Characterization and source apportionment of airborne particulate elements in the Athabasca oil sands region.

The oil sands industries in Alberta, Canada are potential sources of particulate-bound elements in the region. This study explored the ambient concentrations and size distributions, and conducted source apportionment of 48 particulate elements, based on samples collected in 2016-2017 at four air monitoring sites in the Athabasca oil sands region: Fort McKay (AMS1), Buffalo Viewpoint (AMS4), Wapasu Creek (AMS17), and Stoney Mountain (AMS18). Element concentrations in fine and coarse particulate matter (PM2.5 and PM2.5-10 respectively) at the four sites were generally lower than their typical concentrations at other urban and industrial sites in North America. Among all elements, S was the most abundant in PM2.5 with mean concentrations ranging from 189 ng/m3 (AMS18) to 284 ng/m3 (AMS1). Of the trace, toxic elements in PM2.5, Zn was the most abundant with mean concentrations ranging from 3.43 ng/m3 (AMS18) to 5.37 ng/m3 (AMS4). Positive Matrix Factorization (PMF) modeling of the element concentrations in PM2.5 was used for source apportionment for Zone1 (including AMS 1, 4, and 17, situated closer to industrial activities) and for Zone2 (including AMS18, a background site). The sources of elements for Zone1, included crustal dust, bitumen processing, haul road dust, and biomass burning that explained ~33%, ~43%, ~15%, and ~9% of the total resolved elemental mass, respectively. The sources of elements for Zone2, included Pb-rich source, biomass burning, fugitive oil sands, crustal dust, and bitumen processing explaining ~8%, ~7%, ~3%, ~22%, and ~60% of the total resolved elemental mass, respectively. Elemental mass concentrations of the bitumen processing source factor at Zone2 was two-thirds of that in Zone1. Overall, mass proportions of the bitumen processing source factor at all four sites were significant, suggesting that the oil sands industries played a key role in ambient element concentration levels in the region.

Temporal variation in the deposition of polycyclic aromatic compounds in snow in the Athabasca Oil Sands area of Alberta.

Atmospheric deposition of polycyclic aromatic compounds (PACs) via and onto snow, and their releasing during spring snowmelt has been a concern in the Athabasca Oil Sands Region of Alberta. This study was designed to evaluate the concentrations, loadings, and distribution of PACs in springtime snowpack and how they have changed since the first study in 2008. Snowpack samples were collected in late winters 2011-2014 at varying distances from the main developments. PAC concentration and deposition declined exponentially with distance, with pyrenes, chrysenes, and dibenzothiophenes dominating the distribution within the first 50 km. The distribution of PACs was different between sites located close to upgraders and others located close to mining facilities. Overall, PAC loadings were correlated with priority pollutant elements and water chemistry parameters, while wind direction and speed were not strong contributors to the variability observed. Total PAC mass deposition during winter months and within the first 50 km was initially estimated by integrating the exponential decay function fitted through the data using a limited number of sites from 2011 to 2014: 1236 kg (2011), 1800 kg (2012), 814 kg (2013), and 1367 (2014). Total loadings were estimated to have a twofold increase between 2008 and 2014, although the increase observed was not constant. Finally, kriging interpolation is presented as an alternative and more robust approach to estimate PAC mass deposition in the area. After a more intensive sampling campaign in 2014, the PAC mass deposition was estimated to be 1968 kg.

Cytotoxic and inflammatory potential of size-fractionated particulate matter collected repeatedly within a small urban area.

BACKGROUND: Exposure to coarse, fine, and ultrafine particles is associated with adverse population health impacts. We investigated whether size-fractionated particles collected repeatedly in the vicinity of industrial (steel mills and associated coking operations, wastewater treatment), high traffic, and residential areas display systematic differences in biological potency. METHODS: Particulate matter (PM<0.1, PM0.1-0.5, PM0.5-2.5, PM2.5-10, PM>10) samples collected at sites within Windsor, Ontario, were screened for biological potency in human A549 lung epithelial and murine J774A.1 macrophage-like cells using cytotoxicity bioassays (cellular ATP, resazurin reduction, lactate dehydrogenase (LDH) release), cytokine production, and transcript profiles. Potency was determined from the slope of each dose-effect relationship. RESULTS: Cytotoxic potency varied across size fractions and within a fraction across sites and sampling periods, suggesting that particle composition, in addition to size and mass, affected particle toxicity. While ATP and LDH profiles showed some similarity, resazurin reduction (a measure of metabolic activity) exhibited a unique pattern of response, indicating that the cytotoxicity assays were sensitive to distinct particle characteristics. Chemical speciation varied in relation to prevailing winds, consistent with enrichment of source emissions (e.g. higher metal and polycyclic aromatic hydrocarbon content downwind of the industrial site). Notwithstanding this variability, site-dependent differences in particle toxicity were evident, including greater potency of coarse fractions at the industrial site and of ultrafine particles at the traffic site (Site × Size interactions, p < 0.05). Regression of potency against particle constituents revealed correlations between resazurin reduction, induction of metal-responsive genes, and metal content, which were particularly strong for the coarse fraction, and between cytokine release and endotoxin, suggesting that these factors were important drivers of biological effects that explain, at least in part, the contrasting potencies of particles compared on an equivalent mass basis. CONCLUSIONS: The data show that 1) particle potency and composition can exhibit significant temporal variation in relation to source contributions; 2) sources may differentially impact the potency of specific size fractions; and 3) particle constituents, notably metals and endotoxin, may elicit distinct biological responses. Together, the data are consistent with the notion that sources and composition, in addition to size and mass concentration, are relevant to particle toxicity.

n-alkane profiles of engine lubricating oil and particulate matter by molecular sieve extraction.

As part of the Canadian Atmospheric Fine Particle Research Program to obtain reliable primary source emission profiles, a molecular sieve method was developed to reliably determine n-alkanes in lubricating oils, vehicle emissions, and mobile source dominated ambient particulate matter (PM). This work was also initiated to better calculate carbon preference index values (CPI: the ratio of the sums of odd over even n-alkanes), a parameter for estimating anthropogenic versus biogenic contributions in PM. n-Alkanes in lubricating oil and mobile source dominated PM are difficult to identify and quantify by gas chromatography due to the presence of similar components that cannot be fully resolved. This results in a hump, the unresolved complex mixture (UCM) that leads to incorrect n-alkane concentrations and CPI values. The sieve method yielded better chromatography, unambiguous identification of n-alkanes and allowed examination of differences between n-alkane profiles in light (LDV) and heavy duty vehicle (HDV) lubricating oils that would have been otherwise difficult. These profile differences made it possible to relate the LDV profile to that of the PM samples collected during a tunnel study in August 2001 near Vancouver (British Columbia, Canada). The n-alkane PM data revealed that longer sampling times result in a negative artifact, i.e., the desorption of the more volatile n-alkanes from the filters. Furthermore, the sieve procedure yielded n-alkane data that allowed calculation of accurate CPI values for lubricating oils and PM samples. Finally, this method may prove helpful in estimating the respective diesel and gasoline contributions to ambient PM.