This study evaluated the emissions characteristics of hazardous material during fused deposition modeling type 3D printing. Particulate and gaseous materials were measured before, during, and after 3D printing in an exposure chamber. One ABS and two PLA (PLA1 and PLA2) cartridges were tested three times. For online monitoring, a scanning mobility particle sizer, light scattering instrument, and total volatile organic compound (TVOC) monitor were employed and a polycarbonate filter and various adsorbent tubes were used for offline sampling. The particle concentration of 3D printing using ABS material was 33-38 times higher than when PLA materials were used. Most particles were nanosize (<100 nm) during ABS (96%) and PLA1 (98%) use, but only 12% were nanosize for PLA2. The emissions rates were 1.61 × 10(10) ea/min and 1.67 × 10(11) ea/g cartridge with the ABS cartridge and 4.27-4.89 × 10(8) ea/min and 3.77-3.91 × 10(9) ea/g cartridge with the PLA cartridge. TVOCs were also emitted when the ABS was used (GM; 155 ppb, GSD; 3.4), but not when the PLA cartridges were used. Our results suggest that more research and sophisticated control methods, including the use of less harmful materials, blocking emitted containments, and using filters or adsorbents, should be implemented.

Particulate respirators have been used in both general environments and in the workplace. Despite the existence of certified respirators for workers, no strict regulations exist for masks worldwide. The aims of this study were to evaluate the filter efficiency of various mask types using the Korean Food and Drug Administration (KFDA) [similar to the European Union (EU) protocol] and the National Institute for Occupational Safety and Health (NIOSH) protocol and to compare the test results. We tested a total of 44 mask brands of four types (anti-yellow sand, medical, quarantine, general) and handkerchiefs with a TSI 8130 Automatic Filter Tester. A wide variation of penetration and pressure drops was observed by mask types. The overall mean penetration and pressure drop of all tested masks were respectively 35.6 ± 34.7%, 2.7 ± 1.4 mm H 2 O with the KFDA protocol, and 35.1 ± 35.7%, 10.6 ± 5.88 mm H 2 O with the NIOSH protocol. All tested quarantine masks satisfied the KFDA criterion of 6%. Six-ninths and four-sevenths of the anti-yellow sand masks for adults and children satisfied the criterion of 20%, respectively. Medical masks, general masks, and handkerchiefs were found to provide little protection against respiratory aerosols.

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Traffic has long been recognized as the major contributor to polycyclic aromatic hydrocarbon (PAH) concentrations. However, this does not consider the contribution of cooking sources of PAHs. This study set out, first, to assess the characteristics of PAHs and their corresponding benzo[a]pyrene equivalent (B[a]Peq) emissions from cooking sources to the urban atmosphere. To illustrate the importance of cooking sources, PAH emissions from traffic sources were then calculated and compared. The entire study was conducted on a city located in southern Taiwan. PAH samples were collected from the exhaust stacks of four types of restaurant: Chinese, Western, fast food, and Japanese. For total PAHs, results show that the fractions of gaseous PAHs (range, 75.9-89.9%) were consistently higher than the fractions of particulate PAHs (range, 10.1-24.1%) in emissions from the four types of restaurant. But for total B[a]Peq, we found that the contributions of gaseous PAHs (range, 15.7-21.9%) were consistently lower than the contributions of particulate PAHs (range, 78.1-84.3%). For emission rates of both total PAHs and total B[a]Peq, a consistent trend was found for the four types of restaurant: Chinese (2,038 and 154 kg/year, respectively) > Western (258 and 20.4 kg/year, respectively) > fast food (31.4 and 0.104 kg/year, respectively) > Japanese (5.11 and 0.014 kg/year, respectively). By directly adapting the emission data obtained from Chinese restaurants, we found that emission rates on total PAHs and total B[a]Peq for home kitchen sources were 6,639 and 501 kg/year, respectively. By combining both restaurant sources and home kitchen sources, this study yielded emission rates of total PAHs and total B[a]Peq from cooking sources of the studied city of 8,973 and 675 kg/year, respectively. Compared with PAH emissions from traffic sources in the same city, we found that although the emission rates of total PAHs for cooking sources were significantly less than those for traffic sources (13,500 kg/year), the emission rates of total B[a]Peq for cooking sources were much higher than those for traffic sources (61.4 kg/year). The above results clearly indicate that although cooking sources are less important than traffic sources in contributing to total PAH emissions, PAH emissions from cooking sources might cause much more serious problems than traffic sources, from the perspective of carcinogenic potency.

This study set out to identify possible PCDD/F emission sources for different atmospheric environments in a highly industrialized city located in southern Taiwan. We collected stack flue gas samples from five main stationary emission sources of the municipal solid waste incinerators (MSWIs), medical waste incinerators (MWIs), electric arc furnaces (EAFs), secondary aluminum smelters (ALSs), and sinter plants to assess the characteristics of their PCDD/F emissions. For mobile sources, congener profiles reported in U.S. EPA's database for unleaded gas-fueled vehicles (UGFV) and diesel-fueled vehicles (DFV) were directly adopted owing to lack of local data. The congener profiles of the 2,3,7,8-substituted PCDD/Fs were selected as the signatures of these PCDD/F emission sources. We conducted PCDD/F samplings on atmospheric environments of four categories, including background, residential area, traffic area, and industrial area. Through PCA and cluster analyses, we found that traffic areas were most influenced by PCDD/F emissions from UGFV and DFV, while those of industrial areas were mainly influenced by metallurgical facilities and MWIs. The above results were further examined by using the methodology of the indicatory PCDD/Fs. We confirmed that traffic areas were contributed by traffic sources, but industrial areas were simply affected by metallurgical facilities rather than MWIs. In conclusion, besides the use of PCA and cluster analyses, the methodology of the indicatory PCDD/Fs should be conducted for further validation in order to prevent misjudgment.