Search

A hybrid model based on the positive matrix factorization (PMF) model and the health risk assessment model for assessing risks associated with sources of perfluoroalkyl substances (PFASs) in water was established and applied at Dianchi Lake to test its applicability. The new method contains 2 stages: 1) the sources of PFASs were apportioned by the PMF model and 2) the contribution of health risks from each source was calculated by the new hybrid model. Two factors were extracted by PMF, with factor 1 identified as aqueous fire-fighting foams source and factor 2 as fluoropolymer manufacturing and processing and perfluorooctanoic acid production source. The health risk of PFASs in the water assessed by the health risk assessment model was 9.54 × 10−7 a−1 on average, showing no obvious adverse effects to human health. The 2 sources' risks estimated by the new hybrid model ranged from 2.95 × 10−10 to 6.60 × 10−6 a−1 and from 1.64 × 10−7 to 1.62 × 10−6 a−1, respectively. The new hybrid model can provide useful information on the health risks of PFAS sources, which is helpful for pollution control and environmental management. Environ Toxicol Chem 2018;37:107-115. © 2017 SETAC [ABSTRACT FROM AUTHOR]

Concentrations of particulate matter with an aerodynamic diameter less than 10 μm (PM10) and PM with an aerodynamic diameter less than 2.5 μm (PM2.5), and 16 polycyclic aromatic hydrocarbons (PAHs) were measured. The average concentrations of PM10 and PM2.5 reached 209.75 μg/m3 and 141.87 μg/m3, respectively, and those of ΣPAHs were 41.46 ng/m3 for PM10 and 36.77 ng/m3 for PM2.5. The mass ratio concentrations were 219.23 μg/g and 311.01 μg/g in PM10 and PM2.5, respectively. Three sources and their contributions for PAHs were obtained. For individual input mode, diesel exhaust contributed 46.77% (PM10) and 41.12% (PM2.5) for mass concentration and 48.69% (PM10) and 39.47% (PM2.5) for mass ratio concentration; gasoline exhaust contributed 31.02% (PM10) and 39.47% (PM2.5) for mass concentration and 28.95% (PM10) and 36.46% (PM2.5) for mass ratio concentration; and coal combustion contributed 22.22% (PM10) and 19.41% (PM2.5) for mass concentration and 22.36% (PM10) and 15.89% (PM2.5) for mass ratio concentration. For combined input mode, the same source categories were obtained. Source contributions to PM10 and PM2.5 were diesel exhaust (40.70% and 36.64%, respectively, for mass concentration; 49.19% and 38.47%, respectively, for mass ratio concentration), gasoline exhaust (35.09% and 38.47%, respectively, for mass concentration; 32.50% and 33.43%, respectively, for mass ratio concentration), and coal combustion (24.21% and 24.89%, respectively, for mass concentration; 18.31% and18.17%, respectively, for mass ratio concentration). Source risk assessment showed that vehicle emission was a significant contributor. The findings can help elucidate sources of PAHs and provide evidence supporting further applications of the Unmix model and additional studies about PAHs. Environ Toxicol Chem 2015;34:480-487. © 2014 SETAC [ABSTRACT FROM AUTHOR]

Polycyclic aromatic hydrocarbon (PAHs) were measured in sediments from 29 sites throughout Taihu Lake in China during 2 seasons to investigate spatiotemporal characteristics and source contributions using a 3-way source apportionment approach to positive matrix factorization (PMF3). Seasonal and spatial variations of levels and toxicity suggested higher individual carcinogenic PAH concentrations and toxic equivalent quantity (TEQ) in the flooding season. Three-way PAHs dataset (PAH species, spatial variability, and seasonal variability) was analyzed by PMF3, and its results were compared with a widely used 2-way model (PMF2). Consistent results were observed: vehicular emission was the most important contributor (67.08% by PMF2 and 61.83% by PMF3 for the flooding season; 54.21% by PMF2 and 52.94% by PMF3 for dry season), followed by coal combustion and wood combustion in both seasons. The PMF-cluster analysis was employed to investigate spatial variability of source contributions. Findings can introduce the 3-way approach to apportion sources of PAHs and other persistent organic pollutants (POPs) in sediments, offering the advantage of accounting for information on 3-way datasets. Environ Toxicol Chem 2014;33:1747-1753. © 2014 SETAC [ABSTRACT FROM AUTHOR]