The USA is the third-leading cotton-producing country worldwide and cotton farming is common in the state of Georgia. Cotton harvest can be a significant contributor to airborne microbial exposures to farmers and nearby rural communities. The use of respirators or masks is one of the viable options for reducing organic dust and bioaerosol exposures among farmers. Unfortunately, the OSHA Respiratory Protection Standard (29 CFR Part 1910.134) does not apply to agricultural workplaces and the filtration efficiency of N95 respirators was never field-tested against airborne microorganisms and antibiotic resistance genes (ARGs) during cotton harvesting. This study addressed these two information gaps. Airborne culturable microorganisms were sampled using an SAS Super 100 Air Sampler in three cotton farms during cotton harvesting, and colonies were counted and converted to airborne concentrations. Genomic DNA was extracted from air samples using a PowerSoil® DNA Isolation Kit. A series of comparative critical threshold (2−ΔΔCT) real-time PCR was used to quantify targeted bacterial (16S rRNA) genes and major ARGs. Two N95 facepiece respirator models (cup-shaped and pleated) were evaluated for their protection against culturable bacteria and fungi, total microbial load in terms of surface ATP levels, and ARGs using a field experimental setup. Overall, culturable microbial exposure levels ranged between 103 and 104 CFU/m3 during cotton harvesting, which was lower when compared with bioaerosol loads reported earlier during other types of grain harvesting. The findings suggested that cotton harvesting works can release antibiotic resistance genes in farm air and the highest abundance was observed for phenicol. Field experimental data suggested that tested N95 respirators did not provide desirable >95% protections against culturable microorganisms, the total microbial load, and ARGs during cotton harvesting.
Manufacturing sites, such as welding, casting, and asphalt production (fumes), generate vast numbers of ultrafine particles of <0.1 µm in size and submicron particles close to the ultrafine range (0.1–0.5 µm). Although cumulative masses of these particles are negligible in comparison to the larger particles, the health effects are more severe due to the higher penetration in the human lower respiratory tract, other body parts crossing the respiratory epithelial layers, and the larger surface area. This research investigates the effectiveness of two common commercially available N95 filtering facepieces and N95 pleated particulate respirator models against ultrafine and submicron particles. Two specific types of respirators, the N95 filtering facepiece and the N95 pleated particulate models, in both sealed and unsealed conditions to the manikin face, were tested at various commercial and academic manufacturing sites, a welding and foundry site, and an asphalt production plant. Two TSI Nanoscan SMPS nanoparticle counters were used simultaneously to collect data for particles of 10–420 nm in size from inside and outside of the respirators. While one of them represented the workplace exposure levels, the other one accounted for the exposure upon filtration through the respiratory surfaces. The results showed the particles generated by these manufacturing operations were mostly within the range of from 40 to 200 nm. Results also indicated that while the percentage of filtration levels varied based on the particle size, it remained mostly within the desired protection level of 95% for both of the N95 respirator models in sealed conditions and even for the N95 pleated particulate model in the unsealed condition. However, in the case of the N95 filtering facepiece model, unsealed respirators showed that the percentage of penetration was very high, decreasing the protection levels to 60% in some cases. Although the number of workplace airborne particle levels varied considerably, the filtration percentages were relatively consistent.
About Me
Caleb Adeoye DVM, MPH. I am interested in air quality modeling.
Caleb Adeoye DVM, MPH. I am interested in air quality modeling.