fpex) according to participants' time-activity patterns. Then an empirical exposure model was developed to predict personal exposure to PM and particulate compounds as the sum of ambient and non-ambient contributions. Results showed that PM mass observed during the heating period could be well represented through chemical mass reconstruction, because unidentified mass was minimal. Excluding the high observations (>300μg/m3), this empirical exposure model performed well for PM and elemental carbon (EC) that had few indoor sources. These results support the use of Fpex as an indicator for ambient contribution predictions, and the use of empirical non-ambient contribution to assess exposure to particulate compounds.

Mass size distribution and source identification of particulate matter metal components at four urban sites and a background site of Istanbul.

In this study, the size distribution characteristics and metal contents of particulate matter (PM) have been determined. In this scope, PM sampling has been done at five stations in Istanbul. PM filter samples were collected for eight different sizes using the Anderson cascade impactor. PM filters were decomposed and analyzed for 20 metals. The highest median concentration for Fe, Ca, K, and Mg, known as soil metals, were observed as follows: Fe and Ca were observed at Goztepe station (1.20 and 8.28μg/m(3)), K was observed at Kilyos station (0.33μg/m(3)), and Mg was observed at Avcilar station (0.37μg/m(3)). The highest median concentrations for Zn, Cu, Pb, Ni, Cr, V, As, Se, Co, and Cd, known as anthropogenic metals, were observed at Avcilar, Goztepe, and Besiktas stations. Although the lowest metal concentrations was determined at Kilyos stations that was selected as the urban background. The enrichment factors (EFs) of most metals in the fine PM is higher than those in the coarse mode. According to the factor analyses, the most important emission source was observed to be industrial facilities at Avcilar; traffic at Besiktas; traffic and domestic heating at Goztepe; and domestic heating, sea salt aerosols, and ship traffic (in the Bosphorus Channel of Istanbul) at Rasathane.

Direct Analysis of Low-Volatile Molecular Marker Extract from Airborne Particulate Matter Using Sensitivity Correction Method.

Molecular marker analysis of environmental samples often requires time consuming preseparation steps. Here, analysis of low-volatile nonpolar molecular markers (5-6 ring polycyclic aromatic hydrocarbons or PAHs, hopanoids, and n-alkanes) without the preseparation procedure is presented. Analysis of artificial sample extracts was directly conducted by gas chromatography-mass spectrometry (GC-MS). After every sample injection, a standard mixture was also analyzed to make a correction on the variation of instrumental sensitivity caused by the unfavorable matrix contained in the extract. The method was further validated for the PAHs using the NIST standard reference materials (SRMs) and then applied to airborne particulate matter samples. Tests with the SRMs showed that overall our methodology was validated with the uncertainty of ~30%. The measurement results of airborne particulate matter (PM) filter samples showed a strong correlation between the PAHs, implying the contributions from the same emission source. Analysis of size-segregated PM filter samples showed that their size distributions were found to be in the PM smaller than 0.4 μm aerodynamic diameter. The observations were consistent with our expectation of their possible sources. Thus, the method was found to be useful for molecular marker studies.

The Contribution of Lubricant to the Formation of Particulate Matter with Reactivity Controlled Compression Ignition in Light-Duty Diesel Engines

Reactivity controlled compression ignition (RCCI) has been shown in single- and multi-cylinder engine research to achieve high thermal efficiencies with ultra-low NOX and soot emissions. The nature of the particulate matter (PM) produced by RCCI operation has been shown in recent research to be different than that of conventional diesel combustion and even diesel low-temperature combustion. Previous research has shown that the PM from RCCI operation contains a large amount of organic material that is volatile and semi-volatile. However, it is unclear if the organic compounds are stemming from fuel or lubricant oil. The PM emissions from dual-fuel RCCI were investigated in this study using two engine platforms, with an emphasis on the potential contribution of lubricant. Both engine platforms used the same base General Motors (GM) 1.9-L diesel engine geometry. The first study was conducted on a single-cylinder research engine with primary reference fuels (PRFs), n-heptane, and iso-octane. The second study was conducted on a four-cylinder GM 1.9-L ZDTH engine which was modified with a port fuel injection (PFI) system while maintaining the stock direct injection fuel system. Multi-cylinder RCCI experiments were run with PFI gasoline and direct injection of 2-ethylhexyl nitrate (EHN) mixed with gasoline at 5 % EHN by volume. In addition, comparison cases of conventional diesel combustion (CDC) were performed. Particulate size distributions were measured, and PM filter samples were collected for analysis of lube oil components. Triplicate PM filter samples (i.e., three individual filter samples) for both gas chromatography-mass spectroscopy (GC-MS; organic) analysis and X-ray fluorescence (XRF; metals) were obtained at each operating point and queued for analysis of both organic species and lubricant metals. The results give a clear indication that lubricants do not contribute significantly to the formation of RCCI PM.

Advanced scripting for the automated profiling of two-dimensional gas chromatography-time-of-flight mass spectrometry data from combustion aerosol

Multidimensional gas chromatography is an appropriate tool for the non-targeted and comprehensive characterisation of complex samples generated from combustion processes. Particulate matter (PM) emission is composed of a large number of compounds, including condensed semi-volatile organic compounds (SVOCs). However, the complex amount of information gained from such comprehensive techniques is associated with difficult and time-consuming data analysis. Because of this obstacle, two-dimensional gas chromatography still receives relatively little use in aerosol science [1–4]. To remedy this problem, advanced scripting algorithms based on knowledge-based rules (KBRs) were developed in-house and applied to GCxGC-TOFMS data. Previously reported KBRs and newer findings were considered for the development of these algorithms. The novelty of the presented advanced scripting tools is a notably selective search criterion for data screening, which is primarily based on fragmentation patterns and the presence of specific fragments. Combined with “classical” approaches based on retention times, a fast, accurate and automated data evaluation method was developed, which was evaluated qualitatively and quantitatively for type 1 and type 2 errors. The method's applicability was further tested for PM filter samples obtained from ship fuel combustion. Major substance classes, including polycyclic aromatic hydrocarbons (PAH), alkanes, benzenes, esters and ethers, can be targeted. This approach allows the classification of approximately 75% of the peaks of interest within real PM samples. Various conditions of combustion, such as fuel composition and engine load, could be clearly characterised and differentiated.

Assessment of Particulate Matter Levels in Vulnerable Communities in North Charleston, South Carolina prior to Port Expansion

INTRODUCTIONThe Port of Charleston, one of the busiest US ports, currently operates five terminals. The fifth terminal is being planned for expansion to accommodate container ships from the proposed Panama Canal expansion. Such expansion is expected to increase traffic within local vulnerable North Charleston neck communities by at least 7,000 diesel truck trips per day, more than a 70% increase from the present average rate of 10,000 trucks per day. Our objective was to measure the current particulate matter (PM) concentrations in North Charleston communities as a baseline to contrast against future air pollution after the proposed port expansion.METHODSSaturation study was performed to determine spatial variability of PM in local Charleston neck communities. In addition, the temporal trends in particulate air pollution within the region were determined across several decades. With the BGI sampler, PM samples were collected for 24 hours comparable to the federal reference method protocol. Gravimetric analysis of the PM filter samples was conducted following EPA protocol.RESULTSThe range of the PM10 annual average across the region from 1982 to 2006 was 17.0–55.0 μg/m3. On only two occasions were the records of PM10 averaged above the 50.0 μg/m3 national standard. In the case of PM2.5, the annual average for 1999–2006 ranged from 11.0 to 13.5 μg/m3 and no annual average exceeded the 15.0 μg/m3 PM2.5 annual standard.CONCLUSIONSAlthough ambient PM levels have fallen in the Charleston region since the 1960s due to aggressive monitoring by the stakeholders against air pollution, local air pollution sources within the North Charleston neck communities have consistently contributed to the PM levels in the region for several decades. This baseline assessment of ambient PM will allow for comparisons with future assessments to ascertain the impact of the increased truck and port traffic on PM concentrations.

Correlations of particle number concentrations and metals with nitrogen oxides and other traffic-related air pollutants in Glasgow and London

Particle number concentration (PNC) and transition metal content are implicated in the health effects of airborne particulate matter (PM) but they are difficult to measure so consequently their temporal and spatial variations are not well characterized. Daily concentrations of PNC and particle-bound water-soluble metals (V, Cr, Mn, Fe, Ni, Cu, As, Cd and Pb) were measured at background and kerbside sites in Glasgow and London to examine if other metrics of air pollution such as optical darkness (absorbance) of collected filter samples of PM, gravimetric PM, and NO, NO 2 and CO gas concentrations, can be used as surrogates for the temporal and spatial variations of the former. NO 2 and NO x exhibited a high degree of within-site correlation and with PNC and water-soluble metals (Fe, Cu, As, Cd, Pb) at background sites in both cities. There is therefore potential to use NO 2 and NO x as surrogates for PNC and water-soluble metal at background sites. However, correlation was weaker in complex street canyon environments where pollutant concentrations are strongly affected by local sources and the small-scale variations in pollutant dispersion induced by the wind regimes within street canyons. The corollary of the high correlation between NO 2 and PNC and water-soluble metals at the background sites is that the latter pollutants may act as confounders for health effects attributed to NO 2 from such sites. Concentrations of CO cannot be used as a surrogate for PNC. Increments in daily NO x and NO 2 concentrations between trafficked and background sites were shown to be a simple and novel surrogate for daily spatial variation of PNC; for example, increments in NO x explained 78–79% of the variance in PNC at the paired sites in both Glasgow and London, but relationships were city specific. The increments in NO x also explained 70% of the spatial variation in Cu and Ni in Glasgow but not in London. Weekly NO 2 measurements derived from passive diffusion tubes were also shown to correlate well with increments in PNC. A high temporal correlation between PNC and 1,3-butadiene and benzene (which can also be measured by passive sampler) implies that passive sampler measurements may be a straightforward tool for deriving long-term spatial patterns in PNC. ► Particle number concentration (PNC) and transition metals in particulate matter have been associated with health outcomes. ► PNC and metals are difficult and expensive to measure, so they are not routinely monitored. ► NO 2 and NO x can be used as surrogates for PNC and water-soluble metal at background sites but not at street canyons. ► Weekly NO 2 measurements derived from passive diffusion tubes could be used as metrics for long-term exposure to PNC.

Size distribution and seasonal variation of airborne particulate matter in five areas in Istanbul, Turkey

Many studies have focused on measuring fine and course particulate matter (PM) in urban and rural sites around the world. The aim of this research is to gain information on the size distribution of particles. The physical characteristics of PM in the urban air of Istanbul were determined. PM sampling was carried out at five stations (Avcılar, Beşiktaş, Kilyos, Rasathane, and Göztepe) over a period of 2 years. PM filter samples were collected for eight different size ranges (<0.43, 0.43-1, 1-1.7, 1.7-2.6, 2.6-3.5, 3.5-5.2, 5.2-6.5, 6.5-8, and >8 μm) using a Cascade Impactor. The size distributions of the PM samples were determined. The mean total PM concentrations were 48.6 ± 34.0, 34.8 ± 11.6, 28.6 ± 13.6, 21.5 ± 9.1, and 16.8 ± 5.1 μg/m(3) for the Göztepe, Beşiktaş, Avcılar, Rasathane, and Kilyos stations, respectively. The total PM concentrations were found to be 1.2-1.5 times higher in the fall and winter than in the spring and summer, except for at the station in Avcılar. The PM concentrations in Avcılar did not exhibit seasonal variations. This is thought to result from the intense industrial activity in the area. PM(2.6) (below 2.6 μm particles) comprised up to 62% of the total amount of PM in samples collected at the Göztepe, Beşiktaş, and Rasathane stations during the fall and winter. PM(1) was determined to be approximately 45% of the total, corresponding to 57% of the amount of PM(2.5). A multi-modal PM size distribution was observed. The lowest Mass Median Aerodynamic Diameter (MMAD) values observed in Avcılar, Beşiktaş, Rasathane, and Göztepe were 4.2, 3.9, 2.9, and 3.5 μm, respectively, and were observed during the season of active household heating. No difference was measured in the MMAD values (5.2 μm) between the seasons of heating and non-heating in Kilyos.

Physical characterization of fine particulate matter inside the public transit buses fueled by biodiesel in Toledo, Ohio

This study presents the physical characteristics of fine particulate matter (PM) collected inside the urban-public transit buses in Toledo, OH. These buses run on 20% biodiesel blended with ultra-low sulfur diesel (ULSD) (B20). For risk analysis, it is crucial to know the modality of the size distribution and the shape factor of PM collected inside the bus. The number-size distribution, microstructure, and aspect ratio of fine PM filter samples collected in the urban-public transit buses were measured for three years (2007–2009), using an environmental scanning electron microscope (ESEM) coupled with energy dispersive X-ray spectrometry (EDX). Only the reproducible results from repeated experiments on ESEM and size distribution obtained by the GRIMM dust monitor were used in this study. The size distribution was found bi-modal in the winter and fall months and was primarily uni-modal during spring and summer. The aspect ratio for different filter samples collected inside the bus range from 2.4 to 3.6 in average value, with standard deviation ranging from 0.9 to 7.4. The square-shaped and oblong-shaped particles represent the single inhalable particle's morphology characteristics in the air of the Toledo transit buses.

Temporal–spatial analysis of U.S.–Mexico border environmental fine and coarse PM air sample extract activity in human bronchial epithelial cells

Particulate matter less than 10 μm (PM10) has been shown to be associated with aggravation of asthma and respiratory and cardiopulmonary morbidity. There is also great interest in the potential health effects of PM2.5. Particulate matter (PM) varies in composition both spatially and temporally depending on the source, location and seasonal condition. El Paso County which lies in the Paso del Norte airshed is a unique location to study ambient air pollution due to three major points: the geological land formation, the relatively large population and the various sources of PM. In this study, dichotomous filters were collected from various sites in El Paso County every 7 days for a period of 1 year. The sampling sites were both distant and near border crossings, which are near heavily populated areas with high traffic volume. Fine (PM2.5) and Coarse (PM10–2.5) PM filter samples were extracted using dichloromethane and were assessed for biologic activity and polycyclic aromatic (PAH) content. Three sets of marker genes human BEAS2B bronchial epithelial cells were utilized to assess the effects of airborne PAHs on biologic activities associated with specific biological pathways associated with airway diseases. These pathways included in inflammatory cytokine production (IL-6, IL-8), oxidative stress (HMOX-1, NQO-1, ALDH3A1, AKR1C1), and aryl hydrocarbon receptor (AhR)-dependent signaling (CYP1A1). Results demonstrated interesting temporal and spatial patterns of gene induction for all pathways, particularly those associated with oxidative stress, and significant differences in the PAHs detected in the PM10–2.5 and PM2.5 fractions. Temporally, the greatest effects on gene induction were observed in winter months, which appeared to correlate with inversions that are common in the air basin. Spatially, the greatest gene expression increases were seen in extracts collected from the central most areas of El Paso which are also closest to highways and border crossings.