Aerosol particles (0.3–10 μm) inside an educational workshop : Emission rate and inhaled deposited dose

In this study, we measured the concentrations of accumulation and coarse particles inside an educational workshop (March 31–April 6, 2015), calculated particle emission and losses rates, and estimated inhaled deposited dose. We used an Optical Particle Sizer (TSI OPS 3330) that measures the particle number size distribution (diameter 0.3–10 μm) and we converted that into particle mass size distribution (assuming spherical particles and unit density). We focused on two particle size fractions: 0.3–1 μm (referred as PN0.3−1 and PM0.3−1) and 1–10 μm (referred as PN1−10 and PM1−10). The occupants' activities included coffee brewing, lecturing, tobacco smoking, welding, scrubbing, and sorting/drilling iron. The highest concentrations were observed during welding with PN0.3−1 (PM0.3−1) was ∼1866 cm−3 (55 μg/m3) and PN1−10 (PM1−10) was ∼7 cm−3 (103 μg/m3). The lowest concentrations were observed during coffee brewing and metal turning with PN0.3−1 (PM0.3−1) was ∼22 cm−3 (0.7 μg/m3) and PN1−10 (PM1−10) was ∼0.5 cm−3 (4 μg/m3). The emissions rate of coarse particles was 85–1010 particles/hour × cm3 whereas that for submicron particle in the diameter range 0.3–1 μm was 5.7 × 104–9.3 × 104 particles/hour × cm3 depending on the activity and the ventilation rate. The coarse particles losses rate was 0.35–2.1 h−1 and the ventilation rate was 0.24–2.1 h−1. The alveolar received the majority and particles below 1 μm with a fraction of about 53% of the total inhaled deposited dose whereas the head/throat region received about 18%. This study is important for better understanding the health effects at educational workshops.Peer reviewe

Technical control of nanoparticle emissions from desktop 3D printing

Material extrusion (ME) desktop 3D printing is known to strongly emit nanoparticles (NP), and the need for risk management has been recognized widely. Four different engineering control measures were studied in real-life office conditions by means of online NP measurements and indoor aerosol modeling. The studied engineering control measures were general ventilation, local exhaust ventilation (LEV), retrofitted enclosure, and retrofitted enclosure with LEV. Efficiency between different control measures was compared based on particle number and surface area (SA) concentrations from which SA concentration was found to be more reliable. The study found out that for regular or long-time use of ME desktop 3D printers, the general ventilation is not sufficient control measure for NP emissions. Also, the LEV with canopy hood attached above the 3D printer did not control the emission remarkably and successful position of the hood in relation to the nozzle was found challenging. Retrofitted enclosure attached to the LEV reduced the NP emissions 96% based on SA concentration. Retrofitted enclosure is nearly as efficient as enclosure attached to the LEV (reduction of 89% based on SA concentration) but may be considered more practical solution than enclosure with LEV.Peer reviewe

Fingerprints of the urban particle number size distribution in Helsinki, Finland : Local versus regional characteristics

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Notably improved inversion of differential mobility particle sizer data obtained under conditions of fluctuating particle number concentrations

The differential mobility particle sizer (DMPS) is designed for measurements of particle number size distributions. It performs a number of measurements while scanning over different particle sizes. A standard assumption in the data-processing (inversion) algorithm is that the size distribution remains the same throughout each scan. For a DMPS deployed in an urban area this assumption is likely to be violated most of the time, and the resulting size distribution data are unreliable. To improve the reliability, we developed a new algorithm using a statistical model in which the problematic assumption was replaced with more realistic smoothness assumptions, which were expressed through Gaussian process prior probabilities. We tested the model with data from a twin DMPS located at an urban background site in Helsinki and found that it provides size distribution data which are much more realistic. Furthermore, particle number concentrations extracted from the DMPS data were compared with data from a condensation particle counter. At 10 min resolution, the correlation for a period of 10 days was 0.984 with the new algorithm and 0.967 with the old one. Moreover, the time resolution was improved, and at 30 s resolution we obtained positive correlations for 89 % of the scans. Thus, the quality of the inverted data was clearly improved.Peer reviewe

Crawling-induced floor dust resuspension affects the microbiota of the infant breathing zone

Background: Floor dust is commonly used for microbial determinations in epidemiological studies to estimate early-life indoor microbial exposures. Resuspension of floor dust and its impact on infant microbial exposure is, however, little explored. The aim of our study was to investigate how floor dust resuspension induced by an infant's crawling motion and an adult walking affects infant inhalation exposure to microbes. Results: We conducted controlled chamber experiments with a simplified mechanical crawling infant robot and an adult volunteer walking over carpeted flooring. We applied bacterial 16S rRNA gene sequencing and quantitative PCR to monitor the infant breathing zone microbial content and compared that to the adult breathing zone and the carpet dust as the source. During crawling, fungal and bacterial levels were, on average, 8- to 21-fold higher in the infant breathing zone compared to measurements from the adult breathing zone. During walking experiments, the increase in microbial levels in the infant breathing zone was far less pronounced. The correlation in rank orders of microbial levels in the carpet dust and the corresponding infant breathing zone sample varied between different microbial groups but was mostly moderate. The relative abundance of bacterial taxa was characteristically distinct in carpet dust and infant and adult breathing zones during the infant crawling experiments. Bacterial diversity in carpet dust and the infant breathing zone did not correlate significantly. Conclusions: The microbiota in the infant breathing zone differ in absolute quantitative and compositional terms from that of the adult breathing zone and of floor dust. Crawling induces resuspension of floor dust from carpeted flooring, creating a concentrated and localized cloud of microbial content around the infant. Thus, the microbial exposure of infants following dust resuspension is difficult to predict based on common house dust or bulk air measurements. Improved approaches for the assessment of infant microbial exposure, such as sampling at the infant breathing zone level, are needed.Peer reviewe

PAHs in Household Floor Dust Collected in Amman, Jordan

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