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Fine dust (PM2.5) is generated from various sources, and many studies have reported on the sources of PM2.5. However, the current research on PM2.5 toxicity based on its sources is insufficient. In this study, we developed a framework for the prioritization of fine dust (PM2.5) sources on the basis of the multi-endpoint toxicities using the multi-criteria decision-making method (MCDM). To obtain the multi-endpoint toxicities of PM2.5 sources, cell mortality, reactive oxygen species (ROS), inflammation and mutagenicity were measured for diesel exhaust particles (DEP), gasoline exhaust particles (GEP), rice straw burning particles (RBP), coal combustion particles (CCP) and tunnel dust particles (TDP). The integrative toxicity score (ITS) of the PM2.5 source was calculated using MCDM, which consist of four steps: (1) defining the decision-making matrix, (2) normalization and weighting, (3) calculating the ITS (linear aggregation) and (4) a global sensitivity analysis. The indicator of cell mortality had the highest weight (0.3780) followed by inflammation (0.2471), ROS (0.2178) and mutagenicity (0.1571). Additionally, the ITS based on the sources contributing to PM2.5 resulted in the following order: DEP (0.89), GEP (0.44), RBP (0.40), CCP (0.23) and TDP (0.06). The relative toxicity index (RTI), which represents the ratio of toxicity due to the difference in sources, increases as the contribution of the highly toxic sources increases. The RTI over 1 is closely associated with an increased contribution from highly toxic sources, such as diesel exhaust, gasoline exhaust and biomass burning. It is necessary to investigate the toxicity of various PM2.5 sources and PM2.5 risk based on the sources.

Increasing evidence suggests that the toxicity of fine dust particles (PM 2.5 ) is linked to specific components rather than their mass. However, research on the chemical composition and health risk of PM 2.5 is insufficient. This study analyzed the metals, polycyclic aromatic hydrocarbon (PAHs), organochlorine pesticides (OCPs), and polychlorinated biphenyls (PCBs) present in PM 2.5 and evaluated their risk to health during outdoor activities. The concentration of metals was one order of magnitude higher than that of PAHs and the concentration and detection frequency of OCPs and PCBs were considerably lower than those of metals and PAHs. The lifetime excess cancer risk (LECR) for carcinogens in PM 2.5 exceeded de minimis risk (1 × 10 -6 ) as 1.33-3.44 × 10 -6 (at 5th-95th percentile) as Cr(VI), As, and Cd showed high contributions. Children in the 2 < years <18 age group had a high risk of cancer due to early-life susceptibility. The proportion of ∑Metals to LECR was approximately 95%, while ∑PAHs attributed to 5% of total LECR. The effects of ∑OCPs and 2,3',4,4',5'-Pentachlorobiphenyl (PCB-123) on LECR were negligible. The hazard quotient (HQ) for non-carcinogens was <1, and non-carcinogenic effects were not expected. Mn, BaP, Pb, As, and Cd were the key determinants of the HQ values and among the identified PM 2.5 sources they are closely related to industrial activities, oil combustion, and gasoline exhaust. Therefore, control strategies for these sources can effectively reduce PM 2.5 risk. This study measured the concentrations of toxic compounds in ambient PM 2.5 and considered only PM 2.5 exposure during outdoor activities. PM 2.5 health risk during the entire day would be higher than the PM 2.5 risk determined in this study, and further research is required for this evaluating this risk., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Studies investigating toxic organic pollutants in fine dust (PM2.5), such as polycyclic aromatic hydrocarbons (PAHs), organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs), are insufficient, despite the pollutants' potent toxicity. The objective of this study is to develop an analytical method for determining PAHs, OCPs and PCBs in ambient PM2.5 using selective pressurized liquid extraction (SPLE). To maximize the extraction efficiency of target analytes, the extraction parameters of SPLE, particularly solvent type, temperature, static time, and cycle number, were optimized. The highest recoveries were observed under the conditions of dichloromethane:acetone (9:1), 100℃, 5 min of static time, and 1 cycle extraction, which is selected as the optimal method of SPLE. In the method validation, the results showed that the suggested method can quantify 17 PAHs, 20 OCPs, and 63 PCBs in PM2.5. Using urban dust SRM (1648a) and ambient PM2.5 samples, the applicability of the method was also confirmed. Total concentration of PAHs was the highest (2639.42-7377.75 pg/m 3 ) followed by OCPs (80.57-674.69 pg/m 3 ) and PCBs (1.39-9.34 pg/m 3 ). Most of the PAHs were detected, whereas 2-7 compounds among 20 OCPs and 2-6 compounds among 63 PCBs were determined. The developed analytical method is highly efficient in terms of process (a one-step extraction process), time (15 min extraction time per one sample) and solvent usage (less than 30 mL per one sample), showing good performance. This method can be applied to investigate the organic toxicants in PM2.5, and it can contribute to monitoring and risk assessment, leading to an effective risk management policy for PM2.5 in Korea., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Although particulate matter (PM) is composed of various chemicals, investigations regarding the toxicity that results from mixing the substances in PM are insufficient. In this study, the effects of low levels of three PAHs (benz[a]anthracene, benzo[a]pyrene, and dibenz[a,h]anthracene) on Ni toxicity were investigated to assess the combined effect of Ni-PAHs on the environment. We compared the difference in cell mortality and total glutathione (tGSH) reduction between single Ni and Ni-PAHs co-exposure using A549 (human alveolar carcinoma). In addition, we measured the change in Ni solubility in chloroform that was triggered by PAHs to confirm the existence of cation-π interactions between Ni and PAHs. In the single Ni exposure, the dose-response curve of cell mortality and tGSH reduction were very similar, indicating that cell death was mediated by the oxidative stress. However, 10 μM PAHs induced a depleted tGSH reduction compared to single Ni without a change in cell mortality. The solubility of Ni in chloroform was greatly enhanced by the addition of benz[a]anthracene, which demonstrates the cation-π interactions between Ni and PAHs. Ni-PAH complexes can change the toxicity mechanisms of Ni from oxidative stress to others due to the reduction of Ni 2+ bioavailability and the accumulation of Ni-PAH complexes on cell membranes. The abundant PAHs contained in PM have strong potential to interact with metals, which can affect the toxicity of the metal. Therefore, the mixture toxicity and interactions between diverse metals and PAHs in PM should be investigated in the future.

Fine particulate matters less than 2.5 µm (PM 2.5 ) in the ambient atmosphere are strongly associated with adverse health effects. However, it is unlikely that all fine particles are equally toxic in view of their different sizes and chemical components. Toxicity of fine particles produced from various combustion sources (diesel engine, gasoline engine, biomass burning (rice straw and pine stem burning), and coal combustion) and non-combustion sources (road dust including sea spray aerosols, ammonium sulfate, ammonium nitrate, and secondary organic aerosols (SOA)), which are known major sources of PM 2.5 , was determined. Multiple biological and chemical endpoints were integrated for various source-specific aerosols to derive toxicity scores for particles originating from different sources. The highest toxicity score was obtained for diesel engine exhaust particles, followed by gasoline engine exhaust particles, biomass burning particles, coal combustion particles, and road dust, suggesting that traffic plays the most critical role in enhancing the toxic effects of fine particles. The toxicity ranking of fine particles produced from various sources can be used to better understand the adverse health effects caused by different fine particle types in the ambient atmosphere, and to provide practical management of fine particles beyond what can be achieved only using PM mass which is the current regulation standard.