Evaluation of Fine and Ultrafine Particles Proportion in Airborne Dust in an Industrial Area

Indoor air quality and sick building syndrome symptoms in administrative office at public university

Sick Building Syndrome (SBS) is an illness among workers linked to time spent in a building. This study aimed to investigate the Indoor Air Quality (IAQ) and symptoms of Sick Building Syndrome (SBS) among administrative office workers. The IAQ parameters consist of ventilation performance indicators, and physical and chemical parameters were measured using specified instruments for three days during weekdays. The SBS symptoms were assessed by a questionnaire adopted from the Industry Code of Practice of Indoor Air Quality (ICOP-IAQ) 2010 among 19 employees from the office in East Coast Malaysia. Relationship between past symptoms and present symptoms which are draught (past symptoms) with feeling heavy headed (present symptoms) (r = 0.559, p < 0.05), room temperature too high (past symptoms) was highly correlated with feeling heavy headed (present symptoms) (r = 0.598, p < 0.01) and cough (present symptoms) (r = 0.596, p < 0.01). Room temperature (past symptoms) has a positive medium relationship with cough (present symptoms) (r = 0.477, p < 0.05) and scaling itching scalp or ears (present symptoms) has a relationship between stuffy bad air (r = 0.475, p < 0.05) and dry air (r = 0.536, p < 0.05). There was a significant association between RH with drowsiness (χ2 = 7.090, p = 0.049) and dizziness (χ2 = 7.090, p = 0.049). The association was found between temperature and SBS symptoms between temperature with headache (χ2 = 7.574, p = 0.051), feeling heavy-headed (χ2 = 8.090, p = 0.046), and skin rash itchiness (χ2 = 7.451, p = 0.044). Air movement also showed a positive association with symptoms of feeling heavy-headed (x2 = 8.726, p = 0.021). PM10 has positive significance with SBSS which are feeling heavy-headed (χ2 = 7.980, p = 0.023), and eyer's irritation (χ2 = 7.419, p = 0.038). The conclusion of this study showed that there were positive significant between temperature and relative humidity toward SBSS.

Using particle dimensionality-based modeling to estimate lung carcinogenicity of 3D printer emissions

The use of 3D printing technologies by industry and consumers is expanding. However, the approaches to assess the risk of lung carcinogenesis from the emissions of 3D printers have not yet been developed. The objective of the study was to demonstrate a methodology for modeling lung cancer risk related to specific exposure levels as derived from an experimental study of 3D printer emissions for various types of filaments (ABS, PLA, and PETG). The emissions of 15 filaments were assessed at varying extrusion temperatures for a total of 23 conditions in a Class 1,000 cleanroom following procedures described by ANSI/CAN/UL 2904. Three approaches were utilized for cancer risk estimation: (a) calculation based on PM2.5 and PM10 concentrations, (b) a proximity assessment based on the pulmonary deposition fraction, and (c) modeling based on the mass-weighted aerodynamic diameter of particles. The combined distribution of emitted particles had the mass median aerodynamic diameter (MMAD) of 0.35 μm, GSD 2.25. The average concentration of PM2.5 was 25.21 μg/m3 . The spline-based function of aerodynamic diameter allowed us to reconstruct the carcinogenic potential of seven types of fine and ultrafine particles (crystalline silica, fine TiO2 , ultrafine TiO2 , ambient PM2.5 and PM10, diesel particulates, and carbon nanotubes) with a correlation of 0.999, P < 0.00001. The central tendency estimation of lung cancer risk for 3D printer emissions was found at the level of 14.74 cases per 10,000 workers in a typical exposure scenario (average cumulative exposure of 0.3 mg/m3 - years), with the lowest risks for PLA filaments, and the highest for PETG type.

Development and Characterization of a Time-Sequenced Cascade Impactor: Application to Transient PM2.5 Pollution Events in Urbanized and Industrialized Environments

To set up a sampling and analysis strategy for particulate matter (PM) based on the time periods used in international standards is often inadequate for assessing the impact of day/night cycles or episodic emissions on urban air quality. To obtain a detailed physico–chemical characterization of urban PM when concentrations exceed the regulatory thresholds, a new rotary cascade impactor named the Time-Resolved Atmospheric Particle Sampler (TRAPS) was designed and tested for coarse and fine particle sampling. The TRAPS implementation, coupled with Optical Particle Counter measurements, provides time-resolved samples that can be analyzed by a wide range of single-particle analysis techniques. The TRAPS theoretical design was verified experimentally. Experimental cut-off diameters of 1.32 and 0.13 µm, respectively, for coarse and fine stages, were found in good agreement with theoretical values. Additionally, good trace separation, preventing inter-sample contamination, was evidenced by Scanning Electron Microscopy (SEM). The homogeneous distribution of particles of different types over a trace was also verified. As a case study, automated SEM-EDX analysis of 2500 particles, collected during two pollution peaks of a transient PM2.5 pollution event, revealed that individual particles’ chemical composition was influenced by local sources during the first pollution peak, and mainly transported during the second peak.