Review of recent advances in detection of organic markers in fine particulate matter and their use for source apportionment

The main strategies for soil pollution apportionment: A review of the numerical methods

Nowadays, a large number of compounds with different physical and chemical properties have been determined in soil. Environmental behaviors and source identification of pollutants in soil are the foundation of soil pollution control. Identification and quantitative analysis of potential pollution sources are the prerequisites for its prevention and control. Many efforts have made to develop methods for identifying the sources of soil pollutants. These efforts have involved the measurement of source and receptor parameters and the analysis of their relationships via numerical statistics methods. We have comprehensively reviewed the progress made in the development of source apportionment methodologies to date and present our synthesis. The numerical methods, such as spatial geostatistics analysis, receptor models, and machine learning methods are addressed in depth. In most cases, however, the effectiveness of any single approach for source apportionment remains limited. Combining multiple methods to address soil quality problems can reduce uncertainty about the sources of soil pollution. This review also constructively highlights the key strategies of combining mathematical models with the assessment of chemical profiles to provide more accurate source attribution. This review intends to provide a comprehensive summary of source apportionment methodologies to help promote further development.

Comparative analysis of organic chemical compositions in airborne particulate matter from Ulaanbaatar, Beijing, and Seoul using UPLC-FT-ICR-MS and artificial neural network

This paper presents comparative study on the composition and sources of PM2.5 in Ulaanbaatar, Beijing, and Seoul. Ultrahigh performance liquid chromatography (UPLC) combined with ultrahigh resolution mass spectrometry (UHR-MS) were employed to analyze 85 samples collected in winter. The obtained 340 spectra were interpreted with artificial neural network (ANN). PM2.5 mass concentrations in Ulaanbaatar were significantly higher than those in Beijing and Seoul. ANN based interpretation of UPLC UHR-MS data showed that aliphatic/lipid derived organo‑sulfur compounds, polycyclic aromatic and organo‑oxygen compounds were characteristic to Ulaanbaatar. Whereas, aliphatic/lipid-derived organo‑oxygen compounds were major components in Beijing and Seoul. Aromatic organo‑nitrogen compounds were the main contributors to differentiating the spectra obtained from Beijing from the other cities. Based on two-dimensional gas chromatography/high resolution mass spectrometric (GCxGC/HRMS) data, it was determined that the concentrations of the polycyclic aromatic hydrocarbon (PAH) and polycyclic aromatic sulfur heterocycle (PASH) containing sulfur were highest in Ulaanbaatar, followed by Beijing and Seoul. Coal/biomass combustion was identified as the primary source of contamination in Ulaanbaatar, while petroleum combustion was the main contributor to PM2.5 in Beijing and Seoul. The conclusion that diesel-powered heavy-duty trucks and buses are the main contributors to NOx emissions in Beijing is consistent with previous reports. This study provides a more comprehensive understanding of the composition and sources of PM2.5 in the three cities, with a focus on the differences in their atmospheric pollution profiles based on the UPLC UHR-MS and ANN analysis. It is notable that this study is the first to utilize this method on a large-scale sample set, providing a more detailed and molecular-level understanding of the compositional differences among PM2.5. Overall, the study contributes to a better understanding of the sources and composition of PM2.5 in Northeast Asia, which is essential for developing effective strategies to reduce air pollution and improve public health.

Fine particulate matter composition in American Indian vs. Non-American Indian communities

BACKGROUND

Fine particulate matter (PM2.5) exposure is a known risk factor for numerous adverse health outcomes, with varying estimates of component-specific effects. Populations with compromised health conditions such as diabetes can be more sensitive to the health impacts of air pollution exposure. Recent trends in PM2.5 in primarily American Indian- (AI-) populated areas examined in previous work declined more gradually compared to the declines observed in the rest of the US. To further investigate components contributing to these findings, we compared trends in concentrations of six PM2.5 components in AI- vs. non-AI-populated counties over time (2000-2017) in the contiguous US.

METHODS

We implemented component-specific linear mixed models to estimate differences in annual county-level concentrations of sulfate, nitrate, ammonium, organic matter, black carbon, and mineral dust from well-validated surface PM2.5 models in AI- vs. non-AI-populated counties, using a multi-criteria approach to classify counties as AI- or non-AI-populated. Models adjusted for population density and median household income. We included interaction terms with calendar year to estimate whether concentration differences in AI- vs. non-AI-populated counties varied over time.

RESULTS

Our final analysis included 3108 counties, with 199 (6.4%) classified as AI-populated. On average across the study period, adjusted concentrations of all six PM2.5 components in AI-populated counties were significantly lower than in non-AI-populated counties. However, component-specific levels in AI- vs. non-AI-populated counties varied over time: sulfate and ammonium levels were significantly lower in AI- vs. non-AI-populated counties before 2011 but higher after 2011 and nitrate levels were consistently lower in AI-populated counties.

CONCLUSIONS

This study indicates time trend differences of specific components by AI-populated county type. Notably, decreases in sulfate and ammonium may contribute to steeper declines in total PM2.5 in non-AI vs. AI-populated counties. These findings provide potential directives for additional monitoring and regulations of key emissions sources impacting tribal lands.

Use of new Indices for the Assessment of Air Quality in the Safi Region (Morocco) using Lichen Biomonitoring of Air Contamination by Trace Elements

This study aims to use environmental indices as complementary tools to other air quality biomonitoring techniques. The concentrations of trace elements Hg, Se, V, Mo, and Ba were analyzed by ICP-MS in four lichens: Xanthoria calcicola, Xanthoria parietina, Ramalina pollinaria, and Ramalina lacera. To assess the contamination of lichens by trace elements, different environmental indices were calculated: Contamination Index (Ic), Contamination Factor (CF), Pollution Load Index (PLI) and Enrichment Factor (EF). The results revealed that the genus Ramalina has a low tolerance to polymetallic pollution with a PLI not exceeding 0.44. The genus Xanthoria seems more resistant to polymetallic pollution with a maximum PLI of 2.58. The calculation of the enrichment factor revealed a very strong enrichment of the lichens in Mo, Hg and Se with a maximum content in Ba which reflects a strong metallic contamination of various origins especially in the urban and industrial areas of the region.

Emission factors for a biofuel impacted fleet in south America's largest metropolitan area

The Metropolitan Area of São Paulo (MASP) is among the largest urban areas in the Southern Hemisphere. Vehicular emissions are of great concern in metropolitan areas and MASP is unique due to the use of biofuels on a large scale (sugar-cane ethanol and biodiesel). In this work, tunnel measurements were employed to assess vehicle emissions and to calculate emission factors (EFs) for heavy-duty and light-duty vehicles (HDVs and LDVs). The EFs were determined for particulate matter (PM) and its chemical compounds. The EFs obtained for 2018 were compared with previous tunnel experiments performed in the same area. An overall trend of reduction of fine and coarse PM, organic carbon (OC), and elemental carbon (EC) EFs for both LDVs and HDVs was observed if compared to those observed in past years, suggesting the effectiveness of vehicular emissions control policies implemented in Brazil. A predominance of Fe, Cu, Al, and Ba metals emission was observed for the LDV fleet in the fine fraction. Cu presented higher emissions than two decades ago, which was associated with the increased use of ethanol fuel in the region. For HDVs, Zn and Pb were mostly emitted in the fine mode and were linked with lubricating oil emissions from diesel vehicles. A predominance in the emission of three- and four-ring polycyclic aromatic hydrocarbons (PAHs) for HDVs and five-ring PAHs for LDVs agreed with what was observed in previous studies. The use of biofuels may explain the lower PAH emissions for LDVs (including carcinogenic BaP) compared to those observed in other countries. The tendency observed was that LDVs emit higher amounts of carcinogenic species. The use of these real EFs in air quality modeling resulted in more accurate simulations of PM concentrations, showing the importance of updating data with real-world measurements.

Particulate matter fingerprints in biofuel impacted tunnels in South America's largest metropolitan area

This study characterized the chemical composition of particulate matter (PM) from light- (LDV) and heavy-duty (HDV) vehicles based on two traffic tunnel samplings carried out in the megacity of São Paulo (Brazil), which has >7 million vehicles and intense biofuel use. The samples were collected with high-volume samplers and analyzed using chemical characterization techniques (ion and gas chromatography, thermal-optical analysis, and inductively coupled plasma mass spectroscopy). Chemical source profiles (%) were calculated based on the measurements performed inside and outside the tunnels. Identifying a high abundance of Fe and Cu for traffic-related PM in the LDV-impacted tunnel was possible, linked with the emission of vehicles powered by ethanol and gasohol (gasoline and ethanol blend). We calculated diagnostic ratios (e.g., EC/Cu, Fe/Cu, pyrene/benzo[a]pyrene, pyrene/benzo[b]fluoranthene, and fluoranthene/benzo[b]fluoranthene) characteristic of fuel exhausts (diesel/biodiesel and ethanol/gasohol), allowing their use in the assessment of the temporal variation of the fuel type used in urban sites. Element diagnostic ratios (Cu/Sb and Fe/Cu) pointed to the predominance of LDVs exhaust-related copper and can differentiate LDVs exhaust from brake wear emissions. The carbonaceous fraction EC3 was suggested as an HDV emission tracer. A higher total polycyclic aromatic hydrocarbons (PAHs) fraction of traffic-related PM_2.5 was observed in the HDV-impacted tunnel, with a predominance of diesel-related pyrene and fluoranthene, as well as higher oxy-PAHs (e.g., 9,10-anthraquinone, associated with biodiesel blends) abundances. However, carcinogenic species presented higher abundances for the LDV-impacted tunnel (e.g., benzo[a]pyrene). These findings highlighted the impact of biofuels on the characteristic ratios of chemical species and pointed to possible markers for LDVs and HDVs exhausts.

Formation of secondary organic material from gaseous precursors in wood smoke

The apportionment of the contribution of wood smoke emitted particles to the total concentration of particulate matter in a region has been greatly aided by the development of new analytical methods. These analytical methods quantitatively determine organic marker compounds unique to wood combustion such as levoglucosan and dehydroabietic acid. These markers have generally been determined in 24-hour averaged samples. We have developed an instrument based on the collection of particles on an inert filter, desorption of the organic material in an inert atmosphere with subsequent GC separation and MS detection of the desorbed compounds. The GC-MS Organic Aerosol Monitor (OAM) instrument has been used in three field studies. An unexpected finding from these studies was the quantification of the contribution of secondary organic aerosols from gases present in wood smoke in addition to primary wood smoke emitted particles. The identification of this secondary material was made possible by the collection of hourly averaged data that allowed for the time patterns of black carbon, organic material, and wood smoke marker compounds to be included and compared in a Positive Matrix Factorization (PMF) analysis. Most of the organic markers associated with wood smoke (levoglucosan, stearic acid and dehydroabietic acid) are associated with primary wood smoke emissions, but a fraction of the levoglucosan and stearic acid are also associated with secondary organic material formed from gaseous precursors in wood smoke. Additionally, this secondary material was shown to be present in each in of the three urban area where wood smoke burning occurs. There is a need for additional studies to better understand the contribution of secondary particulate formation from both urban and wildfires.Implications: This paper presents results from three field studies which show that in addition to the formation of primary particulate matter from the combustion of wood smoke and secondary particulate matter is also formed from the gaseous compounds emitted with the wood smoke. This material is identified in the studies of wood combustion reported here by the identification and quantification of specific organic marker compounds related to wood combustion and is shown to and represents a contributor nearly as large as the primary emitted material and better quantifying the impact of wood combustion on airborne fine particulate matter.

Seasonal variation and source apportionment of inorganic and organic components in PM2.5: influence of organic markers application on PMF source apportionment

PM_2.5 samples collected over a 1-year period in a Chinese megacity were analyzed for organic carbon (OC), elemental carbon (EC), water-soluble ions, elements, and organic markers such as polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes, and n-alkanes. To study the applicability of organic markers in source apportionment, the relationship between organic and inorganic components was analyzed, and four scenarios were implemented by incorporating different combinations of organic and inorganic tracers. The consistent temporal variations trend of 4-ring PAHs and SO₄^2- prove that coal burning directly emits a portion of sulfate. The concentrations of ∑5-7-ring PAHs, NO₃^-, and NO₂ show a trend of simultaneous increase and decrease, implying collective impacts from the vehicle source. The concentrations of OC and EC positively correlate with the 5-7-ring PAHs and Cu and Zn, which proves that part of Cu and Zn comes from vehicle emissions. Five factors were identified by incorporating only conventional components, including secondary source (SS, 30%), fugitive dust (FD, 14%), construction dust (CD, 4%), traffic source (TS, 19%), and coal combustion (CC, 14%). Six factors were identified by incorporating conventional components and PAHs, including SS (28%), FD (15%), CD (4%), CC (13%), gasoline vehicles (GV, 12%), and diesel vehicles (DV, 10%). Eight factors were identified by incorporating conventional components, PAHs, hopanes, and n-alkanes, including SS (26%), FD (17%), CD (3%), GV (14%), DV (8%), immature coal combustion (ICC, 5%), mature coal combustion (MCC, 10%), and biogenic source (BS, 1%).

An Investigation into Which Methods Best Explain Children’s Exposure to Traffic-Related Air Pollution

There have been several methods employed to quantify individual-level exposure to ambient traffic-related air pollutants (TRAP). These include an individual’s residential proximity to roads, measurement of individual pollutants as surrogates or markers, as well as dispersion and land use regression (LUR) models. Hopanes are organic compounds still commonly found on ambient particulate matter and are specific markers of combustion engine primary emissions, but they have not been previously used in personal exposure studies. In this paper, children’s personal exposures to TRAP were evaluated using hopanes determined from weekly integrated filters collected as part of a personal exposure study in Windsor, Canada. These hopane measurements were used to evaluate how well other commonly used proxies of exposure to TRAP performed. Several of the LUR exposure estimates for a range of air pollutants were associated with the children’s summer personal hopane exposures (r = 0.41–0.74). However, all personal hopane exposures in summer were more strongly associated with the length of major roadways within 500 m of their homes. In contrast, metrics of major roadways and LUR estimates were poorly correlated with any winter personal hopanes. Our findings suggest that available TRAP exposure indicators have the potential for exposure misclassification in winter vs. summer and more so for LUR than for metrics of major road density. As such, limitations are evident when using traditional proxy methods for assigning traffic exposures and these may be especially important when attempting to assign exposures for children’s key growth and developmental windows. If long-term chronic exposures are being estimated, our data suggest that measures of major road lengths in proximity to homes are a more-specific approach for assigning personal TRAP exposures.

Occurrences and Potential Sources of Halogenated Polycyclic Aromatic Hydrocarbons Associated with PM2.5 in Mumbai, India

Occurrences of chlorinated and brominated polycyclic aromatic hydrocarbons (ClPAHs and BrPAHs, respectively) in fine aerosol particulate matter <2.5 μm in diameter were investigated in urban and suburban sites in Mumbai, India; and the possible sources from association with indicators, such as hopanes, steranes, and trace elements are discussed. The mean concentrations of total ClPAHs and BrPAHs were 0.54 and 0.25 ng/m³ in the urban site and 0.16 and 0.02 ng/m³ in the suburban site during the campaign, respectively. The variations in total Cl-/BrPAH concentrations showed a similar trend between the urban and suburban sites, whereas the composition profiles varied in each air sample. The relationships between the concentrations among individual compounds in the urban site suggest that dominant sources of Cl-/BrPAHs could be common to PAHs but not in the suburban site. Principal component analysis using the data set of certain compounds showed that Cl-/BrPAH concentrations in urban and suburban sites are occasionally driven by specific sources of either coal combustion or traffic emissions. In contrast, most air samples during the campaign could be attributed to a mix of those sources. Environ Toxicol Chem 2022;41:312-320. © 2021 SETAC.

Particulate emissions of real-world light-duty gasoline vehicle fleet in Iran

Fine particulate matter cause profound adverse health effects in Iran. Road traffic is one of the main sources of particulate matter (PM) in urban areas, and has a large contribution in PM_2.5 and organic carbon concentration, in Tehran, Iran. The composition of fine PM vehicle emission is poorly known, so this paper aims to determine the mixed fleet source profile by using the analysed data from the two internal stations and the emission factor for PM light-duty vehicles emission. Tunnels are ideal media for extraction vehicle source profile and emission factor, due to vehicles are the only source of pollutant in the urban tunnels. In this study, PM samples were collected simultaneously in two road tunnel stations and at a background site in Niyayesh tunnel in Tehran, Iran. The tunnel samples show a large contribution for some elements and ions, such as Fe (0.23 μg μg^-1 OC), Al (0.02 μg μg^-1 OC), Ca (0.055 μg μg^-1 OC), SO₄ (0.047 μg μg^-1 OC), Docosane (0.0017 μg μg^-1 OC), Triacontane (0.016 μg μg^-1 OC), Anthracenedione (0.0003 μg μg^-1 OC) and Benzo-perylene (0.0002 μg μg^-1 OC). In overall, on-road gasoline vehicle fleets source profile extracted in this study is similar to composite profiles derived from roadside tunnel measurment performed in other countries during the last decades. The PM_2.5 emission factor for Tehran's light-duty vehicle fleet has been extracted 16.23 mg km^-1. vehicle^-1and 0.09 g kg^-1. The profile would be used for Chemical Mass Balance Model studies for Iran and other countries with a similar road traffic fleet mix. Also, it would be very suitable for use in emission inventories improvement. The results of this study can be used for choosing the best management strategies and provide comperhensive insight to fine PM traffic emission in Tehran.

Feasibility of supercritical fluid extraction-supercritical fluid chromatography mass spectrometry for the determination of polycyclic aromatic hydrocarbons in particulate matter samples

There has been an increased interest in the development of green analytical methods for polycyclic aromatic hydrocarbons in environmental samples due to their toxicity and ubiquitous nature. In this work, the feasibility of on-line supercritical fluid extraction-supercritical fluid chromatography-tandem mass spectrometry was investigated for rapid and automated determination of the 16 United States Environmental Protection Agency priority polycyclic aromatic hydrocarbons in particulate matter samples. Three specialty polycyclic aromatic hydrocarbons columns with different stationary phases were screened and an octadecyl-silica column was selected for method development. Enhanced extraction efficiency was achieved using an extraction program with gradient flow rate and gradient concentration of acetonitrile as a modifier. The method was evaluated by analyzing standard reference materials of urban dust and diesel particulate matter from the National Institute of Standards and Technologies. Possible reasons for the unsatisfactory recoveries with certain polycyclic aromatic hydrocarbons are discussed.

Determination and Similarity Analysis of PM2.5 Emission Source Profiles Based on Organic Markers for Monterrey, Mexico

Source attribution of airborne particulate matter (PM) relies on a host of different chemical species. Organic molecular markers are a set of particularly useful marker compounds for estimating source contributions to the fine PM fraction (i.e., PM2.5). Although there are many source apportionment studies based on organic markers, these studies heavily rely on the few studies that report region-specific emission profiles. Source attribution efforts, particularly those conducted in countries with emerging economies, benefit from ad hoc information to conduct the corresponding analyses. In this study, we report organic molecular marker source profiles for PM2.5 emitted from 12 major sources types from five general source categories (meat cooking operations, vehicle exhausts, industries, biomass and trash burning, and urban background) for the Monterrey Metropolitan Area (Mexico). Source emission samples were obtained from a ground-based source-dominated sampling approach. Filter-based instruments were utilized, and the loaded filters were chemically characterized for organic markers by GC-MS. Levoglucosan and cholesterol dominate charbroiled-cooking operation sources while methoxyphenols, PAHs and hopanes dominate open-waste burning, vehicle exhaust and industrial emissions, respectively. A statistical analysis showed values of the Pearson distance < 0.4 and the similarity identity distance > 0.8 in all cases, indicating dissimilar source profiles. This was supported by the coefficient of divergence average values that ranged from 0.62 to 0.72. These profiles could further be utilized in receptor models to conduct source apportionment in regions with similar characteristics and can also be used to develop air pollution abatement strategies.

Ultrafine Particles from Residential Biomass Combustion: A Review on Experimental Data and Toxicological Response

Biomass burning is considered an important source of indoor and outdoor air pollutants worldwide. Due to competitive costs and climate change sustainability compared to fossil fuels, biomass combustion for residential heating is increasing and expected to become the major source of primary particulate matter emission over the next 5–15 years. The understanding of health effects and measures necessary to reduce biomass emissions of harmful compounds is mandatory to protect public health. The intent of this review is to report available data on ultrafine particles (UFPs, i.e., particles with diameter smaller than 100 nm) emitted by residential biomass combustion and their effects on human health (in vitro and in vivo studies). Indeed, as far as we know, papers focusing specifically on UFPs originating from residential biomass combustion and their impact on human health are still lacking.

Application of multivariate statistical analysis using organic compounds: Source identification at a local scale (Napajedla, Czechia)

The study aimed to apply novel source classification tool for local scale air pollution assessment reducing the total number of organic compounds in the model. Samples of particulate matter (PM) were collected in the town of Napajedla (South-eastern Czech Republic) in 2016. The industrial sector of the town is represented by plastics processing and manufacturing, as well as by mechanical engineering. Analytical technique of pyrolysis chromatography with mass spectroscopy detection was employed to identify organic species in the PM₁₀ fraction. Two datasets (465 determined organic compounds and 50 selected organic markers) were used and compared by multivariate analysis - principal component analysis followed with hierarchical clustering on principal components incorporating compositional data approach. Three resulting clusters were observed in both cases. The cluster representing measurements near plastic processing and manufacturing plants was identical in both the analysed datasets with the same organic compounds that characterized resulting cluster Consequently, leading markers for plastic processing and manufacturing sources were suggested (bumetrizole, bis(tridecyl)phthalate, mono(2-ethylhexyl)phthalate). Other two clusters varied among the analysed datasets, however, dataset with selected markers showed more reliable outcomes. The results imply that concept of using only selected organic marker species with the compositional approach in multivariate statistical methods is sufficient and allows properly distinguishing the main air pollution sources between sampling locations even at a small urban scale.

Surface characterization and chemical speciation of adsorbed iron(iii) on oxidized carbon nanoparticles

Carbonaceous nanomaterials represent a significant portion of ultra-fine airborne particulate matter, and iron is the most abundant transition metal in air particles. Owing to their high surface area and atmospheric oxidation, carbon nanoparticles (CNP) are enriched with surface carbonyl functional groups and act as a host for metals and small molecules. Using a synthetic model, concentration-dependent changes in the chemical speciation of iron adsorbed on oxidized carbon surfaces were investigated by a combination of X-ray and electron microscopic and spectroscopic methods. Carbon K-edge absorption spectra demonstrated that the CNP surface was enriched with carboxylic acid groups after chemical oxidation but that microporosity was unchanged. Oxidized CNP showed a high affinity for sorption of Fe(iii) from solution (75-95% uptake) and spectroscopic measurements confirmed a 3+ oxidation state of Fe on CNP irrespective of surface loading. The bonding of adsorbed Fe(iii) at variable loadings was determined by iron K-edge X-ray absorption spectroscopy. At low loadings (3 and 10 μmol Fe m-2 CNP), mononuclear Fe was octahedrally coordinated to oxygen atoms of carboxylate groups. As Fe surface coverage increased (21 and 31 μmol Fe m-2 CNP), Fe-Fe backscatters were observed at interatomic distances indicating iron (oxy)hydroxide particle formation on CNP. Electron-donating surface carboxylate groups on CNP coordinated and stabilized mononuclear Fe(iii). Saturation of high-affinity sites may have promoted hydroxide particle nucleation at higher loading, demonstrating that the chemical form of reactive metal ions may change with surface concentration and degree of CNP surface oxidation. Model systems such as those discussed here, with controlled surface properties and known chemical speciation of adsorbed metals, are needed to establish structure-activity models for toxicity assessments of environmentally relevant nanoparticles.

The burden of disease attributable to ambient PM2.5-bound PAHs exposure in Nagpur, India

Exposure to PM_2.5-bound polycyclic aromatic hydrocarbons (PAHs) can elicit several types of cancer and non-cancer effects. Previous studies reported substantial burdens of PAH-induced lung cancer, but the burdens of other cancer types and non-cancer effects remain unknown. Thus, we estimate the cancer and non-cancer burden of disease, in disability-adjusted life years (DALYs), attributable to ambient PM_2.5-bound PAHs exposure in Nagpur district, India, using risk-based approach. We measured thirteen PAHs in airborne PM_2.5 sampled from nine sites covering urban, peri-urban and rural areas, from February 2013 to June 2014. We converted PAHs concentrations to benzo[a]pyrene equivalence (B[a]P_eq) for cancer and non-cancer effects using relative potency factors, and relative toxicity factors derived from quantitative structure-activity relationships, respectively. We calculated time-weighted exposure to B[a]P_eq, averaged over 30 years, and adjusted for early-life susceptibility to cancer. We estimated the DALYs/year using B[a]P_eq exposure levels, published toxicity data, and severity of the diseases from Global Burden of Disease 2016 database. The annual average concentration of total PM_2.5-bound PAHs was 458 ± 246 ng/m³ and resulted in 49,500 DALYs/year (0.011 DALYs/person/year). The PAH-related DALYs followed this order: developmental (mostly cardiovascular) impairments (55.1%) > cancer (26.5%) or lung cancer (23.1%) > immunological impairments (18.0%) > reproductive abnormalities (0.4%).

Use of a gas chromatography-mass spectrometry organic aerosol monitor for in-field detection of fine particulate organic compounds in source apportionment

A study was conducted on the Brigham Young University campus during January and February 2015 to identify winter-time sources of fine particulate material in Utah Valley, Utah. Fine particulate mass and components and related gas-phase species were all measured on an hourly averaged basis. Light scattering was also measured during the study. Included in the sampling was the first-time source apportionment application of a new monitoring instrument for the measurement of fine particulate organic marker compounds on an hourly averaged basis. Organic marker compounds measured included levoglucosan, dehydroabietic acid, stearic acid, pyrene, and anthracene. A total of 248 hourly averaged data sets were available for a positive matrix factorization (PMF) analysis of sources of both primary and secondary fine particulate material. A total of nine factors were identified. The presence of wood smoke emissions was associated with levoglucosan, dehydroabietic acid, and pyrene markers. Fine particulate secondary nitrate, secondary organic material, and wood smoke accounted for 90% of the fine particulate material. Fine particle light scattering was dominated by sources associated with wood smoke and secondary ammonium nitrate with associated modeled fine particulate water.

IMPLICATIONS

The identification of sources and secondary formation pathways leading to observed levels of PM_2.5 (particulate matter with an aerodynmaic diameter <2.5 μm) is important in making regulatory decisions on pollution control. The use of organic marker compounds in this assessment has proven useful; however, data obtained on a daily, or longer, sampling schedule limit the value of the information because diurnal changes associated with emissions and secondary aerosol formation cannot be identified. A new instrument, the gas chromtography-mass spectrometry (GC-MS) organic aerosol monitor, allows for the determination on these compounds on an hourly averaged basis. The demonstrated potential value of hourly averaged data in a source apportionment analysis indicates that significant improvement in the data used for making regulatory decisions is possible.

Organic speciation of ambient quasi-ultrafine particulate matter (PM0.36) in Augsburg, Germany: Seasonal variability and source apportionment

To investigate the organic composition and their sources of very fine atmospheric particulate matter (PM), size-segregated PM was sampled using rotating drum impactor (RDI) in series with a sequential filter sampler in Augsburg, Germany, from April 2014 to February 2015. Organic speciation analysis and organic carbon/elemental carbon (OC/EC) analysis was performed for the smallest size fraction PM_0.36 (PM<360nm). Different OC fractions were determined by thermal optical EC/OC analyzer, and OC2, OC3 and OC4 refer to OC fractions that were derived at 280, 480 and 580°C, respectively. Positive matrix factorization (PMF) analysis was applied for source apportionment study. PMF resolved 5 sources including biogenic dominated secondary organic aerosol (bioSOA), isoprene dominated SOA (isoSOA), traffic, biomass burning (BB) and biomass burning originated SOA (bbSOA). On annual average, PMF results indicate the largest contribution of biogenic originated SOA (bioSOA plus isoSOA) to OC, followed by traffic and then BB related sources (BB plus bbSOA). Traffic was found to be associated with the smallest particles; whereas bioSOA and BB are associated with larger particles. Secondary organic marker compounds from biogenic precursors, OC2, OC3 and bioSOA, isoSOA source factors show summer maximum. Polycyclic aromatic hydrocarbons (PAHs), biomass burning markers, OC4 and BB, bbSOA source factors show winter maximum. Hopanes and the traffic source factor show little seasonal variation. Summer peaks of OC3 and OC2 are well modeled by PMF and are attributed mainly to biogenic SOA. OC4 was generally poorly modeled due to lack of characteristic low volatile markers. Summer maxima of biogenic SOA related compounds and source factors are positively correlated with temperature, global radiation, O₃ concentration and mixing layer height (MLH). Winter maxima of BB related compounds and source factors are negatively correlated with temperature and MLH; whereas positively correlated with NO₂ level.

Chemical characteristics and source apportionment of PM2.5 in Lanzhou, China

Daily PM_2.5 samples were collected during winter 2012 and summer 2013 at an urban site in Lanzhou and were analyzed for chemical compounds including water soluble inorganic ions (WSIN), trace elements, water soluble organic carbon (WSOC), carbonaceous species (OC/EC), polycyclic aromatic hydrocarbons (PAHs), and humic-like substances (HULIS). The seasonal-average reconstructed PM_2.5 mass was 120.5μgm^-3 in winter and 34.1μgm^-3 in summer. The top three groups of species in PM_2.5 were OC (35.4±13.9μgm^-3), WSIN (34.89±14.21μgm^-3), and EC (13.80±5.41μgm^-3) in winter and WSIN (11.25±3.25μgm^-3), OC (9.74±3.30μgm^-3), and EC (4.44±2.00μgm^-3) in summer. EC exceeded SO₄^2- on most of the days. Several anthropogenic produced primary pollutants such as PAHs, Cl^-, Pb, Cd and OCpri were 4-22 times higher in winter than summer. Carcinogenic substances such as Arsenic, BaP, Pb, and Cd in PM_2.5 exceeded the WHO guideline limits by 274%, 153%, 23% and 7%, respectively. Positive Matric Factorization analysis identified seven source factors including steel industry, secondary aerosols, coal combustion, power plants, vehicle emissions, crustal dust, and smelting industry, which contributed 7.1%, 33.0%, 28.7%, 3.12%, 8.8%, 13.3%, and 6.0%, respectively, to PM_2.5 in winter, and 6.7%, 14.8%, 3.1%, 3.4%, 25.2%, 11.6% and 35.2% in summer. Smelting industry and steel industry were identified for the first time as sources of PM_2.5 in this city, and power plant was distinguished from industrial boiler and residential coal burning.

The chemical composition of ultrafine particles and associated biological effects at an alpine town impacted by wood burning

This work is part of the TOBICUP (TOxicity of BIomass Combustion generated Ultrafine Particles) project which aimed at providing the composition of ultrafine particles (UFPs, i.e. particles with aerodynamic diameter, d_ae, lower than 100nm) emitted by wood combustion and elucidating the related toxicity. Results here reported are from two ambient monitoring campaigns carried out at an alpine town in Northern Italy, where wood burning is largely diffused for domestic heating in winter. Wintertime and summertime UFP samples were analyzed to assess their chemical composition (i.e. elements, ions, total carbon, anhydrosugars, and polycyclic aromatic hydrocarbons) and biological activity. The induction of the pro-inflammatory cytokine interleukin-8 (IL-8) by UFPs was investigated in two human cells lines (A549 and THP-1) and in human peripheral blood leukocytes. In addition, UFP-induced oxidative stress and genotoxicity were investigated in A549 cells. Ambient UFP-related effects were compared to those induced by traffic-emitted particles (DEP) taken from the NIES reference material "vehicle exhaust particulates". Ambient air UFPs induced a dose-related IL-8 release in both A549 and THP-1 cells; the effect was more relevant on summer samples and in general THP-1 cells were more sensitive than A549 cells. On a weight basis our data did not support a higher biological activity of ambient UFPs compared to DEP. The production of IL-8 in the whole blood assay indicated that UFPs reached systemic circulation and activated blood leukocytes. Comet assay and γ-H2AX evaluation showed a significant DNA damage especially in winter UFPs samples compared to control samples. Our study showed that ambient UFPs can evoke a pulmonary inflammatory response by inducing a dose-related IL-8 production and DNA damage, with different responses to UFP samples collected in the summer and winter periods.

A compact gas chromatograph and pre-column concentration system for enhanced in-field separation of levoglucosan and other polar organic compounds

Portable and compact instruments for separating and detecting organic compounds are needed in the field for environmental studies. This is especially the case for pollution studies as in-field detection of organic compounds helps identify sources of pollution. Here we describe the development of a compact GC and simple pre-concentrator coupled to a MS detector. This simple system can easily be incorporated into portable instrumentation. Combining the pre-concentrator and compact column has the advantage of decoupling separation from manual injection and enhances separation of environmentally relevant polar organic compounds, such as levoglucosan. A detection limit of 2.2 ng was obtained for levoglucosan. This simple design has the potential to expand the use of gas chromatography as a routine in-field separation technique.

Hyphenation of Thermal Analysis to Ultrahigh-Resolution Mass Spectrometry (Fourier Transform Ion Cyclotron Resonance Mass Spectrometry) Using Atmospheric Pressure Chemical Ionization For Studying Composition and Thermal Degradation of Complex Materials

In this study, the hyphenation of a thermobalance to an ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometer (UHR FTICR MS) is presented. Atmospheric pressure chemical ionization (APCI) is used for efficient ionization. The evolved gas analysis (EGA), using high-resolution mass spectrometry allows the time-resolved molecular characterization of thermally induced processes in complex materials or mixtures, such as biomass or crude oil. The most crucial part of the setup is the hyphenation between the thermobalance and the APCI source. Evolved gases are forced to enter the atmospheric pressure ionization interface of the MS by applying a slight overpressure at the thermobalance side of the hyphenation. Using the FTICR exact mass data, detailed chemical information is gained by calculation of elemental compositions from the organic species, enabling a time and temperature resolved, highly selective detection of the evolved species. An additional selectivity is gained by the APCI ionization, which is particularly sensitive toward polar compounds. This selectivity on the one hand misses bulk components of petroleum samples such as alkanes and does not deliver a comprehensive view but on the other hand focuses particularly on typical evolved components from biomass samples. As proof of principle, the thermal behavior of different fossil fuels: heavy fuel oil, light fuel oil, and a crude oil, and different lignocellulosic biomass, namely, beech, birch, spruce, ash, oak, and pine as well as commercial available softwood and birch-bark pellets were investigated. The results clearly show the capability to distinguish between certain wood types through their molecular patterns and compound classes. Additionally, typical literature known pyrolysis biomass marker were confirmed by their elemental composition, such as coniferyl aldehyde (C10H10O3), sinapyl aldehyde (C11H12O4), retene (C18H18), and abietic acid (C20H30O2).

Laboratory study on OH-initiated degradation kinetics of dehydroabietic acid

The degradation kinetics of dehydroabietic acid by OH radicals were investigated under various environmental conditions.

Characterization of atmospheric polycyclic aromatic hydrocarbons in a mixed-use urban community in Paterson, NJ: concentrations and sources

Exposure to ambient polycyclic aromatic hydrocarbons (PAHs) is a potential health concern for communities because many PAHs are known to be mutagenic and carcinogenic. However, information on ambient concentrations of PAHs in communities is very limited. During the Urban Community Air Toxics Monitoring Project, Paterson City, NJ, PAH concentrations in ambient air PM10 (particulate matter < or = 10 microm in aerodynamic diameter) were measured from November 2005 through December 2006 in Paterson, a mixed-use urban community located in Passaic County, NJ. Three locations dominated by industrial, commercial, and mobile sources were chosen as monitoring sites. The comparison background site was located in Chester, NJ, which is approximately 58 km west/southwest of Paterson. The concentrations of all of the individual PAHs at all three Paterson sites were found to be significantly higher than those at the background site (P < 0.05). The PAH profiles obtained from the three sites with different land-use patterns showed that the contributions of heavier PAHs (molecular weight > 202) to the total PAHs were significantly higher at the industrial site than those at the commercial and mobile sites. Analysis of the diagnostic ratios between PAH isomers suggested that the diesel-powered vehicles were the major PAH sources in the Paterson area throughout the year. The operation of industrial facilities and other combustion sources also partially contributed to PAH air pollution in Paterson. The correlation of individual PAH, total PAH, and the correlation of total PAHs with other air co-pollutants (copper, iron, manganese, lead, zinc, elemental carbon, and organic carbon) within and between the sampling sites supported the conclusions obtained from the diagnostic ratio analysis.